Biology subjects

Frejno, M.

Publications and source records attributed to Frejno, M..

2 recordsLinked to original sources

bioRxiv2024

Unifying the analysis of bottom-up proteomics data with CHIMERYS

Proteomic workflows generate vastly complex peptide mixtures that are analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS), creating thousands of spectra, most of which are chimeric and contain fragment ions from more than one peptide. Because of differences in data acquisition strategies such as data-dependent (DDA), data-independent (DIA) or parallel reaction monitoring (PRM), separate software packages employing different analysis concepts are used for peptide identification and quantification, even though the underlying information is principally the same. Here, we introduce CHIMERYS, a novel, spectrum-centric search algorithm designed for the deconvolution of chimeric spectra that unifies proteomic data analysis. Using accurate predictions of peptide retention time, fragment ion intensities and applying regularized linear regression, it explains as much fragment ion intensity as possible with as few peptides as possible. Together with rigorous false discovery rate control, CHIMERYS accurately identifies and quantifies multiple peptides per tandem mass spectrum in DDA, DIA and PRM experiments.

biochemistry↗

bioRxiv2018

A deep proteome and transcriptome abundance atlas of 29 healthy human tissues

Genome-, transcriptome- and proteome-wide measurements provide valuable insights into how biological systems are regulated. However, even fundamental aspects relating to which human proteins exist, where they are expressed and in which quantities are not fully understood. Therefore, we have generated a systematic, quantitative and deep proteome and transcriptome abundance atlas from 29 paired healthy human tissues from the Human Protein Atlas Project and representing human genes by 17,615 transcripts and 13,664 proteins. The analysis revealed that few proteins show truly tissue-specific expression, that vast differences between mRNA and protein quantities within and across tissues exist and that the expression levels of proteins are often more stable across tissues than those of transcripts. In addition, only ~2% of all exome and ~7% of all mRNA variants could be confidently detected at the protein level showing that proteogenomics remains challenging, requires rigorous validation using synthetic peptides and needs more sophisticated computational methods. Many uses of this resource can be envisaged ranging from the study of gene/protein expression regulation to protein biomarker specificity evaluation to name a few.

systems biology↗