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1 - How to Track Cells and Molecules

from Part I - Physical Tools

Published online by Cambridge University Press:  12 December 2024

Thomas Andrew Waigh
Thomas Andrew Waigh
Affiliation:
University of Manchester
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Summary

Considers how to track cells and molecules. Introduces tracking algorithms and statistical tools to analyse the resultant data.

Keywords

trackcellmoleculesmicroscopy
Type
Chapter
Information
The Physics of Bacteria
From Cells to Biofilms
 , pp. 3 - 21
Publisher: Cambridge University Press
Print publication year: 2024

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References

Suggested Reading

Höfling, F.; Franosch, T., Anomalous transport in the crowded world of biological cells. Reports on Progress in Physics 2013, 76, 046602. Good overview of the experimental evidence for anomalous transport inside cells.CrossRefGoogle ScholarPubMed
Ibe, O. C. Elements of Random Walks and Diffusion Processes. Wiley: 2013. Introduces anomalous transport (e.g. fractional Brownian motion) in an intelligible manner for non-mathematicians. Also acts as a good primer for stochastic processes.CrossRefGoogle Scholar
Klafter, J.; Sokolov, I. M., First Steps in Random Walks: From Tools to Applications. Oxford University Press: 2011. Short and fairly mathematical introduction to some modern models for anomalous transport.CrossRefGoogle Scholar
Waigh, T. A.; Korabel, N., Heterogeneous anomalous transport in molecular and cellular biology. Reports on Progress in Physics 2023, 86, 126601. Considers some challenges in the modelling of anomalous transport in cellular biology e.g. multi-fractal effects.CrossRefGoogle Scholar

