Multilayered genetic and omics dissection of mitochondrial activity in a mouse reference population.

The manner by which genotype and environment affect complex phenotypes is one of the fundamental questions in biology. In this study, we quantified the transcriptome--a subset of the metabolome--and, using targeted proteomics, quantified a subset of the liver proteome from 40 strains of the BXD mouse genetic reference population on two diverse diets. We discovered dozens of transcript, protein, and metabolite QTLs, several of which linked to metabolic phenotypes. Most prominently, Dhtkd1 was identified as a primary regulator of 2-aminoadipate, explaining variance in fasted glucose and diabetes status in both mice and humans. These integrated molecular profiles also allowed further characterization of complex pathways, particularly the mitochondrial unfolded protein response (UPR(mt)). UPR(mt) shows strikingly variant responses at the transcript and protein level that are remarkably conserved among C. elegans, mice, and humans. Overall, these examples demonstrate the value of an integrated multilayered omics approach to characterize complex metabolic phenotypes.

Probing the salivary proteome for prognostic biomarkers in response to non-surgical periodontal therapy.

AIM: This prospective study investigated the salivary proteome before and after periodontal therapy. MATERIALS AND METHODS: Ten systemically healthy, non-smoking, stage III, grade C periodontitis patients underwent non-surgical periodontal treatment. Full-mouth periodontal parameters were measured, and saliva (n = 30) collected pre- (T0), and one (T1) and six (T6) months post-treatment. The proteome was investigated by label-free quantitative proteomics. Protein expression changes were modelled over time, with significant protein regulation considered at false discovery rate <0.05. RESULTS: Treatment significantly reduced bleeding scores, percentages of sites with pocket depth ≥5 mm, plaque and gingival indexes. One thousand seven hundred and thirteen proteins were identified and 838 proteins (human = 757, bacterial = 81) quantified (≥2 peptides). At T1, 80 (T1 vs. T0: 60↑:20↓), and at T6, 118 human proteins (T6 vs. T0: 67↑:51↓) were regulated. The salivary proteome at T6 versus T1 remained stable. Highest protein activity post- versus pre-treatment was observed for cellular movement and inflammatory response. The small proline-rich protein 3 (T1 vs. T0: 5.4-fold↑) and lymphocyte-specific protein 1 (T6 vs. T0: 4.6-fold↓) were the top regulated human proteins. Proteins from Neisseria mucosa and Treponema socranskii (T1 vs. T0: 8.0-fold↓, 4.9-fold↓) were down-regulated. CONCLUSIONS: Periodontal treatment reduced clinical disease parameters and these changes were reflected in the salivary proteome. This underscores the potential of utilizing saliva biomarkers as prognostic tools for monitoring treatment outcomes.

prolfqua: A Comprehensive R-Package for Proteomics Differential Expression Analysis.

Mass spectrometry is widely used for quantitative proteomics studies, relative protein quantification, and differential expression analysis of proteins. There is a large variety of quantification software and analysis tools. Nevertheless, there is a need for a modular, easy-to-use application programming interface in R that transparently supports a variety of well principled statistical procedures to make applying them to proteomics data, comparing and understanding their differences easy. The prolfqua package integrates essential steps of the mass spectrometry-based differential expression analysis workflow: quality control, data normalization, protein aggregation, statistical modeling, hypothesis testing, and sample size estimation. The package makes integrating new data formats easy. It can be used to model simple experimental designs with a single explanatory variable and complex experiments with multiple factors and hypothesis testing. The implemented methods allow sensitive and specific differential expression analysis. Furthermore, the package implements benchmark functionality that can help to compare data acquisition, data preprocessing, or data modeling methods using a gold standard data set. The application programmer interface of prolfqua strives to be clear, predictable, discoverable, and consistent to make proteomics data analysis application development easy and exciting. Finally, the prolfqua R-package is available on GitHub https://github.com/fgcz/prolfqua, distributed under the MIT license. It runs on all platforms supported by the R free software environment for statistical computing and graphics.

Paneth cells promote angiogenesis and regulate portal hypertension in response to microbial signals.

