MetaNovo

MetaNovo performs probabilistic peptide discovery from complex metaproteomic tandem mass spectrometry (MS/MS) data to identify peptides and estimate taxonomic composition without relying on curated sequence databases.

Key Features:

• De Novo Sequence Tag Matching: Employs scalable de novo sequence tag matching to identify peptides directly from MS/MS data independent of pre-existing sequence databases.
• Probabilistic Optimization Algorithm: Applies a probabilistic optimization algorithm to the UniProt knowledgebase to generate tailored sequence databases for target-decoy searches.
• Bypassing Curated Databases: Estimates taxonomic- and peptide-level information directly from tandem mass spectrometry, enabling peptide identification across all domains of life without prior sample composition knowledge.
• Enhanced Taxonomic Representation: Demonstrated improved identification of both bacterial and non-bacterial peptides and detection of experimental contaminants compared with pipelines such as MetaPro-IQ.
• Benchmarking and Validation: Was benchmarked against samples of known microbial composition using matched metagenomic and whole genomic sequence database workflows, yielding higher numbers of MS/MS identifications for expected taxa.

Scientific Applications:

• Microbiome Research: Enables identification of microbial proteins and taxonomic composition in complex microbial ecosystems for studies of metabolic interactions.
• Human Disease Pathogenesis: Supports analysis of microbiome-derived protein synthesis to investigate microbial contributions to human health and disease.
• Agriculture: Facilitates profiling of soil and plant-associated microbiomes to study impacts on crop productivity and ecosystem sustainability.
• Climate Change Research: Allows analysis of microbial communities involved in biogeochemical cycles to inform studies of environmental impacts related to climate change.

Methodology:

Integrates existing open-source software with scalable de novo sequence tag matching and a probabilistic optimization of the UniProt knowledgebase to create tailored sequence databases for target-decoy searches, estimates taxonomic and peptide-level information directly from tandem mass spectrometry (MS/MS) data, and includes benchmarking against matched metagenomic and whole genomic sequence database workflows and comparison to MetaPro-IQ.