Dataset Information

Assessing viral taxonomic composition in benthic marine ecosystems: reliability and efficiency of different bioinformatic tools for viral metagenomic analyses.

ABSTRACT: In benthic deep-sea ecosystems, which represent the largest biome on Earth, viruses have a recognised key ecological role, but their diversity is still largely unknown. Identifying the taxonomic composition of viruses is crucial for understanding virus-host interactions, their role in food web functioning and evolutionary processes. Here, we compared the performance of various bioinformatic tools (BLAST, MG-RAST, NBC, VMGAP, MetaVir, VIROME) for analysing the viral taxonomic composition in simulated viromes and viral metagenomes from different benthic deep-sea ecosystems. The analyses of simulated viromes indicate that all the BLAST tools, followed by MetaVir and VMGAP, are more reliable in the affiliation of viral sequences and strains. When analysing the environmental viromes, tBLASTx, MetaVir, VMGAP and VIROME showed a similar efficiency of sequence annotation; however, MetaVir and tBLASTx identified a higher number of viral strains. These latter tools also identified a wider range of viral families than the others, providing a wider view of viral taxonomic diversity in benthic deep-sea ecosystems. Our findings highlight strengths and weaknesses of available bioinformatic tools for investigating the taxonomic diversity of viruses in benthic ecosystems in order to improve our comprehension of viral diversity in the oceans and its relationships with host diversity and ecosystem functioning.

SUBMITTER: Tangherlini M

PROVIDER: S-EPMC4916513 | biostudies-literature | 2016 Jun

REPOSITORIES: biostudies-literature

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Assessing viral taxonomic composition in benthic marine ecosystems: reliability and efficiency of different bioinformatic tools for viral metagenomic analyses.

Tangherlini M M Dell'Anno A A Zeigler Allen L L Riccioni G G Corinaldesi C C

Scientific reports 20160622

In benthic deep-sea ecosystems, which represent the largest biome on Earth, viruses have a recognised key ecological role, but their diversity is still largely unknown. Identifying the taxonomic composition of viruses is crucial for understanding virus-host interactions, their role in food web functioning and evolutionary processes. Here, we compared the performance of various bioinformatic tools (BLAST, MG-RAST, NBC, VMGAP, MetaVir, VIROME) for analysing the viral taxonomic composition in simul ...[more]

PMID: 27329207

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Project description:Approaches for computing small molecule binding free energies based on molecular simulations are now regularly being employed by academic and industry practitioners to study receptor-ligand systems and prioritize the synthesis of small molecules for ligand design. Given the variety of methods and implementations available, it is natural to ask how the convergence rates and final predictions of these methods compare. In this study, we describe the concept and results for the SAMPL6 SAMPLing challenge, the first challenge from the SAMPL series focusing on the assessment of convergence properties and reproducibility of binding free energy methodologies. We provided parameter files, partial charges, and multiple initial geometries for two octa-acid (OA) and one cucurbit[8]uril (CB8) host-guest systems. Participants submitted binding free energy predictions as a function of the number of force and energy evaluations for seven different alchemical and physical-pathway (i.e., potential of mean force and weighted ensemble of trajectories) methodologies implemented with the GROMACS, AMBER, NAMD, or OpenMM simulation engines. To rank the methods, we developed an efficiency statistic based on bias and variance of the free energy estimates. For the two small OA binders, the free energy estimates computed with alchemical and potential of mean force approaches show relatively similar variance and bias as a function of the number of energy/force evaluations, with the attach-pull-release (APR), GROMACS expanded ensemble, and NAMD double decoupling submissions obtaining the greatest efficiency. The differences between the methods increase when analyzing the CB8-quinine system, where both the guest size and correlation times for system dynamics are greater. For this system, nonequilibrium switching (GROMACS/NS-DS/SB) obtained the overall highest efficiency. Surprisingly, the results suggest that specifying force field parameters and partial charges is insufficient to generally ensure reproducibility, and we observe differences between seemingly converged predictions ranging approximately from 0.3 to 1.0 kcal/mol, even with almost identical simulations parameters and system setup (e.g., Lennard-Jones cutoff, ionic composition). Further work will be required to completely identify the exact source of these discrepancies. Among the conclusions emerging from the data, we found that Hamiltonian replica exchange-while displaying very small variance-can be affected by a slowly-decaying bias that depends on the initial population of the replicas, that bidirectional estimators are significantly more efficient than unidirectional estimators for nonequilibrium free energy calculations for systems considered, and that the Berendsen barostat introduces non-negligible artifacts in expanded ensemble simulations.

Dataset Information

Assessing viral taxonomic composition in benthic marine ecosystems: reliability and efficiency of different bioinformatic tools for viral metagenomic analyses.

Publications

Assessing viral taxonomic composition in benthic marine ecosystems: reliability and efficiency of different bioinformatic tools for viral metagenomic analyses.

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