0:00

This Week in Virology, the

0:02

podcast about viruses, the kind

0:05

that make you sick. From

0:11

Microbe TV, this is Twiv,

0:13

this Week in Virology, episode

0:15

1109, recorded on April 26,

0:22

2024. I'm Vincent Draconiello, and you're

0:24

listening to the podcast all about

0:27

viruses. Joining me today

0:29

from Fort Lee, New Jersey, Dixon

0:31

de Pomier. Hello, Vincent,

0:33

and everybody else. Looking

0:36

at the window, one would assume

0:38

that since the sun is shining and

0:40

the clouds are all puffy, that it's

0:42

a beautiful day out there, but it's a little

0:44

chilly, and it's a little windy. It's

0:47

not a perfect day, but I think I was told by

0:49

the weather report yesterday that

0:51

Sunday will be spectacular. Here

0:54

in Chelsea, it's 15 degrees

0:57

Celsius and sunny. Also joining us

0:59

from Western Massachusetts, Alan Dove. Good

1:01

to be here, and it's 58

1:04

Fahrenheit, 14 C, and we have

1:07

completely clear skies here. It's beautiful.

1:10

Yep. We're expecting Brienne

1:12

to join us, so she

1:14

will pop in at any moment. She may pop in.

1:17

Vincent, you should have said it says 14 degrees, Chelsea.

1:21

Chelsea. That's very good.

1:23

Sometimes you're funny, Dixon. Inadvertent,

1:26

trust me. Try the veal. I'm here all

1:30

week. If you enjoy these

1:32

programs, these science programs, it's

1:37

WC Fields. We

1:39

would love to have your support, yes,

1:42

because we give you science

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as it is, and not fake

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science. So if you like that,

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go to microbe.tv slash contribute

1:53

so we can reach more and more people.

1:56

A few public servants announcements,

1:59

service announcements. PSA for ASV.

2:03

That's today. If you're interested

2:05

in plant virology, there is

2:07

a special plant virology lunch

2:10

to sign up for at

2:12

registration. If you didn't

2:14

sign up, you can

2:16

change your registration by following the instructions

2:18

from your registration receipt. I

2:21

tried to do that. I couldn't figure it out, but maybe

2:23

you'll have better luck. Will they be

2:25

serving an all meat meal at the plant virology

2:27

lunch? Okay. Right. Well, plants. They

2:30

won't eat plants because they like them, right?

2:32

Right. Right. You

2:34

can also change your registration and consider

2:36

registering for a satellite meeting. If

2:39

you register for anyone, you can go to any of

2:41

the five. These happen the day before. The

2:44

day of the meeting begins in the evening

2:47

with a reception and a keynote and that morning are

2:50

the satellites. So there's an

2:52

invertebrate virology, a veterinary

2:55

virus, a study

2:57

in bats using a one health

2:59

lens virology in a global society

3:01

and navigating virology funding opportunities within

3:04

IHNSF and USD. And

3:07

we have another conference, Pandemic Preparedness Achievements.

3:09

Current challenges and new frontiers. This will

3:11

be 11 to 13 November in Trieste,

3:15

Italy, an overview of

3:17

known and emerging viruses, epidemic risk,

3:20

networking and sharing of information. So

3:23

there's a website that we will put in the

3:25

show notes that you can click on to get

3:27

more information. And here's a

3:29

new conference that I

3:32

recently heard about. And,

3:34

you know, I hear about

3:36

I heard about this at the Ian Lipkin

3:39

Symposium a couple of weeks ago. I sat next to

3:41

the organizer and I said, you know, you ought to

3:43

have a twiv at this

3:46

conference. He said, yeah, that's a good idea.

3:48

Can you advertise it? He said, sure, that's

3:50

a good tradeoff. So this is

3:52

called Molecular Determinants of

3:54

Zoonotic Viruses and Beyond. This

3:57

is going to happen in March of 2025. in

4:01

Freiburg, Germany at

4:04

the university and this

4:07

is Institute of

4:09

Virology there in Freiburg. So

4:12

that's next year and things

4:15

like emerged zoonotic viruses,

4:17

virus-host interactions, molecular-host determinants,

4:19

structural biology and microscopy,

4:21

novel vaccine strategies, therapeutic

4:23

intervention. Let's see

4:25

some conserved speakers. No,

4:29

conserved speakers, right? All right, Brian just

4:31

texted me. She's not coming today. Oh.

4:33

All right, but she was on the schedule. So

4:36

we will just proceed without her.

4:38

We'll just have to gut it out for the three of

4:40

us. John Lavon

4:42

Casanova. See, I had my eye on

4:44

him for a twiv. I

4:47

have Dofogarcia Sastre, Johann

4:51

Nitz, Gustavo Palacios, Tony

4:53

Schaunce, Silke Stertz.

4:55

Now, Silke Stertz figures in one

4:58

of today's paper. Silke

5:00

is in Zurich and I had her

5:02

on a twiv there a couple of

5:04

years ago. She

5:06

discovered the MHC molecule

5:08

as a receptor for bat

5:11

influenza virus, Silke Stertz. Isn't that

5:13

a cool name, Silke? Yes. I

5:16

like different names, not

5:19

Alan and Vincent, you know. Well,

5:21

Dixon is pretty different. Dixon is

5:23

pretty good. That's good, but Silke,

5:25

it's so cool. Name some

5:27

other countries. It can be so cool. I really, really

5:29

like it. So there'll be a link for that in

5:31

the show notes as well. And

5:34

don't forget to buy Dixon's book, The

5:36

New City. You can go to dapalma.com. He

5:38

also has a blog post about it that we

5:40

will link to so you can learn more

5:43

information about it. Thank you,

5:45

Vincent. Now, we

5:48

have some, what

5:51

is it called, in the news, courtesy

5:53

of Amy Rosenfeld, and

5:55

we have an article by, in

5:58

the New York Times. It's an opinion by

6:03

Zainep Tufekki. That looks like a

6:05

Turkish name, doesn't it? Could

6:08

be. It's an opinion columnist,

6:10

actually. And actually, it's talking, she

6:13

talks with Rick Bright. And

6:16

so the problem is the headline, this may be

6:18

your last chance to halt bird flu in humans

6:20

and we are blowing it. This is just, what

6:23

do you call it, Alan? Hyperbole?

6:25

Hyperbole when it, clickbait,

6:27

right? Clickbait, yeah. Come

6:30

on! What

6:33

do you mean halt in humans? It isn't

6:35

doing anything in humans, it's not spreading. Anyways,

6:39

a nice picture of a cow. So

6:42

Rick Bright is an expert on H5N1 and there's a fine

6:47

line between one person and ten. By the time

6:50

we've detected ten, it's probably too late. Okay,

6:53

well you know what Rick? What do you

6:55

want us to do? We have antivirals, we

6:57

have vaccines. Would you like us to call

6:59

all the birds on Earth? Anyway,

7:05

that you should go read it if you can get into

7:07

the times. It's good to

7:11

hear other people's opinions.

7:13

Then we have sequences

7:15

of, I can't

7:19

get to this, here we go,

7:21

USDA publishes sequences of H5N1 on

7:23

a publicly available site, 239 sequences

7:26

from the US

7:28

clade that is currently circulating.

7:32

And what

7:34

I think is interesting is that

7:38

these are still, they don't have any

7:40

human signatures yet. Human

7:43

influenza viruses have certain signatures, which you'll actually hear

7:46

about in one of our papers, and

7:48

these don't have it. It's

7:50

clear that all the cow viruses are from,

7:53

you know, they have a similar origin. Marco

7:56

Warby has said, he

7:59

thinks that the virus may been circulating since late

8:01

2023. And certainly

8:04

this episodic in

8:06

wild animals has been happening since then.

8:08

But the humans, why not? Sure. They're

8:10

cows. Cows. And

8:14

we have a report on measles from

8:16

the CDC. You know, we now have

8:18

128 measles

8:20

cases in 20 jurisdictions.

8:25

So that's the new word for state. Because

8:28

it includes Puerto Rico, right? Right. Because

8:30

it could be Puerto Rico, Guam, Wake,

8:32

etc. Yeah, all those things. Okay. Yeah.

8:34

So they refer to jurisdictions. In this

8:37

case, it's all states. So

8:40

70 of these people have been hospitalized

8:43

so far in this outbreak. So this is

8:45

not trivial. So

8:48

it's increasing. And also

8:51

in England, we have an article from the

8:54

UK. Measles

8:56

is at its highest in

8:59

the UK in

9:01

a decade. Now,

9:04

you may say, why is this? Well, when

9:07

people are reluctant

9:09

to vaccinate, which seems to be a trend

9:11

these days, wouldn't you say

9:13

that? Isn't it a kind of

9:16

trend? Yeah. In certain groups, measles

9:18

virus is one of the first to be

9:20

seen because it's highly contagious. And

9:23

you don't, you know, one person

9:25

can infect many others. It

9:27

spreads in very small droplets

9:29

of respiratory excretions. So this

9:32

is why we're seeing them

9:34

first. But it's, you know, other

9:36

viruses will come back as well.

9:38

You know, according to Paul Offit,

9:40

this is a pushback from the

9:42

mandatory COVID vaccination. Now, parents are

9:44

saying, I don't want my kid vaccinated. So, you

9:47

know, almost every state has a religious

9:50

vaccine exemption that you can choose to

9:52

take. And the parents are saying, no,

9:55

my religion says, I can't take

9:57

a vaccine. And, hmm. You

10:00

know the validity of that is questionable but Paul

10:02

said there's only one religion where it's actually written

10:05

in the Whatever the

10:07

document is for the religion that you can't vaccinate

10:09

yourself. The others is just using it as an

10:11

excuse in my opinion Anyway,

10:13

that's that's bad. You know what measles can

10:15

be bad. So I don't understand

10:18

why you wouldn't immunize your kid What

10:21

do you think measles vaccine is gonna

10:23

do it doesn't cause autism that's been

10:25

shown for decades. Come on folks This

10:27

isn't about facts. Oh, right Vincent

10:33

I want to go back to something you said about the the

10:36

h5n1 in cows the only

10:38

thing that ever if I swear a good Excerpt

10:42

her executive summary of

10:44

that on PBS last night and

10:48

All of the people that were giving

10:50

information were Clear

10:53

to say that all they found

10:55

were sequences. Oh the virus.

10:57

They did not find an entire viral particle. They

11:00

did not Consider it. They tried

11:02

to use milk as an infectious

11:04

agent Two birds and

11:06

it didn't work course and they said this

11:08

these are and then they couldn't

11:10

explain where it came from of course So, you

11:13

know if you look at other in fact, the

11:15

cows are infected Make yeah, but where did the cows

11:17

get it though the chickens? Birds

11:19

the chickens get it birds. Duh. Yeah.

11:22

I mean the chickens we knew it was

11:24

in chickens Yeah, I

11:26

mean more migrating migrating wild boar

11:28

migrating birds who happened past the

11:30

dairy herd so the farms in

11:33

some areas are collection

11:35

areas for migrating birds and

11:37

it's true particularly in Israel

11:40

where you have a lot of farming

11:42

in the surrounding and it's all desert and

11:45

You've got these wild birds coming out of Africa and

11:48

that's I mean, that's where the age of the West

11:50

Nile virus first started I think But

11:54

think of all the food that's available on a

11:56

farm to the animals and

11:59

there are other animals animals out there that want to take advantage

12:01

of that as well so that it's

12:03

very easy to make the association as to where it might

12:05

have come from. Yeah, the milk doesn't

12:08

have infection virus in it. Not at all.

12:10

I'm not worried about the milk. I'm worried about the cows

12:12

infecting people. No, but people might get the wrong idea because

12:15

they don't have the truth. But in Ohio, I was just

12:17

in Ohio and they have a lot of infected

12:20

cows there. And then people are getting

12:22

infected, but they said they're mainly getting

12:24

conjunctivitis. And they're people who work with

12:26

cattle. Yeah, they work with cattle, right. Like,

12:30

you guys work with me and I work with

12:32

you and there are people who work with cows.

12:34

But they don't do it over

12:36

a video conference. Where seldom is

12:38

heard. We can get it. We

12:42

can work with cows here at Microbe TV, but

12:44

we don't have a lot of room. No, we

12:46

could use minicows though. They have little minicows. They

12:48

have minicows, really? They do. They

12:50

do. What do you do with a minicow? Tiny

12:53

little cows. They have minipigs, minicows. Are they pets?

