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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2018

Laboratory and Molecular Surveillance of Paediatric Typhoidal Salmonella in Nepal: Antimicrobial Resistance and Implications for Vaccine Policy

BackgroundChildren are substantially affected by enteric fever in most settings with a high burden of the disease, which could be due to immune naivety, or enhanced risk of exposure to the pathogen. Although Nepal is a high burden setting for enteric fever, the bacterial population structure and transmission dynamics are poorly delineated in young children, the proposed target group for immunization programs.\n\nMethodsBlood culture surveillance amongst children aged 2 months to 15 years of age was conducted at Patan Hospital between 2008 and 2016. A total of 198 S. Typhi and 66 S. Paratyphi A isolated from children treated in both inpatient and outpatient settings were subjected to whole genome sequencing and antimicrobial susceptibility testing. Demographic and clinical data were also collected from the inpatients. The resulting data were used to place these paediatric Nepali isolates into a worldwide context, based on their phylogeny and carriage of molecular determinants of antimicrobial resistance (AMR).\n\nResultsChildren aged [≤]4 years made up >40% of the inpatient population. The majority of isolates (78 %) were S. Typhi, comprising several distinct genotypes but dominated by 4.3.1 (H58). Several distinct S. Typhi genotypes were identified, but the globally disseminated S. Typhi clade 4.3.1 (H58) dominated. The majority of isolates (86%) were insusceptible to fluoroquinolones. This was mainly associated with S. Typhi H58 Lineage II and S. Paratyphi A; non-susceptible strains from these two genotypes accounted for 50% and 25% of all enteric fever cases. Multi-drug resistance (MDR) was rare (3.5% of S. Typhi, 0 S. Paratyphi A) and restricted to chromosomal insertions of AMR genes in H58 lineage I strains. Comparison to global data sets showed the local S. Typhi and S. Paratyphi A strains had close genetic relatives in other South Asian countries, indicating regional strain circulation.\n\nConclusionsThese data indicate that enteric fever in Nepal continues to be a major public health issue with ongoing inter- and intra-country transmission, and highlights the need for regional coordination of intervention strategies. The absence of a S. Paratyphi A vaccine is cause for concern, given its prevalence as an enteric fever agent in this setting, and the large proportion of isolates displaying fluoroquinolone resistance. This study also highlights an urgent need for routine laboratory and molecular surveillance to monitor the epidemiology of enteric fever and evolution of antimicrobial resistance within the bacterial population as a means to facilitate public health interventions in prevention and control of this febrile illness.

molecular biology↗
bioRxiv2018

Timing malaria transmission with mosquito fluctuations

Temporal variations in the activity of arthropod vectors can dramatically affect the epidemiology and evolution of vector-borne pathogens. Here we explore the \"Hawking hypothesis\" stating that these pathogens may evolve the ability to time investment in transmission to match the activity of their vectors. First, we use a theoretical model to identify the conditions promoting the evolution of time-varying transmission strategies in pathogens. Second, we experimentally test the \"Hawking hypothesis\" by monitoring the within-host dynamics of Plasmodium relictum throughout the acute and the chronic phases of the bird infection. To explore the periodicity in the host parasite density, we develop a new methodology to correct for non-stationarities in the host parasitaemia. We detect a periodic increase of parasitaemia and mosquito infection in the late afternoon that coincides with an increase in the biting activity of its natural vector. We also detect a positive effect of mosquito bites on Plasmodium replication in the birds both in the acute and in the chronic phases of the infection. This study highlights that Plasmodium parasites use two different strategies to increase the match between transmission potential and vector availability. We discuss the adaptive nature of these unconditional and plastic transmission strategies with respect to the time-scale and the predictability of the fluctuations in the activity of the vector.\n\nImpact SummarySeasonal and daily fluctuations in the environment affect the abundance and the activity of vectors and may therefore have profound consequences on the transmission of infectious diseases. Here we show that, in accord with evolutionary theory, malaria parasites have evolved two different and complementary strategies to cope with fluctuations in mosquito availability. First, Plasmodium relictum adopts an unconditional strategy whereby within-host parasitaemia and mosquito infection increases in the afternoon and in the evening, when its vector, the Culex pipiens mosquito, is most active. Second, we find evidence for a plastic strategy allowing the parasitaemia to rapidly increase after exposure to mosquito bites.

