AOP ID and Title:

Short Title: ROS leading to growth inhibition via protein oxidation 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 333) describes a linear route by which increased reactive oxygen species (ROS) can lead to decreased organismal growth through oxidative stress-mediated protein oxidation, mitochondrial bioenergetic impairment, ATP depletion, and increased cell injury/death. 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. When oxidant production exceeds antioxidant and repair capacity, proteins become oxidatively modified through processes such as carbonylation, thiol oxidation, glutathionylation, nitration, fragmentation, aggregation, or altered degradation. Oxidative modification of proteins involved in mitochondrial electron transport, ATP synthase activity, substrate transport, or maintenance of mitochondrial membrane potential can impair coupling of oxidative phosphorylation (OXPHOS). Decreased OXPHOS coupling reduces the cellular ATP pool. ATP depletion compromises ion homeostasis, membrane integrity, stress-response capacity, biosynthesis, and the execution of regulated cell death pathways, thereby increasing cell injury/death. Increased loss of viable cells can reduce tissue or organismal growth, particularly in developing, rapidly growing, or metabolically active systems.

    AOP 333 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 energy deposition generates free radicals and oxidative stress and includes oxidative damage to proteins as a downstream consequence (AOP-Wiki, 2026a). The relationship from decreased coupling of OXPHOS to decreased ATP pool is associated with AOP 263, an OECD-published AOP that links OXPHOS uncoupling to growth inhibition through ATP depletion and reduced cell proliferation (AOP-Wiki, 2026b; OECD, 2022; Song and Villeneuve, 2021). AOP 333 differs from AOP 332 by routing ATP depletion through increased cell injury/death rather than through decreased cell proliferation. The cellular injury/death module reuses the broadly shared AOP-Wiki KE 'Increase, Cell injury/death', which occurs in AOPs 12, 13, 17, 38, and 48 in neurotoxicity, oxidative stress, fibrosis, and excitotoxicity contexts (AOP-Wiki, 2026c-g). The AOP is relevant to environmental and human health contexts because ROS generation, oxidative stress responses, protein oxidation, mitochondrial ATP production, cell viability, and growth are broadly conserved among aerobic eukaryotes. The AOP can support mechanistic interpretation of oxidative stress-mediated growth impairment, assay selection, chemical prioritization, integrated approaches to testing and assessment (IATA), and future 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). Proteins are major targets of oxidative attack because amino acid side chains, thiol groups, metal centers, and prosthetic groups can undergo oxidative modification. Protein oxidation can reduce enzyme activity, alter protein-protein interactions, impair folding, increase aggregation, disrupt degradation by proteasomal and lysosomal systems, and contribute to cellular dysfunction (Dalle-Donne et al., 2006).

    AOP 333 was developed to represent the protein oxidation and cell injury/death-driven linear route within the broader ROS-growth AOP network. This route was selected because protein oxidation is a well-established consequence of oxidative stress and because mitochondrial proteins are central determinants of OXPHOS coupling and ATP production. Oxidative modification of respiratory-chain proteins, ATP synthase subunits, mitochondrial carriers, or proteins involved in maintaining mitochondrial membrane potential can reduce respiratory efficiency and ATP synthesis (Murphy, 2009; Nicholls and Ferguson, 2013; Sokolov et al., 2019). ATP depletion is an established contributor to loss of cell viability because cell survival depends on ATP-dependent ion gradients, membrane repair, stress responses, proteostasis, and execution of regulated cell death pathways. Severe ATP depletion can shift cellular outcomes toward irreversible injury or necrosis, whereas less severe depletion may permit apoptosis or adaptive responses (Leist et al., 1997; Bonora et al., 2012).

