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Vesicle at the cell surface over time. The track shows where it moves to and the 'contours' shows where molecules/mountains are. This shows the biological data combined with the mathematical model.

The University has challenged a long-held theory about the way cells behave on the nanoscale, which could revolutionise future research into diabetes and neurological treatments.

Biologists have long agreed that cells that secrete hormones, like insulin, or neurotransmitters, like serotonin, package their cargo in vesicles (bubble-like intra-cellular structure) and move them in a very regulated way, following the same paths to similar places in the cells, akin to a railroad.

The integration of cutting-edge microscopy, with cell biology and mathematical modelling, could be applied to many other problems in biomedicine and will accelerate discovery in the years to come.

Professor Rory Duncan, Institute of Biological Chemistry, Biophysics and Bioengineering

Although the world's most powerful microscopes couldn't see these specific tracks, biologists were convinced they were there because of the observed behaviour of the vesicles. Clusters of nano-sized molecules inside cells were believed to overlap with the vesicles but this theory has now been challenged using state-of-the-art mathematical modelling.

To test the theory, Professor Rory Duncan, Head of the Institute for Biological Chemistry, Biophysics & Bioengineering worked with Professor Gabriel Lord from the School of Mathematical & Computer Sciences.

Using new ‘super-resolution' microscopy techniques, the team mapped the positions of hundreds of thousands of molecules within the cells on a nanoscale (as small to humans as Jupiter is large to us). These molecular data (known as ‘big-data' due to the large amount of information generated) proved ideal for mathematical analysis.

Professor Lord explains: “One of Heriot-Watt's strengths is cross-disciplinary working. Together with our colleagues in Biology, we approached how these cells behave in a radically new way, asking what if the vesicles don't follow paths to special molecular depots inside cells, but instead avoid the cluster of molecules, like a boulder does when following a valley between mountains?

“Working with the biology team and combining microscopy information from diverse experiments into a ‘mathematical model,' we were able to run multiple experiments on a computer that aren't possible in the real world.”

Professor Rory Duncan continued: “In contrast to what biology theorised, vesicles actually avoid areas in the cell previously thought to attract them, following ‘valleys' in between groups of the specific molecules known to drive secretion. The net result to the observer is the same – vesicles re-use similar routes and move to nearly identical places in the cell, but the mechanism is the opposite of previous thinking, and the physical tracks do not exist.

“Our new approach allows us to run experiments on the computer and our resulting model predicts how the vesicles and molecules behave in cells, particularly if they are disrupted or mutated, as happens in disease states.

“This predictive ability is powerful because it tells biologists which molecules to target in future studies and lays the way for larger and more thorough modelling of complex biological processes.

“These findings have wide-reaching possibilities for studying cellular dynamics. For example, when something goes wrong with the transport of neurotransmitters in these vesicles, it leads to a variety of neurological disorders. We don't yet know what goes wrong but now we are starting to understand how cells behave at a molecular level, science may be able to make breakthroughs for conditions like epilepsy or diabetes.

“The integration of cutting-edge microscopy, with cell biology and mathematical modelling, could be applied to many other problems in biomedicine and will accelerate discovery in the years to come.”

The work was funded through the Next Generation Optical Microscopy Initiative, led by the Medical Research Council (MRC), and with co-funding from the Biotechnology and Biological Sciences Research Council (BBSRC) and the Engineering and Physical Sciences Research Council (EPSRC). Funding was also received from Wellcome.

The research was published in the journal, Current Biology.