HolobiomicsLab Paired-Omics BGC <-> Metabolite Linking (genome mining + molecular networking -> ranked links)
Summary
Assembled genomes + paired LC-MS/MS in, a ranked BGC-metabolite link table out: antiSMASH BGC detection, iPRESTO/Pfam domain tokenization, BiG-SCAPE gene cluster family clustering, GNPS molecular networking, and NPLinker-style genomic-metabolomic co-occurrence scoring.
When to use
Use when you have paired genomic and metabolomic data from the same microbial strains and want to link biosynthetic gene clusters (BGCs) to the metabolite features they plausibly encode — mine BGCs from assembled genomes with antiSMASH, tokenize BGC domains with iPRESTO/Pfam and cluster them into gene cluster families (GCFs) with BiG-SCAPE, build an MS/MS molecular network from paired LC-MS/MS data with GNPS to obtain molecular families (MFs), then score GCF-MF co-occurrence across strains (NPLinker-style Metcalf/hypergeometric scoring) to produce a ranked table of candidate BGC-metabolite links for natural-product discovery.
When NOT to use
- The data is not LC-MS.
- You need a single atomic step, not the full pipeline (use the leaf skill directly via the router).
Stages
Stage 1 — bgc_mine
Goal: assembled genomes -> detected BGCs (antiSMASH genome mining)
EDAM operation: operation_0436
Inputs: fasta · Outputs: genbank/antismash-bgc
Candidate leaf skills: biosynthetic-gene-cluster-detection-and-annotation (primary), genomic-bgc-extraction-antismash, biosynthetic-gene-cluster-annotation
Tools (primary): antiSMASH, BiG-SCAPE, NPLinker, GNPS, MIBiG
Other candidate tools: Python, conda, pip, BigScape, pyHMMER, BiG-SLiCE, PFAM 35.0
Grounding: 4 KB(s); DOIs: 10.1093/gigascience/giaa154, 10.1101/2024.10.11.617756, 10.1186/s40168-022-01444-3, 10.1371/journal.pcbi.1008920
Stage 2 — bgc_tokenize
Goal: GenBank BGC records -> Pfam-domain tokens and sub-cluster motifs (iPRESTO)
EDAM operation: operation_3096
Inputs: genbank/antismash-bgc · Outputs: tsv/bgc-domain-tokens
Candidate leaf skills: biosynthetic-gene-cluster-tokenization (primary), bgc-tokenization-with-pfam-domains, gene-tokenization-representation, pfam-domain-pattern-recognition, statistical-sub-cluster-detection
Tools (primary): iPRESTO
Other candidate tools: Pfam
Grounding: 1 KB(s); DOIs: 10.1371/journal.pcbi.1010462
Stage 3 — gcf_cluster
Goal: BGCs -> gene cluster families (BiG-SCAPE similarity clustering)
EDAM operation: operation_3432
Inputs: genbank/antismash-bgc, tsv/bgc-domain-tokens · Outputs: tsv/gcf-table
Candidate leaf skills: gcf-assignment-from-distance-matrix (primary), gene-cluster-family-formation-and-similarity-clustering, big-slice-workflow-execution, bgc-sequence-domain-scanning
Tools (primary): BiG-SLiCE, pyHMMER, antiSMASH v7.0.0
Other candidate tools: antiSMASH, BiG-SCAPE, NPLinker, GNPS, MIBiG, Flask, PFAM 35.0
Grounding: 3 KB(s); DOIs: 10.1093/gigascience/giaa154, 10.1101/2024.10.11.617756, 10.1371/journal.pcbi.1008920
Stage 4 — mf_network
Goal: paired LC-MS/MS spectra -> molecular families (GNPS feature-based molecular networking)
EDAM operation: operation_3767
Inputs: mgf/gnps-fbmn · Outputs: tsv/mf-table
Candidate leaf skills: spectral-similarity-network-generation (primary), metabolomic-spectral-annotation-and-molecular-family-clustering, metabolomic-molecular-family-networking-gnps, spectral-similarity-network-building
Tools (primary): MZmine2, Optimus, GNPS, Cytoscape
Other candidate tools: antiSMASH, BiG-SCAPE, NPLinker, MIBiG, Python, conda, pip, BigScape, q2-qemistree, SIRIUS, CSI:FingerID, ZODIAC, GNPS FBMN, ClassyFire
Grounding: 5 KB(s); DOIs: 10.1021/acs.jnatprod.7b00737, 10.1038/s41589-020-00677-3, 10.1101/2024.10.11.617756, 10.1186/s40168-022-01444-3 …
Stage 5 — link_score
Goal: GCFs + MFs + strain co-occurrence -> ranked GCF-MF links (NPLinker Metcalf/hypergeometric scoring)
EDAM operation: operation_3357
Inputs: tsv/gcf-table, tsv/mf-table · Outputs: tsv/gcf-mf-scores
Candidate leaf skills: bgc-mf-link-scoring (primary), link-scoring-metcalf-algorithm, gcf-mf-link-scoring, gcf-mf-link-scoring-computation, strain-correlation-hypergeometric-adjustment
Tools (primary): NPLinker, antiSMASH, BiG-SCAPE, MIBiG, GNPS
Other candidate tools: Python, conda, pip, BigScape, NumPy or SciPy
Grounding: 3 KB(s); DOIs: 10.1101/2024.10.11.617756, 10.1186/s40168-022-01444-3, 10.1371/journal.pcbi.1008920
Stage 6 — report
Goal: consolidate scored links + provenance into a ranked BGC-metabolite link table
EDAM operation: operation_3695
Inputs: tsv/gcf-mf-scores, tsv/gcf-table · Outputs: tsv
Candidate leaf skills: genomic-metabolomic-link-ranking (primary), statistical-enrichment-analysis, gcf-mf-hierarchical-aggregation
Tools (primary): NPLinker, BiG-SCAPE, IOKR, antiSMASH, GNPS
Other candidate tools: MIBiG
Grounding: 2 KB(s); DOIs: 10.1101/2024.10.11.617756, 10.1371/journal.pcbi.1008920
Grounding
Each stage carries the kb_slugs/dois of the leaves it draws on. Ground any stage against its source paper with the collection's /ground command or bin/perspicacite_kb_bind.py (Perspicacité KB; serverless local-clone fallback).
Verification contract
workflow.yaml is gradable by asb solve-workflow (checkpoint mode). Each stage declares typed outputs; the final stage emits the master deliverable.
Provenance
Generated by compose_workflows.py (semantic binding + EDAM-aware primary selection). derived_from_workflows lists ASB per-paper workflows whose structure corroborated this pipeline — the eval-ablation set (SPEC §8). Staging only; promote via release_gate.py.