The AOP was designed to maximize reuse of existing AOP-Wiki content. AOP 478 was reviewed because it provides a curated AOP-Wiki context for oxidative stress downstream of free radical generation and includes oxidative molecular damage, including modified proteins, as a relevant consequence of oxidative stress (AOP-Wiki, 2026a). AOP 263 was used to anchor the downstream mitochondrial bioenergetic segment because it provides an OECD-published, well-supported module connecting decreased coupling of OXPHOS with decreased ATP pool and decreased growth-related outcomes (AOP-Wiki, 2026b; OECD, 2022; Song and Villeneuve, 2021). AOPs 12, 13, 17, 38, and 48 were reviewed because they reuse the KE 'Increase, Cell injury/death' and provide evidence that cell injury/death is a generic, reusable cellular response to diverse upstream perturbations. In particular, AOP 17 describes oxidative stress-related developmental neurotoxicity that includes cell injury/death, AOP 38 uses cell injury/death as an early response to protein alkylation in liver fibrosis, and AOP 48 includes mitochondrial dysfunction leading to cell injury/death in an excitotoxicity context (AOP-Wiki, 2026e-g).

Strategy

AOP 333 was developed using the principles described in OECD AOP guidance, including modular description of KEs and KERs, evidence evaluation using biological plausibility, empirical support, essentiality, and quantitative understanding, and clear description of the biological domain of applicability (OECD, 2018, 2021). The development approach combined reuse of existing AOP-Wiki content, targeted literature review, and an AI-human hybrid evidence workflow. The objective was to define a focused linear AOP within the broader ROS-growth AOP network rather than to create an isolated de novo pathway.

    The evidence search began with development of event-specific search terms for each KE, including KE names, synonyms, endpoint terms, assay names, stressor terms, taxa, and species names. These terms were used in AOP-helpFinder to search PubMed for co-occurrence of KEs and related mechanistic concepts (Carvaillo et al., 2019; Jornod et al., 2022). AOP-helpFinder outputs, including PMIDs, titles, abstracts, and matched KE terms, were exported and subjected to overlap analysis to remove redundant hits and filter taxa- or endpoint-irrelevant literature.

    The second phase used ChatGPT (OpenAI, San Francisco, CA, USA)-assisted screening to prioritize abstracts and full-text records. The LLM was used as an auxiliary tool to extract study metadata, including stressor, species, biological system, dose or concentration, and exposure time; to classify evidence type, including biological plausibility, empirical support, and essentiality; and to identify weight-of-evidence indicators, including dose-response concordance, temporal concordance, incidence concordance, and intervention or rescue evidence. Studies were categorized as high, medium, or low priority. High-priority studies were retrieved for full-text review, medium-priority studies were reserved as supporting evidence, and low-priority studies were documented but not carried forward for detailed curation.

The final phase consisted of manual expert review and curation. Expert review verified LLM outputs against the full text, extracted evidence into KER evidence tables, and assigned weight-of-evidence calls for biological plausibility, empirical support, essentiality, and quantitative understanding. Targeted manual searches were performed to fill gaps for protein oxidation, mitochondrial bioenergetics, ATP depletion, cell injury/death, and growth outcomes. Studies were prioritized when they measured two or more KEs in the same biological system, reported dose and time information, or supported temporal, dose-response, incidence, or intervention concordance. Mechanistic reviews and OECD reports were used to support biological plausibility where relationships are widely established, whereas primary experimental studies were prioritized for empirical support where available.

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 333 is considered moderate. Biological plausibility is high for all six KERs in the pathway. The mechanistic connections between oxidative stress, protein oxidation, impaired mitochondrial OXPHOS coupling, ATP depletion, cell injury/death, and decreased growth are individually well supported, and the AOP draws on conserved biological processes broadly applicable across aerobic eukaryotes. The central OXPHOS-to-ATP segment is directly associated with OECD-endorsed AOP 263, providing strong mechanistic and quantitative support for this portion of the pathway (OECD, 2022; Song and Villeneuve, 2021). The cell injury/death KE (Event 55) is a widely reused and modular AOP-Wiki element present in endorsed AOPs 12, 13, 17, 38, and 48, reinforcing the credibility of its use as a downstream consequence of severe energetic failure (AOP-Wiki, 2026a-e). Empirical support is high for the ROS-to-oxidative-stress and oxidative-stress-to-protein-oxidation relationships and moderate for the protein-oxidation-to-OXPHOS transition, where supporting evidence is observational and cross-stressor rather than from controlled selective-inhibition studies. The ATP-depletion-to-cell-death and cell-death-to-growth KERs have moderate empirical support. Essentiality is high for the OXPHOS-to-ATP relationship and moderate for the remaining KEs. Quantitative understanding is strongest for the OXPHOS-to-ATP KER and low to moderate elsewhere, reflecting the difficulty of predicting organism-level growth outcomes from upstream molecular damage endpoints. The main uncertainties are the causal versus correlational character of the protein oxidation-OXPHOS association, the ATP threshold dependence of cell death mode and severity, and the multifactorial nature of organismal growth as an apical endpoint. AOP 333 is currently most suitable for qualitative and semi-quantitative use in mechanistic interpretation, hazard identification, and support for integrated testing and assessment strategies (OECD, 2018; Becker et al., 2015).

