The Evolution of Infectious Diseases with Justin Meyer: Lecture 2-Ten Questions About Coronaviruses

The Evolution of Infectious Diseases with Justin Meyer: Lecture 2-Ten Questions About Coronaviruses

(calm music) – Hi everyone. Welcome to the BIEB 152. This is lecture number two. So for this lecture I
just wanted to step back and answer 10 questions that I think many of us are thinking
about with COVID-19. These questions are not all of the questions that we have, obviously. And there’s lots of resources online if you do have questions
about this ongoing pandemic. But they’re the questions that I thought, really, in answering them, we get to more of the
fundamentals of the biology of the disease so that
you guys can learn about how this coronavirus
works and begin to have an intuition for how
microbes might evolve. Okay. So each lecture, I want to start by taking the temperature of the epidemic. So this is where I go over a few slides, updating you on how it’s proceeding, whether or not our
interventions are working, whether or not there’s hopeful
news or maybe bad news. And so we’ll do that and then we’ll move on to the actual course content. This is an update of the data
that I showed you last time. I wasn’t going to show this because it’s just going to look more of the same. This phylogeny here, this
evolutionary relationship of SARS-CoV-2 is going to
probably remain very robust. There’s so much data that’s
put into this phylogeny that I don’t anticipate that
the patterns will change much. And certainly the patterns to the right of the spread of the
disease around the world. It’s spread, it’s everywhere. Now it’s sort of mounting endemic infections in
each of the countries. But I did want to go back to this data because I got an email asking
about this idea that UCSD, it appears, hasn’t been hit
as hard as other places. And people are wondering that they had a really bad cold in the fall, and was that actually some sort of precursor to the current strain of SARS and did that give them
immunity to SARS-CoV-2? And I want to say that I
don’t believe in that theory, and that it is hopeful
that this idea that maybe somehow in San Diego we were
pre-exposed to this pathogen and we’ve developed immunity. And why I’m worried about
that kind of thinking spreading is it’s good to be hopeful, but not so hopeful that we begin to influence our own behaviors and stop doing things
like social distancing. And so the reason why I don’t think that that theory holds is this data here. And so if you see on
this, on the x-axis here, these are dates in which certain strains were isolated and sequenced. And then they’re using
evolutionary biology and phylogenetic reconstruction to be able to predict when the strain probably emerged from bats to humans. And it certainly emerged,
or all of the data suggest that it emerged in early December. And that was in Wuhan, so it was confined to
a region of the world, and then from there it spread out. And we have so much data
now that suggests that, that I just don’t think that’s
actually going to change. There’s also a lot of theories about, was this in Italy first? No, the data does not suggest that. Other theories are that
this was a lab strain. The data we’ll look at
later in this lecture and later in the course suggest that this is certainly not a lab strain, that this looks like a natural variant that’s very similar to variants
that we’ve seen in bats and sampled a couple years ago. So it’s not a lab strain. It emerged in Wuhan and spread
around the world after that. So this is more about checking the temperature of what’s going on. This is a plot that I
showed you last time. And I had fit this little curve here, optimistically hoping that we were no longer in the
exponential increase phase of spread within the United States. But when we look at the data from two days ago and from today, we find that my fit to that
curve was overly optimistic. The rate of increase of the spread within the United States
is still increasing. It does appear to be slowing down. But of course, just a few data points don’t really make a trend. We have to see more data
and see how this unfolds. Certainly the CDC is predicting that in the couple weeks nationwide, that’s when it’s going to be the worst for the United States. But remember, we are states, and we all have different
behaviors in each state and different economies
and different cultures and different times in
which we got the disease. And so it’s probably
a state-by-state basis in which you’re going
to see this sort of peak and then hopefully dropping back down. It looks like that is what
happened already in Washington. I would say that New York is probably at the peak stage now
and will be dropping. And then in the future it’ll sort of cycle through other states as well. So remember to remain social distancing. It’s the best thing that
we can do right now. Okay. And I showed you this
confusing plot last time. And I wasn’t going to show it again because these lines
are all over the place. That y-axis is complicated. That y-axis, I will
explain the math behind it in three lectures when we
talk about natural selection and I go over exponential growth. For now, just know that
higher values are bad, lower values are good, and that if you have a
flat line in this graph, that means that you’re still in exponential expansion of the disease. And so what’s kind of good
news for the world is that in all of these different countries, the trajectory is
downwards rather than flat. And that means that they’re leaving the exponential expansion
phase of the disease and it’s hopefully grinding down and it won’t be as big of a
problem in the near future. But the US, you can see, is
kind of all over the place. This is because we’re a giant country and there’s probably different kinds of dynamics happening within each state, and so it’s hard to just look
at this sort of combined data. But it also reminds us we’re barely deviating at all from exponential growth. And so it reminds us
that we have to remain vigilant on social distancing
and other practices. The CDC is contemplating using masks, face masks now for the
general public as a precaution and as a way to limit the spread. And I would say don’t use masks that are the ones that should
be used in the hospital. We should give them to the
people in the hospital. But there are lots of
ways to make your own mask at home that are relatively effective. And so I do suggest doing that. I haven’t actually worn
a mask outside yet, but I think we should sort of break the kind of social barrier and
acceptability of wearing masks in the United States and
maybe start doing that. Okay, and this is data
that I showed last time, but this is an update on it. And what we can see here is that this is the temperature
data from the smart thermometers that are spread throughout the United States by Kinsa healthcare. And here are some plots. And they just show that COVID-19 was causing these atypical patterns. And now that, once we
started social distancing, now we’ve actually dropped below what they expected would be
the normal level of sick people based on temperature
across the United States. So social distancing is
having a real effect. This is the data that shows it. And so we just need to
