Today we meet with Dr. Jan Mulder, group leader of the Human Protein Atlas (HPA) brain profiling group at Karolinska Institutet, Stockholm, Sweden, and the director of the Brain Atlas, a brand-new addition to the (HPA) project. His research interest is to identify proteins involved in brain development, normal brain physiology, and pathophysiology of brain disorders by using an antibody-based approach combined with multiplex fluorescence immunohistochemistry.

We asked Dr. Mulder 10 questions about the past, the present, and the future of the Brain Atlas.

The brain is arguably the most important and the most complex organ in the human body. There are more than 1,000 disorders of the brain and nervous system. The understanding of how to prevent and treat these disorders is crucial for maintaining the overall health and well-being of the human population. Neuroscientists all around the world strive to make fundamental discoveries about brain function, to teach and train the next generation of scientists and clinicians, and translate research findings into improvements in the diagnosis and treatment of psychiatric and neurological disorders.

Q1: Could you explain the Brain Atlas in simple words?

The Brain Atlas explores the protein expression in the mammalian brain by visualization and integration of data from three mammalian species (human, pig, and mouse). It is a knowledge resource that provides an overview of all proteins expressed in the brain with a special focus on genes differentially expressed between brain regions and brain cells that are most likely very interesting from a functional point of view. 

By making the data open-access, neuroscientists and other researchers can compare data from the Brain Atlas and one another's studies to discover more.

Q2: What does it deliver in terms of biological insights?

The Brain Atlas aims to make complex data easily accessible and provides gene expression overviews, and annotated images based on human, mouse, and pig data. Brain samples are grouped into 10 anatomical regions, providing a regional classification of >16,000 genes based on RNA expression, indicating which proteins are elevated in one region of the brain compared to the other.
 

Q3: What is the translational application, if any?

At the moment all data is based on ‘normal’ (healthy) tissue and no human disease or animal model data is included. However, the ability to compare gene expression in the brains of different mammalian species helps to understand some human-specific pathomechanisms and could be used to validate or select a model system for human disease.

Q4: Could you share a turning point or defining moment in the Brain Atlas creation history?

There have been several time points that are important for the establishment of the Brain Atlas. Already very early on in the project around 2004, we started to explore using HPA antibodies on rodent tissues. We found that there was enough protein homology between mammalian species so we could use the antibodies produced by the HPA project to map brain protein distributions in other species. This allowed us to explore many more brain regions and brain cells by using the much smaller mouse brain.

The primary antibodies used to generate the immunohistochemical staining for the images in the Tissue Atlas are commercially available as Triple A Polyclonals from Atlas Antibodies.
  
Moreover, the developments in transcriptomics analysis enabled us to investigate the expression of protein-coding genes in the brain of humans, pigs, and mice, allowing the creation of a proteome-wide overview on the mRNA level. Combining the efforts provides a complete expression overview with detailed protein distribution data for some selected (brain-relevant) genes.

Q5: How prevalent is the use of the Brain Atlas today compared to other resources?

It is difficult to answer this question at this point since the Brain Atlas is a brand-new part of the HPA. 

However, based on over 15 years of “atlassing” experience from the HPA project and a drive to integrate and update data constantly, the HPA with all its different parts is becoming the to-go-to resource for life sciences.

When it comes to other resources, there are several free accessible smaller and larger datasets. Most famous are the datasets provided by the Allen Institute for Brain Sciences. These datasets are isolated and there are very little efforts to integrate data from different sources to create a complete overview. Another major problem with many datasets is that these are project-based and after completion, there is very little interest to keep the data ‘live’ and updated to the latest genome builds.

A strong fact about the Brain Atlas compared to other atlases, is that it explores the protein expression in the three mammalian brains: human, pig, and mouse. The data focuses on human genes and one-to-one orthologues in pigs and mice. Each gene is provided with a summary page, showing available expression data (mRNA) for summarized regions of the brain as well as protein location for selected targets. High-resolution staining images as well as expression data for the individual sub-regions are all available for exploring the most complex organ.

Q6: What do you see as the barriers to the wider adoption of a Brain Atlas, if any?

I think awareness is the major factor. I think it is important to make more and more people aware of the type of data and the quality of data provided by the Human Protein Atlas in general and the Brain Atlas in particular. This can be done by advertising and promoting our work, but more importantly when users start publishing results based on analysis of our data. We should therefore stay closely connected to the neuroscience community and listen to their feedback and requests.

Q7: How does the Brain Atlas enhance the understanding of brain diseases?

The Brain Atlas is a formidable resource. Understanding how the brain is built is the first necessary step for knowing how to prevent and treat brain disorders.

The data in the Brain Atlas is separated into 10 defined anatomical regions, used for expression classification in individual regions of human, pig, and mouse brains respectively. The normalized expression from the 10 regions as well as the spinal cord and corpus callosum in the human brain is used as a representation of the brain in comparison to the rest of the whole human body, defining the brain's elevated genes on a whole-body level.

The next step would be the implementation of the Brain Atlas with the addition of disease data. Adding data on neurodegenerative disorders like Alzheimer’s or Parkinson’s disease would be of great interest and something I would love to do. However, at the moment we do not have the resources to implement this.

Q8: What questions were you addressing when you started working on the Brain Atlas?

What are the genes that drive specific brain functions? What cells express these genes? Are these genes only expressed in the brain? I think we were able to answer these questions in the Brain Atlas portal. 

Q9: What happens next in the process of brain and discovery?

There are a few interesting developments allowing us to even look at gene expression in a single cell. These methods need to mature with regard to the number of detected genes and the number of cells analyzed in a single experiment.

I could imagine that in the near future, we will also include single-cell data in our brain atlas. Until that time we will continue to generate more spatial detail and look at different isoforms of genes in the human brain.

Q10: If you could offer readers interested in understanding how the brain works one key piece of advice, what would it be?

Try to combine as many resources as possible, this helps to validate the data (agreement) but also combining data based on different approaches can provide new insights in the molecular organization of the brain related to function (1+1=3).

Readings

Sjöstedt E, Zhong W, Fagerberg L, Karlsson M, Mitsios N, Adori et al. An atlas of the protein-coding genes in the human, pig, and mouse brain. Science. 2020 367(6482)

Uhlén M, Fagerberg L, Hallström BM, Lindskog C, et al.  Tissue-based map of the human proteome. Science 2015 347(6220):1260419.