Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “proteomic profiling”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 325 records · Page 18Linked to original sources
PubMed2026

Untargeted metabolomics and proteomics reveals cocoa-mediated mitigation of valproic acid-induced dysregulation in a zebrafish model of autism: pilot study.

INTRODUCTION: Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by behavioral impairments and limited therapeutic options. Emerging evidence suggests that plant-derived polyphenols may offer neuroprotective benefits. OBJECTIVES: This pilot study aimed to investigate the therapeutic potential of polyphenol-rich cocoa extract in a valproic acid (VPA)-induced zebrafish model of ASD. METHODS: Zebrafish were exposed to 3 μM VPA, cocoa powder providing 2.5 μM (-)-epicatechin, a combination of both, or left untreated. Behavioral phenotyping was conducted using DanioVision and gut morphology was assessed. Untargeted metabolomic and proteomic profiling was performed followed by univariate and multivariate analyses. RESULTS: VPA exposure induced ASD-like behavioral hyperactivity, and severe gastrointestinal abnormalities. Cocoa co-treatment ameliorated both behavioral performance and gut architecture. Metabolomic profiling revealed VPA-associated disruptions in neurotransmission, methylation, mitochondrial function and redox homeostasis. Proteomic profiling showed elevated levels of trafficking protein particle complex subunit 11, proteasomal ubiquitin receptor, betaine-homocysteine S-methyltransferase 1 (BHMT-1), and desmoplakin-A, consistent with genotoxic stress and impaired protein trafficking. Cocoa co-treatment normalized BHMT-1 and desmoplakin-A expression and mitigated broader metabolic dysregulation. CONCLUSION: Collectively, these results suggest that polyphenol-rich cocoa may represent a promising multi-targeted nutraceutical approach for mitigating ASD-related neurodevelopmental and metabolic disturbances.

Animals↗
PubMed2004

Proteomic characterization of two snake venoms: Naja naja atra and Agkistrodon halys.

Snake venom is a complex mixture of proteins and peptides, and a number of studies have described the biological properties of several venomous proteins. Nevertheless, a complete proteomic profile of venom from any of the many species of snake is not available. Proteomics now makes it possible to globally identify proteins from a complex mixture. To assess the venom proteomic profiles from Naja naja atra and Agkistrodon halys, snakes common to southern China, we used a combination strategy, which included the following four different approaches: (i) shotgun digestion plus HPLC with ion-trap tandem MS, (ii) one-dimensional SDS/PAGE plus HPLC with tandem MS, (iii) gel filtration plus HPLC with tandem MS and (iv) gel filtration and 2DE (two-dimensional gel electrophoresis) plus MALDI-TOF (matrix-assisted laser desorption ionization-time-of-flight) MS. In the present paper, we report the novel identification of 124 and 74 proteins and peptides in cobra and viper venom respectively. Functional analysis based upon toxin categories reveals that, as expected, cobra venom has a high abundance of cardio- and neurotoxins, whereas viper venom contains a significant amount of haemotoxins and metalloproteinases. Although approx. 80% of gel spots from 2DE displayed high-quality MALDI-TOF-MS spectra, only 50% of these spots were confirmed to be venom proteins, which is more than likely to be a result of incomplete protein databases. Interestingly, these data suggest that post-translational modification may be a significant characteristic of venomous proteins.

Agkistrodon↗
PubMed2005

SPLINDID: a semi-parametric, model-based method for obtaining transcription rates and gene regulation parameters from genomic and proteomic expression profiles.

PURPOSE: To evaluate a semi-parametric, model-based approach for obtaining transcription rates from mRNA and protein expression. METHODS: The transcription profile input was modeled using an exponential function of a cubic spline and the dynamics of translation; mRNA and protein degradation were modeled using the Hargrove-Schmidt model. The transcription rate profile and the translation, and mRNA and protein degradation rate constants were estimated by the maximum likelihood method. RESULTS: Simulated datasets generated from the stochastic, transit compartment and dispersion signaling models were used to test the approach. The approach satisfactorily fit the mRNA and protein data, and accurately recapitulated the parameter and the normalized transcription rate profile values. The approach was successfully used to model published data on tyrosine aminotransferase pharmacodynamics. CONCLUSIONS: The semi-parametric approach is effective and could be useful for delineating the genomic effects of drugs. AVAILABILITY: Code suitable for use with the ADAPT software program is available from the corresponding author. CONTACT: murali@acsu.buffalo.edu.

