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bioRxiv2019

Carrion flies as sentinels for monitoring rabbit calicivirus activity in Australia

Rabbit caliciviruses are an essential tool for managing wild rabbit populations in Australia. Our understanding of rabbit calicivirus epidemiology in Australia currently depends on members of the public submitting liver samples from dead rabbits through a monitoring program called Rabbitscan. However, many wild rabbits die in inaccessible locations or are scavenged before sampling can occur, leading to considerable sampling bias. In this study we screened field-caught carrion flies for the presence of rabbit caliciviruses to monitor virus circulation patterns in the landscape, with an aim to establish a less biased epidemiological surveillance tool. Carrion flies were collected from two study sites over a 22 month period and these samples were used to optimise and validate molecular testing methods in this sample type for the currently circulating rabbit calicivirus variants. Virus was clearly detectable in field-caught carrion flies using optimised SYBR-green RT-qPCR and RT-PCR assays. However, variant identification was frequently hindered by the low virus loads present in carrion fly samples and spurious RT-PCR amplification. This was overcome by frequent sampling, which effectively acts as replicate sampling to verify inconclusive results. There was good correlation between virus detections in carrion flies and in samples recovered from wild rabbits, both temporally and for virus variant identification. The methods reported here provide a robust and efficient additional surveillance tool to monitor rabbit calicivirus activity at a landscape scale, which in turn can help to guide more effective rabbit management programs.

microbiology↗

bioRxiv2019

Estimating the sensitivity of associations between risk factors and outcomes to shared genetic effects

Associations between exposures and outcomes reported in epidemiological studies are typically unadjusted for genetic confounding. We propose a two-stage approach for estimating the degree to which such observed associations can be explained by genetic confounding. First, we assess attenuation of exposure effects in regressions controlling for increasingly powerful polygenic scores. Second, we use structural equation models to estimate genetic confounding using heritability estimates derived from both SNP-based and twin-based studies. We examine associations between maternal education and three developmental outcomes - child educational achievement, Body Mass Index, and Attention Deficit Hyperactivity Disorder. Polygenic scores explain between 14.3% and 23.0% of the original associations, while analyses under SNP- and twin-based heritability scenarios indicate that observed associations could be almost entirely explained by genetic confounding. Thus, caution is needed when interpreting associations from non-genetically informed epidemiology studies. Our approach, akin to a genetically informed sensitivity analysis can be applied widely. Author summaryAn objective shared across the life, behavioural, and social sciences is to identify factors that increase risk for a particular disease or trait. However, identifying true risk factors is challenging. Often, a risk factor is statistically associated with a disease even if it is not really relevant, meaning that even successfully improving the risk factor will not impact the disease. One reason for the existence of such misleading associations stems from genetic confounding. This is when genetic factors influence both the risk factor and the disease, which generates a statistical association even in the absence of a true effect of the risk factor. Here, we propose a method to estimate genetic confounding and quantify its effect on observed associations. We show that a large part of the associations between maternal education and three child outcomes - educational achievement, body mass index and Attention-Deficit Hyperactivity Disorder-is explained by genetic confounding. Our findings can be applied to better understand the role of genetics in explaining associations of key risk factors with diseases and traits.

genetics↗

bioRxiv2019

Detection and quantification of house mouse Eimeria at the species level - challenges and solutions for the assessment of Coccidia in wildlife

Detection and quantification of coccidia in studies of wildlife can be challenging. Therefore, the prevalence of coccidia is often not assessed at the parasite species level in non-livestock animals. Parasite species-specific prevalences are especially important when studying evolutionary questions in wild populations. We tested whether increased host population density increases the prevalence of individual Eimeria species at the farm level, as predicted by epidemiological theory. We studied free-living commensal populations of the house mouse (Mus musculus) in Germany and established a strategy to detect and quantify Eimeria infections. We show that a novel diagnostic primer targeting the apicoplast genome (Ap5) and coprological assessment after flotation provide complementary detection results increasing sensitivity. Genotyping PCRs confirm detection in a subset of samples and cross-validation of different PCR markers does not indicate a bias towards a particular parasite species in genotyping. We were able to detect double infections and to determine the preferred niche of each parasite species along the distal-proximal axis of the intestine. Parasite genotyping from tissue samples provides an additional indication for the absence of species bias in genotyping amplifications. Three Eimeria species were found infecting house mice at different prevalences: Eimeria ferrisi (16.7%; 95% CI 13.2 - 20.7), E. falciformis (4.2%; 95% CI 2.6 - 6.8) and E. vermiformis (1.9%; 95% CI 0.9 - 3.8). We also find that mice in dense populations are more likely to be infected with E. falciformis and E. ferrisi.\n\nWe provide methods for the assessment of prevalences of coccidia at the species level in rodent systems. We show and discuss how such data can help to test hypotheses in ecology, evolution and epidemiology on a species level.

