AOP ID and Title:

Short Title: ROS leading to growth inhibition via LPO and cell death

Authors

You Song, Li Xie, Knut Erik Tollefsen

Norwegian Institute for Water Research (NIVA), Sognsveien 72, 0855, Oslo, Norway

Status

Coaches

• Shihori Tanabe

Abstract

This adverse outcome pathway (AOP 331) describes a linear route by which increased reactive oxygen species (ROS) can lead to decreased organismal growth through lipid peroxidation-mediated mitochondrial bioenergetic impairment and increased cell injury/death. In this AOP, increased ROS is treated operationally as the molecular initiating event because it represents the earliest common measurable redox perturbation shared by many chemical and non-chemical stressors within the broader ROS-growth AOP network. Increased ROS leads to oxidative stress, which promotes lipid peroxidation. Oxidative damage to membrane lipids can impair mitochondrial membrane integrity and coupling of oxidative phosphorylation (OXPHOS). Decreased OXPHOS coupling reduces ATP production, and insufficient ATP availability can compromise membrane homeostasis, ion transport, biosynthesis, stress-response capacity, and execution of regulated cell death pathways, ultimately resulting in increased cell injury/death. Increased loss of viable cells, particularly in developing, growing, or regenerating tissues and organisms, can contribute to decreased growth.

AOP 331 reuses and connects established AOP-Wiki components from several AOP contexts. The upstream ROS and oxidative stress segment is associated with AOP 478, in which deposition of energy leads to oxidative stress through increased free radical generation (AOP-Wiki, 2026a). The lipid peroxidation and mitochondrial bioenergetic segment is connected to the oxidative stress and mitochondrial impairment logic represented in the broader ROS-growth AOP network, while the KER from decreased coupling of OXPHOS to decreased ATP pool is directly associated with AOP 263, an OECD-published AOP that causally links uncoupling of OXPHOS to growth inhibition through ATP depletion and decreased cell proliferation (AOP-Wiki, 2026b; OECD, 2022; Song and Villeneuve, 2021). AOP 331 differs from AOP 326 by routing ATP depletion through increased cell injury/death rather than decreased cell proliferation. This terminal cellular injury module is supported by reuse of the broadly shared AOP-Wiki KE 'Increase, Cell injury/death' and by its occurrence in several AOPs, including AOPs 12, 13, 17, 38, and 48, where cell injury/death is used as an intermediate or downstream KE in neurotoxicity, oxidative stress, fibrosis, and excitotoxicity contexts (AOP-Wiki, 2026c-g). The AOP is relevant to environmental and human health contexts because ROS production, lipid peroxidation, mitochondrial ATP production, cell viability, and growth are conserved biological processes. It can support mechanistic interpretation of oxidative stress-mediated growth impairment, assay selection, chemical prioritization, integrated approaches to testing and assessment (IATA), and quantitative AOP development for oxidative and mitochondrial toxicity.

 

Acknowledgement

This project was funded by the Research Council of Norway (RCN), grant no. RCN-315929 “EXPECT: In silico and experimental screening platform for characterizing environmental impact of industry development in the Arctic” (https://www.niva.no/en/projects/expect), the European Partnership for the Assessment of Risks from Chemicals (PARC) through European Union’s Horizon Europe research and innovation programme (Grant Agreement No 101057014, and supported by the NIVA Computational Toxicology Program, NCTP (https://www.niva.no/en/featured-pages/nctp, grant. No. RCN-342628).

 

AI disclosure

Artificial intelligence (AI) tools were used to support literature prioritization, review and AOP-Wiki page preparation in this work. AOP-helpFinder was used for automated literature mining, and ChatGPT (OpenAI) was used as an auxiliary tool for title and abstract screening, extraction of study metadata, and identification of potential weight-of-evidence indicators. AI-assisted outputs were used only to organize and prioritize information and were verified against the original sources by the authors before inclusion. Additional AI assistance was used for formatting, copy-editing, citation cross-checking, and harmonization of the AOP-Wiki pages. All scientific interpretations, weight-of-evidence judgments, final wording, and conclusions were determined and approved by the authors, who take full responsibility for the content and integrity of the work.

Context

ROS are continuously formed during aerobic metabolism and can also be generated in response to environmental stressors. At controlled levels, ROS participate in redox signaling, whereas excessive ROS can disturb redox homeostasis and initiate oxidative stress (Schieber and Chandel, 2014; Sies et al., 2017). Lipid membranes are important targets of oxidative attack because phospholipids containing polyunsaturated fatty acids can undergo radical-driven peroxidation. Lipid peroxidation generates lipid hydroperoxides and secondary reactive aldehydes, including malondialdehyde and 4-hydroxy-2-nonenal, which can propagate oxidative injury and alter membrane-associated protein and organelle function (Ayala et al., 2014).

    AOP 331 was developed to represent the lipid peroxidation and cell injury/death-driven linear route within the broader ROS-growth AOP network. This route was selected because lipid peroxidation is a well-established consequence of oxidative stress and because mitochondrial membranes are central determinants of OXPHOS coupling. Peroxidative modification of mitochondrial membrane lipids can alter membrane fluidity, proton leak, respiratory control, and mitochondrial membrane potential, providing a mechanistically coherent bridge from oxidative stress to impaired ATP production (Murphy, 2009; Nicholls and Ferguson, 2013; Ouillon et al., 2021). ATP depletion is a well-established contributor to loss of cell viability because cellular survival depends on ATP-dependent ion gradients, membrane repair, protein turnover, stress-response pathways, and the execution of regulated death processes. Depletion of ATP can shift cells from adaptive responses to injury and death, and severe ATP loss can affect the mode of cell death (Leist et al., 1997; Bonora et al., 2012).

The AOP was also developed to take advantage of existing AOP-Wiki modularity. The upstream oxidative stress context is associated with AOP 478, while the OXPHOS-to-ATP KER is associated with AOP 263 (AOP-Wiki, 2026a,b; OECD, 2022). The cell injury/death KE is a highly reusable AOP-Wiki KE and appears across several established AOPs. AOP 17 explicitly includes oxidative stress leading to cell injury/death and also includes several KERs involving cell injury/death and neuroinflammation (AOP-Wiki, 2026e). AOP 48 includes mitochondrial dysfunction leading to cell injury/death in an excitotoxicity context (AOP-Wiki, 2026g). AOP 38 uses cell injury and cell death as key early tissue-level consequences of protein alkylation leading to fibrosis (AOP-Wiki, 2026f). AOPs 12 and 13 also use cell injury/death in neurodegeneration and synaptogenesis-related contexts (AOP-Wiki, 2026c,d).  These associations support the reuse of Event 55 as a generic, modular cellular KE downstream of multiple upstream stressors and upstream of multiple adverse outcomes.

Strategy

AOP 331 was developed using the principles described in OECD AOP guidance, including modular description of KEs and KERs, reuse of existing AOP-Wiki content where appropriate, evidence evaluation using biological plausibility, empirical support, essentiality, and quantitative understanding, and clear description of the biological domain of applicability (OECD, 2018, 2021). The aim was to assemble a focused linear pathway from reusable AOP-Wiki elements rather than to create an isolated de novo pathway. This is important because AOP 331 is one branch of the broader ROS-growth AOP network and because its KEs overlap with oxidative stress, mitochondrial dysfunction, cellular energy metabolism, cell injury/death, and growth-related AOPs.

    Reuse of existing AOP-Wiki content was considered at the outset. AOP 478 was reviewed because it provides an AOP-Wiki precedent for oxidative stress as a central KE downstream of free radical generation and energy deposition. AOP 263 was reviewed because it provides an OECD-published downstream bioenergetics module in which decreased coupling of OXPHOS leads to decreased ATP pool and subsequently growth inhibition, although in AOP 263 the terminal cellular route proceeds through decreased cell proliferation rather than cell injury/death. AOPs 12, 13, 17, 38, and 48 were reviewed because they demonstrate repeated reuse of Event 55, 'Increase, Cell injury/death', across different biological contexts and provide support for treating cell injury/death as a modular KE that can connect distinct upstream mechanisms to downstream tissue or organism-level outcomes. AOP 296 was reviewed during development of the broader ROS-growth network to ensure that oxidative stress and macromolecular damage modules were harmonized with existing oxidative damage content, although AOP 331 specifically follows the lipid peroxidation and bioenergetic injury branch rather than the oxidative DNA damage branch.

    The evidence base was assembled through an AI-human hybrid workflow. First, search terms were developed for each KE, including KE names, synonyms, endpoint names, assay terms, taxa, and representative stressors. AOP-helpFinder was used to search PubMed for co-occurrence between key events and related biological concepts, and the exported outputs included PMIDs, titles, abstracts, and matched KE terms (Carvaillo et al., 2019; Jornod et al., 2022). The exported records were subjected to overlap analysis to remove redundant hits and to filter taxa-related or clearly irrelevant literature.

    Second, ChatGPT (OpenAI, San Francisco, CA, USA)-assisted screening was used as an auxiliary prioritization step. The LLM was used to pre-screen titles and abstracts, extract study metadata including stressor, species, biological system, dose or concentration, and exposure time, identify evidence types such as biological plausibility, empirical support, and essentiality, and flag weight-of-evidence indicators such as dose-response concordance, temporal concordance, incidence concordance, and intervention evidence. The LLM output was used to classify studies as high relevance, medium relevance, or low/not relevant. High-relevance studies were retrieved for full-text review, medium-relevance studies were reserved as supporting evidence, and low-relevance studies were documented as low priority or excluded.

    Third, full-text review and expert curation were used to verify all evidence before inclusion in the AOP. LLM-assisted full-text review was used only to organize candidate evidence; all extracted information was checked manually against the original text. Expert review was then used to populate KER evidence tables with methods, endpoints, results, weight-of-evidence category, and references. Final weight-of-evidence evaluation was performed by expert judgment using biological plausibility, empirical support, essentiality, quantitative understanding, and identification of evidence gaps. Thus, the development process combined text-mining and AI-assisted evidence handling with human expert verification and final decision-making.

    In parallel with this workflow, targeted searches were conducted to fill specific evidence gaps for ROS, oxidative stress, lipid peroxidation, mitochondrial membrane potential, OXPHOS coupling, ATP depletion, cytotoxicity, cell death, and growth inhibition. Studies were prioritized when they measured two or more KEs in the same biological system, reported dose or concentration and exposure time, or provided evidence relevant to dose-response, temporal, or incidence concordance. Mechanistic reviews and OECD reports were used primarily to support biological plausibility, while primary experimental studies were used to support empirical concordance wherever possible.

Summary of the AOP

Events

Molecular Initiating Events (MIE), Key Events (KE), Adverse Outcomes (AO)

Key Event Relationships

Stressors

Overall Assessment of the AOP

The overall weight of evidence supporting AOP 331 is considered moderate. Biological plausibility is high for all six KERs in the pathway. The upstream oxidative stress, lipid peroxidation, and OXPHOS uncoupling sequence follows a well-established mechanistic logic, and the connection from ATP depletion to cell injury/death is supported by the fundamental dependence of cellular survival on adequate energy supply. The cell injury/death-to-growth relationship is reinforced by the broad reuse of Event 55 (Increase, Cell injury/death) as a modular KE across endorsed AOPs 12, 13, 17, 38, and 48 (AOP-Wiki, 2026a-e). The OXPHOS-to-ATP module is directly associated with OECD-endorsed AOP 263 and contributes high biological plausibility and strong quantitative understanding for this segment (OECD, 2022; Song and Villeneuve, 2021). Empirical support is high for the ROS-to-oxidative-stress and oxidative-stress-to-lipid-peroxidation relationships, moderate for the lipid-peroxidation-to-OXPHOS link, and moderate to high for the ATP-depletion-to-cell-death and OXPHOS-to-ATP relationships. The cell death-to-growth relationship has moderate empirical support, as direct concurrent measurement of cell injury/death and organismal growth is less common across the available literature. Essentiality is rated moderate to high overall, with the strongest direct evidence for the AOP 263 bioenergetics segment. Quantitative understanding is highest for the OXPHOS-to-ATP KER and low to moderate elsewhere. The main uncertainties are the quantitative thresholds governing the lipid-peroxidation-to-OXPHOS transition, the severity-dependent mode of cell death triggered by ATP depletion, and the extent to which cell injury/death versus reduced proliferation drives growth impairment in specific biological contexts. AOP 331 is most appropriate for mechanistic interpretation of cytotoxic growth impairment caused by oxidative lipid damage, IATA development, and chemical prioritisation (OECD, 2018; Becker et al., 2015).

