18O-assisted 31P NMR and mass spectrometry for phosphhometabolomic fingerprinting and metabolic monitoring

Tags: J. Biol, A. Terzic, B. Wieringa, PLS-DA, P. P. Dzeja, incorporation, ATP, metabolites, N. D. Goldberg, energetic system, adenine nucleotide, classification statistics, creatine kinase, Mass Spectrometry, CK, turnover rates, metabolite levels, NMR spectroscopy, metabolic fluxes, labelling, P. Dzeja, E. Janssen, spectroscopic techniques, University of Hacettepe, P. Bast, Analytical Chemistry, metabolic flux, Mayo Clinic, metabolic network, profiling, bioenergetics, energy transfer, transgenic animal models, D. Pucar, A. Heerschap, metabolic networks, J. L. Griffin, AK, J. Mol, ATP synthesis, metabolically active, phosphoryl transfer, ATP production, rate, F. Oerlemans, J. Nicholson, analytical techniques, Department of Analytical Chemistry, S. Macura, M. L. Cardenas, N. Zamboni, NMR spectra
Content: 1
5 CHAPTER 9 18O-assisted 31P NMR and
Mass Spectrometry for
Fingerprinting and Metabolic 15
a Division of cardiovascular diseases, Departments of Medicine, Molecular
Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN, USA; b Department of Analytical Chemistry, Faculty of Pharmacy,
University of Hacettepe, Ankara, Turkey
*Email: [email protected]; [email protected]
30 9.1 Introduction Metabolomic analyses require comprehensive and simultaneous systematic fingerprinting of multiple metabolites. These are to be identified and 35 quantified along with their cellular and systemic variations in response to diseases, drugs, toxins and human lifestyle, as well as in the context of
yPresent address: Department of Analytical Chemistry, Faculty of Pharmacy, University of
Hacettepe, 06100 Ankara, Turkey. zPresent address: Mayo Clinic, 200 First Street SW, Stabile 5, Rochester, MN 55905, USA.
Issues in Toxicology No. 21
Metabolic Profiling: Disease and Xenobiotics
Edited by Martin Grootveld
r The Royal Society of Chemistry 2014
Published by the Royal Society of Chemistry, www.rsc.org
TS:1 18O-assisted 31P NMR and Mass Spectrometry
genetic or environmental challenges.1­8 Analytical platforms developed for
metabolomics studies allow screening of hundreds of metabolites from
complex biological samples with analytical precision, comprehensiveness and sample throughput.6,9­12 The physicochemical diversity of metabolites,
from ionic inorganic species to hydrophilic carbohydrates, volatile alcohols 5
and ketones, amino- and non-amino-organic acids, hydrophobic lipids and
complex natural products, necessitates application of different complementary analytical techniques.2,3,9 Currently, no single platform fulfils all
requirements for an ideal global metabolite profiling tool. Application of
advanced and information-rich spectroscopic techniques is typically essen- 10
tial for the generation of metabolic profiles required for metabolomic studies.13 The main spectroscopic techniques employed for metabolomic studies are based on NMR spectroscopy (1H, 31P, 13C and 17O, amongst
others) and mass spectrometry (direct infusion or combined with GC, LC or
CE). Both techniques can give extensive structural and conformational in- 15
formation on multiple chemical classes in a single analytical procedure; however, they have differing analytical strengths and weaknesses.1,11,13
Characterisation of a metabolic phenotype requires knowledge not only of
metabolite levels, but also of their turnover rates from which metabolic
fluxes and, therefore, the dynamic state of a metabolic system can be 20 determined (Figure 9.1).14­16 Since many metabolites are present at low
concentrations and associated with high flux/turnover rates through the
metabolite pools, significant changes in metabolic flux could occur without changes in metabolite concentrations.17 Therefore, dynamic metabolomic
profiling and flux measurements are essential for a complete understanding 25 of metabolic phenotypes.2,16­20
Stable isotope tracer-based metabolomic technologies allow simultaneous
determinations of metabolite levels and their turnover rates with the subsequent evaluation of metabolic network dynamics.14,15,21,22 13C labelling is
widely used to track turnover of the carbon backbone of metabolites and label 30 propagation through metabolic networks.23­25 This technique alone, however,
does not allow acquisition of a full `picture' of metabolic dynamics and of the status of the cell energetic system. 18O isotopes are suitable for the following
of cellular phosphorus turnover and metabolic dynamics of phosphoryls in
energetically and signal transduction-important biomolecules, as well as label 35 distribution through phosphotransfer networks.15,22,26­31 18O is a natural,
stable and non-radioactive isotope of oxygen. When tissues or cells are exposed to media containing water with a known percentage of 18O, H218O rapidly equilibrates with cellular water, and then 18O from water is in-
corporated into cellular phosphate metabolites to an extent proportional to 40 the rate of enzymatic reactions involved.30 The percentage of 18O incorporation into phosphate metabolites of interest can be determined by 31P NMR or mass spectrometry.15,32,33 Incorporation of 18O into phosphoryls as a consequence of cellular metabolic activity induces an isotope shift in the 31P NMR spectrum ascribable to differences in the shielding effects of 16O versus 45 18O on the 31P nucleus, in addition to a shift in the mass spectrum of
Chapter 9
Figure 9.1 Principles of 18O-labelling methodology for dynamic metabolomic
profiling. A ­ Analytical differences between metabolomic (metabolite
levels) and fluxomic (metabolite turnover rates) analyses using meta-
bolic flux-dependent 18O-labelling resulting in induced shift in 31P NMR spectra of phosphoryl containing metabolites. B ­ Schematic
representation of 18O-labelling procedure for comprehensive character-
isation of cellular energetic system and distribution of multiple phos-
photransfer fluxes.
18O-assisted 31P NMR and Mass Spectrometry
phosphoryl-containing metabolite species.15,31,34 Calculation of the percent-
age of 18O incorporation into phosphate metabolites from the induced isotope
shift in 31P NMR spectra acquired can be employed to determine (1) turnover
rates and (2) phosphotransfer fluxes through specific energetic circuits
(Figure 9.1A).
