>> Welcome to Module 3.6,
"Sequencing Strategies for SARS-CoV-2."
This is part of the COVID-19 Genomic Epidemiology Toolkit
from CDC's Office of Advanced Molecular Detection.
My name is Dr. Shatavia Morrison,
and I am a Bioinformatics Unit lead with CDC.
This module introduces some strategies to consider
when deciding when and how to use genome sequencing to assist
with epidemiological surveillance
and investigations of SARS-CoV-2.
Be sure to check out the toolkit's other modules,
which include a combination of case studies
and training materials, to help you get started supplementing
epidemiological data with genomic data.
Modules in Part 1 of this toolkit provide an overview
of the rationale and role for SARS-CoV-2 sequencing
and epidemiological surveillance and investigation.
At the national level, sequencing is important
for monitoring the emergence and distribution of new strains
of SARS-CoV-2 with the potential implications for transmission,
testing, or treatment,
especially after interventions such as vaccination.
At the state and local levels,
genomic data can provide a more granular picture
of the ongoing transmission to support control efforts,
for example by detecting clusters,
investigating outbreaks,
and identifying superspreading events.
US public health laboratories
and territories have made significant strides
in developing capacity for pathogen genome sequencing.
As you can see on the map, the number of states
that have sequencing capacity in red increased
between 2013 and 2020.
However, even in the best-resourced jurisdictions,
sequencing is constrained by cost, not only in materials
but in staff time required to generate
and analyze sequencing data.
It is essential for epidemiologists to stay
in communication with laboratory and bioinformatics colleagues
to set sequencing priorities and adapt them as needed
when conditions change.
To optimize your use of SARS-CoV-2 sequencing,
think first about what you hope to accomplish and then how best
to do so with the resources available.
When we asked epidemiologists and laboratory scientists
in state public health departments how they prioritize
specimens for SARS-CoV-2 sequencing, their answers mapped
to two overarching themes:
targeted outbreak investigations and surveillance.
Outbreak investigations typically start
with an epidemiologically defined group of case-patients
who share characteristics
that increase the risk of transmission.
Examples include people living
in high-risk congregate living settings and those
with shared exposures
that represent a potential superspreader event.
State-level surveillance for emerging strains,
as at the national level, monitors the distribution
and trends in SARS-CoV-2 variants in the population.
Laboratory-based surveillance can select specimens
for sequencing based on test characteristics
such as S-gene target failure on PCR.
This finding is typical of the variant of concern, or VOC,
known as B.1.1.7, or Alpha.
In addition, epidemiological surveillance
of COVID-19 cases can be of particular interest
for sequencing, for example, cases of potential reinfection,
vaccine breakthrough, travel exposure,
or severe COVID-19 in children.
Here are some examples of case studies in the toolkit
that illustrate the motivation for sequencing
and the insights it can provide for epidemiologists involved
in COVID-19 surveillance and outbreak investigations.
You can find these case studies in this section of this toolkit.
We surveyed state and territorial public health labs
to assess their capabilities to sequence for SARS-CoV-2.
When asked for technical considerations that factor
into the selection of specimens for sequencing,
they named genomic completeness, CT thresholds,
and sequencing workflow.
They reported CT values between 28 and 37 as ideal for ensuring
that significant genomic sequencing data could
be recovered.
This schematic is a high-level representation
of the steps involved to generate sequencing data.
The workflow includes both wet lab and dry lab components.
For our purposes, the wet lab component includes the first two
steps, sample collection and sample prep,
where we extract genetic material and prepare it
to be included in the sequencing library.
The dry lab components include the last two steps, sequencing
and bioinformatics analyses, required to produce results
that are useful for genomic epidemiology.
Each of these steps requires trained personnel.
Several US laboratories reported having
about three dedicated personnel for both the wet lab
and dry lab, but in a few instances,
only one person is handling the entire wet lab portion
of this workflow.
CDC is making ongoing efforts to support cross-training
and help labs in this situation get up to speed.
