A quantitative proteomic approach of the different stages of colorectal cancer establishes OLFM4 as a new nonmetastatic tumor marker

Expression profiles represent new molecular tools that are useful to characterize the successive steps of tumor progression and the prediction of recurrence or chemotherapy response. In this study, we have used quantitative proteomic analysis to compare different stages of colorectal cancer. A combination of laser microdissection, OFFGEL separation, iTRAQ labeling, and MALDI-TOF/TOF MS was used to explore the proteome of 28 colorectal cancer tissues. Two software packages were used for identification and quantification of differentially expressed proteins: Protein Pilot and iQuantitator. Based on ～1,190,702 MS/MS spectra, a total of 3138 proteins were identified, which represents the largest database of colorectal cancer realized to date and demonstrates the value of our quantitative proteomic approach. In this way, individual protein expression and variation have been identified for each patient and for each colorectal dysplasia and cancer stage (stages I-IV). A total of 555 proteins presenting a significant fold change were quantified in the different stages, and this differential expression correlated with immunohistochemistry results reported in the Human Protein Atlas database. To identify a candidate biomarker of the early stages of colorectal cancer, we focused our study on secreted proteins. In this way, we identified olfactomedin-4, which was overexpressed in adenomas and in early stages of colorectal tumors. This early stage overexpression was confirmed by immunohistochemistry in 126 paraffin-embedded tissues. Our results also indicate that OLFM4 is regulated by the Ras-NF-κB2 pathway, one of the main oncogenic pathways deregulated in colorectal tumors.     

Fluctuations of hippocampal neuronal protein levels over the estrous cycle in the rat

Hippocampal function is known to be estrous-cycle-dependent but information on estrous-cycle-dependent protein expression is limited. It was therefore the aim to study protein levels of the neuronal network over the estrous cycle in the hippocampus of female rats and in males showing protein chemical neuroanatomy in this area. Female and male OFA Sprague-Dawley rats were used and females were grouped to proestrous, estrous, metestrous and diestrous by using vaginal smears. Hippocampal tissue was taken, proteins extracted, run on two-dimensional gel electrophoresis and proteins were identified by mass spectrometry methods (MALDI-TOF-TOF and nano-LC-ESI-MS/MS). Spot volumes were quantified with specific software. A Synapsin-1 expression form was differentially regulated between proestrous and diestrous, a Synapsin IIa expression form was differentially regulated between proestrous and metestrous, the sum of ERC-2 proteins organizing the cytomatrix at the nerve terminals active zone was showing sex-dependent levels in the proestrous phase and Neurofilament triplet L protein was differentially expressed between the estrous phase and males. The findings may represent estrous-cycle-dependent hippocampal synaptic function that has been shown already in terms of electrophysiology and neuroanatomy. Neurofilament changes over the estrous cycle may reflect endoskeleton changes over the estrous cycle. We learn from this study, although increasing complexity of protein knowledge, that the estrous cycle and not only the sex per se has to be taken into account for design of future studies and interpretation of previous work at the protein level.     

Visualisation and analysis of proteomic data from the procyclic form of Trypanosoma brucei

We have undertaken a large scale study of the proteins expressed in the procyclic form of the parasite Trypanosoma brucei, which causes African sleeping sickness, using 2-DE and MS. The complete data set encompasses over 2000 identifications, of which 770 are distinct proteins. We have discovered that multiple protein isoforms appear to be common in T. brucei, as most proteins have been matched to more than one gel spot. We have developed visualisation software to investigate the differences between isoforms, based on the information from the results of database searches with MS data. We are able to highlight instances where PTMs are the most likely cause of variant forms. In other cases, spots that appear reproducibly across replicates contain fragments of proteins, arising either as experimental artefacts or as part of protein degradation. We are also able to classify clusters of gel spots into different groups based on the pattern of peptides that have been matched from MS data. The entire data set is stored within a relational database system that allows complex queries ( http://www.gla.ac.uk/functionalgenomics). Using specific proteins as examples, we demonstrate how the visualisation software and the database query facilities can be used.     

