IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0057970.html
   My bibliography  Save this article

An Algorithm to Automate Yeast Segmentation and Tracking

Author

Listed:
  • Andreas Doncic
  • Umut Eser
  • Oguzhan Atay
  • Jan M Skotheim

Abstract

Our understanding of dynamic cellular processes has been greatly enhanced by rapid advances in quantitative fluorescence microscopy. Imaging single cells has emphasized the prevalence of phenomena that can be difficult to infer from population measurements, such as all-or-none cellular decisions, cell-to-cell variability, and oscillations. Examination of these phenomena requires segmenting and tracking individual cells over long periods of time. However, accurate segmentation and tracking of cells is difficult and is often the rate-limiting step in an experimental pipeline. Here, we present an algorithm that accomplishes fully automated segmentation and tracking of budding yeast cells within growing colonies. The algorithm incorporates prior information of yeast-specific traits, such as immobility and growth rate, to segment an image using a set of threshold values rather than one specific optimized threshold. Results from the entire set of thresholds are then used to perform a robust final segmentation.

Suggested Citation

  • Andreas Doncic & Umut Eser & Oguzhan Atay & Jan M Skotheim, 2013. "An Algorithm to Automate Yeast Segmentation and Tracking," PLOS ONE, Public Library of Science, vol. 8(3), pages 1-11, March.
    • Handle: RePEc:plo:pone00:0057970
    DOI: 10.1371/journal.pone.0057970
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0057970
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0057970&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0057970?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Stefano Di Talia & Jan M. Skotheim & James M. Bean & Eric D. Siggia & Frederick R. Cross, 2007. "Erratum: The effects of molecular noise and size control on variability in the budding yeast cell cycle," Nature, Nature, vol. 450(7173), pages 1272-1272, December.
    2. Jan M. Skotheim & Stefano Di Talia & Eric D. Siggia & Frederick R. Cross, 2008. "Positive feedback of G1 cyclins ensures coherent cell cycle entry," Nature, Nature, vol. 454(7202), pages 291-296, July.
    3. Stefano Di Talia & Jan M. Skotheim & James M. Bean & Eric D. Siggia & Frederick R. Cross, 2007. "The effects of molecular noise and size control on variability in the budding yeast cell cycle," Nature, Nature, vol. 448(7156), pages 947-951, August.
    4. Sabrina L. Spencer & Suzanne Gaudet & John G. Albeck & John M. Burke & Peter K. Sorger, 2009. "Non-genetic origins of cell-to-cell variability in TRAIL-induced apoptosis," Nature, Nature, vol. 459(7245), pages 428-432, May.
    5. Long Cai & Chiraj K. Dalal & Michael B. Elowitz, 2008. "Frequency-modulated nuclear localization bursts coordinate gene regulation," Nature, Nature, vol. 455(7212), pages 485-490, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chengjun Cao & Keyi Wang & Yina Wang & Tong-Bao Liu & Amariliz Rivera & Chaoyang Xue, 2022. "Ubiquitin proteolysis of a CDK-related kinase regulates titan cell formation and virulence in the fungal pathogen Cryptococcus neoformans," Nature Communications, Nature, vol. 13(1), pages 1-16, December.
    2. repec:plo:pbio00:1000488 is not listed on IDEAS
    3. Andreas P. Cuny & K. Tanuj Sapra & David Martinez-Martin & Gotthold Fläschner & Jonathan D. Adams & Sascha Martin & Christoph Gerber & Fabian Rudolf & Daniel J. Müller, 2022. "High-resolution mass measurements of single budding yeast reveal linear growth segments," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    4. Dola Sengupta & Sandip Kar, 2015. "Are Quasi-Steady-State Approximated Models Suitable for Quantifying Intrinsic Noise Accurately?," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-24, September.
    5. G. Yahya & P. Menges & P. S. Amponsah & D. A. Ngandiri & D. Schulz & A. Wallek & N. Kulak & M. Mann & P. Cramer & V. Savage & M. Räschle & Z. Storchova, 2022. "Sublinear scaling of the cellular proteome with ploidy," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    6. Lucy Ham & Megan A. Coomer & Kaan Öcal & Ramon Grima & Michael P. H. Stumpf, 2024. "A stochastic vs deterministic perspective on the timing of cellular events," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
    7. Anneke Brümmer & Carlos Salazar & Vittoria Zinzalla & Lilia Alberghina & Thomas Höfer, 2010. "Mathematical Modelling of DNA Replication Reveals a Trade-off between Coherence of Origin Activation and Robustness against Rereplication," PLOS Computational Biology, Public Library of Science, vol. 6(5), pages 1-13, May.
