Biology subjects

Sebastian, S.

Publications and source records attributed to Sebastian, S..

8 recordsLinked to original sources

bioRxiv2025

GlialCAM Cytoplasmic Signaling in Oligodendrocytes and Astrocytes is Essential for White Matter Homeostasis in the Brain

Glial cell adhesion molecule (GlialCAM) is an astrocyte- and oligodendrocyte-expressed transmembrane protein with two extracellular IgG-like domains and a cytoplasmic tail with putative signaling functions. While numerous studies have explored functions for the GlialCAM IgG-like domains in brain development and physiology, functions for its cytoplasmic signaling tail remain largely unknown. Therefore, we developed a mutant mouse model that expresses a truncated GlialCAM construct (GlialCAM {Delta}CT) that contains intact extracellular and transmembrane domains but lacks the cytoplasmic tail. Deletion of the GlialCAM cytoplasmic domain in glial cells of the brain results in vacuolization within white matter regions without disrupting neurovascular barrier integrity. Consequently, mutant mice exhibited selective deficits in motor coordination, muscular strength, and memory. Single cell transcriptome sequencing identifies GlialCAM-dependent defects in ECM remodeling pathways in white matter tracts. In situ spatial profiling revealed robust activation of astrocytes and microglia in the mutant brain. Proteomic analysis identified GlialCAM cytoplasmic tail interactors with links to MAPK signaling and cytoskeletal regulatory networks. These data reveal important functions for the GlialCAM cytoplasmic tail in homeostasis of white matter tracts in the adult murine brain. The GlialCAM {Delta}CT model may also be useful for studying the pathogenesis and possible treatment of neurological diseases linked to white matter degeneration.

neuroscience↗

bioRxiv2024

In Situ Single-Cell Spatial Profiling of Matrisome Gene Expression in Glioblastoma

The human brain contains a rich milieu of extracellular matrix (ECM) components that are often dysregulated in pathologies including the malignant cancer glioblastoma (GBM). Here, we have used in situ single-cell spatial transcriptomic platforms to map the expression patterns of nearly 400 ECM genes in normal brain and GBM samples. Our analysis identifies at least four different GBM cell populations with unique ECM expression profiles that show spatial enrichment in distinct intratumor regions. Spatial mapping also demonstrates largely non-overlapping expression signatures of various ECM components in GBM stromal cell types, particularly in vascular endothelial cells and reactive microglia/macrophages. Comparisons of GBM (IDH1 wild type) versus lower-grade II and III astrocytoma samples (IDH1 R132H) identifies differential expression of key ECM components, including elevated levels of select ECM glycoproteins (IGFBP2 and MGP) and ECM-affiliated proteins (ANXA1 and ANXA2). In addition, we detect spatially enriched expression of COL8A1 (collagen), LUM (proteoglycan), and POSTN (ECM glycoprotein) in perivascular stromal cells in GBM but not in lower grade tumors. Computational analysis of putative ligand-receptor interactions reveals novel ECM communication networks between cancer cells and stromal components, particularly in regions of GBM microvascular proliferation and pseudopalisading necrosis. In summary, this comprehensive spatial map provides new insights into microenvironmental control of GBM initiation and progression and identifies potential therapeutic targets in the ECM.

cancer biology↗

bioRxiv2023

Potent immunogenicity and protective efficacy of a multi-pathogen vaccination targeting Zaire ebolavirus, Sudan ebolavirus, Marburg and Lassa viruses