BACKGROUND & AIMS: Paneth cells (PCs) synthesize and secrete antimicrobial peptides that are key mediators of host-microbe interactions, establishing a balance between intestinal microflora and enteric pathogens. We observed that their number increases in experimental portal hypertension and aimed to investigate the mechanisms by which these cells can contribute to the regulation of portal pressure. METHODS: We first treated Math1Lox/LoxVilcreERT2 mice with tamoxifen to induce the complete depletion of intestinal PCs. Subsequently, we performed partial portal vein or bile duct ligation. We then studied the effects of these interventions on hemodynamic parameters, proliferation of blood vessels and the expression of genes regulating angiogenesis. Intestinal organoids were cultured and exposed to different microbial products to study the composition of their secreted products (by proteomics) and their effects on the proliferation and tube formation of endothelial cells (ECs). In vivo confocal laser endomicroscopy was used to confirm the findings on blood vessel proliferation. RESULTS: Portal hypertension was significantly attenuated in PC-depleted mice compared to control mice and was associated with a decrease in portosystemic shunts. Depletion of PCs also resulted in a significantly decreased density of blood vessels in the intestinal wall and mesentery. Furthermore, we observed reduced expression of intestinal genes regulating angiogenesis in Paneth cell depleted mice using arrays and next generation sequencing. Tube formation and wound healing responses were significantly decreased in ECs treated with conditioned media from PC-depleted intestinal organoids exposed to intestinal microbiota-derived products. Proteomic analysis of conditioned media in the presence of PCs revealed an increase in factors regulating angiogenesis and additional metabolic processes. In vivo endomicroscopy showed decreased vascular proliferation in the absence of PCs. CONCLUSIONS: These results suggest that in response to intestinal flora and microbiota-derived factors, PCs secrete not only antimicrobial peptides, but also pro-angiogenic signaling molecules, thereby promoting intestinal and mesenteric angiogenesis and regulating portal hypertension. LAY SUMMARY: Paneth cells are present in the lining of the small intestine. They prevent the passage of bacteria from the intestine into the blood circulation by secreting substances to fight bacteria. In this paper, we discovered that these substances not only act against bacteria, but also increase the quantity of blood vessels in the intestine and blood pressure in the portal vein. This is important, because high blood pressure in the portal vein may result in several complications which could be targeted with novel approaches.

Unraveling the proteomic changes involved in the resistance response of Cajanus platycarpus to herbivory by Helicoverpa armigera.

The pigeonpea wild relative Cajanus platycarpus is resistant to Helicoverpa armigera, one of the major pests responsible for yield losses in Cajanus cajan. Deciphering the molecular mechanism underlying host plant resistance is pertinent to identify proteins that aid in the mitigation of the insect pest. The present study adopted comparative proteomics as a tool to interpret the resistance mechanism(s) in C. platycarpus vis-à-vis C. cajan during continued herbivory (up to 96 h). Over-representation analysis of the differentially expressed proteins implicated a multi-dimensional resistance response accomplished by both physical and chemical barriers in C. platycarpus. While the chemical basis for resistance was depicted by the upregulation of proteins playing a rate limiting role in the phenylpropanoid pathway, the physical basis was provided by the regulation of proteins involved in microtubule assembly and synthesis of lignins. Upregulation of proteins in the polyamine pathway indicated the role of metabolite conjugates to be negatively affecting herbivore growth. Reallocation of resources and diversion of metabolic flux to support the production of secondary metabolites could be the probable approach in the wild relative against herbivory. Our study provided deeper insights into the pod borer resistance mechanism in C. platycarpus for utility in crop improvement. KEY POINTS: • Pod borer resistance in Cajanus platycarpus is multi-dimensional. • Pod borer resistance has been arbitrated to cell wall rigidity and secondary metabolites. • Phenylpropanoid pathway derivatives apparently shaped the plant chemical defense against pod borer.

Targeted Proteomics Guided by Label-free Quantitative Proteome Analysis in Saliva Reveal Transition Signatures from Health to Periodontal Disease.

