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bioRxiv2018

Rapid, Affordable, Collection and Analysis of Bioaerosol Viral Pathogens (Begomoviruses and Whitefly Vectors)

Detection of pathogens is critical to monitoring their distribution and spread, and is a key component in the prediction and management of disease epidemiology. Monitoring for pathogens as bioaerosols requires developing techniques which are sensitive, affordable, and time saving before they will have widespread impact. This approach also overcomes private property issues, which are a major pitfall in monitoring diseases in complex agricultural and urban settings. In this study, we have applied an emerging technology of electrostatic sampling to the detection of an insect-transmitted plant pathogen as a bioaerosol. Where insects aggregate in large numbers, as with whiteflies, leafhoppers, psyllids and honey bees, the pathogen (ie. virus or bacteria) becoming aerosolized as thousands of excreta droplets fall from the plants during feeding. Agricultural systems have not fully measured the impact of bioaerosols on disease epidemiology. Electrostatic sampling provides a valuable, affordable, method for monitoring for diseases as bioaerosols, which includes plant, animal and human pathogens. This study shows results which successfully used an electrostatic sampling device to collect an aerosolized begomovirus from the air near whiteflies feeding on virus-infected tomato plants.

pathology↗

bioRxiv2018

Natural avirulent Shigella boydii strain in the Brazilian Amazon lacks major virulence genes and present Type II, Type III and Type VI Secretion Systems

BackgroundAmong Shigella species, Shigella boydii has always displayed a smaller role to the overall Shigella burden, frequently placed at third in epidemiological studies and described as restricted to Southeast Asia. Here we characterize an S. boydii isolated from an epidemiological study enrolling 1,339 Brazilian children from the Amazon region, in which Shigella species solely was the fourth cause of bacterial diarrhea. S. boydii strain 183 was isolated from rotavirus co-infected children with acute diarrhea. Here we aimed to characterize this strain regarding virulence and, immune response in a pulmonary model.\n\nMethodsAn in vitro HEp-2 epithelial cell invasion assay was used to compare the invasive phenotype of S. boydii strain 183 with clinical and highly virulent S. flexneri strain, both isolated from Brazilian children. A murine pulmonary model was performed to assess lung damage by histopathological analysis. mRNA expression of immune response key genes was retrieved by multiplex real-time PCR and correlations were obtained by network analysis. Broad genome analysis was performed to confirm S. boydii identity and define its virulence profile.\n\nResultsS. boydii strain 183 showed fewer invasion rates in vitro and tissue damage in vivo as compared to virulent S. flexneri 201. When compared to a survival challenge in mice, S. boydii had 100% survival against 10% of virulent S. flexneri. Overall, mRNA immune gene expression suggests a protective response against S. boydii strains 183, in contrast to the inflammatory response induced by the virulent S. flexneri strain 201. Network analysis with S. boydii strain 183 displayed IFN-{gamma} protagonism, contrasting with the correlations centralized on TNF- by the virulent S. flexneri strain 201. The genome showed a lack of effector proteins and enterotoxins in S. boydii strain 183, and sequencing analysis of Ipa invasins revealed mutations at functional sites. This avirulent S. boydii strain 183 presents the Type II Secretion System, T6SS, in addition to T3SS.\n\nConclusionsIn addition to causing no disease, S. boydii strain 183 lacks effector proteins and enterotoxins. The presence of T6SS additional secretion system could provide an advantage to establish this strain among commensal bacteria.\n\nAUTHOR SUMMARYThe Shigella genus is a human pathogen responsible to shigellosis and remains one of the significant causes of morbidity and mortality in children under five years old. This genus has four species, Shigella flexneri, Shigella sonnei, Shigella boydii, and Shigella dysenteriae. S. flexneri and S. sonnei are the most common in the worldwide infections; S. dysenteriae is rarely found, and S. boydii is responsible for 1% of the infections and is known to be restricted to Southeast Asia. Once S. boydii have a relatively small role in global Shigella disease, there are few studies regarding its virulence and mechanisms. Here we characterize an S. boydii isolated from Brazilian children from the Amazon region, and aimed to describe this strain regarding virulence. It is known that Shigella species use the Type 3 Secretion System (T3SS) to invade and colonize the human intestine. We found in S. boydii the presence of Type 2 Secretion System (T2SS), Type 6 Secretion System (T6SS), in addition to the T3SS. The T6SS have been described in S. sonnei only, granting a competitive advantage against S. flexneri mixed cultures. The presence of T6SS additional secretion system could provide a benefit to establish this strain among commensal bacteria.

microbiology↗

bioRxiv2018

Unraveling the implications of environmental, host and pathogen-specific determinants on clinical presentations and disease progression among Indian melioidosis patients.

