 Thank you very much to the organizers for giving me an opportunity to speak about what we do in the laboratory of Timothilu. I apologize he cannot be here so he sent me instead of him. The LULAB is a large operation with many different aspects ranging from biomaterials to eukaryotes in bio with activities in cancer detection and treatment and also production platform and is also involved in biocomputation so building all of those gates that symbio is so interested in. But what I'm going to talk about is the last aspect that the lab develops which involves possible applications of symbio in infectious diseases treatment and microbiome engineering all of that being somehow linked together. The human body is not just eukaryotic cells it's also a very very large amount of microbes trillions of commensal microbes and a very diverse type of microbes. The gut microbiome for example is completely different from the skin microbiome which is itself completely different even from the head microbiome and what I'm going to focus on today is the gut microbiome. The microbiome especially the gut microbiome is heavily involved in a lot of different aspects of health that range from development to immunity eliciting at the very beginning of life digestion mood behavior and so many other things that are still to be discovered. But unfortunately the tools to manipulate it when some problem is discovered are extremely limited. They are basically limited to wiping it out with antibiotics possibly introducing pro or prebiotics although their efficiency is heavily debated as they are and once you've wiped it out with antibiotics maybe replacing it with the healthy microbiome of someone else and that's about all we have as of today if you want to replace the microbiome. So transplant change the microbiome with something completely different which may or may not be healthy. What we want to do is to have a much more delicate approach to microbiome engineering. We'd like to be able to either selectively add a bug with given with predetermined functionalities to an existing microbiome or possibly remove a bug which is involved in a pathogenic situation and this requires tools that do not exist as of now. So the idea that we want is there may be a problem somewhere in the gut. You design a bug which will then be ingested travel through the stomach all the way through the intestine reach the site of inflammation cancer you name it and then elicit a medical action to cure the problem. As I have written here going from the mouth to somewhere in the gut requires passing through a lot of different environments and this is where most of the previous applications of microbiome engineering probiotics and so on failed very few bugs are capable of adapting quickly enough and well enough to all those diverse environments to actually still be alive when they reach the site where they may do something. So that's one of the challenge. What we expect is that synthetic biology with its capability to design desired functions inside of microorganisms can help with designing microbes that will face this. This is a very common description of synthetic biology where it is usually considered to MNA from a concept which leads to a design. The design may be modeled and simulated and there will be none of that today. Then it is constructed probed in vitro in some form of isolated culture measured possibly evolved if something is not optimal so rare right and then if it still fails maybe go back to the design go through another model iteratively until you managed to build whatever it is that you really wanted to build and at MIT we are an engineering school so we are very much for that top-bottom approach where you have an ID and no matter what you will build it. Lots and lots of work on somehow modifying the microbiome was based on E. coli. The vast majority of the probiotics that exist today are either coli or lactic acid bacteria. Coli is slightly better than lactic acid bacteria but none of them really colonized the gut microbiome easily. Gram negative of the type of E. coli are maybe something in the range of zero one percent of the gut microbiome so it's almost negligible it's not completely useless but very much so. So we are looking for other possible bacteria that would be most suited to creating a probiotic that would be stably maintained in the gut and one such bacterium is a bacteria it is Theta iota micron and you will forgive me if I just call it theta it's way too long. So theta is just like coli or gram negative bacterium it's an obligate anaerobic but it tolerates oxygen pretty well it just does not grow but at least it does not die. It's a member of a dominant filer in the microbiome it accounts for about 30 to 40 percent of the total number of species in an average human gut microbiome. It is very abundant to 10 to the 10 CFU program of stool in again an average human microbiome and is present in the in a large sorry in a large amount of microbiomes of humans. And finally it is relatively amenable to genetic modification it's not nearly as easy as coli but it's feasible. The problem with B theta iota micron is that although it is amenable to genetic modification they are hardly any tools yet. And suddenly nothing like we can have in coli where we have banks of various inducible or considerive promoters large amounts of plasmids which are compatible so that you can add gazillions of circuits inside of the exact same cell. So the question is how can we transfer all of those different biological computations. So those are examples of biological computations that were devised in the lab. So the lab devised various methods for integrating memory inside of bacteria. We also devised ways to make analog computation. We worked also in digital computing like many others. We also devised ways of rewriting DNA directly in vivo inside of the cells. And