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Abstract IntroductionTraction force microscopy (TFM) is a widely used technique to measure cell contractility on compliant substrates that mimic the stiffness of human tissues. For every step in a TFM workflow, users make choices which impact the quantitative results, yet many times the rationales and consequences for making these decisions are unclear. We have found few papers which show the complete experimental and mathematical steps of TFM, thus obfuscating the full effects of these decisions on the final output. MethodsTherefore, we present this “Field Guide” with the goal to explain the mathematical basis of common TFM methods to practitioners in an accessible way. We specifically focus on how errors propagate in TFM workflows given specific experimental design and analytical choices. ResultsWe cover important assumptions and considerations in TFM substrate manufacturing, substrate mechanical properties, imaging techniques, image processing methods, approaches and parameters used in calculating traction stress, and data-reporting strategies. ConclusionsBy presenting a conceptual review and analysis of TFM-focused research articles published over the last two decades, we provide researchers in the field with a better understanding of their options to make more informed choices when creating TFM workflows depending on the type of cell being studied. With this review, we aim to empower experimentalists to quantify cell contractility with confidence.
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A Perspective on Developing Modeling and Image Analysis Tools to Investigate Mechanosensing Proteins
Synopsis The shift of funding organizations to prioritize interdisciplinary work points to the need for workflow models that better accommodate interdisciplinary studies. Most scientists are trained in a specific field and are often unaware of the kind of insights that other disciplines could contribute to solving various problems. In this paper, we present a perspective on how we developed an experimental pipeline between a microscopy and image analysis/bioengineering lab. Specifically, we connected microscopy observations about a putative mechanosensing protein, obscurin, to image analysis techniques that quantify cell changes. While the individual methods used are well established (fluorescence microscopy; ImageJ WEKA and mTrack2 programs; MATLAB), there are no existing best practices for how to integrate these techniques into a cohesive, interdisciplinary narrative. Here, we describe a broadly applicable workflow of how microscopists can more easily quantify cell properties (e.g., perimeter, velocity) from microscopy videos of eukaryotic (MDCK) adherent cells. Additionally, we give examples of how these foundational measurements can create more complex, customizable cell mechanics tools and models.
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- Award ID(s):
- 2233770
- PAR ID:
- 10456665
- Publisher / Repository:
- Oxford University Press
- Date Published:
- Journal Name:
- Integrative And Comparative Biology
- ISSN:
- 1540-7063
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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