AOP ID and Title:

Short Title: ROS leading to growth inhibition via protein oxidation and decreased cell proliferation

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 332) describes a linear route by which increased reactive oxygen species (ROS) can lead to decreased organismal growth through oxidative stress-mediated protein oxidation and subsequent impairment of mitochondrial bioenergetics. Increased ROS is treated operationally as the molecular initiating event because it represents the earliest common measurable redox perturbation shared by diverse chemical and non-chemical stressors in the broader ROS-growth AOP network. Increased ROS leads to oxidative stress, which promotes oxidative modification of proteins. Oxidized proteins may lose catalytic, structural, transport, or regulatory function; they may also misfold, aggregate, or become targeted for degradation. When proteins required for mitochondrial electron transport, ATP synthase function, metabolite transport, or maintenance of mitochondrial membrane potential are oxidatively modified, coupling of oxidative phosphorylation (OXPHOS) can decrease. Reduced OXPHOS coupling decreases the cellular ATP pool, impairs ATP-dependent cell proliferation, and ultimately reduces growth.

AOP 332 reuses and connects established AOP-Wiki components from two major AOP contexts. The upstream ROS/oxidative stress module is associated with AOP 478, in which deposition of energy leads to oxidative stress through free radical generation and oxidative molecular damage (AOP-Wiki, 2026a). AOP 478 provides an AOP-Wiki precedent for oxidative stress as a conserved KE downstream of radical-generating stressors and for protein damage as an oxidative stress consequence. The downstream bioenergetic and growth module is directly associated with AOP 263, which causally links decreased coupling of OXPHOS to growth inhibition through ATP depletion and decreased cell proliferation (AOP-Wiki, 2026b; OECD, 2022; Song and Villeneuve, 2021). Thus, AOP 332 links an oxidative protein damage module to an OECD-endorsed OXPHOS-to-growth module. The AOP is relevant to environmental and human health contexts because ROS generation, protein oxidation, mitochondrial ATP production, cell proliferation, and organismal growth are broadly conserved in aerobic eukaryotes. Empirical support comes from studies in algae, fish, mollusks, mammalian systems, and human cells exposed to metals, hydrogen peroxide, hypoxia-reoxygenation, salinity or temperature stress, endogenous aging, and other oxidative stressors. This AOP can support mechanistic interpretation of oxidative stress-mediated growth impairment, assay selection, chemical prioritization, IATA development, and future quantitative AOP approaches for mitochondrial and oxidative stress-related 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 many amino acid side chains and prosthetic groups are susceptible to oxidation, carbonylation, thiol oxidation, nitration, or other oxidative modifications. Protein oxidation can alter enzyme activity, protein-protein interactions, protein folding, stability, and degradation, and it is widely used as a marker of severe oxidative damage and cellular dysfunction (Dalle-Donne et al., 2006).

AOP 332 was developed to represent the protein oxidation-driven linear route within the broader ROS-growth AOP network. This route was selected because oxidative stress can directly modify proteins, including mitochondrial proteins involved in electron transport, OXPHOS coupling, ATP synthesis, metabolite transport, and maintenance of mitochondrial integrity. Oxidation of mitochondrial proteins can impair the efficiency of electron transfer and proton motive force utilization, thereby providing a mechanistically coherent bridge from oxidative stress to decreased coupling of OXPHOS (Murphy, 2009; Nicholls and Ferguson, 2013; Sokolov et al., 2019). The downstream sequence from decreased coupling of OXPHOS to decreased ATP pool, decreased cell proliferation, and decreased growth is represented in AOP 263 and provides the growth-relevant terminal module for AOP 332 (AOP-Wiki, 2026b; OECD, 2022; Song and Villeneuve, 2021).

Strategy

AOP 332 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 objective 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 332 is one branch of the broader ROS-growth AOP network and because its downstream KEs and KERs overlap with the well-developed mitochondrial bioenergetics AOP 263.

    Reuse of existing AOP-Wiki content was considered at the beginning of development. AOP 478 was reviewed because it provides an AOP-Wiki context for oxidative stress downstream of free radical generation and because it recognizes oxidative molecular damage, including protein damage, as a relevant consequence of oxidative stress. The KE increase in oxidative stress (Event 1392) and the conceptual linkage between radical generation, oxidative stress, and protein modification were therefore aligned with the AOP 478 context. AOP 263 was used as the primary source for the downstream module beginning with decreased coupling of OXPHOS (Event 1446), followed by decreased ATP pool (Event 1771), decreased cell proliferation (Event 1821), and decreased growth (Event 1521). The KERs decreased coupling of OXPHOS leading to decreased ATP pool, decreased ATP pool leading to decreased cell proliferation, and decreased cell proliferation leading to decreased growth were retained in the same causal order as AOP 263, supporting modular reuse and consistency with an OECD-endorsed pathway.

    The literature review and evidence assembly process followed an AI-human hybrid workflow. First, event-specific search terms were developed for the KEs in AOP 332, including reactive oxygen species, oxidative stress, protein oxidation, protein carbonylation, oxidized proteins, mitochondrial protein oxidation, OXPHOS coupling, mitochondrial respiration, mitochondrial membrane potential, ATP depletion, cell proliferation, and growth. Synonyms, assay terms, representative stressors, taxa, and species names were also included. These terms were used in AOP-helpFinder to search PubMed for co-occurrence patterns between key events and mechanistic concepts, following text-mining approaches developed for AOP literature support (Carvaillo et al., 2019; Jornod et al., 2022). Exported records containing PMIDs, titles, abstracts, and matched terms were subjected to overlap analysis to remove redundant records and filter weakly relevant taxa- or endpoint-unrelated literature.

