As part of a larger collaboration with research teams from around the world, Salk Institute researchers analyzed more than 500,000 brain cells from three human brains to create an atlas of hundreds of cell types that make up a human brain in unprecedented detail. The study, published in a special issue of the journal Science, is the first time techniques for identifying brain cell subtypes developed and applied in mice have been applied to human brains.
“These papers represent the first tests of whether these approaches can work in human brain samples, and we were excited at just how well they translated. This is really the beginning of a new era in brain science, where we will be able to better understand how brains develop, age, and are affected by disease,”
said Professor Joseph Ecker, director of Salk’s Genomic Analysis Laboratory and a Howard Hughes Medical Institute investigator.
The research consortium is a collaborative effort to learn more about the human brain and its modular, functional structure. The Brain Research Through Advancing Innovative Neurotechnologies (BRAIN) – an effort launched in 2014 to describe the full plethora of cells, as characterized by many different techniques, in mammalian brains – brought the consortium together.
Understanding Brain Cell DNA
Every cell in the human brain carries the same DNA sequence, but various genes are transcribed onto strands of RNA for usage as protein blueprints in different cell types. This final flexibility in which proteins are found in which cells — and at what levels — allows for a wide range of brain cell types and complexity.
Knowing which cells rely on which DNA sequences to function is critical not only to understanding how the brain works, but also how mutations in DNA can cause brain disorders and, relatedly, how to treat those disorders.
“Once we scale up our techniques to a large number of brains, we can start to tackle questions that we haven’t been able to in the past,”
said Margarita Behrens, a research professor in Salk’s Computational Neurobiology Laboratory and a co-principal investigator of the new work.
A Big Leap
Ecker and Behrens headed the Salk team that analyzed 161 different types of cells in the mouse brain in 2020, using methyl chemical markers along DNA to determine when genes are turned on or off. Methylation is a type of DNA control that is one level of cellular identity.
In the new paper, the researchers used the same tools to determine the methylation patterns of DNA in more than 500,000 brain cells from 46 regions in the brains of three healthy adult male organ donors. While mouse brains are largely the same from animal to animal, and contain about 80 million neurons, human brains vary much more and contain about 80 billion neurons.
“It’s a big jump from mice to humans and also introduces some technical challenges that we had to overcome. But we were able to adapt things that we had figured out in mice and still get very high quality results with human brains,”
said Behrens.
At the same time, the researchers utilized a second technique to examine the three-dimensional structure of DNA molecules in each cell to learn more about which DNA sequences are actively utilized. Cells are more likely to access exposed lengths of DNA than neatly packed up stretches of DNA.
“This is the first time we’ve looked at these dynamic genome structures at a whole new level of cell type granularity in the brain, and how those structures may regulate which genes are active in which cell types,”
said co-first author Jingtian Zhou, a postdoctoral researcher in Ecker’s lab.
AI Deep Learning Models
Other research teams, including one at UC San Diego led by Bing Ren, who is also a co-author in Ecker and Behrens’ study, used cells from the same three human brains to test their own cell profiling techniques.
Ren’s team discovered a link between certain types of brain cells and neuropsychiatric illnesses such as schizophrenia, bipolar disorder, Alzheimer’s disease, and significant depression. The researchers also created artificial intelligence deep learning models that forecast the danger of certain illnesses.
Other groups in the global partnership concentrated on measuring RNA levels to classify cells into subtypes. The teams discovered a high level of concordance in each brain region between which genes were activated based on Ecker and Behrens’ DNA research and which genes were identified to be translated into RNA.
3,000 Types of Brain Cells
Scientists from the Allen Institute for Brain Science, a part of the Allen Institute, led five studies and contributed significantly to three others, including one that significantly extends on existing understanding about the number of cell types in the adult human brain.
Scientists from the Karolinska Institute and the Allen Institute analyzed the genes that were activated in individual brain cells using a technique known as single-cell transcriptomics, finding an astounding diversity of cell types: we have over 3,000 different types of brain cells.
Building on previous work mapping brain cell types in high resolution in single regions of the human cortex, the brain’s outermost shell, the newly published package expands those studies to dozens to hundreds of regions throughout the brain.
Where the single region studies found over 100 different brain cell types, the newly released data shows thousands of different kinds of brain cells across the entire brain. That complexity and variety had never before been described for many parts of the brain.
Cutting Edge Scalability
These studies are part of the NIH’s BRAIN Initiative Cell Census Network, or BICCN, a five-year program that was launched in 2017 to create a catalog of brain cell types. This body of work demonstrated the scalability of cutting-edge cellular and molecular approaches to tackle the challenges of size and complexity of the human brain and has set the stage for the next phase of this cell census effort.
This next phase, which is already underway at the Allen Institute, will create much more comprehensive atlases of human and other primate brains via the BRAIN Initiative’s Cell Atlas Network, or BICAN.
“The present suite of studies represents a landmark achievement that continues to build an important bridge toward illuminating the complexity of the human brain at the cellular level,” said Dr. John Ngai, Director of the NIH BRAIN Initiative. “The scientific collaborations forged through BICCN, and continuing in the next phase in BICAN, are propelling the field forward at an exponential pace; the progress—and possibilities—have been simply breathtaking.”
Human studies used postmortem tissue donated by people who had donated their brains to science, as well as healthy living tissue donated by patients who had undergone brain surgery and donated tissue to research.
References:
- Wei Tian et al. Single-cell DNA methylation and 3D genome architecture in the human brain. Science 382, eadf5357 (2023). DOI:10.1126/science.adf5357
- Mattia Maroso et al, A quest into the human brain, Science (2023). DOI: 10.1126/science.adl0913
- Kimberly Siletti et al, Transcriptomic diversity of cell types across the adult human brain, Science (2023) . DOI: 10.1126/science.add7046
- Nelson Johansen et al, Interindividual variation in human cortical cell type abundance and expression, Science (2023). DOI: 10.1126/science.adf2359
- Nelson Johansen et al, Comparative transcriptomics reveals human-specific cortical features, Science (2023). DOI: 10.1126/science.ade9516
- Thomas Chartrand et al, Morphoelectric and transcriptomic divergence of the layer 1 interneuron repertoire in human versus mouse neocortex, Science (2023). DOI: 10.1126/science.adf0805
- Brian R. Lee et al, Signature morphoelectric properties of diverse GABAergic interneurons in the human neocortex, Science (2023). DOI: 10.1126/science.adf6484
Top Image: An abstract representation of cell diversity in the brain. Individual nuclei are colored in the bright hues of t-SNE plots used in epigenomics analysis to distinguish individual brain cell types. Layers of background color represent the local environmental factors of each brain region that influence cell function. Credit: Michael Nunn