Cryogenic Probe 13C NMR Spectroscopy of Urine for Metabonomic

Here, we demonstrate that information-rich 13C NMR spectra of rat urine can be .... Muireann Coen , Elaine Holmes , John C. Lindon and Jeremy K. Nicho...
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Anal. Chem. 2002, 74, 4588-4593

Correspondence

Cryogenic Probe 13C NMR Spectroscopy of Urine for Metabonomic Studies Hector C. Keun,*,† Olaf Beckonert,† Julian L. Griffin,† Christian Richter,‡ Detlef Moskau,‡ John C. Lindon,† and Jeremy K. Nicholson†

Biological Chemistry, Biomedical Sciences, Faculty of Medicine, Imperial College of Science, Technology and Medicine, London, SW7 2AZ, U.K., and Bruker Biospin AG, Industriestrasse 26, CH-8117, Faellanden, Switzerland

Cryogenic probe technology can significantly compensate for the inherently low sensitivity of natural abundance 13C NMR spectroscopy. This now permits its routine use in NMR spectroscopy of biofluids, such as urine or plasma, with acquisition times that enable a high throughput of samples. Metabonomic studies often generate numerous samples in order to characterize fully the time-dependent biochemical response to stimuli, but until now, they have been largely conducted using 1H NMR spectroscopy because of its high sensitivity and hence efficient data acquisition. Here, we demonstrate that information-rich 13C NMR spectra of rat urine can be obtained using appropriately short acquisition times suitable for biochemical samples when using a cryogenic probe. Furthermore, these data were amenable to automated pattern recognition analysis, which produced a profile of the metabolic response to the model hepatotoxin hydrazine that was consistent with earlier studies. Thus, a new source of detailed and complementary information is available to metabonomics using cryogenic probe 13C NMR spectroscopy.

spectroscopy to the study of biofluids and tissues has thus been demonstrated as an efficient method for studying the effects of drug toxicity, for clinical diagnosis and for investigating gene function.7-10 Biofluid NMR spectroscopy, especially of urine, is particularly useful for defining metabolic changes, because the spectra are rich in information, and the collection of these fluids is relatively noninvasive, allowing a reduction in animal numbers for such investigations. High-field 1H NMR spectra of biofluids typically contain several thousand resolvable lines, potentially providing structural and quantitative information on hundreds of compounds in a single, nondestructive analysis that takes only a few minutes. The manual analysis of even a small number of such spectra is a laborious and complex task, and therefore, metabonomics utilizes data reduction and multivariate analysis techniques,11,12 such as principal components analysis (PCA) to facilitate automated NMR pattern recognition (NMR-PR).13-16 In principle, NMR spectra generated using other nuclei could be used for metabonomic studies. For example, 13C NMR spectroscopy would provide complementary structural information17 while potentially reducing the problems of overlap that is

Metabonomics is a holistic approach for measuring time-related biochemical responses in key intermediary biochemical pathways as a result of physiological, pathological, or interventional genetic events, and this has been achieved principally through the use of 1H NMR spectroscopy on biofluids such as urine or plasma.1-3 In addition, tissue samples can be analyzed using magic-anglespinning 1H NMR spectroscopy.4-6 The application of 1H NMR

