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bioRxiv2021

The Orsay Virus as a model for population-wide viral infection dynamics

To this day, epidemics pose a considerable threat to mankind. Experimental models that simulate the spread of infectious diseases are thus crucial to the inception of effective control policies. Current models have had great success incorporating virulence and host immune response but do rarely take host genetics, behavior and host environment into account. Here, we present a full-scale imaging setup that utilizes the infection of the nematode C. elegans with a positive-stranded RNA virus (Orsay Virus) to probe key epidemiological parameters and simulate the spread of infection in a whole population. We demonstrate that our system is able to quantify infection levels and host behavior at a high sampling rate and show that different host genetic backgrounds can influence viral spread, while also highlighting the influence of infection on various host behaviors. Future work will allow the isolation of key behavioral and environmental factors that affect viral spread, potentially enabling novel policies to combat the spread of viral infections. Significance StatementIn the ongoing COVID-19 pandemic, we struggle to find effective control policies that "stop the spread". While current animal models of virus spread in populations are highly sophisticated, they rarely explore effects of host behavior and its environment. We developed an experimental animal model system that allows us to visualize virus transmission in whole populations of C. elegans while also measuring behaviors. We were able to demonstrate how C. elegans genetics influences the progression of viral infection in a population and how animals adjust their behavior when infected. In the future, we envision that animal model systems like ours are used to test the effects of viral control policies on viral spread before they are applied in real world scenarios.

immunology↗

bioRxiv2021

Novel Paju Apodemus Paramyxovirus 1 and 2, Harbored by Apodemus agrarius in The Republic of Korea

Paramyxoviruses, negative-sense single-stranded RNA viruses, pose a potential threat to public health. Currently, 78 species and 17 genera of paramyxoviruses are classified and harbored by multiple natural reservoirs, including rodents, bats, birds, reptiles, and fish. Jeilongvirus has been proposed as a novel paramyxovirus genus containing J-, Beilong, and Tailam viruses, found in wild rodents. Using RT-PCR, 824 Apodemus agrarius individuals were examined for the prevalence of paramyxovirus infections. Paramyxovirus RNA was detected in 108 (13.1%) rodents captured at 14 trapping sites in Korea. We first present two genetically distinct novel paramyxoviruses (genus Jeilongvirus), Paju Apodemus paramyxoviruses 1 (PAPV-1) and 2 (PAPV-2), from A. agrarius. Six PAPV strains were completely sequenced using next-generation and Sanger sequencing. PAPV-1 genome comprised 19,716 nucleotides, with eight genes (3'-N-P/V/C-M-F-SH-TM-G-L-5'), whereas PAPV-2 genome contained 17,475 nucleotides, with seven genes (3'-N-P/V/C-M-F-TM-G-L-5'). The disparity between PAPV-1 and -2 revealed the presence of the SH gene and length of the G gene in the genome organization. The phylogenies of PAPV-1 and -2 belong to distinct genetic lineages of Jeilongvirus despite being from the same natural host. PAPV-1 clustered with Beilong and Tailam viruses, while PAPV-2 formed a genetic lineage with Mount Mabu Lophuromys virus-1. PAPV-1 infected human epithelial and endothelial cells, facilitating the induction of type I/III interferons, interferon-stimulated genes, and proinflammatory cytokines. Therefore, this study provides profound insights into the molecular epidemiology, virus-host interactions, and zoonotic potential of novel rodent-borne paramyxoviruses. ImportanceParamyxoviruses are a critical public health and socio-economic burden to humans. Rodents play a crucial role in transmitting pathogens to humans. In the last decade, novel paramyxoviruses have been discovered in different rodents. Here, we found that Apodemus agrarius harbored two distinct genotypes of the novel paramyxoviruses, Paju Apodemus paramyxovirues 1 (PAPV-1) and 2 (PAPV-2), possessing unique genome structures that are responsible for encoding TM and G proteins of different sizes. In addition, PAPV-1 infected human epithelial and endothelial cells, facilitating the induction of type I/III IFNs, ISGs, and proinflammatory cytokines. Thus, this study provides significant insights into molecular prevalence, virus-host interactions of paramyxoviruses. These observations raise the awareness of physicians and scientists about the emergence of new rodent-borne paramyxoviruses.

