AOP ID and Title:

Short Title: ROS leading to growth inhibition via oxidative DNA damage and cell cycle disruption

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 324) describes a linear genotoxic route by which increased reactive oxygen species (ROS) can lead to decreased organismal growth. In this AOP, increased ROS is treated operationally as the molecular initiating event (MIE) because it represents the earliest common measurable redox perturbation shared by many stressors within the broader ROS-mediated AOP networks. Increased ROS leads to oxidative stress, which causes oxidative DNA damage. When oxidative DNA lesions exceed or impair repair capacity, inadequate DNA repair can occur, allowing DNA strand breaks to accumulate. Strand breaks activate cell cycle checkpoint responses and disrupt progression through the cell cycle. Sustained cell cycle disruption reduces cell proliferation, and reduced cell proliferation ultimately contributes to decreased growth.

    The AOP reuses and connects existing AOP-Wiki components, including key events (KEs) and key event relationships (KERs) from OECD/WPHA-WNT endorsed AOPs. In particular, the oxidative DNA damage module is derived from AOP 296, the oxidative stress and DNA damage context is supported by AOP 478, the cell-cycle disruption KE is shared with AOP 212, and the link from decreased cell proliferation to decreased growth is reused from AOP 263 (AOP-Wiki, 2026a, 2026b, 2026c, 2026d; OECD, 2022, 2023; Carrothers et al., 2025). The AOP is biologically plausible across aerobic eukaryotes because ROS metabolism, antioxidant defenses, DNA damage response pathways, DNA repair, cell cycle regulation, and growth processes are broadly conserved. Empirical support is derived from studies in algae, fish embryos and cell lines, mammalian cells, and other systems exposed to oxidative or genotoxic stressors. The AOP is expected to be useful for mechanistic interpretation of oxidative stress-related toxicity, support of integrated approaches to testing and assessment (IATA), and prioritization of stressors that produce oxidative DNA damage and growth impairment.

 

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 are also generated in response to environmental stressors. At controlled levels, ROS participate in redox signaling, while excessive ROS can disturb redox homeostasis and initiate oxidative damage to cellular macromolecules (Schieber and Chandel, 2014; Sies et al., 2017). DNA is a major target of oxidative attack. Oxidative DNA lesions such as 8-oxo-2'-deoxyguanosine and other oxidized bases can arise endogenously or following toxic insult, and these lesions may contribute to mutation, strand break formation, and activation of DNA damage responses if they are not repaired correctly or efficiently (Cooke et al., 2003; OECD, 2023).

This AOP was developed to represent the DNA damage-driven linear route within the broader ROS-growth AOP network. The route was selected because oxidative DNA damage is a well-established consequence of oxidative stress and because downstream events such as inadequate DNA repair, strand breaks, cell cycle disruption, and reduced cell proliferation provide a mechanistically coherent bridge between molecular damage and decreased organismal growth (Cuddihy and O'Connell, 2003; Conlon and Raff, 1999; OECD, 2022; OECD, 2023). The AOP was therefore designed to provide a focused, reviewable linear representation of one major mechanistic branch by which excessive ROS can impair growth.

Strategy

AOP 324 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 intent was not to create a fully de novo set of biological objects, but to assemble a linear AOP from established and reusable AOP-Wiki components wherever possible. This modular strategy is important because the AOP is part of a broader ROS-growth AOP network and because its individual KEs and KERs are expected to be reused in other oxidative stress, genotoxicity, and growth impairment AOPs.

    Existing AOP-Wiki content and OECD-endorsed AOPs were reviewed at an early stage to identify KEs and KERs that could be reused directly, adapted, or used as supporting context. AOP 296 was the primary source for the oxidative DNA damage module. It is an endorsed AOP describing oxidative DNA damage leading to chromosomal aberrations and mutations and includes KE 1634 (Increase, Oxidative DNA damage), KE 155 (Inadequate DNA repair), KE 1635 (Increase, DNA strand breaks), and relationships involving oxidative DNA damage, inadequate DNA repair, and strand break formation (AOP-Wiki, 2026b; OECD, 2023). AOP 478, an endorsed AOP on deposition of energy leading to cataracts, provided additional support for the upstream oxidative stress context, including KE 1392 (Oxidative stress), KE 1634, KE 155, KE 1635, and the relationship from oxidative stress to oxidative DNA damage in a radiation-relevant setting (AOP-Wiki, 2026a; Carrothers et al., 2025). AOP 212 was reviewed because it contains KE 1505 (Cell cycle, disrupted) and evidence that disruption of cell-cycle regulation can lead to downstream changes in cell fate (AOP-Wiki, 2026c). AOP 263 was reviewed because it is an endorsed AOP linking decreased cell proliferation to decreased growth, and AOP 324 reuses the downstream KE 1821 (Decrease, Cell proliferation), AO 1521 (Decrease, Growth), and KER 2205 (Decrease, Cell proliferation leads to Decrease, Growth) from that AOP (AOP-Wiki, 2026d; OECD, 2022; Song and Villeneuve, 2021).