microbiology↗

bioRxiv2019

Analysis of Heterogeneous Genomic Samples Using Image Normalization and Machine Learning

BackgroundAnalysis of heterogeneous populations such as viral quasispecies is one of the most challenging bioinformatics problems. Although machine learning models are becoming to be widely employed for the analysis of sequencing data associated with such populations, their straightforward application is impeded by multiple challenges associated with technological limitations and biases, difficulty of selection of relevant features and need to compare genomic datastes of different sizes and structures.\n\nMethodsWe propose a novel preprocessing approach to transform irregular genomic data into normalized image data. Such representation allows to restate the problems of classification and comparison of heterogeneous populations as image classification problems which can be solved using variety of available machine learning tools. We then apply the proposed approach to two important molecular epidemiology problems: inference of viral infection stage and detection of viral transmission clusters and outbreaks using next-generation sequencing data.\n\nResultsThe infection staging method has been applied to HCV HVR1 samples collected from 108 recently and 257 chronically infected individuals. The SVM-based image classification approach achieved more than 95% accuracy for both recently and chronically HCV-infected individuals. Clustering has been performed on the data collected from 33 epidemiologically curated outbreaks, yielding more than 97% accuracy.\n\nAvailabilityThe developed software is freely available at https://bitbucket.org/adv_bio_coll/chronic_vs_clinic

bioinformatics↗

bioRxiv2019

Population structure and antimicrobial resistance patterns of Salmonella Typhi isolates in Bangladesh from 2004 to 2016

BackgroundMulti-drug resistant typhoid fever remains an enormous public health threat in low and middle-income countries. However, we still lack a detailed understanding of the epidemiology and genomics of S. Typhi in many regions. Here we have undertaken a detailed genomic analysis of typhoid in Bangladesh to unravel the population structure and antimicrobial resistance patterns in S. Typhi isolated in between 2004-2016.\n\nPrincipal findingsWhole genome sequencing of 202 S. Typhi isolates obtained from three study locations in urban Dhaka revealed a diverse range of S. Typhi genotypes and AMR profiles. The bacterial population within Dhaka were relatively homogenous with little stratification between different healthcare facilities or age groups. We also observed evidence of transmission of Bangladeshi genotypes with neighboring South Asian countries (India, Pakistan and Nepal) suggesting these are circulating throughout the region. This analysis revealed a decline in H58 (genotype 4.3.1) isolates from 2011 onwards, coinciding with a rise in a diverse range of non-H58 genotypes and a simultaneous rise in isolates with reduced susceptibility to fluoroquinolones, potentially reflecting a change in treatment practices. We identified a novel S. Typhi genotype, subclade 3.3.2 (previously defined only to clade level, 3.3), which formed two localised clusters (3.3.2.Bd1 and 3.3.2.Bd2) associated with different mutations in the Quinolone Resistance Determining Region (QRDR) of gene gyrA.\n\nSignificanceOur analysis of S. Typhi isolates from Bangladesh isolated over a twelve year period identified a diverse range of AMR profiles and genotypes. The observed increase in non-H58 genotypes associated with reduced fluoroquinolone susceptibility may reflect a change in treatment practice in this region and highlights the importance of continued molecular surveillance to monitor the ongoing evolution of AMR in Bangladesh. We have defined new genotypes and lineages of Bangladeshi S. Typhi which will facilitate identification of these emerging AMR clones in future surveillance efforts.\n\nAuthor SummaryTyphoid fever, caused by Salmonella enterica serovar Typhi, is an acute and often life-threatening febrile illness in developing countries. Until recently, there have been limited studies focusing on the epidemiology and disease burden of typhoid in poor resource settings including Bangladesh. This study highlights the urgent need for sustained genomics based surveillance studies to monitor the population structure and ongoing evolution of AMR. Our data revealed a diverse range of S. Typhi genotypes and AMR patterns among 202 isolates collected from three urban areas in Dhaka. Moreover, we defined a new genotype, subclade 3.3.2 (previously typed only to clade level, 3.3) with two Bangladesh-localiased clades 3.3.2.Bd1 and 3.3.2.Bd2 showing reduced susceptibility to fluoroquinolones. Our data shows a significant increase in non-H58 genotypes carrying QRDR mutations from 2012 onwards, replacing MDR H58 genotypes. Our data suggest that a shift in treatment practice towards third generation cephalosporins to control typhoid might be beneficial, in addition to the introduction of vaccination programs and improvements in water sanitation and hygiene (WASH) in Bangladesh.

