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

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.

Long-Read Sequencing with Hierarchical Clustering for Antiretroviral Resistance Profiling of Mixed Human Immunodeficiency Virus Quasispecies

BACKGROUND

HIV infections often develop drug resistance mutations (DRMs), which can increase the risk of virological failure. However, it has been difficult to determine if minor mutations occur in the same genome or in different virions using Sanger sequencing and short-read sequencing methods. Oxford Nanopore Technologies (ONT) sequencing may improve antiretroviral resistance profiling by allowing for long-read clustering.

METHODS

A new ONT sequencing-based method for profiling DRMs in HIV quasispecies was developed and validated. The method used hierarchical clustering of long amplicons that cover regions associated with different types of antiretroviral drugs. A gradient series of an HIV plasmid and 2 plasma samples was prepared to validate the clustering performance. The ONT results were compared to those obtained with Sanger sequencing and Illumina sequencing in 77 HIV-positive plasma samples to evaluate the diagnostic performance.

RESULTS

In the validation study, the abundance of detected quasispecies was concordant with the predicted result with the R2 of > 0.99. During the diagnostic evaluation, 59/77 samples were successfully sequenced for DRMs. Among 18 failed samples, 17 were below the limit of detection of 303.9 copies/μL. Based on the receiver operating characteristic analysis, the ONT workflow achieved an F1 score of 0.96 with a cutoff of 0.4 variant allele frequency. Four cases were found to have quasispecies with DRMs, in which 2 harbored quasispecies with more than one class of DRMs. Treatment modifications were recommended for these cases.

CONCLUSIONS

Long-read sequencing coupled with hierarchical clustering could differentiate the quasispecies resistance profiles in HIV-infected samples, providing a clearer picture for medical care.

Transmission Dynamics of a Mycobacterium tuberculosis Complex Outbreak in an Indigenous Population in the Colombian Amazon Region

Whole genome sequencing (WGS) has become the main tool for studying the transmission of Mycobacterium tuberculosis complex (MTBC) strains; however, the clonal expansion of one strain often limits its application in local MTBC outbreaks. The use of an alternative reference genome and the inclusion of repetitive regions in the analysis could potentially increase the resolution, but the added value has not yet been defined. Here, we leveraged short and long WGS read data of a previously reported MTBC outbreak in the Colombian Amazon Region to analyze possible transmission chains among 74 patients in the indigenous setting of Puerto Nariño (March to October 2016). In total, 90.5% (67/74) of the patients were infected with one distinct MTBC strain belonging to lineage 4.3.3. Employing a reference genome from an outbreak strain and highly confident single nucleotide polymorphisms (SNPs) in repetitive genomic regions, e.g., the proline-glutamic acid/proline-proline-glutamic-acid (PE/PPE) gene family, increased the phylogenetic resolution compared to a classical H37Rv reference mapping approach. Specifically, the number of differentiating SNPs increased from 890 to 1,094, which resulted in a more granular transmission network as judged by an increasing number of individual nodes in a maximum parsimony tree, i.e., 5 versus 9 nodes. We also found in 29.9% (20/67) of the outbreak isolates, heterogenous alleles at phylogenetically informative sites, suggesting that these patients are infected with more than one clone. In conclusion, customized SNP calling thresholds and employment of a local reference genome for a mapping approach can improve the phylogenetic resolution in highly clonal MTBC populations and help elucidate within-host MTBC diversity. IMPORTANCE The Colombian Amazon around Puerto Nariño has a high tuberculosis burden with a prevalence of 1,267/100,000 people in 2016. Recently, an outbreak of Mycobacterium tuberculosis complex (MTBC) bacteria among the indigenous populations was identified with classical MTBC genotyping methods. Here, we employed a whole-genome sequencing-based outbreak investigation in order to improve the phylogenetic resolution and gain new insights into the transmission dynamics in this remote Colombian Amazon Region. The inclusion of well-supported single nucleotide polymorphisms in repetitive regions and a de novo-assembled local reference genome provided a more granular picture of the circulating outbreak strain and revealed new transmission chains. Multiple patients from different settlements were possibly infected with at least two different clones in this high-incidence setting. Thus, our results have the potential to improve molecular surveillance studies in other high-burden settings, especially regions with few clonal multidrug-resistant (MDR) MTBC lineages/clades.