Exposure to an extremely low-frequency electromagnetic field only slightly modifies the proteome of Chromobacterium violaceumATCC 12472

Several studies of the physiological responses of different organisms exposed to extremely low-frequency electromagnetic fields (ELF-EMF) have been described. In this work, we report the minimal effects of in situ exposure to ELF-EMF on the global protein expression of Chromobacterium violaceum using a gel-based proteomic approach. The protein expression profile was only slightly altered, with five differentially expressed proteins detected in the exposed cultures; two of these proteins (DNA-binding stress protein, Dps, and alcohol dehydrogenase) were identified by MS/MS. The enhanced expression of Dps possibly helped to prevent physical damage to DNA. Although small, the changes in protein expression observed here were probably beneficial in helping the bacteria to adapt to the stress generated by the electromagnetic field.     

MiR-187 Targets the Androgen-Regulated Gene ALDH1A3 in Prostate Cancer

miRNAs are predicted to control the activity of approximately 60% of all protein-coding genes participating in the regulation of several cellular processes and diseases, including cancer. Recently, we have demonstrated that miR-187 is significantly downregulated in prostate cancer (PCa) and here we propose a proteomic approach to identify its potential targets. For this purpose, PC-3 cells were transiently transfected with miR-187 precursor and miRNA mimic negative control. Proteins were analyzed by a two-dimensional difference gel electrophoresis (2D-DIGE) and defined as differentially regulated if the observed fold change was ±1.06. Then, MALDI-TOF MS analysis was performed after protein digestion and low abundance proteins were identified by LC–MS/MS. Peptides were identified by searching against the Expasy SWISS PROT database, and target validation was performed both in vitro by western blot and qRT-PCR and in clinical samples by qRT-PCR, immunohistochemistry and ELISA. DIGE analysis showed 9 differentially expressed spots (p<0.05) and 7 showed a down-regulated expression upon miR-187 re-introduction. Among these targets we identified aldehyde dehydrogenase 1A3 (ALDH1A3). ALDH1A3 expression was significantly downregulated in PC3, LNCaP and DU-145 cells after miR-187 re-introduction. Supporting these data, the expression of ALDH1A3 was found significantly (p<0.0001) up-regulated in PCa samples and inversely correlated (p<0.0001) with miR-187 expression, its expression being directly associated with Gleason score (p = 0.05). The expression of ALDH1A3 was measured in urine samples to evaluate the predictive capability of this biomarker for the presence of PCa and, at a signification level of 10%, PSA and also ALDH1A3 were significantly associated with a positive biopsy of PCa. In conclusion, our data illustrate for the first time the role of ALDH1A3 as a miR-187 target in PCa and provide insights in the utility of using this protein as a new biomarker for PCa.     

Identification and quantification of differentially expressed proteins in E-cadherin deficient SCC9 cells and SCC9 transfectants expressing E-cadherin by dimethyl isotope labeling, LC-MALDI MS and MS/MS

A strategy based on isotope labeling of peptides and liquid chromatography matrix-assisted laser desorption ionization mass spectrometry (LC-MALDI MS) has been employed to accurately quantify and confidently identify differentially expressed proteins between an E-cadherin-deficient human carcinoma cell line (SCC9) and its transfectants expressing E-cadherin (SCC9-E). Proteins extracted from each cell line were tryptically digested and the resultant peptides were labeled individually with either d(0)- or d(2)-formaldehyde. The labeled peptides were combined and the peptide mixture was separated and fractionated by a strong cation exchange (SCX) column. Peptides from each SCX fraction were further separated by a microbore reversed-phase (RP) LC column. The effluents were then directly spotted onto a MALDI target using a heated droplet LC-MALDI interface. After mixing with a MALDI matrix, individual sample spots were analyzed by MALDI quadrupole time-of-flight MS, using an initial MS scan to quantify the dimethyl labeled peptide pairs. MS/MS analysis was then carried out on the peptide pairs having relative peak intensity changes of greater than 2-fold. The MS/MS spectra were subjected to database searching for protein identification. The search results were further confirmed by comparing the MS/MS spectra of the peptide pairs. Using this strategy, we detected and compared relative peak intensity changes of 5480 peptide pairs. Among them, 320 peptide pairs showed changes of greater than 2-fold. MS/MS analysis of these changing pairs led to the identification of 49 differentially expressed proteins between the parental SCC9 cells and SCC9-E transfectants. These proteins were determined to be involved in different pathways regulating cytoskeletal organization, cell adhesion, epithelial polarity, and cell proliferation. The changes in protein expression were consistent with increased cell-cell and cell-matrix adhesion and decreased proliferation in SCC9-E cells, in line with E-cadherin tumor suppressor activity. Finally, the accuracy of the MS quantification and subcellular localization for 6 differentially expressed proteins were validated by immunoblotting and immunofluorescence assays.     

