Phenylmethanesulfonyl fluoride pretreatment stabilizes plasma lipidome in lipidomic and metabolomic analysis

Though it is standard practice to test the stability of analytes in the matrix for routine bioanalytical method, stability evaluation is always impractical and skipped in untargeted lipidomic and metabolomic analysis because analytes in these studies are enormous, diverse and sometimes unknown. Lipidome represents a major class of plasma metabolome and shows great potential to be diagnostic and prognostic biomarkers. However, lipidome also faces stability problems because plasma contains kinds of lipid degradation enzyme. Here, using liquid chromatography time of flight mass spectrometry based lipidomic methodology, plasma levels of various lipids including triglyceride (TG), diglyceride (DG), free fatty acid (FFA), phosphatidylethanolamine (PE) phosphatidylcholine (PC), lyso-phosphatidylcholine (LPC), lyso-phosphatidylethanolamine (LPE), and sphingomyelin (SM) were dynamically determined within 4 h at ambient temperature. In mouse and rat plasma, the levels of most TG, DG, PC and PE species significantly decreased with respect to time, whereas those of LPC, LPE and FFA significantly increased with respect to time. However, such changes did not occur in human plasma, thus indicating hepatic lipase and esterase might involve in the species-specified degradation of lipid classes in plasma. Phenylmethanesulfonyl fluoride (PMSF) pretreatment prevented such lipidome instability in mouse plasma. The results suggested the instability of plasma lipidome should be highly concerned, and the enhancement of ex vivo stability of plasma lipidome could enable more reliable clinical translation of lipidomic data for biomarker discovery.     

From differentiating metabolites to biomarkers

The current developments in metabolomics and metabolic profiling technologies have led to the discovery of several new metabolic biomarkers. Finding metabolites present in significantly different levels between sample sets, however, does not necessarily make these metabolites useful biomarkers. The route to valid and applicable biomarkers (biomarker qualification) is long and demands a significant amount of work. In this overview, we critically discuss the current state-of-the-art of metabolic biomarker discovery, with highlights and shortcomings, and suggest a pathway to clinical usefulness.

Dansylation isotope labeling liquid chromatography mass spectrometry for parallel profiling of human urinary and fecal submetabolomes

Human urine and feces can be non-invasively collected for metabolomics-based disease biomarker discovery research. Because urinary and fecal metabolomes are thought to be different, analysis of both biospecimens may generate a more comprehensive metabolomic profile that can be better related to the health state of an individual. Herein we describe a method of using differential chemical isotope labeling (CIL) liquid chromatography mass spectrometry (LC-MS) for parallel metabolomic profiling of urine and feces. Dansylation labeling was used to quantify the amine/phenol submetabolome changes among different samples based on ¹²C-labeling of individual samples and ¹³C-labeling of a pooled urine or pooled feces and subsequent analysis of the ¹³C-/¹²C-labeled mixture by LC-MS. The pooled urine and pooled feces are further differentially labeled, mixed and then analyzed by LC-MS in order to relate the metabolite concentrations of the common metabolites found in both biospecimens. This method offers a means of direct comparison of urinary and fecal submetabolomes. We evaluated the analytical performance and demonstrated the utility of this method in the analysis of urine and feces collected daily from three healthy individuals for 7 days. On average, 2534 ± 113 (n = 126) peak pairs or metabolites could be detected from a urine sample, while 2507 ± 77 (n = 63) peak pairs were detected from a fecal sample. In total, 5372 unique peak pairs were detected from all the samples combined; 3089 and 3012 pairs were found in urine and feces, respectively. These results reveal that the urine and fecal metabolomes are very different, thereby justifying the consideration of using both biospecimens to increase the probability of finding specific biomarkers of diseases. Furthermore, the CIL LC-MS method described can be used to perform parallel quantitative analysis of urine and feces, resulting in more complete coverage of the human metabolome.     

