J. Biomedical Science and Engineering, 2011, 4, 110-118
doi:10.4236/jbise.2011.42016 Published Online February 2011 (http://www.SciRP.org/journal/jbise/
JBiSE
).
Published Online February 2011 in SciRes. http://www.scirp.org/journal/JBiSE
High resolution nuclear magnetic resonance investigation of
metabolic disturbances induced by focal traumatic brain
injury in a rat model: a pilot study
Laurent Lemaire1,2, François Seguin3,4, Florence Franconi5, Delphine Bon3,4, Anne Pasco1,2,
Nadège Boildieu3,4, Jean-Jacques Le Jeune1,2
1LUNAM Université, Ingénierie de la Vectorisation Particulaire, Angers, France;
2INSERM U646, Angers, France;
3Université de Poitiers, Ischémie Reperfusion en Transplantation rénale, Poitiers, France;
4INSERM U927, Poitiers, France;
5LUNAM Université, PIAM, Angers, France
Received 1 December 2010; revised 3 January 2011; accepted 12 January 2011
ABSTRACT
Experimental models of traumatic brain injury (TBI)
provide a useful tool for understanding the cerebral
metabolic changes induced by this pathological condi-
tion. Here, we report on the time course of changes in
cerebral metabolites after TBI using high-resolution
proton magnetic resonance spectroscopy (NMR). Ex-
tracts from adult male Sprague-Dawley rats were sub-
jected to fluid lateral percussion and were then exam-
ined by NMR at 3, 24 and 48 h after the injury. A me-
tabolomic approach was carried out to identify the
cerebral metabolites impacted by the TBI and their
quantitative temporal changes. Lactate, valine and
ascorbate were the three first metabolites to be signifi-
cantly modified after TBI. The quantitative elevation
for these compounds last for the entire experimental
time explored. Within 24 hours post-TBI, a significant
elevation in choline-derivates, alanine and glucose were
also measur ed. On the other hand, N-acetyl aspartate, a
neuronal marker, and myo- inositol, an important or-
ganic osmolyte in the mammalian brain, were not sig-
nificantly impacted in the chronic phase of TBI.
Keywords: TBI; 1H-NMR Spectroscopy; Metabolomic;
Traumatic Brain
1. INTRODUCTION
Traumatic brain injury (TBI) is a worldwide problem
that results in death and disability for millions of people
every year. Currently, in industrialized countries it is
estimated that TBI is responsible for 0.15-0.2‰ of
deaths and that 0.2-0.3‰ of the population lives with
permanent disabilities [1-3]. As a result, there is real
need for improved diagnosis [4], treatment and strategies
for rehabilitation post TBI.
Clinical and preclinical studies have now established
that brain trauma is a dynamic process characterized by
two waves of lesions. The first wave corresponds to the
immediate mechanical damage to the central nervous
system (CNS) that occurs at the moment of impact, and
the second wave, initiated at the moment of the trau-
matic insult, will progress over a period of time ranging
from hours to days after injury [5-7]. The most common
and serious consequence of TBI is then, the development
of a brain edema, usually associated with a poor neuro-
logical outcome and the activation of multiple molecular
pathways to counter-balanced the insult [8-13]. MRS
was proven useful to follow those changes; however, the
limited spectral resolution associated to the low concen-
tration of the brain metabolites limit the studies to few
molecules [14]. High resolution NMR allows overcom-
ing those drawbacks and may be used to address those
metabolic modifications, often complex and implying
numerous metabolic pathways [15-18]. Metabolomics
has recently emerged as a powerful approach for the
characterisation of the metabolic responses to stress or
diseases from MS or LC data [19-21] as well as from
high resolution NMR data [16,22-26]. In the present
work, we took advantage of 1H-NMR potentials in term
of easiness of sample preparation, sensitivity, reproduci-
bility, high-throuphut analysis without metabolites sepa-
ration as well as the quantitative information that one
can easily access to, especially using the ERETIC
method [27].
Experimental TBI can be performed by numerous

L. Lemaire et al. / J. Biomedical Science and Engineering 4 (2011) 110-118 111
methods and lead to either focal or diffuse brain lesions
[28] with their own metabolic impairments [15,29,30].
In the presented study, we have chosen the fluid lateral
percussion model that appears to be [31] the most used
model and for which morphological, histo-patho-physio-
logical, behavioural, cognitive and even biochemical
data mainly on exitotoxic molecules are available [32].
Recently, two complementary works[16,31] dealing with
the fluid lateral percussion model in mature rats were
presented. In one hand, a metabolomic approach in the
acute phase of the trauma, i.e. 1hour post insult was re-
ported, whereas on the other hand a longitudinal fol-
low-up of the brain trauma showed a significant evolu-
tion in term of blood brain barrier permeability, water
diffusion properties and blood perfusion of the brain.
Taken all together, we have then investigated the meta-
bolic changes associated with brain trauma evolution
using a metabolomic approach.
2. EXPERIMENTAL
2.1. Animals and Lateral Fluid Percussion
Animal care was carried out in compliance with the rele-
vant European Community regulations (Official Journal
of European Community L358 12/18/1986).
230-270 g female Sprague-Dawley rats where sup-
plied by Angers University Hospital animal facility; they
were anaesthetized with isoflurane via a stereotactic
compatible nose cone (Minerve, Esternay, France). Once
induced, the animal was placed in a stereotactic frame
and brain trauma was induced as previously described
[31]. Briefly, a scalp incision was made, the scalp and
temporal muscles were reflected, and a 2.5 mm crani-
otomy was carried out above the left auditory cortex, 2
mm posterior to the lateral suture. A fitting tube, con-
nected to the fluid lateral percussion device was ce-
mented into the open craniotomy site. A 20 ms pulse at a
pressure of 2.0 ± 0.1 atm induced fluid lateral percussion
(FLP) brain injury. Immediately after fluid lateral per-
cussion, the scalp incision was sutured and the rats were
allowed to recover from anaesthesia. Normothermia was
maintained through the use of a heating pad placed un-
der the animal during all surgical procedures and in the
acute post-injury period. The temperature was main-
tained between 36.5˚C and 37.5˚C.
