Identification of flooding stress responsible cascades in root and hypocotyl of soybean using proteome analysis

Flooding inducible proteins were analyzed using a proteomic technique to understand the mechanism of soybean response to immersion in water. Soybeans were germinated for 2 days, and then subjected to flooding for 2 days. Proteins were extracted from root and hypocotyl, separated by two-dimensional polyacrylamide gel electrophoresis, stained by Coomassie brilliant blue, and analyzed by protein sequencing and mass spectrometry. Out of 803 proteins, 21 proteins were significantly up-regulated, and seven proteins were down-regulated by flooding stress. Of the total, 11 up-regulated proteins were classified as related to protein destination/storage and three proteins to energy, while four down-regulated proteins were related to protein destination/storage and three proteins to disease/defense. The expression of 22 proteins significantly changed within 1 day after flooding stress. The effects of flooding, nitrogen substitution without flooding, or flooding with aeration were analyzed for 1–4 days. The expression of alcohol dehydrogenase increased remarkably by nitrogen substitution compared to flooding. The expression of many proteins that changed due to flooding showed the same tendencies observed for nitrogen substitution; however, the expression of proteins classified into protein destination/storage did not.     

Evaluation of sample preparation methods for the analysis of papaya leaf proteins through two‐dimensional gel electrophoresis

Introduction – A variety of sample preparation protocols for plant proteomic analysis using two‐dimensional gel electrophoresis (2‐DE) have been reported. However, they usually have to be adapted and further optimised for the analysis of plant species not previously studied. Objective – This work aimed to evaluate different sample preparation protocols for analysing Carica papaya L. leaf proteins through 2‐DE. Methodology – Four sample preparation methods were tested: (1) phenol extraction and methanol–ammonium acetate precipitation; (2) no precipitation fractionation; and the traditional trichloroacetic acid–acetone precipitation either (3) with or (4) without protein fractionation. The samples were analysed for their compatibility with SDS–PAGE (1‐DE) and 2‐DE. Fifteen selected protein spots were trypsinised and analysed by matrix‐assisted laser desorption/ionisation time‐of‐flight tandem mass spectrometry (MALDI‐TOF‐MS/MS), followed by a protein search using the NCBInr database to accurately identify all proteins. Results – Methods number 3 and 4 resulted in large quantities of protein with good 1‐DE separation and were chosen for 2‐DE analysis. However, only the TCA method without fractionation (no. 4) proved to be useful. Spot number and resolution advances were achieved, which included having an additional solubilisation step in the conventional TCA method. Moreover, most of the theoretical and experimental protein molecular weight and pI data had similar values, suggesting good focusing and, most importantly, limited protein degradation. Conclusion – The described sample preparation method allows the proteomic analysis of papaya leaves by 2‐DE and mass spectrometry (MALDI‐TOF‐MS/MS). The methods presented can be a starting point for the optimisation of sample preparation protocols for other plant species. Copyright © 2009 John Wiley & Sons, Ltd.     

Proteomic analysis of acrylamide gel separated proteins immobilized on polyvinylidene difluoride membranes following proteolytic digestion in the presence of 80% acetonitrile

Two-dimensional polyacrylamide gel electrophoresis (2-D PAGE) combined with mass spectrometry (MS) is a highly accurate and sensitive means of identifying proteins. We have developed a novel method for digesting proteins on polyvinylidene difluoride (PVDF) membranes for subsequent matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) MS analysis. After Tricine sodium dodecyl sulfate (SDS)-PAGE, separated proteins were electroblotted onto PVDF membranes in a semidry discontinuous buffer system, visualized by staining with Coomassie Blue, excised, digested with trypsin or lysC in 80% acetonitrile, and then analyzed by MALDI-TOF MS. This method has several advantages over in-gel digestion in terms of sample handling, sensitivity, and time. We identified 105 fmol of Bacillus subtilis SecA and 100 approximately 500 fmol of standard proteins. We also analyzed the submembrane protein fraction solubilized by 1% n-dodecyl-beta-D-maltoside from B. subtilis membranes after separation by 2-D PAGE, and identified 116 protein spots. This method can detect proteins at the 10 approximately 50 fmol level by pooling more than ten identical electroblotted protein spots.     

