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.

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.

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.

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 β-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.

Genomic surveillance of Anopheles mosquitoes on the Bijagós Archipelago using custom targeted amplicon sequencing identifies mutations associated with insecticide resistance

BACKGROUND

Insecticide resistance is reducing the efficacy of vector control interventions, consequently threatening efforts to control vector-borne diseases, including malaria. Investigating the prevalence of molecular markers of resistance is a useful tool for monitoring the spread of insecticide resistance in disease vectors. The Bijagós Archipelago (Bijagós) in Guinea-Bissau is a region of stable malaria transmission where insecticide-treated nets are the mainstay for malaria control. However, the prevalence of molecular markers of insecticide resistance in malaria vectors is not well understood.

METHODS

A total of 214 Anopheles mosquitoes were analysed from 13 islands across the Bijagós. These mosquitoes were collected using CDC light traps in November 2019, during the peak malaria transmission season. High-throughput multiplex amplicon sequencing was used to investigate the prevalence of 17 different molecular markers associated with insecticide resistance in four genes: vgsc, rdl, ace1 and gste2.

RESULTS

Of the 17 screened mutations, four were identified in mosquitoes from the Bijagós: vgsc L995F (12.2%), N1570Y (6.2%) and A1746S (0.7%) and rdl A269G (1.1%). This study is the first to report the L995F knock-down resistance (kdr)-west allele in Anopheles melas on the Archipelago. An additional eight non-synonymous single-nucleotide polymorphisms were identified across the four genes which have not been described previously. The prevalences of the vgsc L995F and N1570Y mutations were higher on Bubaque Island than on the other islands in this study; Bubaque is the most populous island in the archipelago, with the greatest population mobility and connection to continental Guinea-Bissau.

CONCLUSIONS

This study provides the first surveillance data for genetic markers present in malaria vectors from islands across the Bijagós Archipelago. Overall prevalence of insecticide resistance mutations was found to be low. However, the identification of the vgsc L995F and N1570Y mutations associated with pyrethroid resistance warrants further monitoring. This is particularly important as the mainstay of malaria control on the islands is the use of pyrethroid insecticide-treated nets.

A computational method for predicting the most likely evolutionary trajectories in the stepwise accumulation of resistance mutations

Pathogen evolution of drug resistance often occurs in a stepwise manner via the accumulation of multiple mutations that in combination have a non-additive impact on fitness, a phenomenon known as epistasis. The evolution of resistance via the accumulation of point mutations in the DHFR genes of Plasmodium falciparum (Pf) and Plasmodium vivax (Pv) has been studied extensively and multiple studies have shown epistatic interactions between these mutations determine the accessible evolutionary trajectories to highly resistant multiple mutations. Here, we simulated these evolutionary trajectories using a model of molecular evolution, parameterised using Rosetta Flex ddG predictions, where selection acts to reduce the target-drug binding affinity. We observe strong agreement with pathways determined using experimentally measured IC50 values of pyrimethamine binding, which suggests binding affinity is strongly predictive of resistance and epistasis in binding affinity strongly influences the order of fixation of resistance mutations. We also infer pathways directly from the frequency of mutations found in isolate data, and observe remarkable agreement with the most likely pathways predicted by our mechanistic model, as well as those determined experimentally. This suggests mutation frequency data can be used to intuitively infer evolutionary pathways, provided sufficient sampling of the population.

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 ).

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.

Mixed infections in genotypic drug-resistant Mycobacterium tuberculosis

Tuberculosis disease (TB), caused by Mycobacterium tuberculosis, is a major global public health problem, resulting in more than 1 million deaths each year. Drug resistance (DR), including multi-drug (MDR-TB), is making TB control difficult and accounts for 16% of new and 48% of previously treated cases. To further complicate treatment decision-making, many clinical studies have reported patients harbouring multiple distinct strains of M. tuberculosis across the main lineages (L1 to L4). The extent to which drug-resistant strains can be deconvoluted within mixed strain infection samples is understudied. Here, we analysed M. tuberculosis isolates with whole genome sequencing data (n = 50,723), which covered the main lineages (L1 9.1%, L2 27.6%, L3 11.8%, L4 48.3%), with genotypic resistance to isoniazid (HR-TB; n = 9546 (29.2%)), rifampicin (RR-TB; n = 7974 (24.4%)), and at least MDR-TB (n = 5385 (16.5%)). TB-Profiler software revealed 531 (1.0%) isolates with potential mixed sub-lineage infections, including some with DR mutations (RR-TB 21/531; HR-TB 59/531; at least MDR-TB 173/531). To assist with the deconvolution of such mixtures, we adopted and evaluated a statistical Gaussian Mixture model (GMM) approach. By simulating 240 artificial mixtures of different ratios from empirical data across L1 to L4, a GMM approach was able to accurately estimate the DR profile of each lineage, with a low error rate for the estimated mixing proportions (mean squared error 0.012) and high accuracy for the DR predictions (93.5%). Application of the GMM model to the clinical mixtures (n = 531), found that 33.3% (188/531) of samples consisted of DR and sensitive lineages, 20.2% (114/531) consisted of lineages with only DR mutations, and 40.6% (229/531) consisted of lineages with genotypic pan-susceptibility. Overall, our work demonstrates the utility of combined whole genome sequencing data and GMM statistical analysis approaches for providing insights into mono and mixed M. tuberculosis infections, thereby potentially assisting diagnosis, treatment decision-making, drug resistance and transmission mapping for infection control.

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.

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.

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.

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.

