Omics analysis unveils changes in the metabolome and lipidome of Caenorhabditis elegans upon polydopamine exposure.

Polydopamine (PDA) is an insoluble biopolymer with a dark brown-black color that forms through the autoxidation of dopamine. Because of its outstanding biocompatibility and durability, PDA holds enormous promise for various applications, both in the biomedical and non-medical domains. To ensure human safety, protect health, and minimize environmental impacts, the assessment of PDA toxicity is important. In this study, metabolomics and lipidomics assessed the impact of acute PDA exposure on Caenorhabditis elegans (C. elegans). The findings revealed a pronounced perturbation in the metabolome and lipidome of C. elegans at the L4 stage following 24 hours of exposure to 100 µg/mL PDA. The changes in lipid composition varied based on lipid classes. Increased lipid classes included lysophosphatidylethanolamine, triacylglycerides, and fatty acids, while decreased species involved in several sub-classes of glycerophospholipids and sphingolipids. Besides, we detected 37 significantly affected metabolites in the positive and 8 in the negative ion modes due to exposure to PDA in C. elegans. The metabolites most impacted by PDA exposure were associated with purine metabolism, biosynthesis of valine, leucine, and isoleucine; aminoacyl-tRNA biosynthesis; and cysteine and methionine metabolism, along with pantothenate and CoA biosynthesis; the citrate cycle (TCA cycle); and beta-alanine metabolism. In conclusion, PDA exposure may intricately influence the metabolome and lipidome of C. elegans. The combined application of metabolomics and lipidomics offers additional insights into the metabolic perturbations involved in PDA-induced biological effects and presents potential biomarkers for the assessment of PDA safety.

Cyclosporine A-induced systemic metabolic perturbations in rats: A comprehensive metabolome analysis.

A better understanding of cyclosporine A (CsA)-induced nephro- and hepatotoxicity at the molecular level is necessary for safe and effective use. Utilizing a sophisticated study design, this study explored metabolic alterations after long-term CsA treatment in vivo. Rats were exposed to CsA with 4, 10, and 25 mg/kg for 4 weeks and then sacrificed to obtain liver, kidney, urine, and serum for untargeted metabolomics analysis. Differential network analysis was conducted to explore the biological relevance of metabolites significantly altered by toxicity-induced disturbance. Dose-dependent toxicity was observed in all biospecimens. The toxic effects were characterized by alterations of metabolites related to energy metabolism and cellular membrane composition, which could lead to the cholestasis-induced accumulation of bile acids in the tissues. The unfavorable impacts were also demonstrated in the serum and urine. Intriguingly, phenylacetylglycine was increased in the kidney, urine, and serum treated with high doses versus controls. Differential correlation network analysis revealed the strong correlations of deoxycytidine and guanosine with other metabolites in the network, which highlighted the influence of repeated CsA exposure on DNA synthesis. Overall, prolonged CsA administration had system-level dose-dependent effects on the metabolome in treated rats, suggesting the need for careful usage and dose adjustment.

Metabolic phenotyping and global functional analysis facilitate metabolic signature discovery for tuberculosis treatment monitoring.

Tracking alterations in polar metabolite and lipid levels during anti-tuberculosis (TB) interventions is an emerging biomarker discovery and validation approach due to its sensitivity in capturing changes and reflecting on the host status. Here, we employed deep plasma metabolic phenotyping to explore the TB patient metabolome during three phases of treatment: at baseline, during intensive phase treatment, and upon treatment completion. Differential metabolites (DMs) in each period were determined, and the pathway-level biological alterations were explored by untargeted metabolomics-guided functional interpretations that bypassed identification. We identified 41 DMs and 39 pathways that changed during intensive phase completion. Notably, levels of certain amino acids including histidine, bile acids, and metabolites of purine metabolism were dramatically increased. The altered pathways included those involved in the metabolism of amino acids, glycerophospholipids, and purine. At the end of treatment, 44 DMs were discovered. The levels of glutamine, bile acids, and lysophosphatidylinositol significantly increased compared to baseline; the levels of carboxylates and hypotaurine declined. In addition, 37 pathways principally associated with the metabolism of amino acids, carbohydrates, and glycan altered at treatment completion. The potential of each DM for diagnosing TB was examined using a cohort consisting of TB patients, those with latent infections, and controls. Logistic regression revealed four biomarkers (taurine, methionine, glutamine, and acetyl-carnitine) that exhibited excellent performance in differential diagnosis. In conclusion, we identified metabolites that could serve as useful metabolic signatures for TB management and elucidated underlying biological processes affected by the crosstalk between host and TB pathogen during treatment.