Assessment of protein stability in cerebrospinal fluid using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry protein profiling

Recent studies have evaluated proper acquisition and storage procedures for the use of serum or plasma for mass spectrometry (MS)-based proteomics. The present study examines the proteome stability of human cerebrospinal fluid (CSF) over time at 23°C (room temperature) and 4°C using surface-enhanced laser desorption/ionization time-of-flight MS. Data analysis revealed that statistically significant differences in protein profiles are apparent within 4 h at 23°C and between 6 and 8 h at 4°C. Inclusion of protease and phosphatase inhibitor cocktails into the CSF samples failed to significantly reduce proteome alterations over time. We conclude that MS-based proteomic analysis of CSF requires careful assessment of sample collection procedures for rapid and optimal sample acquisition and storage.     

A rapid and simple procedure for the depletion of abundant storage proteins from legume seeds to advance proteome analysis: A case study using Glycine max

2‐D analysis of plant proteomes containing thousands of proteins has limited dynamic resolution because only abundant proteins can be detected. Proteomic assessment of the non‐abundant proteins within seeds is difficult when 60–80% is storage proteins. Resolution can be improved through sample fractionation using separation techniques based upon different physiological or biochemical principles. We have developed a fast and simple fractionation technique using 10 mM Ca²⁺ to precipitate soybean (Glycine max) seed storage globulins, glycinin and β‐conglycinin. This method removes 87±4% of the highly abundant seed proteins from the extract, allowing for 541 previously inconspicuous proteins present in soybean seed to be more detectable (volume increase of ≥50%) using fluorescent detection. Of those 541 enhanced spots, 197 increased more than 2.5‐fold when visualized with Coomassie. The majority of those spots were isolated and identified using peptide mass fingerprinting. Fractionation also provided detection of 63 new phosphorylated protein spots and enhanced the visibility of 15 phosphorylated protein spots, using 2‐D electrophoretic separation and an in‐gel phosphoprotein stain. Application of this methodology toward other legumes, such as peanut, bean, pea, alfalfa and others, also containing high amounts of storage proteins, was examined, and is reported here.     

Resurrexit, sicut dixit, alleluia. Snake venomics from a 26-year old polyacrylamide focusing gel

A 26-year-old dried polyacrylamide gel, cast in presence of an immobilized pH gradient and containing focused proteins from the venoms of a northern black-tailed rattlesnake (Crotalus molossus molossus), and of a western diamondback rattlesnake (Crotalus atrox) has been screened in order to see the feasibility of extracting the proteins, analyzing them by mass spectrometry (MS) and assessing their integrity. Nine gel bands were excised along the pH 3-10 gradient and the gel segments reswollen in warm acetonitrile. Upon digestion and MS analysis, all the bands could be identified and attributed to the respective venoms of the two rattlesnake species. Although a few peptides exhibited modified amino acids, the proteins were found to be well preserved even upon such a long storage at room temperature. The present data suggest the feasibility of identifying proteins from very old samples trapped in polyacrylamide gels, and analyzed in a pre-mass spectrometry era, thus of uncertain identity.     

Protein identification and quantification from riverbank grape,Vitis riparia: Comparing SDS‐PAGE and FASP‐GPF techniques for shotgun proteomic analysis

Protein sample preparation optimisation is critical for establishing reproducible high throughput proteomic analysis. In this study, two different fractionation sample preparation techniques (in‐gel digestion and in‐solution digestion) for shotgun proteomics were used to quantitatively compare proteins identified in Vitis riparia leaf samples. The total number of proteins and peptides identified were compared between filter aided sample preparation (FASP) coupled with gas phase fractionation (GPF) and SDS‐PAGE methods. There was a 24% increase in the total number of reproducibly identified proteins when FASP‐GPF was used. FASP‐GPF is more reproducible, less expensive and a better method than SDS‐PAGE for shotgun proteomics of grapevine samples as it significantly increases protein identification across biological replicates. Total peptide and protein information from the two fractionation techniques is available in PRIDE with the identifier PXD001399 ( http://proteomecentral.proteomexchange.org/dataset/PXD001399 ).     