Periodontal diseases are among the most prevalent worldwide, but largely silent, chronic diseases. They affect the tooth-supporting tissues with multiple ramifications on life quality. Their early diagnosis is still challenging, due to lack of appropriate molecular diagnostic methods. Saliva offers a non-invasively collectable reservoir of clinically relevant biomarkers, which, if utilized efficiently, could facilitate early diagnosis and monitoring of ongoing disease. Despite several novel protein markers being recently enlisted by discovery proteomics, their routine diagnostic application is hampered by the lack of validation platforms that allow for rapid, accurate and simultaneous quantification of multiple proteins in large cohorts. Here we carried out a pipeline of two proteomic platforms; firstly, we applied open ended label-free quantitative (LFQ) proteomics for discovery in saliva (n = 67, including individuals with health, gingivitis, and periodontitis), followed by selected-reaction monitoring (SRM)-targeted proteomics for validation in an independent cohort (n = 82). The LFQ platform led to the discovery of 119 proteins with at least 2-fold significant difference between health and disease. The 65 proteins chosen for the subsequent SRM platform included 50 functionally related proteins derived from the significantly enriched processes of the LFQ data, 11 from literature-mining, and four house-keeping ones. Among those, 60 were reproducibly quantifiable proteins (92% success rate), represented by a total of 143 peptides. Machine-learning modeling led to a narrowed-down panel of five proteins of high predictive value for periodontal diseases with maximum area under the receiver operating curve >0.97 (higher in disease: Matrix metalloproteinase-9, Ras-related protein-1, Actin-related protein 2/3 complex subunit 5; lower in disease: Clusterin, Deleted in Malignant Brain Tumors 1). This panel enriches the pool of credible clinical biomarker candidates for diagnostic assay development. Yet, the quantum leap brought into the field of periodontal diagnostics by this study is the application of the biomarker discovery-through-verification pipeline, which can be used for validation in further cohorts.

Quantifying and Localizing the Mitochondrial Proteome Across Five Tissues in A Mouse Population.

We have used SWATH mass spectrometry to quantify 3648 proteins across 76 proteomes collected from genetically diverse BXD mouse strains in two fractions (mitochondria and total cell) from five tissues: liver, quadriceps, heart, brain, and brown adipose (BAT). Across tissues, expression covariation between genes' proteins and transcripts-measured in the same individuals-broadly aligned. Covariation was however far stronger in certain subsets than others: only 8% of transcripts in the lowest expression and variance quintile covaried with their protein, in contrast to 65% of transcripts in the highest quintiles. Key functional differences among the 3648 genes were also observed across tissues, with electron transport chain (ETC) genes particularly investigated. ETC complex proteins covary and form strong gene networks according to tissue, but their equivalent transcripts do not. Certain physiological consequences, such as the depletion of ATP synthase in BAT, are thus obscured in transcript data. Lastly, we compared the quantitative proteomic measurements between the total cell and mitochondrial fractions for the five tissues. The resulting enrichment score highlighted several hundred proteins which were strongly enriched in mitochondria, which included several dozen proteins were not reported in literature to be mitochondrially localized. Four of these candidates were selected for biochemical validation, where we found MTAP, SOAT2, and IMPDH2 to be localized inside the mitochondria, whereas ABCC6 was in the mitochondria-associated membrane. These findings demonstrate the synergies of a multi-omics approach to study complex metabolic processes, and this provides a resource for further discovery and analysis of proteoforms, modified proteins, and protein localization.

The SysteMHC Atlas project.

