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BackgroundIn the last two decades, India has witnessed a substantial decrease in infant mortality attributed to infectious disease and malnutrition. However, the mortality attributed to birth defects remains constant. Studies on the prevalence of birth defects such as neural tube defects and orofacial clefts in India have reported inconsistent results. Therefore, we conducted a systematic review of observational studies to document the birth prevalence of neural tube defects and orofacial clefts.MethodsA comprehensive literature search for observational studies was conducted in MEDLINE and EMBASE databases using key MeSH terms (neural tube defects OR cleft lip OR cleft palate AND Prevalence AND India). Two reviewers independently reviewed the retrieved studies, and studies satisfying the eligibility were included. The quality of included studies was assessed using selected criteria from STROBE statement.ResultsThe overall pooled birth prevalence (random effect) of neural tube defects in India is 4.5 per 1000 total births (95% CI 4.2 to 4.9). The overall pooled birth prevalence (random effect) of orofacial clefts is 1.3 per 1000 total births (95% CI 1.1 to 1.5). Subgroup analyses were performed by region, time period, consanguinity, and gender of newborn.ConclusionThe overall prevalence of neural tube defects from India is high compared to other regions of the world, while that of orofacial clefts is similar to other countries. The majority of studies included in the review were hospital based. The quality of these studies ranged from low to moderate. Further well-designed, high quality community-based observational studies are needed to accurately estimate the burden of neural tube defects and orofacial clefts in India.

Genome-wide association studies (GWAS) have begun to identify the common genetic component to ischaemic stroke (IS). However, IS has considerable phenotypic heterogeneity. Where clinical covariates explain a large fraction of disease risk, covariate informed designs can increase power to detect associations. As prevalence rates in IS are markedly affected by age, and younger onset cases may have higher genetic predisposition, we investigated whether an age-at-onset informed approach could detect novel associations with IS and its subtypes; cardioembolic (CE), large artery atherosclerosis (LAA) and small vessel disease (SVD) in 6,778 cases of European ancestry and 12,095 ancestry-matched controls. Regression analysis to identify SNP associations was performed on posterior liabilities after conditioning on age-at-onset and affection status. We sought further evidence of an association with LAA in 1,881 cases and 50,817 controls, and examined mRNA expression levels of the nearby genes in atherosclerotic carotid artery plaques. Secondly, we performed permutation analyses to evaluate the extent to which age-at-onset informed analysis improves significance for novel loci. We identified a novel association with an MMP12 locus in LAA (rs660599; p = 2.5×10⁻⁷), with independent replication in a second population (p = 0.0048, OR(95% CI) = 1.18(1.05-1.32); meta-analysis p = 2.6×10⁻⁸). The nearby gene, MMP12, was significantly overexpressed in carotid plaques compared to atherosclerosis-free control arteries (p = 1.2×10⁻¹⁵; fold change = 335.6). Permutation analyses demonstrated improved significance for associations when accounting for age-at-onset in all four stroke phenotypes (p

Background Although Southeast Asia is one of the most leptospirosis afflicted regions, little is known about the diversity and molecular epidemiology of the causative agents of this widespread and emerging zoonotic disease. Methodology/Principal findings We used whole genome sequencing to examine genetic variation in 75 Leptospira strains isolated from patients in the Lao PDR (Laos) between 2006 and 2017. Eleven serogroups from 4 Leptospira species and 43 cgMLST-defined clonal groups (CGs) were identified. The most prevalent CG was CG272 (n = 18, 26.8%), composed of L. interrogans serogroup Autumnalis isolates. This genotype was recovered throughout the 12-year period and was associated with deaths, and with a large outbreak in neighbouring Thailand. Genome analysis reveals that the CG272 strains form a highly clonal group of strains that have, for yet unknown reasons, recently spread in Laos and Thailand. Additionally, accessory genes clearly discriminate CG272 strains from the other Leptospira strains. Conclusions/Significance The present study reveals a high diversity of Leptospira genotypes in Laos, thus extending our current knowledge of the pan- and core-genomes of these life-threatening pathogens. Our results demonstrate that the CG272 strains belong to a unique clonal group, which probably evolved through clonal expansion following niche adaptation. Additional epidemiological studies are required to better evaluate the spread of this genotype in Southeast Asia. To further investigate the key factors driving the virulence and spread of these pathogens, more intense genomic surveillance is needed, combining detailed clinical and epidemiological data., Author summary Pathogenic Leptospira are the causative agents for leptospirosis, a neglected and emerging zoonosis occurring worldwide. In this study, we investigated the genetic diversity of Leptospira strains isolated from patients over a 12-year period in Lao PDR. Our genome analysis revealed a high diversity of Leptospira genotypes in this endemic country for leptospirosis, including a group of clonal strains which was responsible for a large outbreak in neighboring Thailand. Further progress in our understanding of the epidemiology of Leptospira circulating genotypes should contribute to the implementation of prevention and intervention measures to reduce the risk of leptospirosis transmission.

One of the most influential accounts of central orbitofrontal cortex—that it mediates behavioral flexibility—has been challenged by the finding that discrimination reversal in macaques, the classic test of behavioral flexibility, is unaffected when lesions are made by excitotoxin injection rather than aspiration. This suggests that the critical brain circuit mediating behavioral flexibility in reversal tasks lies beyond the central orbitofrontal cortex. To determine its identity, a group of nine macaques were taught discrimination reversal learning tasks, and its impact on gray matter was measured. Magnetic resonance imaging scans were taken before and after learning and compared with scans from two control groups, each comprising 10 animals. One control group learned discrimination tasks that were similar but lacked any reversal component, and the other control group engaged in no learning. Gray matter changes were prominent in posterior orbitofrontal cortex/anterior insula but were also found in three other frontal cortical regions: lateral orbitofrontal cortex (orbital part of area 12 [12o]), cingulate cortex, and lateral prefrontal cortex. In a second analysis, neural activity in posterior orbitofrontal cortex/anterior insula was measured at rest, and its pattern of coupling with the other frontal cortical regions was assessed. Activity coupling increased significantly in the reversal learning group in comparison with controls. In a final set of experiments, we used similar structural imaging procedures and analyses to demonstrate that aspiration lesion of central orbitofrontal cortex, of the type known to affect discrimination learning, affected structure and activity in the same frontal cortical circuit. The results identify a distributed frontal cortical circuit associated with behavioral flexibility., The classical idea that central orbitofrontal cortex (cOFC) mediates behavioral flexibility has been recently challenged. This study provides further such evidence, identifying a neural network associated with behavioral flexibility centered on lateral OFC/anterior insula and subcortical regions such as the amygdala.

