bioRxiv Science⌕ Search

Biology subjects

Becher, E.

Publications and source records attributed to Becher, E..

2 recordsLinked to original sources

Neuromuscular dysfunction in patient-derived FUSR244RR-ALS iPSC model via axonal downregulation of neuromuscular junction proteins

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative condition characterized by the progressive degeneration of motor neurons, ultimately resulting in death due to respiratory failure. A common feature among ALS cases is the early loss of axons, pointing to defects in axonal transport and translation as initial disease indicators. Here, we established a FUSR244RR-ALS hiPSC-derived model that recapitulates the motor neuron survival and muscle contractility defects characteristic of ALS patients. Analysis of the protein and mRNA expression profiles in axonal and somatodendritic compartments of ALS-afflicted and isogenic control motor neurons revealed a selective downregulation of proteins essential for the neuromuscular junction function in FUS-ALS axons. Furthermore, analysis of FUS CLIP and RIP data showed that FUS binds mRNAs encoding these proteins. This work shed light on the pathogenic mechanisms of ALS and emphasized the importance of axonal gene expression analysis in elucidating the mechanisms of neurodegenerative disorders.

cell biology↗

VoltRon: A Spatial Omics Analysis Platform for Multi-Resolution and Multi-omics Integration using Image Registration

The growing number of spatial omic technologies have created a demand for computational tools capable of managing, storing, and analyzing spatial datasets with multiple modalities and spatial resolutions. Meanwhile, computer vision is becoming an integral part of processing spatial data readouts where image registration and spatial data alignment of tissue sections are essential prior to data integration. Hence, there is a need for computational platforms that analyze data across spatial datasets with diverse resolutions as well as those that manipulate and process images of microanatomical tissue structures. To this end, we have developed VoltRon, a novel R package for spatial omics analysis with a unique data structure that accommodates data readouts with many levels of spatial resolutions (i.e., multi-resolution) including regions of interest (ROIs), spots, single cells, and even subcellular entities such as molecules. To connect and integrate these spatially diverse omic profiles, VoltRon accounts for spatial organization of tissue blocks (samples), layers (sections) and assays given a multi-resolution collection of spatial data readouts. An easy-to-use computer vision toolbox, OpenCV, is fully embedded in VoltRon that allows users to both automatically and manually register spatial coordinates across adjacent layers for data transfer without the need for external software tools. VoltRon is implemented in the R programming language and is freely available at https://github.com/BIMSBbioinfo/VoltRon.

bioinformatics↗