The 18O labelling procedure is based on the incorporation of one 18O
atom, provided from H218O, into Pi, with each act of ATP hydrolysis and the subsequent distribution of 18O-labelled phosphoryls amongst other phos-
phate-carrying molecules (Figure 9.1B). In conjunction with 18O-assisted 31P
NMR spectroscopy and mass spectrometry, the 18O labelling procedure 10
provides a versatile methodology for the simultaneous measurement of
metabolite levels and metabolic fluxes through phosphotransfer systems, allowing a characterisation of different energetic pathways15,16,22,27­29,33,35,36
(Figure 9.1A). This includes simultaneous recordings of ATP synthesis and
utilisation, phosphotransfer fluxes through adenylate kinase, creatine 15
kinase and glycolytic pathways, as well as mitochondrial Krebs cycle activity,
glycogen turnover and intra-cellular energetic communication (Figure 9.1B). Another advantage of this 18O methodology is that it can measure almost every
phosphotransfer reaction taking place in the cell, including important
signalling molecules such as cAMP, cGMP and AMP turnovers and their 20 metabolically active pool sizes.22,30,37,38 The 18O-phosphoryl labelling procedure detects only newly generated molecules containing 18O-labelled
phosphoryls, reflecting their turnover rates and net fluxes through individual metabolic pathways.15,35,39 Theoretically, up to one-third of all metabolites containing phosphorus,40 and their turnover rates, can be quantified using 25 high-resolution 31P NMR spectroscopy and mass spectrometry. Thus, these
combined technologies permit determination of phosphometabolites and
multiple phosphotransfer fluxes within metabolic networks.
All metabolomic studies result in complex multivariate datasets
that require visualisation software and chemometric methods for inter- 30
pretation. The aim of these procedures is to produce biochemically based
fingerprints that are of diagnostic or other classification value, and to
identify potentially complex sets of biomarkers supporting the diagnosis or classification.1,41­44 Here, multivariate datasets obtained from different analytical techniques and 18O-labelling ratios were combined and inter- 35
preted using principal component analysis (PCA) and partial least squares
discriminant analysis (PLS-DA) chemometric techniques to extract latent
metabolic information, and hence enable sample classification and bio-
marker discovery.
In this chapter, we describe the principles and methodology of metabolic 40
profiling and analysis of phosphometabolite turnover rates using stable isotope 18O-assisted 31P NMR analysis and mass spectrometry. This
advanced phosphometabolomic platform is a valuable tool in studies of
intact muscle energetics and phosphotransfer networks, and unique for
measurements of intra-cellular energetic communication and metabolic 45 signal dynamics. basic concepts of the 18O-labelling technique are explained
Chapter 9
and illustrated with several examples. Special focus is placed on 1 sample preparation, the calculation of labelling rates and multivariate data analyses.
9.2 Methodology
9.2.1 Phosphometabolomic Platforms Phosphorous is an essential element indispensable to life activity, such as genetic inheritance, signal transduction, metabolism and energy con- 10 version.45 Phosphate is the most common fragment via the frequency of occurrence in the metabolome of living organisms.40 In the Human Meta- bolome Database (http://www.hmdb.ca/), there are 744 compounds con- taining `phospho' and 419 with `phosphate' in their structures from 8536 metabolites. Origins of comprehensive analysis of phosphorus-containing 15 metabolites can be traced to Besman's phosphate analyser where 32P-labelling coupled with chromatographic separation and quantification of phosphometabolites was performed.46 Most phosphorus-containing metabolites are highly polar and their separation and analysis represent a major challenge. Phosphometabolites can be measured simultaneously by several analytical 20 techniques, including 31P NMR, LC/MS, GC/MS, CE/MS and HPLC analyses.45,47,48 Although these methods are generally successful in determining the concentration of a range of metabolites, it is not possible to measure all phosphometabolites using one technique in view of their stabilities, concen- trations or the dynamic range of instruments. For example, sugar phosphates 25 are best separated using GC/MS,12 whilst phospholipids are best investigated by 1H and 31P-NMR,49 and nucleotides by LC.50 We established a dynamic phosphometabolomic platform (Figure 9.2) that includes 18O-assisted GC/MS, 18O-assisted 31P NMR, together with 1H NMR and HPLC. We are also developing an LC/MS method for the quan- 30 tification of 18O-labelling of mono- or oligo-phosphometabolites. 18O-assisted GC/MS technology, which originally was developed in Nelson Goldberg's laboratory,27,32,35,37 allows separation and quantitation of 18O/16O isotope ratios in phosphoryl metabolites with a molecular mass o500 Da. Higher molecular weight phosphates and oligo-phosphates, such as ATP or GTP, can be 35 analysed after enzymatic transfer of corresponding phosphoryls to glycerol.27,36 The 18O-assisted 31P NMR technique is dependent on the magnitude of an 18O-induced shift in 31P NMR spectra in order to determine the percentage of 18O-labelling of phosphoryl metabolites.15,31 This technology, which has been used for enzymatic mechanism analyses 40 in vitro,31,34 is adapted and developed for tracking phosphoryl metabolic dynamics in intact tissues.15,22 The critical advantage of the 18O-assisted 31P NMR technique is that it does not require prior metabolite separation and derivatisation; it is stable, and quantitative, and allows simultaneous single- run recordings of multiple metabolite phosphoryls, and those of separate 45 phosphoryls within one molecule such as the a-, b- and g-phosphoryls of
18O-assisted 31P NMR and Mass Spectrometry
247 1 5
Figure 9.2 Stable isotope-based analytical platform for phosphometabolite analy-
sis and phosphometabolomic fingerprinting of metabophenotypes. Combination of 18O-assisted GC/MS and 31P NMR with 1H NMR and
HPLC provides a powerful platform for dynamic phosphometabolomic
profiling of energetic and signalling processes and network analysis
cellular bioenergetics system.
ATP.15,22 However, compared to GC/MS, 18O-assisted 31P NMR is less sensi- tive, and requires a larger amount of sample and a longer analysis time. In our studies, 1H NMR analysis is employed as a complementary technology for the quantification of phosphometabolite levels in tissue extracts and 45 biological fluids.22 HPLC using ion-exchange, reversed-phase, hydrophobic
Chapter 9
and hydrophilic interaction chromatography is a versatile technique for the 1 separation and quantification of major phosphometabolite classes.15,27,36 The use of triethylammonium bicarbonate (TEAB) buffer, introduced by Khorana,51 is preferential since its volatility facilitates sample recovery after HPLC chromatographic separation, and renders it suitable for the mass 5 spectrometric analysis of phosphometabolites.
