SynthesisScience advances2023
Machine learning enables prediction of metabolic system evolution in bacteria.
Synthesis in Science advances, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
- Genomic signatures of host adaptation in Pasteurella multocida from poultry, cattle, swine, and cats: insights from interpretable machine learning.Poultry science · 2026Article
- KEGG orthology-based machine learning reveals functional determinants of antimicrobial resistance inMicrobiology spectrum · 2026Article
- ProteomeLM: A proteome-scale language model enables accurate and rapid prediction of protein-protein interactions and gene essentiality across taxa.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Assessment of genome evolution inmSystems · 2026Article
- Cooperation and the evolution of bacterial niche breadth.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Ensemble learning on serum metabolic fingerprints for early detection of lung adenocarcinoma.NPJ precision oncology · 2026Article
- Host range and antibiotic resistance dissemination are shaped by distinct survival strategies of conjugative plasmids.Nucleic acids research · 2026Article
- Widespread promiscuous alkaline phosphatases underscore ancient microbial phosphite utilization.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- CORGIAS: identifying correlated gene pairs by considering evolutionary history in a large-scale prokaryotic genome dataset.NAR genomics and bioinformatics · 2025Article
- Multiscale metabolic engineering in biological lignin valorization.Innovation (Cambridge (Mass.)) · 2025Review
- Targeting mitochondrial transporters and metabolic reprogramming for disease treatment.Journal of translational medicine · 2025Review
- Implications From the Analogous Relationship Between Evolutionary and Learning Processes.BioEssays : news and reviews in molecular, cellular and developmental biology · 2025Review
- Integrating Intermediate Traits in Phylogenetic Genotype-to-Phenotype Studies.Integrative and comparative biology · 2025Review
- Distinguishing among evolutionary and ecological processes shaping microbiome dynamics.The ISME journal · 2025Review
- Machine learning classification of archaea and bacteria identifies novel predictive genomic features.BMC genomics · 2024Article
- Evolutionary paths toward multi-level convergence of lactic acid bacteria in fructose-rich environments.Communications biology · 2024Article
- Genome engineering on size reduction and complexity simplification: A review.Journal of advanced research · 2024Review
- Towards an Analytical Biology.Current genomics · 2024Article
- Genomic language model predicts protein co-regulation and function.Nature communications · 2024Article
- Contingency, repeatability, and predictability in the evolution of a prokaryotic pangenome.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Evolution prediction is a long-standing goal in evolutionary biology, with potential impacts on strategic pathogen control, genome engineering, and synthetic biology. While laboratory evolution studies have shown the predictability of short-term and sequence-level evolution, that of long-term and system-level evolution has not been systematically examined. Here, we show that the gene content evolution of metabolic systems is generally predictable by applying ancestral gene content reconstruction and machine learning techniques to ~3000 bacterial genomes. Our framework, Evodictor, successfully predicted gene gain and loss evolution at the branches of the reference phylogenetic tree, suggesting that evolutionary pressures and constraints on metabolic systems are universally shared. Investigation of pathway architectures and meta-analysis of metagenomic datasets confirmed that these evolutionary patterns have physiological and ecological bases as functional dependencies among metabolic reactions and bacterial habitat changes. Last, pan-genomic analysis of intraspecies gene content variations proved that even "ongoing" evolution in extant bacterial species is predictable in our framework.
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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.