Highlights • Single-pot workflow for manual or automated enrichment of N-terminal peptides. • Sensitive enrichment of protein N termini from 10,000 cells or 2 g crude proteome. • Data independent acquisition improves precision of peptide level quantification. • First degradomic analyses of sorted immune cells, single seedlings, and mitochondria from patient cells.

The nonlinear signal response of electrospray ionization (ESI) presents a critical limitation for mass spectrometry (MS)-based quantitative analysis. In the field of metabolomics research, this issue has largely remained unaddressed; MS signal intensities are usually directly used to calculate fold changes for quantitative comparison. In this work, we demonstrate that, due to the nonlinear ESI response, signal intensity ratios of a metabolic feature calculated between two samples may not reflect their real metabolic concentration ratios (i.e., fold-change compression), implying that conventional fold-change calculations directly using MS signal intensities can be misleading. In this regard, we developed a quality control (QC) sample-based signal calibration workflow to overcome the quantitative bias caused by the nonlinear ESI response. In this workflow, calibration curves for every metabolic feature are first established using a QC sample injected in serial injection volumes. The MS signals of each metabolic feature are then calibrated to their equivalent QC injection volumes for comparative analysis. We demonstrated this novel workflow in a targeted metabolite analysis, showing that the accuracy of fold-change calculations can be significantly improved. Furthermore, in a metabolomic comparison of the bone marrow interstitial fluid samples from leukemia patients before and after chemotherapy, an additional 59 significant metabolic features were found with fold changes larger than 1.5, and an additional 97 significant metabolic features had fold changes corrected by more than 0.1. This work enables high-quality quantitative analysis in untargeted metabolomics, thus providing more confident biological hypotheses generation.

The high affinity of biotin to streptavidin has made it one of the most widely used affinity tags in proteomics. Early methods used biotin for enrichment alone and mostly ignored the biotin labeled peptide. Recent advances in labeling led to an increase in biotinylation efficiency and shifted the interest to detection of the site of biotinylation. This increased confidence in identification and provides additional structural information yet it requires efficient release of the biotinylated protein/peptide and sensitive separation and detection of biotinylated peptides by LC-MS/MS. Despite its long use in affinity proteomics the effect of biotinylation on the chromatographic, ionization, and fragmentation behaviour and ultimate detection of peptides is not well understood. To address this we compare two commercially-available biotin labels EZ-Link Sulfo-NHS-Biotin and Sulfo-NHS-SS-Biotin, the latter one containing a labile linker to efficiently release biotin to determine the effects of peptide modification on peptide detection. We describe an increase of hydrophobicity and charge reduction with increasing number of biotin labels attached. Based on our data we recommend gradient optimization to account for more hydrophobic biotinylated peptides and include singly charged precursors to account for charge reduction by biotin.