Dataset Information

Deciphering the Human Virome with Single-Virus Genomics and Metagenomics.

ABSTRACT: Single-cell genomics has unveiled the metabolic potential of dominant microbes inhabiting different environments, including the human body. The lack of genomic information for predominant microbes of the human body, such as bacteriophages, hinders our ability to answer fundamental questions about our viral communities. Here, we applied single-virus genomics (SVGs) to natural human salivary samples in combination with viral metagenomics to gain some insights into the viral community structure of the oral cavity. Saliva samples were processed for viral metagenomics (n = 15) and SVGs (n = 3). A total of 1328 uncultured single viruses were sorted by fluorescence-activated virus sorting followed by whole genome amplification. Sequencing of 24 viral single amplified genomes (vSAGs) showed that half of the vSAGs contained viral hallmark genes. Among those bona fide viruses, the uncultured single virus 92-C13 putatively infecting oral Streptococcus-like species was within the top ?10 most abundant viruses in the oral virome. Viral gene network and viral metagenomics analyses of 439 oral viruses from cultures, metagenomics, and SVGs revealed that salivary viruses were tentatively structured into ?200 major viral clusters, corresponding to approximately genus-level groupings. Data showed that none of the publicly available viral isolates, excepting an Actinomyces phage, were significantly abundant in the oral viromes. In addition, none of the obtained viral contigs and vSAGs from this study were present in all viromes. Overall, the data demonstrates that most viral isolates are not naturally abundant in saliva, and furthermore, the predominant viruses in the oral cavity are yet uncharacterized. Results suggest a variable, complex, and interpersonal viral profile. Finally, we demonstrated the power of SVGs in combination with viral metagenomics to unveil the genetic information of the uncultured viruses of the human virome.

SUBMITTER: de la Cruz Pena MJ

PROVIDER: S-EPMC5869506 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Deciphering the Human Virome with Single-Virus Genomics and Metagenomics.

de la Cruz Peña Maria José MJ Martinez-Hernandez Francisco F Garcia-Heredia Inmaculada I Lluesma Gomez Mónica M Fornas Òscar Ò Martinez-Garcia Manuel M

Viruses 20180306 3

Single-cell genomics has unveiled the metabolic potential of dominant microbes inhabiting different environments, including the human body. The lack of genomic information for predominant microbes of the human body, such as bacteriophages, hinders our ability to answer fundamental questions about our viral communities. Here, we applied single-virus genomics (SVGs) to natural human salivary samples in combination with viral metagenomics to gain some insights into the viral community structure of ...[more]

PMID: 29509721

Similar Datasets

Project description:BackgroundObtaining high-quality (HQ) reference genomes from microbial communities is crucial for understanding the phylogeny and function of uncultured microbes in complex microbial ecosystems. Despite improvements in bioinformatic approaches to generate curated metagenome-assembled genomes (MAGs), existing metagenome binners obtain population consensus genomes but they are nowhere comparable to genomes sequenced from isolates in terms of strain level resolution. Here, we present a framework for the integration of single-cell genomics and metagenomics, referred to as single-cell (sc) metagenomics, to reconstruct strain-resolved genomes from microbial communities at once.ResultsOur sc-metagenomics integration framework, termed SMAGLinker, uses single-cell amplified genomes (SAGs) generated using microfluidic technology as binning guides and integrates them with metagenome-assembled genomes (MAGs) to recover improved draft genomes. We compared sc-metagenomics with the metagenomics-alone approach using conventional metagenome binners. The sc-metagenomics approach showed precise contig binning and higher recovery rates (>97%) of rRNA and plasmids than conventional metagenomics in genome reconstruction from the cell mock community. In human microbiota samples, sc-metagenomics recovered the largest number of genomes with a total of 103 gut microbial genomes (21 HQ, with 65 showing >90% completeness) and 45 skin microbial genomes (10 HQ, with 40 showing >90% completeness), respectively. Conventional metagenomics recovered one Staphylococcus hominis genome, whereas sc-metagenomics recovered two S. hominis genomes from identical skin microbiota sample. Single-cell sequencing revealed that these S. hominis genomes were derived from two distinct strains harboring specifically different plasmids. We found that all conventional S. hominis MAGs had a substantial lack or excess of genome sequences and contamination from other Staphylococcus species (S. epidermidis).ConclusionsSMAGLinker enabled us to obtain strain-resolved genomes in the mock community and human microbiota samples by assigning metagenomic sequences correctly and covering both highly conserved genes such as rRNA genes and unique extrachromosomal elements, including plasmids. SMAGLinker will provide HQ genomes that are difficult to obtain using metagenomics alone and will facilitate the understanding of microbial ecosystems by elucidating detailed metabolic pathways and horizontal gene transfer networks. SMAGLinker is available at https://github.com/kojiari/smaglinker . Video abstract.

