 I'm very humbled and extremely excited to present to you the three Nobel laureates of chemistry today Jacques Deboucher, Joachim Frank and Richard Henderson because I use the technology the Nobel Prize is about basically on an everyday basis and we were pretty hyped when these guys got the prize In addition I had the great advantage to meet two of them well said before they received the Nobel Prize at conferences really great scientists wanting to bring the field forward always supporting young scientists, willing to talk to them, giving them advice it's really great. So let's see why these three received the Nobel Prize and what it is actually about. This is the title, just going to read it out developing cryo electron microscopy for the high resolution structure determination of biomolecules in solution. Alright, so what is this in English now? Taking a look at it, so the first thing describes the technology, the cryo electron microscopy I'm going to tell you what it is today and a little bit how it works and they use this technology to target life sciences and they want to look at proteins and thanks to these three guys we look in such a great detail that we can identify the amino acids, the building blocks of the proteins or even atoms. Okay, so shortly you remember this slide maybe from the talk before just repeat it in a second. So genes are important, we know that they are now a DNA in these small segments and these segments get a copy of them, it's made, it's called the RNA and this RNA can be translated into a protein. Okay, we all know that now but what are these proteins, what are they made of, why are they so important? Okay, proteins they are made out of amino acids, these are the small building blocks and depending what amino acids they are and how many these proteins can have different shapes and they can have a shape like this or a shape like this and it gets really interesting if you combine different proteins because then you can get something like a macromolecular machine that really does something. For example you can imagine this small thing to transport something from one area in the cell to another so small car or transport protein. How does this look in real life? This is an artist impression of the HIV virus, not only the coat in brown but also these cone shapes that's sticking out that is all proteins and these adapters are used to attach to cells and later infect them so it's interesting to understand how these proteins look like, how they work. This Y-shaped thing also an artist impression here, these are antibodies completely made out of proteins they help us defend against foreign invaders and if you later maybe in the break have a small snack or a beer then you will need enzymes to break down the food enzymes or proteins and I guess you get where I'm going everything is proteins almost everything and they make the cells work so if we are now a scientist independent what sort of and we want to understand how does a certain protein or macromolecular complex work either to find a cure because it's defect or we want to prevent a virus from entering the cells we have to understand the structure so how would you go about it? You first you have to extract out of a bacteria or a cell or animal cells whatever it is you're targeting you have to extract your protein that you're interested in your complex then you put it into a microscope the microscope produces us images we use powerful computers to generate a 3D structure and then why understanding how it works we can make the world a better place and that is it what it is in science all about okay so much for the rough overview in the center of it all is the microscope this is the technology aspect I'm talking about and the Nobel prize is about the cryo electron microscope cryoem cryo well because something is frozen working on the condition where something will be frozen more to this in a few slides electron because we're losing electrons to create our image well in the microscope we look at something which is very small and be magnified so why do we use electrons for this well if you use the human eye you can obviously see me you could see something which is a little bit smaller like a child you can see my hand my finger on the hair it might get already a little bit difficult so at some point you might want to have a light microscope it might have cells then even or bacteria but there are physical limitations a light microscope can only get so far and if you want to look at the real small things that make up life like the proteins DNA the amino acids or even atoms you need an electron microscope to get there okay electron microscope that's how it looks like these people are not very small the microscope is just very large as it wouldn't fit into this room colleagues from Denmark right here and these are your very friendly neighborhood scientists in front of a microscope inspection is a colleague of mine and you see is a lot of tubings wiring it's a very complicated machinery in the background and there is this big column right here and through this columns the electron come from top and if you look here's a small representation how it works the electrons come from top they will penetrate a small droplet of our sample and we will get an image and going to the first Nobel laureate here Richard Henderson 1990 he could show as a proof of concept that these electron microscopes which have been used for tons of other things before can give you an atomic resolution of a protein and that proved the technologies potential and created this big hype of life science basically moving into this technology in order to visualize proteins and understand how they work this is him professor at the MSc laboratory of molecular biology in Cambridge in the UK at the moment so okay Richard Henderson showed us how it's possible now let's do the same thing we have a protein in a small plastic tube we want to bring it into the microscope and look at it how do we go about it so in here that's just a