Domain of Applicability

Life Stage Applicability Taxonomic Applicability Sex Applicability

The domain of applicability for AOP 331 is broad across aerobic eukaryotic organisms in which ROS generation, oxidative stress responses, lipid peroxidation, mitochondrial oxidative phosphorylation, ATP-dependent homeostasis, cell injury/death, and growth are biologically relevant. The AOP is most applicable to taxa and life stages in which growth depends strongly on maintenance of viable cell number, tissue condition, and mitochondrial energy supply. This includes algae, aquatic invertebrates, fish embryos and juveniles, mollusks, and mammalian or human cell systems.

The stressor domain includes direct ROS generators, redox-cycling chemicals, metals, nanoparticles, mitochondrial toxicants, hypoxia-reoxygenation, and radiation. Because the MIE is defined operationally as increased ROS rather than as a chemical-specific molecular interaction, AOP 331 should be applied to stressors for which evidence supports increased ROS or oxidative stress and downstream concordance with lipid peroxidation, mitochondrial impairment, ATP depletion, cell injury/death, and decreased growth. Environmental factors such as oxygen availability, temperature, lipid composition, diet, nutrient status, and antioxidant capacity may modulate the pathway.

Essentiality of the Key Events

Essentiality is evaluated for the overall AOP based on whether preventing or modifying upstream KEs changes downstream KEs or the AO. Direct essentiality evidence is strongest for the OXPHOS to ATP relationship and for ATP dependence of cell viability. Essentiality for lipid peroxidation is biologically plausible and supported by intervention and association studies, but direct experiments showing that blocking lipid peroxidation prevents all downstream events are less common.

 

Key event	Essentiality	Rationale	Experimental manipulation evidence (KE knock-out / inhibition / rescue)	Uncertainties
Event 1115: Reactive oxygen species, increased	Moderate	ROS scavenging and antioxidant interventions frequently attenuate oxidative stress and downstream lipid peroxidation in oxidative stress models (Schieber and Chandel, 2014; Sies et al., 2017).	Indirect (stop/attenuation): antioxidant and ROS-scavenger pre-treatment reduces oxidative stress and downstream damage across oxidative-stress models (Schieber and Chandel, 2014; Sies et al., 2017). No selective single-source ROS knock-out is available.	ROS also participate in normal signaling; increased ROS does not always progress to adversity if compensation occurs.
Event 1392: Oxidative stress, increased	Moderate to high	Oxidative stress is required for lipid peroxidation when oxidant production exceeds antioxidant buffering. AOP 478 and AOP 17 support oxidative stress as a central KE downstream of free radical generation or decreased protection against oxidative stress (AOP-Wiki, 2026a,e).	Indirect: modulation of antioxidant capacity alters progression to oxidative macromolecular damage; oxidative stress is the curated hub KE in endorsed AOP 478 (AOP-Wiki, 2026a; Carrothers et al., 2025).	Oxidative stress is measured using several indirect biomarkers that may not be equivalent across systems.
Event 1445: Lipid peroxidation, increased	Moderate	Lipid peroxidation can alter membrane properties and generate reactive aldehydes that affect mitochondrial function (Ayala et al., 2014). Dietary PUFA studies in Daphnia show higher lipid peroxidation with lower mitochondrial membrane potential (Moore et al., 2023).	Indirect: antioxidant intervention attenuates lipid peroxidation in oxidative-stress models; direct block-and-rescue isolating LPO from other oxidative damage is uncommon (Murphy, 2009; Ouillon et al., 2021).	Direct blocking experiments are limited; lipid peroxidation may be both a cause and consequence of mitochondrial dysfunction.
Event 1446: Coupling of OXPHOS, decreased	High	The KER from decreased OXPHOS coupling to ATP depletion is associated with AOP 263, where restoration or removal of uncoupling supports a causal role for impaired coupling in ATP depletion (AOP-Wiki, 2026b; OECD, 2022; Song and Villeneuve, 2021).	Direct (rescue): removal of uncouplers or restoration of coupling recovers mitochondrial membrane potential and ATP in the endorsed AOP 263 module (AOP-Wiki, 2026b; OECD, 2022; Song and Villeneuve, 2021).	Mild uncoupling can sometimes reduce ROS generation and may be adaptive; severity and duration determine adversity.
Event 1771: ATP pool, decreased	High	ATP is required for maintenance of ion gradients, membrane repair, cellular stress responses, and execution of regulated cell death pathways. Severe ATP depletion is a well-established determinant of cell injury/death mode and severity (Leist et al., 1997; Bonora et al., 2012).	Indirect: ATP-restoration experiments reduce downstream injury/proliferation deficits; central KE in endorsed AOP 263 (Leist et al., 1997; Nicotera et al., 1998; OECD, 2022).	Compensatory glycolysis can buffer ATP depletion; total ATP may reflect changing cell number in some assays.
Event 55: Cell injury/death, increased	Moderate	Cell injury/death is a shared AOP-Wiki KE used in AOPs 12, 13, 17, 38, and 48. Loss of viable cells provides a plausible and broadly supported mechanism for reduced tissue or organismal growth (AOP-Wiki, 2026c-g).	Indirect: ATP restoration/maintenance reduces injury in some systems, indicating energy-status dependence (Leist et al., 1997; Nicotera et al., 1998); widely reused modular KE (AOPs 12, 13, 17, 38, 48).	Growth can also decrease through reduced proliferation, altered cell size, endocrine disruption, or energy allocation without overt cell death.
Event 1521: Growth, decreased (AO)	Not applicable (AO)	Growth is the adverse outcome and is regulatory relevant across algae, aquatic invertebrate, fish, amphibian, and plant test systems. AOP 263 provides precedent for using decreased growth as an AO in a mitochondrial bioenergetics AOP (OECD, 2022; Song and Villeneuve, 2021).	As the adverse outcome, essentiality is assessed for upstream KEs; AOP 263 provides precedent for decreased growth as an AO downstream of these modules (OECD, 2022; Song and Villeneuve, 2021).	Growth is integrative and can arise through multiple interacting mechanisms.

 

Weight of Evidence Summary

Evidence assessment is organized by KER. Calls follow OECD weight-of-evidence considerations for biological plausibility, empirical support, and quantitative understanding (OECD, 2018, 2021).

 

Biological plausibility of KERs

KER	Biological plausibility call	Rationale
Relationship 2009: ROS increase leads to oxidative stress increase	High	Oxidative stress reflects an imbalance between oxidant production and antioxidant capacity, and ROS are primary oxidant species in cellular redox biology (Schieber and Chandel, 2014; Sies et al., 2017). AOP 478 supports oxidative stress downstream of free radical generation (AOP-Wiki, 2026a).
Relationship 3116: oxidative stress increase leads to lipid peroxidation increase	High	ROS can initiate peroxidation of polyunsaturated fatty acids in membranes, generating lipid hydroperoxides and reactive aldehydes such as MDA and 4-HNE (Ayala et al., 2014; Sies et al., 2017).
Relationship 1599: lipid peroxidation increase leads to decreased coupling of OXPHOS	High	Mitochondrial coupling depends on inner mitochondrial membrane integrity. Lipid peroxidation can disrupt membrane properties, promote proton leak, alter membrane potential, and impair respiratory control (Murphy, 2009; Nicholls and Ferguson, 2013; Ouillon et al., 2021).
Relationship 2203: decreased coupling of OXPHOS leads to decreased ATP pool	High	This relationship is associated with AOP 263. OXPHOS coupling is a major determinant of ATP production in aerobic eukaryotic cells; reduced coupling lowers ATP synthesis efficiency (AOP-Wiki, 2026b; OECD, 2022; Song and Villeneuve, 2021).
Relationship 2768: decreased ATP pool leads to increased cell injury/death	High	ATP is required for survival, ion homeostasis, membrane repair, and regulated death processes. Severe ATP depletion can switch cellular outcomes toward necrosis or irreversible injury, while less severe depletion may permit apoptosis (Leist et al., 1997; Bonora et al., 2012).
Relationship 2767: increased cell injury/death leads to decreased growth	High	Growth depends on viable cell number, tissue integrity, and biomass accumulation. Increased cell death or injury reduces the cellular basis for growth and can impair tissue or organismal development (Conlon and Raff, 1999). Cell injury/death is reused across AOPs 12, 13, 17, 38, and 48 (AOP-Wiki, 2026c-g).

 

Empirical support for KERs

KER	Empirical support call	Rationale	Inconsistencies or evidence gaps
Relationship 2009: ROS increase leads to oxidative stress increase	High	Paraquat increased ROS and antioxidant enzyme responses in Chlorella vulgaris (Qian et al., 2009), and paraquat induced oxidative stress responses in Daphnia magna (Barata et al., 2005). AOP 478 reports extensive evidence linking free radical generation/energy deposition to oxidative stress (AOP-Wiki, 2026a).	ROS is often transient and measured indirectly; oxidative stress biomarkers vary across assays and taxa.
Relationship 3116: oxidative stress increase leads to lipid peroxidation increase	High	Copper increased antioxidant enzyme activity and MDA/TBARS in freshwater green microalgae (Knauert and Knauer, 2008). Paraquat induced lipid peroxidation in algae and Daphnia (Barata et al., 2005; Esperanza et al., 2015; Qian et al., 2009). Gamma radiation in Lemna minor induced a sequential oxidative stress to lipid peroxidation response upstream of mitochondrial membrane potential loss and cell death (Xie et al., 2019; Xie et al., 2022).	MDA/TBARS endpoints can lack specificity; lipid peroxidation and antioxidant responses may have different time courses.
Relationship 1599: lipid peroxidation increase leads to decreased coupling of OXPHOS	Moderate	Dietary PUFA manipulation in Daphnia showed higher lipid peroxidation associated with lower mitochondrial membrane potential (Moore et al., 2023). Cyclic hypoxia in Mya arenaria increased proton leak and reduced OXPHOS coupling efficiency, consistent with oxidative membrane damage effects on mitochondrial coupling (Ouillon et al., 2021). In Lemna minor, lipid peroxidation preceded mitochondrial membrane potential reduction under gamma radiation and 3,5-dichlorophenol exposure, supporting this link in an aquatic primary producer (Xie et al., 2018; Xie et al., 2019).	Direct studies measuring lipid peroxidation and OXPHOS coupling in the same exposure series are limited; mitochondrial dysfunction can also drive lipid peroxidation.
Relationship 2203: decreased coupling of OXPHOS leads to decreased ATP pool	High	AOP 263 reports strong evidence for this KER (AOP-Wiki, 2026b; OECD, 2022; Song and Villeneuve, 2021). Cadmium exposure in oysters reduced state 3 respiration and affected mitochondrial bioenergetics (Sokolova et al., 2005).	Compensatory glycolysis and altered metabolic demand can obscure total ATP changes.
Relationship 2768: decreased ATP pool leads to increased cell injury/death	Moderate to high	ATP depletion and cell death are linked in multiple cell systems. Intracellular ATP concentration influences the decision between apoptosis and necrosis (Leist et al., 1997). Calcium electroporation caused dose-dependent ATP depletion and cancer cell death (Hansen et al., 2015).	ATP assays may reflect both energy state and cell number; direct temporal separation of ATP depletion from cell death is needed.
Relationship 2767: increased cell injury/death leads to decreased growth	Moderate	In Daphnia, toxicant-induced physiological energy disruption and cell/tissue injury are associated with growth reduction (Knops et al., 2001). In bivalves, cadmium and temperature interactions caused cellular energy disruption, mortality, and reduced condition/growth-related outcomes (Cherkasov et al., 2006). Methanol-exposed mouse embryos showed growth reduction and elevated cell death (Abbott et al., 1995).	Growth can be reduced by mechanisms other than cell death; direct dose/time concordance between cell death and growth is not always measured.

