Analysis of mouse skin reveals proteins that are altered in a diet-induced diabetic state: a new method for detection of type 2 diabetes

In this study, proteomic analysis was performed on the skin of C57BL/6J mice with type 2 diabetes and compared to nondiabetic controls. To induce obesity and subsequent diabetes, mice were placed on a high-fat diet for 16 wk. After 16 wk, both diabetic and nondiabetic control mice were sacrificed and their skin removed for analysis. Following 2-DE, proteomic profiles from the skin samples were quantified using PDQuest software. Out of more than 1000 distinct protein spots, 28 were shown to be significantly altered with 6 being decreased and 22 increased in the diabetic state compared to controls. The 28 protein spots were removed from the gels and analyzed by MALDI-TOF and MS/MS analyses. Protein identifications revealed that 17 of the 28 proteins were involved in energy metabolism (60.7% of changes observed). Collectively, none of the significantly altered proteins had been shown previously to be altered in diabetic skin. This study not only helps to identify proteins found in skin samples of obese mice with type 2 diabetes, but also shows that skin biopsies coupled with proteomic analysis may be useful as a noninvasive method for the diagnosis of hyperinsulinemia and diabetes.     

Proteomic methodological recommendations for studies involving human plasma, platelets, and peripheral blood mononuclear cells

This study was designed to develop, optimize and validate protocols for blood processing prior to proteomic analysis of plasma, platelets and peripheral blood mononuclear cells (PBMC) and to determine analytical variation of a single sample of depleted plasma, platelet and PBMC proteins within and between four laboratories each using their own standard operating protocols for 2D gel electrophoresis. Plasma depleted either using the Beckman Coulter IgY-12 proteome partitioning kit or the Amersham albumin and IgG depletion columns gave good quality gels, but reproducibility appeared better with the single-use immuno-affinity column. The use of the Millipore Filter Device for protein concentration gave a 16% ( p < 0.005) higher recovery of protein in flow-through sample compared with acetone precipitation. The use of OptiPrep gave the lowest level of platelet contamination (1:0.8) during the isolation of PBMC from blood. Several proteins (among which are alpha-tropomyosin, fibrinogen and coagulation factor XIII A) were identified that may be used as biomarkers of platelet contamination in future studies. When identifying preselected spots, at least three out of the four centers found similar identities for 10 out of the 10 plasma proteins, 8 out of the 10 platelet proteins and 8 out of the 10 PBMC proteins. The discrepancy in spot identifications has been described before and may be explained by the mis-selection of spots due to laboratory-to-laboratory variation in gel formats, low scores on the peptide analysis leading to no or only tentative identifications, or incomplete resolution of different proteins in what appears as a single abundant spot. The average within-laboratory coefficient of variation (CV) for each of the matched spots after automatic matching using either PDQuest or ProteomWeaver software ranged between 18 and 69% for depleted plasma proteins, between 21 and 55% for platelet proteins, and between 22 and 38% for PBMC proteins. Subsequent manual matching improved the CV with on average between 1 and 16%. The average between laboratory CV for each of the matched spots after automatic matching ranged between 4 and 54% for depleted plasma proteins, between 5 and 60% for platelet proteins, and between 18 and 70% for PBMC proteins. This variation must be considered when designing sufficiently powered studies that use proteomics tools for biomarker discovery. The use of tricine in the running buffer for the second dimension appears to enhance the resolution of proteins especially in the high molecular weight range.     

