Multi-platform whole genome sequencing for tuberculosis clinical and surveillance applications.

Whole genome sequencing (WGS) of Mycobacterium tuberculosis offers valuable insights for tuberculosis (TB) control. High throughput platforms like Illumina and Oxford Nanopore Technology (ONT) are increasingly used globally, although ONT is known for higher error rates and is less established for genomic studies. Here we present a study comparing the sequencing outputs of both Illumina and ONT platforms, analysing DNA from 59 clinical isolates in highly endemic TB regions of Thailand. The resulting sequence data were used to profile the M. tuberculosis pairs for their lineage, drug resistance and presence in transmission chains, and were compared to publicly available WGS data from Thailand (n = 1456). Our results revealed isolates that are predominantly from lineages 1 and 2, with consistent drug resistance profiles, including six multidrug-resistant strains; however, analysis of ONT data showed longer phylogenetic branches, emphasising the technologies higher error rate. An analysis incorporating the larger dataset identified fifteen of our samples within six potential transmission clusters, including a significant clade of 41 multi-drug resistant isolates. ONT's extended sequences also revealed strain-specific structural variants in pe/ppe genes (e.g. ppe50), which are candidate loci for vaccine development. Despite some limitations, our results show that ONT sequencing is a promising approach for TB genomic research, supporting precision medicine and decision-making in areas with less developed infrastructure, which is crucial for tackling the disease's significant regional burden.

Newly Identified Mycobacterium africanum Lineage 10, Central Africa.

Analysis of genome sequencing data from >100,000 genomes of Mycobacterium tuberculosis complex using TB-Annotator software revealed a previously unknown lineage, proposed name L10, in central Africa. Phylogenetic reconstruction suggests L10 could represent a missing link in the evolutionary and geographic migration histories of M. africanum.

New reference genomes to distinguish the sympatric malaria parasites, Plasmodium ovale curtisi and Plasmodium ovale wallikeri.

Despite Plasmodium ovale curtisi (Poc) and wallikeri (Pow) being important human-infecting malaria parasites that are widespread across Africa and Asia, little is known about their genome diversity. Morphologically identical, Poc and Pow are indistinguishable and commonly misidentified. Recent rises in the incidence of Poc/Pow infections have renewed efforts to address fundamental knowledge gaps in their biology, and to develop diagnostic tools to understand their epidemiological dynamics and malaria burden. A major roadblock has been the incompleteness of available reference assemblies (PocGH01, PowCR01; ~ 33.5 Mbp). Here, we applied multiple sequencing platforms and advanced bioinformatics tools to generate new reference genomes, Poc221 (South Sudan; 36.0 Mbp) and Pow222 (Nigeria; 34.3 Mbp), with improved nuclear genome contiguity (> 4.2 Mbp), annotation and completeness (> 99% Plasmodium spp., single copy orthologs). Subsequent sequencing of 6 Poc and 15 Pow isolates from Africa revealed a total of 22,517 and 43,855 high-quality core genome SNPs, respectively. Genome-wide levels of nucleotide diversity were determined to be 2.98 × 10-4 (Poc) and 3.43 × 10-4 (Pow), comparable to estimates for other Plasmodium species. Overall, the new reference genomes provide a robust foundation for dissecting the biology of Poc/Pow, their population structure and evolution, and will contribute to uncovering the recombination barrier separating these species.

Rapid profiling of Plasmodium parasites from genome sequences to assist malaria control.

