Quo Vadis Caenorhabditis elegans Metabolomics-A Review of Current Methods and Applications to Explore Metabolism in the Nematode

Emerging models for studying adipose tissue metabolism

Understanding adipose metabolism is essential for addressing obesity and related health concerns. However, the ethical and scientific pressure to animal testing, aligning with the 3Rs, has triggered the implementation of diverse alternative models for analysing anomalies in adipose metabolism. In this review, we will address this issue from various perspectives. Traditional adipocyte cell cultures, whether animal or human-derived, offer a fundamental starting point. These systems have their merits but may not fully replicate in vivo complexity. Established cell lines are valuable for high-throughput screening but may lack the authenticity of primary-derived adipocytes, which closely mimic native tissue. To enhance model sophistication, spheroids have been introduced. These three-dimensional cultures better mimicking the in vivo microenvironment, enabling the study of intricate cell-cell interactions, gene expression, and metabolic pathways. Organ-on-a-chip (OoC) platforms take this further by integrating multiple cell types into microfluidic devices, simulating tissue-level functions. Adipose-OoC (AOoC) provides dynamic environments with applications spanning drug testing to personalized medicine and nutrition. Beyond in vitro models, genetically amenable organisms (Caenorhabditis elegans, Drosophila melanogaster, and zebrafish larvae) have become powerful tools for investigating fundamental molecular mechanisms that govern adipose tissue functions. Their genetic tractability allows for efficient manipulation and high-throughput studies. In conclusion, a diverse array of research models is crucial for deciphering adipose metabolism. By leveraging traditional adipocyte cell cultures, primary-derived cells, spheroids, AOoCs, and lower organism models, we bridge the gap between animal testing and a more ethical, scientifically robust, and human-relevant approach, advancing our understanding of adipose tissue metabolism and its impact on health.

In vivo neuroprotective capacity of a Dunaliella salina extract - comprehensive transcriptomics and metabolomics study

In this study, an exhaustive chemical characterization of a Dunaliella salina (DS) microalga extract obtained using supercritical fluids has been performed, and its neuroprotective capacity has been evaluated in vivo using an Alzheimer's disease (AD) transgenic model of Caenorhabditis elegans (strain CL4176). More than 350 compounds were annotated in the studied DS extract, with triacylglycerols, free fatty acids (FAs), carotenoids, apocarotenoids and glycerol being the most abundant. DS extract significantly protects C. elegans in a dose-dependent manner against Aβ-peptide paralysis toxicity, after 32 h, 53% of treated worms at 50 µg/mL were not paralyzed. This concentration was selected to further evaluate the transcriptomics and metabolomics changes after 26 h by using advanced analytical methodologies. The RNA-Seq data showed an alteration of 150 genes, mainly related to the stress and detoxification responses, and the retinol and lipid metabolism. The comprehensive metabolomics and lipidomics analyses allowed the identification of 793 intracellular metabolites, of which 69 were significantly altered compared to non-treated control animals. Among them, different unsaturated FAs, lysophosphatidylethanolamines, nucleosides, dipeptides and modified amino acids that have been previously reported as beneficial during AD progression, were assigned. These compounds could explain the neuroprotective capacity observed, thus, providing with new evidences of the protection mechanisms of this promising extract.

The concentration-dependent physiological damage, oxidative stress, and DNA lesions in Caenorhabditis elegans by subacute exposure to landfill leachate

The leakage of landfill leachate (LL) into environmental media would be happened even in the sanitary/controlled landfill, due to the deterioration of geomembrane and the blockage of drainage system after long-term operation. Considering the complex composition and high concentration of pollutants in LL, its toxicity assessment should be conducted as a whole liquid contaminant. Therefore, the impacts of LL on Caenorhabditis elegans (C. elegans) were investigated under the condition of different exposure time and exposure volume fraction (EVF). The stimulating effects on locomotion behavior and growth of C. elegans were observed after acute (24 h) exposure to LL, which were increased firstly and then decreased with the increase of EVF. Meanwhile, the intestinal barrier was not affected by LL, and levels of reactive oxygen species (ROS) and cell apoptosis significantly decreased. However, stimulation and inhibition effects on locomotion behavior and growth of C. elegans were observed when subacute (72 h) exposure to 0.25%-0.5% and 1%-4% of LL, respectively. The intestinal injury index and levels of ROS and cell apoptosis significantly increased when EVF were 2% and 4%. Although the acute exposure of LL had resulted in obviously biological adaptability and antioxidant defense in C. elegans, the protective mechanisms failed to be induced as the exposure time increased (subacute exposure). The toxic effects were confirmed by the down-regulation of genes associated with antioxidant defense and neurobehavior, accompanied by the up-regulation of intestinal injury and cell apoptosis related genes. Moreover, the disturbance of metabolic pathways that associated with locomotion behaviors, growth, and antioxidant defense provided good supplementary evidence for the confirmation of oxidative stress in C. elegans. The research results verified the potential of C. elegans as model organism to determine the complex toxic effects of LL.

