Hydrophilic interaction and reversed-phase ultraperformance liquid chromatography TOF-MS for serum metabonomic analysis of myocardial infarction in rats and its applications

An ultra performance liquid chromatography coupled to mass spectrometry-based metabonomic approach, which utilizes both reversed-performance (RP) chromatography and hydrophilic interaction chromatography (HILIC) separations, has been developed to characterize the global serum metabolic profile associated with myocardial infarction (MI). The HILIC was found necessary for a comprehensive serum metabonomic profiling, providing complementary information to RP chromatography. By combining with partial least squares discriminant analysis, 21 potential biomarkers in rat serum were identified. To further elucidate the pathophysiology of MI, related metabolic pathways have been studied. It was found that MI was closely related to disturbed sphingolipid metabolism, phospholipid catabolism, fatty acid transportation and metabolism, tryptophan metabolism, branched-chain amino acids metabolism, phenylalanine metabolism, and arginine and proline metabolism. With the presented metabonomic method, we systematically analyzed the therapeutic effects of Traditional Chinese Medicine Sini decoction (SND). The results demonstrated that SND administration could provide satisfactory effects on MI through partially regulating the perturbed metabolic pathways.     

Comprehensive peptidome analysis of mouse livers by size exclusion chromatography prefractionation and nanoLC-MS/MS identification

Peptidome analysis has received increasing attention in recent years. Cancer diagnosis by serum peptidome has also been reported by peptides' profiling for discovery of peptide biomarkers. Tissue, which may have a higher biomarker concentration than blood, has not been investigated extensively by means of peptidome analysis. Here, a method for the peptidome analysis of mouse liver was developed by the combination of size exclusion chromatography (SEC) prefractionation with nano-liquid chromatography-tamdem mass spectrometry (nanoLC-MS/MS) analysis. The extracted peptides from mouse liver were separated according to their molecular weight using a size exclusion column. MALDI-TOF MS was used to characterize the molecular weight distribution of the peptides in fractions eluted from the SEC column. The low molecular weight (LMW) (MW < 3000 Da) peptides in the collected fractions were directly analyzed by LC-MS/MS which resulted in the identification of 1181 unique peptides (from 371 proteins). The high molecular weight (HMW) (MW > 3000 Da) peptides in the early two fractions from the SEC column were first digested with trypsin, and the resulted digests were then analyzed by LC-MS/MS, which led to the identification of 123 and 127 progenitor proteins of the HMW peptides in fractions 1 and 2, respectively. Analysis of the peptides' cleavage sites showed that the peptides are cleaved in regulation, which may reflect the protease activity and distribution in body, and also represent the biological state of the tissue and provide a fresh source for biomarker discovery.     

LC-MS-based serum metabolic profiling for genitourinary cancer classification and cancer type-specific biomarker discovery

Bladder cancer (BC) and kidney cancer (KC) are the first two commonly occurring genitourinary cancers in China. In this study, a comprehensive LC-MS-based method, which utilizes both reversed phase liquid chromatography (RPLC) and hydrophilic interaction chromatography (HILIC) separations, has been carried out in conjunction with multivariate data analysis to discriminate the global serum profiles of BC, KC, and noncancer controls. An independent test set consisting of different patients has been used to objectively evaluate the predictive ability of the analysis platform. Excellent sensitivity and specificity have been achieved in detection of KC and BC. The results suggest that serum metabolic profiling could be used for different types of genitourinary cancer diagnosis. Furthermore, cancer type-specific biomarkers were found through a critical selection criterion. As a result, eicosatrienol, azaprostanoic acid, docosatrienol, retinol, and 14'-apo-beta-carotenal were found as specific biomarkers for BC; and PE(P-16:0e/0:0), glycerophosphorylcholine, ganglioside GM3 (d18:1/22:1), C17 sphinganine, and SM(d18:0/16:1(9Z)) were found as specific biomarkers for KC. Receiver operating characteristic (ROC) analysis was used for the preliminary evaluation of the biomarkers. These biomarkers have great potential to be used in the clinical diagnosis after further rigorous assessment.     