苹果属植物树皮组织总蛋白提取及分离方法的建立

为了建立适于苹果属植物树皮组织总蛋白提取的技术方法, 以8年生华月苹果(Malus domestica)树枝条为试材, 通过比较不同提取方法(TCA-丙酮沉淀法(A)、甲醇/醋酸铵沉淀法(B)和改良的Tris-酚抽提方法(C))并优化提取条件, 确立了最适提取及分离方法为改良的Tris-酚抽提方法。在2-DE分离时, 该方法所获得的样品图谱中蛋白点总数为993个, 明显多于TCA-丙酮沉淀(418个)和甲醇醋酸铵沉淀(674个)方法, 并且与其它两种方法相比, 该方法获得的图谱背景更清晰, 蛋白点聚焦效果更好。此外, 经过3个梯度上样量的图谱分离效果比较, 确定了800 μg为本研究中2-DE分析的理想上样量。另外, 为了验证该提取及分离方法的可行性, 进一步对蛋白质表达谱中的部分蛋白点进行了质谱分析, 且这些蛋白点均得到了成功鉴定。该研究通过优化总蛋白提取方法及样品上样量等条件, 获得了理想的双向电泳分离图谱, 为苹果属植物树皮组织材料的蛋白质组学研究奠定了基础。     

Verification of single-peptide protein identifications by the application of complementary database search algorithms.

Data produced from the MudPIT analysis of yeast (S. cerevisiae) and rice (O. sativa) were used to develop a technique to validate single-peptide protein identifications using complementary database search algorithms. This results in a considerable reduction of overall false-positive rates for protein identifications; the overall false discovery rates in yeast are reduced from near 25% to less than 1%, and the false discovery rate of yeast single-peptide protein identifications becomes negligible. This technique can be employed by laboratories utilizing a SEQUEST-based proteomic analysis platform, incorporating the XTandem algorithm as a complementary tool for verification of single-peptide protein identifications. We have achieved this using open-source software, including several data-manipulation software tools developed in our laboratory, which are freely available to download.     

Proteome analysis of barley seeds: Identification of major proteins from two-dimensional gels (pI 4-7)

Germination of monocotyledonous plants involves activation and de novo synthesis of enzymes that degrade cell walls and starch and mobilize stored endosperm reserves for embryo growth. Two-dimensional (2-D) gel electrophoresis and mass spectrometry were applied to identify major water-soluble proteins in extracts of mature barley (Hordeum vulgare) seeds and to follow their fate during germination. About 1200 and 600 spots of pI 4-7 were detected on 2-D gels by silver staining and colloidal Coomassie Brilliant Blue staining, respectively. About 300 spots were selected for in-gel digestion followed by matrix-assisted laser desorption/ionization-mass spectrometry-peptide map fingerprint analysis. Database searches using measured peptide masses resulted in 198 identifications of 103 proteins in 177 spots. These include housekeeping enzymes, chaperones, defence proteins (including enzyme inhibitors), and proteins related to desiccation and oxidative stress. Sixty-four of the identifications were made using expressed sequence tags (ESTs). Numerous spots in the 2-D gel pattern changed during germination (micromalting) and an intensely stained area which contained large amounts of the serpin protein Z appeared centrally on the 2-D gel. Spots containing alpha-amylase also appeared. Identification of 22 spots after three days of germination represented 13 different database entries and 11 functions including hydrolytic enzymes, chaperones, housekeeping enzymes, and inhibitors.     

2-D DIGE analysis of the budding yeast pH 6-11 proteome in meiosis

Meiosis is the cell division that generates haploid gametes from diploid precursors. To provide insight into the functional proteome of budding yeast during meiosis, a 2-D DIGE kinetic approach was used to study proteins in the pH 6-11 range. Nearly 600 protein spots were visualised and 79 spots exhibited statistically significant changes in abundance as cells progressed through meiosis. Expression changes of up to 41-fold were detected and protein sequence information was obtained for 48 spots. Single protein identifications were obtained for 21 spots including different gel mobility forms of 5 proteins. A large number of post-translational events are suggested for these proteins, including processing, modification and import. The data are incorporated into an online 2-DE map of meiotic proteins in budding yeast, which extends our initial DIGE investigation of proteins in the pH 4-7 range. Together, the analyses provide peptide sequence data for 84 protein spots, including 50 single-protein identifications and gel mobility isoforms of 8 proteins. The largest classes of identified proteins include carbon metabolism, protein catabolism, protein folding, protein synthesis and the oxidative stress response. A number of the corresponding genes are required for yeast meiosis and recent studies have identified similar classes of proteins expressed during mammalian meiosis. This proteomic investigation and the resulting protein reference map make an important contribution towards a more detailed molecular view of yeast meiosis.     

