Longitudinal Fluctuations in Protein Concentrations and Higher-Order Structures in the Plasma Proteome of Kidney Failure Patients Subjected to a Kidney Transplant.

Using proteomics and complexome profiling, we evaluated in a year-long study longitudinal variations in the plasma proteome of kidney failure patients, prior to and after a kidney transplantation. The post-transplant period was complicated by bacterial infections, resulting in dramatic changes in the proteome, attributed to an acute phase response (APR). As positive acute phase proteins (APPs), being elevated upon inflammation, we observed the well-described C-reactive protein and Serum Amyloid A (SAA), but also Fibrinogen, Haptoglobin, Leucine-rich alpha-2-glycoprotein, Lipopolysaccharide-binding protein, Alpha-1-antitrypsin, Alpha-1-antichymotrypsin, S100, and CD14. As negative APPs, being downregulated upon inflammation, we identified the well-documented Serotransferrin and Transthyretin, but added Kallistatin, Heparin cofactor 2, and interalpha-trypsin inhibitor heavy chain H1 and H2 (ITIH1, ITIH2). For the patient with the most severe APR, we performed plasma complexome profiling by SEC-LC-MS on all longitudinal samples. We observed that several plasma proteins displaying alike concentration patterns coelute and form macromolecular complexes. By complexome profiling, we expose how SAA1 and SAA2 become incorporated into high-density lipid particles, replacing largely Apolipoprotein (APO)A1 and APOA4. Overall, our data highlight that the combination of in-depth longitudinal plasma proteome and complexome profiling can shed further light on correlated variations in the abundance of several plasma proteins upon inflammatory events.

A cyclin-dependent kinase-mediated phosphorylation switch of disordered protein condensation.

Cell cycle transitions result from global changes in protein phosphorylation states triggered by cyclin-dependent kinases (CDKs). To understand how this complexity produces an ordered and rapid cellular reorganisation, we generated a high-resolution map of changing phosphosites throughout unperturbed early cell cycles in single Xenopus embryos, derived the emergent principles through systems biology analysis, and tested them by biophysical modelling and biochemical experiments. We found that most dynamic phosphosites share two key characteristics: they occur on highly disordered proteins that localise to membraneless organelles, and are CDK targets. Furthermore, CDK-mediated multisite phosphorylation can switch homotypic interactions of such proteins between favourable and inhibitory modes for biomolecular condensate formation. These results provide insight into the molecular mechanisms and kinetics of mitotic cellular reorganisation.

Monitoring Human Milk ß-Casein Phosphorylation and O-Glycosylation Over Lactation Reveals Distinct Differences between the Proteome and Endogenous Peptidome.

Human milk is a vital biofluid containing a myriad of molecular components to ensure an infant's best start at a healthy life. One key component of human milk is ß-casein, a protein which is not only a structural constituent of casein micelles but also a source of bioactive, often antimicrobial, peptides contributing to milk's endogenous peptidome. Importantly, post-translational modifications (PTMs) like phosphorylation and glycosylation typically affect the function of proteins and peptides; however, here our understanding of ß-casein is critically limited. To uncover the scope of proteoforms and endogenous peptidoforms we utilized mass spectrometry (LC-MS/MS) to achieve in-depth longitudinal profiling of ß-casein from human milk, studying two donors across 16 weeks of lactation. We not only observed changes in ß-casein's known protein and endogenous peptide phosphorylation, but also in previously unexplored O-glycosylation. This newly discovered PTM of ß-casein may be important as it resides on known ß-casein-derived antimicrobial peptide sequences.

A serum proteome signature to predict mortality in severe COVID-19 patients.

Here, we recorded serum proteome profiles of 33 severe COVID-19 patients admitted to respiratory and intensive care units because of respiratory failure. We received, for most patients, blood samples just after admission and at two more later time points. With the aim to predict treatment outcome, we focused on serum proteins different in abundance between the group of survivors and non-survivors. We observed that a small panel of about a dozen proteins were significantly different in abundance between these two groups. The four structurally and functionally related type-3 cystatins AHSG, FETUB, histidine-rich glycoprotein, and KNG1 were all more abundant in the survivors. The family of inter-α-trypsin inhibitors, ITIH1, ITIH2, ITIH3, and ITIH4, were all found to be differentially abundant in between survivors and non-survivors, whereby ITIH1 and ITIH2 were more abundant in the survivor group and ITIH3 and ITIH4 more abundant in the non-survivors. ITIH1/ITIH2 and ITIH3/ITIH4 also showed opposite trends in protein abundance during disease progression. We defined an optimal panel of nine proteins for mortality risk assessment. The prediction power of this mortality risk panel was evaluated against two recent COVID-19 serum proteomics studies on independent cohorts measured in other laboratories in different countries and observed to perform very well in predicting mortality also in these cohorts. This panel may not be unique for COVID-19 as some of the proteins in the panel have previously been annotated as mortality markers in aging and in other diseases caused by different pathogens, including bacteria.