Thereafter, rats were housed in temperature- and
light-controlled conditions with food and water ad libi-
tum. Sham-operated rats (n = 3) underwent the same sur-
gery except for percussion. Three hours (n = 3), 24 hours (n
= 3) and 48 hours (n = 3) post TBI, rats were re-anaes-
thetised with isoflurane. Rapid brain removal was then
performed and 2-3 mm slice were dissected directly over
craniectomy, the ispi and the contralateral brain were
separated. Samples were frozen in liquid nitrogen, weighted
and lyophilised. Dried brain was stored at –80˚C until
processing.
2.2. Tissue and Biofluids Preparation for NMR
Spectroscopy
Dried brain tissues (~100 mg) were grounded in liquid
nitrogen prior extraction in 5 mL of acetonitrile/water
50/50 in an ice/water bath. The homogenates were cen-
trifuged at 400 g for 10 min at 4˚C. Pellets were washed
once with 3 mL of acetonitrile/water 50/50 and both su-
pernatants were pooled and lyophilised before being
reconstituted in 0.8 mL D20 containing 0.05 wt% 3-
(trimethylsilyl) propionic –2,2,3,3-d4 acid (TSP). 1H
NMR spectra of tissue extract were measured at 500.13
MHz using an Avance 500 SB spectrometer with 5 mm
broadband inverse probe (BBI) (Bruker Biospin, Wies-
sembourg, France) with non spinning samples and
maintained at 298 K. One dimensional (1D) spectra were
collected into 32 K data points with a spectral width of
5000 Hz and a total acquisition time of 2 min for 16 av-
erages. Spectra were obtained using 1D version of the
NOESY pulse sequence with an acquisition time of 3.28
s, a 1.5 s relaxation delay and a 40 dB field strength ir-
radiation of the water signal during a 2.5 s presaturation
delay and a 100 ms mixing delay.
All datasets were zero-filled to 64 K points and expo-
nential line broadenings of 0.5 Hz applied before Fourier
transformation. The resulting spectra were manually
phased. The baseline was corrected using a quadratic
function and chemical shift were calibrated using the
TSP signal. Peaks were assigned using the Human Me-
tabolome Database [33], the Magnetic resonance Me-
tabolomics Database [34], and performing TOCSY 2D
spectrum when necessary. The quantitative process was
performed using MestReC 4.9.9.6 Software as previ-
ously described [35].
2.3. Post-Processing of NMR Spectra
2.3.1. Multiva r iate Spectral Analysis
NMR data were reduced into equidistant integral region
(bucket) of the spectra (0.8 to 9.0 ppm) with a bucket
width of 0.03 ppm. The spectral region from 4.50-5.50
ppm was excluded to remove variability due to suppres-
sion of the water resonance signal. Each region was in-
tegrated with AMIX software (version 3.7.10, Bruker,
Karlsruhe, Germany). Each bucket was represented as
the ratio of the total integral of all individual regions (X
variables) to normalize for the dilution between individ-
ual samples. Partial Least Square Discriminant Analysis
(PLS-DA) was performed with SIMCA P 11.0 software
(Umetrics, Umea, Sweden). PLS-DA was employed as a
supervised method, requiring a training set, useful for
small data sets with many more variables than samples.
Data were pre-processed using Pareto scaling to separate
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L. Lemaire et al. / J. Biomedical Science and Engineering 4 (2011) 110-118 112
samples according to the maximum variance detected in
correlated metabolites favoring large changes. Spectral
variation was reduced to a series of variables (t) ex-
plaining the largest variation in the X space, each repre-
senting correlated spectral change, and summarized in a
score plot. Validation of PLS-DA was controlled with
the cumulative fraction of X variation (R2X) and Y
variations (R2Y), corresponding to the different classes
of samples, in the three firsts components, and with the
cumulative overall cross validation (Q2) modeled in the
three firsts components. When the scores plot showed
separated groups, a contribution plot was performed to
evidence the variables that deviated from the average
and contributed to the separation of the groups. Spectral
regions were investigated to identify the metabolites
responsible for the classification. Identification of the
metabolites was performed using the Human Metabolome
Database [33] and the Magnetic Resonance Metabolomics
Database [34].
JBiSE
2.3.2. Multiva r i at e Spe ctral Analysis
Quantification of metabolite peaks was performed with
the ERETIC peak as a quantitative reference [27]. Cali-
bration of this peak, which had the same intensity in all
spectra of brain extracts, was made with reference to a 2
mM creatine solution. Metabolite concentration was
calculated according to the following equation:
2
D
O XERR
XR
E
XR D
V AAN
CC
AN AW


T
where Cx is the concentration of the metabolite, Nx is the
number of protons for the frequency of the peak quanti-
fied, and Ax and AE are the areas of the metabolite and
ERETIC peaks, respectively, in the spectrum. AR and AER
are the measured areas of the creatine and ERETIC
peaks, respectively, for the creatine reference, NR is the
number of protons resonating for creatine, CR is the
concentration of creatine (2 mM). The concentrations of
each metabolites was then calculated in µmoles by gram
of dried tissue taking account the weight of dried tissue
(WDT) and the volume of D2O (VD2O) for the reconstitu-
tion of the lyophilized sample.
3. RESULTS
PLS-DA score plots show evidence for a separation be-
tween tissue extracted at the site of TBI with respect to
time (Figure 1(a)), and tissue extracted at the opposite
with respect to time (Figure 1(b)). For the two 3D score
plot the cross validation score (Q2) is at least equal to
50% of the fraction of Y variation (R2Y) confirming the
robustness of the model used. Difference between ispi
and contralateral brain content, for each time point, was
evaluated using PLS-DA score plots and is presented in
Figure 2. At all experimental times, contra and ipsilat-
eral brain separation were confirmed by high Q2 values.
