 Mae'n gylliannych i'r Rheinfeldt southwchll i'r Lligwinsedd. It's my great pleasure to welcome you all here this evening for this Lligwinsedd Institute prosaurial inaugural lecture. I particularly like to welcome Manfredd and Ytta, Martyn's parents who have come over from Germany and are here to see him tonight. So before we begin just the usual housekeeping please. If you could please all turn your mobile phones off or to silent. The bathrooms were either across the atrium or down the corridor to the right. And if there's an emergency, the sirens and lights were flashed and sound and we all gathered outside in the sunshine. Thank you. Tonight is an inaugural lecture for a new Professor and inaugural lectures acknowledge either the appointment or promotion to the professoriate of the University of Auckland. Y profosoriad, wrth gwrs, is the highest academic rank, and as such it is worthy of noting and celebration, particularly when in an institution that's a world-class institution such as the University of Auckland. Accordemio unidol wrth gwrs yw'r Angrant institution ac yn ddefnyddio gr Bergwyr dweud a'r cerdyn nhw'n cael bod Martin yn rasio'r bwrdd ar y cerdyn nhw'n gwneud i'r gwrsio, i sait o'r agoe hyn yn ddefnyddio'r gymhwytaeth a'r gwrdd angrant nhw. Yn y hwds eraill, y gallwn ganhwys o'r cerdyn nhw yng Nghymru wedi'u cyllid yn eu cwrdd liwr i'r gwladnaeth. Mae hefyd myth i ddod oedd y dda wedi cael y honi'r dweud y ysgol hwnnw y ddylch yn bwysig i cam oherwydd ei ddweud ychydig yn y ddweud, a r anxietyd rydyn ni'n rhaid gan ei ddweud. Ysgol yr oedd wedi bod y persyn yn ddiddordeb o'r profisoriad o creu meddwl i hoffa. Pwysig i'r awdurdoddol y viad. A gwein answersonol, mae'r cofnid gyda'r 16 ddysgu a chanolion mewn ein dweud hefyd. ac y dyna'r ffordd yn Auckland, y dyna'r ddweud ac yw'r ffordd yn Auckland, ac y dyna'r ddweud yn University of Auckland. A Cambridge. Mae'r university'r Martin yn ymgyrchol, ychydig yn ymgyrchol, yn ymgyrchol, yn ddweud o'r gawr. Mae'r Martin yn ymgyrchol a'r wych yn ei ffodol i ffodol i'r graddau ac mae'r ffordd yn fwy pompol. Felly, y pwysig ymgyrchol, mae'r ymgyrchol, yn ymgyrchol, yn ymgyrchol i'r ffodol bydd y chyfnod. Maen nhw'n gweithio i'r gaeliaeth a'r PhD o'r Unedigeddiaeth. Felly, ydych chi'n gweithio, ymddangos Professor Jane Harding i'r cymdeithasol yw'r newydd Professor Maen nhw'n gweithio. Yn ymgyrch. Yn ymgyrch. Mae'n fath o'r cyfnod sy'n gweithio bod maen nhw'n gweithio i'r gaeliaeth. Felly, nid ydych chi'n gweithio. Professor Martin Kussmann was born and educated in Germany, graduating with a bachelor's degree in chemistry from the University of Arkan and a master's in analytical chemistry from, as you just heard, university constants. His doctoral research in biochemical, analytical biochemistry was undertaken there and also at the University of California, San Francisco, where he specialised in proteomics and genomics. This was surely an indication of a career to come. So having crossed the Atlantic from Germany to California, he then headed north to Sweden for his postdoctoral training in mass spectrometry and proteomics at Sundansk University in Sweden, where he also worked with Pharmacia Upjorn on protein interactions and drug development. He then, being Martin, set about acquiring a bit more research experience and seeing a bit more of the world. His subsequent roles included posts as a staff scientist in proteomics at Serviasfamma in Switzerland and a post as group leader in mass spectroscopy and robotics at Geneva Proteomics. In 2003 he joined Nestle Research Centre as a group leader in functional genomics, where he built and managed a team of 20 involved in nutrigenomics and nutrient epigenetics. I told you this was the beginning of a theme. And from there he joined Nestle Institute of Health Sciences in Lausanne in Switzerland as head of the molecular biomarkers core, which included proteomics, metabolomics, lipidomics, micronutrient analysis and the clinical applications. And while doing all this, he also acquired appointments as an honorary professor for nutritional sciences at the University of Aarhus in Denmark and a lecturer at the Ecole Polytechnique Féderal Lausanne. Both of them, amongst other things, teaching nutrigenomics. So by now, Martin's worked in at least five different countries, speaks four different languages fluently in a smattering of a few others, has acquired extensive experience in pharmaceuticals, nutrition, biotech start-ups, as well as course, all those omics. This was clearly all the perfect preparation for a new challenge. How far away could he go this time? So he came across the world as far as it was possible to take up an appointment at the University of Auckland in 2016 as the professor of systems biology in nutrition and health at the Liggins Institute and a scientific director of the High Value Nutrition National Science Challenge. Martin has authored more than 130 publications. He's in demand internationally as an author and speaker. He serves on the science advisory boards of Keystone Symposia and the Human Proteome Organization and the OMEX group. And his list of editorial boards won't surprise you if you tell you, amongst others, they are frontiers of genes and nutrition, applied and transnational genomics, the Journal of Proteomics, the OMEX Journal of Integrated Biology and the Journal of Integrated Omics, several of which I had not heard of before. In fact, if you hadn't noticed by now, he knows quite a bit about OMEX and he's also not very good at staying in one place. But he is very good at being collaborative and talking to lots of people, so much so that the first public lecture he gave here in Auckland included in the audience a couple of people who's only linked to the topic or the university was that Martin had got to chatting them in a surf shot the day before. So if any stray surfies in the audience tonight, you're most welcome. It's a great pleasure to welcome Martin here in his inaugural lecture. He's going to introduce us to his world of systems biology and