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

Universal Lineage-Independent Markers of Multidrug Resistance in Mycobacterium tuberculosis

(1) Background: This study was aimed to identify universal genetic markers of multidrug resistance (MDR) in Mycobacterium tuberculosis (Mtb) and establish statistical associations among identified mutations to enhance understanding of MDR in Mtb and inform diagnostic and treatment development. (2) Methods: GWAS analysis and the statistical evaluation of identified polymorphic sites within protein-coding genes of Mtb were performed. Statistical associations between specific mutations and antibiotic resistance were established using attributable risk statistics. (3) Results: Sixty-four polymorphic sites were identified as universal markers of drug resistance, with forty-seven in PE/PPE regions and seventeen in functional genes. Mutations in genes such as cyp123, fadE36, gidB, and ethA showed significant associations with resistance to various antibiotics. Notably, mutations in cyp123 at codon position 279 were linked to resistance to ten antibiotics. The study highlighted the role of PE/PPE and PE_PGRS genes in Mtb's evolution towards a 'mutator phenotype'. The pathways of acquisition of mutations forming the epistatic landscape of MDR were discussed. (4) Conclusions: This research identifies marker mutations across the Mtb genome associated with MDR. The findings provide new insights into the molecular basis of MDR acquisition in Mtb, aiding in the development of more effective diagnostics and treatments targeting these mutations to combat MDR tuberculosis.

Next Generation Sequencing in orthopaedic infections - Where is the road headed?

Next-generation sequencing (NGS) has emerged as a game changer in the field of orthopaedic diagnostics, notably in the detection and management of infections associated with prosthetic joints and implants. This paper conducts an exhaustive examination of the pivotal role, outcomes, and prospective future uses of NGS in diagnosing orthopaedic infections. In comparison to conventional culture-based methods, NGS offers a marked improvement in sensitivity thereby facilitating prompt and comprehensive identification of pathogens. This encompasses the ability to detect polymicrobial infections, antibiotic-resistant strains, and previously imperceptible microorganisms. Furthermore, this article delves into the technology's contribution to advancing personalized medicine and promoting judicious antibiotic use. Nonetheless, the seamless integration of NGS into routine clinical practice is impeded by challenges such as substantial financial outlays, the requisite for specialized equipment and expertise, and the intricacy associated with data analysis. Notwithstanding these impediments, the potential for NGS to revolutionize orthopaedic diagnostics remains substantial, with ongoing advancements poised to address current limitations and broaden its scope within clinical applications.

Current and Future Technologies for the Detection of Antibiotic-Resistant Bacteria

Antibiotic resistance is a global public health concern, posing a significant threat to the effectiveness of antibiotics in treating bacterial infections. The accurate and timely detection of antibiotic-resistant bacteria is crucial for implementing appropriate treatment strategies and preventing the spread of resistant strains. This manuscript provides an overview of the current and emerging technologies used for the detection of antibiotic-resistant bacteria. We discuss traditional culture-based methods, molecular techniques, and innovative approaches, highlighting their advantages, limitations, and potential future applications. By understanding the strengths and limitations of these technologies, researchers and healthcare professionals can make informed decisions in combating antibiotic resistance and improving patient outcomes.

simpiTB - a pipeline designed to extract meaningful information from whole genome sequencing data of Mycobacterium tuberculosis complex, allows to combine genomic, phylogenetic and clustering analyses in existing SITVIT databases

Data obtained from new sequencing technologies are evolving rapidly, leading to the development of specific bioinformatic tools, pipelines and softwares. Several algorithms and tools are today available allowing a better identification and description of Mycobacterium tuberculosis complex (MTBC) isolates worldwide. Our approach consists in applying existing methods to analyze DNA sequencing data (from FASTA or FASTQ files), and tentatively extract meaningful information that would facilitate identification as well as a better understanding and management of MTBC isolates (taking into account whole genome sequencing and classical genotyping data). The aim of this study is to propose a pipeline analysis allowing to potentially simplify MTBC data analysis by providing different ways to interpret genomic or genotyping information based on existing tools. Furthermore, we propose a "reconciledTB" list making a link with results directly obtained from whole genome sequencing (WGS) data and results obtained from classical genotyping analysis (data inferred from SpoTyping and MIRUReader). Data visualization graphics and trees generated provide additional elements to better understand and confer associations among information overlap analyses. Additionally, comparison between data entered in an international genotyping database (SITVITEXTEND) and ensuing data obtained from the pipeline not only provide meaningful information, but further suggest that simpiTB could also be suitable for new data integration in specific TB genotyping databases.

