Biology subjects

Gagneux, S.

Publications and source records attributed to Gagneux, S..

13 recordsLinked to original sources

bioRxiv2018

Insights into the genetic diversity of Mycobacterium tuberculosis in Tanzania

BackgroundHuman tuberculosis (TB) is caused by seven phylogenetic lineages of the Mycobacterium tuberculosis complex (MTBC), Lineage 1-7. Recent advances in rapid genotyping of MTBC based on single nucleotide polymorphisms (SNP), allow for rapid and phylogenetically robust strain classification, paving the way for defining genotype-phenotype relationships in clinical settings. Such studies have revealed that, in addition to host and environmental factors, different strains of the MTBC influence the outcome of TB infection and disease. In Tanzania, such molecular epidemiological studies of TB however are scarce in spite of a high TB burden.\n\nMethods and FindingsHere we used a SNP-typing method to genotype a nationwide collection of 2,039 MTBC clinical isolates obtained from new and retreatment TB cases diagnosed in 2012 and 2013. Four lineages, namely Lineage 1-4 were identified. The distribution and frequency of these lineages varied across the regions but overall, Lineage 4 was the most frequent (n=866, 42.5%), followed by Lineage 3 (n=681, 33.4%) and 1 (n=336, 16.5%), with Lineage 2 being the least frequent (n=92, 4.5%). A total of 64 (3.1%) isolates could not be assigned to any lineage. We found Lineage 2 to be associated with female sex (adjusted odds ratio [aOR] 2.25; 95% confidence interval [95% CI] 1.38 - 3.70, p<0.001) and retreatment (aOR 1.78; 95% CI 1.00 - 3.02, p=0.040). We found no associations between MTBC lineage and patient age or HIV status. Our sublineage typing based on spacer oligotyping revealed the presence of mainly EAI, CAS and LAM families. Finally, we detected low levels of multidrug resistant isolates among a subset of retreatment cases\n\nConclusionsThis study provides novel insights into the influence of pathogen-related factors on the TB epidemic in Tanzania.

epidemiology↗

bioRxiv2018

Transition bias influences the evolution of antibiotic resistance in Mycobacterium tuberculosis

Transition bias, an overabundance of transitions relative to transversions, has been widely reported among studies of mutations spreading under relaxed selection. However, demonstrating the role of transition bias in adaptive evolution remains challenging. We addressed this challenge by analyzing adaptive antibiotic-resistance mutations in the major human pathogen Mycobacterium tuberculosis. We found strong evidence for transition bias in two independently curated datasets comprising 152 and 208 antibiotic resistance mutations. This was true at the level of mutational paths (distinct, adaptive DNA sequence changes) and events (individual instances of the adaptive DNA sequence changes), and across different genes and gene promoters conferring resistance to a diversity of antibiotics. It was also true for mutations that do not code for amino acid changes (in gene promoters and the ribosmal gene rrs), and for mutations that are synonymous to each other and are therefore likely to have similar fitness effects, suggesting that transition bias can be caused by a bias in mutation supply. These results point to a central role for transition bias in determining which mutations drive adaptive antibiotic resistance evolution in a key pathogen.\n\nSignificance statementWhether and how transition bias influences adaptive evolution remain open questions. We studied 296 DNA mutations that confer antibiotic resistance to the human pathogen Mycobacterium tuberculosis. We uncovered strong transition bias among these mutations and also among the number of times each mutation has evolved in different strains or geographic locations, demonstrating that transition bias can influence adaptive evolution. For a subset of mutations, we were able to rule out an alternative selection-based hypothesis for this bias, indicating that transition bias can be caused by a biased mutation supply. By revealing this bias among M. Tuberculosis resistance mutations, our findings improve our ability to predict the mutational pathways by which pathogens overcome treatment.

evolutionary biology↗

bioRxiv2018

Multiple Introductions of the Mycobacterium tuberculosis Lineage 2 Beijing into Africa over centuries

The Lineage 2-Beijing (L2-Beijing) sub-lineage of Mycobacterium tuberculosis has received much attention due to its high virulence, fast disease progression, and association with antibiotic resistance. Despite several reports of the recent emergence of L2-Beijing in Africa, no study has investigated the evolutionary history of this sub-lineage on the continent. In this study, we used whole genome sequences of 817 L2 clinical strains from 14 geographical regions globally distributed to investigate the origins and onward spread of this lineage in Africa. Our results reveal multiple introductions of L2-Beijing into Africa linked to independent bacterial populations from East-and Southeast Asia. Bayesian analyses further indicate that these introductions occurred during the past 300 years, with most of these events pre-dating the antibiotic era. Hence, the success of L2-Beijing in Africa is most likely due to its hypervirulence and high transmissibility rather than drug resistance.