    In accordance with the OECD AOP coaching checklist (ver. 2024-10-30), the lead author (Y. Song) have communicated with the authors of the following existing KEs and KERs that are reused or expanded in this AOPN: KE 1115 (Mystery of ROS consortium, coordinated by S. Tanabe, NIHS Japan); KE 1392, KE 1634, KE 155, KE 1635, KER 2810, KER 1909, KER 1910 (AOP 296 and AOP 478: C. Yauk, University of Ottawa; V. Chauhan, Health Canada); KE 1505 (AOP 212: S. Tanabe, NIHS Japan); KE 55 (AOPs 12, 13, 17, 38, 48: relevant corresponding authors notified); KE 1446, KE 1771, KE 1821, KE 1521, KER 2203, KER 2204, KER 2205 (AOP 263: Y. Song, NIVA). Notification documentation is available from the corresponding author on request.

    The resulting AOP 324 therefore represents an upstream extension and re-routing of established AOP-Wiki knowledge. Compared with AOP 296, AOP 324 extends upstream from oxidative DNA damage to increased ROS and oxidative stress and extends downstream from DNA damage response biology to decreased cell proliferation and growth. Compared with AOP 263, it reuses the final growth-relevant segment but provides a different upstream causal route, namely oxidative DNA damage and cell-cycle disruption rather than mitochondrial uncoupling and ATP depletion. Compared with AOP 478, it reuses the oxidative stress-DNA damage portion of the radiation AOP but directs that conserved genotoxic sequence toward growth inhibition rather than cataract formation. Compared with AOP 212, it reuses cell-cycle disruption as a modular KE but places it in the context of DNA strand break-mediated checkpoint activation rather than histone deacetylase inhibition.

    The literature review and evidence assembly process followed an AI-human hybrid workflow. The first phase consisted of AOP-helpFinder searching and preliminary analysis. Search terms were developed for each event in the pathway, including KE names, common synonyms, endpoint terms, assay terms, taxonomic descriptors, and relevant species names. These terms were used in AOP-helpFinder to search PubMed for co-occurrence patterns between key events and related mechanistic concepts, following published approaches for literature mining in support of AOP development (Carvaillo et al., 2019; Jornod et al., 2022). The exported results included PMIDs, titles, abstracts, and matched key-event terms. These outputs were subjected to overlap analysis to remove redundant records and to filter the initial literature pool, including elimination of clearly irrelevant records and separation of taxa-related evidence where needed.

    The second phase consisted of ChatGPT (OpenAI, San Francisco, CA, USA)-assisted screening. Titles and abstracts from AOP-helpFinder, together with records identified from targeted manual searches, were pre-screened using an large language model (LLM) as an auxiliary prioritization tool. The purpose of this step was not to replace expert judgment, but to increase efficiency and consistency during early evidence triage. The LLM was used to extract study metadata, including stressor, species, biological system, dose or concentration, and exposure duration; identify the evidence type represented in each study, such as biological plausibility, empirical support, or essentiality; and flag weight-of-evidence indicators including dose-response concordance, temporal concordance, incidence concordance, and intervention or rescue evidence. Studies were provisionally classified as high relevance, medium relevance, or low relevance.

    High-relevance studies were retrieved for full-text review, whereas medium-relevance studies were retained as potential supporting evidence. Low-relevance studies were documented as low priority and excluded from detailed curation. For studies moved forward to full-text review, a second LLM-assisted pass was used to organize relevant information from the full paper. All LLM-generated outputs were checked directly against the original article text by human reviewers. The LLM was therefore used only as a screening and structuring aid, not as an independent evaluator of the evidence.