Multiple CD59 Polymorphisms in Chinese Patients with Mycobacterium tuberculosis Infection

Background and Objective. Tuberculosis (TB) is a major threat to human health, especially in developing countries. Its susceptibility and progression depend on interactions between mycobacterium tuberculosis, host immune system, and genetic and environmental factors. Up to now, many studies have presented the association between TB susceptibility and host genetic polymorphisms, but never regarding CD59 gene, which is an essential complement regulator. This study investigated the relationship between multiple CD59 single nucleotide polymorphisms (SNPs) and susceptibility to TB among Chinese patients. Methods. A case–control study was conducted to investigate the SNPs at CD59 rs1047581, rs7046, rs2231460, rs184251026, rs41275164, rs831633, rs704700, rs41275166, and rs10768024 by sequence-specific primer-polymerase chain reaction (SSP-PCR) in 900 tuberculosis patients and 1,534 controls. Results. The minor allele frequencies at rs2231460, rs184251026, rs41275164, and rs41275166 were extremely low both in the Cases (0.00%–0.61%) and in the Controls (0.07%–0.43%), comparatively at rs1047581, rs7046, rs831633, rs704700, and rs10768024 were notably higher both in the Cases (8.23%–48.39%) and in the Controls (8.57%–47.16%). Among the nine SNPs, only homozygous CC genotype at rs10768024 showed a significant protective effect against TB than homozygous TT genotype (OR(95% CI) = 0.59(0.38, 0.91), χ2 = 5.779, $P=0.016$ ), and homozygous TT and heterozygous CT genotypes showed a significant risk of TB infection in the recessive model (OR(95% CI) = 1.68(1.10, 2.56), χ2 = 5.769, $P=0.016$ ). Further analysis verified that rs10768024 CC genotype independently related to TB susceptibility (OR(95% CI) = 0.60(0.39, 0.91), Wald χ2 = 5.664, $P=0.017$ ) in multivariate logistic regression analysis, and its genetic mutation was independent of the other SNPs (r2 = 0.00–0.20) in haplotype analysis. Conclusions. The first investigation of the CD59 gene and susceptibility to TB suggests a significant risk with homozygous TT and heterozygous CT genotypes at rs10768024 loci. The homozygous CC mutation at rs10768024 loci showed a significant protection against TB susceptibility.

Bioinformatics toolbox for exploring target mutation-induced drug resistance

Drug resistance is increasingly among the main issues affecting human health and threatening agriculture and food security. In particular, developing approaches to overcome target mutation-induced drug resistance has long been an essential part of biological research. During the past decade, many bioinformatics tools have been developed to explore this type of drug resistance, and they have become popular for elucidating drug resistance mechanisms in a low cost, fast and effective way. However, these resources are scattered and underutilized, and their strengths and limitations have not been systematically analyzed and compared. Here, we systematically surveyed 59 freely available bioinformatics tools for exploring target mutation-induced drug resistance. We analyzed and summarized these resources based on their functionality, data volume, data source, operating principle, performance, etc. And we concisely discussed the strengths, limitations and application examples of these tools. Specifically, we tested some predictive tools and offered some thoughts from the clinician's perspective. Hopefully, this work will provide a useful toolbox for researchers working in the biomedical, pesticide, bioinformatics and pharmaceutical engineering fields, and a good platform for non-specialists to quickly understand drug resistance prediction.

