ArticleThe ISME journal2021
A network approach to elucidate and prioritize microbial dark matter in microbial communities.
Article in The ISME journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 73 papers, 2 of them syntheses that pooled it.
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Who cites it
73 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- The microbial dark matter and "wanted list" in worldwide wastewater treatment plants.Microbiome · 2023Pooled it
- Reproducible acquisition, management and meta-analysis of nucleotide sequence (meta)data using q2-fondue.Bioinformatics (Oxford, England) · 2022Pooled it
- Stable Bacterial Cores and Patchy Eukaryotic Communities Shape the Summer Microbiomes of Patagonian Fjord Ecosystems Across Spatial, Functional and Temporal Gradients.Environmental microbiology reports · 2026Article
- Unlocking Microbial Dark Matter: A Comprehensive Review of Isolation Technologies from Traditional Culturing to Single-Cell Technologies.Microorganisms · 2026Review
- Establishing community structure and diversity within hydrothermal vent bacterial communities of the East Pacific Rise at 9°50'N.Microbiology spectrum · 2026Article
- Microbial diversity, metabolic specialization, and genomic novelty across polyextreme saline lakes of the Central Dry Andes.Environmental microbiome · 2026Article
- Integrated omics analyses reveal insights into microbial dark matter associated with deep-sea water in Central Indian Ocean.World journal of microbiology & biotechnology · 2026Article
- Quorum-sensing microbial dark matter enables core functions in wastewater microbiomes.ISME communications · 2026Article
- Identifying Differential Network Properties and Driver Microbes in Microbial Association Networks Using CompNet and NetShift.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Multi-omic profiling reveals distinct gut microbial and metabolic landscapes in golden snub-nosed monkeys under contrasting conservation strategies.NPJ biofilms and microbiomes · 2025Article
- Article
- A computational framework for inferring species dynamics and interactions with applications in microbiota ecology.NPJ systems biology and applications · 2025Article
- Stable microbial community promotes aerobic methanotrophy in a large river-reservoir system.mSystems · 2025Article
- Host-Specificity and Network Structure of Tick Microbiota in Co-Distributed Species From the Iberian Peninsula.Ecology and evolution · 2025Article
- Defining the cultured and uncultured bacterial fractions in Cannabis seeds.Environmental microbiome · 2025Article
- The gastrointestinal tract microbiome of Holstein × Angus cross cattle is negatively impacted by the pre-harvest process.Applied and environmental microbiology · 2025Article
- Multi-Metagenome Analysis Unravels Community Collapse After Sampling and Hints the Cultivation Strategy of CPR Bacteria in Groundwater.Microorganisms · 2025Article
- Inferring Species Interactions From Co-occurrence Networks With Environmental DNA Metabarcoding Data in a Coastal Marine Food Web.Molecular ecology · 2025Article
- Differential roles of deterministic and stochastic processes in structuring soil bacterial ecotypes across terrestrial ecosystems.Nature communications · 2025Article
- Identification of stress-alleviating strains from the core drought-responsive microbiome of Arabidopsis ecotypes.The ISME journal · 2025Article
13 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Microbes compose most of the biomass on the planet, yet the majority of taxa remain uncharacterized. These unknown microbes, often referred to as "microbial dark matter," represent a major challenge for biology. To understand the ecological contributions of these Unknown taxa, it is essential to first understand the relationship between unknown species, neighboring microbes, and their respective environment. Here, we establish a method to study the ecological significance of "microbial dark matter" by building microbial co-occurrence networks from publicly available 16S rRNA gene sequencing data of four extreme aquatic habitats. For each environment, we constructed networks including and excluding unknown organisms at multiple taxonomic levels and used network centrality measures to quantitatively compare networks. When the Unknown taxa were excluded from the networks, a significant reduction in degree and betweenness was observed for all environments. Strikingly, Unknown taxa occurred as top hubs in all environments, suggesting that "microbial dark matter" play necessary ecological roles within their respective communities. In addition, novel adaptation-related genes were detected after using 16S rRNA gene sequences from top-scoring hub taxa as probes to blast metagenome databases. This work demonstrates the broad applicability of network metrics to identify and prioritize key Unknown taxa and improve understanding of ecosystem structure across diverse habitats.
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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.