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Collateral Sensitivity Strongly Connected Components in Real-World Clinical Surveillance Data: Retrospective Detection of Evolutionary Traps in WHO Priority Pathogens

Created on 11 Aug 2026

Authors

Goodman, J.

Abstract

Collateral sensitivity (CS) -- acquisition of resistance to one antibiotic inducing hypersensitivity to another -- offers an evolutionary trap for multidrug-resistant pathogens. A strongly connected component (SCC) in the directed CS graph represents a closed cycle in which every drug is reachable from every other via successive CS edges. Prior evidence for CS SCCs derives exclusively from in vitro experiments; whether such structures exist in clinical surveillance has not been tested. We mined 104,337 antibiotic susceptibility records from BV-BRC spanning four WHO critical-priority pathogens (Klebsiella pneumoniae, Escherichia coli, Staphylococcus aureus, Pseudomonas aeruginosa; 18,821 unique isolates). For each species, we applied Fisher's exact test with Benjamini-Hochberg FDR correction to all ordered antibiotic pairs, detected SCCs via Tarjan's algorithm, and assessed significance by permutation (n = 1,000). Two species yielded qualifying SCCs. In K. pneumoniae (4,286 isolates), a 3-node SCC -- imipenem, meropenem, tetracycline -- was detected (empirical p = 0.001); both carbapenem-tetracycline edges are bidirectional (OR = 1.81-1.82, q < 0.002, n > 850 per edge). In E. coli (6,720 isolates), a bidirectional 2-node SCC links colistin and cefotaxime (OR = 10.13, q = 0.042, n = 87; permutation p = 0.008). The carbapenem CS signal is tetracycline-specific: tigecycline shows co-resistance (OR < 0.35), consistent with its distinct RamA/AcrAB-TolC mechanism. Temporal stratification (2009-2014) confirmed carbapenem-tetracycline ORs of 2.2-2.7 across year bands. S. aureus returned no qualifying SCC. These constitute the first large-scale clinical validation of evolutionary-trap CS structure in surveillance data and motivate experimental follow-up in isogenic models.

Preprint server: bioRxiv
The authors list and abstract were imported from bioRxiv on 11 Aug 2026.

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