 Thank you very much. I'd like to thank Friedrich for allowing me to speak to you and introduce GLaD Cosmos, as well as I'll be doing the hands-on on GLaD2CAN later this afternoon. So GLaD Cosmos is a project I've been leading here in Japan with quite a group here. We've been working with Dr. Anari Matsu who was developing databases for quite a while now in Japan for GLaD Comics and GLaD Cosciences. So now we're trying to incorporate everything into GLaD Cosmos as well as GlySpace. So Friedrich already introduced GlySpace, so I don't need to talk about it. Basically the concept, the idea is that we're all sharing our data openly and it allows us to quality check the data that we share, make sure we have consistent information across these different portals and to also receive user feedback and share it among the projects and feedback to the community. So this is an overview of GLaD Cosmos. It's kind of a busy slide, but we have two sections. We have this repositories section and the data resources on the bottom. So I'll focus on the data resources mainly in this lecture. This is a kind of an overview similar kind of trying to give an idea of how GLaD CAN fits into the picture of life sciences. So we have GlyCANs in the center here, but these are synthesized by various genes, we call them glycogenes, which are translated of course into proteins. And these proteins may be lectins, actually the lectin should be over here, but they're glycoproteins. They could be glycosylated, but they can also be proteins that bind to GlyCANs. So there's two different sides of interacting with GlyCANs. And then there are also glycolibids and various diseases and pathways that we also attribute to GlyCANs. So we try to encapsulate all this information through a single portal to allow anyone to access this kind of information. So this is the Glycosmos web portal. The web page was recently released, updated on April 1st. So you go to glycosmos.org. Oh, sorry, by the way, the link, I posted a link to these slides in the doc, the live doc that's been shared to everyone. So there's a link to the PDF. Because I might be going a little bit fast, there's lots of information, but you can have a take a look at it on your own. Oh, people can't hear me. Is that a problem? Should I go continue? Yes, we can hear you very well. Thank you. Okay. So as I mentioned, we have the submission section. Currently, Gly2CAN and Glycopost are the ones that are available. And then we have these different resources that are GlyCAN related. First, I'd like to focus on the genes section. So under Glycosmos glycogenes, actually under the gene section, there's the, we have the gene section, which consists of data, various data resources related to GlyCAN related genes. So there's the Glycosmos glycogenes, which is an integrated resource. Just a second, just a second. Apparently people are hearing me, but not you. Oh, that's weird. It is weird. So wow, I don't know what's happening. I was on mute. Now I'm not anymore. Okay. Let me try again. I'm muting again. So no one can hear Kyoko? No, no. Many people can hear both of us. Yeah, because I had mute, but I'm muted again. Some people just hear me. This is weird. That's weird. Yeah. Okay. Sorry. So let's go continue. I'm muting again. Okay. Should I put my video on? I don't know if that makes any difference. I don't know if it makes a difference, but okay. So let's continue. Let's see how it goes. I'm muting now. Okay. So under the gene section, we have various different resources that have been focused on various aspects of glycan related genes. So there's two resources developed by Narimatsu under the ACGDDB portal that they've created for the Asian community. They're glycogen database and a glyco disease genes database. And then there's a fly Drosophila glycamylated genes as a model organism. And then we have extracted some data from the lipid maps database. So under this glycogen, we've actually integrated many of these resources. So the ACGDDB, DB glycogen database, fly glycodb and actually also keg. So we have the glycogen related genes in keg that is also integrated into glycosmose glycogenes. So this is the list of glycogenes that we have integrated under glycosmose glycogenes. We have sorted by gene symbol. There's the gene ID, NCB gene ID. This is from the ACGDDB database, fly glycodb, keg, and then organisms that are listed here. So this table allows users to easily search for the information that they're looking for. So for example, we can type in homo sapiens and it'll filter this whole list to focus only on homo sapiens genes, human genes. So in here we have 262 entries of human genes. If we select on a single entry, then we find the glycogen entry page which has links to lipid maps and GGDB as well as keg. So it's a simple view of this information that we've integrated. Notice here that in this contents, we only show the bright end of the maps. If you go down the screen, then we have the glycogen database entry which actually shows the glycan structures, the gly2Kan IDs, and showing that for example, this ST3-Gal5 glycosotransferase transfers this siloic acid to this glycan substrate. This is the reference, the general reaction, and then the one below here is actually been experimentally verified by AIST. And if there are multiple reactions that are possible for the same gene, then those will all be displayed in this list. There's also a link to GGDB directly so that you can find the site like this which has more detailed information. There's explanation. These are all manually curated information. So an explanation of how it works, the general