ArticleNature microbiology2023
Genome content predicts the carbon catabolic preferences of heterotrophic bacteria.
Article in Nature microbiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 63 papers.
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Who cites it
63 citing papers in PubMed.
- Strategies and applications for alleviating carbon catabolite repression.Synthetic and systems biotechnology · 2027Review
- Genome-based predictions of metabolic preferences and substrate phenotypes in psychrotrophic bacteria from permafrost environments.Microbiology spectrum · 2026Article
- Increased nutrient diversity can induce loss of microbial diversity through enhanced resource uptake.Nature ecology & evolution · 2026Article
- Predictable shifts in microbial species composition lead to community-wide robustness to environmental stress.Nature microbiology · 2026Article
- Engineered dual-responsive mucoadhesive hydrogel co-delivering fullerenol against radiation-induced vaginal injury and microbiota dysbiosis.Materials today. Bio · 2026Article
- Nitrogen Removal Characteristics and Application by a Novel Cold-Resistant Bacterium.Microorganisms · 2026Article
- Evolutionary insights into an ancient fungal transition from land to sea.bioRxiv : the preprint server for biology · 2026Article
- Article
- Organic carbon oxidation state shapes fermentative methanogenic microbiomes and controls greenhouse gas fluxes.Nature communications · 2026Article
- Linkage of nucleotide and functional diversity varies across gut bacteria.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Whole-Genome Sequencing and Comparative Genomic Analysis ofVeterinary sciences · 2026Article
- quickARSC: standalone package and web interface for profiling elemental stoichiometry of proteomes.Microbiology resource announcements · 2026Article
- Metabolic inequality in microbial communities.bioRxiv : the preprint server for biology · 2026Article
- Defining metabolic niches for marine microbial heterotrophs.Science advances · 2026Article
- Uncovering the ecophysiological potential of Motilimonas through genomic profiling analysis.BMC genomics · 2026Article
- Cross-feeding options define genome evolution and community assembly of deep groundwater microbiome.Environmental microbiome · 2026Article
- Genome-resolved metagenomics uncovers diversity and functional landscapes of the gastrointestinal epithelium-associated microbiome in cattle.Genome biology · 2026Article
- Reduced methane emissions in transgenic rice genotypes are associated with altered rhizosphere microbial hydrogen cycling.Nature communications · 2026Article
- Dynamic reworking of marine diatom endometabolomes in response to temperature and a model bacterium.mSystems · 2026Article
- Genomic adaptation strategies to habitat switching in Korarchaeota.Science advances · 2026Article
3 more citing papers are in PubMed but not listed here.
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Heterotrophic bacteria-bacteria that utilize organic carbon sources-are taxonomically and functionally diverse across environments. It is challenging to map metabolic interactions and niches within microbial communities due to the large number of metabolites that could serve as potential carbon and energy sources for heterotrophs. Whether their metabolic niches can be understood using general principles, such as a small number of simplified metabolic categories, is unclear. Here we perform high-throughput metabolic profiling of 186 marine heterotrophic bacterial strains cultured in media containing one of 135 carbon substrates to determine growth rates, lag times and yields. We show that, despite high variability at all levels of taxonomy, the catabolic niches of heterotrophic bacteria can be understood in terms of their preference for either glycolytic (sugars) or gluconeogenic (amino and organic acids) carbon sources. This preference is encoded by the total number of genes found in pathways that feed into the two modes of carbon utilization and can be predicted using a simple linear model based on gene counts. This allows for coarse-grained descriptions of microbial communities in terms of prevalent modes of carbon catabolism. The sugar-acid preference is also associated with genomic GC content and thus with the carbon-nitrogen requirements of their encoded proteome. Our work reveals how the evolution of bacterial genomes is structured by fundamental constraints rooted in metabolism.
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