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Dynamical analysis of bacteria in microscopy movies.

ABSTRACT: Recent advances in microscopy, computing power and image processing have enabled the analysis of ever larger datasets of movies of microorganisms to study their behaviour. However, techniques for analysing the dynamics of individual cells from such datasets are not yet widely available in the public domain. We recently demonstrated significant phenotypic heterogeneity in the adhesion of Escherichia coli bacteria to glass surfaces using a new method for the high-throughput analysis of video microscopy data. Here, we present an in-depth analysis of this method and its limitations, and make public our algorithms for following the positions and orientations of individual rod-shaped bacteria from time-series of 2D images to reconstruct their trajectories and characterise their dynamics. We demonstrate in detail how to use these algorithms to identify different types of adhesive dynamics within a clonal population of bacteria sedimenting onto a surface. The effects of measurement errors in cell positions and of limited trajectory durations on our results are discussed.

SUBMITTER: Vissers T

PROVIDER: S-EPMC6553751 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Dynamical analysis of bacteria in microscopy movies.

Vissers Teun T Koumakis Nick N Hermes Michiel M Brown Aidan T AT Schwarz-Linek Jana J Dawson Angela A Poon Wilson C K WCK

PloS one 20190606 6

Recent advances in microscopy, computing power and image processing have enabled the analysis of ever larger datasets of movies of microorganisms to study their behaviour. However, techniques for analysing the dynamics of individual cells from such datasets are not yet widely available in the public domain. We recently demonstrated significant phenotypic heterogeneity in the adhesion of Escherichia coli bacteria to glass surfaces using a new method for the high-throughput analysis of video micro ...[more]

PMID: 31170194

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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.

Project description:BackgroundMany biological specimens, such as living cells and their intracellular components, often exhibit very little amplitude contrast, making it difficult for conventional bright field microscopes to distinguish them from their surroundings. To overcome this problem phase contrast techniques such as Zernike, Normarsky and dark-field microscopies have been developed to improve specimen visibility without chemically or physically altering them by the process of staining. These techniques have proven to be invaluable tools for studying living cells and furthering scientific understanding of fundamental cellular processes such as mitosis. However a drawback of these techniques is that direct quantitative phase imaging is not possible. Quantitative phase imaging is important because it enables determination of either the refractive index or optical thickness variations from the measured optical path length with sub-wavelength accuracy. Digital holography is an emergent phase contrast technique that offers an excellent approach in obtaining both qualitative and quantitative phase information from the hologram. A CCD camera is used to record a hologram onto a computer and numerical methods are subsequently applied to reconstruct the hologram to enable direct access to both phase and amplitude information. Another attractive feature of digital holography is the ability to focus on multiple focal planes from a single hologram, emulating the focusing control of a conventional microscope.MethodsA modified Mach-Zender off-axis setup in transmission is used to record and reconstruct a number of holographic amplitude and phase images of cellular and sub-cellular features.ResultsBoth cellular and sub-cellular features are imaged with sub-micron, diffraction-limited resolution. Movies of holographic amplitude and phase images of living microbes and cells are created from a series of holograms and reconstructed with numerically adjustable focus, so that the moving object can be accurately tracked with a reconstruction rate of 300ms for each hologram. The holographic movies show paramecium swimming among other microbes as well as displaying some of their intracellular processes. A time lapse movie is also shown for fibroblast cells in the process of migration.ConclusionDigital holography and movies of digital holography are seen to be useful new tools for visualization of dynamic processes in biological microscopy. Phase imaging digital holography is a promising technique in terms of the lack of coherent noise and the precision with which the optical thickness of a sample can be profiled, which can lead to images with an axial resolution of a few nanometres.

Project description:BackgroundLarge-scale pairwise drug combination analysis has lately gained momentum in drug discovery and development projects, mainly due to the employment of advanced experimental-computational pipelines. This is fortunate as drug combinations are often required for successful treatment of complex diseases. Furthermore, most new drugs cannot totally replace the current standard-of-care medication, but rather have to enter clinical use as add-on treatment. However, there is a clear deficiency of computational tools for label-free and temporal image-based drug combination analysis that go beyond the conventional but relatively uninformative end point measurements.ResultsCOMBImage is a fast, modular and instrument independent computational framework for in vitro pairwise drug combination analysis that quantifies temporal changes in label-free video microscopy movies. Jointly with automated analyses of temporal changes in cell morphology and confluence, it performs and displays conventional cell viability and synergy end point analyses. The image processing algorithms are parallelized using Google's MapReduce programming model and optimized with respect to method-specific tuning parameters. COMBImage is shown to process time-lapse microscopy movies from 384-well plates within minutes on a single quad core personal computer. This framework was employed in the context of an ongoing drug discovery and development project focused on glioblastoma multiforme; the most deadly form of brain cancer. Interesting add-on effects of two investigational cytotoxic compounds when combined with vorinostat were revealed on recently established clonal cultures of glioma-initiating cells from patient tumor samples. Therapeutic synergies, when normal astrocytes were used as a toxicity cell model, reinforced the pharmacological interest regarding their potential clinical use.ConclusionsCOMBImage enables, for the first time, fast and optimized pairwise drug combination analyses of temporal changes in label-free video microscopy movies. Providing this jointly with conventional cell viability based end point analyses, it could help accelerating and guiding any drug discovery and development project, without use of cell labeling and the need to employ a particular live cell imaging instrument.

Dataset Information

Dynamical analysis of bacteria in microscopy movies.

Publications

Dynamical analysis of bacteria in microscopy movies.

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