The variability and reproducibility of whole genome sequencing technology for detecting resistance to anti-tuberculous drugs

The T120P or M172V mutation on rv2172c confers high level para-aminosalicylic acid resistance in Mycobacterium tuberculosis

Although para-aminosalicylic acid (PAS) has been used to treat tuberculosis for decades, mechanisms of resistance to this drug in Mycobacterium tuberculosis (M. tuberculosis) clinical isolates have not been thoroughly investigated. Previously, we found that decreased methylenetetrahydrofolate reductase (MTHFR) activity of Rv2172c led to increased sensitivity to antifolates in M. tuberculosis. In this study, we collected the genome-sequencing data of 173 PAS-resistant and 803 PAS-sensitive clinical isolates and analyzed rv2172c mutations in those 976 isolates. The results showed that two mutations (T120P and M172V) on rv2172c could be identified in a certain proportion (6.36%) of PAS-resistant isolates. The results of AlphaFold2 prediction indicated that the T120P or M172V mutation might affect the enzymatic activity of Rv2172c by influencing nicotinamide adenine dinucleotide (NADH) binding, and this was verified by subsequent biochemical analysis, demonstrating the role of residues Thr120 and Met172 on NADH binding and enzymatic activity of Rv2172c. In addition, the effect of rv2172c T120P or M172V mutation on methionine production and PAS resistance was determined in M. tuberculosis. The results showed that both T120P and M172V mutations caused increased intracellular methionine concentrations and high level PAS resistance. In summary, we discovered new molecular markers and also a novel mechanism of PAS resistance in M. tuberculosis clinical isolates and broadened the understanding of the NADH-dependent MTHFR catalytic mechanism of Rv2172c in M. tuberculosis, which will facilitate the molecular diagnosis of PAS resistance and also the development of new drugs targeting Rv2172c.

Exploring diagnostic methods for drug-resistant tuberculosis: A comprehensive overview

Despite available global efforts and funding, Tuberculosis (TB) continues to affect a considerable number of patients worldwide. Policy makers and stakeholders set clear goals to reduce TB incidence and mortality, but the emergence of multidrug-resistant TB (MDR-TB) and extensively drug-resistant TB (XDR-TB) complicate the reach of these goals. Drug-resistance TB needs to be diagnosed rapidly and accurately to effectively treat patients, prevent the transmission of MDR-TB, minimise mortality, reduce treatment costs and avoid unnecessary hospitalisations. In this narrative review, we provide a comprehensive overview of laboratory methods for detecting drug resistance in MTB, focusing on phenotypic, molecular and other drug susceptibility testing (DST) techniques. We found a large variety of methods used, with the BACTEC MGIT 960 being the most common phenotypic DST and the Xpert MTB/RIF being the most common molecular DST. We emphasise the importance of integrating phenotypic and molecular DST to address issues like resistance to new drugs, heteroresistance, mixed infections and low-level resistance mutations. Notably, most of the analysed studies adhered to the outdated definition of XDR-TB and did not consider the pre-XDR definition, thus posing challenges in aligning diagnostic methods with the current landscape of TB resistance.

Comparisons of genome assembly tools for characterization of Mycobacterium tuberculosis genomes using hybrid sequencing technologies

Background

Next-generation sequencing of Mycobacterium tuberculosis, the infectious agent causing tuberculosis, is improving the understanding of genomic diversity of circulating lineages and strain-types, and informing knowledge of drug resistance mutations. An increasingly popular approach to characterizing M. tuberculosis genomes (size: 4.4 Mbp) and variants (e.g., single nucleotide polymorphisms (SNPs)) involves the de novo assembly of sequence data.

Methods

We compared the performance of genome assembly tools (Unicycler, RagOut, and RagTag) on sequence data from nine drug resistant M. tuberculosis isolates (multi-drug (MDR) n = 1; pre-extensively-drug (pre-XDR) n = 8) generated using Illumina HiSeq, Oxford Nanopore Technology (ONT) PromethION, and PacBio platforms.

Results

Our investigation found that Unicycler-based assemblies had significantly higher genome completeness (~98.7%; p values = 0.01) compared to other assembler tools (RagOut = 98.6%, and RagTag = 98.6%). The genome assembly sizes (bp) across isolates and sequencers based on RagOut was significantly longer (p values < 0.001) (4,418,574 ± 8,824 bp) than Unicycler and RagTag assemblies (Unicycler = 4,377,642 ± 55,257 bp, and RagTag = 4,380,711 ± 51,164 bp). RagOut-based assemblies had the fewest contigs (~32) and the longest genome size (4,418,574 bp; vs. H37Rv reference size 4,411,532 bp) and therefore were chosen for downstream analysis. Pan-genome analysis of Illumina and PacBio hybrid assemblies revealed the greatest number of detected genes (4,639 genes; H37Rv reference contains 3,976 genes), while Illumina and ONT hybrid assemblies produced the highest number of SNPs. The number of genes from hybrid assemblies with ONT and PacBio long-reads (mean: 4,620 genes) was greater than short-read assembly alone (4,478 genes). All nine RagOut hybrid genome assemblies detected known mutations in genes associated with MDR-TB and pre-XDR-TB.

Conclusions

Unicycler software performed the best in terms of achieving contiguous genomes, whereas RagOut improved the quality of Unicycler's genome assemblies by providing a longer genome size. Overall, our approach has demonstrated that short-read and long-read hybrid assembly can provide a more complete genome assembly than short-read assembly alone by detecting pan-genomes and more genes, including IS6110, and SNPs.

Whole-genome sequencing-based genetic diversity, transmission dynamics, and drug-resistant mutations in Mycobacterium tuberculosis isolated from extrapulmonary tuberculosis patients in western Ethiopia

Background

Extrapulmonary tuberculosis (EPTB) refers to a form of Tuberculosis (TB) where the infection occurs outside the lungs. Despite EPTB being a devastating disease of public health concern, it is frequently overlooked as a public health problem. This study aimed to investigate genetic diversity, identify drug-resistance mutations, and trace ongoing transmission chains.

Methods

A cross-sectional study was undertaken on individuals with EPTB in western Ethiopia. In this study, whole-genome sequencing (WGS) was employed to analyze Mycobacterium tuberculosis (MTB) samples obtained from EPTB patients. Out of the 96 genomes initially sequenced, 89 met the required quality standards for genetic diversity, and drug-resistant mutations analysis. The data were processed using robust bioinformatics tools.

Results

Our analysis reveals that the majority (87.64%) of the isolates can be attributed to Lineage-4 (L4), with L4.6.3 and L4.2.2.2 emerging as the predominant sub-lineages, constituting 34.62% and 26.92%, respectively. The overall clustering rate and recent transmission index (RTI) were 30 and 17.24%, respectively. Notably, 7.87% of the isolates demonstrated resistance to at least one anti-TB drug, although multi-drug resistance (MDR) was observed in only 1.12% of the isolates.

Conclusions

The genetic diversity of MTBC strains in western Ethiopia was found to have low inter-lineage diversity, with L4 predominating and exhibiting high intra-lineage diversity. The notably high clustering rate in the region implies a pressing need for enhanced TB infection control measures to effectively disrupt the transmission chain. It's noteworthy that 68.75% of resistance-conferring mutations went undetected by both GeneXpert MTB/RIF and the line probe assay (LPA) in western Ethiopia. The identification of resistance mutations undetected by both GeneXpert and LPA, along with the detection of mixed infections through WGS, emphasizes the value of adopting WGS as a high-resolution approach for TB diagnosis and molecular epidemiological surveillance.