Indeed, at 3, 24 and 48 hours the cross-validation score
were respectively equal to Q2 = 80.2%; Q2 = 98.8% and
Q2 = 92.5%. Using loading plots corresponding to these
score plots, four metabolites influencing the separation
were identified and selected for a quantitative analysis.
Those metabolites were identified as valine H3 (-CH3,
1.07 ppm), lactate H3 (-CH3, 1.33 ppm), alanine H3
(-CH3, 1.44 ppm) and choline-derivates (-N-(CH3)3,
(a) (b)
Figure 1. Score plots of the NMR spectra of tissue extracts. Each point corresponds to a spectrum after a bucketing of 0.03 ppm. (a)
score plot showing the differences between the four classes (Y variable) sham (◊), ipsilateral at 3 hours (■) 24 hours (●) and 48 hours
(▲); R2X = 72.3%, R2Y = 98.3% and Q2 = 92.5%. (b) score plot showing the differences between the four classes sham (◊), contra-
lateral at 3 hours (□), 24 hours (○) and 48 hours (∆); R2X = 71.6%, R2Y = 82.2% and Q2 = 44.1%.

L. Lemaire et al. / J. Biomedical Science and Engineering 4 (2011) 110-118 113
(a) (b) (c)
Figure 2. Score plots of the NMR spectra of tissue extracts evidencing the difference between ipsi and contralataral for each experi-
ment times; (a) ipsi (■) and contralateral (□), for 3 hours, R2X = 79.3%, R2Y = 95.7%, Q2 = 80.2%; (b) ipsi (●) and contralateral (○)
for 24 hours, R2X = 70.7%, R2Y = 99.9%, Q2 = 98.8%; (c) ipsi (▲) and contralateral for (∆) for 48 hours, R2X = 72.3%, R2Y =
98.3%, Q2 = 92.5%.
3.19-3.23 ppm). However as the number of data set in-
cluded for the metabolomic analysis is limited, a quanti-
tative analysis of eleven metabolites that can be identi-
fied from the high resolution 1H-NMR spectrum of a rat
brains (Figure 3), was also performed. Those metabo-
lites were N-acetyl aspartate H6 (-CH3, 2.00 ppm),
GABA H4 (-CH2, 2.28 ppm), glutamate H3 and H4
(-CH2, 2.35 ppm), succinate H2 (-CH2, 2.42 ppm), cit-
rate H3 (CH2, 2.82 ppm), alpha-ketoglutarate H4 (-CH2,
3.01 ppm), creatine/Phosphocreatine (N-CH3, 3.04 ppm),
taurine H3 (CH2-N, 3.42 ppm), myo-inositol H2( CHOH,
4.05 ppm), ascorbate (H5 –CH 4.52 ppm), glucose-1-
Figure 3. Section of a representative 1H NMR spectrum of the
polar metabolites extracted from rat brain 48 hours post-TBI.
The metabolites quantified in Table 1 are assigned as (1) alanine,
(2) ascorbate, (3) citrate, (4) -aminobutyric acid, (5) glucose, (6)
glutamate, (7) lactate, (8) myo-inositol, (9) N-acetylaspartate,
(10) phosphocholine and glycerophosphocholine, (11) phospho-
creatine and creatine, (12) succinate (13) taurine and (14) valine.
(5.2 ppm). Table 1 summarizes the quantitative analysis
of 1H NMR observable metabolites content in the brain
extracts obtained from animals at increasing times after
TBI. Absolutes concentrations are presented as mean ±
sd and expressed in µmol per g of dry tissue as we have
previously shown that in this TBI model, the brain water
content evolves with time [31]. Valine, lactate, alanine,
choline derivates, ascorbate and glucose appeared sig-
nificantly modified with TBI.
4. DISCUSSION
The primary injury induced by TBI consists of a rapid
deformation of the brain, leading to rupture of cell
membranes, escape of intracellular contents, and disrup-
tion of blood flow, resulting in necrotic cell death. Sec-
ondarily a complex series of biochemical, structural and
molecular changes lead to cellular damage and loss. The
main biochemical perturbations associated with TBI
involve the release of excitotoxic glutamate, the produc-
tion of reactive oxygen species, the disruption of mem-
branes, the impairment of mitochondrial functions and
the neuronal death.
4.1. Excitotoxic Injury
Pathologic release of excitatory amino acid neurotrans-
mitters such as glutamate or aspartate have been reported
both in animal models [9,36] and humans [37]. The sub-
sequent activation of glutamate receptors, results in the
influx of Na+, efflux of K+, and subsequent Ca2+ influx
into the cell causing cellular swelling (cytotoxic edema)
and the excitotoxic destruction of cells through direct or
indirect pathways [32]. MR studies have although al-
ways failed to demonstrate a significant initial increase
in glutamate level after focal or diffuse TBI, and when
modifications of glutamate levels were seen, a significant
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L. Lemaire et al. / J. Biomedical Science and Engineering 4 (2011) 110-118 114
Tabl e 1 . Metabolite NMR assignments and their concentrations (expressed in µmol/g dried tissue) in rat brain as a function of time
post-TBI. Data are presented as mean ± SD. Significant differences (ANOVA) are indicated in boldface if values are different from t0
and/or italic if different from the contralateral at the same time point.
