Metabolic Disruption Alters Ribosomal Protein Levels, Enhancing Aminoglycoside Tolerance in E. coli

Core Concepts

Genetic perturbations in the tricarboxylic acid (TCA) cycle and electron transport chain (ETC) of E. coli lead to increased tolerance to aminoglycoside antibiotics, which is not primarily attributed to reduced drug uptake or membrane potential dysregulation, but rather to downregulation of ribosomal proteins and biosynthesis.

Abstract

The study investigated the impact of gene knockouts associated with the TCA cycle and NADH dehydrogenase enzyme on aminoglycoside tolerance in E. coli MG1655. Several knockout strains exhibited increased tolerance to streptomycin, gentamicin, and amikacin compared to the wild-type strain, though some mutants like Δicd, ΔacnB, and ΔfumA did not consistently show enhanced tolerance, highlighting the complex relationship between energy metabolism and antibiotic tolerance.
The researchers focused on four selected mutant strains (ΔsucA, ΔgltA, ΔnuoI, and Δicd) and found that the increased tolerance in ΔsucA, ΔgltA, and ΔnuoI mutants was not linked to altered cell growth, but rather appeared to be transient or reversible, as all mutants regained sensitivity to aminoglycosides during the lag phase of growth.
Further investigations revealed that the observed aminoglycoside tolerance was not primarily due to reduced energy-dependent drug uptake or membrane potential dysregulation. Proteomic analysis, however, unveiled significant downregulation of proteins associated with ribosomal subunits, translation factor activities, protein export mechanisms, and ribonucleoside monophosphate biosynthesis in the mutant strains exhibiting higher gentamicin tolerance (ΔsucA, ΔgltA, and ΔnuoI). This suggests that the altered levels of ribosomal proteins may contribute to the observed aminoglycoside tolerance in these mutants.

Stats

The surviving cell fractions of the wild-type and mutant strains after treatment with 50 μg/ml streptomycin, 50 μg/ml gentamicin, and 50 μg/ml amikacin for 5 hours.
The ATP levels of the wild-type and mutant strains during the mid-exponential and early stationary growth phases.
The cytoplasmic pH of the wild-type and mutant strains during the mid-exponential and early stationary phases.
The fluorescence intensity of DiSC3(5) dye, which indicates membrane potential, in the wild-type and mutant strains before and after gentamicin treatment.

Quotes

"Genetic perturbations in these strains may have decreased proton motive force (PMF) and aminoglycoside uptake."
"Our comprehensive analysis, which encompassed protein-protein association networks and functional enrichment, unveiled a noteworthy upregulation of proteins linked to the TCA cycle in the mutant strains during the mid-exponential growth phase, suggesting that these strains compensate for the perturbation in their energy metabolism by increasing TCA cycle activity to maintain their membrane potential and ATP levels."
"Our pathway enrichment analysis shed light on local network clusters displaying downregulation across all mutant strains, which were associated with both large and small ribosomal binding proteins, ribosome biogenesis, translation factor activity, and the biosynthesis of ribonucleoside monophosphates."

Key Insights Distilled From

METABOLIC DISRUPTION IMPAIRS RIBOSOMAL PROTEIN LEVELS, RESULTING IN ENHANCED AMINOGLYCOSIDE TOLERANCE

by Shiraliyev,R... at www.biorxiv.org 12-21-2023

https://www.biorxiv.org/content/10.1101/2023.12.20.572673v3

Deeper Inquiries

How might the observed downregulation of ribosomal proteins and biosynthesis in the mutant strains be leveraged to develop novel strategies for combating aminoglycoside-tolerant bacterial infections?

The downregulation of ribosomal proteins and biosynthesis in the mutant strains provides a valuable insight into the mechanisms underlying aminoglycoside tolerance. This observation suggests that targeting ribosomal function and protein synthesis could be a promising strategy to combat aminoglycoside-tolerant bacterial infections. By understanding the specific proteins and pathways that are downregulated in these mutants, researchers can develop targeted therapies that disrupt ribosomal function in a way that is detrimental to the survival of aminoglycoside-tolerant bacteria. This approach could involve the development of novel antibiotics or combination therapies that specifically target the ribosomal machinery in aminoglycoside-tolerant strains, thereby enhancing the efficacy of treatment and reducing the likelihood of antibiotic resistance.

What other cellular processes or pathways, beyond energy metabolism and ribosomal function, could potentially contribute to the observed aminoglycoside tolerance in the mutant strains?

In addition to energy metabolism and ribosomal function, several other cellular processes and pathways could potentially contribute to the observed aminoglycoside tolerance in the mutant strains. One such pathway is the efflux pump system, which allows bacteria to actively pump out antibiotics from the cell, reducing their intracellular concentration and efficacy. Mutations or upregulation of efflux pump genes could confer resistance to aminoglycosides in the mutant strains. Furthermore, alterations in cell wall permeability, membrane composition, and stress response pathways could also play a role in aminoglycoside tolerance. For example, changes in the outer membrane structure or the activation of stress response mechanisms could impact the ability of aminoglycosides to enter the cell and exert their bactericidal effects.

Given the complex and strain-specific responses to genetic perturbations, how can a more comprehensive understanding of bacterial metabolic networks and their interactions with antibiotic tolerance mechanisms be achieved to inform the development of effective antimicrobial therapies?

To achieve a more comprehensive understanding of bacterial metabolic networks and their interactions with antibiotic tolerance mechanisms, a multi-faceted approach is essential. This approach could involve integrating omics data, such as genomics, transcriptomics, proteomics, and metabolomics, to elucidate the intricate network of cellular processes involved in antibiotic tolerance. By analyzing the global gene expression patterns, protein interactions, and metabolic pathways in response to antibiotic exposure, researchers can identify key regulatory nodes and potential drug targets for combating antibiotic tolerance. Additionally, advanced computational modeling and systems biology approaches can be employed to simulate and predict the dynamic behavior of bacterial metabolic networks under antibiotic stress. Collaborative efforts between microbiologists, bioinformaticians, and computational biologists are crucial for deciphering the complex interplay between bacterial metabolism and antibiotic tolerance, ultimately leading to the development of more effective antimicrobial therapies.