An overview of next generation sequencing strategies and genomics tools used for tuberculosis research

Tuberculosis (TB) is a grave public health concern and is considered the foremost contributor to human mortality resulting from infectious disease. Due to the stringent clonality and extremely restricted genomic diversity, conventional methods prove inefficient for in-depth exploration of minor genomic variations and the evolutionary dynamics operating in Mycobacterium tuberculosis (M.tb) populations. Until now, the majority of reviews have primarily focused on delineating the application of whole-genome sequencing (WGS) in predicting antibiotic resistant genes, surveillance of drug resistance strains, and M.tb lineage classifications. Despite the growing use of next generation sequencing (NGS) and WGS analysis in TB research, there are limited studies that provide a comprehensive summary of there role in studying macroevolution, minor genetic variations, assessing mixed TB infections, and tracking transmission networks at an individual level. This highlights the need for systematic effort to fully explore the potential of WGS and its associated tools in advancing our understanding of TB epidemiology and disease transmission. We delve into the recent bioinformatics pipelines and NGS strategies that leverage various genetic features and simultaneous exploration of host-pathogen protein expression profile to decipher the genetic heterogeneity and host-pathogen interaction dynamics of the M.tb infections. This review highlights the potential benefits and limitations of NGS and bioinformatics tools and discusses their role in TB detection and epidemiology. Overall, this review could be a valuable resource for researchers and clinicians interested in NGS-based approaches in TB research.

Large-scale statistical analysis of Mycobacterium tuberculosis genome sequences identifies compensatory mutations associated with multi-drug resistance

Tuberculosis (TB), caused by Mycobacterium tuberculosis, has a significant impact on global health worldwide. The development of multi-drug resistant strains that are resistant to the first-line drugs isoniazid and rifampicin threatens public health security. Rifampicin and isoniazid resistance are largely underpinned by mutations in rpoB and katG respectively and are associated with fitness costs. Compensatory mutations are considered to alleviate these fitness costs and have been observed in rpoC/rpoA (rifampicin) and oxyR'-ahpC (isoniazid). We developed a framework (CompMut-TB) to detect compensatory mutations from whole genome sequences from a large dataset comprised of 18,396 M. tuberculosis samples. We performed association analysis (Fisher's exact tests) to identify pairs of mutations that are associated with drug-resistance, followed by mediation analysis to identify complementary or full mediators of drug-resistance. The analyses revealed several potential mutations in rpoC (N = 47), rpoA (N = 4), and oxyR'-ahpC (N = 7) that were considered either 'highly likely' or 'likely' to confer compensatory effects on drug-resistance, including mutations that have previously been reported and validated. Overall, we have developed the CompMut-TB framework which can assist with identifying compensatory mutations which is important for more precise genome-based profiling of drug-resistant TB strains and to further understanding of the evolutionary mechanisms that underpin drug-resistance.

Phenotype versus genotype discordant rifampicin susceptibility testing in tuberculosis: implications for a diagnostic accuracy

IMPORTANCE

An accurate diagnosis of drug resistance in clinical isolates is an important step for better treatment outcomes. The current study observed a higher discordance rate of rifampicin resistance on Mycobacteria Growth Indicator Tube (MGIT) drug susceptibility testing (DST) than Lowenstein-Jenson (LJ) DST when compared with the rpoB sequencing. We detected a few novel mutations and their combination in rifampicin resistance isolates that were missed by MGIT DST and may be useful for the better management of tuberculosis (TB) treatment outcomes. Few novel deletions in clinical isolates necessitate the importance of rpoB sequencing in large data sets in geographic-specific locations, especially high-burden countries. We explored the discordance rate on MGIT and LJ, which is important for the clinical management of rifampicin resistance to avoid the mistreatment of drug-resistant TB. Furthermore, MGIT-sensitive isolates may be subjected to molecular methods of diagnosis for further confirmation and treatment options.

Epidemiological cut-off values for a 96-well broth microdilution plate for high-throughput research antibiotic susceptibility testing of M. tuberculosis

Drug susceptibility testing of M. tuberculosis is rooted in a binary susceptible/resistant paradigm. While there are considerable advantages in measuring the minimum inhibitory concentrations (MICs) of a panel of drugs for an isolate, it is necessary to measure the epidemiological cut-off values (ECOFF/ECVs) to permit comparison with qualitative data. Here we present ECOFF/ECVs for 13 anti-tuberculosis compounds, including bedaquiline and delamanid, derived from 20 637 clinical isolates collected by 14 laboratories based in 11 countries on five continents. Each isolate was incubated for 14 days on a dry 96-well broth microdilution plate and then read. Resistance to most of the drugs due to prior exposure is expected and the MIC distributions for many of the compounds are complex, and therefore a phenotypically wild-type population could not be defined. Since a majority of samples also underwent genetic sequencing, we defined a genotypically wild-type population and measured the MIC of the 99th percentile by direct measurement and via fitting a Gaussian using interval regression. The proposed ECOFF/ECVs were then validated by comparing with the MIC distributions of high-confidence genetic variants that confer resistance and with qualitative drug susceptibility tests obtained via the Mycobacterial Growth Indicator Tube (MGIT) system or Microscopic-Observation Drug Susceptibility (MODS) assay. These ECOFF/ECVs will inform and encourage the more widespread adoption of broth microdilution: this is a cheap culture-based method that tests the susceptibility of 12-14 antibiotics on a single 96-well plate and so could help personalise the treatment of tuberculosis.

Genomic epidemiological analysis of Klebsiella pneumoniae from Portuguese hospitals reveals insights into circulating antimicrobial resistance

Klebsiella pneumoniae (Kp) bacteria are an increasing threat to public health and represent one of the most concerning pathogens involved in life-threatening infections and antimicrobial resistance (AMR). To understand the epidemiology of AMR of Kp in Portugal, we analysed whole genome sequencing, susceptibility testing and other meta data on 509 isolates collected nationwide from 16 hospitals and environmental settings between years 1980 and 2019. Predominant sequence types (STs) included ST15 (n = 161, 32%), ST147 (n = 36, 7%), ST14 (n = 26, 5%) or ST13 (n = 26, 5%), while 31% of isolates belonged to STs with fewer than 10 isolates. AMR testing revealed widespread resistance to aminoglycosides, fluoroquinolones, cephalosporins and carbapenems. The most common carbapenemase gene was blaKPC-3. Whilst the distribution of AMR linked plasmids appears uncorrelated with ST, their frequency has changed over time. Before year 2010, the dominant plasmid group was associated with the extended spectrum beta-lactamase gene blaCTX-M-15, but this group appears to have been displaced by another carrying the blaKPC-3 gene. Co-carriage of blaCTX-M and blaKPC-3 was uncommon. Our results from the largest genomics study of Kp in Portugal highlight the active transmission of strains with AMR genes and provide a baseline set of variants for future resistance monitoring and epidemiological studies.

Portable sequencing of Mycobacterium tuberculosis for clinical and epidemiological applications

With >1 million associated deaths in 2020, human tuberculosis (TB) caused by the bacteria Mycobacterium tuberculosis remains one of the deadliest infectious diseases. A plethora of genomic tools and bioinformatics pipelines have become available in recent years to assist the whole genome sequencing of M. tuberculosis. The Oxford Nanopore Technologies (ONT) portable sequencer is a promising platform for cost-effective application in clinics, including personalizing treatment through detection of drug resistance-associated mutations, or in the field, to assist epidemiological and transmission investigations. In this study, we performed a comparison of 10 clinical isolates with DNA sequenced on both long-read ONT and (gold standard) short-read Illumina HiSeq platforms. Our analysis demonstrates the robustness of the ONT variant calling for single nucleotide polymorphisms, despite the high error rate. Moreover, because of improved coverage in repetitive regions where short sequencing reads fail to align accurately, ONT data analysis can incorporate additional regions of the genome usually excluded (e.g. pe/ppe genes). The resulting extra resolution can improve the characterization of transmission clusters and dynamics based on inferring closely related isolates. High concordance in variants in loci associated with drug resistance supports its use for the rapid detection of resistant mutations. Overall, ONT sequencing is a promising tool for TB genomic investigations, particularly to inform clinical and surveillance decision-making to reduce the disease burden.