12:56

You get tiny amounts of milk. You

12:58

get half, that's right. You get half points.

13:01

By the way, I wanted to, in the

13:03

CDC page about measles, there's

13:06

a chart on vaccine coverage. So there's a

13:08

map of the US and it colors each

13:10

state according to vaccine coverage.

13:14

And so measles requires 90 to

13:17

95% or more coverage with

13:20

vaccine to prevent outbreaks. And

13:23

so California, Montana,

13:27

Nebraska, Maine, New

13:29

York, a bunch of states around

13:31

here. Massachusetts. Massachusetts, Connecticut, Rhode

13:33

Island, Virginia, West Virginia, Delaware, Maryland,

13:35

Tennessee, and Alabama. Are you guys

13:37

proud that I could name them

13:39

by looking at the shape? That's

13:43

good identification of the jurisdictions. The

13:45

jurisdiction. So they're all 95% plus. But then we have a

13:47

lot of states that are 90 to 94. And

13:52

then we have a good number, 1, 2, 3, 4, 5, 6, 7,

13:54

8, 9, 10 states that are less than recipe

14:00

for measles outbreaks. Come

14:03

on, states like, what

14:06

would that be? Ohio. Ohio

14:08

for sure. Wisconsin, Iowa,

14:11

Minnesota. Yeah,

14:14

Georgia, Oklahoma, Colorado, Arizona,

14:16

Idaho, and Hawaii. And

14:19

Hawaii, oh yeah. So

14:22

if anything, this proves that Alan and I

14:24

can recognize states by their shape. There's

14:27

also, I cheated

14:29

a little bit with Iowa because I knew

14:31

it was one of those rectangular Midwestern states.

14:33

Oh, you hover over it. And I hovered

14:35

over it. I didn't do that. I

14:37

didn't do that. But anyway, check that out. That's

14:39

really good. All right,

14:42

we have a snippet and a paper

14:44

for you today. And the

14:46

snippet is a nature communications paper

14:49

called Positive Selection Underlies

14:52

Repeated Knockout of ORF5

14:54

in SARS-CoV-2

14:56

Evolution. And the authors

14:58

are Wagner, Kistler, Perchetti,

15:00

Baker, Frisby, Torres, Aragona,

15:02

Eun, Figgins, Greninger, Akaks,

15:05

Oltin, Roychoudyri, and Bedford. Trevor Bedford

15:07

is a senior author and we

15:09

had Trevor on to live

15:11

last summer at ASV. That is what I

15:13

think you said ORF5. I think it's ORF8.

15:16

Did I say ORF5? You did. I

15:19

wonder why I would do that. I don't know. Well,

15:22

it's ORF8. It is ORF8. It's ORF8.

15:25

And this and the other paper we'll be talking about

15:27

are both open access. And

15:30

the ORF stands for Open Reading

15:32

Frames. So that's the first thing

15:34

I wanted to mention. This is

15:36

a protein encoded by the genome of

15:38

SARS-CoV-2. And now

15:40

proteins can have cool names like spike

15:43

and nucleocapsid protein because we know what

15:45

they do. But ORF8, we

15:47

didn't know what it did. So we just

15:50

called it an open reading frame. It's an open

15:52

reading frame in the sense that it could be

15:54

translated into a protein. We now know that it

15:56

is. And so we just call the protein. Is

15:58

it start codon? stop code on

16:00

all that stuff. Right. Now, I've

16:03

been interested in ORF8 for a long time

16:06

because I heard a talk by Christian Drosten

16:10

back in 2019 or 2018.

16:12

I don't remember when it was in

16:14

Rotterdam at a virus meeting. Well, he

16:16

talked about the fact that this ORF8,

16:18

early in the SARS epidemic

16:20

in 2002-3, right, was

16:26

lost and all subsequent

16:28

isolates had a deletion.

16:31

And there was some

16:33

suggestion that maybe it

16:37

was less virulent in people also. But,

16:39

you know, it was lost early on

16:42

in the outbreak. SARS-1 didn't go very

16:44

far. It went 8,000 cases. And

16:47

I blogged about that in January of 2020. COVID

16:50

was just getting going. And I remember this

16:52

and I heard that SARS-CoV-2 had an ORF8.

16:55

So I said, you know, it'd be interesting

16:57

to see if this thing

16:59

gets deleted in SARS-CoV-2.

17:03

It's completely different ORF8 than the SARS-1,

17:06

though, I presume. Well, it's

17:08

a similar protein. A similar protein.

17:10

Yes. So this paper is

17:12

all about, it turns out that now I

17:14

think over 90% of SARS-CoV-2 isolates have

17:17

lost ORF8. So

17:21

this is a computational paper which

17:23

tries to understand what is driving

17:25

the loss. Right. So

17:27

they presented at the beginning three

17:29

hypotheses. This could just be that

17:32

ORF8 happened to be deleted

17:35

in the context of some other mutation

17:37

or whatever that was advantageous. And so

17:39

it hitchhiked. It

17:42

could be that it was

17:45

like a neutral change, you

17:47

know. Or

17:50

it could be, yeah,

17:53

so it could be that

17:56

it's linked, hitchhiked basically the

17:59

first two. hypotheses are very

18:01

similar. It's different scenarios where

18:03

it would hitchhike. And the third is

18:05

that deleting ORF8 is actually good for

18:07

viral fitness in humans. Right. Yeah,

18:10

so the deletion would be improving the fitness.

18:12

And so this paper looks at

18:14

that. And if you're wondering, ORF8 protein has

18:16

been studied a lot. And

18:19

it's not just in, this

18:22

deletion is not just in SARS-CoV-2,

18:25

but also in Pangolin, coronaviruses,

18:28

and Mink isolates. So

18:33

it's basically an immune

18:35

evasion protein. It's

18:37

got a lot of functions, like it helps

18:39

down-regulate major histocompatibility Class

18:42

1 molecules from the surface, which

18:44

would be an immune antagonist. And

18:47

it decreases a lot of other immune

18:49

activities. And they

18:51

think it might even contribute to

18:54

cytokine storms by

18:56

activating what we call the IL-7

18:58

pathway. So it's involved in immune

19:01

evasion. Okay, so it's not essential

19:04

for a virus reproduction. You could take it down,

19:06

the virus will still reproduce. Although in a host,

19:08

it may have an altered interaction with the host.

19:10

But given all of its effects

19:12

or apparent effects on immune evasion, it's not

19:14

the kind of gene you would expect to

19:16

go away. Seems like it ought to be

19:19

useful. For sure, an

19:21

immune evasive gene would be

19:23

very useful for a virus. Yeah. But

19:27

unless that usefulness is balanced

19:29

by some negative fitness

19:32

impact or something like that. Right, like

19:34

maybe, yeah, that's useful in, well, what

19:36

they're going to get to later in

19:38

the paper is maybe that's useful within

19:40

the host, but it inhibits your ability

19:42

to spread between hosts, in which case

19:44

there'd be a pressure against it. So

19:48

that's very interesting because T-cell

19:52

escapients of viruses are

19:54

only useful within hosts because

19:56

the way they're

20:00

that works is that you

20:02

involve MHC molecules and that's

20:04

so polymorphic that a CTL

20:06

escape mutant in one person is of no

20:08

use to someone else. So it's only good

20:11

in host. But that's fine because

20:13

those are long-term infections of many years.

20:15

So for D-cell

20:17

reactivity to be lost can

20:20

aid the virus. So that's

20:22

a real-world example of that. So

20:24

what they do here is a

20:26

computational analysis of sequences of

20:29

SARS-CoV-2 from Washington. I

20:32

don't have to say state. It's

20:34

Washington. If it's

20:36

D.C., we say Washington, D.C. If it's

20:38

Washington, it is the state

20:40

known as Washington. Why do people have

20:43

to write Washington state, Alan? Because

20:45

they're from D.C. and they think Washington means

20:47

D.C. And we should point out all of the

20:51

authors are from Washington.

20:53

Full stop. University of Washington, Fred Hutch

20:55

and HHMI. They

20:59

did a lot of sequencing. Remember, they had the first

21:02

U.S. case diagnosed, right? Oh,

21:04

in the Washington Department of Health. They

21:06

did a lot of sequencing.

21:09

So they have great coverage.

21:11

So this paper, they take

21:13

sequences from February 2020 to

21:15

March 2023. And it's emitting

21:17

Omicron because Omicron had its

21:19

own incredibly powerful selection. So

21:22

they look at all the others. So the idea

21:24

here is to understand what is

21:26

driving the loss of ORF8. And so they have great

21:28

sequencing coverage here.

21:35

And so they look through all their samples. They have 14,929 samples

21:37

with a potential knockout

21:40

of ORF8. And there's a lot of

21:43

trickiness about identifying knockouts, which I won't

21:45

go into. But it's

21:47

not so straightforward, as you

21:49

might guess, because there's sequencing errors and so forth.

21:51

And you just don't know. Most

21:54

of the knockouts were found in variants

21:58

descending from alpha. Remember? alpha, the very

22:00

first variant to arise. And those

22:05

variants have most of the loss

22:08

of ORF8. And loss of

22:10

ORF8 occurs by the introduction

22:12

of a stop codon, a

22:14

premature stop codon, right? And

22:17

this is, ORF8 is made from its own

22:19

mRNA, so it doesn't matter if it's downstream.

22:26

It doesn't affect anything downstream. So,

22:28

Vincent, this happened sometime after

22:30

the pandemic, of course. So,

22:33

do they pinpoint exactly when it lost

22:35

the ORF8? Well,

22:39

some lineages

22:41

lost it and some didn't. So,

22:47

it's not universal. There

22:51

are lineages where it lost it and

22:53

lineages where it didn't. And

22:55

what they do subsequently, which I think Vincent was probably

22:57

about to get to, is they

23:00

look at those lineages and how successful they

23:02

were subsequently, right? Yeah,

23:07

I think it was quite early in the pandemic

23:09

when you started to see the loss. I

23:12

don't remember. Let's see if

23:14

this tree does. Yeah, it hasn't been

23:16

fixed in the

23:19

viruses spreading in humans. So,

23:21

what was the figure? 90% of

23:24

circulating SARS-CoV-2 has ORF8

23:26

knocked out, but that means about

23:28

10% doesn't. Some of

23:30

them still retain it, yeah. All

23:33

right, so they

23:36

look at these thousands of samples, and

23:38

I said most of the derivatives of

23:40

alpha have the

23:42

loss, and

23:46

most of these losses are by premature

23:49

stop codons. So, basically,

23:51

and most of

23:53

the stop codons occur very near the end terminus

23:56

of the protein. I

23:58

think about 26 amino acids are left before. this

24:01

stop codon. So there's no big

24:03

piece of protein left that could have some

24:06

function. It's 26 amino acids is not enough

24:08

to do anything. They

24:10

compare the loss of orphae

24:12

to other genes in SARS-CoV-2 and this

24:15

is knocked out way more frequently than

24:17

any other gene. Some other genes are

24:19

lost but this one is way more

24:22

frequent. All right, so

24:26

if a gene loss

24:28

is deleterious to the virus,

24:30

it should be eliminated, right? The loss

24:33

shouldn't occur, it shouldn't perpetuate through

24:35

the virus population. And here as they

24:37

say, they look within the

24:39

host because if the high rate

24:41

of knockout in the sequences they're

24:43

looking at, remember these are consensus sequences from

24:45

people. What

24:48

is also seen in

24:50

host, within host, this

24:52

would argue against deleterious fitness

24:55

associated with the

24:58

knockout. So they look, they

25:00

have some sequences

25:02

from from single hosts where

25:05

they can look at the knockout and

25:07

they find that in fact orphate is

25:09

also lost within host as well

25:12

as without outside of the host. So

25:16

that takes care of

25:18

that hypothesis. The

25:21

other thing they do now for most of

25:23

the rest of the paper is to look

25:25

at positive selection. So

25:27

is the knockout good

25:30

for fitness? So is it

25:32

selected for? And so

25:34

is it good or is it just not bad?

25:37

Yeah, is it good or is it just not bad, right? So

25:40

they use... That's a bromorphic. They

25:43

use the computational

25:46

method which looks at synonymous

25:49

versus non-synonymous changes, right? So

25:51

these are amino acid base

25:53

changes. So a base change

25:55

that doesn't change the amino

25:57

acid is a synonymous change.