Lysophosphatidylcholine—biomarker of Metformin action: studied using UPLC/MS/MS

An UPLC/MS/MS based metabonomic method was developed and applied to the elucidation of biomarker of metformin action. The plasma metabolite profiling in healthy volunteers before and after per os metformin was determined with UPLC/MS/MS and analyzed by using multivariate statistics. Significant difference in endogenous metabolite profiles was revealed before and after administration of metformin. Four biomarkers found were lysophosphatidylcholines (LPCs), and their structures were tentatively identified to be 16:0 LPC, 18:0 LPC, 18:1 LPC and 18:2 LPC according to the molecular ions information and corresponding fragments of product ion scan. Lysophosphatidylcholine in blood may be involved in metformin treatment. Copyright © 2009 John Wiley & Sons, Ltd.     

A magnetic bead‐based serum proteomic fingerprinting method for parallel analytical analysis and micropreparative purification

ProteinChip surface‐enhanced laser desorption/ionization technology and magnetic beads‐based ClinProt system are commonly used for semi‐quantitative profiling of plasma proteome in biomarker discovery. Unfortunately, the proteins/peptides detected by MS are non‐recoverable. To obtain the protein identity of a MS peak, additional time‐consuming and material‐consuming purification steps have to be done. In this study, we developed a magnetic beads‐based proteomic fingerprinting method that allowed semi‐quantitative proteomic profiling and micropreparative purification of the profiled proteins in parallel. The use of different chromatographic magnetic beads allowed us to obtain different proteomic profiles, which were comparable to those obtained by the ProteinChip surface‐enhanced laser desorption/ionization technology. Our assays were semi‐quantitative. The normalized peak intensity was proportional to concentration measured by immunoassay. Both intra‐assay and inter‐assay coefficients of variation of the normalized peak intensities were in the range of 4–30%. Our method only required 2 μL of serum or plasma for generating enough proteins for semi‐quantitative profiling by MALDI‐TOF‐MS as well as for gel electrophoresis and subsequent protein identification. The protein peaks and corresponding gel spots could be easily matched by comparing their intensities and masses. Because of its high efficiency and reproducibility, our method has great potentials in clinical research, especially in biomarker discovery.     

Biomarker discovery in psychiatric disorders

Schizophrenia is a multifaceted neuropsychiatric disorder. Its onset is the result of complex interactions between genetic, developmental and environmental factors. It almost certainly presents a heterogeneous group of aetiologies which may not be reflected in the symptomatic/clinical presentation of patients. Therefore, a better molecular understanding of the disease onset and progression is urgently needed. The high complexity of the disorder and the heterogeneity of patient populations account for the slow progress of biomarker discovery approaches. Multi-omics profiling approaches can be employed to investigate large numbers of patient and control samples in a single experiment. These large scale experiments are required to identify disease intrinsic molecular signatures as well as patient subgroups with potentially distinct biochemical pathways underpinning their symptoms. In this overview, we describe some of the most important challenges for biomarker discovery for psychiatric disorders and emphasize how these problems contribute to the requirement of large sample numbers. Results of MS-based protein profiling studies in schizophrenia research are reviewed and technical advantages and difficulties of the methodologies described. We outline recent technological advances that generated impressive results in other areas of research and point to their applicability for biomarker discovery in psychiatric disorders.     

Proteomics comparison of exosomes from serum and plasma between ultracentrifugation and polymer‐based precipitation kit methods

Exosomes are vesicles with sizes ranging from 30 to 150 nm. The analysis and detection of blood exosomes offers an effective route for cancer diagnosis, prognosis assessment, and therapeutic evaluation of diseases. Due to the difference in separation procedure, collection method and the usage of anticoagulants, serum and plasma samples show diversity test results. In order to evaluate the isolation effect of exosomes in serum and plasma samples, two commonly used exosomal isolation methods, ultracentrifugation and polymer‐based precipitation kit, were used, respectively. And the isolation effects were evaluated by comparing the composition and abundant of proteins from isolated exosomes based on MS‐based proteomics analysis. The results showed that the plasma exosomes extracted by ultracentrifugation identified more exosome biomarkers, and the concentrations of these biomarkers were higher than others. And plasma exosomes could be a better sample for blood‐based proteomics research of exosomes. It would be more useful for future targeted biomarker discovery.     

