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Work packages

A short description of each WP, which includes its objectives, methodology, and deliverables, is given below:

Work Package 1: Quantification of T lymphocyte dynamics by in vivo labelling

Recruited researchers:
Pedro Costa del Amo (ESR1) at Imperial
Mariona Baliu Pique (ESR2) at UCMU
Julio Lahoz Beneytez (ESR3) at Bayer

Research question: understanding the behaviour of peripheral T cells with mathematical and computational models and in combination with experimental data.

Objectives: quantification of the proliferation and death rates of defined lymphocyte populations in vivo, during healthy ageing and during immune reconstitution, in mice and men; study the spatial distribution of compounds (such as glucose) through the human and murine body; establish whole-body physiologically-based pharmacokinetic (PBPK) models including relevant lymphoid organs.

Methodology: stable isotopes (deuterium in the form of deuterated glucose or deuterated water) to label the DNA of dividing cells; deuterium enrichment data will be modelled by means of ordinary differential equations (ODEs)to determine the rate of turnover of specific, phenotypically defined lymphocyte populations, including naive and memory CD4+ and CD8+ T cells and regulatory T cells; extension of generic Bayer whole-body PBPK models15,18.

Deliverables: estimates for the death and division rates of naive and memory CD4+ and CD8+ T cells and regulatory T cells during healthy ageing and immune reconstitution, in both mice and humans; generic whole-body physiologically-based pharmacokinetic (PBPK) models extended by relevant lymphoid organs; PBPK models to describe label pharmacokinetics; framework to model lymphocyte populations on an organism scale; three trained scientists: ESR1, ESR2 and ESR3.

Work Package 2: Quorum sensing of CD4+ T cell populations: establishment and immunological challenge

Recruited researchers:
Sary El Daker (ER1) at Institut Pasteur
Luis de la Higuera Romero (ESR4) at Leeds

Research question: determine the role of IL-2 producing (IL-2p) and regulatory CD4+ T cells (T regs) in the establishment of the populations in the periphery and during immune responses.

Objectives: determine the specific niche of IL-2p CD4+ T cells; investigate the role of IL-2 in the regulation of IL-2p CD4+ T cells; determine the interplay between IL-2p CD4+ T cells and T regs in the contraction phase of an immune response.

Methodology: use in vivo experiments to track IL-2p and regulatory cells during the establishment and during immune responses (flow cytometry, histology and confocal microscopy); deterministic and stochastic mathematical models of CD4+ T cell populations that include cell division, death, differentiation, IL-2 production and suppression; van Kampen approximation and Gillespie algorithm; multi-variate statistical analysis.

Deliverables: understanding of the role of regulatory CD4+ T cells in the control of T cell homeostasis, anti-viral and anti-tumour immune responses and autoimmune diseases; tested, validated and refined mathematical models of CD4+ populations; two trained scientists: ER1 and ESR4.

Work Package 3: Evaluation of CD8+ T cell numbers and repertoires

Recruited researchers:
Pedro Goncalves (ER2) at INSERM
Marco Ferrarini (ESR5) at Leeds
Yaxuan Yu (ESR6) at NUI Galway

Research question: determine the number and the TCR repertoire diversity of the naive CD8+ T cell pool and the expansion and contraction rates and repertoire selection during immune responses.

Objectives: optimise deep-sequencing approaches to allow the evaluation of rare CD8+ T cell populations; determine clonal sizes and repertoire diversity at the peak of the immune response and in the CD8+ T cell memory pool; develop bio-informatics resources for the analysis of deep TCR sequencing data; develop mathematical models of TCR diversity of naive and memory populations.

Methodology: high-throughput sequencing and MHC tetramer technologies; single-cell RT-PCR to study expression of the TCR chains and to allow evaluation of their usage; LCMV infection models in the B6 mouse; bio-informatics and statistical analysis; multi-variate competition stochastic processes.

