A pilot study of GC/MS-based serum metabolic profiling of acute rejection in renal transplantation

Longitudinal non-targeted metabolomic profiling of urine samples for monitoring of kidney transplantation patients

The assessment of kidney function within the first year following transplantation is crucial for predicting long-term graft survival. This study aimed to develop a robust and accurate model using metabolite profiles to predict early long-term outcomes in patient groups at the highest risk of early graft loss. A group of 61 kidney transplant recipients underwent thorough monitoring during a one-year follow-up period, which included a one-week hospital stay and follow-up assessments at three and six months. Based on their 12-month follow-up serum creatinine levels: Group 2 had levels exceeding 1.5 mg/dl, while Group 1 had levels below 1.5 mg/dl. Metabolites were detected by mass spectrometer and first pre-processed. Univariate and multivariate statistical analyses were employed to identify significant differences between the two groups. Nineteen metabolites were found to differ significantly in the 1st week, and seventeen metabolites in the 3rd month (adjusted p-value < 0.05, quality control (QC) < 30, a fold change (FC) > 1.1 or a FC < 0.91, Variable Influence on Projection (VIP) > 1). However, no significant differences were observed in the 6th month. These distinctive metabolites mainly belonged to lipid, fatty acid, and amino acid categories. Ten models were constructed using a backward conditional approach, with the best performance seen in model 5 for Group 2 at the 1st-week mark (AUC 0.900) and model 3 at the 3rd-month mark (AUC 0.924). In conclusion, the models developed in the early stages may offer potential benefits in the management of kidney transplant patients.

Oral administration of the commensal Alistipes onderdonkii prolongs allograft survival

Intestinal commensals can exert immunomodulatory effects on the host, with beneficial or detrimental consequences depending on underlying diseases. We have previously correlated longer survival of minor mismatched skin grafts in mice with the presence of an intestinal commensal bacterium, Alistipes onderdonkii. In this study, we investigated its sufficiency and mechanism of action. Oral administration of A onderdonkii strain DSM19147 but not DSM108265 was sufficient to prolong minor mismatched skin graft survival through inhibition of tumor necrosis factor production. Through metabolomic and metagenomic comparisons between DSM19147 and DSM108265, we identified candidate gene products associated with the anti-inflammatory effect of DSM19147. A onderdonkii DSM19147 can lower inflammation both at a steady state and after transplantation and may serve as an anti-inflammatory probiotic beneficial for transplant recipients.

Proteomics for Biomarker Discovery for Diagnosis and Prognosis of Kidney Transplantation Rejection

Renal transplantation is currently the treatment of choice for end-stage kidney disease, enabling a quality of life superior to dialysis. Despite this, all transplanted patients are at risk of allograft rejection processes. The gold-standard diagnosis of graft rejection, based on histological analysis of kidney biopsy, is prone to sampling errors and carries high costs and risks associated with such invasive procedures. Furthermore, the routine clinical monitoring, based on urine volume, proteinuria, and serum creatinine, usually only detects alterations after graft histologic damage and does not differentiate between the diverse etiologies. Therefore, there is an urgent need for new biomarkers enabling to predict, with high sensitivity and specificity, the rejection processes and the underlying mechanisms obtained from minimally invasive procedures to be implemented in routine clinical surveillance. These new biomarkers should also detect the rejection processes as early as possible, ideally before the 78 clinical outputs, while enabling balanced immunotherapy in order to minimize rejections and reducing the high toxicities associated with these drugs. Proteomics of biofluids, collected through non-invasive or minimally invasive analysis, e.g., blood or urine, present inherent characteristics that may provide biomarker candidates. The current manuscript reviews biofluids proteomics toward biomarkers discovery that specifically identify subclinical, acute, and chronic immune rejection processes while allowing for the discrimination between cell-mediated or antibody-mediated processes. In time, these biomarkers will lead to patient risk stratification, monitoring, and personalized and more efficient immunotherapies toward higher graft survival and patient quality of life.

Estimating Glomerular Filtration Rate from Serum Myo-Inositol, Valine, Creatinine and Cystatin C

Assessment of renal function relies on the estimation of the glomerular filtration rate (eGFR). Existing eGFR equations, usually based on serum levels of creatinine and/or cystatin C, are not uniformly accurate across patient populations. In the present study, we expanded a recent proof-of-concept approach to optimize an eGFR equation targeting the adult population with and without chronic kidney disease (CKD), based on a nuclear magnetic resonance spectroscopy (NMR) derived 'metabolite constellation' (GFRNMR). A total of 1855 serum samples were partitioned into development, internal validation and external validation datasets. The new GFRNMR equation used serum myo-inositol, valine, creatinine and cystatin C plus age and sex. GFRNMR had a lower bias to tracer measured GFR (mGFR) than existing eGFR equations, with a median bias (95% confidence interval [CI]) of 0.0 (-1.0; 1.0) mL/min/1.73 m2 for GFRNMR vs. -6.0 (-7.0; -5.0) mL/min/1.73 m2 for the Chronic Kidney Disease Epidemiology Collaboration equation that combines creatinine and cystatin C (CKD-EPI2012) (p < 0.0001). Accuracy (95% CI) within 15% of mGFR (1-P15) was 38.8% (34.3; 42.5) for GFRNMR vs. 47.3% (43.2; 51.5) for CKD-EPI2012 (p < 0.010). Thus, GFRNMR holds promise as an alternative way to assess eGFR with superior accuracy in adult patients with and without CKD.

Integrated Metabolomics and Proteomics Analyses in the Local Milieu of Islet Allografts in Rejection versus Tolerance

An understanding of the immune mechanisms that lead to rejection versus tolerance of allogeneic pancreatic islet grafts is of paramount importance, as it facilitates the development of innovative methods to improve the transplant outcome. Here, we used our established intraocular islet transplant model to gain novel insight into changes in the local metabolome and proteome within the islet allograft’s immediate microenvironment in association with immune-mediated rejection or tolerance. We performed integrated metabolomics and proteomics analyses in aqueous humor samples representative of the graft’s microenvironment under each transplant outcome. The results showed that several free amino acids, small primary amines, and soluble proteins related to the Warburg effect were upregulated or downregulated in association with either outcome. In general, the observed shifts in the local metabolite and protein profiles in association with rejection were consistent with established pro-inflammatory metabolic pathways and those observed in association with tolerance were immune regulatory. Taken together, the current findings further support the potential of metabolic reprogramming of immune cells towards immune regulation through targeted pharmacological and dietary interventions against specific metabolic pathways that promote the Warburg effect to prevent the rejection of transplanted islets and promote their immune tolerance.

Serum Myo-Inositol, Dimethyl Sulfone, and Valine in Combination with Creatinine Allow Accurate Assessment of Renal Insufficiency-A Proof of Concept

Evaluation of renal dysfunction includes estimation of glomerular filtration rate (eGFR) as the initial step and subsequent laboratory testing. We hypothesized that combined analysis of serum creatinine, myo-inositol, dimethyl sulfone, and valine would allow both assessment of renal dysfunction and precise GFR estimation. Bio-banked sera were analyzed using nuclear magnetic resonance spectroscopy (NMR). The metabolites were combined into a metabolite constellation (GFRNMR) using n = 95 training samples and tested in n = 189 independent samples. Tracer-measured GFR (mGFR) served as a reference. GFRNMR was compared to eGFR based on serum creatinine (eGFRCrea and eGFREKFC), cystatin C (eGFRCys-C), and their combination (eGFRCrea-Cys-C) when available. The renal biomarkers provided insights into individual renal and metabolic dysfunction profiles in selected mGFR-matched patients with otherwise homogenous clinical etiology. GFRNMR correlated better with mGFR (Pearson correlation coefficient r = 0.84 vs. 0.79 and 0.80). Overall percentages of eGFR values within 30% of mGFR for GFRNMR matched or exceeded those for eGFRCrea and eGFREKFC (81% vs. 64% and 74%), eGFRCys-C (81% vs. 72%), and eGFRCrea-Cys-C (81% vs. 81%). GFRNMR was independent of patients' age and sex. The metabolite-based NMR approach combined metabolic characterization of renal dysfunction with precise GFR estimation in pediatric and adult patients in a single analytical step.

