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Protein Engineering Market To Reach USD 4.77 Billion By 2027 | Reports And Data – PR Newswire UK

Posted on July 28, 2020 by Prof Baldwin

- The increasing research in protein engineering and rising government funding for new drug discovery are expected to be some major drivers for the market

- Market Size USD 1.86 Billion in 2019, Market Growth CAGR of 12.3%, Market Trends The growing research institutions across developing economies is expected to fuel the market in the forecast period

NEW YORK, July 28, 2020 /PRNewswire/ -- According to the current analysis of Reports and Data, theProtein Engineering marketwas valued at USD 1.86 billion in 2019 and is expected to reach USD 4.77 billion by the year 2027, at a CAGR of 12.3%. Protein engineering is the process of conception and production of unnatural polypeptides, which is achieved through the modification of different amino acid sequences that are found in nature. With the wide application of protein engineering, various synthetic protein structures and functions can now be designed completely using a computer and produced in the laboratory using various methods.

With the advent of technology, the rising demand is expected to provide traction to the market. For instance, computational protein design holds a potential promise to revolutionize protein engineering. Protein engineering is significantly in demand as it can develop useful or valuable proteins. It is known to be an emerging research field that helps researchers in understanding protein folding and recognition used for protein design principles. Protein engineering market is spurred by various reasons such as availability of immense information regarding 3D protein structure, advancement in structural bioinformatics, novel protein design algorithms, and other factors that have made it possible to use computational approaches for research and development in protein engineering. Strategic utilization of approaches that have been discovered with research has enabled better stability and increased catalytic activity of the protein. Moreover, it has increased its applicability in various fields that will further expand the market. Protein engineering has also evolved to become a potent tool contributing considerably to the developments in both synthetic biology and metabolic engineering. The rising funding for synthetic biology by governments and other healthcare institutions may drive the industry extensively in the future. Furthermore, substantial ongoing research in the drug discovery process is expected to fuel the market during the forecast period. Growing technological advancements and innovative instruments useful for protein engineering may drive the market extensively in the future. The emergence of new diseases due to microorganisms may also trigger market growth.

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However, factors such as high cost of instrumentation and lack of skill professional may hamper the protein engineering industry in the forecast period.

COVID-19 Impact:

WHO is focused on the latest scientific findings and knowledge on COVID-19. Various researchers and scientists are discovering new ways to tackle COVID-19 infection. Furthermore, the market of protein engineering is also going to get significantly affected due to the multiple kinds of research which are being carried out in this field. With the advent of technology, improving protein stability is an essential goal for clinical and industrial applications, however no commonly accepted and widely used strategy for efficient engineering is known. Furthermore, during the COVID-19 outbreak, protein engineering market is significantly impacted because many of the procedures involve lab automation. Market players are focusing on a research-based approach that will provide traction to the market. For instance, Vir Biotech identified two antibodies that could be effective in preventing and treating COVID-19. However, the high requirement of funds is expected to hamper the market during this period.

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Further key findings from the report suggest

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For the purpose of this report, Reports and Data has segmented the Protein Engineering market on the basis of product, type, technology, end use and region:

By Product Outlook (Revenue in Million USD; 2017-2027)

By Type Outlook (Revenue in Million USD; 2017-2027)

By Technology Outlook (Revenue in Million USD; 20172027)

By End Use Outlook (Revenue in Million USD;20172027)

Regional Outlook (Revenue, USD Billion; 2017-2027)

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Reports and Data is a market research and consulting company that provides syndicated research reports, customized research reports, and consulting services. Our solutions purely focus on your purpose to locate, target and analyze consumer behavior shifts across demographics, across industries and help client's make a smarter business decision. We offer market intelligence studies ensuring relevant and fact-based research across a multiple industries including Healthcare, Technology, Chemicals, Power and Energy. We consistently update our research offerings to ensure our clients are aware about the latest trends existent in the market. Reports and Data has a strong base of experienced analysts from varied areas of expertise.

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Protein Engineering Market To Reach USD 4.77 Billion By 2027 | Reports And Data - PR Newswire UK

Protein Engineering Market To Reach USD 4.77 Billion By 2027 | Reports And Data – PRNewswire

Posted on July 29, 2020 by Prof Baldwin

Request free sample of this research report at: https://www.reportsanddata.com/sample-enquiry-form/3369

However, factors such as high cost of instrumentation and lack of skill professional may hamper the protein engineering industry in the forecast period.

COVID-19 Impact:

To identify the key trends in the industry, click on the link below:https://www.reportsanddata.com/report-detail/protein-engineering-market

Further key findings from the report suggest

Order Now: https://www.reportsanddata.com/checkout-form/3369

For the purpose of this report, Reports and Data has segmented the Protein Engineering market on the basis of product, type, technology, end use and region:

By Product Outlook (Revenue in Million USD; 2017-2027)

By Type Outlook (Revenue in Million USD; 2017-2027)

By Technology Outlook (Revenue in Million USD; 20172027)

By End Use Outlook (Revenue in Million USD;20172027)

Regional Outlook (Revenue, USD Billion; 2017-2027)

Browse more similar reports on Biotechnology category by Reports And Data

About Reports and Data

John WHead of Business DevelopmentReports And Data | Web:www.reportsanddata.comDirect Line: +1-212-710-1370E-mail: [emailprotected]LinkedIn | Twitter | Blogs

SOURCE Reports And Data

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Protein Engineering Market To Reach USD 4.77 Billion By 2027 | Reports And Data - PRNewswire

Explained: How corona of the virus changes into a hairpin shape and why – The Indian Express

Posted on July 24, 2020 by Prof Baldwin

Written by Kabir Firaque | New Delhi | Updated: July 24, 2020 10:45:13 am Structure of SARS-CoV-2, including the spike protein. (Source: Wikipedia)

The spike protein of SARS-CoV-2 the corona in the coronavirus that causes Covid-19 disease has just revealed new secrets. Researchers have found that the spike protein changes its form after it attaches itself to a human cell, folding in on itself and assuming a rigid hairpin shape. The researchers have published their findings in the journal Science, and believe the knowledge can help in vaccine development.

It is a protein that protrudes from the surface of a coronavirus, like the spikes of a crown or corona hence the name coronavirus. In the SARS-CoV-2 coronavirus, it is the spike protein that initiates the process of infection in a human cell. It attaches itself to a human enzyme, called the ACE2 receptor, before going on to enter the cell and make multiple copies of itself.

Using the technique of cryogenic electron microscopy (cryo-EM), Dr Bing Chen and colleagues at Boston Childrens Hospital have freeze-framed the spike protein in both its shapes before and after fusion with the cell.

The images show a dramatic change to the hairpin shape after the spike protein binds with the ACE2 receptor. In fact, the researchers found that the after shape can also show itself before fusion without the virus binding to a cell at all. The spike can go into its alternative form prematurely.

Dr Chen suggests that assuming the alternative shape may help keep SARS-CoV-2 from breaking down. Studies have shown that the virus remains viable on various surfaces for various periods of time. Chen suggests that the rigid shape may explain this.

More significantly, the researchers speculate that the postfusion form may also protect SARS-CoV-2 from our immune system.

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The postfusion shape could induce antibodies that do not neutralise the virus. In effect, the spikes in this form may act as decoys that distract the immune system.

Antibodies specifically targeting the postfusion state would not be able to block membrane fusion (viral entry) since it would be too late in the process. This is well established in the field of other viruses, such as HIV, Chen told The Indian Express, by email.

In principle, if both conformations shared neutralising epitopes (the part of the virus targeted by antibodies), then the postfusion form too could induce neutralising antibodies, Chen said. But because the two structures are often very different, in particular, in case of SARS-CoV-2 and HIV, I think it is not very likely that the postfusion form would be useful as an immunogen, he explained.

Yes, both the before and after forms have sugar molecules, called glycans, at evenly spaced locations on their surface. Glycans are another feature that helps the virus avoid immune detection.

The researchers believe the findings have implications for vaccine development. Many vaccines that are currently in development use the spike protein to stimulate the immune system. But these may have varying mixes of the prefusion and postfusion forms, Chen said. And that may limit their protective efficacy.

Chen stressed the need for stabilising the spike protein in its prefusion structure in order to block the conformational changes that lead to the postfusion state. If the protein is not stable, antibodies may be induced but they will be less effective in terms of blocking the virus, he said.

Using our prefusion structure as a guide, we should be able to do better (introducing stabilizing mutations) to mimic the prefusion state, which could be more effective in eliciting neutralizing antibody responses, Chen told The Indian Express. We are in the process of doing this in case the first round of vaccines are not as effective as we all hope.

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Explained: How corona of the virus changes into a hairpin shape and why - The Indian Express

DeepMinds Protein Folding AI Is Going After Coronavirus

Posted on July 24, 2020 by Prof Baldwin

In late December last year, Dr. Li Wenliang began warning officials about a novel coronavirus in Wuhan, China, but was silenced by the police before tragically succumbing to the disease two months later. Meanwhile, almost simultaneously, a computer server halfway across the world started issuing worrying alerts of a potential new outbreak. The server runs software by BlueDot, a company based in San Francisco that uses AI to monitor infectious disease outbreaks for signs of early trouble.

Not enough people listened to either human expertise or AI. Then cases skyrocketed in Wuhan and spread across the world, and people had to take note.

Hindsight is 20/20, but it is remarkable that BlueDot and other machine learning-based services are beginning to catch early signs of infectious disease outbreaksalmost within the same time frame as health experts, if just for COVID-19. We often hear about AI as the next second coming of healthcare, where it can catch cases early, accelerate drug development, and personalize treatment. Yet COVID-19 is the first global pandemic to ever hold healthcare AIs feet to the flame in a global, serious, and urgent real-world test case. In a head-to-head race, can AI actually accelerate new anti-virals or vaccines for COVID-19, something the world has never previously seen? Or will traditional biotech measures excel, in turn unveiling that AIs hype massively outstrips reality?

MIT Technology Review recently reported an excellent piece that comprehensively looks at how AIat its current ability levelcan help us predict, diagnose, and treat novel viral threats. Im on board with the general idea: AIs potential is enormous.

Yet for now, dont look to AI to help tackle COVID-19; its simply not ready.

That said, it is enormously helpful to see how major machine learning companies are utilizing or repositioning their technologies for tackling the crisis. People often critique AI tested in toy cases, or standardized, limited datasets that may have limited significance in the real world. With companies working on COVID-19, thats no longer the case.

Ready, player, go? Heres how one major AI player in healthtech, DeepMind, is trying to knee-cap COVID-19.

The promise of AI for accelerating medical drug discovery is almost a universally supported idea. One caveat: so far, though new drugs have been discovered using AI, no AI-based drug candidate has made it through the approval process (yet), or even demonstrated that the tech makes the whole process faster to market (yet).

In very broad strokes, AI could be enormously helpful for initial drug discovery in two main ways: one, screening through millions of chemical compounds for potential drugs in simulation tests, far faster than any human expert; two, identifying targets that new drugs can latch onto, either to reduce their impact (making people less sick), or to slow their spread among people.

For COVID-19, DeepMind is focusing on the second route. Known mostly for its algorithms that beat human players at Go, DOTA, and other games, DeepMind has nevertheless been working directly on solutions for drug discovery. Their secret sauce? AlphaFold, a deep learning system that tries to predict protein structures accurately when no similar proteins exist.

Stay with me. How a protein looks in 3D is essential for developing new drugs, especially for new viruses. COVID-19, for example, has really spikey proteins that jut out from its surface. Normally, human cells dont carethey wont let the virus inside. But COVID-19s spikey proteins also harbor a Trojan Horse that activates it in certain cells with a complementary component. Lung cells have an abundance of these factors, which is why theyre susceptible to invasion.

Bottom line: if a drug is going to fit into a protein like a key into a lock to trigger a whole cascade of nasty reactions, then the first step is to figure out the structure of the lock. Thats what DeepMinds AlphaFold is doing.

Thanks to a surge of global collaboration, China released the genomic blueprint of the COVID-19 virus in open-access databases, whereas others have posted online the structure of some of its proteinseither determined by experiments or through computational modeling. DeepMind is taking these data to the next level by focusing on a few understudied but potentially important proteins that could become drug or vaccine targets using machine learning.

Protein folding has been a decades-long, fundamental problem in biochemistry and drug discovery. Almost all of our existing drugs grab onto certain proteins to work, so identifying protein structure is akin to surveying the enemy landscape and figuring out best attack point simultaneously. The problem is the genetic code doesnt translate to how proteins look. When it comes to a new virus, without predicting protein structures were basically fighting viruses and diseases as if they were the Invisible Man.

Traditional methods use high-tech microscopes, freezing proteins into crystal-looking entities, and other strange and expensive ways to understand their structure. Under the scope, a protein is basically a chain of chemical letters that wrap around itself into intricate structureskinda like how your headphones always tangle into inconceivable structures while youre sleeping. For DeepMind and other protein-folding efforts, the key is to predictand then find methods to decipher drug targets fromthose structures.

AlphaFold stands out as a union of decades of deep learning progress, but guided by expertise from protein structure databases in the public domain. In a nutshell, AlphaFold uses genome sequences (available for COVID-19 and relatively easy to get) to predict the properties of resulting proteins that actually do the work, by looking at the distance of each letter or component that makes up a certain protein. It doesnt predict specific sequences with special powerssuch as those that bind to a cellbut offers a quick police sketch of the virus perp in sight.

Theres no doubt that AlphaFold is new to the protein-folding game. Even DeepMind itself stresses that these structure predictions have not been experimentally verified, but could galvanize efforts at making anti-virals and/or vaccines. For now, its difficult to judge how much AlphaFold will contribute to the pandemic, if at all. But by automating a critical aspect of drug discovery, its also en route to becoming a much larger player in the next epidemic.

Of note: all of this would not be possible without public, open-source databases of protein structures (like UniProt and the Protein Data Bank) thats been building for decades. DeepMinds release, posted with open access, has been lauded by fellow scientists as a way of giving back to the community.

Chinas long-time Google surrogate and AI behemoth, Baidu, is using an algorithm to predict the structure of another important biomolecule, mRNA. mRNA shuttles information from the genome to protein factories, so shoot the mRNA messenger, then the viral proteins are never born. Similarly, AI could one day potentially predict epidemics and how a virus changes over timebut it will only help if theres enough trust to listen to the models.

Various AI companies are also making a play towards efficient diagnosticsidentifying COVID-19 signs in medical scansor other measures to support at-risk and overworked medical frontline heroes. The problem is that with any new outbreak, we dont have enough data to train an AI, which means that they will struggle to find subtle differences in imperfect medical scans, at least for now.

So, is AI our savior? Not in this pandemic. Similar to the 2003 SARS outbreak, the best response is something that has existed for centuries: social distancing. As I mentioned previously, before COVID-19 exploded into a pandemic, science was ready to provide answers for COVID-19 as long as governments were also ready to respond. And because AI is based on scientific data and helping otherwise difficult efforts, machine learning is rapidly learning to do the same.

But perhaps ironically, COVID-19 is exposing both the best and weakest parts of AI in our current society for healthcare: great models that in theory should work, solid predictions that can be tested, but not without any recommendations without a heavy dose of skepticism. COVID-19 presents a brutal test case for AI in healthcare.

But for now, the toughest case is that of government management and what we do in response.

Note: To learn more about the Covid-19 pandemic, tune into Singularity Universitys free virtual summit: Covid-19: The State & Future of Pandemics.

Image Credit: Vektor Kunst from Pixabay

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DeepMinds Protein Folding AI Is Going After Coronavirus

Demand for Syndromes of Progressive Ataxia and Weakness Disorders Market to Witness Rapid Surge – Lake Shore Gazette

Posted on July 16, 2020 by Prof Baldwin

Ataxia is a neurological condition, characterized by lack of voluntary coordination of muscle movement. Ataxia causes head trauma, stroke, Transient Ischemic Attack (TIA), tumor and toxic reaction. Progressive ataxia and weakness disorders are related to damage, degeneration or loss of neurons of the brain which leads to muscle coordination disability.

The global market for treatments of syndromes of progressive ataxia and weakness disorders is categorized based on various drugs used for treatment of progressive ataxia syndromes, drugs for progressive weakness syndromes and by technology. The progressive ataxia syndrome segment is further sub-segmented into major diseases, such as Friedreichs ataxia, Gertsman-Straussler-Scheinker disease and Machado-Joseph disease. The progressive weakness syndrome segment includes amyotrophic lateral sclerosis, hereditary spastic paraplegia, hereditary neuropathies, progressive bulbar palsy and multiple sclerosis. The technology segment is further sub-segmented into small molecules based therapies and monoclonal antibody.

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In terms of geography, the U.S. and Canada holds major market share of treatments for syndromes of progressive ataxia and weakness disorders market in North America. In Europe, Germany, France and the U.K are major markets for treatments of syndromes of progressive ataxia and weakness disorders.

Globally, treatments for syndromes of progressive ataxia and weakness disorders market are growing due to novel drug development and rapid technological advancement for treatment of progressive ataxia and weakness disorders. Some of the major technological advancement involved in growth of the market are protein mis-folding, gene mutation and stem cell therapy. In addition, increased collaborations between industry players for development of new therapies is a key trend for the market.

However, patent expiries of major drugs hampers growth of the treatments for syndromes of progressive ataxia and weakness disorders market. Moreover, stringent regulations and standard requires for approval process of new drugs impede growth of the treatments for syndromes of progressive ataxia and weakness disorders market. Several government agencies, such as FDA and European Medicines Agency, are responsible for the approval of every drug. In addition, the approval process takes a very long time to approve a specific drug.

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Some of the major companies operating in the treatment for syndromes of progressive ataxia and weakness disorders market are Abbott Laboratories, Acorda Therapeutics Inc., American Regent Inc., Baxter International Inc., Biogen Idec., Bristol-Myers Squibb, Cadila Healthcare Ltd., Eli Lilly and Company, Glaxosmilthkline Plc., Sanofi, Roche Holding Ltd., Pfizer Inc. and Novartis AG.

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Demand for Syndromes of Progressive Ataxia and Weakness Disorders Market to Witness Rapid Surge - Lake Shore Gazette

Microsoft Executive Vice President Jason Zander: Digital Transformation Accelerating Across the Energy Spectrum; Being Carbon Negative by 2030; The…

Posted on July 23, 2020 by Prof Baldwin

WASHINGTON--(BUSINESS WIRE)--Microsoft Executive Vice President Jason Zander says the company has never been more busy partnering with the energy industry on cloud technologies and energy transition; the combination of COVID-19 and the oil market shock has condensed years of digital transformation into a two-month period; the companys return to its innovative roots and its goal to have removed all of the companys historic carbon emissions by 2050 in the latest edition of CERAWeek Conversations.

In a conversation with IHS Markit (NYSE: INFO) Vice Chairman Daniel Yergin, Zanderwho leads the companys cloud services business, Microsoft Azurediscusses Microsofts rapid and massive deployment of cloud-based apps that have powered work and commerce in the COVID-19 economy; how cloud technologies are optimizing business and vaccine research; the next frontiers of quantum computing and its potential to take problems that would take, literally, a thousand years, you might be able to solve in 10 seconds, and more.

The complete video is available at: http://www.ceraweek.com/conversations

Selected excerpts:Interview Recorded Thursday, July 16, 2020

(Edited slightly for brevity only)

Watch the complete video at: http://www.ceraweek.com/conversations

Weve already prepositioned in over 60 regions around the world hundreds of data center, millions and millions of server nodestheyre already there. If you can imagine COVID, if you had to go back and do a procurement exercise and figure out a place to put the equipment, and the supply chains were actually shut down for a while because of COVID. Thats why I say, even three to five years ago we as industries would have been pretty challenged to respond as quickly as we had.

Thats on the more tactical end of the spectrum. On the other end weve also done a lot of things around data sets and advanced data work. How do we find a cure? Weve done things like [protein] folding at home and making sure that those things could be hosted on the cloud. These are thingsthat will be used in the search of a vaccine for the virus. Those are wildly different spectrums from the tactical 'we need to manage and do logistics' to 'we need a search for things that are going to get us all back to basically normal.'

Theres also a whole bunch of stimulus packages and payment systems that are getting created and deployed. Weve had financial services companies that run on top of the cloud. They may have been doing a couple of hundred big transactions a day; weve had them do tens to hundreds of thousands a day when some of this kicked in.

The point is with the cloud I can just go to the cloud, provision it, use it, and eventually when things cool back down, I can just shut it off. I dont have to worry about having bought servers, find a place for them to live, hiring people to take care of them.

There was disruption in supply chain also. Many of us saw this at least in the Statesif you think even the food supply chain, every once in a while, youd see some hiccups. Theres a whole bunch of additional work that weve done around how do we do even better planning around that, making sure we can hit the right levels of scale in the future? God forbid we should have another one of these, but I think we can and should be responsible to make sure that weve got it figured out.

The policy and investment sideit has never been more important for us to collaborate with healthcare, universities, and with others. Weve kicked off a whole bunch of new partnerships and work that will benefit us in the future. This was a good wake up call for all of us in figuring out how to marshal and be able to respond even better in the future.

Weve had a lot of cases where people have been moving out of their own data centers and into ours. Let us basically take care of that part of the system. We can run it cheaply and efficiently. Im seeing a huge amount of data center accelerationfolks that really want to move even faster on getting their workloads removed. Thats true for oil and gas but its also true for the financial sector and retail.

Specifically, for oil and gas, one of the things that were trying to do in particular is bring this kind of cloud efficiency, this kind of AI, and especially help out with places where you are doing exploration. What these have in common is the ability to take software especially from the [independent software vendors] that work in the spacereservoir simulation, explorationand marry that to these cloud resources where I can spin things up and spin things down. I can take advantage of that technology that Ive got, and I am more efficient. I am not spending capex; I can perhaps do even more jobs than I was doing before. That allows me to go do that scale. If youre going to have less resources to do something, you of course want to increase your hit rate; increase your efficiency. Those are some of the core things that were seeing.

A lot of folks, especially in oil and gas, have some of the most sophisticated high-performance computing solutions that are out there today. What we want to be able to do with the cloud is to be able to enable you to do even more of those solutions in a much more efficient way. Weve got cases where people have been able to go from running one reservoir simulation job a day on premises [to] where they can actually go off to the cloud and since we have all of this scale and all of this equipment, you can spin up and do 100 in one day. If that is going to be part of how you drive your efficiency, then being able to subscribe to that and go up and down its helping you do that job much more efficiently than you used to and giving you a lot more flexibility.

Were investing in a $1 billion fund over the next four years for carbon removal technology. We also are announcing a Microsoft sustainability calculator for cloud customers. Basically, you can help get transparency into your Scope 1,2, and 3 carbon emissions to get control. You can think of us as we want to hit this goal, we want to do it ourselves, we want to figure out how we build technology to help us do that and then we want to share that technology with others. And then all along the way we want to partner with energy companies so that we can all be partnering together on this energy transition.

From a corporate perspective weve made pledges around being carbon negative, but then also working with our energy partners. The way that we look at this is youre going to have continued your requirements and improvements in standards of living around the entire planet. One of the core, critical aspects to that is energy. The world needs more energy, not less. There are absolutely the existing systems that we have out there that we need to continue to improve, but they are also a core part of how things operate.

What we want to do is have a very responsible program where were doing things like figuring out how to go carbon negative and figuring out ways that we as a company can go carbon negative. At the same time, taking those same techniques and allowing others to do the same and then partnering with energy companies around energy transformation. We still want the investments in renewables. We want to figure out how to be more efficient at the last mile when we think about the grid. I generally find that when you get that comprehensive answer back to our employees, they understand what we are doing and are generally supportive.

Coming up is a digital feedback loop where you get enough data thats coming through the system that you can actually start to be making smart decisions. Our expectation is well have an entire connected environment. Now we start thinking about smart cities, smart factories, hospitals, campuses, etc. Imagine having all of that level of data thats coming through and the ability to do smart work shedding or shaping of electrical usage, things where I can actually control brownout conditions and other things based on energy usage. Theres also the opportunity to be doing smart sharing of systems where we can do very efficient usage systemsintelligent edge and edge deployments are a core part of that.

How do we keep all the actual equipment that people are using safe? If you think about 5G and additional connectivity, were getting all this cool new technology thats there. You have to figure out a way in which youre leveraging silicon, youre leveraging software and the best in securityand were investing in all three.

The idea of being able to harness particle physics to do computing and be able to figure out things in minutes that would literally take centuries to go pull off otherwise in classical computing is kind of mind-blowing. Were actually working with a lot of the energy companies on figuring out how could quantum inspired algorithms make them more efficient today. As we get to full scale quantum computing then they would run natively in hardware and would be able to do even more amazing things. That one has just the potential to really, really change the world.

The meta point is problems that would take, literally, a thousand years, you might be able to solve in 10 seconds. Weve proven how that kind of technology can work. The quantum-inspired algorithms therefore allow us to take those same kind of techniques, but we can run them on the cloud today using some of the classic cloud computers that are there. Instead of taking 1,000 years, maybe its something that we can get done in 10 days, but in the future 10 seconds.

About CERAWeek Conversations:

CERAWeek Conversations features original interviews and discussion with energy industry leaders, government officials and policymakers, leaders from the technology, financial and industrial communitiesand energy technology innovators.

The series is produced by the team responsible for the worlds preeminent energy conference, CERAWeek by IHS Markit.

New installments will be added weekly at http://www.ceraweek.com/conversations.

Recent segments also include:

A complete video library is available at http://www.ceraweek.com/conversations.

About IHS Markit (www.ihsmarkit.com)

IHS Markit (NYSE: INFO) is a world leader in critical information, analytics and solutions for the major industries and markets that drive economies worldwide. The company delivers next-generation information, analytics and solutions to customers in business, finance and government, improving their operational efficiency and providing deep insights that lead to well-informed, confident decisions. IHS Markit has more than 50,000 business and government customers, including 80 percent of the Fortune Global 500 and the worlds leading financial institutions. Headquartered in London, IHS Markit is committed to sustainable, profitable growth.

IHS Markit is a registered trademark of IHS Markit Ltd. and/or its affiliates. All other company and product names may be trademarks of their respective owners 2020 IHS Markit Ltd. All rights reserved.