reaction, orthologs in mouse and rat, the references to the substrates, expression information in which tissues they've been found to be expressed, gene ontology information, and then vector information where they actually tested or experimented on this gene. Okay, so then under a glyco disease gene database, this is also a manually curated list of glycan-related diseases. There's two types of diseases listed, congenital disorders of glycosolation and lysosomal storage diseases. So the list on glycoxmos again shows the same table where you can enter query terms for each of these different categories. But you can also go to the actual GGDB home page. There's this, sorry, there's a link here on top that will take you to the home page which shows all diseases and they can be filtered by various categories. So this is a faceted search. You can look for diseases that are found in the GGDB database and or, you know, this current database, the CDGs, lysosomal manifestations, and then the gene ontology tree. Okay, so glycoproteins is one of the largest data sets that are being incorporated by all the glycoproteins members. So these are under the protein section which contains glycosmose proteins, also glycosmose lectins, the glycoprote DB and LFDB from ACGGDDB. And this is the list of the glycoproteins, mainly from Uniprot and also linked with this database called McConDB, which I'll describe a little bit later. Again, the same table is shown, so you can search across different categories. But you can also sort by clicking on the headers. So initially it will show that this list has on top these proteins, but they have glycosylation sites, but the glycans have not been identified, and so they don't have glytucan IDs. But if you want to search for those that have glytucan IDs, just click on the header twice and it will sort in decreasing order to show you the list of proteins that have lots of glycans on them, or at least identify characterized. And if you click on cadhera N16, for example, then it will show you this glycan glycoprotein page with data from Uniprot indicating positions that have, that are glycosylated. There's the potential sequan, which is a very short motif, and three amino acid motifs, which are potential glycosylation sites for N-glycans, and then the actual glycosylation sites that have been identified. And going down the screen, we'll have this view of, from taking from the ProgVista software in Uniprot, which shows that we have information from both glycoprote DB and Uniprot identifying these sites as being glycosylated. Clicking on the site will show you the actual list of glytucan IDs that have been shown to be glycosylated, this particular site. So you'll find different compositions of glycans that have been identified. So it means that one of these kinds of compositions have been found at some point at this glycosylation site on this protein. And these are the PubMed IDs that point to the publications that reported this. Well, as you've reported, as far as Uniprot is concerned, and then glycoprote DB is the one that provides these glycan annotations. Then the glycosylactins list is a list of lectins that have been taken from Uniprot that have been annotated as lectins. So this actually is just a smaller list of Uniprot. And again, we can have the surges here, the surges across all columns. And in this case, since the lectin, there may be experiments using glycan arrays, which studied the glycans that these lectins were binding to. So if you click on McCall ID's twice, then we get to list the ID's of this McCall database, which I'll use the example later. But this indicates that this particular lectin was studied in the CFG as a glycan array, on the glycan array to find out which glycans that was found to bind to this particular lectin. There's also the Uniprot ID, PDB ID's and glycosylation sites as well. In this example, I'd like to go to this anti-H lectin, which has two glycosylation sites. And where you'll see, again, the PubMed ID's positions of glycosylation, and the fact that this is an end-linked glycan on this lectin itself. And this is the McCall DB, going down this page, you'll find these glycan array experiments and the results that were obtained from those experiments. It's kind of an alignment of the glycans that were found to bind to this lectin. And so it kind of summarizes the general pattern that the lectin could be attracted to in order to bind. So in these three different examples, these three different experiments that were taken in the Consortium for Functional Iconics, we see that this fucosylated galactose pattern across all three experiments, so indicating that this lectin recognizes this pattern. Also below we have the PDB structures for this lectin, and we have a viewer to Leitmull. I think Frederic also displayed this view of, so if you click on this, you'll get a new page for the actual protein structure and the glycan attached to it using the SNFG symbols. Okay, and then under, okay, so sorry, going back, I'm going to go back a little bit. So this information I mentioned here that identified the glycans on the proteins, these are taken from the glycoprote DB. This was part of the ACGG DB I mentioned before, the Asian Consortium for Asian Data Database, ACGG DB. So if you go to actual ACGG DB entry, actually the homepage, you can go to the search menu where there'll be a list of all the experiments that have been done using this IGOT MS experimental technique to identify glycosylation sites and glycoforms where they have reported them to make them available. So if you click on all these, all the checkboxes, including the