Selected Grantee Publications
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- 8 results found
- Aquatic Vertebrate Models
- Imaging
Stat3 Mediates Fyn Kinase-Driven Dopaminergic Neurodegeneration and Microglia Activation
Siddiqui et al., Disease Models & Mechanisms. 2024.
https://pubmed.ncbi.nlm.nih.gov/39641161
The FYN gene is a risk locus for Alzheimer’s disease and several other neurodegenerative disorders. FYN encodes Fyn kinase, and previous studies have shown that Fyn signaling in dopaminergic neurons and microglia plays a role during neurodegeneration. This study investigated Fyn signaling using zebrafish that express a constitutively active Fyn Y531F mutant in neural cells. Activated neural Fyn signaling in the mutant animals resulted in dopaminergic neuron loss and induced inflammatory cytokine expression when compared with controls. Transcriptomic and chemical inhibition analyses revealed that Fyn-driven changes were dependent on the Stat3 and NF-κB signaling pathways, which work synergistically to activate neuronal inflammation and degeneration. This study provides insight into the mechanisms underlying neurodegeneration, identifying Stat3 as a novel effector of Fyn signaling and a potential translational target. Supported by ORIP (R24OD020166).
Gigapixel Imaging With a Novel Multi-Camera Array Microscope
Thomson et al., eLife. 2022.
https://www.doi.org/10.7554/eLife.74988
The dynamics of living organisms are organized across many spatial scales. The investigators created assembled a scalable multi-camera array microscope (MCAM) that enables comprehensive high-resolution, large field-of-view recording from multiple spatial scales simultaneously, ranging from structures that approach the cellular scale to large-group behavioral dynamics. By collecting data from up to 96 cameras, they computationally generated gigapixel-scale images and movies with a field of view over hundreds of square centimeters at an optical resolution of 18 µm. This system allows the team to observe the behavior and fine anatomical features of numerous freely moving model organisms on multiple spatial scales (e.g., larval zebrafish, fruit flies, slime mold). Overall, by removing the bottlenecks imposed by single-camera image acquisition systems, the MCAM provides a powerful platform for investigating detailed biological features and behavioral processes of small model organisms. Supported by ORIP (R44OD024879), NIEHS, NCI, and NIBIB.
Functional and Ultrastructural Analysis of Reafferent Mechanosensation in Larval Zebrafish
Odstrcil et al., Current Biology. 2022.
https://www.sciencedirect.com/science/article/pii/S096098222101530X
All animals need to differentiate between exafferent stimuli (caused by the environment) and reafferent stimuli (caused by their own movement). Researchers characterized how hair cells in zebrafish larvae discriminate between reafferent and exafferent signals. Dye labeling of the lateral line nerve and functional imaging was combined with ultra-structural electron microscopy circuit reconstruction to show that cholinergic signals originating from the hindbrain transmit efference copies, and dopaminergic signals from the hypothalamus may affect threshold modulation. Findings suggest that this circuit is the core implementation of mechanosensory reafferent suppression in these young animals. Supported by ORIP (R43OD024879, R44OD024879) and NINDS.
Whole-Organism 3D Quantitative Characterization of Zebrafish Melanin by Silver Deposition Micro-CT
Katz et al., eLife. 2021.
https://www.biorxiv.org/content/10.1101/2021.03.11.434673v1
This research team combined micro-computed tomography (CT) with a novel application of ionic silver staining to characterize melanin distribution in whole zebrafish larvae. The resulting images enabled whole-body, computational analyses of regional melanin content and morphology. Normalized micro-CT reconstructions of silver-stained fish consistently reproduced pigment patterns seen by light microscopy and allowed direct quantitative comparisons of melanin content. Silver staining of melanin for micro-CT provides proof-of-principle for whole-body, 3D computational phenomic analysis of a specific cell type at cellular resolution. Advances such as this in whole-organism, high-resolution phenotyping provide superior context for studying the phenotypic effects of genetic, disease, and environmental variables. Supported by ORIP (R24OD018559).
Deep Learning-Based Framework for Cardiac Function Assessment in Embryonic Zebrafish from Heart Beating Videos
Naderi et al., Computers in Biology and Medicine. 2021.
https://www.sciencedirect.com/science/article/pii/S0010482521003590
Zebrafish is a powerful model system for a host of biological investigations, cardiovascular studies, and genetic screening. However, the current methods for quantifying and monitoring zebrafish cardiac functions involve tedious manual work and inconsistent estimations. Naderi et al. developed a Zebrafish Automatic Cardiovascular Assessment Framework (ZACAF) based on a U-net deep learning model for automated assessment of cardiovascular indices, such as ejection fraction (EF) and fractional shortening (FS) from microscopic videos of wildtype and cardiomyopathy mutant zebrafish embryos. The framework could be widely applicable with any laboratory resources, and the automatic feature holds promise to enable efficient, consistent, and reliable processing and analysis capacity. Supported by ORIP (R44OD024874)
Loss of Gap Junction Delta-2 (GJD2) Gene Orthologs Leads to Refractive Error in Zebrafish
Quint et al., Communications Biology. 2021.
https://pubmed.ncbi.nlm.nih.gov/34083742/
Myopia is the most common developmental disorder of juvenile eyes. Although little is known about the functional role of GJD2 in refractive error development, the authors find that depletion of gjd2a (Cx35.5) or gjd2b (Cx35.1) orthologs in zebrafish cause changes in eye biometry and refractive status. Their immunohistological and scRNA sequencing studies show that Cx35.5 (gjd2a) is a retinal connexin; its depletion leads to hyperopia and electrophysiological retina changes. They found a lenticular role; lack of Cx35.1 (gjd2b) led to a nuclear cataract that triggered axial elongation. The results provide functional evidence of a link between gjd2 and refractive error. Supported by ORIP (R24OD026591), NIGMS, and NINDS.
Algorithms Underlying Flexible Phototaxis in Larval Zebrafish
Chen et al., Journal of Experimental Biology. 2021.
https://pubmed.ncbi.nlm.nih.gov/34027982/
Given that physiological and environmental variables undergo constant fluctuations over time, how do biological control systems maintain control over these values? The authors demonstrate that larval zebrafish use phototaxis to maintain environmental luminance at a set point, that the value of this set point fluctuates on a time scale of seconds when environmental luminance changes, and it is determined by calculating the mean input across both sides of the visual field. Feedback from the surroundings drives allostatic changes to the luminance set point. The authors describe a novel behavioral algorithm with which larval zebrafish exert control over a sensory variable. Supported by ORIP (R43OD024879, R44OD024879) and NINDS.
Acoustofluidic Rotational Tweezing Enables High-Speed Contactless Morphological Phenotyping of Zebrafish Larvae
Chen et al., Nature Communications. 2021.
https://pubmed.ncbi.nlm.nih.gov/33602914/
These authors demonstrate an acoustofluidic rotational tweezing platform that enables contactless, high-speed, 3D multispectral imaging and digital reconstruction of zebrafish larvae for quantitative phenotypic analysis. The acoustic-induced polarized vortex streaming achieves contactless and rapid (~1 s/rotation) rotation of zebrafish larvae enabling multispectral imaging of the zebrafish body and internal organs. They developed a 3D reconstruction pipeline that yields accurate 3D models based on the multi-view images for quantitative evaluation. With its contactless nature and advantages in speed and automation, the acoustofluidic rotational tweezing system has the potential to be a valuable asset for developmental biology and pre-clinical drug development in pharmacology. Supported by ORIP (R43OD024963), NCI, and NIGMS.