Biology subjects

Petrosius, V.

Publications and source records attributed to Petrosius, V..

10 recordsLinked to original sources

bioRxiv2026

Defining Quality Control Standards for Single-Cell Proteomics by Inter-Laboratory Benchmarking

Single-cell proteomics can quantify thousands of proteins from individual mammalian cells, yet the absence of community-wide quality control limits biological interpretability. Here, the HUPO Single Cell Initiative presents the first inter-laboratory single-cell proteomics benchmarking study across seven laboratories using standardized 384-well plates acquired on Orbitrap Astral and timsTOF Ultra2 instruments. Centralized analysis across six DIA software tools revealed that software choice impacts identification depth and quantitative accuracy more than instrument vendor. Multi-layered quality control enabled the detection of cell-leakage during sorting, LC misconfiguration, column degradation and site-specific pipetting failures. Inter-lab quantitative correlations were strongest between instruments of the same vendor relative to cross-platform comparisons. Sequential correction for plate identity and well position recovered clean cell-type separation for confident downstream differential expression analysis. This study provides a data-driven quality control framework spanning plate design to batch correction for reproducible single-cell proteomics across laboratories and platforms.

biochemistry↗

bioRxiv2026

CRISPR-PTM and CRISPR-VEIS: Multiplexed platforms for quantitative functional analysis of endogenous phosphosites

Connecting protein post-translational modifications (PTMs) to phenotypic outcomes is a central challenge. Although phosphoproteomics has richly catalogued specific sites, reliable methods to measure the endogenous effects of individual phosphosites on cellular fitness and signaling are still lacking. Here, we introduce CRISPR-PTM and CRISPR-VEIS as complementary platforms for quantitative, endogenous phosphosite interrogation at both individual and clustered phosphorylation events. CRISPR-PTM is a multiplexed knock-in framework generating defined phosphosite variants with internal allelic markers, enabling precise relative fitness effects in pooled populations. CRISPR-VEIS (Visualisation of Edits In Situ) is an in situ mRNA-genotyping approach that directly links endogenous allelic edits to single-cell phenotypes, addressing needs for subclonal isolation or exogenous reporters. We applied these methods to the WEE1-CDK1 regulatory pathway, where canonical CDK1-Y15 phosphorylation alone cannot explain WEE1 loss or inhibition phenotypes. CRISPR-PTM systematically quantified fitness consequences of CDK1 phosphosite variants and identified Y19 as a previously unrecognized WEE1-dependent inhibitory site. Single non-phosphorylatable substitutions at Y15 or Y19 had minimal impact, but combined CDK1-Y15F/Y19F editing caused pronounced fitness defects, phenocopying WEE1 inactivation and showing epistasis to WEE1 inhibitors. CRISPR-VEIS further demonstrated that acute endogenous editing of both sites correlated with elevated CDK activity at the single-cell level. Together, CRISPR-PTM and CRISPR-VEIS provide broadly applicable approaches for quantitative analysis of PTM function, enabling direct linkage of endogenous phosphosite variation to cellular fitness and signaling phenotypes.

cell biology↗

bioRxiv2025

Informed Data-Independent Acquisition Enables Targeted Quantification of Key Regulatory Proteins in Cell Fate Decision at Single-Cell Resolution

Low-abundance regulatory proteins, including transcription factors (TFs), remain largely inaccessible to direct quantification in single cells despite their central roles in cellular state transitions. Although single-cell proteomics by mass spectrometry (scp-MS) enables broad proteome profiling, current approaches often lack the sensitivity required to quantify these regulators at the protein level robustly. Here, we present informed data-independent acquisition (iDIA), a cross-instrument MS acquisition framework combining sensitive targeted measurements with global proteome profiling of the same cell. Thereby, iDIA significantly improves the sensitivity for predefined regulatory proteins, while preserving global proteome coverage. Applied to hematopoietic stem and progenitor cells, iDIA quantified 12 lineage-associated TFs, including GATA1 and SPI1, alongside the global proteome from single cells. Integrated analysis reconstructed the differentiation hierarchy and revealed protein-level states of early granulocytic-monocytic lineage priming and coordinated changes between erythroid TF abundance and cell-cycle progression. Thus, iDIA opens scp-MS to the regulatory architecture of cell state transitions.