keep on social distancing. So let’s keep moving forward. The other data I showed
is kind of bad data. It seems that we’re still in
the exponential expansion phase in the United States
in most of the states. So I wanted to share
some good information. And this is a little bit old compared to a lot of the
information that I’m sharing. But basically, the NIH has started a clinical trial of a COVID-19 vaccine. All over the world people are coming together to develop these vaccines. There’s trials either
starting or have started in other countries in the world. But this is very promising. And hopefully we can have a vaccine and just sort of forget about SARS-CoV-2. I have this picture here. That’s just a model of the virus itself. And then it has these red protrusion. And that’s this structure, this protein here are
those red protrusions. That’s the S protein. That’s the host recognition protein. And this is highlighted
because this is likely the feature that they’re
using to put in the vaccine to elicit immunological
response from our own bodies to become immune from this viral particle. The vaccine is being carried out by this collaborative
effort, which is amazing. I can’t even imagine putting
all of these pieces together. But you have Kaiser Healthcare. They have hospitals in, all
over the West Coast especially, but in Washington where they
are doing this clinical trial. You have the NIH through one of the NIAID funding the science and
also scientists that are associated with them doing the research. You have Moderna, which is a company in Massachusetts in Cambridge. And they’re helping the
development with their scientists. And then you have this
Coalition for Epidemic Preparedness Innovations in Norway that’s actually manufacturing
some of the vaccine. So it is, it’s this collaborative effort. But I have to say that it’s more than just this one group and
this one collaboration. In the New York Times just yesterday they were pointing out that scientists are working together across the world,. Whether they’re in the
public sector like I am or in the private sector,
they’re working together, sharing data, and it’s
just, it’s a great thing. There was news that Trump tried to get a company from Germany to move over here so that we would have the
rights, I guess, to the vaccine. Or maybe not the rights, but
control over the vaccine. And China also proposed a similar kind of deal with another
company in German. And so it seems that our politicians are sort of going to
fight over this vaccine. But at least the scientists
are not engaged in that. So, hopefully there will
be enough for everybody and we will get over this soon. What’s the timeline for vaccine testing? At least a year. So it’s going to take a long time. We have to continue social
distancing and other practices. Okay, so let’s actually
get into the lecture. So, 10 questions answered
about coronavirus. And like I said, I picked
these questions out because I think they help inform about the biology of the coronavirus. This is going to be
focused on the large group of viruses that are called coronaviruses. But we will also talk about SARS-CoV-2, the strain that’s causing COVID-19. Okay, what is a coronavirus? And so, if you are listening
to the recording of this and you have the option to actually pause, I would actually say that
after I pose a question, hit pause and think to yourself. Have your brain sort of sort through. What do you really know
about a coronavirus and how would you personally define it? Then once you have that
in mind, then hit play. And what that’s doing is it’s helping you stay focused and engaged in the lecture, but it also, it’s opening your brain up to make all these connections to pathways that are connected to coronavirus. And I’m hoping I don’t,
I’m not a neurobiologist. I study viruses, which
certainly don’t have neurons. But I’m hoping that having
that thought process ahead of time will sort of
help cement these details down. And so this is something I would do throughout the entire course. Okay, so let’s move forward. What is a coronavirus? And so this is an electron micrograph of multiple particles of the coronavirus. You can see that they have
all of these sort of spikes. They’re called a coronavirus
because they have these spikes that make them
look like they have a crown. A corona is a crown. And a coronavirus is in
the family Coronaviridae. And it is a group IV
positive strand RNA virus. So this is just sort of
basic virology information. And if you know what
those things are, great. If you don’t, don’t
worry too much about it. I will explain what a positive strand RNA virus is in a second. As an evolutionary biologist, what I find really
compelling about this virus is that it’s been co-evolving with bats, and it’s for a very long time. It’s actually estimated
for maybe 55 million years. And so this is a very, it’s
a large group of viruses. It’d had plenty of time to evolve and diversify into different strains. It’s mostly in bats, although it does now, it has spread to other species and it’s coexisting with other
species like humans as well. So I just think it’s very fascinating that it has such a long history and has had such time to evolve and adapt in very interesting ways
that we’ll learn about. So, what are the building
blocks of the coronavirus? So pause if you want to. For you guys listening live, we’re just going to dive into the answer. Okay, so this is what a
coronavirus looks like. It has relatively few components. I guess relatively compared to a cell. But to a virus, this is about normal. It has these spike glycoproteins, the S. These are the things that
make it the coronavirus. These are the things that interact with the outer membrane of our cells. People really focus on these a lot. A lot of research that we’ll
talk about on the S protein. The M protein is also
in this outer membrane. That’s the envelope. You have this HE protein also there. You have the envelope. And so an important part of this is you have the RNA that’s inside. There’s an N protein that
interacts with the RNA to make sure that it’s compressed and condensed into this structure so that it fits inside the particle. You have this other E protein
on the outer membrane. So it just is a bunch
of structural proteins. You have the membrane. That’s the envelope. Then you have the genetic
information in the center. That’s the instructions
for it to be able to take over the cell and
replicate more viral particles and spread to more people. It’s 120 nanometers,
which is, I don’t know, kind of big for some viruses, but certainly not the
biggest virus out there. It’s very tiny though
in the scheme of things. Lots of them can fit onto
the head of a needle. I don’t know exactly how many,
but it’s very, very small. Okay. What are some characteristics
of a coronavirus genome? So the coronavirus genome is actually relatively big for RNA viruses. And so I’m showing you a schematic of two different coronavirus genomes. We have the SARS-CoV and the MERS-CoV. We’ll talk in a second about the diversity of different coronaviruses and talk a little bit more about the characteristics of these
two different viruses. But just remember that
SARS-CoV is not the SARS-CoV-2, although their genomes are very,
