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Mosquitoes of the genus Aedes are the main vectors of many viruses, e.g. dengue and Zika, which affect millions of people each year and for which there are limited treatment options. Understanding how Aedes mosquitoes tolerate high viral loads may lead to better disease control strategies. Elucidating endogenous viral elements (EVEs) within vector genomes may give exploitable biological insights. Previous studies have reported the presence of a large number of EVEs in Aedes genomes. Here we investigated if flavivirus EVEs are conserved across populations and different Aedes species by using ~ 500 whole genome sequence libraries from Aedes aegypti and Aedes albopictus, sourced from colonies and field mosquitoes across continents. We found that nearly all flavivirus EVEs in the Ae. aegypti reference genome originate from four separate putative viral integration events, and that they are highly conserved across geographically diverse samples. By contrast, flavivirus EVEs in the Ae. albopictus reference genome originate from up to nine distinct integration events and show low levels of conservation, even within samples from narrow geographical ranges. Our analysis suggests that flaviviruses integrated as long sequences and were subsequently fragmented and shuffled by transposable elements. Given that EVEs of Ae. aegypti and Ae. albopictus belong to different phylogenetic clades and have very differing levels of conservation, they may have different evolutionary origins and potentially different functional roles. Graphical Abstract

Multidrug-resistant tuberculosis (MDR TB), pre-extensively drug-resistant tuberculosis (pre-XDR TB), and extensively drug-resistant tuberculosis (XDR TB) complicate disease control. We analyzed whole-genome sequence data for 579 phenotypically drug-resistant M. tuberculosis isolates (28% of available MDR/pre-XDR and all culturable XDR TB isolates collected in Thailand during 2014-2017). Most isolates were from lineage 2 (n = 482; 83.2%). Cluster analysis revealed that 281/579 isolates (48.5%) formed 89 clusters, including 205 MDR TB, 46 pre-XDR TB, 19 XDR TB, and 11 poly-drug-resistant TB isolates based on genotypic drug resistance. Members of most clusters had the same subset of drug resistance-associated mutations, supporting potential primary resistance in MDR TB (n = 176/205; 85.9%), pre-XDR TB (n = 29/46; 63.0%), and XDR TB (n = 14/19; 73.7%). Thirteen major clades were significantly associated with geography (p

Antimicrobials against bacterial, viral and parasitic pathogens have transformed human and animal health. Nevertheless, their widespread use (and misuse) has led to the emergence of antimicrobial resistance (AMR) which poses a potentially catastrophic threat to public health and animal husbandry. There are several routes, both intrinsic and acquired, by which AMR can develop. One major route is through non-synonymous single nucleotide polymorphisms (nsSNPs) in coding regions. Large scale genomic studies using high-throughput sequencing data have provided powerful new ways to rapidly detect and respond to such genetic mutations linked to AMR. However, these studies are limited in their mechanistic insight. Computational tools can rapidly and inexpensively evaluate the effect of mutations on protein function and evolution. Subsequent insights can then inform experimental studies, and direct existing or new computational methods. Here we review a range of sequence and structure-based computational tools, focussing on tools successfully used to investigate mutational effect on drug targets in clinically important pathogens, particularly Mycobacterium tuberculosis. Combining genomic results with the biophysical effects of mutations can help reveal the molecular basis and consequences of resistance development. Furthermore, we summarise how the application of such a mechanistic understanding of drug resistance can be applied to limit the impact of AMR.

Tuberculosis disease (TB), caused by Mycobacterium tuberculosis, is a major public health issue in Thailand. The high prevalence of modern Beijing (Lineage 2.2.1) strains has been associated with multi- and extensively drug-resistant infections (MDR-, XDR-TB), complicating disease control. The impact of rarer proto-Beijing (L2.1) strains is less clear. In our study of thirty-seven L2.1 clinical isolates spanning thirteen years, we found a high prevalence of XDR-TB cases (32.4%). With ≤ 12 pairwise SNP distances, 43.2% of L2.1 patients belong to MDR-TB or XDR-TB transmission clusters suggesting a high level of clonal expansion across four Thai provinces. All XDR-TB (100%) were likely due to transmission rather than inadequate treatment. We found a 47 mutation signature and a partial deletion of the fadD14 gene in the circulating XDR-TB cluster, which can be used for surveillance of this rare and resilient M. tuberculosis strain-type that is causing increasing health burden. We also detected three novel deletion positions, a deletion of 1285 bp within desA3 (Rv3230c), large deletions in the plcB, plcA, and ppe38 gene which may play a role in the virulence, pathogenesis or evolution of the L2.1 strain-type.

Resistance to drugs used to treat tuberculosis disease (TB) continues to remain a public health burden, with missense point mutations in the underlying Mycobacterium tuberculosis bacteria described for nearly all anti-TB drugs. The post-genomics era along with advances in computational and structural biology provide opportunities to understand the interrelationships between the genetic basis and the structural consequences of M. tuberculosis mutations linked to drug resistance. Pyrazinamide (PZA) is a crucial first line antibiotic currently used in TB treatment regimens. The mutational promiscuity exhibited by the pncA gene (target for PZA) necessitates computational approaches to investigate the genetic and structural basis for PZA resistance development. We analysed 424 missense point mutations linked to PZA resistance derived from ∼35K M. tuberculosis clinical isolates sourced globally, which comprised the four main M. tuberculosis lineages (Lineage 1–4). Mutations were annotated to reflect their association with PZA resistance. Genomic measures (minor allele frequency and odds ratio), structural features (surface area, residue depth and hydrophobicity) and biophysical effects (change in stability and ligand affinity) of point mutations on pncA protein stability and ligand affinity were assessed. Missense point mutations within pncA were distributed throughout the gene, with the majority (>80%) of mutations with a destabilising effect on protomer stability and on ligand affinity. Active site residues involved in PZA binding were associated with multiple point mutations highlighting mutational diversity due to selection pressures at these functionally important sites. There were weak associations between genomic measures and biophysical effect of mutations. However, mutations associated with PZA resistance showed statistically significant differences between structural features (surface area and residue depth), but not hydrophobicity score for mutational sites. Most interestingly M. tuberculosis lineage 1 (ancient lineage) exhibited a distinct protein stability profile for mutations associated with PZA resistance, compared to modern lineages.

Funder: UK National Measurement System, Funder: NIHR BRC and NIHR Policy Research Programme (NIBSC Regulatory Science Research Unit), Funder: National Institute of Health Research (NIHR) Imperial Biomedical Research Centre (BRC), Funder: EMBL core funds, Funder: Quadram Institute Bioscience BBSRC Strategic Programme: Microbes in the Food Chain; Grant(s): BB/R012504/1) and its constituent projects BBS/E/F/000PR10348 and BBS/E/F/000PR10349, Despite the advent of whole genome metagenomics, targeted approaches (such as 16S rRNA gene amplicon sequencing) continue to be valuable for determining the microbial composition of samples. Amplicon microbiome sequencing can be performed on clinical samples from a normally sterile site to determine the aetiology of an infection (usually single pathogen identification) or samples from more complex niches such as human mucosa or environmental samples where multiple microorganisms need to be identified. The methodologies are frequently applied to determine both presence of micro-organisms and their quantity or relative abundance. There are a number of technical steps required to perform microbial community profiling, many of which may have appreciable precision and bias that impacts final results. In order for these methods to be applied with the greatest accuracy, comparative studies across different laboratories are warranted. In this study we explored the impact of the bioinformatic approaches taken in different laboratories on microbiome assessment using 16S rRNA gene amplicon sequencing results. Data were generated from two mock microbial community samples which were amplified using primer sets spanning five different variable regions of 16S rRNA genes. The PCR-sequencing analysis included three technical repeats of the process to determine the repeatability of their methods. Thirteen laboratories participated in the study, and each analysed the same FASTQ files using their choice of pipeline. This study captured the methods used and the resulting sequence annotation and relative abundance output from bioinformatic analyses. Results were compared to digital PCR assessment of the absolute abundance of each target representing each organism in the mock microbial community samples and also to analyses of shotgun metagenome sequence data. This ring trial demonstrates that the choice of bioinformatic analysis pipeline alone can result in different estimations of the composition of the microbiome when using 16S rRNA gene amplicon sequencing data. The study observed differences in terms of both presence and abundance of organisms and provides a resource for ensuring reproducible pipeline development and application. The observed differences were especially prevalent when using custom databases and applying high stringency operational taxonomic unit (OTU) cut-off limits. In order to apply sequencing approaches with greater accuracy, the impact of different analytical steps needs to be clearly delineated and solutions devised to harmonise microbiome analysis results.

