Protein precipitation of diluted samples in SDS‐containing buffer with acetone leads to higher protein recovery and reproducibility in comparison with TCA/acetone approach

Proteomic approaches are extremely valuable in many fields of research, where mass spectrometry methods have gained an increasing interest, especially because of the ability to perform quantitative analysis. Nonetheless, sample preparation prior to mass spectrometry analysis is of the utmost importance. In this work, two protein precipitation approaches, widely used for cleaning and concentrating protein samples, were tested and compared in very diluted samples solubilized in a strong buffer (containing SDS). The amount of protein recovered after acetone and TCA/acetone precipitation was assessed, as well as the protein identification and relative quantification by SWATH‐MS yields were compared with the results from the same sample without precipitation. From this study, it was possible to conclude that in the case of diluted samples in denaturing buffers, the use of cold acetone as precipitation protocol is more favourable than the use of TCA/acetone in terms of reproducibility in protein recovery and number of identified and quantified proteins. Furthermore, the reproducibility in relative quantification of the proteins is even higher in samples precipitated with acetone compared with the original sample.     

尿液蛋白富集方法的比较

人尿液中蛋白含量低,在进行质谱分析时易被高丰度蛋白掩盖。因此,发展高效和高选择性的富集方法,是实现尿蛋白标记物深度覆盖的必要前提。探究不同实验方法对尿液蛋白富集和尿蛋白质组的影响尤为重要。本研究采用超滤法、硝酸纤维素膜富集法和饱和硫酸铵沉淀法,等体积各处理5例健康志愿者和膀胱癌患者10 mL尿液样本,富集尿液蛋白,SDS-PAGE分离尿蛋白,比较不同方法纯化的效率;通过质谱分析,比较不同纯化方法的肽段鉴定效果,确定针对尿液蛋白质组蛋白的最佳富集方法。相对于超滤和硝酸纤维素膜富集法,饱和硫酸铵沉淀法成功地应用于健康人尿蛋白的富集和质谱检测,在保证回收蛋白质量的前提下,可减少高丰度白蛋白的干扰,富集更多低丰度蛋白,提高了质谱鉴定的灵敏度。综上所述,饱和硫酸铵提取尿蛋白的效果较好,该方法具有大规模处理尿液、提高蛋白质组学筛选临床诊断标记物研究的应用潜力。     

Sampling methods for NMR-based metabolomics of Staphylococcus aureus

To select an appropriate sampling method for comparison of metabolite profiles between planktonic and biofilm Staphylococcus aureus using NMR techniques, we evaluated three methods: quenching-centrifugation (QC), filtration-quenching (FQ) and filtration-quenching-lyophilization (FQL). We found differences in metabolite loss, yield, reproducibility and metabolite profile. QC caused severe metabolite leakage and possible decomposition of nucleotides. FQ achieved high yields and reproducibility, although it had the disadvantages of long filtration and rinse times before quenching. FQL resulted in a loss of a few metabolites and a lower yield due to lyophilization. Although the biomarkers discovered by each method were nearly the same and seemed insensitive to technical variances, we conclude that FQ is the most appropriate sampling method because of its high yield and reproducibility.     

Recovery of Protective Activity in Rabies Virus Vaccines Concentrated and Purified by Four Different Methods

Rabies vaccines concentrated by ultrafiltration, zinc acetate precipitation, ammonium sulfate precipitation, or aluminum phosphate gel adsorption were compared with respect to recovery of protective activity and purity, as measured by protective activity per mg of protein. Vaccine obtained by ammonium sulfate precipitation had a better recovery rate and a higher purity than those prepared by the other methods. Potent vaccines were also obtained by the zinc acetate precipitation and aluminum phosphate gel adsorption methods, whereas ultrafiltration was the least satisfactory method from the standpoint of vaccine purity. Chromatography of virus concentrated by ultrafiltration on a cellulose ion exchange column reduced the level of nonviral proteins. The protective activity data obtained for the vaccines examined in these experiments were found to correlate with the vaccine's complement fixation titer per mg of protein.     

