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At least 613 records · Page 34Linked to original sources
PubMed2004

Sperm proteome mapping of a patient who experienced failed fertilization at IVF reveals altered expression of at least 20 proteins compared with fertile donors: case report.

The aim of this study was to compare the sperm protein expression profile (proteome map) from a patient who experienced failed fertilization at IVF with fertile controls. One patient and three fertile donor sperm samples were characterized using two-dimensional electrophoresis. Differences in protein expression were established using gel analysis software before attempted protein identification. Gel analysis of the fertile donor proteome maps revealed excellent reproducibility as well as very low intra-donor and inter-donor variability in the presence of protein spots. In the patient samples, we have noted 20 consistent differences in protein expression (six spots missing, three additional spots, four less abundant, seven more abundant) compared with the controls. Two proteins that were more intense in the patient have been conclusively identified as secretory actin-binding protein and outer dense fibre protein 2/2. In conclusion proteome variation between different fertile donors was very low. In contrast, the patient proteome exhibited 20 differences compared with controls, which we believe is an underestimate. These proteins merit further investigation to determine whether failed fertilization at IVF might be caused by abnormalities in their expression. This case report represents a proof of principle that proteomics may be useful to study defects in sperm function.

Case-Control Studies↗
PubMed2003

Clinical applications of proteomics.

Proteomics, the systematic evaluation of changes in the protein constituency of a cell, is more than just the generation of lists of proteins that increase or decrease in expression as a cause or consequence of disease. The ultimate goal is to characterize the information flow through protein pathways that interconnect the extracellular microenvironment with the control of gene transcription. The nature of this information can be a cause or a consequence of disease processes. Clinical applications of proteomics involve the use of proteomic technologies at the bedside. The analysis of human cancer as a model for how proteomics can have an impact at the bedside is now employing several new proteomic technologies that are being developed for early detection, therapeutic targeting and finally, patient-tailored therapy.

Gene Expression Profiling↗
PubMed2006

Proteomics and its role in nutrition research.

There are approximately 100,000 proteins in humans with various physiological functions. The complement of proteins in the organism as well as their interactions is defined as the proteome. Its analysis (proteomics) by highly specific, sensitive, and accurate MS has been made possible with matrix-assisted laser desorption ionization or electrospray ionization of proteins and large peptides. Currently, the most commonly used proteomics technologies involve either specific digestion of proteins (the bottom-up approach using 2-dimensional polyacrylamide gel electrophoresis and multidimensional protein identification technology) or direct analysis of intact proteins after their chromatographic separation (the top-down approach and surface-enhanced laser desorption ionization). Proteomics holds great promise for discoveries in nutrition research, including profiles and characteristics of dietary and body proteins; digestion, absorption, and metabolism of nutrients; functions of nutrients and other dietary factors in growth, reproduction, and health; biomarkers of the nutritional status and disease; and individualized requirements of nutrients. The proteome analysis is expected to play an important role in solving major nutrition-associated problems in humans and animals, such as obesity, diabetes, cardiovascular disease, cancer, aging, and intrauterine fetal retardation.

Electrophoresis, Polyacrylamide Gel↗
PubMed2001

Proteome Analysis Database: online application of InterPro and CluSTr for the functional classification of proteins in whole genomes.

The SWISS-PROT group at EBI has developed the Proteome Analysis Database utilising existing resources and providing comparative analysis of the predicted protein coding sequences of the complete genomes of bacteria, archaea and eukaryotes (http://www.ebi.ac. uk/proteome/). The two main projects used, InterPro and CluSTr, give a new perspective on families, domains and sites and cover 31-67% (InterPro statistics) of the proteins from each of the complete genomes. CluSTr covers the three complete eukaryotic genomes and the incomplete human genome data. The Proteome Analysis Database is accompanied by a program that has been designed to carry out InterPro proteome comparisons for any one proteome against any other one or more of the proteomes in the database.

Animals↗
PubMed2003

Proteomics in uveal melanoma.

A new tool in the search for tumour markers is proteomic technology. Proteomics (or protein profiling) is the study of the proteome, the protein complement of the genome. The advantage of this technique in comparison with genomics is that the actual protein production can be measured. Gene microarrays determine levels of mRNA but do not necessarily predict the level of the corresponding proteins in a cell. In this study, we evaluated the use of proteomics in the aqueous humour of uveal melanoma patients compared with control patients using the surface-enhanced laser desorption ionization time-of-flight technique. The protein mass spectra of aqueous humours from 24 uveal melanoma eyes were compared with 24 control eyes using a strong anion exchange surface protein chip array. On the basis of two proteins (4543.43 and 6853.30 kDa), the aqueous humour of melanoma eyes and control eyes could be distinguished in 89% of cases. Therefore, proteomic evaluation might be helpful in finding diagnostic markers for uveal melanoma patients.

Aqueous Humor↗
PubMed2005

Analysis of prostate cancer by proteomics using tissue specimens.

PURPOSE: Prostate cancer cells differ from their normal counterpart in gene expression. Therefore, cancer and normal tissue/cells would show differences in their proteomes. From a diagnostic standpoint differences in the composition of secreted protein species are especially relevant. We used ProteinChip Array (Ciphergen Biosystems, Fremont, California) surface enhanced laser desorption/ionization (SELDI) time of flight mass spectrometry to profile prostate tissue samples to generate phenomic fingerprints. We used quantitative proteomics based on glycopeptide capture followed by tandem mass spectrometry to identify differentially expressed proteins. MATERIALS AND METHODS: Patient matched cancer and noncancer specimens were digested by collagenase to single cells. After digestion the cells were pelleted and the cell-free supernatant was used for analysis. A reversed phase hydrophobic ProteinChip Array was used to generate SELDI patterns from 43 primary prostate tumors, including 26 with matched noncancer specimens. Quantitative proteomics was applied to 1 specimen and the expression pattern was verified by Western blotting and immunohistochemistry. RESULTS: SELDI profiles showed that cancers of similar TNM stages were more likely to have similar profiles. On quantitative proteomics tissue metalloproteinase inhibitor-1 was identified to be down-regulated in cancer. Tissue metalloproteinase inhibitor-1 expression was localized to secretory cells. CONCLUSIONS: Protein profiling by SELDI is relatively easy to perform and it has great potential in prostate cancer diagnosis through pattern recognition. Quantitative proteomics can potentially determine the identity of many biomarkers specific for prostate cancer.

Biomarkers, Tumor↗
PubMed2003

Experimental analysis of the Arabidopsis mitochondrial proteome highlights signaling and regulatory components, provides assessment of targeting prediction programs, and indicates plant-specific mitochondrial proteins.

A novel insight into Arabidopsis mitochondrial function was revealed from a large experimental proteome derived by liquid chromatography-tandem mass spectrometry. Within the experimental set of 416 identified proteins, a significant number of low-abundance proteins involved in DNA synthesis, transcriptional regulation, protein complex assembly, and cellular signaling were discovered. Nearly 20% of the experimentally identified proteins are of unknown function, suggesting a wealth of undiscovered mitochondrial functions in plants. Only approximately half of the experimental set is predicted to be mitochondrial by targeting prediction programs, allowing an assessment of the benefits and limitations of these programs in determining plant mitochondrial proteomes. Maps of putative orthology networks between yeast, human, and Arabidopsis mitochondrial proteomes and the Rickettsia prowazekii proteome provide detailed insights into the divergence of the plant mitochondrial proteome from those of other eukaryotes. These show a clear set of putative cross-species orthologs in the core metabolic functions of mitochondria, whereas considerable diversity exists in many signaling and regulatory functions.

Arabidopsis↗
PubMed2006

The chloroplast lumen and stromal proteomes of Arabidopsis thaliana show differential sensitivity to short- and long-term exposure to low temperature.

Cold acclimation and over-wintering by herbaceous plants are energetically expensive and are dependent on functional plastid metabolism. To understand how the stroma and the lumen proteomes adapt to low temperatures, we have taken a proteomic approach (difference gel electrophoresis) to identify proteins that changed in abundance in Arabidopsis chloroplasts during cold shock (1 day), and short- (10 days) and long-term (40 days) acclimation to 5 degrees C. We show that cold shock (1 day) results in minimal change in the plastid proteomes, while short-term (10 days) acclimation results in major changes in the stromal but few changes in the lumen proteome. Long-term acclimation (40 days) results in modulation of the proteomes of both compartments, with new proteins appearing in the lumen and further modulations in protein abundance occurring in the stroma. We identify 43 differentially displayed proteins that participate in photosynthesis, other plastid metabolic functions, hormone biosynthesis and stress sensing and signal transduction. These findings not only provide new insights into the cold response and acclimation of Arabidopsis, but also demonstrate the importance of studying changes in protein abundance within the relevant cellular compartment.