systems biology↗

bioRxiv2024

Quantitative Label-Free Single-Cell Proteomics on the Orbitrap Astral MS

Single-cell proteomics by mass spectrometry (scp-MS) holds the potential to provide unprecedented insights into molecular features directly linked to the cellular phenotype, while deconvoluting complex organisms into their basic building blocks. Tailored sample preparation that maximizes the extracted amount of material that is introduced into the mass spectrometer has rapidly propelled the field forward. However, the measured signal is still at the lower edge of detection approaching the sensitivity boundary of current instrumentation. Here, we investigate the capacity of the enhanced sensitivity of the Orbitrap Astral mass spectrometer to facilitate deeper proteome profiles from low-input to single-cell samples. We carry out a comprehensive data acquisition method survey to pinpoint which parameters provide most sensitivity. Furthermore, we explore the quantitative accuracy of the obtained measurements to ensure that the obtained abundances are in line with expected ground truth values. We culminate our technical exploration by generating small datasets from two cultured cell lines and a primary bone marrow sample, to showcase obtainable proteome coverage differences from different source materials. Finally, as a proof of concept we explore protein covariation to showcase how information on known protein complexes is captured inherently in our scp-MS data.

biochemistry↗

bioRxiv2024

Unraveling the proteome landscape of mouse hematopoietic stem and progenitor compartment with high sensitivity low-input proteomics

Proteins play a key role in defining cellular phenotypes, yet comprehensive proteomic analysis often requires substantial input material, posing challenges in studying rare populations in complex cell systems. Here, we present an accessible, label-free low-input proteomics workflow that allows for comprehensive proteome coverage reminiscent of classical bulk samples from only 500 cells and showcase its application in murine hematopoiesis. With this approach, we construct a proteomic map of hematopoietic stem and progenitor cell (HSPC) populations isolated by fluorescence-activated cell sorting (FACS) from the bone marrow of a single mouse, identifying approximately 7,000 proteins per cell population. Our study recapitulates the differentiation trajectories along the megakaryocytic-erythroid and granulocytic-monocytic lineages. We specifically focus on the dynamics of transcriptional regulators and provide insights into both known and novel population-specific factors. Furthermore, we extend our exploration to the most primitive stem and progenitor compartment, and identify ADP-Ribosyltransferase ART4 (CD297) as a novel cell surface marker that can potentially be used to enrich for long-term hematopoietic stem cells (LT-HSC). The low-input proteomics workflow presented here holds promise for overcoming the challenges associated with analyzing proteomes of rare cell populations, thereby paving the way for broader applications in biomedical research.

cell biology↗

bioRxiv2024

Refining Spatial Proteomics by Mass Spectrometry: An Efficient Workflow Tailored for Archival Tissue

BackgroundFormalin-fixed, paraffin-embedded (FFPE) tissue remains the gold standard for extensively archiving biological specimens, providing biobanks with large repositories of retrospective potential. However, while formalin crosslinking is effective at preserving tissue, it poses significant challenges for extracting molecular information, including the proteome. Traditionally, this process required high levels of input material, which, in turn, limited the ability to preserve cell-type heterogeneity and spatial information. To address these limitations, we developed an easily adaptable and highly efficient workflow for extracting deep proteomes from low-input materials, such as biopsies used in routine histopathological diagnostics. MethodsWe compared the extraction efficiency of pancreatic acinar cells identified in FFPE tissue samples stained with conventional hematoxylin-eosin (H&E) against that of cells isolated from tissue samples immunostained for the epithelial cell adhesion molecule (EpCAM) across material inputs ranging from 1,166 to 800,000 {micro}m2 (estimated to 2 to 1,310 cells in volume). Cells were isolated using laser capture microdissection and subsequently analyzed using Liquid Chromatography-Tandem Mass Spectrometry. ResultsSimilar yields for both methods were observed, with EpCAM-positive cells yielding slightly higher results--approximately 1,200 unique protein groups at the lowest input and up to 5,900 at the highest. In cells isolated from H&E-stained tissue, [~]900 to [~]5,200 protein groups were identified. We decided that the optimal balance for our workflow, ensuring maximum protein identification while minimizing input material, lies within the range of approximately 50,000 to 100,000 {micro}m2. With these results, we tested spatial capabilities and biological relevance by isolating cancer cells from biopsies of pancreatic cancer, lung cancer, or glioblastoma, with the first two being stained with EpCAM and the latter being stained against the tumor-suppressor protein p53. We successfully identified tissue-specific protein expressions and observed prominent clustering of all cell populations. DiscussionOur results highlight the feasibility of performing spatial proteomics on FFPE tissue using minimal input material. This adaptable methodology opens up possibilities for investigating cell-type-specific biology while preserving spatial and histological information.

bioengineering↗

bioRxiv2023

Evaluating the capabilities of the Astral mass analyzer for single-cell proteomics