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Microsoft Executive Vice President Jason Zander: Digital Transformation Accelerating Across the Energy Spectrum; Being Carbon Negative by 2030; The...

Learn the ‘right way’ to make scrambled eggs with this French technique – TODAY

Posted on July 14, 2020 by Prof Baldwin

Scrambled eggs are a breakfast staple and everyone seems to have their own particular method for cooking up the fluffiest eggs possible. But the quest for the perfect scrambled eggs may be over, thanks to this French-style recipe by private chef and YouTuber Bruno Albouze.

Unlike traditional scrambled eggs, which are fluffy and form more solid curds, the French style offers a silkier, creamier variation on the breakfast food, Albouze told TODAY.

If (the eggs are) cooked the right way, it changes the texture, the mouthfeel is just incredible, he said. If it's overcooked, you just don't get the same thing. You're pretty much eating chopped omelet.

According to Albouze, the French way of cooking scrambled eggs is the right way.

While Albouze may have mastered this classic technique, he didnt invent it. Chef Brendan Walsh, the dean of the School of Culinary Arts at The Culinary Institute of America, explained that while scrambled eggs have likely been around for thousands of years in places where chickens were first domesticated (like China and Egypt), the French style emerged in the early days of haute or "high cuisine." This term refers to the style of food preparation that blossomed in France during the 16th century, and is still served in many Michelin-starred eateries today.

Eggs are a staple in cooking school," Albouze said. "Cooking eggs is a big thing, because eggs are the trickiest thing to cook. It's composed mostly of water, because the egg white is watery, and the yolk is fat, but it's tricky because it can overcook very fast.

"Scrambled eggs are definitely the item not everyone knows how to cook it properly. And very very few restaurants know how to do it without them being overcooked.

Albouze, 50, has been cooking since he began an apprenticeship at the age of 14 in France, where he learned the art of cooking, baking and pastry making. Growing up, Albouze said he used to walk to nearby farms for fresh, pasture-raised eggs to make omelets and scrambled eggs.

During his career, the chef has worked at the Htel Plaza Athne in Paris under renowned chef Alain Ducasse and as an instructor at the Culinary Institute Lenotre in Houston.

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But the chef, who now lives in San Diego, really found his stride in 2009 when he started his own YouTube channel. Albouze now has over 760,000 subscribers and 70 million total video views. One of his most popular videos, a recipe for ratatouille, has garnered over 10 million views.

In one of his latest cooking demos, Albouze shared his favorite method for cooking scrambled eggs in the French style. In 2015, he showcased how to cook French-style eggs in water bath. Both methods require constant stirring and movement over low heat to achieve the desired creamy texture.

One method Albouze demonstrated uses a nonstick pan, while the other uses a water bath, which is known as a "bain marie in French and culinary terms.

Walsh added that the French way is a technique where "slow and low, patience and respect" result in the creamiest eggs possible. It is a preparation method that is taught at the CIA, although he said he rarely sees the technique used in America outside of fancier hotels and restaurants.

"It is important in egg cookery to create soft and supple textures," Walsh said via email. "Too high of heat will dry out the protein and take away the supple creaminess that the protein can provide.

Cooking is about ingredients, Albouze added. 80% (is) about the ingredients, 10% skills and 10% time. So, it tells us you don't have to be skilled, just if you understand that ingredients are the most important part of cooking.

For this reason, he recommends using pasture-raised eggs, which means that the egg-laying hens are allowed to spend plenty of time outside, and feed on grass, bugs or worms instead of a corn- or soy-based diet.

These days, if the egg aisle at your supermarket seems a little empty, it might not be a bad idea to take a road trip out to a local farm, pick up some fresh eggs and try out this fun technique at home.

Said Walsh, Crispy toast and creamy French-style eggs are just the sexiest start to the chefs morning."

This recipes serves two people and takes about 15 minutes from start to finish.

Said Albouze, There's no question that the most important factor when cooking eggs is the cooking technique itself. In the case of scrambled eggs, that means using gentle heat and taking the eggs off the flame a little early to account for carryover cooking.

1. Crack eggs into a bowl and set aside. Do not whisk the eggs. Set flame to medium and allow heat to gently warm the pan prior to adding any fat.

2. Add the olive oil and butter to the pan. Let melt slightly before adding the unbeaten eggs. With a whisk or a rubber spatula, poke the egg yolks and cook slowly on medium heat while constantly stirring, folding and shaking the pan.

3. Continue to cook and move the eggs as they start to scramble. They should yield a soft, delicate and creamy texture in about 5 minutes. As the eggs start to come together, turn off the heat and continue to stir the eggs.

4. To stop the cooking process, whisk in a dash of milk or cream. Season the eggs with salt and a few grinds of pepper before youre ready to serve. Salting the eggs too early may make your eggs watery.

5. If desired, serve the scrambled eggs with some fresh herbs, such as dill or chives. Eggs also pair remarkably well with caviar, salmon roe, truffle, cured salmon or bacon. Either way, these eggs should be served immediately.

Bon apptit!

Clare Boothe Luce Scholarship Prepares Women Scientists for the Future – St John’s University News

Posted on July 15, 2020 by Prof Baldwin

July 15, 2020

Named for the visionary woman who excelled in myriad fields, St. Johns Clare Boothe Luce (CBL) Undergraduate Scholarship encourages gifted women to pursue collegiate studies in the sciences and technologyareas in which women historically are underrepresented. The CBL scholarship is an outgrowth of the UniversitysWomen in Science (WIS) Scholarship Program. St. Johns College of Liberal Arts and Sciences Class of 2020 included three recipients of the prestigious scholarship, each with an inspiring story to tell.

When toxicology major Kathryn Bozell enrolled at St. Johns four years ago, she was not even aware of the CBL scholarship. This fall, the scholarship recipient returns to the University to pursue her masters degree in toxicology as a CBL Graduate Fellow.

During her first year, Kathryn, a native of Louisville, KY, was encouraged to apply for the CBL scholarship by several faculty, who saw great promise in the budding scientist.

Upon learning about the exciting opportunities available through WIS and the CBL scholarship program, I eagerly applied, she recalled. The scholarship program provided me with the opportunity to connect with incredible female mentors and peers. It also inspired me to continue my studies and pursue a masters degree.

The experience also served as a launchpad for her research on the effects of copper dimethyldithiocarbamate (CDDC) on the release of a protein that is known to propagate the inflammation of nervous tissue. Neuronalinflammation has been linked to neurodegenerative diseases, such as Alzheimers disease, Parkinsons disease, and Multiple Sclerosis.

Participating in WIS activities was an integral part of my academic and professional development at St. Johns, she recalled. In addition to the invaluable networking opportunities it offered, it provided me the chance to build personal relationships with other women in science, which greatly enriched my academic experience overall.

Kathryn is excited to return to campus to begin her graduate work and serve as a role model for younger students. As I continue my education and research, I am excited to inspire the next generation of women in science in the same manner, she said. I would highly encourage all young women interested in a career in the sciences to learn more about the Clare Boothe Luce Scholarship program.

For Teagan Sweet, the CBL scholarship was a connection to a welcoming community of female scientists at St. Johns and around the globe.

CBL was such a pivotal experience for me, the native of North Attleborough, MA, recalled. I loved being surrounded byand supported bythe strong women in STEM at St. Johns who became my role models. CBL validated my experience in science.

That experience saw the chemistry major complement her study of the field with minors in photography and international studies. She also explored computational research, focusing on understanding how orientation and the folding of proteins leadto large-scale changes in the cell.

Teagan traveled to Dublin, Irelands Trinity College to work on the development of new green materials, which could one day lead to advances in energy storage, solar cells, and drug delivery.

In addition to her rigorous course load, Teagan was Head Skull of the Skull and Circle Honor Society, St. Johns Colleges highest honor for students, and was awarded the prestigiousJeannette K. Watson Fellowshipa three-year, international internship program funded by the Thomas J. Watson Foundation. She was also an S-STEM scholar and contributed to research in collaboration with the National Science Foundation, which focused on the development of a biodegradable water filter to be used in disaster situations.

Both the WIS and CBL programs assisted Teagan in her graduate school application process, through mentorship, as well as words of wisdom. This fall, she will pursue a Ph.D. in inorganic chemistry at the University of Notre Dame.

Thanks to these programs, I feel especially connected not only to women in STEM at St. Johns, but across the country, as well, she said. I will always be proud to be a part of this elite, intelligent community.

Like many students, Natalie Williams entered her senior year unsure of her postgraduation plans. A chemistry major with a minor in graphic design, Natalie sought the advice of a faculty mentor, who suggested she pursue a career where she could combine her passion for chemistry with her love of the arts.

One of my professors told me about science-related research at art museums, she recalled. I had not given this field any serious thought, but now my goal is to be a scientific researcher at a museum.

In pursuit of that goal, Natalie will attend Yale University this fall, where she will work toward her Ph.D. in material chemistry. While her focus now is on the future, she looks back on her four years at St. Johns with fondness and gratitude.

The CBL scholarship helped me not only financially, but professionally, making the way for new and lasting professional connections, she said. This program introduced me to fellow women in science who will always serve as my inspiration.

Natalie was a member of St. Johns National Science Foundation-funded S-STEM Scholars Program, which introduced her to undergraduate student research, including a research group in the chemistry department that designed, synthesized, and analyzed materials using DNA nanotechnology. There, she was able to combine her chemistry and biotechnology skills with her graphic design knowledge and made nanometer-scale DNA origami objects, which fold themselves into particular shapes.

She was also a member of the American Chemical Societys Scholar Program, an extremely competitive program for underrepresented minority students who plan to pursue careers in chemistry. In addition, Natalie participated in the BIOMOD research competition, an international bio-molecular design competition for students sponsored by the Wyss Institute for Biologically Inspired Engineering at Harvard University.

Natalie is grateful for the support she received as a CBL scholar as St. Johns. Everyone here gave me great advice that helped guide me in the best direction to achieve my goals, she recalled. Conducting research on art is something that truly fascinates me, and I plan to fulfill this dream.

Global Research report on Molecular Modelling Market Size, Analysis and Growth Forecast by Applications, S … – Adify Media News

Posted on October 11, 2020 by Prof Baldwin

Molecular Modelling Market report provides a detailed evaluation of the market by highlighting information on different aspects which include drivers, restraints, opportunities, threats, and global markets including progress trends, competitive landscape analysis, and key regions expansion status.This report is comprehensive numerical analyses of the Molecular Modelling industry and provides data for making strategies to increase the market growth and success. The Report also estimates the market size, Price, Revenue, Gross Margin and Market Share, cost structure and growth rate for decision making.

Molecular Modelling Market provides key analysis on the market status of theMolecular Modelling manufacturers with best facts and figures, meaning, definition, SWOT analysis, expert opinions and the latest developments across the globe. The Report also calculate the market size,Molecular Modelling Sales, Price, Revenue, Gross Margin and Market Share, cost structure and growth rate.

Final Report will add the analysis of the impact of COVID-19 on this industry.

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The research covers the current Molecular Modellingmarket size of the market and its growth rates based on 6-year records with company outline of Key players/manufacturers:

Brief Description about Molecular Modelling market:

Molecular modelling encompasses all methods, theoretical and computational, used to model or mimic the behaviour of molecules. The methods are used in the fields of computational chemistry, drug design, computational biology and materials science to study molecular systems ranging from small chemical systems to large biological molecules and material assemblies.

Molecular modelling methods are now used routinely to investigate the structure, dynamics, surface properties, and thermodynamics of inorganic, biological, and polymeric systems. The types of biological activity that have been investigated using molecular modelling include protein folding, enzyme catalysis, protein stability, conformational changes associated with biomolecular function, and molecular recognition of proteins, DNA, and membrane complexes.

By the product type, the Molecular Modelling marketis primarily split into:

By the end users/application, Molecular Modelling marketreport coversthe following segments:

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The key regions covered in theMolecular Modelling market report are:

Key Reasons to Purchase:

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Table of Contents with Major Points :

Detailed TOC of Global Molecular ModellingMarket Research Report 2020-2026, by Manufacturers, Regions, Types and Applications

1 Molecular Modelling MarketOverview1.1ProductOverviewandScopeof Molecular Modelling1.2 Molecular Modelling SegmentbyType1.3 Molecular Modelling SegmentbyApplication1.4Global Molecular Modelling MarketSizeEstimatesandForecasts1.5 Molecular Modelling Industry1.6 Molecular Modelling MarketTrends

2Global Molecular Modelling MarketCompetitionbyManufacturers2.1Global Molecular Modelling SalesMarketSharebyManufacturers(2015-2020)2.2Global Molecular Modelling RevenueSharebyManufacturers(2015-2020)2.3Global Molecular Modelling AveragePricebyManufacturers(2015-2020)2.4Manufacturers Molecular Modelling ManufacturingSites,AreaServed,ProductType2.5 Molecular Modelling MarketCompetitiveSituationandTrends2.6ManufacturersMergers&Acquisitions,ExpansionPlans2.7PrimaryInterviewswithKey Molecular Modelling Players(OpinionLeaders)

3 Molecular Modelling RetrospectiveMarketScenariobyRegion3.1Global Molecular Modelling RetrospectiveMarketScenarioinSalesbyRegion:2015-20203.2Global Molecular Modelling RetrospectiveMarketScenarioinRevenuebyRegion:2015-20203.3NorthAmerica Molecular Modelling MarketFacts&FiguresbyCountry3.4Europe Molecular Modelling MarketFacts&FiguresbyCountry3.5AsiaPacific Molecular Modelling MarketFacts&FiguresbyRegion3.6LatinAmerica Molecular Modelling MarketFacts&FiguresbyCountry3.7MiddleEastandAfrica Molecular Modelling MarketFacts&FiguresbyCountry

4Global Molecular Modelling HistoricMarketAnalysisbyType4.1Global Molecular Modelling SalesMarketSharebyType(2015-2020)4.2Global Molecular Modelling RevenueMarketSharebyType(2015-2020)4.3Global Molecular Modelling PriceMarketSharebyType(2015-2020)4.4Global Molecular Modelling MarketSharebyPriceTier(2015-2020):Low-End,Mid-RangeandHigh-End

5Global Molecular Modelling HistoricMarketAnalysisbyApplication5.1Global Molecular Modelling SalesMarketSharebyApplication(2015-2020)5.2Global Molecular Modelling RevenueMarketSharebyApplication(2015-2020)5.3Global Molecular Modelling PricebyApplication(2015-2020)

6CompanyProfilesandKeyFiguresin Molecular Modelling Business7 Molecular Modelling ManufacturingCostAnalysis8MarketingChannel,DistributorsandCustomers9MarketDynamics9.1MarketTrends9.2OpportunitiesandDrivers9.3Challenges9.4PortersFiveForcesAnalysis

10GlobalMarketForecast10.1Global Molecular Modelling MarketEstimatesandProjectionsbyType10.2 Molecular Modelling MarketEstimatesandProjectionsbyApplication10.3 Molecular Modelling MarketEstimatesandProjectionsbyRegion10.4NorthAmerica Molecular Modelling EstimatesandProjections(2021-2026)10.5Europe Molecular Modelling EstimatesandProjections(2021-2026)10.6AsiaPacific Molecular Modelling EstimatesandProjections(2021-2026)10.7LatinAmerica Molecular Modelling EstimatesandProjections(2021-2026)10.8MiddleEastandAfrica Molecular Modelling EstimatesandProjections(2021-2026)

11ResearchFindingandConclusion12MethodologyandDataSource

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Europe Protein A Resins Market Research, Recent Trends and Growth Forecast 2025 – CueReport

Posted on August 21, 2020 by Prof Baldwin

A Research study on Europe Protein A Resins Market analyzes and offers ideas of exhaustive research on ancient and recent Europe Protein A Resins market size. Along with the estimated future possibilities of the market and emerging trends in the Europe Protein A Resins market.

Rapid expansion of biotechnology and pharmaceutical companies will spur protein A resins market growth. Also, rising funding for protein-based research will augment the market growth. However, availability of alternatives such as crystallization, ultrafiltration, capillary electrophoresis and high pressure folding for purification methods may restrain the industry growth in forthcoming years.

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Europe Protein A Resins MarketSize Estimated To Exceed USD 232.0 Million By 2026. Growing demand for chromatography for purification and discovery of biological entities will escalate the adoption of Protein A resins in Europe over the analysis timeframe. Owing to improved, cost-effective and widely accepted component for purification of biological samples, protein A resins are widely used in chromatography technique. Furthermore, increasing product approvals of monoclonal antibodies from regulatory bodies to cater the increasing demand for immunotherapy will further fuel the industry growth.

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Demand for protein A resins in biopharmaceutical companies will progress at 8.4% CAGR during the projection period. Growing demand for drug development coupled with increase research and development spending will augment the segment share. With rising adoption by biotechnology industries for protein A resins for antibody production, will offer profitable growth in the forecast timeframe.

Antibody purification application segment accounted for more than 77% revenue share in 2019. With rising incidence of chronic diseases such as rheumatoid arthritis, protein A resin kits are developed for purification of antibodies for structural and diagnostic studies. They are also used as molecular probes for research and development activities. Monoclonal antibodies exhibit remarkable results in the management of chronic conditions such as cancer and rheumatoid arthritis. Thus, wide applications and benefits of antibodies will render a lucrative potential for protein A resins market growth in the forthcoming years.

Agarose-based matrix segment is estimated to grow at 8.3% CAGR over the forecast timeframe. Suitable resolution, favorable pH conditions and high flow rate drives the segment growth over the forecast time period. The benefits of using agarose-based matrix include excellent biocompatibility, considerable mechanical resistance, and hydrophobic nature that significantly contribute to product preference, thus increasing segmental growth.

Europe protein A resins industry was led by Germany protein A resins market in 2019 and is estimated to show a positive trend throughout the projection period. UK protein A resins business is forecasted to proceed at more than 7.5% CAGR across the forecast timeframe. Increasing number of pharmaceutical industry and presence of major market players in the country will influence market growth in the future. Furthermore, expanding applications of immunotherapy will augment the UK protein A resins business growth in future.

Recombinant protein A resins market held more than USD 80 million revenue size in 2019. Recombinant protein A is generally formulated in E.coli and functioning is same as that of natural protein A resins. When other sources of production offer less non-specific binding, recombinant protein A resins are generally preferred. Thus, higher inclination towards recombinant protein A resins owing to its advantages will augment the segmental growth.

Major market players in Europe protein A resins market are Thermo Fisher Scientific, EMD Millipore, GE Healthcare, and Bio-Rad Laboratories among other industry participants. These market players are undertaking strategies such as technology advancements and inorganic growth strategies to strengthen their market presence and company expansion. For instance, in June 2018, Purolite introduced advanced protein A agarose resin. The new-generation resins, Praesto Jetted A50 shows improved performance aimed at widening their product and customer base.

A Pin-point overview of TOC of Europe Protein A Resins Market are:

Overview and Scope of Europe Protein A Resins Market

Europe Protein A Resins Market Insights

Industry analysis - Porter's Five Force

Company Profiles

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Europe Protein A Resins Market Research, Recent Trends and Growth Forecast 2025 - CueReport

Global Zinc Deficiency Treatment Market to Witness Heightened Growth During the Period 2017 2025 – My Amazon Echo

Posted on August 13, 2020 by Prof Baldwin

Zinc is a micronutrient and essential trace element required for metabolism reactions that catalyze number of enzyme reactions, protein folding, gene expression etc. Deficiency of zinc may cause range of infectious diseases and other complications affecting almost every aspect of health such as delayed or retarded growth in children, hair loss, lack of cognitive function, reduced sense of taste and smell, loss of appetite, immunosuppression, anemia, night blindness, etc. Zinc deficiency may also cause deficiency of vitamin A as zinc is required for vitamin A absorption. Zinc deficiency is the fifth leading factor causing disease across the globe, and according to World Health Organization (WHO) 31% of the global population is experiencing zinc deficiency. Underdeveloped countries are facing major problem of death due to childhood diarrhea and pneumonia caused due to zinc deficiency. As per International Zinc Nutrition Consultative Group (IZiNCG) zinc deficiency is expected to cause 176,000 diarrhea deaths, 406,000 pneumonia deaths and 207,000 malaria deaths across the world Regions such as Africa, Middle East and South-East Asia are bearing high burden of zinc deficiency due to poor nutrition, lack of breastfeeding etc. Treatment of zinc deficiency mainly involves intake of zinc rich food and zinc supplements. Mild zinc deficiency requires treatment with zinc supplements at 2-3 times the recommended dietary allowance (RDA) and moderate to severe zinc deficiency requires zinc supplements with 4-5 times the RDA and treatment is continued for at least 6 months.

Oral repletion of zinc in the form of zinc acetate, zinc sulfate, zinc aspartate, zinc orotate and zinc gluconate, multivitamin supplements etc. and zinc supplements are available in the form of oral tablets capsules, syrups or intravenous solutions. National Institute of Health (NIH) recommends daily intake of 20-40 mg zinc for adults orally to avoid complications caused by zinc deficiency. High dose of zinc i.e. more than 50 mg per day is recommended to patients with severe zinc deficiency or patients with irreversible malabsorptive disorders. Intravenous administration of zinc is rarely recommended unless the patient is suffering from intestinal failure or on long-tern treatment with total parenteral nutrition.

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Market for zinc deficiency treatment is primarily driven by increasing occurrence of malnutrition in underdeveloped and developing countries. Increasing incidence of anemia, hypovitaminosis A, etc. are other factors driving demand for zinc supplements across the globe. Zinc supplements are also used as an adjunctive therapy in many disorders such as alopecia, ulcers, electrolyte replenishment therapy for diarrhea, etc.; high incidence of which can propel the demand for zinc supplements over the forecast period. However, unavailability of treatment opportunities in the underdeveloped countries can be the factor which can hamper growth of global zinc deficiency treatment market.

The global market for zinc deficiency treatment is segmented on basis of product types, treatment, dosage form, distribution channel and geography:

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Among treatment type, dietary supplements is expected to dominate the global market as dietary zinc supplements are recommended along with drug therapy in every patient suffering from zinc deficiency. Among all four distribution channels of zinc supplements, e-commerce is expected to experience highest growth over the forecast period.

On the basis of geography, global zinc deficiency treatment testing market is segmented into five key regions viz. North America, Latin America, Europe, Asia Pacific, and Middle East & Africa. Asia Pacific is expected to dominate the global market for zinc deficiency treatment due to high level of malnutrition in developing countries such as India, Bangladesh, Sri Lanka, etc. The region is expected to witness robust growth due to growing awareness towards malnutrition and its consequences. North America and Western Europe shows lower occurrence of zinc deficiency as adequate intake of animal food by population in the region. Despite high incidence of zinc deficiency in Middle East and Africa market growth is limited by access to zinc supplements due to low purchasing power and poor health consciousness among general population.

Some of the key players present in global zinc deficiency treatment market are Hospira, Inc. (Pfizer Inc.), Metagenics, Inc., Sandoz International GmbH (subsidiary of Novartis AG), Teva Pharmaceutical Industries Ltd., Nu Life Nutrition Ltd., Twin Laboratories Inc., Amway Corp., DSM Nutritional Products, etc. among others.

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First subject dosed with ZF874, a potential disease-modifying treatment for alpha-1-antitrypsin deficiency – Cambridge Network

Posted on August 22, 2020 by Prof Baldwin

AATD is a common genetic disorder, affecting around in 1 in 2000 people in Western countries, where a single mistake in the DNA encoding the protein alpha-1-antitrypsin (A1AT) causes both liver and lung disease.

Nearly all of the cases of AATD are caused by just a single mutation in the A1AT gene, known as the Z mutation. The Z mutation causes most of the A1AT to misfold, forming polymers that stay in the liver instead of being secreted into the blood where it plays a key role in protecting the lungs and other organs from the damaging effects of inflammation explained Jim Huntington, Professor at the University of Cambridge and Founder of Z Factor (pictured). The low levels of correctly-folded A1AT in the lungs results in the development of emphysema in nearly all AATD sufferers. At the same time, accumulation of Z-A1AT polymers in the liver can cause liver disease, sometimes manifesting as liver failure in newborns and more commonly cirrhosis and liver cancer as carriers of this mutation age.

ZF874 was developed with the help of a proprietary crystal structure solved by the Huntington lab. It is a novel compound that acts as a molecular patch for the faulty protein, allowing it to fold correctly, thereby simultaneously relieving the liver burden of polymer accumulation and providing fully-functional Z-A1AT in the circulation to protect the lungs. In mice genetically engineered to express human Z-A1AT in their livers, oral doses of ZF874 were able to substantially increase levels of correctly folded protein in the blood and to completely eliminate accumulation of misfolded protein in the liver.

We are excited to have dosed our first human volunteer with ZF874, said Trevor Baglin, Chief Medical Officer for Z Factor. This trial is designed to allow us to determine how safe and effective it is at raising Z-A1AT levels in humans in a short period of time. We expect to have top-line results for this potentially disease-modifying treatment in subjects carrying the Z mutation by the end of this year.

ZF874 has an excellent safety profile in preclinical toxicology studies and is suitable for oral dosing, ideal for the long-term treatment of patients with AATD, and eventually in the 2-3% of the population carrying a single copy of this mutant gene, who are also at increased risk of both liver and lung disease.

Only one other program targeting Z-A1AT folding is currently in the clinic, from the US pharmaceutical company Vertex (NASDAQ: $VRTX), who expect to report data on a similar time-frame to Z Factor.

The burden of disease caused by the Z-A1AT genetic defect has largely gone under the radar, said David Grainger, Executive Chairman at Z Factor. As many as a third of all emphysema and cirrhosis cases in Western countries, amounting to millions of patients, can trace the origins of their disease to this single error in their DNA. There is a huge unmet clinical need here.

Z Factor was founded in 2015, as a spin-out from the University of Cambridge, armed with the worlds first detailed structure of the Z-A1AT polymer from the Huntington laboratory. Cambridge Enterprise, the commercialisation arm of the University of Cambridge, licensed the technology into Z Factor. Cambridge Enterprise also participated in both the seed round and the Series A round, which was led by Medicxi, with Cambridge Innovation Capital participating.