    Data and methods availability: The literature evidence triage records, including AOP-helpFinder search term libraries, ChatGPT (OpenAI, San Francisco, CA, USA) screening outputs, and human reviewer verification notes, are available from the corresponding author (you.song@niva.no) upon request. All ChatGPT-assisted screening outputs were verified against the original article text by at least one human expert reviewer before any evidence was accepted into KER evidence tables. ChatGPT was used only as an auxiliary prioritization and metadata-extraction tool and not as an independent evaluator of scientific content. The final snapshot PDF of this AOP and the review process PDF will be deposited at the AOP-Wiki forum following completion of the coaching compliance check.

    The final phase consisted of manual expert curation and weight-of-evidence evaluation. Domain experts verified the relevance and interpretation of the literature selected in the earlier stages, resolved ambiguous cases, and extracted information to populate KER evidence tables. These tables captured the biological system studied, stressor, method, endpoint, result, concordance pattern, weight-of-evidence category, and bibliographic source. Expert review was then used to evaluate the evidence for each KER in terms of biological plausibility, empirical support, essentiality, quantitative understanding, and evidence gaps. Targeted manual searches were also used to fill specific gaps for ROS biology, oxidative DNA damage, DNA repair, DNA strand breaks, DNA damage response, cell cycle disruption, cell proliferation, and growth inhibition. Studies were prioritized when they measured two or more KEs in the same biological system, reported exposure time and dose or concentration, or provided evidence relevant to dose-response, temporal, or incidence concordance. Mechanistic reviews and OECD reports were used primarily to support biological plausibility, whereas primary experimental studies were prioritized for empirical support wherever possible (Cooke et al., 2003; Cuddihy and O'Connell, 2003; Qian et al., 2009; Hlavová et al., 2011; Quevedo et al., 2021; OECD, 2023).

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 (WoE) supporting AOP 324 is considered moderate. Biological plausibility is high for all seven KERs in the pathway, reflecting well-established mechanistic connections between ROS accumulation, oxidative stress, oxidative DNA damage, inadequate DNA repair, DNA strand break formation, cell cycle checkpoint activation, reduced cell proliferation, and decreased growth. This biological coherence is reinforced by the reuse of curated KEs and KERs from OECD-endorsed AOPs 263, 296, 478, and 212, which independently support each module in the pathway. Empirical support is high for the upstream (ROSàoxidative stress, oxidative stressàDNA damage relationships), and decreases progressively toward the downstream cell cycle disruption and reduced cell proliferation events, where cross-KE studies in the same biological system are less common. Essentiality of the KEs is rated moderate for most events, reflecting mechanistic support and some intervention evidence but the absence of fully selective, pathway-specific blocking experiments across the whole AOP. Quantitative understanding is low to moderate for most KERs, with the exception of the cell proliferationàgrowth relationship reused from AOP 263, which has moderate quantitative support. The main uncertainties include the relative contribution of the genotoxic route compared with other branches of the broader ROS-growth AOP network, the dual role of ROS in physiological signaling versus toxicological damage, and the multifactorial nature of growth as an apical endpoint. Given the current state of evidence, AOP 324 is most suitable for qualitative and semi-quantitative applications, including mechanistic interpretation of oxidative DNA-damage-driven growth impairment, chemical prioritization, and support for integrated approaches to testing and assessment (IATA). More quantitative regulatory applications will require further empirical studies measuring multiple KEs in the same biological system and under the same stressor exposure (OECD, 2018; Becker et al., 2015).

Domain of Applicability

Life Stage Applicability Taxonomic Applicability Sex Applicability

The biological domain of applicability of AOP 324 is defined by the conservation of the KEs and KERs linking oxidative DNA damage to impaired proliferation and growth. The AOP is applicable to aerobic eukaryotic systems in which ROS can oxidize DNA, DNA repair and checkpoint responses regulate genomic integrity, cell cycle progression determines proliferation, and proliferation contributes to growth. The AOP is most relevant to developmental or actively growing systems, including algae, embryos, larvae, juveniles, and proliferative tissues.

The stressor domain is broad but not unlimited. Stressors are relevant when they generate ROS, impair antioxidant defenses, induce oxidative DNA lesions, or produce DNA strand breaks through mechanisms that converge on oxidative damage and checkpoint activation. Examples include redox-cycling organic chemicals, peroxides, metals, nanoparticles, ionizing radiation, ultraviolet radiation, and other stressors capable of producing oxidative DNA damage. The AOP should not be used where decreased growth is driven primarily by mechanisms unrelated to oxidative DNA damage or cell-cycle disruption.