evolutionary biology↗
bioRxiv2018

INSaFLU: an automated open web-based bioinformatics suite “from-reads” for influenza whole-genome-sequencing-based surveillance

A new era of flu surveillance has already started based on the genetic characterization and exploration of influenza virus evolution at whole-genome scale. Although this has been prioritized by national and international health authorities, the demanded technological transition to whole-genome sequencing (WGS)-based flu surveillance has been particularly delayed by the lack of bioinformatics infrastructures and/or expertise to deal with primary next-generation sequencing (NGS) data. Here, we launch INSaFLU (\"INSide the FLU\"), which, to the best of our knowledge, is the first influenza-specific bioinformatics free web-based suite that deals with primary data (reads) towards the automatic generation of the output data that are actually the core first-line \"genetic requests\" for effective and timely influenza laboratory surveillance (e.g., type and sub-type, gene and whole-genome consensus sequences, variants annotation, alignments and phylogenetic trees). By handling NGS data collected from any amplicon-based schema, the implemented pipeline enables any laboratory to perform advanced, multi-step software intensive analyses in a user-friendly manner without previous training in bioinformatics. INSaFLU gives access to user-restricted sample databases and projects management, being a transparent and highly flexible tool specifically designed to automatically update project outputs as more samples are uploaded. Data integration is thus completely cumulative and scalable, fitting the need for a continuous epidemiological surveillance during the flu epidemics. Multiple outputs are provided in nomenclature-stable and standardized formats that can be explored in situ or through multiple compatible downstream applications for fine-tune data analysis. This platform additionally flags samples as \"putative mixed infections\" if the population admixture enrolls influenza viruses with clearly distinct genetic backgrounds, and enriches the traditional \"consensus-based\" influenza genetic characterization with relevant data on influenza sub-population diversification through a depth analysis of intra-patient minor variants. This dual approach is expected to strengthen our ability not only to detect the emergence of antigenic and drug resistance variants, but also to decode alternative pathways of influenza evolution and to unveil intricate routes of transmission. In summary, INSaFLU supplies public health laboratories and influenza researchers with an open \"one size fits all\" framework, potentiating the operationalization of a harmonized multi-country WGS-based surveillance for influenza virus.\n\nINSaFLU can be accessed through https://insaflu.insa.pt (see homepage view in Figure 1).\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC=\"FIGDIR/small/253161_fig1.gif\" ALT=\"Figure 1\">\nView larger version (26K):\norg.highwire.dtl.DTLVardef@1111419org.highwire.dtl.DTLVardef@3e99c2org.highwire.dtl.DTLVardef@1e0a953org.highwire.dtl.DTLVardef@8c9ea6_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 1.C_FLOATNO INSaFLU homepage\n\nC_FIG

bioinformatics↗
bioRxiv2018

Phylodynamic model adequacy using posterior predictive simulations

Rapidly evolving pathogens, such as viruses and bacteria, accumulate genetic change at a similar timescale over which their epidemiological processes occur, such that it is possible to make inferences about their infectious spread using phylogenetic time-trees. For this purpose it is necessary to choose a phylodynamic model. However, the resulting inferences are contingent on whether the model adequately describes key features of the data. Model adequacy methods allow formal rejection of a model if it cannot generate the main features of the data. We present TreeModelAdequacy (TMA), a package for the popular BEAST2 software, that allows assessing the adequacy of phylodynamic models. We illustrate its utility by analysing phylogenetic trees from two viral outbreaks of Ebola and H1N1 influenza. The main features of the Ebola data were adequately described by the coalescent exponential-growth model, whereas the H1N1 influenza data was best described by the birth-death SIR model.