BackgroundThe COVID-19 pandemic, caused by the SARS-CoV-2 virus, has a major global health and socio-economic burden. It has instigated the mobilisation of resources into the development of control tools, such as diagnostics and vaccines. The poor performance of some diagnostic serological tools has emphasised the need for up to date immune-informatic analyses to inform the selection of viable targets for further study. This requires the integration and analysis of genetic and immunological data for SARS-CoV-2 and its homology with other human coronavirus species to understand cross-reactivity.MethodsWe have developed an online “immuno-analytics” resource to facilitate SARS-CoV-2 research, combining an extensive B/T-cell epitope mapping and prediction meta-analysis, and human CoV sequence homology mapping and protein database annotation, with an updated variant database and geospatial tracking for >7,800 non-synonymous mutation positions derived from >150,000 whole genome sequences. To demonstrate its utility, we present an integrated analysis of SARS-CoV-2 spike and nucleocapsid proteins, both being vaccine and serological diagnostic targets, including an analysis of changes in relevant mutation frequencies over time.ResultsOur analysis reveals that the nucleocapsid protein in its native form appears to be a sub-optimal target for use in serological diagnostic platforms. The most frequent mutations were the spike protein D614G and nsp12 L314P, which were common (>86%) across all the geographical regions. Some mutations in the spike protein (e.g. A222V and L18F) have increased in frequency in Europe during the latter half of 2020, detected using our automated algorithms. The tool also suggests that orf3a proteins may be a suitable alternative target for diagnostic serologic assays in a post-vaccine surveillance setting.ConclusionsThe immuno-analytics tool can be accessed online (http://genomics.lshtm.ac.uk/immuno) and will serve as a useful resource for biological discovery and surveillance in the fight against SARS-CoV-2. Further, the tool may be adapted to inform on biological targets in future outbreaks, including potential emerging human coronaviruses that spill over from animal hosts.

Background Malaria, caused by Plasmodium parasites, is a major global public health problem. To assist an understanding of malaria pathogenesis, including drug resistance, there is a need for the timely detection of underlying genetic mutations and their spread. With the increasing use of whole-genome sequencing (WGS) of Plasmodium DNA, the potential of deep learning models to detect loci under recent positive selection, historically signals of drug resistance, was evaluated. Methods A deep learning-based approach (called “DeepSweep”) was developed, which can be trained on haplotypic images from genetic regions with known sweeps, to identify loci under positive selection. DeepSweep software is available from https://github.com/WDee/Deepsweep. Results Using simulated genomic data, DeepSweep could detect recent sweeps with high predictive accuracy (areas under ROC curve > 0.95). DeepSweep was applied to Plasmodium falciparum (n = 1125; genome size 23 Mbp) and Plasmodium vivax (n = 368; genome size 29 Mbp) WGS data, and the genes identified overlapped with two established extended haplotype homozygosity methods (within-population iHS, across-population Rsb) (~ 60–75% overlap of hits at P DeepSweep hits included regions proximal to known drug resistance loci for both P. falciparum (e.g. pfcrt, pfdhps and pfmdr1) and P. vivax (e.g. pvmrp1). Conclusion The deep learning approach can detect positive selection signatures in malaria parasite WGS data. Further, as the approach is generalizable, it may be trained to detect other types of selection. With the ability to rapidly generate WGS data at low cost, machine learning approaches (e.g. DeepSweep) have the potential to assist parasite genome-based surveillance and inform malaria control decision-making.

The evolutionary epidemiology, resistome, virulome and mobilome of thirty-one multidrug resistant Klebsiella pneumoniae clinical isolates from the northern Vila Real region of Portugal were characterized using whole-genome sequencing and bioinformatic analysis. The genomic population structure was dominated by two main sequence types (STs): ST147 (n = 17, 54.8%) and ST15 (n = 6, 19.4%) comprising four distinct genomic clusters. Two main carbapenemase coding genes were detected (blaKPC-3 and blaOXA-48) along with additional extended-spectrum &beta, lactamase coding loci (blaCTX-M-15, blaSHV-12, blaSHV-27, and blaSHV-187). Moreover, whole genome sequencing enabled the identification of one Klebsiella variicola KPC-3 producer isolate previously misidentified as K. pneumoniae, which in addition to the blaKPC-3 carbapenemase gene, bore the chromosomal broad spectrum &beta, lactamase blaLEN-2 coding gene, oqxAB and fosA resistance loci. The blaKPC-3 genes were located in a Tn4401b transposon (K. variicolan = 1, K. pneumoniaen = 2) and Tn4401d isoform (K. pneumoniaen = 28). Overall, our work describes the first report of a blaKPC-3 producing K. variicola, as well as the detection of this species during infection control measures in surveillance cultures from infected patients. It also highlights the importance of additional control measures to overcome the clonal dissemination of carbapenemase producing clones.

Tuberculosis disease is a major global public health concern and the growing prevalence of drug-resistant Mycobacterium tuberculosis is making disease control more difficult. However, the increasing application of whole-genome sequencing as a diagnostic tool is leading to the profiling of drug resistance to inform clinical practice and treatment decision making. Computational approaches for identifying established and novel resistance-conferring mutations in genomic data include genome-wide association study (GWAS) methodologies, tests for convergent evolution and machine learning techniques. These methods may be confounded by extensive co-occurrent resistance, where statistical models for a drug include unrelated mutations known to be causing resistance to other drugs. Here, we introduce a novel ‘cannibalistic’ elimination algorithm (“Hungry, Hungry SNPos”) that attempts to remove these co-occurrent resistant variants. Using an M. tuberculosis genomic dataset for the virulent Beijing strain-type (n = 3,574) with phenotypic resistance data across five drugs (isoniazid, rifampicin, ethambutol, pyrazinamide, and streptomycin), we demonstrate that this new approach is considerably more robust than traditional methods and detects resistance-associated variants too rare to be likely picked up by correlation-based techniques like GWAS., Author summary Tuberculosis is one of the deadliest infectious diseases, being responsible for more than one million deaths per year. The causing bacteria are becoming increasingly drug-resistant, which is hampering disease control. At the same time, an unprecedented amount of bacterial whole-genome sequencing is increasingly informing clinical practice. In order to detect the genetic alterations responsible for developing drug resistance and predict resistance status from genomic data, bio-statistical methods and machine learning models have been employed. However, due to strongly overlapping drug resistance phenotypes and genotypes in multidrug-resistant datasets, the results of these correlation-based approaches frequently also contain mutations related to resistance against other drugs. In the past, this issue has often been ignored or partially resolved by either restricting the input data or in post-analysis screening—with both strategies relying on prior information. Here we present a heuristic algorithm for finding resistance-associated variants and demonstrate that it is considerably more robust towards co-occurrent resistance compared to traditional techniques. The software is available at https://github.com/julibeg/HHS.

BackgroundThere is growing recognition that recent global increases in obesity are the product of a complex interplay between genetic and environmental factors. However, in gene-environment studies of obesity, ‘environment’ usually refers to individual behavioural factors that influence energy balance, whereas more upstream environmental factors are overlooked. We examined gene-environment interactions between genetic risk of obesity and two neighbourhood characteristics likely to be associated with obesity (proximity to takeaway/fast-food outlets and availability of physical activity facilities).MethodsWe used data from 335 046 adults aged 40–70 in the UK Biobank cohort to conduct a population-based cross-sectional study of interactions between neighbourhood characteristics and genetic risk of obesity, in relation to body mass index (BMI). Proximity to a fast-food outlet was defined as distance from home address to nearest takeaway/fast-food outlet, and availability of physical activity facilities as the number of formal physical activity facilities within 1 km of home address. Genetic risk of obesity was operationalised by weighted Genetic Risk Scores of 91 or 69 single nucleotide polymorphisms (SNP), and by six individual SNPs considered separately. Multivariable, mixed-effects models with product terms for the gene-environment interactions were estimated.ResultsAfter accounting for likely confounding, the association between proximity to takeaway/fast-food outlets and BMI was stronger among those at increased genetic risk of obesity, with evidence of an interaction with polygenic risk scores (p=0.018 and p=0.028 for 69-SNP and 91-SNP scores, respectively) and in particular with a SNP linked to MC4R (p=0.009), a gene known to regulate food intake. We found very little evidence of gene-environment interaction for the availability of physical activity facilities.ConclusionsIndividuals at an increased genetic risk of obesity may be more sensitive to exposure to the local fast-food environment. Ensuring that neighbourhood residential environments are designed to promote a healthy weight may be particularly important for those with greater genetic susceptibility to obesity.

The Beijing genotype comprises a highly disseminated strain type that is frequently associated with multidrug resistant (MDR) tuberculosis (TB) and increased transmissibility but, countries such as Portugal and Guinea-Bissau fall outside the regions phylogeographically associated with this specific genotype. Nevertheless, recent data shows that this genotype might be gradually emerging in these two countries as an underlying cause of primary MDR-TB. Here, we describe the emergence of Mycobacterium tuberculosis Beijing strains associated with MDR-TB in Portugal and Guinea-Bissau demonstrating the presence of the well described superclusters 100-32 and 94-32 in Portugal and Guinea-Bissau, respectively. Genome-wide analysis and comparison with a global genomic dataset of M. tuberculosis Beijing strains, revealed the presence of two genomic clusters encompassing isolates from Portugal and Guinea-Bissau, GC1 (n = 121) and GC2 (n = 39), both of which bore SNP signatures compatible with the 100-32/B0/W148 and 94-32/Central Asia Outbreak clades, respectively. Moreover, GC2 encompasses a cross-border cluster between Portugal, Guinea-Bissau and Brazil thus supporting migration-associated introduction of MDR-TB and subsequent clonal expansion at the community-level. The comparison with global Beijing datasets demonstrates the global reach of the disease and its complex dissemination across multiple countries while in parallel there are clear microevolutionary trajectories towards extensively drug resistant TB. This work was supported by the Biotechnology and Biological Sciences Research Council [grant number BB/R013063/ 1]; Fundação para a Ciência e a Tecnologia [grant number UID/DTP/04138/2019,UID/Multi/04413/2013]; Medical Research Council [grant numbers MR/K000551/1, MR/ M01360X/1, MR/N010469/1, MR/R0209]; Russian Science Foundation [grant number 19-14-00013]. info:eu-repo/semantics/publishedVersion

