Scientist Stories: Patricia Severino, Cancer, stem cells, and gene expression regulation

So we have some people here who we haven't heard from or met yet yesterday. So I think if we have a short round of maybe very, very quick 10-second presentation of yourselves, like your names, where you're from, and maybe a line on what you're interested in, that would be great. I don't know how we can do this. I could pick people from what appears first in my screen, but maybe we could— okay, so the first one here in my screen is Wilson Silva.

Hi.

Hi, Wilson.

Hi.

Can I say where you're from and what you're interested in to everyone?

Yes. I'm professor at the University of São Paulo, and now I moved to Guarapuava, the city that I presented yesterday. And there we are building one core facility for single-cell genomic analysis. Now we have the basic infrastructure to do that, and we start to training people to, to analyze the data from single cell. And it's a big challenge for me because it's everything that is new, but we have the support for the, the, the government from Paraná to maybe they will launch some grants for different projects, especially now for single cell genomics. And we have, we just created one genomic network with 13 institutions from the Paraná state, and we are using the expertise from the, the researchers from the network to push some research in single-cell genomics, and we are very excited to to provide that platform, scientific platform, to help HCA Latin America to conduct some project.

Maybe we can already take note of this as a strength because we have then a new institute in the south of Brazil which is equipped, and you have a network with 13 institutions who would be willing to get together to discuss projects. And you might have a grant for single-cell analysis also. Yeah, platform. So I think this can be called a strength that we have here, right? I don't know what Christine thinks, but I think this, uh, this looks like a powerful something for us to start with. Yeah, yeah, yeah, that's, that's really great. Cool. Next here on my screen is Dr. Enrique Hernandez.

Yes, hello everyone. I'm Enrique Hernandez-Lemus. I'm a principal investigator and a program coordinator at the National Institute of Genomic Medicine in Mexico. It's one of Mexico's NIHs dedicated to genomics and its impact in healthcare. And I also run a lab, and my lab has been focused for some time on trying to dissect gene regulation patterns at the global scale networks in cancer, particularly breast cancer. And in the recent time, we have been interested in the role that the different infiltrates of immune cells within the tumors are playing in the overall gene regulation. So we are interested in studying multicellular gene regulatory networks in breast cancer.

Thank you so much. And your institute is also interested in starting to work with single-cell analysis?

Yes, we have been using 10x for some time. And we are interested in using it to start not only developing the computational and analytical skills, which is more on my side of the work, but also on perhaps establishing dedicated facilities for single cell.

I think we can also put that as a strength. That's Mexico also coming up with a already technology installed, just like Wilson was saying, and computational analysis team that also help. I think that's great. Great. Thank you very much, Dr. Enrique. Okay. Next to my screen is Daniela, Daniela Robles. Hi everyone.

So yes, I'm Daniela Robles. I'm a group leader at the National Autonomous University of Mexico, also called UNAM in its And I have never worked with single-cell data, but I would like to start using it. We've been thinking about starting for some time and we had already been talking to the Mexican distributors of 10x, for example, Genomics to start, but then the pandemic came because we did start talking about this at the beginning of the year. We study at the moment a rare type of cancer acral lentiginous melanoma. It's not been studied deeply because it's considered a rare type of melanoma in other parts of the world, but here in Mexico is the most common, as well as in other countries in Latin America, Africa, and Asia. So we have now a collaboration with the National Cancer Institute of Mexico to collect hundreds of samples from these patients and do genomics, transcriptomics, PDx models for this type of cancer and try to, yeah, try to identify therapeutic targets, drivers, and all these analyses that we can do. But we have not started with single-cell data, so I'm very excited to see if there's any way in which we can start collaborating. Also studying NAFLD and NASH, there were some talks yesterday about that, so we're also starting studies on that.

That's great. You have the cords, right? You have the patients then. We do, yeah. We already have a collaborator for you here who is Enrique Hernandez, who's also over there, and he has the machine. You have the cords, so I think that's already great.

That is true.

That is one possibility. Very good. Having the patients and the scientific question is also a very important strength, so I think that biological samples can also be considered a strength here in the group. Next on my screen is Christine Wells. She's our co-chair here in this session. Christine has a lot of experience with the HCA group, so I think she can tell us a little bit about that.

I'm Christine. I'm a stem cell biologist and a genome biologist in Melbourne, Australia. I think most of the experience I've had in consortia have been with consortia such as FANTOM, actually, which Jay Shin is also very familiar with. And the great thing about consortia like Human Cell Atlas and FANTOM, I think, is not just the capacity to participate in global science, but also the networks of scientists that you expose your trainees to, PhD students, and the capabilities that you can do as a group are much greater than the capabilities you could do on your own. So it's a really exciting time to do science and to be able to build on the networks locally as well. I'm very interested to hear what Latin America will do, how your individual countries will support you, and how we in the rest of the world can support you as well.

Thank you so much, Christine. Thank you. Next here is Jay. Jay, do you want to tell them a little bit about what you're doing there within the HC HCA context.

Yeah, um, hello everyone, I'm Jay Shin and I'm currently in weekend Japan, Yokohama. I am— I've been in HCA since the inception, so since 2016, so I kind of understand the complexity of it all, but at the same time trying to simplify it here in Asia to to motivate and kind of bring people and build communities here. So one of the things that I focus on is single-cell RNA sequencing, looking at gene regulation, and that's why I joined this breakout session. And I study a lot of stem cells, cell reprogramming mainly, and cell fate determinations. So trying to manipulate gene regulation in order to induce cell reprogramming using single-cell technologies. So with that, we do use 10x Genomics quite a bit, but we also have access to other single-cell platforms such as iCell8, which is microwell-based. You also have the Fluidigm, which we don't use anymore. We have other custom-compatible droplet systems called Nadia, and, you know, that's I'd be happy to share with you what are the advantages and disadvantages of different platforms, but 10x is somewhat of a useful tool because many other labs are using it, so it's becoming a lot easier to integrate and standardize. So it's becoming like the Illumina of single-cell technology, and that's not always a good thing either, but nevertheless you do 10x genomics. One thing that I would also vouch for is to consider multiplexing samples, and I'd be happy to discuss more about how to do this because that will significantly reduce the costs of your operation. So yesterday I talked about this AIDA project, and we multiplex PBMCs from 16 different individuals a single run. So that costs— that reduces the cost to 1/16. So I think that is going to be quite powerful and useful for a place where funding can be limited. So the starting cost is high, but if you calculate the cost per cell and per sample, it can be quite cost-effective. So that I'll stop there, but I'd be happy to kind of share some of these experiences and help in a way to be more efficient. Thanks.

Could we agree that this can also be considered a strength in the sense of having common interest with Asian HCA in reducing costs and having protocols that have already been established and validated, right? I think absolutely. Yeah, yeah.

So we have protocols that we share, protocols.io. We'll be happy to send you guys the link, how to multiplex, how much you should load, how to demultiplex, and things like that. So I'd be happy to share that.

Okay, Jay, that's really great. I think for groups which are just starting to work with the platforms, that's really important because usually we have only the very, I don't know, code protocols from the companies, right? And optimization is something that takes a long time. So I think that would be very helpful and I don't know if anyone has a comment on that. Maybe we saw that Dr. Henrique is already using this platform too, so maybe he would be interested in directly talking to about optimization. It's good. Okay, great. So here next to my screen I have Inácio. Inácio, what's the— Yes, a little bit complicated last name. Okay, so—

Hi everyone, my name is Ignacio Wijman and I'm a PhD in medical sciences here in Chile. I work at the Pontificia Universidad Católica de Chile and I just finished my PhD about a month ago. So my PhD, my doctoral thesis was based on the transcriptomic changes and changes in stem cell biology and reprogramming of gastric stem cells into gastric cancer cells. So I was looking for transcription factors that could regulate the expression of long non-coding RNAs in this process, and how these changes could actually affect the balance of long non-coding RNAs and messenger RNAs that share microRNA binding. So I only did this from bulk RNA-seq and bulk microarray data, only public databases. And we got some really interesting results. And one of the questions that Vinicius actually asked me, because he was in my thesis committee, what would I think about doing single-cell RNA-seq for the, these transformation and reprogramming of gastric stem cells into cancer cells? And I don't have any experience or funding, but I think that for people studying cancer, single-cell analysis would be really interesting to see how these cells reprogram and where the origin of cancer lies, if it's within resident stem cells or other cells that become stem-like in the process of cancer trait acquisition. And now I'm applying to a postdoctoral grant where I'm going to study also the response of T cells and exhausted T cells to neoantigens. So that would also be a really interesting field to apply single-cell transcriptomics on.

That's great. I think we have a lot of people here with interest in stem cell and cancer, so I think that's, that's very, very nice to know. And do you have over there also cohorts? You work with data analysis, right?

Yeah.

Okay, that's just public datasets, and they have some operations with Vinicius group at Universidad de Chile and also with Elmer Fernandez in Córdoba, Argentina.

Okay, okay. Also, you're already working with Vinicius? Okay, I was gonna just I see that. Okay. Well, that's great. You already have a little hub there of people, of groups that are interested in single-cell analysis.

And Carolina Uzama, who's also here. She's going to talk afterwards.