bioinformatics↗
bioRxiv2018

Why multiple infections favour virulent parasites

It is now a fact that several strains/species (hereafter types) of parasites circulate in natural host populations. Parasite polymorphism can even occur within the same host, where distinct parasite types can interact in various ways. This can affect their transmission and, therefore, their evolution. We still lack general predictions regarding the evolution, in such multiple infection contexts, of virulence - the infection-induced host mortality, essentially because its emanation from within-host growth was often ignored so far. Here, we explicitly investigate within-host interactions, within-host competition outcomes, epidemiological dynamics and evolutionary invasibility using a formalism as general as possible. Focusing on chronic dimorphic infections caused by horizontally-transmitted microparasites, we apply both dynamical systems and probabilistic approaches to this bottom-up sequence of dynamics to explore the evolutionary outcomes. We show that within-host growth traits are under strong selective pressure and when small mutations affect them, most of the surviving mutants are more virulent than their resident. We thus identify a robust and unavoidable selection bias towards higher virulence.

evolutionary biology↗
bioRxiv2018

Investigation Of Gluthatione S-Transferase Variants In A Healht Population In Goiania-Go

Genetic polymorphisms in glutathione S-transferases (GSTs) genes might influence the detoxification activities of the enzymes predisposing individuals to a lot of disiases. Owing to the presence of these genetic variants, inter-individual and ethnic differences in GSTs detoxification capacity have been observed in various populations. Therefore, the present study was performed to determine the prevalence GSTM1*0/*0, GSTT1*0/*0 and GSTP1 Ile105Val polymorphisms in 100 healthy individuals from Goiania - GO. GSTM1 and GSTT1 polymorphisms were analyzed by a Multiplex-PCR approach, whereas GSTP1 polymorphisms were examined by PCR-RFLP. The frequencies of GSTM1 and GSTT1 *0/*0 genotypes are 49% and 31%, respectively. The frequencies of GSTP1 Ile/Ile, Ile/Val, and Val/Val genotypes were 40%, 53%, and 7%, respectively. The wild-type (Ile) and variant (Val) allele frequencies were 66.5% and 33.5%, respectively. The combined genotypes distribution of GSTM1, GSTT1 and GSTP1 polymorphisms showed 12 possible genotypes present in our population; seven of them have a frequency greater than 5%. The effect of combined genotypes of these GSTs polymorphisms is still unknown. These findings in healthy population, give us such more information for the future epidemiological and clinical studies. Using to examine the effect of these combinations in drugs metabolism and cancer predisposition, further largest group would be needed, since their frequencies are quite low. To our of GSTs polymorfisms, this is the first study indicating the frequencies of genetic polimorphisms of GST superfamily in a health population in a Goiania population.

genetics↗
bioRxiv2018

Characterization of missing values in untargeted MS-based metabolomics data and evaluation of missing data handling strategies

BACKGROUNDUntargeted mass spectrometry (MS)-based metabolomics data often contain missing values that reduce statistical power and can introduce bias in epidemiological studies. However, a systematic assessment of the various sources of missing values and strategies to handle these data has received little attention. Missing data can occur systematically, e.g. from run day-dependent effects due to limits of detection (LOD); or it can be random as, for instance, a consequence of sample preparation.\n\nMETHODSWe investigated patterns of missing data in an MS-based metabolomics experiment of serum samples from the German KORA F4 cohort (n = 1750). We then evaluated 31 imputation methods in a simulation framework and biologically validated the results by applying all imputation approaches to real metabolomics data. We examined the ability of each method to reconstruct biochemical pathways from data-driven correlation networks, and the ability of the method to increase statistical power while preserving the strength of established genetically metabolic quantitative trait loci.\n\nRESULTSRun day-dependent LOD-based missing data accounts for most missing values in the metabolomics dataset. Although multiple imputation by chained equations (MICE) performed well in many scenarios, it is computationally and statistically challenging. K-nearest neighbors (KNN) imputation on observations with variable pre-selection showed robust performance across all evaluation schemes and is computationally more tractable.\n\nCONCLUSIONMissing data in untargeted MS-based metabolomics data occur for various reasons. Based on our results, we recommend that KNN-based imputation is performed on observations with variable pre-selection since it showed robust results in all evaluation schemes.\n\nKey messagesO_LIUntargeted MS-based metabolomics data show missing values due to both batch-specific LOD-based and non-LOD-based effects.\nC_LIO_LIStatistical evaluation of multiple imputation methods was conducted on both simulated and real datasets.\nC_LIO_LIBiological evaluation on real data assessed the ability of imputation methods to preserve statistical inference of biochemical pathways and correctly estimate effects of genetic variants on metabolite levels.\nC_LIO_LIKNN-based imputation on observations with variable pre-selection and K = 10 showed robust performance for all data scenarios across all evaluation schemes.\nC_LI

