Genomics Cells use gene expression to synthesize proteins and other products that are essential for various cellular functions. Gene expression levels, while associated with metabolism, cannot solely predict the functional impact on metabolism. This creates a gap in understanding the complex physiological relation between genes and metabolism. researchers are using XF Technology to link functional metabolism to gene expression for a complete picture. The XF Cell mito stress Test measures the key parameters of mitochondrial respiration: basal respiration, ATP-linked respiration, maximal respiration, and spare respiratory capacity. The XF Glycolysis stress Test measures the key parameters of glycolytic activity: glycolysis, glycolytic capacity, glycolytic reserve.
XF Assay reveals a link between histone deacetylase 9 (Hdac9) deletion and mitochondrial respiration correlating to a genetic and functional increase in T regulatory cells.
(beier uH et al., 2015. FAseb J.)
XF Cell Mito Stress Test predicts differentiation status in neuronal progenitor cells (NPCs) derived from patients with mutations causing mitochondrial encepharopathy and stroke-like episodes (MELAS) which correlates to gene expression.
(ma H et al., 2015. nature.)
stanDaRD paRameteRs oF Functional metabolism
Oxy
gen
Con
sum
ptio
n R
ate
(OC
R)
(pm
ol/m
in)
Basal Oligomycin FCCP
500
400
300
200
100
0basal oligomycin
*
OC
R (p
mol
/min
)
FCCP
Control Hdac9 deleted
Rel
ativ
e Ex
pres
sion
Lev
els
MELAS-IPS1
100000
10000
1000
100
10
1
0.1
0.01
0.001MELAS-IPS2 MELAS-IPS3
OCT4SOX1PAX6
NANOGNESTIN
Oxy
gen
Con
sum
ptio
n R
ate
(OC
R)
(pm
ol/m
in/µ
g pr
otei
n)
MELAS-iPS1
MELAS-iPS3
MELAS-iPS2
Basal respiration
P<0.054
3
2
1
0
3
2
1
0
3
2
1
0
6
4
2
0
P<0.05
P<0.05P<0.05
MELAS-iPS1
MELAS-iPS3
MELAS-iPS2
MELAS-iPS1
MELAS-iPS3
MELAS-iPS2
MELAS-iPS1
MELAS-iPS3
MELAS-iPS2
MELAS-iPS1
MELAS-iPS3
MELAS-iPS2
pmol
O2 p
er m
in p
er m
g pr
otei
n
pmol
O2 p
er m
in p
er µ
g pr
otei
n
pmol
O2 p
er m
in p
er µ
g pr
otei
n
pmol
O2 p
er m
in p
er µ
g pr
otei
n
Maximum respiration
ATP turnover
Oxidative reserveMaximal Respiration
MELAS-iPS1
MELAS-iPS3
MELAS-iPS2Oxy
gen
Con
sum
ptio
n R
ate
(OC
R)
(pm
ol/m
in/m
g pr
otei
n)
Basal respiration
P<0.054
3
2
1
0
3
2
1
0
3
2
1
0
6
4
2
0
P<0.05
P<0.05P<0.05
MELAS-iPS1
MELAS-iPS3
MELAS-iPS2
MELAS-iPS1
MELAS-iPS3
MELAS-iPS2
MELAS-iPS1
MELAS-iPS3
MELAS-iPS2
MELAS-iPS1
MELAS-iPS3
MELAS-iPS2
pmol
O2 p
er m
in p
er m
g pr
otei
n
pmol
O2 p
er m
in p
er µ
g pr
otei
n
pmol
O2 p
er m
in p
er µ
g pr
otei
n
pmol
O2 p
er m
in p
er µ
g pr
otei
n
Maximum respiration
ATP turnover
Oxidative reserve
Basal Respiration
MELAS-iPS1
MELAS-iPS3
MELAS-iPS2
Oxy
gen
Con
sum
ptio
n R
ate
(OC
R)
(pm
ol/m
in/µ
g pr
otei
n)
Basal respiration
P<0.054
3
2
1
0
3
2
1
0
3
2
1
0
6
4
2
0
P<0.05
P<0.05P<0.05
MELAS-iPS1
MELAS-iPS3
MELAS-iPS2
MELAS-iPS1
MELAS-iPS3
MELAS-iPS2
MELAS-iPS1
MELAS-iPS3
MELAS-iPS2
MELAS-iPS1
MELAS-iPS3
MELAS-iPS2
pmol
O2 p
er m
in p
er m
g pr
otei
n
pmol
O2 p
er m
in p
er µ
g pr
otei
n
pmol
O2 p
er m
in p
er µ
g pr
otei
n
pmol
O2 p
er m
in p
er µ
g pr
otei
n
Maximum respiration
ATP turnover
Oxidative reserveSpare Capacity
Oxy
