RNA-viromics reveals diverse communities of soil RNA viruses with the potential to affect grassland ecosystems across multiple trophic levels

The distribution and diversity of RNA viruses in soil ecosystems are largely unknown, despite their significant impact on public health, ecosystem functions, and food security. Here, we characterise soil RNA viral communities along an altitudinal productivity gradient of peat, managed grassland and coastal soils. We identified 3462 viral contigs in RNA viromes from purified virus-like-particles in five soil-types and assessed their spatial distribution, phylogenetic diversity and potential host ranges. Soil types exhibited minimal similarity in viral community composition, but with >10-fold more viral contigs shared between managed grassland soils when compared with peat or coastal soils. Phylogenetic analyses predicted soil RNA viral communities are formed from viruses of bacteria, plants, fungi, vertebrates and invertebrates, with only 12% of viral contigs belonging to the bacteria-infecting Leviviricetes class. 11% of viral contigs were found to be most closely related to members of the Ourmiavirus genus, suggesting that members of this clade of plant viruses may be far more widely distributed and diverse than previously thought. These results contrast with soil DNA viromes which are typically dominated by bacteriophages. RNA viral communities, therefore, have the potential to exert influence on inter-kingdom interactions across terrestrial biomes

Modelling fish habitat preference with a genetic algorithm-optimized Takagi-Sugeno model based on pairwise comparisons

Species-environment relationships are used for evaluating the current status of target species and the potential impact of natural or anthropogenic changes of their habitat. Recent researches reported that the results are strongly affected by the quality of a data set used. The present study attempted to apply pairwise comparisons to modelling fish habitat preference with Takagi-Sugeno-type fuzzy habitat preference models (FHPMs) optimized by a genetic algorithm (GA). The model was compared with the result obtained from the FHPM optimized based on mean squared error (MSE). Three independent data sets were used for training and testing of these models. The FHPMs based on pairwise comparison produced variable habitat preference curves from 20 different initial conditions in the GA. This could be partially ascribed to the optimization process and the regulations assigned. This case study demonstrates applicability and limitations of pairwise comparison-based optimization in an FHPM. Future research should focus on a more flexible learning process to make a good use of the advantages of pairwise comparisons

Tracing the fate of wastewater viruses reveals catchment-scale virome diversity and connectivity

The discharge of wastewater-derived viruses in aquatic environments impacts catchment-scale virome composition and is a potential hazard to human health. Here, we used viromic analysis of RNA and DNA virus-like particle preparations to track virus communities entering and leaving wastewater treatment plants and the connecting river catchment system and estuary. We found substantial viral diversity and geographically distinct virus communities associated with different wastewater treatment plants. River and estuarine water bodies harboured more diverse viral communities in downstream locations, influenced by tidal movement and proximity to wastewater treatment plants. Shellfish and beach sand were enriched in viral communities when compared with the surrounding water, acting as entrapment matrices for virus particles. We reconstructed >40,000 partial viral genomes into 10,149 species-level groups, dominated by dsDNA and (+)ssRNA bacteriophages (Caudovirales and Leviviridae). We identified 73 (partial) genomes comprising six families that could pose a risk to human health; Astroviridae, Caliciviridae (sapovirus), Picornaviridae (cocksackievirus), Reoviridae (rotavirus), Parvoviridae and Circoviridae. Based on the pattern of viral incidence, we observe that wastewater-derived viral genetic material is commonly deposited in the environment, but due to fragemented nature of these viral genomes, the risk to human health is low, and is more likely driven by community transmission, with wastewater-derived viruses subject to cycles of dilution, enrichment and virion degradation influenced by local geography, weather events and tidal effects. Our data illustrate the utility of viromic analyses for wastewater- and environment-based epidemiology, and we present a conceptual model for the circulation of viruses in a freshwater catchment

Viromic Analysis of Wastewater Input to a River Catchment Reveals a Diverse Assemblage of RNA Viruses