systems biology↗
bioRxiv2018

Molecular Typing with COI - DNA Barcode of mosquitoes with medical importance from rural area from La Pintada, Antioquia, Colombia

DNA barcode is a methodology that allows the identification of species using a short fragment of cytochrome oxidase I and library sequences stored in the barcode of life database (bold>), make up an alternative tool for mosquito identification in areas epidemiologically active for arboviruses, protozoa and bacteria. In our study, we collected 114 adult mosquitoes in a rural area in the municipality of La Pintada (Antioquia, Colombia), and were separate for genus and species using morphological keys. Two Legs were taken of specimens mounted, and these were used for DNA extraction, amplification of COI-Barcode through PCR and sequencing. 38 sequences were characterized of seven mosquito species and used in bold> for molecular identification, subsequent characterization of genetic distances intra/interspecies, and MOTUs grouping by neighbor-joining analyses. Seven MOTUs were separate corresponding to seven species identify by morphological keys. bold> was able to identify five species, and two were identified to the genre. The following medically important mosquitoes were recorded in the rural area from La Pintada (Antioquia): Aedes aegypti, Anopheles triannulatus, Coquillettidia nigricans, Mansonia titillans, Ochlerotatus angustivitatus, Psorophora ferox and Psorophora (Grabhamia) sp.

zoology↗
bioRxiv2018

Identifying tissues implicated in Anorexia Nervosa using Transcriptomic Imputation

Anorexia nervosa (AN) is a complex and serious eating disorder, occurring in ~1% of individuals. Despite having the highest mortality rate of any psychiatric disorder, little is known about the aetiology of AN, and few effective treatments exist.\n\nGlobal efforts to collect large sample sizes of individuals with AN have been highly successful, and a recent study consequently identified the first genome-wide significant locus involved in AN. This result, coupled with other recent studies and epidemiological evidence, suggest that previous characterizations of AN as a purely psychiatric disorder are over-simplified. Rather, both neurological and metabolic pathways may also be involved.\n\nIn order to elucidate more of the system-specific aetiology of AN, we applied transcriptomic imputation methods to 3,495 cases and 10,982 controls, collected by the Eating Disorders Working Group of the Psychiatric Genomics Consortium (PGC-ED). Transcriptomic Imputation (TI) methods approaches use machine-learning methods to impute tissue-specific gene expression from large genotype data using curated eQTL reference panels. These offer an exciting opportunity to compare gene associations across neurological and metabolic tissues. Here, we applied CommonMind Consortium (CMC) and GTEx-derived gene expression prediction models for 13 brain tissues and 12 tissues with potential metabolic involvement (adipose, adrenal gland, 2 colon, 3 esophagus, liver, pancreas, small intestine, spleen, stomach).\n\nWe identified 35 significant gene-tissue associations within the large chromosome 12 region described in the recent PGC-ED GWAS. We applied forward stepwise conditional analyses and FINEMAP to associations within this locus to identify putatively causal signals. We identified four independently associated genes; RPS26, C12orf49, SUOX, and RDH16. We also identified two further genome-wide significant gene-tissue associations, both in brain tissues; REEP5, in the dorso-lateral pre-frontal cortex (DLPFC; p=8.52x10-07), and CUL3, in the caudate basal ganglia (p=1.8x10-06). These genes are significantly enriched for associations with anthropometric phenotypes in the UK BioBank, as well as multiple psychiatric, addiction, and appetite/satiety pathways. Our results support a model of AN risk influenced by both metabolic and psychiatric factors.

