Proteomic analysis of eccrine sweat: implications for the discovery of schizophrenia biomarker proteins

Liquid chromatography-tandem mass spectrometry (LC-MS/MS) and multiple reaction monitoring mass spectrometry (MRM-MS) proteomics analyses were performed on eccrine sweat of healthy controls, and the results were compared with those from individuals diagnosed with schizophrenia (SZ). This is the first large scale study of the sweat proteome. First, we performed LC-MS/MS on pooled SZ samples and pooled control samples for global proteomics analysis. Results revealed a high abundance of diverse proteins and peptides in eccrine sweat. Most of the proteins identified from sweat samples were found to be different than the most abundant proteins from serum, which indicates that eccrine sweat is not simply a plasma transudate and may thereby be a source of unique disease-associated biomolecules. A second independent set of patient and control sweat samples were analyzed by LC-MS/MS and spectral counting to determine qualitative protein differential abundances between the control and disease groups. Differential abundances of selected proteins, initially determined by spectral counting, were verified by MRM-MS analyses. Seventeen proteins showed a differential abundance of approximately 2-fold or greater between the SZ pooled sample and the control pooled sample. This study demonstrates the utility of LC-MS/MS and MRM-MS as a viable strategy for the discovery and verification of potential sweat protein disease biomarkers.     

The plasma proteome, adductome and idiosyncratic toxicity in toxicoproteomics research

Toxicoproteomics uses the discovery potential of proteomicsin toxicology research by applying global protein measurementtechnologies to biofluids and tissues after host exposure toinjurious agents. Toxicoproteomic studies thus far have focusedon protein profiling of major organs and biofluids such as liverand blood in preclinical species exposed to model toxicants.The slow pace of discovery for new biomarkers, toxicity signaturesand mechanistic insights is partially due to the limited proteomecoverage derived from analysis of native organs, tissues andbody fluids by traditional proteomic platforms. Improved toxicoproteomicanalysis would result by combining higher data density LC-MS/MSplatforms with stable isotope labelled peptides and paralleluse of complementary platforms. Study designs that remove abundantproteins from biofluids, enrich subcellular structures and includecell specific isolation from heterogeneous tissues would greatlyincrease differential expression capabilities. By leveragingresources from immunology, cell biology and nutrition researchcommunities, toxicoproteomics could make particular contributionsin three inter-related areas to advance mechanistic insightsand biomarker development: the plasma proteome and circulatingmicroparticles, the adductome and idiosyncratic toxicity.      

Preclinical metabolism of LB42908, a novel farnesyl transferase inhibitor, and its effects on the cytochrome P450 isozyme activities

Metabolism of LB42908, a novel farnesyl transferase inhibitor, was investigated for preclinical development. In vitro hepatic metabolism of LB42908 gave rise to at least 9 metabolites via phase I biotransformation pathways, which were characterized by HPLC-UV, LC-MS, and LC-MS/MS analyses. N-Dealkylation was shown to be a major phase I metabolic pathway. Species-specific in vitro metabolism of LB42908 was studied in liver fractions of rat, dog, monkey, and human. Order of metabolic stability is human≈dog>rat≈monkey in both S9 and microsomal fractions. Tissue-specific metabolism of LB42908 in various tissue homogenates of rats demonstrated that the liver was the major organ responsible for phase I metabolism of LB42908. The results from both qualitative and quantitative metabolism studies such as metabolic profiling and metabolic clearance indicated that dog would be the animal model of choice for preclinical toxicology studies. In addition, LB42908 was a potent CYP3A4 inhibitor in human liver microsomes and induced the activities of several CYP isozymes, implying that it has the potential for drug-drug interactions. Repeated dosing of LB42908 in rats did not significantly affect its own metabolism, indicating that long-term administration of LB42908 would not alter its pharmacokinetic profiles.     