    8. Augusto Sales de Queiroz & Guilherme Sales Santa Cruz & Alain Jean-Marie & Dorian Mazauric & Jérémie Roux & Frédéric Cazals, 2022. "Gene prioritization based on random walks with restarts and absorbing states, to define gene sets regulating drug pharmacodynamics from single-cell analyses," PLOS ONE, Public Library of Science, vol. 17(11), pages 1-22, November.
    9. Xiaolu Guo & Adewunmi Adelaja & Apeksha Singh & Roy Wollman & Alexander Hoffmann, 2025. "Modeling heterogeneous signaling dynamics of macrophages reveals principles of information transmission in stimulus responses," Nature Communications, Nature, vol. 16(1), pages 1-17, December.
    10. repec:plo:pcbi00:1002901 is not listed on IDEAS
    11. repec:plo:pone00:0014624 is not listed on IDEAS
    12. repec:plo:pone00:0029716 is not listed on IDEAS
    13. Chad Liu & Chuan-Yuan Li & Fan Yuan, 2014. "Mathematical Modeling of the Phoenix Rising Pathway," PLOS Computational Biology, Public Library of Science, vol. 10(2), pages 1-10, February.
    14. repec:plo:pone00:0153738 is not listed on IDEAS
    15. Vojislav Gligorovski & Ahmad Sadeghi & Sahand Jamal Rahi, 2023. "Multidimensional characterization of inducible promoters and a highly light-sensitive LOV-transcription factor," Nature Communications, Nature, vol. 14(1), pages 1-18, December.
    16. Subhadip Raychaudhuri, 2010. "A Minimal Model of Signaling Network Elucidates Cell-to-Cell Stochastic Variability in Apoptosis," PLOS ONE, Public Library of Science, vol. 5(8), pages 1-7, August.
    17. Leighton T Izu & Tamás Bányász & Ye Chen-Izu, 2015. "Optimizing Population Variability to Maximize Benefit," PLOS ONE, Public Library of Science, vol. 10(12), pages 1-17, December.
    18. C Caranica & A Al-Omari & Z Deng & J Griffith & R Nilsen & L Mao & J Arnold & H-B Schüttler, 2018. "Ensemble methods for stochastic networks with special reference to the biological clock of Neurospora crassa," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-28, May.
    19. Andreas Raue & Marcel Schilling & Julie Bachmann & Andrew Matteson & Max Schelke & Daniel Kaschek & Sabine Hug & Clemens Kreutz & Brian D Harms & Fabian J Theis & Ursula Klingmüller & Jens Timmer, 2013. "Lessons Learned from Quantitative Dynamical Modeling in Systems Biology," PLOS ONE, Public Library of Science, vol. 8(9), pages 1-17, September.
    20. Kazunari Iwamoto & Yuki Shindo & Koichi Takahashi, 2016. "Modeling Cellular Noise Underlying Heterogeneous Cell Responses in the Epidermal Growth Factor Signaling Pathway," PLOS Computational Biology, Public Library of Science, vol. 12(11), pages 1-18, November.
    21. Niklas Kolbe & Lorenz Hexemer & Lukas-Malte Bammert & Alexander Loewer & Mária Lukáčová-Medvid’ová & Stefan Legewie, 2022. "Data-based stochastic modeling reveals sources of activity bursts in single-cell TGF-β signaling," PLOS Computational Biology, Public Library of Science, vol. 18(6), pages 1-29, June.
    22. Artémis Llamosi & Andres M Gonzalez-Vargas & Cristian Versari & Eugenio Cinquemani & Giancarlo Ferrari-Trecate & Pascal Hersen & Gregory Batt, 2016. "What Population Reveals about Individual Cell Identity: Single-Cell Parameter Estimation of Models of Gene Expression in Yeast," PLOS Computational Biology, Public Library of Science, vol. 12(2), pages 1-18, February.
    23. Jan Hasenauer & Christine Hasenauer & Tim Hucho & Fabian J Theis, 2014. "ODE Constrained Mixture Modelling: A Method for Unraveling Subpopulation Structures and Dynamics," PLOS Computational Biology, Public Library of Science, vol. 10(7), pages 1-17, July.
    24. repec:plo:pcbi00:1005122 is not listed on IDEAS
    25. repec:plo:pcbi00:1007374 is not listed on IDEAS
    26. repec:plo:pgen00:1007874 is not listed on IDEAS
    27. Joachim Almquist & Loubna Bendrioua & Caroline Beck Adiels & Mattias Goksör & Stefan Hohmann & Mats Jirstrand, 2015. "A Nonlinear Mixed Effects Approach for Modeling the Cell-To-Cell Variability of Mig1 Dynamics in Yeast," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-32, April.
    28. Szymon Stoma & Alexandre Donzé & François Bertaux & Oded Maler & Gregory Batt, 2013. "STL-based Analysis of TRAIL-induced Apoptosis Challenges the Notion of Type I/Type II Cell Line Classification," PLOS Computational Biology, Public Library of Science, vol. 9(5), pages 1-14, May.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0057970. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.