Evidence map›Paper›PMID 40952906›Full record

ArticleeLife2025

The success of artificial selection for collective composition hinges on initial and target values.

Juhee Lee, Wenying Shou, Hye Jin Park

Abstract read
In one paragraph

Article in eLife, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

1 citing paper in PubMed.

  1. Article
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.

Juhee LeeDepartment of Physics, Inha University, Incheon, Republic of Korea.ORCID https://orcid.org/0000-0003-3318-6377
Wenying ShouCentre for Life's Origins and Evolution, Department of Genetics, Evolution and Environment, University College London, London, United Kingdom.ORCID https://orcid.org/0000-0001-5693-381X
Hye Jin ParkDepartment of Physics, Inha University, Incheon, Republic of Korea.ORCID https://orcid.org/0000-0003-3552-6275

Funding

Academy of Medical Sciences ProfessorshipAsia Pacific Center for Theoretical Physics JRG ProgramInha University Research grantNational Research Foundation of Korea RS-2023-00214071National Research Foundation of Korea RS-2024-00460958Royal Society Wolfson Fellowship
6 · The paper itself

Abstract

Microbial collectives can perform functions beyond the capability of individual members. Enhancing collective functions through artificial selection is, however, challenging. Here, we explore the 'rafting-a-waterfall' metaphor where achieving a target population composition depends on both target and initial compositions. Specifically, collectives comprising fast-growing (F) and slow-growing (S) individuals were grown for 'maturation' time, and the collective with S-frequency closest to the target value is chosen to 'reproduce' via inoculating offspring collectives. During collective maturation, intra-collective selection acts like a waterfall, relentlessly driving the S-frequency to lower values, while during collective reproduction, inter-collective selection resembles a rafter striving to reach the target frequency. Using simulations and analytical calculations, we show that intermediate target S frequencies are the most challenging, akin to a target within the vertical drop of a waterfall, rather than above or below it. This arises because intra-collective selection is the strongest at intermediate S-frequencies, which can overpower inter-collective selection. While achieving a low target S frequencies is consistently feasible, attaining high target S-frequencies requires an initially high S-frequency - much like a raft that can descend but not ascend a waterfall. As Newborn size increases, the region of achievable target frequency is reduced until no frequency is achievable. In contrast, the number of collectives under selection plays a less critical role. In scenarios involving more than two populations, the evolutionary trajectory must navigate entirely away from the metaphorical 'waterfall drop.' Our findings illustrate that the strength of intra-collective evolution is frequency-dependent, with implications in experimental planning.

Indexed as

Computer SimulationEvolution, MolecularSelection, Geneticartificial selection on microbial collectivesevolutionary biologynonestochastic processvariation and inheritance of collective's composition

Identifiers

PMID40952906
PMCPMC12435894

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.