    In the second phase, titles and abstracts from AOP-helpFinder and targeted manual searches were pre-screened using ChatGPT (GPT-4, OpenAI, San Francisco, CA, USA) as an auxiliary prioritization tool. The LLM was used to extract study metadata, including stressor, species, biological system, dose or concentration, and exposure duration; to identify evidence type, including biological plausibility, empirical support, and essentiality; and to flag weight-of-evidence indicators such as dose-response concordance, temporal concordance, incidence concordance, and intervention or rescue evidence. Studies were classified as high, medium, or low relevance. 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. For full texts, LLM-assisted review was used only to organize candidate information; all outputs were verified against the original articles by human experts.

The final phase consisted of manual expert curation and weight-of-evidence evaluation. Experts verified relevance and interpretation of selected studies, extracted data into KER evidence tables, and evaluated biological plausibility, empirical support, essentiality, quantitative understanding, inconsistencies, and modulating factors. Targeted searches were also performed to fill evidence gaps for protein oxidation and mitochondrial dysfunction. Studies were prioritized when they measured two or more KEs in the same system, reported exposure duration and dose or concentration, or provided evidence relevant to concordance across the pathway. Mechanistic reviews and OECD reports were used to support well-established biological plausibility, whereas primary experimental studies were prioritized for empirical support (Dalle-Donne et al., 2006; Canesi et al., 2010; Almaida-Pagán et al., 2014; Sokolov et al., 2019; Song and Villeneuve, 2021; OECD, 2022).

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 332 is considered moderate. Biological plausibility is high for all six KERs in the pathway. The chemical reactivity of ROS with proteins is well established, and the functional consequences of oxidative modification of mitochondrial respiratory proteins for OXPHOS coupling are mechanistically well supported. The downstream module from decreased OXPHOS coupling through ATP depletion, reduced cell proliferation, and decreased growth is directly reused from OECD-endorsed AOP 263, contributing high biological plausibility and established quantitative relationships for this segment (OECD, 2022; Song and Villeneuve, 2021). Empirical support is high for the upstream ROS-to-oxidative-stress and oxidative-stress-to-protein-oxidation relationships, where multiple stressors across algae, fish, mollusks, and mammalian systems demonstrate concordant increases in oxidative stress markers and protein carbonylation or oxidized protein products. Empirical support for the protein oxidation-to-OXPHOS coupling transition (KER 3633) is rated moderate, as evidence from aging, hypoxia-reoxygenation, and metal exposure studies links oxidative mitochondrial proteome changes to altered bioenergetics, but controlled intervention experiments specifically targeting protein oxidation without confounding other oxidative damage processes are limited. Essentiality is rated moderate to high overall, with the strongest direct support for the AOP 263 OXPHOS and ATP segment. Quantitative understanding is highest for the AOP 263-derived downstream module and low to moderate for the protein oxidation-to-OXPHOS transition, where generalizable cross-taxa quantitative models are lacking. The main uncertainties are the causal versus correlational nature of the protein oxidation-OXPHOS relationship, given that lipid peroxidation and other oxidative processes often co-occur, and the variable capacity of proteasomal and chaperone systems to mitigate protein oxidation-related mitochondrial dysfunction. AOP 332 is most suitable for mechanistic interpretation and chemical prioritisation for oxidative stress-related growth impairment (OECD, 2018; Becker et al., 2015).

Domain of Applicability

Life Stage Applicability Taxonomic Applicability Sex Applicability

The domain of applicability for AOP 332 is broad across aerobic eukaryotic organisms in which ROS generation, oxidative stress responses, protein oxidation, mitochondrial oxidative phosphorylation, ATP-dependent cell proliferation, and growth are biologically relevant. The AOP is most directly applicable to organisms or life stages in which growth depends substantially on mitochondrial ATP supply and cell proliferation. It is also applicable to cellular systems used to evaluate oxidative stress, mitochondrial dysfunction, ATP depletion, and proliferation outcomes.

    The stressor domain includes direct oxidants, redox-cycling chemicals, metals, radiation, hypoxia-reoxygenation, temperature or salinity stress, and endogenous oxidative stress. Because the MIE is defined operationally as increased ROS rather than as a chemical-specific interaction, AOP 332 should be applied when evidence demonstrates increased ROS or oxidative stress and when downstream evidence supports protein oxidation and mitochondrial bioenergetic impairment. Important modifiers include antioxidant capacity, protein repair and degradation capacity, mitochondrial reserve capacity, temperature, oxygen availability, nutrient status, species metabolic rate, and growth stage.

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. The strongest direct essentiality evidence is available for the downstream AOP 263 module, where restoring mitochondrial coupling or ATP production can recover downstream bioenergetic and proliferative functions. Essentiality for protein oxidation is mechanistically plausible and supported by intervention and association evidence, but direct experiments showing that selective prevention of protein oxidation blocks all downstream events remain limited.

