An NMR-based metabonomic investigation of the toxic effects of 3-trifluoromethyl-aniline on the earthworm Eisenia veneta

¹H NMR spectra of earthworms Eisenia veneta treated with 3-trifluoromethyl-aniline in a 72-h contact filter paper test have been analysed using pattern recognition techniques to determine the biochemical response. Various strategies for data reduction of the metabolite profile, and illustration by principal components analysis are applied and discussed. The use of mean principal components plots in simplifying group data representation and highlighting the dose-response function is demonstrated. Hierarchical cluster analysis, and cluster significance analysis of the principal components were also used to examine the relative distribution of dose groups. Identification and assignment of metabolite responses to toxicity were found via correlation coefficient-shift plots. As measured by the correlation coefficients alanine was the most significant metabolite, but increased levels of other amino acids such as glycine and asparagine were also observed. Further, elevated levels of glucose, and the citric acid cycle intermediates citrate and succinate were noted as potential biomarkers of toxicity. This work provides a basis for examining the biochemical response of invertebrates to toxins. This should provide a framework to examine toxicity effects of other halogenated aromatic pollutants to earthworms used as environmental monitors.     

A correlation between antioxidant activity and metabolite release during the blanching of Chrysanthemum coronarium L

Liquid chromatography tandem mass spectrometry (LCMS/MS)-based metabolite profiling was applied to elucidate the correlation between metabolite release and antioxidant activity during water blanching of Chrysanthemum coronarium L. (CC). Some major metabolites showing differences between fresh CC and blanched CC (BCC) were selected by principal component analysis (PCA) and partial least-square discriminate analysis (PLS-DA) loading plots, and were identified as dicaffeoylquinic acid (DCQA), succinoyl-DCQA, and acetylmycosinol. By PLS regression analysis of the correlation between antioxidant components and effects, candidate antioxidative metabolites were predicted due to strong positive correlations with DCQA and succinoyl-DCQA, and by a relatively weak positive correlation with acetylmycosinol.     

A Correlation between Antioxidant Activity and Metabolite Release during the Blanching of Chrysanthemum coronarium L.

Liquid chromatography tandem mass spectrometry (LCMS/MS)-based metabolite profiling was applied to elucidate the correlation between metabolite release and antioxidant activity during water blanching of Chrysanthemum coronarium L. (CC). Some major metabolites showing differences between fresh CC and blanched CC (BCC) were selected by principal component analysis (PCA) and partial least-square discriminate analysis (PLS-DA) loading plots, and were identified as dicaffeoylquinic acid (DCQA), succinoyl-DCQA, and acetylmycosinol. By PLS regression analysis of the correlation between antioxidant components and effects, candidate antioxidative metabolites were predicted due to strong positive correlations with DCQA and succinoyl-DCQA, and by a relatively weak positive correlation with acetylmycosinol.     

The influence of habitat provisioning: use of earthworm burrows by the terrestrial salamander, Plethodon cinereus

Studies examining the influence of habitat provisioning by one species on the behavior of other species can provide key insights regarding impacts of ecosystem engineers on the availability of resources to other species. More specifically, an organism’s use of additional habitat provided by ecosystem engineers may affect the interpretation of observational or demographic data. We chose to examine the possible influence of earthworms, as ecosystem engineers, on the behavior of terrestrial salamanders, common forest vertebrates in North America. We conducted two experiments in microcosms to examine whether the earthworm Lumbricus terrestris acted as an ecosystem engineer by providing additional habitat (burrows) for Plethodon cinereus, a common woodland salamander. We also examined whether the behavioral changes of the non-burrowing, fossorial P. cinereus differed across age classes. Adults and juveniles responded similarly, with both adults and juveniles found under cover objects more often when earthworms were absent and using earthworm burrows when available. Our field data supported our experimental data in that greater numbers of earthworms on field plots were associated with a lower proportion of cover objects being occupied by salamanders (i.e., salamanders were likely underground). We found no differences in the response of adults and juveniles to the presence of earthworms. By providing underground habitat for a common terrestrial amphibian, the presence of earthworms may impact demographic studies on salamanders and conclusions drawn from those studies regarding aboveground faunal communities in eastern North America.     