small liquid solution we will have our proteins and actually they don't look like this it more looks like this because even at room temperature if you can't see it the nanopaticles they are freely mobile they are always tumbling and we have to somehow stop this and freeze them in order to image them otherwise all this tumbling we won't get a sharp image so they have to freeze just like when the video stops right here and so we want to get from this to a frozen state where we can image them okay then let's just put them into the freezer for an hour or then they will be frozen and everything is fine people tried that problem is ice crystals and ice crystals they will destroy these very small proteins the molecular machines and shear them apart if we freeze them and get ice crystals we won't be able to see anything because there will only be fragments left so ice crystals are bad and we had to find a way to get the proteins movement arrested in some way without creating ice crystals and this is where Jacques Dubichet comes into play and he perfected something which is called vitrification so what is this exactly because everybody who works in cryoEM does this all the time tiny drop of the sample is placed onto a copper grid just a small copper grid, 3 mm in diameter if we look at the side we will see a small liquid drop on top only 3 microliters are needed it's not much, the grid is very thin and the excess liquid blob is blotted away and then we only have a very small, very thin liquid film and this is then frozen in liquid ethane cooled by liquid nitrogen, minus 200 degrees and the sample, thanks to the liquid ethane it freezes so fast that ice crystals don't form and then you get something very special this is called vitreous ice it's basically a solid liquid sounds kind of crazy, but it's true it's basically a solid thing that isn't a crystal and has been liquid before if you freeze very fast you can achieve that Jacques de Boucher in the 1980s he perfected this and he could show that biomolecules in vitreous ice retained their natural shape great, even in the aggressive vacuum of the electron microscope and thanks to this we now finally can take an image ok, let's continue on this is him at the University of Lausanne in Switzerland also a professor so if you now want to take an image of a protein with electrons the beam are coming from the front yes, is the electron beam and you have a protein which is frozen like this then you will get an image like this but take note if the protein has been oriented differently you will get an image like this still the same protein, it's just a different view and an interesting challenge then also will be imagine you have a protein that lives long and prosper might look like this from this way but might look very similar than the open hand from this way and this is a challenge that people often face if they don't have a clean sample you have to find out what is the protein you are interested in and what is the other stuff ok, so how does this work in the microscope here we have an example of the three molecules trapped in different orientations the electron beam will come from top underneath in former times photographic film now direct electron detectors every electron can be detected they move through and create a unique shadow shadow because it's not a real shadow but contains the internal information of the molecule as well then you get these 2D images this is what an electron microscope image will look like and if you now take a closer look you can find one view is pretty similar this one here just a few examples and these are other views so this is a side view for example this is a top view of the protein we are searching for but we don't see amino acids here it looks quite fuzzy still and this is what the images look like when they are boxed out and I'm trying to tell you now we can see atoms from this you can even see the pixels there so there's a trick to get this done in the end is that you group together the same images of the same orientation like this they rotate it that they show all the same positioning and then you put them together overlay them and then you get a super sharp image and a more... yeah compared to before and of course this is just a small example the more images you use the sharper and more accurate this will get and the less noise you will have in the background and then we repeat this you remember the example with the hand with different orientations for example here you see you have quite a lot there not so much of this orientation this is why you have more noise in the background and then you can combine them computationally out of 2D you recreate the 3D structure and remember we have this special shadow so to say meaning we don't just get the outer shape we get the interior as well and then we have a complete 3D model of the protein Joachim Frank here in the middle he showed and developed the image processing method that fuzzy two-dimensional images can be analyzed and merged together and in the end reveal a sharp 3D structure okay and he is currently residing Columbia University in New York in the US also a professor this is... I rendered this just for you today from a very cool model a colleague has this is a three-dimensional structure the electron density how it comes from the microscope and if you look at this you will be like okay that's a very nice artistic sculpture you have there what is this exactly since we know the genetic code and we know by this the amino acids the protein has we can now model the amino acids inside correctly and see where do these amino acids make what interactions how does the critical functional side of a protein looks like how does the area looks like where it couples to another protein or a virus wants to adapt to get attached integrated into the cell is there maybe a mutation and something is missing because this protein is not functioning the person is ill you can find out a lot of interesting stuff if you know a high level if you can reconstruct