26:00

You could think of it as a synonym, right?

26:03

And a non-synonymous change changes

26:05

the amino acid. So

26:07

they look at the ratio of

26:09

non-synonymous to synonymous changes, which you

26:11

can just do by scanning the

26:13

sequences with the computer program.

26:16

And so, for example, if the

26:18

dN over dS is more than

26:21

one, that's indicative of

26:23

positive selection. So that change is

26:25

maintained in all the different isolates

26:28

that you have. If

26:30

it's less than one, it's

26:32

negative selection.

26:36

So it's not good and it's being selected

26:38

about. And one is neutral

26:45

evolution. So if the top and bottom

26:47

are equivalent, it's neutral evolution. So they

26:50

look at ORF8 and

26:52

ask what's going on there. And ORF8

26:54

has a high value,

26:56

greater than one, and

27:01

it's higher than that of any other

27:03

gene, which suggests positive

27:05

selection. And then they

27:07

say, well, there's some caveats here, so

27:09

let's address these caveats. And even after

27:12

addressing the caveats, it still looks like

27:14

the ORF8 deletion is being

27:17

positively selected. So in other

27:19

words, it's of some

27:21

benefit to SARS-CoV-2.

27:24

What that might be, we don't know, but that's

27:27

what the genome is telling us. They

27:29

then quantify that. They

27:31

look at lineages

27:38

of virus that have the ORF8 deletion,

27:42

and they find that these

27:44

are larger than CLAs with

27:48

a synonymous mutation in

27:50

ORF8. So the

27:54

ones with the deletion

27:57

are larger, plus they circulate longer.

28:03

11 and a half days

28:05

for the ORF8 deletion versus

28:08

seven days for synonymous mutation

28:10

in ORF8. So

28:12

we're comparing a deletion versus a synonymous mutation,

28:14

which is a little different, but they said

28:16

we can do this. We

28:18

know what we're doing. Don't try this at

28:20

home, but we know. They have a biostatistics

28:23

license. They're allowed. They

28:26

also look at the rate at

28:28

which these clades with ORF8 deletions grow. In

28:30

other words, you have an

28:32

initial one in an area, and then how fast

28:34

does it propagate? And

28:37

the clusters with nonsense mutations in ORF8,

28:39

that is, that lead to deletions, grow

28:44

6.3 times faster than those with synonymous

28:46

mutations. So the stop codon

28:49

is a non-synonymous mutation, obviously, right?

28:51

Because it changes the amino acid

28:53

to a stop codon. And

28:56

that's why they're treating it as a non-synonymous

28:58

mutation. It's totally fine, yeah. And

29:01

so they say this tells us that

29:03

the knockout is somehow boosting virus fitness.

29:06

Yep. Okay.

29:10

So some function of ORF8

29:13

is not good for fitness. Let's

29:18

see here. They do

29:20

then also discuss the

29:23

possibility, and they can't really sort this out. So

29:29

ORF8 may have

29:32

an advantage within the host and

29:34

a disadvantage spreading between hosts. That's

29:36

the hypothesis, and they present some

29:38

previous work from other groups that

29:40

supports that notion. And

29:44

then the idea is that in a

29:46

chronic infection, which is, we think,

29:48

maybe the source of a lot

29:51

of new variants, you keep ORF8,

29:53

the virus keeps ORF8 because it's

29:55

advantageous in the host and

29:58

in the chronic infectious state. the

30:01

virus is more pressured to

30:03

continue surviving in that host than to

30:05

spread to the next one. And

30:08

that may be the reservoir that prevents the

30:11

orphate deletion from getting fixed

30:13

in the population. So that's

30:17

the source of new orphate coming

30:19

in. They also

30:21

note that so

30:25

many, many changes in spike are positively

30:27

selected for and they're associated with fitness

30:29

gains. In fact, the rate of growth

30:31

of those compared to orphate are similar.

30:34

So they say this is more evidence

30:36

that maybe the orphate is positively selected.

30:40

And also look at whether it's

30:44

found in one clade versus another, one variant

30:46

or one clade versus another. And there's

30:48

some clades that mostly have it, but it's

30:51

also found in others as well. So

30:53

there's no clade-specific association of that. And

30:56

the deletion may decrease pathogenesis.

30:58

That's, again, they

31:01

cite some various evidence on that. Yeah.

31:03

So people have suggested that it reduces clinical

31:05

severity. So then they say, all right, let's

31:08

take our genome sequences and link them with

31:10

outcomes in the disease reporting system.

31:14

And they do this again with

31:16

pre-Omicron because the Omicron itself was

31:18

thought to be... Different story. ...different

31:20

story. So 8% of individuals infected

31:22

with intact orphate were hospitalized. 6.7%

31:26

with orphate knocked out were hospitalized.

31:29

1.8% of individuals infected by intact orphate

31:34

containing virus died compared

31:36

to 1.3%. These are very small differences. But

31:40

I want to remind people, they do

31:42

not take into account population

31:45

immunity, age, comorbidities,

31:47

which could all influence

31:50

this. So I don't... I

31:53

think this needs more study, frankly. It

31:57

may be too late to study that. It may be too late.

32:00

fact, yes. It was... I

32:02

gather that no geographic

32:04

distributions were noted

32:07

or age- Well, this is all a

32:09

study from Washington, right? Well, no, they

32:11

did look at international samples and I

32:14

don't think they found that

32:16

there was any striking, like

32:19

if you're in a particular

32:21

place, you don't get ORF8 deleted.

32:23

It just seems to be consistent.

32:26

Yeah, but

32:28

most of their data is from

32:30

Washington State. I think that's correct

32:32

that it's found elsewhere. I had

32:34

the unfortunate event

32:39

happen to me at the ASTM and

32:41

H meeting in Seattle. Yes. I

32:43

caught and so did you, Vincent. You

32:45

did. Acquired. I

32:48

wondered if we had an ORF8 deletion or not.

32:50

Good question. Maybe.

32:54

Was that December 2022? As

32:57

we know exactly when it was because the

32:59

woman in charge of the exhibits came around

33:01

and shook everybody's hand the morning of the

33:03

opening events. The next day she phoned up

33:05

and said, oh, by the way, I just

33:08

tested positive for Scoville Have

33:11

a nice day. All

33:15

of this, Dixon, have you followed this so

33:17

far? You're kind of the late person here.

33:20

You got it?

33:22

I got whatever there is to get. I mean, I

33:25

don't understand why the deletion occurred. I don't

33:27

understand why the deletion is still there. And

33:30

I don't understand why in the same populations

33:32

there is no deletion. Well, first of all,

33:34

it's not a deletion of the gene. It's

33:37

an introduction of a stop code on. So the protein

33:40

is gone. Oh, that's

33:42

what I meant. It's not really a deletion

33:44

in the genome, right? It's a knockout. That's

33:46

fine. That's fine. So it's best

33:48

to say ORF8 null virus. The

33:50

rows just because random changes happen all the

33:52

time. Why doesn't that happen to the whole

33:55

damn virus and just get rid of it

33:57

then? Well, that's not going to be positive.

34:00

Selective pressure is what that is. No, no,

34:02

I understand. You're trying to find an argument

34:04

why this happened. Right.

34:06

That is something that remains

34:08

a little up in the air. So

34:10

all this paper shows, which is important,

34:13

is that there seems to be a

34:15

positive selection to eliminate

34:18

the orphate protein in human

34:20

infections for SARS-CoV-2.

34:22

And so there's

34:25

some selective pressure that's causing

34:28

the virus to lose this

34:30

protein repeatedly. And

34:34

that's worth investigating further. Yep.

34:37

Oh, yeah. No, no, not part of your... Now,

34:39

they do speculate a little about what the mechanism

34:41

might be. Right. And I

34:43

think this is interesting. So they say that

34:46

an orphate

34:48

protein interacts with spike in

34:51

the endoplasmic reticulum. Okay?

34:54

And it reduces the

34:57

display of spike on the virus

34:59

particle's surface. And

35:02

they've shown that in experiments that it

35:04

leads to less spike on the surface

35:06

of the particle. And what they say,

35:10

that could give you better fitness by

35:12

avoiding the host immune response. Because if

35:14

you have fewer spikes on the particle,

35:16

you're going to be less able to

35:18

be neutralized by antibodies. Right. But

35:20

you may be less able to transmit to the next host. Right.

35:24

Because you have less spike on the viral particle. And

35:27

when you go through a bottleneck of transmitting from

35:29

host to host, that may affect the ability to

35:32

establish new infection. Right. Now,

35:34

they did find an elevated within-host rate

35:36

loss of orphate

35:38

compared to outside of the host.

35:41

Right. So

35:43

these are all acute infections. And we may

35:45

not be seeing the effect of loss there.

35:49

Then they say, you

35:51

know, these not going to have not

35:53

been fixed. First of all, they've not been fixed, only 90%.

35:56

And they've only spread in alpha and

35:59

XBB subclays. and they don't

36:01

know why that is. But one thing they

36:03

do say is very interesting. They

36:07

say this could knock out the loss of, and I

36:09

don't think we should say knockout because it implies that

36:11

I guess it's a knockout. This protein

36:13

loss is an example

36:15

of, maybe an example of what they call

36:17

clonal interference. Okay, so an

36:21

example of that would be that, so

36:24

here's how it would work. XBB

36:27

descendants have ORF8

36:29

knocked out, then suddenly

36:32

BA286 outcompetes

36:35

XBB, and ORF8

36:39

doesn't matter. It's not going to help as much

36:41

because BA2.86 is

36:44

so much more fit than XBB that

36:46

having ORF8 knocked out doesn't matter. And

36:48

so they say that could be

36:50

why ORF8 is not present in

36:53

all lineages. And

36:56

they also say, I think Alan you mentioned this,

36:59

these ORF8 chains are not present

37:01

in chronic infection associated infections, right?

37:05

And they say maybe because

37:09

having intact aid allows persistence and

37:11

evasion of the immune response because

37:13

you have a long-term infection where

37:15

immunity is going to make... Different

37:17

pressures. Different pressures, yeah. So

37:20

they say they hypothesize disproportionate

37:22

contribution of chronic infections to

37:25

global evolution could prevent ORF8

37:27

knockout fixation. So there's a

37:29

good fraction of infections that are

37:31

in, that are chronic and immunosuppressed people. And

37:33

so that could be

37:35

the reason. But you know, these are immunosuppressed

37:38

people, so I'm not sure how

37:40

much of an immune response you need to evade,

37:42

right? There's

37:44

probably some, and it depends on the patient,

37:46

and yeah. Yeah, they're all different. That's true.

37:50

You just have to be careful when you speak in

37:52

these global terms that you are... Really,

37:55

yeah. There's not a

37:57

complete absence of an immune response in every immuno...

38:00

compromised patients. It's different kinds and

38:02

so that may be where Orphate

38:04

is doing it. So I think

38:06

this is interesting and tells

38:09

you that there's probably positive selection

38:11

for Orphate loss and

38:15

now what do we do? Well there's not

38:17

much we can do. This is an interesting

38:19

problem and it's a virological problem

38:21

in my point, my view. I don't think

38:23

it helps

38:25

in any way of surveillance and

38:28

epidemiology. You just get vaccinated and

38:30

you'll be protected, right? Yeah, the

38:33

longer term way I see this helping, I mean of

38:35

course it's always best to know

38:38

more about a serious disease causing virus,

38:41

but I might imagine if we find

38:43

out that Orphate is involved in the

38:46

cytokine storm, we already know that that

38:48

is one of the deadliest parts of

38:50

this and many other viral infections and

38:52

maybe we could target that and

38:56

develop something that's going to

38:58

stop that aspect of it.

39:00

Yeah, yeah. Dixon, you have

39:03

any other questions? No,

39:05

and I don't have any answers either. I

39:08

think the best thing to say at this point is stay

39:10

tuned. Dixon, what's the

39:12

most successful parasite of

39:15

humans? Um,

39:17

toxoplasma. I

39:20

thought so. Yeah, in

39:23

fact it's the most successful parasite period. It

39:26

infects all mammals. Someone had another answer

39:29

and I said no, I think Dixon

39:31

would say toxo. I would definitely say

39:33

toxo. Okay, I

39:36

forgot which one they said but... 10-1 maybe.

39:39

No, it was not a parasite. I forgot

39:42

what it was. All right, so I

39:44

learned that from you anyway. That toxo

39:46

is very successful. Well, I can contribute.