Metabolic changes in Atlantic salmon exposed to Aeromonas salmonicida detected by 1H-nuclear magnetic resonance spectroscopy of plasma

1H-NMR (nuclear magnetic resonance)-based chemometric methods have been applied for the first time to investigate changes in the plasma metabolite profiles of Atlantic salmon Salmo salar as a result of exposure to Aeromonas salmonicida subsp. salmonicida, a Gram-negative bacterium that is the etiological agent of furunculosis. Plasma samples were obtained from salmon that survived 21 d post exposure to A. salmonicida, and from a control group maintained under similar conditions. 1D 1H-NMR spectra were acquired and principal components analysis (PCA) was used to assess differences between the spectral profiles of plasma from salmon that survived an A. salmonicida challenge, and non-infected controls. PCA enables simultaneous comparison of spectra, presenting a simplified overview of the relationship between spectral data, where spectra cluster based on metabolite profile similarities and differences; information regarding the metabolite variations can therefore be readily deciphered. The major metabolite changes responsible for the spectral differences were related to modification in the lipoprotein profile and choline-based residues, with minor changes in carbohydrates, glycerol, trimethylamine-N-oxide and betaine. These changes indicated that exposure to A. salmonicida induced a characteristic biochemical response which could be used to determine the health status of salmon. This study suggests that with further development this metabolite profiling technique may be a useful tool for diagnosis of disease states in salmon and could provide a better understanding of the host-pathogen relationship which at present is poorly understood for A. salmonicida and Atlantic salmon.     

Directly coupled high-performance liquid chromatography and nuclear magnetic resonance spectroscopic with chemometric studies on metabolic variation in Sprague--Dawley rats

We report here the first combined use of NMR-PR (pattern recognition) analysis and directly coupled HPLC--NMR analysis to identify metabolic subpopulations in normal laboratory animals and their discriminating endogenous urinary biomarkers. Urine samples obtained from control Sprague-Dawley rats (n = 68) were analyzed using (1)H NMR spectroscopy and principal components (PC) analysis to investigate physiological variability. Two distinct subpopulations of animals were classified based on metabolite excretion profiles. Analysis of the PC loadings established the spectral regions that were responsible for classification of the subpopulations and was used to direct the identification of biomarkers using a directly coupled HPLC--NMR analysis. One population had low urinary hippurate levels together with an increased concentration of 3-(3-hydroxyphenyl)propionic acid (3-HPPA)and 3-hydroxycinnamic acid (3-HCA). The other subpopulation excreted high levels of hippurate. Thus, we report the bimodal occurrence of hippuric acid and chlorogenic acid metabolites in a genetically homogeneous population of rats maintained under identical conditions, which may have significance in relation to the understanding of the consequences of biochemical variation in animals used for drug toxicity testing.     

On-line process monitoring and chemometric modeling with 2D fluorescence spectra obtained in recombinant E. coli fermentations

2D spectrofluorometry produces a large volume of spectral data during fermentation processes with recombinant E. coli, which can be analyzed using chemometric methods such as principal component analysis (PCA), principal component regression (PCR) and partial least square regression (PLS). An analysis of the spectral data by PCA results in scores and loadings that are not only visualized in the score-loading plots but are also used to monitor the fermentation processes on-line. The score plots provided useful qualitative information on four fermentation processes for the production of extracellular 5-aminolevulinic acid (ALA). Two chemometric models (PCR and PLS) were used to examine the correlation between the 2D fluorescence spectra and a few parameters of the fermentation processes. The results showed that PLS had slightly better calibration and prediction performance than PCR.     

Antioxidative defence and photoprotection in pine needles under field conditions. A multivariate approach to evaluate patterns of physiological responses at natural sites