BackgroundMelioidosis is gaining recognition as an emerging infectious disease with diverse clinical manifestations and high-case fatality rates,worldwide. However, the molecular epidemiology of the disease outside the endemic regions such as,Thailand and Northern Australia remains unclear.\n\nMethodsClinical data and B. pseudomallei (Bps) isolates obtained from 199 culture-confirmed cases of melioidosis, diagnosed during 2006-2016 inSouth India were used to elucidate the host and pathogen-specific variable virulence determinants associated with clinical presentations and disease progression. Further, we determined the temporal variations and the influence of ecological factors on Bps Lipopolysaccharide (LPS) genotypes causing infections.\n\nResultSevere forms of the disease were observed amongst 169 (85%) patients. Renal dysfunction and infection due to Bps harboring Bim-ABm variant had significant associations with severe forms of the disease. Diabetes mellitus, septicemic melioidosis and infection due to LPS-B genotype were independent risk factors for mortality. LPS-B (74%) and LPS-A (20.6%) were the prevalent genotypes causing infections. Both genotypes demonstrated temporal variations and had significant correlations with rainfall and humidity.\n\nConclusionOur study findings suggest that the pathogen-specific virulence traits, under the influence of ecological factors are the key drivers for geographical variations in the molecular epidemiology of melioidosis.

microbiology↗

bioRxiv2018

Comparative genomic analysis of the emerging pathogen Streptococcus pseudopneumoniae: novel insights into virulence determinants and identification of a novel species-specific molecular marker

Streptococcus pseudopneumoniae is a close relative of the major human pathogen S. pneumoniae. While initially considered as a commensal species, it has been increasingly associated with lower-respiratory tract infections and high prevalence of antimicrobial resistance (AMR). S. pseudopneumoniae is difficult to identify using traditional typing methods due to similarities with S. pneumoniae and other members of the mitis group (SMG). Using phylogenetic and comparative genomic analyses of SMG genomes, we identified a new molecular marker specific for S. pseudopneumoniae and absent from any other bacterial genome sequenced to date. We found that a large number of known virulence and colonization genes are present in the core S. pseudopneumoniae genome and we reveal the impressive number of known and new surface-exposed proteins encoded by this species. Phylogenetic analyses of S. pseudopneumoniae show that specific clades are associated with allelic variants of core proteins. Resistance to tetracycline and macrolides, the two most common resistances, were encoded by Tn916-like integrating conjugative elements and Mega-2. Overall, we found a tight association of genotypic determinants of AMR as well as phenotypic AMR with a specific lineage of S. pseudopneumoniae. Taken together, our results sheds light on the distribution in S. pseudopneumoniae of genes known to be important during invasive disease and colonization and provide insight into features that could contribute to virulence, colonization and adaptation.\n\nImportanceS. pseudopneumoniae is an overlooked pathogen emerging as the causative agent of lower-respiratory tract infections and associated with chronic obstructive pulmonary disease (COPD) and exacerbation of COPD. However, much remains unknown on its clinical importance and epidemiology, mainly due to the lack of specific means to distinguish it from S. pneumoniae. Here, we provide a new molecular marker entirely specific for S. pseudopneumoniae. Furthermore, our research provides a deep analysis of the presence of virulence and colonization genes, as well as AMR determinants in this species. Our results provide crucial information and pave the way for further studies aiming at understanding the pathogenesis and epidemiology of S. pseudopneumoniae.

microbiology↗

bioRxiv2018

Prospective real-time metagenomic sequencing during norovirus outbreak reveals discrete transmission clusters