genomics↗

bioRxiv2019

Genomes of intracellular Leishmania parasites directly sequenced from patients

Whole genome sequencing (WGS) is increasingly used for molecular diagnosis and epidemiology of infectious diseases. Current Leishmania genomic studies rely on DNA extracted from cultured parasites, which might introduce sampling and biological biases into the subsequent analyses. Up to now, direct analysis of Leishmania genome in clinical samples is hampered by high levels of human DNA and large variation in parasite load in patient samples. Here, we present a method, based on target enrichment of Leishmania donovani DNA with Agilent SureSelect technology, that allows the analysis of Leishmania genomes directly in clinical samples. We validated our protocol with a set of artificially mixed samples, followed by the analysis of 63 clinical samples (bone marrow or spleen aspirates) from visceral leishmaniasis patients in Nepal. We were able to identify genotypes using a set of diagnostic SNPs in almost all of these samples (97%) and access comprehensive genome-wide information in most (83%). This allowed us to perform phylogenomic analysis, assess chromosome copy number and identify large copy number variants (CNVs). Pairwise comparisons between the parasite genomes in clinical samples and derived in vitro cultured promastigotes showed a lower aneuploidy in amastigotes as well as genomic differences, suggesting polyclonal infections in patients. Altogether our results underline the need for sequencing parasite genomes directly in the host samples.\n\nAuthor summaryVisceral leishmaniasis (VL) is caused by parasitic protozoa of the Leishmania donovani complex and is lethal in the absence of treatment. Whole Genome Sequencing (WGS) of L. donovani clinical isolates revealed hitherto cryptic population structure in the Indian Sub-Continent and provided insights into the epidemiology and potential mechanisms of drug resistance. However, several biases are likely introduced during the culture step. We report here the development of a method that allows determination of parasite genomes directly in clinical samples, and validate it on bone marrow and splenic aspirates of VL patients in Nepal. Our study sheds a new light on the biology of Leishmania in the human host: we found that intracellular parasites of the patients had very low levels of aneuploidy, in sharp contrast to the situation in cultivated isolates. Moreover, the observed differences in genomes between intracellular amastigotes of the patient and the derived cultured parasites suggests polyclonality of infections, with different clones dominating in clinical samples and in culture, likely due to fitness differences. We believe this method is most suitable for clinical studies and for molecular tracking in the context of elimination programs.

microbiology↗

bioRxiv2019

An integrated framework for the joint inference of demographic history and sampling intensity from genealogies or genetic sequences

Estimating past population dynamics from molecular sequences that have been sampled longitudinally through time is an important problem in infectious disease epidemiology, molecular ecology and macroevolution. Popular solutions, such as the skyline and skygrid methods, infer past effective population sizes from the coalescent event times of phylogenies reconstructed from sampled sequences, but assume that sequence sampling times are uninformative about population size changes. Recent work has started to question this assumption by exploring how sampling time information can aid coalescent inference. Here we develop, investigate, and implement a new skyline method, termed the epoch sampling skyline plot (ESP), to jointly estimate the dynamics of population size and sampling rate through time. The ESP is inspired by real-world data collection practices and comprises a flexible model in which the sequence sampling rate is proportional to the population size within an epoch but can change discontinuously between epochs. We show that the ESP is accurate under several realistic sampling protocols and we prove analytically that it can at least double the best precision achievable by standard approaches. We generalise the ESP to incorporate phylogenetic uncertainty in a new Bayesian package (BESP) in BEAST2. We re-examine two well-studied empirical datasets from virus epidemiology and molecular evolution and find that the BESP improves upon previous coalescent estimators and generates new, biologically-useful insights into the sampling protocols underpinning these datasets. Sequence sampling times provide a rich source of information for coalescent inference that will become increasingly important as sequence collection intensifies and becomes more formalised.

genetics↗

bioRxiv2019

Characterisation of cefotaxime-resistant urinary Escherichia coli from primary care in South-West England 2017-2018.

