Identification of proteins in human substantia nigra

Characterization of the human brain proteome is a critical area of research. While examination of the human cortex has provided some insight, very little is known about the proteome of the human midbrain, which demonstrates substantial loss of dopaminergic neurons in the substantia nigra pars compacta (SNpc) in Parkinson's disease (PD). Therefore, characterization of this region is essential to a better understanding of the pathogenesis of PD. This dataset paper reports two separate studies, where human SNpc was collected from PD and control subjects and 1263 proteins were identified using MALDI-TOF/TOF as well as linear ion trap MS platforms. With gene ontology analysis, the proteins were categorized according to their biological processes, as well as cellular components. These data were also compared with previous proteomic characterization of the human frontal and temporal cortex, and cerebrospinal fluid to establish shared proteins of relevance. The present dataset is the most extensive survey of the human SNpc proteome, to date. Further characterization of the SNpc proteome will significantly facilitate our understanding of the function and expression of proteins involved in PD, as well as provide potential proteins that may be utilized as biomarkers.     

The proteome of the human breast cancer cell line MDA-MB-231: Analysis by LTQ-Orbitrap mass spectrometry

We have used a combination of SDS-PAGE and LTQ-Orbitrap MS to explore the proteome of the highly invasive MDA-MB-231 breast cancer cell line. Based on about 520?000 MS/MS spectra, a total of 3481 proteins were identified and subsequently classified according to their cellular distribution and molecular function. Interestingly, a large proportion of proteins (38%) were from cellular membranes and we were able to characterize numerous proteins involved in cancer initiation and progression such as the tumor suppressor p53 and the epidermal growth factor receptor. Together, this study represents the largest proteome database of breast cancer cells realized to date and demonstrates the value of using Orbitrap MS for deeper proteome analysis.     

Proteome of human endometrium: Identification of differentially expressed proteins in proliferative and secretory phase endometrium

Purpose: To exploit the potential of proteomics to identify and study additional yet‐unidentified important proteins present in human endometrium. Experimental design: The proteome of human endometrium would be established using 2‐DE and MALDI and the data analyzed to identify differential protein expression in the proliferative and secretory phase of the menstrual cycle using PDQuest software and MALDI. Results: In the present work, 2‐DE of human endometrium protein led to the resolution of over 200 spots. Subsequent MALDI analysis of 215 spots allowed the identification of 194 proteins. A total of 57 out of the 215 spots were found to be differentially expressed, out of which 49 could be identified using MALDI. These differentially expressed proteins included structural proteins, molecular chaperones, signaling proteins, metabolic proteins, proteins related to immunity, RNA biogenesis, protein biosynthesis and others. The differential expressions of seven representative proteins in secretory and proliferative phase endometrium tissue were confirmed by immunoblot analysis. Conclusion and clinical relevance: This study establishes the 2‐D proteome of human endometrium represented by 194 identified protein spots. The present data provides an important clue towards determining the function of these proteins with respect to endometrium related diseases.     

Large-scale protein identification of human urine proteome by multi-dimensional LC and MS/MS

Urine is a human specimen that is easily obtained non-invasively for clinical diagnosis. We attempted to enhance the resolution of current human urine proteomes and construct a comprehensive reference database for advanced studies, such as the discovery of biomarkers for renal diseases. Multi-dimensional LC-MS/MS was coupled with de novo sequencing and database matching. The proposed approach improved the identification of not only the proteins, but also the post-translational sites of urinary proteins. We identified 165, 200 and 259 unique gene products in the urine proteomes from males, females and pregnant women, respectively. When all of the results were combined and the redundancies removed, a total of 1095 distinct peptides were identified. Of these, 1016 peptides were associated with 334 unique gene products. In this study, over 100 gene products, including some disease-related proteins, were detected in urine for the first time by proteomic approaches. Various proteins with novel post-translational hydroxylation were identified using the MASCOT program and de novo sequencing. All proteins with peptide information were summarized into a comprehensive urine protein database. We believe that this comprehensive urine proteome database will assist in the identification of urinary proteins/polypeptides whose spectra are difficult to interpret in the discovery of urinary biomarkers.     

Implementation of Proteomics Biomarkers in Nephrology: From Animal Models to Human Application?

Preclinical animal models are extensively used in nephrology. In this review, the utility of performing proteome analysis of kidney tissue or urine in such models and transfer of the results to human application has been assessed. Analysis of the literature identified 68 relevant publications. Pathway analysis of the reported proteins clearly indicated links with known biological processes in kidney disease providing validation of the observed changes in the preclinical models. However, although most studies focused on the identification of early markers of kidney disease or prediction of its progression, none of the identified makers has made it to substantial validation in the clinic or at least in human samples. Especially in renal disease where urine is an abundant source of biomarkers of diseases of the kidney and the urinary tract, it therefore appears that the focus should be on human material based discovery studies. In contrast, the most valid information of proteome analysis of preclinical models in nephrology for translation in human disease resides in studies focusing on drug evaluation, both efficacy for translation to the clinic and for mechanistic insight.     