Background With no effective treatments for cognitive decline or dementia, improving the evidence base for modifiable risk factors is a research priority. This study investigated associations between risk factors and late-life cognitive decline on a global scale, including comparisons between ethno-regional groups. Methods and findings We harmonized longitudinal data from 20 population-based cohorts from 15 countries over 5 continents, including 48,522 individuals (58.4% women) aged 54–105 (mean = 72.7) years and without dementia at baseline. Studies had 2–15 years of follow-up. The risk factors investigated were age, sex, education, alcohol consumption, anxiety, apolipoprotein E ε4 allele (APOE*4) status, atrial fibrillation, blood pressure and pulse pressure, body mass index, cardiovascular disease, depression, diabetes, self-rated health, high cholesterol, hypertension, peripheral vascular disease, physical activity, smoking, and history of stroke. Associations with risk factors were determined for a global cognitive composite outcome (memory, language, processing speed, and executive functioning tests) and Mini-Mental State Examination score. Individual participant data meta-analyses of multivariable linear mixed model results pooled across cohorts revealed that for at least 1 cognitive outcome, age (B = −0.1, SE = 0.01), APOE*4 carriage (B = −0.31, SE = 0.11), depression (B = −0.11, SE = 0.06), diabetes (B = −0.23, SE = 0.10), current smoking (B = −0.20, SE = 0.08), and history of stroke (B = −0.22, SE = 0.09) were independently associated with poorer cognitive performance (p < 0.05 for all), and higher levels of education (B = 0.12, SE = 0.02) and vigorous physical activity (B = 0.17, SE = 0.06) were associated with better performance (p < 0.01 for both). Age (B = −0.07, SE = 0.01), APOE*4 carriage (B = −0.41, SE = 0.18), and diabetes (B = −0.18, SE = 0.10) were independently associated with faster cognitive decline (p < 0.05 for all). Different effects between Asian people and white people included stronger associations for Asian people between ever smoking and poorer cognition (group by risk factor interaction: B = −0.24, SE = 0.12), and between diabetes and cognitive decline (B = −0.66, SE = 0.27; p < 0.05 for both). Limitations of our study include a loss or distortion of risk factor data with harmonization, and not investigating factors at midlife. Conclusions These results suggest that education, smoking, physical activity, diabetes, and stroke are all modifiable factors associated with cognitive decline. If these factors are determined to be causal, controlling them could minimize worldwide levels of cognitive decline. However, any global prevention strategy may need to consider ethno-regional differences., Darren Lipnicki and the Sydney COSMIC team analysed cognitive performance and risk factor data from older people from 15 countries to assess associations between risk factors and late-life cognition, Author summary Why was this study done? There is a growing global burden associated with cognitive decline and dementia. Evidence for modifiable risk factors that could be targeted to reduce this burden needs to be improved. Risk factors for cognitive decline and dementia might differ between ethno-regional groups. What did the researchers do and find? We analyzed cognitive performance and risk factor data from 48,522 older individuals, provided by 20 studies of aging representing 15 countries (Australia, Brazil, Cuba, France, Germany, Greece, Hong Kong, Italy, Japan, Singapore, Spain, South Korea, The Netherlands, the United Kingdom, and the United States). Cognitive performance was measured as Mini-Mental State Examination (MMSE) and global cognition scores. When controlling for confounding risk factors, the apolipoprotein E ε4 allele (APOE*4), depression, diabetes, current smoking, and history of stroke were associated with poorer cognitive performance, and higher levels of education and vigorous physical activity were associated with better performance. Age, APOE*4, and diabetes were associated with faster cognitive decline. Compared to white people, Asian people showed stronger associations between having ever smoked and cognitive performance, and between diabetes and cognitive decline. What do these findings mean? Modifiable risk factors associated with cognitive decline include education, smoking, physical activity, diabetes, and stroke. If these associations are determined to be causal, interventions targeting these factors may help reduce the global burden of cognitive decline and dementia. Interventions may require tailoring to particular ethno-regional groups.

Background The countries of West Africa are largely portrayed as cholera endemic, although the dynamics of outbreaks in this region of Africa remain largely unclear. Methodology/Principal findings To understand the dynamics of cholera in a major portion of West Africa, we analyzed cholera epidemics from 2009 to 2015 from Benin to Mauritania. We conducted a series of field visits as well as multilocus variable tandem repeat analysis and whole-genome sequencing analysis of V. cholerae isolates throughout the study region. During this period, Ghana accounted for 52% of the reported cases in the entire study region (coastal countries from Benin to Mauritania). From 2009 to 2015, we found that one major wave of cholera outbreaks spread from Accra in 2011 northwestward to Sierra Leone and Guinea in 2012. Molecular epidemiology analysis confirmed that the 2011 Ghanaian isolates were related to those that seeded the 2012 epidemics in Guinea and Sierra Leone. Interestingly, we found that many countries deemed “cholera endemic” actually suffered very few outbreaks, with multi-year lulls. Conclusions/Significance This study provides the first cohesive vision of the dynamics of cholera epidemics in a major portion of West Africa. This epidemiological overview shows that from 2009 to 2015, at least 54% of reported cases concerned populations living in the three urban areas of Accra, Freetown, and Conakry. These findings may serve as a guide to better target cholera prevention and control efforts in the identified cholera hotspots in West Africa., Author summary We analyzed cholera epidemics from Benin to Mauritania, during 2009 to 2015, and performed a series of field visits as well as molecular epidemiology analyses of V. cholerae isolates from most recent epidemics throughout West Africa. We found that at least 54% of cases concerned populations living in the three urban areas of Accra, Freetown, and Conakry. Accra, Ghana represented the main cholera hotspot in the entire study region. Our findings indicate that the water network system in Accra may play a role in the rapid diffusion of cholera throughout the city. As observed in Accra, Conakry, and Freetown, once cholera cases arrive in overpopulated urban settings with poor sanitation, increased rainfall facilitated the contamination of unprotected water sources with human waste from cholera patients, thus promoting a rapid increase in cholera incidence. To more efficiently and effectively combat cholera in West Africa, these findings may serve as a guide to better target cholera prevention and control interventions.

