83 – Oligos that target translation to restore SYNGAP1 levels

Bryan Dickinson, PhD

Dr. Dickinson’s bio

Bryan earned his B.S. in Biochemistry from the University of Maryland and his Ph.D. in Chemistry from the University of California at Berkeley. After a Jane Coffin Childs Memorial postdoctoral fellowship at Harvard University, he joined the faculty at the University of Chicago in the Department of Chemistry in the Summer of 2014, was promoted to Associate Professor in 2019, and Professor in 2023. The Dickinson Group employs synthetic organic chemistry, molecular evolution, and protein design to develop molecular technologies to study and control chemistry in living systems. The group’s current primary research interests include: 1) developing new evolution technologies to reprogram and control biomolecular interactions, 2) engineering RNA-targeting biotechnologies as new therapeutic platforms, and 3) leveraging chemical biology to study biomolecular interactions. The motivating principle of the Dickinson Group is that chemists’ ability to create functional molecules through both rational and evolutionary approaches can lead to new breakthroughs in biology and biotechnology.

THIS IS A TRANSCRIPT ONLY:

hello everyone and welcome to today’s webinar my name is olab bod and I’m a part of the team here at s research fund

0:14our presentation today discusses olos that Target translation to restore singap one levels I have the pleasure to

0:21introduce to today’s speaker Dr Brian Dickinson from the University of Chicago

0:26Ryan earned his BS in Biochemistry from the University of Maryland and his PhD in chemistry from the University of

0:33California at Berkeley and after a Jane coffin child’s Memorial postdoctoral fellowship at Harvard University he

0:40joined the faculty at the University of Chicago in the Department of Chemistry

0:45in the summer of 2014 in 2019 he was promoted to associate professor and in

0:502023 he was promoted to Professor the Dickenson group employs synthetic organic chemistry molecular Evolution

0:58and protein design to develop molecular Technologies to study and control chemistry in living

1:04systems the group’s current primary research interests include one

1:09developing new Evolution Technologies to reprogram and control biomolecular

1:15interactions two engineering RNA targeting biotechnologies as new therapeutic platforms and three

1:22leveraging chemical biology to study biom biomolecular molecular sorry

1:28interactions the motivating principle of the Dickinson group is that chemist’s ability to create functional molecules

1:35through both rational and evolutionary approaches can lead to new breakthroughs in biology and

1:43biotechnology a recorded version of this webinar will be available on the srf website under the webinars on the family

1:50menu by the end of the presentation you will have the opportunity to get your answers to your questions we’d love to

1:57hear from you so please write your questions in the q& QA below and for those of you just joining us welcome and

2:04again our speaker is Brian Dickinson it’s now my pleasure to turn things over to Brian thank

2:11you great thank you for having me today it’s really nice to get to chat with a

2:17really diverse audience about some of our work um let me share my screen now so this might be a little bit different

2:25than the way these have um normally run in the sense that our lab is really a

2:30platform technology lab and I’m going to talk today about some of the kind of platforms we’ve been developing to

2:36Target gene expression in a variety of contexts but I’m going to try to highlight how this relates to syap one

2:42in particular so I’m going to start with a rationale of how we think about s Gap one and why we’re um interested in going

2:48after it as a therapeutic Target and then a lot of the talk is going to be just about Technologies we’re developing

2:54and then we’ll come back at the end to show you how we’re developing these um specifically force in gap one

3:00okay so yeah my lab is at the University of Chicago in the Department of Chemistry a really diverse team of researchers thinking about designing

3:06molecules that study and control chemistry and living systems in a variety of different contexts so um

3:13starting off with the rationale with instant Gap one as this audience knows very well there’s a really complex set

3:21of pathology that emerges from deficiency of the syap one protein um a

3:27lot of uh you know human suffering Emer is from what is in many ways a kind of

3:32innocuous quite boring protein so syap one protein is a Ras GPS activating protein um deficiency in this protein

3:40results in this kind of complex set of pathological phenotypes like intellectual disability developmental

3:46disorder severe autism Etc as well as an epileptic an epileptic phenotype and as

3:51you all know there’s there’s currently no treatment that directly targets the underlying cause of the disease so from

3:57a kind of um human biology perspective perspective and medical perspective this is really complicated and and and quite

4:03and quite tragic from a chemistry perspective what we can recognize is it’s a really uh frustratingly simple

4:10problem this is some of our data with a collaborator here in Chicago that looked at the syap one protein levels from a

4:16healthy matched uh uh control patient versus a patient who heterozygous

4:22deficient in the syap one protein and it’s just 50% too little of the protein is present so from a molecular

4:28standpoint we know the problem um there’s just too little of this protein being made roughly 50% too

4:33little um but that results in really complicated um human uh pathology

4:39because of that uh that that deficiency in that one protein product so this gets at the idea of Hain

4:46sufficiency diseases if you look at you know humans have you know 20 or 30,000 different proteins and each of those

4:52proteins need to be expressed at the right time and place within the body in order to drive physiology um and

4:59probably for a lot of proteins there’s a relatively narrow band of kind of healthy physiological protein expression

5:06levels and too much or too little of that protein can result in disease in

5:11the case of deficiencies where one of the two copies of the gene is mutated either with a premature stop codon or

5:18some sort of deactivating mutation one way we can view the the kind of molecular basis of disease is that

5:23there’s just 50% roughly too little of that protein being made and we’re kind of outside of that kind of band of the

5:31kind of healthy expression levels from the kind of normal patient population that you would see and this is called a

5:36halfin sufficiency so ideally if we could have a technology that could restore those

5:42protein expression levels back into that physiological band of expression that would be a way to directly go after

5:48these sorts of diseases what makes this really complicated though is this kind of healthy expression level could be

5:54highly cell type dependent maybe one cell needs one level a different cell needs a different level and the cont EXT

5:59of neurological diseases maybe neurons need the protein expressed and maybe even at different levels depending on

6:05the subtype of neuron but other types of cells maybe shouldn’t have it expressed so it’s really difficult to kind of get

6:11this goldilock scenario where you need the protein present but not too much or too little and have it in the right

6:17place at the right time um that that’s a very challenging problem um so getting

6:22at what my lab does we study gene expression regulation in a variety of different contexts we have Evolution

6:28Technologies where we’re using Evolution to design complex molecules that interact with biological systems we do

6:34chemical biology of protein lipidation we target RNA with engineered biological

6:39systems and we map RNA localization that’s the kind of four main project areas all geared at this

6:46idea of thinking about how gene expression is regulated at the RNA and biomolecular level so for today thinking

6:52about how we can Target hlin sufficiency diseases and and diseases of Gene sufficiency I’m going to talk about our

6:58subgroup on controlling protein RNA interactions in particular designing bifunctional molecules the targetting

7:04expression at the RNA level and how we think that this could be one strategy to think about developing targeted

7:10Therapeutics for deficiency disorders such as syap one so if you think about a barrent gene

7:17expression I already said that in some cases the problem is too little of a particular Gene is being expressed because one of the copies is mutated DNA

7:24to RNA to protein protein composition is in most cases the underlying cause of

7:30human disease um and therefore it’s unsurprising that almost every single drug on the market targets proteins in

7:38most cases by inhibiting them whether that’s antibody Therapeutics that sequester targets or small molecules

7:44bind to proteins we have a very protein Centric view of drug Discovery um of

7:50course in cases where the problem is not an overactive protein but actually something that’s missing small molecules

7:56and biologics to Target proteins can’t really help in most cases right um because if the problem is a lack of

8:03something not too much of something then this kind of inhibitory mindset um isn’t really

8:08viable um we live in A Brave New World where one can think about now going in and making specific changes to the

8:14underlying DNA of a cell to correct uh genetic basis of disease at the DNA level and that is really exciting um but

