<p>Whole Genome Sequencing of Ceftolozane-Tazobactam and Ceftazidime-Avibactam Resistant <em>Pseudomonas aeruginosa</em> Isolated from a Blood Stream Infection Reveals VEB and Chromosomal Metallo-Beta Lactamases as Genetic Determinants: A Case Report</p>

Abstract Background Traditional methods of outbreak investigations utilize reactive whole genome sequencing (WGS) to confirm or refute the outbreak. We have implemented WGS surveillance and a machine learning (ML) algorithm for the electronic health record (EHR) to retrospectively detect previously unidentified outbreaks and determine the responsible transmission routes. Methods We performed WGS surveillance to identify and characterize clusters of genetically-related Pseudomonas aeruginosa infections during a 24 month period. ML of the EHR was used to identify potential transmission routes. A manual review of the EHR was performed by an infection preventionist to determine the most likely route and results were compared to the ML algorithm. Results We identified a cluster of six genetically related P. aeruginosa cases that occurred during a seven-month period. The ML algorithm identified gastroscopy as a potential transmission route for four of the six patients. Manual EHR review confirmed gastroscopy as the most likely route for five patients. This transmission route was confirmed by identification of a genetically-related P. aeruginosa incidentally cultured from a gastroscope used on four of the five patients. Three infections, two of which were blood stream infections, could have been prevented if the ML algorithm had been running in real-time. Conclusions WGS surveillance combined with a ML algorithm of the EHR identified a previously-undetected outbreak of gastroscope-associated P. aeruginosa infections. These results underscore the value of WGS surveillance and ML of the EHR for enhancing outbreak detection in hospitals and preventing serious infections.

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Comparison of Whole Genome Sequencing and Repetitive Element PCR for Multidrug- Resistant Pseudomonas aeruginosa Strain Typing

Journal of Molecular Diagnostics ◽

10.1016/j.jmoldx.2021.10.004 ◽

2021 ◽

Author(s):

Jennifer K. Spinler ◽

Sabeen Raza ◽

Santosh Thapa ◽

Alamelu Venkatachalam ◽

Tiana Scott ◽

...

Keyword(s):

Pseudomonas Aeruginosa ◽

Whole Genome Sequencing ◽

Genome Sequencing ◽

Repetitive Element ◽

Multidrug Resistant ◽

Whole Genome ◽

Strain Typing

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Identifying Genetic Determinants of Atopic Dermatitis and Bacterial Colonization Using Whole Genome Sequencing

Journal of Allergy and Clinical Immunology ◽

10.1016/j.jaci.2014.12.1903 ◽

2015 ◽

Vol 135 (2) ◽

pp. AB391 ◽

Cited By ~ 2

Author(s):

Rasika A. Mathias ◽

Sameer Chavan ◽

Kruthika R. Iyer ◽

Nicholas M. Rafaels ◽

Meher Boorgula ◽

...

Keyword(s):

Atopic Dermatitis ◽

Whole Genome Sequencing ◽

Genome Sequencing ◽

Bacterial Colonization ◽

Whole Genome ◽

Genetic Determinants

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77 Whole genome sequencing of multiple isolates of the Pseudomonas aeruginosa Liverpool epidemic strain reveals transmission and geographical clustering

Journal of Cystic Fibrosis ◽

10.1016/s1569-1993(15)30254-x ◽

2015 ◽

Vol 14 ◽

pp. S77

Author(s):

M. Moore ◽

D. Williams ◽

S. Paterson ◽

N. Tucker ◽

D. Kenna ◽

...

Keyword(s):

Pseudomonas Aeruginosa ◽

Whole Genome Sequencing ◽

Genome Sequencing ◽

Whole Genome ◽

Epidemic Strain ◽

Geographical Clustering

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Whole-Genome Sequencing Allows for Improved Identification of Persistent Listeria monocytogenes in Food-Associated Environments

Applied and Environmental Microbiology ◽

10.1128/aem.01049-15 ◽

2015 ◽

Vol 81 (17) ◽

pp. 6024-6037 ◽

Cited By ~ 76

Author(s):

Matthew J. Stasiewicz ◽

Haley F. Oliver ◽

Martin Wiedmann ◽

Henk C. den Bakker

Keyword(s):