References

Lane, N., The unseen world: Reflections on Leeuwenhoek (1677) ‘Concerning little animals’. Philosophical Transactions of the Royal Society B 2015, 370 (1666), 20140344.CrossRefGoogle ScholarPubMed
Mertz, J., Introduction to Optical Microscopy. Cambridge University Press: 2019.CrossRefGoogle Scholar
Perkins, H. T.; Allan, V. J.; Waigh, T. A., Network organisation and the dynamics of tubules in the endoplasmic reticulum. Scientific Reports 2021, 11 (1), 16230.CrossRefGoogle ScholarPubMed
Dubay, M. M.; Acres, J.; Riebeles, M.; Nadeau, J. L., Recent advances in experimental design and data analysis to characterise prokaryotes motility. Journal of Microbiological Methods 2023, 204, 106658.CrossRefGoogle ScholarPubMed
Chen, B. C.; et al., Lattice light-sheet microscopy-imaging molecules to embryos at high spatiotemporal resolution. Science 2014, 346 (6208), 1257998.CrossRefGoogle ScholarPubMed
Wolff, J. O.; Scheiderer, L.; Engelhardt, T.; Maththias, J.; Hell, S. W., MINIFLUX dissects the unimpeded walking of kinesin-1. Science 2023, 379 (6636), 1004–1010.CrossRefGoogle Scholar
Rogers, S. S.; Waigh, T. A.; Zhao, X.; Lu, J. R., Precise particle tracking against a complicated background: Polynomial fitting with Gaussian weight. Physical Biology 2007, 4 (3), 220–227.CrossRefGoogle ScholarPubMed
Helgadottir, S.; Argua, A.; Volpe, G., Digital video microscopy enhanced by deep learning. Optica 2019, 6 (4), 506.CrossRefGoogle Scholar
Szeliski, R., Computer Vision: Algorithms and Applications, 2nd ed. Springer: 2022.CrossRefGoogle Scholar
Waigh, T. A., Advances in the microrheology of complex fluids. Reports on Progress in Physics 2016, 79 (7), 074601.CrossRefGoogle ScholarPubMed
Xu, C.; Zhang, L.; Huang, S.; Ma, T.; Liu, F.; Yonezawa, H.; Zhang, Y.; Xiao, M., Sensing and tracking enhanced by quantum squeezing. Photonics Research 2019, 7 (6), 14.CrossRefGoogle Scholar
Taylor, M. A.; Janousek, J.; Daria, V.; Knittel, J.; Hage, B.; Bachor, H. A.; Bowen, W. P., Biological measurement beyond the quantum limit. Nature Photonics 2013, 7 (3), 229–233.CrossRefGoogle Scholar
Hart, J. W.; Waigh, T. A.; Lu, J. R.; Roberts, I. S., Microrheology and spatial heterogeneity of Staphylococcus aureus biofilms modulated by hydrodynamic shear and biofilm-degrading enzymes. Langmuir 2019, 35 (9), 3553–3561.CrossRefGoogle ScholarPubMed
Rogers, S. S.; van der Walle, C.; Waigh, T. A., Microrheology of bacterial biofilms in vitro: Staphylococcus aureus and Pseudomonas aeruginosa. Langmuir 2008, 24 (23), 13549–13555.CrossRefGoogle ScholarPubMed
Moerner, W. E.; Kardor, L., Optical detection and spectroscopy of single molecules in a solid. PRL 1989, 62 (21), 2535–2538.CrossRefGoogle ScholarPubMed
Leake, M. C., Single-Molecular Cellular Biophysics. Cambridge University Press: 2013.CrossRefGoogle Scholar
Cox, H.; Xu, H.; Waigh, T. A.; Lu, J. R., Single-molecule study of peptide gel dynamics reveals states of prestress. Langmuir 2018, 34 (48), 14678–14689.CrossRefGoogle ScholarPubMed
Cox, H.; Cao, M.; Xu, H.; Waigh, T. A.; Lu, J. R., Active modulation of states of prestress in self-assembled short peptide gels. Biomacromolecules 2019, 20 (4), 1719–1730.CrossRefGoogle ScholarPubMed
Newby, J. M.; Schaefer, A. M.; Lee, P. T.; Forest, M. G.; Lai, S. K., Convolutional neural networks automate detection for tracking of submicron-scale particles in 2D and 3D. Proceedings of the National Academy of Sciences 2018, 115 (36), 9026–9031.CrossRefGoogle ScholarPubMed
Chenouard, N.; et al., Objective comparison of particle tracking methods. Nature Methods 2014, 11 (3), 281–289.CrossRefGoogle ScholarPubMed
Wu, P. H.; Agarwal, A.; Hess, H.; Khargonekar, P. P.; Tseng, Y., Analysis of video-based microscopic particle trajectories using Kalman filtering. Biophysical Journal 2010, 98 (12), 2822–2830.CrossRefGoogle ScholarPubMed
Murphy, K. P., Probabilistic Machine Learning: An Introduction. MIT: 2022.Google Scholar
Waigh, T. A.; Korabel, N., Heterogeneous anomalous transport in cellular and molecular biology. Reports on Progress in Physics 2023, 86 (12), 126601.CrossRefGoogle ScholarPubMed
Dacret, A.; Quardokus, E. M.; Brun, Y. V., MicrobeJ, a tool for high throughput bacterial cell detection and quantitative analysis. Nature Microbiology 2016, 1 (7), 1.Google Scholar
Hartmann, R.; et al., Quantitative image analysis of microbial communities with BiofilmQ. Nature Microbiology 2021, 6 (2), 151.CrossRefGoogle ScholarPubMed
Kopera, B. A. F.; Retsch, M., Computing the 3D radial distribution function from particle positions: An advanced analytic approach. Analytic Chemistry 2018, 90 (23), 13909–13914.CrossRefGoogle ScholarPubMed
Holmes, S.; Huber, W., Modern Statistics for Modern Biology. Cambridge University Press: 2019.Google Scholar