very similar to each other. And SARS-CoV caused an
epidemic awhile ago. MERS-CoV more recently, and
it is an ongoing epidemic. But these are two of these coronaviruses that caused these really bad epidemics. And they’re also very highly deadly. Even more deadly than SARS-CoV-2. Okay, and so these are just,
like, a bunch of blocks. Like, what am I looking at here? What information am I gaining from this? Basically, the take
home message for this is it’s a relatively large genome. There’s multiple genes. It’s organized in an interesting way. And so this open reading frame
1a and open reading frame 1b, that’s what ORF is, open reading frame, these are actually not just two proteins, but they are 16 proteins that get cut up by enzymes that turn this long sequence into smaller proteins. And so all of these proteins
at this side of the genome, since they’re on this side of the genome, they’re read first and
turned into proteins first. And so these are the
proteins that are used for DNA replication and
some other functions. But mostly DNA replication. Or not, I’m sorry. I said DNA. RNA. This is an RNA virus and
it never has a DNA phase. We’ll talk about that in a second. So, replicating RNA. And what’s interesting is it needs to replicate a lot of RNA. The RNA is then used to make the other proteins down here. The RNA itself is the genetic material, so RNA has to be packaged within each of those viral particles. And so that’s obviously a
really important function and you have to start that up immediately when you begin to infect the cell. And so that’s what it does. And then it has a bunch of these other structural proteins in the genome. This, actually, diagram is not to scale. This is the first 2/3 of the genome. And we’ll have another diagram
later that is to scale. And then this takes up
just 1/3 of the genome. So most of the information is about getting this running start
and replicating your RNA. Viruses spread very quickly, and that’s part of their adaptation. Okay. So, genome replication. It is a single-stranded RNA. When it gets into the cell, we’ll go over this again
with a better picture, it creates a negative strand, a mirror copy of the single-stranded RNA. And then that template is used to then make new versions
of the genomic RNA. Right? That makes sense. This is what you need to package, so you make its mirror image. And then you use that mirror
image to reverse back. So a double mirror image gets you back to the positive sense single-stranded RNA. Okay. So the next thing that really interests me about these viruses. Okay, so somebody is asking me to refresh what a positive strand RNA is. And so basically this is a, you think of DNA as being
a double-stranded molecule where you have two sets of code that directly mirror each other, side by side connected to each other. RNA is usually single-stranded. And so this is just one strand of RNA. And so it has the code,
but the nucleotides are not connected together
with other nucleotides. They’re not pairing. And what positive sense strand means is this is the direction in which the cell should read the RNA to
properly produce proteins. And so it’s in the form right now where it wants to be read like this. And so when it replicates itself, it needs to replicate more of those forms. But it has to go through
this intermediate phase where it makes a mirror image of itself so that then the replication machinery can make a mirror image
of that mirror image, which then produces another, a new positive strand single-stranded RNA. So I hope that that helps. So, getting back to something I’m a little bit more interested
in than just kind of the molecular biology of
viruses, is their mutation rates. This is the first step in
the evolutionary process. And so understanding
what the mutation rate is helps us get an insight into the potential for this virus to actually evolve. There’s actually kind
of good and bad news. This is a theme so far in these lectures. So, RNA viruses in general
have very high mutation rates compared to DNA-based
viruses or DNA organisms. So they have a lot of potential to mutate and change and evolve. But it turns out that this RNA virus has the lowest mutation rate
of the RNA viruses known. And the hypothesis for why it has such a low mutation rate is that it has a very large genome for
the foreign RNA virus. And if you have a high mutation
rate and a large genome, then you have a lot of potential
for errors to accumulate. And you don’t want errors in your genome. Sometimes they’re good,
sometimes they’re adaptive, but most of the time they’re bad. And so it appears that the
coronaviruses actually evolved a polymerase that has a subunit
on it that helps proofread. So as this is replicating here, it is also looking at the code and it has a mechanism to see, oh, shoot, I’ve accidentally incorporated
the wrong nucleotide and I’m going to change that and make sure that it’s not in there, that mutation hasn’t happened. Of course no molecular
machinery is perfect, and certainly not when
you’re replicating RNA. But it is better than the
rest of the RNA viruses. So it should evolve more slowly, a lot more slowly than influenza and HIV. But it still has a relatively
high mutation rate. Lots of errors per replication. And the next lecture is on mutation rates. So we’ll get into the
implications of that in there. Okay, so that’s sort of
what I want to go over on the genome of this virus, on how it’s structured
and its adaptations. So the next question is, well, how does this coronavirus replicate? So, it is amazing. And I have to tell you that when I look at a figure like this, my brain just sort of shuts down. There’s so much stuff going on. I’m more comfortable with mathematics and equations than I
am with these drawings with all of these little
cartoons and so forth. But I want to just walk you through it, because it is really amazing
how these things actually work. And so what we have here
is we have the virus. These large appendages are the S protein. And so the S protein is grabbing onto, for humans, and for
coronavirus, or I’m sorry, SARS-CoV-2, that is going to be grabbing onto this protein called ACE2. That’s what we call a receptor. And so it’s grabbing onto there. You can see that there’s other components of the virus that are also
connecting to the outer membrane. So often viruses will have
receptors and then co-receptors. And so those are other
proteins in the virus that are interacting
with these co-receptors that are on the outer
membrane of the host cell. Once those are, I should say
that the co-receptors are, there’s none known so far for SARS-CoV-2, but they might exist. But certainly ACE2 is the main receptor. Once the viral particle begins to interact with the outer membrane, it then triggers it to come into the cell and initiate the infection process. There’s a couple different hypotheses for how that’s triggered and
there’s not great evidence that I know of yet of which
mechanism it actually uses. So that’s what that is saying. And then once you get inside the cell, the first thing you do is
the RNA goes to the ribosome in the cell and then begins
to replicate that RNA. And then, by doing that, you can then get further copies of RNA that other ribosomes can replicate. And then also, you can begin to produce, I’m sorry, ribosomes are
producing the proteins and polymerases are being produced and then they’re replicating the RNAs. And then, so from there you just have, the cell is really
stressed out at this point and it’s making a ton of new RNAs and it’s making a ton of new proteins. And so that’s what the
figure is showing now. So this is number three, is the polymerase is producing
all of these proteins. I mean, sorry, polymerase is
producing the minus strand. You can tell molecular
biology is not my field. And then the ribosomes are
producing the proteins. And then the minus strand is also
producing, like I said before, it’s producing new strands of
the full length of the genome. So it’s producing small ones for protein replication or production, and then it’s producing these
larger strands of the genome. These things are interacting
with this N protein, which is encoded by the virus. And what they do is they just
take this mess of a molecule and package it up nicely and they bring it over to the endoplasmic reticulum. And this is sort of a membrane
structure in the cell, if you don’t remember. And what’s happening at the
endoplasmic reticulum is that there is also this little
factory producing proteins and putting them into this membrane. And then the RNA is coming together with the membrane that has
these structural proteins in it. And it’s making new viral particles. So that envelope that
we talked about before is actually being donated by the host. And then the Golgi bodies actually move this. And so that’s the last step. The Golgi vesicles actually move the viral particle outside of the cell, and now the viral
particle is free to spread and to move to new cells
within your own body or leave your body and
spread to new people. So, people are asking about, a lot about the details of the pathway. And so one question is, what governs the RNA
polymerase to either make a full length genome or a shorter fragment that is used
then to make proteins? I actually don’t know the
answer to that question. I’m sure I can look that up and go to the discussion board later. So yeah, so I think in general, the thing that makes me
amazed by this whole process is that there must be
incredible synchronization between all of these different processes to come together and rapidly
make these new viral particles. And that synchronization
evolved over time, and it’s incredible. And so there’s a lot of research into gene expression in general, and also viral gene expression and how these steps are
synchronized with each other. But I’m certainly not an expert in that. Thank you for the question. Okay, so let’s move
onto the next question. Does the coronavirus, so now that we know how the coronavirus
replicates, are there any steps in that process that leave the virus vulnerable to maybe
drugs that we could make or some other way that we could intervene? And luckily for us, there are some steps that we think we have medications that might be able to
intervene in the replication and stop them from replicating,
cure people faster, and stop the spread of the pathogen from one patient to the next patient. And so there are three
different classes of these. Oftentimes there’s multiple
different compounds within the class or multiple
different strategies of interfering within
that step in the process. And so I guess I want to
say before we get into the medications that you could think of the virus’s ability to spread
or lack of ability to spread, because as we talked about, it’s an enveloped virus
that eventually will die and if it’s just out in the environment. So we can think of that as a vulnerability that we’re interfering with right now through social distancing
or masks or cleaning our, washing our hands and so forth. Okay, so that’s at the sort of end of the life cycle
of the virus that we’re currently interfering with
its ability to transmit. But there are steps early in the process that we can interfere with too. And so one of them is we can produce monoclonal antibodies
or convalescent plasmid. Okay, so let me explain
what those are in a second. What they do is they
actually attack the proteins. The things that make the
coronavirus have a corona, these S proteins, we can
have them attack these and knock them out so that they can’t, the virus can’t bind to ACE2 and it can’t get inside of the cell. So, monoclonal antibodies
are basically using immune systems to create
these molecules that can attack the virus, like I talked about. And this plasma, I mean,
as far as I understand, what that is is you are taking
plasma blood from somebody who has already survived
an infection and is healed. And so they will have antibodies and they’ll have an immune
response that’s in their blood, that hopefully you can take that and transfer it to another patient. And this is usually not the best way of going about treating somebody. But it can, if you have a
really severe infection. It looks like there’s some promising results so far that it can help out. So that’s an interesting idea. It feels pretty, like, Middle Ages to me. But if it works, we have to use the tools
that work right now. And the other idea is that
there’s also these compounds. These compounds were in the news because somebody took the wrong compound in a high dosage that
thought it was this one in order to act as a repellent to this virus and they ended up dying. So definitely only ever use drugs that doctors prescribe to you. But you can also interfere with this step of endocytosis using these compounds. So we’re waiting at least
a year for a vaccine. But hopefully the development of these products will come out much faster. They tend to not have as many
side effects as a vaccine, which is actually interacting with your immune system to mount a response. The thing that I talked
about in the first lecture where I was in the hospital
for a month and blind and couldn’t breathe for 10 days, that was caused by an autoimmune response. And so for vaccines, they
can inspire those types of autoimmune responses and
have obviously even worse side effects than having the COVID-19. So we need to make sure
that the vaccine is safe. These things tend to have, are acting more directly on the virus and there isn’t an intermediate of co-opting something from your own body. And so hopefully we won’t have as many potential bad side effects and production can go a lot faster. And so I’m hopeful that
some of these will work. Some of these ideas were in
production for MERS and SARS well before we had SARS-CoV-2. So hopefully they work. And I do know that there are
companies even within San Diego that are working on these
multiclonal antibodies. And so one thing before we move on that I wanted to point out is that I am really encouraged that we’re not just going down one avenue,
but multiple avenues. Of course that’s beneficial to hedge your bets so that one of them works. But it’s also beneficial
in that hopefully actually a couple of these things
go online simultaneously. And the reason why I say that, and this is from experience with HIV, and it also plays out given the math and how evolutionary processes work. That if you only have one drug, and if that one drug, the
virus can mutate with maybe one single mutation to be
