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bioRxiv2020

Whole-Genome Enrichment and Sequencing of Chlamydia trachomatis Directly from Patient Clinical Vaginal and Rectal Swabs

Chlamydia trachomatis is the most prevalent cause of bacterial sexually transmitted infections (STIs) worldwide. U.S. cases have been steadily increasing for more than a decade in both the urogenital tract and rectum. C. trachomatis is an obligate intracellular bacterium that is not easily cultured, limiting the capacity for genome studies to understand strain diversity and emergence among various patient populations globally. While Agilent SureSelectXT target-enrichment RNA bait libraries have been developed for whole-genome enrichment and sequencing of C. trachomatis directly from clinical urine, vaginal, conjunctival and rectal samples, efficiencies are only 60-80% for [≥]95-100% genome coverage. We therefore re-designed and expanded the RNA bait library to augment enrichment of the organism from clinical samples to improve efficiency. We describe the expanded library, the limit of detection for C. trachomatis genome copy input, and the 100% efficiency and high-resolution of generated genomes where genomic recombination among paired vaginal and rectal specimens from four patients was identified. This workflow provides a robust approach for discerning genomic diversity and advancing our understanding of the molecular epidemiology of contemporary C. trachomatis STIs across sample types, among geographic populations, sexual networks, and outbreaks associated with proctitis/proctocolitis among women and men who have sex with men. ImportanceChlamydia trachomatis is an obligate intracellular bacterium that is not easily cultured, and there is limited information on rectal C. trachomatis transmission and its impact on morbidity. To improve efficiency of previous studies involving whole genome target enrichment and sequencing of C. trachomatis directly from clinical urine, vaginal, conjunctival, and rectal specimens, we expanded the RNA bait library to augment enrichment of the organism from clinical samples. We demonstrate an increased efficiency in the percentage of reads mapping to C. trachomatis. We show the new system is sensitive for near identical genomes of C. trachomatis from two body sites in four women. Further, we provide a robust genomic epidemiologic approach to advance our understanding of C. trachomatis strains causing ocular, urogenital and rectal infections, and to explore geo-sexual networks, outbreaks of colorectal infections among women and men who have sex with men, and the role of these strains in morbidity.

genomics↗

bioRxiv2020

Multi-locus genotyping reveals established endemicity of a geographically distinct Plasmodium vivax population in Mauritania, West Africa

BackgroundPlasmodium vivax has been recently discovered as a significant cause of malaria in Mauritania, although very rare elsewhere in West Africa. It has not been known if this is a recently introduced or locally remnant parasite population, nor whether the genetic structure reflects epidemic or endemic transmission. Methodology / Principal FindingsTo investigate the P. vivax population genetic structure in Mauritania and compare with populations previously analysed elsewhere, multi-locus genotyping was undertaken on 100 clinical isolates, using a genome-wide panel of 38 single nucleotide polymorphisms (SNPs), plus seven SNPs in drug resistance genes. The Mauritanian P. vivax population is shown to be genetically diverse and divergent from populations elsewhere, indicated consistently by genetic distance matrix analysis, principal components analyses, and fixation indices. Only one isolate had a genotype clearly indicating recent importation, from a southeast Asian source. There was no linkage disequilibrium in the local parasite population, and only a small number of infections appeared to be closely genetically related, indicating that there is ongoing genetic recombination consistent with endemic transmission. The P. vivax diversity in a remote mining town was similar to that in the capital Nouakchott, with no indication of local substructure or of epidemic population structure. Drug resistance alleles were virtually absent in Mauritania, in contrast with P. vivax in other areas of the world. Conclusions / SignificanceThe molecular epidemiology indicates that there is long-standing endemic transmission that will be very challenging to eliminate. The virtual absence of drug resistance alleles suggests that most infections have been untreated, and that this endemic infection has been more neglected in comparison to P. falciparum locally or to P. vivax elsewhere. Author SummaryPlasmodium vivax is a widespread cause of malaria in Mauritania, in contrast to its rarity elsewhere throughout West Africa. To investigate whether the parasite may be recently introduced or epidemic, multi-locus genotyping was performed on 100 Mauritanian P. vivax malaria cases. Analysis of a genome-wide panel of single nucleotide polymorphisms showed the P. vivax population to be genetically diverse and divergent from populations elsewhere, indicating that there has been long-standing endemic transmission. Almost all infections appear to be locally acquired, with the exception of one that was presumably imported with a genotype similar to infections seen in Southeast Asia. The Mauritanian P. vivax population shows no linkage disequilibrium, and very few infections have closely related genotypes, indicating ongoing recombination. The parasite showed no indication of local substructure or epidemic population structure. Drug resistance alleles were virtually absent, suggesting that most infections have been untreated historically. The molecular epidemiology indicates that there has been long-standing endemic transmission of this neglected parasite that requires special attention for control.

