Directed Evolution of Enzymes: Golden Age Insights

[00:00:01]uh it is uh our pleasure to introduce uh Miguel alcal to all of you um so Miguel is uh going to talk about the Golden Age of directed evolution of enzymes and we are thrilled to uh listen to your talk obviously Miguel is full physique Professor from The Institute of the catalysis Pica in canto cantoblanco campus is uh as I said theik research professor and founder of Evo Evo enzyme which is a spin-off stemming from his research group um the central research of uh Professor Miguel alcal primarily focuses on the engineering of enzymes by directed Evolution for a wide range of biotechnological purposes as well as synthetic biology studies for environmental energy and Industrial applications Miguel is a biologist by training with postdoctoral State at Caltech in the group of Francis Arnold who was a novel liate in chemistry in 2018 co-author of over 150 articles of on enzyme engineering and applied bio biocatalysis and 14 fied patents Professor alcal has supervised 37 research projects and 12 PhD thesis he was working as a manager of national research agency of Spain in the area of biotechnology from 2019 to 2021 and was in charge of coordinating the section of molecular biotechnology and synthetic biology of the Spanish Society of biochemistry and molecular biology from 2017 to 2020 he's a current board member of the bio biocatalysis division of the European Federation of biotechnology so with no further Ado please Migel thanks for coming okay uh well first of all thank you very much uh the organizers The Institute for the invitation I truly appreciate it it's great to be here um yeah today I'm going to talk about the about directed evolution of f science I've entitled M the Golden Age of directed Evolution and in case um you are not familiar with directed Evolution uh I've divided my thought into two parts first a brief introduction about direct and evolution and afterwards I'm going to to illustrate uh uh what we do with directed evolution in terms of protein engineering with different case studies taken from my laboratory I'm going to discuss a little bit about chimeric Li casis also about a a exotic research topic which is the resurrection and evolution of ancestral enzymes and last but not least I would like to say a few words about peroxy Genesis in synthetic chemistry so let's start with the introduction about directed Evolution um all of you know that that enzymes are wonderful biocatalyst H which can speed up chemical reactions millions millions of times uh and that's why they find a lot of applications in different H industrial energy environmental sectors however to uh adapt enes to Industrial standards they need uh to be modified genetically modified by the hands of a revolutionary technique named as directed Evolution uh and now one can doubt now about the power of directed Evolution it's a reliable method An Elegant a robust approach to tailor enzymes metabolic pathways or even whole microorganisms with improved traits H basically by mimicking the darwinian algorithm of natural selection by the introduction of random mutations uh by DNA Rec comination and coping this to artificial selection we can reduce the timeline of evolution from millions of years until only a few days of work on the bench of the laboratory indeed by directed Evolution we can sculture different biochemical properties in enzymes in proteins antibodies uh in terms of activities we can modify substrate specificities we can generate catalytic promiscuity we can modify Cho and antio radio selectivities but also we can develop more robust biocatalyst we can generate stronger stabilities against high temperatures or the presence of organic solvents or uh enes that can tolerate different kinds of Inhibitors or even to H enhance functional expression levels in a host from a scratch so the ultimate goal of a directed directed Evolution experiment the ultimate objective is the design of customized s and that's why uh this re revolutionary method was uh recognized well the inventor of this My Mentor in IND directed Evolution my teacher Francis Arnold was recognized with Nobel priceing chemistry in 2018 because of the impact that these uh methodologies had in society but of course also in science um in case you're not familiar with directed Evolution this is just a a brief picture about how a directed Evolution workflow is basically we start from a gen a collection of Parental genes with certain degree of sequence identity within each other uh these parental gen are going to codify for a given enzy that we going to improve uh we generate diversity DNA diversity by different molecular biology techniques we introduce random mutations we induce recognition events and these mutant libraries are going to be transformed and going to be introduced in an H typically either eoli or Yeast we IND use the expression of the Gen we IND use the expression of the enzymes and we screen towards the biochemical property we want to improve let's say that we want to have an enzyme that somehow must be more stable at high temperature we incubate these libraries which are typically in this 96 well plate format at high temperature in such a manner that only those variants which contains mutation that somehow adap Den to these conditions are going to show a reliable colorimetric or fluorometric response against a pro and we choose these variance uh as parental types for a new round of evolution round after round of evolution we are accumulating beneficial mutations on improvements until we achieve the desired trade um at this point I would like to say that in my laboratory and also in other Laboratories all around the world people researchers are using sakaris as Aur host for directed Evolution we are I would say that in 95% of the cases in my lab we are working with eotic genes and therefore we perform directed Evolution with eotic cells in sacaria not only because allows the H secretion of enzymes and also because the advantage in terms of postal modifications but also because saramis has a high frequency of DNA recombination and this Ino Gap repair mechanism of saramis is extremely useful in directed Evolution experiments uh for the generation of DNA diversity and even though this is something that somehow is out of the scope of my talk for today because uh we don't have enough time to disain this but nevertheless let me tell you that uh most of the examples you are going to see here in my presentation for today are based are supported by the directed evolution by the Sorry by the physiology of the S Machinery in terms of Library creation um