MycoVarP: Mycobacterium Variant and Drug Resistance Prediction Pipeline for Whole-Genome Sequence Data Analysis

Whole-genome sequencing (WGS) provides a comprehensive tool to analyze the bacterial genomes for genotype–phenotype correlations, diversity of single-nucleotide variant (SNV), and their evolution and transmission. Several online pipelines and standalone tools are available for WGS analysis of Mycobacterium tuberculosis (Mtb) complex (MTBC). While they facilitate the processing of WGS data with minimal user expertise, they are either too general, providing little insights into bacterium-specific issues such as gene variations, INDEL/synonymous/PE-PPE (IDP family), and drug resistance from sample data, or are limited to specific objectives, such as drug resistance. It is understood that drug resistance and lineage-specific issues require an elaborate prioritization of identified variants to choose the best target for subsequent therapeutic intervention. Mycobacterium variant pipeline (MycoVarP) addresses these specific issues with a flexible battery of user-defined and default filters. It provides an end-to-end solution for WGS analysis of Mtb variants from the raw reads and performs two quality checks, viz, before trimming and after alignments of reads to the reference genome. MycoVarP maps the annotated variants to the drug-susceptible (DS) database and removes the false-positive variants, provides lineage identification, and predicts potential drug resistance. We have re-analyzed the WGS data reported by Advani et al. (2019) using MycoVarP and identified some additional variants not reported so far. We conclude that MycoVarP will help in identifying nonsynonymous, true-positive, drug resistance–associated variants more effectively and comprehensively, including those within the IDP of the PE-PPE/PGRS family, than possible from the currently available pipelines.

Whole genome sequencing reveals large deletions and other loss of function mutations in Mycobacterium tuberculosis drug resistance genes

Drug resistance in Mycobacterium tuberculosis, the causative agent of tuberculosis disease, arises from genetic mutations in genes coding for drug-targets or drug-converting enzymes. SNPs linked to drug resistance have been extensively studied and form the basis of molecular diagnostics and sequencing-based resistance profiling. However, alternative forms of functional variation such as large deletions and other loss of function (LOF) mutations have received much less attention, but if incorporated into diagnostics they are likely to improve their predictive performance. Our work aimed to characterize the contribution of LOF mutations found in 42 established drug resistance genes linked to 19 anti-tuberculous drugs across 32689 sequenced clinical isolates. The analysed LOF mutations included large deletions (n=586), frameshifts (n=4764) and premature stop codons (n=826). We found LOF mutations in genes strongly linked to pyrazinamide (pncA), isoniazid (katG), capreomycin (tlyA), streptomycin (e.g. gid) and ethionamide (ethA, mshA) (P<10^-5), but also in some loci linked to drugs where relatively less phenotypic data is available [e.g. cycloserine, delaminid, bedaquiline, para-aminosalicylic acid (PAS), and clofazimine]. This study reports that large deletions (median size 1115 bp) account for a significant portion of resistance variants found for PAS (+7.1% of phenotypic resistance percentage explained), pyrazinamide (+3.5%) and streptomycin (+2.6%) drugs, and can be used to improve the prediction of cryptic resistance. Overall, our work highlights the importance of including LOF mutations (e.g. large deletions) in predicting genotypic drug resistance, thereby informing tuberculosis infection control and clinical decision-making.

Retrospective evaluation of routine whole genome sequencing of Mycobacterium tuberculosis at the Belgian National Reference Center, 2019

OBJECTIVES

Since January 2019, the Belgian National Reference Center for Mycobacteria (NRC) has switched from conventional typing to prospective whole-genome sequencing (WGS) of all submitted Mycobacterium tuberculosis complex (MTB) isolates. The ISO17025 validated procedure starts with semi-automated extraction and purification of gDNA directly from the submitted MGIT tubes, without preceding subculturing. All samples are then sequenced on an Illumina MiSeq sequencer and analyzed using an in-house developed and validated bioinformatics workflow to determine the species and antimicrobial resistance. In this study, we retrospectively compare results obtained via WGS to conventional phenotypic and genotypic testing, for all Belgian MTB strains analyzed in 2019 (n = 306).

RESULTS

In all cases, the WGS-based procedure was able to identify correctly the MTB species. Compared to MGIT drug susceptibility testing (DST), the sensitivity and specificity of genetic prediction of resistance to first-line antibiotics were respectively 100 and 99% (rifampicin, RIF), 90.5 and 100% (isoniazid, INH), 100 and 98% (ethambutol, EMB) and 61.1 and 100% (pyrazinamide, PZA). The negative predictive value was above 95% for these four first-line drugs. A positive predictive value of 100% was calculated for INH and PZA, 80% for RIF and 45% for EMB.

