The virtual microbiome: A computational framework to evaluate microbiome analyses

PLOS ONE RESEARCH ARTICLE The virtual microbiome: A computational framework to evaluate microbiome analyses Belén Serrano-Antón ID1¤a¤b, Francisco Rodrı́guez-Ventura1, Pere Colomer-Vidal ID1, Riccardo Aiese Cigliano2*, Clemente F. Arias ID1,3*, Federica Bertocchini1* 1 CIB, Centro de Investigaciones Biológicas Margarita Salas (CSIC), Madrid, Spain, 2 Sequentia Biotech SL, Barcelona, Spain, 3 Grupo Interdisciplinar de Sistemas Complejos de Madrid (GISC), Madrid, Spain a1111111111 a1111111111 a1111111111 a1111111111 a1111111111 OPEN ACCESS Citation: Serrano-Antón B, Rodrı́guez-Ventura F, Colomer-Vidal P, Cigliano RA, Arias CF, Bertocchini F (2023) The virtual microbiome: A computational framework to evaluate microbiome analyses. PLoS ONE 18(2): e0280391. https://doi.org/10.1371/ journal.pone.0280391 Editor: Patrizia Falabella, Universita degli Studi della Basilicata, ITALY Received: July 13, 2022 Accepted: December 28, 2022 ¤a Current address: FlowReserve Labs SL, Santiago de Compostela, Spain ¤b Current address: Group of Nonlinear Physics, University of Santiago de Compostela, Santiago de Compostela, Spain * (RAC); (CFA); (FB) 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 virtual bacterial populations that exhibit the ecological structure of real-world microbiomes. Confronting the analyses of virtual microbiomes 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 and optimizing the use of this information. Published: February 8, 2023 Peer Review History: PLOS recognizes the benefits of transparency in the peer review process; therefore, we enable the publication of all of the content of peer review and author responses alongside final, published articles. The editorial history of this article is available here: https://doi.org/10.1371/journal.pone.0280391 Copyright: © 2023 Serrano-Antón et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability Statement: All relevant data are within the paper and its Supporting information files. Introduction The characterization of the microorganisms colonizing a particular ambient is becoming a gateway to the analysis of the physiological niche that the environment represents, revealing its potential functions or eventual pathological conditions. Examples in this direction are represented by the deep interest in the human gut microbiome (the compendium of microorganisms colonizing the human gut), due to the growing concern in the relationships between the microbiome and the immune system, and henceforth in the potential development of disease [1–4]; or the increasing focus on the genomic analyses of water (ocean or river) and soil samples, in search for potentially useful cataloging of the environmental niches we live in [5]. Microbiome studies are receiving increasing attention for their possible implications in the field of bioremediation, embracing issues such as degradation of organic chemicals, conversion of toxic compounds (e.g. pesticides), production of biofuels, or else from various PLOS ONE | https://doi.org/10.1371/journal.pone.0280391 February 8, 2023 1 / 19 PLOS ONE Funding: FB and CFA gratefully acknowledge support by the Roechling foundation. BS was partially supported by MINECO grant MTM201785020-P. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing interests: The authors have declared that no competing interests exist. The virtual microbiome: A computational framework to evaluate microbiome analyses substrates [6–9]. The strong interest in communities of microorganisms crossed fields and extended to the studies of insect guts [10, 11]. A growing body of research focuses on insect microbiomes in the quest for solutions within the bioremediation field [12]. For example, termites and beetles have raised interest due to their capacity to degrade lignin, an ability potentially dependent in some cases on microorganisms colonizing certain portions of their intestine [13–17]. Recently, some coleopteran and lepidopteran species revealed the astonishing capability to degrade fossil fuel-derived plastics, like the sturdy polyethylene and polystyrene [18–21], opening up a new niche within the field of bioremediation by insects. Even if the molecular mechanisms responsible for this extraordinary capacity are still unknown, they are normally ascribed to the microorganisms colonizing the digestive tracts of those insects. This line of research has resulted in an ever-increasing list of microorganisms with the potential to biodegrade plastics, although with still un-concluding outcomes [20–26]. Studies in this field typically monitor the changes induced by alternative treatments in the relative abundance of the species present in the microbiome. For instance, feeding insects a diet of plastic is a standard procedure to identify the microorganisms that thrive in their gut as potential candidates for plastic metabolization [18, 20, 23, 26–28]. Analogously, the microbiome of patients suffering a given clinical condition is often compared to that of healthy control individuals, expecting the shifts in the relative abundance of microbial species to account for the observed effects or to provide effective diagnostic tools [29]. This functional approach to the study of microbiomes relies on several implicit assumptions, whose general validity is far from evident. First, a causal link is presumed between changing conditions and the differential selection (either positive or negative) of particular microbial species. In the case of plastic fed-insects, for instance, possible metabolic changes induced by a diet of plastic in the host insect are normally neglected, implying that the microorganisms colonizing the digestive tracts are considered responsible for any metabolic activity the animal embarks on. Leaving aside its biological plausibility, this perspective takes for granted other assumptions that have to do with th (...truncated)