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Rapid, precise quantification of bacterial cellular dimensions across a genomic-scale knockout library

BACKGROUND: The determination and regulation of cell morphology are critical components of cell-cycle control, fitness, and development in both single-cell and multicellular organisms. Understanding how environmental factors, chemical perturbations, and genetic differences affect cell morphology req...

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Autores principales: Ursell, Tristan, Lee, Timothy K., Shiomi, Daisuke, Shi, Handuo, Tropini, Carolina, Monds, Russell D., Colavin, Alexandre, Billings, Gabriel, Bhaya-Grossman, Ilina, Broxton, Michael, Huang, Bevan Emma, Niki, Hironori, Huang, Kerwyn Casey
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5320674/
https://www.ncbi.nlm.nih.gov/pubmed/28222723
http://dx.doi.org/10.1186/s12915-017-0348-8
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author Ursell, Tristan
Lee, Timothy K.
Shiomi, Daisuke
Shi, Handuo
Tropini, Carolina
Monds, Russell D.
Colavin, Alexandre
Billings, Gabriel
Bhaya-Grossman, Ilina
Broxton, Michael
Huang, Bevan Emma
Niki, Hironori
Huang, Kerwyn Casey
author_facet Ursell, Tristan
Lee, Timothy K.
Shiomi, Daisuke
Shi, Handuo
Tropini, Carolina
Monds, Russell D.
Colavin, Alexandre
Billings, Gabriel
Bhaya-Grossman, Ilina
Broxton, Michael
Huang, Bevan Emma
Niki, Hironori
Huang, Kerwyn Casey
author_sort Ursell, Tristan
collection PubMed
description BACKGROUND: The determination and regulation of cell morphology are critical components of cell-cycle control, fitness, and development in both single-cell and multicellular organisms. Understanding how environmental factors, chemical perturbations, and genetic differences affect cell morphology requires precise, unbiased, and validated measurements of cell-shape features. RESULTS: Here we introduce two software packages, Morphometrics and BlurLab, that together enable automated, computationally efficient, unbiased identification of cells and morphological features. We applied these tools to bacterial cells because the small size of these cells and the subtlety of certain morphological changes have thus far obscured correlations between bacterial morphology and genotype. We used an online resource of images of the Keio knockout library of nonessential genes in the Gram-negative bacterium Escherichia coli to demonstrate that cell width, width variability, and length significantly correlate with each other and with drug treatments, nutrient changes, and environmental conditions. Further, we combined morphological classification of genetic variants with genetic meta-analysis to reveal novel connections among gene function, fitness, and cell morphology, thus suggesting potential functions for unknown genes and differences in modes of action of antibiotics. CONCLUSIONS: Morphometrics and BlurLab set the stage for future quantitative studies of bacterial cell shape and intracellular localization. The previously unappreciated connections between morphological parameters measured with these software packages and the cellular environment point toward novel mechanistic connections among physiological perturbations, cell fitness, and growth. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12915-017-0348-8) contains supplementary material, which is available to authorized users.
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spelling pubmed-53206742017-02-24 Rapid, precise quantification of bacterial cellular dimensions across a genomic-scale knockout library Ursell, Tristan Lee, Timothy K. Shiomi, Daisuke Shi, Handuo Tropini, Carolina Monds, Russell D. Colavin, Alexandre Billings, Gabriel Bhaya-Grossman, Ilina Broxton, Michael Huang, Bevan Emma Niki, Hironori Huang, Kerwyn Casey BMC Biol Software BACKGROUND: The determination and regulation of cell morphology are critical components of cell-cycle control, fitness, and development in both single-cell and multicellular organisms. Understanding how environmental factors, chemical perturbations, and genetic differences affect cell morphology requires precise, unbiased, and validated measurements of cell-shape features. RESULTS: Here we introduce two software packages, Morphometrics and BlurLab, that together enable automated, computationally efficient, unbiased identification of cells and morphological features. We applied these tools to bacterial cells because the small size of these cells and the subtlety of certain morphological changes have thus far obscured correlations between bacterial morphology and genotype. We used an online resource of images of the Keio knockout library of nonessential genes in the Gram-negative bacterium Escherichia coli to demonstrate that cell width, width variability, and length significantly correlate with each other and with drug treatments, nutrient changes, and environmental conditions. Further, we combined morphological classification of genetic variants with genetic meta-analysis to reveal novel connections among gene function, fitness, and cell morphology, thus suggesting potential functions for unknown genes and differences in modes of action of antibiotics. CONCLUSIONS: Morphometrics and BlurLab set the stage for future quantitative studies of bacterial cell shape and intracellular localization. The previously unappreciated connections between morphological parameters measured with these software packages and the cellular environment point toward novel mechanistic connections among physiological perturbations, cell fitness, and growth. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12915-017-0348-8) contains supplementary material, which is available to authorized users. BioMed Central 2017-02-21 /pmc/articles/PMC5320674/ /pubmed/28222723 http://dx.doi.org/10.1186/s12915-017-0348-8 Text en © Ursell et al. 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Software
Ursell, Tristan
Lee, Timothy K.
Shiomi, Daisuke
Shi, Handuo
Tropini, Carolina
Monds, Russell D.
Colavin, Alexandre
Billings, Gabriel
Bhaya-Grossman, Ilina
Broxton, Michael
Huang, Bevan Emma
Niki, Hironori
Huang, Kerwyn Casey
Rapid, precise quantification of bacterial cellular dimensions across a genomic-scale knockout library
title Rapid, precise quantification of bacterial cellular dimensions across a genomic-scale knockout library
title_full Rapid, precise quantification of bacterial cellular dimensions across a genomic-scale knockout library
title_fullStr Rapid, precise quantification of bacterial cellular dimensions across a genomic-scale knockout library
title_full_unstemmed Rapid, precise quantification of bacterial cellular dimensions across a genomic-scale knockout library
title_short Rapid, precise quantification of bacterial cellular dimensions across a genomic-scale knockout library
title_sort rapid, precise quantification of bacterial cellular dimensions across a genomic-scale knockout library
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5320674/
https://www.ncbi.nlm.nih.gov/pubmed/28222723
http://dx.doi.org/10.1186/s12915-017-0348-8
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