BackgroundNorovirus outbreaks in hospital settings are a common challenge for infection prevention teams. Given the high burden of norovirus in most communities, it can be difficult to distinguish between on-going in-hospital transmission of virus and new introductions from the community and challenging to understand the long-term impacts of outbreak-associated viruses within medical systems using traditional epidemiological approaches alone.\n\nMethodsReal-time metagenomic sequencing during an on-going norovirus outbreak associated with a retrospective cohort study.\n\nResultsWe describe a hospital-associated norovirus outbreak that affected 13 patients over a 27-day period in a large tertiary pediatric hospital and was chronologically associated with a spike in self-reported gastrointestinal symptoms among staff. Real-time metagenomic next-generation sequencing (mNGS) of norovirus genomes demonstrated that 10 chronologically overlapping hospital-acquired norovirus cases were partitioned into three discrete transmission clusters. Sequencing data also revealed close genetic relationships between some hospital-acquired and some community-acquired cases. Finally, this data was used to demonstrate chronic viral shedding by an immunocompromised hospital-acquired case patient. Analysis of serial samples from this patient provided novel insights into the evolution of norovirus within an immunocompromised host.\n\nConclusionsThis study documents one of the first applications of real-time mNGS during a hospital-associated viral outbreak. Given its demonstrated ability to detect transmission patterns within outbreaks and elucidate the long-term impacts of outbreak-associated viral strains on patients and medical systems, mNGS constitutes a powerful resource to help infection control teams understand, prevent, and respond to viral outbreaks.\n\nSummary StatementReal-time metagenomic sequencing performed during a hospital-associated norovirus outbreak identified genetically-distinct, chronologically-overlapping case clusters. After the epidemiologically-defined outbreak had ceased, on-going transmission and shedding of outbreak-associated virus was also detected. These findings illustrate the value of genomics as a tool for infection control.

genomics↗

bioRxiv2018

Ecological and life history traits are associated with Ross River virus infection among sylvatic mammals in Australia

BackgroundRoss River virus (RRV) is Australias most important arbovirus given its annual burden of disease and the relatively large number of Australians at risk for infection. This mosquito-borne arbovirus is also a zoonosis, making its epidemiology and infection ecology complex and cryptic. Our grasp of enzootic, epizootic, and zoonotic RRV transmission dynamics is imprecise largely due to a poor understanding of the role of wild mammalian hosts in the RRV system.\n\nMethodsThe current study applied a piecewise structural equation model (PSEM) toward an interspecific comparison of sylvatic Australian mammals to characterize the ecological and life history profile of species with a history of RRV infection relative to those species with no such history among all wild mammalian species surveyed for RRV infection. The effects of species traits were assessed through multiple causal pathways within the PSEM framework.\n\nResultsSylvatic mammalian species with a history of RRV infection tended to express dietary specialization and smaller population density. These species were also characterized by a longer gestation length.\n\nConclusionsThis study provides the first interspecific comparison of wild mammals for RRV infection and identifies some potential targets for future wildlife surveys into the infection ecology of this important arbovirus. An applied RRV macroecology may prove invaluable to the epidemiological modeling of RRV epidemics across diverse sylvatic landscapes, as well as to the development of human and animal health surveillance systems.

ecology↗

bioRxiv2018

Exenatide reverts the high-fat-diet-induced impairment of BDNF signaling and inflammatory response in an animal model of Alzheimer’s disease

Backgroundpreclinical, clinical, and epidemiological evidence support the notion that Alzheimers disease(AD) is a multifactorial condition in which, along with {beta}-amyloid (A{beta}) and tau-related pathology, the synergistic activity of genetic, environmental, vascular, metabolic, and inflammatory factors promote the onset and progression of the disease. Epidemiological evidence indicate that glucose intolerance, deficits in insulin secretion or type 2 diabetes mellitus (T2DM) participate in increasing the risk of developing cognitive impairment or dementia. A pivotal role in the process is played by insulin as the hormone critically regulates brain functioning. GLP-1, the glucagon-like peptide 1, facilitates insulin signaling, regulates glucose homeostasis, and modulates synaptic plasticity. Exenatide is a GLP-1R agonist, characterized by an extended half-life, employed in T2DM. However, exenatide has also been shown to affect the signaling of the brain-derived neurotrophic factor (BDNF), synaptic plasticity, and cognitive performances in animal models of brain aging and neurodegeneration.\n\nMethodsin this study, we tested whether exenatide exerts neuroprotection in a preclinical AD model set to mimic the clinical complexity of the human disease. To that aim, we investigated the effects of 3-month exenatide treatment in 3xTg-AD mice challenged for six months with a high-fat diet (HFD). Endpoints of the study were variations in systemic metabolism, insulin and neurotrophic signaling, neuroinflammation, levels of A{beta} and tau pathology as well as changes in cognitive performances.\n\nFindings and interpretationresults of the study indicate that exenatide reverts the adverse changes of BDNF signaling and the neuroinflammation status of 3xTg-AD mice undergoing HFD.

neuroscience↗

bioRxiv2018

GenomeGraphR: A user-friendly open-source web application for foodborne pathogen Whole Genome Sequencing data integration, analysis, and visualization.