ObjectivesThird-generation cephalosporin-resistant Escherichia coli from community-acquired urinary tract infections (UTI) have been increasingly reported worldwide. In this study we sought to determine and characterise the mechanisms of cefotaxime-resistance (CTX-R) employed by urinary E. coli obtained from primary care over a 12-month period, in Bristol and surrounding counties in the South West of England.\n\nMethodsCephalexin resistant (Ceph-R) E. coli isolates were identified directly from general practice (GP) referred urine samples using disc susceptibility testing as per standard diagnostic procedures. CTX-R was determined by subsequent plating onto MIC breakpoint plates. {beta}-Lactamase genes were detected by PCR. Whole Genome Sequencing (WGS) was performed on 225 urinary isolates and analyses were performed using the Centre for Genomic Epidemiology platform. Patient information provided by the referring GPs was reviewed.\n\nResultsDuring the study period, Ceph-R E. coli (n=900) were obtained directly from urines from 146 GPs. Seventy-percent (626/900) of isolates were CTX-R. WGS of 225 non-duplicate isolates identified that the most common mechanism of CTX-R was blaCTX-M carriage (185/225; 82.2%), predominantly blaCTX-M-15 (114/185; 61.6%), followed by carriage of plasmid mediated AmpCs (pAmpCs) (17/225; 7.6%), ESBL blaSHV variants (6/225; 2.7%), AmpC hyperproduction (13/225; 5.8%), or a combination of both blaCTX-M and pAmpC carriage (4/225; 1.8%). Forty-four sequence types (STs) were identified with ST131 representing 101/225 (45.0%) of sequenced isolates, within which the blaCTX-M-15-positive clade C2 was dominant (54/101; 53.5%). Ciprofloxacin-resistance (CIP-R) was observed in 128/225 (56.9%) of sequenced CTX-R isolates - predominantly associated with fluoroquinolone-resistant clones ST131 and ST1193.\n\nConclusionsMost Ceph-R urinary E. colis were CTX-R, predominantly caused by blaCTX-M carriage. There was a clear correlation between CTX-R and CIP-R, largely attributable to the dominance of the high-risk pandemic clones, ST131 and ST1193 in this study. This localised epidemiological data provides greater resolution than regional data and can be valuable for informing treatment choices in the primary care setting.

microbiology↗

bioRxiv2019

Microevolution in the major outer membrane protein OmpA of Acinetobacter baumannii

Acinetobacter baumannii is nowadays a relevant nosocomial pathogen characterized by multidrug resistance (MDR) and concomitant difficulties to treat infections. OmpA is the most abundant A. baumannii outer membrane (OM) protein, and is involved in virulence, host cell recognition, biofilm formation, regulation of OM stability, permeability, and antibiotic resistance. OmpA members are two-domain proteins with an N-terminal eight-stranded {beta}-barrel domain with four external loops (ELs) interacting with the environment, and a C-terminal periplasmic domain binding non-covalently to the peptidoglycan. Here, we combined data from genome sequencing, phylogenetic, and multilocus sequence analyses from 242 strains of the Acinetobacter calcoaceticus/Acinetobacter baumannii complex (ACB), 222 from A. baumannii, to explore ompA microevolutionary divergence. Five major ompA variant groups were identified (V1 to V5) comprising 50 different alleles coding for 29 different proteins. Polymorphisms were concentrated in 5 regions corresponding to the four ELs and the C-terminal end, and provided evidence for different intra-genic recombination events. ompA variants were not randomly distributed across the A. baumannii phylogeny, with the most frequent V1a1 allele almost exclusive to clonal complex 1 (CC1) strains and the second most frequent V2a1 allele found in the majority of CC2 strains. Evidence was found for assortative exchanges of ompA alleles not only between different A. baumannii clonal lineages, but also different ACB species. Within A. baumannii ompA non-synonymous substitutions were concentrated in the ELs regions, but were more abundant in the transmembrane regions between different Acinetobacter species. The overall results have implications for A. baumannii evolution, epidemiology, virulence, and vaccine design.\n\nImportanceAcinetobacter baumannii is an increasing MDR threat in nosocomial settings associated with prolonged hospitalization and concomitantly increased healthcare costs. The main A. baumannii OM protein, OmpA, is a multifaceted two-domain protein implicated in host cell recognition and adhesion, cytotoxicity, biofilm formation, and as a slow porin for antibiotics and small hydrophilic nutrients. A. baumannii OmpA has been proposed as a potential target for anti-virulence drugs and as a vaccine candidate. Given the many interactions of this protein with environmental factors including host defenses, it is certainly subjected to many selective pressures. Here, we analyzed the microevolution of this OM protein in the A. baumannii population to obtain clues on the extent to which selection in the clinical setting has shaped this protein. The results provide relevant information on the main causes driving evolution of this protein, with potential implications in A. baumannii epidemiology, virulence, and vaccine design.

microbiology↗

bioRxiv2019

Co-colonization interactions drive explicit frequency-dependent dynamics among N types

