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A Candida auris outbreak has been ongoing in Southern Nevada since August 2021. In this manuscript we describe the sequencing of over 200 C. auris isolates from patients at several facilities. Genetically distinct subgroups of C. auris were detected from Clade I (3 distinct lineages) and III (1 lineage). Open-source bioinformatic tools were developed and implemented to aid in the epidemiological investigation. The work herein compares three methods for C. auris whole genome analysis: Nullarbor, MycoSNP and a new pipeline TheiaEuk. We also describe a novel analysis method focused on elucidating phylogenetic linkages between isolates within an ongoing outbreak. Moreover, this study places the ongoing outbreaks in a global context utilizing existing sequences provided worldwide. Lastly, we describe how the generated results were communicated to the epidemiologists and infection control to generate public health interventions., Competing Interests: Authors FA, MS, KL and JS were employed by Theiagen Consulting LLC. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Gorzalski, Ambrosio, Massic, Scribner, Siao, Hua, Dykema, Schneider, Njoku, Libuit, Sevinsky, Van Hooser, Pandori and Hess.)

The 2022 multicountry mpox outbreak concurrent with the ongoing Coronavirus Disease 2019 (COVID-19) pandemic further highlighted the need for genomic surveillance and rapid pathogen whole-genome sequencing. While metagenomic sequencing approaches have been used to sequence many of the early mpox infections, these methods are resource intensive and require samples with high viral DNA concentrations. Given the atypical clinical presentation of cases associated with the outbreak and uncertainty regarding viral load across both the course of infection and anatomical body sites, there was an urgent need for a more sensitive and broadly applicable sequencing approach. Highly multiplexed amplicon-based sequencing (PrimalSeq) was initially developed for sequencing of Zika virus, and later adapted as the main sequencing approach for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). Here, we used PrimalScheme to develop a primer scheme for human monkeypox virus that can be used with many sequencing and bioinformatics pipelines implemented in public health laboratories during the COVID-19 pandemic. We sequenced clinical specimens that tested presumptively positive for human monkeypox virus with amplicon-based and metagenomic sequencing approaches. We found notably higher genome coverage across the virus genome, with minimal amplicon drop-outs, in using the amplicon-based sequencing approach, particularly in higher PCR cycle threshold (Ct) (lower DNA titer) samples. Further testing demonstrated that Ct value correlated with the number of sequencing reads and influenced the percent genome coverage. To maximize genome coverage when resources are limited, we recommend selecting samples with a PCR Ct below 31 Ct and generating 1 million sequencing reads per sample. To support national and international public health genomic surveillance efforts, we sent out primer pool aliquots to 10 laboratories across the United States, United Kingdom, Brazil, and Portugal. These public health laboratories successfully implemented the human monkeypox virus primer scheme in various amplicon sequencing workflows and with different sample types across a range of Ct values. Thus, we show that amplicon-based sequencing can provide a rapidly deployable, cost-effective, and flexible approach to pathogen whole-genome sequencing in response to newly emerging pathogens. Importantly, through the implementation of our primer scheme into existing SARS-CoV-2 workflows and across a range of sample types and sequencing platforms, we further demonstrate the potential of this approach for rapid outbreak response., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: NDG is a consultant for Tempus Labs and the National Basketball Association for work related to COVID-19. All other authors have declared that no competing interests exist., (Copyright: © 2023 Chen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The coronavirus disease 2019 (COVID-19) pandemic has provided a stage to illustrate that there is considerable value in obtaining rapid, whole-genome-based information about pathogens. This article describes the utility of a commercially available, automated severe acute respiratory syndrome associated coronavirus 2 (SARS-CoV-2) library preparation, genome sequencing, and a bioinformatics analysis pipeline to provide rapid, near-real-time SARS-CoV-2 variant description. This study evaluated the turnaround time, accuracy, and other quality-related parameters obtained from commercially available automated sequencing instrumentation, from analysis of continuous clinical samples obtained from January 1, 2021, to October 6, 2021. This analysis included a base-by-base assessment of sequencing accuracy at every position in the SARS-CoV-2 chromosome using two commercially available methods. Mean turnaround time, from the receipt of a specimen for SARS-CoV-2 testing to the availability of the results, with lineage assignment, was <3 days. Accuracy of sequencing by one method was 100%, although certain sites on the genome were found repeatedly to have been sequenced with varying degrees of read error rate., (Copyright © 2023 Association for Molecular Pathology and American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.)