Identification of Protein Markers Specific for Papillary Renal Cell Carcinoma Using Imaging Mass Spectrometry

Since the emergence of proteomics methods, many proteins specific for renal cell carcinoma (RCC) have been identified. Despite their usefulness for the specific diagnosis of RCC, such proteins do not provide spatial information on the diseased tissue. Therefore, the identification of cancer-specific proteins that include information on their specific location is needed. Recently, matrix-assisted laser desorption ionization (MALDI) mass spectrometry (MS) based imaging mass spectrometry (IMS) has emerged as a new tool for the analysis of spatial distribution as well as identification of either proteins or small molecules in tissues. In this report, surgical tissue sections of papillary RCC were analyzed using MALDI-IMS. Statistical analysis revealed several discriminative cancer-specific m/z-species between normal and diseased tissues. Among these m/z-species, two particular proteins, S100A11 and ferritin light chain, which are specific for papillary RCC cancer regions, were successfully identified using LC-MS/MS following protein extraction from independent RCC samples. The expressions of S100A11 and ferritin light chain were further validated by immunohistochemistry of human tissues and tissue microarrays (TMAs) of RCC. In conclusion, MALDI-IMS followed by LC-MS/MS analysis in human tissue identified that S100A11 and ferritin light chain are differentially expressed proteins in papillary RCC cancer regions.     

A platform for accurate mass and time analyses of mass spectrometry data

We describe an integrated suite of algorithms and software for general accurate mass and time (AMT) tagging data analysis of mass spectrometry data. The AMT approach combines identifications from liquid chromatography (LC) tandem mass spectrometry (MS/MS) data with peptide accurate mass and retention time locations from high-resolution LC-MS data. Our workflow includes the traditional AMT approach, in which MS/MS identifications are located in external databases, as well as methods based on more recent hybrid instruments such as the LTQ-FT or Orbitrap, where MS/MS identifications are embedded with the MS data. We demonstrate our AMT workflow's utility for general data synthesis by combining data from two dissimilar biospecimens. Specifically, we demonstrate its use relevant to serum biomarker discovery by identifying which peptides sequenced by MS/MS analysis of tumor tissue may also be present in the plasma of tumor-bearing and control mice. The analysis workflow, referred to as msInspect/AMT, extends and combines existing open-source platforms for LC-MS/MS (CPAS) and LC-MS (msInspect) data analysis and is available in an unrestricted open-source distribution.     

Quantitative determination of cyclic polylactic acid oligomers in serum by direct injection liquid chromatography tandem mass spectrometry

Polylactic acid (PLA) is a biodegradable polymer, currently used in pharmaceutical and surgical devices. There is a concern that cyclic polylactic acid (CPLA), which is a by-product of PLA synthesis, may be introduced into the human body as an undesirable contaminant. We carried out a quantitation investigation of the CPLA heptamer (CPLA-7) by liquid chromatography mass spectrometry (LC-MS). We found that CPLA-7 binds strongly with serum proteins and that only 62% of CPLA-7 was recovered after routine deproteination; therefore, we directly injected serum into the LC-MS/MS system after passage through a bovine serum albumin (BSA)-coated chromatographic column and found the recovery of CPLA-7 was improved to 84%, and that the detection (S/N=3) and quantitation limit (S/N=10 and below 15% relative standard deviation) were 1.5 and 2.5 ng/mL, respectively. We conclude that direct injection LC-MS/MS, using a BSA column, is a simple and effective quantitative analysis method for CPLA in serum.     

Application of Holistic Liquid Chromatography-High Resolution Mass Spectrometry Based Urinary Metabolomics for Prostate Cancer Detection and Biomarker Discovery