Use of High-Resolution Geospatial and Genomic Data to Characterize Recent Tuberculosis Transmission, Botswana

Combining genomic and geospatial data can be useful for understanding Mycobacterium tuberculosis transmission in high-burden tuberculosis (TB) settings. We performed whole-genome sequencing on M. tuberculosis DNA extracted from sputum cultures from a population-based TB study conducted in Gaborone, Botswana, during 2012-2016. We determined spatial distribution of cases on the basis of shared genotypes among isolates. We considered clusters of isolates with ≤5 single-nucleotide polymorphisms identified by whole-genome sequencing to indicate recent transmission and clusters of ≥10 persons to be outbreaks. We obtained both molecular and geospatial data for 946/1,449 (65%) participants with culture-confirmed TB; 62 persons belonged to 5 outbreaks of 10-19 persons each. We detected geospatial clustering in just 2 of those 5 outbreaks, suggesting heterogeneous spatial patterns. Our findings indicate that targeted interventions applied in smaller geographic areas of high-burden TB identified using integrated genomic and geospatial data might help interrupt TB transmission during outbreaks.

Variants associated with Bedaquiline (BDQ) resistance identified in Rv0678 and efflux pump genes in Mycobacterium tuberculosis isolates from BDQ naïve TB patients in Pakistan

Background

Mutations in the Rv0678, pepQ and atpE genes of Mycobacterium tuberculosis (MTB) have been reported to be associated with reduced antimycobacterial susceptibility to bedaquiline (BDQ). Resistance conferring mutations in treatment naïve MTB strains is likely to have implications for BDQ based new drug regimen that aim to shorten treatment duration. We therefore investigated the genetic basis of resistance to BDQ in MTB clinical isolates from BDQ naïve TB patients from Pakistan. In addition, mutations in genes associated with efflux pumps were investigated as an alternate mechanism of resistance.

Methods

Based on convenience sampling, we studied 48 MTB clinical isolates from BDQ naïve TB patients. These isolates (from our strain bank) included 38 MDR/pre-XDR/XDR (10 BDQ resistant, 8 BDQ intermediate and 20 BDQ susceptible) and 10 pan drug susceptible MTB isolates. All strains were subjected to whole genome sequencing and genomes were analysed to identify variants in Rv0678, pepQ, atpE, Rv1979c, mmpLS and mmpL5 and drug resistance associated efflux pump genes.

Results

Of the BDQ resistant and intermediate strains 44% (8/18) had variants in Rv0678 including; two reported mutations S63R/G, six previously unreported variants; L40F, R50Q and R107C and three frameshift mutations; G25fs, D64fs and D109fs.

Variants in efflux pumps; Rv1273c (G462K), Rv0507c (R426H) and Rv1634c (E198R) were found to be present in drug resistant isolates including BDQ resistant and intermediate isolates. E198R in efflux pump gene Rv1634c was the most frequently occurring variant in BDQ resistant and intermediate isolates (n = 10).

Conclusion

We found RAVs in Rv0678 to be commonly associated with BDQ resistance. Further confirmation of the role of variants in efflux pump genes in resistance is required so that they may be incorporated in genome-based diagnostics for drug resistant MTB.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12866-022-02475-4.