Push forward LC-MS-based therapeutic drug monitoring and pharmacometabolomics for anti-tuberculosis precision dosing and comprehensive clinical management.

The spread of tuberculosis (TB), especially multidrug-resistant TB and extensively drug-resistant TB, has strongly motivated the research and development of new anti-TB drugs. New strategies to facilitate drug combinations, including pharmacokinetics-guided dose optimization and toxicology studies of first- and second-line anti-TB drugs have also been introduced and recommended. Liquid chromatography-mass spectrometry (LC-MS) has arguably become the gold standard in the analysis of both endo- and exo-genous compounds. This technique has been applied successfully not only for therapeutic drug monitoring (TDM) but also for pharmacometabolomics analysis. TDM improves the effectiveness of treatment, reduces adverse drug reactions, and the likelihood of drug resistance development in TB patients by determining dosage regimens that produce concentrations within the therapeutic target window. Based on TDM, the dose would be optimized individually to achieve favorable outcomes. Pharmacometabolomics is essential in generating and validating hypotheses regarding the metabolism of anti-TB drugs, aiding in the discovery of potential biomarkers for TB diagnostics, treatment monitoring, and outcome evaluation. This article highlighted the current progresses in TDM of anti-TB drugs based on LC-MS bioassay in the last two decades. Besides, we discussed the advantages and disadvantages of this technique in practical use. The pressing need for non-invasive sampling approaches and stability studies of anti-TB drugs was highlighted. Lastly, we provided perspectives on the prospects of combining LC-MS-based TDM and pharmacometabolomics with other advanced strategies (pharmacometrics, drug and vaccine developments, machine learning/artificial intelligence, among others) to encapsulate in an all-inclusive approach to improve treatment outcomes of TB patients.

Population pharmacokinetic model of rifampicin for personalized tuberculosis pharmacotherapy: Effects of SLCO1B1 polymorphisms on drug exposure.

BACKGROUND: Rifampicin (RIF) exhibits high pharmacokinetic (PK) variability among individuals; a low plasma concentration might result in unfavorable treatment outcomes and drug resistance. This study evaluated the contributions of non- and genetic factors to the interindividual variability of RIF exposure, then suggested initial doses for patients with different weight bands. METHODS: This multicenter prospective cohort study in Korea analyzed demographic and clinical data, the solute carrier organic anion transporter family member 1B1 (SLCO1B1) genotypes, and RIF concentrations. Population PK modeling and simulations were conducted using nonlinear mixed-effect modeling. RESULTS: In total, 879 tuberculosis (TB) patients were divided into a training dataset (510 patients) and a test dataset (359 patients). A one-compartment model with allometric scaling for effect of body size best described the RIF PKs. The apparent clearance (CL/F) was 16.6% higher among patients in the SLCO1B1 rs4149056 wild-type group than among patients in variant group, significantly decreasing RIF exposure in the wild-type group. The developed model showed better predictive performance compared with previously reported models. We also suggested that patients with body weights of <40 kg, 40-55 kg, 55-70 kg, and >70 kg patients receive RIF doses of 450, 600, 750, and 1050 mg/day, respectively. CONCLUSIONS: Total body weight and SLCO1B1 rs4149056 genotypes were the most significant covariates that affected RIF CL/F variability in Korean TB patients. We suggest initial doses of RIF based on World Health Organization weight-band classifications. The model may be implemented in treatment monitoring for TB patients.

Alterations of lipid-related genes during anti-tuberculosis treatment: insights into host immune responses and potential transcriptional biomarkers.

