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Temporal encoding of bacterial identity and traits in growth dynamics.

ABSTRACT: In biology, it is often critical to determine the identity of an organism and phenotypic traits of interest. Whole-genome sequencing can be useful for this but has limited power for trait prediction. However, we can take advantage of the inherent information content of phenotypes to bypass these limitations. We demonstrate, in clinical and environmental bacterial isolates, that growth dynamics in standardized conditions can differentiate between genotypes, even among strains from the same species. We find that for pairs of isolates, there is little correlation between genetic distance, according to phylogenetic analysis, and phenotypic distance, as determined by growth dynamics. This absence of correlation underscores the challenge in using genomics to infer phenotypes and vice versa. Bypassing this complexity, we show that growth dynamics alone can robustly predict antibiotic responses. These findings are a foundation for a method to identify traits not easily traced to a genetic mechanism.

SUBMITTER: Zhang C

PROVIDER: S-EPMC7443910 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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Temporal encoding of bacterial identity and traits in growth dynamics.

Zhang Carolyn C Song Wenchen W Ma Helena R HR Peng Xiao X Anderson Deverick J DJ Fowler Vance G VG Thaden Joshua T JT Xiao Minfeng M You Lingchong L

Proceedings of the National Academy of Sciences of the United States of America 20200803 33

In biology, it is often critical to determine the identity of an organism and phenotypic traits of interest. Whole-genome sequencing can be useful for this but has limited power for trait prediction. However, we can take advantage of the inherent information content of phenotypes to bypass these limitations. We demonstrate, in clinical and environmental bacterial isolates, that growth dynamics in standardized conditions can differentiate between genotypes, even among strains from the same specie ...[more]

PMID: 32747578

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Project description:Seed endophytes are of interest because they are believed to affect seed quality, and ultimately, plant growth and fitness. A comprehensive understanding of the assembly of the seed microbiome during seed development and maturation, the fate of microbes during storage, and the migration of microbes during seedling growth are still lacking. In this study, to understand the assembly and fate of endogenous bacteria in rice seeds from the ripening stage to the storage and seedling stages, we employed culture-dependent and metagenomic analyses. Bacterial communities in rice seeds were composed of a few dominant taxa that were introduced at the milky and dough stages, and they persisted during seed maturation. The culturable bacterial population gradually increased during the ripening stage, whereas there was a gradual decrease during storage. Bacteria that persisted during storage proliferated after imbibition and were distributed and established in the shoots and roots of rice seedlings. The storage temperature influenced the abundance of bacteria, which consequently changed the bacterial composition in the shoots and roots of seedlings. Pantoea, Pseudomonas, and Allorhizobium were consistently abundant from seed development to the germination stage. Some endogenous bacterial strains significantly promoted the growth of Arabidopsis and rice plants. Overall, our results indicate that rice seeds are colonized by a few bacterial taxa during seed development, and their relative abundance fluctuates during storage and contributes significantly to the establishment of endophytes in the stems and roots of rice plants. The selected bacterial isolates can be used to improve the growth and health of rice plants. To the best of our knowledge, this is the first study to reveal the dynamics of bacterial populations during storage of rice seeds at different temperatures. The temporal dynamics of the bacterial community during seed storage provide clues for the manipulation of endogenous bacteria in rice plants.

Dataset Information

Temporal encoding of bacterial identity and traits in growth dynamics.

Publications

Temporal encoding of bacterial identity and traits in growth dynamics.

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