Literature DB >> 31598381

High-throughput quantification of microbial birth and death dynamics using fluorescence microscopy.

Samuel F M Hart1, David Skelding1, Adam J Waite1, Justin C Burton1, Wenying Shou1.   

Abstract

BACKGROUND: Microbes live in dynamic environments where nutrient concentrations fluctuate. Quantifying fitness in terms of birth rate and death rate in a wide range of environments is critical for understanding microbial evolution and ecology.
METHODS: Here, using high-throughput time-lapse microscopy, we have quantified how Saccharomyces cerevisiae mutants incapable of synthesizing an essential metabolite (auxotrophs) grow or die in various concentrations of the required metabolite. We establish that cells normally expressing fluorescent proteins lose fluorescence upon death and that the total fluorescence in an imaging frame is proportional to the number of live cells even when cells form multiple layers. We validate our microscopy approach of measuring birth and death rates using flow cytometry, cell counting, and chemostat culturing.
RESULTS: For lysine-requiring cells, very low concentrations of lysine are not detectably consumed and do not support cell birth, but delay the onset of death phase and reduce the death rate compared to no lysine. In contrast, in low hypoxanthine, hypoxanthine-requiring cells can produce new cells, yet also die faster than in the absence of hypoxanthine. For both strains, birth rates under various metabolite concentrations are better described by the sigmoidal-shaped Moser model than the well-known Monod model, while death rates can vary with metabolite concentration and time.
CONCLUSIONS: Our work reveals how time-lapse microscopy can be used to discover non-intuitive microbial birth and death dynamics and to quantify growth rates in many environments.

Entities:  

Keywords:  Saccharomyces cerevisiae; birth rate; death rate; fluorescence microscopy; microbial growth

Year:  2019        PMID: 31598381      PMCID: PMC6785046          DOI: 10.1007/s40484-018-0160-7

Source DB:  PubMed          Journal:  Quant Biol        ISSN: 2095-4689


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