3'sialyllactose and 6'sialyllactose enhance performance in endurance-type exercise through metabolic adaptation

Human milk oligosaccharides (HMOs) belong to a group of multifunctional glycans that are abundantly present in human breast milk. While health effects of neutral oligosaccharides have been investigated extensively, a lot remains unknown regarding health effects of acidic oligosaccharides, such as the two sialyllactoses (SLs), 3'sialyllactose (3'SL), and 6'sialyllactose (6'SL). We utilized Caenorhabditis elegans (C. elegans) to investigate the effects of SLs on exercise performance. Using swimming as an endurance-type exercise, we found that SLs decrease exhaustion, signifying an increase in endurance that is strongest for 6'SL. Through an unbiased metabolomics approach, we identified changes in energy metabolism that correlated with endurance performance. Further investigation suggested that these metabolic changes were related to adaptations of muscle mitochondria that facilitated a shift from beta oxidation to glycogenolysis during exercise. We found that the effect of SLs on endurance performance required AMPK- (aak-1/aak-2) and adenosine receptor (ador-1) signaling. We propose a model where SLs alter the metabolic status in the gut, causing a signal from the intestine to the nervous system toward muscle cells, where metabolic adaptation increases exercise performance. Together, our results underline the potential of SLs in exercise-associated health and contribute to our understanding of the molecular processes involved in nutritionally-induced health benefits.

Omics approaches to investigate the neuroprotective capacity of a Citrus sinensis (sweet orange) extract in a Caenorhabditis elegans Alzheimer's model

Citrus sinensis by-products are a promising source of neuroprotective molecules. In this study, a pressurized liquid extract of Citrus by-products (PLE100) has been extensively characterized, and its neuroprotective capacity tested in the Caenorhabditis elegans strain CL4176, a validated in vivo model of Alzheimer's disease (AD). More than 450 compounds have been annotated in the extract, being triacylglycerols (TGs), stigmastanes, fatty acids (FAs) and carbohydrates the most abundant. The results demonstrate that worms PLE100-treated are significantly protected in a dose-dependent manner against the Aβ-peptide paralysis toxicity. The RNA-Seq data showed an alteration of 294 genes mainly related to the stress response defense along with genes involved in the lipid transport and metabolism. Moreover, the comprehensive metabolomics study allowed the identification of 818 intracellular metabolites, of which 54 were significantly altered (mainly lipids). The integration of these and previous results provides with new evidences of the protection mechanisms of this promising extract.

Metabolomic analysis reveals a differential adaptation process of the larval stages of Anisakis simplex to the host environment

Introduction: Anisakis simplex are parasitic nematodes that cause anisakiasis. The possibility of infection with this parasite is through consumption of raw or undercooked fish products. A. simplex infections are often misdiagnosed, especially in subclinical cases that do not present with typical symptoms such as urticaria, angioedema, and gastrointestinal allergy. The resulting allergic reactions range from rapid-onset and potentially fatal anaphylactic reactions to chronic, debilitating conditions. While there have been numerous published studies on the genomes and proteomes of A. simplex, less attention has been paid to the metabolomes. Metabolomics is concerned with the composition of metabolites in biological systems. Dynamic responses to endogenous and exogenous stimuli are particularly well suited for the study of holistic metabolic responses. In addition, metabolomics can be used to determine metabolic activity at different stages of development or during growth. Materials and methods: In this study, we reveal for the first time the metabolomes of infectious stages (L3 and L4) of A. simplex using untargeted metabolomics by ultra-performance liquid chromatography-mass spectrometry. Results: In the negative ionization mode (ESI-), we identified 172 different compounds, whereas in the positive ionization mode (ESI+), 186 metabolites were found. Statistical analysis showed that 60 metabolites were found in the ESI- mode with different concentration in each group, of which 21 were more enriched in the L3 larvae and 39 in the L4 stage of A. simplex. Comparison of the individual developmental stages in the ESI + mode also revealed a total of 60 differential metabolites, but 32 metabolites were more enriched in the L3 stage larvae, and 28 metabolites were more concentrated in the L4 stage. Discussion: The metabolomics study revealed that the developmental stages of A. simplex differed in a number of metabolic pathways, including nicotinate and nicotinamide metabolism. In addition, molecules responsible for successful migration within their host, such as pyridoxine and prostaglandins (E1, E2, F1a) were present in the L4 stage. In contrast, metabolic pathways for amino acids, starch, and sucrose were mainly activated in the L3 stage. Our results provide new insights into the comparative metabolome profiles of two different developmental stages of A. simplex.