Background: The optimal diagnosis and treatment of tuberculosis (TB) are challenging due to underdiagnosis and inadequate treatment monitoring. Lipid-related genes are crucial components of the host immune response in TB. However, their dynamic expression and potential usefulness for monitoring response to anti-TB treatment are unclear. Methodology: In the present study, we used a targeted, knowledge-based approach to investigate the expression of lipid-related genes during anti-TB treatment and their potential use as biomarkers of treatment response. Results and discussion: The expression levels of 10 genes (ARPC5, ACSL4, PLD4, LIPA, CHMP2B, RAB5A, GABARAPL2, PLA2G4A, MBOAT2, and MBOAT1) were significantly altered during standard anti-TB treatment. We evaluated the potential usefulness of this 10-lipid-gene signature for TB diagnosis and treatment monitoring in various clinical scenarios across multiple populations. We also compared this signature with other transcriptomic signatures. The 10-lipid-gene signature could distinguish patients with TB from those with latent tuberculosis infection and non-TB controls (area under the receiver operating characteristic curve > 0.7 for most cases); it could also be useful for monitoring response to anti-TB treatment. Although the performance of the new signature was not better than that of previous signatures (i.e., RISK6, Sambarey10, Long10), our results suggest the usefulness of metabolism-centric biomarkers. Conclusions: Lipid-related genes play significant roles in TB pathophysiology and host immune responses. Furthermore, transcriptomic signatures related to the immune response and lipid-related gene may be useful for TB diagnosis and treatment monitoring.

Molecular and Metabolic Phenotyping of Hepatocellular Carcinoma for Biomarker Discovery: A Meta-Analysis.

Identifying and translating hepatocellular carcinoma (HCC) biomarkers from bench to bedside using mass spectrometry-based metabolomics and lipidomics is hampered by inconsistent findings. Here, we investigated HCC at systemic and metabolism-centric multiomics levels by conducting a meta-analysis of quantitative evidence from 68 cohorts. Blood transcript biomarkers linked to the HCC metabolic phenotype were externally validated and prioritized. In the studies under investigation, about 600 metabolites were reported as putative HCC-associated biomarkers; 39, 20, and 10 metabolites and 52, 12, and 12 lipids were reported in three or more studies in HCC vs. Control, HCC vs. liver cirrhosis (LC), and LC vs. Control groups, respectively. Amino acids, fatty acids (increased 18:1), bile acids, and lysophosphatidylcholine were the most frequently reported biomarkers in HCC. BAX and RAC1 showed a good correlation and were associated with poor prognosis. Our study proposes robust HCC biomarkers across diverse cohorts using a data-driven knowledge-based approach that is versatile and affordable for studying other diseases.

Bioactive-Guided Phytochemical Investigations, In Vitro and In Silico Alpha-Glucosidase Inhibition of Two Vietnamese Medicinal Plants Dicranopteris linearis and Psychotria adenophylla.

Little is known about the chemical and biological profiles of Dicranopteris linearis and Psychotria adenophylla. No previous studies have investigated alpha-glucosidase inhibition using extracts from D. linearis and P. adenophylla. In this paper, bioactive-guided isolation procedures were applied to the plants D. linearis and P. adenophylla based on alpha-glucosidase inhibition. From the most active fractions, 20 compounds (DL1-DL13 and PA1-PA7) were isolated. The chemical structures were elucidated using spectroscopic data and compared with those available in the literature. These compounds were evaluated for alpha-glucosidase inhibition, while a molecular docking study was performed to elucidate the mechanisms involved. Consequently, D. linearis and P. adenophylla might serve as a good potential for developing new antidiabetic preparations.

Unveiling potentially convergent key events related to adverse outcome pathways induced by silver nanoparticles via cross-species omics-scale analysis.

The adverse effects of silver nanoparticles (AgNPs) have been studied in various models. However, there has been discordance between molecular responses across the literature, attributed to methodological biases and the physicochemical variability of AgNPs. In this study, a gene pathway meta-analysis was conducted to identify convergent and divergent key events (KEs) associated with AgNPs and explore common patterns of these KEs across species. We performed a cross-species analysis of transcriptomic data from multiple studies involving various AgNPs exposure. Pathway enrichment analysis revealed a set of pathways linked to oxidative stress, apoptosis, and metabolite and lipid metabolism, which are considered potentially conserved KEs across species. Subsequently, experiments confirmed that oxidative stress responses could be early KEs in both Caenorhabditis elegans and HepG2 cells. Moreover, AgNPs preferentially impaired the mitochondria, as evidenced by mitochondrial fragmentation and dysfunction. Furthermore, disruption of amino acids, nucleotides, sulfur compounds, glycerolipids, and glycerophospholipids metabolism were in good agreement with gene pathway shreds of evidence. Our findings imply that, although there may be organism-specific responses, potentially conserved events could exist regardless of species and physicochemical factors. These results provide valuable insights into the development of adverse outcome pathways of AgNPs across species and the regulatory toxicity of AgNPs.

Pathway-level multi-omics analysis of the molecular mechanisms underlying the toxicity of long-term tacrolimus exposure.

Tacrolimus (TAC)-based treatment is associated with nephrotoxicity and hepatotoxicity; however, the underlying molecular mechanisms responsible for this toxicity have not been fully explored. This study elucidated the molecular processes underlying the toxic effects of TAC using an integrative omics approach. Rats were sacrificed after 4 weeks of daily oral TAC administration at a dose of 5 mg/kg. The liver and kidney underwent genome-wide gene expression profiling and untargeted metabolomics assays. Molecular alterations were identified using individual data profiling modalities and further characterized by pathway-level transcriptomics-metabolomics integration analysis. Metabolic disturbances were mainly related to an imbalance in oxidant-antioxidant status, as well as in lipid and amino acid metabolism in the liver and kidney. Gene expression profiles also indicated profound molecular alterations, including in genes associated with a dysregulated immune response, proinflammatory signals, and programmed cell death in the liver and kidney. Joint-pathway analysis indicated that the toxicity of TAC was associated with DNA synthesis disruption, oxidative stress, and cell membrane permeabilization, as well as lipid and glucose metabolism. In conclusion, our pathway-level integration of transcriptome and metabolome and conventional analyses of individual omics profiles, provided a more comprehensive picture of the molecular changes resulting from TAC toxicity. This study also serves as a valuable resource for subsequent investigations aiming to understand the mechanism underlying the molecular toxicology of TAC.

Development of a population pharmacokinetic model of pyrazinamide to guide personalized therapy: impacts of geriatric and diabetes mellitus on clearance.

Objectives: This study was performed to develop a population pharmacokinetic model of pyrazinamide for Korean tuberculosis (TB) patients and to explore and identify the influence of demographic and clinical factors, especially geriatric diabetes mellitus (DM), on the pharmacokinetics (PK) of pyrazinamide (PZA). Methods: PZA concentrations at random post-dose points, demographic characteristics, and clinical information were collected in a multicenter prospective TB cohort study from 18 hospitals in Korea. Data obtained from 610 TB patients were divided into training and test datasets at a 4:1 ratio. A population PK model was developed using a nonlinear mixed-effects method. Results: A one-compartment model with allometric scaling for body size effect adequately described the PK of PZA. Geriatric patients with DM (age >70 years) were identified as a significant covariate, increasing the apparent clearance of PZA by 30% (geriatric patients with DM: 5.73 L/h; others: 4.50 L/h), thereby decreasing the area under the concentration-time curve from 0 to 24 h by a similar degree compared with other patients (geriatric patients with DM: 99.87 µg h/mL; others: 132.3 µg h/mL). Our model was externally evaluated using the test set and provided better predictive performance compared with the previously published model. Conclusion: The established population PK model sufficiently described the PK of PZA in Korean TB patients. Our model will be useful in therapeutic drug monitoring to provide dose optimization of PZA, particularly for geriatric patients with DM and TB.

Untargeted Metabolomics Approach for the Differentiation between Panax vietnamensis var. vietnamensis and Panax vietnamensis var. fuscidiscus.

Panax vietnamensis var. vietnamensis (PVV) and Panax vietnamensis var. fuscidiscus (PVF) both belong to Panax vietnamensis species and are chemically and morphologically similar, making it hard to distinguish for the consumer. Herein, 42 PVF and 12 PVV samples were collected in Quang Nam and Lai Chau Province, respectively, and subsequently characterized by ITSr-DNA sequence data to verify their origins. Next, untargeted metabolomics combined with multivariate statistical analysis was developed to differentiate PVV and PVF. The metabolic profiles of PVV and PVF were found to be distinct and classified well using Partial Least-Squares Discriminant Analysis (PLS-DA) in the training set. Among them, seven ginsenosides were of high abundance in PVV, while six were of high abundance in PVF. Next, the test set was used to validate 13 putative differential markers found in the training set, illustrating a complete match with the expression patterns of these ginsenosides in the training set. Finally, PLS-DA and linear Support Vector Machine models both indicated distinct ginsenoside profiles of PVV and PVF without misclassification in the test set. Conclusively, the developed untargeted metabolomics approach might serve as a powerful tool for the authentication of PVV and PVF at the metabolome level.

Recommendation of pharmacokinetics/pharmacodynamics target of ethambutol to suppress tuberculosis resistance: A population pharmacokinetics study on a large prospective cohort.

BACKGROUND: The ability of ethambutol (EMB) to suppress bacterial resistance has been demonstrated in a time-dependent manner. Through the development of a population pharmacokinetics (PK) model, this study aimed to suggest the PK/pharmacodynamics (PD) target and identify the significant covariates that influence interindividual variability (IIV) in the PK of EMB. METHODS: In total, 837 patients from 20 medical centres across Korea were enrolled in this study. The non-linear mixed-effect method was used to establish and validate the population PK model. RESULTS: A two-compartment model with transit compartment absorption was sufficient to describe the PK of EMB. Body weight and renal function were identified as significant covariates that affect IIV of the apparent clearance (CL/F) of EMB. Patients with moderate renal function showed 35% and 55% lower CL/F (CL/F 89.9 L/h) compared with those with mild and normal renal function, respectively. All the renal function groups with simulated doses ranging from 800 to 1200 mg achieved area under the curve over minimum inhibitory concentration (MIC) >119, and maintained T>MIC for >23 h for MIC of 0.5 µg/mL. Based on our simulation result, it is suggested that doses of 800, 1000, and 1200 mg should obtain the T>MIC target of 4, 6, and 8 h, respectively. This model was validated internally and externally. CONCLUSION: This study provides insight into the PK/PD indexes of EMB for three different renal function groups and T>MIC targets for different doses. The results could be used to provide optimal-dose suggestions for EMB.

Multimodal plasma metabolomics and lipidomics in elucidating metabolic perturbations in tuberculosis patients with concurrent type 2 diabetes.

Type 2 diabetes mellitus (DM) poses a major burden for the treatment and control of tuberculosis (TB). Characterization of the underlying metabolic perturbations in DM patients with TB infection would yield insights into the pathophysiology of TB-DM, thus potentially leading to improvements in TB treatment. In this study, a multimodal metabolomics and lipidomics workflow was applied to investigate plasma metabolic profiles of patients with TB and TB-DM. Significantly different biological processes and biomarkers in TB-DM vs. TB were identified using a data-driven, knowledge-based framework. Changes in metabolic and signaling pathways related to carbohydrate and amino acid metabolism were mainly captured by amide HILIC column metabolomics analysis, while perturbations in lipid metabolism were identified by the C18 metabolomics and lipidomics analysis. Compared to TB, TB-DM exhibited elevated levels of bile acids and molecules related to carbohydrate metabolism, as well as the depletion of glutamine, retinol, lysophosphatidylcholine, and phosphatidylcholine. Moreover, arachidonic acid metabolism was determined as a potentially important factor in the interaction between TB and DM pathophysiology. In a correlation network of the significantly altered molecules, among the central nodes, chenodeoxycholic acid was robustly associated with TB and DM. Fatty acid (22:4) was a component of all significant modules. In conclusion, the integration of multimodal metabolomics and lipidomics provides a thorough picture of the metabolic changes associated with TB-DM. The results obtained from this comprehensive profiling of TB patients with DM advance the current understanding of DM comorbidity in TB infection and contribute to the development of more effective treatment.

Lipid class-dependent alterations of Caenorhabditis elegans under harmane exposure.

Altered lipid patterns in Caenorhabditis elegans (C. elegans) resulting from exposure to harmane remain to be explored. In this study, untargeted lipidomics was carried out to elucidate the effects of acute exposure to harmane on the lipidome of C. elegans. Exposure to the compound was evaluated based on the reproduction ability of the worms at 0.1 and 1 µg/mL. No significant effects of harmane were observed at these concentrations. Furthermore, we found that the modulatory effects of harmane on the lipidome of C. elegans at 1 µg/mL were lipid class dependent. In particular, harmane-treated worms were enriched in triglycerides and fatty acids, regardless of the degree of saturation. Glycerophospholipids were generally down-regulated. Furthermore, functional analyses suggested that there was a reduction in lipid membrane bilayer-related terms, and in some related to the mitochondria, and endoplasmic reticulum of C. elegans when treated with harmane. Lipid droplets and storage appeared to be up-regulated. In conclusion, our findings suggest that harmane exposure affects the lipidome of C. elegans in a sophisticated manner. Further investigations are required to elucidate the molecular mechanisms underlying these lipid pattern changes.