Listeria Monocytogenes ◽

Whole Genome Sequencing ◽

Genome Sequencing ◽

Whole Genome Sequence ◽

Whole Genome ◽

Genetic Determinants ◽

Single Nucleotide ◽

Content Type ◽

Food Borne ◽

Clonal Spread

ABSTRACTWhile the food-borne pathogenListeria monocytogenescan persist in food associated environments, there are no whole-genome sequence (WGS) based methods to differentiate persistent from sporadic strains. Whole-genome sequencing of 188 isolates from a longitudinal study ofL. monocytogenesin retail delis was used to (i) apply single-nucleotide polymorphism (SNP)-based phylogenetics for subtyping ofL. monocytogenes, (ii) use SNP counts to differentiate persistent from repeatedly reintroduced strains, and (iii) identify genetic determinants ofL. monocytogenespersistence. WGS analysis revealed three prophage regions that explained differences between three pairs of phylogenetically similar populations with pulsed-field gel electrophoresis types that differed by ≤3 bands. WGS-SNP-based phylogenetics found that putatively persistentL. monocytogenesrepresent SNP patterns (i) unique to a single retail deli, supporting persistence within the deli (11 clades), (ii) unique to a single state, supporting clonal spread within a state (7 clades), or (iii) spanning multiple states (5 clades). Isolates that formed one of 11 deli-specific clades differed by a median of 10 SNPs or fewer. Isolates from 12 putative persistence events had significantly fewer SNPs (median, 2 to 22 SNPs) than between isolates of the same subtype from other delis (median up to 77 SNPs), supporting persistence of the strain. In 13 events, nearly indistinguishable isolates (0 to 1 SNP) were found across multiple delis. No individual genes were enriched among persistent isolates compared to sporadic isolates. Our data show that WGS analysis improves food-borne pathogen subtyping and identification of persistent bacterial pathogens in food associated environments.

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Case Report: Hyper IgM Syndrome Identified by Whole Genome Sequencing in a Young Syrian Man Presenting With Atypical, Severe and Recurrent Mucosal Leishmaniasis

Frontiers in Immunology ◽

10.3389/fimmu.2020.567856 ◽

2020 ◽

Vol 11 ◽

Author(s):

Camilla Heldbjerg Drabe ◽

Rasmus L. Marvig ◽

Line Borgwardt ◽

Jens D. Lundgren ◽

Hanne Vibeke Hansen Maquart ◽

...

Keyword(s):

Case Report ◽

Whole Genome Sequencing ◽

Genome Sequencing ◽

Whole Genome ◽

Hyper Igm Syndrome ◽

Mucosal Leishmaniasis ◽

Hyper Igm

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High-Resolution Analysis by Whole-Genome Sequencing of an International Lineage (Sequence Type 111) of Pseudomonas aeruginosa Associated with Metallo-Carbapenemases in the United Kingdom

Journal of Clinical Microbiology ◽

10.1128/jcm.00505-15 ◽

2015 ◽

Vol 53 (8) ◽

pp. 2622-2631 ◽

Cited By ~ 33

Author(s):

Jane F. Turton ◽

Laura Wright ◽

Anthony Underwood ◽

Adam A. Witney ◽

Yuen-Ting Chan ◽

...

Keyword(s):

Pseudomonas Aeruginosa ◽

United Kingdom ◽

Whole Genome Sequencing ◽

Genome Sequencing ◽

Sequence Type ◽

Polymorphism Analysis ◽

Whole Genome ◽

Evolutionary Analysis ◽

Accessory Gene ◽

The United Kingdom

Whole-genome sequencing (WGS) was carried out on 87 isolates of sequence type 111 (ST-111) of Pseudomonas aeruginosa collected between 2005 and 2014 from 65 patients and 12 environmental isolates from 24 hospital laboratories across the United Kingdom on an Illumina HiSeq instrument. Most isolates (73) carried VIM-2, but others carried IMP-1 or IMP-13 (5) or NDM-1 (1); one isolate had VIM-2 and IMP-18, and 7 carried no metallo-beta-lactamase (MBL) gene. Single nucleotide polymorphism analysis divided the isolates into distinct clusters; the NDM-1 isolate was an outlier, and the IMP isolates and 6/7 MBL-negative isolates clustered separately from the main set of 73 VIM-2 isolates. Within the VIM-2 set, there were at least 3 distinct clusters, including a tightly clustered set of isolates from 3 hospital laboratories consistent with an outbreak from a single introduction that was quickly brought under control and a much broader set dominated by isolates from a long-running outbreak in a London hospital likely seeded from an environmental source, requiring different control measures; isolates from 7 other hospital laboratories in London and southeast England were also included. Bayesian evolutionary analysis indicated that all the isolates shared a common ancestor dating back ∼50 years (1960s), with the main VIM-2 set separating approximately 20 to 30 years ago. Accessory gene profiling revealed blocks of genes associated with particular clusters, with some having high similarity (≥95%) to bacteriophage genes. WGS of widely found international lineages such as ST-111 provides the necessary resolution to inform epidemiological investigations and intervention policies.

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