Shiga Toxin–Producing Escherichia coli Transmission
via Fecal Microbiota Transplant
Clinical Infectious Diseases

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.

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Community-acquired in name only: A cluster of carbapenem-resistant Acinetobacter baumannii in a burn intensive care unit and beyond
Infection Control & Hospital Epidemiology

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.

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Plasmids and genes contributing to high-level quinolone resistance in Escherichia coli
International Journal of Antimicrobial Agents

This research on an E. coli strain with a remarkably high resistance to broad-spectrum antibiotics helps us better understand the transmission of antibiotic resistance between strains via plasmids.

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Drug-Resistant E. coli Bacteremia Transmitted by Fecal Microbiota Transplant
The New England Journal of Medicine

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.

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Multiple Copies of qnrA1 on an IncA/C2 Plasmid Explain Enhanced Quinolone Resistance in an Escherichia coli Mutant
Antimicrobial Agents and Chemotherapy

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Abstracts and Posters


epiXact : Rapid, precise and robust bacterial relatedness and outbreak detection from WGS data

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.

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Pilot study of a novel whole-genome sequencing based rapid bacterial identification assay in patients with bacteremia

This is the first proof-of-concept feasibility study in an inpatient clinical setting of our culture-free, species agnostic process using whole genome sequencing and algorithmic tools for identifying the species and antimicrobial resistance profile of a bloodstream infection in real-time. The results suggest the approach is potentially more sensitive and significantly faster than gold standard culture-based diagnostics.

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Blood2Bac: species ID and AMR prediction of bacterial pathogens at low concentrations in blood using a rapid ultra-high enrichment process and nanopore sequencing

This study demonstrated Blood2Bac’s ability, when paired with Keynome, to test for a broad range of infections (50 bacterial species) and recover almost the entirety of the pathogen’s genome directly from whole blood. The results represent a significant advancement over current molecular diagnostic approaches that are limited to testing just a handful of species and recover a very small portion of the pathogen’s genetic code.

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BacDetect: Development of a rapid, ultra-sensitive platform for bacterial detection from blood

To address slow turnaround times related to culture-based diagnostics for blood stream infections, we have developed BacDetect, a rapid DNA amplification-based detection method that determines the presence of gram-positive or gram-negative bacteria in a sample in 30 minutes.

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Democratizing Sequencing for Infection Control: A Scalable, Automated Pipeline for WGS Analysis for Outbreak Detection

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.

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Rapid ultra-high enrichment of bacterial pathogens at low concentration from whole blood for species ID and AMR prediction using Oxford Nanopore sequencing

Blood2BacTM is our species-agnostic culture-free method for enriching bacterial DNA directly from whole blood samples by a factor of 100,000,000. When this is coupled with rapid whole genome sequencing and our algorithmic tools, we can determine bacterial species identification and antimicrobial resistance within hours instead of days with culture.

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Multi-copy qnrA1 Plasmid Causes Elevated Quinolone Resistance in E. coli

Analyzing the role large multi-drug resistance (MDR) plasmids play in cultivating resistance can be tremendously challenging. In this work, we leverage nanopore long-read sequencing to overcome these challenges and produced a complete sequence of an MDR plasmid with multiple copies of resistance genes that appeared to significantly increase resistance to ciprofloxacin in E. coli strains carrying the plasmid.

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Achievement of rapid whole genome coverage of bacterial pathogens at 1 CFU/mL in blood

Using whole genome sequencing for culture-free diagnosis of bacterial bloodstream infections is difficult because very little bacterial DNA is present in a clinical sample. Human DNA outnumbers bacterial DNA by 8-9 orders of magnitude. This work describes how we are able to rapidly enrich and sequence bacterial DNA for diagnosing bacterial bloodstream infections directly from clinical blood samples.

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counterr: Characterization of Context Dependent MinION Sequencing Errors

In this work we described how we used counterr, our lightweight command line tool to characterize the error distributions in both amplified and native microbial ONT MinION sequencing data. Our results confirm a widely held belief that errors in MinION data strongly depend on sequence context. We hope that this improved error characterization can be useful for read error correction.

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Quantification of Predictive Power of Genomic Resistance Locus Databases Reveals Potential Limitations of Marker-Based Diagnostics

Tools that rapidly and accurately predict the antibiotic resistance of a clinical infection promise to allow healthcare providers to quickly provide targeted, effective treatments to patients. However, most emerging diagnostic approaches detect the presence or absence of only a limited panel of resistance markers. In the this work we analyze the power of genomic resistance locus databases to predict the resistance profiles of Staphylococcus aureus, Streptococcus pneumonia, and Mycobacterium tuberculosis clinical isolates.

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