Inconsistencies and uncertainties

The main uncertainty for AOP 331 is the quantitative strength and directionality of the lipid peroxidation to OXPHOS coupling relationship. Lipid peroxidation can impair mitochondrial membranes, but mitochondrial dysfunction can also enhance ROS generation and thereby increase lipid peroxidation. AOP 331 represents one biologically plausible and empirically supported direction within a broader feedback-prone network. Another uncertainty is that ATP depletion can lead to different cellular outcomes depending on severity and duration; moderate depletion may reduce proliferation or activate adaptive stress responses, whereas severe depletion promotes cell injury/death. Finally, growth is a multifactorial endpoint. Increased cell injury/death is an important contributor to impaired growth, but decreased growth can also arise through reduced proliferation, altered cell size, altered energy allocation, endocrine signaling, or developmental delay without overt cell death.

Quantitative Consideration

Quantitative understanding varies across the AOP. The relationship between OXPHOS coupling and ATP production has the strongest quantitative foundation, while the relationships linking oxidative stress to lipid peroxidation and cell injury/death to organismal growth are more often qualitative or semi-quantitative.

 

KER	Quantitative understanding call	Rationale
2009: ROS increase to oxidative stress increase	Low to moderate	ROS measurements are reactive, transient, and assay-dependent. Quantitative relationships can be defined within a specific assay, but generalizable prediction across taxa and stressors remains limited (Sies et al., 2017).
3116: oxidative stress increase to lipid peroxidation increase	Low to moderate	Dose-response relationships are reported for oxidative stress markers and lipid peroxidation, but lipid composition and assay differences strongly affect response magnitude (Ayala et al., 2014; Knauert and Knauer, 2008).
1599: lipid peroxidation increase to decreased OXPHOS coupling	Low to moderate	Quantitative associations exist between lipid peroxidation and mitochondrial membrane potential or coupling efficiency, but broadly generalizable models are not established (Moore et al., 2023; Ouillon et al., 2021).
2203: decreased OXPHOS coupling to decreased ATP pool	High	AOP 263 reports strong quantitative understanding, supported by bioenergetic theory and models linking mitochondrial coupling and ATP production (AOP-Wiki, 2026b; OECD, 2022; Song and Villeneuve, 2021).
2768: decreased ATP pool to increased cell injury/death	Moderate	ATP thresholds influence the type and severity of cell death, and quantitative relationships are reported in defined systems, but thresholds vary by cell type and exposure condition (Leist et al., 1997; Hansen et al., 2015).
2767: increased cell injury/death to decreased growth	Low to moderate	Quantitative linkage between cell loss and organismal growth is plausible and can be modeled in defined systems, but empirical cross-taxa response-response relationships remain limited (Conlon and Raff, 1999).

 

BMD/POD-anchored concordance

The following benchmark-dose/point-of-departure (BMD/POD) concordance table anchors AOP 331 to quantitative cross-KE ordering, in line with Handbook section 4C. The multiomics point-of-departure (moPOD) dataset for gamma-irradiated Daphnia magna (Song et al., 2023) provides POD magnitudes for increased ROS, decreased ATP, decreased OXPHOS coupling, and cell death, demonstrating the expected upstream-to-downstream POD ordering (more sensitive PODs upstream). The moPOD is presented as POD magnitude evidence, not as a causal re-ordering of KEs. The Lemna minor EDR50 range provides a whole-pathway apical anchor in an aquatic primary producer.

 

Key event (functional category)	POD metric	POD value (mGy/h)	POD ordering	Source
KE 1115: ROS, increased (mROS)	moPOD (multiomics POD)	0.4	1 (most sensitive)	Song et al., 2023
KE 1771: ATP pool, decreased	moPOD	2.5	2	Song et al., 2023
KE 1446: OXPHOS coupling, decreased (UPS/OXPHOS module)	moPOD	42.3	3	Song et al., 2023
KE 55: Cell injury/death (apoptosis)	moPOD	42.3	3 (least sensitive)	Song et al., 2023
Upstream KE chain → growth (Lemna minor, gamma)	EDR50 (growth)	31.5–54.8 (mGy/h)	whole-pathway apical	Xie et al., 2018, 2019, 2022

 

Considerations for Potential Applications of the AOP (optional)

AOP 331 can support mechanistic interpretation of growth impairment caused by oxidative stressors that induce lipid peroxidation, mitochondrial bioenergetic dysfunction, ATP depletion, and cell injury/death. The AOP is particularly relevant for hazard identification and chemical prioritization when evidence indicates increased ROS or oxidative stress together with lipid peroxidation, mitochondrial membrane potential changes, reduced respiratory control, ATP depletion, cytotoxicity, or growth inhibition. The AOP may also support IATA development by linking upstream NAM endpoints, such as ROS assays, lipid peroxidation markers, mitochondrial membrane potential, oxygen consumption rate, ATP content, cytotoxicity assays, and organismal growth measurements.

AOP 331 can support chemical grouping and read-across for stressors that share evidence of oxidative lipid damage, mitochondrial bioenergetic impairment, and ATP-associated cell injury. Because oxidative stress and lipid peroxidation are not chemical-specific, this AOP should not be used as a stand-alone basis for regulatory decisions. Instead, it should be applied as part of a weight-of-evidence framework that considers stressor mode of action, exposure context, assay specificity, taxonomic relevance, and concordance across multiple KEs. The AOP also highlights method-development needs, particularly standardized assays for lipid peroxidation, OXPHOS coupling, ATP depletion, and cell injury/death endpoints that can be connected quantitatively to apical growth outcomes.

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AOP-Wiki. 2026a. AOP 478: Deposition of energy leading to occurrence of cataracts. Collaborative Adverse Outcome Pathway Wiki. Available from: https://aopwiki.org/aops/478.

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Appendix 1

List of MIEs in this AOP

Event: 1115: Increase, Reactive oxygen species

Short Name: Increase, ROS

Event Component

AOPs Including This Key Event

Biological Context

Cell term

Organ term

Domain of Applicability

Taxonomic Applicability Life Stage Applicability Sex Applicability

ROS is a normal constituent found in all organisms, lifestages, and sexes.

Key Event Description

Biological State: increased reactive oxygen species (ROS)

Biological compartment: an entire cell -- may be cytosolic, may also enter organelles.

Reactive oxygen species (ROS) are O₂- derived molecules that can be both free radicals (e.g. superoxide, hydroxyl, peroxyl, alcoxyl) and non-radicals (hypochlorous acid, ozone and singlet oxygen) (Bedard and Krause 2007; Ozcan and Ogun 2015). ROS production occurs naturally in all kinds of tissues inside various cellular compartments, such as mitochondria and peroxisomes (Drew and Leeuwenburgh 2002; Ozcan and Ogun 2015). Furthermore, these molecules have an important function in the regulation of several biological processes – they might act as antimicrobial agents or triggers of animal gamete activation and capacitation (Goud et al. 2008; Parrish 2010; Bisht et al. 2017). 
However, in environmental stress situations (exposure to radiation, chemicals, high temperatures) these molecules have its levels drastically increased, and overly interact with macromolecules, namely nucleic acids, proteins, carbohydrates and lipids, causing cell and tissue damage (Brieger et al. 2012; Ozcan and Ogun 2015). 

How it is Measured or Detected

Photocolorimetric assays (Sharma et al. 2017; Griendling et al. 2016) or through commercial kits purchased from specialized companies.

Yuan, Yan, et al., (2013) described ROS monitoring by using H₂-DCF-DA, a redox-sensitive fluorescent dye. Briefly, the harvested cells were incubated with H₂-DCF-DA (50 µmol/L final concentration) for 30 min in the dark at 37°C. After treatment, cells were immediately washed twice, re-suspended in PBS, and analyzed on a BD-FACS Aria flow cytometry. ROS generation was based on fluorescent intensity which was recorded by excitation at 504 nm and emission at 529 nm.

Lipid peroxidation (LPO) can be measured as an indicator of oxidative stress damage Yen, Cheng Chien, et al., (2013).

Chattopadhyay, Sukumar, et al. (2002) assayed the generation of free radicals within the cells and their extracellular release in the medium by addition of yellow NBT salt solution (Park et al., 1968). Extracellular release of ROS converted NBT to a purple colored formazan. The cells were incubated with 100 ml of 1 mg/ml NBT solution for 1 h at 37 °C and the product formed was assayed at 550 nm in an Anthos 2001 plate reader. The observations of the ‘cell-free system’ were confirmed by cytological examination of parallel set of explants stained with chromogenic reactions for NO and ROS.

On the basis of the pathogenesis of drug-induced phototoxicity, a reactive oxygen species (ROS) assay was proposed to evaluate the phototoxic risk of chemicals. The ROS assay can monitor generation of ROS, such as singlet oxygen and superoxide, from photoirradiated chemicals, and the ROS data can be used to evaluate the photoreactivity of chemicals (Onoue et al. , 2014, Onoue et al. , 2013, Onoue and Tsuda, 2006).  The ROS assay is a recommended approach by guidelines to evaluate the phototoxic risk of chemicals (ICH, 2014, PCPC, 2014).

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List of Key Events in the AOP

Event: 1392: Increase, Oxidative Stress

Short Name: Increase, Oxidative Stress

Event Component

AOPs Including This Key Event

Stressors

Biological Context

Domain of Applicability

Taxonomic Applicability Life Stage Applicability Sex Applicability

Taxonomic applicability: Occurrence of oxidative stress is not species specific.  

Life stage applicability: Occurrence of oxidative stress is not life stage specific. 

Sex applicability: Occurrence of oxidative stress is not sex specific. 

Evidence for perturbation by prototypic stressor: There is evidence of the increase of oxidative stress following perturbation from a variety of stressors including exposure to ionizing radiation and altered gravity (Bai et al., 2020; Ungvari et al., 2013; Zhang et al., 2009).  

Key Event Description

Oxidative stress is defined as an imbalance in the production of reactive oxygen species (ROS) and antioxidant defenses. High levels of oxidizing free radicals can be very damaging to cells and molecules within the cell.  As a result, the cell has important defense mechanisms to protect itself from ROS. For example, Nrf2 is a transcription factor and master regulator of the oxidative stress response. During periods of oxidative stress, Nrf2-dependent changes in gene expression are important in regaining cellular homeostasis (Nguyen, et al., 2009) and can be used as indicators of the presence of oxidative stress in the cell. 

In addition to the directly damaging actions of ROS, cellular oxidative stress also changes cellular activities on a molecular level. Redox sensitive proteins have altered physiology in the presence and absence of ROS, which is caused by the oxidation of sulfhydryls to disulfides on neighboring amino acids (Antelmann & Helmann 2011). Importantly Keap1, the negative regulator of Nrf2, is regulated in this manner (Itoh, et al. 2010). 

