Dataset Information

Metagenomic analysis of the viral communities in fermented foods.

ABSTRACT: Viruses are recognized as the most abundant biological components on Earth, and they regulate the structure of microbial communities in many environments. In soil and marine environments, microorganism-infecting phages are the most common type of virus. Although several types of bacteriophage have been isolated from fermented foods, little is known about the overall viral assemblages (viromes) of these environments. In this study, metagenomic analyses were performed on the uncultivated viral communities from three fermented foods, fermented shrimp, kimchi, and sauerkraut. Using a high-throughput pyrosequencing technique, a total of 81,831, 70,591 and 69,464 viral sequences were obtained from fermented shrimp, kimchi and sauerkraut, respectively. Moreover, 37 to 50% of these sequences showed no significant hit against sequences in public databases. There were some discrepancies between the prediction of bacteriophages hosts via homology comparison and bacterial distribution, as determined from 16S rRNA gene sequencing. These discrepancies likely reflect the fact that the viral genomes of fermented foods are poorly represented in public databases. Double-stranded DNA viral communities were amplified from fermented foods by using a linker-amplified shotgun library. These communities were dominated by bacteriophages belonging to the viral order Caudovirales (i.e., Myoviridae, Podoviridae, and Siphoviridae). This study indicates that fermented foods contain less complex viral communities than many other environmental habitats, such as seawater, human feces, marine sediment, and soil.

SUBMITTER: Park EJ

PROVIDER: S-EPMC3067239 | biostudies-literature | 2011 Feb

REPOSITORIES: biostudies-literature

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Metagenomic analysis of the viral communities in fermented foods.

Park Eun-Jin EJ Kim Kyoung-Ho KH Abell Guy C J GC Kim Min-Soo MS Roh Seong Woon SW Bae Jin-Woo JW

Applied and environmental microbiology 20101223 4

Viruses are recognized as the most abundant biological components on Earth, and they regulate the structure of microbial communities in many environments. In soil and marine environments, microorganism-infecting phages are the most common type of virus. Although several types of bacteriophage have been isolated from fermented foods, little is known about the overall viral assemblages (viromes) of these environments. In this study, metagenomic analyses were performed on the uncultivated viral com ...[more]

PMID: 21183634

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Project description:BACKGROUND: The main limitations in the analysis of viral metagenomes are perhaps the high genetic variability and the lack of information in extant databases. To address these issues, several bioinformatic tools have been specifically designed or adapted for metagenomics by improving read assembly and creating more sensitive methods for homology detection. This study compares the performance of different available assemblers and taxonomic annotation software using simulated viral-metagenomic data. RESULTS: We simulated two 454 viral metagenomes using genomes from NCBI's RefSeq database based on the list of actual viruses found in previously published metagenomes. Three different assembly strategies, spanning six assemblers, were tested for performance: overlap-layout-consensus algorithms Newbler, Celera and Minimo; de Bruijn graphs algorithms Velvet and MetaVelvet; and read probabilistic model Genovo. The performance of the assemblies was measured by the length of resulting contigs (using N50), the percentage of reads assembled and the overall accuracy when comparing against corresponding reference genomes. Additionally, the number of chimeras per contig and the lowest common ancestor were estimated in order to assess the effect of assembling on taxonomic and functional annotation. The functional classification of the reads was evaluated by counting the reads that correctly matched the functional data previously reported for the original genomes and calculating the number of over-represented functional categories in chimeric contigs. The sensitivity and specificity of tBLASTx, PhymmBL and the k-mer frequencies were measured by accurate predictions when comparing simulated reads against the NCBI Virus genomes RefSeq database. CONCLUSIONS: Assembling improves functional annotation by increasing accurate assignations and decreasing ambiguous hits between viruses and bacteria. However, the success is limited by the chimeric contigs occurring at all taxonomic levels. The assembler and its parameters should be selected based on the focus of each study. Minimo's non-chimeric contigs and Genovo's long contigs excelled in taxonomy assignation and functional annotation, respectively.tBLASTx stood out as the best approach for taxonomic annotation for virus identification. PhymmBL proved useful in datasets in which no related sequences are present as it uses genomic features that may help identify distant taxa. The k-frequencies underperformed in all viral datasets.

Dataset Information

Metagenomic analysis of the viral communities in fermented foods.

Publications

Metagenomic analysis of the viral communities in fermented foods.

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