OMEX and also explain to us why a science career plan does not make sense. Ladies and gentlemen, please welcome Professor Martin Cusman. There's not much left to talk about. Jane said everything. I should say Kia ora. I speak a few languages, but I have a very strong accent when I speak Maori so the rest will be in English. I am particularly honoured to wear this not only because it's the colours of the university, it's also the colours of Germany actually. And I would like to take you now through my talk which has a bit of an unusual title. Or can I do this deliver without that hat because I'm so excited and I'm already a little sweaty. So this is by no means a lack of respect but I feel a little more comfortable. So I want to take you through a talk that is entitled Science Why a Science Career Plan does in my view not make sense. And I will also take you through a sunrise of a monument valley. Some of you have seen this already so my apologies but this is dedicated to my parents because we were there in 1983 and also to my family we were there last year. So I chose this title. Let's see whether this works here. Ah, there you go. I've chosen this title because unlike some corporate thinking about human resources and I come from a more corporate world where people think you can plan your career I think that really doesn't work. I believe that especially in science your career path or your way of life is basically in my view a result of an interaction between your passion and your exposure. So basically whom you meet on your way and where you live. And this is in my view a nice analogy to gene environment interactions we are today studying where we thought and I will come to this theme as we go along that genes will explain basically your destiny in terms of health and future but it's not quite as simple as that. It's gene environment interactions and this is the reason for the title of that talk. So here we have a little outlook and I will spend a little bit of time to share with you my way of at least a professional life and then go into some aspects of genomics also the personal aspects and then this is really of course my shtig you know everything from Jane, mass spec and omics allude to the theme of systems biology and bring some examples along as we go and then also spend some time on actual work that is now being carried out in my group here at the Ligans. So my way of life looks approximately as follows. Actually I can skip that slide because you said everything. I think you said everything. You know I'm born in Germany I did my studies in Aachen in Constans it's all done. I was in San Francisco and then I joined the Vikings. Actually this I first went to Denmark and then to Sweden that was the only little thing that I could maybe add to what you said and then I went to different places in Switzerland I cannot add more national flags only cantonal flags. The cantons are the little states federal states of Switzerland and then I joined Nestlé and by that time I also got affiliated with the Danish University in Alhus and then I landed here in New Zealand. So that's my way of professional life and do you think there is a science career plan behind this? I don't think so and I will try to explain why I do not think so and why this has come this way. So I came from Switzerland to this place and this is probably drawn to scale not in terms of volume so Switzerland is a very small country but very large in terms of volume so if you flat it out it's actually much bigger than it's much bigger than New Zealand. So I joined the Elegans Institute because I think this is one of the most meaningful things to work on is early life health. It's much better to work on something to get it right in the first place to prevent disease and to maintain health than only focusing on repair of course we also must do repair and my second hat is not like this but my second hat is function is to scientifically direct the National Science Challenge a high value nutrition and that is one of 11 challenges in New Zealand here. I think it's one of the largest and this is about basic translational nutritional science and innovation in the food sector. And I would not be here if I hadn't met three wise men and I would like to thank those people in the beginning of my talk and I will thank many other people as we go along. The first guy I would like to thank is Peter Röpstof. He is a Viking, he is a sailor, he is a chain smoker and he is in perfect health and he is the father of mass spec based peptide and protein sequencing. Actually he published a paper on the nomenclature of ions that are generated when you put peptides in the mass spectrometer and you break it into pieces and this follows certain rules it's not a random process. So Peter introduced me to mass spec and protein and peptide sequencing and I found this fascinating because this was a way, I mean when these instruments came about this was a way to all of a sudden make biology much more molecular than it has been possible before. He is a professor still at the University of Southern Denmark and he hired me as a postdoc. The second person I'd like to thank is Denny Hochstrasser. He is Swiss French, which means he is Swiss but French speaking. He is the father of clinical proteomics and I worked with him for the biotech in Geneva and that was one of the first, if not the first industrial biotechnology company that was doing blood plasma proteomics for biomarker discovery in cardiovascular disease and this was a collaboration with Novartis. He is a very good skier and I was, I share the passion for sailing with Peter and the passion for skiing with Denny and he is a professor at the University of Geneva still. And the third gentleman I'd like to say is Laurent Fay. He is a Frenchman, also a very good skier and a windsurfer and we will come to that theme as we go along. I would call him the father of molecular nutrition. So I have a lot of fathers beside my own father who sits here. None of them comes as near anywhere close but I have a number of