8:21I think in some cases this is going to be really problematic to do in some tissues and in um and in some context so

8:29our lab is really interested in targeting RNA therapeutically for a couple different reasons RNA is the

8:35intermediate in the kind of gene expression central dogma um the RNA

8:40content of a cell is cell type dependent so if we target RNA regulation at the

8:45transcriptome RNA level then the effects of that Target will be reflected by the

8:52content of the RNA within the cell so in other words if we’re making a change to a cell based off of an RNA that’s

8:58expressed in the cell the level of that RNA will kind of dictate the response that that cell will

9:03have so a cell that has a lot of the RNA will have more of a response a cell that doesn’t have the RNA will have less of a

9:09response so it kind of lets the cell guide its own response to the therapeutic based off of its RNA content

9:17and we think that’s really one way to get around this challenge of getting cell type dependent expression which is

9:22needed in a lot of these sorts of complex human diseases um so it’s it’s highly regulated um it’s cell type

9:30specific and also RNA regulation is very tunable we can kind of fine-tune gene expression up or down at the RNA level

9:36if we can harness these regulatory processes so a lot of classic biologist

9:42viewed RNA is just this intermediate it’s really not a lot of gene expression is highly regulated at the RNA level so

9:49just to give you a a sense of what that means that the amount of protein made per RNA is a very regulated process and

9:56that’s something that we’re going to talk about targeting today the half-life of an RNA and how long it lives within

10:01the cell is also a regulated process and therapeutic strategies like RNA Target the degradation process of rnas to to

10:09rec to retune the halflife of an RNA one way that cells regulate Ras is by

10:14chemically modifying them with a variety of chemical marks and these chemical marks then serve as adapter for other

10:20proteins to bind to the RNA and regulate it um rnas are spliced in some cases

10:26splicing can drive disease in some cases sping can be targeted to restore homeostatic protein levels rnas are also

10:34edited and the bases can be changed to alter the proteogenic nature of a particular RNA and then all these

10:40processes as well as localization are Guided by protein RNA interactions which control say export from the nucleus and

10:47trafficking Etc and collectively all this regulation is often referred to as epitranscriptomics which basically just

10:53means all the different uh ways the cell Tunes gene expression at the RNA level

10:58and if you look at this from an engineering perspective we can see all this regulation is coordinated by really

11:04two main processes protein RNA interactions so affector proteins binding to rnas and altering their

11:11regulation and then cellular localization where the RNA is present and how it’s kind of guided through the

11:17cell and we’re studying both of these processes and and and really again from an engineering perspective we view all

11:23this complex regulation as possible ways to control RNA regulation if we can design syst systems that specifically

11:30harness each of them so we started on this a while ago

11:36where we looked at one of the regulatory networks within the cell that targets RNA and that’s the m6a pathway so this

11:44uh chemical modification here called m6a is present on the aase of RNA methylation here and cells have

11:51dedicated methyl transferases and demethylases which dynamically Mark subsets of the mrnas within a cell with

11:58this chemical Mark that chemical Mark then allows those rnas to be recognized by these so-called reader proteins which

12:05bind to those m6a modified transcripts and alter their regulation either their

12:10Half-Life or their rate of translation or other features of that RNA and what we realized uh a few years ago is that

12:18the reader proteins that the cell naturally uses to regulate RNA are kind of bifunctional molecules they have an

12:24m6a binding piece and then an affector piece that kind of recruits other factors to alter the regulation of the

12:30RNA so we had this idea of what if we could remove the m6a binding domain from

12:36this uh protein and make it into something that we can engineer so that the protein doesn’t bind to all the

12:42transcripts with this m6a mark but instead binds to the specific transcript that we want to regulate so the way we

12:49did this is we engineered a cast protein this cast 13 system which is an RNA

12:55dependent RNA binding protein it’s the RNA cousin of C 9 which which are probably quite familiar with and this

13:01guide dependent RNA binding protein basically just binds to a transcript that we want based off of the programmable nature of this guide RNA

13:09and what we showed is that we can then pluck these affector domains out of their native context engineer them onto

13:15these cast 13 systems and turn them from m6a dependent readers into guide

13:20dependent readers so that now we can drive these responses to specific transcripts within the cell so for

13:27example we can get guide dependent Gene activation that’s analogous to what we would want to do in the context of

13:33something like a halfin sufficiency such as s Gap one or we can get guide dependent destabilization of the

13:38transcript and degradation in a programmable way so basically this just showed this idea of taking these natural

13:45RNA regulatory proteins and directing them to transcripts that we want using these engineered guide dependent

13:51systems so these crisper systems have a lot of advantages of course they’re being deployed therapeutically but there

13:56are a couple challenges with thinking about how we would deploy them therapeutically one is they’re quite large which precludes delivery with like

14:03an aav based therapeutic and they’re also potentially immun genic and that’s going to be potentially problematic in

14:09some applications in human Therapeutics and um many of us already have antibodies against cast proteins in our

14:15in our systems because we’ve been infected with microbes that that have them as part of their proteum so we asked the question a few

14:22years ago can we rebuild a programmable RNA fector protein complex that’s as small as possible critically not built

14:30out of these kind of microbial protein systems with the idea that that would potentially circumvent some of these

14:36imity issues that we were quite concerned with so this was our original

14:41design based off of the C 13 system we have the C 13 Protein that’s deactivated

14:47with a guide that binds a target of Interest we then engineer it with these various affector proteins that then are

14:53driven by that guide to Target an RNA and then elicit some sort of an effect on that RNA and what we realized is that

15:01this kind of protein engineering concept is relatively simple and we thought that

15:06perhaps we could build a system that does all of this but that uses only components derived from the human

15:13proteum so kind of an allum protein based system the idea was what if we took a small high Affinity RNA protein

15:22complex from the human proteome and simply displayed a guide RNA off of that

15:27now this wouldn’t be very happy in a Cell because it will look like a viral RNA and will be recognized by an innate

15:32immune response but the way cast systems deal with this is through nonspecific protein RNA interactions so we have

15:38specific protein RNA interactions that drive interaction with the guide and then non-specific interactions that kind

15:44of Shield that guide sequence from interaction with other cell components so we thought we could just engineer

15:50that onto our system with a small nonsp specific RNA binding protein so now we’d get this guide dependent RNA binding

15:56protein complex we could then put all of our effector domains we want to interact with onto that system and if it works

16:03ideally now have a guide dependent RNA um uh binding protein that elicits and

16:09effects based off of that guide sequence and we call this technology the crisper cast inspired RNA targeting system or

16:16Cs and what’s really powerful about this is rather than using microbially derived proteins and repurposing them as

16:22Therapeutics we can just take all of the kind of human proteins present in our

16:27body and use those as kind of a collection of starting materials to then think about how to engineer them

16:33together to build these guide dependent Arn binding protein system so while the fusions between them are not natural at

16:39least all the kind of core building blocks of the C system are built out of human proteins but really repurposed for

16:45this new for this new role so we can design these systems so here is an example of a simple one this

16:52is a nuclease so it’s a guide dependent RNA nuclease we can show that it binds an RNA based off of its guide and it can

17:00degrade an RNA based off of that guide so it’s a guide dependent RNA nucleus very analogous to the Natural crisper

17:06systems crisper cast systems but now in this case built out of entirely human protein

17:12components we can then uh append all sorts of different factors onto it so we

17:17can make it into a nuclease and then these uh data I’m showing you in human cells an of Target guide in Gray versus

17:24an ontarget guide in Black showing different effects so if the effector is a nucleus we can get guide dependent RNA

17:30nucleus activity and degrade the target RNA very similar this is our system the search system this is the natural cast

17:38system very similar activity we can put a translational activator this again

