Aviv Regev and Sarah Teichmann are the founders of the Human Cell Atlas (HCA). The HCA was founded in 2016 and has grown to more than 2,700 members, from over 1,000 institutes and 86 countries around the world. HCA membership is open to the entire scientific community worldwide.
Aviv Regev is the head of Genentech Research and Early Development. Prior to Genentech, Regev served as Chair of the Faculty and Core Member at the Broad Institute of MIT and Harvard, and as Professor of Biology at MIT and Investigator at the Howard Hughes Medical Institute. She is a recipient of multiple prizes and honors, including the Overton and Innovator Prizes from the International Society of Computational Biology, the Paul Marks Prize, the Lurie Prize in Biomedical Sciences, the Keio Medical Science Prize, Schering Prize, Vanderbilt Prize, James Prize and Nakasone Award.
Sarah Teichmann is Head of Cellular Genetics and Senior Group Leader at the Wellcome Sanger Institute, Cambridge, UK. Sarah is a Fellow of the Royal Society, an EMBO Member, a Fellow of the International Society of Computational Biology and of the Academy of Medical Sciences. Her work has been recognised by numerous awards, including the EMBO Gold Medal, Genetics Society Mary Lyons Award and Biochemical Society GlaxoSmithKline Award among others.
Dear Aviv and Sarah,
You are the founders and leaders of the Human Cell Atlas (HCA), a consortium that aims to create a comprehensive reference map of all human cells. Can you tell us how your interest in this topic emerged and how the HCA was started and has evolved? A little over a decade ago, it was just becoming possible to sequence the RNA expressed from genes that are active in individual cells. Before that, to understand which genes were working, we needed much more material (RNA) than could be found in individual cells, so we had to grind up whole tissues, but this meant that rare cells with unique gene expression patterns, as well as the subtle variations between cells of the same type, could get lost in the mix. This relatively new breakthrough technique, known as single cell RNA-seq, reveals which of the 20,000 human genes that make up our genomes are expressed and at which level in each cell. This expression profile is a unique window into a cell’s type, origin and function, and can also tell us a lot about its potential to communicate with other cells, and even more so when combined with even newer spatial genomics techniques.
Aviv’s lab, and her colleagues at the Klarman Cell Observatory she established at the Broad, were one of the early innovators in this space, and after they did their first single cell RNA-seq profiling experiments in 2011-2012, Aviv felt that -- if we could scale these approaches -- we would be able to build a unified atlas of the cells of the human body. However, at that time, the lab methods we had were limited in scale, and our computational methods were limited in their resolution. She spent the next few years developing the necessary experimental and computational techniques to make single-cell sequencing at scale possible, and in 2014 presented the idea of a “Human Cell Atlas” at a US National Institutes of Health Challenge Talk.
In parallel, Sarah, an early researcher in single cell genomics, co-founded the Sanger-EBI Single Cell Genomics Centre in 2012, with colleagues across the Wellcome Genome Campus. Sarah separately realised that scaling up the technology would make it possible to map all of the cells of the human body and revolutionise our understanding of how the body works.
In early 2016, we decided to join forces to bring together a community of scientists to establish the international Human Cell Atlas (HCA) initiative. With 37.2 trillion cells in the human body, building a human cell atlas is an enormous undertaking, larger even than the Human Genome Project, and it will transform our understanding of the human body in health and disease. We believe that the HCA is much too big for any one institute or country or even continent to achieve, and will only be possible thanks to global collaboration, technological and computational breakthroughs, and science at great scale.
In October 2016, we organised the HCA launch meeting in London, bringing together 93 scientists from institutes around the world to start the initiative. HCA’s mission, as laid out in our ‘manifesto’ following the meeting, is to create comprehensive reference maps of all human cells—the fundamental units of life—as a basis for both understanding human health and diagnosing, monitoring, and treating disease.
To create the Human Cell Atlas, we planned to harness the power of massively parallel single cell genomics, along with then-nascent spatial genomics methods to determine the location of cell types in tissues, and computational technologies and machine learning algorithms to integrate, analyse and query the data. The initial plans of how to achieve this were detailed in our White Paper in 2017 when we launched the data collection phase of HCA.
From its start, HCA needed to be a global collaborative consortium to engage scientists and benefit people all over the world. It would chart the cell types in the healthy body, across time from development to adulthood, and eventually to old age, and the data would be openly available wherever possible.
Our initiative has grown to an international community of more than 2,700 biologists, clinicians, technologists, physicists, computer scientists, software engineers and mathematicians from 86 countries across the world. It is a vibrant, open community, and anyone over 16 years old who is committed to our mission and values may join – we welcome new members.
There are now 18 HCA Biological Networks that focus on individual organs, tissues or systems including lung, heart, brain, kidney, immune, skin, gut and developing tissues, as well as to cross cutting efforts such as mapping cells across human ancestral diversity. Together, HCA members have profiled more than 120 million individual cells so far, and our discoveries have led to 125 published papers, with many more on the way, and the data cited used by many other researchers for additional discoveries. These have generated unparalleled insights into human biology, health and disease, including rare disease, cancer, neurodegenerative disease and COVID-19. Our aim is to release a first integrated draft Atlas of selected tissues in 2025, and then to complete the construction of a comprehensive single cell and spatial Atlas of all tissues in the following 5 years.