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 often attenuate oxidative stress and protein oxidation 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 serve physiological signaling roles; increased ROS may not progress if antioxidant systems compensate.
Event 1392: Oxidative stress, increased	Moderate to high	Oxidative stress is required for widespread oxidative protein modification when oxidant production exceeds antioxidant and repair capacity. AOP 478 supports oxidative stress as a central KE downstream of radical generation (AOP-Wiki, 2026a).	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).	Different oxidative stress biomarkers may capture different aspects of redox imbalance.
Event 1767: Protein oxidation, increased	Moderate	Protein carbonylation and related oxidative modifications can impair enzyme activity, protein folding, degradation, and mitochondrial function (Dalle-Donne et al., 2006). Cadmium-induced protein carbonylation and actin glutathionylation in mussel hemocytes were reduced by oxidase/NOS inhibitors, supporting causal involvement of oxidative signaling (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).	Protein oxidation can be cause, consequence, or marker of cellular stress; selective intervention evidence is limited.
Event 1446: Coupling of OXPHOS, decreased	High	This KE is reused from AOP 263. Evidence from AOP 263 supports essentiality because uncoupler removal or restoration of mitochondrial coupling can recover mitochondrial membrane potential and ATP levels (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 be adaptive and may reduce ROS generation depending on context.
Event 1771: ATP pool, decreased	Moderate	ATP depletion is associated with reduced proliferation and cytotoxicity in multiple systems and is a central KE in AOP 263 (AOP-Wiki, 2026b; OECD, 2022).	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 via glycolysis or altered energy allocation.
Event 1821: Cell proliferation, decreased	Moderate	Growth is dependent on cell number and biomass accumulation; AOP 263 supports decreased cell proliferation as a direct link between bioenergetic impairment and growth reduction (AOP-Wiki, 2026b; Conlon and Raff, 1999; OECD, 2022).	Indirect: proliferation deficit links bioenergetic/genotoxic upstream to growth; reused from endorsed AOP 263 with KER 2205 (AOP-Wiki, 2026d; Conlon and Raff, 1999; OECD, 2022; Song and Villeneuve, 2021).	Growth can also be influenced by cell size, nutrient status, development, and cell death.
Event 1521: Growth, decreased (AO)	Not applicable (AO)	Growth is the adverse outcome and a regulatory-relevant endpoint across several OECD and ISO test systems; AOP 263 provides precedent for decreased growth as an AO downstream of mitochondrial bioenergetic impairment (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 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 oxidants and antioxidant defenses; ROS are major cellular oxidants and primary drivers of redox imbalance (Schieber and Chandel, 2014; Sies et al., 2017). AOP 478 provides a curated context for oxidative stress downstream of radical generation (AOP-Wiki, 2026a).
Relationship 3632: oxidative stress increase leads to protein oxidation increase	High	ROS and related oxidants can modify protein side chains, thiols, metal centers, and prosthetic groups, producing carbonylated, glutathionylated, misfolded, or aggregated proteins (Dalle-Donne et al., 2006; Sies et al., 2017).
Relationship 3633: protein oxidation increase leads to decreased coupling of OXPHOS	Moderate to high	Mitochondrial OXPHOS depends on the integrity of electron transport complexes, ATP synthase, carrier proteins, 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).
Relationship 2203: decreased coupling of OXPHOS leads to decreased ATP pool	High	This relationship is reused from 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 2204: decreased ATP pool leads to decreased cell proliferation	High	This relationship is reused from AOP 263. Cell proliferation requires ATP for DNA replication, mitosis, biosynthesis, and maintenance of cellular processes; ATP depletion therefore plausibly reduces proliferation (AOP-Wiki, 2026b; Bonora et al., 2012; OECD, 2022).
Relationship 2205: decreased cell proliferation leads to decreased growth	High	This relationship is reused from AOP 263. Organismal, tissue, and population growth require accumulation of cells and biomass; sustained reduction in proliferation is therefore expected to reduce growth (AOP-Wiki, 2026b; Conlon and Raff, 1999; OECD, 2022).

 

Empirical support for KERs

KER	Empirical support call	Rationale	Inconsistencies or evidence gaps
Relationship 2009: ROS increase leads to oxidative stress increase	High	Multiple studies demonstrate concordance between ROS-producing stressors and oxidative stress biomarkers. Paraquat increased ROS and antioxidant enzyme responses in Chlorella vulgaris (Qian et al., 2009). In fish, infection-induced ROS coincided with antioxidant and inflammatory responses (Gao et al., 2022).	ROS is often transient and indirectly measured; oxidative stress endpoints differ across studies.
Relationship 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.
Relationship 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.
Relationship 2203: decreased coupling of OXPHOS leads to decreased ATP pool	High	This relationship is supported by AOP 263 and by multiple studies of mitochondrial uncouplers and mitochondrial toxicants showing ATP depletion following reduced OXPHOS efficiency (AOP-Wiki, 2026b; OECD, 2022; Song and Villeneuve, 2021).	Cells may transiently compensate through glycolysis or substrate switching.
Relationship 2204: decreased ATP pool leads to decreased cell proliferation	Moderate to high	AOP 263 reports concordance between ATP depletion and decreased cell proliferation across biological systems. ATP content is widely used as a quantitative indicator of cell viability and proliferative capacity (AOP-Wiki, 2026b; Bonora et al., 2012; OECD, 2022).	ATP depletion may lead to either proliferation arrest or cell death depending on severity and duration.
Relationship 2205: decreased cell proliferation leads to decreased growth	Moderate	AOP 263 provides empirical support for this relationship and identifies growth as a biologically and regulatory relevant endpoint downstream of reduced cell proliferation (AOP-Wiki, 2026b; OECD, 2022; Song and Villeneuve, 2021).	Growth integrates many processes, and direct measurement of proliferation and organismal growth in the same study is less common.

