Microbiota-derived metabolites inhibit Salmonella virulent subpopulation development by acting on single-cell behaviors.
Alyson M HockenberryGabriele MicaliGabriella TakácsJessica WengWolf-Dietrich HardtMartin AckermannPublished in: Proceedings of the National Academy of Sciences of the United States of America (2021)
Salmonella spp. express Salmonella pathogenicity island 1 Type III Secretion System 1 (T3SS-1) genes to mediate the initial phase of interaction with their host. Prior studies indicate short-chain fatty acids, microbial metabolites at high concentrations in the gastrointestinal tract, limit population-level T3SS-1 gene expression. However, only a subset of Salmonella cells in a population express these genes, suggesting short-chain fatty acids could decrease T3SS-1 population-level expression by acting on per-cell expression or the proportion of expressing cells. Here, we combine single-cell, theoretical, and molecular approaches to address the effect of short-chain fatty acids on T3SS-1 expression. Our in vitro results show short-chain fatty acids do not repress T3SS-1 expression by individual cells. Rather, these compounds act to selectively slow the growth of T3SS-1-expressing cells, ultimately decreasing their frequency in the population. Further experiments indicate slowed growth arises from short-chain fatty acid-mediated depletion of the proton motive force. By influencing the T3SS-1 cell-type proportions, our findings imply gut microbial metabolites act on cooperation between the two cell types and ultimately influence Salmonella's capacity to establish within a host.
Keyphrases
- fatty acid
- single cell
- induced apoptosis
- poor prognosis
- escherichia coli
- gene expression
- cell cycle arrest
- rna seq
- listeria monocytogenes
- ms ms
- endoplasmic reticulum stress
- cell therapy
- cell death
- type iii
- oxidative stress
- microbial community
- signaling pathway
- long non coding rna
- mesenchymal stem cells
- pseudomonas aeruginosa
- bone marrow
- biofilm formation
- transcription factor
- genome wide analysis