Role of microorganisms in the evolution of animals and plants: the hologenome theory of evolution
Abstract
We present here the hologenome theory of evolution, which considers the holobiont (the animal or plant with all of its associated microorganisms) as a unit of selection in evolution. The hologenome is defined as the sum of the genetic information of the host and its microbiota. The theory is based on four generalizations: (1) All animals and plants establish symbiotic relationships with microorganisms. (2) Symbiotic microorganisms are transmitted between generations. (3) The association between host and symbionts affects the fitness of the holobiont within its environment. (4) Variation in the hologenome can be brought about by changes in either the host or the microbiota genomes; under environmental stress, the symbiotic microbial community can change rapidly. These points taken together suggest that the genetic wealth of diverse microbial symbionts can play an important role both in adaptation and in evolution of higher organisms. During periods of rapid changes in the environment, the diverse microbial symbiont community can aid the holobiont in surviving, multiplying and buying the time necessary for the host genome to evolve. The distinguishing feature of the hologenome theory is that it considers all of the diverse microbiota associated with the animal or the plant as part of the evolving holobiont. Thus, the hologenome theory fits within the framework of the 'superorganism' proposed by Wilson and Sober.
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Behavior that facilitates social interaction among holobionts might be considered evolutionarily adaptive/advantageous because it gives rise to greater transmission of microbiota, thereby enhancing genetic variation.
“behavior that facilitates social interaction among holobionts might be considered evolutionarily adaptive/advantageous as it gives rise to greater transmission of microbiota, thereby enhancing genetic variation (Rosenberg et al., 2010;Rosenberg et al., 2009;Zilber-Rosenberg and Rosenberg, 2008).”
From The Microbiota-Gut-Brain Axis (2019) · cites this paper as Zilber-Rosenberg and Rosenberg, 2008
One key principle of the hologenome theory is that genetic variation in the holobiont is facilitated by both the host genome and its associated microbial genome.
“One key principle of the hologenome theory is that genetic variation in the holobiont is facilitated by both the host genome and its associated microbial genome.”
From The Microbiota-Gut-Brain Axis (2019) · cites this paper as Zilber-Rosenberg and Rosenberg, 2008
The hologenome theory of evolution suggests that the holobiont and its associated hologenome act as a unit of evolutionary selection.
“the hologenome theory of evolution, which suggests that the holobiont and its associated hologenome acts as a unit of evolutionary selection (Zilber-Rosenberg and Rosenberg, 2008).”
From The Microbiota-Gut-Brain Axis (2019) · cites this paper as Zilber-Rosenberg and Rosenberg, 2008
Cites
Human gut microbes associated with obesity
Ley, R. E., Turnbaugh, P. J., Klein, S., & Gordon, J. I. (2006) · Nature · doi:10.1038/4441022a · Cited by 8,785 · see citing works
Biodiversity and ecosystem productivity in a fluctuating environment: The insurance hypothesis
Yachi, S., & Loreau, M. (1999) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.96.4.1463 · Cited by 3,211 · see citing works
The gut flora as a forgotten organ
O'Hara, A. M., & Shanahan, F. (2006) · The EMBO Reports · doi:10.1038/sj.embor.7400731 · Cited by 2,791 · see citing works
Mechanisms underlying the resistance to diet-induced obesity in germ-free mice
Bäckhed, F., Manchester, J. K., Semenkovich, C. F., & Gordon, J. I. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0605374104 · Cited by 2,615 · see citing works
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Cryan, J. F., O'Riordan, K. J., Cowan, C. S. M., Sandhu, K. V., Bastiaanssen, T. F. S., Boehme, M., Codagnone, M. G., Cussotto, S., Fulling, C., Golubeva, A. V., et al. (2019) · Physiological Reviews · doi:10.1152/physrev.00018.2018 · Cited by 5,286 · see citing works
Proteobacteria: Microbial signature of dysbiosis in gut microbiota
Shin, N.-R., Whon, T. W., & Bae, J.-W. (2015) · Trends in Biotechnology · doi:10.1016/j.tibtech.2015.06.011 · Cited by 3,954 · see citing works
Microbiome definition re-visited: old concepts and new challenges
Berg, G., Rybakova, D., Fischer, D., Cernava, T., Vergès, M.-C. C., Charles, T., Chen, X., Cocolin, L., Eversole, K., Corral, G. H., et al. (2020) · Microbiome · doi:10.1186/s40168-020-00875-0 · Cited by 2,275 · see citing works
Milani, C., Duranti, S., Bottacini, F., Casey, E., Turroni, F., Mahony, J., Belzer, C., Delgado Palacio, S., Arboleya Montes, S., Mancabelli, L., et al. (2017) · Microbiology and Molecular Biology Reviews · doi:10.1128/mmbr.00036-17 · Cited by 1,950 · see citing works
