ReviewCurrent research in microbial sciences2022
Functional characterization of prokaryotic dark matter: the road so far and what lies ahead.
Review in Current research in microbial sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed, 20 citations in OpenAlex.
- DiMER: a modular framework for replacing uninformative annotations in protein datasets.Microbiology resource announcements · 2026Article
- In silico structural and functional characterisation of two hypothetical proteins from the plant‑associated bacterium Kosakonia cowanii F52.Genomics & informatics · 2026Article
- Cultivation-independent high-quality microbial genome reconstruction from environmental samples with midi-metagenomics.Genome research · 2026Article
- Genomic and experimental characterization of unique Antarctic temperate phage Perkons reveals multiple integrases and complex lysogenic dynamics in Psychrobacillus sp. L4.BMC microbiology · 2026Article
- Augmenting microbial phylogenomic signal with tailored marker gene sets.Nature communications · 2025Article
- Changes in Probiotic Lachnospiraceae Genera Across Different Stages of COVID-19: A Meta-Analysis of 16S rRNA Microbial Data.Microorganisms · 2025Article
- The hidden bacterial microproteome.Molecular cell · 2025Article
- Article
- Deciphering the proteome ofComputational and structural biotechnology journal · 2025Article
- Catalytic Enantioselective C-C Coupling of Alcohols for Polyketide Total Synthesis beyond Chiral Auxiliaries and Premetalated Reagents.Chemical reviews · 2024Review
- Exploring Microbial Dark Matter for the Discovery of Novel Natural Products: Characteristics, Abundance Challenges and Methods.Journal of microbiology and biotechnology · 2024Review
- The Cryptic Bacterial Microproteome.bioRxiv : the preprint server for biology · 2024Article
- Article
- MiST 4.0: a new release of the microbial signal transduction database, now with a metagenomic component.Nucleic acids research · 2024Article
- Effect of castration timing and weaning strategy on the taxonomic and functional profile of ruminal bacteria and archaea of beef calves.Animal microbiome · 2023Article
- Article
- Elucidating the functional roles of prokaryotic proteins using big data and artificial intelligence.FEMS microbiology reviews · 2023Review
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Eight-hundred thousand to one trillion prokaryotic species may inhabit our planet. Yet, fewer than two-hundred thousand prokaryotic species have been described. This uncharted fraction of microbial diversity, and its undisclosed coding potential, is known as the "microbial dark matter" (MDM). Next-generation sequencing has allowed to collect a massive amount of genome sequence data, leading to unprecedented advances in the field of genomics. Still, harnessing new functional information from the genomes of uncultured prokaryotes is often limited by standard classification methods. These methods often rely on sequence similarity searches against reference genomes from cultured species. This hinders the discovery of unique genetic elements that are missing from the cultivated realm. It also contributes to the accumulation of prokaryotic gene products of unknown function among public sequence data repositories, highlighting the need for new approaches for sequencing data analysis and classification. Increasing evidence indicates that these proteins of unknown function might be a treasure trove of biotechnological potential. Here, we outline the challenges, opportunities, and the potential hidden within the functional dark matter (FDM) of prokaryotes. We also discuss the pitfalls surrounding molecular and computational approaches currently used to probe these uncharted waters, and discuss future opportunities for research and applications.
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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.