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Flow cytometric fingerprinting for microbial strain discrimination and physiological characterization

Affiliations

  • 1 Center for Microbial Ecology and Technology (CMET), Department of Biochemical and Microbial Technology, Ghent University, Coupure links 653, Ghent B-9000, Belgium.
  • 2 Laboratory of Microbiology (LM-UGent), Ghent University, K. L. Ledeganckstraat 35, Ghent B-9000, Belgium.
  • 3 Department of Mathematical Modeling, Statistics and Bioinformatics (Biomath), Ghent University, Coupure links 653, Ghent B-9000, Belgium.
  • PMID: 29266796
  • DOI: 10.1002/cyto.a.23302

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Flow cytometric fingerprinting for microbial strain discrimination and physiological characterization

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Authors

Affiliations

  • 1 Center for Microbial Ecology and Technology (CMET), Department of Biochemical and Microbial Technology, Ghent University, Coupure links 653, Ghent B-9000, Belgium.
  • 2 Laboratory of Microbiology (LM-UGent), Ghent University, K. L. Ledeganckstraat 35, Ghent B-9000, Belgium.
  • 3 Department of Mathematical Modeling, Statistics and Bioinformatics (Biomath), Ghent University, Coupure links 653, Ghent B-9000, Belgium.
  • PMID: 29266796
  • DOI: 10.1002/cyto.a.23302

Abstract

The analysis of microbial populations is fundamental, not only for developing a deeper understanding of microbial communities but also for their engineering in biotechnological applications. Many methods have been developed to study their characteristics and over the last few decades, molecular analysis tools, such as DNA sequencing, have been used with considerable success to identify the composition of microbial populations. Recently, flow cytometric fingerprinting is emerging as a promising and powerful method to analyze bacterial populations. So far, these methods have primarily been used to observe shifts in the composition of microbial communities of natural samples. In this article, we apply a flow cytometric fingerprinting method to discriminate among 29 Lactobacillus strains. Our results indicate that it is possible to discriminate among 27 Lactobacillus strains by staining with SYBR green I and that the discriminatory power can be increased by combined SYBR green I and propidium iodide staining. Furthermore, we illustrate the impact of physiological changes on the fingerprinting method by demonstrating how flow cytometric fingerprinting is able to discriminate the different growth phases of a microbial culture. The sensitivity of the method is assessed by its ability to detect changes in the relative abundance of a mix of polystyrene beads down to 1.2%. When a mix of bacteria was used, the sensitivity was as between 1.2% and 5%. The presented data demonstrate that flow cytometric fingerprinting is a sensitive and reproducible technique with the potential to be applied as a method for the dereplication of bacterial isolates. © 2017 International Society for Advancement of Cytometry.

Keywords: Lactobacillus; SYBR green; clustering; dereplication; microbiology.

© 2017 International Society for Advancement of Cytometry.

The analysis of microbial populations is fundamental, not only for developing a deeper understanding of microbial communities but also for their engineering in biotechnological applications. Many methods have been developed to study their characteristics and over the last few decades, molecular anal …