BackgroundRapid diagnostic tests (RDTs) that detect the malaria antigen histidine-rich protein 2 (HRP2) are widely used in endemic areas globally to confirm Plasmodium falciparum infection in febrile patients. The emergence of parasites lacking the gene encoding HRP2 and escaping RDT detection threatens progress in malaria control and elimination. Many health facilities in malaria endemic countries are dependent on RDTs for diagnosis and some National Health Service hospitals without expert microscopists rely on them for diagnosis out of hours. It is vital to study the emergence and the extent of such parasites globally to guide diagnostic policy. Currently, verification of the presence of such parasites in a blood sample requires a series of PCR assays to confirm the presence of P. falciparum and in the absence of amplicons from pfhrp2 and/or pfhrp3, which encodes a cross-reactive protein isoform. These tests have different limits of detection and many laboratories have reported difficulty in confirming the absence of pfhrp2 and pfhrp3 with certainty.MethodsWe developed and validated a novel and rapid multiplex real time quantitative (qPCR) assay to detect pfhrp2, pfhrp3, confirmatory parasite and human reference genes simultaneously. We also applied the assay to detect pfhrp2 and pfhrp3 deletion in 462 field samples from different endemic countries and UK travellers.ResultsThe qPCR assay showed limit of detection and quantification of 0.76-1.5 parasites per μl. The amplification efficiency, coefficient of determination (R2) and slope for the genes were 96-1.07%, 0.96-0.98 and −3.375 2 to −3.416 respectively. The assay demonstrated diagnostic sensitivity of 100% (n=19, 95% CI= (82.3%; 100%)) and diagnostic specificity of 100% (n=31; 95% CI= (88.8%; 100%)) in detecting pfhrp2 and pfhrp3 in. In addition, the qPCR assay estimates P. falciparum parasite density and can detect pfhrp2 and pfhrp3 deletions masked in polyclonal infections. We report pfhrp2 and pfhrp3 deletions in parasite isolates from Kenya, Tanzania and in UK travellers.ConclusionThe new qPCR assay is simple to use and offers significant advantages in speed and ease of interpretation. It is easily scalable to routine surveillance studies in countries where P. falciparum parasites lacking pfhrp2 and pfhrp3 are a threat to malaria control.

BackgroundSARS-CoV-2 most likely evolved from a bat beta-coronavirus and started infecting humans in December 2019. Since then it has rapidly infected people around the world, with more than 4.5 million confirmed cases by the middle of May 2020. Early genome sequencing of the virus has enabled the development of molecular diagnostics and the commencement of therapy and vaccine development. The analysis of the early sequences showed relatively few evolutionary selection pressures. However, with the rapid worldwide expansion into diverse human populations, significant genetic variations are becoming increasingly likely. The current limitations on social movement between countries also offers the opportunity for these viral variants to become distinct strains with potential implications for diagnostics, therapies and vaccines.MethodsWe used the current sequencing archives (NCBI and GISAID) to investigate 15,487 whole genomes, looking for evidence of strain diversification and selective pressure.ResultsWe used 6,294 SNPs to build a phylogenetic tree of SARS-CoV-2 diversity and noted strong evidence for the existence of two major clades and six sub-clades, unevenly distributed across the world. We also noted that convergent evolution has potentially occurred across several locations in the genome, showing selection pressures, including on the spike glycoprotein where we noted a potentially critical mutation that could affect its binding to the ACE2 receptor. We also report on mutations that could prevent current molecular diagnostics from detecting some of the sub-clades.ConclusionThe worldwide whole genome sequencing effort is revealing the challenge of developing SARS-CoV-2 containment tools suitable for everyone and the need for data to be continually evaluated to ensure accuracy in outbreak estimations.

Mycobacterium tuberculosis, which causes tuberculosis, expresses a large proportion of leaderless transcripts lacking the canonical bacterial translation initiation signals. The role leaderless genes play in the physiology of this pathogen, which can undergo prolonged periods of non-replicating persistence in the host, is currently unknown. We have previously demonstrated that levels of leaderless transcription increase under conditions of nutrient starvation. However, little is known about the implications of this for persistent infection. Here, we performed ribosome profiling to characterise the translational landscape ofM. tuberculosis in vitro. Our data reveals robust leaderless translation in the pathogen and points towards different mechanisms for their initiation of translation compared to canonical Shine-Dalgarno genes. Furthermore, under conditions of nutrient starvation, we found a significant global up-regulation of leaderless genes in the translatome. Our data represents a rich resource for others seeking to understand translational regulation not only inM. tuberculosisbut in bacterial pathogens.

Background Tuberculosis (TB), particularly multi- and or extensive drug resistant TB, is still a global medical emergency. Whole genome sequencing (WGS) is a current alternative to the WHO-approved probe-based methods for TB diagnosis and detection of drug resistance, genetic diversity and transmission dynamics of Mycobacterium tuberculosis complex (MTBC). This study compared WGS and clinical data in participants with TB. Results This cohort study performed WGS on 87 from MTBC DNA isolates, 57 (66%) and 30 (34%) patients with drug resistant and susceptible TB, respectively. Drug resistance was determined by Xpert® MTB/RIF assay and phenotypic culture-based drug-susceptibility-testing (DST). WGS and bioinformatics data that predict phenotypic resistance to anti-TB drugs were compared with participant’s clinical outcomes. They were 47 female participants (54%) and the median age was 35 years (IQR): 29–44). Twenty (23%) and 26 (30%) of participants had TB/HIV co-infection BMI 2 respectively. MDR-TB participants had MTBC with multiple mutant genes, compared to those with mono or polyresistant TB, and the majority belonged to lineage 3 Central Asian Strain (CAS). Also, MDR-TB was associated with delayed culture-conversion (median: IQR (83: 60–180 vs. 51:30–66) days). WGS had high concordance with both culture-based DST and Xpert® MTB/RIF assay in detecting drug resistance (kappa = 1.00). Conclusion This study offers comparison of mutations detected by Xpert and WGS with phenotypic DST of M. tuberculosis isolates in Tanzania. The high concordance between the different methods and further insights provided by WGS such as PZA-DST, which is not routinely performed in most resource-limited-settings, provides an avenue for inclusion of WGS into diagnostic matrix of TB including drug-resistant TB.

Portugal is a low incidence country for tuberculosis (TB) disease. Now figuring among TB low incidence countries, it has since the 1990s reported multidrug resistant and extensively drug resistant (XDR) TB cases, driven predominantly by two strain-types: Lisboa3 and Q1. This study describes the largest characterization of the evolutionary trajectory of M/XDR-TB strains in Portugal, spanning a time-period of two decades. By combining whole-genome sequencing and phenotypic susceptibility data for 207 isolates, we report the geospatial patterns of drug resistant TB, particularly the dispersion of Lisboa3 and Q1 clades, which underly 64.2% and 94.0% of all MDR-TB and XDR-TB isolates, respectively. Genomic-based similarity and a phylogenetic analysis revealed multiple clusters (n = 16) reflecting ongoing and uncontrolled recent transmission of M/XDR-TB, predominantly associated with the Lisboa3 and Q1 clades. These clades are now thought to be evolving in a polycentric mode across multiple geographical districts. The inferred evolutionary history is compatible with MDR- and XDR-TB originating in Portugal in the 70's and 80's, respectively, but with subsequent multiple emergence events of MDR and XDR-TB particularly involving the Lisboa3 clade. A SNP barcode was defined for Lisboa3 and Q1 and comparison with a phylogeny of global strain-types (n = 28 385) revealed the presence of Lisboa3 and Q1 strains in Europe, South America and Africa. In summary, Portugal displays an unusual and unique epidemiological setting shaped by >40 years of uncontrolled circulation of two main phylogenetic clades, leading to a sympatric evolutionary trajectory towards XDR-TB with the potential for global reach. Financial support was provided by the European Society of Clinical Microbiology and Infectious Diseases, for which we would like to would like to acknowledge the Study Group for Mycobacterial Infections. Supported in part by UID/DTP/04138/2019 from Fundação para a Ciência e Tecnologia (FCT), Portugal. JP [CEECIND/00394/2017] and DM are supported by FCT through Estímulo Individual ao Emprego Científico. DM, IC and MV are funded by project PTDC/BIA-MIC/30692/2017 and the Global Health and Tropical Medicine (GHTM) Research Center (Grant UID/Multi/04413/2013) from FCT. TGC received funding from the MRC UK (Grant no. MR/K000551/1, MR/M01360X/1, MR/N010469/1, MR/R020973/1) and BBSRC UK (BB/R013063/1). SC received funding from the Medical Research Council UK grants (MR/R020973/1) and the BBSRC UK (BB/R013063/1). JPhe is funded by the Medical Research Council UK grants (MR/S03563X/1). info:eu-repo/semantics/publishedVersion

