Tooluniverse Metagenomics Analysis

Metagenomics & Microbiome Analysis

Integrated pipeline for exploring microbiome studies, classifying taxa, assessing genome quality, linking microbial composition to clinical phenotypes, and interpreting findings through pathway analysis and literature context.

Guiding principles: 1. Study context first -- understand biome, sequencing method, and metadata before diving into taxa 2. Taxonomic consistency -- GTDB taxonomy as reference standard; reconcile NCBI where needed 3. Genome quality matters -- CheckM completeness/contamination thresholds determine trustworthy MAGs 4. Interpretation over enumeration -- explain what taxa mean for the biological question 5. English-first queries -- use English terms in tool calls

LOOK UP, DON'T GUESS

When uncertain about any scientific fact, SEARCH databases first rather than reasoning from memory.

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COMPUTE, DON'T DESCRIBE

When analysis requires computation (statistics, data processing, scoring, enrichment), write and run Python code via Bash. Don't describe what you would do — execute it and report actual results. Use ToolUniverse tools to retrieve data, then Python (pandas, scipy, statsmodels, matplotlib) to analyze it.

Core Databases

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Workflow

Phase 0: Parse query → organism, biome, phenotype, or accession
Phase 1: Study Discovery → MGnify_search_studies, ENAPortal_search_studies
Phase 2: Taxonomic Classification → GTDB_search_genomes, GTDB_get_species, GTDB_search_taxon
Phase 3: Genome Quality → MGnify_search_genomes, MGnify_get_genome (CheckM metrics)
Phase 4: Functional Annotation → MGnify GO terms + KEGG pathway mapping
Phase 5: Clinical Associations → GMrepo species-phenotype links
Phase 6: Literature → PubMed/EuropePMC + CTD gene-disease
Phase 7: Interpretation & Report Synthesis

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Key Phase Notes

Phase 1: ENA requires structured queries (e.g., study_title="*IBD*"), not free text. If ENA fails, fall back to MGnify.

Phase 2: GTDB uses its own naming (e.g., s__Bacteroides_A fragilis vs NCBI Bacteroides fragilis). Always note discrepancies. Use GTDB_search_taxon(operation="search_taxon", query=name).

Phase 3 - Quality tiers (MIMAG):

• High: >= 90% complete, <= 5% contamination, rRNA + >= 18 tRNAs
• Medium: >= 50% complete, <= 10% contamination
• Low: below medium -- flag but don't exclude

Phase 4 - Functional interpretation: Don't just list GO terms. Connect to biology:

Use kegg_search_pathway(keyword=...) (NOT query). Pathway IDs need organism prefix (hsa, ko, eco), NOT bare map.

Phase 5: GMrepo uses MeSH terms: "Crohn Disease" not "IBD", "Colitis, Ulcerative" not "UC", "Colorectal Neoplasms" not "colorectal cancer". Try NCBI taxon IDs if species name fails.

Phase 6 - Evidence grading:

• Strong: Meta-analysis or >5 studies, consistent direction
• Moderate: 2-5 studies consistent, or 1 large cohort
• Preliminary: Single study or conflicting
• Mechanistic only: In vitro/animal, no human epidemiology

Phase 7 - Report: Executive summary, study landscape, GTDB taxonomy, functional interpretation (not GO term lists), clinical relevance with evidence grades, mechanistic model, genome catalog with quality tiers, data gaps.

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Edge Cases & Fallbacks

• Taxon not in GTDB: Try partial search or fall back to MGnify (NCBI taxonomy)
• No GMrepo data: Normal for non-gut organisms; use literature
• GMrepo 0 results: Use formal MeSH terms or NCBI taxon IDs
• No KEGG match: Check MetaCyc or literature

Limitations

• GMrepo: Gut-only
• GTDB: Bacteria/Archaea only
• ENA: Raw data only, strict query syntax
• No sequence analysis: Queries databases, not raw FASTQ/FASTA