if you are wondering how we introduce these mutations there are two ways or to to approaches what we call the sexual approach which basically means the introduction of random mutations and the sexual one how we introduce random mutations typically through a error prom PCR we you know that when we are amplifying DNA we are using polymerases with High Fidelity so basically we H alter the conditions of the PCR reaction in such a manner that the polymerases are making mistakes and those mistakes basically means that this this this polymeres are introducing mutations in the process of amplification of DNA and this introduction of mutation is occurring randomly um and the second approach is the sexual one which basically means the rec combination of different parental genes in order to H have chimic answers let me uh establish an analogy between what we call animal breathing and molecular breathing in animal breathing we start only with two parenes two parental types in molecular reading we use one two or many parents actually we can Shuffle many different enzymes many different genes from different sources in an in animal breathing we have only one of a spring uh however in molecular breathing we can have tens of different of Springs the limitation is only imposed by the screen as we have in hand in animal breathing we have a stet philogenetic barriers we cannot mix a whale with a Dunkey indirected evolution we do uh we mix well with d actually we mix very different genes with sequence identity below 50% in some cases and last but not least H in animal breathing everything is slow but in molecular breing in directed Evolution we can generate diversity even daily still H we have several botter necks in directed Evolution and I'm going to give you some figures to for you to understand how difficult is to find or to design an enzy still by directec Evolution let's say that we have a given protein a given polypeptide that we want to evolve formed by 300 amino acids if we just want to change one amino acid anywhere by the 20 naturaline amino acids the number of possible variants is roughly 6,000 is something that is handable we can screen that with our robotic PL platforms but in case we want to change two positions anywhere by the 20 naturally uring amino acids we move to this number 16 Millions which is not something that a laboratory can handle and let's go further so if we want to explore all the possibilities in a 300 protein amino acid we move to this number 20 to the power of 300 which is as Francis anold said in his novel lecture an astronomical number even higher than the number of atoms that exist in our known universe in other words even though we have wonderful molecular biology tools and good ideas we cannot explore all the possibilities and it's a Pity because I wish we could have the whole picture of a directed Evolution experiment with a given en right but things are changing little by little um well let me tell you something about this before uh about the solutions and is that apart from the astronomical number of the B protein sequ space we have to take into account that when going through these mutations in a given protein in the best scenario perhaps we can improve the enzyme but most of the cases we are going to harm the enzyme because most of the mutations that we are introducing in an enzy are the lerus some of them are neutral and only a few are beneficial mutations and besides this we have to take into account that a portion of the landscape the protein F landscape is responsible for encoding functional proteins with clips and holes where slight changes in sequence lead to a total loss of function so as I'm saying here it's very difficult to engineer insance in the laboratory but still we are getting good results so we are lucky and what I was saying before is that things are changing little by little because now with the revolution of computational algorithms uh more Laboratories around the world are uh in implenting a machine learning guide DED Evolution where you can generate functional data labels what we call labels say function sequence uh information experimentally in the we lab and we transfer this information to uh uh machine learning deep learning algorithms in such a manner that they give us an output with which we can after work fit the experimental work and this iterative process is taking part of the directed Evolution work flow right now also apart from machine darling H there are other computation algorithms which are in the toolbox of uh uh strategies for directed Evolution atomistic and philogenetic design I'm going to discuss a little bit about this and also in case we want to make structure guided Evolution uh of course the recent developments in Alpha to so Al together more or less uh is uh what the real advances in direct Evolution are taking place right now and now that we have I have put you I hopefully in context about the directed Evolution I'm going to give you some case studies from my laboratory starting with LA cases but before starting let me share with you a hidden secret what is not a hidden secret anymore is that uh I'm super fan of a Star Wars movies and I put in this slide because in the next few uh minutes you are going to find strange names of mutants La Vader bad one grou Han Solo or whatever and those mutants is because the responsibility once we evolve fin in the laboratory the final variant ER we put this kind of names and it's my own responsibility because I'm super fan of Star Wars and I must apologize about that it's not a matter of my student it's just my my responsibility okay so having said this let's start with fungal laes La cases are uh blue multier containing enzymes they are polyphenol oxidases which catalyze the oxidation of of phenols polyphenols um many other aromatic compounds um with the concomitant reduction of molecular oxygen to water actually La cases are considered by many as the ideal green Catalyst because they can oxidat a bunch of different compounds releasing water as only by product and using oxygen for a and we've done a lot of directed Evolution campaigns with different Lac cases actually when I return from Caltech the ver the first IGN with which I was working with a la cas and we've spent the last couple of DEC doing things with LA cases but for today I've just taking this example about Chim Li cases so actually we wanted to combine the properties of different Li cases from different sources H using a computational and directed Evolution algorithms and we did this in collaboration with Francis uh actually she developed when I was there an algorithm a computational