Accurate and rapid prediction of tuberculosis drug resistance from genome sequence data using traditional machine learning algorithms and CNN

Effective and timely antibiotic treatment depends on accurate and rapid in silico antimicrobial-resistant (AMR) predictions. Existing statistical rule-based Mycobacterium tuberculosis (MTB) drug resistance prediction methods using bacterial genomic sequencing data often achieve varying results: high accuracy on some antibiotics but relatively low accuracy on others. Traditional machine learning (ML) approaches have been applied to classify drug resistance for MTB and have shown more stable performance. However, there is no study that uses deep learning architecture like Convolutional Neural Network (CNN) on a large and diverse cohort of MTB samples for AMR prediction. We developed 24 binary classifiers of MTB drug resistance status across eight anti-MTB drugs and three different ML algorithms: logistic regression, random forest and 1D CNN using a training dataset of 10,575 MTB isolates collected from 16 countries across six continents, where an extended pan-genome reference was used for detecting genetic features. Our 1D CNN architecture was designed to integrate both sequential and non-sequential features. In terms of F1-scores, 1D CNN models are our best classifiers that are also more accurate and stable than the state-of-the-art rule-based tool Mykrobe predictor (81.1 to 93.8%, 93.7 to 96.2%, 93.1 to 94.8%, 95.9 to 97.2% and 97.1 to 98.2% for ethambutol, rifampicin, pyrazinamide, isoniazid and ofloxacin respectively). We applied filter-based feature selection to find AMR relevant features. All selected variant features are AMR-related ones in CARD database. 78.8% of them are also in the catalogue of MTB mutations that were recently identified as drug resistance-associated ones by WHO. To facilitate ML model development for AMR prediction, we packaged every step into an automated pipeline and shared the source code at https://github.com/KuangXY3/MTB-AMR-classification-CNN.

Experimental confirmation that an uncommon rrs gene mutation (g878a) of Mycobacterium tuberculosis confers resistance to streptomycin

The effective treatment of patients diagnosed with drug resistant tuberculosis is highly dependent upon the ability to rapidly and accurately determine the antibiotic susceptibility profile of the Mycobacterium tuberculosis isolate(s) involved. Thus, as more clinical microbiology laboratories advance towards the use of DNA sequence-based diagnostics, it is imperative that their predictive functions extend beyond the well-known resistance mutations, in order to also encompass as many of the lower-frequency mutations as possible. However, in most cases, the fundamental experimental proof that links these uncommon mutations with phenotypic resistance is lacking. One such example is the g878a polymorphism within the rrs 16s rRNA gene. We, and others, have identified this mutation within a small number of drug-resistant isolates, although a consensus regarding exactly which aminoglycoside antibiotic(s) it confers resistance toward has not previously been reached. Here we have employed oligo-mediated recombineering to introduce the g878a polymorphism into the rrs gene of M. bovis BCG - a close relative of M. tuberculosis - and demonstrate that it confers low-level resistance to streptomycin alone. It does not confer cross-resistance towards amikacin, capreomycin, nor kanamycin. We also demonstrate that the rrs g878a mutation exerts a substantial fitness defect in vitro , that may at least in part explain why clinical isolates bearing this mutation appear to be quite rare. Overall, this study provides clarity to the phenotype attributable to the rrs g878a mutation and is relevant to the future implementation of genomics-based diagnostics, as well as the clinical management of patients where this particular polymorphism is encountered.

Nanopore Sequencing for Mycobacterium tuberculosis: a Critical Review of the Literature, New Developments, and Future Opportunities

The next-generation, short-read sequencing technologies that generate comprehensive, whole-genome data with single nucleotide resolution have already advanced tuberculosis diagnosis, treatment, surveillance, and source investigation. Their high costs, tedious and lengthy processes, and large equipment remain major hurdles for research use in high tuberculosis burden countries and implementation into routine care. The portable next-generation sequencing devices developed by Oxford Nanopore Technologies (ONT) are attractive alternatives due to their long-read sequence capability, compact low-cost hardware, and continued improvements in accuracy and throughput. A systematic review of the published literature demonstrated limited uptake of ONT sequencing in tuberculosis research and clinical care. Of the 12 eligible articles presenting ONT sequencing data on at least one Mycobacterium tuberculosis sample, four addressed software development for long-read ONT sequencing data with potential applications for M. tuberculosis. Only eight studies presented results of ONT sequencing of M. tuberculosis, of which five performed whole-genome and three did targeted sequencing. Based on these findings, we summarize the standard processes, reflect on the current limitations of ONT sequencing technology, and the research needed to overcome the main hurdles. The low capital cost, portable nature and continued improvement in the performance of ONT sequencing make it an attractive option for sequencing for research and clinical care, but limited data are available on its application in the tuberculosis field. Important research investment is needed to unleash the full potential of ONT sequencing for tuberculosis research and care.