Different techniques for urinary protein analysis of normal and lung cancer patients

Many components in urine are useful in clinical diagnosis and urinary proteins are known as important components to define many diseases such as proteinuria, kidney, bladder and urinary tract diseases. In this study, we focused on the comparison of different sample preparation methods for isolating urinary proteins prior to protein analysis of pooled healthy and lung cancer patient samples. Selective method was used for preliminary investigation of some putative urinary protein markers. Urine samples were passed first through a gel filtration column (PD-10 desalting column) to remove high salts and subsequently concentrated. Remaining interferences were removed by ultrafiltration or four precipitation methods. The analysis of urinary proteins by high-performance liquid chromatography and sodium dodecyl sulfate-polyacrylamide gel electrophoresis showed many similarities in profiles among preparation methods and a few profiles were different between normal and lung cancer patients. In contrast, the results of two-dimensional gel electrophoresis (2-DE) showed more distinctly different protein patterns. Our finding showed that the sequential preparation of urinary proteins by gel filtration and ultrafiltration could retain most urinary proteins which demonstrated the highest protein spots on 2-D gels and able to identify preliminary urinary protein markers related to cancer. Although sequential preparation of urine samples by gel filtration and protein precipitation resulted in low amounts of proteins on 2-D gels, high Mr proteins were easily detected. Therefore, there are alternative choices for urine sample preparation for studying the urinary proteome and identifying urinary protein markers important for further preclinical diagnostic and therapeutic applications.     

硝酸纤维膜和丙酮沉淀尿蛋白质保存方法的比较

硝酸纤维膜法是一种简单、快速、经济的尿液蛋白质保存方法,但其与传统尿液蛋白质丙酮沉淀方法的差异有待进一步研究。相同尿液分别经硝酸纤维膜法和丙酮沉淀法制备尿蛋白质,经液相串联质谱分析鉴定蛋白质,采用谱图数定量,研究两种不同方法的差别。结果显示硝酸纤维膜法和丙酮沉淀法鉴定蛋白质数目几乎相同,鉴定蛋白质在谱图数的分布上几乎相同,鉴定蛋白质在蛋白质变异系数的分布上也几乎相同。因此,硝酸纤维膜法处理尿蛋白质与丙酮沉淀法基本一致,可以应用于大规模临床尿液样本的保存。     

Quantitative Proteomics and Metabolomics Analysis of Normal Human Cerebrospinal Fluid Samples*

