MODELLING THE HUMAN IMMUNE RESPONSE

Transcription

1 MODELLING THE HUMAN IMMUNE RESPONSE Professor John Gordon MRC Centre for Immune Regulation Institute of Biomedical Research The Medical School Birmingham, UK Slides available for download at:

2 The Need DISEASE BURDEN relevant to the Immune System: Infection Inflammation Autoimmunity Allergy Transplantation Cancer When System GOOD: How do we harness, bolster, redirect to improve the response? When System BAD: How do we dampen, switch off, redirect to lessen the response?

3 MAJOR ISSUES Animal models prevail In vitro modelling crude

4 MAJOR ISSUE 1 Animal models prevail

5 Mice are Potent Vehicles for Genetic Manipulation to Address How the Immune System Operates (in Rodents) by: Knocking in Knocking out Shaking it all about of specific genes to perturb their immune responses But...

6 Spot the difference NO MOUSE?

7 Speciation Speciation 50 million years

8 Not just Tails & Whiskers Mice cf. to Us are: 3000x smaller 100x faster growth rate 30x more rapid aging 40x lower living horizon Diet, habitat, survival, reproduction strategies, etc, etc Then there is: The Enemy Within...

9 Living with the Enemy Viruses Bacteria Parasites Allergens Evolve or or Die

10 Non-optimised Immune System = Death from EBV-infection 3 Million years of coexistence/coadaptation Epstein-Barr virus Healthy Happy Immuno-compromised New World Primates Old World Primates X Malaria Cyclosporin A HIV Dead

11 The human immune system has undoubtedly been shaped by its coevolution with EBV and its ancestors. Every component of humoral, innate, and adaptive immunity is brought to bear on the virus and virally infected cells. NEJM (2006) 355: 2708 George Miller, M.D. Yale University School of Medicine New Haven, CT 06520

12 (Selectable) HIV Protection CCR5 Chemokine Receptor Mutation A mutation in the CCR5 chemokine receptor gene has been discovered that provides protection against infection by HIV-1, the most common strain in North America The CCR5-Delta32 deletion mutation has been found with a high frequency in European populations, but has not been found in African, Asian, Middle Eastern and American Indian populations. The frequency of the resistance allele is estimated at approximately 10% in European populations.

13 Modeling Infectious Disease in Mice: Co-Adaptation and the Role of Host-Specific IFNγ Responses PLoS Pathog May;5(5):e Coers J, Starnbach MN, Howard JC Stark Differences Exist between the Murine and Human IRG* Resistance Systems *GTPases named p47 Immunity Related GTPase The inherent resistance of mice to highly adapted human pathogens should not be a surprise: because pathogens co-evolve with and adapt to their preferred host, their successful specialization often renders them highly dependent on their host species. Such host tropism or host restriction limits the usefulness of the mouse as a model for infectious disease research.

14 MAJOR ISSUE 2 In vitro modelling crude 1. Cell lines 2. PBMC

15 Cultured Cell Lines: An Industry Norm Useful for Tox screens and 1st look&-see Scant Relevance to Physiological Immune Cell Behaviour e.g. Lymphoblastoid Cell Lines EBV drives in B cells uncontrolled enlargement, activation, homotypic clustering, proliferation, & fixes differentiation status by viral gene products hijacking central B-cell physiological signaling pathways (e.g. BCR & CD40)

16 Peripheral Blood Mononuclear Cells: An Industry Norm WHITE BLOOD CELLS PBMC Neutrophil 65% Eosinophil 4% Basophil <1% Level of resolution typically investigated = PBMC (peripheral blood mononuclear cells): Poor level of resolution - due to masking of drug impact on critical or undeveloped subsets in native PBMC (small percentage populations) Incomplete predictive track record Lymphocytes 25% Monocyte 6% [Percentages shown represent percentage of total white blood cell population]

17 The Complex Layers of PBMC WHITE BLOOD CELLS PBMC Neutrophil 65% Eosinophil 4% Basophil <1% Lymphocytes 25% Monocyte 6% Dendritic cells Th1 <3% B cells 5% NK cells 4% T cells 16% Naïve B cells 3% Memory B cells 2% CD4 T cells 10% CD8 T C cells 6% γ/δ T cells <1% NKT cells <1% CD5 -ve 3% CD5 +ve <1% IgG 1% IgA 1% IgE <1% Th1 <3% Th2 <3% Th17 <0.2% Treg 1%