microbiology↗

bioRxiv2020

Staphylococcus sciuri C2865 from a distinct subspecies cluster as reservoir of the novel transferable trimethoprim resistance gene, dfrE, and adaptation driving mobile elements

Four methicillin-resistant Staphylococcus sciuri (MRSS) strains isolated from stranded dogs showed trimethoprim (TMP) resistance, while all staphylococcal TMP resistant dihydrofolate reductase genes (dfr) were negative. An in-depth whole-genome-sequencing approach on strain C2865 was followed for resistome and mobilome profiling, and for comparative genomics with S. sciuri group available genomes. Lack of species host tropism was observed, with MRSS C2865 placed at a separate sub-branch within S. sciuri species, close to the average nucleotide identity to be considered a different species (95-96%). S. sciuri proved a pronounced accessory genome (73% of genes), while MRSS C2865 distinctively harboured the highest total gene number and highest number of unique genes, with 75% associated to the recognised mobilome. A novel multidrug resistance mosaic plasmid (pUR2865-34) with several adaptive, mobilization (oriT mimic) and segregational stability (Type Ib par system) traits and two small single resistance plasmids were identified. Plasmid pUR2865-34 enclosed a novel staphylococcal TMP resistance gene, named dfrE, which shared highest identity with dfr of soil-related Paenibacillus anaericanus (68%). DfrE conferred high-level TMP resistance in S. aureus and Escherichia coli. Database searches revealed that dfrE was formerly denoted (dfr_like) in an Exiguobacterium spp. from a fish-farm sediment and that was present but unnoticed in several staphylococcal and onemacrococcal genomes with different epidemiological backgrounds. Novel chromosomal site-specific mobile islands with resourceful traits were identified, including a multidrug-resistant SCCmec cassette lacking cassette chromosome recombinase (Ccr) genes, a staphylococcal pathogenicity island of the SaPI4 family, and three unrelated siphoviridae prophages, two of which enclosed recombinases with the conserved Ccr-motif. We reveal a novel staphylococcal TMP resistance dfrE gene already present in diverse bacterial backgrounds. We confirm the ubiquity, high genome plasticity and low host tropism of S. sciuri highlighting its role as a resourceful reservoir for evolutionary novel features contributing to its extraordinary versatility and adaptability. Author summaryStaphylococcus spp. are ubiquitous bacteria present in diverse ecological niches, including humans, animals and the environment. They are clinically relevant opportunistic pathogens and are notorious for their ability to acquire antimicrobial resistance (AMR) and virulence properties, resulting in a significant impact for Public Health. Mobile genetic elements (MGEs) play a central role in this adaptation process and are a means to transfer genetic information across bacterial species. Staphylococcus sciuri represents one of the most ancestral species in the genus and has been suggested a reservoir for AMR genes. Here, following a refined whole genome sequencing approach we determined the entire genome of an animal and environment-associated multidrug resistant (MDR) S. sciuri strain uncovering a novel acquired staphylococcal TMP resistance gene already spread among different bacterial species from different epidemiological backgrounds. We also reveal several additional MGEs, including a novel MDR mobilizable plasmid that encloses several adaptive and stabilization features, and novel mobilizable chromosomal islands with resourceful traits, including three unrelated prophages. Together with comparative genomics, we confirm the ubiquity, high intraspecies heterogenicity, genome plasticity and low host tropism of this species, highlighting its role as resourceful reservoir for evolutionary novel features contributing to its extraordinary versatility and adaptability.

microbiology↗

bioRxiv2020

ProkEvo: an automated, reproducible, and scalable framework for high-throughput bacterial population genomics analyses

