A high throughput drug screening paradigm using transgenic Caenorhabditis elegans model of Alzheimer’s disease

Structure activity relationship and target prediction for ABX464 analogues in Caenorhabditis elegans

Global challenges with treatment failures and/or widespread resistance in parasitic worms against commercially available anthelmintics lend impetus to the development of new anthelmintics with novel mechanism(s) of action. The free-living nematode Caenorhabditis elegans is an important model organism used for drug discovery, including the screening and structure-activity investigation of new compounds, and target deconvolution. Previously, we conducted a whole-organism phenotypic screen of the 'Pandemic Response Box' (from Medicines for Malaria Venture, MMV) and identified a hit compound, called ABX464, with activity against C. elegans and a related, parasitic nematode, Haemonchus contortus. Here, we tested a series of 44 synthesized analogues to explore the pharmacophore of activity on C. elegans and revealed five compounds whose potency was similar or greater than that of ABX464, but which were not toxic to human hepatoma (HepG2) cells. Subsequently, we employed thermal proteome profiling (TPP), protein structure prediction and an in silico-docking algorithm to predict ABX464-target candidates. Taken together, the findings from this study contribute significantly to the early-stage drug discovery of a new nematocide based on ABX464. Future work is aimed at validating the ABX464-protein interactions identified here, and at assessing ABX464 and associated analogues against a panel of parasitic nematodes, towards developing a new anthelmintic with a mechanism of action that is distinct from any of the compounds currently-available commercially.

Caenorhabditis elegans Multi-Tracker Based on a Modified Skeleton Algorithm

Automatic tracking of Caenorhabditis elegans (C. egans) in standard Petri dishes is challenging due to high-resolution image requirements when fully monitoring a Petri dish, but mainly due to potential losses of individual worm identity caused by aggregation of worms, overlaps and body contact. To date, trackers only automate tests for individual worm behaviors, canceling data when body contact occurs. However, essays automating contact behaviors still require solutions to this problem. In this work, we propose a solution to this difficulty using computer vision techniques. On the one hand, a skeletonization method is applied to extract skeletons in overlap and contact situations. On the other hand, new optimization methods are proposed to solve the identity problem during these situations. Experiments were performed with 70 tracks and 3779 poses (skeletons) of C. elegans. Several cost functions with different criteria have been evaluated, and the best results gave an accuracy of 99.42% in overlapping with other worms and noise on the plate using the modified skeleton algorithm and 98.73% precision using the classical skeleton algorithm.

Caenorhabditis elegans for rare disease modeling and drug discovery: strategies and strengths

Although nearly 10% of Americans suffer from a rare disease, clinical progress in individual rare diseases is severely compromised by lack of attention and research resources compared to common diseases. It is thus imperative to investigate these diseases at their most basic level to build a foundation and provide the opportunity for understanding their mechanisms and phenotypes, as well as potential treatments. One strategy for effectively and efficiently studying rare diseases is using genetically tractable organisms to model the disease and learn about the essential cellular processes affected. Beyond investigating dysfunctional cellular processes, modeling rare diseases in simple organisms presents the opportunity to screen for pharmacological or genetic factors capable of ameliorating disease phenotypes. Among the small model organisms that excel in rare disease modeling is the nematode Caenorhabditis elegans. With a staggering breadth of research tools, C. elegans provides an ideal system in which to study human disease. Molecular and cellular processes can be easily elucidated, assayed and altered in ways that can be directly translated to humans. When paired with other model organisms and collaborative efforts with clinicians, the power of these C. elegans studies cannot be overstated. This Review highlights studies that have used C. elegans in diverse ways to understand rare diseases and aid in the development of treatments. With continuing and advancing technologies, the capabilities of this small round worm will continue to yield meaningful and clinically relevant information for human health.