 

Inconsistencies and uncertainties

The main uncertainty in AOP 332 is the causal versus correlational nature of the protein oxidation to decreased OXPHOS coupling relationship (KER 3633), because lipid peroxidation and other oxidative processes frequently co-occur and can independently impair mitochondrial function. Controlled intervention experiments that target protein oxidation without confounding other oxidative damage are limited, and the capacity of proteasomal and chaperone systems to mitigate protein-oxidation-related mitochondrial dysfunction varies across taxa and exposure conditions. As with the other AOPs in this network, ROS-mediated growth inhibition can also proceed through genotoxic, lipid peroxidation, and cell death branches, so the protein oxidation branch represented here captures only one mechanistic route. Finally, growth is a multifactorial apical endpoint, which limits quantitative prediction of organismal growth from upstream protein oxidation and bioenergetic events.

Quantitative Consideration

Quantitative understanding of AOP 332 is strongest for the downstream AOP 263 module and more limited for the protein oxidation to OXPHOS transition. Protein oxidation is measurable using protein carbonyl assays, redox proteomics, and targeted detection of oxidized mitochondrial proteins, but translation from the extent of protein oxidation to a quantitative decrement in OXPHOS coupling remains context-dependent.

 

KER	Quantitative understanding call	Rationale
Relationship 2009: ROS increase leads to oxidative stress increase	Low to moderate	ROS and oxidative stress biomarkers can be quantified, but ROS are short-lived and measurement is assay-dependent (Sies et al., 2017).
Relationship 3632: oxidative stress increase leads to protein oxidation increase	Moderate	Protein carbonyls and redox proteomics provide quantitative measures of protein oxidation, but response-response models linking oxidative stress magnitude to protein oxidation are not broadly generalizable (Dalle-Donne et al., 2006).
Relationship 3633: protein oxidation increase leads to decreased coupling of OXPHOS	Low to moderate	Specific oxidation of mitochondrial proteins can be linked to altered mitochondrial function in some systems, but predictive quantitative models are not yet established across taxa or stressors (Sokolov et al., 2019).
Relationship 2203: decreased coupling of OXPHOS leads to decreased ATP pool	High	AOP 263 includes quantitative understanding for OXPHOS coupling and ATP depletion, supported by bioenergetic theory and experimental response-response relationships (AOP-Wiki, 2026b; OECD, 2022; Song and Villeneuve, 2021).
Relationship 2204: decreased ATP pool leads to decreased cell proliferation	Moderate	ATP is often used as a quantitative indicator of cell status and proliferation, but thresholds vary by cell type and stress duration (Bonora et al., 2012; OECD, 2022).
Relationship 2205: decreased cell proliferation leads to decreased growth	Moderate	Quantitative relationships between proliferation and growth exist in developmental and tissue growth biology, but stressor-specific models for this AOP remain limited (Conlon and Raff, 1999; OECD, 2022).

 

BMD/POD-anchored concordance

The following benchmark-dose/point-of-departure (BMD/POD) concordance table anchors AOP 332 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 332 can support mechanistic interpretation of growth impairment caused by oxidative stressors that produce protein oxidation and mitochondrial bioenergetic dysfunction. It is particularly useful for organizing evidence from assays measuring protein carbonyls, redox proteomics, mitochondrial respiration, mitochondrial membrane potential, ATP content, cell proliferation, and organismal growth. Because the downstream module is shared with AOP 263, the AOP can contribute to IATA and NAM-based screening strategies that use mitochondrial function, ATP status, and proliferation as early warning indicators for growth effects.

The AOP may also support chemical prioritization and grouping for stressors that induce ROS generation or oxidative stress and that show evidence for protein oxidation or mitochondrial impairment. Potential stressor classes include metals, redox-active organic chemicals, radiation, hypoxia-reoxygenation, and other environmental conditions that increase oxidative protein damage. The AOP should not be used as a stand-alone quantitative predictor of growth inhibition without additional empirical support, because the protein oxidation to OXPHOS transition remains less quantitatively resolved than the downstream AOP 263 module.