Characterisation of drug-resistant Mycobacterium tuberculosis mutations and transmission in Pakistan

Tuberculosis, caused by Mycobacterium tuberculosis, is a high-burden disease in Pakistan, with multi-drug (MDR) and extensive-drug (XDR) resistance, complicating infection control. Whole genome sequencing (WGS) of M. tuberculosis is being used to infer lineages (strain-types), drug resistance mutations, and transmission patterns-all informing infection control and clinical decision making. Here we analyse WGS data on 535 M. tuberculosis isolates sourced across Pakistan between years 2003 and 2020, to understand the circulating strain-types and mutations related to 12 anti-TB drugs, as well as identify transmission clusters. Most isolates belonged to lineage 3 (n = 397; 74.2%) strain-types, and were MDR (n = 328; 61.3%) and (pre-)XDR (n = 113; 21.1%). By inferring close genomic relatedness between isolates (< 10-SNPs difference), there was evidence of M. tuberculosis transmission, with 55 clusters formed consisting of a total of 169 isolates. Three clusters consist of M. tuberculosis that are similar to isolates found outside of Pakistan. A genome-wide association analysis comparing 'transmitted' and 'non-transmitted' isolate groups, revealed the nusG gene as most significantly associated with a potential transmissible phenotype (P = 5.8 × 10^-10). Overall, our study provides important insights into M. tuberculosis genetic diversity and transmission in Pakistan, including providing information on circulating drug resistance mutations for monitoring activities and clinical decision making.

Artificial Intelligence and Cardiovascular Genetics

Polygenic diseases, which are genetic disorders caused by the combined action of multiple genes, pose unique and significant challenges for the diagnosis and management of affected patients. A major goal of cardiovascular medicine has been to understand how genetic variation leads to the clinical heterogeneity seen in polygenic cardiovascular diseases (CVDs). Recent advances and emerging technologies in artificial intelligence (AI), coupled with the ever-increasing availability of next generation sequencing (NGS) technologies, now provide researchers with unprecedented possibilities for dynamic and complex biological genomic analyses. Combining these technologies may lead to a deeper understanding of heterogeneous polygenic CVDs, better prognostic guidance, and, ultimately, greater personalized medicine. Advances will likely be achieved through increasingly frequent and robust genomic characterization of patients, as well the integration of genomic data with other clinical data, such as cardiac imaging, coronary angiography, and clinical biomarkers. This review discusses the current opportunities and limitations of genomics; provides a brief overview of AI; and identifies the current applications, limitations, and future directions of AI in genomics.

The whole-genome sequencing in predicting Mycobacterium tuberculosis drug susceptibility and resistance in Papua, Indonesia

BACKGROUND

Tuberculosis is one of the deadliest disease caused by Mycobacterium tuberculosis. Its treatment still becomes a burden for many countries including Indonesia. Drug resistance is one of the problems in TB treatment. However, a development in the molecular field through Whole-genome sequencing (WGS) can be used as a solution in detecting mutations associated with TB- drugs. This investigation intended to implement this data for supporting the scientific community in deeply understanding any TB epidemiology and evolution in Papua along with detecting any mutations in genes associated with TB-Drugs.

RESULT

A whole-genome sequencing was performed on the random samples from TB Referral Laboratory in Papua utilizing MiSeq 600 cycle Reagent Kit (V3). Furthermore, TBProfiler was used for genome analysis, RAST Server was employed for annotation, while Gview server was applied for BLAST genome mapping and a Microscope server was implemented for Regions of Genomic Plasticity (RGP). The largest genome of M. tuberculosis obtained was at the size of 4,396,040 bp with subsystems number at 309 and the number of coding sequences at 4326. One sample (TB751) contained one RGP. The drug resistance analysis revealed that several mutations associated with TB-drug resistance existed. In details, mutations of rpoB gene which were identified as S450L, D435Y, H445Y, L430P, and Q432K had caused the reduced effectiveness of rifampicin; while the mutases in katG (S315T), kasA (312S), inhA (I21V), and Rv1482c-fabG1 (C-15 T) genes had contributed to the resistance in isoniazid. In streptomycin, the resistance was triggered by the mutations in rpsL (K43R) and rrs (A514C, A514T) genes, and, in Amikacin, its resistance was led by mutations in rrs (A514C) gene. Additionally, in Ethambutol and Pyrazinamide, their reduced effectiveness was provoked by embB gene mutases (M306L, M306V, D1024N) and pncA (W119R).

CONCLUSIONS

The results from whole-genome sequencing of TB clinical sample in Papua, Indonesia could contribute to the surveillance of TB-drug resistance. In the drug resistance profile, there were 15 Multi Drugs Resistance (MDR) samples. However, Extensively Drug-resistant (XDR) samples have not been found, but samples were resistant to only Amikacin, a second-line drug.

Decreased methylenetetrahydrofolate reductase activity leads to increased sensitivity to para-aminosalicylic acid in Mycobacterium tuberculosis

Tuberculosis (TB), caused by Mycobacterium tuberculosis, is one of the most fatal diseases in the world. Methylenetetrahydrofolate reductase (MTHFR) catalyzes the production of 5-methyltetrahydrofolate (5-CH₃-THF), which is required for the de novo biosynthesis of methionine in bacteria. Here, we identified Rv2172c as an MTHFR in M. tuberculosis through in vitro and in vivo analyses and determined that the protein is essential for the in vitro growth of the bacterium. Subsequently, we constructed rv2172c R159N and L214A mutants in M. tuberculosis and found that these mutants were more sensitive to the antifolates para-aminosalicylic acid (PAS) and sulfamethoxazole (SMX). Combining biochemical and genetic methods, we found that rv2172c R159N or L214A mutation impaired methionine production, leading to increased susceptibility of M. tuberculosis to PAS, which was largely restored by adding exogenous methionine. Moreover, overexpression of rv2172c in M. tuberculosis could increase methionine production and lead to PAS resistance. This research is the first to identify an MTHFR in M. tuberculosis and reveals that the activity of this enzyme is associated with susceptibility to antifolates. These findings have particular value for antitubercular drug design for the treatment of drug-resistant TB.

Evaluation of whole-genome sequence data analysis approaches for short- and long-read sequencing of Mycobacterium tuberculosis

Whole-genome sequencing (WGS) of Mycobacterium tuberculosis (MTB) isolates can be used to get an accurate diagnosis, to guide clinical decision making, to control tuberculosis (TB) and for outbreak investigations. We evaluated the performance of long-read (LR) and/or short-read (SR) sequencing for anti-TB drug-resistance prediction using the TBProfiler and Mykrobe tools, the fraction of genome recovery, assembly accuracies and the robustness of two typing approaches based on core-genome SNP (cgSNP) typing and core-genome multi-locus sequence typing (cgMLST). Most of the discrepancies between phenotypic drug-susceptibility testing (DST) and drug-resistance prediction were observed for the first-line drugs rifampicin, isoniazid, pyrazinamide and ethambutol, mainly with LR sequence data. Resistance prediction to second-line drugs made by both TBProfiler and Mykrobe tools with SR- and LR-sequence data were in complete agreement with phenotypic DST except for one isolate. The SR assemblies were more accurate than the LR assemblies, having significantly (P <0.05) fewer indels and mismatches per 100 kbp. However, the hybrid and LR assemblies had slightly higher genome fractions. For LR assemblies, Canu followed by Racon, and Medaka polishing was the most accurate approach. The cgSNP approach, based on either reads or assemblies, was more robust than the cgMLST approach, especially for LR sequence data. In conclusion, anti-TB drug-resistance prediction, particularly with only LR sequence data, remains challenging, especially for first-line drugs. In addition, SR assemblies appear more accurate than LR ones, and reproducible phylogeny can be achieved using cgSNP approaches.