9.2.2 18O Metabolic Labelling Procedure
18O is a natural, stable and non-radioactive isotope of oxygen. When tissue or 10 cells are exposed to media containing a known percentage (20­30%) of 18O, H218O rapidly equilibrates with cellular water, and then water-containing 18O from water is transferred to cellular phosphate metabolites proportionally to
the rate of enzymatic reactions involved. The rates of sequential enzymatic reactions between Pi, g-ATP and CrP are high (Figure 9.3A) and upon 18O
labelling display exponential kinetics with saturation occurring within
2 min.22,29 (Figure 9.3B). Therefore the labelling of metabolites should be
performed within the initial linear phase (0­1 min.) of the 18O labelling
curve, whilst for b-ADP and b-ATP, which have lower turnover rates, labelling can be performed within a 5 min. time window. After the desired time of
exposure with H218O, cellular metabolism is instantaneously quenched by
immersing cells or tissue into liquid N2.
40 Figure 9.3 Analysis of heart phosphotransfer dynamics. A) Schematic representation of 18O-labelling reaction sequence and B) kinetics of 18O-labelling 45 of major heart phosphometabolites.
18O-assisted 31P NMR and Mass Spectrometry
Heart perfusion and 18O phosphoryl labelling
Hearts from heparinised (50 U ip) and anaesthetised (75 mg kgА1 pento-
barbital sodium ip) wild-type or transgenic mice are excised and retrogradely
perfused with a 95% O2­5% CO2-saturated Krebs­Henseleit (K­H) solution
(in mM: 118 NaCl, 5.3 KCl, 2.0 CaCl2, 19 NaHCO3, 1.2 MgSO4, 11.0 glucose,
0.5 EDTA; 37 1C) at a perfusion pressure of 70 mmHg. Hearts were paced at
400 beats minА1, and then perfused for 30 min. and subjected to labelling
with 18O, which was introduced for 30­60 s with the K­H buffer supplemented
with 20­30% of 18O-labelled H2O (Isotec). Then hearts were freeze-clamped, 10 pulverised under liquid N2 and extracted in a solution containing 0.6 M HClO4
and 1.00 mM EDTA. Extracts were neutralised with 2 M KHCO3 and used to determine 18O incorporation into metabolite phosphoryls.28,33
18O-labelling of cultured cells or isolated cardiomyocytes
Cells were washed with PBS and pre-incubated with ADS or an alternative medium.52,53 After 15 min., the medium was removed and replaced with a
2.00 ml volume of this matrix (for a 35 mm dish), enriched with a 20­30%
solution of H218O and incubated for 2 min. at 37 1C. The incubation was terminated by rapid removal of H218O-enriched ADS medium and the
immediate addition of ice-cold 0.60 M perchloric acid containing 1.00 mM
EDTA. Whilst on ice, the cells were scraped from the surface and transferred
AQ:1 along with the HC104 to a test tube. Subsequently, acid extracts were
neutralised with 2.00 M KHCO3. The final extracts obtained from cell or heart tissue were then analysed using 18O-assisted GC-MS or 31P-NMR analysis in
order to determine 18O labelling ratios in phosphate metabolites of interest,
and also calculate phosphotransfer rates. The tissue levels of metabolites
were analysed using GC-MS, HPLC, 1H NMR and 31P NMR spectroscopy for
metabolomic `fingerprinting'.15,16,22,28,29
9.2.3 GC/MS Analysis of 18O-labelling of Metabolite Phosphoryls 18O labelling ratios of monophosphates (such as G3P, G6P and G1P) were 35 evaluated using GC-MS following their purification with HPLC in view of their low concentrations in samples evaluated in this manner. Although Pi has high concentration in the sample, it must be separated from other phosphate-containing metabolites, since some are very unstable during GCMS analysis, and metabolites such as CrP and GA3P are easily degraded to 40 liberate Pi, which, of course, interferes with the free Pi level in the sample. Therefore, samples were fractionated and concentrated using HPLC. Consequently, the labelling ratio can be precisely determined. Cellular phophometabolites are purified and quantified with HPLC (Figure 9.4A) using a Mono Q HR 5/5 ion-exchange column (Pharmacia Biotech) 45 with triethylammonium bicarbonate buffer (pH 8.8) at a 1.00 ml minА1
Chapter 9
30 Figure 9.4 Phosphometabolite 18O-labelling analysis using GC-MS. A) Sample preparation and HPLC fractionation for subsequent GC-MS analysis, B) analysis of 18O-metabolic labelling of Pi, G3P and G6P using GC-MS and C) 18O-labelling based fluxomic analysis of glycolytic and glycogenolytic phosphotransfers and mitochondrial substrate shuttle activity. 35 flow-rate.33,36,52 From each sample, seven fractions were collected. The first fraction contained G6P, G3P, G1P and CrP, and fractions from the second to the seventh contained AMP, Pi, ADP, GDP, ATP and GTP, respectively (Figure 9.4A). Fractions were dried using vacuum centrifugation (SpeedVac, Savant), and reconstituted with water. Monophosphates were then trans- 40 ferred to GC-MS vials for silylation, whilst oligo-phosphates were subjected to enzymatic reactions in Eppendorf tubes to transfer each phosphoryl group to glycerol. The g-phosphoryl of ATP or GTP was transferred to glycerol by glycerokinase, and b-phosphoryls of ATP and ADP were transferred to gly- cerol by a combined catalytic action of adenylate kinase and glycerokinase. 45 The b-phosphoryls of GTP and GDP were transferred to glycerol by the
18O-assisted 31P NMR and Mass Spectrometry
combined catalytic action of guanylate kinase and glycerokinase. The 1
phosphoryl group of CrP was transferred to g-ATP by creatine kinase, and
then to glycerol with glycerokinase. Samples containing the g-ATP, g-GTP,
b-ATP, b-ADP, b-GTP/GDP phosphoryl groups as G3P, Pi, G6P, G1P, G3P and CrP were converted to their respective trimethylsilyl derivatives with Tri-Sil/ 5 AQ:2 BSA (Pierce) as a derivatisating agent.22,33 The 18O-enrichments of phos-
phoryls were determined with GC-MS operated in the select ion-monitoring mode. GC-MS analysis of 18O-labelling in Pi, G3P and G6P labelling is pre- sented in Figure 9.4B. The left panel represents GC-MS chromatograms of
the metabolites, whilst in the right panel the isotope abundance of oxygen is 10
shown. Another phosphometabolite, G1P, can be analysed in this HPLC
fraction too (data not shown). Using this approach in a single run, the
metabolic dynamics of glycolysis and glycogenolysis, and mitochondrial
substrate shuttle activity can be monitored (Figure 9.4C). Our data indicate
that G-3-P metabolic dynamics is altered in transgenic animal models, an 15
observation indicating defects in substrate shuttle and the supply of
reducing equivalents to mitochondria. This is of much importance, since
G-3-P turnover abnormalities and metabolic arrest are linked to human
diseases such as `sudden-death' syndrome. Mass ions (m/z) of selected
metabolites monitored as trimethylsilyl derivatives are given in the 20
AQ:3 Table 9.1. Monophosphates are able to be labelled with labelling up to three
oxygens, whilst Pi and PPi can be labelled with up to four and seven oxygens,
respectively. Mass ions (m/z) of monophosphates corresponding to phos-
phoryl species of 16O, 18O1, 18O2 and 18O3 are monitored as the parent ion
(containing 16O) ю 2, ю4 and ю6, respectively.33,35
Table 9.1 Mass ions (m/z) of selected phosphometabolites that correspond to 18O-labelled phosphoryl species monitored as trimethylsilyl derivatives.