The metabolic contribution of SKN-1/Nrf2 to the lifespan of Caenorhabditis elegans

BACKGROUND AND AIMS

SKN-1, a C. elegans transcription factor analogous to the mammalian NF-E2-related factor (Nrf2), has been known to promote oxidative stress resistance aiding nematodes' longevity. Although SKN-1's functions suggest its implication in lifespan modulation through cellular metabolism, the actual mechanism of how metabolic rearrangements contribute to SKN-1's lifespan modulation has yet to be well characterized. Therefore, we performed the metabolomic profiling of the short-lived skn-1-knockdown C. elegans.

METHODS

We analyzed the metabolic profile of the skn-1-knockdown worms with nuclear magnetic resonance (NMR) spectroscopy and liquid chromatography-tandem mass spectrometry (LC-MS/MS) and obtained distinctive metabolomic profiles compared to WT worms. We further extended our study with gene expression analysis to examine the expression level of genes encoding all metabolic enzymes.

RESULTS

A significant increase in the phosphocholine and AMP/ATP ratio, potential biomarkers of aging, was observed, accompanied by a decrease in the transsulfuration metabolites, NADPH/NADP⁺ ratio, and total glutathione (GSHt), which are known to be involved in oxidative stress defense. skn-1-RNAi worms also exhibited an impairment in the phase II detoxification system, confirmed by the lower conversion rate of paracetamol to paracetamol-glutathione. By further examining the transcriptomic profile, we found a decrease in the expression of cbl-1, gpx, T25B9.9, ugt, and gst, which are involved in GSHt and NADPH synthesis as well as in the phase II detoxification system.

CONCLUSION

Our multi-omics results consistently revealed that the cytoprotective mechanisms, including cellular redox reactions and xenobiotic detoxification system, contribute to the roles of SKN-1/Nrf2 in the lifespan of worms.

β-triketone herbicide exposure cause tyrosine and fat accumulation in Caenorhabditis elegans

β-triketone herbicides have been efficiently employed as an alternate to atrazine. Triketones are 4-hydroxyphenylpyruvate dioxygenase (HPPD) enzyme inhibitors and exposure is reported to cause significant increase in plasma tyrosine levels. In this study, we have employed a non-target organism Caenorhabditis elegans to determine the impact of β-triketone exposures at recommended field doses (RfD). Our results indicate sulcotrione and mesotrione, negatively influence the survival, behavior, and reproduction of the organism at RfD. Additionally, we have traced the parallels regarding the impact of triketones on the tyrosine metabolism pathway, in C. elegans to those in mammalian models, wherein the expression of the tyrosine metabolism pathway genes are altered, directly influencing tyrosine catabolism leading to significant tyrosine accumulation in exposed organism. Further, we investigated the impact of sulcotrione and mesotrione exposure on fat deposition (triglyceride levels, Oil-Red-O staining and lipidomics) and the fatty acid metabolism pathway. In the exposed worms, the expression of enlongases and fatty acid desaturases were up-regulated along with an increase in the levels of triglycerides. Thus, the data indicates a positive association of β-triketone exposure to mis-regulation of the fatty acid metabolism pathway genes leading to fat accumulation in worms. Therefore, β-triketone might be a potential obesogen.