17:43would be the the the kind of sort of effect we would look for in a s Gap one guide dependent activation now we can

17:50put a destabilizer a destabilizer that deenal the RNA we now get a guide dependent destabilization or we can put

17:56a base Editor to cause single BAS Bas edits on the RNA and now we have a a guide dependent RNA editor so we can

18:03kind of again hijack all these different types of Regulation that occurs at the RNA level and Now guide that regulation

18:09to specific transcripts to alter gene expression at that RNA

18:14level we’ve more recently shown that these can work in Vivo in in a mouse model and with small molecule control so

18:22this is really a more synthetic biology application but what we can do is we can split the RNA binding protein component

18:28of the sear system from the affector protein so that in the kind of a basil

18:34State nothing happens to the RNA but then when we add a small molecule in this case this plant hormone abscisic

18:41acid that induces the dimerization and the kind of full assembly of the system

18:46which then causes regulation to occur at the RNA level and in this experiment we have a liver editing assay where there’s

18:53a luciferase from fireflies expressed in the liver of these mice with a stop cat

18:59on in it and what we can do is in the case where those mice are just growing they don’t have any luminescence emerging from their from their livers

19:06but when we add in this small molecule of pisc acid we can turn on our RNA regulatory system and cause single base

19:12edits on that transcript which restores this Firefly luciferase Gene and then we see light emerging from the the livers

19:18of these mice and what this is really showing is that we can even engineer kind of exogenous control over this RNA

19:25regulation thinking of what about disease cases where we want to kind of fine-tune gene expression based off of

19:31the kind of symptomatic development of a patient we can now add small molecule exogenous control over those RNA

19:37regulatory processes and this also gives us the ability to kind of test these systems in in kind of a mouse

19:43model so now what we’re doing this is ongoing work in the lab is we’re trying to take these sez constructs and further

19:50expand their activity um both activators and destabilizers in cases where we need

19:56this kind of tight band of homeostatic Gene regulation um and syap is one of the targets that we’re currently

20:01screening different types of effectors for and specifically for for activators in this context but we have kind of a

20:07range of human diseases we’re looking at where we think this sort of approach could be valuable and we’re right now

20:13going through mining the human prodium to find all sorts of different effectors that can work well for destabilization

20:18or activation and really trying to understand how do we design those systems how do we deploy them what sort

20:25of matching occurs between different types of effect with different set types of targets and really trying to expand

20:31that technology I should also note for full disclosure I did um uh start a

20:36company that’s trying to um develop this sort of technology for therapeutic

20:43applications so in a summary of this first part these are protein based systems that can Target RNA regulation

20:48and they really fit into a broad array of different exciting Technologies the target RNA regulation I think since the

20:55co you know we started this before the co era but I think now postco the world is a lot more comfortable with thinking

21:01about genetic therapies and and RNA targeting Technologies so I think we’re really excited about seeing how far we

21:06can push these to these uh diseases where there just there just isn’t a simpler alternative where we really need

21:12to have this high level of control I think RNA is a really good application of that so like I said we’re improving

21:18the performance of these systems expanding them developing pre-clinical models and a couple different of applications and working on delivery of

21:25these systems um primarily through a based uh delivery uh

21:30strategies so I want to switch gears now and talk about a completely different project that really emerg from some of

21:36our thinking about RNA regulation with these crisper systems um but moving toward a different modality and as a

21:43chemist you know I really think about the molecules we’re using to build Technologies out of and so far we’ve

21:48been talking about these protein RNA complexes which is one strategy um

21:53primarily used with like a viral-based delivery system for uh human Therapeutics like an aav based system

22:00that’s how we’re thinking about those um but we were interested in moving toward other modalities and I’m going to talk

22:05next about aligo modalities um and then we’re also thinking about even moving beyond that towards small molecule

22:11modalities so thinking about where you know what sorts of chemical material

22:16makes sense for the particular application in terms of disease and what we actually want to do within a cell so

22:22I’m going to switch away from these protein based systems and talk about something totally different which is an oligo based system but still trying to

22:28Target RNA regulation now if we think about oligos meaning rnas or RNA like

22:34molecules oligos have now been engineered to Target almost every aspect of RNA regulation so we can Target the

22:41degradation of an RNA with RNA or Asos uh we could Target splicing with Asos

22:48that’s a really interesting therapeutic technology right now and that’s um being deployed for syap one um in some

22:55applications as a as a strategy um we can control the chemical modification state of rnas even with rnas and then we

23:02can even direct base editors to rnas with oligos and these are so-called Adar recruiting oligos which is another

23:07really exciting area in biotech right now of therapeutic technology

23:12development so the one area which is what we would ideally want to do for diseases like syap one that we really

23:20can’t effectively do with oligos at the moment is Target translation basically to tell the cell to make more protein

23:27from the arm that’s already present within the cell um now there is and and

23:33you know and the reason this can work is the amount of protein made per RNA is a highly regulated process I already

23:38showed you that with some of the crisper like systems I described about how we can activate translation from a Target

23:43rnaa now there is one technology that’s currently being commercialized that’s been developed over the last decade or

23:49so that’s really interesting this is called signups these are long non-coding rnas that bind at the stop codon of a

23:56Target RNA um and activate translation through still somewhat uh completely um not

24:03worked out mechanisms but what’s really neat about these sign elements is you can direct them to the start codon of an

24:09mRNA and boost protein production from that RNA um so like I said these are being uh uh there’s a small startup

24:16developing these therapeutically um and uh I think that’s really interesting they’re still quite long so they tend to

24:23be in the hundreds of nucleotides long so not not a true oligo I’m probably aav

24:28would be the best strategy for something like this but kind of an alternative to the protein based systems I talked about

24:34so we set out a goal for ourselves to to develop an oligo based system that’s small enough to be chemically

24:40synthesized that programmably targets RNA regulation from a mechanistically defined in a mechanistically defined way

24:46so that we know the effects we know how to design it and we know how to make it

24:52work okay so if we think about how one would Target translational regulation if we think about trans we have an mRNA

24:59that’s expressed in the cell we then have what are called initiation factors that bind the RNA and then uh tell the

25:05cell to assemble ribosomes on it that make that RNA and and translate it into a protein so our simple idea was if we

25:13know that these initiation factors are kind of rate limiting in this process what if we design a bifunctional RNA

25:20which we call a translational activating RNA or ta RNA that has a guide dependent

25:26binding modality on it some sort of linker and then some sort of an initiation Factor recruitment domain

25:33such that if we can bind initiation factors onto that RNA perhaps we can tell the cell to put more ribosomes per

25:40time on that RNA making more protein product now in particular we want to design these systems that bind to the

25:46three prime utr that’s on this side of the RNA and the reason for that is what we learned from some of our work with

25:53the crisper like systems is that the five Prime utrs for many genes are both small small and crowded and we really

25:59wanted to design systems that could work in the three prime utr of an RNA now the

26:04reason you can get translational regulation in the thre Prime utr which we already knew based off some of the natural regulatory mechanisms that occur

26:11for translation is that the RNA kind of exists in this Loop structure so binding things over here can at least in

26:18three-dimensional space at least in our Mind’s Eye be sort of near the translational start site so that can

26:24have an impact on translation even when bound over here but it’s helpful because the thre Prim utr has a lot of free real

26:30estate to interact with a lot of unpaired bases with with low degrees of secondary structure that we can get

26:36oligos to bind to reasonably effectively okay so now the the key here

26:41is where are we going to find these RNA elements that bind initiation factors and of course Nature has evolved these

26:47for us so viral rnas like hepatitis C virus and and and many viral rnas use

26:54what are called irises internal ribosome entry sites these are structured rnas

27:00that once the RNA is inside a cell hijacks the um initiation factors that

27:06are endogenously expressed in that cell to turn that Viral RNA into a viral proteome these are also present in in