Although Plasmodium vivax parasites are the predominant cause of malaria outside of sub-Saharan Africa, they not always prioritised by elimination programmes. P. vivax is resilient and poses challenges through its ability to re-emerge from dormancy in the human liver. With observed growing drug-resistance and the increasing reports of life-threatening infections, new tools to inform elimination efforts are needed. In order to halt transmission, we need to better understand the dynamics of transmission, the movement of parasites, and the reservoirs of infection in order to design targeted interventions. The use of molecular genetics and epidemiology for tracking and studying malaria parasite populations has been applied successfully in P. falciparum species and here we sought to develop a molecular genetic tool for P. vivax. By assembling the largest set of P. vivax whole genome sequences (n = 433) spanning 17 countries, and applying a machine learning approach, we created a 71 SNP barcode with high predictive ability to identify geographic origin (91.4%). Further, due to the inclusion of markers for within population variability, the barcode may also distinguish local transmission networks. By using P. vivax data from a low-transmission setting in Malaysia, we demonstrate the potential ability to infer outbreak events. By characterising the barcoding SNP genotypes in P. vivax DNA sourced from UK travellers (n = 132) to ten malaria endemic countries predominantly not used in the barcode construction, we correctly predicted the geographic region of infection origin. Overall, the 71 SNP barcode outperforms previously published genotyping methods and when rolled-out within new portable platforms, is likely to be an invaluable tool for informing targeted interventions towards elimination of this resilient human malaria., Author summary Plasmodium vivax is the most widespread parasite causing human malaria, with more than one-third of the world’s population being at risk of infection. P. vivax is resilient due to its dormant liver phase, and there are increasing reports of drug-resistance and life-threatening infections. Despite this, P. vivax malaria is not always prioritised by elimination programmes. New molecular tools are needed to inform elimination efforts, including through better understanding the geographical source and outbreaks of P. vivax, thereby leading to the halting of transmission and the targeting of reservoirs of infection. Our work describes a 71 genetic marker barcode for P. vivax that has high predictive ability to identify the geographic origin, and has the potential to distinguish local transmission networks. If the 71 genetic marker barcode is implemented within new portable molecular platforms, it is likely to be an invaluable tool for informing targeted interventions towards elimination of this resilient human malaria.

BackgroundAntimicrobial resistance (AMR) poses a threat to public health. Clinical microbiology laboratories typically rely on culturing bacteria for antimicrobial susceptibility testing (AST). As the implementation costs and technical barriers fall, whole-genome sequencing (WGS) has emerged as a ‘one-stop’ test for epidemiological and predictive AST results. Few published comparisons exist for the myriad analytical pipelines used for predicting AMR. To address this, we performed an inter-laboratory study providing sets of participating researchers with identical short-read WGS data sequenced from clinical isolates, allowing us to assess the reproducibility of the bioinformatic prediction of AMR between participants and identify problem cases and factors that lead to discordant results.MethodsWe produced ten WGS datasets of varying quality from cultured carbapenem-resistant organisms obtained from clinical samples sequenced on either an Illumina NextSeq or HiSeq instrument. Nine participating teams (‘participants’) were provided these sequence data without any other contextual information. Each participant used their own pipeline to determine the species, the presence of resistance-associated genes, and to predict susceptibility or resistance to amikacin, gentamicin, ciprofloxacin and cefotaxime.ResultsIndividual participants predicted different numbers of AMR-associated genes and different gene variants from the same clinical samples. The quality of the sequence data, choice of bioinformatic pipeline and interpretation of the results all contributed to discordance between participants. Although much of the inaccurate gene variant annotation did not affect genotypic resistance predictions, we observed low specificity when compared to phenotypic AST results but this improved in samples with higher read depths. Had the results been used to predict AST and guide treatment a different antibiotic would have been recommended for each isolate by at least one participant.ConclusionsWe found that participants produced discordant predictions from identical WGS data. These challenges, at the final analytical stage of using WGS to predict AMR, suggest the need for refinements when using this technology in clinical settings. Comprehensive public resistance sequence databases and standardisation in the comparisons between genotype and resistance phenotypes will be fundamental before AST prediction using WGS can be successfully implemented in standard clinical microbiology laboratories.

Many rapid diagnostic tests (RDT) used on suspected malaria cases are based on the detection of the protein encoded by the Plasmodium falciparum histidine-rich protein-2 (pfhrp2) gene, which shares a high sequence homology with pfhrp3 in the 3D7 reference genome. Parasite isolates showing pfhrp2 and pfhrp3 gene deletions have been emerging over the years, but a comprehensive genetic analysis of these variants is still lacking. With this purpose, genomic data from experimental P. falciparum genetic crosses between different laboratory lines (3D7, HB3, DD2, 7G8 and GB4) were first analysed (n = 98). The frequency of pfhrp2 deletions was consistent with a Mendelian prediction in HB3 × DD2 (56.7%; 95%CI = (39.5%-72.9%)). Moreover, the pfhrp2 and pfhrp3 deletions segregated independently of each other in the same genetic cross. Analysis of 3D7 × HB3 and 7G8 × GB4 estimated the probability of spontaneously generating a pfhrp2 deletion during sexual recombination to be up to 6.2%. Next, whole genome sequence data from 1970 P. falciparum isolates collected globally were analysed. Nine samples displayed depth of coverage consistent with pfhrp2 deletions (0.5%), but the corresponding split-read analysis could not confirm deletions in seven of these samples. Twenty-eight isolates had evidence of pfhrp3 deletions (1.4%), which are widespread in Southeast Asia. Finally, a meta-analysis of published data revealed a positive mean association between the frequencies of pfhrp2 and pfhrp3 deletions in Africa and South America. This result suggested a shared selective pressure acting on these genetic variants. In conclusion, evidence of genetic selection on both pfhrp2 and pfhrp3 deletions was presented, but experimental crosses do not provide evidence of a fitness cost of these variants. Further work is urgently needed to accurately determine the prevalence and the degree of association between these genetic variants, and the respective impact on diagnostic accuracy of many in-use RDT.

The emergence of programmatically incurable tuberculosis threatens to destabilise control efforts. The aim of this study was to collect prospective patient-level data to inform treatment and containment strategies.In a prospective cohort study, 273 South African patients with extensively drug-resistant tuberculosis, or resistance beyond extensively drug-resistant tuberculosis, were followed up over a period of 6 years. Transmission dynamics, infectiousness, and drug susceptibility were analysed in a subset of patients from the Western Cape using whole-genome sequencing (WGS; n=149), a cough aerosol sampling system (CASS; n=26), and phenotypic testing for 18 drugs (n=179).Between Oct 1, 2008, and Oct 31, 2012, we enrolled and followed up 273 patients for a median of 20·3 months (IQR 9·6-27·8). 203 (74%) had programmatically incurable tuberculosis and unfavourable outcomes (treatment failure, relapse, default, or death despite treatment with a regimen based on capreomycin, aminosalicylic acid, or both). 172 (63%) patients were discharged home, of whom 104 (60%) had an unfavourable outcome. 54 (31%) home-discharged patients had failed treatment, with a median time to death after discharge of 9·9 months (IQR 4·2-17·4). 35 (20%) home-discharged cases were smear-positive at discharge. Using CASS, six (23%) of 26 home-discharged cases with data available expectorated infectious culture-positive cough aerosols in the respirable range (5 μm), and most reported inter-person contact with suboptimal protective mask usage. WGS identified 17 (19%) of the 90 patients (with available sequence data) that were discharged home before the diagnosis of 20 downstream cases of extensively drug-resistant tuberculosis with almost identical sequencing profiles suggestive of community-based transmission (five or fewer single nucleotide polymorphisms different and with identical resistance-encoding mutations for 14 drugs). 11 (55%) of these downstream cases had HIV co-infection and ten (50%) had died by the end of the study. 22 (56%) of 39 isolates in patients discharged home after treatment failure were resistant to eight or more drugs. However, five (16%) of 31 isolates were susceptible to rifabutin and more than 90% were likely to be sensitive to linezolid, bedaquiline, and delamanid.More than half of the patients with programmatically incurable tuberculosis were discharged into the community where they remained for an average of 16 months, were at risk of expectorating infectious cough aerosols, and posed a threat of transmission of extensively drug-resistant tuberculosis. Urgent action, including appropriate containment strategies, is needed to address this situation. Access to delamanid, bedaquiline, linezolid, and rifabutin, when appropriate, must be accelerated along with comprehensive drug susceptibility testing.UK Medical Research Council, South African Medical Research Council, South African National Research Foundation, EuropeanDeveloping Countries Clinical Trials Partnership, Oppenheimer Foundation, Newton Fund, Biotechnology and Biological Sciences Research Council, King Abdullah University of ScienceTechnology.

Summary Recombinase polymerase amplification (RPA), an isothermal nucleic acid amplification method, is enhancing our ability to detect a diverse array of pathogens, thereby assisting the diagnosis of infectious diseases and the detection of microorganisms in food and water. However, new bioinformatics tools are needed to automate and improve the design of the primers and probes sets to be used in RPA, particularly to account for the high genetic diversity of circulating pathogens and cross detection of genetically similar organisms. PrimedRPA is a python-based package that automates the creation and filtering of RPA primers and probe sets. It aligns several sequences to identify conserved targets, and filters regions that cross react with possible background organisms. Availability and implementation PrimedRPA was implemented in Python 3 and supported on Linux and MacOS and is freely available from http://pathogenseq.lshtm.ac.uk/PrimedRPA.html. Supplementary information Supplementary data are available at Bioinformatics online.