39:48

Among other things. Our

39:50

next paper is also in nature

39:52

communications. How about that? How about

39:54

that? Now, since we've been talking

39:56

about influenza H5N1 viruses, I

39:59

thought we would talk about some

40:01

other influenza virus. And

40:03

this is cross-species spillover potential

40:06

of the H9N2 bat influenza

40:08

A virus. Very cool, H9N2.

40:13

And bat influenza virus. Bat

40:16

influenza, did you know that bats

40:18

could have influenza viruses?

40:20

Well, now you're gonna learn. The

40:22

first author is Rabbe

40:24

El-Shazni. I don't know how many

40:27

co-first there are. There's only one first

40:29

author and only one senior author, Richard

40:31

Webby. Richard Webby.

40:33

I do wanna call out the third from

40:35

last author, Muhammad Ali. Mm. I'm

40:39

sure it's not the same for you.

40:41

I think Muhammad is spelled differently, but. Yes,

40:43

it is. And this

40:46

group is from a whole bunch of

40:48

different places all over the

40:50

world. National Research Center in Giza, Egypt.

40:54

So there's someone from Giza and someone

40:56

from Memphis, but that's the Giza in

40:58

Egypt and someone from Memphis in Tennessee,

41:00

St. Jude Children's Research Hospital. Some

41:03

place called Human Link in Dubai, and I don't know

41:05

if that's a company or a research center. High

41:09

Point University in High Point, North Carolina,

41:11

University of Hong Kong, and

41:14

Scripps in La Jolla. So

41:16

really very global. Have you been to

41:19

Dubai? Yes. Well,

41:23

I wish I had been there during the flood.

41:26

I mean, that would have been an interesting

41:28

time to experience an old

41:30

desert phenomenon that

41:33

has never happened before. But

41:35

yeah, I was there when the Burj

41:38

Khalifa building became

41:40

the tallest building. I was there for the tall

41:42

building council meeting, and it

41:45

was quite an amazing building to look at. It looked like

41:49

from a distance, it didn't look like a building. It almost

41:51

looked like a fountain pen. It

41:53

was so skinny, and so, they

41:55

must have done, or was

41:58

it a wind tunnel work? just

42:00

to make sure that the damn thing wouldn't fall over.

42:03

And I

42:05

was impressed with that, and I was also impressed

42:07

with the fact that there were a lot of

42:09

buildings in Dubai that had their family names on

42:12

them, and the buildings did absolutely

42:14

nothing but just show off the fact that they had

42:16

a lot of money. That's all. So,

42:19

unfortunately, that's still the case.

42:22

So, the senior author, Richard Webby, will be on

42:25

Twivs at some point. I think we're finding a

42:27

date for him to talk about H5N1. So

42:30

that'll be fun. All right. So, most

42:33

influenza viruses, you know, they're in people,

42:35

and the reservoir is waterfowl,

42:38

right? The major reservoir are waterfowl. Many

42:41

mammalian hosts are infected besides

42:43

humans, dogs, horses,

42:45

cows, pigs, et cetera, cats.

42:49

But they've

42:51

been recently found in bats, and we

42:55

covered this first

42:57

paper, Twiv a long time ago, 2009-10. The

43:01

first influenza virus of bats was found in

43:04

a little yellow-shouldered bat in Guatemala.

43:06

I just love the name, little

43:08

yellow-shouldered. Bats, many bats have really

43:11

charming names. Totally

43:14

different from all other known

43:16

influenza viruses. The

43:18

HA and the NA were very different. And

43:21

then another one was found. So that one

43:23

was called H17N10. And

43:28

in 2010, another one was found in Peru in

43:31

New World flat-faced fruit

43:34

bats. And

43:37

this was called A18N11. And

43:41

both of these bats were asymptomatic. They

43:43

weren't sick, and they got

43:45

these influenza viruses from them.

43:48

Now, the cool thing about the

43:50

hemagglutinin of- Yeah, and the H18N11 is also not

43:52

related to any other. Any

43:55

other, right. These are like totally

43:58

bizarre, came from Mars. flu

44:00

viruses. And that paper

44:02

we did on Twift. Now as I

44:05

mentioned earlier, the receptor for the hemagglutinin

44:07

of these viruses is not sialic acid

44:09

as it is for most other

44:12

influenza virus that we know of, but

44:14

it is major is

44:16

to compatibility molecule.

44:20

Class II, and

44:22

that was discovered by a group including

44:24

Silke Schurk. As I told you a

44:27

while ago, she was going to factor in and she's going to

44:29

be at one of those meetings. So

44:33

they use a proteanaceous receptor rather than a

44:35

sugar to enter cells. And

44:38

these viruses in the bats were

44:40

detected in rectal swabs. So

44:44

maybe a fecal oral transmission

44:46

rather than respiratory. Got

44:49

that Dixon? Yeah,

44:52

so up to that point, it

44:54

was pretty much bat influenza viruses

45:00

are off in their own department. They

45:02

use a different receptor. They've got these

45:04

distant relation HNN. And

45:11

then 2017, the virus in this paper

45:14

showed up. Now this virus is H17 and

45:16

H18N11. Bats

45:23

are highly cerebropevolent in Central and South

45:25

America, but not in Europe. So this

45:27

virus could be restricted. Now

45:29

the virus of this paper was

45:31

discovered in 2017 in Egypt from Egyptian fruit

45:34

bats. And

45:37

it's different from H17N10 and H18N11, but

45:39

it is within the H9N2 subtype, which is known

45:49

to be avian influenza

45:51

viruses. So the HA

45:54

and the NA are distinct,

45:58

but the HA is not. in the NA

46:00

or H9N2, right, that's what you get

46:02

that from. And the remaining genes come

46:04

also from avian influenza viruses,

46:06

it looks like. It was first

46:09

found in oral swabs of the bats that

46:12

could be grown in chicken eggs, unlike those

46:14

bat viruses. And inoculating

46:17

fruit bats with the virus in the lab

46:19

gives you an infection. So,

46:23

and also some bat-to-bat

46:26

transmission seem to have occurred in that. So,

46:28

you got now bats have two

46:31

distinct forms of influenza viruses. You have

46:33

the H17, H18, which are

46:35

very distinct genetically and they bind

46:37

to different receptor. And then these

46:40

HN92-like viruses, which they say the

46:42

simplest explanation is that it came

46:44

from a bird into a bat

46:46

and now it's established in a

46:48

bat. So, if I were a bat,

46:50

I would start working on vaccines. And

46:53

stay away from the birds. Stay away

46:55

from birds. Do birds

46:57

and bats ever mix? They

47:01

must because, you know, the flyway

47:04

from all of central and western

47:07

Africa goes up through the Nile

47:10

River. So, each and there's

47:12

no water anywhere else. Right. So,

47:16

well, the late Max Don't

47:40

know. All right. So, this paper is going to look

47:42

at this H is bat H9N2

47:45

virus and

47:47

try and know if it's a threat to people

47:50

as far as we can know. Right. Because

47:52

this is a, this is

47:54

a familiar, kind of familiar looking flu virus.

47:56

And it appears to come from birds into

47:58

a mammal. That's kind of the

48:01

pattern you look for for a new pandemic

48:03

flu virus. And this

48:05

one binds Alpha three thousand, two,

48:07

Three Selleck acids, which is what

48:09

Avian Influenza viruses typically do right?

48:11

So they're gonna do a number

48:13

of experiments now. First one, they

48:15

look at a P. H. In

48:18

activation of the virus

48:20

and basically incubating virus

48:22

is it. A

48:24

range of Ph is ah and with

48:27

a signed. His says

48:29

this is Gibson Fruit bat virus.

48:32

The. School aged nine and two. Is.

48:35

Has. Resistance to an

48:37

activation at a ph of similar

48:39

to that of of it's human

48:41

influenza virus the South's P. H

48:44

resistance of influenza viruses His tracks

48:46

with the passage in this city

48:48

and to his miscibility and the.

48:51

Resistance pattern of this virus to ph

48:53

is similar to that of human versus.

48:55

So. That's kind of interesting. Say

49:00

look at the Neuraminidase. Of

49:03

this virus now the Neuraminidase.

49:06

Is. A enzyme on the serfs

49:08

to the virus particles who's function

49:10

in most influence versus to cut

49:12

sale a cast from proteins to

49:14

allow the virus to spread after

49:17

it's release themselves. And.

49:19

The ignoramuses of age. Of

49:22

eight seventeen and ten at age eighteen and

49:24

eleventh is does not cut sale a gas

49:26

it isn't have what we call say our

49:28

days. Cutting. Off sale

49:31

at acid activity. But. This

49:33

one does this age two and. A

49:35

H nine and two from Egyptian

49:37

Fruit Bats does have say our

49:39

days activity so. And as.

49:42

Makes sense because if you bind ace assure a

49:44

say alec assets you have to have and

49:46

your minutes to cut it off. otherwise the virus

49:48

that's made will stick to cells wants to

49:50

try to stay. right? And the

49:52

other, the other bad flu viruses probably

49:55

don't need that because they're not using

49:57

that receptor out for using a protean

49:59

A receptors. right? I'm.

50:02

You. Know why? Why viruses like

50:04

that don't need some The catalyst their receptors

50:07

is unknown but know your poliovirus doesn't have

50:09

anything to cut it off of the poliovirus.

50:11

We sept I guess lad an issue Rayo.

50:14

Must. Not be an issue. Or

50:17

a so. These.

50:21

Is that he? We know the sequence. Of

50:24

them. The Am. The

50:27

he was glutenin of this virus and

50:29

they said previously people showed that this

50:31

him a gluten and has of the

50:33

receptor binding residues typical of those. They.

50:35

Chased By now says to Three

50:37

Links Sale Agassiz and they just.

50:40

Do. More. Studies on

50:42

binding to different sugars and

50:44

confirm that this. Receptive.

50:47

Specificity of this H nine. He was

50:49

goodness. Similar to avian viruses set to

50:52

are found in North America. There it's

50:54

a the alpha to three lengths. I

50:56

alec acids are common to birds and

50:59

the alpha to six months. I alec

51:01

ask for more common to humans. So

51:03

normally you see a shift from alpha

51:05

to three to alpha to six and

51:08

going from birds to mammals, but these

51:10

viruses don't seem to have had to

51:12

make that shift. They're still alpha to

51:15

three avian style bindings, but they're obviously.

51:17

Infecting mammals. night. I.

51:20

See never going to some insects and experiments.

51:23

And by the way I

51:25

love the just that this

51:27

this is a are fully

51:29

modern interesting important paper that's

51:31

like. Mostly. Classical Fire

51:33

allergy is amazing. Could have done these

51:35

experiments thirty years ago if you'd have.

51:37

If you've known to look for this

51:40

wire fence, Sisters are a very good.

51:42

I think this this underscores that we

51:44

still need to do certain kinds of

51:46

experiments. Yeah, So

51:49

they make They want to know how

51:51

these viruses reproduce in humans. Cel coaches

51:53

who they make. A air

51:56

liquid interface coaches of Human Bronco

51:58

Frankie ill and lungs. It's

52:00

a with that his his. You

52:02

tube take Brown Killer human lungs are

52:05

his lung cells from people's You played

52:07

them on a membrane. And

52:09

them. Then you take. The.

52:12

Membrane is is sub sub banned it in

52:14

the cell culture this others medium underneath it

52:16

and then the top is exposed to air

52:18

and and the cells like being in air

52:20

because that's what they do. we know oneself

52:22

spare loves us are they differentiate the all

52:24

the right cell types of course as was

52:26

cool air liquid as liquid underneath gives of

52:29

nutrition and then the air. They're. Like

52:31

ah finally something the breeze. And

52:35

an insect them with the states

52:37

nine and two and they also and

52:39

sex them with an H five and

52:41

one and a A. H

52:44

Nine and Two as representatives in a

52:46

human does two thousand and nine. H

52:48

One N One Pandemic Virus as a

52:50

representative Human fires right. So

52:54

as a human virus replicates really well

52:56

in these human cells as you might

52:58

expect with all the other viruses of

53:00

bad words and replicate the lower cells

53:03

as well as the ones from avian.

53:05

Sources: So this is what

53:07

you would expect. For

53:10

a human versus a bad were a

53:12

bird virus. So. This is called

53:14

ex vivo replication of physics is doing

53:16

in cells and culture so that's a

53:19

good word. We're using this in the

53:21

textbook. With you know there's

53:23

in Vivo in vitro and then his

53:25

Ex Vivo and Xv trucks and and

53:27

of this X be true. But.