Mass spectrometry (MS)-based immunopeptidomics investigates the repertoire of peptides presented at the cell surface by major histocompatibility complex (MHC) molecules. The broad clinical relevance of MHC-associated peptides, e.g. in precision medicine, provides a strong rationale for the large-scale generation of immunopeptidomic datasets and recent developments in MS-based peptide analysis technologies now support the generation of the required data. Importantly, the availability of diverse immunopeptidomic datasets has resulted in an increasing need to standardize, store and exchange this type of data to enable better collaborations among researchers, to advance the field more efficiently and to establish quality measures required for the meaningful comparison of datasets. Here we present the SysteMHC Atlas (https://systemhcatlas.org), a public database that aims at collecting, organizing, sharing, visualizing and exploring immunopeptidomic data generated by MS. The Atlas includes raw mass spectrometer output files collected from several laboratories around the globe, a catalog of context-specific datasets of MHC class I and class II peptides, standardized MHC allele-specific peptide spectral libraries consisting of consensus spectra calculated from repeat measurements of the same peptide sequence, and links to other proteomics and immunology databases. The SysteMHC Atlas project was created and will be further expanded using a uniform and open computational pipeline that controls the quality of peptide identifications and peptide annotations. Thus, the SysteMHC Atlas disseminates quality controlled immunopeptidomic information to the public domain and serves as a community resource toward the generation of a high-quality comprehensive map of the human immunopeptidome and the support of consistent measurement of immunopeptidomic sample cohorts.

OpenMS: a flexible open-source software platform for mass spectrometry data analysis.

High-resolution mass spectrometry (MS) has become an important tool in the life sciences, contributing to the diagnosis and understanding of human diseases, elucidating biomolecular structural information and characterizing cellular signaling networks. However, the rapid growth in the volume and complexity of MS data makes transparent, accurate and reproducible analysis difficult. We present OpenMS 2.0 (http://www.openms.de), a robust, open-source, cross-platform software specifically designed for the flexible and reproducible analysis of high-throughput MS data. The extensible OpenMS software implements common mass spectrometric data processing tasks through a well-defined application programming interface in C++ and Python and through standardized open data formats. OpenMS additionally provides a set of 185 tools and ready-made workflows for common mass spectrometric data processing tasks, which enable users to perform complex quantitative mass spectrometric analyses with ease.

rawDiag: An R Package Supporting Rational LC-MS Method Optimization for Bottom-up Proteomics.

Optimizing methods for liquid chromatography coupled to mass spectrometry (LC-MS) is a nontrivial task. Here we present rawDiag, a software tool supporting rational method optimization by providing MS operator-tailored diagnostic plots of scan-level metadata. rawDiag is implemented as an R package and can be executed on the R command line or through a graphical user interface (GUI) for less experienced users. The code runs platform-independent and can process 100 raw files in <3 min on current consumer hardware, as we show in our benchmark. As a demonstration of the functionality of our package we include a real-world example taken from our daily core facility business.

Targeted proteomics coming of age - SRM, PRM and DIA performance evaluated from a core facility perspective.

Quantitative mass spectrometry is a rapidly evolving methodology applied in a large number of omics-type research projects. During the past years, new designs of mass spectrometers have been developed and launched as commercial systems while in parallel new data acquisition schemes and data analysis paradigms have been introduced. Core facilities provide access to such technologies, but also actively support the researchers in finding and applying the best-suited analytical approach. In order to implement a solid fundament for this decision making process, core facilities need to constantly compare and benchmark the various approaches. In this article we compare the quantitative accuracy and precision of current state of the art targeted proteomics approaches single reaction monitoring (SRM), parallel reaction monitoring (PRM) and data independent acquisition (DIA) across multiple liquid chromatography mass spectrometry (LC-MS) platforms, using a readily available commercial standard sample. All workflows are able to reproducibly generate accurate quantitative data. However, SRM and PRM workflows show higher accuracy and precision compared to DIA approaches, especially when analyzing low concentrated analytes.

Developmental stage-specific proteome analysis of the legume pod borer Maruca vitrata provides insights on relevant proteins.