gen
Con
sum
ptio
n R
ate
(OC
R)
(pm
ol/m
in/µ
g pr
otei
n)
Time (min)
15
10
5
0
MELAS-iPS1 MELAS-iPS2 MELAS-iPS3
Oxy
gen
Con
sum
ptio
n R
ate
(pm
ol O
2 per
µg
prot
ein)
Oligomycin
1007550250
FCCP
Time (min)
Rotenone &antimycin A
MElAS-iPS1 MElAS-iPS2 MElAS-iPS3
Oligomycin FCCPRotenone &antimycin A
MELAS-iPS1
MELAS-iPS3
MELAS-iPS2Oxy
gen
Con
sum
ptio
n R
ate
(OC
R)
(pm
ol/m
in/µ
g pr
otei
n)
Basal respiration
P<0.054
3
2
1
0
3
2
1
0
3
2
1
0
6
4
2
0
P<0.05
P<0.05P<0.05
MELAS-iPS1
MELAS-iPS3
MELAS-iPS2
MELAS-iPS1
MELAS-iPS3
MELAS-iPS2
MELAS-iPS1
MELAS-iPS3
MELAS-iPS2
MELAS-iPS1
MELAS-iPS3
MELAS-iPS2
pmol
O2 p
er m
in p
er m
g pr
otei
n
pmol
O2 p
er m
in p
er µ
g pr
otei
n
pmol
O2 p
er m
in p
er µ
g pr
otei
n
pmol
O2 p
er m
in p
er µ
g pr
otei
n
Maximum respiration
ATP turnover
Oxidative reserve
ATP Production
mouse T cells
Human neuronal progenitor cells
stanDaRD paRameteRs oF Functional metabolism
pRoteomics Advances in proteomic technology enables genome-wide data analysis, pinpointing specific proteins and expression levels. Proteomic data directly links to metabolism without requiring the regulatory mechanisms associated with mrnA expression and final protein expression. However, conclusions utilizing only these types of experiments are limited. XF Technology not only confirms proteomic data but also allows for further investigation of protein function.
XF Cell Mito Stress Test reveals that protein kinase A (PKA)- dependent changes in protein and gene expression
correlate with changes in ATP-linked respiration.(Wilderman A et al., 2015. J Cell biology.)
XF Glycolysis Stress Test reveals the increased glycolytic capacity of granulocyte-stimulated macrophages (M-BMM), confirming the
inherently higher glycolytic protein expression.(na Yr et al., 2015. mol Cell Proteomics.)
the WoRlD’s most aDVanceD metabolic analyZeRs
Microarray Fold Change2.0 + 1.50-1.99 0.71-1.49
0.51-0.70 0.5-
Not represented
200
150
100
50
0CPT-cAMP - + - +
*
WT PKA-deficient
ATP-
linke
d R
espi
ratio
n R
ate
(pm
ol O
2 /m
in/ 1
x105 c
ells
)
GM-BMM M-BMM
Time (min)
Glucose Oligomycin 2-DG
50
40
30
20
10
01 30 60 90 12
015
018
021
024
0
***
GM-BMM M-BMM
Time (min)
Glucose Oligomycin 2-DG
50
40
30
20
10
01 30 60 90 12
015
018
021
024
0
***
GM-BMM M-BMM
Time (min)
Glucose Oligomycin 2-DG
50
40
30
20
10
01 30 60 90 12
015
018
021
024
0
***
GM-BMM M-BMM
Time (min)
Glucose Oligomycin 2-DG
50
40
30
20
10
01 30 60 90 12
015
018
021
024
0
***
Extra
cellu
lar A
cidi
ficat
ion
Rat
e (E
CAR
)(m
pH/m
in)
GM-BMM M-BMM GO_BP:Glucose metabolic process
mRNA protein
relative expression levelGM-BMM/ M-BMM
0 1 2 3 10 12
RPIAPYGLPFKPLDHBGYS1
FABP5ENO1
ALDOC
Gene & Protein Expression Profile
mRNA protein
pRoVen technoloGy FoR cuttinG eDGe ReseaRch There are over 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.
I
II
III
IV
Lactate
Pyruvate
Glucose
murine bone-derived macrophagesmurine lymphoma cells
GLYCOLYSIS — ECAR (Extracellular Acidification Rate)
Cells generate ATP via glycolysis independent of oxygen, producing lactic acid and protons. XF Analyzers measure glycolysis by measuring the extracel-lular acidification rate (eCAr) of cells.
