Recipient organisationUniversity of ExeterSource-published name: University of Exeter
Funding£2.1M
PeriodMar 2019 — Sept 2022
In plain English
AI plain-English summary
A new optical tweezer technology will measure the tiny forces—down to a millionth of a billionth of a Newton—that enzymes exert as they change shape during chemical reactions. Current single-molecule techniques cannot detect these femto-Newton forces, leaving a blind spot in understanding how enzymes, the molecular machines driving nearly all biochemistry, actually work. This programme will build nanosensors sensitive enough to probe those forces, revealing the mechanical motions enzymes undergo while catalysing reactions. The researchers will also use the sensors to manipulate enzyme movements, potentially controlling their activity. If successful, the technology could transform how fungal bloodstream infections—which cause around 250,000 cases per year—are diagnosed. By attaching enzymes that break down sugars on the cell walls of *Candida albicans*, the nanosensors would detect pathogen-specific signals far faster than current culture-based methods. The approach will be tested on clinical samples from a lab in Cape Town, South Africa. Beyond diagnostics, the work is fundamentally about understanding nature’s design principles for nanomachines, which could eventually guide the engineering of custom enzymes for chemical or medical tasks.
View original technical description
Laser light can be used to perform multiple roles, including sensing, manipulating and moving objects within a laser trap (so-called optical tweezers). It is remarkable that the application of light allows one to exert minute optical forces on individual protein molecules. By pulling on individual molecules it has been possible to study DNA and protein structures in great detail. The pulling and unfolding of proteins has revealed the intramolecular forces that give them their three-dimensional structure. Optical tweezer experiments have also allowed the direct measurement of pico-Newton forces that are exerted by individual motor proteins. However, optical tweezers and other single-molecule techniques are currently not sensitive enough to resolve femto-Newton (fN) forces, and hence not all molecular forces can yet be investigated. An important, but so far poorly understood example is the miniscule fN forces that are exerted by active enzymes when they are catalysing reactions in living systems. This research programme will develop an entirely novel and much more sensitive alternative optical tweezer technology. The nanosensors developed in this programme will provide optical 'hands' that can probe and feel-out fN forces of enzymes. This allows precise sensing of the energetics of conformational changes of enzymes, i.e. their own deforming motion, for the first time. Such measurements will provide fundamental insights into the forces that drive the conformational changes that are required for catalysis. We will visualise the enzyme movements and this will allow us to develop more accurate models to predict how these very important molecular machines function. Our approach will unravel nature's design principles for a class of nanomachines that carry out most of the important biochemistry and molecular signalling that make our bodies work. The technology developed in this programme will not only sense forces exerted by enzymes, but allows us to manipulate the complex motions of active enzymes. Such control offers the possibility of making some patterns of molecular organisation in an enzyme more likely than another, and can be used to control enzymatic activity. Demonstrating this capability will prepare the ground for future manipulation and exploitation of synthetic biomolecular machinery and designing enzymes for specific chemical or medical tasks. Our pathway to impact work will demonstrate the extreme sensitivity of our technology in healthcare diagnostic tests that we will develop for human pathogens. Nanosensors will be modified by attaching enzymes. This will allow us to measure pathogen-specific signals during enzymatic breakdown of different sugars present on cell-walls of the human fungal pathogen Candida albicans - a pathogenic fungus that causes around 250,000 blood stream infections per year. This measurement will enable a more rapid identification of fungal pathogens than current microbial diagnostics of infections based on cell cultures. This approach will be tested on samples provided by the Fungal Immunology Group, AFGrica, located in Cape Town, South Africa.
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