Project description:Nucleo-cytoplasmic large DNA viruses are doubled stranded DNA viruses capable of infecting eukaryotic cells. Since the discovery of Mimivirus and Pandoravirus, there has been no doubt about their extraordinary features compared to "classic" viruses. Recently, we reported the expansion of the proposed family Pithoviridae, with the description of Cedratvirus and Orpheovirus, two new viruses related to Pithoviruses. Studying the major capsid protein of Orpheovirus, we detected a homologous sequence in a mine drainage metagenome. The in-depth exploration of this metagenome, using the MG-Digger program, enabled us to retrieve up to 10 contigs with clear evidence of viral sequences. Moreover, phylogenetic analyses further extended our screening with the discovery in another marine metagenome of a second virus closely related to Orpheovirus IHUMI-LCC2. This virus is a misidentified virus confused with and annotated as a Rickettsiales bacterium. It presents a partial genome size of about 170 kbp.
Project description:The viral metagenome within an activated sludge microbial assemblage was sampled using culture-dependent and culture-independent methods and compared to the diversity of activated sludge bacterial taxa. A total of 70 unique cultured bacterial isolates, 24 cultured bacteriophages, 829 bacterial metagenomic clones of 16S rRNA genes, and 1,161 viral metagenomic clones were subjected to a phylogenetic analysis.
Project description:BACKGROUND: Metagenomics, based on culture-independent sequencing, is a well-fitted approach to provide insights into the composition, structure and dynamics of environmental viral communities. Following recent advances in sequencing technologies, new challenges arise for existing bioinformatic tools dedicated to viral metagenome (i.e. virome) analysis as (i) the number of viromes is rapidly growing and (ii) large genomic fragments can now be obtained by assembling the huge amount of sequence data generated for each metagenome. RESULTS: To face these challenges, a new version of Metavir was developed. First, all Metavir tools have been adapted to support comparative analysis of viromes in order to improve the analysis of multiple datasets. In addition to the sequence comparison previously provided, viromes can now be compared through their k-mer frequencies, their taxonomic compositions, recruitment plots and phylogenetic trees containing sequences from different datasets. Second, a new section has been specifically designed to handle assembled viromes made of thousands of large genomic fragments (i.e. contigs). This section includes an annotation pipeline for uploaded viral contigs (gene prediction, similarity search against reference viral genomes and protein domains) and an extensive comparison between contigs and reference genomes. Contigs and their annotations can be explored on the website through specifically developed dynamic genomic maps and interactive networks. CONCLUSIONS: The new features of Metavir 2 allow users to explore and analyze viromes composed of raw reads or assembled fragments through a set of adapted tools and a user-friendly interface.
Project description:Metagenomic analyses of marine viruses generate an overview of viral genes present in a sample, but the percentage of the resulting sequence fragments that can be reassembled is low and the phenotype of the virus from which a given sequence derives is usually unknown. In this study, we employed physical fractionation to characterize the morphological and genomic traits of a subset of uncultivated viruses from a natural marine assemblage. Viruses from Kāne'ohe Bay, Hawai'i were fractionated by equilibrium buoyant density centrifugation in a cesium chloride (CsCl) gradient, and one fraction from the CsCl gradient was then further fractionated by strong anion-exchange chromatography. One of the fractions resulting from this two-dimensional separation appeared to be dominated by only a few virus types based on genome sizes and morphology. Sequences generated from a shotgun clone library of the viruses in this fraction were assembled into significantly more numerous contigs than have been generated with previous metagenomic investigations of whole DNA viral assemblages with comparable sequencing effort. Analysis of the longer contigs (up to 6.5 kb) assembled from our metagenome allowed us to assess gene arrangement in this subset of marine viruses. Our results demonstrate the potential for physical fractionation to facilitate sequence assembly from viral metagenomes and permit linking of morphological and genomic data for uncultivated viruses.
Project description:The large diversity of viruses that exist in human populations are potentially excreted into sewage collection systems and concentrated in sewage sludge. In the U.S., the primary fate of processed sewage sludge (class B biosolids) is application to agricultural land as a soil amendment. To characterize and understand infectious risks associated with land application, and to describe the diversity of viruses in human populations, shotgun viral metagenomics was applied to 10 sewage sludge samples from 5 wastewater treatment plants throughout the continental U.S, each serving between 100,000 and 1,000,000 people. Nearly 330 million DNA sequences were produced and assembled, and annotation resulted in identifying 43 (26 DNA, 17 RNA) different types of human viruses in sewage sludge. Novel insights include the high abundance of newly emerging viruses (e.g., Coronavirus HKU1, Klassevirus, and Cosavirus) the strong representation of respiratory viruses, and the relatively minor abundance and occurrence of Enteroviruses. Viral metagenome sequence annotations were reproducible and independent PCR-based identification of selected viruses suggests that viral metagenomes were a conservative estimate of the true viral occurrence and diversity. These results represent the most complete description of human virus diversity in any wastewater sample to date, provide engineers and environmental scientists with critical information on important viral agents and routes of infection from exposure to wastewater and sewage sludge, and represent a significant leap forward in understanding the pathogen content of class B biosolids.
