ArticleJournal of immunological methods2015
Integrative analysis of T cell motility from multi-channel microscopy data using TIAM.
Article in Journal of immunological methods, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 11 citations in OpenAlex.
- isMap - immunological synapse map analysis program.Frontiers in immunology · 2026Article
- Interpreting T-cell search "strategies" in the light of evolution under constraints.PLoS computational biology · 2023Article
- In vitro machine learning-based CAR T immunological synapse quality measurements correlate with patient clinical outcomes.PLoS computational biology · 2022Article
- A tissue-like platform for studying engineered quiescent human T-cells' interactions with dendritic cells.eLife · 2019Article
- Cutting Edge: Synapse Propensity of Human Memory CD8 T Cells Confers Competitive Advantage over Naive Counterparts.Journal of immunology (Baltimore, Md. : 1950) · 2019Article
- Durable Interactions of T Cells with T Cell Receptor Stimuli in the Absence of a Stable Immunological Synapse.Cell reports · 2018Article
- T Lymphocyte Migration: An Action Movie Starring the Actin and Associated Actors.Frontiers in immunology · 2015Review
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Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
Abstract
Integrative analytical approaches are needed to study and understand T cell motility as it is a highly coordinated and complex process. Several computational algorithms and tools are available to track motile cells in time-lapse microscopy images. In contrast, there has only been limited effort towards the development of tools that take advantage of multi-channel microscopy data and facilitate integrative analysis of cell-motility. We have implemented algorithms for detecting, tracking, and analyzing cell motility from multi-channel time-lapse microscopy data. We have integrated these into a MATLAB-based toolset we call TIAM (Tool for Integrative Analysis of Motility). The cells are detected by a hybrid approach involving edge detection and Hough transforms from transmitted light images. Cells are tracked using a modified nearest-neighbor association followed by an optimization routine to join shorter segments. Cell positions are used to perform local segmentation for extracting features from transmitted light, reflection and fluorescence channels and associating them with cells and cell-tracks to facilitate integrative analysis. We found that TIAM accurately captures the motility behavior of T cells and performed better than DYNAMIK, Icy, Imaris, and Volocity in detecting and tracking motile T cells. Extraction of cell-associated features from reflection and fluorescence channels was also accurate with less than 10% median error in measurements. Finally, we obtained novel insights into T cell motility that were critically dependent on the unique capabilities of TIAM. We found that 1) the CD45RO subset of human CD8 T cells moved faster and exhibited an increased propensity to attach to the substratum during CCL21-driven chemokinesis when compared to the CD45RA subset; and 2) attachment area and arrest coefficient during antigen-induced motility of the CD45A subset is correlated with surface density of integrin LFA1 at the contact.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.