resistant to that drug, then the first time you use that drug, you are going to select
for resistant variants. And it’s possible that if that
resistant variant escapes, you could then have a
spread of a resistant virus. And so all of that therapeutic
that we just worked all this time on creating
is now no longer functional and no longer cures people. And so that’s a huge problem. And one of the ways that
we’ll learn about to sidestep that problem is to
do, like, a one-two punch. Where you’re hitting the virus
in two of its weak points. And in order for it to evolve resistance, it would have to evolve resistance maybe in two different proteins. And that’s just much, much harder for viruses to do or any organism to do. And so it would be great
if we could start out first thing with a combination therapy. Okay, so, moving onto the next question. I have a question here. Based on how the
coronavirus is replicated, this virus doesn’t kill the host cell. Is death due to the human immune response? Okay, that’s a great question. And I did mean to go over that. So thank you for reminding me. So you’re right. And this is based on the last slide. So I’m sorry that I left
you waiting so long. So yeah, so the cells don’t actually die immediately from the
production of the virus. So some viruses actually have enzymes that cause the cells to burst,
and that kills off the cells. And then if you have enough of those cells being killed off by the virus, then that’s a direct threat on your body and that’s what causes
morbidity and mortality. But what’s happening here
is that the cells can just, they become just factories
for these viruses. The thing is though is that
they are producing so much protein and so much RNA at
such a rapid rate that you begin to get proteins misfolding
and junking up the cell. I’m not sure exactly what’s
going on with the RNA, but certainly the proteins misfolding cause problems for the cell. And so eventually the
cell just dies itself, because it can’t keep up
with that level of production and it has all this junk floating around. So the cells do die as a direct result of the viral replication. Although that isn’t programmed
into the viral genome, that it actually directly kills the cell. It’s just the consequence
of reproducing so quickly. So that helps cause
morbidity and mortality. But certainly this question of
the immune system is relevant and whether or not our own
bodies are hurting ourselves. And certainly it seems that with the coronavirus and other viruses, that a lot of the mortality is not caused directly by viral reproduction, but is your immune system
reacting to the virus and reacting to such an
extent that it ends up killing off too many of your own cells and causing inflammation
and causing problems. So I’m definitely not an immunologist. But that’s sort of what I understand. And I guess I should say that, so a missing piece from that is that one of the actions of the
immune system is to actually trigger cell death of
cells that are infected. And so the idea there is that if you have these cells that are
factories for the virus and you want to kill off the virus, well, the cell is just spewing
out tons and tons of virus. Then your countermeasures
are just going to be swamped out by the
production of new viruses. And so the immune system
triggers cells to die and that stops the virus from replicating. But if too many of the
cells are triggered to die, obviously that begins
to cause tissue damage, inflammation, and so forth. I hope that helps you understand why this thing is so deadly. And remember, the cells
that are being infected, and we haven’t gone over this yet, so I shouldn’t have said “remember,” but the cells that are being
infected are respiratory cells. These are the cells in your lungs. And so you obviously need those. You can’t have too many being knocked out. Okay. What species do coronaviruses infect? Okay, so this is just a very straightforward slide,
straightforward answer. We already know that they’re in bats. They have jumped from bats
to humans in this case. But they spread in a lot
of different animals. These animals are birds and mammals. And so why does that make sense that they would be these two groups? These are big groups of organisms and they’re very
different from each other, except they’re both warm blooded. And so this pathogen is
adapted to bodies that have homeostasis and
maintain their temperatures. Okay, so, there are coronaviruses that we have found in cows and
in horses and in dogs. And so this is kind of scary, because we’re talking
about coronavirus from bats that emerged into human populations. But we are all the time interacting with these other animals. Some of them live in our houses. And so should we be worried about their coronaviruses causing the next pandemic? I think you have to be worried about everything all the time, especially given what we’re
going through right now. But I have to say that the coronaviruses that inhabit these organisms are very, very different than
the one that is causing COVID-19 currently. These viruses diverged from the ones that infect humans a very, very long time ago. And so hopefully the idea there is that they’re distinct enough now that it’s very difficult for them to make the cross. The virus that is in bats
that spread to humans diverged from the human
versions of coronavirus, I would say just decades ago. So they’re much more similar, and the idea is that they have much more potential to cross into humans. So bats seem like the main reservoir. Although in the past it seems that, I think SARS might have had a transition phase where
it went into civets. So that’s what this is here. A pretty exotic, interesting creature. I think it’s related to the weasels. And this is a pangolin. There are ideas that maybe this virus actually came from pangolin. It seems that it
definitely came from bats. Although there is some very few locations in the genome of the current CoV-2 that are similar to ones
that were found in pangolin. So there could have been a little bit of genetic recombination, but the majority of the genome is much more like the bat version. So it seems like it came from there. Okay, so a wide range of different
hosts have coronaviruses. This is a very old viral group, and so it has lots of time to evolve and diversify into lots
of different viruses. Which coronaviruses infect humans? And there’s sort of three big categories that we have hinted at and talked about, but we’ll just be a little
bit more explicit now. We have severe acute respiratory syndrome. SARS coronavirus. So now this is talking about SARS-1. Now we have SARS-2. And so this was an outbreak
that happened in 2002, 2003. There were just thousands of cases. Hundreds of deaths though. So this was very pathogenic. It caused a lot of mortality, given how large the spread was. And we had a slow response. That’s probably why it
got as big as it did. And the reservoir seems to be bats and that civet that we
talked about a second ago. That one seems to be
over in terms of humans. We have SARS-2, which is distinct. There is MERS, Middle
East Respiratory Syndrome, which is actually an ongoing outbreak. You don’t hear about it too often. It doesn’t seem like it’s spreading as much from human to human. It seems localized in the Middle East. And it seems that what’s
