Narayanan, V. | bioRxiv Science

bioRxiv2020

Complex genetic network underlying the convergent of Rett Syndrome like (RTT-L) phenotype in neurodevelopmental disorders

Mutations of the X-linked gene encoding methyl-CpG-binding protein 2 (MECP2) cause classical forms of Rett syndrome (RTT) in girls. Patients with features of classical Rett syndrome, but do not fulfill all the diagnostic criteria (e.g. absence of a MECP2 mutation), are defined as atypical Rett syndrome. Genes encoding for cyclin-dependent kinase-like 5 (CDKL5) and forkhead box G1 (FOXG1) are more commonly found in patients with atypical Rett syndrome. Nevertheless, a subset of patients who are recognized to have an overlapping phenotype with RTT but are lacking a mutation in a gene that causes typical or atypical RTT are described as having Rett syndrome like phenotype (RTT-L). Whole Exome Sequencing (WES) of 8 RTT-L patients from our cohort revealed mutations in the genes GABRG2, GRIN1, ATP1A2, KCNQ2, KCNB1, TCF4, SEMA6B, and GRIN2A, which are seemingly unrelated to Rett syndrome genes. We hypothesized that the phenotypic overlap in RTT and RTT-L is caused by mutations in genes that affect common cellular pathways critical for normal brain development and function. We annotated the list of genes identified causing RTT-L from peer-reviewed articles and performed a protein-protein interaction (PPI) network analysis. We also investigated their interaction with RTT (typical or atypical) genes such as MECP2, CDKL5, NTNG1, and FOXG1. We found that the RTT-L-causing genes were enriched in the biological pathways such as circadian entrainment, the CREB pathway, and RET signaling, and neuronal processes like ion transport, synaptic transmission, and transcription. We conclude that genes that significantly interact with the PPI network established by RTT genes cause RTT-L, explaining the considerable feature overlap between genes that are indicated for RTT-L and RTT.

genomics↗

bioRxiv2019

A Predictive Model of Intercellular Tension and Cell-Matrix Mechanical Interactions in a Multicellular Geometry

Epithelial cells form continuous sheets of cells that exist in tensional homeostasis. Homeostasis is maintained through cell-to-cell adhesions that distribute tension and balance forces between cells and their underlying matrix. Disruption of tensional homeostasis can lead to Epithelial-Mesenchymal Transition (EMT), which is a transdifferentiation process in which epithelial cells adopt a mesenchymal phenotype, where cell-cell adhesion is lost and individual cell migration is acquired. This process is critical during embryogenesis and wound healing, but is also dysregulated in many disease states. To further understand the role of intercellular tension in spatial patterning of epithelial cell monolayers, we developed a multicellular computational model of cell-cell and cell-substrate forces. This work builds on a hybrid Cellular Potts-finite element model to evaluate cell-matrix mechanical feedback of an adherent multicellular cluster. Thermodynamically-constrained cells migrate by generating traction forces on a finite element substrate to minimize the total energy of the system. Junctional forces at cell-cell contacts balance these traction forces, thereby producing a mechanically stable epithelial monolayer. Simulations were compared to in vitro experiments using fluorescence-based junction force sensors in clusters of cells undergoing EMT. Results indicate that the multicellular CPM model can reproduce many aspects of EMT, including epithelial monolayer formation dynamics, changes in cell geometry, and spatial patterning of cell geometry and cell-cell forces in an epithelial colony.\n\nAuthor summaryEpithelial cells line all organs of the human body and act as a protective barrier by forming a continuous sheet. These cells exert force on both their neighboring cells as well as the underlying extracellular matrix, which is a network of proteins that creates the structure of tissues. Here we develop a model that encompasses both cell-cell forces and cell-matrix forces in an epithelial cell sheet. The model accounts for cell migration and proliferation, and regulates how cell-cell adhesions are formed. We demonstrate how the interplay between cell-cell forces and cell-matrix forces can regulate the formation of the epithelial cell sheet, the organization of cells within the sheet, and the pattern of cell geometries and cell forces within the sheet. We compare computational results with experiments in which epithelial cell sheets are disrupted and cell-cell junction forces are measured, and demonstrate that the model captures many aspects of epithelial cell dynamics observed experimentally.

cell biology↗