Motivation Tracking SARS-CoV-2 variants through genomic sequencing has been an important part of the global response to the pandemic. As well as whole-genome sequencing of clinical samples, this surveillance effort has been aided by amplicon sequencing of wastewater samples, which proved effective in real case studies. Because of its relevance to public healthcare decisions, testing and benchmarking wastewater sequencing analysis methods is also crucial, which necessitates a simulator. Although metagenomic simulators exist, none are fit for the purpose of simulating the metagenomes produced through amplicon sequencing of wastewater. Results Our new simulation tool, SWAMPy ( S imulating SARS-CoV-2 W astewater A mplicon M etagenomes with Py thon), is intended to provide realistic simulated SARS-CoV-2 wastewater sequencing datasets with which other programs that rely on this type of data can be evaluated and improved. Availability The code for this project is available at https://github.com/goldman-gp-ebi/SWAMPy It can be installed on any Unix-based operating system and is available under the GPL-v3 license.

Wastewater-based epidemiology has been used extensively throughout the COVID-19 (coronavirus disease 19) pandemic to detect and monitor the spread and prevalence of SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) and its variants. It has proven an excellent, complementary tool to clinical sequencing, supporting the insights gained and helping to make informed public-health decisions. Consequently, many groups globally have developed bioinformatics pipelines to analyse sequencing data from wastewater. Accurate calling of mutations is critical in this process and in the assignment of circulating variants; yet, to date, the performance of variant-calling algorithms in wastewater samples has not been investigated. To address this, we compared the performance of six variant callers (VarScan, iVar, GATK, FreeBayes, LoFreq and BCFtools), used widely in bioinformatics pipelines, on 19 synthetic samples with known ratios of three different SARS-CoV-2 variants of concern (VOCs) (Alpha, Beta and Delta), as well as 13 wastewater samples collected in London between the 15th and 18th December 2021. We used the fundamental parameters of recall (sensitivity) and precision (specificity) to confirm the presence of mutational profiles defining specific variants across the six variant callers. Our results show that BCFtools, FreeBayes and VarScan found the expected variants with higher precision and recall than GATK or iVar, although the latter identified more expected defining mutations than other callers. LoFreq gave the least reliable results due to the high number of false-positive mutations detected, resulting in lower precision. Similar results were obtained for both the synthetic and wastewater samples.

Within months of the COVID-19 pandemic being declared on March 20, 2020, novel, more infectious variants of SARS-CoV-2 began to be detected in geospatially distinct regions of the world. With international travel being a lead cause of spread of the disease, the importance of rapidly identifying variants entering a country is critical. In this study, we utilized wastewater-based epidemiology (WBE) to monitor the presence of variants in wastewater generated in managed COVID-19 quarantine facilities for international air passengers entering the United Kingdom. Specifically, we developed multiplex reverse transcription quantitative PCR (RT-qPCR) assays for the identification of defining mutations associated with Beta (K417N), Gamma (K417T), Delta (156/157DEL), and Kappa (E154K) variants which were globally prevalent at the time of sampling (April to July 2021). The assays sporadically detected mutations associated with the Beta, Gamma, and Kappa variants in 0.7%, 2.3%, and 0.4% of all samples, respectively. The Delta variant was identified in 13.3% of samples, with peak detection rates and concentrations observed in May 2021 (24%), concurrent with its emergence in the United Kingdom. The RT-qPCR results correlated well with those from sequencing, suggesting that PCR-based detection is a good predictor for variant presence; although, inadequate probe binding may lead to false positive or negative results. Our findings suggest that WBE coupled with RT-qPCR may be used as a rapid, initial assessment to identify emerging variants at international borders and mass quarantining facilities. IMPORTANCE With the global spread of COVID-19, it is essential to identify emerging variants which may be more harmful or able to escape vaccines rapidly. To date, the gold standard to assess variants circulating in communities has been the sequencing of the S gene or the whole genome of SARS-CoV-2; however, that approach is time-consuming and expensive. In this study, we developed two duplex RT-qPCR assays to detect and quantify defining mutations associated with the Beta, Gamma, Delta, and Kappa variants. The assays were validated using RNA extracts derived from wastewater samples taken at quarantine facilities. The results showed good correlation with the results of sequencing and demonstrated the emergence of the Delta variant in the United Kingdom in May 2021. The assays developed here enable the assessment of variant-specific mutations within 2 h after the RNA extract was generated which is essential for outbreak rapid response.

