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The virtualome: a computational framework to evaluate microbiome analyses

Belén Serrano-Antón, Francisco Rodríguez-Ventura, Pere Colomer-Vidal, Riccardo Aiese Cigliano, Clemente F. Arias, Federica Bertocchini
doi: https://doi.org/10.1101/2022.06.16.496511
Belén Serrano-Antón
1CIB, Centro de Investigaciones Biológicas Margarita Salas (CSIC), 28040 Madrid, Spain
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Francisco Rodríguez-Ventura
1CIB, Centro de Investigaciones Biológicas Margarita Salas (CSIC), 28040 Madrid, Spain
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Pere Colomer-Vidal
1CIB, Centro de Investigaciones Biológicas Margarita Salas (CSIC), 28040 Madrid, Spain
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Riccardo Aiese Cigliano
2Sequentia Biotech SL, Barcelona, Spain
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  • For correspondence: raiesecigliano@sequentiabiotech.com tifar@ucm.es federica.bertocchini@csic.es
Clemente F. Arias
1CIB, Centro de Investigaciones Biológicas Margarita Salas (CSIC), 28040 Madrid, Spain
3Grupo Interdisciplinar de Sistemas Complejos de Madrid (GISC), Spain
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  • For correspondence: raiesecigliano@sequentiabiotech.com tifar@ucm.es federica.bertocchini@csic.es
Federica Bertocchini
1CIB, Centro de Investigaciones Biológicas Margarita Salas (CSIC), 28040 Madrid, Spain
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  • For correspondence: raiesecigliano@sequentiabiotech.com tifar@ucm.es federica.bertocchini@csic.es
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ABSTRACT

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 Statement

The authors have declared no competing interest.

Footnotes

  • Group of Nonlinear Physics. University of Santiago de Compostela, 15782 Santiago de Compostela, Spain

  • https://data.mendeley.com/datasets/shm68b8x6t/1

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted June 17, 2022.
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The virtualome: a computational framework to evaluate microbiome analyses
Belén Serrano-Antón, Francisco Rodríguez-Ventura, Pere Colomer-Vidal, Riccardo Aiese Cigliano, Clemente F. Arias, Federica Bertocchini
bioRxiv 2022.06.16.496511; doi: https://doi.org/10.1101/2022.06.16.496511
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The virtualome: a computational framework to evaluate microbiome analyses
Belén Serrano-Antón, Francisco Rodríguez-Ventura, Pere Colomer-Vidal, Riccardo Aiese Cigliano, Clemente F. Arias, Federica Bertocchini
bioRxiv 2022.06.16.496511; doi: https://doi.org/10.1101/2022.06.16.496511

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