CONCLUSIONS

Our study confirms the effectiveness of WGS for the rapid detection of M. tuberculosis complex and its drug resistance profiles for first-line drugs even when working directly on MGIT tubes, and supports the introduction of this test into the routine workflow of laboratories performing tuberculosis diagnosis.

Application of Computational Methods in Understanding Mutations in Mycobacterium tuberculosis Drug Resistance

The emergence of drug-resistant strains of Mycobacterium tuberculosis (Mtb) impedes the End TB Strategy by the World Health Organization aiming for zero deaths, disease, and suffering at the hands of tuberculosis (TB). Mutations within anti-TB drug targets play a major role in conferring drug resistance within Mtb; hence, computational methods and tools are being used to understand the mechanisms by which they facilitate drug resistance. In this article, computational techniques such as molecular docking and molecular dynamics are applied to explore point mutations and their roles in affecting binding affinities for anti-TB drugs, often times lowering the protein’s affinity for the drug. Advances and adoption of computational techniques, chemoinformatics, and bioinformatics in molecular biosciences and resources supporting machine learning techniques are in abundance, and this has seen a spike in its use to predict mutations in Mtb. This article highlights the importance of molecular modeling in deducing how point mutations in proteins confer resistance through destabilizing binding sites of drugs and effectively inhibiting the drug action.

Whole genome sequencing of clinical samples reveals extensively drug resistant tuberculosis (XDR TB) strains from the Beijing lineage in Nigeria, West Africa

Multi-drug (MDR) and extensively drug-resistant (XDR) tuberculosis (TB) continues to be a global public health problem especially in high TB burden countries like Nigeria. Many of these cases are undetected and go on to infect high risk individuals. Clinical samples from positive rifampicin resistant Xpert®MTB/Rif assay were subjected to direct whole genome sequencing and bioinformatics analysis to identify the full antibiotics resistance and lineage profile. We report two (2) XDR TB samples also belonging to the East-Asian/Beijing family of lineage 2 Mycobacterium tuberculosis complex from clinical samples in Nigeria. Our findings further reveal the presence of mutations that confer resistance to first-line drugs (rifampicin, isoniazid, ethambutol and pyrazanimide), second-line injectables (capreomycin, streptomycin, kanamycin and/or amikacin) and at least one of the fluoroquinolones (ofloxacin, moxifloxacin, levofloxacin and/or ciprofloxacin) in both samples. The genomic sequence data from this study not only provide the first evidence of XDR TB in Nigeria and West Africa, but also emphasize the importance of WGS in accurately detecting MDR and XDR TB, to ensure adequate and proper management treatment regimens for affected individuals. This will greatly aid in preventing the spread of drug resistance TB in high burden countries.

The Epistatic Landscape of Antibiotic Resistance of Different Clades of Mycobacterium tuberculosis

Drug resistance (DR) remains a global challenge in tuberculosis (TB) control. In order to develop molecular-based diagnostic methods to replace the traditional culture-based diagnostics, there is a need for a thorough understanding of the processes that govern TB drug resistance. The use of whole-genome sequencing coupled with statistical and computational methods has shown great potential in unraveling the complexity of the evolution of DR-TB. In this study, we took an innovative approach that sought to determine nonrandom associations between polymorphic sites in Mycobacterium tuberculosis (Mtb) genomes. Attributable risk statistics were applied to identify the epistatic determinants of DR in different clades of Mtb and the possible evolutionary pathways of DR development. It was found that different lineages of Mtb exploited different evolutionary trajectories towards multidrug resistance and compensatory evolution to reduce the DR-associated fitness cost. Epistasis of DR acquisition is a new area of research that will aid in the better understanding of evolutionary biological processes and allow predicting upcoming multidrug-resistant pathogens before a new outbreak strikes humanity.