The spotted pod borer, Maruca vitrata (Lepidoptera: Crambidae) is a destructive insect pest that inflicts significant productivity losses on important leguminous crops. Unravelling insect proteomes is vital to comprehend their fundamental molecular mechanisms. This research delved into the proteome profiles of four distinct stages -three larval and pupa of M. vitrata, utilizing LC-MS/MS label-free quantification-based methods. Employing comprehensive proteome analysis with fractionated datasets, we mapped 75 % of 3459 Drosophila protein orthologues out of which 2695 were identified across all developmental stages while, 137 and 94 were exclusive to larval and pupal stages respectively. Cluster analysis of 2248 protein orthologues derived from MaxQuant quantitative dataset depicted six clusters based on expression pattern similarity across stages. Consequently, gene ontology and protein-protein interaction network analyses using STRING database identified cluster 1 (58 proteins) and cluster 6 (25 proteins) associated with insect immune system and lipid metabolism. Furthermore, qRT-PCR-based expression analyses of ten selected proteins-coding genes authenticated the proteome data. Subsequently, functional validation of these chosen genes through gene silencing reduced their transcript abundance accompanied by a marked increase in mortality among dsRNA-injected larvae. Overall, this is a pioneering study to effectively develop a proteome atlas of M. vitrata as a potential resource for crop protection programs.

Bacterial symbionts in oral niche use type VI secretion nanomachinery for fitness increase against pathobionts.

Microbial ecosystems experience spatial and nutrient restrictions leading to the coevolution of cooperation and competition among cohabiting species. To increase their fitness for survival, bacteria exploit machinery to antagonizing rival species upon close contact. As such, the bacterial type VI secretion system (T6SS) nanomachinery, typically expressed by pathobionts, can transport proteins directly into eukaryotic or prokaryotic cells, consequently killing cohabiting competitors. Here, we demonstrate for the first time that oral symbiont Aggregatibacter aphrophilus possesses a T6SS and can eliminate its close relative oral pathobiont Aggregatibacter actinomycetemcomitans using its T6SS. These findings bring nearer the anti-bacterial prospects of symbionts against cohabiting pathobionts while introducing the presence of an active T6SS in the oral cavity.

Protocol for analyzing the function of the type VI secretion system of the oral symbiont Aggregatibacter aphrophilus in targeting pathobionts.

Here, we present a protocol for evaluating type VI secretion system (T6SS)-dependent fitness of the oral symbiont A. aphrophilus using biofilm competition assays and metaproteomics. We describe steps for designing T6SS-specific mutants. We then detail procedures for using them in competition assays with the pathobiont A. actinomycetemcomitans and in biofilm models, analyzing metaproteomes to assess the impact of the T6SS on multiple pathobionts. The biofilm model is designed to mimic the oral plaque ecosystem and includes seven species. For complete details on the use and execution of this protocol, please refer to Oscarsson et al.1.

Proceedings of the EuBIC-MS developers meeting 2023.

The 2023 European Bioinformatics Community for Mass Spectrometry (EuBIC-MS) Developers Meeting was held from January 15th to January 20th, 2023, in Congressi Stefano Franscin at Monte Verità in Ticino, Switzerland. The participants were scientists and developers working in computational mass spectrometry (MS), metabolomics, and proteomics. The 5-day program was split between introductory keynote lectures and parallel hackathon sessions focusing on "Artificial Intelligence in proteomics" to stimulate future directions in the MS-driven omics areas. During the latter, the participants developed bioinformatics tools and resources addressing outstanding needs in the community. The hackathons allowed less experienced participants to learn from more advanced computational MS experts and actively contribute to highly relevant research projects. We successfully produced several new tools applicable to the proteomics community by improving data analysis and facilitating future research.

Proteomic profiling of canine fibrosarcoma and adjacent peritumoral tissue.