References

Almaida-Pagán, P.F., Lucas-Sánchez, A., & Tocher, D.R. (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

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

AOP-Wiki. (2026b). AOP 263: Uncoupling of oxidative phosphorylation leading to growth inhibition via decreased cell proliferation. Adverse Outcome Pathway Wiki. https://aopwiki.org/aops/263

Ayala, A., Munoz, M.F., & 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

Barata, C., Varo, I., Navarro, J.C., Arun, S., & Porte, C. (2005). Antioxidant enzyme activities and lipid peroxidation in the freshwater cladoceran Daphnia magna exposed to redox cycling compounds. Comparative Biochemistry and Physiology Part C: Toxicology & Pharmacology, 140(2), 175-186. https://doi.org/10.1016/j.cca.2005.01.013

Bonora, M., Patergnani, S., Rimessi, A., De Marchi, E., Suski, J.M., Bononi, A., Giorgi, C., Marchi, S., Missiroli, S., Poletti, F., Wieckowski, M.R., & Pinton, P. (2012). ATP synthesis and storage. Purinergic Signaling, 8(3), 343-357. https://doi.org/10.1007/s11302-012-9305-8

Canesi, L., Ciacci, C., Betti, M., Lorusso, L.C., Marchi, B., Burattini, S., Falcieri, E., & Gallo, G. (2010). The role of signaling molecules on actin glutathionylation and protein carbonylation induced by cadmium in hemocytes of mussel Mytilus galloprovincialis. Journal of Experimental Biology, 213(3), 361-372. https://doi.org/10.1242/jeb.035550

Carvaillo, J.C., Barouki, R., Coumoul, X., & Audouze, K. (2019). Linking bisphenol S to adverse outcome pathways using a combined text mining and systems biology approach. Environmental Health Perspectives, 127(4), 047005. https://doi.org/10.1289/EHP4200

Conlon, I., & Raff, M. (1999). Size control in animal development. Cell, 96(2), 235-244. https://doi.org/10.1016/S0092-8674(00)80563-2

Curtis, J. M., Hahn, W. S., Stone, M. D., Inda, J. J., Droullard, D. J., Kuzmicic, J. P., Donoghue, M. A., Long, E. K., Armien, A. G., Lavandero, S., Arriaga, E., Griffin, T. J., & Bernlohr, D. A. (2012). Protein carbonylation and adipocyte mitochondrial function. Journal of Biological Chemistry, 287(39), 32967-32980. https://doi.org/10.1074/jbc.M112.400663

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

Gao, J., Liu, M., Guo, H., Zhu, K., Liu, B., Liu, B., & Zhang, D. (2022). ROS induced by Streptococcus agalactiae activate inflammatory responses via the TNF-alpha/NF-kappaB signaling pathway in golden pompano Trachinotus ovatus (Linnaeus, 1758). Antioxidants, 11(9), 1809. https://doi.org/10.3390/antiox11091809

Jornod, F., Jaylet, T., Blaha, L., Sarigiannis, D., Tamisier, L., & Audouze, K. (2022). AOP-helpFinder webserver: A tool for comprehensive analysis of the literature to support adverse outcome pathways development. Bioinformatics, 38(4), 1173-1175. https://doi.org/10.1093/bioinformatics/btab750

Murphy, M.P. (2009). How mitochondria produce reactive oxygen species. Biochemical Journal, 417(1), 1-13. https://doi.org/10.1042/BJ20081386

Nicholls, D.G., & Ferguson, S.J. (2013). Bioenergetics 4. Academic Press.

Nicotera, P., Leist, M., & Ferrando-May, E. (1998). Intracellular ATP, a switch in the decision between apoptosis and necrosis. Toxicology Letters, 102-103, 139-142. https://doi.org/10.1016/S0378-4274(98)00298-7

OECD. (2018). Users' handbook supplement to the guidance document for developing and assessing adverse outcome pathways. OECD Series on Adverse Outcome Pathways No. 1. OECD Publishing.

OECD. (2021). Guidance document for the scientific review of adverse outcome pathways. OECD Series on Testing and Assessment No. 344. OECD Publishing.

OECD. (2022). Uncoupling of oxidative phosphorylation leading to growth inhibition via decreased cell proliferation. OECD Series on Adverse Outcome Pathways No. 28. OECD Publishing. https://doi.org/10.1787/f20867c1-en

Qian, H., Chen, W., Sun, L., Jin, Y., Liu, W., & Fu, Z. (2009). Inhibitory effects of paraquat on photosynthesis and the response to oxidative stress in Chlorella vulgaris. Ecotoxicology, 18(5), 537-543. https://doi.org/10.1007/s10646-009-0311-8

Schieber, M., & Chandel, N.S. (2014). ROS function in redox signaling and oxidative stress. Current Biology, 24(10), R453-R462. https://doi.org/10.1016/j.cub.2014.03.034

Sies, H., Berndt, C., & Jones, D.P. (2017). Oxidative stress. Annual Review of Biochemistry, 86, 715-748. https://doi.org/10.1146/annurev-biochem-061516-045037

Sokolov, E.P., Markert, S., Hinzke, T., Hirschfeld, C., Becher, D., Ponsuksili, S., & Sokolova, I.M. (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

Song, Y., & Villeneuve, D.L. (2021). AOP report: Uncoupling of oxidative phosphorylation leading to growth inhibition via decreased cell proliferation. Environmental Toxicology and Chemistry, 40(11), 2951-2963. https://doi.org/10.1002/etc.5197

Tseng, Y.C., Chen, R.D., Lucassen, M., Schmidt, M.M., Dringen, R., Abele, D., & Hwang, P.P. (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, C.H., Puppo, C., Gontero, B., Cassier-Chauvat, C., Decottignies, P., & Lemaire, S.D. (2012). Glutathionylation in the photosynthetic model organism Chlamydomonas reinhardtii: A proteomic survey. Molecular & Cellular Proteomics, 11(8), M111.014142. https://doi.org/10.1074/mcp.M111.014142

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).

