Comparative evaluation of soil DNA extraction kits for long read metagenomic sequencing.

Metagenomics has been transformative in our understanding of the diversity and function of soil microbial communities. Applying long read sequencing to whole genome shotgun metagenomics has the potential to revolutionise soil microbial ecology through improved taxonomic classification, functional characterisation and metagenome assembly. However, optimisation of robust methods for long read metagenomics of environmental samples remains undeveloped. In this study, Oxford Nanopore sequencing using samples from five commercially available soil DNA extraction kits was compared across four soil types, in order to optimise read length and reproducibility for comparative long read soil metagenomics. Average extracted DNA lengths varied considerably between kits, but longer DNA fragments did not translate consistently into read lengths. Highly variable decreases in the length of resulting reads from some kits were associated with poor classification rate and low reproducibility in microbial communities identified between technical repeats. Replicate samples from other kits showed more consistent conversion of extracted DNA fragment size into read length and resulted in more congruous microbial community representation. Furthermore, extraction kits showed significant differences in the community representation and structure they identified across all soil types. Overall, the QIAGEN DNeasy PowerSoil Pro Kit displayed the best suitability for reproducible long-read WGS metagenomic sequencing, although further optimisation of DNA purification and library preparation may enable translation of higher molecular weight DNA from other kits into longer read lengths. These findings provide a novel insight into the importance of optimising DNA extraction for achieving replicable results from long read metagenomic sequencing of environmental samples.

Utility of wastewater genomic surveillance compared to clinical surveillance to track the spread of the SARS-CoV-2 Omicron variant across England.

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.

Comparison of metagenomic and targeted methods for sequencing human pathogenic viruses from wastewater.

Wastewater-based epidemiology is a powerful tool for monitoring the emergence and spread of viral pathogens at the population scale. Typical polymerase chain reaction (PCR)-based methods of quantitative and genomic monitoring of viruses in wastewater provide high sensitivity and specificity. However, these methods are limited to the surveillance of target viruses in a single assay and require prior knowledge of the target genome(s). Metagenomic sequencing methods may represent a target-agnostic approach to viral wastewater monitoring, allowing for the detection of a broad range of target viruses, including potentially novel and emerging pathogens. In this study, targeted and untargeted metagenomic sequencing methods were compared with tiled-PCR sequencing for the detection and genotyping of viral pathogens in wastewater samples. Deep shotgun metagenomic sequencing was unable to generate sufficient genome coverage of human pathogenic viruses for robust genomic epidemiology, with samples dominated by bacteria. Hybrid-capture enrichment of shotgun libraries for respiratory viruses led to significant increases in genome coverage for a range of targets. Tiled-PCR sequencing led to further improvements in genome coverage compared to hybrid capture for severe acute respiratory syndrome coronavirus 2, enterovirus D68, norovirus GII, and human adenovirus F41 in wastewater samples. In conclusion, untargeted shotgun sequencing was unsuitable for genomic monitoring of the low virus concentrations in wastewater samples analyzed in this study. Hybrid-capture enrichment represented a viable method for simultaneous genomic epidemiology of a range of viral pathogens, while tiled-PCR sequencing provided the optimal genome coverage for individual viruses with the minimum sequencing depth. IMPORTANCE Most public health initiatives that monitor viruses in wastewater have utilized quantitative polymerase chain reaction (PCR) and whole genome PCR sequencing, mirroring techniques used for viral epidemiology in individuals. These techniques require prior knowledge of the target viral genome and are limited to monitoring individual or small groups of viruses. Metagenomic sequencing may offer an alternative strategy for monitoring a broad spectrum of viruses in wastewater, including novel and emerging pathogens. In this study, while amplicon sequencing gave high viral genome coverage, untargeted shotgun sequencing of total nucleic acid samples was unable to detect human pathogenic viruses with enough sensitivity for use in genomic epidemiology. Enrichment of shotgun libraries for respiratory viruses using hybrid-capture technology provided genotypic information on a range of viruses simultaneously, indicating strong potential for wastewater surveillance. This type of targeted metagenomics could be used for monitoring diverse targets, such as pathogens or antimicrobial resistance genes, in environmental samples.

Postpandemic rebound of adeno-associated virus type 2 (AAV2) infections temporally associated with an outbreak of unexplained severe acute hepatitis in children in the United Kingdom.

