VEBA: a modular end-to-end suite for in silico recovery, clustering, and analysis of prokaryotic, microeukaryotic, and viral genomes from metagenomes

Abstract

Background With the advent of metagenomics, the importance of microorganisms and how their interactions are relevant to ecosystem resilience, sustainability, and human health has become evident. Cataloging and preserving biodiversity is paramount not only for the Earth’s natural systems but also for discovering solutions to challenges that we face as a growing civilization. Metagenomics pertains to the in silico study of all microorganisms within an ecological community in situ, however, many software suites recover only prokaryotes and have limited to no support for viruses and eukaryotes. Results In this study, we introduce the Viral Eukaryotic Bacterial Archaeal (VEBA) open-source software suite developed to recover genomes from all domains. To our knowledge, VEBA is the first end-to-end metagenomics suite that can directly recover, quality assess, and classify prokaryotic, eukaryotic, and viral genomes from metagenomes. VEBA implements a novel iterative binning procedure and hybrid sample-specific/multi-sample framework that yields more genomes than any existing methodology alone. VEBA includes a consensus microeukaryotic database containing proteins from existing databases to optimize microeukaryotic gene modeling and taxonomic classification. VEBA also provides a unique clustering-based dereplication strategy allowing for sample-specific genomes and genes to be directly compared across non-overlapping biological samples. Finally, VEBA is the only pipeline that automates the detection of candidate phyla radiation bacteria and implements the appropriate genome quality assessments. VEBA’s capabilities are demonstrated by reanalyzing 3 existing public datasets which recovered a total of 948 MAGs (458 prokaryotic, 8 eukaryotic, and 482 viral) including several uncharacterized organisms and organisms with no public genome representatives. Conclusions The VEBA software suite allows for the in silico recovery of microorganisms from all domains of life by integrating cutting edge algorithms in novel ways. VEBA fully integrates both end-to-end and task-specific metagenomic analysis in a modular architecture that minimizes dependencies and maximizes productivity. The contributions of VEBA to the metagenomics community includes seamless end-to-end metagenomics analysis but also provides users with the flexibility to perform specific analytical tasks. VEBA allows for the automation of several metagenomics steps and shows that new information can be recovered from existing datasets.

Disentangling the Functional Role of Fungi in Cold Seep Sediment

“…For metagenomic and metatranscriptomic data, we used the VEBA v1.0.3 suite of tools ( 95 ) for its robust ability to use ab initio , non-database-reliant methods for binning eukaryotic genomes. All modules were used in default settings unless stated here.…”

Differential network analysis of oral microbiome metatranscriptomes identifies community scale metabolic restructuring in dental caries

“…S1 and Table S1 , respectively. Metagenomic and metatranscriptomic workflows were performed using early versions of the VEBA software suite ( 51 ).…”

Unveiling the Microbial Realm with VEBA 2.0: A modular bioinformatics suite for end-to-end genome-resolved prokaryotic, (micro)eukaryotic, and viral multi-omics from either short- or long-read sequencing

“…The classification protocol has been previously described (4) and the only modification is that it can now handle taxa with incomplete lineages such is the case for many protists and fungi. If genome clusters are provided, then it performs consensus lineage classification.…”

“…However, aside from prophages, many microbiome studies focus primarily on the prokaryome (i.e., bacteria and archaea) and do not assess the eukaryome and virome from a genome-resolved perspective. The motivating factor for developing the Viral Eukaryotic Bacterial Archaeal ( VEBA ) open-source software suite (4) was to extend modular end-to-end (meta-)genomics/transcriptomics methodologies beyond the prokaryome to support the eukaryome and virome. The eukaryome in this context is defined as the fraction of microbes composed of nucleated organisms such as protists and unicellular fungi (adapted from (5)) while the virome consists of all the viruses within an ecosystem, including those integrated into host genomes (6).…”