evolutionary biology↗

bioRxiv2018

Whole genome sequencing for drug resistance profile prediction in Mycobacterium tuberculosis

Whole genome sequencing allows rapid detection of drug-resistant M. tuberculosis isolates. However, high-quality data linking quantitative phenotypic drug susceptibility testing (DST) and genomic data have thus far been lacking.\n\nWe determined drug resistance profiles of 176 genetically diverse clinical M. tuberculosis isolates from Democratic Republic of the Congo, Ivory Coast, Peru, Thailand and Switzerland by quantitative phenotypic DST for 11 antituberculous drugs using the BD BACTEC MGIT 960 system and 7H10 agar dilution to generate a cross-validated phenotypic DST readout. We compared phenotypic drug susceptibility results with predicted drug resistance profiles inferred by whole genome sequencing.\n\nBoth phenotypic DST methods identically classified the strains into resistant/susceptible in 73-99% of the cases, depending on the drug. Changes in minimal inhibitory concentrations were readily explained by mutations identified by whole genome sequencing. Using the whole genome sequences we were able to predict quantitative drug resistance levels where wild type and mutant MIC distributions did not overlap. The utility of genome sequences to predict quantitative levels of drug resistance was partially limited due to incompletely understood mechanisms influencing the expression of phenotypic drug resistance. The overall sensitivity and specificity of whole genome-based DST were 86.8% and 94.5%, respectively.\n\nDespite some limitations, whole genome sequencing has high predictive power to infer resistance profiles without the need for time-consuming phenotypic methods.\n\nOne sentence summaryWhole genome sequencing of clinical M. tuberculosis isolates accurately predicts drug resistance profiles and may replace culture-based drug susceptibility testing in the future.

microbiology↗

bioRxiv2018

Reference Set of Mycobacterium tuberculosis Clinical Strains: A tool for research and product development

The Mycobacterium tuberculosis complex (MTBC) causes tuberculosis (TB) in humans and various other mammals. The human-adapted members of the MTBC comprise seven phylogenetic lineages that differ in their geographical distribution. There is growing evidence that this phylogenetic diversity modulates the outcome of TB infection and disease. For decades, TB research and development has focused on the two canonical MTBC reference strains H37Rv and Erdman, both of which belong to Lineage 4. Relying on only a few laboratory-adapted strains can be misleading as study results might not be directly transferrable to clinical settings where patients are infected with a diverse array of strains, including drug-resistant variants. Here, we argue for the need to expand TB research and development by incorporating the phylogenetic diversity of the MTBC. To facilitate such work, we have assembled a group of 20 genetically well-characterized clinical strains representing the seven known human-adapted MTBC lineages. With the \"MTBC clinical strains reference set\" we aim to provide a standardized resource for the TB community. We hope it will enable more direct comparisons between studies that explore the physiology of MTBC beyond the lab strains used thus far. We anticipate that detailed phenotypic analyses of this reference strain set will increase our understanding of TB biology and assist in the development of new control tools that are universally effective.

microbiology↗

bioRxiv2018

A New Phylogenetic Framework for the Animal-adapted Mycobacterium tuberculosis Complex

Tuberculosis (TB) affects humans and other animals and is caused by bacteria from the Mycobacterium tuberculosis complex (MTBC). Previous studies have shown that there are at least nine members of the MTBC infecting animals other than humans; these have also been referred to as ecotypes. However, the ecology and the evolution of these animal-adapted MTBC ecotypes are poorly understood. Here we screened 12,886 publicly available MTBC genomes and newly sequenced 17 animal-adapted MTBC strains, gathering a total of 529 genomes of animal-adapted MTBC strains. Phylogenomic and comparative analyses confirm that the animal-adapted MTBC members are paraphyletic with some members more closely related to the human-adapted Mycobacterium africanum Lineage 6 than to other animal-adapted strains. Furthermore, we identified four main animal-adapted MTBC clades that might correspond to four main host shifts; two of these clades are proposed to reflect independent cattle domestication events. Contrary to what would be expected from an obligate pathogen, MTBC nucleotide diversity was not positively correlated with host phylogenetic distances, suggesting that host tropism in the animal-adapted MTBC seems to be driven more by contact rates and demographic aspects of the host population rather than host relatedness. By combining phylogenomics with ecological data, we propose an evolutionary scenario in which the ancestor of Lineage 6 and all animal-adapted MTBC ecotypes was a generalist pathogen that subsequently adapted to different host species. This study provides a new phylogenetic framework to better understand the evolution of the different ecotypes of the MTBC and guide future work aimed at elucidating the molecular mechanisms underlying host specificity.

evolutionary biology↗

bioRxiv2018

Drug susceptibility testing and mortality in patients treated for tuberculosis in high-burden countries