BACKGROUND: Malaria continues to be a major threat to global public health. Whole genome sequencing (WGS) of the underlying Plasmodium parasites has provided insights into the genomic epidemiology of malaria. Genome sequencing is rapidly gaining traction as a diagnostic and surveillance tool for clinical settings, where the profiling of co-infections, identification of imported malaria parasites, and detection of drug resistance are crucial for infection control and disease elimination. To support this informatically, we have developed the Malaria-Profiler tool, which rapidly (within minutes) predicts Plasmodium species, geographical source, and resistance to antimalarial drugs directly from WGS data. RESULTS: The online and command line versions of Malaria-Profiler detect ~ 250 markers from genome sequences covering Plasmodium speciation, likely geographical source, and resistance to chloroquine, sulfadoxine-pyrimethamine (SP), and other anti-malarial drugs for P. falciparum, but also providing mutations for orthologous resistance genes in other species. The predictive performance of the mutation library was assessed using 9321 clinical isolates with WGS and geographical data, with most being single-species infections (P. falciparum 7152/7462, P. vivax 1502/1661, P. knowlesi 143/151, P. malariae 18/18, P. ovale ssp. 5/5), but co-infections were identified (456/9321; 4.8%). The accuracy of the predicted geographical profiles was high to both continental (96.1%) and regional levels (94.6%). For P. falciparum, markers were identified for resistance to chloroquine (49.2%; regional range: 24.5% to 100%), sulfadoxine (83.3%; 35.4- 90.5%), pyrimethamine (85.4%; 80.0-100%) and combined SP (77.4%). Markers associated with the partial resistance of artemisinin were found in WGS from isolates sourced from Southeast Asia (30.6%). CONCLUSIONS: Malaria-Profiler is a user-friendly tool that can rapidly and accurately predict the geographical regional source and anti-malarial drug resistance profiles across large numbers of samples with WGS data. The software is flexible with modifiable bioinformatic pipelines. For example, it is possible to select the sequencing platform, display specific variants, and customise the format of outputs. With the increasing application of next-generation sequencing platforms on Plasmodium DNA, Malaria-Profiler has the potential to be integrated into point-of-care and surveillance settings, thereby assisting malaria control. Malaria-Profiler is available online (bioinformatics.lshtm.ac.uk/malaria-profiler) and as standalone software ( https://github.com/jodyphelan/malaria-profiler ).

Functional genetic variation in pe/ppe genes contributes to diversity in Mycobacterium tuberculosis lineages and potential interactions with the human host.

Introduction: Around 10% of the coding potential of Mycobacterium tuberculosisis constituted by two poorly understood gene families, the pe and ppe loci, thought to be involved in host-pathogen interactions. Their repetitive nature and high GC content have hindered sequence analysis, leading to exclusion from whole-genome studies. Understanding the genetic diversity of pe/ppe families is essential to facilitate their potential translation into tools for tuberculosis prevention and treatment. Methods: To investigate the genetic diversity of the 169 pe/ppe genes, we performed a sequence analysis across 73 long-read assemblies representing seven different lineages of M. tuberculosis and M. bovis BCG. Individual pe/ppe gene alignments were extracted and diversity and conservation across the different lineages studied. Results: The pe/ppe genes were classified into three groups based on the level of protein sequence conservation relative to H37Rv, finding that >50% were conserved, with indels in pe_pgrs and ppe_mptr sub-families being major drivers of structural variation. Gene rearrangements, such as duplications and gene fusions, were observed between pe and pe_pgrs genes. Inter-lineage diversity revealed lineage-specific SNPs and indels. Discussion: The high level of pe/ppe genes conservation, together with the lineage-specific findings, suggest their phylogenetic informativeness. However, structural variants and gene rearrangements differing from the reference were also identified, with potential implications for pathogenicity. Overall, improving our knowledge of these complex gene families may have insights into pathogenicity and inform the development of much-needed tools for tuberculosis control.

Detection of insecticide resistance markers in Anopheles funestus from the Democratic Republic of the Congo using a targeted amplicon sequencing panel.

