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  • Project No: NC-16
  • Intake: 2024 KIR Non Clinical


Granulopoiesis, the generation of new neutrophilic granulocytes, is crucial to health. During healthy neutrophil development its nucleus goes through dramatic morphological changes, from a simple round nucleus to a multi-segmented, lobulated nucleus. Indeed, the nuclear morphology is the main parameter used by pathologists to define the states of human neutrophil development. However, the molecular mechanisms controlling nuclear segmentation and the functional impacts of it are not understood.

Chromatin architecture is what connects global nuclear shape and local regulation of gene expression. Chromatin is organized into distinct compartments within the nucleus and further segregated into spatially distinct regions. While neutrophils develop from progenitor cells to their multi-lobed form, long-range interactions are induced, leading to the chromatin contraction that may facilitate the folding of the neutrophil genome into the confined geometry of a toroid and segmented nucleus [1]. Our recent work and results of others clearly demonstrate that neutrophils acquire different functions, such as production of reactive oxygen species, secretion of inflammatory molecules, formation of neutrophil extracellular traps, phagocytosis, bacterial killing etc, at different stages of their differentiation [2,3]. Moreover, we have identified and validated several key transcriptional regulators of neutrophil morphological development and/or functional responses [4]. This indicates that the transcriptional programming of morphological and functional maturation may be partially intertwined and are likely to be connected via changes in chromatin architecture.

Here we will apply cutting edge chromatin conformation assays and gene expression analysis to correlate dynamic changes in the chromatin organization of the neutrophil genome to changes in gene expression and acquisition of specific functions during neutrophil maturation. Specific objectives:

1.  To capture global chromatin topology changes during neutrophil differentiation using various cutting edge chromatin conformation capture (3-C) analyses of neutrophils throughout the differentiation trajectory [5]. Established computational pipelines would be used for visualization of contact maps, chromatin compartment analysis, chromatin compaction analysis, and finding differentially enriched topologically associating domains. The experimental setup would be used to assess changes to chromatin topology when key transcription factors for neutrophil development are depleted.  

2. To identify regions of local ‘topology dependent’ open and closed chromatin using ATAC-seq analysis to classify regions that show chromatinization changes (open/closed) in regions that gain/loss chromatin interactions. Single-cell ATAC-seq would be used for accessing heterogeneity in local chromatin conformation.

3. To identify chromatin topology-dependent gene expression alterations using RNA-seq analysis to pin point genes that show topology and chromatin changes in their regulatory promoter/enhancer regions along the differentiation trajectory. The identified gene list will be checked for motifs for the previously identified key transcriptional regulators and validated in neutrophils with specific knock-out of these factors.

The outcomes of this study are expected to unravel the regulation and functional consequences of the fundamental biological process, such as segmentation of neutrophil nucleus during the differentiation. This will lead to setting up a framework for further analysis of selective perturbations to this process during immunopathologies.



Neutrophils, transcriptional regulators, computational genomics/epigenomics, spatial transcriptomics, mathematical modelling



The Kennedy Institute is a world-renowned research centre and is housed in a state-of-the-art research facility. Training will be provided in a wide range of functional genomics approaches (e.g. RNA-Seq, ATAC-Seq, ChIP-Seq etc), immunological (cell isolation, tissue culture, FACS), and imaging (immunofluorescence on tissue sections) approaches, as well as cutting edge single cell platforms (10x, Nanostring GeoMx, Nanostring CosMx) and computational pipelines. Recently developed novel in vivo models of inflammatory diseases will be extensively used and new models will be generated.  A core curriculum of lectures will be taken in the first term to provide a strong foundation across a broad range of subjects, including musculoskeletal biology, inflammation, epigenetics, translational immunology and data analysis. The student will attend weekly seminars within the department and those relevant in the wider University. They will present their research regularly to the department and the Genomics of Inflammation group, and at the Computational Genomics Forum. They will also attend external conferences at which they will present their research to a global audience.  The student will also have the opportunity to work closely with members of the Genome Biology laboratory, MRC Weatherall Institute of Molecular Medicine, University of Oxford, and to further broaden their experimental expertise and theoretical knowledge of the chromatin organisation in health and disease.



(1)        Zhu, Y. … Murre C. Comprehensive characterization of neutrophil genome topology. Genes Dev 2017 Jan 15;31(2):141-153

(2)        Ballesteros I, … Udalova IA, Ng LG, Ostuni R, Hidalgo A. Co-option of Neutrophil Fates by Tissue Environments. Cell. 2020 Nov 25;183(5):1282-1297.e18.

(3)        Wang L, Luqmani R, Udalova IA. The role of neutrophils in rheumatic disease-associated vascular inflammation. Nature Reviews Rheumatology. 2022 Mar;18(3):158-170.

(4)        Khoyratty T*, Ai Z*, …, Udalova IA. Distinct transcription factor networks control neutrophil-driven inflammation. Nature Immunology, 2021 Sep;22(9):1093-1106.

(5)        Oudelaar AM, …, Hughes JR. Dynamics of the 4D genome during in vivo lineage specification and differentiation. Nature Communications. 2020 Jun 1;11(1):2722.



Immunology; Computational Genomics; Spatial transcriptomics; Mathematical modelling



Prof Irina Udalova,

Prof Jim Hughes,;

Dr Ananda Mukherjee,