Multi-type spreading processes are ubiquitous in ecology, epidemiology and social systems, but remain hard to model mathematically and to understand on a fundamental level. Here, we describe and study a multi-type susceptible-infected-susceptible (SIS) model that allows for up to two co-infections of a host. Fitness differences between N infectious agents are mediated through altered susceptibilities to secondary infections that depend on colonizer- co-colonizer interactions. By assuming small differences between such pairwise traits (and other infection parameters equal), we derive a model reduction framework using separation of timescales. This quasi-neutrality in strain space yields a fast timescale where all types behave as neutral, and a slow timescale where non-neutral dynamics take place. On the slow timescale, N equations govern strain frequencies and accurately approximate the dynamics of the full system with O(N2) variables. We show that this model reduction coincides with a special case of the replicator equation, which, in our system, emerges in terms of the pairwise invasion fitnesses among strains. This framework allows to build the multi-type community dynamics bottom-up from only pairwise outcomes between constituent members. We find that mean fitness of the multi-strain system, changing with individual frequencies, acts equally upon each type, and is a key indicator of system resistance to invasion. Besides efficient computation and complexity reduction, these results open new perspectives into high-dimensional community ecology, detection of species interactions, and evolution of biodiversity, with applications to other multi-type biological contests. By uncovering the link between an epidemiological system and the replicator equation, we also show our co-infection model relates to Fishers fundamental theorem and to conservative Lotka-Volterra systems.

ecology↗

bioRxiv2019

Extended-spectrum beta-lactamase (ESBL)-producing and non-ESBL-producing Escherichia coli isolates causing bacteremia in the Netherlands (2014 - 2016) differ in ST distribution, antimicrobial resistance gene and virulence gene content

BackgroundKnowledge on the molecular epidemiology of Escherichia coli causing E. coli bacteremia (ECB) in the Netherlands is mostly based on extended-spectrum beta-lactamase-producing E. coli (ESBL-Ec). We determined differences in clonality and resistance and virulence gene (VG) content between non-ESBL-producing E. coli (non-ESBL-Ec) and ESBL-Ec blood isolates with different epidemiological characteristics.\n\nMaterials/methodsA random selection of non-ESBL-Ec isolates as well as all available ESBL-Ec blood isolates was obtained from two Dutch hospitals between 2014 and 2016. Whole genome sequencing was performed to infer sequence types (STs), serotypes, acquired antibiotic resistance genes and VG scores, based on presence of 49 predefined putative pathogenic VG.\n\nResultsST73 was most prevalent among the 212 non-ESBL-Ec (N=26, 12.3%) and ST131 among the 69 ESBL-Ec (N=30, 43.5%). Prevalence of ST131 among non-ESBL-Ec was 10.4% (N=22, P value < 0.001 compared to ESBL-Ec). O25:H4 was the most common serotype in both non-ESBL-Ec and ESBL-Ec. Median acquired resistance gene counts were 1 (IQR 1 - 6) and 7 (IQR 4 - 9) for non-ESBL-Ec and ESBL-Ec, respectively (P value < 0.001). Among non-ESBL-Ec, acquired resistance gene count was highest among blood isolates from a primary gastro-intestinal focus (median 4, IQR 1 - 8). Median VG scores were 13 (IQR 9 - 20) and 12 (IQR 8 - 14) for non-ESBL-Ec and ESBL-Ec, respectively (P value = 0.002). VG scores among non-ESBL-Ec from a primary urinary focus (median 15, IQR 11 - 21) were higher compared to non-ESBL-Ec from a primary gastro-intestinal (median 10, IQR 6 - 13) or hepatic-biliary focus (median 11, IQR 5 - 18) (P values = 0.007 and 0.036, respectively). VG content varied between different E. coli STs.\n\nConclusionsNon-ESBL-Ec and ESBL-Ec blood isolates from two Dutch hospitals differed in clonal distribution, resistance gene and VG content. Also, resistance gene and VG content differed between non-ESBL-Ec from different primary foci of ECB.

microbiology↗

bioRxiv2019

Seroprevalence of Foot and Mouth Disease Virus Infection in some Wildlife and Cattle in Bauchi State, Nigeria

