Search results for " proteomic"
showing 10 items of 171 documents
Proteomic Strategies and their Application in Cancer Research
2006
The understanding of carcinogenesis and tumor progression on a molecular basis needs a detailed study of proteins as effector molecules and as critical components of the multiple interconnected signaling pathways that drive the neoplastic phenotype. Thus, the proteomic approach represents a powerful tool for the challenge of the post-genomic era. The term “cancer proteome” refers to the collection of proteins expressed by a given cancer cell and should be considered as a highly dynamic entity within the cell, which affects a variety of cellular activities. The emerging proteomic analysis platforms including 2D-PAGE, mass spectrometry technologies, and protein microarrays represent powerful…
Protein modulation in mouse heart under acute and chronic hypoxia
2011
Exploring cellular mechanisms underlying beneficial and detrimental responses to hypoxia represents the object of the present study. Signaling molecules controlling adaptation to hypoxia (HIF-1α), energy balance (AMPK), mitochondrial biogenesis (PGC-1α), autophagic/apoptotic processes regulation and proteomic dysregulation were assessed. Responses to acute hypoxia (AH) and chronic hypoxia (CH) in mouse heart proteome were detected by 2-D DIGE, mass spectrometry and antigen-antibody reactions. Both in AH and CH, the results indicated a deregulation of proteins related to sarcomere stabilization and muscle contraction. Neither in AH nor in CH the HIF-1α stabilization was observed. In AH, the …
Biomedical applications of ion mobility-enhanced data-independent acquisition-based label-free quantitative proteomics.
2014
Mass spectrometry-based proteomics greatly benefited from recent improvements in instrument performance and the development of bioinformatics solutions facilitating the high-throughput quantification of proteins in complex biological samples. In addition to quantification approaches using stable isotope labeling, label-free quantification has emerged as the method of choice for many laboratories. Over the last years, data-independent acquisition approaches have gained increasing popularity. The integration of ion mobility separation into commercial instruments enabled researchers to achieve deep proteome coverage from limiting sample amounts. Additionally, ion mobility provides a new dimens…
Enhancing Sensitivity of Microflow-Based Bottom-Up Proteomics through Postcolumn Solvent Addition.
2019
The introduction of more sensitive mass spectrometers allows researchers to adapt front-end liquid chromatography (LC) to individual needs for the analysis of complex proteomes. Where absolute sensitivity is not paramount, it is advantageous to switch from a highly sensitive nanoflow-LC setup, the de facto standard platform in mass-spectrometry (MS)-based discovery proteomics, to a more robust, high-throughput-compatible microflow or conventional-flow setup. To enhance the microflow-LC-MS electrospray process of complex proteomic samples, we tested the effects of different solvents, including 2-propanol, methanol, and acetonitrile, pure or as mixture with dimethyl sulfoxide, which were adde…
Mass Spectrometry and Imaging Analysis of Nanoparticle-Containing Vesicles Provide a Mechanistic Insight into Cellular Trafficking
2014
Rational design of nanocarriers for drug delivery approaches requires an unbiased knowledge of uptake mechanisms and intracellular trafficking pathways. Here we dissected these processes using a quantitative proteomics approach. We isolated intracellular vesicles containing superparamagnetic iron oxide polystyrene nanoparticles and analyzed their protein composition by label-free quantitative mass spectrometry. The proteomic snapshot of organelle marker proteins revealed that an atypical macropinocytic-like mechanism mediated the entry of nanoparticles. We show that the entry mechanism is controlled by actin reorganization, atypical macropinocytic signaling, and ADP-ribosylation factor 1. A…
Using Deep Learning to Extrapolate Protein Expression Measurements
2020
Mass spectrometry (MS)-based quantitative proteomics experiments typically assay a subset of up to 60% of the ≈20 000 human protein coding genes. Computational methods for imputing the missing values using RNA expression data usually allow only for imputations of proteins measured in at least some of the samples. In silico methods for comprehensively estimating abundances across all proteins are still missing. Here, a novel method is proposed using deep learning to extrapolate the observed protein expression values in label-free MS experiments to all proteins, leveraging gene functional annotations and RNA measurements as key predictive attributes. This method is tested on four datasets, in…
Unraveling the Composition of Insecticidal Crystal Proteins in Bacillus thuringiensis: a Proteomics Approach.
2020
ABSTRACT Bacillus thuringiensis (Bt) is the most widely used active ingredient for biological insecticides. The composition of δ-endotoxins (Cry and Cyt proteins) in the parasporal crystal determines the toxicity profile of each Bt strain. However, a reliable method for their identification and quantification has not been available, due to the high sequence identity of the genes that encode the δ-endotoxins and the toxins themselves. Here, we have developed an accurate and reproducible mass spectrometry-based method (liquid chromatography-tandem mass spectrometry-multiple reaction monitoring [LC-MS/MS-MRM]) using isotopically labeled proteotypic peptides for each protein in a particular mix…
A Proposed Knowledge Based Approach for Solving Proteomics Issues
2010
In this paper we present a novel knowledge-based approach that aims at helping scientists to face and resolve a large number of proteomics problem. The system architecture is based on an ontology to model the knowledge base, a reasoner that starting from the user's request and a set of rules builds the workflow of tasks to be done, and an executor that runs the algorithms and software scheduled by the reasoner. The system can interact with the user showing him intermediate results and several options in order to refine the workflow and supporting him to choose among different forks. Thanks to the presence of the knowledge base and the modularity provided by the ontology, the system can be e…
Missing value imputation in proximity extension assay-based targeted proteomics data
2020
Targeted proteomics utilizing antibody-based proximity extension assays provides sensitive and highly specific quantifications of plasma protein levels. Multivariate analysis of this data is hampered by frequent missing values (random or left censored), calling for imputation approaches. While appropriate missing-value imputation methods exist, benchmarks of their performance in targeted proteomics data are lacking. Here, we assessed the performance of two methods for imputation of values missing completely at random, the previously top-benchmarked ‘missForest’ and the recently published ‘GSimp’ method. Evaluation was accomplished by comparing imputed with remeasured relative concentrations…
Proteomic fingerprinting of apple fruit, juice, and cider via combinatorial peptide ligand libraries and MS analysis
2018
Combinatorial peptide ligand libraries coupled to MS was applied to extensively map the proteome of apple fruit, and to detect its presence in commercial apple juice and cider to evaluate their authenticity and genuineness. Using the Uniprot_Malus database, 96 proteins were detected in apples, among which 30 proteins were specifically captured via combinatorial peptide ligand libraries. Next, three proteins, previously recognized in fruits, were found in apple juice, which were involved in cellular metabolism of fruit maturation and in allergenic reactions. On the other hand, only one Malus allergen was identified in cider beads eluate, demonstrating that the industrial processes did not pr…