Proteomic interrogation of antibiotic resistance and persistence in Escherichia coli - progress and potential for medical research

Multi-omics analysis explores the impact of ofloxacin pressure on the metabolic state in Escherichia coli

OBJECTIVES

The rising threat of antibiotic resistance poses a significant challenge to public health. The research on the new direction of resistance mechanisms is crucial for overcoming this hurdle. This study examines metabolic changes by comparing sensitive and experimentally induced ofloxacin-resistant Escherichia coli (E. coli) strains using multi-omics analyses, aiming to provide novel insights into bacterial resistance.

METHODS

An ofloxacin-resistant E. coli strain was selected by being exposed to high concentration of ofloxacin. Comparative analyses involving transcriptomics, proteomics, and acetylomics were conducted between the wild-type and the ofloxacin-resistant (Re-OFL) strains. Enrichment pathways of differentially expressed genes, proteins and acetylated proteins between the two strains were analysed using gene ontology and Kyoto Encyclopedia of Genes and Genomes method. In addition, the metabolic network of E. coli was mapped using integrated multi-omics analysis strategies.

RESULTS

We identified significant differences in 2775 mRNAs, 1062 proteins, and 1015 acetylated proteins between wild-type and Re-OFL strains. Integrated omics analyses revealed that the common alterations enriched in metabolic processes, particularly the glycolytic pathway. Further analyses demonstrated that 14 metabolic enzymes exhibited upregulated acetylation levels and downregulated transcription and protein levels. Moreover, seven of these metabolic enzymes (fba, tpi, gapA, pykA, sdhA, fumA, and mdh) were components related to the glycolytic pathway.

CONCLUSIONS

The changes of metabolic enzymes induced by antibiotics seem to be a key factor for E. coli to adapt to the pressure of antibiotics, which shed new light on understanding the adaptation mechanism when responding to ofloxacin pressure.

Proteome profiling of evolved methicillin-resistant Staphylococcus aureus strains with distinct daptomycin tolerance and resistance phenotypes

Methicillin-resistant Staphylococcus aureus (MRSA) is a highly dangerous pathogen, and daptomycin has been increasingly used to treat its infections in clinics. Recently, several groups have shown that tolerance and resistance of microbes can evolve rapidly under cyclic antibiotic exposure. We have previously shown that the same tolerance and resistance development occurs in MRSA treated with daptomycin in an adaptive laboratory evolution (ALE) experiment. In the present study, we performed proteomic analysis to compare six daptomycin-tolerant and resistant MRSA strains that were evolved from the same ancestral strain. The strain with a higher tolerance level than the others had the most different proteome and response to antibiotic treatment, resembling those observed in persister cells, which are small subpopulations of bacteria that survive lethal antibiotics treatment. By comparing the proteome changes across strains with similar phenotypes, we identified the key proteins that play important roles in daptomycin tolerance and resistance in MRSA. We selected two candidates to be confirmed by gene overexpression analysis. Overexpression of EcsA1 and FabG, which were up-regulated in all of the tolerant evolved strains, led to increased daptomycin tolerance in wild-type MRSA. The proteomics data also suggested that cell wall modulations were implicated in both resistance and tolerance, but in different ways. While the resistant strains had peptidoglycan changes and a more positive surface charge to directly repel daptomycin, the tolerant strains possessed different cell wall changes that do not involve the peptidoglycan nor alterations of the surface charge. Overall, our study showed the differential proteome profiles among multiple tolerant and resistant strains, pinpointed the key proteins for the two phenotypes and revealed the differences in cell wall modulations between the daptomycin-tolerant/resistant strains.

Functional analysis of Escherichia coli K12 toxin-antitoxin systems as novel drug targets using a network biology approach

Bacterial resistance to various drugs and antibiotics has become a significant issue in the fight against infectious diseases. Due to the presence of diverse toxin-antitoxin (TA) systems, bacteria undergo adaptive metabolic alterations and can tolerate the effects of drugs and antibiotics. Bacterial TA systems are unique and can be therapeutic targets for developing new antimicrobial agents, owing to their ability to influence bacterial fate. With this background, our study aims to identify novel drug targets against Escherichia coli K12 MG1655 antitoxin using homology modelling approach. In this study, the protein-protein interaction network of 87 E. coli K12 MG1655 TA systems identified through literature mining was screened for the identification of hub proteins. The model evaluation, assessment, and homology modelling of the hub proteins were evaluated. Furthermore, computer-aided mathematical models of selected phytochemicals have been tested against the identified hub proteins. The TA system was functionally enriched in regulation of cell growth, negative regulation of cell growth, regulation of mRNA stability, mRNA catabolic process and RNA phosphodiester bond hydrolysis. RelE, RelB, MazE, MazF, MqsR, MqsA, and YoeB were identified as hub proteins. The robustness and superior quality of the RelB and MazE modelled structure were discovered by model evaluation, quality assessment criteria, and homology modelling of hub proteins. Clorobiocin was found to be a strong inhibitor by docking these modelled structures. Clorobiocin could be utilized as an antibacterial agent against multidrug resistant E. coli which may inactivate antitoxins and cause programmed cell death.