Development of an amplicon-based sequencing approach in response to the global emergence of mpox.

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.

GalaxyTrakr: a distributed analysis tool for public health whole genome sequence data accessible to non-bioinformaticians.

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.

Effect of manure application on abundance of antibiotic resistance genes and their attenuation rates in soil: field-scale mass balance approach.

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.

GAMBIT (Genomic Approximation Method for Bacterial Identification and Tracking): A methodology to rapidly leverage whole genome sequencing of bacterial isolates for clinical identification.

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.

Rapid Lineage Assignment of Severe Acute Respiratory Syndrome Coronavirus 2 Cases through Automated Library Preparation, Sequencing, and Bioinformatic Analysis.

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.

The use of whole-genome sequencing and development of bioinformatics to monitor overlapping outbreaks of Candida auris in southern Nevada.

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.

TheiaEuk: a species-agnostic bioinformatics workflow for fungal genomic characterization.

Introduction: The clinical incidence of antimicrobial-resistant fungal infections has dramatically increased in recent years. Certain fungal pathogens colonize various body cavities, leading to life-threatening bloodstream infections. However, the identification and characterization of fungal isolates in laboratories remain a significant diagnostic challenge in medicine and public health. Whole-genome sequencing provides an unbiased and uniform identification pipeline for fungal pathogens but most bioinformatic analysis pipelines focus on prokaryotic species. To this end, TheiaEuk_Illumina_PE_PHB (TheiaEuk) was designed to focus on genomic analysis specialized to fungal pathogens. Methods: TheiaEuk was designed using containerized components and written in the workflow description language (WDL) to facilitate deployment on the cloud-based open bioinformatics platform Terra. This species-agnostic workflow enables the analysis of fungal genomes without requiring coding, thereby reducing the entry barrier for laboratory scientists. To demonstrate the usefulness of this pipeline, an ongoing outbreak of C. auris in southern Nevada was investigated. We performed whole-genome sequence analysis of 752 new C. auris isolates from this outbreak. Furthermore, TheiaEuk was utilized to observe the accumulation of mutations in the FKS1 gene over the course of the outbreak, highlighting the utility of TheiaEuk as a monitor of emerging public health threats when combined with whole-genome sequencing surveillance of fungal pathogens. Results: A primary result of this work is a curated fungal database containing 5,667 unique genomes representing 245 species. TheiaEuk also incorporates taxon-specific submodules for specific species, including clade-typing for Candida auris (C. auris). In addition, for several fungal species, it performs dynamic reference genome selection and variant calling, reporting mutations found in genes currently associated with antifungal resistance (FKS1, ERG11, FUR1). Using genome assemblies from the ATCC Mycology collection, the taxonomic identification module used by TheiaEuk correctly assigned genomes to the species level in 126/135 (93.3%) instances and to the genus level in 131/135 (97%) of instances, and provided zero false calls. Application of TheiaEuk to actual specimens obtained in the course of work at a local public health laboratory resulted in 13/15 (86.7%) correct calls at the species level, with 2/15 called at the genus level. It made zero incorrect calls. TheiaEuk accurately assessed clade type of Candida auris in 297/302 (98.3%) of instances. Discussion: TheiaEuk demonstrated effectiveness in identifying fungal species from whole genome sequence. It further showed accuracy in both clade-typing of C. auris and in the identification of mutations known to associate with drug resistance in that organism.

Pathogen genomics in public health laboratories: successes, challenges, and lessons learned from California's SARS-CoV-2 Whole-Genome Sequencing Initiative, California COVIDNet.

The capacity for pathogen genomics in public health expanded rapidly during the coronavirus disease 2019 (COVID-19) pandemic, but many public health laboratories did not have the infrastructure in place to handle the vast amount of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequence data generated. The California Department of Public Health, in partnership with Theiagen Genomics, was an early adopter of cloud-based resources for bioinformatics and genomic epidemiology, resulting in the creation of a SARS-CoV-2 genomic surveillance system that combined the efforts of more than 40 sequencing laboratories across government, academia and industry to form California COVIDNet, California's SARS-CoV-2 Whole-Genome Sequencing Initiative. Open-source bioinformatics workflows, ongoing training sessions for the public health workforce, and automated data transfer to visualization tools all contributed to the success of California COVIDNet. While challenges remain for public health genomic surveillance worldwide, California COVIDNet serves as a framework for a scaled and successful bioinformatics infrastructure that has expanded beyond SARS-CoV-2 to other pathogens of public health importance.