The funding allowed the team to leverage this window onto the folding defect caused by the Z mutation, working in collaboration with the local out-sourced discovery platform company, RxCelerate, to create ZF874. Entry into the clinic marks a significant step in the development pathway for a drug from concept to approval.

We are one important step closer to delivering a drug that will not only treat the diseases associated with AATD, but that, given prophylactically, may ensure carriers of the Z mutation never develop these diseases in the first place said Huntington.

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First subject dosed with ZF874, a potential disease-modifying treatment for alpha-1-antitrypsin deficiency - Cambridge Network

Bioinformatics Platforms Market: Year 2017-2027 and its detail analysis by focusing on top key players like Illumina, Qiagen, ID Business Solutions,…

Posted on July 24, 2020 by Prof Baldwin

Bioinformatics Platforms Market 2020 Global Industry research report explores analysis of historical data along with size, share, growth, demand, revenue and forecast of the global Bioinformatics Platforms and estimates the future trend of market on the basis of this detailed study. The study shares market performance both in terms of volume and revenue and this factor which is useful & helpful to the business.

Bioinformatics is one of the branch of information technology which deals with the development of software solutions in order to process biological data. Some of the applications included in the bioinformatics research includes, genome annotation, modeling, molecular folding, expression profiling, and gene/protein prediction. The emergence and advancements in bioinformatics are associated with the computerized programming which are specially designed to handle large volumes of DNAs, RNAs, proteins, and metabolites.

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The report provides a detailed overview of the industry including both qualitative and quantitative information. It provides an overview and forecast of the global Bioinformatics Platforms market based on the deployment type and application. It also provides market size and forecast till 2027 for overall Bioinformatics Platforms market with respect to five major regions, namely; North America, Europe, Asia-Pacific (APAC), Middle East and Africa (MEA) and South America (SAM). The market by each region is later sub-segmented by respective countries and segments. The report covers the analysis and forecast of 18 countries globally along with the current trend and opportunities prevailing in the region.

The study conducts SWOT analysis to evaluate strengths and weaknesses of the key players in the Bioinformatics Platforms market. Further, the report conducts an intricate examination of drivers and restraints operating in the market. The report also evaluates the trends observed in the parent market, along with the macro-economic indicators, prevailing factors, and market appeal according to different segments. The report also predicts the influence of different industry aspects on the Bioinformatics Platforms market segments and regions.

Bioinformatics Platforms Market Company Profiles

The List of Companies Illumina Inc., Qiagen, ID Business Solutions,, Dassault Systems, Agilent Technologies, Genologics Life Sciences Software Inc., Sophia Genetics, DNASTAR, Wuxi NextCODE,BGI

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Most important type of Bioinformatics Platforms covered in this report are:

Based on end user/application, this report focuses on the status and outlook for major applications:

The research provides answers to the following key questions:

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Insecurity about the future

Our research and insights help our clients anticipate upcoming revenue compartments and growth ranges. This will help our clients invest or divest their assets.

Understanding market opinions:

It is extremely vital to have an impartial understanding of market opinions for a strategy. Our insights provide a keen view on the market sentiment. We keep this reconnaissance by engaging with Key Opinion Leaders of a value chain of each industry we track.

Understanding the most reliable investment centers:

Our research ranks investment centers of market by considering their future demands, returns, and profit margins. Our clients can focus on most prominent investment centers by procuring our market research.

Evaluating potential business partners:

Our research and insights help our clients identify compatible business partners.

Table Of Content

1.INTRODUCTION

2. KEY TAKEAWAYS3. RESEARCH METHODOLOGY4. BIOINFORMATICS PLATFORMS LANDSCAPE

5. BIOINFORMATICS PLATFORMS KEY MARKET DYNAMICS

6. BIOINFORMATICS PLATFORMS GLOBAL MARKET ANALYSIS

7. BIOINFORMATICS PLATFORMS REVENUE AND FORECASTS TO 2027 PLATFORM TYPE

8. BIOINFORMATICS PLATFORMS REVENUE AND FORECASTS TO 2027 APPLICATION

9. BIOINFORMATICS PLATFORMS REVENUE AND FORECASTS TO 2027 END USER

10. BIOINFORMATICS PLATFORMS REVENUE AND FORECASTS TO 2027 GEOGRAPHICAL ANALYSIS

11. INDUSTRY LANDSCAPE

12. BIOINFORMATICS PLATFORMS, KEY COMPANY PROFILES

13. APPENDIX

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A nucleotidyltransferase toxin inhibits growth of Mycobacterium tuberculosis through inactivation of tRNA acceptor stems – Science Advances

Posted on August 1, 2020 by Prof Baldwin

INTRODUCTION

Toxin-antitoxin (TA) systems are widely distributed throughout prokaryotic genomes and have been shown to help bacteria to survive predation by bacteriophages, immune responses, and antibiotic treatments (15). In many cases, however, the roles of chromosomal TA systems remain largely unknown, primarily due to the lack of a phenotype associated with deletion mutants under in vitro laboratory conditions (69). TA systems are also widespread among mobile genetic elements, including plasmids, superintegrons, cryptic prophages, and conjugative transposons, where they contribute to their stability (10, 11).

TA systems encode two components, a toxic protein that targets an essential cellular process and an antagonistic antitoxin, which blocks toxin activity when cells are growing under favorable conditions. Although the processes that lead to toxin activation remain under debate, it has been proposed that under certain stress conditions, increased toxin transcription and synthesis may lead to activation (8, 12). This, in turn, reduces growth rate, which can provide a means to survive with minimal metabolic burden until favorable conditions return (13).

TA systems are divided into six types according to the nature of the toxin and antitoxin (whether they are RNA or protein) and the mechanism of toxin antagonism (3). Type II systems, in which a protein toxin is sequestered by a protein antitoxin, have been most extensively studied. They are also remarkably abundant in Mycobacterium tuberculosis, which potentially encodes more than 80 type II TA systems, and are thought to have contributed to the success of M. tuberculosis as a human pathogen (1416). Many of the putative M. tuberculosis toxins tested thus far were shown to inhibit bacterial growth, suggesting that these TA systems are functionally active and could modulate M. tuberculosis growth under certain conditions, thereby contributing to survival in the human host (15, 17). Accordingly, many M. tuberculosis TA operons were shown to be induced in response to relevant stressors, including hypoxia, the presence of antimicrobial drugs, or macrophage engulfment (14, 17). As M. tuberculosis encodes, among others, more than 50 VapBC, 10 MazEF, 3 HigBA, and 3 RelBE TA systems, it might be expected that there is redundancy between them, alongside condition-specific applications for each system. Furthermore, the highly toxic nature of some of these toxins suggests that their antibacterial mechanisms could be developed into antimicrobials (18).

This study focuses on a family of four putative toxins from M. tuberculosis, namely, Rv0078A, Rv0836c, Rv1045, and Rv2826c, which share a conserved nucleotidyltransferase (NTase)like domain annotated as domain of unknown function (DUF) 1814 (Fig. 1A). The most well-characterized example of this DUF1814 family is AbiEii from Streptococcus agalactiae, which shares 18.3% sequence identity with Rv1045, and was identified within the AbiE abortive infection bacteriophage-defense systems (19). AbiEii was shown to constitute a new type of TA system, type IV, based on the observation that no interaction could be detected between the toxin and the antitoxin proteins (20). The DUF1814 family of proteins is widespread in bacterial, archaeal, and fungal genomes (20), though not all examples are genetically linked to putative antitoxins. As putative NTases, DUF1814 proteins contain four conserved motifs. The N-terminal motifs I and II are found in DNA polymerase and are proposed to coordinate a metal ion for nucleotide binding and transfer (20). The C-terminal motif III is similar to that of tRNA NTases that add the 3-CCA motif to immature tRNAs and may be important for base stacking with substrates (21). The C-terminal motif IV is unique to DUF1814 proteins and is proposed to form a catalytic site with motif III (20).

(A) Scaled representation of the four M. tuberculosis TA systems containing NTase-like toxin genes with original and revised nomenclature (left), and corresponding toxicity and antitoxicity assays in M. smegmatis (right). For toxicity and antitoxicity assays, cotransformants of M. smegmatis mc2 155 containing pGMC-vector, -MenT1, -MenT2, -MenT3, or -MenT4 (toxins) and pLAM-vector, -MenA1, -MenA2, -MenA3, or -MenA4 (antitoxins) were plated on LB-agar in the presence or absence of anhydrotetracycline (Atc; 100 ng ml1) and acetamide (Ace; 0.2%) inducers for toxin and antitoxin expression, respectively. Plates were incubated for 3 days at 37C. T and A denote toxin and antitoxin, respectively. and + represent absence or presence of inducer, respectively. (B) M. smegmatis strain mc2 155 transformed with plasmid pGMCS-TetR-P1-RBS1-MenT3 was grown in complete 7H9 medium with Sm. At time 0, the culture was divided into two. Half was kept in the same medium (pale blue bars) and half was additionally treated with Atc (200 ng ml1) (dark blue bars). Samples were harvested at the indicated times, washed, diluted, and plated on LB-agar with Sm but without Atc. Colonies were counted after 3 days at 37C. Shown values are the average of three biological replicates with SD. CFU, colony-forming unit. (C) Samples of the same cultures as in (B) were harvested after 8 or 24 hours, labeled with the LIVE/DEAD BacLite dyes [Syto 9; propidium iodide (PI)], and analyzed by fluorescence-activated cell sorting. The percentage of PI-positive cells is shown for each sample (pale blue bars, no Atc; dark blue bars, 200 ng ml1 Atc). Shown values are the average of three biological replicates with SD. (D) M. tuberculosis wild-type (WT) H37Rv or mutant strain H37Rv (menA3-menT3)::dif6 were transformed with 100 ng of plasmids expressing either menA3, menT3, or menA3-menT3. These plasmids encode a consensus Shine-Dalgarno sequence (RBS1), except for Weak-RBS-menT3, which encodes a near-consensus sequence (RBS4) to weaken expression. After phenotypic expression, half of the transformation mix was plated on 7H11 oleic acidalbumin-dextrose-catalase (OADC) plates with Sm, and the other half was plated on 7H11 OADC Sm plates supplemented with Atc (200 ng ml1). Plates were imaged after 20 days at 37C; data are representative of three independent experiments. (E) Mutant strain H37Rv (menA3-menT3)::dif6 was transformed with 100 ng of plasmids expressing either menT3 WT or mutant alleles introducing the D80A, K189A, or D211A substitutions. After phenotypic expression, half of the transformation mix was plated on 7H11 OADC plates with Sm, and the other half was plated on 7H11 OADC Sm plates supplemented with Atc (200 ng ml1). Pictures were taken after 20 days at 37C; data are representative of three independent experiments.

In M. tuberculosis, the DUF1814 toxins are encoded downstream of a variety of putative antitoxins (Fig. 1A). The toxin gene rv0078A is paired with a short upstream open reading frame encoding a 68amino acid antitoxin, Rv0078B, related to MazE antitoxins, which is predicted to be disordered and lacking a DNA-binding domain (16). Toxin gene rv0836c lies downstream of a COG4861 gene, encoding a much larger putative antitoxin than the cognate toxin (Fig. 1A). Rv1045 and Rv2826c toxins are downstream of their cognate putative antitoxins Rv1044 and Rv2827c, respectively, both of which are COG5340 transcriptional regulator family proteins (Fig. 1A). COG5340 proteins include the S. agalactiae AbiEi antitoxin partner of AbiEii, which has previously been shown to bind to and repress the abiE promoter, similar to autoregulation observed in type II TA loci (22). An earlier transposon site hybridization study identified both the Rv1044 and Rv2827c antitoxins as essential for growth (23). Saturating transposon mutagenesis has additionally demonstrated that Rv1044 is essential, while transposon insertions in Rv2827c impart a growth defect (24). The fact that both antitoxins are important for M. tuberculosis growth strongly suggests that their putative cognate Rv1045 and Rv2826c toxins inhibit growth in M. tuberculosis.

Here, we undertook a series of microbiological, structural, genetic, and biochemical studies to investigate the DUF1814 toxins of M. tuberculosis and reveal their mode of action. We show that the Rv1045 toxin is a tRNA NTase that is active in M. tuberculosis and blocks translation through a previously undescribed mechanism involving inactivation of serine tRNAs.

We first investigated the activity of the putative TA systems containing NTase-like DUF1814 toxins in Mycobacterium smegmatis, which is closely related to M. tuberculosis and does not encode similar antitoxins (15). On the basis of the findings presented below, we renamed these putative systems as mycobacterial AbiE-like NTase toxins (MenT) and antitoxins (MenA), numbered according to their order in the M. tuberculosis genome (Fig. 1A). Toxins and antitoxins were expressed in trans, with the toxins cloned into the pGMC-integrative plasmid under the control of an anhydrotetracycline (Atc)inducible promoter and the antitoxins into the compatible pLAM plasmid under the control of an acetamide (Ace)inducible promoter (Fig. 1A). Among the four putative toxins, only MenT1 has been tested so far and was shown to be toxic in M. smegmatis when expressed without the upstream open reading frame encoding MenA1, suggesting that MenA1-MenT1 form a functional TA system (16). Accordingly, the data presented in Fig. 1A show that MenT1 toxicity was efficiently counteracted by MenA1 expressed in trans. Both MenA3-MenT3 and MenA4-MenT4 also acted as TA pairs, while MenT2 expression was not toxic (Fig. 1A). Inhibition of MenT4 toxicity could only be achieved when the putative antitoxin was expressed in the context of the menA4-menT4 operon (Fig. 1A). Expression of MenA4 alone from pLAM was toxic (fig. S1A), indicating that MenA4-MenT4 might not function as a typical TA pair under these conditions. Similar experiments performed in Escherichia coli confirmed the phenotypes observed in M. smegmatis for MenA2-MenT2, MenA3-MenT3, and MenA4-MenT4 (including MenA4 toxicity), but not for MenT1, which exhibited no detectable toxicity in E. coli (fig. S1B). Last, coexpression of the active toxins with noncognate antitoxins did not reveal any detectable cross-talk between the different TA pairs (fig. S1, A and C). Note that cross-talk assays with MenA4 antitoxin expressed from pLAM in M. smegmatis could not be performed because of its toxicity.

Ectopic expression of MenT3 in the presence of inducer showed the most robust toxicity in both M. smegmatis and E. coli when compared to the other toxins (Fig. 1A and fig. S1). In M. smegmatis, only a few MenT3 transformants were obtained, even in the absence of inducer. Ectopic expression of MenT3 in M. smegmatis induced a rapid drop of about 3-log10 in colony-forming units only 2 hours after induction with Atc (Fig. 1B). LIVE/DEAD BacLight stains have previously been used to study the effects of toxin expression on cell viability in M. tuberculosis (18). Flow cytometry analysis of M. smegmatis expressing MenT3 revealed that the proportion of propidium iodidepermeable cells was substantially higher in MenT3-induced versus noninduced cells 8 or 24 hours after induction with Atc (Fig. 1C), indicating that MenT3 strongly affects cell viability.

To investigate the impact of MenA3 and MenT3 on M. tuberculosis growth, plasmids encoding the toxin, the antitoxin, or both, were introduced into H37Rv wild-type (WT) strain. The resulting transformants were not sensitive to ectopic expression of MenT3 (Fig. 1D), presumably because endogenous MenA3 was sufficient to neutralize the sum of endogenous and ectopic MenT3. To confirm this hypothesis, we attempted to construct a strain deleted for the menA3-menT3 operon. Previous work showed that menA3 cannot be disrupted by transposon insertion (24). Accordingly, we found that deletion of the menA3-menT3 operon in M. tuberculosis H37Rv strain could not be achieved, most likely because simultaneous disruption of both genes resulted in a toxic effect from residual MenT3. To circumvent this problem, we constructed the deletion in a derivative of H37Rv carrying a second copy of menA3 constitutively expressed from a pGMC integrative plasmid. Once the menA3-menT3 operon was deleted, it was then possible to remove the ectopic copy of menA3 by pGMC plasmid replacement (fig. S2). The menA3-menT3 mutant became highly sensitive to the MenT3 toxin, even in the absence of inducer (Fig. 1D). Therefore, to finally obtain transformants, menT3 was cloned downstream of a weaker Shine-Dalgarno sequence. Using this construct, we observed inducible MenT3 toxicity, which was fully abolished by the presence of the antitoxin (Fig. 1D). Together, these data demonstrate that the MenT3 toxin inhibits growth and that MenA3-MenT3 functions as a bona fide TA pair in M. tuberculosis.

A previous amino acid sequence alignment of DUF1814 putative NTases highlighted conserved residues, a number of which were confirmed as essential for AbiEii toxicity in S. agalactiae (20). To investigate whether some of these residues were important for MenT3 toxicity, we selected and engineered three conserved residues for substitution: D80A, localized in the DNA pol superfamily motif, and K189A and D211A, both toxin-specific residues. We then tested the impact of these substitutions on M. tuberculosis growth (Fig. 1E). All three substitutions abolished MenT3 toxicity in both M. tuberculosis (Fig. 1E) and E. coli (fig. S3A).

Next, we investigated whether the MenT3 toxin and MenA3 antitoxin could interact in vivo. Since this TA pair is functional in E. coli, we performed affinity-tagged in vivo copurification experiments in E. coli using His-tagged variants of MenT3 and MenA3, which were first confirmed to be active as toxin and antitoxin, respectively (fig. S4A). In strains coexpressing both the toxin and the antitoxin (with either the toxin or the antitoxin tagged), and with tagged toxin and tagged antitoxin alone as controls, the in vivo copurification revealed that a small but significant fraction of the MenT3 toxin and the MenA3 antitoxin copurified, whether the toxin or the antitoxin was used as bait (fig. S4, C and D). Similar results were obtained with the MenA1-MenT1 pair, which encodes a much shorter, unrelated antitoxin (fig. S4, B, E, and F). Together, these data show that both TA partners can interact, but it remains to be determined whether a direct interaction between an NTase toxin and its cognate antitoxin is required for toxin inhibition.

To begin investigations into the mechanism of toxicity of MenT3, we solved its structure to 1.6 resolution by x-ray crystallography (Fig. 2A and Table 1). MenT3 is a monomeric bi-lobed globular protein, with two hemispheres connected by a short linker (Fig. 2A). This monomeric assembly matches the expected size observed by size exclusion chromatography. Surface electrostatics show a distinct electropositive surface leading to a deeper recess (Fig. 2B, left), which contains residues D80, K189, and D211 that were needed for toxicity in vivo (Fig. 1E). This potentially indicates the position of the active site, and the electropositive surface may facilitate interaction with electronegative substrates such as nucleic acids. To further characterize the DUF1814 family, we also solved the MenT4 toxin structure to 1.2 resolution (Fig. 2C and Table 1). MenT4 is also monomeric (also observed by size exclusion chromatography) and the overall architecture is similar to, but not exactly the same as, MenT3. MenT4 has a bi-lobed globular structure and distinct electropositive patches close to a similarly positioned active site region (Fig. 2, C and D). Aligning MenT3 and MenT4 by sequence gave a poor root mean square deviation (RMSD) of 13.4 ; however, this can be improved to 4.7 using sequence-independent superposition, which demonstrates similarity in overall fold (Fig. 2E). A close-up of MenT3 residues D80, K189, and D211 show them clustered at the putative active site, and when overlaid, the homologous MenT4 residues, D69, K171, and D186, respectively, take up similar positions (Fig. 2F). There was also density for a phosphoserine at MenT3 S78, but the corresponding residue in MenT4, S67, was not phosphorylated (Fig. 2F). Searches for structural homologs of MenT3 and MenT4 were performed using the DALI server (25). Among multiple hits for NTases, the best match was for JHP933 from Helicobacter pylori, a predicted NTase encoded by the jhp0933 gene (26). JHP933 aligned to MenT3 with an RMSD of 2.4 , though multiple additional helices were resolved in the MenT3 structure (Fig. 2G). An analysis of the H. pylori genome revealed that the jhp0932 gene lies just upstream of jhp0933 and partially overlaps its coding sequence. The presence of these genes in what appears to be a classic TA configuration suggests that JHP933 may belong to the MenT3/MenT4 family of NTase-like toxins.

(A) Structure of monomeric MenT3 toxin, with views from front and back, shown as cyan cartoon representations. (B) Surface electrostatics of MenT3, viewed as in (A), with red for electronegative and blue for electropositive potential. (C) Structure of monomeric MenT4, with views from front and back, shown as salmon cartoon representations. (D) Surface electrostatics of MenT4, viewed as in (C), colored as per (B). (E) Superposition of MenT4 onto MenT3, viewed and colored as per (A) and (C). (F) Tilted close-up view of the toxin active sites, as indicated by the boxed region of (E). MenT3 residues S78 (phosphorylated), D80, K189, and D211 are indicated, along with the homologous MenT4 residues S67, D69, K171, and D186. (G) Alignment of JHP933 (PDB: 4O8S) as orange cartoon representation, against MenT3 viewed and colored as per (A, left).

MenT3 is the most toxic of the four M. tuberculosis NTase-like toxins tested, both in mycobacteria and in E. coli (Fig. 1 and fig. S1). We therefore took advantage of this robust toxicity to search for E. coli genes that were able to suppress MenT3-mediated growth inhibition when overexpressed. We reasoned that identification of such suppressors might potentially shed light on the cellular processes affected by the toxin. Details of the genetic selection used are described in Materials and Methods. Among the approximately 60,000 clones of the E. coli genomic plasmid library tested in this work, we identified 18 plasmids that passed two rounds of selection and appeared to encode bona fide suppressors of MenT3 toxicity. We observed that the toxin-resistant colonies were noticeably smaller and translucent compared to noninduced cells, indicating that, although notably reduced, MenT3 toxicity is not fully suppressed. Sequencing of the genomic regions encoded by the 18 suppressor plasmids revealed that several of these candidate plasmids harbored the same genomic fragments. Six different suppressor clones encompassing two different regions of the E. coli chromosome were identified. Two of the six suppressor plasmids harbored the ydeA gene, encoding an l-arabinose (l-ara) exporter protein known to decrease l-ara levels in E. coli (27). These suppressors were discarded as YdeA overexpression would presumably decrease toxicity of many toxic proteins expressed from the araBAD promoter. The four other suppressor plasmids harbored the rph gene, encoding the phosphorolytic ribonuclease (RNase PH), involved in the 3 processing of RNAs (Fig. 3A). RNase PH removes nucleotides downstream of the 3-CCA sequence, required for aminoacylation of tRNAs, from tRNA precursors with 3 extensions. It is also involved in other RNA maturation and quality control processes, including the maturation of rRNA (28).

(A) The E. coli K-12 genomic region containing the rph gene is shown. Suppressor plasmids that counteract MenT3 toxicity encoded rph, as depicted by small arrows under the adjacent genes pyrE, yicC, and dinD. The positions in base pair of the ends of each suppressor fragment, in relation to the E. coli K-12 chromosome, are indicated between brackets. (B) Overexpression of E. coli RNase PH partially suppresses MenT3 toxicity. E. coli DLT1900 strains containing either pK6-vector () or pK6-MenT3 (+) were cotransformed with p29SEN-vector () or p29SEN-Rph (RNase PH) (+). The resulting cotransformants were serially diluted, spotted onto LB-agar plates in the presence or absence of l-ara (0.1%) and IPTG (200 M) inducers, and incubated at 37C. (C) Deletion of rph further increases MenT3 toxicity. Transformants of E. coli DLT1900 WT and rph mutant strains containing plasmid pK6-MenT3 were serially diluted, spotted onto LB-agar plates with or without l-ara (0.01%), and incubated at 37C. (D) In vitro transcription/translation reactions assessing levels of DHFR control protein produced in the absence or presence of increasing concentrations of MenT3 toxin. Samples were separated by SDSpolyacrylamide gel electrophoresis and stained with InstantBlue. (E) For in vivo assays, transformants of E. coli BL21 (DE3) containing plasmid pET-MenT3 or the empty vector were grown in M9M at 37C. Following overexpression of MenT3, tRNAs were extracted, separated, and visualized by Northern blot using specific radiolabeled probes against tRNATrp. For in vitro assays, purified MenT3 (10 M) was added to transcription/translation assays producing GatZ protein. After 2 hours at 37C, tRNAs were extracted, separated, and visualized by Northern blot as performed for the in vivo samples. All images are representative of triplicate data.

Suppression of MenT3 toxicity by RNase PH overexpression was confirmed by cloning rph alone in a lowcopy number plasmid under the control of an isopropyl--d-thiogalactopyranoside (IPTG)inducible promoter and assaying for growth in the presence of MenT3 in E. coli (Fig. 3B). We also showed that the toxicity of MenT3 was enhanced when expressed in E. coli carrying a deletion of the rph gene, even with a 10-fold decrease in inducer levels (Fig. 3C), further reinforcing the genetic link between menT3 and rph. The primary role of RNase PH in processing tRNAs suggests that DUF1814 NTase-like toxins could act directly at the site of aminoacylation at the 3-end of tRNA, thus inhibiting translation. Whether endogenous RNase PH would be sufficiently induced in response to toxin expression to help restore the functional tRNA pool in recovering M. tuberculosis cells remains to be determined.

MenT3 WT and the MenT3(D80A) and MenT3(K189A) substitutions were overexpressed and purified for biochemical characterization. When tested in an in vitro transcription/translation reaction that uses recombinant E. coli components, purified MenT3 WT reduced production of the E. coli dihydrofolate reductase (DHFR) control protein in a concentration-dependent manner (Fig. 3D). Compared to MenT3 WT, MenT3(D80A) and MenT3(K189A) had a markedly reduced impact on the production of DHFR (fig. S5A). The same trend was observed when MenT3 WT, MenT3(D80A), and MenT3(K189A) were used in in vitro reactions producing WaaF and GatZ as test proteins (fig. S5, B and C). We also expressed and purified MenT4 WT and demonstrated that this, too, prevented the production of DHFR in a concentration-dependent manner in in vitro transcription/translation assays (fig. S5D).