In-Depth Characterization of the Staphylococcus aureus Phosphoproteome Reveals New Targets of Stk1.

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 Fe3+-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.

Single-cell derived tumor organoids display diversity in HLA class I peptide presentation.

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.

Benefits of Collisional Cross Section Assisted Precursor Selection (caps-PASEF) for Cross-linking Mass Spectrometry.

Ion mobility separates molecules in the gas-phase based on their physico-chemical properties, providing information about their size as collisional cross-sections. The timsTOF Pro combines trapped ion mobility with a quadrupole, collision cell and a TOF mass analyzer, to probe ions at high speeds with on-the-fly fragmentation. Here, we show that on this platform ion mobility is beneficial for cross-linking MS (XL-MS). Cross-linking reagents covalently link amino acids in proximity, resulting in peptide pairs after proteolytic digestion. These cross-linked peptides are typically present at low abundance in the background of normal peptides, which can partially be resolved by using enrichable cross-linking reagents. Even with a very efficient enrichable cross-linking reagent, like PhoX, the analysis of cross-linked peptides is still hampered by the co-enrichment of peptides connected to a partially hydrolyzed reagent - termed mono-linked peptides. For experiments aiming to uncover protein-protein interactions these are unwanted byproducts. Here, we demonstrate that gas-phase separation by ion mobility enables the separation of mono-linked peptides from cross-linked peptide pairs. A clear partition between these two classes is observed at a CCS of 500 Å2 and a monoisotopic mass of 2 kDa, which can be used for targeted precursor selection. A total of 50-70% of the mono-linked peptides are prevented from sequencing, allowing the analysis to focus on sequencing the relevant cross-linked peptide pairs. In applications to both simple proteins and protein mixtures and a complete highly complex lysate this approach provides a substantial increase in detected cross-linked peptides.

Gaining Confidence in the Elusive Histidine Phosphoproteome.

Recent technological advances have made it possible to investigate the hitherto rather elusive protein histidine phosphorylation. However, confident site-specific localization of protein histidine phosphorylation remains challenging. Here, we address this problem, presenting a mass-spectrometry-based approach that outperforms classical HCD fragmentation without compromising sensitivity. We use the phosphohistidine immonium ion as a diagnostic tool as well as ETD-based fragmentation techniques to achieve unambiguous identification and localization of histidine-phosphorylation sites. The work presented here will allow more confident investigation of the phosphohistidine proteome to reveal the roles of histidine phosphorylation in cellular signaling events.

Toward an efficient workflow for the analysis of the human milk peptidome.

There is a growing interest for investigating endogenous peptides from human biofluids which may provide yet unknown functional benefits or provide an early indication of disease states as potential biomarkers. A major technical bottleneck in the investigation of endogenous peptides from body fluids, e.g., serum, urine, saliva, and milk, is that each of these fluids seems to require unique workflows for peptide extraction and analysis. Thus, protocols optimized for serum cannot be directly translated to milk. One biofluid that is readily available, but which has not been extensively explored, is human milk, whose analysis could contribute to our understanding of the immune development of the newborn infant. Due to the occurrence of highly abundant lipids, proteins, and saccharides, milk peptidomics requires dedicated sample preparation steps. The aim of this study was to develop a time and cost-efficient workflow for the analysis of the human milk peptidome, for which we compared peptide extraction methodologies and peptide fragmentation methods. A method using strong acid protein precipitation and analysis by collision-induced dissociation fragmentation was found to be superior to all other test methods, allowing us qualitative and quantitative detection of about 4000 endogenous human milk peptides in a total analysis time of just 18 h.

Discovery and Quantification of Nonhuman Proteins in Human Milk.

