Abstracts

Poster Abstracts
when compared with hqSNPs inferred on
uncorrected reads. In a cluster of Salmonella
Paratyphi B var. (L+) tartrate+, the Bayes-
Hammer-cleaned reads and FastX-trimmed
reads yielded 314 and 311 informative hqSNP
positions, respectively. In the same set, the
uncorrected reads yielded 292 informative
hqSNP positions, unexpectedly outperforming
the Quake-cleaned reads with 241 hqSNP
positions. In the fifth data set, a cluster of E.
coli O157:H7, FastX-trimmed reads yielded
66 hqSNP positions and Quake-cleaned reads
yielded 65 hqSNP positions. BayesHammercleaned
reads and uncorrected reads both performed
worse for the O157:H7 set, with 61 and
59 hqSNP postions, respectively. In the Enteritidis
and Baildon sets, BayesHammer-corrected
reads yielded hqSNP phylogenies with
median bootstrap support values, 61% and
24%, respectively, across all internal branches
of each tree. By comparison, FastX-trimmed or
untrimmed reads had a median bootstrap support
of at least 49% for the Baildon cluster and
0% bootstrap support for the Enteritidis cluster.
For the Paratyphi B hqSNP phylogeny, median
bootstrap values were 100% across all four
read-trimming methods, but ranged from 1%
support in the untrimmed tree up to 20% support
in the FastX tree. Quake-corrected reads
yielded hqSNP trees with the highest median
bootstrap values for the Salmonella Newport
cluster (median support = 51%) and the E. coli
O157 cluster (median support =27%). These
results indicate that BayesHammer enables
discovery of the largest numbers of hqSNPs
and while BayesHammer and Quake both perform
well for inferring hqSNPs phylogenetic
trees. Yet, as Quake may decrease the counts
of phylogenetically-informative SNP positions,
BayesHammer and FastX are likely the best
first-pass cleaning/correction tools for hqSNPs
pipelines.
n 85
EVALUATION OF WHOLE GENOME
SEQUENCING TO CONFIRM OR REFUTE
CLONALITY OF CONVENTIONAL GENOTYPE-
DEFINED CLUSTERS OF MYCOBACTERIUM
TUBERCULOSIS
L. Cowan, J. Posey;
Centers for Disease Control and Prevention,
Atlanta, GA.
Since 2004, the Division of Tuberculosis Elimination
has conducted genotyping surveillance
of Mycobacterium tuberculosis. Genotyping
data is integrated with patient demographic
and clinical data and routinely analyzed to
identify suspected outbreaks. However, the
discriminatory power of the current genotyping
methods are sometimes insufficient, and some
suspected outbreaks identified by genotyping
include a mix of outbreak and sporadic cases
or do not represent an outbreak. Genomic surveillance
has the power to increase the accuracy
of outbreak detection systems by analyzing
the entire genome versus less than 1% using
conventional methods. We conducted whole
genome sequencing (WGS) for 20 (number of
isolates per cluster, 10 - 100) suspected large
outbreaks identified by routine genotyping.
Reference-guided assemblies of Illumina sequence
read sets were created using LaserGene
SeqMan NGen (DNAStar). Polymorphisms
between the clustered isolates were identified
by comparing assembled genomes including
coverage statistics read depth and distribution
of base calls for reliable differences. The final
set of polymorphisms were confirmed in each
assembly by visually checking each position in
the mapped reads of the assembly. The number
of single nucleotide polymorphisms (SNPs)
identified for each cluster ranged from 8 to
101. WGS exhibited a higher level of resolution
for each cluster as compared to conventional
genotyping methods and identified cases
that were not involved in recent transmission
among the samples analyzed. The preliminary
results indicate that WGS data could result in
more focused targeting of limited public health
ASM Conference on Rapid Next-Generation Sequencing and Bioinformatic
Pipelines for Enhanced Molecular Epidemiologic Investigation of Pathogens
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