Measurements of antioxidants and chloroplast pigments have been widely used as markers of stress and vitality of conifers in the field. However, due to the high variability of these data and the multiple environmental influences tress are exposed to, a quantification of physiological stress responses has only scarcely been possible. Physiological stress responses cannot be monitored by single stress markers, but are governed by many different interactions. The objective of this study was to evaluate patterns of biochemical stress markers in an objective and repeatable manner. For this purpose, a data set of 12 stress-physiological variables (chloroplast pigments, epoxidation state of the xanthophyll cycle, α-tocopherol, ascorbate and dehydroascorbate, GSH and GSSG) measured on field-grown Pinus canariensis needles (n = 90) was subjected to explorative statistical techniques. Four principal components (PC), which explained 80% of the variance of the original data, were extracted by principal component analysis. According to stress-physiological principles, complex responses were assigned to these PCs. Principal component 1 was positively affected by concentrations of a-tocopherol and total ascorbate, and negatively by the proportion of epoxides in the xanthophyll cycle and by α-carotene contents. Principal component 2 was composed of chlorophyll, lutein, neoxanthin, and β-carotene contents, PC 3 contained information about GSH concentrations and the proportions of GSSG and dehydoascorbate; and PC 4 mainly comprised the pool size of the xanthophyll cycle. These components could be ascribed physiological principles such as antioxidative response in chloroplasts (PC 1), pigment content (PC 2), or antioxidant regeneration (PC 3). Via cluster analysis a classification of samples was made based on the patterns of their PC scores. The resulting clusters represented typical physiological response patterns: Cluster 1 was related to initial stages of oxidative damage, cluster 2 to antioxidative responses, whereas cluster 3 represented healthy trees. The spatial distribution of members of these clusters among field plots revealed that different response patterns could be observed at the same plot, a fact that might be ascribed to small scale differences and/or individually differing resistances, and something that is frequently overlooked in the field.     

Statistical multivariate metabolite profiling for aiding biomarker pattern detection and mechanistic interpretations in GC/MS based metabolomics

A strategy for robust and reliable mechanistic statistical modelling of metabolic responses in relation to drug induced toxicity is presented. The suggested approach addresses two cases commonly occurring within metabonomic toxicology studies, namely; 1) A pre-defined hypothesis about the biological mechanism exists and 2) No such hypothesis exists. GC/MS data from a liver toxicity study consisting of rat urine from control rats and rats exposed to a proprietary AstraZeneca compound were resolved by means of hierarchical multivariate curve resolution (H-MCR) generating 287 resolved chromatographic profiles with corresponding mass spectra. Filtering according to significance in relation to drug exposure rendered in 210 compound profiles, which were subjected to further statistical analysis following correction to account for the control variation over time. These dose related metabolite traces were then used as new observations in the subsequent analyses. For case 1, a multivariate approach, named Target Batch Analysis, based on OPLS regression was applied to correlate all metabolite traces to one or more key metabolites involved in the pre-defined hypothesis. For case 2, principal component analysis (PCA) was combined with hierarchical cluster analysis (HCA) to create a robust and interpretable framework for unbiased mechanistic screening. Both the Target Batch Analysis and the unbiased approach were cross-verified using the other method to ensure that the results did match in terms of detected metabolite traces. This was also the case, implying that this is a working concept for clustering of metabolites in relation to their toxicity induced dynamic profiles regardless if there is a pre-existing hypothesis or not. For each of the methods the detected metabolites were subjected to identification by means of data base comparison as well as verification in the raw data. The proposed strategy should be seen as a general approach for facilitating mechanistic modelling and interpretations in metabolomic studies.     

Effects of feeding and body weight loss on the 1H-NMR-based urine metabolic profiles of male Wistar Han rats: implications for biomarker discovery.

For almost two decades, 1H-NMR spectroscopy has been used as an 'open' system to study the temporal changes in the biochemical composition of biofluids, including urine, in response to adverse toxic events. Many of these in vivo studies have reported changes in individual metabolites and patterns of metabolites that correlated with toxicological changes. However, many of the proposed novel biomarkers are common to a number of different types of toxicity. These may therefore reflect non-specific effects of toxicity, such as weight loss, rather than a specific pathology. A study was carried out to investigate the non-specific effects on urinary metabolite profiles by administering four hepatotoxic compounds, as a single dose, to rats at two dose levels: hydrazine hydrate (0.06 or 0.08 g kg (1)), 1,2-dimethylhydrazine (0.1 or 0.3 g kg (-1)), alpha-napthylisothiocyanate (0.1 or 0.15 g kg(-1)) and carbon tetrachloride (1.58 or 3.16 g kg(-1)). The study included weight-matched control animals along with those that were dosed, which were then 'pair-fed' with the treated animals so they achieved a similar weight loss. The urinary metabolite profiles were investigated over time using 1H-NMR spectroscopy and compared with the pathology from the same animals. The temporal changes were analysed statistically using multivariate statistical data analysis including principal component analysis, partial least squares, parallel factor analysis and Fisher's criteria. A number of metabolites associated with energy metabolism or which are partially dietary in origin, such as creatine, creatinine, tricarboxylic acid (TCA) cycle intermediates, phenylacetylglycine, fumarate, glucose, taurine, fatty acids and N-methylnicotinamide, showed altered levels in the urine of treated and pair-fed animals. Many of these changes correlated well with weight loss. Interestingly, there was no increase in ketone bodies (acetate and beta-hydroxybutyrate), which might be expected if energy metabolism was switched from glycolysis to fatty acid beta-oxidation. In some instances, the metabolites that changed were considered to be non-specific markers of toxicity, but were also identified as markers of a specific type of toxicity. For example, taurine was raised significantly in carbon tetrachloride-treated animals but reduced in the pair-fed group. However, raised urinary bile acid levels were only seen after alpha-napthylisothiocyanate treatment. The methodology, statistical analysis used and the data generated will help improve the identification of specific markers or patterns of urinary markers of specific toxic effects.     

