Evidence map›Paper›PMID 33183356›Full record

ArticleMicrobiome2020

Unravelling the importance of the eukaryotic and bacterial communities and their relationship with Legionella spp. ecology in cooling towers: a complex network.

Kiran Paranjape, Émilie Bédard, Deeksha Shetty, Mengqi Hu, Fiona Chan Pak Choon, Michèle Prévost, Sébastien P Faucher

Open access · goldAbstract readVideo-Audio Media
In one paragraph

Article in Microbiome, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
5.7field-weighted citation impact, top 4% of its field
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

16 citing papers in PubMed, 37 citations in OpenAlex.

  1. Article
  2. Variable inhibition of differentApplied and environmental microbiology · 2025
    Article
  3. Microorganisms · 2025
    Article
  4. Article
  5. Review
  6. Article
  7. Review
  8. Review
  9. Article
  10. Microorganisms · 2023
    Article
  11. Article
  12. FEMS microbes · 2023
    Article
  13. Review
  14. Article
  15. Article
  16. Microorganisms · 2021
    Review
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 at 2 institutions in 1 country.

Kiran ParanjapeDepartment of Natural Resource Sciences, Faculty of Agricultural and Environmental Sciences, McGill University, Sainte-Anne-de-Bellevue, QC, Canada.
Émilie BédardDepartment of Civil Engineering, Polytechnique Montreal, Montréal, QC, Canada.
Deeksha ShettyDepartment of Natural Resource Sciences, Faculty of Agricultural and Environmental Sciences, McGill University, Sainte-Anne-de-Bellevue, QC, Canada.
Mengqi HuDepartment of Natural Resource Sciences, Faculty of Agricultural and Environmental Sciences, McGill University, Sainte-Anne-de-Bellevue, QC, Canada.
Fiona Chan Pak ChoonDepartment of Natural Resource Sciences, Faculty of Agricultural and Environmental Sciences, McGill University, Sainte-Anne-de-Bellevue, QC, Canada.
Michèle PrévostDepartment of Civil Engineering, Polytechnique Montreal, Montréal, QC, Canada.
Sébastien P FaucherDepartment of Natural Resource Sciences, Faculty of Agricultural and Environmental Sciences, McGill University, Sainte-Anne-de-Bellevue, QC, Canada. sebastien.faucher2@mcgill.ca.ORCID 0000-0002-2721-7715
McGill University · CAPolytechnique Montréal · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCooling towers are a major source of large community-associated outbreaks of Legionnaires' disease, a severe pneumonia. This disease is contracted when inhaling aerosols that are contaminated with bacteria from the genus Legionella, most importantly Legionella pneumophila. How cooling towers support the growth of this bacterium is still not well understood. As Legionella species are intracellular parasites of protozoa, it is assumed that protozoan community in cooling towers play an important role in Legionella ecology and outbreaks. However, the exact mechanism of how the eukaryotic community contributes to Legionella ecology is still unclear. Therefore, we used 18S rRNA gene amplicon sequencing to characterize the eukaryotic communities of 18 different cooling towers. The data from the eukaryotic community was then analysed with the bacterial community of the same towers in order to understand how each community could affect Legionella spp. ecology in cooling towers.

resultsWe identified several microbial groups in the cooling tower ecosystem associated with Legionella spp. that suggest the presence of a microbial loop in these systems. Dissolved organic carbon was shown to be a major factor in shaping the eukaryotic community and may be an important factor for Legionella ecology. Network analysis, based on co-occurrence, revealed that Legionella was correlated with a number of different organisms. Out of these, the bacterial genus Brevundimonas and the ciliate class Oligohymenophorea were shown, through in vitro experiments, to stimulate the growth of L. pneumophila through direct and indirect mechanisms.

conclusionOur results suggest that Legionella ecology depends on the host community, including ciliates and on several groups of organisms that contribute to its survival and growth in the cooling tower ecosystem. These findings further support the idea that some cooling tower microbiomes may promote the survival and growth of Legionella better than others. Video Abstract.

Indexed as

BiotaEukaryotaLegionellaWater MicrobiologyCarbonHumansLegionella pneumophilaLegionnaires' DiseaseCarbon18S rRNA gene amplicon sequencingBrevundimonas sp.Dissolved organic carbonEukaryotic communityLegionella pneumophilaNetwork analysisWhole genome sequencing

Identifiers

PMID33183356
PMCPMC7664032
OpenAlexW3106419186

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.