THE IMMUNITY-METABOLISM LINK
Immunology
Cell Metabolism Assays
Research
for
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XF Fatty Acid Oxidation Profile Exogenous & Endogenous Fatty Acid Oxidation
XF Glycolysis Stress Test Profile Glycolytic Function
051015202530354045
Extra
cellu
lar A
cidi
ficat
ion
Rate
(EC
AR)
(mpH
/min
)
Glycolysis
Glucose Oligomycin 2-DG
Glycolytic Capacity
Glycolytic Reserve
0 10 20 30 40 50 60 70 80 90 100
Non-glycolytic Acidification
Time (minutes)
XF Cell Mito Stress Test Profile Mitochondrial Respiration
Basal Respiration
FCCPRotenone & antimycin A
Proton Leak
004080120160200240280320360
10 20 30 40 50 60 70 80 90 100 110
Non-mitochondrial Respiration
Time (minutes)
Oxy
gen
Con
sum
ptio
n Ra
te (O
CR)
(p
mol
/min
)
Spare Capacity
ATPProduction
Oligomycin
Maximal Respiration
XF Cell Energy Phenotype Test Metabolic Phenotype & Potential
Oxy
gen
Con
sum
ptio
n Ra
te (O
CR)
Extracellular Acidification Rate (ECAR)
GOLD STANDARD METABOLIC ASSAYSMEASURING THE KEY PARAMETERS OF CELL METABOLISM
FCCPRotenone & antimycin A
020406080100120140160180200
10 20 30 40 50 60Time (minutes)
Oxy
gen
Con
sum
ptio
n Ra
te (O
CR)
(p
mol
/min
)
Oligomycin
Basal
Maximal
Exogenous Palmitate Oxidation
Endogenous FAO
Exogenous Palmitate Oxidation
Endogenous FAO
CELL LINEAGE AND IMMUNOMETABOLISM
Naive T cell
ActivatedT cell
E�ectorT cell
MemoryT cell
Fatty acid oxidation
Mitochondrial respiration (OCR)
Glycolysis (ECAR)
FUNCTIONAL XF METABOLIC ASSAYS - THE INTERSECTION OF IMMUNOLOGY & METABOLISM XF TECHNOLOGY PROVIDES THE TOOLS TO MEASURE IMMUNOMETABOLISM
Immunologists study how the innate and adaptive immune system recognizes and responds to insults. Whether the research focus is on a specific immune cell type, signaling pathway, or disease area, immunologists are actively exploring the mechanisms that drive and perpetuate antigen recognition and response.
Immune system metabolism (referred to as ‘immunometabolism’) has emerged as a key mechanism in understanding the connection between metabolic pathways and immune responses. Each immune cell type has a specialized role in an immune response, as well as a preferred metabolic pathway to generate energy required to maintain homeostasis.
Research into metabolic changes provides insight into metabolic signature, signaling, and substrate preference. These metabolic choices are leading to new opportunities to modulate immunological response for therapeutic intervention.
XF Technology is at the forefront, providing powerful and effective tools to explore the burgeoning field of immunometabolism.
Metabolism
Cell Type
SignalingPathways
DiseaseArea
GLUCOSE
GLUTAMATE
FATTY ACID
FATTY ACIDLACTATE CITRATE
Acetyl-CoA
TCA
GLUTAMINEGLYCOLYSIS
(ECAR)
MITOCHONDRIAL RESPIRATION
(OCR)
GLUTAMATE
ETC
PYRUVATE
SUBSTRATES AND METABOLISM
Extracellular Acidification Rate (ECAR)
Oxy
gen
Con
sum
ptio
n R
ate
(OC
R)
Glycolysis
XFp Cell Energy Phenotype Profile
Mito
chon
dria
l Res
pira
tion
Metabolic Potential
Aerobic
Quiescent
BaselinePhenotype
StressedPhenotype
Energetic
Glycolytic
Rev
2
ImmunologyBrochure.indd 1-3 7/6/15 3:25 PM
Control
ns100
80
60
40
20
0
****
Rapa
- glucose
+ glucose
MEASURING THE KEY PARAMETERS OF IMMUNOMETABOLISM
METABOLIC SIGNATURES Cell activation, amplification, and effector function are crucial aspects of the immune cell life cycle. Researchers are using XF Technology to examine the cross-talk between immune cells and their metabolic signatures to gain insight into disease pathology, etiology, and possible treatment options. The XF Cell Mito Stress Test measures the key parameters of mitochondrial function: basal respiration, ATP-linked respiration, proton leak, maximal respiration, and spare respiratory capacity. The XF Glycolysis Stress Test measures the three key parameters of glycolytic function: glycolysis, glycolytic capacity, and glycolytic reserve.