Multivariate analysis of benthic invertebrate communities: the implication of choosing particular data standardizations,measures of association,and ordination methods

Benthic invertebrate data from thirty-nine lakes in south-central Ontario were analyzed to determine the effect of choosing particular data standardizations, resemblance measures, and ordination methods on the resultant multivariate summaries. Logarithmic-transformed, 0–1 scaled, and ranked data were used as standardized variables with resemblance measures of Bray-Curtis, Euclidean distance, cosine distance, correlation, covariance and chi-squared distance. Combinations of these measures and standardizations were used in principal components analysis, principal coordinates analysis, non-metric multidimensional scaling, correspondence analysis, and detrended correspondence analysis. Correspondence analysis and principal components analysis using a correlation coefficient provided the most consistent results irrespective of the choice in data standardization. Other approaches using detrended correspondence analysis, principal components analysis, principal coordinates analysis, and non-metric multidimensional scaling provided less consistent results. These latter three methods produced similar results when the abundance data were replaced with ranks or standardized to a 0–1 range. The log-transformed data produced the least consistent results, whereas ranked data were most consistent. Resemblance measures such as the Bray-Curtis and correlation coefficient provided more consistent solutions than measures such as Euclidean distance or the covariance matrix when different data standardizations were used. The cosine distance based on standardized data provided results comparable to the CA and DCA solutions. Overall, CA proved most robust as it demonstrated high consistency irrespective of the data standardizations. The strong influence of data standardization on the other ordination methods emphasizes the importance of this frequently neglected stage of data analysis.     

浙江省丝瓜种质资源主成分分析和聚类分析

为进行丝瓜品种选育,以32个不同丝瓜种质资源为研究材料,调查结瓜习性、叶缘、瓜棱、雌花节率等共22个性状,对得到的性状数据采用DPS软件进行主成分分析和系统聚类分析。结果表明:22个性状可综合为5个主成分,其累积贡献率达81.308%,根据前5个主成分与性状的相关性,选出14个影响力较大的性状。在主成分分析的基础上,对32个丝瓜种质资源进行了系统聚类分析,在欧氏距离的水平上首先将其划分成2大类,又可进一步划分为6个亚类。     

Patterns of ethnic, linguistic, and geographic heterogeneity of palmar interdigital ridge counts in the Indian subcontinent

Published data on palmar interdigital ridge counts (a-b, b-c, and c-d) among 57 populations from the Indian subcontinent were analyzed with reference to ethnic, socioeconomic, linguistic, and geographic affiliations of the studied populations. The spatial autocorrelation analysis suggests significant correlation between dermatoglyphic and geographic distances. The congruence with the ethnic semblance of the groups is also apparent in the data, and, in fact, the multiresponse permutation procedure did suggest highly significant within-group homogeneity, confirming the biological validity of the social and ethnic criteria used in the analysis. The plots of populations on the first two principal components, accounting for 92% of the total variance, complement and support the results based on the other analyses, which show certain ethnic and geographic patterns. These findings can serve as baseline information for future studies on population variation in India, particularly studies based on molecular genetic markers, a trend that has already gained momentum.     