Lysosomal proteomics and disease

A recent trend in proteomic studies has been to analyze macromolecular complexes such as subcellular organelles instead of complete cells or tissues. This "divide and conquer" approach circumvents some of the formidable problems associated with whole proteome analyses and allows focus on a subset of proteins that may be involved in a particular process or disease of interest. One organelle that has been the focus of considerable attention in proteomic studies is the lysosome, an acidic, membrane-delimited compartment that plays an essential role in the degradation and recycling of biological macromolecules. Lysosomal proteomics have been driven in part by the well-established involvement of this organelle in numerous human diseases, but also by the availability of approaches to selectively visualize and/or isolate subsets of lysosomal proteins. In terms of clinical application, proteomic studies of the lysosome have led to the identification of gene defects in three human hereditary diseases. This review summarizes past progress, current limitations and future directions in the field of lysosomal proteomics.     

Proteomics of traumatic brain injury and regeneration

Despite the enormous medical and economic consequences of traumatic brain injury (TBI), little is known about the proteins involved in the resulting pathology. Major advances in the identification of such proteins have been made in recent years through application of differential proteome analysis. Such an approach has revealed a number of novel proteins as potential regulators of the degenerative and regenerative processes that take place in the mammalian brain after a traumatic insult. Some of these proteins may serve as diagnostic and prognostic markers to assess the severity of the brain damage. Comparative proteome analysis of brain systems differing in their intrinsic regenerative potential are likely to provide new insights into the cellular signals that could be targeted for therapeutic intervention to increase the repair capacity of the human brain.     

An evaluation of multidimensional fingerprinting in the context of clinical proteomics

Multidimensional fingerprinting (MDF) utilizes measurable peptide characteristics to identify proteins. In this study, 3‐D fingerprinting, namely, parent protein molecular weight, peptide mass, and peptide retention time on RPLC, is used to identify 331 differentially expressed proteins between normal and human colon cancer plasma membrane samples. A false discovery rate (FDR) procedure is introduced to evaluate the performance of MDF on the colon cancer dataset. This evaluation establishes a false protein identification rate below 15% for this dataset. Western blot analysis is performed to validate the differential expression of the MDF‐identified protein VDAC1 on the original tissue samples. The limits of MDF are further assessed by a simulation study where key parameters such as database size, query size, and mass accuracy are varied. The results of this simulation study demonstrate that fingerprinting with three dimensions yields low FDR values even for large queries on the complete human proteome without the need for prior peptide sequencing by tandem mass spectrometry. Specifically, when mass accuracy is 10 ppm or lower, full human proteome searches can achieve FDR values of 10% or less.     

Comparison of two-dimensional gel electrophoresis based and shotgun strategies in the study of plasma membrane proteome

Membrane proteins play important roles in various plasma membrane (PM) activities such as signal transduction and cell recognition. However, a comprehensive proteomic study of membrane proteins remains difficult. Different strategies have been employed to study PM proteome, but little effort has been made to systematically evaluate them. In the present work, liver PM was prepared by subcellular fractionation and an aliquot was washed by sodium carbonate. After evaluation of the PM fraction by electron microscopy and Western blotting, proteins in both original and carbonate washed PM were identified by either 2-DE coupled MALDI-TOF-MS or shotgun strategies. Then protein characteristics such as molecular weight, pI, grand average hydrophobicity, subcellular location, and transmembrane domains were systematically compared. The comparative analysis showed that shotgun strategies were more suitable to identify membrane proteins, while 2-DE-based strategies may serve as a complement. Furthermore, carbonate washing obviously enriched the integral membrane proteins. All the results suggested that the strategy combining carbonate washing and shotgun identification was the optimum strategy to study human liver PM proteome. Using this strategy, 260 high-confidence proteins were identified, wherein 139 were integral membrane proteins which had 1-17 transmembrane domains.     

