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Cited by 2,275Microbial Community Ecology and PhysiologyGut microbiota and healthPlant-Microbe Interactions and Immunity

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Microbiome definition re-visited: old concepts and new challenges

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Berg, Gabriele, Rybakova, Daria, Fischer, Doreen, Cernava, Tomislav, Vergès, Marie-Christine Champomier, Charles, Trevor, Chen, Xiaoyulong, Cocolin, Luca, Eversole, Kellye, Corral, Gema Herrero, Kazou, Maria, Kinkel, Linda, Lange, Lene, Lima, Nelson, Loy, Alexander, Macklin, James A., Maguin, Emmanuelle, Mauchline, Tim, McClure, Ryan, Mitter, Birgit, Ryan, Matthew, Sarand, Inga, Smidt, Hauke, Schelkle, Bettina, Roume, Hugo, Kiran, G. Seghal, Selvin, Joseph, Souza, Rafael Soares Correa de, van Overbeek, Leo, Singh, Brajesh K., Wagner, Michael, Walsh, Aaron, Sessitsch, Angela, Schloter, Michael·2020·Microbiome
DOI 10.1186/s40168-020-00875-0PMC PMC7329523
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Abstract

The field of microbiome research has evolved rapidly over the past few decades and has become a topic of great scientific and public interest. As a result of this rapid growth in interest covering different fields, we are lacking a clear commonly agreed definition of the term “microbiome.” Moreover, a consensus on best practices in microbiome research is missing. Recently, a panel of international experts discussed the current gaps in the frame of the European-funded MicrobiomeSupport project. The meeting brought together about 40 leaders from diverse microbiome areas, while more than a hundred experts from all over the world took part in an online survey accompanying the workshop. This article excerpts the outcomes of the workshop and the corresponding online survey embedded in a short historical introduction and future outlook. We propose a definition of microbiome based on the compact, clear, and comprehensive description of the term provided by Whipps et al. in 1988, amended with a set of novel recommendations considering the latest technological developments and research findings. We clearly separate the terms microbiome and microbiota and provide a comprehensive discussion considering the composition of microbiota, the heterogeneity and dynamics of microbiomes in time and space, the stability and resilience of microbial networks, the definition of core microbiomes, and functionally relevant keystone species as well as co-evolutionary principles of microbe-host and inter-species interactions within the microbiome. These broad definitions together with the suggested unifying concepts will help to improve standardization of microbiome studies in the future, and could be the starting point for an integrated assessment of data resulting in a more rapid transfer of knowledge from basic science into practice. Furthermore, microbiome standards are important for solving new challenges associated with anthropogenic-driven changes in the field of planetary health, for which the understanding of microbiomes might play a key role.