2‐D PAGE and MS analysis of proteins from formalin‐fixed,paraffin‐embedded tissues

In the past decade, encouraging results have been obtained in extraction and analysis of proteins from formalin‐fixed, paraffin‐embedded (FFPE) tissues. However, 2‐D PAGE protein maps with satisfactory proteomic information and comparability to fresh tissues have never been described to date. In the present study, we report 2‐D PAGE separation and MS identification of full‐length proteins extracted from FFPE skeletal muscle tissue. The 2‐D protein profiles obtained from FFPE tissues could be matched to those achieved from frozen tissues replicates. Up to 250 spots were clearly detected in 2‐D maps of proteins from FFPE tissue following standard mass‐compatible silver staining. Protein spots from both FFPE and frozen tissue 2‐D gels were excised, subjected to in situ hydrolysis, and identified by MS analysis. Matched spots produced matched protein identifications. Moreover, 2‐D protein maps from FFPE tissues were successfully subjected to Western immunoblotting, producing comparable results to fresh‐frozen tissues. In conclusion, this study provides evidence that, when adequately extracted, full‐length proteins from FFPE tissues might be suitable to 2‐D PAGE‐MS analysis, allowing differential proteomic studies on the vast existing archives of healthy and pathological‐fixed tissues.     

Using standard positions and image fusion to create proteome maps from collections of two-dimensional gel electrophoresis images

Databases for two-dimensional protein gels pose new challenges in extracting meaningful information from large numbers of experiments. In order to create expression profiles, positions of corresponding protein spots across all gel images have to be established. In larger gel sets errors may accumulate rapidly during this spot matching process, effectively limiting the number of samples available for data mining. Here we present a novel approach for organizing spot data based on the concept of a standard position for a protein species. Standard positions are meaningful average positions that are determined using all occurrences of a protein species. They can be extended to spots that are not annotated via interpolation. The standard position of a spot can serve as a unifying index across all gels in a database, thus allowing creation and analysis of expression profiles that span the whole collection. The standard position gives a much more accurate estimation of a spot's position on a gel than can be obtained using theoretical isoelectric point and molecular weight. Positional indexing is a complement to a priori identifications (e.g. by mass spectrometry or Edman degradation). Moreover it can be used in advance to select spots that are worth identifying because they show relevant expression profiles. Furthermore, we show how to combine all spots that occur on any of the gels into one synthetic but nevertheless realistic-looking image. This composite image is produced such that all spots have their standard positions. It can serve as a proteome reference map for an organism. As an application, we have computed a reference map from 23 gel images of Bacillus subtilis, using an enhanced prerelease version of the gel analysis software Delta2D (DECODON, Greifswald, Germany).     

Characterization of metaproteomics in crop rhizospheric soil

Soil rhizospheric metaproteomics is a powerful scientific tool to uncover the interactions between plants and microorganisms in the soil ecosystem. The present study established an extraction method suitable for different soils that could increase the extracted protein content. Close to 1000 separate spots with high reproducibility could be identified in the stained 2-DE gels. Among the spots, 189 spots representing 122 proteins on a 2-DE gel of rice soil samples were successfully identified by MALDI-TOF/TOF-MS. These proteins mainly originated from rice and microorganisms. They were involved in protein, energy, nucleotide, and secondary metabolisms, as well as signal transduction and resistance. Three characteristics of the crop rhizospheric metaproteomics seemed apparent: (1) approximately one-third of the protein spots could not be identified by MALDI-TOF/TOF/MS, (2) the conservative proteins from plants formed a feature distribution of crop rhizospheric metaproteome, and (3) there were very complex interactions between plants and microorganisms existing in a crop rhizospheric soil. Further functional analysis on the identified proteins unveiled various metabolic pathways and signal transductions involved in the soil biotic community. This study provides a paradigm for metaproteomic research on soil biology.     