Evaluating coverage bias in next-generation sequencing of Escherichia coli

Whole-genome sequencing is essential to many facets of infectious disease research. However, technical limitations such as bias in coverage and tagmentation, and difficulties characterising genomic regions with extreme GC content have created significant obstacles in its use. Illumina has claimed that the recently released DNA Prep library preparation kit, formerly known as Nextera Flex, overcomes some of these limitations. This study aimed to assess bias in coverage, tagmentation, GC content, average fragment size distribution, and de novo assembly quality using both the Nextera XT and DNA Prep kits from Illumina. When performing whole-genome sequencing on Escherichia coli and where coverage bias is the main concern, the DNA Prep kit may provide higher quality results; though de novo assembly quality, tagmentation bias and GC content related bias are unlikely to improve. Based on these results, laboratories with existing workflows based on Nextera XT would see minor benefits in transitioning to the DNA Prep kit if they were primarily studying organisms with neutral GC content.

Reporting practices for genomic epidemiology of tuberculosis: a systematic review of the literature using STROME-ID guidelines as a benchmark

BACKGROUND

Pathogen genomics have become increasingly important in infectious disease epidemiology and public health. The Strengthening the Reporting of Molecular Epidemiology for Infectious Diseases (STROME-ID) guidelines were developed to outline a minimum set of criteria that should be reported in genomic epidemiology studies to facilitate assessment of study quality. We evaluate such reporting practices, using tuberculosis as an example.

METHODS

For this systematic review, we initially searched MEDLINE, Embase Classic, and Embase on May 3, 2017, using the search terms "tuberculosis" and "genom* sequencing". We updated this initial search on April 23, 2019, and also included a search of bioRxiv at this time. We included studies in English, French, or Spanish that recruited patients with microbiologically confirmed tuberculosis and used whole genome sequencing for typing of strains. Non-human studies, conference abstracts, and literature reviews were excluded. For each included study, the number and proportion of fulfilled STROME-ID criteria were recorded by two reviewers. A comparison of the mean proportion of fulfilled STROME-ID criteria before and after publication of the STROME-ID guidelines (in 2014) was done using a two-tailed t test. Quasi-Poisson regression and tobit regression were used to examine associations between study characteristics and the number and proportion of fulfilled STROME-ID criteria. This study was registered with PROSPERO, CRD42017064395.

FINDINGS

976 titles and abstracts were identified by our primary search, with an additional 16 studies identified in bioRxiv. 114 full texts (published between 2009 and 2019) were eligible for inclusion. The mean proportion of STROME-ID criteria fulfilled was 50% (SD 12; range 16-75). The proportion of criteria fulfilled was similar before and after STROME-ID publication (51% [SD 11] vs 46% [14], p=0·26). The number of criteria reported (among those applicable to all studies) was not associated with impact factor, h-index, country of affiliation of senior author, or sample size of isolates. Similarly, the proportion of criteria fulfilled was not associated with these characteristics, with the exception of a sample size of isolates of 277 or more (the highest quartile). In terms of reproducibility, 100 (88%) studies reported which bioinformatic tools were used, but only 33 (33%) reported corresponding version numbers. Sequencing data were available for 86 (75%) studies.

INTERPRETATION

The reporting of STROME-ID criteria in genomic epidemiology studies of tuberculosis between 2009 and 2019 was low, with implications for assessment of study quality. The considerable proportion of studies without bioinformatics version numbers or sequencing data available highlights a key concern for reproducibility.

Prediction of Mycobacterium tuberculosis pyrazinamidase function based on structural stability, physicochemical and geometrical descriptors

BACKGROUND

Pyrazinamide is an important drug against the latent stage of tuberculosis and is used in both first- and second-line treatment regimens. Pyrazinamide-susceptibility test usually takes a week to have a diagnosis to guide initial therapy, implying a delay in receiving appropriate therapy. The continued increase in multi-drug resistant tuberculosis and the prevalence of pyrazinamide resistance in several countries makes the development of assays for prompt identification of resistance necessary. The main cause of pyrazinamide resistance is the impairment of pyrazinamidase function attributed to mutations in the promoter and/or pncA coding gene. However, not all pncA mutations necessarily affect the pyrazinamidase function.

OBJECTIVE

To develop a methodology to predict pyrazinamidase function from detected mutations in the pncA gene.

METHODS

We measured the catalytic constant (kcat), KM, enzymatic efficiency, and enzymatic activity of 35 recombinant mutated pyrazinamidase and the wild type (Protein Data Bank ID = 3pl1). From all the 3D modeled structures, we extracted several predictors based on three categories: structural stability (estimated by normal mode analysis and molecular dynamics), physicochemical, and geometrical characteristics. We used a stepwise Akaike's information criterion forward multiple log-linear regression to model each kinetic parameter with each category of predictors. We also developed weighted models combining the three categories of predictive models for each kinetic parameter. We tested the robustness of the predictive ability of each model by 6-fold cross-validation against random models.

RESULTS

The stability, physicochemical, and geometrical descriptors explained most of the variability (R2) of the kinetic parameters. Our models are best suited to predict kcat, efficiency, and activity based on the root-mean-square error of prediction of the 6-fold cross-validation.

CONCLUSIONS

This study shows a quick approach to predict the pyrazinamidase function only from the pncA sequence when point mutations are present. This can be an important tool to detect pyrazinamide resistance.

Whole-genome sequencing and Mycobacterium tuberculosis: Challenges in sample preparation and sequencing data analysis

The numbers of patients with tuberculosis (TB) caused by resistant strains are still alarming. Therefore, it is necessary to determine resistance more quickly and precisely, than it is with the currently used phenotypic and genotypic methods. In recent years, technological advances have been made and the whole-genome sequencing (WGS) method has been introduced as a part of routine diagnostics in clinical laboratories. Comparing a wide range of mycobacterial genomic variations with a reference genome leads to a consistent evaluation of molecular-epidemiology and resistance of Mycobacterium tuberculosis (M. tuberculosis) to a wide range of anti-TB drugs. The quality of the obtained sequencing data is closely related to the type of sample and the method used for DNA extraction and sequencing library preparation. Moreover, the correct interpretation of results is also influenced by a bioinformatic data processing. A large number of bioinformatics pipelines are currently available, the sensitivity of which varies due to the different sizes of databases containing relevant mutations. This review focuses on the individual steps included in the sequencing workflow and factors that may affect the interpretation of final results.

Resistance Sniffer: An online tool for prediction of drug resistance patterns of Mycobacterium tuberculosis isolates using next generation sequencing data

The effective control of multidrug resistant tuberculosis (MDR-TB) relies upon the timely diagnosis and correct treatment of all tuberculosis cases. Whole genome sequencing (WGS) has great potential as a method for the rapid diagnosis of drug resistant Mycobacterium tuberculosis (Mtb) isolates. This method overcomes most of the problems that are associated with current phenotypic drug susceptibility testing. However, the application of WGS in the clinical setting has been deterred by data complexities and skill requirements for implementing the technologies as well as clinical interpretation of the next generation sequencing (NGS) data. The proposed diagnostic application was drawn upon recent discoveries of patterns of Mtb clade-specific genetic polymorphisms associated with antibiotic resistance. A catalogue of genetic determinants of resistance to thirteen anti-TB drugs for each phylogenetic clade was created. A computational algorithm for the identification of states of diagnostic polymorphisms was implemented as an online software tool, Resistance Sniffer (http://resistance-sniffer.bi.up.ac.za/), and as a stand-alone software tool to predict drug resistance in Mtb isolates using complete or partial genome datasets in different file formats including raw Illumina fastq read files. The program was validated on sequenced Mtb isolates with data on antibiotic resistance trials available from GMTV database and from the TB Platform of South African Medical Research Council (SAMRC), Pretoria. The program proved to be suitable for probabilistic prediction of drug resistance profiles of individual strains and large sequence data sets.

