Sequencing

11th Annual Sequencing, Finishing, and Analysis in the Future Meeting
AN EXTENDED CORE GENE MLST TARGET
IDENTIFICATION AND SUBSET SELECTION PIPELINE
FOR CULTURE-INDEPENDENT PATHOGEN
SUBTYPING
Wednesday, 1st June 20:00 La Fonda NM Room (1st floor) Poster (PS‐1b.117)
JoWilliams Newkirk 1 , Eija Trees 2 , John Besser 2 , Heather Carleton 2
1 IHRC, 2 Centers for Disease Control and Prevention
While isolate‐based whole genome sequencing is being rapidly integrated into the US public health
surveillance system, isolate availability for surveillance continues to decline as a result of the adoption
of culture‐independent diagnostic tests by clinical laboratories. As affordable methods are not
yet available for obtaining the same genome resolution directly from shotgun metagenomic sequencing
of clinical samples, particularly microbially complex samples such as stool, alternative methods
are needed to reliably capture genetic information relevant to pathogen subtyping. Targeted amplification
and sequencing of informative genomic regions (i.e. multilocus sequence typing, MLST)
is a well understood and robust typing method whose resolution is limited only by the number of
sites used. Unfortunately, identifying large numbers of informative regions with conserved primer
sites is labor intensive, particularly if hundreds or thousands of reference genomes are used for site
selection.
To facilitate the rapid development of extended MLST schemes for targeted pathogen groups, we
developed a custom pipeline leveraging widely used open source programs to identify potential MLST
targets with conserved primers sites and to find subsets of those targets that recapitulate a reference
phylogeny (user provided or generated by the pipeline from concatenated core genes). Our pipeline
accepts whole genome annotation files from the targeted pathogen group in GenBank (.gbk) format.
Core genes are identified by protein BLAST of all annotated open reading frames (ORFs) from a
single genome against the ORFs from all GenBank files submitted to the pipeline. Hits are filtered
to retain only single copy ORFs which occur in all submitted genomes and are 50% similar across
50% of the query length. Hits found in multiple putative single copy ORF groups are also discarded.
The nucleotide sequences for these core ORFs are aligned in Muscle and trimmed to remove end gaps.
Up to ten conserved primer pairs producing amplicons of ~250 bp are designed for each alignment in
Primer3. The primer pairs and amplicons are filtered to retain only those that do not overlap and
capture polymorphisms between input genomes. Users may either retain all passing amplicons or
use one of two methods to select an optimized subset for typing. The concordance of the subtyping
provided by the selected amplicons to the reference phylogeny can be assessed using a variety metrics,
including those that compare the resulting trees (e.g. Kendall‐Colijn metric) and those that compare
cluster membership (e.g. adjusted Wallace coefficient).
Scripts for the pipeline were written in Python 2.7 and R, and management is provided by bpipe
with support for both standard multicore machines and cluster environments. We demonstrate the
utility of this pipeline using a collection of 266 Salmonella bongori and enterica genomes representing
68 serotypes.
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