Background The burden of typhoid in sub-Saharan African (SSA) countries has been difficult to estimate, in part, due to suboptimal laboratory diagnostics. However, surveillance blood cultures at two sites in Nigeria have identified typhoid associated with Salmonella enterica serovar Typhi (S. Typhi) as an important cause of bacteremia in children. Methods A total of 128 S. Typhi isolates from these studies in Nigeria were whole-genome sequenced, and the resulting data was used to place these Nigerian isolates into a worldwide context based on their phylogeny and carriage of molecular determinants of antibiotic resistance. Results Several distinct S. Typhi genotypes were identified in Nigeria that were related to other clusters of S. Typhi isolates from north, west and central regions of Africa. The rapidly expanding S. Typhi clade 4.3.1 (H58) previously associated with multiple antimicrobial resistances in Asia and in east, central and southern Africa, was not detected in this study. However, antimicrobial resistance was common amongst the Nigerian isolates and was associated with several plasmids, including the IncHI1 plasmid commonly associated with S. Typhi. Conclusions These data indicate that typhoid in Nigeria was established through multiple independent introductions into the country, with evidence of regional spread. MDR typhoid appears to be evolving independently of the haplotype H58 found in other typhoid endemic countries. This study highlights an urgent need for routine surveillance to monitor the epidemiology of typhoid and evolution of antimicrobial resistance within the bacterial population as a means to facilitate public health interventions to reduce the substantial morbidity and mortality of typhoid., Author Summary Typhoid fever, a serious bloodstream infection caused by the bacterium Salmonella Typhi, is a major cause of disease and death around the world. There have been limited data on the epidemiology of typhoid in many countries in sub-Saharan African, including Nigeria. Recent evidence, however, showed that typhoid was an important cause of bacteraemia in children residing in two regions of Nigeria. Here, we analyzed the whole genome sequences of 128 S. Typhi isolates from two studies in order to elucidate the population structure and characterize the genetic components of antimicrobial resistance. We found that the multiple S. Typhi genotypes identified were closely related to other S. Typhi from neighboring regions of Africa and that multidrug resistance (MDR) was common among these isolates, and in many cases was associated with the IncHI1 plasmid known to cause MDR typhoid. These results provide evidence that typhoid was established in Nigeria as a result of several independent introductions into the country and that there has been extensive exchange of S. Typhi in and around the region of West Africa. This study emphasizes the importance of surveillance to improve our understanding of the epidemiology of typhoid, which is needed to underpin public health measures to reduce the spread of disease and facilitate patient management.

International audience; The ICF syndrome is a rare autosomal recessive disorder, the most common symptoms of which are immunodeficiency, facial anomalies and cytogenetic defects involving decondensation and instability of chromosome 1, 9 and 16 centromeric regions. ICF is also characterised by significant hypomethylation of the classical satellite DNA, the major constituent of the juxtacentromeric heterochromatin. Here we report the first attempt at analysing some of the defining genetic and epigenetic changes of this syndrome from a nuclear architecture perspective. In particular, we have compared in ICF ( Type 1 and Type 2) and controls the large-scale organisation of chromosome 1 and 16 juxtacentromeric heterochromatic regions, their intra-nuclear positioning, and co-localisation with five specific genes (BTG2, CNN3, ID3, RGS1, F13A1), on which we have concurrently conducted expression and methylation analysis. Our investigations, carried out by a combination of molecular and cytological techniques, demonstrate the existence of specific and quantifiable differences in the genomic and nuclear organisation of the juxtacentromeric heterochromatin in ICF. DNA hypomethylation, previously reported to correlate with the decondensation of centromeric regions in metaphase described in these patients, appears also to correlate with the heterochromatin spatial configuration in interphase. Finally, our findings on the relative positioning of hypomethylated satellite sequences and abnormally expressed genes suggest a connection between disruption of long-range geneheterochromatin associations and some of the changes in gene expression in ICF. Beyond its relevance to the ICF syndrome, by addressing fundamental principles of chromosome functional organisation within the cell nucleus, this work aims to contribute to the current debate on the epigenetic impact of nuclear architecture in development and disease.

The classic organization of a gene structure has followed the Jacob and Monod bacterial gene model proposed more than 50 years ago. Since then, empirical determinations of the complexity of the transcriptomes found in yeast to human has blurred the definition and physical boundaries of genes. Using multiple analysis approaches we have characterized individual gene boundaries mapping on human chromosomes 21 and 22. Analyses of the locations of the 5' and 3' transcriptional termini of 492 protein coding genes revealed that for 85% of these genes the boundaries extend beyond the current annotated termini, most often connecting with exons of transcripts from other well annotated genes. The biological and evolutionary importance of these chimeric transcripts is underscored by (1) the non-random interconnections of genes involved, (2) the greater phylogenetic depth of the genes involved in many chimeric interactions, (3) the coordination of the expression of connected genes and (4) the close in vivo and three dimensional proximity of the genomic regions being transcribed and contributing to parts of the chimeric RNAs. The non-random nature of the connection of the genes involved suggest that chimeric transcripts should not be studied in isolation, but together, as an RNA network. This work has been supported by grants U01HG003150 and U01HG003147 from the National Human Genome Research for the ENCODE project. RG was also supported by a grant from the Spanish Ministry of Education and Science. In addition, KS-A, RM, XY, CL, LG and MV were supported by a grant from the Ellison Foundation and as Institute Sponsored Research from the Dana Farber Cancer Institute Strategic Initiative. The laboratories of SA and AR were supported by grants from the Swiss National Science Foundation and the European Commission AnEUploidy Integrated Project. SA was also supported by the National Center of Excellence ‘‘Frontiers in Genetics’’, ChildCare Foundation and an ERC grant from the European Union. AF, TH and JM acknowledge support from the Wellcome Trust. The work of JLG and MO has been supported by the Spanish Ministry of Science (CTQ2005-09365-C02-02, BIO2009-10964), Instituto Nacional de Bioinformática, the Consolider E-science project (CSD2007-00050), COMBIOMED RETICS and the Fundación Marcelino Botin. JD is supported by a grant from the National Institutes of Health (HG003143) and a W. M. Keck Foundation Distinguished Young Scholar Award. JS is supported by a grant from the National Institutes of Health (U54 HG004592). The work of MT and AV was supported by Consolider E-Science (CSD2007-00050) and the Instituto Nacional de Bioinformática. MV (Center for Cancer Systems Biology, CCSB) is a ‘‘Chercheur Qualifié Honoraire’’ from the Fonds de la Recherche Scientifique (FRS-FNRS, French Community of Belgium). This work has also been funded by grant to TG by NHGRI (U54HG004557) and partially byAffymetirix, Corp

