ArticleNature communications2023
Functional comparison of metabolic networks across species.
Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed.
- RefiningMicrobial genomics · 2026Article
- Evolutionary signals in metabolic networks of insect endosymbionts revealed through comparative topological modeling.BMC genomics · 2026Article
- Comparing the ability of embedding methods on metabolic hypergraphs for capturing taxonomy-based features.Algorithms for molecular biology : AMB · 2026Article
- Synergy and antagonism in a genome-scale model of metabolic hijacking by bacteriophages.Science advances · 2026Article
- In silico analysis and comparison of the metabolic capabilities of different organisms by reducing metabolic complexity.Microbiome · 2026Article
- Review
- Metadag: a web tool to generate and analyse metabolic networks.BMC bioinformatics · 2025Article
- A data-driven modeling framework for mapping genotypes to synthetic microbial community functions.bioRxiv : the preprint server for biology · 2025Article
- Integrated metabolomics and metagenomics reveal plant-microbe interactions driving aroma differentiation in flue-cured tobacco leaves.Frontiers in plant science · 2025Article
- Modular, inducible, and titratable expression systems forMicrobiology spectrum · 2024Article
- A benchmark of RNA-seq data normalization methods for transcriptome mapping on human genome-scale metabolic networks.NPJ systems biology and applications · 2024Article
- Panera: An innovative framework for surmounting uncertainty in microbial community modeling using pan-genera metabolic models.iScience · 2024Article
- Modular, inducible, and titratable expression systems forbioRxiv : the preprint server for biology · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Metabolic phenotypes are pivotal for many areas, but disentangling how evolutionary history and environmental adaptation shape these phenotypes is an open problem. Especially for microbes, which are metabolically diverse and often interact in complex communities, few phenotypes can be determined directly. Instead, potential phenotypes are commonly inferred from genomic information, and rarely were model-predicted phenotypes employed beyond the species level. Here, we propose sensitivity correlations to quantify similarity of predicted metabolic network responses to perturbations, and thereby link genotype and environment to phenotype. We show that these correlations provide a consistent functional complement to genomic information by capturing how network context shapes gene function. This enables, for example, phylogenetic inference across all domains of life at the organism level. For 245 bacterial species, we identify conserved and variable metabolic functions, elucidate the quantitative impact of evolutionary history and ecological niche on these functions, and generate hypotheses on associated metabolic phenotypes. We expect our framework for the joint interpretation of metabolic phenotypes, evolution, and environment to help guide future empirical studies.
Indexed as
Identifiers
What OpenQuestion holds
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.