Comparison of in silico predicted Mycobacterium tuberculosis spoligotypes and lineages from whole genome sequencing data

Bacterial strain-types in the Mycobacterium tuberculosis complex underlie tuberculosis disease, and have been associated with drug resistance, transmissibility, virulence, and host-pathogen interactions. Spoligotyping was developed as a molecular genotyping technique used to determine strain-types, though recent advances in whole genome sequencing (WGS) technology have led to their characterization using SNP-based sub-lineage nomenclature. Notwithstanding, spoligotyping remains an important tool and there is a need to study the congruence between spoligotyping-based and SNP-based sub-lineage assignation. To achieve this, an in silico spoligotype prediction method ("Spolpred2") was developed and integrated into TB-Profiler. Lineage and spoligotype predictions were generated for > 28 k isolates and the overlap between strain-types was characterized. Major spoligotype families detected were Beijing (25.6%), T (18.6%), LAM (13.1%), CAS (9.4%), and EAI (8.3%), and these broadly followed known geographic distributions. Most spoligotypes were perfectly correlated with the main MTBC lineages (L1-L7, plus animal). Conversely, at lower levels of the sub-lineage system, the relationship breaks down, with only 65% of spoligotypes being perfectly associated with a sub-lineage at the second or subsequent levels of the hierarchy. Our work supports the use of spoligotyping (membrane or WGS-based) for low-resolution surveillance, and WGS or SNP-based systems for higher-resolution studies.

Feature Weighted Models (FWM) 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 characterise underlying mutations from whole genome sequences. However, such approaches may not generalise 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 (AUC-ROC 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.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Case report: A successfully treated case of community-acquired urinary tract infection due to Klebsiella aerogenes in Bangladesh

Klebsiella aerogenes, a nosocomial pathogen, is increasingly associated with extensive drug resistance and virulence profiles. It is responsible for high morbidity and mortality. This report describes the first successfully treated case of community-acquired urinary tract infection (UTI) caused by Klebsiella aerogenes in an elderly housewife with Type-2 diabetes (T2D) from Dhaka, Bangladesh. The patient was empirically treated with intravenous ceftriaxone (500 mg/8 h). However, she did not respond to the treatment. The urine culture and sensitivity tests, coupled with bacterial whole-genome sequencing (WGS) and analysis, revealed the bacteria to be K. aerogenes which was extensively drug-resistant but was susceptible to carbapenems and polymyxins. Based on these findings, meropenem (500 mg/8 h) was administered to the patient, who then responded to the treatment and recovered successfully without having a relapse. This case raises awareness of the importance of diagnosis of not-so-common etiological agents, correct identification of the pathogens, and targeted antibiotic therapy. In conclusion, correctly identifying etiological agents of UTI using WGS approaches that are otherwise difficult to diagnose could help improve the identification of infectious agents and improve the management of infectious diseases.

Genome-wide genetic variation and molecular surveillance of drug resistance in Plasmodium falciparum isolates from asymptomatic individuals in Ouélessébougou, Mali

Sequence analysis of Plasmodium falciparum parasites is informative in ensuring sustained success of malaria control programmes. Whole-genome sequencing technologies provide insights into the epidemiology and genome-wide variation of P. falciparum populations and can characterise geographical as well as temporal changes. This is particularly important to monitor the emergence and spread of drug resistant P. falciparum parasites which is threatening malaria control programmes world-wide. Here, we provide a detailed characterisation of genome-wide genetic variation and drug resistance profiles in asymptomatic individuals in South-Western Mali, where malaria transmission is intense and seasonal, and case numbers have recently increased. Samples collected from Ouélessébougou, Mali (2019-2020; n = 87) were sequenced and placed in the context of older Malian (2007-2017; n = 876) and African-wide (n = 711) P. falciparum isolates. Our analysis revealed high multiclonality and low relatedness between isolates, in addition to increased frequencies of molecular markers for sulfadoxine-pyrimethamine and lumefantrine resistance, compared to older Malian isolates. Furthermore, 21 genes under selective pressure were identified, including a transmission-blocking vaccine candidate (pfCelTOS) and an erythrocyte invasion locus (pfdblmsp2). Overall, our work provides the most recent assessment of P. falciparum genetic diversity in Mali, a country with the second highest burden of malaria in West Africa, thereby informing malaria control activities.

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 bla_CTX-M-15 (50%). Around 9% (3/32) isolates exhibited a difficult-to-treat phenotype, harboring carbapenem resistance genes (2 strains harbored bla_NDM-5 plus bla_OXA-232, one isolate bla_OXA-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.

Population dynamics and drug resistance mutations in Plasmodium falciparum on the Bijagós Archipelago, Guinea-Bissau

Following integrated malaria control interventions, malaria burden on the Bijagós Archipelago has significantly decreased. Understanding the genomic diversity of circulating Plasmodium falciparum malaria parasites can assist infection control, through identifying drug resistance mutations and characterising the complexity of population structure. This study presents the first whole genome sequence data for P. falciparum isolates from the Bijagós Archipelago. Amplified DNA from P. falciparum isolates sourced from dried blood spot samples of 15 asymptomatic malaria cases were sequenced. Using 1.3 million SNPs characterised across 795 African P. falciparum isolates, population structure analyses revealed that isolates from the archipelago cluster with samples from mainland West Africa and appear closely related to mainland populations; without forming a separate phylogenetic cluster. This study characterises SNPs associated with antimalarial drug resistance on the archipelago. We observed fixation of the PfDHFR mutations N51I and S108N, associated with resistance to sulphadoxine-pyrimethamine, and the continued presence of PfCRT K76T, associated with chloroquine resistance. These data have relevance for infection control and drug resistance surveillance; particularly considering expected increases in antimalarial drug use following updated WHO recommendations, and the recent implementation of seasonal malaria chemoprevention and mass drug administration in the region.

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.

IFNγ, TNFα polymorphisms and IFNγ serum levels are associated with the clearance of drug-resistant P. falciparum in Malian children

Host immunity has been suggested to clear drug-resistant parasites in malaria-endemic settings. However, the immunogenetic mechanisms involved in parasite clearance are poorly understood. Characterizing the host's immunity and genes involved in controlling the parasitic infection can inform the development of blood-stage malaria vaccines. This study investigates host regulatory cytokines and immunogenomic factors associated with the clearance of Plasmodium falciparum carrying a chloroquine resistance genotype. Biological samples from participants of previous drug efficacy trials conducted in two Malian localities were retrieved. The P. falciparum chloroquine resistance transporter (Pfcrt) gene was genotyped using parasite DNA. Children carrying parasites with the mutant allele (Pfcrt-76T) were classified based on their ability to clear their parasites. The levels of the different cytokines were measured in serum. The polymorphisms of specific human genes involved in malaria susceptibility were genotyped using human DNA. The prevalence of the Pfcrt-76T was significantly higher in Kolle than in Bandiagara (81.6 % vs 38.6 %, p < 10^-6). The prevalence of children who cleared their mutant parasites was significantly higher in Bandiagara than in Kolle (82.2 % vs 67.4 %, p < 0.05). The genotyping of host genes revealed that IFN-γ -874 T and TNF-α -308A alleles were positively associated with parasite clearance. Cytokine profiling revealed that IFN-γ level was positively associated with parasite clearance (p = 0.04). This study highlights the role of host's immunity and immunogenetic factors to clear resistant parasites, suggesting further characterization of these polymorphisms may help to develop novel approaches to antiparasitic treatment strategies.

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 β-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.

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.

Risk factors for SARS-CoV-2 infection in primary and secondary school students and staff in England in the 2020/2021 school year: a longitudinal study

OBJECTIVES

Investigate risk factors for SARS-CoV-2 infections in school students and staff.

METHODS

In the 2020/2021 school year, we administered polymerase chain reaction, antibody tests, and questionnaires to a sample of primary and secondary school students and staff, with data linkage to COVID-19 surveillance. We fitted logistic regression models to identify the factors associated with infection.

RESULTS

We included 6799 students and 5090 staff in the autumn and 11,952 students and 4569 staff in the spring/summer terms. Infections in students in autumn 2020 were related to the percentage of students eligible for free school meals. We found no statistical association between infection risk in primary and secondary schools and reported contact patterns between students and staff in either period in our study. Using public transports was associated with increased risk in autumn in students (adjusted odds ratio = 1.72; 95% confidence interval 1.31-2.25) and staff. One or more infections in the same household during either period was the strongest risk factor for infection in students and more so among staff.

CONCLUSION

Deprivation, community, and household factors were more strongly associated with infection than contacts patterns at school; this suggests that the additional school-based mitigation measures in England in 2020/2021 likely helped reduce transmission risk in schools.

Towards environmental detection, quantification, and molecular characterization of Anopheles stephensi and Aedes aegypti from experimental larval breeding sites

The invasion and establishment of An. stephensi mosquitoes in the Horn of Africa represents a significant regional threat, which may jeopardise malaria control, particularly in urban areas which were formally free from disease transmission. Novel vector surveillance methods are urgently needed, both agnostic to mosquito larval morphology, and simple to implement at the sampling stage. Using new multiplex TaqMan assays, specifically targeting An. stephensi and Ae. aegypti, we validated the use of environmental DNA (eDNA) for simultaneous vector detection in shared artificial breeding sites. Study findings demonstrated that An. stephensi and Ae. aegypti eDNA deposited by as few as one second instar larva in 1L of water was detectable. Characterization of molecular insecticide resistance mechanisms, using novel amplicon-sequencing panels for both vector species, was possible from eDNA shed by as few as 16-32 s instar larvae in 50 ml of water. An. stephensi eDNA, derived from emergent pupae for 24 h, was remarkably stable, and still detectable ~ 2 weeks later. eDNA surveillance has the potential to be implemented in local endemic communities and at points of country entry, to monitor the spread of invasive vector species. Further studies are required to validate the feasibility of this technique under field conditions.

Population genetic analysis of Plasmodium knowlesi reveals differential selection and exchange events between Borneo and Peninsular sub-populations

