Hello and thank you for listening to the MicroBinfeed podcast. Here we will be
discussing topics in microbial bioinformatics. We hope that we can give you some
insights, tips, and tricks along the way. There's so much information we all
know from working in the field, but nobody really writes it down. There's no
manual, and it is assumed you'll pick it up. We hope to fill in a few of these
gaps. My co-hosts are Dr. Nabil Ali Khan of Enterobase, GrapeTree, and
BrakeFame, and Dr. Andrew Page of such works as Plasmatron 5000, Rory, and
Gubbins. I am Dr. Lee Katz, and you might know me from my tree-making pipeline,
MassTree, or my SNP pipeline, Liveset. Both Nabil and Andrew work at the Quadram
Institute in Norwich, UK, where we work on microbes in food and the impact on
human health. I work at the Centers for Disease Control and Prevention and am an
adjunct professor at the University of Georgia in the US. Hello and welcome to
the Microbial Bioinformatics podcast. Andrew and I are co-hosts today. Nabil is
on a much-needed break. Our guests today are Kevin Libouette and Curtis Kapczak.
They each started off with a college track in biology and then graduated with a
master's in biology from James Madison University. Kevin was the lead
bioinformatics scientist in the Virginia State Public Health Lab, DCLS, and a
founder of the Staff B workgroup. Most recently, he joined the bioinformatics
contracting world through Theogen Genomics with Curtis Kapczak and Joel
Savinsky. Curtis began his career in Colorado with Joel Savinsky for just a mere
eight months before we nabbed him as a contractor at CDC on my team. However, in
just the last two years, Joel has started his own company to help public health
labs and has already started subcontracting. It is bittersweet that Curtis is
now one of those subcontractors with Joel and has left my team. Okay, so Kevin,
you've had quite an interesting career so far. You're not that old, certainly a
lot younger than me, and you've gone from biology into bioinformatics and then
you went into the state labs and now you've gone into industry. So you've got
quite a nice range of activities that you've gone through. So first of all, tell
me about, well, why did you go into bioinformatics from biology? Why didn't you
just kind of stay in that beautiful world of pipetting and white lab coats?
Yeah, no, that's a great question. I'm glad we're talking about this on the
career aspect too, because I definitely know I have a bit more of an unorthodox
path to have gotten where I've gotten. And I like sharing this ideas out there
because I'm sure there's some early career or even students who are looking into
a career and not knowing how to make their own path. So I've had the opportunity
to do that and been mentored by a lot of people that have given me that
opportunity. So at the jump though, even how I got into biology is how I think a
lot of at least US biologists get into biology in that we get into university
and we have some level of a draw to sciences and we want to help people. And
that's kind of like our baseline heuristic of how we decide our majors and
things. And if you go into an undergraduate institution in the US and you look
at the biology majors, you're going to see an overwhelming focus on pre-med. So
you come in with those two basic premises. I like sciences and I want to help
people. The only careers available to us in our minds that have a level of
prestige as well is being a physician. And so a lot of us get into biology
thinking, okay, we like the sciences. We want to help people. Let's be
physicians. On that route, I think a couple of things happen to a lot of
students. First of which we start to understand what it means to be a physician
and what that world actually looks like. And some of us decide, I don't know if
that's necessarily the route I want to go. And that's actually what happened to
me. So I got into a research laboratory at James Madison University with the
intent to bolster my med school application. But as a product of that, I found
how much I really enjoyed biological research and contributing to the scientific
discussion. So at that point, it wasn't just biology was being taught to me, but
I was really having a participation in the conversation that is biology that
sort of seeded an interest in me and like opened a whole new career door of
career opportunities of like, okay, maybe a career in sciences is the route I
want to start walking. And so I did that. So I really dove into the research
laboratory that I was in under Dr. James Herrick at James Madison at that lab is
where I met Curtis and we started working together and Curtis can speak on this
as well. But we come from that similar path in that Curtis was pre-med and we
both like found a real love for research and communicating the ideas that were
our own. And then so Curtis and I were in a traditional microbiology lab and we
had the white coats and we had the pipettes. Though I will say our white coats
were tie-dyed purple and gold, our university colors of which I think, yeah,
we've since handed down to the university and they still use those tie-dyed lab
coats. So we were those guys. Can I add? I think Dr. Herrick still teaches in
those tie-dyed lab coats. Yes, yes. So, and then also there was a, not to speak
against anybody who's going the pre-med route, but it is relatively competitive
to be on that route, especially in the US. Whereas in the research world, even
if it evidenced by this tie-dyed community thing, but there was a collaborative
spirit that we really enjoyed. And that, as we talked in the last recording
about Staff B, that spirit of collaboration and communication and open source
development is something that Curtis and I were exposed to early on in the
research world and that being what really drew us to it. So where did you first
get exposed to bioinformatics and sequencing data and things like that? Yeah. So
our focus at university was on antimicrobial resistance and the horizontal gene
transfer elements of plasmids. And so at first we were focusing on what is the
observable antimicrobial resistance in the environments we were investigating.
