Global Survey of Human T Leukemic Cells by Integrating Proteomics and Transcriptomics Profiling

Wu, Linfeng; Hwang, Sun-Il; Karim, Rezaul; Lu, Long; Mayya, Viveka; Gerstein, Mark; Eng, Jimmy K.; Lundgren, Deborah H.; Han, David K.

doi:10.1074/mcp.m700017-mcp200

Cited by 31 publications

(39 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Duplicate analysis was performed on all samples because earlier studies indicated that 1 MS analysis is not sufficient for exhaustive protein coverage (10). Consistently, in the present study, we detected additional proteins upon reanalysis of the same sample (average of 26% more proteins for human subjects 3 and 4 and 21% for mouse).…”

Section: Protein Identification By Sequential 1-dimensional Page and supporting

confidence: 76%

Human myelin proteome and comparative analysis with mouse myelin

Ishii¹,

Dutta

Wark³

et al. 2009

Proc. Natl. Acad. Sci. U.S.A.

Self Cite

106

View full text Add to dashboard Cite

Myelin, formed by oligodendrocytes (OLs) in the CNS, is critical for axonal functions, and its damage leads to debilitating neurological disorders such as multiple sclerosis. Understanding the molecular mechanisms of myelination and the pathogenesis of human myelin disease has been limited partly by the relative lack of identification and functional characterization of the repertoire of human myelin proteins. Here, we present a large-scale analysis of the myelin proteome, using the shotgun approach of 1-dimensional PAGE and liquid chromatography/tandem MS. Three hundred eight proteins were commonly identified from human and mouse myelin fractions. Comparative microarray analysis of human white and gray matter showed that transcripts of several of these were elevated in OL-rich white matter compared with gray matter, providing confidence in their detection in myelin. Comparison with other databases showed that 111 of the identified proteins/transcripts also were expressed in OLs, rather than in astrocytes or neurons. Comparison with 4 previous myelin proteomes further confirmed more than 50% of the identified proteins and revealed the presence of 163 additional proteins. A select group of identified proteins also were verified by immunoblotting. We classified the identified proteins into biological subgroups and discussed their relevance in myelin biogenesis and maintenance. Taken together, the study provides insights into the complexity of this metabolically active membrane and creates a valuable resource for future in-depth study of specific proteins in myelin with relevance to human demyelinating diseases.microarray ͉ oligodendrocyte ͉ proteomics ͉ mass spectrometry

show abstract

Section: Protein Identification By Sequential 1-dimensional Page and supporting

confidence: 76%

Human myelin proteome and comparative analysis with mouse myelin

Ishii¹,

Dutta

Wark³

et al. 2009

Proc. Natl. Acad. Sci. U.S.A.

Self Cite

106

View full text Add to dashboard Cite

show abstract

“…This dataset was taken from a study on Human Jurkat A3 T leukemic cells (43). The cells were lysed, the lysate was separated using one-dimensional SDS-PAGE, and sections of the gel were digested with trypsin.…”

Section: Methodsmentioning

confidence: 99%

Combining Results of Multiple Search Engines in Proteomics

Shteynberg

Nesvizhskii

Moritz

et al. 2013

Molecular & Cellular Proteomics

171

159

View full text Add to dashboard Cite

A crucial component of the analysis of shotgun proteomics datasets is the search engine, an algorithm that attempts to identify the peptide sequence from the parent molecular ion that produced each fragment ion spectrum in the dataset. There are many different search engines, both commercial and open source, each employing a somewhat different technique for spectrum identification. The set of high-scoring peptide-spectrum matches for a defined set of input spectra differs markedly among the various search engine results; individual engines each provide unique correct identifications among a core set of correlative identifications. This has led to the approach of combining the results from multiple search engines to achieve improved analysis of each dataset. Here we review the techniques and available software for combining the results of multiple search engines and briefly compare the relative performance of these techniques. The most commonly used proteomics approach, shotgun proteomics, has become an invaluable tool for the highthroughput characterization of proteins in biological samples (1). This workflow relies on the combination of protein digestion, liquid chromatography (LC) 1 separation, tandem mass spectrometry (MS/MS), and sophisticated data analysis in its aim to derive an accurate and complete set of peptides and their inferred proteins that are present in the sample being studied. Although many variations are possible, the typical workflow begins with the digestion of proteins into peptides with a protease, typically trypsin. The resulting peptide mixture is first separated via LC and then subjected to mass spectrometry (MS) analysis. The MS instrument acquires fragment ion spectra on a subset of the peptide precursor ions that it measures. From the MS/MS spectra that measure the abundance and mass of the peptide ion fragments, peptides present in the mixture are identified and proteins are inferred by means of downstream computational analysis.The informatics component of the shotgun proteomics workflow is crucial for proper data analysis (2), and a wide variety of tools have emerged for this purpose (3). The typical informatics workflow can be summarized in a few steps: conversion from vendor proprietary formats to an open format, high-throughput interpretation of the MS/MS spectra with a search engine, and statistical validation of the results with estimation of the false discovery rate at a selected score threshold. Various tools for measuring relative peptide abundances may be applied, dependent on the type of quantitation technique applied in the experiment. Finally, the proteins present, and their abundance in the sample, are inferred based on the peptide identifications.One of the most computationally intensive and diverse steps in the computational analysis workflow is the use of a search engine to interpret the MS/MS spectra in order to determine the best matching peptide ion identifications (4), termed peptide-spectrum matches (PSMs). There are three main types of engines: sequence searc...

show abstract

“…In-gel digestion of unique bands was performed using trypsin, followed by microcapillary HPLC and LC-MS/MS analysis on the linear trap quadrupole. The obtained MS/MS data were subjected to database searches of mouse proteome using SEQUEST software, as described (41).…”

Section: Methodsmentioning

confidence: 99%

Essential roles of grp94 in gut homeostasis via chaperoning canonical Wnt pathway

Liu

Staron

Hong

et al. 2013

Proc. Natl. Acad. Sci. U.S.A.

103

109

View full text Add to dashboard Cite

Increasing evidence points to a role for the protein quality control in the endoplasmic reticulum (ER) in maintaining intestinal homeostasis. However, the specific role for general ER chaperones in this process remains unknown. Herein, we report that a major ER heat shock protein grp94 interacts with MesD, a critical chaperone for the Wnt coreceptor low-density lipoprotein receptor-related protein 6 (LRP6). Without grp94, LRP6 fails to export from the ER to the cell surface, resulting in a profound loss of canonical Wnt signaling. The significance of this finding is demonstrated in vivo in that grp94 loss causes a rapid and profound compromise in intestinal homeostasis with gut-intrinsic defect in the proliferation of intestinal crypts, compromise of nuclear β-catenin translocation, loss of crypt-villus structure, and impaired barrier function. Taken together, our work has uncovered the role of grp94 in chaperoning LRP6-MesD in coordinating intestinal homeostasis, placing canonical Wnt-signaling pathway under the direct regulation of the general protein quality control machinery in the ER.

show abstract

Global Survey of Human T Leukemic Cells by Integrating Proteomics and Transcriptomics Profiling

Cited by 31 publications

References 34 publications

Human myelin proteome and comparative analysis with mouse myelin

Human myelin proteome and comparative analysis with mouse myelin

Combining Results of Multiple Search Engines in Proteomics

Essential roles of grp94 in gut homeostasis via chaperoning canonical Wnt pathway

Contact Info

Product

Resources

About