Whole Genome Sequence (WGS) data from bacterial species is used for a variety of applications ranging from basic microbiological research, diagnostics, and epidemiological surveillance. The availability of WGS data from hundreds of thousands of individual isolates of individual microbial species poses a tremendous opportunity for discovery and hypothesis-generating research into ecology and evolution of these microorganisms. Scalability and user-friendliness of existing pipelines for population-scale inquiry, however, limit applications of systematic, population-scale approaches. Here, we present ProkEvo, an automated, scalable, and open-source framework for bacterial population genomics analyses using WGS data. ProkEvo was specifically developed to achieve the following goals: 1) Automation and scaling of complex combinations of computational analyses for many thousands of bacterial genomes from inputs of raw Illumina paired-end sequence reads; 2) Use of workflow management systems (WMS) such as Pegasus WMS to ensure reproducibility, scalability, modularity, fault-tolerance, and robust file management throughout the process; 3) Use of high-performance and high-throughput computational platforms; 4) Generation of hierarchical population-based genotypes at different scales of resolution based on combinations of multi-locus and Bayesian statistical approaches for classification; 5) Detection of antimicrobial resistance (AMR) genes, putative virulence factors, and plasmids from curated databases and association with genotypic classifications; and 6) Production of pan-genome annotations and data compilation that can be utilized for downstream analysis. The scalability of ProkEvo was measured with two datasets comprising significantly different numbers of input genomes (one with ~2,400 genomes, and the second with ~23,000 genomes). Depending on the dataset and the computational platform used, the running time of ProkEvo varied from ~3-26 days. ProkEvo can be used with virtually any bacterial species and the Pegasus WMS facilitates addition or removal of programs from the workflow or modification of options within them. All the dependencies of ProkEvo can be distributed via conda environment or Docker image. To demonstrate versatility of the ProkEvo platform, we performed population-based analyses from available genomes of three distinct pathogenic bacterial species as individual case studies (three serovars of Salmonella enterica, as well as Campylobacter jejuni and Staphylococcus aureus). The specific case studies used reproducible Python and R scripts documented in Jupyter Notebooks and collectively illustrate how hierarchical analyses of population structures, genotype frequencies, and distribution of specific gene functions can be used to generate novel hypotheses about the evolutionary history and ecological characteristics of specific populations of each pathogen. Collectively, our study shows that ProkEvo presents a viable option for scalable, automated analyses of bacterial populations with powerful applications for basic microbiology research, clinical microbiological diagnostics, and epidemiological surveillance.

bioinformatics↗

bioRxiv2020

Sero-prevalence of anti-SARS-CoV-2 Antibodies in Addis Ababa, Ethiopia

BackgroundAnti-SARS-CoV-2 antibody tests are being increasingly used for sero-epidemiological purposes to provide better understanding of the extent of the infection in the community, and monitoring the progression of the COVID-19 epidemic. We conducted sero-prevalence study to estimate prior infection with with SARS-CoV-2 in Addis Ababa. MethodsA cross-sectional study was done from April 23 to 28, 2020 among 301 randomly selected residents of Addis Ababa; with no known history of contact with confirmed COVID-19 person. Interviews on socio demographic and behavioural risk factor followed by serological tests were performed for SARS-CoV-2 IgM, and IgG antibodies, using COVID-19 IgG/IgM Rapid Test Cassette. The test has sensitivity of 87{middle dot}9% and specificity of 100% for lgM; and a sensitivity of 97{middle dot}2% and specificity of 100% for IgG. RT-PCR test was also done on combined nasopharyngeal and oropharengeal swabs as an important public health consideration. FindingsThe unadjusted antibody-based crude SARS-CoV-2 prevalence was 7{middle dot}6% and the adjusted true SARS-CoV-2 prevalence was estimated at 8{middle dot}8% (95% CI 5{middle dot}5%-11{middle dot}6%) for the study population. Higher sero-prevalence were observed for males (9.0%), age below 50 years (8.2%), students and unemployed (15.6%), those with primary education (12.1%), smokers (7.8%), alcohol consumers (8.6%), chatt-chewers (13.6%) and shish smokers (18.8%). Seroprevalence was not significantly associated neither with socio-demographic not behavioral characteristics. According to the findings, possibly more individuals had been infected in Addis Ababa than what was being detected and reported by RT-PCR test suggestive of community transmission. The use of serological test for epidemiological estimation of the extent of SARS-CoV-2 epidemic gives a more precise estimate of magnitude which would be used for further monitoring and surveillance of the magnitude of the SARS CoV-2 infection.

microbiology↗

bioRxiv2020

FastMLST: A multi-core tool for multilocus sequence typing of draft genome assemblies

Multilocus Sequence Typing (MLST) is a precise microbial typing approach at the intra-species level for epidemiological and evolutionary purposes. It operates by assigning a sequence type (ST) identifier to each specimen, based on a combination of allelic sequences obtained for multiple housekeeping genes included in a defined scheme. The use of MLST has multiplied due to the availability of large numbers of genomic sequences and epidemiological data in public repositories. However, data processing speed has become problematic due to datasets massive size. Here, we present FastMLST, a tool that is designed to perform PubMLST searches using BLASTn and a divide-and-conquer approach. Compared to mlst, CGE/MLST, MLSTar, and PubMLST, FastMLST takes advantage of current multi-core computers to simultaneously type thousands of genome assemblies in minutes, reducing processing times by at least 16-fold and with more than 99.95% consistency. Availability and ImplementationThe source code, installation instructions and documentation are available at https://github.com/EnzoAndree/FastMLST

bioinformatics↗

bioRxiv2020

Live poultry feeding and trading network and the transmission of avian influenza A(H5N6) virus in a large city in China, 2014-2015

To understand clearly the mechanism of H5N6 transmission, the role of a live poultry feeding and trading network should be explored deeply. However, there is little data to show the network in an area. In this study, we performed a field epidemiological investigation to collect the numbers of farms, wholesale markets, and live poultry retail markets, and the numbers of purchased (from where) and sold (to where) live birds in Changsha City, China in 2014. We also collected samples from the network in the city from January 2014 to March 2015, including the LPMs visited by the patient known to be infected with A(H5N6) virus, and sequenced the genomes of 10 A(H5N6) viral strains isolated from these environmental samples, to determine the source of virus that infected the patient reported in Changsha. Additionally, we collected and analyzed A(H5N6) virus genome sequence isolated from humans, poultry, and LPMs registered in National Center for Biotechnology Information (NCBI; NIH, Bethesda, MD, USA) 14, to determine the source of other human infections with A(H5N6) virus reported in China. Changsha City in China has a large live poultry feeding and trading network (LPFTN) which had 665 farms, 5 wholesale markets, and 223 live poultry retail markets in 2014. The network covered nine provinces and purchased and sold more than 150000 live birds every day. About 840 environmental samples collected from the LPFTN network from January 2014 to March 2015. About 8.45% (71/840) environmental samples were shown to be positive for N6 and 10 full genome sequences of H5N6 virus were analyzed. We performed phylogenetic analyses and virus characterization, which demonstrated that the H5N6 viral strains isolated from Chinese patients were closely related to those isolated from the poultry and environmental samples obtained from the LPFTN network. This indicates that the network with a large volume of live poultry provides a platform for the transmission of H5N6, and provides an infectious pool which makes the people in high risk. ImportanceAvian influenza A(H5N6) virus is an emerging threat to public health. With several human cases reported in recent years, it has become a dominant avian influenza virus (AIV) subtype in China. Live poultry feeding and trading network (LPFTN) contributes to the presence of novel AIV. By a field epidemiological investigation in the complex LPFTN in Changsha, we demonstrated that the H5N6 viral strains isolated from Chinese patients were closely related to those isolated from the poultry and environmental samples obtained from the network, suggesting the LPFTN with a large volume of live poultry provides a platform for the transmission of H5N6 and creates an infectious pool which makes people in high risk. Considering the wide circulation and dynamic reassortment of this highly pathogenic avian influenza H5N6 virus, it should be carefully monitored in poultry and humans due to the pandemic potential.

molecular biology↗

bioRxiv2020

The spatial-temporal dynamics of respiratory syncytial virus infections across the east-west coasts of Australia during 2016-17

Respiratory syncytial virus (RSV) is an important human respiratory pathogen. In temperate regions a distinct seasonality is observed, where peaks of infections typically occur in early winter, often preceding the annual influenza season. Infections are associated with high rates of morbidity and mortality, and in some populations exceeds that of influenza. Two subtypes, RSV-A and RSV-B, have been described, and molecular epidemiological studies have shown that both viruses mostly co-circulate. This trend also appears to be the case for Australia, however previous genomic studies have been limited to cases from one Eastern state - New South Wales. As such, the broader spatial patterns and viral traffic networks across the continent are not known. Here, we conducted a whole genome study of RSV comparing strains across eastern and western Australia during the period January 2016 to June 2017. In total, 96 new RSV genomes were sequenced, compiled with previously generated data, and examined using a phylodynamic approach. This analysis revealed that both RSV-A and RSV-B strains were circulating, and each subtype was dominated by a single genotype, RSV-A/ON1-like and RSV-B/BA10-like viruses. Some geographical clustering was evident in strains from both states with multiple distinct sub-lineages observed and relatively low mixing across jurisdictions suggesting that endemic transmission was likely seeded from imported, unsampled locations. Overall, the RSV phylogenies reflected a complex pattern of interactions across multiple epidemiological scales from fluid virus traffic across global and regional networks to fine-scale local transmission events.

microbiology↗

bioRxiv2020

Antibiotic resistance profiles and population structure of disease-associated Staphylococcus aureus infecting patients in Fort Portal Regional Referral Hospital, Western Uganda