Okay. Okay.

Okay. I think that's also an interesting strength that we have a group already formed in Chile that is already actively working with the analysis of datasets. I think that looks a bit like us here, right, Wilson? Because we have a group of people already working with data analysis. We haven't really generated our sets yet, but this is moving forward fast, I think, at the understanding data analysis. Okay, great, great, Ignacio. So yeah, next coming up is Carolina Pizama. I think you are colleagues, right?

Hello everyone, first of all, congratulations for the initiative and invitation for this workshop. I am researcher, I am a doctor of science, and I am actually working as an assistant professor of the Department of Pathology in Pontificia Universidad Católica de Chile. In School of Medicine. The School of Medicine actually have a biobank of tissue and blood fluids. And I actually, I am a principal researcher of a fund that's Project of the government of Chile, focused on the use of organoid platform, has a model of tumor biology in gastrointestinal cancers, and has a platform to predict the response of chemotherapy and immunotherapy in gastrointestinal cancer. I have no experience in single cells analysis, but I would like so much can be characterized my organoids, in specific, the plasticity of the stem cell inside of the organoid. I would like so much contribute and collaborate with the organoid sample or tissue samples that are necessary to complete the research.

Thank you, Carolina. That's great. So can we also add this to our strengths that they are working with organoids, they also have a biobank, and they have this very streamlined— I think this is great. And there is also this connection with the HCA Organoid Working Group. They have a lot of information on that. So I think that is an interface that we can also explore and consider it a strength, plus the biobank, because that's really great. Thank you. Thank you so much. Next. Yeah, we'll talk more later. Everyone keep in mind what we are discussing, and afterwards we're gonna come back to this to see what challenges are for us to be working together with these groups. And how we could get research funding and maybe some small hubs within this breakout session that could already start discussing some collaborations. So take notes of what you're listening, and afterwards we are going to come back to this. Next here, my— thank you so much, Carolina. Here next to my screen is Marilene López. Hi. Hi everyone. So first of all, I'd like to thank the organization for this opportunity to share with you and discuss with you a little bit about our work. So I'm associate professor of Institute of Biomedical Sciences, University of São Paulo. And I'm very interested in understanding the biology of stem cells in different contexts, in glioblastoma stem cells and also pluripotent stem cells, we have potential candidate to modulate both biology, I mean biology of stem cells and also glioblastoma stem cells. So we work with PDX and also patient samples. We have a collaboration with a SICA Margo Cancer Center in São Paulo. So we work with patient-derived xenografts and also patient samples. We have this specific protein as a cell membrane protein, and we know that this protein is expressed different levels of this protein expressed in the glioblastoma cells. So we have this heterogeneous expression of this protein in glioblastoma. So both approaches, I mean, glioblastoma stem cells and also pluripotent stem cells are very heterogeneous. That's why I'm very interested in implementing in my laboratory the single-cell analysis to understand a little bit more about the contribution of our potential candidates and the biology of the cells. That's great. I think we already have a clear common interest with Wilson, who is also working with glioblastoma. I don't know if you're familiar with that, and he has a great center for single-cell analysis, right, that he was just describing. So I think that that can be also noted. Thank you. Next, we have here another USP colleague, right? João Paulo Fabi is in my screen here. Hello everyone, my name is João Paulo Fábio, but you can call me JP. I think it's better and it's easier. So I work with— I work at the University of São Paulo.

I am an assistant professor and I work in the nutrition and food department. So I am interested and I am working with the dietary fiber and the fermentation and the the results of the short-chain fat acids in the biogenesis of colon cancer and inhibition of colon cancer. And I work with, also with organoids, so with colon organoids. And of course, I don't have an experience with single-cell RNA. I am a colleague of Eldon Nakaya, so he said that, of course, we could join some forces to try to make some founding. So that's the reason that I am here.

Thank you so much, Jean-Paul. I remember you from some of the initiatives from last year, right? That you're interested in that, and I think this is like building on that discussion from last year. So yes, we think that we are gonna come up.

Yeah, definitely. And I am a part of CPD from FOSAPESP, from FAPES that is called FORC, that is Food Research Center. So we are trying to join all the force we could do it for it.

Thanks, everyone.

JP, I think it's a really great strength if you can bring different modalities to the analysis of single cells. So transcriptomics or DNA is one modality, but being able to look at metabolomics across, particularly in situ. Sections would be hugely interesting as well.

Yeah, we have a facility for metabolomics and proteomics, but we don't have the transcriptome one. And I am the only one that is working with RNA-seq in my, in my group. So I was trying to, to, to, to see how we could do it starting from organoids and afterwards trying to get some patients, but I don't have the cohort.

Patricia knows that, but of course we could join something and someone from biobanks too. Yeah, they have— you have the hypothesis, right? I remember you had a hypothesis and he needs the samples, but they are— yeah, that's great, great, great. Yeah, thank you. Okay, so I don't know if everybody saw in the chat that Jay Shin shared with us, linked with protocols. That's great. Thank you very much, Jay. Next on my screen is Mariana Baroni. Hi, hi, nice to see you again today. Hi, Patricia. Hi, everyone. So I am Mariana Baroni. You can also call me Mari if it's easier. I am the group leader of the bioinformatics lab in the Brazilian National Cancer Institute. I am also one of the CZI grantees. I am really interested in studying the tumor microenvironment. We are very, like, yeah, interested in the plasticity of some cells in this microenvironment, especially the myeloid-derived ones. Regarding the resources we can offer, Here in the institute, we have a sequencing facility. We also have a computational platform that can be available. We are trying to acquire single-cell RNA-seq platform. And we also have a tumor biobank here, so we can have several samples Right now they are frozen, but we can also manage to run new, I don't know, new, yeah, to get new samples, fresh ones. Mari, do you have the support from Inca? What does Inca think about this? Has this been discussed? This institute, I'm just asking her, is a very important cancer institute in Brazil. They have a lot of samples and a lot of very strong research groups. Have they been discussing this internally? Well, just in the research, but not like in the whole hospital. But I'm sure they are— they were very glad with the CZI grant, so I'm sure they will be very happy and we too, very happy to help as well. So I don't think this is going to be a problem. We were all very happy with your CZI grant. We were all very proud. Yeah, it was a very big, I don't know, like a very big, how do you say, I forgot the word, something that, anyway, we're all very happy, very, very proud of you guys for having got that increase in money. We are very glad and we are very, yeah, we are willing and to help you guys as well and also to fortify these new hubs that I'm sure it's gonna— And don't forget that now all the eyes are on you and you have to do a great job because you are gonna be the reference from Brazil working with this project.

Oh my gosh, so much pressure on me.

Yes, yes, yes. But we are very, very sure that you guys are gonna do a great job. But anyway, we're all like hoping that everything goes as good as possible. Thank you. We'll get back to you. So this is a great strength to have people from the Inca in the group because they're a big cancer center in Brazil. They have a lot of resources, a lot of samples, a lot of patients, clinical trials, right? And a lot of drug response also. Cohorts, right? So it's great. Thank you. Next here in my screen is Dr. Masako Suzuki. Hi. Hello. Hi, my name is Masako Suzuki from Albert Einstein College of Medicine in New York, the Bronx, New York, and I am interested in the prenatal environment, how that affects the help the offspring later in life. Especially the Bronx, we have so many Hispanic, Latino population in here. So that is why I'd like to join this team to see, you know, like the, actually like the Latino, the Latin American, the researcher is working how, you know, like they're working on the single cell studies. That is why I joined. Mucho gusto. That's really great. I was wondering because we didn't have many people coming from the US, right? Yeah. And now I can understand why you joined, and that's such a great idea. I think this is a great strength for us to be able to collaborate with a group from the US with a population that could be similar to the original countries from Latin America. That's Really great. I hope this is— I'm sure this will work out. Thank you. Thank you for joining us. Let me see if we have someone else that has— and yeah, Vinícius. Vinícius.

Hi, Patricia. I am Vinícius Manacaja Coutinho. I'm Brazilian, but I'm currently located in Chile. I am a group leader at the University of Chile, and also I am an associate professor of the Advanced Center for Chronic Disease, which we— which is one of the centers of excellence that we have here in Chile. This is a center that's co-hosted at the University of Chile and the Catholic University of Chile. And in this center, we follow up a cohort of 10,000 people from a particular small town in the south of Chile. And also through ACTES— ACTES is the acronym of this center— we can have access to both University of Chile and Catholic University biobanks. Also, I am permanent faculty of the PhD program on bioinformatics from the Federal University of Rio Grande do Norte in Brazil, and I am director of the, of a postgraduate course in bioinformatics and computational biology here in Chile. My research interests are related to gene regulation and also development of tools for that analysis. And now we are trying to characterize at a single cell level the different non-coding RNAs. And another field of research that we are interested in is the epitranscriptomics. And we would like to go to start to try to, how can I say, to put together, I don't know, the nanopore sequencing with with 10x Genomics in order to obtain direct RNA-seq and then perform deeper analysis in order to identify modified sites in these transcripts. Right now, we, together with other centres of excellence here in Chile, we applied for funding from the national government related to the acquisition of equipment. The results we were expecting last week, but we are not. I don't know why. I'm here with another screen updating every time because we can have a maybe a chromium here in Chile in— and the result might— I believe that we will have it today related to network.