Metabolite Group and
chemical shift Sham 3 hours 24 hours 48 hours
Traumatized
Brain
Controlateral
Brain
Traumatized
Brain
Controlateral
Brain Traumatized Brain
Controlateral
Brain
Valine 1.07; dd; -CH3 0.06 ± 0.01 0.11 ± 0.03 0.06 ± 0.01 0.09 ± 0.010.06 ± 0.01 0.09 ± 0.01 0.08 ± 0.02
Lactate 1.33; d; -CH3 9.05 ± 0.77 10.84 ± 1. 64 9.73 ± 1.64 14.01 ± 1.2812.54 ± 1.56 14.70 ± 0.77 12.02 ± 1. 09
Alanine 1.44; d; -CH3 0.63 ± 0.15 0.81 ± 0.37 0.65 ± 0.04 0.93 ± 0.030.65 ± 0.04 0.84 ± 0.12 0.66 ± 0.06
NAA 2.00;s; -CH3 3.67 ± 0.76 3.84 ± 0.65 3.58 ± 1.27 2.77 ± 0.834.43 ± 0.13 3.08 ± 0.47 3.42 ± 0.93
GABA 2.28; t; -CH2 2.11 ± 0.69 2.02 ± 0.82 2.22 ± 1.02 2.04 ± 0.512.27 ± 0.23 2.01 ± 0.33 2.28 ± 0.49
Glutamate 2.35; t; -CH2 5.97 ± 0.74 6.15 ± 1.00 5.88 ± 0.73 5.78 ± 0.906.55 ± 0.59 6.39 ± 0.13 6.85 ± 0.75
Succinate 2.42, s; -CH2 0.75 ± 0.30 0.83 ± 0.27 0.80 ± 0.31 0.93 ± 0.150.96 ± 0.07 0.87 ± 0.15 0.84 ± 0.15
Citrate 2.82; dd; -CH2 1.00 ± 0.27 0.92 ± 0.10 1.22 ± 0.31 0.83 ± 0.020.87 ± 0.06 1.04 ± 0.28 1.51 ± 0.53
PCr and Cr 3.04; s;N-CH3 4.92 ± 0.95 5.29 ± 1.04 5.28 ± 1.29 4.79 ± 0.545.72 ± 0.46 5.23 ± 0.44 5.69 ± 0.30
PC and GPC 3.20; s; N-(CH3)3 0.43 ± 0.12 0.48 ± 0.11 0.41 ± 0.13 0.47 ± 0.040.46 ± 0.04 0.63 ± 0.07 0.52 ± 0.16
Taurine 3.42; t; N-CH2 2.64 ± 0.66 3.00 ± 0.74 2.99 ± 0.58 3.00 ± 0.293.35 ± 0.14 3.32 ± 0.09 3.44 ± 0.35
Myoinositol 4.05; t; -CHOH 5.01 ± 3.04 5.07 ± 1.40 6.22 ± 2.05 4.66 ± 0.854.86 ± 0.59 4.77 ± 0.50 5.86 ± 1.69
Ascorbate 4.52; d; -CH 0.03 ± 0.05 0.19 ± 0.14 0.08 ± 0.13 0.13 ± 0.010.22 ± 0.05 0.17 ± 0.02 0.1 9 ± 0 .06
Glucose 5.20; d; -CH 0 0 0 0.25 ± 0.090 0.17 ± 0.14 0
decrease[16,38], ranging from –40% to –15% was ob-
served. In the present study, the glutamate appeared not
significantly modified regardless of the experimental
time. The discrepancy between glutamate levels deter-
mined using NMR and other quantitative techniques
such as microdialysis may be discussed according to the
pool of glutamate assessed. First of all, microdialysis
measured glutamate level corresponding to the extracel-
lular pool of this compound whereas the NMR glutamate
level measured on tissue extract corresponds to the total
glutamate, i.e., the extracellular pool and the intra-neuronal
pool, which taken as an all cannot be significantly
changed, at least in the early phase of the injury. Later
on, the extracellular glutamate which has moved from
the neurons to the extracellular space, may be up-taken
by astrocytes and converted to glutamine [39] leading to
an overall decrease in glutamate level as revealed using
NMR.
4.2. Oxidative Stress
Despite a short half-life in biological tissue but accord-
ing to their high reactivity, oxygen species such as su-
peroxide anion, hydroxylradical, peroxynitrite and nitric
oxide produce in TBI induce brain tissue oxidative
damage [40,41]. It is therefore important to evaluate the
levels of the two main water-soluble antioxidants, i.e.
glutathione and ascorbate. However and with respect to
the low concentration of gluthatione [42], this compound
is not detectable in this study as in a previous one using
NMR [16]. Concerning ascorbate, a significant increase
is detectable at all time points in the traumatized brain
but also in the contralateral hemisphere at day 1 and day
2 compared to the ascorbate level measured in shams.
The increase of ascorbate has never been observed and is
striking as it suggests a massive de novo synthesis of
ascorbate [41,42]. It has previously been shown that an
increase in extracellular ascorbate is observed after TBI
as the result of the release of an intracellular pool [43]
and in order to limit the oxidative damages linked to the
potential pro-oxidant interactions with metal ions that
are released as tissue damage occur [40,41,44]. However,
when working with tissues extracts, the measured
ascorbate corresponds to the total pool, i.e. intra and
extracellular, and therefore, the increase must corre-
spond to an influx/de novo synthesis of ascorbate to the
brain. Nevertheless, one may evoked the circadian evo-
lution of ascorbate as a potential artefact even though the
drop from maximal value during the night to minimal
value during the day occurs within 3 hours [45] and that
all rats were operated at least 2 hours after the day-cycle
was powered on.
4.3. Membrane Markers
In the very early phase after TBI, clear evidence for a
decrease in the levels of phosphocholine and glyc-
erophosphocholine were previously reported [16,38],
evidences that only occurred during the acute phase.
Indeed, as soon as 3 hours post TBI, phosphocholine and
glycerophosphocholine levels recover there pre-TBI
levels prior to significantly increase with time[16,38,42].
In the present study, the same pattern is observed with
no statistical changes 3 hours post trauma followed by a
significant increase that reaches 50% within 2 days. In
the initial acute phase, primary lesions result in mem-
brane disruption and ions leakage that may activate for
example Ca2+ dependant phospholipases and lead to a
global decrease of the choline pool. In the chronic phase,
the choline elevation was attributed to larger membrane
degradation/repair, demyelination, inflammatory reac-
tion and glial reaction [14,46,47]. Gliosis is associated
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L. Lemaire et al. / J. Biomedical Science and Engineering 4 (2011) 110-118 115
with elevation in inositol level and is therefore observed
in the late phase post TBI [14,48] even though astrocytes
damage are reported as early as 30 min post FLP in-
duced TBI [49].In our experiment, variation were lim-
ited in magnitude (ca.10%) and never significant.