Comparative proteomics analysis of Barrett metaplasia and esophageal adenocarcinoma using two-dimensional liquid mass mapping

Esophageal adenocarcinoma, currently the seventh leading cause of cancer-related death, has been associated with the presence of Barrett metaplasia. The malignant potential of Barrett metaplasia is evidenced by ultimate progression of this condition to invasive adenocarcinoma. We utilized liquid phase separation of proteins with chromatofocusing in the first dimension and nonporous reverse phase HPLC in the second dimension followed by ESI-TOF mass spectrometry to identify proteins differentially expressed in six Barrett metaplasia samples as compared with six esophageal adenocarcinoma samples; all six Barrett samples were obtained from the identical six patients from whom we obtained the esophageal adenocarcinoma tissue. Approximately 300 protein bands were detected by mass mappings, and 38 differentially expressed proteins were identified by microLC-MS/MS. The false positive rates of the peptide identifications were evaluated by reversed database searching. Among the proteins that were identified, Rho GDP dissociation inhibitor 2, alpha-enolase, Lamin A/C, and nucleoside-diphosphate kinase A were demonstrated to be up-regulated in both mRNA and protein expression in esophageal adenocarcinomas relative to Barrett metaplasia. Candidate proteins were examined at the mRNA level using high density oligonucleotide microarrays. The cellular expression patterns were verified in both esophageal adenocarcinomas and in Barrett metaplasia by immunohistochemistry. These differentially expressed proteins may have utility as useful candidate markers of esophageal adenocarcinoma.     

Detecting differential and correlated protein expression in label-free shotgun proteomics

Recent studies have revealed a relationship between protein abundance and sampling statistics, such as sequence coverage, peptide count, and spectral count, in label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS) shotgun proteomics. The use of sampling statistics offers a promising method of measuring relative protein abundance and detecting differentially expressed or coexpressed proteins. We performed a systematic analysis of various approaches to quantifying differential protein expression in eukaryotic Saccharomyces cerevisiae and prokaryotic Rhodopseudomonas palustris label-free LC-MS/MS data. First, we showed that, among three sampling statistics, the spectral count has the highest technical reproducibility, followed by the less-reproducible peptide count and relatively nonreproducible sequence coverage. Second, we used spectral count statistics to measure differential protein expression in pairwise experiments using five statistical tests: Fisher's exact test, G-test, AC test, t-test, and LPE test. Given the S. cerevisiae data set with spiked proteins as a benchmark and the false positive rate as a metric, our evaluation suggested that the Fisher's exact test, G-test, and AC test can be used when the number of replications is limited (one or two), whereas the t-test is useful with three or more replicates available. Third, we generalized the G-test to increase the sensitivity of detecting differential protein expression under multiple experimental conditions. Out of 1622 identified R. palustris proteins in the LC-MS/MS experiment, the generalized G-test detected 1119 differentially expressed proteins under six growth conditions. Finally, we studied correlated expression of these 1119 proteins by analyzing pairwise expression correlations and by delineating protein clusters according to expression patterns. Through pairwise expression correlation analysis, we demonstrated that proteins co-located in the same operon were much more strongly coexpressed than those from different operons. Combining cluster analysis with existing protein functional annotations, we identified six protein clusters with known biological significance. In summary, the proposed generalized G-test using spectral count sampling statistics is a viable methodology for robust quantification of relative protein abundance and for sensitive detection of biologically significant differential protein expression under multiple experimental conditions in label-free shotgun proteomics.     

