Evidence map›Paper›PMID 39639304›Full record

ArticleBMC biology2024

Species specificity and specificity diversity (SSD) framework: a novel method for detecting the unique and enriched species associated with disease by leveraging the microbiome heterogeneity.

Zhanshan Sam Ma

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Article in BMC biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

1 author.

Zhanshan Sam MaComputational Biology and Medical Ecology Lab, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China. ma@alumni.uidaho.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDifferentiating the microbiome changes associated with diseases is challenging but critically important. Majority of existing efforts have been focused on a community level, but the discerning power of community or holistic metrics such as diversity analysis seems limited. This prompts many researchers to believe that the promise should be downward to species or even strain level-effectively and efficiently identifying unique or enriched species in diseased microbiomes with statistical rigor. Nevertheless, virtually, all species-level approaches such as differential abundance and differential network analysis methods exclusively rely on species abundances without considering species distribution information, while it can be said that distribution is equally, if not more, important than abundance in shaping the spatiotemporal heterogeneity of community compositions.

resultsHere, we fill the gap by developing a novel framework-species specificity and specificity diversity (SSD)-that synthesizes both abundance and distribution information to differentiate microbiomes, at both species and community scales, under different environmental gradients such as the healthy and diseased treatments. The proposed SSD framework consists of three essential elements. The first is species specificity (SS), a concept that reincarnates the traditional specialist-generalist continuum and is defined by Mariadassou et al. (Ecol Lett 18:974-82, 2015). The SS synthesizes a species' local prevalence (distribution) and global abundance information and attaches specificity measure to each species in a specific habitat (e.g., healthy or diseased treatment). The second element is a new concept to introduce here, the (species) specificity diversity (SD), which is inspired by traditional species (abundance) diversity in community ecology and measures the diversity of specificity (a proxy for metacommunity heterogeneity, essentially) with Renyi's entropy. The third element is a pair of statistical tests based on the principle of permutation tests.

conclusionsThe SSD framework can (i) identify and catalogue lists of unique species (US), significantly enriched species (ES) in each treatment based on SS and specificity permutation (SP) test and (ii) measure the holistic differences between assemblages (or treatments) based on SD and specificity diversity permutation (SDP) test. Both capacities can be enabling technologies for general comparative microbiome research including risk assessment, diagnosis, and treatment of microbiome-associated diseases.

Indexed as

MicrobiotaSpecies SpecificityBiodiversityHumansCompositional heterogeneityEnriched species (ES)GoutSpecies specificity (SS)Specificity diversity permutation (SDP) testSpecificity diversity (SD)Specificity permutation (SP) testUnique species (US)

Identifiers

PMID39639304
PMCPMC11619696

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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.