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
Department of Bioengineering, Stanford University, Stanford, CA, 94305, USA.
Department of Physics, University of Oregon, Eugene, OR, 97403, USA.
BMC Biol. 2017 Feb 21;15(1):17. doi: 10.1186/s12915-017-0348-8.
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.
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.
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.
细胞形态的确定和调控是单细胞和多细胞生物细胞周期控制、适应性及发育的关键组成部分。了解环境因素、化学扰动和基因差异如何影响细胞形态，需要对细胞形状特征进行精确、无偏且经过验证的测量。
在此，我们介绍了两个软件包，即形态计量学软件包（Morphometrics）和模糊实验室软件包（BlurLab），它们共同实现了对细胞和形态特征的自动化、计算高效且无偏的识别。我们将这些工具应用于细菌细胞，因为这些细胞体积小，且某些形态变化细微，迄今为止掩盖了细菌形态与基因型之间的相关性。我们利用革兰氏阴性菌大肠杆菌非必需基因的庆应义塾敲除文库的在线图像资源，证明细胞宽度、宽度变异性和长度之间相互显著相关，且与药物处理、营养变化及环境条件相关。此外，我们将遗传变异的形态学分类与基因荟萃分析相结合，揭示了基因功能、适应性和细胞形态之间的新联系，从而暗示了未知基因的潜在功能以及抗生素作用模式的差异。
形态计量学软件包（Morphometrics）和模糊实验室软件包（BlurLab）为未来细菌细胞形状和细胞内定位的定量研究奠定了基础。这些软件包测量的形态学参数与细胞环境之间此前未被认识到的联系，指向了生理扰动、细胞适应性和生长之间新的机制联系。