基于质谱和生物信息学分析的小菜蛾蛋白质鉴定

本研究以非模式昆虫小菜蛾Plutella xylostella为材料, 对比2, 3, 4龄幼虫的蛋白质组双向电泳图谱, 得到24个蛋白质差异点, 从中选取了编号为1111的差异表达蛋白质点进行质谱鉴定和生物信息学分析. 采用胶内酶解的多肽进行MALDI-TOF/TOF分析, 获得该点的肽质量指纹图谱（PMF）及串联质谱（MS/MS）图谱。将获得的PMF分别用MASCOT和ProFound等常用软件在NCBInr的Metazoa蛋白质数据库进行搜索, 匹配结果不理想. 进一步用PMF+MS/MS谱图搜索NCBInr的Metazoa蛋白质数据库, 以及小菜蛾EST数据库。 在NCBInr库中匹配结果为拟暗果蝇Drosophila pseudoobscura中的一种假定蛋白GA18218-PA, 而用EST库搜索的结果为家蚕Bombyx mori的ATP合酶的亚基。为验证搜索结果, 将该蛋白质点进行磺基异硫氰酸苯酯（SPITC）化学衍生后de novo测序, 最后确认该点可能为ATP合酶的一个亚基。最后着重讨论了蛋白质的质谱鉴定与生物信息学分析的联合使用, 希望据此选择出最适合于非模式昆虫蛋白质组学鉴定的方法。     

Developing the wool proteome

The wool proteome has been largely uncharted due to a lack of database coverage, poor protein extractability and dynamic range issues. Yet, investigating correlations between wool physical properties and protein content, or characterising UV-, heat- or processing-induced protein damage requires the availability of an identifiable and identified proteome.In this study we have achieved unprecedented wool proteome identification through a strategy of comprehensive data acquisition, iterative protein identification/validation and concurrent augmentation of the sequence database. Data acquisition comprised a range of different hyphenated MS techniques including LC–MS/MS, LC–MALDI, 2D-LC–MS/MS and SDS-PAGE LC–MS. Using iterative searching of databases and search result combination using ProteinScape, a systematic expansion of identifiable proteins in the sequence database was achieved. This was followed by extensive validation and rationalisation of the protein identifications. In total, 72 complete and 30 partial ovine-specific protein sequences were added to the database, and 113 wool proteins were identified.Enhanced access to ovine-specific protein identification and characterisation will facilitate all wool fibre protein chemistry and proteomics research.     

A high‐confidence reference dataset of differentially expressed proteins in elongating cotton fiber cells

In our previous study, we used a comparative proteomic approach based on 2DE to profile dynamic proteomes of cotton fibers and found 235 protein spots differentially expressed during the elongation process ranging from 5 to 25 days post‐anthesis. Of them, only 106 differentially expressed proteins (DEPs) were identified by MS due to database limitations at the time. In the present work, we successfully identified the remaining 129 DEPs from the same experimental system using high‐resolution MS with an updated database. Bioinformatic analysis revealed that proteins involved in carbohydrate and protein metabolism, transport, and redox homeostasis are the most abundant, and glycolysis was found to be the most significantly regulated process during fiber elongation. Our high‐confidence reference dataset, composed of 235 DEPs, provides a valuable resource for future studies on the molecular mechanism of cotton fiber elongation.     

