The mutational signatures of poor treatment outcomes on the drug-susceptible Mycobacterium tuberculosis genome

  1. Yiwang Chen
  2. Qi Jiang
  3. Mijiti Peierdun
  4. Howard E Takiff
  5. Qian Gao  Is a corresponding author
  1. Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS), School of Basic Medical Sciences, Shanghai Medical College, Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, China
  2. National Clinical Research Center for Infectious Diseases, Shenzhen Third People's Hospital, China
  3. School of Public Health, Public Health Research Institute of Renmin Hospital, Wuhan University, China
  4. Department of Epidemiology and Biostatistics,School of Public Health, Xinjiang Medical University, China
  5. Instituto Venezolano de Investigaciones Cientificas (IVIC), Venezuela
5 figures, 3 tables and 1 additional file

Figures

Sample origin and genetic structure of Mycobacterium tuberculosis.

(A) Geographic location of the samples analyzed and study cohort characteristics. (B) The phylogenetic tree of 3196 drug-susceptible tuberculosis strains. The different colors on the branches indicate different lineages and sublineages. The outside circle indicates the treatment outcomes of corresponding patients.

Figure 2 with 4 supplements
Generation of the functional mutation set.

(A) Manhattan plots of genome-wide association study (GWAS) for fixed single nucleotide polymorphisms (SNPs) associated with poor treatment outcomes. The dashed red line highlights the Bonferroni-corrected threshold (p=5.04 × 10–7). (B) Distribution of GWAS identified unfixed SNPs across gene functional categories. CWP, cell wall, and cell processes; IMR, intermediary metabolism, and respiration; CH, conserved hypotheticals; LM, lipid metabolism; IP, information pathways; RP, regulatory proteins; VDA, virulence, detoxification, adaptation; UN, unknown. (C) Gene prioritization strategies (based on p-value rank) for significantly associated unfixed SNPs. (D) Gene expression from RNA-seq (log2FPKM) of Rv2164c under drug pressure and hypoxia.

Figure 2—figure supplement 1
Manhattan plots of unfixed single nucleotide polymorphisms (SNPs) associated with poor treatment outcomes.

The top 50 unfixed mutations were annotated with the gene. The dashed red line highlights the Bonferroni-corrected threshold (p=4.82 × 10–6).

Figure 2—figure supplement 2
Gene expression (log2FPKM) from RNA-seq after drug exposure and hypoxia.
Figure 2—figure supplement 3
Within-host frequency distribution of genome-wide association study (GWAS)-identified unfixed mutations.
Figure 2—figure supplement 4
Manhattan plot of genome-wide association study (GWAS) analysis based on the Malawi dataset.

The dashed red line highlights the Bonferroni-corrected threshold (p=2.66 × 10–6).

Bacterial whole-genome mutation features between patients with different treatment outcomes.

(A) The proportion of six mutation types in all fixed and unfixed mutations (t-test, mean range: mean ± SE). (B) Distribution of total unfixed mutations and nonsynonymous unfixed mutations across gene functional categories (t-test). VDA, virulence, detoxification, adaptation; LM, lipid metabolism; IP, information pathways; CWP, cell wall, and cell processes; ISP, insertion seqs and phages; IMR, intermediary metabolism, and respiration; RP, regulatory proteins; CH, conserved hypotheticals; UN, unknown. (C) Comparison of nucleotide genetic diversity between isolated patients with good and poor outcomes (t-test). (D) Distribution of Mycobacterium tuberculosi (MTB) lineages and sublineages (chi-square test). p-value <0.05 was considered significant. *, p<0.05, ns, no significant.

Effects of genome-wide association study (GWAS) identified mutations on tuberculosis treatment outcomes.

(A) Univariable and multivariable logistic regression on the risk factors for poor treatment outcomes. (B) Nomogram for predicting the probability of poor treatment outcomes. (C) ROC curves are based on risk factors that may be predictive of tuberculosis treatment outcomes. p-value <0.05 was considered significant. *p<0.05, **p<0.01, ***p<0.001.

Author response image 1
Schematics of false positive filter in three single colonies.

The density plot above the scatter plot shows the distribution of mutation depth while the plot to the right of the scatter plot shows the distribution of mutation frequency. The first row shows the SNP calling results from the raw data, in which there were many false positive mutations (FPMs). The second row shows the results after most FPMs were filtered out, leaving only those SNPs with frequency greater than 5% (horizontal yellow dashed line) and sequencing depth greater than 5 (vertical red dashed line). The third row shows the results after the remaining FPMs were filtered out with our validated pipeline.

Tables

Author response table 1
Comparison of the ratio of strains carrying the GWAS-identified fixed mutation in different lineages.
L2L4P-valueL2L4P-value
Rv0051 Q149HYes550.13FctpB
E345K
Yes27150.14
No2368818No2346808
Rv0260c
T72I
Yes41220.09Rv0648
P454S
Yes87420.07
No2332801No2286781
Rv1248c
*1232S
Yes87430.05Rv1747
T191A
Yes9466<0.001
No2286780No2279757
otsB1
G559D
Yes1490.14cobN
A751V
Yes9860<0.001
No2359814No2275763
Rv2164c
D233G
Yes96460.06dlaT
V55A
Yes94500.01
No2277777No2279773
Rv3168
E308*
Yes1790.30metA
G146D
Yes106500.07
No2356814No2267773
metA E149GYes104560.01papA1
I497T
Yes511F
No2273763No2368822
Author response table 2
Comparison of the ratios of strains carrying at least one GWAS-identified fixed mutation from relapse cases with strains from all other patients.
GWAS-identified mutationsP-value
YesNo
RelapseYes1334P < 0.001
No2412908
Author response table 3
Comparison of the ratio of strains carrying at least one GWAS-identified fixed mutation from the relapse cases with strains from patients with other poor treatment outcomes.
GWAS-identified mutationsP-value
YesNo
RelapseYes1334P = 0.422
No935

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  1. Yiwang Chen
  2. Qi Jiang
  3. Mijiti Peierdun
  4. Howard E Takiff
  5. Qian Gao
(2023)
The mutational signatures of poor treatment outcomes on the drug-susceptible Mycobacterium tuberculosis genome
eLife 12:e84815.
https://doi.org/10.7554/eLife.84815