G1P CrP(G3P)a
aPhosphate labelling was determined as G3P after enzymatically transferring it to glycerol. bPPi can be labelled up to seven oxygen atoms. For simplicity, four of them were given in the
Chapter 9
18O-assisted 31P NMR and Mass Spectrometry
9.2.4 31P NMR Analysis of 18O Incorporation into Phosphoryl 1 Metabolites
Samples were pre-cleansed for 1.0 h with Chelex-100 resin (Sigma) sup-
plemented with the 31P NMR spectroscopy internal standard methylene
diphosphonate, and concentrated via vacuum centrifugation (Savant) to a
volume of 0.30 ml. Concentrated extracts were then filtered (centrifuge filter;
0.22 mm, Milipore) and supplemented with 0.10 ml of D2O (Isotec) and 0.10 ml of a 1.00 mM EDTA solution. Samples were additionally cleansed
with the Chelex resin by rotation at 4 1C for 12 hr. To maximise resolution of 10 18O-induced shifts in 31P NMR spectra, and also to increase sample stability,
HC104-extracted tissue samples were subjected to extensive chelation in order to remove divalent cations.15,22,28,29 31P NMR data acquisition was performed at 202.5 MHz using a Bruker 11 T
(Avance) spectrometer in high-quality 5-mm diameter NMR tubes (535-PP-7 15 Wilmad Glass) at ambient temperature and a sample spinning rate of 20 Hz.
9000 scans were acquired without relaxation delay (acquisition time 1.61 s)
using a pulse width of 10 ms (531 angle) with proton decoupling during data acquisition (WALTZ-16 with 901 angle, pulse width of 506 ms for 1H). Prior to
Fourier-transformation, FIDs were zero-filled to 32 K, and multiplied by an 20 exponential window function with 0.30 Hz line-broadening (Figure 9.5A).
Peak areas were integrated using the Bruker software after automatic cor-
rections of phase and baseline. Typical line-widths at half height of various cellular phosphates in 31P NMR spectra were ca. 0.0080 ppm (1.5 Hz on 202.5 MHz), a value significantly less than the 18O-induced shift ranging 25 between 0.0210 and 0.0280 ppm. The internal standard was used to refer-
ence chemical shift values to 16.00 ppm, and also to determine metabolite
levels. The metabolite levels normalised to the internal standard were cor-
rected for NOE (by factors determined in a typical sample recorded both with
and without decoupling), and incomplete relaxation (by factors calculated 30 from T1 times in a typical sample, measured by the inversion-recovery technique) as previously described.28,33 A typical 31P NMR spectrum of heart extract is shown in Figure 9.5A. In- corporation of 18O resulting from cellular metabolic activity induces an isotope shift in the 31P NMR spectrum of phosphoryl containing metabol- 35 ites.31 Although the 18O-induced isotope shift is rather small (around 0.020
ppm), it can be visualised and quantified using high-resolution NMR spectroscopy (Figure 9.5B). Incorporation of each 18O isotope induces shifts of
Figure 9.5 Non-destructive phosphometabolite and 18O-labelling analysis using 40
31P NMR spectroscopy. A) A typical 31P NMR spectrum of major
phosphometabolites in heart extract; B) 18O assisted 31P NMR spectra
of 18O-labelled Pi, CrP, G6P, g-ATP, b-ATP and a-ATP in rat heart extract
(red line indicates unlabelled, while green line shows 18O-labelled
species). Incorporation of 18O induces an isotopic shift in 31P NMR
spectra of phosphoryl contained metabolites. 16O, 18O1, 18O2, 18O3 and 45
18O4 designate phosphoryls containing 0, 1, 2, 3 and 4 atoms of 18O.
Chapter 9
between 0.0210 and 0.0250 ppm in the 31P NMR spectrum of Pi, CrP, g-ATP,
b-ATP, a-ATP, b-ADP, a-ADP, AMP, PC, G6P and G3P. It should also be noted
that the isotope shift in the spectrum of b ATP was different for bridging and
non-bridging 18O oxygens, specifically 0.0170 and 0.0287 ppm, respectively.
Moreover, since G6P exists in equatorial and axial forms, the 16O and 18O
species of G6P were represented as two peaks corresponding to each of the
two forms (Figure 9.5B). During the integration procedure, the bridging and
non-bridging forms of b-ATP, as well as the equatorial and axial forms of G6P for particular 16O or 18O species, were integrated as single peaks.