And so a natural follow-up question to that is, okay, we have started to define
the phenotype. What is the genotype behind this? And so right after, or as we
were working on our programs or our projects, the university got a Ion Torrent
actually sequencer at the university. And so our PI was like, Hey, you guys want
to sequence this? Was it one of the original PGMs with the iPod dock? Yep. Yes.
Yes, it was. And it was, it was, it was a wild experience. I think like my first
year of my master's program was learning how to run the Ion Torrent PGM. And it
was, it's amazing. You know, it's funny because like throughout my whole career,
I've always had like professors and mentors who talked about, Oh man, you don't
understand how far the technology has come. But now even like just five years
into my career, I can say that same sentence of like how difficult it was to
just sequence one plasmid on the Ion Torrent PGM. Now I'm helping laboratories
sequence thousands of SARS-CoV-2 samples without even, you know, batting an eye,
but either way. So the, yeah, so we got into sequencing through the university,
procuring some instruments and also through a collaboration with Oxford Nanopore
and their early access program. So we learned how to sequence samples and
generate data. Then we had a bunch of data. And then, so just, you know, to
complete the thesis, it was learning how to analyze these data. So Curtis and I
were really lucky enough to be mentored by Dr. Stephen Turner, who at the time
was the director at the UVA Bioinformatics Corps. We kind of learned by
observation. He would do an analysis. He would share the scripts with us. And
then Curtis and I would try to in some way recapitulate what was happening and
ensuring that we can generate the same outputs. And then we found a real love in
the computational world. I think, and Curtis can speak on his own side of this,
but I just like the quicker feedback loops relative to growing microbes. And,
you know, when people talk about lab hands, that's a thing, right? There's like
a bit of an art to being a good wet lab scientist. And that was a skillset I was
less inclined to develop relative to my computational skills. So I just prefer
the quicker feedback loops and being able to also scale what we were building.
We talked about the containers and how widely distributed that is. That was a
big draw for us. And then when I graduated, that was also the needed skillset in
public health. And that's kind of where my career has taken off from there. I
agree with all of what Kevin said. He says it so well. I too was on the pre-med
track. I wanted to be a doctor. I watched a lot of the TV show, House MD. And
Hugh Laurie was my idol. Right. But I too fell in love with research and
eventually dropped the pre-med program and pursued research. You know, I did my
undergrad in biology and stuck around for a master's to dive deeper into it as
well. So, yeah, I agree with all of what Kevin said. Sorry, can I say on the
point of Hugh Laurie, have you seen Blackadder? Uh-uh, no. Oh, you have to see
it. It's quite a different side of Hugh. Yeah. Blackadder, it's a classic
British TV comedy show. How's it looking that up? One caveat. Yeah, I think the
U.S. perspective of Hugh is much different than, you know, the European
perspective of Hugh. You guys know him as like this sort of goofy, gaggy guy
with like humor and his work with, oh my gosh, I can't believe I'm not coming.
Stephen Fry. And like the kind of a funny niche of like hyper academic, funny
people. Right.  were introduced to Hillary as like this serious actor,
investigative M.D. guy. Yeah, I was introduced to Hugh Laurie as the passenger
who sat next to Rachel and friends. Now, that was the one that I got. That's
good. That's good. That's funny. He made an impressionable cameo on France.
