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      The Ribbon-Helix-Helix Domain Protein CdrS Regulates the Tubulin Homolog ftsZ2 To Control Cell Division in Archaea

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          Abstract

          Healthy cell growth and division are critical for individual organism survival and species long-term viability. However, it remains unknown how cells of the domain Archaea maintain a healthy cell cycle. Understanding the archaeal cell cycle is of paramount evolutionary importance given that an archaeal cell was the host of the endosymbiotic event that gave rise to eukaryotes. Here, we identify and characterize novel molecular players needed for regulating cell division in archaea. These molecules dictate the timing of cell septation but are dispensable for growth between divisions. Timing is accomplished through transcriptional control of the cell division ring. Our results shed light on mechanisms underlying the archaeal cell cycle, which has thus far remained elusive.

          ABSTRACT

          Precise control of the cell cycle is central to the physiology of all cells. In prior work we demonstrated that archaeal cells maintain a constant size; however, the regulatory mechanisms underlying the cell cycle remain unexplored in this domain of life. Here, we use genetics, functional genomics, and quantitative imaging to identify and characterize the novel CdrSL gene regulatory network in a model species of archaea. We demonstrate the central role of these ribbon-helix-helix family transcription factors in the regulation of cell division through specific transcriptional control of the gene encoding FtsZ2, a putative tubulin homolog. Using time-lapse fluorescence microscopy in live cells cultivated in microfluidics devices, we further demonstrate that FtsZ2 is required for cell division but not elongation. The cdrS-ftsZ2 locus is highly conserved throughout the archaeal domain, and the central function of CdrS in regulating cell division is conserved across hypersaline adapted archaea. We propose that the CdrSL-FtsZ2 transcriptional network coordinates cell division timing with cell growth in archaea.

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          Direct multiplexed measurement of gene expression with color-coded probe pairs.

          We describe a technology, the NanoString nCounter gene expression system, which captures and counts individual mRNA transcripts. Advantages over existing platforms include direct measurement of mRNA expression levels without enzymatic reactions or bias, sensitivity coupled with high multiplex capability, and digital readout. Experiments performed on 509 human genes yielded a replicate correlation coefficient of 0.999, a detection limit between 0.1 fM and 0.5 fM, and a linear dynamic range of over 500-fold. Comparison of the NanoString nCounter gene expression system with microarrays and TaqMan PCR demonstrated that the nCounter system is more sensitive than microarrays and similar in sensitivity to real-time PCR. Finally, a comparison of transcript levels for 21 genes across seven samples measured by the nCounter system and SYBR Green real-time PCR demonstrated similar patterns of gene expression at all transcript levels.
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            Identification of mutations in laboratory-evolved microbes from next-generation sequencing data using breseq.

            Next-generation DNA sequencing (NGS) can be used to reconstruct eco-evolutionary population dynamics and to identify the genetic basis of adaptation in laboratory evolution experiments. Here, we describe how to run the open-source breseq computational pipeline to identify and annotate genetic differences found in whole-genome and whole-population NGS data from haploid microbes where a high-quality reference genome is available. These methods can also be used to analyze mutants isolated in genetic screens and to detect unintended mutations that may occur during strain construction and genome editing.
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              MicrobeJ, a tool for high throughput bacterial cell detection and quantitative analysis

              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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                Author and article information

                Contributors
                Role: Editor
                Journal
                mBio
                mBio
                mbio
                mbio
                mBio
                mBio
                American Society for Microbiology (1752 N St., N.W., Washington, DC )
                2150-7511
                11 August 2020
                Jul-Aug 2020
                : 11
                : 4
                : e01007-20
                Affiliations
                [a ]Biology Department, Duke University, Durham, North Carolina, USA
                [b ]Department of Molecular and Cellular Biology, Harvard University, Cambridge, Massachusetts, USA
                [c ]Department of Biology, Rosenstiel Basic Medical Science Research Center, Brandeis University, Waltham, Massachusetts, USA
                [d ]Center for Genomics and Computational Biology, Duke University, Durham, North Carolina, USA
                Max Planck Institute for Terrestrial Microbiology
                Author notes
                Address correspondence to Amy K. Schmid, amy.schmid@ 123456duke.edu .
                Author information
                https://orcid.org/0000-0001-5821-8000
                Article
                mBio01007-20
                10.1128/mBio.01007-20
                7439475
                32788376
                26502e50-62fe-441b-8b54-786ff6ece66a
                Copyright © 2020 Darnell et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license.

                History
                : 27 April 2020
                : 6 July 2020
                Page count
                Figures: 8, Tables: 3, Equations: 0, References: 80, Pages: 22, Words: 13814
                Funding
                Funded by: HHS | National Institutes of Health (NIH), https://doi.org/10.13039/100000002;
                Award ID: DP2AI117923
                Award Recipient :
                Funded by: National Science Foundation (NSF), https://doi.org/10.13039/100000001;
                Award ID: MCB-1651117
                Award Recipient :
                Funded by: National Science Foundation (NSF), https://doi.org/10.13039/100000001;
                Award ID: MCB-1417750
                Award Recipient :
                Funded by: National Science Foundation (NSF), https://doi.org/10.13039/100000001;
                Award ID: 1541959
                Award Recipient :
                Funded by: Wellcome Trust (Wellcome), https://doi.org/10.13039/100004440;
                Award ID: 203276/Z/16/Z
                Award Recipient :
                Categories
                Research Article
                Molecular Biology and Physiology
                Custom metadata
                July/August 2020

                Life sciences
                archaea,cell division,gene regulation,transcription factors,video microscopy
                Life sciences
                archaea, cell division, gene regulation, transcription factors, video microscopy

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