厌氧产氢颗粒污泥蛋白质组分析样品的高效制备方法

【背景】厌氧产氢颗粒污泥比絮状产氢污泥具有更高的生物量、沉降性与反应效率,对颗粒污泥进行蛋白质组学研究,有助于揭示其代谢调控的分子机制,从而对厌氧代谢过程进行优化调控。目前关于产氢颗粒污泥蛋白质组分析样品制备方法的研究尚未见文献报道。革兰氏阳性菌Ethanoligenens harbinense YUAN-3是自凝集产氢发酵细菌,在间歇和连续流培养中可形成自聚集的厌氧颗粒,由于其全基因组信息清楚,可作为模式研究材料对制备方法进行评估。【目的】针对厌氧产氢颗粒污泥的蛋白质组学研究,比较不同蛋白质提取方法进行优化。【方法】分别利用液氮研磨、超声破碎、匀浆破碎对产氢颗粒污泥破碎,比较这3种方法对总蛋白提取量的影响;通过双向电泳比较三氯乙酸(Trichloroacetic acid,TCA)-丙酮沉淀法与苯酚抽提法对总蛋白提取效果的影响;对总蛋白样品分别进行同位素标记相对和绝对定量标记(Isobarictagsforrelativeandabsolutequantification,i TRAQ)、串联质谱标签(Tandemmasstag,TMT)标记以及质谱鉴定。【结果】液氮研磨、超声破碎、匀浆破碎3种破碎方法下总蛋白的提取量分别是对照样品的2.0、3.9与5.2倍。与TCA-丙酮沉淀法相比,苯酚抽提法总蛋白样品在双向电泳图谱上的蛋白质点明显增多,分布均匀,同时其在碱性蛋白端与小分子量蛋白端的蛋白质点也明显增多。质谱分析发现,iTRAQ标记样品与TMT标记样品中分别鉴定到1797个与1644个蛋白,在分子量、等电点、亚细胞定位的各个分布范围内,这些蛋白良好地覆盖了E.harbinenseYUAN-3中各个类型的蛋白。【结论】匀浆破碎与苯酚抽提法联用的总蛋白制备方法更适用于厌氧产氢颗粒污泥,该方法有利于后续的蛋白质双向电泳和定量蛋白质组质谱分析,可作为产氢颗粒污泥以及革兰氏阳性菌总蛋白制备的方法参考。     

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.     

多维蛋白鉴别技术分析天蓝色链霉菌膜内侧蛋白质组

链霉菌是一类具有重要工业价值和复杂调控机制的微生物,天蓝色链霉菌是这个属的模式菌。已报道天蓝色链霉菌的蛋白组学的研究多采用二维聚丙烯酰胺凝胶电泳与基质辅助激光解吸电离飞行时间质谱相结合的方法,但由于膜蛋白疏水性较强,天然丰度较低,此法得到的膜蛋白很少。用蛋白酶K保护/高pH蛋白酶K法制备链霉菌膜内侧蛋白组样品,并用多维蛋白鉴别技术进行分析,得到154个可能的膜内侧蛋白（包括膜内在蛋白和膜外周蛋白）,其中含跨膜区的膜内在蛋白44个,含3个以上跨膜区的膜内在蛋白有23个。此外,还鉴定了一批膜内侧蛋白的亲水性肽段及其在膜上的拓扑位置。该结果有助于对天蓝色链霉菌的膜蛋白进行拓扑学分类和功能研究。     

Analysis of proteomic changes in roots of soybean seedlings during recovery after flooding

A proteomic approach was used to identify proteins involved in post-flooding recovery in soybean roots. Two-day-old soybean seedlings were flooded with water for up to 3 days. After the flooding treatment, seedlings were grown until 7 days after sowing and root proteins were then extracted and separated using two-dimensional polyacrylamide gel electrophoresis (2-DE). Comparative analysis of 2-D gels of control and 3 day flooding-experienced soybean root samples revealed 70 differentially expressed protein spots, from which 80 proteins were identified. Many of the differentially expressed proteins are involved in protein destination/storage and metabolic processes. Clustering analysis based on the expression profiles of the 70 differentially expressed protein spots revealed that 3 days of flooding causes significant changes in protein expression, even during post-flooding recovery. Three days of flooding resulted in downregulation of ion transport-related proteins and upregulation of proteins involved in cytoskeletal reorganization, cell expansion, and programmed cell death. Furthermore, 7 proteins involved in cell wall modification and S-adenosylmethionine synthesis were identified in roots from seedlings recovering from 1 day of flooding. These results suggest that alteration of cell structure through changes in cell wall metabolism and cytoskeletal organization may be involved in post-flooding recovery processes in soybean seedlings.     

