RiPP peptide sequence database construction
Summary
Construct a post-translationally modified RiPP structure database from genome-derived precursor peptides and predicted biosynthetic modifications. This database serves as the search target for tandem mass spectra in natural product dereplication workflows.
When to use
When you have genomic sequences (assembled contigs or antiSMASH/BOA mining results) and want to match experimental tandem mass spectra against predicted RiPP structures. Apply this skill before executing database search pipelines (Dereplicator, VarQuest, Dereplicator+) that require a curated RiPP structure database as input.
When NOT to use
- Input is already a validated RiPP structure database or chemical structure library (skip to direct spectrum matching).
- You lack genomic data or genome mining results; only have mass spectra without sequence information (use blind spectral search instead).
- The organism is not a known RiPP producer or the target natural product class is unknown (consider using Dereplicator+ or blind PTM search instead of class-specific prediction).
Inputs
- Assembled DNA contigs (.fasta format)
- antiSMASH genome mining output (.final.gbk or .gbk file)
- BOA genome mining output (.annotated.txt file)
- Raw nucleotide sequences (.fasta format)
Outputs
- RiPP structure database (formatted for Dereplicator, VarQuest, or Dereplicator+ input)
- Precursor peptide sequences and predicted post-translational modifications
- BGC annotations with coordinates and associated peptide sequences
How to apply
Starting from assembled genome sequences or genome mining tool output (antiSMASH .final.gbk/.gbk, BOA .annotated.txt, or raw .fasta contigs), use MetaMiner to identify putative biosynthetic gene clusters (BGCs) and extract corresponding precursor peptides. MetaMiner then constructs putative RiPP structure databases by predicting post-translational modifications (PTMs) characteristic of the RiPP class of interest (e.g., lantibiotic modifications for the default class, or arbitrary PTMs when run with the --blind flag). The resulting structure database is formatted for direct input to downstream database search tools. Key decision points: choose input source (antiSMASH output works with some limitations; raw contig FASTA is more reliable); specify RiPP class or use --blind mode for modification-agnostic discovery.
Related tools
- MetaMiner (Primary tool for identifying BGCs, extracting precursor peptides, and constructing post-translationally modified RiPP structure databases from genomic sequences) — https://github.com/mohimanilab/MetaMiner
- antiSMASH (Upstream genome mining tool whose output (.final.gbk or .gbk files) can be ingested by MetaMiner to identify biosynthetic gene clusters)
- BOA (Upstream genome mining tool whose .annotated.txt output can be used by MetaMiner for BGC and precursor peptide identification) — https://github.com/idoerg/BOA
- SPAdes / metaSPAdes (Upstream genome assembly tool to generate contigs (.fasta) from raw DNA short reads before RiPP database construction)
- Dereplicator (Downstream database search pipeline that accepts the constructed RiPP structure database to match against tandem mass spectra) — https://github.com/ablab/npdtools
- VarQuest (Downstream modification-tolerant database search tool that accepts the RiPP structure database for variant detection) — https://github.com/ablab/npdtools
- Dereplicator+ (Downstream database search pipeline for both peptidic and non-peptidic metabolites that uses the constructed database) — https://github.com/ablab/npdtools
Examples
python metaminer.py test_data/metaminer/msms/ -s test_data/metaminer/fasta/ -o metaminer_outdir
Evaluation signals
- RiPP structure database file is generated and formatted correctly for downstream Dereplicator/VarQuest/Dereplicator+ input.
- Precursor peptides are extracted from identified BGCs with correct start and stop coordinates in genomic sequences.
- Post-translational modifications are predicted for the specified RiPP class (e.g., lantibiotic PTMs are present for default lantibiotic-class predictions).
- When run on the same input, MetaMiner successfully detects known RiPP precursors (e.g., AmfS when using contigs.fasta, though antiSMASH .final.gbk output may fail for some BGCs).
- Resulting database yields match hits with reported scan identifiers, match scores, p-values, and false discovery rates when queried by downstream search tools.
Limitations
- antiSMASH output (.final.gbk) fails to detect some BGCs (e.g., AmfS) while the raw contig FASTA file succeeds, indicating input format dependency.
- RiPP class specification (default lantibiotic) may miss novel or uncharacterized RiPP types; --blind flag enables discovery but increases computation.
- Requires functional genome assembly and gene annotation upstream; poor-quality contigs or assembly gaps lead to missed or truncated precursor peptides.
- No changelog available in repository; version-specific behavior changes and bug fixes may not be documented.
Evidence
- [methods] identifies putative BGCs and the corresponding precursor peptides: "Starting from the genome assemblies, MetaMiner (i) identifies putative BGCs and the corresponding precursor peptides"
- [methods] constructs putative RiPP structure databases: "(ii) constructs putative RiPP structure databases"
- [readme] NPDtools 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"
- [readme] raw nucleotide sequences or output of specific genome mining tools: "The metabologenomic pipelines (currently MetaMiner only) require either raw genome nucleotide sequences or output of specific genome mining tools."