ROS also undermine the mitochondrial defense system from oxidative damage. The antioxidant systems consist of superoxide dismutase, catalase, glutathione peroxidase and glutathione reductase, as well as antioxidants such as α-tocopherol and ubiquinol, or antioxidant vitamins and minerals including vitamin E, C, carotene, lutein, zeaxanthin, selenium, and zinc (Fletcher, 2010). The enzymes, vitamins and minerals catalyze the conversion of ROS to non-toxic molecules such as water and O2. However, these antioxidant systems are not perfect and endogenous metabolic processes and/or exogenous oxidative influences can trigger cumulative oxidative injuries to the mitochondria, causing a decline in their functionality and efficiency, which further promotes cellular oxidative stress (Balasubramanian, 2000; Ganea & Harding, 2006; Guo et al., 2013; Karimi et al., 2017).  

However, an emerging viewpoint suggests that ROS-induced modifications may not be as detrimental as previously thought, but rather contribute to signaling processes (Foyer et al., 2017). 

 

Sources of ROS Production 

Direct Sources: Direct sources involve the deposition of energy onto water molecules, breaking them into active radical species. When ionizing radiation hits water, it breaks it into hydrogen (H*) and hydroxyl (OH*) radicals by destroying its bonds. The hydrogen will create hydroxyperoxyl free radicals (HO2*) if oxygen is available, which can then react with another of itself to form hydrogen peroxide (H2O2) and more O2 (Elgazzar and Kazem, 2015). Antioxidant mechanisms are also affected by radiation, with catalase (CAT) and peroxidase (POD) levels rising as a result of exposure (Seen et al. 2018; Ahmad et al. 2021).  

Indirect Sources: An indirect source of ROS is the mitochondria, which is one of the primary producers in eukaryotic cells (Powers et al., 2008).  As much as 2% of the electrons that should be going through the electron transport chain in the mitochondria escape, allowing them an opportunity to interact with surrounding structures. Electron-oxygen reactions result in free radical production, including the formation of hydrogen peroxide (H2O2) (Zhao et al., 2019). The electron transport chain, which also creates ROS, is activated by free adenosine diphosphate (ADP), O2, and inorganic phosphate (Pi) (Hargreaves et al. 2020; Raimondi et al. 2020; Vargas-Mendoza et al. 2021). The first and third complexes of the transport chain are the most relevant to mammalian ROS production (Raimondi et al., 2020). The mitochondria has its own set of DNA and it is a prime target of oxidative damage (Guo et al., 2013). ROS is also produced through nicotinamide adenine dinucleotide phosphate oxidase (Nox) stimulation, an event commenced by angiotensin II, a product/effector of the renin-angiotensin system (Nguyen Dinh Cat et al. 2013; Forrester et al. 2018). Other ROS producers include xanthine oxidase, immune cells (macrophage, neutrophils, monocytes, and eosinophils), phospholipase A2 (PLA2), monoamine oxidase (MAO), and carbon-based nanomaterials (Powers et al. 2008; Jacobsen et al. 2008; Vargas-Mendoza et al. 2021). 

How it is Measured or Detected

Oxidative Stress: Direct measurement of ROS is difficult because ROS are unstable. The presence of ROS can be assayed indirectly by measurement of cellular antioxidants, or by ROS-dependent cellular damage. Listed below are common methods for detecting the KE, however there may be other comparable methods that are not listed 

• Detection of ROS by chemiluminescence (https://www.sciencedirect.com/science/article/abs/pii/S0165993606001683) 
• Detection of ROS by chemiluminescence is also described in OECD TG 495 to assess phototoxic potential. 
• Glutathione (GSH) depletion. GSH can be measured by assaying the ratio of reduced to oxidized glutathione (GSH:GSSG) using a commercially available kit (e.g., http://www.abcam.com/gshgssg-ratio-detection-assay-kit-fluorometric-green- ab138881.html). 
• TBARS. Oxidative damage to lipids can be measured by assaying for lipid peroxidation using TBARS (thiobarbituric acid reactive substances) using a commercially available kit. 
• 8-oxo-dG. Oxidative damage to nucleic acids can be assayed by measuring 8-oxo-dG adducts (for which there are a number of ELISA based commercially available kits),or HPLC, described in Chepelev et al. (Chepelev, et al. 2015). 

  

Molecular Biology: Nrf2. Nrf2’s transcriptional activity is controlled post-translationally by oxidation of Keap1. Assay for Nrf2 activity include: 

• Immunohistochemistry for increases in Nrf2 protein levels and translocation into the nucleus Western blot for increased Nrf2 protein levels 
• Western blot of cytoplasmic and nuclear fractions to observe translocation of Nrf2 protein from the cytoplasm to the nucleus qPCR of Nrf2 target genes (e.g., Nqo1, Hmox-1, Gcl, Gst, Prx, TrxR, Srxn), or by commercially available pathway-based qPCR array (e.g., oxidative stress array from SABiosciences) 
• Whole transcriptome profiling by microarray or RNA-seq followed by pathway analysis (in IPA, DAVID, metacore, etc.) for enrichment of the Nrf2 oxidative stress response pathway (e.g., Jackson et al. 2014) 
• OECD TG422D describes an ARE-Nrf2 Luciferase test method 

In general, there are a variety of commercially available colorimetric or fluorescent kits for detecting Nrf2 activation.

Assay Type & Measured Content	Description	Dose Range Studied	Assay Characteristics (Length/Ease of use/Accuracy)
ROS  Formation in the Mitochondria assay (Shaki et al., 2012)	“The mitochondrial ROS measurement was performed flow cytometry using DCFH-DA. Briefly, isolated kidney mitochondria were incubated with UA (0, 50, 100 and 200 µM) in respiration buffer containing (0.32 mM sucrose, 10mM Tris, 20 mM Mops, 50 µM EGTA, 0.5 mM MgCl2, 0.1 mM KH2PO4 and 5 mM sodium succinate) [32]. In the interval times of 5, 30 and 60 min following the UA addition, a sample was taken and DCFH-DA was added (final concentration, 10 µM) to mitochondria and was then incubated for 10 min.Uranyl acetate-induced ROS generation in isolated kidney mitochondria were determined through the flow cytometry (Partec, Deutschland) equipped with a 488-nm argon ion laser and supplied with the Flomax software and the signals were obtained using a 530-nm bandpass filter (FL-1 channel). Each determination is based on the mean fluorescence intensity of 15,000 counts.”	0, 50,100 and 200 µM of Uranyl Acetate	Long/ Easy High accuracy
Mitochondrial Antioxidant Content Assay Measuring GSH content (Shaki et al., 2012)	“GSH content was determined using DTNB as the indicator and spectrophotometer method for the isolated mitochondria. The mitochondrial fractions (0.5 mg protein/ml) were incubated with various concentrations of uranyl acetate for 1 h at 30 °C and then 0.1 ml of mitochondrial fractions was added into 0.1 mol/l of phosphate buffers and 0.04% DTNB in a total volume of 3.0 ml (pH 7.4). The developed yellow color was read at 412 nm on a spectrophotometer (UV-1601 PC, Shimadzu, Japan). GSH content was expressed as µg/mg protein.”	0, 50,  100, or  200 µM  Uranyl Acetate
H2O2 Production Assay Measuring H2O2 Production in isolated mitochondria (Heyno et al., 2008)	“Effect of CdCl2 and antimycin A (AA) on H2O2 production in isolated mitochondria from potato. H2O2 production was measured as scopoletin oxidation. Mitochondria were incubated for 30 min in the measuring buffer  (see the Materials and Methods) containing 0.5 mM succinate as an electron donor and 0.2 µM mesoxalonitrile 3‐chlorophenylhydrazone (CCCP) as an uncoupler, 10 U horseradish peroxidase and 5 µM scopoletin.”	0, 10, 30  µM Cd2+     2 µM antimycin A
Flow Cytometry ROS & Cell Viability (Kruiderig et al., 1997)	“For determination of ROS, samples taken at the indicated time points were directly transferred to FACScan tubes. Dih123 (10 mM, final concentration) was added and cells were incubated at 37°C in a humidified atmosphere (95% air/5% CO2) for 10 min. At t 5 9, propidium iodide (10 mM, final concentration) was added, and cells were analyzed by flow cytometry at 60 ml/min. Nonfluorescent Dih123 is cleaved by ROS to fluorescent R123 and detected by the FL1 detector as described above for Dc (Van de Water 1995)”“For determination of ROS, samples taken at the indicated time points were directly transferred to FACScan tubes. Dih123 (10 mM, final concentration) was added and cells were incubated at 37°C in a humidified atmosphere (95% air/5% CO2) for 10 min. At t 5 9, propidium iodide (10 mM, final concentration) was added, and cells were analyzed by flow cytometry at 60 ml/min. Nonfluorescent Dih123 is cleaved by ROS to fluorescent R123 and detected by the FL1 detector as described above for Dc (Van de Water 1995)”		Strong/easy medium
DCFH-DA  Assay Detection of hydrogen peroxide production (Yuan et al.,  2016)	Intracellular ROS production was measured using DCFH-DA as a probe. Hydrogen peroxide oxidizes DCFH to DCF. The probe is hydrolyzed intracellularly to DCFH carboxylate anion. No direct reaction with H2O2 to form fluorescent production.	0-400  µM	Long/ Easy High accuracy
H2-DCF-DAAssay Detection of superoxide production (Thiebault etal., 2007)	This dye is a stable nonpolar compound which diffuses readily into the cells and yields H2-DCF. Intracellular OH or ONOO- react with H2-DCF when cells contain peroxides, to form the highly fluorescent compound DCF, which effluxes the cell. Fluorescence intensity of DCF is measured using a fluorescence spectrophotometer.	0–600  µM	Long/ Easy High accuracy
CM-H2DCFDA  Assay (Eruslanov  & Kusmartsev, 2009)	The dye (CM-H2DCFDA) diffuses into the cell and is cleaved by esterases, the thiol reactive chlormethyl group reacts with intracellular glutathione which can be detected using flow cytometry.		Long/Easy/ High Accuracy

 