The fact that MenT3 inhibited protein synthesis, and that RNase PH is involved in the removal of nucleotides following the 3-CCA sequence required for tRNA aminoacylation, suggested that tRNA charging might be affected by MenT3 expression in vivo. To address this hypothesis, we first used a method developed for E. coli, which separates charged from uncharged tRNAs and allows their detection by Northern blot after extraction in vivo (29). We chose tRNATrp as a model tRNA because (i) the tryptophanyl-tRNA can be well separated from uncharged tRNATrp and (ii) there is only one tRNATrp in E. coli (29). No charged tryptophanyl-tRNATrp could be detected following overexpression of MenT3 when compared to the empty vector control (Fig. 3E and fig. S5E). tRNATrp charging levels were also investigated in vitro by adding purified MenT3 to the transcription/translation assay described above (Fig. 3E). In this case, MenT3 also affected tRNATrp charging in vitro, thus supporting the hypothesis that the toxin inhibits protein synthesis by preventing aminoacylation of tRNA.

The observation that MenT3 is related to NTases (Fig. 2G) suggests that its mode of action is to directly transfer nucleotides to tRNAs, thereby preventing aminoacylation. We performed assays using radiolabeled tRNAs to track the addition of nucleotides by MenT3 WT, MenT3(D80A), and MenT3(K189A) (Fig. 4).

(A) Radiolabeled E. coli tRNATrp was incubated with 1, 0.1, 0.01, or 0.001 g of MenT3 WT or no toxin () for 20 min at 37C in the presence of unlabeled GTP, ATP, UTP, or CTP. Extended products are indicated with arrowheads throughout all panels. (B) Radiolabeled E. coli tRNATrp was incubated with 1, 0.1, or 0.01 g of MenT3 WT or MenT3(D80A) with CTP or UTP, as per conditions in (A). (C) Incubation of radiolabeled E. coli tRNATrp with 1, 0.1, 0.01, or 0.001 g of MenT3 WT or MenT3(K189A), with CTP, UTP, or a mixture of both, as per conditions in (A). (D) Radiolabeled E. coli tRNATrp preparations, made with or without a 3-CCA motif, were incubated with 1, 0.1, or 0.01 g of either MenT3 WT, MenT3(K189A), or no toxin (), for 20 min at 37C in the presence of unlabeled UTP or CTP. Note that the () CCA lanes have been overexposed to equalize intensity to the (+) CCA lanes of the same gel. Assays of the individual WT and MenT3 substitution proteins and tRNATrp CCA substrates shown in (A) to (D) were performed between two and four times.

MenT3 WT was incubated with tRNATrp from E. coli, as a model recipient tRNA, in the presence of guanosine 5-triphosphate (GTP), adenosine 5-triphosphate (ATP), uridine 5-triphosphate (UTP), or cytidine 5-triphosphate (CTP), and nucleotide transfer was monitored as an increase in tRNA size by high-resolution polyacrylamide gel electrophoresis (PAGE; Fig. 4A). At high concentrations of the enzyme, we found that MenT3 can add two to three extra nucleotides to tRNATrp in the presence of CTP or UTP, with a slight preference for CTP, suggesting that MenT3 is a pyrimidine-specific NTase (Fig. 4A). No transfer was observed with purines ATP or GTP as substrates (Fig. 4A). MenT3(D80A), which was unable to inhibit in vitro protein synthesis (fig. S5, A to C), had no NTase activity with either UTP or CTP (Fig. 4B). MenT3(K189A), which was also inactive in the in vitro transcription/translation assay (fig. S5, A to C), only lost its NTase activity in the presence of UTP, but retained some activity (albeit less than WT) in the presence of CTP, or both nucleotides (Fig. 4C). This could imply that K189A is important for substrate nucleotide selectivity. No synergistic effect was seen when MenT3 WT was incubated with a mixture of CTP and UTP, as the pattern with both nucleotides together resembled that of CTP alone (Fig. 4C).

Canonical tRNA NTases typically add the 3-CCA motif to tRNAs lacking an encoded 3-CCA that are processed at the level of the discriminator nucleotide (nucleotide 73). They also repair this motif when 3-exoribonucleases, such as RNase PH, fail to stop at the 3-CCA motif when processing tRNA precursors containing an encoded 3-CCA, typically removing the terminal A residue. Since M. tuberculosis contains a mixture of tRNA genes encoding or lacking a 3-CCA motif, we wondered whether MenT3 had a preference for one class (or another class) of substrate. While faint NTase activity was observed when MenT3 WT and MenT3(K189A) were incubated with CTP and tRNATrp lacking a 3-CCA, the data show that MenT3 had a clear preference for tRNAs that already possessed a 3-CCA motif (Fig. 4D). This is in contrast to the normal function of tRNA NTases, which prefer tRNAs lacking an intact 3-CCA. Again, MenT3 WT modified tRNATrp using both CTP and UTP as substrate, while MenT3(K189A) could only use CTP (Fig. 4D). Addition of nucleotides to mature tRNAs by MenT3 would completely abolish the ability of these tRNAs to be charged with their cognate amino acid and take part in translation, accounting for their cellular toxicity.

Our in vivo data show that toxins MenT3, as well as MenT1 and MenT4, are significantly less toxic in E. coli than in mycobacteria (Fig. 1 and fig. S1), which suggests that these toxins may have a tRNA target preference. We therefore asked whether MenT3 would exhibit some specificity toward the different tRNAs of M. tuberculosis. We made polymerase chain reaction (PCR) templates allowing us to in vitro transcribe the 45 different tRNAs of M. tuberculosis, each with a 3-CCA motif (fig. S6). As before, each radiolabeled tRNA was incubated with MenT3 and nonradiolabeled CTP (Fig. 5A). To our surprise, MenT3 appeared to be highly specific, preferentially modifying the four M. tuberculosis tRNASer isoacceptors, along with weak modification of tRNALeu5 (Fig. 5A). Although we cannot exclude that MenT3 can modify other tRNAs in vivo, the data show that the toxin presents a high degree of specificity toward different tRNAs in vitro, which may explain the variable toxicity observed in different bacteria.

(A) Radiolabeled M. tuberculosis tRNAs were incubated with 0.1 g of MenT3 WT (+) or no toxin () for 20 min at 37C in the presence of unlabeled CTP. E. coli tRNATrp (EcTrp) was used as a positive control. The global screen of all M. tuberculosis tRNA was performed once and the effect of MenT3 tRNASer2 was confirmed twice independently. (B) Schematic diagram of the MenT3 toxin mechanism of action. MenT3 elongates the 3-CCA motif of specific tRNAs, preventing their charging by aminoacyl-tRNA synthetases (AaRS), thereby interfering with translation and inhibiting bacterial growth.

Last, we asked whether the antitoxin MenA3 inhibited the NTase activity of MenT3 directly, or whether it could simply reverse its action by removing the added nucleotides in a manner similar to the RNase PH multicopy suppressor. Addition of MenA3 strongly inhibited the NTase activity of MenT3 on the natural substrate M. tuberculosis tRNASer2 when coincubated with the toxin at a molar ratio > 2.5. However, MenA3 failed to remove the added nucleotides from tRNASer2 when added after a preincubation of tRNASer2 with MenT3, even at high concentrations (fig. S7). This suggests that the antitoxin is likely to inhibit the toxin rather than reverse the reaction on the substrate.

This study has characterized a family of TA systems from M. tuberculosis containing NTase-like DUF1814 toxins, establishing MenT3 as a potent toxin in this problematic pathogen. We have solved the structures of the homologous toxins MenT3 and MenT4 by x-ray crystallography, revealing fold similarity and conserved residues within the proposed active sites, and have observed a similar mode of toxin activity, targeting protein synthesis. We have further elucidated the mechanism of toxicity for MenT3, showing that it functions as a pyrimidine-specific NTase preferentially targeting M. tuberculosis tRNASer in vitro (Fig. 5B).

The observation that the three NTase toxins identified in this work show different levels of toxicity when expressed in the same host, and that such toxic signatures can vary when expressed in different bacterial hosts (i.e., E. coli versus mycobacteria), is intriguing (Fig. 1 and fig. S1). The most marked example is MenT1, which shows robust toxicity in M. smegmatis but no toxicity in E. coli (Fig. 1A and fig. S1B). Although we cannot exclude this being a result of improper folding or expression of the toxin in E. coli, it is also reasonable to assume that the toxin may not be able to recognize its tRNA targets due, for example, to tRNA modification, or the absence of its preferred tRNA target (30). Another possibility is that tRNA targets are expressed at higher levels in E. coli and are thus sufficiently abundant to overcome the noxious effect of the toxin in vivo. The fact that M. tuberculosis and M. smegmatis only have 45 and 46 tRNA genes, respectively, while E. coli has 86, is in line with this hypothesis (30, 31).

The apparent in vitro specificity of MenT3 for certain M. tuberculosis tRNAs, especially tRNASer, is remarkable (Fig. 5A). We did not test other tRNAs in E. coli besides tRNATrp; it may well have been fortuitous that the only tRNA we tested in this organism was detectably modified by the toxin in vitro (Fig. 4A) and in vivo, inferred from the reduced charging levels following toxin expression (Fig. 3E). We checked whether the M. tuberculosis tRNAs that were substrates of MenT3 had any distinguishing features and were struck by the fact that all serine tRNAs and several leucine tRNAs were unique among M. tuberculosis tRNAs in that they had long variable arms (fig. S8A) (32). While this is intriguing and may contribute to substrate specificity, it cannot be the only recognition element because (i) two leucine tRNAs besides tRNALeu5 have variable loops but are not MenT3 substrates in vitro and (ii) E. coli tRNATrp does not have a variable loop (fig. S8B), but can be extended by the NTase activity of the toxin. It is also intriguing in this regard that M. tuberculosis tRNATrp is not a MenT3 substrate in vitro. E. coli and M. tuberculosis tRNATrp are highly homologous but do show differences in their variable- and T-arm sequences (fig. S8C). Substrate specificity therefore appears to come from a combination of multiple sequence and structure motifs. Having identified these tRNA targets in vitro, further work is now needed to confirm targeting in vivo in M. tuberculosis.

Our observed TA interactions raise questions regarding the molecular mechanisms of antitoxicity for DUF1814 toxins (fig. S4, C to F). Typically, in type II TA systems, antitoxin function is in part driven by its strong and direct interaction with the cognate toxin (3). While we have shown interactions between cognate toxins and antitoxins (fig. S4, C to F), the antitoxin interaction in vivo appears weak. We additionally demonstrated that coincubation of the MenA3 antitoxin with MenT3 is able to neutralize the NTase activity (fig. S7). This suggests that any interaction-based antitoxicity might be a transient and labile mechanism and, due to the difference in size and sequence between antitoxins MenA1 and MenA3 (Fig. 1A), may well differ between these systems.

The DUF4433 DarT toxin from M. tuberculosis was recently identified as a single-stranded DNA NTase that specifically and reversibly adenosine 5-diphosphate (ADP)ribosylates thymidines (33). Our study identifies MenT3 as an NTase toxin from the unrelated DUF1814 protein family. In comparison to DarT, MenT3 acts via a distinct and novel mode of toxicity where the MenT3 toxin preferentially targets M. tuberculosis tRNAs in vitro, preventing their charging with cognate amino acids by adding nucleotides to the 3-CCA acceptor stem (Fig. 5B). Accordingly, antitoxin function also appears to differ between these systems. Whereas DarT is counteracted enzymatically by the cognate antitoxin DarG via target de-ADP-ribosylation (33), we found that MenA3 was unable to reverse MenT3 toxicity by removing nucleotides, suggesting that MenA3 likely inhibits the toxin activity.

Increasing numbers of toxins have been identified that target tRNAs by various mechanisms (13). The M. tuberculosis type II VapC toxins function as endoribonucleases cleaving tRNAs (34), whereas TacT from Salmonella Typhimurium and AtaT from E. coli are tRNA acetyltransferases, modifying charged tRNAs to block translation (35, 36). That MenT3 provides yet another way to inhibit tRNA activity is perhaps not unusual, given the essential nature of translation to cellular growth and survival. This likely reflects the value of possessing multiple TA systems to promote adaptability to different stressful environments via tRNA metabolism, with downstream effects ranging from stalling cell growth to potentially altering translation output (13). It remains to be seen whether this mechanism is conserved among DUF1814-toxins; while MenT4 shares structural similarities to MenT3 and inhibits protein synthesis in vitro (Fig. 2 and fig. S5D), we have not yet explored the molecular mechanism behind its toxicity. Given the continued significance of M. tuberculosis worldwide, the mechanism used by the MenA3-MenT3 TA system highlights a new way to block protein synthesis. We propose that further exploring the molecular mechanisms of both toxicity and antitoxicity will provide useful insights into the regulation of bacterial growth.

E. coli DH5 (Invitrogen), DH10B (Thermo Fisher Scientific), BL21 (DE3) (Novagen), ER2566 (New England Biolabs), W3110 [strain American Type Culture Collection (ATCC) 27325], DLT1900 (37), and M. smegmatis mc2 155 (strain ATCC 700084) are as previously described. To construct BL21 (DE3) slyD, the slyD::KmR allele from JW3311 (Keio collection) was moved into BL21 (DE3) using bacteriophage P1-mediated transduction. To construct the unmarked DLT1900 rph mutant, the rph::KmR allele from JW3618 (Keio collection) was first moved into DLT1900 using bacteriophage P1-mediated transduction and by subsequent removing of the kanamycin (Km) resistance cassette using plasmid pCP20, as previously described (38). E. coli were routinely grown at 37C in LB medium or M9 minimal (M9M) medium supplemented when necessary with Km (50 g ml1), ampicillin (Ap; 50 g ml1), chloramphenicol (Cm; 34 g ml1), streptomycin (Sm; 25 g ml1), spectinomycin (Sp; 50 g ml1), IPTG (1 mM), l-ara (0.1% w/v), or d-glucose (glu; 0.2% w/v). M. smegmatis mc2 155 strains were routinely grown at 37C in either LB or 7H9 medium (Difco). M. tuberculosis H37Rv (WT; ATCC 27294) and mutant strains were routinely grown at 37C in complete 7H9 medium (Middlebrook 7H9 medium, Difco) supplemented with 10% albumin-dextrose-catalase (ADC; Difco) and 0.05% Tween 80 (Sigma-Aldrich), or on complete 7H11 solid medium (Middlebrook 7H11 agar medium, Difco) supplemented with 10% oleic acidADC (OADC; Difco). When required, mycobacterial growth media were supplemented with Km (50 g ml1), hygromycin (Hm; 50 g ml1), Sm (25 g ml1), zeocin (Zc; 25 g ml1), Ace (0.2% w/v), or Atc (100 or 200 ng ml1).

Plasmids pMPMK6 (39), p29SEN (40), pGMCS (41), pGMCZ (42), pLAM12 (43), pETDuet-1, pET15b and pRARE (Novagen), pBAD30 (44), and pTA100 (4) have been described. Primers used for plasmid construction are described in table S1. All the plasmids constructed in this work have been verified by sequencing. The pMPMK6 derivatives expressing the toxins, namely, pK6-MenT1, pK6-MenT2, pK6-MenT3, and pK6-MenT4, were constructed as follows: menT1, menT2, menT3, and menT4 were PCR-amplified from the M. tuberculosis H37Rv genome and cloned as Eco RI/Hind III fragments (menT1 and menT2) and Mfe I/Hind III fragments (menT3 and menT4) into Eco RI/Hind IIIdigested pMPMK6.

The p29SEN plasmid derivatives encoding the antitoxins, namely, p29SEN-MenA1, p29SEN-MenA2, p29SEN-MenA3, and p29SEN-MenA4, were constructed as follows: menA1, menA2, menA3, and menA4 were PCR-amplified from the M. tuberculosis H37Rv genome and cloned either as Eco RI/Hind III fragments (menA1, menA2, and menA3) or as Mfe I/Hind III fragments (menA4) into Eco RI/Hind IIIdigested p29SEN. For p29SEN-Rph, the rph gene was PCR-amplified from the E. coli DLT1900 genome and cloned as an Eco RI/Hind III fragment into Eco RI/Hind IIIdigested p29SEN.

To construct pGMC-MenT2, pGMC-MenT3, and pGMC-MenT4, menT2, menT3, and menT4 were PCR-amplified using pK6-MenT2, pK6-MenT3, and pK6-MenT4 templates, respectively, and cloned into pGMCS using In-Fusion HD Cloning Kits (Takara Bio). Plasmid pGMC-MenT1 and pGMC-MenT1-His were obtained following PCR amplification of menT1 and menT1-His using pK6-MenT1 as a template and homologous recombination in linearized pGMCS plasmid by In-Fusion HD Cloning Kits (Takara Bio). For pGMC-*MenA4-MenT4, the menA4-menT4 operon was PCR-amplified from the H37Rv genome and cloned into linearized pGMCS plasmid by In-Fusion HD Cloning Kits (Takara Bio).

To construct plasmids pLAM-MenA2, pLAM-MenA3, and pLAM-MenA4, menA2, menA3, and menA4 were PCR-amplified using p29SEN-MenA2, p29SEN-MenA3, and p29SEN-MenA4 as templates, respectively. These were cloned as Nde I/Eco RI fragments (menA2 and menA3) and Nde I/Mfe I fragments (menA4) into Nde I/Eco RIdigested pLAM12. Plasmid p29SEN-MenA1 was used to amplify menA1 and menA1-His, which were then cloned as Nde I/Eco RI fragments into Nde I/Eco RIdigested pLAM12 to produce pLAM-MenA1 and pLAM-MenA1-His, respectively.

The pET vector derivatives used in this work were constructed as follows. To construct plasmid pET-MenT3-His, menT3-His (with an added fragment encoding a Ser-Ser-Gly-His6 C-terminal tag) was PCR-amplified from pK6-MenT3 template and cloned as an Nde I/Mfe I fragment into Nde I/Mfe Idigested pETDuet-1. Plasmid pET-MenT3-His was used as a template to construct pET-MenT3-His(D80A) and pET-MenT3-His(K189A) by QuikChange site-directed mutagenesis (Agilent) using appropriate primers. Plasmid pET-MenA3-His, encoding an N-terminal His6-tagged MenA3 antitoxin, was constructed by PCR amplification of menA3-His using p29SEN-MenA3 as a template, Nde I/Hind III digestion, and cloning into Nde I/Hind IIIdigested pET15b plasmid. To construct plasmid pET-MenT3/MenA3-His, menA3-His was first PCR-amplified from p29SEN-MenA3 template and cloned as an Nco I/Hind III fragment into Nco I/Hind IIIdigested pETDuet-1. menT3 was then PCR-amplified from pK6-MenT3, digested with Nde I/Mfe I, and cloned into Nde I/Mfe Idigested pET-MenA3-His. To construct pET-MenT3-His/MenA3, menA3 was first PCR-amplified using p29SEN-MenA3 as a template and cloned as an Nco I/Hind III fragment into Nco I/Hind IIIdigested pET-MenT3-His. To generate pET-MenT1-His (expressing MenT1 with an N-terminal His6-Ser-Ser-Gly-tag), menT1-His was PCR-amplified from pK6-MenT1 and cloned as an Nde I/Mfe I fragment into Nde I/Mfe Idigested pETDuet-1. For pET-MenA1-His (expressing MenA1 with an N-terminal His6-Ser-Ser-Gly-tag), menA1-His was PCR-amplified from p29SEN-MenA1 template and cloned as an Nco I/Bam HI fragment into Nco I/Bam HIdigested pETDuet-1. For pET-MenT1/MenA1-His, menT1 was PCR-amplified from pK6-MenA1 and cloned as an Nde I/Mfe I fragment into Nde I/Mfe Idigested pET-MenA1-His. For pET-MenT1-His/MenA1, menA1 was PCR-amplified from p29SEN-MenA1 and cloned as an Nco I/Bam HI fragment into Nco I/Bam HIdigested pET-MenT1His.

To generate MenT3 and MenT4 expression constructs for crystallization and biochemistry, overlap PCRs were performed to fuse a sentrin protease (SENP)cleavable N-terminal His6-SUMO tag, amplified from the pBAT4 derivative (45), pSAT1-LIC (this study), to either menT3 or menT4, amplified from H37Rv genomic DNA. The resulting PCR products were cloned as either Kpn I/Hind III fragments into Kpn I/Hind IIIdigested pBAD30 (menT3), producing pTRB517, or as Xma I/Hind III fragments into Xma I/Hind IIIdigested pBAD30 (menT4) to generate pTRB544.

Plasmids pPF656 and pPF657 were constructed by amplifying menA3 and menT3 from H37Rv genomic DNA and cloning as Mfe I/Xma I fragments into Eco RI/Xma Idigested pTA100 and pBAD30, respectively. To express His6-SUMO-tagged MenT3(D80A), site-directed mutagenesis was carried out using pTRB517 as a template. Briefly, nonoverlapping inverse primers were used to amplify menT3(D80A), followed by incubation with a mix of T4 DNA ligase, T4 polynucleotide kinase, and DpnI at 37C to remove template and circularize amplified DNA. This reaction was then used to transform E. coli DH5, resulting in pTRB593. Similarly, this method was used to generate MenT3(D80A), MenT3(K189A), and MenT3(D211A) for functional testing, using pPF657 as a template, resulting in pTRB591, pTRB562, and pTRB592, respectively.

Plasmid pTRB491 was generated by amplifying menA3 from H37Rv genomic DNA and cloning into pSAT1-LIC via ligation-independent cloning (LIC). The pSAT1-LIC plasmid features a LIC site that fuses an N-terminal His6-SUMO tag to the target protein. To produce MenT3(K189A) protein, the mutated gene was amplified from pTRB562 and similarly cloned into pTRB550 via LIC, resulting in pTRB577. The pTRB550 plasmid features a His6-SUMO LIC site, originally amplified from pSAT1-LIC and cloned as an Eco RI/Hind III fragment into Eco RI/Hind IIIdigested pBAD30.

To produce plasmids for use in M. tuberculosis, menA3, menT3, or both genes were amplified by PCR using PrimeSTAR GXL DNA polymerase, with M. tuberculosis H37Rv genomic DNA as template and primer pairs clo-RBS1-MenA3-attB2/clo-MenA3-attB3, clo-RBS1-MenT3-attB2/clo-MenT3-attB3, clo-RBS4-MenT3-attB2/clo-MenT3-attB3, or clo-RBS1-MenA3-attB2/clo-MenT3-attB3, respectively (tables S1 and S2). RBS1 (AGGAAGACAGGCTGCCC) and RBS4 (ACGAAGACAGGCTGCCC), corresponding to a strong or weak Shine-Dalgarno sequence, respectively, were placed upstream from the ATG translation start of MenA3 or the GTG translation start of MenT3. Plasmids pGMCS-TetR-P1-RBS1-MenA3, pGMCS-TetR-P1-RBS1-MenA3-MenT3, pGMCS-TetR-P1-RBS1-MenT3, or pGMCS-TetR-P1-RBS4-MenT3 were constructed by multisite gateway recombination (18), using plasmid pDE43-MCS as the destination vector. These plasmids are integrative vectors (insertion at the attL5 mycobacteriophage insertion site in the glyV tRNA gene) and express MenA3, MenT3, or MenA3-MenT3 under the control of P1 (Pmyc1 tetO), a tetracycline-inducible promoter (table S2) (46).

Construction of MenT3 D80A, D211A, and K189A substitutions for use in M. tuberculosis was performed as follows: Plasmid pGMCS-TetR-P1-RBS4-MenT3 was amplified by PCR with PrimeSTAR GXL DNA polymerase and the oligonucleotides pairs InFus-MenT3D80A-right/InFus-MenT3D80A-left, InFus-MenT3D211A-right/InFus-MenT3D211A-left, or InFus-MenT3K189A-right/InFus-MenT3K189A-left (table S1). The amplified linear fragments were purified on agarose gels and circularized using the In-Fusion HD Cloning Kit (Takara), as recommended by the manufacturer. Plasmids used to transform Stellar recipient cells were verified by sequencing and introduced by electroporation into M. tuberculosis (menA3-menT3)::dif6/pGMCZ (see the next paragraph).

Mutant strains of M. tuberculosis H37Rv were constructed by allelic exchange using recombineering (43), as previously described (fig. S2) (47). Two ~0.5-kb DNA fragments flanking the menA3-menT3 operon were amplified by PCR using PrimeSTAR GXL DNA polymerase (Takara), M. tuberculosis H37Rv genomic DNA, and the primer pairs MenA3Am-For/MenA3Zc-Am-Rev or MenT3Zc-Av-For/MenT3Av-Rev, respectively (table S1). A three-fragment PCR fused these two fragments to a Zc-resistance cassette flanked by two dif6 variants of the M. tuberculosis dif site and the recombination substrate was recovered by agarose gel purifications. The recipient strain for recombineering was a derivative of M. tuberculosis H37Rv carrying two plasmids: pJV53H, an Hm-resistant pJV53-derived plasmid expressing recombineering enzymes (43), and the integrative plasmid pGMCS-P1-MenA3, constitutively expressing menA3 (table S2). This strain was grown in complete 7H9 medium supplemented with Hm until mid-log phase and expression of recombineering enzymes was induced by Ace (0.2%) overnight at 37C. After induction, electrotransformation was performed with 100 ng of the linear DNA fragment for allelic exchange. After a 48-hour incubation at 37C, mycobacteria were plated onto agar supplemented with Zc. Zc-resistant clones were restreaked on the same medium, grown in complete 7H9 without antibiotic, and verified to be carrying the expected allele replacement by PCR amplification of chromosomal DNA and subsequent DNA sequencing, using primers MenA3Am-For/MenT3Av-Rev (fig. S1C and table S1). Spontaneous loss of the Zc-resistance cassette by XerCD-dependent recombination and of the pJV53H plasmid was obtained by serial rounds of culture without antibiotics and phenotypic tests for ZcS and HmS. Plasmid pGMCS-P1-MenA3 was then removed by transformation with pGMCZ, a similar integrative vector but carrying resistance to Zc, resulting in the deleted strain M. tuberculosis (menA3-menT3)::dif6/pGMCZ.

