Biology subjects

Mahdessian, D.

Publications and source records attributed to Mahdessian, D..

5 recordsLinked to original sources

bioRxiv2025

A Morpho-Proteomic Atlas of Mitosis at Sub-Minute Resolution

Precise spatiotemporal protein organization is critical for fundamental biological processes including cell division1,2. Indeed, aberrant mitosis and mitotic factors are involved in diverse diseases, including various cancers3,4, Alzheimers disease5, and rare diseases6. During mitosis, complex spatial rearrangements and regulation ensure the accurate separation of replicated sister chromatids to produce genetically identical daughter cells7-9. Previous studies employed high-throughput methodologies to follow specific proteins during mitosis10-15. Still a temporally refined systems-level approach capable of monitoring morphological and proteomic changes throughout mitosis has been lacking. Here, we achieved unprecedented resolution by phenotypically decomposing mitosis into 40 subsections of a regression plane for proteomic analysis using deep learning and regression techniques. Our deep visual proteomics (DVP) workflow16, revealed rapid, dynamic proteomic changes throughout mitosis. We quantified 4,350 proteins with high confidence, demonstrating that 147 show significant dynamic abundance changes during mitotic progression. Clustering revealed coordinated patterns of protein regulation, while network analysis uncovered tight regulation of core cell cycle proteins and a link between cell cycle and cancer-linked mutations. Immunofluorescence validated abundance changes and linked previously uncharacterised proteins, like C19orf53, to mitosis. To facilitate data navigation, we developed Mito-Omix, a user-friendly online platform that integrates intricate morphological and molecular data. Our morphological and proteomic dataset spans mitosis at high resolution, providing a rich resource for understanding healthy and aberrant cell division.

cell biology↗

bioRxiv2024

Intrinsic Diversity in Primary Cilia Revealed Through Spatial Proteomics

Primary cilia are a critical organelle found on most human cells, and their dysfunction is linked to hereditary ciliopathies with a wide phenotypic spectrum. Despite their significance, the specific roles of cilia in different cell types remain poorly understood due to limitations in analyzing ciliary protein composition. We employed antibody-based spatial proteomics to expand the Human Protein Atlas to primary cilia. Our analysis identified the subciliary locations of 715 proteins across three cell lines, examining 128,156 individual cilia. We found that 69% of the ciliary proteome is cell-type specific, and 78% exhibited single-cilia heterogeneity. Our findings portray cilia as sensors tuning their proteome to effectively sense the environment and compute cellular responses. We identified 91 novel cilia proteins and found a genetic candidate variant in CREB3 in one clinical case with features overlapping ciliopathy phenotypes. This open, spatial cilia atlas advances research on cilia and ciliopathies.

cell biology↗

bioRxiv2024

Dissecting autonomous enzyme variability in single cells

Metabolic enzymes perform life-sustaining functions in various cellular compartments. Anecdotally, metabolic activity is observed to vary between genetically identical cells, which impacts drug resistance, differentiation, and immune cell activation. However, no large-scale resource systematically reporting metabolic cellular heterogeneity exists. Here, we leverage imaging-based single-cell spatial proteomics to reveal the extent of non-genetic variability of the human enzymatic proteome, as a proxy for metabolic states. Nearly two fifths of enzymes exhibit cell-to-cell variable expression, and half localize to multiple cellular compartments. Metabolic heterogeneity arises largely autonomously of cell cycling, and individual cells reestablish these myriad metabolic phenotypes over several cell divisions. Multiplexed imaging revealed that metabolic states are continuous and that the correlation between metabolic pathways is metabolic state dependent. These results establish cell-to-cell enzymatic heterogeneity as an organizing principle of cell biology that may rewire our understanding of drug resistance, treatment design, and other aspects of medicine.

cell biology↗

bioRxiv2020

Mapping of the nucleolar proteome reveals spatiotemporal organization related to intrinsic protein disorder

The nucleolus is essential for ribosome biogenesis and is involved in many other cellular functions. We performed a systematic spatiotemporal dissection of the human nucleolar proteome using confocal microscopy. In total, 1,318 nucleolar proteins were identified; 287 were localized to fibrillar components, and 157 were enriched along the nucleoplasmic border, indicating a potential fourth nucleolar subcompartment (nucleoli rim). We found 65 nucleolar proteins (36 uncharacterized) to relocate to the chromosomal periphery during mitosis. Interestingly, we observed temporal partitioning into two recruitment phenotypes: early (prometaphase) and late (after metaphase), suggesting phase-specific functions. We further show that expression of MKI67 is critical for this temporal partitioning. We provide the first proteome-wide analysis of intrinsic protein disorder for the human nucleolus and show that nucleolar proteins in general, and mitotic chromosome proteins in particular, have significantly higher intrinsic disorder level compared to cytosolic proteins. In summary, this study provides a comprehensive and essential resource of spatiotemporal expression data for the nucleolar proteome as part of the Human Protein Atlas.

cell biology↗

bioRxiv2019

Spatiotemporal dissection of the cell cycle regulated human proteome

Cellular division is a fundamental source of cell-to-cell variability, and studies of transcript and protein abundances have revealed several hundred genes that are regulated by the cell cycle1-8. However, none of these studies provide single-cell resolution of protein expression, leaving an incomplete understanding of cell-to-cell heterogeneity and the roles of cycling transcripts and proteins. Here, we present the first comprehensive map of spatiotemporal heterogeneity of the human proteome by integrating proteomics at subcellular resolution, single-cell transcriptomics, and pseudotime measurements of individual cells within the cell cycle. We identify that 17% of the human proteome displays cell-to-cell variability, of which 26% is correlated to cell cycle progression, and we present the first evidence of cell cycle association for 235 proteins. Only 15% of proteomic cell cycle regulation is due to transcriptomic cycling, which points to other means of regulation such as post-translational modifications. For proteins regulated at the transcript level, we observe a 7.7 hour delay between peak expression of transcript and protein on average. This spatially resolved proteomic map of the cell cycle has been integrated into the Human Protein Atlas and serves as a valuable resource for accelerating molecular studies of the human cell cycle and cell proliferation.

cell biology↗