Collaborating Institutions
PNG Institute of Medical Research
Kenya Medical Research Institute Mozambique
Centre for Clinical Health Research
The Walter and Eliza Hall Institute
of Medical Research
Malaria Immunology and Epidemiology studies in PNG
Understanding the targets and mechanisms of immunity to malaria to
rationalize the development of vaccines.
Examine both antibody and cellular compartments of the immune
response to the malaria.
Studies: Funders:
-Mugil study (2004) US Dept. Veterans Affairs
-Alexishafen pregnancy study (2006-11) MiP Consortium
-Ilaita (R03) mixed infection study (2007) NIH, HHMI Lab funds
-MALGEN severe malaria study (2006-10) Gates Grand Challenges, NH&MRC
-Cellex P. vivax study (2008) Cellex Foundation with CRESIB
-IPTi study (2008-2010) IPTi Consortium
-Albimana study (2009) Lab funds
-ICEMR study (2010-17) NIH
Malaria Immunology and Epidemiology studies in PNG
Understanding the targets and mechanisms of immunity to malaria to
rationalize the development of vaccines.
Examine both antibody and cellular compartments of the immune
response to the malaria.
Studies: Funders:
-Mugil study (2004) US Dept. Veterans Affairs
-Alexishafen pregnancy study (2006-11) MiP Consortium
-Ilaita (R03) mixed infection study (2007) Lab funds (HHMI)
-MALGEN severe malaria study (2006-10) Gates Grand Challenges, NH&MRC
-Cellex P. vivax study (2008) Cellex Foundation with CRESIB
-IPTi study (2008-2010) IPTi Consortium
-Albimana study (2009) Lab funds
-ICEMR study (2010-17) NIH
Observational cohorts studies (n = ~ 500)
Malaria Immunology and Epidemiology studies in PNG
Understanding the targets and mechanisms of immunity to malaria to
rationalize the development of vaccines.
Examine both antibody and cellular compartments of the immune
response to the malaria.
Studies: Funders:
-Mugil study (2004) US Dept. Veterans Affairs
-Alexishafen pregnancy study (2006-11) MiP Consortium
-Ilaita (R03) mixed infection study (2007) Lab funds (HHMI)
-MALGEN severe malaria study (2006-10) Gates Grand Challenges, NH&MRC
-Cellex P. vivax study (2008) Cellex Foundation with CRESIB
-IPTi study (2008-2010) IPTi Consortium
-Albimana study (2009) Lab funds
-ICEMR study (2010-17) NIH
Intervention studies (n = ~ 1500-2000)
Systems biology (‘omics’)
Biology and Clinical insight
Population platforms (field sites, cohort studies)
Population biology
Epidemiology
Stats
Malaria
Tuberculosis?
Population biology: platform for discovery
PNG Field Studies
2004-2013
Study villages
Longitudinal Study Design
0 days 30 60 90 120 150 180
Clinical examination 10mL blood taken
Immune cells purified
drug treatment
(baseline)
Baseline
Active case detection
-Clinical exam
-Blood films (LM)
-Finger prick (PCR)
-Symptomatic children
taken to Mugil Health Centre
Passive case detection 12 months
Parasitological and clinical outcomes
Michon et al., 2007
~95% of children were re-
infected with P. falciparum
~50% of children
experienced a clinical
episode of P. falciparum
Clinical episode: fever +
5000 parasites/μL
80
Pro
po
rtio
n u
nin
fect
ed
80
Pro
po
rtio
n u
nin
fect
ed
Moving beyond serology to define targets of naturally
acquired immunity
• Development of functional assays measuring relevant host/pathogen
interactions
– Growth inhibitory antibodies
– Opsonising antibodies
Anti-Rh5 antibodies associated with reduced risk of
high parasitemia
There Are Conflicting Reports as to the Cellular
Source of Innate IFNg in Humans
gd-T
CD
56
CD3
SS
C
SS
C
ab-TCR gd-TCR
NK
•A comprehensive phenotypic characterization of all innate IFNg producing cells
had not been done
NK cells also shown to be a major
source of innate IFNg (Artavanis-
Tsakonas & Riley, 2002)
gdT cells shown to be a major
source of innate IFNg (Hensmann
& Kwiatkowski, 2001)
Major Questions
• What cells produce IFNg in response to malaria in humans?