If you do, if you do, don't forget to email us because we are all expecting that too.

Of course, of course. Currently I am a very close collaborator of Elden Nakaya and also different groups in Brazil, Argentina, and Peru. And all these groups, they are already starting or interested in performing single-cell transcriptomics or genomics integrated into their research lines. And also, just to finish, I am also connected with KABANA. That's a national— it's a network led by EBI, the European Bioinformatics Institute, with the aim of, I don't know, to improve the workforce on bioinformatics in Latin America. Together with them at the beginning of this year, we were starting to organize a hands-on workshop on single-cell data analysis. The idea was to have it here at the south of Chile, in the Chilean Patagonia, but the COVID-19 stopped us. But we are still planning to, as soon as we have this situation solved, the idea was to have this hands-on course here in Chile with people from specifically from Latin America who are doing something on the field, of course with some speakers students from abroad, from EBI and other centers.

This is it.

Thank you.

This is really great. I don't know if Jay and Christine would like to comment on this because workshop on data analysis in Chile for South American researchers, I think Wilson is probably involved with that too, right?

So I mean, I think it's one of the most straightforward things that you can do in a collaborative sense is share data and share code. I would encourage you if you're going to be sharing data to look at the data portal for the HCA, you know, making sure that you've got the metadata associated with the experiments so that the phenotype of the tissues and samples that you've collected, and also the experimental platforms that it's been run on are really well articulated. I'm not sure if the data portal are accepting the long read sequencing at the moment, but I certainly know that there is some long read RNA that's being paired with single cell data in the kind of Nanopore community. So please get in touch if you aren't able to get a hold of any of them.

I think that the organisation of the data analysis groups, we have in mind having this core group, right Wilson, that could be supporting the whole network.

Yes, I think it's a great idea, maybe the next semester in 2021, to organize one workshop, like Latin America single cell workshop with hands-on, maybe 2 or 3 days for, for lecture to training theory about the equipment, the method, protocol, and the rest of the, the, the week, or to do the hands-on in different spots like in Chile, in São Paulo, Paraná, Mexico. In the same time, we can use the public data. Maybe we can, we can discuss one, one biological question and take the data, the public data, to do the hands-on. I think it's for training people, it's very, very, very interesting. We have the experience here in some courses, it works very well.

Specifically for what Vinícius is proposing, which is data analysis, you can do it even if you're not physically together, right?

Exactly, exactly, exactly.

And we are discussing in— because the idea of having this hands-on workshop physically, it was to put together people and they stay there for a week and have all that connections. But at the current situation, I think we are discussing with people from EBI to do change it to an online course. And I believe it would be great to have you on it, Wilson. Yeah, you put together people from— the goal is the same because we started that with Cabana with this idea to put together people from Latin America and, and prioritizing people from here. 10 people.

That's where—

I think that's a pretty good point for us to already highlight as a strength, which is data analysis groups organizing themselves for data sharing and protocols and protocols for data analysis. That's really great news, Vinícius, and if you can have most of the groups involved, especially if it's going to be online, then you can really invite a lot of these South American groups to join, right? That's great. Marie also has a— I would like to say that I can also help on that. Yeah, I was going to just say that Mariana has a very good group there too. So yeah, thank you. Thank you, Mariana.

Can I encourage you to reach out to Timothy Tickle, who's with the Human Cell Atlas data portal? And I think he would be really interested in participating in something like this. The Data Portal Group are very, very keen to support easy data use across the HCA network, and they have a good team, not just not just with the husbandry of the data, but also they have data wranglers to help you get the data out in formats you want as well. So they're interested in partnering with communities to understand what it is that your— what your use cases for the data are.

Yep, you have one here today, so any questions?

Yeah, sorry, I have— I was just gonna say, Erik is here.

Yeah, I have a very unstable connection today. Sorry, that's why I have my cam turned off.

That's great.

And he was in the talk yesterday, remember, Vinicius? So he's one of the data wranglers.

That's great.

And he's a very nice person. So thank you. Yeah, so if you have any questions either about metadata or whatever, like point in the how to start a contribution or whatever, just ask me. I can help you.

Or just email the data, the Data Wrangler team at wrangler-data@—

let me check that again. I don't just use it too much. So you can send it to us in the chat. I think that's good. Yeah, I will send it.

One second. Okay, that's great.

So good to have one, one of them here today. I think that's one of the things that can— data analysis is what we can do, right, first, and it's very important to have it going before we have actually data from biology. So I think it's great what you guys are doing. Alright, so let me see. Next here in my screen is Hernandes Carvalho. Hi.

Hi, hello. I am from Campinas, São Paulo. I teach cell biology in the University of Campinas, better known as UNICAMP. And I've been working with the prostate gland, mostly using animal models, and I've been doing some ChIP-seq, RNA-seq, ATAC-seq, like, to answer specific questions, but never worked with single cells. And I believe this is a good opportunity to change gears in my lab just to go into human samples and perhaps doing single-cell analysis. I'm very enthusiastic of this approach, so I'm very excited.

That's great, great. And it's great to have somebody from UNICampi here, right? You can also stimulate your colleagues over there to join us, right? Because it's huge, right? So we're trying to reach out for these big centers in Brazil. And great, great, great to have you here. You have a lot of experience in RNA-seq, ATAC-seq, and other methodologies that you can also share with us. Thank you. Thank you so much. Next here on my screen is Gustavo. Hi, Gustavo.

Hey, hello everyone. I'm Gustavo Marantimendes. I am a professor and the vice director of the Institute of Biomedical Science, where the same as Marilene and Lucio are operating. I am somewhere in between cell biology and immunology, so I work quite a bit in the past with leukemia.

Now I'm moving to melanoma.

I'm interested in also in, from the immunology point of view, to review the macrophages dynamics and CD8 T cell differentiation, tumor microenvironment. I'm developing organoids as well, like artificial skin. Mostly with, we working with mice.

Also we have connections to different hospitals, including the Einstein Hospital where Patty works.

So I have a personal— I have never worked with single cell.

I'd like to add that to the projects, to the approach we are using in the lab.

But also as the Vice Director of the Institute, we want to be one of the reference institutes in Brazil. We already have huge facilities where from proteomics, genomics, flow cytometry, imaging, that we offer service to the whole community. Again, particularly in the city and state of São Paulo, but also people from all over the country come to us to develop some of the, their experiments.

So we would like to adapt the single cell and be one of the references in the area.

Thank you.

Thank you so much, Gustavo. Gustavo is very, very experienced in all these topics and has been working with cell biology and molecular biology for the longest time, also immunology. And the infrastructure of University of São Paulo and specifically of the Biosciences Institute is very, very useful, important, really essential to us. So thank you, Gustavo, for joining us and pointing that out. It's very important to have your institute committed to this, right? I know the facilities are great, so we will be using them.

Thank you.

Next, we have another colleague from University of São Paulo. Is Tatiana Malta. Hi everyone, so I'm currently a young investigator. I'm a grantee of one of these grants from FAPESP to help young people start their own labs. So I started my group 1 year ago at School of Pharmaceutical Sciences here in Ribeirão Preto. I have some experience in data analysis. I worked in a couple of projects in the context of the Cancer Genome Atlas, or TCGA. And my main goal right now is studying stemness in cancer. So that's part of my Young Investigator Grant. But we are in this time that we notice that we acknowledge that the single-cell data can improve our work. And we are very interested in studying the tumor microenvironment right now. Specifically in longitudinal samples from gliomas, primaries and recurrences. And we— I have a student that has been working with single-cell public data, but we realized that most of the work that has been published focused on the tumor cells, and we are kind of more interested in the non-tumor cells or the immune infiltration. So I'm interested in generating some data And I have access to tumor banks both here in Ribeirão Preto and also in the US. And I love to collaborate with people here. I noticed that they might have some interests in common. Thank you so much, Tatiana. Yeah, a lot of people here talked about nervous systems cancer. And so, yeah, yeah, I think I'm sure Plus to have a group of people from the University of São Paulo who are engaged, that's really important too. Thank you. Thank you. Yeah, also actually I also have a collaboration where we are interested in studying the inflammatory aspects of the sickle cell disease. So I also have access with people here at the blood center. And actually we are right now trying to get funding to support this this project. A biobank, okay, that's great. I think that would be good for us to talk a little bit about biobanks and sample sharing in a bit. We have, I think, two more people who haven't spoken. So I have Dalia Ramirez. Hi. Hi, everyone. Hi, Talia is also from Mexico, right? Yes.

Hello, everyone.

My name is Talia Ramirez. I am an associate researcher in Mexico. I am currently working on acute lymphoblastic leukemia, which is the main cause of death worldwide in pediatric patients due to malignant neoplasms. We perform cytomic of the patient to try to identify leukemia-initiating cells. And the accompaniment of the tumor by immune cells and how they are remodeled by the tumor microenvironment. The reason of being here is to learn about a little, a little more about the big data analysis and other approaches to address the pathology. Have you, in your, do you work with patients, right? You have patient samples? Right, okay, that's true. Bone marrow samples. Thank you, thank you so much, Dalia. And who hasn't spoken? Joaquín, right? Joaquín Gueret from Uruguay. Hi, I am from Montevideo, Uruguay, and I am in my last stages of master's degree in the genomics department And well, our group is interested in, has experience in gene regulation analysis such as transcriptomics and translatomics.