all of that was developed for coli but how can we transfer all of that into theta when we don't even have a single promoter which is properly described. So the first step in doing what we wanted to do was to develop a set of basic promoters inducible and constitutive a set of ribosome binding sites. The very basic set of tools that you need to build any circuit into any living organism. We started from that simple plasmid developed in the Gordon lab PNBU2 which is an integrative plasmid in theta yota micron that integrates here catalyzes its integration into a serine tRNA. The good thing about that integration inside of a serine tRNA is that there are only two in theta. So if you inactivate one with your construct the other one has to be here. So that limits the possibility of having multiple integrations. And it is selected with erythromycin and it's a suicide plasmid obviously in theta. And it has here a nanolook which is a smaller version of luciferase that gives you a readout for anything you clone in front of it. So what we'll do from that PNBU2 sequence is to vary ribosome binding site sequence just in front of nanolook very promoter sequence. I say luciferase activity in different conditions and see what we can do and finally engineer all of that to see if we can change levels. In coli the ribosome binding site is well defined. It has a consensus sequence of AGG, AGG that matches well to the end of the 16s RNA. All of that is good and if you modify the sequences on both sides of the ribosome binding site or within the ribosome binding site you can change the level of expression of genes from zero to maximum which is whatever coli is capable of tolerating. In bacteriolidus the consensus sequence of the ribosome binding site is not that different. It matches to the end of the 16s RNA just as well. And so the idea was well if we do exactly the same thing as in coli then that should work right? That looks feasible and even the natural coli ribosome binding site should work well enough. So there shouldn't be too many problems with translation. So that's exactly what we did. We took our PNB U2 Plasmid. It had we cloned known constitutive promoter from Theta in front of it. The Cheyenne Dalgarno was that of that BT1311 gene and we started making libraries by randomizing the sequences around the Cheyenne Dalgarno and assessing function. So just for reference this is the kind of thing you can get in coli when you modify the sequence of the ribosome binding site. So you get from very high to absolutely zero with some of the mutants you make. Interestingly enough when you do exactly the same thing in Theta you go from high so that red line here is the natural ribosome binding site the one we started from. So we can increase a little bit maybe half a log. We can decrease some we can decrease by about two log but there is no way to make it completely negative. For some reason you can put any sequence and no matter what you will still get some level of expression. Some people suggest that actually the pairing with the 16s INE is not the major determinant of specificity of the ribosome binding site and that in Theta it's more binding to the S1 protein of the ribosome which dictates recognition. So there's a lot less of the base pairing involved as recognition of an actual phosphate backbone. Ribo phosphate backbone because I don't think anyone knows where it really binds. Nonetheless we could still get something in the range of about three logs difference between the strongest and the weakest of our ribosome binding site. But this large difference in behavior between coli and Theta probably explains why a lot of parts that were brought from coli into Theta completely failed because they are obviously immense differences in how the two bacteria work. Now we decided to look at promoters. In coli, promoter specificity is dictated by a sigma factor. There are several in coli. I'm not going to go into the detail. Each of those sigma factor recognize consensus sequences which are different and so exactly the same way as you could do with the ribosome binding sites earlier if you modify either those consensus sequences or the sequences in the middle you can vary the strength of the promoters. Theta has a completely different promoter architecture. There is a single sigma factor which is responsible for all transcription in the genome of the bug. And the consensus sequence is pretty different from that of coli with instead of a minus 10 or minus seven box and instead of a minus 35 or minus 33 box which does not look very much like that of coli. So when you have a circuit that works in coli it's pretty unlikely to work in Theta directly because if the ribosome binding site may possibly work there's no way transcription will ever work. So we started building libraries of constitutive promoters using the randomization strategy that I told you. So this is our starting promoter PBT 1311. We also clone a few other promoters from B Theta that were expected to work well. And we also started introducing viability in all those various regions highlighted in blue here either replacing those regions with those from other promoters or from completely random sequences and I'm just showing you a few examples of the promoters we got out. And all together the different constitutive promoters we managed to build span about two logs of magnitude in expression level. So when you combine the different transcription levels we're capable of reaching with the different translation strengths that we're capable of doing within the ribosome binding site library we get about five log difference which is about four logs more than whatever was possible before. But constitutive expression is still fairly limiting. A lot of the constructs we use for any circuit require being capable of turning things on and off on demand. So we wondered how we could