The analysis of cerebrospinal fluid (CSF) is used in biomarker discovery studies for various neurodegenerative central nervous system (CNS) disorders. However, little is known about variation of CSF proteins and metabolites between patients without neurological disorders. A baseline for a large number of CSF compounds appears to be lacking. To analyze the variation in CSF protein and metabolite abundances in a number of well-defined individual samples of patients undergoing routine, non-neurological surgical procedures, we determined the variation of various proteins and metabolites by multiple analytical platforms. A total of 126 common proteins were assessed for biological variations between individuals by ESI-Orbitrap. A large spread in inter-individual variation was observed (relative standard deviations [RSDs] ranged from 18 to 148%) for proteins with both high abundance and low abundance. Technical variation was between 15 and 30% for all 126 proteins. Metabolomics analysis was performed by means of GC-MS and nuclear magnetic resonance (NMR) imaging and amino acids were specifically analyzed by LC-MS/MS, resulting in the detection of more than 100 metabolites. The variation in the metabolome appears to be much more limited compared with the proteome: the observed RSDs ranged from 12 to 70%. Technical variation was less than 20% for almost all metabolites. Consequently, an understanding of the biological variation of proteins and metabolites in CSF of neurologically normal individuals appears to be essential for reliable interpretation of biomarker discovery studies for CNS disorders because such results may be influenced by natural inter-individual variations. Therefore, proteins and metabolites with high variation between individuals ought to be assessed with caution as candidate biomarkers because at least part of the difference observed between the diseased individuals and the controls will not be caused by the disease, but rather by the natural biological variation between individuals.The analysis of CSF¹ is indispensable in the diagnosis and understanding of various neurodegenerative CNS disorders (1–3). CSF is a fluid that has different functions, such as the protection of the brain from outside forces, transport of biological substances, and excretion of toxic and waste substances. It is in close contact with the extracellular fluid of the brain. Therefore, the composition of CSF can reflect biological processes of the brain (4). By discovering the characterization of the proteome and metabolome of CSF we may gain better insight on the pathogenesis of CNS disorders. This would be significant because, for many of these disorders, the etiology is still unclear.CSF is produced in the ventricles of the brain and in the subarachnoidal spaces. Humans normally produce around 500 mL of CSF each day, and the total volume of CSF at a given time is approximately 150 mL. CSF reflects the composition of blood plasma, although the concentrations of most proteins and metabolites in CSF are lower. However, individual proteins and metabolites can act differently. Active transport from blood and secretion from the brain contribute to the specific composition of CSF. This composition can be disturbed in neurological disorders (5–6). Since CNS-specific proteins and metabolites are typically low in abundance compared with their levels in blood, this change in composition is more likely to be found in CSF because in blood the more abundant plasma proteins can completely mask the signal of the less abundant proteins. Also, if the disease markers do not cross the blood-brain-barrier, then the CSF is the only viable biofluid source. Therefore, CSF might be an excellent source for biomarker discovery for CNS disorders if we follow the hypothesis that neurological diseases induce alterations in CSF protein and metabolite levels.Analysis of metabolites in CSF has been common practice in clinical chemistry for decades to analyze biomarkers for inborn errors of metabolism. The approaches used are either metabolite profiling of CSF using NMR (7), or targeted analysis of one or a few metabolites using specific analytical methods (8). Metabolomics includes the analysis of metabolites in biofluids by NMR or MS-based approaches, i.e. LC-MS or GC-MS. Several metabolite profiling studies were performed on CSF using NMR, some of which were published only recently (9,10). Surprisingly, very few metabolomics studies using MS-based methods have been performed on CSF to date (11,12). One of the reasons is the fact that the human CSF metabolome has not yet been characterized very well. Many CSF metabolites remain unidentified, and for those that have been identified there is not much known about normal concentration ranges. A systematic categorization of the CSF metabolome is necessary and expected to be beneficial for future biomarker discoveries. Recently, Wishart et al. made a good start in exploring the human CSF metabolome with their computer-aided literature survey that resulted in 308 detectable metabolites in human CSF (13).The CSF proteome has been characterized to a much larger extent than the CSF metabolome and is currently the topic of investigations in several research groups worldwide. Recently, studies have been published with numerous identities and quantities of CSF proteins. Pan and co-workers were able to identify 2,594 proteins in well-characterized pooled human CSF samples using strict proteomics criteria with a combination of linear trap quadrupole LTQ-FT (Thermo Fisher Scientific, Bremen, Germany) and MALDI TOF/TOF equipment (14). They were also able to quantify several proteins using a targeted LC MALDI TOF/TOF approach (15). Hu et al. have studied the intra- and inter-individual variation in human CSF and found large variations in protein concentrations in six patients by means of two dimensional–gel electrophoresis (16), focusing mainly on the variations within individuals at two different time-points. Although only a limited number of proteins was analyzed, the variation between the time-points was profound, exceeding 200% for seven proteins.Unique CSF biomarkers may contribute to a deeper understanding of the mechanisms of CNS disorders. However, for this assumption to come true, there are still challenges ahead. Although CSF is not as complex as blood (almost missing the cellular part and the clotting system present in blood), it is expected to consist of thousands of organic- and non-organic salts, sugars, lipids, and proteins. A large part of the CSF consists of a few highly abundant metabolites and proteins, which hamper, if no precautions are undertaken, the identification and quantification of metabolites and proteins that occur in lower amounts. The analysis of the CSF metabolome is complicated because of the diverse chemical nature of metabolites and the lower concentration of metabolites compared with blood. Analytical method development is still required because it is not possible to identify the entire range of CSF metabolites with one single analytical method. Although in proteome research efforts have been made to quantify proteins, metabolomics studies up to now either do not provide quantitative information or they only give information for the most abundant metabolites.Another challenge is the sample amount obtained by lumbar puncture to collect CSF. Lumbar puncture is an invasive method that is not performed as frequently as blood sampling. However, often after the analysis of various clinical parameters, only a limited amount of CSF sample is available for biomarker discovery. Metabolomics studies are hampered by limited CSF sample amount. Therefore, analytical methods are required that are suitable to handle relatively small sample volumes.The main objectives of this study were (1) to analyze the variation in CSF protein and metabolite abundances in a number of well-defined individual samples by multiple analytical platforms; and (2) to integrate metabolomics and proteomics to present biological variations in metabolite and protein abundances and compare these with technical variations with the currently used analytical methods. The results will facilitate and increase the application of CSF for future biomarker discovery studies in the field of neurodegenerative diseases and neuro-oncology.     

