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11th Annual <strong>Sequencing</strong>, Finishing, and Analysis in the Future Meeting ASSESSING THE SINGLE NUCLEOTIDE POLYMORPHISM (SNP) VARIABILITY OF OUTBREAK STRAINS DURING IN VITRO PASSAGE Wednesday, 1st June 20:00 La Fonda NM Room (1st floor) Poster (PS‐1b.03) Ashley Sabol Centers for Disease Control and Prevention Foodborne bacterial pathogens are responsible for approximately 9.4 million illnesses each year. The mode in which these organisms are passed from environmental or food source to humans can be varied. Furthermore, the rate at which these pathogens change can be identified through molecular subtyping of strains that belong to the same outbreak or source or by passaging them several times in vitro or in vivo. It is important to gain insight on the observed strain variability that may occur due to laboratory manipulations such as culture passages especially after recovery from a patient – in order to accurately distinguish genetic differences (unrelated strains) from background variation resulting from laboratory manipulations. This is particularly important for high resolution methods, such as whole genome sequencing (WGS) which is currently being adopted by the US public health laboratories for routine surveillance and outbreak investigations of foodborne bacterial pathogens. Four outbreak‐associated strains across 4 species Salmonella enterica serovar Newport, Shiga toxinproducing Escherichia coli (STEC) serogroup O157:H7, Vibrio cholerae, and Listeria monocytogenes – were passed 20 times in vitro. Three colony picks were selected at passes 1, 5, 10, 15, & 20 and streaked to blood agar plates. After incubation for 16‐24 hours at 37°C, DNA extractions were performed for each pick, DNA libraries were prepared using the NexteraXT kit (Illumina Inc.) and sequenced paired‐end on the Illumina MiSeq (500 cycles). The high quality single nucleotide polymorphism (hqSNP) calls were determined using Lyve‐Set v1.1.4e (http://github.com/lskatz/Lyve‐SET) at 10x coverage, 75% frequency for Listeria and Vibrio, and 20x coverage, 95% frequency for STEC and Salmonella. SNPs clustered closer than 5 bp were filtered. Over the course of 20 passes, anywhere from 0‐6 hqSNPs were observed among the 15 colony picks sequenced for each strain. The higher number of hqSNP differences for each strain were observed among picks from the later passes (i.e. passes 10‐20). The least number of SNP differences between picks were observed among the STEC colony picks with 0‐1 SNPs observed. The most SNP differences for a single pick were identified for Listeria pass 15, where 4‐6 SNP differences were counted when compared to all other picks for that strain. This study has provided preliminary evidence that WGS data, as measured by hqSNP analysis, remains stable despite of in vitro manipulations and can hence be used to assess genetic relatedness among foodborne bacterial strains during outbreak investigations. Future plans for this study are to expand it to include Campylobacter spp. and an additional Salmonella enterica serotype, as well as exploring different analysis approaches such as whole genome multi‐locus sequence typing (wgMLST). 69
11th Annual <strong>Sequencing</strong>, Finishing, and Analysis in the Future Meeting COMPARISON AND CONSOLIDATION OF VIRULENCE FACTOR DATABASES FOR NEW MODULES IN EDGE BIOINFORMATICS Wednesday, 1st June 20:00 La Fonda NM Room (1st floor) Poster (PS‐1b.04) Logan Voegtly 1 , Chienchi Lo 2 , Po‐E Li 2 , Joseph Anderson 3 , Karen Davenport 2 , Kimberly Bishop Lilly 1 , Theron Hamilton 4 , Patrick Chain 2 1 Naval Medical Research Center; Henry M. Jackson Foundation, 2 Los Alamos National Laboratory, Los Alamos, NM, 3 Naval Medical Research Center; Defense Threat Reduction Agency, 4 Naval Medical Research CenterMD Next generation sequencing (NGS) technology allows for not only rapid detection and identification of pathogens from a variety of sample types, but also rapid genetic characterization. Rapid characterization of pathogenic bacteria and their virulence factors from an isolate or a metagenomic sample is critical for threat detection and biodefense. A key component to virulence factors identification is a well curated database. With new virulence factors being discovered on a regular basis it is necessary to use the most up to date and well documented database possible. The EDGE Bioinformatic software package represents a collaborative effort between Los Alamos National Laboratory and Naval Medical Research Center to provide a user‐friendly bioinformatic software package that enables rapid NGS data analysis, even when resources are limited. To support the development of a virulence factor identification module in EDGE, we have performed comparisons of the existing virulence factors databases (VFDB, PATRIC_VF, MvirDB, and Victors) to determine which databases are most up‐to‐date, most accurate and inclusive, and contain useful metadata about the virulence factors. We have condensed two databases, VFDB and PATRIC_VF, into one database, removing redundant entries at the strain level. This database will be used by a new module in the EDGE Bioinformatics software platform to annotate called genes as virulence factors within an isolate. With the use of software like ShortBRED the database will also be used to generate a profile of the virulence factors that are detected in a metagenomic sample. In an alternative approach, this database will also be used with the STRING protein‐protein network database as input for a novel bioinformatic approach to determine the probability of sample virulence. 70
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Reliable solutions for focused NGS
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Sequencing

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