Metabolic flux profiling of
Escherichia coli
mutants in central
carbon metabolism using GC-MS
Eliane Fischer and Uwe Sauer
Institute of Biotechnology, ETH Zu
¨
rich, Zu
¨
rich, Switzerland
We describe here a novel methodology for rapid diagnosis of
metabolic changes, which is based on probabilistic equations
that relate GC-MS-derived mass distributions in proteino-
genic amino acids to in vivo enzyme activities. This metabolic
flux ratio analysis by GC-MS provides a comprehensive
perspective on central metabolism by quantifying 14 ratios
of fluxes through converging pathways and reactions from
[1-
13
C] and [U-
13
C]glucose experiments. Reliability and
accuracy of this method were experimentally verified by
successfully capturing expected flux responses of Escherichia
coli to environmental modifications and seven knockout
mutations in all major pathways of central metabolism.
Furthermore, several mutants exhibited additional, unex-
pected flux responses that provide new insights into the
behavior of the metabolic network in its entirety. Most
prominently, the low in vivo activity of the Entner–
Doudoroff pathway in wild-type E. coli increased up to a

13
C-labeling
experiments. In this approach,
13
C-labeled substrates are
administered and
13
C-labeled products of metabolism are
analyzed by methods that distinguish between different
isotope labeling patterns, in particular NMR and MS
[2,3,8]. In the most advanced methodology, a comprehen-
sive isotope isomer (isotopomer) model of metabolism is
used to map metabolic fluxes in an iterative fitting procedure
on the isotopomer pattern of network metabolites that are
deduced from NMR or MS data [2]. This global data
interpretation enables integrated and quantitative consid-
eration of all physiological and
13
C-labeling data. Typically,
protein hydrolysates are subjected to NMR or GC-MS
analysis, which provides not only isotopomer pattern of the
amino acids but also of their related precursor molecules
that are key components of central metabolism. With the
presently available models and software, these isotopomer
balancing methods have attained a high level of precision
and applicability [2,9,10].
In contrast to isotopomer balancing, direct analytical
interpretation of
13
C-labeling patterns has long been used not

accepted 7 January 2003)
Eur. J. Biochem. 270, 880–891 (2003) Ó FEBS 2003 doi:10.1046/j.1432-1033.2003.03448.x
Hence, the favorable agreement of results obtained by both
approaches for the same experimental data provides strong
evidence for their reliability [18,19].
Here we develop a novel methodology for metabolic flux
ratio analysis based on GC-MS data from [1-
13
C] and
[U-
13
C]glucose experiments. This methodology is used for
metabolic network analysis in Escherichia coli strains with
knockout mutations in all major pathways of central carbon
metabolism. The analyses presented here provide not only
novel insights into central metabolism but represent also
experimental verification of the reliability of metabolic flux
ratio analysis by GC-MS.
Materials and methods
Strains, media, and growth conditions
The nomenclature of the employed E. coli knockout
mutants indicates the affected genes (Table 1). Unless
indicated otherwise, aerobic batch cultures were grown at
37 °C in 500 mL baffled shake flasks with 50 mL of M9
minimal medium on a gyratory shaker at 200 r.p.m.
Anaerobic cultures were grown in 100 mL sealed glass
flasks containing 50 mL medium that was gassed with N
2
prior to sterilization for 10 min. The M9 medium contained
per litre of deionized water: 0.8 g NH

4
Æ7H
2
O, 0.12 g CuCl
2
Æ2H
2
O,
0.12 g MnSO
4
ÆH
2
O, 0.18 g CoCl
2
Æ6H
2
O, and 22.25 g
Na
2
EDTAÆ2H
2
O. Filter-sterilized glucose was added to a
final concentration of 3 g per litre. For
13
C-labeling
experiments, glucose was added either entirely as the
[1-
13
C] labeled isotope isomer (> 99%; Euriso-top, GIF-
sur-Yvette, France) or as a mixture of 20% (w/w) [U-

