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Stargazing in Cells Developing astronomy techniques for the analysis of single molecule data Dan Rolfe & Dave Clarke, STFC Central Laser Facility, Research Complex at Harwell Astronomy • Big, bright objects • Lots of light • Easy to measure...? Astronomy • A long way away • Want to look further (back in time) • Some interesting faint objects e.g. extrasolar planets • Can't make them brighter • Every photon counts Astronomy • Build bigger telescopes But… • £££ • Lots of smaller telescopes to exploit Astronomy • Develop clever analysis techniques • Fancy maths 𝑃 𝐴 𝐵 = • Make most of every photon • Lots of computing power 𝑃 𝐵 𝐴 𝑃(𝐴) 𝑃(𝐵) Hobson & McLachlan, MNRAS 338, 765 (2003) • Astronomy has led the way in developing advanced image analysis techniques Single molecule microscopy • Example motivation - EGFR family • Receptor molecules on cell membrane which act as switches • Interactions control cell growth, death, movement • Malfunction = cancer HER3 • Attach fluorescent labels • Look at in custom microscope EGFR/ HER1 HER2 HER4 FOUR SIGNALLING RECEPTORS ON THE CELL SURFACE Single molecule microscopy • Noisy • Background Bayesian segmentation • Understand noise in images • Calculate relative probability of noise+BG and noise+BG+spot • Detect and measure molecules in nasty sm images Tracking Single Molecules Tracking molecular orientation Further cross-disciplinary benefits • Approach - robust, systematic, quantitative • Lucky imaging approach in nanopositioning • Understand errors, pick fortuitously good measurements to identify different separations 36 nm 60 nm Recent Development – New Method for Single Particle Tracking • “Biggles” from engineering/signal processing • State of the art tracker • Considers and rates all possible tracking solutions • Considers all time points together • Accounts for ambiguity from crowded field properly • "Holy grail" of single particle tracking Summary • Astronomy's need to cherish every photon has produced amazing developments in image and data analysis • Translating these techniques to the newly quantitative world of bioimaging is enabling step changes in understanding disease Acknowledgments CLF-RCaH Chris Tynan Benjamin Coles Dave Clarke Michael Hirsch Dimitris Korovesis Marisa Martin-Fernandez Sarah Needham Selene Roberts Dan Rolfe Stephen Webb Laura Zanetti Domingues Cambridge Mike Hobson Sumeetpal Singh Rich Wareham Daresbury Johannes Kaestner Hannes Loeffler Valeria Losasso Martyn Winn
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