ArticleNature microbiology2023
BacterAI maps microbial metabolism without prior knowledge.
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 22 papers, 1 of them a synthesis that pooled it.
What it found
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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
22 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Principles for Rigorous Design and Application of Synthetic Microbial Communities.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Pooled it
- Multi-omics-driven precision medicine.iMeta · 2026Review
- Describing the persistence landscape for introducing microbes into complex communities.Applied and environmental microbiology · 2026Review
- Opportunities for artificial intelligence and synthetic biology in designing living drug delivery systems.Advanced drug delivery reviews · 2026Review
- Microbial biobanking: safeguarding the tiny treasures for sustainable human welfare.Folia microbiologica · 2026Review
- Nutrient control enables metabolic reconstruction ofbioRxiv : the preprint server for biology · 2026Article
- MicrobeDiscover: A Knowledge Graph-Enabled AI Framework for Identifying Microbes for Inorganic Nanomaterial Biosynthesis.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Artificial Intelligence for Microbial Isolation and Cultivation: Progress and Challenges.Microorganisms · 2026Review
- Underexplored maternal microbiomes: immune, metabolic, and microbial pathways shaping pregnancy outcomes.Infection and immunity · 2026Review
- Review
- Accelerating primer design for amplicon sequencing using large language model-powered agents.Nature biomedical engineering · 2026Article
- Review
- The Future of a Myriad of Accelerated Biodiscoveries Lies in AI-Powered Mass Spectrometry and Multiomics Integration.Journal of mass spectrometry : JMS · 2025Article
- Linear scaling reveals low-dimensional structure in observable microbial dynamics.bioRxiv : the preprint server for biology · 2025Article
- Automating the practice of science: Opportunities, challenges, and implications.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Ten species comprise half of the bacteriology literature, leaving most species unstudied.bioRxiv : the preprint server for biology · 2025Article
- Discovery and cultivation of prokaryotic taxa in the age of metagenomics and artificial intelligence.The ISME journal · 2025Article
- Improving the odds: Artificial intelligence and the great plate count anomaly.Microbial biotechnology · 2024Article
- Emerging tools and best practices for studying gut microbial community metabolism.Nature metabolism · 2024Review
- Strategies for tailoring functional microbial synthetic communities.The ISME journal · 2024Review
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Authors and funding
7 authors.
Funding
Abstract
Training artificial intelligence (AI) systems to perform autonomous experiments would vastly increase the throughput of microbiology; however, few microbes have large enough datasets for training such a system. In the present study, we introduce BacterAI, an automated science platform that maps microbial metabolism but requires no prior knowledge. BacterAI learns by converting scientific questions into simple games that it plays with laboratory robots. The agent then distils its findings into logical rules that can be interpreted by human scientists. We use BacterAI to learn the amino acid requirements for two oral streptococci: Streptococcus gordonii and Streptococcus sanguinis. We then show how transfer learning can accelerate BacterAI when investigating new environments or larger media with up to 39 ingredients. Scientific gameplay and BacterAI enable the unbiased, autonomous study of organisms for which no training data exist.
Indexed as
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37142775What 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.