The world has moved into a new stage of managing the SARS-CoV-2 pandemic with minimal restrictions and reduced testing in the population, leading to reduced genomic surveillance of virus variants in individuals. Wastewater-based epidemiology (WBE) can provide an alternative means of tracking virus variants in the population but decision-makers require confidence that it can be applied to a national scale and is comparable to individual testing data. We analysed 19,911 samples from 524 wastewater sites across England at least twice a week between November 2021 and February 2022, capturing sewage from >70% of the English population. We used amplicon-based sequencing and the phylogeny based de-mixing tool Freyja to estimate SARS-CoV-2 variant frequencies and compared these to the variant dynamics observed in individual testing data from clinical and community settings. We show that wastewater data can reconstruct the spread of the Omicron variant across England since November 2021 in close detail and aligns closely with epidemiological estimates from individual testing data. We also show the temporal and spatial spread of Omicron within London. Our wastewater data further reliably track the transition between Omicron subvariants BA1 and BA2 in February 2022 at regional and national levels. Our demonstration that WBE can track the fast-paced dynamics of SARS-CoV-2 variant frequencies at a national scale and closely match individual testing data in time shows that WBE can reliably fill the monitoring gap left by reduced individual testing in a more affordable way.

BackgroundSchools are high-risk settings for infectious disease transmission. Wastewater monitoring for infectious diseases has been used to identify and mitigate outbreaks in many near-source settings during the COVID-19 pandemic, including universities and hospitals but less is known about the technology when applied for school health protection. This study aimed to implement a wastewater surveillance system to detect SARS-CoV-2 and other public health markers from wastewater in schools in England. MethodsA total of 855 wastewater samples were collected from 16 schools (10 primary, 5 secondary and 1 post-16 and further education) over 10 months of school term time. Wastewater was analysed for SARS-CoV-2 genomic copies of N1 and E genes by RT-qPCR. A subset of wastewater samples was sent for genomic sequencing, enabling determination of the presence of SARS-CoV-2 and emergence of variant(s) contributing to COVID-19 infections within schools. In total, >280 microbial pathogens and >1200 AMR genes were screened using RT-qPCR and metagenomics to consider the utility of these additional targets to further inform on health threats within the schools. ResultsWe report on wastewater-based surveillance for COVID-19 within English primary, secondary and further education schools over a full academic year (October 2020 to July 2021). The highest positivity rate (80.4%) was observed in the week commencing 30(th) November 2020 during the emergence of the Alpha variant, indicating most schools contained people who were shedding the virus. There was high SARS-CoV-2 amplicon concentration (up to 9.2x10(6) GC/L) detected over the summer term (8th June - 6th July 2021) during Delta variant prevalence. The summer increase of SARS-CoV-2 in school wastewater was reflected in age-specific clinical COVID-19 cases. Alpha variant and Delta variant were identified in the wastewater by sequencing of samples collected from December to March and June to July, respectively. Lead/lag analysis between SARS-CoV-2 concentrations in school and WWTP data sets show a maximum correlation between the two-time series when school data are lagged by two weeks. Furthermore, wastewater sample enrichment coupled with metagenomic sequencing and rapid informatics enabled the detection of other clinically relevant viral and bacterial pathogens and AMR. ConclusionsPassive wastewater monitoring surveillance in schools can identify cases of COVID-19. Samples can be sequenced to monitor for emerging and current variants of concern at the resolution of school catchments. Wastewater based monitoring for SARS-CoV-2 is a useful tool for SARS-CoV-2 passive surveillance and could be applied for case identification and containment, and mitigation in schools and other congregate settings with high risks of transmission. Wastewater monitoring enables public health authorities to develop targeted prevention and education programmes for hygiene measures within undertested communities across a broad range of use cases.

Monitoring the spread of viral pathogens in the population during epidemics is crucial for mounting an effective public health response. Understanding the viral lineages that constitute the infections in a population can uncover the origins and transmission patterns of outbreaks and detect the emergence of novel variants that may impact the course of an epidemic. Population-level surveillance of viruses through genomic sequencing of wastewater captures unbiased lineage data, including cryptic asymptomatic and undiagnosed infections, and has been shown to detect infection outbreaks and novel variant emergence before detection in clinical samples. Here, we present an optimised protocol for quantification and sequencing of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in influent wastewater, used for high-throughput genomic surveillance in England during the COVID-19 pandemic. This protocol utilises reverse compliment PCR for library preparation, enabling tiled amplification across the whole viral genome and sequencing adapter addition in a single step to enhance efficiency. Sequencing of synthetic SARS-CoV-2 RNA provided evidence validating the efficacy of this protocol, while data from high-throughput sequencing of wastewater samples demonstrated the sensitivity of this method. We also provided guidance on the quality control steps required during library preparation and data analysis. Overall, this represents an effective method for high-throughput sequencing of SARS-CoV-2 in wastewater which can be applied to other viruses and pathogens of humans and animals.