obtain inducible systems. Bacteriodes Theta has an extremely varied array of carbon source usability. It is capable of degrading a lot more carbon sources than Coli and just like Coli it senses them and induces the genes for their degradation only on demand when the carbon source is there. So there is a large amount of systems that can be borrowed from the genome for sensing at least carbon sources. One such example is the Ramnose regulation system. In Theta Ramnose sensing functions very much like Arabian sensing in Coli. So you have a single regulator called RaR that binds to Ramnose and then activates the Ramnose operand promoter PBT3763. And so if we clone that promoter in front of Nando Luke you can see that while we increase Ramnose concentration we increase expression of Nando Luke of Luciferase and we get an about 104 fold difference between absence of inducer and inducer which is pretty good. We screen the genome for other types of inducible promoters. A lot of those carbon sources are sensed through kinase response regulator systems, two component systems, although those of Theta are different from those of Coli. And one such example is the Kondroitin sulfate response regulator BT3334 which senses Kondroitin sulfate activates the promoter and we got about 60 fold with that system or the Arabianogalactan system encoded by PBT0268 which gives us about 29 fold induction between absence or presence. Now we had a number of simple parts we wanted to check to what extent we could build more complicated parts. So try to import functions that are not native to Theta. And the most simple system to do that is probably the LAC system of Coli. So we wanted to see if we could get LACI to function in Theta. So we put LACI under the control of Theta promoter PBT3011 actually and then created a mutant of the PBT3111 promoter with LAC operator sites at various locations. And we build actually all possible combinations of one, two, or three operators. Interestingly, they all worked. They did not work great. There is limited dynamic range in those promoters. But what's interesting is that by modifying the relative position of those LAC operators, we could change the sensitivity of those promoters. So that gave us the possibility to induce at various levels of IPTG. Finally, we tested whether all of those promoters that have different inducers, but remember they're all sugars or derivatives of sugars were orthogonal to each other. That is if the inducer of one system would induce another promoter. And what you can see on that graph is that there is induction when you combine the inducer of a given system with its corresponding promoter, but absolutely not any induction with the other inducer. So they're perfectly orthogonal. So now we have a good library of parts for transcriptional control. And we wanted to see if we could go a little farther in complexity. And what we've done is to see if we could replicate memory integration inside of theta. The idea behind that memory integration is pretty simple. It uses the capacity of integrators to flip pieces of DNA between inverted recognition sites for that given integrators. And we used a system developed by our neighbors in the Voigt lab where they built an array of different integrator recognition sites along with all of the integrators that specifically recognize each of those sites. We only cloned four of them as a test trial and checked what happened if we would transform theta carrying this on its genome with plasmids constitutively expressing the integrates. And what these gels tell you is that in the presence of the corresponding integrates you get the right the expected inversion. So everything works great. We then checked briefly if it worked with an inducible integrates and to make a long story short it does. It does actually beautifully much better than in coli because we have absolutely no activity of the recombinase when we don't add any inducer which is rare of coli promoters. The vast majority of coli promoters have some leakiness especially in those systems. Still pushing further in complexity we wanted to check if we could benefit from all of the advances of CRISPR-Cas. So I'm expecting everyone is familiar with CRISPR-Cas but in case not very briefly Cas9 the natural Cas9 is a nucleus which requires a small RNA to direct itself to the appropriate sequence in the DNA that it then cleaves. Here we're using a D-Cas9 which is a deactivated Cas9 so the active site of the nuclease were modified so that it can no longer cut DNA but it can still land on it and stay there. So what we were hoping with a D-Cas9 based system was that we could perturb expression from genes. The first system we built was pretty simple. It used an IPTG inducible D-Cas9. We would clone whatever guide RNA we need to direct a D-Cas9 to given sequences within the promoter or the coding sequence of nanolook and then we would measure the luciferase activity as a function of IPTG and what this graph or this graph they both show the same thing show you is that it works beautifully when you add IPTG then luciferase activity goes down indicating that the D-Cas9 really does land here and does prevent transcription. It's a little surprising though that even the single guide RNA is targeting the coding sequence of luciferase still had an activity. Again this is a big difference with Coli. In Coli D-Cas9 really only works if you target within the promoter and as soon as you get outside of the promoter it quickly sees working. We then wanted to check again with that system if we could target those genes genes. These two genes here are involved in polymixin B resistance so we wanted to check if by using the D-Cas9 targeted system we could inactivate those genes and thus decrease resistance to polymixin and that's indeed what happens. We also use that exact same system but targeting some of the