algorithm which is called schema rasp and it's a computation method by which we can obtain ktic proteins by homologous Rec combination of different parental types so basically this algorithm allows us to establish crossover points between different parental types and Define the blocks which are going to be Rec combined and afterwards after these calculations which are based of course in the structure of the protein so you need the structure of the protein this is important but also in the interaction between enzymes and the neighborhood uh uh we trans transer that information which was calculated computationally to the world lab and we have this we have done this with uh three different Lac cases with different Redux potentials with different substrate promiscuities and different stabilities we generate a libraries uh several libraries of schema rasp and at the end we selected one in which we Define four different H schema Ras blocks as you can see here and interestingly uh the catalytic pocket of the Dias were conformed by the different blocks of the different parental lenss and we screen this M library uh against thost stability because one of the most beautiful uh approaches of schema rasis that once you create the family of chimeras you can improve the Thal stability and indeed we did uh if you take a look at the at the um these three guys are the parental types and this is the ER half life the half life we Define as the time in minutes required by the en to lose 50% of his agial activity at room temperature when incubated at 70 degrees so these three guys especially the the first one the a a a a parental type are strongly thermostable but if you take a look at the chimeras for example this Chimera surar by by by far the behavior of Parental types so in other words the cheras were much more thermostable than the parental type which is a good result and other interesting information that uh we we learned from this experiment is that because the catalytic actic site which is formed by four copper atoms one coer atom and one coer site and three copper atom which are cluster in a three nuclear coer cluster where oxygen binds this catalytic site where was confirmed by the participation of the different Lac parental enzymes and we detected that the promiscuity the substrate specificity of the enzy was broader in the chimic enzymes than in Parental tyes which was very useful in terms of future applications in in different sectors as we wanted to improve further the thermostability of this enzy we thought that might be interesting taking a look at the experiments we did many years ago with other La cases finding stabilizing mutations which could be incorporated in this chimic enzy and actually by Rec combining all these mutations in the ktic enzyme we obtain this final variant which we call La B mutant whose half life at 80 deges is over 200 minutes this enzy is one of the most potent laccases reported so far because has several attributes together has a high rate potential at the1 per actually one of the highest reported so far because was evolve also uh for this application has a high th stability and has a broad substrate specific okay and now let's change a little bit about uh uh about uh other applications in terms of protein engine I'm going to discuss a little bit about resurrection and evolution of ancestral en this this topic we have to to think in the basics about the the origin of our of of life in in our planet um um it is well known that when life AR arose many many years ago in our planet the Primitive cells only contain a limited set of enzymes a few doz or hundreds of enzymes not like modern cells which contains thousand of enzymes because they couldn't afford to have a whole Repertory of enes for every single metabolic task within the cell but what happened in the course of Natural Evolution is that these enzymes which were generalized in terms that they were displaying different activities for the different metabolic Tas that were required for survival they specialize in the course of evolution in such a manner that all these activities some of their were improved as you can see here in a mod en but other were lost okay now with h the arise of uh uh a computational methods is possible to infer the sequence of ancestral enzymes in your computer afterwards you have that sequence you send an email to a company which is going to synthesize for you the DNA of which correspond to that protein and you can introduce that DNA into a mod micro the infer the infer of the infering the the sequence of an ancestral is soal ancestral reconstruction and put that Gene into a mod micro is called ancestral resurrection and in principle this ancestral nodes are Virg molds for directed Evolution are good canvas for directed Evolution because what we could do afterwards is take advantage of this ancestral enzyme and move forward by aded evolution in order to have enzymes that show different activities of properties that were present in the praman era for example but are not in our planet anymore because they were disappearing little by in the course of evolution or even we could take the other way around we could travel back from a mod counterpart by genetic drift which is the introduction of Random mutations which are neutral mutations and that can open the subst promiscuity and afterwards travel forward by Evolution whatever the case this concept of uh evolving resurrected resurrected enzymes can be a suited veicle to engineer Noel catalytic functions but also to explore natural evolutionary principles in terms of protein robustness and bability and we've done this with different enzymes with laccases with peroxygenases with cinis but today I'm going to show you the first example that we published that was with a rubisco with a an ancestral rubisco all of you know that rubisco is an enzyme that is strongly linked to the conditions of our planet actually it's an ancestral enzyme that is involved in the fixation of CO2 in the biosphere and this was a project funded by repol foundation in collaboration with Spencer winey who is a who is an international reputed expert in in rubisco engineering and also with Jose Manel Sanchez R who is Pioneer in the concepts of ancestral reconstruction so what we did in this project was well of course we did a lot of things but as you can imagine because it's a company behind I only can tell you a really tiny story about all the results we got what we H H where allow to publish was that uh we resurrected s ancestral notes from a rubis from a mother rubisco a mod rubisco was used as a query and we use that mod rubisco to inere the