53:29

Ex Vivo is not an animal, but it's

53:32

in cells and culture. In.

53:35

Cells it's in primaries cells I felt

53:37

for us so these are not pass

53:39

or take outlines if there's ex vivo

53:41

just taken out of the out of

53:43

a hostess race. So you may wonder

53:45

how you get bronchial and lung cells

53:47

Some patience. Of

53:49

people have bits of their lung taken out

53:51

all the time and their bronchitis so those

53:53

are those are available am. Okay,

53:57

Next. They look at. Alveolar.

54:00

epithelial cells. So the alveoli are

54:02

the cells lining the alveoli, duh,

54:05

all the way down in the

54:07

lung where the air exchange

54:09

occurs from the air

54:11

into the blood. And

54:14

so these are called primary human

54:16

alveolar epithelial cells. And the

54:19

avian virus, they say

54:21

there's not much difference in titers among

54:23

all of these except for the H5N1. So they're

54:25

all replicating

54:28

similarly in those cells. And

54:32

that's interesting because that's

54:34

where humans have most of their alpha-2,3-linked

54:36

sialic acid way down in the bronchi

54:38

and the alveoli. So

54:40

maybe that's part of the reason for that. So

54:44

then they look at what cytokines

54:46

are induced by these viruses

54:48

when they infect cells. And why is that interesting? Well,

54:50

you know, many of

54:52

these highly pathogenic viruses induce a cytokine

54:54

storm in people, and that's part

54:57

of the severe pathogenesis. So they want

54:59

to say, can we learn anything from

55:01

this? And they say the

55:03

H5N1 induced the highest levels

55:06

of cytokine mRNAs, cytokine and

55:08

chemokines. And the bat

55:10

Egypt had the least mRNA

55:13

encoding chemokines and cytokines.

55:15

So the H5N1s, when

55:17

they infect people, they cause cytokine storms.

55:20

That's the basis of

55:22

severe disease in many individuals. So

55:25

this is saying that that bat virus isn't

55:27

there yet. Right?

55:30

Which is good news. It's good news. Now,

55:33

how about pathogenicity? We're going to

55:35

look at two different hosts for

55:38

this virus, mice and ferrets. And

55:41

remember, mice lie,

55:44

monkeys exaggerate, and ferrets are not

55:47

humans. Right. Which

55:49

just tells you that mouse and animal

55:51

models, you've got to be careful about

55:53

them. So they inoculate

55:55

mice with the bat virus and

55:58

also a... avian

56:00

H9N2. So it's

56:02

another H9N2 but it's more

56:08

virulent than the duck virus.

56:10

It caused more weight loss

56:13

and more virus reproduction in

56:15

the lungs. And

56:18

they confirmed that by

56:20

immunostaining lung sections with antibody to

56:23

the viral nucleoprotein

56:25

and you can see diffuse replication

56:27

throughout the lung. So that's

56:29

interesting that the bat virus is more... And

56:32

at higher titers the bat virus kills

56:34

the mice, whereas

56:37

the duck virus does not. That's

56:39

right. They met human

56:41

endpoints at doses

56:43

of 10,000 and above

56:45

EID 50. But

56:51

we don't know what that means because these are mice.

56:53

These are mice, yes. But

56:56

that's what we have. But it's a mammalian

56:58

model that is straightforward

57:00

to use and you took this virus

57:02

from bats and you put it in

57:05

mice and the mice die at the

57:07

reasonable inocula of

57:09

this virus and that's something to

57:13

look out for. But the ferret

57:15

model gives you, according to WHO, that

57:17

what happens in ferrets is important for

57:19

pandemic risk assessment, right? So

57:21

they do some ferret transmission studies.

57:25

So they put, you know, they'll infect the

57:27

ferret and put it in the same cage

57:29

as another ferret and see if the

57:31

virus is transmitted. So that would be contact transmission

57:34

because, you know, ferrets can't resist touching

57:36

each other. And

57:38

then they put ferrets in a separate

57:41

cage, uninfected ferrets in a separate cage,

57:43

who would need to have aerosol or

57:45

respiratory droplet driven transmission and

57:48

see if the recipient gets it. And that would

57:50

be a more likely,

57:52

a more reasonable model for human

57:54

transmission. Well, it's a more

57:57

reasonable model for human transmission in

57:59

public. Whereas the direct contact

58:01

is more like a household. Humans

58:04

contact each other? So

58:06

I've heard. Okay. Yeah,

58:11

I don't even shake hands anymore. No, right. So

58:18

they infect ferrets with either the

58:20

bat H2, H9N2 or the duck

58:22

H9N2. They

58:26

measure the virus in the nasal washes. They

58:29

say both viruses called

58:31

mild clinical symptoms in

58:33

signs in infected

58:35

animals. Right. This is a sign. The

58:37

symptom is very, very mild. Like the

58:40

weight loss is not noticeable

58:42

at all. They see

58:44

maybe a slight decrease

58:46

in body temperature. And

58:48

I mean, these ferrets are fine. Ferrets

58:53

have symptoms, but they can't tell you about

58:55

them. So we don't know what they would

58:57

be. So we measure signs in them. The

59:01

bat H9N2 transmitted

59:03

to contact ferrets by

59:06

two days, but the duck H9N2 did

59:08

not. Right. And

59:10

the bat one transmitted both

59:12

with direct contact and airborne

59:14

contact. Very interesting. Yes. Right.

59:16

So that is a little

59:20

bit concerning, because as

59:22

they say later, well, we'll get

59:25

to that in the discussion. The WHO looks

59:27

at ferretransmission as an indicator for

59:30

pandemic threat. They

59:33

took these animals apart after the

59:35

experiment and looked for virus in different

59:38

tissues. They could find it in

59:40

the lung and the nasal turbinate. It

59:42

turbinated initially at three days. And at five days,

59:44

they find trachea brain in addition.

59:49

And they also did immunostaining

59:51

to confirm these findings.

59:55

They also looked at, this

59:58

is a new one, replication. and

1:00:00

transmission in mallard ducks, yes.

1:00:04

Hmm. So, the infect

1:00:06

birds, with

1:00:08

both viruses, the bat H9 and

1:00:10

the mallard duck

1:00:12

H9, no clinical

1:00:14

symptoms for two weeks. The

1:00:17

bat virus did not replicate in

1:00:19

the ducks. They got no

1:00:22

virus out, no seroconversion, but

1:00:24

the duck virus did replicate.

1:00:26

It was found in cloacal

1:00:29

swabs. That's the other end

1:00:31

of the bird. Yes. Right?

1:00:34

You know, in the bat,

1:00:36

it's a rectal swab. So, in a duck,

1:00:38

it's a cloacal swab, right? Because ducks have

1:00:41

one hole for everything. There

1:00:43

you go. Is that right? Yeah.

1:00:46

So, that's for peeing, pooping, and reproduction. It's

1:00:48

all through the cloaca. So, would that be

1:00:50

like one hole to rule them all? Yes.

1:00:54

Indeed. Dixon, you got

1:00:57

that cultural reference, didn't you? Pop

1:01:00

cultural reference. Yeah, yeah, yeah. All

1:01:02

right. So, it's interesting. So,

1:01:04

the duck virus replicates and ducks, the bat

1:01:06

virus does not. And

1:01:08

that's the story here. Right. So,

1:01:12

let's just chat a little bit more. The

1:01:15

idea, again, that

1:01:17

this virus most likely came to

1:01:19

a bat from birds, perhaps, perhaps

1:01:22

ducks. But H9N2

1:01:25

in general, they

1:01:27

say the H9N2 viruses

1:01:29

became established in land-based poultry in the

1:01:31

1990s. And

1:01:36

many isolates have been taken, which

1:01:38

they, and these viruses taken

1:01:41

from land-based poultry,

1:01:43

these H9N2s, have

1:01:45

an amino acid change in the hemagglutinin, which

1:01:49

allows the hemagglutinin to bind

1:01:52

alpha-2-6-syallic acids. So,

1:01:54

it's a signature for human receptor

1:01:56

specificity. Remember, the avian hemagglutinin

1:01:58

is bind. alpha-2,3-syllic

1:02:01

acids, the humans

1:02:03

alpha-2,6. So these viruses

1:02:05

from chikens, these H9N2 viruses

1:02:07

from chikens, have human receptor

1:02:10

binding specificity. Are

1:02:12

there any non-land-based poultry? Poultry?

1:02:16

No, I don't know. Poultry,

1:02:18

I think, is domesticated birds, right? I

1:02:21

don't know. What is poultry? What

1:02:23

is poultry? So many

1:02:26

good questions. Poultry is domesticated

1:02:28

birds kept by humans, yes.

1:02:30

Bingo. So

1:02:33

they're all land-based. They're

1:02:35

all land-based, yes. Well, a duck

1:02:37

is a waterfowl. It

1:02:40

is. And in

1:02:42

China, they raise them in ponds. Yeah.

1:02:45

In other words, to assess whether or

1:02:47

not the mallard ducks actually were suffering

1:02:50

or not from the infection, they should have

1:02:52

sent them to a correct doctor. Yes,

1:02:54

of course. Correct duck. No, they

1:02:56

should quack them open and look. They should quack them open and look.

1:02:58

I like that. Exactly. I

1:03:01

like that very much. All right. So

1:03:06

the bad viruses that the

1:03:08

bad H9N2 that we've been talking about in

1:03:11

this paper has

1:03:14

a glutamine at amino acid 226

1:03:16

of HA, which is a signature

1:03:18

of alpha-2,3-cylic acid binding. The human

1:03:21

alpha-2,6-binding HA's have a leucine at

1:03:23

226. So you can sequence

1:03:25

it and know immediately what the binding

1:03:27

is going to be. And consistent

1:03:30

with that, the bad H9N2

1:03:32

binds mainly to alpha-2,3-linked sugars.

1:03:35

But that's one amino acid change away

1:03:37

from being able to bind to the

1:03:40

other. Yeah. Yeah, so it's one amino

1:03:42

acid change. I don't understand why the

1:03:44

chicken H9N2s have all the human signature

1:03:48

in them. I'm not quite sure. Maybe we'll

1:03:50

ask Robert Webby that. Yeah. Is

1:03:52

that his name, Robert or Richard? Richard.

1:03:56

Thank you very much, Dixon. Thank you, Richard Webby.

1:04:01

Okay, so they say little brown

1:04:03

bats, myotis

1:04:07

lucifugus, are widely

1:04:09

throughout North America. They have both alpha-2,3

1:04:11

and alpha-2,6 salic acid throughout their respiratory

1:04:13

tract. So this makes sense that this

1:04:15

virus can reproduce in bats, right? And

1:04:19

they say there's no selection for

1:04:21

alpha-2,6 because bats have both. So if you

1:04:23

already got a virus with alpha-2,3, it's not

1:04:25

going to change to alpha-2,6 unless there's a

1:04:27

fitness advantage, and apparently there is not. So

1:04:32

these viruses, these H9N2 bat

1:04:34

viruses have avian-like HA receptor

1:04:36

signatures, and they say that

1:04:39

replication in primary human cells

1:04:42

are also avian-like. They don't reset.

1:04:44

They're low replication compared to the

1:04:46

human viruses, which replicate the

1:04:49

higher titers.

1:04:51

But when

1:04:53

you go down into the alveoli,

1:04:57

there's a little difference between

1:04:59

the replication, where there's alpha-2,3, mostly

1:05:02

salic acid. So that's interesting. All

1:05:06

right, so what else here? This

1:05:08

says here, the robust transmission of this

1:05:10

virus to animals,

1:05:12

ferrets, does imply an elevated risk

1:05:14

to human health. The

1:05:17

ability to transmit between ferrets is

1:05:19

a highly weighted element in the

1:05:22

WHO's tool for influenza pandemic risk

1:05:24

assessment. So

1:05:26

that's part of the... And the

1:05:29

influenza risk assessment tool the CDC uses,

1:05:31

which I assume is very similar. It

1:05:34

has different acronyms. Yes, so you can use

1:05:37

the TIPRA or the IRAT, but... Oh

1:05:39

my gosh, so many acronyms. Oh,

1:05:43

if you interact with any government agency, it

1:05:45

just gets completely out of control. That's true.