Proteome analysis of human foetal, aged and advanced nuclear cataract lenses

The most complete proteome of human lenses has been compiled using 2-D LC-MS/MS analysis of foetal, aged normal and advanced nuclear cataract lenses. A total of 231 proteins were identified across all lens groups, including 112 proteins that have not been reported previously. Proteins were grouped according to their PANTHER molecular function classification in order to facilitate comparisons. Previously unreported N-terminal acetylation was detected in a number of proteins, with the majority being associated with the prior removal of a methionine residue. This pattern of proteolysis may indicate that methionine aminopeptidase activity is present in human lenses. Acetylation is likely to aid in the stability of proteins that are present in the lens for many decades. Protein sequences were also used to interrogate the three human lens cDNA libraries publicly available. Surprisingly, 84 proteins we identified were not present in the cDNA libraries.     

Multidimensional protein identification technology analysis highlights mitoxantrone‐induced expression modulations in the primary prostate cancer cell proteome

Chemotherapeutic agents as they are used today have limited effectiveness against prostate cancer, but may potentially be used in new combinations with more efficacious results. Mitoxantrone, used for palliation of prostate cancer, has recently been found by our group to improve the susceptibility of primary prostate cancer cells to killing through the Fas‐mediated death pathway. Here we used a shotgun proteomics approach to first profile the entire prostate cancer proteome and then identify specific factors involved in this mitoxantrone response. Peptides derived from primary prostate cancer cells treated with or without 100 nM mitoxantrone were analyzed by multidimensional protein identification technology (MudPIT). Strict limits and data filtering hierarchies were applied to identify proteins with high confidence. We identified 1498 proteins belonging to the prostate cancer proteome, 83 of which were significantly upregulated and 27 of which were markedly downregulated following mitoxantrone treatment. These proteins perform diverse functions, including ceramide production, tumour suppression, and oxidative reduction. Detailed proteomic analyses of prostate cancer cells and their response to mitoxantrone will further our understanding of its mechanisms of action. Identification of proteins influenced by treatment with mitoxantrone or other compounds may lead to the development of more effective drug combinations against prostate cancer.     

Comparative proteome profiling of MCF10A and 184A1 human breast epithelial cells emphasized involvement of CDK4 and cyclin D3 in cell proliferation

Acquiring high proliferation rate is crucial for carcinogenic transformation of cells. We report here proteome profiling of human breast epithelial cells with low (184A1) and high (MCF10A) proliferation rates. We identified 183 proteins in 184A1 and 318 proteins in MCF10A cells. These datasets provide the most comprehensive proteome annotations of 184A1 and MCF10A cells. Proteins were taken for identification from 2-D gels in a systematic and unbiased way. Functional clustering of the identified proteins showed similarities in distribution of proteins to the same functional domains, indicating similarities in proteomes of 184A1 and MCF10A cells. Among observed differences in protein expression, we validated correlation of expression of endogenous cyclin-dependent kinase 4 (CDK4), cyclin D3, cdc25B, and p38γ with cell proliferation. Furthermore, down-regulation of CDK4 and cyclin D3 with specific siRNA inhibited cell proliferation, which emphasized the role of CDK4 and cyclin D3 in enhancement of cell proliferation rate of human breast epithelial cells.     

Analysis of the differential proteome of human erythroblasts during in vitro erythropoiesis by 2-D DIGE

In the present study we have used an in vitro culture system that induces differentiation of human CD34(+) cells down the erythroid lineage along with 2-D DIGE to determine the differential proteome of erythroblasts at specific developmental stages during erythropoiesis. We initially distinguished 154 proteins differentially expressed between pro-normoblasts and polychromatic/orthochromatic erythroblasts, of which 24 protein spots, representing 21 different proteins, were identified following MS/MS and verification in replicate experiments with cells from different individuals. These data were confirmed by analysis of the differential proteome of erythroblasts at more discrete stages of erythropoiesis using 2-D DIGE and by mapping the expression of three identified proteins (Annexin I, Annexin II, Carbonic Anhydrase I) throughout erythropoiesis by Western blot with specific antisera. In addition, the differential expression of proteins due to biological variation, such as polymorphism, was determined by comparing erythroblasts at the same developmental stage from different individuals; none of the proteins thus identified were represented in the above data set. Finally, we discuss the problems associated with 2-D DIGE gel-based proteomic approaches such as ours and suggest a modified approach for decreased inter-gel variation, improved protein resolution and increased protein concentration, which should significantly facilitate protein identification.     