Salmonella enterica subspecies enterica is traditionally subdivided into serovars by serological and nutritional characteristics. We used Multilocus Sequence Typing (MLST) to assign 4,257 isolates from 554 serovars to 1092 sequence types (STs). The majority of the isolates and many STs were grouped into 138 genetically closely related clusters called eBurstGroups (eBGs). Many eBGs correspond to a serovar, for example most Typhimurium are in eBG1 and most Enteritidis are in eBG4, but many eBGs contained more than one serovar. Furthermore, most serovars were polyphyletic and are distributed across multiple unrelated eBGs. Thus, serovar designations confounded genetically unrelated isolates and failed to recognize natural evolutionary groupings. An inability of serotyping to correctly group isolates was most apparent for Paratyphi B and its variant Java. Most Paratyphi B were included within a sub-cluster of STs belonging to eBG5, which also encompasses a separate sub-cluster of Java STs. However, diphasic Java variants were also found in two other eBGs and monophasic Java variants were in four other eBGs or STs, one of which is in subspecies salamae and a second of which includes isolates assigned to Enteritidis, Dublin and monophasic Paratyphi B. Similarly, Choleraesuis was found in eBG6 and is closely related to Paratyphi C, which is in eBG20. However, Choleraesuis var. Decatur consists of isolates from seven other, unrelated eBGs or STs. The serological assignment of these Decatur isolates to Choleraesuis likely reflects lateral gene transfer of flagellar genes between unrelated bacteria plus purifying selection. By confounding multiple evolutionary groups, serotyping can be misleading about the disease potential of S. enterica. Unlike serotyping, MLST recognizes evolutionary groupings and we recommend that Salmonella classification by serotyping should be replaced by MLST or its equivalents., Author Summary Microbiologists have used serological and nutritional characteristics to subdivide pathogenic bacteria for nearly 100 years. These subdivisions in Salmonella enterica are called serovars, some of which are thought to be associated with particular diseases and epidemiology. We used MultiLocus Sequence-based Typing (MLST) to identify clusters of S. enterica isolates that are related by evolutionary descent. Some clusters correspond to serovars on a one to one basis. But many clusters include multiple serovars, which is of public health significance, and most serovars span multiple, unrelated clusters. Despite its broad usage, serological typing of S. enterica has resulted in confusing systematics, with a few exceptions. We recommend that serotyping for strain discrimination of S. enterica be replaced by a DNA-based method, such as MLST. Serotyping and other non-sequence based typing methods are routinely used for detecting outbreaks and to support public health responses. Moving away from these methods will require a major shift in thinking by public health microbiology laboratories as well as national and international agencies. However, a transition to the routine use of MLST, supplemented where appropriate by even more discriminatory sequence-based typing methods based on entire genomes, will provide a clearer picture of long-term transmission routes of Salmonella, facilitate data transfer and support global control measures.

Multiple Sclerosis (MS) is the most common progressive and disabling neurological condition affecting young adults in the world today. From a genetic point of view, MS is a complex disorder resulting from the combination of genetic and non-genetic factors. We aimed to identify previously unidentified loci conducting a new GWAS of Multiple Sclerosis (MS) in a sample of 296 MS cases and 801 controls from the Spanish population. Meta-analysis of our data in combination with previous GWAS was done. A total of 17 GWAS-significant SNPs, corresponding to three different loci were identified:HLA, IL2RA, and 5p13.1. All three have been previously reported as GWAS-significant. We confirmed our observation in 5p13.1 for rs9292777 using two additional independent Spanish samples to make a total of 4912 MS cases and 7498 controls (ORpooled = 0.84; 95%CI: 0.80-0.89; p = 1.36×10-9). This SNP differs from the one reported within this locus in a recent GWAS. Although it is unclear whether both signals are tapping the same genetic association, it seems clear that this locus plays an important role in the pathogenesis of MS. © 2012 Matesanz et al.

International audience; Background: The HapMap samples were collected for medical-genetic studies, but are also widely used in populationgenetic and evolutionary investigations. Yet the ascertainment of the samples differs from most population-genetic studies which collect individuals who live in the same local region as their ancestors. What effects could this non-standard ascertainment have on the interpretation of HapMap results? Methodology/Principal Findings: We compared the HapMap samples with more conventionally-ascertained samples used in population-and forensic-genetic studies, including the HGDP-CEPH panel, making use of published genome-wide autosomal SNP data and Y-STR haplotypes, as well as producing new Y-STR data. We found that the HapMap samples were representative of their broad geographical regions of ancestry according to all tests applied. The YRI and JPT were indistinguishable from independent samples of Yoruba and Japanese in all ways investigated. However, both the CHB and the CEU were distinguishable from all other HGDP-CEPH populations with autosomal markers, and both showed Y-STR similarities to unusually large numbers of populations, perhaps reflecting their admixed origins. Conclusions/Significance: The CHB and JPT are readily distinguished from one another with both autosomal and Ychromosomal markers, and results obtained after combining them into a single sample should be interpreted with caution. The CEU are better described as being of Western European ancestry than of Northern European ancestry as often reported. Both the CHB and CEU show subtle but detectable signs of admixture. Thus the YRI and JPT samples are well-suited to standard population-genetic studies, but the CHB and CEU less so.

Background Yellow fever (YF) is an arboviral disease which is endemic to Brazil due to a sylvatic transmission cycle maintained by infected mosquito vectors, non-human primate (NHP) hosts, and humans. Despite the existence of an effective vaccine, recent sporadic YF epidemics have underscored concerns about sylvatic vector surveillance, as very little is known about their spatial distribution. Here, we model and map the environmental suitability of YF’s main vectors in Brazil, Haemagogus spp. and Sabethes spp., and use human population and NHP data to identify locations prone to transmission and spillover risk. Methodology/Principal findings We compiled a comprehensive set of occurrence records on Hg. janthinomys, Hg. leucocelaenus, and Sabethes spp. from 1991–2019 using primary and secondary data sources. Linking these data with selected environmental and land-cover variables, we adopted a stacked regression ensemble modelling approach (elastic-net regularized GLM, extreme gradient boosted regression trees, and random forest) to predict the environmental suitability of these species across Brazil at a 1 km x 1 km resolution. We show that while suitability for each species varies spatially, high suitability for all species was predicted in the Southeastern region where recent outbreaks have occurred. By integrating data on NHP host reservoirs and human populations, our risk maps further highlight municipalities within the region that are prone to transmission and spillover. Conclusions/Significance Our maps of sylvatic vector suitability can help elucidate potential locations of sylvatic reservoirs and be used as a tool to help mitigate risk of future YF outbreaks and assist in vector surveillance. Furthermore, at-risk regions identified from our work could help disease control and elucidate gaps in vaccination coverage and NHP host surveillance., Author summary Yellow fever virus (YFV) is an arbovirus transmitted to humans from mosquitoes and can lead to severe disease and death. Recent sporadic outbreaks coupled with low vaccination coverage have highlighted the importance of mosquito surveillance for preventing future outbreaks and potential virus spillover into dense urban areas. Yet, very little is known about the spatial distribution of mosquitoes known to transmit YFV and the factors that contribute to their environmental suitability in Brazil. We compiled an occurrence database of primary and secondary mosquito vectors belonging to Haemagogus and Sabethes species’ collected between 1991–2019 and integrated this data with environmental and land-use data to predict their spatial suitability at 1 km x 1 km resolution. Using this information, we identified suitable regions for their co-existence. We overlaid this information with human population density and locations of non-human primate host reservoirs to identify areas at risk of transmission and spillover. Our study provides high-resolution mapping tools to assist with mosquito and arbovirus surveillance which is especially useful in low-resource settings.