BackgroundDrug resistance and HIV co-infection are challenges for the global control of tuberculosis.\n\nMethodsWe collected Mycobacterium tuberculosis isolates from adult patients in Cote dIvoire, Democratic Republic of the Congo, Kenya, Nigeria, South Africa, Peru, and Thailand, stratified by HIV status and tuberculosis drug resistance. Molecular or phenotypic drug susceptibility testing (DST) was done locally and at the Swiss tuberculosis reference laboratory. We examined mortality during treatment according to DST results and treatment adequacy in logistic regression models adjusting for sex, age, sputum microscopy and HIV status.\n\nFindings634 tuberculosis patients were included; median age was 33.2 years, 239 (37.7%) were female, 272 (42.9%) HIV-positive and 69 (10.9%) patients died. Based on the reference laboratory DST, 394 (62.2%) strains were pan-susceptible, 45 (7.1%) mono-resistant, 163 (25.7%) multidrug-resistant (MDR-TB), and 30 (4.7%) had pre-extensive or extensive drug resistance (pre-XDR/XDR-TB). Results of reference and local laboratories were discordant in 121 (19.1%) cases, corresponding to a sensitivity of 84.3% and a specificity of 90.8%. In patients with drug-resistant tuberculosis, discordant results were associated with increased mortality (risk ratio 1.81; 95% CI 1.07-3.07). In logistic regression, compared to adequately treated patients with pan-susceptible strains, the adjusted odds ratio for death was 4.23 (95% CI 2.16-8.29) for adequately treated patients with drug-resistant strains and 21.54 (95% CI 3.36-138.1) for inadequately treated patients with drug-resistant strains. HIV status was not associated with mortality.\n\nInterpretationUsing a reference laboratory standard, inaccurate DST leading to inappropriate treatment of drug-resistant tuberculosis, but not HIV infection, contributed to mortality.

epidemiology↗

bioRxiv2018

Compensatory evolution drives multidrug-resistant tuberculosis in Central Asia

Bacterial factors favoring the unprecedented multidrug-resistant tuberculosis (MDR-TB) epidemic in the former Soviet Union remain unclear.\n\nWe utilized whole genome sequencing and Bayesian statistics to analyze the evolutionary history, temporal emergence of resistance and transmission networks of MDR-MTBC strains from Karakalpakstan, Uzbekistan (2001-2006).\n\nOne MTBC-clone (termed Central Asian outbreak, CAO) with resistance mediating mutations to eight anti-TB drugs existed prior the worldwide introduction of standardized WHO-endorsed directly observed treatment, short-course (DOTS). DOTS implementation in Karakalpakstan in 1998 likely selected for these CAO-strains, comprising 75% of sampled MDR-TB strains in 2005/2006. CAO-strains were also identified in a previously published cohort from Samara, Russia (2008-2010). Similarly, transmission success and resistance development was linked to mutations compensating fitness deficits associated with rifampicin resistance.\n\nThe genetic make-up of these outbreak clades threatens the success of both empirical and standardized guideline driven MDR-TB therapies, including the newly WHO-endorsed short MDR-TB regimen in Uzbekistan.

evolutionary biology↗

bioRxiv2018

Genomic determinants of sympatric speciation of the Mycobacterium tuberculosis complex across evolutionary timescales.

BACKGROUNDModels on how bacterial lineages differentiate increase our understanding on early bacterial speciation events and about the genetic loci involved. Here, we analyze the population genomics events leading to the emergence of the tuberculosis pathogen.\n\nRESULTSThe emergence is characterized by a combination of recombination events involving core pathogenesis functions and purifying selection on early diverging loci. We identify the phoR gene, the sensor kinase of a two-component system involved in virulence, as a key functional player subject to pervasive positive selection after the divergence of the MTBC from its ancestor. Previous evidence showed that phoR mutations played a central role in the adaptation of the pathogen to different host species. Now we show that phoR have been under selection during the early spread of human tuberculosis, during later expansions and in on-going transmission events.\n\nCONCLUSIONSOur results show that linking pathogen evolution across evolutionary and epidemiological timescales point to past and present virulence determinants.

evolutionary biology↗

bioRxiv2018

Treemmer: a tool to reduce large phylogenetic datasets with minimal loss of diversity

Large sequence datasets are difficult to visualize and handle. Additionally, they are often not an adequate representation of the natural diversity, but the result of uncoordinated and convenience sampling. Consequently, they can suffer from redundancy and sampling biases. Here we present Treemmer, a simple tool to evaluate the redundancy of phylogenetic trees and reduce their complexity by eliminating leaves that contribute the least to the tree diversity.\n\nTreemmer can reduce the size of datasets with different phylogenetic structures and levels of redundancy while maintaining a sub-sample that is representative of the original diversity.