exponential growth-phase, defined as D
600
of 0.8–1.5, and
centrifuged at 14 000 g at room temp. for 5 min. Pellets
were washed once in 1 mL 0.9% (w/v) NaCl and hydro-
lyzed in 1.5 mL 6
M
HCl at 105 °Cfor24hinsealedglass
tubes. The hydrolysate was dried in a vacuum centrifuge
at room temperature and derivatized at 85 °Cin50lL
tetrahydrofurane (Fluka, Switzerland) and 50 lLof
N-(tert-butyldimethylsilyl)-N-methyl-trifluoroacetamide
(Fluka, Switzerland) for 60 min [20]. 1 lL of derivatized
sample was injected into a series 8000 GC, combined
with an MD 800 mass spectrometer (Fisons Instruments,
Beverly, MA, USA), on a SPB-1 column (SUPELCO,
30 m · 0.32 mm · 0.25 lm fused silica) with a split
injection of 1 : 20. GC conditions were: carrier gas
(helium) flow rate at 2 mL per min, oven temperature
programmed from 150 °C(2min)to280°Cat3°Cper
min, source temperature at 200 °C and interface tempera-
ture at 250 °C. Electron impact (EI) spectra were obtained
at )70 eV. GC-MS raw data were analyzed using the
software package MassLab (Fisons), avoiding detector
overload and isotope fractionation as described [20].
The amino acids analyzed by GC-MS were aspartate,
glutamate, glycine, histidine, isoleucine, leucine, phenyl-
alanine, proline, serine, threonine, tyrosine, and valine for
[U-
13

B
+
supE thi D(lac-proAB)] [45]
Zwf G6P dehydrogenase-deficient K10 (DF2001) [46]
Pgi Phosphoglucose isomerase-deficient W3110 (LJ110) [47]
PfkA Phosphofructokinase-deficient K10 (AM1) [48]
PykAF Pyruvate kinase-deficient JM101 (PB25) [49]
Mae/Pck Malic enzymes (ScfA and Mae)- and PEP carboxykinase-deficient K12 (EJ1321) [50]
SdhA/Mdh Succinate dehydrogenase- and malate dehydrogenase-deficient MG1655 (DL323) [29]
FumA Fumarase A-deficient K12 (EJ1535) [30]
Ó FEBS 2003 Metabolic flux profiling in E. coli (Eur. J. Biochem. 270) 881
Correction for naturally occurring isotopes
The obtained EI spectral data are sets of ion clusters, each
representing the distribution of mass isotopomers of a given
amino-acid fragment. For each fragment a,amass
isotopomer distribution vector (MDV):
MDV
a
¼
ðm
0
Þ
ðm
1
Þ
ðm
2
Þ
ÁÁÁ
ðm

derivatization reagent, and (c)
13
C in the carbon skeleton of
the amino-acid fragment that were incorporated from
naturally or artificially
13
C-labeled substrates. To obtain
the exclusive mass isotope distribution of the carbon
skeleton, MDV
a
were corrected for the natural isotope
abundance of O, N, H, Si, S, and C atoms in the derivatizing
agent by using correction matrices as described elsewhere
[23], yielding MDV*
a
. Prior to analysis, the contribution of
13
C from unlabeled biomass in culture inocula was
subtracted from MDV*
a
yielding MDV
AA
according to
MDV
AA
¼
MDV
Ã
a
À f

c
ðiÞ
1
n
i

ð3Þ
c
0
and c
1
represent the natural abundance of
12
Cand
13
C,
respectively, and
n
i
ÀÁ
is a binomial coefficient. The corrected
MDV
AA
now represent the mass distributions of the carbon
skeletons due to substrate incorporation (Fig. 2A).
MDV of metabolites
Amino acids are derived from one or more metabolic
intermediates and MDV
M
of these metabolites (or their