microbiology↗

bioRxiv2021

Detection of ESKAPE pathogens and Clostridioides difficile in Simulated Skin Transmission Events with Metagenomic and Metatranscriptomic Sequencing

1BackgroundAntimicrobial resistance is a significant global threat, posing major public health risks and economic costs to healthcare systems. Bacterial cultures are typically used to diagnose healthcare-acquired infections (HAI); however, culture-dependent methods provide limited presence/absence information and are not applicable to all pathogens. Next generation sequencing (NGS) has the capacity to detect a wide variety of pathogens, virulence elements, and antimicrobial resistance (AMR) signatures in healthcare settings without the need for culturing, but few research studies have explored how NGS could be used to detect viable human pathogen transmission events under different HAI-relevant scenarios. MethodsThe objective of this project was to assess the capability of NGS-based methods to detect the direct and indirect transmission of high priority healthcare-related pathogens. DNA was extracted and sequenced from a previously published study exploring pathogen transfer with simulated skin containing background microorganisms, which allowed for complementary culture and metagenomic analysis comparisons. RNA was also isolated from an additional set of samples to evaluate metatranscriptomic analysis methods at different concentrations. ResultsUsing various analysis methods and custom reference databases, both pathogenic and non-pathogenic members of the microbial community were taxonomically identified. Virulence and AMR genes known to reside within the community were also routinely detected. Ultimately, pathogen abundance within the overall microbial community played the largest role in successful taxonomic classification and gene identification. ConclusionsThese results illustrate the utility of metagenomic analysis in clinical settings or for epidemiological studies, but also highlight the limits associated with the detection and characterization of pathogens at low abundance in a microbial community.

genomics↗

bioRxiv2021

Defining the scope of the European Antimicrobial Resistance Surveillance network in Veterinary medicine (EARS-Vet): a bottom-up and One Health approach

BackgroundBuilding the European Antimicrobial Resistance Surveillance network in Veterinary medicine (EARS-Vet) was proposed to strengthen the European One Health antimicrobial resistance (AMR) surveillance approach. ObjectivesThe objectives were to (i) define the combinations of animal species, production types, age categories, bacterial species, specimens and antimicrobials to be monitored in EARS-Vet and to (ii) determine antimicrobial test panels able to cover most combinations. MethodsThe EARS-Vet scope was defined by consensus between 26 European experts. Decisions were guided by a survey of the combinations that are relevant and feasible to monitor in diseased animals in 13 European countries (bottom-up approach). Experts also considered the One Health approach and the need for EARS-Vet to complement existing European AMR monitoring systems coordinated by the European Centre for Disease Prevention and Control (ECDC) and the European Food Safety Authority (EFSA). ResultsEARS-Vet would monitor AMR in six animal species (cattle, swine, chicken (broiler and laying hen), turkey, cat and dog), for 11 bacterial species (Escherichia coli, Klebsiella pneumoniae, Mannheimia haemolytica, Pasteurella multocida, Actinobacillus pleuropneumoniae, Staphylococcus aureus, Staphylococcus pseudintermedius, Staphylococcus hyicus, Streptococcus uberis, Streptococcus dysgalactiae and Streptococcus suis). Relevant antimicrobials for their treatment were selected (e.g. tetracyclines) and complemented with antimicrobials of more specific public health interest (e.g. carbapenems). Three test panels of antimicrobials were proposed covering most EARS-Vet combinations of relevance for veterinary antimicrobial stewardship. ConclusionsWith this scope, EARS-Vet would enable to better address animal health in the strategy to mitigate AMR and better understand the multi-sectoral AMR epidemiology in Europe.

microbiology↗

bioRxiv2021

A smoothed version of the Lassosum penalty for fitting integrated risk models

Polygenic risk scores are a popular means to predict the disease risk or disease susceptibility of an individual based on its genotype information. When adding other important epidemiological covariates such as age or sex, we speak of an integrated risk model. Methodological advances for fitting more accurate integrated risk models are of immediate importance to improve the precision of risk prediction, thereby potentially identifying patients at high risk early on when they are still able to benefit from preventive steps/interventions targeted at increasing their odds of survival, or at reducing their chance of getting a disease in the first place. This article proposes a smoothed version of the "Lassosum" penalty used to fit polygenic risk scores and integrated risk models. The smoothing allows one to obtain explicit gradients everywhere for efficient minimization of the Lassosum objective function while guaranteeing bounds on the accuracy of the fit. An experimental section on both Alzheimers disease and COPD (chronic obstructive pulmonary disease) demonstrates the increased accuracy of the proposed smoothed Lassosum penalty compared to the original Lassosum algorithm, allowing it to draw equal with state-of-the-art methodology such as LDpred2 when evaluated via the AUC (area under the ROC curve) metric.