Essentiality of the Key Events

Essentiality was evaluated at the AOP level by considering whether modification of an upstream KE would be expected to prevent, attenuate, or alter downstream KEs and/or the AO. Because many KEs in this AOP represent conserved cellular stress-response processes, direct essentiality evidence is strongest for some biological modules and weaker for others. Evidence is summarized below.

 

Key event	Essentiality	Rationale	Experimental manipulation evidence (KE knock-out / inhibition / rescue)	Uncertainties
Event 1115: Reactive oxygen species, increased	Moderate	ROS are causally linked to oxidative stress because oxidative stress occurs when oxidant formation exceeds antioxidant capacity. Antioxidant and radical-scavenging interventions can reduce oxidative stress and oxidative DNA damage in many systems, supporting the importance of ROS as an upstream driver (Schieber and Chandel, 2014; Sies et al., 2017; OECD, 2023).	Indirect: antioxidant and ROS-scavenger pre-treatment reduces oxidative stress and downstream damage across oxidative-stress models (Schieber and Chandel, 2014; Sies et al., 2017). No selective single-source ROS knock-out is available.	ROS can also function in physiological signaling at low levels; oxidative stress can be sustained by altered antioxidant capacity even when a specific ROS source is removed.
Event 1392: Oxidative stress, increased	High	Oxidative stress provides the biochemical context for oxidative DNA damage. Excess ROS and redox imbalance can oxidize DNA bases and promote strand breaks; AOP 478 and AOP 296 both use oxidative stress/oxidative DNA damage relationships as central components of endorsed AOP logic (AOP-Wiki, 2026a, 2026b; Cooke et al., 2003; Carrothers et al., 2025; OECD, 2023).	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).	Cellular antioxidant and DNA repair capacity can delay or prevent progression to downstream events.
Event 1634: Oxidative DNA damage, increased	Moderate to high	AOP 296 identifies oxidative DNA damage as a core initiating event for irreversible genomic damage and reports support from studies using ROS scavengers and DNA repair modulation (AOP-Wiki, 2026b; OECD, 2023). Oxidative lesions such as 8-oxo-dG are mechanistically linked to repair demand and strand break formation (Cooke et al., 2003).	Indirect: ROS-scavenger and DNA-repair-modulation studies referenced in endorsed AOP 296 alter oxidative DNA lesion burden (AOP-Wiki, 2026b; OECD, 2023; Cooke et al., 2003).	Direct intervention studies that isolate oxidative DNA damage while keeping other ROS-mediated damage constant are limited.
Event 155: Inadequate DNA repair, increased	Moderate	DNA repair capacity determines whether oxidative lesions are correctly resolved or persist as repair intermediates and strand breaks. AOP 296 explicitly includes inadequate DNA repair as a key event connecting oxidative DNA damage to downstream genomic damage (AOP-Wiki, 2026b; OECD, 2023).	Indirect: repair-capacity modulation changes strand-break persistence; included as a KE in endorsed AOP 296 (AOP-Wiki, 2026b; OECD, 2023).	Repair systems differ by lesion type, cell-cycle phase, species, and tissue; direct essentiality evidence is context-specific.
Event 1635: DNA strand breaks, increased	Moderate	DNA strand breaks are strong activators of DNA damage checkpoint signaling and are central to the transition from molecular damage to cell-cycle disruption. AOP 296 and AOP 478 both include DNA strand breaks in genotoxic pathways downstream of oxidative stress or oxidative DNA damage (AOP-Wiki, 2026a, 2026b; Carrothers et al., 2025; OECD, 2023).	Indirect: strand-break burden tracks with checkpoint activation; shared with endorsed AOPs 296 and 478 (AOP-Wiki, 2026a, 2026b; OECD, 2023).	DNA strand breaks may arise from direct DNA attack, repair intermediates, or replication stress; separating these routes can be difficult.
Event 1505: Cell cycle disruption, increased	Moderate	Cell-cycle disruption is essential for translating DNA damage into reduced proliferation. AOP 212 reuses cell-cycle disruption as a key event in an endorsed pathway, and DNA damage checkpoint literature supports the causal role of checkpoint activation in delaying or arresting cell-cycle progression (AOP-Wiki, 2026c; Cuddihy and O'Connell, 2003).	Indirect: checkpoint activation following DNA damage demonstrated in algae and zebrafish cells (Hlavóvá et al., 2011; Quevedo et al., 2021); KE reused from endorsed AOP 212 (AOP-Wiki, 2026c).	Transient arrest may allow repair and recovery; sustained arrest is more clearly linked to decreased proliferation.
Event 1821: Cell proliferation, decreased	Moderate	Reduced proliferation is a direct determinant of tissue and organismal growth. AOP 263 reuses this KE and KER 2205 as the final step from decreased proliferation to decreased growth (AOP-Wiki, 2026d; OECD, 2022; Song and Villeneuve, 2021).	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 is multifactorial and can also be influenced by energy allocation, nutrition, endocrine signaling, and cell death.
Event 1521: Growth, decreased (AO)	Not applicable (AO)	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).	Not applicable (AO).

