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 is so much information we all
know from working in the field, but nobody writes it down. There is no manual,
and it's assumed you'll pick it up. We hope to fill in a few of these gaps. My
co-hosts are Dr. Nabil Ali Khan and Dr. Andrew Page. I am Dr. Lee Katz. Both
Andrew and Nabil work in the Quadram Institute in Norwich, UK, where they work
on microbes in food and the impact on human health. I work at Centers for
Disease Control and Prevention and am an adjunct member at the University of
Georgia in the U.S. Hello and welcome to the MicroBinFeed podcast. Andrew and I
are co-hosts today, and today we're continuing our discussion on Campylobacter,
and we're going to this time be delving into some of the specific issues that
bioinformaticians need to keep in mind when studying this organism. Our guest
today is Dr. Ozan Gongadou. He leads the foodborne enteric pathogen group at the
London School of Hygiene and Tropical Medicine, where they study the physiology
and pathogenesis of Campylobacter and other related enteric microorganisms like
Listeria and Fibrio. He has a background in molecular biology and computer
science. He completed his PhD at LSHTM back in 2011. He works on a number of
different projects, continuing Campy pathogenesis and somomics, and he started
his position as assistant professor at LSHTM back in 2019. So hello again, Ozan,
good to have you back. Hi, thanks for having me. So last time we were discussing
a lot of the theory and the sort of context for Campylobacter, why it's
important, and some of the nuances that are specific to it rather than other
organisms. I think this time we're going to dive into the practicalities in
terms of the bioinformatics and what someone jumping into this organism needs to
keep in mind. So maybe we can start back with the genome. I think you mentioned
last time that the genome was sequenced back in 1999 at the Sanger. What else
can you tell us about the genome that makes it special of Campylobacter? And in
this case, it was jejuni they did first. The first Campylobacter jejuni, it was
the strain NCTC1116A, which a lot of people still use for their laboratory
experiment. Relatively small genome size, 1.64 megabases, approximately 1654
predicted open reading frames. And, you know, there were some key things that
came out of this. There were some key loci structures identified for Lipo
oligosaccharide for this capsule. It did not have classical enteric bacteria
secretion system. So at the time, there was no type 3 and type 4. Subsequently
down the line, some type 4 have been found in some strains on plasmids as well.
And also the type 6 secretion system has been found. Some of the really
interesting things that came out for this was the number, for example, of genes
that contained homopolymeric tracts. So these are series of nucleotides up to 7,
8, 9. What they can lead to is phase variability. So what that means is that if
you're potentially encoding, you know, really long gene open reading frame, and
those two open reading frames were actually on two different frames, what it
could do was that the polymerase can actually make errors and it could stop
halfway or continue encoding the whole two open reading frames. And so these
were often found on structures such as the capsule on the Lipo oligosaccharide
and they are, you know, believed to be mechanisms of giving diversity,
essentially, for the bacteria to evade immune systems. So what is the GC content
like of Campy, like that would allow for those homopolymer, polymeric tracts to
exist? The GC content is approximately 30%. However, generally the bacteria is
considered to be incredibly promiscuous and it will take up DNA. So even if you
do a transformation experiments within the laboratory, you can leave, you know,
amplicons, you can leave PCR amplicons and you can leave, you know,
transformation natural on the bench overnight and there's a chance that it could
take up your, yeah. So, and that, you know, that leads to some interesting
questions because, you know, there are implications to that. Now, since then,
there have been a number of different species and strains sequenced and we're up
to, you know, you could probably download over 50,000 Campylobacter genomes now.
