Detecting, mapping, and suppressing the spread of a decade-long Pseudomonas aeruginosa nosocomial outbreak with genomics

Whole-genome sequencing is revolutionizing bacterial outbreak investigation but its application to the clinic remains limited. In 2020, prospective and retrospective surveillance detected a Pseudomonas aeruginosa outbreak with 254 isolates collected from 82 patients in 27 wards of a hospital. Its origin was dated to the late 90s, just after the facility opened, and patient-to-patient and environment-to-patient cases of transmission were inferred. Over time, two epidemic subclones evolved in separate hosts and hospital areas, including newly opened wards, and hospital-wide sampling confirmed reservoirs persisted in the plumbing. Pathoadaptive mutations in genes associated with virulence, cell wall biogenesis, and antibiotic resistance were identified. While the latter correlated with the acquisition of phenotypic resistances to 1st (cephalosporin), 2nd (carbapenems) and 3rd (colistin) lines of treatment, maximum parsimony suggested that a truncation in a lipopolysaccharide component coincided with the emergence of a subclone prevalent in chronic infections. Since initial identification, extensive infection control efforts guided by routine, near real-time surveillance have proved successful at slowing transmission. SIGNIFICANCE STATEMENT Every year, millions of hospital-associated infections are threatening patient lives. This, in a world in which rates of resistances to existing antibiotics are increasing. And this, at a time dubbed the post-antibiotic era when new drugs are scarce. But now is also the golden age of genomics. Here, applying this transformative technology to the clinic revealed an outbreak of Pseudomonas aeruginosa, resistant to last line antibiotics, that had escaped detection for decades. The mapping of transmission chains, through hospital floors, pointed to environmental reservoirs in intensive care units but also provided critical insights into the evolution and adaptation of this pathogen. Genomic data, shared in near real-time with the hospital, resulted in targeted interventions and the prevention of new cases.

Selection on resistance genes and rising prevalence of CRPA due to porin defects.

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Genotypically, outbreak isolates contained no plasmids (based on the finished genomes 1 9 2 of a diverse subset of isolates, Table S1) and, besides an intrinsic AmpC-type β -lactamase, 1 9 3 only carried two acquired resistance genes, known to confer resistance to ciprofloxacin 1 9 4 (crpP) and tobramycin (aac(6')-Ib4) ( Table S1). To explain other phenotypic resistances, 1 9 5 and in the absence of an acquired ESBL or carbapenemase, a genome-wide analysis of non- isolates (Table S5). From a list of 164 genes ( predicted LOF) in 37/164 genes were identified in at least one outbreak isolate (Table S7).
Of particular interest, 8 genes (or functional clusters) were each mutated independently three 2 0 1 or more times (Fig. 4B).

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Though rare, the presence and impact of mutations in genes associated with resistance 2 2 7 to colistin, a last-line antibiotic, was examined. NSY mutations were detected in the TCSs ColRS (three distinct sites in four isolates) (Fig. 4B) and PmrAB (two distinct sites in three 2 2 9 isolates) ( Table S7) but colistin MIC's were the same as wild-type isolates (4 mg/L). By 2 3 0 contrast, patient 2 (who had a history of colistin therapy) acquired a predicted LOF mutation 2 3 1 (E77fs) in sensor protein PhoQ in two serial isolates resulting in an 8-fold increase in MIC 2 3 2 (32 mg/L) (Fig. 4C). Notably, the emergence of this colistin resistant strain, which occurred 2 3 3 in early 2011 (Fig. 2), remained constrained to a single patient and no further spread was 2 3 4 detected. Mutational convergence in virulence, cell wall biogenesis and signaling pathways. Genome-wide, 64 genes were each mutated independently two or more times over the 2 3 8 course of this outbreak (Table S5). Compared to the distribution observed for the whole 2 3 9 1 2 genome, these 64 genes were functionally enriched for signal transduction (28% vs 6% in the 2 4 0 whole genome, p<0.05) and cell wall/membrane biogenesis (17% vs 7%, p<0.05) (Fig. 5A).

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ESBLs, carbapenemases) 4-6 , would also fail to detect this ST-621 outbreak clone. Indeed, faucets directing water straight into the drain, similar to those in Facility A (Fig. 3A), have 2 8 7 been linked to increased back splash onto nearby surfaces and medical equipment 26 .

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Besides environmental contamination, reservoirs within patients likely contributed to contaminated with an outbreak clone of P. aeruginosa before the arrival of the first patients 17 .

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One of the most notable features of this outbreak was the evolution of antibiotic for the many independently evolved OprD mutants, one of the most common mechanisms for 3 2 1 carbapenem resistance in P. aeruginosa 11 . Finally, albeit a sporadic event, the emergence of 3 2 2 colistin resistance, through a well characterized mechanism, is a reminder that the threat of 3 2 3 extensively drug resistant P. aeruginosa is only a prescription and a few mutations away 31 .

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The data generated during this study has resulted in various ongoing interventions reported in over 9 months, and the unbiased contemporary data using all P. aeruginosa from 3 2 9 patients at this facility confirms the spread has slowed, with just 3 cases identified in 2022. United States. In total, 253 isolates belonged to the ST-621 outbreak clone.

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Antibiotic susceptibility testing (AST) was performed in a College of American Pathologists (CAP)-accredited lab at Facility A using a Vitek 2 (card GN AST 71 and GN ID; accredited clinical lab as previously described 34 . To evaluate the strength of the temporal signal, TempEst v1.5.3 was utilized to visualize 4 0 9 the relationship between root-to-tip genetic distances for samples with known collection 4 1 0 dates 47 . To date internal nodes of interest on the phylogeny, bayesian phylogenetic inference 4 1 1 was performed using BEAST2 v2.6.5 on a recombination free alignment, removing samples       and Infection Secondary to Imperfect Intensive Care Unit Room Design . Infect.