Vector control strategies have been successful in reducing the number of malaria cases and deaths globally, but the spread of insecticide resistance represents a significant threat to disease control. Insecticide resistance has been reported across Anopheles (An.) vector populations, including species within the An. funestus group. These mosquitoes are responsible for intense malaria transmission across sub-Saharan Africa, including in the Democratic Republic of the Congo (DRC), a country contributing > 12% of global malaria infections and mortality events. To support the continuous efficacy of vector control strategies, it is essential to monitor insecticide resistance using molecular surveillance tools. In this study, we developed an amplicon sequencing ("Amp-seq") approach targeting An. funestus, and using multiplex PCR, dual index barcoding, and next-generation sequencing for high throughput and low-cost applications. Using our Amp-seq approach, we screened 80 An. funestus field isolates from the DRC across a panel of nine genes with mutations linked to insecticide resistance (ace-1, CYP6P4, CYP6P9a, GSTe2, vgsc, and rdl) and mosquito speciation (cox-1, mtND5, and ITS2). Amongst the 18 non-synonymous mutations detected, was N485I, in the ace-1 gene associated with carbamate resistance. Overall, our panel represents an extendable and much-needed method for the molecular surveillance of insecticide resistance in An. funestus populations.

Large-scale reference-free analysis of flavivirus sequences in Aedes aegypti whole genome DNA sequencing data.

Flaviviruses are a diverse group of RNA viruses, which include the etiological agents of Zika, dengue and yellow fever that are transmitted by mosquitoes. Flaviviruses do not encode reverse transcriptase and cannot reverse transcribe into DNA, yet DNA sequences of flaviviruses are found both integrated in the chromosomes of Aedes aegypti mosquitoes and as extrachromosomal sequences. We have previously examined the Ae. aegypti reference genome to identify flavivirus integrations and analyzed conservation of these sequences among whole-genome data of 464 Ae. aegypti collected across 10 countries globally. Here, we extended this analysis by identifying flavivirus sequences in these samples independently of the Ae. aegypti reference assembly. Our aim was to identify the complete set of viral sequences, including those absent in the reference genome, and their geographical distribution. We compared the identified sequences using BLASTn and applied machine learning methods to identify clusters of similar sequences. Apart from clusters of sequences that correspond to the four viral integration events that we had previously described, we identified 19 smaller clusters. The only cluster with a strong geographic association consisted of Cell-fusing agent virus-like sequences specific to Thailand. The remaining clusters did not have a geographic association and mostly consisted of near identical short sequences without strong similarity to any known flaviviral genomes. The short read sequencing data did not permit us to determine whether identified sequences were extrachromosomal or integrated into Ae. aegypti chromosomes. Our results suggest that Liverpool strain and field Ae. aegypti mosquitoes have a similar variety of conserved flaviviral DNA, whose functional role should be investigated in follow-up studies.

Genomic and functional portrait of multidrug-resistant, hydrogen sulfide (H2S)-producing variants of Escherichia coli.

Atypical Escherichia coli forms exhibit unusual characteristics compared to typical strains. The H2S-producing variants of some atypical E. coli strains cause a wide range of illnesses in humans and animals. However, there are sparse reports on such strains worldwide. We performed whole-genome sequencing (WGS) and detailed characterization of four H2S-producing E. coli variants from poultry and human clinical sources in Dhaka, Bangladesh. All four isolates were confirmed as E. coli using biochemical tests and genomic analysis, and were multidrug-resistant (MDR). WGS analysis including an additional Chinese strain, revealed diverse STs among the five H2S-producing E. coli genomes, with clonal complex ST10 being detected in 2 out of 5 genomes. The predominant phylogroup detected was group A (n = 4/5). The blaTEM1B (n = 5/5) was the most predominant extended-spectrum beta-lactamase (ESBL) gene, followed by different alleles of blaCTX-M (blaCTX-M -55,-65,-123; n = 3/5). Multiple plasmid replicons were detected, with IncX being the most common. One E. coli strain was classified as enteropathogenic E. coli. The genomes of all five isolates harbored five primary and four secondary function genes related to H2S production. These findings suggest the potential of these isolates to cause disease and spread antibiotic resistance. Therefore, such atypical E. coli forms should be included in differential diagnosis to understand the pathogenicity, antimicrobial resistance and evolution of H2S-producing E. coli.