Urinary oxylipin signature as biomarkers to monitor the allograft function during the first six months post-renal transplantation

Oxylipins such as isoprostanes (IsoPs), prostaglandins (PGs) and thromboxanes (TXs) are lipid mediators derived from the oxidation of polyunsaturated fatty acids, which regulate the magnitude of oxidative stress and inflammation processes and play an important role in pathophysiological processes in the kidney. A total of 36 oxylipins were analyzed by UHPLC-QqQ-MS/MS in the urine of 41 renal recipients from cadaveric donors of the Nephrology Unit of the University Hospital Virgen de la Arrixaca during the first six months after renal transplantation, in order to investigate several candidate oxylipins as more accurate and predictive biomarkers in renal transplantation than classical biological variables. A decrease in nine PGs, mostly from the AA-D pathway (p < 0.05) and one IsoP: 15-keto-15-F_2t-IsoP (p < 0.001) was observed. Moreover, two PGs (2,3-dinor-11β-PGF_2α and 17-trans-PGF_3α) increased between five days and six months after renal transplantation (p < 0.05). In addition, when kidney function improved, a positive correlation between oxylipin levels and the excretion of urine proteins was observed. These results suggest that oxylipins could be useful markers for monitoring renal function in the post-renal transplantation period. These findings could be of utility not only for the development of strategies for long-term preservation of graft function, but also for innovative and alternative therapies -using oxylipins as predictive markers-to avoid organ rejection.

Urinary metabolomic profiling for noninvasive diagnosis of acute T cell-mediated rejection after kidney transplantation

To improve early renal allograft function, it is important to develop a noninvasive diagnostic method for acute T cell-mediated rejection (TCMR). This study aims to explore potential noninvasive urinary biomarkers to screen for acute TCMR in kidney transplant recipients (KTRs) using untargeted metabolomic profiling. Urinary metabolites, collected from KTRs with stable graft function (STA) or acute TCMR episodes, were analyzed using liquid chromatography-mass spectrometry (LC-MS). Multivariate statistical analyses were performed to discriminate differences in urinary metabolites between the two groups. Receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic performance of potential urinary biomarkers. Statistical analysis revealed the differences in urinary metabolites between the two groups and indicated several statistically significant metabolic features suitable for potential biomarkers. By comparing the retention times and mass fragmentation patterns of the chemicals in metabolite databases, samples, and standards, six of these features were clearly identified. ROC curve analysis showed the best performance of the training set (area under the curve value, 0.926; sensitivity, 90.0%; specificity, 84.6%) using a panel of five potential biomarkers: guanidoacetic acid, methylimidazoleacetic acid, dopamine, 4-guanidinobutyric acid, and L-tryptophan. The diagnostic accuracy of this model was 62.5% for an independent test dataset. LC-MS-based untargeted metabolomic profiling is a promising method to discriminate between acute TCMR and STA groups. Our model, based on a panel of five potential biomarkers, needs to be further validated in larger scale studies.

Potential applications of lipid peroxidation products - F4-neuroprostanes, F3-neuroprostanesn-6 DPA, F2-dihomo-isoprostanes and F2-isoprostanes - in the evaluation of the allograft function in renal transplantation

F₄-neuroprostanes, F₃-neuroprostanes_{n-6 DPA}, and F₂-dihomo-isoprostanes, metabolites of non-enzymatic lipid peroxidation of polyunsaturated fatty acids [docosahexaenoic acid, n-6 docosapentanoic acid, and adrenic acid respectively], have become important biomarkers for oxidative stress in several diseases like epilepsy and alzheimer. These biomarkers and the 15-F_2t-isoprostane (also known as 8-iso-PGF_2α)_, a F₂-isoprostane isomer measured as reference oxidative marker at systemic level, were analyzed by UHPLC-QqQ-MS/MS in the urine of 60 renal recipients from cadaveric donors of the Nephrology Unit of the University Hospital Virgen de la Arrixaca, at six different times during the first six months after renal transplantation, and were compared with a control group of 60 healthy subjects from the same hospital. A total of 11 metabolites were analyzed and different patterns were observed. A tendency to decrease was observed in three metabolites (4-epi-4-F_3t- NeuroP_{n-6 DPA}, ent-7(RS)-7-F_2t-dihomo-IsoP, and ent-7(S)-7-F_2t-dihomo-IsoP) and in our reference oxidative marker (15-F_2t-IsoP) when kidney function improved and the excretion of urine proteins decreased. These results suggest that these three biomarkers of oxidative stress could be useful to assess renal function in the postransplant phase. Unfortunately, little is known about this kind of biomarker in this cohort of patients, so further investigation would be required in the clinical field to clarify the relationship between oxidative stress and the graft function, as well as the usefulness of these biomarkers as rejection markers.

Therapeutic Apheresis in Immunologic Renal and Neurological Diseases

Since the mid 1970s, when membrane modules became available, plasma separation techniques have gained in importance especially in the past few years. The advantages of this method are a complete separation of the corpuscular components from the plasma and due to increased blood flow rate and higher efficacy. Systemic autoimmune diseases based on an immune pathogenesis produce autoantibodies and circulating immune complexes, which cause inflammation in the tissues of various organs. In most cases, these diseases have a poor prognosis without treatment. Therapeutic apheresis (TA) in combination with immunosuppressive therapies has led to a steady increase in survival rates over the last 40 years. The updated information on immunology and molecular biology of different immunologic diseases are discussed in relation to the rationale for apheresis therapy and its place in combination with other modern treatments. The different diseases can be treated by various apheresis methods such as therapeutic plasma exchange (TPE) with substitution solution, or with online plasma or blood purification using adsorption columns, which contain biological or non-biological agents. Here, the authors provide an overview of the most important pathogenic aspects indicating that TA can be a supportive therapy in systemic autoimmune diseases such as renal and neurological disorders. For the immunological diseases that can be treated with TA, the guidelines of the German Working Group of Clinical Nephrology and of the Apheresis Committee of the American Society for Apheresis are cited.

Non-invasive approaches in the diagnosis of acute rejection in kidney transplant recipients, part II: omics analyses of urine and blood samples

Kidney transplantation (KTx) represents the best available treatment for patients with end-stage renal disease. Still, the full benefits of KTx are undermined by acute rejection (AR). The diagnosis of AR ultimately relies on transplant needle biopsy. However, such an invasive procedure is associated with a significant risk of complications and is limited by sampling error and interobserver variability. In the present review, we summarize the current literature about non-invasive approaches for the diagnosis of AR in kidney transplant recipients (KTRs), including in vivo imaging, gene-expression profiling and omics analyses of blood and urine samples. Most imaging techniques, such as contrast-enhanced ultrasound and magnetic resonance, exploit the fact that blood flow is significantly lowered in case of AR-induced inflammation. In addition, AR-associated recruitment of activated leucocytes may be detectable by 18F-fluorodeoxyglucose positron emission tomography. In parallel, urine biomarkers, including CXCL9/CXCL10 or a three-gene signature of CD3ε, CXCL10 and 18S RNA levels, have been identified. None of these approaches has yet been adopted in the clinical follow-up of KTRs, but standardization of analysis procedures may help assess reproducibility and comparative diagnostic yield in large, prospective, multicentre trials.

Molecular phenotyping of a UK population: defining the human serum metabolome

Phenotyping of 1,200 'healthy' adults from the UK has been performed through the investigation of diverse classes of hydrophilic and lipophilic metabolites present in serum by applying a series of chromatography-mass spectrometry platforms. These data were made robust to instrumental drift by numerical correction; this was prerequisite to allow detection of subtle metabolic differences. The variation in observed metabolite relative concentrations between the 1,200 subjects ranged from less than 5 % to more than 200 %. Variations in metabolites could be related to differences in gender, age, BMI, blood pressure, and smoking. Investigations suggest that a sample size of 600 subjects is both necessary and sufficient for robust analysis of these data. Overall, this is a large scale and non-targeted chromatographic MS-based metabolomics study, using samples from over 1,000 individuals, to provide a comprehensive measurement of their serum metabolomes. This work provides an important baseline or reference dataset for understanding the 'normal' relative concentrations and variation in the human serum metabolome. These may be related to our increasing knowledge of the human metabolic network map. Information on the Husermet study is available at http://www.husermet.org/. Importantly, all of the data are made freely available at MetaboLights (http://www.ebi.ac.uk/metabolights/).

