Single-particle tracking

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Principle of single-particle tracking: The rectangles represent frames from an image acquisition at times t = 0, 1, 2, ... The tracked particles are represented as red circles, and in the last frame, the reconstructed trajectories are shown as blue lines

Single-particle tracking (SPT) is the observation of the motion of individual particles within a medium. The coordinates time series, which can be either in two dimensions (x, y) or in three dimensions (x, y, z), is referred to as a trajectory. The trajectory is typically analyzed using statistical methods to extract information about the underlying dynamics of the particle.[1][2][3] These dynamics can reveal information about the type of transport being observed (e.g., thermal or active), the medium where the particle is moving, and interactions with other particles. In the case of random motion, trajectory analysis can be used to measure the diffusion coefficient.

Applications

In life sciences, single-particle tracking is broadly used to quantify the dynamics of molecules/proteins in live cells (of bacteria, yeast, mammalian cells and live Drosophila embryos).[4][5][6][7][8] It has been extensively used to study the transcription factor dynamics in live cells.[9][10][11] This method has been extensively used in the last decade to understand the target-search mechanism of proteins in live cells. It addresses fundamental biological questions such as how a protein of interest finds its target in the complex cellular environment? how long does it take to find its target site for binding? what is the residence time of proteins binding to DNA?[5] Recently, SPT has been used to study the kinetics of protein translating and processing in vivo. For molecules which bind large structures such as ribosomes, SPT can be used to extract information about the binding kinetics. As ribosome binding increases the effective size of the smaller molecule, the diffusion rate decreases upon binding. By monitoring these changes in diffusion behavior, direct measurements of binding events are obtained.[12][13] Furthermore, exogenous particles are employed as probes to assess the mechanical properties of the medium, a technique known as passive microrheology.[14] This technique has been applied to investigate the motion of lipids and proteins within membranes,[15][16] molecules in the nucleus [8] and cytoplasm,[17] organelles and molecules therein,[18] lipid granules,[19][20][21] vesicles, and particles introduced in the cytoplasm or the nucleus. Additionally, single-particle tracking has been extensively used in the study of reconstituted lipid bilayers,[22] intermittent diffusion between 3D and either 2D (e.g., a membrane) [23] or 1D (e.g., a DNA polymer) phases, and synthetic entangled actin networks.[24][25]

Methods

The most common type of particles used in single particle tracking are based either on scatterers, such as polystyrene beads or gold nanoparticles that can be tracked using bright field illumination, or fluorescent particles. For fluorescent tags, there are many different options with their own advantages and disadvantages, including quantum dots, fluorescent proteins, organic fluorophores, and cyanine dyes.

On a fundamental level, once the images are obtained, single-particle tracking is a two step process. First the particles are detected and then the localized different particles are connected in order to obtain individual trajectories.

Besides performing particle tracking in 2D, there are several imaging modalities for 3D particle tracking, including multifocal plane microscopy,[26] double helix point spread function microscopy,[27] and introducing astigmatism via a cylindrical lens or adaptive optics.