Drug resistance profiling of asymptomatic and low-density Plasmodium falciparum malaria infections on Ngodhe island, Kenya, using custom dual-indexing next-generation sequencing.

Malaria control initiatives require rapid and reliable methods for the detection and monitoring of molecular markers associated with antimalarial drug resistance in Plasmodium falciparum parasites. Ngodhe island, Kenya, presents a unique malaria profile, with lower P. falciparum incidence rates than the surrounding region, and a high proportion of sub-microscopic and low-density infections. Here, using custom dual-indexing and Illumina next generation sequencing, we generate resistance profiles on seventy asymptomatic and low-density P. falciparum infections from a mass drug administration program implemented on Ngodhe island between 2015 and 2016. Our assay encompasses established molecular markers on the Pfcrt, Pfmdr1, Pfdhps, Pfdhfr, and Pfk13 genes. Resistance markers for sulfadoxine-pyrimethamine were identified at high frequencies, including a quintuple mutant haplotype (Pfdhfr/Pfdhps: N51I, C59R, S108N/A437G, K540E) identified in 62.2% of isolates. The Pfdhps K540E biomarker, used to inform decision making for intermittent preventative treatment in pregnancy, was identified in 79.2% of isolates. Several variants on Pfmdr1, associated with reduced susceptibility to quinolones and lumefantrine, were also identified (Y184F 47.1%; D1246Y 16.0%; N86 98%). Overall, we have presented a low-cost and extendable approach that can provide timely genetic profiles to inform clinical and surveillance activities, especially in settings with abundant low-density infections, seeking malaria elimination.

High throughput human genotyping for variants associated with malarial disease outcomes using custom targeted amplicon sequencing.

Malaria has exhibited the strongest known selective pressure on the human genome in recent history and is the evolutionary driving force behind genetic conditions, such as sickle-cell disease, glucose-6-phosphatase deficiency, and some other erythrocyte defects. Genomic studies (e.g., The 1000 Genomes project) have provided an invaluable baseline for human genetics, but with an estimated two thousand ethno-linguistic groups thought to exist across the African continent, our understanding of the genetic differences between indigenous populations and their implications on disease is still limited. Low-cost sequencing-based approaches make it possible to target specific molecular markers and genes of interest, leading to potential insights into genetic diversity. Here we demonstrate the versatility of custom dual-indexing technology and Illumina next generation sequencing to generate a genetic profile of human polymorphisms associated with malaria pathology. For 100 individuals diagnosed with severe malaria in Northeast Tanzania, variants were successfully characterised on the haemoglobin subunit beta (HBB), glucose-6-phosphate dehydrogenase (G6PD), atypical chemokine receptor 1 (ACKR1) genes, and the intergenic Dantu genetic blood variant, then validated using pre-existing genotyping data. High sequencing coverage was observed across all amplicon targets in HBB, G6PD, ACKR1, and the Dantu blood group, with variants identified at frequencies previously observed within this region of Tanzania. Sequencing data exhibited high concordance rates to pre-existing genotyping data (> 99.5%). Our work demonstrates the potential utility of amplicon sequencing for applications in human genetics, including to personalise medicine and understand the genetic diversity of loci linked to important host phenotypes, such as malaria susceptibility.

Feature weighted models to address lineage dependency in drug-resistance prediction from Mycobacterium tuberculosis genome sequences.