- [methods] antiSMASH result fails to detect AmfS using contigs.fasta succeeds: "While
MetaMiner successfully detect AmfS using the contigs.fasta file, it fails with antiSMASH result as input"
- [methods] matches tandem mass spectra against the constructed post-translationally modified RiPPs structure database using Dereplicator: "(iii) matches tandem mass spectra against the constructed post-translationally modified RiPPs structure database using Dereplicator"
1---2name: ripp-peptide-sequence-database-construction3description: Use when when you have genomic sequences (assembled contigs or antiSMASH/BOA mining results) and want to match experimental tandem mass spectra against predicted RiPP structures.4license: CC-BY-4.05---67# RiPP peptide sequence database construction89## Summary1011Construct a post-translationally modified RiPP structure database from genome-derived precursor peptides and predicted biosynthetic modifications. This database serves as the search target for tandem mass spectra in natural product dereplication workflows.1213## When to use1415When you have genomic sequences (assembled contigs or antiSMASH/BOA mining results) and want to match experimental tandem mass spectra against predicted RiPP structures. Apply this skill before executing database search pipelines (Dereplicator, VarQuest, Dereplicator+) that require a curated RiPP structure database as input.1617## When NOT to use1819- Input is already a validated RiPP structure database or chemical structure library (skip to direct spectrum matching).20- You lack genomic data or genome mining results; only have mass spectra without sequence information (use blind spectral search instead).21- The organism is not a known RiPP producer or the target natural product class is unknown (consider using Dereplicator+ or blind PTM search instead of class-specific prediction).2223## Inputs2425- Assembled DNA contigs (.fasta format)26- antiSMASH genome mining output (.final.gbk or .gbk file)27- BOA genome mining output (.annotated.txt file)28- Raw nucleotide sequences (.fasta format)2930## Outputs3132- RiPP structure database (formatted for Dereplicator, VarQuest, or Dereplicator+ input)33- Precursor peptide sequences and predicted post-translational modifications34- BGC annotations with coordinates and associated peptide sequences3536## How to apply3738Starting from assembled genome sequences or genome mining tool output (antiSMASH .final.gbk/.gbk, BOA .annotated.txt, or raw .fasta contigs), use MetaMiner to identify putative biosynthetic gene clusters (BGCs) and extract corresponding precursor peptides. MetaMiner then constructs putative RiPP structure databases by predicting post-translational modifications (PTMs) characteristic of the RiPP class of interest (e.g., lantibiotic modifications for the default class, or arbitrary PTMs when run with the --blind flag). The resulting structure database is formatted for direct input to downstream database search tools. Key decision points: choose input source (antiSMASH output works with some limitations; raw contig FASTA is more reliable); specify RiPP class or use --blind mode for modification-agnostic discovery.3940## Related tools4142- **MetaMiner** (Primary tool for identifying BGCs, extracting precursor peptides, and constructing post-translationally modified RiPP structure databases from genomic sequences) — https://github.com/mohimanilab/MetaMiner43- **antiSMASH** (Upstream genome mining tool whose output (.final.gbk or .gbk files) can be ingested by MetaMiner to identify biosynthetic gene clusters)44- **BOA** (Upstream genome mining tool whose .annotated.txt output can be used by MetaMiner for BGC and precursor peptide identification) — https://github.com/idoerg/BOA45- **SPAdes / metaSPAdes** (Upstream genome assembly tool to generate contigs (.fasta) from raw DNA short reads before RiPP database construction)46- **Dereplicator** (Downstream database search pipeline that accepts the constructed RiPP structure database to match against tandem mass spectra) — https://github.com/ablab/npdtools47- **VarQuest** (Downstream modification-tolerant database search tool that accepts the RiPP structure database for variant detection) — https://github.com/ablab/npdtools48- **Dereplicator+** (Downstream database search pipeline for both peptidic and non-peptidic metabolites that uses the constructed database) — https://github.com/ablab/npdtools4950## Examples5152```53python metaminer.py test_data/metaminer/msms/ -s test_data/metaminer/fasta/ -o metaminer_outdir54```5556## Evaluation signals5758- RiPP structure database file is generated and formatted correctly for downstream Dereplicator/VarQuest/Dereplicator+ input.59- Precursor peptides are extracted from identified BGCs with correct start and stop coordinates in genomic sequences.60- Post-translational modifications are predicted for the specified RiPP class (e.g., lantibiotic PTMs are present for default lantibiotic-class predictions).61- When run on the same input, MetaMiner successfully detects known RiPP precursors (e.g., AmfS when using contigs.fasta, though antiSMASH .final.gbk output may fail for some BGCs).62- Resulting database yields match hits with reported scan identifiers, match scores, p-values, and false discovery rates when queried by downstream search tools.6364## Limitations6566- antiSMASH output (.final.gbk) fails to detect some BGCs (e.g., AmfS) while the raw contig FASTA file succeeds, indicating input format dependency.67- RiPP class specification (default lantibiotic) may miss novel or uncharacterized RiPP types; --blind flag enables discovery but increases computation.68- Requires functional genome assembly and gene annotation upstream; poor-quality contigs or assembly gaps lead to missed or truncated precursor peptides.69- No changelog available in repository; version-specific behavior changes and bug fixes may not be documented.7071## Evidence7273- [methods] identifies putative BGCs and the corresponding precursor peptides: "Starting from the genome assemblies, MetaMiner (i) identifies putative BGCs and the corresponding precursor peptides"74- [methods] constructs putative RiPP structure databases: "(ii) constructs putative RiPP structure databases"75- [readme] NPDtools 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"76- [readme] raw nucleotide sequences or output of specific genome mining tools: "The metabologenomic pipelines (currently MetaMiner only) require either raw genome nucleotide sequences or output of specific genome mining tools."77- [methods] antiSMASH result fails to detect AmfS using contigs.fasta succeeds: "While `MetaMiner` successfully detect AmfS using the `contigs.fasta` file, it fails with antiSMASH result as input"78- [methods] matches tandem mass spectra against the constructed post-translationally modified RiPPs structure database using Dereplicator: "(iii) matches tandem mass spectra against the constructed post-translationally modified RiPPs structure database using Dereplicator"