professional fathers and Laurent hired me at Nestlé as Jane said and he is now head of the infant nutrition R&D at Nestlé. So without these three guys I wouldn't be standing here. Now when you meet all these mentors it's important for you because it has an impact. The mentor always sets the example, right? Peter here shows a very positive spirit and he also was very much interested in gene environment interactions and promoting a very healthy lifestyle here. And so as we come along we will see what kind of influence that had on my further proceeding. So the theme here is genes, early nutrition and health and there are many reasons why I think we are now doing this research as we do it today. I will come to the human genome project in a minute but one of the sobering results of the human genome project was it's only 23,000 genes. That's not much more than the fruit fly and by all respect for the fly I think there is a little bit difference of complexity. These genes cannot explain human complexity and individuality. Rather it is the interaction of your genotype with the environment that makes your phenotype and this is what we are looking at today. Another key thing that brought me here is that nutrition has the most lifelong health impact and that early life influences later life. And this all comes together for a philosophy where we can maintain health and prevent disease and these were five good reasons for me to come here. Now let's spend a bit of a moment on personal genomics. This is actually an outdated paper. Now the human genome is, it is year 17 and the older one of us still remember when it was published. Bill Clinton was there and Craig Venter and the public consortium. There were basically two competing consortia. I mean basically one company and a consortium were competing and they were published at the same time. What we now would call an average human genome sequence in just a human. But there was such a milestone and there were very high expectations in terms of disease prevention at that time. And I had actually the chance to meet Craig Venter in person 11 years later when he came to Nestle. It's a pretty impressive personality and he has institutes in the US. And so there was this publication of these 23,000 gene-containing genome where, and we heard this morning that most of the genome sequence is non-coding which means most of the sequence doesn't code for any proteins. So what is all the rest about? And this publication and this milestone in science has triggered a lot of also commercial and consumer health output in the sense that companies were born that would sequence you in terms of genes and then tell you something about your health and disease risk and your prospects of how to stay healthy or not. And 23 and me, I've been in touch with them while I was with Nestle. We had the chance to discuss with them as one of those companies where you basically take a buckle swap and you can send it in and they sequence you. So you have your personal genome sequence and then they come up with a risk score across basically every kind of disease you can imagine so everything that can go wrong in your life except being hit by a meteorite maybe. So, and these risk scores are based on risk factors that are associated with individual gene variants and so basically variants of gene sequence that has been statistically associated with the risk of getting a certain disease or not. But what this does not do, so my question here is, is this really actionable? And we have discussed this this morning during the student, all day during the student day, is this pure sequence information actionable? And today we know it's not sufficient to predict the future in terms of health and disease because what this information does not consider is gene-gene interactions, not so much, at least not what 23 and me does, and gene environment interactions. So it's much more complicated than that. Now, that was one of the reasons why I got so fund of proteomics and this is just a slide to, I think that nicely illustrates in simple terms what's the difference. These two different stages of life have the same genomes but different proteomes. So it's the same sequence of genes that are, but different genes are made use of in different phases in development. And this is why we studied this. Learning from the example has always been very important so you can see here that my mentor had a very good influence. I show here the positive spirit definitely smeared off and I very readily adopted the lifestyle of the Vikings with beer and some nicotine. So this was a very positive influence. Now, the next part of my talk is now about the tools and that enables the omics sciences downstream of genomics and especially mass spectrometry and I would like to take you through some examples here. I've grown up with Pink Floyd. I think it's the greatest rock band ever. I'm very content and proud that my sons also like Pink Floyd so they have a really good taste. But Pink Floyd is not only the best rock band ever, they're also very visionary in explaining mass spectrometry but they didn't know at that time. So basically what mass spectrometry does is you have here a beam of ions, let's say peptides and then you separate them according to mass much like the prism spreads out the different wavelengths of the light spectrum. So here it's all one beam and there you can separate things by mass and even tandem mass spectrometry has been greatly envisaged here because what you can then do is you can pick one of those separate masses and sequence it down into the amino acids. So you have a stream of peptides here, pick one peptides and sequence this into the amino acids. And this is the analogy of genome sequencing. It's just much more complicated in terms of technique and it's unfortunately not as fast and simple. So now let me take you through a few examples of how proteomics came along and that makes me really feel old because if you look back what you have been working on yourself you realize the technological progress