Grant: Discovery Grants Program - Individual
The University of British Columbia
$138,000.00
Super-resolution imaging, single cell analysis, and modelling approaches applied to the study of immune cell signaling and behaviour
FY 2024-25
Summary
Cells of the immune system, such as B cells, sense their environment using an array of specialized surface receptors. Upon binding a suitable ligand, these receptors generate intracellular signals, allowing the cell to respond appropriately to a given stimulus. During cellular stimulation, surface receptors reorganize their movement and location. For example, B cell antigen receptors (BCR) are observed to change the form of their nanoscale clusters on the cell surface. Our understanding of how receptor signaling leads to changes in receptor motion, and how these dynamic changes affect subsequent signaling, is a key part of our knowledge of the processes governing lymphocyte activation. The main objective of this proposal is to perform quantitative analysis of B cell receptor motion and organization. This will be done using a combination of super-resolution imaging and other microscopic imaging approaches, supported to a great extent by mathematical modeling.
We will use imaging of single labelled receptors to study the motion of chosen surface molecules on B cell lines, during different activation states of the B cell. Snapshots of their spatial distribution will also be made using super-resolution imaging of fixed cells. Using multicolour labelling we will investigate relative motion, co-localization and co-clustering of multiple receptor molecules. Photoactivatable fluorescent tags will be exploited to obtain, sequentially, a very large number of individual tracks from a single cell.
Mathematical and computational tools will be developed with two main themes of analysis. The first theme is to support improved experimental interpretation, through image / movie analysis of single particle tracking and live cell imaging data, clustering analysis applied to fixed cell super-resolution images, and refined approaches to handling high-dimensional data in understanding cell phenotypes. The different parts of this theme build on extensive recent projects in my group. The second theme is to develop spatiotemporal mathematical models of immune receptor signaling, with the goal of improving our understanding of how spatial effects modulate cell signalling. This theme links back to my earlier work on T cell signalling.
Overall, the proposed work seeks to bring precision to models of immune receptor motion and signaling. The future effects of this work will be in the biomedical field with eventual applications in disease process studies and drug discovery/design. Although we will use B cell signaling as the model system, our techniques and results will be generally applicable to other immune cells such as T cells and Natural Killer cells. The experimental approaches proposed are state-of-the-art and the combination with development and fitting of new mathematical models is extremely unusual. Hence, the proposed work forms a perfect basis for training of highly qualified personnel at the interface between cell biology and the mathematical sciences.
Program
Discovery Grants Program - Individual
Recipient
Location
British Columbia, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data
As published
Application id
RGPIN-2020-04820
Name nom
Coombs, Daniel
Department département
Mathematics - Mathematics
Organization id
2
Institution établissement
The University of British Columbia
Province en
British Columbia
Province fr
Colombie-Britannique
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2024
Competition year année de concours
2020
Award amount
138000
Program id
RGPIN
Program name en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
DISCOVERY RESEARCH
Group fr
RECHERCHE AXÉE SUR LA DÉCOUVERTE
Committee code
1501
Committee name en
Genes, Cells and Molecules
Committee name fr
Gènes, cellules et molécules
Area of application code
1201
Area of application group en
Advancement of knowledge
Area of application group fr
Avancement des connaissances
Area of application en
Life sciences (including biotechnology)
Area of application fr
Sciences de la vie (y compris biotechnologie)
Research subject code
5103
Research subject group en
Cell biology
Research subject group fr
Biologie cellulaire
Research subject en
Cell membranes
Research subject fr
Membranes cellulaires
Field of research list names en
Not available
Field of research list names fr
Non disponible
Socioeconomic objective list names en
Not available
Socioeconomic objective list names fr
Non disponible
Application title
Super-resolution imaging, single cell analysis, and modelling approaches applied to the study of immune cell signaling and behaviour
Keywords
immune cell signaling; b lymphocytes; super-resolution microscopy; flow cytometry; mass cytometry; mathematical modelling; image analysis; single particle tracking
Application summary
Cells of the immune system, such as B cells, sense their environment using an array of specialized surface receptors. Upon binding a suitable ligand, these receptors generate intracellular signals, allowing the cell to respond appropriately to a given stimulus. During cellular stimulation, surface receptors reorganize their movement and location. For example, B cell antigen receptors (BCR) are observed to change the form of their nanoscale clusters on the cell surface. Our understanding of how receptor signaling leads to changes in receptor motion, and how these dynamic changes affect subsequent signaling, is a key part of our knowledge of the processes governing lymphocyte activation. The main objective of this proposal is to perform quantitative analysis of B cell receptor motion and organization. This will be done using a combination of super-resolution imaging and other microscopic imaging approaches, supported to a great extent by mathematical modeling.
We will use imaging of single labelled receptors to study the motion of chosen surface molecules on B cell lines, during different activation states of the B cell. Snapshots of their spatial distribution will also be made using super-resolution imaging of fixed cells. Using multicolour labelling we will investigate relative motion, co-localization and co-clustering of multiple receptor molecules. Photoactivatable fluorescent tags will be exploited to obtain, sequentially, a very large number of individual tracks from a single cell.
Mathematical and computational tools will be developed with two main themes of analysis. The first theme is to support improved experimental interpretation, through image / movie analysis of single particle tracking and live cell imaging data, clustering analysis applied to fixed cell super-resolution images, and refined approaches to handling high-dimensional data in understanding cell phenotypes. The different parts of this theme build on extensive recent projects in my group. The second theme is to develop spatiotemporal mathematical models of immune receptor signaling, with the goal of improving our understanding of how spatial effects modulate cell signalling. This theme links back to my earlier work on T cell signalling.
Overall, the proposed work seeks to bring precision to models of immune receptor motion and signaling. The future effects of this work will be in the biomedical field with eventual applications in disease process studies and drug discovery/design. Although we will use B cell signaling as the model system, our techniques and results will be generally applicable to other immune cells such as T cells and Natural Killer cells. The experimental approaches proposed are state-of-the-art and the combination with development and fitting of new mathematical models is extremely unusual. Hence, the proposed work forms a perfect basis for training of highly qualified personnel at the interface between cell biology and the mathematical sciences.