Caenorhabditis elegans: a model organism in the toxicity assessment of environmental pollutants

The unfavorable effects of environmental pollutants are becoming increasingly evident. In recent years, Caenorhabditis elegans (C. elegans) has been used as a powerful terrestrial model organism for environmental toxicity studies owing to its various advantages, including ease of culture, short lifespan, small size, transparent body, and well-characterized genome. In vivo bioassays and field studies can analyze and evaluate various toxic effects of the toxicants on the model organism, while emerging technologies allow profound insights into molecular disturbances underlying the observed phenotypes. In this review, we discuss the applications of C. elegans as a model organism in environmental toxicity studies and delineate apical assays such as lifespan, growth rate, reproduction, and locomotion, which are widely used in toxicity evaluation. In addition to phenotype assays, a comprehensive understanding of the toxic mode of action and mechanism can be achieved through a highly sensitive multi-omics approach, including the expression levels of genes and endogenous metabolites. Recent studies on environmental toxicity using these approaches have been summarized. This review highlights the practicality and advantages of C. elegans in evaluating the toxicity of environmental pollutants and presents the findings of recent toxicity studies performed using this model organism. Finally, we propose crucial technical considerations to escalate the appropriate use of C. elegans in examining the toxic effects of environmental pollutants.

Application of Caenorhabditis elegans in Lipid Metabolism Research

Over the last decade, the development and prevalence of obesity have posed a serious public health risk, which has prompted studies on the regulation of adiposity. With the ease of genetic manipulation, the diversity of the methods for characterizing body fat levels, and the observability of feeding behavior, Caenorhabditis elegans (C. elegans) is considered an excellent model for exploring energy homeostasis and the regulation of the cellular fat storage. In addition, the homology with mammals in the genes related to the lipid metabolism allows many aspects of lipid modulation by the regulators of the central nervous system to be conserved in this ideal model organism. In recent years, as the complex network of genes that maintain an energy balance has been gradually expanded and refined, the regulatory mechanisms of lipid storage have become clearer. Furthermore, the development of methods and devices to assess the lipid levels has become a powerful tool for studies in lipid droplet biology and the regulation of the nematode lipid metabolism. Herein, based on the rapid progress of C. elegans lipid metabolism-related studies, this review outlined the lipid metabolic processes, the major signaling pathways of fat storage regulation, and the primary experimental methods to assess the lipid content in nematodes. Therefore, this model system holds great promise for facilitating the understanding, management, and therapies of human obesity and other metabolism-related diseases.

Natural Products Drug Discovery: On Silica or In-Silico?

Natural products have been the most important source for drug development throughout the human history. Over time, the formulation of drugs has evolved from crude drugs to refined chemicals. In modern drug discovery, conventional natural products lead-finding usually uses a top-down approach, namely bio-guided fractionation. In this approach, the crude extracts are separated by chromatography and resulting fractions are tested for activity. Subsequently, active fractions are further refined until a single active compound is obtained. However, this is a painstakingly slow and expensive process. Among the alternatives that have been developed to improve this situation, metabolomics has proved to yield interesting results having been applied successfully to drug discovery in the last two decades. The metabolomics-based approach in lead-finding comprises two steps: (1) in-depth chemical profiling of target samples, e.g. plant extracts, and bioactivity assessment, (2) correlation of the chemical and biological data by chemometrics. In the first step of this approach, the target samples are chemically profiled in an untargeted manner to detect as many compounds as possible. So far, NMR spectroscopy, LC-MS, GC-MS, and MS/MS spectrometry are the most common profiling tools. The profile data are correlated with the biological activity with the help of various chemometric methods such as multivariate data analysis. This in-silico analysis has a high potential to replace or complement conventional on-silica bioassay-guided fractionation as it will greatly reduce the number of bioassays, and thus time and costs. Moreover, it may reveal synergistic mechanisms, when present, something for which the classical top-down approach is clearly not suited. This chapter aims to give an overview of successful approaches based on the application of chemical profiling with chemometrics in natural products drug discovery.

Characterization of Eight Bacterial Biosensors for Microbial Diagnostic and Therapeutic Applications

