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Automated tracking of label-free cells with enhanced recognition of whole tracks.

ABSTRACT: Migration and interactions of immune cells are routinely studied by time-lapse microscopy of in vitro migration and confrontation assays. To objectively quantify the dynamic behavior of cells, software tools for automated cell tracking can be applied. However, many existing tracking algorithms recognize only rather short fragments of a whole cell track and rely on cell staining to enhance cell segmentation. While our previously developed segmentation approach enables tracking of label-free cells, it still suffers from frequently recognizing only short track fragments. In this study, we identify sources of track fragmentation and provide solutions to obtain longer cell tracks. This is achieved by improving the detection of low-contrast cells and by optimizing the value of the gap size parameter, which defines the number of missing cell positions between track fragments that is accepted for still connecting them into one track. We find that the enhanced track recognition increases the average length of cell tracks up to 2.2-fold. Recognizing cell tracks as a whole will enable studying and quantifying more complex patterns of cell behavior, e.g. switches in migration mode or dependence of the phagocytosis efficiency on the number and type of preceding interactions. Such quantitative analyses will improve our understanding of how immune cells interact and function in health and disease.

SUBMITTER: Al-Zaben N

PROVIDER: S-EPMC6397148 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

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Automated tracking of label-free cells with enhanced recognition of whole tracks.

Al-Zaben Naim N Medyukhina Anna A Dietrich Stefanie S Marolda Alessandra A Hünniger Kerstin K Kurzai Oliver O Figge Marc Thilo MT

Scientific reports 20190301 1

Migration and interactions of immune cells are routinely studied by time-lapse microscopy of in vitro migration and confrontation assays. To objectively quantify the dynamic behavior of cells, software tools for automated cell tracking can be applied. However, many existing tracking algorithms recognize only rather short fragments of a whole cell track and rely on cell staining to enhance cell segmentation. While our previously developed segmentation approach enables tracking of label-free cells ...[more]

PMID: 30824740

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Project description:Extracellular vesicles (EVs) that circulate in body fluids possess significant potential for disease diagnosis. Their use in clinical settings, however, has been limited owing to lack of simple and robust isolation methods. To rectify this problem, a centrifugal device for automatic, fast, and efficient isolation of EVs from whole-blood, called Exodisc-B is presented in this paper. Methods: The device comprises a built-in chamber to facilitate plasma separation and two nanoporous filters-one for removing larger particles and the other for enriching EVs. The performance of the device in comparison to ultracentrifugation (UC) was evaluated by analyzing the yield, purity, protein and RNA content of the isolated EVs. Additionally, the EV protein marker expressions were measured by ELISA and statistically analyzed to differentiate prostate cancer patients from healthy donors. Results: Compared with the UC technique, the proposed device is capable of isolating at least an order of magnitude higher number of EVs with about 30-fold higher mRNA count within 40 min. Sandwich ELISA of EV-specific membrane proteins-CD9-CD81-confirmed that Exodisc-B can isolate EVs from a volume of whole blood as low as 30 µL with a capture efficiency exceeding 75%. The device also facilitates temporal monitoring of tumor progression within live mouse xenograft models over a period of 13 weeks while using minimal volumes of weekly collected blood samples. Further, in ELISA analyses of multiple cancer-related proteins, such as prostate-specific antigen (PSA), prostate-specific membrane antigen (PSMA), epithelial cell adhesion molecule (EpCAM), epidermal growth factor receptor 1 (EGFR1), and heat shock protein 90 (HSP90), extracted from EVs isolated from human plasma, 43 patients were differentiated from 30 healthy donors. Conclusion: The results demonstrated the ability of Exodisc-B to provide a rapid, sensitive, and point-of-care-type method for extracting intact EVs from small volumes of clinical blood samples for disease diagnosis and monitoring.

Dataset Information

Automated tracking of label-free cells with enhanced recognition of whole tracks.

Publications

Automated tracking of label-free cells with enhanced recognition of whole tracks.

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