SUBSTRATE UTILIZATION, FLEXIBILITY & DEPENDENCY Each immune cell type has a specific function within the immune system. Cell fate decisions, activation, amplification, and effector function are driven by metabolism. To maintain the energy demands of the cell at each stage of its life cycle, the metabolic requirements for substrates or fuels that feed into the metabolic ‘engines’ are altered. XF Technology provides the capability to examine the effect of substrate utilization and dependency, yielding powerful metabolic data.
XF Cell Mito Stress Test profiles metabolic signatures of activated bone marrow-derived macrophage subtypes.
Mouse bone-derived macrophages
Huang SC et al., (2014) Nat Immunol.
Human T cells
Hegedus A et al., (2014) Retrovirology
XF Assays reveal the role of glycolysis in HIV infection.
0
2
4
6
8
10
12
100 200 3000 400 500
Inhibitor or DMSOα-CD3 and α-CD28
PI(3)K/Akt inhibitorDMSO
Even
ts (%
max
)
eFluor 670
0100 104103102101
20
60
40
80
100
ActivatedActivated + PI(3)K inhibitor
0
125100755025
150175200225250275
0 30 60 75 10515 45 90 120
Oligomycin FCCP
SRC
Rotenone/ antimycin A
M0 M1 M2
Oxy
gen
Con
sum
ptio
n R
ate
(OC
R)
(pm
ol/m
in)
XF Metabolic Switch Assay reveals distinct metabolic signatures in platelets and leukocytes.
Human platelets and leukocytes
Kramer PA et al., (2014) Redox Biol.
456789
10
3210
0 2 31 4 5 6 7 8 9 10
BasalOligomycinMonocytes
Platelets
Lymphocytes
Neutrophils
Oxy
gen
Con
sum
ptio
n R
ate
(OC
R)
(pm
ol/m
in/μ
g pr
otei
n)
Extra
cellu
lar A
cidi
ficat
ion
Rat
e (E
CAR
) (%
mpH
/min
)
(mpH/min/μg protein) Extracellular Acidification Rate (ECAR)
GOLD STANDARD ASSAYS FOR MEASURING METABOLIC REPROGRAMMING
Human T cells
Yin Y et al., (2015) Sci Transl Med.
Murine T helper cells
Chatterjee S et al., (2014) Cancer Res.
METABOLIC EFFECT OF THERAPEUTICS The primary role of the immune system is to protect the host by targeting foreign antigens, controlling or clearing infections, and attacking cancerous cells. However, metabolic interventions present a largely untapped area of disease research. XF Technology provides the necessary tools to understand the effects of therapeutic candidates on the antigen of interest, and on the immune system.
Real-time activation reveals metabolic signatures of lupus patient-derived CD4+ T cells.
XF Assays reveal a metabolic switch which correlates to the antitumor ability of Th17IL1β cells.
Tum
or s
ize (m
m2 )
Days
400
500 Control
Th17TGFβ1
Th17IL1β
300
200
100
00 10 155 20 25
Don
or c
ells
(per
mL
of b
lood
)
3º Day 7Recall
1º Day 7Recall
0
1x105
2x105
3x105
4x105 *
Murine T cells
Fraser KA et al., (2013) Immunity
XF Assays reveal that tertiary immunization increases memory CD8+ T cell recall.
1000
750
500
250
00 20 40 60 80 100 120
Oligomycin FCCP Rotenone
3ºSRC
1ºSRC
Naive 1º Day 7 3º Day 7
Oxy
gen
Con
sum
ptio
n R
ate
(OC
R)
(pm
ol/m
in)
Time (min)
80
60
40
Th17TGFβ1 Th17IL1β
20
0
2,000
1,500
1,000
500
0
**
***
Exrta
cellu
lar A
cici
ficat
ion
Rat
e (E
CAR
) (m
pH/m
in)
Oxy
gen
Con
sum
ptio
n R
ate
(OC
R)
pmol
O2/m
in
THE WORLD’S MOST ADVANCED METABOLIC ANALYZERS
PROVEN TECHNOLOGY FOR CUTTING EDGE RESEARCH There are nearly 2,000 references utilizing XF Technology published in leading journals such as Nature and Cell. Scientists are embracing XF Technology to identify metabolic phenotypes and reprogramming to target metabolic pathways for therapeutic purposes.
