As the ability to analyze individual cells in microbial populations expands, it is becoming apparent that isogenic microbial populations contain substantial cell-to-cell differences in physiological parameters such as growth rate, resistance to stress and regulatory circuit output. Subpopulations exist that are manyfold different in these parameters from the population average, and these differences arise by stochastic processes. Such differences can dramatically affect the response of cells to perturbations, especially stress, which in turn dictates overall population response. Defining the role of cell-to-cell heterogeneity in population behavior is important for understanding population-based research problems, including those involving infecting populations, normal flora and bacterial populations in water and soils. Emerging technological breakthroughs are poised to transform single-cell analysis and are critical for the next phase of insights into physiological heterogeneity in the near future. These include technologies for multiparameter analysis of live cells, with downstream processing and analysis.
At a glance
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