glycoform, you'll get this table listing the genes, the protein IDs, and then the links to data that has glycoform information on them. It also describes the tissues that they found this protein to be expressed. Clicking on the glycoprote DB page, there'll be more detailed information. So the interesting part of glycoprote DB is that not only did they identify the locations of the glycans, they used lectins to determine what kind of glycans might be there. So based on lectins that are known to have a particular binding affinity to a certain glycan pattern, they could guess as to what kind of glycan might be on that site. So instead of using the very complex MS-MS, tandem MS techniques, they use lectins. As an example, as if you go down the page, if you click on this in more detail, go down the page, you'll see the actual encapsulation sites and the peptide sequence and the lectins that have been shown to bind to that sequence. So they here, for example, is 137 to 152 peptide sequence. They found many of these lectins to bind to this location. If you want to know what kind of glycans these lectins bind to, you can click on one of them on the name. For example, if you click on con A, then oops, sorry, actually RCA. This is the wrong, I put the wrong arrow. So if I click on RCA-120, this is a ricin B lectin and it's known to bind to galactose. And you know, the 3D structure and the sequence information, etc., is all there. So indicating that the glycan at this position is probably has a galactose on it. Furthermore, in the lectin frontier database, it shows all the glycans to which this lectin bound. So there's a way to sort by values. So these are all the x-axis are the different glycans that they used to test the affinity. Sorting by values, you can click on the largest peak and it'll show you the glycan that bound most strongly to this ricin. So we see all these galactoses at the end, which gives us a hint that most likely that the glycan at this position would have something like this at that site. Okay, and then going on, there's also the glycolipids page. So currently, there aren't a lot of lipid data sets for glycolipids, but you know, there's a lipid map structure database, you know, based on the consortium for lipid structures. So we currently extracted the data from there for anything glycan related. We show the classification at the top for all the lipids. And if you click on one of these classifications, it'll show you the list of lipids that are in that category. This is all we have currently. If you click on the LMID, it goes directly to the lipid maps homepage, which will show you the lipid structure and other related meta information. But our plan is to be able to link these, the glycan parts of these two gly2 can, and also with the glycogenes that are known to synthesize it, etc. So there's lots of work left to do, but this is one of the starting points that we have for the lipids. Under the glycomes, so there's three data sets that we have that try to assess and try to identify the glycomb. So one of the earlier tools that we developed was this glycomb atlas, which is extracted data from the CFG. Again, they used glycomics technologies to identify glycans in human and mouse species. And then recently, we added zebrafish. So what this tool allows you to do is to select the tissue and it'll display all the glycans that have identified in that tissue. And conversely, if you click on the glycan itself, then the other tissues that contain that glycan are highlighted in pink. So the selected tissues in yellow, and then the ones that have the selected glycans will be highlighted in pink. So it gives you an idea of the distribution of different glycans across different species. Then there's the LM glycom atlas, which we just published last year. LM stands for leptin microarray. So again, now we're trying to understand the glycom using leptins from AIST. So based on the mouse figure we had in glycom atlas, the tissues have been expanded and then we have actual tissue sections of formalin fixed paraffin emitted mouse tissue sections and images of them. And by clicking on these various sections on these tissue sections, you can see the amount of binding of different leptins in that tissue. So this will give you an indication of the different types of glycans that might be found in these different sections. What's interesting is that these different sections may have different glycan profiles indicating the variety of glycans across different areas of even the same tissue. Then there's the glycosmos pathways, which is the section of pathways, diseases, and organisms which we lump together. Under the pathways section, we have two resources. Diseases includes the glyco disease genes I've already described. Also a pathogen adherence to carbohydrate database, a pathogen database known to pathogens known to bind to glycans. And then a summary of different organisms that have been integrated in glycosmos. So I'll describe these a little bit. Under the glycosmos pathways, these are data extracted from the reactome database. So they have a very complex but very dynamic view of different pathways across lots of different species. What we did was we took the glycoproteins, we took those pathways that had glycoproteins in them and extracted them and stored them in glycosmos. So what you can do is, for example, go through a selective species, enter a keyword, and for example, you can find pathways related to diseases of signal transduction, which will give you this view where you can go down even further and find that there are pathways with diseases related to signaling