A protein-transcriptome atlas of haematopoiesis across the human life span

The cell represents a fundamental unit of biology, as all of our organs are composed of cells, where cells with different specialized functions combine to provide overall functionality. Specialization of cells is perhaps best understood in the blood system, where red blood cells for example are dedicated to carrying oxygen round the body, while a myriad of specialized immune cells help to fight infections. A better understanding of the molecular features that characterize individual cells is not only essential for us to gain a better understanding of how the human body functions normally, but also to be able to design better drugs that can reverse the abnormal behaviour of cells, which causes many diseases including blood cancers and immune disorders.

Recent technological innovations have made it possible to map very comprehensively the activity of all genes within single cells, at a scale of thousands of cells at the same time. We propose to utilize one of the latest protocols in this field to map both messenger RNA as well as protein levels, and thus obtain especially detailed insights into the molecular make up of over 550,000 individual blood and immune cells across the human lifespan. Through integration with the wider Human Cell Atlas Initiative, our datasets will deliver an important reference, that will serve as a platform for future studies aiming to reveal the molecular alterations that cause the misbehaviour of blood cells in a broad range of disorders including blood cancers and immune diseases.

The recent development of Cite-Seq technology coupled with the commercialization of dedicated antibody and droplet-based sequencing reagents represent a golden opportunity to generate a comprehensive Cite-Seq dataset to complement ongoing projects across the Human Cell Atlas Initiative. We have assembled a team of PIs with expert knowledge of human fetal and adult haematopoiesis as well as single cell molecular profiling techniques, complemented with expert collaborators with specialist knowledge of experimental and computational aspects of Cite-Seq technology.

Cite-Seq technology enables the joint profiling of mRNA and protein from the same single cells using high-throughput next generation sequencing technology. The specific aims of our proposal are to (i) use Cite-Seq to generate combined protein and transcriptome profiles for over 550,000 haematopoietic progenitor and mature cells across the human lifespan, and (ii) to integrate the resulting datasets into the Human Cell Atlas data platform and establish pipelines for single cell multi-omics analysis. Subfractionation based on CD34+ and CD34- cell subsets will provide the progenitor and mature populations respectively. Samples will be obtained from fetal liver, yolk sac, and bone marrow, newborn cord blood, adult bone marrow and spleen and aged adult bone marrow. Sample acquisition will occur under already existing ethics permissions, thus ensuring that the project can start without any delay.

The proposed Cite-Seq datasets for haematopoietic progenitor and mature cells across the human lifespan will provide a multiomic resource highly complementary to currently ongoing HCA projects. Development of data analysis and data integration pipelines will furthermore provide important guidance for future adaptation of the Cite-Seq method not just to projects mapping other tissues, but also to investigators studying blood and/or immune cell disorders.

Generation of a comprehensive protein-transcriptome atlas of haematopoiesis across the human lifespan is likely to have substantial impact across a range of stakeholders of MRC-funded research, as outlined below:

Human Cell Atlas Initiative: The work proposed here represents the first concerted effort to employ Cite-Seq technology in a systematic fashion to map single cell states for a major human organ across the lifespan. The resulting dataset therefore has potential to constitute a significant component of the HCA in itself. Moreover, lessons learned from computational analysis and data integration are likely to be broadly useful for future HCA-directed analysis of other organ systems, including tools that can map between spatial data (Hyperion CyTOF) and suspension cell single cell profiling by Cite-Seq, where measurement of the same proteins with both assays serves as a common denominator to facilitate data integration.

Broader biomedical research community: The open access philosophy of the HCA means that our datasets will be freely available to the broader community at the earliest opportunity. Likely applications will include the use of our dataset as a reference to assess perturbations, either experimentally induced or when studying patient samples. The computational analysis pipelines will also represent a platform for the bioinformatics community to develop tools for the analysis of single cell multiomic datasets.

Industry: The pharmaceutical and biotech industry critically depends on high-level characterisation of preclinical model systems, to enable the creation of better disease models and thus reduce the exorbitant costs associated with late stage failure in drug development programmes. Single cell molecular profiling is rapidly recognised as a potentially very powerful analytical technique for the characterisation of all biological systems, including disease and preclinical models. A particularly attractive feature of Cite-Seq in this context is the multidimensional nature of the data, including comprehensive information on protein expression.

Training: Although the experimental staff requested for this project is small, and taking advantage of existing expertise across the PIs' laboratories, there is a substantial need for training more young scientists in computational analytical techniques. In this context, the computational post offers exciting opportunities. The lead PI has a strong track record in training young bioinformaticians, evidenced for example by the fact that his former postdoc David Ruau currently fulfils the very senior role of Head of Data Science at Bayer, and his former postdoc Anagha Joshi is a full professor at the University of Bergen. Moreover, the named collaborators John Marioni and Rahul Satija are both internationally leading in the field of computational single cell biology.

General Public: Although relatively small on its own, the work proposed here will form a component of the wider HCA Initiative, which regularly receives news coverage in both the international and national press. We will work with our press and outreach teams in Cambridge and Newcastle, to reach out to the public locally and across the UK, with the overall goal of increasing the public understanding of science and the importance of public buy-in for large initiatives such as the HCA. To this end, we also aim to take advantage of occasions where the broader HCA project is in the news, so that we can highlight contributions made through MRC funding.