And well, as a part of my thesis, we propose to start analyzing single-cell RNA-seq data in order to analyze ribosomal proteins mRNA levels in single neurons. Part of these results were presented by Pablo yesterday.

Perhaps, yeah, right? Yes, yes.

And well, I am currently learning how to analyze correctly this data, and I'm willing to learn more and apply these things to more projects.

Great, great.

You guys have a lot of experience with gene regulation, and I talked a little bit with Pablo yesterday. He said be joining us from Uruguay. Yeah, yeah, it's great. We would, we would like really to have a person from each one of the Latin American countries in each group so we could interact and really maybe get together on something already. Thank you, thank you for being here. I have also here Mauro Castro. Mauro is also from Brazil, but from the— yeah, right, from São Paulo State. Let's see if he's here. Hi, Mauro.

Hi.

Oh, we cannot hear you.

Mauro is from Federal University of Paraná.

Ah, from Paraná. We can hear you now. Ah, no, we can hear you very, very, very low. Can you put your volume up?

Little better now?

Little, little bit. Little. Sorry, I am through the Mac. We cannot really hear you. Wilson, do you want to introduce him?

Or can you try without the microphone?

Hello, can you hear me better now? No, no, now it's some very high background noise. Let me try to turn it off and on again. Okay, but can you hear as well? You can hear us? Perfect. Okay, okay, okay. So we wait for you to join later.

Okay, continue.

Uh, I have another person here that haven't— hasn't talked. Eduardo? Eduardo?

Hello, I mean, hello, hi, it's Edro Aldo. I'm from Brazil, Universidade Federal de Santa Catarina, maybe the only one from Santa Catarina here.

For sure, yes.

Yeah, I have been working with single-cell genomics since 2015 when the datasets have only about 50 cells, and now we have this explosion in cell numbers. I did pretty much all my postdoctoral training at George Daley Lab at Harvard Medical School, and I have access to these technologies and analytical tools since they were in their early stages. So I'm very much experienced in that. Uh, I returned to Brazil like by the end of 2018. And started my lab here at the Universidade Federal de Santa Catarina by the end of 2019, like November or so. And my lab focuses mostly on developing new methods for analyzing single-cell data. I'm originally a computer scientist which migrated to biology over the years And I have experience in every stage of experimental design, sample collection, and especially develop new algorithms that can help to address new questions. And in my lab, we do a lot of methods development and also experimental work in cancer and stem cells, especially trying to learn how the immune system develops, develops from hematopoietic stem cells in the bone marrow, and then try to engineer induced pluripotent stem cells to create immune cells for cancer immunotherapy. That's one of the research lines in my lab right now. Since I started, I have been applying to several grants, international and national ones, to, to get started in some, some projects that we about to start in the lab. So basically that's it. I have a lot of experience with methods development and analysis of single-cell data in cancer, stem cells, and any other tissue that might be of interest.

It's really, really great to hear from you. I was wondering why we had missed you last year when we were doing the workshops. Because we were looking for people that had experience. But I suppose because you were not here, right? You just came back.

Yeah, I just came back. And also, I think I'm a little bit shy, so I was trying to avoid us.

Okay, too bad. Now you cannot avoid us anymore because now we know where you are.

Yeah, but actually I started last year, so I'm, I'm only now trying to build connections here in Brazil because I spent like 4 years abroad, 4 or 5 years abroad. And now I'm hopeful to connect to people here in Brazil and hopefully do some exciting science together.

As you can see, we have quite a few people who talked here who are really looking forward to building a group to work with single-cell analysis. So you're most welcome. It's great to know that you are in Santa Catarina because we hardly ever hear from Santa Catarina, right, in our I hope to change that. Exactly. Change that a little bit. Yes. You're also near Wilson and his institute in Paraná. So that's also great. I really hope you guys are going to get connected and start working together. Yeah.

Awesome. Sounds great. That's nice to meet you, Wilson.

Yeah. That was a very great surprise to meet you here today. Thank you.

Let's talk about that. I appreciate that.

And the IPS models of blood development are really fascinating, I think, and there's some interesting parallels coming out from a few people speaking about the role of the immune system and inflammatory cells in different tumor microenvironments, and I think being able to model that from pluripotent stem cell is really powerful because you've got opportunities of adding some of the lineage tracing tools and some of the reporter tools to look at immune tumor interactions that are hard to introduce to the primary cells. So that's really exciting technology.

That's great. Eduardo, are you setting up also the wet lab research or data analysis? Are you gonna do—

Yes, my hope is that my lab is gonna do both the wet lab and the dry lab research. And I have been applying for grants to fund the dry lab aspects of the work because working with pluripotent stem cells is quite expensive. And here at Universidade Federal de Santa Catarina, I don't know anybody who actually does that. So I have connections with Lígia Pereira. She is in another session, and she's providing me some very valuable feedback to set up a pluripotent stem cell lab here in the South. And Let's see how it goes. But most of the work that we are doing in the lab right now, it's the dry lab stuff regarding novel development of new algorithms and reanalyzing data to generate hypotheses for when the money comes from the wet lab stuff. We have everything in place to get started on that.

That's great. That's great to hear. Meanwhile, if you can join with people who are getting together for data analysis, that's going to be just fantastic. Okay. We have one more person who recently joined us here, Catherine. Hello, everybody. I'm talking with you from France. I work in a commercial platform. Focused on NGS. And we are recently—

I'm in charge of making the validation for CE marking software for data analysis in cancer.

And we are trying to develop for our customers new NGS techniques from wet lab to dry lab and data interpretation in a regulated context. So for delivering for delivery of clinical results. And I have a great interest in knowing what's going on in single cell and generally interpretation of microenvironment in cancer biology. I think it— I think that if you can help us use different technologies or complementary technologies, I think that would be really great to have you around, so feel free to give your opinion. My pleasure. Yes, please share that with us. I think that with Catherine we have heard from anyone. Is there anyone there that hasn't been contacted?

I think I managed to come back again.

Maude is back, okay.

Okay, thank you. Sorry for my internet connection. I hope the connection is better now.

Can you hear me?

Okay. Yeah. So first of all, I would like to congratulate the, the, the initiative to bring this, this meeting to Latin America. It's great. Yeah. And, and for us that are really keen on data analysis, this is even more great. My name is Mauro Castro, I am professor at the UFPR University of Paraná, and I am a group leader in the area of bioinformatics. I coordinate a brand new PhD course that should start next month, to, to contribute with human resources in the area, which I think is great for our state here. This is the first PhD course in the, in the south of Brazil dedicated to bioinformatics, and we are very enthusiastic in terms of community to bring people together and to dedicate efforts to assess high-quality and high-standard data, datasets produced by consortia. We have close collaborations with several groups here in Brazil and the United States, in Canada, in UK, in Holland. And so we personally, my group is dedicated to develop new methods in the area of data analysis, focusing on cancer research. One of the key aspects of my group is to try to find master regulators in cancer, master regulators and modulators in cancer, using what we call global coherent datasets. For example, when you, for the same set of samples, you have genome epigenome, transcriptomes, ATAC-seq data, methylation data, and to integrate all these multiple levels of information for the same set of samples, which is really challenging, not just for us but for all the collaborators that I have the experience to work with. Single-cell analysis bring another level of complexity turn lives much more interesting but much more challenging.

Have you tried that yet?

We have some methods that we are trying to migrate from bulk tissue to single cell, but they are not yet available for community. We have some collaboration with Penn State University in the United States. And with some very, very early initiatives to try to transform some of our methods to query master regulators in single-cell datasets. But as I said, this is very immature, very early, but we are very enthusiastic in doing this. This, this bridge between both tissue and single cell.

That's really great to have you also from Paraná. I think that if we think about Brazil, Brazil incorporates many different countries because we're so big. So it's great to have people with contacts in the north and in the center and in the south. Thank you, thank you so much for joining us. I think we got to hear everybody and we have a very good idea of what we have within this break session group to discuss some specific points of what we want to bring to the rest of the, of the, of the group, to the big group. When we think about how we could best collaborate with Human Cell Atlas, we have some shared interests here, but it's a group that is working with cancer and stem cells in this context. Any opinions about our specific strengths on that? I heard about some rare kind of cancer that hasn't been studied and organoid models too.

Yes, so I could start. Indeed, we are— we think this is a strength of maybe something we could study. Actually, I've been talking to Mari, who's also here, and Patricia, who's also asked to be in this meeting, but she was put in the inherited diseases one. But we've been talking about this for some time now, and I think, or we think, it's a good thing that we could let's say, direct from, from this area of the world, also with Asian countries because it's also a very important disease over there. So we, yeah, we've been collecting samples from Brazilian patients and Mexican patients and doing many different studies. We think this is a strength because we have been able to also get funding internationally from Wellcome Trust, from Medical Research Council, also nationally, because it's actually not very well studied, this disease. And I am not aware of any, for example, transcriptomic datasets, even bulk, that have been published from this. So I would think it's a good— at least one of the things we could suggest could be focused on that. And I know there's also interest from other people in this. And also, I've been writing with everyone as as my, my job as secretary here, what everyone has been saying. And I also heard another researcher— I'm looking here through my notes— that also mentioned melanoma, Gustavo. All right, so could also be interesting for him as well.