Food safety risk assessments and large-scale epidemiological investigations have the potential to provide better and new types of information when whole genome sequence (WGS) data are effectively integrated. Today, the NCBI Pathogen Detection database WGS collections have grown significantly through improvements in technology, coordination, and collaboration, such as the GenomeTrakr and PulseNet networks. However, high-quality genomic data is not often coupled with high-quality epidemiological or food chain metadata. We have created a set of tools for cleaning, curation, integration, analysis and visualization of microbial genome sequencing data. It has been tested using Salmonella enterica and Listeria monocytogenes data sets provided by NCBI Pathogen Detection (160,000 sequenced isolates). GenomeGraphR presents foodborne pathogen WGS data and associated curated metadata in a user-friendly interface that allows a user to query a variety of research questions such as, transmission sources and dynamics, global reach, and persistence of genotypes associated with contamination in the food supply and foodborne illness across time or space. The application is freely available (https://fda-riskmodels.foodrisk.org/genomegraphr/).

microbiology↗

bioRxiv2018

DRD2 and FOXP2 are implicated in the associations between computerized device use and psychiatric disorders

1.The societal health effects of ubiquitous computerized device use (CDU) is mostly unknown. Epidemiological evidence supports associations between CDU and psychiatric traits, but the underlying biological mechanisms are unclear. We investigated genetic overlaps, causal relationships, and molecular pathways shared between these traits using genome-wide data regarding CDU (UK Biobank; up to N=361,194 individuals) and Psychiatric Genomics Consortium phenotypes (14,477<N<150,064). The strongest genetic correlations were between \"weekly usage of mobile phone in last 3 months\" (PhoneUse) vs. attention deficit hyperactivity disorder (ADHD) (rg=0.425, p=4.59x10-11) and \"plays computer games\" (CompGaming) vs. schizophrenia (SCZ) (rg=-0.271, p=7.16x10-26). Latent causal variable analysis did not support causal relationships between these traits, but the observed genetic overlap was related to shared molecular pathways, including: dopamine transport (Gene Ontology:0015872, pSCZvsCompGaming=2.74x10-10) and DRD2 association (pSCZ=7.94x10-8; pCompGaming=3.98x10-25), and FOXP2 association (pADHD=9.32x10-7; pPhoneUse=9.00x10-11). Our results support epidemiological observations with genetic data, and uncover biological mechanisms underlying psychiatric disorders contribution to CDUs.

genomics↗

bioRxiv2018

A Nanopore-based method for generating complete coding region sequences of dengue virus in resource-limited settings

Dengue virus (DENV) sequencing is a vital tool for surveillance and epidemiology studies. However, the current methods employed for sequencing DENV are expensive, laborious and technically demanding, often due to intra- and inter-serotype variability. Therefore, on-site DENV sequencing is not feasible in many of the areas where DENV is endemic. Surveillance in these areas can only be performed by shipping samples to well-equipped central laboratories for sequencing. However, long periods of inadequate storage and unreliable shipping conditions mean that such samples can arrive degraded, rendering sequence recovery difficult. We therefore aimed to develop an approach that is simple, portable and effective, to be used for on-site DENV sequencing in limited resource settings.\n\nTo achieve this, we first used the Primal Scheme primer design tool to develop a simple and robust protocol for generating multiple short amplicons, covering the complete coding-region of DENV isolates. We then paired this method with the Nanopore MinION, a portable and affordable sequencing device, well-suited to minimal resource settings.\n\nThe multiplex PCR method produced full-coding-region coverage of all DENV samples tested with no optimisation required, and Nanopore sequencing of the short amplicons generated consensus sequences with high accuracy (99.52 - 99.92 %). Phylogenetic analysis of the consensus sequences generated using the new method showed that they formed monophyletic clusters with those produced by the current, long-amplicon, Illumina method, thus demonstrating that the two approaches are comparable. The multiplex methods simplicity and portability compared to the current DENV sequencing approach make it well-suited for use in resource-limited, DENV-endemic regions. Deployment of the method in these regions would increase the capacity for DENV surveillance and has the potential to provide vital resolution for future DENV epidemiology studies.

