In silico metatranscriptomic approach for tracking biofilm-related effectors in dairies and its importance for improving food safety

Abstract

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Sessile microorganisms are usually recalcitrant to antimicrobial treatments, and it is possible that finding biofilm-related effectors in metatranscriptomics datasets helps to understand mechanisms for bacterial persistence in diverse environments, by revealing protein-encoding genes that are expressed in situ. For this research, selected dairy-associated metatranscriptomics bioprojects were downloaded from the public databases JGI GOLD and NCBI (eight milk and 45 cheese samples), to screen for sequences encoding biofilm-related effectors. Based on the literature, the selected genetic determinants were related to adhesins, BAP, flagellum-related, intraspecific QS (AHL, HK, and RR), interspecific QS (LuxS), and QQ (AHL-acylases, AHL-lactonases). To search for the mRNA sequences encoding for those effector proteins, a custom database was built from UniprotKB, yielding 1,154,446 de-replicated sequences that were indexed in DIAMOND for alignment. The results revealed that in all the dairy-associated metatranscriptomic datasets obtained, there were reads assigned to genes involved with flagella, adhesion, and QS/QQ, but BAP-reads were found only for milk. Significant Pearson correlations (p < 0.05) were observed for transcripts encoding for flagella, RR, histidine kinases, adhesins, and LuxS, although no other significant correlations were found. In conclusion, the rationale used in this study was useful to demonstrate the presence of biofilm-associated effectors in metatranscriptomics datasets, pointing out to possible regulatory mechanisms in action in dairy-related biofilms, which could be targeted in the future to improve food safety.

Keywords

• metatranscriptomic data
• biofilm effectors
• gene expression
• dairy
• milk