Computational tools for viral metagenomics and their application in clinical research

Fancello, Laura; Raoult, Didier; Desnues, Christelle

doi:10.1016/j.virol.2012.09.025

Cited by 61 publications

(63 citation statements)

References 150 publications

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“…We opted to predict the abundance by aligning the predicted ORFs and rRNA against GBT because of it"s ability to obtain insights into complex gene structure, which would not be possible to obtain from short read data. Furthermore, performing taxonomic classification using raw sequence reads has been shown to result in lower statistical confidence (Huson et al, 2007;Fancello et al, 2012). We performed binning of the predicted genes in order to get the taxonomic assignment.…”

Section: Feature Prediction Annotation Of Function and Taxonomic Assmentioning

confidence: 99%

Metagenomics as a preliminary screen for antimicrobial bioprospecting

Al-Amoudi

Razali

Essack

et al. 2016

Gene

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Since the composition of soil directs the diversity of the contained microbiome and its potential to produce bioactive compounds, many studies has been focused on sediment types with unique features characteristic of extreme environments. However, not much is known about the potential of microbiomes that inhabit the highly saline and hot Red Sea lagoons. This case study explores mangrove mud and the microbial mat of sediments collected from the Rabigh harbor lagoon and Al Kharrar lagoon for antimicrobial bioprospecting. Rabigh harbor lagoon appears the better location, and the best sediment type for this purpose is mangrove mud. On the other hand, Al Kharrar lagoon displayed increased anaerobic hydrocarbon degradation and an abundance of bacterial DNA associated with antibiotic resistance. Moreover, our findings show an identical shift in phyla associated with historic hydrocarbon contamination exposure reported in previous studies (that is, enrichment of Gamma- and Delta-proteobacteria), but we also report that bacterial DNA sequences associated with antibiotic synthesis enzymes are derived from Gamma-, Delta- and Alpha-proteobacteria. This suggests that selection pressure associated with hydrocarbon contamination tend to enrich the bacterial classes DNA associated with antibiotic synthesis enzymes. Although Actinobacteria tends to be the common target for research when it comes to antimicrobial bioprospecting, our study suggests that Firmicutes (Bacilli and Clostridia), Bacteroidetes, Cyanobacteria, and Proteobacteria should be antimicrobial bioprospecting targets as well. To the best of our knowledge, this is the first metagenomic study that analyzed the microbiomes in Red Sea lagoons for antimicrobial bioprospecting.

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Section: Feature Prediction Annotation Of Function and Taxonomic Assmentioning

confidence: 99%

Metagenomics as a preliminary screen for antimicrobial bioprospecting

Al-Amoudi

Razali

Essack

et al. 2016

Gene

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“…Even though homology-based searches are the most important applications for assigning taxonomy and function to sequence data, alternative approaches based on databaseindependent analysis have been developed [48][49][50] . Fancello et al 51 provide a complete review of computational tools and algorithms used in viral metagenomics.…”

Section: Viral Metagenomicsmentioning

confidence: 99%

Purifying the Impure: Sequencing Metagenomes and Metatranscriptomes from Complex Animal-associated Samples

Lim

Haynes

Furlan

et al. 2014

JoVE

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The accessibility of high-throughput sequencing has revolutionized many fields of biology. In order to better understand host-associated viral and microbial communities, a comprehensive workflow for DNA and RNA extraction was developed. The workflow concurrently generates viral and microbial metagenomes, as well as metatranscriptomes, from a single sample for next-generation sequencing. The coupling of these approaches provides an overview of both the taxonomical characteristics and the community encoded functions. The presented methods use Cystic Fibrosis (CF) sputum, a problematic sample type, because it is exceptionally viscous and contains high amount of mucins, free neutrophil DNA, and other unknown contaminants. The protocols described here target these problems and successfully recover viral and microbial DNA with minimal human DNA contamination. To complement the metagenomics studies, a metatranscriptomics protocol was optimized to recover both microbial and host mRNA that contains relatively few ribosomal RNA (rRNA) sequences. An overview of the data characteristics is presented to serve as a reference for assessing the success of the methods. Additional CF sputum samples were also collected to (i) evaluate the consistency of the microbiome profiles across seven consecutive days within a single patient, and (ii) compare the consistency of metagenomic approach to a 16S ribosomal RNA gene-based sequencing. The results showed that daily fluctuation of microbial profiles without antibiotic perturbation was minimal and the taxonomy profiles of the common CF-associated bacteria were highly similar between the 16S rDNA libraries and metagenomes generated from the hypotonic lysis (HL)-derived DNA. However, the differences between 16S rDNA taxonomical profiles generated from total DNA and HL-derived DNA suggest that hypotonic lysis and the washing steps benefit in not only removing the human-derived DNA, but also microbial-derived extracellular DNA that may misrepresent the actual microbial profiles.

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“…More than 40 viral metagenomics studies have been published in the past decade ranging from marine, freshwater, arctic, soil, human feces, gut and oral cavity environments (Rosario and Breitbart, 2011;Fancello et al, 2012;Mokili et al, 2012). Each study reveals not only new insights into the interplay between viruses and their hosts, but expands our understanding of the 'unknown virosphere.'…”

Section: Introductionmentioning

confidence: 99%

“…A variety of bioinformatic tools have been developed to analyze the structure and/or diversity of viral assemblages from metagenomics data sets (reviewed extensively in Fancello et al, 2012;Mokili et al, 2012). Although these tools provide taxonomic classification, functional assignment and estimates of virus community structure and diversity, they are frequently dependent on sequence comparisons against databases of known sequences or function, and do not account well for the large variation in sequences and functions typically associated with viral families.…”

Section: Introductionmentioning

confidence: 99%

Viral assemblage composition in Yellowstone acidic hot springs assessed by network analysis

et al. 2015

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Understanding of viral assemblage structure in natural environments remains a daunting task. Total viral assemblage sequencing (for example, viral metagenomics) provides a tractable approach. However, even with the availability of next-generation sequencing technology it is usually only possible to obtain a fragmented view of viral assemblages in natural ecosystems. In this study, we applied a network-based approach in combination with viral metagenomics to investigate viral assemblage structure in the high temperature, acidic hot springs of Yellowstone National Park, USA. Our results show that this approach can identify distinct viral groups and provide insights into the viral assemblage structure. We identified 110 viral groups in the hot springs environment, with each viral group likely representing a viral family at the sub-family taxonomic level. Most of these viral groups are previously unknown DNA viruses likely infecting archaeal hosts. Overall, this study demonstrates the utility of combining viral assemblage sequencing approaches with network analysis to gain insights into viral assemblage structure in natural ecosystems.

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Computational tools for viral metagenomics and their application in clinical research

Cited by 61 publications

References 150 publications

Metagenomics as a preliminary screen for antimicrobial bioprospecting

Metagenomics as a preliminary screen for antimicrobial bioprospecting

Purifying the Impure: Sequencing Metagenomes and Metatranscriptomes from Complex Animal-associated Samples

Viral assemblage composition in Yellowstone acidic hot springs assessed by network analysis

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