Quorum-sensing microbial dark matter enables core functions in wastewater microbiomes.

Authors

Qiuju Liu, Han Su, Sai Gong, Ying Jin, Yingzheng Fan, Mengxiong Wu, Jianhua Guo, Xinkun Ren, Jinfeng Wang

Published in

ISME communications. Volume 6. Issue 1. Pages ycag264. Epub Sep 16, 2026.

Abstract

Quorum-sensing bacteria (QSB) play a crucial role in coordinating microbial activities in activated sludge. However, our knowledge is primarily based on cultivated or taxonomically classified species, neglecting microbial dark matter (MDM), which comprises lineages lacking reference genomes and is prevalent in wastewater communities. Herein, 3569 high- and medium-quality metagenome-assembled genomes were obtained from 69 full-scale wastewater treatment plants. A total of 1289 MDM lineages were identified to possess quorum sensing (QS) capabilities, designated as MDM-QSB. Among them, 127 novel genera were identified. These organisms possess larger genomes enriched in genes for energy metabolism and environmental information processing, allowing a broader ecological niche compared to non-QS MDM (P < .001). They occupy central positions in co-occurrence networks and are predicted as dominant keystones by a deep learning model. Their robust metabolic potential and network keystone position enable coordinated community-level metabolic responses, as evidenced by stronger carbon, nitrogen, phosphorus, and sulfur element cycling functions and higher associations with chemical oxygen demand, total nitrogen, and ammonium nitrogen removal (P < .05). Furthermore, genome-scale metabolic modeling reveals they engage in extensive cross-feeding with nitrifiers, denitrifiers, and polyphosphate-accumulating organisms, supplying metabolites such as protoheme and serine alongside QS signals. Together, these findings identify MDM-QSB as previously overlooked multifunctional hubs of activated sludge microbiomes. Given their crucial roles in community stability and process performance, incorporating these previously overlooked populations into monitoring and control frameworks is expected to improve the resilience and predictability of biological wastewater treatment processes.

PMID:
42841094
Bibliographic data and abstract were imported from PubMed on 07 Oct 2026.

Read full publication at:
Please sign in to see all details.

Stats

1-terrible, 9-excellent. How would you rate this publication? Sign in in to submit your rating.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.