Acclimatization↗
PubMed2007

Proteomics analysis in lung cancer: challenges and opportunities.

Recent technological developments in proteomic analysis are bringing us new insights into the molecular classification of tumours. Although proteomic analysis in cancer profiling is still under development both in terms of the instruments used and the data analytical tools, this method has great potential advantages for the analysis of biospecimens of many types. Direct measurement of abnormally expressed or modified proteins in the tumour tissue and/or patient blood may be an effective approach for discovering new biomarkers. Proteomics has the significant advantage of being able to discern not only changes in expression levels but also in post-translational modifications. Thus, the proteomics approach to protein profiling and biomarker discovery uncovers biomarkers from a different viewpoint than microarray analysis. This review summarizes the range of proteomics technologies employed for cancer profiling, and how they have been used to derive new classification models for human lung cancer.

Biomarkers, Tumor↗
PubMedDate not supplied

Differential proteomic profiling to study the mechanism of cardiac pharmacological preconditioning by resveratrol.

Recent studies demonstrated that resveratrol, a grape-derived polyphenolic phytoalexin, provides pharmacological preconditioning of the heart through a NO-dependent mechanism. To further explore the molecular mechanisms involved in resveratrol-mediated cardioprotection, we monitored the effects of resveratrol treatment after ischemia-reperfusion on the protein profile by implementation of proteomic analysis. Two groups of rats were studied; one group of animals was fed resveratrol for 7 days, while the other group was given vehicle only. The rats were sacrificed for the isolated working heart preparation and for isolation of cytoplasmic fraction from left ventricle homogenates to carry out the proteomic as well as immunoblot at baseline and at the end of 30 min ischemia/2-h perfusion. The results demonstrate significant cardioprotection with resveratrol evidenced by improved ventricular recovery and reduced infarct size and cardiomyocyte apoptosis. The left ventricular cytoplasmic fractions were separated by two-dimensional electrophoresis (2-DE). Differentially regulated proteins were detected with quantitative computer analysis of the Coomassie blue stained 2-DE images and identified by MALDI-TOF (MS) and nanoLC-ESI-Q-TOF mass spectrometry (MS/MS). Five redox-regulated and preconditioning- related proteins were identified that were all upregulated by resveratrol: MAPKK, two different alphaB-crystallin species, HSP 27 and PE binding protein. Another HSP27 species and aldose reductase were downregulated and peroxiredoxin- 2 remained constant. The results of the immunoblot analysis of phosphorylated MAPKK, -HSP27 and -alphaB-crystallin and PE binding protein were consistent with the proteomic findings, but not with peroxiredoxin-2. The proteomic analysis showed also downregulation of some proteins in the mitochondrial respiratory chain and matrix and the myofilament regulating protein MLC kinase-2. The results of the present study demonstrate that proteomic profiling enables the identification of resveratrol induced preconditioning-associated proteins which reflects not only changes in their expression level but also isoforms, post-translational modifications and regulating binding or activating partner proteins.

Animals↗
PubMed2006

Towards second-generation proteome analysis of murine enamel-forming cells.

Proteome analysis of rat enamel-forming cells, initiated over a decade ago, has provided valuable insights to enamel biology. In preparation for a more comprehensive, second-generation proteomic exploration, we evaluated an updated microsample-profiling strategy that comprises sequential extraction of enamel epithelium, parallel one- and two-dimensional gel electrophoresis, and mass spectrometric sequence analysis. The results indicated that several hundred proteins, representing various cellular compartments (including membranes), are amenable to identification with a starting tissue volume of <10 microl. With its increased proteomic depth and breadth, this straightforward approach constitutes a major advance from the first-generation work (10-fold increased proteome coverage), although care was needed to ensure a comparably high stringency of protein identification. Expression proteomics has an exciting potential to elucidate the inner workings of murine enamel epithelial cells, leading to an improved understanding of enamel in health and disease.

Ameloblasts↗
PubMed2001

Proteomic approaches within the NCI early detection research network for the discovery and identification of cancer biomarkers.

