Evidence map›Paper›PMID 40718753›Full record

ArticleISME communications2025

Models of microbiome evolution incorporating host resource provisioning.

Yao Xiao, Teng Li, Allen Rodrigo

Abstract read
In one paragraph

Article in ISME communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Yao XiaoSchool of Biological Sciences, The University of Auckland, 3A Symonds St, Auckland 1010, New Zealand.
Teng LiSchool of Biological Sciences, The University of Auckland, 3A Symonds St, Auckland 1010, New Zealand.
Allen RodrigoSchool of Biological Sciences, The University of Auckland, 3A Symonds St, Auckland 1010, New Zealand.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Multicellular hosts and their associated microbial partners (i.e. microbiomes) often interact in mutually beneficial ways. Consequently, hosts may choose to allocate resources to regulate and recruit appropriate microbes. In doing so, hosts may incur an energetic cost and, in turn, these costs can affect host fitness. It remains unclear how hosts have evolved to balance the costs of expending resources to manage their microbiomes against the benefits that might accrue by doing so. To address this question, we extend a previously developed agent-based computational model of host-microbiome evolution by incorporating a resource provisioning process, to determine how hosts have evolved to balance the costs and benefits of expending resources to manage their microbiomes. Our results indicate that resource provisioning will evolve when hosts provide a high percentage of microbes to their offspring and contribute a low percentage of their microbiome to the environment. In contrast, resource provisioning will not evolve when hosts contribute a high percentage of their microbiome to the environment. This is because hosts that do not provide resources to acquire microbes can nonetheless still acquire microbes from the environmental contributions of hosts that do provide such resources. Since resource provisioning incurs a fitness cost to the host, over evolutionary time, resource provisioning will not be favored. Our results also show that hosts are less likely to provide resources to acquire beneficial microbes if hosts can obtain a high proportion of these microbes from the environment.

Indexed as

evolutionmicrobiomemodelresource provisioning

Identifiers

PMID40718753
PMCPMC12291540

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.