happening is that it spreads in camels and that it jumps
from camels to humans. And so that happens also
with bird flu and pig flu, where most of the time they stay. There’s lots of strains that just stay within their traditional host. But sometimes they can jump to humans, but maybe not jump from
one human to another human. Once you have that human
to human transmission, that’s when you have the problem. That’s what we’re experiencing
right now with SARS-2. And then we have a bunch
of other SARS viruses that cause just the common cold. And so there’s four
variants that I know of. There’s probably many
more variants as well. These are under-studied because, well, the common cold is not as bad as influenza and some other pathogens. So we don’t, or at least I don’t know too much about those strains. Okay, moving on. So, is there something
unique about SARS-CoV-2 that allowed it to cause this pandemic? Okay, we have another question. So the question is, when SARS jumped into, so SARS-2 jumped into humans, it’s causing a lot of mortality. And the question is,
when it’s infecting bats, does it have the same
negative impact on bats? Do they die at this high of rate? Are they as sick as we
are when we get SARS? And the answer is no. It’s not as deadly to bats. And so there’s kind of two components to this question that we will cover in a lot more depth later in the lectures. One is how these host shifts happen. And then another one is natural
selection on pathogenicity. And actually, it turns out that
there is a lot of incentive for viruses to evolve not
to kill off their hosts. And basically, if you kill off your host, you’re going to sink with the ship and you’re not going to
spread to other places or other hosts, other individuals. And so you don’t want to do that. And so the pattern seems to be that brand new viruses that have just emerged into a new population
are kind of off-kilter and cause a lot of
mortality and morbidity. And eventually, it seems that they tend to evolve to be less pathogenic. So when we talk about HIV, the sub-strain of HIV that’s spreading the fastest around the globe is actually less virulent than
other sub-strains of HIV that had previously
spread around the globe. Suggesting that this one is favored because it’s less harmful to people. And so we’ll talk about
the math behind that and everything and lots
of aspects of that later. But it does seem that when pathogens co-evolve with their hosts for awhile, they end up becoming more and more benign. It’s not great to have the
common cold, for instance. But it often doesn’t threaten your life. Okay. So let’s go back to what might be unique about this SARS-CoV-2. So really, this question is
inspired by the idea that, well, are there genetic
mutations in this virus that explain why it spread to humans? And if we have that information, then maybe we could figure out how to surveil viral populations to find those genetic mutations and make sure that viruses that have them are eliminated from bat populations. Or you could imagine if that’s a way to identify the weak point of the virus, you could intervene by
maybe those mutations creating some kind of susceptibility to a compound or a therapy or something. But it’s also just, we’re
scientists and we want to know why things happen and why this strain. And so I don’t have a great answer. There are some interesting hints
at what might have happened and what might be some genetic mutations that helped facilitate
its spread into humans. And so obviously people have to do these experiments to figure this out and so that we know what to
look for, what problems are. Okay, so there was a paper published in, I think January, Zhou et al. So, in Nature this year. And they compared genomic sequences of this virus to many other viruses. And they found that they did
have a version of the virus that they had isolated in bats awhile ago that shared 96% identity with the SARS-CoV-2 that’s
now spreading in humans. So to some people, that suggested that, well, this seems very
similar to other bat viruses. And so maybe it’s just not, it’s not predisposed
genetically to infect humans, but it’s just kind of this unlucky thing where a bat virus got
into humans and spread. But actually, in that 4%, and there’s a lot of potential mutations. And we have shown in my
lab with a set of viruses, and other labs with influenza, that a few critical mutations in a genome can actually facilitate
host range expansions. And so I look at that
number and I say, okay, it is very similar to things that are in nature that we’ve found before. But that doesn’t really tell me about, it doesn’t let me rule out the hypothesis that there’s a genetic
change in this virus that allowed it to spread to humans. What they also pointed out in this paper is that there is this interesting
pattern in the S gene, and in an important part of the S gene. And so what I’m showing you here is our amino acid sequences of a
region of the S protein. And they are aligned so there are one, two, three, four, five, six, seven different genotypes. So seven different individual viruses that they have the sequences for. And so they are aligned to each other. And we have multiple rows. One, two, three, four, five, six rows. That’s just the sequence stretched out. And then repeat, then move
to the next line down, then move to the next line down, and move to the next line down. And so we can look at
here and you can see that there are similarities and differences. If you want to know sort of what exactly all of these strains, that the IDs relate
to, look up this paper. But the important part is
that these two at the top, this is the virus that spread into humans and this is a close, close
relative that they found in bats. And so they’re looking to say, is there anything in these viruses that are distinct from
the rest of these viruses? Because those differences
then become our hypothesis for what might have enhanced this group of viruses’ ability
to spread in humans. And what they find, which I find extremely
interesting, are insertions. And so those are highlighted
in those blue boxes. Insertions are relatively rare. So insertions are a type of mutation that we’ll go over next lecture. And they are where you actually
put in new nucleotides. And often they’re rare because the polymerases don’t tend to
make those kinds of mistakes. And they have really deleterious
effects, often on proteins. So, but when you see them in sequences, they’re something to
look at because they can radically change the
function of the protein. Especially if they’re in the correct spot. And so there’s clear differences between these strains and these regions. We know it’s important
for binding to the ACE2. And so our hypothesis is that
these might be responsible for why this strain of virus
could spread so well in humans. The reason why I also highlight this is that in the virus that I study, and we’ll talk about it later
more in-depth in the course, when we look at natural
variance of that virus, it has this kind of pattern of insertions and deletions in its
host recognition protein and we were able to show
