Cyborg sensor could unlock anesthesia’s secrets

Researchers have shown a way to mass-produce devices that could be useful in drug development and a variety of diagnostic tests

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, Univ. of Penn researchers created 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, researchers have shown a way to mass-produce devices that could be useful in drug development and a variety of diagnostic tests.

Their study combines recent advances from several disciplines and labs around campus, including those of A.T. Charlie Johnson, director of Penn’s Nano/Bio Interface Center and professor of physics in Penn Arts & Sciences, Renyu Liu, assistant professor of anesthesiology in the Perelman School of Medicine, and Jeffery Saven, professor of chemistry in Penn Arts & Sciences.

Saven’s and Liu’s groups have used computational techniques to redesign 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 en masse using genetically engineered bacteria, 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 on attaching a similar receptor protein to carbon nanotubes. In that case, the protein was difficult to grow genetically, and needed to include additional biological structures from the receptors’ natural membranes in order to remain stable.

Saven and Liu’s computationally redesigned protein, however, could be readily grown and attached directly to graphene, opening up the possibility of mass-producing biosensor devices that utilize these receptors.

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