of FGFR1, 2, 3, and 4. Selecting one of these pathways displays a dynamic diagram. So this is generated dynamically of the pathway that was selected. So there's a legend below, but the proteins are these round, this is a protein, this is a complex, and then simple carbohydrate or simple chemical compounds are shown, ATP, ADP. And clicking on one of these proteins will list the protein, which is a complex. So this lists all the proteins in that complex. And if there's a glycoprotein icon next to it, that means that we have a glycoprotein page to that. So then you can go from the pathway to more to the back to the glycoprotein page to find out where it might be glycosylated and then find the glycan structures on them. So in this way, we're trying to integrate all these different resources that we have. Okay, and then we have also this glycomaple tool, which is developed in collaboration with Dr. Fujita in China. So we created these drawn pathways. So we know this is kind of something manually done, these drawn pathways. What we can do is we can take expression and data, so gene expression, glycogen expression information, RNA-seq expression data, for example, and upload them. And then it'll be the expression values will be reflected in these pathway arrows. In this example, we also have data from HPA, the Human Protein Atlas. So in this particular cell type, if you select it, then it'll display where the higher, highly expressed genes are, which will give you an indication of kind of glycans you might expect to find in those different cell types, for example. So these are just snapshots of the different pathways that we have. So n-glycan processing, also heparin sulfate pathways. And this is sugar nucleotide biosynthesis. So how the sugar nucleotides are synthesized and the genes are related to those. Am I, I hope I'm not going too fast. Okay, so then we have a pathogen adherence to carbohydrate database. So this is a database that has been manually curated for information on pathogen, bacteria, fungus, toxins, and viruses that are known to adhere to carbohydrates. So this first view, again, is the black cosmos view of listening to the table of different species, the molecule that's bound, ligand names, the features of ligands, target sources, you know, the actual glycan sequence, and whether it binds or not, along with their PubMed IDs. Unfortunately, these are not linked to Gly2-canyet, but they should be. So we hope to be able to do that in the near future. But as, yeah, so in this case, you can search by species and filter down this list by different, of these different categories. So for example, I tried to search for corona. We find that there is a coronavirus entry, but the molecule that it hears to is unknown. But we find that they are glycoproteins that it binds to. The actual page on the PAKDB entry page will just, you know, show some more information about that with the PMIDs, but to find a more interesting example, you can go to the actual homepage itself where it lists 446 microorganisms, and you can filter by various categories, which are listed here. So there's diseases and species, target sources, just organisms, cells, molecules, microbial glycan binding protein, oops, sorry, natural proteins or glycans, monosaccharides and epitopes, and or different structural features of the carbide or ligands. So this is a manually, it's a little bit old, might need to be updated, but at least for many of those well-known pathogens that bind to glycans, you can find what kind of glycans that they might bind to. Well, there is a question about glycol maple. Currently, so should I go back just real quick, the file that can be uploaded takes the gene ID and an FPKM value, so it's basically not RNA-seq, but it's basically a gene ID and a number, so you can adjust the range of the numbers that you want to display on the pathway, so it can take any gene ID and a value and display that information on the pathway. Okay, and then under the glycosmos organisms, so this is a page we kind of put together based on organism information that we have accumulated in glycogenes, glycol glycan structures, glycoproteins, lectins and pathways, and so it may still need to be cleaned up a little bit, but at least it gives an overview of the type of information that we have currently accumulated in glycosmos across different organisms. So you can search, find for example, which organism has the most number of glycogenes registered with it, so if you can click on it twice, we can sort in decreasing order, and you'll find that I don't know what this organism is, but there are many organisms that have glycogen information related to it, and by clicking on the glycogen, then it will show you the list of the glycogenes that we showed earlier, but sorted or filtered according to that organism. Okay, and then so I've now quickly, maybe too quickly, but I went through all these different data sets that we have now in glycosmos, and we also have this area called standards. So these are the information about standards that we tried to implement in glycosmos, which we tried to share with the Glyspace Alliance members to make sure that we have consistent, used consistent ontologies and notations. So the ontologies that we use in glycosmos include glycol RDF, glycol COO, which is for glycol conjugates, then we, the GTDB and the GDDB, the glycol disease gene database uses GDDontal, and then the pathogen database uses pathontal. Yeah, so you can find more information about the details about these by clicking on these links, and then the notations that we use. So I kind of, I skipped over the glycans