Biology subjects

San-Miguel, A.

Publications and source records attributed to San-Miguel, A..

5 recordsLinked to original sources

bioRxiv2023

Morphological hallmarks of dopaminergic neurodegeneration are associated with altered neuron function in Caenorhabditis elegans

Caenorhabditis elegans (C. elegans) is an excellent model system to study neurodegenerative diseases, such as Parkinsons disease, as it enables analysis of both neuron morphology and function in live animals. Multiple structural changes in neurons, such as cephalic dendrite morphological abnormalities, have been considered hallmarks of neurodegeneration in this model, but their relevance to changes in neuron function are not entirely clear. We sought to test whether hallmark morphological changes associated with chemically induced dopaminergic neuron degeneration, such as dendrite blebbing, breakage, and loss, are indicative of neuronal malfunction and result in changes in behavior. We adapted an established dopaminergic neuronal function assay by measuring paralysis in the presence of exogenous dopamine, which revealed clear differences between cat-2 dopamine deficient mutants, wildtype worms, and dat-1 dopamine abundant mutants. Next, we integrated an automated image processing algorithm and a microfluidic device to segregate worm populations by their cephalic dendrite morphologies. We show that nematodes with dopaminergic dendrite degeneration markers, such as blebbing or breakage, paralyze at higher rates in a dopamine solution, providing evidence that dopaminergic neurodegeneration morphologies are correlated with functional neuronal outputs.

neuroscience↗

bioRxiv2023

An unbiased, automated platform for scoring dopaminergic neurodegeneration in C. elegans

Caenorhabditis elegans (C. elegans) has served as a simple model organism to study dopaminergic neurodegeneration, as it enables quantitative analysis of cellular and sub-cellular morphologies in live animals. These isogenic nematodes have a rapid life cycle and transparent body, making high-throughput imaging and evaluation of fluorescently tagged neurons possible. However, the current state-of-the-art method for quantifying dopaminergic degeneration requires researchers to manually examine images and score dendrites into groups of varying levels of neurodegeneration severity, which is time consuming, subject to bias, and limited in data sensitivity. We aim to overcome the pitfalls of manual neuron scoring by developing an automated, unbiased image processing algorithm to quantify dopaminergic neurodegeneration in C. elegans. The algorithm can be used on images acquired with different microscopy setups and only requires two inputs: a maximum projection image of the four cephalic neurons in the C. elegans head and the pixel size of the users camera. We validate the platform by detecting and quantifying neurodegeneration in nematodes exposed to rotenone, cold shock, and 6-hydroxydopamine using 63x epifluorescence, 63x confocal, and 40x epifluorescence microscopy, respectively. Analysis of tubby mutant worms with altered fat storage showed that, contrary to our hypothesis, increased adiposity did not sensitize to stressor-induced neurodegeneration. We further verify the accuracy of the algorithm by comparing code-generated, categorical degeneration results with manually scored dendrites of the same experiments. The platform, which detects 19 different metrics of neurodegeneration, can provide comparative insight into how each exposure affects dopaminergic neurodegeneration patterns.

bioengineering↗

bioRxiv2021

Endogenous DAF-16 Spatiotemporal Activity Quantitatively Predicts Lifespan Extension Induced by Dietary Restriction

In many organisms, dietary restriction (DR) leads to lifespan extension through the activation of cell protection and pro-longevity gene expression programs. In the nematode C. elegans, the DAF-16 transcription factor is a key aging regulator that governs the Insulin/IGF-1 signaling pathway and undergoes translocation from the cytoplasm to the nucleus of cells when animals are exposed to food limitation. In this work, we assess the endogenous activity of DAF-16 under various DR regimes by coupling CRISPR/Cas9-enabled fluorescent tagging of DAF-16 with quantitative image analysis and machine learning. Our results indicate that lifelong DAF-16 endogenous activity is a robust predictor of mean lifespan in C. elegans, and it accounts for 78% of the lifespan variability induced by DR. We found that this lifespan-extending mechanism occurs mainly in the intestine and neurons, and that DR drives DAF-16 activity in unexpected locations such as the germline and intestinal nucleoli.

systems biology↗

bioRxiv2021

Antagonistic effects of chemical mixtures on the oxidative stress response are silenced by heat stress and reversed under dietary restriction

Chemical agents released into the environment can induce oxidative stress in organisms, which is detrimental for health. Although environmental exposures typically incorporate multiple chemicals, organismal studies on oxidative stress derived from chemical agents commonly study exposures to individual compounds. In this work, we explore how chemical mixtures drive the oxidative stress response under various conditions in the nematode C. elegans, by quantitatively assessing levels of gst-4 expression. Our results indicate that naphthoquinone mixtures drive responses differently than individual components, and that altering environmental conditions, such as increased heat and reduced food availability, result in dramatically different oxidative stress responses mounted by C. elegans. When exposed to heat, the oxidative stress response is diminished. Notably, when exposed to limited food, the oxidative stress response specific to juglone is significantly heightened, while identified antagonistic interactions between some naphthoquinone components in mixtures are abolished. This implies that organismal responses to xenobiotics is confounded by environment and stressor interactions. Given the high number of variables under study, and their potential combinations, a simplex centroid design was used to capture such non-trivial response over the design space. This makes the case for the adoption of Design of Experiments approaches as they can greatly expand the experimental space probed in noisy biological readouts, and in combinatorial experiments. Our results also reveal gaps in our current knowledge of the organismal oxidative stress response, which can be addressed by employing sophisticated design of experiments approaches to identify significant interactions.

physiology↗

bioRxiv2020

Deep learning-enabled phenotyping reveals distinct patterns of neurodegeneration induced by aging and cold-shock

Access to quantitative information is crucial to obtain a deeper understanding of biological systems. In addition to being low-throughput, traditional image-based analysis is mostly limited to error-prone qualitative or semi-quantitative assessment of phenotypes, particularly for complex subcellular morphologies. In this work, we apply deep learning to perform quantitative image-based analysis of complex neurodegeneration patterns exhibited by the PVD neuron in C. elegans. We apply a Convolutional Neural Network algorithm (Mask R-CNN) to identify neurodegenerative sub-cellular protrusions that appear after cold-shock or as a result of aging. A multiparametric phenotypic profile captures the unique morphological changes induced by each perturbation. We identify that acute cold-shock-induced neurodegeneration is reversible and depends on rearing temperature, and importantly, that aging and cold-shock induce distinct neuronal beading patterns.

systems biology↗