over that time. It's incredible. So proteomics in inverted commerce 1997 looked like this. I was working at the, they were still at the University of Constance and then I moved to Denmark to join Peter because we were very fond of a neural cell adhesion protein neuralin which is involved in neural regeneration in fish. So fish can regenerate certain nerves and we know that we cannot. So this has a tremendous interest in medicine. And there is a model as a fish model where you basically cut the nerve that connects the eye with the brain and there is a regeneration process that can restore this connection and fish can do that. And neuralin was involved in this process and we were interested in its primary structure because some of the function of this protein was due to glycosylation and this glycosylation was specific for certain interactions. So what this paper is about is about one protein and we sequenced the heck out of it so that basically the whole amino acid sequence and we knew where the glycosylation was. Paper done. Bwng gwrach if you want to publish this today because it's one protein. Of course you have all the information of the primary structure but still we worked on one protein and this was quite a big deal. A few years later when I worked in the biotech that was founded by Denny, we've been going into much larger scale proteomics in the sense that we took lots and lots of blood of a pooled sample from several donors in order to identify as many proteins as possible and then we would go into the individual samples of the patients we had and controls to see which biomarkers were in which sample. So there was first an identification database building phase and then there was a phase where we tried to understand who was at an elevated risk of cardiovascular disease versus a lower risk of cardiovascular disease based on these biomarkers. And then that was based on 50, 5, 0 mass spectrometers and lots of robots and we also synthesized then some of these markers and targets that we had identified by chemical means. So this is not recombinant expression of proteins in cells or bacteria, but with this chemical synthesis. So what you can basically do is you can synthesize large pieces of polypeptides and then ligate them in the order you would like to do it. And the reason why we did it chemically at the time was that the purity and the yield is much higher than an expression system. This is also when you have the tools, it's much cheaper. So this was quite a difference in terms of what you would do in terms of proteomics. And very recently when I was at Nestle and I had this fabulous team there, we were going into biomarker discovery in human plasma and this was more about not so much about how many proteins can you see, how many post-insulation modifications can you see in the academic proteomics world. The race for protein numbers is very much on but what people have I think underestimated is how difficult it is to analyze a significant number of samples in a significant, in a reasonable amount of time. So how do you deal with large-scale clinical studies because proteomics is much slower than genomics. That's for sure. So we came up with a workflow that was based on a range from biobanking to tandem aspect data analysis here. And I will cite an example of application of this workflow as we go through the presentation. So this is another, I think, dimension because proteomics now becomes more relevant for clinical research. For those of the PhD students that want to do a postdoc, be aware it's tough, physically and very tiring. So I will come to that theme as we go along but a postdoc is always a big challenge and I have myself experienced that. Now the fourth part of my talk is, I can't, of course, resist on talking about systems biology and my partner in crime and my boss in the very nutrition challenge, Joe, and Todd, who is also in the audience, is, by now means, I think, converted into systems biology too, biologists too. So systems biology, I would like to spend a few moments about to share my view about what this is and why we need it. So some of you know that slide but I think it's still a good introduction of what it really means. Biological systems have been, for many years and for most of the molecular biology research, I think, been studied in the way that we would analyze the individual parts. So you have here basically a disassembled car and this is what is called reductionist approach. So you learn about the bits and pieces about the system but you study them individually, okay? And that gives, of course, the basis of the key knowledge for more systems oriented approaches but it's still a study of individual elements. Now, again, I say this, I should change the slide in times of the diesel scandal but I come from Germany so I keep still the VW slide here. Systems have emergent properties that cannot be predicted by adding basically the properties of the individual parts. That's not possible. The sum is greater than, the whole is greater than the sum of the parts. That's the connotation of systems biology and this is actually particularly true for nutrition. So nutrition is, in my view, one of the best cases, I'm wandering around too much, right? I'm stressing the cameraman here. I can see he's, I'm very excited about what I do so I never stay in one place. It's a bit like Heisenberg, you can never tell place and time at the same moment so you have to get used to that. So the point here is that nutrition is a prime case for systems biology and we can even coin the word systems nutrition because we do not eat ingredients, we do not eat nutrients, we eat diets, okay? So it all comes together and it all interacts. So if you look at individual components at a time, it's just not good enough. So for those of you who are a little further away, for example my dad is a lawyer so he understands everything I'm talking about but maybe just a little analogy that helps those of you that are not too much into that kind of science. I think systems biology, you can look