BackgroundFoot and mouth disease (FMD) is one of the most economically important transboundary animal diseases with devastating consequence on livestock production and wildlife conservation. The objectives of the study were: to determine the seroprevalence of FMDV in wildlife and cattle and identify circulating FMDV serotypes in wildlife and identify potential risk factors that will contribute to transmission of the disease at the wildlife-livestock interface in Yankari Game Reserve and Sumu Wildlife Park in Bauchi State, Nigeria.\n\nMethodsBlood samples were collected between 2013 to 2015 from some wildlife and cattle respectively within and around Yankari Game Reserve (YGR) and Sumu Wildlife Park (SWP) in Bauchi State, Nigeria. The Wild animals were immobilized for blood collection using a combination of Etorphine Hydrochloride (M99(R) Kruger-Med South Africa) at 0.5-2 mg/kg and Azaperone (Stresnil(R), Janssen Pharmaceuticals (Pty.) Ltd., South Africa) at 0.1 mg/kg using a Dan-Inject(R) rifle (Dan-Inject APS, Sellerup Skovvej, Denmark) fitted with 3 ml dart syringe and for reversal, Naltrexone (Trexonil(R) Kruger-Med South Africa) at 1.5 mg IM was used, cattle were restrained by the owners for blood collection. Harvested Sera from blood were screened for presence of Antibodies against FMDV using prioCHECK(R) 3 ABC NSP ELISA kit and positive samples from wildlife were serotyped using Solid-Phase Competitive ELISA, (IZSLER Brescia-Italy). Data obtained were analysed using Graphpad Prism version 7.\n\nResultsThe results showed that 197 (65.7%) of the 300 serum samples from cattle and 13 (24.5%) of the 53 serum samples from wildlife tested positive for antibodies to the highly conserved non-structural 3-ABC protein of FMDV and statistically significant (P <0.05). Classification of cattle into breed and sex showed that detectable antibodies to FMDV were higher (P <0.05) in White Fulani 157 (72.8%) than red Bororo 23 (39.7%) and Sokoto Gudali 17 (33.3%) breeds of cattle whereas in females detectable FMDV antibodies were higher (P <0.05) 150 (72.8%) than in males 47 (50.0%). In the wildlife species, antibodies to FMDV were detected in waterbuck 2 (28.6%), elephant 1 (25.0%), wildebeest 4 (33.3%) and eland 6 (25.0%). Four serotypes of FMDV: O, A, SAT-1 and SAT-2 were detected from the 3-ABC positive reactors in waterbuck, elephant, wildebeest and eland. Contact of wildlife and cattle during utilization of the rich resources in the conservation areas is a potential risk factor for the spread of FMDV in the study area.\n\nConclusionsPresence of FMDV antibodies in cattle and some wildlife were observed and serotypes of FMDV: O, A, SAT-1 and SAT-2 were detected from the 3-ABC positive reactors in some of the wildlife. The study highlights the need for active surveillance of FMDV in wildlife and pastoral cattle within and around wildlife conservation areas in Nigeria. FMD surveillance system, control and prevention program that targets wildlife and livestock at the wildlife-livestock interface level will be beneficial to the livestock industry and wildlife conservation goals in Bauchi State, Nigeria.\n\nAuthor summaryFoot and mouth disease (FMD) is an important trans-boundary viral disease of both domestic and wild cloven hoofed animals characterized by high morbidity with devastating consequence on the livestock worldwide. Despite the endemic nature of FMD in Nigeria, little is known about the epidemiology of the disease at the wildlife-livestock interface level. To address this gap, blood samples were collected between 2013 to 2015 from some wildlife and cattle respectively within and around Yankari Game Reserve (YGR) and Sumu Wildlife Park (SWP) in Bauchi State, Nigeria. Wild animals were immobilized using a combination of Etorphine Hydrochloride (M99(R) Kruger-Med South Africa) at 0.5-2 mg/kg and Azaperone (Stresnil(R), Janssen Pharmaceuticals (Pty.) Ltd., South Africa) at 0.1 mg/kg using a Dan-Inject(R) rifle (Dan-Inject APS, Sellerup Skovvej, Denmark) fitted with 3 ml dart syringe and for reversal, Naltrexone (Trexonil(R) Kruger-Med South Africa) at 1.5 mg IM was used, cattle were restrained by the owners for blood collection. Harvested Sera from blood were screened for presence of Antibodies against FMDV using prioCHECK(R) 3 ABC NSP ELISA kit and positive samples were serotyped using Solid-Phase Competitive ELISA, (IZSLER Brescia-Italy). Out of the 300 and 53 sera collected from cattle and wildlife 197 (65.7%) and 13 (24.5%) (P <0.05) respectively tested positive for antibodies to the highly conserved non-structural 3-ABC protein of FMDV by the FMDV-NS blocking ELISA. Classification of cattle into breed and sex showed that detectable antibodies to FMDV were higher (P <0.05) in White Fulani 157 (72.8%) than red Bororo 23 (39.7%) and Sokoto Gudali 17 (33.3%) breeds of cattle whereas in females detectable FMDV antibodies were higher (P <0.05) 150 (72.8%) than in males 47 (50.0%). In the wildlife species, antibodies to FMDV were detected in waterbuck 2 (28.6%), elephant 1 (25.0%), wildebeest 4 (33.3%) and eland 6 (25.0%). Four serotypes of FMDV: O, A, SAT-1 and SAT-2 were detected from the 3-ABC positive reactors in waterbuck, elephant, wildebeest and elands. The results showed presence of antibodies to FMDV in some wildlife and cattle and suggest that wildlife could equally play an important role in the overall epidemiology of FMD in Nigeria. FMD surveillance system, control and prevention program should be intensified in the study area.