Metabolomic Analysis of Rat Brain by High Resolution Nuclear Magnetic Resonance Spectroscopy of Tissue Extracts

Studies of gene expression on the RNA and protein levels have long been used to explore biological processes underlying disease. More recently, genomics and proteomics have been complemented by comprehensive quantitative analysis of the metabolite pool present in biological systems. This strategy, termed metabolomics, strives to provide a global characterization of the small-molecule complement involved in metabolism. While the genome and the proteome define the tasks cells can perform, the metabolome is part of the actual phenotype. Among the methods currently used in metabolomics, spectroscopic techniques are of special interest because they allow one to simultaneously analyze a large number of metabolites without prior selection for specific biochemical pathways, thus enabling a broad unbiased approach. Here, an optimized experimental protocol for metabolomic analysis by high-resolution NMR spectroscopy is presented, which is the method of choice for efficient quantification of tissue metabolites. Important strengths of this method are (i) the use of crude extracts, without the need to purify the sample and/or separate metabolites; (ii) the intrinsically quantitative nature of NMR, permitting quantitation of all metabolites represented by an NMR spectrum with one reference compound only; and (iii) the nondestructive nature of NMR enabling repeated use of the same sample for multiple measurements. The dynamic range of metabolite concentrations that can be covered is considerable due to the linear response of NMR signals, although metabolites occurring at extremely low concentrations may be difficult to detect. For the least abundant compounds, the highly sensitive mass spectrometry method may be advantageous although this technique requires more intricate sample preparation and quantification procedures than NMR spectroscopy. We present here an NMR protocol adjusted to rat brain analysis; however, the same protocol can be applied to other tissues with minor modifications.     

A new view of the bacterial cytosol environment

The cytosol is the major environment in all bacterial cells. The true physical and dynamical nature of the cytosol solution is not fully understood and here a modeling approach is applied. Using recent and detailed data on metabolite concentrations, we have created a molecular mechanical model of the prokaryotic cytosol environment of Escherichia coli, containing proteins, metabolites and monatomic ions. We use 200 ns molecular dynamics simulations to compute diffusion rates, the extent of contact between molecules and dielectric constants. Large metabolites spend ～80% of their time in contact with other molecules while small metabolites vary with some only spending 20% of time in contact. Large non-covalently interacting metabolite structures mediated by hydrogen-bonds, ionic and π stacking interactions are common and often associate with proteins. Mg(2+) ions were prominent in NIMS and almost absent free in solution. Κ(+) is generally not involved in NIMSs and populates the solvent fairly uniformly, hence its important role as an osmolyte. In simulations containing ubiquitin, to represent a protein component, metabolite diffusion was reduced owing to long lasting protein-metabolite interactions. Hence, it is likely that with larger proteins metabolites would diffuse even more slowly. The dielectric constant of these simulations was found to differ from that of pure water only through a large contribution from ubiquitin as metabolite and monatomic ion effects cancel. These findings suggest regions of influence specific to particular proteins affecting metabolite diffusion and electrostatics. Also some proteins may have a higher propensity for associations with metabolites owing to their larger electrostatic fields. We hope that future studies may be able to accurately predict how binding interactions differ in the cytosol relative to dilute aqueous solution.     

