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How Nose Swabs Detect New Covid-19 Strains

Scientists from around the world are using nose swabs to track the emergence of SARS-CoV-2 variants. Here's how it works.

Released on 01/27/2022

Transcript

[Narrator] The nose swab's journey seems pretty direct,

going from here, to here, to here.

But before it ends here, its journey may continue

as part of a mapping of genomic sequences.

It's being used by scientists all around the world

to track the emergence of SARS-CoV-2 variants.

Here's how it works.

[dynamic music]

Remember that nose swab you took?

If it was a PCR test,

around five to 10% of them end up here,

in laboratories set up to conduct genomic sequencing.

Genomic sequencing is a process used to analyze

the genetic makeup of viruses.

It's sort of like creating

and then assembling really large puzzles.

The SARS-CoV-2 genome is about 30,000 bases long.

It's an RNA single-stranded positive RNA virus.

And that length, if you just typed out

the As, Us, and Gs, and Cs, it's about the same length

as the US Constitution and Bill of Rights.

[Narrator] All viruses, like SARS-CoV-2,

continually evolve as they replicate.

Those changes in the genetic code are called mutations.

A variant has one or more of these mutations.

Labs continuously analyze the genome of SARS-CoV-2

to keep track of variants

that pose threats to public health.

A lot of the laboratory testing itself

is moving a lot of the twos around.

The example of Contagion gives you a good sense

of what that process kind of looks like on the back end.

[Woman] Blue is virus, and the gold is human,

and the red is the viral attachment protein.

We have tools like Nextstrain, and Microreact,

and others that allow us to put sequence data

into place and time.

For SARS-CoV-2, most labs use an approach

called amplicon sequencing,

which means that small overlapping pieces of the genome

are amplified by PCR,

same sort of approach that is used for testing.

They're sequenced, and then powerful

bioinformatic pipeline algorithms are used

to then put those pieces back together

and compare them to other genomes.

[Narrator] The sequencing is done by a mix of academic

and clinical laboratories,

along with local, state, and federal agencies.

Within two weeks from this sensation,

the sequence is available in public databases.

While lab results will tell you

if you're positive or negative,

they most likely won't tell you what variant you had.

But is there any way to find out?

I think you can probably make an educated guess.

If you were infected over the summer

and fall in the United States,

the high likelihood, just based on the viruses

that were circulating, is that you had a Delta virus.

[Narrator] Genetic sequencing often focuses

on the spike protein, since it's the tool

the virus uses to penetrate cells and spread infection.

Genomic sequencing monitors mutations

and allows scientists to assess how evolving variants

might impact existing treatments.

If a variant emerges, it's classified by the CDC

into four categories, variant being monitored,

variant of interest, variant of concern,

and variant of high consequence.

Let's take a look at Omicron,

which falls into the variant of concern category.

Omicron does look pretty different from both Delta,

as well as many of the viruses that went before it.

It was first identified by public health research groups

in Botswana, in South Africa,

specifically Dr. Moyo and the team

at the Botswana-Harvard AIDS Institute Partnership.

It has an accumulation of 32 documented mutations

in the spike protein,

which sounds like a lot, because it is.

It has that deletion, at residue 69 and 70,

which lead to that as SGTF, S-gene target failure marker,

that is often used to understand where

and how it's transmitted.

That was important with some of the early cases of Omicron,

mostly because a lot of what we've been seeing

in the United States over the course of the summer

and early fall was Delta, which lacked that mutation.

So when you started to see an increasing number

of these SGTF failures, it gave you a good indication

of how much Omicron you're seeing across your sample,

even when you didn't have the sequencing data in hand.

[Narrator] With variants of concern,

existing therapeutics, vaccines, and treatments

all still work to stop the virus's spread.

But it may not be as effective.

The next category, variants of high consequence,

is the most serious.

Now we haven't seen a variant of high consequence yet.

Omicron is much more transmissible

than other reported variants.

It shows evidence of immune evasion,

even among vaccinated individuals.

And it's hitting many communities

and healthcare systems hard.

The specific risk categorization though

shouldn't mean that we treat any of these viruses

with any less seriousness.

[Narrator] The emergence of new variants

also begs the question, what should we call them?

Well, the answer depends on who you ask.

The Pango nomenclature system, that's like B117.

There are next strain nomenclatures

that are more like a named hurricane type of approach.

So those would be like 21A or 21B.

We have usually a year and then a letter.

All of these can be a mouthful.

And so the WHO, over the course of last spring and summer,

brought together a group to help name and designate,

come up with a consistent nomenclature system

for variants of interest and variants of concern.

The names have to be specific, they have to be distinctive.

They have to be easy to pronounce

and search for in multiple languages.

And most importantly, they shouldn't be

associated with a specific place or people.

If you think of viruses like Marburg from Germany,

Norwalk from Ohio,

all of those are viruses that are associated with

the places where they were first identified,

sometimes pretty negatively.

[Narrator] So the WHO decided on Greek letters.

It's hard to imagine the course of this pandemic

without genomic sequencing.

Even if you've never heard of it before,

it's played an important role in monitoring

and adapting to the pandemic's global scale.

I think one of the most important lessons,

at least from the point of view of genomic surveillance,

is that open data and rapid data sharing

is an incredibly useful tool for public health

and pandemic response.

The potential for global public health is really exciting,

but there are a lot of barriers that we have to overcome.

How do we pull all these different types of data together?

How do we actually collect the samples

that we need to collect in a timely way

so that we can get the information that we need?

When you go to a test site and get your nose swabbed,

you're really helping to understand transmission dynamics.

So that'll help us understand not only the virus

that infected you personally,

but also trends in your local region,

in your state, and across the country.

[dynamic music]

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