27:14some human rnas for alternative start sites now these viral RNA elements bind

27:20different initiation factors and promote translation in nature these are always Cy acting elements meaning that these

27:27RNA structures are part of the RNA that is going to be translated into protein and that makes sense because you can see

27:33in these schematics we line up all these proteins on the RNA and then translation starts at the start codon so what sort

27:39of and and in the TNA strategy we’re going to be asking to have them function in trans meaning we’re going to be

27:45delivering them to a GU to another RNA and trying to promote the translation of an RNA that they’re not even a part of

27:52so what sort of indication did we think that that was even possible so it turns out if you look at some plant viruses um

27:59unrelated to these some plant viruses have RNA structures in the three prime

28:05utr so still part of the RNA but very far away in primary sequence space but

28:11there are these three prime utr elements called site elements that actually recruit initiation factors to promote

28:18the translation of that RNA so at least in in three dimensional space very far

28:23apart but still able to promote translation and this gets at this Central idea of how we think about

28:28biology that’s really all about local concentration and proximity so potentially our hypothesis was we can

28:35find the right types of elements to get them to just line up on the RNA in the right way perhaps that would be able to

28:41promote translation in Trans in the TNA design and it turns out after some screening that was true so we started

28:48with some simple luciferase reporter assays in human cells where we had um these TNA designs where we just took

28:55full irises from a bunch of different viruses engineered guides onto them to see if we could promote the translation

29:01of a of a luciferase reporter Gene so in Gray is an of Target guide and blue is

29:07an On Target guide so this class 4 design TNA with a class 4 Iris which

29:13directly promotes ribosomes doesn’t have an impact really on the translation of that mRNA but you can see these class

29:19three and class two which promote all sorts of different interactions promote the translation of this reporter

29:26critically while we see increases in protein there’s no change at the RNA level see these are translationally

29:32activating systems so we then picked one of the more well studied hits from our initial

29:37screen which is from the hepatitis C virus which is this RNA shown here and we started doing studies to see what are

29:44the key interactions that drive this activity what are the key targets of it and can we shrink the system down to a

29:50more oligos siiz system so through truncation studies we found out that just this element up here this so-called

29:573abc domain was enough to recapitulate much of the gene activation of the TR

30:03system so we could take this 500 or so nucleotide system shrink it down to just

30:08120 nucleotides which includes a 40 nucleotide guide this Linker and this three ABC domain shown here and that

30:16that alone could recapitulate much of the gene activation we were seeing based off of studies from other

30:22researchers we knew a particular mutation u28c that in the natural virus

30:28T Iris element um that ablated one of its key interactions of this domain

30:33which is binding to eif3 when we make that mutation in the TNA which blocks

30:40ef3 binding biochemically um we can see a diminishment in activity so now we

30:45know one of the key initiation Factor targets of the system that’s responsible for part of the activity and then we

30:52could take that kind of truncation understanding of what is the key feature of this particular irus and Transplant

30:58that into other irises from other viruses this csfv and this PTV truncation also works so we have kind of

31:05multiple structures from multiple viruses we can kind of shrink down to a a piece about this size here and have it

31:11function so this PTV 3ab element which is actually the sequence I have shown

31:17here that’s the one that seemed to work most consistently and that was kind of our lead TNA design that we use to kind

31:23of move forward toward other studies so we can then and that was all

31:28with a plasmid expressing the RNA so now we want to actually deliver rnas to cells to see if the system works in an

31:34RNA delivery assay so now uh to stabilize the RNA and keep it from being

31:39degraded we put these kind of stabilizing hair pins on each end of the RNA so we can then make the RNA in a

31:46test tube and then put it into cells to see if it works um so with this whole

31:52system here we have uh the stabilizing hair pin a guide RNA that directs it to a particular mRNA within the cell and

31:59then the Spector domain that binds eif3 and promotes the translation of that Target with a stabilizing hair pin on

32:04the opposite side so in this experiment we inv vitro transcribe that RNA and then deliver it to cells and in this

32:10case we’re targeting a tumor suppressor P10 just as kind of a a model Target and what you can see here by Western blot

32:17and then Quantified is we can boost P10 expression with this RNA system so we’re now again using an RNA to promote the

32:24production of a particular mRNA into protein within a human cell we can then do this in Vivo so we

32:31can package these into lipid nanop particles uh very similar to those that

32:36uh are used for the coid vaccine and we can inject these into mice the lipid nanop particles will tend to accumulate

32:43in the liver and then we can ask can we also promote the translation of this P10 Gene in the liver of mice so we inject

32:50weight 12 hours isolate the liver and what you can see again by a western blot and quantification is we can promote the

32:56translation within the liver of a mouse as well now with these kind of biochemically

33:01stabilized rnas the effect is relatively shortlived because eventually these rnas will be degraded and the effect will be

33:08lost so this is really a way to transiently activate gene expression if one wanted a longer term response you’d

33:14want to install chemical modifications into the system such as like is used with an RNA type therapeutic in order to

33:21kind of stabilize that response that’s something that we’re trying to work on in the lab right now okay so next we wanted to uh go

33:30after a clinical model and let’s uh kind of finally get back to S Gap one here so

33:35with a collaborator Al George at Northwestern um we uh were’re able to check um the activity of these TRNA

33:42systems in ipsc derived neurons from a halfin sufficient patient donor um of

33:48the singap one halfin sufficiency so this is the first two um blots here are the original data I showed you at the

33:54very beginning of the talk of a healthy match ipsc derived neuron versus a s Gap

34:00one patient and again I told you that there’s about 50% too little of that protein being made so then we can grow

34:06these neurons in culture package tnas in lipid nanoparticles now that deliver

34:12that technology to the syap 1 mRNA and ask if we can promote um upregulation of

34:20the S Gap 1 Gene from the healthy copy of that syap one mRNA to try to restore

34:25levels to the healthy matched control donor so get about twofold increase in gene expression is the goal of this

34:31experiment so we take those ipsc derived neurons um add our L our lipid anop

34:37particles en encapsulating uh our TNA into those wait 8 to 12 hours and then

34:43measure the S Gap one levels with the Western blot and we have of Target controls here with On Target tnas that

34:50activate the sin Gap 1 Gene and what you can see is we promote the translation and what was really gratifying about

34:55these initial experiments is we actually promoted it to a level that was pretty near what we were looking for so again

35:01traditional gene therapy when you’re just overexpressing something you don’t have a lot of control over how much the

35:07gene is expressed so you get levels that reflect how much of the technology is delivered to a specific cell in this

35:13case because we’re just subtly upregulating gene expression we don’t dramatically boost protein levels but we

35:19do kind of pump them up a little bit and I think that that is really useful for something like these halfen deficiencies

35:25such as s Gap one so then with that kind of initial kind of positive hit for S Gap one we decided

35:32to really go after it and try to optimize the system biochemically to Target singap 1 so syap 1 mRNA has a

35:39pretty long three prime utr and this is actually another really nice example of why we think targeting a three prime utr

35:46is a much more widely useful strategy if you look at the syap 1 mRNA it has a pretty small five Prime utr about 202

35:54nucleotides and from our experience there’s not a lot of real estate to interact with there there’s a lot of

35:59bound proteins in that five Prime utr and not a lot of accessible sites to interact with but we have you know 17 or

36:051800 nucleotides in the three Prime utr with lots of different sites predicted to be unstructured so the first thing we

36:12did is we took our initial guide which bound right after the stop codeon guide one which worked reasonably well and we

36:19just looked at other guide Landing sites across the three prime utr and we found in particular this guide four which

36:26binds about 200 nucleotides after the stop codon seem to perform the most reproducibly into the highest efficacy