carbon source usability operance of Theta and you can see here that when we induce the D-Cas9 system with IPTG then growth on fructose stops pretty abruptly indicating that the targeting works as expected. Everything tends to work pretty easily in the lab in culture medium very often when you go to a more natural environment things stop working so we wanted to see to an extent all of those parts that we had built would still work within some form of natural environment and we chose mice because they're easy to manipulate. So what we did was to treat mice with tritomycin to strip them off of most of their microbiome then remove antibiotics colonized with various Theta strains that would not have synthetic constructs and then treat those microbiomes with induces as needed collect the stools and then measure luminescence and measure the presence and abundance of Theta by QPCR. The first system we tried was a very simple Arabino galactane induced Luciferae system just to see if anything would happen whatsoever and what you can see here is that this represents times when there is Arabino galactane in the water of the mice and you can see that there is a sharp increase in Luciferase activity in the stool as we induce and it goes back to baseline very quickly after we remove inducer. So it seems to work well we then tested the CRISPR system in a similar system so it's exactly the same system as I presented earlier it's just a lot more complicated so there are a lot more places where things could go wrong nonetheless it still works okay we're probably reaching the border of what no longer works but here again we have IPTG addition and you can see that when we add IPTG Luciferase activity drops which is exactly what we would expect when it stays perfectly flat in the system that doesn't have all of the regulatory systems. So here I have described an additive system to add a programmed micro inside of the microbiome the problem is doing it still requires a pretty heavy treatment with antibiotics to strip off everything that is not really desired and replace it with what we want so we are now focusing our efforts on trying to build systems to selectively remove a given member of the microbiome and replace it with what we want a subtractive approach to a microbiome engineering. Our first attempt at that was using again Cas9 this time the real Cas9 the one that cuts DNA and was aimed at targeting antimicrobial resistance gene in natural environments so the idea was pretty simple you have delivery vehicle in this case phage M13 because it's very easy to engineer that M13 delivers a piece of DNA that has the Cas9 the tracer RNA which is required for Cas9 functionality and most importantly arrays of guide RNAs that direct Cas9 to their target and the target may be in the genome or in plasmids and in most cases in bacteria when you make a double strand cut the cell just dies it's particularly true on plasmids because most plasmids have toxin anti-toxin systems and if you make a double strand cut very quickly the anti-toxin degrades and the toxin kicks in killing the cell so results can be seen here here you have all of the control strains that means they do not have the target for the Cas9 system and you see that there is absolutely no toxicity so if the target for the guide RNA is not here nothing happens however you can see here for example that in a strain that has NDM1 the phage that targets the NDM1 sequence kills the cells here you have a similar system targeting another type of antimicrobial resistance genes and exactly the same thing happens it is very specific to the sequence and you can even mix the phages together and target both at the same time if you want you can also direct the Cas9 cleavage to the chromosome this is what we've done here we've isolated a mutant of our test strain EMG2 that is naludixic acid resistance so has a mutation jar A this is a single base pair mutation and the guide as you can see is extremely specific it kills the mutant it does not kill the wild type what we've done next was to see if we could counter select variance factors so here we've been targeting the Intamin gene that we've heard about yesterday I believe which is a major variance factor of enterohemorrhagic coli and once again with the proper with the proper guide RNAs we managed to eradicate the targeted cells with our engineered phages and we've also looked at whether or not these engineered m13 phages could help with survival in the case of infection we've used the waxworm model here and we're following death of the worms after being injected with either a non-sensitive sensitive cell so bacteria that cannot be targeted by our engineered m13 or cells that can be targeted with the Intamin targeting phage and what you can see is that if you don't infect the waxworms they don't die if you infect them with just the phage or with sorry with a phage which does not target the strain that we are also putting in the worms they die if you treat them with SM buffer so just any buffer they die but if you treat them with the Intamin targeting phage which is the one that can kill off the bacteria that we're injecting they survive significantly better there is one major flow with that project m13 is wonderful for molecular biology it's small it's easy to to engineer you can do a lot of things with it the problem is it's absolutely F dependent it's a conjugative plasmid and F is extremely rare in nature so this is a very nice system in the lab absolutely useless in real life so we have to find other delivery vehicles the system can work but we need other delivery vehicles phages are probably one of the most efficient system for delivering DNA to bacteria conjugation requires way to intimate contacts to be useful again in the context of a microbiome where you have billions and billions of other bacteria so the probability of encounter close