And also Mari from INCA that could look into this specific cancer type. Groups that are more rare and possibly more common in Brazil and Mexico, and they could be also assessed, right? If you think about that and the biobanks that I wanted to get back to, because we have quite a few groups here that mentioned they have biological samples. Before we talk about that, just to wrap up, that one big strength that we saw in this group is that we have a lot of people engaged in data analysis. So I think that for data analysis, we have a lot of already consistency in what's been done. Different groups, they share a lot in common about how they want to proceed with that. So that we can already say that's a great strength that we have already been established, right? And considering then the biology, we may consider that we have rare samples, so samples from rare cancer types, for example, that could be studied in different ways and that would be more typical or found in Brazil or Mexico, for example. And if we don't think about the other— about the specific cancer types, we also have a lot of resources considering biobanks in general, right? We have a lot of samples that should include a lot of genetic diversity. What do you think about that?

Maybe I just want to comment that biobanks are great, and I think Orit from MIT mentioned this yesterday at the Technology Standard Working Group is you can use nuclear sequencing, single nuclear sequencing, and that really allows you to extract the nucleus and profile the gene expression without dissociation. So as long as the tissues are well preserved, you should be able to do single nuclear sequencing. And although I think you do have to be aware that there are discrepancies between between dissociated approach and the nuclear approach. I think she already also mentioned, for instance, that immune infiltrated immune cells will be very different. So if you're studying T cells, for instance, I think one of the members here was interested in that, you might need to just keep aware of that. So yeah, I think this is a very good strength that you guys have a bioinformatics biobanks that can already be accessible for single-cell sequencing.

Jay?

Yes, Masako? Yeah, so Jay, you said there are some like the important part for like having a biobank is how you store the samples, right? Does the human cell address group provide how should we store the specimens from the— after we, we collected the samples? I think that will be a very good information for like everybody who will start collecting the samples.

Yes, so, so there are general approaches are kind of the snap-free— snap frozen. So if you're taking resection or biopsies. I think the most standard way is snap freezing. But once you do that, you are committing yourself to do nuclear extraction, right, because it is nearly impossible to dissociate cells once they are frozen. So that's why I think, you know, biobanks that already have been collected, you may have to resort to nuclear sequencing. However, if you do plan to do whole cells, I believe there are various protocols out there to encourage people to dissociate first and then freeze down, and that preserves the quality of the RNA. And there are various protocols depending on the tissue and the cancer type that you would need to implement and test and verify and QC. And HCA does provide that either at protocols.io or from Orit's presentation. The Standardization Working Group also provides some recommendations. So I don't know if that answered your question.

Yeah, I think that that's great because that we do have biobanks, quite a few in the country, and some of them are very populated with completely different population characteristics. I think this is great, but many of them are also collecting prospectively. So it's very good to have this information about how we could move from now on if we want to include single-cell analysis. Yeah, that's really great.

So there's There's spatial technologies that are on the horizon as well. So if you have biobank samples, you can already do spatial transcriptomics as long as the RNA is good quality.

I think it's also important to remember that a lot of these methods are still under development, and there isn't a perfect way to isolate all of the cells from any one tissue that's universal across all tissues.

Issues.

So you really will want to draw on your own expertise of working with, with that particular tissue type to get the best out of it. And if you're interested in the immune cell components, then particularly the myeloid cells, the granulocytes, are very hard to isolate using dissociation techniques. You may be better off with the snap frozen if you want to capture that immune component.

That's also great to know. Okay. I don't know how it works for other countries. We have Mexico, Uruguay, and Chile here, and also the US. In Brazil, we have ethical committees that regulate the use of samples. And it's often complicated for us to ship samples to be analyzed abroad unless there is a very clear need for that to be done. Does anyone want to comment on that? Does anyone have experience with this kind of work? Or we could also discuss that each country can manipulate their own samples and share data?

Yeah, I can say, or I don't know if someone else wants to speak.

You can speak.

Okay, we have sent samples indeed to the Sanger Institute to be— we have sent paraffin blocks and DNA just like that, and it wasn't, it wasn't difficult to send from Mexico, we hired this UPS company called Marken, and they handled everything. Basically, they told us, don't worry, we see this with the authorities, and they just came and collected the box and took it, and in 2 days it was there. We sent samples to Brazil to Patricia Pozic at INCAA, who's working with Mari, and those were frozen samples, and they also reached there in under 2 days with the same company. So it seems that at least for us, sending samples outside is not a problem. People say that importing them back is a problem, so we haven't done that yet.

But for us, here's the opposite. We have no problems receiving them, but if we ship them, it's, it's very complicated. Uh, it's the opposite.

I, I would have thought that should be the case in a way, because you're sending samples outside, you know, is your resource But it doesn't seem, at least in my experience so far, it doesn't seem to be the case. It's been easy, at least to Brazil and to the UK, to send samples. We don't know how easy it is to receive them.

But the reason I'm bringing this up is because I think it's always feasible, and each country is going to have their own regulations, right? So it can be more or less difficult. So I think that is okay. But the reason I'm bringing this up is because we seem to have a path to go before we can really process samples over here. And there is the funding issue. So if we can get funding from partners abroad to run, for example, wet lab experiments, and we could do data analysis or part of the analysis being done abroad, like spatial analysis, for example, where we're going to be sending up slides or nuclear sequencing if we have frozen samples, that could be an alternative. Does anyone want to talk about that? If for example we would like to send it to— I don't know if Edmond is here.

Yeah, I think he has his hand up. Yeah. I think I just might have a comment because since we are about to set up this from scratch here, maybe it might be important to think about technologies that we can collect the data right on the bedside, let's say like that, because 10x is great, but you have to have the equipment and move that around, which I don't think it's a good idea. And for really precious primary samples, frozen them down and then shipping them abroad. I don't think that's going to produce really good quality data. At least when I was in Boston and I used to generate data in the Harvard Single Cell Core Facility, they were very explicit about us giving them high-quality viable cells. So the data is not going to be good. At least with the in-drop-seq type of technology. I don't know how robust this becomes the last year or so because there's been 2 years that I don't generate any new data using any of the single-cell technologies. But as far as I can tell, primary samples, they, they are gonna be precious, especially for rare tumors. And we should also think about a way to collect the samples on the, on the site of collection. And for that, I used, for example, Sequel from Alex Scheelek lab. I actually used that in there. A postdoc in his lab came by to our lab and prepared the samples with us. Yeah, I think it's a good technology for these more precious samples.

Yeah, yeah, Sequel has to be established in the lab too, so it's possible. Of course, we could have a collaboration to do that.

But—

and I think everybody agrees with that— if we're talking about live cells and for transcriptomics of live cells, you are completely correct. We are here considering besides that to have collaborators that could sequence your libraries or that they could do spatial biology in slides. Or single nucleus sequencing on frozen tissue. But you're completely right. It's very important for us to keep in mind that if we want to sequence live cells, it's going to have to be on site, or somebody can sequence your libraries later on. Yeah.

Yeah. Just keep in mind as we are about to design this. Sorry.

Yeah.

I saw Mari had her hand up as well.

Mari? Yeah, I did, but actually you made the points I would like to make as well. But just to let you know, guys, that we are trying to acquire the 10x equipment, and so it would be easier to manage the library's preparation and so on. So we can— I think we're gonna— yeah, I think we already have Wilson with one machine in São Paulo, UCLA has one, there is another one in Ribeirão Preto, I guess. So we need many ones because we cannot be also walking around with the cells. So it's great to know, great to know that you're gonna have one. Okay, anyone else needs to comment on this?

It's not directly related to this, but now that you're talking about reagents and all of that, I don't think this is highlighted mentioned enough in the HCA talks. Actually, when you are registered with the HCA, you get some discounts. I have just posted something. It's not too well formatted, sorry. You get some discounts in 10x Genomics, in BioLegend, NanoString, and Takara Bio. And registering is free. I don't know the specifics about those discounts, so sorry about that.

But you can email them and ask them about it. That's great, that's great to know. Yeah, I don't think everybody here was aware of it, but yes.

I think, yeah, for setting it up, I think it's actually pretty important. And yeah, it's not too highlighted.

I didn't know about this. It's really great to talk about that. Yes, it's true. I mean, everything that we can like cut costs on, it's it's really important. This could bring us to financial resources. We have seen here that quite a few groups have infrastructure to help out and could do part of the, of the work, right? But there is having access to funding for the experiments themselves. Does anyone want to comment about that? Ideas on how we could fund groups to collaborate?

