Development and evaluation of a novel, semiautomated Clostridium difficile typing platform

We describe a novel, semiautomated Clostridium difficile typing platform that is based on PCR-ribotyping in conjunction with a semiautomated molecular typing system. The platform is reproducible with minimal intra- or interassay variability. This method exhibited a discriminatory index of 0.954 and is therefore comparable to more arduous typing systems, such as pulsed-field gel electrophoresis

Whole-genome analysis of Exserohilum rostratum from an outbreak of fungal meningitis and other infections

Exserohilum rostratum was the cause of most cases of fungal meningitis and other infections associated with the injection of contaminated methylprednisolone acetate produced by the New England Compounding Center (NECC). Until this outbreak, very few human cases of Exserohilum infection had been reported, and very little was known about this dematiaceous fungus, which usually infects plants. Here, we report using whole-genome sequencing (WGS) for the detection of single nucleotide polymorphisms (SNPs) and phylogenetic analysis to investigate the molecular origin of the outbreak using 22 isolates of E. rostratum retrieved from 19 case patients with meningitis or epidural/spinal abscesses, 6 isolates from contaminated NECC vials, and 7 isolates unrelated to the outbreak. Our analysis indicates that all 28 isolates associated with the outbreak had nearly identical genomes of 33.8 Mb. A total of 8 SNPs were detected among the outbreak genomes, with no more than 2 SNPs separating any 2 of the 28 genomes. The outbreak genomes were separated from the next most closely related control strain by ∼136,000 SNPs. We also observed significant genomic variability among strains unrelated to the outbreak, which may suggest the possibility of cryptic speciation in E. rostratum

Tourism and toponymy: Commodifying and Consuming Place Names

Academic geographers have a long history of studying both tourism and place names, but have rarely made linkages between the two. Within critical toponymic studies there is increasing debate about the commodification of place names, but to date the role of tourism in this process has been almost completely overlooked. In some circumstances, toponyms can become tourist sights based on their extraordinary properties, their broader associations within popular culture, or their role as metanyms for some other aspect of a place. Place names may be sights in their own right or ‘markers’ of a sight and, in some cases, the marker may be more significant than the sight to which it refers. The appropriation of place names through tourism also includes the production and consumption of a broad range of souvenirs based on reproductions or replicas of the material signage that denote place names. Place names as attractions are also associated with a range of performances by tourists, and in some cases visiting a place name can be a significant expression of fandom. In some circumstances, place names can be embraced and promoted by tourism marketing strategies and are, in turn, drawn into broader circuits of the production and consumption of tourist space

Pathogen genomics in public health

Rapid advances in DNA sequencing technology (“next-generation sequencing”) have inspired optimism about the potential of human genomics for “precision medicine.” Meanwhile, pathogen genomics is already delivering “precision public health” through more effective investigations of outbreaks of foodborne illnesses, better-targeted tuberculosis control, and more timely and granular influenza surveillance to inform the selection of vaccine strains. In this article, we describe how public health agencies have been adopting pathogen genomics to improve their effectiveness in almost all domains of infectious disease. This momentum is likely to continue, given the ongoing development in sequencing and sequencing-related technologies

PHA4GE quality control contextual data tags:standardized annotations for sharing public health sequence datasets with known quality issues to facilitate testing and training

As public health laboratories expand their genomic sequencing and bioinformatics capacity for the surveillance of different pathogens, labs must carry out robust validation, training, and optimization of wet- and dry-lab procedures. Achieving these goals for algorithms, pipelines and instruments often requires that lower quality datasets be made available for analysis and comparison alongside those of higher quality. This range of data quality in reference sets can complicate the sharing of sub-optimal datasets that are vital for the community and for the reproducibility of assays. Sharing of useful, but sub-optimal datasets requires careful annotation and documentation of known issues to enable appropriate interpretation, avoid being mistaken for better quality information, and for these data (and their derivatives) to be easily identifiable in repositories. Unfortunately, there are currently no standardized attributes or mechanisms for tagging poor-quality datasets, or datasets generated for a specific purpose, to maximize their utility, searchability, accessibility and reuse. The Public Health Alliance for Genomic Epidemiology (PHA4GE) is an international community of scientists from public health, industry and academia focused on improving the reproducibility, interoperability, portability, and openness of public health bioinformatic software, skills, tools and data. To address the challenges of sharing lower quality datasets, PHA4GE has developed a set of standardized contextual data tags, namely fields and terms, that can be included in public repository submissions as a means of flagging pathogen sequence data with known quality issues, increasing their discoverability. The contextual data tags were developed through consultations with the community including input from the International Nucleotide Sequence Data Collaboration (INSDC), and have been standardized using ontologies - community-based resources for defining the tag properties and the relationships between them. The standardized tags are agnostic to the organism and the sequencing technique used and thus can be applied to data generated from any pathogen using an array of sequencing techniques. The tags can also be applied to synthetic (lab created) data. The list of standardized tags is maintained by PHA4GE and can be found at https://github.com/pha4ge/contextual_data_QC_tags. Definitions, ontology IDs, examples of use, as well as a JSON representation, are provided. The PHA4GE QC tags were tested, and are now implemented, by the FDA's GenomeTrakr laboratory network as part of its routine submission process for SARS-CoV-2 wastewater surveillance. We hope that these simple, standardized tags will help improve communication regarding quality control in public repositories, in addition to making datasets of variable quality more easily identifiable. Suggestions for additional tags can be submitted to PHA4GE via the New Term Request Form in the GitHub repository. By providing a mechanism for feedback and suggestions, we also expect that the tags will evolve with the needs of the community.</p