E. coli MC4100 dnaKdnaJ::KmR tig:CmR double mutant (40) was partially digested with Sau3 AI restriction enzyme and DNA fragments of about 1.5 to 4 kb in size were purified, then ligated into linearized and dephosphorylated Bam HIdigested pMPM2 (ColE1 origin) plasmid (39), and used to transform E. coli DH10B. About 25,000 independent transformants were pooled to constitute the multicopy library. This library has previously been used as a tool to identify multicopy suppressors of chaperone mutants (48).

In vivo toxicity and antitoxicity assays by cognate or noncognate antitoxins in E. coli were performed as follows. E. coli DLT1900 were cotransformed with pMPMK6-vector, pK6-MenT1, -MenT2, -MenT3, or -MenT4 (toxins), and p29SEN-vector, p29SEN-MenA1, -MenA2, -MenA3, or -MenA4 (antitoxins). Transformants were re-seeded from overnight cultures and grown at 37C to mid-log phase in LB supplemented with Km and Ap, and then serially diluted and spotted on LB-agar plates supplemented with Km and Ap, with or without l-ara (0.1%) and/or IPTG (200 M). Plates were incubated at 37C overnight and then imaged and counted. MenT3 substitutions were tested for toxicity in E. coli DH5 carrying pBAD30-vector, -MenT3 WT (pPF657), -MenT3(D80A) (pTRB591), -MenT3(K189A) (pTRB562), or -MenT3(D211A) (pTRB592). Strains were grown to mid-log phase, then serially diluted, and spotted onto M9M-agar plates supplemented with Ap, with or without l-ara (0.1%). After a 2-day incubation at 37C, plates were imaged and counted.

In vivo toxicity and rescue assays by cognate or noncognate antitoxins in M. smegmatis were performed as follows. Cultures of mc2 155 strain grown in LB at 37C were cotransformed with the integrative pGMC-vector, -MenT1, -MenT2, -MenT3, or -MenT4 (toxins), and with pLAM12-vector, pLAM-MenA1, -MenA2, -MenA3, or -MenA4 (antitoxins). Samples were selected on LB-agar plates supplemented with Km and Sm for 3 days at 37C, in the presence or absence of Atc (100 ng ml1) and Ace (0.2%) for toxin and antitoxin expression, respectively. A similar procedure was applied for pGMC-*MenA4-MenT4 carrying the menA4-menT4 operon, with the exception that no cotransformation with pLAM12 derivatives or selection on Km was needed.

Exponentially growing cultures [OD600 (optical density at 600 nm) between 0.05 and 0.2] of M. smegmatis strain mc2 155 containing plasmid pGMCS-TetR-P1-RBS1-MenT3 were divided in two: Half was left in complete 7H9 growth medium with Sm (uninduced cultures), while the other half was additionally treated with Atc (200 ng ml1) to induce expression from the P1 promoter. For labeling with LIVE/DEAD BacLight (Molecular Probes) dyes, cells were harvested 8 hours after Atc induction. Cells were centrifuged, resuspended in phosphate-buffered saline buffer, and stained as recommended by the manufacturer. Labeled cells were analyzed by fluorescence-activated cell sorting using a BD LSRFortessa X20 flow cytometer. Flow cytometry data analysis was performed using FlowJo software.

M. tuberculosis strains H37Rv or H37Rv (menA3-menT3)::dif6/pGMCZ were transformed by electroporation with 100 ng of plasmids pGMCS-TetR-P1-RBS1-MenA3, pGMCS-TetR-P1-RBS1-MenA3-MenT3, pGMCS-TetR-P1-RBS1-MenT3, pGMCS-TetR-P1-RBS4-MenT3, pGMCS-TetR-P1-RBS4-MenT3(D80A), pGMCS-TetR-P1-RBS4-MenT3(K189A), or pGMCS-TetR-P1-RBS4-MenT3(D211A). After 3 days of phenotypic expression in 7H9 ADC Tween at 37C, the transformation mix was divided into two halves. One half was plated on 7H11 OADC with Sm; the other half was plated on 7H11 OADC Sm supplemented with Atc (200 ng ml1). Plates were imaged after 20 days of incubation at 37C.

To perform in vivo copurification assays, E. coli BL21 slyD was transformed with (i) pET-MenT3-His, pET-MenA3-His, pET-MenT3/MenA3-His, or pET-MenT3-His/MenA3, or with (ii) pET-MenT1-His, pET-MenA1-His, pET-MenT1/MenA1-His, or pET-MenT1-His/MenA1, and selected on LB-agar plates supplemented with Ap and glu (20%). Transformants were grown at 37C to an OD600 of approximately 0.4 and then protein expression was induced overnight at 20C with 1 mM IPTG. Cell lysis and affinity purification of the protein complexes were performed as described below for MenT3-His purification. Elution fractions were separated on SDS-PAGE and proteins revealed using InstantBlue Protein Stain (Expedeon, catalog no. ISB1L).

To purify MenT3 for biochemistry, BL21 (DE3) slyD transformed with pET-MenT3-His, pET-MenT3-His(D80A), or pET-MenT3-His(K189A) was grown to an OD600 of approximately 0.4 at 37C. IPTG (1 mM) was then added, and the culture was incubated overnight at 20C. Under such conditions, MenT3 expression in E. coli was better tolerated and led to a reasonable amount of soluble MenT3 that could be collected for purification. Cultures were centrifuged at 5000g for 10 min at 4C, pellets were resuspended in Lysis buffer [300 mM NaCl, 50 mM tris (pH 7.5), and protease inhibitor tablet (Roche); 20 ml of buffer per 1 liter of cell culture] and incubated for 30 min on ice. Lysis was performed using the One Shot cell disrupter at 1.5 kbar (One Shot model, Constant Systems Ltd.). Lysates were centrifuged for 30 min at 30,000g in 4C, and the resulting supernatants were gently mixed at 4C for 30 min with Ninitrilotriacetic acid agarose beads (Qiagen, catalog no. 30230) preequilibrated with buffer PD [300 mM NaCl and 50 mM tris (pH 7.5)], using a 10-ml poly-prep column (Bio-Rad, catalog no. 7311550). Columns were stabilized for 10 min at 4C and washed three times with 10 ml of buffer PD plus 25 mM imidazole, and proteins were then eluted with buffer PD containing 250 mM imidazole. Elutions (500 l) were collected and PD MiniTrap G-25 columns (GE Healthcare, catalog no. 16924748) were used to exchange buffer with buffer PD supplemented with 10% glycerol. Proteins were concentrated using Vivaspin 6 columns with a 5000-Da cutoff (Sartorius, catalog no. 184501257). Proteins were stored at 80C until further use.

For additional MenT3 and MenT3(K189A) expression, either for crystallization or biochemistry, E. coli ER2566 pRARE pPF656 was transformed with either pTRB517 or pTRB577, respectively. For MenT3(D80A) expression, E. coli ER2566 pRARE was transformed with pTRB593. MenT4 was expressed in E. coli BL21 (DE3) transformed with pTRB544. MenA3 was expressed in E. coli ER2566 transformed with pTRB491. For these expressions, the same procedure was followed: Overnight cultures were re-seeded 1:100 into 2-liter flasks containing 1-liter 2 YT. Cells were grown at 175 rpm in 37C until an OD600 of 0.3 was reached and then at 22C until OD600 0.5, whereupon expression was induced by the addition of l-ara (0.1%) for toxins and IPTG (1 mM) for antitoxins. Cells were left to grow overnight at 16C, shaking at 175 rpm.

For selenomethionine incorporation, starter cultures of ER2566 pRARE pPF656 pTRB517 were grown overnight in LB at 37C with 200 rpm shaking. Cells were pelleted, washed, and resuspended in M9M, and then sub-cultured into 500 ml of M9M in 2-liter baffled flasks to a starting OD600 of 0.075. Cells were grown at 37C with 175 rpm shaking until an OD600 of 0.6, whereupon cells were centrifuged at 4200g and resuspended in fresh M9M. This sample was divided between separate 2-liter baffled flasks containing new M9M and shaken at 175 rpm for a further 1 hour at 37C. Once an OD600 of 0.7 was reached, 12 ml of nutrient mix [l-lysine hydrate (4 mg ml1), l-threonine (4 mg ml1), l-phenylalanine (4 mg ml1), l-leucine (2 mg ml1), l-isoleucine (2 mg ml1), l-valine (2 mg ml1), and 4 mM CaCl2] was added to each flask to promote feedback inhibition of methionine synthesis, followed by 250 SelenoMethionine Solution (Molecular Dimensions) to a final concentration of 40 g ml1, and cells were left to incubate for 1 hour at 20C. Last, toxin and antitoxin expression were induced by the addition of l-ara (0.1%) and IPTG (1 mM), and samples were left to grow overnight at 175 rpm in 16C.

All five proteins were purified in the same manner. Bacteria were harvested by centrifugation at 4200g, and the pellets were resuspended in buffer A500 [20 mM tris-HCl (pH 7.9), 500 mM NaCl, 5 mM imidazole, and 10% glycerol]. Cells were lysed by sonication at 40 kpsi and then centrifuged (45,000g, 4C). The clarified lysate was next passed over a HisTrap HP column (GE Healthcare), washed for 10 column volumes with A500, followed by 10 column volumes of buffer A100 [20 mM tris-HCl (pH 7.9), 100 mM NaCl, 5 mM imidazole, and 10% glycerol], and then eluted directly onto a HiTrap Q HP column (GE Healthcare) with buffer B100 [20 mM tris-HCl (pH 7.9), 100 mM NaCl, 250 mM imidazole, and 10% glycerol]. The Q HP column was transferred to an kta Pure (GE Healthcare), washed with 3 column volumes of A100, and then proteins were eluted using a gradient from 100% A100 to 100% buffer C1000 [20 mM tris-HCl (pH 7.9), 1000 mM NaCl, and 10% glycerol]. Fractions containing the protein peak were analyzed by SDS-PAGE, pooled, and incubated overnight at 4C with hSENP2 SUMO protease to cleave the His6-SUMO tag from the target protein. The following day, the samples were passed through a second HisTrap HP column and the flow-through fractions containing untagged target protein were collected. These samples were concentrated and run over a HiPrep 16/60 Sephacryl S-200 size exclusion column (GE Healthcare) in buffer S [50 mM tris-HCl (pH 7.9), 500 mM KCl, and 10% glycerol]. Peak fractions were analyzed by SDS-PAGE, pooled, and concentrated. Optimal fractions were separated and either flash-frozen in liquid N2 for storage at 80C or dialyzed overnight at 4C into buffer X [20 mM tris-HCl (pH 7.9), 150 mM NaCl, and 2.5 mM dithiothreitol (DTT)] for crystallographic studies. Crystallization samples were quantified and stored on ice and then either used immediately or flash-frozen in liquid N2 for storage at 80C. Frozen crystallization samples still formed usable crystals 15 months after storage.

Native and selenomethionine-derivatized MenT3 were concentrated to 12 mg ml1 and MenT4 was concentrated to 6 mg ml1, all in buffer X (see above). Initial crystallization screens were performed using a Mosquito Xtal3 robot (TTP Labtech) to set 200:100 nl and 100:100 nl protein:condition sitting drops. After initial screening and optimization, both MenT3 protein samples formed thick, six-sided needles in condition G5 [0.2 M calcium acetate hydrate, 0.1 M tris (pH 8.5), and 25% w/v polyethylene glycol 2000 monomethyl ether] of Clear Strategy II HT-96 (Molecular Dimensions). MenT4 formed thin, six-sided needles in the same condition as MenT3. To harvest, 20 l of condition reservoir was added to 20 l of cryo buffer [25 mM tris-HCl (pH 7.9), 187.5 mM NaCl, 3.125 mM DTT, and 80% glycerol] and mixed quickly by vortexing; an equal volume of this mixture was then added to the drop. After addition of cryo buffer, crystals were immediately extracted using a nylon loop and flash-frozen in liquid N2.

Diffraction data were collected at Diamond Light Source on beamlines I04 (MenT3 native), I03 (MenT3 selenomethionine-derivatized), and I24 (MenT4 native) (Table 1). Single 360 datasets were collected for native MenT3 and MenT4. Two 360 datasets from MenT3 selenomethionine-derivatized crystals measured at the selenium peak (0.9793 ) were merged using iSpyB (Diamond Light Source). Additional MenT3 selenomethionine-derivatized datasets were collected at selenium high remote (0.9641 ) and inflection (0.9795 ) wavelengths. Diffraction data were processed with XDS (49), and then AIMLESS from CCP4 (50) was used to corroborate the space groups (Table 1). The crystal structure of MenT3 was solved by MAD by providing the SHELX suite in CCP4 with the native and three anomalous MenT3 datasets. The solved starting model for MenT3 was built in REFMAC within CCP4. The crystal structure of MenT4 was solved ab initio using ARCIMBOLDO (51). Both models were then iteratively refined and built using PHENIX (52) and COOT (53), respectively. The quality of the final model was assessed using COOT and the wwPDB validation server. Structural figures were generated using PyMOL (Schrdinger). Comparison against models within the Protein Data Bank (PDB) was performed using DALI (25).

The following genetic procedure was developed and applied to select for E. coli genes that confer resistance to the MenT3 toxin. E. coli strain DLT1900 was first transformed with pK6-MenT3 (KmR) plasmid and transformants were selected at 37C on LB-agar plates supplemented with Km and glu (0.2%) to repress toxin expression from the araBAD promoter of pK6-MenT3. DLT1900 containing pK6-MenT3 was then grown in LB supplemented with Km and glu, transformed with the pMPMA2-based multicopy library of E. coli genes, and plated on selective LB-agar supplemented with Km, Ap, and l-ara (0.1%) to induce toxin expression. Plates were incubated for 24 hours at 37C. A control aliquot of transformants plated on nonselective plates (no l-ara) indicated that the number of transformants tested during the selection procedure was approximately 60,000. Note that under such conditions, E. coli DLT1900 pK6-MenT3 transformed with pMPMA2 empty vector did not produce any colonies on selective plates. We identified 72 toxin-resistant colonies that grew on selective plates after 24 hours, although they were smaller and translucent, indicating that growth inhibition by the toxin is not fully blocked by the suppressors identified. Of the 72 toxin-resistant colonies identified, only 41 were able to grow in culture. Plasmids were extracted from the 41 cultures, used to re-transform DLT1900 pK6-MenT3, and plated as above, to validate growth rescue in the presence of MenT3. Of 41 clones, 18 suppressors passed the second round of selection and were sequenced using the pMPMA2-For and -Rev primers (table S1).

Assays were performed as previously described (54). Briefly, template DNAs of DHFR (P0ABQ4), WaaF-Strep (P37692), and GatZ-Strep (P0C8J8) were used for in vitro transcription/translation coupled assays (PURExpress, New England Biolabs). These were performed according to the manufacturers instructions, in the presence or absence of the toxin. Following protein synthesis reactions of 2 hours at 37C, samples were separated on SDS-PAGE and visualized by InstantBlue staining (DHFR) or Western blots using anti-Strep tag antibodies (WaaF-Strep and GatZ-Strep).

Prevention of E. coli tRNATrp aminoacylation by MenT3 was monitored using a combination of two previously published methods (29, 55). E. coli BL21 (DE3) transformed with pETDuet or pET-MenT3 was grown at 37C to OD600 0.1 in M9M, whereupon expression of MenT3 was induced with 1 mM IPTG until an OD600 of about 0.4. The bacterial culture (25 ml) was then kept on ice and centrifuged for 10 min at 5000g in 4C. The pellet was resuspended in 0.5 ml of cold 0.3 M sodium acetate (pH 4.5) and 10 mM EDTA and transferred to a precooled 1.5-ml microcentrifuge tube, and 0.5 ml of phenol (equilibrated with the same buffer) was then added. After gentle pipetting, the sample was transferred into phase-lock tubes with an additional 400 l of cold chloroform. After 30 seconds shaking, the sample was first incubated on ice for 15 min and then centrifuged for 20 min at 20,000g in 4C. The aqueous phase was then transferred to a new cold 1.5-ml tube. Five hundred microliters of cold isopropanol was added and immediately mixed. RNA was precipitated for 1 hour at 20C, before the sample was centrifuged for 30 min at 20,000g in 4C (55). The supernatant was discarded and 1 ml of cold 75% ethanol was carefully added without disturbing the RNA pellet. After further centrifugation for 10 min at 20,000g in 4C, the supernatant was removed and the pellet was air-dried until no ethanol remained. The pellet was then resuspended by vigorously mixing in 20 l of cold 10 mM sodium acetate (pH 4.5) and 1 mM EDTA. Samples were stored at 80C. Samples were separated on a denaturing urea acrylamide gel for 3 hours at 100 V in 4C, as previously described (29). Northern blot and visualization with a radiolabeled DNA probe against tRNATrp was performed as previously described (56). Note that to distinguish the band of aminoacylated tRNA from its deacylated counterpart on the Northern blot, a chemically deacylated aliquot of RNA sample prepared from strain containing the empty vector was subjected to alkaline treatment. In this case, 46 l of tris-HCl (pH 9.0) was added to a 4-l aliquot of the RNA sample and incubated for 2 hours at 37C. Fifteen microliters of 0.3 M sodium acetate at pH 4.5 was added and followed by 125 l of 96% ethanol. RNA was precipitated at 20C for 1 hour, resuspended, and separated as described above.

For in vitro tRNA charging, in vitro transcription/translation assays were performed as above, using gatZ as DNA template. After a 2-hour reaction at 37C with or without MenT3 toxin (10 M), tRNA extraction, separation, and visualization were performed as described for the in vivo samples.

Labeled tRNAs were prepared by in vitro transcription of PCR templates containing an integrated T7 RNA polymerase promoter sequence. The template for E. coli tRNATrp was made by PCR amplification of chromosomal DNA from strain MG1655 with the primers CC2556 and CC2557 (CC2591 for tRNATrp without CCA) (table S1). The oligos for M. tuberculosis tRNAs are given in table S1. The T7 RNA polymerase in vitro transcription reactions were performed in 25-l total volume, with a 5-l nucleotide mix of 2.5 mM ATP, 2.5 mM CTP, 2.5 mM GTP, and 60 M UTP and 2 to 4 l of 10 mCi ml1 of radiolabeled UTP [-P32]. Template (0.1 to 0.2 g) was used per reaction with 1.5 l of rRNasin (40 U ml1) (Promega), 5 l of 5 optimized transcription buffer (Promega), 2 l of T7 RNA polymerase (20 U ml1), and 2.5 l of 100 mM DTT. Template DNA was removed by the addition of 2 l of RQ DNase (1 U ml1) (Promega). Unincorporated nucleotides were removed by G50 spin columns (GE Healthcare) according to the manufacturers instructions, in a final volume of 30 l. For E. coli tRNATrp, the transcript reaction was gel-purified on a denaturing 5% acrylamide gel and eluted in 0.3 M sodium acetate for 4 hours overnight at 4C. The supernatant was removed, ethanol-precipitated, and resuspended in 20 to 30 l of nuclease-free H2O.

MenT3 NTase activity was assayed in 10-l reaction volumes containing 50 mM tris-HCl (pH 9.5), 10 mM MgCl2, and 2.5 mM rNTPs and incubated for 20 min at 37C. Fresh, uniformly labeled tRNA (0.5 l) was used per assay, with different dilutions of the protein (1, 0.1, 0.01, and 0.001 mg ml1) in 50 mM tris-HCl (pH 7.8), 300 mM NaCl, and 10% glycerol. The 10-l reactions were mixed directly with 10 l of RNA loading dye (95% formamide, 1 mM EDTA, 0.025% SDS, xylene cyanol, and bromophenol blue), denatured at 90C, and applied to 5% polyacrylamide-urea gels. The gel was vacuum-dried at 80C and exposed to a PhosphorImager screen.

The effect of MenA3 antitoxin was assayed using in vitro-transcribed tRNASer2 as a substrate. For the coincubation assay, MenT3 (5 M) and increasing molar ratios of MenA3 were incubated with tRNASer2 and 2.5 mM CTP in 10-l reaction volumes containing 50 mM tris-HCl (pH 9.5) and 10 mM MgCl2 for 20 min at 37C. For the postincubation assay, the reactions were first incubated for 20 min at 37C with MenT3 alone in 7-l reaction volumes, then 3 l containing different concentrations of MenA3 were added, and the reactions were incubated for a further 20 min at 37C.

The tRNA screening was performed using 0.5 l of uniformly labeled M. tuberculosis tRNAs, all containing the CCA motif. The activity was tested in 50 mM tris-HCl (pH 9.5), 10 mM MgCl2, and 2.5 mM rCTP in 10-l reaction volumes and incubated for 20 min at 37C. The transcripts were incubated with 1 l of MenT3 (0.1 mg ml1), or with nuclease-free water as a control. The reaction was stopped with 10 l of RNA loading dye (95% formamide, 1 mM EDTA, 0.025% SDS, xylene cyanol, and bromophenol blue), denatured at 90C, and applied to 5% polyacrylamide-urea gels. The gel was vacuum-dried at 80C and exposed to a PhosphorImager screen.

Acknowledgments: We thank D.-J. Bigot for plasmid constructs, and P. Bordes, M.-P. Castani-Cornet, L. Falquet, L. Poljak, L. Hadjeras, and H. Akarsu for valuable advice. We also thank K. Semeijn and R. Dy for initial plasmid construction and testing, and E. Naser (Genotoul TRI-IPBS imaging facility) for help with flow cytometry analysis. Funding: This work was supported by a scholarship from the China Scholarship Council (CSC) as part of a joint international PhD program with Toulouse University Paul Sabatier (Y.C.); Springboard Award (SBF0021104) from the Academy of Medical Sciences (B.U. and T.R.B.); University of Otago Research Grant (P.C.F.), the School of Biomedical Sciences Bequest Fund, and University of Otago (P.C.F.); CNRS (UPR 9073), Universit Paris VII-Denis Diderot, the Agence Nationale de la Recherche (ARNr-QC), and the Labex (Dynamo) program (A.T. and C.C.); European Commission (contracts NEWTBVAC n241745 and TBVAC2020 n643381), Centre National de la Recherche Scientifique, Universit Paul Sabatier, Agence Nationale de la Recherche (ANR-13-BSV8-0010-01), and Fondation pour la Recherche Mdicale (DEQ20160334902) (C.G. and O.N.); and grant SNF CRSII3_160703 (P.G.). Author contributions: Conceptualization, all authors. Investigation, Y.C., B.U., C.G., A.T., and M. M. Writing, all authors. Funding acquisition, P.C.F., C.C., O.N., P.G., and T.R.B. Supervision, C.C., O.N., P.G., and T.R.B. Competing interests: The authors declare that they have no competing interests. Data and materials availability: The crystal structures of MenT3 and MenT4 have been deposited in the Protein Data Bank under accession numbers 6Y5U and 6Y56, respectively. All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials. Additional data related to this paper may be requested from the authors.

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A nucleotidyltransferase toxin inhibits growth of Mycobacterium tuberculosis through inactivation of tRNA acceptor stems - Science Advances

Solve Puzzles for Science | Foldit

Posted on July 19, 2020 by Prof Baldwin

(This post was originally sent out on July 3 to our mailing list. You can sign up for the mailing list here to receive weekly updates about Foldit, including tips and tricks and see the top-scoring solutions to the week's puzzles. Don't forget to join our Discord as well to stay in the chat even when you're not folding!)

Hey folders!

Dev Josh here with your weekly Foldit update.

This week we saw the introduction of the Reaction Design tool. The devs are working hard on polishing it up and making it more usable! As always, thanks for your feedback and bug reports. You can submit more feedback here.

In this puzzle, I accidentally evo'ed on a broken developer build and got the top score. Whoops, sorry about that!Here are some of the solutions at the top of the leaderboards. [A note from our scientists: the top of the leaderboards doesn't always mean the most scientifically useful. These highlights are not scientific feedback and are not officially endorsed as scientifically valid designs by the Foldit team.]

Join the mailing list to see what others are folding!

This week's recipe is an oldie but a goodie from drjr. The recipe is called Reset, and it does what it says on the tin: reset to the best score, unfreeze the protein, remove all your bands, and set the CI to 1. A simple recipe, but a handy quality of life tool for when you just need to backtrack a little.

Quick shoutout to argyrw for always being a friendly voice in chat! Say hi to her in global or veteran chat.

Beginner: Are you still using Pull to draft your protein in the early game? Try making cutpoints and moving pieces around with the Move tool, it's so much easier! Don't forget to disable cutpoint bands in the Behavior tab, or they'll all come together again when you wiggle.

Intermediate: It can be really tempting mid-game to just switch to running recipes. But give some time to carefully inspect every acceptor and donor (the red and blue dots) to see what hydrogen bonds you can form, and manually mutate as needed. Not only will this lower your BUNS, but it'll help form a strong hbond network. The scientists love this, and your rank will too!

Expert: If you haven't already, read bkoep's blog on binder design metrics. DDG, SASA, and SC are going to become really important soon since we're looking to add objectives for them. So understanding and practicing these principles now can help you get a headstart on the competition! Use the protein design sandbox to try out some ideas.

Have a tip to share or a recipe to recommend? Reply with your suggestions or make a wiki page for your ideas! Reaction Design doesn't have a page yet, so if you understand this tool, help out your community by writing about it! (Since writing this post, LociOiling has graciously created the page for Reaction Design puzzles.)

Until next time, happy folding!

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Solve Puzzles for Science | Foldit

Proteasomal degradation of the intrinsically disordered protein tau at single-residue resolution – Science Advances

Posted on July 22, 2020 by Prof Baldwin

INTRODUCTION

Intrinsically disordered proteins (IDPs) are abundant in the human proteome and are implicated as therapeutic targets in major human diseases (1). IDPs have amino acid sequences of low complexity and lack an ordered three-dimensional (3D) structure (1). This allows IDPs to dynamically bind to diverse interaction partners and thus influence many biological processes (1). The activity of IDPs is regulated by posttranslational modifications including phosphorylation and truncation (1, 2). Because of their structural instability, IDPs are particularly sensitive to proteolytic degradation (35).