Algorithms↗
PubMedDate not supplied

Proteome analysis of antibody-expressing CHO cells in response to hyperosmotic pressure.

To better understand intracellular responses to hyperosmotic pressure of recombinant Chinese hamster ovary (rCHO) cells expressing an antibody, we have taken a proteomics approach. Using two-dimensional electrophoresis and mass spectrometry, a proteome profile of rCHO cells comprising 23 identified proteins was established. On the basis of this proteome profile, we found three proteins of which expression levels were significantly changed at 450 mOsm/kg. Compared to the results at 300 mOsm/kg, two glycolytic enzymes, glyceraldehyde-3-phosphate dehydrogenase and pyruvate kinase, were found to be up-regulated, probably leading to an increased metabolic energy for antibody synthesis. The elevation of specific glucose consumption rate at 450 mOsm/kg agreed with the up-regulation of these glycolytic enzymes. On the other hand, tubulin expression was down-regulated, reflecting a depressed cell growth rate at 450 mOsm/kg. Taken together, this study shows the potential of the proteomics approach in understanding intracellular and physiological changes in cells and seeking a better insight into possible environmental or genetic manipulation approaches for increasing foreign protein production in rCHO cells.

Amino Acid Sequence↗
PubMed2006

Proteomic analysis of urine in kidney transplant patients with BK virus nephropathy.

The differentiation of BK virus-associated renal allograft nephropathy (BKVAN) from acute allograft rejection (AR) in renal transplant recipients is an important clinical problem because the treatment can be diametrically opposite for the two conditions. The aim of this discovery-phase biomarker development study was to examine feasibility of developing a noninvasive method to differentiate BKVAN from AR. Surface-enhanced laser desorption/ionization (SELDI) time-of-flight mass spectrometry analysis was used to compare proteomic profiles of urine samples of 21 patients with BKVAN, 28 patients with AR (Banff Ia to IIb), and 29 patients with stable graft function. SELDI analysis showed proteomic profiles that were significantly different in the BKVAN group versus the AR and stable transplant groups. Peaks that corresponded to m/z values of 5.872, 11.311, 11.929, 12.727, and 13.349 kD were significantly higher in patients with BKVAN. Bioinformatics analyses allowed distinction of profiles of patients with BKVAN from patients with AR and stable patients. SELDI profiles also showed a high degree of reproducibility. Proteomic analysis of urine may offer a noninvasive way to differentiate BKVAN from AR in clinical practice. The identification of individual proteomic peaks can improve further the clinical utility of this screening method.

Adult↗
PubMed2005

Proteome analysis and comparison of Clostridium acetobutylicum ATCC 824 and Spo0A strain variants.

The proteomic profiles of several Clostridium acetobutylicum strains were compared by two-dimensional gel electrophoresis and mass spectroscopy. The proteomic profile of C. acetobutylicum wild type strain ATCC 824 with and without a commonly used control plasmid and with a spo0A overexpression plasmid pMSPOA was compared. A total of 2,081 protein spots were analyzed; 23 proteins were chosen to be identified of which 18 were unique and 5 were proteins located in more than one location. The proteins identified were classified into heat shock stress response, acid and solvent formation, and transcription and translation proteins. Spo0A was identified and its protein expression was confirmed to be absent in the spo0A knockout SKO1 strain as expected, as was the protein Adc, which is known to be regulated by Spo0A. The expression of six proteins was not detected in strain SKO1 indicating these proteins require Spo0A. Spo0A overexpression affected the abundance of proteins involved in glycolysis, translation, heat shock stress response, and energy production. Two features were identified: five of the 23 proteins identified were located in more than one position and clusters of protein spots resembled fingers of a straightened hand. Normally a protein localizes to only one spot on the gel; localization of a protein to more than one spot is indicative of post-translational modifications, suggesting that such modification of proteins may be a more prevalent mechanism in C. acetobutylicum than previously thought. The clusters of protein spots resembling fingers of a straightened hand were in the acidic high molecular weight areas. Two such protein spots were identified as variants of the same protein, GroEL.

Bacterial Proteins↗
PubMed2002

A comparative study on feature selection and classification methods using gene expression profiles and proteomic patterns.