Human exhibit wide variations in their metabolic profiles because of differences in genetic factors, diet and lifestyle. Therefore in order to detect metabolic differences between individuals robust analytical methods are required. A protocol was produced based on the use of Liquid Chromatography- High Resolution Mass Spectrometry (LC-HRMS) in combination with orthogonal Hydrophilic Interaction (HILIC) and Reversed Phase (RP) liquid chromatography methods for the analysis of the urinary metabolome, which was then evaluated as a diagnostic tool for prostate cancer (a common but highly heterogeneous condition). The LC-HRMS method was found to be robust and exhibited excellent repeatability for retention times (<±1%), and mass accuracy (<±1 ppm). Based on normalised data (against creatinine levels, osmolality or MS total useful signals/MSTUS) coupled with supervised multivariate analysis using Orthogonal Partial Least Square-Discriminant Analysis (OPLS-DA), we were able to discriminate urine samples from men with or without prostate cancer with R2Y(cum) >0.9. In addition, using the receiver operator characteristics (ROC) test, the area under curve (AUC) for the combination of the four best characterised biomarker compounds was 0.896. The four biomarker compounds were also found to differ significantly (P<0.05) between an independent patient cohort and controls. This is the first time such a rigorous test has been applied to this type of model. If validated, the established protocol provides a robust approach with a potentially wide application to metabolite profiling of human biofluids in health and disease.     

Candidate biomarkers in renal cell carcinoma

Although the human genome has been decoded, the knowledge about the pathogenesis of diseases including cancer is still limited. By focusing on renal cell carcinoma (RCC) we here summarize the data of various research groups analyzing the protein/peptide expression profiles of tumor lesions/cell lines or serum obtained from patients and respective controls. Different powerful approaches such as 2-DE, PROTEOMEX/SERPA/SPEARS, and T cell epitope discovery upon elution of MHC class I-bound peptides in combination with MS/LC-MS/MS revealed 500 differentially expressed proteins. The overlap in target recognition limits the pool to 299 unique protein identities, but only few thereof (12%) have been validated. The management, analysis, and interpretation of the distinct data sets derived from 27 publications required bioinformatic restructuring of the results. However, the comprehensive analysis of the results expands the knowledge about the pathophysiology of RCC in particular of the most prominent clear cell subtype by providing information on the differentially expressed proteins, their regulation status in RCC compared to normal kidney epithelium next to additional information on MHC-presented T cell epitopes and on serological targets. Despite the low number of validated differentially expressed proteins some of them might serve as candidate biomarkers for the diagnosis and/or as therapeutic targets.     

Automated, fast and sensitive quantification of 17 alpha-hydroxy-progesterone, androstenedione and testosterone by tandem mass spectrometry with on-line extraction

Plasma 17 alpha-hydroxyprogesterone (17-OHP), androstenedione and testosterone measurements are important for the diagnosis and monitoring of hyperandrogenic disorders, most importantly for congenital adrenal hyperplasia (CAH) due to 21-hydroxylase deficiency. The reliability of immunoassays has proved questionable especially for newborns and children. In order to reduce the analytical interferences due to cross-reactivity or matrix effects, to improve accuracy and shorten the analysis time, we have developed a liquid chromatography-tandem mass spectrometry (LC-MS/MS) method with atmospheric pressure chemical ionization (APCI) for simultaneous measurement. An on-line extraction cartridge with column-switching technique and liquid chromatography over a Chromolith RP 18 e column allow a rapid and easy quantification. The lowest limit of detection was 0.03-0.06 microg/L. Our method has proved linear up to 250 microg/L (r=0.999). Recoveries (S.D.) of 17-OHP, androstenedione and testosterone in plasma were 100% (5), 102% (2) and 92% (4), respectively. The regression equation for the LC-MS/MS (x) and immunoassay (y) methods for 17-OHP (excluding neonate samples) was y=1.942 x+0.255 nmol/L (r=0.695; n=97). In comparison to our values, the immunoassay generally overestimates steroid concentration. The regression equation for the LC-MS/MS (x) and immunoassay (y) methods for testosterone was y=0.963 x+0.035 nmol/L (r=0.955; n=107). Preliminary reference intervals for children were determined as a function of age and sex. The sensitivity and specificity of the LC-MS/MS method offer advantages over routine immunoassays due to the elimination of interferences especially for newborns, high throughput and short chromatographic run time.     

