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

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 Amorphotheca. We identified a high number of genes, which are related to kerosene degradation and biofilm formation. Surprisingly, a large number of genes coded enzymes involved in polymer degradation and potential bio-corrosion processes. Thereby, the transcriptionally most active microorganisms were affiliated with the genera Methylobacteria, Pseudomonas, Kocuria, Amorpotheka, Aspergillus, Fusarium, and Penicillium. Many not yet cultured bacteria and fungi appeared to contribute to the biofilm transcriptional activities. The largest numbers of transcripts were observed for dehydrogenase, oxygenase, and exopolysaccharide production, attachment and pili/flagella-associated proteins, efflux pumps, and secretion systems as well as lipase and esterase activity.

Microbiologically influenced corrosion: The gap in the field

“…As technology becomes ever more available, an ideal baseline characterization of the biological threat should contain a qualitative and a quantitative assessment of the planktonic and sessile populations using New Generation Sequencing techniques and quantitative PCR, respectively. The former refers to the use of tools such as shotgun metagenomics, metatranscriptomics or 16S rRNA-based metagenomics, also referred to as metataxonomics, to qualitatively analyze microbial community compositions (Marchesi and Ravel, 2015;Pal et al, 2019;Krohn et al, 2021;McDaniel et al, 2021). Since unlike microbial cultures such molecular biology methods do not rely on microbial growth but rather on the detection of microbial components or products, they can reflect more accurately the composition of field microbiomes (Larsen et al, 2013;Eckert and Skovhus, 2018).…”