Tackling antimicrobial resistance (AMR) is particularly challenging in low-resource settings such as Fort Portal Regional Referral Hospital (FPRRH) in Western Uganda. Specific knowledge of local AMR epidemiology is required to inform evidence-based improvement of antibiotic stewardship measures in the hospital. To address this, we combined existing antimicrobial susceptibility testing (AST) from FPRRH, with whole genome sequencing (WGS) of 41 Staphylococcus aureus isolates (2017-2019). AST revealed 73% (30/41) of isolates were resistant to one or more antibiotics and 29% (12/41) were multi-drug resistant (MDR). Resistance phenotypes were largely explained by the presence of antibiotic resistance genes in WGS data. Five isolates were methicillin-resistant S. aureus (MRSA) and MDR. Although all isolates were susceptible to clindamycin, a 24% carriage of erm genes suggests potential for rapid development of resistance. We inferred a population structure for the S. aureus isolates by comparing their core genomes. Twenty isolates formed a tight cluster corresponding to multilocus sequence typing clonal complex (CC) 152, a CC found to be particularly prevalent in northern Africa. The frequency of genes associated with methicillin, chloramphenicol and ciprofloxacin resistance were significantly lower among CC152 strains than non-CC152 strains; thus, in keeping with previous work, we find that CC152 is almost exclusively methicillin-sensitive S. aureus (MSSA). Also, in agreement with other studies, we observed that the occurrence of Panton-Valentine leukocidin toxin-encoding genes was significantly higher among CC152 strains than non-CC152 strains. However, we also observed that the coagulase gene was over-represented in this CC, further defining the virulence strategy of this important pathogen. By generating detailed information about the epidemiology of circulating S. aureus and their antibiotic susceptibility, our study has provided, for the first time, data on which evidence-based infection and AMR interventions at FPRRH can be based.

microbiology↗

bioRxiv2020

Using a non-destructive sugar-feeding assay for sporozoite detection and estimating the extrinsic incubation period of Plasmodium falciparum in mosquito vectors

Despite its epidemiological importance, the time Plasmodium parasites take to achieve development in the vector mosquito (the extrinsic incubation period, EIP) remains poorly characterized. A novel non-destructive assay designed to estimate EIP in single mosquitoes, and more broadly to study Plasmodium - Anopheles vectors interactions, is presented. The assay uses small pieces of cotton wool soaked in sugar solution to collect malaria sporozoites from individual mosquitoes during sugar feeding to monitor infection status over time. This technique has been tested across four natural malaria mosquito species of Africa and Asia, six parasite isolates of Plasmodium falciparum, and across a range of temperatures relevant to malaria transmission in field conditions. We find that monitoring individual infectious mosquitoes is feasible, although due to the frequency of mosquito sugar feeding and inter-individual variation in infection intensity, there is inherent risk that this technique will result in some false negatives. The sensitivity rate ranged from 0.27 to 0.81 depending on mosquito species and on infection intensity in mosquitoes used to collect saliva. Using this non-destructive technique, the estimated median extrinsic incubation period of P. falciparum at 27{degrees}C was 11 to 14 days depending on mosquito species and parasite isolate. Long-term individual tracking also revealed that sporozoite transfer onto cotton wool can occur at least until day 40 post-infection. In addition to contributing to a better understanding of EIP and mosquito to human transmission with implications for improving epidemiological models, this technique also allows to link different transmission traits at the mosquito individual level. As one example, we found a significant relationship between EIP and mosquito lifespan, with short individual EIP associated with short mosquito lifespan. Correlations between mosquito/parasite traits often reveal trade-offs and constraints and have important implications for understanding the evolution of parasite transmission strategies.

molecular biology↗

bioRxiv2020

Microbial Species Abundance Distributions Guide Human Population Size Estimation from Sewage Metagenomes

