ArticleFrontiers in bioinformatics2022
Metascan: METabolic Analysis, SCreening and ANnotation of Metagenomes.
Article in Frontiers in bioinformatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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9 citing papers in PubMed, 16 citations in OpenAlex.
- Electrogenic CH4 oxidation on a bioanode: putative extracellular electron transport system in Methylobacter sp.FEMS microbiology ecology · 2026Article
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- Long-Term Euxinia Restricts Microbial Methane Removal in Eutrophic Coastal Basins.Environmental science & technology · 2025Article
- Hydrogen Oxidation Benefits Alphaproteobacterial Methanotrophs Under Severe Methane Limitation.Environmental microbiology · 2025Article
- Hidden Markov Model-Based Prokaryotic Genome Space Mining Reveals the Widespread Pervasiveness of Complex I and Its Potential Evolutionary Scheme.Genome biology and evolution · 2025Article
- Sediments From a Seasonally Euxinic Coastal Ecosystem Show High Nitrogen Cycling Potential.Environmental microbiology · 2025Article
- Comprehensive evaluation of primer pairs targeting the ammonia monooxygenase subunit A gene of complete ammonia-oxidizingMicrobiology spectrum · 2024Article
- Genomic analysis of the class Phycisphaerae reveals a versatile group of complex carbon-degrading bacteria.Antonie van Leeuwenhoek · 2024Article
- Microbial paracetamol degradation involves a high diversity of novel amidase enzyme candidates.Water research X · 2022Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Large scale next generation metagenomic sequencing of complex environmental samples paves the way for detailed analysis of nutrient cycles in ecosystems. For such an analysis, large scale unequivocal annotation is a prerequisite, which however is increasingly hampered by growing databases and analysis time. Hereto, we created a hidden Markov model (HMM) database by clustering proteins according to their KEGG indexing. HMM profiles for key genes of specific metabolic pathways and nutrient cycles were organized in subsets to be able to analyze each important elemental cycle separately. An important motivation behind the clustered database was to enable a high degree of resolution for annotation, while decreasing database size and analysis time. Here, we present Metascan, a new tool that can fully annotate and analyze deeply sequenced samples with an average analysis time of 11 min per genome for a publicly available dataset containing 2,537 genomes, and 1.1 min per genome for nutrient cycle analysis of the same sample. Metascan easily detected general proteins like cytochromes and ferredoxins, and additional
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