(6) Griffin, J. L.; Walker, L.; Shore, R. F.; Nicholson, J. K. Xenobiotica 2001, 31, 377-385. (7) Robertson, D. G.; Reily, M. D.; Sigler, R. E.; Wells, D. F.; Paterson, D. A.; Braden, T. K. Toxicol. Sci. 2000, 57, 326-337. (8) Gavaghan, C. L.; Holmes, E.; Lenz, E.; Wilson, I. D.; Nicholson, J. K. FEBS Lett. 2000, 484, 169-174. (9) Griffin, J. L.; Walker, L. A.; Shore, R. F.; Nicholson, J. K. Chem. Res. Toxicol. 2001, 14, 1428-1434. (10) Waters, N. J.; Holmes, E.; Williams, A.; Waterfield, C. J.; Farrant, R. D.; Nicholson, J. K. Chem. Res. Toxicol. 2001, 14, 1401-1412. (11) Eriksson, L.; Johansson, E.; Kettaneh-Wold, H.; Wold, S. Introduction to Multi and Megavariate Analysis using Projection Methods (PCA & PLS); UMETRICS Inc.: Box 7960, SE90719 Umeå, Sweden, 1999, 267-296. (12) Jurs, P. C. Science 1986, 232, 1219-1224. (13) Holmes, E.; Nicholson, J. K.; Nicholls, A. W.; Lindon, J. C.; Connor, S. C.; Polley, S.; Connelly, J. Chemom. Intell. Lab. Syst. 1998, 44, 245-255. (14) Anthony, M. L.; Sweatman, B. C.; Beddell, C. R.; Lindon, J. C.; Nicholson, J. K. Mol. Pharmacol. 1994, 46, 199-211. (15) Holmes, E.; Nicholls, A. W.; Lindon, J. C.; Ramos, S.; Spraul, M.; Neidig, P.; Connor, S. C.; Connelly, J.; Damment, S. J.; Haselden, J.; Nicholson, J. K. NMR Biomed. 1998, 11, 235-244. (16) Holmes, E.; Nicholls, A. W.; Lindon, J. C.; Connor, S. C.; Connelly, J.; Haselden, J. N.; Damment, S. J.; Spraul, M.; Neidig, P.; Nicholson, J. K. Chem. Res. Toxicol. 2000, 13, 471-478. (17) Fan, T. W-M. Prog. NMR Spectrosc. 1996, 28, 161-219.

* To whom correspondence should be addressed. Tel: 44-(0)20-7594-3142. Fax: 44-(0)20-7594-3226. E-mail: [email protected]. † Imperial College of Science, Technology and Medicine. ‡ Bruker Biospin AG. (1) Nicholson, J. K.; Lindon, J. C.; Holmes, E. Xenobiotica 1999, 29, 11811189. (2) Lindon, J. C.; Nicholson, J. K.; Holmes, E.; Everett, J. R. Prog. NMR Spectrosc. 2000, 12, 289-320. (3) Nicholson, J. K.; Connelly, J.; Lindon, J. C.; Holmes, E. Nat. Drug. Discov. 2002, 1, 153-161. (4) Garrod, S.; Humpfer, E.; Spraul, M.; Connor, S. C.; Polley, S.; Connelly, J.; Lindon, J. C.; Nicholson, J. K.; Holmes, E. Magn. Reson. Med. 1999, 41, 1108-1118. (5) Bollard, M. E.; Garrod, S.; Holmes, E.; Lindon, J. C.; Humpfer, E.; Spraul, M.; Nicholson, J. K. Magn. Reson. Med. 2000, 44, 201-207.

