Compensatory evolution drives multidrug-resistant tuberculosis in Central Asia

Merker, Matthias; Barbier, Maxime; Cox, Helen; Rasigade, Jean‐Philippe; Feuerriegel, Silke; Köhl, Thomas; Diel, Roland; Borrell, Sònia; Gagneux, Sebastian; Nikolayevskyy, Vladyslav; Andres, Sönke; Nübel, Ulrich; Supply, Philip; Wirth, Thierry; Niemann, Stefan

doi:10.1101/334599

Cited by 14 publications

(26 citation statements)

References 26 publications

(43 reference statements)

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“…Cases with resistance beyond the four drugs/drug classes defining extensively drug-resistant TB (XDR-TB, resistance to isoniazid, rifampicin, at least one second-line injectable and a fluoroquinolone) are the result of further acquisition of resistance [1][2][3], primary (transmitted) resistance [4] or a combination thereof [5]. Strains of the Beijing lineage of the Mycobacterium tuberculosis complex have previously been associated with an increased ability to develop multidrug resistance (MDR, resistance to at least isoniazid and rifampicin) and spread [6][7][8]. Examples are the documented outbreaks in Russia [9] and South Africa (Gauteng Province) [10], as well as the widespread transmission of a highly resistant strain in the Eastern Cape (EC) Province of South Africa [4].…”

Section: Introductionmentioning

confidence: 99%

A landscape of genomic alterations at the root of a near-untreatable tuberculosis epidemic

Klopper

Heupink

Hill-Cawthorne

et al. 2020

BMC Med

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Background: Atypical Beijing genotype Mycobacterium tuberculosis strains are widespread in South Africa and have acquired resistance to up to 13 drugs on multiple occasions. It is puzzling that these strains have retained fitness and transmissibility despite the potential fitness cost associated with drug resistance mutations. Methods: We conducted Illumina sequencing of 211 Beijing genotype M. tuberculosis isolates to facilitate the detection of genomic features that may promote acquisition of drug resistance and restore fitness in highly resistant atypical Beijing forms. Phylogenetic and comparative genomic analysis was done to determine changes that are unique to the resistant strains that also transmit well. Minimum inhibitory concentration (MIC) determination for streptomycin and bedaquiline was done for a limited number of isolates to demonstrate a difference in MIC between isolates with and without certain variants. Results: Phylogenetic analysis confirmed that two clades of atypical Beijing strains have independently developed resistance to virtually all the potent drugs included in standard (pre-bedaquiline) drug-resistant TB treatment regimens. We show that undetected drug resistance in a progenitor strain was likely instrumental in this resistance acquisition. In this cohort, ethionamide (ethA A381P) resistance would be missed in first-line drug-susceptible isolates, and streptomycin (gidB L79S) resistance may be missed due to an MIC close to the critical concentration. Subsequent inadequate treatment historically led to amplification of resistance and facilitated spread of the strains. Bedaquiline resistance was found in a small number of isolates, despite lack of exposure to the drug. The highly resistant clades also carry inhA promoter mutations, which arose after ethA and katG mutations. In these isolates, inhA promoter mutations do not alter drug resistance, suggesting a possible alternative role. Conclusion:The presence of the ethA mutation in otherwise susceptible isolates from ethionamide-naïve patients demonstrates that known exposure is not an adequate indicator of drug susceptibility. Similarly, it is demonstrated that bedaquiline resistance can occur without exposure to the drug. Inappropriate treatment regimens, due to missed resistance, leads to amplification of resistance, and transmission. We put these results into the context of current WHO treatment regimens, underscoring the risks of treatment without knowledge of the full drug resistance profile.

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Section: Introductionmentioning

confidence: 99%

A landscape of genomic alterations at the root of a near-untreatable tuberculosis epidemic

Klopper

Heupink

Hill-Cawthorne

et al. 2020

BMC Med

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“…To validate the method within a clinical setting we analyzed data from a study conducted in Uzbekistan between 2003 and 2008 30,46 , which was approved by the Médecins Sans Frontières international ethics review board. This already published study addressed the development of OFX resistance and the development of XDR-TB during MDR-TB treatment 30,46 . At that time the IS6110 DNA fingerprint method was used to check samples for re-and mixed infection 30 .…”

Section: Methodsmentioning

confidence: 99%

Detection of low-frequency resistance-mediating SNPs in next-generation sequencing data of Mycobacterium tuberculosis complex strains with binoSNP

