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 .

Tumor heterogeneity is a major cause of therapeutic resistance. Immunotherapy may exploit alternative vulnerabilities of drug-resistant cells, where tumor-specific human leukocyte antigen (HLA) peptide ligands are promising leads to invoke targeted anti-tumor responses. Here, we investigate the variability in HLA class I peptide presentation between different clonal cells of the same colorectal cancer patient, using an organoid system. While clone-specific differences in HLA peptide presentation were observed, broad inter-clone variability was even more prevalent (15–25%). By coupling organoid proteomics and HLA peptide ligandomics, we also found that tumor-specific ligands from DNA damage control and tumor suppressor source proteins were prominently presented by tumor cells, coinciding likely with the silencing of such cytoprotective functions. Collectively, these data illustrate the heterogeneous HLA peptide presentation landscape even within one individual, and hint that a multi-peptide vaccination approach against highly conserved tumor suppressors may be a viable option in patients with low tumor-mutational burden.

Genome sequencing of arguably the simplest known animal, Trichoplax adhaerens, uncovered a rich array of transcription factor and signalling pathway genes. Although the existence of such genes allows speculation about the presence of complex regulatory events, it does not reveal the level of actual protein expression and functionalization through posttranslational modifications. Using high-resolution mass spectrometry, we here semi-quantify 6,516 predicted proteins, revealing evidence of horizontal gene transfer and the presence at the protein level of nodes important in animal signalling pathways. Moreover, our data demonstrate a remarkably high activity of tyrosine phosphorylation, in line with the hypothesized burst of tyrosine-regulated signalling at the instance of animal multicellularity. Together, this Trichoplax proteomics data set offers significant new insight into the mechanisms underlying the emergence of metazoan multicellularity and provides a resource for interested researchers.

Quality control is increasingly recognized as a crucial aspect of mass spectrometry based proteomics. Several recent papers discuss relevant parameters for quality control and present applications to extract these from the instrumental raw data. What has been missing, however, is a standard data exchange format for reporting these performance metrics. We therefore developed the qcML format, an XML-based standard that follows the design principles of the related mzML, mzIdentML, mzQuantML, and TraML standards from the HUPO-PSI (Proteomics Standards Initiative). In addition to the XML format, we also provide tools for the calculation of a wide range of quality metrics as well as a database format and interconversion tools, so that existing LIMS systems can easily add relational storage of the quality control data to their existing schema. We here describe the qcML specification, along with possible use cases and an illustrative example of the subsequent analysis possibilities. All information about qcML is available at http://code.google.com/p/qcml.

cAMP regulates cellular functions primarily by activating PKA. The involvement of PKAs in various signaling pathways occurring simultaneously in different cellular compartments necessitates stringent spatial and temporal regulation. This specificity is largely achieved by binding of PKA to protein scaffolds, whereby a distinct group of proteins called A kinase anchoring proteins (AKAPs) play a dominant role. AKAPs are a diverse family of proteins that all bind via a small PKA binding domain to the regulatory subunits of PKA. The binding affinities between PKA and several AKAPs can be different for different isoforms of the regulatory subunits of PKA. Here we employ a combination of affinity chromatography and mass spectrometry-based quantitative proteomics to investigate specificity in PKA-AKAP interactions. Three different immobilized cAMP analogs were used to enrich for PKA and its interacting proteins from several systems; HEK293 and RCC10 cells and rat lung and testis tissues. Stable isotope labeling was used to confidently identify and differentially quantify target proteins and their preferential binding affinity for the three different cAMP analogs. We were able to enrich all four isoforms of the regulatory subunits of PKA and concomitantly identify more than 10 AKAPs. A selective enrichment of the PKA RI isoforms could be achieved; which allowed us to unravel which AKAPs bind preferentially to the RI or RII regulatory domains of PKA. Of the twelve AKAPs detected, seven preferentially bound to RII, whereas the remaining five displayed at least dual specificity with a potential preference for RI.