MOTIVATION: Tuberculosis (TB) is caused by members of the Mycobacterium tuberculosis complex (MTBC), which has a strain- or lineage-based clonal population structure. The evolution of drug-resistance in the MTBC poses a threat to successful treatment and eradication of TB. Machine learning approaches are being increasingly adopted to predict drug-resistance and characterize underlying mutations from whole genome sequences. However, such approaches may not generalize well in clinical practice due to confounding from the population structure of the MTBC. RESULTS: To investigate how population structure affects machine learning prediction, we compared three different approaches to reduce lineage dependency in random forest (RF) models, including stratification, feature selection, and feature weighted models. All RF models achieved moderate-high performance (area under the ROC curve range: 0.60-0.98). First-line drugs had higher performance than second-line drugs, but it varied depending on the lineages in the training dataset. Lineage-specific models generally had higher sensitivity than global models which may be underpinned by strain-specific drug-resistance mutations or sampling effects. The application of feature weights and feature selection approaches reduced lineage dependency in the model and had comparable performance to unweighted RF models. AVAILABILITY AND IMPLEMENTATION: https://github.com/NinaMercedes/RF_lineages.

Genome dynamics of high-risk resistant and hypervirulent Klebsiella pneumoniae clones in Dhaka, Bangladesh.

Klebsiella pneumoniae is recognized as an urgent public health threat because of the emergence of difficult-to-treat (DTR) strains and hypervirulent clones, resulting in infections with high morbidity and mortality rates. Despite its prominence, little is known about the genomic epidemiology of K. pneumoniae in resource-limited settings like Bangladesh. We sequenced genomes of 32 K. pneumoniae strains isolated from patient samples at the International Center for Diarrhoeal Disease Research, Bangladesh (icddr,b). Genome sequences were examined for their diversity, population structure, resistome, virulome, MLST, O and K antigens and plasmids. Our results revealed the presence of two K. pneumoniae phylogroups, namely KpI (K. pneumoniae) (97%) and KpII (K. quasipneumoniae) (3%). The genomic characterization revealed that 25% (8/32) of isolates were associated with high-risk multidrug-resistant clones, including ST11, ST14, ST15, ST307, ST231 and ST147. The virulome analysis confirmed the presence of six (19%) hypervirulent K. pneumoniae (hvKp) and 26 (81%) classical K. pneumoniae (cKp) strains. The most common ESBL gene identified was blaCTX-M-15 (50%). Around 9% (3/32) isolates exhibited a difficult-to-treat phenotype, harboring carbapenem resistance genes (2 strains harbored blaNDM-5 plus blaOXA-232, one isolate blaOXA-181). The most prevalent O antigen was O1 (56%). The capsular polysaccharides K2, K20, K16 and K62 were enriched in the K. pneumoniae population. This study suggests the circulation of the major international high-risk multidrug-resistant and hypervirulent (hvKp) K. pneumoniae clones in Dhaka, Bangladesh. These findings warrant immediate appropriate interventions, which would otherwise lead to a high burden of untreatable life-threatening infections locally.

Identification of two insecticide resistance markers in Ethiopian Anopheles stephensi mosquitoes using a multiplex amplicon sequencing assay.

Since its first detection in 2012 in Djibouti, Anopheles stephensi has invaded and established in the Horn of Africa, and more recently Nigeria. The expansion of this vector poses a significant threat to malaria control and elimination efforts. Integrated vector management is the primary strategy used to interrupt disease transmission; however, growing insecticide resistance is threatening to reverse gains in global malaria control. We present a next-generation amplicon-sequencing approach, for high-throughput monitoring of insecticide resistance genes (ace1, GSTe2, vgsc and rdl), species identification and characterization of genetic diversity (its2 and cox1) in An. stephensi. Ninety-five An. stephensi mosquitoes, collected in Ethiopia, were screened, identifying 104 SNPs, including the knock-down mutation L958F (L1014F in Musca domestica), and for the first time in this vector species, the A296S substitution (A301S in Drosophila melanogaster) in the rdl locus. Two other amino acid substitutions (ace1-N177D, GSTe2-V189L) were also identified but have not been previously implicated in insecticide resistance. Genetic diversity in the mitochondrial cox1 gene revealed shared haplotypes between Ethiopian An. stephensi with samples from Pakistan, Sudan, and Djibouti. Overall, we present a reliable, cost-effective strategy using amplicon-sequencing to monitor known insecticide resistance mutations, with the potential to identify new genetic variants, to assist in the high-throughput surveillance of insecticide resistance in An. stephensi populations.