[Mass spectrometry-based identification of new serum biomarkers in patients with multidrug resistant pulmonary tuberculosis]

OBJECTIVE

To screen new serum metabolic biomarkers for different drug resistance profiles of pulmonary tuberculosis (TB) and explore their mechanisms and functions.

METHODS

We collected serum samples from TB patients with drug sensitivity (DS), monoresistance to isoniazid (MR-INH), monoresistance to rifampin (MR-RFP), multidrug resistance (MDR), and polyresistance (PR). The metabolites in the serum samples were extracted by oscillatory and deproteinization for LC-MS/MS analysis, and the results were normalized by Pareto-scaling method and analyzed using Metaboanalyst 4.0 software to identify the differential metabolites. The differential metabolites were characterized by function enrichment and co-expression analysis to explore their function and possible pathological mechanisms.

RESULTS

Compared with the DS group, 286 abnormally expressed metabolites were identified in MR-INH group, 362 in MR-RPF group, 277 in MDR group and 1208 in PR group by LC-MS/MS analysis. Acetylagmatine (P < 0.05), aminopentol (P < 0.05), and tetracosanyl oleate (P < 0.05) in MR-INH group; Ala His Pro Thr (P < 0.001) and glycinoprenol-9 (P < 0.05) in MR-RFP group; trimethylamine (P < 0.05), penaresidin A (P < 0.05), and verazine (P < 0.05) in MDR group; and PIP (18:1(11Z)/ 18:3(6Z, 9Z, 12Z)) (P < 0.001), Pro Arg Trp Tyr (P < 0.001), N-methyldioctylamine (P < 0.001), and phytolaccoside E (P < 0.05) in PR group all showed significant differential expressions. Significant differential expressions of phthalic acid mono-2-ethylhexyl ester (P < 0.05) and eicosanoyl-EA (P < 0.05) were found in all the drug resistant groups as compared with DS group.

CONCLUSIONS

Acetylagmatine, aminopentol, tetracosanyl oleate, Ala His Pro Thr, glycinoprenol-9, trimethylamine, penaresidin A, verazine, PIP(18:1(11Z)/18:3(6Z, 9Z, 12Z)), Pro Arg Trp Tyr, N-methyldioctylamine, phytolaccoside E, phthalic acid mono-2-ethylhexyl ester, and eicosanoyl-EA are potentially new biomarkers that indicate monoresistance, multi-drug resistance and polyresistance of Mycobacterium tuberculosis. The combined use of these biomarkers potentially allows for assessment of drug resistance in TB and enhances the diagnostic sensitivity and specificity.

Personalized Approach as a Basis for the Future Diagnosis of Tuberculosis (Literature Review)

The global spread of tuberculosis remains one of actual problems of public health despite of introduction of public health safety programs. Early, rapid and accurate identification of M. tuberculosis and determination of drug susceptibility are essential for treatment and management of this disease. Delay in delivering results prolongs potentially inappropriate antituberculosis therapy, contributing to emergence of drug resistance, reducing treatment options and increasing treatment duration and associated costs, resulting in increased mortality and morbidity. Faster, more comprehensive diagnostics will enable earlier use of the most appropriate drug regimen, thus improving patient outcomes and reducing overall healthcare costs. The treatment of infection based on the using of massive antimicrobial therapy with analysis of bacterial strains resistance to first line drugs (FLD) isoniazid (INH), rifampin (RIF), pyrazinamide (PZA), ethambutol (EMB) and streptomycin (SM). However, the public health practitioners pay no attention to functional activity of human immune system genes. The interaction of bacterial genomes and immune system genes plays the major role in infection progress. There is growing evidence that, together with human and environmental factors, Mycobacterium tuberculosis complex strain diversity contributes to the variable outcome of infection and disease in human TB. We suppose that the future of diagnosis and treatment of tuberculosis lies in the field of personal medicine with comprehensive analysis of host and pathogen genes.

Integrating informatics tools and portable sequencing technology for rapid detection of resistance to anti-tuberculous drugs

Background

Mycobacterium tuberculosis resistance to anti-tuberculosis drugs is a major threat to global public health. Whole genome sequencing (WGS) is rapidly gaining traction as a diagnostic tool for clinical tuberculosis settings. To support this informatically, previous work led to the development of the widely used TBProfiler webtool, which predicts resistance to 14 drugs from WGS data. However, for accurate and rapid high throughput of samples in clinical or epidemiological settings, there is a need for a stand-alone tool and the ability to analyse data across multiple WGS platforms, including Oxford Nanopore MinION.

Results

We present a new command line version of the TBProfiler webserver, which includes hetero-resistance calling and will facilitate the batch processing of samples. The TBProfiler database has been expanded to incorporate 178 new markers across 16 anti-tuberculosis drugs. The predictive performance of the mutation library has been assessed using > 17,000 clinical isolates with WGS and laboratory-based drug susceptibility testing (DST) data. An integrated MinION analysis pipeline was assessed by performing WGS on 34 replicates across 3 multi-drug resistant isolates with known resistance mutations. TBProfiler accuracy varied by individual drug. Assuming DST as the gold standard, sensitivities for detecting multi-drug-resistant TB (MDR-TB) and extensively drug-resistant TB (XDR-TB) were 94% (95%CI 93–95%) and 83% (95%CI 79–87%) with specificities of 98% (95%CI 98–99%) and 96% (95%CI 95–97%) respectively. Using MinION data, only one resistance mutation was missed by TBProfiler, involving an insertion in the tlyA gene coding for capreomycin resistance. When compared to alternative platforms (e.g. Mykrobe predictor TB, the CRyPTIC library), TBProfiler demonstrated superior predictive performance across first- and second-line drugs.

Conclusions

The new version of TBProfiler can rapidly and accurately predict anti-TB drug resistance profiles across large numbers of samples with WGS data. The computing architecture allows for the ability to modify the core bioinformatic pipelines and outputs, including the analysis of WGS data sourced from portable technologies. TBProfiler has the potential to be integrated into the point of care and WGS diagnostic environments, including in resource-poor settings.

Electronic supplementary material

The online version of this article (10.1186/s13073-019-0650-x) contains supplementary material, which is available to authorized users.

Genomic characterization of MDR/XDR-TB in Kazakhstan by a combination of high-throughput methods predominantly shows the ongoing transmission of L2/Beijing 94-32 central Asian/Russian clusters

Background

Kazakhstan remains a high-burden TB prevalence country with a concomitent high-burden of multi-drug resistant tuberculosis. For this reason, we performed an in depth genetic diversity and population structure characterization of Mycobacterium tuberculosis complex (MTC) genetic diversity in Kazakhstan with both patient and community benefit.

Methods

A convenience sample of 700 MTC DNA cultures extracts from 630 tuberculosis patients recruited from 12 out of 14 regions in Kazakhstan, between 2010 and 2015, was independently studied by high-throughput hybridization-based methods, TB-SPRINT (59-Plex, n = 700), TB-SNPID (50-Plex, n = 543). DNA from 391 clinical isolates was successfully typed by two methods. To resolve the population structure of drug-resistant clades in more detail two complementary assays were run on the L2 isolates: an IS6110-NTF insertion site typing assay and a SigE SNP polymorphism assay.