Project description:RNA viruses have been associated with enteritis in poultry and have been isolated from diseased birds. The same viral agents have also been detected in healthy flocks bringing into question their role in health and disease. In order to understand better eukaryotic viruses in the gut, this project focused on evaluating alternative methods to purify and concentrate viral particles, which do not involve the use of density gradients, for generating viral metagenome data. In this study, the sequence outcomes of three tissue processing methods have been evaluated and a data analysis pipeline has been established for RNA viruses from the gastrointestinal tract. In addition, with the use of the best method and increased sequencing depth, a glimpse of the RNA viral community in the gastrointestinal tract of a clinically normal 5-week old turkey is presented. The viruses from the Reoviridae and Astroviridae families together accounted for 76.3% of total viruses identified. The rarefaction curve at the species level further indicated that majority of the species diversity was included with the increased sequencing depth, implying that viruses from other viral families were present in very low abundance.
Project description:With its capacity for anaerobic methane oxidation and denitrification, the bacterium Methylomirabilis oxyfera plays an important role in natural ecosystems. Its unique physiology can be exploited for more sustainable wastewater treatment technologies. However, operational stability of full-scale bioreactors can experience setbacks due to, for example, bacteriophage blooms. By shaping microbial communities through mortality, horizontal gene transfer, and metabolic reprogramming, bacteriophages are important players in most ecosystems. Here, we analyzed an infected Methylomirabilis sp. bioreactor enrichment culture using (advanced) electron microscopy, viral metagenomics and bioinformatics. Electron micrographs revealed four different viral morphotypes, one of which was observed to infect Methylomirabilis cells. The infected cells contained densely packed ~55 nm icosahedral bacteriophage particles with a putative internal membrane. Various stages of virion assembly were observed. Moreover, during the bacteriophage replication, the host cytoplasmic membrane appeared extremely patchy, which suggests that the bacteriophages may use host bacterial lipids to build their own putative internal membrane. The viral metagenome contained 1.87 million base pairs of assembled viral sequences, from which five putative complete viral genomes were assembled and manually annotated. Using bioinformatics analyses, we could not identify which viral genome belonged to the Methylomirabilis- infecting bacteriophage, in part because the obtained viral genome sequences were novel and unique to this reactor system. Taken together these results show that new bacteriophages can be detected in anaerobic cultivation systems and that the effect of bacteriophages on the microbial community in these systems is a topic for further study.
Project description:Viral metagenomics (viromics) is increasingly used to obtain uncultivated viral genomes, evaluate community diversity, and assess ecological hypotheses. While viromic experimental methods are relatively mature and widely accepted by the research community, robust bioinformatics standards remain to be established. Here we used in silico mock viral communities to evaluate the viromic sequence-to-ecological-inference pipeline, including (i) read pre-processing and metagenome assembly, (ii) thresholds applied to estimate viral relative abundances based on read mapping to assembled contigs, and (iii) normalization methods applied to the matrix of viral relative abundances for alpha and beta diversity estimates.Tools specifically designed for metagenomes, specifically metaSPAdes, MEGAHIT, and IDBA-UD, were the most effective at assembling viromes. Read pre-processing, such as partitioning, had virtually no impact on assembly output, but may be useful when hardware is limited. Viral populations with 2-5 × coverage typically assembled well, whereas lesser coverage led to fragmented assembly. Strain heterogeneity within populations hampered assembly, especially when strains were closely related (average nucleotide identity, or ANI ?97%) and when the most abundant strain represented <50% of the population. Viral community composition assessments based on read recruitment were generally accurate when the following thresholds for detection were applied: (i) ?10 kb contig lengths to define populations, (ii) coverage defined from reads mapping at ?90% identity, and (iii) ?75% of contig length with ?1 × coverage. Finally, although data are limited to the most abundant viruses in a community, alpha and beta diversity patterns were robustly estimated (±10%) when comparing samples of similar sequencing depth, but more divergent (up to 80%) when sequencing depth was uneven across the dataset. In the latter cases, the use of normalization methods specifically developed for metagenomes provided the best estimates.These simulations provide benchmarks for selecting analysis cut-offs and establish that an optimized sample-to-ecological-inference viromics pipeline is robust for making ecological inferences from natural viral communities. Continued development to better accessing RNA, rare, and/or diverse viral populations and improved reference viral genome availability will alleviate many of viromics remaining limitations.
Project description:Reconstructing the genomes of microbial community members is key to the interpretation of shotgun metagenome samples. Genome binning programs deconvolute reads or assembled contigs of such samples into individual bins. However, assessing their quality is difficult due to the lack of evaluation software and standardized metrics. Here, we present Assessment of Metagenome BinnERs (AMBER), an evaluation package for the comparative assessment of genome reconstructions from metagenome benchmark datasets. It calculates the performance metrics and comparative visualizations used in the first benchmarking challenge of the initiative for the Critical Assessment of Metagenome Interpretation (CAMI). As an application, we show the outputs of AMBER for 11 binning programs on two CAMI benchmark datasets. AMBER is implemented in Python and available under the Apache 2.0 license on GitHub.