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often found in 1H NMR spectra of complex biofluids, since the chemical shift range for 13C is ∼20 times that of 1H. In addition, all scalar couplings are usually removed by 1H decoupling, thus simplifying the spectrum to a single line for each chemically nonequivalent carbon. Of particular advantage is the absence of a water resonance, and hence, effective solvent suppression, which can cause the loss of peaks close to the water peak in 1H NMR spectra, is no longer required. Other factors, such as differential nuclear Overhauser effect (NOE) enhancement for different 13C nuclei, may need to be considered, although this problem can be ameliorated by decoupling only during acquisition. The longer T1 values for 13C nuclei compared to 1H nuclei can also require longer recycle delays, but it will be shown that useful 13C NMR spectra can be acquired in reasonable times without the need for methods to shorten T1, such as addition of paramagnetic relaxation agents. Despite enhancement by techniques such as NOE, the low natural abundance (∼1.1%) and low gyromagnetic ratio of 13C nuclei (∼25% of 1H) means that for typical metabolite concentrations in biofluids, 13C NMR spectra suffer from poor sensitivity and exorbitant acquisition times. The examination of numerous samples of biofluids, typical in a metabonomic study, would therefore require prohibitively long acquisition times or extreme concentration techniques that could lead to solubility problems for some analytes. In other studies, for example, in protein structure determination, it is possible to alleviate the sensitivity limitation through extensive stable isotope labeling. This is not generally possible in whole-organism metabolic studies because of the high cost and spurious label losses, although some specific biochemical pathways can be labeled. NMR signal-to-noise ratios (S/N) can be significantly improved by cooling the NMR radio frequency detector and preamplifier.18 The noise figure is reduced approximately by a factor proportional to the square root of the temperature ratio in degrees K, and thus, the combination of cooling the coil and preamplifier from room temperature to ∼20 K reduces the thermal noise by ∼4-fold. This gives a corresponding gain in S/N per scan or for the same S/N a reduction in acquisition time of ∼16-fold. This improved sensitivity for 13C nuclei is such that cryogenic probes allow good S/N with reasonable acquisition times using biofluid samples. The difficulties of using cryogenic probes to measure 1H NMR spectra of high-ionic-strength samples, such as urine, are predominantly associated with water suppression, and this is not necessary for 13C NMR data acquisition. Experiments such as 13C DEPT and 1H -13C HSQC also become more accessible, facilitating spectral assignment. The problem still remains that 13C nuclei with long T1 relaxation times, such as carbonyl groups, still give reduced signal intensities, and hence, quantification can be problematic. Nevertheless, for metabonomic studies in which all samples are measured under identical conditions, such quantitation is less necessary, because it is the overall pattern of response which can be interpreted. In the current work, rat urine samples from a study of hydrazine toxicity were examined. Hydrazine is a model liver toxin and has been identified as a metabolite of a number of pharmaceuticals, such as the antituberculosis drug isoniazid and the (18) Styles, P.; Soffe, N. F.; Scott, C. A.; Cragg, D. A.; Row, F.; White, D. J.; White, P. C. J. J. Magn. Reson. 1984, 60, 397-404.

antihypertensive drug hydralazine.19 Hydrazine itself has been commonly used as a model hepatotoxin in animal studies,20-22 although carcinogenicity, mutagenicity, and neurotoxicity have also been observed.21,22 Here, we demonstrate that 13C NMR spectroscopy conducted using a cryogenically cooled probe can produce data suitable for metabonomic analysis on a time scale that allows its routine use. EXPERIMENTAL SECTION Sample Collection. Male 8-10-week-old Sprague-Dawley rats were housed in metabolism cages and acclimatized for 48 h prior to dosing. A standard diet, Purina chow 5002, was given to all animals, and free access to food and water was permitted throughout the study. A temperature of 21 ( 2 °C and a relative humidity of 55 ( 10% was maintained with fluorescent lighting between 06.00 and 18.00 (1h. Animals were randomly assigned to dose groups: control (vehicle only), low-effect dose (30 mg/ kg), and pathological dose (90 mg/kg). The dose of hydrazine dihydrochloride in saline (10 mL/kg) was administered p.o. at 0 h. Urine samples used for the current work were collected 2448 h post dose from 3 animals from each dose group. On collection, urine samples were centrifuged at 3000 rpm for 10 min to remove any solid debris, and were subsequently stored at -70 °C pending 13C NMR spectroscopic analysis. NMR Spectroscopy. To minimize the variation in pH and to provide a field-frequency lock, 200 µL of a buffer solution (1 M Na2HPO4/NaH2PO4, pH 7.0) and 50 µL of D2O were added to 400 µL of each urine sample. TSP, 1 mM, was included in the buffer to provide an internal reference standard. The resulting solutions were allowed to stand for 10 min at room temperature and were then centrifuged at 6000-8000 rpm for 10 min to remove any insoluble material. One-dimensional 13C NMR spectra were acquired on a Bruker DRX-600 AVANCE spectrometer (Bruker AG, Faellanden, Switzerland) using a conventional 5-mm broadband inverse detection probe. Typically, a total of 12 000 transients each of 16 k data points was acquired with an acquisition time of 1.04 s, a 5-s interpulse delay, a spectral width of 250 ppm, and with GARP 1H decoupling throughout the experiment. A pulse width of 13 µs at -3 dB (90°) was used. The free induction decay (FID) was zero-filled by a factor of 2 and multiplied by a 1 Hz exponential line-broadening factor prior to Fourier transformation. To evaluate the cryoprobe technology, other spectra were acquired on a Bruker DRX-500 AVANCE spectrometer (Bruker Biospin AG, Faellanden, Switzerland) using a direct detection 5-mm 13C-1H cryoprobe attached to a CryoPlatform (the preamplifier cooling unit). One-dimensional 13C spectra were acquired using 512 transients each of 64 k data points with a 2.5-s interpulse delay, an acquisition time of 1.04 s, a spectral width of 250 ppm, and with WALTZ-16 1H decoupling throughout the experiment, resulting in ∼30 min acquisition time. A pulse of 8.25 µs at 2 dB (90°) was used. The FIDs were zero-filled by a factor of 2 and multiplied by a 1 Hz exponential line-broadening factor prior to Fourier transformation. To confirm spectral assignments, a 1H-13C het(19) Blair, I. A.; Mansilla-Tinoco, R.; Brodie, M.; Clare, R. A.; Dollery, C. T.; Timbrell, J. A.; Beaver, I. A. Hum. Toxicol. 1985, 4, 195-202. (20) Waterfield, C. J.; Turton, J. A.; Scales, M. D. C.; Timbrell, J. A. Arch. Toxicol. 1993, 67, 244-254. (21) Sax, N. I. Dangerous Prop. Ind. Mater. Rep. 1990, 10, 21-58. (22) Moloney, S. J.; Prough, R. A. Rev. Biochem. Toxicol. 1983, 5, 313-346.

