Evidence map›Paper›PMID 34045709›Full record

ReviewNature reviews. Microbiology2021

Host specificity of the gut microbiome.

Elizabeth K Mallott, Katherine R Amato

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature reviews. Microbiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 118 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
118citing papers in PubMed, 1 pooled it
–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

118 citing papers in PubMed, 1 synthesis or guideline pooled it.

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58 more citing papers are in PubMed but not listed here.

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

2 authors.

Elizabeth K MallottDepartment of Anthropology, Northwestern University, Evanston, IL, USA.ORCID http://orcid.org/0000-0001-5446-8563
Katherine R AmatoDepartment of Anthropology, Northwestern University, Evanston, IL, USA. katherine.amato@northwestern.edu.ORCID http://orcid.org/0000-0003-2722-9414

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Developing general principles of host-microorganism interactions necessitates a robust understanding of the eco-evolutionary processes that structure microbiota. Phylosymbiosis, or patterns of microbiome composition that can be predicted by host phylogeny, is a unique framework for interrogating these processes. Identifying the contexts in which phylosymbiosis does and does not occur facilitates an evaluation of the relative importance of different ecological processes in shaping the microbial community. In this Review, we summarize the prevalence of phylosymbiosis across the animal kingdom on the basis of the current literature and explore the microbial community assembly processes and related host traits that contribute to phylosymbiosis. We find that phylosymbiosis is less prevalent in taxonomically richer microbiomes and hypothesize that this pattern is a result of increased stochasticity in the assembly of complex microbial communities. We also note that despite hosting rich microbiomes, mammals commonly exhibit phylosymbiosis. We hypothesize that this pattern is a result of a unique combination of mammalian traits, including viviparous birth, lactation and the co-evolution of haemochorial placentas and the eutherian immune system, which compound to ensure deterministic microbial community assembly. Examining both the individual and the combined importance of these traits in driving phylosymbiosis provides a new framework for research in this area moving forward.

Indexed as

Gastrointestinal MicrobiomePhylogenyAnimalsHost Microbial InteractionsHost SpecificityMammalsMiceRNA, Ribosomal, 16SSymbiosisRNA, Ribosomal, 16S

Identifiers

What OpenQuestion holds

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Read underepoch 390

Registered trials

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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.