The zoonotic Plasmodium knowlesi parasite is a growing public health concern in Southeast Asia, especially in Malaysia, where elimination of P. falciparum and P. vivax malaria has been the focus of control efforts. Understanding of the genetic diversity of P. knowlesi parasites can provide insights into its evolution, population structure, diagnostics, transmission dynamics, and the emergence of drug resistance. Previous work has revealed that P. knowlesi fall into three main sub-populations distinguished by a combination of geographical location and macaque host (Macaca fascicularis and M. nemestrina). It has been shown that Malaysian Borneo groups display profound heterogeneity with long regions of high or low divergence resulting in mosaic patterns between sub-populations, with some evidence of chromosomal-segment exchanges. However, the genetic structure of non-Borneo sub-populations is less clear. By gathering one of the largest collections of P. knowlesi whole-genome sequencing data, we studied structural genomic changes across sub-populations, with the analysis revealing differences in Borneo clusters linked to mosquito-related stages of the parasite cycle, in contrast to differences in host-related stages for the Peninsular group. Our work identifies new genetic exchange events, including introgressions between Malaysian Peninsular and M. nemestrina-associated clusters on various chromosomes, including in parasite invasion genes (DBP[Formula: see text], NBPX[Formula: see text] and NBPX[Formula: see text]), and important proteins expressed in the vertebrate parasite stages. Recombination events appear to have occurred between the Peninsular and M. fascicularis-associated groups, including in the DBP[Formula: see text] and DBP[Formula: see text] invasion associated genes. Overall, our work finds that genetic exchange events have occurred among the recognised contemporary groups of P. knowlesi parasites during their evolutionary history, leading to apparent mosaicism between these sub-populations. These findings generate new hypotheses relevant to parasite evolutionary biology and P. knowlesi epidemiology, which can inform malaria control approaches to containing the impact of zoonotic malaria on human communities.

Genome-wide host-pathogen analyses reveal genetic interaction points in tuberculosis disease

The genetics underlying tuberculosis (TB) pathophysiology are poorly understood. Human genome-wide association studies have failed so far to reveal reproducible susceptibility loci, attributed in part to the influence of the underlying Mycobacterium tuberculosis (Mtb) bacterial genotype on the outcome of the infection. Several studies have found associations of human genetic polymorphisms with Mtb phylo-lineages, but studies analysing genome-genome interactions are needed. By implementing a phylogenetic tree-based Mtb-to-human analysis for 714 TB patients from Thailand, we identify eight putative genetic interaction points (P < 5 × 10-8) including human loci DAP and RIMS3, both linked to the IFNγ cytokine and host immune system, as well as FSTL5, previously associated with susceptibility to TB. Many of the corresponding Mtb markers are lineage specific. The genome-to-genome analysis reveals a complex interactome picture, supports host-pathogen adaptation and co-evolution in TB, and has potential applications to large-scale studies across many TB endemic populations matched for host-pathogen genomic diversity.

Population-based genomic study of Plasmodium vivax malaria in seven Brazilian states and across South America

Background

Brazil is a unique and understudied setting for malaria, with complex foci of transmission associated with human and environmental conditions. An understanding of the population genomic diversity of P. vivax parasites across Brazil can support malaria control strategies.

Methods

Through whole genome sequencing of P. vivax isolates across 7 Brazilian states, we use population genomic approaches to compare genetic diversity within country (n = 123), continent (6 countries, n = 315) and globally (26 countries, n = 885).

Findings

We confirm that South American isolates are distinct, have more ancestral populations than the other global regions, with differentiating mutations in genes under selective pressure linked to antimalarial drugs (pvmdr1, pvdhfr-ts) and mosquito vectors (pvcrmp3, pvP45/48, pvP47). We demonstrate Brazil as a distinct parasite population, with signals of selection including ABC transporter (PvABCI3) and PHIST exported proteins.

Interpretation

Brazil has a complex population structure, with evidence of P. simium infections and Amazonian parasites separating into multiple clusters. Overall, our work provides the first Brazil-wide analysis of P. vivax population structure and identifies important mutations, which can inform future research and control measures.

Funding

AI is funded by an MRC LiD PhD studentship. TGC is funded by the Medical Research Council (Grant no. MR/M01360X/1, MR/N010469/1, MR/R025576/1, MR/R020973/1 and MR/X005895/1). SC is funded by Medical Research Council UK grants (MR/M01360X/1, MR/R025576/1, MR/R020973/1 and MR/X005895/1) and Bloomsbury SET (ref. CCF17-7779). FN is funded by The Shloklo Malaria Research Unit - part of the Mahidol Oxford Research Unit, supported by the Wellcome Trust (Grant no. 220211). ARSB is funded by São Paulo Research Foundation - FAPESP (Grant no. 2002/09546-1). RLDM is funded by Brazilian National Council for Scientific and Technological Development - CNPq (Grant no. 302353/2003-8 and 471605/2011-5); CRFM is funded by FAPESP (Grant no. 2020/06747-4) and CNPq (Grant no. 302917/2019-5 and 408636/2018-1); JGD is funded by FAPESP fellowships (2016/13465-0 and 2019/12068-5) and CNPq (Grant no. 409216/2018-6).

Large-scale genomic analysis of global Klebsiella pneumoniae plasmids reveals multiple simultaneous clusters of carbapenem-resistant hypervirulent strains

BACKGROUND

Klebsiella pneumoniae (Kp) Gram-negative bacteria cause nosocomial infections and rapidly acquire antimicrobial resistance (AMR), which makes it a global threat to human health. It also has a comparatively rare hypervirulent phenotype that can lead to severe disease in otherwise healthy individuals. Unlike classic Kp, canonical hypervirulent strains usually have limited AMR. However, after initial case reports in 2015, carbapenem-resistant hypervirulent Kp has increased in prevalence, including in China, but there is limited understanding of its burden  in other geographical regions.

METHODS

Here, we examined the largest collection of publicly available sequenced Kp isolates (n=13,178), containing 1603 different sequence types (e.g. ST11 15.0%, ST258 9.5%), and 2174 (16.5%) hypervirulent strains. We analysed the plasmid replicons and carbapenemase and siderophore encoding genes to understand the movement of hypervirulence and AMR genes located on plasmids, and their convergence in carbapenem-resistant hypervirulent Kp.