Analysis of the HUPO Brain Proteome reference samples using 2-D DIGE and 2-D LC-MS/MS

Within the Human Proteome Organization (HUPO) Brain Proteome Project, a pilot study was launched with reference samples shipped to nine international laboratories (see Hamacher et al., this Special Issue) to evaluate different proteome approaches in neuroscience and to build up a first version of a brain protein database. One part of the study addresses quantitative proteome alterations between three developmental stages (embryonic day 16; postnatal day 7; 8 weeks) of mouse brains. Five brains per stage were differentially analyzed by 2-D DIGE using internal standardization and overlapping pH gradients (pH 4-7 and 6-9). In total, 214 protein spots showing stage-dependent intensity alterations (> two-fold) were detected, 56 of which were identified. Several of them, e.g. members of the dihydropyrimidinase family, are known to be associated with brain development. To feed the HUPO BPP brain protein database, a robust 2-D LC-MS/MS method was applied to murine postnatal day 7 and human post-mortem brain samples. Using MASCOT and the IPI database, 350 human and 481 mouse proteins could be identified by at least two different peptides. The data are accessible through the PRIDE database (http://www.ebi.ac.uk/pride/).     

In‐depth protein profiling of the postsynaptic density from mouse hippocampus using data‐independent acquisition proteomics

Located at neuronal terminals, the postsynaptic density (PSD) is a highly complex network of cytoskeletal scaffolding and signaling proteins responsible for the transduction and modulation of glutamatergic signaling between neurons. Using ion‐mobility enhanced data‐independent label‐free LC‐MS/MS, we established a reference proteome of crude synaptosomes, synaptic junctions, and PSD derived from mouse hippocampus including TOP3‐based absolute quantification values for identified proteins. The final dataset across all fractions comprised 49 491 peptides corresponding to 4558 protein groups. Of these, 2102 protein groups were identified in highly purified PSD in at least two biological replicates. Identified proteins play pivotal roles in neurological and synaptic processes providing a rich resource for studies on hippocampal PSD function as well as on the pathogenesis of neuropsychiatric disorders. All MS data have been deposited in the ProteomeXchange with identifier PXD000590 ( http://proteomecentral.proteomexchange.org/dataset/PXD000590 ).     

Proteomic profiling and protein identification by MALDI-TOF mass spectrometry in unsequenced parasitic nematodes

Lack of genomic sequence data and the relatively high cost of tandem mass spectrometry have hampered proteomic investigations into helminths, such as resolving the mechanism underpinning globally reported anthelmintic resistance. Whilst detailed mechanisms of resistance remain unknown for the majority of drug-parasite interactions, gene mutations and changes in gene and protein expression are proposed key aspects of resistance. Comparative proteomic analysis of drug-resistant and -susceptible nematodes may reveal protein profiles reflecting drug-related phenotypes. Using the gastro-intestinal nematode, Haemonchus contortus as case study, we report the application of freely available expressed sequence tag (EST) datasets to support proteomic studies in unsequenced nematodes. EST datasets were translated to theoretical protein sequences to generate a searchable database. In conjunction with matrix-assisted laser desorption ionisation time-of-flight mass spectrometry (MALDI-TOF-MS), Peptide Mass Fingerprint (PMF) searching of databases enabled a cost-effective protein identification strategy. The effectiveness of this approach was verified in comparison with MS/MS de novo sequencing with searching of the same EST protein database and subsequent searches of the NCBInr protein database using the Basic Local Alignment Search Tool (BLAST) to provide protein annotation. Of 100 proteins from 2-DE gel spots, 62 were identified by MALDI-TOF-MS and PMF searching of the EST database. Twenty randomly selected spots were analysed by electrospray MS/MS and MASCOT Ion Searches of the same database. The resulting sequences were subjected to BLAST searches of the NCBI protein database to provide annotation of the proteins and confirm concordance in protein identity from both approaches. Further confirmation of protein identifications from the MS/MS data were obtained by de novo sequencing of peptides, followed by FASTS algorithm searches of the EST putative protein database. This study demonstrates the cost-effective use of available EST databases and inexpensive, accessible MALDI-TOF MS in conjunction with PMF for reliable protein identification in unsequenced organisms.     