Results

Strains belonged to L2/Beijing and L4/Euro-American sublineages; L2/Beijing prevalence totaled almost 80%. 50% of all samples were resistant to RIF and to INH., Subtyping showed that: (1) all L2/Beijing were “modern” Beijing and (2) most of these belonged to the previously described 94–32 sublineage (Central Asian/Russian), (3) at least two populations of the Central Asian/Russian sublineages are circulating in Kazakhstan, with different evolutionary dynamics.

Conclusions

For the first time, the global genetic diversity and population structure of M. tuberculosis genotypes circulating in Kazakhstan was obtained and compared to previous local studies. Results suggest a region-specific spread of a very limited number of L2/Beijing clonal complexes in Kazakhstan many strongly associated with an MDR phenotype.

Electronic supplementary material

The online version of this article (10.1186/s12879-019-4201-2) contains supplementary material, which is available to authorized users.

A large scale evaluation of TBProfiler and Mykrobe for antibiotic resistance prediction in Mycobacterium tuberculosis

Recent years saw a growing interest in predicting antibiotic resistance from whole-genome sequencing data, with promising results obtained for Staphylococcus aureus and Mycobacterium tuberculosis. In this work, we gathered 6,574 sequencing read datasets of M. tuberculosis public genomes with associated antibiotic resistance profiles for both first and second-line antibiotics. We performed a systematic evaluation of TBProfiler and Mykrobe, two widely recognized softwares allowing to predict resistance in M. tuberculosis. The size of the dataset allowed us to obtain confident estimations of their overall predictive performance, to assess precisely the individual predictive power of the markers they rely on, and to study in addition how these softwares behave across the major M. tuberculosis lineages. While this study confirmed the overall good performance of these tools, it revealed that an important fraction of the catalog of mutations they embed is of limited predictive power. It also revealed that these tools offer different sensitivity/specificity trade-offs, which is mainly due to the different sets of mutation they embed but also to their underlying genotyping pipelines. More importantly, it showed that their level of predictive performance varies greatly across lineages for some antibiotics, therefore suggesting that the predictions made by these softwares should be deemed more or less confident depending on the lineage inferred and the predictive performance of the marker(s) actually detected. Finally, we evaluated the relevance of machine learning approaches operating from the set of markers detected by these softwares and show that they present an attractive alternative strategy, allowing to reach better performance for several drugs while significantly reducing the number of candidate mutations to consider.

Molecular Diagnosis of Drug-Resistant Tuberculosis; A Literature Review

Drug-resistant tuberculosis is a global health problem that hinders the progress of tuberculosis eradication programs. Accurate and early detection of drug-resistant tuberculosis is essential for effective patient care, for preventing tuberculosis spread, and for limiting the development of drug-resistant strains. Culture-based drug susceptibility tests are the gold standard method for the detection of drug-resistant tuberculosis, but they are time-consuming and technically challenging, especially in low- and middle-income countries. Nowadays, different nucleic acid-based assays that detect gene mutations associated with resistance to drugs used to treat tuberculosis are available. These tests vary in type and number of targets and in sensitivity and specificity. In this review, we will describe the available molecular tests for drug-resistant tuberculosis detection and discuss their advantages and limitations.

Comparisons of whole-genome sequencing and phenotypic drug susceptibility testing for Mycobacterium tuberculosis causing MDR-TB and XDR-TB in Thailand

Drug-resistant tuberculosis (TB) is a major public health problem. There is little information regarding the genotypic-phenotypic association of anti-TB drugs, especially for second-line drugs. This study compared phenotypic drug susceptibility testing (DST) with predictions based on whole-genome sequencing (WGS) data for 266 Mycobacterium tuberculosis isolates. Phenotypic DST used the standard proportional method. Clinical isolates of M. tuberculosis collected in Thailand between 1998 and 2013 comprised 51 drug-sensitive strains, six mono-resistant strains, two multiple-resistant strains, 88 multi-drug-resistant strains, 95 pre-extensively drug-resistant strains and 24 extensively drug-resistant strains. WGS analysis was performed using the computer programs PhyResSE and TB-Profiler. TB-Profiler had higher average concordance with phenotypic DST than PhyResSE for both first-line (91.96% vs. 91.4%) and second-line (79.67% vs. 78.20%) anti-TB drugs. The average sensitivity for all anti-TB drugs was also higher (83.13% vs. 72.08%) with slightly lower specificity (83.50% vs. 86.68%). Regardless of the program used, isoniazid, rifampicin and amikacin had the highest concordance with phenotypic DST (96.2%, 93.5% and 95.6%, respectively). Ethambutol, ethionamide and fluoroquinolones had the lowest concordance (87.34%, 81.44% and 73.85%, respectively). Concordance rates of ofloxacin (a second-generation fluoroquinolone), levofloxacin, moxifloxacin and gatifloxacin (third- and fourth-generation fluoroquinolones) were 91.79%, 76.62%, 72.64% and 57.35%, respectively. Discordance between phenotypic and WGS-based DSTs may be due, in part, to the choice of critical concentration and variable reproducibility of the phenotypic tests. It may also be due to limitations of the mutation databases (especially for the second-line drugs) and the analysis program used. Mutations related to fluoroquinolone resistance, especially the later generations, need to be identified.

Advances in the molecular diagnosis of tuberculosis: From probes to genomes

Tuberculosis, disease caused by Mycobacterium tuberculosis, is currently the leading cause of death by a single infectious agent worldwide. Early, rapid and accurate identification of M. tuberculosis and the determination of drug susceptibility is essential for the treatment and management of this disease. Tuberculosis diagnosis is mainly based on chest radiography, smear microscopy and bacteriological culture. Smear microscopy has variable sensitivity, mainly in patients co-infected with the human immunodeficiency virus (HIV). Conventional culture for M. tuberculosis isolation, identification and drug susceptibility testing requires several weeks owning to the slow growth of M. tuberculosis. The delay in the time to results drives the prolongation of potentially inappropriate antituberculosis therapy contributing to the emergence of drug resistance, reducing treatment options and increasing treatment duration and associated costs, resulting in increased mortality and morbidity. For these reasons, novel diagnostic methods are need for timely identification of M. tuberculosis and determination of the antibiotic susceptibility profile of the infecting strain. Molecular methods offer enhanced sensitivity and specificity, early detection and the capacity to detect mixed infections. These technologies have improved turnaround time, cost effectiveness and are amenable for point-of-care testing. However, although these methods produce results within hours from sample collection, the phenotypic susceptibility testing is still needed for the determination of drug susceptibility and quantify the susceptibility levels of a given strain towards individual antibiotics. This review presents the history, advances and forthcoming promises in the molecular diagnosis of tuberculosis. An overview on the general principles, diagnostic value and the main advantages and disadvantages of the molecular methods used for the detection and identification of M. tuberculosis and its associated disease, is provided. It will be also discussed how the current phenotypic methods should be used in combination with the genotypic methods for rapid antituberculosis susceptibility testing.