ancestral nodes of uh this evolutionary trajectory and we obtain three ancestral nodes which were we travel back actually roughly almost three billion years salt to the praman ER and we obtain this ancestral not we were functionally Express Nicolai and which had uh roughly 50% of mutations in its ancestral mutations in its structure and afterwards I wanted to know whether an ancestral enzyme could be ER evolved in the same manner that as mod enzyme so what we did was a directed Evolution campaign in parallel evolving a modern rubisco and evolving an ancestral one and what we observe H in this experiment is that the ancestral rubisco was much more tolerant to the introduction of mutations in the process of evolution which makes sense because let me put in this way an ancestral enzy in principle has not be has not suffered the process of Natural Evolution when you are evolving something in nature when something is evolving in nature you're accumulating beneficial mutations but also destabilizing mutations and this ancestral enzyme in principle did not contain destabilizing mutations and that's why was capable to keep a good stability and high mutational loadings in a process of directed Evolution nevertheless um I I I including this this slide because it's very funny uh you know that I have already shared with you that I'm super fan of Star Wars and science fiction movies in general terms and a guy emailed me one afternoon late late in the evening and he told me well I'm working in the C D asrology from CS I I'm the director and I want to send your ense to Mars and I thought that was a yoke and actually it wasn't because this guy is Victor parro who was you know in this kind of uh uh program in collaboration with NASA and and actually H H they were trying to put to prepare a pro for the detection of signs of life in the Perma for frost of uh the surface of of Mars so the idea was was with prepare this Pro with the antibodies of our ancestor en another en that they were taking from here and there make a hole in the Perma fro and try to find signs of life so this a really exotic application about our ancestral enes I never thought that our enes could travel to to Mars the bad news is that the the the program is still pending because there is a strong competition between different agencies and we'll see whether or not our Lac cases or our our risos are going to travel at the end of this of this period but nevertheless it's exciting okay okay and to end my talk I'm going to give you a few words about peroxygenases H for synthetic chemistry because it's an enzyme in which we've ER has invested a lot of effort in the last uh 10 years uh the was discovered by my colleague my friend Martin Hofer from the Technical University of dresen in 2004 and since it's Beginnings was considered by many as a chimic IGN because it shares the catalytic attrib of peroxidases generic peroxidases in terms of that these enzymes can perform one electron oxidation reactions but also of cytochrom for 50 monoxygenases so uh basically the especially the the the peroxygen activity of peroxygen is very interesting because they can introduce they can introduce oxygen in carbon hydrogen bonds selectively using only hydrogen peroxide as final electron receptor a main oxygen source so you are going to find a lot of advantages if you compare peroxygenases with p450s because p450 can do the same of course but they need expensive auxiliary flow proteins Rosco factors they are link membrane proteins however peroxy are secret I highly are highly stable and extracellular and uh indeed since uh this enzyme was first reported in 2004 over 300 subst has been already tested H for oxy functionalizations and I like to represent this enzy like a SSS army knife which can unfold a Repertory a portfolio of different reactions among then you can find brominations sulfoxidations en oxidations aromatic hydroid Al hydroid epoxidation ether cleavage and this in many of the cases unwanted one electron oxidation reaction um this slight is summarizing the efforts done by my lab and other labs around the world in terms of of engineering peroxy Genesis there are two families Longos short yup I'm not going to go in details in this because it's too much but keep in mind that we are using all these methods for directed Evolution and among the prospects we are also applying very resly atomistic and philogenetic design artificial intelligence guided Evolution Etc uh and indeed you can see here are son of the directed Evolution campaigns we've done with peroxy Genesis so far we have evolved peroxy Genesis to be more selective to be more active against a nonnatural substr actually we are creating new to Nature peroxygenases to perform new to Nature chemistries um to work high temperatures or just to perform let's say the Hydrox relation the terminal Hydrox relation of ales which is a milestone in synthetic chemistry still despite of this all these advantages in terms of reaction engineering of perox genis there are some Bott legs first of all all peroxy Genesis reported so far show tiny expression levels in an host and as you have said you have seen in in my presentation to be to to engineer an enzy must be functionally expressing an host and second in some cases we have have lack of control in the selectivity so uh how to solve this of course we apply directed Evolution and even though the first peroxygen reported in 2004 was only until 2014 when the first peroxygen was functionally exess in Anu host in this case in yeast and we did this by directed Evolution we sued the Agro peroxygen a peroxygen which is coming from an edable musroom the first peroxygen is reported we subjected this Gene to H random mutation and recombination in G as you can see here we apply inod shling recombining the best mutations of of of the process and at the end of this evolutionary campaign we obtain the P mutant which was functionally expressed High titer in sakar but specifically also in pikia stories in collaboration with julan from this house uh we obtain the crystal structure of of of this of this mutant which is very interesting because it's opening a lot of possibilities to perform a structure guided Evolution you can make directed Evolution completely randomly introducing mutations here and there or you can just focus the pollution in certain regions in order to reduce the exploration of the vast protein SE space so once we have solved the problem of functional expression well take into account that this is an example about one peroxygen we have evolve for peroxygen also for functional expression but I'm not going to comment here because