1:05:49

Why do they like acronyms? Because they've got

1:05:51

all these programs that have names and they

1:05:54

have to abbreviate them because they... Why

1:05:56

do we have jargon? I mean, why do we refer to

1:05:58

RNA and DNA? Yeah, yeah, yeah.

1:06:00

And, you know, giving the whole name is because...

1:06:02

It saves time. It saves time. We speak in

1:06:05

a shorthand and... But it... ...people in the policy

1:06:07

world do the same thing. Yes,

1:06:09

but then if somebody needs to communicate

1:06:11

outside of that sphere, it

1:06:13

becomes very alienating. So,

1:06:15

you know, like, here, you mentioned

1:06:18

a term before, Vince, use CTL. Ah,

1:06:20

yes. The cytotoxic lymphocytes.

1:06:22

The lymphocytes, right. If you

1:06:24

just... but it takes longer. Yep.

1:06:27

That's all. I should have said cytotoxic T

1:06:29

lymphocytes. Ah, because we are trying to explain

1:06:31

to the public. Yeah. Don't

1:06:34

worry about it. People outside of a royal machine. I

1:06:36

say it that way all the time. Yeah.

1:06:38

The conclusion here is that the

1:06:42

phenotypes of this bat H9N2

1:06:44

virus has some phenotypes

1:06:46

of avian viruses, some with human. They

1:06:49

say this mix makes it difficult to

1:06:51

assess the pandemic risk

1:06:54

of this virus. They say we

1:06:57

should, they say, further

1:07:00

investigating the abundance and nature of

1:07:02

influenza viruses in bats in comparison with

1:07:04

other avian viruses appears

1:07:06

prudent. Yes. Which

1:07:08

I would agree. The other thing... And

1:07:11

excluding bats from contact

1:07:13

with farm animals, I think, would be

1:07:16

prudent. I would be hard to do. Yeah.

1:07:19

Imagine how many people are

1:07:21

conducting surveys with

1:07:24

mist nets to catch bats, to tag

1:07:26

them and release them. How

1:07:28

many of them are carriers for influenza viruses?

1:07:30

I mean, you know, there's plenty

1:07:32

of opportunities for the bats and humans to come in

1:07:35

contact with each other as well. Well,

1:07:37

I don't know how many people are actually doing that,

1:07:39

Dixon. I think a lot of

1:07:41

people are. I really do. Are

1:07:44

you advocating no sampling, no wildlife sampling?

1:07:46

Not at all. But that just creates

1:07:49

an opportunity for people

1:07:51

and bats to come together. I would hope that

1:07:53

the people... And speed workers. Speed

1:07:55

workers. Yes. Okay. So

1:07:58

Yeah, I would hope that the people who are doing the sampling... A bad

1:08:00

for other scientific purposes. Are very careful

1:08:02

about this sort of thing. I mean,

1:08:04

not just because a flu viruses, but

1:08:06

because of rabies And because of Verona

1:08:09

viruses. I would

1:08:11

be much more concerned about people who

1:08:13

have less. Less.

1:08:16

Training: Who might accidentally contact?

1:08:18

Bats Spelunkers You mentioned Anybody

1:08:20

who works in addicts or

1:08:22

around structures were bats. My

1:08:24

Proust: Yeah.

1:08:28

But. That's not. that's a lot of people to your

1:08:30

point India and lot of people in contact with.

1:08:32

It's a new said. Present. Contact

1:08:34

between Batson. Wild.

1:08:37

Animals I know. I said prevent contact

1:08:39

between bats and farm animals. A farm

1:08:41

animals who they're they're use as you

1:08:43

have to keep the animals indoor space.

1:08:45

Yes, But. Bats can fly

1:08:47

indoors race they can drum. And.

1:08:50

That is that leave us story and it's

1:08:52

the but it's my I mean my concern

1:08:54

here would be as these bats are in

1:08:57

contact with pigs and you get this virus

1:08:59

going into pigs than maybe that's the intermediate

1:09:01

host. Or. Okay,

1:09:04

that's it. Let's do some email. Have

1:09:07

club. He's. You know, dixon last week

1:09:09

we didn't all email episode. I am sorry

1:09:11

I missed. The. Our was fund

1:09:13

was me, allen and Brin. Or

1:09:16

that doesn't them. I didn't want to

1:09:18

step one of the bodies are was

1:09:20

snowing on earth of of you would

1:09:23

know talented. you take the first one

1:09:25

please. Sure Braden Rights! Thank you for

1:09:27

reading an answering my question. How check

1:09:29

out the Cancers Know Mix project to

1:09:31

see if there's a way to minimize

1:09:33

my risk of dying from kept pancreatic

1:09:35

cancer. I think it was the email

1:09:37

after mine. The talked about comment threads

1:09:39

project that I did to spiff up

1:09:41

my Cv for grad school applications was

1:09:43

about Motor Sport Twitter. Basically.

1:09:45

Reading the comment threads and using grounded

1:09:47

siri methods to analyze at all. I've.

1:09:50

Also been part of a few isa

1:09:52

tearing what's app groups in my home

1:09:55

town for the Path last several years,

1:09:57

ostensibly to promote my events. These

1:09:59

are hard. The ads for Rfk Jr.

1:10:01

Sand I'm in disinformation. My posts

1:10:04

regularly go like. Sorry.

1:10:06

To be the science buzz kill. but. For.

1:10:08

Example and allopathic doctor is better

1:10:11

play with place to treat your

1:10:13

spider bite than an aroma therapists

1:10:15

Wilde areas peer reviewed evidence to

1:10:17

support that herbal supplement Helping her

1:10:19

supplements helping cancer patients. Ask

1:10:22

your oncologist about drug drug interactions

1:10:24

before using As/ivor Mack and Cure

1:10:26

is Rosacea because that's a parasitic

1:10:28

infection, but it isn't effective Against

1:10:30

Proven: Even though I'm sorry for

1:10:32

her and her family that Jackie

1:10:34

Stone header medical license revoked for

1:10:36

prescribing it. Comes. Along

1:10:38

those lines, I stay in

1:10:41

the groups because I've received feedback in

1:10:43

private messages that people appreciate someone speaking

1:10:45

up for common sense. If

1:10:47

you're man wants to effect change in

1:10:50

people's minds, he can join a similar

1:10:52

group and be as civil, compassionate, and

1:10:54

calm as possible. Randoms.

1:10:56

Yelling on to internet don't

1:10:58

change people's minds. People we

1:11:00

know are far more credible.

1:11:03

People. We know are far more credible than

1:11:05

some guy in a lab coat on the news

1:11:07

or someone who trolls us on social media. That's.

1:11:10

Why your more credible to me than Rfk

1:11:12

Jr who I've only ever heard stories about.

1:11:14

I. Like to think that during the recent

1:11:16

polio outbreak in Harare, some people from the

1:11:19

group. Allow. Their kids to

1:11:21

get Opie the update vaccines because I

1:11:23

spent two days explaining from knowledge gained

1:11:25

on with the risks and relative risks

1:11:27

and benefits of vaccines and that if

1:11:29

they could get ip the from their

1:11:31

private doctor that was the best option.

1:11:34

followed by getting Opie V from W

1:11:36

Oh people who went to the school.

1:11:38

And. Natural polio infection brought up the

1:11:40

rear with side effects like a lifelong

1:11:42

disabling paralysis living inside an iron lung

1:11:45

and death. I included

1:11:47

a list of things like. Quote.

1:11:49

Feed your kid anti inflammatory foods to

1:11:51

keep the or their immune systems focused

1:11:54

on the task at hand and. Book

1:11:57

an appointment with a Reiki healer for after

1:11:59

the vaccine. appointment to fill them up with good

1:12:01

energy, in the hopes that

1:12:03

having a possibly psychosomatic toolkit to

1:12:06

minimize ill effects would help them overcome

1:12:08

their vaccine hesitancy. Yes, taking

1:12:10

my stack of peer-reviewed research about

1:12:12

Russian-sponsored anti-vax disinformation around to beat

1:12:15

the sense into them would have

1:12:17

been more satisfying, but it's possible

1:12:19

that a few parents consented to

1:12:21

their kids receiving an OPV booster

1:12:23

with a Reiki healing chaser because they knew

1:12:25

me and I could speak their language. Have

1:12:28

a great day and keep up the good work, Braden. Cool.

1:12:32

What is Reiki healer?

1:12:34

Reiki, I think, is that the one

1:12:36

where they place warm stones on the

1:12:38

body along chakras or

1:12:40

something? I

1:12:44

gather it's a quite

1:12:46

innocuous alternative

1:12:49

therapy thing that if it makes you

1:12:51

feel good, fine. Uses

1:12:54

gentle touch and placement to heal

1:12:56

you. Sure. Okay. Do

1:13:00

you think, Alan, that the Russians sponsor

1:13:03

anti-vax disinformation in the US? We

1:13:05

know that. We do. Yeah,

1:13:07

that's been documented that

1:13:11

one of the many aspects of

1:13:13

the Russian disinformation campaigns on social

1:13:15

media was built around

1:13:18

sewing discord on issues including

1:13:20

vaccines. Okay. Dixon,

1:13:23

can you take the next one, please? I

1:13:26

would be more than happy to. Bryce

1:13:30

writes, hi, this week in

1:13:32

virology team. My interest

1:13:34

in virology has been growing while watching your

1:13:36

podcast for the past few weeks and while

1:13:38

taking a virology course class, BI115

1:13:41

at Caltech this term. It

1:13:44

has been fascinating to learn about the ways

1:13:46

the immune system can combat viral infections and

1:13:49

the different treatment and vaccination approaches that

1:13:51

have been tried and used for fighting

1:13:53

different types of viruses. One

1:13:55

thing that particularly piqued my

1:13:57

interest, discussed during your podcast,

1:14:00

was the additional roles of B

1:14:02

cells in combating viral infections beyond

1:14:04

producing antibodies. I had

1:14:06

a couple of questions related to some of the

1:14:08

podcast episodes that you have put out over the

1:14:10

past few weeks. On

1:14:13

Twiv 1103, you talk about two

1:14:15

protein substitutions boosting the expression and

1:14:18

stability of the spike protein in

1:14:20

many coronaviruses. A model

1:14:22

came out of Bill Clemens' lab

1:14:24

at Caltech called IMPROVE for

1:14:27

predicting the expression of integral membrane proteins

1:14:29

in E. coli based on their sequences.

1:14:33

Are there similar computational models to

1:14:35

IMPROVE that have been used for

1:14:37

boosting the expression of viral envelope

1:14:39

proteins like spike proteins discussed? On

1:14:42

Twiv 1099, it

1:14:45

was mentioned that it

1:14:48

is rare to find two identical genomes of

1:14:50

hepatitis C virus, even in the

1:14:52

same patient. What is

1:14:54

it about this virus that allows its genome

1:14:56

and the associated proteins to be so tolerant

1:14:59

to mutation? Would such

1:15:01

a high mutation rate not lead to

1:15:03

many dysfunctional viruses being produced? Thank

1:15:06

you for all you have taught me through your

1:15:08

podcast and for taking the time to look at

1:15:10

my questions. Best wishes, Brace.

1:15:14

Very thoughtful and

1:15:17

interesting letter from

1:15:19

a newbie student of virology that has some

1:15:22

pretty deep questions for a person

1:15:24

that's just recently been exposed, does

1:15:26

that say? I don't know about

1:15:30

models to boost

1:15:33

production of envelope proteins. I'm not

1:15:35

aware of any of those. I know that when we talked

1:15:37

to Jason McClellan in

1:15:40

Texas, he talked about ways to design

1:15:44

vaccines which include adding prolines

1:15:46

but also adding disulfide

1:15:48

bonds and trying to

1:15:50

fill in pockets of a ton of molecules

1:15:52

that lead to conformational change and so forth.

1:15:56

I'm not aware. Do you know of any Allen models?

1:15:58

No, it hasn't. hasn't come up, but that doesn't

1:16:01

mean much. Yeah. To

1:16:04

Jason would know, because

1:16:06

he might use them. Yeah. And

1:16:09

the reason hep C,

1:16:11

it just,

1:16:14

so it's very interesting. The

1:16:17

mutation rates for RNA viruses are all

1:16:20

pretty similar in terms of the error

1:16:22

frequency of the polymerase, with the exception

1:16:24

of the coronaviruses, which have error correction.