Domain of Applicability

Life Stage Applicability Taxonomic Applicability Sex Applicability

The domain of applicability for AOP 333 is broad across aerobic eukaryotic organisms in which ROS generation, oxidative stress responses, protein oxidation, mitochondrial oxidative phosphorylation, ATP-dependent homeostasis, cell injury/death, and growth are biologically relevant. The AOP is most applicable to biological contexts in which increased ROS is sufficient to induce oxidative protein damage and where mitochondrial ATP production is important for cellular survival and growth.

    The stressor domain includes direct ROS generators, redox-cycling chemicals, metals, nanoparticles, mitochondrial toxicants, hypoxia-reoxygenation, radiation, and inflammatory or pathogen-related stressors. Because the MIE is defined operationally as increased ROS rather than as a stressor-specific molecular interaction, AOP 333 should be applied with attention to evidence that the stressor actually induces oxidative stress and protein oxidation in the biological context under evaluation.

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 protein oxidation is biologically plausible but less directly demonstrated because selective prevention of protein oxidation without altering other oxidative stress processes is experimentally difficult.

 

Key event	Essentiality	Rationale	Experimental manipulation evidence (KE knock-out / inhibition / rescue)	Uncertainties
Event 1115: Reactive oxygen species, increased	Moderate	ROS are causally linked to oxidative stress because oxidative stress occurs when oxidant formation exceeds antioxidant capacity. Antioxidant and radical-scavenging interventions can reduce oxidative stress and downstream oxidative damage in many systems, supporting the importance of ROS as an upstream driver (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 can also function in physiological signaling at low levels; oxidative stress can be sustained by altered antioxidant capacity even when a specific ROS source is removed.
Event 1392: Oxidative stress, increased	Moderate to high	Antioxidant interventions commonly reduce downstream oxidative damage and cell injury. Oxidative stress downstream of radical generation is represented in AOP 478 (AOP-Wiki, 2026a; Schieber and Chandel, 2014; Sies et al., 2017).	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 can be adaptive at low levels and harmful at higher intensity or duration.
Event 1767: Protein oxidation, increased	Moderate	Protein carbonylation and other oxidative modifications impair protein function and can contribute to mitochondrial dysfunction (Dalle-Donne et al., 2006). Cadmium-induced protein carbonylation and actin glutathionylation were reduced by oxidase/NOS inhibitors in mussel hemocytes (Canesi et al., 2010).	Direct (partial): cadmium-induced protein carbonylation and actin glutathionylation reduced by oxidase/NOS inhibitors in mussel hemocytes (Canesi et al., 2010); GSTA4 silencing raised mitochondrial protein carbonylation and target knockdown reduced respiration (Curtis et al., 2012).	Selective rescue of protein oxidation alone is uncommon; protein oxidation can be both causal and a marker of broader damage.
Event 1446: Coupling of OXPHOS, decreased	High	This KE is associated with AOP 263. Recovery of OXPHOS coupling can restore mitochondrial function and ATP production, supporting essentiality of this KE for downstream 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 may sometimes be adaptive and reduce ROS production.
Event 1771: ATP pool, decreased	High	ATP depletion is directly linked to loss of cell viability and can influence the mode of cell death. Intracellular ATP concentration can act as a switch between apoptosis and necrosis (Leist et al., 1997).	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).	Cells may compensate through glycolysis or altered energy allocation.
Event 55: Cell injury/death, increased	Moderate	Cell injury/death is a shared KE used in AOPs 12, 13, 17, 38, and 48. Loss of viable cells provides a plausible mechanism for reduced growth and tissue function (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 decline through reduced proliferation, altered cell size, or developmental delay without overt cell death.
Event 1521: Growth, decreased (AO)	Not applicable (AO)	Growth is the adverse outcome and a regulatory-relevant endpoint across multiple taxa. AOP 263 provides precedent for decreased growth as an AO downstream of mitochondrial bioenergetic impairment (AOP-Wiki, 2026b; 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 may arise from multiple 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
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).
3632: oxidative stress increase leads to protein oxidation increase	High	ROS and related oxidants can modify amino acid side chains, thiols, metal centers, and prosthetic groups, producing carbonylated, glutathionylated, misfolded, aggregated, or degraded proteins (Dalle-Donne et al., 2006; Sies et al., 2017).
3633: protein oxidation increase leads to decreased coupling of OXPHOS	Moderate to high	Mitochondrial OXPHOS depends on intact electron transport complexes, ATP synthase, metabolite carriers, and membrane-associated protein assemblies. Oxidative modification of these proteins can impair electron transfer, proton pumping, membrane potential, and ATP synthesis efficiency (Murphy, 2009; Nicholls and Ferguson, 2013; Sokolov et al., 2019).
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).
2768: decreased ATP pool leads to increased cell injury/death	High	ATP is required for survival, ion homeostasis, membrane repair, proteostasis, and regulated death processes. Severe ATP depletion can switch cellular outcomes toward necrosis or irreversible injury (Leist et al., 1997; Bonora et al., 2012).
2767: increased cell injury/death leads to decreased growth	High	Growth depends on viable cell number, tissue integrity, and biomass accumulation. Increased cell injury/death reduces the cellular basis for growth and is reused across AOPs 12, 13, 17, 38, and 48 (AOP-Wiki, 2026c-g; Conlon and Raff, 1999).