Systems-level multi-omics characterization provides novel molecular insights into indomethacin toxicity.

The mechanism of indomethacin toxicity at the systemic level is largely unknown. In this study, multi-specimen molecular characterization was conducted in rats treated with three doses of indomethacin (2.5, 5, and 10 mg/kg) for 1 week. Kidney, liver, urine, and serum samples were collected and analyzed using untargeted metabolomics. The kidney and liver transcriptomics data (10 mg indomethacin/kg and control) were subjected to a comprehensive omics-based analysis. Indomethacin exposure at 2.5 and 5 mg/kg doses did not cause significant metabolome changes, whereas considerable alterations in the metabolic profile compared to the control were induced by a dose of 10 mg/kg. Decreased levels of metabolites and an increased creatine level in the urine metabolome indicated injury to the kidney. The integrated omics analysis in both liver and kidney revealed an oxidant-antioxidant imbalance due to an excess of reactive oxygen species, likely originating from dysfunctional mitochondria. Specifically, indomethacin exposure induced changes in metabolites related to the citrate cycle, cell membrane composition, and DNA synthesis in the kidney. The dysregulation of genes related to ferroptosis and suppression of amino acid and fatty acid metabolism were evidence of indomethacin-induced nephrotoxicity. In conclusion, a multi-specimen omics investigation provided important insights into the mechanism of indomethacin toxicity. The identification of targets that ameliorate indomethacin toxicity will enhance the therapeutic utility of this drug.

Comprehensive lipid profiles investigation reveals host metabolic and immune alterations during anti-tuberculosis treatment: Implications for therapeutic monitoring.

In this study, we investigated the lipidome of tuberculosis patients during standard chemotherapy to discover biosignatures that could aid therapeutic monitoring. UPLC-QToF MS was used to analyze 82 baseline and treatment plasma samples of patients with pulmonary tuberculosis. Subsequently, a data-driven and knowledge-based workflow, including robust annotation, statistical analysis, and functional analysis, was applied to assess lipid profiles during treatment. Overall, the lipids species from 17 lipid subclasses were significantly altered by anti-tuberculosis chemotherapy. Cholesterol ester (CE), monoacylglycerols, and phosphatidylcholine (PC) were upregulated, whereas triacylglycerols, sphingomyelin, and ether-linked phosphatidylethanolamines (PE O-) were downregulated. Notably, PCs demonstrated a clear upward expression pattern during tuberculosis treatment. Several lipid species were identified as potential biomarkers for therapeutic monitoring, such as PC(42:6), PE(O-40:5), CE(24:6), and dihexosylceramide Hex2Cer(34:2;2 O). Functional and lipid gene enrichment analysis revealed alterations in pathways related to lipid metabolism and host immune responses. In conclusion, this study provides a foundation for the use of lipids as biomarkers for clinical management of tuberculosis.

Advancing personalized medicine for tuberculosis through the application of immune profiling.

While early and precise diagnosis is the key to eliminating tuberculosis (TB), conventional methods using culture conversion or sputum smear microscopy have failed to meet demand. This is especially true in high-epidemic developing countries and during pandemic-associated social restrictions. Suboptimal biomarkers have restricted the improvement of TB management and eradication strategies. Therefore, the research and development of new affordable and accessible methods are required. Following the emergence of many high-throughput quantification TB studies, immunomics has the advantages of directly targeting responsive immune molecules and significantly simplifying workloads. In particular, immune profiling has been demonstrated to be a versatile tool that potentially unlocks many options for application in TB management. Herein, we review the current approaches for TB control with regard to the potentials and limitations of immunomics. Multiple directions are also proposed to hopefully unleash immunomics' potential in TB research, not least in revealing representative immune biomarkers to correctly diagnose TB. The immune profiles of patients can be valuable covariates for model-informed precision dosing-based treatment monitoring, prediction of outcome, and the optimal dose prediction of anti-TB drugs.

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.