Caenorhabditis elegans in neuroscience: from neural communication to neurodegenerative disease modeling

Abstract

Consistent with humans and other metazoans, the nematode Caenorhabditis elegans (C. elegans) undergoes progressive structural and functional decline during aging. Possessing highly conserved genetic pathways that share extensive homology with human genes, and characterized by a streamlined, fully mapped connectome, C. elegans has emerged as a robust model for dissecting the mechanisms underlying neuronal aging and degeneration. In this review, we summarize the intrinsic advantages of C. elegans as a model organism, highlighting its readily quantifiable behavioral phenotypes, short lifespan, and genetic tractability. We elaborate on its foundational neural communication architecture and its unique utility in constructing molecular models of neurodegenerative diseases. Additionally, we explore the integration of this model system with high-throughput pharmacological screening, environmental toxicology evaluations, and advanced genomic sequencing technologies. Ultimately, this synthesis aims to provide a comprehensive framework for investigating neurodegenerative mechanisms and facilitating clinical translation under specific stress conditions, particularly hypoxia.

Graphical abstract

1. Introduction

The primary objective of neuroscience is to elucidate how the nervous system enables organisms to execute complex functions, ranging from sensory perception and homeostasis to advanced cognitive behaviors. This neural adaptability allows diverse biological species to thrive in volatile environments (Cell editorial team, 2024). Contemporary neurobiology is undergoing a significant shift toward resolving dynamic, subcellular processes within living mammals. This advancement builds directly upon foundational, in-depth studies originally conducted in invertebrates and optically transparent vertebrates (Jan, 2018). The non-parasitic nematode Caenorhabditis elegans (C. elegans) serves as a premier model organism in this context. Since its introduction as an experimental model in the 1970s, this millimeter-sized organism has offered unique and enduring research value. It is characterized by a minute body size, self-fertilization capacity, a brief life cycle, and low maintenance costs; at 20 °C, it matures into an adult within just three days. These biological traits, combined with accessible forward genetic screening and straightforward CRISPR-Cas9 genome editing, render C. elegans an ideal platform for high-throughput drug screening and dissecting the molecular mechanisms of complex phenomena such as aging (Brenner, 1974; Liang et al., 2024). Wild-type C. elegans populations primarily comprise self-fertilizing hermaphrodites, with males naturally occurring at a frequency below 0.2%. This reproductive strategy, along with a large brood size, significantly streamlines the generation of novel lines through genetic crosses (Salinas and Risi, 2018). Consequently, the research utility of this nematode extends across diverse biomedical domains, ranging from ontogeny and aging to pathological modeling, toxicology, and pharmacological screening, establishing it as a foundational model in modern biology.

In nature, C. elegans primarily thrives in microbe-rich, decaying organic matter. In contrast, standard laboratory protocols utilize Escherichia coli as the primary food source, maintaining the nematodes on Nematode Growth Medium agar plates. The life cycle of C. elegans encompasses an embryonic phase, four sequential larval stages (L1 to L4), and a final reproductive adult stage (Zhang et al., 2020). Newly hatched L1 larvae immediately arrest development upon nutrient deprivation. When subjected to starvation, crowding, or thermal stress, L2-stage larvae bypass the standard reproductive cycle to enter the dauer stage—a highly stress-resistant, dormant state. Similarly, egg-laying adults experiencing sudden nutrient deprivation halt germline stem cell division and may even resorb existing embryos to prioritize maternal survival, resuming reproduction only when food availability is restored (Blaxter and Denver, 2012; Corsi et al., 2015). As the first multicellular organism to achieve complete genome sequencing, C. elegans serves as a foundational model for human disease due to its genetic conservation.

Sequence alignments indicate that roughly 60 to 80% of human protein-coding genes share recognizable homologs with the nematode (Culetto and Sattelle, 2000; Rubin et al., 2000), despite the vast structural differences in the non-coding regions that constitute 98% of the human genome. This conservation of functional coding networks allows for robust modeling of various neurodegenerative pathways, which is heavily facilitated by the vast strain repository available through the Caenorhabditis Genetics Center (Harris et al., 2004; Torres et al., 2025; Pir et al., 2026). Despite its structural simplicity, C. elegans exhibits complex behaviors such as navigation, learning, and decision-making, all coordinated by compact neural circuits. Anatomically, the 302 total neurons are partitioned into a 20-cell pharyngeal system and a 282-cell somatic system. Excluding three specific neurons (CANL/R and VC06) due to their unique connectivity profiles, the remaining 279 core somatic neurons constitute the standard platform for network analysis (White et al., 1986; Nicosia et al., 2013). Although synaptic counts are subject to minor variance across different reconstructions, Varshney et al. (2011) remains the widely cited compilation standard. Under this framework, the core somatic network encompasses 6,393 chemical synapses, 890 gap junctions, and 1,410 neuromuscular junctions (Lapierre and Hansen, 2012). Genetic manipulation in C. elegans is remarkably facile. Mutations are typically induced in hermaphrodites through targeted genetic methods, and these alterations are subsequently inherited by offspring via self-fertilization, thereby bypassing the requirement for mating (Liu et al., 2026). Compared to mammals, this nematode offers a fully resolved cell lineage and an exceptionally precise synaptic network, making it an excellent model for studying human pathologies (Eck et al., 2023).

This review systematically articulates the biological characteristics of C. elegans and its unique advantages in behavioral neuroscience. As a powerful model organism, this nematode facilitates precise quantitative measurements and in-depth mechanistic dissections of complex neural behaviors and disease phenotypes. To bridge the gap left by previous reviews that often overlook model constraints, this article systematically compares design choices with a particular emphasis on the explicit drawbacks of each C. elegans model of neurodegenerative diseases, thereby providing a more rigorous framework for evaluating their interpretability and clinical relevance.

2. The nervous system structure of C. elegans

C. elegans offers a highly advantageous whole-organism system for exploring the pathogenic mechanisms of human neurological diseases. This suitability is largely attributed to the fact that C. elegans possesses orthologs for nearly half of all human disease-associated genes; furthermore, its fundamental neurobiological processes, such as synaptic transmission and neural development, remain highly conserved across evolution. Facilitated by a completely sequenced genome and a well-defined neural connectome map, this nematode has become an essential model organism in contemporary neuroscientific research (Roussos et al., 2023).