we don't have enough time the point is that we could go to other more challenges uh challenging approaches and among then we thought that might be interesting to test peroxygenases for the Pharma sector H specifically in the synthesis of human drug metabolites human drug metabolites as all of you know are the result of the metabolization of a pharmaceutical by our liver p450s and for the Pharma company for the development of of medicines is Paramount to have in large amounts and purities human drug metabolites in terms of performing a pharmacokinetic and pharmacodynamic the problem here is that of course to prepare this kind of human D metabolites chemically is very difficult because you need a lot of steps of protection the protection so it's a Tous process and if you try with a liver p450s is something that you can do but Li p450 are difficult lenses to work with so we thought okay could we make a universal peroxygen that behave like an artificial liver in the production of human drug metabolites and the first step in this direction was uh uh published a few years ago um For the synthesis of five hydroxy propranol the human drug metabol of propanol propanolol is this beta blocker drug which some of my students are taking to reduce the Rhythm during the presentations so um and the the challenge here was to full on the first hand we need a peroxygen that must be engineered in such a manner that hydroxy propanolol selectively radio selectively into five hydroxy propan but here we have a strong problem I said before that peroxy genasis contains or or carries two different activities the oxygen insertion in carbohydr bonds the peroxy activity but also the peroxy activity which is a reminiscent activity of its peroxidase character and indeed the problem here is that once five hydroxy Propranolol is accumulated in the reaction media is going to become substrate of the oxid activity of the en the en is going to take this product as a substrate is going to is going to take an electron from this aromatic ring producing a phenoxy radical andos which are going to polymerize non-enzymatically reducing the production of our wanted product so the challenge here was how to enhance this activity while blocking this peroxidase this unwanted activity and we did this by structure H guided Evolution uh taken advantage of the crystal structure of the para Mutan we uh Focus the directed evolution in this uh Alpha elix highlighted here in pink along with sun Loops after soking experiments and we perform directed evolution in this area by using this H strategy the morphine strategy was a strategy developed in my lab some years ago which we are currently using a still in many different projects and basically consists in the introduction of random mutations and recognation events only in a specific sections of the protein while keeping a sight of evolution the remaining part of the and this is done everything in Vivo in sacar in one pot so it's very simple and a straightforward approach uh also we combine morphine with saturation mutagenesis that all of you know saturation mutagenesis is Introduction of H the 20 naturally occuring amino acids in a given position in a combinatorial manner so after this process we obtain a mutant which we call solo variant whose catalytic activity whose catalytic efficiency was improved by two orders of magnitude and uh as we wanted to demonstrate that this enine could be scalable at Industrial Level in collaboration with my colleague Frank Holman from the Technical University of Del we couple a Cas reaction for the in ins supply of hydrogen peroxide in such a way that at the end of the process we obtain total T Numbers close to 300,000 which is are is very is very close to the industrial standards and actually this was before publication was patent and was the based of the spinoff company that we found it I'm going to show you a few slides at the end of my presentation um as we wanted to know actually how these mutations affect the behavior of insign in collaboration with Professor Victor W from the Barcelona super super competing Center he run some molecular dyamics and quantum mechanics molecular mechanics and also protein energy land Escape exporation experiments and what he found out is that these two mutations in the H Channel highlighted here in red and orange were responsible for this effect so basically what happened was that propanol was even a better substate for the enzyme while the product of the oxygenation of propanol five hydroxy propanol was not a good substrate anymore and that's why we increase notably the efficiency of the enzyme in the production of this human drug metabol and to end my lecture I would like to say a few words about sell fman is a colleague of mine with whom we are collaborating deeply in the last few years he was making the postdoctoral state with Dave Baker and as you can imagine coming from that laboratory basically means that he's a genius in in in computational approaches for protein engineering and actually possibly you know the sadles work and he has developed wonderful algorithms like Pro algorithm like f algorithm and we've applied recently the F algorithm in our peroxygenases F lip is an algorithm which basically take advantage of the evolutionary information to rule out mutations that are hardly observed in the natural diversity and also this is combined with procet atomistic calculations to eliminate the stabilizing mutations so basically the idea of f is to introduce a set of mutations in the active pocket of an enzy but when I'm saying a set I'm saying four to five mutations which is very aggressive because all of you know many of you are working with proteins when you need to do these mutations in an active pocket in most of the cases you are going to activate the enzy in this case we are not talking about introducing one or two mutations we are talking about introducing five mutations in the active Pockets at this and this is very aggressive so the very first thing you have to do when you are applying are applying F Li algorithm is to select the area in which you are going to run the algorithm in our case we were we had a clear picture about this because we wanted to just map the whole H access channel of theing so basically all these residues which are highlighted here in green were subjected to the algorithm and we obtain a family of the science with mutations from 4 to five in the H ACC channel 22 from the 25 the signs were active functionally Express and stable which is very very amazing in terms of protein engineering and what was more surprising is that some of the designs many of them