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Figure 1. Comparison of partial 13C NMR spectra attained with different probe systems for the same urine sample: (upper) conventional broadband inverse 5-mm probe at an observation frequency of 150 MHz and (lower) cryogenic direct detection 5 mm probe at an observation frequency of 125 MHz.

eronuclear single quantum correlation (HSQC) spectrum was acquired on one sample using a standard echo/antiecho-TPPI gradient selection pulse sequence.23 The parameters comprised a J-coupling delay of 0.86 ms, time domain points of 2 k (F2) and 1 k (F1), spectrum width (1H) of 12 ppm, spectrum width (13C) of 200 ppm, GARP 13C decoupling, 8 scans/increment, acquisition time of 0.17 s, and a relaxation delay of 2 s. In addition, a 1H-13C heteronuclear multiple quantum correlation (HMQC) spectrum24 optimized for long-range couplings was acquired on the same sample. The parameters comprised a J-coupling delay of 1.74 ms, time domain points of 4 k (F2) and 1 k (F1), spectrum width (1H) of 12 ppm, spectrum width (13C) of 250 ppm, GARP 13C decoupling, 16 scans/increment, and an acquisition time of 0.34 s. These experiments were performed to correlate 1H and 13C resonances. Data Reduction and Pattern Recognition. Each 13C NMR spectrum was segmented into 195 regions of equal width (1 ppm) over the region 5-200 ppm and the signal intensity in each region was integrated using AMIX (version 2.5.9, Bruker Analytik, Rheinstetten, Germany). The region 165-167 ppm was deleted to remove the effect of variability in the levels of urea. Finally, to take account of large variations in urine concentration, all spectra were normalized to a constant integrated intensity of 100 units. The data were tabulated such that the rows corresponded to urine sample 13C NMR spectra and the columns comprised the NMR integral values. Multivariate analysis was performed using SIMCA-P software (version 8.0, Umetrics AB, Umeå, Sweden). Meancentered scaling was used in which the mean of each integral value was subtracted from each column of the data set. This is equivalent to subtracting the mean spectrum from each other spectrum in the data set and performing subsequent analyses on the mean-subtracted spectra. Principal components analysis (PCA) (23) Schleucher, J.; Schwendinger, M.; Sattler, M.; Schmidt, P.; Schedletzky, O.; Glaser, S. J.; Sorensen, O. W.; Griesinger, C. J. Biomol. NMR 1994, 4, 301-306. (24) Palmer, A. G.; Cavanagh, J.; Wright. P. E.; Rance, M. J. Magn. Reson. 1991, 93, 151-170.

