Biology subjects

Axelsson, U.

Publications and source records attributed to Axelsson, U..

7 recordsLinked to original sources

bioRxiv2025

Proximity proteomics of primary cilia in human hypothalamic neurons

Primary cilia are hair-like sensory organelles that project from the cell bodies of most cell types, including appetite-regulatory hypothalamic neurons where they likely help sense metabolic factors to regulate food intake. We hypothesized that characterising the proteins present in the primary cilia of hypothalamic neurons would shed mechanistic insights into their sensory role and identify new therapeutic targets for obesity. We therefore targeted the ascorbate peroxidase APEX2 to primary cilia in human induced pluripotent stem cells (hiPSC)-derived hypothalamic neurons to biotinylate and identify ciliary proteins. Among the cilia-enriched proteins, we identified synaptic proteins, neurotransmitter receptors, and cell-cell adhesion and axon guidance proteins, extending recent findings that primary cilia interact with neuronal synapses. We also found genes associated with increased body weight and metabolic phenotypes that could represent new therapeutic targets including the lysophosphatidic receptor 1 (LPAR1), which we validated is cilia-localized and we confirmed that its ligand (LPA) mediates ciliary shortening. These findings provide insights into the molecular mechanisms by which primary cilia functionally impact appetite-regulatory neurons.

cell biology↗

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

SubCell: Vision foundation models for microscopycapture single-cell biology

Cell morphology and subcellular protein organization provide important insights into cellular function and behavior. These cellular features can be studied using large-scale fluorescence microscopy, and machine learning has become a powerful tool to interpret the resulting images for biological insights. Here, we introduce SubCell, a deep learning model for fluorescence microscopy designed to accurately capture cellular morphology, protein localization, cellular forganization, and biological function beyond what humans can readily perceive. SubCell was trained on the proteome-wide image collection from the Human Protein Atlas with a novel proteome-aware learning objective. SubCell outperforms state-of-the-art methods across a variety of tasks relevant to single-cell biology and generalizes to other fluorescence microscopy datasets without any fine-tuning. Additionally, we construct the first proteome-wide hierarchical map of proteome organization that is directly learned from image data. This vision-based multiscale cell map defines cellular subsystems down to protein complex resolution, reveals proteins with similar functions, and distinguishes dynamic and stable behaviors within cellular compartments. Finally, combining SubCell with a protein sequence model enables a rich multimodal approach to capture gene function better than either vision-only or sequence-only models alone. In conclusion, SubCell creates deep, image-driven representations of cellular architecture that are applicable across diverse biological contexts and datasets.

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↗

bioRxiv2024

Evaluation of Iron Oxide Nanoparticles for Lymph Node Detection with Magnetomotive Ultrasound- A Pilot Study in Rats

IntroductionThe inadequate detection of lymph node metastases by current imaging methods has led to overtreatment in rectal cancer. Magnetomotive ultrasound (MMUS) has the potential of being a more accurate diagnostic imaging method for lymph node metastases. This method is based on the detection of tissue movement that is induced by the vibration of iron oxide nanoparticles, caused by an external alternating magnetic field. This study investigated the suitability of the subcutaneous administration of two iron oxide nanoparticles--Ferrotran(R) and Magtrace(R)--and their distribution in lymph nodes, with regard to the possibility of identifying lymph node metastases in rectal cancer by MMUS. MethodsMale Sprague Dawley rats were injected subcutaneously with 10.7 mg Ferrotran(R) (n=9), 10.5 mg Magtrace(R) (n=9), or saline (n=3) dorsally at the root of the tail. On euthanization of the rats after 1, 5, and 24 hours, the proximal and distal lymph nodes were harvested and analyzed by histology [hematoxylin/eosin, Perls Prussian Blue (PPB)] and inductively coupled plasma-optical emission spectroscopy. The primary aim was to evaluate the distribution of the iron oxide nanoparticles throughout the lymphatic system; the general health of the rats after subcutaneous administration of these nanoparticles was also monitored. ResultsAt 1 hour after subcutaneous injection, Ferrotran(R) and Magtrace(R) accumulated in the proximal lymph nodes. After 24 hours, both particles had spread to distal lymph nodes, but only Ferrotran(R) reached the mesenteric and mandibular lymph nodes. In addition, Ferrotran(R) penetrated the lymph nodes more deeply than Magtrace(R) at 24 hours. No toxicity was observed with either nanoparticle. ConclusionAlthough both compounds disseminated well, Ferrotran(R) accumulated better and more rapidly in lymph nodes than Magtrace(R). Because accumulation and time are important parameters for imaging, our data indicate that Ferrotran(R) is a potentially more suitable particle for MMUS in clinical use.

biophysics↗

bioRxiv2022

Subcellular mapping of the protein landscape of SARS-CoV-2 infected cells for target-centric drug repurposing

The COVID-19 pandemic has resulted in millions of deaths and affected socioeconomic structure worldwide and the search for new antivirals and treatments are still ongoing. In the search for new drug target and to increase our understanding of the disease, we used large scale immunofluorescence to explore the host cell response to SARS-CoV-2 infection. Among the 602 host proteins studied in this host response screen, changes in abundance and subcellular localization were observed for 97 proteins, with 45 proteins showing increased abundance and 10 reduced abundances. 20 proteins displayed changed localization upon infection and an additional 22 proteins displayed altered abundance and localization, together contributing to diverse reshuffling of the host cell protein landscape. We then selected existing and approved small-molecule drugs (n =123) against our identified host response proteins and identified 3 compounds - elesclomol, crizotinib and rimcazole, that significantly reduced antiviral activity. Our study introduces a novel, targeted and systematic approach based on host protein profiling, to identify new targets for drug repurposing. The dataset of [~]75,000 immunofluorescence images from this study are published as a resource available for further studies.

cell biology↗