4.4. Neuronal Damage
The most prominent peak of the normal high resolution
1H-NMR spectra is that of NAA. This compound is
known since long to be located within neurons and is
therefore traditionally used as marker of neuronal integ-
rity [50]. In the acute phase, NAA remained unchanged
in the ispsi lateral brain but, even though not significant,
decreased later on by about 20%. In previous studies,
NAA was reported reduced as early as 1 hour post TBI
[14,16] ( range –15; –60%) and associated with neuronal
injury [14]. Differences in magnitude and dynamic of
NAA change may reflect the milder traumatic model
used in the present study. Even though extracellular
NAA is transported into astrocytes [51] to be rapidly
hydrolyzed into acetate and aspartate [52], none of these
catabolites were changed after TBI.
4.5. Energy Metabolism and Lactate
FLP induced TBI was demonstrated to induced a tran-
sient but significant 50% reduction in cerebral blood
flow (CBF) within the ipsilateral brain, and a chronic
reduction of up to 80% in contralateral hemisphere [31].
Despite the CBF reduction in the contralateral brain, and
apart from lactate and ascorbate, none of the measured
metabolites were significantly impaired, suggesting that
the transient hypoperfusion was not deleterious for the
brain. However, in the traumatized brain, the mechanical
insult associated with the hypoperfusion induces pertur-
bation in the energy metabolism. Very prominent is the
marked and constantly increased characteristic doublet
around 1.32 ppm, corresponding to lactate. Different
sources for lactate after trauma are known. Initially, a
continuous production of lactate via glycolisis might
occur. Indeed, the increased energy demand to re-estab-
lish ionic homeostasis leads to increased glucose utiliza-
tion, resulting in an increase in lactate [53]. Moreover,
lactate may also arise from astrocytes metabolism through
the astrocyte-neuron lactate shuttle or a Ca2+ mediated
mitochondrial dysfunction with impaired ATP produc-
tion of the respiratory chain was reported in TBI [14,54].
Even though possible, the contribution of infiltrated in-
flammatory cells or of necrotic contusion core, to lactate
production may be marginal as neither are massively
present in this TBI model [31]. Finally, as the time be-
tween TBI and the NMR analysis increase, free glucose
is detected in the traumatized cortex as previously shown
using 13C-labeled glucose [29].
4.6. GABA and Other Biomarkers
GABAergic neurotransmission has been extensively
studied following TBI [55,56] and extracellular level of
GABA following cortical TBI contusion in rats were
proven either increased or stable [9,16,17,57]. For ex-
ample, in a recent study where metabolites levels were
followed with a high temporal resolution, a 25-fold in-
crease in protective GABA was measured 15 min post
TBI, to recover a pre-TBI within 45-60 min [9]. In the
present study, GABA level was not significantly modi-
fied at the time points studied. On the other hand, and as
previously reported, levels of numerous amino-acid are
affected in focal or diffuse brain trauma [16,17]. In this
longitudinal study, levels of valine and alanine were sig-
nificantly increased with time.
4.7. Conclusions
Numerous studies have looked at metabolite profiles
following TBI and complementary or opposite data are
available. Two main points have to be highlighted once
dealing with TBI. On one hand, the type of TBI, i.e. dif-
fuse or focal and on the other hand the timing between
TBI and analysis. In the first half-hour post-TBI, irre-
spective of the model, major changes occur such as
hemodynamic drop [31,58], Blood Brain Barrier per-
meation [59] and metabolic perturbations [9,16]. For the
latest, a substantial increase in metabolites is usually
observed corresponding probably to the leakage from the
intracellular space leading to the aggravation of the ini-
tial lesion.
5. ACKNOWLEDGEMENTS
The authors would like to thank l’Association les Gueules Cassées for
their financial support and P. LEGRAS and J. ROUX from the Hospital
& University Animal Facility (SCAHU) for the care and housing of the
animals.
REFERENCES
[1] Thurman, D., Alverson, C., Dunn, K., Guerrero, J. (1999)
Traumatic brain injury in the United States: A public
health perspective. Journal of Head Trauma Rehabilita-
tion, 14, 602-615.
doi:10.1097/00001199-199912000-00009
[2] Kay, A. and Teasdale, G. (2001) Head injury in the
United Kingdom. World Journal of Surgery, 25, 1210-
1220. doi:10.1007/s00268-001-0084-6
[3] Mathe, J., Richard, I. and Rome, J. (2005) Serious brain
injury and public health, epidemiologic and financial
considerations, comprehensive management and care.
Ann Fr Anesth Reanim, 24, 688-694.
[4] Theodoraki, E.M., Katsaragakis, S., Koukouvinos, C. and
Parpoula, C. (2010) Innovative data mining approaches
for outcome prediction of trauma patients. Journal of
C
opyright © 2011 SciRes. JBiSE

L. Lemaire et al. / J. Biomedical Science and Engineering 4 (2011) 110-118 116
Biomedical Science and Engineering, 3, 791-798.
doi:10.4236/jbise.2010.38105
[5] Sahuquillo, J., Poca, M.A. and Amoros, S. (2001) Cur-
rent aspects of pathophysiology and cell dysfunction af-
ter severe head injury. Current Pharmaceutical Design, 7,
1475-1503. doi:10.2174/1381612013397311
[6] Graham, D.I., Adams, J.H. and Doyle, D (1978) Ischae-
mic brain damage in fatal non-missile head injuries.
Journal of the Neurological Sciences, 39, 213-234.
[7] Pasco, A., Ter Minassian, A., Chapon, C., Lemaire, L.,
Franconi, F., Darabi, D., Caron, C., Benoit, J.P. and Le
Jeune, J.J. (2006) Dynamics of cerebral edema and the
apparent diffusion coefficient of water changes in pa-
tients with severe traumatic brain injury. A prospective
MRI study. European Radiology, 16, 1501-1508.