microbiology↗

bioRxiv2019

Molecular basis of P major human rotavirus VP8* domain interactions with histo-blood group antigens

Initial cell attachment of rotavirus (RV) to specific cell surface glycans, which is the essential first step in RV infection, is mediated by the VP8* domain of the spike protein VP4. Recently, human histo-blood group antigens (HBGAs) have been identified as ligands or receptors for human RV strains. RV strains in the P[4] and P[8] genotypes of the P[II] genogroup share common recognition of the Lewis b and H type 1 antigens, while P[6], which is one of the other genotypes in P[II], only recognizes the H type 1 antigen. The molecular basis of receptor recognition by the major human P[8] RVs remains unknown due to lack of experimental structural information. Here, we used nuclear magnetic resonance (NMR) titration experiments and NMR-derived high ambiguity driven docking (HADDOCK) methods to elucidate the molecular basis for P[8] VP8* recognition of the Leb and type 1 HBGAs and for P[6] recognition of H type 1 HBGAs. Unlike P[6] VP8* that recognizes H type 1 HGBAs in a binding surface composed of an -helix and a {beta}-sheet, referred as \"{beta} binding domain\", the P[8] VP8* binds the type 1 HBGAs requiring the presence of the Lewis epitope in a previously undescribed pocket formed by two {beta}-sheets, referred as \"{beta}{beta} binding domain\". The observation that P[6] and P[8] VP8* domains recognize different glycan structures at distinct binding sites supports the hypothesis that RV evolution is driven, at least in part, by selective pressure driven adaptation to HBGA structural diversity of their natural hosts living in the world. Recognition of the role that HBGAs play in driving RV evolution is essential to understanding RV diversity, host ranges, disease burden and zoonosis and to developing strategies to improve vaccines against RV infections.\n\nAuthor summaryRotaviruses (RV)s are the main cause of severe diarrhea in humans and animals. Significant advances in understanding RV diversity, evolution and epidemiology have been made after discovering that RVs recognize histo-blood group antigens (HBGAs) as host cell receptors. While different RV strains are known to have distinct binding preferences for HBGA receptors, the molecular basis in controlling strain-specific host ranges remains unclear. In this study, we used solution nuclear magnetic resonance to determine the molecular level details for interactions of the human P[8] and P[6] RV VP8* domains with their HBGA receptors. The distinct binding patterns observed between these major human RVs and their respective receptor ligands provides insight into the evolutionary relationships between different P[II] genotypes that ultimately determine host ranges, disease burden, zoonosis and epidemiology, which may impact future strategies for vaccine development against RVs.

biochemistry↗

bioRxiv2019

Sex Differences in Mutational Processes

Sex differences have been observed in multiple facets of cancer epidemiology, treatment and biology, and in most cancers outside the sex organs. Efforts to link these clinical differences to specific molecular features have focused on somatic mutations within the coding regions of the genome. Here, we describe the first pan-cancer analysis of sex differences in whole genomes of 1,983 tumours of 28 subtypes from the ICGC Pan-Cancer Analysis of Whole Genomes project. We both confirm the results of exome studies, and also uncover previously undescribed sex differences. These include sex-biases in coding and non-coding cancer drivers, mutation prevalence and strikingly, in mutational signatures related to underlying mutational processes. These results underline the pervasiveness of molecular sex differences and strengthen the call for increased consideration of sex in cancer research. Sex disparities in cancer epidemiology include an increased overall cancer risk in males corresponding with higher incidence in most tumor types, even after adjusting for known risk factors1,2. Cancer mortality is also higher in males, due in part to better survival for female patients in many cancer types, including those of the colon and head & neck3. Interestingly, female colorectal cancer patients respond better to surgery4 and adjuvant chemotherapy, though this is partially due to biases in tumour location and microsatellite instability5. Similarly, premenopausal female nasopharyngeal cancer patients have improved survival regardless of tumour stage, radiation or chemotherapy regimen6. There is a growing body of evidence for sex differences in cancer genomics7-13, but their molecular origins and clinical implications remain largely elusive. Previous studies have mostly focused on protein coding regions, leaving the vast majority of the genome unexplored. We hypothesized that there are uncharacterized sex differences in the non-coding regions of the genome. Using whole genome sequencing data from the Pan-cancer Analysis of Whole Genomes (PCAWG) project14, we performed a survey of sex-biased mutations in 1,983 samples (1,213 male, 770 female) from 28 tumour subtypes, excluding those of the sex organs (Supplementary Table 1). We also excluded the X and Y chromosomes to focus on autosomal sex differences in cancers affecting both men and women, but there are known to be significant X-chromosome mutational differences between tumours arising in men and women15. Our analysis revealed sex differences in both genome-wide phenomena and in specific genes. These sex-biases occur not only at the pan-cancer level across all 1,983 samples, but also in individual tumour subtypes.