RESULTS

We identified and analysed 3034 unique plasmid replicons to inform the epidemiology and transmission dynamics of carbapenem-resistant hypervirulent Kp (n=1028, 7.8%). We found several outbreaks globally, including one involving ST11 strains in China and another of ST231 in Asia centred on India, Thailand, and Pakistan. There was evidence of global flow of Kp, including across multiple continents. In most cases, clusters of Kp isolates are the result of hypervirulence genes entering classic strains, instead of carbapenem resistance genes entering canonical hypervirulent ones.

CONCLUSIONS

Our analysis demonstrates the importance of plasmid analysis in the monitoring of carbapenem-resistant and hypervirulent strains of Kp. With the growing adoption of omics-based technologies for clinical and surveillance applications, including in geographical regions with gaps in data and knowledge (e.g. sub-Saharan Africa), the identification of the spread of AMR will inform infection control globally.

JC Polyomavirus T-antigen protein expression and the risk of colorectal cancer: Systematic review and meta-analysis of case-control studies

JC Polyomavirus (JCV) is a human polyomavirus encoding T-antigen protein, which is implicated in carcinogenesis. JCV is prevalent in the upper and lower gastrointestinal track. Several studies have reported JCV associations with the risk of developing colorectal cancer (CRC), however, these findings remain controversial. Since JCV DNA may be present in healthy tissues as well as transformed tissues, JCV T-antigen expression could be a more useful measure of JCV's association with cancer development. The aim of this study is to conduct a meta-analysis of case-control studies to investigate if there is a significant association between JCV T-antigen protein expression and risk of CRC. A systematic review was performed to identify studies reporting JCV DNA prevalence in CRC and JCV T-antigen expression. The strength of the association was estimated by odds ratios (ORs). Five (of 66) studies satisfied analysis inclusion criteria, and spanned years 1999 to 2022. Random effects meta-analysis of CRC cases versus controls showed an 11-fold increased risk of CRC development in JCV DNA positive samples with JCV T-antigen expression versus normal tissues (OR 10.95; 95% CI: 2.48-48.24; P = 0.0016). The results of this meta-analysis of JCV infection followed by JCV T-antigen protein expression for the risk of CRC support the argument that JCV infection significantly increases the risk of colorectal cancer in tissues where the JCV T-antigen protein is expressed. Further research with JCV T-antigen expression in relation to CRC development is needed.

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.

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.

A next generation targeted amplicon sequencing method to screen for insecticide resistance mutations in Aedes aegypti populations reveals a rdl mutation in mosquitoes from Cabo Verde

Aedes mosquito vectors transmit many viruses of global health concern, including dengue, chikungunya and Zika. These vector-borne viral diseases have a limited number of treatment options, and vaccines vary in their effectiveness. Consequently, integrated vector management is a primary strategy for disease control. However, the increasing emergence and spread of insecticide resistance is threatening the efficacy of vector control methods. Identifying mutations associated with resistance in vector populations is important to monitor the occurrence and evolution of insecticide resistance and inform control strategies. Rapid and cost-effective genome sequencing approaches are urgently needed. Here we present an adaptable targeted amplicon approach for cost-effective implementation within next generation sequencing platforms. This approach can identify single nucleotide polymorphisms (SNPs) and small insertions and deletions (indels) in genes involved in insecticide resistance in Aedes aegypti mosquitoes. We designed and tested eleven amplicons, which included segments of the ace-1 (carbamate target), the Voltage-Gated Sodium Channel (vgsc; pyrethroids, DDT and organochlorines), and rdl (dieldrin) genes; thereby covering established knockdown resistance (kdr) mutations (e.g., S989P, I1011M/V, V1016G/I and F1534C), with the potential to identify novel ones. The amplicon assays were designed with internal barcodes, to facilitate multiplexing of large numbers of mosquitoes at low cost, and were sequenced using an Illumina platform. Our approach was evaluated on 152 Ae. aegypti mosquitoes collected in Cabo Verde, an archipelago with a history of arbovirus outbreaks. The amplicon sequence data revealed 146 SNPs, including four non-synonymous polymorphisms in the vgsc gene, one in ace-1 and the 296S rdl mutation previously associated with resistance to organochlorines. The 296S rdl mutation was identified in 98% of mosquitoes screened, consistent with the past use of an organochlorine compound (e.g., DDT). Overall, our work shows that targeted amplicon sequencing is a rapid, robust, and cost-effective tool that can be used to perform high throughput monitoring of insecticide resistance.

Geographical classification of malaria parasites through applying machine learning to whole genome sequence data

Malaria, caused by Plasmodium parasites, is a major global health challenge. Whole genome sequencing (WGS) of Plasmodium falciparum and Plasmodium vivax genomes is providing insights into parasite genetic diversity, transmission patterns, and can inform decision making for clinical and surveillance purposes. Advances in sequencing technologies are helping to generate timely and big genomic datasets, with the prospect of applying Artificial Intelligence analytical techniques (e.g., machine learning) to support programmatic malaria control and elimination. Here, we assess the potential of applying deep learning convolutional neural network approaches to predict the geographic origin of infections (continents, countries, GPS locations) using WGS data of P. falciparum (n = 5957; 27 countries) and P. vivax (n = 659; 13 countries) isolates. Using identified high-quality genome-wide single nucleotide polymorphisms (SNPs) (P. falciparum: 750 k, P. vivax: 588 k), an analysis of population structure and ancestry revealed clustering at the country-level. When predicting locations for both species, classification (compared to regression) methods had the lowest distance errors, and > 90% accuracy at a country level. Our work demonstrates the utility of machine learning approaches for geo-classification of malaria parasites. With timelier WGS data generation across more malaria-affected regions, the performance of machine learning approaches for geo-classification will improve, thereby supporting disease control activities.

