--- name: rippp-structure-database-matching description: 'Use when you have: (1) tandem MS/MS spectra in MGF, mzXML, mzML, or mzData format from LC-MS/MS analysis; (2) a set of predicted RiPP precursor peptides derived from genomic biosynthetic gene cluster mining (via antiSMASH, BOA, or raw FASTA);' license: CC-BY-4.0 metadata: edam_operation: http://edamontology.org/operation_3646 edam_topics: - http://edamontology.org/topic_0121 - http://edamontology.org/topic_3373 - http://edamontology.org/topic_3520 tools: - MetaMiner - NPDtools 2.5.0 - matplotlib - networkx - Dereplicator - antiSMASH - BOA - ProteoWizard derived_from: - doi: 10.1038/s41467-018-06082-8 title: dereplicator evidence_spans: - MetaMiner is a metabologenomic pipeline which integrates metabolomic (tandem mass spectra) and genomic data to identify novel RiPPs - MetaMiner is a metabologenomic pipeline which integrates metabolomic (tandem mass spectra) and genomic data to identify novel Ribosmally synthesized and Post-translationally modified Peptides (RiPPs) - The latest version is available in the Natural Product Discovery toolkit (NPDtools) at https://github.com/ablab/npdtools - For presenting Spectral Network propagation graphs, MetaMiner also requires `matplotlib` and `networkx` Python libraries claims: [] provenance: collection: https://w3id.org/holobiomicslab/asb-skill/collection/metabolomics/v1 assembled_by: scripts/collect_metabolomics_collection.py sources: - build: coll_dereplicator doi: 10.1038/s41467-018-06082-8 title: dereplicator dedup_kept_from: coll_dereplicator schema_version: 0.2.0 --- # RiPP Structure Database Matching ## Summary Match tandem mass spectra against a constructed database of post-translationally modified RiPP structures to identify novel ribosomally synthesized and post-translationally modified peptides. This is a core step in the MetaMiner metabologenomic pipeline that bridges genomic predictions with mass spectrometry evidence. ## When to use Apply this skill when you have: (1) tandem MS/MS spectra in MGF, mzXML, mzML, or mzData format from LC-MS/MS analysis; (2) a set of predicted RiPP precursor peptides derived from genomic biosynthetic gene cluster mining (via antiSMASH, BOA, or raw FASTA); and (3) the goal is to identify which genomically predicted RiPPs are actually expressed and detectable in the sample. ## When NOT to use - Input spectra are not centroided (profile mode) — preprocessing to centroid is required before matching. - RiPP precursor sequences are unavailable or not provided — matching requires known or predicted peptide sequences. - The goal is to identify small-molecule metabolites or non-peptidic natural products — use Dereplicator+ or VarQuest instead for broader chemical structure databases. ## Inputs - Tandem MS/MS spectra (MGF, mzXML, mzML, or mzData format) - RiPP precursor peptide sequences (FASTA file) - Genomic context (antiSMASH .final.gbk/.gbk files or raw contigs.fasta, optional but recommended) ## Outputs - Dereplicator match results with PSM scores and p-values - List of identified RiPPs with matched spectra and modification assignments - Detailed match report showing theoretical vs. observed fragmentation patterns ## How to apply The matching process uses Dereplicator, which scores PSMs (peptide-spectrum matches) between experimental MS/MS spectra and in silico fragmentation patterns of post-translationally modified RiPP structures constructed from genomic precursor sequences. Run MetaMiner with the `--blind` flag for open modification search if testing novel RiPPs, or without it for modification-restricted search. The workflow reads the RiPP FASTA file (or antiSMASH .final.gbk / .gbk output), generates candidate PTM-modified structures, and scores matches against the input spectra. Evaluate matches using the scoring metrics reported in the output; higher PSM scores and lower p-values indicate stronger matches. The detailed output includes matched spectral peaks, theoretical fragmentation patterns, and per-spectrum match confidence. ## Related tools - **Dereplicator** (Core scoring and matching engine that performs database search of MS/MS spectra against RiPP structure database) — https://github.com/ablab/npdtools - **MetaMiner** (Wrapper pipeline that orchestrates RiPP structure database construction from genomic sequences and invokes Dereplicator for matching) — https://github.com/mohimanilab/MetaMiner - **antiSMASH** (Genome mining tool to identify biosynthetic gene clusters and predict RiPP precursor peptides from genomic DNA) - **BOA** (Alternative genome mining tool for BGC identification and precursor peptide prediction) — https://github.com/idoerg/BOA - **ProteoWizard** (Spectrum format conversion utility (msconvert) to convert non-native MS formats to MGF before matching) ## Examples ``` python metaminer.py test_data/metaminer/msms/ -s test_data/metaminer/fasta/ -o metaminer_outdir ``` ## Evaluation signals - PSM p-value < 0.05 (or equivalent significance threshold reported in results) indicates a confident match. - Matched spectra show substantial overlap between observed and theoretical fragment peaks, with peak intensity ranking preserved. - Multiple spectra from the same RiPP or related cluster match, increasing confidence in the identification. - Identified RiPPs correspond to BGCs detected in genomic data, confirming biosynthetic plausibility. - Output files (match scores, matched fragments, modification assignments) are non-empty and properly formatted. ## Limitations - Database-dependent: matching relies on accurate RiPP precursor sequence prediction; errors in genomic mining (e.g., antiSMASH missing AmfS) will reduce sensitivity. - PTM diversity: the tool can only identify RiPPs with PTMs in its modification grammar; novel or unexpected modifications may be missed. - Spectral quality: low-resolution or noisy spectra reduce match confidence; centroided data is required. - No changelog available for version 2.5.0, limiting clarity on algorithm changes or bug fixes from prior releases. ## Evidence - [methods] matches tandem mass spectra against the constructed post-translationally modified RiPPs structure database using Dereplicator: "matches tandem mass spectra against the constructed post-translationally modified RiPPs structure database using Dereplicator" - [methods] MetaMiner successfully detect AmfS using the contigs.fasta file, it fails with antiSMASH result as input: "While `MetaMiner` successfully detect AmfS using the `contigs.fasta` file, it fails with antiSMASH result as input" - [methods] MetaMiner natively supports MGF, mzXML, mzData and uses msconvert utility from the ProteoWizard package to convert spectra in other formats to MGF: "MetaMiner natively supports MGF, mzXML, mzData and uses msconvert utility from the ProteoWizard package to convert spectra in other formats to MGF" - [other] python metaminer.py -s test_data/metaminer/molnet/example_RiPP.fasta --blind --spec-network test_data/metaminer/molnet/ProteoSAFe-METABOLOMICS-SNETS-V2-unpacked -o metaminer_outdir: "python metaminer.py -s test_data/metaminer/molnet/example_RiPP.fasta --blind --spec-network test_data/metaminer/molnet/ProteoSAFe-METABOLOMICS-SNETS-V2-unpacked -o metaminer_outdir" - [readme] Spectra files must be centroided and be in an open spectrum format (MGF, mzXML, mzML or mzData): "Spectra files must be centroided and be in an open spectrum format (**MGF**, **mzXML**, **mzML** or **mzData**)."