Evidence map›Paper›PMID 41184333›Full record

ArticleScientific reports2025

Prokaryotic co-occurrence patterns in diverse Indian mangrove ecosystems.

Ananya Ghosh, Anwesh Maile, Hampapathalu Adimurthy Nagarajaram

Abstract read
In one paragraph

Article in Scientific reports, 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

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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.

Ananya Ghosh *DBT-Centre for Microbial Informatics (DBT-CMI), School of Life Sciences, University of Hyderabad, Hyderabad, 500046, India.ORCID http://orcid.org/0009-0008-8829-6665
Anwesh Maile *DBT-Centre for Microbial Informatics (DBT-CMI), School of Life Sciences, University of Hyderabad, Hyderabad, 500046, India. anweshmaile@uohyd.ac.in.ORCID http://orcid.org/0000-0003-2164-3251
Hampapathalu Adimurthy NagarajaramDBT-Centre for Microbial Informatics (DBT-CMI), School of Life Sciences, University of Hyderabad, Hyderabad, 500046, India.ORCID http://orcid.org/0000-0001-8568-0620

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mangrove ecosystems are unique coastal zones known to harbour a rich biodiversity of flora and fauna, including microbial communities. These microorganisms play a crucial role in nutrient cycling and sustain the primary productivity driven by plants within this ecosystem. Recent advancements in microbial ecology research emphasise that microbial community structure and composition are critical for an ecosystem to thrive. Studies have focused on the microbial diversity within Indian mangrove forests; however, there is a limited understanding of the co-occurrence patterns and functional roles of microbial communities in these ecosystems. This study explores prokaryotic diversity, primarily focusing on community interactions across three major Indian mangrove forests: the Bhitarkanika mangrove forest in Odisha, the Goan mangroves, and the Sundarbans in West Bengal. By analysing the publicly available 16 S rRNA amplicon datasets of the Indian mangrove microbiomes and performing co-occurrence network analysis on these datasets, we identified positively correlated genera and their predicted functional roles. Furthermore, the findings revealed the co-occurrence of several pathogenic bacteria in two of the mangrove ecosystems. Overall, our study highlights the shared functional roles adopted by co-occurring microbes in three major Indian mangrove ecosystems and suggests the need for large-scale studies in these understudied Indian ecosystems.

Indexed as

BacteriaEcosystemMicrobiotaWetlandsBiodiversityIndiaPhylogenyRNA, Ribosomal, 16SSoil MicrobiologyRNA, Ribosomal, 16SAmplicon sequencingCo-occurrence networksIndian mangrovesMangrove microbiomeMarine microbial ecology

Identifiers

PMID41184333
PMCPMC12583659

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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.