ArticleNature ecology & evolution2023
Annotation-free discovery of functional groups in microbial communities.
Article in Nature ecology & evolution, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 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
25 citing papers in PubMed.
- AI-empowered human microbiome research.Gut · 2026Review
- Learning functional groups in complex microbiomes.bioRxiv : the preprint server for biology · 2026Article
- Article
- Constructing a "periodic table" of bacteria to map diversity in trait space.The ISME journal · 2026Article
- Environmental selection constrains metabolic network architecture despite taxonomic turnover in anaerobic digestion communities.The ISME journal · 2026Article
- Microbiome determinants of productivity in aquaculture of whiteleg shrimp.Applied and environmental microbiology · 2025Article
- Environmental instability reduces shock resistance by enriching specialist taxa with distinct two component regulatory systems.NPJ biofilms and microbiomes · 2025Article
- Microbial functional guilds respond cohesively to rapidly fluctuating environments.bioRxiv : the preprint server for biology · 2025Article
- Timescale of environmental change modulates metabolic guild cohesion in microbial communities.The ISME journal · 2025Article
- On exploring cross-sectional stability and persistence of microbiome in a multiple body site colorectal cancer dataset.Frontiers in microbiology · 2025Article
- Short-term virus-host interactions and functional dynamics in recently deglaciated Antarctic tundra soils.ISME communications · 2025Article
- A formal approach to the hierarchical structures of microbial communities with negative interactions.Computational and structural biotechnology journal · 2025Article
- Linear-regression-based algorithms can succeed at identifying microbial functional groups despite the nonlinearity of ecological function.PLoS computational biology · 2024Article
- Individual methanogenic granules are whole-ecosystem replicates with reproducible responses to environmental cues.Environmental microbiome · 2024Article
- A bacterial sensor taxonomy across earth ecosystems for machine learning applications.mSystems · 2024Article
- Microbial community composition predicts bacterial production across ocean ecosystems.The ISME journal · 2024Article
- Quantifying microbial guilds.ISME communications · 2024Article
- Specialty grand challenge: how can we use integrative approaches to understand microbial community dynamics?Frontiers in systems biology · 2024Article
- Searching for Principles of Microbial Ecology Across Levels of Biological Organization.Integrative and comparative biology · 2023Article
- Statistically learning the functional landscape of microbial communities.Nature ecology & evolution · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Recent studies have shown that microbial communities are composed of groups of functionally cohesive taxa whose abundance is more stable and better-associated with metabolic fluxes than that of any individual taxon. However, identifying these functional groups in a manner that is independent of error-prone functional gene annotations remains a major open problem. Here we tackle this structure-function problem by developing a novel unsupervised approach that coarse-grains taxa into functional groups, solely on the basis of the patterns of statistical variation in species abundances and functional read-outs. We demonstrate the power of this approach on three distinct datasets. On data of replicate microcosms with heterotrophic soil bacteria, our unsupervised algorithm recovered experimentally validated functional groups that divide metabolic labour and remain stable despite large variation in species composition. When leveraged against the ocean microbiome data, our approach discovered a functional group that combines aerobic and anaerobic ammonia oxidizers whose summed abundance tracks closely with nitrate concentrations in the water column. Finally, we show that our framework can enable the detection of species groups that are probably responsible for the production or consumption of metabolites abundant in animal gut microbiomes, serving as a hypothesis-generating tool for mechanistic studies. Overall, this work advances our understanding of structure-function relationships in complex microbiomes and provides a powerful approach to discover functional groups in an objective and systematic manner.
Indexed as
Identifiers
36997739What 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.