MDV
M
were obtained from a least squares fit to all
MDV
AA
using the MATLAB function lsqnonlin with the
additional constraint that the sum of their element equals 1.
MDV of substrate fragments
A fragment with n carbon atoms of a mixture of uniformly
and naturally labeled substrate has the following mass
distribution
MDV
S;n
U
ðiÞ¼ ð1 À lÞ c
ðnÀiÞ
0
c
i
1
þ lð1 À pÞ
ðnÀiÞ
p
i

n
i

ð5Þ
where l is the labeled fraction and p is the purity of the

ð6Þ
A summary of all obtained MDV is given in Table 2.
Calculation of metabolic flux ratios
The intracellular pool of a given metabolite can be derived
from other metabolite pools through biochemical pathways
(Fig. 2B). The fractional contribution f of a pathway to a
target metabolite pool with MDV1 was determined as:
f ¼
MDV1 À MDV3
MDV2 À MDV3
ð7Þ
where MDV2 and MDV3 are the mass distributions of the
source metabolites degraded through the examined and the
alternative pathway, respectively. As MDV are vectors and
Fig. 2. Example of the information flow from experimentally deter-
mined mass distributions in amino acids to metabolites (A) and the
calculation of flux ratios (B). Bars illustrating the mass distribution
(m
0
, m
1
,…,m
n
)aredrawntoscalefortheexampleofanE. coli batch
culture grown on a mixture of 20% [U-
13
C] and 80% unlabeled
glucose. Mass distributions of amino-acid fragments (MDV
AA
)are

ð8Þ
with f
3
¼ 1 ) f
1
) f
2
.
The origin of several intracellular metabolite pools can be
determined with Eqns (7) and (8). Specifically, MDV
M
of six
metabolites and MDV
AA
of two amino acids were used for
metabolic flux ratio analysis (Table 2) together with MDV
S
of substrate fragments. In some cases, however, the
metabolic precursors MDV2 or MDV3 were combinations
of two MDV
M
. Eqn (4) was applied to calculate the mass
distribution of these combinations.
Pentose phosphate pathway
E. coli can potentially catabolize glucose to trioses via three
different biochemical pathways, i.e. glycolysis, ED pathway,
and PP pathway [24] (Fig. 1). Upon growth on a mixture of
[U-
13
C] and unlabeled glucose, introduction and cleavage

flux via transketolase.
Two other metabolites that reflect transketolase and
transaldolase activities are P5P and E4P. P5P molecules
may be produced either via the oxidative PP pathway
from G6P, thus yielding an intact five carbon skeleton
from a source molecule of glucose, or via the transketolase
reaction, which cleaves between C
3
–C
4
. Additionally, P5P
may also originate from E4P and a one carbon unit
through the combined action of transaldolase and trans-
ketolase. The contributions of the three converging
pathways are thus calculated using Eqn (8). As transketo-
lase can reversibly cleave P5P and multiple cycling may
occur through the PP pathway, P5P from G6P is
calculated as a lower bound for the fraction of P5P
molecules that were generated via the oxidative PP
pathway.
The second PP pathway intermediate, E4P, is either
produced from F6P as an uncleaved four carbon unit or via
the combined activity of transketolase and transaldolase
from P5P. The latter introduces E4P molecules with cleaved
C
1
–C
2
bonds originating from the fraction of P5P that was
cleaved between C

input substrate, it was treated as an additional unknown
using
f
f à l
CO
2
!
¼
OAA
ð1À4Þ
À OGA
ð2À5Þ
Â
PEP
ð1À3Þ
0
Ã
À OGA
ð2À5Þ
0 PEP
ð1À3Þ
ÂÃ
À PEP
ð1À3Þ
0
ÂÃ
!
ð9Þ
The fraction of OAA molecules that originate through the
TCA cycle is thus determined as 1 ) f. The remaining

PEP U PEP
(1)3)
PEP
(2)3)
PEP
(1)2)
1 PEP
(1)2)
Pyruvate U Pyruvate
(1)3)
Pyruvate
(2)3)
1 Pyruvate
(1)3)
Pyruvate
(2)3)
OAA U OAA
(1)4)
OAA
(2)4)
OAA
(1)2)
1 OAA
(1)4)
OAA
(2)4)
OAA
(1)2)
OGA U OGA
(1)5)