cancer biology↗

bioRxiv2019

The molecular clock of Mycobacterium tuberculosis

The molecular clock and its phylogenetic applications to genomic data have changed how we study and understand one of the major human pathogens, Mycobacterium tuberculosis (MTB), the causal agent of tuberculosis. Genome sequences of MTB strains sampled at different times are increasingly used to infer when a particular outbreak begun, when a drug resistant clone appeared and expanded, or when a strain was introduced into a specific region. Despite the growing importance of the molecular clock in tuberculosis research, there is a lack of consensus as to whether MTB displays a clocklike behavior and about its rate of evolution. Here we performed a systematic study of the MTB molecular clock on a large genomic data set (6,285 strains), covering most of the global MTB diversity and representing different epidemiological settings. We found wide variation in the degree of clocklike structure among data sets, indicating that sampling times are sometimes insufficient to calibrate the clock of MTB. For data sets with temporal structure, we found that MTB genomes accumulate between 1x10-8 and 5x10-7 nucleotide changes per-site-per-year, which corresponds to 0.04 - 2.2 SNPs per-genome-per-year. Contrary to what expected, these estimates were not dependent on the time of the calibration points as they did not change significantly when we used epidemiological isolates (sampled in the last 40 years) or ancient DNA samples (about 1,000 years old) to calibrate the tree. Additionally, the uncertainty and the discrepancies in the results of different methods were often large, highlighting the importance of using different methods, and of considering carefully their assumptions and limitations. Significance StatementOne of the major recent advancement in evolutionary biology is the development of statistical methods to infer the past evolutionary history of species and populations with genomic data. In the last five years, many researchers have used the molecular clock to study the evolution of Mycobacterium tuberculosis, a bacterial pathogen that causes tuberculosis and is responsible for millions of human deaths every year. The application of the molecular clock to tuberculosis is extremely useful to understand the evolution of drug resistance, the spread of different strains and the origin of the disease. Since some of these studies found contrasting results, we performed a systematic analysis of the molecular clock of MTB. This study will provide an important guideline for future analyses of tuberculosis and other organisms.

evolutionary biology↗

bioRxiv2019

Robust Genome-Wide Ancestry Inference for Heterogeneous Datasets and Ancestry Facial Imaging based on the 1000 Genomes Project

