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Adaptive evolutionary trajectories in complexity: repeated transitions between unicellularity and differentiated multicellularity
Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.ORCID iD: 0000-0003-4918-1140
Umeå University, Faculty of Science and Technology, Department of Molecular Biology (Faculty of Science and Technology). Umeå University, Faculty of Medicine, Umeå Centre for Microbial Research (UCMR).ORCID iD: 0000-0003-1510-8324
Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics. Umeå University, Faculty of Medicine, Umeå Centre for Microbial Research (UCMR).ORCID iD: 0000-0002-6569-5793
(English)Manuscript (preprint) (Other academic)
National Category
Evolutionary Biology
Identifiers
URN: urn:nbn:se:umu:diva-224560OAI: oai:DiVA.org:umu-224560DiVA, id: diva2:1858892
Available from: 2024-05-20 Created: 2024-05-20 Last updated: 2024-05-20
In thesis
1. Adaptation during the early evolution of multicellularity: mathematical models reveal the impact of unicellular history, environmental stress, and life cycles
Open this publication in new window or tab >>Adaptation during the early evolution of multicellularity: mathematical models reveal the impact of unicellular history, environmental stress, and life cycles
2024 (English)Doctoral thesis, comprehensive summary (Other academic)
Alternative title[sv]
Anpassning av flercellighet under tidig evolution : matematisk modellering av encellig historia, miljöstress, och livscykler
Abstract [en]

Multicellular organisms, such as plants and animals, have independently evolved several times over the last hundreds of millions of years. The evolution of multicellularity has significantly shaped modern ecosystems, yet its origins remain largely unknown. Due to the ancient history and the small size scale of early multicellular organisms, few intact fossils have been preserved. To uncover the origins of large and complex life, researchers have turned to alternative methods such as phylogenetic modeling, experimental evolution, and theoretical frameworks. While these approaches have provided novel insights in the early steps of multicellular evolution, few studies have considered the role of adaptation in these novel life cycles. This thesis addresses the gap in our knowledge by employing mathematical modeling and computer simulations to study adaptation in novel multicellular life cycles.

The first paper investigates the effects of unicellular reproduction modes, such as budding or binary fission, on the spread of growth rate mutations. It demonstrates that unicellular history significantly influences the adaptation rate, with budding cells exhibiting greater sensitivity to the spatial distribution of mutations.

In Paper II, the role of multicellular reproduction mode for the adaptation of altruistic and selfish mutations is explored. Specifically, the study examines how adaptation is affected when the filaments are exposed to a size-based selective pressure. It reveals that while the adaptation of altruistic mutations is favored by large offspring, the spread of selfish mutations depends on both offspring size and selection strength.

While Papers I and II assume deterministic life cycle structures at the multicellular level, paper III investigates the evolution of life cycle regulation when cells use internal information. The model demonstrates that when cells only have access to a limited amount of information, there is significant variation in the types of life cycles that emerge. This suggests that to evolve regulated life cycles, additional mechanisms beyond internal information may be necessary, such as cell communication.

Papers I-III explore multicellular life cycles where all cells are of the same type, yet most multicellular organisms have evolved cell differentiation, with specialized cells performing various tasks. In Paper IV, the evolutionary paths leading to differentiated multicellularity are investigated when a unicellular population is exposed to an abiotic (non-evolving) selective pressure. The model reveals that while a wide range of phenotypic backgrounds and environmental conditions may induce differentiation and multicellularity, continued adaptation to the stress eventually leads to reversion to unicellularity. This reversion occurs because as cells adapt to the stress, the costs associated with differentiation and group formation may no longer be justified. One potential strategy to prevent reversion could involve considering biotic selective pressures that can co-evolve with the population.

Lastly, paper V delves into organisms composed by combinations of uni- and multicellular species. Utilizing this framework to examine present multi-species multicellularity reveals that the species composition influences both the ease of partnership establishment and its stability. Additionally, these chimeric groups can reproduce through various strategies, including fragmentation and complete dissociation. Leaving the constellation endows organisms with a memory of prior partnerships, enhancing their adaptability in forming new ones. This extension opens up novel evolutionary pathways for further exploration.

In summary, this thesis offers new insights into how the life cycle structures of simple multicellular organisms impact mutation accumulation and the acquisition of new traits. The adaptability of organisms plays a pivotal role in fostering higher complexity and paving the way for further evolution. Enhancing our understanding in this domain will continue to illuminate the origins of complex life and elucidate the evolutionary factors underlying the rich diversity of multicellular organisms we encounter today.

Place, publisher, year, edition, pages
Umeå: Umeå University, 2024. p. 66
Series
Research report in mathematics, ISSN 1653-0810 ; 77/24
Keywords
Multicellularity, evolution, adaptation, life cycles, mutations, unicellular history, information, selective pressures, fragmentation, computational simulations, mathematical modeling
National Category
Evolutionary Biology Computational Mathematics
Identifiers
urn:nbn:se:umu:diva-224561 (URN)978-91-8070-382-6 (ISBN)978-91-8070-381-9 (ISBN)
Public defence
2024-06-14, Hörsal MIT.A.121, Umeå, 09:00 (English)
Opponent
Supervisors
Available from: 2024-05-24 Created: 2024-05-20 Last updated: 2024-05-20Bibliographically approved

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Isaksson, HannaLind, Peter ALibby, Eric

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Department of Mathematics and Mathematical StatisticsDepartment of Molecular Biology (Faculty of Science and Technology)Umeå Centre for Microbial Research (UCMR)
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