on purpose because I'll be describing it later in the afternoon in talking about glytucan, but in glytucan we use this works representation for, for carbohydrates, but admittedly the glycol, glycol CT developed by Lily von der Lief and many other people in this group use glycol CT. So glycol CT is used quite often, and so glytucan also supports glycol CT, and then the symbol, the location for glycans to describe glycans graphically. So these links provide more detailed information about these notations. And if you noticed that there's this question mark across, there's different areas of glycosmos. So this question mark by, it leads to a, leads to the glycol forum homepage here, which is known for the glycol word series of different terms in glycol biology. So in glycol forum, there's now this glycan and database series, which we've been working on this past year. So last year, this was the first, the first issue in this series was about glycanomenclature and various glycamrelated resources. So under the notations, actually click on this, it'll give you the link, you can jump to this information. There's also information, this is the whole contents of this series. We started out these nomenclature, but also then we go through a introduction to the glycosmos portal and mirage. And then all of these are introduction to the different databases in the glycosmos portal. So the glycogenes, the lectins, glycans, glyco conjugates, and pathways and diseases. And there's one more issue remaining with, they're waiting for me to write it about the future of glycol, the glycol informatics and how we imagine AI and simulations and things like that to take a place in glycol informatics. Okay, so we're back to the glycosmos portal in the main page. I want to mention that there is a search function where you can search across all these different resources. If you don't want to go to any particular resource, you can simply type in a keyword in the search. Admittedly, it's a little bit slow. So you might have to wait a minute or so to get the results. But for example, as a result of looking for a foot two, which is the name of a glycogen, we'll find 46 entries, probably across different organisms that all have foot two in them. Then the glycoprotein entries, and then pathway entries that are also divided up into the different species. So if we click on the Homo sapiens pathways for foot two, for example, it'll give you the page of the search results for searching for Homo sapiens and foot two, which includes these biosynthesis pathways and an O-like oscillation of T-sardomain containing proteins. Clicking on the ABO blood group biosynthesis pathway, then we can again show the pathway that is taken from reactome to describe how this antigen is synthesized. But we also provide a link to reactome itself, so you can go back to the original database from where this data came from. But we do, so yeah, so that's in the future plans, which will happen pretty soon actually. We also want to link to Rhea as well as Glytucan. So there are glycans that are referenced in reactome, but they don't have glytucan IDs. So we need to work on getting that implemented. And so in the submission section, I've been mentioning glytucan a lot, so I'll talk about glytucan later. But there's also glycopost, which Frederic also mentioned, which is a repository for mass spec data for both glycomics and glycoproteomics. And we are working with Unicarb DR and Unicarb DB to link and annotate these spectra that are depositing glycopost. So glycopost only takes the mass spec, the raw data. The annotations are stored as files directly, but they can be parsed in Unicarb DR and linked with glytucan to eventually be curated in Unicarb DB. So in summary, we are attempting to integrate life science databases relevant to the glycosciences. And as a member of the glycephase alliance, glycoproteins, pathways, reactions, etc., are all shared via our license requiring only attribution of the data, meaning they're all CC by 4.0. So it's all freely available, as long as you say that you've got it from Cosmos. And then more integrations will continue. There are lots more overlapping data that will be available, meaning that there's information in glygine and glycomic acid exposy, which is still going to be integrated, and they'll be overlapping with each other. But we also make sure that we have links back to the database sources so that users can find the most appropriate website and database that they're looking for. So there are lots, lots of resources, but it's often difficult to figure out which one is the best. So we hope to be able to lead users to the most appropriate resource via these integrations and sharing through the glycephase alliance. And of course, this is all dependent on feedback from the community. Without feedback, we don't know if we're doing well or not. So we have a feedback page for users to submit feedback. Things are not working or things are nice. We don't get positive feedback a lot, but we are always open to improving this resource as much as possible. Also, this Lycosmos is actually part of the Japanese Society of Carbohydrate Research, the JSCR. So it's been recognized as its official portal. And so we have this steering committee of both chemists and biologists in Lycosciences. So we try to make sure we have the accurate data and user-friendly interfaces for the whole community. And acknowledging again all the, my collaborators as well as advisors, which also includes Niki and the funding agencies for this work. Okay, and I'm happy to take questions. We have extra time for questions. Thank you.