Method of Measurement	References	Description	OECD-Approved Assay
Chemiluminescence	(Lu, C. et al., 2006;   Griendling, K. K., et al., 2016)	ROS can induce electron transitions in molecules, leading to electronically excited products. When the electrons transition back to ground state, chemiluminescence is emitted and can be measured. Reagents such as luminol and lucigenin are commonly used to amplify the signal.	No
Spectrophotometry	(Griendling, K. K., et al., 2016)	NO has a short half-life. However, if it has been reduced to nitrite (NO2-), stable azocompounds can be formed via the Griess Reaction, and further measured by spectrophotometry.	No
Direct or Spin Trapping-Based electron paramagnetic resonance (EPR) Spectroscopy	(Griendling, K. K., et al., 2016)	The unpaired electrons (free radicals) found in ROS can be detected with EPR and is known as electron paramagnetic resonance. A variety of spin traps can be used.	No
Nitroblue Tetrazolium Assay	(Griendling, K. K., et al., 2016)	The Nitroblue Tetrazolium assay is used to measure O2.− levels. O2.− reduces nitroblue tetrazolium (a yellow dye) to formazan (a blue dye), and can be measured at 620 nm.	No
Fluorescence analysis of dihydroethidium (DHE) or Hydrocyans	(Griendling, K. K., et al., 2016)	Fluorescence analysis of DHE is used to measure O2.− levels.  O2.− is reduced to O2 as DHE is oxidized to 2-hydroxyethidium, and this reaction can be measured by fluorescence. Similarly, hydrocyans can be oxidized by any ROS, and measured via fluorescence.	No
Amplex Red Assay	(Griendling, K. K., et al., 2016)	Fluorescence analysis to measure extramitochondrial or extracellular H2O2 levels. In the presence of horseradish peroxidase and H2O2, Amplex Red is oxidized to resorufin, a fluorescent molecule measurable by plate reader.	No
Dichlorodihydrofluorescein Diacetate (DCFH-DA)	(Griendling, K. K., et al., 2016)	An indirect fluorescence analysis to measure intracellular H2O2 levels.  H2O2 interacts with peroxidase or heme proteins, which further react with DCFH, oxidizing it to dichlorofluorescein (DCF), a fluorescent product.	No
HyPer Probe	(Griendling, K. K., et al., 2016)	Fluorescent measurement of intracellular H2O2 levels. HyPer is a genetically encoded fluorescent sensor that can be used for in vivo and in situ imaging.	No
Cytochrome c Reduction Assay	(Griendling, K. K., et al., 2016)	The cytochrome c reduction assay is used to measure O2.− levels. O O2.− is reduced to O2 as ferricytochrome c is oxidized to ferrocytochrome c, and this reaction can be measured by an absorbance increase at 550 nm.	No
Proton-electron double-resonance imaging (PEDRI)	(Griendling, K. K., et al., 2016)	The redox state of tissue is detected through nuclear magnetic resonance/magnetic resonance imaging, with the use of a nitroxide spin probe or biradical molecule.	No
Glutathione (GSH) depletion	(Biesemann, N. et al., 2018)	A downstream target of the Nrf2 pathway is involved in GSH synthesis. As an indication of oxidation status, GSH can be measured by assaying the ratio of reduced to oxidized glutathione (GSH:GSSG) using a commercially available kit (e.g., http://www.abcam.com/gshgssg-ratio-detection-assay-kit-fluorometric-green-ab138881.html).	No
Thiobarbituric acid reactive substances (TBARS)	(Griendling, K. K., et al., 2016)	Oxidative damage to lipids can be measured by assaying for lipid peroxidation with TBARS using a commercially available kit.	No
Protein oxidation (carbonylation)	(Azimzadeh et al., 2017; Azimzadeh et al., 2015; Ping et al., 2020)	Can be determined with ELISA or a commercial assay kit. Protein oxidation can indicate the level of oxidative stress.	No
Seahorse XFp Analyzer	Leung et al. 2018	The Seahorse XFp Analyzer provides information on mitochondrial function, oxidative stress, and metabolic dysfunction of viable cells by measuring respiration (oxygen consumption rate; OCR) and extracellular pH (extracellular acidification rate; ECAR).	No

 

Molecular Biology: Nrf2. Nrf2’s transcriptional activity is controlled post-translationally by oxidation of Keap1. Assays for Nrf2 activity include:  

Method of Measurement	References	Description	OECD-Approved Assay
Immunohistochemistry	(Amsen, D., de Visser, K. E., and Town, T., 2009)	Immunohistochemistry for increases in Nrf2 protein levels and translocation into the nucleus	No
qPCR	(Forlenza et al., 2012)	qPCR of Nrf2 target genes (e.g., Nqo1, Hmox-1, Gcl, Gst, Prx, TrxR, Srxn), or by commercially available pathway-based qPCR array (e.g., oxidative stress array from SABiosciences)	No
Whole transcriptome profiling via microarray or via RNA-seq followed by a pathway analysis	(Jackson, A. F. et al., 2014)	Whole transcriptome profiling by microarray or RNA-seq followed by pathway analysis (in IPA, DAVID, metacore, etc.) for enrichment of the Nrf2 oxidative stress response pathway	No

 

References

Ahmad, S. et al. (2021), “60Co-γ Radiation Alters Developmental Stages of Zeugodacus cucurbitae (Diptera: Tephritidae) Through Apoptosis Pathways Gene Expression”, Journal Insect Science, Vol. 21/5, Oxford University Press, Oxford, https://doi.org/10.1093/jisesa/ieab080 

Antelmann, H. and J. D. Helmann (2011), “Thiol-based redox switches and gene regulation.”, Antioxidants & Redox Signaling, Vol. 14/6, Mary Ann Leibert Inc., Larchmont, https://doi.org/10.1089/ars.2010.3400 

Amsen, D., de Visser, K. E., and Town, T. (2009), “Approaches to determine expression of inflammatory cytokines”, in Inflammation and Cancer, Humana Press, Totowa, https://doi.org/10.1007/978-1-59745-447-6_5  

Azimzadeh, O. et al. (2015), “Integrative Proteomics and Targeted Transcriptomics Analyses in Cardiac Endothelial Cells Unravel Mechanisms of Long-Term Radiation-Induced Vascular Dysfunction”, Journal of Proteome Research, Vol. 14/2, American Chemical Society, Washington, https://doi.org/10.1021/pr501141b 

Azimzadeh, O. et al. (2017), “Proteome analysis of irradiated endothelial cells reveals persistent alteration in protein degradation and the RhoGDI and NO signalling pathways”, International Journal of Radiation Biology, Vol. 93/9, Informa, London, https://doi.org/10.1080/09553002.2017.1339332 

Azzam, E. I. et al. (2012), “Ionizing radiation-induced metabolic oxidative stress and prolonged cell injury”, Cancer Letters, Vol. 327/1-2, Elsevier, Ireland, https://doi.org/10.1016/j.canlet.2011.12.012 

Bai, J. et al. (2020), “Irradiation-induced senescence of bone marrow mesenchymal stem cells aggravates osteogenic differentiation dysfunction via paracrine signaling”, American Journal of Physiology - Cell Physiology, Vol. 318/5, American Physiological Society, Rockville, https://doi.org/10.1152/ajpcell.00520.2019. 

Balasubramanian, D (2000), “Ultraviolet radiation and cataract”, Journal of ocular pharmacology and therapeutics, Vol. 16/3, Mary Ann Liebert Inc., Larchmont, https://doi.org/10.1089/jop.2000.16.285.   

Biesemann, N. et al., (2018), “High Throughput Screening of Mitochondrial Bioenergetics in Human Differentiated Myotubes Identifies Novel Enhancers of Muscle Performance in Aged Mice”, Scientific Reports, Vol. 8/1, Nature Portfolio, London, https://doi.org/10.1038/s41598-018-27614-8.  

Elgazzar, A. and N. Kazem. (2015), “Chapter 23: Biological effects of ionizing radiation” in The Pathophysiologic Basis of Nuclear Medicine, Springer, New York, pp. 540-548 

Eruslanov, E., & Kusmartsev, S. (2010). Identification of ROS using oxidized DCFDA and flow-cytometry. Methods in molecular biology ,N.J.,  Vol. 594,  https://doi.org/10.1007/978-1-60761-411-1_4 

Fletcher, A. E (2010), “Free radicals, antioxidants and eye diseases: evidence from epidemiological studies on cataract and age-related macular degeneration”, Ophthalmic Research, Vol. 44, Karger International, Basel, https://doi.org/10.1159/000316476.  

Forlenza, M. et al. (2012), “The use of real-time quantitative PCR for the analysis of cytokine mRNA levels” in Cytokine Protocols, Springer, New York, https://doi.org/10.1007/978-1-61779-439-1_2  

Forrester, S.J. et al. (2018), “Angiotensin II Signal Transduction: An Update on Mechanisms of Physiology and Pathophysiology”, Physiological Reviews, Vol. 98/3, American Physiological Society, Rockville, https://doi.org/10.1152/physrev.00038.201 

Foyer, C. H., A. V. Ruban, and G. Noctor (2017), “Viewing oxidative stress through the lens of oxidative signalling rather than damage”, Biochemical Journal, Vol. 474/6, Portland Press, England, https://doi.org/10.1042/BCJ20160814 

Ganea, E. and J. J. Harding (2006), “Glutathione-related enzymes and the eye”, Current eye research, Vol. 31/1, Informa, London, https://doi.org/10.1080/02713680500477347.  

Griendling, K. K. et al. (2016), “Measurement of reactive oxygen species, reactive nitrogen species, and redox-dependent signaling in the cardiovascular system: a scientific statement from the American Heart Association”, Circulation research, Vol. 119/5, Lippincott Williams & Wilkins, Philadelphia, https://doi.org/10.1161/RES.0000000000000110  

Guo, C. et al. (2013), “Oxidative stress, mitochondrial damage and neurodegenerative diseases”, Neural regeneration research, Vol. 8/21, Publishing House of Neural Regeneration Research, China, https://doi.org/10.3969/j.issn.1673-5374.2013.21.009 

Hargreaves, M., and L. L. Spriet (2020), “Skeletal muscle energy metabolism during exercise.”, Nature Metabolism, Vol. 2, Nature Portfolio, London, https://doi.org/10.1038/s42255-020-0251-4 

Hladik, D. and S. Tapio (2016), “Effects of ionizing radiation on the mammalian brain”, Mutation Research/Reviews in Mutation Research, Vol. 770, Elsevier, Amsterdam, https://doi.org/10.1016/j.mrrev.2016.08.003 

Itoh, K., J. Mimura and M. Yamamoto (2010), “Discovery of the negative regulator of Nrf2, Keap1: a historical overview”, Antioxidants & Redox Signaling, Vol. 13/11, Mary Ann Leibert Inc., Larchmont, https://doi.org/10.1089/ars.2010.3222  

Jackson, A.F. et al. (2014), “Case study on the utility of hepatic global gene expression profiling in the risk assessment of the carcinogen furan.”, Toxicology and Applied Pharmacology, Vol. 274/11, Elsevier, Amsterdam, https://doi.org/10.1016/j.taap.2013.10.019 

Jacobsen, N.R. et al. (2008), “Genotoxicity, cytotoxicity, and reactive oxygen species induced by single-walled carbon nanotubes and C60 fullerenes in the FE1-MutaTM Mouse lung epithelial cells”, Environmental and Molecular Mutagenesis, Vol. 49/6, John Wiley & Sons, Inc., Hoboken, https://doi.org/10.1002/em.20406 

Karimi, N. et al. (2017), “Radioprotective effect of hesperidin on reducing oxidative stress in the lens tissue of rats”, International Journal of Pharmaceutical Investigation, Vol. 7/3, Phcog Net, Bengaluru, https://doi.org/10.4103/jphi.JPHI_60_17.  

Leung, D.T.H., and Chu, S. (2018), “Measurement of Oxidative Stress: Mitochondrial Function Using the Seahorse System” In: Murthi, P., Vaillancourt, C. (eds) Preeclampsia. Methods in Molecular Biology, vol 1710. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7498-6_22 

Lu, C., G. Song, and J. Lin (2006), “Reactive oxygen species and their chemiluminescence-detection methods”, TrAC Trends in Analytical Chemistry, Vol. 25/10, Elsevier, Amsterdam, https://doi.org/10.1016/j.trac.2006.07.007 

Nguyen Dinh Cat, A. et al. (2013), “Angiotensin II, NADPH oxidase, and redox signaling in the vasculature”, Antioxidants & redox signaling, Vol. 19/10, Mary Ann Liebert, Larchmont, https://doi.org/10.1089/ars.2012.4641 

Ping, Z. et al. (2020), “Oxidative Stress in Radiation-Induced Cardiotoxicity”, Oxidative Medicine and Cellular Longevity, Vol. 2020, Hindawi, https://doi.org/10.1155/2020/3579143 

Powers, S.K. and M.J. Jackson. (2008), “Exercise-Induced Oxidative Stress: Cellular Mechanisms and Impact on Muscle Force Production”, Physiological Reviews, Vol. 88/4, American Physiological Society, Rockville, https://doi.org/10.1152/physrev.00031.2007 

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Vargas-Mendoza, N. et al. (2021), “Oxidative Stress, Mitochondrial Function and Adaptation to Exercise: New Perspectives in Nutrition”, Life, Vol. 11/11, Multidisciplinary Digital Publishing Institute, Basel, https://doi.org/10.3390/life11111269 

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Event: 1445: Increase, Lipid peroxidation

Short Name: Increase, LPO

Event Component

AOPs Including This Key Event

Biological Context

Cell term

Organ term

Domain of Applicability

Taxonomic Applicability Life Stage Applicability Sex Applicability

The biological domain of applicability for this KE is broad because lipid membranes and oxidizable fatty acids are widely conserved biological features. The event is applicable wherever lipid substrates susceptible to oxidation are present and where oxidants can access those substrates. The KE is therefore relevant across many biological systems, including unicellular algae, invertebrates, fish, mammals and human-derived cells. The current evidence base is strongest in mammalian systems because lipid peroxidation chemistry and analytical methods have been extensively studied there, but ecotoxicological evidence supports relevance in algae, crustaceans, mollusks and fish.

