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Funder: UK National Measurement System, Funder: NIHR BRC and NIHR Policy Research Programme (NIBSC Regulatory Science Research Unit), Funder: National Institute of Health Research (NIHR) Imperial Biomedical Research Centre (BRC), Funder: EMBL core funds, Funder: Quadram Institute Bioscience BBSRC Strategic Programme: Microbes in the Food Chain; Grant(s): BB/R012504/1) and its constituent projects BBS/E/F/000PR10348 and BBS/E/F/000PR10349, 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.

Succinate dehydrogenase inhibitor (SDHI) fungicides are widely used for the control of a broad range of fungal diseases. This has been the most rapidly expanding fungicide group in terms of new molecules discovered and introduced for agricultural use over the past fifteen years. A particular pattern of differential sensitivity (resistance) to the stretched heterocycle amide SDHIs (SHA-SDHIs), a subclass of chemically-related SDHIs, was observed in naïve Zymoseptoria tritici populations not previously exposed to these chemicals. Subclass-specific resistance was confirmed at the enzyme level but did not correlate with the genotypes of the succinate dehydrogenase (SDH) encoding genes. Mapping and characterization of the molecular mechanisms responsible for standing SHA-SDHI resistance in natural field isolates identified a gene paralog of SDHC, termed ZtSDHC3, which encodes for an alternative C subunit of succinate dehydrogenase, named alt-SDHC. Using reverse genetics, we showed that alt-SDHC associates with the three other SDH subunits, leading to a fully functional enzyme and that a unique Qp-site residue within the alt-SDHC protein confers SHA-SDHI resistance. Enzymatic assays, computational modelling and docking simulations for the two SQR enzymes (altC-SQR, WT_SQR) enabled us to describe enzyme-inhibitor interactions at an atomistic level and to propose rational explanations for differential potency and resistance across SHA-SDHIs. European Z. tritici populations displayed a presence (20–30%) / absence polymorphism of ZtSDHC3, as well as differences in ZtSDHC3 expression levels and splicing efficiency. These polymorphisms have a strong impact on SHA-SDHI resistance phenotypes. Characterization of the ZtSDHC3 promoter in European Z. tritici populations suggests that transposon insertions are associated with the strongest resistance phenotypes. These results establish that a dispensable paralogous gene determines SHA-SDHIs fungicide resistance in natural populations of Z. tritici. This study paves the way to an increased awareness of the role of fungicidal target paralogs in resistance to fungicides and demonstrates the paramount importance of population genomics in fungicide discovery., Author summary Zymoseptoria tritici is the causal agent of Septoria tritici leaf blotch (STB) of wheat, the most devastating disease for cereal production in Europe. Multiple succinate dehydrogenase inhibitor (SDHI) fungicides have been developed and introduced for the control of STB. We report the discovery and detailed characterization of a paralog of the C subunit of the SDH enzyme conferring standing resistance towards the SHA-SDHIs, a particular chemical subclass of the SDHIs. The SDHC paralog is characterized by its presence/absence, expression and alternative splicing polymorphisms, which in turn influence resistance levels. The identified mechanisms exemplify the importance of population genomics for the discovery and rational design of the most adapted solutions.

Recombination is one of the determinants of genetic diversity in the foot-and-mouth disease virus (FMDV). FMDV sequences have a mosaic structure caused by extensive intra- and inter-serotype recombination, with the exception of the capsid-encoding region. While these genome-wide patterns of broad-scale recombination are well studied, not much is known about the patterns of recombination that may exist within infected hosts. In addition, detection of recombination among viruses evolving at the within-host level is challenging due to the similarity of the sequences and the limitations in differentiating recombination from point mutations. Here, we present the first analysis of recombination events between closely related FMDV sequences occurring within buffalo hosts. The detection of these events was made possible by the occurrence of co-infection of two viral swarms with about 1% nucleotide divergence. We found more than 15 recombination events, unequally distributed across eight samples from different animals. The distribution of these events along the FMDV genome was neither uniform nor related to the phylogenetic distribution of recombination breakpoints, suggesting a mismatch between within-host evolutionary pressures and long-term selection for infectivity and transmissibility.

Nonenveloped viruses protect their genomes by packaging them into an outer shell or capsid of virus-encoded proteins. Packaging and capsid assembly in RNA viruses can involve interactions between capsid proteins and secondary structures in the viral genome, as exemplified by the RNA bacteriophage MS2 and as proposed for other RNA viruses of plants, animals, and human. In the picornavirus family of nonenveloped RNA viruses, the requirements for genome packaging remain poorly understood. Here, we show a novel and simple approach to identify predicted RNA secondary structures involved in genome packaging in the picornavirus foot-and-mouth disease virus (FMDV). By interrogating deep sequencing data generated from both packaged and unpackaged populations of RNA, we have determined multiple regions of the genome with constrained variation in the packaged population. Predicted secondary structures of these regions revealed stem-loops with conservation of structure and a common motif at the loop. Disruption of these features resulted in attenuation of virus growth in cell culture due to a reduction in assembly of mature virions. This study provides evidence for the involvement of predicted RNA structures in picornavirus packaging and offers a readily transferable methodology for identifying packaging requirements in many other viruses. IMPORTANCE In order to transmit their genetic material to a new host, nonenveloped viruses must protect their genomes by packaging them into an outer shell or capsid of virus-encoded proteins. For many nonenveloped RNA viruses the requirements for this critical part of the viral life cycle remains poorly understood. We have identified RNA sequences involved in genome packaging of the picornavirus foot-and-mouth disease virus. This virus causes an economically devastating disease of livestock affecting both the developed and developing world. The experimental methods developed to carry out this work are novel, simple, and transferable to the study of packaging signals in other RNA viruses. Improved understanding of RNA packaging may lead to novel vaccine approaches or targets for antiviral drugs with broad-spectrum activity.