Almost every biological process involves sensing the presence of a certain chemical. Finely tuned over millions of years of evolution, the body's different receptors are shaped to accept certain target chemicals. When they bind, the receptors tell their host cells to produce nerve impulses, regulate metabolism, defend the body against invaders or myriad other actions depending on the cell, receptor and chemical type.

Now, researchers from the University of Pennsylvania have led an effort to create an artificial chemical sensor based on one of the human body's most important receptors, one that is critical in the action of painkillers and anesthetics. In these devices, the receptors' activation produces an electrical response rather than a biochemical one, allowing that response to be read out by a computer.

By attaching a modified version of this mu-opioid receptor to strips of graphene, they have shown a way to mass produce devices that could be useful in drug development and a variety of diagnostic tests. And because the mu-opioid receptor belongs to the most common class of such chemical sensors, the findings suggest that the same technique could be applied to detect a wide range of biologically relevant chemicals.

The study, published in the journal Nano Letters, was led by A.T. Charlie Johnson, director of Penn's Nano/Bio Interface Center and professor of physics in Penn's School of Arts & Sciences; Renyu Liu, assistant professor of anesthesiology in Penn's Perelman School of Medicine; and Mitchell Lerner, then a graduate student in Johnson's lab. It was made possible through a collaboration with Jeffery Saven, professor of chemistry in Penn Arts & Sciences. The Penn team also worked with researchers from the Seoul National University in South Korea.

Their study combines recent advances from several disciplines.

Johnson's group has extensive experience attaching biological components to nanomaterials for use in chemical detectors. Previous studies have involved wrapping carbon nanotubes with single-stranded DNA to detect odors related to cancer andattaching antibodies to nanotubes to detect the presence of the bacteria associated with Lyme disease.

The groups of Saven and Liu have used computational techniques toredesign the mu-opioid receptor to make it easier to use in research. In its natural state, the receptor is not water soluble, making many common experimental techniques impossible. Worse, proteins like this receptor would normally be grown in genetically engineered bacteria to generate the quantity necessary for extensive study, but parts of the natural mu-opioid receptor are toxic to the E. coli used in this method.

After Saven and Liu addressed these problems with the redesigned receptor, they saw that it might be useful to Johnson, who had previously published a study onattaching a similar receptor protein to carbon nanotubes. In that case, the protein was difficult to grow genetically, and Johnson and his colleagues also needed to include additional biological structures from the receptors' natural membranes in order to keep them stable.

In contrast, the computationally redesigned protein could be readily grown and attached directly to graphene, opening up the possibility of mass producing biosensor devices that utilize these receptors.

"Due to the challenges associated with isolating these receptors from their membrane environment without losing functionality," Liu said, "the traditional methods of studying them involved indirectly investigating the interactions between opioid and the receptor via radioactive or fluorescent labeled ligands, for example. This multi-disciplinary effort overcame those difficulties, enabling us to investigate these interactions directly in a cell free system without the need to label any ligands."

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Graphene and painkiller receptor combined into scalable chemical sensor