The question whether and which nonhuman peptides or proteins are present in human milk was raised many decades ago. However, due to cross-reactivity or nonspecific antibody recognition, the accuracy of detection by immunochemical methods has been a concern. Additionally, the relative low-abundance of nonhuman peptides/proteins in the complex milk sample makes them a challenging target to detect. Here, by deep proteome profiling, we detected several nonhuman peptides, which could be grouped as nonhuman proteins. We next estimated their concentration in human milk by combining data-dependent shotgun proteomics and parallel reaction monitoring. First, we fractionated human milk at the protein level and were able to detect 1577 human proteins. Additionally, we identified 109 nonhuman peptides, of which 71 were grouped into 36 nonhuman proteins. In the next step, we targeted 37 nonhuman peptides and nine of them could be repeatedly quantified in human milk samples. Peptides/proteins originating from bovine milk products were the dominant nonhuman proteins observed, notably bovine caseins (α-S1-, α-S2-, ß-, κ-caseins) and ß-lactoglobulin. The method we present here can be expanded to investigate more about nonhuman peptides and proteins in human milk and give a better understanding of how human milk plays a role in allergy prevention.

PaDuA: A Python Library for High-Throughput (Phospho)proteomics Data Analysis.

The increased speed and sensitivity in mass spectrometry-based proteomics has encouraged its use in biomedical research in recent years. Large-scale detection of proteins in cells, tissues, and whole organisms yields highly complex quantitative data, the analysis of which poses significant challenges. Standardized proteomic workflows are necessary to ensure automated, sharable, and reproducible proteomics analysis. Likewise, standardized data processing workflows are also essential for the overall reproducibility of results. To this purpose, we developed PaDuA, a Python package optimized for the processing and analysis of (phospho)proteomics data. PaDuA provides a collection of tools that can be used to build scripted workflows within Jupyter Notebooks to facilitate bioinformatics analysis by both end-users and developers.

Cross-ID: Analysis and Visualization of Complex XL-MS-Driven Protein Interaction Networks.

Protein interactions enable much more complex behavior than the sum of the individual protein parts would suggest and represents a level of biological complexity requiring full understanding when unravelling cellular processes. Cross-linking mass spectrometry has emerged as an attractive approach to study these interactions, and recent advances in mass spectrometry and data analysis software have enabled the identification of thousands of cross-links from a single experiment. The resulting data complexity is, however, difficult to understand and requires interactive software tools. Even though solutions are available, these represent an agglomerate of possibilities, and each features its own input format, often forcing manual conversion. Here we present Cross-ID, a visualization platform that links directly into the output of XlinkX for Proteome Discoverer but also plays well with other platforms by supporting a user-controllable text-file importer. The platform includes features like grouping, spectral viewer, gene ontology (GO) enrichment, post-translational modification (PTM) visualization, domains and secondary structure mapping, data set comparison, previsualization overlap check, and more. Validation of detected cross-links is available for proteins and complexes with known structure or for protein complexes through the DisVis online platform ( http://milou.science.uu.nl/cgi/services/DISVIS/disvis/ ). Graphs are exportable in PDF format, and data sets can be exported in tab-separated text files for evaluation through other software.

Toward an Optimized Workflow for Middle-Down Proteomics.

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.

Opposite Electron-Transfer Dissociation and Higher-Energy Collisional Dissociation Fragmentation Characteristics of Proteolytic K/R(X)n and (X)nK/R Peptides Provide Benefits for Peptide Sequencing in Proteomics and Phosphoproteomics.

A key step in shotgun proteomics is the digestion of proteins into peptides amenable for mass spectrometry. Tryptic peptides can be readily sequenced and identified by collision-induced dissociation (CID) or higher-energy collisional dissociation (HCD) because the fragmentation rules are well-understood. Here, we investigate LysargiNase, a perfect trypsin mirror protease, because it cleaves equally specific at arginine and lysine residues, albeit at the N-terminal end. LysargiNase peptides are therefore practically tryptic-like in length and sequence except that following ESI, the two protons are now both positioned at the N-terminus. Here, we compare side-by-side the chromatographic separation properties, gas-phase fragmentation characteristics, and (phospho)proteome sequence coverage of tryptic (i.e., (X)nK/R) and LysargiNase (i.e., K/R(X)n) peptides using primarily electron-transfer dissociation (ETD) and, for comparison, HCD. We find that tryptic and LysargiNase peptides fragment nearly as mirror images. For LysargiNase predominantly N-terminal peptide ions (c-ions (ETD) and b-ions (HCD)) are formed, whereas for trypsin, C-terminal fragment ions dominate (z-ions (ETD) and y-ions (HCD)) in a homologous mixture of complementary ions. Especially during ETD, LysargiNase peptides fragment into low-complexity but information-rich sequence ladders. Trypsin and LysargiNase chart distinct parts of the proteome, and therefore, the combined use of these enzymes will benefit a more in-depth and reliable analysis of (phospho)proteomes.

