Single-Cell Microfluidics to Study the Effects of Genome Deletion on Bacterial Growth Behavior.

Abstract

By directly monitoring single cell growth in a microfluidic platform, we interrogated genome-deletion effects in Escherichia coli strains. We compared the growth dynamics of a wild type strain with a clean genome strain, and their derived mutants at the single-cell level. A decreased average growth rate and extended average lag time were found for the clean genome strain, compared to those of the wild type strain. Direct correlation between the growth rate and lag time of individual cells showed that the clean genome population was more heterogeneous. Cell culturability (the ratio of growing cells to the sum of growing and nongrowing cells) of the clean genome population was also lower. Interestingly, after the random mutations induced by a glucose starvation treatment, for the clean genome population mutants that had survived the competition of chemostat culture, each parameter markedly improved (i.e., the average growth rate and cell culturability increased, and the lag time and heterogeneity decreased). However, this effect was not seen in the wild type strain; the wild type mutants cultured in a chemostat retained a high diversity of growth phenotypes. These results suggest that quasi-essential genes that were deleted in the clean genome might be required to retain a diversity of growth characteristics at the individual cell level under environmental stress. These observations highlight that single-cell microfluidics can reveal subtle individual cellular responses, enabling in-depth understanding of the population.

• Authors: Xiaofei Yuan, Jillian M Couto, Andrew Glidle, Yanqing Song, William Sloan, Huabing Yin
• Journal: ACS synthetic biology (ACS Synth Biol) Vol. 6 Issue 12 Pg. 2219-2227 (12 15 2017) ISSN: 2161-5063 [Electronic] United States
• PMID: 28844132 (Publication Type: Journal Article)

Topics

• Escherichia coli (genetics, growth & development)
• Gene Deletion
• Genome, Bacterial
• Microfluidic Analytical Techniques
• Stress, Physiological (genetics)