Proteomic analysis of p38alpha mitogen-activated protein kinase-regulated changes in membrane fractions of RAS-transformed fibroblasts

Oncogenic Ras signaling has been long known to play an important role in tumorigenesis and human cancer. In this report, we have used the sensitive 2-D-DIGE coupled to MS for the identification of proteins differentially expressed at the cell membrane level between oncogenic H-RasV12-transformed wild-type and p38alpha-deficient mouse embryo fibroblasts (MEFs). Following trifluoroethanol solubilization, 76 proteins were found to be differentially regulated. After PMF, 63 spots containing 42 different proteins were unequivocally identified by MALDI-TOF MS coupled with database interrogation. As expected, many of them were membrane proteins. Six proteins were selected for further validation studies based on their potential functional link with malignant transformation and signal transduction. These were prohibitin (PHB), protein disulfide isomerase 3 (PDIA3), focal adhesion kinase 2 (FAK2), c-GMP dependent protein kinase 2 (KGP2), NADH-ubiquinone oxidoreductase 30 kDa subunit (NUGM) and translationally controlled tumor protein (TCTP). All these proteins were up-regulated in the membranes of H-RasV12-transformed p38alpha-/-cells, except for prohibitin, which was down-regulated. An excellent correlation was found between DIGE results and Western blot studies, indicating the reliability of the 2-D-DIGE analysis. The available evidence about the putative function of the identified proteins supports the emerging role of p38alpha as a negative regulator of tumorigenesis. Further studies are in progress to elucidate the implications of these findings in the regulation of H-Ras-induced transformation by p38alpha signaling.     

Exploring membrane and cytoplasm proteomic responses of Alkalimonas amylolytica N10 to different external pHs with combination strategy of de novo peptide sequencing

Identification of differentially proteomic responses to external pHs would pave an access for understanding of survival mechanisms of bacteria living at extreme pH environment. We cultured Alkalimonas amylolytica N10 (N10), a novel alkaliphilic bacterium found in Lake Chahannor, in media with three different pHs and extracted the correspondent membrane and cytoplasm proteins for proteomic analysis through 2‐DE. The differential 2‐DE spots corresponding to the altered pHs were delivered to MALDI TOF/TOF MS for protein identification. Since the genomic data of strain N10 was unavailable, we encountered a problem at low rate of protein identification with 18.1%. We employed, therefore, a combined strategy of de novo sequencing to analyze MS/MS signals generated from MALDI TOF/TOF MS. A significantly improved rate of protein identification was thus achieved at over than 70.0%. Furthermore, we extensively investigated the expression of these pH‐dependent N10 genes using Western blot and real‐time PCR. The conclusions drawn from immunoblot and mRNA measurements were mostly in agreement with the proteomic observations. We conducted the bioinformatic analysis to all the pH‐dependent N10 proteins and found that some membrane proteins participated in iron transport were differentially expressed as external pH elevated and most of differential proteins with increased or bell‐shape mode of pH‐dependence were involved in bioenergetic process and metabolism of carbohydrates, fatty acid, amino acids, and nucleotides. Our data thus provide a functional profile of the pH‐responsive proteins in alkaliphiles, leading to elucidation of alkaliphilic‐adaptive mechanism.     

Plant defense in response to chewing insects: proteome analysis of Arabidopsis thaliana damaged by Plutella xylostella

The interactions between Arabidopsis thaliana and Plutella xylostella have been considered as a model system to unravel the responses of plants to herbivorous insects. Here, we use a 2-DE proteome approach to detect protein expression changes in the leaves of Arabidopsis plants exposed to P. xylostella larval infestation at 27°C within 8?h. Approximately 450 protein spots were reproducibly detected on gels. Of these, comparing healthy and infested leaves, we identified 18 differentially expressed protein spots. Thirteen proteins were successfully identified by MALDI-TOF/MS and LC-ESI-MS/MS. Functional classification analysis indicated that the differentially identified proteins were associated with amino acid, carbohydrate, energy, lipid metabolism, and photosynthesis. In addition, their relative abundances were assessed according to larval pest feeding on Arabidopsis leaves. These data provide valuable new insights for further works in plant-biotic and environmental stress interaction.