show an antio Divergence which is very interesting in terms of application of peroxygenases summarizing this project uh these designs were active and stable in a range of temperature and pH displaying an anti Divergence and increasing catalytic inicien in some cases notably with a total t numbers several folds over the parental type um we try to find a reasonable explanation about the effect the pistas is between the different mutations but it's difficult to rational rationalize this whatever the case what we say at the end of of the of this project is that this constellation of multipoint active side mutations are compatible with protein folding and expression and this is because of the F algorithm which is based on Rosetta and now we are connecting this kind of experiments with directed Evolution because all these variants are wonderful departing points for far engineering byed Evolution and in my lab we are using some of these variants to evolve them towards different approaches okay uh so to conclude my lecture I would like to say that uh we've seen a wonderful uh uh Journey since the origin of directed Evolution till today where enzymes were at the beginning evolved afterwards metabolic pathways now we can see even whole mic organizations involved in the laboratory by genome safling so the limits are only imposed by our our imagination in some cases and indeed with the revolution that we are witnessing right now in terms of the introduction of new computational approaches like machine learning likea design like ancestral reconstruction we can now play a lot in engineering for different applications so directed Evolution as as I see directed evolution is definitely at the core of synthetic biology metabolic engineering and system biology and with the incorporation of all these tools we are closer to close the biotechnological rainbow which is formed by the blue green red and white biotechnologies and indeed we can travel beyond the natureal limits by directed Evolution to prepare en signs for new chemistries or to work in the natural environments to work in the degradation of plastics are much more and finally just let me tell you a few words about my little son which is well I have three son at home they are beautiful but also we have this this guy which is our company our spinoff company sign uh which uh was uh well right now we are set up in the scientific Park of Madrid we have our own offices Laboratories and we are pretty proud about about the the the how the things are going so far the company was founded in 2019 and achieved the break even point in 2020 so in the middle of the covid crisis which is a is a miracle and we were very active in terms of acceleration programs in terms of applications for European grants and of course in terms of looking for customers and well the company is based on the research I've done in my laboratory for over a couple of decades and was based on a patent on the pattern of the peroxy for human Dr metabolites from that starting point we have developed a plethora of of of of possibilities and uh basically the focus of the company is to fold on the one hand we are commercializing our own enzymes we have a small reperat of enzymes that are being commercialized mostly peroxygenases but also La cases actin Asis for the Pharma chemical and and environmental sectors so we are little by little and moving forward for the plastic degradation issue and also we developed a a directed Evolution projects for the customer so a customer comes to us and want to you know have a problem with an enine or even don't have don't have a clue about which enine to use in a process we select the enine We R the en for them and we give them the enine in a final in a final result and these are the areas where the compan is involved actually well on the one hand we have of course grants we are right now running five European projects together some of then in which for example the W project which is a Pathfinder project we are coordinating that Pathfinder project in different areas but of course we have a a nice portfolio of customers with whom we are collaborating to develop igns for their specific projects and uh that's basically all in case you want to have a reliable partner for future applications for National or International grants don't hesitate to contct Us in case you are interested and finally just to thank all the people of my laboratory and also fromo enin who are always working with high enthusiasm and motivation special thanks to Francis Arnold because without her support and and guidance over the years this couldn't be possible and all the colleagues uh along all these years that also we are collaborating closely thank you very much [Applause] thank you uh Migel congratulations also on uh work and thanks for the presentation it was amazing now um let's open the time for questions from the audience or comments uh thank you very much much uh uh Miguel for this nice presentation so I wonder how this uh the evolution of uh artificial intelligence could really modify the the perspective you have right now because right now you don't need to really have a a a Natural Evolution somehow of the proteins because you can design completely synthetic proteins without the the typical faults uh that has been preserved during this million years Evol solution so do you think do you explore right now how to prepare these kind of fully artificial enzymes considering also the evolution somehow in a different way yeah well actually this is a difficult question to answer um from my perspective we are learning how to apply machine learning Evolution to be fully honest and the idea here is actually that at the end we are just scratching uh the the the possibilities that we can achieve by protein inine my feeling is that in the the best of the cases we can improve I don't know thousand of fults the activity of an enzy but we are not achieving the global Optima so basically in the fitness landscape of evolution there are the local Optima where you could be a stack as always happens a directed Evolution problem problem or you just could go ideally to the global Optima the global Optima is the enzy with the highest Catal efficiency my feeling is that perhaps in a few years uh I have to close my laboratory because everything is going to be done computationally that's my feeling of course we have to test it experimentally but I think the the the the arise of uh machine learning is going to change everything well it's already going to it's changing everything right now if you see the chat GTP and all these kind of stories right and in protein engineering