    The KE is not intrinsically limited by sex or life stage. However, the magnitude of lipid peroxidation and its downstream consequences may be modified by lipid composition, antioxidant capacity, oxygen availability, temperature, metabolic rate, nutritional status, metal availability, and exposure duration. Organisms or tissues enriched in polyunsaturated fatty acids, exposed to high oxygen flux, or experiencing antioxidant depletion may be particularly susceptible. In photosynthetic organisms, lipid peroxidation may also occur in chloroplast and thylakoid membranes; in animals, mitochondria and plasma membranes are common sites of interest.

    Within the ROS-growth AOP network, this KE is especially relevant as a molecular damage event linking oxidative stress to impaired mitochondrial membrane function, decreased coupling of oxidative phosphorylation, reduced ATP production, cell injury, and decreased growth. Nevertheless, this KE should remain modular: it may be reused in other AOPs whenever increased lipid oxidation products are measured as a consequence of oxidative stress or other lipid-damaging perturbations.

 

Key Event Description

Lipid peroxidation is an oxidative degradation process affecting lipids, particularly polyunsaturated fatty acids in cellular and organelle membranes. The process is initiated when oxidants, including free radicals and reactive oxygen species, abstract hydrogen atoms from susceptible lipid chains. This generates lipid radicals that react with molecular oxygen to form lipid peroxyl radicals and lipid hydroperoxides. These products can propagate chain reactions, producing additional oxidized lipids and secondary reactive aldehydes such as malondialdehyde (MDA), 4-hydroxy-2-nonenal (4-HNE), and related hydroxyalkenals (Esterbauer et al., 1991; Yin et al., 2011; Ayala et al., 2014).

    As a key event, increased lipid peroxidation represents a measurable increase in oxidized lipid products relative to an appropriate control state. The event may reflect direct oxidative damage to membrane lipids, increased formation of lipid hydroperoxides, increased accumulation of MDA or 4-HNE, or increased abundance of specific oxidized phospholipid or fatty acid species. Because lipid peroxidation products can alter membrane fluidity, permeability and signaling, the event is relevant both as a marker of oxidative damage and as a potential contributor to downstream mitochondrial dysfunction, loss of membrane integrity, cytotoxicity and impaired growth (Esterbauer et al., 1991; Uchida, 2003; Ayala et al., 2014).

This KE should be described independently of any specific upstream or downstream event. In an AOP context, lipid peroxidation is commonly downstream of oxidative stress and upstream of events related to decreased mitochondrial coupling, cellular injury, or altered membrane-dependent biological processes. However, the KE itself is defined only by the increased lipid oxidation state and its measurable biochemical products.

How it is Measured or Detected

No OECD Test Guideline is currently dedicated specifically to measurement of lipid peroxidation as a standalone endpoint. Nevertheless, the KE can be measured using several well-established biochemical and analytical methods. Scientific confidence is highest when methods quantify specific lipid peroxidation products or oxidized lipid species directly, and lower when nonspecific colorimetric assays are used without appropriate controls or confirmatory methods.

 

Measurement approach	Endpoint measured	Representative method names	Scientific confidence and limitations
TBARS / MDA assays	Thiobarbituric acid reactive substances, often interpreted as MDA or MDA-like products	TBARS assay; spectrophotometric or fluorometric MDA assays	Widely used and sensitive, but not fully specific because TBA can react with compounds other than MDA. Best used as a screening or comparative indicator of lipid peroxidation, particularly when supported by extraction, HPLC separation or additional markers (Buege and Aust, 1978; Ohkawa et al., 1979; Janero, 1990; Draper and Hadley, 1990).
4-HNE and hydroxyalkenal assays	4-hydroxy-2-nonenal and related reactive aldehydes	ELISA, immunoblotting of HNE-protein adducts, HPLC or LC-MS quantification	Mechanistically informative because 4-HNE is a major bioactive lipid peroxidation product. Antibody-based methods can detect protein adducts, whereas chromatographic or mass spectrometric methods improve specificity (Esterbauer et al., 1991; Uchida, 2003; Ayala et al., 2014).
Lipid hydroperoxide assays	Primary lipid hydroperoxides	FOX assay; iodometric assays; commercial lipid hydroperoxide kits	Useful for detecting relatively early lipid peroxidation products. Hydroperoxides can be unstable and sample handling is critical. FOX-based methods provide a simple approach for lipid hydroperoxide detection (Jiang et al., 1992).
Chromatography and mass spectrometry	Specific oxidized fatty acids, oxidized phospholipids, oxylipins or oxidized lipid classes	HPLC, GC, LC-MS/MS, lipidomics	High specificity and quantitative power when standards and validated workflows are available. These methods can distinguish individual oxidized lipid species and are preferred for detailed mechanistic studies (Yin et al., 2011; Li et al., 2019).
Fluorescent probes and imaging	Oxidation-sensitive fluorescent signal in cellular lipids	BODIPY 581/591 C11 and related lipid oxidation probes	Useful for cell-based or imaging applications and spatial localization, but probe specificity, photoxidation and calibration must be considered. Best used with complementary biochemical or analytical endpoints.

 

 

References

AOP-Wiki. 2026. Key Event 1445: Increase, Lipid peroxidation. AOP-Wiki. Available at: https://aopwiki.org/events/1445. Accessed 14 May 2026.

Alam MR, Ehiguese FO, Vitale D, Martín-Díaz ML. 2022. Oxidative stress response to hydrogen peroxide exposure of Mytilus galloprovincialis and Ruditapes philippinarum: reduced embryogenesis success and altered biochemical response of sentinel marine bivalve species. Environmental Chemistry and Ecotoxicology 4:97-105.

Ayala A, Munoz MF, Arguelles S. 2014. Lipid peroxidation: production, metabolism, and signaling mechanisms of malondialdehyde and 4-hydroxy-2-nonenal. Oxidative Medicine and Cellular Longevity 2014:360438. https://doi.org/10.1155/2014/360438.

Belaid C, Sbartai I. 2021. Assessing the effects of Thiram to oxidative stress responses in a freshwater bioindicator cladoceran (Daphnia magna). Chemosphere 268:128808. https://doi.org/10.1016/j.chemosphere.2020.128808.

Buege JA, Aust SD. 1978. Microsomal lipid peroxidation. Methods in Enzymology 52:302-310. https://doi.org/10.1016/S0076-6879(78)52032-6.

Cong B, Liu C, Wang L, Chai Y. 2020. The impact on antioxidant enzyme activity and related gene expression following adult zebrafish (Danio rerio) exposure to dimethyl phthalate. Animals 10(4):717. https://doi.org/10.3390/ani10040717.

Draper HH, Hadley M. 1990. Malondialdehyde determination as index of lipid peroxidation. Methods in Enzymology 186:421-431. https://doi.org/10.1016/0076-6879(90)86135-I.

Esperanza M, Cid A, Herrero C, Rioboo C. 2015. Acute effects of a prooxidant herbicide on the microalga Chlamydomonas reinhardtii: screening cytotoxicity and genotoxicity endpoints. Aquatic Toxicology 165:210-221. https://doi.org/10.1016/j.aquatox.2015.06.004.

Esterbauer H, Schaur RJ, Zollner H. 1991. Chemistry and biochemistry of 4-hydroxynonenal, malonaldehyde and related aldehydes. Free Radical Biology and Medicine 11(1):81-128. https://doi.org/10.1016/0891-5849(91)90192-6.

Janero DR. 1990. Malondialdehyde and thiobarbituric acid-reactivity as diagnostic indices of lipid peroxidation and peroxidative tissue injury. Free Radical Biology and Medicine 9(6):515-540. https://doi.org/10.1016/0891-5849(90)90131-2.

Jiang ZY, Hunt JV, Wolff SP. 1992. Ferrous ion oxidation in the presence of xylenol orange for detection of lipid hydroperoxide in low density lipoprotein. Analytical Biochemistry 202(2):384-389. https://doi.org/10.1016/0003-2697(92)90122-N.

Knauert S, Knauer K. 2008. The role of reactive oxygen species in copper toxicity to two freshwater green algae. Journal of Phycology 44(2):311-319. https://doi.org/10.1111/j.1529-8817.2008.00471.x.

Li L, Zhong S, Shen X, Li Q, Xu W, Tao Y, Yin H. 2019. Recent development on liquid chromatography-mass spectrometry analysis of oxidized lipids. Free Radical Biology and Medicine 144:16-34. https://doi.org/10.1016/j.freeradbiomed.2019.06.006.

Moore TD, Martin-Creuzburg D, Yampolsky LY. 2023. Diet effects on longevity, heat tolerance, lipid peroxidation and mitochondrial membrane potential in Daphnia. Oecologia 202(1):151-163. https://doi.org/10.1007/s00442-023-05382-1.

Ohkawa H, Ohishi N, Yagi K. 1979. Assay for lipid peroxides in animal tissues by thiobarbituric acid reaction. Analytical Biochemistry 95(2):351-358. https://doi.org/10.1016/0003-2697(79)90738-3.

Ouillon N, Sokolov EP, Otto S, Rehder G, Sokolova IM. 2021. Effects of variable oxygen regimes on mitochondrial bioenergetics and reactive oxygen species production in a marine bivalve, Mya arenaria. Journal of Experimental Biology 224(4):jeb237156. https://doi.org/10.1242/jeb.237156.

Tseng YC, Chen RD, Lucassen M, Schmidt MM, Dringen R, Abele D, Hwang PP. 2011. Exploring uncoupling proteins and antioxidant mechanisms under acute cold exposure in brains of fish. PLoS ONE 6(3):e18180. https://doi.org/10.1371/journal.pone.0018180.

Uchida K. 2003. 4-Hydroxy-2-nonenal: a product and mediator of oxidative stress. Progress in Lipid Research 42(4):318-343. https://doi.org/10.1016/S0163-7827(03)00014-6.

Yin H, Xu L, Porter NA. 2011. Free radical lipid peroxidation: mechanisms and analysis. Chemical Reviews 111(10):5944-5972. https://doi.org/10.1021/cr200084z.

Event: 1446: Decrease, Coupling of oxidative phosphorylation

Short Name: Decrease, Coupling of OXPHOS

Event Component

AOPs Including This Key Event

Stressors

Biological Context

Cell term

Domain of Applicability

Taxonomic Applicability Life Stage Applicability Sex Applicability

Taxonomic applicability domain

This key event is in general considered applicable to most eukaryotes, as the mitochondrion and oxidative phosphorylation are highly conserved (Roger 2017).

 

Life stage applicability domain

This key event is considered applicable to all life stages, as ATP synthesis by oxidative phosphorylation is an essential biological process for most living organisms.

 

Sex applicability domain

This key event is considered sex-unspecific, as both males and females use oxidative phosphorylation as a main process to generate ATP.

Key Event Description

Decreased coupling of oxidative phosphorylation (OXPHOS), or uncoupling of OXPHOS, describes dissipation of protonmotive force (PMF) across the inner mitochondrial membrane (IMM) by environmental stressors. In eukaryotes, the mitochondrial electron transport chain mediates a series of redox reactions to create a PMF across the IMM. The PMF is used as energy to drive adenosine triphosphate (ATP) synthesis through phosphorylation of adenosine diphosphate (ADP). These processes are coupled and referred to as OXPHOS. A number of chemicals can dissipate the PMF, leading to uncoupling of OXPHOS. This key event describes the main outcome of the interactions between an uncoupler and the transmembrane PMF. An uncoupler can bind to a proton in the mitochondrial inter membrane space, transport the proton to the matrix side of the IMM, release the proton and move back to the inter membrane space. These processes are repeated until the transmembrane PMF is dissipated. This KE is therefore a lumped term of these processes and represents the final consequence of the interactions.

How it is Measured or Detected

Uncoupling of oxidative phosphorylation can be indicated by reduced mitochondrial membrane potential, increased proton leak and/or increased oxygen consumption rate.

• Mitochondrial membrane potential can be determined using ToxCast high-throughput screening bioassays such as “APR_HepG2_MitoMembPot”, “APR_Hepat_MitoFxnI”, and “APR_Mitochondrial_membrane_potential”, and the Tox21 high-throughput screening assay “tox21-mitotox-p1”.
• Mitochondrial membrane potential can also be measured using commercially available fluorescent probes such as TMRM (tetramethylrhodamine, methyl ester, perchlorate), TMRE (tetramethylrhodamine, ethyl ester, perchlorate) and JC-1 (Perry 2011).
• Proton leak and oxygen consumption rate can be measured using a high-resolution respirometry (Affourtit 2018) or a Seahorse XF analyzer (Divakaruni 2014).

References

Affourtit C, Wong H-S, Brand MD. 2018. Measurement of proton leak in isolated mitochondria. In Palmeira CM, Moreno AJ, eds, Mitochondrial Bioenergetics: Methods and Protocols. Springer New York, New York, NY, pp 157-170.

Attene-Ramos MS, Huang R, Sakamuru S, Witt KL, Beeson GC, Shou L, Schnellmann RG, Beeson CC, Tice RR, Austin CP, Xia M. 2013. Systematic study of mitochondrial toxicity of environmental chemicals using quantitative high throughput screening. Chemical Research in Toxicology 26:1323-1332. DOI: 10.1021/tx4001754.

Attene-Ramos MS, Huang RL, Michael S, Witt KL, Richard A, Tice RR, Simeonov A, Austin CP, Xia MH. 2015. Profiling of the Tox21 chemical collection for mitochondrial function to identify compounds that acutely decrease mitochondrial membrane potential. Environ Health Persp 123:49-56. DOI: 10.1289/ehp.1408642.

Divakaruni AS, Paradyse A, Ferrick DA, Murphy AN, Jastroch M. 2014. Chapter Sixteen - Analysis and Interpretation of Microplate-Based Oxygen Consumption and pH Data. In Murphy AN, Chan DC, eds, Methods in Enzymology. Vol 547. Academic Press, pp 309-354.

Dreier DA, Denslow ND, Martyniuk CJ. 2019. Computational in vitro toxicology uncovers chemical structures impairing mitochondrial membrane potential. J Chem Inf Model 59:702-712. DOI: 10.1021/acs.jcim.8b00433.

Escher BI, Schwarzenbach RP. 2002. Mechanistic studies on baseline toxicity and uncoupling of organic compounds as a basis for modeling effective membrane concentrations in aquatic organisms. Aquatic Sciences 64:20-35. DOI: 10.1007/s00027-002-8052-2.

Legradi J, Dahlberg A-K, Cenijn P, Marsh G, Asplund L, Bergman Å, Legler J. 2014. Disruption of Oxidative Phosphorylation (OXPHOS) by Hydroxylated Polybrominated Diphenyl Ethers (OH-PBDEs) Present in the Marine Environment. Environmental Science & Technology 48:14703-14711. DOI: 10.1021/es5039744.

Naven RT, Swiss R, Klug-Mcleod J, Will Y, Greene N. 2012. The development of structure-activity relationships for mitochondrial dysfunction: Uncoupling of oxidative phosphorylation. Toxicol Sci 131:271-278. DOI: 10.1093/toxsci/kfs279.

Perry SW, Norman JP, Barbieri J, Brown EB, Gelbard HA. 2011. Mitochondrial membrane potential probes and the proton gradient: a practical usage guide. BioTechniques 50:98-115. DOI: 10.2144/000113610.

Roger AJ, Munoz-Gomez SA, Kamikawa R. 2017. The origin and diversification of mitochondria. Curr Biol 27:R1177-R1192. DOI: 10.1016/j.cub.2017.09.015.

Russom CL, Bradbury SP, Broderius SJ, Hammermeister DE, Drummond RA. 1997. Predicting modes of toxic action from chemical structure: Acute toxicity in the fathead minnow (Pimephales promelas). Environ Toxicol Chem 16:948-967. DOI: https://doi.org/10.1002/etc.5620160514.

Schultz TW, Cronin MTD. 1997. Quantitative structure-activity relationships for weak acid respiratory uncouplers to Vibrio fisheri. Environ Toxicol Chem 16:357-360. DOI: https://doi.org/10.1002/etc.5620160235.

Shim J, Weatherly LM, Luc RH, Dorman MT, Neilson A, Ng R, Kim CH, Millard PJ, Gosse JA. 2016. Triclosan is a mitochondrial uncoupler in live zebrafish. J Appl Toxicol 36:1662-1667. DOI: 10.1002/jat.3311.

Sugiyama Y, Shudo T, Hosokawa S, Watanabe A, Nakano M, Kakizuka A. 2019. Emodin, as a mitochondrial uncoupler, induces strong decreases in adenosine triphosphate (ATP) levels and proliferation of B16F10 cells, owing to their poor glycolytic reserve. Genes to Cells 24:569-584. DOI: https://doi.org/10.1111/gtc.12712.

Terada H. 1990. Uncouplers of oxidative phosphorylation. Environ Health Perspect 87:213-218. DOI: 10.1289/ehp.9087213.

Troger F, Delp J, Funke M, van der Stel W, Colas C, Leist M, van de Water B, Ecker GF. 2020. Identification of mitochondrial toxicants by combined in silico and in vitro studies – A structure-based view on the adverse outcome pathway. Computational Toxicology 14:100123. DOI: https://doi.org/10.1016/j.comtox.2020.100123.

Weatherly LM, Shim J, Hashmi HN, Kennedy RH, Hess ST, Gosse JA. 2016. Antimicrobial agent triclosan is a proton ionophore uncoupler of mitochondria in living rat and human mast cells and in primary human keratinocytes. Journal of Applied Toxicology 36:777-789. DOI: https://doi.org/10.1002/jat.3209.

Xia M, Huang R, Shi Q, Boyd WA, Zhao J, Sun N, Rice JR, Dunlap PE, Hackstadt AJ, Bridge MF, Smith MV, Dai S, Zheng W, Chu PH, Gerhold D, Witt KL, DeVito M, Freedman JH, Austin CP, Houck KA, Thomas RS, Paules RS, Tice RR, Simeonov A. 2018. Comprehensive analyses and prioritization of Tox21 10K chemicals affecting mitochondrial function by in-depth mechanistic studies. Environ Health Perspect 126:077010. DOI: 10.1289/EHP2589.

Event: 1771: Decrease, Adenosine triphosphate pool

Short Name: Decrease, ATP pool

Event Component

AOPs Including This Key Event

Stressors

Biological Context

Cell term

Domain of Applicability

Taxonomic Applicability Life Stage Applicability Sex Applicability

Taxonomic applicability domain

This key event is in general considered applicable to all eukaryotes utilizing ATP as a direct source of energy and signaling molecule.

 

Life stage applicability domain

This key event is considered applicable to all life stages, as all developmental stages require energy supply to maintain necessary physiological processes.

 

Sex applicability domain

This key event is considered sex-unspecific, as both males and females use ATP as an essential energy molecule.

Key Event Description

Decreased adenosine triphosphate (ATP) pool describes the loss of balance between ATP synthesis and ATP consumption, leading to reduced total ATP. As a primary form of biological energy, ATP is used by many biological processes (Bonora 2012). Decrease in ATP level normally attributes to metabolic disorders in major ATP synthetic pathways, such as mitochondrial oxidative phosphorylation, fatty acid β-oxidation, glycolysis and plant photophosphorylation.

How it is Measured or Detected

-The ATP pool in cells or tissue can be quantified using a well-established ATP bioluminescent assay (Lemasters 1978; Wibom 1990). Assay principles: ATP can react with luciferase and luciferin from firefly and the luminescence emitted from the reaction is proportional to the ATP concentration:

ATP + D-Luciferin + O₂ è Oxyluciferin + AMP + PPi + CO₂ + Light

-ToxCast high-throughput screening bioassays, such as “NCCT_HEK293T_CellTiterGLO” and “NIS_HEK293T_CTG_Cytotoxicity” can be used to measure this KE.

 

References

Bonora M, Patergnani S, Rimessi A, De Marchi E, Suski JM, Bononi A, Giorgi C, Marchi S, Missiroli S, Poletti F, Wieckowski MR, Pinton P. 2012. ATP synthesis and storage. Purinergic Signalling 8:343-357. DOI: 10.1007/s11302-012-9305-8.

Lemasters JJ, Hackenbrock CR. 1978. [4] Firefly luciferase assay for ATP production by mitochondria. Methods in Enzymology. Vol 57. Academic Press, pp 36-50.

Wibom R, Lundin A, Hultman E. 1990. A sensitive method for measuring ATP-formation in rat muscle mitochondria. Scandinavian Journal of Clinical and Laboratory Investigation 50:143-152. DOI: 10.1080/00365519009089146.

Event: 55: Increase, Cell injury/death

Short Name: Cell injury/death

Event Component

AOPs Including This Key Event

Biological Context

Cell term

Domain of Applicability

Taxonomic Applicability Life Stage Applicability Sex Applicability

Cell death is an universal event occurring in cells of any species (Fink and Cookson,2005).

Key Event Description

Two types of cell death can be distinguished by morphological features, although it is likely that these are two ends of a spectrum with possible intermediate forms. Apoptosis involves shrinkage, nuclear disassembly, and fragmentation of the cell into discrete bodies with intact plasma membranes. These are rapidly phagocytosed by neighbouring cells. An important feature of apoptosis is the requirement for adenosine triphosphate (ATP) to initiate the execution phase. In contrast, necrotic cell death is characterized by cell swelling and lysis. This is usually a consequence of profound loss of mitochondrial function and resultant ATP depletion, leading to loss of ion homeostasis, including volume regulation, and increased intracellular Ca2+. The latter activates a number of nonspecific hydrolases (i.e., proteases, nucleases, and phospholipases) as well as calcium dependent kinases. Activation of calpain I, the Ca2+-dependent cysteine protease cleaves the death-promoting Bcl-2 family members Bid and Bax which translocate to mitochondrial membranes, resulting in release of truncated apoptosis-inducing factor (tAIF), cytochrome c and endonuclease in the case of Bid and cytocrome c in the case of Bax. tAIF translocates to cell nuclei, and together with cyclophilin A and phosphorylated histone H2AX (γH2AX) is responsible for DNA cleavage, a feature of programmed necrosis. Activated calpain I has also been shown to cleave the plasma membrane Na+–Ca2+ exchanger, which leads to build-up of intracellular Ca2+, which is the source of additional increased intracellular Ca2+. Cytochrome c in cellular apoptosis is a component of the apoptosome.

DNA damage activates nuclear poly(ADP-ribose) polymerase-1(PARP-1), a DNA repair enzyme. PARP-1 forms poly(ADP-ribose) polymers, to repair DNA, but when DNA damage is extensive, PAR accumulates, exits cell nuclei and travels to mitochondrial membranes, where it, like calpain I, is involved in AIF release from mitochondria. A fundamental distinction between necrosis and apoptosis is the loss of plasma membrane integrity; this is integral to the former but not the latter. As a consequence, lytic release of cellular constituents promotes a local inflammatory reaction, whereas the rapid removal of apoptotic bodies minimizes such a reaction. The distinction between the two modes of death is easily accomplished in vitro but not in vivo. Thus, although claims that certain drugs induce apoptosis have been made, these are relatively unconvincing. DNA fragmentation can occur in necrosis, leading to positive TUNEL staining (see explanation below). Conversely, when apoptosis is massive, it can exceed the capacity for rapid phagocytosis, resulting in the eventual appearance of secondary necrosis.

Two alternative pathways - either extrinsic (receptor-mediated) or intrinsic (mitochondria-mediated) - lead to apoptotic cell death. The initiation of cell death begins either at the plasma membrane with the binding of TNF or FasL to their cognate receptors or within the cell. The latter is due to the occurrence of intracellular stress in the form of biochemical events such as oxidative stress, redox changes, covalent binding, lipid peroxidation, and consequent functional effects on mitochondria, endoplasmic reticulum, microtubules, cytoskeleton, or DNA. The intrinsic mitochondrial pathway involves the initiator, caspase-9, which, when activated, forms an “apoptosome” in the cytosol, together with cytochrome c, which translocates from mitochondria, Apaf-1 and dATP. The apoptosome activates caspase-3, the central effector caspase, which in turn activates downstream factors that are responsible for the apoptotic death of a cell (Fujikawa, 2015). Intracellular stress either directly affects mitochondria or can lead to effects on other organelles, which then send signals to the mitochondria to recruit participation in the death process (Fujikawa, 2015; Malhi et al., 2010). Constitutively expressed nitric oxide synthase (nNOS) is a Ca2+-dependent cytosolic enzyme that forms nitric oxide (NO) from L-arginine, and NO reacts with the free radical such as superoxide (O2−) to form the very toxic free radical peroxynitrite (ONOO−). Free radicals such as ONOO−, O2 − and hydroxyl radical (OH−) damage cellular membranes and intracellular proteins, enzymes and DNA (Fujikawa, 2015; Malhi et al., 2010; Kaplowitz, 2002; Kroemer et al., 2009).  

How it is Measured or Detected

 

Necrosis:

Lactate dehydrogenase (LDH) is a soluble cytoplasmic enzyme that is present in almost all cells and is released into extracellular space when the plasma membrane is damaged. To detect the leakage of LDH into cell culture medium, a tetrazolium salt is used in this assay. In the first step, LDH produces reduced nicotinamide adenine dinucleotide (NADH) when it catalyzes the oxidation of lactate to pyruvate. In the second step, a tetrazolium salt is converted to a colored formazan product using newly synthesized NADH in the presence of an electron acceptor. The amount of formazan product can be colorimetrically quantified by standard spectroscopy. Because of the linearity of the assay, it can be used to enumerate the percentage of necrotic cells in a sample (Chan et al., 2013). 

The MTT assay is a colorimetric assay for assessing cell viability. NAD(P)H-dependent cellular oxidoreductase enzymes may reflect the number of viable cells present. These enzymes are capable of reducing the tetrazolium dye MTT 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide to its insoluble formazan, which has a purple color. Other closely related tetrazolium dyes include XTT, MTS and the WSTs. Tetrazolium dye assays can also be used to measure cytotoxicity (loss of viable cells) or cytostatic activity (shift from proliferation to quiescence) of potential medicinal agents and toxic materials. MTT assays are usually done in the dark since the MTT reagent is sensitive to light (Berridgeet al.,2005).

Propidium iodide (PI) is an intercalating agent and a fluorescent molecule used to stain necrotic cells. It is cell membrane impermeant so it stains only those cells where the cell membrane is destroyed. When PI is bound to nucleic acids, the fluorescence excitation maximum is 535 nm and the emission maximum is 617 nm (Moore et al.,1998)

Alamar Blue (resazurin) is a fluorescent dye. The oxidized blue non fluorescent Alamar blue is reduced to a pink fluorescent dye in the medium by cell activity (O'Brien et al., 2000) (12).

Neutral red uptake, which is based on the ability of viable cells to incorporate and bind the supravital dye neutral red in lysosomes (Repetto et al., 2008)(13). Moreover, quantification of ATP, signaling the presence of metabolically active cells, can be performed (CellTiter-Glo; Promega).

ATP assay: Quantification of ATP, signaling the presence of metabolically active cells (CellTiter-Glo; Promega).

Apoptosis:

TUNEL is a common method for detecting DNA fragmentation that results from apoptotic signalling cascades. The assay relies on the presence of nicks in the DNA which can be identified by terminal deoxynucleotidyl transferase or TdT, an enzyme that will catalyze the addition of dUTPs that are secondarily labeled with a marker. It may also label cells that have suffered severe DNA damage.

Caspase activity assays measured by fluorescence. During apoptosis, mainly caspase-3 and -7 cleave PARP to yield an 85 kDa and a 25 kDa fragment. PARP cleavage is considered to be one of the classical characteristics of apoptosis. Antibodies to the 85 kDa fragment of cleaved PARP or to caspase-3 both serve as markers for apoptotic cells that can be monitored using immunofluorescence (Li, Peng et al., 2004).

Hoechst 33342 staining: Hoechst dyes are cell-permeable and bind to DNA in live or fixed cells. Therefore, these stains are often called supravital, which means that cells survive a treatment with these compounds. The stained, condensed or fragmented DNA is a marker of apoptosis (Loo, 2002; Kubbies and Rabinovitch, 1983). 

Acridine Orange/Ethidium Bromide staining is used to visualize nuclear changes and apoptotic body formation that are characteristic of apoptosis. Cells are viewed under a fluorescence microscope and counted to quantify apoptosis.

References

• Fujikawa, D.G. (2015), The role of excitotoxic programmed necrosis in acute brain injury, Comput Struct Biotechnol J, vol. 13, pp. 212-221.
• Malhi, H. et al. (2010), Hepatocyte death: a clear and present danger, Physiol Rev, vol. 90, no. 3, pp. 1165-1194.
• Kaplowitz, N. (2002), Biochemical and Cellular Mechanisms of Toxic Liver Injury, Semin Liver Dis, vol. 22, no. 2, http://www.medscape.com/viewarticle/433631 (accessed on 20 January 2016).
• Kroemer, G. et al., (2009), Classification of cell death: recommendations of the Nomenclature Committee on Cell Death, Cell Death Differ, vol. 16, no. 1, pp. 3-11.
• Chan, F.K., K. Moriwaki and M.J. De Rosa (2013), Detection of necrosis by release of lactate dehydrogenase (LDH) activity, Methods Mol Biol, vol. 979, pp. 65–70.
• Berridge, M.V., P.M. Herst and A.S. Tan (2005), Tetrazolium dyes as tools in cell biology: new insights into their cellular reduction. Biotechnology Annual Review, vol. 11, pp 127-152.
• Moore, A, et al.(1998), Simultaneous measurement of cell cycle and apoptotic cell death,Methods Cell Biol, vol. 57, pp. 265–278.
• Li, Peng et al. (2004), Mitochondrial activation of apoptosis, Cell, vol. 116, no. 2 Suppl,pp. S57-59, 2 p following S59.
• Loo, D.T. (2002), TUNEL Assay an overview of techniques, Methods in Molecular Biology, vol. 203: In Situ Detection of DNA Damage, chapter 2, Didenko VV (ed.), Humana Press Inc.
• Kubbies, M. and P.S. Rabinovitch (1983), Flow cytometric analysis of factors which influence the BrdUrd-Hoechst quenching effect in cultivated human fibroblasts and lymphocytes, Cytometry, vol. 3, no. 4, pp. 276–281.
• Fink, S.L. and B.T. Cookson (2005), Apoptosis, pyroptosis, and necrosis: mechanistic description of dead and dying eukaryotic cells, Infect Immun, vol. 73, no. 4, pp.1907-1916.
• O'Brien J, Wilson I, Orton T, Pognan F. 2000. Investigation of the Alamar Blue (resazurin) fluorescent dye for the assessment of mammalian cell cytotoxicity. European journal of biochemistry / FEBS 267(17): 5421-5426.
• Repetto G, del Peso A, Zurita JL. 2008. Neutral red uptake assay for the estimation of cell viability/cytotoxicity. Nature protocols 3(7): 1125-1131.

List of Adverse Outcomes in this AOP

Event: 1521: Decrease, Growth

Short Name: Decrease, Growth

Event Component

AOPs Including This Key Event

Stressors

Biological Context

Domain of Applicability

Taxonomic Applicability Life Stage Applicability Sex Applicability

Taxonomic applicability domain

This key event is in general applicable to all eukaryotes.

 

Life stage applicability domain

This key event is applicable to early life stages such as embryo and juvenile.

 

Sex applicability domain

This key event is sex-unspecific.

Key Event Description

Decreased growth refers to a reduction in size and/or weight of a tissue, organ or individual organism. Growth is normally controlled by growth factors and mainly achieved through cell proliferation (Conlon 1999).

How it is Measured or Detected

Growth can be indicated by measuring weight, length, total volume, and/or total area of a tissue, organ or individual organism.  

Regulatory Significance of the AO

Growth is a regulatory relevant chronic toxicity endpoint for almost all organisms. Multiple OECD test guidelines have included growth either as a main endpoint of concern, or as an additional endpoint to be considered in the toxicity assessments. Relevant test guidelines include, but not only limited to:

 

-Test No. 201: Freshwater Alga and Cyanobacteria, Growth Inhibition Test

-Test No. 208: Terrestrial Plant Test: Seedling Emergence and Seedling Growth Test

-Test No. 211: Daphnia magna Reproduction Test

-Test No. 212: Fish, Short-term Toxicity Test on Embryo and Sac-Fry Stages

-Test No. 215: Fish, Juvenile Growth Test

-Test No. 221: Lemna sp. Growth Inhibition Test

-Test No. 228: Determination of Developmental Toxicity to Dipteran Dung Flies (Scathophaga stercoraria L. (Scathophagidae), Musca autumnalis De Geer (Muscidae))

-Test No. 241: The Larval Amphibian Growth and Development Assay (LAGDA)

-Test No. 407: Repeated Dose 28-day Oral Toxicity Study in Rodents

-Test No. 408: Repeated Dose 90-Day Oral Toxicity Study in Rodents

-Test No. 416: Two-Generation Reproduction Toxicity

-Test No. 422: Combined Repeated Dose Toxicity Study with the Reproduction/Developmental Toxicity Screening Test

-Test No. 443: Extended One-Generation Reproductive Toxicity Study

-Test No. 453: Combined Chronic Toxicity/Carcinogenicity Studies

References

Conlon I, Raff M. 1999. Size control in animal development. Cell 96:235-244. DOI: 10.1016/s0092-8674(00)80563-2.

Appendix 2

List of Key Event Relationships in the AOP