 

Empirical support for KERs

KER	Empirical support call	Rationale	Inconsistencies or evidence gaps
2009: ROS increase leads to oxidative stress increase	High	Paraquat increased ROS and antioxidant enzyme responses in Chlorella vulgaris (Qian et al., 2009). Infection-induced ROS coincided with antioxidant and inflammatory responses in golden pompano (Gao et al., 2022). AOP 478 reports evidence linking free radical generation/energy deposition to oxidative stress (AOP-Wiki, 2026a).	ROS is transient and often measured indirectly; oxidative stress biomarkers vary by assay and taxa.
3632: oxidative stress increase leads to protein oxidation increase	High	Oxidative stressors increase protein carbonyls or related protein oxidation endpoints. Cadmium and hydrogen peroxide increased protein carbonylation and redox modification in Chlamydomonas systems (Zaffagnini et al., 2012). Cadmium induced protein carbonylation and actin glutathionylation in mussel hemocytes (Canesi et al., 2010). Thermal stress in zebrafish increased protein carbonyls with antioxidant responses (Tseng et al., 2011).	Protein oxidation endpoints are heterogeneous; some studies measure total carbonyls whereas others identify specific oxidized proteins.
3633: protein oxidation increase leads to decreased coupling of OXPHOS	Moderate	Evidence links oxidative protein damage or mitochondrial proteome modification with altered mitochondrial function. Age-associated oxidative changes in zebrafish were associated with changes in mitochondrial oxidative status and aconitase activity (Almaida-Pagán et al., 2014). Hypoxia-reoxygenation altered mitochondrial proteome and bioenergetics in Crassostrea gigas (Sokolov et al., 2019).	Many studies measure correlation rather than direct causation; protein oxidation may occur alongside lipid peroxidation or other mitochondrial damage.
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.
2768: decreased ATP pool leads to increased cell injury/death	Moderate to high	ATP depletion and cell death are linked in multiple 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.
2767: increased cell injury/death leads to decreased growth	Moderate	Cell injury/death is reused as a KE in several established AOPs (AOP-Wiki, 2026c-g). Methanol-exposed mouse embryos showed growth reduction and elevated cell death (Abbott et al., 1995). In bivalves, cadmium and temperature interactions caused cellular energy disruption, mortality, and reduced condition/growth-related outcomes (Cherkasov et al., 2006).	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 333 is the quantitative strength and directionality of the protein oxidation to OXPHOS coupling relationship. Protein oxidation can impair mitochondrial enzymes and respiratory complexes, but mitochondrial dysfunction can also enhance ROS generation and thereby increase protein oxidation. AOP 333 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 protein oxidation 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).
3632: oxidative stress increase to protein oxidation increase	Moderate	Protein carbonyl assays and redox proteomics provide quantitative measures of protein oxidation, but response-response relationships are not broadly generalizable across stressors or taxa (Dalle-Donne et al., 2006).
3633: protein oxidation increase to decreased OXPHOS coupling	Low to moderate	Specific oxidation of mitochondrial proteins can be associated with altered mitochondrial function, but predictive quantitative models are not yet established across taxa or stressors (Sokolov et al., 2019).
2203: decreased OXPHOS coupling to decreased ATP pool	High	AOP 263 reports strong quantitative understanding, supported by bioenergetic theory and experimental response-response relationships (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 333 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 333 can support mechanistic interpretation of growth impairment caused by oxidative stressors that induce protein oxidation, 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 protein carbonylation, redox proteomic signatures, 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, oxidative stress biomarkers, protein carbonyl assays, redox proteomics, mitochondrial membrane potential, oxygen consumption rate, ATP content, cytotoxicity assays, and organismal growth measurements.