genetics↗
bioRxiv2018

Evidence of a common causal relationship between body mass index and inflammatory skin disease: a Mendelian Randomization study

ObjectivePsoriasis and eczema are common inflammatory skin diseases that have been reported to be associated with obesity. However, causality has not yet been established. We aimed to investigate the possible causal relationship between body mass index (BMI) and psoriasis or eczema.\n\nMethodsFollowing a review of published epidemiological evidence of the association between obesity and either psoriasis or eczema, Mendelian Randomization (MR) was used to test for a causal relationship between BMI and these inflammatory skin conditions. We used a genetic instrument comprising 97 single nucleotide polymorphisms (SNPs) associated with BMI. One-sample MR was conducted using individual-level data (401,508 individuals) from the UK Biobank and the Nord-Trondelag Health Study (HUNT), Norway. Two-sample MR was performed with summary-level data (731,021 individuals) from published BMI, psoriasis and eczema GWAS. The one-sample and two-sample MR estimates were meta-analysed using a fixed effect model. To explore the reverse causal direction, MR analysis with genetic instruments comprising variants from recent genome-wide analyses for psoriasis and eczema were used to test if inflammatory skin disease has a causal effect on BMI.\n\nResultsPublished observational data show an association of greater BMI with both psoriasis and eczema case status. The observational associations were confirmed in UK Biobank and HUNT datasets. MR analyses provide evidence that higher BMI causally increases the odds of psoriasis (by 53% per 5 units higher BMI; OR= 1.09 (1.06 to 1.12) per 1 kg/m2; P=4.67x10-9) and eczema (by 8% per 5 units higher BMI; OR=1.02 (1.00 to 1.03) per 1 kg/m2; P=0.09). When investigating causality in the opposite direction, MR estimates provide little evidence for an effect of either psoriasis or eczema influencing BMI.\n\nConclusionOur study, using genetic variants as instrumental variables for BMI, shows that higher BMI leads to a higher risk of inflammatory skin disease. The causal relationship was stronger for psoriasis than eczema. Therapies and life-style interventions aimed at controlling BMI or targeting the mechanisms linking obesity with skin inflammation may offer an opportunity for the prevention or treatment of these common skin diseases.

genetics↗
bioRxiv2018

A systematic approach for identifying shared mechanisms in epilepsy and its comorbidities

Cross-sectional epidemiological studies have shown that the incidence of several nervous system diseases is more frequent in epilepsy patients than in the general population. Some comorbidities (e.g., Alzheimers disease and Parkinsons disease) are also risk factors for the development of seizures; suggesting they may share pathophysiological mechanisms with epilepsy.\n\nA literature-based approach was used to identify gene overlap between epilepsy and its comorbidities as a proxy for a shared genetic basis for disease, or genetic pleiotropy, as a first effort to identify shared mechanisms. While the results identified neurological disorders as the group of diseases with the highest gene overlap, this analysis was insufficient for identifying putative common mechanisms shared across epilepsy and its comorbidities. This motivated the use of a dedicated literature mining and knowledge assembly approach in which a cause-and-effect model of epilepsy was captured with Biological Expression Language.\n\nAfter enriching the knowledge assembly with information surrounding epilepsy, its risk factors, its comorbidities, and antiepileptic drugs, a novel comparative mechanism enrichment approach was used to propose several downstream effectors (including the GABA receptor, GABAergic pathways, etc.) that could explain the therapeutic effects carbamazepine in both the contexts of epilepsy and AD.\n\nWe have made the Epilepsy Knowledge Assembly available at https://www.scai.fraunhofer.de/content/dam/scai/de/downloads/bioinformatik/epilepsy.bel and queryable through NeuroMMSig at http://neurommsig.scai.fraunhofer.de. The source code used for analysis and tutorials for reproduction are available on GitHub at https://github.com/cthoyt/epicom.

systems biology↗
bioRxiv2018

The tumor suppressor FBW7 and the vitamin D receptor are mutual cofactors.