Background Many countries have moved into a new stage of managing the SARS-CoV-2 pandemic with minimal restrictions and reduced testing in the population, leading to reduced genomic surveillance of virus variants in individuals. Wastewater-based epidemiology (WBE) can provide an alternative means of tracking virus variants in the population but is lacking verifications of its comparability to individual testing data. Methods We analysed more than 19,000 samples from 524 wastewater sites across England at least twice a week between November 2021 and February 2022, capturing sewage from >70% of the English population. We used amplicon-based sequencing and the phylogeny based de-mixing tool Freyja to estimate SARS-CoV-2 variant frequencies and compared these to the variant dynamics observed in individual testing data from clinical and community settings. Findings We show that wastewater data can reconstruct the spread of the Omicron variant across England since November 2021 in close detail and aligns closely with epidemiological estimates from individual testing data. We also show the temporal and spatial spread of Omicron within London. Our wastewater data further reliably track the transition between Omicron subvariants BA1 and BA2 in February 2022 at regional and national levels. Interpretation Our demonstration that WBE can track the fast-paced dynamics of SARS-CoV-2 variant frequencies at a national scale and closely match individual testing data in time shows that WBE can reliably fill the monitoring gap left by reduced individual testing in a more affordable way. Funding Department of Health and Social Care, UK, Natural Environmental Research Council, UK, COG-UK Evidence before this study Genomic monitoring of wastewater for SARS-CoV-2 variants has been introduced in several countries and shown to effectively detect the spread of known variants in multiple studies. However, verification of its alignment with individual testing data at a national scale has so far been reported only for Austria, where sampling covered around 5.4million people. Further and larger scale verifications of the reliability of wastewater-based epidemiology (WBE) are needed to increase confidence in its use for public health monitoring. Added value of this study We provide evidence that WBE was able to closely track the spread of the emerging SARS-CoV-2 variant Omicron, as well as its sub lineage dynamics, at a regional and national scale across England. Our sampling covered >70% of the English population, equivalent to 39.4 million people. We thereby demonstrate the scalability of our approach to national levels. We also show how WBE is able to track dynamics in different regions of the UK and at a finer scale within London. Its close alignment, in estimated epidemiological timings, with results from intensive individual testing in the same timeframe provides evidence that wastewater-based monitoring can be a reliable alternative when large scale data from individual testing is not available. Implications of all the available evidence Altogether, evidence is accumulating that WBE is a reliable approach for monitoring SARS-CoV-2 variant dynamics and informing public health measures across spatial scales. ### Competing Interest Statement The authors have declared no competing interest. ### Clinical Protocols ### Funding Statement Funding was provided by DHSC UK (2020\_097) and NERC (NE/V003860/1). This report is independent research funded by the Department of Health and Social Care. COG-UK is supported by funding from the Medical Research Council (MRC) part of UK Research & Innovation (UKRI), the National Institute of Health Research (NIHR) [grant code: MC\_PC_19027], and Genome Research Limited, operating as the Wellcome Sanger Institute. The authors acknowledge use of data generated through the COVID-19 Genomics Programme funded by the Department of Health and Social Care. The views expressed are those of the authors and not necessarily those of the Department of Health and Social Care or UKHSA. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Use of surplus nucleic acid derived from routine diagnostics and associated patient data was approved through the COG-UK consortium by the Public Health England Research Ethics and Governance Group (R&D NR0195). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes Wastewater sequencing data are publicly available on the European Nucleotide Archive under Study ID PRJEB55313. The clinical case data used in this study are visualised at . A filtered, privacy conserving version of the lineage-LTLA-week dataset is publicly available online () and gives access to almost all used data, despite a small number of cells having been suppressed to conserve patient privacy.

