bims-metalz 2023-07-09 papers

Issue of 2023–07–09
two papers selected by
Mikaila Chetty, Goa University

Toxicol Res. 2023 Jul;39(3): 355-372

Recent insights into autophagy and metals/nanoparticles exposure.

Qiong Li, Yajing Feng, Ruike Wang, Rundong Liu, Yue Ba, Hui Huang.

Some anthropogenic pollutants, such as heavy metals and nanoparticles (NPs), are widely distributed and a major threat to environmental safety and public health. In particular, lead (Pb), cadmium (Cd), chromium (Cr), arsenic (As), and mercury (Hg) have systemic toxicity even at extremely low concentrations, so they are listed as priority metals in relation to their significant public health burden. Aluminum (Al) is also toxic to multiple organs and is linked to Alzheimer's disease. As the utilization of many metal nanoparticles (MNPs) gradually gain traction in industrial and medical applications, they are increasingly being investigated to address potential toxicity by impairing certain biological barriers. The dominant toxic mechanism of these metals and MNPs is the induction of oxidative stress, which subsequently triggers lipid peroxidation, protein modification, and DNA damage. Notably, a growing body of research has revealed the linkage between dysregulated autophagy and some diseases, including neurodegenerative diseases and cancers. Among them, some metals or metal mixtures can act as environmental stimuli and disturb basal autophagic activity, which has an underlying adverse health effect. Some studies also revealed that specific autophagy inhibitors or activators could modify the abnormal autophagic flux attributed to continuous exposure to metals. In this review, we have gathered recent data about the contribution of the autophagy/mitophagy mediated toxic effects and focused on the involvement of some key regulatory factors of autophagic signaling during exposure to selected metals, metal mixtures, as well as MNPs in the real world. Besides this, we summarized the potential significance of interactions between autophagy and excessive reactive oxygen species (ROS)-mediated oxidative damage in the regulation of cell survival response to metals/NPs. A critical view is given on the application of autophagy activators/inhibitors to modulate the systematic toxicity of various metals/MNPs.

Keywords: Autophagy; Metals; Nanoparticles; Toxicity

DOI: https://doi.org/10.1007/s43188-023-00184-2

PLoS One. 2023 ;18(7): e0281797

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

Andrew S Clark, Zachary Kalmanson, Katherine Morton, Jessica Hartman, Joel Meyer, Adriana San-Miguel.

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 user's 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 20 different metrics of neurodegeneration, can provide comparative insight into how each exposure affects dopaminergic neurodegeneration patterns.

DOI: https://doi.org/10.1371/journal.pone.0281797