Microfluidic single-cell analysis links boundary environments and individual microbial phenotypes

Environ Microbiol. 2015 Jun;17(6):1839-56. doi: 10.1111/1462-2920.12667. Epub 2014 Dec 17.

Abstract

Life is based on the cell as the elementary replicative and self-sustaining biological unit. Each single cell constitutes an independent and highly dynamic system with a remarkable individuality in a multitude of physiological traits and responses to environmental fluctuations. However, with traditional population-based cultivation set-ups, it is not possible to decouple inherent stochastic processes and extracellular contributions to phenotypic individuality for two central reasons: the lack of environmental control and the occlusion of single-cell dynamics by the population average. With microfluidic single-cell analysis as a new cell assay format, these issues can now be addressed, enabling cultivation and time-resolved analysis of single cells in precisely manipulable extracellular environments beyond the bulk. In this article, we explore the interplay of cellular physiology and environment at a single-cell level. We review biological basics that govern the functional state of the cell and put them in context with physical fundamentals that shape the extracellular environment. Furthermore, the significance of single-cell growth rates as pivotal descriptors for global cellular physiology is discussed and highlighted by selected studies. These examples illustrate the unique opportunities of microfluidic single-cell cultivation in combination with growth rate analysis, addressing questions of fundamental bio(techno)logical interest.

Publication types

  • Review

MeSH terms

  • Cell Physiological Phenomena / physiology*
  • Cell Proliferation / physiology*
  • Corynebacterium glutamicum / growth & development
  • Environment
  • Escherichia coli / growth & development
  • Flow Cytometry
  • Microfluidics / methods*
  • Phenotype
  • Pseudomonas aeruginosa / growth & development
  • Research Design
  • Single-Cell Analysis / methods*
  • Stochastic Processes
  • Time