at it as a language of life where you basically have an analogy here. You have an increasing complexity so let's say we have here the basis that are the building blocks of the genes. Here we have the genes, the genome that express other ohms as we go further up in complexity and systems biology at least in the molecular terms embraces everything. And it's a little bit like when you go from letters to words to vocabulary to grammar to language. So it's a matter of at which level you want to study the system and how detailed you can study it at this complexity level. Systems biology can for example characterize the relationship between diet, microbiota and host phenotype and we are doing this here at the Liggins and also in conjunction with external partners. So this is one of those examples where you can see diet is complex in terms of composition, microbiota, these are the bacteria that colonize your body. You're actually a eukaryotic minority in a pro-karyotic ecosystem. So you're just guessed in an ecosystem of bacteria when it comes to cell numbers and there are other people in the room that know much more about this. So if you want to study the relationship between diet, this ecosystem and especially the ecosystem in the gut and what is the resulting phenotype, so phenotype is basically a collection of observable traits and characteristics of an organism. Systems biology is a good case. And now imagine you can do this at several levels. So and this is what we can call molecular phenotyping. I've been spending quite some time on the genomics part, on the proteomics part but there are other omics and everything ends up essentially in a complex picture of what makes you up as an individual in a given situation. And we have now, we live now in a situation where we can measure all these things and that hasn't been possible for a long time. So now I take you through a few examples of how this molecular phenotyping can generate useful information. In one of the pioneers of this was Michael Snyder. I'd like to cite his paper and this is the personal omics profiling paper. What Michael Snyder did is he analyzed himself over time from all different kind of angles. This is from an ethics point of view actually a very good idea because you can get it filed pretty easily because you don't have to ask all the participants. You just measure yourself. That was one of the reasons why he did it. And of course from a technology point of view and interpretation point of view it's very complex and I don't want to take you into too much detail but what he actually did is he omicked basically himself from all different kind of angles plus he did clinical monitoring over time. He was observing himself over time. And with all these techniques we have discussed before. And one of the interesting outputs of this exercise was that he could discover that there was an infectious event in his trajectory that caused a pre-diabetic state and then he could correct for this by nutritional adaptation. And retrospectively this omics signature appeared earlier than as if he had waited for this pre-diabetic state to occur with classical diagnostic means. So for example when you are transiently glucose intolerant and you make the classical test. So this was one example of this multi-angle self-observation over time where you could see okay there was a moment in time when infection caused metabolic state that is not healthy and I can correct for it for by nutritional means. My groups have also worked on this molecular phenotyping in different contexts and one example here is infant health and here we have looked at breastfeeding, breastfed infants and infants that were fed either a high or low protein formula and these infants were all born from overweight and obese mothers. And we did this with the metabolic techniques for once not with mass spectrometry but with NMR spectroscopy. That doesn't matter so much because the concept is the same. So what you see here on the slide is basically bars of different colors and they are grouped. So the different colors basically mean the different feeding regimen. So either the infants were breastfed or they received a high or low protein formula. These are the colors and the three different bars here means time points three, six, 12 months. So what you can do is in the metabolic space is you measure all these small molecules typically in urine or also in feces so you have to be minimally invasive especially when you work with infants and you measure these molecules over time and then you can ask the question what happens over time and if you integrate this information in this particular case we could for example see that the breastfed infants differed from the formula fed infants at different levels of metabolism. Carbohydr metabolism, energy metabolism, lipid metabolism and you can see here a few details where these differences were observed. For example of course breastfed infants showed milk oligosaccharides in the stool because only human breast milk has these complex oligosaccharides that can actually give rise to the growth of health beneficial bacteria in early life infant guts. So this just gives you a flavor of what you can do and this is something also what we do here at the Ligans. Another example is in the gastrointestinal health and here we looked at children that were either healthy or affected by IBD and IBD stands for inflammatory bowel disease. When children are affected by inflammatory bowel disease it's actually very problematic not only because the gut causes a lot of pain but also they don't grow well, they don't dwell, they can stand actually and they don't develop as they should. So if you do not diagnose and correct for IBD in children they simply don't develop as they should. And here we also did a metabolomics exercise so we minimally invasive took samples from urine and other sources and then what you can do is you can see where do your metabolites fall onto in terms of biochemical pathways and where do you see the most significant changes and