The metagenome embedded in urban sewage is an attractive new data source to understand urban ecology and assess human health status at scales beyond a single host. Analyzing the viral fraction of wastewater in the ongoing COVID-19 pandemic has shown the potential of wastewater as aggregated samples for early detection, prevalence monitoring, and variant identification of human diseases in large populations. However, using census-based population size instead of real-time population estimates can mislead the interpretation of data acquired from sewage, hindering assessment of representativeness, inference of prevalence, or comparisons of taxa across sites. Here, we show that taxon abundance and sub-species diversisty in gut-associated microbiomes are new feature space to utilize for human population estimation. Using a population-scale human gut microbiome sample of over 1,100 people, we found that taxon-abundance distributions of gut-associated multi-person microbiomes exhibited generalizable relationships with respect to human population size. Here and throughout this paper, the human population size is essentially the sample size from the wastewater sample. We present a new algorithm, MicrobiomeCensus, for estimating human population size from sewage samples. MicrobiomeCensus harnesses the inter-individual variability in human gut microbiomes and performs maximum likelihood estimation based on simultaneous deviation of multiple taxas relative abundances from their population means. MicrobiomeCensus outperformed generic algorithms in data-driven simulation benchmarks and detected population size differences in field data. New theorems are provided to justify our approach. This research provides a mathematical framework for inferring population sizes in real time from sewage samples, paving the way for more accurate ecological and public health studies utilizing the sewage metagenome. Author summaryWastewater-based epidemiology (WBE) is an emerging field that employs sewage as aggregated samples of human populations. This approach is particularly promising for tracking diseases that can spread asymptomatically in large populations, such as the COVID-19. As a new type of biological data, sewage has its own unique challenges to utilize. While wastewater samples are usually assumed to represent large populations, it is not guaranteed, because of stochasticity in toilet flushes; unlike epidemiological experiments collecting data from individuals, sample size, i.e., the human population size represented by a wastewater sample, is a fundamental yet difficult-to-characterize parameter for sewage samples. Researchers would need to aggregate data from large areas and week-long collection to stabilize data, during which, important spikes in small areas or short time scales may be lost. It also remains challenging to turn viral titers into case prevalences, evaluating representativeness, or comparing measurements across sites/studies. This study provides a framework to estimate human population size from sewage utilizing human gut-associated microorganisms. Through analysis, we demonstrate that variance of taxon abundances and single-nucleotide polymorphism as two variables that change with population size. We provide a new tool MicrobiomeCensus that performs population size estimation from microbial taxon abundances. MicrobiomeCensus outperforms generic algorithms in terms of computational efficiency while at comparable or better accuracy. Using MicrobiomeCensus, we detected population size differences in sewage samples taken in Cambridge, MA, under two sampling approaches, i.e., "grab" or "composite" sampling. This study provides a framework to utilize individual-level microbiomes to learn from sewage, paving the way to prevalence estimation and improved spatio-temporal resolutions in WBE..

bioinformatics↗

bioRxiv2020

VirStrain: a strain identification tool for RNA viruses

1Genome epidemiology, which uses genomic data to analyze the source and spread of infectious diseases, provides important information beyond interview-based methods. Given fast accumulation of sequenced viral genomes, a basic need in genome epidemiology is to identify which reference genomes are identical or closest to the ones in a sequenced sample. Then the associated metadata such as the geographical locations can be utilized to infer the transmission network. In this work, we deliver VirStrain, a fast and accurate tool for conducting strain-level analysis from short reads. By using a greedy covering algorithm, we are able to derive unique k-mer combinations for highly similar reference genomes. VirStrain is able to detect the most possible strain and also multiple strains that may simultaneously infect the same host. We tested VirStrain on three types of RNA viruses whose reference genomes have different similarity distri-butions. For each types of virus, we assessed VirStrain across multiple bench-mark datasets of different properties and complexity. The experimental results on both simulated and real sequencing data show that VirStrain outperforms other strain identification tools.

bioinformatics↗

bioRxiv2021

Sequencing of Sars-CoV-2 genome using different Nanopore chemistries

Nanopore sequencing has emerged as a rapid and cost-efficient tool for diagnostic and epidemiological surveillance of SARS-CoV-2 during the COVID-19 pandemic. This study compared results from sequencing the SARS-CoV-2 genome using R9 vs R10 flow cells and Rapid Barcoding Kit (RBK) vs Ligation Sequencing Kit (LSK). The R9 chemistry provided a lower error rate (3.5%) than R10 chemistry (7%). The SARS-CoV-2 genome includes few homopolymeric regions. Longest homopolymers were composed of 7 (TTTTTTT) and 6 (AAAAAA) nucleotides. The R10 chemistry resulted in a lower rate of deletions in timine and adenine homopolymeric regions than R9, at expenses of a larger rate (~10%) of mismatches in these regions. The LSK had a larger yield than RBK, and provided longer reads than RBK. It also resulted in a larger percentage of aligned reads (99% vs 93%) and also in a complete consensus genome. The results from this study suggest that the LSK used on a R9 flow cell could maximize the yield and accuracy of the consensus sequence when used in epidemiological surveillance of SARS-CoV-2. KeypointsO_LISequencing SARS-CoV-2 genome is of great importance for the pandemic surveillance C_LIO_LINanopore offers a low cost and accurate method to sequence SARS-CoV-2 genome C_LIO_LILigation sequencing is preferred rather than the rapid kit using transposases C_LI

microbiology↗

bioRxiv2021

Sequencing of SARS CoV2 in local transmission cases through oxford nanopore MinION platform from Karachi Pakistan

