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Identifying pathoadaptation in Pseudomonas aeruginosa using glycopolymer sensor arrays [dataset] Open Access

In-host bacterial evolution presents a major barrier to effective infection management, driving phenotypic adaptations such as antibiotic resistance and altered virulence. Pseudomonas aeruginosa, a key opportunistic pathogen, frequently undergoes rapid evolutionary change during chronic lung infections, complicating diagnosis and treatment. Current strain typing via whole genome sequencing or selective culturing is costly and time-intensive, and the complex relationship between genetic variations and the phenotype displayed makes clinically relevant pathotypes difficult to identify. Here, we report a cross-reactive glycopolymer-based fluorescent sensor array capable of directly identifying phenotypic changes related to in-host evolution in P. aeruginosa. The sensor array can accurately distinguish phenotypic variations arising from single-gene defects and discriminate clinical isolates with known differences in their evolutionary and pathoadaptive trajectories. Notably, our system is also capable of identifying P. aeruginosa isolates as distinct from other bacterial species commonly found in complex polymicrobial lung infections. Our modular platform presents an opportunity to develop sensor arrays which target carbohydrate recognition in a variety of pathogens, offering potential application as a rapid diagnostic tool to inform clinical treatment decisions based on the direct classification of phenotypic profiles.

Descriptions

Resource type

Dataset

Contributors

Mahon, Clare ¹
Leslie, Kathryn ¹
Creator: Johnson, Callum ¹

¹ Durham University, UK

Funder

Engineering and Physical Sciences Research Council [EP/X014479/1; UKRI Future Leaders Fellowship MR/V027018; MoSMED CDT EP/S022791/1]
Challenge Grant (Ref. nr.: NNF19OC0056411)
Clinical research stipend (Ref. nr.: NNF12OC1015920) from the Novo Nordisk Foundation

Research methods

Other description

Keyword

Sensor arrays
Differential sensing
Glycopolymers
Biosensing
Bacterial evolution
Pathoadaptation
Bacterial virulence

Subject

Bacteria--Evolution
Virulence (Microbiology)

Location

Language

Cited in

Identifier

ark:/32150/r1mp48sc83w
doi:10.15128/r1mp48sc83w

Rights

Creative Commons Attribution 4.0 International (CC BY)

Publisher

Durham University

Date Created

File Details

Depositor

C. Johnson

Date Uploaded

12 September 2025, 07:09:22

Date Modified

25 November 2025, 14:11:21

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Characterization

File format: zip (ZIP Format)

Mime type: application/zip

File size: 6299473

Last modified: 2025:11:25 13:52:47+00:00

Filename: Identifying_pathoadaptation_in_Pseudomonas_aeruginosa_using_glycopolymer_sensor_array.zip

Original checksum: eb3a7ab866e05cb7db300da988ee6db2