that those insertions and deletions are related to its ability to change its host range. So I think drawing on my research and these patterns in this, I would strongly propose the hypothesis that these are responsible. But this is just a hypothesis. This is not tested yet. The research is ongoing. Okay, so the question is from the class. What action did humans commit in order to get COVID-19 from bats? From the genomic data, we
can tell when this happened, or roughly when this
happened, where it happened. But it’s very difficult to understand exactly how the virus got
from the bat into the human. Certainly bat droppings. I know that human feces from patients of COVID-19
have viral particles in them. So that’s a possibility. Or maybe just being nearby, if this was spread by an aerosol. So it’s really impossible for us to know. But certainly, like I
said in the first lecture, we should just limit our
contact with organisms, with animals that we know have
just diverse sets of viruses that could possibly jump
into the human population. Let’s move forward. Oh, and so this might make
you paranoid about the bats maybe in North America
and trying to avoid them. People are obviously
naturally afraid of things like bats flying around at
night and things like that. I’m not personally afraid of bats in the neighborhood or whatever. But I don’t know. Keep things clean and sterile and avoid direct contact
with wildlife, I should say. Okay. Is SARS-CoV-2 evolving? You know the answer to this because this is the evolution
of infectious disease and I would not ask that
question if the course that I’m teaching was not relevant. So, yeah, I’m sorry. I definitely have a
mix-up with the slides. So, the ordering of the slides. So this is that data that we’ve looked at a couple times now. But now I’m showing you new
data, which is over here. Which is, it is basically this phylogeny, but right now the y-axis on
this phylogeny is arbitrary. It’s just sort of creating distance so that you can see these
bifurcations in the tree and you can see the
evolutionary relationships. But on the right what we have is, you still see these evolutionary connections between all of the points. But now the y-axis is number of mutations. And so what we can see
there is that over time, the virus is accumulating
lots and lots of mutations. And so absolutely, this virus is evolving. The only reason why we can track how it’s been spreading is
because as it’s spreading, it’s accumulating more and more mutations. And you can think of that
as a molecular fingerprint that we can read and create
these evolutionary relationships and literally go back in
time and retrace its steps. We will talk a lot about
that later in the lectures about how to build a phylogeny and the logic behind retracing the steps. But what this graph is showing us is that, yeah, they’re just continually mutating and changing
and now diversifying. So now we have lots of different strains with different sets of mutations. And what’s fascinating is that the accumulation of mutations
is what we call clock-like. It is highly repeatable
and there’s a certain rate at which these strains are
accumulating mutations. And that rate is 23.988
substitutions per year. And so we will talk a lot
about molecular clocks and how to establish that rate. It’s not the mutation rate. It’s influenced by the
mutation rate of a virus, but it’s not the mutation rate. And next time we’ll talk about how to quantify mutation rates, and then later we’ll talk
about molecular clocks and how you compute them
based on mutation rates. But they’re not always
directly mutation rates. Okay, so certainly this thing is evolving. But often when people are asking the question is something evolving, what they really mean is,
is something adapting? Often we think of adaptation
by natural selection as being synonymous with
evolution, but it’s not. There’s lots of different
evolutionary processes that contribute to the change
in a species over time. That’s the definition of evolution. And natural selection is just
one of those many processes. It’s the coolest one. It’s the one that gives us all of these interesting innovations and adaptations. Or at least from my perspective, I think it’s the coolest process. But it’s not the only one. So yeah, so it’s just
rephrase this question. Is there evidence that
this new virus to humans is actually adapting to humans? As it’s spreading around the world, is it accumulating mutations that better able it to use us as hosts? Those mutations may make it
worse off for us because it may spread better from one
person to the next person. Or those mutations may
allow it not to kill us off so that it can exist
within our own bodies, its own host, for longer
and spread to more people. And so these adaptations to us can be bad, but they can also be good for us. You could get a strain in the
future that is less fatal. So, but just the question. Forget about its impact on us. Is it actually just adapting to us? And so obviously data is
really preliminary still. But there are some interesting patterns. Let’s start out with just the, this is an output from
that And what this is is this
is the genome laid out on the x-axis from left to right. This is now a more formal
picture of the genome than that cartoon version
that I showed you before. Now things are all to scale. We have ORF1 and ORF2. Somebody asked me to repeat what ORF is. It’s open reading frame. So this is used to produce an amino acid, a chain of amino acids,
a peptide that then gets cut up into lots
of different proteins. Okay, so this is the genome. And what is now plotted
on the y-axis here, and we looked at this in the
last lecture too, is diversity. So it’s going along the genome. And most sites in the genome, most of the viruses that we’ve sequenced have the identical nucleotide
at those positions. But there are some positions in the genome where we actually see lots
of different variants. So maybe you’ll have an A or a G or a C. Different strains will have
those different nucleotides. And so this is just highlighting
points in the genome that are doing something different. There’s lots of genetic variation. And we have a natural
inclination to say, well, if there’s a lot of evolution
happening at a site, well maybe that site is under
natural selection to change. This is called positive selection, and we’ll go over it soon. And that inclination actually is, there is evidence with other studies of other epidemics that, yeah, these sites that have a
lot of genetic variation in the virus population actually, and we call this variation polymorphic. So these polymorphisms
indicate that that is probably changing because
of natural selection. And so one of my
colleagues, Tami Lieberman, is the one that proved this. And so we’ll talk about her work. It was actually on bacteria. A bacterial epidemic,
not a viral epidemic. But I believe that the patterns probably hold for that epidemic
and this one as well. And so these sites of enormous variation are likely sites in different proteins that are under positive selection. Maybe not all of them, but I
bet a good subset of them are. And so I’m honing in on this S gene. This is the host recognition gene. This is what makes it a corona. And so people have studied this gene and this genetic variation in that gene in much more depth than