bioinformatics↗

bioRxiv2021

Seasonal dynamics and repeatability of gastrointestinal parasite burdens in wild Soay sheep

Seasonality is a ubiquitous feature of wildlife disease ecology, but is determined by a complex interplay of environmental, parasitological and host factors. Gastrointestinal parasites often exhibit strong seasonal dynamics in wild vertebrate populations due to, for example, environmental influences on free-living or vectored life stages, and variation in the physiological and immune status of hosts across their annual cycle. At the same time, wild populations are typically infected with multiple parasites. The seasonal dynamics of co-infecting parasites may differ depending on age and reproductive status, and associations among parasites may be driven by short-term within-individual changes or longer-term interactions that are consistent among hosts. Here, we used faecal samples and egg counts collected repeatedly from individually marked and monitored wild Soay sheep that were part of a long-term study to investigate seasonal dynamics of six gastrointestinal parasite groups (strongyle nematodes, coccidian protozoa, Capillaria, Strongyloides, Nematodirus, and Moniezia). Prevalence and abundance generally tended to be higher spring and summer, and burdens were higher in lambs than adults. Within the highly prevalent strongyle nematode group, we found differences in seasonality of egg counts depending on adult reproductive status. Reproductive ewes had increased counts in spring around the time of birth followed by a drop in abundance in summer, while barren ewes showed little evidence of seasonality. Males showed a sustained rise in egg counts through spring and summer, and sex differences were only strongly apparent in summer. In contrast, in similarly prevalent coccidia we found a peak in faecal oocyst counts in spring but no differences in seasonality among males, barren and pregnant ewes. Using multivariate mixed-effects models, we went on to show that both strongyle and coccidia counts are moderately repeatable across seasons among individuals. We further show that apparent positive correlation between strongyle and coccidia counts was driven by short-term within-individual changes in both parasite burdens rather than long-term among-individual covariation. Overall, our results demonstrate that seasonality varies across demographic and parasite groups and highlight the value of investigating fluctuating susceptibility and exposure over time for understanding epidemiology of a population.

ecology↗

bioRxiv2021

Deep learning from phylogenies to uncover the transmission dynamics of epidemics

Widely applicable, accurate and fast inference methods in phylodynamics are needed to fully profit from the richness of genetic data in uncovering the dynamics of epidemics. Standard methods, including maximum-likelihood and Bayesian approaches, generally rely on complex mathematical formulae and approximations, and do not scale with dataset size. We develop a likelihood-free, simulation-based approach, which combines deep learning with (1) a large set of summary statistics measured on phylogenies or (2) a complete and compact representation of trees, which avoids potential limitations of summary statistics and applies to any phylodynamics model. Our method enables both model selection and estimation of epidemiological parameters from very large phylogenies. We demonstrate its speed and accuracy on simulated data, where it performs better than the state-of-the-art methods. To illustrate its applicability, we assess the dynamics induced by superspreading individuals in an HIV dataset of men-having-sex-with-men in Zurich. Our tool PhyloDeep is available on github.com/evolbioinfo/phylodeep.

bioinformatics↗

bioRxiv2021

Life-history evolution of class-structured populations in fluctuating environments

What is the influence of periodic environmental fluctuations on life-history evolution? We present a general theoretical framework to understand and predict the long-term evolution of lifehistory traits under a broad range of ecological scenarios. Specifically, we investigate how periodic fluctuations affect selection when the population is also structured in distinct classes. This analysis yields time-varying selection gradients that clarify the influence of the fluctuations of the environment on the competitive ability of a specific life-history mutation. We use this framework to analyse the evolution of key life-history traits of pathogens. We examine three different epidemiological scenarios and we show how periodic fluctuations of the environment can affect the evolution of virulence and transmission as well as the preference for different hosts. These examples yield new and testable predictions on pathogen evolution, and illustrate how our approach can provide a better understanding of the evolutionary consequences of time-varying environmental fluctuations in a broad range of scenarios.