The E3 ligase FBW7 targets drivers of cell cycle progression such as c-MYC for proteasomal degradation. It is frequently mutated in cancer, and is a tumor suppressor. Extensive epidemiological data links vitamin D deficiency to increased incidence of several cancers, although the underlying cancer-preventive mechanisms are poorly understood. Here, we show that hormonal 1,25-dihydroxyvitamin D3 (1,25D) rapidly stimulates the interaction of the VDR with FBW7, and that of FBW7 with c-MYC. In contrast, it blocks the association of FBW7 with c-MYC antagonist MXD1. 1,25D also enhances the association of FBW7, proteasome subunits, and ubiquitin with DNA-bound c-MYC, consistent with induced degradation of c-MYC on DNA. In addition to c-MYC, 1,25D accelerates the turnover of other FBW7 target proteins. Intriguingly, FBW7 is essential for optimal VDR gene expression. It is also recruited to VDR targets genes, and its depletion attenuates 1,25D-stimulated VDR DNA binding, transactivation, and cell cycle arrest. Thus, the VDR and FBW7 are mutual cofactors, which provides a molecular basis for the cancer-preventive actions of vitamin D through accelerated turnover of FBW7 target proteins.

molecular biology↗
bioRxiv2018

Humidity as a non-pharmaceutical intervention for influenza A

Influenza is a global problem infecting 5-10 % of adults and 20-30 % of children annually. Non-pharmaceutical interventions (NPIs) are attractive approaches to complement vaccination in the prevention and reduction of influenza. Strong cyclical reduction of absolute humidity has been associated with influenza outbreaks in temperate climates. This study tested the hypothesis that raising absolute humidity above seasonal lows would impact influenza virus survival and transmission in a key source of influenza distribution, a community school. Air samples and objects handled by students (e.g. blocks and markers) were collected from preschool classrooms. All samples were processed and PCR used to determine the presence of influenza and its amount. Additionally samples were tested for their ability to infect cells in cultures. Deliberate classroom humidification (with commercial steam humidifiers) resulted in a significant reduction of the total number of influenza positive samples (air and fomite), viral copy number, and efficiency of viral infectivity. This is the first prospective study suggesting that exogenous humidification could serve as a scalable NPI for influenza or other viral outbreaks.\n\nAuthor summaryHuman influenza infections have a substantial impact on society (including lost productivity and medical costs). Children, 3-4 years of age are the main introducers and spreaders of influenza within a household and community. There is evidence from laboratory and epidemiological studies that suggests that low humidity in winter (in temperate climates) may increase the ability of influenza virus to survive and spread between individuals. We wanted to know if added in humidity (through steam humidifiers) could reduce the amount of influenza present and its spread within preschool classrooms (students aged 3-4 years)? Additionally, we looked at the infectivity of the influenza isolated and if there were differences in the number of students with influenza-like illnesses during our study. We show that humidification can reduce the amount of influenza present within samples from preschool classrooms and that there were fewer infectious samples compared to non-humidified rooms. There were small numbers of students ill with influenza like illnesses during our study so additional studies will need to look further at humidification as a way to reduce influenza infection and transmission.

microbiology↗
bioRxiv2018

Arsenite exposure inhibits histone acetyltransferase p300 for attenuating H3K27ac at enhancers in low-dose exposed mouse embryonic fibroblast cells

Epidemiological investigations have validated the positive relationships between arsenic in drinking water and several cancers, including skin, liver and lung cancers. Besides genotoxicity, arsenic exposure-related pathogenesis of disease is widely considered through epigenetic mechanisms; however, the underlying mechanistic insight remains elusive. Herein we explore the initial epigenetic changes via acute low-dose arsenite exposures of mouse embryonic fibroblast (MEF) cells and Dot1L knockout MEF (Dot1L-/- for abbreviation) cells. Our RNA-seq and Western blot data demonstrated that, in both cell lines, acute low-dose arsenite exposure abolished histone acetyltransferase p300 at the RNA level and subsequent protein level. Consequently, p300-specific main target histone H3K27ac, a marker separating active from poised enhancers, decreased dramatically as validated by both Western blot and ChIP-seq analyses. Concomitantly, H3K4me1 as another well-known marker for enhancers also showed significant decreases, suggesting an underappreciated crosstalk between H3K4me1 and H3K27ac involved in arsenite exposure. Significantly, arsenite exposure-reduced H3K27ac and H3K4me1 inhibit the expression of genes including EP300 itself and Kruppel Like Factor 4(Klf4), a tumor suppressor gene. Collectively, our investigations identify p300 as an internal bridging factor within cells to sense external environmental arsenite exposure to alter chromatin, thereby changing gene transcription for disease pathogenesis.