The potential utility of wastewater-based epidemiology as an early warning tool has been explored widely across the globe during the current COVID-19 pandemic. Methods to detect the presence of SARS-CoV-2 RNA in wastewater were developed early in the pandemic, and extensive work has been conducted to evaluate the relationship between viral concentration and COVID-19 case numbers at the catchment areas of sewage treatment works (STWs) over time. However, no attempt has been made to develop a model that predicts wastewater concentration at fine spatio-temporal resolutions covering an entire country, a necessary step towards using wastewater monitoring for the early detection of local outbreaks.We consider weekly averages of flow-normalised viral concentration, reported as the number of SARS-CoV-2N1 gene copies per litre (gc/L) of wastewater available at 303 STWs over the period between 1 June 2021 and 30 March 2022. We specify a spatially continuous statistical model that quantifies the relationship between weekly viral concentration and a collection of covariates covering socio-demographics, land cover and virus associated genomic characteristics at STW catchment areas while accounting for spatial and temporal correlation.We evaluate the model’s predictive performance at the catchment level through 10-fold cross-validation. We predict the weekly viral concentration at the population-weighted centroid of the 32,844 lower super output areas (LSOAs) in England, then aggregate these LSOA predictions to the Lower Tier Local Authority level (LTLA), a geography that is more relevant to public health policy-making. We also use the model outputs to quantify the probability of local changes of direction (increases or decreases) in viral concentration over short periods (e.g. two consecutive weeks).The proposed statistical framework can predict SARS-CoV-2 viral concentration in wastewater at high spatio-temporal resolution across England. Additionally, the probabilistic quantification of local changes can be used as an early warning tool for public health surveillance.

Sequencing of SARS-CoV-2 in wastewater provides a key opportunity to monitor the prevalence of variants spatiotemporally, potentially facilitating their detection simultaneously with, or even prior to, observation through clinical testing. However, there are multiple sequencing methodologies available. This study aimed to evaluate the performance of alternative protocols for detecting SARS-CoV-2 variants. We tested the detection of two synthetic RNA SARS-CoV-2 genomes in a wide range of ratios and at two concentrations representative of those found in wastewater using whole-genome and Spike -gene-only protocols utilising Illumina and Oxford Nanopore platforms. We developed a Bayesian hierarchical model to determine the predicted frequencies of variants and the error surrounding our predictions. We found that most of the sequencing protocols detected polymorphic nucleotide frequencies at a level that would allow accurate determination of the variants present at higher concentrations. Most methodologies, including the Spike -only approach, could also predict variant frequencies with a degree of accuracy in low-concentration samples but, as expected, with higher error around the estimates. All methods were additionally confirmed to detect the same prevalent variants in a set of wastewater samples. Our results provide the first quantitative statistical comparison of a range of alternative methods that can be used successfully in the surveillance of SARS-CoV-2 variant frequencies from wastewater.Impact Genetic sequencing of SARS-CoV-2 in wastewater provides an ideal system for monitoring variant frequencies in the general population. The advantages over clinical data are that it is more cost efficient and has the potential to identify new variants before clinical testing. However, to date, there has been no direct comparison to determine which sequencing methodologies perform best at identifying the presence and prevalence of variants. Our study compares seven sequencing methods to determine which performs best. We also develop a Bayesian statistical methodology to estimate the confidence around variant frequency estimates. Our results will help monitor SARS-CoV-2 variants in wastewater, and the methodology could be adapted for other disease monitoring, including future pandemics.### Competing Interest StatementThe authors have declared no competing interest.### Funding StatementNatural Environment Research Council (NERC) (N-WESP, NE/V010441/1 grant to TB) ### Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesI confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesAll data produced in the present study are available upon reasonable request to the authors

