Inheritance of extraordinary metabolic activity from parental bacteria individuals
Many phenotypic traits, such as fermentation activity, have been shown to be instable due to stochastic gene expression and environmental influence. While previous studies only have obtained understanding at the level of the microbial community, the fate of extraordinary traits of an individual through generations of reproduction has yet to be adequately investigated. This work uses the lactic acid bacteri <i>Lactiplantibacillus plantarum</i> as a research model to study the activity inheritance between parental generations and filial generations. An integrated single-cell manipulation strategy is established, including fluorescent screening using an extracellular pH probe and a microwell array, micropicking using a micropipette, and amplifying an individual bacterium via single-cell culture. Consequently, it is found that daughter bacteria can well inherit the strong acid-producing activity from their parental bacterial individuals, although as the reproduction proceeds over 30 generations, the offspring gradually regresses to the mediocre, thus setting a caveat for the limiting generations for desired inheritance. This is likely due to the deterioration of the cell living environment. This work illustrates the inheritable features of bacterial metabolic traits at the level of individual bacteria and is therefore fundamentally insightful for biotechnological applications like bioenergy production that require consistent or at least predictable metabolic performance.
Authors
- Yuyang Lu (ORCID: https://orcid.org/0009-0007-8344-7420)
- Yaoyao Zhang
- Ruo‐Chen Xie
- Jia Gao
- Wei Wang (ORCID: https://orcid.org/0000-0002-4628-1755)
- Hua Su (ORCID: https://orcid.org/0000-0002-2524-6985)
Institutions
- Nanjing University of Chinese Medicine (CN)
- State Key Laboratory of Analytical Chemistry for Life Science (CN)
- Nanjing University (CN)
Publication Details
- Journal
- Proceedings of the National Academy of Sciences
- Published
- 2025-05-09
- DOI
- https://doi.org/10.1073/pnas.2502818122
- Citations
- 4
- Primary Topic
- Gene Regulatory Network Analysis
- Type
- article
- Field-Weighted Citation Impact
- 3.22
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Jiangsu Province