Aggregation of IDPs into insoluble deposits is the hallmark of neurodegenerative diseases (3). Aggregates of the IDP tau are linked to the progression of Alzheimers disease (AD) and are found in other age-related disorders termed tauopathies (6). The longest tau isoform in the human central nervous system comprises 441 residues (7). The N-terminal ~150 residues of tau project away from the microtubule surface and are thus termed projection domain (8). The central part of the tau sequence is formed by pseudo-repeats, which bind to microtubules (8, 9) and are essential for pathogenic aggregation and folding into cross- structure in tau amyloid fibrils (10, 11). Phosphorylated tau accumulates during the development of AD (6, 12).

The 20S proteasome forms the proteolytic core particle of the 26S proteasome holoenzyme (13). In contrast to the proteasomal degradation of most cellular proteins, IDPs can be degraded by the 20S proteasome in an ubiquitin- and adenosine triphosphate (ATP)independent process without the necessity of the 19S regulatory particle (35). Soluble tau is degraded by the 20S proteasome (14, 15), while phosphorylation and aggregation of tau inhibit its turnover by the proteasome (2, 1517). Decline of proteasomal activity and accumulation of tau have been linked to neurodegeneration (2, 18, 19): Decreased proteasomal activity results in tau accumulation, neurotoxicity, and cognitive dysfunction in cell and animal models of neurodegenerative disorders. Pharmacological activation of the 20S proteasome, direct administration of proteasome, or targeted proteasomal degradation of tau is therefore the focus of current therapeutic strategies targeting tauopathies (20, 21).

Here, we study the degradation of the IDP tau by the 20S proteasome through a residue-specific and quantitative approach that combines nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS). We provide detailed insights into the identity and properties of the proteasomal degradation products of tau, the single-residue degradation kinetics, and their specific regulation by phosphorylation in different tau domains/by different kinases.

The 20S proteasome (20S) is a barrel-shaped complex comprised by two stacked heptameric -rings that are sandwiched by two heptameric -rings (Fig. 1A) (13). The proteolytic sites, which hydrolyze the peptide bonds of substrates, are located in the subunits. IDPs thus traverse through the -rings to reach the active sites in the interior of the 20S proteasome (Fig. 1B). To study degradation of the IDP tau, we recombinantly prepared 20S from Thermoplasma acidophilum, which contains only one type of subunit and one type of subunit. This 20S particle thus has 14 identical chymotrypsin-like active sites, which are positioned at equal distances around the -rings (Fig. 1B). Electron microscopy (EM) showed intact barrel-shaped 20S complexes (Fig. 1C). The 441-residue isoform of tau (hTau40; also termed 2N4R tau; Fig. 1D) was also expressed in Escherichia coli.

(A) Schematic representation depicting the architecture of the 20S proteasome (20S) comprising 28 subunits arranged in four heptameric rings (7777). (B) The proteolytic active sites of the 20S proteasome are located in its interior, thus enabling degradation of hTau40 into short peptides once it has entered the 20S core. (C) Negatively stained EM micrograph of the 20S proteasome. (D) Domain organization of full-length hTau40 composed of 441 amino acids (aa) (UniProt ID 10636-8). N1 and N2 are the two inserts in the N-terminal projection domain, P1 and P2 correspond to the two proline-rich regions, and R1 to R are five pseudo-repeats. (E) (Left) SDS-PAGE gel showing hTau40 (1) and the degradation of (2 to 5) hTau40 by the 20S proteasome over time. The samples were incubated at 37C for 30 min (2), 90 min (3), and 150 min (4) and were subsequently put at 4C for additional 48 hours (5). After 48 hours, two well-resolved bands at ~28 and ~30 kDa (red lined box) appeared. (Right) The amino acid sequences of the upper (~30 kDa) and lower bands were identified with in-gel analysis and marked in red. Both intermediates correspond to the N-terminal domain of hTau40.

Recombinant hTau40 was incubated with the 20S proteasome, and degradation was followed by SDSpolyacrylamide gel electrophoresis (PAGE) (Fig. 1E, left). After ~150 min, a clear decrease in the intensity of the hTau40 band at ~60 kDa was apparent (lane 4 in Fig. 1E). In addition, two bands running at ~30 and 28 kDa appeared. Analysis after 48 hours of incubation confirmed the presence of the two new bands, while the full-length protein was degraded to near completion (lane 5 in Fig. 1E).

The two intermediate bands were precisely and independently excised from the gel, subjected to in-gel digestion using trypsin, which specifically cleaves at the peptide bond C terminus of lysine or arginine residues, and analyzed using liquid chromatography (LC)MS/MS. For both bands, the MS analysis confidently identified several peptides from the N-terminal domain (Fig. 1E, right). No peptides were identified in the region from 127 to 210, which contains multiple lysine and arginine residues such that trypsin digestion will produce too short sequences to be analyzed by LC-MS/MS. In the case of the upper band, the additional peptide RTPSLPTPPTR (residues 211 to 221 of hTau40) was identified (Fig. 1E, right).

We also separated the two long fragments using LC and detected their molecular weight by intact MS, giving masses of 25.782 and 22.257 kDa (fig. S1). Manual matching of the determined masses to N-terminal sequences of hTau40 showed that the long fragment contains residues 1 to 251, and the short one has residues 1 to 218. Previous studies showed that the upper band is recognized by the antibody Tau-5 (14), which binds to residues in the region from 218 to 225 (22).

To gain insight into the structural properties of the long tau fragments generated during 20S degradation, we recombinantly prepared a tau protein comprising residues 1 to 239 of hTau40. Tau(1239) contains the full epitope for the Tau-5 antibody (residues 218 to 225) and has a length in between the two long N-terminal fragments. Particle size analysis by dynamic light scattering (fig. S2A) showed that both hTau40 and Tau(1239) are more compact than the average size values for IDPs (fig. S2B) (23). hTau40, with an experimental size of 5.2 nm and an expected size for its number of residues of 5.5 nm, is 5% more compact than expected, while Tau(1239) is 18% more compact than expected with 3.3 and 4 nm as experimental and expected sizes, respectively. Despite the stronger compaction of Tau(1239), both proteins present the typical pattern of random coil conformation in circular dichroism spectra (fig. S2C).

Figure S2D shows the 1H-15N heteronuclear single-quantum coherence (HSQC) spectrum of 15N-labeled Tau(1239). The backbone cross peaks are located in the region between 7.6 and 8.6 parts per million (ppm), which is characteristic for IDPs. When compared to hTau40, chemical shift perturbation was restricted to the most C-terminal residues of Tau(1239) (fig. S2E), i.e., residues where Tau(1239), but not hTau40, ends. Analysis of the secondary structure propensities using the chemical shifts of carbonyl and C (fig. S2F) furthermore showed that both hTau40 and Tau(1239) are mainly random coil, in agreement with circular dichroism spectra (fig. S2C).

In addition, the single-residue analysis showed that Tau(1239) contains elements of transient secondary structure: residues 116 to 119 with a tendency for helical structure and two short stretches (residues 150 to 152 and 225 to 230) with extended conformation. The same transiently structured regions were detected in hTau40 (fig. S2F). TALOS+ also identified four regions with preference for extended conformation (residues 275 to 279, 306 to 310, 337 to 339, and 392 to 399) and one with helical content (residues 431 to 437) in hTau40, in agreement with previous analysis (24). The presence of extended conformations in the repeat region has previously been suggested to be responsible for the observation that the repeat region of tau, which is not present in Tau(1239), is less compact when compared to a pure random coil conformation. The combined data thus point to a compaction of the N-terminal cleavage intermediates of hTau40 (fig. S2, A and B).

To identify short tau peptides generated by 20S, we analyzed the released peptides in the supernatant after incubation of hTau40 and 20S using MS. The largest fraction of identified peptides was from hTau40s pseudo-repeat region (Fig. 2, A and B). In addition, peptides from the C-terminal domain and the residue regions 2 to 13, 84 to 103, and 167 to 192 were detected but with very low responses in MS in the supernatant (Fig. 2C). The tau peptides and their cleavage sites identified by MS are generally in good agreement with the proteasomal cleavage sites predicted by NetChop 3.1 (Fig. 2B) (25).

(A) Domain organization of hTau40. (B) Amino acid sequence of hTau40 depicting in color [color code as in (A)] the 20S-generated peptides, which were identified by LC-MS/MS. The peptides underlined with black dots were also present in the in-solution sample but with low intensities. The slashes depict all identified cleavage sites. Cleavage sites predicted by the NetChop server are marked by arrows. The bar on top of the VQIVYK sequence indicates the ability of this sequence to form amyloid-like filaments (26). (C) (Left) Histogram representation of the peak area of 20S-generated tau peptides [color code as in (A)] identified by in-solution analysis. Insert depicting the sequences of the identified peptides and the cleavage sites (marked with slashes). (Right) Histogram representing the most intense peptides in the R3 region. A.U., arbitrary units. (D) ThT fluorescence during incubation of the peptide 309VYKPVDL315. The peptide (50, 100, and 150 M) was incubated with heparin (peptide:heparin molar ratio of 4:1) in triplicates.

The peptide with the highest ion peak area was 309VYKPVDL315 (Fig. 2C, right). It partially overlaps with the hexapeptide sequence 306VQIVYK311 at the beginning of pseudo-repeat R3 (Fig. 2B).

The 306VQIVYK311 sequence is the most hydrophobic residue stretch of tau, is a major driving force for pathogenic tau aggregation, and can form amyloid-like filaments in isolation (26). We therefore tested whether the 20S-generated tau peptide 309VYKPVDL315 can aggregate into amyloid fibrils. To this end, the 309VYKPVDL315 peptide was incubated with heparin at a molar ratio of 4:1.

Figure 2D shows the results from thioflavin-T (ThT) fluorescence measurements of 309VYKPVDL315/heparin samples at three different peptide concentrations during incubation at 37C for 6 days. For all of the samples, the background-corrected ThT intensity was very low and did not increase during incubation (Fig. 2D). No increase in ThT intensity was detected even when the peptide was incubated for 6 days in the absence of heparin (fig. S3). Because ThT fluorescence intensity increases upon binding to amyloid fibrils, the data show that the 20S-generated peptide 309VYKPVDL315 is not able/has a very low propensity to form amyloid fibrils.

To gain insight into the kinetics of degradation of tau by the 20S proteasome and define its residue specificity, we used NMR spectroscopy. Figure 1A displays the 2D 1H-15N HSQC spectrum of 15N-labeled hTau40. The NMR spectrum was recorded at 5C to attenuate the exchange of amide protons with solvent and thus exchange-induced NMR signal broadening. Comparison of the HSQC spectrum of hTau40 alone with the spectra recorded after 30 min and 66 hours (red) in the presence of 20S (hTau40:20S molar ratio of 4:1) showed that after 30 min, the spectrum of hTau40 was essentially unchanged (fig. S4), but after 66 hours, additional sharp cross peaks were present. Four of the newly appearing cross peaks overlapped with signals observed in a natural abundance 1H-15N HSQC spectrum of the 309VYKPVDL315 peptide, i.e., the peptide with the highest ion peak area in MS (fig. S5). The degradation-associated cross peaks were not observed for a separate sample, which additionally contained the proteasome inhibitor oprozomib (Fig. 3A, right spectrum).

(A) Superposition of 2D 1H-15N HSQC spectra of hTau40 at 5C in the presence of the 20S proteasome after 3 hours (black) and 66 hours (red) in the absence (left) and presence (right) of the proteasome inhibitor oprozomib. (B) (Top) Evolution of relative peak intensities, I(t)/I0, in 2D 1H-15N HSQC spectra of hTau40 in the presence of 20S with increasing incubation time at 5C. I0 is the cross-peak intensity observed in the first HSQC. (Middle) Residue-specific rate constants of a first-order model of the 20S degradation kinetics of hTau40. Correlation coefficients for the fit to the first-order model are color-coded (color code bar to the right). Error bars represent SD. (Bottom) Evolution of relative peak intensities in 2D 1H-15N HSQC spectra of hTau40 in the presence of the 20S proteasome and the proteasome inhibitor oprozomib.

When tau is degraded by the proteasome into small peptides, the chemical environment of residues changes. To gain insights into the kinetics of 20S degradation, the intensity of IDP cross peaks at their location in the absence of 20S can be analyzed (27). Because a 1H-15N backbone correlation can be observed for every non-proline residue in the 2D 1H-15N HSQC, up to 397 (441 residues minus the C terminus and 43 prolines, and depending on signal overlap) sequence-specific probes for tau degradation are thus available.

The top panel in Fig. 3B displays the decrease of NMR signal intensities along the hTau40 sequence with increasing 20S incubation time. The fastest decrease occurred in the repeat domain. To derive residue-specific degradation rates, we fitted first-order decay kinetics via linear regression to the residue-specific intensity data. The highest rates occurred in repeat R3 and reached up to 0.015 hours1 at 5C (Fig. 3B, middle, and table S1). Fast degradation kinetics were also observed in the other pseudo-repeats, in agreement with similar sequence compositions. In addition, taus C terminus as well as residues ~220 to 250 at the end of the proline-rich region were rapidly affected by degradation.

Oprozomib predominantly inhibits the chymotrypsin-like activity of the 20S proteasome (28). Detailed analysis of the hTau40 spectra in the presence of both 20S and the small-molecule oprozomib showed that the cross peaks of residues in R2 and R3 decreased in intensity by up to 20% after 66 hours (Fig. 3B, bottom, and table S1). Thus, the 20S complex has residual proteolytic activity, which is not inhibited by oprozomib.

A large number of kinases can phosphorylate tau (29). These include proline-directed kinases [e.g., glycogen synthase kinase 3 (GSK3) and cyclin-dependent kinase 5 (cdk5)] that phosphorylate proline-serine/threonine motifs, notably in the proline-rich region of tau, as well as non-prolinedirected kinases [e.g., microtubule affinity-regulating kinase (MARK), protein kinase A (PKA), and Ca2+/calmodulin-dependent protein kinase II (CaMKII)], which phosphorylate the KXGS motifs in the pseudo-repeats. CaMKII phosphorylates tau at several sites (30) and colocalizes with neurofibrillary tangles (NFTs) in AD brains (31).

To gain insight into the influence of substrate phosphorylation on 20S degradation, we phosphorylated recombinant hTau40 with CaMKII in vitro. SDS-PAGE demonstrated an upfield shift in the hTau40 band, confirming successful phosphorylation (Fig. 4A). According to MS/MS analysis, CaMKII phosphorylates S131 and T135 in the projection domain, T212 and S214 in P2, S262 in R1, and S356 in R4 (30). 1H-15N NMR spectroscopy further showed that S214, S356, and S413 are fully phosphorylated in hTau40 (Fig. 4B). In addition, S262, S324, and S352 were found to be partially phosphorylated (Fig. 4B).

(A) SDS-PAGE gel demonstrating phosphorylation of hTau40 by CaMKII in the presence of calmodulin. (B) (Left) Enlarged region with phosphorylated residues taken from the first 2D 1H-15N HSQC recorded at 5C for a total duration of 3 hours on CaMKII-phosphorylated hTau40 in the presence of 20S. On top, the location of the phosphorylated residues is marked by short black lines in the context of the domain diagram of hTau40. (Right) Superposition of the first 2D 1H-15N HSQC spectrum (black; total measurement time: 3 hours) of CaMKII-phosphorylated hTau40 in the presence of 20S with the spectrum completed after 66 hours (red). (C) Relative peak intensities in 2D 1H-15N HSQC spectra of CaMKII-phosphorylated hTau40 in the presence of the 20S proteasome with increasing time of incubation at 5C (from red to blue).

We then incubated CaMKII-phosphorylated hTau40 with 20S proteasome at 5C. Even after 66 hours, no degradation peaks were observed in the 1H-15N HSQC spectrum (Fig. 4B and fig. S6). In addition, hTau40 cross-peak intensities remained largely unaffected (Fig. 4C and fig. S6). Similarly, CaMKII phosphorylation of the tau construct K18, which only contains the repeat domain, attenuated its degradation by the 20S proteasome (fig. S7). Thus, phosphorylation of tau by CaMKII interferes with the degradation of tau by the 20S proteasome.

GSK3 is ubiquitously expressed in mammalian tissue and has been implicated as a major tau kinase in AD (32). In vitro modification of hTau40 by GSK3 results in phosphorylation of S46, T175, T181, S202, T205, T212, T217, T231, S235, S396, S400, and S404 (33). NMR confirmed complete phosphorylation of S396, S400, and S404 (Fig. 5A). In contrast to CaMKII phosphorylation (Fig. 4), phosphorylation by GSK3 did not block proteasomal processing of hTau40 [Figs. 5A (red spectrum) and 6]. Analysis of cross-peak intensities at increasing 20S incubation times further showed that rapid degradation occurred in repeats R2 and R3 of hTau40 (Fig. 5B).

(A) (Left) Enlarged region with phosphorylated residues taken from the first 2D 1H-15N HSQC recorded at 5C for a total duration of 3 hours on GSK3-phosphorylated hTau40 in the presence of 20S. On top, the cartoon depicts the sites of phosphorylation of hTau40 by GSK3. (Right) Superposition of the first 2D 1H-15N HSQC spectrum (black; total measurement time: 3 hours) of GSK3-phosphorylated hTau40 in the presence of 20S with the spectrum completed after 66 hours (red). (B) Relative peak intensities in 2D 1H-15N HSQC spectra of GSK3-phosphorylated hTau40 in the presence of the 20S proteasome with increasing time of incubation at 5C (from red to blue).

(A and B) Per-residue rate constants for degradation of tau by the 20S proteasome. Residue-specific rate constants of a first-order model of the 20S degradation kinetics of hTau40 at 5C (A, top; same as in Fig. 3B), in the presence of the inhibitor oprozomib (A, bottom), of hTau40 phosphorylated by CaMKII (B, top), and of hTau40 phosphorylated by GSK3 (B, bottom). Correlation coefficients for the fit to the first-order model are color-coded (color code bars to the right). Error bars represent SD. (C) Schematic representation illustrating the phosphorylation-dependent degradation of the AD-related protein tau by the 20S proteasome: Wild-type tau (hTau40) is degraded by the 20S proteasome starting from the pseudo-repeat region and the C-terminal domain, producing short peptides (blue, pink, and orange) from those regions, followed by degradation of the N-terminal domain, which generates two long N-terminal fragments. Depending on the sites of phosphorylation, 20S degradation of tau is inhibited (CaMKII; top) or attenuated (GSK3; bottom). The color code of different hTau40 domains is described in Fig. 1.

Figure 6 (A and B) compares the residue-specific degradation rates of unmodified hTau40 in the presence of the 20S proteasome (Fig. 6A, top), unmodified hTau40 in the presence of 20S and the inhibitor oprozomib (Fig. 6A, bottom), CaMKII-phosphorylated hTau40 and 20S (Fig. 6B, top), and GSK3-phosphorylated hTau40 and 20S (Fig. 6B, bottom, and table S1). As calculated from the time-dependent decrease in cross-peak intensities, GSK3-phosphorylated hTau40 is most efficiently processed by the 20S proteasome in repeats R2 and R3. The phosphorylation of selected residues in taus C-terminal domain, however, blocks cleavage of peptide bonds in this region. In addition, the decay of NMR signals in the proline-rich region was strongly attenuated (Fig. 5B and fig. S4), in agreement with phosphorylation of T212, T217, T231, and S235 by GSK3 (33).

Within the cell, IDPs are constantly synthesized and degraded by the proteasome. Because they lack a globular structure, IDPs can directly be processed by the 20S proteasome without the need for previous ubiquitination and unfolding by the 26S proteasome (35, 34). In parallel, IDPs can be degraded in a ubiquitin-dependent manner by the 26S proteasome. Aggregates of IDPs cannot properly be degraded by the proteasome and are instead processed through autophagy (18, 19). In addition, tau aggregates might inhibit the activity of proteasomes and thereby contribute to neurodegeneration (2, 17, 18). Detailed insights into the processing of tau and other IDPs by the 20S proteasome may therefore be important for treating neurodegeneration and other human diseases (34).

Inhibition of the proteasome by small molecules results in increased amounts of tau in SH-SY5Y cells and rat brain (14, 35). In addition, the four-repeat isoform hTau43 (also termed 0NR4 tau) was shown to be degraded by the human 20S proteasome in vitro without previous ubiquitination (14). In agreement with the latter study, which used human 20S (14), we observed two relatively stable populations of long tau fragments from the N terminus when incubating hTau40 with the 20S proteasome from T. acidophilum (Fig. 1). To determine the identity of the two hTau40 fragments, we performed MS analysis and found that the long and short fragments contain residues 1 to 251 and 1 to 218, respectively (Fig. 1).

Proteasomes cleave their substrates to short peptides with mean lengths between 6 and 10 amino acids (4, 36). Longer (>50 amino acids) degradation intermediates are rarely detected, because the substrate is thought not to dissociate from the proteasome during the degradation process. The presence of two long truncated tau fragments during 20S degradation is therefore unexpected. The more than 200-residue-long tau fragments contain multiple, potential proteasomal cleavage sites (Fig. 2B). To investigate whether the generation of these fragments is the result of specific structural properties of the N-terminal domain of hTau40, we characterized this domain at a single-residue level by NMR spectroscopy. The analysis showed that Tau(1239) is more compact than hTau40 (fig. S2). We speculate that the more compact structure might interfere with 20S cleavage of the N-terminal fragments.

The short ~6- to 10-residue tau peptides generated by the 20S proteasome can further be cleaved by other proteases (2). In parallel, they might itself contain activity, which is relevant for pathological processes. Consistent with this hypothesis, the six-residue tau peptide 306VQIVYK311 can form insoluble amyloid-like filaments in vitro (26). We therefore used MS to identify the tau peptides generated by 20S degradation (Fig. 2). From the large number of different 20S-generated peptides, the tau peptide with the highest ion peak area was 309VYKPVDL315. Consistent with the high abundance of the 309VYKPVDL315 peptide generated by 20S degradation, signals corresponding to this peptide were identified in the NMR spectra of degraded tau (fig. S4). The 309VYKPVDL315 peptide lacks the first three amino acids of the filament-forming 306VQIVYK311 sequence but has four additional N-terminal residues including the two hydrophobic residues V313 and L315. Despite an overall high hydrophobicity, however, the tau peptide 309VYKPVDL315 did not aggregate into amyloid-like filaments in the presence of the aggregation enhancer heparin (Fig. 2D). Notably, all of the other 20S-generated peptides in the region from 308 to 320 also contain residue P312, i.e., a proline with known -strandbreaking property (Fig. 2C, right). Cleavage of tau by the 20S proteasome thus generates peptides that are unable to aggregate into amyloid-like filaments.

A wide range of assays have been developed to follow protein degradation. These assays often sample the degradation reaction at discrete time points using SDS-PAGE and antibody binding, autoradiography, protein staining, or Western blotting (37). In addition, proteasome activity can be analyzed through the measurement of fluorescence anisotropy of small-molecule dyes attached to substrate proteins. The identity of degradation products can furthermore be determined using MS. Here, we combined MS with NMR to (i) gain insight into the structural properties of the long degradation intermediates of tau identified by MS and (ii) quantify degradation kinetics in the IDP tau with single-residue and high temporal resolution. MS and NMR spectroscopy are thereby complementary, because MS enables large-scale identification of substrate fragments and peptides generated by proteasomal degradation, but cannot identify all released peptides, lacks single-residue resolution, and is limited in temporal resolution. NMR spectroscopy makes it possible to follow substrate degradation, while the reaction occurs in the test tube, and quantify degradation kinetics at high spatial/per-residue and temporal resolution. On the other hand, a high number of generated peptides and fragments complicate their identification by NMR especially for large IDPs, such as tau, which have many cross peaks. In addition, it has to be taken into account that the cleavage of a peptide bond can be sensed by residues that are several positions removed from the site of proteolysis (27). Because of the abovementioned aspects, we believe that the combination of MS and NMR will also be useful to investigate differences in the degradation pattern and substrate selectivity of 20S proteasomes from different organisms.

Using NMR spectroscopy, we found that the 20S degradation of many tau residues follows first-order decay kinetics (Fig. 3). The maximum degradation rate reached ~0.015 hours1 at 5C, which corresponds to a degradation half-time of ~46 hours. The reported half-life of tau in HT22 cells is 60 hours (15). The analysis further showed that the 20S proteasome from T. acidophilum preferentially cleaves tau in the pseudo-repeat region, with the fastest rates observed in repeat R3 (Fig. 3). Repeat R3 is part of the cross- structure of heparin-induced tau fibrils (38). In addition, R3 is located in the core of paired helical filaments purified from the brains of patients with AD (10). The data suggest that the 20S proteasome preferentially degrades the regions of tau, which are important for pathogenic aggregation.

SDS-PAGE analysis, in combination with antibody binding, was used to suggest that the degradation of tau by the 20S proteasome is bidirectional (14), supporting degradation models in which 20S degradation has a preference for the free NH2 or COOH terminus of a substrate (39). In contrast, we find that the proteasome degradation of tau is most efficient in the repeat domain (followed by the C-terminal domain; Fig. 3). Our results are thus in agreement with reports showing that the 20S proteasome can initiate endoproteolytic cleavage at internal sites of IDPs (5). The efficient cleavage of the pseudo-repeat region also enables the generation of the two long fragments from the N terminus of tau (Fig. 1).

The strength of the quantitative, combined MS/NMR approach was further supported by the experiments, in which we studied the influence of phosphorylation of tau on its degradation by the 20S proteasome (Figs. 4 and 5). Tau molecules found in NFTs in the brains of patients with AD are hyperphosphorylated, and dysregulation of tau phosphorylation has been linked to neuronal toxicity (6). Consistent with the hypothesis that impaired proteasomal degradation results in tau accumulation, phosphomimetic tau variants were less efficiently degraded by the proteasome in autophagy-deficient mouse embryonic fibroblasts (16).