References

Akai, K., et al. (2004). "Ability of ferric nitrilotriacetate complex with three pH-dependent conformations to induce lipid peroxidation." Free Radic Res. Sep;38(9):951-62. doi: 10.1080/1071576042000261945

Ashoka, A. H., et al. (2020). "Recent Advances in Fluorescent Probes for Detection of HOCl and HNO." ACS omega, 5(4), 1730-1742. doi:10.1021/acsomega.9b03420

B.H. Park, S.M. Fikrig, E.M. Smithwick Infection and nitroblue tetrazolium reduction by neutrophils: a diagnostic aid Lancet, 2 (1968), pp. 532-534

Bedard, Karen, and Karl-Heinz Krause. 2007. “The NOX Family of ROS-Generating NADPH Oxidases: Physiology and Pathophysiology.” Physiological Reviews 87 (1): 245–313.

Bisht, Shilpa, Muneeb Faiq, Madhuri Tolahunase, and Rima Dada. 2017. “Oxidative Stress and Male Infertility.” Nature Reviews. Urology 14 (8): 470–85.

Brieger, K., S. Schiavone, F. J. Miller Jr, and K-H Krause. 2012. “Reactive Oxygen Species: From Health to Disease.” Swiss Medical Weekly 142 (August): w13659.

Calcerrada, P., et al. (2011). "Nitric oxide-derived oxidants with a focus on peroxynitrite: molecular targets, cellular responses and therapeutic implications." Curr Pharm Des 17(35): 3905-3932.

Chattopadhyay, Sukumar, et al. "Apoptosis and necrosis in developing brain cells due to arsenic toxicity and protection with antioxidants." Toxicology letters 136.1 (2002): 65-76.

Chowdhury, A. R., et al. (2020). "Mitochondria-targeted paraquat and metformin mediate ROS production to induce multiple pathways of retrograde signaling: A dose-dependent phenomenon." Redox Biol. doi: 10.1016/j.redox.2020.101606. PMID: 32604037; PMCID: PMC7327929.

Dickinson, B. C. and Chang C. J. (2011). "Chemistry and biology of reactive oxygen species in signaling or stress responses." Nature chemical biology 7(8): 504-511.

Drew, Barry, and Christiaan Leeuwenburgh. 2002. “Aging and the Role of Reactive Nitrogen Species.” Annals of the New York Academy of Sciences 959 (April): 66–81.

Egea, J., et al. (2017). "European contribution to the study of ROS: A summary of the findings and prospects for the future from the COST action BM1203 (EU-ROS)." Redox biology 13: 94-162.

Flaherty, R. L., et al. (2017). "Glucocorticoids induce production of reactive oxygen species/reactive nitrogen species and DNA damage through an iNOS mediated pathway in breast cancer." Breast Cancer Research, 19(1), 1–13. https://doi.org/10.1186/s13058-017-0823-8

Foote CS. Definition of type I and type II photosensitized oxidation. Photochem Photobiol. 1991;54:659.

Fuloria, S., et al. (2021). "Comprehensive Review of Methodology to Detect Reactive Oxygen Species (ROS) in Mammalian Species and Establish Its Relationship with Antioxidants and Cancer." Antioxidants (Basel, Switzerland) 10(1) 128. doi:10.3390/antiox10010128

Go, Y. M. and Jones, D. P. (2013). "The redox proteome." J Biol Chem 288(37): 26512-26520.

Goud, Anuradha P., Pravin T. Goud, Michael P. Diamond, Bernard Gonik, and Husam M. Abu-Soud. 2008. “Reactive Oxygen Species and Oocyte Aging: Role of Superoxide, Hydrogen Peroxide, and Hypochlorous Acid.” Free Radical Biology & Medicine 44 (7): 1295–1304.

Granger, D. N. and Kvietys, P. R. (2015). "Reperfusion injury and reactive oxygen species: The evolution of a concept" Redox Biol. doi: 10.1016/j.redox.2015.08.020. PMID: 26484802; PMCID: PMC4625011.

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 119(5): e39-75.

Griendling, Kathy K., Rhian M. Touyz, Jay L. Zweier, Sergey Dikalov, William Chilian, Yeong-Renn Chen, David G. Harrison, Aruni Bhatnagar, and American Heart Association Council on Basic Cardiovascular Sciences. 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 119 (5): e39–75.

ICH. ICH Guideline S10 Guidance on Photosafety Evaluation of Pharmaceuticals.: International Council on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use; 2014.

Itziou, A., et al. (2011). "In vivo and in vitro effects of metals in reactive oxygen species production, protein carbonylation, and DNA damage in land snails Eobania vermiculata." Archives of Environmental Contamination and Toxicology, 60(4), 697–707. https://doi.org/10.1007/s00244-010-9583-5

Ji, W. O., et al. "Quantitation of the ROS production in plasma and radiation treatments of biotargets." Sci Rep. 2019 Dec 27;9(1):19837. doi: 10.1038/s41598-019-56160-0. PMID: 31882663; PMCID: PMC6934759.