Murine T cells
van der Windt GJ et al., (2013) PNAS
Murine T cells
Fletcher M et al., (2015) Cancer Res.
Human B cells
Liu T et al., (2014) Cell Death Dis.
I
II
III
IV
Lactate
Pyruvate
Glucose
Glycolysis ECAR (Extracellular Acidification Rate)
Mitochondrial Respiration OCR (Oxygen
Consumption Rate)
XF Assays reveal a role of fatty acid oxidation in memory T cell response.
XF Glycolysis Stress Test identifies L-Arginine dependence for proliferation in T cells.
XF Assays reveal a glucose dependence in B-cell acute lymphoblastic leukemia (B-ALL) cells.
XF Assays reveal glucose-insensitivity of naïve T cells in the presence of rapamycin.
400
300
200
100
00 10050 150
controlor
etomoxir
Control Etomoxir
PMA/ionomycin
Time (min)
Oxy
gen
Con
sum
ptio
n R
ate
(OC
R)
(pm
ol/m
in)
No Fuel Glutamine Glutamine + Glucose
B-ALL
cell lin
e #1
B-ALL
cell lin
e #2
B-ALL
cell lin
e #3B ce
ll
line #1 B ce
ll
line #2 B ce
ll
line #3Ex
trace
llula
r Aci
dific
atio
n R
ate
(EC
AR)
(mpH
/min
)
METABOLIC REPROGRAMMING Signaling plays an important role in eliciting immunological response by coordinating immune cell communication and actions. Researchers are using XF Technology to probe the signaling and metabolic programming of immune cells.
XF Cell Mito Stress Test identifies IFNAR requirement for metabolic reprogramming.
Murine dendritic cells
Pantel A et al., (2014) PLoS Biol.
Human T cells
Gubser PM et al., (2013) Nat Immunol.
Real-time activation of memory T cells demonstrates a connection amongst signaling pathways, glycolysis, and proliferation.
XF Assays reveal Natural Killer (NK) cell dependence on mTORC1 following stimulation of IL-2 and IL-12.
Murine Natural Killer cells
Donnelly RP et al., (2014) J Immunol.
Uninfected HIV-infected
1000
800
400
600
200
030 5040 7060 80
Glucose Oligomycin
** **
300
200
17 85 9425 34 42 51 60 68 77
WT Poly ICIFNAR-/- Poly ICIFNAR-/- Poly PBS
WT PBS
100
00 8
FCCPOligomycin Rotenone/antimycin A
Oxy
gen
Con
sum
ptio
n R
ate
(OC
R)
(pm
ol/m
in)
ECAR
(mpH
/min)
Rapa
Unstim
- -
IL2/12
40
20
*
+Extra
cellu
lar A
cidi
ficat
ion
Rat
e (E
CAR
) (m
pH/m
in)
Extra
cellu
lar A
cidi
ficat
ion
Rat
e (E
CAR
) (m
pH/m
in)
Time (min)Time (min)
5
10
15
20
0WT IFNAR -/-
ECAR
(mpH
/min)
60
αCD3/CD28
BaselineSRC
InducedSRC
Oligomycin
αCD3/CD28 Control
FCCP Rotenone/antimycin A
20
40
020 60 100
Oxy
gen
Con
sum
ptio
n R
ate
(OC
R)
(pm
ol/m
in)
Glucose Oligomycin 2-DG
Peg-BSA Peg-Arg I
250
200
100
150
50
-50
02010 30 5040 7060 80 10090 110
% T
cell
s pr
olife
ratin
g(C
FSE)
(μg/ml pegylated protein)
100
75
50
25
00
0.50.25
0.125 1 2
***
Time (min) Time (min)Time (min)
Extra
cellu
lar A
cidi
ficat
ion
Rat
e (E
CAR
) (m
pH/m
in)
Time (min)
Time (min)
Murine T cells
Goldberg EL, et al., (2014) J Immol.
Extra
cellu
lar A
cidi
ficat
ion
Rat
e (E
CAR
) (m
pH/m
in)
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