1:16:27

So hep C is just as error-prone

1:16:29

as poliovirus. And

1:16:34

so if you track poliovirus

1:16:36

as it goes from the mouth when

1:16:38

you ingest it to the feces, in

1:16:41

about five days it changes 5% of the genome. And

1:16:45

so it varies just

1:16:48

as much as hepatitis C. And

1:16:50

you ask, would such a high mutation rate lead

1:16:53

to many dysfunctional viruses? Yeah,

1:16:56

it could. And they would be removed by

1:16:58

purifying selection, right? Just

1:17:00

like ORF8, no. If

1:17:03

it were bad, it would be removed. Yeah.

1:17:05

A lot of the genomes that get produced

1:17:07

in, well, in any viral infection, but in

1:17:09

an RNA viral infection in particular, are going

1:17:11

to be broken.

1:17:14

And if they get packaged,

1:17:16

they'll get sent out. And that's a particle

1:17:18

that won't initiate a productive infection. But

1:17:21

the virus is producing so many copies

1:17:24

that some of them are going to be fine. The

1:17:28

other part of this question is, what is it

1:17:30

about the virus that allows the genome and proteins

1:17:32

to be so tolerant? So the protein, that's the

1:17:34

key. Many viral proteins are

1:17:36

more tolerant than others. Like the spike

1:17:38

of SARS-CoV-2 can tolerate

1:17:41

many amino acid changes, right? But

1:17:44

what is it? The spike of measles virus

1:17:46

is less tolerant. We did

1:17:48

that study, remember, which we likened to

1:17:50

the airplanes that came back where were

1:17:53

the bullet holes, right? They reinforced those

1:17:55

parts of the wing. So

1:17:58

measles. It

1:18:01

must be a structural thing, right?

1:18:06

All right, Terry writes, your

1:18:08

videos not only got me through my

1:18:10

own virology course at University of Alaska

1:18:13

Fairbanks, but you have inspired me to

1:18:15

go into virology and eventually work in

1:18:17

biosecurity. I'm actually presenting

1:18:19

as an undergraduate at the AAAS

1:18:21

Regional Conference in San Diego this

1:18:24

June on the boreal pox virus,

1:18:26

formerly known as Alaska pox. I

1:18:29

cannot thank you enough for the inspiration and giving me

1:18:31

the courage to follow through. You are one of the

1:18:33

authors of my textbook that I cherish, and I just

1:18:35

needed to say thank you for everything. Thank

1:18:38

you, Terry. We appreciate you. Thanks.

1:18:41

So many thanks. We

1:18:43

do love hearing stories of how we help

1:18:45

you. I

1:18:48

think we're back at the top with Alan, right? Back

1:18:50

to me. Anthony writes,

1:18:52

the cartoon image attachment in the

1:18:54

preceding email was posted on Facebook

1:18:56

as an example of the idiocy

1:18:59

slash lunacy of anti-vaxxers. I

1:19:01

thought it too ridiculous to be so,

1:19:03

but I found in the Chicago Tribune

1:19:05

article that the image had

1:19:07

been posted by one of the Trump delegates. This

1:19:11

is a cartoon of cattle waiting at

1:19:13

the slaughterhouse, and one of them is

1:19:16

complaining that one of the ones ahead of him is

1:19:18

not wearing his mask. And

1:19:21

obviously being that taking

1:19:24

SARS-CoV-2 seriously is

1:19:26

like being led to slaughter. Yeah,

1:19:29

that's pretty insane. Cartoon

1:19:32

was sent to me by a Hudson

1:19:34

County resident, an anti-vaxxer. I

1:19:36

was shocked that anyone would think this image

1:19:39

to be insightful or persuasive. If the individual

1:19:41

had recently arrived from some backwater or was

1:19:43

intellectually challenged, I'd not have given it a

1:19:45

thought. But this person grew up

1:19:48

in Queens, New York and had worked in China

1:19:50

for a major US financial publisher. Remember

1:19:53

Ionesco's Rhinoceros? Ionesco's

1:19:55

Rhinoceros? I'm

1:19:58

looking it up. So

1:20:00

it's flagged by Jean Yonesco.

1:20:03

Right. Oh, it's the theater of the

1:20:05

absurd. Indeed. Do

1:20:07

you know that, Dixon? I know the theater

1:20:10

of the absurd. I didn't realize that the particular

1:20:13

episode, Rhinoceros, was in it. Over the

1:20:15

course of three acts, the inhabitants of

1:20:17

a small French town turn into Rhinoceroses.

1:20:19

Ultimately, the only human who does not

1:20:22

succumb to this mass metamorphosis is the

1:20:24

central character,

1:20:27

blah, blah, blah. The play is often read

1:20:30

as a response and criticism to the sudden

1:20:32

upsurge of fascism and Nazism during the events

1:20:34

preceding World War II, and

1:20:37

explores themes of conformity, culture,

1:20:39

fascism, responsibility, logic, mass movements,

1:20:41

mob mentality, philosophy, and morality.

1:20:45

Okay? That's Rhinoceros. Rhinoceros.

1:20:47

Rhinoceros. Thank you, Anthony, for that reference. I'm

1:20:49

sorry I didn't get it. The real reason

1:20:51

he didn't convert to Rhinoceros was because he

1:20:53

didn't want to horn in. Right. By

1:20:58

the way, there seems to be

1:21:00

considerable intersection between anti-vax and hatred

1:21:02

of cars. That's interesting. The electric

1:21:04

car mania, I strongly suspect, to

1:21:07

be a facet of the Oedipus

1:21:09

complex. Removal of the internal combustion

1:21:11

engine is equated with castration and

1:21:13

perhaps EV sounds like ED. Gosh.

1:21:16

Okay. Hatred of electric cars,

1:21:19

maybe, is what you meant. Yeah, I think so.

1:21:22

Okay. Well, electric

1:21:25

cars have more thrust, so

1:21:27

think of that what you like. Oh

1:21:29

my gosh. Sorry, sorry. It's a family

1:21:31

show. Dixon, you're next. I know, I

1:21:33

know, I'm not sure I'm going to

1:21:35

go on. John writes,

1:21:37

Vincent and the Twiv team, based

1:21:40

on the comments of a few Twiv episodes ago

1:21:43

when H5N1 was repeatedly mentioned in the

1:21:45

news, I thought it would send along

1:21:47

a new map with data

1:21:49

updated to April 20th, 2024 of the confirmed

1:21:51

cases of wild birds infected with

1:21:56

AVN H5N1 influenza. The

1:21:59

map contains more... than 10,000 data points

1:22:01

and gives the location at the county

1:22:04

health department reporting level,

1:22:06

the species of bird infected, and the

1:22:08

strain of H5N1. Oh, that's

1:22:10

interesting. Well, I sent

1:22:12

in another map to you almost six months ago,

1:22:14

which you talked about on the air, but this

1:22:16

map is now complete and accounts for the extremely

1:22:19

rapid increase in case reporting. And

1:22:21

then it gives a link to that. Also,

1:22:23

we have now compiled the data on

1:22:25

mammals from the USDA Plant and Animal

1:22:27

Health Inspection Service, whose data

1:22:30

now confirms more than 200 domestic

1:22:32

and wild mammals that have died from AV and

1:22:34

H5N1. Here

1:22:37

is the map for that if you're interested. And it

1:22:39

gives the next link. I love the show.

1:22:42

That is an understatement as there is nothing else

1:22:44

like it out there. And I've

1:22:46

been listening and supporting since the beginning. You

1:22:49

should have a GIS scientist on one of those days

1:22:51

to talk about the difficulties in mapping

1:22:53

the spread of things like H5N1. That's

1:22:56

a great idea, which is a nightmare

1:22:58

map to map and keep

1:23:00

track of at the field level. You

1:23:03

know, there's no question

1:23:05

about this. And the

1:23:08

best thing I've seen so far for

1:23:10

something like this has been the

1:23:14

epidemic of opioid

1:23:16

overdose. I'll

1:23:18

send you the map of that. It's not a map,

1:23:20

actually. It's a single figure. But the

1:23:23

width of the figure at the particular

1:23:25

time of the year equals

1:23:27

the number of deaths from

1:23:29

opioid overdose. And it's

1:23:32

alarming to say the

1:23:34

least to see it visualized like that, because

1:23:36

you can envision how this thing

1:23:38

works. And it's still out

1:23:40

there. And it's still having its effects. I

1:23:44

don't know what to suggest about this, except the

1:23:46

more easy it is to see

1:23:48

what's happening, the more understanding there

1:23:50

will be. The maps

1:23:52

are amazing. Yeah. Yeah,

1:23:54

I mean, this is a great idea if

1:23:56

we can get an epidemiology GIS person

1:23:59

on. I would love that.

1:24:02

John, if you know someone. Or if

1:24:05

you are someone. John is

1:24:07

a lecturer in applied

1:24:09

mathematics and geographic information science. This

1:24:12

graphic is very small. That's John

1:24:16

Hopkins. GIS is, right? Yeah,

1:24:18

so geographic information science is GIS.

1:24:22

Actually, I know someone over at Hunter College

1:24:24

if you're interested. His name is Sean A.

1:24:26

Hearn. And we actually published

1:24:28

a paper once on the West Nile virus epidemic

1:24:31

because it was evolving. And

1:24:33

he's really very good at it. So

1:24:36

the first map, which is the H5N1 isolation,

1:24:39

is you click on each dot and

1:24:41

you get information about where it's

1:24:43

from. Just the way it should be. Oh my

1:24:45

gosh. Ohio, bald eagle.

1:24:48

February 28th, 7 p.m. Wow.

1:24:52

And then it's all over the U.S. Look,

1:24:54

except some places are sparser than others. But

1:24:56

that may just be a population issue. Yeah.

1:25:00

And then there's one of mammals, which is far

1:25:02

less, but let's click on the one in New

1:25:04

York. And that is

1:25:06

a red fox in Rhode

1:25:08

Island. This

1:25:11

is great. We will put links to this. You can

1:25:13

have fun. This is cool. With this.

1:25:16

The mammals seem to be north biased,

1:25:18

don't they? Maybe,

1:25:21

yeah. Maybe they're not looking in the south.

1:25:23

I don't know. Thank you, John.

1:25:25

That's very cool. All right. We

1:25:27

have another email, but we'll save it for Angela

1:25:29

because it's a vet question. Right. Which

1:25:33

now brings us to our picks. And

1:25:36

Dixon, what do you have for us?

1:25:38

Well, I have two of them. The

1:25:40

second one is a short pick, but it's

1:25:43

really worth watching, however. The

1:25:45

first one is a video produced

1:25:47

by NASA on

1:25:51

a theoretical journey that you could take

1:25:54

to the Andromeda Galaxy. And

1:25:57

there has been so much detail.

1:26:00

now that

1:26:02

the James Webb Space Telescope is in operation,

1:26:05

that you can actually go to various

1:26:07

parts of the Andromeda Nebula and

1:26:10

see what it would look like if you turned around

1:26:12

and looked back to the other way and saw what

1:26:14

our galaxy looks like from the Andromeda

1:26:17

Nebula. Well, the significance of all that

1:26:19

is that the Andromeda Nebula

1:26:21

is slowly but surely moving

1:26:24

towards our galaxy. And

1:26:28

that's the Andromeda Galaxy. What

1:26:30

did I say? You said Nebula but

1:26:33

it's... I'm sorry. I meant galaxy.