18 HUMAN IMMUNE CELL INTERACTIONS: A highly dynamic/interactive/orchestrated symphony DC Th0 Th2 Th17 Th1 Treg IL-5 Eos IL-17 IL-2, IFNγ TGF-ß, IL-10 IL-4, IL13 AUTOIMMUNITY/ INFLAMMATION N IgG B IgG4, IgE ALLERGY IgA

19 Th1 <3% The Th1 Pathway Some Simplified Views

20 Then there s the issue of...

21 Where B cells do their thing Pathogens/Allergens* fist seen in the periphery by antigen-capturing cells then taken to local lymphoid organs B B B B *Paradigm: IgE/Allergic responses

22 Where B cells do their thing lymph node B B B B

23 Where B cells do their thing lymph node B cells activated and then expand in follicles follicles (germinal centres) T zone B B B B

24 Where B cells do their thing follicles centres) lymph node giving rise to: memory cells & plasma cells (germinal periphery memory cell B B B B bone marrow (follicles mature to germinal centres ) plasma cell

25 B cell first need to be primed: Ménage-à-trois model [alternatives exist]

26 Then they need to decide /be-instructed to stay outside of or to enter follicles

27 Follicles then morph to Germinal Centres: Highly Organised & Dynamic Structures CB = centroblast; cc = centrocyte; M = macrophage; FDC = follicular dendritic cell; TH = T helper cell Follicular Dendritic Cells do NOT exist in blood (PBMC) yet are ESSENTIAL for most forms of antibody class switching (incl. to IgE) & affinity maturation of antibody responses

28 Knowing the signals delivered by FDC (& specialised follicular TH cells) means we can construct culture systems to deliver signals optimally to develop responses in vitro N.B. Naive and Memory B Cells migrate, localise & respond differently We therefore need to look at these subsets individually for any potential contribution to Disease: and the impact of a drug thereon

29 MAGNETIC CELL SORTING OF NAÏVE AND MEMORY B CELL SUBSETS Naive AET-SRBC depleted tonsil IgD α-cd3 α-cd38 α-cd14 CD27/IgD IgM IgD/IgM α-cd27 α-iga α-igg α-igd IgM IgM IgD/IgM IgD Memory IgD/IgM CD27 IgD IgD

30 Phenotype of freshly isolated naïve and memory B cell subsets naïve memory naïve memory naïve memory size (FSC) CD23 CD5 naïve memory naïve memory naïve memory CD80 CD86 CD95

31 Allergy Jun;54(6): Epitope-dependent synergism and antagonism between CD40 antibodies and soluble CD40 ligand for the regulation of CD23 expression and IgE synthesis in human B cells. Challa A, Pound JD, Armitage RJ, Gordon J. MRC Centre for Immune Regulation, University of Birmingham, Edgbaston, UK 140 IgE production (ng/ml) Undetectable Drug vehicle Drug vehicle Drug+ 0 PBMC Immune cell subset Standard PBMC Assay fails to develop IgE response; whereas precise reconstitution of and correctly timed physiological signals to the exact immune cell subsets engaged in allergic reactions develops robust IgE responses. This now allows inhibitory impact of a drug to be revealed.

32 Optimal Resolution of Modifiers of IgE Responses in vitro require Optimal Knowledge & Reconstruction of the Human IgE Response in vivo Ongoing refinement of culture systems as knowledge evolves Minimal requirements: Correct target B-cell subset Correctly polarised T-cell subset A reconstituted FDC Correct accessory signals (cytokines/tnf-family ligands) Correct timing of signal delivery/cell interactions Fourteen day culture in toto

33 Conclusions Current Industry Norms (Animal/PBMC) not just limited but potentially LEAD TO DECISIONS WHICH CAN BE: Erroneous Dangerous/Lethal Solutions Harness expertise that has the capacity to UNDERSTAND, ISOLATE, DEVELOP precisely & appropriately each component of the HUMAN Immune System Harness expertise that contains knowledge of HOW, WHEN & WHERE the separate components come together and interact in vivo to recapitulate responses in vitro Harness expertise that understands how DYSFUNCTION or UNDERPERFORMANCE of Immune System components and interactions leads to Disease Harness expertise that is directed and dedicated to improving Human Health through detailed knowledge of Human Immune System Behaviour

34 MODELLING THE HUMAN IMMUNE RESPONSE Slides available for download at: