Evidence map›Paper›PMID 34675897›Full record

ArticleFrontiers in microbiology2021

Deep (Meta)genomics and (Meta)transcriptome Analyses of Fungal and Bacteria Consortia From Aircraft Tanks and Kerosene Identify Key Genes in Fuel and Tank Corrosion.

Ines Krohn, Lutgardis Bergmann, Minyue Qi, Daniela Indenbirken, Yuchen Han, Pablo Perez-Garcia, Elena Katzowitsch, Birgit Hägele, Tim Lübcke, Christian Siry and 3 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in microbiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.4field-weighted citation impact, top 48% 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

5 citing papers in PubMed, 14 citations in OpenAlex.

  1. Article
  2. Dominance of non-Microbiology (Reading, England) · 2025
    Article
  3. Review
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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

13 authors at 6 institutions in 1 country.

Ines KrohnDepartment of Microbiology and Biotechnology, Institute of Plant Science and Microbiology, University of Hamburg, Hamburg, Germany.
Lutgardis BergmannDepartment of Microbiology and Biotechnology, Institute of Plant Science and Microbiology, University of Hamburg, Hamburg, Germany.
Minyue QiBioinformatics Core, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Daniela IndenbirkenVirus Genomics, Heinrich-Pette-Institute, Leibniz Institute for Experimental Virology, Hamburg, Germany.
Yuchen HanDepartment of Microbiology and Biotechnology, Institute of Plant Science and Microbiology, University of Hamburg, Hamburg, Germany.
Pablo Perez-GarciaInstitute of General Microbiology, Molecular Microbiology, Kiel University, Kiel, Germany.
Elena KatzowitschFaculty of Medicine, Core Unit Systems Medicine, University of Würzburg, Würzburg, Germany.
Birgit HägeleT/TQ-MN, Lufthansa Technik AG HAM, Hamburg, Germany.
Tim LübckeT/TQ-MN, Lufthansa Technik AG HAM, Hamburg, Germany.
Christian SiryT/TQ-MN, Lufthansa Technik AG HAM, Hamburg, Germany.
Ralf RiemannT/TQ-MN, Lufthansa Technik AG HAM, Hamburg, Germany.
Malik AlawiBioinformatics Core, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Wolfgang R StreitDepartment of Microbiology and Biotechnology, Institute of Plant Science and Microbiology, University of Hamburg, Hamburg, Germany.
Universität Hamburg · DELufthansa (Germany) · DEKiel University · DELeibniz Institute of Virology (LIV) · DEUniversity Medical Center Hamburg-Eppendorf · DEUniversity of Würzburg · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Microbial contamination of fuels, associated with a wide variety of bacteria and fungi, leads to decreased product quality and can compromise equipment performance by biofouling or microbiologically influenced corrosion. Detection and quantification of microorganisms are critical in monitoring fuel systems for an early detection of microbial contaminations. To address these challenges, we have analyzed six metagenomes, one transcriptome, and more than 1,200 fluid and swab samples taken from fuel tanks or kerosene. Our deep metagenome sequencing and binning approaches in combination with RNA-seq data and qPCR methods implied a metabolic symbiosis between fungi and bacteria. The most abundant bacteria were affiliated with α-, β-, and γ-Proteobacteria and the filamentous fungi

Indexed as

bacteria and fungibiocorrosionbiofilm formationbiofoulingfuel contaminationkerosene and aircraftomics analysis

Identifiers

PMID34675897
PMCPMC8525681
OpenAlexW3203777723

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.