Detection of minor variants in Mycobacterium tuberculosis whole genome sequencing data

The study of genetic minority variants is fundamental to the understanding of complex processes such as evolution, fitness, transmission, virulence, heteroresistance and drug tolerance in Mycobacterium tuberculosis (Mtb). We evaluated the performance of the variant calling tool LoFreq to detect de novo as well as drug resistance conferring minor variants in both in silico and clinical Mtb next generation sequencing (NGS) data. The in silico simulations demonstrated that LoFreq is a conservative variant caller with very high precision (≥96.7%) over the entire range of depth of coverage tested (30x to1000x), independent of the type and frequency of the minor variant. Sensitivity increased with increasing depth of coverage and increasing frequency of the variant, and was higher for calling insertion and deletion (indel) variants than for single nucleotide polymorphisms (SNP). The variant frequency limit of detection was 0.5% and 3% for indel and SNP minor variants, respectively. For serial isolates from a patient with DR-TB; LoFreq successfully identified all minor Mtb variants in the Rv0678 gene (allele frequency as low as 3.22% according to targeted deep sequencing) in whole genome sequencing data (median coverage of 62X). In conclusion, LoFreq can successfully detect minor variant populations in Mtb NGS data, thus limiting the need for filtering of possible false positive variants due to sequencing error. The observed performance statistics can be used to determine the limit of detection in existing whole genome sequencing Mtb data and guide the required depth of future studies that aim to investigate the presence of minor variants.

A 3D-Printed Microfluidic Device for qPCR Detection of Macrolide-Resistant Mutations of Mycoplasma pneumoniae

Mycoplasma pneumonia (MP) is a common respiratory infection generally treated with macrolides, but resistance mutations against macrolides are often detected in mycoplasma pneumoniae in China. Rapid and accurate identification of mycoplasma pneumoniae and its mutant type is necessary for precise medication. This paper presents a 3D-printed microfluidic device to achieve this. By 3D printing, the stereoscopic structures such as microvalves, reservoirs, drainage tubes, and connectors were fabricated in one step. The device integrated commercial polymerase chain reaction (PCR) tubes as PCR chambers. The detection was a sample-to-answer procedure. First, the sample, a PCR mix, and mineral oil were respectively added to the reservoirs on the device. Next, the device automatically mixed the sample with the PCR mix and evenly dispensed the mixed solution and mineral oil into the PCR chambers, which were preloaded with the specified primers and probes. Subsequently, quantitative real-time PCR (qPCR) was carried out with the homemade instrument. Within 80 min, mycoplasma pneumoniae and its mutation type in the clinical samples were determined, which was verified by DNA sequencing. The easy-to-make and easy-to-use device provides a rapid and integrated detection approach for pathogens and antibiotic resistance mutations, which is urgently needed on the infection scene and in hospital emergency departments.

Microevolution of Mycobacterium tuberculosis Subpopulations and Heteroresistance in a Patient Receiving 27 Years of Tuberculosis Treatment in Germany