Enantioselective toxicity and degradation of chiral herbicide fenoxaprop-ethyl in earthworm Eisenia fetida

The enantioselective degradation of fenoxaprop-ethyl in ecological indicator earthworm was studied and the main metabolites (fenoxaprop, 6-chloro-2,3-dihydrobenzoxazol-2-one, ethyl-2-(4-hydroxyphenoxy)propanoate, 2-(4-hydroxyphenoxy)propanoic acid) were also monitored on an enantiomeric level. The individual enantiomers of fenoxaprop-ethyl and its three chiral metabolites were prepared to study the acute toxicity to earthworm. Chiral analysis methods were set up based on HPLC–MS/MS with chiralpak IC chiral column. Fenoxaprop-ethyl was not found in earthworms, while the primary metabolite fenoxaprop was in relatively high levels indicating a quick hydrolysis degradation. Fenoxaprop was accumulated almost exclusively with R-enantiomer in earthworms and the bio-concentration factors of R-fenoxaprop and S-fenoxaprop were 1.39 and 0.17 respectively with the enantiomer fraction (EF) values about 0.99. The degradation of R-fenoxaprop in earthworms followed first-order kinetics with half-life of 1.82 day. The other metabolites could not be detected in earthworms. The calculated LC₅₀ values showed ecological indicator earthworm was more sensitive to the four metabolites than fenoxaprop-ethyl. Furthermore, earthworm was more sensitive to the R-form of the chiral metabolites than the S-form and rac-form. The results suggested metabolites and enantioselectivity should be taken into consideration to better predict the exposure concentration and apply ecological indicators in toxicological studies.     

Investigations into biochemical changes due to diurnal variation and estrus cycle in female rats using high-resolution (1)H NMR spectroscopy of urine and pattern recognition

Metabonomic methods utilizing (1)H NMR spectroscopy and pattern recognition analysis (NMR-PR) have been applied to investigate biochemical variation in a control population of female rats over time in relation to diurnal and estrus cycle fluctuations. Urine samples were collected twice daily (6 AM-6 PM and 6 PM-6 AM) from female rats (n = 10) for a period of 10 days. (1)H NMR spectroscopic analysis and PR were performed on each sample. Subtle differences in the endogenous metabolite excretion profiles of urine samples at the various stages of the estrus cycle were observed. The main inherent metabolic clustering in the principal components analysis (PCA) maps was related to interrat variation and was observed in the first two principal components (PCs), accounting for 66% of the variance in these data. Separation of urinary data according to time of sampling (day and night) was achieved in the lower PCs. Some of the differences in the urinary profiles of day and night samples causing this separation were attributed to the increase in metabolic activity of the rat during the night. Individual rat data were also mapped as a function of time, using PCA, to produce a metabolic trajectory, which in a number of cases facilitated separation of one or more stages of the estrus cycle. Several of the fluctuations observed between urine samples collected during the different stages of the estrus cycle may be related to hormone levels. Although variation in metabolite profiles relating to both diurnal and hormonal variation could be detected these perturbations were minor compared with the effects observed due to interrat variation. This is the first time that a hormonal cycle has been described for individuals based on NMR spectroscopic and multivariate analysis of metabolic data and shows the value of metabonomic methods in the investigation of physiological variation and rhythms.     

Spatial Distribution of Biochemical Parameters Indicating Biomass and Community Composition of Microbial Assemblies In Estuarine Mud Flat Sediments

The spatial distribution of communities was examined in estuarine mud flat sediments by the biochemical analysis of the lipids and lipid components extracted from the sediments. Total phospholipid was used as a measure of total biomass, and fatty acids were used as indicators of community composition. Comparisons were made among 2- by 2-m (location) and 0.2- by 0.2-m (cluster) sampling plots by using a nested analysis of variance to design an optimal sampling strategy to define the microbial content of a large, relatively homogenous area. At two of the three stations, a 2- by 2-m plot was representative of the station, but 0.2- by 0.2-m areas were in no case representative of the station. The biomass measured by the extractable phospholipid and the total lipid palmitic acid showed excellent correlation with the fatty acid “signatures” characteristic of bacteria, but showed a lower correlation with the long-chain polyenoic fatty acids characteristic of the microfauna.     

The Extended Statistical Analysis of Toxicity Tests Using Standardised Effect Sizes (SESs): A Comparison of Nine Published Papers