Yeah, but but getting to what Curtis is saying, I think this that's why I love a
podcast like this, because Curtis and I come from that same world. We we didn't
know what else you did with liking science and wanting to help people. So it's
like that was the one career that was broadcast to us. Like a guy who thinks
about problems deeply and helps people. It was like that was our media of
entertainment. So like you, Laurie was was in Dr. House was the sort of idol
that that we we we found. So, yeah, podcasts like this. And I want to give a
shout out to the to the Skype. A scientist program is a really incredible
program. I'll I'll give some more information. I wish I had the names up at the
top of mind. But it's an initiative to expose students to professional
scientists in a way that they can start to relate and understand what are the
different professional avenues available to them if they have some affinity to
the sciences and also, you know, altruism and wanting to impact the community in
a positive way. So you did some mathematics in your master's. And then what did
you do next? We both sort of did a similar thing. I believe Kevin started an
internship first at the Virginia State Lab. Yeah. But immediately following, he
started his APHL slash CDC bioinformatics fellowship. Right. And so for those
that don't know, APHL is the Association of Public Health Labs. They're a
nonprofit organization that supports public health labs across the country. They
interface with the CDC, with many other organizations. I'm not listing here, but
they offer a one or two year bioinformatics fellowship where you're placed at
either a state lab or a CDC federal lab, and you spend a year or two developing
bioinformatics skills, working on a number of projects that that lab, your host
laboratory is participating in. So Kevin did his fellowship at the Virginia
State Lab, and I was placed at the Colorado State Lab for for my fellowship. So
that for me was when I really dove into doing bioinformatics full time, whereas
in my master's, it was a mix of wet lab, you know, science and microbiology and
prepping DNA for sequencing, but also a little bit of bioinformatics. But now
it's full time bioinformatics all day, every day. And I love it. So that that
initial placement that you had, were you? I hope you weren't the lone
bioinformatician, you know, and you actually had mentors on site to actually
guide you through all of this different stuff. Yes. Yep. You make a great point.
Yes. So as part of that fellowship program, the laboratory that is going to host
you also requires there to be a mentor there. And for, you know, given projects
for the fellow to do during their time. So I was very lucky to have an amazing
mentor, Joel Savinsky. I spent eight months there at the Colorado Lab learning a
whole lot and learning a lot from Joel, as well as the previous bioinformatics
fellow, Logan Fink. He was he was there. So I was lucky to not be a lone
bioinformatician. I had the support of both Joel and Logan, but also that time
is when I was introduced to the StaffB community. And, you know, there started a
the StaffB started a Slack channel, which has been very, very useful and
valuable to communicate with all the bioinformatics scientists at the state labs
and CDC as well. And yeah, so it's it's been a great environment to be a part of
because everybody, you know, they're in the in pursuit of the same goal of of
improving public health. So it's a it's a very great environment to be a part of
great people to work with. And not to put another back in my day comment here.
But even though Curtis was, I think, just a year or two after me in terms of
starting his bioinformatics fellowship, when I started my bioinformatics
fellowship, my cohort, we didn't really that no one there was no extant
bioinformatics mentor at any public health laboratory, really. So that in that I
say that to say how incredibly quickly APHL-CDC bioinformatics program has grown
and matured. Because at this point now, any fellow that is taken on, they have a
whole community of practitioners that they can plug into, whether or not their
host institution has, you know, card carrying bioinformatics scientists to
mentor that incoming fellow. Nonetheless, they're going to have guidance
throughout the entire staff, the community. So how far down Robert Hill did you
go? I mean, were you guys learning about genomic epidemiology and, you know,
actually going and investing in the outbreaks and things like that for your
state? Or were you stopping more at the infrastructure bioinformatics analysis
end? So I think there was like three main pillars of bioinformatics integration
when I started, and these are are starting to be solved to a large extent. But
these are still, I think, the biggest challenges that we were facing as coming
into public health, because especially in 2016, I think I had mentioned either
on this or the previous podcast, I was the only bioinformatics scientist in the
state of Virginia in the Mid-Atlantic region. There was challenges on every
front, and the three main challenges was infrastructure development, like you
had mentioned, Andrew, like getting the compute resources to support this work.