Fibrosarcoma (FSA) are rare soft tissue tumors that display aggressive local behavior and invasive growth leading to high rates of tumor recurrence. While the low incidence in humans hampers detailed understanding of the disease, FSA are frequent in dogs and present potential models for the human condition. However, a lack of in-depth molecular characterization of FSA and unaffected peritumoral tissue (PTT) in both species impedes the translational potential of dogs. To address this shortcoming, we characterized canine FSA and matched skeletal muscle, adipose and connective tissue using laser-capture microdissection (LCM) and LC-MS/MS in 30 formalin-fixed paraffin embedded (FFPE) specimens. Principal component analysis of 3'530 different proteins detected across all samples clearly separates the four tissues, with several targets strongly differentiating tumor from all three PTTs. 25 proteins were exclusively found in tumor tissue in ≥80% of cases. Among these, CD68 (a macrophage marker), Optineurin (OPTN), Nuclear receptor coactivator 5 (NCOA5), RAP1GDS1 (Rap1 GTPase-GDP dissociation stimulator 1) and Stromal cell derived factor 2 like 1 (SDF2L1) were present in ≥90% of FSA. Protein expression across all FSA was highly homogeneous and characterized by MYC and TP53 signaling, hyperactive EIF2 and immune-related changes as well as strongly decreased oxidative phosphorylation and oxidative lipid metabolism. Finally, we demonstrate significant molecular homology between canine FSA and human soft-tissue sarcomas, emphasizing the relevance of studying canine FSA as a model for human FSA. In conclusion, we provide the first detailed overview of proteomic changes in FSA and surrounding PTT with relevance for the human disease.

Modic type 2 changes are fibroinflammatory changes with complement system involvement adjacent to degenerated vertebral endplates.

Background: Vertebral endplate signal intensity changes visualized by magnetic resonance imaging termed Modic changes (MC) are highly prevalent in low back pain patients. Interconvertibility between the three MC subtypes (MC1, MC2, MC3) suggests different pathological stages. Histologically, granulation tissue, fibrosis, and bone marrow edema are signs of inflammation in MC1 and MC2. However, different inflammatory infiltrates and amount of fatty marrow suggest distinct inflammatory processes in MC2. Aims: The aims of this study were to investigate (i) the degree of bony (BEP) and cartilage endplate (CEP) degeneration in MC2, (ii) to identify inflammatory MC2 pathomechanisms, and (iii) to show that these marrow changes correlate with severity of endplate degeneration. Methods: Pairs of axial biopsies (n = 58) spanning the entire vertebral body including both CEPs were collected from human cadaveric vertebrae with MC2. From one biopsy, the bone marrow directly adjacent to the CEP was analyzed with mass spectrometry. Differentially expressed proteins (DEPs) between MC2 and control were identified and bioinformatic enrichment analysis was performed. The other biopsy was processed for paraffin histology and BEP/CEP degenerations were scored. Endplate scores were correlated with DEPs. Results: Endplates from MC2 were significantly more degenerated. Proteomic analysis revealed an activated complement system, increased expression of extracellular matrix proteins, angiogenic, and neurogenic factors in MC2 marrow. Endplate scores correlated with upregulated complement and neurogenic proteins. Discussion: The inflammatory pathomechanisms in MC2 comprises activation of the complement system. Concurrent inflammation, fibrosis, angiogenesis, and neurogenesis indicate that MC2 is a chronic inflammation. Correlation of endplate damage with complement and neurogenic proteins suggest that complement system activation and neoinnervation may be linked to endplate damage. The endplate-near marrow is the pathomechanistic site, because MC2 occur at locations with more endplate degeneration. Conclusion: MC2 are fibroinflammatory changes with complement system involvement which occur adjacent to damaged endplates.

Multi-omics HeCaToS dataset of repeated dose toxicity for cardiotoxic & hepatotoxic compounds.

The data currently described was generated within the EU/FP7 HeCaToS project (Hepatic and Cardiac Toxicity Systems modeling). The project aimed to develop an in silico prediction system to contribute to drug safety assessment for humans. For this purpose, multi-omics data of repeated dose toxicity were obtained for 10 hepatotoxic and 10 cardiotoxic compounds. Most data were gained from in vitro experiments in which 3D microtissues (either hepatic or cardiac) were exposed to a therapeutic (physiologically relevant concentrations calculated through PBPK-modeling) or a toxic dosing profile (IC20 after 7 days). Exposures lasted for 14 days and samples were obtained at 7 time points (therapeutic doses: 2-8-24-72-168-240-336 h; toxic doses 0-2-8-24-72-168-240 h). Transcriptomics (RNA sequencing & microRNA sequencing), proteomics (LC-MS), epigenomics (MeDIP sequencing) and metabolomics (LC-MS & NMR) data were obtained from these samples. Furthermore, functional endpoints (ATP content, Caspase3/7 and O2 consumption) were measured in exposed microtissues. Additionally, multi-omics data from human biopsies from patients are available. This data is now being released to the scientific community through the BioStudies data repository ( https://www.ebi.ac.uk/biostudies/ ).