Metabolite profiling of human plasma by different extraction methods through gas chromatography–mass spectrometry—An objective comparison

For the comprehensive metabolite profiling of human plasma, sample preparation is a crucial step. In this investigation, we have compared 10 different extraction techniques for metabolite profiling by GC–MS. Six one-dimensional (1D) and four two-dimensional (2D) extraction techniques involving solvent precipitation, molecular weight cut off tube (MWCOT) and solid phase extraction (SPE) by using silica, RP C18, cation and anion were investigated. Pooled samples of 50 Healthy Male Plasma (HMP), 50 Healthy Female Plasma (HFP) and 100 Healthy Pakistani Plasma (HPP) were subjected to these extraction methods for comparison purposes. Metabolites obtained were identified through NIST mass spectral (Wiley registry), METLIN and Fiehn RTL libraries. XCMS Software was used for the detection of metabolic features, retention time correction, alignment, annotation and statistical analysis in each method. 116–34 peaks were detected by various methods and approx 33% of the peaks were characterized in each method. Hierarchical clustering of the 10 extraction methods showed a low similarity index (50.1%) which indicated different chemical nature of metabolites, resulting from different methods. Venn diagram highlights the GC–MS peaks (33–77%) common in various methods. Metabolites which were different in male and female groups were detected using a threshold value of p ≤ 0.0001, q ≤ 0.001 and fold change ≥3 by employing Welch's t-test and identified through METLIN. Results indicated that 2D-C18 and 2D-silica offers a comprehensive metabolite profile in term of reproducibility, number of peaks and difference in metabolite pattern of male and female.     

The effects of abundant plasma protein depletion on global glycan profiling using NanoLC FT-ICR mass spectrometry

We report the results of abundant plasma protein depletion on the analysis of underivatized N-linked glycans derived from plasma proteins by nanoLC Fourier-transform ion cyclotron resonance mass spectrometry. N-linked glycan profiles were compared between plasma samples where the six most abundant plasma proteins were depleted (n = 3) through a solid-phase immunoaffinity column and undepleted plasma samples (n = 3). Three exogenous glycan standards were spiked into all samples which allowed for normalization of the N-glycan abundances. The abundances of 20 glycans varying in type, structure, composition, and molecular weight (1,200–3,700 Da) were compared between the two sets of samples. Small fucosylated non-sialylated complex glycans were found to decrease in abundance in the depleted samples (greater than or equal to tenfold) relative to the undepleted samples. Protein depletion was found to marginally effect (less than threefold) the abundance of high mannose, hybrid, and large highly sialylated complex species. The significance of these findings in terms of future biomarker discovery experiments via global glycan profiling is discussed.     

A two step fractionation approach for plasma proteomics using immunodepletion of abundant proteins and multi-lectin affinity chromatography: Application to the analysis of obesity, diabetes, and hypertension diseases

Plasma is an important biological material for biomarker discovery. However, the wide dynamic range in protein concentration remains a major challenge. In this paper, we introduce the development of a proteomic platform for analysis of plasma samples. The method utilizes a double fractionation approach which combines the MARS immunodepletion column with multi-lectin affinity chromatography, M-LAC, to deplete the most abundant proteins in plasma, the majority of which are glycosylated. To determine the suitability of this methodology, we applied the workflow described in this study to a sample set composed of four groups: a control pool and three different disease pools: obesity, diabetes, and hypertension. We were able to identify changes in the level of several proteins; for example, a protein such as angiotensinogen was found to be present at high levels in patients with obesity plus diabetes and hypertension. On the other hand, apolipoprotein CI was shown to be elevated in all disease groups. A review of the literature supported our observation. The methodology presented in this report was shown to be effective for profiling changes in the plasma proteome of subjects with obesity and its associated complications such as diabetes and hypertension.     

Effect of quality characteristics of single sample preparation steps in the precision and coverage of proteomic studies—A review

Proteomic profiling and biomarker search are analytical tools as many other. Nevertheless, in the proteomic discovery phase considerable sample fractionation is inevitable before readout. Since these procedures are of notable complexity, proteomic tools need in particular analytical quality validation standards as prevail for other analytical methods. With acceptance of the rule of error propagation the values of imprecision and yield of each preparation step determine overall reproducibility and therewith information harvest of a propagated method series. Thereto, we examined recent proteomic reports with reproducibility data and with parallelization, and automation approaches. Based on the data available from literature it is highly probable, that at least a part of current proteomic platforms actually suffer from high technical variance.     