Plasma metabolomic profiling of dairy cows affected with ketosis using gas chromatography/mass spectrometry

Background

Ketosis is an important problem for dairy cows` production performance. However, it is still little known about plasma metabolomics details of dairy ketosis.

Results

A gas chromatography/mass spectrometry (GC/MS) technique was used to investigate plasma metabolic differences in cows that had clinical ketosis (CK, n=22), subclinical ketosis (SK, n=32), or were clinically normal controls (NC, n=22). The endogenous plasma metabolome was measured by chemical derivatization followed by GC/MS, which led to the detection of 267 variables. A two-sample t-test of 30, 32, and 13 metabolites showed statistically significant differences between SK and NC, CK and NC, and CK and SK, respectively. Orthogonal signal correction-partial least-square discriminant analysis (OPLS-DA) revealed that the metabolic patterns of both CK and SK were mostly similar, with the exception of a few differences. The development of CK and SK involved disturbances in many metabolic pathways, mainly including fatty acid metabolism, amino acid metabolism, glycolysis, gluconeogenesis, and the pentose phosphate pathway. A diagnostic model arbitrary two groups was constructed using OPLS-DA and receiver–operator characteristic curves (ROC). Multivariate statistical diagnostics yielded the 19 potential biomarkers for SK and NC, 31 for CK and NC, and 8 for CK and SK with area under the curve (AUC) values. Our results showed the potential biomarkers from CK, SK, and NC, including carbohydrates, fatty acids, amino acids, even sitosterol and vitamin E isomers, etc. 2-piperidinecarboxylic acid and cis-9-hexadecenoic acid were closely associated with metabolic perturbations in ketosis as Glc, BHBA and NEFA for dealing with metabolic disturbances of ketosis in clinical practice. However, further research is needed to explain changes of 2,3,4-trihydroxybutyric acid, 3,4-dihydroxybutyric acid, α-aminobutyric acid, methylmalonic acid, sitosterol and α-tocopherol in CK and SK, and to reveal differences between CK and SK.

Conclusion

Our study shows that some new biomarkers of ketosis from plasma may find new metabolic changes to have clinically new utility and significance in diagnosis, prognosis, and prevention of ketosis in the future.

Metabonomics study of the acute graft rejection in rat renal transplantation using reversed-phase liquid chromatography and hydrophilic interaction chromatography coupled with mass spectrometry

Acute graft rejection is one of the most common and serious post complications in renal transplantation, noninvasive diagnosis of acute graft rejection is essential for reducing risk of surgery and timely treatment. In this study, a non-targeted metabonomics approach based on ultra performance liquid chromatography (UPLC) coupled with quadrupole time-of-flight mass spectrometry (MS) is used to investigate the effect of acute graft rejection in rat renal transplantation on metabolism. To collect more metabolite information both hydrophilic interaction chromatography and reversed-phase liquid chromatography were used. Using the partial least squares-discriminant analysis, we found that the change of metabonome in a sham-operated group and a non-graft rejection group had a similar trend, while that of the acute graft rejection group was clearly different. Several discriminating metabolites of the acute graft rejection were identified, including creatinine, phosphatidyl-cholines, lyso-phosphatidylcholines, carnitine C16:0, free fatty acids and indoxyl sulfate etc. These discriminating metabolites suggested that acute graft rejection in renal transplantation can lead to the accumulation of creatinine in the body, and also the abnormal metabolism of phospholipids. These findings are useful to understand the mechanisms of the rejection, it also means that a UPLC-MS metabonomic approach is a suitable tool to investigate the metabolic abnormality in the acute graft rejection in renal transplantation.

Biological responses to perfluorododecanoic acid exposure in rat kidneys as determined by integrated proteomic and metabonomic studies

Background

Perfluorododecanoic acid (PFDoA) is a perfluorinated carboxylic chemical (PFC) that has broad applications and distribution in the environment. While many studies have focused on hepatotoxicity, immunotoxicity, and reproductive toxicity of PFCAs, few have investigated renal toxicity.