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was used to calculate a new, smaller set of orthogonal variables from linear combinations of the 195 intensity variables while retaining the maximum variability present within the data. These new variables are the derived principal components (PCs), and the distribution of their values (scores) permits the simple visualization of separation or clustering between samples. The weightings (loadings) given to each integral region in calculating the PCs allows for the identification of those spectral regions of greatest influence to the separation/clustering and, hence, the deduction of biomarkers of toxicity.13 RESULTS The use of a cryoprobe shows a clear advantage in sensitivity over a typical 13C NMR spectrum acquired using a conventional probe, thus resulting in significantly reduced acquisition times (Figure 1). It should be noted that the conventional 13C NMR spectrum was acquired at an observation frequency of 150 MHz (equivalent to 600 MHz for 1H NMR spectroscopy), and the cryoprobe spectrum was obtained at 125 MHz (equivalent to 500 MHz for 1H NMR spectroscopy). A direct comparison of the two probe configurations on the same spectrometer was not possible because of the unavailability of a 600 MHz cryoprobe or a conventional 500 MHz inverse broadband probe in the same laboratory. However, it is possible to make an estimate of the improvement in sensitivity provided by the cryoprobe. The measured S/N ratio for the conventional probe is about one-half that of the cryoprobe, but required 34 times the data acquisition period. This suggests that the improvement in S/N per unit time using the cryoprobe was about 11. However, in the acquisition period for the conventional data, the relaxation period was doubled, indicating that the comparable S/N for the conventional probe was underestimated by a factor of up to x2, making the true improvement given by the cryoprobe to be a factor of ∼7, ignoring the minor difference in intrinsic sensitivity due to the difference in magnetic field strength. It should be pointed out that the cryoprobe had a direct 13C NMR detection configuration with

Figure 2. Typical 500 MHz cryogenic probe 13C NMR spectra of rat urine samples taken at 48 h post dose for each dose group, as described in the Experimental Section: (A) control; (B) low dose hydrazine, 30 mg/kg; and (C) high dose hydrazine, 90 mg/kg. Each spectrum took ∼30 min total acquisition time. ArgSuc, argininosuccinate; Citrl, citrulline; NacCitrl, N-acetyl citrulline; Citr, citrate; 2-AA, 2-aminoadipate; Ala, alanine; Crea, creatine; Crn, creatinine; Tau, taurine; THOPC, 1,4,5,6-tetrahydro-6-oxo-3-pyridazine carboxylic acid (*tentatively assigned); and Tyr, tyrosine.

Figure 3. Scores, t, (A) and loadings, p, (B) plots of a 2-component PCA model of nine 13C NMR spectra of rat urine. Circles: high-dose hydrazine, 90 mg/kg. Squares: low-dose hydrazine, 30 mg/kg. Triangles: controls (vehicle only). The explained variance was 61.2 and 16.8% in PC1 and PC2, respectively (Q2cum ) 55%). Variables, denoted by their chemical shift values in ppm, that significantly contribute to the observed separation were assigned as follows: 46, 47, 48, 78, 181, 184, citrate; 65, 66, 73, 74, 75, glucose; 50 taurine; 39, 181, β-alanine; 26, 30, 43, 56, 65, 158, argininosuccinate; 24, 33, 39, 57, 177, 2-aminoadipate; 129, 131, 135, hippurate; 133, tyrosine; 33, 39, 177, creatine; 24, 58, 177, N-acetyl citrulline; and 57, 177, citrulline.

