Genetic studies have revealed many genes linked to common and rare diseases, but to understand how these genes cause disease and use this knowledge to help develop therapies, scientists need to know where they are active in the body. Single-cell research can help achieve this goal, by studying gene activity in specific cell types. Scientists need to profile all cell types and compare them between organs in the body to learn about the full spectrum of human disease, but this is difficult to do with existing methods.
Now, researchers from the Broad Institute at MIT and Harvard have developed a robust experimental pipeline that can profile many more cell types from more tissues than can be studied with other techniques, as well as methods of analysis. machine learning to gather this data and query the resulting map. , or atlas. The team used it to identify specific cell types from various tissues implicated in multiple diseases. Their approach will allow for further large-scale studies of various cell types and comparisons between tissues, including cells from frozen tissues that can be harvested from many patients. This work opens up a wealth of samples stored in research collections around the world for this type of single-cell analysis, and also brings scientists a huge step closer to their goal of an atlas of human cells that lists every type of cell in the human body, in a large number of individuals from various backgrounds.
Previous single-cell studies have primarily focused on one tissue type at a time, to create tissue-specific maps. Using their new pipeline, the team built a huge atlas of hundreds of thousands of cells in multiple tissues in the body. This allowed them to discover unexpected new functions and gene expression programs for several cell types, such as muscle cell programs expressed in lung connective tissue cells. The results also revealed genetic similarities between cells from different tissues and linked certain cell types to specific diseases for the first time.
The atlas is the first cross-tissue atlas to be based on measurements of gene activity in individual cell nuclei, which allowed the team to capture a wider variety of cell types than existing methods that measure whole-cell gene expression.
This study is part of the international program Atlas of human cells (HCA), which aims to map every type of cell in the human body as a basis both for understanding human health and for diagnosing, monitoring and treating disease. An open, global, and scientist-led consortium, HCA is a collaborative effort of researchers, institutes, and funders around the world, with more than 2,300 members from 83 countries around the world.
The paper is one of four major collaborative studies for the Human Cell Atlas published in Science this week, which have created comprehensive, freely available inter-tissue cell atlases. The complementary studies shed light on health and disease and will contribute to the creation of a unique atlas of human cells.
“These studies represent a key moment for single-cell research and the Human Cell Atlas,” said Aviv Regev, the study’s co-lead author who was a senior fellow at the institute at Broad when the study started and is currently the head of Genentech Research. and Early Development. “In our study, we have shown that this approach can generate crucial insights into the role of cells and tissues in many diseases, which will spark new scientific and biomedical investigations with a common goal of revolutionizing medicine.
The right teams at the right time
Over the past decade, Regev and others at Klarman’s Cellular Observatory at Broad have been leaders in the development and implementation of techniques that analyze gene activity, or the expression of RNA, in single cells, but these methods do not work well on large fat or muscle tissue cells or on delicate cells like neurons. Regev lab scientists therefore began to develop new approaches that could be applied to a wider variety of cell types by isolating the cell nucleus for RNA measurement, rather than the entire cell. Additionally, these approaches can easily be applied to frozen tissue rather than fresh tissue, allowing researchers to collect the large number of samples needed to capture a diversity of human populations around the world.
At the same time, another group of Broad scientists realized that they would benefit from this same method. Leading researchers from the Genotype-Tissue Expression (GTEx) project, funded by the National Institutes of Health, had documented how small changes in DNA sequence, including disease-associated variants, can impact the gene expression in dozens of tissues in the human body. Since 2010, they’ve analyzed dozens of tissue types from hundreds of donors using methods that turn tissue into a bulk mixture, but they wanted to see how genetic variation altered individual cells.
“We needed a closer look at cells in tissues, because the cell is where biology happens, both in health and disease,” said institute scientist Kristin Ardlie, co-lead author of the new study and director of the GTEx Laboratory Data Analysis and Coordinating Center at Broad.
Existing single-cell RNA sequencing methods can be used to analyze fresh tissue, but GTEx’s tissue bank samples were all frozen. Ardlie and his team suspected that the single-core methods developed in Regev’s lab could give them a powerful way to analyze their banked frozen samples — and more cell types within them — while providing their colleagues with a collection collection of human tissues that they could use to compare the single-core approach.
“Both groups needed each other, at the right time, to build a new way to scale up these studies,” said study co-first author Gökcen Eraslan, a postdoctoral fellow at Genentech who was a member of the Klarman Cell Observatory when the study began.
Plot a new type of cell atlas
In the new study, the GTEx team, the Regev lab and their colleagues collaborated to develop a novel large-scale single-core sequencing pipeline. In an effort led by Orit Rozenblatt-Rosen, executive director of cell and tissue genomics at Genentech who was scientific director of the Klarman Cell Observatory during the study, the team first optimized four different single-core protocols. , then used them to analyze 200,000 cells. in frozen samples of 8 tissue types originally collected by the GTEx project. They used a deep learning-based model to compare cellular profiles between tissues, donors, and methods, and showed that their single-core profiling pipeline performed as well as reference methods for measuring the RNA in single cells, while capturing cell types that cell-based methods could not capture.
The researchers generated an inter-tissue molecular reference map that reveals critical data about the cell types residing in various tissues. “With these new technologies, we are able to map cells in healthy tissues of the human body,” Rozenblatt-Rosen said. “It gives us a comprehensive basis to understand what is wrong with the disease.”
Scientists have also demonstrated that the approach can generate new biological insights, which can trigger new studies linking findings to health and disease. For example, in all tissues, the team observed two populations of a type of immune cell called macrophages: one population that plays an immune role and another that supports tissue function, with different proportions of each in various fabrics. The discovery helps explain how tissues come to a self-regulated balance, or homeostasis, and how a type of white blood cell called monocytes transforms into macrophages with different functions. In the lungs, they also observed connective tissue cells called fibroblasts that express gene programs typically associated with muscle cell function, suggesting a yet unrecognized role for these cells in lung tissue.
To explore the atlas’ ability to support disease studies, the team then turned to a catalog of Mendelian diseases, which are caused by changes in a single gene. The researchers cross-referenced the 6,000 known genes underlying these disorders with gene-level data from their atlas and identified new cell types that may be involved in the disease, such as non-myocyte cell types that may play a role in muscular dystrophy. They also demonstrated the value of the atlas in coming up with known and new cell types that can affect a range of common diseases and traits, such as heart disease or inflammatory bowel disease, by comparing genes enriched in gene-specific cell types suggested by whole genome association. studies.
“Such intertissue cell atlases can help researchers understand the causes of comorbidities and how genetic variants can predispose to multiple diseases or conditions in the same person,” said Ayellet Segrè, co-lead author of the study who is a member of associate of Broad and assistant professor at the Mass. Eye and Ear and at Harvard Medical School.
The researchers believe their approach now paves the way for larger-scale studies, involving hundreds of individuals or more from diverse ancestral backgrounds, to further explore the genes and cells underlying rare and common diseases. .
“Multi-tissue profiling is the only way to see this level of detail,” Eraslan said. “We always wanted to be able to profile the entire human body. In the past this was not possible, but the technology and algorithms are mature enough to do this now. We’ve been waiting for this moment to come and now it’s here.
The work was also led by Bristol Principal Investigator Eugene Drokhlyansky Myers Squibb, who was a postdoctoral fellow at Broad during the study, and Francois Aguet, Principal Investigator at Illumina Artificial Intelligence Lab and former Broad’s Cancer Group Leader. Schedule.
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