Proteins and metabolites fingerprints of gestational diabetes mellitus forming protein–metabolite interactomes are its potential biomarkers

Gestational diabetes mellitus (GDM) is a consequence of glucose intolerance with an inadequate production of insulin that happens during pregnancy and leads to adverse health consequences for both mother and fetus. GDM patients are at higher risk for preeclampsia, and developing diabetes mellitus type 2 in later life, while the child born to GDM mothers are more prone to macrosomia, and hypoglycemia. The universally accepted diagnostic criteria for GDM are lacking, therefore there is a need for a diagnosis of GDM that can identify GDM at its early stage (first trimester). We have reviewed the literature on proteins and metabolites fingerprints of GDM. Further, we have performed protein–protein, metabolite–metabolite, and protein–metabolite interaction network studies on GDM proteins and metabolites fingerprints. Notably, some proteins and metabolites fingerprints are forming strong interaction networks at high confidence scores. Therefore, we have suggested that those proteins and metabolites that are forming protein–metabolite interactomes are the potential biomarkers of GDM. The protein–metabolite biomarkers interactome may help in a deep understanding of the prognosis, pathogenesis of GDM, and also detection of GDM. The protein–metabolites interactome may be further applied in planning future therapeutic strategies to promote long-term health benefits in GDM mothers and their children.     

Hydrolysis of Soybean Proteins with Kamchatka Crab Hepatopancreas Enzyme Complex

To perform hydrolysis with the enzyme complex from the hepatopancreas of the Kamchatka crab, a protein mixture was isolated from soybean meal by extraction at alkaline pH values. Extractable low-molecular impurities were removed by ultrafiltration and precipitation of proteins with alcohol. The amino acid composition of the obtained protein extract turned out to be similar to the composition of the fish meal traditionally used in the production of fish feeds. Analysis of the products of fermentolysis by DDS-electrophoresis, HPLC, and mass spectrometry showed a high degree of hydrolysis of soybean proteins. Depending on the time of fermentolysis, the hydrolysates contained up to 60% (18 h of hydrolysis) of free amino acids (the fraction of the weight of the hydrolyzed protein mixture) and short peptides (2–20 amino acid residues).     

A multi-analytical platform approach to the metabonomic analysis of plasma from normal and Zucker (fa/fa) obese rats

Plasma obtained from 20 week old normal Wistar-derived and Zucker (fa/fa) rats was analysed using a number of different analytical methodologies to obtain global metabolite profiles as part of metabonomic investigations of animal models of diabetes. Samples were analysed without sample pre-treatment using 1H NMR spectroscopy, after acetonitrile solvent protein precipitation by ultra-performance liquid chromatography-MS (UPLC-MS) and after acetonitrile protein precipitation and derivatisation for capillary gas chromatography-MS (GC-MS). Subsequent data analysis using principal components analysis revealed that all three analytical platforms readily detected differences between the plasma metabolite profiles of the two strains of rat. There was only limited overlap between the metabolites detected by the different methodologies and the combination of all three methods of metabolite profiling therefore provided a much more comprehensive profile than would have been provided by their use individually.     

Sample preparation and bioinformatics in MALDI profiling of urinary proteins

One of the challenges of current proteomics research is identifying healthy and diseased mass spectrometric (MS) patterns within biological fluids. As a result, sample preparation methodologies, as well as the mathematical tools utilized for MS data analysis become pivotal. This study involves a thorough evaluation of the reproducibility and protein resolution that various urinary protein preparation methodologies provide in MALDI MS analysis. Several precipitation approaches, ultrafiltration, as well as direct dilution of urine in MALDI MS compatible buffers were applied in combination to a thorough bioinformatics analysis of the generated MS data. Our results indicate that ultrafiltration, as well as direct dilution of urine in TFA, can provide information rich and reproducible spectra for mass ranges up to 20 kDa. The importance of the presence of peak reproducibility filters when generating disease classification models is suggested.     

