Femtomol sensitivity post-digest18O labeling for relative quantification of differential protein complex composition

2004 ◽  
Vol 18 (8) ◽  
pp. 869-876 ◽  
Author(s):  
Marcus Bantscheff ◽  
Birgit Dümpelfeld ◽  
Bernhard Kuster
2021 ◽  
Vol 1 ◽  
Author(s):  
Gökçe Senger ◽  
Martin H. Schaefer

Protein assembly is a highly dynamic process and proteins can interact in different ways and stoichiometries within a complex. The importance of maintaining protein stoichiometry for complex function and avoiding aggregation of orphan subunits has been demonstrated. However, how exactly the organization of proteins into complexes constrains differential protein abundance in extreme cellular conditions like cancer, where a lot of protein abundance changes occur, has not been systematically investigated. To study this, we collected proteomic data made available by the Clinical Proteomic Tumor Analysis Consortium (CPTAC) to quantify proteomic changes during carcinogenesis and systematically tested five interaction types in complexes to investigate which of these features impact on protein abundance correlation patterns in cancer. We found that higher than expected fraction of protein complex subunits does not show changes in their abundances compared to those in the normal samples. Furthermore, we found that the way proteins interact in complexes indeed constrains their co-abundance patterns. Our results highlight the role of the interactions between the proteins and the need of cancer cells to deal with aberrant changes in protein abundance.


Author(s):  
Yusuke Matsui ◽  
Yuichi Abe ◽  
Kohei Uno ◽  
Satoru Miyano

Abstract Motivation The full spectrum of abnormalities in cancer-associated protein complexes remains largely unknown. Comparing the co-expression structure of each protein complex between tumor and healthy cells may provide insights regarding cancer-specific protein dysfunction. However, the technical limitations of mass spectrometry-based proteomics, including contamination with biological protein variants, causes noise that leads to non-negligible over- (or under-) estimating co-expression. Results We propose a robust algorithm for identifying protein complex aberrations in cancer based on differential protein co-expression testing. Our method based on a copula is sufficient for improving identification accuracy with noisy data compared to conventional linear correlation-based approaches. As an application, we use large-scale proteomic data from renal cancer to show that important protein complexes, regulatory signaling pathways and drug targets can be identified. The proposed approach surpasses traditional linear correlations to provide insights into higher-order differential co-expression structures. Availability and implementation https://github.com/ymatts/RoDiCE. Supplementary information Supplementary data are available at Bioinformatics online.


2021 ◽  
Author(s):  
Youngwoo Lee ◽  
Thomas W Okita ◽  
Daniel B Szymanski

Multiprotein complexes execute and coordinate diverse cellular processes such as organelle biogenesis, vesicle trafficking, cell signaling, and metabolism. Knowledge about their composition and localization provides useful clues about the mechanisms of cellular homeostasis and systems-level control. This is of great biological importance and practical significance in heterotrophic rice endosperm and aleurone-subaleurone tissues that are a primary source of seed vitamins and stored energy. Dozens of protein complexes have been implicated in the synthesis, transport, and storage of seed proteins, lipids, vitamins, and minerals. Mutations in protein complexes that control RNA transport result in aberrant endosperm with shrunken and floury phenotypes, significantly reducing seed yield and quality. The purpose of this research is to broadly predict protein complex composition in the aleurone-subaleurone layers of developing rice seeds using co-fractionation mass spectrometry. Following orthogonal chromatographic separations of biological replicates, thousands of protein elution profiles were subjected to distance-based clustering to enable a large-scale determination of multimerization state and complex composition. Predictions included evolutionarily conserved proteins across diverse functional categories, including novel heteromeric RNA binding protein complexes that influence seed quality. This effective and open-ended proteomics pipeline provides useful clues about systems-level controls in the early stage of rice seed development.


2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Jonathan D. Lautz ◽  
Edward P. Gniffke ◽  
Emily A. Brown ◽  
Karen B. Immendorf ◽  
Ryan D. Mendel ◽  
...  

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