Application Note
Cell Analysis andMetabolomics

Extracellular Flux Analysis and 13C
Stable-Isotope Tracing Reveals
Metabolic Changes in LPS-Stimulated
Macrophages
Authors
Agnieszka Broda and Gerald
Larrouy-Maumus
MRC Centre for MolecularBacteriology and Infection,
Department of Life Sciences,
Faculty of Natural Sciences,
Imperial College London,
London, SW7 2AZ, UK
Sufyan Pandor
Agilent Technologies, Inc.
Cheadle, UK

Abstract
Eukaryotic cells are known to generate ATP by mitochondrial (oxidative
phosphorylation) and non-mitochondrial (glycolysis) metabolism. Agilent Seahorsetechnology is an invaluable tool to gain access in real time to the bioenergetics
activity of the cell by measuring cellular oxygen consumption rates (OCR) andextracellular acidification rates (ECAR) as measures of mitochondrial respirationand glycolysis, respectively. Even though Seahorse provides phenotypic information
about the bioenergetic state of the cell, an in-depth understanding of the changes
in the metabolic pathways requires measuring the abundances and rates ofmetabolite interconversion of the molecules involved in the key metabolic pathways(e.g. glycolysis, tricarboxylic acid cycle (TCA) cycle, pentose phosphates pathway).
This is achieved by performing stable-isotope tracing analysis on an LC/Q-TOF,
providing a detailed view of cellular metabolism. Advancements in LC/Q-TOF
technology coupled with integrated qualitative flux analysis software reveal moredetails by tracking the in vivo turnover of metabolites through pathways. In thisapplication note, we present an example of using both Seahorse XF technology
and 13C stable-isotope-tracing analysis with Agilent MassHunter VistaFlux
software to study the response to lipopolysaccharide (LPS) treatment of RAW
264.7 macrophages. The aim of this application note is to demonstrate thecomplementarity of phenotypic analysis using Seahorse technology and targetedstable-isotope-tracing analysis using an Agilent 6546 LC/Q-TOF.

Introduction
Immunometabolism research hassignificantly expanded our understandingof immune cell function in recent years.
Modulation of metabolism appears
to be crucial for controlling cell fate.1,2
In this context, Seahorse technology
enables insight into the bioenergetic
state of the cell in response to stimuli.
This is achieved by simultaneously
measuring, in real time, the changesin oxygen consumption rate (OCR, aqualitative indicator of mitochondrial
oxidative phosphorylation) and the rateof extracellular acidification (ECAR, aqualitative indicator of glycolysis), as
shown in Figure 1.
To gain further insight into themechanism leading to changes in
OCR and ECAR in response to stimuli,
metabolomics allows a direct snapshotof pathway activities and metabolite
regulation. For yet more detailed
information on metabolic pathwaychanges, stable-isotope‑tracing analysis(e.g. 13C, 15N, 2H) can be applied.
Stable‑isotope labeling provides
a different picture of intracellular
metabolism than metabolomics.
Although untargeted metabolomics
provides the abundance of different
metabolites within metabolic pathways,
several metabolic changes do nota fortiori result in an increase or adecrease in the metabolite level.
Stable‑isotope‑tracing provides
information not revealed by conventional
untargeted metabolomics by measuring
the rates of metabolite interconversion
as a readout of metabolic
enzyme regulation. This makes
stable‑isotope‑tracer studies a powerful
option to probe metabolic changes incomplex biological systems.
Insights into the full picture of cell
metabolism from the combination of
Seahorse and LC/Q-TOF data can informbiological research as answers from2

one platform can drive experiments on
the other, allowing a feedback loop forfollow-up experiments (Figure 2).

(specific assays on the Seahorse andpathway-driven experiments on the
LC/Q-TOF).

Such workflows can provide accurate
answers to biological questions much
faster as both experiments are targeted

Within immunometabolism research,macrophages are known to play a central
role in pathogen recognition, exhibiting

Figure 1. Schematic illustration of cellular metabolism pathways and the link between phenotypicmeasurements using Agilent Seahorse (ECAR and OCR) and the metabolites from relevant metabolic
pathways (e.g., glycolysis, TCA cycle, and mitochondrial respiration) using stable-isotope-tracing
analysis by LC/Q-TOF. G-6-P: glucose-6-phosphate; R-5-P: ribose-5-phosphate; G-3-P: glyceraldehyde-3phosphate; PEP: phosphoenolpyruvate; ECAR: extracellular acidification rate; OCR: oxygen consumption
rate; ETC: electron transport chain.

Biological question
Phenotypic in vitro assay• Grow cells• Biochemistry/immunohistochemistry

Follow-up
experiment

Extracellular flux analysis• Grow cells• Determine phenotype

Stable-isotope-tracing analysis• Grow cells with labelled substrate• Determine flux for target metabolites

Answers and mechanisms
Figure 2. Workflow used to address biological questions by combining conventional phenotypic assays,
Agilent Seahorse measurements, and stable-isotope-tracing analysis on an LC/Q-TOF.

an array of immediate physiologicalremodeling in response to pathogen
stimuli. Elucidation of the mechanisms
regulating metabolic pathways andthe balance of metabolites is crucial
for understanding macrophagefunction and their remodeling upon
external stimuli. One such example
is macrophage activation. Classicalactivation of macrophages is performedby pro-inflammatory stimuli such as
LPS and/or interferon gamma (IFNγ).
Several studies have demonstrated
that activated macrophages undergoa metabolic switch that includes
immediate up-regulation of glycolysis,
remodeling of the TCA cycle, and theinhibition of mitochondrial respiration.3
These processes follow an orchestrated
sequence of metabolic adaptions
that can be followed in real time via
extracellular flux analysis.10
For example, itaconic acid, a
non‑amino organic acid derived fromcis‑aconitate by the action of cisaconitate decarboxylase (cadA), is
known to be one of the most highly
induced metabolites following LPS
stimulation in bone marrow derived
macrophages (BMDMs).4,5 This process
is known to be energy costly for themacrophages as they lose the ability toperform mitochondrial substrate-level
phosphorylation.6
In this application note, we present
an example of the combination of
Seahorse XF technology with 13C
stable-isotope‑tracing analysis using
MassHunter VistaFlux software to

Extracellular flux analysis on the
Seahorse XFp Analyzer

understand the response of RAW 264.7
macrophages to 4 hours of LPS
treatment. The presented workflow
can be adapted to different cell types
to decipher the molecular mechanisms
underpinning immunometabolism.

Experimental
Cell culture and reagentsRAW 264.7 cells were prepared from thefrozen stock (–80 °C) and cultured in atissue culture flask (~0.5 × 105 cells/mL)in DMEM medium (Dulbecco’s Modified
Eagle’s Medium, Sigma-Aldrich)
supplemented with 10% heat-inactivatedfetal bovine serum (FBS). After 48 hours
of incubation at 37 °C in CO2, confluent
cells were split and cultured in fresh
media. The process of splitting was
repeated five to six times until the cells
were fully recovered from being frozen.

Phenotypic in vitro assay-cytokine
measurement by ELISAThe RAW 264.7 cells were cultured ina six-well plate and incubated at 37 °C
in CO2 for three to five hours to adhere,
then treated with LPS at 100 ng/mL finalor plain media for the next four hours.
The supernatant was collected forcytokine TNFα analysis. The TNFα
production by RAW 264.7 macrophages
was determined using the mouse TNFαELISA kit (Ready-SET-Go; Affymetrix
eBioscience; Invitrogen 88732486)
according to the manufacturer’s
instructions. Absorbance readings were
measured at 450 nm.

RAW 264.7 cells were seeded on aneight-well miniplate at cell densitiesof 4 × 105 cells/mL and left to adhere
overnight. Cells were or were not treatedwith LPS at 100 ng/mL final or plain
media, and after four hours, the OCR
and ECAR were measured using an
Agilent Seahorse XFp Analyzer. The day
before the assay, the sensor cartridge
was hydrated by filling the utility plate’smoats and wells with 400 and 200 μL of
double-distilled sterile water, respectively,
and incubating overnight at 37 °C in a
non‑CO2 incubator. On the day of theassay, the water was replaced with
200 μL of prewarmed Agilent XF calibrantand incubated for another one hour. Also,
the culture medium was replaced with180 μL of Agilent Seahorse XF RPMI
medium, pH 7.4, that was supplemented
with 10 mM glucose, 2 mM sodium
pyruvate, and 2 mM glutamine, andthe cells were incubated at 37 °C in a
non-CO2 incubator for one hour. The
Seahorse miniplate with cells was placed
into the XFp Analyzer for subsequent
analysis at 37 °C. Measurement cycles
consisted of three minutes mixing andthree minutes measuring. Baseline
rates were measured at 37 °C threetimes before sequentially injecting
the following mitochondrial inhibitors:
oligomycin (2 μM), carbonyl cyanidep-(trifluoromethoxy) phenylhydrazone(FCCP, 2 μM), and a rotenone/antimycin
A mixture (0.5 μM) all from the Agilent
Seahorse XFp Cell Mito Stress Test kit.
After the addition of each inhibitor, three
readings were taken. OCR and ECAR