 

Weight of Evidence Summary

The evidence assessment is organized by KER. Calls follow the OECD framework for biological plausibility, empirical support, and quantitative understanding (OECD, 2018, 2021).

 

Biological plausibility of KERs

KER	Evidence	Rationale
Relationship 2009: ROS increase leads to oxidative stress increase	High	The relationship is mechanistic and widely accepted: oxidative stress reflects an imbalance between oxidants and antioxidant defenses, and ROS are the dominant oxidant species represented in this AOP. AOP 478 also describes deposition of energy leading to ROS production and oxidative stress (Schieber and Chandel, 2014; Sies et al., 2017; AOP-Wiki, 2026a; Carrothers et al., 2025).
Relationship 2810: oxidative stress increase leads to oxidative DNA damage increase	High	ROS generated under oxidative stress can oxidize DNA bases and damage the sugar-phosphate backbone. This KER is shared with endorsed AOP 478 and provides the upstream connection into the oxidative DNA damage module of AOP 296 (AOP-Wiki, 2026a, 2026b; Cooke et al., 2003; OECD, 2023).
Relationship 1909: oxidative DNA damage increase leads to inadequate DNA repair increase	High	Oxidative DNA lesions increase demand on base excision repair and related repair processes. When lesion burden or repair intermediates exceed repair capacity, repair becomes inadequate. This relationship is used in AOP 296 and AOP 478 (AOP-Wiki, 2026a, 2026b; OECD, 2023).
Relationship 1910: inadequate DNA repair increase leads to DNA strand breaks increase	Moderate to high	Inadequate or incomplete repair can generate or allow persistence of strand breaks, including repair intermediates and replication-associated breaks. AOP 296 includes this relationship as part of the oxidative DNA damage module (AOP-Wiki, 2026b; OECD, 2023).
Relationship 3480: DNA strand breaks increase leads to cell cycle disruption increase	High	DNA strand breaks activate DNA damage response pathways, including ATM/ATR and checkpoint signaling, that delay or arrest cell-cycle progression to allow repair or prevent propagation of damage (Cuddihy and O'Connell, 2003; OECD, 2023).
Relationship 3363: cell cycle disruption increase leads to cell proliferation decrease	High	Cell proliferation requires orderly progression through the cell cycle. Sustained checkpoint activation, G1/S arrest, G2/M arrest, or mitotic disruption reduces the rate of cell division. KE 1505 is shared with AOP 212, supporting its reuse as a modular checkpoint-related KE (AOP-Wiki, 2026c; Cuddihy and O'Connell, 2003).
Relationship 2205: cell proliferation decrease leads to growth decrease	High	Organismal and tissue growth depend on net accumulation of cell number, cell size, and extracellular components. This relationship is reused from endorsed AOP 263, where decreased cell proliferation is linked to decreased growth (AOP-Wiki, 2026d; Conlon and Raff, 1999; OECD, 2022; Song and Villeneuve, 2021).

 