9.2.5 Phosphometabolite Analysis by 1H-NMR 1H NMR provides a robust and precise method for metabolite quantification including the number of phosphometabolites. 1H NMR data acquisition was performed at 500 MHz using a Bruker 11 T (Avance) 15 spectrometer at ambient temperature and sample spinning at a rate of 20 Hz. 128 scans were accumulated under fully relaxed conditions (12.8 s relaxation delay), with a pulse width of 9 ms (901 angle). FIDs were zerofilled to 32 K, and Fourier-transformed without filtering. Phase and baselines were manually adjusted before integration and deconvolution. Chemical 20 shifts were assigned relative to that of the trimethylsilyl propionate (TSP) signal at 0.00 ppm. Metabolite levels such as those of AMP, ATP, ADP, IMP, CrP, glycolytic intermediates and phospholipids were calculated by the expression of their resonance areas relative to that of TSP used as an internal standard. The identity of metabolites was conducted using Chenomx NMR 25 software suite, which provides a pattern recognition technique, an efficient method for identifying metabolites in biofluids; these identities were confirmed by standard additions.
30 9.2.6 data analysis and Calculations of Phosphoryl Turnover and Phosphotransfer Fluxes Introduction of 18O-labelled water in tissues of interest leads to 18O incorporation into cellular phosphates according to the rate of involved phos- 35 photransfer reactions (see Figure 9.1).15,27,30,36 Such a property allows the tracking of high-energy phosphoryl transfer routes, and the quantification of respective enzymatic fluxes at different levels of cellular activity.15,22,27­30,33,36 Up to three 18O atoms can be incorporated in monophosphate (G3P, G6P, G1P and CrP) and phosphate at different positions in oligo-phosphate (g-, b- and a- 40 for triphosphates, and b- and a- for diphosphates), and up to four and seven for Pi and PPi, respectively. The percentages of 16O, 18O1, 18O2, 18O3 and 18On are proportional to the integrals of their respective resonances in the 31P NMR spectrum, or in the GC-MS chromatograms15,22,28,29 (see Figures 9.4 and 9.5). The cumulative percentage of phosphoryl oxygens replaced by 18O in the 45 metabolites is calculated as [%18O1 ю 2(%18O2) ю 3(%18O3) ю Б Б Б Б n(%18On)]/ [n(%18O in H2O)].15,22
18O-assisted 31P NMR and Mass Spectrometry
The total cellular ATP turnover can be estimated from the total number of 1
18O atoms that appeared in the phosphoryl-containing metabolites and
orthophosphate.22,33,36 The kinetics of 18O-labelled phosphoryl appearance
in g-ATP reflects the cellular ATP synthesis rate, whilst the kinetics of Pi 18O-
labelling indicates cellular ATPase activity.33 The Pi/g-ATP 18O-labelling ratio,
an index of intra-cellular energetic communication,54 is calculated using the
amount or percentage of 18O-incorporated into Pi and g-ATP. 18O-induced shifts in 31P NMR spectra and the kinetics of 18O-labelling of Pi and g-ATP are presented in Figure 9.6. Indeed, the incorporation of 18O into Pi and g- ATP induces very robust multiple shifts in 31P NMR spectra depending on 10
the number of oxygens replaced (Figure 9.6A). From each shift, the labelling
ratio can be calculated at different cycle levels (Figure 9.6B), or total labelling
from the sum of these different cycles. Labelling reaches saturation within
2­5 min., from which the metabolically active pool size can be determined.
Figure 9.6 Dynamics of heart ATP utilisation and synthesis processes. A) 31P NMR
spectra of unlabelled and 18O-labelled Pi and g-ATP at different time
points; incorporation of 18O induces an isotopic shift in 31P NMR spectra of Pi and g-ATP; B) kinetics of 18O-labelling of Pi and g-ATP; C)
schematic representation of Pi 2 ATP cycling and sequential 18O
incorporation into Pi during cell energetic cycle.
Chapter 9
At saturation, almost 100% of g-ATP, and ca. 80% of Pi are metabolically
active (18O labelled) (Figure 9.6B). Incorporation of one, two, three and four
atoms of 18O into phosphoryl groups reflects Pi2ATP cycling between ATP
consumption and ATP production sites (Figure 9.6C).
Adenylate kinase phosphotransfer fluxes can be determined from the rate 5 of appearance of 18O-containing b-phosphoryls in ADP and ATP using a computer model based on Stella software22,35 or CWave,55 FiatFlux,56 FluxSimulator57 or other available software. To obtain AK velocity, the total number of 18O-labelled phosphoryls in b-ADP and b-ATP produced by the AK
catalysis is counted. The pool of metabolically active ADP, obtained from 10
labelling studies, is usually larger than `free' ADP calculated from the CK equilibrium,32,58 and is in dynamic equilibrium between the free and bound states.59,60 The best fits to experimental data are obtainable using a metabolically active (18O-labelled) pool size of 90% for b-ATP, and 30% for bADP.32 Total AMP turnover (AK- and non-AK-mediated) is estimated from the 15
kinetics of AMP a-phosphoryl (non-AK-mediated) and b-ATP/b-ADP phosphoryl (mediated by AK) 18O-labelling. The metabolically active AMP or other
phosphometabolite pool size is determined after prolonged (20­30 min.) 18O-labelling performed in order to establish isotopic equilibrium.32 At
saturation, almost 100% of g-ATP and CrP, and about 80% of Pi are labelled 20 and metabolically active. The calculation of a-AMP turnover time is conducted using the formula: SAt ј 1 А (2АN), where SAt is specific activity of a-AMP 18O-labelling at a given time t, and N is equal to the number of turnover cycles observed during the Incubation period.61,62 Thus, AK
independent turnover time of the AMP pool can be calculated from the 25
expression T ј t/N, where T is the turnover time in s. AK-dependent AMP
turnover can be calculated using the formula:
dN/dt ј r(P*/P А N*/N)
where N*/N is the specific 18O-labelling of adenine nucleotide b-phosphoryls, 30 P*/P the specific 18O-labelling of precursor adenine nucleotide g-phosphoryls and r the rate of 18O-labelling in the nucleotide pool per time unit.61,62 The creatine kinase phosphotransfer rate is determined from the rate of appearance of CrP species containing 18O-labelled phosphoryls, and can be modelled using Stella22,35 and other available software.55­57 The glyco- 35 lytic flux and glycerol phosphate shuttle is determined from the rate of appearance of 18O-labelled G6P and G3P, respectively,16,22 whereas glycogen flux is determined from the rate of appearance of 18O-labelled G1P. The activity of NDPK/Succinyl-CoA synthase is determined from g-GTP 18O-labelling, whilst b-GTP/GDP 18O-labelling indicates guanylate kinase 40 activity.