In the postgenome era, proteomics provides a powerful approach for the analysis of normal and transformed cell functions, for the identification of disease-specific targets, and for uncovering novel endpoints for the evaluation of chemoprevention agents and drug toxicity. Unfortunately, the genomic information that has greatly expounded the genetic basis of cancer does not allow an accurate prediction of what is actually occurring at the protein level within a given cell type at any given time. The gene expression program of a given cell is affected by numerous factors in the in vivo environment resulting from tissue complexity and organ system orchestration, with cells acting in concert with each other and responding to changes in their microenvironment. Repositories of genomic information can be considered master "inventory lists" of genes and their maps, which need to be supplemented with protein-derived information. The National Cancer Institute's Early Detection Research Network is employing proteomics, or "protein walking", in the discovery and evaluation of biomarkers for cancer detection and for the identification of high-risk subjects. Armed with microdissection techniques, including the use of Laser Capture Microdissection (LCM) to procure pure populations of cells directly from human tissue, the Network is facilitating the development of technologies that can overcome the problem of tissue heterogeneity and address the need to identify markers in easily accessible biological fluids. Proteomic approaches complement plasma-based assays of circulating DNA for cancer detection and risk assessment. LCM, coupled with downstream proteomics applications, such as two-dimensional polyacrylamide gel electrophoresis and SELDI (surface enhanced laser desorption ionization) separation followed by mass spectrometry (MS) analysis, may greatly facilitate the characterization and identification of protein expression changes that track normal and disease phenotypes. We highlight recent work from Network investigators to demonstrate the potential of proteomics to identify proteins present in cancer tissues and body fluids that are relevant for cancer screening.

Biomarkers, Tumor↗
PubMed2025

Proteomic analysis reveals distinct cerebrospinal fluid signatures across genetic frontotemporal dementia subtypes.

We used an untargeted mass spectrometric approach, tandem mass tag proteomics, for the identification of proteomic signatures in genetic frontotemporal dementia (FTD). A total of 238 cerebrospinal fluid (CSF) samples from the Genetic FTD Initiative were analyzed, including samples from 107 presymptomatic (44 C9orf72, 38 GRN, and 25 MAPT) and 55 symptomatic (27 C9orf72, 17 GRN, and 11 MAPT) mutation carriers as well as 76 mutation-negative controls ("noncarriers"). We found shared and distinct proteomic alterations in each genetic form of FTD. Among the proteins significantly altered in symptomatic mutation carriers compared with noncarriers, we found that a set of proteins including neuronal pentraxin 2 and fatty acid binding protein 3 changed across all three genetic forms of FTD and patients with Alzheimer's disease from previously published datasets. We observed differential changes in lysosomal proteins among symptomatic mutation carriers with marked abundance decreases in MAPT carriers but not other carriers. Further, we identified mutation-associated proteomic changes already evident in presymptomatic mutation carriers. Weighted gene coexpression network analysis combined with gene ontology annotation revealed clusters of proteins enriched in neurodegeneration and glial responses as well as synapse- or lysosome-related proteins indicating that these are the central biological processes affected in genetic FTD. These clusters correlated with measures of disease severity and were associated with cognitive decline. This study revealed distinct proteomic changes in the CSF of patients with genetic FTD, providing insights into the pathological processes involved in the disease. In addition, we identified proteins that warrant further exploration as diagnostic and prognostic biomarker candidates.

Humans↗
PubMed2003

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.

Animals↗
PubMed2003

Initial proteome analysis of model microorganism Haemophilus influenzae strain Rd KW20.

The proteome of Haemophilus influenzae strain Rd KW20 was analyzed by liquid chromatography (LC) coupled with ion trap tandem mass spectrometry (MS/MS). This approach does not require a gel electrophoresis step and provides a rapidly developed snapshot of the proteome. In order to gain insight into the central metabolism of H. influenzae, cells were grown microaerobically and anaerobically in a rich medium and soluble and membrane proteins of strain Rd KW20 were proteolyzed with trypsin and directly examined by LC-MS/MS. Several different experimental and computational approaches were utilized to optimize the proteome coverage and to ensure statistically valid protein identification. Approximately 25% of all predicted proteins (open reading frames) of H. influenzae strain Rd KW20 were identified with high confidence, as their component peptides were unambiguously assigned to tandem mass spectra. Approximately 80% of the predicted ribosomal proteins were identified with high confidence, compared to the 33% of the predicted ribosomal proteins detected by previous two-dimensional gel electrophoresis studies. The results obtained in this study are generally consistent with those obtained from computational genome analysis, two-dimensional gel electrophoresis, and whole-genome transposon mutagenesis studies. At least 15 genes originally annotated as conserved hypothetical were found to encode expressed proteins. Two more proteins, previously annotated as predicted coding regions, were detected with high confidence; these proteins also have close homologs in related bacteria. The direct proteomics approach to studying protein expression in vivo reported here is a powerful method that is applicable to proteome analysis of any (micro)organism.

