Additional file 2 of Detection of a historic reservoir of bedaquiline/clofazimine resistance-associated variants in Mycobacterium tuberculosis
Creators: name: Nimmo, Camus
name: Ortiz, Arturo Torres
name: Tan, Cedric C. S.
name: Pang, Juanita
name: Acman, Mislav
name: Millard, James
name: Padayatchi, Nesri
name: Grant, Alison D.
name: O’Donnell, Max
name: Pym, Alex
name: Brynildsrud, Ola B.
name: Eldholm, Vegard
name: Grandjean, Louis
name: Didelot, Xavier
name: Balloux, François
name: van Dorp, Lucy
Publisher: name: figshare
Year: 2024
Subjects: subject: Medicine
subject: Genetics
subject: FOS: Biological sciences
subject: Pharmacology
subject: Biotechnology
subject: Evolutionary Biology
subject: Environmental Sciences not elsewhere classified
subject: Cancer
subject: Infectious Diseases
subject: FOS: Health sciences
subject: Virology
subject: Computational Biology

description: Additional file 2: Fig S1. Distribution of difference (in decimal years) of collection date to release date for sequences in the lineage 2 (L2) and lineage 4 (L4) dataset. For lineage 4, having excluded samples from three eighteenth century mummies, an average of 6.9 years (0.6–19.1 years 95% CI) was obtained. For lineage 2, an average lag-time of 4.7 years (0.5–12.6 years 95% CI) was obtained. Fig S2. Maximum likelihood phylogenetic tree of the lineage 2 (a) and lineage 4 (b) datasets. Tip colours provide the country of sample collection and outer bars give the resistance to four antimycobacterial drugs: fluroquinolones (FLQ), isoniazid (INH), kanamycin (KAN) and rifampicin (RMP). Fig S3. Number (count) of mmpR5 variants split by predicted phenotype (x-axis) for each geographic region included in each of the lineage 2 (a) and lineage 4 b) datasets. Fig S4. Co-occurrence count of mmpR5 variant phenotype predictions (x-axis) and resistance status a) and genotypic resistances b) for the lineage 2 dataset. Fig S5. Co-occurrence count of mmpR5 variant phenotype predictions (x-axis) and resistance status a) and genotypic resistances b) for the lineage 4 dataset. Fig S6. Contingency tables and χ2 results for the distribution of susceptible, MDR and XDR Mtb amongst strains carrying variants in mmpR5 in the lineage 2 dataset. Plots provide the squared standardised residuals contributing to the rejection of the null hypothesis. The colour intensity and size of the circle is proportion to the contribution with positive displayed in blue and negative in red. Fig S7. Contingency tables and χ2 results for the distribution of susceptible, MDR and XDR Mtb amongst strains carrying variants in mmpR5 in the lineage 4 dataset. Plots provide the squared standardised residuals contributing to the rejection of the null hypothesis. The colour intensity and size of the circle is proportion to the contribution with positive displayed in blue and negative in red. Fig S8. Phylogenetic distribution of LOF mutations identified in mmpL5 and mmpS5 identified in L2 isolates. Phylogeny is provided with tip colours according to inferred bedaquiline resistance status. Heatmap provides colour for presence of a mutation as ordered by the vertical columns. Fig S9. Phylogenetic distribution of LOF mutations identified in mmpL5 and mmpS5 identified in L4 isolates. Phylogeny is provided with tip colours according to inferred bedaquiline resistance status. Heatmap provides colour for presence of a mutation as ordered by the vertical columns. Fig S10. Summary plot of SHAP values. Each point represents the SHAP value of a single prediction for a particular feature. Points are stacked vertically using density estimation. ‘WT’, ‘mutant’ and ‘MW’ denotes the wild type amino acid, amino acid variant and molecular weight (Da) respectively. ‘Property’ refers to whether an amino acid was non-polar, polar, positively charged or negatively charged. ‘Ligand_binding’, ‘dna_binding’ and ‘dimerisation’ refer to whether the amino acid residue is involved in ligand binding, DNA binding or dimerisation. ‘Position’ refers to the integer 5’-3’ position of the variant. Positive SHAP values imply an increase in the predicted probability of resistance due to the presence of the feature. Fig S11. Linear regressions of root-to-tip distance (y-axis) versus sampling dates (x-axis) for global Mtb datasets; lineage 2 (a-b) and lineage 4 (c-d). Regressions are performed both without (a-c) and with (b-d) imputation of missing dates (see Methods). Here, the p-value (tiprandomisation test) is calculated by fitting a linear regression