RT Journal Article
SR Electronic
T1 The virtualome: a computational framework to evaluate microbiome analyses
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2022.06.16.496511
DO 10.1101/2022.06.16.496511
A1 Serrano-Antón, Belén
A1 Rodríguez-Ventura, Francisco
A1 Colomer-Vidal, Pere
A1 Cigliano, Riccardo Aiese
A1 Arias, Clemente F.
A1 Bertocchini, Federica
YR 2022
UL http://biorxiv.org/content/early/2022/06/17/2022.06.16.496511.abstract
AB Microbiomes have been the focus of a substantial research effort in the last decades. The composition of microbial populations is normally determined by comparing DNA sequences sampled from those populations with the sequences stored in genomic databases. Therefore, the amount of information available in databanks should be expected to constrain the accuracy of microbiome analyses. Albeit normally ignored in microbiome studies, this constraint could severely compromise the reliability of microbiome data. To test this hypothesis, we generated virtualomes, virtual bacterial populations that exhibit the ecological structure of real-world microbiomes. Confronting the analyses of virtualomes with their original composition revealed critical issues in the current approach to characterizing microbiomes, issues that were empirically confirmed by analyzing the microbiome of Galleria mellonella larvae. To reduce the uncertainty of microbiome data, the effort in the field must be channeled towards significantly increasing the amount of available genomic information.Competing Interest StatementThe authors have declared no competing interest.