scientific communication and education↗

bioRxiv2019

Novel computational deep learning strategy for neuroprotection identification reveals unique set of nicotine analogs as potential therapeutic compounds against Parkinsons disease

Dopaminergic replacement has been used for Parkinsons Disease (PD) treatment with positive effects on motor symptomatology but with low effects over disease progression and prevention. Different epidemiological studies have shown that nicotine consumption decreases PD prevalence through the activation of neuroprotective mechanisms. Nicotine-induced neuroprotection has been associated with the overstimulation of intracellular signaling pathways (SP) such as Phosphatidyl Inositol 3-kinase/Protein kinase-B (PI3K/AKT) through nicotinic acetylcholine receptors (e.g 7 nAChRs) and the over-expression of the anti-apoptotic gene Bcl-2. Considering its harmful effects (toxicity and dependency), the search for nicotine analogs with decreased secondary effects, but similar neuroprotective activity, remains a promissory field of study. In this work, a computational strategy integrating structural bioinformatics, signaling pathway (SP) manual reconstruction, and deep learning was performed to predict the potential neuroprotective activity of a series of 8 novel nicotine analogs over the behavior of PI3K/AKT. We performed a protein-ligand analysis between nicotine analogs and 7 nAChRs receptor using geometrical conformers, physicochemical characterization of the analogs and developed a manually curated neuroprotective dataset to analyze their potential activity. Additionally, we developed a predictive machine-learning model for neuroprotection in PD through the integration of Markov Chain Monte-Carlo transition matrix for the SP with synthetic training datasets of the physicochemical properties and structural dataset. Our model was able to predict the potential neuroprotective activity of seven new nicotine analogs based on the binomial Bcl-2 response regulated by the activation of PI3K/AKT. We present a new computational strategy to predict the pharmacological neuroprotective potential of nicotine analogs based on SP architecture, using deep learning and structural data. Our theoretical strategy can be further applied to the study new treatments related with SP deregulation and may ultimately offer new opportunities for therapeutic interventions in neurodegenerative diseases.\n\nAuthor SummaryParkinsons disease is one of the most prevalent neurodegenerative diseases across population over age 50. Affecting controlled movements and non-motor symptoms, treatments for Parkinson prevention are indispensable to reduce patients population in the future. Epidemiological data provide evidence that nicotine have a neuroprotective effect decreasing Parkinson prevalence. By interacting with nicotine receptors in neurons and modulating signaling pathways expressing anti-apoptotic genes nicotine arise as a putative neuroprotective therapy. Nevertheless, toxicity and dependency prevent the use of nicotine as a suitable drug. Nicotine analogs, structurally similar compounds emerge as an alternative for Parkinson preventive treatment. In this sense we developed a quantitative strategy to predict the potential neuroprotective activity of nicotine analogs. Our model is the first approach to predict neuroprotection in the context of Parkinson and signaling pathways using machine learning and computational chemistry.

bioinformatics↗

bioRxiv2019

Overlapping Genetic Architecture between Parkinson Disease and Melanoma

Epidemiologic studies have reported inconsistent results regarding an association between Parkinson disease (PD) and cutaneous melanoma (melanoma). Identifying shared genetic architecture between these diseases can support epidemiologic findings and identify common risk genes and biological pathways. Here we apply polygenic, linkage disequilibrium-informed methods to the largest available case-control, genome-wide association study summary statistic data for melanoma and PD. We identify positive and significant genetic correlation (correlation: 0.17, 95% CI 0.10 to 0.24; P = 4.09 x 10-06) between melanoma and PD. We further demonstrate melanoma and PD-inferred gene expression to overlap across tissues (correlation: 0.14, 95% CI 0.06 to 0.22; P = 7.87 x 10-04), and highlight seven genes including PIEZO1, TRAPPC2L, and SOX6 as potential mediators of the genetic correlation between melanoma and PD. These findings demonstrate specific, shared genetic architecture between PD and melanoma that manifests at the level of gene expression.

genetics↗

bioRxiv2019

A psychometric evaluation of the 12-item EPQ-R neuroticism scale in 384,183 UK Biobank participants using item response theory (IRT)