Antibiotic Toxicity and Absorption in Zebrafish Using Liquid Chromatography-Tandem Mass Spectrometry

Evaluation of drug toxicity is necessary for drug safety, but in vivo drug absorption is varied; therefore, a rapid, sensitive and reliable method for measuring drugs is needed. Zebrafish are acceptable drug toxicity screening models; we used these animals with a liquid chromatography-tandem mass spectrometry (LC-MS/MS) method in a multiple reaction monitoring mode to quantify drug uptake in zebrafish to better estimate drug toxicity. Analytes were recovered from zebrafish homogenate by collecting supernatant. Measurements were confirmed for drugs in the range of 10–1,000 ng/mL. Four antibiotics with different polarities were tested to explore any correlation of drug polarity, absorption, and toxicity. Zebrafish at 3 days post-fertilization (dpf) absorbed more drug than those at 6 h post-fertilization (hpf), and different developmental periods appeared to be differentially sensitive to the same compound. By observing abnormal embryos and LD₅₀ values, zebrafish embryos at 6 hpf were considered to be suitable for evaluating embryotoxicity. Also, larvae at 3 dpf were adapted to measure acute drug toxicity in adult mammals. Thus, we can exploit zebrafish to study drug toxicity and can reliably quantify drug uptake with LC-MS/MS. This approach will be helpful for future studies of toxicology in zebrafish.     

Integrated pipeline for mass spectrometry-based discovery and confirmation of biomarkers demonstrated in a mouse model of breast cancer

Despite their potential to impact diagnosis and treatment of cancer, few protein biomarkers are in clinical use. Biomarker discovery is plagued with difficulties ranging from technological (inability to globally interrogate proteomes) to biological (genetic and environmental differences among patients and their tumors). We urgently need paradigms for biomarker discovery. To minimize biological variation and facilitate testing of proteomic approaches, we employed a mouse model of breast cancer. Specifically, we performed LC-MS/MS of tumor and normal mammary tissue from a conditional HER2/Neu-driven mouse model of breast cancer, identifying 6758 peptides representing >700 proteins. We developed a novel statistical approach (SASPECT) for prioritizing proteins differentially represented in LC-MS/MS datasets and identified proteins over- or under-represented in tumors. Using a combination of antibody-based approaches and multiple reaction monitoring-mass spectrometry (MRM-MS), we confirmed the overproduction of multiple proteins at the tissue level, identified fibulin-2 as a plasma biomarker, and extensively characterized osteopontin as a plasma biomarker capable of early disease detection in the mouse. Our results show that a staged pipeline employing shotgun-based comparative proteomics for biomarker discovery and multiple reaction monitoring for confirmation of biomarker candidates is capable of finding novel tissue and plasma biomarkers in a mouse model of breast cancer. Furthermore, the approach can be extended to find biomarkers relevant to human disease.     

Molecular classification of liver cirrhosis in a rat model by proteomics and bioinformatics

Liver cirrhosis is a worldwide health problem. Reliable, noninvasive methods for early detection of liver cirrhosis are not available. Using a three-step approach, we classified sera from rats with liver cirrhosis following different treatment insults. The approach consisted of: (i) protein profiling using surface-enhanced laser desorption/ionization (SELDI) technology; (ii) selection of a statistically significant serum biomarker set using machine learning algorithms; and (iii) identification of selected serum biomarkers by peptide sequencing. We generated serum protein profiles from three groups of rats: (i) normal (n=8), (ii) thioacetamide-induced liver cirrhosis (n=22), and (iii) bile duct ligation-induced liver fibrosis (n=5) using a weak cation exchanger surface. Profiling data were further analyzed by a recursive support vector machine algorithm to select a panel of statistically significant biomarkers for class prediction. Sensitivity and specificity of classification using the selected protein marker set were higher than 92%. A consistently down-regulated 3495 Da protein in cirrhosis samples was one of the selected significant biomarkers. This 3495 Da protein was purified on-chip and trypsin digested. Further structural characterization of this biomarkers candidate was done by using cross-platform matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) peptide mass fingerprinting (PMF) and matrix-assisted laser desorption/ionization time of flight/time of flight (MALDI-TOF/TOF) tandem mass spectrometry (MS/MS). Combined data from PMF and MS/MS spectra of two tryptic peptides suggested that this 3495 Da protein shared homology to a histidine-rich glycoprotein. These results demonstrated a novel approach to discovery of new biomarkers for early detection of liver cirrhosis and classification of liver diseases.     

Mapping Drug Physico-Chemical Features to Pathway Activity Reveals Molecular Networks Linked to Toxicity Outcome

The identification of predictive biomarkers is at the core of modern toxicology. So far, a number of approaches have been proposed. These rely on statistical inference of toxicity response from either compound features (i.e., QSAR), in vitro cell based assays or molecular profiling of target tissues (i.e., expression profiling). Although these approaches have already shown the potential of predictive toxicology, we still do not have a systematic approach to model the interaction between chemical features, molecular networks and toxicity outcome. Here, we describe a computational strategy designed to address this important need. Its application to a model of renal tubular degeneration has revealed a link between physico-chemical features and signalling components controlling cell communication pathways, which in turn are differentially modulated in response to toxic chemicals. Overall, our findings are consistent with the existence of a general toxicity mechanism operating in synergy with more specific single-target based mode of actions (MOAs) and provide a general framework for the development of an integrative approach to predictive toxicology.     