Preexisting and newly emerging resistant pathogen subpopulations (heteroresistance) are potential risk factors for treatment failure of multi/extensively drug resistant (MDR/XDR) tuberculosis (TB). Intrapatient evolutionary dynamics of Mycobacterium tuberculosis complex (Mtbc) strains and their implications on treatment outcomes are still not completely understood. To elucidate how Mtbc strains escape therapy, we analyzed 13 serial isolates from a German patient by whole-genome sequencing. Sequencing data were compared with phenotypic drug susceptibility profiles and the patient's collective 27-year treatment history to further elucidate factors fostering intrapatient resistance evolution. The patient endured five distinct TB episodes, ending in resistance to 16 drugs and a nearly untreatable XDR-TB infection. The first isolate obtained, during the patient's 5th TB episode, presented fixed resistance mutations to 7 anti-TB drugs, including isoniazid, rifampin, streptomycin, pyrazinamide, prothionamide, para-aminosalicylic acid, and cycloserine-terizidone. Over the next 13 years, a dynamic evolution with coexisting, heterogeneous subpopulations was observed in 6 out of 13 sequential bacterial isolates. The emergence of drug-resistant subpopulations coincided with frequent changes in treatment regimens, which often included two or fewer active compounds. This evolutionary arms race between competing subpopulations ultimately resulted in the fixation of a single XDR variant. Our data demonstrate the complex intrapatient microevolution of Mtbc subpopulations during failing MDR/XDR-TB treatment. Designing effective treatment regimens based on rapid detection of (hetero) resistance is key to avoid resistance development and treatment failure.

Thin-Layer-Agar-Based Direct Phenotypic Drug Susceptibility Testing on Sputum in Eswatini Rapidly Detects Mycobacterium tuberculosis Growth and Rifampicin Resistance Otherwise Missed by WHO-Endorsed Diagnostic Tests

Xpert MTB/RIF rapidly detects resistance to rifampicin (RR); however, this test misses I491F-RR conferring rpoB mutation, common in southern Africa. In addition, Xpert MTB/RIF does not distinguish between viable and dead Mycobacterium tuberculosis (MTB). We aimed to investigate the ability of thin-layer agar (TLA) direct drug-susceptibility testing (DST) to detect MTB and its drug-resistance profiles in field conditions in Eswatini. Consecutive samples were tested in parallel with Xpert MTB/RIF and TLA for rifampicin (1.0 μg/ml) and ofloxacin (2.0 μg/ml). TLA results were compared at the Reference Laboratory in Antwerp with indirect-DST on Löwenstein-Jensen or 7H11 solid media and additional phenotypic and genotypic testing to resolve discordance. TLA showed a positivity rate for MTB detection of 7.1% versus 10.0% for Xpert MTB/RIF. Of a total of 4,547 samples included in the study, 200 isolates were available for comparison to the composite reference. Within a median of 18.4 days, TLA detected RR with 93.0% sensitivity (95% confidence interval [CI], 77.4 to 98.0) and 99.4% specificity (95% CI, 96.7 to 99.9) versus 62.5% (95% CI, 42.7 to 78.8) and 99.3% (95% CI, 96.2 to 99.9) for Xpert MTB/RIF. Eight isolates, 28.6% of all RR-confirmed isolates, carried the I491F mutation, all detected by TLA. TLA also correctly identified 183 of the 184 ofloxacin-susceptible isolates (99.5% specificity; 95% CI, 97.0 to 99.9). In field conditions, TLA rapidly detects RR, and in this specific setting, it contributed to detection of additional RR patients over Xpert MTB/RIF, mainly but not exclusively due to I491F. TLA also accurately excluded fluoroquinolone resistance.

In-host population dynamics of Mycobacterium tuberculosis complex during active disease

Tuberculosis (TB) is a leading cause of death globally. Understanding the population dynamics of TB’s causative agent Mycobacterium tuberculosis complex (Mtbc) in-host is vital for understanding the efficacy of antibiotic treatment. We use longitudinally collected clinical Mtbc isolates that underwent Whole-Genome Sequencing from the sputa of 200 patients to investigate Mtbc diversity during the course of active TB disease after excluding 107 cases suspected of reinfection, mixed infection or contamination. Of the 178/200 patients with persistent clonal infection >2 months, 27 developed new resistance mutations between sampling with 20/27 occurring in patients with pre-existing resistance. Low abundance resistance variants at a purity of ≥19% in the first isolate predict fixation in the subsequent sample. We identify significant in-host variation in 27 genes, including antibiotic resistance genes, metabolic genes and genes known to modulate host innate immunity and confirm several to be under positive selection by assessing phylogenetic convergence across a genetically diverse sample of 20,352 isolates.