to the root to tip distance vs sampling date for 10,000 randomisations and adding the number of randomised fits that present a better regression coefficient than the real data (divided by 10,000). Fig S12. Sub-sampled datasets temporal regression. The lineage 2 data covered 24 years of molecular evolution. The lineage 4 dataset comprised 232 years of evolution. Fig S13. Full mutational timeline for the estimated date of emergence (x-axis) and confidence intervals of nodes with descendent tips carrying nonsynonymous variants in mmpR5 in the lineage 2 dataset. All nonsynonymous variants are depicted. Confidence bars are coloured according to the region where the isolate was collected. Symbols provide the point estimates of the age of the node coloured by mmpR5 predicted phenotype. Symbols are used for all mutations occurring in ≥5 isolates, in this case. Grey dashed lines provide the collection date of all sequenced isolates included in the analysis with mmpR5 variants. Data available in Supplementary Table S7. Fig S14. Full mutational timeline for the estimated date of emergence (x-axis) and confidence intervals of nodes with descendent tips carrying nonsynonymous variants in mmpR5 in the lineage 4 dataset. All nonsynonymous variants are depicted. Confidence bars are coloured according to the region where the isolate was collected. Symbols provide the point estimates of the age of the node coloured by mmpR5 predicted phenotype. Symbols are used for all mutations occurring in ≥5 isolates. Grey dashed lines provide the collection date of all sequenced isolates included in the analysis with mmpR5 variants. Data available in Supplementary Table S7. Fig S15. a) Lineage 4 Peruvian mmpR5 Ile67fs + mmpL5 Arg202fs carrying clade phylogeny, which has a tMRCA dating to 1702 (1657–1732). Phenotypic resistances for fluoroquinolones (FLQ), isoniazid (INH), kanamycin (KAN) and rifampicin (RMP) are provided as outer coloured rings. Most samples are from Peru (purple), though two samples are from Europe (Sweden and the Netherlands). b) Provides the generalised skyline plot estimate of effective population size through time based on the timed phylogeny of this clade. Grey lines provide the full skyline plot, black lines provide the coalescent intervals. The first clinical use of clofazimine and bedaquiline are provided by the axis at top. Table S2. Source of whole genome sequences included in the global lineage 2 and lineage 4 alignments following quality checks and as given in Table S1. The number in brackets designate those with mmpR5 differing from wild type. Table S3. Classification of previously observed resistance associated with mmpR5 variants identified in this study. Table S4. Sequence data identified with mmpR5 variants predating 2007. Dates flagged with an asterisk (*) indicate those dates which have been permuted using the metadata of all samples (see Est. column of Supplementary Table S1). Table S5. Number of estimated emergence (homoplasic) events for major mmpR5 variants considered. Table S6. Summary of phylogenetic dating approaches applied to the L4 and L2 datasets. BactDating was run in both cases but failed to converge after 1e7 or 3e7 MCMC iterations for the L4 dataset. The subsampled BEAST2 runs highlighted yellow provided the highest likelihood following path sampling over all strict clock models and were run only on accessions with associated collection dates. These rates were applied to the maximum likelihood phylogenetic tree for temporal estimation of resistance emergence (main text Fig. 2, see Methods). Table S7 [external excel document]. Inferred age of nodes and preceding nodes for L2 samples with mmpR5 nonsynonymous variants. Cells are coloured as per phenotype annotations (see main text Fig. 1, 2, 3). Presence of mmpL5 variants is noted, as are MICs where available. TBProfiler resistance profiles as either “S” for susceptible, “RR” for rifampicinresistant and “preXDR” for fluoroquinolone-resistant. Table S8 [external excel document]. Predicted probability of bedaquiline resistance based on the amino acid properties of mmpR5 variants following a machine learning predictive approach (see Methods and Supplementary Note 1). Table S9. Precision, recall, F1, AUPRC, sensitivity and specificity scores for gradient-boosted tree classifier. Standard deviation was calculated across the 10 outer loops of the nested crossvalidation protocol. Supplementary Note 1. Predicting bedaquline resistance using machine learning techniques.