Ralstonia pickettii and Pseudomonas aeruginosa Bloodstream Infections Associated with Contaminated Extracorporeal Membrane Oxygenation Water Heater DevicesBaker AM et al.Clinical Infectious Diseases May 2022
After tracking a rash of unusual infections, Brigham and Women’s Hospital’s infection control team called on epiXact, our rapid, whole-genome sequencing (WGS) service using single-nucleotide polymorphism analysis, to help trace outbreak strains of Burholderia, Ralstonia picketti and Pseudomonas aeruginosa. With the high resolution offered by WGS, the infection control team was able to conclusively link the outbreak with (ECMO) water heater devices which would have been otherwise challenging due to the prevalence of multiple species collected from various locations.VIEW PUBLICATION
Cluster of Burkholderia cepacia Complex Infections Associated with Extracorporeal Membrane Oxygenation Water Heater Devices
Rhee et al. Clinical Infectious Diseases 2022 March.
Our epiXact healthcare-associated infection (HAI) service helped Brigham and Women’s hospital link a cluster of Burkholderia cepacia complex infections in cardiothoracic ICU patients to contaminated Extracorporeal Membrane Oxygenation Water Heater Devices.
Shiga Toxin–Producing Escherichia coli Transmission via Fecal Microbiota Transplant
Zellmer et al. Clinical Infectious Diseases 2021 June, Vol 72, Issue 11.
Our epiXact service for healthcare-associated infections (HAIs) confirmed the first known report of an undetected transmission of Shiga toxin-producing E. coli (STEC) in a fecal microbiota transplantation, despite enzyme-based STEC screening having been performed on donor samples. Following epiXact’s actionable findings, OpenBiome worked, in consultation with the FDA, to implement prospective PCR-based testing to enhance patient safety and avoid future transmissions.
Community-acquired in Name Only: A Cluster of Carbapenem-resistant Acinetobacter Baumannii in a Burn Intensive Care Unit and Beyond
Shenoy et al. Infection Control & Hospital Epidemiology 2020 May;41(5):531-538. doi.org/10.1017/ice.2020.15
Mass General Hospital used our epiXact service to rapidly identify and respond to a highly-resistant A. baumannii outbreak in an ICU burn unit that was initially believed to be caused by community-transmission.
Drug-Resistant E. coli Bacteremia Transmitted by Fecal Microbiota Transplant
DeFilipp et al. The New England Journal of Medicine 2019 October.
Our epiXact service was used by Mass General Hospital to provide high-resolution whole-genome sequencing analysis in less than two days to help uncover the cause of the first known fecal matter transplant patient death.
Abstracts & Posters
Identification of subclinical healthcare-associated clusters of Staphylococcus epidermidis in an orthopedic patient population
Results presented by New England Baptist Hospital (NEBH) on the use of our epiXact PRO service to investigate genetic, epidemiologic, and environmental factors contributing to positive S. epidermidis joint cultures and prosthetic joint infection. S. epidermidis isolates from hip or knee cultures were identified and obtained between 2017-2020 from patients with one or more prior intraarticular procedures from NEBH. Whole-genome sequencing and single nucleotide polymorphism (SNP) based clonality analysis was performed using the epiXact service. This included species identification, in silico multi-locus sequence typing (MLST), phylogenomic analysis, along with genotypic assessment of the prevalence of specific antibiotic resistance and virulence genes.
Validation of epiXact: Robust Bacterial Relatedness and Outbreak Detection Pipeline for WGS Data
Large-scale validation for Clinical Laboratory Improvement Amendments (CLIA ) certification for epiXact, our automated computational pipeline for detecting pathogen relatedness from WGS data. The epiXact pipeline demonstrated high accuracy for determining clonality between bacterial isolates across 5 species achieving 100% analytical sensitivity and 98.5% analytical specificity in determining clonality, and 100% repeatability.
Same-day Transmission Analysis of Nosocomial Transmission Using Nanopore Whole-genome Sequencing
ID Week 2021
This poster demonstrates the utility of the Oxford Nanopore Technologies (ONT) platform, a rapid sequencing technology, for use with our epiXact healthcare-associated infection (HAI) service. ONT sequencing offers many advantages with faster speed and lower costs over short-read technologies that could prove to be an attractive platform for the commercial epiXact service reducing turnaround time from ≥34-46 hours to same day service and pave the way for real-time HAI transmission detection and prospective outbreak warning system.
Uncluttering Case Clusters: Use of Rapid Sequencing to Exclude Transmission Event
Results presented by Mass General Hospital (MGH) on the use of epiXact healthcare-associated infection (HAI) service to investigate a cluster of methicillin-resistant Staphylococcus aureus (MRSA) and a cluster of carbapenem-resistant Enterobacterales (CRE) inpatient nosocomial infections. Whole-genome sequencing results allowed for early discontinuation of cluster investigations and conservation of resources.
EpiXact: Rapid, Precise and Robust Bacterial Relatedness and Outbreak Detection from WGS Data
ASM Conference on Rapid Applied Microbial Next-Generation Sequencing and Bioinformatic Pipelines 2020
This poster analyzes recent results of our epiXact service for healthcare-associated infections (HAIs). The poster highlights results from 24 recent cases of suspected HAIs submitted for epiXact investigation by clinical customers, encompassing a total of 116 bacterial samples across 12 different pathogens. The analysis demonstrated epiXact’s robust ability to detect outbreaks quickly, leveraging the automated and precise algorithm to provide conclusive evidence of 16 outbreak cases within 24-48 hours from sample receipt. With these rapid results, infection control specialists can make timely and accurate decisions to get the infection outbreak back under control.
Democratizing Sequencing for Infection Control: A Scalable, Automated Pipeline for WGS Analysis for Outbreak Detection
SHEA/CDC’s Decennial 2020
This abstract describes how our technology stack for detecting healthcare-associated infections (HAIs) can efficiently analyze large-scale datasets. Including a recent analysis of over 5,000 clinical bacterial samples collected between 2015 and 2019 which uncovered previously unidentified transmission clusters. With this robust technology stack, we can scale to analyze tens of thousands of samples and support infection control teams in performing prospective outbreak detection without the need for specialized computational biology training.