Urine proteomics for profiling of human disease using high accuracy mass spectrometry

Knowledge of the biologically relevant components of human tissues has enabled the invention of numerous clinically useful diagnostic tests, as well as non-invasive ways of monitoring disease and its response to treatment. Recent use of advanced MS-based proteomics revealed that the composition of human urine is more complex than anticipated. Here, we extend the current characterization of the human urinary proteome by extensively fractionating urine using ultra-centrifugation, gel electrophoresis, ion exchange and reverse-phase chromatography, effectively reducing mixture complexity while minimizing loss of material. By using high-accuracy mass measurements of the linear ion trap-Orbitrap mass spectrometer and LC-MS/MS of peptides generated from such extensively fractionated specimens, we identified 2362 proteins in routinely collected individual urine specimens, including more than 1000 proteins not described in previous studies. Many of these are biomedically significant molecules, including glomerularly filtered cytokines and shed cell surface molecules, as well as renally and urogenitally produced transporters and structural proteins. Annotation of the identified proteome reveals distinct patterns of enrichment, consistent with previously described specific physiologic mechanisms, including 336 proteins that appear to be expressed by a variety of distal organs and glomerularly filtered from serum. Comparison of the proteomes identified from 12 individual specimens revealed a subset of generally invariant proteins, as well as individually variable ones, suggesting that our approach may be used to study individual differences in age, physiologic state and clinical condition. Consistent with this, annotation of the identified proteome by using machine learning and text mining exposed possible associations with 27 common and more than 500 rare human diseases, establishing a widely useful resource for the study of human pathophysiology and biomarker discovery.     

Proteome alterations induced in human white blood cells by consumption of Brussels sprouts: Results of a pilot intervention study

Epidemiological studies indicate a correlation of cruciferous vegetables consumption with reduced incidence of cancer. This study was designed to investigate molecular mechanisms, which may help to understand the beneficial effects of Brussels sprout consumption. In order to avoid the limitations of in vitro model systems, we performed a dietary intervention study with five participants. We investigated, whether sprout consumption affects the proteome profile of primary white blood cells. In order to achieve maximal sensitivity in detecting specific adaptive proteome alterations, we metabolically labelled freshly isolated cells in the presence of ³⁵S‐methionine/cysteine and performed autoradiographic quantification of protein synthesis. Proteins were separated by 2‐DE and spots of interest were cut out, digested and identified by MS. After the intervention, we found a significant up‐regulation of the synthesis of manganese superoxide dismutase (1.56‐fold) and significant down‐regulation of the synthesis of heat shock 70 kDa protein (hsp70; 2.27‐fold). Both proteins play a role in malignant transformation of cells. Hsp‐70 is involved in the regulation of apoptosis, which leads to elimination of cancer cells, while SOD plays a key role in protection against reactive oxygen species mediated effects. Our findings indicate that the alteration of the synthesis of these proteins may be involved in the anticarcinogenic effects of cruciferous vegetables, which was observed in earlier laboratory studies with animals.     

Systematic investigation of lycopene effects in LNCaP cells by use of novel large‐scale proteomic analysis software

Lycopene, the red pigment of tomatoes, is a carotenoid with potent antioxidant properties. Although lycopene may function as a prostate cancer chemoprevention agent, little is known about its effects at the cellular level. To define general changes induced by treatment of cells with lycopene, and to gain insights into the possible chemoprevention properties of lycopene, we investigated changes in protein expression after lycopene treatment in human LNCaP cells. The high throughput proteomics data were then visualized and analyzed by novel biological protein pathway modeling software. Differentially expressed proteins were identified, and the data were analyzed by protein pathway simulation software, without the need for specialized programming, by importing pathway models from a number of sources or by creating our own. One notable outcome was the identification of a group of upregulated proteins involved in detoxification of reactive oxygen species. This finding suggests that a possible mechanism of lycopene chemoprevention is the stimulation of detoxification enzymes associated with the antioxidant response element. Novel biological pathway modeling software enhances analysis of large proteomics data. When applied to the analysis of proteins differentially expressed in prostate cancer cells upon treatment with lycopene, the up‐regulation of detoxification enzymes was identified.     

Proteomics in clinical prostate research

The incidence of early prostate cancer (PCa) has increased rapidly in recent years. The majority of newly diagnosed PCa are in early tumor phase. Presently, we do not have adequate biomarkers to assess tumor aggressiveness in individual cases. Consequently, too many patients are given curatively intended treatment. An exploration of the human proteome may provide clinically useful markers. 2-DE has been successfully used for analysis of the protein phenotype using clinical samples. Proteins are separated according to size and charge, gels are compared by image analysis, protein spots of interest are excised, and proteins identified by MS. This method is exploratory and allows protein identification. However, low-abundance proteins are difficult to detect and 2-DE is currently too labor-intensive for routine use. In recent years, nongel based techniques, such as LC-MS, SELDI-MS, and protein arrays have emerged. They require smaller sample sizes and can be more automated than 2-DE. In this review, we describe studies of the protein expression of benign prostatic tissue and PCa, which is likely to serve as the first step in prognostic biomarker discovery. The prostate proteome is still far from a complete mapping which would enhance our understanding of PCa biology.