Plasma fatty acid metabolic profiling and biomarkers of type 2 diabetes mellitus based on GC/MS and PLS-LDA

Metabolic profiling has increasingly been used as a probe in disease diagnosis and pharmacological analysis. Herein, plasma fatty acid metabolic profiling including non-esterified fatty acid (NEFA) and esterified fatty acid (EFA) was investigated using gas chromatography/mass spectrometry (GC/MS) followed by multivariate statistical analysis. Partial least squares-linear discrimination analysis (PLS-LDA) model was established and validated to pattern discrimination between type 2 diabetic mellitus (DM-2) patients and health controls, and to extract novel biomarker information. Furthermore, the PLS-LDA model visually represented the alterations of NEFA metabolic profiles of diabetic patients with abdominal obesity in the treated process with rosiglitazone. The GC/MS-PLS-LDA analysis allowed comprehensive detection of plasma fatty acid, enabling fatty acid metabolic characterization of DM-2 patients, which included biomarkers different from health controls and dynamic change of NEFA profiles of patients after treated with medicine. This method might be a complement or an alternative to pathogenesis and pharmacodynamics research.     

A large-scale assay library for targeted protein quantification in renal cell carcinoma tissues

Renal cell carcinoma (RCC) represents 2.2% of all cancer incidences; however, prognostic or predictive RCC biomarkers at protein level are largely missing. To support proteomics research of localized and metastatic RCC, we introduce a new library of targeted mass spectrometry assays for accurate protein quantification in malignant and normal kidney tissue. Aliquots of 86 initially localized RCC, 75 metastatic RCC and 17 adjacent non-cancerous fresh frozen tissue lysates were trypsin digested, pooled, and fractionated using hydrophilic chromatography. The fractions were analyzed using LC-MS/MS on QExactive HF-X mass spectrometer in data-dependent acquisition (DDA) mode. A resulting spectral library contains 77,817 peptides representing 7960 protein groups (FDR = 1%). Further, we confirm applicability of this library on four RCC datasets measured in data-independent acquisition (DIA) mode, demonstrating a specific quantification of a substantially increased part of RCC proteome, depending on LC-MS/MS instrumentation. Impact of sample specificity of the library on the results of targeted DIA data extraction was demonstrated by parallel analyses of two datasets by two pan human libraries. The new RCC specific library has potential to contribute to better understanding the RCC development at molecular level, leading to new diagnostic and therapeutic targets.     

Collisional fragmentation of central carbon metabolites in LC-MS/MS increases precision of ¹³C metabolic flux analysis

Experimental determination of fluxes by (13)C-tracers relies on detection of (13)C-patterns in metabolites or by-products. In the field of (13)C metabolic flux analysis, the most recent developments point toward recording labeling patterns by liquid chromatography (LC)-mass spectrometry (MS)/MS directly in intermediates in central carbon metabolism (CCM) to increase temporal resolution. Surprisingly, the flux studies published so far with LC-MS measurements were based on intact metabolic intermediates-thus neglected the potential benefits of using positional information to improve flux estimation. For the first time, we exploit collisional fragmentation to obtain more fine-grained (13)C-data on intermediates of CCM and investigate their impact in (13)C metabolic flux analysis. For the case study of Bacillus subtilis grown in mineral medium with (13)C-labeled glucose, we compare the flux estimates obtained by iterative isotopologue balancing of (13)C-data obtained either by LC-MS/MS for solely intact intermediates or LC-MS/MS for intact and fragmented intermediates of CCM. We show that with LC-MS/MS data, fragment information leads to more precise estimates of fluxes in pentose phosphate pathway, glycolysis, and to the tricarboxylic acid cycle. Additionally, we present an efficient analytical strategy to rapidly acquire large sets of (13)C-patterns by tandem MS, and an in-depth analysis of the collisional fragmentation of primary intermediates. In the future, this catalogue will enable comprehensive in silico calculability analyses to identify the most sensitive measurements and direct experimental design.     

