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      MicrobeJ, a tool for high throughput bacterial cell detection and quantitative analysis

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      * , , *
      Nature microbiology

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          Abstract

          Single cell analysis of bacteria and subcellular protein localization dynamics has shown that bacteria have elaborate life cycles, cytoskeletal protein networks, and complex signal transduction pathways driven by localized proteins. The volume of multi-dimensional images generated in such experiments and the computation time required to detect, associate, and track cells and subcellular features pose considerable challenges, especially for high-throughput experiments. Therefore, there is a need for a versatile, computationally efficient image analysis tool capable of extracting the desired relationships from images in a meaningful and unbiased way. Here we present MicrobeJ, a plug-in for the open-source platform ImageJ. MicrobeJ provides a comprehensive framework to process images derived from a wide variety of microscopy experiments with special emphasis on large image sets. It performs the most common intensity and morphology measurements as well as customized detection of poles, septa, fluorescent foci, and organelles, determines their sub-cellular localization with sub-pixel resolution, and tracks them over time. Because a dynamic link is maintained between the images, measurements, and all data representations derived from them, the editor and suite of advanced data presentation tools facilitates the image analysis process and provides a robust way to verify the accuracy and veracity of the data.

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          Most cited references15

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          High-throughput, subpixel precision analysis of bacterial morphogenesis and intracellular spatio-temporal dynamics.

          Bacteria display various shapes and rely on complex spatial organization of their intracellular components for many cellular processes. This organization changes in response to internal and external cues. Quantitative, unbiased study of these spatio-temporal dynamics requires automated image analysis of large microscopy datasets. We have therefore developed MicrobeTracker, a versatile and high-throughput image analysis program that outlines and segments cells with subpixel precision, even in crowded images and mini-colonies, enabling cell lineage tracking. MicrobeTracker comes with an integrated accessory tool, SpotFinder, which precisely tracks foci of fluorescently labelled molecules inside cells. Using MicrobeTracker, we discover that the dynamics of the extensively studied Escherichia coli Min oscillator depends on Min protein concentration, unveiling critical limitations in robustness within the oscillator. We also find that the fraction of MinD proteins oscillating increases with cell length, indicating that the oscillator has evolved to be most effective when cells attain an appropriate length. MicrobeTracker was also used to uncover novel aspects of morphogenesis and cell cycle regulation in Caulobacter crescentus. By tracking filamentous cells, we show that the chromosomal origin at the old-pole is responsible for most replication/separation events while the others remain largely silent despite contiguous cytoplasm. This surprising position-dependent silencing is regulated by division. © 2011 Blackwell Publishing Ltd.
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            Oufti: an integrated software package for high-accuracy, high-throughput quantitative microscopy analysis.

            With the realization that bacteria display phenotypic variability among cells and exhibit complex subcellular organization critical for cellular function and behavior, microscopy has re-emerged as a primary tool in bacterial research during the last decade. However, the bottleneck in today's single-cell studies is quantitative image analysis of cells and fluorescent signals. Here, we address current limitations through the development of Oufti, a stand-alone, open-source software package for automated measurements of microbial cells and fluorescence signals from microscopy images. Oufti provides computational solutions for tracking touching cells in confluent samples, handles various cell morphologies, offers algorithms for quantitative analysis of both diffraction and non-diffraction-limited fluorescence signals and is scalable for high-throughput analysis of massive datasets, all with subpixel precision. All functionalities are integrated in a single package. The graphical user interface, which includes interactive modules for segmentation, image analysis and post-processing analysis, makes the software broadly accessible to users irrespective of their computational skills.
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              Cell age dependent concentration of Escherichia coli divisome proteins analyzed with ImageJ and ObjectJ

              The rod-shaped Gram-negative bacterium Escherichia coli multiplies by elongation followed by binary fission. Longitudinal growth of the cell envelope and synthesis of the new poles are organized by two protein complexes called elongasome and divisome, respectively. We have analyzed the spatio-temporal localization patterns of many of these morphogenetic proteins by immunolabeling the wild type strain MC4100 grown to steady state in minimal glucose medium at 28°C. This allowed the direct comparison of morphogenetic protein localization patterns as a function of cell age as imaged by phase contrast and fluorescence wide field microscopy. Under steady state conditions the age distribution of the cells is constant and is directly correlated to cell length. To quantify cell size and protein localization parameters in 1000s of labeled cells, we developed ‘Coli-Inspector,’ which is a project running under ImageJ with the plugin ‘ObjectJ.’ ObjectJ organizes image-analysis tasks using an integrated approach with the flexibility to produce different output formats from existing markers such as intensity data and geometrical parameters. ObjectJ supports the combination of automatic and interactive methods giving the user complete control over the method of image analysis and data collection, with visual inspection tools for quick elimination of artifacts. Coli-inspector was used to sort the cells according to division cycle cell age and to analyze the spatio-temporal localization pattern of each protein. A unique dataset has been created on the concentration and position of the proteins during the cell cycle. We show for the first time that a subset of morphogenetic proteins have a constant cellular concentration during the cell division cycle whereas another set exhibits a cell division cycle dependent concentration variation. Using the number of proteins present at midcell, the stoichiometry of the divisome is discussed.
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                Author and article information

                Journal
                101674869
                44774
                Nat Microbiol
                Nat Microbiol
                Nature microbiology
                2058-5276
                5 May 2016
                20 June 2016
                2016
                20 December 2016
                : 1
                : 7
                : 16077
                Affiliations
                Department of Biology, Indiana University, 1001 E. 3 rd St, Bloomington, IN, 47405
                Author notes
                [* ] corresponding authors: ybrun@ 123456indiana.edu , 812-855-8860, adrien.ducret@ 123456ibcp.fr , +33 (0)4-72-72-26-79
                [1]

                Current address: Bases Moléculaires et Structurales des Systèmes Infectieux, IBCP, Université Lyon 1, CNRS, UMR 5086, 7 passage du Vercors, 69367 Lyon Cedex 07, France

                Article
                NIHMS782612
                10.1038/nmicrobiol.2016.77
                5010025
                27572972
                bec4a8f2-7bbc-425a-98c2-4b33bdee3359

                Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.com/authors/editorial_policies/license.html#terms

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