Kruk, J. and Aboul-Enein, H. Y. (2017). "Reactive Oxygen and Nitrogen Species in Carcinogenesis: Implications of Oxidative Stress on the Progression and Development of Several Cancer Types." Mini-Reviews in Medicinal Chemistry, 17:11. doi:10.2174/1389557517666170228115324

Lee, D. Y., et al. (2020). "PEGylated Bilirubin-coated Iron Oxide Nanoparticles as a Biosensor for Magnetic Relaxation Switching-based ROS Detection in Whole Blood." Theranostics, 10(5), 1997-2007. doi:10.7150/thno.39662

Li, Z., et al. (2020). "Inhibition of MiR-25 attenuates doxorubicin-induced apoptosis, reactive oxygen species production and DNA damage by targeting pten." International Journal of Medical Sciences, 17(10), 1415–1427. https://doi.org/10.7150/ijms.41980

Liou, G. Y. and Storz, P. "Reactive oxygen species in cancer." Free Radic Res. 2010 May;44(5):479-96. doi:10.3109/10715761003667554. PMID: 20370557; PMCID: PMC3880197.

Lu, Y., et al. (2010). "Phosphatidylinositol-3-kinase/akt regulates bleomycin-induced fibroblast proliferation and collagen production." American journal of respiratory cell and molecular biology, 42(4), 432–441. https://doi.org/10.1165/rcmb.2009-0002OC

Onoue, S., et al. (2013). "Establishment and intra-/inter-laboratory validation of a standard protocol of reactive oxygen species assay for chemical photosafety evaluation." J Appl Toxicol. 33(11):1241-50. doi: 10.1002/jat.2776. Epub 2012 Jun 13. PMID: 22696462.

Onoue S, Hosoi K, Toda T, Takagi H, Osaki N, Matsumoto Y, et al. Intra-/inter-laboratory validation study on reactive oxygen species assay for chemical photosafety evaluation using two different solar simulators. Toxicology in vitro : an international journal published in association with BIBRA. 2014;28:515-23.

Onoue S, Hosoi K, Wakuri S, Iwase Y, Yamamoto T, Matsuoka N, et al. Establishment and intra-/inter-laboratory validation of a standard protocol of reactive oxygen species assay for chemical photosafety evaluation. Journal of applied toxicology : JAT. 2013;33:1241-50.

Onoue S, Kawamura K, Igarashi N, Zhou Y, Fujikawa M, Yamada H, et al. Reactive oxygen species assay-based risk assessment of drug-induced phototoxicity: classification criteria and application to drug candidates. J Pharm Biomed Anal. 2008;47:967-72.

Onoue S, Seto Y, Gandy G, Yamada S. Drug-induced phototoxicity; an early in vitro identification of phototoxic potential of new drug entities in drug discovery and development. Current drug safety. 2009;4:123-36.

Onoue S, Tsuda Y. Analytical studies on the prediction of photosensitive/phototoxic potential of pharmaceutical substances. Pharmaceutical research. 2006;23:156-64.

Ozcan, Ayla, and Metin Ogun. 2015. “Biochemistry of Reactive Oxygen and Nitrogen Species.” In Basic Principles and Clinical Significance of Oxidative Stress, edited by Sivakumar Joghi Thatha Gowder. Rijeka: IntechOpen.

Parrish, A. R. 2010. “2.27 - Hypoxia/Ischemia Signaling.” In Comprehensive Toxicology (Second Edition), edited by Charlene A. McQueen, 529–42. Oxford: Elsevier.

PCPC. PCPC 2014 safety evaluation guidelines; Chapter 7: Evaluation of Photoirritation and Photoallergy potential. Personal Care Products Council; 2014.

Ramos, M. F. P., et al. (2018). "Xanthine oxidase inhibitors and sepsis." Int J Immunopathol Pharmacol. 32:2058738418772210. doi:10.1177/2058738418772210

Ravanat, J. L., et al. (2014). "Radiation-mediated formation of complex damage to DNA: a chemical aspect overview." Br J Radiol 87(1035): 20130715.

Schutzendubel, A. and Polle, A. (2002). "Plant responses to abiotic stresses: heavy metal-induced oxidative stress and protection by mycorrhization." Journal of Experimental Botany, 53(372), 1351–1365. https://doi.org/10.1093/jexbot/53.372.1351

Seto Y, Kato M, Yamada S, Onoue S. Development of micellar reactive oxygen species assay for photosafety evaluation of poorly water-soluble chemicals. Toxicology in vitro : an international journal published in association with BIBRA. 2013;27:1838-46.

Sharma, Gunjan, Nishant Kumar Rana, Priya Singh, Pradeep Dubey, Daya Shankar Pandey, and Biplob Koch. 2017. “p53 Dependent Apoptosis and Cell Cycle Delay Induced by Heteroleptic Complexes in Human Cervical Cancer Cells.” Biomedicine & Pharmacotherapy = Biomedecine & Pharmacotherapie 88 (April): 218–31.