TB-ML-a framework for comparing machine learning approaches to predict drug resistance of Mycobacterium tuberculosis.

Motivation: Machine learning (ML) has shown impressive performance in predicting antimicrobial resistance (AMR) from sequence data, including for Mycobacterium tuberculosis, the causative agent of tuberculosis. However, current ML development and publication practices make it difficult for researchers and clinicians to use, test or reproduce published models. Results: We packaged a number of published and unpublished ML models for predicting AMR of M.tuberculosis into Docker containers. Similarly, the pipelines required for pre-processing genomic data into the formats required by the models were also packaged into separate containers. By following a minimal container I/O standard, we ensured as much interoperability as possible. We also created a command-line application, TB-ML, which can be used to easily combine pre-processing and prediction containers into complete pipelines ready for predicting resistance from novel, raw data with a single command. As long as there is adherence to this minimal standard for the container interface, containers produced by researchers holding new models can likewise be included in these pipelines, making benchmark comparisons of different models simple and facilitating faster uptake in the clinic. Availability and implementation: TB-ML contains a simple Docker API written in Python and is available at https://github.com/jodyphelan/tb-ml. Example Docker containers for resistance prediction and corresponding data pre-processing as well as a tutorial on how to create new containers for TB-ML are available at https://tb-ml.github.io/tb-ml-containers/. Contact: jody.phelan@lshtm.ac.uk.

The Evolution and Transmission Dynamics of Multidrug-Resistant Tuberculosis in an Isolated High-Plateau Population of Tibet, China.

On the Tibetan Plateau, most tuberculosis is caused by indigenous Mycobacterium tuberculosis strains with a monophyletic structure and high-level drug resistance. This study investigated the emergence, evolution, and transmission dynamics of multidrug-resistant tuberculosis (MDR-TB) in Tibet. The whole-genome sequences of 576 clinical strains from Tibet were analyzed with the TB-profiler tool to identify drug-resistance mutations. The evolution of the drug resistance was then inferred based on maximum-likelihood phylogeny and dated trees that traced the serial acquisition of mutations conferring resistance to different drugs. Among the 576 clinical M. tuberculosis strains, 346 (60.1%) carried at least 1 resistance-conferring mutation and 231 (40.1%) were MDR-TB. Using a pairwise distance of 50 single nucleotide polymorphisms (SNPs), most strains (89.9%, 518/576) were phylogenetically separated into 50 long-term transmission clusters. Eleven large drug-resistant clusters contained 76.1% (176/231) of the local multidrug-resistant strains. A total of 85.2% of the isoniazid-resistant strains were highly transmitted with an average of 6.6 cases per cluster, of which most shared the mutation KatG Ser315Thr. A lower proportion (71.6%) of multidrug-resistant strains were transmitted, with an average cluster size of 2.9 cases. The isoniazid-resistant clusters appear to have undergone substantial bacterial population growth in the 1970s to 1990s and then subsequently accumulated multiple rifampicin-resistance mutations and caused the current local MDR-TB burden. These findings highlight the importance of detecting and curing isoniazid-resistant strains to prevent the emergence of endemic MDR-TB. IMPORTANCE Emerging isoniazid resistance in the 1970s allowed M. tuberculosis strains to spread and form into large multidrug-resistant tuberculosis clusters in the isolated plateau of Tibet, China. The epidemic was driven by the high risk of transmission as well as the potential of acquiring further drug resistance from isoniazid-resistant strains. Eleven large drug-resistant clusters consisted of the majority of local multidrug-resistant cases. Among the clusters, isoniazid resistance overwhelmingly evolved before all the other resistance types. A large bacterial population growth of isoniazid-resistant clusters occurred between 1970s and 1990s, which subsequently accumulated rifampicin-resistance-conferring mutations in parallel and accounted for the local multidrug-resistant tuberculosis burden. The results of our study indicate that it may be possible to restrict MDR-TB evolution and dissemination by prioritizing screening for isoniazid (INH)-resistant TB strains before they become MDR-TB and by adopting measures that can limit their transmission.

