2021
DOI: 10.3390/microorganisms9112277
|View full text |Cite
|
Sign up to set email alerts
|

Single-Cell Technologies to Study Phenotypic Heterogeneity and Bacterial Persisters

Abstract: Antibiotic persistence is a phenomenon in which rare cells of a clonal bacterial population can survive antibiotic doses that kill their kin, even though the entire population is genetically susceptible. With antibiotic treatment failure on the rise, there is growing interest in understanding the molecular mechanisms underlying bacterial phenotypic heterogeneity and antibiotic persistence. However, elucidating these rare cell states can be technically challenging. The advent of single-cell techniques has enabl… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2

Citation Types

0
2
0

Year Published

2023
2023
2023
2023

Publication Types

Select...
5

Relationship

0
5

Authors

Journals

citations
Cited by 13 publications
(2 citation statements)
references
References 157 publications
0
2
0
Order By: Relevance
“…In eukaryotic cell biology, measuring single-cell behaviors and cell-to-cell heterogeneity in a complex environment is key to understanding cellular interactions in different physiological conditions. For microorganisms, the heterogeneity in genotypic and phenotypic traits has a direct impact on human health and the functioning of environmental microbiomes. Consequently, the rapidly developing single-cell technologies have revolutionized microbiology. Among omics-based analyses, single-cell metabolomics provides the most immediate and dynamic picture of the functionality of a cell, but it is arguably the most difficult to measure. , Due to the small amount of metabolites present in single cells and the inability for amplification, detection sensitivity challenges are posed on metabolomics technology, especially when analyzing the comparably small bacterial and archaeal cells. Additionally, as the function of a cell in a given set of physiochemical conditions is a variable and dynamic property that cannot be reliably predicted from either metabolic reconstructions or genomics data alone, genotyping integrated with metabolic analysis provides a better way to understand how microorganisms interact with their biotic and abiotic environment.…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation
“…In eukaryotic cell biology, measuring single-cell behaviors and cell-to-cell heterogeneity in a complex environment is key to understanding cellular interactions in different physiological conditions. For microorganisms, the heterogeneity in genotypic and phenotypic traits has a direct impact on human health and the functioning of environmental microbiomes. Consequently, the rapidly developing single-cell technologies have revolutionized microbiology. Among omics-based analyses, single-cell metabolomics provides the most immediate and dynamic picture of the functionality of a cell, but it is arguably the most difficult to measure. , Due to the small amount of metabolites present in single cells and the inability for amplification, detection sensitivity challenges are posed on metabolomics technology, especially when analyzing the comparably small bacterial and archaeal cells. Additionally, as the function of a cell in a given set of physiochemical conditions is a variable and dynamic property that cannot be reliably predicted from either metabolic reconstructions or genomics data alone, genotyping integrated with metabolic analysis provides a better way to understand how microorganisms interact with their biotic and abiotic environment.…”
Section: Introductionmentioning
confidence: 99%
“… 1 7 For microorganisms, the heterogeneity in genotypic and phenotypic traits has a direct impact on human health and the functioning of environmental microbiomes. 8 11 Consequently, the rapidly developing single-cell technologies have revolutionized microbiology. 12 16 Among omics-based analyses, single-cell metabolomics provides the most immediate and dynamic picture of the functionality of a cell, but it is arguably the most difficult to measure.…”
Section: Introductionmentioning
confidence: 99%