bioinformatics↗

bioRxiv2017

Tuberculosis outbreak investigation using phylodynamic analysis

The fast evolution of pathogenic viruses has allowed for the development of phylodynamic approaches that extract information about the epidemiological characteristics of viral genomes. Thanks to advances in whole genome sequencing, they can be applied to slowly evolving bacterial pathogens like Mycobacterium tuberculosis.\n\nIn this study, we investigate the epidemiological dynamics underlying two M. tuberculosis outbreaks using phylodynamic methods. The first outbreak occurred in the Swiss city of Bern (1993-2012) and was caused by a drug-susceptible strain belonging to the phylogenetic M. tuberculosis Lineage 4. The second outbreak was caused by a multidrug-resistant (MDR) strain of Lineage 2, imported from the Wat Tham Krabok (WTK) refugee camp in Thailand into California.\n\nThere is little temporal signal in the Bern data set and moderate temporal signal in the WTK data set. We estimate an evolutionary rate of 0.0039 per single nucleotide polymorphism (SNP) per year for Bern and 0.0024 per SNP per year for WTK. Nevertheless, due to its high sampling proportion (90%) the Bern outbreak allows robust estimation of epidemiological parameters despite the poor temporal signal. Conversely, theres much uncertainty in the epidemiological estimates concerning the WTK outbreak, which has a small sampling proportion (9%). Our results suggest that both outbreaks peaked around 1990, although the Bernese outbreak was only detected in 1993, and the WTK outbreak around 2004. Furthermore, individuals were infected for a significantly longer period (around 9 years) in the WTK outbreak than in the Bern outbreak (4-5 years).\n\nOur work highlights both the limitations and opportunities of phylodynamic analysis of outbreaks involving slowly evolving pathogens: (i) estimation of the evolutionary rate is difficult on outbreak time scales and (ii) a high sampling proportion allows quantification of the age of the outbreak based on the sampling times, and thus allows for robust estimation of epidemiological parameters.

epidemiology↗

bioRxiv2017

Reduced transmission of Mycobacterium africanum compared to Mycobacterium tuberculosis in urban West Africa

BackgroundUnderstanding transmission dynamics is useful for tuberculosis (TB) control. We conducted a population-based molecular epidemiological study to understand TB transmission in Ghana.\n\nMethodsMycobacterium tuberculosis complex (MTBC) isolates obtained from prospectively-sampled pulmonary TB patients between July, 2012 and December, 2015 were confirmed as MTBC using IS6110 PCR. MTBC lineages were identified by large sequence polymorphism and single nucleotide polymorphism assays and further characterized using spoligotyping and standard 15-loci MIRU-VNTR typing. We used the n-1 method to estimate recent TB transmission and identified associated risk factors using logistic regression analysis.\n\nFindingsOut of 2,309 MTBC isolates, we identified 1,082 (46{middle dot}9%) single cases with 1,227 (53{middle dot}1%) isolates belonging to one of 276 clustered cases (clustering range; 2-35). Recent TB transmission rate was estimated to be 41{middle dot}2%. While we see no significant difference in the recent transmission rates between lineages of Mycobacterium africanum (lineage-5 (31{middle dot}8%); lineage-6 (24{middle dot}7%), p=0{middle dot}118), we found that lineage-4 belonging to the M. tuberculosis transmitted significantly higher (44{middle dot}9%, p<0{middle dot}001). Finally, apart from age being significantly associated with recent TB transmission (p=0{middle dot}007), we additionally identified a significant departure in the male/female ratio among very large clustered cases compared to the general TB patient population (3:1 vs. 2:1, p=0{middle dot}022).\n\nInterpretationsOur findings indicate high recent TB transmission suggesting occurrences of unsuspected outbreaks. The observed reduced transmission rate of M. africanum suggests other factor(s) may be responsible for its continuous presence in West Africa.\n\nFundingWellcome Trust Intermediate Fellowship Grant 097134/Z/11/Z to Dorothy Yeboah-Manu.

epidemiology↗

bioRxiv2017

Comparative genomics of Mycobacterium africanum Lineage 5 and Lineage 6 from Ghana suggests different ecological niches

Mycobacterium africanum (Maf) causes up to half of human tuberculosis in West Africa, but little is known on this pathogen. We compared the genomes of 253 Maf clinical isolates from Ghana, including both L5 and L6. We found that the genomic diversity of L6 was higher than in L5, and the selection pressures differed between both groups. Regulatory proteins appeared to evolve neutrally in L5 but under purifying selection in L6. Conversely, human T cell epitopes were under purifying selection in L5, but under positive selection in L6. Although only 10% of the T cell epitopes were variable, mutations were mostly lineage-specific. Our findings indicate that Maf L5 and L6 are genomically distinct, possibly reflecting different ecological niches.

genomics↗