scholarly journals Highly Multiplexed and Reproducible Ion-Current-Based Strategy for Large-Scale Quantitative Proteomics and the Application to Protein Expression Dynamics Induced by Methylprednisolone in 60 Rats

2014 ◽  
Vol 86 (16) ◽  
pp. 8149-8157 ◽  
Author(s):  
Eslam Nouri-Nigjeh ◽  
Siddharth Sukumaran ◽  
Chengjian Tu ◽  
Jun Li ◽  
Xiaomeng Shen ◽  
...  
Keyword(s):  
Protein Expression ◽  
Quantitative Proteomics ◽  
Large Scale ◽  
Ion Current

scholarly journals Automation of large scale transient protein expression in mammalian cells

2011 ◽  
Vol 175 (2) ◽  
pp. 209-215 ◽  
Author(s):  
Yuguang Zhao ◽  
Benjamin Bishop ◽  
Jordan E. Clay ◽  
Weixian Lu ◽  
Margaret Jones ◽  
...  
Keyword(s):  
Protein Expression ◽  
Mammalian Cells ◽  
Large Scale ◽  
Transient Protein Expression ◽  
Expression In Mammalian Cells

scholarly journals Label-Free Quantitative Proteomics in a Methylmalonyl-CoA Mutase-Silenced Neuroblastoma Cell Line

2018 ◽  
Vol 19 (11) ◽  
pp. 3580 ◽  
Author(s):  
Michele Costanzo ◽  
Armando Cevenini ◽  
Emanuela Marchese ◽  
Esther Imperlini ◽  
Maddalena Raia ◽  
...  
Keyword(s):  
Protein Expression ◽  
Cell Line ◽  
Quantitative Proteomics ◽  
Quantitative Methods ◽  
Neuroblastoma Cell ◽  
Neuroblastoma Cell Line ◽  
Mitochondrial Activity ◽  
Label Free ◽  
Inborn Errors ◽  
Odd Chain Fatty Acids

Methylmalonic acidemias (MMAs) are inborn errors of metabolism due to the deficient activity of methylmalonyl-CoA mutase (MUT). MUT catalyzes the formation of succinyl-CoA from methylmalonyl-CoA, produced from propionyl-CoA catabolism and derived from odd chain fatty acids β-oxidation, cholesterol, and branched-chain amino acids degradation. Increased methylmalonyl-CoA levels allow for the presymptomatic diagnosis of the disease, even though no approved therapies exist. MMA patients show hyperammonemia, ketoacidosis, lethargy, respiratory distress, cognitive impairment, and hepatomegaly. The long-term consequences concern neurologic damage and terminal kidney failure, with little chance of survival. The cellular pathways affected by MUT deficiency were investigated using a quantitative proteomics approach on a cellular model of MUT knockdown. Currently, a consistent reduction of the MUT protein expression was obtained in the neuroblastoma cell line (SH-SY5Y) by using small-interfering RNA (siRNA) directed against an MUT transcript (MUT siRNA). The MUT absence did not affect the cell viability and apoptotic process in SH-SY5Y. In the present study, we evaluate and quantify the alterations in the protein expression profile as a consequence of MUT-silencing by a mass spectrometry-based label-free quantitative analysis, using two different quantitative strategies. Both quantitative methods allowed us to observe that the expression of the proteins involved in mitochondrial oxido-reductive homeostasis balance was affected by MUT deficiency. The alterated functional mitochondrial activity was observed in siRNA_MUT cells cultured with a propionate-supplemented medium. Finally, alterations in the levels of proteins involved in the metabolic pathways, like carbohydrate metabolism and lipid metabolism, were found.

scholarly journals New insights into Trypanosoma cruzi evolution and genotyping based on system-wide protein expression profiles (PhyloQuant)

2020 ◽  
Author(s):  
Simon Ngao Mule ◽  
Andrè Guillherme da Costa Martins ◽  
Livia Rosa-Fernandes ◽  
Gilberto Santos de Oliveira ◽  
Carla Monadeli Rodrigues ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Trypanosoma Cruzi ◽  
Protein Expression ◽  
Large Scale ◽  
Expression Profiles ◽  
Shotgun Proteomics ◽  
Close Correlation ◽  
Evolutionary Relationships ◽  
Trypanosome Species ◽  
Protein Expression Profiles