Animal venoms are considered sterile sources of antimicrobial compounds with strong membrane-disrupting activity against multidrug-resistant bacteria. However, venomous bite wound infections are common in developing nations. Investigating the envenomation organ and venom microbiota of five snake and two spider species, we observed venom community structures that depend on the host venomous animal species and evidenced recovery of viable microorganisms from black-necked spitting cobra (Naja nigricollis) and Indian ornamental tarantula (Poecilotheria regalis) venoms. Among the bacterial isolates recovered from N. nigricollis, we identified two venom-resistant, novel sequence types of Enterococcus faecalis whose genomes feature 16 virulence genes, indicating infectious potential, and 45 additional genes, nearly half of which improve bacterial membrane integrity. Our findings challenge the dogma of venom sterility and indicate an increased primary infection risk in the clinical management of venomous animal bite wounds. IMPORTANCE Notwithstanding their 3 to 5% mortality, the 2.7 million envenomation-related injuries occurring annually-predominantly across Africa, Asia, and Latin America-are also major causes of morbidity. Venom toxin-damaged tissue will develop infections in some 75% of envenomation victims, with E. faecalis being a common culprit of disease; however, such infections are generally considered to be independent of envenomation. Here, we provide evidence on venom microbiota across snakes and arachnida and report on the convergent evolution mechanisms that can facilitate adaptation to black-necked cobra venom in two independent E. faecalis strains, easily misidentified by biochemical diagnostics. Therefore, since inoculation with viable and virulence gene-harboring bacteria can occur during envenomation, acute infection risk management following envenomation is warranted, particularly for immunocompromised and malnourished victims in resource-limited settings. These results shed light on how bacteria evolve for survival in one of the most extreme environments on Earth and how venomous bites must be also treated for infections.

Despite the advent of whole genome metagenomics, targeted approaches (such as 16S rRNA gene amplicon sequencing) continue to be valuable for determining the microbial composition of samples. Amplicon microbiome sequencing can be performed on clinical samples from a normally sterile site to determine the aetiology of an infection (usually single pathogen identification) or samples from more complex niches such as human mucosa or environmental samples where multiple microorganisms need to be identified. The methodologies are frequently applied to determine both presence of micro-organisms and their quantity or relative abundance. There are a number of technical steps required to perform microbial community profiling, many of which may have appreciable precision and bias that impacts final results. In order for these methods to be applied with the greatest accuracy, comparative studies across different laboratories are warranted. In this study we explored the impact of the bioinformatic approaches taken in different laboratories on microbiome assessment using 16S rRNA gene amplicon sequencing results. Data were generated from two mock microbial community samples which were amplified using primer sets spanning five different variable regions of 16S rRNA genes. The PCR-sequencing analysis included three technical repeats of the process to determine the repeatability of their methods. Thirteen laboratories participated in the study, and each analysed the same FASTQ files using their choice of pipeline. This study captured the methods used and the resulting sequence annotation and relative abundance output from bioinformatic analyses. Results were compared to digital PCR assessment of the absolute abundance of each target representing each organism in the mock microbial community samples and also to analyses of shotgun metagenome sequence data. This ring trial demonstrates that the choice of bioinformatic analysis pipeline alone can result in different estimations of the composition of the microbiome when using 16S rRNA gene amplicon sequencing data. The study observed differences in terms of both presence and abundance of organisms and provides a resource for ensuring reproducible pipeline development and application. The observed differences were especially prevalent when using custom databases and applying high stringency operational taxonomic unit (OTU) cut-off limits. In order to apply sequencing approaches with greater accuracy, the impact of different analytical steps needs to be clearly delineated and solutions devised to harmonise microbiome analysis results.

African cichlid fishes not only exhibit remarkably high rates of speciation but also have some of the fastest evolving sex determination systems in vertebrates. However, little is known empirically in cichlids about the genetic mechanisms generating new sex-determining variants, what forces dictate their fate, the demographic scales at which they evolve, and whether they are related to speciation. To address these questions, we looked for sex-associated loci in full genome data from 647 individuals of Astatotilapia calliptera from Lake Masoko, a small isolated crater lake in Tanzania, which contains two distinct ecomorphs of the species. We identified three separate XY systems on recombining chromosomes. Two Y alleles derive from mutations that increase expression of the gonadal soma-derived factor gene ( gsdf ) on chromosome 7; the first is a tandem duplication of the entire gene observed throughout much of the Lake Malawi haplochromine cichlid radiation to which A. calliptera belongs, and the second is a 5 kb insertion directly upstream of gsdf . Both the latter variant and another 700 bp insertion on chromosome 19 responsible for the third Y allele arose from transposable element insertions. Males belonging to the Masoko deep-water benthic ecomorph are determined exclusively by the gsdf duplication, whereas all three Y alleles are used in the Masoko littoral ecomorph, in which they appear to act antagonistically among males with different amounts of benthic admixture. This antagonism in the face of ongoing admixture may be important for sustaining multifactorial sex determination in Lake Masoko. In addition to identifying the molecular basis of three coexisting sex determining alleles, these results demonstrate that genetic interactions between Y alleles and genetic background can potentially affect fitness and adaptive evolution.