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Figure 4. Assignment of the NMR resonances in the aliphatic region of the 1H-13C HSQC spectrum: ArgSuc, argininosuccinate; Citrl, citrulline; NAcCitrl, N-acetyl citrulline; Citr, citrate; 2-AA, 2-aminoadipate; Ala, alanine; DMA, dimethylamine; DMG, dimethylglycine; Crea, creatine; Crn, creatinine; Glc, glucose; Tau, taurine; THOPC, 1,4,5,6-tetrahydro-6-oxo-3-pyridazine carboxylic acid (*tentatively assigned); and Tyr, tyrosine. This spectrum was acquired in 4.5 h.

the coil close to the sample, and the conventional probe was of the inverse detection configuration such that the 13C NMR detection is achieved through the decoupler coil further from the sample. Hence, the apparent improvement of a factor of 7 has to be reduced because the conventional probe had a poorer filling factor, thereby bringing the true improvement closer to the theoretical value. Thus, the S/N gain is of the order expected by theory and demonstrates that for 13C NMR spectroscopy, S/N losses caused by this type of ionic sample are not important. The 13C NMR spectral profiles of urines from control and highhydrazine-dose animals are markedly different, with the modulation of the intensity of peaks from many endogenous metabolites and the appearance of several new resonances post dose (Figure 2). Changes can be observed across the entire spectrum, encompassing carbonyl, aromatic, and aliphatic resonances. When all of these data are combined using PCA, the different treatments cluster separately, and the PCA loadings immediately highlight the regions of the spectrum responsible for the greatest variation in these data (Figure 3). The variation between the clusters of different dose and control samples appears largely dose-dependent. The high-dose samples cluster tightly and are well-separated from the control group. In addition, the urine NMR spectra from low-dose animals, although showing some variation, are also 4592

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separated from those of controls and are in an intermediate position between the control and high-dose groups. This data set adequately demonstrates that rapidly acquired 13C NMR spectra carry classification information analogous to a 1H NMR study. Examination of the loadings plots in Figure 3B allows identification of those resonances responsible for the class separation seen in Figure 3A. These spectral regions were further investigated, and many of their constituent resonances were assigned to endogenous metabolites using literature values17,25-27 and 1H13C correlation experiments (Figure 4), the efficiency of which is also markedly improved by cryogenic probe technology. From these assignments, the profiling of the biochemical response to hydrazine treatment at 48 h after dosing (Table 1) was possible. Elevation in levels of 2-aminoadipate, taurine, creatine, citrulline, N-acetyl citrulline, argininosuccinate, and β-alanine were observed, together with concomitant decreases in urinary glucose, citrate, and hippurate. (25) Willker, W.; Engelmann, J.; Brand, A.; Leibfritz, D. J. Magn. Res. Anal. 1996, 2, 21-32. (26) Nicholson, J. K.; Foxall, P. J. D.; Spraul, M.; Farrant, R. D.; Lindon, J. C. Anal. Chem. 1995, 67, 793-811. (27) Pouchert, C. J.; Behnke, J. The Aldrich library of 13C and 1H FT NMR spectra; Aldrich Chemical Co.: Milwaukee, WI, 1993.

Table 1. 13C NMR Chemical Shifts and Assignments for the Endogenous Urinary Metabolites Responsible for the Separation of Samples from Control and Hydrazine Dosed Animals

metabolite 2-aminoadipic acid citrate creatine taurine argininosuccinate β-alanine glucose hippurate N-acetyl-citrulline citrulline

13C

chemical shifts (ppm)17,25-27

C3-5: 24.3, 33.2, 39.7; C2: 57.6; C1,6: 177.7, 185.4 C3COO-: 184.5; C1,5: 181.8; C3: 78.3; C2,4: 46.7, 48.1 (exchange-broadened) C1: 177.4; NCN: 160; NMe/C2: 39.8, 56.7 S-CH2: 38.4; N-CH2: 50.5 CΗ2: 26.8, 30.6, 43.8; CH: 55.7; (NH)(H2N)CdN (Arg): 158.5 CH2: 36.5, 39.6; COO-: 181.5 C6R/β: 64-66; C2R, C4R/β, C5R: 73-76, C2,3,5β: 78-79; C1β: 98.8 phe:129.9, 131.6, 135.0; COO-: 173.6 CH3CO-: 24.8, CHR: 58.0, COO-: 177 CHR: 57.3; COO-: 177