Whole genome sequencing (WGS) of clinical bacterial isolates has the potential to transform the fields of diagnostics and public health. To realize this potential, bioinformatic software that reports identification results needs to be developed that meets the quality standards of a diagnostic test. We developed GAMBIT (Genomic Approximation Method for Bacterial Identification and Tracking) using k-mer based strategies for identification of bacteria based on WGS reads. GAMBIT incorporates this algorithm with a highly curated searchable database of 48,224 genomes. Herein, we describe validation of the scoring methodology, parameter robustness, establishment of confidence thresholds and the curation of the reference database. We assessed GAMBIT by way of validation studies when it was deployed as a laboratory-developed test in two public health laboratories. This method greatly reduces or eliminates false identifications which are often detrimental in a clinical setting., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Lumpe et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: Processing and analyzing whole genome sequencing (WGS) is computationally intense: a single Illumina MiSeq WGS run produces ~ 1 million 250-base-pair reads for each of 24 samples. This poses significant obstacles for smaller laboratories, or laboratories not affiliated with larger projects, which may not have dedicated bioinformatics staff or computing power to effectively use genomic data to protect public health. Building on the success of the cloud-based Galaxy bioinformatics platform ( http://galaxyproject.org ), already known for its user-friendliness and powerful WGS analytical tools, the Center for Food Safety and Applied Nutrition (CFSAN) at the U.S. Food and Drug Administration (FDA) created a customized 'instance' of the Galaxy environment, called GalaxyTrakr ( https://www.galaxytrakr.org ), for use by laboratory scientists performing food-safety regulatory research. The goal was to enable laboratories outside of the FDA internal network to (1) perform quality assessments of sequence data, (2) identify links between clinical isolates and positive food/environmental samples, including those at the National Center for Biotechnology Information sequence read archive ( https://www.ncbi.nlm.nih.gov/sra/ ), and (3) explore new methodologies such as metagenomics. GalaxyTrakr hosts a variety of free and adaptable tools and provides the data storage and computing power to run the tools. These tools support coordinated analytic methods and consistent interpretation of results across laboratories. Users can create and share tools for their specific needs and use sequence data generated locally and elsewhere., Results: In its first full year (2018), GalaxyTrakr processed over 85,000 jobs and went from 25 to 250 users, representing 53 different public and state health laboratories, academic institutions, international health laboratories, and federal organizations. By mid-2020, it has grown to 600 registered users and processed over 450,000 analytical jobs. To illustrate how laboratories are making use of this resource, we describe how six institutions use GalaxyTrakr to quickly analyze and review their data. Instructions for participating in GalaxyTrakr are provided., Conclusions: GalaxyTrakr advances food safety by providing reliable and harmonized WGS analyses for public health laboratories and promoting collaboration across laboratories with differing resources. Anticipated enhancements to this resource will include workflows for additional foodborne pathogens, viruses, and parasites, as well as new tools and services.

Objectives: The use of fluoroscopy for indirect guidance in orthopaedic trauma surgery has increased. The purpose of this investigation was to assess how real-time visualization of radiation exposure impacts dose levels during orthopaedic trauma operations., Design: Observational comparative study., Setting: Level 1 trauma center orthopaedic trauma surgery operating room., Patients/participants: The participants in this study were 83 patients with fractures of the ankle, tibia, femur, or acetabulum receiving definitive surgical fixation of their fracture; children under 18 years of age were excluded from the study. Fellowship trained orthopaedic trauma surgeons, resident orthopaedic surgeons, radiology technicians, and scrub nurses involved in the operations on included fracture patients were also participants., Intervention: Real-time radiation exposure feedback from the Philips DoseAware device., Main Outcome Measurements: Radiation exposure from fluoroscopy compared between phase 1, during which participants were blinded to exposure levels, and phase 2, during which participants were able to see exposure levels in real time., Results: Overall mean radiation exposure was decreased by 60% in phase 2 compared with phase 1 (P = 0.023). Mean surgeon (MS; average of primary and assistant surgeon) and mean nonsurgeon personnel (average of x-ray technician, scrub nurse, and patient) radiation exposures were decreased from phase 1 to phase 2, by 58% and 80%, respectively (MS, P = 0.034; mean nonsurgeon personnel, P = 0.043). From phase 1 to phase 2, MS radiation for femoral shaft fractures decreased by 80% or 162.0 μSv (P = 0.02) and by 81% or 128.9 μSv (P = 0.014) for acetabular fractures., Discussion: Our data demonstrate that real-time visualization of radiation exposure during orthopaedic trauma operations can decrease radiation exposure in the highest exposure cases. Further research is necessary to determine whether the reduction in radiation exposure is sustained over time and to understand how real-time radiation exposure data mitigates exposure., Level of Evidence: Therapeutic Level III. See Instructions for Authors for a complete description of levels of evidence.

The development of models for understanding antibiotic resistance gene (ARG) persistence and transport is a critical next step toward informing mitigation strategies to prevent the spread of antibiotic resistance in the environment. A field study was performed that used a mass balance approach to gain insight into the transport and dissipation of ARGs following land application of manure. Soil from a small drainage plot including a manure application site, an unmanured control site, and an adjacent stream and buffer zone were sampled for ARGs and metals before and after application of dairy manure slurry and a dry stack mixture of equine, bovine, and ovine manure. Results of mass balance suggest growth of bacterial hosts containing ARGs and/or horizontal gene transfer immediately following slurry application with respect to ermF, sul1, and sul2 and following a lag (13 days) for dry-stack-amended soils. Generally no effects on tet(G), tet(O), or tet(W) soil concentrations were observed despite the presence of these genes in applied manure. Dissipation rates were fastest for ermF in slurry-treated soils (logarithmic decay coefficient of -3.5) and for sul1 and sul2 in dry-stack-amended soils (logarithmic decay coefficients of -0.54 and -0.48, respectively), and evidence for surface and subsurface transport was not observed. Results provide a mass balance approach for tracking ARG fate and insights to inform modeling and limiting the transport of manure-borne ARGs to neighboring surface water.