Track bacterial strains using MASH, sourmash, fastANI, and inStrain. Compare genomes, detect contamination, and monitor strain-level variation. Use when needing sub-species resolution for outbreak tracking, transmission analysis, or within-host strain dynamics.
Reference examples tested with: inStrain 1.8+, StrainPhlAn/MetaPhlAn 4.1+, dRep 3.4+, skani 0.2+, Bowtie2 2.5+, samtools 1.19+, pandas 2.2+.
Before using code patterns, verify installed versions match. If versions differ:
inStrain profile -h, strainphlan -h, skani dist -h to confirm flags and defaultspip show <package> then help(module.function) to check signaturesIf code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.
The mapping REFERENCE defines the answer. Map to genomes present in the sample set (dRep-dereplicated MAGs from this dataset), not generic database genomes - a distant reference inflates apparent SNVs and corrupts popANI. Record the reference set, the popANI/nGD threshold, the minimum coverage and breadth, and the co-detection rate; the "strain" is defined by these, not by nature.
"Is the same strain in samples A and B?" -> Compare per-position SNV populations (not consensus genomes) at adequate depth - because a strain is defined by the chosen threshold, and ANI cannot resolve the difference that matters.
inStrain profile sample.bam reps.fasta -o sample.IS -s reps.stb -p 8 then inStrain compareScope: in-situ strain resolution, sharing, and deconvolution from a community. Pure-culture isolate outbreak SNP/cgMLST trees -> epidemiological-genomics. MAG assembly/binning -> genome-assembly/metagenome-assembly. Species presence/abundance -> kraken-classification, metaphlan-profiling.
There is no universal definition of a metagenomic strain. A strain is an operational construct fixed by the reference mapped to, the genome fraction comparable at adequate depth, and the cutoff drawn. inStrain's popANI >= 99.999% over >= 50% of the genome IS the strain definition; Valles-Colomer's per-species nGD threshold IS the strain definition. Changing the cutoff changes how many strains exist. Two corollaries:
| Task | Question | Tools | |------|----------|-------| | Identification | which known reference strain is present? | StrainGST, sourmash gather, MIDAS | | Tracking / sharing | is the SAME strain in samples A and B? | inStrain compare, StrainPhlAn, MIDAS2, metaSNV, SameStr | | Deconvolution | how many strains coexist in ONE sample, what are their haplotypes? | DESMAN, Strainberry, strainFlye, Strainy |
Genome-to-genome ANI (MASH/skani/fastANI) is a fourth, orthogonal task - "are these two assembled genomes the same?" - isolate/MAG comparison and dereplication, NOT in-situ strain resolution.
| Tool | Citation | Mechanism / role | When | |------|----------|------------------|------| | inStrain | Olm 2021 Nat Biotechnol 39:727 | popANI/conANI microdiversity from reads mapped to MAGs | the reference standard for shared-strain detection | | StrainPhlAn | Truong 2017 Genome Res 27:626 | marker-SNV consensus -> phylogeny -> nGD | large cross-sample marker surveys, no assembly needed | | MIDAS2 | Zhao 2023 Bioinformatics 39:btac713 | UHGG pan-genome SNV + gene CNV | accessory-genome strain signal at scale | | StrainGE | van Dijk 2022 Genome Biol 23:74 | k-mer search + low-coverage variant calling | low-abundance strains down to 0.5x coverage | | metaSNV v2 | Van Rossum 2022 Bioinformatics 38:1162 | SNV distances + subspecies clustering | subspecies structure across samples | | skani | Shaw 2023 Nat Methods 20:1661 | sparse-chaining ANI | genome-vs-genome ANI; robust on fragmented MAGs (prefer over fastANI) | | Strainberry / strainFlye | Vicedomini 2021 Nat Commun 12:4485; Fedarko 2022 Genome Res 32:2119 | long-read haplotype separation | deconvolute co-occurring strains (-> genome-assembly) |
| Scenario | Recommended | Why | |----------|-------------|-----| | Is a strain shared between two metagenomes? | inStrain compare (popANI) | microdiversity-aware; the field standard | | Cross-sample transmission survey, many samples | StrainPhlAn (per-species nGD) | marker-based, scalable, no assembly | | Low-abundance pathogen (< 1% / < 5x) | StrainGE | detects/compares down to 0.5x | | Accessory-genome / pan-genome strain signal | MIDAS2 | adds gene-content axis SNV tools miss | | Separate co-occurring strains into haplotypes | DESMAN (many samples) or long-read Strainberry/strainFlye | SNV tools do not partition a mixture | | Compare two assembled genomes / dereplicate | skani (or fastANI) | genome-vs-genome ANI, not in-situ strains | | Pure-culture isolate outbreak tree | -> epidemiological-genomics | cgMLST/SNP-distance on one genome per sample |
Goal: Decide whether two metagenomes share a strain without being fooled by which allele happens to be the majority.
Approach: dRep the dataset's MAGs into representative genomes, map reads to the concatenated references, profile each sample, then compare on popANI (microdiversity-aware) over the co-covered genome fraction.