Silva, R., et al. (2019). "Light exposure during growth increases riboflavin production, reactive oxygen species accumulation and DNA damage in Ashbya gossypii riboflavin-overproducing strains." FEMS Yeast Research, 19(1), 1–7. https://doi.org/10.1093/femsyr/foy114

Tsuchiya K, et al. (2005). "Oxygen radicals photo-induced by ferric nitrilotriacetate complex." Biochim Biophys Acta. 1725(1):111-9. doi:10.1016/j.bbagen.2005.05.001

Wang, J., et al. (2017). "Glucocorticoids Suppress Antimicrobial Autophagy and Nitric Oxide Production and Facilitate Mycobacterial Survival in Macrophages." Scientific reports, 7(1), 982. https://doi.org/10.1038/s41598-017-01174-9

Wang, X., et al. (2013). "Imaging ROS signaling in cells and animals." Journal of molecular medicine 91(8): 917-927.

Yen, Cheng Chien, et al. "Inorganic arsenic causes cell apoptosis in mouse cerebrum through an oxidative stress-regulated signaling pathway." Archives of toxicology 85 (2011): 565-575.

Yuan, Yan, et al. "Cadmium-induced apoptosis in primary rat cerebral cortical neurons culture is mediated by a calcium signaling pathway." PloS one 8.5 (2013): e64330.

Zhang, Z., et al. (2011). "Reactive oxygen species mediate arsenic induced cell transformation and tumorigenesis through Wnt/β-catenin pathway in human colorectal adenocarcinoma DLD1 cells. " Toxicology and Applied Pharmacology, 256(2), 114-121. doi:10.1016/j.taap.2011.07.016

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 

Raimondi, V., F. Ciccarese and V. Ciminale. (2020), “Oncogenic pathways and the electron transport chain: a dangeROS liason”, British Journal of Cancer, Vol. 122/2, Nature Portfolio, London, https://doi.org/10.1038/s41416-019-0651-y 

Seen, S. and L. Tong. (2018), “Dry eye disease and oxidative stress”, Acta Ophthalmologica, Vol. 96/4, John Wiley & Sons, Inc., Hoboken, https://doi.org/10.1111/aos.13526 

Ungvari, Z. et al. (2013), “Ionizing Radiation Promotes the Acquisition of a Senescence-Associated Secretory Phenotype and Impairs Angiogenic Capacity in Cerebromicrovascular Endothelial Cells: Role of Increased DNA Damage and Decreased DNA Repair Capacity in Microvascular Radiosensitivity”, The Journals of Gerontology Series A: Biological Sciences and Medical Sciences, Vol. 68/12, Oxford University Press, Oxford, https://doi.org/10.1093/gerona/glt057.  

 

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 

Wang, H. et al. (2019), “Radiation-induced heart disease: a review of classification, mechanism and prevention”, International Journal of Biological Sciences, Vol. 15/10, Ivyspring International Publisher, Sydney, https://doi.org/10.7150/ijbs.35460  

Zhang, R. et al. (2009), “Blockade of AT1 receptor partially restores vasoreactivity, NOS expression, and superoxide levels in cerebral and carotid arteries of hindlimb unweighting rats”, Journal of applied physiology, Vol. 106/1, American Physiological Society, Rockville, https://doi.org/10.1152/japplphysiol.01278.2007. 

Zhao, R. Z. et al. (2019), “Mitochondrial electron transport chain, ROS generation and uncoupling”, International journal of molecular medicine, Vol. 44/1, Spandidos Publishing Ltd., Athens, https://doi.org/10.3892/ijmm.2019.4188 

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: 1821: Decrease, Cell proliferation

Short Name: Decrease, Cell proliferation

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 applicable to all eukaryotes, as most organisms are known to use cell proliferation to achieve growth.

 

Life stage applicability domain

This key event is in general applicable to all life stages. As cell proliferation not only occurs in developing organisms, but also in adults.

 

Sex applicability domain

This key event is sex-unspecific, as both genders use the same cell proliferation mechanisms.

Key Event Description

Decreased cell proliferation describes the outcome of reduced cell division and cell growth. Cell proliferation is considered the main mechanism of tissue and organismal growth (Conlon 1999). Decreased cell proliferation has been associated with abnormal growth-factor signaling and cellular energy depletion (DeBerardinis 2008).

How it is Measured or Detected

Multiple types of in vitro bioassays can be used to measure this key event:

• ToxCast high-throughput screening bioassays such as “BSK_3C_Proliferation”, “BSK_CASM3C_Proliferation” and “BSK_SAg_Proliferation” can be used to measure cell proliferation status.
• Commercially available methods such as the well-established 5-bromo-2’-deoxyuridine (BrdU) (Raza 1985; Muir 1990) or 5-ethynyl-2’-deoxyuridine (EdU) assay. Both assays measure DNA synthesis in dividing cells to indicate proliferation status.

References

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

DeBerardinis RJ, Lum JJ, Hatzivassiliou G, Thompson CB. 2008. The biology of cancer: metabolic reprogramming fuels cell growth and proliferation. Cell Metabolism 7:11-20. DOI: https://doi.org/10.1016/j.cmet.2007.10.002.

Muir D, Varon S, Manthorpe M. 1990. An enzyme-linked immunosorbent assay for bromodeoxyuridine incorporation using fixed microcultures. Analytical Biochemistry 185:377-382. DOI: https://doi.org/10.1016/0003-2697(90)90310-6.

Raza A, Spiridonidis C, Ucar K, Mayers G, Bankert R, Preisler HD. 1985. Double labeling of S-phase murine cells with bromodeoxyuridine and a second DNA-specific probe. Cancer Research 45:2283-2287.

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