– Do they express NKC &/or KIR receptors?
• Is IFNg production by these cells associated with altered risk of disease in individuals living in malaria-endemic areas as it is in mice?
Malaria IFNg Elicitation Assay
Blood from
Purify
PBMC
P. falciparum
iRBC
Malaria
naive donors
16 hour incubation at 37ºC
Measure IFNg
in supernatants
by ELISA
Determine which
PBMC produce
IFNg by FACS
uRBC
or
IFNg
gdTCR
CD3
CD56
uRB
C
iRBC
IFNg
CD3
IFNg+ PBMC from 15
donors phenotypically
characterized
93% of
donors
gdT cells
7% of
donors
NK cells
D’Ombrain et al., 2007
gdT Cells Are The Predominant Source of IFNg in
93% of Donors
gdT Cells Are The Predominant Source of IFNg in
93% of donors NK cells
gdT cells
abT cells
other cells
D’Ombrain et al., 2007
0%
20%
40%
60%
80%
100%
H N G I L F K M D A E J B O C
Donors
% o
f T
ota
l IF
N- g
+ C
ells
•Cell frequency & the % contribution of each cell type were not associated with
heterogeneity in IFNg responsiveness
D’Ombrain et al., 2007
Depletion of gdT Cells Abrogates IFNg Production
CD3
CD56
gdTCR
abTC
R
97%
89%
96%
PBMC Depleted
PBMC
uRBC
iRBC
0
300
600
900
1200
1500
NK cell
depleted
gdT
depleted
abT
depleted
0
300
600
900
1200
1500
IFN
g (p
g/m
L)
PBMC
*
Vg9 54.2 45.8
CD8 29.9 70.1
Vd2 83.6 16.4
CD4 4.7 95.3
Vd1 9.5 90.5
+
Malaria Responsive gdT Cells Are Mainly of
the Vg9Vd2 Subset
iRBC
gdTCR+ & IFNg+ PBMC
phenotypically characterised
gdTCR
iRBC
IFNg
iRBC
D’Ombrain et al., 2007
NKG2A
68.2 31.8
NKG2D
83.2 16.8
CD94 89.4 10.6
CD161 73.5 26.5
+ iRBC
gdTCR+ & IFNg+ PBMC
phenotypically characterised
gdTCR
iRBC
IFNg
iRBC
The Majority of Malaria Responsive gdT Cells
Express NKC Receptors
D’Ombrain et al., 2007
NKC & KIR Receptors Are Differentially
Expressed on IFNg+ & IFNg- gdT Cells
+ iRBC
gdTCR+ & IFNg- or IFNg+
PBMC compared by
Wilcoxon Signed-Rank
Tests
gdTCR IFNg
0%
25%
50%
75%
100%
E F G D K H I
NKG2A p<0.01
Donors
% I
FN
g- &
IF
Ng+
gdT
cel
ls
expre
ssin
g N
KG
2A
D’Ombrain et al., 2007
IFN-g- gdT cells IFN-g+ gdT cells
iRBC iRBC
0%
10%
20%
30%
E F G D K H I
KIR2DL1 p<0.01
Donors
% I
FN
g- &
IF
Ng+
gdT
cel
ls
expre
ssin
g K
IR2D
L1
Summary: PART 1
There is heterogeneity among donors in the innate IFNg response to iRBC
gdT cells that express NK receptors, not NK cells, are the major cellular source of IFNg
NK receptors are differentially expressed on IFNg+ & IFNg- gdT cells
Are gdT cell involved in risk of disease?
