Matthias Selbach

Even cells of the same type growing in the same environment show cell-to-cell differences in protein abundance, a phenomenon known as gene expression noise. This variability can be decomposed into intrinsic components, reflecting molecular randomness, and extrinsic components, arising from differences in cellular state. While gene expression noise has been studied genome-wide in microbes, its global organization remains largely unknown in mammalian cells. Here, we develop a spike-in-based stable isotope single-cell proteomics approach that enables robust quantification of protein-level gene expression noise across thousands of human proteins. We find that protein noise scales inversely with abundance until reaching a plateau, consistent with an extrinsic noise floor and conserved scaling principles observed in bacteria and yeast. Cell cycle stage and cell size contribute substantially to protein variability but do not fully account for the observed heterogeneity. Gene-specific features such as mRNA and protein half-lives and translation efficiency show only weak associations with protein noise, and variability at the mRNA level is a weak predictor of protein variability. Instead, protein noise is largely extrinsic, with coordinated variation across proteins encoding biologically organized cellular states. Consistently, coordinated proteome programs predict intercellular differences in proteome dynamics, linking protein variability to cellular function. Together, these results provide a proteome-wide view of gene expression noise in mammalian cells, establishing that protein-level variability encodes structured and functionally relevant differences in cellular state.

Skeletal muscle atrophy is a pathological condition characterized by the loss of muscle mass and strength, driven by diverse stimuli including disuse, malnutrition, acute and chronic inflammation, ...

The role of plasma and serum proteomics in characterizing human disease, identifying biomarkers, and advancing diagnostic technologies is rapidly increasing. However, there is an ongoing need to improve proteomic workflows in terms of accuracy, reproducibility, and cost-effectiveness, and to achieve cross-platform transferability. Based on large serum and plasma proteome studies, we generate the Charité Open Peptide Standard for Plasma Proteomics (OSPP), an open, versatile peptide internal standard for targeted and untargeted mass spectrometry-based proteomic studies. The OSPP includes 211 concentration-matched stable-isotope-labeled peptides selected for consistent quantification across a large number of plasma and serum proteome studies, and synthetic accessibility. We show they are consistently quantified across serum and EDTA, citrate, and heparin plasma using multiple LC-MS platforms. Despite being selected for technical parameters, the OSPP peptides represent proteins that function in a wide range of biological processes, are used in routine clinical tests, or are targets of FDA-approved drugs, making OSPP able to serve as an expandable clinical marker panel. We demonstrate the utility of OSPP in a COVID-19 inpatient cohort study for improving analytical performances, for cross-platform alignment of proteomic data, disease stratification, and biomarker discovery.

INTRODUCTION: Mutations in SORL1 , encoding the sorting receptor Sortilin‐related receptor with A‐type repeats (SORLA), are found in individuals with Alzheimer's disease (AD). We studied SORLA ^N1358S , carrying a mutation in its ligand binding domain, to learn more about receptor functions relevant for human brain health. METHODS: We investigated consequences of SORLA ^N1358S expression in induced pluripotent stem cell (iPSC)‐derived human neurons and microglia, using unbiased proteome screens and functional cell assays. RESULTS: We identified alterations in the SORLA ^N1358S interactome linked to biogenesis of exosomes. Consequently, the mutant receptor failed to promote release and neurotrophic qualities of exosomes, a defect attributed to altered exosomal content of microRNAs controlling neuronal maturation. DISCUSSION: We identified a role for SORLA in controlling quantity and neurotrophic quality of exosomes secreted by cells, suggesting impaired cellular cross talk through exosomes as a pathological trait contributing to AD pathology in carriers of SORL1 variants. Highlights: Familial Alzheimer's disease mutation in SORL1 changes interactome of mutant Sortilin‐related receptor with A‐type repeats (SORLA). Mutant SORLA impairs release of exosomes from neurons and microglia. Mutant exosomes lack neurotrophic qualities. Defect linked to alterations in microRNA content.