The first case of severe acute respiratory syndrome 2 (SARS CoV2) was imported to Pakistan in February 2020 since then 10,258 deaths have been witnessed. The virus has been mutating and local transmission cases from different countries vary due to host dependent viral adaptation. Many distinct clusters of variant SARS CoV2 have been defined globally. In this study, the epidemiology of SARS CoV2 was studied and locally transmitted SARS CoV2 isolates from Karachi were sequenced to compared and identify any possible variants.The real time PCR was performed on nasopharyngeal specimen to confirm SARSCoV2 with Orf 1ab and E gene as targets. The viral sequencing was performed through oxford nanopore technology MinION platform. Isolates from first and second wave of COVID-19 outbreak in Karachi were compared. The overall positivity rate for PCR was 26.24% with highest number of positive cases in June. Approximately, 37.45% PCR positive subjects aged between 19-40 years. All the isolates belonged to GH clade and shared missense mutation D614G in spike protein linked to increased transmission rate worldwide. Another spike protein mutation A222V coexisted with D614G in the virus from second wave of COVID-19. Based on the present findings it is suggested that the locally transmitted virus from Karachi vary from those reported from other parts of Pakistan. Slight variability was also observed between viruses from first and second wave. Variability in any potential vaccine target may result in failed trials therefore information on any local viral variants is always useful for effective vaccine design and/or selection. Authors summaryDespite precautionary measures the COVID-19 pandemic is causing deaths all over the world. The continuous mutations in viral genome is making it difficult to design vaccines. Variability in genome is host dependent and data sharing has revealed that variant for different geographical locations may harbor different mutations. Keeping this in mind the current study was focused on the epidemiology of SARS CoV2 in symptomatic and asymptomatic COVID -19 suspected cases with impact of age and gender. The locally transmitted SARS CoV2 isolates from Karachi were sequenced to compared and identify any possible variants. The sequenced viral genome varied from the already submitted sequences from Pakistan thereby confirming that slightly different viruses were causing infections during different time periods in Karachi. All belonged to GH clade with D614G, P323L and Q57H mutations. The virus from second wave had A222V mutation making it more different. This information can be useful in selecting or designing a vaccine.

genomics↗

bioRxiv2021

Modelling tuberculosis drug resistance amplification rates in high-burden settings

BackgroundAntimicrobial resistance develops following the accrual of mutations in the bacterial genome, and may variably impact organism fitness and hence, transmission risk. Classical representation of tuberculosis (TB) dynamics using a single or two strain (DS/MDR-TB) model typically does not capture elements of this important aspect of TB epidemiology. To understand and estimate the likelihood of resistance spreading in high drug-resistant TB incidence settings, we used molecular understanding to develop a compartmental epidemiological model of Mycobacterium tuberculosis (Mtb) transmission. MethodsA four-strain (drug-susceptible (DS), isoniazid mono-resistant (INH-R), rifampicin mono-resistant (RIF-R) and multidrug-resistant (MDR)) compartmental deterministic Mtb transmission model was developed to explore the progression from DS-to MDR-TB. The model incorporated strain-specific fitness costs and was calibrated using data from national tuberculosis prevalence surveys and drug resistance surveys from Philippines and Viet Nam. Using an adaptive Metropolis algorithm, we estimated drug resistance amplification and transmission rates. ResultsThe posterior estimates for the proportion of isoniazid mono-resistant amplification among treatment failure was 0.75 (0.64 - 0.85) for Philippines and 0.55 (0.39 - 0.63) for Viet Nam. The proportion of rifampicin mono-resistant amplification among treatment failure was 0.05 (0.04 - 0.06) for Philippines and 0.011 (0.010 - 0.012) for Viet Nam. In Philippines, the estimated proportion of primary resistance resulting from transmission was 56% (42 - 68) for INH-R, 48% (34 - 62) for RIF-R and 42% (34 - 50) for MDR-TB. For Viet Nam, the estimated proportion of drug resistance due to transmission was 79% (70 - 86) for INH-R, 68% (58 - 75) for RIF-R and 50% (45 - 53) for MDR-TB. DiscussionRIF-R strains were more likely to be transmitted than acquired through amplification, while both mechanisms of acquisition were important contributors in the case of INH-R. These findings highlight the complexity of drug resistance dynamics in high-incidence settings, and emphasize the importance of prioritizing testing algorithms which also allow for early detection of INH-R.