Discovery of safety biomarkers for atorvastatin in rat urine using mass spectrometry based metabolomics combined with global and targeted approach

In order to develop a safety biomarker for atorvastatin, this drug was orally administrated to hyperlipidemic rats, and a metabolomic study was performed. Atorvastatin was given in doses of either 70 mg kg⁻¹ day⁻¹ or 250 mg kg⁻¹ day⁻¹ for a period of 7 days (n = 4 for each group). To evaluate any abnormal effects of the drug, physiological and plasma biochemical parameters were measured and histopathological tests were carried out. Safety biomarkers were derived by comparing these parameters and using both global and targeted metabolic profiling. Global metabolic profiling was performed using liquid chromatography/time of flight/mass spectrometry (LC/TOF/MS) with multivariate data analysis. Several safety biomarker candidates that included various steroids and amino acids were discovered as a result of global metabolic profiling, and they were also confirmed by targeted metabolic profiling using gas chromatography/mass spectrometry (GC/MS) and capillary electrophoresis/mass spectrometry (CE/MS). Serum biochemical and histopathological tests were used to detect abnormal drug reactions in the liver after repeating oral administration of atorvastatin. The metabolic differences between control and the drug-treated groups were compared using PLS-DA score plots. These results were compared with the physiological and plasma biochemical parameters and the results of a histopathological test. Estrone, cortisone, proline, cystine, 3-ureidopropionic acid and histidine were proposed as potential safety biomarkers related with the liver toxicity of atorvastatin. These results indicate that the combined application of global and targeted metabolic profiling could be a useful tool for the discovery of drug safety biomarkers.     

Comprehensive profiling of mercapturic acid metabolites from dietary acrylamide as short-term exposure biomarkers for evaluation of toxicokinetics in rats and daily internal exposure in humans using isotope dilution ultra-high performance liquid chromatography tandem mass spectrometry

Mercapturic acid metabolites from dietary acrylamide are important short-term exposure biomarkers for evaluating the in vivo toxicity of acrylamide. Most of studies have focused on the measurement of two metabolites, N-acetyl-S-(2-carbamoylethyl)-l-cysteine (AAMA) and N-acetyl-S-(2-carbamoyl-2-hydroxyethyl)-l-cysteine (GAMA). Thus, the comprehensive profile of acrylamide urinary metabolites cannot be fully understood. We developed an isotope dilution ultra-high performance liquid chromatography tandem mass spectrometry (UHPLC-MS/MS) method for the simultaneous determination of all four mercapturic acid adducts of acrylamide and its primary metabolite glycidamide under the electroscopy ionization negative (ESI-) mode in the present study. The limit of detection (LOD) and limit of quantification (LOQ) of the analytes ranged 0.1–0.3 ng/mL and 0.4–1.0 ng/mL, respectively. The recovery rates with low, intermediate and high spiking levels were calculated as 95.5%–105.4%, 98.2%–114.0% and 92.2%–108.9%, respectively. Acceptable within-laboratory reproducibility (RSD < 7.0%) substantially supported the use of current method for robust analysis. Rapid pretreatment procedures and short run time (8 min per sample) ensured good efficiency of metabolism profiling, indicating a wide application for investigating short-term internal exposure of dietary acrylamide. Our proposed UHPLC-MS/MS method was successfully applied to the toxicokinetic study of acrylamide in rats. Meanwhile, results of human urine analysis indicated that the levels of N-acetyl-S-(2-carbamoylethyl)-l-cysteine-sulfoxide (AAMA-sul), which did not appear in the mercapturic acid metabolites in rodents, were more than the sum of GAMA and N-acetyl-S-(1-carbamoyl-2-hydroxyethyl)-l-cysteine (iso-GAMA). Thus, AAMA-sul may alternatively become a specific biomarker for investigating the acrylamide exposure in humans. Current proposed method provides a substantial methodology support for comprehensive profiling of toxicokinetics and daily internal exposure evaluations of acrylamide in vivo.     