Emergence of KPC-3- and OXA-181-producing ST13 and ST17 Klebsiella pneumoniae in Portugal: genomic insights on national and international dissemination.

BACKGROUND: Carbapenem-resistant Klebsiella pneumoniae (CRKP) strains are of particular concern, especially strains with mobilizable carbapenemase genes such as blaKPC, blaNDM or blaOXA-48, given that carbapenems are usually the last line drugs in the ß-lactam class and, resistance to this sub-class is associated with increased mortality and frequently co-occurs with resistance to other antimicrobial classes. OBJECTIVES: To characterize the genomic diversity and international dissemination of CRKP strains from tertiary care hospitals in Lisbon, Portugal. METHODS: Twenty CRKP isolates obtained from different patients were subjected to WGS for species confirmation, typing, drug resistance gene detection and phylogenetic reconstruction. Two additional genomic datasets were included for comparative purposes: 26 isolates (ST13, ST17 and ST231) from our collection and 64 internationally available genomic assemblies (ST13). RESULTS: By imposing a 21 SNP cut-off on pairwise comparisons we identified two genomic clusters (GCs): ST13/GC1 (n = 11), all bearing blaKPC-3, and ST17/GC2 (n = 4) harbouring blaOXA-181 and blaCTX-M-15 genes. The inclusion of the additional datasets allowed the expansion of GC1/ST13/KPC-3 to 23 isolates, all exclusively from Portugal, France and the Netherlands. The phylogenetic tree reinforced the importance of the GC1/KPC-3-producing clones along with their rapid emergence and expansion across these countries. The data obtained suggest that the ST13 branch emerged over a decade ago and only more recently did it underpin a stronger pulse of transmission in the studied population. CONCLUSIONS: This study identifies an emerging OXA-181/ST17-producing strain in Portugal and highlights the ongoing international dissemination of a KPC-3/ST13-producing clone from Portugal.

Large-scale genomic analysis of Mycobacterium tuberculosis reveals extent of target and compensatory mutations linked to multi-drug resistant tuberculosis.

Resistance to isoniazid (INH) and rifampicin (RIF) first-line drugs in Mycobacterium tuberculosis (Mtb), together called multi-drug resistance, threatens tuberculosis control. Resistance mutations in katG (for INH) and rpoB (RIF) genes often come with fitness costs. To overcome these costs, Mtb compensatory mutations have arisen in rpoC/rpoA (RIF) and ahpC (INH) loci. By leveraging the presence of known compensatory mutations, we aimed to detect novel resistance mutations occurring in INH and RIF target genes. Across ~ 32 k Mtb isolates with whole genome sequencing (WGS) data, there were 6262 (35.7%) with INH and 5435 (30.7%) with RIF phenotypic resistance. Known mutations in katG and rpoB explained ~ 99% of resistance. However, 188 (0.6%) isolates had ahpC compensatory mutations with no known resistance mutations in katG, leading to the identification of 31 putative resistance mutations in katG, each observed in at least 3 isolates. These putative katG mutations can co-occur with other INH variants (e.g., katG-Ser315Thr, fabG1 mutations). For RIF, there were no isolates with rpoC/rpoA compensatory mutations and unknown resistance mutations. Overall, using WGS data we identified putative resistance markers for INH that could be used for genotypic drug-resistance profiling. Establishing the complete repertoire of Mtb resistance mutations will assist the clinical management of tuberculosis.

Genetic mutations underlying isoniazid-resistant Mycobacterium tuberculosis in Khyber Pakhtunkhwa, Pakistan.