here the take-home message is that this non-invasive urine sampling and the longitudinal design which means you looked at the same infant over time so you observed healthy children over time how they grew and the IBD affected children over time how they grow. You can identify molecular profiles that are actually linked to specific deficits that are observed in IBD affected children and then you can correct for them so you can see where the metabolism differs between the diseased and the healthy infants and you can nutritionally intervene to compensate for these. For example, observations that have to do with malabsorption of certain nutrients. IBD children have usually problems with absorbing nutrients in sufficient quantities. A further example here is about the metabolic health area and here we have studied a large cohort of overweight subjects in an European collaborative study and my now ex-colleagues are still working on these data so here we have recruited obese subjects at a certain moment in time and then they were screened and then they were put on a weight loss diet and then they were put on four different diets in order to see who is able to maintain the weight or who regains weight or who further loses weight when this weight loss diet has been completed. So you don't need omics to know that if you are on 800 kilocalories per day you lose weight. I'm glad I was not part of that study. That's not much but the interesting thing is that usually it's so difficult to keep the weight off once you have lost it and if we had analyzed these individuals in a classical fashion basically by group so you say the individuals that are on high protein, low GI, low protein, high GI and all the permutations we had four different diets then you would have said okay on average high protein and low GI is better than the other diets while that we knew before but when you look at individuals is that in each and every dietary intervention group all trajectories were present so there were successful people in all different groups and there were non-successful people in all different groups and one of the questions we had is can we predict the success? Can we say what happens here at this baseline? And yes we can to cite American president who is unfortunately a little longer in charge but that's a different story so we can say we can do this in the sense that we can tell a baseline based on a proteomic signature that we derived from human blood plasma and that was exactly the workflow I've shown you before remember the analysis of the thousand samples in a clinical study this was exactly the tools that were used to address this and so we can say here a protein signature at baseline at time zero consisting of 33 different markers can tell you who should actually use which diet in order to be successful we also have been working on cognition that is something that is maybe not so present here at the ligans but in terms of infant development definitely yes and here we developed a panel of analytes that are involved in or metabolites are involved in the one-carbon metabolism one-carbon metabolism is a key pathway in the body that provides the body with the building blocks of one-carbon units and we worked here on cognitive decline and so we had a cohort of people of elderly people that were either on declining cognitively or mentally performing consistently over time so we had different time points and here the message is that we know that high homocysteine levels and especially in CSF so this is cerebral spinal fluid that's the fluid that surrounds the brain and is also in the spinal cord that is a risk factor for cognitive decline and dementia and also this includes Alzheimer's disease and there is currently in the clinics there is a reference model being applied a reference model means it's a collection of data points that are statistically interpreted and that are used for diagnosis and this includes age so ageing is not good unfortunately years of education a beta 1-42 stands for amyloid beta peptide and that is a feature of Alzheimer's disease where this peptide is miscleaved and causes plaques and this is another protein which is erroneously phosphorylated and not the way it should be phosphorylated and if you look at this classical model the diagnostic accuracy is about 80% so we came out with two models based on either CSF derived or plasma derived metabolites of the one-carbon metabolism and because this is a molecularly speaking quite a complex panel we could tap into and we could analytically grasp we can see here that our diagnostic accuracy actually surpassed the one with the classical model now this has of course to be validated in other cohorts but this is a good example of where molecular phenotyping can be also very useful for diagnostics and if you display this in another way you can see here when you have these graphs here that basically plot the true positive rate over the false positive rate so this means sensitivity versus specificity if you have here a diagonal this is flipping a coin so this is just chance you can't tell anything and you want this area under that curve to be very very large so the larger this area is the better the predictive power and you can see here that our model performs better than the reference model and we have a subsequent paper now on going also in Alzheimer's research and therapy where we did this plasma values so also other scientists are fond of mass spec and hopefully you are now the same it is also used in forensics so this is just to underline the power of this technology am I okay with time? it's the last part it's alright? I wouldn't tell it anyway so I would now like to tell you a little bit what the group, my relatively new group here at the Liggins is doing some of you may have been listening to Sheikah's talk about human breast milk and infant health outcomes and she gave a public lecture the other day you may have heard Stephanie speaking this morning about early life serifri DNA diagnostics to grasp, to capture influences of maternal