Pattern recognition analysis for <Superscript>1</Superscript>H NMR spectra of plasma from hemodialysis patients

¹H NMR spectroscopic and pattern recognition-based methods (NMR-PR) were applied to the metabolic profiling studies on hemodialysis (HD). Plasma samples were collected from 37 patients before and after HD and measured by 600 MHz NMR spectroscopy. Each spectrum was data-processed and subjected to principal component analysis for pattern recognition. Spectral patterns of plasma between pre- and post-dialyses were clearly discriminated, together with significant fluctuations in the levels of creatinine, trimethylamine-N-oxide, glucose, lactate, and acetate, which were quantitated. We have first observed the significant elevation of lactate levels in post-dialysis plasma. The present study has demonstrated the high feasibility of NMR-PR method for monitoring the dialysis condition and comprehensive profiling of the change of low-molecular-weight metabolites in HD. Figure PCA for 1H NMR spectra of plasma from HD patients     

Assessing the suitability of capillary electrophoresis‐mass spectrometry for biomarker discovery in plasma‐based metabolomics

The actual utility of capillary electrophoresis‐mass spectrometry (CE‐MS) for biomarker discovery using metabolomics still needs to be assessed. Therefore, a simulated comparative metabolic profiling study for biomarker discovery by CE‐MS was performed, using pooled human plasma samples with spiked biomarkers. Two studies have been carried out in this work. Focus of study I was on comparing two sets of plasma samples, in which one set (class I) was spiked with five isotope‐labeled compounds, whereas another set (class II) was spiked with six different isotope‐labeled compounds. In study II, focus was also on comparing two sets of plasma samples, however, the isotope‐labeled compounds were spiked to both class I and class II samples but with concentrations which differ by a factor two between both classes (with one compound absent in each class). The aim was to determine whether CEMS‐based metabolomics could reveal the spiked biomarkers as the main classifiers, applying two different data analysis software tools (MetaboAnalyst and Matlab). Unsupervised analysis of the recorded metabolic profiles revealed a clear distinction between class I and class II plasma samples in both studies. This classification was mainly attributed to the spiked isotope‐labeled compounds, thereby emphasizing the utility of CE‐MS for biomarker discovery.     

Pre-analytical method for NMR-based grape metabolic fingerprinting and chemometrics

Although metabolomics aims at profiling all the metabolites in organisms, data quality is quite dependent on the pre-analytical methods employed. In order to evaluate current methods, different pre-analytical methods were compared and used for the metabolic profiling of grapevine as a model plant. Five grape cultivars from Portugal in combination with chemometrics were analyzed in this study. A common extraction method with deuterated water and methanol was found effective in the case of amino acids, organic acids, and sugars. For secondary metabolites like phenolics, solid phase extraction with C-18 cartridges showed good results. Principal component analysis, in combination with NMR spectroscopy, was applied and showed clear distinction among the cultivars. Primary metabolites such as choline, sucrose, and leucine were found discriminating for ‘Alvarinho’, while elevated levels of alanine, valine, and acetate were found in ‘Arinto’ (white varieties). Among the red cultivars, higher signals for citrate and GABA in ‘Touriga Nacional’, succinate and fumarate in ‘Aragonês’, and malate, ascorbate, fructose and glucose in ‘Trincadeira’, were observed. Based on the phenolic profile, ‘Arinto’ was found with higher levels of phenolics as compared to ‘Alvarinho’. ‘Trincadeira’ showed lowest phenolics content while higher levels of flavonoids and phenylpropanoids were found in ‘Aragonês’ and ‘Touriga Nacional’, respectively. It is shown that the metabolite composition of the extract is highly affected by the extraction procedure and this consideration has to be taken in account for metabolomics studies.     

Mining the human plasma proteome with three-dimensional strategies by high-resolution Quadrupole Orbitrap Mass Spectrometry

Human plasma is a readily available clinical sample that reflects the status of the body in normal physiological and disease states. Although the wide dynamic range and immense complexity of plasma proteins are obstacles, comprehensive proteomic analysis of human plasma is necessary for biomarker discovery and further verification. Various methods such as immunodepletion, protein equalization and hyper fractionation have been applied to reduce the influence of high-abundance proteins (HAPs) and to reduce the high level of complexity. However, the depth at which the human plasma proteome has been explored in a relatively short time frame has been limited, which impedes the transfer of proteomic techniques to clinical research. Development of an optimal strategy is expected to improve the efficiency of human plasma proteome profiling.     

