1. Microbiology and Infectious Disease
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Impact of HIV co-infection on the evolution and transmission of multidrug-resistant tuberculosis

  1. Vegard Eldholm  Is a corresponding author
  2. Adrien Rieux
  3. Johana Monteserin
  4. Julia Montana Lopez
  5. Domingo Palmero
  6. Beatriz Lopez
  7. Viviana Ritacco
  8. Xavier Didelot  Is a corresponding author
  9. Francois Balloux  Is a corresponding author
  1. Norwegian Institute of Public Health, Norway
  2. University College London, United Kingdom
  3. ANLIS Carlos Malbrán, Argentina
  4. Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Argentina
  5. Hospital Muñiz, Argentina
  6. Imperial College London, United Kingdom
Research Article
Cite this article as: eLife 2016;5:e16644 doi: 10.7554/eLife.16644
6 figures, 4 tables and 3 additional files

Figures

Whole-genome Bayesian evolutionary phylogeny of the M outbreak.

The peripheral color strips indicate the HIV status of patients from which the clinical isolates were collected and the resistance burden of the isolate. The scale bar is given in years since the most recent common ancestor of the outbreak.

https://doi.org/10.7554/eLife.16644.003
Figure 2 with 1 supplement
Impact of HIV co-infection on Mtb evolution.

Left: Rate of evolution (substitutions/site/year) on terminal branches (p = 0.1920). Right: resistance load (number of antimicrobials to which resistance-conferring mutations were found in clinical Mtb isolates, stratified by HIV status of the host.

https://doi.org/10.7554/eLife.16644.005
Figure 2—figure supplement 1
Evolution of Mtb within patients as a function of HIV status.

From top to bottom: Rate of evolution (substitutions/site/year) (p=0.1920). Terminal branch lengths (p=0.0006). Number of SNPs on terminal branches (p=0.0009). *** denotes p<0.001.

https://doi.org/10.7554/eLife.16644.006
Figure 3 with 3 supplements
Reconstruction of transmission events.

(A) Graphs representing two selected high-likelihood transmission chains. The colors of the edges indicate the probabilities of each transmission event from high (red) to lower (orange). Patient HIV-status is indicated by grey (negative) and blue (positive). (B) The corresponding transmission chains annotated in the timed phylogenetic tree. Red color highlights isolates linked by transmission events from a single source. Branches in magenta indicate subsequent transmission from a secondary case to additional cases (blue).

https://doi.org/10.7554/eLife.16644.008
Figure 3—source data 1

Likelihood matrix of all possible pairwise transmission events.

https://doi.org/10.7554/eLife.16644.009
Figure 3—source data 2

Conversion table linking transmission graph nodes and sample IDs.

https://doi.org/10.7554/eLife.16644.010
Figure 3—figure supplement 1
Inferred transmission graph including all 251 transmission events (grey boxes HIV negative; blue HIV positive).Graph edges colored by likelihood from high (red) to low (yellow).
https://doi.org/10.7554/eLife.16644.011
Figure 3—figure supplement 2
Inferred transmission graph including only the most likely transmissions after applying various cut-offs (grey boxes HIV negative; blue HIV positive).Graph edges colored by likelihood from high (red) to low (yellow).

(A) Top 45% likely transmissions. (B) Top 35% likely transmissions. (C) Top 25% likely transmissions.

https://doi.org/10.7554/eLife.16644.012
Figure 3—figure supplement 3
Top 25% likely transmission events mapped on the timed phylogeny.

Red coloring is used to highlight isolates linked by transmission events from a single source. Branches in magenta indicate isolates transmitted further from one of the secondary cases to other cases (blue).

https://doi.org/10.7554/eLife.16644.013
Estimating latency time as a function of HIV status.

(A) For pairs of samples connected by a transmission event from i to j, transmission of Mtb is expected to have occurred on the terminal branch above j. Even though we do not know exactly when j went from latent TB to active TB, the latent period is included in the length of the terminal branch leading to j (see main text). We therefore use this branch length as an upwardly biased estimate for latency time. (B) For transmission pairs in the calculated transmission networks, the length (in years) of terminal branches leading to the recipient of the pairs (overestimated latency period) was extracted and stratified by HIV status of the recipient. To account for incomplete sampling, the analyses were performed on all 251 calculated transmission events as well as subsets including only the most likely transmission pairs (top 45, 35 and 25%). ***denotes p<0.001, *denotes p<0.05 as determined by unpaired t-test.

https://doi.org/10.7554/eLife.16644.016
Figure 5 with 1 supplement
Correlations between global patterns of HIV, TB and MDR-TB prevalence.