2.1. Synaptic organization and connectivity

Organisms rely on the nervous system to process internal and external stimuli, generating adaptive physiological responses. Determining the specific contributions of individual neurons or distinct brain regions to these mechanisms remains a central objective in neuroscience (Cisek and Green, 2024). Synapses are specialized structures mediating communication between neurons and target cells. Despite hundreds of millions of years of evolution, their molecular composition and functional architecture remain remarkably consequently, the fundamental principles of neural activity can be effectively deciphered by examining the synaptic networks of anatomically tractable organisms, such as C. elegans (Emmons, 2024).

In a landmark study, White et al. extensively elucidated the nervous system of C. elegans using serial section electron microscopy, reconstructing the spatial connectivity of its 302 neurons. This structural foundation has enabled researchers to visualize broader functional synaptic architectures in live animals via calcium imaging and fluorescence intensity quantification (White et al., 1986; Frankel and Kurshan, 2025). During development, neurons extend neurites to establish intricate communication networks, with synapses serving as the core structures that mediate intercellular signal transmission. Given that the molecular mechanisms underlying electrical synapse formation are relatively less understood than those of chemical synapses, contemporary research focus remains heavily directed toward the structural composition and organizing pathways of chemical synapses (Yogev and Shen, 2014; Portman et al., 2026).

The mononucleated body wall muscle cells in C. elegans are innervated by motor neuron processes extending along the dorsal and ventral nerve cords. These neurons largely exhibit an unmyelinated, unipolar morphology, forming synapses en passant along adjacent parallel neurites (Witvliet et al., 2021). High-resolution electron microscopy reveals the intricate synaptic microstructures of these networks, characterized by distinct presynaptic dense projections, surrounding clear synaptic vesicles containing neurotransmitters, and dense-core vesicles that control neuropeptide release (Mizumoto et al., 2023). To establish these networks, C. elegans body wall muscles extend “muscle arms”—cytoplasmic processes analogous to neuronal dendrites—through which each cell receives dual inputs from excitatory cholinergic and inhibitory gamma-aminobutyric acid-ergic (GABAergic) motor neurons. This unique neuromuscular junction architecture offers an ideal model for investigating how distinct neurotransmitter receptors are sub-compartmentalized and concentrated at corresponding release sites (Calahorro and Izquierdo, 2018). Within this structural framework, muscle arm development defective-4 (MADD-4) functions as a crucial anterograde synaptic organizing factor that ensures precise structural and functional alignment between presynaptic neurotransmitter release zones and postsynaptic receptors. Consequently, a single deletion of MADD-4 significantly reduces the clustering of synaptic neuroligin-1 (NLG-1) and Type-A GABA receptors (GABA_A Rs), whereas a double deletion of MADD-4 and Neurexin-1 causes complete receptor dispersal, thereby disrupting inhibitory synaptic transmission (Maro et al., 2015). The C. elegans synaptic signaling network achieves this precise regulation through the differential actions of distinct MADD-4 isoforms. At excitatory cholinergic synapses, motor neurons secrete the long isoform, MADD-4 L, to induce the clustering of two distinct receptor types. Levamisole-sensitive acetylcholine receptors (L-AChRs) rely on the assistance of an extracellular protein complex including LEVamisole-resistant 9 (LEV-9), LEVamisole-resistant 10 (LEV-10), and One ImmunoGlobulin domain protein 4 (OIG-4). In contrast, nicotine-sensitive acetylcholine receptors (N-AChRs) depend on the transmembrane proteins syndecan-1 (SDN-1) and uncoordinated-40 (UNC-40) for their proper synaptic localization (Hendi et al., 2019). Conversely, at inhibitory GABAergic synapses, the short isoform MADD-4S drives the postsynaptic clustering of GABA_A Rs through two parallel pathways: it directly binds the cell adhesion molecule NLG-1 and recruits UNC-40 to support receptor localization (Tu et al., 2015). This process, whereby UNC-40 assembles the intracellular postsynaptic scaffold, is strictly orchestrated by MADD-4S (Maro et al., 2015; Xu et al., 2015; Zhou et al., 2020). This sophisticated dual-isoform mechanism elegantly demonstrates how mononucleated muscle cells utilize partially overlapping core components to specifically segregate and assemble postsynaptic microdomains corresponding to different neurotransmitters on the same plasma membrane (Jin, 2015; Bhandari et al., 2024). The molecular organization of C. elegans neuromuscular junctions and postsynaptic domains is illustrated in Figure 1.

Figure 1.

The neuromuscular system of C. elegans. (A) Assembly of local postsynaptic protein complexes. (B) Schematic topology of the C. elegans neuromuscular network. VNC, ventral nerve cord; DNC, dorsal nerve cord; GABA, gamma-aminobutyric acid; S/L, short/long (isoforms); DCC, deleted in colorectal cancer; FERM, protein4.1, Ezrin, Radixin, Moesin; FA, FERM-Adjacent; PDZ, PSD-95/Dlg/ZO-1; GAGs, glycosaminoglycans; LIN-2, lineage-2; CASK, calmodulin-dependent serine protein kinase.

2.2. Neurotransmitter and neuropeptide signaling networks

Neurons release classical neurotransmitters in tandem with multiple neuropeptides, which integrate within neural circuits to cooperatively orchestrate behavioral outputs. Accumulating evidence demonstrates that small-molecule and neuropeptide cotransmission pairs are conserved across both invertebrate and vertebrate lineages. Consequently, C. elegans serves as a premier genetic model for delineating the architecture of neuropeptide signaling networks and the mechanistic underpinnings of behavioral regulation (Nusbaum et al., 2017). Table 1 summarizes the primary neurotransmitters and neuromodulators in C. elegans.

Table 1.

Major neurotransmitters and neuromodulators in C. elegans.