Improving skeleton algorithm for helping Caenorhabditis elegans trackers

One of the main problems when monitoring Caenorhabditis elegans nematodes (C. elegans) is tracking their poses by automatic computer vision systems. This is a challenge given the marked flexibility that their bodies present and the different poses that can be performed during their behaviour individually, which become even more complicated when worms aggregate with others while moving. This work proposes a simple solution by combining some computer vision techniques to help to determine certain worm poses and to identify each one during aggregation or in coiled shapes. This new method is based on the distance transformation function to obtain better worm skeletons. Experiments were performed with 205 plates, each with 10, 15, 30, 60 or 100 worms, which totals 100,000 worm poses approximately. A comparison of the proposed method was made to a classic skeletonisation method to find that 2196 problematic poses had improved by between 22% and 1% on average in the pose predictions of each worm.

Application of optogenetic Amyloid-β distinguishes between metabolic and physical damages in neurodegeneration

The brains of Alzheimer’s disease patients show a decrease in brain mass and a preponderance of extracellular Amyloid-β plaques. These plaques are formed by aggregation of polypeptides that are derived from the Amyloid Precursor Protein (APP). Amyloid-β plaques are thought to play either a direct or an indirect role in disease progression, however the exact role of aggregation and plaque formation in the aetiology of Alzheimer’s disease (AD) is subject to debate as the biological effects of soluble and aggregated Amyloid-β peptides are difficult to separate in vivo. To investigate the consequences of formation of Amyloid-β oligomers in living tissues, we developed a fluorescently tagged, optogenetic Amyloid-β peptide that oligomerizes rapidly in the presence of blue light. We applied this system to the crucial question of how intracellular Amyloid-β oligomers underlie the pathologies of A. We use Drosophila, C. elegans and D. rerio to show that, although both expression and induced oligomerization of Amyloid-β were detrimental to lifespan and healthspan, we were able to separate the metabolic and physical damage caused by light-induced Amyloid-β oligomerization from Amyloid-β expression alone. The physical damage caused by Amyloid-β oligomers also recapitulated the catastrophic tissue loss that is a hallmark of late AD. We show that the lifespan deficit induced by Amyloid-β oligomers was reduced with Li⁺ treatment. Our results present the first model to separate different aspects of disease progression.

Alzheimer's disease is a progressive condition that damages the brain over time. The cause is not clear, but a toxic molecule called Amyloid-β peptide seems to play a part. It builds up in the brains of people with Alzheimer's disease, forming hard clumps called plaques. Yet, though the plaques are a hallmark of the disease, experimental treatments designed to break them down do not seem to help. This raises the question – do Amyloid-β plaques actually cause Alzheimer's disease?

Answering this question is not easy. One way to study the effect of amyloid plaques is to inject clumps of Amyloid-β peptides into model organisms. This triggers Alzheimer's-like brain damage, but it is not clear why. It remains difficult to tell the difference between the damage caused by the injected Amyloid-β peptides and the damage caused by the solid plaques that they form. For this, researchers need a way to trigger plaque formation directly inside animal brains. This would make it possible to test the effects of plaque-targeting treatments, like the drug lithium.

Optogenetics is a technique that uses light to control molecules in living animals. Hsien, Kaur et al. have now used this approach to trigger plaque formation by fusing light-sensitive proteins to Amyloid-β peptides in worms, fruit flies and zebrafish. This meant that the peptides clumped together to form plaques whenever the animals were exposed to blue light. This revealed that, while both the Amyloid-β peptides and the plaques caused damage, the plaques were much more toxic. They damaged cell metabolism and caused tissue loss that resembled late Alzheimer's disease in humans. To find out whether it was possible to test Alzheimer's treatments in these animals, Hsien, Kaur et al. treated them with the drug, lithium. This increased their lifespan, reversing some of the damage caused by the plaques.

Alzheimer's disease affects more than 46.8 million people worldwide and is the sixth leading cause of death in the USA. But, despite over 50 years of research, there is no cure. This new plaque-formation technique allows researchers to study the effects of amyloid plaques in living animals, providing a new way to test Alzheimer's treatments. This could be of particular help in studies of experimental drugs that aim to reduce plaque formation.