Publications des scientifiques de l'IRD

Verneau J., Levasseur A., Raoult Didier, La Scola B., Colson P. (2016). MG-Digger : an automated pipeline to search for giant virus-related sequences in metagenomes. Frontiers in Microbiology, 7, p. art. 428. ISSN 1664-302X.

Titre du document
MG-Digger : an automated pipeline to search for giant virus-related sequences in metagenomes
Année de publication
2016
Type de document
Article référencé dans le Web of Science WOS:000373277200001
Auteurs
Verneau J., Levasseur A., Raoult Didier, La Scola B., Colson P.
Source
Frontiers in Microbiology, 2016, 7, p. art. 428 ISSN 1664-302X
The number of metagenomic studies conducted each year is growing dramatically. Storage and analysis of such big data is difficult and time-consuming. Interestingly, analysis shows that environmental and human metagenomes include a significant amount of non-annotated sequences, representing a 'dark matter.' We established a bioinformatics pipeline that automatically detects metagenome reads matching query sequences from a given set and applied this tool to the detection of sequences matching large and giant DNA viral members of the proposed order Megavirales or virophages. A total of 1,045 environmental and human metagenomes (approximate to Terabase) were collected, processed, and stored on our bioinformatics server. In addition, nucleotide and protein sequences from 93 Megavirales representatives, including 19 giant viruses of amoeba, and 5 virophages, were collected. The pipeline was generated by scripts written in Python language and entitled MG-Digger. Metagenomes previously found to contain megavirus-like sequences were tested as controls. MG-Digger was able to annotate 100s of metagenome sequences as best matching those of giant viruses. These sequences were most often found to be similar to phycodnavirus or mimivirus sequences, but included reads related to recently available pandoraviruses, Pithovirus sibericum, and faustoviruses. Compared to other tools, MG-Digger combined stand-alone use on Linux or Windows operating systems through a user-friendly interface, implementation of ready-to-use customized metagenome databases and query sequence databases, adjustable parameters for BLAST searches, and creation of output files containing selected reads with best match identification. Compared to Metavir 2, a reference tool in viral metagenome analysis. MG-Digger detected 8% more true positive Megavirales-related reads in a control metagenome. The present work shows that massive, automated and recurrent analyses of metagenomes are effective in improving knowledge about the presence and prevalence of giant viruses in the environment and the human body.
Plan de classement
Entomologie médicale / Parasitologie / Virologie [052] ; Biotechnologies [084]
Identifiant IRD
PAR00014432
Contact