Metformin retards aging in C. elegans by altering microbial folate and methionine metabolism
Cabreiro, F., Au, C., Leung, K.-Y., Vergara-Irigaray, N., Cochemé, H. M., Noori, T., Weinkove, D., Schuster, E., Greene, N. D. E., & Gems, D. (2013) · Cell · doi:10.1016/j.cell.2013.02.035 · Cited by 967 · see citing works
Exploring the bovine rumen bacterial community from birth to adulthood
Jami, E., Israel, A., Kotser, A., & Mizrahi, I. (2013) · The ISME Journal · doi:10.1038/ismej.2013.2 · Cited by 963 · see citing works
Current challenges and best-practice protocols for microbiome analysis
Bharti, R., & Grimm, D. G. (2021) · Briefings in Bioinformatics · doi:10.1093/bib/bbz155 · Cited by 592 · see citing works
Microbiota and the social brain
Sherwin, E., Bordenstein, S. R., Quinn, J. L., Dinan, T. G., & Cryan, J. F. (2019) · Science · doi:10.1126/science.aar2016 · Cited by 462 · see citing works
Establishment of ruminal bacterial community in dairy calves from birth to weaning is sequential
Rey, M., Enjalbert, F., Combes, S., Cauquil, L., Bouchez, O., & Monteils, V. (2014) · Journal of Applied Microbiology · doi:10.1111/jam.12405 · Cited by 314 · see citing works
Microbiome in healthy skin, update for dermatologists
Dréno, B., Araviiskaia, E., Berardesca, E., Gontijo, G., Sanchez Viera, M., Xiang, L. F., Martin, R., & Bieber, T. (2016) · Journal of the European Academy of Dermatology and Venereology · doi:10.1111/jdv.13965 · Cited by 292 · see citing works
Janik, R., Thomason, L. A. M., Stanisz, A. M., Forsythe, P., Bienenstock, J., & Stanisz, G. J. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2015.11.018 · Cited by 283 · see citing works
Cross talk: the microbiota and neurodevelopmental disorders
Kelly, J. R., Minuto, C., Cryan, J. F., Clarke, G., & Dinan, T. G. (2017) · Frontiers in Neuroscience · doi:10.3389/fnins.2017.00490 · Cited by 271 · see citing works
Problems with the concept of gut microbiota dysbiosis
Brüssow, H. (2020) · Microbial Biotechnology · doi:10.1111/1751-7915.13479 · Cited by 250 · see citing works
Gut Dysbiosis and Muscle Aging: Searching for Novel Targets against Sarcopenia
Picca, A., Fanelli, F., Calvani, R., Mulè, G., Pesce, V., Sisto, A., Pantanelli, C., Bernabei, R., Landi, F., & Marzetti, E. (2018) · Mediators of Inflammation · doi:10.1155/2018/7026198 · Cited by 181 · see citing works
Correcting index databases improves metagenomic studies
Méric, G., Wick, R. R., Watts, S. C., Holt, K. E., & Inouye, M. (2019) · doi:10.1101/712166 · Cited by 34 · see citing works
Sandybayeva, S. K., Kossalbayev, B. D., Zayadan, B. K., Sadvakasova, A. K., Bolatkhan, K., Zadneprovskaya, E. V., Kakimov, A. B., Alwasel, S., Leong, Y. K., Allakhverdiev, S. I., et al. (2022) · Biochemical Engineering Journal · doi:10.1016/j.bej.2022.108640 · Cited by 44 · see citing works
Understanding asthma and allergies by the lens of biodiversity and epigenetic changes
Fiuza, B. S. D., Fonseca, H. F., Meirelles, P. M., Marques, C. R., da Silva, T. M., & Figueiredo, C. A. (2021) · Frontiers in Immunology · doi:10.3389/fimmu.2021.623737 · Cited by 38 · see citing works
Durand, L., Roumagnac, M., Cueff-Gauchard, V., Jan, C., Guri, M., Tessier, C., Haond, M., Crassous, P., Zbinden, M., Arnaud-Haond, S., et al. (2015) · FEMS Microbiology Ecology · doi:10.1093/femsec/fiv101 · Cited by 32 · see citing works
Basso, M., Johnstone, N., Knytl, P., Nauta, A., Groeneveld, A., & Cohen Kadosh, K. (2022) · Nutrients · doi:10.3390/nu14030614 · Cited by 28 · see citing works
The holobiont mind: A bridge between 4E-cognition and the microbiome
Palacios-Garcia, I., & Parada, F. J. (2021) · doi:10.31234/osf.io/thuvc · Cited by 21 · see citing works
- Authors
- Zilber-Rosenberg, I., & Rosenberg, E.
- Affiliations
- Tel Aviv University (IL)
- Corresponding author
- Rosenberg, Eugene
- ORCID
- Rosenberg, Eugene
- Venue
- FEMS Microbiology Reviews
- Publisher
- Oxford University Press (OUP)
- Published
- 2008-08
- Volume
- 32
- Issue
- 5
- Pages
- 723-735
- ISSN
- 0168-6445 (ISSN-L)
- 1574-6976
- OpenAlex
- W2170025869
- Cited by
- 1,739
- References
- 4
- Citations by year
- 2026: 102 · 2025: 123 · 2024: 139 · 2023: 130 · 2022: 127 · 2021: 176 · 2020: 146 · 2019: 155 · 2018: 146 · 2017: 105 · 2016: 110 · 2015: 82 · 2014: 46 · 2013: 54 · 2012: 32
- FWCI
- 2.05
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- FEMS Microbiology Reviews (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Evolution and Genetic Dynamics
- Life Sciences › Agricultural and Biological Sciences › Insect Science › Insect symbiosis and bacterial influences
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protist diversity and phylogeny
- Keywords
- holobiont, host-microbe symbiosis, microbiota, units of selection, host adaptation, environmental stress, superorganism, host genome evolution
- MeSH terms
- Adaptation, Biological, Adaptation, Physiological, Animals, Biological Evolution, Host-Parasite Interactions, Plants, Symbiosis
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