© 2021 Ellis et al., Aberrant repair of DNA double-strand breaks can recombine distant chromosomal breakpoints. Chromosomal rearrangements compromise genome function and are a hallmark of ageing. Rearrangements are challenging to detect in non-dividing cell populations, because they reflect individually rare, heterogeneous events. The genomic distribution of de novo rearrangements in non-dividing cells, and their dynamics during ageing, remain therefore poorly characterized. Studies of genomic instability during ageing have focussed on mitochondrial DNA, small genetic variants, or proliferating cells. To characterize genome rearrangements during cellular ageing in non-dividing cells, we interrogated a single diagnostic measure, DNA breakpoint junctions, using Schizosaccharomyces pombe as a model system. Aberrant DNA junctions that accumulated with age were associated with microhomology sequences and R-loops. Global hotspots for age-associated breakpoint formation were evident near telomeric genes and linked to remote breakpoints elsewhere in the genome, including the mitochondrial chromosome. Formation of breakpoint junctions at global hotspots was inhibited by the Sir2 histone deacetylase and might be triggered by an age-dependent de-repression of chromatin silencing. An unexpected mechanism of genomic instability may cause more local hotspots: age-associated reduction in an RNA-binding protein triggering R-loops at target loci. This result suggests that biological processes other than transcription or replication can drive genome rearrangements. Notably, we detected similar signatures of genome rearrangements that accumulated in old brain cells of humans. These findings provide insights into the unique patterns and possible mechanisms of genome rearrangements in non-dividing cells, which can be promoted by ageing-related changes in gene-regulatory proteins., This research was funded by a BBSRC-DTP studentship to DAE (London Interdisciplinary Doctoral Programme) [grant number BB/M009513/1] funded by the Biotechnology and Biological Sciences Research Council (https://bbsrc.ukri.org/); a Wellcome Senior Investigator Award to JB [grant number 095598/Z/11/Z] funded by the Wellcome Trust (https://wellcome.org/); and Medical Research Council funding to SM (https://mrc.ukri.org/).

BackgroundAdolescents tend to experience heightened vulnerability to risky and reckless behavior. Adolescents living in rural settings may often experience poverty and a host of risk factors which can increase their vulnerability to various forms of health risk behavior (HRB). Understanding HRB clustering and its underlying factors among adolescents is important for intervention planning and health promotion. This study examines the co-occurrence of injury and violence, substance use, hygiene, physical activity, and diet-related risk behaviors among adolescents in a rural setting on the Kenyan coast. Specifically, the study objectives were to identify clusters of HRB; based on five categories of health risk behavior, and to identify the factors associated with HRB clustering.MethodsA cross-sectional survey was conducted of a random sample of 1060 adolescents aged 13–19 years living within the area covered by the Kilifi Health and Demographic Surveillance System. Participants completed a questionnaire on health behaviors which was administered via an Audio Computer-Assisted Self–Interview. Latent class analysis on 13 behavioral factors (injury and violence, hygiene, alcohol tobacco and drug use, physical activity, and dietary related behavior) was used to identify clustering and stepwise ordinal logistic regression with nonparametric bootstrapping identified the factors associated with clustering. The variables of age, sex, education level, school attendance, mental health, form of residence and level of parental monitoring were included in the initial stepwise regression model.ResultsWe identified 3 behavioral clusters (Cluster 1:Low-risk takers (22.9%);Cluster 2:Moderate risk-takers (67.8%);Cluster 3:High risk-takers (9.3%)). Relative to the cluster 1, membership of higher risk clusters (i.e. moderate or high risk-takers) was strongly associated with older age (pConclusionThere is clustering of health risk behaviors that underlies communicable and non-communicable diseases among adolescents in rural coastal Kenya. This suggests the urgent need for targeted multi-component health behavior interventions that simultaneously address all aspects of adolescent health and well-being, including the mental health needs of adolescents.

© 2021 Moore et al. Bioinformatics training is required at every stage of a scientist’s research career. Continual bioinformatics training allows exposure to an ever-changing and growing repertoire of techniques and databases, and so biologists, computational scientists, and healthcare practitioners are all seeking learning opportunities in the use of computational resources and tools designed for data storage, retrieval, and analysis. There are abundant opportunities for accessing bioinformatics training for scientists in high-income countries (HICs), with well-equipped facilities and participants and trainers requiring minimal travel and financial costs alongside a range of general advice for developing short bioinformatics training courses [1–3]. However, regionally targeted bioinformatics training in low- and middle-income countries (LMICs) often requires more extensive local and external support, organization, and travel. Due to the limited expertise in bioinformatics in LMICs in general, most bioinformatics training requires a fair amount of collaboration with experts beyond the local community, country, or region. A common model of training, used as the basis of this article, includes a local host collaborating with local, regional, and international experts gathering to train local or regional participants. Recently, there has been a growth of capacity strengthening initiatives in LMICs, such as the Pan African Bioinformatics Network for Human Heredity and Health in Africa (H3ABioNet) Initiative [4–6], the Capacity Building for Bioinformatics in Latin America (CABANA) Project [7], the Asia Pacific BioInformatics Network (APBioNet) [8], and the Wellcome Connecting Science Courses and Conferences program [9]. One of the important strands of these initiatives is a drive to organize and deliver valuable bioinformatics training, but organizing and delivering short bioinformatics training workshops in an LMIC present a unique set of challenges. This paper attempts to build upon the sage advice for organizing bioinformatics workshops with specific guidance for organizing and delivering them in LMICs. It describes the processes to follow in organizing courses taking into consideration the low-resource setting. We should also note that LMICs are not a monolithic group and that setting, context, temporality, and specific location matters. LMICs are a complex regional grouping [10] and should be treated as such; however, we will present some common lessons that we hope will help organizers and trainers of bioinformatics training events in LMICs to navigate the often different, challenging, and rewarding experience. The authors who contributed to this manuscript are funded as follows: BM receives salary support from Wellcome Trust grants [WT108749/Z/15/Z, WT108749/Z/15/A], PC, VR, NM, AG’s salaries are funded in whole, or in part, by the NIH Common Fund H3ABioNet grant [U24HG006941], MC, SLFV, AR, PG, PCL’s salaries were partly funded by the UKRI-BBSRC ‘Capacity building for bioinformatics in Latin America’ (CABANA) grant, on behalf of the Global Challenges Research Fund [BB/P027849/1], JDLR is funded by ISCiii AES [ref. PI18/00591] at the CSIC/USAL (Spain) and by CYTED, RIABIO (Red Iberoamericana 521RT0118), AM’s salary is funded by [WT206194/Z/17/Z], GO is funded by the CABANA grant and SM is funded by the EMBL-EBI.