evolutionary biology↗

bioRxiv2021

Time dependent proinflammatory responses shape virus interference during coinfections of influenza A virus and influenza D virus

Both influenza A virus (IAV) and influenza D virus (IDV) are enzootic in pigs. IAV causes approximately 100% morbidity with low mortality, whereas IDV leads to only mild respiratory diseases in pigs. In this study, we performed a series of coinfection experiments in vitro and in vivo to understand how IAV and IDV interact and cause pathogenesis during coinfection. Results showed that IAV inhibited IDV replication when infecting swine tracheal epithelial cells (STEC) with IAV 24- or 48-hours prior to IDV inoculation, and that IDV suppressed IAV replication when IDV preceded IAV inoculation by 48 hours. Virus interference was not identified during simultaneous IAV/IDV infections or with 6 hours between the two viral infections, regardless of their order. The interference pattern at 24- and 48-hours correlated with proinflammatory responses induced by the first infection, which was about 24-hours slower for IDV than IAV. The viruses did not interfere with each other if both infected the cells before proinflammatory responses were induced. Coinfection in pigs further demonstrated that IAV interfered both viral shedding and virus replication of IDV, especially in the upper respiratory tract. Clinically, coinfection of IDV and IAV did not show significant enhancement of disease pathogenesis, compared with the pigs infected with IAV alone. In summary, this study suggests that interference during coinfection of IAV and IDV is primarily due to the proinflammatory response and is therefore dependent on the time between infection, and the order of infection. ImportanceBoth IAV and IDV are enzootic in pigs, and feral pigs have a higher risk for both IAV and IDV exposures than IDV exposure alone. This study suggests that in coinfection with IAV and IDV either virus can interfere with the replication of the other virus by stimulating proinflammatory responses; however, the proinflammatory response was 24 hours slower for IDV than IAV. In vitro there was no interference during simultaneous coinfection, regardless of infection order. Coinfection of IDV and IAV in pigs did not show enhanced pathogenesis, compared with those infected only with IAV. This study can facilitate our understanding of virus epidemiology and pathogenesis associated with IAV and IDV coinfection.

microbiology↗

bioRxiv2021

First isolation of virulent Tenacibaculum maritimum strains from diseased orbicular batfish (Platax orbicularis) farmed in Tahiti Island

The orbicular batfish (Platax orbicularis), also called Paraha peue in Tahitian, is the most important marine fish species reared in French Polynesia. Sudden and widespread outbreaks of severe white-patch disease have occurred since 2011 in batfish farms one to three weeks after the transfer of juveniles from bio-secured hatcheries to lagoon cages. With cumulative mortality ranging from 20 to 90%, the sustainability of aquaculture of this species is severely threatened. In this study, we describe for the first time the isolation from diseased batfish of several strains belonging to the species Tenacibaculum maritimum, a major pathogen of many marine fish species. Histopathological analysis, an experimental bath challenge and a field monitoring study showed that T. maritimum is associated with white-patch disease. Moreover, molecular and serological analyses performed on representative strains revealed some degree of genetic diversity among the isolates, a finding of primary importance for epidemiological studies and for the development of management and control strategies such as vaccination.

pathology↗

bioRxiv2021

Functionally distinct T-helper cell phenotypes predict resistance to different types of parasites in a wild mammal