Glucose U Glc,n
U
1 Glc,n
1
Glc,n
unlabeled
884 E. Fischer and U. Sauer (Eur. J. Biochem. 270) Ó FEBS 2003
Gluconeogenic reactions
Fluxes from the TCA cycle to the lower part of glycolysis
via malic enzyme and PEP carboxykinase can be diagnosed
as cleaved C
2
–C
3
bonds in pyruvate and PEP, respectively.
The interconversion of malate to pyruvate via the malic
enzymes (ScfA and Mae) can thus be determined by
comparing the pyruvate
(2)3)
and PEP
(2)3)
fragments using
Eqn (7). As the mass distribution of malate is unknown, a
pyruvate
(2)3)
molecule produced via malic enzyme was
assumed to have the mass distribution of two combined one
carbon units, each with the fractional
13
C-label of the input

the extreme case of full equilibration of the malate and
OAA pools.
Similarly, PEP carboxykinase activity can be detected in
the cleaved fraction of PEP
(2)3)
using Eqn (7). As a cleaved
C
2
–C
3
bond in PEP may also result from transaldolase
activity, the thus calculated fraction of PEP originating
from OAA remains an upper bound on the PEP carboxy-
kinase activity.
C1-metabolism
The reversible exchange of the serine and glycine pools was
quantified by determining the fraction of serine
(1)3)
origin-
ating from glycine
(1)2)
and a one carbon unit vs. the fraction
that is identical with PEP
(1)3)
(Eqn 7). Additionally, the
fraction of glycine
(1)2)
derived from serine
(1)2)
was attained

13
C-labeled
at C
1
(Eqn 7).
If the ED pathway is active, additional label is introduced
at the level of pyruvate, resulting in different MDV of
serine
(1)3)
and pyruvate
(1)3)
, which can be used to assess the
relative contribution of this pathway to pyruvate synthesis
using Eqn (7). Additionally, pyruvate derived through the
ED pathway is labeled at C
1
, while pyruvate originating
from glycolysis is labeled at C
3
. The fraction of pyruvate
molecules labeled at C
1
can be calculated from the difference
between pyruvate
(1)3)
and pyruvate
(2)3)
. This information is
used to verify that the label is indeed introduced through the
ED pathway and not through a gluconeogenic reaction.

M
after the
least-squares fitting step and calculated analytically for the
final flux ratios.
Results
Sensitivity of metabolic flux ratio analysis using
different mixtures of [U-
13
C] and unlabeled glucose
For economical reasons, low fractions of expensive
13
C-labeled substrates are desirable for labeling experiments,
provided that analytical resolution and sensitivity are
maintained. To identify an optimal compromise, we grew
E. coli MG1655 batch cultures in 5 mL M9 medium with
different mixtures of [U-
13
C] and unlabeled glucose. While
fully
13
C-labeled or unlabeled biomass contained no infor-
mation on metabolic fluxes, mixtures of 20/80, 40/60, 60/40,
and 80/20 of [U-
13
C] and unlabeled glucose, respectively,
allowed to determine flux ratios that were consistent within
the experimental error (data not shown). Although the
lowest experimental error is achieved at around equimolar
fractions of [U-
13

biomass aliquots harvested at D
600
values between 0.8 and
1.5.
Next, we investigated the metabolic impact of different
levels of aeration from fully aerobic (500 mL baffled shake
flask) to suboptimally aerated (15 mL vials) and anaerobic
E. coli batch cultures (Fig. 4). With decreasing oxygen
availability, most prominently, the fraction of OAA origin-
ating through the TCA cycle decreases from 44% to 5%.
This reveals a branched, noncyclic operation of the TCA
cycle to fulfill exclusively biosynthetic requirements, as was
also shown earlier [7,16,26]. Although the oxidative PP
pathway is still active under anaerobic conditions (serine
through glycolysis), its relative contribution to glucose
catabolism is decreased from 19% to 5% (Fig. 4), which
concurs with most [7,16] but not all [26] reports. The
frequently reported upper bound on in vivo PP pathway
activity obtained from [U-
13
C]glucose experiments, in
contrast (PEP from P5P), is not sensitive to this decrease.
Unexpectedly, suboptimally aerated conditions promote
relatively high in vivo malic enzyme activity (pyruvate from
malate). Likewise, the of CO
2
originating from air in the
[U-
13
C]glucose experiments decreased with decreasing oxy-