[8] Ueda, T., Iwata, A., Komatsu, H., Aihara, N., Yamada, K.,
Ugawa, S. and Shimada, S. (2001) Diffuse brain injury
induces local expression of Na+/myo-inositol cotrans-
porter in the rat brain. Molecular Brain Research, 86,
63-69. doi:10.1016/S0169-328X(00)00261-8
[9] Zhong, C., Zhao, X., Van, K.C., Bzdega, T., Smyth, A.,
Zhou, J., Kozikowski, A.P., Jiang, O'Connor, W.T., Ber-
man, R.F., Neale, J.H. and Lyeth, B.G. (2006) NAAG
peptidase inhibitor increases dialysate NAAG and re-
duces glutamate, aspartate and GABA levels in the dorsal
hippocampus following fluid percussion injury in the rat.
Journal of Neurochemistry, 97, 1015-1025.
[10] Zhou, Z., Daugherty, W.P., Sun, D., Levasseur, J.E., Al-
tememi, N., Hamm, R.J., Rockswold, G.L. and Bullock,
M.R. (2007) Protection of mitochondrial function and
improvement in cognitive recovery in rats treated with
hyperbaric oxygen following lateral fluid-percussion in-
jury. Journal of Neurosurgery, 106, 687-694.
[11] Martinez-Murillo, R., Fernandez, A.P., Serrano, J., Rod-
rigo, J., Salas, E., Mourelle, M. and Martinez, A. (2007)
The nitric oxide donor LA 419 decreases brain damage in
a focal ischemia model. Neuroscience Letters, 415, 149-
153. doi:10.1016/j.neulet.2007.01.011
[12] Chapon, C., Franconi, F., Lacoeuille, F., Hindré, F., Saul-
nier, P., Benoit, J.-P., Le Jeune, J.-J. and Lemaire, L.
(2009) Imaging E-selectin expression following trau-
matic brain injury in the rat using a targeted USPIO con-
trast agent. Magnetic Resonance Materials in Physics,
Biology and Medicine, 22, 167-174.
[13] Bellander, B.M., Lidman, O., Ohlsson, M., Meijer, B.,
Piehl, F. and Svensson, M. (2010) Genetic regulation of
microglia activation, complement expression, and neu-
rodegeneration in a rat model of traumatic brain injury.
Experimental Brain Research, 205, 103-114.
[14] Schuhmann, M.U., Stiller, D., Skardelly, M., Bernarding,
J., Klinge, P.M., Samii, A., Samii, M. and Brinker, T.
(2003) Metabolic changes in the vicinity of brain contu-
sions: A proton magnetic resonance spectroscopy and
histology study. Journal of Neurotrauma, 20, 725-743.
doi:10.1089/089771503767869962
[15] Bartnik, B.L., Sutton, R.L., Fukushima, M., Harris, N.G.,
Hovda, D.A. and Lee, S.M. (2005) Upregulation of pen-
tose phosphate pathway and preservation of tricarboxylic
acid cycle flux after experimental brain injury. Journal of
Neurotrauma, 22, 1052-1065.
[16] Viant, M.R., Lyeth, B.G., Miller, M.G. and Berman, R.F.
(2005) An NMR metabolomic investigation of early
metabolic disturbances following traumatic brain injury
in a mammalian model. NMR Biomed, 18, 507-516.
doi:10.1002/nbm.980
[17] Pascual, J.M., Solivera, J., Prieto, R., Barrios, L., Lo-
pez-Larrubia, P., Cerdan, S. and Roda, J.M. (2007) Time
course of early metabolic changes following diffuse
traumatic brain injury in rats as detected by H NMR
spectroscopy. Journal of Neurotrauma, 24, 944-959.
[18] Casey, P.A., McKenna, M.C., Fiskum, G., Saraswati, M.
and Robertson, C.L. (2008) Early and sustained altera-
tions in cerebral metabolism after traumatic brain injury
in immature rats. Journal of Neurotrauma, 25, 603-614.
doi:10.1089/neu.2007.0481
[19] Catchpole, G.S., Beckmann, M., Enot, D.P., Mondhe, M.,
Zywicki, B., Taylor, J., Hardy, N., Smith, A., King, R.D.,
Kell, D.B., Fiehn, O. and Draper, J. (2005) Hierarchical
metabolomics demonstrates substantial compositional
similarity between genetically modified and conventional
potato crops. Proceedings of the National Academy of
Sciences, 102, 14458-14462.
[20] Soga, T. (2007) Capillary electrophoresis-mass spec-
trometry for metabolomics. Methods in Molecular Biol-
ogy, 358, 129-137. doi:10.1007/978-1-59745-244-1_8
[21] Dettmer, K., Aronov, P.A. and Hammock, B.D. (2007)
Mass spectrometry-based metabolomics. Mass Spec-
trometry Reviews, 26, 51-78.
[22] Brindle, J.T., Antti, H., Holmes, E., Tranter, G., Nichol-
son, J.K., Bethell, H.W., Clarke, S., Schofield, P.M.,
McKilligin, E., Mosedale, D.E. and Grainger, D.J. (2002)
Rapid and noninvasive diagnosis of the presence and se-
verity of coronary heart disease using 1H-NMR-based
metabonomics. Nature Medicine, 8, 1439-1444.
[23] Griffiths, J.R. and Stubbs, M. (2003) Opportunities for
studying cancer by metabolomics: preliminary observa-
tions on tumors deficient in hypoxia-inducible factor 1.
Advances in Enzyme Regulation, 43, 67-76.
[24] Morvan, D. and Demidem, A. (2007) Metabolomics by
proton nuclear magnetic resonance spectroscopy of the
response to chloroethylnitrosourea reveals drug efficacy
and tumor adaptive metabolic pathways. Cancer Re-
search, 67, 2150-2159.
doi:10.1158/0008-5472.CAN-06-2346
[25] Viant, M.R. (2007) Revealing the metabolome of animal
tissues using 1H nuclear magnetic resonance spectros-
copy. Methods in Molecular Biology, 358, 229-246.