Enteric viruses cause gastrointestinal illness and are commonly transmitted through the fecal-oral route. When wastewater is released into river systems, these viruses can contaminate the environment. Our results show that we can use viromics to find the range of potentially pathogenic viruses that are present in the environment and identify prevalent genotypes. The ultimate goal is to trace the fate of these pathogenic viruses from origin to the point where they are a threat to human health, informing reference-based detection methods and water quality management.Detection of viruses in the environment is heavily dependent on PCR-based approaches that require reference sequences for primer design. While this strategy can accurately detect known viruses, it will not find novel genotypes or emerging and invasive viral species. In this study, we investigated the use of viromics, i.e., high-throughput sequencing of the biosphere’s viral fraction, to detect human-/animal-pathogenic RNA viruses in the Conwy river catchment area in Wales, United Kingdom. Using a combination of filtering and nuclease treatment, we extracted the viral fraction from wastewater and estuarine river water and sediment, followed by high-throughput RNA sequencing (RNA-Seq) analysis on the Illumina HiSeq platform, for the discovery of RNA virus genomes. We found a higher richness of RNA viruses in wastewater samples than in river water and sediment, and we assembled a complete norovirus genotype GI.2 genome from wastewater effluent, which was not contemporaneously detected by conventional reverse transcription-quantitative PCR (qRT-PCR). The simultaneous presence of diverse rotavirus signatures in wastewater indicated the potential for zoonotic infections in the area and suggested runoff from pig farms as a possible origin of these viruses. Our results show that viromics can be an important tool in the discovery of pathogenic viruses in the environment and can be used to inform and optimize reference-based detection methods provided appropriate and rigorous controls are included

BAG3 Pro209 mutants associated with myopathy and neuropathy relocate chaperones of the CASA-complex to aggresomes

Three missense mutations targeting the same proline 209 (Pro209) codon in the co-chaperone Bcl2-associated athanogene 3 (BAG3) have been reported to cause distal myopathy, dilated cardiomyopathy or Charcot-Marie-Tooth type 2 neuropathy. Yet, it is unclear whether distinct molecular mechanisms underlie the variable clinical spectrum of the rare patients carrying these three heterozygous Pro209 mutations in BAG3. Here, we studied all three variants and compared them to the BAG3_Glu455Lys mutant, which causes dilated cardiomyopathy. We found that all BAG3_Pro209 mutants have acquired a toxic gain-of-function, which causes these variants to accumulate in the form of insoluble HDAC6- and vimentin-positive aggresomes. The aggresomes formed by mutant BAG3 led to a relocation of other chaperones such as HSPB8 and Hsp70, which, together with BAG3, promote the so-called chaperone-assisted selective autophagy (CASA). As a consequence of their increased aggregation-proneness, mutant BAG3 trapped ubiquitinylated client proteins at the aggresome, preventing their efficient clearance. Combined, these data show that all BAG3_Pro209 mutants, irrespective of their different clinical phenotypes, are characterized by a gain-of-function that contributes to the gradual loss of protein homeostasis

Transcriptomic profiling of pancreatic alpha, beta and delta cell populations identifies delta cells as a principal target for ghrelin in mouse islets.

AIMS/HYPOTHESIS: Intra-islet and gut-islet crosstalk are critical in orchestrating basal and postprandial metabolism. The aim of this study was to identify regulatory proteins and receptors underlying somatostatin secretion though the use of transcriptomic comparison of purified murine alpha, beta and delta cells. METHODS: Sst-Cre mice crossed with fluorescent reporters were used to identify delta cells, while Glu-Venus (with Venus reported under the control of the Glu [also known as Gcg] promoter) mice were used to identify alpha and beta cells. Alpha, beta and delta cells were purified using flow cytometry and analysed by RNA sequencing. The role of the ghrelin receptor was validated by imaging delta cell calcium concentrations using islets with delta cell restricted expression of the calcium reporter GCaMP3, and in perfused mouse pancreases. RESULTS: A database was constructed of all genes expressed in alpha, beta and delta cells. The gene encoding the ghrelin receptor, Ghsr, was highlighted as being highly expressed and enriched in delta cells. Activation of the ghrelin receptor raised cytosolic calcium levels in primary pancreatic delta cells and enhanced somatostatin secretion in perfused pancreases, correlating with a decrease in insulin and glucagon release. The inhibition of insulin secretion by ghrelin was prevented by somatostatin receptor antagonism. CONCLUSIONS/INTERPRETATION: Our transcriptomic database of genes expressed in the principal islet cell populations will facilitate rational drug design to target specific islet cell types. The present study indicates that ghrelin acts specifically on delta cells within pancreatic islets to elicit somatostatin secretion, which in turn inhibits insulin and glucagon release. This highlights a potential role for ghrelin in the control of glucose metabolism.This work was supported by the European Foundation for the Study of Diabetes and Boehringer Ingelheim Basic Research Programme; the Wellcome Trust (grants 106262/Z/14/Z, 106263/Z/14/Z and 100574/ Z/12/Z); the Medical Research Council Metabolic Diseases Unit (grants MRC_MC_UU_12012/3 and MRC_MC_UU_12012/5); and the Novo Nordisk Foundation