DISCUSSION Metabonomics represents a new approach for comprehensively characterizing the dynamic metabolic response of an organism, and the NMR-PR approach to this is now well established.3 Any experimental design that sets out to simultaneously test the extent of dose-related, time-related, and physiological variation will generate many samples per study. Although the acquisition of a 1H NMR spectrum of a urine sample typically takes a few minutes on a conventional probe, 13C NMR spectroscopy on biofluids generally takes several hours per spectrum to obtain useful S/N ratios, prohibiting its routine use for nonenriched samples. Here, it is demonstrated that using cryogenic NMR probe technology, information-rich 13C NMR biofluid spectra can be acquired in ∼30 min, making possible the efficient use of 13C NMR spectroscopy alongside 1H NMR spectroscopy in metabonomic studies. It is also shown that PR analysis can be applied to 13C NMR data and that it provides a similarly successful means of classification as for 1H NMR spectra. Large 13C spectral datasets can thus be rapidly and reliably scrutinized. The protocol presented here appears to overcome potential problems of a sparse data matrix and pH-dependent chemical shift changes and may yet further be improved by elimination of noise regions or an increase in the number of reduced variables. The significantly greater dispersion of the 13C chemical shift, as compared to 1H, offers distinct advantages for metabolite identification and resonance assignment in biofluid NMR spectroscopy. The correlation of 1H and 13C NMR data is a logical development of the approach that would presumably enhance the efficacy of mining metabonomic data. This can be achieved either (28) Amenta, J.; Johnston, H. Lab. Invest. 1962, 11, 956-962. (29) Ray, P. D.; Hanson, R. L.; Lardy, H. J. Biol. Chem. 1970, 245, 690-695. (30) Nicholls, A. W.; Holmes, E.; Lindon, J. C.; Shockcor, J. P.; Farrant, R. D.; Haselden, J. N.; Damment, S. J.; Waterfield, C. J.; Nicholson, J. K. Chem. Res. Toxicol. 2001, 14, 975-87.

increase (v) or decrease (V) relative to controls v V v v v v V V v v

directly by 2D NMR spectroscopy or indirectly by statistical means, and both approaches are currently under further investigation. Several studies have shown that hydrazine produces liver and muscle glycogenolysis,28 inhibition of glucogenesis,29 hypoglycemia,29 elevation of lactate, pyruvate, citrate, malate, and oxaloacetate in the blood29 and a rise in fatty acids and the appearance of fatty liver.28 More recent work by Waterfield et. al., found that urinary taurine levels increased up to 48 h post dose, although liver taurine levels showed little or no alteration.20 A recent metabonomic study, using 1H NMR spectroscopic studies of rat urine following hydrazine treatment concurs with the observations here of increases in β-alanine, creatine, taurine, argininosuccinate and 2-aminoadipate, as well as decreases in glucose, citrate, and hippurate.30 Other changes reported in the literature, principally decreases in other Krebs cycle intermediates, have not been unambiguously assigned in the current work. Although further analysis will continue, these differences may, in part, be a result of differing response dynamics (only 48 h postdose samples were examined). 13C NMR spectroscopy now becomes a viable addition to the metabonomics toolkit. Cryogenic probe technology combined with the type of data acquisition and processing protocols presented here provides a valuable first step into this area. ACKNOWLEDGMENT We thank the Consortium on Metabonomic Toxicology (COMET) for provision of samples used in this study and we would like to acknowledge COMET (H.C.K. and O.B.) and the Royal Society of Great Britain (J.L.G.) for funding. Received for review April 9, 2002. Accepted July 10, 2002. AC025691R

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