I'd like to talk a little bit about that. Of course, today, the current situation, I believe, in all Latin America is a little bit hard for funding. I believe all countries are dealing with the same issue. But of course, we can, once, at least for the, once we have a the funding for at least to generate an experiment, and you need to have, I don't know, money for that analysis. There are some, some several initiatives that I, when I was in Brazil, I never heard about, but I, here in Chile, I have seen. There are several fellowships that you can send students abroad along South America and Latin America. I, for example, last year a student was for 6 months in Córdoba, Argentina, with Elmer Fernández. And this is a very interesting way on how to send some student to, to have funding to send some student to, to other groups to establish the collaboration, also for the training of these students. And also there are some fellowships, some grants for— they are not for to fund your research, but at least to fund a collaborative initiative. CyTED, there are several that every year we have these grants available, and I believe we should do something with that related specifically to single cell and in Latin America. I believe this is something that we need to explore more.

That's a great point. We don't always have access to all that is available, and we tend to be looking always at the same agencies. That's very good. I think that if we can have a small group sharing these possibilities, it's great. And for sharing, for the transfer, transference of students, I mean, yeah, for training, that's what we need. Thank you. Yeah, let's put— let's take note of that. Daniela? Yeah.

Yes, I'd like to share there as well. Of course, I, as I did say, I do not have experience with single cell, sequencing yet, but I have seen that there's several international consortia or foundations that do award fellowships and grants to Latin American countries. For example, the Wellcome Trust has very good fellowships that will fund for example, a mid-career researcher in Latin America for— do your experiments. You don't really have to justify a lot what you have to— what you want to do. Just have a, you know, a research plan and you can use it as you see fit. That's a very good option. The Medical Research Council in the UK, if you have a partner in the UK, they will send a good, you know, good money and a part of a good grant to Latin America. And the Newton Fund, the Newton Fund does a lot of funding also. In the last round was for Brazil. I think they have a country or two or three countries that they choose somehow every round, and the last one, as I remember, was for Brazil. So those ones are also very good options. That's for training indeed with a partner in the UK that that, you know, if you have someone that you collaborate with, then they fund all the travel, all the conferences, uh, for them to give and teach, and you can go work, and that kind of thing.

So yeah, could we consider then that funding, even though for us it would be a challenge, we do have opportunities that are unexplored, and those opportunities could be considered strengths, like in 2 minutes, we listed a lot of things that maybe are not within our radar, so we could propose to have a small group of us that are going to be monitoring and sharing this within Latin American interested groups.

Yes, yes, yes.

There are some considerations related to the funding from, from UK. For example, they welcome trust funding. Chile and Uruguay, they cannot have access to that. Because they are a high-income country. Yeah, for example, we are not part of, officially part of Cabana, but we are unofficially part of Cabana.

But if we are all collaborating and someone gets the grant, then it would be okay, right? So I think the important thing is to be in touch so we can know about the opportunities.

And something really nice is that Chile started to be part of embu as a foreigner country and can apply to some funding from embu directly. For example, for the course that we are discussing with EBI, we— it would be an embu workshop.

That's, that's really great. That's really great. So let's put it that we would like to have this little committee group of people that are going to be monitoring and sharing between the groups that later on decide to really be part of this and communicating so we can all have access maybe to, to this. Okay, and it's great to know that Chile is doing so well.

So can I comment about the—

Yes, yes, sure.

So equity and equity working group was presented yesterday, and I think this is one of the major missions of the Human Cell Atlas and to ensure that the data is actually generated by the sample providers themselves and that it's not shipped across to Boston or to UK, but it is actually building grassroots research groups that are able to generate their own dataset and deposit into the Human Cell Atlas. So there is a strong motivation, and I believe CZI and other funders who are— who have been supporting HTA are also on board with that mission. So what I mean by that is if there's a push to create such programs where you train the people and provide the pipelines of the network As long as you are providing value to an HCA database, that will have a good— I guess an opportunity to apply for funding with CCI. I guess CCI usually is kind of— HCA is a healthy reference. So we talked about cancer previously, and it may be difficult just to say we will profile cancer samples. So you will need to consider how to balance the healthy aspect and the disease aspect when you're applying with CTI. But nevertheless, the motivations to make the data set more equitable is high priority for us.

But you know, one strategy might be to actually invite those funders to come to your planning meeting. Ask them to sit in and see where the priorities are for you and help them set the right scheme for you. And I think that you will find that the CZI— funders like the CZI, Welcome, Gates, and so on— will come and spend time talking to you about what your needs are.

I think that's a great idea for one of the ways to go. I think that's a very good idea. Get the funders together and see how they would like to see this going, and we would share with them what we have and what we're thinking and hear from them.

Yeah, I mean, I think it's important that you're helping them set their funding agenda. If this is going to be truly equitable access to these and equitable about capability building.

I think that's a great idea.

I also want to mention NIH has many funds that invites foreign collaborations or even foreign researchers can apply directly. So there's one that I'm—

That's getting tougher, Jerry.

It's getting tougher.

It's very tough.

But maybe finding a partner like Masako.

Yes, Masako.

And co-apply, right?

Yeah.

I'm more than happy to. Actually, Albert Einstein has the 10x machine, and then we have the sequencer as well. And then like we are also partner with the New York Genome Center. So like the New York Genome Center has like a lot of like the technical development as well. So like if you like the starting collaboration is a good thing to like the— for like the making like a good network group. And then I'm very interesting to work on the Hispanic/Latino population. In here as well as the, the country. I should not say, but the original, but the original country as well. That's a great idea. I think that is a great idea. Well, we're coming to the end of our, uh, together genetics. Yes, Jay, please.

Oh no, no, go ahead, I'm done.

No, no, well, yeah, no, it's just that we have some time and I would like to know if we— there is some something else that everybody has the urge to talk about? We have some minutes still, so it would be good if we would like to discuss anything else.

OK, well, I was going to mention genetic diversity being one of the importance. And so as I mentioned in my presentation yesterday, even Asians are underrepresented significantly and makes the clinical use very limiting. So yeah, I think there are fundings as well that really encouraging more data production from underrepresented regions. So I think starting with genotyping and doing some single-cell PBMCs, it's not a very sexy disease per se, but I think it really helps to learn the ropes, trying to get IRBs approved, the ethics, learning how to multiplex and building the communication channels across different laboratories, starting with PBMCs and genotyping and trying to integrate data set and build upon from that experience. Experience to more complex tissues. And this, of course, you can start with cancer or start with brain tissues.

I think you're making a very good point, Jay, about how do we want to start? Because if we pull together to start with something that is maybe not that fancy, but everybody could collaborate a little bit, you know, and we could find a way to finance genetic diversity, which is something that hasn't really been—

May I comment?

Yes, of course.

Jay, you said to study genetic diversity for reference population or for disease. What are you— because—

I think it's reference population.

Yeah, because yesterday I mentioned in my presentation, we are maybe in October, we are launching one project for sequence at least 1,000 people from the Guarapuava city, and the idea is exactly to know to show the genetic diversity of the city and use this information to try to implement the precision medicine. And also we are, of course, collect samples from different diseases including cancer. And maybe we can discuss more about that because it's not the representative from Brazil population, but from the cities, specifically from the Guarapuava city. I think this is more easy to know and to manage the information, try to understand one part of the diverse of the Brazilian population. Maybe, I think it's very nice if we can discuss about that.

Together.

Yeah, I think that's excellent. And if you already have the access to cohorts and individuals, yeah, only thing that you can do is then add the single-cell PBMCs, right? So if you already have plans to do genotyping or genome sequencing, you already have the samples, so you just take the PBMCs and run and You can do eQTLs. You can do very interesting additional analysis that could be very valuable. So yeah, I think that's a really good starting point, which may help to build connections.

Guys, we have Enrique Hernandez who wants to ask a question too, or to contribute.

Yes, I want to to contribute by telling that perhaps half of us are computational biologists. So we have a strong analytics, let's say, power here. And from past experience with the International Cancer Genome Consortium, we have a lot of trouble in setting up like analytical standards, standards of analysis. Perhaps the Broad Institute pipeline somehow established as the standard, but there were many different types of analytical approaches that were not like given a following. So perhaps we may think about forming some kind of network or some kind of task force to join forces and to establish the best practices of analysis for this type of data early on so that the different expertises and so on may in some sense converge to have well-defined, high-quality computational pipelines. So that may be a good goal to start or to establish here.

That's a great point. Do you want to comment on this, Jay? Or Enrique?

Yeah, maybe Enrique can comment quickly, but maybe I would highly encourage you to connect with the Global HCA. There are an analysis working group who have been investing a lot of time to set the right standards. However, I do recognize that it's not always easy to connect with the global ACA, and also a lot of these pipelines depending on the technology you use and which biological questions you may have or which analysis you plan to do. So I agree, I think it's an excellent idea to formulate a regional working group regarding the analysis, but at the same time trying to stay in line with the global ACA so you don't necessarily reinvent the wheel. Yeah, but then still you have your own kind of ownership and leadership into that in the region. I think that's very important.

I think that's a very good point. I would suggest, I don't know what Vinícius, Wilson, and Eduardo, all the other ones that are working with data analysis, maybe the way to go would be for you guys to have a group that would join forces, sit together, and think about how to go about this. So people are not reinventing the wheel or not like maybe even within Latin America redoing the same things. I don't know if you think this is a good idea. Ederaldo wants to comment, please.