Neuroticism has been described as a broad and pervasive personality dimension or heterogeneous trait measuring components of mood instability, such as worry; anxiety; irritability; moodiness; self-consciousness and sadness. Consistent with depression and anxiety-related disorders, increased neuroticism places an individual vulnerable for other unipolar and bipolar mood disorders and therefore highly relevant in epidemiologic research. However, the measurement of neuroticism remains a challenge. We aimed to adapt the 12-item Eysenck Personality Questionnaire-Revised Neuroticism (EPQ-RN) scale for use in epidemiologic studies by identifying psychometrically efficient items using item response theory. The 12-item EPQ-RN scale was evaluated by estimating an IRT model on data from 401,527 UK Biobank participants aged 39 to 73 years (M = 56.41 years; SD = 8.06), 53.68% female. The IRT model yielded two item characteristics: item discrimination, an indicator of how well an item differentiates between respondents, and item difficulty, an indicator of the amount of the latent construct (neuroticism) needed to endorse an item. The EPQ-RN exhibited psychometric inefficiency with poor discrimination at extremes of the scale range. High and low scores are relatively poorly represented and uninformative suggesting that high neuroticism scores derived from the scale are a function of cumulative mid-range values. Following systematic item deletion, a 3-item scale was found to have high levels of discrimination, but offered a narrow range of difficulty i.e. was not sensitive to low levels of neuroticism. A 7-item scale was found to be most informative; providing high levels of discrimination across the range of neuroticism scores.

neuroscience↗

bioRxiv2019

The ancestral population size conditioned on the reconstructed phylogenetic tree with occurrence data

We consider a homogeneous birth-death process with three different sampling schemes. First, individuals can be sampled through time and included in a reconstructed tree. Second, they can be sampled through time and only recorded as a point occurrence along a timeline. Third, extant individuals are sampled and included in the reconstructed tree with a fixed probability. We further consider that sampled individuals can be removed or not from the process, upon sampling, with fixed probability.\n\nGiven an outcome of the process, composed of the joint observation of a reconstructed phylogenetic tree and a record of occurrences not included in the tree, we derive the conditional probability distribution of the population size any time in the past. We additionally provide an algorithm to simulate ancestral population size trajectories given the observation of a reconstructed tree and occurrences.\n\nThis distribution can readily be used to perform inferences of the ancestral population size in the field of epidemiology and macroevolution. In epidemiology, these results will pave the way towards jointly considering data from case count studies and reconstructed transmission trees. In macroevolution, it will foster the joint examination of the fossil record and extant taxa to reconstruct past biodiversity.

evolutionary biology↗

bioRxiv2019

High Plasmodium infection intensity in naturally infected malaria vectors in Africa

The population dynamics of human-to-mosquito malaria transmission in the field has important implications for the genetics, epidemiology and control of malaria. The number of oocysts in oocysts positive mosquitoes developing from a single, naturally acquired infectious blood meal (herein referred to as parasite exposure) greatly influence the effectiveness of transmission blocking interventions but still remains poorly documented. During a year-long analysis of malaria parasite transmission in Burkina Faso we caught and dissected wild malaria vectors to assess Plasmodium oocysts prevalence and load (the number of oocysts counted in mosquitoes with detectable oocysts) and the prevalence of salivary gland sporozoites. This was compared to malaria endemicity in the human population assessed in cross-sectional surveys. Data was analyzed using a novel transmission mathematical model to estimate the per-bite transmission probability and the average parasite exposure of mosquitoes for each location. Observed oocysts load and estimated parasite exposure in naturally infected mosquitoes is substantially higher than previous estimates (ranging from 3.2 to 24.5 according to seasons and locations) and indicates a strong positive association between parasite exposure of mosquitoes and parasite prevalence in human. This work suggests that highly infected mosquitoes may have a greater influence on the epidemiology and genetics of the parasite and that novel partially effective transmission blocking interventions may become more effective at halting transmission as parasite exposure is diminished.

ecology↗

bioRxiv2019

Evidence of adaptive host and vector manipulation by plant viruses revealed through combined meta-analysis and modeling approaches.

A growing number of studies indicate that plant viruses enhance their own transmission by modifying host phenotypes and vector behavior, leading to the hypothesis that such effects are manipulations resulting from virus adaptations. However, few studies have linked putative manipulations with virus components, and the true frequency and magnitude of host and vector manipulation across virus taxa remains unknown. To address this knowledge gap, we performed a meta-analysis to quantify convergence in virus effects on hosts and vectors across taxonomic groups that share transmission mechanism traits, and thereby stand to benefit from similar sequences of vector behavior. We then combined meta-analysis outputs with an epidemiological model to assess consequences of manipulation for virus spread. Overall, transmission mechanism traits strongly predicted the magnitude and nature of virus effects on vector preferences and performance. Models parameterized with meta-analysis data demonstrate that manipulation effects enhance virus spread, and that viruses with long acquisition times and retention durations are under strong selection pressure to manipulate transmission. By combining meta-analysis with epidemiological modeling, our results confirm that host and vector manipulation are important aspects of plant virus ecology and evolution while emphasizing the need to incorporate more pathosystems and transmission mechanism traits in future studies.

ecology↗