a high level three-dimensional structure examples we heard about this one before this is the protein of the cacadine rhythm that keeps our internal clock in check solved by cryoEM the pressure sensor that hopefully makes you hear me and maybe also understand me you have in the ear which basically helps you hear the circa virus which calls a lot of problems for infants in the recent years also visualized by cryoEM with the goal to find a cure so cryoEM is to see very powerful and thanks to these three nowadays nearly every corner of the cell can be captured in atomic detail and thanks to this we can not only understand but also cure a lot of things more and we will get now very very exciting since this technology received so much attention with the Nobel Prize I want to thank of course the scientists but also the team of 15x4 for supporting this great environment and supporting me in polishing this torque I work at the LMU to be specific at genes and immunity great working environment out in Großhaden and I'm very happy to take questions from you now or in the break or you can write me and I will answer you thank you very much so funny thing this has been a little bit of a sport so people try to come from sample purification as we say to a model in 24 hours this is possible if you know what you want to reconstruct if like you say ok you want to show that this can be done really fast it can be done has been done in 24 hours a little bit more maybe if you're working with something where you don't know what it looks like or your resolution is not good enough that you can model it in the end it might take much more time to refine the structure so can be done within a few days I would say up to several weeks or months if you have a really challenging complicated project yes I am very often where you have experiments like this you also have simulation for the same things so is there a capable simulator approach for reconstructing model processes or this kind of process it's a very cool question so people of course try to predict how proteins look like but at some points especially if the proteins get too big and the complexes get too big the question are so extensive that despite the super powerful computers we have nowadays the prediction cannot replace this and of course secondary structure prediction exists which already tells you ok this area might be a little bit formed like this the other area a little bit formed like this but how the connections work and especially how the proteins then get together simulation sadly won't do it for us doesn't do it yet I like to understand the last thing you showed so you would in theory you would know how such a protein is built but you don't know how it looks like how they kind of dock to each other therefore you need the microscope ok it's a good question because maybe this was a little bit too fast in the end so the point is we know the code but this goes a little bit into the simulation question we don't know what it looks like and especially the complicated machines which have a hundred of proteins and then also RNA segments in between you might not have an idea how this looks like so you need to model all this small proteins in one after the other and in the end you can understand the machine but you need CryoEM to have something to build it in otherwise you just have the amino acid code but you don't know how it looks like it could be formed a line, it could be a circular shape you need somewhere to model it in another technology exists it's called crystallography where you crystallize a protein and then also get a structure this is another possibility question on this side when you have different proteins in the solution how do you define which view belongs to which protein and you combine them through the use to do you use it again yes so this can I want to start off with saying this is a big problem so taking a picture takes some time and let's say you can take 2,000 pictures a day and then you have on one picture 50 of your images and if you maybe get into the 10,000, 20,000, 30,000 you can reconstruct a nice 3D structure maybe you want 50,000 to get a real high resolution model depends on the size but let's stick with that suddenly only half of the proteins are of interest because you have some impurities with it or only one tenth then suddenly you have to collect for a very, very long time which might not even be physically possible in order to get what you want and what we do is we try to find views that overlap and then you have to make the critical decision which views belong together so normally you might have some idea what your protein looks like it is really difficult to differentiate especially if it is the same size is this just some let's say garbage that I copyright or is this my protein for real de novo structure where you don't have any prior knowledge a very difficult problem okay one last one so you said that it's kind of written trial to predict from the 2D to the 3D structure of the protein so let's say if there are some false positives in that how do you detect that it's a false positive? so normally you give the 2D images a 3D model to align so you have maybe some idea how your protein looks like or you have a protein where you know what it looks like couple another one to it and you don't know how it looks like so you can align the 2D images as a base if this works and you have some which don't belong there they will align randomly create so to say more noise for your model but they won't disrupt it in a meaningful way if you have too much of this your 3D model will essentially be useless or not refined to high resolution that's also something that we uncover where you have to say okay maybe my model doesn't refine good enough I have to look back at the images maybe I included too much of the stuff I don't want that prevents me from reaching the high quality I want in the end Thank you very much we will have now a break and you can ask Andrei every questions that she would like