FROM THE BENCH
South Carolina Automates WGS for Foodborne
Outbreak Surveillance
By Laura M. Lane, PhD, Molecular Microbiology Lab Supervisor, South Carolina Department of Health and Environmental Control (SC DHEC),
Megan Davis, MS, Microbiology Division Director, SC DHEC, Haley Flores, Laboratory Technologist, SC DHEC and R. Brent Dixon, PhD,
Public Health Laboratory Director, SC DHEC
The common goal of public health
laboratories (PHLs) is to provide
specialized laboratory testing for the
accurate screening, diagnosis, prevention
and surveillance of disease, foodborne
illness and congenital disorders to
improve public health and quality of
life. In line with this goal, whole genome
sequencing (WGS) has produced genomic
information that has been instrumental
in identifying congenital disorders,
recognizing mutations involved in
cancer progression and tracking disease
outbreaks. While WGS is often associated
with sequencing human genomes, its
scalability, applicability to all organisms
and ability to produce large volumes of
high-resolution data have made it the
leading method for performing bacterial
foodborne disease surveillance and
tracking outbreaks internationally.
Compared to pulse-field gel
electrophoresis (PFGE), WGS is highly
sensitive and data collected is much
more detailed. This data can be used
for outbreak clustering, to identify
molecular commonalities among
resistant microbiological strains
and to determine early intervention
points within food safety.
Although WGS brings major advances
in data quality and quantity, it still
has its challenges. Avoiding sample
contamination and preparation errors,
improving staff competency training
and developing proactive method
improvement procedures all contribute
to addressing quality control challenges
that arise during WGS. This summary
highlights how the implementation of
automated WGS preparation techniques
addresses some of WGS’ most common
wet lab challenges.
18
LAB MATTERS Summer 2019
Library Preparation
Sequencing clinical samples with the Illumina MiSeq. Photo:
SC PHL
Samples processed using
automated WGS methodologies can
be managed in greater numbers
(up to 96 samples at a time)
with a large decrease in error.
Sample Processing
High-quality sample DNA input is
paramount to successful WGS, as most
library preparation protocols depend
on accurate input DNA and precise
quantifications to obtain optimal
fragment sizes, sample coverage, cluster
density, etc. Impurities and poor template
DNA quality can also be problematic;
they negatively affect many enzymatic
stages during WGS library preparation.
To improve the efficiency of WGS
DNA extraction protocols, automated
DNA extractors, such as the Qiagen
QIAcube, offer high-throughput DNA
extraction options and improve sequence
concentration and purity. Automation
of this WGS step also reduces cross
contamination of samples, which
subsequently lessens the number of
samples that have to be re-sequenced.
During WGS library preparation,
extracted sample DNA is sheared,
either mechanically or enzymatically,
and tagged with a universal overhang
(i.e., adapters and indices (barcodes)).
Samples then undergo several cycles
of PCR amplification in preparation
for sequencing. During this process,
indices are individually added to
samples to create unique combinations
so that samples can be identified post-
sequencing. Errors during manual
addition of indices can lead to missing
barcodes on samples and/or samples
that share the same index combination.
This affects downstream analysis of
sequencing data as some samples could
contain non-index reads while others
could be indistinguishable from each
other.
The Eppendorf epMotion ® 5075 liquid
handler provides an automated solution
that reduces errors arising from manual
index assignment. Prior to sample library
preparation, an index plate containing
multiple unique index combinations
is created by the epMotion ® , and this
plate is then used to add unique index
combinations to samples in an automated
fashion. This ensures that each sample
receives a distinctive barcode for
sequencing.
Tagmentation, which involves
transposons cleaving and tagging double-
stranded DNA with a universal overhang,
determines the success of the library prep,
since libraries that are too small (<200bp)
or too large (>1.2kb) do not cluster well
on the flow cell. A second challenge
observed during WGS library preparation
involves over- or under-tagmentation of
sample DNA. This can occur for a number
of reasons (poor initial DNA quality,
enzymatic inhibitors, etc.) but, more
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