[26] Barba, I., Jaimez-Auguets, E., Rodriguez-Sinovas, A. and
Garcia-Dorado, D. (2007) 1H NMR-based metabolomic
identification of at-risk areas after myocardial infarction
in swine. Magnetic Resonance Materials in Physics, Bi-
ology and Medicine, 20, 265-271.
doi:10.1007/s10334-007-0097-8
[27] Silvestre, V., Goupry, S., Trierweiler, M., Robins, R. and
Akoka, S. (2001) Determination of substrate and product
concentrations in lactic acid bacterial fermentations by
proton NMR using the ERETIC method. Analytical
Chemistry, 73, 1862-1868.
[28] Morales, D.M., Marklund, N., Lebold, D., Thompson,
H.J., Pitkanen, A., Maxwell, W.L., Longhi, L., Laurer, H.,
Maegele, M., Neugebauer, E., Graham, D.I., Stocchetti,
N., McIntosh, T.K. (2005) Experimental models of trau-
matic brain injury: do we really need to build a better
mousetrap? Neuroscience, 136, 971-989.
C
opyright © 2011 SciRes. JBiSE

L. Lemaire et al. / J. Biomedical Science and Engineering 4 (2011) 110-118 117
[29] Bartnik, B.L., Lee, S.M., Hovda, D.A. and Sutton, R.L.
(2007) The fate of glucose during the period of decreased
metabolism after fluid percussion injury: A 13C NMR
study. Journal of Neurotrauma, 24, 1079-1092.
[30] Bartnik, B.L., Hovda, D.A. and Lee, P.W. (2007) Glucose
metabolism after traumatic brain injury: Estimation of
pyruvate carboxylase and pyruvate dehydrogenase flux
by mass isotopomer analysis. Journal of Neurotrauma,
24, 181-194. doi:10.1089/neu.2006.0038
[31] Pasco, A., Lemaire, L., Franconi, F., Lefur, Y., Noury, F.,
Saint-Andre, J.P., Benoit, J.P., Cozzone, P.J. and Le Jeune,
J.J. (2007) Perfusional deficit and the dynamics of cere-
bral edemas in experimental traumatic brain injury using
perfusion and diffusion-weighted magnetic resonance
imaging. Journal of Neurotrauma, 24, 1321-1330.
[32] Thompson, H.J., Lifshitz, J., Marklund, N., Grady, M.S.,
Graham, D.I., Hovda, D.A. and McIntosh, T.K. (2005)
Lateral fluid percussion brain injury: A 15-year review
and evaluation. Journal of Neurotrauma, 22, 42-75.
[33] Wishart, D.S., Knox, C., Guo, A.C., Eisner, R., Young, N.,
Gautam, B., Hau, D.D., Psychogios, N., Dong, E.,
Bouatra, S., Mandal, R., Sinelnikov, I., Xia, J., Jia, L.,
Cruz, J.A., Lim, E., Sobsey, C.A., Shrivastava, S., Huang,
P., Liu, P., Fang, L., Peng, J., Fradette, R., Cheng, D.,
Tzur, D., Clements, M., Lewis, A., De Souza, A., Zuniga,
A., Dawe, M., Xiong, Y., Clive, D., Greiner, R., Nazy-
rova, A., Shaykhutdinov, R., Li, L., Vogel, H.J. and
Forsythe, I. (2009) HMDB: A knowledgebase for the
human metabolome. Nucleic Acids Research, 37, 603-
610. doi:10.1093/nar/gkn810
[34] Lundberg, P., Vogel, T., Malusek, A., Lundquist, P.-O.
and Cohen, L. (2005) MDL—The Magnetic Resonance
Metabolomics Database (mdl.imv.liu.se). 22th Annual
Meeting of the European Society for Magnetic Resonance
in Medicine and Biology, Magnetic Resonance Materials
in Physics, Biology and Medicine, 18, Basel, S168-S169.
[35] Simoes, R.V., Martinez-Aranda, A., Martin, B., Cerdan,
S., Sierra, A. and Arus, C. (2008) Preliminary charac-
terization of an experimental breast cancer cells brain
metastasis mouse model by MRI/MRS. Magnetic Reso-
nance Materials in Physics, Biology and Medicine, 21,
237-249.
[36] Sakowitz, O.W., Unterberg, A.W. and Stover, J.F. (2002)
Neuronal activity determined by quantitative EEG and
cortical microdialysis is increased following controlled
cortical impact injury in rats. Acta Neurochirurgica Sup-
plementum, 81, 221-223.
[37] Hlatky, R., Furuya, Y., Valadka, A.B., Goodman, J.C. and
Robertson, C.S. (2002) Comparison of microdialysate
arginine and glutamate levels in severely head-injured
patient. Acta Neurochirurgica Supplementum, 81, 347-
349.
[38] Schuhmann, M.U., Stiller, D., Skardelly, M., Thomas, S.,
Samii, M. and Brinker, T. (2002) Long-time in-vivo
metabolic monitoring following experimental brain con-
tusion using proton magnetic resonance spectroscopy.
Acta Neurochirurgica Supplementum, 81, 209-212.
[39] Takahashi, M., Billups, B., Rossi, D., Sarantis, M., Ha-
mann, M. and Attwell, D. (1997) The role of glutamate
transporters in glutamate homeostasis in the brain. Jour-
nal of Experimental Biology, 200, 401-409.
[40] Lewen, A., Matz, P. and Chan, P.H. (2000) Free radical
pathways in CNS injury. Journal of Neurotrauma, 17,
871-890. doi:10.1089/neu.2000.17.871
[41] Tyurin, V.A., Tyurina, Y.Y., Borisenko, G.G., Sokolova,
T.V., Ritov, V.B., Quinn, P.J., Rose, M., Kochanek, P.,
Graham, S.H. and Kagan, V.E. (2000) Oxidative stress
following traumatic brain injury in rats: Quantitation of
biomarkers and detection of free radical intermediates.
Journal of Neurochemistry, 75, 2178-2189.
[42] Bayir, H., Tyurin, V.A., Tyurina, Y.Y., Viner, R., Ritov, V.,
Amoscato, A.A., Zhao, Q., Zhang, X.J., Janesko-Feldman,
K.L., Alexander, H., Basova, L.V., Clark, R.S., Kochanek,
P.M. and Kagan, V.E. (2007) Selective early cardiolipin
peroxidation after traumatic brain injury: an oxidative
lipidomics analysis. Annals of Neurology, 62, 154-169.