9.2.7 Multivariate statistical analysis Multivariate datasets obtained from different analytical techniques and 45 labelling ratios were combined and interpreted using principal component
18O-assisted 31P NMR and Mass Spectrometry
analysis (PCA) and partial least squares discriminant analysis (PLS-DA) 1
methods. Initially, data are examined with PCA scatter plots of the first two
score vectors (t1­t2) in order to reveal the homogeneity of the data, together
with any groupings, outliers and trends. Then PLS-DA is applied to acquire
additional information, increase the class separation and simplify inter- 5 pretation, and detect potential biomarkers.63,64 The additional information
(significant metabolites in group classification) may assist with VIP (variable
importance in the projection), loading and regression coefficients plots. The VIP (variable importance in the projection) values,63,65,66 a weighted sum of
squares of the PLS weight which indicates the importance of the variable to 10
the whole model, are calculated to identify the most important molecular
variables for the `clustering' of specific groups, whilst the regression co-
efficient plots of metabolic variables in the PLS-DA model show the effect of
variables on the groups' larger coefficient values (positive or negative) have a
stronger correlation with group metabolic profile classification. Examin- 15
ation of the corresponding loading plot indicated those metabolites re-
sponsible for the clustering of groups. Metabolites located in the centre of
the plot do not contribute to the clustering of the patient groups, whereas
those in the same geographical region of a sample group in the corres-
ponding scores plot are responsible for the separation. Attention must be 20
given to PLS-DA analysis, since it is a supervised method. Even if the two
groups are not different from each other; the method is forced to separate them.67 Therefore, the PLS-DA model must be validated. For validation, R2 (the fraction of variance explained by a component) and Q2 (the fraction of
the total variation predicted by a component) values are considered as 25
measures of goodness-of-model and the model robustness, respectively. The value of Q2 ranges from 0 to 1, and typically a Q2 value of 40.4 is considered a good model, and those with Q2 values over 0.5 are viewed as robust.63,68
Additionally, the validation of the PLS-DA model can be performed by
comparison to the classification statistics of models generated after random 30 permutations of the class matrix. If the model R2 and Q2 values are higher
than those obtained in random permuted models across all iterations, the
method is valid. Calculation of the PCA and PLS-DA model parameters was
carried out using SIMCA-P ю (v12.0, Umetrics AB, Umea, MalmoЁ, Sweden)
and the MetaboAnalyst web browser.66
9.3 Results
9.3.1 Phosphometabolomic Profiling of Transgenic
Animal Models Adenylate Kinase AK1 Knockout Hearts
Maintenance of optimal cardiac function requires precise control of cellular nucleotide ratios and high-energy phosphoryl fluxes. Within the cellular 45 energetic infrastructure, adenylate kinase has been recognised as an
Chapter 9
important phosphotransfer enzyme that catalyses adenine nucleotide ex- 1 change (ATP ю AMP!2ADP) and facilitates transfer of both b- and g-phosphoryls in ATP. In this manner, adenylate kinase doubles the energetic potential of ATP as a high-energy-phosphoryl carrying molecule, and pro- vides an additional energy source under conditions of increased demand 5 and/or compromised metabolic state. By regulating adenine nucleotide processing, adenylate kinase has been implicated in metabolic signal transduction. Indeed, phosphoryl flux through adenylate kinase has been shown to correlate with functional recovery in the metabolically comprom- ised heart, and facilitates intra-cellular energetic communi- 10 cation.15,20­22,28,29,32,33,35,36,54,69 Deletion of the major adenylate kinase AK1 isoform, which catalyses adenine nucleotide exchange, disrupts cellular energetic economy and compromises metabolic signal transduction and ischemia-reperfusion response.16,28,29,69,70 Here, we compare the metabo- lomic phenotypes, phosphometabolite and phosphotransfer dynamics in the 15 hearts of wild-type and AK1 knockout mice at baseline. Male homozygous AK1 knockout (AK1А/А) mice were compared with age- and sex-matched wild-type controls.16,29 In hearts with a null mutation of the AK1 gene, which encodes the major adenylate kinase isoform, the total adenylate kinase activity and ATP/ADP b- 20 phosphoryl transfer was reduced by 94% and 36%, respectively. Knockout of the major adenylate kinase isoform, AK1, disrupted the synchrony between inorganic phosphate Pi turnover at ATP-consuming sites, and g-ATP exchange at ATP synthesis sites, as revealed by 18O-assisted 31P NMR analysis.70 This reduced energetic signal communication in the post-ischemic 25 heart.29 Moreover, AK1 gene deletion `blunted' vascular adenylate kinase phosphotransfer, compromised the contractility-coronary flow relationship and precipitated inadequate coronary reflow following ischemiareperfusion.70 This was associated with up-regulation of phosphoryl flux through the remaining minor adenylate kinase isoforms, and the glycolytic 30 phosphotransfer enzyme 3-phosphoglycerate kinase.28 Data acquired from 18O labelling rate, together with those from 31P and 1H NMR analysis, are transformed into meaningful data through Multivariate Analysis of global profiling by unsupervised PCA and supervised PLS-DA. Initially, data were examined with a PCA score plot of the first two score 35 vectors (t1­t2) in order to reveal the homogeneity of the data, plus any groupings, outliers and trends. As seen in Figure 9.7A, there is clear separation between the groups without any outliers and trends. To improve the visualisation, these profiles were displayed as hierarchical cluster analysis (Figure 9.7B). The heat map represents the unsupervised hierarchical 40 clustering of the data grouped by sample type (rows), which also enabled visualisation of the up- or down-regulation of each metabolite (columns). Hierarchical clustering was performed with Spearman's rank correlation for similarity measurement, and Ward's linkage for clustering using MetaboAnalyst Web server.66 As noted in Figure 9.7, a very clear clustering 45 is visible between two groups. Subsequently, PLS-DA was applied to gain
18O-assisted 31P NMR and Mass Spectrometry
259 1 5
Figure 9.7 Metabolomic profiling of wild-type and AK1А/А mutant hearts. A) PCA
score plot shows clear separation between metabolomic profiles of WT 40
and AK1А/А mice; B) hierarchical clustering and heat map represen-
tation of the metabolomic dataset. The dendrogram on the left of the
figure shows the WT and AK1А/А mice, while observed metabolic
differences are indicated by colour changes where blue and red indicate
down- and up-regulated metabolites, respectively.