For example, CDC's Technical Outreach and Assistance
to States Team, TOAST,
is providing technical assistance including developing
bioinformatics pipelines and protocols for both wet
and dry labs to help remove barriers.
In addition to the motivation and technical considerations
for sequencing, there are a few more overarching things
that you may want to consider when onboarding sequencing
in your laboratory for SARS-CoV-2.
Let's break this down into people, places, and things.
For the purposes of this module, we will define "people"
as a trained workforce to handle the wet lab
and dry lab components of sequencing
or genomic epidemiology; "places" as laboratory space
to house the sequencing instruments
and perform the necessary operations to generate
and analyze sequencing data; and finally, "things" as the items
such as reagents, tips, and pipettes
for the wet lab components in the computing infrastructure
to handle the dry lab components.
One size does not fit all when it comes
to sequencing strategies and laboratory capacity.
The next set of slides will provide examples of beginner,
intermediate, and advanced laboratories
and their potential capabilities based
on observations around the US.
For the purposes of this module, we will refer to "capacity"
in terms of equipment access, associated supplies,
and personnel needed to perform sequencing.
A beginner lab is one that never or rarely uses sequencing
for surveillance or outbreak investigation.
This lab probably doesn't have sufficient in-house capacity
to handle both the wet lab
and dry lab components for sequencing.
There may be a single person performing both sequencing
and analytics, or perhaps only sequencing library preparation
can be handled on site.
A handful of US public health laboratories have reported they
need to submit some samples or specimens
to a collaborator for sequencing.
This can be an appropriate way to address capacity issues
and should be considered if there are obstacles
to rapidly standing up high-throughput sequencing.
Next, let's take a look at what could be considered
as an intermediate laboratory.
An intermediate lab occasionally uses sequencing for outbreak
and surveillance activities.
This lab probably has more wet lab capacity
than dry lab capacity.
About half of US state laboratories describe themselves
as intermediate.
This can perform sequencing and primary bioinformatics analyses,
however lack capacity for high-throughput processes,
and as a result, they struggle
to handle large increase in sequencing.
Some intermediate labs have addressed this issue
by forming partnerships with labs
with high-throughput capacity.
An advanced lab routinely uses sequencing in outbreak
and surveillance activities on a large scale.
They probably have multiple sequencing instruments,
are able to perform sequencing on hundreds
to thousands of specimens monthly.
They have access
to a high-performance computing environment,
such as cloud computing or a computing cluster.
They also have multiple highly trained staff
who perform specialized wet lab and dry lab tasks.
After generating sequencing data, it's important
to consider submitting them
to a public health repository like GISAID or NCBI.
By uploading your data, you contribute
to the collective knowledge base for open-source resources,
like Nextstrain, which in turn provide essential context
for your own analyses.
Check out Module 3.6 for information
about public repositories for SARS-CoV-2 sequence data
and links to resources.
Be sure to check out your own organization's requirements
and protocols for submitting data.
Now you're ready to integrate genomic sequence data
into your epidemiological investigations, for example,
to identify the most prevalent strains circulating
within your population or to analyze transmission
in an apparent outbreak.
Here are some more toolkit modules that discuss how
to get started with genomic epidemiology.
In this module, we discussed motivations
for sequencing SARS-CoV-2
to enhance epidemiological surveillance investigations.
We outlined a few technical considerations to keep
in mind-like how much of the genome
to sequence (is sequencing the spike protein sufficient?),
sample quality (does the Ct value suggest the success
of sequencing?), and capacity for handling the wet
and dry lab components of sequencing.
Finally, we presented a few different strategies depending
on your laboratory capacity.
Understanding your motivation
and technical capabilities will help you
to ensure you are getting a maximum return
on your sequencing efforts.
This concludes Module 3.6.
Part 3 of this toolkit focuses on useful tools and skills
for using genomic data in epidemiological investigations.
Please visit the COVID-19 Genomic Epidemiology Toolkit
page where you can find further reading on this topic,
as well as a short survey
to provide feedback about this module.
On the toolkit page, you can also subscribe
to our mailing list and receive announcements as new modules
and material are released.
Thank you.