Klebsiella pneumoniae has emerged as an important nosocomial pathogen, with whole-genome sequencing (WGS) significantly improving our ability to characterize associated outbreaks. Our study sought to perform a genome-wide analysis of multiclonal K. pneumoniae isolates (n=39; 23 patients) producing extended spectrum beta-lactamases and/or carbapenemases sourced between 2011 and 2016 in a Portuguese tertiary-care hospital. All isolates showed resistance to third-generation cephalosporins and six isolates (five patients) were also carbapenem resistant. Genome-wide-based phylogenetic analysis revealed a topology representing ongoing dissemination of three main sequence-type (ST) clades (ST15, ST147 and ST307) and transmission across different wards, compatible with missing links that can take the form of undetected colonized patients. Two carbapenemase-coding genes were detected: blaKPC-3 , located on a Tn4401d transposon, and blaGES-5 on a novel class 3 integron. Additionally, four genes coding for ESBLs (blaBEL-1 , blaCTX-M-8 , blaCTX-M-15 and blaCTX-M-32 ) were also detected. ESBL horizontal dissemination across five clades is highlighted by the similar genetic environments of blaCTX-M-15 gene upstream of ISEcp1 on a Tn3-like transposon. Overall, this study provides a high-resolution genome-wide perspective on the epidemiology of ESBL and carbapenemase-producing K. pneumoniae in a healthcare setting while contributing for the adoption of appropriate intervention and prevention strategies.

Background: Tuberculosis disease, caused by Mycobacterium tuberculosis, is a major public health problem. The emergence of M. tuberculosis strains resistant to existing treatments threatens to derail control efforts. Resistance is mainly conferred by mutations in genes coding for drug targets or converting enzymes, but our knowledge of these mutations is incomplete. Whole genome sequencing (WGS) is an increasingly common approach to rapidly characterize isolates and identify mutations predicting antimicrobial resistance and thereby providing a diagnostic tool to assist clinical decision making. Methods: We applied machine learning approaches to 16,688 M. tuberculosis isolates that have undergone WGS and laboratory drug-susceptibility testing (DST) across 14 antituberculosis drugs, with 22.5% of samples being multidrug resistant and 2.1% being extensively drug resistant. We used non-parametric classification-tree and gradient-boosted-tree models to predict drug resistance and uncover any associated novel putative mutations. We fitted separate models for each drug, with and without "co-occurrent resistance" markers known to be causing resistance to drugs other than the one of interest. Predictive performance was measured using sensitivity, specificity, and the area under the receiver operating characteristic curve, assuming DST results as the gold standard. Results: The predictive performance was highest for resistance to first-line drugs, amikacin, kanamycin, ciprofloxacin, moxifloxacin, and multidrug-resistant tuberculosis (area under the receiver operating characteristic curve above 96%), and lowest for third-line drugs such as D-cycloserine and Para-aminosalisylic acid (area under the curve below 85%). The inclusion of co-occurrent resistance markers led to improved performance for some drugs and superior results when compared to similar models in other large-scale studies, which had smaller sample sizes. Overall, the gradient-boosted-tree models performed better than the classification-tree models. The mutation-rank analysis detected no new single nucleotide polymorphisms linked to drug resistance. Discordance between DST and genotypically inferred resistance may be explained by DST errors, novel rare mutations, hetero-resistance, and nongenomic drivers such as efflux-pump upregulation. Conclusion: Our work demonstrates the utility of machine learning as a flexible approach to drug resistance prediction that is able to accommodate a much larger number of predictors and to summarize their predictive ability, thus assisting clinical decision making and single nucleotide polymorphism detection in an era of increasing WGS data generation.

Tuberculosis (TB), caused by Mycobacterium tuberculosis bacteria, is a leading infectious cause of mortality worldwide, including in Pakistan. Drug resistant M. tuberculosis is an emerging threat for TB control, making it important to detect the underlying genetic mutations, and thereby inform treatment decision making and prevent transmission. Whole genome sequencing has emerged as the new diagnostic to reliably predict drug resistance within a clinically relevant time frame, and its deployment will have the greatest impact on TB control in highly endemic regions. To evaluate the mutations leading to drug resistance and to assess for evidence of the transmission of resistant strains, 81 M. tuberculosis samples from Khyber Pakhtunkhwa province (North West Pakistan) were subjected to whole genome sequencing and standard drug susceptibility testing for eleven anti-TB drugs. We found the majority of M. tuberculosis isolates were the CAS/Delhi strain-type (lineage 3; n = 57; 70.4%) and multi-drug resistant (MDR; n = 62; 76.5%). The most frequent resistance mutations were observed in the katG and rpoB genes, conferring resistance to isoniazid and rifampicin respectively. Mutations were also observed in genes conferring resistance to other first and second-line drugs, including in pncA (pyrazinamide), embB (ethambutol), gyrA (fluoroquinolones), rrs (aminoglycosides), rpsL, rrs and giB (streptomycin) loci. Whilst the majority of mutations have been reported in global datasets, we describe unreported putative resistance markers in katG, ethA (ethionamide), gyrA and gyrB (fluoroquinolones), and pncA. Analysis of the mutations revealed that acquisition of rifampicin resistance often preceded isoniazid in our isolates. We also observed a high proportion (17.6%) of pre-MDR isolates with fluoroquinolone resistance markers, potentially due to unregulated anti-TB drug use. Our isolates were compared to previously sequenced strains from Pakistan in a combined phylogenetic tree analysis. The presence of lineage 2 was only observed in our isolates. Using a cut-off of less than ten genome-wide mutation differences between isolates, a transmission analysis revealed 18 M. tuberculosis isolates clustering within eight networks, thereby providing evidence of drug-resistant TB transmission in the Khyber Pakhtunkhwa province. Overall, we have demonstrated that drug-resistant TB isolates are circulating and transmitted in North West Pakistan. Further, we have shown the usefulness of whole genome sequencing as a diagnostic tool for characterizing M. tuberculosis isolates, which will assist future epidemiological studies and disease control activities in Pakistan.

Background Mycobacterium tuberculosis resistance to anti-tuberculosis drugs is a major threat to global public health. Whole genome sequencing (WGS) is rapidly gaining traction as a diagnostic tool for clinical tuberculosis settings. To support this informatically, previous work led to the development of the widely used TBProfiler webtool, which predicts resistance to 14 drugs from WGS data. However, for accurate and rapid high throughput of samples in clinical or epidemiological settings, there is a need for a stand-alone tool and the ability to analyse data across multiple WGS platforms, including Oxford Nanopore MinION. Results We present a new command line version of the TBProfiler webserver, which includes hetero-resistance calling and will facilitate the batch processing of samples. The TBProfiler database has been expanded to incorporate 178 new markers across 16 anti-tuberculosis drugs. The predictive performance of the mutation library has been assessed using > 17,000 clinical isolates with WGS and laboratory-based drug susceptibility testing (DST) data. An integrated MinION analysis pipeline was assessed by performing WGS on 34 replicates across 3 multi-drug resistant isolates with known resistance mutations. TBProfiler accuracy varied by individual drug. Assuming DST as the gold standard, sensitivities for detecting multi-drug-resistant TB (MDR-TB) and extensively drug-resistant TB (XDR-TB) were 94% (95%CI 93–95%) and 83% (95%CI 79–87%) with specificities of 98% (95%CI 98–99%) and 96% (95%CI 95–97%) respectively. Using MinION data, only one resistance mutation was missed by TBProfiler, involving an insertion in the tlyA gene coding for capreomycin resistance. When compared to alternative platforms (e.g. Mykrobe predictor TB, the CRyPTIC library), TBProfiler demonstrated superior predictive performance across first- and second-line drugs. Conclusions The new version of TBProfiler can rapidly and accurately predict anti-TB drug resistance profiles across large numbers of samples with WGS data. The computing architecture allows for the ability to modify the core bioinformatic pipelines and outputs, including the analysis of WGS data sourced from portable technologies. TBProfiler has the potential to be integrated into the point of care and WGS diagnostic environments, including in resource-poor settings.

The Philippines has a high incidence of tuberculosis disease (TB), with an increasing prevalence of multidrug-resistant Mycobacterium tuberculosis (MDR-TB) strains making its control difficult. Although the M. tuberculosis “Manila” ancient lineage 1 strain-type is thought to be prevalent in the country, with evidence of export to others, little is known about the genetic diversity of circulating strains. By whole genome sequencing (WGS) 178 isolates from the Philippines National Drug Resistance Survey, we found the majority (143/178; 80.3%) belonged to the lineage 1 Manila clade, with the minority belonging to lineages 4 (European-American; n = 33) and 2 (East Asian; n = 2). A high proportion were found to be multidrug-resistant (34/178; 19.1%), established through highly concordant laboratory drug susceptibility testing and in silico prediction methods. Some MDR-TB isolates had near identical genomic variation, providing potential evidence of transmission. By placing the Philippine isolates within a phylogeny of global M. tuberculosis (n > 17,000), we established that they are genetically similar to those observed outside the country, including a clade of Manila-like strain-types in Thailand. An analysis of the phylogeny revealed a set of ~200 SNPs that are specific for the Manila strain-type, and a subset can be used within a molecular barcode. Sixty-eight mutations known to be associated with 10 anti-TB drug resistance were identified in the Philippine strains, and all have been observed in other populations. Whilst nine putative streptomycin resistance conferring markers in gid (8) and rrs (1) genes appear to be novel and with functional consequences. Overall, this study provides an important baseline characterisation of M. tuberculosis genetic diversity for the Philippines, and will fill a gap in global datasets and aid the development of a nation-wide database for epidemiological studies and clinical decision making. Further, by establishing a molecular barcode for detecting Manila strains it will assist with the design of diagnostic tools for disease control activities.

