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Becher, E.

Publications and source records attributed to Becher, E..

3 recordsLinked to original sources

Multimodal imaging reveals no evidence for magnetite-based magnetoreceptors in the mole-rat eye

Magnetoreception, the ability to perceive the geomagnetic field, is widespread across animals. The underlying sensory mechanism remains elusive, but a long-standing hypothesis proposes single-domain magnetite linked to mechanosensitive ion channels. The Ansells mole-rat (Fukomys anselli) is a subterranean rodent with a magnetic sense, and published behavioral and histological data are consistent with magnetite-based magnetoreceptors in the cornea or retina. Here, we systematically screened for magnetite in the mole-rat eye, combining iron detection via enhanced Prussian blue staining and synchrotron X-ray fluorescence microscopy (XFM) with magnetic detection via MRI quantitative susceptibility mapping (MRI-QSM) and quantum-diamond microscopy (QDM). This revealed only a few iron particles in the retina and cornea, which predominantly overlapped with titanium or chromium, indicating a non-biogenic origin. XFM showed iron-enriched lines in the cornea, but these did not show ferrimagnetic signals. Focusing on other ocular tissues, MRI-QSM revealed the highest susceptibility in the ciliary body, where iron-rich pigmented cells were identified. A TEM-screen, however, failed to detect single-domain magnetite particles in these cells. We conclude that our high-sensitivity multimodal screen provides no evidence for magnetite-based magnetoreceptors in the mole-rat eye, suggesting that mole-rat magnetoreceptors either do not reside in the eye or are based on different physical principles.

neuroscience↗

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↗