Research output per year
Research output per year
The physics of biological systems
Physics is important in a wide range of biological systems, from the fluid dynamics of a swimming bacterium to the geometry of root systems. In my lab, we use novel microscopy techniques and advanced image processing algorithms to probe some of these systems. In particular, digital holographic microscopy (DHM) has proved useful in studies of microscopic biological systems. This technique was pioneered in the early 1990s, but modern computing power has opened the method to the non-specialist user. The method allows a sample to be imaged in high speed and in three dimensions, using a standard microscope equipped with a coherent or quasi-coherent light source (typically an LED or a laser). We have applied DHM to several different biological systems, including swimming algae, malaria and leishmania parasites, and planktonic bacteria.
Another method we use for interrogating biological samples is computational scattering. Traditional scattering techniques such as X-ray crystallography have proved invaluable in deducing the structure of proteins. They work by probing a purified sample of many protein molecules with a coherent beam (of X-rays or neutrons, typically) and measuring the pattern of scattered radiation. This scattering pattern can be reverse-engineered to obtain the average underlying structure of the target molecules, which are too small to see by other methods. In most implementations of this technique, information is lost during the scattering/recording process, so computer modelling is required to perform the reverse engineering step (a phenomenon known as the ‘phase problem’). We harness the mathematics of this process, but apply it to much larger samples, such as suspensions of swimming bacteria. Instead of using a beam of high-energy radiation to create a scattering pattern, we image the sample using a conventional microscope and calculate the scattering pattern. In doing so, we retain all information about the sample, allowing us to probe individual and collective dynamics.
Laurence Wilson received his PhD from the University of Edinburgh in 2007, working under Prof. Wilson C.K. Poon on optical force measurements in colloidal suspensions. During a subsequent 3-year postdoctoral position in the same research group, he worked on applying soft matter physics methods to biological systems. In 2010, he won a prestigious Rowland Junior Fellowship at the Rowland Institute at Harvard University (Cambridge, MA, USA). This fellowship allowed him to increase his knowledge of microbiology through collaboration with the labs of Profs. Howard Berg (Harvard) and Jay Tang (Brown), and build up a body of experimental techniques for interrogating biological systems. In 2014, he moved his lab to the University of York to take up a lectureship in the department of physics alongside Prof. Mark Leake, as part of a growing biological physics research theme.
Research output: Contribution to journal › Letter › peer-review
Research output: Contribution to journal › Article › peer-review
Research output: Contribution to journal › Article › peer-review
Wilson, L. G. (Principal investigator)
1/08/24 → 30/04/25
Project: Other project (funded) › Restricted grant
Wilson, L. G. (Principal investigator)
MEDICAL RESEARCH COUNCIL (MRC)
1/07/24 → 30/06/27
Project: Research project (funded) › Research
Bees, M. A. (Principal investigator) & Wilson, L. G. (Co-investigator)
16/03/19 → 15/03/22
Project: Research project (funded) › Research
Wilson, L. G. (Chair)
Activity: Talk or presentation › Public lecture
Wilson, L. G. (Chair)
Activity: Talk or presentation › Public lecture
Wilson, L. G. (Chair)
Activity: Talk or presentation › Invited talk
Wilson, L. G. (Creator), University of York, 16 Jul 2020
DOI: 10.15124/6b44e8e4-a22c-4a55-a2fc-b2976a06d2b4
Dataset
Wilson, L. G. (Creator), University of York, 6 Aug 2019
DOI: 10.15124/7788c73c-f739-4c39-9c5f-066c209e6886
Dataset
Wilson, L. G. (Creator), University of York, 27 Jul 2020
DOI: 10.15124/a8eabcd4-66c1-41a3-aa4b-423921b06568
Dataset