Methodology/Principal Findings

Here, we used comparative proteomic and metabonomic technologies to provide a global perspective on renal response to PFDoA. Male rats were exposed to 0, 0.05, 0.2, and 0.5 mg/kg/day of PFDoA for 110 days. After 2-D DIGE and MALDI TOF/TOF analysis, 79 differentially expressed proteins between the control and the PFDoA treated rats (0.2 and 0.5 mg-dosed groups) were successfully identified. These proteins were mainly involved in amino acid metabolism, the tricarboxylic acid cycle, gluconeogenesis, glycolysis, electron transport, and stress response. Nuclear magnetic resonance-based metabonomic analysis showed an increase in pyruvate, lactate, acetate, choline, and a variety of amino acids in the highest dose group. Furthermore, the profiles of free amino acids in the PFDoA treated groups were investigated quantitatively by high-coverage quantitative iTRAQ-LC MS/MS, which showed levels of sarcosine, asparagine, histidine, 1-methylhistidine, Ile, Leu, Val, Trp, Tyr, Phe, Cys, and Met increased markedly in the 0.5 mg dosed group, while homocitrulline, α-aminoadipic acid, β-alanine, and cystathionine decreased.

Conclusion/Significance

These observations provide evidence that disorders in glucose and amino acid metabolism may contribute to PFDoA nephrotoxicity. Additionally, α_2u globulin may play an important role in protecting the kidneys from PFDoA toxicity.

Gas chromatography-mass spectrometric method for metabolic profiling of tobacco leaves

A gas chromatography-mass spectrometric method was developed for profiling of tobacco leaves. The differentiation among tobacco leaves planted in two different regions was investigated. Prior to analysis, the extraction solvent formulation was optimized and a combination of water, methanol and acetonitrile with a volume ratio of 3:1:1 was found to be optimal. The reproducibility of the method was satisfactory. Kendall tau-b rank correlation coefficients were equal to 1 (p<0.05) for 82% of the resolved peaks (up to 95% of the overall peak areas), indicating the good response correlation. Forty-four compounds including 9 saccharides, 9 alcohols, 9 amino acids, 16 organic acids and phosphoric acid were identified based on standard compounds. The method was successfully applied for profiling of tobacco leaves from Zimbabwe and Yunnan of China. Our result revealed that levels of saccharides and their derivatives including xylose, ribose, fructose, glucose, turanose, xylitol and glyceric acid were more abundant while sucrose, glucitol and D-gluconic acid were less abundant in tobacco leaves from Yunnan as compared to those from Zimbabwe. Amino acids such as L-alanine, L-tyrosine and L-threonine were found to be richer in Zimbabwe tobacco than in Yunnan tobacco.

Dialysis modality-dependent changes in serum metabolites: accumulation of inosine and hypoxanthine in patients on haemodialysis

BACKGROUND

The body metabolism of patients with end-stage renal disease may be altered in response to long-term dialysis treatment. Moreover, the pattern of serum metabolites could change depending on the type of dialysis modality used. However, dialysis modality-dependent changes in serum metabolites are poorly understood. Our aim was to profile comprehensively serum metabolites by exploiting a novel method of (1)H-NMR-based metabonomics and identify the differences in metabolite patterns in subjects receiving haemodialysis (HD) and peritoneal dialysis (PD).

METHODS

Anuric and non-diabetic HD patients were matched to PD patients for age, sex and dialysis duration. Accurate concentrations of serum metabolites were determined using the target-profiling procedure, and differences in the levels of metabolites were compared using multivariate analysis.

RESULTS

Principal Components Analysis score plots showed that the metabolic patterns could be discriminated by dialysis modalities. Hypoxanthine and inosine were present only with HD, whereas serum xanthine oxidase activity and uric acid levels were not different. In contrast, PD was associated with higher levels of lactate, glucose, maltose, pyruvate, succinate, alanine, and glutamate linked to glucose metabolism and the tri-carboxylic acid cycle. Maltose appeared only in patients using icodextrin solution for PD. Known uraemic retention solutes such as urea, creatinine, myo-inositol and trimethylamine-N-oxide were increased in both dialysis groups.

CONCLUSIONS

Metabonomics shows apparent differences in the profiles of serum metabolites between HD and PD, which were influenced by dialysis-related processes. Inosine and hypoxanthine are present only in HD patients, which is likely to represent more hypoxic and oxidative stress.