Empirical support for KERs

KER	Evidence	Rationale	Inconsistencies or limitations
Relationship 2009: ROS increase leads to oxidative stress increase	High	Multiple experimental systems show concordance between ROS generation and oxidative stress biomarkers. For example, paraquat increased ROS and antioxidant enzyme responses in Chlorella vulgaris (Qian et al., 2009), and radiation-induced ROS/oxidative stress relationships are documented in AOP 478 (AOP-Wiki, 2026a; Carrothers et al., 2025).	Direct ROS measurements are technically challenging and probe-specific; some studies infer ROS from antioxidant responses or downstream damage.
Relationship 2810: oxidative stress increase leads to oxidative DNA damage increase	Moderate to high	Oxidative stress is widely associated with oxidative DNA lesions and DNA strand-break endpoints. AOP 478 includes oxidative stress leading to oxidative DNA damage and reports high biological plausibility, while AOP 296 provides a curated oxidative DNA damage module (AOP-Wiki, 2026a, 2026b; Cooke et al., 2003; OECD, 2023).	Some studies measure DNA strand breaks rather than lesion-specific oxidative DNA damage; stressor-specific pathways may include direct genotoxicity.
Relationship 1909: oxidative DNA damage increase leads to inadequate DNA repair increase	Moderate	AOP 296 identifies this relationship and supports it with evidence that excessive oxidative lesions can overwhelm or alter repair processes (AOP-Wiki, 2026b; OECD, 2023).	Direct co-measurement of oxidative lesions and inadequate repair in the same study is less common than measurement of damage endpoints alone.
Relationship 1910: inadequate DNA repair increase leads to DNA strand breaks increase	Moderate	AOP 296 includes inadequate repair leading to DNA strand breaks and broader genomic damage, supported by genotoxicity evidence and repair biology (AOP-Wiki, 2026b; OECD, 2023).	Directionality can be difficult because strand breaks can both result from repair intermediates and trigger repair responses.
Relationship 3480: DNA strand breaks increase leads to cell cycle disruption increase	Moderate	Green algal studies show DNA strand breaks and cell-cycle disruption or division impairment following genotoxic stressors: N-OH-2-AAF-induced DNA strand breaks in Chlamydomonas reinhardtii (David et al., 2009) and zeocin/FdUrd-associated cell-cycle effects in Scenedesmus quadricauda (Hlavová et al., 2011). Silver exposure in embryonic zebrafish cells produced DNA damage and cell-cycle arrest responses (Quevedo et al., 2021).	Evidence is taxonomically diverse but not always tied specifically to oxidative DNA damage as the upstream cause.
Relationship 3363: cell cycle disruption increase leads to cell proliferation decrease	Moderate	Cell-cycle disruption is empirically associated with reduced division and proliferation. AOP 212 provides support for cell-cycle disruption as a reusable KE in an endorsed AOP context, and algal and zebrafish cell studies show reduced division/proliferation following DNA damage-related cell-cycle effects (AOP-Wiki, 2026c; Hlavová et al., 2011; Quevedo et al., 2021).	Recovery can occur if damage is repaired; transient checkpoint activation does not necessarily lead to long-term proliferation decrease.
Relationship 2205: cell proliferation decrease leads to growth decrease	Moderate	AOP 263 reports this relationship as the final growth-relevant KER and assesses it in an endorsed AOP context. Growth effects in algae exposed to paraquat and other stressors provide additional organism-level consistency (AOP-Wiki, 2026d; Qian et al., 2009; Jamers and De Coen, 2010; OECD, 2022; Song and Villeneuve, 2021).	Growth is an apical endpoint influenced by many processes; direct co-measurement of cell proliferation and organismal growth is less common than measurement of growth alone.

Inconsistencies and uncertainties

The main uncertainty in AOP 324 is that ROS-mediated growth inhibition can proceed through multiple branches, including genotoxic, energetic, lipid peroxidation, protein oxidation, and cell death pathways. The present AOP captures only the genotoxic branch. Therefore, failure to observe one KE in this linear pathway does not exclude ROS-mediated growth inhibition through another branch of the broader AOP network. Another uncertainty is the dual biological role of ROS. Low or transient ROS levels may support adaptive redox signaling, whereas sustained or excessive ROS promotes oxidative stress and damage. Quantitative thresholds separating adaptive from adverse ROS signaling are not well established across taxa.

    A further uncertainty is the directionality and specificity of DNA repair-related events. Oxidative DNA damage can lead to repair activation, repair intermediates, strand breaks, or mutation depending on lesion type and cell-cycle phase. Similarly, DNA strand breaks can be both a consequence of inadequate repair and a stimulus for repair. For AOP-Wiki purposes, the KER sequence used in this AOP follows the linear representation shown in Figure 1 and aligns with the curated oxidative DNA damage module of AOP 296. Finally, the linkage between reduced cell proliferation and decreased growth is biologically strong, but growth is affected by many other physiological factors. This limits quantitative prediction of organismal growth from upstream molecular events.

Quantitative Consideration

Quantitative understanding of AOP 324 is strongest for local relationships that have well-defined biological or assay endpoints, and weaker for full-pathway prediction from ROS increase to decreased growth. Direct quantitative prediction is limited by the short half-life and assay dependence of ROS measurements, variability in oxidative DNA damage endpoints, differences in repair capacity, and the multifactorial nature of growth.

