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Antibiotic Resistance Potential of ESKAPE Pathogens

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Multidrug-resistant (MDR) bacterial infections pose a major health threat and are considered among the leading causes of mortality worldwide. As a result, many pharmaceutical companies have reduced the production of antibiotics. Bacteria can acquire resistance through various mechanisms such as mutations, gene transfer, and amplification of genomic segments. Understanding these mechanisms before antibiotic development can help in designing antibiotics that are less susceptible to bacterial resistance. However, this is a complex problem for three reasons

1. Different molecular mechanisms contribute to antibiotic resistance.

2. Different pathogens need to be studied

3. Different antibiotics need to be tested.

The present study mainly aimed to investigate how new antibiotics differ from older, currently used antibiotics in how bacteria develop resistance. Two approaches were mainly used: laboratory evolution-which involves growing bacteria under lab conditions to study resistance, and functional metagenomics– which involves studying genes from environmental samples to see what resistance genes are already out there and how they might affect antibiotics. Researchers compared new antibiotics (post-2017 or in development) with older, currently used ones to see if bacteria develop resistance differently. The selected antimicrobial compounds mainly targeted Gram-negative bacteria.

Overlap in Resistance Mechanisms Between Current and Emerging Antibiotics

The researchers of the study selected 40 representative strains from 4 Gram-negative bacterial pathogens, including Escherichia coli, K. pneumoniae, A. baumannii, and P. aeruginosa, and measured their effectiveness against 22 in-use antibiotics and 13 antibiotics that were introduced post-2017. 8 strains out of 40 were categorized under extensively drug resistant (XDR). Newer antibiotics showed greater efficacy against these 40 strains when compared to older antibiotics with a similar mode of action.

When the researchers grouped antibiotics based on bacterial response patterns, new and old antibiotics with similar working methods tended to cluster. This suggests that resistance patterns are tied to the antibiotic’s mode of action, not just whether it’s new or old. Multidrug-resistant (MDR) and extensively drug-resistant (XDR) bacteria were less sensitive to old and new antibiotics than drug-sensitive strains of the same species.

Resistance Development in Different Bacterial Species in vitro

The researchers aimed to investigate whether bacteria could rapidly develop resistance to both new (recent) and older (control) antibiotics, rendering them less effective in the long term under laboratory conditions. To investigate this, two types of bacterial strains for each of the four major pathogens were selected.

one MDR (multidrug-resistant) strain
one SEN (drug-sensitive) strain

The pathogens tested were: E. coli, Klebsiella pneumoniae, Pseudomonas aeruginosa, and Acinetobacter baumannii.

Frequency of resistance assay(FoR) was performed to assess first-step antibiotic resistance. This assay revealed that 50% of bacterial populations developed resistance against antibiotics. Resistance frequency and magnitude did not differ between recent and control antibiotics.

Adaptive laboratory evolution (ALE) was employed to capture rarer mutations that standard assays often overlook. Researchers performed ALE over 120 generations to generate highly resistant bacterial populations. ALE allows microbial populations to accumulate mutations under defined growth conditions. Hence, it is particularly helpful to study molecular mechanisms through which bacteria become resistant to new and control antibiotics.

Resistance increased on average by ~64× over ancestors. This assay showed that both new and old antibiotics were equally vulnerable to resistance. Researchers concluded that resistance evolution is strongly shaped by bacterial genetic background in an antibiotic-specific way.

How Bacteria Reuse Mutations to Outsmart Antibiotics?

The study sequenced 516 resistant bacterial lines and identified 1,817 unique mutations. Most mutations were non-synonymous, suggesting selection for resistance, and ~20% were loss-of-function changes. When bacteria evolve resistance in the lab, they accumulate lots of mutations, and many of the same genes get hit repeatedly, even when exposed to different antibiotics. Some of these mutations make bacteria resistant to multiple drugs at once (cross-resistance), which is worrying for newer antibiotics like gepotidacin that were designed to avoid this. Many of the same resistance mutations that appeared in the lab are already present in natural and clinical bacterial isolates, meaning the potential for resistance to new drugs already exists in the real world.

Instead of just looking at mutations within bacterial genomes, the researchers also examined mobile antibiotic resistance genes (ARGs) — bits of DNA that can jump between bacteria. They built libraries from polluted soils, human guts, and clinical samples, and screened them for DNA fragments that could make normally sensitive E. coli and K. pneumoniae resistant. They found 690 fragments that conferred resistance (sometimes up to 256-fold), most of which matched known ARGs involved in inactivation, efflux, or target protection. These genes came from diverse bacterial origins. Clinical samples were the largest source of mobile ARGs, contributing more than half of the resistance fragments. Overall, both new and older antibiotics were similarly affected by mobile ARGs, but some ARGs were flagged as “high risk” because they were mobile, present in human microbiomes, and found in pathogens — making them more likely to spread. Importantly, the mechanisms differ: mutations tended to cause resistance through efflux or target changes, whereas mobile ARGs often relied on antibiotic inactivation.

Health-risk analysis of ARGs

Researchers assessed antibiotic resistance genes (ARGs) for risk based on mobility, presence in human microbiomes, and occurrence in pathogens. About 25% of detected ARGs were classified as potential risk, meaning they could easily spread and fuel multidrug resistance. Some older antibiotics (like apramycin) had very few high-risk ARGs, while recent antibiotics such as sulopenem, cefiderocol, and ceftobiprole already had many, often involving dangerous enzymes like NDM β-lactamases.

Overall evaluation of new antibiotics

An ideal antibiotic should combine broad-spectrum activity, low resistance potential, minimal mobile ARGs, and limited prevalence of resistance mechanisms. None of the tested compounds in this study met all these criteria. Using a composite resistance metric, researchers ranked candidates and found significant variation across classes: membrane-targeting antibiotics appeared less prone to resistance than tetracyclines or topoisomerase inhibitors, though their efficacy still needs improvement.