Background Lateral flow urine lipoarabinomannan (LAM) tests could offer important new opportunities for the early detection of tuberculosis (TB). The currently licensed LAM test, Alere Determine TB LAM Ag (‘LF-LAM’), performs best in the sickest people living with HIV (PLHIV). However, the technology continues to improve, with newer LAM tests, such as Fujifilm SILVAMP TB LAM (‘SILVAMP-LAM’) showing improved sensitivity, including amongst HIV-negative patients. It is important to anticipate the epidemiological impact that current and future LAM tests may have on TB incidence and mortality. Methods and findings Concentrating on South Africa, we examined the impact that widening LAM test eligibility would have on TB incidence and mortality. We developed a mathematical model of TB transmission to project the impact of LAM tests, distinguishing ‘current’ tests (with sensitivity consistent with LF-LAM), from hypothetical ‘future’ tests (having sensitivity consistent with SILVAMP-LAM). We modelled the impact of both tests, assuming full adoption of the 2019 WHO guidelines for the use of these tests amongst those receiving HIV care. We also simulated the hypothetical deployment of future LAM tests for all people presenting to care with TB symptoms, not restricted to PLHIV. Our model projects that 2,700,000 (95% credible interval [CrI] 2,000,000–3,600,000) and 420,000 (95% CrI 350,000–520,000) cumulative TB incident cases and deaths, respectively, would occur between 2020 and 2035 if the status quo is maintained. Relative to this comparator, current and future LAM tests would respectively avert 54 (95% CrI 33–86) and 90 (95% CrI 55–145) TB deaths amongst inpatients between 2020 and 2035, i.e., reductions of 5% (95% CrI 4%–6%) and 9% (95% CrI 7%–11%) in inpatient TB mortality. This impact in absolute deaths averted doubles if testing is expanded to include outpatients, yet remains, Saskia Ricks and colleagues model the impact of urine-LAM diagnostics for reducing tuberculosis incidence, across different implementation scenarios., Author summary Why was this study done? Although tuberculosis (TB) is often a disease of the lungs, new tests are being developed that can diagnose TB using urine samples alone, and that are simple enough to be used with minimal training. Current urine-based lipoarabinomannan (LAM) tests only perform well in the sickest patients, especially those infected by both TB and HIV. As a result, current WHO guidelines only recommend the use of these tests in specific patient groups. Recent years have seen the emergence of newer LAM tests with improved performance, even amongst patients without HIV infection. There is a need to understand the impact that these LAM tests may have on the TB epidemic across different implementation scenarios. What did the researchers do and find? We developed a mathematical model that captures TB and HIV dynamics in South Africa, a country where 59% of TB cases are coinfected with HIV. We modelled the adoption of 2019 WHO guidelines for the use of the currently licensed LAM test amongst those in HIV care. We also modelled a hypothetical scenario where a future LAM test is used outside HIV care, amongst all patients being tested for TB, regardless of HIV status. When used only to test for TB amongst HIV patients, LAM testing would avert less than 1% of the total TB cases and deaths in South Africa between 2020 and 2035. However, using a future LAM test to test for TB amongst all people with symptoms, regardless of their HIV status, could avert 30% of TB deaths and 18% of TB cases between 2020 and 2035. What do these findings mean? LAM tests can save lives amongst the sickest TB patients. However, to reduce a country’s TB epidemic, future LAM tests will need to have sufficient performance to be deployed more broadly than in HIV care. Future work is needed to determine the cost-effectiveness of deployment as new LAM tests are developed.

Zoonotic diseases affect resource-poor tropical communities disproportionately, and are linked to human use and modification of ecosystems. Disentangling the socio-ecological mechanisms by which ecosystem change precipitates impacts of pathogens is critical for predicting disease risk and designing effective intervention strategies. Despite the global “One Health” initiative, predictive models for tropical zoonotic diseases often focus on narrow ranges of risk factors and are rarely scaled to intervention programs and ecosystem use. This study uses a participatory, co-production approach to address this disconnect between science, policy and implementation, by developing more informative disease models for a fatal tick-borne viral haemorrhagic disease, Kyasanur Forest Disease (KFD), that is spreading across degraded forest ecosystems in India. We integrated knowledge across disciplines to identify key risk factors and needs with actors and beneficiaries across the relevant policy sectors, to understand disease patterns and develop decision support tools. Human case locations (2014–2018) and spatial machine learning quantified the relative role of risk factors, including forest cover and loss, host densities and public health access, in driving landscape-scale disease patterns in a long-affected district (Shivamogga, Karnataka State). Models combining forest metrics, livestock densities and elevation accurately predicted spatial patterns in human KFD cases (2014–2018). Consistent with suggestions that KFD is an “ecotonal” disease, landscapes at higher risk for human KFD contained diverse forest-plantation mosaics with high coverage of moist evergreen forest and plantation, high indigenous cattle density, and low coverage of dry deciduous forest. Models predicted new hotspots of outbreaks in 2019, indicating their value for spatial targeting of intervention. Co-production was vital for: gathering outbreak data that reflected locations of exposure in the landscape; better understanding contextual socio-ecological risk factors; and tailoring the spatial grain and outputs to the scale of forest use, and public health interventions. We argue this inter-disciplinary approach to risk prediction is applicable across zoonotic diseases in tropical settings., Author summary Worldwide, impacts of zoonotic diseases, that cycle between animals and people, are concentrated in tropical communities and often linked to the way people use and change ecosystems. Interventions for zoonotic diseases could be targeted better using risk maps based on computer models that integrate social and ecological risk factors across degraded ecosystems. However, such predictive models often perform poorly at local scales, incorporate narrow ranges of risk factors, and are disconnected from policy, managers and interventions. Co-production brings together stakeholders and knowledge, across the human health, animal health and environmental sectors, aligning with the OneHealth Initiative, to develop more informative predictive tools for zoonotic diseases. Through co-production, we develop predictive models for a fatal tick-borne disease, Kyasanur Forest Diseases (KFD) that is spreading across the degraded Western Ghats forest in India. These models incorporating contextual risk factors identified by stakeholders, accurately predicted patterns in human cases of KFD (2014–2018) in Shivamogga district, Karnataka State, and identified new hotspots of infection during the subsequent 2019 outbreak. Landscapes at highest risk encompassed diverse forest-plantation mosaics with high coverage of moist evergreen forest and plantation, high indigenous cattle density, and low coverage of dry deciduous forest. Co-production resulted in outbreak data that reflected where exposure occurred in the landscape and outputs of value for targeting of interventions, matched to the scale of forest use and public health interventions.