nutrition on early life health and what I would like to present here is actually a project that is funded by Hiverian nutrition by the National Science Challenge and Claire Wall is also in the room and the two of us we are running this Claire is a pediatrician and a nutritionist and I try to bring this all my stuff into the game so we are interested in weaning that is the moment or the period in life where either breastfeeding or formula feeding in infants is being phased out and the introduction of solid foods is gradually being phased in and that typically happens because it is actually a bit dependent here I think it happens around six months of age in other countries maybe later but this is what this is about and because you change food dramatically also the microbiome changes and the microbiome especially those bacteria that are residing in the gut so this graph or this illustration just summarizes a bit the influences that determine and can influence microbiome especially in intestinal microbiome so we have here birth the first year of life and then the toddler age we are also speaking about the first thousand days of life that are very important that's approximately three years so there are maternal factors postnatal factors and even later factors that influence the microbiome so there is gut microbiota from the mother there is vaginal microbiota then the birth delivery matters whether it's vaginal or caesarean that has an influence on the composition and then here we are in the weaning space where solid food is introduced and of course these bacteria live also on what we eat so they are commensals there at the table and this has a strong influence about the later life immune and metabolic health as the microbiome changes so the copyright for this title goes to Frank and Frank said why don't you call it seeding through feeding I think this is a real cool project title maybe it helped us defending it getting funded by high value nutrition so we had the question whether we can promote healthy immunity in infants around weaning by feeding immune beneficial bacteria as members of the infant gut microbiome that was the essential question we had and the classical approach would have been feed and bleed or you could say testing prebiotic candidates so it's not like we don't know anything about it we know that some prebiotic and prebiotics basically means it's a nutrient for probiotic and probiotic means is a health beneficial bacterium so these are the three names or terms you have to remember so the classical approach would be feeding and bleeding which means testing candidates but we had that would be the classical workflow here but our approach was different we said we would like to go about it with reverse genomics which means we define a health benefit we ask what part of the ecosystem in the gut could contribute to this health benefit and we ask the question on which prebiotics do these bacteria feed and where we can find these feed in the food space so it's working from the benefit and backwards rather than testing and see what happens and I think we have by now although the project is still very young a nice proof of concept and we work here together with Cospi which is a systems biology institute in Italy and Biju I don't know where he is in the room and he is driving this so what we basically did is we went to the public domain and bioinformatically searched for good food for good bugs and what does this mean well this is a sophisticated choice it's a little more sophisticated than PubMed so what Cospi has is essentially they can develop vocabularies, dictionaries and they can develop intelligent text mining full text mining tools or to retrieve information from the public domain that you could never retrieve by reading all these papers because it's just impossible to do so we went through about 37,000 PubMed microbiome publications and you can see how big this space is and this search yielded approximately 2,000 papers that were related to infant cut microbiome and immunity because this was our health benefit we were focusing on bacteria that can protect infants from infections so the outcome would be infants have less or fewer infections then we brought it down to about 50 bacterial genera which correspond to about 500 bacterial species in the human gut around that time in life and 10 of these bacterial genera and 50 of these species were specifically related to infant gut microbiome and immunity so you basically study all or retrieve all the microbiome studies that have been published and you brought it down to what matters for your research question and the nice thing about this approach is not only did we discover of course new candidates we also found things we were expected to find so this is like in analytics if you want to discover new biomarkers you better make sure that you see molecules and markers that you are expected to see so you're sensitive and specific enough so lactobacilli and bifidobacteria for example we found and then you can try to illustrate this and you know this is one of those slides where one used to say I don't want to go into detail which means you can't read it but what my point here is that we have basically wheels of interactions or connections where on the one hand we have the bacteria and if it's health beneficial we can say probiotics on the other side we have the nutrients the prebiotics and then we can zoom in and try to understand who feeds on what and for example here you can actually I think you can read it with a little bit of fantasy that the bifidobacterium longum feeds for example among many other nutrients on L runnose which is a fairly simple sugar and what you can also do is when you have these wheels of connections you can ask the question of competition a different bugs competing for the same nutrients and you can also ask the question where's cooperativity so some bacteria provide nutrients for others so this is more the ecosystem perspective so it's too simple to say well we find a bug that we can feed and the