Application of metabolomics to investigate the process of human orthotopic liver transplantation: a proof-of-principle study

To improve the outcome of orthotopic liver transplantation (OLT), knowledge of early molecular events occurring upon ischemia/reperfusion is essential. Powerful approaches for profiling metabolic changes in tissues and biofluids are now available. Our objective was to investigate the applicability of two technologies to a small but well-defined cohort of patients undergoing OLT: consecutive liver biopsies by Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) and microdialysates of extracellular fluid by coulometric electrochemical array detection (CEAD). FT-ICR MS detected reproducibly more than 4,000 peaks, revealing hundreds of significant metabolic differences between pre- and postreperfusion grafts. These included increased urea production, bile acid synthesis and clearance of preservation solution upon reperfusion, indicating a rapid resumption of biochemical function within the graft. FT-ICR MS also identified successfully the only graft obtained by donation-after-cardiac-death as a "metabolic outlier." CEAD time-profile analysis showed that there was considerable change in redox-active metabolites (up to 18 h postreperfusion), followed by their stabilization. Collectively these results verify the applicability of FT-ICR MS and CEAD for characterizing multiple metabolic pathways during OLT. The success of this proof-of-principle application of these technologies to a clinical setting, considering the potential metabolic heterogeneity across only eight donor livers, is encouraging.

Extraction of pure components from overlapped signals in gas chromatography-mass spectrometry (GC-MS)

Gas chromatography-mass spectrometry (GC-MS) is a widely used analytical technique for the identification and quantification of trace chemicals in complex mixtures. When complex samples are analyzed by GC-MS it is common to observe co-elution of two or more components, resulting in an overlap of signal peaks observed in the total ion chromatogram. In such situations manual signal analysis is often the most reliable means for the extraction of pure component signals; however, a systematic manual analysis over a number of samples is both tedious and prone to error. In the past 30 years a number of computational approaches were proposed to assist in the process of the extraction of pure signals from co-eluting GC-MS components. This includes empirical methods, comparison with library spectra, eigenvalue analysis, regression and others. However, to date no approach has been recognized as best, nor accepted as standard. This situation hampers general GC-MS capabilities, and in particular has implications for the development of robust, high-throughput GC-MS analytical protocols required in metabolic profiling and biomarker discovery. Here we first discuss the nature of GC-MS data, and then review some of the approaches proposed for the extraction of pure signals from co-eluting components. We summarize and classify different approaches to this problem, and examine why so many approaches proposed in the past have failed to live up to their full promise. Finally, we give some thoughts on the future developments in this field, and suggest that the progress in general computing capabilities attained in the past two decades has opened new horizons for tackling this important problem.

Measurement of glucose and fructose in clinical samples using gas chromatography/mass spectrometry

OBJECTIVE

The impact of increased fructose consumption on carbohydrate metabolism is a topic of current interest, but determination of serum level has been hindered due to low concentration and interference from serum glucose. We are reporting a method for the quantification of glucose and fructose in clinical samples using gas chromatography/mass spectrometry (GC/MS). The accuracy and precision of GC/MS and an enzymatic assay were compared.

DESIGN AND METHODS

Mass spectrometry fragmentation patterns of methyloxime peracetate derivatized aldose and ketose were determined. Unique fragments for glucose and fructose were used for quantitative analysis using isotope labeled recovery standards.

RESULTS

Methyloxime peracetate derivatives of glucose and fructose showed characteristic loss of acetate (M-60) or ketene (M-42) under chemical ionization (CI). Under electron impact (EI) ionization, a unique C1-C2 fragment of glucose was formed, while a C1-C3 fragment was formed from keto-hexoses. These unique fragments were used in the quantitative assay of glucose and fructose in clinical samples. In clinical samples, the GC/MS assay has a lower limit of detection than that of the enzymatic assay. In plasma samples from patients evaluated for diabetes the average serum glucose and fructose were 6.19+/-2.72 mM and 46+/- 25.22 microM. Fructose concentrations in many of these samples were below the limit of detection of the enzymatic method.

CONCLUSION

Derivatization of aldose and ketose monosaccharides to their respective O-methyloxime acetates for GC/MS analysis is a facile method for determination of serum/plasma glucose and fructose samples.