microbiology↗

bioRxiv2021

Molecular dynamics simulation study of effects of key mutations in SARS-CoV-2 on protein structures

SARS-CoV-2 has been spreading rapidly since 2019 and has produced large-scale mutations in the genomes. The mutation in genes may lead to changes in protein structure, which would have a great impact on the epidemiological characteristics. In this study, we selected the key mutations of SARS-CoV-2 from a real-time monitoring tool, including D614G, A222V, N501Y, T716I, S982A, D1118H of spike (S) protein, and performed molecular dynamics (MD) simulations on single-site mutant D614G, double-site mutant D614G&A222V and penta-site mutant N501Y&D614G&T716I&S982A&D1118H to investigate their effects on protein structure and stability using molecular dynamics (MD) simulations. The results suggested that D614G improved the stability of S protein, while D614G&A222V and N501Y&D614G&T716I&S982A&D1118H showed an increased solvent accessible surface area and they might enhance the ability of protein to react with the outside environment. Our findings could complement the mechanistic link between genotype--phenotype--epidemiological characteristics in the study of SARS-CoV-2. We also found no significant difference between the antigenicity of S protein and the mutants through Ellipro, which may reference for vaccine development and application.

bioinformatics↗

bioRxiv2021

How public reaction to disease information across scales and the impacts of vector control methods influence disease prevalence and control efficacy

With the development of social media, the information about vector-borne disease incidence over broad spatial scales can cause demand for local vector control before local risk exists. Anticipatory intervention may still benefit local disease control efforts; however, infection risks are not the only focal concerns governing public demand for vector control. Concern for environmental contamination from pesticides and economic limitations on the frequency and magnitude of control measures also play key roles. Further, public concern may be focused more on ecological factors (i.e., controlling mosquito populations) or on epidemiological factors (i.e., controlling infection-carrying mosquitoes), which may lead to very different control outcomes. Here we introduced a generic Ross-MacDonald model, incorporating these factors under three spatial scales of disease information: local, regional, and global. We tailored and parameterized the model for Zika virus transmitted by Aedes aegypti mosquito. We found that overreaction caused by larger-scale incidence information could decrease average human infections per patch breeding capacity, however, the associated increase in total control effort plays a larger role, which leads to an overall decrease in control efficacy. The shift of focal concerns from epidemiological to ecological risk could relax the negative effect of overreaction on control efficacy when mosquito breeding capacity populations are expected to be large. This work demonstrates that, depending on expected total mosquito breeding capacity population size, and weights of different focal concerns, large-scale disease information can reduce disease infections without lowering control efficacy. Our findings provide guidance for vector-control strategies by considering public reaction through social media.

ecology↗

bioRxiv2021

Early low-level developmental arsenic exposure impacts mouse hippocampal synapticfunction

BackgroundArsenic is a well-established carcinogen known to increase all-cause mortality, but its effects on the central nervous system are less well understood. Recent epidemiological studies suggest that early life exposure to arsenic is associated with learning deficits and behavioral changes, and increased arsenic exposure continues to affect an estimated 200 million individuals worldwide. Previous studies on arsenic exposure and synaptic function have demonstrated a decrease in synaptic transmission and long-term potentiation in adult rodents, but have relied on in vitro or extended exposure in adulthood. Therefore, little is known about the effect of arsenic exposure in development. ObjectiveHere, we studied the effects of gestational and early developmental arsenic exposure in juvenile mice. Specifically, our objective was to investigate the impact of arsenic exposure on synaptic transmission and plasticity in the hippocampus. MethodsC57BL/6 females were exposed to arsenic (0, 50ppb, 36ppm) in their drinking water two weeks prior to mating and continued to be exposed to arsenic throughout gestation and after parturition. We then performed field recordings in acute hippocampal slices from the juvenile offspring prior to weaning (P17-P23). In this paradigm, the juvenile mice are only exposed to arsenic in utero and via the mothers milk. ResultsHigh (36ppm) and relatively low (50ppb) arsenic exposure both lead to decreased basal synaptic transmission in the hippocampus of juvenile mice. There was a mild decrease in paired-pulse facilitation in juvenile mice exposed to high, but not low, arsenic, suggesting the alterations in synaptic transmission are primarily post-synaptic. Finally, high developmental arsenic exposure led to a significant increase in long-term potentiation. DiscussionThese results suggest that indirect, ecologically-relevant arsenic exposure in early development impacts hippocampal synaptic transmission and plasticity that could underlie learning deficits reported in epidemiological studies.

neuroscience↗