Toward Chemical Ecology of Plant-Parasitic Nematodes: Kairomones, Pheromones, and Other Behaviorally Active Chemical Compounds

A high-throughput behavioral screening platform for measuring chemotaxis by C. elegans

Throughout history, humans have relied on plants as a source of medication, flavoring, and food. Plants synthesize large chemical libraries and release many of these compounds into the rhizosphere and atmosphere where they affect animal and microbe behavior. To survive, nematodes must have evolved the sensory capacity to distinguish plant-made small molecules (SMs) that are harmful and must be avoided from those that are beneficial and should be sought. This ability to classify chemical cues as a function of their value is fundamental to olfaction and represents a capacity shared by many animals, including humans. Here, we present an efficient platform based on multiwell plates, liquid handling instrumentation, inexpensive optical scanners, and bespoke software that can efficiently determine the valence (attraction or repulsion) of single SMs in the model nematode, Caenorhabditis elegans. Using this integrated hardware-wetware-software platform, we screened 90 plant SMs and identified 37 that attracted or repelled wild-type animals but had no effect on mutants defective in chemosensory transduction. Genetic dissection indicates that for at least 10 of these SMs, response valence emerges from the integration of opposing signals, arguing that olfactory valence is often determined by integrating chemosensory signals over multiple lines of information. This study establishes that C. elegans is an effective discovery engine for determining chemotaxis valence and for identifying natural products detected by the chemosensory nervous system.

An efficient behavioral screening platform classifies natural products and other chemical cues according to their chemosensory valence in C. elegans

Throughout history, humans have relied on plants as a source of medication, flavoring, and food. Plants synthesize large chemical libraries and release many of these compounds into the rhizosphere and atmosphere where they affect animal and microbe behavior. To survive, nematodes must have evolved the sensory capacity to distinguish plant-made small molecules (SMs) that are harmful and must be avoided from those that are beneficial and should be sought. This ability to classify chemical cues as a function of their value is fundamental to olfaction, and represents a capacity shared by many animals, including humans. Here, we present an efficient platform based on multi-well plates, liquid handling instrumentation, inexpensive optical scanners, and bespoke software that can efficiently determine the valence (attraction or repulsion) of single SMs in the model nematode, Caenorhabditis elegans. Using this integrated hardware-wetware-software platform, we screened 90 plant SMs and identified 37 that attracted or repelled wild-type animals, but had no effect on mutants defective in chemosensory transduction. Genetic dissection indicates that for at least 10 of these SMs, response valence emerges from the integration of opposing signals, arguing that olfactory valence is often determined by integrating chemosensory signals over multiple lines of information. This study establishes that C. elegans is an effective discovery engine for determining chemotaxis valence and for identifying natural products detected by the chemosensory nervous system.

Involvement of cyclic nucleotide-gated channels in soybean cyst nematode chemotaxis and thermotaxis

The soybean cyst nematode (SCN) is one of the most damaging pests affecting soybean production. SCN displays important host recognition behaviors, such as hatching and infection, by recognizing several compounds produced by the host. Therefore, controlling SCN behaviors such as chemotaxis and thermotaxis is an attractive pest control strategy. In this study, we found that cyclic nucleotide-gated channels (CNG channels) regulate SCN chemotaxis and thermotaxis and Hg-tax-2, a gene encoding a CNG channel, is an important regulator of SCN behavior. Gene silencing of Hg-tax-2 and treatment with a CNG channel inhibitor reduced the attraction of second-stage juveniles to nitrate, an attractant with a different recognition mechanism from the host-derived chemoattractant(s), and to host soybean roots, as well as their avoidance behavior toward high temperatures. Co-treatment of ds Hg-tax-2 with the CNG channel inhibitor indicated that Hg-tax-2 is a major regulator of SCN chemotaxis and thermotaxis. These results suggest new avenues for research on control of SCN.