the rest of the genome. And there is a pre-print. And so a lot of the information on the ongoing outbreak has not
been peer reviewed yet, but has been published online so that we can get data faster. There’s a hazard in this in that if they made the calculations improperly or if they did something wrong, it might have been caught
by a peer reviewer yet. And so you should think
of this as a caveat, that what I’m about to tell
you has not been proofed by other people yet,
has not been reviewed. And so there could be something wrong that the authors accidentally missed. But the patterns that they show are so strong that I
actually do trust them. Okay, so let’s move forward. So here are a bunch of data
that’s focusing on that S gene. So this, you can think of
this little panel here, is zoomed in on this panel. You’ll notice that the pattern
of spikes is different here. This is because this paper
was using older data. This is data from just this morning. And so that’s why this
pattern looks different. What is this up here? This is just a, it’s a zoomed in diagram
of this single gene. So we have multiple subunits. And this RBD is the region that actually interacts directly with the ACE2, the host receptor, the host protein that it
uses to infect the cell. So that’s why it’s
highlighting these things. And so we see that there
are certain positions in this gene that have genetic diversity. And what they did is they did two computational studies that
I find very fascinating. One is that they took different segments of the gene, corresponds to here, and
they calculating this thing that you guys will learn how to calculate. A dN/dS ratio. What you need to know at
the moment about this ratio is that it’s a way of
looking at genetic sequences and detecting whether
or not natural selection has acted on those genetic sequences to drive the increase of variants. So whether or not natural selection is favoring certain genetic variants. And the way that dN/dS ratio works is that a value above one
means positive selection, a value of one means no selection, and a value below one means what you have purifying selection where there’s selection for the virus not to change. The virus is already optimal. So our hypothesis naturally is that the virus is not well adapted to humans. And so as it spreads in
the human population, it might be accumulating
adaptive mutations that helps it better spread
in those human populations. And just looking at S and looking at these different regions of S, you can see that you have
actually very high dN/dS ratios. This infinity, that just means that the signal was so strong
for natural selection acting in a positive way to change the amino acid sequence of the protein that is broke the math
behind the dN/dS ratio. And so it just means that it’s
a very, very strong signal. As strong as it possibly could be. But all of these values are above one. And so it suggests that, yes, S is evolving in a way that’s adaptive. And then moving onto here. Now this is even more
complicated than the dN/dS ratio. So let’s not worry about the details. But they have computer simulations that can model how this S protein interacts with ACE2 in humans. And what they can show is that actually, on this graph here, a lower
value means that it interacts better with the human
receptor than a higher value. And so these strains or these sequences that are from bats and pangolin CoVs do not interact as well with the one that is spreading in humans right now. And then there’s a bunch of, each one of these is a
mutation that was found in strains that are spreading in humans. And as you add in those mutations, a lot of them do cause a significantly tighter fit between the S and the ACE2. So that’s assumed to be a
stronger, more stable interaction and be able to facilitate
infection better. So the take home message, we’re not going to be to understand all of the details behind these figures, is that there’s genetic variation. Lots of genetic variation
among the viruses that are spreading around the globe. When we zoom into a single
gene that we know is highly, highly affects whether or not
this virus can infect cells, we do an analysis to show that there is absolutely positive selection
happening on these sequences. And that this is just a
computational way to say that, well, we think the positive selection is actually resulting in
better molecular interactions between that S protein
and the ACE2 protein. And so that should help
facilitate infection, a more efficient infection of human cells. Okay. So this is the last question, and I’ll make it as quick as possible. Obviously I’ve had fun describing all of this stuff to you guys. I can’t believe that this
lecture has gone on this long. But the question is, are the red coronaviruses
the most virus-y? And so this question actually
comes from one of my friend’s kids who sent me a video
asking me this question. And so the question is, I think it gets to a larger important
question about coronavirus. It’s based on the fact
that all of these images of coronavirus have these
red proteins on them. Obviously, not obviously,
but viruses don’t have color. These are colored this way just so that we can see these features
on the virus so that we can distinguish different
proteins from each other. The reason why viruses
don’t have color is that they’re actually just so
small that waves of light don’t even interact with them. They just pass through them. So, but that leads us to a question. Are some coronaviruses more deadly, and why are they more deadly? So we have that whole spectrum of viruses that we talked about before. This goes from common cold to common cold to the SARS outbreaks to MERS. And so we’ve kind of already talked about this spectrum already. And the leading hypothesis for why some of them are more
dangerous than other ones is what region of the
lungs they tend to infect. And so the ones that cause a lot of problems are in these upper regions, and the ones that cause less of a problem are in these lower regions. That’s just the hypothesis, but I think it’s a pretty good one. So which cells they are able to target and prefer can influence how
pathogenic these viruses are. You can imagine them
evolving to be able to prefer different sets of lung cells
so that they cause less harm. Hopefully that is what is happening. Thank you. I hope you enjoyed this. Take care. Social distance. (calm music)


4 thoughts on “The Evolution of Infectious Diseases with Justin Meyer: Lecture 2-Ten Questions About Coronaviruses”

  • yes, everyone (especially the media) really needs to stop getting excited over a one or two day glitch in numbers.. of course it's human nature to desperately search for something that might vaguely resemble a glimmer of hope, but that's really not how this kind of thing works.. i'm not even willing to CONSIDER something might be a possible downward "trend" unless/until we have a full WEEK of numbers to substantiate it.. throwing a party based on anything less than that and they just embarrass themselves and raise false hopes, only for the public to have them dashed (plummeting them even further into demoralizing depression).

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