Brownian diffusion

Main page: Brownian motion

See also

References

  1. Metzler, Ralf; Jeon, Jae-Hyung; Cherstvy, Andrey G.; Barkai, Eli (2014). "Anomalous diffusion models and their properties: non-stationarity, non-ergodicity, and ageing at the centenary of single particle tracking". Phys. Chem. Chem. Phys. 16 (44): 24128–24164. doi:10.1039/c4cp03465a. ISSN 1463-9076. PMID 25297814. Bibcode2014PCCP...1624128M. 
  2. Manzo, Carlo; Garcia-Parajo, Maria F (2015-10-29). "A review of progress in single particle tracking: from methods to biophysical insights". Reports on Progress in Physics 78 (12): 124601. doi:10.1088/0034-4885/78/12/124601. ISSN 0034-4885. PMID 26511974. Bibcode2015RPPh...78l4601M. 
  3. Anthony, Stephen; Zhang, Liangfang; Granick, Steve (2006). "Methods to Track Single-Molecule Trajectories". Langmuir 22 (12): 5266–5272. doi:10.1021/la060244i. ISSN 0743-7463. PMID 16732651. 
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  5. 5.0 5.1 Podh, Nitesh Kumar; Paliwal, Sheetal; Dey, Partha; Das, Ayan; Morjaria, Shruti; Mehta, Gunjan (5 November 2021). "In-vivo Single-Molecule Imaging in Yeast: Applications and Challenges". Journal of Molecular Biology 433 (22): 167250. doi:10.1016/j.jmb.2021.167250. PMID 34537238. 
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  7. Mir, Mustafa; Reimer, Armando; Stadler, Michael; Tangara, Astou; Hansen, Anders S.; Hockemeyer, Dirk; Eisen, Michael B.; Garcia, Hernan et al. (2018), Lyubchenko, Yuri L., ed., "Single Molecule Imaging in Live Embryos Using Lattice Light-Sheet Microscopy", Nanoscale Imaging: Methods and Protocols, Methods in Molecular Biology (New York: Springer) 1814: pp. 541–559, doi:10.1007/978-1-4939-8591-3_32, ISBN 978-1-4939-8591-3, PMID 29956254 
  8. 8.0 8.1 Ball, David A.; Mehta, Gunjan D.; Salomon-Kent, Ronit; Mazza, Davide; Morisaki, Tatsuya; Mueller, Florian; McNally, James G.; Karpova, Tatiana S. (December 2016). "Single molecule tracking of Ace1p in Saccharomyces cerevisiae defines a characteristic residence time for non-specific interactions of transcription factors with chromatin". Nucleic Acids Research 44 (21): e160. doi:10.1093/nar/gkw744. ISSN 0305-1048. PMID 27566148. 
  9. Mehta, Gunjan D.; Ball, David A.; Eriksson, Peter R.; Chereji, Razvan V.; Clark, David J.; McNally, James G.; Karpova, Tatiana S. (2018-12-06). "Single-Molecule Analysis Reveals Linked Cycles of RSC Chromatin Remodeling and Ace1p Transcription Factor Binding in Yeast". Molecular Cell 72 (5): 875–887.e9. doi:10.1016/j.molcel.2018.09.009. ISSN 1097-2765. PMID 30318444. 
  10. Morisaki, Tatsuya; Müller, Waltraud G.; Golob, Nicole; Mazza, Davide; McNally, James G. (2014-07-18). "Single-molecule analysis of transcription factor binding at transcription sites in live cells". Nature Communications 5 (1): 4456. doi:10.1038/ncomms5456. ISSN 2041-1723. PMID 25034201. Bibcode2014NatCo...5.4456M. 
  11. Presman, Diego M.; Ball, David A.; Paakinaho, Ville; Grimm, Jonathan B.; Lavis, Luke D.; Karpova, Tatiana S.; Hager, Gordon L. (2017-07-01). "Quantifying transcription factor binding dynamics at the single-molecule level in live cells". Methods. The 4D Nucleome 123: 76–88. doi:10.1016/j.ymeth.2017.03.014. ISSN 1046-2023. PMID 28315485. 
  12. Volkov, Ivan L.; Lindén, Martin; Aguirre Rivera, Javier; Ieong, Ka-Weng; Metelev, Mikhail; Elf, Johan; Johansson, Magnus (June 2018). "tRNA tracking for direct measurements of protein synthesis kinetics in live cells". Nature Chemical Biology 14 (6): 618–626. doi:10.1038/s41589-018-0063-y. ISSN 1552-4469. PMID 29769736. 
  13. Metelev, Mikhail; Volkov, Ivan L.; Lundin, Erik; Gynnå, Arvid H.; Elf, Johan; Johansson, Magnus (2020-10-12). "Direct measurements of mRNA translation kinetics in living cells". Nature Communications 13 (1): 1852. doi:10.1038/s41467-022-29515-x. PMID 35388013. 
  14. Wirtz, Denis (2009). "Particle-Tracking Microrheology of Living Cells: Principles and Applications". Annual Review of Biophysics 38 (1): 301–326. doi:10.1146/annurev.biophys.050708.133724. ISSN 1936-122X. PMID 19416071. 
  15. Saxton, Michael J.; Jacobson, Ken (1997). "Single-Particle Tracking: Applications to Membrane Dynamics". Annual Review of Biophysics and Biomolecular Structure 26: 373–399. doi:10.1146/annurev.biophys.26.1.373. PMID 9241424. 
  16. Krapf, Diego (2015), "Mechanisms Underlying Anomalous Diffusion in the Plasma Membrane", Lipid Domains, Current Topics in Membranes, 75, Elsevier, pp. 167–207, doi:10.1016/bs.ctm.2015.03.002, ISBN 9780128032954, PMID 26015283, http://linkinghub.elsevier.com/retrieve/pii/S1063582315000034, retrieved 2018-08-20 
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  18. Nixon-Abell, Jonathon; Obara, Christopher J.; Weigel, Aubrey V.; Li, Dong; Legant, Wesley R.; Xu, C. Shan; Pasolli, H. Amalia; Harvey, Kirsten et al. (2016-10-28). "Increased spatiotemporal resolution reveals highly dynamic dense tubular matrices in the peripheral ER". Science 354 (6311): aaf3928. doi:10.1126/science.aaf3928. ISSN 0036-8075. PMID 27789813. 
  19. Tolić-Nørrelykke, Iva Marija (2004). "Anomalous Diffusion in Living Yeast Cells". Physical Review Letters 93 (7): 078102. doi:10.1103/PhysRevLett.93.078102. PMID 15324280. Bibcode2004PhRvL..93g8102T. 
  20. Jeon, Jae-Hyung (2011). "In Vivo Anomalous Diffusion and Weak Ergodicity Breaking of Lipid Granules". Physical Review Letters 106 (4): 048103. doi:10.1103/PhysRevLett.106.048103. PMID 21405366. Bibcode2011PhRvL.106d8103J. 
  21. Chen, Yu; Rees, Thomas W; Ji, Liangnian; Chao, Hui (2018). "Mitochondrial dynamics tracking with iridium(III) complexes". Current Opinion in Chemical Biology 43: 51–57. doi:10.1016/j.cbpa.2017.11.006. ISSN 1367-5931. PMID 29175532. 
  22. Knight, Jefferson D.; Falke, Joseph J. (2009). "Single-Molecule Fluorescence Studies of a PH Domain: New Insights into the Membrane Docking Reaction". Biophysical Journal 96 (2): 566–582. doi:10.1016/j.bpj.2008.10.020. ISSN 0006-3495. PMID 19167305. Bibcode2009BpJ....96..566K. 
  23. Campagnola, Grace; Nepal, Kanti; Schroder, Bryce W.; Peersen, Olve B.; Krapf, Diego (2015-12-07). "Superdiffusive motion of membrane-targeting C2 domains". Scientific Reports 5 (1): 17721. doi:10.1038/srep17721. ISSN 2045-2322. PMID 26639944. Bibcode2015NatSR...517721C. 
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  25. Wang, Bo; Anthony, Stephen M.; Bae, Sung Chul; Granick, Steve (2009-09-08). "Anomalous yet Brownian". Proceedings of the National Academy of Sciences 106 (36): 15160–15164. doi:10.1073/pnas.0903554106. PMID 19666495. Bibcode2009PNAS..10615160W. 
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