Identification of additional proteins in differential proteomics using protein interaction networks

In this study, we developed a novel computational approach based on protein–protein interaction networks to identify a list of proteins that might have remained undetected in differential proteomic profiling experiments. We tested our computational approach on two sets of human smooth muscle cell protein extracts that were affected differently by DNase I treatment. Differential proteomic analysis by saturation DIGE resulted in the identification of 41 human proteins. The application of our approach to these 41 input proteins consisted of four steps: (i) Compilation of a human protein–protein interaction network from public databases; (ii) calculation of interaction scores based on functional similarity; (iii) determination of a set of candidate proteins that are needed to efficiently and confidently connect the 41 input proteins; and (iv) ranking of the resulting 25 candidate proteins. Two of the three highest‐ranked proteins, beta‐arrestin 1, and beta‐arrestin 2, were experimentally tested, revealing that their abundance levels in human smooth muscle cell samples were indeed affected by DNase I treatment. These proteins had not been detected during the experimental proteomic analysis. Our study suggests that our computational approach may represent a simple, universal, and cost‐effective means to identify additional proteins that remain elusive for current 2D gel‐based proteomic profiling techniques.     

Discovery of biomarker candidates for coronary artery disease from an APOE-knock out mouse model using iTRAQ-based multiplex quantitative proteomics

Due to the lack of precise markers indicative of its occurrence and progression, coronary artery disease (CAD), the most common type of heart diseases, is currently associated with high mortality in the United States. To systemically identify novel protein biomarkers associated with CAD progression for early diagnosis and possible therapeutic intervention, we employed an iTRAQ‐based quantitative proteomic approach to analyze the proteome changes in the plasma collected from a pair of wild‐type versus apolipoprotein E knockout (APOE^?/?) mice which were fed with a high fat diet. In a multiplex manner, iTRAQ serves as the quantitative ‘in‐spectra’ marker for ‘cross‐sample’ comparisons to determine the differentially expressed/secreted proteins caused by APOE knock‐out. To obtain the most comprehensive proteomic data sets from this CAD‐associated mouse model, we applied both MALDI and ESI‐based mass spectrometric (MS) platforms coupled with two different schemes of multidimensional liquid chromatography (2‐D LC) separation. We then comparatively analyzed a series of the plasma samples collected at 6 and 12 wk of age after the mice were fed with fat diets, where the 6‐ or 12‐wk time point represents the early or intermediate phase of the fat‐induced CAD, respectively. We then categorized those proteins showing abundance changes in accordance with APOE depletion. Several proteins such as the γ and β chains of fibrinogen, apolipoprotein B, apolipoprotein C‐I, and thrombospondin‐4 were among the previously known CAD markers identified by other methods. Our results suggested that these unbiased proteomic methods are both feasible and a practical means of discovering potential biomarkers associated with CAD progression.     

Reversed-phase high-performance liquid chromatographic prefractionation of immunodepleted human serum proteins to enhance mass spectrometry identification of lower-abundant proteins