[43] Hillered, L., Nilsson, P., Ungerstedt, U. and Ponten, U.
(1990) Trauma-induced increase of extracellular ascor-
bate in rat cerebral cortex. Neuroscience Letters, 113,
328-332. doi:10.1016/0304-3940(90)90606-A
[44] Liebler, D.C., Kling, D.S. and Reed, D.J. (1986) Anti-
oxidant protection of phospholipid bilayers by alpha-
tocopherol. Control of alpha-tocopherol status and lipid
peroxidation by ascorbic acid and glutathione. The Jour-
nal of Biological Chemistry, 261, 12114-12119.
[45] Fillenz, M. and O'Neill, R.D. (1986) Effects of light re-
versal on the circadian pattern of motor activity and
voltammetric signals recorded in rat forebrain. Journal of
Physiology, 374, 91-101.
[46] Ross, B.D., Ernst, T., Kreis, R., Haseler, L.J., Bayer, S.,
Danielsen, E., Bluml, S., Shonk, T., Mandigo, J.C., Caton,
W., Clark, C., Jensen, S.W., Lehman, N.L., Arcinue, E.,
Pudenz, R. and Shelden, C.H. (1998) 1H MRS in acute
traumatic brain injury. Journal of Magnetic Resonance
Imaging, 8, 829-840. doi:10.1002/jmri.1880080412
[47] Cecil, K.M., Lenkinski, R.E., Meaney, D.F., McIntosh,
T.K. and Smith, D.H. (1998) High-field proton magnetic
resonance spectroscopy of a swine model for axonal in-
jury. Journal of Neurochemistry, 70, 2038-2044.
[48] Fortuna, S., Pestalozza, S., Lorenzini, P., Bisso, G.M.,
Morelli, L. and Michalek, H. (1997) Transient global
brain hypoxia-ischemia in adult rats: Neuronal damage,
glial proliferation, and alterations in inositol phosphol-
ipid hydrolysis. Neurochemistry International, 31, 563-
569. doi:10.1016/S0197-0186(97)00005-3
[49] Zhao, X., Ahram, A., Berman, R.F., Muizelaar, J.P. and
Lyeth, B.G. (2003) Early loss of astrocytes after experi-
mental traumatic brain injury. Glia, 44, 140-152.
[50] Ross, B. and Michaelis, T. (1994) Clinical applications of
magnetic resonance spectroscopy. Magn Reson Q, 10,
191-247.
[51] Huang, W., Wang, H., Kekuda, R., Fei, Y.J., Friedrich, A.,
Wang, J., Conway, S.J., Cameron, R.S., Leibach, F.H.
and Ganapathy, V. (2000) Transport of N-acetylaspartate
by the Na(+)-dependent high-affinity dicarboxylate trans-
porter NaDC3 and its relevance to the expression of the
transporter in the brain. Journal of Pharmacol Exp Ther,
295, 392-403.
[52] Tsai, G., van Kammen, D.P., Chen, S., Kelley, M.E.,
Grier, A. and Coyle, J.T. (1998) Glutamatergic neuro-
transmission involves structural and clinical deficits of
schizophrenia. Biol Psychiatr y, 44, 667-674.
doi:10.1016/S0006-3223(98)00151-6
[53] Kawamata, T., Katayama, Y., Hovda, D.A., Yoshino, A.
C
opyright © 2011 SciRes. JBiSE

L. Lemaire et al. / J. Biomedical Science and Engineering 4 (2011) 110-118 118
JBiSE
and Becker, D.P. (1992) Administration of excitatory
amino acid antagonists via microdialysis attenuates the
increase in glucose utilization seen following concussive
brain injury. Cerebral Blood Flow & Metabolism, 12,
12-24.
[54] Xiong, Y., Peterson, P.L., Muizelaar, J.P. and Lee, C.P.
(1997) Amelioration of mitochondrial function by a
novel antioxidant U-101033E following traumatic brain
injury in rats. Journal of Neurotrauma, 14, 907-917.
[55] Imaizumi, M., Kim, H.J., Zoghbi, S.S., Briard, E., Hong,
J., Musachio, J.L., Ruetzler, C., Chuang, D.M., Pike,
V.W., Innis, R.B. and Fujita, M. (2007) PET imaging
with [11C] PBR28 can localize and quantify upregulated
peripheral benzodiazepine receptors associated with cere-
bral ischemia in rat. Neuroscience Letters, 411, 200-205.
doi:10.1016/j.neulet.2006.09.093
[56] Grossman, R., Shohami, E., Alexandrovich, A., Yatsiv, I.,
Kloog, Y. and Biegon, A. (2003) Increase in peripheral
benzodiazepine receptors and loss of glutamate NMDA
receptors in a mouse model of closed head injury: A
quantitative autoradiographic study. Neuroimage, 20,
1971-1981. doi:10.1016/j.neuroimage.2003.06.003
[57] Nilsson, P., Hillered, L., Ponten, U. and Ungerstedt, U.
(1990) Changes in cortical extracellular levels of en-
ergy-related metabolites and amino acids following con-
cussive brain injury in rats. Journal of Cereb Blood Flow
Metab, 10, 631-637.
[58] Assaf, Y., Holokovsky, A., Berman, E., Shapira, Y., Sho-
hami, E. and Cohen, Y. (1999) Diffusion and perfusion
magnetic resonance imaging following closed head in-
jury in rats. Journal of Neurotrauma, 16, 1165-1176.
doi:10.1089/neu.1999.16.1165
[59] Beaumont, A., Marmarou, A., Hayasaki, K., Barzo, P.,
Fatouros, P., Corwin, F., Marmarou, C. and Dunbar, J.
(2000) The permissive nature of blood brain barrier
(BBB) opening in edema formation following traumatic
brain injury. Journal of Experimental Biology, 76, 125-
129.