Viral haemorrhagic fevers (VHF) pose a significant threat to human health. In recent years, VHF outbreaks caused by Ebola, Marburg and Lassa viruses have caused substantial morbidity and mortality in West and Central Africa. In 2022, an Ebola disease outbreak in Uganda caused by Sudan ebolavirus resulted in 164 cases with 55 deaths. In February 2023, a Marburg disease outbreak was confirmed in Equatorial Guinea resulting in 15 confirmed and 23 suspected cases to date, with a second outbreak occurring concurrently in Tanzania. There are no clearly defined correlates of protection against these VHF, impeding targeted subunit vaccine development. Any vaccine developed should therefore induce strong and preferably long-lasting humoral and cellular immunity against these viruses. Ideally this immunity should also cross-protect against viral variants, which are known to circulate in animal reservoirs and cause human disease. We have utilized two viral vectored vaccine platforms, an adenovirus (ChAdOx1) and Modified Vaccinia Ankara (MVA), to develop a multi-pathogen vaccine regime against three filoviruses (Zaire ebolavirus, Sudan ebolavirus, Marburg) and an arenavirus (Lassa). These platform technologies have consistently demonstrated the capability to induce robust cellular and humoral antigen-specific immunity in humans, most recently in the rollout of the licensed ChAdOx1-nCoV19 /AZD1222. Here, we show that our multi-pathogen vaccines elicit strong cellular and humoral immunity, induce a diverse range of chemokines and cytokines, and most importantly, confers protection after lethal Zaire ebolavirus, Sudan ebolavirus and Marburg virus challenges in a small animal model. Author summaryOutbreaks caused by Ebola and Lassa viruses have made headlines worldwide in recent years. Most recently, in 2023 a Marburg virus outbreak has claimed tens of lives with a high case fatality rate. As yet, no licensed vaccine exists to protect against this and other viral haemorrhagic fevers. An ideal vaccine would induce long-lasting immunity to, and protection from, viruses causing viral haemorrhagic fevers. We developed vaccines which can target multiple strains of Ebolavirus, the closely related Marburg virus and Lassa virus. The geographical ranges of these viruses overlap in West and Central Africa. We used viral vector platform technologies to generate these vaccines; ChAdOx1 has now been administered worldwide as part of COVID-19 vaccine rollouts, and MVA has been used in numerous clinical trials thus far. We found that both long lasting, antigen specific T cell and antibody responses were induced after vaccination. Lastly, we demonstrated these vaccines could protect small animals against challenge with Zaire ebolavirus, Sudan ebolavirus and Marburg virus.

immunology↗

bioRxiv2022

Muscle stem cell function is impaired in absence of Talpid3 - a gene required for primary cilia formation

Skeletal muscle stem cells (MuSC) are crucial for tissue homeostasis and repair after injury. Following activation, they proliferate to generate differentiating myoblasts. A proportion of cells selfrenew, re-enter the MuSC niche under the basal lamina outside the myofiber and become quiescent. Quiescent MuSC have a primary cilium, which is disassembled upon cell cycle entry. Ex vivo experiments suggest cilia are important for MuSC self-renewal, however, their role in muscle regeneration in vivo remains poorly understood. Talpid3 (TA3) is essential for primary cilia formation and Hedgehog (Hh) signalling. Here we use tamoxifen-inducible conditional deletion of TA3 in MuSC (iSC-KO) and show that regeneration is impaired in response to cytotoxic injury. Repeat injury exacerbates the regeneration phenotype in TA3iSC-KO mice, indicating depletion of MuSCs. Single cell transcriptomics of MuSC progeny isolated from myofibers identifies components of several signalling pathways, which are deregulated in absence of TA3, including Hh and Wnt. Pharmacological activation of Wnt restores muscle regeneration, while purmorphamine, an activator of the Smoothened (Smo) co-receptor in the Hh pathway, has no effect. Together, our data suggest that TA3 and primary cilia are important for MuSC self-renewal, and that pharmacological treatment can efficiently restore muscle regeneration.

cell biology↗

bioRxiv2022

HepaCAM Suppresses Glioblastoma Stem Cell Invasion in the Brain

Glioblastoma (GBM) is a malignant brain cancer that contains sub-populations of highly invasive tumor cells that drive progression and recurrence after surgery and radiochemotherapy. The exact mechanisms that enable GBM cells to disperse from the main tumor mass and navigate throughout the brain microenvironment remain largely unknown. As a result, there is a lack of effective strategies to block cancer cell invasive growth in primary and recurrent GBM. Here we report that hepatocyte cell adhesion molecule (hepaCAM), which is normally expressed in perivascular astrocytes, plays central roles in controlling the invasive growth features of GBM cells. Genetically targeting HEPACAM induces a transition from GBM cell proliferation/self-renewal to invasion. Increased invasion is due, in part, to an activation of focal adhesion signaling pathways and enhanced GBM cell adhesion to the extracellular matrix (ECM) in the brain microenvironment. Transcriptional profiling of GBM cells reveals various HEPACAM-regulated genes with links to polarity and invasion. Collectively, these data show that hepaCAM balances ECM adhesion and signaling pathways to control cancer cell proliferation versus invasion in the brain parenchyma. Targeting select components of the hepaCAM pathway may be an effective way to block tumor progression and recurrence in patients with GBM.

