Nerlov Group: Single Cell Biology and Machine Learning in Blood Development, Cancer and Ageing

Supervisor: Claus Nerlov 

The Nerlov laboratory studies the fundamental processes by which blood (or hematopoietic) stem cells sustain blood cell production throughout life and how ageing and haematological malignancies perturb this process, in order to develop molecularly informed strategies to counteract adverse blood phenotypes.

About the Research 

We use single cell genomic technologies (ATAC-seq and RNA-seq) and advanced genetics to study hematopoietic stem– and progenitor cells in normal development, during ageing and when blood cancers develop. We use computational biology and machine learning to identify the gene regulatory networks that control normal blood formation and the perturbations that occur when adverse phenotypes develop, and employ this knowledge to generate molecularly informed therapeutic strategies for conditions where cell types are dysfunctional (age-associated immune decline), under- or overproduced (anaemia, hypereosinophilia, mastocytosis), premalignant (clonal hematopoiesis (CH)) or malignant (acute myeloid leukaemia (AML), myeloproliferative disorders (MPD).

Modelling and targeting of gene regulatory networks that control normal and dysfunctional hematopoiesis. Blood cells are specified from multipotent hematopoietic stem cells via a series of increasingly lineage-restricted progenitors. To identify the gene regulatory networks that control these successive lineage bifurcations, we will combine RNAseq and ATACseq to identify candidate regulators, which will be validated using in vivo CRISPR-Cas9-based gene manipulation, and physiological and oncogenic perturbations. We will use computational and statistical modelling together with advanced deep learning approaches (algebraic, geometric and topological deep learning) to model the entire blood lineage specification process using multilayer/higher order neural networks to generate a predictive model, which will form the basis for identification and targeting of the regulatory elements that control age- and malignancy-associated phenotypes.

Genetic and computational modelling of clonal hematopoiesis – from the clinic to the lab and back. Clonal hematopoiesis involves the expansion of mutant hematopoietic stem cell (HSC) clones over time, and becomes frequent in humans with age, reaching a prevalence of ~40% at 75 years. While it is well-established that the presence of expanded mutant HSC populations is associated with a 10-fold elevated risk of development of acute myeloid leukemia (AML) we still do not understand why only some mutant HSC clones expand, or why only a subset of these convert to overt malignancy. In particular, the role of ageing and inflammation in the expansion of mutant HSCs remains to be understood. In this project, we will combine genetic modelling of clonal hematopoiesis with in vivo barcoding techniques to measure the frequency with which mutant HSC clones expand and subsequently transform to AML. Single cell transcriptome and epigenome profiling will be used to identify molecular traits associated with disease development. In parallel, clinical samples from patients with clonal hematopoiesis will be analysed using mathematical modelling and single cell profiling to identify potential drivers of malignant progression.  Potential drivers of clonal expansion and transformation will be functionally validated in the mouse models, the overall aim being to identify therapeutically tractable targets.

The role of ageing in leukaemia development and immune decline. Ageing is associated with decreased production of lymphocytes and erythrocytes, leading to anaemia and declining adaptive immunity. We previously showed that a key feature of hematopoietic ageing is increased platelet-lineage bias of HSCs, which directly suppresses lymphopoiesis (Grover et al., Nat Comms. 2016). Through comprehensive molecular profiling of both hematopoietic and stromal cell types from young and aged mice, we have shown that increased TGFb1 and IL-6 signalling in the aged bone marrow regulates this process (Valletta et al., Nat Comms. 2020). We are now investigating how interfering with these signals can counteract ageing of HSCs and associated alterations in the production of blood cells, as well as decrease susceptibility to myeloid malignancies. We are also using genetically accurate models of AML to identify the age-associated changes that contribute to increased prevalence and poor prognosis of AML in elderly patients, with a particular focus on secreted factors that support leukemia progression as putative therapeutic targets. Finally, we have used deep learning to identify ageing programs shared by mice and humans in both hematopoietic stem cells and T-cells – this modelling will be used to perform cross-species identification and pharmacological targeting of regulators of hematopoietic ageing.

This project is not suitable for part-time research.

Training Opportunities

Training is available in the areas of HSC and progenitor biology, biology and treatment of myeloid malignancies, biology of ageing, transcription factor biology, cytokine biology, single cell analysis of HSC/progenitor function, single cell functional genomics (RNAseq, ATACseq), advanced flow cytometry, advanced mouse genetics, CRISPR/Cas9-based genome editing and library screening technologies, advanced bioinformatics, mathematical/statistical modelling and advanced deep learning.

Students will be enrolled on the MRC Weatherall Institute of Molecular Medicine DPhil Course, which takes place in the autumn of their first year. Running over several days, this course helps students to develop basic research and presentation skills, as well as introducing them to a wide range of scientific techniques and principles, ensuring that students have the opportunity to build a broad-based understanding of differing research methodologies.

Generic skills training is offered through the Medical Sciences Division's Skills Training Programme. This programme offers a comprehensive range of courses covering many important areas of researcher development: knowledge and intellectual abilities, personal effectiveness, research governance and organisation, and engagement, influence, and impact. Students are actively encouraged to take advantage of the training opportunities available to them.

As well as the specific training detailed above, students will have access to a wide range of seminars and training opportunities through the many research institutes and centres based in Oxford.

The Department has a successful mentoring scheme, open to graduate students, which provides an additional possible channel for personal and professional development outside the regular supervisory framework. We hold an Athena SWAN Silver Award in recognition of our efforts to build a happy and rewarding environment where all staff and students are supported to achieve their full potential.

Additional supervisors 

1. Paresh Vyas

2. Bethan Psaila

3. Pietro Lio

Publications