The complexity of human physiology arises from well-orchestrated interactions between trillions of single cells in the body. While single-cell RNA sequencing (scRNA-seq) has enhanced our understanding of cell diversity, gene expression alone does not fully characterize cell phenotypes. Additional molecular dimensions, such as proteins, are needed to define cellular states accurately. Mass spectrometry (MS)-based proteomics has emerged as a powerful tool for comprehensive protein analysis, including single-cell applications. However, challenges remain in terms of throughput and proteomic depth, in order to maximize the biological impact of single-cell proteomics by Mass Spectrometry (scp-MS) workflows. This study leverages a novel high-resolution, accurate mass (HRAM) instrument platform, consisting of both an Orbitrap and an innovative HRAM Asymmetric Track Lossless (Astral) analyzer. The Astral analyzer offers high sensitivity and resolution through lossless ion transfer and a unique flight track design. We evaluate the performance of the Thermo Scientific Orbitrap Astral MS using Data-Independent Acquisition (DIA) and assess proteome depth and quantitative precision for ultra-low input samples. Optimal DIA method parameters for single-cell proteomics are identified, and we demonstrate the ability of the instrument to study cell cycle dynamics in Human Embryonic Kidney (HEK293) cells, and cancer cell heterogeneity in a primary Acute Myeloid Leukemia (AML) culture model.

systems biology↗

bioRxiv2023

Assessing the role of trypsin in quantitative plasma- and single-cell proteomics towards clinical application

Mass spectrometry-based bottom-up proteomics is rapidly evolving and routinely applied in large biomedical studies. Proteases are a central component of every bottom-up proteomics experiment, digesting proteins into peptides. Trypsin has been the most widely applied protease in proteomics, due to its characteristics. With ever-larger cohort sizes and possible future clinical application of mass spectrometry-based proteomics, the technical impact of trypsin becomes increasingly relevant. To assess possible biases introduced by trypsin digestion, we evaluated the impact of eight commercially available trypsins in a variety of bottom-up proteomics experiments, and across a range of protease concentrations and storage times. To investigate the universal impact of these technical attributes, we included bulk HeLa-cell lysate, human plasma and single HEK293 cells, which were analyzed over a range of Selected Reaction Monitoring (SRM), Data-Independent Acquisition (DIA), and Data-Dependent Acquisition (DDA) instrument methods on three LC-MS instruments. Quantification methods employed encompassed both label-free approaches and absolute quantification utilizing spike-in heavy-labeled recombinant protein fragment standards. Based on this extensive dataset, we report variations between commercial trypsins, their source, as well as their concentration. Furthermore, we provide suggestions on the handling of trypsin in large scale studies.

molecular biology↗

bioRxiv2023

Synthetic lethal interaction between WEE1 and PKMYT1 is a target for multiple low dose treatment of high-grade serous ovarian carcinoma

Ovarian cancer is driven by genetic alterations that necessitate protective DNA damage and replication stress responses through cell cycle control and genome maintenance. This creates specific vulnerabilities that may be exploited therapeutically. WEE1 kinase is a key cell cycle control kinase, and it has emerged as a promising cancer therapy target. However, adverse effects have limited its clinical progress, especially, when tested in combination with chemotherapies. A strong genetic interaction between WEE1 and PKMYT1 led us to hypothesize that a multiple low dose approach utilising joint WEE1 and PKMYT1 inhibition would allow exploitation of the synthetic lethality. In the present study, we found that the combination of WEE1 and PKMYT1 inhibition exhibited synergistic effects in eradicating ovarian cancer cells and ovarian organoid models at a low dose. The WEE1 and PKMYT1 inhibition synergistically promoted activation of CDK1 by decreasing the phosphorylation levels of T14 and Y15 residues. Furthermore, the combined treatment exacerbated DNA replication stress and replication catastrophe, leading to increase of the genomic instability and inflammatory STAT1 signalling activation. Finally, the multiple low dosing was well tolerated in mice. These findings suggest a new multiple low dose approach to harness the potency of WEE1 inhibition through the synthetic lethal interaction with PKMYT1 that may contribute to the development of new treatments for ovarian cancer.

cancer biology↗

bioRxiv2022

Enhancing single-cell proteomics through tailored Data-Independent Acquisition and micropillar array-based chromatography

Single-cell resolution analysis of complex biological tissues is fundamental to capture cell-state heterogeneity and distinct cellular signaling patterns that remain obscured with population-based techniques. The limited amount of material encapsulated in a single cell however, raises significant technical challenges to molecular profiling. Due to extensive optimization efforts, mass spectrometry-based single-cell proteomics (scp-MS) has emerged as a powerful tool to facilitate proteome profiling from ultra-low amounts of input, although further development is needed to realize its full potential. To this end, we carried out comprehensive analysis of orbitrap-based data independent acquisition (DIA) for limited material proteomics. Notably, we found a fundamental difference between optimal DIA methods for high- and low-load samples. We further improved our low-input DIA method by relying on high-resolution MS1 quantification, thus more efficiently utilizing available mass analyzer time. With our ultra-low input tailored DIA method, we were able to accommodate long injection times and high resolution, while keeping the scan cycle time low enough to ensure robust quantification. Finally, we establish a complete experimental scp-MS workflow, combining DIA with accessible single-cell sample preparation and the latest chromatographic and computational advances and showcase our developments by profiling real single cells.

systems biology↗