Background Continuing evolution of the Mycobacterium tuberculosis (Mtb) complex genomes associated with resistance to anti-tuberculosis drugs is threatening tuberculosis disease control efforts. Both multi- and extensively drug resistant Mtb (MDR and XDR, respectively) are increasing in prevalence, but the full set of Mtb genes involved are not known. There is a need for increased sensitivity of genome-wide approaches in order to elucidate the genetic basis of anti-microbial drug resistance and gain a more detailed understanding of Mtb genome evolution in a context of widespread antimicrobial therapy. Population structure within the Mtb complex, due to clonal expansion, lack of lateral gene transfer and low levels of recombination between lineages, may be reducing statistical power to detect drug resistance associated variants. Results To investigate the effect of lineage-specific effects on the identification of drug resistance associations, we applied genome-wide association study (GWAS) and convergence-based (PhyC) methods to multiple drug resistance phenotypes of a global dataset of Mtb lineages 2 and 4, using both lineage-wise and combined approaches. We identify both well-established drug resistance variants and novel associations; uniquely identifying associations for both lineage-specific and -combined GWAS analyses. We report 17 potential novel associations between antimicrobial resistance phenotypes and Mtb genomic variants. Conclusions For GWAS, both lineage-specific and -combined analyses are useful, whereas PhyC may perform better in contexts of greater diversity. Unique associations with XDR in lineage-specific analyses provide evidence of diverging evolutionary trajectories between lineages 2 and 4 in response to antimicrobial drug therapy. Electronic supplementary material The online version of this article (10.1186/s12864-019-5615-3) contains supplementary material, which is available to authorized users.

Human tuberculosis disease (TB), caused by Mycobacterium tuberculosis (Mtb), is a complex disease, with a spectrum of outcomes. Genomic, transcriptomic and methylation studies have revealed differences between Mtb lineages, likely to impact on transmission, virulence and drug resistance. However, so far no studies have integrated sequence-based genomic, transcriptomic and methylation characterisation across a common set of samples, which is critical to understand how DNA sequence and methylation affect RNA expression and, ultimately, Mtb pathogenesis. Here we perform such an integrated analysis across 22 M. tuberculosis clinical isolates, representing ancient (lineage 1) and modern (lineages 2 and 4) strains. The results confirm the presence of lineage-specific differential gene expression, linked to specific SNP-based expression quantitative trait loci: with 10 eQTLs involving SNPs in promoter regions or transcriptional start sites; and 12 involving potential functional impairment of transcriptional regulators. Methylation status was also found to have a role in transcription, with evidence of differential expression in 50 genes across lineage 4 samples. Lack of methylation was associated with three novel variants in mamA, likely to cause loss of function of this enzyme. Overall, our work shows the relationship of DNA sequence and methylation to RNA expression, and differences between ancient and modern lineages. Further studies are needed to verify the functional consequences of the identified mechanisms of gene expression regulation.

DNA methylation is an epigenetic modification of the genome involved in regulating crucial cellular processes, including transcription and chromosome stability. Advances in PacBio sequencing technologies can be used to robustly reveal methylation sites. The methylome of the Mycobacterium tuberculosis complex is poorly understood but may be involved in virulence, hypoxic survival and the emergence of drug resistance. In the most extensive study to date, we characterise the methylome across the 4 major lineages of M. tuberculosis and 2 lineages of M. africanum, the leading causes of tuberculosis disease in humans. We reveal lineage-specific methylated motifs and strain-specific mutations that are abundant globally and likely to explain loss of function in the respective methyltransferases. Our work provides a set of sixteen new complete reference genomes for the Mycobacterium tuberculosis complex, including complete lineage 5 genomes. Insights into lineage-specific methylomes will further elucidate underlying biological mechanisms and other important phenotypes of the epi-genome.

Summary Mycobacterium tuberculosis, which causes tuberculosis, can undergo prolonged periods of non-replicating persistence in the host. The mechanisms underlying this are not fully understood, but translational regulation is thought to play a role. A large proportion of mRNA transcripts expressed in M. tuberculosis lack canonical bacterial translation initiation signals, but little is known about the implications of this for fine-tuning of translation. Here, we perform ribosome profiling to characterize the translational landscape of M. tuberculosis under conditions of exponential growth and nutrient starvation. Our data reveal robust, widespread translation of non-canonical transcripts and point toward different translation initiation mechanisms compared to canonical Shine-Dalgarno transcripts. During nutrient starvation, patterns of ribosome recruitment vary, suggesting that regulation of translation in this pathogen is more complex than originally thought. Our data represent a rich resource for others seeking to understand translational regulation in bacterial pathogens., Graphical Abstract, Highlights • A resource for studying translation and its regulation in M. tuberculosis • Translation of non-canonical transcripts is robust and widespread • Positional data of initiating ribosomes reveal differences in initiation • Ribosome stabilization factors are upregulated in starvation, Sawyer et al. use ribosome profiling to characterize the translational landscape of Mycobacterium tuberculosis. They find widespread translation of non-canonical transcripts lacking canonical bacterial translation signals. Ribosome positioning reveals differences in initiation mechanisms, and factors that stabilize intact ribosomes may ensure continued robust translation during conditions of stress.

Background Mixed, polyclonal Mycobacterium tuberculosis infection occurs in natural populations. Developing an effective method for detecting such cases is important in measuring the success of treatment and reconstruction of transmission between patients. Using whole genome sequence (WGS) data, we assess two methods for detecting mixed infection: (i) a combination of the number of heterozygous sites and the proportion of heterozygous sites to total SNPs, and (ii) Bayesian model-based clustering of allele frequencies from sequencing reads at heterozygous sites. Results In silico and in vitro artificially mixed and known pure M. tuberculosis samples were analysed to determine the specificity and sensitivity of each method. We found that both approaches were effective in distinguishing between pure strains and mixed infection where there was relatively high (> 10%) proportion of a minor strain in the mixture. A large dataset of clinical isolates (n = 1963) from the Karonga Prevention Study in Northern Malawi was tested to examine correlations with patient characteristics and outcomes with mixed infection. The frequency of mixed infection in the population was found to be around 10%, with an association with year of diagnosis, but no association with age, sex, HIV status or previous tuberculosis. Conclusions Mixed Mycobacterium tuberculosis infection was identified in silico using whole genome sequence data. The methods presented here can be applied to population-wide analyses of tuberculosis to estimate the frequency of mixed infection, and to identify individual cases of mixed infections. These cases are important when considering the evolution and transmission of the disease, and in patient treatment. Electronic supplementary material The online version of this article (10.1186/s12864-018-4988-z) contains supplementary material, which is available to authorized users.

Tuberculosis presents a global health challenge. Mycobacterium tuberculosis is divided into several lineages, each with a different geographical distribution. M. tuberculosis lineage 1 (L1) is common in the high-burden areas in East Africa and Southeast Asia. Although the founder effect contributes significantly to the phylogeographic profile, co-evolution between the host and M. tuberculosis may also play a role. Here, we reported the genomic analysis of 480 L1 isolates from patients in northern Thailand. The studied bacterial population was genetically diverse, allowing the identification of a total of 18 sublineages distributed into three major clades. The majority of isolates belonged to L1.1 followed by L1.2.1 and L1.2.2. Comparison of the single nucleotide variant (SNV) phylogenetic tree and the clades defined by spoligotyping revealed some monophyletic clades representing EAI2_MNL, EAI2_NTM and EAI6_BGD1 spoligotypes. Our work demonstrates that ambiguity in spoligotype assignment could be partially resolved if the entire DR region is investigated. Using the information to map L1 diversity across Southeast Asia highlighted differences in the dominant strain-types in each individual country, despite extensive interactions between populations over time. This finding supported the hypothesis that there is co-evolution between the bacteria and the host, and have implications for tuberculosis disease control.

Background: \ud Plasmodium knowlesi is the most common cause of malaria in Malaysian Borneo, with reporting limited to clinical cases presenting to health facilities and scarce data on the true extent of transmission. Serological estimations of transmission have been used with other malaria species to garner information about epidemiological patterns. However, there are a distinct lack of suitable serosurveillance tools for this neglected disease.\ud \ud Methodology/Principal findings: \ud Using in silico tools, we designed and expressed four novel P. knowlesi protein products to address the distinct lack of suitable serosurveillance tools: PkSERA3 antigens 1 and 2, PkSSP2/TRAP and PkTSERA2 antigen 1. Antibody prevalence to these antigens was determined by ELISA for three time-points post-treatment from a hospital-based clinical treatment trial in Sabah, East Malaysia (n = 97 individuals; 241 total samples for all time points). Higher responses were observed for the PkSERA3 antigen 2 (67%, 65/97) across all time-points (day 0: 36.9% 34/92; day 7: 63.8% 46/72; day 28: 58.4% 45/77) with significant differences between the clinical cases and controls (n = 55, mean plus 3 SD) (day 0 p

Genomic studies of Mycobacterium tuberculosis bacteria have revealed loci associated with resistance to anti-tuberculosis drugs. However, the molecular consequences of polymorphism within these candidate loci remain poorly understood. To address this, we have used computational tools to quantify the effects of point mutations conferring resistance to three major anti-tuberculosis drugs, isoniazid (n = 189), rifampicin (n = 201) and D-cycloserine (n = 48), within their primary targets, katG, rpoB, and alr. Notably, mild biophysical effects brought about by high incidence mutations were considered more tolerable, while different structural effects brought about by haplotype combinations reflected differences in their functional importance. Additionally, highly destabilising mutations such as alr Y388, highlighted a functional importance of the wildtype residue. Our qualitative analysis enabled us to relate resistance mutations onto a theoretical landscape linking enthalpic changes with phenotype. Such insights will aid the development of new resistance-resistant drugs and, via an integration into predictive tools, in pathogen surveillance.