0
2000
4000
6000
8000
10000
12000
14000
14
3
10
9
23
1
41
40
1
50
10
8
13
8
14
6
56
12
1
40 9
30
3
42
5
21
0
22
2
30
2
14
14
1
30
7
41
3
20
5
24
3
42
7
24
5
24
4
42
1 6
31
High
Medium
Low
Heterogeneity in IFNg Responses Among Semi-
immune PNG Children
IFN
g (p
g/m
L)
PNG Children
Heterogeneity in IFNg Responses is Malaria
Specific
≤ ≤
iRBC PHA
High IFNg Responses Are Associated With a Lower
Risk of High Density Infections
No change
in risk
Higher risk
(pathogenic)
Lower risk
(protective)
Haz
ard
Rat
io
Hazard Ratio: Ratio of hazard of having a P. falciparum
infection to high IFNg responsiveness
(clinical) low density
infections high density
infections
A case-control study of severe malaria in PNG
Severe Malaria
n=202
Uncomplicated malaria controls
n=174
Healthy community controls
n=164
• >1000 P.f./μL
• WHO (2000) definition of severe
malaria
• Admitted to Modilon Hospital
• >1000 P.f./μL
• No severe disease
• Health / immunization clinics
• No acute illness
• No severe malaria within 2 weeks
• Immunization clinics
Groups matched by age, sex, and province
of parent’s birth
Cases Controls
Cytokine responses to pRBC are associated with disease
severity
Cytokine responses to pRBC are associated
with disease severity
Cytokine responses are associated with
specific severe malaria syndromes
Respiratory distress Deep coma Hyperlactataemia
gd T cells in severe malaria produce TNF and monokines
Vg9Vd2 T Cells
•Evidence for 2 mechanisms of activation:
phospho-
antigens
APC
Expansion
•Vg9Vd2T cells are activated by phosphoantigens
1. Vg9Vd2TCR can function as a PRR
2. Vg9Vd2TCR can also be MHC
IFNg
Vg9Vd2TCR
restricted
Malaria Immunology and Epidemiology studies in PNG
Understanding the targets and mechanisms of immunity to malaria to
rationalize the development of vaccines.
Examine both antibody and cellular compartments of the immune
response to the malaria.
Studies: Funders:
-Mugil study (2004) US Dept. Veterans Affairs
-Alexishafen pregnancy study (2006-11) MiP Consortium
-Ilaita (R03) mixed infection study (2007) Lab funds (HHMI)
-MALGEN severe malaria study (2006-10) Gates Grand Challenges, NH&MRC
-Cellex P. vivax study (2008) Cellex Foundation with CRESIB
-IPTi study (2008-2010) IPTi Consortium
-Albimana study (2009) Lab funds
-ICEMR study (2010-17) NIH
Observational cohorts studies (n = ~ 500)
Malaria Immunology and Epidemiology studies in PNG
Understanding the targets and mechanisms of immunity to malaria to
rationalize the development of vaccines.
Examine both antibody and cellular compartments of the immune
response to the malaria.
Studies: Funders:
-Mugil study (2004) US Dept. Veterans Affairs
-Alexishafen pregnancy study (2006-11) MiP Consortium
-Ilaita (R03) mixed infection study (2007) Lab funds (HHMI)
-MALGEN severe malaria study (2006-10) Gates Grand Challenges, NH&MRC
-Cellex P. vivax study (2008) Cellex Foundation with CRESIB
-IPTi study (2008-2010) IPTi Consortium
-Albimana study (2009) Lab funds
-ICEMR study (2010-17) NIH
Intervention studies (n = ~ 1500-2000)
Cohort study questions
• How do malaria-specific CD4+ T cell and gd T cell responses differ in phenotype, frequencies and function in relation to age, parasitological and clinical outcomes?
• What responses are associated with differential clinical and parasitological risk i.e correlates of immunity or susceptibility?
• Are CD4+ ab T cell and gd T cell responses correlated?
• How do CD4+ T cell responses to EBV and CMV differ to malaria-specific CD4+ T cell responses?
Our more recent approaches
• Multiparameter flow cytometry consisting of:
Viability dye to exclude non-viable cells;
5 population markers to identify T cell populations
of interest and memory status;
3 markers to identify differentiation/antigen-
experience and immunosenescence;
4 markers to assess functional activity of cells and
polyfunctionality.
Immune regulation of gd T cell responses
• Rationale: Conventional T cells are tightly regulated by expression of receptors that suppresses cell activation. Prolonged and inappropriate expression of these receptors occur during chronic disease and immune exhaustion resulting in dysfunctional cell functions
• Study questions:
- Are gd T cell responses regulated in a similar manner as conventional T cells?