I know some research that has come out recently looking at a number of different
Campylobacter strains and I believe that the number was over 50,000. In terms
of, you know, model reference organisms, you know, things like the EBI, for
example, have, I think they have over 150, what I considered model well
annotated reference organisms. A lot of these were back in the day came from the
Sanger Institute. And so there are differences between strains. So the classic
thing that we're studying and we're finding now in the type six secretion
system, you know, this is quite, this is quite a big thing because historically
Campylobacter has not had a mechanism to secrete defectors, to secrete proteins,
to potentially damage other bacteria, to damage host cells or allow it to
survive better. We found approximately that 25 to 30% of Campylobacter have type
six secretion system. And this kind of resembles what we find generally in gram
negative enteric and gram negatives in general. And so this leads to the
question as to do bacteria that have type six secretion system, do they have an
increased advantage in terms of competition, in terms of microbial population
niche environment? So with such an extreme GCAT bias there, right, are these
homopolymer tracks really just an artifact, you know, are they actually real or
is it just because we've used short read sequencing and it's not very good with
homopolymers, you know, and if there's five or six there, well, you can't really
tell the signal because the signal hasn't changed in the sequencer itself. So
are these just, you know, sequencing artifacts and how do you know they're
actually real? Yeah, that's a good question. So, I mean, these were originally
done with Sanger sequencing back in the day. And then more recently, I believe
they have been looked at with long read sequencing. And it's an area that has
caused a lot of headache to researchers, because if you're growing the bacteria
within the laboratory and you're passaging it, you know, every three or four
days with Campylobacter, you have to basically take it and put it on a new plate
so it grows. Essentially, it's like looking after a pet. There is a chance, for
example, that these genes that are within the capsule or lipolygosaccharide will
change in terms of actual product, protein, transcription, translation. And so
you potentially are changing your bacteria. Now, recent research from, for
example, the Quadram Institute, they've created a software, I believe it's
pronounced Tata-Huba, you may correct me, Tata-Juba, Tata-Juba, yeah. And this
is an example of a piece of research that is based on analysing these
homopoietic tracts in more detail. This isn't just a problem in Campy, because
this kind of situation occurs in other bacteria as well. So I was wondering,
right, you mentioned that Campy can suck up lots of other DNA very easily and
it's very promiscuous. So would things like Tradis work well on this, you know,
where you can put in some transposons and it can take it up easily? And can that
tell us more about it? Yeah, I haven't personally done work on, done a Tradis
experiment, but from what I've seen in the literature, Tradis experiments do
work. And it's interesting, certain strains, for example, another classic
strain, 81176, okay, which a lot of people use for experiments, does have
plasmid, a plasmid, Pvia, Ptet. However, what you find is that actually, if you
passage it, you can lose the plasmid, the plasmids can drop out. And this is a
constant headache with laboratory experiments, because there's obviously
tetracycline resistance on this Ptet plasmid in 81176. And if you're doing
passages, and you're continuing your experiment, and then some of these plasmids
have dropped out, that can have implications on the phenotypes that you see. So
I've heard in the grapevine that there is phage that are associated with Campy,
but they actually can't be sequenced with Illumina because of the epigenetic
modifications, and you have to go and use other technologies. So it'd be
interesting to know, how many of these sequencing projects have you undertaken
with short-read sequencing that are missing, you know, that critical component,
like you mentioned with passaging and plasmids dropping out, you know, are we
missing other phage that have dropped out, and it's only with long-read
sequencing that we're actually going to recover that, because they're actually
able to sequence these molecules? Andrew, that's a great question. And the short
answer is, I don't know. I'm not aware of that. I haven't heard it myself. You
may be more up to date on that than I am. Yeah. So, I mean, it's interesting.
What I remember is that, for example, the original genome, the NCTC1168 genome,
I, as you know, back in 2005, actually went to the Sanger Institute for a year.
And one of the, I think it's 2006, one of the reasons for that is we wanted to
update the genome, okay? Because within that five, six years, since his original
genome, original publication, there had been so much work that actually had
updated and studied gene product functionality that I actually managed to update
20% almost of the gene product functions, which is not pretty bad going for a
five, six year time span since the original genome. And I think at the time, we
basically published some work saying, you know, how important it is to obviously
annotate genomes as well as you can, but let's not forget about the re-
annotations. And this was pre-next-gen sequencing.  actually found is that even
in that 11168 genome, there were CRISPR remnants within the genome, and some of
the adaptive, I think, is it the associated or adaptive proteins that are linked
with the CRISPR region that we identified and we actually annotated within the
genome. So, yeah, in terms of the bacteriophage story, I'm not, I can't answer
your question. I'm not, I'm not aware of that myself. Just a couple of other
things that, that are quite interesting about, that have come about from the
genome sequencing. So, I mentioned, for example, that historically, you know,
secretion systems are not present within the genome. There is some research that
actually shows, really interestingly, that the flagella, which historically is
used for motility, actually secretes effectors. Okay, so there's a group in the
US that has been working on this for quite a while, and they are, they are
actually, their research is showing that the flagella can secrete effectors,
acting as a secretion system, and obviously, this has implications in terms of
bacterial competition and survival. Other things that came out, obviously, were
related to Campylobacter in the genome, is why is it able to survive in this
environment? So, there were a number of genes that were identified, genes that
encode for enzymes that are involved in the breakdown of, for example, of
reactive oxygen species, which are damaging to the bacteria. What about AMR
genes? You know, that's the thing that's on everyone's mind at the moment. Yeah,
it's interesting which angle you come from that, because there's been studies
that, obviously, looking at genes that could be linked to AMR. Okay, so in
terms, if you do a comparison of, you know, a thousand strains, and they're
looking for potential SNPs, potential GWAS studies that could be linked to AMR,
and it comes down to also identification of the genes that could be linked to
AMR. So, just to go back on that, one of the points I wanted to make is, as
important, and in terms of number, as the oxidative genes that were involved in
the breakdown of reactive oxygen species, for example, was, and this is the key
bit, I think, about Campylobacter, is the number of regulators, the number of
transcription factors, the number of regulators that were found to be involved
controlling those enzymes, those genes that encode for those enzymes in the
breakdown of damaging products. And that's where Campylobacter, in terms of the
genome, we've seen that it's incredibly complicated. It has a highly complex
system, and being able to survive in these non-ambient conditions. So, these
were some of the interesting things that came out from the genome project. So,
it sounds like it's quite difficult to work with this in the lab. How far does
the lab science really get you, and how much do you have to start thinking about
in vivo, in studying Campy? We all need to understand the physiology and
pathogenesis within the laboratory. And there are a lot of different
experiments, you know, you can do a lot of mutational experiments, you can do a
lot of phenotypic assays within the laboratory. Again, there are issues about
convenient, good animal models. Interestingly, actually, there are, in the last
few years, some novel murine models that are beginning to actually give a
disease phenotype that you see in humans within mice. And it's based on the
principles of, you know, administering a broad spectrum of antibiotics for a few
weeks to these mice and giving, I believe, a low zinc diet, which can then
apparently give the same disease profile that you see in humans. So, these are
great, and we're learning more about the bacteria every day. However, what we've
seen is that the situation in a real world scenario is very different, because,
you know, the bacteria is present in the environment, and it's present in
chickens in poultry in high numbers. One of the things we've tried to do is to
say, how can we apply this knowledge that we have in the laboratory, that we're
building on every single day, how can we apply this into the field, into real
world scenarios, whether that be from low middle income resource situation where
you have backyard markets or peri-urban markets to industrialized systems. And
so, one of the areas that we've really tried to investigate is how the microbial
population structure within the chicken gut microbiome is changing over time,
and how can we infer information and knowledge from this as to why campylobacter
is appearing typically in two weeks, and what are the sort of microbial changes
that are happening pre and post, and try to understand, you know, the evolution
of campy within the chicken gut microbiome over time. So, we barely know what's
in the human microbiome, so surely there's very little research done on chicken
microbiome, and is that what you're going to spend the next 10-20 years on?
Yeah, so definitely, you know, the experiments we've done up to now has been
with 16S microbiome metagenomic studies, and we all know the limitations that
come with 16S studies. They are useful, but up to a point. And I think, you
know, taking advantage of the third generation sequencing of long-read
sequencing, PacBio, Oxford Nanopore, is definitely the way to go forward, so
that we can try to appreciate, understand what's going on in the chicken
microbiome. I think it's important that, you know, from our studies, one of the
things that we've really taken advantage of is the metadata that comes with
these experiments, and I think that's a key point. So, metadata in terms of
environmental, you know, environmental factors, but also metadata in terms of,
for example, if you're doing different kinds of experiments, where you're
looking, for example, like prebiotics, probiotics, these kind of things, things
like the chicken weight, the feed conversion ratio, things like histology, the
immunology of the chicken. So, all of these factors come into play. Linking that
with the actual sequencing information, I would say, is the way to go. For
example, we found, even with our 16S studies, changing the feed of the chickens
has a huge impact on the chicken gut microbiome population structure, and also
the greatest amount of microbial changes were happening a day or two before we
find Campylobacter, again at day two weeks. In a subsequent study, for example,
we found real impact in terms of, we wanted to assess the different types of
farms, the different types of parameters within these farms, how they not only,
again, impact performance and microbial population structure, but what's the
knock-on effect of that on Campylobacter numbers. And, you know, we found huge
variation in terms of even adding such a supplement like Omega, which has been
added into the feed, for example, of chickens as a performance enhancer without
really understanding the reasons why, but what are the implications of that
addition of Omega in terms of numbers for Campylobacter. And so, yeah, I think
the availability of the technology in terms of next-gen sequencing, in terms of
metagenomics microbiome with long-read sequencing, is the way forward. I think
there's been over 150 studies in the last six, seven years that have looked at
the chicken microbiomes with or without Campylobacter coming into the story. And
they've all been with short-read sequencing. And so that can only get you to a
certain level of understanding of appreciation mechanistically of what's
actually happening there. Yeah. Yeah. I mean, if it's only short-read
sequencing, you're going to be looking at it from a thousand yards. You won't be
able to tell very much. Everything will be in 20,000 pieces and you'll only be
able to make a rough guess, particularly since I'm sure many species in the
chicken microbiome are totally unknown because they've never, they're probably
not in humans, you know, all these commensals. Exactly. So the way forward
definitely is with long-read, but just to re-emphasise, it's that metadata that
really gives that extra additional information, depending on the experimental
type you have. If you want to go for the natural infectivity studies, that's
risky because sometimes you might not get full infection at the level you want.
For example, we've managed to look at the impact using various aspects of our
environmental data. How is the microbial population structure changing over
time? And at one point, we was heavily based on competitive factors. And at a
certain time point, there was a shift to linking to environmental factors and
the environment in this case being potentially the chicken itself. Obviously,
the chicken is getting more healthier and it can potentially impact different
microbial population structure directionality. So this is an example where you
have your microbiome data, but you link it with analyses that allow you to link
your metadata into and try to infer different aspects of your structure. So
where does this microbiome come from, right? Because my understanding of modern
poultry production, certainly in the UK, is you have eggs are laid, they go to
like a hatchery somewhere else, you know, they're hatched, and then the chicks
go to another place to be reared. And so you've got these multiple different
factories and cutouts. I presume they don't have a microbiome when they're on an
egg. So where is this microbiome coming from? And how can it be so rich, you
know, so quickly and so suddenly? So the ceca of the chicken, okay, of the
poultry is where it houses the biggest number of bacteria. And that's where we
obtain the genomic DNA to do experiments. You can also get it from things like
the small large intestine, the duodenum. So there are various points along the
pipeline. It only takes, you know, a few campy to get into that farm. And for
that to get on within a chicken, and for that to spread by the feces, you know,
that will spread and that farm, all of those chickens will potentially have
campylobacter. And that's the problem. You know, the problem we have is how, if
it's in the environment, how do you stop it from coming into a farm? And then
the question then goes, well, if it's that difficult to manage that, to stop
that prevention at that step, how do you then work?  the steps that you can take
to manage it? And that's where some of those other things that we talked about
earlier come in. So has anyone done any genomic studies, say looking at
particular farms and saying, is it the same campy that comes in every time
genomically? Or is it different? You know, is it just a constant flow in from
the environment? Or is it just it's ingrained in the building infrastructure
itself, and you can never get rid of it? So I would say most of the studies have
been microbiome metagenomic studies, but because only recently has the long
read, I'm not, I'm not even sure if there has been a chicken microbiome long
read study. Andrew, maybe we need to do one. I think Mark Palin did the chicken
microbiome using long reads. So if he's gone down to species level, then it's
possible to disentangle that and see if there were different species. Clearly,
we know the limitations with short read, and you know, you're most likely going
down to genus level. So yeah, it's a good question. And we'd have to look into
Mark Palin's manuscript to observe those results. Grant, it sounds like we have
to have a joint project there to answer that question. Sounds good. I mean,
anyone who wants to get involved, just get in touch. The other side of that is,
if we look at the whole genome sequencing side of things, you know, there's a
lot of sequences now available. I believe Arnaud Van Vliet has put a bioarchive
study out where he's looked at over, I believe he's looked at over 50,000
isolates of Campi. So this is good as well, because this is looking at the other
side of things, the whole genome sequencing side of things. Comparisons in terms
of location, phylogenies, and, you know, using really interesting and useful
software such as Rory on 50,000 isolates would be fantastic. I feel like there's
a gap in our knowledge. I feel like, for example, we haven't had those global
thousands and thousands of strains, isolates, comparisons, those kind of
studies. You know, Arnaud's is a really good one, I think. I'm not sure the
exact number, but I think it's over 50,000. So I think that's one of the first,
actually, that have really taken everything out there and done a comprehensive
analysis on that. So I think we have historically been missing that kind of
study in Campylobacter. So I'm curious about one aspect of this, which is we've
been talking about the fact that much of the differences that drive Campy seems
to be things that are regulatory or antigenic, that are obviously going to get
missed in short read sequencing. But I'm curious, in your opinion now, having
gone through the whole, gone through these genomes, seen all these papers, and
then looking at some of the long read stuff, how much are we actually missing?
Is it a case that to really get the picture, like you can have two Campylobacter
that basically have the same chain content, but then behave very, very
differently because of differences with homopolymers or differences in something
else? Even when we compare the same strain, there are single nucleotide
polymorphism differences. OK, so even if this is a case of we're not just
talking about, you know, different continents, we're talking potentially the
same lab because obviously passages change things. And that's why it's really
important that when you do get your stock of bacteria, you make a significant
stock of that because you don't want that variation to come in from you changing
your your reference strain you want to be using for your project, the same
bacteria. So how much, sorry, how much plasticity would you expect then in one
of these experiments? Well, at the least you'll have, you know, snips up to
potentially up to over 10 genes with single nucleotide polymorphisms changing,
which you don't know if it's going to have a phenotypic effect. And there's been
studies that have said we've looked at X amount of Campy and we've found that
this is the core genome. How can you reliably calculate a molecular clock in a
short time frame with a limited thing like that if you're expecting that much
variation within the lab? And then does that not mean that to really understand
Campylobacter evolution, we need to have long term sampling so that we can
identify that aberrant variation? Because I'm assuming bulk of that does not
fix. Yeah, I mean, what a lot of people do, this is what they do in the
laboratory, right? They get their reference, they make a huge glycerol stock of
that for the minus 80. And they will say for the next three years, I'm using
this and I'm only going to passage it once or twice, because I don't want to
introduce variation after passaging it, you know, and a number of times. And
even by default, if you passage it, you can, if you passage it, for example,
over seven times, you might even physically see a difference on the bacteria.
This is what makes Campy difficult to work with these kind of attributes. What
happens with like the NCTC type strains? Have they been passaged like 50 times?
And are they the same as you know, when the the organism was first deposited?
Yeah, so again, that can happen. And people have worked with, if people have
ordered that bacteria from, I don't know, ATCC, or I'm not sure where else you
can purchase it from. What they will tend to do is make a stock of this. And so
you want to introduce as less variation as possible. It may be the case that a
few years down the line, you're not able to replicate and reproduce the
experiments, the assays that you preview, what you what you're expecting as your
reference is not being produced. And at that point, it may be a case of going
back to an older stock or actually reordering that bacteria from ATCC. But I
guess this knowledge that we have now about all the changes of passaging, it
wasn't necessarily known, you know, 10, 20, 30 years ago, when some of these
strains were deposited in those archives. Yeah, I'm curious. I mean, we had
this, we had a poke around with with some salmonella, and we were horrified to
find that some of the reference strains were had one or two snips between labs.
And that was that was an absolute debacle. And then by the sounds of this, that
if we just told everyone to send us a bit of DNA from their type strain, we'd
probably have a very, we'd probably have an entire cloud of variation there.
Well, I remember looking at a Typhie CT18, which is like a type strain. And
that's the strain where we have re-sequenced, you know, as a technical control
was missing like a 20 kb flagellin, like genes, it was just crazy, you know?
