Caenorhabditis elegans is a compact, attractive system for neural circuit analysis. An understanding of the functional dynamics of neural computation requires physiological analyses. We undertook the characterization of transfer at a central synapse in C. elegans by combining optical stimulation of targeted neurons with electrophysiological recordings. We show that the synapse between AFD and AIY, the first stage in the thermotactic circuit, exhibits excitatory, tonic, and graded release. We measured the linear range of the input-output curve and estimate the static synaptic gain as 0.056 (<0.1). Release showed no obvious facilitation or depression. Transmission at this synapse is peptidergic. The AFD/AIY synapse thus seems to have evolved for reliable transmission of a scaled-down temperature signal from AFD, enabling AIY to monitor and integrate temperature with other sensory input. Combining optogenetics with electrophysiology is a powerful way to analyze C. elegans' neural function.
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http://dx.doi.org/10.1073/pnas.1106617108 | DOI Listing |
Alzheimers Dement
December 2024
Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil.
Background: The molecular mechanisms associated with Alzheimer's Disease (AD) have been extensively studied in mouse models (Mus musculus). However, experimental research in these models is costly and time-consuming. In this context, the nematode Caenorhabditis elegans (C.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil.
Background: Replacement, Reduction, and Refinement (3R) guidelines propose the use of alternative models to study human diseases. These models have high homology and are less onerous compared to rodents, which dominate Alzheimer's disease (AD) research. However, it is still necessary to investigate whether evolutionary components are conserved among AD models cross-species.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
Cleveland Clinic Lou Ruvo Center for Brain Health, Cleveland, OH, USA.
Background: The emerging tools of protein-protein interactome network offer a platform to explore not only the molecular complexity of human diseases, but also to identify risk genes and drug targets. Integration of the genome, transcriptome, proteome, and the interactome networks are essential for such identification, including Alzheimer's disease (AD), Parkinson disease (PD), and Amyotrophic lateral sclerosis (ALS) METHOD: In this study, we performed multi-modal analyses of cross-species protein interactome networks and human brain functional genomics data to identify risk genes and drug targets for neurodegenerative diseases. We presented a multi-view topology-based deep learning framework to identify disease-associated genes for cross-species interactome (TAG-X).
View Article and Find Full Text PDFNat Commun
January 2025
Laboratory of High Resolution Optical Imaging, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, Maryland, USA.
Optical aberrations hinder fluorescence microscopy of thick samples, reducing image signal, contrast, and resolution. Here we introduce a deep learning-based strategy for aberration compensation, improving image quality without slowing image acquisition, applying additional dose, or introducing more optics. Our method (i) introduces synthetic aberrations to images acquired on the shallow side of image stacks, making them resemble those acquired deeper into the volume and (ii) trains neural networks to reverse the effect of these aberrations.
View Article and Find Full Text PDFNat Nanotechnol
January 2025
ICFO-Institut de Ciències Fotòniques, Castelldefels, The Barcelona Institute of Science and Technology, Barcelona, Spain.
Quantifying the mechanical response of the biological milieu (such as the cell's interior) and complex fluids (such as biomolecular condensates) would enable a better understanding of cellular differentiation and aging and accelerate drug discovery. Here we present time-shared optical tweezer microrheology to determine the frequency- and age-dependent viscoelastic properties of biological materials. Our approach involves splitting a single laser beam into two near-instantaneous time-shared optical traps to carry out simultaneous force and displacement measurements and quantify the mechanical properties ranging from millipascals to kilopascals across five decades of frequency.
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