Non-lactose fermenting Escherichia coli: Following in the footsteps of lactose fermenting E. coli high-risk clones

Multi-resistant pathogenic strains of non-lactose fermenting Escherichia coli (NLF E. coli) are responsible for various intestinal and extraintestinal infections. Although several studies have characterised such strains using conventional methods, they have not been comprehensively studied at the genomic level. To address this gap, we used whole-genome sequencing (WGS) coupled with detailed microbiological and biochemical testing to investigate 17 NLF E. coli from a diagnostic centre (icddr,b) in Dhaka, Bangladesh. The prevalence of NLF E. coli was 10%, of which 47% (8/17) exhibited multi-drug resistant (MDR) phenotypes. All isolates (17/17) were confirmed as E. coli and could not ferment lactose sugar. WGS data analysis revealed international high-risk clonal lineages. The most prevalent sequence types (STs) were ST131 (23%), ST1193 (18%), ST12 (18%), ST501 (12%), ST167 (6%), ST73 (6%) and ST12 (6%). Phylogenetic analysis corroborated a striking clonal population amongst the studied NLF E. coli isolates. The predominant phylogroup detected was B2 (65%). The bla CTX-M-15 extended-spectrum beta-lactamase gene was present in 53% of isolates (9/17), whilst 64.7% (11/17) isolates were affiliated with pathogenic pathotypes. All extraintestinal pathogenic E. coli pathotypes demonstrated β-hemolysis. Our study underscores the presence of critical pathogens and MDR clones amongst non-lactose fermenting E. coli. We suggest that non-lactose fermenting E. coli be considered equally capable as lactose fermenting forms in causing intestinal and extraintestinal infections. Further, there is a need to undertake systematic, unbiased monitoring of predominant lineages amongst non-lactose fermenting E. coli that would help in better treatment and prevention strategies.

Epidemiology of SARS-CoV-2 infection among staff and students in a cohort of English primary and secondary schools during 2020-2021

Background

There remains uncertainty about the epidemiology of SARS-CoV-2 among school students and staff and the extent to which non-pharmaceutical-interventions reduce the risk of school settings.

Methods

We conducted an open cohort study in a sample of 59 primary and 97 secondary schools in 15 English local authority areas that were implementing government guidance to schools open during the pandemic. We estimated SARS-CoV-2 infection prevalence among those attending school, antibody prevalence, and antibody negative to positive conversion rates in staff and students over the school year (November 2020-July 2021).

Findings

22,585 staff and students participated. SARS-CoV-2 infection prevalence among those attending school was highest during the first two rounds of testing in the autumn term, ranging from 0.7% (95% CI 0.2, 1.2) among primary staff in November 2020 to 1.6% (95% CI 0.9, 2.3) among secondary staff in December 2020. Antibody conversion rates were highest in the autumn term. Infection patterns were similar between staff and students, and between primary and secondary schools. The prevalence of nucleoprotein antibodies increased over the year and was lower among students than staff. SARS-CoV-2 infection prevalence in the North-West region was lower among secondary students attending school on normal school days than the regional estimate for secondary school-age children.

Interpretation

SARS-CoV-2 infection prevalence in staff and students attending school varied with local community infection rates. Non-pharmaceutical interventions intended to prevent infected individuals attending school may have partially reduced the prevalence of infection among those on the school site.

Funding

UK Department of Health and Social Care.

Genomic surveillance of SARS-COV-2 reveals diverse circulating variant lineages in Nairobi and Kiambu Counties, Kenya

Genomic surveillance and identification of COVID-19 outbreaks are important in understanding the genetic diversity, phylogeny, and lineages of SARS-CoV-2. Genomic surveillance provides insights into circulating infections, and the robustness and design of vaccines and other infection control approaches. We sequenced 57 SARS-CoV-2 isolates from a Kenyan clinical population, of which 55 passed quality checks using the Ultrafast Sample placement on the Existing tRee (UShER) workflow. Phylo-genome-temporal analyses across two regions in Kenya (Nairobi and Kiambu County) revealed that B.1.1.7 (Alpha; n = 32, 56.1%) and B.1 (n = 9, 15.8%) were the predominant lineages, exhibiting low Ct values (5-31) suggesting high infectivity, and variant mutations across the two regions. Lineages B.1.617.2, B.1.1, A.23.1, A.2.5.1, B.1.596, A, and B.1.405 were also detected across sampling sites within target populations. The lineages and genetic isolates were traced back to China (A), Costa Rica (A.2.5.1), Europe (B.1, B.1.1, A.23.1), the USA (B.1.405, B.1.596), South Africa (B.1.617.2), and the United Kingdom (B.1.1.7), indicating multiple introduction events. This study represents one of the genomic SARS-CoV-2 epidemiology studies in the Nairobi metropolitan area, and describes the importance of continued surveillance for pandemic control.