The engineering of microbial cells to produce and secrete therapeutics directly in the human body, known as advanced microbial therapeutics, is an exciting alternative to current drug delivery routes. These living therapeutics can be engineered to sense disease biomarkers and, in response, deliver a therapeutic activity. This strategy allows for precise and self-regulating delivery of a therapeutic that adapts to the disease state of the individual patient. Numerous sensing systems have been characterized for use in prokaryotes, but a very limited number of advanced microbial therapeutics have incorporated such sensors. We characterized eight different sensors that respond to physiologically relevant conditions and molecules found in the human body in the probiotic strain Escherichia coli Nissle 1917. The resulting sensors were characterized under aerobic and anaerobic conditions and were demonstrated to be functional under gut-like conditions using the nematode Caenorhabditis elegans as an in vivo model. We show for the first time how a biosensor is able to detect in vivo the bile acid-like molecule Δ⁴-dafachronic acid, a small molecule in C. elegans that regulates lifespan. Furthermore, we exemplify how bacterial sensors can be used to dynamically report on changes in the intestinal environment of C. elegans, by demonstrating the use of a biosensor able to detect changes in lactate concentrations in the gut lumen of individual C. elegans. The biosensors presented in this study allow for dynamic control of expression in vivo and represent a valuable tool in further developing advanced microbiome therapeutics.

Effects of bioactive substances isolated from Siberian medicinal plants on the lifespan of Caenorhabditis elegans

Medicinal plants are sources of natural antioxidants. Acting as reducing agents, these substances protect the human body against oxidative stress and slow down the aging process. We aimed to study the effects of bioactive substances isolated from medicinal plants on the lifespan of Caenorhabditis elegans L. used as a model organism. High-performance liquid chromatography was applied to isolate bioactive substances from the extracts of callus, suspension, and root cultures of meadowsweet (Filipendula ulmaria L.), ginkgo (Ginkgo biloba L.), Baikal skullcap (Scutellaria baicalensis L.), red clover (Trifolium pretense L.), alfalfa (Medicágo sativa L.), and thyme (Thymus vulgaris L.). Their effect on the lifespan of C. elegans nematodes was determined by counting live nematodes treated with their concentrations of 10, 50, 100, and 200 µmol/L after 61 days of the experiment. The results were recorded using IR spectrometry. The isolated bioactive substances were at least 95% pure. We found that the studied concentrations of trans-cinnamic acid, baicalin, rutin, ursolic acid, and magniferin did not significantly increase the lifespan of the nematodes. Naringenin increased their lifespan by an average of 27.3% during days 8–26. Chlorogenic acid at a concentration of 100 µmol/L increased the lifespan of C. elegans by 27.7%. Ginkgo-based kaempferol and quercetin, as well as red clover-based biochanin A at the concentrations of 200, 10, and 100 µmol/L, respectively, increased the lifespan of the nematodes by 30.6, 41.9, and 45.2%, respectively. The bioactive substances produced from callus, root, and suspension cultures of the above medicinal plants had a positive effect on the lifespan of C. elegans nematodes. This confirms their geroprotective properties and allows them to be used as anti-aging agents.

Untargeted Multimodal Metabolomics Investigation of the Haemonchus contortus Exsheathment Secretome

In nematodes that invade the gastro-intestinal tract of the ruminant, the process of larval exsheathment marks the transition from the free-living to the parasitic stages of these parasites. To investigate the secretome associated with larval exsheathment, a closed in vitro system that effectively reproduces the two basic components of an anaerobic rumen environment (CO2 and 39 °C) was developed to trigger exsheathment in one of the most pathogenic and model gastrointestinal parasitic nematodes, Haemonchus contortus (barber‘s pole worm). This study reports the use of multimodal untargeted metabolomics and lipidomics methodologies to identify the metabolic signatures and compounds secreted during in vitro larval exsheathment in the H. contortus infective third-stage larva (iL3). A combination of statistical and chemoinformatic analyses using three analytical platforms revealed a panel of metabolites detected post exsheathment and associated with amino acids, purines, as well as select organic compounds. The major lipid classes identified by the non-targeted lipidomics method applied were lysophosphatidylglycerols, diglycerides, fatty acyls, glycerophospholipids, and a triglyceride. The identified metabolites may serve as metabolic signatures to improve tractability of parasitic nematodes for characterizing small molecule host–parasite interactions related to pathogenesis, vaccine and drug design, as well as the discovery of metabolic biomarkers.

Understanding Inborn Errors of Metabolism through Metabolomics

Inborn errors of metabolism (IEMs) are rare diseases caused by a defect in a single enzyme, co-factor, or transport protein. For most IEMs, no effective treatment is available and the exact disease mechanism is unknown. The application of metabolomics and, more specifically, tracer metabolomics in IEM research can help to elucidate these disease mechanisms and hence direct novel therapeutic interventions. In this review, we will describe the different approaches to metabolomics in IEM research. We will discuss the strengths and weaknesses of the different sample types that can be used (biofluids, tissues or cells from model organisms; modified cell lines; and patient fibroblasts) and when each of them is appropriate to use.