Project description:Chicken gut microbiota has paramount roles in host performance, health and immunity. Understanding the topological difference in gut microbial community composition is crucial to provide knowledge on the functions of each members of microbiota to the physiological maintenance of the host. The gut microbiota profiling of the chicken was commonly performed previously using culture-dependent and early culture-independent methods which had limited coverage and accuracy. Advances in technology based on next-generation sequencing (NGS), offers unparalleled coverage and depth in determining microbial gut dynamics. Thus, the aim of this study was to investigate the ileal and caecal microbiota development as chicken aged, which is important for future effective gut modulation.Ileal and caecal contents of broiler chicken were extracted from 7, 14, 21 and 42-day old chicken. Genomic DNA was then extracted and amplified based on V3 hyper-variable region of 16S rRNA. Bioinformatics, ecological and statistical analyses such as Principal Coordinate Analysis (PCoA) was performed in mothur software and plotted using PRIMER 6. Additional analyses for predicted metagenomes were performed through PICRUSt and STAMP software package based on Greengenes databases.A distinctive difference in bacterial communities was observed between ilea and caeca as the chicken aged (P < 0.001). The microbial communities in the caeca were more diverse in comparison to the ilea communities. The potentially pathogenic bacteria such as Clostridium were elevated as the chicken aged and the population of beneficial microbe such as Lactobacillus was low at all intervals. On the other hand, based on predicted metagenomes analysed, clear distinction in functions and roles of gut microbiota such as gene pathways related to nutrient absorption (e.g. sugar and amino acid metabolism), and bacterial proliferation and colonization (e.g. bacterial motility proteins, two-component system and bacterial secretion system) were observed between ilea and caeca, respectively (P < 0.05).The caeca microbial communities were more diverse in comparison to ilea. The main functional differences between the two sites were found to be related to nutrient absorption and bacterial colonization. Based on the composition of the microbial community, future gut modulation with beneficial bacteria such as probiotics may benefit the host.

Project description:Accurate identification of the transmitted virus and sequences evolving from it could be instrumental in elucidating the transmission of human immunodeficiency virus type 1 (HIV-1) and in developing vaccines, drugs, or microbicides to prevent infection. Here we describe an experimental approach to analyze HIV-1 env genes as intact genetic units amplified from plasma virion RNA by single-genome amplification (SGA), followed by direct sequencing of uncloned DNA amplicons. We show that this strategy precludes in vitro artifacts caused by Taq-induced nucleotide substitutions and template switching, provides an accurate representation of the env quasispecies in vivo, and has an overall error rate (including nucleotide misincorporation, insertion, and deletion) of less than 8 x 10(-5). Applying this method to the analysis of virus in plasma from 12 Zambian subjects from whom samples were obtained within 3 months of seroconversion, we show that transmitted or early founder viruses can be identified and that molecular pathways and rates of early env diversification can be defined. Specifically, we show that 8 of the 12 subjects were each infected by a single virus, while 4 others acquired more than one virus; that the rate of virus evolution in one subject during an 80-day period spanning seroconversion was 1.7 x 10(-5) substitutions per site per day; and that evidence of strong immunologic selection can be seen in Env and overlapping Rev sequences based on nonrandom accumulation of nonsynonymous mutations. We also compared the results of the SGA approach with those of more-conventional bulk PCR amplification methods performed on the same patient samples and found that the latter is associated with excessive rates of Taq-induced recombination, nucleotide misincorporation, template resampling, and cloning bias. These findings indicate that HIV-1 env genes, other viral genes, and even full-length viral genomes responsible for productive clinical infection can be identified by SGA analysis of plasma virus sampled at intervals typical in large-scale vaccine trials and that pathways of viral diversification and immune escape can be determined accurately.

Dataset Information

Deciphering the Human Virome with Single-Virus Genomics and Metagenomics.

Publications

Deciphering the Human Virome with Single-Virus Genomics and Metagenomics.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets