The gut-liver axis and liver disease (microbiota and more) with Noah Palm

Transcript

• 00:16Welcome back, this session is
• 00:18being recorded. Thank you.
• 00:23Good afternoon, my name is Cliff bug.
• 00:25I'm professor and chair of Pediatrics
• 00:27here at Yale School of Medicine.
• 00:29I'm proud to welcome you to this session
• 00:32entitled The Path ahead and I'll be Co
• 00:34chairing this session with Chen Liu,
• 00:36who's a professor and chair of
• 00:39the Department of Pathology.
• 00:41For our first speaker we
• 00:44I'm proud to welcome.
• 00:45Welcome Noah palm.
• 00:47Noah is an associate professor of
• 00:50Immunobiology at the Yale School
• 00:51of Medicine and he's going to
• 00:53be speaking on the gut liver,
• 00:55axis and liver disease,
• 00:58macrobiotics and more.
• 01:04Alright, thanks very much for that
• 01:07introduction for the invitation to
• 01:09share some of our our work here,
• 01:10so I'm going to go ahead and share my screen.
• 01:12Let me know if there are any problems.
• 01:19This look OK Cliff. Looks great.
• 01:21OK, so I'm going to.
• 01:24Apologize in advance that I'm not going
• 01:26to talk too much about things very,
• 01:28very specific to the liver today,
• 01:30but I want to share some work with you
• 01:32that I think it will be hopefully obvious,
• 01:34and I'll try to note along the way how
• 01:36this can be applied to understanding
• 01:38the effect of the trillions of
• 01:40microbes that that live in our guts
• 01:42on on liver pathology in particular,
• 01:44but really kind of the focus of my lab.
• 01:48More broadly is just understanding
• 01:50the impacts of these microbes
• 01:53that live in and on us.
• 01:54On diverse aspects of of human
• 01:56biology and so I'm going to try to
• 01:59kind of give you an overview of the
• 02:01problems we like to think about some
• 02:03of the kind of unique approaches
• 02:05that that we take and then tell you
• 02:08very briefly some recent findings
• 02:10that are coming out of a project
• 02:13that started as a collaboration with
• 02:14a colleague of mine here at Yale.
• 02:16Aaron ring.
• 02:16I guess almost seven years ago now
• 02:18that we're really excited about
• 02:20and so excited to kind of share.
• 02:22Kind of this very hot off the press.
• 02:24This is kind of work with you today
• 02:27and so the the the title slightly
• 02:29different from the title on the on the.
• 02:32Schedule is mapping uncharted
• 02:34landscapes of host microbiotic
• 02:36communication and so by now I think
• 02:37all of you are aware that we're
• 02:39constitutively colonized by trillions
• 02:41of microbes at all barrier surfaces,
• 02:43maybe most notably in our
• 02:45gastrointestinal tract,
• 02:45where each of us contain a
• 02:48unique consortium or harbor.
• 02:49A unique consortium of hundreds
• 02:51of species that encode millions
• 02:54of genes and produce thousands,
• 02:56or maybe even 10s of thousands or
• 02:58hundreds of thousands of unique
• 03:00small molecule metabolites.
• 03:01And you're probably also all aware that.
• 03:04Alterations in these microbial communities,
• 03:06particularly gut microbial communities,
• 03:07have been associated with basically every
• 03:10disease and disorder you can imagine.
• 03:12Particularly diseases involving
• 03:13a chronic inflammation,
• 03:15including diseases of the liver,
• 03:17as as many of you will be interested in.
• 03:20However,
• 03:21despite kind of a revolution in
• 03:24understanding of and our ability to catalog,
• 03:28the microbes and their genes and
• 03:31their products that exist in in
• 03:34across a diverse array of humans,
• 03:37using new omics technologies
• 03:39like next generation sequencing
• 03:41or untargeted metabolomics,
• 03:43it actually remains quite hard and quite
• 03:46challenging to draw causal connections
• 03:49between specific changes in microbial.
• 03:51Communities or individual microbes.
• 03:54Are there products and and specific
• 03:57physiological outcomes or pathophysiological
• 04:00outcomes in humans and there really
• 04:03are two main reasons for that that
• 04:05my lab really tries to tackle.
• 04:08One is that correlation does
• 04:10not equal causation,
• 04:11so there are lots of reasons that you can
• 04:13see alterations in microbial communities
• 04:15that are for epidemiological reasons,
• 04:17or in fact where the change in the microbial
• 04:20community is in effect of the disease.
• 04:21Rather than the cause of the disease,
• 04:23and the 2nd is that although
• 04:25we're now getting better
• 04:26and better at again generating
• 04:28catalogs say of these millions of genes
• 04:30that are encoded by these microbes,
• 04:32we're still not very good at
• 04:34actually understanding what these
• 04:35genes and their products do.
• 04:37And therefore most of the genes and products,
• 04:39and of these microbes remain
• 04:42completely unannotated,
• 04:43and so that kind of brings me to the major
• 04:46question that drives really, you know,
• 04:48at least half of the work that we do
• 04:50in my lab that's focused on technology.
• 04:52Development, which I'll focus on today.
• 04:54Which is, you know,
• 04:55given this enormous amount of complexity,
• 04:57and this this real annotation challenge,
• 05:01how can we go about actually
• 05:03sifting through all of these genes,
• 05:05metabolites and microbes and
• 05:06potentially being able to pick out
• 05:08those microbes and metabolites?
• 05:10For example,
• 05:11that are actually playing causal roles
• 05:14in in human disease when they're
• 05:16hidden in this vast sea of mostly
• 05:19irrelevant and mostly unannotated noise.
• 05:22And are somewhat unique solution
• 05:23to this problem is to develop new
• 05:26technologies that we refer to often
• 05:28as functional profiling technologies,
• 05:30which we conceptualize as using
• 05:32the host as a lens.
• 05:34To achieve this kind of complexity
• 05:36reduction exercise that I alluded to
• 05:38to really illuminate the microbes
• 05:40and microbial products that are most
• 05:43likely to be shaping our own biology
• 05:45as well as their mechanisms of action.
• 05:47And all of these technologies.
• 05:48I won't go through the details of
• 05:50of all of the specifics of how
• 05:52we accomplish this.
• 05:53I'll just tell you about it.
• 05:54At a high level,
• 05:55but kind of the concept behind
• 05:56this is is really very simple,
• 05:58which is that those microbes or
• 06:00microbial metabolites that are most
• 06:02likely to impact us are those microbes
• 06:05or metabolites that can interact with
• 06:07our own biology in some specific way.
• 06:09And so we've developed a number of
• 06:12technologies to to kind of fish out these
• 06:15kinds of specific specific microbes,
• 06:17including a technology that uses the
• 06:19antibody response to the microbiology,
• 06:21to fish out immunomodulatory.
• 06:22Microbes which we've shown that
• 06:24these this can actually highlight
• 06:26microbes that play causal roles
• 06:27in inflammatory bowel disease.
• 06:29More recently,
• 06:30we've developed technologies that
• 06:32allow us to identify microbes that
• 06:34create and produce small molecules that
• 06:36activate G protein coupled receptors.
• 06:39Many of you may be familiar with
• 06:40this receptor family,
• 06:41that's the largest family of of
• 06:43receptors encoded in the human genome.
• 06:46But today I'm going to focus
• 06:48on on this middle group here,
• 06:50which is all unpublished work.
• 06:52Which is actually a technology we've
• 06:55developed to simultaneously assess
• 06:57all in potential interactions between
• 06:59individual microbes and nearly all
• 07:01human extracellular and secreted proteins.
• 07:04So all receptors expressed on the
• 07:06surface of cells or proteins secreted
• 07:08into the outside of the of the host cells,
• 07:11and so these would be nearly all
• 07:14proteins with which an extracellular
• 07:15microbe would be able to interact.
• 07:18And this, as I mentioned at the beginning,
• 07:20really is a.
• 07:22And incredibly close collaboration
• 07:23with my colleague Aaron Ring,
• 07:25who actually started his lab here
• 07:27at about the same
• 07:28time and was spearheaded by a commenter
• 07:30graduate student, Connor Rosen.