 

KER	Evidence	Rationale
Relationship 2009: ROS increase leads to oxidative stress increase	Low to moderate	ROS and oxidative stress biomarkers can be measured quantitatively, but direct ROS measurement is probe- and context-dependent. AOP 478 reports high quantitative understanding for deposition of energy leading to oxidative stress, but this does not translate directly into a generalized ROS-to-oxidative-stress response-response model for all stressors (AOP-Wiki, 2026a; Sies et al., 2017).
Relationship 2810: oxidative stress increase leads to oxidative DNA damage increase	Low to moderate	Oxidative DNA damage endpoints such as 8-oxo-dG and comet assay endpoints can be quantified, but quantitative prediction from oxidative stress biomarkers to DNA lesion burden remains limited and context-dependent (Cooke et al., 2003; OECD, 2023; AOP-Wiki, 2026a).
Relationship 1909: oxidative DNA damage increase leads to inadequate DNA repair increase	Low	Quantitative thresholds at which oxidative DNA damage overwhelms repair capacity are not well generalized across taxa, cell types, or lesion types (OECD, 2023).
Relationship 1910: inadequate DNA repair increase leads to DNA strand breaks increase	Low	Repair kinetics can be measured, but quantitative prediction of strand break accumulation from inadequate repair remains context-specific (OECD, 2023).
Relationship 3480: DNA strand breaks increase leads to cell cycle disruption increase	Moderate	DNA strand breaks and cell-cycle phase distribution can be quantified, and threshold-like checkpoint responses are biologically expected. However, quantitative relationships vary by cell type, repair capacity, and checkpoint status (Cuddihy and O'Connell, 2003; Hlavová et al., 2011; Quevedo et al., 2021).
Relationship 3363: cell cycle disruption increase leads to cell proliferation decrease	Moderate	Cell-cycle arrest and proliferation can both be quantified, but quantitative translation depends on arrest duration, reversibility, and cell population dynamics (Cuddihy and O'Connell, 2003).
Relationship 2205: cell proliferation decrease leads to growth decrease	Moderate	AOP 263 reports moderate quantitative understanding for this KER. Growth models and developmental biology support the relationship, but quantitative prediction across taxa and exposure contexts remains limited (AOP-Wiki, 2026d; Conlon and Raff, 1999; OECD, 2022; Song and Villeneuve, 2021).

 

BMD/POD-anchored concordance

The following BMD/POD concordance table provides quantitative anchoring for AOP 324 in line with Handbook section 4C. Algal EC50/LOEC values supply POD magnitudes for the downstream energetic and growth events, and the gamma-Daphnia moPOD ordering (Song et al., 2023) is included as cross-network POD-magnitude context. Values are presented as POD magnitudes, not as a causal re-ordering of KEs.

 

Key event (functional category)	POD metric	POD value (units as noted)	POD ordering	Source
KE 1771: ATP pool, decreased (Chlamydomonas, paraquat)	EC50	0.34 µM	upstream of death	Nestler et al., 2012
KE 55: Cell death (Chlamydomonas, paraquat)	EC50	~1.0 µM	downstream of ATP	Nestler et al., 2012
AO 1521: Growth, decreased (Chlamydomonas, paraquat)	EC50 / LOEC	0.26 µM / 0.1 µM	apical	Jamers and De Coen, 2010
KE 1115: ROS, increased (mROS)	moPOD (multiomics POD)	0.4 mGy/h	1 (most sensitive)	Song et al., 2023

 

Considerations for Potential Applications of the AOP (optional)

AOP 324 can support mechanistic interpretation of toxicity data where ROS generation, oxidative stress, DNA damage, cell cycle disruption, or reduced proliferation are observed together with growth effects. The AOP may be useful for hazard identification, prioritization of stressors that generate oxidative DNA damage, and organization of evidence in IATA or defined approaches. It can also support chemical grouping or read-across where chemicals share evidence of ROS-mediated DNA damage and downstream checkpoint or proliferation effects.

    The AOP also highlights assay opportunities and gaps. Several KEs can be measured using established or standardized methods, including DNA strand breaks using OECD TG 489 and growth using OECD growth-related test guidelines such as TG 201 and TG 210 (OECD, 2011, 2013, 2014). Other KEs, such as ROS increase, oxidative DNA damage, inadequate DNA repair, and cell cycle disruption, are supported by mechanistic assays but may require careful interpretation of assay specificity and biological context. High-throughput or other new approach methodology (NAM) assays measuring oxidative stress responses, DNA damage signaling, cell cycle arrest, and proliferation may be mapped to the AOP to support screening and prioritization.