- How does expression of regulatory receptors on gd T cells effect functional capacity and cytokine profiles?
- How does expression of regulatory receptors on gd T cells relate to protective immunity during malaria?
Immune regulation: Programmed cell death-1 (PD-1)
• PD-1 is a cell surface receptor that suppresses activation of immune cells.
• PD-1 is expressed by dysfunctional cells in chronic diseases such as HIV and HCV. Porichis et al Blood 2011, Razziorrouh et al Gastroeneterology 2011
• Blocking of PD-1 interaction with it’s ligand results in restored cell function. Day et al Nature
2006
• In malaria blocking of PD-1 result in reduced parasite burden in an animal model. Butler
et al Nat Immunol 2012
gd T cell PD-1 expression
Immune regulation: and T-cell immunoglobulin and
mucin domain-containing protein 3 (Tim-3)
• Tim-3 engagement in mice result in apoptosis and loss of effector T cells.
• Zhu et al. Nat Immunol 2005
• In humans Tim-3 is associated with functional exhaustion.
• Jin et al PNAS 2010, Jones et al JEM 2008
• Blocking of Tim-3 partially reverse cell dysfunction.
• Sakuichi et al JEM 2010
• Very few studies have investigated Tim-3 on non-conventional T cells.
gd T cell Tim-3 expression
Innate lymphocytes – unexplored players in defense against
novel non-classical pathogen ligands?
Mucosa = largest exposed surface of the body – 1st barrier
Up to 1012 bacteria/cm3 – not all of which are friendly
humans exposed to multitude of organisms daily
250 m2 gut
70m2 lungs
The mucosal defense system – a central motor
Coordinates cross-talk among epithelium, immune system and
endogenous microflora of gut
Implicated in a wide range of diseases
Lung disease – asthma, TB
Autoimmune disease – mediated by ILC and alterations of gut
microbiota
Intestinal disease – inflammatory bowel disease,
Crohn’s disease
Innate lymphocytes – new players in lung defense
Diverse populations form an intricate innate
lymphocyte network
Spits et al. Nature Reviews Immunology 13, 145-149 (February 2013) | doi:10.1038/nri3365
ILC subsets, functions and disease associations
Highly conserved gene program between mice and man
Spits et al. Nature Reviews Immunology 13, 145-149 (February 2013) | doi:10.1038/nri3365
Bioinformatics at WEHI: world leading in transcriptomic statistics
Eliminating background noise by focusing on gene sets linked to cell populations or
processes of interest
Gene set testing is a powerful method to identify coordinated changes in genes
associated with a particular population or process of interest.
It is particularly useful in complex processes where the timing of up- and down-
regulation of genes can occur at different rates.
We successfully used Gordon Smyth’s rotational gene set testing (ROAST) and
competitive gene set testing (Camera) methods in Achtman et al. 2012 Effective
adjunctive therapy by an innate defense regulatory peptide in preclinical severe
malaria. Science Translational Medicine Sci Transl Med. 4 (135):135ra64. doi:
10.1126/scitranslmed.3003515.
Terry Speed
Gordon Smyth
Deconvolution of data based on additional information on population
sizes
The quanta unit of the immune system is the cell, yet analyzed samples are often heterogeneous
with respect to cell subsets - which can confound interpretation.
Experimentally, researchers face a difficult choice whether to profile heterogeneous samples with
the ensuing confounding effects, or a priori focus on a few cell subsets of interest, potentially
limiting new discoveries.
An attractive alternative solution is to extract cell subset-specific information directly from
heterogeneous samples via computational deconvolution techniques, thereby capturing both cell-
centered and whole system level context.
Our plan to define cellular immunity to P.falciparum Malaria
Study design Key Questions:
How do malaria-specific T cells phenotypes differ in relation to: (i) age; (ii) exposure; (iii) parasitological
outcomes; (iv) clinical outcomes; and (v) elicitation stimuli?
Analyses:
Whole blood RNAseq transciptomes at base-line, clinical episode and convalesence
PBMC isolation, 16hr in vitro elicitation with whole parasites in presence/absence of autologous plasma.