36:33in the system so we then use this guide four to kind of further optimize the system around so want to shrink the

36:41system even further to kind of make it a more um kind of compact system that’s more aligned with kind of what can be

36:47chemically synthesized in the lab so our original system looked like this through kind of iterative rounds of truncation

36:54optimization we’re able to further shrink it down through a couple of different changes first off we didn’t

37:00need 40 nucleotides to bind to a target of Interest we could truncate that down to 30 nucleotides without losing much

37:06efficacy we also realized this Linker was dispensable in this case and some of this kind of stem here was also

37:13dispensable based off of truncation studies so through all those extra kind of um kind of uh uh Precision changes to

37:21the system we’re able to shrink this down so that the core structure is is now only 95 nucle so we’re now below 100

37:28nucleotides total of the core system um that’s if it were chemically synthesized in this case we still have these kind of

37:34biochemically stabilized elements on the ends to kind of allow us to deliver as RNA and and look for efficacy in in in

37:41our biological models so here is comparing our mini TRNA system to our

37:47original shrunken system so now with those changes we didn’t lose any efficacy but We Shrunk the system down

37:53this is looking at s Gap one levels in two different contexts in n2a cells this is a mouse cell line or in HEX cells

38:00this is a human cancer cell line and in both cases we can see a nice promotion of the singap one

38:07expression so as the final piece of data I’ll show you this is kind of the best experiment we’ve run so far this is

38:12going back now to those patient derived neurons to ask if we can restore syap 1 levels with now this kind of what we

38:18call Mini TNA system this the shrunken system again packaged in lipin Nano

38:24particles and delivered to those neurons and again we do all these experiments with a healthy match donor so that’s

38:30this uh experiment shown here this plus plus genotype this is the healthy level of s Gap one the Hain sufficient um

38:37patient derive neurons we have 50% too little this is our mini TNA with an off

38:42Target guide it has no effect on syap 1 levels but when we have the guide delivering the system to the syap 1 mRNA

38:49we promote the translation and again when we look at the quantification it it really nicely lines up with the roughly

38:56two fold we’re looking for in the healthy match control it’s kind of a downstream marker of whether we actually

39:02altered the physiology of the cell by doing this we can look at the phosphorilation levels of irk it’s known

39:08that when you are deficient in syap one irk becomes hyper phosphorated we can see that in these two bands here when we

39:15restore syap one levels with our TNA irk phosphorilation goes down and that can be shown here too so we can not only see

39:22um this is a molecular phenotype so not like physiology but we can see at least the cell is responding to this up

39:29regulation of s Gap one in levels that we would predict based off of what is known in the literature so we’re really

39:34excited about this result because it really looks like we’re at least at the molecular level in line with what the

39:40needs of these cells are based off of this halfin sufficiency so what are we doing with

39:46this now so we’re trying to improve the performance of this system both in terms of reproducibility and size and just

39:52really expand the number of of targets we have to interact with so we’re testing other irises working on

39:58engineering them and asking about whether there are other targets that we can interact with we have at least one other initiation factor that seems to be

40:06able to promote the translation of some Target transcript so we’re asking you know when is one better than the other

40:11and what context do they work do they have Synergy or not um those sorts of kind of fundamental questions we’re

40:18trying to push forward in pre-clinical models and targets um singap one being one of the ones that we’re most interested in in this case and we have

40:24some collaborators that are helping us kind of establish some of those preclinical models and of course for for

40:30clinical application critical for any sort of biotechnology is thinking about delivery so whether it’s an AEV strategy

40:36in the context of our crisper like systems and our searz technology or lipid Nano particles or oligo based

40:41Technologies in this case we need to think about chemical optimization and other sorts of um pre-clinical

40:47optimization to make these actually Deployable as therapeutic so there’s a lot of work that needs to be done to

40:52move to that stage but I think as we develop the technology and think about the sorts of needs of patients and where

40:58they are and what sorts of delivery strategies we can deploy based off the needs of those patients and the

41:04technology we have I think that’s a way to really move forward toward developing novel novel sorts of therapeutic

41:10strategies for again these diseases that really seem intractable but I think once you have this kind of engineering

41:15mindset you can start to at least Envision how this sort of strategy can be used to Target gen expression in a

41:22really defined and programmable and targeted way so um I’ll end there I want to

41:28acknowledge my team I run a a really eclectic mix of grad students and posts and undergrads that do all this research

41:34um I want to call out Yang sha who is here who’s now a postto at Berkeley who developed the TNA technology and also

41:41Riley who’s a current grad student in the lab who’s developing our Sears platform um including working on S Gap

41:48one in the lab with that system so um stay tuned for some updates on that work I also want to call out our

41:54collaborators Al George at Northwestern um who is working with us on the patient

41:59derived neuronal systems um will green Bill Green at us Chicago who’s a neurobiologist who helps us think about

42:05the neurobiology aspects of it um Jimmy holder from Baylor who actually isolated the syap 1 ipsc derived um cells um and

42:13then suou at UIC who helped us kind of mechanistically interrogate the TR

42:18platform to some degree um so with that I’d love to answer questions and tell you more about what we’re doing um and

42:24and I’d be happy to talk more in the future as well so reach out if you have any questions or ideas and and thanks

42:30for uh providing me with this opportunity to tell you about our work today

42:36um okay hang on thank you very much I’m got an

42:43audio you guys hear my echo or a little

42:50Echo okay that should have fixed it um sorry about that wow I’m I’m I’m

42:57speechless which rarely happens that was that was I love hearing about it when someone’s been working on singap one and

43:03we weren’t paying for it and we didn’t even know it was happening and you’ve got such great results um so before I

43:09jump in with like a lot of questions and then I I saw your message Jr that you can’t talk on this one but please type

43:15furiously if you can if you’ve got questions um so first of all I want to

43:21say you know we do have a number of ipscs at a cro we work with called rare base I think we have six lines with um

43:27samesex family controls that if you want to expand your library those are freely available like there’s some transfer

43:34cost but we can fix that um so if you’re if you’re double clicking on singap and you want to expand the number of lines

43:40you’re playing with just know that those are available number one number two I’m sure you’re aware that

43:47um Rick huganir lab put out two mice with patient derived mutations and then

43:52we’ve actually made a third one at jackon which we’re which we’re about to fund the characterization of so

43:58there’s three Mouse lines that are have a mutation in them as opposed to being

44:03Knockouts which actually gets to one of my questions um about the three prime end

44:11so when you’ve been putting I think you’ve put this in mice already but I’m not sure not yet no okay so when you put

44:17this in mice I mean I’m always curious like in the old days by which I

44:24mean like a few years ago we just had knockout mice right and that was the model for the disease but now as we’re

44:29getting to these increasingly sophisticated therapies like what you’re talking about it’s a fair question like

44:35okay well what is is The Knockout the right model like what’s happening to with in the mutant alil right and and

44:42would it make more sense to to understand what you’re doing what so the three prime end for the uninitiated do

44:48might beting is for the for Mortals who don’t have phds is sort of the end of

44:54the protein right and what we tell the RNA end of the RNA the RNA pardon me the

44:59end of the RNA what we tell the parents is like look when you have a stop cat on part’s over but with the r the RNA since

45:06the three like what’s happening in the protein truncating mutants yeah yeah

45:12that’s a leading question because you know what my next question’s going to be right which was what’s happening in the msense mutants yeah

45:20but so I just want to advertise that we have the cell lines and we have the mice in case you want cooler models to play

45:26with or more models to play with but is it is it fair to think that your

45:38therapy is primarily focused on protein truncating variance it’s a great

45:44question so um yeah and at first for the ipsc uh that that’s great I’ll

45:49definitely um yeah so we’re working really closely with Al George who’s who’s really um very connected I think