The other major challenge was workforce development. OK, now I'm speaking a
completely different language than the collaborators that I'm working with in my
host institution. So getting them up to speed on what this technology is and how
does it inform public health? And then the third pillar is doing the actual
bioinformatics work itself, getting the tools to run on the resources that the
laboratory has and then starting to perform those analytical processes of
genomic epidemiology. But I think even before any of that, the first things that
was actually working on was quality control. And that was also a big change from
academics versus being in public health. And not to say, obviously, quality is
of most importance in every field. But at public health, you know, it informs
action, government action and intervention. So it's held to a different
standard. So at Virginia, that is absolutely the motto, is standing behind the
quality of the data that we end up reporting. So that's where Denise Toney, the
director of DCLS, wanted to focus a lot of my time is on ensuring we had quality
control set. So that's that's where we were starting over the past five years.
Then we started to get into the more, you know, biological questions of genetic
relatedness, genomic epidemiology, AMR detection and everything in between
there. But it started first with, can we have confidence in the data we're
generating? And so I presume you guys started with one pathogen and then you
kind of snowball from there as people got more used to using it, actually, for
taking action in public health labs. So what organisms did you start off with?
And then how did you see that progress over your time in those labs? Yeah, so
for me, what I was working on primarily in Colorado was enteric foodborne
pathogens. So salmonella, enterica, E. coli. Those were the probably the the two
pathogens that were sequenced in the highest volume. But we also worked on other
pathogens that are that are important to the PulseNet program. So things like
Listeria, Campylobacter, Shigella. Don't don't worry about heading on. There are
too many. So after enterics, I had the opportunity to work on some H.I.I.
pathogens, some Klebsiella, some Citrobacter, I believe, and a few others here
and there. And then post fellowship, I was working full time on enteric
pathogens at CDC. And now in my my role, it's full time SARS-CoV-2. So I've made
a quick transition and I'm I'm learning a whole lot now. Welcome to the club.
It's been my life for the past year, and I know Lee has been dragged in. Nabil
obviously works for me, but he's been doing it for a year. I think everyone now
has been dragged into SARS-CoV-2 in some way or another. I have exited. We'll
miss you on the toast team, man. Yeah, your presence is missed on the toast
team. Thanks. So I've heard I've heard how you guys have transitioned from
biology into bioinformatics. And then you went and then yada, yada, yada. You're
in the APHL Bioinformatics Fellowship. How did you guys decide on public health?
Like, go. I mean, I think it's a great career choice, obviously. But I mean,
that it is different than going into medicine. What made you go in or, you know,
other academic kind of laboratory science? What made you go to public health?
Yeah, that's a great question. And something I don't actually think about often
enough. But my professional network was growing and those opportunities became
exposed to me strictly through my professional network. I didn't I mean, I kind
of knew what public health was. And like I knew what the CDC was and what the
FDA was. But I didn't know a single public health scientist. But my P.I., Dr.
James Herrick at JMU, he's really proactive in connecting with the different
industries and and he kind of broke down, OK, there's government work, there's
industry work, and then, you know, everything else in between. And he had a
project with I think it was started with the FDA in Genome Tracker, and they
were trying to, you know, decentralize some of the surveillance sequencing
efforts. And then that got him in contact with DCLS. And so all that to say, a
lot of that was outside of my control. And it was kind of the first professional
opportunity that got presented to me as I was graduating. The one priority I had
in mind was that I wanted to be able to travel, take some time off to travel to
South America. Right. And so.  I figured, okay, I'm going to graduate. It's
going to take some time to find a job. I might as well, you know, I pursue the,
this, this, the traveling bug I have here. And I didn't even concern myself with
professional job seeking quite yet. So I kind of had that as a plan. And then
Dr. James Herrick said, Hey, Virginia public health system. They're looking to
bring on bioinformatics applications into the lab. Uh, would you be willing to
do this? And I was like, Hey, you know, uh, I'm really trying to spend some time
in South America. I'm not sure if I could do it. And then he said, well, it's
completely remote. You're going to be doing cloud computing. So I thought, okay,
okay. I think I could do this. So my first bioinformatics position with the
state government, I served from Bogota, Columbia. And I was able to do that
through AWS cloud computing that was made available to me. So that's how I got
in. So that in terms of how I chose public health, I hate to use this, but
public health chose me, right? Like it was the opportunities aligned. My
professor had an opportunity that aligned with being able to also travel in, in,
in the way that I wanted to travel. So, uh, that's how I came to public health
and I was made aware of it. And then I realized how much everything that I
wanted to do in terms of applying science, applying deep thinking and helping
the community was already there in public health. So any advocacy for more
public health scientists in podcasts like this, this is what I I'm an advocate
for it. I want to more people to realize that this is a career opportunity here.