enough between your donor bacteria and your recipient bacteria is way too low so um classically if you want more phages you isolate them from nature uh and you end up with a wide variety of phages that may or may not build strictly litig that may or may not integrate in the genome that may or may not possess uh various factors and you assemble them into a cocktail of phages that collectively target all of the possible strains that you need to target um the problem with that is that for every phage you add to your cocktail you need a whole lot of tests to make sure that everything works the way you want it to work uh so the approach that we are trying to use is what if we could transform phages into some form of antibody where we keep everything that makes it a phage that makes it a good delivery vehicle and change what makes it target a given type of strain so that you can develop a set of phages originating from the exact same chassis but targeting different bacteria maybe a graphical visualization will make it clear let's say that these are all the strains you need to target to treat any given disease they all have a different envelope they may have different sets of genes inside of them that may provide defenses against phages traditionally you go into a sewer plant or whatever natural environment suits you gather a few liters of the of the effluent and pretty easily you find phage against pretty much any bacteria so that's what you see here you find phages and they may infect a single bacterium or infect several and it's pretty unpredictable then if you want to use them in any kind of industrial setting they need to be tested one by one for specificity for stability in terms of storage for their biology do they have erroneous factors are they lysogenic or strictly lytic then if it is for a medical application you also need to test safety efficacy delivery all of that one by one before you finally think about putting them all together and have a product which obviously because bacteria where they are they evolve so that cocktail will need to be updated probably twice yearly so twice a year you need to go through all of that for your new cocktail that just cannot work so what if instead of that we use a single chassis a single phage which we have decided is a good starting point make all of those uh uh testings so that we know everything about it everything we can and for some of the phages we already have this is almost there and then simply grab from all of those natural phages or all of the DNA banks that we have the sequences that we need to make that single chassis infect all of the strains hopefully then limiting the amount of testing you need to make to get it approved for any kind of medical application obviously at this point this is just a project uh but actually the FDA at least is pretty interested in it and we have some fair amount of hope that this can be a viable solution to phage therapy in western worlds so let's test it the phage we decided to use for initial testing of that ID is the family of T7 the reason why we decided to use T7 like phages because they are very widespread in nature they're very easy to use in the lab they are well studied and understood they have a relatively short genome genome with few activities so not too many chances for surprises and most importantly they are extremely host independent outside of their receptor the surface of the bacterium the only other gene they need from their host is the cyroredoxin which is an adjuvant to their own RNA polymerase to make it more processive so there is hope that it can actually work in a wide variety of bugs the other reason is by informatic if you align all of the tail fiber genes which is the major host determinant in T7 from all of the sequence T7 like phages together what you find is that the first about 150 amino acids are pretty conserved with the rest is not conserved at all the consensus to explain that is that that 150 amino acid and terminus is involved in binding the tail fiber to the phage because the rest is different because it infects different bacteria so it needs to recognize different receptors so one of the ID is can we start from T7 or T3 and graft inside of either one of them any of those other tail fibers thus changing host range summarized here so you take phage A that infects bacterium A phage B that infects bacterium B what happens if you graft the tail fiber gene of gene B of phage B inside of bacterium phage A does it go after bacterium B bacterium A or something completely different to start simply we started with T7 and T3 they are both coli phages they are both well studied they are both understood but they don't both recognize the exact same receptor well T7 binds somewhat deeply in the LPS of coli T3 binds at the very top so that in principle and it's been demonstrated in some cases exchanging the gene should change the phenotype and we can indeed see that here while sorry while T3 and T7 infects B strain perfectly well as well as regular K12 cloning strains T3 here does not infect MT1655 or BW25113 with T7 dose so we now have a screen if we change the GP17 genes to I'm going to skip because time is running out so now how are we going to do that because engineering phages is much more complicated than it seems traditionally it's done without the replacement systems to make it short because I'm running out of time this rarely works it's long and painful so what we've developed is a system that uses the gap repair system of saccharomyces cerevisiae to completely reconstruct the genomes inside of yeast before booting them back to life inside of coli so the system is pretty simple you isolate the genome of whatever phage you want to play with you need a yeast artificial chromosome which will make the final construct replicate inside of yeast you transform either the genome plus the yak or