Towards a high resolution separation of human cerebrospinal fluid

Human cerebrospinal fluid is an ultrafiltrate of plasma that is largely produced by the choroid plexus. It consists of a mixture of anorganic salts, various sugars, lipids and proteins from the surrounding brain tissues. The predominant proteins in cerebrospinal fluid are isoforms of serum albumin, transferrin and immunoglobulins, representing more than 70% of the total protein amount. A rough overview of the protein compounds of human cerebrospinal fluid including their respective concentrations is given by Blennow et al. [Eur. Neurol. 33 (1993) 129]. In contrast, the aim of this work is to display the detailed protein composition of CSF by two-dimensional gel electrophoresis and to identify both high and low concentrated proteins using different mass spectrometry techniques. This extensive overview of proteins in human cerebrospinal fluid will be highly relevant for clinical research. Furthermore, the comparison of 2D gels will help to analyze the standard protein variability in CSF of healthy persons and detect specific protein variations of patients with various neurological diseases (e.g., Alzheimer's disease, Huntington's chorea). Sample preparation for two-dimensional gel electrophoresis must include concentration and desalting steps such as precipitation and ultrafiltration due to the high amount of salts, sugars and lipids and the low total amount of protein of 0.3-0.7 microg/microl present in human CSF. Up to now we were able to identify more than 480 spots from suchlike generated 2D gels using MALDI- and ESI-mass spectrometry.     

Enhanced Human Tissue Microdialysis Using Hydroxypropyl-?-Cyclodextrin as Molecular Carrier

Microdialysis sampling of lipophilic molecules in human tissues is challenging because protein binding and adhesion to the membrane limit recovery. Hydroxypropyl-ß-cyclodextrin (HP-ß-CD) forms complexes with hydrophobic molecules thereby improving microdialysis recovery of lipophilic molecules in vitro and in rodents. We tested the approach in human subjects. First, we determined HP-ß-CD influences on metabolite stability, delivery, and recovery in vitro. Then, we evaluated HP-ß-CD as microdialysis perfusion fluid supplement in 20 healthy volunteers. We placed 20 kDa microdialysis catheters in subcutaneous abdominal adipose tissue and in the vastus lateralis muscle. We perfused catheters with lactate free Ringer solution with or without 10% HP-ß-CD at flow rates of 0.3–2.0 µl/min. We assessed tissue metabolites, ultrafiltration effects, and blood flow. In both tissues, metabolite concentrations with Ringer+HP-ß-CD perfusate were equal or higher compared to Ringer alone. Addition of HP-ß-CD increased dialysate volume by 10%. Adverse local or systemic reactions to HP-ß-CD did not occur and analytical methods were not disturbed. HP-ß-CD addition allowed to measure interstitial anandamide concentrations, a highly lipophilic endogenous molecule. Our findings suggest that HP-ß-CD is a suitable supplement in clinical microdialysis to enhance recovery of lipophilic molecules from human interstitial fluid.     

Metabolomics and metabolite profiling — can we achieve the goal?

Deciphering of the plant metabolome is one of the most difficult analytical tasks in functional genomic research. Studies directed at the gene or protein expression are well established, sequencing analyses of these kinds of biopolymers on genome or proteome level are possible. This is not the case for metabolites, where identification in single sample of many chemical entities of different elemental composition and structures and various physicochemical properties is necessary. Different instrumental methods are applied for identification of metabolites but none of them allows obtaining unambiguous structural information about more than 500 compounds in single mixture (metabolite profiling). This is a much smaller number of metabolites than is predicted for single plant metabolome. However, instrumental approaches were proposed (metabolite fingerprinting) in which biochemical phenotype of an organism may be estimated, but identification of individual compounds is not possible.     

Global urinary metabolic profiling procedures using gas chromatography-mass spectrometry

The role of urinary metabolic profiling in systems biology research is expanding. This is because of the use of this technology for clinical diagnostic and mechanistic studies and for the development of new personalized health care and molecular epidemiology (population) studies. The methodologies commonly used for metabolic profiling are NMR spectroscopy, liquid chromatography mass spectrometry (LC/MS) and gas chromatography-mass spectrometry (GC/MS). In this protocol, we describe urine collection and storage, GC/MS and data preprocessing methods, chemometric data analysis and urinary marker metabolite identification. Results obtained using GC/MS are complementary to NMR and LC/MS. Sample preparation for GC/MS analysis involves the depletion of urea via treatment with urease, protein precipitation with methanol, and trimethylsilyl derivatization. The protocol described here facilitates the metabolic profiling of ～400-600 metabolites in 120 urine samples per week.     