A xenograft mouse model coupled with in-depth plasma proteome analysis facilitates identification of novel serum biomarkers for human ovarian cancer

Proteomics discovery of novel cancer serum biomarkers is hindered by the great complexity of serum, patient-to-patient variability, and triggering by the tumor of an acute-phase inflammatory reaction. This host response alters many serum protein levels in cancer patients, but these changes have low specificity as they can be triggered by diverse causes. We addressed these hurdles by utilizing a xenograft mouse model coupled with an in-depth 4-D protein profiling method to identify human proteins in the mouse serum. This strategy ensures that identified putative biomarkers are shed by the tumor, and detection of low-abundance proteins shed by the tumor is enhanced because the mouse blood volume is more than a thousand times smaller than that of a human. Using TOV-112D ovarian tumors, more than 200 human proteins were identified in the mouse serum, including novel candidate biomarkers and proteins previously reported to be elevated in either ovarian tumors or the blood of ovarian cancer patients. Subsequent quantitation of selected putative biomarkers in human sera using label-free multiple reaction monitoring (MRM) mass spectrometry (MS) showed that chloride intracellular channel 1, the mature form of cathepsin D, and peroxiredoxin 6 were elevated significantly in sera from ovarian carcinoma patients.     

The Plasma Proteome: High Abundance versus Low Abundance

The field of proteomics is rapidly turning towards targeted mass spectrometry (MS) methods to quantify putative markers or known proteins of biological interest. Historically, the enzyme-linked immunosorbent assay (ELISA) has been used for targeted protein analysis, but, unfortunately, it is limited by the excessive time required for antibody preparation, as well as concerns over selectivity. Despite the ability of proteomics to deliver increasingly quantitative measurements, owing to limited sensitivity, the leads generated are in the microgram per milliliter range. This stands in stark contrast to ELISA, which is capable of quantifying proteins at low picogram per milliliter levels. To bridge this gap, targeted liquid chromatography (LC) tandem MS (MS/MS) analysis of tryptic peptide surrogates using selected reaction monitoring detection has emerged as a viable option for rapid quantification of target proteins. The precision of this approach has been enhanced by the use of stable isotope-labeled peptide internal standards to compensate for variation in recovery and the influence of differential matrix effects. Unfortunately, the complexity of proteinaceous matrices, such as plasma, limits the usefulness of this approach to quantification in the mid-nanogram per milliliter range (medium-abundance proteins). This article reviews the current status of LC/MS/MS using selected reaction monitoring for protein quantification, and specifically considers the use of a single antibody to achieve superior enrichment of either the protein target or the released tryptic peptide. Examples of immunoaffinity-assisted LC/MS/MS are reviewed that demonstrate quantitative analysis of low-abundance proteins (subnanogram per milliliter range). A strategy based on this technology is proposed for the expedited evaluation of novel protein biomarkers, which relies on the synergy created from the complementary nature of MS and ELISA.     

Coupling immunoaffinity techniques with MS for quantitative analysis of low-abundance protein biomarkers

The field of proteomics is rapidly turning towards targeted mass spectrometry (MS) methods to quantify putative markers or known proteins of biological interest. Historically, the enzyme-linked immunosorbent assay (ELISA) has been used for targeted protein analysis, but, unfortunately, it is limited by the excessive time required for antibody preparation, as well as concerns over selectivity. Despite the ability of proteomics to deliver increasingly quantitative measurements, owing to limited sensitivity, the leads generated are in the microgram per milliliter range. This stands in stark contrast to ELISA, which is capable of quantifying proteins at low picogram per milliliter levels. To bridge this gap, targeted liquid chromatography (LC) tandem MS (MS/MS) analysis of tryptic peptide surrogates using selected reaction monitoring detection has emerged as a viable option for rapid quantification of target proteins. The precision of this approach has been enhanced by the use of stable isotope-labeled peptide internal standards to compensate for variation in recovery and the influence of differential matrix effects. Unfortunately, the complexity of proteinaceous matrices, such as plasma, limits the usefulness of this approach to quantification in the mid-nanogram per milliliter range (medium-abundance proteins). This article reviews the current status of LC/MS/MS using selected reaction monitoring for protein quantification, and specifically considers the use of a single antibody to achieve superior enrichment of either the protein target or the released tryptic peptide. Examples of immunoaffinity-assisted LC/MS/MS are reviewed that demonstrate quantitative analysis of low-abundance proteins (subnanogram per milliliter range). A strategy based on this technology is proposed for the expedited evaluation of novel protein biomarkers, which relies on the synergy created from the complementary nature of MS and ELISA.     

