No abstract

Ion mobility brings an additional dimension of separation to liquid chromatography-mass spectrometry, improving identification of peptides and proteins in complex mixtures. A recently introduced timsTOF mass spectrometer (Bruker) couples trapped ion mobility separation to time-of-flight mass analysis. With the parallel accumulation serial fragmentation (PASEF) method, the timsTOF platform achieves promising results, yet analysis of the data generated on this platform represents a major bottleneck. Currently, MaxQuant and PEAKS are most commonly used to analyze these data. However, due to the high complexity of timsTOF PASEF data, both require substantial time to perform even standard tryptic searches. Advanced searches (e.g. with many variable modifications, semi- or non-enzymatic searches, or open searches for post-translational modification discovery) are practically impossible. We have extended our fast peptide identification tool MSFragger to support timsTOF PASEF data, and developed a label-free quantification tool, IonQuant, for fast and accurate 4-D feature extraction and quantification. Using a HeLa data set published by Meier et al. (2018), we demonstrate that MSFragger identifies significantly (~30%) more unique peptides than MaxQuant (1.6.10.43), and performs comparably or better than PEAKS X+ (~10% more peptides). IonQuant outperforms both in terms of number of quantified proteins while maintaining good quantification precision and accuracy. Runtime tests show that MSFragger and IonQuant can fully process a typical two-hour PASEF run in under 70 minutes on a typical desktop (6 CPU cores, 32 GB RAM), significantly faster than other tools. Finally, through semi-enzymatic searching, we significantly increase the number of identified peptides. Within these semi-tryptic identifications, we report evidence of gas-phase fragmentation prior to MS/MS analysis.

Identification of post-translationally or chemically modified peptides in mass spectrometry-based proteomics experiments is a crucial yet challenging task. We have recently introduced a fragment ion indexing method and the MSFragger search engine to empower an open search strategy for comprehensive analysis of modified peptides. However, this strategy does not consider fragment ions shifted by unknown modifications, preventing modification localization and limiting the sensitivity of the search. Here we present a localization-aware open search method, in which both modification-containing (shifted) and regular fragment ions are indexed and used in scoring. We also implement a fast mass calibration and optimization method, allowing optimization of the mass tolerances and other key search parameters. We demonstrate that MSFragger with mass calibration and localization-aware open search identifies modified peptides with significantly higher sensitivity and accuracy. Comparing MSFragger to other modification-focused tools (pFind3, MetaMorpheus, and TagGraph) shows that MSFragger remains an excellent option for fast, comprehensive, and sensitive searches for modified peptides in shotgun proteomics data.

Match-between-runs is a powerful approach to mitigate the missing value problem in label-free quantification. It transfers features identified by MS/MS from one run to the other, but previously, there was no false discovery rate control over this process. We present a mixture model-based approach to estimate and control the false discovery rate, which we have implemented in IonQuant. We demonstrate the sensitivity, accuracy, and speed of IonQuant using proteomics data from timsTOF, Orbitrap, and Orbitrap coupled to FAIMS. Highlights• A mixture-model approach controls the false discovery rate of match-between-runs.• The method is implemented in IonQuant.• Experiments with various data types show high sensitivity and accuracy of IonQuant.

Oxidases are found to play a growing role in providing functional chemistry to marine adhesives for the permanent attachment of macrofouling organisms. Here, we demonstrate active peroxidase and lysyl oxidase enzymes in the adhesive layer of adult Amphibalanus amphitrite barnacles through live staining, proteomic analysis, and competitive enzyme assays on isolated cement. A novel full-length peroxinectin (AaPxt-1) secreted by barnacles is largely responsible for oxidizing phenolic chemistries; AaPxt-1 is driven by native hydrogen peroxide in the adhesive and oxidizes phenolic substrates typically preferred by phenoloxidases (POX) such as laccase and tyrosinase. A major cement protein component AaCP43 is found to contain ketone/aldehyde modifications via 2,4-dinitrophenylhydrazine (DNPH) derivatization, also called Brady's reagent, of cement proteins and immunoblotting with an anti-DNPH antibody. Our work outlines the landscape of molt-related oxidative pathways exposed to barnacle cement proteins, where ketone- and aldehyde-forming oxidases use peroxide intermediates to modify major cement components such as AaCP43.