Comprehensive proteomic analysis of human cervical-vaginal fluid using colposcopy samples

Background  

Cervical-vaginal fluid (CVF) plays an important role in the prevention of gynecological infections, although little is known about the contribution of CVF proteins to the immunity of the lower female genital tract. In order to analyze the protein composition of human CVF, we used CVF samples that are routinely collected during colposcopy, but are usually discarded. Since these samples are available in large quantities we aimed to analyze their usefulness for proteomics experiments. The samples were analyzed using different prefractionation techniques (ultrafiltration and C₄(RP)-LC protein separation) followed by C₁₈(RP)-LC peptide separation and identification by MALDI-TOF-TOF mass spectrometry. To determine the reproducibility of this proteomics platform we analyzed three technical replicates. Using spectral counting, protein abundances were estimated in a semiquantitative way. We also compared the results obtained in this study with those from previous studies derived from patients with different physiological conditions in order to determine an overlapping protein set.     

液质联用多反应监测法定量目标多肽或蛋白质

为建立优化的血浆内源性多肽提取方法,并且构建目标多肽和蛋白质的质谱定量方 法,本研究考察了超滤法、有机溶剂沉淀法和固相萃取法对血浆内源性多肽的提取效果 ,并通过Tricine-SDS-PAGE对提取效果进行比较.通过液相色谱串联质谱多反应监测 （MRM）分析,建立了多肽标准品ESAT-6定量方法,并将ESAT-6定量建立的液相色谱和质谱条件应用于蛋白质的定量,对多肽和蛋白质MRM定量的标准曲线进行了考 察.Tricine-SDS-PAGE结果表明,乙腈沉淀法是最佳的血浆内源性多肽提取方法,低分子量的多肽可以得到很好的富集,且能有效地去除高分子蛋白质的污染.液相色谱串联 质谱MRM法检测血浆内提取的多肽,标准曲线的线性较好,相关系数为0.999.另外,采 用MRM法对胶内分离的蛋白质进行定量,标准曲线的线性相关系数为0.995.综上所述, 本研究构建了一种简单有效的血浆多肽提取方法,通过液质联用MRM法成功地实现了目标多肽和蛋白质定量测定.该定量方法可以推广应用于复杂样品中的多肽和蛋白质的定 量分析.     

Identification and characterization of hADSC-derived exosome proteins from different isolation methods

Exosomes are secreted into the extracellular space by most cell types and contain various molecular constituents, which play roles in many biological processes. Adipose-derived mesenchymal stem cells (ADSCs) can differentiate into a variety of cell types and secrete a series of paracrine factors through exosomes. ADSC-derived exosomes have shown diagnostic and therapeutic potential in many clinical diseases. The molecular components are critical for their mechanisms. Several methods have been developed for exosome purification, including ultracentrifugation, ultrafiltration, density gradient purification, size-based isolation, polymer precipitation and immuno-affinity purification. Thus, we employed four methods to isolate exosomes from the hADSC culture medium, including ultracentrifugation, size exclusion chromatography, ExoQuick-TC precipitation and ExoQuick-TC ULTRA isolation. Following exosome isolation, we performed quantitative proteomic analysis of the exosome proteins using isobaric tags for relative and absolute quantification (iTRAQ) labelling, combined with 2D-LC-MS/MS. There were 599 universal and 138 stably expressed proteins in hADSC-derived exosomes. We proved that these proteins were potential hADSC-derived exosomes markers, including CD109, CD166, HSPA4, TRAP1, RAB2A, RAB11B and RAB14. From the quantitative proteomic analysis, we demonstrated that hADSC-derived exosome protein expression varied, with lipopolysaccharide (LPS) treatment, in the different isolation methods. Pathway analysis and proliferation, migration and endothelial tube formation assays showed varying effects in cells stimulated with hADSC-derived exosomes from different isolation methods. Our study revealed that different isolation methods might introduce variations in the protein composition in exosomes, which reflects their effects on biological function. The pros and cons of these methods are important points to consider for downstream research applications.