cancer biology↗

bioRxiv2021

Parallel Framework for Inferring Genome-Scale Gene Regulatory Networks

Genome-scale network inference is essential to understand comprehensive interaction patterns. Current methods are limited to the reconstruction of small to moderate-size networks. The most obvious alternative is to propose a novel method or alter existing methods that may leverage parallel computing paradigms. Very few attempts also have been made to re-engineer existing methods by executing selective iterative steps concurrently. We propose a generic framework in this paper that leverages parallel computing without re-engineering the original methods. The proposed framework uses state-of-the-art methods as a black box to infer sub-networks of the segmented data matrix. A simple merger was designed based on preferential attachment to generate the global network by merging the sub-networks. Fifteen (15) inference methods were considered for experimentation. Qualitative and speedup analysis was carried out using DREAM challenge networks. The proposed framework was implemented on all the 15 inference methods using large expression matrices. The results were auspicious as we could infer large networks in reasonable time without compromising the qualitative aspects of the original (serial) algorithm. CLR, the top performer, was then used to infer the network from the expression profiles of an Alzheimers disease (AD) affected mouse model consisting of 45,101 genes. We have also highlighted few hub genes from the network that are functionally related to various diseases.

bioinformatics↗

bioRxiv2020

Supersampling Enables Accurate Microstructural Bone Adaptation Simulations in Human in vivo HR-pQCT Images

In silico trials of treatments in a virtual physiological human (VPH) would revolutionize research in the biomedical field. Hallmarks of bone disease and treatments can already be simulated in pre-clinical models and in ex vivo data of humans using microstructural bone adaptation simulations. The increasing availability of in vivo high resolution peripheral quantitative computed tomography (HR-pQCT) images provides novel opportunities to validate and ultimately utilize microstructural bone adaptation simulations to improve our understanding of bone diseases and move towards in silico VPH decision support systems for clinicians. In the present study, we investigated if microstructural bone adaptation simulations of in vivo human HR-pQCT images yielded accurate results. Since high-resolution ground truth images cannot be obtained in vivo, we applied an ex vivo approach to study resolution dependence and the effect of upscaling on morphometric accuracy. To address simulation initialisation issues, we developed an input regularisation approach to reduce initialisation shocks observed in microstructural bone adaptation simulations and evaluated upscaling as a way to improve the accuracy of model inputs. Finally, we compared our ex vivo results to simulations run on in vivo images to investigate whether in vivo image artefacts further affect simulation outcomes.

bioinformatics↗

bioRxiv2019

Molecular profiling predicts meningioma recurrence and reveals loss of DREAM complex repression in aggressive tumors

Meningiomas account for one-third of all primary brain tumors. Although typically benign, about 20% of meningiomas are aggressive, and despite the rigor of the current histopathological classification system, there remains considerable uncertainty in predicting tumor behavior. Here, we analyzed 160 tumors from all three WHO grades (I-III) using clinical, gene expression and sequencing data. Unsupervised clustering analysis identified three molecular types (A, B, and C) that reliably predicted recurrence. These groups did not directly correlate with the WHO grading system, which would classify more than half of the tumors in the most aggressive molecular type as benign. Transcriptional and biochemical analyses revealed that aggressive meningiomas involve loss of the repressor function of the DREAM complex, which results in cell cycle activation; only tumors in this category tend to recur after full resection. These findings should improve our ability to predict recurrence and develop targeted treatments for these clinically challenging tumors.\n\nSignificance StatementMeningiomas are the most common primary brain tumors. Although most of these tumors are benign, one-fifth will recur despite apparently complete resection. Several studies have demonstrated that genomic approaches can yield important insights into the biology of these tumors. We performed RNA sequencing and whole-exome sequencing of 160 tumors from 140 patients, which identified three distinct groups of meningioma that correlate with recurrence better than the current WHO grading system. Our analysis also revealed that the most aggressive type was characterized by loss of the repressive DREAM complex. These findings should improve prognostication for patients and lead to viable therapeutic targets.

cancer biology↗