Accurate inference of genomic ancestry is critically important in human genetics, epidemiology, and related fields. Geneticists today have access to multiple heterogeneous population-based datasets from studies collected under different protocols. Therefore, joint analyses of these datasets require robust and consistent inference of ancestry, where a common strategy is to yield an ancestry space generated by a reference dataset. However, such a strategy is sensitive to batch artefacts introduced by different protocols. In this work, we propose a novel robust genome-wide ancestry inference method; referred to as SUGIBS, based on an unnormalized genomic (UG) relationship matrix whose spectral (S) decomposition is generalized by an Identity-by-State (IBS) similarity degree matrix. SUGIBS robustly constructs an ancestry space from a single reference dataset, and provides a robust projection of new samples, from different studies. In experiments and simulations, we show that, SUGIBS is robust against individual outliers and batch artifacts introduced by different genotyping protocols. The performance of SUGIBS is equivalent to the widely used principal component analysis (PCA) on normalized genotype data in revealing the underlying structure of an admixed population and in adjusting for false positive findings in a case-control admixed GWAS. We applied SUGIBS on the 1000 Genome project, as a reference, in combination with a large heterogeneous dataset containing auxiliary 3D facial images, to predict population stratified average or ancestry faces. In addition, we projected eight ancient DNA profiles into the 1000 Genome ancestry space and reconstructed their ancestry face. Based on the visually strong and recognizable human facial phenotype, comprehensive facial illustrations of the populations embedded in the 1000 Genome project are provided. Furthermore, ancestry facial imaging has important applications in personalized and precision medicine along with forensic and archeological DNA phenotyping. Author SummaryEstimates of individual-level genomic ancestry are routinely used in human genetics, epidemiology, and related fields. The analysis of population structure and genomic ancestry can yield significant insights in terms of modern and ancient population dynamics, allowing us to address questions regarding the timing of the admixture events, and the numbers and identities of the parental source populations. Unrecognized or cryptic population structure is also an important confounder to correct for in genome-wide association studies (GWAS). However, to date, it remains challenging to work with heterogeneous datasets from multiple studies collected by different laboratories with diverse genotyping and imputation protocols. This work presents a new approach and an accompanying open-source software toolbox that facilitates a robust integrative analysis for population structure and genomic ancestry estimates for heterogeneous datasets. Given that visually evident and easily recognizable patterns of human facial characteristics covary with genomic ancestry, we can generate predicted ancestry faces on both the population and individual levels as we illustrate for the 26 1000 Genome populations and for eight eminent ancient-DNA profiles, respectively.

genetics↗

bioRxiv2019

Allergic inflammation hinders synergistic viral-bacterial co-infection in C57BL/6 mice

Asthma is a chronic airways disease that can be exacerbated during respiratory infections. Our previous findings that the inflammatory state of allergic airways at the time of influenza A virus (IAV) infection in combination with epidemiologic findings that asthmatics were less likely to suffer from severe influenza during the 2009 pandemic suggest that additional complications of influenza, such as increased susceptibility to bacterial superinfection, may be mitigated in the allergic host. To test this hypothesis, we developed a murine model of triple-disease in which mice were first rendered allergic to Aspergillus fumigatus and co-infected with IAV and Streptococcus pneumoniae seven days apart. Significant alterations to known synergistic effects of co-infection were noted in the allergic mice including reduced morbidity and mortality, bacterial burden, maintenance of alveolar macrophages, and reduced lung inflammation and damage. The lung microbiome of allergic mice differed from that of non-allergic mice during co-infection. To investigate the impact of the microbiome on the pathogenesis of lung disease, we induced a perturbation with a short course of fluoroquinolone antibiotic that is often prescribed for lung infections. A significant change in the microbiome was complemented with alterations to the inflammatory profile and a drastic increase in pro-inflammatory cytokines in allergic mice which were now susceptible to severe disease from IAV and S. pneumoniae co-infection. Our data suggest that responses to co-infection in allergic hosts likely depends on the immune and microbiome states and that antibiotics should be used with caution in individuals with underlying chronic lung disease. Author Summary Asthma is a condition of the lungs that affects millions worldwide. Traditionally, respiratory infections are considered to have a negative impact on asthmatics. However, epidemiological data surrounding the 2009 influenza pandemic suggest that asthmatics may be better equipped to counter severe influenza including bacterial pneumonia. Herein, we introduce a novel mouse model system designed to recapitulate an influenza virus and Streptococcal co-infection in a host with fungal asthma. We found that underlying allergic asthma protects against severe disease induced by co-infection. Mice with underlying allergic inflammation had reduced damage to the lungs and did not show signs of respiratory distress. Among the differences noted in the allergic mice that were protected from viral and bacterial co-infection, was the lung microbiome. Allergic mice lost their protection from co-infection after we perturbed their lung microbiome with antibiotics suggesting that the lung microbiome plays a role in host immunity against invading pathogens.

pathology↗

bioRxiv2019

%svy_logistic_regression: A generic SAS(R) macro for simple and multiple logistic regression and creating quality publication-ready tables using survey or non-survey data

