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

BMC Biology

Software

Alexandre Colavin¹  Carolina Tropini²  Timothy K. Lee³  Ilina Bhaya-Grossman³  Handuo Shi³  Russell D. Monds⁴  Kerwyn Casey Huang⁵  Tristan Ursell⁶  Michael Broxton⁷  Gabriel Billings⁸  Bevan Emma Huang⁹  Hironori Niki^1,10  Daisuke Shiomi^1,11 

[1] Biophysics Program, Stanford University School of Medicine, 94305, Stanford, CA, USA;Biophysics Program, Stanford University School of Medicine, 94305, Stanford, CA, USA;Department of Microbiology and Immunology, Stanford University School of Medicine, 94305, Stanford, CA, USA;Department of Bioengineering, Stanford University, 94305, Stanford, CA, USA;Department of Bioengineering, Stanford University, 94305, Stanford, CA, USA;Current address: Synthetic Genomics Inc., 92037, La Jolla, CA, USA;Department of Bioengineering, Stanford University, 94305, Stanford, CA, USA;Department of Microbiology and Immunology, Stanford University School of Medicine, 94305, Stanford, CA, USA;Department of Bioengineering, Stanford University, 94305, Stanford, CA, USA;Department of Physics, University of Oregon, 97403, Eugene, OR, USA;Department of Computer Science, Stanford University, 94305, Stanford, CA, USA;Department of Physics, Stanford University, 94305, Stanford, CA, USA;Janssen Research and Development, 94025, Menlo Park, CA, USA;National Institute of Genetics, Shizuoka, Japan;National Institute of Genetics, Shizuoka, Japan;Current address: Department of Life Science, Rikkyo University, Tokyo, Japan;

关键词: Microbiology;    Cell biology;    Cell morphology;    Cell shape;    Imaging;    Chemical genomics;    Principal component analysis;    Segmentation;    Microscopy;    Computer vision;   

DOI  :  10.1186/s12915-017-0348-8

 received in 2016-08-18, accepted in 2017-01-06,  发布年份 2017

来源: Springer

【 摘 要 】

BackgroundThe 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.ResultsHere 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.ConclusionsMorphometrics 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.

【 授权许可】

CC BY   
© Ursell et al. 2017