Mass spectrometry (MS)-based proteomics workflows can crudely be classified into two distinct regimes, targeting either relatively small peptides (i.e., 0.7 kDa < Mw < 3.0 kDa) or small to medium sized intact proteins (i.e., 10 kDa < Mw < 30 kDa), respectively, termed bottom-up and top-down proteomics. Recently, a niche has started to be explored covering the analysis of middle-range peptides (i.e., 3.0 kDa < Mw < 10 kDa), aptly termed middle-down proteomics. Although middle-down proteomics can follow, in principle, a modular workflow similar to that of bottom-up proteomics, we hypothesized that each of these modules would benefit from targeted optimization to improve its overall performance in the analysis of middle-range sized peptides. Hence, to generate middle-range sized peptides from cellular lysates, we explored the use of the proteases Asp-N and Glu-C and a nonenzymatic acid induced cleavage. To increase the depth of the proteome, a strong cation exchange (SCX) separation, carefully tuned to improve the separation of longer peptides, combined with reversed phase-liquid chromatography (RP-LC) using columns packed with material possessing a larger pore size, was used. Finally, after evaluating the combination of potentially beneficial MS settings, we also assessed the peptide fragmentation techniques, including higher-energy collision dissociation (HCD), electron-transfer dissociation (ETD), and electron-transfer combined with higher-energy collision dissociation (EThcD), for characterization of middle-range sized peptides. These combined improvements clearly improve the detection and sequence coverage of middle-range peptides and should guide researchers to explore further how middle-down proteomics may lead to an improved proteome coverage, beneficial for, among other things, the enhanced analysis of (co-occurring) post-translational modifications.

Diseases at the molecular level are complex and patient dependent, necessitating development of strategies that enable precision treatment to optimize clinical outcomes. Organoid technology has recently been shown to have the potential to recapitulate the in vivo characteristics of the original individual's tissue in a three-dimensional in vitro culture system. Here, we present a quantitative mass-spectrometry-based proteomic analysis and a comparative transcriptomic analysis of human colorectal tumor and healthy organoids derived, in parallel, from seven patients. Although gene and protein signatures can be derived to distinguish the tumor organoid population from healthy organoids, our data clearly reveal that each patient possesses a distinct organoid signature at the proteomic level. We demonstrate that a personalized patient-specific organoid proteome profile can be related to the diagnosis of a patient and with future development contribute to the generation of personalized therapies.

The original PRIDE Converter tool greatly simplified the process of submitting mass spectrometry (MS)-based proteomics data to the PRIDE database. However, after much user feedback, it was noted that the tool had some limitations and could not handle several user requirements that were now becoming commonplace. This prompted us to design and implement a whole new suite of tools that would build on the successes of the original PRIDE Converter and allow users to generate submission-ready, well-annotated PRIDE XML files. The PRIDE Converter 2 tool suite allows users to convert search result files into PRIDE XML (the format needed for performing submissions to the PRIDE database), generate mzTab skeleton files that can be used as a basis to submit quantitative and gel-based MS data, and post-process PRIDE XML files by filtering out contaminants and empty spectra, or by merging several PRIDE XML files together. All the tools have both a graphical user interface that provides a dialog-based, user-friendly way to convert and prepare files for submission, as well as a command-line interface that can be used to integrate the tools into existing or novel pipelines, for batch processing and power users. The PRIDE Converter 2 tool suite will thus become a cornerstone in the submission process to PRIDE and, by extension, to the ProteomeXchange consortium of MS-proteomics data repositories.

Staphylococcus aureus is a major cause of infections worldwide, and infection results in a variety of diseases. As of no surprise, protein phosphorylation is an important game player in signaling cascades and has been shown to be involved in S. aureus virulence. Albeit long neglected, eukaryotic-type serine/threonine kinases in S. aureus have been implicated in this complex signaling cascades. Due to the substoichiometric nature of protein phosphorylation and a lack of suitable analysis tools, the knowledge of these cascades is, however, to date, still limited. Here, were apply an optimized protocol for efficient phosphopeptide enrichment via Fe 3+ -IMAC followed by LC-MS/MS to get a better understanding of the impact of protein phosphorylation on the complex signaling networks involved in pathogenicity. By profiling a serine/threonine kinase and phosphatase mutant from a methicillin-resistant S. aureus mutant library, we generated the most comprehensive phosphoproteome data set of S. aureus to date, aiding a better understanding of signaling in bacteria. With the identification of 3800 class I p-sites, we were able to increase the number of identifications by more than 21 times compared with recent literature. In addition, we were able to identify 74 downstream targets of the only reported eukaryotic-type Ser/Thr kinase of the S. aureus strain USA300, Stk1. This work allowed an extensive analysis of the bacterial phosphoproteome and indicates that Ser/Thr kinase signaling is far more abundant than previously anticipated in S. aureus .