The Integration of Proteomics and Metabolomics Data Paving the Way for a Better Understanding of the Mechanisms Underlying Microbial Acquired Drug Resistance

Antibacterial activity and mechanism of luteolin isolated from Lophatherum gracile Brongn. against multidrug-resistant Escherichia coli

Infections caused by multidrug-resistant (MDR) bacteria have become a major challenge for global healthcare systems. The search for antibacterial compounds from plants has received increasing attention in the fight against MDR bacteria. As a medicinal and edible plant, Lophatherum gracile Brongn. (L. gracile) has favorable antibacterial effect. However, the main antibacterial active compound and its antimicrobial mechanism are not clear. Here, our study first identified the key active compound from L. gracile as luteolin. Meanwhile, the antibacterial effect of luteolin was detected by using the broth microdilution method and time-kill curve analysis. Luteolin can also cause morphological structure degeneration and content leakage, cell wall/membrane damage, ATP synthesis reduction, and downregulation of mRNA expression levels of sulfonamide and quinolones resistance genes in multidrug-resistant Escherichia coli (MDR E. coli). Furthermore, untargeted UPLC/Q-TOF-MS-based metabolomics analysis of the bacterial metabolites revealed that luteolin significantly changed riboflavin energy metabolism, bacterial chemotaxis cell process and glycerophospholipid metabolism of MDR E. coli. This study suggests that luteolin could be a potential new food additive or preservative for controlling MDR E. coli infection and spread.

Identifying and mathematically modeling the time-course of extracellular metabolic markers associated with resistance to ceftolozane/tazobactam in Pseudomonas aeruginosa

Extracellular bacterial metabolites have potential as markers of bacterial growth and resistance emergence but have not been evaluated in dynamic in vitro studies. We investigated the dynamic metabolomic footprint of a multidrug-resistant hypermutable Pseudomonas aeruginosa isolate exposed to ceftolozane/tazobactam as continuous infusion (4.5 g/day, 9 g/day) in a hollow-fiber infection model over 7-9 days in biological replicates (n = 5). Bacterial samples were collected at 0, 7, 23, 47, 71, 95, 143, 167, 191, and 215 h, the supernatant quenched, and extracellular metabolites extracted. Metabolites were analyzed via untargeted metabolomics, including hierarchical clustering and correlation with quantified total and resistant bacterial populations. The time-courses of five (of 1,921 detected) metabolites from enriched pathways were mathematically modeled. Absorbed L-arginine and secreted L-ornithine were highly correlated with the total bacterial population (r -0.79 and 0.82, respectively, P<0.0001). Ribose-5-phosphate, sedoheptulose-7-phosphate, and trehalose-6-phosphate correlated with the resistant subpopulation (0.64, 0.64, and 0.67, respectively, P<0.0001) and were likely secreted due to resistant growth overcoming oxidative and osmotic stress induced by ceftolozane/tazobactam. Using pharmacokinetic/pharmacodynamic-based transduction models, these metabolites were successfully modeled based on the total or resistant bacterial populations. The models well described the abundance of each metabolite across the differing time-course profiles of biological replicates, based on bacterial killing and, importantly, resistant regrowth. These proof-of-concept studies suggest that further exploration is warranted to determine the generalizability of these findings. The metabolites modeled here are not exclusive to bacteria. Future studies may use this approach to identify bacteria-specific metabolites correlating with resistance, which would ultimately be extremely useful for clinical translation.

Multi-Omics Profiling of Candida albicans Grown on Solid Versus Liquid Media

Candida albicans is a common pathogenic fungus that presents a challenge to healthcare facilities. It can switch between a yeast cell form that diffuses through the bloodstream to colonize internal organs and a filamentous form that penetrates host mucosa. Understanding the pathogen's strategies for environmental adaptation and, ultimately, survival, is crucial. As a complementary study, herein, a multi-omics analysis was performed using high-resolution timsTOF MS to compare the proteomes and metabolomes of Wild Type (WT) Candida albicans (strain DK318) grown on agar plates versus liquid media. Proteomic analysis revealed a total of 1793 proteins and 15,013 peptides. Out of the 1403 identified proteins, 313 proteins were significantly differentially abundant with a p-value < 0.05. Of these, 156 and 157 proteins were significantly increased in liquid and solid media, respectively. Metabolomics analysis identified 192 metabolites in total. The majority (42/48) of the significantly altered metabolites (p-value 0.05 FDR, FC 1.5), mainly amino acids, were significantly higher in solid media, while only 2 metabolites were significantly higher in liquid media. The combined multi-omics analysis provides insight into adaptative morphological changes supporting Candida albicans' life cycle and identifies crucial virulence factors during biofilm formation and bloodstream infection.

Translating eco-evolutionary biology into therapy to tackle antibiotic resistance

Antibiotic resistance is currently one of the most important public health problems. The golden age of antibiotic discovery ended decades ago, and new approaches are urgently needed. Therefore, preserving the efficacy of the antibiotics currently in use and developing compounds and strategies that specifically target antibiotic-resistant pathogens is critical. The identification of robust trends of antibiotic resistance evolution and of its associated trade-offs, such as collateral sensitivity or fitness costs, is invaluable for the design of rational evolution-based, ecology-based treatment approaches. In this Review, we discuss these evolutionary trade-offs and how such knowledge can aid in informing combination or alternating antibiotic therapies against bacterial infections. In addition, we discuss how targeting bacterial metabolism can enhance drug activity and impair antibiotic resistance evolution. Finally, we explore how an improved understanding of the original physiological function of antibiotic resistance determinants, which have evolved to reach clinical resistance after a process of historical contingency, may help to tackle antibiotic resistance.

Alanine-Dependent TCA Cycle Promotion Restores the Zhongshengmycin-Susceptibility in Xanthomonas oryzae

Xanthomonas oryzae pv. oryzicola (Xoo) is a plant pathogenic bacterium that can cause rice bacterial blight disease, which results in a severe reduction in rice production. Antimicrobial-dependent microbial controlling is a useful way to control the spread and outbreak of plant pathogenic bacteria. However, the abuse and long-term use of antimicrobials also cause microbial antimicrobial resistance. As far as known, the mechanism of antimicrobial resistance in agricultural plant pathogenic bacteria still lacks prospecting. In this study, we explore the mechanism of Zhongshengmycin (ZSM)-resistance in Xoo by GC-MS-based metabolomic analysis. The results showed that the down-regulation of the TCA cycle was characteristic of antimicrobial resistance in Xoo, which was further demonstrated by the reduction of activity and gene expression levels of key enzymes in the TCA cycle. Furthermore, alanine was proven to reverse the ZSM resistance in Xoo by accelerating the TCA cycle in vivo. Our results are essential for understanding the mechanisms of ZSM resistance in Xoo and may provide new strategies for controlling this agricultural plant pathogen at the metabolic level.