Analysis of Whole-Genome Sequences for the Prediction of Penicillin Resistance and β-Lactamase Activity in Bacillus anthracis

Penicillin (PEN) is a low-cost option for anthrax treatment, but naturally occurring resistance has been reported. β-Lactamase expression (bla1, bla2) in Bacillus anthracis is regulated by a sigma factor (SigP) and its cognate anti-sigma factor (RsiP). Mutations leading to truncation of RsiP were previously described as a basis for PEN resistance. Here, we analyze whole-genome sequencing (WGS) data and compare the chromosomal sigP-bla1 regions from 374 B. anthracis strains to determine the frequency of mutations, identify mutations associated with PEN resistance, and evaluate the usefulness of WGS for predicting PEN resistance. Few (3.5%) strains contained at least 1 of 11 different mutations in sigP, rsiP, or bla1. Nine of these mutations have not been previously associated with PEN resistance. Four strains showed PEN resistance (PEN-R) by conventional broth microdilution, including 1 strain with a novel frameshift in rsiP. One strain that carries the same rsiP frameshift mutation as that found previously in a PEN-R strain showed a PEN-susceptible (PEN-S) phenotype and exhibited decreased bla1 and bla2 transcription. An unexpectedly small colony size, a reduced growth rate, and undetectable β-lactamase activity levels (culture supernatant and cell lysate) were observed in this PEN-S strain. Sequence analysis revealed mutations in genes associated with growth defects that may contribute to this phenotype. While B. anthracis rsiP mutations cannot be exclusively used to predict resistance, four of the five strains with rsiP mutations were PEN-R. Therefore, the B. anthracis sigP-bla1 region is a useful locus for WGS-based PEN resistance prediction, but phenotypic testing remains essential. IMPORTANCE Determination of antimicrobial susceptibility of B. anthracis is essential for the appropriate distribution of antimicrobial agents for postexposure prophylaxis (PEP) and treatment of anthrax. Analysis of WGS data allows for the rapid detection of mutations in antimicrobial resistance (AMR) genes in an isolate, but the presence of a mutation in an AMR gene does not always accurately predict resistance. As mutations in the anti-sigma factor RsiP have been previously associated with high-level penicillin resistance in a limited number of strains, we investigated WGS assemblies from 374 strains to determine the frequency of mutations and performed functional antimicrobial susceptibility testing. Of the five strains that contained mutations in rsiP, only four were PEN-R by functional antimicrobial susceptibility testing. We conclude that while sequence analysis of this region is useful for AMR prediction in B. anthracis, genetic analysis should not be used exclusively and phenotypic susceptibility testing remains essential.

Genome Sequence of Staphylococcus aureus Ex1, Isolated from a Patient with Spinal Osteomyelitis

Here, we present the genome sequence of Staphylococcus aureus Ex1, isolated in 2015 from a patient with spinal osteomyelitis at the Royal Devon and Exeter Hospital in the United Kingdom. The availability of the Ex1 genome sequence provides a resource for studying the basis for spinal infection and horizontal gene transfer in S. aureus.

Use of whole genome sequencing in surveillance of drug resistant tuberculosis

INTRODUCTION

The threat of resistance to anti-tuberculosis drugs is of global concern. Current efforts to monitor resistance rely on phenotypic testing where cultured bacteria are exposed to critical concentrations of the drugs. Capacity for such testing is low in TB endemic countries. Drug resistance is caused by mutations in the Mycobacterium tuberculosis genome and whole genome sequencing to detect these mutations offers an alternative means of assessing resistance. Areas covered: The challenges of assessing TB drug resistance are discussed. Progress in elucidating the M. tuberculosis resistome and evidence of the accuracy of next generation sequencing for detecting resistance is reviewed. Expert Commentary: There are considerable advantages to using next generation sequencing for TB drug resistance surveillance. Accuracy is high for detecting resistance to the major first-line drugs but is currently lower for the second-line drugs due to our incomplete knowledge regarding resistance causing mutations. With the advances in sequencing technology and the opportunity to replace phenotypic drug susceptibility testing with safer and more cost effective methods it would appear that the question is when to implement. Current bottlenecks are sample extraction to allow whole genome sequencing directly from sputum and the lack of bioinformatics expertise in some TB endemic countries.

The challenges of designing a benchmark strategy for bioinformatics pipelines in the identification of antimicrobial resistance determinants using next generation sequencing technologies

Next-Generation Sequencing (NGS) technologies are expected to play a crucial role in the surveillance of infectious diseases, with their unprecedented capabilities for the characterisation of genetic information underlying the virulence and antimicrobial resistance (AMR) properties of microorganisms.  In the implementation of any novel technology for regulatory purposes, important considerations such as harmonisation, validation and quality assurance need to be addressed.  NGS technologies pose unique challenges in these regards, in part due to their reliance on bioinformatics for the processing and proper interpretation of the data produced.  Well-designed benchmark resources are thus needed to evaluate, validate and ensure continued quality control over the bioinformatics component of the process.  This concept was explored as part of a workshop on "Next-generation sequencing technologies and antimicrobial resistance" held October 4-5 2017.   Challenges involved in the development of such a benchmark resource, with a specific focus on identifying the molecular determinants of AMR, were identified. For each of the challenges, sets of unsolved questions that will need to be tackled for them to be properly addressed were compiled. These take into consideration the requirement for monitoring of AMR bacteria in humans, animals, food and the environment, which is aligned with the principles of a “One Health” approach.

The challenges of designing a benchmark strategy for bioinformatics pipelines in the identification of antimicrobial resistance determinants using next generation sequencing technologies

Next-Generation Sequencing (NGS) technologies are expected to play a crucial role in the surveillance of infectious diseases, with their unprecedented capabilities for the characterisation of genetic information underlying the virulence and antimicrobial resistance (AMR) properties of microorganisms.  In the implementation of any novel technology for regulatory purposes, important considerations such as harmonisation, validation and quality assurance need to be addressed.  NGS technologies pose unique challenges in these regards, in part due to their reliance on bioinformatics for the processing and proper interpretation of the data produced.  Well-designed benchmark resources are thus needed to evaluate, validate and ensure continued quality control over the bioinformatics component of the process.  This concept was explored as part of a workshop on "Next-generation sequencing technologies and antimicrobial resistance" held October 4-5 2017.   Challenges involved in the development of such a benchmark resource, with a specific focus on identifying the molecular determinants of AMR, were identified. For each of the challenges, sets of unsolved questions that will need to be tackled for them to be properly addressed were compiled. These take into consideration the requirement for monitoring of AMR bacteria in humans, animals, food and the environment, which is aligned with the principles of a "One Health" approach.

Dissecting whole-genome sequencing-based online tools for predicting resistance in Mycobacterium tuberculosis: can we use them for clinical decision guidance?

Whole-genome sequencing (WGS)-based bioinformatics platforms for the rapid prediction of resistance will soon be implemented in the Tuberculosis (TB) laboratory, but their accuracy assessment still needs to be strengthened. Here, we fully-sequenced a total of 54 multidrug-resistant (MDR) and five susceptible TB strains and performed, for the first time, a simultaneous evaluation of the major four free online platforms (TB Profiler, PhyResSE, Mykrobe Predictor and TGS-TB). Overall, the sensitivity of resistance prediction ranged from 84.3% using Mykrobe predictor to 95.2% using TB profiler, while specificity was higher and homogeneous among platforms. TB profiler revealed the best performance robustness (sensitivity, specificity, PPV and NPV above 95%), followed by TGS-TB (all parameters above 90%). We also observed a few discrepancies between phenotype and genotype, where, in some cases, it was possible to pin-point some "candidate" mutations (e.g., in the rpsL promoter region) highlighting the need for their confirmation through mutagenesis assays and potential review of the anti-TB genetic databases. The rampant development of the bioinformatics algorithms and the tremendously reduced time-frame until the clinician may decide for a definitive and most effective treatment will certainly trigger the technological transition where WGS-based bioinformatics platforms could replace phenotypic drug susceptibility testing for TB.

Genetic sequencing for surveillance of drug resistance in tuberculosis in highly endemic countries: a multi-country population-based surveillance study

Background

In many countries, regular monitoring of the emergence of resistance to anti-tuberculosis drugs is hampered by the limitations of phenotypic testing for drug susceptibility. We therefore evaluated the use of genetic sequencing for surveillance of drug resistance in tuberculosis.

Methods

Population-level surveys were done in hospitals and clinics in seven countries (Azerbaijan, Bangladesh, Belarus, Pakistan, Philippines, South Africa, and Ukraine) to evaluate the use of genetic sequencing to estimate the resistance of Mycobacterium tuberculosis isolates to rifampicin, isoniazid, ofloxacin, moxifloxacin, pyrazinamide, kanamycin, amikacin, and capreomycin. For each drug, we assessed the accuracy of genetic sequencing by a comparison of the adjusted prevalence of resistance, measured by genetic sequencing, with the true prevalence of resistance, determined by phenotypic testing.