Quantification of 3-deazaneplanocin A, a novel epigenetic anticancer agent, in rat biosamples by hydrophilic interaction liquid chromatography-tandem mass spectrometric detection

A sensitive and selective LC-MS/MS based bioanalytical method was developed and validated for the quantification of 3-deazaneplanocin A (DZNep), a novel epigenetic anti-tumor drug candidate, in Sprague-Dawley (SD) rat biosamples (plasma, urine, feces and tissue samples). The method comprises a phenylboronic acid (PBA)-containing solid phase extraction procedure, serving for binding and clean-up of DZNep in rat biosamples spiked with tubercidin (as internal standard). The analytes were separated on an Agilent hydrophilic interaction chromatography (HILIC) column. LC-MS/MS in positive ion mode was used to perform multiple reaction monitoring at m/z of 263/135 and 267/135 for DZNep and tubercidin, respectively. The limit of quantification (LOQ) of DZNep in rat biosamples was 20 ng/mL. The data of intra-day and inter-day accuracy were within 15% of nominal concentration while the precision (relative standard deviation) less than 10% for all biosamples. The extraction recoveries for DZNep and tubercidin were consistent and reproducible (around 80%) and the matrix effects were negligible (around 10% suppression) in all biosamples. This method was demonstrated to be applicable for pharmacokinetic studies of DZNep in SD rats.     

A comprehensive peptidome profiling technology for the identification of early detection biomarkers for lung adenocarcinoma

The mass spectrometry-based peptidomics approaches have proven its usefulness in several areas such as the discovery of physiologically active peptides or biomarker candidates derived from various biological fluids including blood and cerebrospinal fluid. However, to identify biomarkers that are reproducible and clinically applicable, development of a novel technology, which enables rapid, sensitive, and quantitative analysis using hundreds of clinical specimens, has been eagerly awaited. Here we report an integrative peptidomic approach for identification of lung cancer-specific serum peptide biomarkers. It is based on the one-step effective enrichment of peptidome fractions (molecular weight of 1,000-5,000) with size exclusion chromatography in combination with the precise label-free quantification analysis of nano-LC/MS/MS data set using Expressionist proteome server platform. We applied this method to 92 serum samples well-managed with our SOP (standard operating procedure) (30 healthy controls and 62 lung adenocarcinoma patients), and quantitatively assessed the detected 3,537 peptide signals. Among them, 118 peptides showed significantly altered serum levels between the control and lung cancer groups (p<0.01 and fold change >5.0). Subsequently we identified peptide sequences by MS/MS analysis and further assessed the reproducibility of Expressionist-based quantification results and their diagnostic powers by MRM-based relative-quantification analysis for 96 independently prepared serum samples and found that APOA4 273-283, FIBA 5-16, and LBN 306-313 should be clinically useful biomarkers for both early detection and tumor staging of lung cancer. Our peptidome profiling technology can provide simple, high-throughput, and reliable quantification of a large number of clinical samples, which is applicable for diverse peptidome-targeting biomarker discoveries using any types of biological specimens.     

Detection of new exemestane metabolites by liquid chromatography interfaced to electrospray-tandem mass spectrometry

Exemestane is an irreversible aromatase inhibitor used for anticancer therapy. Unfortunately, this drug is also misused in sports to avoid some adverse effects caused by steroids administration. For this reason exemestane has been included in World Anti-Doping Agency prohibited list. Usually, doping control laboratories monitor prohibited substances through their metabolites, because parent compounds are readily metabolized. Thus metabolism studies of these substances are very important. Metabolism of exemestane in humans is not clearly reported and this drug is detected indirectly through analysis of its only known metabolite: 17β-hydroxyexemestane using liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) and gas chromatography coupled to mass spectrometry (GC-MS). This drug is extensively metabolized to several unknown oxidized metabolites. For this purpose LC-MS/MS has been used to propose new urinary exemestane metabolites, mainly oxidized in C6-exomethylene and simultaneously reduced in 17-keto group. Urine samples from four volunteers obtained after administration of a 25mg dose of exemestane were analyzed separately by LC-MS/MS. Urine samples of each volunteer were hydrolyzed followed by liquid-liquid extraction and injected into a LC-MS/MS system. Three unreported metabolites were detected in all urine samples by LC-MS/MS. The postulated structures of the detected metabolites were based on molecular formulae composition obtained through high accuracy mass determination by liquid chromatography coupled to hybrid quadrupole-time of flight mass spectrometry (LC-QTOF MS) (all mass errors below 2ppm), electrospray (ESI) product ion spectra and chromatographic behavior.     