bug has a health benefit we also need to consider the ecological context and then you can ask the question where do we find the nutrients that are so attractive so again you have here the nutrients here the food sources then you can zoom in and for example you can see here that the what is it here the common walnut contains Cystus thion as a prebiotic nutrient and you can do this in many other ways so we are now going through this kind of information and this discovery approach or this in silico approach has informed the design of the complementary feed that we are now designing in a clinical trial where we feed about 50 infants with a prebiotic whole food and we came up with Kumara as a good source of some of these prebiotics we have found and so this approach can inform the design of the complementary or weaning food that we are now applying in a clinical trial to see whether we can whether we can have success in seeding the right bacteria with the right food I come to pretty much the end of the talk by just summarizing a little bit where we stand so I would just like to highlight this collaborative paper here that has tried to define some major nutrition research goals of the years to come and so just to say that I believe that with this kind of research it's more than having a few good ideas over a nice glass of Sauvignon from Marlborough Sound so I think we are pretty much spot on then because if you look at what the nutrition research community thinks is something we need to do is first of all it's identifying and mitigating the errors in nutritional science and errors in nutritional science traditionally I think have been many research reductionism and also maybe a little too little innovative clinical designs so we are very much locked into case control designs based on limited phenotyping so longitudinal studies where you are your own case and control can contribute to change that second theme that was mentioned nourishing the immune system of course you have seen examples that we are working on this human of microbiome I think there is no grant that can be written without mentioning this it is definitely something which is on top of the nutrition research agenda and then of course it's a lot about big data and it's not only storing the data and making them accessible it's interpreting these data because you can imagine that from all these different toolboxes there is an enormous set of data emerging but that doesn't necessarily mean information we have to convert it to information so I will wrap up now by sharing a few statements for the young folks in the room here I think there has never been a better time for doing science because the bottleneck has been moving from basically the laboratory to the brain I think not so long ago it was difficult to measure things and now we can actually measure many more things than our brain can digest so this means scientific brains are needed more than ever because interpretation cannot be automated I mean you can use computers of course for and algorithms and programs to visualize things you may not see but you need to interpret it a few words I would like to say for those that are still at their early career phase and I wish I was there still I think you should follow your passion you should be mobile and I think there is no such thing that science is either applied and a bit more boring but you get industry money for it or it's more sexy and more academic but it's very difficult to get funded I mean sciences I think has to be excellent and relevant and if it's excellent and relevant at the same time it's going to be picked up I think working at interfaces is always a very exciting idea I've been spending a lot of time at the public-private interface and I'm doing this here as well so high-vary nutrition has a lot of commercial spin and at the same time we do a lot of basic science here at the Liggins well that's a very these are now the human factors I think it's very important to build and maintain good relationships and also to choose good mentors if you have seen because they can have such a wonderful influence on you I hope this is my summary of about 45 minutes I think this was the most awarded banner during the March of Science in the US where a lot of people were a bit concerned about what would happen to science with the new administration I would like to thank my ex-team at Nestlé they have been most of the things I have presented still stems from that time but also of course warmly thank my new team here at the Liggins with some very recent additions and we can never be on the same photo because always somebody is not here so thank you to those wonderful people that made it possible here to start my research here at the Liggins and at HVN I would like to thank my family some of them are here in the room they have been supporting me along all this journey to come back to the central theme of my talk and still say you can still do it as a professor now you can of course say well this could be anybody but because you cannot recognize me but the author, the copyright of this video sits in the room that's Jonas who is by now the much better windsurfer but if you have doubts who that is I think he can testify that it's me thank you very much after such a long day and it was wonderful to spend this moment with you here thank you through your life technology omics systems biology but how all those things can interact together to make a difference to health and you also added in the final part that makes a really good inaugural lecture which is to be sometimes a little bit controversial and a little bit provocative by saying that why a science plan makes sense and it was provocative enough to find out exactly what he means by that at least the title is cool now when they find out about the story maybe they don't based on what we've heard tonight I think they'll be very interested indeed so thank you again very much for that wonderful lecture and it's great to have you as a member of the professor thank you thank you everyone