IntroductionReproducible research is increasingly gaining interest in the research community. Automating the production of research manuscript tables from statistical software can help increase the reproducibility of findings. Logistic regression is used in studying disease prevalence and associated factors in epidemiological studies and can be easily performed using widely available software including SAS, SUDAAN, Stata or R. However, output from these software must be processed further to make it readily presentable. There exists a number of procedures developed to organize regression output, though many of them suffer limitations of flexibility, complexity, lack of validation checks for input parameters, as well as inability to incorporate survey design.\n\nMethodsWe developed a SAS macro, %svy_logistic_regression, for fitting simple and multiple logistic regression models. The macro also creates quality publication-ready tables using survey or non-survey data which aims to increase transparency of data analyses. It further significantly reduces turn-around time for conducting analysis and preparing output tables while also addressing the limitations of existing procedures.\n\nResultsWe demonstrate the use of the macro in the analysis of the 2013-2014 National Health and Nutrition Examination Survey (NHANES), a complex survey designed to assess the health and nutritional status of adults and children in the United States. The output presented here is directly from the macro and is consistent with how regression results are often presented in the epidemiological and biomedical literature, with unadjusted and adjusted model results presented side by side.\n\nConclusionsThe SAS code presented in this macro is comprehensive, easy to follow, manipulate and to extend to other areas of interest. It can also be incorporated quickly by the statistician for immediate use. It is an especially valuable tool for generating quality, easy to review tables which can be incorporated directly in a publication.

bioinformatics↗

bioRxiv2019

Estimating relatedness between malaria parasites

1.Understanding the relatedness of individuals within or between populations is a common goal in biology. Increasingly, relatedness features in genetic epidemiology studies of pathogens. These studies are relatively new compared to those in humans and other organisms, but are important for designing interventions and understanding pathogen transmission. Only recently have researchers begun to routinely apply relatedness to apicomplexan eukaryotic malaria parasites, and to date have used a range of different approaches on an ad hoc basis. It remains unclear how to compare different studies, therefore, and which measures to use. Here, we systematically compare measures based on identity-by-state and identity-by-descent using a globally diverse data set of malaria parasites, Plasmodium falciparum and Plasmodium vivax, and provide marker requirements for estimates based on identity-by-descent. We formally show that the informativeness of polyallelic markers for relatedness inference is maximised when alleles are equifrequent. Estimates based on identity-by-state are sensitive to allele frequencies, which vary across populations and by experimental design. For portability across studies, we thus recommend estimates based on identity-by-descent. To generate reliable estimates, we recommend approximately 200 biallelic or 100 polyallelic markers. Confidence intervals illuminate inference across studies based on different sets of markers. These marker requirements, unlike many thus far reported, are immediately applicable to haploid malaria parasites and other haploid eukaryotes. This is the first attempt to provide rigorous analysis of the reliability of, and requirements for, relatedness inference in malaria genetic epidemiology, and will provide a basis for statistically informed prospective study design and surveillance strategies.

genetics↗

bioRxiv2019

Development of a deep amplicon sequencing method to determine the proportional species composition of piroplasm haemoprotozoa as an aid in their control

Piroplasmosis is caused by tick-borne haemoprotozoa of the genera Theileria and Babesia. These parasitic infections can cause serious impact on the health of livestock and production. Multiple piroplasm species can infect a single host, but reliable molecular diagnostic tools are needed with which to understand the composition of these complex parasite communities. Theileria and Babesia vary in their epidemiology, drug sensitivity, pathogenicity and interaction of co-infecting species, but are similar in the animals, become persistent carriers after recovery from primary infection, acting as reservoir hosts. Here, we describe for the first time the use of a deep amplicon sequencing platform to identify proportions of piroplasm species in co-infecting communities and develop the concept of a \"haemoprotobiome\". First, four phenotypically-verified species of Theileria and Babesia were used to prepare mock pools with random amounts of the parasites and amplified with four different numbers of PCR cycles to assess sequence representation of each species. Second, we evaluated the detection threshold of the deep amplicon sequencing assay for each of the four species and to assess the accuracy of proportional quantification of all four species. Finally, we applied the assay to the field samples to afford insight of the species composition of piroplasm communities in small and large ruminants in the Punjab province of Pakistan. The \"haemoprotobiome\" concept has several potential applications in veterinary and human research, including understanding of responses to drug treatment; parasite epidemiology and ecology; species interactions during mixed infections; and parasite control strategies.

microbiology↗