RT-SVR+q: a strategy for post-Mascot analysis using retention time and q value metric to improve peptide and protein identifications

Shotgun proteomics commonly utilizes database search like Mascot to identify proteins from tandem MS/MS spectra. False discovery rate (FDR) is often used to assess the confidence of peptide identifications. However, a widely accepted FDR of 1% sacrifices the sensitivity of peptide identification while improving the accuracy. This article details a machine learning approach combining retention time based support vector regressor (RT-SVR) with q value based statistical analysis to improve peptide and protein identifications with high sensitivity and accuracy. The use of confident peptide identifications as training examples and careful feature selection ensures high R values (>0.900) for all models. The application of RT-SVR model on Mascot results (p=0.10) increases the sensitivity of peptide identifications. q Value, as a function of deviation between predicted and experimental RTs (ΔRT), is used to assess the significance of peptide identifications. We demonstrate that the peptide and protein identifications increase by up to 89.4% and 83.5%, respectively, for a specified q value of 0.01 when applying the method to proteomic analysis of the natural killer leukemia cell line (NKL). This study establishes an effective methodology and provides a platform for profiling confident proteomes in more relevant species as well as a future investigation of accurate protein quantification.     

Evaluation of sample extraction methods for proteomic analysis of coniferous seeds

In this study, three methods of protein extraction from the seeds of the Chinese fir were compared by examining the quality (including the number of protein spots observed) in the two-dimensional gel electrophoresis (2-DE), obtained by isoelectric focusing and sodium dodecyl sulfate polyacrylamide gel electrophoresis of the total released protein. Three protein extraction methods were: TCA-acetone precipitation, SDS extraction/acetone precipitation, and phenol extraction methanol/ammonium acetate precipitation. The results showed that TCA-acetone precipitation was the most effective method for protein extraction; it gave the highest yield of total protein (8.9 mg protein per g seed weight) and the greatest number of proteins spots (1,034 spots) on the 2-DE gel. Further, several proteins were identified by liquid chromatography mass spectrometry (LC MS/MS), which are legumin-like storage protein, similar to AMP binding/acetate-CoA ligase, similar to 40S ribosomal protein S20, actin, ascorbate peroxidase, Similar to cysteine synthase, and unknown protein. These data demonstrates that TCA-acetone precipitation followed by 2-DE and LC MS/MS is a suitable method for proteomic analysis of coniferous species, such as Chinese fir and provides a valuable starting point for similar proteomic analysis of other coniferous tree species.     

不同提取方法及上样量对牡丹试管苗茎基部蛋白双向电泳的影响

为建立一套适合于牡丹试管苗茎基部蛋白的双向电泳技术,以便更好地利用蛋白质组技术研究牡丹试管苗不定根的发生机理,本研究比较了三种不同蛋白质提取方法对双向电泳结果的影响,并在蛋白质上样量方面进行了比较。结果表明,乙酸铵/甲醇酚提取法所得2-DE图谱的蛋白点很少,仅检测到45个,且较模糊,有明显的拖尾现象,分辨率很低;乙醇/乙醚丙酮法所得的蛋白点也较少(101个),较模糊,且横竖纹干扰较大;三氯乙酸/丙酮法所得蛋白点数较多,可检测到434个清晰的蛋白点,且形状规则,重复性好,适合后续分析,操作也较为简便。用三氯乙酸/丙酮法提取蛋白,采用800μg、1000μg和1200μg三个不同的上样量进行双向电泳,在上样量为1200μg时(IPGpH3～10,24cm),蛋白质在12%SDS-PAGE胶上得到了较好的分离,在2-DE图谱上可分辨出562个蛋白点。因此,三氯乙酸/丙酮法是较适合于牡丹试管苗茎基部蛋白质提取的方法,1200μg是较为合适的上样量。     