Identification of membrane proteins from mammalian cell/tissue using methanol-facilitated solubilization and tryptic digestion coupled with 2D-LC-MS/MS

The core prerequisites for an efficient proteome-scale analysis of mammalian membrane proteins are effective isolation, solubilization, digestion and multidimensional liquid chromatography-tandem mass spectrometry (LC-MS/MS). This protocol is for analysis of the mammalian membrane proteome that relies on solubilization and tryptic digestion of membrane proteins in a buffer containing 60% (vol/vol) methanol. Tryptic digestion is followed by strong cation exchange (SCX) chromatography and reversed phase (RP) chromatography coupled online with MS/MS for protein identification. The use of a methanol-based buffer eliminates the need for reagents that interfere with chromatographic resolution and ionization of the peptides (e.g., detergents, chaotropes, inorganic salts). Sample losses are minimized because solubilization and digestion are carried out in a single tube avoiding any sample transfer or buffer exchange between these steps. This protocol is compatible with stable isotope labeling at the protein and peptide level, enabling identification and quantitation of integral membrane proteins. The entire procedure--beginning with isolated membrane fraction and finishing with MS data acquisition--takes 4-5 d.     

Metabolomics-Based Discovery of Diagnostic Biomarkers for Onchocerciasis

Background

Development of robust, sensitive, and reproducible diagnostic tests for understanding the epidemiology of neglected tropical diseases is an integral aspect of the success of worldwide control and elimination programs. In the treatment of onchocerciasis, clinical diagnostics that can function in an elimination scenario are non-existent and desperately needed. Due to its sensitivity and quantitative reproducibility, liquid chromatography-mass spectrometry (LC-MS) based metabolomics is a powerful approach to this problem.

Methodology/Principal Findings

Analysis of an African sample set comprised of 73 serum and plasma samples revealed a set of 14 biomarkers that showed excellent discrimination between Onchocerca volvulus–positive and negative individuals by multivariate statistical analysis. Application of this biomarker set to an additional sample set from onchocerciasis endemic areas where long-term ivermectin treatment has been successful revealed that the biomarker set may also distinguish individuals with worms of compromised viability from those with active infection. Machine learning extended the utility of the biomarker set from a complex multivariate analysis to a binary format applicable for adaptation to a field-based diagnostic, validating the use of complex data mining tools applied to infectious disease biomarker discovery and diagnostic development.

Conclusions/Significance

An LC-MS metabolomics-based diagnostic has the potential to monitor the progression of onchocerciasis in both endemic and non-endemic geographic areas, as well as provide an essential tool to multinational programs in the ongoing fight against this neglected tropical disease. Ultimately this technology can be expanded for the diagnosis of other filarial and/or neglected tropical diseases.     

Metabolite targeting: development of a comprehensive targeted metabolomics platform for the assessment of diabetes and its complications

Biomarker studies for metabolic disorders like diabetes mellitus (DM) are an important approach towards a better understanding of the underlying pathophysiological mechanisms of diseases (Roberts and Gerszten in Cell Metab 18:43–50, 2013; Wilson et al. in Proteome Res 4:591–598, 2005). Furthermore, screening of potential metabolic biomarkers opens the opportunity of early diagnosis as well as therapy and drug monitoring of metabolic disorders (Rhee et al. in J Clin Invest 10:1–10, 2011; Wang et al. in Nat Med 17:448–458, 2011; Wenk in Nat Rev Drug Discov 4:594–610, 2005). The aim of the present study was to develop methods for the quantitative determination of 74 potential metabolite biomarkers for DM and diabetic nephropathy (DN) in serum. Several studies have shown that the concentrations of many polar metabolites like amino or organic acids are changed in subjects suffering from diabetes (Wang et al. in Nat Med 17:448–458, 2011; Yuan et al. in J Chromatogr B 813:53–58, 2007). Analyzing polar analytes presents a challenge in liquid chromatography (LC) coupled with ESI–MS/MS (Gika et al. in J Sep Sci 31:1598–1608, 2008; Spagou et al. in J Sep Sci 33:716–727, 2010). Considering those reasons we decided to develop a specific HILIC–ESI–QqQ–MS/MS-method for quantitative determination of these polar metabolites. A subsequent method validation was carried out for both HILIC and RP chromatography with respect to the guidelines of the Food and Drug Administration (FDA in Food and Drug Administration: Guidance for industry, bioanalytical method validation, 2001). The HILIC and RP LC–MS methods were successfully validated. Furthermore, the HILIC method presented here was applied to serum samples of GIPR^dn transgenic mice, a diabetic strain developing DN, and non transgenic littermate controls. Significant, diabetes-associated changes were observed for the concentrations of 21 out of 62 metabolites. The new methods described here accurately quantify 74 metabolites known to be regulated in diabetes, allowing for direct comparison between studies and laboratories. Thus, these methods may be highly adoptable in clinical research, providing a starting point for early diagnosis and metabolic screening.     