This deposit is composed by a publication in which the IGC's authors have had the role of collaboration (it's a collaboration publication). This type of deposit in ARCA is in restrictedAccess (it can't be in open access to the public), and can only be accessed by two ways: either by requesting a legal copy from the author (the email contact present in this deposit) or by visiting the following link: https://www.nature.com/articles/s41588-018-0074-3 This publication hasn't any creative commons license associated. This deposit is composed simultaneously by the original published article and also by the "correction" for the published article (erratum). The link for the original article: https://www.nature.com/articles/s41588-017-0029-0#Ack1 This deposit is composed by the main article plus the supplementary materials of the publication. In the version of this article initially published, the URL listed for TubercuList was incorrect. The correct URL is https://mycobrowser.epfl.ch/. The error has been corrected in the HTML and PDF versions of the article. To characterize the genetic determinants of resistance to antituberculosis drugs, we performed a genome-wide association study (GWAS) of 6,465 Mycobacterium tuberculosis clinical isolates from more than 30 countries. A GWAS approach within a mixed-regression framework was followed by a phylogenetics-based test for independent mutations. In addition to mutations in established and recently described resistance-associated genes, novel mutations were discovered for resistance to cycloserine, ethionamide and para-aminosalicylic acid. The capacity to detect mutations associated with resistance to ethionamide, pyrazinamide, capreomycin, cycloserine and para-aminosalicylic acid was enhanced by inclusion of insertions and deletions. Odds ratios for mutations within candidate genes were found to reflect levels of resistance. New epistatic relationships between candidate drug-resistance-associated genes were identified. Findings also suggest the involvement of efflux pumps (drrA and Rv2688c) in the emergence of resistance. This study will inform the design of new diagnostic tests and expedite the investigation of resistance and compensatory epistatic mechanisms. The project was supported by the KAUST faculty baseline research fund (BAS/1/1020-01-01) to A.P. The authors wish to thank members of the KAUST Bioscience Core laboratory who sequenced samples. We thank the Wellcome Trust Sanger Institute core and pathogen sequencing and informatics teams who were involved in the Malawi and Uganda studies. The work was funded in part by the Wellcome Trust (grant numbers WT096249/Z/11/B, WT088559MA, WT081814/Z/06/Z and WT098051) and the Wellcome Trust–Burroughs Wellcome Fund Infectious Diseases Initiative grant (number 063410/ABC/00/Z). F.C. was the recipient of a Bloomsbury College PhD Studentship and was supported by the Wellcome Trust (201344/Z/16/Z); J. Perdigão received a Fundação para a Ciência e a Tecnologia (Portugal) postdoctoral fellowship fund (SFRH/BPD/95406/2013). The Calouste Gulbenkian Foundation, the Institute Gulbenkian in Lisbon and the European Society of Clinical Microbiology and Infectious Diseases supported the research of C.P., J. Perdigão, I.P. and M.V. J. Phelan is funded by a BBSRC PhD studentship. T.G.C. is funded by the Medical Research Council UK (grant numbers MR/K000551/1, MR/M01360X/1, MR/N010469/1 and MC_PC_15103). N.F. is funded by the Medical Research Council UK (grant number MR/K020420/1). T.M. is supported by the Ministry of Health, Labor and Welfare of Japan (H21-Shinkou-Ippan-008 and H24-Shinkou-Ippan-010). info:eu-repo/semantics/publishedVersion

Zika virus infections can cause a range of neurologic disorders including congenital microcephaly. However, while Zika infections have been notified across all regions in Brazil, there has been an unusual number of congenital microcephaly case notifications concentrated in the Northeast of the country. To address this observation, we investigated epidemiological data (2014-2016) on arbovirus co-distribution, environmental and socio-economic factors for each region in Brazil. Data on arbovirus reported cases and microcephaly were collected from several Brazilian Ministry of Health databases for each Federal unit. These were complemented by environmental management, social economic and Aedes aegypti infestation index data, extracted from multiple databases. Spatial time "ecological" analysis on the number of arboviruses transmitted by Aedes mosquitoes in Brazil show that the distribution of dengue and Zika was widespread in the whole country, with higher incidence in the West-Central region. However, reported chikungunya cases were higher in the Northeast, the region also with the highest number of microcephaly cases registered. Social economic factors (human development index and poverty index) and environmental management (water supply/storage and solid waste management) pointed the Northeast as the less wealthy region. The Northeast is also the region with the highest risk of Aedes aegypti house infestation due to the man-made larval habitats. In summary, the results of our ecological analysis support the hypothesis that the unusual distribution of microcephaly might not be due to Zika infection alone and could be accentuated by poverty and previous or co-infection with other pathogens. Our study reinforces the link between poverty and the risk of disease and the need to understand the effect on pathogenesis of sequential exposure to arboviruses and co-viral infections. Comprehensive large-scale cohort studies are required to corroborate our findings. We recommend that the list of infectious diseases screened, particularly during pregnancy, be regularly updated to include and effectively differentiate all viruses from ongoing outbreaks.

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

Macrophages play an essential role in the early immune response to Mycobacterium tuberculosis and are the cell type preferentially infected in vivo. Primary macrophages and macrophage-like cell lines are commonly used as infection models, although the physiological relevance of cell lines, particularly for host-pathogen interaction studies, is debatable. Here we use high-throughput RNA-sequencing to analyse transcriptome dynamics of two macrophage models in response to M. tuberculosis infection. Specifically, we study the early response of bone marrow-derived mouse macrophages and cell line J774 to infection with live and γ-irradiated (killed) M. tuberculosis. We show that infection with live bacilli specifically alters the expression of host genes such as Rsad2, Ifit1/2/3 and Rig-I, whose potential roles in resistance to M. tuberculosis infection have not yet been investigated. In addition, the response of primary macrophages is faster and more intense than that of J774 cells in terms of number of differentially expressed genes and magnitude of induction/repression. Our results point to potentially novel processes leading to immune containment early during M. tuberculosis infection, and support the idea that important differences exist between primary macrophages and cell lines, which should be taken into account when choosing a macrophage model to study host-pathogen interactions.

It is challenging to understand mechanisms of drug resistance in Mycobacterium tuberculosis (MTB) due to the large variability in resistance associated genes. Efflux pump genes contribute to drug resistance and thus add to this complexity. Efflux pump gene protein superfamilies have been characterized by genome analysis of drug resistant strains and through in vitro transcriptional studies. However, there is limited information regarding efflux pump genes in extensively drug resistant (XDR) tuberculosis (TB) isolates. Whole genome sequencing (WGS) based analysis of 37 extensively drug resistant (XDR) and five drug sensitive (DS) MTB clinical isolates was performed. Single nucleotide polymorphisms (SNPs) in efflux pump genes Rv0194, Rv1217, Rv1218, drrA, drrB, Rv1258, Rv1634, Rv2688, Rv1273, Rv1819, Rv1458, Rv1877 and Rv1250 were determined in the clinical isolates as compared with the H37Rv reference strain. Allele frequencies of SNPs identified in XDR strains were compared with DS strains. Gene expression of Rv0194, Rv2688, Rv1634, drrA and drrB was determined in XDR -TB isolates (n = 9), DS-TB strains (n = 4) and H37Rv. We identified SNPs in XDR-TB isolates which were either unique or present at very low frequencies in DS strains; Rv0194 G170V; Rv1217 L151R; Rv1258 P369T and G391R; Rv1273 S118G and I175T; Rv1877 I534T; Rv1250 V318X/A and S333A, and Rv2688 P156T. The expression of Rv2688 and drrB was found to be raised in XDR-TB as compared with DS-TB strains. We identified unique SNPs in efflux pump genes which may be associated with increased drug resistance in the isolates. Increased levels of Rv2688 and drrB efflux pump gene expression observed in XDR strains even in the absence of antibiotics suggests that these clinical isolates may be more refractory to treatment. Further studies are required to directly associate these mutations with increased resistance in MTB.

