Evidence map›Paper›PMID 40235649›Full record

ArticleEnvironmental science and ecotechnology2025

Genome-resolved metatranscriptomics unveils distinct microbial functionalities across aggregate sizes in aerobic granular sludge.

A Y A Mohamed, Laurence Gill, Alejandro Monleon, Mario Pronk, Mark van Loosdrecht, Pascal E Saikaly, Muhammad Ali

Abstract read
In one paragraph

Article in Environmental science and ecotechnology, 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

7 authors.

A Y A MohamedDepartment of Civil, Structural & Environmental Engineering, Trinity College Dublin, The University of Dublin, Dublin 2, Ireland.
Laurence GillDepartment of Civil, Structural & Environmental Engineering, Trinity College Dublin, The University of Dublin, Dublin 2, Ireland.
Alejandro MonleonDepartment of Civil, Structural & Environmental Engineering, Trinity College Dublin, The University of Dublin, Dublin 2, Ireland.
Mario PronkDepartment of Biotechnology, Delft University of Technology, Delft, 2629 HZ, the Netherlands.
Mark van LoosdrechtDepartment of Biotechnology, Delft University of Technology, Delft, 2629 HZ, the Netherlands.
Pascal E SaikalyEnvironmental Science and Engineering Program, Biological and Environmental Science and Engineering (BESE) Division, King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Saudi Arabia.
Muhammad AliDepartment of Civil, Structural & Environmental Engineering, Trinity College Dublin, The University of Dublin, Dublin 2, Ireland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Microbial aggregates of different sizes in aerobic granular sludge (AGS) systems have been shown to exhibit distinct microbial community compositions. However, studies comparing the microbial activities of different-sized aggregates in AGS systems remain limited. In this study, genome-resolved metatranscriptomics was used to investigate microbial activity patterns within differently sized aggregates in a full-scale AGS plant. Our analysis revealed a weak correlation between the relative abundance of metagenome-assembled genomes (MAGs) and their transcriptomic activity, indicating that microbial abundance does not directly correspond to metabolic activity within the system. Flocculent sludge (FL; <0.2 mm) predominantly featured active nitrifiers and fermentative polyphosphate-accumulating organisms (PAOs) from

Indexed as

Aerobic granular sludgeDifferential expression analysisGenome-resolved metatranscriptomicsMicrobial activityWastewater treatment

Identifiers

PMID40235649
PMCPMC11999188

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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.