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Fig. 1 The history of microbiome research from seventieth century until our days, highlighting the shift of the paradigm from microbes as unsocial organisms causing diseases to the holistic view of microorganisms being the center of the One Health Concept: positively interconnecting all areas of our lives. The list of the literature used for this figure can be found in the Supplemental File 1
Fig. 1 The history of microbiome research from seventieth century until our days, highlighting the shift of the paradigm from microbes as unsocial organisms causing diseases to the holistic view of microorganisms being the center of the One Health Concept: positively interconnecting all areas of our lives. The list of the literature used for this figure can be found in the Supplemental File 1CC BY · PubMed Central
Fig. 2 A schematic highlighting the composition of the term microbiome containing both the microbiota (community of microorganisms) and their “theatre of activity” (structural elements, metabolites/signal molecules, and the surrounding environmental conditions)
Fig. 2 A schematic highlighting the composition of the term microbiome containing both the microbiota (community of microorganisms) and their “theatre of activity” (structural elements, metabolites/signal molecules, and the surrounding environmental conditions)CC BY · PubMed Central
Fig. 3 Microbial interactions visualized through microbial co-occurrence networks. a Microbial interactions are influenced by environmental factors and are separated into positive, neutral, and negative interactions types. b Microbial co-occurrence and co-exclusion networks help visualizing microbial interactions. In such networks, nodes usually represent taxa of microorganisms, and edges represent statistically significant associations between nodes. Green edges usually stay for positive interactions, while red edges visualize negative interactions between the microorganisms. c Testing of the hypotheses resulted from the network analyses in relevant model systems is required for a comprehensive study of microbial interactions
Fig. 3 Microbial interactions visualized through microbial co-occurrence networks. a Microbial interactions are influenced by environmental factors and are separated into positive, neutral, and negative interactions types. b Microbial co-occurrence and co-exclusion networks help visualizing microbial interactions. In such networks, nodes usually represent taxa of microorganisms, and edges represent statistically significant associations between nodes. Green edges usually stay for positive interactions, while red edges visualize negative interactions between the microorganisms. c Testing of the hypotheses resulted from the network analyses in relevant model systems is required for a comprehensive study of microbial interactionsCC BY · PubMed Central
Fig 4 Microbiome dynamics in time and scale. a Temporal dynamics of the microbiome is characterized by considering both the transient state of microbiome as response to environmental perturbations, such as, for example, seasonal or circadian rhythms, and the resident state that contains rather constant core microbiota. b Spatial dynamics of the microbiome is characterized by variations in the microbial composition between similar habitats separated in space. The separation may be between the organisms (e.g., same plants species grown in two different locations), between the parts of one organism (e.g., plant roots and the whole plant), or even within an organ (e.g., comparing microbiomes of various intestinal segments)
Fig 4 Microbiome dynamics in time and scale. a Temporal dynamics of the microbiome is characterized by considering both the transient state of microbiome as response to environmental perturbations, such as, for example, seasonal or circadian rhythms, and the resident state that contains rather constant core microbiota. b Spatial dynamics of the microbiome is characterized by variations in the microbial composition between similar habitats separated in space. The separation may be between the organisms (e.g., same plants species grown in two different locations), between the parts of one organism (e.g., plant roots and the whole plant), or even within an organ (e.g., comparing microbiomes of various intestinal segments)CC BY · PubMed Central
Fig. 5 Methods for assessing microbial functioning. Complex microbiome studies cover various areas, starting from the level of complete microbial cells (microscopy, culturomics), followed by the DNA (single cell genomics, metabarcoding, metagenomics), RNA (metatranscriptomics), protein (metaproteomics), and metabolites (metabolomics). In that order, the focus of the studies shifts from the microbial potential (learning about available microbiota in the given habitat) over the metabolic potential (deciphering available genetic material) towards microbial functioning (e.g., the discovery of the active metabolic pathways)
Fig. 5 Methods for assessing microbial functioning. Complex microbiome studies cover various areas, starting from the level of complete microbial cells (microscopy, culturomics), followed by the DNA (single cell genomics, metabarcoding, metagenomics), RNA (metatranscriptomics), protein (metaproteomics), and metabolites (metabolomics). In that order, the focus of the studies shifts from the microbial potential (learning about available microbiota in the given habitat) over the metabolic potential (deciphering available genetic material) towards microbial functioning (e.g., the discovery of the active metabolic pathways)CC BY · PubMed Central
Fig. 6 A shift in the understanding of the microbial-host coevolution from the “separation” theories to the holistic approach. The hosts and their associated microbiota are assumed to have coevolved with each other, whereby different approaches are considered to describe the coevolution theory. According to the “separation” approach (upper part of the figure), the microorganisms can be divided into pathogens, neutral, and symbionts, depending on their interaction with their host. The coevolution between host and its associated microbiota may be accordingly described as antagonistic (based on negative interactions) or mutualistic (based on positive interactions). The recent emerge in publications about opportunistic pathogens and pathobionts gave a shift towards holistic approach in the coevolutions theory (lower part of the figure). The holistic approach sees the host and its associated microbiota as one unit (so-called holobiont), that coevolves as one entity. According to the holistic approach, holobiont’s disease state is linked to dysbiosis, low diversity of the associated microbiota, and their variability: a so-called “pathobiome” state. The healthy state, on the other hand, is accompanied with eubiosis, high diversity, and uniformity of the respective microbiota. The dynamic flow of microorganisms from one host to another and to the environment, described by the One Health concept, underpins the holistic approach in the coevolution
Fig. 6 A shift in the understanding of the microbial-host coevolution from the “separation” theories to the holistic approach. The hosts and their associated microbiota are assumed to have coevolved with each other, whereby different approaches are considered to describe the coevolution theory. According to the “separation” approach (upper part of the figure), the microorganisms can be divided into pathogens, neutral, and symbionts, depending on their interaction with their host. The coevolution between host and its associated microbiota may be accordingly described as antagonistic (based on negative interactions) or mutualistic (based on positive interactions). The recent emerge in publications about opportunistic pathogens and pathobionts gave a shift towards holistic approach in the coevolutions theory (lower part of the figure). The holistic approach sees the host and its associated microbiota as one unit (so-called holobiont), that coevolves as one entity. According to the holistic approach, holobiont’s disease state is linked to dysbiosis, low diversity of the associated microbiota, and their variability: a so-called “pathobiome” state. The healthy state, on the other hand, is accompanied with eubiosis, high diversity, and uniformity of the respective microbiota. The dynamic flow of microorganisms from one host to another and to the environment, described by the One Health concept, underpins the holistic approach in the coevolutionCC BY · PubMed Central
Fig. 7 The schematic showing the cross-field microbiome-application trend that goes from broad-band applications direction microbiome-based precision treatment in all areas of microbiome research, such as agriculture, human and animal medicine, and bioeconomy, while the interconnection between these areas by the means of the cycling of subsets of microbial communities is an underlying concept behind the One Health approach. The synergies between the microbiome applications in the areas of medicine (left) and agriculture (right) are shown with the horizontal arrows following the flow (vertical arrows) from the broadband applications (upper part) to the precision treatments (lower part)
Fig. 7 The schematic showing the cross-field microbiome-application trend that goes from broad-band applications direction microbiome-based precision treatment in all areas of microbiome research, such as agriculture, human and animal medicine, and bioeconomy, while the interconnection between these areas by the means of the cycling of subsets of microbial communities is an underlying concept behind the One Health approach. The synergies between the microbiome applications in the areas of medicine (left) and agriculture (right) are shown with the horizontal arrows following the flow (vertical arrows) from the broadband applications (upper part) to the precision treatments (lower part)CC BY · PubMed Central