is not a is not a it's always is also happening so um yeah definitely I think we are going to engineer artificial enzy uh in a period of perhaps uh 10 years or so and completely from scratch even using computational models so and at the end they are going to be tested in the we lab of course because they must they must be tested but possibly all the screening all the hyut facilities we are using right now perhaps they are not needed anymore we'll see we'll see thank you very much um so um um like if you could make some comments in terms of structure I I have like like two questions first like how do you date a protein like how can you say when this protein appeared in evolution and the second in terms of structure what is like can you say something about ER particular fults or uh you know uh patterns of secondary structure that are more tolerant to accept mutations so that in that sense that are more like ancient no in evolution you meaning you mean the in terms of ancestral reconstruction right well how we date the the the enci is basically because at the end it's a it's it's an approximation so actually we don't there is a a a a strong discussion about this in in the scientific Community because some people believe that this an ancestral reconstruction process is working well but actually we don't truly know whether or not these enes are real ancestral enzymes they are a plausible approximation but actually we can't guarantee that they are real approximation of ancestral in my case for me doesn't really matter I don't want to to enter into the this kind of debate because uh for me what is important is that those enes whether or not they are ancestral it doesn't matter they are wonderfulest canvas for for making direct Evolution how we make the the estimation of the of the of the of the the date of ancestral is comparing the the the the the in in fear process that we have subjected with the tree of life so you can estimate that that enzyme could belong to the perian AA or to the mesos or or or to other period of of of of timeing in in in the in our planet the life in our planet and concerning the motivs which are in principle it's curiously with with ancestral because if you see the the in general terms you see the even though the structure of of an ancestral enzyme change a lot I mean the composition of amino acids changed a lot in some cases 50% of the of the enzyme is new in terms of the sequence however the overall folding is similar the overall folding is similar San R who is the spert this question possibly might be better respond by skin he says that there is a kind of a a dynamic exibility in ancestral enzymes that allow them to adapt to different conditions but I wouldn't say that this Loop here or this Alix there is responsible for the the stronger behavior of ancestral enzyme in terms of robustness what is true is that all these ancestral enzymes in general terms they are much better functionally expressed which makes sense because as I said in my presentation H primitive cell only produce a few enzymes to to to to be alive therefore the the production levels the expression levels should be higher and also H they are more robust they are more ther stable much more thermostable than other counterparts but H it's difficult if you at the end take a look at the papers about ancestral reconstruction they don't give an explanation about is because of this Loop or because of this H uh secondary no it's it's not it's not that clear so I don't know I don't know uh thank you very much for this nice nice talk uh coming back to the uh handful of enzymes that probably uh had the ancient organis the onset of life on Earth uh do you think that among these enzymes there are uh enzymes involv in in electron transfer very powerful enzymes involving these processes and I said uh and I said that because uh because it is supposed that at that time the solar radiation was very high on earth and the radiation damage provoked by this radiation on biomolecules is the generation of Ross so do you think there are uh maybe uh very powerful enzymes dealing with rust at that time possibly yes possibly yes but I I'm not fully sure I mean it's difficult to to understand that I mean at the end all these stories are wonderful because you can hypothesize about what how go our planet in in in the paman era right but I've got the feeling that yes at the end you have to keep in mind that even photosynthesis is is linked to to to electron transfer Pathways right so um uh I would say that yes but of course they could have their own mechanism to protect themselves from this generation of reactive oxygen species so um but this is something that P penologist could answer much better than me and also somehow related to this uh in those anerobic uh conditions do you have you observed any uh anerobic fingerprint in the structure of anti enzymes well my my experience with ancestral enzymes is limited we've only resurrected peroxygenases rubisco um lais and cinis so uh the rubisco was the only with which is linked to the to the production of oxygen in in in in our planet right so but we we haven't traced that this is something that we are not involved so I don't know yeah thank you many thanks for the wonderful talk um correct me if I am wrong but I think that I have read this year an article or something like that talking about rubisco and the all the effort that the community has made to create a better rubisco and the failure you know saying saying like like you know Natural Evolution has made a perfect job and and this link to the you know one thing is to creating a a new function and another thing and thinking and taking into account what you have talked about your spin-off is is you know you know that you receive the the um um the the someone comes to you to say hey I want this mzy and I want to improve this which Nature has done at you know right you know up to now so you know you know this you know Natural Evolution versus H artificial Evolution or lab Evolution and you know I have no expert on this but you know thinking about this topic on trisco what do you think you know this is more a philosophical question uh so what do you think about all you know I guess that you have a very complete overview about it what is been done in this field yeah my feeling with rubisco is a very complex s to work with so I would never start working with rubisco again now now that no one can hear me that rubis is a nightmare is a nightmare it's very difficult and actually I was in a reviewer panel of a Fed project where tobia Ser who is involved in in photosynthesis he's one of the most important