MITOCHONDRIAL RESPIRATION —
OCR (Oxygen Consumption Rate)
mitochondria consume oxygen when oxidizing fatty
acids or other substrates to generate ATP. XF
Analyzers measure mitochondrial respiration by measuring the oxygen
consumption rate (oCr) of cells.
Glucose
G6P/F6P
Fructose1,6-P
DHAP
1,3-PGlycerate
Glycerate3P
PEP
Pyruvate
Lactate
Glycerol3P
6PGluconate
G3P
Eryhrose4P
Sedoheptulose7P
Cis-Aconitate
Th1Th17Treg
Relative level normalized to naive(red line)
α-Ketoglutarate
Succinate
Fumarate
Malate
Oxaloacetate
Acetyl CoA
Citrate
1.5
0.50
1
1.5
0.50
1
1.5
0.50
1
3
10
2
6
20
4
15
50
10
6
2
0
4
2
0.51
0
1.5
2
0.51
0
1.5
15
50
10
5
2
0
43
1
5
2
0
43
1
5
2
0
43
1
5
2
0
43
1
25
10
0
2015
5
2.5
1
0
21.5
0.5
2.5
1
0
21.5
0.5
20
510
0
15
8
24
0
6
20
510
0
15
Glycolysis
Oxidative PPP
Nonoxidative PPP
TCA cycle
measuRinG the key paRameteRs oF Functional cell metabolismmetabolomics Techniques, such as mass spectrometry (ms) and nuclear magnetic resonance (nmr), enable the analysis of hundreds of metabolites in a given sample. However, the data from these techniques alone are not sufficient to assess functionality within a biological context. XF Technology provides real-time analysis of cellular response to stress or nutrients, and can direct metabolomics research, adding efficiency and direction to any area of research.
XF Glycolysis Stress Test predicts sensitivity to first-line EGFR inhibitors used in lung adenocarcinoma cells, and correlates to reduced metabolite levels.
(makinoshima H et al., 2014. J biol Chem.)
XF Glycolysis Stress Test and XF Cell Mito Stress Test reveal increased levels of mitochondrial respiration and glycolytic activity in TH17 (T cells) which correlate to changes in metabolite levels.
(Gerriets VA et al., 2015. J Clin invest.)
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)
Oxy
gen
Con
sum
ptio
n R
ate
(OC
R)
(pm
ol/m
in)
ECAR
(mpH
/min
)
DM
SO GEF
ERLO
DMSO
120
60
0
****** ***
**
HCC827 PC9 H1975
GEF ERLO
DM
SO GEF
ERLO
DM
SO GEF
ERLO
1 2 3
350
175
0pmol
/106 c
ells
**
1 2 3
2,500
1,250
0
pmol
/106 c
ells
*
*
1 2 3
80
40
0pmol
/106 c
ells *
1 2 3
90
45
0pmol
/106 c
ells *
1 2 3
350
175
0pmol
/106 c
ells **
1 2 3
300
150
0pmol
/106 c
ells ***
***
1 2 3
350
175
0pmol
/106 c
ells * **
1 2 3
120
60
0pmol
/106 c
ells **
**
1 2 3
10,000
1,000
100
10pmol
/106 c
ells
****
1 2 3
50,000
25,000
0pmol
/106 c
ells
**
1 2 3
20,000
10,000
0pmol
/106 c
ells **
1 2 3
1,000
500
0pmol
/106 c
ells *
Glucose
GLUTsHKs
PKMsLDHs
PDHs
G6P 6PG
X5PF6P
FBP
DHAP
ATP
G3P 3PG
PEP
PyruvateLactate
Acetyl-CoA
E4P
Ru5P
R5P
60
50
40
30
20
10
00 25 50 75
Glucose Oligomycin 2-DGTh1 Th17 Treg
Extra
cellu
ar A
cidi
ficat
ion
Rat
e (E
CAR
)(m
pH/m
in)
100 125 150
Th1 Th17 Treg60
50
40
30
20
10
00 25 50 75
Glucose Oligomycin 2-DGTh1 Th17 Treg
Extra
cellu
ar A
cidi
ficat
ion
Rat
e (E
CAR
)(m
pH/m
in)
100 125 150
12001400
1000800600400200
00 25 50 75
Time (min)
FCCPOligomycinRotenone &antimycin A
Oxy
gen
Con
sum
ptio
n R
ate
(OC
R)
(pm
ol/m
in)
100 125 150
60
50
40
30
20
10
00 25 50 75
Glucose Oligomycin 2-DGTh1 Th17 Treg
Extra
cellu
ar A
cidi
ficat
ion
Rat
e (E
CAR
)(m
pH/m
in)
100 125 150
12001400
1000800600400200
00 25 50 75
Time (min)
FCCPOligomycinRotenone &antimycin A
Oxy
gen
Con
sum
ptio
n R
ate
(OC
R)
(pm
ol/m
in)
100 125 150
60
50
40
30
20
10
00 25 50 75
Glucose Oligomycin 2-DGTh1 Th17 Treg
Extra
cellu
ar A
cidi
ficat
ion
Rat
e (E
CAR
)(m
pH/m
in)
100 125 150
12001400
1000800600400200
00 25 50 75
Time (min)
FCCPOligomycinRotenone &antimycin A
Oxy
gen
Con
sum
ptio
n R
ate
(OC
R)
(pm
ol/m
in)
100 125 150
12001400
1000800600400200
00 25 50 75
Time (min)
FCCPOligomycinRotenone &antimycin A
Oxy
gen
Con
sum
ptio
n R
ate
(OC
R)
(pm
ol/m
in)
100 125 150
“With very little learning curve, XF Technology provides high-quality data. We generated publishable results within the first month.”
