Pathogen Typing

What the source does

• FilesystemNone observedNo reads or writes in the source
• NetworkNone observedNo outbound calls in the source
• ShellNone observedNo commands run in the source
• DependenciesPinnedNothing floats
• SecretsNone foundNo keys in source

Five audit layers

Gates applied: no behavioural pass.

Audit 0.4.1 · source sha c8c1fc3a2b13 · 19 Oct 2026Report an issue or request a re-scan

• PublisherGPTomics GitHub organizationOwner of the repository this skill is read from
• Source folderGPTomics/bioSkills/epidemiological-genomics/pathogen-typingThe exact folder we audited
• LicenceMITAs the repository states it
• Commit pinned for this verdictc8c1fc3a2b13A new audit runs when the source changes
• Repository statusArchivedLast push 65 days ago
• Sandboxed runNot runSkills are read, not executed; layer L4 is skipped

Its description: Assigns isolate identity at the right resolution for the question -- ANI/Mash species triage, 7-locus MLST historical comparability, cgMLST/wgMLST outbreak resolution (chewBBACA, BIGSdb, Ridom SeqSphere, EnteroBase…

---
name: bio-epidemiological-genomics-pathogen-typing
description: Assigns isolate identity at the right resolution for the question -- ANI/Mash species triage, 7-locus MLST historical comparability, cgMLST/wgMLST outbreak resolution (chewBBACA, BIGSdb, Ridom SeqSphere, EnteroBase HierCC), in-silico serotyping (SISTR/SeqSero2 Salmonella, SerotypeFinder E. coli, Kaptive Klebsiella, SeroBA pneumococcus, spa+SCCmec S. aureus), and lineage callers (TB-Profiler/Mykrobe barcode for MTBC, Pangolin + Nextclade for SARS-CoV-2, PopPUNK GPSC for S. pneumoniae). Use when typing bacterial isolates for surveillance or outbreak investigation, choosing between cgMLST allele distance and core-SNP distance for cluster definition, harmonising calls across schemas/database versions, assigning MTBC lineage with the Napier 90-SNP barcode, calling Salmonella serovar via SISTR with monophasic Typhimurium awareness, running Pangolin UShER mode with pangolin-data version pinning, or selecting a typing resolution to match the surveillance question.
tool_type: mixed
primary_tool: chewBBACA
---

## Version Compatibility

Reference examples tested with: mlst 2.23+, chewBBACA 3.3+, SISTR 1.1+, SeqSero2 1.3+, SerotypeFinder 2.0+, Kleborate 3.0+, Kaptive 3.0+, SeroBA 1.0+, PopPUNK 2.7+, pangolin 4.3+ (pangolin-data 1.30+), nextclade 3.8+, tb-profiler 6.2+, mykrobe 0.13+, mash 2.3+, skani 0.2+, snippy 4.6+, snp-dists 0.8+, pandas 2.2+, BioPython 1.84+.

Before using code patterns, verify installed versions match. If versions differ:
- Python: `pip show <package>` then `help(module.function)` to check signatures
- R: `packageVersion('<pkg>')` then `?function_name`
- CLI: `<tool> --version` then `<tool> --help` to confirm flags
- Pangolin: `pangolin --all-versions` records pangolin + pangolin-data + scorpio + constellations
- Nextclade dataset: `nextclade dataset list --tag latest sars-cov-2`
- chewBBACA schema: schemas are versioned independently; record the schema source AND the schema-fetch date for any published call
- TB-Profiler bundled DB: `tb-profiler list_db` for the WHO catalogue edition currently bundled

If a tool reports an unexpected serovar / lineage / ST, the schema or barcode version is the first thing to check; introspect the installed package and database date before re-running.

# Pathogen Typing

**"What is this isolate, and is it the same as that one?"** -> Pick a typing resolution that matches the epidemiological question, then run the appropriate caller and report the call with explicit schema / database / lineage-barcode versions. Resolution mismatch is the single most common typing error -- using 7-locus MLST to investigate a 20-isolate outbreak (multiple unrelated isolates share an ST) and using cgMLST to track decade-long lineage trends (allele drift obscures the lineage signal) are equally wrong, in opposite directions.