Biomarkers for severity of spinal cord injury in the cerebrospinal fluid of rats

One of the major challenges in management of spinal cord injury (SCI) is that the assessment of injury severity is often imprecise. Identification of reliable, easily quantifiable biomarkers that delineate the severity of the initial injury and that have prognostic value for the degree of functional recovery would significantly aid the clinician in the choice of potential treatments. To find such biomarkers we performed quantitative liquid chromatography-mass spectrometry (LC-MS/MS) analyses of cerebrospinal fluid (CSF) collected from rats 24 h after either a moderate or severe SCI. We identified a panel of 42 putative biomarkers of SCI, 10 of which represent potential biomarkers of SCI severity. Three of the candidate biomarkers, Ywhaz, Itih4, and Gpx3 were also validated by Western blot in a biological replicate of the injury. The putative biomarkers identified in this study may potentially be a valuable tool in the assessment of the extent of spinal cord damage.     

Proteomic analysis of methyl parathion-responsive proteins in Sparus latus liver

The contamination of marine ecosystems by organophosphate pesticides is of great concern. The use of protein expression profiles may provide a good method to help us understand the methyl parathion (MP) toxicity to aquatic organisms. In this study, Sparus latus, was selected as the target organism. The toxicological effects of MP were investigated after 24 h exposure using proteomics to analyze their liver tissues. Certain enzyme activity parameters of the liver extracts were also examined, including CAT. After analyzing the proteomic profile of the liver using 2D gel electrophoresis, we found that the protein expression levels of 25 spots increased or decreased significantly in the exposed groups. Sixteen of the 25 protein spots were successfully identified using MALDI-TOF MS/MS. These proteins were roughly categorized into diverse functional classes such as cell redox homeostasis, metabolic processes and cytoskeleton system. These data demonstrated that proteomics was a powerful tool to provide valuable insights into the possible mechanisms of toxicity of MP contaminants in aquatic species. Additionally, these data may provide novel biomarkers for evaluation of MP contamination in the environment.     

Region-resolved proteomics profiling of monkey heart

Nonhuman primates (NHPs) play an indispensable role in biomedical research because of their similarities in genetics, physiological, and neurological function to humans. Proteomics profiling of monkey heart could reveal significant cardiac biomarkers and help us to gain a better understanding of the pathogenesis of heart disease. However, the proteomic study of monkey heart is relatively lacking. Here, we performed the proteomics profiling of the normal monkey heart by measuring three major anatomical regions (vessels, valves, and chambers) based on iTRAQ-coupled LC-MS/MS analysis. Over 3,200 proteins were identified and quantified from three heart tissue samples. Furthermore, multiple bioinformatics analyses such as gene ontology analysis, protein–protein interaction analysis, and gene-diseases association were used to investigate biological network of those proteins from each area. More than 60 genes in three heart regions are implicated with heart diseases such as hypertrophic cardiomyopathy, heart failure, and myocardial infarction. These genes associated with heart disease are mainly enriched in citrate cycle, amino acid degradation, and glycolysis pathway. At the anatomical level, the revelation of molecular characteristics of the healthy monkey heart would be an important starting point to investigate heart disease. As a unique resource, this study can serve as a reference map for future in-depth research on cardiac disease-related NHP model and novel biomarkers of cardiac injury.     

Streamlined Development of Targeted Mass Spectrometry‐Based Method Combining Scout‐MRM and a Web‐Based Tool Indexed with Scout Peptides