Hello, yes, so I'm developing in my lab what I'm calling a framework for unified single-cell analysis. I try to follow the standards from the AGC as best as I can, but the software is still under development and it's going to include features for multimodal single-cell analysis to integrate transcriptome, CITE-seq, and also single-cell ATAC-seq. And also it's gonna put together the same computational platforms, the algorithms that I have been developing over the years, including classical clustering, differential expression, but also trajectory inference algorithm that I have developed in the past year, and another ones that I have been implementing in my lab along the year. So I'm trying to put together a computational platform that integrates several features that are used for single-cell analysis that are not yet readily available through any other software package. So it's not going to reinvent any analytical tools that are already available, but it's going to include the new tools that I hope— hopefully new tools that I'm now developing in the lab. To integrate single-cell data in multiple levels in one single platform. So we can push together to maybe make this high standard in terms of the quality of the software, because I'm pretty much developing this with a scientific initiation student. So it requires a lot of software engineering to make this globally useful, let's say like that. Thank you.

I think that's great to know. I think that's aligned with what we were just saying. There's a lot of competence on that and you guys have to get together to discuss that. And Enrique from the DCP just shared here some pipelines already implemented by the HCA. I think that What you just said, Eduardo, is great. It's not about redoing what's already there. So I think that it would be great if you got together to check it out. Let me just tell you something here. One of our participants is suggesting that everybody writes down full names and emails in the chat so we can talk together after this. Christine, you want to say something?

I could see that Enrico had an additional comment.

Yes, I did.

So, I don't know if any of you have joined the HCA Slack, but it's open. And like adding to what Jay said, in the HCA Slack, there is a data pipelines team a channel in which you can chat with Kylie, which is kind of the manager, that, and with many other people that are working on it. So if you have any questions, just drop in there. People is really nice, so feel free to ask any question in there and they will be able to answer better than me.

That's great. I think that's great. I think we all have to keep in mind that the HCA during the past years, they have already come a long way on a lot of aspects that we are discussing here, even on biology protocols, data analysis protocols, even ethics. They have a lot of working groups dedicated to all these aspects. So we really have to dig into it, you know, and try to reach out and to collaborate directly with them so we don't have to start from zero. So the idea is, since we're starting, let's start, like, take advantage of all that. What we want is to contribute with the HCA. So, um, also, so I think it's, it's important that we keep that in mind. Uh, it's a very good point. And does anybody want to share any views on what they think HCA Latin America should look like? Yes? Is this all too new for us to imagine what a Latin American Human Cell Atlas would look like as a group?

Well, I think It would be important to highlight if there are any differences in, even if it's some of the same diseases or tissues that we study, you know, as the main Human Cell Atlas. I think this diversity should be one of the first points. Like, is there, I don't know the answer. I don't know enough about the literature in this topic, but is there any difference in gene gene regulation, you know, that is more prevalent in certain ethnicities that can be related to certain diseases that are more prevalent in certain places. For example, here in Mexico, of course, we're the most obese country in the world. And that's not only related to diet. Of course, a lot of that has to do with diet, but we also have one of the highest prevalences of certain polymorphisms that are, you know, just associated with, with obesity. So For example, is there a difference in genetics, you know, at the level of gene regulation? Can you see different proportions of cells doing certain things than others in certain organs? I don't know how that would look like. And of course, focusing, I would think, in diseases that are important for these countries that, you know, may be also important in other places, but that sometimes have been just overlooked because they're not that common in other places. So I would think that's the best, at least in my point of view, view of how this could look like as a Latin American initiative.

Do we think that if we set a goal to have in one year some ideas of, for example, important cohorts of diseases which are most prevalent in our countries, or access to samples that could address genetic diversity, just like Wilson is constructing here. We are also going to have one on rare diseases. So Albert Einstein Hospital is sequencing thousands of genomes also, and we have over 1,000 also genomes that have just recently been published from Brazil. So I believe the other Latin American countries may have that. Do you think that in one year we can come up with that? Do you think this is a realistic goal that we can get together to organize this framework for HCA Latin America?

Why not?

It's a great goal.

Yeah, that would be a more or less short-term, well-prevalent diseases with cohorts, genomic data for genomic diversity?

I'm not sure about the genomic data, at least here though. I mean, we for sure can get probably together cohorts, you know, collaborating with hospitals that have access to these patients of, you know, from diseases with importance here, but I'm not sure in a year we can generate at least somewhere.

Yeah, I'm not sure about generating, but having a complete picture of what is available. So each— yeah, so like for us to design what we really can do, first we have to have access to groups that have it and have a clear picture of what we could do. So have this framework and we can create a working group that would be in touch to collect this kind of information. And then from there, well, meanwhile, of course, we're going to have all these projects that we are going to try to get funding for, but maybe have this framework in a year timeline. Mauro wants to say something.

Yes, Patti. Just a thought to share with the group. According to the data generated by the consortium, how is— is there a framework that we could understand and look at about how to share this data, for example, for data analysis? And maybe to organize working groups dedicated to understand and to, for example, to bring their methods to assess these datasets, these very interesting and very rich datasets.

I'm not sure I understand what you're talking about. Are you talking about datasets that already exist? The HCA ones?

I presume that the ATLAS has generated single cell data that still—

Enrique has shared here in the chat how to have access to pipelines and also yesterday in the talk he shared how we can have access to Human Cell Atlas data that is already available. I think you can reach out to Henrique to understand more how this works. But yes, most certainly, yes, they are already available. And that would be one of the task forces. Henrique is just sharing here again in the group of people who work with computational biology and data analysis getting together to understand how these resources are accessible.

I actually asked this because this is one way to organize groups in terms of non-funding requirements. I have some experience with the TCGA analysis working groups.

Yeah.

Because they also produce a lot of data that need inputs from different expertise. And the way they organize groups is very interesting. In the sense that they have clear targets, clear goals, and get together people that can contribute with their expertise. So I think I see that the Atlas has a very unique and rich datasets that can be shared by the community.

And this— I think that, Mauro, yes, that is a very good idea as one of the working groups. And there are quite a few of you guys already working with these datasets. Wilson, Helder is also doing this. I think Vinicius too. So I think, Maude, it would be great if you— we— as one of our goals, data analysis is already happening when we are ready to generate biological data. So I think it's really important what you're saying, because this requires minimum funding at many times and can be already done. Can we also say then that we have a relatively short-term goal of this first year that data analysis groups can be organized into that? What do you think, Mauro and Wilson, Vinicius and Hernandez from Mexico? Enrique Hernandez from Mexico.

I guess it's a doable goal, at least setting—

yeah, setting yourselves as a working group.

It's, it's, uh, yes, most likely doable. And with, with all the previous experience and all the previous guidelines that we already have, we, we may even have not starting at zero, but having like wrapping up everything already established and trying to adapt it to the way we work in Latin America.

That's great. Guys, we unfortunately have to finish the discussion here because we have to in 20 minutes get together in the other room. Remember the other room where we were before? The webinar room to communicate to the others some of the points that we were discussing here. So it was great talking to everyone here. We will get back to everyone, you know, like we will have this yesterday, this was mentioned, we're going to mention it today again, that we're going to try to have follow-up meetings more informal in the next month so that people can come back and reconnect so that we don't lose this, we don't miss the opportunity of really having this going now. So I think there's going to be one or two meetings opportunities per day the next month. So this is going to be shared with you. And in those meetings, we assumed that we were going to really be able to put together people who are really interested in having this going for the next year. And then we're going to have smaller working groups to try to make this happen. But we will be sharing this all with you guys later. So thank you very much. If you want to go grab a cup of coffee or something, I have now to talk to Christina and Daniela, right? So we can put together some notes.

Yes.

Thank you, guys. This was really great.

Thank you.

Thank you very much.

Lovely to meet you all.

Back to everyone.

Thank you, guys.

Thank you very much. Thank you, everyone.

Thank you.

Bye-bye.

Patricia, what a fantastic job you did sharing that. Well done. It was really great.

It's such a great crowd. It's such a great crowd, right? They're all great.

Such great discussions, and you pulled out the theme so beautifully. That was really great.

Thank you so much, everybody, for being here. It was a great crowd. That's why, right? They're all so good.

A bit quiet at the beginning, but that's normal, right? It's also very early at some place. And not— well, I shouldn't say for me, but I do work at nights usually. So for me, it's like— this is why I look like this. It's just like I woke up and so at the beginning it was a bit hard. But we're fine now.

It's true, I guess. And also, not like some other people here that were here, I know them, they're very chatty, but it's hard when you have like 30 people, right, to be able to like discuss, right?

No, you were great.

Yeah, and yeah, so amazing actually how thematic it was. So, Danielle, what were your main things?

I don't know how we can do this feedback.

So should we write a thing in a Word document and read it?

That we could share? Yeah. I wrote it in a paper here. Did anybody already write it in a—

Yeah, mine is the same.

Write in paper?

I wrote in the computer.

Ah, so if you wrote in a computer, maybe you can read it to us and then we can maybe add? What do you think, Christine?