Two geographically distant M. tuberculosis sublineages, Tur from Turkey and T3-Osaka from Japan, exhibit partially identical genotypic signatures (identical 12-loci MIRU-VNTR profiles, distinct spoligotyping patterns). We investigated T3-Osaka and Tur sublineages characteristics and potential genetic relatedness, first using MIRU-VNTR locus analysis on 21 and 25 samples of each sublineage respectively, and second comparing Whole Genome Sequences of 8 new samples to public data from 45 samples uncovering human tuberculosis diversity. We then tried to date their Most Recent Common Ancestor (MRCA) using three calibrations of SNP accumulation rate (long-term = 0.03 SNP/genome/year, derived from a tuberculosis ancestor of around 70,000 years old; intermediate = 0.2 SNP/genome/year derived from a Peruvian mummy; short-term = 0.5 SNP/genome/year). To disentangle between these scenarios, we confronted the corresponding divergence times with major human history events and knowledge on human genetic divergence. We identified relatively high intrasublineage diversity for both T3-Osaka and Tur. We definitively proved their monophyly; the corresponding super-sublineage (referred to as “T3-Osa-Tur”) shares a common ancestor with T3-Ethiopia and Ural sublineages but is only remotely related to other Euro-American sublineages such as X, LAM, Haarlem and S. The evolutionary scenario based on long-term evolution rate being valid until T3-Osa-Tur MRCA was not supported by Japanese fossil data. The evolutionary scenario relying on short-term evolution rate since T3-Osa-Tur MRCA was contradicted by human history and potential traces of past epidemics. T3-Osaka and Tur sublineages were found likely to have diverged between 800 y and 2000 years ago, potentially at the time of Mongol Empire. Altogether, this study definitively proves a strong genetic link between Turkish and Japanese tuberculosis. It provides a first hypothesis for calibrating TB Euro-American lineage molecular clock; additional studies are needed to reliably date events corresponding to intermediate depths in tuberculosis phylogeny. © 2016 Elsevier B.V., Research Councils UK King Abdullah University of Science and Technology, This study was financed by UMR9198, CEA-CNRS-UPS, Institut de Biologie Intégrative de la Cellule, Gif-sur-Yvette, France . GR and CS hold respectively an assistant professorship and a full professorship position at University Paris-Sud. No competitive interest is to be declared. JP is supported by a BBSRC UK PhD studentship. TGC is funded by the Medical Research Council UK (Grant no. MR/K000551/1 , MR/M01360X/1 , MR/N010469/1 )., This work was initiated in 2005 in the Institut Pasteur of Guadeloupe, and Dr. Nalin Rastogi and Dr. Riza Durmaz are acknowledged for material support, stimulating discussions, and/or for having initiated long-term collaborative studies on MTBC DNA from Turkey. During the 2007–2008 period, T. Dos Vultos, J. Rauzier and B. Gicquel through the extensive 3R MTBC gene diversity study, provided an important advance to the T3-Osa-Tur hypothesis by providing confirmatory preliminary results. Technical support was provided by the Luminex Corp. (Austin, TX) for SNP genotyping, and by King Abdullah University of Science and Technology (KAUST) for Whole Genome Sequencing. GR and CS acknowledge recurrent support from CNRS-Univ. Paris-Sud.

Background The ongoing epidemic of multidrug-resistant tuberculosis (MDR-TB) in Georgia highlights the need for more effective control strategies. A new regimen to treat MDR-TB that includes pyrazinamide (PZA) is currently being evaluated and PZA resistance status will largely influence the success of current and future treatment strategies. PZA susceptibility testing was not routinely performed at the National Reference Laboratory (NRL) in Tbilisi between 2010 and September 2015. We here provide a first insight into the prevalence of PZA resistant TB in this region. Methods Phenotypic susceptibility to PZA was determined in a convenience collection of well-characterised TB patient isolates collected at the NRL in Tbilisi between 2012 and 2013. In addition, the pncA gene was sequenced and whole genome sequencing was performed on two isolates. Results Out of 57 isolates tested 33 (57.9%) showed phenotypic drug resistance to PZA and had a single pncA mutation. All of these 33 isolates were MDR-TB strains. pncA mutations were absent in all but one of the 24 PZA susceptible isolate. In total we found 18 polymorphisms in the pncA gene. From the two major MDR-TB clusters represented (94–32 and 100–32), 10 of 15, 67.0% and 13 of 14, 93.0% strains, respectively were PZA resistant. We also identified a member of the potentially highly transmissive clade A strain carrying the characteristic I6L substitution in PncA. Another strain with the same MLVA type as the clade A strain acquired a different mutation in pncA and was genetically more distantly related suggesting that different branches of this particular lineage have been introduced into this region. Conclusion In this high MDR-TB setting more than half of the tested MDR-TB isolates were resistant to PZA. As PZA is part of current and planned MDR-TB treatment regimens this is alarming and deserves the attention of health authorities. Based on our typing and sequence analysis results we conclude that PZA resistance is the result of primary transmission as well as acquisition within the patient and recommend prospective genotyping and PZA resistance testing in high MDR-TB settings. This is of utmost importance in order to preserve bacterial susceptibility to PZA to help protect (new) second line drugs in PZA containing regimens.

Background Combating the spread of drug resistant tuberculosis is a global health priority. Whole genome association studies are being applied to identify genetic determinants of resistance to anti-tuberculosis drugs. Protein structure and interaction modelling are used to understand the functional effects of putative mutations and provide insight into the molecular mechanisms leading to resistance. Methods To investigate the potential utility of these approaches, we analysed the genomes of 144 Mycobacterium tuberculosis clinical isolates from The Special Programme for Research and Training in Tropical Diseases (TDR) collection sourced from 20 countries in four continents. A genome-wide approach was applied to 127 isolates to identify polymorphisms associated with minimum inhibitory concentrations for first-line anti-tuberculosis drugs. In addition, the effect of identified candidate mutations on protein stability and interactions was assessed quantitatively with well-established computational methods. Results The analysis revealed that mutations in the genes rpoB (rifampicin), katG (isoniazid), inhA-promoter (isoniazid), rpsL (streptomycin) and embB (ethambutol) were responsible for the majority of resistance observed. A subset of the mutations identified in rpoB and katG were predicted to affect protein stability. Further, a strong direct correlation was observed between the minimum inhibitory concentration values and the distance of the mutated residues in the three-dimensional structures of rpoB and katG to their respective drugs binding sites. Conclusions Using the TDR resource, we demonstrate the usefulness of whole genome association and convergent evolution approaches to detect known and potentially novel mutations associated with drug resistance. Further, protein structural modelling could provide a means of predicting the impact of polymorphisms on drug efficacy in the absence of phenotypic data. These approaches could ultimately lead to novel resistance mutations to improve the design of tuberculosis control measures, such as diagnostics, and inform patient management. Electronic supplementary material The online version of this article (doi:10.1186/s12916-016-0575-9) contains supplementary material, which is available to authorized users.

Background Approximately 10 % of the Mycobacterium tuberculosis genome is made up of two families of genes that are poorly characterized due to their high GC content and highly repetitive nature. The PE and PPE families are typified by their highly conserved N-terminal domains that incorporate proline-glutamate (PE) and proline-proline-glutamate (PPE) signature motifs. They are hypothesised to be important virulence factors involved with host-pathogen interactions, but their high genetic variability and complexity of analysis means they are typically disregarded in genome studies. Results To elucidate the structure of these genes, 518 genomes from a diverse international collection of clinical isolates were de novo assembled. A further 21 reference M. tuberculosis complex genomes and long read sequence data were used to validate the approach. SNP analysis revealed that variation in the majority of the 168 pe/ppe genes studied was consistent with lineage. Several recombination hotspots were identified, notably pe_pgrs3 and pe_pgrs17. Evidence of positive selection was revealed in 65 pe/ppe genes, including epitopes potentially binding to major histocompatibility complex molecules. Conclusions This, the first comprehensive study of the pe and ppe genes, provides important insight into M. tuberculosis diversity and has significant implications for vaccine development. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-2467-y) contains supplementary material, which is available to authorized users.

Background The Americas were the last continent colonized by humans carrying malaria parasites. Plasmodium falciparum from the New World shows very little genetic diversity and greater linkage disequilibrium, compared with its African counterparts, and is clearly subdivided into local, highly divergent populations. However, limited available data have revealed extensive genetic diversity in American populations of another major human malaria parasite, P. vivax. Methods We used an improved sample preparation strategy and next-generation sequencing to characterize 9 high-quality P. vivax genome sequences from northwestern Brazil. These new data were compared with publicly available sequences from recently sampled clinical P. vivax isolates from Brazil (BRA, total n = 11 sequences), Peru (PER, n = 23), Colombia (COL, n = 31), and Mexico (MEX, n = 19). Principal findings/Conclusions We found that New World populations of P. vivax are as diverse (nucleotide diversity π between 5.2 × 10−4 and 6.2 × 10−4) as P. vivax populations from Southeast Asia, where malaria transmission is substantially more intense. They display several non-synonymous nucleotide substitutions (some of them previously undescribed) in genes known or suspected to be involved in antimalarial drug resistance, such as dhfr, dhps, mdr1, mrp1, and mrp-2, but not in the chloroquine resistance transporter ortholog (crt-o) gene. Moreover, P. vivax in the Americas is much less geographically substructured than local P. falciparum populations, with relatively little between-population genome-wide differentiation (pairwise FST values ranging between 0.025 and 0.092). Finally, P. vivax populations show a rapid decline in linkage disequilibrium with increasing distance between pairs of polymorphic sites, consistent with very frequent outcrossing. We hypothesize that the high diversity of present-day P. vivax lineages in the Americas originated from successive migratory waves and subsequent admixture between parasite lineages from geographically diverse sites. Further genome-wide analyses are required to test the demographic scenario suggested by our data., Author summary Plasmodium vivax is the most common human malaria parasite in the Americas, but how and when this species arrived in the New World remains unclear. Here we describe high-quality whole-genome sequence data for nine P. vivax isolates from Brazil, a country that accounts for 37% of the malaria burden in this continent, and compare these data with additional publicly available P. vivax genomes from Brazil, Peru, Colombia, and Mexico. P. vivax populations from the New World were found to be as diverse as their counterparts from areas with substantially higher malaria transmission, such as Southeast Asia, and to carry several non-synonymous substitutions in candidate drug-resistance genes. Moreover, genome-wide patterns of linkage disequilibrium between pairs of polymorphic sites are consistent with very frequent outcrossing in these populations. Interestingly, local P. vivax is more polymorphic, with less between-population differentiation, than sympatric populations of P. falciparum, possibly as a result of different demographic histories of these two species in the Americas. We hypothesize that local P. vivax lineages originated from successive migratory waves and subsequent admixture between parasites from geographically diverse sites.