In order to monitor progress towards malaria elimination, it is crucial to be able to measure changes in spatio-temporal transmission. However, common metrics of malaria transmission such as parasite prevalence are under powered in elimination contexts. China has achieved major reductions in malaria incidence and is on track to eliminate, having reporting zero locally-acquired malaria cases in 2017 and 2018. Understanding the spatio-temporal pattern underlying this decline, especially the relationship between locally-acquired and imported cases, can inform efforts to maintain elimination and prevent re-emergence. This is particularly pertinent in Yunnan province, where the potential for local transmission is highest. Using a geo-located individual-level dataset of cases recorded in Yunnan province between 2011 and 2016, we introduce a novel Bayesian framework to model a latent diffusion process and estimate the joint likelihood of transmission between cases and the number of cases with unobserved sources of infection. This is used to estimate the case reproduction number, Rc. We use these estimates within spatio-temporal geostatistical models to map how transmission varied over time and space, estimate the timeline to elimination and the risk of resurgence. We estimate the mean Rc between 2011 and 2016 to be 0.171 (95% CI = 0.165, 0.178) for P. vivax cases and 0.089 (95% CI = 0.076, 0.103) for P. falciparum cases. From 2014 onwards, no cases were estimated to have a Rc value above one. An unobserved source of infection was estimated to be moderately likely (p>0.5) for 19/ 611 cases and high (p>0.8) for 2 cases, suggesting very high levels of case ascertainment. Our estimates suggest that, maintaining current intervention efforts, Yunnan is unlikely to experience sustained local transmission up to 2020. However, even with a mean of 0.005 projected up to 2020, locally-acquired cases are possible due to high levels of importation., Author summary Although malaria is still responsible for a great deal of death and illness in many parts of the world, many national control programmes have made great strides in controlling malaria and now are in a position to aim for elimination. However, in order to monitor progress towards elimination and plan interventions, it is crucial to measure malaria transmission and how it varies over space and time. However, traditional metrics used to measure malaria transmission are not suitable in elimination settings. China is one example of a country approaching elimination, with aims to eliminate the disease by 2020. Using a detailed individual level dataset of the times and locations of people showing symptoms of malaria, we use approaches adapted from the study of how information spreads through social networks to estimate the likelihood of transmission occurring between cases. This information is used to estimate how many people we expect each case to go on to infect. In elimination settings, this number is an indication of how quickly elimination will be reached and how likely we are to see a resurgence in cases once elimination is achieved. Our results show a decline in this metric over time, as well as seasonal changes in transmission which are different to the patterns in when the most cases were observed.

© 2020 Zhong et al., Clustering of the enteropathogenic Escherichia coli (EPEC) type III secretion system (T3SS) effector translocated intimin receptor (Tir) by intimin leads to actin polymerisation and pyroptotic cell death in macrophages. The effect of Tir clustering on the viability of EPEC-infected intestinal epithelial cells (IECs) is unknown. We show that EPEC induces pyroptosis in IECs in a Tir-dependent but actin polymerisation-independent manner, which was enhanced by priming with interferon gamma (IFNγ). Mechanistically, Tir clustering triggers rapid Ca2+ influx, which induces lipopolysaccharide (LPS) internalisation, followed by activation of caspase-4 and pyroptosis. Knockdown of caspase-4 or gasdermin D (GSDMD), translocation of NleF, which blocks caspase-4 or chelation of extracellular Ca2+, inhibited EPEC-induced cell death. IEC lines with low endogenous abundance of GSDMD were resistant to Tir-induced cell death. Conversely, ATP-induced extracellular Ca2+ influx enhanced cell death, which confirmed the key regulatory role of Ca2+ in EPEC-induced pyroptosis. We reveal a novel mechanism through which infection with an extracellular pathogen leads to pyroptosis in IECs., T.I.R and J.S.C are supported by the Cancer Research UK Centre grant C309/A25144. GF is supported a Wellcome Investigator Award 107057/Z/15/Z. QZ is supported by Imperial College President’s PhD Scholarship. GF is supported by a Wellcome Investigator Award (107057/Z/15/Z). T.I.R and J.S.C were funded by the CRUK Centre grant (C309/A25144).

Background West Nile virus (WNV) transmission was much greater in 2018 than in previous seasons in Europe. Focusing on Emilia-Romagna region (northern Italy), we analyzed detailed entomological and epidemiological data collected in 2013–2018 to quantitatively assess environmental drivers of transmission and explore hypotheses to better understand why the 2018 epidemiological season was substantially different than the previous seasons. In particular, in 2018 WNV was detected at least two weeks before the observed circulation in 2013–2017 and in a larger number of mosquito pools. Transmission resulted in 100 neuroinvasive human cases in the region, more than the total number of cases recorded between 2013 and 2017. Methodology We used temperature-driven mathematical models calibrated through a Bayesian approach to simulate mosquito population dynamics and WNV infection rates in the avian population. We then estimated the human transmission risk as the probability, for a person living in the study area, of being bitten by an infectious mosquito in a given week. Finally, we translated such risk into reported WNV human infections. Principal findings The estimated prevalence of WNV in the mosquito and avian populations were significantly higher in 2018 with respect to 2013–2017 seasons, especially in the eastern part of the region. Furthermore, peak avian prevalence was estimated to have occurred earlier, corresponding to a steeper decline towards the end of summer. The high mosquito prevalence resulted in a much greater predicted risk for human transmission in 2018, which was estimated to be up to eight times higher than previous seasons. We hypothesized, on the basis of our modelling results, that such greater WNV circulation might be partially explained by exceptionally high spring temperatures, which have likely helped to amplify WNV transmission at the beginning of the 2018 season., Author summary West Nile virus (WNV) is one of the most recent emerging mosquito-borne diseases in Europe and North America. While most human infections are asymptomatic, about 1% of them can result in severe neurological diseases which might be fatal. WNV transmission was unusually greater in 2018 than in previous years in many European countries, resulting in a large number of human infections. Focusing on Emilia-Romagna region (Italy), we developed an epidemiological model informed by entomological data; through that we found that exceptionally high spring temperatures might have contributed at amplifying WNV transmission at the beginning of the season, causing greater WNV prevalence in mosquito and avian populations during the summer, which resulted in a higher estimated risk for human transmission. Thus, weather anomalies at the beginning of the mosquito breeding season, which are likely to become more common under the projected scenarios of climate change, might act as an early warning signal for public health authorities, enabling them to design efficient surveillance and prevention strategies.