The safety of chemicals, drugs, novel foods and genetically modified crops is often tested using repeat-dose sub-acute toxicity tests in rats or mice. It is important to avoid misinterpretations of the results as these tests are used to help determine safe exposure levels in humans. Treated and control groups are compared for a range of haematological, biochemical and other biomarkers which may indicate tissue damage or other adverse effects. However, the statistical analysis and presentation of such data poses problems due to the large number of statistical tests which are involved. Often, it is not clear whether a “statistically significant” effect is real or a false positive (type I error) due to sampling variation. The author''s conclusions appear to be reached somewhat subjectively by the pattern of statistical significances, discounting those which they judge to be type I errors and ignoring any biomarker where the p-value is greater than p = 0.05. However, by using standardised effect sizes (SESs) a range of graphical methods and an over-all assessment of the mean absolute response can be made. The approach is an extension, not a replacement of existing methods. It is intended to assist toxicologists and regulators in the interpretation of the results. Here, the SES analysis has been applied to data from nine published sub-acute toxicity tests in order to compare the findings with those of the author''s. Line plots, box plots and bar plots show the pattern of response. Dose-response relationships are easily seen. A “bootstrap” test compares the mean absolute differences across dose groups. In four out of seven papers where the no observed adverse effect level (NOAEL) was estimated by the authors, it was set too high according to the bootstrap test, suggesting that possible toxicity is under-estimated.     

Genetic evidence for the phylogenetic relationship between Na-Dene and Yeniseian speakers

Ruhlen's hypothesis, based on linguistic evidence, for a common phylogenetic origin of Na-Dene and Yeniseian speakers is tested using genetic data. Gene frequency data for the Kets, the only surviving Yeniseian speakers, were collected during a field study in 1993. Data for several Na-Dene groups, as well as other New World and Siberian populations, were compiled from the literature. These data were analyzed using R-matrix, principal components analysis, and Mantel tests. In a comparison of 10 New World and Siberian populations using eight alleles, 55.8% of the variation was accounted for by the first principal component, and 22.1% of the variation was subsumed by the second principal component. Contrary to Ruhlen's interpretation of the linguistic data, analysis of the genetic data shows that the Na-Dene cluster with other Native American populations, while the Kets genetically resemble the surrounding Siberian groups. This conclusion is further supported by correlations that are higher when the Kets are considered unrelated to Na-Dene speakers, and an insignificant partial correlation between genes and language when geography is held constant, indicating that spatial patterning accounts for most of the variation present in these populations.     

A cranial morphometric study of deer (Mammalia, Cervidae) from Argentina using three-dimensional landmarks

This study examines morphological variation in the crania (n = 70) of eight cervid species from Argentina. Forty 3-dimensional landmarks were acquired on each adult cervid cranium. The data were analysed using Morphologika software. The co-ordinates were registered and scaled to remove size differences by Procrustes analysis, and then principal components analysis was applied to examine shape variation. Shape variation associated with each principal component can be visualised in the program. The first principal component correlates strongly with the centroid size of the crania and also with the body mass and height of each species. The larger species were distinguished by relatively longer snouts and relatively smaller brains. The smallerMazama andPudu species cluster closely on the first as well as the other principal components. Among the larger species, the twoHippocamelus species, which live at higher altitudes, were clearly distinguished from the lowland species,Ozotoceros bezoarticus andBlastocerus dichotomus, on the basis of cranial flexion and the orientation of the occipital region. FinallyO. bezoarticus andB. dichotomus were compared directly and small differences were noted in the orbital region. The shape data was used to produce a distance matrix and a phenogram, which we relate to some of currently accepted phylogenetic relationships of this group of cervids.     

Metabolomic profiling of heat stress: hardening and recovery of homeostasis in Drosophila

Frequent exposure of terrestrial insects to temperature variation has led to the evolution of protective biochemical and physiological mechanisms, such as the heat shock response, which markedly increases the tolerance to heat stress. Insight into such mechanisms has, so far, mainly relied on selective studies of specific compounds or characteristics or studies at the genomic or proteomic levels. In the present study, we have used untargeted NMR metabolomic profiling to examine the biological response to heat stress in Drosophila melanogaster. The metabolite profile was analyzed during recovery after exposure to different thermal stress treatments and compared with untreated controls. Both moderate and severe heat stress gave clear effects on the metabolite profiles. The profiles clearly demonstrated that hardening by moderate heat stress led to a faster reestablishment of metabolite homeostasis after subsequent heat stress. Several metabolites were identified as responsive to heat stress and could be related to known physiological and biochemical responses. The time course of the recovery of metabolite homeostasis mirrored general changes in gene expression, showing that recovery follows the same temporal pattern at these two biological levels. Finally, our data show that heat hardening permits a quicker return to homeostasis, rather than a reduction of the acute metabolic perturbation and that the reestablishment of homeostasis is important for obtaining maximal heat-hardening effect. The results display the power of NMR metabolomic profiling for characterization of the instantaneous physiological condition, enabling direct visualization of the perturbation of and return to homeostasis.