Proteomic studies using mass spectrometry (MS)-based quantification are a main approach to the discovery of new biomarkers. However, a number of analytical conditions in front and during MS data acquisition can affect the accuracy of the obtained outcome. Therefore, comprehensive quality assessment of the acquired data plays a central role in quantitative proteomics, though, due to the immense complexity of MS data, it is often neglected. Here, we address practically the quality assessment of quantitative MS data, describing key steps for the evaluation, including the levels of raw data, identification and quantification. With this, four independent datasets from cerebrospinal fluid, an important biofluid for neurodegenerative disease biomarker studies, were assessed, demonstrating that sample processing-based differences are already reflected at all three levels but with varying impacts on the quality of the quantitative data. Specifically, we provide guidance to critically interpret the quality of MS data for quantitative proteomics. Moreover, we provide the free and open source quality control tool MaCProQC, enabling systematic, rapid and uncomplicated data comparison of raw data, identification and feature detection levels through defined quality metrics and a step-by-step quality control workflow.

Mesenchymal stem cells (MSCs) gain an increasing focus in the field of regenerative medicine due to their differentiation abilities into chondrocytes, adipocytes, and osteoblastic cells. However, it is apparent that the transformation processes are extremely complex and cause cellular heterogeneity. The study aimed to characterize differences between MSCs and cells after adipogenic (AD) or osteoblastic (OB) differentiation at the proteome level. Comparative proteomic profiling was performed using tandem mass spectrometry in data-independent acquisition mode. Proteins were quantified by deep neural networks in library-free mode and correlated to the Molecular Signature Database (MSigDB) hallmark gene set collections for functional annotation. We analyzed 4108 proteins across all samples, which revealed a distinct clustering between MSCs and cell differentiation states. Protein expression profiling identified activation of the Peroxisome proliferator-activated receptors (PPARs) signaling pathway after AD. In addition, two distinct protein marker panels could be defined for osteoblastic and adipocytic cell lineages. Hereby, overexpression of AEBP1 and MCM4 for OB as well as of FABP4 for AD was detected as the most promising molecular markers. Combination of deep neural network and machine-learning algorithms with data-independent mass spectrometry distinguish MSCs and cell lineages after adipogenic or osteoblastic differentiation. We identified specific proteins as the molecular basis for bone formation, which could be used for regenerative medicine in the future.

Platelets, the smallest cells in human blood, known for their role in primary hemostasis, are also able to interact with pathogens and play a crucial role in the immune response. In severe coronavirus disease 2019 (COVID-19) cases, platelets become overactivated, resulting in the release of granules, exacerbating inflammation and contributing to the cytokine storm. This study aims to further elucidate the role of platelets in COVID-19 progression and to identify predictive biomarkers for disease outcomes. A comparative proteome analysis of highly purified platelets from critically diseased COVID-19 patients with different outcomes (survivors and non-survivors) and age- and sex-matched controls was performed. Platelets from critically diseased COVID-19 patients exhibited significant changes in the levels of proteins associated with protein folding. In addition, a number of proteins with isomerase activity were found to be more highly abundant in patient samples, apparently exerting an influence on platelet activity via the non-genomic properties of the glucocorticoid receptor (GR) and the nuclear factor κ-light-chain-enhancer of activated B cells (NFκB). Moreover, carbonic anhydrase 1 (CA-1) was found to be a candidate biomarker in platelets, showing a significant increase in COVID-19 patients.

Fumaric acid esters have proven to be effective medications in relapsing-remitting multiple sclerosis with neuroprotective effects. In this study, we investigated the impact of fumaric acid esters on primary murine microglia in vitro compared to DMSO vehicle control. Monomethyl fumarate (MMF) increased MTT reduction in a dose-dependent manner, whereas dimethyl fumarate (DMF) exhibited a biphasic response with low concentrations enhancing MTT reduction and higher concentrations inducing toxicity. Notably, complementary analyses of cell number and cell death did not reveal differences between MMF-treated and control conditions, indicating that the increased MTT reduction reflects enhanced cellular metabolic activity rather than increased viability. Consistent with this interpretation, MMF-treated cells exhibited higher basal and maximal oxygen consumption, spare respiratory capacity, and ATP production in the Seahorse XF Cell Mito Stress Test. Proteomic analysis did not indicate an upregulation of mitochondrial respiratory chain proteins, but instead suggested a qualitative shift in mitochondrial homeostasis, including increased expression of mitophagy-associated proteins. MMF-treated Nrf2-deficient microglia showed a blunted increase in MTT reduction, suggesting an involvement of Nrf2 in mediating MMF-induced metabolic effects. Additionally, MMF modulated the microglial iron metabolism and reduced the uptake of non-transferrin-bound iron and altered the gene expression of iron transport proteins, promoting a shift toward the uptake of less toxic, transferrin-bound iron. MMF mitigated iron-induced toxicity and was associated with upregulation of the ferroptosis suppressor protein, indicating a protective response to iron overload. Together, these findings suggest that MMF enhances microglial metabolic activity and mitochondrial function while reducing iron-mediated toxicity, thereby contributing to its neuroprotective effects. Graphical Abstract Summary of the proposed cellular effects of monomethyl fumarate in primary murine microglia. Created in BioRender. Faissner (2026). https://help.biorender.com/hc/en-gb/articles/17605511350685

Mineralized bone tissue is essential for skeletal integrity, mechanical stability, and mineral homeostasis. Osteocytes, the most abundant bone cell type, play central roles in bone remodeling and endocrine regulation but remain difficult to investigate because of their embedded localization within the mineralized matrix. Consequently, the molecular mechanisms underlying osteoblast-to-osteocyte differentiation remain incompletely understood.Here, we performed a comprehensive quantitative proteomic analysis of the widely used human SaOS-2 cell line during osteoblast-to-osteocyte-like differentiation. More than 5,000 proteins were quantified, providing a comprehensive proteomic roadmap of this differentiation process. Proteomic profiling demonstrated extensive molecular remodeling accompanied by extracellular matrix reorganization and dynamic changes in collagen abundance. Although differentiated SaOS-2 cells retained characteristics of late osteoblasts and did not fully recapitulate the phenotype of mature osteocytes, they acquired a distinct osteocyte-like proteomic signature. Furthermore, we identified and orthogonally validated several candidate protein markers associated with the osteoblast and osteocyte-like states.Together, our study provides the first comprehensive protein-level characterization of SaOS-2 osteoblast-to-osteocyte-like differentiation. Beyond improving the molecular characterization of this widely used model, it provides a valuable resource for future studies investigating bone biology, extracellular matrix remodeling, and skeletal disease