Work Package 4: Defining the branch-point between short-lived effector and long-lived memory T cells.

Recruited researchers:
Aridaman Pandit (ER3) at UU
Ali Can Sahillioglu (ESR7) at NKI
Saikrishna Gadhamsetty (ER4) at Bayer

Research question: define the branch-point between short-lived effector and long-lived memory T cells.

Objectives: determine at what point during T cell responses, daughter cells commit to either short-lived or longlived fate; determine if the time of commitment is influenced by infection conditions; establish whole-body T cell migration model.

Methodology: CFSE labelling and barcoding (tracing and bio-informatics); deterministic and stochastic mathematical modelling (branching processes). Whole-body model framework (developed in WP1) to describe T cell migration between blood, lymph, and relevant lymphoid organs based on experimental data.

Deliverables: deep-sequencing data on T cell commitment; experimental infectious models; mathematical models to analyse CFSE data; bio-informatics analysis of deep-sequencing data; mathematical models of clonal expansion and differentiation (stochastic branching processes); whole-body T cell migration model; three trained scientists: ER3, ESR7 and ER4.

Work Package 5: Can T cell signal integration be understood through competing stochastic processes?

Recruited researchers:
Giulio Prevdello (ESR8) at NUI Maynooth
Harry Tideswell (ESR9) at NUI Maynooth

Research question: can T cell signal integration be understood through competing stochastic processes?

Objectives: test the hypothesis that T cell signal integration during an adaptive immune response should be viewed as impacting upon the parameters of stochastic programmes for times to differentiation, death and division fates; determine the impact of various signals on this stochastic machinery in order to develop an appropriate paradigm for identifying signal manipulation to achieve desirable population-level outcomes of cell-type distribution and of total cell numbers.

Methodology: experiments to be carried out at WEHI; flow cytometry techniques to measure population level behaviour and bio-informatics methodologies to identify cohort level genetic components; in vitro time lapse microscopy techniques in order to record per-cell level information on time to differentiate, die and divide post-exposure to a mitogenic stimulus; perform experiments varying key signalling T cell inputs: affinity and concentration of ligands; co-stimuli such as CD28; and cytokines such as IL-2; stochastic processes, model fitting techniques, data comparison and feedback to experimental data.

Deliverables: protocol for T cell in vitro microscopy; per-cell data sets reporting times to differentiate, divide and die of T cells when exposed to distinct stimuli conditions; models based on stochastic processes and model fitting techniques for data comparison; two trained scientists: ESR8 and ESR9.

Work Package 6: Cytokine memory in T cells

Recruited researchers:
Melania Barile (ESR10) at DKFZ
Domonkos Varga (ESR11) at Charité

Research question: how does the plasticity of cytokine memory in Th cells emerge from molecular interaction networks of signal transduction and gene regulation.

Objectives: define the network mechanisms of cytokine memory in T cells based on time-resolved measurements of transcriptome, microRNA, protein expression and signalling on primary T cells in iteration with mathematical modelling.

Methodology: time-resolved measurements of the transcriptome and microRNA in primary CD4+ T cells ex vivo; flow cytometry to quantitate key protein concentrations and signal-transduction dynamics with single-cell resolution; perturbations of physiological differentiation will be studied with the help of transgenic mouse models; mechanistically-based mathematical models, formulated in terms of deterministic and stochastic dynamical systems.

Deliverables: comprehensive quantitative time courses of cytokine-induced Stat1/4/5/6 activity during Th cell differentiation and plasticity; genome-wide, time-resolved mRNA and microRNA profiles during Th1/2 differentiation and plasticity; network chart for the interaction Th1- and Th2-inducing differentiation pathways based on experimental data; deterministic kinetic model of the interplay between Th1- and Th2-inducing differentiation pathways; stochastic gene-regulatory network model of master transcription factor regulation in Th cell plasticity; two trained scientists: ESR10 at DKFZ and ESR11 at Charite.

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Last update: 11 June 2017