I really loved the way you framed the forward-looking piece. You know, this is our goal within a year, these are what the working groups can probably achieve. Why not let's frame the discussion around that? Because then we can talk about the challenges and opportunities about use, you know, the opportunities with the biobanks and the challenges really understanding how to set the methods and how to generate the data in the various sites. The opportunities where you've got very, very cohesive interest in biology, But, you know, the challenge of being so geographically dispersed, and, you know, reasonably isolated pockets of people too. And then the opportunity of having so many people interested in the bioinformatics, the challenge of really understanding data interoperability, and the importance of connecting back.

And also to get them to talk together and define how to work, because they tend to be very within their walls when they—

Yeah, I can tell.

Yeah, they all are already like developing as something else, right? And to get them down to earth to analyze data that needs to be analyzed is, that's a challenge. Let's not point it out.

You know, by setting your 1-year goal, in a year we will reviewed how best to interact with the biobanks and set the themes that we're going to really focus on and bring the funders together and have some further workshops to talk about how we network. That's a brilliant goal, and through that time these data analysis people have been tasked with setting up some training workshops, and and working out how to operate with the Data Portal so that we can exchange data between teams.

Do you think we have to have a PowerPoint for that, or can we just say it?

I think you've got it.

I'm writing, I'm trying to organize, because I wrote this while we were talking.

Oh, that's great, we love that.

I'm trying to organize it in So we have points.

Let's say that we have a 1-year goal of understanding how much information we have in our biobanks, cohorts, and the aim would be to work with genetic diversity or specific diseases. So we would have this time frame to understand that. We would also like to set up meetings with the funders, and that could be international ones like the CZI, maybe the NIH. I don't know how accessible they are, but the Gates—

they can say no.

Yeah, and welcome, welcome is amazing.

The welcome. Yeah, the Welcome Gates, and in Brazil, the FAPES, they're called, the FAPES, for a discussion on what we have and how they would like us to frame our project proposals that would be competitive and interesting for the HCA.

How do you spell, sorry, these Brazilian—

FAP, Fundação de Amparo à Pesquisa, and they have one in each state of the federation.

Okay.

So I think that's a national one in Brazil that can fund collaborations, and many times they have international collaborations that they fund. So meetings with the funders, and then we would have working groups with the bioinformatics people so they can already start training students and organizing themselves on how to work with us, not with themselves.

And interoperability of the data with the HCA data portal.

Yes, that's very good too.

If they can't work it back with that, then it's going to be very difficult for you.

The last training piece— Yes, how they can operate with the HCA portal and all the information that is available.

And the last training piece that you drew together really nicely was all of these side groups, fellowships, exchange opportunities, to bring, to help other incidental training that might sit outside the HCA, but allows for a lot of networking people.

Yes, so we will have a group.

So we will have a group. All of those different fellowships.

Yeah, yeah, we want to set up a group of people who would take care of that, exchanging Yeah, I'm just going to remove Joanna. Okay, I don't know, I think that's a— what is that? I don't know, maybe she's part of it.

Do we have what we need?

Are you putting that in a PowerPoint, Daniela, for us? With pictures?

Okay, I'm writing— well, I'm writing a Word document organizing the thing, but we can— when it's actually organized, it's easy to put in slides.

Oh, okay, that's great.

Just put it in different— because I wrote a lot of stuff here and it's from different places, so I'm trying to just put it— so I'm organizing it first, the goals. So Yes, there's the 1-year goal, which is, as we were discussing, understanding what's available in different countries and having a complete picture of what we can work with and what we need. And then there's kind of side goals, I would say. I mean, you know, like other projects that we can pursue now, in a way. So I don't know how to write that.

Like, yeah, you can, you can write like immediate goal. We have a lot of common interests within the group. So you put goals, immediate goal. We have a lot of common interests, right? So we could get together in small hubs to call specific projects. Yes, specific projects, right? So there is that. Then in— that's immediate. Then in 1 year, we want— where do we want to be in 1 year? So in 1 year, so we're going to be working together this 1 year to understand the biobanks, resources, specific diseases, so that by 1 year from now, we will really have a clear picture of how we can collaborate as HCA Latin America.

Jay was suggesting an immediate goal to you should be just to choose some simple tissues and benchmark between sites how each laboratory is basically being confident that each other is generating equivalent data. With equivalent cells.

Can this go together with the bioinformatics working group that would be getting together to—

I think this would be the data generators, so the people who have the machines.

Ah, okay. Oh yes, okay, that could be one of the immediate goals, right? People who have the machine. Yeah, so specific projects and something like that. Choose the same kind of sample that would be more genetic, just like PBMCs, right?

And he was suggesting PBMCs, and what they did in Japan and what we did in Australia was have some blood that was taken from one set of donors shipped between the different sites And then everyone did the library preparation at those sites, and we just came back and compared data and said, so if we get data from Mexico and we get data from Brazil, are they the— is it the same? It's a very interesting benchmarking activity, but it— and it does take a lot of trust, but it lets you know whether or not the methods you've got are robust.

Okay. Yes. I think that's— okay, good. So those would be two immediate things: setting up small projects and getting people who have the machines to work with common samples.

Just to work with each other, yeah.

Yeah.

Mm-hmm.

To be able to work with each other and with the protocols, right? Immediate also would be the working group for data analysis that we were just mentioning. So workshops, learning how to work with HCA data, with the protocol establishing, looking at the protocols that are already available.

Yeah, look, the protocols you need are so tissue-specific that, you know, I would— my strong advice to you is you are the experts in the tissues that you're working with. You're going to be able to work out the best way of isolating that tissue. You can start with the HCA protocol, but a lot of the tissues you're interested in, like melanoma, are not in the outlets.

It's true.

I remember Orit mentioned some of that too, right? That there are some specifics and you try the protocols, maybe that's not really going to work as well.

Yeah.

The blood—

and so the only reason you would use something like PBMCs is so that you've got a benchmark to compare different facilities with. Because you're not going to use those protocols on a more complex tissue.

Of course, yeah. You'd be more like to learn how to work together, get used to generating the data, sharing the data, analyzing the data.

This is a reasonably cheap sample to get. How easy is it to ship between sites? Is it worth shipping, or do we lose the sample?

Yeah, okay. And then also within this This year, Daniela, would be the meetings with the funders.

Immediate goal.

Yeah.

It might take you a year to get them at the table, but—

Yes, yes. Within a year, we want to do that. Immediate goal is the initial specific projects and benchmarking protocols. And bioinformatics. Within one year, biodiversity, biobanks, diseases, and the meeting with the funders. Yeah, okay.

And then there was the list of having a working group who's going to get a list of the training opportunities, the small grant training opportunities, which may be particularly facilitating laboratory exchange, so you can get trainees to come back with the EBI methods or the Recon methods.

Okay, coming, coming.

They want us to be back in 5 minutes.

Okay, okay, coming, coming. I'm almost done.

Okay, you have to send this to me by email. Let me see. Yes, I'm gonna write my email here.

It's just that I'm trying to put— so very quickly, okay, there's— oh yeah, the discounts and all these things.

Oh, you can save the chat.

Do you want to save it?

Yeah. I think, right, so I have here— yeah, so I have here— I can send it to you. I didn't— okay, yeah, all right. So let me send you both. Oh, I can send it in the chat as well, right?

No, I don't know how to pick it up from here, but maybe, yeah, I don't know. Do I download it?

I think you can, so I can send it both.

Yeah, just send it to my email. I'll get it there.

Okay, so I have it here. So email.

It was great help, Daniela.

Well, I hear it is. So is it the Einstein.pdf?

BR? No, send me to this. I just put it here in the chat.

Ah, Morrigan PS?

Yeah, because the Gmail is faster. The lab one takes a while to—

Christine, do you want me to send them to you as well?

Yeah, that would be great.

Thank you so much. I'll send you my email as well.

I did not include here the participants' summaries, but I have them as well. So do I— I can put them, but they would be raw. I did not pull, you know, I did not pull, I'd say clean those ones, but I can add them at the end.

I'm not sure.

Okay, yeah, so sending now.

Where is your email?

Ah yeah, okay, right, so it's gone. You should get them now, I hope. So basically, while they arrive, I'll open it again. So I wrote down basically goals. Immediate goal, formation of small hubs to pursue specific projects. Immediate goal, choose some simple tissues, PBMCs from the same donors, for example, to benchmark techniques and results against the main HCA. Immediate goal, create working group for bioinformatics.

To learn to work with HCA data and learning protocols.

Another immediate goal is meeting with funders and see what they're interested in to help them fulfill their funding agenda. And I wrote welcome CSI Brazilian FAP. And then one-year goal, understanding what's available in the different countries, biobanks, resources, specific diseases, and how to picture how we can collaborate as HCA Latin America. Then strengths, Lots of common interests, potential for collaboration, several groups in different countries with data, I have wrote data, significant data analysis experience. Data analysis experience.

That's great.

Several groups with access to biobanks from genetic—

Exactly my main— Girls, I have to go because they are— I have— we have to be in another room.

Oh, okay.

And if I don't leave the meeting, I cannot go in the other room, but we can communicate after. Answers in the meeting. It was great. Thank you so much, Daniela. Thank you so much.

So we go back to the meeting, right? All of us?

Yeah.

Yeah. Okay, perfect.

Bye.