Tuberculosis, caused by Mycobacterium tuberculosis, is a major public health issue in Pakistan. Isoniazid is a first-line pro-drug that requires activation through an enzyme called catalase peroxidase, but is subject to widespread resistance, driven by mutations in katG and inhA genes and other loci with compensatory effects (e.g., ahpC). Here, we used whole genome sequencing data from 51 M. tuberculosis isolates collected from Khyber Pakhtunkhwa province (years 2016-2019; all isoniazid phenotypically resistant) to investigate the genetic diversity of mutations in isoniazid candidate genes. The most common mutations underlying resistance were katG S315T (37/51), fabG1 -15C>T (13/51; inhA promoter), and inhA -154G>A (7/51). Other less common mutations (n < 5) were also identified in katG (R128Q, V1A, W505*, A109T, D311G) and candidate compensatory genes ahpC (-54C>T, -51G>A) and oxyS (M249T). Using DynaMut2 software, the mutants exhibited various degrees of stability and flexibility on protein structures, with some katG mutations leading to a decrease in KatG protein flexibility. Overall, the characterisation of circulating isoniazid resistant-linked mutations will assist in drug resistant TB management and control activities in a highly endemic area of Pakistan.

Genomic analysis of Salmonella enterica from Metropolitan Manila abattoirs and markets reveals insights into circulating virulence and antimicrobial resistance genotypes.

The integration of next-generation sequencing into the identification and characterization of resistant and virulent strains as well as the routine surveillance of foodborne pathogens such as Salmonella enterica have not yet been accomplished in the Philippines. This study investigated the antimicrobial profiles, virulence, and susceptibility of the 105 S. enterica isolates from swine and chicken samples obtained from slaughterhouses and public wet markets in Metropolitan Manila using whole-genome sequence analysis. Four predominant serovars were identified in genotypic serotyping, namely, Infantis (26.7%), Anatum (19.1%), Rissen (18.1%), and London (13.3%). Phenotypic antimicrobial resistance (AMR) profiling revealed that 65% of the isolates were resistant to at least one antibiotic, 37% were multidrug resistant (MDR), and 57% were extended-spectrum ß-lactamase producers. Bioinformatic analysis revealed that isolates had resistance genes and plasmids belonging to the Col and Inc plasmid families that confer resistance against tetracycline (64%), sulfonamide (56%), and streptomycin (56%). Further analyses revealed the presence of 155 virulence genes, 42 of which were serovar-specific. The virulence genes primarily code for host immune system modulators, iron acquisition enzyme complexes, host cell invasion proteins, as well as proteins that allow intracellular and intramacrophage survival. This study showed that virulent MDR S. enterica and several phenotypic and genotypic AMR patterns were present in the food chain. It serves as a foundation to understand the current AMR status in the Philippines food chain and to prompt the creation of preventative measures and efficient treatments against foodborne pathogens.

Deep learning-derived cardiovascular age shares a genetic basis with other cardiac phenotypes.

Artificial intelligence (AI)-based approaches can now use electrocardiograms (ECGs) to provide expert-level performance in detecting heart abnormalities and diagnosing disease. Additionally, patient age predicted from ECGs by AI models has shown great potential as a biomarker for cardiovascular age, where recent work has found its deviation from chronological age ("delta age") to be associated with mortality and co-morbidities. However, despite being crucial for understanding underlying individual risk, the genetic underpinning of delta age is unknown. In this work we performed a genome-wide association study using UK Biobank data (n=34,432) and identified eight loci associated with delta age ([Formula: see text]), including genes linked to cardiovascular disease (CVD) (e.g. SCN5A) and (heart) muscle development (e.g. TTN). Our results indicate that the genetic basis of cardiovascular ageing is predominantly determined by genes directly involved with the cardiovascular system rather than those connected to more general mechanisms of ageing. Our insights inform the epidemiology of CVD, with implications for preventative and precision medicine.