水稻稻瘟菌抗性相关蛋白的双向电泳分析

建立抗感水稻品种受稻瘟菌侵染和未侵染蛋白质的双向凝胶电泳图谱,分析其差异表达的蛋白,寻找稻瘟病的抗性相关蛋白,以阐明稻瘟病的发病机制。采用TCA/丙酮沉淀法提取四种愈伤组织材料的总蛋白并采用固相pH梯度( immobilized pH gradient, IPG)双向凝胶电泳( two-dimensional gel electrophshiya, oresis, 2-DE)分离四种材料总蛋白质, 凝胶经银染显色后,用PDQuest图像分析软件进行比较分析、识别差异表达的蛋白质。成功获得抗感水稻品种受稻瘟菌侵染和未侵染蛋白质的双向凝胶电泳图谱。获得未侵染内香优2号平均蛋白点数为447个,汕优63平均蛋白点数为440个;侵染后抗性品种内香优2号平均蛋白数为523个,感性品种汕优63平均蛋白质点数为326个。内香优2号未经侵染和侵染后图谱匹配率达 89%和 87%,汕优63未经侵染和侵染后图谱匹配率达86％和85％。内香优2号的差异表达蛋白点数为76个,汕优63的差异表达蛋白点数为114个。两者间存在一些差异表达的蛋白质,为阐明稻瘟病的发病机制打下了坚实的基础。     

Development of a Listeria monocytogenes EGDe partial proteome reference map and comparison with the protein profiles of food isolates

A partially annotated proteome reference map of the food pathogen Listeria monocytogenes was developed for exponentially growing cells under standardized, optimal conditions by using the sequenced strain EGDe (serotype 1/2a) as a model organism. The map was developed by using a reproducible total protein extraction and two-dimensional (2-D) polyacrylamide gel electrophoresis analysis procedure, and it contained 33 identified proteins representing the four main protein functional classes. In order to facilitate analysis of membrane proteins, a protein compartmentalization procedure was assessed. The method used provided partial fractionation of membrane and cytosolic proteins. The total protein 2-D profiles of three serotype 1/2a strains and one serotype 1/2b strain isolated from food were compared to the L. monocytogenes EGDe proteome. An average of 13% of the major protein spots in the food strain proteomes were not matched in the strain EGDe proteome. The variation was greater for the less intense spots, and on average 28% of these spots were not matched. Two of the proteins identified in L. monocytogenes EGDe were missing in one or more of the food isolates. These two proteins were proteins involved in the main glycolytic pathway and in metabolism of coenzymes and prosthetic groups. The two corresponding genes were found by PCR amplification to be present in the four food isolates. Our results show that the L. monocytogenes EGDe reference map is a valuable starting point for analyses of strains having various origins and could be useful for analyzing the proteomes of different isolates of this pathogen.     

Characterization of the rat liver membrane proteome using peptide immobilized pH gradient isoelectric focusing

Membrane proteins are of particular interest in proteomics because of their potential therapeutic utility. Past proteomic approaches used to investigate membrane proteins have only been partially successful at providing a comprehensive analysis due to the inherently hydrophobic nature and low abundance for some of these proteins. Recently, these difficulties have been improved by analyzing membrane protein enriched samples using shotgun proteomics. In addition, the recent application of methanol-assisted trypsin digestion of membrane proteins has been shown to be a method to improve membrane protein identifications. In this study, a comparison of different concentrations of methanol was assessed for assisting membrane protein digestion with trypsin prior to analysis using a gel-based shotgun proteomics approach called peptide immobilized pH gradient isoelectric focusing (IPG-IEF). We demonstrate the use of peptide IEF on pH 3-10 IPG strips as the first dimension of two-dimensional shotgun proteomics for protein identifications from the membrane fraction of rat liver. Tryptic digestion of proteins was carried out in varying concentrations of methanol in 10 mM ammonium bicarbonate: 0% (v/v), 40% (v/v), and 60% (v/v). A total of 800 proteins were identified from 60% (v/v) methanol, which increased the protein identifications by 17% and 14% compared to 0% (v/v) methanol and 40% (v/v) methanol assisted digestion, respectively. In total, 1549 nonredundant proteins were identified from all three concentrations of methanol including 690 (42%) integral membrane proteins of which 626 of these proteins contained at least one transmembrane domain. Peptide IPG-IEF separation of peptides was successful as the peptides were separated into discrete pI regions with high resolution. The results from this study prove utility of 60% (v/v) methanol assisted digestion in conjunction with peptide IPG-IEF as an optimal shotgun proteomics technique for the separation and identification of previously unreported membrane proteins.     