Sepsis plasma protein profiling with immunodepletion, three-dimensional liquid chromatography tandem mass spectrometry, and spectrum counting

Sepsis is a systemic, often fatal inflammatory response whose biochemical pathways are not fully understood and with no single biomarker capable of its reliable prediction. Increased interest in protein profiling to reveal fundamental biochemical events as well as disease diagnosis has grown considerably, largely due to advances in mass spectrometry and related front-end technologies. In this study, patients with sepsis and systemic inflammatory response syndrome (SIRS) were examined using plasma protein profiling following immunodepletion treatment to remove the most abundant proteins, serum albumin, transferrin, haptoglobin, anti-trypsin, IgG, and IgA. These proteins cause significant signal suppression, and their removal allows for lower abundance proteins to be examined through improved ion signal. Analyses after immunodepletion were performed using 3-dimensional reverse phase/strong cation exchange/reverse phase liquid chromatography with electrospray ion trap mass spectrometry (3D LC-MS/MS) and spectrum counting for comparative quantitation. The results revealed a major theme in immune system activity, including activation of the complement and coagulation pathways. Additionally, lipid transport may prove to be important in distinguishing sepsis from SIRS. Specifically, significant multi-fold changes were observed in 10 proteins and are now being investigated for the early diagnosis of sepsis.     

Metabolic profiling of fifteen amino acids in serum of chemical-induced liver injured rats by hydrophilic interaction liquid chromatography coupled with tandem mass spectrometry

Amino acids (AA) play a crucial role in the metabolic process of animals, plants and microbial cells, which are useful for the diagnosis, follow-up and prognostics of liver disorders affecting AA metabolism. A rapid, simple and sensitive analytical method is in urgent need to investigate the intact metabolic profile and to simultaneously determine individual AA in biological samples. Here, a hydrophilic interaction liquid chromatography (HILIC) coupled with tandem mass spectrometry (MS/MS) analytical method was developed and validated for simultaneous quantification of 15 AA in rat serum using isotope stable-labeled phenylalanine and alanine as internal standards. The 15 AA without derivatization were separated on a hydrophilic interaction silica column (TSK-GEL AMIDE-80), the total analytical time was within 8?min, and the concentrations of the 15 AA were determined using a multiple reaction monitoring (MRM) mode. Limits of detection (LOD) ranged from 0.01 to 0.05???g/ml, and the calibration curve was linear in the range of 0.05?C10???g/ml (r?>?0.99). The HILIC-MS method was employed to the analysis of AA in serum samples obtained from N-acetyl-p-amino-phenol (APAP)- and chloropromazine hydrochloride (CH)- induced liver injured rats. The concentrations of each AA ranged from the low quantification value up to 10???g/ml. Based on metabolic profile of AA, multivariate statistics using principal component analysis (PCA) and partial least squares discriminate analysis (PLS-DA) could differentiate two distinct groups corresponding to APAP-induced and CH-induced rats. This novel metabolic profile study of AA based on the HILIC-MS analysis and chemometric analysis provided not only an accurate quantitative assay of the serum concentrations of biomarkers, but also a promising methodology for evaluation of chemical-induced hepatotoxicity in reflecting AA metabolic pathway.