Reviews & Perspectives
- In Brief Availability of proteomics data in the public domain has become the norm, as it has been the case in genomics and transcriptomics for many years. Analogously to sequencing data, there are increasing ethical issues and legal requirements related to sensitive human clinical proteomics data. We review the current state of the art and make concrete recommendations to address these issues in the proteomics field, which are summarized in four different areas.
- In Brief The analytical power of targeted proteomics depends on how efficiently the mass spectrometer detects target peptides. A number of “smart” acquisition approaches have been developed that enable more targets per run and improve analytical performance such as sensitivity, specificity, and quantitative accuracy. This review provides an introduction to these methods and highlights their inherent strengths and weaknesses.
- In Brief Recent years have seen an explosion in novel strategies for quantitative glycomics and glycoproteomics. Whether through metabolic incorporation of stable isotopes, deposition of custom isotopic labels, or high-throughput isobaric chemical tags, these numerous novel strategies provide ease of access to glycomic and glycoproteomic investigation. This review highlights the recent innovations in labeling methods, label-free strategies, acquisition modes, and bioinformatic tools for glycan and glycopeptide quantitation, while providing critical evaluations and technical considerations to enable effective analysis.
- In Brief To understand the roles of glycoproteins in biological processes, it is necessary to quantify the changes that occur to glycosylation at individual sites and to the whole molecule. That glycoprotein glycosylation is inherently heterogeneous means that the distribution of glycoforms at each glycosite must be quantified in order to inform calculation of molecular similarities. We review analytical and statistical methods for determining glycoprotein molecular similarities from glycoproteomics data.