Single-cell multi-omics of leukemic and healthy stem cells

Acute Myeloid Leukemia (AML) develops through sequential genetic lesions in hematopoietic stem cells (HSCs). For example, preleukemic HSCs (pHSCs) already carry mutations present in AML (e.g., DNMT3A or TET2), but retain their ability to differentiate into healthy blood cells. The acquisition of additional mutations in these cells eventually leads to AML with chemo-resistant leukemia stem cells (LSCs) at the top of a cellular hierarchy. Targeted therapies of LSCs to improve the clinical outcomes of AML patients is an area of active research, but a major challenge remains: LSCs, preleukemic HSCs, healthy HSCs, and leukemia cells lacking stem cell properties (called blasts) are difficult to separate using conventional methods. Only combined genome and transcriptome analyses of individual cells have the potential to clearly distinguish between healthy blood stem cells, pre-leukemic cells and leukemia cells with and without stem cell properties. Together with Dr. Simon Raffel (University Clinics Heidelberg) we are generating such single-cell multi-omics datasets to systematically identify LSC-specific markers, biological processes, and potential therapeutic targets. In the future, we plan to apply similar clonal tracking approaches also to the study of lineage dynamics in healthy hematopoiesis.

Single cell and synthetic genomics of gene regulatory elements

During cellular development and differentiation, genetic information needs to be activated in a precise and highly controlled manner. For example, the differentiation of hematopoietic stem cells to mature blood and immune cells involves the coordinate activation and inactivation of 100s of genes with very distinct activity patterns across cell types and differentiation stages. It is therefore evident that a complex regulatory logic connects the current cellular state, cell-extrinsic signals, and gene expression.

Ultimately, the decision as to which genes become active is made in cis, by the integration of signals at promoters and enhancers. To that end, transcription factors present in a given cell interact on DNA via complex rules involving cooperativity, synergies and antagonisms. However, these rules are poorly understood, and it therefore remains unclear how the DNA sequence of promoters and enhancers coordinates gene expression during development and differentiation. In particular, a quantitative understanding of the cis-regulatory grammar of gene regulation during cellular differentiation is lacking. 

In a project funded by the Spanish ministry of science and innovation, we combine synthetic biology, single cell genomics and deep learning to study the regulatory grammar of enhancers in the hematopoietic system.

In the past we have created maps of enhancers and their target genes by using a combination of pooled CRISPR screens and single cell transcriptomics. Reference: Schraivogel et al., Nature Methods 2020