O_LIThe adaptive immune system is critical to an effective, long-lasting ability to respond to infection in vertebrates and T-helper (Th) cells play a key role in orchestrating the adaptive immune response. Laboratory studies show that functionally distinct Th responses provide protection against different kinds of parasites (i.e., Th1 responses against microparasites and Th2 against macroparasites). C_LIO_LINatural populations must deal with challenges from a wide range of infectious agents and co-infection with different types of parasite is the norm, so different Th responses are likely to play an important and dynamic role in maintaining host health and fitness. However, the relationship between T helper immune phenotypes and infection with different types of parasites remains poorly understood in wild animals. C_LIO_LIIn this study, we characterised variation in functionally distinct Th responses (Th1, Th2, Th17 and regulatory responses) in a wild population of Soay sheep using flow cytometry to detect Th-subset specific transcription factors, and ex vivo lymphocyte stimulation to quantify release of Th-associated cytokines. We specifically tested the prediction that raised Th1 and Th2 responses should predict reduced apicomplexan (coccidian) and helminth (nematode) parasite burdens, respectively. C_LIO_LICell counts of different Th subsets measured by flow cytometry did not vary with age or sex. However, all measures of Th-associated ex vivo cytokine production increased with age, and Th17- and regulatory Th-associated cytokine production increased more rapidly with age in males than females. C_LIO_LIIndependent of age and sex, Th2-associated immune measures negatively predicted gastro-intestinal strongyle nematode faecal egg count, while production of the Th1-associated cytokine IFN-{gamma} negatively predicted coccidian faecal oocyst count. C_LIO_LIOur results provide important support from outside the laboratory that Th1 and Th2 responses confer resistance to different kinds of parasites (micro- and macro-parasites, respectively). They also add to mounting evidence from wild populations that Th1/Th2 trade-offs often observed in controlled laboratory experiments may not readily translate to more complex natural systems. C_LIO_LIOur study illustrates that harnessing more specific reagents and tools from laboratory immunology has the potential to illuminate our understanding of epidemiology and host-parasite co-evolution in the wild. C_LI

ecology↗

bioRxiv2021

DNA spike-ins enable confident interpretation of SARS-CoV-2 genomic data from amplicon-based sequencing

The rapid global spread and continued evolution of SARS-CoV-2 has highlighted an unprecedented need for viral genomic surveillance and clinical viral sequencing. Amplicon-based sequencing methods provide a sensitive, low-cost and rapid approach but suffer a high potential for contamination, which can undermine lab processes and results. This challenge will only increase with expanding global production of sequences by diverse research groups for epidemiological and clinical interpretation. We present an approach which uses synthetic DNA spike-ins (SDSIs) to track samples and detect inter-sample contamination through a sequencing workflow. Applying this approach to the ARTIC Consortiums amplicon design, we define a series of best practices for Illumina-based sequencing and provide a detailed characterization of approaches to increase sensitivity for low-viral load samples incorporating the SDSIs. We demonstrate the utility and efficiency of the SDSI method amidst a real-time investigation of a suspected hospital cluster of SARS-CoV-2 cases.

molecular biology↗

bioRxiv2021

Post-transcriptional regulation of Leishmania fitness gain

The protozoan parasite Leishmania donovani causes fatal human visceral leishmaniasis in absence of treatment. Genome instability has been recognized as a driver in Leishmania fitness gain in response to environmental change or chemotherapy. How genome instability generates beneficial phenotypes despite potential deleterious gene dosage effects is unknown. Here we address this important open question applying experimental evolution and integrative systems approaches on parasites adapting to in vitro culture. Phenotypic analyses of parasites from early and late stages of culture adaptation revealed an important fitness tradeoff, with selection for accelerated growth in promastigote culture (fitness gain) impairing infectivity (fitness costs). Comparative genomics, transcriptomics and proteomics analyses revealed a complex regulatory network driving parasite fitness, with genome instability causing highly reproducible, gene dosage-dependent changes in protein abundance linked to post-transcriptional regulation. These in turn were associated with a gene dosage-independent reduction in abundance of flagellar transcripts and a coordinated increase in abundance of coding and non-coding RNAs implicated in ribosomal biogenesis and protein translation. We correlated differential expression of small nucleolar RNAs (snoRNAs) with changes in rRNA modification, providing first evidence that Leishmania fitness gain in culture may be controlled by post-transcriptional and epitranscriptomic regulation. Our findings propose a novel model for Leishmania fitness gain in culture, where differential regulation of mRNA stability and the generation of fitness-adapted ribosomes may potentially filter deleterious from beneficial gene dosage effects and provide proteomic robustness to genetically heterogenous, adapting parasite populations. This model challenges the current, genome-centric approach to Leishmania epidemiology and identifies the Leishmania transcriptome and non-coding small RNome as potential novel sources for the discovery of biomarkers that may be associated with parasite phenotypic adaptation in clinical settings.