Feature selection plays an important role in classification. We present a comparative study on six feature selection heuristics by applying them to two sets of data. The first set of data are gene expression profiles from Acute Lymphoblastic Leukemia (ALL) patients. The second set of data are proteomic patterns from ovarian cancer patients. Based on features chosen by these methods, error rates of several classification algorithms were obtained for analysis. Our results demonstrate the importance of feature selection in accurately classifying new samples.

Algorithms↗
PubMed2005

Possible prediction of chemoradiosensitivity of esophageal cancer by serum protein profiling.

PURPOSE: Establishment of a reliable method of predicting the efficacy of chemotherapy and radiotherapy is necessary to provide the most suitable treatment for each cancer patient. We investigated whether proteomic profiles of serum samples obtained from untreated patients were capable of being used to predict the efficacy of combined preoperative chemoradiotherapy against esophageal cancer. EXPERIMENTAL DESIGN: Proteomic spectra were obtained from a training set of 27 serum samples (15 pathologically diagnosed responders to preoperative chemoradiotherapy and 12 nonresponders) by surface-enhanced laser desorption and ionization coupled with hybrid quadrupole time-of-flight mass spectrometry. A proteomic pattern prediction model was constructed from the training set by machine learning algorithms, and it was then tested with an independent validation set consisting of serum samples from 15 esophageal cancer patients in a blinded manner. RESULTS: We selected a set of four mass peaks, at 7,420, 9,112, 17,123, and 12,867 m/z, from a total of 859 protein peaks, as perfectly distinguishing responders from nonresponders in the training set with a support vector machine algorithm. This set of peaks (i.e., the classifier) correctly diagnosed chemoradiosensitivity in 93.3% (14 of 15) of the cases in the validation set. CONCLUSIONS: Recent mass spectrometric approaches have revealed that serum contains a large volume of information that reflects the microenvironment of diseased organs. Although a multi-institutional large-scale study will be necessary to confirm each component of the classifier, there is a subtle but definite difference in serum proteomic profile between responders and nonresponders to chemoradiotherapy.

Aged↗
PubMed2005

Cytokine profile and proteome analysis in bronchoalveolar lavage of patients with sarcoidosis, pulmonary fibrosis associated with systemic sclerosis and idiopathic pulmonary fibrosis.

The aim of this study was to analyze the type of immune response (Th1, Th2) and protein composition of bronchoalveolar lavage (BAL) of patients with sarcoidosis, pulmonary fibrosis associated with systemic sclerosis (SSc) and idiopathic pulmonary fibrosis (IPF). Flow cytometry analysis of intracellular cytokines revealed different patterns: in IPF and SSc Th2 profiles were predominant, whereas in sarcoidosis Th1 prevailed. The proteomic analysis of BAL fluid (BALF) showed that there were quantitative differences between the three diseases. These were more evident between sarcoidosis and IPF, confirming our previous observations, whereas SSc had an intermediate profile between the two, however with some peculiarities. Comparison of BALF protein maps, constructed with the same quantity of total proteins, enabled us to identify the main profiles of the three diseases: an increase in plasma protein prevalent in sarcoidosis and also present in SSc, though for fewer proteins with respect to IPF and a greater abundance of low molecular weight proteins, mainly locally produced, in IPF. These findings are in line with the different pathogenesis of these diseases: IPF is considered a prevalently fibrotic disorder limited to the lung, with intense local production of functionally different proteins, whereas sarcoidosis and SSc are systemic immunoinflammatory diseases.

Adult↗
PubMed2006

Proteome-on-a-chip: mirage, or on the horizon?

Proteomics has emerged as the next great scientific challenge in the post-genome era. But even the most basic form of proteomics, proteome profiling, i.e., identifying all of the proteins expressed in a given sample, has proven to be a demanding task. The proteome presents unique analytical challenges, including significant molecular diversity, an extremely wide concentration range, and a tendency to adsorb to solid surfaces. Microfluidics has been touted as being a useful tool for developing new methods to solve complex analytical challenges, and, as such, seems a natural fit for application to proteome profiling. In this review, we summarize the recent progress in the field of microfluidics in four key areas related to this application: chemical processing, sample preconcentration and cleanup, chemical separations, and interfaces with mass spectrometry. We identify the bright spots and challenges for the marriage of microfluidics and proteomics, and speculate on the outlook for progress.

Animals↗
PubMed2006

SELDI-TOF plasma profiles distinguish individuals in a protein C-deficient family with thrombotic episodes occurring before age 40.