Allen, M. P.; Tildesley, D. J., Computer Simulation of Liquids. Oxford University Press: 2017.CrossRefGoogle Scholar
Hansen, J. P.; McDonald, I. R., Theory of Simple Liquids: With Applications to Soft Matter. Academic Press: 2013.Google Scholar
Metzler, R.; Klafter, J., The restaurant at the end of the random walk. Journal of Physics A: General Physics 2004, 37 (31), R161–R208.CrossRefGoogle Scholar
Han, D.; Korabel, N.; Chen, R.; Johnston, M.; Gavrilova, A.; Allan, V. J.; Fedotov, S.; Waigh, T. A., Deciphering anomalous heterogeneous intracellular transport with neural networks. eLife 2020, 9, e52224.CrossRefGoogle ScholarPubMed
Nielsen, A., Practical Time Series Analysis: Prediction with Statistics and Machine Learning. O’Reilly: 2020.Google Scholar
Hofling, F.; Franosch, T., Anomalous transport in the crowded world of biological cells. Reports on Progress in Physics 2013, 76, 046602.CrossRefGoogle ScholarPubMed
Sornette, D., Critical Phenomena in Natural Sciences. Springer: 2003.Google Scholar
Ibe, O. C., Elements of Random Walks and Diffusion Processes. Wiley: 2013.CrossRefGoogle Scholar
Birkhoff, G. D., Proof of the ergodic theorem. Proceedings of the National Academy of Sciences 1931, 17 (12), 656–660.CrossRefGoogle ScholarPubMed
Korabel, N.; Taloni, A.; Pagnini, G.; Allan, V. J.; Fedotov, S.; Waigh, T. A., Ensemble heterogeneity mimics ageing for endosomal dynamics within eukaryotic cells. Scientific Reports 2023, 13 (1), 8789.CrossRefGoogle ScholarPubMed
Berg, H. C., Random Walks in Biology. Princeton University Press: 1993.Google Scholar
Rogers, S. S.; Flores-Rodriguez, N.; Allan, V. J.; Woodman, P. G.; Waigh, T. A., The first passage probability of intracellular particle trafficking. PCCP 2010, 12 (15), 3753–3761.CrossRefGoogle ScholarPubMed
Aalen, O.; Borgan, O.; Gjessing, H., Survival and Event History Analysis: A Process Point of View. Springer: 2008.CrossRefGoogle Scholar
Blee, J. A.; Roberts, I. S.; Waigh, T. A., Membrane potentials, oxidative stress and the dispersal response of bacterial biofilms to 405 nm light. Physical Biology 2020, 17 (4), 036001.CrossRefGoogle ScholarPubMed
Flores-Rodriguez, N.; Rogers, S. S.; Kenwright, D. A.; Waigh, T. A.; Woodman, P. G.; Allan, V. J., Roles of dynein and dynactin in early endosome dynamics revealed using automated tracking and global analysis. PLOS One 2011, 6 (9), e24479.CrossRefGoogle ScholarPubMed
Redner, S., A Guide to First Passage Processes. Cambridge University Press: 2001.CrossRefGoogle Scholar
Harrison, A. W.; Kenwright, D. A.; Waigh, T. A.; Woodman, P. G.; Allan, V. J., Modes of correlated angular motion in live cells across three distinct time scales. Physical Biology 2013, 10 (3), 036002.CrossRefGoogle ScholarPubMed
Levine, A. J.; Lubensky, T. C., One- and two-particle microrheology. Physical Review Letters 2000, 85, 1774.CrossRefGoogle ScholarPubMed
Vicsek, T.; Czirok, A.; Ben-Jacob, E.; Cohen, I.; Shochet, O., Novel type of phase transition in a system of self-driven particles. Physical Review Letters 1995, 75 (6), 1226–1229.CrossRefGoogle Scholar
Cavagna, A.; Giardina, I.; Grigera, T. S., The physics of flocking: Correlation as a compass from experiments to theory. Physics Reports 2018, 728 (3), 1–62.CrossRefGoogle Scholar
Itto, Y.; Beck, C., Superstatistical modelling of protein diffusion dynamics in bacteria. Journal of the Royal Society – Interface 2021, 18 (176), 20200927.CrossRefGoogle ScholarPubMed
Gittes, F.; Mickey, B.; Nettleton, J.; Howard, J., Flexural rigidity of microtubules and actin filaments measured from thermal fluctuations in shape. Journal of Cellular Biology 1993, 120 (4), 923–934.CrossRefGoogle ScholarPubMed
Monzel, C.; Sengupta, K., Measuring shape fluctuations in biological membranes. Journal of Physics D: Applied Physics 2016, 49 (24), 243002.CrossRefGoogle Scholar
Germain, D.; Leocmach, M.; Gibaud, T., Differential dynamic microscopy to characterize Brownian motion and bacteria motility. American Journal of Physics 2016, 84 (3), 202.CrossRefGoogle Scholar
Berne, B. J.; Percora, R., Dynamic Light Scattering: With Applications to Chemistry, Biology and Physics. Dover: 2003.Google Scholar
Cerbino, R.; Cicuta, P., Perspective: Differential dynamic microscopy extracts multiscale activity in complex fluids and biological systems. Journal of Chemical Physics 2017, 147 (11), 110901.CrossRefGoogle ScholarPubMed
Rigler, R.; Elson, E. S., Fluorescence Correlation Spectroscopy: Theory and Applications. Springer: 2001.CrossRefGoogle Scholar
Stolle, M. D.; Fradin, C., Anomalous diffusion in inverted variable-lengthscale fluorescence correlation spectroscopy. Biophysical Journal 2019, 116 (5), 791–806.CrossRefGoogle ScholarPubMed

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