That is super interesting. I never knew that about you, that you worked remotely
there. Yeah. Yeah. I didn't tell DCLS into a couple of months, like a year
later, I was like, Oh, by the way, that fellowship, like it was completely
remote. I, I was in Bogota and it was like, and you know, it was, it worked out.
I had cloud computing and even now that that skillset of using cloud resources
allows, you know, Curtis and I, for example, we have international partners now,
just the other day, we were helping CDC Thailand analyze their MinION data. And
that's all based on these Google cloud distributed resources. Something that I
picked up by being in Bogota and helping DCLS on their first bioinformatics
initiative for, I think it was, it was probably Salmonella at that point. Yeah.
So can I ask, what happened with your honeymoon? Oh, okay. Okay. Yes. Yeah. But
good question. Okay. And so there wasn't a honeymoon. So it was, this was a
sabbatical story that that's worth telling. So 2016, I got into public health
bioinformatics at DCLS and, you know, I had a crazy opportunity to really be a
part of the building of a program. And then that turned into a mid Atlantic
regional lead for bioinformatics. And it was an incredible opportunity. And I
got to be a part of the national conversation at a really early stage. And my
wife who's a physician assistant, she also has a pretty, you know, demanding job
in her life. And, you know, in early on in our marriage, this was okay. We
understood that our professional pursuits and things like this, but we also made
the personal decision that we want to take some time away from our professional
lives and pursue some of our personal interests. And so in 2019, we had made the
decision that 2020 was the year that we were going to have a bit of a self-
funded sabbatical. We were going to do an international trip where we had things
set up in Spain, in Vietnam and Argentina. Um, you know, I'm in public health,
she's in healthcare. So we, we had a couple of professional things set up with
educating, uh, laboratories there, and she was gonna work in the hospital
systems. I applied to the Fulbright funding. So I was like on the roster. So I
had like some funding available to me there as well. And 2020 was going to be
the year we could relax and enjoy ourselves and focus on like, you know, things
that we wanted to focus on, uh, on a personal level, you know, just as husband
and wife. And so we made that announcement in 2019 and it was like, Hey, this
has been great guys, like, but we're going abroad. Right. And then, you know, I
think I was scheduled to leave in February and then we had travels all the way
up until the end of the year, uh, 2020, of course, you know, that all got thrown
to the side because of, uh, the global pandemic. So I ended up staying with, uh,
Virginia's public health lab until July or so. This allowed me to develop a lot
of their critical SARS-CoV-2 bioinformatics, uh, resources there and also hire
and train my replacement. So, you know, not wanting to just leave at a time
where, you know, a global pandemic is happening. So that, that gave us
opportunity to do that. Nonetheless, my wife and I still had this desire to
spend some time between she and I. And if anything, you know, being a global
pandemic, I think highlights the need of taking time for your professional
pursuits, uh, especially, you know, uh, as a husband and wife, my wife and I saw
that as an utmost priority, um, if anything highlighted by a global pandemic. So
in July of last year, um, once I knew DCLS was set with my replacement and they
had the base infrastructure for SARS-CoV-2 analysis, we ended up leaving. And so
instead of an international trip, we took a three month domestic, uh, sabbatical
in which we, um, you know, we envisioned like, you know, meeting people in
cities and learning languages and doing all these things. But what it came to be
was spending a lot of times in the back country of America, like national parks,
national forests, a lot of backpacking and camping and seeing the, the amazing
spread of, uh, geography in the U S. Um, and at that time too, still, you know,
being able to focus on learning who I am and who my wife is, you know, like
throughout early stages of my career. I remember it was kind of a funny feeling
getting like subject matter expert kind of put associated with my name. And
that's, you know, that was a testament to how much time and mentorship I had
throughout my career, but in the same respect, you know, I wanted to be a
subject matter expert of, of being a husband, uh, being a supportive, uh,
partner to my wife of knowing who I am is outside of my professional endeavors.