Over 1000 cases of unexplained severe acute hepatitis in children have been reported to date worldwide. An association with adeno-associated virus type 2 (AAV2) infection, a human parvovirus, prompted us to investigate the epidemiology of AAV in the United Kingdom. Three hundred pediatric respiratory samples collected before (April 03, 2009-April 03, 2013) and during (April 03, 2022) the COVID-19 pandemic were obtained. Wastewater samples were collected from 50 locations in London (August 2021-March 2022). Samples were tested for AAV using real-time polymerase chain reaction followed by sequencing. Selected adenovirus (AdV)-positive samples were also sequenced. The detection frequency of AAV2 was a sevenfold higher in 2022 samples compared with 2009-2013 samples (10% vs. 1.4%) and highest in AdV-positive samples compared with negatives (10/37, 27% vs. 5/94, 5.3%, respectively). AAV2-positive samples displayed high genetic diversity. AAV2 sequences were either very low or absent in wastewater collected in 2021 but increased in January 2022 and peaked in March 2022. AAV2 was detected in children in association with AdV of species C, with a highest frequency in 2022. Our findings are consistent with the expansion of the population of children unexposed to AAV2, leading to greater spread of the virus once distancing restrictions were lifted.

Comparison of the impact of two key fungal signalling pathways on Zymoseptoria tritici infection reveals divergent contribution to invasive growth through distinct regulation of infection-associated genes.

The lifecycle of Zymoseptoria tritici requires a carefully regulated asymptomatic phase within the wheat leaf following penetration of the mesophyll via stomata. Here we compare the roles in this process of two key fungal signalling pathways, mutants of which were identified through forward genetics due to their avirulence on wheat. Whole-genome resequencing of avirulent Z. tritici T-DNA transformants identified disruptive mutations in ZtBCK1 from the kinase cascade of the cell wall integrity (CWI) pathway, and the adenylate cyclase gene ZtCYR1. Targeted deletion of these genes abolished the pathogenicity of the fungus and led to similar in vitro phenotypes to those associated with disruption of putative downstream kinases, both supporting previous studies and confirming the importance of these pathways in virulence. RNA sequencing was used to investigate the effect of ZtBCK1 and ZtCYR1 deletion on gene expression in both the pathogen and host during infection. ZtBCK1 was found to be required for the adaptation to the host environment, controlling expression of infection-associated secreted proteins, including known virulence factors. Meanwhile, ZtCYR1 is implicated in controlling the switch to necrotrophy, regulating expression of effectors associated with this transition. This represents the first study to compare the influence of CWI and cAMP signalling on in planta transcription of a fungal plant pathogen, providing insights into their differential regulation of candidate effectors during invasive growth.

Optimised protocol for monitoring SARS-CoV-2 in wastewater using reverse complement PCR-based whole-genome sequencing.

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.

Distinct roles for different autophagy-associated genes in the virulence of the fungal wheat pathogen Zymoseptoria tritici.

The fungal wheat pathogen Zymoseptoria tritici causes major crop losses as the causal agent of the disease Septoria tritici blotch. The infection cycle of Z. tritici displays two distinct phases, beginning with an extended symptomless phase of 1-2 weeks, before the fungus induces host cell death and tissue collapse in the leaf. Recent evidence suggests that the fungus uses little host-derived nutrition during asymptomatic colonisation, raising questions as to the sources of energy required for this initial growth phase. Autophagy is crucial for the pathogenicity of other fungal plant pathogens through its roles in supporting cellular differentiation and growth under starvation. Here we characterised the contributions of the autophagy genes ZtATG1 and ZtATG8 to the development and virulence of Z. tritici. Deletion of ZtATG1 led to inhibition of autophagy but had no impact on starvation-induced hyphal differentiation or virulence, suggesting that autophagy is not required for Z. tritici pathogenicity. Contrastingly, ZtATG8 deletion delayed the transition to necrotrophic growth, despite having no influence on filamentous growth under starvation, pointing to an autophagy-independent role of ZtATG8 during Z. tritici infection. To our knowledge, this study represents the first to find autophagy not to contribute to the virulence of a fungal plant pathogen, and reveals novel roles for different autophagy-associated proteins in Z. tritici.