scholarly journals Chemically-blocked Antibody Microarray for Multiplexed High-throughput Profiling of Specific Protein Glycosylation in Complex Samples

10.3791/3791 ◽  
2012 ◽  
Author(s):  
Chen Lu ◽  
Joshua L. Wonsidler ◽  
Jianwei Li ◽  
Yanming Du ◽  
Timothy Block ◽  
...  
Keyword(s):  
High Throughput ◽  
Specific Protein ◽  
Protein Glycosylation ◽  
Antibody Microarray ◽  
Complex Samples

scholarly journals High-throughput single-cell rheology in complex samples by dynamic real-time deformability cytometry

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Bob Fregin ◽  
Fabian Czerwinski ◽  
Doreen Biedenweg ◽  
Salvatore Girardo ◽  
Stefan Gross ◽  
...  
Keyword(s):  
Single Cell ◽  
Real Time ◽  
High Throughput ◽  
Complex Samples ◽  
Cell Rheology ◽  
Deformability Cytometry

The study of protein–protein interactions in bacteria

2012 ◽  
Vol 58 (11) ◽  
pp. 1241-1257 ◽  
Author(s):  
Roberto Velasco-García ◽  
Rocío Vargas-Martínez
Keyword(s):  
Hybrid System ◽  
High Throughput ◽  
Protein Interactions ◽  
Specific Protein ◽  
False Positives ◽  
Interaction Networks ◽  
Protein Protein Interactions ◽  
Extensive Data ◽  
False Positives And Negatives

Many of the functions fulfilled by proteins in the cell require specific protein–protein interactions (PPI). During the last decade, the use of high-throughput experimental technologies, primarily based on the yeast 2-hybrid system, generated extensive data currently located in public databases. This information has been used to build interaction networks for different species. Unfortunately, due to the nature of the yeast 2-hybrid system, these databases contain many false positives and negatives, thus they require purging. A method for confirming these PPI is to test them using a technique that operates in vivo and detects binary PPI. This article comprises an overview of the study of PPI and describes the main techniques that have been used to identify bacterial PPI, prioritizing those that can be used for their verification, and it also mentions a number of PPI that have been identified or confirmed using these methods.

scholarly journals Sensitive and fast characterization of site-specific protein glycosylation with capillary electrophoresis coupled to mass spectrometry

Talanta ◽  
2018 ◽  
Vol 179 ◽  
pp. 22-27 ◽  
Author(s):  
Yanyan Qu ◽  
Liangliang Sun ◽  
Guijie Zhu ◽  
Zhenbin Zhang ◽  
Elizabeth H. Peuchen ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Capillary Electrophoresis ◽  
Specific Protein ◽  
Protein Glycosylation ◽  
Site Specific

scholarly journals GlypNirO: An automated workflow for quantitative N- and O-linked glycoproteomic data analysis

2020 ◽  
Author(s):  
Toan K. Phung ◽  
Cassandra L. Pegg ◽  
Benjamin L. Schulz
Keyword(s):  
Mass Spectrometry ◽  
Hepatocellular Carcinoma ◽  
Data Analysis ◽  
High Throughput ◽  
Protein Glycosylation ◽  
Software Pipeline ◽  
Site Specific ◽  
Proteome Discoverer ◽  
Automated Software

AbstractMass spectrometry glycoproteomics is rapidly maturing, allowing unprecedented insights into the diversity and functions of protein glycosylation. However, quantitative glycoproteomics remains challenging. We developed GlypNirO, an automated software pipeline which integrates the complementary outputs of Byonic and Proteome Discoverer to allow high-throughput automated quantitative glycoproteomic data analysis. The output of GlypNirO is clearly structured, allowing manual interrogation, and is also appropriate for input into diverse statistical workflows. We used GlypNirO to analyse a published plasma glycoproteome dataset and identified changes in site-specific N- and O-glycosylation occupancy and structure associated with hepatocellular carcinoma as putative biomarkers of disease.

scholarly journals GlypNirO: An automated workflow for quantitative N- and O-linked glycoproteomic data analysis

2020 ◽  
Vol 16 ◽  
pp. 2127-2135 ◽  
Author(s):  
Toan K Phung ◽  
Cassandra L Pegg ◽  
Benjamin L Schulz
Keyword(s):  
Mass Spectrometry ◽  
Hepatocellular Carcinoma ◽  
Data Analysis ◽  
High Throughput ◽  
Protein Glycosylation ◽  
Software Pipeline ◽  
Site Specific ◽  
Proteome Discoverer ◽  
Automated Software

Mass spectrometry glycoproteomics is rapidly maturing, allowing unprecedented insights into the diversity and functions of protein glycosylation. However, quantitative glycoproteomics remains challenging. We developed GlypNirO, an automated software pipeline which integrates the complementary outputs of Byonic and Proteome Discoverer to allow high-throughput automated quantitative glycoproteomic data analysis. The output of GlypNirO is clearly structured, allowing manual interrogation, and is also appropriate for input into diverse statistical workflows. We used GlypNirO to analyse a published plasma glycoproteome dataset and identified changes in site-specific N- and O-glycosylation occupancy and structure associated with hepatocellular carcinoma as putative biomarkers of disease.

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