AbstractThe etiological agent of Chagas disease, Trypanosoma cruzi, is subdivided into seven genetic subdivisions termed discrete typing units (DTUs), TcI-TcVI and Tcbat. The relevance of T. cruzi genetic diversity to the variable clinical course of the disease, virulence, pathogenicity, drug resistance, transmission cycles and ecological distribution justifies the concerted efforts towards understanding the population structure of T. cruzi strains. In this study, we introduce a novel approach termed ‘phyloquant’ to infer the evolutionary relationships and assignment of T. cruzi strains to their DTUs based on differential protein expression profiles evidenced by bottom up large scale mass spectrometry-based quantitative proteomic features. Mass spectrometry features analyzed using parsimony (MS1, iBAQ and LFQ) showed a close correlation between protein expression and T. cruzi DTUs and closely related trypanosome species. Although alternative topologies with minor differences between the three MS features analyzed were demonstrated, we show congruence to well accepted evolutionary relationships of T. cruzi DTUs; in all analyses TcI and Tcbat were sister groups, and the parental nature of genotype TcII and the hybrid genotypes TcV/TcVI were corroborated. Character mapping of genetic distance matrices based on phylogenetics and phyloquant clustering showed statistically significant correlations. We propose the first quantitative shotgun proteomics approach as a complement strategy to the genetic-based assignment of T. cruzi strains to DTUs and evolutionary inferences. Moreover, this approach allows for the identification of differentially regulated and strain/DTU/species-specific proteins, with potential application in the identification of strain/DTU specific biomarkers and candidate therapeutic targets. In addition, the correlation between multi-gene protein expression and divergence of trypanosome species was evaluated, adding another level to understand the genetic subdivisions among T. cruzi DTUs.

scholarly journals ComplexBrowser: a tool for identification and quantification of protein complexes in large scale proteomics datasets

2019 ◽  
Author(s):  
Wojciech Michalak ◽  
Vasileios Tsiamis ◽  
Veit Schwämmle ◽  
Adelina Rogowska-Wrzesińska
Keyword(s):  
T Cell Activation ◽  
Protein Complex ◽  
Quantitative Proteomics ◽  
Large Scale ◽  
Protein Complexes ◽  
Quantitative Measure ◽  
Exploratory Analysis ◽  
List Type ◽  
Link Type ◽  
Complex Components

AbstractWe have developed ComplexBrowser, an open source, online platform for supervised analysis of quantitative proteomics data that focuses on protein complexes. The software uses information from CORUM and Complex Portal databases to identify protein complex components. Based on the expression changes of individual complex subunits across the proteomics experiment it calculates Complex Fold Change (CFC) factor that characterises the overall protein complex expression trend and the level of subunit co-regulation. Thus up- and down-regulated complexes can be identified. It provides interactive visualisation of protein complexes composition and expression for exploratory analysis. It also incorporates a quality control step that includes normalisation and statistical analysis based on Limma test. ComplexBrowser performance was tested on two previously published proteomics studies identifying changes in protein expression in human adenocarcinoma tissue and during activation of mouse T-cells. The analysis revealed 1519 and 332 protein complexes, of which 233 and 41 were found co-ordinately regulated in the respective studies. The adopted approach provided evidence for a shift to glucose-based metabolism and high proliferation in adenocarcinoma tissues and identification of chromatin remodelling complexes involved in mouse T-cell activation. The results correlate with the original interpretation of the experiments and also provide novel biological details about protein complexes affected. ComplexBrowser is, to our knowledge, the first tool to automate quantitative protein complex analysis for high-throughput studies, providing insights into protein complex regulation within minutes of analysis.A fully functional demo version of ComplexBrowser v1.0 is available online via http://computproteomics.bmb.sdu.dk/Apps/ComplexBrowser/The source code can be downloaded from: https://bitbucket.org/michalakw/complexbrowserHighlightsAutomated analysis of protein complexes in proteomics experimentsQuantitative measure of the coordinated changes in protein complex componentsInteractive visualisations for exploratory analysis of proteomics resultsIn briefComplexBrowser is capable of identifying protein complexes in datasets obtained from large scale quantitative proteomics experiments. It provides, in the form of the CFC factor, a quantitative measure of the coordinated changes in complex components. This facilitates assessing the overall trends in the processes governed by the identified protein complexes providing a new and complementary way of interpreting proteomics experiments.

Sign in / Sign up

Export Citation Format

Share Document