45:54um so defin glad to hear that Al George has gotten out of the channelopathies because that was just so boring I’m glad to hear he’s finally I don’t

46:01think well I think everyone I mean so I’m a technologist so one of the reasons we were attracted to S Gap one is um you

46:09know there’s a lot of hence deficiencies especially within the brain there are all sorts of rare and semi- rare genetic

46:15disorders and for all of them it’s always an open question how much of the pathology is driven from the deficiency

46:22of the healthy Al versus the pathological Al doing something that it shouldn’t be doing kind of this

46:28so-called dominant negative effect and for most diseases it’s not known there’s

46:33some combination probably of both the mutant protein is doing stuff it shouldn’t be doing and the healthy protein isn’t there isn’t enough of it

46:40and the combination of those two effects leads to pathology one of the reasons we got really excited about going after s

46:47Gap one is it seems like s Gap one more so than a lot of other diseases is

46:52primarily driven at least in my from my read from the hlin deficiency now for a

46:58particular patient’s mutation we don’t know right there could be a dominant negative effect also that is driving

47:05some of the phenotype that that patient is you know is experiencing um and then I think the

47:10question in terms of mouse model is does the mouse model even recapitulate that we don’t know right um but right now

47:17when we target three perr and we target translation we’re going to be T it’s not mutant specific right we’re going to be

47:23targeting both the healthy copy and the unhealthy copy so if by targeting the unhealthy copy we just upregulate the

47:30bad stuff that’s happening that we can’t avoid that right now um but we are going to be promoting the the healthy copy so

47:37this will be most effective for patients who are suffering from a true hlin sufficiency um and then you know a

47:43question is can we actually identify those patients and do we know that that’s the case absolutely I mean I I don’t you

47:51probably don’t follow my podcast but whoever is doing singap in your lab should be and I just did an episode on

47:57missense mutants and I’m what I what I what I’ve what I what I try to bang into patients heads is all protein truncating

48:04variants are assumed to be behaved the same right classic hone sufficiency but

48:09if you have a missense mutation we should probably make a cell line because when we we start talking about

48:16therapies like yours like that question will be genotype specific well does it work in this one and doesn’t work in

48:22this one and doesn’t work in this one and we’re absolutely our our said and and I had I’ve had this

48:27conversation with people in government and and i’ I’ve said I’ve been blown away when I hear about studies and

48:33research and clinical trials and people aren’t genotyping and they’re like yeah we’re we’re we’re actually get we’re

48:39we’re with you it’s so I think this is some I think this is a question that’s going to keep coming up just one other

48:44note about that that’s actually important for when you make mouse models I mean for us because we’re targeting the sequence of the RNA it also may be

48:51important to have the M the human Knockin Mouse model because the sequences we’re targeting we try to be

48:57strategic and pick sequences that are basically the same in The Mouse and the human but some of the things that can

49:03work really well in one it’s just the sequence is totally different and we’re two too Divergent so even the three

49:08prims can be very Divergent between different species um so that’s just another another complexity in the system

49:15good news that’s been made yeah so we have a humanized mouse and it’s at the

49:20Jack prosers lab made it at upen and he sent it to the Jacks and they’re Crossing it so we’re going to have a

49:26humanized mouse and a humanized head that’s great so yeah look forward to playing with that um I you you you

49:34acknowledged um that you had a company in in the course of your conversation to

49:39to a comment and a question there the question is can you tell us what it’s called or

49:45is it in stealth and and the comment is I think it’s you said that like it was almost like you were confessing

49:50something and I think the opposite is true like I I think uh people as brilliant as you who have established

49:56labs and are doing science that are closely connected to or have your own companies are actually probably who

50:02organizations like our should be preferring because it it means that you actually get that this has to be

50:08translated into something that can be commercialized right so I think there are people out there who are like there’s all this cool science and one

50:14day somebody else should commercialize it and that’s where I’m like I’m done because I don’t care I love science but

50:20what I care about is making therapies for kids and so the fact that you are thinking about it from bench to you know

50:27marketing is is is I think hugely important but what can you tell us anything else about your company or is

50:33it yeah so so that that’s on the First Technology the Cs technology the protein based system so it is still in stealth

50:39so I can’t really talk a lot about it but yeah no I think broadly speaking we are very I mean these sorts of projects

50:44only have I mean we learn interesting things along the way but they really only have an impact if they actually go and help someone so I think as a lab

50:50this whole subgroup in my lab is very motivated on thinking about um you know

50:55what we can do to have an impact and and again it’s with biotechnology it’s a complicated set of

51:01questions picking out the areas that have an unmet need but that also you know frankly have a market so that someday there are enough patients that

51:07can be identified and organizations like this can actually pull out patients to ultimately run clinical trials is really

51:13critical to ever making a therapeutic and then having reasonable endpoints for those and then thinking about yeah I

51:18mean as a lab we think a lot about where to focus our attention to try to make that impact it’s it’s it’s really

51:24difficult but I I’m totally aligned with that for sure you’re touching on so many cool

51:29things I think patient identification is a huge problem right

51:35and the good news and bad news on singap the good news on singap is the data the the the the genetic models and like

51:41Dennis laws written on this and I can send you the papers if you haven’t seen them there’s a lot of data to suggest

51:46there’s a ton of singap good news bad news clinically they’re hard to find right they don’t start seizing at Birth

51:53the phenotype progression is slow so that that that’s like the bummer like it’s it’s it’s going to be work to find

51:59these patients the good news is I have a I have a um I have I have a list of like

52:04two year olds one or two year olds and there’s like 10 of them now because what’s happening is kids are getting

52:09sequenced at age one as soon as there’s delays or or like people are catching seizures and that was unheard of five

52:15years ago right so the the the rate at which we’re offering genetic testing

52:21thankfully is going up now we’re losing a ton of kids to missenses which get busted but that’s a separate

52:28conversation and and um and then the question is you know how do we figure how do we figure out if therapies like

52:35yours how do we figure out which missense mutants therapies like yours

52:40can help right like that assay of understanding is a missense dominant negative is it a null is it something in

52:46between that is a huge um rabbit hole that we we don’t have to go down right

52:52now okay so Jr has put two questions in the chat um oh I want to ask you about delivery

52:57but I’ll go to Jr’s questions first do you wanna do you want to read them because yeah sure let’s see comment

53:05on human variation if the three Prem is highly conserved then we’ll get binding Al both Al for whatever RNA didn’t get

53:10MD if the three PR has more varation each patient needs to be sequenced and perhaps the AL can be separated ah yeah

53:15that’s a great question the the the heter heterogeneity of the three peras I don’t know the answer to that

53:23um yeah I think that we haven’t seen indication I don’t I don’t think we

53:29would get lucky enough to find mutants in the three prrs that

53:34correlate with the disease mutation um that allowed us to get specificity

53:39usually one nucleotide or so which is what the most you would ever hope for probably isn’t enough to differentiate

53:45so um we probably can’t use it in a positive way in the negative sense though if a patient had a mutation that

53:53precluded binding of our system that would be a problem so I guess you know you would you would diagnose the patient

53:59in terms of what their mutation is driving the disease and at the same time sequencer three prut and make sure the

54:04system actually can bined to it so I think that that would have to be part of the um part of the pipeline for how you

54:10would identify people um let’s see how next question is how

54:16much nmd um for each PTV is a total variable based on intron xent Boundary distance

54:22and other issues sorry what’s what don’t know can you write what is NM nmd not

54:28since mediated Decay oh oh oh oh oh oh well so we’re not targeting nonsense

54:33mediated Decay we’re targeting direct promotion of translation so this is not

54:39this is not uh related to the oligos that try to promote translation or try

54:45to promote gen expression through nonsense Med Decay we’re not doing any of that this is completely orthogonal to