Seahorse XFp Analyzer workflow-18 hours-4 hours

Seed cells
Hydrate cartridge

Pretreat cells-1 hours
Change media
Load and calibrate
cartridge

0 hours

Acquire data

1 hourExtract phenotype
parameters3were automatically calculated by the
Seahorse XFp Wave software. Each data
point represents an average of threedifferent well measurements that werenormalized to the number of cells per
well. For a more complete understandingof the general metabolic changes, aphenotype analysis was conducted using
the Cell Mito Stress Test data result file.

Qualitative flux analysis
Metabolite extraction
RAW 264.7 cells were seeded ona six-well plate at a cell density of
5 × 105 cells/mL and incubated for three
to five hours to adhere. After this time,the media was changed for the media
supplemented with [U-13C6]‑glucose
at 4.5 mg/mL. Cells were or were nottreated with LPS at 100 ng/mL media
concentration and in the presence of[U-13C6]-glucose at a concentrationequivalent to a 1:1 ratio of 12C and 13C
glucose present in the culture medium,
then incubated for four hours. The
microplate was placed on ice, andthe media was removed carefully.
The adhered cells were washed threetimes with cold PBS before additionof a metabolite extraction buffer(acetonitrile, methanol, and water at aratio of 40:40:20 v/v/v at –20 °C) at adensity of 107 cells/mL. Cells were thenscraped and transferred to an Eppendorf
vial. A 100 μL aliquot of the metabolite
solution was then mixed with 100 μL
of acetonitrile with 0.2% acetic acid at–20 °C and centrifuged for 10 minutes at
17,000 g at 4 °C. The final concentrationof 70% acetonitrile was compatible withthe starting conditions of the HILIC
chromatography. The supernatant wasthen transferred to an Agilent LC/MS
V-shape vial (p/n 5188-2788) and 4 μL
was injected into the LC/MS.

4

LC/Q-TOF data acquisition

Target metabolite list creation

Data were acquired on an Agilent
1290 Infinity II LC coupled toan 6546 LC/Q‑TOF system.
Chromatographic separation
was performed on an Agilent
InfinityLab Poroshell 120 HILIC-Z,
2.1 × 100 mm, 2.7 μm column(part number 675775‑924). The HILIC
methodology was optimized for polar
acidic metabolites (details in Table 1).
For easy and consistent mobile phase
preparation, a concentrated 10x solution
consisting of 100 mM ammonium
acetate, pH 9.0, in water was prepared to
produce mobile phases A and B.

As Seahorse provides phenotypic
information about glycolysis (ECAR) andmitochondrial oxidative phosphorylation(OCR), a target list of metabolites related
to those pathways was created using
Agilent MassHunter Pathways to PCDL
software. From a public pathways
database, the software generates atarget personal compound database(PCDL) that contains names, formulas,and various identifiers. Addition of
metabolite retention times in the target
PCDL were provided from a pre-existing
in-house database.

Table 1. Liquid chromatography conditions.
LC Conditions
ColumnAgilent InfinityLab Poroshell 120 HILIC-Z, 2.1 × 100 mm, 2.7 μm (p/n 675775-924)

Mobile PhaseA) 10 mM ammonium acetate in water, pH 9 with 5 μm Agilent InfinityLab Deactivator
Additive (p/n 5191-4506)
B) 10 mM ammonium acetate, pH 9 in 10:90 (v:v) water/acetonitrile

Flow Rate

0.5 mL/min

Gradient

Time (min)
0
11.5
12
15
20

Column Temperature

30 °C

Injection Volume

1 μL

Multisampler Temperature

6 °C

%A
%B
0
100
30
70
0
100
0
100
Post time

Table 2. Mass spectrometry conditions.
MS Conditions
MS System

Agilent 6546 LC/Q-TOF

SWARM Autotune Selection

m/z 50 to 750 fragile ion mode

Ionization Source

Agilent Jet Stream

Polarity

Negative

Gas Temperature

200 °C

Drying Gas Flow

10 L/min

Nebulizer Pressure

40 psig

Sheath Gas Temperature

300 °C

Sheath Gas Flow

12 L/minCapillary Voltage

3000 V

Nozzle Voltage

0V

Fragmentor

115

Acquisition Range

m/z 40–1000

Reference Massm/z 68.995758 and 980.016375

Statistical analysis
Data are presented as the mean ±standard error of the mean fromtwo biological replicates and four
technical replicates per condition
for all experiments. Unpaired
two‑tailed Student’s t-tests wereused to compare values, with p <0.05
considered significant.