- CLI: `mlst assembly.fa` -- 7-locus MLST via Seemann's mlst with PubMLST schemas
- CLI: `chewBBACA.py AlleleCall -i assemblies/ -g schema/ -o alleles/ --cpu 8` -- cgMLST allele profile
- CLI: `pangolin sequences.fasta --analysis-mode usher --all-versions` -- SARS-CoV-2 Pango lineage with version provenance
- CLI: `tb-profiler profile -1 r1.fq.gz -2 r2.fq.gz -p sample` -- MTBC lineage (Coll/Napier barcode) plus DR call
- Python: `pandas` + `snp-dists` for cluster definition with pathogen-specific thresholds

## The Single Most Important Modern Insight -- cgMLST and core-SNP distance answer different questions

cgMLST counts allele changes (one wobble within a 1-kb locus = 1 allelic difference, regardless of how many SNPs sit inside that allele) and is robust to small assembly artifacts; core-SNP counts every position and is sensitive to alignment / mapping artifacts but recovers higher resolution. The EFSA harmonised foodborne approach uses cgMLST for *Salmonella* / *Listeria* / *E. coli* (Salm cgMLST <=5 alleles = cluster; PulseNet *Listeria* <=4 alleles); UK / EU TB outbreak literature uses core-SNP with recombination masking (Walker 2013: <=12 SNPs = likely transmission; <=5 = recent). Mixing the two yields incompatible cluster definitions: the same 50-isolate outbreak under cgMLST may cluster as 1 group at threshold 5, under core-SNP as 3 groups at threshold 12. The output of pathogen-typing is not a single distance -- it is a distance metric, a threshold derived from a specific population, and a schema or reference version. All three must travel with the call.

## Algorithmic Taxonomy

| Method | Mechanism | Resolution | Strength | Fails when |
|--------|-----------|-----------|----------|------------|
| ANI / fastANI / skani | Pairwise nucleotide identity over orthologous regions | Species (>=95% ANI = same species) | Species-level QC; cross-genus is non-metric for Mash | Species below ~80% ANI; Mash distance violates triangle inequality |
| Mash (Ondov 2016 *Genome Biol* 17:132) | MinHash sketches; fast pairwise distances | Species triage | Seconds per pair; the rapid screening standard | Distance non-metric at low identity; ANI <80% unreliable |
| 7-locus MLST (Maiden 2013 *Nat Rev Microbiol* 11:728; Seemann mlst tool) | PubMLST allele lookup at 7 housekeeping loci | Sequence type | Historical comparability across decades | Insufficient resolution for outbreaks; multiple unrelated isolates may share ST |
| cgMLST (chewBBACA; BIGSdb; Ridom SeqSphere) | Allele lookup across ~1000-3000 core loci | Outbreak / multi-country surveillance | Allele-distance is robust to small mapping errors | Schema-version-dependent; cross-schema NON-comparable; missing-locus handling matters |
| wgMLST | Allele lookup across all genes including accessory | Highest typing resolution | Maximum resolution within schema | Even more schema-dependent than cgMLST |
| Core-SNP typing (snippy + snp-dists; Parsnp; Lyve-SET) | Reference-based SNP calling on core genome | Single-SNP resolution | Highest resolution; underlies most Mtb work | Reference-dependent; recombination must be masked for bacteria 

Excerpt, first 6,000 characters of SKILL.md, verbatim from the audited commit. It is text from someone else’s repository, quoted so you can judge it before your agent reads it.

pip install pandas biopython

git clone https://github.com/GPTomics/bioSkills
git -C bioSkills checkout c8c1fc3a2b13

Works in

1. 2026-10-19
   ✓SAFE B 89 / 100

   first audit · source c8c1fc3a2b13

Questions about Pathogen Typing

• github.com/GPTomics/bioSkills/tree/main/epidemiological-genomics — the audited source at commit c8c1fc3a2b13 and every finding aboveObserved · 19 Oct 2026

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