Global proteome discovery using an online three-dimensional LC-MS/MS

We have developed a proteomics technology featuring on-line three-dimensional liquid chromatography coupled to tandem mass spectrometry (3D LC-MS/MS). Using 3D LC-MS/MS, the yeast-soluble, urea-solubilized peripheral membrane and SDS-solubilized membrane protein samples collectively yielded 3019 unique yeast protein identifications with an average of 5.5 peptides per protein from the 6300-gene Saccharomyces Genome Database searched with SEQUEST. A single run of the urea-solubilized sample yielded 2255 unique protein identifications, suggesting high peak capacity and resolving power of 3D LC-MS/MS. After precipitation of SDS from the digested membrane protein sample, 3D LC-MS/MS allowed the analysis of membrane proteins. Among 1221 proteins containing two or more predicted transmembrane domains, 495 such proteins were identified. The improved yeast proteome data allowed the mapping of many metabolic pathways and functional categories. The 3D LC-MS/MS technology provides a suitable tool for global proteome discovery.     

Navigated laser capture microdissection as an alternative to direct histological staining for proteomic analysis of brain samples

Proteomic analysis of the brain is complicated by the need to obtain cells from specific anatomical regions, or nuclei. Laser capture microdissection (LCM) is a technique that is precise enough to dissect single cells within a tissue section, and thus could be useful for isolating specific brain nuclei for analysis. However, we and others have previously demonstrated that histological staining protocols used to guide LCM have detrimental effects on protein separation by two-dimensional electrophoresis (2-DE). Here we describe a new LCM method called navigated LCM. This microdissection method uses fixed but unstained tissue as starting material and thus enables us to avoid artifacts induced by tissue staining. By comparing 2-DE results obtained from fixed, unstained LCM brain tissue samples to those obtained from manually dissected samples, we demonstrated that this microdissection process gave similar protein recovery rates and similar resolution of protein spots on 2-DE gels. Moreover, matrix-assisted laser desorption/ionization-time of flight mass spectrometry analysis of selected spots from gels derived from control and fixed, LCM samples revealed that the fixation-LCM process had no effect on protein identification. Navigated LCM of tissue sections is therefore a practical and powerful method for performing proteomic studies in specifically defined brain regions.     

一种适合针刺活检样品的蛋白质组学分析方法

针刺活检样品是一种重要的临床组织样品,其蕴涵的蛋白质信息,对了解人类疾病极为重要.然而,由于该样品的体积极小,其研究受到很大限制.本文建立和优化了适合针刺活检样品的基于双向电泳的蛋白质组学分析平台：通过直接抽提获得针刺活检组织的蛋白质样品;用24 cm 固定梯度干胶条(pH 3-10NL)等电聚焦及12.5% SDS-PAGE分离获得蛋白质样品;感兴趣的蛋白质点经过胰酶酶解后用MALDI TOF/TOF质谱分析.运用所建立的平台对3例来自3只不同大鼠的肝脏针刺活检样品进行分析,获得了多于2500个蛋白质点的高重复性的二维凝胶银染图谱.应用该方法分析人前列腺针刺活检样品的蛋白质组,同样获得了高质量、高重复性的结果.其中随机选取的包括低丰度点在内的57个蛋白质点,经胰酶酶解后进行MALDI串联质谱分析,均获得了高确定性的鉴定结果.通过建立针刺活检样品的蛋白质组学分析方法,为研究人类疾病的分子机制提供了必要的前提保障.