Results and discussion
LPS stimulation induces a large
increase in TNFα
RAW 264.7 cells are widely used tounderstand molecular mechanismsof macrophage activation. Here, we
assessed macrophage activation bymeasuring the amount of tumor necrosis
factor alpha (TNFα) released in the cell
culture medium in response to LPS
stimulation. As expected, activation ofVistaFlux workflow
Acquire LC/MS
data

Extract
isotopologue
results

Create target
metabolite list

RAW 264.7 cells by 100 ng/mL of LPS for
four hours leads to a 100-fold increasein the abundance of secreted TNFα,
confirming the activation state of thecells (Figure 3).
1.0E+04

TNFα (pg/mL)

Agilent MassHunter Profinder 10 is thebatch-processing module of VistaFlux.
Data files were imported and assigned totreatment groups. The chromatographic
data were time-aligned against an
in-house database of compoundswith known retention times. The batch
isotopologue extraction wizard wasused to extract isotopologues for thetarget metabolites list as well as tocorrect for natural abundance of 13C andfor the tracer purity. In stable-isotope
tracing, results are self-normalized foreach metabolite as the isotopologue
enrichment percentage is calculated
relative to the other isotopologues. The
13
C tracer purity in this experiment was
50%, so the result of these corrections isthat 100% label incorporation represents
full incorporation of 13C into themetabolite. The results from Profinder
were transferred to Omix Premium,
another module of VistaFlux, forvisualization of metabolic fluxes onpathways.

1.0E+03

1.0E+02

1.0E+01
Control

LPS-treated

Visualize resultson pathway

LPS stimulation induces a shift
towards a glycolytic phenotype
To demonstrate how LPS activation
impacts cell bioenergetics in RAW 264.7,
we investigated the cell phenotype with
the Seahorse XFp Analyzer (Figure 4).
The Seahorse phenotype analysis
software shows the metabolic activityof cells under basal conditions andunder stressed conditions to reveal
the metabolic potential. The analysis
showed a general shift of the RAW 264.7
towards a more glycolytic phenotype
when stimulated with LPS in the basal
as well as in the stressed phenotype.
This is in line with the literature showingthat a glycolytic switch is an essential
component of the pro-inflammatory
function of macrophages.7-9

Figure 3. Level of TNFα in response to four hours of
stimulation by 100 ng/mL of LPS in RAW 264.7 cells.
30

Aerobic

Energetic

25
Mitochondrial respiration
OCR (pmol/min/10k cells)

Batch isotopologue data analysis

Control
LPS
20

15

10

5

Quiescent00Glycolytic
246ECAR (mpH/min/10k cells)
Glycolysis

Figure 4. OCR versus ECAR plot for metabolic phenotype analysis measured intriplicates. Open quadrats represent the basal phenotype and closed quadrats thestressed phenotype (metabolic capacity after injection of oligomycin and FCCP).
Four hours of stimulation by 100 ng/mL of LPS in RAW 264.7 cells induce a shift
towards increased glycolytic activity.

5

LPS stimulation results in aredirection of carbon flux towards
itaconic acid synthesis
As shown previously by Seahorse XFp
analysis, LPS stimulation of RAW 264.7
cells increases ECAR. As discussed
earlier, ECAR informs on glycolysis.
Therefore, to gain insight into thechanges in metabolite turnover in
response to LPS stimuli leading tochanges in ECAR, we undertook[U-13C6]‑glucose stable-isotope tracing
focusing on metabolites involved incentral carbon catabolism and the TCA
cycle (Table 3). RAW 264.7 cells were
simulated or not with LPS for four hours
in a culture medium containing[U-13C6]‑glucose, and incorporation of 13C
was determined by LC/MS.
As shown in Figure 5, both lactate andpyruvate display very high levels of
13
C incorporation, reaching up to 95%
labeled independently of the treatment
applied. However, the major change
occurs at the level of cis-aconitate,and specifically itaconic acid, where
LPS activation drastically alters theisotopologue distribution. Effectively,
upon LPS stimulation, a large increasein 13C incorporation is observed for M+1,
M+2, M+4, and M+5 concomitant witha decrease in M+0. This is consistent
with the literature where LPS activation
is known to promote the production

