Review outlines collateral-sensitivity strategies for antimicrobial resistance

A 2026 review in Molecular Biology Reports examines how collateral sensitivity could be used to develop alternative strategies against multidrug-resistant bacteria. The review article, published on 16 September 2026 by Rishav Jana and Priyanka Bhowmik, summarizes recent work rather than reporting a new laboratory or clinical study.

According to the published abstract, collateral sensitivity is an evolutionary trade-off in which bacteria resist one antibiotic while becoming more vulnerable to another. The authors describe this vulnerability as a potential means of selecting against resistant isolates, but the abstract does not report efficacy results from human treatment or establish that collateral-sensitivity-guided therapy has been clinically validated.

The review discusses rationally designed approaches for harnessing this trade-off in multidrug-resistant bacteria. Laboratory evolution studies, genome sequencing, deep mutagenesis, artificial intelligence and machine learning are identified as tools that may help devise bespoke strategies. The abstract also states that the article addresses translational barriers to clinical implementation and outlines evidence-based design principles for optimizing collateral-sensitivity-guided therapy.

Only the abstract and publisher preview were available for this report, so the specific studies considered, the extent of laboratory or clinical validation, and the strength of evidence supporting individual design principles could not be assessed. The review is therefore best understood as a synthesis of proposed strategies and implementation challenges, not as evidence of clinical benefit.

Subject of Research: A review of collateral-sensitivity-based strategies for addressing antimicrobial resistance

Article Title: Collateral sensitivity-harnessing microbial vulnerabilities as a solution to antimicrobial resistance

Article References: Jana, R., & Bhowmik, P. (2026). Collateral sensitivity-harnessing microbial vulnerabilities as a solution to antimicrobial resistance. Molecular Biology Reports, 53(1), Article 1586. https://doi.org/10.1007/s11033-026-12752-4

Image Credits: AI Generated

DOI: 10.1007/s11033-026-12752-4

Keywords: collateral sensitivity, antimicrobial resistance, multidrug-resistant bacteria, antibiotic resistance, laboratory evolution, genome sequencing, deep mutagenesis, artificial intelligence, machine learning, clinical translation, Collateral, sensitivity-harnessing