Wastewater-based epidemiology (WBE) has become a complimentary surveillance tool during the SARS-CoV-2 pandemic. Viral concentration methods from wastewater are still being optimised and compared, whilst viral recovery under different wastewater characteristics and storage temperatures remains poorly understood. Using urban wastewater samples, we tested three viral concentration methods; polyethylene glycol precipitation (PEG), ammonium sulphate precipitation (AS), and CP select™ InnovaPrep® (IP) ultrafiltration. We found no major difference in SARS-CoV-2 and faecal indicator virus (crAssphage) recovery from wastewater samples (n = 46) using these methods, PEG slightly (albeit non-significantly), outperformed AS and IP for SARS-CoV-2 detection, as a higher genome copies per litre (gc/l) was recorded for a larger proportion of samples. Next generation sequencing of 8 paired samples revealed non-significant differences in the quality of data between AS and IP, though IP data quality was slightly better and less variable. A controlled experiment assessed the impact of wastewater suspended solids (turbidity; 0-400 NTU), surfactant load (0-200 mg/l), and storage temperature (5-20 °C) on viral recovery using the AS and IP methods. SARS-CoV-2 recoveries were >20% with AS and <10% with IP in turbid samples, whilst viral recoveries for samples with additional surfactant were between 0-18% for AS and 0-5% for IP. Turbidity and sample storage temperature combined had no significant effect on SARS-CoV-2 recovery (p > 0.05), whilst surfactant and storage temperature combined were significant negative correlates (p < 0.001 and p < 0.05, respectively). In conclusion, our results show that choice of methodology had small effect on viral recovery of SARS-CoV-2 and crAssphage in wastewater samples within this study. In contrast, sample turbidity, storage temperature, and surfactant load did affect viral recovery, highlighting the need for careful consideration of the viral concentration methodology used when working with wastewater samples.

ABSTRACT Purple prairie clover (PPC; Dalea purpurea Vent.) containing 84.5 g/kg dry matter (DM) of condensed tannin (CT) was ensiled without (control) or with polyethylene glycol (PEG) for 76 days, followed by 14 days of aerobic exposure. Changes in fermentation characteristics were determined, and the composition of bacterial and fungal communities were assessed using metagenomic sequencing. The addition of polyethylene glycol (PEG) that deactivated CT at ensiling increased ( P < 0.05 to ∼0.001) soluble N, nonprotein N, lactic acid, total volatile fatty acids, ammonia N, deoxynivalenol (DON), and ochratoxin A (OTA) but decreased ( P < 0.001) pH and water-soluble carbohydrates. The concentrations of DON and OTA increased ( P < 0.001) for both silages, with the extent of increase being greater for control than for PEG-treated silage during aerobic exposure. The PEG-treated silage exhibited higher ( P < 0.01 to ∼0.001) copy numbers of total bacteria, Lactobacillus , yeasts, and fungi than the control. The addition of PEG decreased ( P < 0.01) bacterial diversity during both ensiling and aerobic exposure, whereas it increased ( P < 0.05) fungal diversity during aerobic exposure. The addition of PEG at ensiling increased ( P < 0.05) the abundances of Lactobacillus and Pediococcus species but decreased ( P < 0.01) the abundances of Lactococcus and Leuconostoc species. Filamentous fungi were found in the microbiome at ensiling and after aerobic exposure, whereas Bacillus spp. were the dominate bacteria after aerobic exposure. In conclusion, CT decreased protein degradation and improved the aerobic stability of silage. These desirable outcomes likely reflect the ability of PPC CT to inhibit those microorganisms involved in lowering silage quality and in the production of mycotoxins. IMPORTANCE The present study reports the effects of condensed tannins on the complex microbial communities involved in ensiling and aerobic exposure of purple prairie clover. This study documents the ability of condensed tannins to lower mycotoxin production and the associated microbiome. Taxonomic bacterial community profiles were dominated by Lactobacillales after fermentation, with a notable increase in Bacillus spp. as a result of aerobic exposure. It is interesting to observe that condensed tannins decreased bacterial diversity during both ensiling and aerobic exposure but increased fungal diversity during aerobic exposure only. The present study indicates that the effects of condensed tannins on microbial communities lead to reduced lactic acid and total volatile fatty acid production, proteolysis, and mycotoxin concentration in the terminal silage and improved aerobic stability. Condensed tannins could be used as an additive to control unfavorable microbial development and maybe enhanced feed safety.