Category	Neurotransmitter/neuropeptide	Key markers (Genes)	Primary functions	References
Classical neurotransmitters	Acetylcholine	ChAT (cha-1) VAChT (unc-17)	Primary excitatory neurotransmitter; drives body wall muscle contraction; maintains pharyngeal pumping rhythm; regulates egg-laying and mating behaviors.	Cook et al. (2020), Duerr et al. (2021), Emerson et al. (2021)
	GABA	GAD (unc-25) VGAT (unc-47)	Primary inhibitory neurotransmitter; maintains coordinated body bending; triggers defecation; restricts head foraging amplitude.	Yemini et al. (2021), Wang et al. (2024), Yue et al. (2024)
	Glutamate	VGLUT (eat-4)	Sensory perception; associative learning and memory; formulation of foraging strategies.	Sato et al. (2021), Taylor et al. (2021)
Biogenic amines	Dopamine	TH (cat-2)	Mechanosensation; habituation learning.	Kindt et al. (2007), Han et al. (2017), Millet et al. (2025)
	Serotonin	TPH (tph-1)	Enhances pharyngeal pumping; mediates food-induced slowing response; promotes egg-laying.	Flavell et al. (2013), Dag et al. (2023)
	Tyramine	TDC (tdc-1)	Promotes escape responses; inhibits exploratory head swinging.	Donnelly et al. (2013)
	Octopamine	TBH (tbh-1)	Inhibits egg-laying during starvation; antagonizes 5-HT signaling; promotes food-seeking behavior.	Fernandez et al. (2020)
Neuropeptides	FMRFamide-like peptides	flp family (flp-1 ~ flp-34)	Induces systemic quiescence for physiological protection under stress; fine-tunes locomotion rate, turning frequency, and egg-laying.	Nelson et al. (2014), Ripoll-Sánchez et al. (2023), Watteyne et al. (2024)
	Neuropeptide-like proteins	nlp family (nlp-1 ~ nlp-82)	Balances sensory perception and foraging behaviors; regulates homeostasis during stress responses.	Fadda et al. (2020), Peng et al. (2023), Ripoll-Sánchez et al. (2023)
	Insulin-like peptides	ins family (ins-1 ~ ins-39, daf-28)	Regulates development, metabolism, lifespan, learning, and memory.	Cho et al. (2016), Zheng et al. (2018), Tomioka et al. (2022)

ChAT, choline acetyltransferase; GABA, γ-aminobutyric acid; NLPs, neuropeptide-like proteins; FLPs, FMRFamide-like peptides; ILPs, insulin-like peptides; VAChT, vesicular acetylcholine transporter; GAD, glutamate decarboxylase; VGAT, vesicular inhibitory amino acid transporter; VGLUT, vesicular glutamate transporter; TH, tyrosine hydroxylase; TPH, tryptophan hydroxylase; TDC, tyrosine decarboxylase; TBH, tyramine β-hydroxylase; PC2, proprotein convertase 2; CPE, carboxypeptidase E.

2.2.1. Classical neurotransmitters

Acetylcholine, glutamate, and GABA collectively form the foundation of rapid signal transduction within nematode neural circuits. Acetylcholine acts on ligand-gated ion channels to mediate muscle contraction and regulate various cognitive and addictive behaviors. The C. elegans genome encodes 29 acetylcholine receptor subunits. However, the assembly patterns and specific physiological mechanisms of most neuronal receptors remain incompletely elucidated and warrant further investigation (Zhao J. et al., 2026). GABA is classically recognized as a primary inhibitory signal. Recent findings reveal an unexpected paradigm in C. elegans. GABA released by D-type motor neurons exerts an excitatory—rather than inhibitory—effect on A-type motor neurons to coordinate backward locomotion. Yet, the precise organizational and synaptic scaffolding mechanisms of these atypical excitatory GABA receptors within the motor circuit remain poorly defined (Wang et al., 2026). Glutamate serves as the principal excitatory neurotransmitter. To investigate its behavioral consequences while bypassing direct, acute neurotoxic cell death, researchers have utilized C. elegans to construct a glutamate spillover model. By inactivating the glial glutamate transporter GLT-1, they precisely delineated the specific impacts of synaptic glutamate spillover on nematode behavior (Katz et al., 2019). However, whether these chronic behavioral shifts in transport-deficient nematodes accurately model the progressive, non-cell-autonomous excitotoxicity seen in mammalian neurodegeneration remains a critical challenge.

2.2.2. Biogenic amine neurotransmitters

High-performance liquid chromatography enables the isolation and identification of four primary biogenic amine neurotransmitters in C. elegans: octopamine, dopamine, serotonin, and tyramine. Collectively, these transmitters enable the nematode to modulate behavioral motivation in response to environmental changes (Chase and Koelle, 2007). Octopamine acts as an analog of vertebrate norepinephrine. By dissecting the neural circuits downstream of octopaminergic neurons in invertebrates such as C. elegans, researchers found that starvation upregulates octopamine synthesis (Tao et al., 2016). This elevation subsequently mediates diverse physiological and behavioral processes, including lipid metabolism, stress responses, egg-laying, and foraging (Zhao H. et al., 2026). Synthesized via the catalytic action of tyrosine hydroxylase, dopamine regulates complex behaviors, including locomotion, learning, and habituation to environmental signals. Because the dopaminergic network is highly conserved, C. elegans serves as a critical model organism to decipher the molecular mechanisms of aging and to simulate neurodegenerative conditions such as Parkinson’s disease (Muralidhara and Hardege, 2025). The serotonin system primarily originates from three specific neuron pairs: neurosecretory motor neuron (NSM), amphid sensory neuron (ADF), and hermaphrodite specific neuron (HSN). NSM detects food availability and releases serotonin to stimulate feeding, motor slowing, and dwelling behavior. ADF senses bacterial metabolites to modulate acute feeding and learned avoidance responses against pathogenic bacteria. Located in the midbody, HSN neurons orchestrate egg-laying and locomotion rhythms (Feng et al., 2025). As another vital invertebrate trace amine closely biosynthetically linked to octopamine, tyramine is synthesized via the catalytic action of tyrosine decarboxylase. Upon external stimulation, the TA signaling system rapidly responds to diverse stressors, playing a central role in mediating fight-or-flight-like stress behaviors (Rosikon et al., 2023).

2.2.3. Neuropeptide

The diverse and functionally complex neuropeptides in C. elegans constitute an extensive extrasynaptic signaling network that is structurally distinct from synaptic and monoaminergic systems. These neuropeptides are primarily classified into three major categories: FLPs, NLPs, and ILPs (Beets et al., 2023). Specifically, FLPs function as central regulators of neuromuscular activity; although they typically suppress nervous system activity in most behavioral assays, pharmacological evidence indicates they can also exert excitatory effects (Li and Kim, 2014). Encompassing over 40 distinct genes that encode more than 80 mature peptides, the nlp gene family exhibits profound functional diversity and is strongly hypothesized to modulate feeding behavior due to its prominent expression in C. elegans pharyngeal neurons (Papaioannou et al., 2008). Insulin-like peptides directly regulate animal metabolism, growth, and development, and C. elegans research has been essential for deciphering these conserved molecular mechanisms. The nematode possesses a single canonical insulin/IGF-1 receptor, DAF-2. Current models suggest that the expansive repertoire of insulin-like (INS) peptides transduces signals predominantly through this receptor (Zhu and Chin-Sang, 2024). While the comprehensive resources accumulated for C. elegans—spanning synaptic connectivity, whole-brain neural activity, and molecular expression profiles—provide robust data support for network modeling, translating these multi-omic datasets into predictive functional maps remains a major challenge.

3. Modeling neurodegenerative diseases in C. elegans

Neurodegenerative diseases constitute a major public health challenge affecting a substantial portion of the global population. Alzheimer’s disease (AD), Parkinson’s disease (PD), amyotrophic lateral sclerosis (ALS), and Huntington’s disease (HD) represent the most prevalent forms worldwide. C. elegans serves as an essential bridge between in vitro assays and mammalian models. Leveraging its distinct capacity for high-throughput in vivo screening, this nematode significantly accelerates the candidate drug development pipeline (Panda et al., 2025). To provide a comprehensive overview, Table 2 summarizes the established C. elegans models utilized for these neurodegenerative conditions.

Table 2.

Overview of C. elegans models for neurodegenerative disorders.

Disease	Strain (Promoter::Transgene)	Transgene expression	Phenotype	Limitations	Reference
Alzheimer’s disease	CL2006 (unc-54p::human Aβ1-42)	Constitutive expression in muscle cells	Progressive, adult-onset paralysis. Intramuscular Aβ deposits, shortened lifespan.	Limited to muscle toxicity, cannot mimic central cell-to-cell propagation.	Link (1995), Alvarez et al. (2022)
	GRU102 (myo-2p::YFP+unc-119p::Aβ1-42)	Constitutive pan-neuronal expression	Impaired neuromuscular, sensorimotor behavior.	Lack of neuron-type specificity, low-throughput behavioral scoring.	Fong et al. (2016), Tiwari et al. (2024)
	CL4176 (myo-3p::human Aβ1-42)	Constitutive expression in muscle cells	Temperature-induced paralysis and progeny arrest; Roller phenotype.	Temperature-sensitive, low batch reproducibility.	Drake et al. (2003), Caldero-Escudero et al. (2024)
	CL2122 (unc-54p::SP::human Aβ1-42)	Constitutive expression in muscle cells	Slow adult movement. Intramuscular Aβ deposits.	Muscle-specific expression, lacks neuronal microenvironment.	Fay et al. (1998), Navarro-Hortal et al. (2022)
	CL2331 [myo-3p::GFP::A-Beta (3–42)]	Constitutive expression in muscle cells	Low brood size. Sicker at higher temperatures	Non-specific toxicity phenotypes limit its utility for high-throughput drug screening.	Link et al. (2008), Wen et al. (2024)
	CL2355 (snb-1p::SP::human Aβ1-42::long 3′UTR)	Inducible pan-neuronal expression	Memory deficits, abnormal thrashing in liquid, partial sterility.	Non-specific pan-neuronal vulnerability, low-throughput, highly variable cognitive assays	Luo et al. (2009), Sillapakong et al. (2025)
	GMC101 (unc-54p::Aβ1-42)	Constitutive expression in muscle cells	Temp-induced paralysis & muscular Aβ1-42 aggregation.	Muscle expression lacks neuronal context, temp-induced thermal stress.	McColl et al. (2012), Lin et al. (2022), Liu L. et al. (2025)
	CL2120 (unc-54p::human Aβ1-42)	Constitutive expression in muscle cells	Aβ expression and fibrillation; temperature-enhanced toxicity.	Developmental confounding from constitutive expression.	Fay et al. (1998), Di Carlo (2012)
	CK10 (aex-3p::h4R1NTauV337M; myo-2p::gfp)	Constitutive pan-neuronal expression	Progressive uncoordinated movement, insoluble phosphorylated Tau aggregates.	Lacks circuit specificity, constitutive expression risks developmental confounding.	Kraemer et al. (2003), Kow et al. (2023)
	PIR5 pirIs5[snb-1p::htau40A152T-low; myo-2p::gfp]	Constitutive pan-neuronal expression	Synaptic transmission impairments, reduced lifespan; independent of protein aggregation.	Lacks circuit specificity, constitutive expression risks developmental confounding.	Pir et al. (2016)
	CK2620 (snb-1p::hTMEM106b-core+ myo-3p::mCherry)	Constitutive pan-neuronal expression	Severe progressive locomotor deficits, extensive cytoplasmic protein aggregation.	Lacks full-length transmembrane architecture, alters native proteotoxicity profiles.	Riordan et al. (2025)
Parkinson’s disease	NL5901 (unc-54p::alpha-synnuclein::YFP)	Constitutive expression in muscle cells	Muscular expression of α-synuclein-YFP and in vivo aggregation.	No dopaminergic neuronal microenvironment	van Ham et al. (2008), Chen M. et al. (2024)
	BY273 (dat-1p::alpha-synuclein)	Dopaminergic neurons	Progressive dopaminergic neuronal loss with neurite blebbing	Promoter downregulation risks false-positive cell loss scoring	SenGupta et al. (2021), Tiwari et al. (2024)
	UA44 (dat-1p::alpha -syn high)	Specific expression in dopaminergic neurons	Locomotion reduced, neuron degeneration	Localized to DA neurons, missing pan-neuronal networks; prone to promoter-silencing artifacts	Gaeta et al. (2023), Griffin and Owens (2025)
	DDP1 (unc-54p::alpha -syn::CFP)	Constitutive expression in muscle cells	Reduced lifespan and pharyngeal pumping; in vivo α-synuclein aggregation.	Lacks neuronal specificity	Bodhicharla et al. (2012), Maulik et al. (2017)
	OW13 (unc-54p::alpha -syn::YFP)	Constitutive expression in muscle cells	Muscular α-syn aggregation	Muscle-specific expression lacks neuronal microenvironment	van Ham et al. (2008), Brunetti et al. (2020)
	BZ555 (dat-1p::GFP)	Specific expression in dopaminergic neurons	GFP-labeled dopaminergic neurons; 6-OHDA resistant.	Signals protein down-regulation/synaptic failure, not true cell death.	Nass et al. (2002), Limke et al. (2023)
Amyotrophic lateral sclerosis	CK422 [snb-1p::TDP-43(G290A), myo-2p::dsRED]	Pan-neuronal expression	Pan-neuronal TDP-43 aggregation, severe motor dysfunction, shortened lifespan.	Lacks motor neuron specificity; rapid decline narrows experimental window.	Liachko et al. (2010), Garcia-Toscano et al. (2024)
	BR5270 (rab-3p::F3ΔK280 + myo-2p::mCherry)	Constitutive pan-neuronal	Neuronal Tau aggregation, impaired chemotaxis and locomotion.	Lacks cell-type specificity; fragment expression misses full-length tau interactions.	Fatouros et al. (2012), Chen L. et al. (2024)
	XQ207 xqIs133 [unc- 47p::TDP-43(A315T); unc-119(+)]	Constitutive expression in GABAergic motor neurons	Insoluble TDP-43/FUS aggregation and neuronal degeneration, adult-onset progressive paralysis, normal lifespan.	Lacks cholinergic motor neuron targeting; manual touch-response assays impede high-throughput screening.	Vaccaro et al. (2012), Pir et al. (2026)
	AM263 [unc-54p::Hsa-sod-1 (WT)::YFP]	Constitutive expression in muscle cells	WT SOD-1 expression, mild age-dependent aggregation.	Non-neuronal targeting; lacks robust baseline phenotypes; fusion tag artifacts.	Gidalevitz et al. (2009), Liu et al. (2018)
	PJH897 [rgef-1p::FUS (P525L)]	Constitutive pan-neuronal	Cytoplasmic FUS aggregation, shortened lifespan, severe paralysis.	Pan-neuronal non-specificity; narrow experimental window; missing glial cross-talk.	Murakami et al. (2012)
	HA2987 sod-1 ( rt449 [G93AC]) II	Endogenous expression	Axonal degeneration in GABAergic motor neurons, progressive paralysis.	Mild baseline neurodegeneration; ubiquitous expression lacks cell-type specificity.	Baskoylu et al. (2022), Tossing et al. (2022)
	ZM5844 (rgef-1p::FUSP525L::GFP)	Pan-neuronal expression	Mutant FUS expression in neurons, reduced motor activity.	Lacks motor neuron specificity	Murakami et al. (2012), Alirzayeva et al. (2024)
	GA801 wuIs152 contains [sod-1(genomic)]	Constitutive ubiquitous expression	Roller phenotype; increased protein oxidative damage and altered oxidative stress resistance	No baseline pathology; rol-6 marker confounds motility assays; lacks tissue-specific resolution.	Doonan et al. (2008), Cabreiro et al. (2011)
Huntington’s disease	AM138 (unc-54p::Q24::YFP)	Constitutive expression in muscle cells	Diffuse distribution of soluble Q24-YFP without toxicity.	Lacks protein aggregation pathology; body-wall muscle expression limited.	Morley et al. (2002)
	HA759 (osm-10p::HtnQ150)	Specific expression in ASH sensory neurons	Accelerated ASH neuronal death, larval onset.	Limited ASH neuron specificity; rol-6 background disrupts normal locomotion.	Bicca Obetine Bicca Obetine Baptista et al. (2020)
	AM141 (unc-54p::Q40::YFP)	Constitutive expression in muscle cells	Age-dependent Q40-YFP aggregation	Body-wall muscle expression limited.	Morley et al. (2002), Vela et al. (2022)
	AM101 (F25B3.3p::Q40::YFP)	Pan-neuronal expression	Neuron degeneration, mild motor defects.	Absence of robust behavioral phenotypes; nerve ring imaging resolution limited.	Brignull et al. (2006), Redweik and Xue (2025)
	AM716 (F25B3.3p::Q67::YFP)	Pan-neuronal expression	Neuronal polyQ67 aggregation, age-dependent loss of motility.	Densely packed neural imaging limitations; high genetic background vulnerability to silencing.	Brignull et al. (2006), Lee et al. (2023)
	AM140 (unc-54p::Q35::YFP)	Constitutive expression in muscle cells	Muscle polyQ35 aggregation, age-dependent motor dysfunction.	Borderline threshold causing high phenotypic variability; body-wall muscle expression limited.	Morley et al. (2002), Wu Y. et al. (2025)
	EAK103 [unc-54p::Htt513(Q128)]	Constitutive expression in muscle cells	Muscle polyQ128 aggregation, motility defect.	Limited to body-wall muscle expression; background confounding pure polyQ pathways.	Lee et al. (2017), Liu et al. (2024)

Notes: This table summarizes the C. elegans models commonly used in the study of AD, PD, ALS, and HD. Aβ_1-42, Amyloid beta1-42; α-syn, Alpha-synuclein; Htt / Htn, Huntingtin; Hsa, Homo sapiens (Human); TDP-43, TAR DNA-binding protein 43; FUS, Fused in sarcoma; Temp, Temperature; YFP, Yellow Fluorescent Protein; GFP, Green Fluorescent Protein; SOD-1, Superoxide dismutase 1; CFP, Cyan Fluorescent Protein; SP, Signal Peptide; WT, Wild Type; dsRED, Discosoma sp. red fluorescent protein; 6-OHDA, 6-Hydroxydopamine; P indicates promoter (e.g., Punc-54 represents the unc-54 promoter); polyQ/Q, Polyglutamine/Glutamine (e.g., Q40 represents a tract of 40 glutamines); UTR, Untranslated region (e.g., 3′UTR).

3.1. Alzheimer’s disease

Alzheimer’s disease represents a chronic, progressive neurological disorder that currently affects over 57 million people worldwide, accounting for 60 to 70% of all dementia cases and generating nearly 10 million novel incident cases annually (World Health Organization, 2025, 3.31). As the disease advances, pathological changes sweep through an array of brain areas, heavily impacting the entorhinal cortex and hippocampus before extending to the prefrontal cortex and the broader limbic network (Anand et al., 2025). The primary pathological signatures of the disease are characterized by the extracellular aggregation of amyloid-beta plaques, alongside the formation of neurofibrillary tangles within neurons (Zheng and Wang, 2025). Neurofibrillary tangles (NFTs) consist primarily of hyperphosphorylated tau. Physiologically, tau promotes tubulin assembly into microtubules and stabilizes these structural filaments (Wang and Mandelkow, 2016). Extracellular plaques comprise aggregated Aβ peptides. Following extracellular accumulation, neurotoxic Aβ oligomers undergo endocytotic uptake. This internalization induces tau phosphorylation and subsequent NFT formation (Alvarez et al., 2022). Mechanistically, aberrant Aβ accumulation likely triggers a pathogenic cascade. It drives abnormal tau phosphorylation and NFT assembly, destabilizing microtubules and obstructing axonal transport to precipitate neuronal dysfunction and death (Hardy and Selkoe, 2002; Mandelkow and Mandelkow, 2012). Both Aβ plaques and NFTs independently provoke reactive oxygen species generation, exacerbating neurotoxic damage (Tiwari et al., 2019; Wu et al., 2023). C. elegans lacks endogenous orthologs for the amyloid precursor protein and its cleavage enzyme, β-secretase. This means that C. elegans cannot produce Aβ naturally. Consequently, the AD model in C. elegans is mainly set up by driving transgenic expression of Amyloid-β transgenes, tau proteins, or both of them (Fang et al., 2019). The precise molecular pathology of AD remains incompletely understood despite decades of research. Accelerated by the aging global population, this disorder has evolved into a severe public health challenge (da Silva et al., 2026).