pharmacology and toxicology↗
bioRxiv2018

Breast cancer susceptibility: an integrative analysis of genomic data

BackgroundGenome wide association studies (GWAS) are greatly accelerating the pace of discovery of germline variants underlying the genetic architecture of sporadic breast cancer predisposition. We have built the first knowledge-base dedicated to this field and used it to generate hypotheses on the molecular pathways involved in disease susceptibility.\n\nMethodsWe gathered data on the common single nucleotide polymorphisms (SNPs) discovered by breast cancer risk GWAS. Information on SNP functional effect (including data on linkage disequilibrium, expression quantitative trait locus, and SNP relationship with regulatory motifs or promoter/enhancer histone marks) was utilized to select putative breast cancer predisposition genes (BCPGs). Ultimately, BCPGs were subject to pathway (gene set enrichment) analysis and network (protein-protein interaction) analysis.\n\nResultsData from 38 studies (28 original case-control GWAS enrolling 383,260 patients with breast cancer; and 10 GWAS meta-analyses) were retrieved. Overall, 281 SNPs were associated with the risk of breast cancer with a P-value <10E-06 and a minor allele frequency >1%. Based on functional information, we identified 296 putative BCPGs. Primary analysis showed that germline perturbation of classical cancer-related pathways (e.g., apoptosis, cell cycle, signal transduction including estrogen receptor signaling) play a significant role in breast carcinogenesis. Other less established pathways (such as ribosome and peroxisome machineries) were also highlighted. In the main subgroup analysis, we considered the BCPGs encoding transcription factors (n=36), which in turn target 252 genes. Interestingly, pathway and network analysis of these genes yielded results resembling those of primary analyses, suggesting that most of the effect of genetic variation on disease risk hinges upon transcriptional regulons.\n\nConclusionsThis knowledge-base, which is freely available and will be annually updated, can inform future studies dedicated to breast cancer molecular epidemiology as well as genetic susceptibility and development.\n\nAbbreviations

cancer biology↗
bioRxiv2018

Topographic effects on dispersal patterns of Phytophthora cinnamomi at a stand scale in a Spanish heathland

Phytophthora cinnamomi is one of the most important plant pathogens in the world, causing root rot in more than a thousand plant species. This observational study was carried out on a P. cinnamomi infected heathland of Erica umbellata used as goat pasture. The patterns and shapes of disease foci and their distribution were described in a spatial and temporal context using an aerial photograph record. A set of topographic traits was selected on the basis of a disease dynamic hypothesis and their effects on observed spatial disease patterns were analyzed. Incipient infections situated in flat terrain expanded as compact circular front patterns with a low growth rate. On slopes, disease patches developed more rapidly down slope, forming parabolic shapes. The axis direction of the parabolas was highly correlated with terrain aspect, while the parabolic amplitude was associated with land curvature and slope. New secondary foci appeared over the years producing an accelerated increase of the affected surface. These new foci were observed in sites where disease density was higher or near sites more frequently visited by animals such as the stable or the forage crop. In contrast, a smaller number of disease foci occur in areas which animals are reluctant to visit, such as where they have a short range of vision. Our results suggest that 1) the growth of existing P. cinnamomi foci is controlled by a combination of root-to-root contact and water flows, 2) the increase in the diseased area arises mainly from the multiplication of patches, 3) the formation of new foci is mediated by long-distance transport due to the movement of animals and humans along certain preferential pathways, and 4) geomorphology and topography traits are associated with the epidemiology of this soil-borne pathogen.

