Can We Boost -Glycopeptide Identification Confidence? Smart Collision Energy Choice Taking into Account Structure and Search Engine.

High confidence and reproducibility are still challenges in bottom-up mass spectrometric -glycopeptide identification. The collision energy used in the MS/MS measurements and the database search engine used to identify the species are perhaps the two most decisive factors. We investigated how the structural features of -glycopeptides and the choice of the search engine influence the optimal collision energy, delivering the highest identification confidence.

Neonatal Screening for Cystic Fibrosis in Hungary-First-Year Experiences.

The aim of this study is to evaluate the strategy of the cystic fibrosis newborn screening (CFNBS) programme in Hungary based on the results of the first year of screening. A combined immunoreactive trypsinogen (IRT) and pancreatitis-associated protein (PAP) CFNBS protocol (IRT/IRT×PAP/IRT) was applied with an IRT-dependent safety net (SN). Out of 88,400 newborns, 256 were tested screen-positive.

Diversity Matters: Optimal Collision Energies for Tandem Mass Spectrometric Analysis of a Large Set of N-Glycopeptides.

Identification and characterization of N-glycopeptides from complex samples are usually based on tandem mass spectrometric measurements. Experimental settings, especially the collision energy selection method, fundamentally influence the obtained fragmentation pattern and hence the confidence of the database search results ("score"). Using standards of naturally occurring glycoproteins, we mapped the Byonic and pGlyco search engine scores of almost 200 individual N-glycopeptides as a function of collision energy settings on a quadrupole time of flight instrument.