Personalized Proteome Profiles of Healthy and Tumor Human Colon Organoids Reveal Both Individual Diversity and Basic Features of Colorectal Cancer.

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.

An Augmented Multiple-Protease-Based Human Phosphopeptide Atlas.

Although mass-spectrometry-based screens enable thousands of protein phosphorylation sites to be monitored simultaneously, they often do not cover important regulatory sites. Here, we hypothesized that this is due to the fact that nearly all large-scale phosphoproteome studies are initiated by trypsin digestion. We tested this hypothesis using multiple proteases for protein digestion prior to Ti(4+)-IMAC-based enrichment. This approach increases the size of the detectable phosphoproteome substantially and confirms the considerable tryptic bias in public repositories. We define and make available a less biased human phosphopeptide atlas of 37,771 unique phosphopeptides, correlating to 18,430 unique phosphosites, of which fewer than 1/3 were identified in more than one protease data set. We demonstrate that each protein phosphorylation site can be linked to a preferred protease, enhancing its detection by mass spectrometry (MS). For specific sites, this approach increases their detectability by more than 1,000-fold.

The Early Metazoan Trichoplax adhaerens Possesses a Functional O-GlcNAc System.

Protein O-GlcNAcylation is a reversible post-translational signaling modification of nucleocytoplasmic proteins that is essential for embryonic development in bilateria. In a search for a reductionist model to study O-GlcNAc signaling, we discovered the presence of functional O-GlcNAc transferase (OGT), O-GlcNAcase (OGA), and nucleocytoplasmic protein O-GlcNAcylation in the most basal extant animal, the placozoan Trichoplax adhaerens. We show via enzymatic characterization of Trichoplax OGT/OGA and genetic rescue experiments in Drosophila melanogaster that these proteins possess activities/functions similar to their bilaterian counterparts. The acquisition of O-GlcNAc signaling by metazoa may have facilitated the rapid and complex signaling mechanisms required for the evolution of multicellular organisms.

Characterization of biases in phosphopeptide enrichment by Ti(4+)-immobilized metal affinity chromatography and TiO2 using a massive synthetic library and human cell digests.

Outcomes of comparative evaluations of enrichment methods for phosphopeptides depend highly on the experimental protocols used, the operator, the source of the affinity matrix, and the samples analyzed. Here, we attempt such a comparative study exploring a very large synthetic library containing thousands of serine, threonine, and tyrosine phosphorylated peptides, being present in roughly equal abundance, along with their nonphosphorylated counterparts, and use an optimized protocol for enrichment by TiO2 and Ti(4+)-immobilized metal affinity chromatography (IMAC) by a single operator. Surprisingly, our data reveal that there are minimal differences between enrichment of phosphopeptides by TiO2 and Ti(4+)-IMAC when considering biochemical and biophysical parameters such as peptide length, sequence surrounding the site, hydrophobicity, and nature of the amino acid phosphorylated. Similar results were obtained when evaluating a tryptic digest of a cellular lysate, representing a more natural source of phosphopeptides. All the data presented are available via ProteomeXchange with the identifier PXD000759.

qcML: an exchange format for quality control metrics from mass spectrometry experiments.

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.

Quantitative and qualitative proteome characteristics extracted from in-depth integrated genomics and proteomics analysis.

Quantitative and qualitative protein characteristics are regulated at genomic, transcriptomic, and posttranscriptional levels. Here, we integrated in-depth transcriptome and proteome analyses of liver tissues from two rat strains to unravel the interactions within and between these layers. We obtained peptide evidence for 26,463 rat liver proteins. We validated 1,195 gene predictions, 83 splice events, 126 proteins with nonsynonymous variants, and 20 isoforms with nonsynonymous RNA editing. Quantitative RNA sequencing and proteomics data correlate highly between strains but poorly among each other, indicating extensive nongenetic regulation. Our multilevel analysis identified a genomic variant in the promoter of the most differentially expressed gene Cyp17a1, a previously reported top hit in genome-wide association studies for human hypertension, as a potential contributor to the hypertension phenotype in SHR rats. These results demonstrate the power of and need for integrative analysis for understanding genetic control of molecular dynamics and phenotypic diversity in a system-wide manner.