plant biology↗
bioRxiv2018

Leveraging Existing 16S rRNA Gene Surveys to Identify Reproducible Biomarkers in Individuals with Colorectal Tumors

An increasing body of literature suggests that both individual and collections of bacteria are associated with the progression of colorectal cancer. As the number of studies investigating these associations increases and the number of subjects in each study increases, a meta-analysis to identify the associations that are the most predictive of disease progression is warranted. We analyzed previously published 16S rRNA gene sequencing data collected from feces and colon tissue. We quantified the odds ratios (ORs) for individual bacterial taxa that were associated with an individual having tumors relative to a normal colon. Among the fecal samples, there were no taxa that had significant ORs associated with adenoma and there were 8 taxa with significant ORs associated with carcinoma. Similarly, among the tissue samples, there were no taxa that had a significant OR associated with adenoma and there were 3 taxa with significant ORs associated with carcinoma. Among the significant ORs, the association between individual taxa and tumor diagnosis was equal or below 7.11. Because individual taxa had limited association with tumor diagnosis, we trained Random Forest classification models using only the taxa that had significant ORs, using the entire collection of taxa found in each study, and using operational taxonomic units defined based on a 97% similarity threshold. All training approaches yielded similar classification success as measured using the Area Under the Curve. The ability to correctly classify individuals with adenomas was poor and the ability to classify individuals with carcinomas was considerably better using sequences from fecal or tissue.\n\nImportanceColorectal cancer is a significant and growing health problem in which animal models and epidemiological data suggest that the colonic microbiota have a role in tumorigenesis. These observations indicate that the colonic microbiota is a reservoir of biomarkers that may improve our ability to detect colonic tumors using non-invasive approaches. This meta-analysis identifies and validates a set of 8 bacterial taxa that can be used within a Random Forest modeling framework to differentiate individuals as having normal colons or carcinomas. When models trained using one dataset were tested on other datasets, the models performed well. These results lend support to the use of fecal biomarkers for the detection of tumors. Furthermore, these biomarkers are plausible candidates for further mechanistic studies into the role of the gut microbiota in tumorigenesis.

microbiology↗
bioRxiv2018

The changing landscape of VREfm in Victoria, Australia: a state-wide genomic snapshot

Vancomycin-resistant Enterococcus faecium (VREfm) represent a major source of nosocomial infection worldwide. In Australia, the vanB genotype is dominant; however there has been a recent increase in the predominantly plasmid-encoded vanA genotype, prompting investigation into the genomic epidemiology of VREfm in this context.\n\nMaterials and MethodsA cross-sectional study of VREfm in Victoria, Australia (Nov.10th - Dec.9th, 2015). A total of 321 VREfm isolates (from 286 patients) were collected and whole-genome sequenced with Illumina NextSeq. Single nucleotide polymorphisms (SNPs) were used to assess relatedness. Multi-locus sequence types (STs), and genes associated with resistance and virulence were identified. The vanA-harbouring plasmid from an isolate from each ST was assembled using long-read data.\n\nResultsvanA-VREfm comprised 17.8% of isolates. ST203, ST80 and a pstS(-) clade, ST1421, predominated (30.5%, 30.5% and 37.2% of vanA-VREfm, respectively). Most vanB-VREfm were ST796 (77.7%). vanA-VREfm isolates were closely-related within hospitals vs. between them (core SNPs 10 [interquartile range 1-357] vs. 356 [179-416] respectively), suggesting discrete introductions of vanA-VREfm, with subsequent intra-hospital transmission. In contrast, vanB-VREfm had similar core SNP distributions within vs. between hospitals, due to widespread dissemination of ST796. Overall, vanA-harbouring plasmids differed across STs, and with exception of ST78 and ST796, Tn1546 transposons also varied.\n\nConclusionsvanA-VREfm in Victoria is associated with multiple STs, and is not solely mediated by a single shared plasmid/Tn1546 transposon; clonal transmission appears to play an important role, predominantly within, rather than between, hospitals. In contrast, vanB-VREfm appears to be well-established and widespread across Victorian healthcare institutions.

genomics↗