Evidence map›Paper›PMID 39254351›Full record

ArticlemSystems2024

The predicted secreted proteome of activated sludge microorganisms indicates distinct nutrient niches.

Kenneth Wasmund, Caitlin Singleton, Morten Kam Dahl Dueholm, Michael Wagner, Per Halkjær Nielsen

Abstract read
In one paragraph

Article in mSystems, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

5 authors.

Kenneth WasmundCenter for Microbial Communities, Department of Chemistry and Bioscience, Aalborg University, Aalborg, Denmark.ORCID 0000-0001-6706-7291
Caitlin SingletonCenter for Microbial Communities, Department of Chemistry and Bioscience, Aalborg University, Aalborg, Denmark.ORCID 0000-0001-9688-8208
Morten Kam Dahl DueholmCenter for Microbial Communities, Department of Chemistry and Bioscience, Aalborg University, Aalborg, Denmark.
Michael WagnerCenter for Microbial Communities, Department of Chemistry and Bioscience, Aalborg University, Aalborg, Denmark.
Per Halkjær NielsenCenter for Microbial Communities, Department of Chemistry and Bioscience, Aalborg University, Aalborg, Denmark.ORCID 0000-0002-6402-1877

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In wastewater treatment plants (WWTPs), complex microbial communities process diverse chemical compounds from sewage. Secreted proteins are critical because many are the first to interact with or degrade external (macro)molecules. To better understand microbial functions in WWTPs, we predicted secreted proteomes of WWTP microbiota from more than 1,000 high-quality metagenome-assembled genomes (MAGs) from 23 Danish WWTPs with biological nutrient removal. Focus was placed on examining secreted catabolic exoenzymes that target major classes of macromolecules. We demonstrate that Bacteroidota has a high potential to digest complex polysaccharides, but also proteins and nucleic acids. Poorly understood activated sludge members of Acidobacteriota and Gemmatimonadota also have high capacities for extracellular polysaccharide digestion. Secreted nucleases are encoded by 61% of MAGs indicating an importance for extracellular DNA and/or RNA digestion in WWTPs. Secreted lipases were the least common macromolecule-targeting enzymes predicted, encoded mainly by Gammaproteobacteria and Myxococcota. In contrast, diverse taxa encode extracellular peptidases, indicating that proteins are widely used nutrients. Diverse secreted multi-heme cytochromes suggest capabilities for extracellular electron transfer by various taxa, including some Bacteroidota that encode undescribed cytochromes with >100 heme-binding motifs. Myxococcota have exceptionally large secreted protein complements, probably related to predatory lifestyles and/or complex cell cycles. Many Gammaproteobacteria MAGs (mostly former Betaproteobacteria) encode few or no secreted hydrolases, but many periplasmic substrate-binding proteins and ABC- and TRAP-transporters, suggesting they are mostly sustained by small molecules. Together, this study provides a comprehensive overview of how WWTPs microorganisms interact with the environment, providing new insights into their functioning and niche partitioning.IMPORTANCEWastewater treatment plants (WWTPs) are critical biotechnological systems that clean wastewater, allowing the water to reenter the environment and limit eutrophication and pollution. They are also increasingly important for the recovery of resources. They function primarily by the activity of microorganisms, which act as a "living sponge," taking up and transforming nutrients, organic material, and pollutants. Despite much research, many microorganisms in WWTPs are uncultivated and poorly characterized, limiting our understanding of their functioning. Here, we analyzed a large collection of high-quality metagenome-assembled genomes from WWTPs for encoded secreted enzymes and proteins, with special emphasis on those used to degrade organic material. This analysis showed highly distinct secreted proteome profiles among different major phylogenetic groups of microorganisms, thereby providing new insights into how different groups function and co-exist in activated sludge. This knowledge will contribute to a better understanding of how to efficiently manage and exploit WWTP microbiomes.

Indexed as

ProteomeSewageBacteriaBacterial ProteinsMetagenomeMicrobiotaNutrientsBacterial ProteinsNutrientsProteomeSewageactivated sludgecytochromesexoenzymesextracellular enzymesmacromoleculesmetagenomesecreted proteomewastewater

Identifiers

PMID39254351
PMCPMC11495043

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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.