3.1.1. Amyloid-β models

The initial C. elegans AD model utilized the unc-54 promoter to drive the expression of Aβ peptides containing a secretory signal in body wall muscles, intending to simulate extracellular amyloid deposition. This transgenic nematode exhibited a characteristic paralysis phenotype. It established a highly efficient quantitative model for evaluating Aβ toxicity and screening potential therapeutics (Chen and Zhang, 2022). The endogenous C. elegans amyloid precursor protein homolog (APL-1) lacks the human Aβ sequence. Because the APL-1 protein differs in amino acid sequence from the beta-amyloid peptide region in human APP, it cannot generate beta-amyloid peptides. This trait ensures a clean endogenous background, rendering the nematode an ideal in vivo model to investigate the specific toxicity of human Aβ (Daigle and Li, 1993). Early modeling efforts, hindered by aberrant cleavage of synthetic signal peptides, yielded truncated Aβ_3-42.

Current transgenic C. elegans strains are primarily constructed to specifically express Aβ_1-42 in body wall muscle cells, as this fragment is considered the most toxic Aβ isoform (McColl et al., 2009; Roussos et al., 2023). Inserting an Asp-Ala (DA) sequence at the N-terminus of the human Aβ sequence achieves full-length Aβ_1-42 expression in nematode muscles. This drives the accumulation of soluble oligomers and induces severe progressive paralysis, mirroring classic degenerative phenotypes (McColl et al., 2012). To dissect oligomer formation and its pathogenic consequences, an optogenetic model was developed. This system expresses a fluorescently tagged Aβ protein in vivo that rapidly oligomerizes upon blue light illumination (Timofeeva et al., 2025). RNAi screening in muscle-expression models demonstrated that inhibiting mitochondrial ferritin-1 attenuates mitochondrial reactive oxygen species (ROS) levels. This intervention effectively reduces paralysis rates and extends nematode lifespan (Huang et al., 2018). However, such technological intricacy does not obscure the physiological simplicity of C. elegans, which carries inherent translational drawbacks. AD is a human neurological disorder, yet the most commonly used high-throughput drug screening models in C. elegans express Aβ within the muscles. The mechanisms of drugs screened in the muscles may fundamentally fail to explain synaptic regression or neuronal death. Furthermore, C. elegans lacks endogenous β-secretase and therefore cannot fully simulate the complex proteolytic processing dynamics of amyloid precursor protein inside the human body.

3.1.2. Microtubule-associated protein tau (MAPT)models

The intracellular accumulation of aberrantly phosphorylated Tau and the subsequent formation of NFTs represent a core pathological hallmark of Alzheimer’s disease and other age-related neurodegenerative disorders (Scheltens et al., 2021). Tau is a microtubule-associated protein. It primarily functions to stabilize the microtubule network. In humans, this protein is encoded by the single-copy MAPT gene, which comprises 16 exons and is located on chromosome 17q21 (Pir et al., 2017). As the sole identified Tau homolog in C. elegans, PTL-1 shares high structural conservation with human Tau. This protein is indispensable for maintaining nervous system homeostasis throughout the nematode lifespan and regulating age-associated neurodegeneration (McDermott et al., 1996). Loss of ptl-1 function reduces the number of viable offspring and impairs touch sensitivity; however, normal development remains unaffected. By generating transgenic nematode models expressing human Tau, researchers can accurately recapitulate Tau hyperphosphorylation and conformational pathology in vivo (Pir et al., 2017; Natale et al., 2020). These models are highly effective for identifying genetic modifiers of AD and tauopathies and elucidating the intercellular transmission mechanisms of pathogenic proteins. They also provide a robust screening platform to rapidly isolate drug candidates capable of lowering pathological Tau levels (Sandhof et al., 2025; Carroll et al., 2026). Nevertheless, these systems carry distinct limitations regarding physiological fidelity. Most transgenic strains utilize pan-neuronal promoters to drive human Tau overexpression, which creates non-physiological toxicity artifacts and precipitates acute cellular collapse.

3.2. Parkinson’s disease

Parkinson’s disease ranks as the second most prevalent neurodegenerative disorder worldwide. The disease exhibits a general population prevalence of approximately 0.3%, which escalates to over 3% in individuals aged 80 and older. Excluding rare early-onset cases, it predominantly afflicts the elderly demographic (Ye et al., 2023). Progressive loss of dopaminergic neurons and subsequent motor dysfunction constitute its core clinical features. Clinicians currently face a dual challenge: the absence of reliable biomarkers for early diagnosis and the lack of disease-modifying therapies capable of reversing the disease course. At the cytopathological level, misfolded fibrillar α-synuclein (α-syn) pathologically aggregates within neurons to form Lewy bodies. This intracellular accumulation represents the classic hallmark driving the neurodegenerative process (Redl et al., 2025). A complex pathogenic cascade governs PD onset and progression at deeper molecular dimensions. Oxidative damage triggered by mitochondrial complex I defects, impaired protein degradation pathways, and sustained chronic neuroinflammation intertwine to construct the core pathogenic network of the disease (Chaudhary et al., 2025). α-Synuclein regulates synaptic vesicle assembly, and its encoding gene, SNCA (PARK1/PARK4), was the first identified causative gene for familial PD. Genetic mutations, duplications, or triplications of SNCA directly manifest as autosomal dominant Parkinson’s disease (Cooper and Van Raamsdonk, 2018).

C. elegans retains an evolutionarily conserved neurotransmission system. The nematode synthesizes dopamine through exactly eight dopaminergic neurons. It provides a robust platform for evaluating neurotoxin effects and offers established transgenic strains expressing human α-synuclein. Orthologs of human PD-associated genes—including lrk-1, pink-1, pdr-1, djr-1.1, and catp-6—are present and functionally intact within this model (da Silva et al., 2024). To quantify nematode behavioral phenotypes and screen for therapeutics capable of alleviating PD-like motor dysfunction, researchers developed the machine-learning algorithm CeSnAP (C. elegans Snapshot Analysis Platform). Utilizing this platform, a high-throughput thrashing analysis was conducted on over 17,000 nematodes to evaluate a library of 50 FDA-approved drugs. This large-scale screen successfully identified enasidenib, ethosuximide, metformin, and nitisinone as highly promising candidate therapeutics for late-stage PD intervention (Sohrabi et al., 2021). Recent studies reveal that metformin suppresses the TLR4/MyD88/NF-κB pathway, coupling neuroinflammation attenuation with copper homeostasis regulation—a mechanism distinct from ferroptosis. Metformin reduces intracellular copper accumulation and downregulates cuproptosis-associated proteins (FDX1 and SLC31A1). This alleviates copper-dependent proteotoxic stress, thereby blocking cuproptosis and protecting dopaminergic neurons in PD models (Shang et al., 2025).

However, C. elegans lacks the complex nigrostriatal pathway characteristic of the human brain. Motor impairments such as a reduction in curling or thrashing frequencies can hardly be mapped fully onto human clinical symptoms like resting tremors or bradykinesia. Furthermore, these models present distinct spatiotemporal limitations in simulating disease progression. While models induced by neurotoxins such as 6-OHDA represent acute neurotoxic phenotypes, authentic PD is a progressive, degenerative process spanning decades.

3.3. Amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS), also known as Charcot’s disease or Lou Gehrig’s disease, is a devastating motor neuron disease (MND). Its core pathological feature involves the progressive degeneration and retraction of motor nerve terminals from target muscles, subsequently affecting upper and lower motor neurons that control voluntary musculature within the central nervous system (Kwaśniewska et al., 2026). Clinically, patients present with muscle stiffness and progressive weakness of the limbs and bulbar muscles, inexorably leading to varying degrees of speech, swallowing, and respiratory dysfunction (Katz et al., 2026). Mechanistically, the vast majority of ALS cases are sporadic; only about 10% are familial (fALS). Genomic variations in the superoxide dismutase 1 (SOD1) gene constitute the primary causative factor for fALS, accounting for approximately 20% of these familial cases (O'Neill et al., 2025; Xie et al., 2025). Mutations in the fused in sarcoma (FUS) gene—which encodes an essential DNA- and RNA-binding protein critical for transcription, splicing, transport, and genomic stability—account for approximately 4% of familial instances (Vance et al., 2009; Dormann et al., 2010). Approximately 3% of familial ALS cohorts are characterized by aberrations in TDP-43. This ubiquitous 43 kDa nucleic acid-binding protein serves as a master regulator of transcriptional control, alternative mRNA splicing, and RNA stability (Lagier-Tourenne and Cleveland, 2009).

To comprehensively dissect the intricate pathogenic mechanisms of ALS, researchers have widely utilized transgenic C. elegans models, which are systematically summarized in Table 2. Featuring highly conserved cellular stress and pro-survival pathways, alongside unique advantages for delineating neural activities—such as processing sensory information, integrating motor circuits, and modulating behavioral states—this nematode serves as an exceptional organismal platform for modeling ALS (Prova et al., 2026). Utilizing these models, numerous studies have confirmed that widespread dysregulation across multiple signaling pathways drives disease progression. This encompasses loss-of-function mutations in mitochondria-associated genes, viral-mediated microRNA dysregulation, and pathological cascades involving the inflammatory mediator NF-κB (Källstig et al., 2021; Meijboom and Brown, 2022; Menge et al., 2025). Driven by these progressive mechanistic insights, leveraging C. elegans models to investigate deficits in energy metabolism has burgeoned into a pivotal front-line research direction, which will significantly facilitate the development of novel therapeutic strategies for ALS (Tefera et al., 2021). Nevertheless, C. elegans lacks a complex circulatory system, distinct vascular structures, and mammalian-like organ-to-organ metabolic crosstalk. This inherently limits its capability to fully recapitulate systemic energy redistribution and the multi-tissue metabolic collapse observed in higher mammalian models.

3.4. Huntington’s disease

Huntington’s disease is a progressive neurodegenerative disorder with autosomal dominant inheritance. At the molecular level, pathogenesis is driven by an abnormal CAG trinucleotide repeat expansion (typically ≥35), which generates a cytotoxic polyglutamine (polyQ) tract at the N-terminus of the huntingtin (HTT) protein. The length of this polyQ tract correlates strictly with both the age of onset and overall disease severity. Pathological aggregates accumulate continuously within neuronal somata over decades; because frank neurodegeneration erupts only after crossing a critical pathogenic threshold, patients experience a distinctly prolonged preclinical phase (El Din and Thabit, 2024; Scahill et al., 2025). During this protracted disease course, non-motor symptoms such as insomnia, sleep fragmentation, and circadian rhythm disruptions are highly prevalent. Clinical studies confirm that patients frequently exhibit significantly reduced nocturnal melatonin levels alongside delayed secretion peaks (Gu et al., 2026). To model these pathological features, transgenic C. elegans strains have been widely utilized, wherein polyQ tracts are typically expressed specifically within sensory neurons. These nematode models successfully recapitulate core disease features, including progressive protein aggregation and neurodegeneration. Through these in vivo systems, researchers have identified multiple conserved neuroprotective mechanisms; these defense systems primarily involve proteostasis networks, encompassing molecular chaperones, autophagic components, and the insulin/IGF-1 signaling pathway (Xu et al., 2025). However, although these nematode models provide essential insights for identifying novel drug targets, they possess a critical limitation: C. elegans lacks an endogenous HTT ortholog. Furthermore, pronounced mechanistic discrepancies exist across diverse animal species. Future efforts must prioritize the generation of animal models expressing full-length mutant HTT and mandate rigorous cross-species validation, which is imperative to bridge the translational gap between basic discovery and clinical application (Sandhof et al., 2020). Methodologically, while restricting polyQ expression to localized tissues facilitates high-throughput scoring, it might obscure complex, network-wide pathogenic cascades. Furthermore, relying on isolated short fragments rather than the full-length HTT macromolecule could potentially simplify aggregation kinetics and alter cytotoxicity profiles. Consequently, phenotypic rescues in these simplified platforms may not fully mirror therapeutic efficacy in higher organisms, highlighting the need for cautious extrapolation of drug-screening data. The schematic illustration of the transgenic expression strategies across these distinct disease models is presented in Figure 2.

Figure 2.

Simplified anatomical schematic of C. elegans. Schematic diagram of C. elegans anatomy illustrating the specific tissue distribution of transgenic expression in the discussed disease models. The targeted sites are categorized into two primary physiological systems, which are further classified by four distinct neurodegenerative disorders. The nervous system is highlighted in green, whereas the muscular system is depicted in gray.

4. Translational applications and frontier technology prospects of C. elegans

4.1. Optimization of screening models

Historically, traditional drug screening models have long struggled to reconcile high throughput with physiological relevance. However, propelled by automated sorting and microfluidic technologies, the C. elegans model has successfully bridged this gap. Emerging platforms—encompassing microfluidic, non-microfluidic, and optofluidic imaging—are advancing rapidly, shifting the field toward a combination of high throughput and single-organism resolution while steadily accelerating imaging speeds (Mahbub et al., 2025). Traditional solid-media nematode culture presents distinct bottlenecks during large-scale applications. The preparation of extensive agar plates prepared with varying drug batches is both labor-intensive and cost-prohibitive, which further complicates the precise control of drug concentrations. Researchers developed fully automated liquid screening workflows compatible with standard 96- to 384-well microplates, resolving previous constraints regarding dosing precision and operational scale (Au - Gao et al., 2019; O'Brien et al., 2025). Because liquid culture systems seamlessly integrate with automated liquid handling robotics, a 384-well plate can be partitioned within minutes. This capacity easily elevates the weekly screening capacity to over 10,000 compounds, enhancing throughput by several orders of magnitude (Mahbub et al., 2025). The advent of microfluidic technology refines the assessment of complex nematode behaviors, overcoming the limitations of traditional microplate assays that struggle to evaluate intricate phenotypes such as chemotaxis, learning, and memory. By executing precise, dynamic control over fluidic and physical environments at the micrometer scale, this technology achieves profound standardization and reproducibility (Pan et al., 2021).

4.2. Environmental toxicity assessment

Environmental pollution has become increasingly severe, causing nine million deaths globally each year (Fuller et al., 2022). C. elegans exhibits high sensitivity to environmental pollutants, including heavy metals, pesticides, and nanomaterials. These substances disrupt neurodevelopment, induce oxidative stress, and impair synaptic function, resulting in abnormal motor, learning, and sensory behaviors in the nematode (Taylor et al., 2025; Wu J. et al., 2025). Consequently, C. elegans is increasingly utilized as a biological sensor to evaluate the neurotoxicity of environmental pollutants, serving as an early warning system for environmental safety and public health (Lemmon et al., 2025). Because heavy metals resist degradation and exhibit significant bioaccumulation, they remain a primary focus of environmental toxicology. Cadmium, a highly toxic heavy metal pollutant, enters the human body through multiple routes, including the consumption of contaminated food and water, or the inhalation of cadmium-containing particles from cigarette smoke and industrial emissions (Arruebarrena et al., 2023). Upon cadmium exposure, C. elegans undergoes transcriptomic reprogramming. During this process, expression levels of the heat shock protein gene hsp-16.2 and metallothionein genes (mtl-1 and mtl-2) increase significantly (Cui et al., 2007; Hall et al., 2012; Liu H. et al., 2025). Recent studies identified a novel cadmium-responsive gene, T08G5.1, which is dramatically upregulated following exposure. Under identical cadmium exposure conditions, L3 larvae exhibited more extensive transcriptomic reprogramming than L4 larvae. This indicates a heightened transcriptional sensitivity to cadmium pollution during early developmental stages (Almutairi et al., 2024).

4.3. Applications of omics technologies

High-throughput sequencing technologies are advancing rapidly. Transcriptomic studies in C. elegans have transitioned from traditional bulk RNA-seq to a new era of multidimensional single-cell and spatial profiling. Bulk RNA-seq frequently masks transcriptional heterogeneity among individual cells (Ma and Zheng, 2023). By resolving gene expression patterns at single-cell resolution, single-cell RNA sequencing (scRNA-seq) facilitates the construction of high-precision, whole-organism cellular atlases. Cao, Packer, and colleagues demonstrated that scRNA-seq achieves accurate identification of diverse cell types across the nematode. Using pseudotime analysis, they successfully reconstructed complex cellular developmental trajectories (Cao et al., 2017; Packer et al., 2019). Because scRNA-seq requires tissue dissociation, it inevitably strips away cellular spatial coordinates and microenvironmental context. Spatial transcriptomics effectively bridges this technical gap. By integrating high-resolution in situ imaging techniques like multiplexed error-robust fluorescence in situ hybridization (MERFISH), researchers can directly map gene expression profiles while preserving the intact anatomical architecture of the nematode (He et al., 2022). The deep integration of single-cell and spatial omics technologies yields a panoramic molecular map essential for deciphering complex physiological mechanisms. Figure 3 outlines the future research directions for C. elegans.

Figure 3.

The application prospects of C. elegans in neuroscience. Clinical practice with three possible directions for future development as follows: from drug screening to environmental toxicology assessment, as well as the application of omics technology.

5. Conclusion

In the fundamental study of molecular biology and brain science, C. elegans serves as a uniquely powerful model organism. Despite its established status in fundamental neurobiology, the nematode also presents significant limitations for clinical translation. Electrophysiologically, the organism relies primarily on graded potentials rather than classical action potentials for signal transduction. Pharmacokinetically, its highly impermeable cuticle forms a formidable physical barrier that restricts the delivery of many neuroprotective compounds. Lacking a complex circulatory system and a definitive blood–brain barrier, this model frequently generates false-negative results during in vivo drug screening. Finally, behavioral assessments face an inherent ceiling imposed by its extremely streamlined nervous system. While altered locomotion or shortened lifespan adequately reflects baseline neurotoxicity, these metrics fail to authentically recapitulate the complex cognitive decline, memory loss, and higher-order emotional disturbances characteristic of human neurodegenerative diseases.

Funding Statement

The author(s) declared that financial support was received for this work and/or its publication. This review was supported by grants from the National Natural Science Foundation of China (82271514).

Author contributions

ZP: Writing – original draft, Writing – review & editing. YS: Data curation, Writing – review & editing. DP: Data curation, Writing – review & editing. LT: Data curation, Writing – review & editing. TR: Data curation, Writing – review & editing. YL: Data curation, Writing – review & editing. XZ: Conceptualization, Writing – review & editing. HL: Software, Funding acquisition, Writing – review & editing, Supervision, Formal analysis.

Conflict of interest

The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The author(s) declared that Generative AI was used in the creation of this manuscript. The authors employed Gemini 3.0 Pro solely as a supportive tool for language polishing and grammatical verification during the writing process. All AI-generated suggestions were thoroughly vetted and edited by the authors to ensure scientific precision. The authors assume complete responsibility for the entire work, including the parts processed by the AI system.

Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.