, and specific glucose uptake
rates of 6.5–8.5 mmolÆg(CDW)
)1
Æh
)1
may be considered as
normal for E. coli (Table 3). Hence, only the Pgi, PfkA,
and Mae/Pck mutants exhibited clear physiological
phenotypes with significantly reduced growth and glucose
uptake rates.
While the flux profiles were similar in the three wild-type
strains with small differences in the fractions of serine
originating from glycine and OAA originating through the
TCA cycle (Fig. 5), major changes were seen in the mutants
(Fig. 6). Consistent with its severely reduced growth rate,
the phosphoglucose isomerase-deficient Pgi mutant exhi-
bited a very different flux profile without any glycolytic flux
(serine through glycolysis in Fig. 6). Unexpectedly, the ED
pathway was found to contribute about 30% to glucose
catabolism in the Pgi mutant (pyruvate through ED
Fig. 4. Origin of metabolic intermediates in E. co li wild-type during
aerobic (white bars), suboptimally aerated (gray bars), and anaerobic
(black bars) growth. The experimental error was estimated from
redundant mass distributions. Asterisks indicate results obtained from
100% [1-
13
C] glucose experiments. All other results were from 20%
[U-
13
C] and 80% unlabeled glucose experiments. The fractions of

consequence, the low growth rate on glucose are expected
(Table 3). Consistently, the major fraction of serine is still
generated through glycolysis (Fig. 6), probably catalyzed by
the intact minor isoform phosphofructokinase B. However,
the flux partitioning into the PP pathway (PEP from P5P) is
significantly increased.
Flux profiles of the Zwf and PykAF mutants defective in
G6P dehydrogenase and both pyruvate kinase isoforms,
respectively, were somewhat similar to that of the wild-type.
Significant flux changes in the Zwf mutant were seen in the
reactions related to the PP pathway (data partly shown in
Fig. 6). A 93% fraction of serine originating through
glycolysis indicates residual PP pathway and/or ED path-
way fluxes for glucose catabolism in the range of 7%.
Consistent with the previously described metabolic bypass
of pyruvate kinase knockout via PEP carboxylase and malic
enzyme [7,18], the PykAF mutant exhibited lower fractions
of OAA originating through the TCA cycle and higher
fractions of pyruvate originating from malate (Fig. 6).
During the growth on glucose investigated here, simul-
taneous inactivation of the two gluconeogenic reactions
catalyzed by malic enzyme and PEP carboxykinase had no
significant effect on the flux profile of the Mae/Pck mutant
(Fig. 6). This result was expected, as the fractions of
pyruvate originating from malate and PEP originating from
OAA that are indicative of in vivo malic enzyme and PEP
carboxykinase activity, respectively, were already at detec-
tion level in the wild-type strains (Fig. 5). Disruption of the
TCA cycle in the Sdh/Mdh and FumA mutants [29,30]
reduced primarily the fraction of OAA generated through