# 1. dRep -> representative genomes (97-99% ANI); concatenate; build scaffold-to-bin (.stb).
# 2. Map reads to the concatenated reps - your OWN MAGs, not database genomes.
bowtie2 -x reps -1 r1.fq.gz -2 r2.fq.gz | samtools sort -o sampleA.bam
inStrain profile sampleA.bam reps.fasta -o sampleA.IS -s reps.stb -g genes.fna -p 8
inStrain profile sampleB.bam reps.fasta -o sampleB.IS -s reps.stb -g genes.fna -p 8
inStrain compare -i sampleA.IS sampleB.IS -o compare.out -s reps.stb -p 8
conANI calls a difference whenever the consensus base differs - confounded by within-sample microdiversity (a minor-allele flip fakes a difference). popANI calls a difference only if the two samples share NO alleles at all, including minor ones, so popANI >= conANI always and is what detects shared strains consensus tools miss. Read genome-level calls from genomeWide_compare.tsv (breadth column percent_compared); the per-scaffold comparisonsTable.tsv uses percent_genome_compared.
metaphlan sample.fq.gz --input_type fastq -s sample.sam.bz2 --bowtie2out sample.bz2 -o profile.tsv # need the SAM (-s)
sample2markers.py -i sams/*.sam.bz2 -o consensus_markers -n 8
extract_markers.py -c t__SGB1877 -o clade_markers/
strainphlan -s consensus_markers/*.json -m clade_markers/t__SGB1877.fna \
-r reference_genomes/*.fna.bz2 -o output -c t__SGB1877 \
--marker_in_n_samples_perc 80 --sample_with_n_markers 20 --nproc 8 # 4.0 named this --marker_in_n_samples
The output tree gives a pairwise nGD (normalized genetic distance). There is no universal nGD strain cutoff - derive a per-species threshold from the data (same-individual-different-timepoint pairs fall below it, unrelated pairs above), as in Valles-Colomer 2023. Low coverage means too few markers pass the filters and the sample is dropped from the species tree silently - so a missing shared-strain call is not evidence of no shared strain.
skani dist genomeA.fasta genomeB.fasta # prefer skani over fastANI: robust on fragmented MAGs
~95% ANI is the species boundary (Jain 2018 Nat Commun 9:5114). ANI saturates above that and cannot resolve same-vs-different strain - use it to compare isolates/MAGs and to dereplicate, never to call transmission.
Trigger: "MASH distance < 0.001 = same strain" or "fastANI > 99% = same strain." Mechanism: ANI operates on consensus genomes, saturates above 99.9%, and ignores microdiversity. Symptom: distinct transmissible strains called identical; transmission inferred from an ANI number. Fix: use ANI for isolate/MAG comparison; use inStrain popANI / StrainPhlAn nGD for strain sharing.
Trigger: concluding "no transmission" or "strain turnover." Mechanism: a shared strain can only be called for a species detected at adequate depth in BOTH samples (inStrain >= 5x and >= 50% breadth; StrainPhlAn enough markers). Symptom: a coverage dropout misread as biological absence; sharing rates biased to abundant taxa. Fix: report co-detection rates alongside sharing rates; use StrainGE for low-abundance targets.
Trigger: narrating "A infected B." Mechanism: a shared strain is an undirected edge. Symptom: directionality claimed from one cross-sectional comparison. Fix: direction comes from timepoints, contact metadata, or a known index case - the published landscapes infer it from study design, not the genomic comparison.
Trigger: mapping to a generic database genome. Mechanism: a distant reference inflates apparent SNVs. Symptom: corrupted popANI; spurious differences. Fix: map to dRep-dereplicated MAGs from the sample set.
Trigger: "what are the two strains here?" from inStrain. Mechanism: SNV/marker tools characterize population diversity; they do not partition it into haplotypes. Symptom: a category error. Fix: use DESMAN (many samples) or long-read Strainberry/strainFlye/Strainy for haplotype separation.
| Threshold | Source | Rationale | |-----------|--------|-----------| | popANI >= 99.999% same strain | Olm 2021 Nat Biotechnol 39:727 | empirical shared-strain cutoff; IS the operational definition | | percent_compared >= 50% (genome-level breadth) | Olm 2021 Nat Biotechnol 39:727 | a genome below 50% breadth is not confidently present | | min_cov 5x | Olm 2021 Nat Biotechnol 39:727 | lowest coverage at which sub-50% minor alleles are reliable | | StrainGE detection ~0.5x | van Dijk 2022 Genome Biol 23:74 | tracks low-abundance strains below the inStrain floor | | Per-species nGD threshold (derive it) | Valles-Colomer 2023 Nature 614:125 | no universal cutoff; separate within-host timepoints from unrelated | | ~95% ANI species boundary | Jain 2018 Nat Commun 9:5114 | ANI saturates above this; cannot resolve strains |
| Error / symptom | Cause | Solution | |-----------------|-------|----------| | Everything looks like one strain | ANI/MASH used for strain calls | switch to inStrain popANI / StrainPhlAn nGD | | Sample missing from the StrainPhlAn tree | too few markers passed filters at low coverage | report co-detection; do not read absence as no-sharing | | popANI implausibly low across the board | mapped to a distant database reference | map to dRep MAGs from the dataset | | inStrain compare gives no genomes | < 50% breadth or < 5x in one sample | deepen sequencing or use StrainGE for that taxon | | "Who infected whom" asked of one timepoint | sharing is undirected | need longitudinal/epi design for direction |
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