Yeah, this is a huge issue in not just Campy and other bacteria. The advice that
we've always gone with is, when you get your stuff from, you know, NCTC or ATCC,
or whoever you're buying it from, you make a significant batch of that that will
last you for a good few years. And you basically do your assays and experiments
with the early passage, because you don't want to introduce very SNP changes or
variation. And, you know, a good indication is you need to have a couple of
assays that are your default assays, which you think they should always be
producing this data, you should always be seeing an OD growth of your bacteria
at this time point at this level. And if you're seeing that kind of thing, then
that's a rough indication. But again, there is a very good chance that some of
those genes, you know, the odd SNP is occurring here and there. God, that sounds
like unit tests for microbes. The test driven laboratory science. So I would
say, you know, with the availability of this latest technology, of course, it
gives another layer of understanding and a layer of accuracy. Something that I
think we've discussed on emails a few times recently, is a lot of the time when
you're doing whole genome sequencing, which short reads, you have this DNA at
the end of it, which is not necessarily assigned to any part of the genome, and
it could most likely be part of plasmids. Okay, that's a really interesting
area. There's a lot of these, let's look at the circular genome, and they're not
even analysing what's there in terms of this extra chromosomal material in terms
of plasmids. You can get more information, as you mentioned in discussions
previously from doing that with long read sequencing. These factors we really
need to move towards considering them so that when we know that we're working on
this bacteria, this species, it has this plasmid or it has these plasmids,
because they will potentially have an impact on our phenotypic results that
we're observing. I've observed that with other enterics that you can have very
small plasmids that do just drop out with short read sequencing. It's not a
question of even having the trash at the back of the genome, they just never
show up. There's no reads apparent, it just never gets picked up in the
protocol. So really, there is a lot more to be done with CAMPY, and we're really
at the early stages of understanding CAMPY and its genomics, and we're going to
be at this for many more years to come now. What I would say is that we've
learned a hell of a lot in the last 20 years since that first genome sequence
came out. We know a lot about functionality, we know a lot about physiology,
we're starting to understand more and more of the intricacies, for example, how
and why, how campylobacter can survive in the environment. I think what is 100%
clear is because historically it's been a difficult bacteria to grow, and we
haven't had a good convenient animal model. And allayed to that, you know,
linked to that is all of these difficulties in terms of changes in genomic
structure, even through passaging, you know, these things cause issues with
CAMPY. And I think certainly things like long read sequencing, cheaper
sequencing, that we can do sequencing,  more often, these kind of things will
really help us in the future to try and get a hold of these issues. And
something like that software, for example, to look at homopolymeric tracts in
more detail is the kind of thing we need to basically have an explanation when,
one, our phenotypic assays are not giving results that we've seen historically,
and two, to ensure that our phenotypic assays are actually giving a correct
phenotype, not caused by differences between strains, for example. Since you're
touching on that, new bioinformaticians are moving into working on CAMPY, what
are some of the things that they need to know? I mean, this issue around passage
and being circumspective about your genomics is important. That's something to
keep in mind. You don't normally have to worry about that with other organisms.
What else is there for CAMPY? I think that there's just sheer variation between
not only species, but even in strains. And I just think just to be conscious
that sequencing a single campylobacter, it's no way representative, a strain is
no way representative even of that species. And you will get huge variation, you
know, for scientists, for computational scientists to come into the field,
really to be aware of that, that there is this huge variation. There is this
huge plasticity. Having that in the back of your mind, I think will go a long
way in terms of helping you to analyse these genomes. Yeah, so you've already
touched on TataJubas, one of the kinds of software you'd like to see coming out
from bioinformaticians in helping with CAMPY, but what else is on the wishlist?
What else can BIMFIs do? Yeah, I think bearing in mind, we have such an
increased number of isolates and strains being sequenced all the time. Those
large genomic comparisons are great. And the software, you know, software that
can do those pan-genome analysis, we touched on one with Rory, those kind of
software, they really help. In the lab, obviously, we need a better convenient
animal model. And, you know, there can always be, you know, incorporation of
novel techniques, for example, to make mutagens, mutants, mutagenesis, better
and newer techniques. I think there's a lot of laboratory scientists, and I feel
also that there sometimes is still a lag in the CAMPY laboratory field, that the
historical people who work, for example, in pathogenesis and physiology, they're
not necessarily adopting all the available tools bioinformatically,
computationally available. And there is a lag. I'm hoping that the newer
generation can have a sort of foothold in both bioinformatics and laboratory
science. It's not always easy, easy to do that. But at the least, I would say
that the next generation of researchers that come through, they will, at the
least, are what I feel, what I've seen, more comfortable in a computational
environment, so they can at the least incorporate these tools in their research.
Okay. And with that, that's all the time we have for today. We've been talking
about CAMPY labacter and the specifics that bioinformaticians need to keep in
mind when studying this organism. Our guest today was Dr. Ozan Gongadou. He
leads the Foodborne Enteric Pathogen Group at the London School of Hygiene and
Tropical Medicine. And again, it's been really great to have you on, Ozan, and
talking CAMPY. Yep. And we'll see all of you next time on the MicroBinfy
podcast. Thank you so much for listening to us at home. If you like this
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