Bacteria of the genus Shigella, consisting of 4 species and Ͼ50 serotypes, cause shigellosis, a foodborne disease of significant morbidity, mortality, and economic loss worldwide. Classical Shigella identification based on selective media and serology is tedious, time-consuming, expensive, and not always accurate. A molecular diagnostic assay does not distinguish Shigella at the species level or from enteroinvasive Escherichia coli (EIEC). We inspected genomic sequences from 221 Shigella isolates and observed low concordance rates between conventional designation and molecular serotyping: 86.4% and 80.5% at the species and serotype levels, respectively. Serotype determinants for 6 additional serotypes were identified. Examination of differentiation gene markers commonly perceived as characteristic hallmarks in Shigella showed high variability among different serotypes. Using this information, we developed ShigaTyper, an automated workflow that utilizes limited computational resources to accurately and rapidly determine 59 Shigella serotypes using Illumina paired-end whole-genome sequencing (WGS) reads. Shigella serotype determinants and species-specific diagnostic markers were first identified through read alignment to an in-house curated reference sequence database. Relying on sequence hits that passed a threshold level of coverage and accuracy, serotype could be unambiguously predicted within 1 min for an average-size WGS sample of ϳ500 MB. Validation with WGS data from 380 isolates showed an accuracy rate of 98.2%. This pipeline is the first step toward building a comprehensive WGS-based analysis pipeline of Shigella spp. in a field laboratory setting, where speed is essential and resources need to be more cost-effectively dedicated. IMPORTANCE Shigella causes diarrheal disease with serious public health implications. However, conventional Shigella identification methods are laborious and timeconsuming and can be erroneous due to the high similarity between Shigella and enteroinvasive Escherichia coli (EIEC) and cross-reactivity between serotyping antisera. Further, serotype interpretation is complicated for inexperienced users. To develop an easier method with higher accuracy based on whole-genome sequencing (WGS) for Shigella serotyping, we systematically examined genomic information of Shigella isolates from 53 serotypes to define rules for differentiation and serotyping. We created ShigaTyper, an automated pipeline that accurately and rapidly excludes non-Shigella isolates and identifies 59 Shigella serotypes using Illumina paired-end WGS reads. A serotype can be unambiguously predicted at a data processing speed of 538 MB/min with 98.2% accuracy from a regular laptop. Once it is installed, training in bioinformatics analysis and Shigella genetics is not required. This pipeline is particularly useful to general microbiologists in field laboratories.

Rab monomeric GTPases regulate specific aspects of vesicle transport in eukaryotes including coat recruitment, uncoating, fission, motility, target selection and fusion. Moreover, individual Rab proteins function at specific sites within the cell, for example the ER, golgi and early endosome. Importantly, the localization and function of individual Rab subfamily members are often conserved underscoring the significant contributions that model organisms such as Caenorhabditis elegans can make towards a better understanding of human disease caused by Rab and vesicle trafficking malfunction. With this in mind, a bioinformatics approach was first taken to identify and classify the complete C. elegans Rab family placing individual Rabs into specific subfamilies based on molecular phylogenetics. For genes that were difficult to classify by sequence similarity alone, we did a comparative analysis of intron position among specific subfamilies from yeast to humans. This two-pronged approach allowed the classification of 30 out of 31 C. elegans Rab proteins identified here including Rab31/Rab50, a likely member of the last eukaryotic common ancestor (LECA). Second, a molecular toolset was created to facilitate research on biological processes that involve Rab proteins. Specifically, we used Gateway-compatible C. elegans ORFeome clones as starting material to create 44 full-length, sequence-verified, dominant-negative (DN) and constitutive active (CA) rab open reading frames (ORFs). Development of this toolset provided independent research projects for students enrolled in a research-based molecular techniques course at California State University, East Bay (CSUEB).

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The objective of this study was to develop a rapid, simple method for enhanced detection and isolation of low levels of Escherichia coli O157:H7 from leafy produce and surface water using recirculating immunomagnetic separation (RIMS) coupled with real-time PCR and a standard culture method. The optimal enrichment conditions for the method also were determined. Analysis of real-time PCR data (C(T) values) suggested that incubation of lettuce and spinach leaves rather than rinsates provides better enrichment of E. coli O157:H7. Enrichment of lettuce or spinach leaves at 42 degrees C for 5 h provided better detection than enrichment at 37 degrees C. Extended incubation of surface water for 20 h at 42 degrees C did not improve the detection. The optimized enrichment conditions were also employed with modified Moore swabs, which were used to sample flowing water sites. Positive isolation rates and real-time PCR results indicated an increased recovery of E. coli O157:H7 from all samples following the application of RIMS. Under these conditions, the method provided detection and/or isolation of E. coli O157:H7 at levels as low as 0.07 CFU/g of lettuce, 0.1 CFU/g of spinach, 6 CFU/100 ml of surface water, and 9 CFU per modified Moore swab. During a 6-month field study, modified Moore swabs yielded high isolation rates when deployed in natural watershed sites. The method used in this study was effective for monitoring E. coli O157:H7 in the farm environment, during postharvest processing, and in foodborne outbreak investigations.