Targeted kinase inhibitors are a cornerstone of cancer therapy, but their success is often hindered by the complexity of cellular signaling networks that can lead to resistance. Overcoming this challenge necessitates a deep understanding of cellular signaling responses. While standard global phosphoproteomics offers extensive insights, lengthy processing times, the complexity of data interpretation, and frequent omission of crucial phosphorylation sites limit its utility. Here, we combine data-independent acquisition (DIA) with spike-in of synthetic heavy stable isotope-labeled phosphopeptides to facilitate the targeted detection of particularly informative phosphorylation sites. Our spike-in enhanced detection in DIA (SPIED-DIA) approach integrates the improved sensitivity of spike-in-based targeted detection with the discovery potential of global phosphoproteomics into a simple workflow. We employed this method to investigate synergistic signaling responses in colorectal cancer cell lines following MEK inhibition. Our findings highlight that combining MEK inhibition with growth factor stimulation synergistically activates JNK signaling in HCT116 cells. This synergy emphasizes the therapeutic potential of concurrently targeting MEK and JNK pathways, as evidenced by the significantly impaired growth of HCT116 cells when treated with both inhibitors. Our results demonstrate that SPIED-DIA effectively identifies synergistic signaling responses in colorectal cancer cells, presenting a valuable tool for uncovering new therapeutic targets and strategies in cancer treatment.

Skeletal muscle atrophy is a pathological condition characterized by the progressive loss of muscle mass and function, driven by factors such as disuse, inflammation, and aging. While the ubiquitin-proteasome system is established as the central mediator of myofibrillar protein degradation, the role of autophagy in selective protein turnover remains largely unexplored. To address this, we employed a quantitative, time-resolved analysis of protein synthesis and degradation in C2C12 myotubes undergoing TNF-α-induced atrophy, using dynamic Stable Isotope Labeling by Amino Acids in Cell Culture (dynamic SILAC) coupled with LC-MS/MS. Our data challenges the classical view of atrophy as a uniform, degradation-centric process. Instead, we reveal temporally distinct patterns of selective protein turnover, including differential degradation of myofibrillar, ribosomal, and endoplasmic reticulum (ER)-resident proteins. Early atrophy is characterized by suppressed short-term protein synthesis, increased ubiquitin-ligase expression, proteasomal activation, and ribosome turnover. In contrast, late atrophy features proteasome-dependent myofibrillar protein degradation, selective synthesis of mitochondrial ribosomes and cytoplasmic ribosome degradation, indicative of metabolic adaptation. Moreover, we identify a temporal shift in autophagic selectivity: from ER homeostasis maintenance to a stress-induced ER-degradation program. Notably, inhibition of autophagy during atrophy leads to accumulation of ER-phagy receptors Tex264 and Calcoco1, implicating ER-phagy as a key contributor to atrophic remodeling, underscoring an underexplored regulatory mechanism in muscle proteostasis. By elucidating the role of autophagy in degradation of the ER, this study opens new avenues for therapeutic interventions targeting proteostasis regulation in inflammation-induced muscle-wasting disorders, ultimately contributing to a more refined understanding of muscle atrophy beyond proteasomal degradation.

Summary: Alternative splicing and proteolytic processing expand the functional diversity of the human proteome by generating distinct protein isoforms from a single gene. However, the extent to which transcript isoforms give rise to distinct protein products remains unclear, in part due to technical limitations in proteomic workflows. Here, we combine full-length mRNA sequencing with SDS-PAGE-based protein fractionation and quantitative mass spectrometry to construct an integrated landscape of mRNA and protein isoforms in human RPE-1 cells. To overcome the inherent ambiguity of bottom-up proteomics in isoform detection, we developed IsoFrac , a computational pipeline that resolves protein isoforms based on their migration profiles across gel fractions. This approach enabled the identification of ∼45,000 full-length transcripts, ∼32,000 ORFs, and ∼16,000 distinct protein isoforms. Comparative analyses revealed widespread translation of alternative transcripts and uncovered proteolytic processing as a major, underappreciated source of proteome complexity. Our results establish a scalable framework for isoform-resolved proteogenomics and provide a reference resource for studying the molecular diversity encoded by the human genome.