Can you comment on how the HCA will help to understand cell-cell communication? What else could we do to advance knowledge in this field? Is this knowledge likely to produce large medical benefits?
The HCA is already advancing our understanding of cell-cell communication enormously by revealing the gene expression in each cell type in a tissue individually and in the context of other cells around them, through direct spatial measurement techniques as well as through computational inference. This allows us to see what signals individual cells have the potential to send and receive via ligand and receptor expression profiles, respectively, as well as the inferred activity of downstream signal transduction pathways and gene programs in recipient cells. For example, to understand the cellular interactions within and between the placenta and decidua that support early pregnancy (Vento-Tormo et al. 2018) HCA researchers developed a method for predicting cell–cell interactions (CellPhoneDB.org) based on the expression of multi-subunit ligand-receptor complexes. Such methods have since been expanded and developed (Luz Garcia-Alonso et al. 2021) to include signalling expression modules and spatial transcriptomics, and are widely used by the genomics community. Other methods such as CellChat and NicheNet have also been developed, which are also helping to understand the communication between cells.
Other approaches to understanding cell-cell interactions aim to find gene programs whose expression is coordinated between cells of different types which are directly proximal to each other (in spatial genomics data) or part of the same niche, reflecting the way in which the expression programs of one cells are impacted by another (Jerby-Arnon and Regev, 2022, Mitchel et al. 2022, Fischer et al. 2021). For example, the method DIALOGUE (Jerby-Arnon and Regev, 2022) maps such multicellular programs in tissue from single-cell or spatial transcriptomics data. This enables the analysis of multicellular regulation in health and disease. Thanks to advances in spatial genomics, we are able to pinpoint the exact location of cells and their neighbours in tissues, and the combination of spatial and single-cell genomics is revealing cell communication in unprecedented detail. Continuing advances in single-cell and spatial genomics, and the development of deep-learning methods to integrate and analyse the huge amounts of data we produce, will allow even greater understanding.
Further in-depth understanding of how cells communicate is likely to produce great medical benefits. Even as it is being built, the HCA is already having an impact on medicine (Rood et al. 2022). The HCA is being used as a molecular and cellular guidebook, to understand the mechanisms of disease at the cellular and tissue levels, this will allow the development of more accurate disease diagnostics and more targeted therapeutics. The healthy guidebook, and corresponding cell atlases from diseased tissue, can enable the identification of viral entry points, pathways for potential new therapies, and even precisely locate which cells specific therapeutics act on, for drug repurposing or reducing side effects. Finally, by mapping development and revealing cell-cell communication signals that guide differentiation, the HCA can be used as a blueprint for engineering specific cell types in vitro, which can be used in research and also empower new kinds of treatments, from cancer therapies to regenerative medicine.
Aviv Regev and Sarah Teichmann et al. Science Forum: The Human Cell Atlas (2017) eLife https://elifesciences.org/articles/27041
Aviv Regev and Sarah Teichmann et al. The Human Cell Atlas White Paper. (2017) arXiv. https://arxiv.org/abs/1810.05192
Vento-Tormo et al. (2018) Single-cell reconstruction of the early maternal–fetal interface in humans. Nature. https://doi.org/10.1038/s41586-018-0698-6).
Luz Garcia-Alonso et al. (2021) Mapping the temporal and spatial dynamics of the human endometrium in vivo and in vitro. Nature Medicine https://www.nature.com/articles/s41588-021-00972-2
Suoqin Jin et al. (2021) Inference and analysis of cell-cell communication using CellChat. Nature Communications https://www.nature.com/articles/s41467-021-21246-9
Robin Browaeys, Wouter Saelens and Yvan Saeys (2019). NicheNet: modeling intercellular communication by linking ligands to target genes. Nature Methods https://www.nature.com/articles/s41592-019-0667-5
David S. Fischer et al. (2021) Learning cell communication from spatial graphs of cells. bioRxiv https://www.biorxiv.org/content/10.1101/2021.07.11.451750v1
Jonathan Mitchel et al. (2022),Tensor decomposition reveals coordinated multicellular patterns of transcriptional variation that distinguish and stratify disease individuals. bioRxiv https://www.biorxiv.org/content/10.1101/2022.02.16.480703v1
Livnat Jerby-Arnon and Aviv Regev (2022) DIALOGUE maps multicellular programs in tissue from single-cell or spatial transcriptomics data. Nature Biotechnology https://pubmed.ncbi.nlm.nih.gov/35513526/
Jennifer E. Rood, Aidan Maartens, Anna Hupalowska, Sarah A. Teichmann & Aviv Regev. (2022) Impact of the Human Cell Atlas on medicine. Nature Medicinehttps://www.nature.com/articles/s41591-022-02104-7