• 07:33And so hopefully it's obvious to many
• 07:35of you why it would be interesting to
• 07:38understand these specific interactions
• 07:40between microbes and the host,
• 07:42both because microbes that interact
• 07:43with the host in this specific
• 07:44way are likely to be interesting,
• 07:46and also because by understanding
• 07:48which receptors they engage and
• 07:50leveraging our our core knowledge
• 07:52about those host receptors,
• 07:54we can potentially make some very
• 07:56sophisticated predictions about what the
• 07:58outcomes of these interactions may be.
• 08:00And I'll give I'll show you one
• 08:01example of that at the end of the talk.
• 08:03Also, for this crowd,
• 08:04I think it's notable that we're
• 08:06accumulating more and more evidence that
• 08:08even though we used to conceptualize
• 08:10tissues such as the liver as being sterile,
• 08:13that in fact,
• 08:14in in many pathophysiological states as
• 08:17well as possibly even physiological states,
• 08:19that we do have microbes making
• 08:21it to places like the liver,
• 08:23and there's accumulating evidence
• 08:24that the the microbes that make it
• 08:27to those environments can actually
• 08:28play causal roles in initiating or
• 08:31exacerbating a diversity of diseases.
• 08:33Including diseases like primary
• 08:34sclerosing cholangitis,
• 08:35which we're all very familiar with,
• 08:37as well as even a seeding,
• 08:40a systemic autoimmunity from
• 08:42those liver sites.
• 08:44So we basically set out a few
• 08:46years ago to think about whether
• 08:48we could actually systematically
• 08:50interrogate this interaction space,
• 08:52the dream being to actually understand
• 08:54and math all of the potential
• 08:57interactions between individual
• 08:59hundreds of individual microbes cultured
• 09:02from human gut samples and all human
• 09:06extracellular and secreted proteins.
• 09:09And so this is kind of was the goal
• 09:10was to create this kind of molecular
• 09:12search engine where the input would
• 09:14be a microbe plus the human explodium,
• 09:16all extracellular and secreted proteins,
• 09:18which is about 5000 proteins.
• 09:19The output would be this interactome
• 09:20and that we would undercover these
• 09:22new interactions.
• 09:23That may explain the role of
• 09:25these microbes and disease.
• 09:26And I'm gonna go very quickly
• 09:28over this complex slide,
• 09:28but suffice it to say that using
• 09:31yeast display and the really hard
• 09:33work of remarkable student Connor,
• 09:35who painstakingly curated and cloned
• 09:384000 proteins during his PhD,
• 09:41that we were able to set up this
• 09:43technology where we could basically mix
• 09:44a bacterium with a library of yeast,
• 09:46pull out the yeast that bind.
• 09:48And because we had genetically
• 09:50barcoded these yeast,
• 09:51we were able to use next generation
• 09:53sequencing to determine which
• 09:55host extracellular.
• 09:56Looking actually in dowed
• 09:58that binding capacity.
• 10:00And we've done this now across
• 10:02actually hundreds of microbes,
• 10:04not just within the gut microbiome,
• 10:06but actually across multiple different
• 10:09tissues from skin oral cavity.
• 10:12Long,
• 10:13and also including the female
• 10:16reproductive tract.
• 10:17And in going through this
• 10:19exercise and kind of,
• 10:21I think,
• 10:21really illustrating the power of
• 10:23these kinds of combinatorial technologies,
• 10:25we were able to explore almost
• 10:282,000,000 potential binary
• 10:29interactions between individual
• 10:30microbes and individual host proteins,
• 10:33and have and we've actually
• 10:35uncovered a really extensive network
• 10:36of what you could think of as Trans
• 10:39Kingdom connectivity that we're
• 10:40just starting to dig through now.
• 10:42I should mention that we've validated now
• 10:44many of these interactions we identified.
• 10:47Thousands of interactions involving hundreds
• 10:48of strains and hundreds of proteins.
• 10:51Of course, as you would expect.
• 10:52Still, most proteins don't
• 10:53interact with bacteria at all,
• 10:55and most bacteria interact with
• 10:57very few or sometimes even don't
• 10:59interact with any proteins at all.
• 11:01But we do see really fascinating
• 11:04examples of specific interactions
• 11:06among these hundreds of interactions
• 11:09we've uncovered that imply that
• 11:11there really is this rich landscape
• 11:13of interactions that may play really
• 11:15diverse roles in in both microbial.
• 11:17Colonization of specific niches in
• 11:21microbial manipulation of those niches,
• 11:23potentially to for the benefit
• 11:25of that bacterium.
• 11:26For example,
• 11:27the initiation of tissue remodeling which
• 11:30may have really interesting implications
• 11:32in in the multitude of diseases.
• 11:33And finally as an immunologist,
• 11:35it was particularly exciting
• 11:37to me to see that that we see a
• 11:39number of examples of interactions
• 11:41that imply that these microbes,
• 11:43even though these are
• 11:44quote commensal microbes,
• 11:44are not pathogens that similar
• 11:46to pathogens that.
• 11:48That some or even many of these commensal
• 11:51microbes may interact with the immune
• 11:53system in ways that lead to immunomodulation,
• 11:56and so.
• 11:57One example of that that we've found
• 11:59really interesting is this example
• 12:01of Ruminococcus Navis strain that has
• 12:04been associated with Crohn's disease,
• 12:06which actually binds to this Co receptor
• 12:09expressed on T cells called CD 7,
• 12:12and we validated this with an
• 12:14orthogonal fact standing here
• 12:16and this was really intriguing.
• 12:18For us,
• 12:19because actually CD 7 is really
• 12:21highly expressed on these specialized
• 12:23subset of lymphocytes that don't
• 12:25circulate in our blood but actually
• 12:27live within the epithelium.
• 12:29These so called intraepithelial
• 12:30lymphocytes and so it raises this
• 12:32interesting possibility that
• 12:33this bug may be able to actually
• 12:36directly activate these special
• 12:37this specialized cell type leading
• 12:39to potentially outcomes consistent
• 12:41with the inflammation that we see
• 12:44in chronic disease. OK, so.
• 12:46Just to finish up in the last
• 12:493030 or 60 seconds,
• 12:50we've used this new technology to
• 12:53really build what we think is the
• 12:55first Atlas of host microbiota.
• 12:57Interactions across nearly whole
• 13:00EXO proteome scale.
• 13:03This really is the first glimpse that
• 13:05we have of this potential interaction space,
• 13:08but it implies a lot of interesting
• 13:10things about how micro,
• 13:11which microbes are interesting,
• 13:13how those microbes may be doing those
• 13:15interesting things and what particular.
• 13:17Phenotypes,
• 13:18those those host phenotypes
• 13:21those microbes may elicit,
• 13:23and so kind of going forward.
• 13:25We're really excited about the
• 13:27possibility that we can continue
• 13:28to leverage these technologies to
• 13:30identify causal microbes and their
• 13:32mechanisms of action that eventually
• 13:33this is going to allow us to actually
• 13:35start to solve that annotation problem.
• 13:37I alluded to that will start to
• 13:39be able to actually combine these
• 13:41technologies with other omics
• 13:43technologies to be able to assign
• 13:45functions to dozens or maybe
• 13:47even hundreds
• 13:47of bacterial genes.
• 13:49Previously were completely unstudied,
• 13:51and finally that by understanding these
• 13:54specific interactions we may be able to
• 13:57actually identify subsets of patients
• 13:59that share core disease etiologies.
• 14:01Microbially driven etiologies of disease,
• 14:05and this has obvious also
• 14:07therapeutic implications,
• 14:08and so with that I'll just say
• 14:09thank you guys for your attention.
• 14:11Hopefully I finished close to on
• 14:14time and really just acknowledge
• 14:17Aaron's Ring and Connor.
• 14:18We started the project and that since
• 14:20been taken over by over by a really
• 14:22talented graduate student in my lab,
• 14:24the full sonnet and also
• 14:26Chris Buttonholer at Harvard,
• 14:27who is a really brilliant.
• 14:30Computational biologist who's
• 14:31been helping us with a lot of the
• 14:33more sophisticated analysis that
• 14:34we've had to start working on now.
• 14:36And of course, the funders as well.
• 14:38So thank you guys for your time and
• 14:40and thanks again for the invitation.