AOP 333 can support chemical grouping and read-across for stressors that share evidence of oxidative protein damage, mitochondrial bioenergetic impairment, and ATP-associated cell injury. Because oxidative stress and protein oxidation 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 protein oxidation, OXPHOS coupling, ATP depletion, and cell injury/death endpoints that can be connected quantitatively to apical growth outcomes.

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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

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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 

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Event: 1767: Increase, Protein oxidation

Short Name: Increase, Protein oxidation

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 proteins are universal biological macromolecules and many amino-acid residues are susceptible to oxidative modification. The KE is applicable wherever proteins are exposed to oxidants and where oxidative modification can be measured. It is therefore relevant across unicellular algae, invertebrates, fish, mammals, plants and human-derived cell systems. The evidence base is strongest in mammalian toxicology and biomedical studies, but ecotoxicological evidence supports relevance in algae, fish, mollusks and crustaceans.

    The KE is not intrinsically limited by life stage or sex. However, the magnitude and toxicological importance of protein oxidation may be modified by antioxidant capacity, proteasomal and lysosomal degradation capacity, protein turnover, metal ion availability, oxygen availability, temperature, inflammatory status, nutritional status, mitochondrial activity, and exposure duration. Tissues or cells with high metabolic demand, high mitochondrial density, high inflammatory activity, or low proteostatic reserve may be especially susceptible.

    Within the ROS-growth AOP network, this KE functions as a molecular damage event linking oxidative stress to downstream impairment of mitochondrial function and cellular injury. Nevertheless, the KE should remain modular. It may be reused in any AOP in which increased oxidative modification of proteins is measured or inferred as a discrete biological state, regardless of whether the downstream effect is impaired oxidative phosphorylation, cell death, altered signaling, immune dysfunction, neurotoxicity, growth inhibition or another adverse outcome.

Key Event Description

Protein oxidation refers to an increase in oxidative modification of proteins relative to an appropriate control state. Proteins are abundant and chemically diverse macromolecules that contain amino-acid side chains and peptide backbones susceptible to attack by ROS and related oxidants. Oxidation can lead to formation of protein carbonyls, oxidation of sulfur-containing amino acids such as cysteine and methionine, nitration or hydroxylation of aromatic residues, disulfide formation, S-glutathionylation, fragmentation, cross-linking, aggregation, altered folding and changes in enzymatic or structural function (Stadtman and Levine, 2003; Dalle-Donne et al., 2006; Fedorova et al., 2014).

    The KE is defined by the observed or measured increase in oxidatively modified proteins rather than by a particular upstream stressor or downstream consequence. Protein oxidation can be reversible or irreversible depending on the chemical modification. Reversible thiol oxidation, disulfide formation, S-glutathionylation and methionine oxidation may participate in redox signaling and adaptive regulation, whereas irreversible carbonylation, backbone cleavage and protein aggregation are more commonly associated with protein dysfunction, proteostatic burden and cellular injury (Stadtman and Levine, 2003; Dalle-Donne et al., 2006; Reichmann et al., 2018).