We tested the hypothesis that differences in the low-molecular-weight (500-20,000 Da) proteomic profile of plasma may be detectable between members of a protein C-deficient family who have suffered thrombotic events before age 40 compared to family members without a history of venous thrombosis. Unfractionated plasma samples from members of a previously described large thrombophilic kindred with type I protein C deficiency were applied to ProteinChip weak cation exchange interaction arrays (WCX2; Ciphergen Biosystems, Fremont, CA, USA) and subjected to SELDI-TOF (surface-enhanced laser desorption/ionization time-of-flight) mass spectrometry using the Ciphergen PBSII ProteinChip System (Ciphergen Biosystems). Profiles were analyzed by a boosted decision-tree algorithm. When individuals who had presented with deep venous thrombosis (DVT) before the age of 40 (n = 21) were compared to age-matched, healthy family members (n = 50), the proteomic patterns defined by the decision-tree analysis could classify the entity of DVT before age 40 with 67% sensitivity, at a specificity of 86%. When a small group of cases with history of superficial venous thrombosis (n = 6) was added to the case group, the sensitivity was 87.5% at a specificity of 80%. These data support the hypothesis that members of the protein C deficient Vermont kindred II who suffer a thrombotic event before age 40 display significant differences in low-molecular-weight proteomics profile compared to those who remain disease-free. This is the first study to apply SELDI-TOF technology in conjunction with a bioinformatics tool to analyze low-molecular-weight proteomic patterns in patients with venous thrombosis.

Adult↗
PubMed2007

Analysis of antihypertensive drugs in the heart of animal models: a proteomic approach.

Arterial hypertension is the most frequent chronic disease and it is an important cause of morbidity and mortality in the developed world. Arterial hypertension is associated with such adverse effects as accelerated arteriosclerosis and pathological left ventricular hypertrophy, among others. The molecular mechanisms affecting left ventricular hypertrophy remain mostly unknown. The advent of proteome profiling has facilitated the elucidation of disease-associated proteins, paving the way for molecular diagnostics and the identification of novel therapeutic targets. We explored the proteomic profile of pathological left ventricular hypertrophy in comparison with normal heart in a model of rats and investigated the proteomic changes in response to different antihypertensive regimens in order to elucidate their cardioprotective effects. Here we describe in depth the protocol for this type of study.

Animals↗
PubMed2026

A Rapid Poly(ethylene glycol)-Assisted Magnetic Isolation Approach for High-Throughput Extracellular Vesicle Isolation and Subsequent Biomarker Analysis.

Extracellular vesicles (EVs) are crucial mediators of intercellular communication and have the potential to serve as biomarkers for disease diagnosis and therapeutic monitoring. However, most EV isolation methods often require large sample volumes and specialized instruments or involve trade-offs between purity, yield, cost, and scalability. We developed MagPEG, a workflow that combines poly(ethylene glycol) (PEG)-mediated EV aggregation with magnetic beads to provide a simple, reproducible alternative to ultracentrifugation, size-exclusion chromatography, and commercial precipitation kits. Our optimization experiments clarified the PEG concentration, ionic strength, and bead surface chemistry that collectively influence EV aggregation, capture efficiency, and contaminant coprecipitation, allowing us to define conditions that improve purity while maintaining high recovery. Compared with commonly used methods, MagPEG produced EVs with comparable size distribution, EV markers, and proteomic profiles while relying only on standard laboratory supplies. A key feature of the platform is that EVs and EV-associated DNA, RNA, and proteins can be sequentially extracted from the same bead-bound material, reducing sample loss and hands-on time and enabling multiomic analysis for limited clinical or small animal samples. MagPEG is compatible with downstream applications including proteomics, bead-based assays, and miRNA quantification. When applied to human serum, the method supported high-throughput EV proteomic profiling and enabled the identification of Alzheimer's disease-associated protein signatures, illustrating its utility for biomarker discovery. Overall, our results establish MagPEG as a powerful, rapid, scalable, and high-throughput solution for translational applications in biomarker discovery.

Polyethylene Glycols↗
PubMedDate not supplied

Synthesis of acid-cleavable light isotope-coded affinity tags (ICAT-L) for potential use in proteomic expression profiling analysis.