6of itaconic acid.4,5 Based on the XF
data presented here, LPS stimulation
leads to an increase in glycolysis. We
therefore investigated the change in theisotopologue distribution of metabolites
involved in this pathway. As shown in
Figure 5, we observed an increase in
13
C incorporation in metabolites involved
in glycolysis as well as the oxidative
branch of the TCA cycle leading towards
the production of itaconic acid. An

associated decrease in metabolites
found in the reductive branch of the
TCA cycle was observed, confirming an
inhibition of the turnover of metabolites
from the reductive branch of the TCA
cycle upon LPS stimulation. Taken
together, these data suggest that upon
LPS stimulation, RAW 264.7 cells redirect
their carbon flux towards itaconic acidproduction, leading to an alteration in13
C turnover in the TCA cycle.

Table 3. Target metabolite list for isotopologue extraction showing mean measured retention
time of eight control samples.
Information Pathway

ECAR

OCR

FormulaRT (min)

CAS

β-D-Glucose 6-phosphate

Metabolite

C6H13O9P

9.60

15209-12-8

D-Fructose 6-phosphate

C6H13O9P

8.22

643-13-0

β-D-Fructose 1,6-bisphosphate

C6H14O12P2

10.2

488-69-7

D-Glyceraldehyde 3-phosphate

C3H7O6P

7.03

591-57-1

Dihydroxyacetone phosphate

C3H7O6P

7.95

57-04-5

Pyruvic acid

C3H4O41.40

127-17-4

Lactic acid

C3H6O3

2.21

50-21-5Citric acid

C6H8O7

8.88

77-92-9cis-Aconitic acid

C6H6O6

7.86

585-84-2

D-threo-Isocitric acid

C6H8O7

6.94

6061-97-8

Oxoglutaric acid

C5H6O5

6.04

328-50-7

L-Glutamate

C5H9NO4

6.25

56-86-0

Succinic acid

C4H6O4

6.54

110-15-6

Fumaric acid

C4H4O46.88

110-17-8

L-Malic acid

C4H6O5

6.79

97-67-6

L-Aspartic acid

C4H7NO4

1.22

56-84-8

Itaconic acid

C5H6O4

6.68

97-65-4

Figure 5. Summary of [U-13C6]-glucose stable-isotope-tracing analysis of RAW 264.7 cells stimulated for four hours by 100 ng/mL of LPS compared to untreated
RAW 264.7 cells (control). Results are displayed as quilt plots on the pathways where each quilt plot shows corrected abundance for each isotopologue for control
and treated cells. Statistical significance is denoted by an *.

7

Conclusion
Combining real-time extracellular
flux information with 13C
stable‑isotope‑tracing allows greater
insight into the mechanism ofmacrophage activation. Where Seahorsetechnology provides information
about the metabolic phenotypes andthe activities of the two major energy
pathways from a macroscopic view, 13C
stable-isotope-tracing analysis allows amicroscopic insight into the pathways
leading to these changes.
Seahorse XF assays provide real-time,
live-cell metabolic analysis. With thistechnology, a glycolytic shift in thephenotype of the living macrophages
was shown, which is a prerequisite
for pro-inflammatory macrophageactivation. This was confirmed whenlooking into the metabolic details by
qualitative flux analysis. The increased
glycolytic rate was confirmed by theincreased incorporation of 13C into
glycolysis metabolites relative to thebasal case. Flux analysis also showed
an increased production of itaconic acid,a potent antimicrobial compound
produced by pro-inflammatory
macrophages, and thereby provided amore detailed picture of the changes
in metabolism.

www.agilent.com/chem
For Research Use Only. Not for use in diagnostic procedures.
DE.5524421296
This information is subject to change without notice.
© Agilent Technologies, Inc. 2020
Printed in the USA, April 14, 2020
5994-1846EN

This workflow and the technologies
used can be applied to other cell
types to study cell metabolism at thephenotype and metabolite levels to
uncover molecular mechanisms of cell
metabolism in response to external
triggers or genetic manipulations.

6.

Nemeth, B.et al. Abolition of
mitochondrial substrate-level
phosphorylation by itaconic acidproduced by LPS-induced Irg1
expression in cells of murine
macrophage lineage. FASEB J 2016,30, 286–300.

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Artyomov, M. N.; Sergushichev, A.;
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Mills, E. L. et al. Itaconate is an
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10. Kam, Y. et al. Real Time
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