- researcher at Case Western
Reserve University
“When we decided to more closely investigate branched - chain amino acid metabolism, we chose to incorporate our XF Technology, knowing that it is a powerful tool for assessing mitochondrial function and metabolism.” - researcher at university of
California, san diego
“We were really surprised by the impact of measuring metabolism in our model system. This opens up new research avenues for us.” - researcher at rosalind Franklin
medical schoolGEF= Gefitinib ERlO= Erolotinib
What ouR customeRs aRe sayinG
Human lung adenocarcinoma cells
murine T cells
Functional metabolic assaysthe Genotype-phenotype link
The traditional paradigm encompassing the flow of information from gene to protein to function can be found in nearly every biology and biochemistry textbook. At the time, this discovery was thought to explain all of biology, health, and disease. However, only focusing on the expression of a single gene or protein neglects the multi-faceted consequences of that expression on metabolism, as well as overall cell and tissue health.
FullPicture of CellHealth
Gene Expression
FunctionalMetabolism
ProteinExpression
GLUCOSE
GLUTAMATE
FATTY ACID
FATTY ACIDLACTATE CITRATE
Acetyl-CoA
TCA
GLUTAMINEGLYCOLYSIS
(ECAR)
MITOCHONDRIAL RESPIRATION
(OCR)
GLUTAMATE
ETC
PYRUVATE
subsTrATes And meTAbolism
mitochondria are at the crux of cellular energy generation, intracellular signaling, and cell death and survival regulation. Compromised mitochondria can strain the expansive and intricate cellular metabolic network. There is increasing appreciation for the role of mitochondria in disease pathology, etiology, and cell health.
integrating processes that demonstrate the link amongst genes, proteins, and metabolism allows researchers to analytically answer their scientific questions. XF Technology provides researchers the necessary tools to measure the functional, metabolic impact of gene and protein expression, faster and easier using live cells.
PI3/AKT
GLUTAMINOLYSIS
PI3/AKT
HIF1
HIF1 LIPID SYNTHESIS
HIF1
p53
MYC
MYC
MYC
PYRUVATE
TCA
GLUCOSE
GLYCOLYSIS
Genes & meTAbolism linK
© 2015 All rights reserved. Seahorse Bioscience and the Seahorse logo are trademarks of Seahorse Bioscience Inc. The content in this brochure is for informational purposes only and may be subject to change without notice.
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XF Mito Fuel Flex Test Profile Mitochondrial Function
XF Glycolysis Stress Test Profile Glycolytic Function
05
1015202530354045
Extra
cellu
lar A
cidi
ficat
ion
Rate
(EC
AR)
(mpH
/min
)
Glucose
Glycolysis
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
FCCPRotenone & antimycin A
Proton Leak
00
4080
120160200240280320360
10 20 30 40 50 60 70 80 90 100 110
Non-mitochondrial Oxygen Consumption
Time (minutes)
Oxy
gen
Con
sum
ptio
n Ra
te (O
CR)
(p
mol
/min
)
Spare Capacity
ATPProduction
Oligomycin
Maximal Respiration
Basal 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
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
Aerobic
Quiescent
Energetic
Glycolytic
BaselinePhenotype
StressedPhenotype
Metabolic Potentia
l
Glucose Pathway
% G
LC+G
LN+F
A Fu
el O
xida
tion
Glutamine Pathway Fatty Acid PathwayGlucose Pathway Glutamine Pathway Fatty Acid Pathway
% G
LC+G
LN+F
A O
xida
tion
XF Mito Fuel Flex Test ProfileMitochondrial Function
100
80
60
40
20
0
Capa
city
Capa
city
Capa
city
Flexibility
DependencyDependency
Dependency
Flexibility
Rev
1