various PCR products that span the entire length of the chromosome of the phage with ants homologous to the yeast artificial chromosome and used by some miracle reassembles that into a fully assembled genome you extract that yeast artificial chromosome transform it into bacteria and if you've done your design properly you get functional phages which you can then maintain grow play with obviously in some cases it's not going to work but at least compared to other replacement methods we have the yeast clone we can at least go back sequence regions check if it didn't work because something happened during the PCR there is a mutation and the phage is dead or if that's simply our design which is wrong and we need to go back to the drawing board interestingly enough that works with a lot of different phages so we've tested it with a number of different T7 like phages and again long story short it works with all of them independently of what hosts they normally infect and we built from T7 a T7 that has the T3 tail fiber and a T7 that has just the C terminal part of the T3 tail fiber remember that only the end terminus is conserved we had no idea if the T3 tail fiber would be able to bind the T7 capsid by itself so here is again all of those phages plated on BL21 which is a common host for them and then tested against a selective host you can see that while T7 still grows on MG1655 the reconstructed T7 has exactly the same phenotype but the T7 with the T3 tail fiber no longer grows on MG1655 and conversely for the T3 mutants so the idea works if you change the tail fiber genes you can change host range we then wanted to see if we could cross species barrier here we resorted to a completely synthetic approach to making the genomes it turns out that that phage R that infects Yasinia only has three point mutation difference in the with the T3 gene 17 so the tail fiber genes so instead of sourcing out gene R amplifying the whole GP17 we just decided to order a piece of DNA that corresponded to that region where they are the mutations and then go through the exact same assembly process to make a T3 phage with the R C terminus of the tail fiber and you can see here that while T3 does not grow on Yasinia T3R grows perfectly fine on Yasinia and kills it extremely efficiently in vitro we wanted to go even farther and try something a little more difficult we had tried so K11 here sorry it's nowhere K11 is a klepsiola phage Klepsiola is very different from coli that they are all capsulated in sharp contrast with the laboratory coli which all have a rather rough phenotype so a capsule is something that a normal tail fiber cannot bind to it's a thick layer of mucus surrounding the cell and that prevents the phages that recognize LPS from actually finding it so we wanted to see if we could graft onto T7 something that would allow it to go through that capsule and infect klepsiola so our first attempt was to simply replace the tail fibers of T7 with those from K11 but that did not work we don't know why but it did not work so we started trying out all of the possible combinations and it turns out that if we replace the whole tail the tail being composed of GP11 12 and 17 then we get a phage that infects klepsiola just as wild type so this is T7 on coli T7 on klepsiola you see it does not infect there are no plaques and here we have K11 wild type it does not infect coli but infects klepsiola and if you bring the tail of K11 into T7 then you get a phage that grows on klepsiola and conversely if you bring the T7 tail inside of K11 you get a phage that grows on coli so that tells us that although tail fiber swapping is a method that can work it's not always a sufficient and that points out to the extreme lack of knowledge we have in the structure function relationship in phages because there is no reason why just cloning the c-terminus of K11 GP17 would not work there is no bioinformatic way to predict that still it did not work so we are here hoping for as Patrick was saying maybe more predictive tools maybe more bioinformatics maybe it's just that the tools that we have are not sufficient what I want to point out and that will be the end and I will almost be on time is that we used those engineered phages in a synthetic baxial consortia to check if they could work just as well as wild type phages in removing their specific bacteria in the context of some simple microbiome this is only in vitro we are doing any more experiments right now but they're not at all ready so the idea is pretty simple you mix in approximately equal amount probiotic coli nasal the target strain for K11 the target strain for R yasinia and then you try the various phage combinations and see what happens after a short while and what you can see is that even in 30 minutes when you add K11 onto that synthetic consortia Klebsiola is completely annihilated so on a pie chart like that it's difficult to see but we have an about five order of magnitude decrease so there is a very tiny croissant here it's just not visible and the same thing is true if you use the engineered phage T7 K11 GP 11 12 17 although just as we could see earlier it's not quite as efficient it's probably good enough but it's not quite as good but if you give it a little more time it still works and if you mix T7 which targets here senior and the phage targeting Klebsiola then you can almost you can completely remove the the two pathogens in about an hour that being said I would like to acknowledge members of the lab as I said the lulab is a big operation lots of people so particularly Hirokiando who worked with me on all of the phage engineering work Rob Citoric who worked on the M13 cast delivery Fahim and Marc who worked on the bacteriodes aspect of things along with our collaborators from the Chris Voigt lab and all of the other members of the lab and our funding sources thank you very much