ArticleProceedings of the National Academy of Sciences of the United States of America2020
Temporal encoding of bacterial identity and traits in growth dynamics.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
15 citing papers in PubMed, 21 citations in OpenAlex.
- Engineering microbial consortia for distributed signal processing.Nature communications · 2026Article
- Patient-Specific Coculture of S. aureus and P. aeruginosa Enhances Epithelial Barrier Disruption and Virulence in CRS.International forum of allergy & rhinology · 2026Article
- A foundation model for microbial growth dynamics.bioRxiv : the preprint server for biology · 2025Article
- The Kocurious case of Noodlococcus: genomic insights intoMicrobial genomics · 2025Article
- Data-driven discovery of the interplay between genetic and environmental factors in bacterial growth.Communications biology · 2024Article
- Article
- Private benefit of β-lactamase dictates selection dynamics of combination antibiotic treatment.Nature communications · 2024Article
- Metabolic capabilities are highly conserved among human nasal-associatedbioRxiv : the preprint server for biology · 2024Article
- Genome sequence of the plant-growth-promoting bacterium Bacillus velezensis EU07.Access microbiology · 2024Article
- Identification and characterization of a potential strain for the production of polyhydroxyalkanoate from glycerol.Frontiers in microbiology · 2024Article
- Autoencoder neural networks enable low dimensional structure analyses of microbial growth dynamics.Nature communications · 2023Article
- Culture of attenuatedHuman vaccines & immunotherapeutics · 2023Article
- Drug-dependent growth curve reshaping reveals mechanisms of antifungal resistance in Saccharomyces cerevisiae.Communications biology · 2022Article
- Article
- Machine Learning Establishes Single-Cell Calcium Dynamics as an Early Indicator of Antibiotic Response.Microorganisms · 2021Article
Corrections and comments
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Authors and funding
9 authors at 2 institutions in 2 countries.
Funding
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.