1:26:37

The thing that I was confused about in

1:26:39

the beginning of all of this a long

1:26:41

time ago was that why are some things

1:26:43

moving towards each other when Hubble says everything

1:26:45

is moving away from each other? Well, that's

1:26:48

true on a large scale but on a

1:26:50

small scale. You have these perturbations. So

1:26:52

in about 4.5 billion years from now,

1:26:55

and I'm sure everybody's out

1:26:57

there biting their fingernails worried about all this,

1:27:00

these two galaxies will join

1:27:02

and become one with

1:27:04

one another as it were. And

1:27:06

as I put it, we will become scrambled

1:27:08

eggs because the Andromeda Galaxy is more organized

1:27:14

and probably is heading towards us more

1:27:16

than we're heading toward it. But

1:27:20

it's amazing to think

1:27:22

about the galactic pressures

1:27:25

that are at work

1:27:27

for the gravity to be so

1:27:29

immense to include trillions

1:27:32

of stars from each of these

1:27:34

two galaxies. I

1:27:36

can't possibly imagine it

1:27:39

but you can actually watch

1:27:41

it actually happen before

1:27:43

your eyes. So

1:27:45

I thought that was a startling thing to

1:27:47

think about in the long term. But

1:27:49

in the short term, I thought this snippet

1:27:52

of the highest

1:27:55

jump ever recorded

1:27:57

by a human being, and it was

1:28:00

documented by this

1:28:02

guy jumps like

1:28:04

50. I forget

1:28:07

how quiet it is. It's a 12

1:28:10

and a half foot high. He's at the

1:28:12

top of the scale. You can't go higher than that because

1:28:14

they don't have a way to measure it. Well,

1:28:17

basketball hoop is 10 feet and he's two feet

1:28:20

on the rim. Yeah,

1:28:22

the thing is that you wonder

1:28:24

about things like this, whether they're actually

1:28:27

photoshopped or fake or something else. And

1:28:29

I don't think so. I've actually seen

1:28:31

this where he was doing several

1:28:35

practice jumps first and

1:28:37

they were all equally off

1:28:39

the charts. So that's just

1:28:41

for an enjoyment's sake. Very

1:28:44

cool. Those are my two picks. We

1:28:47

had some corrections from last week

1:28:49

for you about collisions and

1:28:51

black holes. What did I say? Oh,

1:28:53

yeah, we read some letters about... Great.

1:28:56

You mean I got roasted? Correcting

1:28:58

your astronomy. Yeah, no, you weren't

1:29:00

exactly roasted. It was astronomers

1:29:02

writing into. Oh, dear. But they said you

1:29:04

got most of it right. They were just

1:29:07

confused things. I got most of it right.

1:29:09

They said they love you anyway. You're

1:29:12

still a star to them. A

1:29:16

fading star, no, but no less. I'm

1:29:18

running out of hydrogen for God's sakes. Alan,

1:29:22

what do you have for us? I have

1:29:24

one pick but two links. One

1:29:28

is a gallery that

1:29:30

Nature put together about

1:29:32

what a scientist looks like. And

1:29:35

I love this thing. It's

1:29:38

so it's it's a bunch

1:29:40

of pictures. They got clearly

1:29:43

they got professional photographers or at least people

1:29:45

who could be professional photographers to do these

1:29:48

portraits. They're very well shot. And

1:29:51

I love the diversity

1:29:53

that it shows not just in

1:29:55

the appearances of the people, which

1:29:57

there's a lot of, but

1:29:59

also in the... the activities in which they're

1:30:01

engaging. So it's not a bunch of

1:30:03

people standing around in lab coats, some

1:30:06

of them are, but it's also not

1:30:08

just field scientists standing with a mountain

1:30:10

in the background, though some

1:30:12

of them are. It's just all

1:30:14

kinds of neat stuff that people

1:30:16

are doing that is scientific

1:30:18

research. You've got an astronomer looking into

1:30:21

a huge telescope, you've got somebody in

1:30:23

a greenhouse and somebody handling a snake

1:30:25

and somebody, you know, in a rainforest

1:30:27

and someone in the lab. I love

1:30:29

it. It's just really, it's

1:30:32

a great, I

1:30:35

think it's just a really good public outreach

1:30:37

effort for people to get their minds around

1:30:39

what science really entails.

1:30:42

And then they took this all a step

1:30:44

further, they have

1:30:46

put 50 of these photographs on public

1:30:49

display at bus stops in London. Oh,

1:30:52

cool. Like where you would normally see an

1:30:54

ad, there's one of these pictures of one

1:30:56

of these scientists explaining what

1:30:58

this person does. And I

1:31:00

think that's really cool. And

1:31:03

I would love to see them do that in more

1:31:05

cities. I know they have offices, nature has offices in

1:31:07

New York, so that seems like it ought to be

1:31:10

something they do, maybe elsewhere too. Wow.

1:31:16

Yeah, well, scientists look like everyone

1:31:18

else basically. They look like everybody else. They

1:31:20

do. They're doing all kinds of cool things.

1:31:22

They are everybody else. All

1:31:26

right. I have two picks

1:31:28

which relate to what's been happening this

1:31:30

week. At Columbia, which

1:31:32

is there have been protests, of course, and

1:31:35

on campus, which brings

1:31:38

you back to the 1960s, Dix and I

1:31:40

were talking about Mark

1:31:42

Rudd and Grayson Kirk

1:31:45

and the Students for a Democratic

1:31:47

Society. The SDS, or the

1:31:49

sodium dodeckel sulfate. Yeah, that's what I always

1:31:51

thought about it. That's right. Anyway,

1:31:55

there's one article in The Atlantic. I mean,

1:31:58

they're just views on the... on the protests, which

1:32:00

I think are very good. The

1:32:03

campus left occupation that broke higher

1:32:05

education by George Packer.

1:32:07

Elite colleges are now reaping the consequences

1:32:09

of promoting a pedagogy that trashed the

1:32:11

post-war ideal of

1:32:15

the liberal university. So

1:32:18

basically, liberal universities are supposed

1:32:20

to be places where you can say anything

1:32:22

you want. Where

1:32:24

else in the world can you do

1:32:26

that? You can't protest at many other

1:32:28

places. And

1:32:31

so now we see

1:32:33

reactions to that. He

1:32:35

says they started all in the 1960s with

1:32:37

the occupation of the president's office at

1:32:40

Columbia University. So

1:32:43

basically, it's the fault of the Boomers. Is

1:32:45

it? I don't know whose

1:32:47

fault it is, but that's how I see it.

1:32:50

Well, last night, they said the largest

1:32:53

protest ever on campus was

1:32:55

after the news leaked out that

1:32:58

Nixon had ordered the bombing of

1:33:00

Cambodia. And

1:33:02

McNamara said, we have not done that. And

1:33:04

then Nixon admits that we have done it.

1:33:07

And that triggered an enormous response

1:33:09

from students. The most

1:33:12

that ever, like 900 campuses, including

1:33:15

high schools and grade schools, everything, just

1:33:18

went crazy. I don't remember that event, actually. Well,

1:33:21

you notice that the protests are not just at Columbia. There

1:33:23

are many universities. There are many places. Because those are places

1:33:25

where you can. If you think about it, you can't just

1:33:28

go out on the street. Permit.

1:33:30

And if you don't have one, you're going to get arrested.

1:33:33

You can't do it in a building of a business. They're not

1:33:35

going to let you do that. So that

1:33:37

leaves campuses. And now this article

1:33:39

is arguing, now they're cracking

1:33:41

down against the thing that they think

1:33:44

they're promoting. So that's kind

1:33:46

of an interesting dichotomy. So

1:33:49

that's interesting to read. And then

1:33:51

my second one is an opinion by

1:33:54

John McWhorter, who's a Columbia professor. It's called,

1:33:56

I'm a Columbia professor. The protests on my

1:33:58

campus are not just. And

1:34:02

you know, there's a

1:34:04

photograph. So, when I went last

1:34:06

Wednesday, over

1:34:08

a week ago, right, the main gate was

1:34:11

closed. There were police with riot helmets there.

1:34:13

There was a line of people protesting outside.

1:34:16

And then inside, there was some kind

1:34:18

of demonstration. And

1:34:20

we had to go around to get

1:34:24

another gate. But that's all fine. On

1:34:26

Monday, they said, don't come at all.

1:34:28

Teach remotely by Zoom. And

1:34:31

then we went back this following Wednesday. I

1:34:35

think this is a good perspective

1:34:37

because he said he's arguing basically,

1:34:39

it's not peaceful. And

1:34:42

you're entitled to protest, but you're

1:34:44

not entitled to be anti-Semitic, for

1:34:46

example. That's not what protest is

1:34:48

about. But that's, he also

1:34:50

says that if these people had

1:34:53

been chanting anti-black slogans, they would have

1:34:55

been shouted down immediately by other students

1:34:57

and so forth. But I

1:34:59

think they're both interesting perspectives,

1:35:02

right? So

1:35:04

that's why people have sent them to

1:35:06

me, actually, in the course of the

1:35:08

week. So I thought maybe people

1:35:10

would be interested in what's going

1:35:12

on. I don't know what the solution is

1:35:14

when, you know, the

1:35:17

university itself cannot make

1:35:21

changes that they want, right? They

1:35:23

cannot end the conflict.

1:35:25

No. Right.

1:35:28

Someone else, but they were going to stay

1:35:30

there at Columbia until, you know,

1:35:33

it doesn't seem to be rational to

1:35:35

me, but I don't know. Anyway,

1:35:37

they're interesting. No, I can understand protesting

1:35:40

for the university to

1:35:42

divest investments from particular

1:35:45

things because that is something that is in

1:35:47

the university's power. Yeah.

1:35:51

That saying, you know, we're going to protest

1:35:53

until there's peace in the Middle East, that's

1:35:55

not really something that needs to

1:35:57

be fixed. In the 60s occupation, the demand for peace is not going to be

1:35:59

as good as it is. was to stop

1:36:01

Columbia stop investing in military research.

1:36:03

When I was in college there

1:36:05

was a whole raft of protests

1:36:07

around divestment from South Africa. And

1:36:11

divestment from companies that had significant presence

1:36:13

in South Africa and you

1:36:16

know that's the kind of thing that I

1:36:18

think makes sense whether

1:36:21

you agree with the cause or not but that's a

1:36:23

that's a kind of demand that you could make in

1:36:25

this context and it

1:36:28

would be reasonable. Well he mentions that in this

1:36:30

article as well that

1:36:33

the South African protests. Right. Yeah. Alright

1:36:35

we also have a listener pick from David.

1:36:38

Back in the 90s one of the highlights of

1:36:40

my video career was being able to record the

1:36:42

US Navy's Blue Angels at an

1:36:44

air show in Kalamazoo, Michigan but the

1:36:46

ground-based footage I got is nothing compared

1:36:49

to the visuals captured by the camera

1:36:51

affixed to the bottom of the team's

1:36:53

lead plane seen in this YouTube video

1:36:56

containing what amounts to their entire show

1:36:59

over San Francisco in October 2019. It

1:37:01

is both a thrilling demonstration of the

1:37:04

Blue Angels extraordinary flying skills as

1:37:06

well as a virtual overhead travelogue

1:37:08

of San Francisco region including such

1:37:10

landmarks as the Golden Gate Bridge

1:37:13

in Alcatraz. And while the

1:37:15

visuals are thrilling the soundtrack which is muted

1:37:17

engine noise is paradoxically soothing

1:37:19

being essentially a form of white noise.

1:37:21

If you don't have time to watch

1:37:23

the entire 45-minute program at least the

1:37:26

last 15 minutes contains some of the

1:37:28

best bits and he gives

1:37:30

a YouTube. It is a very cool video.

1:37:32

David is a micro TV video editor. Oh

1:37:35

wow. Who will be hearing this read

1:37:37

as he's editing this video on Saturday sometime.

1:37:39

Thank you David. Fabulous.

1:37:42

Yeah. That's it for Twiv 1109.

1:37:44

1109 as show

1:37:47

notes are at microbe.tv slash Twiv. If

1:37:49

you want to communicate with us for

1:37:51

any reason pick

1:37:55

a comment a question the email

1:37:57

is twiv at microbe.tv and

1:38:00

We would love to have your financial

1:38:02

support. It means that you enjoy what

1:38:04

we do and it also will help

1:38:06

us do more of it. You go

1:38:08

to microbe.tv slash contribute. Dixon

1:38:11

de Pomier is at

1:38:13

trickinella.org and thelivingriver.org. Thank

1:38:16

you, Dixon. Thank you, Vincent, and

1:38:18

thank you, Dan. It's not Daniel, whoever

1:38:20

I am. Alan,

1:38:23

Alan the dove. Yeah,

1:38:26

and how dare you speak out against war. Yeah,

1:38:29

that's a very good way to say it.

1:38:34

Alan Dove is at alandove.com

1:38:36

and turbidplaque.com. Thank you, Alan.

1:38:38

Thank you. It's always

1:38:41

a pleasure. I'm Vincent Raconiello. You can find me

1:38:43

at microbe.tv. I'd like

1:38:45

to thank the American Society for Virology

1:38:47

and the American Society

1:38:50

for Microbiology for their support of

1:38:52

Twiv, Ronald Jenkes for the music,

1:38:55

and Jolene for the timestamps. You've

1:38:58

been listening to This Week in Virology.

1:39:00

Thanks for joining us. We'll be back

1:39:02

next week. Another Twiv. This

1:39:04

is Virology. This is Virology.