Pgi 0.17 (0.15) 0.39 (0.40) 2.5 (2.0)
PfkA 0.08 (0.08) 0.41 (0.41) 1.4 (1.5)
PykAF 0.60 (0.59) 0.41 (n.d) 8.1 (n.d)
Mae/Pck 0.41 (0.44) 0.40 (0.42) 5.7 (5.8)
SdhA/Mdh 0.50 (0.51) 0.43 (0.40) 6.5 (7.1)
FumA 0.67 (0.65) 0.46 (0.45) 8.2 (8.3)
Fig. 5. Origin of metabolic intermediates in the E. c oli wild-type strains
MG1655 (white), JM101 (gray), and W3110 (black) during aerobic
exponential growth. The experimental error was estimated from
redundant mass distributions. Asterisks indicate results obtained from
100% [1-
13
C]glucose experiments. All other results were from 20%
[U-
13
C] and 80% unlabeled glucose experiments.
Fig. 6. Origin of metabolic intermediates in
E. c oli mutants during aerobic exponential
growth. The experimental error was estimated
from redundant mass distributions. Asterisks
indicate results obtained from [1-
13
C]glucose
experiments. All other results were from 20%
[U-
13
C] and 80% unlabeled glucose experi-
ments.
Ó FEBS 2003 Metabolic flux profiling in E. coli (Eur. J. Biochem. 270) 887
TCA cycle and exclusive origin of OAA through the

Using metabolic flux ratio analysis by GC-MS, we dissect
here flux responses of E. coli central metabolism to
environmental and genetic modifications for two reasons:
to (a) experimentally verify the accuracy of the new
methodology and to (b) identify novel metabolic response.
Estimation of in vivo PP pathway activity has received
considerable attention, due to its variability with environ-
mental conditions and relevance for NADPH metabolism.
For aerobic batch cultures of E. coli, the relative contribu-
tion of the PP pathway to glucose catabolism has long been
a matter of debate, yielding values between less than 10%
to about 50% of glucose consumption [26,33]. For three
different E. coli wild-type strains, we show here that the PP
pathway contribution to fully aerobic glucose catabolism
varies between 14% and 20% (Figs 5 and 7 A and 7B). This
contribution does not change significantly upon mutations
downstream of triose 3-phosphate. When forced to serve as
the primary route for glucose catabolism in the phospho-
glucose isomerase knockout (Fig. 7A), the PP pathway
supports only a significantly lower growth rate than that
observed for the wild-type. The strong reduction of PP and
ED pathway fluxes upon knockout of G6P dehydrogenase
(Fig. 7B) reveals the nonessential nature of both pathways
for growth on glucose, as the growth physiology of the Zwf
mutant was indistinguishable from that of the wild-type.
Noticeably, a fraction of about 7% of the serine molecules
does not originate from glycolysis in the Zwf mutant. The
13
C labeling pattern of serine is instead consistent with a low
but significant flux through either the PP or ED pathway. A

in our batch cultures. Consistent with previous flux analyses
based on NMR data [7,18], the sole exception was the
PykAF mutant, which bypassed the pyruvate kinase
reaction by redirecting carbon flow via PEP carboxylase
and malic enzyme (Fig. 6).
A very important flux ratio characterizing the metabolic
state of a culture is the fraction of OAA originating through
the TCA cycle, which quantifies the proportion to which the
TCA cycle is used for energy generation vs. biosynthetic
precursor supply via the anaplerotic PEP carboxylase
(Fig. 7D). Consequently, this ratio is influenced by envi-
ronmental factors such as growth phase (Fig. 3), aeration
(Fig. 4), and overflow metabolism, but to some extent
also by the genetic background of the wild-type strains
(Fig. 5), as was noted previously for different organisms
[7,16,26,35,36]. Generally, anaplerosis is high under condi-
tions that invoke overflow metabolism, as acetate formation
reduces the fraction of intact two carbon units entering the
TCA cycle. Metabolic flux ratio analysis by GC-MS
successfully captures the effective disruption of the TCA
cycle in the Sdh/Mdh mutant (Figs 6 and 7D). Although the
major fumarase isoform is inactivated in the FumA mutant,
its respiratory TCA cycle flux is still at about one third of
that in the wild-type (Fig. 6). This reveals that the two
remaining fumarase isoforms are also important during
growth on glucose.
Despite the different genetic backgrounds of the
mutants in the upper part of central metabolism and
their variations in growth rate, however, we observed
surprisingly small deviations in this fraction of OAA

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Supplementary material
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