Researchers receive an updated look at the Human Cell Atlas, and it is remarkable
Atlas of Human Neural Organoid Cells of the Gungurial Tract: An Investigation of Metaplasticity in Infants and Infants
Single-cell sequencing is a rapidly evolving field in which technological advances continuously reshape scientists’ understanding and definitions of cell identities. Atlases such as the HCA will probably remain as ‘living resources’, adapting to incorporate new data and discoveries. Innovative frameworks in machine-learning methods are offered by this fast-growing data source. However, as with any field that is dependent on rapidly changing data, models trained on existing data sets will have limited lifespans; they are finely tuned to the specific data sets used in training and might require adaptation as data emerges and data-collection biases evolve.
The gastrointestinal tract is divided into five parts: mouth through to the stomach, intestines, and colon. Many previous data sets have been created, but the present atlas deftly integrates these — using an innovative computational approach — into a large-scale atlas of 1.1 million cells, along with annotations of the resident cell types and states. The authors of this map put together a gastrointestinal data sets from people who have inflammatory diseases like Crohn’s disease and coeliac disease. Intestinal inflammation can cause cells to undergo metaplasia, a shift from one cell type to another. By analysing the layered data sets, the authors inferred the origin of these metaplastic cells by comparing them with stem cells in the atlas. This insight highlights the benefit of the atlas’s completeness, which allows for the comparison of disease states in one organ with the normal states of cells in different organs.
Organoids have become a very useful model for analyzing the function of the brain. A human neural organoid cell Atlas was created by combining 36 single-cell data sets with 26 protocols for making organoids from cultured cells. The question of how faithfully organoids capture the parts of the developing brain that are not covered in the atlas is being shed light on. The authors found a correspondence between the length of time the organoids were in culture and the developmental stages that they resemble in the human brain: in the first three months of culture, the organoid resembles the cellular state of the fetal brain during the first trimester of pregnancy, whereas in the next three months, it resembles the second trimester. The authors found an interesting limit to the correspondence. Fetal brain during the last trimester of pregnancy was not captured, leaving an open question as to what signals are missing from organoid models.
Yayon et al.4 created a map of the thymus, a lymphoid organ that produces immune cells, in its early fetal development and early postnatal stages. Using spatial coordinates, they created a framework to map the tissue. This model of the axis between the outer part of the thymus and its centre (the cortico-medullary axis) allows for a deeper understanding of tissue organization and comparison of the organ both in and between individuals. It will be interesting to study how this atlas extends to other stages of life, such as old age.
The studies give an important foundation for understanding early development in humans. However, findings related to cellular relationships, cellular crosstalk and the establishment of tissue architecture are mostly based on inferences from transcriptomic data, and should therefore be considered as hypothesis-generating discoveries. Future advances in organoid technologies and other mechanistic models will be essential to validate and expand these findings.
Fetal and embryonic development of the skull and joints of the limbs was studied by To and colleagues. Through the simultaneous mapping of transcriptomic and epigenetic profiles of single cells, they identified keygene-regulatory networks that direct the commitment of cells to bone formation. The authors inferred probable lineage relationships along differentiation pathways and propose how cellular crosstalk might guide the formation of bone, identifying a potential key role for interactions with the vascular system. The authors used an elegant approach to integrate the data from association studies with their single-cell analysis to identify cell states that may be linked to osteoarthritis in the adult skeleton.
Gopee and colleagues present a comprehensive cellular Atlas of skin development within 7–17 weeks after conception. In using a combination of single-cell and spatial transcriptomic technologies, the authors mapped dynamic changes in cell states and details how these cells organize to form complex structures and interact with skin niches. Their findings highlight the unexpectedly diverse role of immune cells in coordinating developmental processes, particularly the involvement of macrophages in the formation of blood vessels by endothelial cells. The innovative organoid system recapitulates the key aspects of skin development.
PopV is a model for moving cell-type labels from annotated atlases to unannotated data sets. The popV model is an ensemble model, which means that it combines classification predictions from existing models to produce both cell-type labels and uncertainty scores based on the degree of disagreement between the underlying tools. This approach highlights ambiguous cases, which reduces manual review, and draws attention to cell populations that are challenging to classify. This feature enhances the interpretability of results and streamlines the overall annotation process by reducing the load on researchers, making popV adaptable to future models.
The MultiDGD model integrates multiple data points such as gene expression and accessibility of chromatin into a single model. This type of machine learning uses hidden variables to learn patterns without the need to identify important features. MultiDGD enables post-hoc data integration across data sets, making it suitable for multi-omics studies, in which data were gathered from different sources. An essential step in understanding gene-regulatory networks is to understand the associations between genes and regulatory regions of the genome, which can be accomplished by clustering shared representations.
Together, popV and scTab lead efforts in standardized annotation and consensus-building, whereas multiDGD opens up avenues for data integration across complex multimodal data sets.
The impact of these methods is not lessened by this, it highlights the field’s rapid pace and importance of innovation. Future research is likely to include solutions that can be adapted. These methods contribute valuable foundations for future advancements, paving the way for even more adaptable and scalable models for single-cell, multi-omics data.
The Human Cell Atlas: What’s Happening after a Decade after the Global Project, and Where are We Going? (A Wikipedia for Cells, and Its Remarkable)
Coming less than a decade after its launch, the studies emerging from the global project are a major achievement. Funders should sign up for the long haul.
Findings from researchers working on the lung cell atlas, for example, highlight the differences between the lungs of a sample of people in Malawi who died from COVID-19 and those who died from other lung diseases2. Scientists have also been studying the development of organs during gestation, for example, through analyses of prenatal human skin3 and developing joints and craniums4.
The HCA would not have been possible without earlier projects, notably the Human Genome Project and, more recently, the NIH BRAIN Initiative, as well as ENCODE, a project to build a ‘parts list’ of functional elements in the human genome. The HCA teams have also worked hard to reflect human diversity in their data. The consortium includes scientists from Africa, Asia, Latin America and the Middle East5. HCA invited researchers from these regions to join, as well as help lead and coordinate HCA projects according to priorities relevant to local populations. The initiative involves more than 3000 scientists who are recording and studying data from around the world.
Large-scale consortiums are among research projects with a limited lifespan. Ten years is considered generous. A handful of projects might last a few years longer. Permanent funding tends to be reserved for projects of national or international importance, including essential infrastructure — the tools and technologies without which vital discoveries and inventions would not be possible. That is what the HCA needs to be compared to.
What do HCA researchers really know about disease-associated variants? A comment from the Human Genome Molecular Analytical Association (HCA)
More than 100,000 disease-associated variant have been mapped in the human genome, but HCA researchers write that they don’t know which cells are active. Without this knowledge, they say,we can’t fully understand biology, study more powerful models of disease, deploy better diagnostics and develop more effective therapies.
A team of international researchers has developed a Human Neural Organoid Atlas of 1.1 million cells, which they hope will lead to a better understanding of how metaplastic cells develop in human infants and children. The atlas was developed by combining 36 single-cell data sets with 26 protocols for making organoids from cultured cells.