54:51all those like you know whatever yeah Tango and all those sorts of things so we are the RNA is there and

54:57we’re just telling the cell make some more protein from this RNA so totally different

55:03so yeah it’s has nothing to do with intron exons this is after splicing um

55:10so do you think both the Le will be there yes both the leals are there so in principle if we target the three per it

55:16will Target the disease and the healthy and they will both go up that is definitely a potential challenge that we

55:23would face but that’s one of the reasons we went for S Gap one because it looks like that would have clinical efficacy so let me just let me just

55:29rephrase that for The Mortals who were trying to follow along DNA makes RNA

55:35makes protein the people with protein truncating variants have a variant that would cause

55:41a premature stop codon at the protein level would cause that protein to be spit out by nonsense mediated Decay but

55:49at the RNA level both the good copy and the bad copy the wild type and the mutant alil will both have RNA and your

55:56technology will attach to the three prime end the the the back of the the

56:01good and the bad copy and make more of both yes is that right that’s right okay

56:08um yeah very Co yeah so again thinking toward the future like if you had a way

56:14to and people are working on this for Gene duplication based disorders if you had a way to knock down the mutant

56:20disease you know dominant negative copy that’s that’s a viable Strat there and

56:25then potentially that would be what would be needed if it turns out that that’s the main issue for S Gap then you

56:31would combine it right get knock down the disease causing variant or the

56:36disease causing mRNA promote production from the healthy um but yeah I think I

56:41think we we have to see like I said there’s a lot of evidence that appears that the dominant negative aspect of it

56:46um is pro for from many mutations is probably less critical um and the other

56:52note about how to eventually commercialize or translate things like this I mean what I also personally find

56:58interesting about singap one is there’s gwas data that suggests that there much there might be a much broader population

57:04of say autism patients that are not direct mutants in s Gap one but that are

57:10syap one deficient for other reasons that would also benefit from a syap one restoration therapeutic so in that case

57:17they’re not they don’t have a mutant alal per se but they may be S Gap deficient and have autism for a very

57:24similar reason so I think thinking about a pipeline for how would we ever make a therapeutic for autism I’ve kind of bought into this

57:30idea that one way to do that is you pick a semi- rare disease like syap um you get a therapy for it and then you just

57:36see does this help with a broader population um that you can identify through other other sorts of metrics so

57:42I think do you give an example of why somebody would be syap deficient if they weren’t a mutant well we don’t know I mean so you know human gene expression

57:50is such a hetero you know it’s it’s you know environmental factors all the other other you know mutations within that

57:56patient that changes gene expression um so it’s a little unclear but if you look at gwas data kind of there there are

58:01things that point to the singap one Al you know the singap one gene for for various reasons so um very cool very

58:09cool um I might follow up with you on that and ask you to point me to something that puts that in writing I

58:14mean there is a there’s a whole other group of people who were like too and singap definitely interact and I could I could set up a

58:21debate right now I can tell you exactly who will argue that ta is pushing down singap and people who would argue that singap is pushing down to and these two

58:28people not agree on anything um but I like your

58:33idea as it applies to the autism Community because certainly singap unlike you know the channelopathy is is

58:40a as a synaptopathy is a really complicated Gene which actually gets me to my next question

58:45right one of the complications of singap aside from the fact it acts in the synapse and it has so many different

58:52functions right is is it structural is it functional or whatever there’s at least 11

58:58isoforms and and there are there are some therapeutic strategies that say this is the isopor that matters let’s

59:03just make more of it well let’s I won’t go down this and some people are like well don’t

59:10mess with the isoforms until you understand what they all do because you could be creating other problems right

59:16your therapeutic approach leaves isopor selection to the body is that right

59:21that’s right yeah exactly as long as we pick the right site to bind to in the three primr then yes exactly it’ll be

59:27reflected by whatever the content of that cell is that you deliver

59:33to so given that the three prime yeah depending on where you you so in a sense

59:40because the three prime utr is part of what chooses which isopor yeah so we could we could in principle design them

59:47to Target something that’s isopor specific but you know therapeutically probably the best strategy would be pick

59:53something that is Broad that’s you know present in as many contexts as possible

59:58so that then you let the cell decide which ones are expressed and you assume in this case I should say that like the

1:00:05healthy Al is being expressed at the levels it should have been expressed at based off of the cell context I mean

1:00:11that is kind of a key assumption that we’re making with this sort of

1:00:18strategy I I I have to think more about that because I remember your SL you had the G1 the G2 the G3 and the G4 and just

1:00:24thinking about depending on which G you connect to what is the downstream implication of will

1:00:31certain transcripts I don’t know if that’s the right word or certain RNA you know certain rnas will

1:00:37then be upregulated but what would that mean for ones that were to the left or to the right of that in terms of isof

1:00:44form selection I yeah it’s just a matter of whether those guides sites are binding whether that sequence is present

1:00:51in the MRNA that you’re targeting that that’s the only question um and that’s you know and and I guess one advantage

1:00:57of the system is we have a lot of flexibility so we can you know we show we can kind of Target we can’t Target any site in 3 prtr but if we have it’s

1:01:04huge right there’s hundreds and hundreds thousands of of bases so we have a lot of different options that we can kind of

1:01:10go after within the three Prem it’s not like one site that we need to Target cool all right uh then Jr has another

1:01:16great question um I want to ask you one more yeah so the question is delivery

1:01:22which is the correct question to answer and just big step back from me thinking about biotechnology right any

1:01:29therapeutic involves three things it involves the technology which is what I get really excited about how are we

1:01:34going to do cool stuff to a cell that that other people hadn’t done yet the other one is the patients do patients

1:01:40actually need this and what are the needs that they can kind of you know what what are their what what’s their pathology and what are they willing to

1:01:46accept from a therapy and then third is the delivery strategy how to you actually get that cool technology into

1:01:51those patients and I think those three things are all equally important when thinking about a new a new therapeutic

1:01:57technology um so in this case like I said my lab is really focused on the technology this is what we care about we think about those other two but you know

1:02:04the the question is what what is viable right if we’re going to go after you know one of these one of these kids that

1:02:10doesn’t have another option then the question is what are they you know what are they willing to try right is an is

1:02:16an interthal injection a viable option um longlasting alligo do we really need

1:02:22to get to um is is a therapy type approach with a viable then maybe our

1:02:27search platform would be an alternative mechanism for this um or do we really need an ory bioavailable compound and

1:02:35really a small molecule in which case these are really just stepping stones toward an ultimate kind of small

1:02:40molecule drug um that that one would take via pill and if that’s the case it’s going to take a lot longer to get to that um so my long answer is you know

1:02:48I think from the academic lab we get the Technologies and then the idea is eventually we hopefully start companies

1:02:53that think through through these issues and what’s the quickest way to get um to get you know help to patients um

1:03:00specifically in this case though what we’re doing in the lab is we’re testing things via aav when that makes sense we’re testing things via RNA delivery

1:03:07when that makes sense the brain is really tough as as you probably know um

1:03:12we can get oligos in the Asos for splice switching things like the nonsense media

1:03:17Decay there’s some evidence that suggests those can work in the brain um lipid nanop particles don’t work well in

1:03:23in the brain Unfortunately they work great in neurons and culture xvivo they work really poorly in the brain but

1:03:29there are other delivery strategies and oligos making their way into that um and then I would just say maybe from a more

1:03:35optimistic view there are so many interesting aligo Technologies being developed I talked about some of them

1:03:40there’s just many out there so I think in the next couple of years the hope at least that we’re counting on is that

1:03:47more strategies will emerge more kind of positive clinical data will come out and there’ll be other options for how to

1:03:52actually get things delivered effective itively um but you know long term we’re not counting on that like I said we’re