microbiology↗

bioRxiv2021

Measuring splash-dispersal of a major wheat pathogen in the field

Capacity for dispersal is a fundamental fitness component of plant pathogens. Empirical characterization of plant pathogen dispersal is of prime importance for understanding how plant pathogen populations change in time and space. We measured dispersal of Zymoseptoria tritici in natural environment. Primary disease gradients were produced by rain-splash driven dispersal and subsequent transmission via asexual pycnidiospores from infected source. To achieve this, we inoculated field plots of wheat (Triticum aestivum) with two distinct Z. tritici strains and a 50/50 mixture of the two strains. We measured effective dispersal of the Z. tritici population based on pycnidia counts using automated image analysis. The data were analyzed using a spatially-explicit mathematical model that takes into account the spatial extent of the source. We employed robust bootstrapping methods for statistical testing and adopted a two-dimensional hypotheses test based on the kernel density estimation of the bootstrap distribution of parameter values. Genotyping of re-isolated pathogen strains with strain-specific PCR-reaction further confirmed the conclusions drawn from the phenotypic data. The methodology presented here can be applied to other plant pathosystems. We achieved the first estimates of the dispersal kernel of the pathogen in field conditions. The characteristic spatial scale of dispersal is tens of centimeters - consistent with previous studies in controlled conditions. Our estimation of the dispersal kernel can be used to parameterize epidemiological models that describe spatial-temporal disease dynamics within individual wheat fields. The results have the potential to inform spatially targeted control of crop diseases in the context of precision agriculture.

plant biology↗

bioRxiv2021

Genome-wide Association Study of Pancreatic Fat: The Multiethnic Cohort Adiposity Phenotype Study

Several studies have found associations between higher pancreatic fat content and adverse health outcomes, such as diabetes and the metabolic syndrome, but investigations into the genetic contributions to pancreatic fat are limited. This genome-wide association study, comprised of 804 participants with MRI-assessed pancreatic fat measurements, was conducted in the ethnically diverse Multiethnic Cohort-Adiposity Phenotype Study (MEC-APS). Two genetic variants reaching genome-wide significance, rs73449607 on chromosome 13q21.2 (Beta = -0.67, P = 4.50x10-8) and rs7996760 on chromosome 6q14 (Beta = -0.90, P = 4.91x10-8) were associated with percent pancreatic fat on the log scale. Rs73449607 was most common in the African American population (13%) and rs79967607 was most common in the European American population (6%). Rs73449607 was also suggestively associated with lower risk of type 2 diabetes (OR = 0.95, 95% CI = 0.89-1.00, P = 0.047) in the Population Architecture Genomics and Epidemiology (PAGE) Study and the DIAbetes Genetics Replication and Meta-analysis (DIAGRAM), which included substantial numbers of non-European ancestry participants (53,102 cases and 193,679 controls). Rs73449607 is located in an intergenic region between GSX1 and PLUT, and rs79967607 is in intron 1 of EPM2A. PLUT, a linkRNA, regulates transcription of an adjacent gene, PDX1, that controls beta-cell function in the mature pancreas, and EPM2A encodes the protein laforin, which plays a critical role in regulating glycogen production. If validated, these variants may suggest a genetic component for pancreatic fat and a common etiologic link between pancreatic fat and type 2 diabetes.

cell biology↗

bioRxiv2021

Should deep-sequenced amplicons become the new gold-standard for analysing malaria drug clinical trials?

BackgroundRegulatory clinical trials are required to ensure the continued supply and deployment of effective antimalarial drugs. Patient follow-up in such trials typically lasts several weeks as the drugs have long half-lives and new infections often occur during this period. "Molecular correction" is therefore used to distinguish drug failures from new infections. The current WHO-recommend method for molecular correction uses length-polymorphic alleles at highly diverse loci but is inherently poor at detecting low density clones in polyclonal infections. This likely leads to substantial underestimates of failure rates, delaying the replacement of failing drugs with potentially lethal consequences. Deep sequenced amplicons (AmpSeq) substantially increase the detectability of low-density clones and may offer a new "gold standard" for molecular correction. MethodsPharmacological simulation of clinical trials was used to evaluate the suitability of AmpSeq for molecular correction. We investigated the impact of factors such as the number of amplicon loci analysed, the informatics criteria used to distinguish genotyping noise from real low density signals, the local epidemiology of malaria transmission, and the potential impact of genetic signals from gametocytes. ResultsAmpSeq greatly improved molecular correction and provided accurate drug failure rate estimates. The use of 3 to 5 amplicons was sufficient, and simple, non-statistical, criteria could be used to classify recurrent infections as drug failures or new infections. ConclusionsThese results strongly endorse the deployment of AmpSeq as the standard for molecular correction in regulatory trials, with its potential extension into routine surveillance once the requisite technical support becomes established.