Multiparameter flow cytometry for:
Surface Markers:
gd TCR
Live dead
CD3 (stained intracellularly)
CD4
CCR7 (memory marker)
CD45RA (memory marker)
CD27 (differentiation)
CD28 (differentiation)
Functional Markers:
IFNg (intracellular cytokine)
IL-2 (intracellular cytokine)
TNFa (intracellular cytokine)
CD154 (surface activation marker (stained in culture))
CD57 (surface exhaustion marker)
Post elicitation RNAseq transciptomes
Rotational gene set testing (ROAST) and competitive gene set testing (Camera), computational deconvolution.
Statistical model building, logistic regression, risk factor analysis.
ACKNOWLEDGMENTS
Schofield lab.
Krystal Evans
Ramin Mazhari
Ariel Achtman
Emily Eriksson
Marthe D’Ombrain
Leanne Robinson
Danika Hill
Stephanie Tan
Natalia Sampaio
Thuan Phuong
Amandine Carmagnac
Wasan Forsyth
Other WEHI labs.
Ivo Mueller
Diana Hansen
Marc Pelligrini
Gabrielle Belz
Bioinformatics
Terry Speed
Gordon Smyth
PNGIMR
Peter Siba
Inoni Betuela
Andrew Valleley
Suparat Phuanukoonnon
Queensland Mycobacterial Reference Laboratory
Chris Coulter
Swiss Tropical Public Health Institute
Marcel Tanner
Sebastian Gagneaux
Massachussetts Institute of Technology
Peter Seeberger
Mike Hewitt
Centers for Disease Control
John Barnwell
Ancora Pharmaceuticals Inc.
Stew Campbell
Merck Inc.
Jan ter Meulen
Craig Pryziecki
Mahidol University
Jetsumon Prachumsri
Australian Institute of Tropical Health
and Medicine
Brenda Govan
Natkuman Ketheesan CRESIB, Barcelona
Pedro Alonso
Carlota Dobano
Alfredo Mayor
Case Western Reserve University
Jim Kazura
Chris King
STUDY CHILDREN & GUARDIANS
Health Centre staff &
Teachers at Mugil and Megiar schools.
University of Melbourne
Stephen Rogerson
Louis Schofield, Director
AITHM - State and Federal Agreements
• Queensland Government $19.8 million – Oct. 2011
• Queensland Government $42.2 million – June 2013
• Federal Government $42.2 million (Sept 2013)
• Total $103 million
Budget breakdown
• State Government Budget $42 million
• 72% for Infrastructure – including equipment
• Infrastructure – AITHM Townsville
• Infrastructure – AITHM Torres Strait
• 28% for Operations and Research
• Federal Government Budget $42 million
• 62% for Infrastructure – including equipment
• Infrastructure – AITHM Cairns
• 38% for Operations and Research
Karkar
Balimo
Hiri
Wosera
Kikori
Torres Strait
Institutional Partnerships in our new TB program
• Papua New Guinea Institute of Medical Research (Peter Siba)
• Papua New Guinea Department of Health incl. Central Public Health Laboratory
• Australian Institute of Tropical Health and Medicine (Louis Schofield)
• The Walter and Eliza Hall Institute (Schofield, Mueller, Speed, Smyth, Belz)
• Queensland Health, including Local Health and Hospital Boards;
• Queensland Tropical Health Alliance (Louis Schofield);
• Swiss Tropical Public Health Institute (Marcel Tanner, Sebastian Gagneaux);
• Queensland Mycobacterial Reference Laboratory (Chris Coulter);
• International research institutions/agencies with a focus on tropical health;
• Key community groups and representatives.
Value proposition (for discussion)
Observational and interventional study designs in DSS, GPS
mapped, population-based longitudinal cohorts with nested clinical
case controls, in communities with v. high incidence of TB and
inadequate BCG coverage;
Integrated transcriptomic, multiparameter flow and statistical
analyses of diverse lymphoid lineages within intuitive conceptual
frameworks;
Collaborative ethos, community, institutional and political support.
Objectives:
Define natural and BCG-induced correlates of immunity and
susceptibility to TB
Improved public health tools and interventions
Vaccine trials