High-throughput barcoding method for the genetic surveillance of insecticide resistance and species identification in Anopheles gambiae complex malaria vectors

Surveillance of malaria vector species and the monitoring of insecticide resistance are essential to inform malaria control strategies and support the reduction of infections and disease. Genetic barcoding of mosquitoes is a useful tool to assist the high-throughput surveillance of insecticide resistance, discriminate between sibling species and to detect the presence of Plasmodium infections. In this study, we combined multiplex PCR, custom designed dual indexing, and Illumina next generation sequencing for high throughput single nucleotide polymorphism (SNP)-profiling of four species from the Anopheles (An.) gambiae complex (An. gambiae sensu stricto, An. coluzzii, An. arabiensis and An. melas). By amplifying and sequencing only 14 genetic fragments (500 bp each), we were able to simultaneously detect Plasmodium infection; insecticide resistance-conferring SNPs in ace1, gste2, vgsc and rdl genes; the partial sequences of nuclear ribosomal internal transcribed spacers (ITS1 and ITS2) and intergenic spacers (IGS), Short INterspersed Elements (SINE), as well as mitochondrial genes (cox1 and nd4) for species identification and genetic diversity. Using this amplicon sequencing approach with the four selected An. gambiae complex species, we identified a total of 15 non-synonymous mutations in the insecticide target genes, including previously described mutations associated with resistance and two new mutations (F1525L in vgsc and D148E in gste2). Overall, we present a reliable and cost-effective high-throughput panel for surveillance of An. gambiae complex mosquitoes in malaria endemic regions.

Genomic analysis of hypervirulent Klebsiella pneumoniae reveals potential genetic markers for differentiation from classical strains

The majority of Klebsiella pneumoniae (Kp) infections are nosocomial, but a growing number of community-acquired infections are caused by hypervirulent strains (hvKp) characterised by liver invasion and rapid metastasis. Unlike nosocomial Kp infections, hvKp are generally susceptible to antibiotics. Due to the rapid progression of hvKp infections, timely and accurate diagnosis is required for effective treatment. To identify potential drivers of the hypervirulent phenotype, we performed a genome-wide association study (GWAS) analysis on single nucleotide variants and accessory genome loci across 79 publicly available Kp isolates collected from patients’ liver and a diverse global Kp dataset (n = 646). The GWAS analysis revealed 29 putative genes (P < 10^–10) associated with higher risk of liver phenotype, including hypervirulence linked salmochelin iro (odds ratio (OR): 29.8) and aerobactin iuc (OR: 14.1) loci. A minority of liver isolates (n = 15, 19%) had neither of these siderophores nor any other shared biomarker, suggesting possible unknown drivers of hypervirulence and an intrinsic ability of Kp to invade the liver. Despite identifying potential novel loci linked to a liver invasive Kp phenotype, our work highlights the need for large-scale studies involving more sequence types to identify further hypervirulence biomarkers to assist clinical decision making.

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.

Sero-epidemiological study of arbovirus infection following the 2015-2016 Zika virus outbreak in Cabo Verde

In November 2015, cases of Zika virus infection were recorded in Cabo Verde (Africa), originating from Brazil. The outbreak subsided after seven months with 7580 suspected cases. We performed a serological survey (n = 431) in Praia, the capital city, 3 months after transmission ceased. Serum samples were screened for arbovirus antibodies using ELISA techniques and revealed seroconverted individuals with Zika (10.9%), dengue (1-4) (12.5%), yellow fever (0.2%) and chikungunya (2.6%) infections. Zika seropositivity was predominantly observed amongst females (70%). Using a logistic model, risk factors for increased odds of Zika seropositivity included age, self-reported Zika infection, and dengue seropositivity. Serological data from Zika and dengue virus assays were strongly correlated (Spearman's r_s = 0.80), which reduced when using a double antigen binding ELISA (Spearman's r_s = 0.54). Overall, our work improves an understanding of how Zika and other arboviruses have spread throughout the Cabo Verde population. It also demonstrates the utility of serological assay formats for outbreak investigations.

High clustering rate and genotypic drug-susceptibility screening for the newly recommended anti-tuberculosis drugs among global extensively drug-resistant Mycobacterium tuberculosis isolates

Multidrug-resistant tuberculosis (MDR-TB) and extensively drug-resistant tuberculosis (XDR-TB) make TB difficult to control. Global susceptibility data for six newly recommended anti-TB drugs against M/XDR-TB are still limited. Using publicly available whole-genome sequences, we determined the proportion of 513 phenotypically XDR-TB isolates that carried mutations associated with resistance against these drugs (bedaquiline, clofazimine, linezolid, delamanid, pretomanid and cycloserine). Mutations of Rv0678 and Rv1979c were detected in 69/513 isolates (13.5%) for bedaquiline resistance and 79/513 isolates (15.4%) for clofazimine resistance with additional mmpL5 mutations. Mutations conferring resistance to delamanid were detected in fbiB and ddn genes for 11/513 isolates (2.1%). For pretomanid, a mutation was detected in the ddn gene for 3/513 isolates (0.6%). Nineteen mutations of pykA, cycA, ald, and alr genes, conferring resistance to cycloserine, were found in 153/513 isolates (29.8%). No known mutations associated with linezolid resistance were detected. Cluster analysis showed that 408/513 isolates fell within 99 clusters and that 354 of these isolates were possible primary drug-resistant TB (292 XDR-TB, 57 pre-XDR-TB and 5 MDR-TB). Clonal transmission of primary XDR isolates might contribute significantly to the high prevalence of DR-TB globally.

How has mass drug administration with dihydroartemisinin-piperaquine impacted molecular markers of drug resistance? A systematic review

The World Health Organization (WHO) recommends surveillance of molecular markers of resistance to anti-malarial drugs. This is particularly important in the case of mass drug administration (MDA), which is endorsed by the WHO in some settings to combat malaria. Dihydroartemisinin-piperaquine (DHA-PPQ) is an artemisinin-based combination therapy which has been used in MDA. This review analyses the impact of MDA with DHA-PPQ on the evolution of molecular markers of drug resistance. The review is split into two parts. Section I reviews the current evidence for different molecular markers of resistance to DHA-PPQ. This includes an overview of the prevalence of these molecular markers in Plasmodium falciparum Whole Genome Sequence data from the MalariaGEN Pf3k project. Section II is a systematic literature review of the impact that MDA with DHA-PPQ has had on the evolution of molecular markers of resistance. This systematic review followed PRISMA guidelines. This review found that despite being a recognised surveillance tool by the WHO, the surveillance of molecular markers of resistance following MDA with DHA-PPQ was not commonly performed. Of the total 96 papers screened for eligibility in this review, only 20 analysed molecular markers of drug resistance. The molecular markers published were also not standardized. Overall, this warrants greater reporting of molecular marker prevalence following MDA implementation. This should include putative pfcrt mutations which have been found to convey resistance to DHA-PPQ in vitro.

PowerBacGWAS: a computational pipeline to perform power calculations for bacterial genome-wide association studies

Genome-wide association studies (GWAS) are increasingly being applied to investigate the genetic basis of bacterial traits. However, approaches to perform power calculations for bacterial GWAS are limited. Here we implemented two alternative approaches to conduct power calculations using existing collections of bacterial genomes. First, a sub-sampling approach was undertaken to reduce the allele frequency and effect size of a known and detectable genotype-phenotype relationship by modifying phenotype labels. Second, a phenotype-simulation approach was conducted to simulate phenotypes from existing genetic variants. We implemented both approaches into a computational pipeline (PowerBacGWAS) that supports power calculations for burden testing, pan-genome and variant GWAS; and applied it to collections of Enterococcus faecium, Klebsiella pneumoniae and Mycobacterium tuberculosis. We used this pipeline to determine sample sizes required to detect causal variants of different minor allele frequencies (MAF), effect sizes and phenotype heritability, and studied the effect of homoplasy and population diversity on the power to detect causal variants. Our pipeline and user documentation are made available and can be applied to other bacterial populations. PowerBacGWAS can be used to determine sample sizes required to find statistically significant associations, or the associations detectable with a given sample size. We recommend to perform power calculations using existing genomes of the bacterial species and population of study.

A Natural History of Disease Framework for Improving the Prevention, Management, and Research on Post-viral Fatigue Syndrome and Other Forms of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome

We propose a framework for the treatment, rehabilitation, and research into Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) using a natural history of disease approach to outline the distinct disease stages, with an emphasis on cases following infection to provide insights into prevention. Moving away from the method of subtyping patients based on the various phenotypic presentations and instead reframing along the lines of disease progression could help with defining the distinct stages of disease, each of which would benefit from large prospective cohort studies to accurately describe the pathological mechanisms taking place therein. With a better understanding of these mechanisms, management and research can be tailored specifically for each disease stage. Pre-disease and early disease stages call for management strategies that may decrease the risk of long-term morbidity, by focusing on avoidance of further insults, adequate rest to enable recovery, and pacing of activities. Later disease stages require a more holistic and tailored management approach, with treatment-as this becomes available-targeting the alleviation of symptoms and multi-systemic dysfunction. More stringent and standardised use of case definitions in research is critical to improve generalisability of results and to create the strong evidence-based policies for management that are currently lacking in ME/CFS.

A modified decision tree approach to improve the prediction and mutation discovery for drug resistance in Mycobacterium tuberculosis

BACKGROUND

Drug resistant Mycobacterium tuberculosis is complicating the effective treatment and control of tuberculosis disease (TB). With the adoption of whole genome sequencing as a diagnostic tool, machine learning approaches are being employed to predict M. tuberculosis resistance and identify underlying genetic mutations. However, machine learning approaches can overfit and fail to identify causal mutations if they are applied out of the box and not adapted to the disease-specific context. We introduce a machine learning approach that is customized to the TB setting, which extracts a library of genomic variants re-occurring across individual studies to improve genotypic profiling.

RESULTS

We developed a customized decision tree approach, called Treesist-TB, that performs TB drug resistance prediction by extracting and evaluating genomic variants across multiple studies. The application of Treesist-TB to rifampicin (RIF), isoniazid (INH) and ethambutol (EMB) drugs, for which resistance mutations are known, demonstrated a level of predictive accuracy similar to the widely used TB-Profiler tool (Treesist-TB vs. TB-Profiler tool: RIF 97.5% vs. 97.6%; INH 96.8% vs. 96.5%; EMB 96.8% vs. 95.8%). Application of Treesist-TB to less understood second-line drugs of interest, ethionamide (ETH), cycloserine (CYS) and para-aminosalisylic acid (PAS), led to the identification of new variants (52, 6 and 11, respectively), with a high number absent from the TB-Profiler library (45, 4, and 6, respectively). Thereby, Treesist-TB had improved predictive sensitivity (Treesist-TB vs. TB-Profiler tool: PAS 64.3% vs. 38.8%; CYS 45.3% vs. 30.7%; ETH 72.1% vs. 71.1%).

CONCLUSION

Our work reinforces the utility of machine learning for drug resistance prediction, while highlighting the need to customize approaches to the disease-specific context. Through applying a modified decision learning approach (Treesist-TB) across a range of anti-TB drugs, we identified plausible resistance-encoding genomic variants with high predictive ability, whilst potentially overcoming the overfitting challenges that can affect standard machine learning applications.