Dreyer

Utpatel

Kohl

et al. 2020

Sci Rep

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Accurate drug resistance detection is key for guiding effective tuberculosis treatment. While genotypic resistance can be rapidly detected by molecular methods, their application is challenged by mixed mycobacterial populations comprising both susceptible and resistant cells (heteroresistance). for this, next-generation sequencing (nGS) based approaches promise the determination of variants even at low frequencies. However, accurate methods for a valid detection of low-frequency variants in nGS data are currently lacking. to tackle this problem, we developed the variant detection tool binoSnp which allows the determination of low-frequency single nucleotide polymorphisms (Snps) in nGS datasets from Mycobacterium tuberculosis complex (MtBc) strains. By taking a reference-mapped file as input, binoSNP evaluates each genomic position of interest using a binomial test procedure. binoSnp was validated using in-silico, in-vitro, and serial patient isolates datasets comprising varying genomic coverage depths (100-500×) and SNP allele frequencies (1-30%). Overall, the detection limit for low-frequency Snps depends on the combination of coverage depth and allele frequency of the resistance-associated mutation. binoSnp allows for valid detection of resistance associated Snps at a 1% frequency with a coverage ≥400×. in conclusion, binoSnp provides a valid approach to detect lowfrequency resistance-mediating Snps in nGS data from clinical MtBc strains. it can be implemented in automated, end-user friendly analysis tools for nGS data and is a step forward towards individualized tB therapy. Globally, tuberculosis (TB) is the leading cause of death from a single infectious agent with an estimated 1.3 million deaths and 10 million new TB cases in 2017 1. The emergence of drug-resistance challenges global TB control efforts with 558 000 estimated cases in 2017 being resistant to the frontline drug rifampicin (RMP); 82% of those were classified as multidrug resistant (MDR) strains, defined as showing additional resistance against isoniazid (INH) 1 and even 10% of those were estimated to be extremely drug resistant (XDR) which means carrying further resistances to a quinolone and one injectable drug 1. Early case detection, rapid drug susceptibility testing (DST), and effective treatment are core elements of global TB programs to control the spread, emergence, and transmission of resistant strains 2. Resistance of Mycobacterium tuberculosis complex (MTBC) strains is caused by spontaneous mutations, mainly single nucleotide polymorphisms (SNPs), in specific regions of the pathogen's genome. In general, mutations appear by chance with a probability of between 10-6 and 10-8 per generation depending on the observed locus 3. Normally, mutations in resistance associated genes are associated with a fitness cost, however, under a selection pressure such as antibiotic treatment resistant cells are selected and fixed in the population 4. The current gold standard to determine drug resistance in clinical MTBC strains is broth-based phenotypic...

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“…(9) A recent expansion of drug-resistant isolates in the country is linked to the spread of "successful" Central Asian/Russian sublineage of M. tuberculosis Beijing genotype. (10) At the same time, a number of studies have reported rapid acquisition of drug-resistance in the LAM family including KZN isolates from South Africa and LAM-RUS sublineage widespread in Kazakhstan and its neighboring countries. (8,11) In previous studies, the LAM genetic family was found at a proportion of 11% in a sample of 470 M. tuberculosis isolates from 12 provinces of Kazakhstan (51/470 = 10.85%).…”

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Genomic analysis of Latin American-Mediterranean family of Mycobacterium tuberculosis clinical strains from Kazakhstan

Tarlykov

Atavliyeva

Alenova³

et al. 2020

Mem. Inst. Oswaldo Cruz

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The human-adapted strains of the Mycobacterium tuberculosis complex (MTBC) comprise seven phylogenetic lineages originally associated with their geographical distribution. Here, we report the genomes of three drug-resistant clinical isolates of the Latin American-Mediterranean (LAM) family collected in Kazakhstan. We utilised whole-genome sequencing to study the distribution and drug resistance of these isolates. Phylogenetic analysis grouped the genomes described in this study with the sequences from Russia, Uzbekistan, and Kazakhstan belonging to the LAM family. One isolate has acquired extensive drug resistance to seven antituberculosis drugs. Our results suggest at least two multi-drug resistant (MDR)/extensively drug-resistant (XDR)-associated genotypes of the LAM family circulate in Kazakhstan.

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Compensatory evolution drives multidrug-resistant tuberculosis in Central Asia

Cited by 14 publications

References 26 publications

A landscape of genomic alterations at the root of a near-untreatable tuberculosis epidemic

A landscape of genomic alterations at the root of a near-untreatable tuberculosis epidemic

Detection of low-frequency resistance-mediating SNPs in next-generation sequencing data of Mycobacterium tuberculosis complex strains with binoSNP

Genomic analysis of Latin American-Mediterranean family of Mycobacterium tuberculosis clinical strains from Kazakhstan

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