microbiology↗

bioRxiv2021

Target Capture Sequencing of SARS-CoV-2 Genomes Using the ONETest Coronaviruses Plus

BackgroundGenomic sequencing is important to track and monitor genetic changes in SARS-CoV-2. We introduce a target capture next-generation sequencing methodology, the ONETest Coronaviruses Plus, to sequence SARS-CoV-2 genomes and select genes of other respiratory viruses simultaneously. MethodsWe applied the ONETest on 70 respiratory samples (collected in Florida, USA between May and July, 2020), in which SARS-CoV-2 had been detected by a qualitative PCR assay. For 48 (69%) of the samples, we also applied the ARTIC protocol for Illumina sequencing. All the libraries were sequenced as 2x150 nucleotide reads on an Illumina instrument. The ONETest data were analyzed using an in-house pipeline and the ARTIC data using a published pipeline to produce consensus SARS-CoV-2 genome sequences, to which lineages were assigned using pangolin. ResultsOf the 70 ONETest libraries, 45 (64%) had a complete or near-complete SARS-CoV-2 genome sequence (> 29,000 bases and with > 90% of its bases covered by at least 10 reads). Of the 48 ARTIC libraries, 25 (52%) had a complete or near-complete SARS-CoV-2 genome sequence. In 24 out of 34 (71%) samples in which both the ONETest and ARTIC sequences were complete or near-complete and in which lineage could be assigned to both the ONETest and ARTIC sequences, the SARS-CoV-2 lineage identified was the same. ConclusionsThe ONETest can be used to sequence the SARS-CoV-2 genomes in archived samples and thereby enable detection of circulating and emerging SARS-CoV-2 variants. Target capture approaches, such as the ONETest, are less prone to loss of sequence coverage probably due to amplicon dropouts encountered in amplicon approaches, such as ARTIC. With its added value of characterizing other major respiratory pathogens, although not assessed in this study, the ONETest can help to better understand the epidemiology of infectious respiratory disease in the post COVID-19 era.

genomics↗

bioRxiv2021

A Statistical Model for Describing and Simulating Microbial Community Profiles

Many methods have been developed for statistical analysis of microbial community profiles, but due to the complex nature of typical microbiome measurements (e.g. sparsity, zero-inflation, nonindependence, and compositionality) and of the associated underlying biology, it is difficult to compare or evaluate such methods within a single systematic framework. To address this challenge, we developed SparseDOSSA (Sparse Data Observations for the Simulation of Synthetic Abundances): a statistical model of microbial ecological population structure, which can be used to parameterize real-world microbial community profiles and to simulate new, realistic profiles of known structure for methods evaluation. Specifically, SparseDOSSAs model captures marginal microbial feature abundances as a zero-inflated log-normal distribution, with additional model components for absolute cell counts and the sequence read generation process, microbemicrobe, and microbe-environment interactions. Together, these allow fully known covariance structure between synthetic features (i.e. "taxa") or between features and "phenotypes" to be simulated for method benchmarking. Here, we demonstrate SparseDOSSAs performance for 1) accurately modeling human-associated microbial population profiles; 2) generating synthetic communities with controlled population and ecological structures; 3) spiking-in true positive synthetic associations to benchmark analysis methods; and 4) recapitulating an end-to-end mouse microbiome feeding experiment. Together, these represent the most common analysis types in assessment of real microbial community environmental and epidemiological statistics, thus demonstrating SparseDOSSAs utility as a general-purpose aid for modeling communities and evaluating quantitative methods. An open-source implementation is available at http://huttenhower.sph.harvard.edu/sparsedossa2.

bioinformatics↗