Aerobiosis↗
PubMed2026

Subphenogroups of acute heart failure with preserved ejection fraction: comprehensive proteomics and pathway analysis.

BACKGROUND: Heterogeneity of heart failure with preserved ejection fraction (HFpEF) results in significant challenges for treatment development. Identifying and characterising distinct HFpEF phenogroups may aid in tailoring therapeutic strategies for these patients. The objective of this study was to assess proteomic patterns of HFpEF phenogroups identified through a machine-learning-based clustering model, with the aim of uncovering specific biological pathways associated with each phenogroup. METHODS: This study represents a post-hoc analysis of the ongoing Prospective mUlticenteR obServational stUdy of patIenTs with Heart Failure with preserved Ejection Fraction (PURSUIT-HFpEF) study, which is a multicentre prospective observational study of hospitalised patients with acute decompensated HFpEF. Of the overall cohort (N=1238), this study analysed 198 patients with HFpEF with available proteomics data. These patients were classified into four phenogroups using the machine-learning-based clustering model. The SomaScan assay V.4.1 was used to measure levels of >7000 plasma proteins, and subsequent pathway analysis was conducted to determine the biological differences among the phenogroups. RESULTS: We identified four distinct phenogroups: Phenogroup 1 ('rhythm trouble'), Phenogroup 2 ('ventricular-arterial uncoupling'), Phenogroup 3 ('low output and systemic congestion') and Phenogroup 4 ('systemic failure'). The proteomics revealed distinct protein expression profiles among the phenogroups, with ribonuclease 4, tax1-binding protein 1, regenerating islet-derived protein 3-gamma and alpha-1-antichymotrypsin being the most significant markers to specific identified phenogroups. Pathway analysis suggested differences in immune response, autonomic activation, cellular homeostasis and tissue repair mechanisms across the phenogroups. CONCLUSIONS: Using a comprehensive plasma proteomics approach, our study identified distinct proteomic profiles of HFpEF phenogroups, which in turn suggest specific underlying biological processes. These profiles suggest the involvement of inflammatory activation, tissue injury and regenerative responses, immune modulation and systemic stress signalling as key components of HFpEF pathophysiology. TRIAL REGISTRATION NUMBER: UMIN-CTR ID: UMIN000021831.

Humans↗
PubMed2003

Bioinformatics meets proteomics--bridging the gap between mass spectrometry data analysis and cell biology.

Proteomics research programs typically comprise the identification of protein content of any given cell, their isoforms, splice variants, post-translational modifications, interacting partners and higher-order complexes under different conditions. These studies present significant analytical challenges owing to the high proteome complexity and the low abundance of the corresponding proteins, which often requires highly sensitive and resolving techniques. Mass spectrometry plays an important role in proteomics and has become an indispensable tool for molecular and cellular biology. However, the analysis of mass spectrometry data can be a daunting task in view of the complexity of the information to decipher, the accuracy and dynamic range of quantitative analysis, the availability of appropriate bioinformatics software and the overwhelming size of data files. The past ten years have witnessed significant technological advances in mass spectrometry-based proteomics and synergy with bioinformatics is vital to fulfill the expectations of biological discovery programs. We present here the technological capabilities of mass spectrometry and bioinformatics for mining the cellular proteome in the context of discovery programs aimed at trace-level protein identification and expression from microgram amounts of protein extracts from human tissues.

Computational Biology↗
PubMed2006

Proteomics and genomics of microgravity.

Many serious adverse physiological changes occur during spaceflight. In the search for underlying mechanisms and possible new countermeasures, many experimental tools and methods have been developed to study microgravity caused physiological changes, ranging from in vitro bioreactor studies to spaceflight investigations. Recently, genomic and proteomic approaches have gained a lot of attention; after major scientific breakthroughs in the fields of genomics and proteomics, they are now widely accepted and used to understand biological processes. Understanding gene and/or protein expression is the key to unfolding the mechanisms behind microgravity-induced problems and, ultimately, finding effective countermeasures to spaceflight-induced alterations. Significant progress has been made in identifying the genes/proteins responsible for these changes. Although many of these genes and/or proteins were observed to be either upregulated or downregulated, however, no large-scale genomics and proteomics studies have been published so far. This review aims at summarizing the current status of microgravity-related genomics and proteomics studies and stimulating large-scale proteomics and genomics research activities.

Animals↗