leaders in in in in rubisco and in photorespiration engineering and they decide not to go through the rubisco pathway anymore because it's you know it's a it's so complex and instead they are trying to create artificial photorespiratory Pathways to solve the problem of the the Slow Grow of of of crops which is a is an nen problem in our planet right um so in terms of rubisco my feeling is that it's very difficult to to evolve the and to to enhance it catalytic efficiency which is Tiny But in that project we were not higher to enhance the catalytic efficiency of Risco we were hired by by by repol company for other issues to fix CO2 in something okay and I can tell you the results of course but it was a very complex project nevertheless in terms of our company of course people come with crazy ideas something that nature has never thought about why don't Evol financing towards a different and this is the beauty about directed Evolution that you can open new evolutionary pathways new EV evolutionary trajectories where Nature has never been before and this is something that can be done but I wouldn't trade with rubisco because rubisco was a a real uh stressful experience but um yeah it's something that uh my my feeling is that by directed Evolution you can engineer almost everything ER as long as you have tiny activity ltin activity or promiscous activity you know you can rise up and activity if is there if not is difficult it's not is difficult to create an activity from nothing is not at least by this moment is not possible hello so thank you very much for your talk I really enjoyed it um I was wondering since uh I've seen other groups that do invivo Evolution instead of xvivo the selection process and I was wondering why your approach was focused or on xvivo or if you're focusing back to invivo or do you contemplate doing those studies yeah well I mean we've done also s Evolution you mean bi biological selection systems right so yeah the point is that in biological selection systems ER the property you want to evolve must be linked to the survival of the host and that's a limitation because if you want to evolve a property that is not linked to The Host survival of the host let say an enzyme that must be stable at high concentration of organic solvent so with a new substrate this is something that you cannot explore with biological selection systems still you can do directed evolution by in biological selection system and and actually with it I haven't explained here but we've done H experiments with uh iron suful enzymes which are you know vital for for the grow of eoli so but in principle if you take a look at literature you are not going to find many examples about biological selection system because you want to Evol f for things that are useful for the humankind and and in these cases it's not possible to copel the property you want to evolve to the survival of the host thank you for the talk was very inspiring I guess the probably one of the Holy gra of of enzyme Evolution will be to have an enzyme to produce hydrogen for instance no what will be the best starting point as enzyme or family of enzymes or systems to achieve this which I guess will be many many H energy Industries after that's a good question and actually we are working in one of the projects we are involved with sorry well it doesn't matter um well uh for example um with we are working in a project which is dealing with hydrogen production and also and we are exploring different types of enzy then we are working with hydrogenesis but also uh we were involved years ago with laccases for hydrogen production so there are many different different enzymes that could be applied trying to find promiscous activities that could be boost by directed Evolution anyway hydrogen is a Hot Topic definitely so but it's very complex because at the end when you are working with hydrogen you are working with most of the cases with an airobic enzymes and that's an issue um yeah undirected evolution in anerobic in the an in the anerobic Box is is difficult because you have limitations so in those cases you could work with biological selection systems that was going to be my next question whether it's better to use an enzyme or an organism I would say an organism because technically it's very complicated to work in an aerosis in directed Evolution unless you have you are no SS that you have a chamber of 100 met square with all the things in an aerobiosis but as we are a small company thinking in my company and also thinking in the project in which we are involved right now we are trying to move towards biological selection systems yes all right great great talk thank you um so my question is you you've said throughout your talk and you repeated it a couple minutes ago that direct Evolution lets us uh explore New Paths that nature has never explored before um I guess my question then is have you ever considered that maybe some of those Evolutions actually happened and didn't Prosper for a reason um and I guess um so yeah have you ever considered that some of your projects or some of the things you're trying to do have been done before by Natural Evolution and failed of course of course or perhaps are happening now but we haven't discovered yet yeah you know because we are only talking about what we know but nature is a universe of possibilities and perhaps there are ins that are now producing hydrogen and we don't know because we haven't explor in the in the proper site for the proper place for for for these enzymes right metagenomics these kind of approaches are very interesting as well to find new genes that are you know in aggressive environments and and those gen are definitely good departing points for for for protein engineering for directed Evolution but yes perhaps nature failed and this is the the beauty about directed Evolution we are going to try uh to to to to have success where nature failed or perhaps nature never thought about that if nature can think I mean and I guess link to that question have you had examples where you tried to evolve an enzyme and actually failed later on in the process just realized that of course of course actually I'm only showing you uh 10% of my research 9 95% or so is just fails and and a mistakes so yeah of course directed evolution is not that easy but yeah we only all of us only tell the case success stories right so okay so I think that we can call it a day uh thanks uh let's thank Miguel for his great talk thank you and as usual we would like you to receive a souvenir from our Institute so you can remember this visit in the future thank you for coming very much