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3D time-lapse microscopy paired with endpoint lineage analysis in mouse blastocysts.

ABSTRACT: Determining how signaling dynamics relate to gene expression and cell fate is essential to understanding multicellular development. We present a unified live imaging and lineage analysis method that allows integrated analysis of both techniques in the same mouse embryos. This protocol describes the embryo isolation, confocal imaging, immunofluorescence, and in silico alignment required to connect time-lapse and endpoint measurements. By utilizing different biosensors and fixed readouts, this method allows interrogation of signaling dynamics that specify cell fates in developing embryos. For complete details on the use and execution of this protocol, please refer to Pokrass et al. (2020).

SUBMITTER: Pokrass MJ

PROVIDER: S-EPMC8055709 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature

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3D time-lapse microscopy paired with endpoint lineage analysis in mouse blastocysts.

Pokrass Michael J MJ Regot Sergi S

STAR protocols 20210408 2

Determining how signaling dynamics relate to gene expression and cell fate is essential to understanding multicellular development. We present a unified live imaging and lineage analysis method that allows integrated analysis of both techniques in the same mouse embryos. This protocol describes the embryo isolation, confocal imaging, immunofluorescence, and <i>in silico</i> alignment required to connect time-lapse and endpoint measurements. By utilizing different biosensors and fixed readouts, t ...[more]

PMID: 33899025

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Project description:The objective of this study was to evaluate the time of blastulation monitored by time-lapse technology to predict in vitro viability of bovine blastocysts. This technology can be a powerful tool for bovine embryos selection with higher implantation capacity and competence. Also, in humans an early blastulation is associated with higher quality and pregnancy rate. Cumulus oocyte complexes (COCs) were matured for 20 to 22 h and then fertilized by co-incubation of COCs and spermatozoa (10,000 sperm per oocyte) for 18 h. Presumptive zygotes were placed individually in microwells, in droplets of commercial culture medium. The Primo Vision TL system (EVO+; Vitrolife) captured digital images of developing embryos every 15 minutes. The time frame from IVF to the start of blastulation (tSB) and to blastocyst development (tB) was recorded. After day 7.5, the blastocysts were in vitro culture for 48 h until day 9.5 after IVF to evaluate post hatching development. In vitro viability was evaluated at day 9.5: those with a diameter greater than 200 μm and a total cell count greater than 180 were classified as viable (value 1), while the rest were classified as non in vitro viable (value 0). The area under the ROC curve (AUC) was estimated to determine the predictive power of in vitro viability through blastulation time. In addition, binary logistic regression analysis was used to generate a mathematical model with morphokinetic variables that allow the best prediction of in vitro viability. In 13 sessions, the blastocyst production rate was 46.2% (96/208). The cut-off time to discriminate early or late blastulation was 149.8 h. The post-hatching development of the embryos with early blastulation was 63.3% (31/49), being statistically superior (p = 0.001) than the late blastulation group 14.9% (7/47). Likewise, the time of blastulation showed an accuracy of 90.8% (p < 0.001) in predicting in vitro viability of bovine blastocysts. In conclusion, the selection of blastocysts based on blastulation time (< 155 h) and blastocyst diameter measured on day 7.5 after IVF (> 180 μm) maximizes the in vitro viability.

Project description:BackgroundThe software available to date for analyzing image sequences from time-lapse microscopy works only for certain bacteria and under limited conditions. These programs, mostly MATLAB-based, fail for microbes with irregular shape, indistinct cell division sites, or that grow in closely packed microcolonies. Unfortunately, many organisms of interest have these characteristics, and analyzing their image sequences has been limited to time consuming manual processing.ResultsHere we describe BactImAS - a modular, multi-platform, open-source, Java-based software delivered both as a standalone program and as a plugin for Icy. The software is designed for extracting and visualizing quantitative data from bacterial time-lapse movies. BactImAS uses a semi-automated approach where the user defines initial cells, identifies cell division events, and, if necessary, manually corrects cell segmentation with the help of user-friendly GUI and incorporated ImageJ application. The program segments and tracks cells using a newly-developed algorithm designed for movies with difficult-to-segment cells that exhibit small frame-to-frame differences. Measurements are extracted from images in a configurable, automated fashion and an SQLite database is used to store, retrieve, and exchange all acquired data. Finally, the BactImAS can generate configurable lineage tree visualizations and export data as CSV files. We tested BactImAS on time-lapse movies of Mycobacterium smegmatis and achieved at least 10-fold reduction of processing time compared to manual analysis. We illustrate the power of the visualization tool by showing heterogeneity of both icl expression and cell growth atop of a lineage tree.ConclusionsThe presented software simplifies quantitative analysis of time-lapse movies overall and is currently the only available software for the analysis of mycobacteria-like cells. It will be of interest to the community of both end-users and developers of time-lapse microscopy software.

Dataset Information

3D time-lapse microscopy paired with endpoint lineage analysis in mouse blastocysts.

Publications

3D time-lapse microscopy paired with endpoint lineage analysis in mouse blastocysts.

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