The quantitative NMR-based degradation analysis showed that phosphorylation of tau by the non-prolinedirected serine/threonine kinase CaMKII inhibits degradation of tau by the 20S proteasome (Figs. 4 and 6). When the proteasome cannot degrade tau, autophagy becomes important, in agreement with the observation that autophagy is the primary route for clearing phosphorylated tau in neurons (16). However, using the same quantitative approach, we found that tau phosphorylated by GSK3, which phosphorylates Pro-Ser/Thr epitopes seen in NFTs in AD (32), only blocks cleavage in certain regions but does not interfere with tau cleavage in the pseudo-repeats R2 and R3 (Figs. 5 and 6). The regions of tau, which are no longer cleaved such as the C-terminal domain and the proline-rich domain, contain residues phosphorylated by GSK3 (Fig. 5). While GSK3 does not phosphorylate residues in the repeat region, CaMKII phosphorylates S262, S324, S352, and S356 and blocks degradation by the 20S proteasome (Figs. 4 and 6). Phosphorylation of S262, S324, S352, and S356 therefore appears to play an important role in the inhibition of tau degradation by the 20S proteasome. S262, S324, S352, and S356 are also phosphorylated by microtubule-associated protein/MARKs, and their phosphorylation affects tau aggregation as well as microtubule binding of tau (40). Currently, the mechanism of impaired degradation of CaMKII-phosphorylated tau is unknown but could involve (i) an impaired/restricted entry through the 20S gate formed by the first 12 amino acids of the subunit and (ii) a blocked interaction with the catalytic sites in the subunit. Our study provides the basis to quantify with single-residue resolution the degradation of tau and other IDPs, their different isoforms, and posttranslationally modified variants and thus gain mechanistic insight into disease-associated accumulation of IDPs.

Unlabeled and 15N-labeled Tau protein (hTau40, UniProt ID 10636-8, 441 residues) were expressed in E. coli strain BL21(DE3) from a pNG2 vector (a derivative of pET-3a, Merck-Novagen, Darmstadt) in the presence of an antibiotic. In case of unlabeled protein, cells were grown in 1 to 10 liters of LB and induced with 0.5 mM IPTG (isopropyl--d-thiogalactopyranoside) at OD600 (optical density at 600 nm) of 0.6 to 0.8. To obtain 15N-labeled protein, cells were grown in LB until an OD600 of 0.6 to 0.8 was reached, then centrifuged at low speed, washed with M9 salts (Na2HPO4, KH2PO4, and NaCl), and resuspended in minimal medium M9 supplemented with 15NH4Cl as the only nitrogen source and induced with 0.5 mM IPTG. After induction, the bacterial cells were harvested by centrifugation, and the cell pellets were resuspended in lysis buffer [20 mM MES (pH 6.8), 1 mM EGTA, and 2 mM dithiothreitol (DTT)] complemented with protease inhibitor mixture, 0.2 mM MgCl2, lysozyme, and deoxyribonuclease (DNase) I. Subsequently, cells were disrupted with a French pressure cell press (in ice-cold conditions to avoid protein degradation). In the next step, NaCl was added to a final concentration of 500 mM and boiled for 20 min. Denaturated proteins were removed by ultracentrifugation at 4C. The supernatant was dialyzed overnight at 4C against dialysis buffer [20 mM MES (pH 6.8), 1 mM EDTA, 2 mM DTT, 0.1 mM phenylmethylsulfonyl fluoride (PMSF), and 50 mM NaCl] to remove salt. The following day, the sample was filtered and applied onto a previously equilibrated ion-exchange chromatography column, and the weakly bound proteins were washed out with buffer A (same as the dialysis buffer). Tau protein was eluted with a linear gradient of 60% final concentration of buffer B [20 mM MES (pH 6.8), 1 M NaCl, 1 mM EDTA, 2 mM DTT, and 0.1 mM PMSF]. Protein samples were concentrated by ultrafiltration (5 kDa Vivaspin from Sartorius) and purified by gel filtration chromatography. Last, the protein was dialyzed against 50 mM sodium phosphate (NaP) (pH 6.8).

20S proteasomes from T. acidophilum were expressed from pRSETA containing the bicistronic gene including psmA and psmB. Transformed BL21 cells were induced with 0.1 mM IPTG and incubated for 18 hours at 37C. Harvested cells were resuspended in 3 ml of lysis buffer (50 mM Na2HPO4 pH 8.0, 300 mM NaCl) per 1 g of cells and lysed with the French press. The lysate was incubated at 65C for 15 min. Heat-denatured proteins were removed by centrifugation at 30,000g at 4C. Polyethylenimine (0.1%, w/v) was added to the supernatant to precipitate contaminating nucleic acids. Precipitated nucleic acids were removed by centrifugation at 100,000g for 1 hour. The supernatant was subjected to differential precipitation with polyethylene glycol 400 (PEG; number signifies the mean molecular weight of the PEG polymer). PEG400 was added to a concentration of 20% (v/v) to the supernatant under stirring at 18C and incubated for 30 min. Precipitated proteins were removed by centrifugation at 30,000g for 30 min at 4C. The supernatant was then precipitated by raising the concentration of PEG400 to 40% (v/v). The precipitate of this step contained the 20S proteasomes and was recovered by centrifugation at 30,000g for 30 min at 4C and resuspended in purification buffer (0.05 M BisTris pH 6.5, 0.05 M K(OAc), 0.01 M Mg(OAc)2, 0.01 M -Glycerophosphate) containing 5% (w/v) sucrose, 10 mM DTT, and 0.01% (w/v) lauryl maltose neopentyl glycol (LMNG) on an orbital shaker at 18C. The resuspended material was loaded on 10 to 30% (w/v) sucrose gradients in purification buffer containing 5 mM DTT, which are centrifuged at 284,000g for 16 hours at 4C. Gradients were harvested in 400 l of fractions. SDS-PAGE was used to identify fractions containing 20S proteasomes. Selected fractions were pooled and precipitated by the addition of 40% (v/v) PEG400. After centrifugation (30,000g, 20 min), the supernatant was removed and the precipitate was resuspended in purification buffer containing 5% (w/v) sucrose, 10 mM DTT, and 0.01% (w/v) LMNG. The resuspended material was loaded on linear 10 to 40% (w/v) sucrose gradients in purification buffer containing 5 mM DTT, which are centrifuged at 284,000g for 18 hours at 4C. Fractions containing 20S proteasomes are yet again identified by SDS-PAGE, precipitated and concentrated by the addition of 40% PEG400, and resuspended in purification buffer containing 5% (w/v) sucrose and 5 mM DTT, yielding the final purified protein preparation at 26 mg/ml. Protein concentrations were determined by the Bradford assay (Bio-Rad, Munich, Germany) using bovine serum albumin (BSA) as a standard.

For grid preparation, a protein stock solution (6 mg/ml) was diluted to 0.25 mg/ml with standard buffer without sucrose. Glutaraldehyde was added to the diluted protein solution to a concentration of 0.1% (v/v). After incubation for 2.5 min at room temperature, the reaction was quenched by the addition of 50 mM l-aspartate (pH 6.5). A continuous carbon foil was floated on the protein solution for 1 min at 4C. A holey carbon copper grid was used to remove the continuous carbon foil from the protein solution. Excess liquid was removed with a tissue paper. Proteins were stained by floating the grid on a saturated uranyl formate solution for 1 min at 4C. Remaining staining solution was removed with a tissue, and the grid was dried under ambient conditions. Negative-stain EM images were taken with a Philips CM200 microscope (160 kV). Images were acquired at a magnification of 66,000. The pixel size corresponds to 3.34 per pixel. The TVIPS charge-coupled device camera was used to record the micrographs.

hTau40 was phosphorylated by CaMKII (recombinant human CaMKII alpha protein from Abcam) and GSK3 [recombinant human GSK3 beta protein (active) from Abcam]. The reaction was performed by mixing 0.2 mM hTau40 with 0.02 mg/ml kinase, 2 mM DTT, 2 mM ATP, 1 mM PMSF, and 5 mM MgCl2 in 40 mM Hepes (pH 7.4). In case of CaMKII, we additionally used 2 M calmodulin (bovine calmodulin, recombinant from Sigma), 1 mM CaCl2, and, in case of GSK3, 2 mM EGTA. The samples were incubated at 30C overnight and buffer-exchanged to 50 mM NaP (pH 6.8). Protein concentrations were determined by the Bradford assay using BSA as a standard.

For detection of hTau40 degradation products/fragments generated by the 20S proteasome (hTau40:20S molar ratio of 3:1), we used a 18% separating gel [ddH2O, 30% acrylamide, 1.5 M tris (pH 8.8), 10% SDS, 10% ammonium persulfate (APS), and tetramethylethylenediamine (TEMED)] and a 4% stacking gel [ddH2O, 30% acrylamide, 1 M tris (pH 6.8), 10% SDS, 10% APS, and TEMED]. For validation of hTau40 phosphorylation, we used a 12% separating gel and a 4% stacking gel.

hTau40 was incubated with 20S proteasome for 150 min at 37C and 1 day at 4C. The resulting reaction sample was in 50 mM NaP (pH 6.8). The buffer was exchanged to MS compatible sample buffer using Amicon Ultra centrifugal filters with a molecular weight cutoff of 3000. The filter was first washed using water. The reaction sample and 300 l of sample buffer [0.1% formic acid (FA)] were then added to the filter and centrifuged at 7500g for 30 min. After removing the buffer, 300 l of sample buffer was added and centrifuged for 30 min. The buffer exchange was then repeated one more time. Last, the samples were diluted to 100 ng/l for the following MS analysis.

The intact MS experiment was performed on Q Exactive HF-X2 (Thermo Fisher Scientific) coupled to a Dionex UltiMate 3000 UHPLC system (Thermo Fisher Scientific) equipped with a PepSwift Monolithic Trap Column [200 m inside diameter (ID) 5 mm] and a ProSwift RP-4H Monolithic Nano Column (100 m ID 25 cm). The flow rate was set to 1 l/min. Mobile phase A and mobile phase B were 0.1% (v/v) FA and 80% (v/v) acetonitrile (ACN), 0.08% FA, respectively. The gradient started at 20% B and increased to 50% B in 33 min and then kept B constant at 90% for 4 min, followed by re-equilibration of the column with 5% B. MS spectra were acquired with the following settings: microscans, 1; resolution, 120,000; mass analyzer, Orbitrap; automatic gain control (AGC) target, 3 106; injection time, 100 ms; mass range, 450 to 2000 mass/charge ratio (m/z).

hTau40 samples were incubated with 20S proteasome (molar ratio of 3:1) for different times (30, 90, and 150 min at 37C and, additionally, 48 hours at 4C). The samples were then analyzed by SDS-PAGE electrophoresis as described above. The two fragments (around 25 to 30 kDa) were carefully cut from the gel and used for in-gel analysis. The in-gel digestion of the two bands was performed using trypsin (Promega) to the gels. In the next step, the extracted peptides were desalted by using stage tips. In the last step, the samples were dried (SpeedVac) and readied for further analysis.

hTau40 was incubated with 20S proteasome (molar ratio of 3:1) at 37C for 3 hours before the analysis. The samples were precipitated by acetone and put at 30C overnight. Then, the samples were centrifuged at 14,000g for 10 min, and the supernatant was collected and dried. In the next step, contaminates were removed by the sp3 method, followed by direct injection into the mass spectrometer.

In-geldigested peptides were analyzed using an Orbitrap Fusion Tribrid (Thermo Fisher Scientific) instrument. In-solution samples were analyzed using Orbitrap Fusion Lumos (Thermo Fisher Scientific). Both instruments are coupled to a Dionex UltiMate 3000 UHPLC system (Thermo Fisher Scientific) equipped with an in-housepacked C18 column (ReproSil-Pur 120 C18-AQ, 1.9 m pore size, 75 m inner diameter, 30 cm length, Dr. Maisch GmbH). Both Orbitrap Fusions (Tribrid and Lumos) were operating in data-dependent mode for MS2. Dried samples were resuspended in 5% ACN, 0.1% FA. Samples were centrifuged for 10 min at 14,000g, and the supernatants were transferred to new sample tubes. In both cases, the flow rate was set to 300 nl/min. Mobile phase A and mobile phase B were 0.1% FA (v/v) and 80% ACN, 0.08% FA (v/v), respectively. The gradient in Orbitrap Fusion Tribrid (in-gel samples) started at 10% B and increased to 42% B in 43 min and then kept B constant at 90% for 6 min, followed by re-equilibration of the column with 5% B. MS1 spectra were acquired with the following settings: resolution, 120,000; mass analyzer, Orbitrap; mass range, 380 to 1500 m/z; injection time, 50 ms; AGC target, 4 105; S-Lens radio frequency (RF) levels, 60; charge state, +2 to +7; dynamic exclusion after n time, n = 1, dynamic exclusion duration = 60 s. MS2 parameters were as follows: first mass, 120; activation type, higher-energy collisional dissociation (HCD); collision energy, 35; Orbitrap resolution, 30,000; maximum injection time, 250 ms; AGC target, 100,000. The gradient in Orbitrap Fusion Lumos (in-solution samples) increased to 30% B in 42 min and further to 40% B in 4 min and then kept B constant at 90% for 6 min, followed by re-equilibration of the column with 5% B. MS1 spectra were acquired with the following settings: resolution, 120,000; mass analyzer, Orbitrap; mass range, 350 to 1600 m/z; injection time, 50 ms; AGC target, 5 105; S-Lens RF levels, 30; charge state, +2 to +7; dynamic exclusion after n time, n = 1, dynamic exclusion duration = 30 s. MS2 parameters were as follows: first mass, 120; activation type, HCD; collision energy, 30; Orbitrap resolution, 15,000; maximum injection time, 120 ms; AGC target, 100,000.

Thermo Proteome Discoverer (2.1.0.81) was used for database searching. In Proteome Discoverer, the Sequest HT, fixed value peptide spectrum match validator, and Precursor Ions Area Detector nodes were used. Parameters for database searching were as follows: the hTau40 protein sequence (P10636-8) was downloaded from Swiss-Prot. Mass tolerance for precursors and fragment ions was set as 10 and 20 ppm, respectively. Maximal missed cleavage was 4. Dynamic modifications were set as oxidation (M) and acetylation (protein N terminus). For in-gel samples, fixed modification was carbamidomethylation (C). Trypsin was used as the enzyme, and its specificity was set as semi-specific. For in-solution sample, no enzyme was set. For precursor ions area detector, mass precision was 2 ppm. Only the peptides that were identified with high confidence were used in this study. For in-solution samples, the peak area of precursors was used for quantification of the identified peptides.

The peptide VYKPVDL was synthesized as trifluoroacetic acid salts by GenScript, and the stock solution (1 mM) was made in 25 mM Hepes (pH 7.4). To test whether the peptide can aggregate into amyloid fibrils, we used 50, 100, and 150 M of the peptide in 25 mM Hepes (pH 7.4). The stock solution of ThT (purchased from Sigma) was prepared in ddH2O, and for the binding assay, 50 M was used. When heparin (~20 kDa, Roth) was added to the sample, the molar ratio of the peptide to heparin was 4:1. ThT fluorescence was then measured with excitation at 440 nm and emission at 482 nm at 37C using a multimode microplate reader (Spark 20M, TECAN).

2D 1H-15N HSQC and 3D spectra (HNCO and HNCA) of hTau40 and Tau(1239) were acquired at 5C on a Bruker 800 MHz spectrometer equipped with triple-resonance 5-mm cryogenic probe. The protein concentration was 125 M in 50 mM NaP buffer (pH 6.8), 5% D2O, 0.1% NaN3, and 50 M dextran sulfate sodium. Spectra were processed with TopSpin 3.5 (Bruker) and analyzed using Sparky.

NMR degradation experiments with 20S proteasome involving hTau40, phosphorylated hTau40, and hTau40 in the presence of the proteasome inhibitor were acquired and processed as explained above. 2D 1H-15N HSQC spectra were recorded for 15N-labeled hTau40 and 20S proteasome in a molar ratio of 4:1 in 50 mM NaP buffer (pH 6.8) and 10% D2O. The dead time between mixing hTau40 and 20S proteasome and starting the first HSQC experiments was ~30 min.

To study the kinetics of the degradation of hTau40 by the 20S proteasome, 60-min HSQCs were measured every hour during the first 24 hours and then for 180-min HSQCs every 3 hours (for a total of 38 measurements) up to 66 hours. In case of the sample with the inhibitor as well as the phosphorylated samples, 180-min HSQCs were recorded every 3 hours for a total of 22 measurements (66 hours). For our control sample, we used the proteasome inhibitor oprozomib (ApexBio), which was incubated for 2 hours at 37C in 250 molar excess before the experiment.

Peak intensities were extracted from a series of 1H-15N HSQC datasets at predetermined time intervals. After peak assignment with the software Sparky, the peak intensities were normalized with respect to the initial peak intensity for each residue, taking into account the duration of each HSQC. A residue was excluded from plotting and further analysis if a consecutively recorded peak intensity increased to more than 115% of the relative intensity of the preceding measurement. Such an increase in peak intensity when compared to the preceding measurement can arise from more favorable relaxation properties in the generated peptides when compared to full-length tau. In addition, peak overlap can potentially cause fluctuating intensities.

The peak intensities at all recorded times of the remaining (i.e., not excluded) residues were analyzed by fitting to first-order decay kinetics via linear regression of the data with respect to the analytic solution of the normalized first-order decay model. The fitted first-order decay reaction constants were plotted for all nonexcluded residues of hTau40. The statistical uncertainty in the determined degradation rates expressed in terms of SDs of fits was estimated as follows. For each sample, we randomly excluded five (in case of samples hTau40 + 20S in molar ratios of 4:1 and 4.5:1) or three (in case of samples hTau40 + 20S + inhibitor, hTau40 + CaMKII + 20S, and hTau40 + 20S + GSK3) intensity profiles collected at the various time intervals from the fitting procedure and repeated this procedure 20 times. The selection was performed by randomly drawing five (three, respectively) numbers from a uniform distribution over all profiles measured at different time intervals, and the fitting procedure was carried out on each of these subsamples and each amino acid residue. From the 21 fits per residue obtained this way (20 undersampled plus 1 fit based on all measured profiles), we calculated the sample SD and depicted it as error bars. The plots depicting degradation rates were plotted as the full-data fit (declared here as the mean estimated value) plus/minus the SD. In addition, we determined the Pearson correlation coefficients for all respective fits, which are encoded in the color. Fits with an incorrect sign of (i.e., implying an incorrect/unphysical trend) were excluded from the plot.

Acknowledgments: We thank N. Rezaei-Ghaleh for help with NMR experiments and the Max Planck society for support. Funding: The financial support from the German Research Foundation (DFG) through the Emmy Noether Program GO 2762/1-1 (to A.G.) is acknowledged. P.F. is supported by a Manfred-Eigen-Fellowship from the Max Planck Institute for Biophysical Chemistry. M.Z. was supported by the advanced grant 787679-LLPS-NMR of the European Research Council. Author contributions: T.U.-G. performed tau phosphorylation, NMR experiments, and data analysis. P.F. and K.-T.P. performed MS and data analysis. A.I.d.O. analyzed Tau(1239) and performed NMR experiments and K18 degradation. F.H. prepared 20S proteasome. A.G. performed NMR data analysis. M.-S.C.-O. prepared Tau(1239). A.C. supervised 20S preparation. H.U. supervised MS. E.M. and M.Z. designed the study. The manuscript was written through contributions of all authors. Competing interests: The authors declare that they have no competing interests. Data and materials availability: The MS proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD015349. The chemical shifts of Tau(1239) were deposited in the BMRB (identifier: 28065). All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials. Additional data related to this paper may be requested from the authors.

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Proteasomal degradation of the intrinsically disordered protein tau at single-residue resolution - Science Advances

What’s the Best Human Brain Alternative for Hungry Zombies? – Gizmodo UK

Posted on July 13, 2020 by Prof Baldwin

Lets say youre a zombie. Youre lumbering around, doing your zombie-mumble, and just ten feet ahead you see a living human being. Your first impulse, of course, is to head over there and eat their brain. And youre about to do just that, when suddenly you feel a pang of something like shame. You remember, dimly, being a human yourself. You remember how you mightve felt, if an undead weirdogot to gnawing on your skull. Youre at an impasse: at once desperate for brain meat and reluctant to kill for it. So you head to your zombie psychologist and start explaining the situation, and your zombie psychologist starts grinning, which annoys you at first I mean, youre baring your soul to this guy until he explains whats on his mind. Turns out, hes been toying with an idea a pilot program for conscience-stricken zombies. Instead of human brains, theyll be fed stuff that looks and tastes justlikebrains, thereby sparing them the obligation to kill. The only thing they need to work out is: what would be an acceptable substitute for human brains? For this weeksGiz Asks, we reached out to a number of brain experts to find out.

Associate Professor, Neurobiology, Harvard Medical School

The brain is of course composed primarily of lipids, and so it is perfectly reasonable to assume that it is brain lipids that zombies really crave. But why human brains and not, say, mouse brains? Lipidomic analysis reveals that human brains are unusually enriched in a compound called sphingomyelin (relative to brains from rodents), and so it is further reasonable to assume that what zombies want is actually lots of sphingomyelin. So where to get it? Eggs. Eggs are packed with sphingomyelin. Furthermore, eggs also have the advantage of having a white outer cortex and a lipid-rich center, just like the human brain, so they seem a reasonable substitute all around.

Chair and Professor of Neurology at the David Geffen School of Medicine at UCLA and Co-Director UCLA Broad Stem Cell Center

A food-based substitute would require a fair amount of work, because youd have to get a sort of fatty, proteinaceous slop together as a mimic for the brain. A thick macaroni and cheese might work, with a larger noodle like ziti or rigatoni and no tang, meaning a thick white cheese, as opposed to cheddar.

The brain sandwich, made from cow brains, was an unusual delicacy in St. Louis for years. When I lived there, I saw what it looked like as they fried it, and its hard to imagine any other organ meat could substitute for the real thing. Kidney and liver are too firm and too structured; most foods we eat, or could think about eating, are also too firm, and not fatty enough.

A brain from another animal might work, though it would have to be an animal with an advanced brain that is, one with the folds we see when we look at the brains surface (which are called gyri and cilici). Those are what distinguish higher mammals from lower mammals. They also make the human brain this particularly characteristic thing in terms of substance and texture and appearance. So an animal brain, to sub for a human brain, would need to have those features. That would mean anything from, say, a dog or cat on up those both have gyri and cilici, whereas rodents and rabbits, for example, do not.

Assistant Professor of Brain Science, Psychiatry and Human Behaviourat Brown University

I think my Zombie would be a vegan. The thing that I have found to be the closest in texture to the brain is tofu (not the firm kind). People are often surprised by that fact, because its really soft you can put your finger through it easily.

Broadly, I study the kind of complex planning and decision making that is localised to the front of the brain, the prefrontal cortex. This area is also one of the most likely to be injured if you hit your head, because your very soft brain bounces around inside your skull. Our lab typically does a demo for Brain Week and other events that lets people feel tofu, and then shake it around in a container and see what happens to it. Shake it around in some water (mimicking some of the protections that our brain has in the cerebro-spinal fluid that it floats in) and the tofu does much better (which is why its packaged in water!).

Unfortunately tofu doesnt mimic all the wonderful folding that it has that lets us pack so many brain cells into a tight space. A sheet of paper crumpled up is best to show that capacity, but paper is probably much less tasty than tofu (to humans anyway, I dont know about zombies!).

Professor, Systems Biology, George Mason University

My proposal is: a literal pound of flesh. Many people have too much of it; its very similar to the brain in texture; it has a lot of cholesterol, which is important, because in my opinion at least zombies would crave exactly that. Also, adipose tissue is very rich with various kinds of growth hormones and other kinds of bioactive stuff. If you could develop some kind of device that would transfer the flesh to the zombies, people might even be grateful they wouldnt have to get liposuction.

Senior Lecturer, Medical Biotechnology, Deakin University

The best thing to do would be to make small versions of a brain from stem cells, called organoids. These are almost, but not quite, brains. You grow them in an artificial 3D environment that mimics the properties of the central nervous tissue, and allow them to develop networks of neural cells in a structured way. Theyre used for research into drugs and diseases and so on, but would probably be an acceptable meat-free snack for an ethically conscious zombie plague.

Professor in Neurology and Professor of Biomedical Engineering at Duke University

If I were a vegetarian zombie, I would try to make a brain substitute using the major components of the brain carbohydrates, proteins, and cells. The major carbohydrate component is hyaluronic acid (which is found in many beauty products, and can be purchased in bulk). Though by itself it does not form a solid, only a very viscous liquid, it can be combined with other materials that do form a solid. For example, sea weed has a carbohydrate named alginate that does form gels when combined with calcium. So, a blend of hyaluronic acid and alginate with calcium can yield a material that has the mechanics of the brain. For the protein component, eggs, beans, soy, and quinoa all can be good choices. To get the texture right, the calcium can be added while stirring to generate chunks. If it is ok to eat other animals, then I would buy pig brains, which are often discarded. Pig organs are close to the same size of humans and have even been used for transplantation due to similarities in physiology/biochemistry. That would be the simplest choice.

Associate Professor, Psychology and Neuroscience, George Mason University

Whenever I eat cauliflower, I think of the cerebellum or little brain. It is tucked away behind the cerebrum, or main part of the brain. The cerebellum is small, but it is where about 80 percent of the entire brains neurons are found! Most of the cerebellums neurons, or gray matter, are found on its outer surface. They are tightly packed together in little folds called folia. The neurons in the folia are connected to each other by nerve fibres, also known as white matter. When the cerebellum is cut in half, the white matter appears as this beautiful network of branches called the arbor vitae, or tree of life. It really does look just like a head of cauliflower!

Professor, Psychology and Neuroscience, Trinity College

The brain is actually quite soft and squishy. Fortunately for us it normally floats in a pool of cerebrospinal fluid that serves as a cushiony packing material protecting the delicate brain from the hard skull. But the brain is so soft it can easily become injured without the head striking any object. If there is enough rotational or acceleration/deceleration motion for the brain to hit the skull the tips of the brain can be bruised and individual cells can be stretched or sheared from their connections. This can happen, for example, in motor vehicle accidents or shaken baby syndrome where the head is thrown very quickly forwards and then backwards.