[Background] There are not enough nationwide studies on perinatal HIV transmission in connection with a combination of antiretroviral treatments in Spain. Our objectives were to study sociodemographic changes and trends in the rates of HIV diagnoses and perinatal transmission in Spain from 1997 to 2015., [Methods] A retrospective study using data from Spanish Paediatric HIV Network (CoRISpe) and Spanish Minimum Basic Data Set (MDBS) was performed. HIV- diagnosed children between 1997 and 2015 were selected. Sociodemographic, clinical and immunovirological data of HIV-infected children and their mothers were studied in four calendar periods (P1: 1997–2000; P2: 2001–2005; P3: 2006–2010; P4: 2011–2015). Rates of perinatal HIV diagnoses and transmission from 1997 to 2015 were calculated., [Results] A total of 532 HIV-infected children were included in this study. Of these children, 406 were Spanish (76.3%) and 126 immigrants (23.7%). A decrease in the number of HIV diagnoses, 203 (38.2%) children in the first (P1), 149 (28%) in the second (P2), 130 (24.4%) in the third (P3) and 50 (9.4%) in the fourth (P4) calendar periods was studied. The same decrease in the Spanish HIV-infected children (P1, 174 (46.6%), P2, 115 (30.8%), P3, 65 (17.4%) and P4, 19 (5.1%)) was monitored. However, an increase in the number of HIV diagnoses by sexual contact (P1: 0%; P2: 1.3%; P3: 4.6%; P4: 16%) was observed. The rates of new perinatal HIV diagnoses and perinatal transmission in Spanish children decreased from 0.167 to 0.005 per 100,000 inhabitants and 11.4% to 0.4% between 1997 and 2015, respectively., [Conclusions] A decline of perinatal HIV diagnoses and transmission was observed. However, an increase of teen-agers HIV diagnoses with sexual infection was studied. Public awareness campaigns directed to teen-agers are advisable to prevent HIV infection by sexual contact., This work has been partially funded by Red Temática de Investigación en SIDA (RED RIS) supported by Instituto de Salud Carlos III (ISCIII) (RD12/0017/0035, RD12/0017/0037 and RD16/0025/0019), project as part of the Plan R+D+I (2008–2011; 2013–2016) and cofinanced by ISCIII- Subdirección General de Evaluación and Fondo Europeo de Desarrollo Regional (FEDER), RIS-EPICLIN-19/2015, Fondo para la Investigación Sanitaria of the Spanish Ministry of Science and Innovation (FIS PI13/00422, PI16/01863), CYTED (214RT0482) and EPIICAL Project. CIBER-BBN is an initiative funded by the VI National R&D&I Plan 2008–2011, Iniciativa Ingenio 2010, the Consolider Program, and CIBER Actions and financed by the Instituto de Salud Carlos III with assistance from the European Regional Development Fund. COST CA17140 Cancer Nanomedicine-Front The Bench to Bebside. We thank the Spanish HIV HGM BioBank supported by ISC III project RETIC PT13/0010/0028 and PT17/0015/0042. No funding for this work was received from National Institutes of Health (NIH), Wellcome Trust and Howard Hughes Medical Institute (HHMI).

Background The highest burden of disease from hepatitis C virus (HCV) is found in Southeast Asia, but our understanding of the epidemiology of infection in many heavily burdened countries is still limited. In particular, there is relatively little data on acute HCV infection, the outcome of which can be influenced by both viral and host genetics which differ within the region. We studied HCV genotype and IL28B gene polymorphism in a cohort of acute HCV-infected patients in Southern Vietnam alongside two other cohorts of chronic HCV-infected patients to better understand the epidemiology of HCV infection locally and inform the development of programs for therapy with the increasing availability of directly acting antiviral therapy (DAAs). Methods We analysed plasma samples from patients with acute and chronic HCV infection, including chronic HCV mono-infection and chronic Human Immunodeficiency Virus (HIV)-HCV coinfection, who enrolled in four epidemiological or clinical research studies. HCV infection was confirmed with RNA testing. The 5’ UTR, core and NSB5 regions of HCV RNA positive samples were sequenced, and the genotype and subtype of the viral strains were determined. Host DNA from all HCV positive patients and age- and sex-matched non-HCV-infected control individuals were analysed for IL28B single nucleotide polymorphism (SNP) (rs12979860 and rs8099917). Geolocation of the patients were mapped using QGIS. Results 355 HCV antibody positive patients were analysed; 54.6% (194/355) and 46.4% (161/355) were acute and chronic infections, respectively. 50.4% (81/161) and 49.6.4% (80/161) of chronic infections had HCV mono-infection and HIV-HCV coinfection, respectively. 88.7% (315/355) and 10.1% (36/355) of the patients were from southern and central regions of Vietnam, respectively. 92.4% (328/355) of patients were HCV RNA positive, including 86.1% (167/194) acute and 100% (161/161) chronic infections. Genotype could be determined in 98.4% (322/328) patients. Genotypes 1 (56.5%; 182/322) and 6 (33.9%; 109/322) predominated. Genotype 1 including genotype 1a was significantly higher in HIV-HCV coinfected patients compared to acute HCV patients [43.8% (35/80) versus 20.5% (33/167)], (p =

[Background]: Bovine tuberculosis (bTB) caused by Mycobacterium bovis is a re-emerging problem in both livestock and humans. The association of some M. bovis strains with hyper-virulence, MDR-TB and disseminated disease makes it imperative to understand the biology of the pathogen., [Methods]: Mycobacterium bovis (15) among 1755 M. tuberculosis complex (MTBC) isolated between 2012 and 2014 were characterized and analyzed for associated patient demography and other risk factors. Five of the M. bovis isolates were whole-genome sequenced and comparatively analyzed against a global collection of published M. bovis genomes., [Results]: Mycobacterium bovis was isolated from 3/560(0.5%) females and 12/1195(1.0%) males with pulmonary TB. The average age of M. bovis infected cases was 46.8 years (7-72years). TB patients from the Northern region of Ghana (1.9%;4/212) had a higher rate of infection with M. bovis (OR = 2.7,p = 0.0968) compared to those from the Greater Accra region (0.7%;11/1543). Among TB patients with available HIV status, the odds of isolating M. bovis from HIV patients (2/119) was 3.3 higher relative to non-HIV patients (4/774). Direct contact with livestock or their unpasteurized products was significantly associated with bTB (p, [Conclusion]: Our data indicate potential zoonotic transmission of bTB in Ghana and hence calls for intensified public education on bTB, especially among risk groups., This work was supported by the Wellcome Trust Intermediate Fellowship awarded to DYM (Grant Number 097134/Z/11/Z).