Clockwise: Per country prevalence of MDR-TB as a function of TB prevalence (p=2.2 × 10−16); TB prevalence as a function of HIV prevalence (p=5.9 × 10−6); MDR-TB prevalence as a function of HIV prevalence (p=1.6 × 10−4); Proportion of MDR-TB cases among TB patients as a function of HIV prevalence (p=0.8). All values are log-transformed. The depth of shading of individual dots reflect the TB prevalence in individual countries.

https://doi.org/10.7554/eLife.16644.017
Figure 5—source data 1

Global per-country health, economy and disease metrics.

https://doi.org/10.7554/eLife.16644.018
Figure 5—figure supplement 1
Correlations between global patterns of HIV, TB and MDR-TB prevalence restricted to the top 50% countries in terms of GDP per capita.

Clockwise: Per country prevalence of MDR-TB as a function of TB prevalence (p=1.5 × 10−15); TB prevalence as a function of HIV prevalence (p=5.3 × 10−5); MDR-TB prevalence as a function of HIV prevalence (p=5.1 × 10−5); Proportion of MDR-TB cases among TB patients as a function of HIV prevalence (p=0.11). All values are log-transformed. The depth of shading of individual dots reflect the TB prevalence in individual countries.

https://doi.org/10.7554/eLife.16644.019
Timed phylogeny used in simulation of SEIR model.
https://doi.org/10.7554/eLife.16644.020

Tables

Table 1

Number of SNPs accumulated in clinical isolates.

https://doi.org/10.7554/eLife.16644.004

Host HIV status

n

Mutations total

Mean number per isolate

χ2 p-value

Negative

99

262

2.646

< 0.001

Positive

153

277

1.810

Table 2

Identified events of within-patient acquired resistance.

https://doi.org/10.7554/eLife.16644.007

Isolate ID

HIV

Treatment history

Mutation

Acquired resistance

107

-

follow-up (ETH* treated)

ethA L225fs

ETH

108

-

follow-up (ETH and FLQ treated)

ethA S208P

ETH

516

-

follow-up (unknown treatment)

pncA D129G

PZA

1757

-

follow-up (ETH and FLQ treated)

ethA H22P

ETH

2098

-

follow-up (ETH and FLQ treated)

ethA F302S + gyrB D461V

ETH + FLQ

2485

-

follow-up (unknown treatment)

ethA G437fs

ETH

POGU

-

follow-up (ETH and FLQ treated)

ethA R259fs + gyrB R292G

ETH + FLQ

110

+

follow-up (ETH and FLQ treated)

gyrB R446S

FLQ

257

+

follow-up (ETH and FLQ treated)

inhA -15 C>T

ETH

1298

+

follow-up (ETH and FLQ treated)

gyrA D94N

FLQ

2569

+

follow-up (ETH treated)

ethA S251fs

ETH

  1. *Patient received the ETH analogue prothionamide

Table 3

Number of reconstructed transmission events.

https://doi.org/10.7554/eLife.16644.014

Transmission event cut-off

Donor HIV status

Observed

Expected

Obs/Exp

χ2 p value

All transmissions

Negative

80

98.61

0.81

0.3185

Positive

171

152.39

1.12

Top 25% events

Negative

20

24.75

0.81

0.2205

Positive

43

38.25

1.12

Top 35% events

Negative

30

34.57

0.87

 0.3185

Positive

58

53.43

1.09

Top 45% events

Negative

36

44.39

0.81

0.1060

Positive

77

68.61

1.12

Table 4

Distribution of transmissions as a function of HIV status of transmitter.

https://doi.org/10.7554/eLife.16644.015

All transmission events

Transmissions per transmitter:

Kruskal-Wallis p value

HIV status

none

1

2

3

4

5

6

7

8

9

10

11

 

neg

50

37

4

2

1

5

0

0

0

0

0

0

0.075

pos

63

58

11

10

5

2

2

1

0

0

0

1

Top 25% likely transmission events

Transmissions per transmitter:

 

HIV status

none

1

2

3

4

5

 

neg

83

15

0

0

0

1

0.304

pos

121

25

3

4

0

0

Top 35% likely transmission events

Transmissions per transmitter:

 

HIV status

none

1

2

3

4

5

 

neg

75

21

2

0

0

1

0.505

pos

111

33

4

4

0

1

Top 45% likely transmission events

Transmissions per transmitter:

 

HIV status

none

1

2

3

4

5

 

neg

69

27

2

0

0

1

0.324

pos

100

39

7

5

1

1

Additional files

Supplementary file 1

M. tuberculosis sample information.

https://doi.org/10.7554/eLife.16644.021
Supplementary file 2

Patient treatment histories.

https://doi.org/10.7554/eLife.16644.022
Supplementary file 3

SNP distances and transmission reconstruction results for samples pairs with known epidemiological link.

https://doi.org/10.7554/eLife.16644.023

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