MS‐based targeted proteomics is a relevant technology for sensitive and robust relative or absolute quantification of proteins biomarker candidates in complex human biofluids or tissue extracts. Performing a multiplex assay imposes time scheduling of peptide monitoring only around their expected retention time that needs to be defined with synthetic peptide. Time‐scheduled monitoring is clearly a constraint that precludes from straightforward assay transfer between biological matrices or distinct experimental setup. Any unexpected retention time (RT) shift challenges assay robustness and its implementation for large‐scale analysis. Recently, Scout‐multiple reaction monitoring that fully releases multiplexed targeted acquisition from RT scheduling by successively monitoring complex transition groups triggered with sentinel molecules called Scout has been introduced. It is herein documented how Peptide Selector database and tool streamlines the building of a multiplexed method thanks to RT indexation relative to Scout peptides. This case study deals with surrogate peptides of biomarker candidates related to drug‐induced liver and vascular injury, running such on‐line built method (eight Scouts triggering the monitoring of a total of 692 transitions) enables 100% recovery of a panel of 93 spiked‐in heavy labeled standards, despite significant RT shifts between serum, plasma, or urine. This result illustrates the simplicity of automatically building and deploying robust proteomics targeted assay.     

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.     

Liquid chromatography-mass spectrometry/mass spectrometry method development for drug metabolism studies: Examining lipid matrix ionization effects in plasma

Glycerophosphocholines (GPCho's) are known to cause liquid chromatography-mass spectrometry/mass spectrometry (LC-MS/MS) matrix ionization effects during the analysis of biological samples (i.e. blood, plasma). We have developed a convenient new method, which we refer to as "in-source multiple reaction monitoring" (IS-MRM), for detecting GPCho's during LC-MS/MS method development. The approach uses high energy in-source collisionally induced dissociation (CID) to yield trimethylammonium-ethyl phosphate ions (m/z 184), which are formed from mono- and disubstituted GPCho's. The resulting ion is selected by the first quadrupole (Q1), passed through the collision cell (Q2) in the presence of collision gas at low energy to minimize fragmentation, and m/z 184 selected by the third quadrupole. This approach can be combined with standard multiple reaction monitoring (MRM) transitions with little compromise in sensitivity during method development and sample analysis. Hence, this approach was used to probe ionization matrix effects in plasma samples. The resulting information was employed to develop LC-MS/MS analyses for drugs and their metabolites with cycle times less than 5 min.     

Recent advances in mass spectrometry: data independent analysis and hyper reaction monitoring

New mass spectrometry (MS) methods, collectively known as data independent analysis and hyper reaction monitoring, have recently emerged. These methods hold promises to address the shortcomings of data-dependent analysis and selected reaction monitoring (SRM) employed in shotgun and targeted proteomics, respectively. They allow MS analyses of all species in a complex sample indiscriminately, or permit SRM-like experiments conducted with full high-resolution product ion spectra, potentially leading to higher sequence coverage or analytical selectivity. These methods include MS^E, all-ion fragmentation, Fourier transform-all reaction monitoring, SWATH Acquisition, multiplexed MS/MS, pseudo-SRM (pSRM) and parallel reaction monitoring (PRM). In this review, the strengths and pitfalls of these methods are discussed and illustrated with examples. In essence, the suitability of the use of each method is contingent on the biological questions posed. Although these methods do not fundamentally change the shape of proteomics, they are useful additional tools that should expedite biological discoveries.     

代谢组学技术及其在临床研究中的应用

在后基因组时代, 系统生物学研究成为人们关注的焦点。转录组学、蛋白质组学等功能基因组学研究方法可同时检测药物或其他因素影响下大量基因或蛋白质的表达变化情况, 但这些变化不能与生物学功能的变化建立直接联系。代谢组学方法则可为代谢物含量变化与生物表型变化建立直接相关性。代谢组学研究的目的是定量分析一个生物系统内所有代谢物的含量, 进行全面代谢物分析需要分析化学技术的支撑, 核磁共振和基于质谱的分析技术是代谢组学研究的两种主要技术手段。代谢组学研究可产生大量数据信息, 对这些数据进行分析离不开化学统计学的应用, 比如主成分分析、多维缩放、各种聚类分析技术以及功能差异分析等。文章综述了近年来代谢组学分析技术及数据分析技术的研究进展, 在此基础上, 对代谢组学在临床研究及临床前研究中的应用研究进展进行了综述。对疾病代谢表型图谱的研究有助于人们了解疾病发生、发展以及致死的机制; 在临床条件下, 这些代谢图谱可以作为疾病诊断、预后以及治疗的评判标准。代谢物组成的变化是毒物胁迫对机体造成的最终影响, 利用代谢组技术可以直接反映毒物对机体的影响。质谱技术、核磁共振技术的应用使得药物筛选过程可以快速完成, 并有助于实现个性化用药。此外, 利用代谢组学技术还可以进行已知酶的新活性研究, 也可以研究未知酶。