Genomic surveillance reveals multiple introductions of SARS-CoV-2 into Northern California

The COVID-19 pandemic caused by the novel coronavirus SARS-CoV-2 has spread globally, with >52,000 cases in California as of May 4, 2020. Here we investigate the genomic epidemiology of SARS-CoV-2 in Northern California from late January to mid-March 2020, using samples from 36 patients spanning 9 counties and the Grand Princess cruise ship. Phylogenetic analyses revealed the cryptic introduction of at least 7 different SARS-CoV-2 lineages into California, including epidemic WA1 strains associated with Washington State, with lack of a predominant lineage and limited transmission between communities. Lineages associated with outbreak clusters in 2 counties were defined by a single base substitution in the viral genome. These findings support contact tracing, social distancing, and travel restrictions to contain SARS-CoV-2 spread in California and other states

Infectious disease surveillance needs for the United States: lessons from Covid-19

The COVID-19 pandemic has highlighted the need to upgrade systems for infectious disease surveillance and forecasting and modeling of the spread of infection, both of which inform evidence-based public health guidance and policies. Here, we discuss requirements for an effective surveillance system to support decision making during a pandemic, drawing on the lessons of COVID-19 in the U.S., while looking to jurisdictions in the U.S. and beyond to learn lessons about the value of specific data types. In this report, we define the range of decisions for which surveillance data are required, the data elements needed to inform these decisions and to calibrate inputs and outputs of transmission-dynamic models, and the types of data needed to inform decisions by state, territorial, local, and tribal health authorities. We define actions needed to ensure that such data will be available and consider the contribution of such efforts to improving health equity

Development and Validation of an Internationally-Standardized, High-Resolution Capillary Gel-Based Electrophoresis PCR-Ribotyping Protocol for Clostridium difficile

PCR-ribotyping has been adopted in many laboratories as the method of choice for C. difficile typing and surveillance. However, issues with the conventional agarose gel-based technique, including inter-laboratory variation and interpretation of banding patterns have impeded progress. The method has recently been adapted to incorporate high-resolution capillary gel-based electrophoresis (CE-ribotyping), so improving discrimination, accuracy and reproducibility. However, reports to date have all represented single-centre studies and inter-laboratory variability has not been formally measured or assessed. Here, we achieved in a multi-centre setting a high level of reproducibility, accuracy and portability associated with a consensus CE-ribotyping protocol. Local databases were built at four participating laboratories using a distributed set of 70 known PCR-ribotypes. A panel of 50 isolates and 60 electronic profiles (blinded and randomized) were distributed to each testing centre for PCR-ribotype identification based on local databases generated using the standard set of 70 PCR-ribotypes, and the performance of the consensus protocol assessed. A maximum standard deviation of only ±3.8bp was recorded in individual fragment sizes, and PCR-ribotypes from 98.2% of anonymised strains were successfully discriminated across four ribotyping centres spanning Europe and North America (98.8% after analysing discrepancies). Consensus CE-ribotyping increases comparability of typing data between centres and thereby facilitates the rapid and accurate transfer of standardized typing data to support future national and international C. difficile surveillance programs

Future-proofing and maximizing the utility of metadata: The PHA4GE SARS-CoV-2 contextual data specification package

Background The Public Health Alliance for Genomic Epidemiology (PHA4GE) (https://pha4ge.org) is a global coalition that is actively working to establish consensus standards, document and share best practices, improve the availability of critical bioinformatics tools and resources, and advocate for greater openness, interoperability, accessibility, and reproducibility in public health microbial bioinformatics. In the face of the current pandemic, PHA4GE has identified a need for a fit-for-purpose, open-source SARS-CoV-2 contextual data standard. Results As such, we have developed a SARS-CoV-2 contextual data specification package based on harmonizable, publicly available community standards. The specification can be implemented via a collection template, as well as an array of protocols and tools to support both the harmonization and submission of sequence data and contextual information to public biorepositories. Conclusions Well-structured, rich contextual data add value, promote reuse, and enable aggregation and integration of disparate datasets. Adoption of the proposed standard and practices will better enable interoperability between datasets and systems, improve the consistency and utility of generated data, and ultimately facilitate novel insights and discoveries in SARS-CoV-2 and COVID-19. The package is now supported by the NCBI’s BioSample database