1:03:58investing some of our resources and thinking about other types of modalities to go after um to move away from aligos

1:04:04we have protein based systems and viral delivery that’s a really quick way to get into a patient that we could do very

1:04:10rapidly um but has its own limitations so there’s no right answer it’s a matter

1:04:15of control and technology and then like I said What patients actually want and

1:04:21what you know how fast you want to move into the clinic I think yeah it’s it’s a it’s a rich answer to a loaded question

1:04:28I mean it it it so let me let me take the Willing part headon our our our kids you know kids

1:04:35with singap turned into adults with sing Gap and um I can share this data with you if you’re if you’re curious there’s

1:04:41a poster out of chop that beautifully illustrates that on the behavioral and the autistic features of sing gapan as

1:04:48compared to Rhett as compared to Angelman as compared to epilepsy cohorts we are

1:04:53like way above the meat right so the the our patients are are um our patients

1:04:59suffer mightily they’re very challenging wonderful human beings but they’re very challenging to manage and um it takes a

1:05:06huge toll on the on the on the humans the families right all rare does these family struggle but the but the behavior

1:05:12part makes it really hard for our families to get help because people kick our kids out of programs all the time

1:05:18because they just don’t understand what’s going on with our kids so I think the willingness to take on ther be it

1:05:24interthal or whatever you know obviously I can’t speak for everybody but one of the reasons I I do what I do and I’m

1:05:30constantly talking and I’m constantly telling people about people like you is because I want families to

1:05:37understand that they will have a chance to do an interthal injection in at some point in the future and they should take

1:05:43it very seriously right they have to but that’s part of why we’re having this conversation right now I want people to

1:05:48be thinking about this so I I would I would go as far as to say I believe we can find families who be willing to take

1:05:55these therapies for their kids because they because um as as Gavin RBA said in our last scientific meeting you know

1:06:02neurons want their sing Gap back and and we believe that the brain is plastic enough and that the way the synapse

1:06:08works is if we restored sing Gap we could you know kids aren’t going to become neurotypical but they could seize

1:06:13less they could sleep more they could be less anxious they could be easier to manage so I think there’s a huge there’s

1:06:19tremendous willingness and incredible need here and I and I and I would I would encourage any family member on the

1:06:25call to chime in and tell me if you have another perspective or if you agree on the um on the just just a quick note of

1:06:32that I mean honestly that’s really helpful to hear I mean from our perspective as like basic technologists

1:06:37it’s really hard sometimes it feels overwhelming to do this sort of work because you do have to think about so

1:06:42many things at once and it seems intractable so you know we can develop Technologies but you know having a sense

1:06:49that okay we can actually test these ideas and there’s a short-term goal right and maybe a medium-term goal it

1:06:54really is I think very helpful to make you know make the scientists feel like okay they’re empowered to actually try

1:07:00something because yeah these these seem like I said they just seem intractable but I don’t think they are I think we’re you know world is right now there are

1:07:07solutions that can exist they’re not and we’re willing I mean I’m just looking through the participant list like we

1:07:12have a a parents of an 18y old a four-year-old a two-year-old another two-year-old and 17 I mean that all ages

1:07:21all of them everybody’s everybody’s eager for help and wants to um understand this I want to talk like

1:07:27delivery I I this is something that’s really hard for me as somebody who sits

1:07:32and gets proposals from everyone and their mother right all these cool Technologies right from Tango to what you’re doing to other cool

1:07:39stuff and then you have people who are talking about different delivery mechanisms and they’re like ASO intal

1:07:45keep it simple and then other people are like you know this aav is good this aav has gone

1:07:53through A9 everybody’s used it let’s just use it av9 sucks doesn’t get to another the brain a pick a number this

1:07:59is better we’re doing it in my two years this will be better and I’m just like oh my you’re you’re all making my head hurt

1:08:05and at the end of the day I think it’s going to be both right like I think you guys figure out how to make an

1:08:12elegant efficient minimal off Target effect solution and then there’s a lot

1:08:18of good people working on a lot of Delivery Systems and the question is who’s going

1:08:24to you know H we just have to hope pray slash introduce you to each other that

1:08:30you guys meet in the middle and you know people like Al George and others know a

1:08:35lot of these players and can say hey you should talk to for instance you know we know that at pen there’s this wonderful

1:08:40Grant where they’re doing a lot of sing Gap work and and Bev Davidson is working on some aavs so like if you’re thinking

1:08:47about potential Partners you know the the pen team has

1:08:52is thinking about a and singap delivery and I think delivery to the brain is a whole ball of wax that

1:09:01hopefully people are thinking of but I think what’s loaded in JR’s question this is cool is she she mentions gut

1:09:08pituitary and other system so what if which obviously Jr and others believe

1:09:15singap actually affects outside of the brain and it’s just called singap because you know Rick found it and Rick’s neuroscientist so everything’s

1:09:21the brain and nothing else matters right God bless Rick and and so but what if we need singap in other parts of the body H

1:09:27how how would that work how would we deliver this to other parts of the body

1:09:33yeah it’s tough It’s really tough um if it was the liver would be easy the liver is the one place we can deliver things

1:09:38to Super efficiently with libin NE particles because everything goes to the liver right everything goes to the liver but yeah other places I mean it’s really

1:09:45tough honestly it’s really tough I think and probably my guess is mouse models I don’t know but probably wouldn’t even be

1:09:52you know sensitive enough to see some of those effects I mean honestly I and and to your answer I mean I think I I do

1:09:57think that all these delivery strategies each have validity and I think um yeah they’ll each find their right

1:10:03application maybe their own the right patient subset um so there’s not going to be at least not in the short term one

1:10:09answer I think in a hundred years I’m a chemist in a hundred years we will take everything we learned from all this and everything will turn back into a nice

1:10:15small molecule drug pill that we can take and just have the defined activity it’s going to take another Century to

1:10:21get to that so it’s really just these intermediates right where we need to do viruses or rnas in this case or these

1:10:27things where we just don’t we’re not good enough at designing molecules that have more complex function yet but um

1:10:34yeah I don’t know I think a lot about this it’s challenging you could do a and other tissues but systemic whole body

1:10:40aav delivery I think is not I mean that that seems like a pretty big ask at least for a you know a first generation

1:10:47of a clinical trial you wouldn’t want to do that I don’t think totally totally I think in the short run we deliver to the

1:10:52brain I think what and and I would encourage if not you definitely I think you said his name was Riley whoever’s in

1:10:58your lab if they can’t come P if they can’t come in person anding in person

1:11:03call me um but they should definitely live follow the live stream we have an incredible day of science on November

1:11:0930th science and clinical readout and um whoever in your lab is thinking about singap in the

1:11:14morning that that’s going to be a great meeting awesome that’s really great um with that I grateful for your time um

1:11:23J.R jly says it best this is it was a beautiful presentation very lucid really

1:11:28cool Tech and J.R also echoed my point on these kids need help so we’re we’re

1:11:34glad you’ve chosen singap and uh we look forward to staying in touch last call for the audience if you type now or

1:11:41forever hold your piece okay yeah no thank you all and I I’ll pass on I mean it’s really helpful

1:11:48again the grad students are actually in the lab doing these sorts of things I mean I think like I said a lot of everyone on this team I think is really

1:11:53motivated about trying to use their you know they’re all in their 20s using the best years of their life spending long

1:11:59hours in the lab trying to do something that has some off chance of benefiting the world so it’s really helpful to know

1:12:04that there are you know there are people on the other side of what we’re thinking about so I I I’ll definitely pass that on to them and if you want to if anyone

1:12:10wants to reach out um we’d be more than happy to to make more connections it’s really important for what we do great

1:12:17thank you so much this is aw okay thanks so much for the invite again it was really really a pleasure same here all

1:12:23right