The consistency I think the brain comes closest to is a gelatin. But I would recommend that our zombie make the gelatin with milk rather than water. This will give it a closer consistency to a brain, the color will be more opaque like a real brain, and it will provide more of the much needed protein the zombie craves. There are even commercially made gelatin molds if the zombie is able to access stores or online shopping.

Another option would be a soft tofu. This might be a great option for a zombie who is a vegetarian or vegan. There is plenty of protein but it will be much harder to mold into the right shape. Sadly, most zombies are not portrayed to have the fine motor skills needed to create a brain shape from scratch, so the tofu would just have to be eaten as is.

On a side note, if our zombie truly finds that nothing satisfies like a real brain, they could certainly consider becoming a neurosurgeon that specializes in therapeutic surgeries, like temporal lobe resections. In this case, a small portion of the temporal lobe of the brain is removed to relieve a person of intractable epilepsy. This might allow for a chance to satisfy their craving while providing benefit to the person involved.

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What's the Best Human Brain Alternative for Hungry Zombies? - Gizmodo UK

Tennessee scientists have partnered on cutting-edge discoveries in a race against COVID-19 – Knoxville News Sentinel

Posted on July 14, 2020 by Prof Baldwin

Scientists at Oak Ridge National Laboratory havetaken an important step in the race to understand SARS-CoV, the virus that causes COVID-19. Using sophisticated techniques, the scientists mapped out the structure of a critical protein of the coronavirus.

They'rehoping to answer this age-old scientific question that's more pressing than ever in this pandemic:How do you kill something that's not really alive?

The results of the groundbreaking work at Oak Ridge National Laboratory were published in Nature,a leading science journal.

Without this protein, the coronavirus cannot replicate. The scientists hope that by studying this structure, they will be able to find drugs that can stop it.

"The most important part is probably the fact that this protein is essential for the replication of this virus," said Dr.Daniel Kneller, a researcher at Oak Ridge National Lab andthe first author of the study. "If you inhibit this protein you're preventing the virus from assembling. Period."

While this study is focused on a very specific aspect of COVID-19, it opens a window onto the immense network of scientists and scientific organizations working on the pandemic. Tennessee is home to a state-spanning, drug development pipeline that is a microcosm of nationaland global research.

The COVID-19 protease protein is both shaped like a heart and functions as one. Without it the virus cannot grow and spread.(Photo: Andrey Kovalevsky, ORNL, U.S. Department of Energy)

Viruses are hard to treat because they arent like other things that cause diseases. Antibiotics, antifungals and antiparasitic drugs stop cells from replicating or kill them outright. But viruses arent made of cells. They are bundles of proteins and genetic material that hijack cells, forcing them to produce viral particles. Viruses cannot replicate on their own.

Theres debate among biologists as to whether viruses are actually alive because of this.

"How do you kill something that's not really alive?" said Dr. Martha S. Head, director of the Joint Institute for Biological Sciences at Oak Ridge National Lab. She oversees Oak Ridge's COVID-19 molecular design research projects. She explained that this study was part of a push to shut down viral replication at multiple stages, which is how HIV is treated.

"That combination (of drugs) shuts down so many parts of the (HIV) life cycle that you drive down viral loads to where they don't matter," Head explained.

COVID-19 Protease crystals, grown in Oak Ridge National Labs Protein Crystallization and Characterization laboratory and pictured in microscopic view.(Photo: Daniel Kneller: ORNL, U.S. Department of Energy)

To do this, the Oak Ridge team went right to the heart of the coronavirus itsproteins. When a virus infects a cell, it forces the cell to produce viral proteins. But host cells often cant create finished viral proteins, just long strands of unfinished, conjoined, protein.

Proteins are a bit like self-folding origami. Once theyre assembledthey fold into their final shape. Some proteins need to be cut by enzymes, like a protease, to get them into their final shape.Viral proteins cant do that when they're conjoined.

To make finished protein, each viral particle carries a protein enzyme called protease. The COVID-19 protease cuts unfinished viral protein, freeing it to fold itself into a final shape. If the protease cant do this, new virus cannot be made.

It is the heart of viral replication. Finding a chemical compound that can attach to and stop the heart of COVID-19 could be critical for developing a treatment. This is actually the therapeutic approach for anti-HIV drugs like Atazanavir.

But to quickly discover a drug,scientists it helps to have anaccurate map of the protease.

"If part of the protein is incorrectly modeled when you try to design drugs you may miss interactions that would otherwise form (between the drug and the protein)," explained Dr. Andrey Kovalesky, a researcher at Oak Ridge who worked on the study. He explained that without an accurate structure model, researchers might miss a potential drug or get bogged down in false positives.

To find the structure, the scientists grew large crystals made of viral protein in the lab. They took these crystals and exposed them to x-rays. When x-rays hit the protein crystal, they bend and scatter in different directions based on the shape of the protein. After they scatter they hit sensitive x-ray detectors. The scientists use the pattern of x-ray hits to ultimately figure out the shape of the protein.

This is called x-ray crystallography and was famously used to discover the structure of DNA.

The technique is like taking multiple photographs from different angles of the same object. By looking at all angles of the object you can figure out its 3-D structure.

Usually this kind of experiment is done at very cold temperatures. Thats because protein molecules tend to move more at warm temperatures. Its like photographing a moving object.

Unfortunately, getting a clearer picture can also mean missing theshape of the protein or how they move. Viruses often change shape but they cant when theyre frozen. Its like looking at frozen meat and expecting it to behave like a living muscle.

"You really have to appreciate that it's one single confirmation that you're looking at," said Dr. Paul McGonigle,director of the Drug Discovery and Development Program at Drexel University. "You hope that this is the confirmation the protein exists in most of the time, but you never know for sure."

The scientists at Oak Ridge did something special. They did this study at room temperature. Their equipment is more sensitive than the type typically used for this kind of experiment. Because of that, they could see the a fuller range of motion in the of COVID-19 protein that accuracy is very important for developing a drug.

"I think it's useful for them to have these different confirmations to target," said Dr. Ole Mortensen, associate professor of pharmacology at Drexel University. Mortensen explained that his own drug development work was made more challenging because he only had a single snapshot of his target protein.

"I'm worried that I could be missing some of the other ones. I think it makes sense what they're doing. They're opening up more possibilities." Mortensen said.

Oak Ridge might not immediately come to mind when you think medical research. But the national lab system has played a role in medical science since its inception. Sex chromosomes were discovered by pioneering geneticistLiane Russell at Oak Ridge, for example.

When Congress injected hundreds of millions of dollars into COVID-19 research through the CARES Act, The Department of Energy received $99.5 million for the national lab system. Compared to other agencies like the National Institutes of Health or Department of Defense, which got $945 million and $415 million respectively, that might not seem like a lot.

But the national lab system has unique resources that can be quickly marshaled against COVID-19. The Neutron Spallation Facility has the kind of sensitive x-ray detectors necessary to scan a protein at room temperature. The facility houses a lab capable of quickly growing large protein crystals.

"Oak Ridge is uniquely good at growing really big protein crystals," said Charles Sanders, a professor of biochemistry at Vanderbilt University. "Because they have that general expertise, it lets them do room temperature crystallography."

"They also have a network of people around the country, so if the big dogs at these agencies want stuff to happen then it can be, a wartime response, basically," Sanders said.

When the CARES act passed, it let the scientists clear their schedule and focus on COVID-19. Ordinarily, research like this takes months if not years of applying for grants and negotiating for time on equipment. This study mapped and published the protease structure in about a month.

"This is different than our usual projects," said Dr. Head. "Acrossthe Department of Energy as a whole, the speed (of organizing research) is astronomically fast."

Importantly, Oak Ridge houses the Summit supercomputer, one of the fastest supercomputers in the world. Once the structure was figured out by one team, the Summit team quickly screened it against a massive library of potential compounds, looking for potential matches.

"We broke a world record on the supercomputer," said Jeremy Smith,director of the Center for Molecular Biophysics at Oak Ridge. "We screened 1.2 billion compounds in less than a single day."

This is not the first time Dr. Smith has run a massive simulated drug test like this. Knox News covered his experiments back in March. The difference here is scale. Smiths team screened the COVID-19 protease against 1.2 billion possible drugs in a single day using Summit's whole processing system. Now the most promising candidates are being sorted out for eventual testing against live COVID-19 virus.

As impressive as Oak Ridges facilities are, they dont have the ability to do that kind of testing in house. For that, Smith turned to Dr. ColleenJonsson, a professorUniversity of Tennessee Health Sciences Center in Memphis.

Dr. Jonsson is an experienced virologist and virus hunter. She also happens to be the director of the Southeast Regional Biocontainment Laboratory, one of a small network of labs authorized by the federal government to do research on dangerous biological agents and emerging infectious diseases. She had the facility and staff to do what Oak Ridge could not:validate potential drug targets in the real world.

"A virtual screen (in a computer)is a theoretical screen." Dr. Jonsson said. "Once we find them we have to validate we're actually hitting the right thing."

Jonsson saidthat earlier in the year Smith reached out to her to test possible drugs targeting a different protein, the spike protein the coronavirus uses to attach to cells. Since then, her lab has expanded to validating other potential drugs targeting other proteins. While Dr. Jonsson hasnt yet begun to work on the COVID-19 protease, she expects to shortly.

This part of the process, where drugs are tested in live cells to see if they stop a virus from replicating, is arduous. Scientists working at the Biocontainment Lab don full biohazard suits to run their tests. Even after they validate that a potential drug works on a virus in a dish, they still need to run extensive dosage and safety testing, a process that can take months if not years.

Then they have to see if the drug actually works in a real infection. For this they need to test the drug in an infected animal that gets infected with COVID-19 like a human would. Getting an accurate animal model is a difficult process that requires its own experiments and validation.

Dr. Jonsson's team has been busy with this, and other COVID-19 work, since the start of the pandemic. They are among the very few people reporting to work at the University of Tennessee Health Sciences Center campus during the initial lockdowns. The Biocontainment team worked quickly to get everything ready for coronavirus research.

"They worked every day through the Safer at Home order with remarkable dedication," said Dr. Jonsson. "Everyone was working seven days a week to get everything ready."

In spite of its critical role in coronavirus research, the Biocontainment Lab is operating semi-independently. It has not received any funding yet through the CARES Act and is working solely on University of Tennessee funding.

None of thisscience is settled. The author of another structural study on the COVID-19 protease,Dr. Rolf Hilgenfeld of the German Center for Infection Research, was not convinced that the Oak Ridge study would amount to anything.

"I don't think this small difference, (between the shape of the proteins at different temperatures)whatever is its cause, matters for drug design," wrote Hilgenfeld in an email to Knox News.

The Oak Ridge team is planning to scan COVID-19 proteins using a higher resolution technique, neutron scattering,to get even better structures. Dr. Jonsson's team hopes to be running animal tests for possible COVID-19 drugs by the end of the year.

Read or Share this story: https://www.knoxnews.com/story/news/2020/07/14/tennessee-scientists-cutting-edge-discoveries-covid-19-race-oak-ridge-vaccine/5408399002/

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Tennessee scientists have partnered on cutting-edge discoveries in a race against COVID-19 - Knoxville News Sentinel

Setting the bar in education – The Star Online

Posted on July 18, 2020 by Prof Baldwin

Cheahs belief in working with the best and learning from the best also birthed the appointments of the Jeffrey Cheah distinguished professors.

Under the collaboration between Jeffrey Cheah Foundation and globally acclaimed academic institutions, eminent experts and scholars - who have contributed to solving critical global issues in health, disease and economy amongst others - are appointed to share their knowledge and expertise with Malaysian academics, students and the general public.

Among the prominent names on the list are:

Prof Jeffrey David Sachs

As a world renowned economist and director of the UN Sustainable Development Solutions Network, Prof Sachs is one of the worlds most influential experts on sustainable economic development.

A passionate leader in the fight against poverty and the special advisor to the UN secretary-general on sustainable development, he has advised heads of states and governments on economic strategy for more than a quarter century.

Appointed as an honorary Jeffrey Cheah distinguished professor of sustainable development at Sunway University this year, he is also the chairman of the Jeffrey Sachs Centre on Sustainable Development.

Prof Sir Leszek Borysiewicz

The chairman of Cancer Research United Kingdom (UK) since 2016, Prof Borysiewicz is an Honorary Jeffrey Cheah distinguished professor who is now the emeritus vice-chancellor of the University of Cambridge, after serving as its vice-chancellor from 2011 to 2017.

A founding fellow of the Academy of Medical Sciences, he has been chief executive of the UKs Medical Research Council since 2007 and was knighted in 2001 for his breakthroughs in vaccines, including developing Europes first trial of a vaccine to treat cervical cancer.

Prof Sir Alan Fersht

World leading protein scientist Prof Fersht, also an honorary Jeffrey Cheah distinguished professor and life fellow of Gonville and Caius College Cambridge, is widely regarded as one of the main pioneers of protein engineering, which is a process to analyse the structure, activity and folding of proteins.

His current research involves a fusion of protein engineering, structural biology, biophysics and chemistry to study the structure, activity, stability and folding of proteins, as well as the role of protein misfolding and instability in cancer and disease.

Prof Kay-Tee Khaw

Prof Khaw, a leading expert in the field of health and disease, is a Jeffrey Cheah professorial fellow in Gonville and Caius College, Cambridge. She is currently one of the principal UK scientists working on the European Prospective Investigation into Cancer and Nutrition, a Europe-wide project investigating the links between diet, lifestyle and cancer.

Appointed as a Commander of the order of the British Empire in 2003, Prof Khaw has been recognised for developing improved methods for collecting information on peoples diets and levels of exercise and relating this to the number of diagnosed cancer cases.

Prof Rema Hanna

A highly distinguished economist, Prof Hanna is the Jeffrey Cheah professor of South East Asia Studies and chair of the Harvard Kennedy School International Development Area, as well as the faculty director of evidence for policy design at Harvards Centre for International Development and the co-scientific director of the Abdul Latif Jameel Poverty Action Lab South East Asia office in Indonesia.

Her focus is on improving overall service delivery, understanding the impacts of corruption, bureaucratic absenteeism and discrimination against disadvantaged minority groups on delivery outcomes.

Prof Ketan J Patel

Prof Patel is a Jeffrey Cheah professorial fellow in Gonville and Caius College, Cambridge and the principal research scientist at the famous MRC Laboratory of Molecular Biology in the University of Cambridge.

His research, which focuses on the molecular basis of inherited genomic instability and the role it plays in the biology of stem cells, has been recognised through prestigious awards and prizes, including being elected as a fellow of the Royal Society of London, a member of the European Molecular Biology Organisation and a fellow of the Academy of Medical Sciences UK.

Prof John Todd

The Jeffrey Cheah fellow in medicine at Brasenose College, Oxford and professor of precision medicine, Prof Todd is a leading pioneer researcher in the fields of genetics, immunology and diabetes. His research areas include Type 1 diabetes genetics and disease mechanisms with the aim of clinical intervention.

In his former role as a professor of human genetics and a Wellcome Trust principal research fellow at Oxford, he helped pioneer genome-wide genetic studies, first in mice and then in humans.

Prof William Swadling

Prof Swadling, a Jeffrey Cheah professorial fellow, is a senior law fellow at Brasenose College, Oxford and Professor in the Law of Property in the Oxford University Law School.

An expert on the Law of Restitution, he is a contributor to Halsburys Laws of England, wrote the section on property in Burrows (ed) English Private Law and is widely cited in the British courts.

Prof William James

A Jeffrey Cheah professorial fellow emeritus and fellow in medicine at Brasenose College, Oxford, Prof James is a virologist with a background in genetics and microbiology.

As the professor of virology with the University of Oxford, he is the principal investigator at the Stem Cell Research Institute of Oxford, running a research lab studying HIV-macrophage biology using stem cell technology.

Prof Mark Wilson

Prof Wilson, the dean of Brasenose College, is a Jeffrey Cheah professorial fellow at the college and the professor of physical chemistry in the University of Oxfords physical and theoretical chemistry department.

The primary focus of his research interest is on the construction, development and application of relatively simple potential models to assess a wide range of systems with potentially unique properties.

Prof Jarlath Ronayne

Appointed in 2010 as the first Jeffrey Cheah distinguished professor, Prof Ronayne is a key member of Sunway Universitys board of directors and has played a pivotal role in establishing links between Sunway, Oxford and Cambridge.

Under his leadership, the Jeffrey Cheah Professorial Fellowships at Gonville and Caius College, Cambridge as well as Brasenose College, Oxford and the Jeffrey Cheah Scholar-in-Residence programmes in both colleges were established, alongside the prestigious Oxford University-Jeffrey Cheah Graduate Scholarship launched by the British High Commissioner in 2018. All these initiatives are in perpetuity.

Prof Sibrandes Poppema

A medical expert on Hodgkins disease, Prof Poppema has published more than 200 articles that have been cited more than 17,000 times.

The Jeffrey Cheah distinguished professor is also the co-owner of 12 patents and the founder of two biotechnology companies, as well as the advisor to the chancellor at Sunway University, especially on the establishment of a new medical school at the university.

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Setting the bar in education - The Star Online

Prayers Answered – The Herald

Posted on July 11, 2020 by Prof Baldwin

Story by Leann BurkePhotos by Marlena Sloss

Early afternoon sunlight shone through the stained glass windows of the new St. Mary Catholic Church building in Ireland as Pat Gress led his mother, the late Rita Gress, through the building she helped plan for and prayed about for decades.

As the pair entered the nave that late May day, Rita looked to the high altar a combination of the high altar and two side altars from the now closed St. Patrick Catholic Church in Corning and teared up.

Duane Gress takes his mother, Rita, on a tour led by his brother, Pat, not pictured, of the new St. Mary Catholic Church in Ireland on May 17. Rita was part of the original long-term planning committee for the new church and Pat was the construction manager. She had leukemia and was able to visit the new church weeks before she died.

Its just fantastic, she said of the whole church. I just cant believe it.

Im glad you like it, Pat said. You were instrumental in getting this thing going.

Pat managed construction on behalf of the church.

The congregation at St. Mary began discussing the possibility of building a new church about 40 years ago. The old building located at 2829 N. 500 W opened in 1905, and at that time, about 45 families attended the church. Today, the church is home to about 1,000 families, many of whom have been members for generations. The Gress family, for example, has been part of the congregation for about a century, and Rita was part of the early discussions about expanding.

When the first long-range planning committee formed in the 1970s, Rita joined and advocated for the construction of a new church building. Ultimately, the committee chose to expand the 1905 building and to begin saving for the construction of a new church down the line.

Then, in the early 2000s, discussion about building a new church picked up again. Rita eagerly took a role on that iteration of the long-range planning committee, as did her son-in-law, Steve Buechler. Steve attended Holy Family Catholic Church in Jasper before he married Ritas daughter, Margaret, and began attending St. Mary.

The 15-person committee spent hours talking to parishioners about what style they wanted the church to have traditional, country Catholic was the consensus and researching architects and designs. Part of their research included a structural study of the 1905 building, which revealed some issues that would have made the cost of remodeling that building about the same as building a new one. That, coupled with the knowledge that a remodel would mean losing that traditional, country look, led the committee to pursue building a new church.

We took a very serious approach, Steve said. We knew we were planning for the next 100 years of our parish.

The new church began to become a reality in 2017 when the parish launched the Building Our Future capital campaign to raise the $6 million needed for the project. As of March, the campaign had raised about $5.6 million.

Construction crews work on the pillars on the top of the new St. Mary Catholic Church in Ireland on Jan. 16. The new church was designed to look as similar as possible to the old church, seen in the background.

According to guidelines from the Catholic Diocese of Evansville, the campaign needed $4.8 million 80% of the total cost to break ground. That threshold was met by 2018, and construction crews broke ground that year. At last, the decades of research and planning were turning into something tangible.

St. Mary parishioners dedicated so many years to planning for their new church that when Evansvilles bishop, Joseph Siegel, dedicated the new building on June 28, he joked in his homily that the parishioners had been dreaming of their new church almost as long as the biblical Jews of Jesus time spent building the temple from which Jesus expelled merchants in the second chapter of The Gospel of John. According to the story which was the Gospel reading for the dedication Mass that biblical temple took 46 years to build.

The years of hard work and planning paid off, however. The final designs for the new church yielded a traditional country church that looks much like the old building, but will fit 700 per mass, with room for additional folding chairs if need be, rather than the 380 the 1905 building housed. It also includes several features the parishioners wanted, including an additional parking lot, a space inside the church building for offices, a cry/bridal room, a covered entrance and a narthex, a large open area before the nave where parishioners can gather before and after church services.

The builders did an amazing job of bringing our vision into reality, Steve said.

The wish list also included refurbishing the original nine stained-glass windows from the 1904 church for use in the new building, and the commissioning of 11 new windows. For that, the parish called on Mominee Studios of Evansville. The original windows were made according to the American Opalescent style following the technique developed by John La Farge, an artist at the forefront of the American Arts and Crafts Movement of the late 1800s, according to the Smithsonian American Art Museum.

When [St. Mary Church] was built in 1904, all the churches were using [that style], said Jules Mominee, owner of Mominee Studios.

To restore the nine old windows, Jules and members of his team spent most of a day carefully removing the century-old, intricately decorated windows some of which consisted of three glass panels and loading them into a truck for transport to the studio in Evansville. There, the team refurbished the windows to make them vibrant again.

Mominee Studios employee Nick Morgan assembles the St. Scholastica stained glass window in Evansville on Oct. 17. Mominee Studios worked on 26 windows for the new church, including designing and building 9 new windows. From the beginning of the design process to the installation of the final window, Mominee Studios spent two years on the project.

The artists also built the 11 new windows at the studio, following techniques almost identical to those used by La Farge in the late 1800s. If a single artist worked on one window from start to finish, Jules said, the process would take two months, but his team of six artists can complete a single window in two weeks, and they always work on groups of windows at the same time to make a project move along quickly.

Like the stained-glass windows, the high altar, too, took a long time to prepare for its place in the new church. Jim Buechlein, owner of Buechleins Kwik Strip & Custom Furniture & Design in Jasper, oversaw the removal of the three altars from St. Patrick in Corning three years ago and refurbished them into the ornate, gothic-style altar that is now the focal point in St. Marys nave.

It was no small task, but Jim who attends Precious Blood Catholic Church in Jasper and has built custom pieces for several local churches, including Precious Blood and St. Ferdinand was confident he could create a beautiful piece for the new church.

The process included sanding down and refinishing the altars before combining the three separate altars into a single high altar. The latter meant rebuilding some of the pieces before painting the entire structure white with milk paint, which is an architectural paint made from the milk protein casein mixed with lime, clay and earth pigments. Its a type of paint common to historic pieces.

All finished, Jim estimates the altar is worth about $1 million. He and his team installed the altar in late May.

It was like a sigh of relief, he said. It felt good to see it sitting in the church.

Jim Buechlein, left, of Buechlein's Kwik Strip & Custom Furniture & Design, hands a piece of the altar to Sam Wagner of Wagner Brothers Construction while they assemble the altar at the new St. Mary Catholic Church in Ireland on May 15. The altar was re-designed from three separate altars from a St. Patrick Parish Church in Corning that closed down.

Tom Wagner and a team of workers helped Jim install the altar. A lifelong member of St. Mary, Tom was excited to see the new church coming together and to be part of it.

It was time, Tom said of building a new church. Its going to be a lot better.

After about two years of construction, the new church building opened to parishioners on Sunday, June 28, with the Rite of Dedication led by Bishop Siegel. The pews filled with mask-clad parishioners who spread throughout the pews to socially distance and eagerly waited to anoint the halls of their new house of worship. Several local priests also attended to celebrate the event with St. Marys Father Joseph Effie Erbacher and the parish.

The dedication kicked off with the handing over of the building when representatives of the architect and general contractor presented plans for the building to Bishop Siegel. Then, Fr. Erbacher opened the doors to the nave, beginning the processional to the altar.

Enter the gates of the Lord with thanksgiving, his courts with songs of praise, Bishop Siegel said as Fr. Erbacher opened the doors.

In addition to the celebration of the eucharist, the dedication Mass also included several steps to consecrate the building and prepare it to house decades of worship. As soon as the bishop reached the altar, he performed the blessing and sprinkling of water where he blessed water before sprinkling it over the parishioners and the walls of the church. During the anointing of the altar and the walls of the church with sacred Chrism a consecrated oil used in certain sacraments the bishop spread Chrism over the Altar of Sacrifice before he and Fr. Erbacher anointed the walls of the church with the oil as well.

Pat participated in the anointing of the altar as one of two parishioners who wiped down the altar after it was anointed.

Im extremely happy to have been part of it. I almost teared up a few times, he said. Seeing people in there and knowing it is the first of hundreds of years of worshippers is an amazing feeling.

The bishop also blessed the altar with incense while deacons carried braziers with incense through the aisles to bless the parishioners and walls as well, and the candles surrounding the altar and throughout the church were lit ceremonially.

Bishop Joseph Siegel spreads holy water on The Altar of Sacrifice during the new St. Mary Catholic Church dedication in Ireland on June 28.

Toward the end of the dedication, Fr. Erbacher addressed his congregation.

It has been three years of faith, dedication and love, and I thank you all very much, he said.

Missing from the pews during the dedication was Rita. Despite the decades of prayer and intentional action she dedicated to making the new church a reality, she was not meant to attend Mass in the new building. She passed away a few weeks prior to the dedication. Her funeral Mass held June 29 was the first Mass Fr. Erbacher led in the new church.

Cindy Gress, Rita Gress' daughter-in-law, touches Rita's casket after speaking during her funeral Mass at the new St. Mary Catholic Church in Ireland on June 29.

The Gress family chose to wait to hold her funeral Mass until after the dedication because of how much the church meant to her and how active shed been in bringing the new building to fruition. In the last days of her life, the idea of having her funeral in the new building brought her peace, said her daughter, Carla Allbright of Mitchell.

Although Pat and the rest of his family had hoped Rita would live to see the new church building open, Rita didnt expect to herself, and she seemed at peace with that knowledge. As her tour of the nearly completed church came to an end that day in May, she looked around the nave with tears of joy in her eyes and a smile on her face.

When its all finished, she said, Ill see it from heaven.

Continued here:
Prayers Answered - The Herald

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