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Research works printed but not linked: 5

  1. Hiltner L. Die Keimungsverhältnisse der Leguminosensamen und ihre Beeinflussung durch Organismenwirkung. In: Parey P, Springer J, editors. Arb Biol Abt Land u Forstw K Gsndhtsamt (3). Berlin, Germany; 1902. p. 1-545.
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Metadata

Authors
Berg, G., Rybakova, D., Fischer, D., Cernava, T., Vergès, M.-C. C., Charles, T., Chen, X., Cocolin, L., Eversole, K., Corral, G. H., Kazou, M., Kinkel, L., Lange, L., Lima, N., Loy, A., Macklin, J. A., Maguin, E., Mauchline, T., McClure, R., Mitter, B., Ryan, M., Sarand, I., Smidt, H., Schelkle, B., Roume, H., Kiran, G. S., Selvin, J., Souza, R. S. C. D., van Overbeek, L., Singh, B. K., Wagner, M., Walsh, A., Sessitsch, A., & Schloter, M.
Affiliations
  • Graz University of Technology (AT)
  • Helmholtz Munich (DE)
  • University of Waterloo (CA)
  • Guizhou University (CN)
  • European Food Information Council (BE)
  • Département Microbiologie et Chaîne Alimentaire (FR)
  • University of Minnesota (US)
  • University of Vienna (AT)
  • Agriculture and Agri-Food Canada (CA)
  • AgroParisTech (FR)
  • Rothamsted Research (GB)
  • Pacific Northwest National Laboratory (US)
  • AIT Austrian Institute of Technology GmbH (AT)
  • CAB International (GB)
  • Tallinn University of Technology (EE)
  • Wageningen University & Research (NL)
  • MetaGenoPolis (FR)
  • Pondicherry University (IN)
  • Universidade Estadual de Campinas (UNICAMP) (BR)
  • Western Sydney University (AU)
  • Teagasc - The Irish Agriculture and Food Development Authority (IE)
Corresponding author
  • Berg, Gabriele
  • Schloter, Michael
ORCID
Venue
Microbiome
Publisher
Springer Science and Business Media LLC
Published
2020-06-30
Volume
8
Issue
1
Pages
103-103
ISSN
2049-2618 (ISSN-L)
DOI
10.1186/s40168-020-00875-0
PMC
PMC7329523
OpenAlex
W3040245690
Cited by
2,275
References
201
Citations by year
2026: 329 · 2025: 443 · 2024: 444 · 2023: 425 · 2022: 367 · 2021: 230 · 2020: 34
FWCI
140.07
Type
journal article
Language
en
Update notices
correction (2020-08-20)
Open access
Licence
Locations
  • Microbiome (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Socio-Environmental Systems Modeling (acceptedVersion, cc-by)
  • Arrow@dit (Dublin Institute of Technology) (acceptedVersion)
  • Institutional Research Information System University of Turin (University of Turin) (submittedVersion, other-oa)
  • OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
  • PuSH - Publication Server of Helmholtz Zentrum München (submittedVersion, cc-by)
  • HAL (submittedVersion, cc-by)
  • HAL (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Site cant be reached (submittedVersion, cc-by)
  • Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) (submittedVersion, other-oa)
  • Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) (submittedVersion, cc-by-nc-nd)
  • T-Stór (Teagasc) (submittedVersion, cc-by-nc-sa)
  • Lenus, The Irish Health Repository (Dr Steevens Hospital Library) (submittedVersion)
  • Data Archiving and Networked Services (DANS) (submittedVersion, cc-by)
Funders
Horizon 2020 (European Union's Horizon 2020)
Topics
  • Physical Sciences › Environmental Science › Ecology › Microbial Community Ecology and Physiology
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
  • Life Sciences › Agricultural and Biological Sciences › Plant Science › Plant-Microbe Interactions and Immunity
Keywords
microbiota, core microbiome, keystone species, microbial community dynamics, microbial network stability, host-microbe interactions, interspecies interactions, planetary health, anthropogenic change
MeSH terms
Terminology as Topic, Surveys and Questionnaires, Microbiota

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