Chapter 9
additional information, increase the class separation, and simplify inter- 1 pretation, and also to discover potential biomarkers.64 Genetic deletion of AK1 removed all but 6% of total myocardial adenylate kinase activity, yet the intra-cellular adenylate kinase phosphotransfer flux was only halved in AK1 knockout hearts. The reduced adenylate kinase- 5 catalysed phosphotransfer-induced rearrangements in adenine nucleotide and glycolytic metabolism shifted cellular energetics into an apparently new steady state. These changes produced a differential metabolomic profile of the WT and AK1А/А KO mice heart as noted in the PCA and PLS-DA scores plots (Figure 9.8A). In order to determine significant metabolites in the 10 group differentiation, VIP, loading and regression coefficient plots were used (Figure 9.8B­D). From these plots, it can be concluded that glycolytic and nucleotide metabolism, and adenylate kinase flux, has been altered significantly. Adenylate kinase fluxomic (b-ATP[18O] and b-ADP[18O] turnover), alanine, glucose, threonine, CrP, GPE and nucleotide levels (ADP, AMP and 15 IMP) were decreased in AK1А/А mice, whilst those of 3-PG, pyruvate, Pi, G3P, G6P, g-ATP[18O] and CrP[18O] turnover, glutamate, succinate and F6P all were increased. Alterations in 3-PG, G3P, G6P and F6P metabolites indicate adaptations in glycolytic and substrate shuttle activities, whilst changes in glutamate and succinate levels point to altered mitochondrial 20 Krebs cycle activity. Taken together, these changes indicate a system-wide response of cellular energy metabolism to the deletion of one significant node in the network. With PLS-DA analysis performed to model the metabolic changes associated with gene deletion, a robust predictive model was produced (R2(X) ј 0.68; R2(Y) ј 0.98; Q2 ј 0.89 for the three components) 25 (Figure 9.8E). This model passed cross-validation according to a random 100 permutations of the class matrix. The model R2 and Q2 values on the right were higher than those obtained in random permuted models across all 100 iterations, which indicates validity of the method. Thus, phosphometabolomic profiling of adenylate kinase-deficient hearts revealed rearrangements 30 and adaptations in its energetic system, with an induced shift in glycolytic and creatine kinase phosphotransfer pathways and substrate utilisation networks. Creatine Kinase M-CK Knockout Hearts
Creatine kinase (CK)-catalysed phosphotransfer is the major component of energy transfer and distribution network in the heart, and compromised CK function represents a `hallmark' of abnormal bioenergetics in diseased hearts.39,71­77 Studies of transgenic animal models have demonstrated an 40 inherent plasticity of the cellular energetic system, and the development of cytoarchitectural and metabolic compensatory mechanisms in striated muscles.16,20,28,59,78­83 These studies have led to the concept that the inter- changeability and rearrangement of phosphotransfer networks provide an intra-cellular energetic continuum which couples discrete mitochondrial 45 energetic units with ATP utilisation sites.39,84­86
18O-assisted 31P NMR and Mass Spectrometry
261 1 5
Figure 9.8 Phosphometabolomic profiling of wild-type and AK1А/А mutant
hearts. A) PLS-DA score plot of metabolomic profiles shows clear
separation between groups; B) VIP plot of the PLS-DA method repre-
sents importance of metabolites in discriminating between metabolo-
mic profiles of the groups; C) regression coefficient plots of metabolic variables in the PLS-DA model; larger coefficient values (positive or 35
negative) indicate a stronger correlation with group metabolic profile
classification; D) loading plot of the PLS-DA plot. Red and blue dots
correspond to the mean position of WT and AK1А/А group in the plot,
respectively; E) validation of the PLS-DA model by comparison to the
classification statistics of models generated after 100 random permu-
tations of the class matrix.
Although hearts deficient in the major CK isoforms have no gross basal functional abnormalities, under increased load they cannot sustain normal global ATP/ADP ratios, a phenomenon indicating a compromised com- munication between ATP-consuming and ATP-generating cellular 45 sites.58,81,87­89 This renders contractions to be more energetically costly,
Chapter 9
forcing the heart to operate under less efficient cardiac bioenergetics.58,89
Such energetic abnormalities reduce the ability of the myocardium to respond to b-adrenergic stimulation,90 and CK-deficient hearts are more vulnerable to ischemia-reperfusion injury.91 In addition, CK-deficient hearts
cannot maintain adequate sub-sarcolemmal nucleotide exchange, and also 5 have increased electrical instability under metabolic stress.92 It is likely that
CK-deficient hearts develop cytoarchitectural and metabolic adaptations that modulate energetic disturbances.82,93­95 However, the adaptive meta-
bolomic phenotype, and rearrangements in the bioenergetic system in
CK-deficient hearts, are still poorly understood.
Here, adult wild-type mice (strain C57/BL6) and transgenic mice lacking cytosolic CK isoform (M-CKА/А ), were employed.78,96 Male homozygous
M-CKА/А mice were compared with age- and sex-matched wild-type controls. Hearts were perfused and labelled with 18O as outlined in Section 2.2. 18O labelling procedure. Metabolic signatures for M-CK knockout hearts 15
were revealed using PLS-DA analysis. As demonstrated in the PLS-DA scores
plot (Figure 9.9A), a good separation was obtained between wild-type and M-CK knockout hearts based on metabolite levels and their turnover/18O-
labelling rates, and substrate metabolism. In order to determine significant
metabolites in group discrimination, VIP, plus loading and regression co- 20
efficient plots, were used (Figure 9.9B­D). With PLS-DA analysis conducted
to model the metabolic changes associated with gene deletion, a robust predictive model was produced (R2(X) ј 0.59; R2(Y) ј 0.99; Q2 ј 0.86 for the
three components) (Figure 9.9E).