Serum analysis represents an extreme challenge due to the dynamic range of the proteins of interest, and the high structural complexity of the constituent proteins. In serum, the quantities of proteins and peptides of interest range from those considered "high abundance", present at 2-70% by mass of total protein, to those considered "low abundance", present at 10(-12) M or less. This range of analytical target molecules is outside the realm of available technologies for proteomic analysis. Therefore, in this study, we have developed a workflow toward addressing the complexity of these samples through the application of multidimensional separation techniques. The use of reversed-phase methods for the separation and fractionation of protein samples has been investigated, with the goal of developing an optimized serum separation for application to proteomic analysis. Samples of human serum were depleted of the six most abundant proteins, using an immunoaffinity LC method, then were separated under a variety of reversed-phase (RP) conditions using a macroporous silica C18 surface modified column material. To compare the qualities of the RP separations of this complex protein sample, absorbance chromatograms were compared, and fractions were collected for off-line SDS-PAGE and 2D-LC-MS/MS analysis. The column fractions were further investigated by determination of protein identities using either whole selected fractions, or gel bands excised from SDS-PAGE gels of the fractions. In either case samples underwent tryptic fragmentation and peptide analysis using MALDI-MS or LC-MS/MS. The preferred conditions for RP protein separation exhibited reproducibly high resolution and high protein recoveries (>98%, as determined by protein assay). Using the preferred conditions also permitted high column mass load, with up to 500 microg of protein well tolerated using a 4.6 mm ID x 50 mm column, or up to 1.5 mg on a 9.4 mm ID x 50 mm column. Elevated column temperature (80 degrees C) was observed to be a critical operational parameter, with poorer results observed at lower temperatures. The combination of sample simplification by immunoaffinity depletion combined with a robust and high recovery RP-HPLC fractionation yields samples permitting higher quality protein identifications by coupled LC-MS methods.     

Proteomics reveals selective regulation of proteins in response to memory-related serotonin stimulation in Aplysia californica ganglia

The marine mollusk Aplysia californica (Aplysia) is a powerful model for learning and memory due to its minimalistic nervous system. Key proteins, identified to be regulated by the neurotransmitter serotonin in Aplysia, have been successfully translated to mammalian models of learning and memory. Based upon a recently published large‐scale analysis of Aplysia proteomic data, the current study investigated the regulation of protein levels 24 and 48 h after treatment with serotonin in Aplysia ganglia using a 2‐D gel electrophoresis approach. Protein spots were quantified and protein‐level changes of selected proteins were verified by Western blotting. Among those were Rab GDP dissociation inhibitor alpha (RabGDIα), synaptotagmin‐1 and deleted in azoospermia‐associated protein (DAZAP‐1) in cerebral ganglia, calreticulin, RabGDIα, DAZAP‐1, heterogeneous nuclear ribonucleoprotein F (hnRNPF), RACK‐1 and actin‐depolymerizing factor (ADF) in pleural ganglia and DAZAP‐1, hnRNPF and ADF in pedal ganglia. Protein identity of the majority of spots was confirmed by a gel‐based mass spectrometrical method (FT‐MS). Taken together, protein‐level changes induced by the learning‐related neurotransmitter serotonin in Aplysia ganglia are described and a role for the abovementioned proteins in synaptic plasticity is proposed.     

Urinary proteome alterations in HER2 enriched breast cancer revealed by multipronged quantitative proteomics

Globally, breast cancer is the second most common cancer among women. Although biomarker discoveries through various proteomic approaches of tissue and serum samples have been studied in breast cancer, urinary proteome alterations in breast cancer are least studied. Urine being a noninvasive biofluid and a significant source of proteins, it has the potential in early diagnosis of breast cancer. This study used complementary quantitative gel‐based and gel‐free proteomic approaches to find a panel of urinary protein markers that could discriminate HER2 enriched (HE) subtype breast cancer from the healthy controls. A total of 183 differentially expressed proteins were identified using three complementary approaches, namely 2D‐DIGE, iTRAQ, and sequential window acquisition of all theoretical mass spectra. The differentially expressed proteins were subjected to various bioinformatics analyses for deciphering the biological context of these proteins using protein analysis through evolutionary relationships, database for annotation, visualization and integrated discovery, and STRING. Multivariate statistical analysis was undertaken to identify the set of most significant proteins, which could discriminate HE breast cancer from healthy controls. Immunoblotting and MRM‐based validation in a separate cohort testified a panel of 21 proteins such as zinc‐alpha2‐glycoprotein, A2GL, retinol‐binding protein 4, annexin A1, SAP3, SRC8, gelsolin, kininogen 1, CO9, clusterin, ceruloplasmin, and α1‐antitrypsin could be a panel of candidate markers that could discriminate HE breast cancer from healthy controls.