Antibiotic resistance: Time of synthesis in a post-genomic age

Antibiotic resistance has been highlighted by international organizations, including World Health Organization, World Bank and United Nations, as one of the most relevant global health problems. Classical approaches to study this problem have focused in infected humans, mainly at hospitals. Nevertheless, antibiotic resistance can expand through different ecosystems and geographical allocations, hence constituting a One-Health, Global-Health problem, requiring specific integrative analytic tools. Antibiotic resistance evolution and transmission are multilayer, hierarchically organized processes with several elements (from genes to the whole microbiome) involved. However, their study has been traditionally gene-centric, each element independently studied. The development of robust-economically affordable whole genome sequencing approaches, as well as other -omic techniques as transcriptomics and proteomics, is changing this panorama. These technologies allow the description of a system, either a cell or a microbiome as a whole, overcoming the problems associated with gene-centric approaches. We are currently at the time of combining the information derived from -omic studies to have a more holistic view of the evolution and spread of antibiotic resistance. This synthesis process requires the accurate integration of -omic information into computational models that serve to analyse the causes and the consequences of acquiring AR, fed by curated databases capable of identifying the elements involved in the acquisition of resistance. In this review, we analyse the capacities and drawbacks of the tools that are currently in use for the global analysis of AR, aiming to identify the more useful targets for effective corrective interventions.

Evaluation of drug susceptibility profile of Mycobacterium tuberculosis Lineage 1 from Brazil based on whole genome sequencing and phenotypic methods

BACKGROUND

The evaluation of procedures for drug susceptibility prediction of Mycobacterium tuberculosis based on genomic data against the conventional reference method test based on culture is realistic considering the scenario of growing number of tools proposals based on whole-genome sequences (WGS).

OBJECTIVES

This study aimed to evaluate drug susceptibility testing (DST) outcome based on WGS tools and the phenotypic methods performed on isolates of M. tuberculosis Lineage 1 from the state of Pará, Brazil, generally associated with low levels of drug resistance.

METHODOLOGY

Culture based DST was performed using the Proportion Method in Löwenstein-Jensen medium on 71 isolates that had been submitted to WGS. We analysed the seven main genome sequence-based tools for resistance and lineage prediction applied to M. tuberculosis and for comparison evaluation we have used the Kappa concordance test.

FINDINGS

When comparing the WGS-based tools against the DST, we observed the highest level of agreement using TB-profiler. Among the tools, TB-profiler, KvarQ and Mykrobe were those which identified the largest number of TB-MDR cases. Comparing the four most sensitive tools regarding resistance prediction, agreement was observed for 43 genomes.

MAIN CONCLUSIONS

Drug resistance profiling using next-generation sequencing offers rapid assessment of resistance-associated mutations, therefore facilitating rapid access to effective treatment.

Simvastatin decreases the silver resistance of E. faecalis through compromising the entrapping function of extracellular polymeric substances against silver

Enterococcus faecalis (E. faecalis) is a Gram-positive bacterium closely related to many refractory infections of human and shows the resistant ability against the antibacterial effects of silver. Simvastatin is a semisynthetic compound derived from lovastatin and a hydroxymethyl glutaryl coenzyme A(HMG-COA) reductase inhibitor showing certain inhibitive effects on bacteria. The main purpose of this study was to establish and characterize the Ag⁺/silver nanoparticles (AgNPs)-resistant E. faecalis, and further evaluate the function of extracellular polymeric substances (EPS) in the silver resistance and the effect of simvastatin on the silver-resistance of E. faecalis. The results showed that the established silver-resistant E. faecalis had strong resistance against both Ag⁺ and AgNPs and simvastatin could decrease the silver-resistance of both original and Ag⁺/AgNPs-resistant E. faecalis. The Transmission electron microscopy (TEM), High-angle annular dark-field (HAADF) and mapping images showed that the silver ions or particles aggregated and confined in the EPS on surface areas of the cell membrane when the silver-resistant E. faecalis were incubated with Ag⁺ or AgNPs. When the simvastatin was added, the silver element was not confined in the EPS and entered the bacteria. These findings may indicate that the silver resistance of E. faecalis was derived from the entrapping function of EPS, but simvastatin could compromise the function of EPS to decrease the silver resistant ability of E. faecalis.