    Within oxidative stress AOPs, protein oxidation is an important molecular damage KE because it links redox imbalance to functional impairment of enzymes, structural proteins, signaling proteins and organelle proteins. In the ROS-growth AOP network, oxidation of mitochondrial respiratory proteins, cytoskeletal proteins or metabolic enzymes may contribute to decreased coupling of oxidative phosphorylation, impaired ATP production, altered cell cycle regulation, increased cell injury/death and reduced growth. However, these downstream consequences should be described on separate KER and AOP pages so that KE 1767 remains modular and reusable.

How it is Measured or Detected

Protein oxidation can be measured using biochemical, immunochemical, fluorescence-based and proteomic approaches. No single method captures all forms of protein oxidation. Protein carbonylation is one of the most widely used and relatively stable indicators of oxidative protein damage, but other modifications such as methionine sulfoxide, cysteine oxidation, nitrotyrosine, S-glutathionylation and protein cross-linking may be more appropriate in particular biological contexts. Confidence is highest when the method directly detects a defined oxidized protein modification or oxidized peptide, and lower when broad assays are used without complementary specificity checks.

 

Measurement approach	Endpoint measured	Representative method names	Scientific confidence and limitations
Protein carbonyl assays	Protein carbonyl groups formed by direct oxidation or by adduction of reactive carbonyl species	DNPH derivatization with spectrophotometry, ELISA, immunoblotting or OxyBlot; hydrazide-based probes	Widely used, relatively stable and broadly accepted as a marker of protein oxidation. DNPH methods are sensitive but do not identify individual proteins unless combined with immunoblotting or proteomics. Carbonyls may arise from direct oxidation or from secondary reactions with lipid peroxidation products (Levine et al., 1990; Dalle-Donne et al., 2006; Fedorova et al., 2014).
Redox proteomics	Oxidized proteins or oxidized amino-acid residues at protein or peptide level	2D gel electrophoresis plus anti-DNP immunoblotting; LC-MS/MS redox proteomics; carbonyl-reactive enrichment workflows	High mechanistic value because it can identify protein targets and modification sites. Requires careful sample handling, derivatization or enrichment, and appropriate bioinformatic analysis (McDonagh et al., 2005; Fedorova et al., 2014; Butterfield and Dalle-Donne, 2014).
Thiol oxidation assays	Oxidation state of protein thiols and disulfides	Biotin-switch methods; maleimide labeling; redox Western blot; differential alkylation; thiol redox proteomics	Useful for reversible cysteine oxidation and redox signaling. Interpretation depends on preservation of redox state during sampling and on whether reversible signaling events or irreversible damage are being assessed (Dalle-Donne et al., 2006; Reichmann et al., 2018).
S-glutathionylation assays	Protein S-glutathionylation as a reversible thiol redox modification	Anti-glutathione immunoblotting; redox proteomics; mass spectrometry	Mechanistically informative for redox regulation and oxidative stress responses. It may represent adaptive regulation rather than irreversible damage and should be interpreted in biological context (Dailianis et al., 2009; Zaffagnini et al., 2012).
Nitrotyrosine and other specific oxidized residue assays	Specific oxidized or nitrated amino-acid residues	Anti-nitrotyrosine immunoassays; LC-MS/MS; targeted proteomics	Provides higher chemical specificity for particular oxidant pathways, such as peroxynitrite-associated nitration, but does not capture all protein oxidation. Best used when the expected chemistry is known.
Advanced oxidation protein products and aggregate assays	Bulk oxidized protein products, cross-linked proteins or protein aggregates	AOPP assays; aggregate detection; protein insolubility assays	Useful for broad screening of oxidative protein burden but less specific than defined chemical or proteomic measurements. Should be interpreted as supportive evidence, especially when combined with carbonyl or mass-spectrometric endpoints.

 

References

AOP-Wiki. 2026. Key Event 1767: Increase, Protein oxidation. AOP-Wiki. Available at: https://aopwiki.org/events/1767. Accessed 14 May 2026.