A Deep Learning-Based Decision Support Tool for Plant-Parasitic Nematode Management

Plant-parasitic nematodes (PPN), especially sedentary endoparasitic nematodes like root-knot nematodes (RKN), pose a significant threat to major crops and vegetables. They are responsible for causing substantial yield losses, leading to economic consequences, and impacting the global food supply. The identification of PPNs and the assessment of their population is a tedious and time-consuming task. This study developed a state-of-the-art deep learning model-based decision support tool to detect and estimate the nematode population. The decision support tool is integrated with the fast inferencing YOLOv5 model and used pretrained nematode weight to detect plant-parasitic nematodes (juveniles) and eggs. The performance of the YOLOv5-640 model at detecting RKN eggs was as follows: precision = 0.992; recall = 0.959; F1-score = 0.975; and mAP = 0.979. YOLOv5-640 was able to detect RKN eggs with an inference time of 3.9 milliseconds, which is faster compared to other detection methods. The deep learning framework was integrated into a user-friendly web application system to build a fast and reliable prototype nematode decision support tool (NemDST). The NemDST facilitates farmers/growers to input image data, assess the nematode population, track the population growths, and recommend immediate actions necessary to control nematode infestation. This tool has the potential for rapid assessment of the nematode population to minimise crop yield losses and enhance financial outcomes.

Nematode Pheromones: Structures and Functions

Pheromones are chemical signals secreted by one individual that can affect the behaviors of other individuals within the same species. Ascaroside is an evolutionarily conserved family of nematode pheromones that play an integral role in the development, lifespan, propagation, and stress response of nematodes. Their general structure comprises the dideoxysugar ascarylose and fatty-acid-like side chains. Ascarosides can vary structurally and functionally according to the lengths of their side chains and how they are derivatized with different moieties. In this review, we mainly describe the chemical structures of ascarosides and their different effects on the development, mating, and aggregation of nematodes, as well as how they are synthesized and regulated. In addition, we discuss their influences on other species in various aspects. This review provides a reference for the functions and structures of ascarosides and enables their better application.

Structure-Based Virtual Screening of Natural Products and Optimization for the Design and Synthesis of Novel CeCht1 Inhibitors as Nematicide Candidates

Nematode chitinases are critical components of the nematode life cycle, and CeCht1 is a potential target for developing novel nematicides. Herein, lunidonine, a natural quinoline alkaloid, was first discovered to have inhibitory activity against CeCht1, which was acquired from a library of over 16,000 natural products using a structure-based virtual screening methodology. A pocket-based lead optimization strategy was employed based on the predicted binding mode of lunidonine. Subsequently, a series of benzo[d][1,3]dioxole-5-carboxylate derivatives were designed and synthesized, and their inhibitory activities against CeCht1 as well as in vitro nematicidal activities against Caenorhabditis elegans were assessed. The analysis of structure-activity relationship and inhibitory mechanisms provided insights into their interactions with the CeCht1 active site, which could facilitate future research in improving the potency of the inhibitory activity. Especially, compound a12 interacted well with CeCht1 and exhibited excellent in vitro nematicidal activity against C. elegans with a LC₅₀ value of 41.54 mg/L, suggesting that it could be a promising candidate for a novel chemical nematicide targeting CeCht1. The known binding modes and structural features of these inhibitors will contribute to the design of stronger CeCht1-based nematicides to control nematodes in agriculture.

Low Dose and Non-Targeted Radiation Effects in Environmental Protection and Medicine-A New Model Focusing on Electromagnetic Signaling

The role of signalling in initiating and perpetuating effects triggered by deposition of ionising radiation energy in parts of a system is very clear. Less clear are the very early steps involved in converting energy to chemical and biological effects in non-targeted parts of the system. The paper aims to present a new model, which could aid our understanding of the role of low dose effects in determining ultimate disease outcomes. We propose a key role for electromagnetic signals resulting from physico-chemical processes such as excitation decay, and acoustic waves. These lead to the initiation of damage response pathways such as elevation of reactive oxygen species and membrane associated changes in key ion channels. Critically, these signalling pathways allow coordination of responses across system levels. For example, depending on how these perturbations are transduced, adverse or beneficial outcomes may predominate. We suggest that by appreciating the importance of signalling and communication between multiple levels of organisation, a unified theory could emerge. This would allow the development of models incorporating time, space and system level to position data in appropriate areas of a multidimensional domain. We propose the use of the term "infosome" to capture the nature of radiation-induced communication systems which include physical as well as chemical signals. We have named our model "the variable response model" or "VRM" which allows for multiple outcomes following exposure to low doses or to signals from low dose irradiated cells, tissues or organisms. We suggest that the use of both dose and infosome in radiation protection might open up new conceptual avenues that could allow intrinsic uncertainty to be embraced within a holistic protection framework.