So that three months allowed us to do that. I will say though, too, it was still
pretty scary to do, uh, leaving a position that I was in as a lead scientist at
DCLS, that's a position. A lot of people seek from the onset is like the goal
position to stay in being a lead scientist at that level. And, um, but knowing
that this was something that my wife and I wanted to do, we made the jump, we
made the leap of faith there and now being on the other side of it, it's only
helped my career. It's helped to, uh, you know, further underline who I am and
why I want to do what it is. I do. I had the time to take a step back and
reflect, you know, what it is I want to do with my career and how I want to
contribute to, to what's happening in our community. And, um, in the time off
has allowed me to, you know, come back with a clearer mind and now working with
the agent, uh, we're working at a hundred miles an hour. It's so it's a pace
that I don't know that I could sustain if I had not been able to take some time
away and then step back into the community. Cool. It was kind of scary taking
three months off. And maybe that's not true for Europeans. I think Europeans
have a different work life, uh, balance and culture on leave and things like
that. But not many people do that in the U S. Uh, but now being on the other
side of it, it's like, oh, that was like a blip in the career. No one even
mentions it that much anymore. It's like, it's, it hasn't in any way negatively
impacted my, my career opportunities, if anything, it's been a cool talking
point that people can relate to on more of a personal level and kind of opens
the doors for communication in that way. I still remember the bad luck, Brian,
uh, me and you that day, like plans, uh, uh, international honeymoon. But
endemic, exactly, exactly. Yeah. And yeah, DC less was really supportive about
it. Uh, I think, uh, you guys see this as well, but the public health community
does a great job of recognizing the people that are public health scientists
and, and, you know, recognizing that this is a demanding job and, you know, when
people need to take off, I think, uh, I've only seen encouragement in that
respect, um, whereas, you know, internally in my mental dialogue, I didn't, I
thought it would be looked at as a smudge or like selfish in some way, but it
really hasn't been the case in any way at all. I mean, in European terms, three
months is nothing, you know, it's, yeah, yeah, exactly. Yeah, it's a long
weekend. Um, okay. So, uh, you've made the jump into, into contracting, so that
must give you a huge variety of projects to work on. Or is it more focused just
on say SARS-CoV-2 because everything is focused on that these days? Yeah. With
being in the contracting world, it is, there is, yeah, more explicit. Objectives
in that way, but it also still gives us the wide variety of partners that we can
work with at DCLS. You know, I was in Virginia and Virginia was my priority as,
you know, and I don't say that as, as any kind of negative or anything like
that, but, um, being on the independent contractor side, I have, you know,
whomever needs, uh, this kind of resource can be a potential partner of mine.