Association of proteomic markers with nutritional risk and response to nutritional support: A secondary pilot study of the EFFORT trial using an untargeted proteomics approach.

BACKGROUND: By means of a structured nutritional support intervention, EFFORT showed a risk reduction for adverse events in medical in-patients. We were interested in the prognostic and therapeutic potential of an untargeted proteomics approach to understand response to nutritional support, risk of 30-day mortality, and distinct patterns in severity of malnutrition risk as assessed by the Nutritional Risk screening (NRS 2002), respectively. METHODS: From 2,088 patients, we randomly took 120 blood samples drawn before treatment initiation on day 1 after hospital admission. Cases were selected by treatment allocation (nutritional support vs. usual nutrition), NRS 2002, and mortality at 30 days, but not on disease type. We measured proteins by untargeted liquid chromatography mass spectrometry (LC-MS/MS). RESULTS: We found 242 distinct proteins in 120 patients of which 81 (67.5%) survived until day 30. Between group analysis revealed a slight difference between the treatment groups in patients with a NRS 3, but not in those with a higher NRS. C-statistic between non-survivors and survivors at day 30 ranged from 0.60 (95% confidence interval 0.34-0.78) for a combination of 3 proteins/predictors to 0.65 (95% CI 0.53-0.78) for a combination of 32 proteins/predictors. In nutritional support non-survivors, pathway analysis found significant enrichment in pathways for signal transduction, platelet function, immune system regulation, extracellular matrix organization, and integrin cell surface interactions compared to survivors. CONCLUSION: Within this pilot study using an untargeted proteomics approach, there was only little prognostic and therapeutic potential of proteomics for phenotyping the risk of malnutrition and response to nutritional therapy. The small sample size and high heterogeneity of our population regarding comorbidity burden calls for more targeted approaches in more homogenous populations to understand the true potential of proteomics for individualizing nutritional care. TRIAL REGISTRATION: This is a pre-planned secondary analysis of the EFFORT trial (ClinicalTrials.gov NCT02517476).

Proteomic identification of proliferation and progression markers in human polycythemia vera stem and progenitor cells.

Polycythemia vera (PV) is a stem cell disorder characterized by hyperproliferation of the myeloid lineages and the presence of an activating JAK2 mutation. To elucidate mechanisms controlling PV stem and progenitor cell biology, we applied a recently developed highly sensitive data-independent acquisition mass spectrometry workflow to purified hematopoietic stem and progenitor cell (HSPC) subpopulations of patients with chronic and progressed PV. We integrated proteomic data with genomic, transcriptomic, flow cytometry, and in vitro colony formation data. Comparative analyses revealed added information gained by proteomic compared with transcriptomic data in 30% of proteins with changed expression in PV patients. Upregulated biological pathways in hematopoietic stem and multipotent progenitor cells (HSC/MPPs) of PV included mammalian target of rapamycin (MTOR), STAT, and interferon signaling. We further identified a prominent reduction of clusterin (CLU) protein expression and a corresponding activation of nuclear factor-κB (NF-κB) signaling in HSC/MPPs of untreated PV patients compared with controls. Reversing the reduction of CLU and inhibiting NF-κB signaling decreased proliferation and differentiation of PV HSC/MPPs in vitro. Upon progression of PV, we identified upregulation of LGALS9 and SOCS2 protein expression in HSC/MPPs. Treatment of patients with hydroxyurea normalized the expression of CLU and NF-κB2 but not of LGALS9 and SOCS2. These findings expand the current understanding of the molecular pathophysiology underlying PV and provide new potential targets (CLU and NF-κB) for antiproliferative therapy in patients with PV.