Genomic and Phenotypic Inconsistencies in Pseudomonas aeruginosa Resistome among Intensive Care Patients Provisionally Accepted

Mihails Dolgusevs¹ Nityanand Jain^1* Oksana Savicka¹ Reinis Vangravs² Jevgenijs Bodrenko³ Edvins Bergmanis¹ Dace Zemite⁴ Solvita Selderina² Aigars Reinis¹ Baiba Rozentale¹

• ¹Riga Stradiņš University, Latvia
• ²Riga East University hospital, Latvia
• ³Laboratory “Latvian Centre of Infectious Diseases”, National Microbiology Reference Laboratory, Riga East University Hospital, Latvia
• ⁴Laboratory “Centrala laboratorija", Latvia

Objective
Pseudomonas aeruginosa, a difficult-to-manage nosocomial pathogen, poses a serious threat to clinical outcomes in intensive care (ICU) patients due to its high antimicrobial resistance (AMR). To promote effective management, it is essential to investigate the genomic and phenotypic differences in AMR expression of the isolates.

Methods
A prospective observational study was conducted from July 2022 to April 2023 at Liepaja Regional Hospital in Latvia. The study included all adult patients who were admitted to the ICU and had a documented infection with P. aeruginosa, as confirmed by standard laboratory microbiological testing and short-read sequencing. Since ResFinder is the only sequencing-based database offering antibacterial susceptibility testing (AST) data for each antibiotic, we conducted a comparison of the resistance profile with the results of phenotypic testing, evaluating if ResFinder met the US Food and Drug Administration (FDA) requirements for approval as a new AMR diagnostic test. Next, to improve precision, AST data from ResFinder was compared with two other databases – AMRFinderPlus and RGI. Additionally, data was gathered from environmental samples to inform the implementation of appropriate infection control measures in real time.

Results
Our cohort consisted of 33 samples from 29 ICU patients and 34 environmental samples. The presence of P. aeruginosa infection was found to be associated with unfavourable clinical outcomes. A third of the patient samples were identified as multi-drug resistant isolates. Apart from resistance against colistin, significant discrepancies were observed when phenotypic data were compared to genotypic data. For example, the aminoglycoside resistance prediction of ResFinder yielded a major errors value of 3.03% for amikacin, which was marginally above the FDA threshold. Among the three positive environmental samples, one sample exhibited multiple AMR genes similar to the patient samples in its cluster.

Conclusions
Our findings underscore the importance of utilizing a combination of diagnostic methods for the identification of resistance mechanisms, clusters, and environmental reservoirs in ICUs.