Um, like I had mentioned, you know, we're working at international scale now to
having an opportunity to work with APHL and CDC Thailand, but at the same time,
the local laboratories throughout the U S that, that I had very little
interaction with, um, at DCLS and then also broaden the scope in terms of, you
know, there's, there's a influx of funding and resources to public health for
SARS-CoV-2. Uh, but we also realize that because we have this opportunity for
funding and resources, we need to make sure that we take advantage of that to,
uh, beyond just SARS-CoV-2. You know, it's, I don't know if in our lifetime,
we'll see another kind of resource influx in the way that we're seeing right
now. So we need to be able to capitalize on that and ensure, yeah, ensure that
we have, uh, uh, other infectious diseases in mind, uh, as we develop these
things. So there's a huge priority on SARS-CoV-2, but also the objective being
written in for other infectious disease surveillance as well. So can I ask what
type of support are you giving? Are you like setting up the infrastructure,
bioinformatics infrastructure for SARS-CoV-2, or are you doing a day-to-day
analysis or are you doing training, you know, like there's so many different
things you can possibly do and, uh, you can't do it alone, I'm sure. I think
this is getting into kind of like the technological innovations that have
happened in the field in the past, you know, five years. So in the last podcast,
we were talking.  about Docker containers kind of revolutionizing how we do
things. And to me, there was like, there's three of those major events that have
happened in public health. Docker is being one of them. So once Docker has
happened, you know, there's no need to put a markdown file of how you're
downloading this thing locally anymore. It's like, just use the Docker
container. The other thing I saw come about maybe 2019, 2020 was workflow
languages. So now we can, you know, it's a much simpler language. You can, it's
modular and you can start writing these workflow languages. What we're seeing
now is the kind of next step is web applications that tie workflow languages
with a back-end cloud computing infrastructure. And so what this allows us to do
is write this sort of technical bioinformatics workflow, but then immediately
give access to these tools to a non-technical user. So that is, has been kind of
our model of distribution with the age in genomics and kind of pioneered with
obviously the Broad Institute and then Joel Savinsky's adoption of that
methodology. So in terms of support, this also gets to the scalability of these
kinds of practices. I can build a SARS-CoV-2 workflow that's in the, you know,
the Whittle workflow language, make it available through Terra, the web
application from the Broad Institute that connects Google Cloud resources and
Whittle workflows. And once I build that one time, I can support a whole range
of laboratories because it's more than anything. And now it's just about
training them on how to use these inputs and how to use these workflows,
configure their inputs and understand their outputs. And that can be done in a
scalable way. You know, we have a couple of YouTube videos walking through
people how to use this. And now there's more people than, you know, I can keep
up with who have access to these tools where, you know, two, three years ago,
supporting this many labs is absolutely unthinkable. But now we have a sort of
centralized system. A centralized system that is inherently distributable allows
us to support as many labs as we are right now. Curtis is doing work on the data
transfer and all the other technical details involved in that too. Yeah. So
Curtis, maybe to you, what are the inputs in your containers and workflows? Is
it like the fast five level or is it fast queue or is it something more refined
than that? Like say VCF files? So I'm new and I'm still learning the workflows,
but so Kevin, correct me if I'm wrong, but I believe the inputs are fast queues
for both Illumina and Nanopore platforms. I think the input is fast queues and
then a table with metadata on the various samples. So Terra accepts, you know, a
simple CSV table, you import it, you point it to the data, which is stored on
Google storage, you know, Google buckets, and then click go. So I just wanted to
add that it's incredible. Like I've been here as part of Diagen for what, five
days now, and I've been able to witness multiple labs get up and running with
analyzing source could be two genomes within an hour. If they have the data, if
they have the data up on BaseSpace or another avenue, they can go from having
the data to having submission ready genomes within an hour. And the agility that
comes with being in a contracting role or in a, I guess, private industry role
is phenomenal. You know, we can get labs that have, you know, very limited
experience or capacity for whole genome sequencing and bioinformatics. And just
like that, with a little bit of work, get them up and going. You're gonna suffer
the same problem I have where somebody brings up the podcast about a month
later, which is when this is gonna air, and you're gonna know a lot more at your
job at that point. It's so funny. But yeah, yeah. So the standard input files
that the community is familiar with FASTQ, FASTAZE, metadata. With the SARS-
CoV-2 focus, it's, you know, generally the workflows at least we have available,
it's ARTIC, V3, Tiled Amplicon, FASTQs, and then the metadata required for data
submission to GISAID or GenBank. And again, even that level of data submission
to repositories, that is a major challenge that a lot of labs are facing. And I
think in the UK and also in Canada, again, there's that centralized model where