Networks and Graphs Discovery in Metabolomics Data Analysis and Interpretation

Both targeted and untargeted mass spectrometry-based metabolomics approaches are used to understand the metabolic processes taking place in various organisms, from prokaryotes, plants, fungi to animals and humans. Untargeted approaches allow to detect as many metabolites as possible at once, identify unexpected metabolic changes, and characterize novel metabolites in biological samples. However, the identification of metabolites and the biological interpretation of such large and complex datasets remain challenging. One approach to address these challenges is considering that metabolites are connected through informative relationships. Such relationships can be formalized as networks, where the nodes correspond to the metabolites or features (when there is no or only partial identification), and edges connect nodes if the corresponding metabolites are related. Several networks can be built from a single dataset (or a list of metabolites), where each network represents different relationships, such as statistical (correlated metabolites), biochemical (known or putative substrates and products of reactions), or chemical (structural similarities, ontological relations). Once these networks are built, they can subsequently be mined using algorithms from network (or graph) theory to gain insights into metabolism. For instance, we can connect metabolites based on prior knowledge on enzymatic reactions, then provide suggestions for potential metabolite identifications, or detect clusters of co-regulated metabolites. In this review, we first aim at settling a nomenclature and formalism to avoid confusion when referring to different networks used in the field of metabolomics. Then, we present the state of the art of network-based methods for mass spectrometry-based metabolomics data analysis, as well as future developments expected in this area. We cover the use of networks applications using biochemical reactions, mass spectrometry features, chemical structural similarities, and correlations between metabolites. We also describe the application of knowledge networks such as metabolic reaction networks. Finally, we discuss the possibility of combining different networks to analyze and interpret them simultaneously.

Glucose-Potentiated Amikacin Killing of Cefoperazone/Sulbactam Resistant Pseudomonas aeruginosa

Multidrug-resistant Pseudomonas aeruginosa has become one of global threat pathogens for human health due to insensitivity to antibiotics. Recently developed reprogramming metabolomics can identify biomarkers, and then, the biomarkers were used to revert the insensitivity and elevate antibiotic-mediated killing. Here, the methodology was used to study cefoperazone/sulbactam (SCF)-resistant P. aeruginosa (PA-R_SCF) and identified reduced glycolysis and pyruvate cycle, a recent clarified cycle providing respiratory energy in bacteria, as the most key enriched pathways and the depressed glucose as one of the most crucial biomarkers. Further experiments showed that the depression of glucose was attributed to reduction of glucose transport. However, exogenous glucose reverted the reduction to elevate intracellular glucose via activating glucose transport. The elevated glucose fluxed to the glycolysis, pyruvate cycle, and electron transport chain to promote downstream proton motive force (PMF). Consistently, exogenous glucose did not promote SCF-mediated elimination but potentiated aminoglycosides-mediated killing since aminoglycosides uptake is PMF-dependent, where amikacin was the best one. The glucose-potentiated amikacin-mediated killing was effective to both lab-evolved PA-R_SCF and clinical multidrug-resistant P. aeruginosa. These results reveal the depressed glucose uptake causes the reduced intracellular glucose and expand the application of metabolome-reprogramming on selecting conventional antibiotics to achieve the best killing efficacy.

Workflow for Segmentation of Caenorhabditis elegans from Fluorescence Images for the Quantitation of Lipids

The small and transparent nematode Caenorhabditis elegans is increasingly employed for phenotypic in vivo chemical screens. The influence of compounds on worm body fat stores can be assayed with Nile red staining and imaging. Segmentation of C. elegans from fluorescence images is hereby a primary task. In this paper, we present an image-processing workflow that includes machine-learning-based segmentation of C. elegans directly from fluorescence images and quantifies their Nile red lipid-derived fluorescence. The segmentation is based on a J48 classifier using pixel entropies and is refined by size-thresholding. The accuracy of segmentation was >90% in our external validation. Binarization with a global threshold set to the brightness of the vehicle control group worms of each experiment allows a robust and reproducible quantification of worm fluorescence. The workflow is available as a script written in the macro language of imageJ, allowing the user additional manual control of classification results and custom specification settings for binarization. Our approach can be easily adapted to the requirements of other fluorescence image-based experiments with C. elegans.