Abstracts

Poster Abstracts
isolates with varying degrees of antimicrobial
resistance. These results will help to shed light
on the role of epigenetics in antimicrobial
resistance.
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DEVELOPMENT OF A BIONUMERICS
DATABASE AND EVALUATION OF AVERAGE
NUCLEOTIDE IDENTITY USING MUMMER
(ANI-M), RIBOSOMAL MULTI-LOCUS
SEQUENCE TYPING (RMLST), AND RPOB
GENE PHYLOGENY FOR IDENTIFICATION OF
ENTERIC BACTERIA BY WHOLE GENOME
SEQUENCE ANALYSIS
G. Williams 1 , J. Pruckler 1 , R. L. Lindsey 1 , L.
Gladney 1 , A. Huang 1 , L. S. Katz 1 , L. Garcia-
Toledo 1 , S. Im 1 , K. Roache 1 , M. Turnsek 1 ,
Z. Kucerova 1 , D. Stripling 1 , H. Martin 1 , B.
Dinsmore 1 , S. van Duyne 1 , H. Carleton 1 , H.
Pouseele 2 , N. Strockbine 1 , C. Tarr 1 , P. Fields 1 ,
P. Gerner-Smidt 1 , C. Fitzgerald 1 ;
1
Centers for Disease Control and Prevention,
Atlanta, GA, 2 Applied Maths, Sint-Martens-
Latem, BELGIUM.
Background: Conventional phenotypic and
genotypic methods employed for identification
of enteric bacteria, including Campylobacter,
Escherichia, Shigella, Salmonella and Listeria,
are labor-intensive, expensive, and require
multiple workflows. We have begun development
of an Enteric Identification Whole
Genome Sequence (WGS) database. The
PulseNet infrastructure (BioNumerics v 7.5) is
being used to build the database, with the goal
of identifying these enteric bacteria in a single
workflow using WGS. Materials and Methods:
Three different methods are being evaluated
for inclusion in the BioNumerics Enteric
Identification database: 1) Average Nucleotide
Identity using MUMmer (ANI-m), which
describes a pairwise distance between two
genomes, 2) Ribosomal Multi-Locus Sequence
Typing (rMLST), which is a presence/absence
binary phylogeny for ribosomal genes, and 3)
rpoB gene phylogeny, which describes the sequencing
of rpoB and comparing it in a larger
phylogeny. A set of genome assemblies - 157
Campylobacter, 126 Escherichia, 23 Shigella,
and 73 Listeria genomes, representing 23, 5,
4, and 15 species for each genus, respectively
- generated at CDC, provided by external partners,
or publicly available through NCBI were
selected to evaluate the methods. Results:
ANI-m showed identities of ≥95% for members
within a species for the six most common
clinically-relevant Campylobacter species and
≤92% for inter-species comparisons; ≥95%
for members within a species for Escherichia
and Shigella, and ≤90% for inter-species
comparisons; ≥95% for members within a species
for Listeria and ≤91% for inter-species
comparisons. Due to the diversity of its four
lineages, L. monocytogenes had slightly lower
intra-species identity values (≥92%) and interlineage
identity values (≥92% and ≤95%).
Intra-lineage identity values for L. monocytogenes
were consistent with ANI values of other
Listeria species (≥95%). Total allele assignments
for the 53 rMLST loci ranged from 14
to 53 across the validation set, with fewer loci
called for species rarely received at CDC. An
rMLST phylogeny appropriately clustered all
genomes in this evaluation to the species level
when two or more genomes were represented
for a species. Where the full-length rpoB gene
was annotated, phylogenies appropriately clustered
each species, with intra-species similarity
≥91% and ≥95% for subspecies. Conclusions:
This Enteric WGS Identification BioNumerics
database will provide a single, unified,
cost-effective approach for accurate species
identification. Through continued collaboration
with domestic and international partners,
we will continue to test and refine the database
and CLIA validate the reference identification
methods within the next year.
ASM Conference on Rapid Next-Generation Sequencing and Bioinformatic
Pipelines for Enhanced Molecular Epidemiologic Investigation of Pathogens
87