The CK activity of M-CKА/А hearts was reduced by 71%, leading to 25 decreases in CK flux assessed by a rate of appearance of 18O-labelled phos-
phoryls in PCr of 23%. However, the overall ATP synthesis rate measured as the rate of appearance of 18O-labelled phosphoryls in g-ATP did not differ
amongst wild-type and M-CK deficient hearts, an observation suggesting a robustness of cellular energetic system. The trend of an increased g-ATP 18O- 30
labelling and a smaller pool size of metabolically active Pi, together with the decreased Pi/g-ATP 18O-labelling ratio (an indicator of intra-cellular energetic communication), observed here for M-CK deficient hearts, indicate less
efficient phosphotransfer energetics. The VIP results show the importance of parameters of glycolytic metabolism (G6P 18O-labelling), AK phospho- 35 transfer (b-ATP/b-ADP 18O-labelling), Pi/ATPase rate (Pi 18O-labelling, Pi, TP) and adenine nucleotide metabolism and ATP turnover (g-ATP 18O-labelling,
ADP and AMP levels) in group classification (Figure 9.9B). Glycolysis, in
addition to its traditional role in ATP production, also catalyses rapid
phosphoryl exchange, and has been implicated in intra-cellular energy 40 transfer and distribution.20,85 Here, changes in glycolytic phosphotransfer in
wild-type and M-CK knockout hearts were assessed by monitoring the appearance of 18O-labelled phosphoryls in G6P as a result of a reaction
catalysed by hexokinase, the entry point into glycolysis. In wild-type hearts, 18O-labelling of G6P was 8.1 Ж 0.5%, which was more than 10% of g-ATP 45 turnover. Deletion of M-CK resulted in an increase of G6P 18O-labelling to
18O-assisted 31P NMR and Mass Spectrometry
263 1 5
Figure 9.9 Phosphometabolomic profiling of wild-type and M-CKА/А mutant
hearts. A) PLS-DA score plot shows clear separation between groups;
B) VIP plot of the PLS-DA method represents importance of metabolites
in discriminating between metabolomic profiles of the groups; C)
regression coefficient plots of metabolic variables in the PLS-DA 35 model; larger coefficient values (positive or negative) indicate a stron-
ger correlation with group metabolic profile classification; D) loading
plot of the PLS-DA plot. Red and blue dots correspond to the mean
position of WT and M-CKА/А group in the plot, respectively; E) valid-
ation of the PLS-DA model by comparison to the classification statistics
of models generated after 100 random permutations of the class 40
13.3 Ж 0.8%, which corresponded to 27% of g-ATP turnover. Therefore, glycolytic phosphotransfer is accelerated in M-CK knockout hearts and may represent an important compensation factor which alleviates myocardial 45 energetic disturbances.
Chapter 9
These results are consistent with studies of CK-deficient hearts 1 performed by other researchers. Increased activities of glycolytic enzymes such as pyruvate kinase and GAPDH were also found in the hearts of CK knockout animals.94 M-CK deficient cardiomyocytes display a higher sensitivity to glycolytic inhibition manifested in premature opening of 5 ATP-sensitive potassium channels, and a shortening of action potential when compared to the wild-type mice,92 suggesting a greater reliance on glycolytic metabolism. To this end, compensation provided by adenylate kinase and glycolytic phosphotransfers in CK-deficient muscles indicate their integral role in facilitating intra-cellular high-energy phosphoryl 10 exchange, especially under conditions of genetic or metabolic stress. Thus, metabolomic profiling and flux analysis reveal plasticity and restructuring of the cellular bioenergetic system in response to genetic deficiency. 15 9.4 Conclusions The 18O-assisted 31P NMR and mass spectrometric analysis techniques provide a versatile methodology, allowing simultaneous recordings of multiple parameters of cellular bioenergetics, and also the characterisation of 20 metabolic fluxes through different energetic pathways. This includes the simultaneous recordings of ATP synthesis and utilisation, phosphotransfer fluxes through adenylate kinase, creatine kinase and glycolytic pathways, as well as mitochondrial Krebs cycle-associated nucleotide turnover and glycogen metabolism. This methodology has also a unique capability to 25 measure intra-cellular energetic communication via comparisons of the kinetics of Pi 18O-labelling (in the ATPase compartment) to that of g-ATP (in the ATP synthesis compartment). Integrated kinetic data obtained using 18O-labelling technology provides a basis for a novel cardiac system bioenergetics concept where major ATP-consuming and ATP-generating 30 processes are inter-connected by phosphotransfer network composed by adenylate kinase and creatine kinase circuits, together with glycolytic/ glycogenolytic network nodes. Metabolomic and fluxomic profiling of phosphotransfer enzyme-deficient Transgenic Animals (AK1А/А and M-CKА/А ) using GC/MS, plus 1H and 18O-assisted 31P NMR analyses, in- 35 dicate metabolic perturbations and adaptations in the whole energetic system. In summary, the 18O-labelling technique has the capacity to monitor phosphotransfer reactions and energetic dynamics in all systems of interest in living tissues. Our studies demonstrate that this approach is valuable for 40 metabolomic and fluxomic profiling of pre-conditioned and failing hearts, as well as transgenic animal models simulating human diseases, and also the diagnosis of mitochondrial energetic deficiency.15,20,22,28,29 Hence, metabolomic analyses in conjunction with system and network approaches provide new avenues for an increased level of understanding of cellular 45 energetic systems in health and diseases.
18O-assisted 31P NMR and Mass Spectrometry
3-Phosphoglyceric acid 6-Phosphogluconate Adenosine diphosphate Adenosine monophosphate Adenosine triphosphate Cyclic adenosine monophosphate Capillary electrophoresis Creatine Creatine phosphate Dihydroxyacetone phosphate Fructose 1,6-bisphosphate Flavin adenine dinucleotide Flavin adenine dinucleotide reduced Fructose 1,6-bisphosphate Glucose 1-phosphate Glycerol 3-phosphate Glucose 6-phosphate Glyceraldehyde 3-phosphate Gas chromatography Guanosine diphosphate Guanosine monophosphate Glycerophosphocholine Glycerophosphoethanolamine Glycerol 3-phosphoserine Guanosine triphosphate Inosine monophosphate Lactate Liquid chromatography Nicotinamide adenine dinucleotide phosphate Nicotinamide adenine dinucleotide phosphate reduced Nuclear magnetic resonance Phosphocholine Principal component analysis Phospho(enol)pyruvic acid Inorganic phosphate Partial least squares discriminant analysis Pyrophosphate Ribose 5-phosphate Total phosphate
265 1 5 10 15 20 25 30 35 40
Acknowledgments Supported by National Institutes of Health, Marriott heart disease Research 45 Program, Marriott Foundation and The Mayo Clinic.
Chapter 9
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