Almaida-Pagán PF, Lucas-Sánchez A, Tocher DR. 2014. Changes in mitochondrial membrane composition and oxidative status during rapid growth, maturation and aging in zebrafish, Danio rerio. Biochimica et Biophysica Acta - Molecular and Cell Biology of Lipids 1841(7):1003-1011. https://doi.org/10.1016/j.bbalip.2014.04.004.

Butterfield DA, Dalle-Donne I. 2014. Redox proteomics: from protein modifications to cellular dysfunction and diseases. Mass Spectrometry Reviews 33(1):1-6. https://doi.org/10.1002/mas.21382.

Dailianis S, Patetsini E, Kaloyianni M. 2009. The role of signaling molecules on actin glutathionylation and protein carbonylation induced by cadmium in hemocytes of mussel Mytilus galloprovincialis. Journal of Experimental Biology 212(22):3612-3620. https://doi.org/10.1242/jeb.031211.

Dalle-Donne I, Aldini G, Carini M, Colombo R, Rossi R, Milzani A. 2006. Protein carbonylation, cellular dysfunction, and disease progression. Journal of Cellular and Molecular Medicine 10(2):389-406. https://doi.org/10.1111/j.1582-4934.2006.tb00407.x.

Fedorova M, Bollineni RC, Hoffmann R. 2014. Protein carbonylation as a major hallmark of oxidative damage: update of analytical strategies. Mass Spectrometry Reviews 33(2):79-97. https://doi.org/10.1002/mas.21381.

Levine RL, Garland D, Oliver CN, Amici A, Climent I, Lenz AG, Ahn BW, Shaltiel S, Stadtman ER. 1990. Determination of carbonyl content in oxidatively modified proteins. Methods in Enzymology 186:464-478. https://doi.org/10.1016/0076-6879(90)86141-H.

Martínez M, Rodríguez-Graña L, Santos L, Denicola A, Calliari D. 2020. Long-term exposure to salinity variations induces protein carbonylation in the copepod Acartia tonsa. Journal of Experimental Marine Biology and Ecology 526:151337. https://doi.org/10.1016/j.jembe.2020.151337.

McDonagh B, Tyther R, Sheehan D. 2005. Carbonylation and glutathionylation of proteins in the blue mussel Mytilus edulis detected by proteomic analysis and Western blotting: actin as a target for oxidative stress. Aquatic Toxicology 73(3):315-326. https://doi.org/10.1016/j.aquatox.2005.03.020.

Mukherjee K, Chio TI, Sackett DL, Bane SL. 2015. Detection of oxidative stress-induced carbonylation in live mammalian cells using a hydrazine-based fluorescent probe. Free Radical Biology and Medicine 84:11-21. https://doi.org/10.1016/j.freeradbiomed.2015.03.011.

Parvez S, Raisuddin S. 2005. Protein carbonyls: novel biomarkers of exposure to oxidative stress-inducing pesticides in freshwater fish Channa punctata (Bloch). Environmental Toxicology and Pharmacology 20(1):112-117. https://doi.org/10.1016/j.etap.2004.11.002.

Reichmann D, Voth W, Jakob U. 2018. Maintaining a healthy proteome during oxidative stress. Molecular Cell 69(2):203-213. https://doi.org/10.1016/j.molcel.2017.12.021.

Sokolov EP, Markert S, Hinzke T, Hirschfeld C, Becher D, Ponsuksili S, Sokolova IM. 2019. Effects of hypoxia-reoxygenation stress on mitochondrial proteome and bioenergetics of the hypoxia-tolerant marine bivalve Crassostrea gigas. Journal of Proteomics 194:99-111. https://doi.org/10.1016/j.jprot.2018.12.009.

Stadtman ER, Levine RL. 2003. Free radical-mediated oxidation of free amino acids and amino acid residues in proteins. Amino Acids 25(3-4):207-218. https://doi.org/10.1007/s00726-003-0011-2.

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.

Zaffagnini M, Bedhomme M, Groni H, Marchand CH, Puppo C, Gontero B, Cassier-Chauvat C, Decottignies P, Lemaire SD. 2012. Glutathionylation in the photosynthetic model organism Chlamydomonas reinhardtii: a proteomic survey. Molecular & Cellular Proteomics 11(2):M111.014142. https://doi.org/10.1074/mcp.M111.014142.

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