Integrated Profiling of Gram-Positive and Gram-Negative Probiotic Genomes, Proteomes and Metabolomes Revealed Small Molecules with Differential Growth Inhibition of Antimicrobial-Resistant Pathogens

革兰氏阳性和革兰氏阴性益生菌基因组、蛋白质组和代谢组的综合分析揭示了对抗菌素耐药性病原体具有不同生长抑制作用的小分子

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作者:Petronella R Hove, Nora Jean Nealon, Siu Hung Joshua Chan, Shea M Boyer, Hannah B Haberecht, Elizabeth P Ryan

Abstract

Probiotics produce small molecules that may serve as alternatives to conventional antibiotics by suppressing growth of antimicrobial resistant (AMR) pathogens. The objective of this study was to identify and examine antimicrobials produced and secreted by probiotics using 'omics' profiling with computer-based metabolic flux analyses. The cell-free supernatant of Gram-positive Lacticaseibacillus rhamnosus GG (LGG) and Gram-negative Escherichia coli Nissle (ECN) probiotics inhibited growth of AMR Salmonella Typhimurium, Escherichia coli, and Klebsiella oxytoca ranging between 28.85 - 41.20% (LGG) and 11.48 - 29.45% (ECN). A dose dependent analysis of probiotic supernatants showed LGG was 6.27% to 20.55% more effective at reducing AMR pathogen growth when compared to ECN. Principal component analysis showed clear separation of ECN and LGG cell free supernatant metabolomes. Among 667 metabolites in the supernatant, 304 were differentially abundant between LGG and ECN probiotics. Proteomics identified 87 proteins, whereby 67 (ECN) and 14 (LGG) showed differential expression as enzymes related to carbohydrate and energy metabolic pathways. The whole genomes and metabolomes were next used for in-silico metabolic network analysis. The model predicted the production of 166 metabolites by LGG and ECN probiotics across amino acid, carbohydrate/energy, and nucleotide metabolism with antimicrobial functions. The predictive accuracy of the metabolic flux analysis highlights the novel utility for profiling probiotic supplements as dietary-based antimicrobial alternatives in the control of AMR pathogen growth.

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