Evidence map›Paper›PMID 39841150›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2025

Adaptive evolutionary trajectories in complexity: Transitions between unicellularity and facultative differentiated multicellularity.

Hanna Isaksson, Peter Lind, Eric Libby

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Hanna IsakssonDepartment of Mathematics and Mathematical Statistics, Umeå University, Umeå 90187, Sweden.ORCID 0000-0003-4918-1140
Peter LindIceLab, Umeå University, Umeå 90187, Sweden.ORCID 0000-0003-1510-8324
Eric LibbyDepartment of Mathematics and Mathematical Statistics, Umeå University, Umeå 90187, Sweden.ORCID 0000-0002-6569-5793

Funding

Vetenskapsrådet (VR) 2018-03630
6 · The paper itself

Abstract

Multicellularity spans a wide gamut in terms of complexity, from simple clonal clusters of cells to large-scale organisms composed of differentiated cells and tissues. While recent experiments have demonstrated that simple forms of multicellularity can readily evolve in response to different selective pressures, it is unknown if continued exposure to those same selective pressures will result in the evolution of increased multicellular complexity. We use mathematical models to consider the adaptive trajectories of unicellular organisms exposed to periodic bouts of abiotic stress, such as drought or antibiotics. Populations can improve survival in response to the stress by evolving multicellularity or cell differentiation-or both; however, these responses have associated costs when the stress is absent. We define a parameter space of fitness-relevant traits and identify where multicellularity, differentiation, or their combination is fittest. We then study the effects of adaptation by allowing populations to fix mutations that improve their fitness. We find that while the same mutation can be beneficial to populations of different complexity, e.g., strict unicellularity or life cycles with stages of differentiated multicellularity, the magnitudes of their effects can differ and alter which is fittest. As a result, we observe adaptive trajectories that gain and lose complexity. We also show that the order of mutations, historical contingency, can cause some transitions to be permanent in the absence of neutral evolution. Ultimately, we find that continued exposure to a selective driver for multicellularity can either lead to increasing complexity or a return to unicellularity.

Indexed as

Adaptation, PhysiologicalBiological EvolutionCell DifferentiationModels, BiologicalMutationSelection, GeneticStress, Physiologicaladaptationcomplexitydifferentiationmulticellularity

Identifiers

PMID39841150
PMCPMC11789074

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.