Findings

Isolates were taken from 7094 patients with tuberculosis who were enrolled in the study between November, 2009, and May, 2014. In all tuberculosis cases, the overall pooled sensitivity values for predicting resistance by genetic sequencing were 91% (95% CI 87–94) for rpoB (rifampicin resistance), 86% (74–93) for katG, inhA, and fabG promoter combined (isoniazid resistance), 54% (39–68) for pncA (pyrazinamide resistance), 85% (77–91) for gyrA and gyrB combined (ofloxacin resistance), and 88% (81–92) for gyrA and gyrB combined (moxifloxacin resistance). For nearly all drugs and in most settings, there was a large overlap in the estimated prevalence of drug resistance by genetic sequencing and the estimated prevalence by phenotypic testing.

Interpretation

Genetic sequencing can be a valuable tool for surveillance of drug resistance, providing new opportunities to monitor drug resistance in tuberculosis in resource-poor countries. Before its widespread adoption for surveillance purposes, there is a need to standardise DNA extraction methods, recording and reporting nomenclature, and data interpretation.

Funding

Bill & Melinda Gates Foundation, United States Agency for International Development, Global Alliance for Tuberculosis Drug Development.

Genome-wide analysis of multi- and extensively drug-resistant Mycobacterium tuberculosis

To characterize the genetic determinants of resistance to antituberculosis drugs, we performed a genome-wide association study (GWAS) of 6,465 Mycobacterium tuberculosis clinical isolates from more than 30 countries. A GWAS approach within a mixed-regression framework was followed by a phylogenetics-based test for independent mutations. In addition to mutations in established and recently described resistance-associated genes, novel mutations were discovered for resistance to cycloserine, ethionamide and para-aminosalicylic acid. The capacity to detect mutations associated with resistance to ethionamide, pyrazinamide, capreomycin, cycloserine and para-aminosalicylic acid was enhanced by inclusion of insertions and deletions. Odds ratios for mutations within candidate genes were found to reflect levels of resistance. New epistatic relationships between candidate drug-resistance-associated genes were identified. Findings also suggest the involvement of efflux pumps (drrA and Rv2688c) in the emergence of resistance. This study will inform the design of new diagnostic tests and expedite the investigation of resistance and compensatory epistatic mechanisms.

A standardised method for interpreting the association between mutations and phenotypic drug resistance in Mycobacterium tuberculosis

A clear understanding of the genetic basis of antibiotic resistance in Mycobacterium tuberculosis is required to accelerate the development of rapid drug susceptibility testing methods based on genetic sequence.Raw genotype-phenotype correlation data were extracted as part of a comprehensive systematic review to develop a standardised analytical approach for interpreting resistance associated mutations for rifampicin, isoniazid, ofloxacin/levofloxacin, moxifloxacin, amikacin, kanamycin, capreomycin, streptomycin, ethionamide/prothionamide and pyrazinamide. Mutation frequencies in resistant and susceptible isolates were calculated, together with novel statistical measures to classify mutations as high, moderate, minimal or indeterminate confidence for predicting resistance.We identified 286 confidence-graded mutations associated with resistance. Compared to phenotypic methods, sensitivity (95% CI) for rifampicin was 90.3% (89.6-90.9%), while for isoniazid it was 78.2% (77.4-79.0%) and their specificities were 96.3% (95.7-96.8%) and 94.4% (93.1-95.5%), respectively. For second-line drugs, sensitivity varied from 67.4% (64.1-70.6%) for capreomycin to 88.2% (85.1-90.9%) for moxifloxacin, with specificity ranging from 90.0% (87.1-92.5%) for moxifloxacin to 99.5% (99.0-99.8%) for amikacin.This study provides a standardised and comprehensive approach for the interpretation of mutations as predictors of M. tuberculosis drug-resistant phenotypes. These data have implications for the clinical interpretation of molecular diagnostics and next-generation sequencing as well as efficient individualised therapy for patients with drug-resistant tuberculosis.

Use of whole genome deep sequencing to define emerging minority variants in virus envelope genes in herpesvirus treated with novel antimicrobial K21

New antivirals are required to prevent rising antimicrobial resistance from replication inhibitors. The aim of this study was to analyse the range of emerging mutations in herpesvirus by whole genome deep sequencing. We tested human herpesvirus 6 treatment with novel antiviral K21, where evidence indicated distinct effects on virus envelope proteins. We treated BACmid cloned virus in order to analyse mechanisms and candidate targets for resistance. Illumina based next generation sequencing technology enabled analyses of mutations in 85 genes to depths of 10,000 per base detecting low prevalent minority variants (<1%). After four passages in tissue culture the untreated virus accumulated mutations in infected cells giving an emerging mixed population (45-73%) of non-synonymous SNPs in six genes including two envelope glycoproteins. Strikingly, treatment with K21 did not accumulate the passage mutations; instead a high frequency mutation was selected in envelope protein gQ2, part of the gH/gL complex essential for herpesvirus infection. This introduced a stop codon encoding a truncation mutation previously observed in increased virion production. There was reduced detection of the glycoprotein complex in infected cells. This supports a novel pathway for K21 targeting virion envelopes distinct from replication inhibition.

Mycobacterium tuberculosis resistance prediction and lineage classification from genome sequencing: comparison of automated analysis tools

Whole-genome sequencing (WGS) has the potential to accelerate drug-susceptibility testing (DST) to design appropriate regimens for drug-resistant tuberculosis (TB). Several recently developed automated software tools promise to standardize the analysis and interpretation of WGS data. We assessed five tools (CASTB, KvarQ, Mykrobe Predictor TB, PhyResSE, and TBProfiler) with regards to DST and phylogenetic lineage classification, which we compared with phenotypic DST, Sanger sequencing, and traditional typing results for a collection of 91 strains. The lineage classifications by the tools generally only differed in the resolution of the results. However, some strains could not be classified at all and one strain was misclassified. The sensitivities and specificities for isoniazid and rifampicin resistance of the tools were high, whereas the results for ethambutol, pyrazinamide, and streptomycin resistance were more variable. False-susceptible DST results were mainly due to missing mutations in the resistance catalogues that the respective tools employed for data interpretation. Notably, we also found cases of false-resistance because of the misclassification of polymorphisms as resistance mutations. In conclusion, the performance of current WGS analysis tools for DST is highly variable. Sustainable business models and a shared, high-quality catalogue of resistance mutations are needed to ensure the clinical utility of these tools.

Removing the bottleneck in whole genome sequencing of Mycobacterium tuberculosis for rapid drug resistance analysis: a call to action

Whole genome sequencing (WGS) can provide a comprehensive analysis of Mycobacterium tuberculosis mutations that cause resistance to anti-tuberculosis drugs. With the deployment of bench-top sequencers and rapid analytical software, WGS is poised to become a useful tool to guide treatment. However, direct sequencing from clinical specimens to provide a full drug resistance profile remains a serious challenge. This article reviews current practices for extracting M. tuberculosis DNA and possible solutions for sampling sputum. Techniques under consideration include enzymatic digestion, physical disruption, chemical degradation, detergent solubilization, solvent extraction, ligand-coated magnetic beads, silica columns, and oligonucleotide pull-down baits. Selective amplification of genomic bacterial DNA in sputum prior to WGS may provide a solution, and differential lysis to reduce the levels of contaminating human DNA is also being explored. To remove this bottleneck and accelerate access to WGS for patients with suspected drug-resistant tuberculosis, it is suggested that a coordinated and collaborative approach be taken to more rapidly optimize, compare, and validate methodologies for sequencing from patient samples.