Document

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