Accelerating bioinformatics implementation in public health.

We have adopted an open bioinformatics ecosystem to address the challenges of bioinformatics implementation in public health laboratories (PHLs). Bioinformatics implementation for public health requires practitioners to undertake standardized bioinformatic analyses and generate reproducible, validated and auditable results. It is essential that data storage and analysis are scalable, portable and secure, and that implementation of bioinformatics fits within the operational constraints of the laboratory. We address these requirements using Terra, a web-based data analysis platform with a graphical user interface connecting users to bioinformatics analyses without the use of code. We have developed bioinformatics workflows for use with Terra that specifically meet the needs of public health practitioners. These Theiagen workflows perform genome assembly, quality control, and characterization, as well as construction of phylogeny for insights into genomic epidemiology. Additonally, these workflows use open-source containerized software and the WDL workflow language to ensure standardization and interoperability with other bioinformatics solutions, whilst being adaptable by the user. They are all open source and publicly available in Dockstore with the version-controlled code available in public GitHub repositories. They have been written to generate outputs in standardized file formats to allow for further downstream analysis and visualization with separate genomic epidemiology software. Testament to this solution meeting the requirements for bioinformatic implementation in public health, Theiagen workflows have collectively been used for over 5 million sample analyses in the last 2 years by over 90 public health laboratories in at least 40 different countries. Continued adoption of technological innovations and development of further workflows will ensure that this ecosystem continues to benefit PHLs.

Development of an amplicon-based sequencing approach in response to the global emergence of human monkeypox virus.

The 2022 multi-country monkeypox (mpox) outbreak concurrent with the ongoing COVID-19 pandemic has 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 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 samples that tested presumptive 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 (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 cycle threshold 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.

Assessment of mold contamination in hurricane-damaged homes in Houston, Texas after sanitization by volunteers.

The purpose of this pilot study was to evaluate the effectiveness of mold sanitation in homes that suffered hurricane-related water damage. After a home is flooded, sanitation of the structure for mold is necessary before the interior of the home can be rebuilt. In this study, homes (n = 6) in Houston, Texas that had been flooded by Hurricane Harvey were sanitized by volunteers. At either 6, 8, 15, 25, 34, or 56 days after the sanitation was completed, a Button™ sampler was used to collect a 48-hour air sample, so that the mold cells in the air could be quantified. Each air sample was then analyzed by quantitative PCR (qPCR) assays for the 36 molds in the Environmental Relative Moldiness Index (ERMI) panel of indicator molds. Quantifying the 36-ERMI molds in air samples results in "ERMI-like" values. The ERMI-like values in the sanitized homes were inversely correlated (Pearson p - value 0.04) with the log of the number of days after the sanitation was completed, an indication that it takes time after sanitation for the mold levels to stabilize. This pilot study demonstrated that the ERMI-like metric was useful in assessing post-sanitation mold levels in previously flooded homes.

Rapid repeat infection of SARS-CoV-2 by two highly distinct delta-lineage viruses.

An instance of sequential infection of an individual with, firstly, the Delta variant and secondly a Delta-sub-lineage has been identified. The individual was found positive for the AY.26 lineage 22 days after being found positive for the Delta [B.1.617.2] variant. The viruses associated with the cases showed dramatic genomic difference, including 31 changes that resulted in deletions or amino acid substitutions. Seven of these differences were observed in the Spike protein. The patient in question was between 30 and 35 years old and had no underlying health conditions. Though singular, this case illustrates the possibility that infection with the Delta variant may not itself be fully protective against a population of SARS-CoV-2 variants that are becoming increasingly diverse.

Draft Genome Sequences of Two Salmonella Strains Isolated from Wild Animals on the Eastern Shore of Virginia.

Antimicrobial-resistant (AMR) Salmonella infections pose a significant public health threat. Here, we announce two draft genomes of Salmonella strains isolated from wildlife harboring an alarming array of antibiotic resistance genes. Continued investigations of these genomes will provide insight into the possible attribution of AMR Salmonella infection of wild animals.