A convenient synthesis of some homologous light isotope-coded affinity tags (ICAT-L) containing an acid-labile moiety between the affinity component biotin and an electrophilic polar linker is described. These light ICAT reagents give smooth mass spectral signals in tandem mass spectrometry (MS/MS) analyses of some commercially available cysteine-containing peptides. However, these ICAT molecules are designed for use in identification and relative quantification of whole or partially purified cellular and tissue proteomes. Since the biotin moiety can be readily cleaved off the reagent after mass tagging, undesired residual fragmentation patterns caused by biotin of derived peptides, as normally observed using biotin-containing ICAT reagents, are effectively eliminated. This strategy should enhance peptide sequence coverage significantly which, in turn, should result in improving the quality of data obtained during data-dependent peptide mass and tandem mass spectral analysis of whole proteomes.

Biotin↗
PubMed2002

Evaluation of proteome reference maps for cross-species identification of proteins by peptide mass fingerprinting.

We tested whether proteome reference maps established for one species can be used for cross-species protein identification by comparing two-dimensional protein gel patterns and protein identification data of two closely related bacterial strains and four plant species. First, proteome profiles of two strains of the fully sequenced bacterium Sinorhizobium meliloti were compared as an example of close relatedness, high reproducibility and sequence availability. Secondly, the proteome profiles of three legumes (Medicago truncatula, Melilotus alba and Trifolium subterraneum), and the nonlegume rice (Oryza sativa) were analysed to test cross-species similarities. In general, we found stronger similarities in gel patterns of the arrayed proteins between the two bacterial strains and between the plant species than could be expected from the sequence similarities. However, protein identity could not be concluded from their gel position, not even when comparing strains of the same species. Surprisingly, in the bacterial strains peptide mass fingerprinting was more reliable for species-specific protein identification than N-terminal sequencing. While peptide masses were found to be unreliable for cross-species protein identification, we present useful criteria to determine confident matching against species-specific expressed sequence tag databases. In conclusion, we present evidence that cautions the use of proteome reference maps and peptide mass fingerprinting for cross-species protein identification.

Electrophoresis, Gel, Two-Dimensional↗
PubMed2006

A proteomic approach for dissecting H-Ras signaling networks in NIH/3T3 mouse embryonic fibroblast cells.

To elucidate an understanding into H-Ras protein network, we have established various oncogene H-Ras-expressing NIH/3T3 mouse embryonic fibroblast cell clones, which are expressing G12V H-Ras, G12R H-Ras, and G12V/T35S H-Ras proteins under the tight control of expression by an antibiotic doxycycline. Here we provide a catalog of proteome profiles in total cell lysate derived from the oncogenic and partial loss of function H-Ras-expressing NIH/3T3 cells. In this biological context, we compared total proteome changes by the combined methods of 2-DE, quantitative image analysis and MALDI-TOF-MS analysis both commonly in oncogenic and partial loss of function H-Ras expression system. Thus, we tried to dissect H-Ras signaling pathway, especially a downstream effector molecule, Raf in NIH/3T3 cells using proteomics tools. In this study, we centralized upon the proteome profile changes as common targets for oncogenic H-Ras and a partial loss of function H-Ras in the H-Ras-expressing cells. Thirteen protein spots were selected as what the staining intensities on the gels for 2-DE images from both kinds of cells were consistently changed in their protein expression level. Differentially regulated expression was further confirmed for some subsets of candidates by semiquantitative RT-PCR and Western blot analysis using specific antibodies. Taken together, our results obtained and present here show that the comparative analysis of proteome from oncogenic and partial loss of function H-Ras-expressing cells has yielded interpretable data to elucidate the protein network directly and/or indirectly.

Animals↗
PubMedDate not supplied

[Clinical proteomics: towards early detection of cancers].

A key challenge in clinical proteomic of cancer is the identification of biomarkers that would allow early detection, diagnosis and monitor progression of the disease to improve long-term survival of patients. Recent advances in proteomic instrumentation and computational methodologies offer unique chance to rapidly identify these new candidate markers or pattern of markers. The combination of retentate affinity chromatography and surfaced-enhanced laser desorption/ionization time-of-flight (SELDI-TOF) mass spectrometry is one of the most interesting new approaches for cancer diagnostic using proteomic profiling. This review aims to summarize the results of studies that have used this new technology method for the early diagnosis of human cancer. Despite promising results, the use of the proteomic profiling as a diagnostic tool brought some controversies and technical problems and still requires some efforts to be standardised and validated.

Biomarkers, Tumor↗