everyone just kind of sends the data to a single specialist, and they're able to
curate the metadata and format things and get going from there. We don't
necessarily have that at our disposal at the US, just based on how our public
health and government infrastructure is designed. So there was an absolute need
to identify a way where we can distribute those capabilities to different
laboratories. And like Curtis said, like within an hour, we can get laboratories
to do that exactly. So we can get them to perform the genomic characterization,
assembly, and lineage and clade typing of SARS-CoV-2 samples, that we can prep
the metadata for GISAID and GenBank submission, and then also start performing
the genomic epidemiology through the use of the Augur algorithms. Yeah, I mean,
you're so right there. It is so difficult just to submit data. And even with
COG-UK having a centralized database and submission system, it's still a pain,
and it still doesn't work necessarily very smoothly, and it still requires
constantly talking to the people in the archives to fix it, and emails, and
whatnot. So I've got how many, you know, small little lab, who doesn't, you
know, it's their first time sequencing. It's just, it's a huge barrier. Yeah,
yeah, and I'm also involved in the Public Health Alliance for Genomic
Epidemiology. And, you know, there's obviously a huge focus on how we also
include other countries that have not been a part of this conversation yet, and
getting them resources to be able to perform these kind of analysis and data
sharing. I know it sounds like we work for Tara here, but I really can't praise
them enough in terms of providing a platform that enables us to do that for
countries. Like, for example, like I said, CDC Thailand that we're working with,
and other countries that we're starting to be involved with through the PHAGE
Consortium in Africa, and South America, and everything else in between. This is
really like, this was the goal ever since, you know, we started, you know, five
years ago in public health bioinformatics, is distributing these kinds of
resources and getting the capabilities in different laboratories without
necessarily having to hire people who've spent a decade in the field. You know,
you want public health scientists to focus on public health information, not,
you know, is my library dependencies appropriate in my version and Docker
containers, all of these. You want that all abstracted away. And that's what
Tara has allowed us to do. In also, I might add, in an open source community
kind of way. So everything we write is on GitHub. Everything is freely
available, transparent, and available to the entire community. Well said. Yeah,
I mean, in terms of end caps and things like that, yeah, I think I've had a
pretty wild career in that the timing of things coming out of grad school and,
you know, having learned a specific science, right? Like I sometimes make the
joke that, you know, our whole field, you know, of infectious disease
bioinformatics, so you don't have that one international conference of ASM NGS
in DC. And like, we didn't even really fill up the main ballroom, right? That
was like our entire community. But now we're kind of at the forefront of
geopolitical decision-making. And we're like the small group of people who have
that specialized skill. So this is kind of our turn at bat here. And it's been
incredibly rewarding just pursuing this field out of curiosity and a desire to
collaborate and better the community. And if there's any, you know, students or
even academics or other professionals listening to this thing, we need more
talent. We need more people who are curious about these technologies at the
computer science level, at the, you know, training level, at the applications of
using a software like Terra. With theogen genomics, we are so exposed to the
need in the shortcomings of having the technical expertise to support this work,
you know, not only in the US, but globally. So if there's anyone who with any
kind of inclination for bioinformatics, you know, lean into it, because this is
a field that only seems to be growing. Thanks. And Curtis, do you have any last
thoughts? I don't think so. Just, it's been awesome to be on this podcast. It's,
you know, it's an honor to be on here. So thank you for the invitation, for
having us. It's been great. Wonderful. We've been really happy having you on and
thanks for listening to the Microbial Bioinformatics Podcast. Our guests today
were Curtis Kapsak and Kevin Liboued. And you guys really tied everything
together from last time with the containers and how you went through college and
grad school and chose the paths that you went on. Very interesting. So thank you
for sharing your stories with us. Yeah. And thank you guys for giving us this
platform to, you know, to speak about our careers. Thank you guys for all the
work you've done in the community before Curtis and I got here. You know, so we
stand on the shoulders of giants, which, you know, in our eyes, we include you
guys, you know, Rory and, you know, Liveset. Those are the tools that started
our careers. So it's pretty cool to be at this stage, being able to speak to you
guys as peers in some respects. So thank you guys too. Thank you all so much for
listening to us at home. If you like this podcast, please subscribe and like us
on iTunes or Google Play. And if you don't like the podcast, please don't do
anything. This podcast was recorded by the Microbial Bioinformatics Group. The
opinions expressed here are our own and do not necessarily reflect the views of
CDC or the Quadrant Institute. This podcast was recorded by the Microbial
Bioinformatics Group. The opinions expressed here are our own and do not
necessarily reflect the views of CDC or the Quadrant Institute.