Delipidation‐based solid‐phase extraction pretreatment technique for plasma broad‐coverage metabolomic profiling to reveal the potential pathogenesis of yeast‐induced fever in rats

During the process of metabolomics profiling by using ultra high performance liquid chromatography coupled with time‐of flight mass spectrometry, blood sample pretreatment is a crucial step for biomarker discovery. Herein, in order to prevent the potential loss of metabolites and ion suppression phenomena caused by the proteins and phospholipids contained in blood fluids, a delipidation‐based solid‐phase extraction pretreatment technique for plasma broad‐coverage metabolomic profiling was performed. This technique can be summarized as a single extraction, a single elution of solid‐phase extraction plate, followed by four times measuring with electrospray ionization in positive and negative ion mode, respectively. This approach significantly increased the number of features detected in plasma, and 1572 features in positive mode and 1352 features in negative mode were detected, respectively. Besides, the stability and repeatability of the approach were greatly improved. For these advantages, the approach was employed to elucidate the potential pathogenesis of yeast‐induced fever in rats. The biomarkers associated with the pathogenesis of fever were shown to be related to amino acids metabolism and lipid metabolism. The delipidation‐based solid‐phase extraction pretreatment approach can provide a useful tool to reveal the pathological mechanisms of such systemic pathological process.     

Fast determination of hydroxylated polychlorinated biphenyls in human plasma by online solid phase extraction coupled to liquid chromatography-tandem mass spectrometry

Hydroxylated polychlorinated biphenyls (OH-PCBs) have been shown to be strongly retained in human blood causing endocrine-related toxicity, particularly on the thyroid system. Traditionally, analytical methods for the determination of OH-PCBs require labor-intensive and long-time consuming sample preparation with several extraction, evaporation and cleanup procedures steps and, in some cases, derivatization prior to the analysis by gas or liquid chromatography-mass spectrometry (GC–MS or LC-MS). The present study developed and validated a novel, sensitive and high throughput online solid phase extraction (SPE) method coupled to LC-tandem mass spectrometry (MS/MS) for the separation and quantitation of relevant congeners of OH-PCBs in human plasma. The developed method presented limits of quantification (LOQ) ranging from 0.02 to 0.5 ng mL⁻¹ and extraction recoveries from 71 to 134% for all congeners, requiring small amount of sample (only 100 μL) and minimal sample preparation. In order to evaluate the applicability of the method, preliminary tests (N = 93) were conducted in plasma from individuals occupationally exposed to very high levels of PCBs in a German cohort. Penta-through hepta-chlorinated OH-PCBs were the predominant congeners in human plasma with concentrations up to 44.5 ng mL⁻¹, while lower chlorinated OH-PCBs were occasionally detected. In addition, a new PCB 28 metabolite has been synthesized and identified for the first time in human plasma and associations between OH-PCBs and their parent compounds in the studied cohort were also assessed.     

Fractionation of the human plasma proteome for monoclonal antibody proteomics‐based biomarker discovery 2: Antigen identification by dot‐blot array screening

Immunization with complex mixtures, like the human plasma resulted in the generation of cloned mAb libraries (PlasmaScan? and QuantiPlasma? libraries, with >1000 individual mAbs) reacting with a nonredundant set of antigenic epitopes. mAb proteomics refers to quasi‐hypothesis‐free profiling of plasma samples with nascent or cloned mAb libraries for the discovery of disease‐specific biomarkers. Once mAbs with biomarker potential have been identified, the next task is the determination of cognate antigens recognized by the respective mAbs. To determine the cognate protein antigen corresponding to each individual mAbs in the cloned mAb libraries, we have separated human plasma by consecutive steps of desalting and various chromatography procedures. The process resulted in 783 fractions, which we termed “Analyte Library” (AL). The AL represents the human plasma proteome in relatively low‐protein complexity fractions. Here, to determine the utility of the AL, we selected ten plasma proteins and checked for their presence in the fractions. Among the ten cases, the distribution of four selected plasma proteins matched expectations, as these proteins were present only in a few fractions corresponding to their physical, chemical, and biochemical properties. However, in six cases, we observed “smear” ‐like distribution or complete absence of the proteins, suggesting that protein–protein interactions or protein variants may alter the observed plasma distribution profiles. Nevertheless, we conclude that the AL is an efficient, high throughput tool to complement the mAb biomarker discovery process with cognate protein antigen identification for each mAbs.