Hunter, E. | Search bioRxiv

bioRxiv2018

Evaluation of whole genome sequencing for the identification and typing of Vibrio cholerae

Epidemiological and microbiological data on Vibrio cholerae isolated between 2004 and 2017 (n=836) and held in the Public Health England culture archive were reviewed. The traditional biochemical species identification and serological typing results were compared with the genome derived species identification and serotype for a sub-set of isolates (n=152). Of the 836 isolates, 750 (89.7%) were from faecal specimens, 206 (24.6%) belonged to serogroup O1 and seven (0.8%) were serogroup O139, and 792 (94.7%) isolates from patients reporting recent travel abroad, most commonly to India (n=209) and Pakistan (n=104). Of the 152 isolates of V. cholerae speciated by kmer identification, 149 (98.1%) were concordant with the traditional biochemical approach. Traditional serotyping results were 100% concordant with the whole genome sequencing (WGS) analysis for identification of serogroups O1 and O139 and Classical and El Tor biotypes. ctxA was detected in all isolates of V. cholerae O1 El Tor and O139 belonging to sequence type (ST) 69, and in V. cholerae O1 Classical variants belonging to ST73. A phylogeny of isolates belonging to ST69 from UK travellers clustered geographically, with isolates from India and Pakistan located on separate branches. Moving forward, WGS data from UK travellers will contribute to global surveillance programs, and the monitoring of emerging threats to public health and the global dissemination of pathogenic lineages. At the national level, these WGS data will inform the timely reinforcement of direct public health messaging to travellers and mitigate the impact of imported infections and the associated risks to public health.

microbiology↗

bioRxiv2018

OMEGA: a software tool for the management, analysis, and dissemination of intracellular trafficking data that incorporates motion type classification and quality control

MOTIVATIONParticle tracking coupled with time-lapse microscopy is critical for understanding the dynamics of intracellular processes of clinical importance. Spurred on by advances in the spatiotemporal resolution of microscopy and automated computational methods, this field is increasingly amenable to multi-dimensional high-throughput data collection schemes (Snijder et al., 2012). Typically, complex particle tracking datasets generated by individual laboratories are produced with incompatible methodologies that preclude comparison to each other. There is therefore an unmet need for data management systems that facilitate data standardization, meta-analysis, and structured data dissemination. The integration of analysis, visualization, and quality control capabilities into such systems would eliminate the need for manual transfer of data to diverse downstream analysis tools. At the same time, it would lay the foundation for shared trajectory data, particle tracking, and motion analysis standards. RESULTSHere, we present Open Microscopy Environment inteGrated Analysis (OMEGA), a cross-platform data management, analysis, and visualization system, for particle tracking data, with particular emphasis on results from viral and vesicular trafficking experiments. OMEGA provides intuitive graphical interfaces to implement integrated particle tracking and motion analysis workflows while providing easy to use facilities to automatically keep track of error propagation, harvest data provenance and ensure the persistence of analysis results and metadata. Specifically, OMEGA: 1) imports image data and metadata from data management tools such as the Open Microscopy Environment Remote Objects (OMERO; Allan et al., 2012); 2) tracks intracellular particles movement; 3) facilitates parameter optimization and trajectory results inspection and validation; 4) performs downstream trajectory analysis and motion type classification; 5) estimates the uncertainty propagating through the motion analysis pipeline; and, 6) facilitates storage and dissemination of analysis results, and analysis definition metadata, on the basis of our newly proposed FAIRsharing.org complainant Minimum Information About Particle Tracking Experiments (MIAPTE; Rigano and Strambio-De-Castillia, 2016; 2017) guidelines in combination with the OME-XML data model (Goldberg et al., 2005). In so doing, OMEGA maintains a persistent link between raw image data, intermediate analysis steps, the overall analysis output, and all necessary metadata to repeat the analysis process and reproduce its results. Availability and implementationOMEGA is a cross-platform, open-source software developed in Java. Source code and cross-platform binaries are freely available on GitHub at https://github.com/OmegaProject/Omega (doi: 10.5281/zenodo.2535523), under the GNU General Public License v.3. Contactcaterina.strambio@umassmed.edu and alex.rigano@umassmed.edu Supplementary informationSupplementary Material is available at BioRxiv.org

bioinformatics↗