Metagenomics, the study of genetic material recovered directly from environmental samples, has the potential to provide insight into the structure and function of heterogeneous microbial communities. There has been an increased use of metagenomics to discover and understand the diverse biosynthetic capacities of marine microbes, thereby allowing them to be exploited for industrial, food, and health care products. This ELIXIR pilot action was motivated by the need to establish dedicated data resources and harmonized metagenomics pipelines for the marine domain, in order to enhance the exploration and exploitation of marine genetic resources. In this paper, we summarize some of the results from the ELIXIR pilot action “Marine metagenomics – towards user centric services”.

Metagenomics, the study of genetic material recovered directly from environmental samples, has the potential to provide insight into the structure and function of heterogeneous microbial communities. There has been an increased use of metagenomics to discover and understand the diverse biosynthetic capacities of marine microbes, thereby allowing them to be exploited for industrial, food, and health care products. This ELIXIR pilot action was motivated by the need to establish dedicated data resources and harmonized metagenomics pipelines for the marine domain, in order to enhance the exploration and exploitation of marine genetic resources. In this paper, we summarize some of the results from the ELIXIR pilot action “Marine metagenomics – towards user centric services”.

EBI metagenomics (http://www.ebi.ac.uk/metagenomics) provides a free to use platform for the analysis and archiving of sequence data derived from the microbial populations found in a particular environment. Over the past two years, EBI metagenomics has increased the number of datasets analysed 10-fold. In addition to increased throughput, the underlying analysis pipeline has been overhauled to include both new or updated tools and reference databases. Of particular note is a new workflow for taxonomic assignments that has been extended to include assignments based on both the large and small subunit RNA marker genes and to encompass all cellular micro-organisms. We also describe the addition of metagenomic assembly as a new analysis service. Our pilot studies have produced over 2400 assemblies from datasets in the public domain. From these assemblies, we have produced a searchable, non-redundant protein database of over 50 million sequences. To provide improved access to the data stored within the resource, we have developed a programmatic interface that provides access to the analysis results and associated sample metadata. Finally, we have integrated the results of a series of statistical analyses that provide estimations of diversity and sample comparisons.

EBI metagenomics (EMG, https://www.ebi.ac.uk/metagenomics/ ) is a free to use hub for the analysis and exploration of metagenomic, metatranscriptomic, amplicon and assembly data. The resource provides rich functional and taxonomic analyses of user-submitted sequences, as well as analysis of publicly available metagenomic datasets that are held within the European Nucleotide Archive (ENA). The pipeline is capable of providing analysis of extremely large datasets. For example, in 2015, we analysed the oceanographic dataset, Tara Oceans, which is the largest project to be processed by EMG to date, with ∼10 Tb of sequence data (∼29 billion sequences). The pipeline is also able to provide a high level of throughput: the number of analysed datasets within the resource has grown 10-fold in 2016 (as of 22 July 2016), and now comprises over 55,000 sequence runs, with over 200 billion sequences analysed in total. To address future analysis challenges, as metagenomic datasets grow ever larger, we have continued to refine the pipeline, with the aim of improving scalability and portability. As part of this process, we have begun to investigate ways to deploy the pipeline on computing clouds within the ELIXIR hub, as well as commercial clouds, such as Amazon or Google. Here, we give an overview of the analysis pipeline itself, outline a number of updates that we have made to ensure scalability and discuss the ongoing work to deploy it on the cloud.

The EBI Metagenomics portal The EBI Metagenomics portal [6] is a free to use analysis service for metagenomics data. In order to have your data analysed by EBI Metagenomics, your sequence data have to be archived in the European Nucleotide Archive [7] (ENA). This tutorial will explain why you have to follow this procedure and will then guide you through the process of archiving your metagenomic data in the ENA.

EBI metagenomics (https://www.ebi.ac.uk/metagenomics/) is a freely available hub for the analysis and archiving of metagenomic and metatranscriptomic data. Over the last 2 years, the resource has undergone rapid growth, with an increase of over five-fold in the number of processed samples and consequently represents one of the largest resources of analysed shotgun metagenomes. Here, we report the status of the resource in 2016 and give an overview of new developments. In particular, we describe updates to data content, a complete overhaul of the analysis pipeline, streamlining of data presentation via the website and the development of a new web based tool to compare functional analyses of sequence runs within a study. We also highlight two of the higher profile projects that have been analysed using the resource in the last year: the oceanographic projects Ocean Sampling Day and Tara Oceans.