For regulatory application, the AOP is currently most suitable for qualitative or semi-quantitative use, such as supporting biological plausibility, organizing mechanistic evidence, and identifying data gaps. More quantitative applications, such as prediction of decreased growth from upstream ROS or oxidative DNA damage measurements, will require further development of response-response relationships, better characterization of modulating factors, and additional studies measuring multiple KEs in the same biological system over time.

References

Ankley, G. T., Bennett, R. S., Erickson, R. J., Hoff, D. J., Hornung, M. W., Johnson, R. D., Mount, D. R., Nichols, J. W., Russom, C. L., Schmieder, P. K., Serrano, J. A., Tietge, J. E., & Villeneuve, D. L. (2010). Adverse outcome pathways: A conceptual framework to support ecotoxicology research and risk assessment. Environmental Toxicology and Chemistry, 29(3), 730-741. https://doi.org/10.1002/etc.34

AOP-Wiki. (2026a). AOP 478: Deposition of energy leading to occurrence of cataracts. Collaborative Adverse Outcome Pathway Wiki. Accessed 14 May 2026.

AOP-Wiki. (2026b). AOP 296: Oxidative DNA damage leading to chromosomal aberrations and mutations. Collaborative Adverse Outcome Pathway Wiki. Accessed 14 May 2026.

AOP-Wiki. (2026c). AOP 212: Histone deacetylase inhibition leading to testicular atrophy. Collaborative Adverse Outcome Pathway Wiki. Accessed 14 May 2026.

AOP-Wiki. (2026d). AOP 263: Uncoupling of oxidative phosphorylation leading to growth inhibition via decreased cell proliferation. Collaborative Adverse Outcome Pathway Wiki. Accessed 14 May 2026.

Becker, R. A., Ankley, G. T., Edwards, S. W., Kennedy, S. W., Linkov, I., Meek, M. E., Sachana, M., Segner, H., Van der Burg, B., Villeneuve, D. L., Watanabe, H., & Barton-Maclaren, T. S. (2015). Increasing scientific confidence in adverse outcome pathways: Application of tailored Bradford-Hill considerations for evaluating weight of evidence. Regulatory Toxicology and Pharmacology, 72(3), 514-537. https://doi.org/10.1016/j.yrtph.2015.04.004

Carrothers, E., et al. (2025). Adverse Outcome Pathway on Deposition of Energy Leading to Cataracts. OECD Series on Adverse Outcome Pathways, No. 40. OECD Publishing, Paris. https://doi.org/10.1787/5ad6b263-en

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

Cooke, M. S., Evans, M. D., Dizdaroglu, M., & Lunec, J. (2003). Oxidative DNA damage: Mechanisms, mutation, and disease. The FASEB Journal, 17(10), 1195-1214. https://doi.org/10.1096/fj.02-0752rev

Cuddihy, A. R., & O'Connell, M. J. (2003). Cell-cycle responses to DNA damage in G2. International Review of Cytology, 222, 99-140. https://doi.org/10.1016/S0074-7696(02)22013-6

Fang, P., Li, X., Zhang, Y., & Wang, Z. (2024). Single and joint bioaccumulation and toxicity of isoproturon and cadmium in green algae (Chlamydomonas reinhardtii). Chemical and Biological Technologies in Agriculture, 11, 106. https://doi.org/10.1186/s40538-024-00617-6

Finkel, T., & Holbrook, N. J. (2000). Oxidants, oxidative stress and the biology of aging. Nature, 408(6809), 239-247. https://doi.org/10.1038/35041687

Jamers, A., & De Coen, W. (2010). Effect assessment of the herbicide paraquat on a green alga using differential gene expression and biochemical biomarkers. Environmental Toxicology and Chemistry, 29(4), 893-901. https://doi.org/10.1002/etc.102

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

OECD. (2011). Test No. 201: Freshwater alga and cyanobacteria, growth inhibition test. OECD Guidelines for the Testing of Chemicals, Section 2. OECD Publishing, Paris. https://doi.org/10.1787/9789264069923-en

OECD. (2013). Test No. 210: Fish, early-life stage toxicity test. OECD Guidelines for the Testing of Chemicals, Section 2. OECD Publishing, Paris. https://doi.org/10.1787/9789264203785-en

OECD. (2014). Test No. 489: In vivo mammalian alkaline comet assay. OECD Guidelines for the Testing of Chemicals, Section 4. OECD Publishing, Paris. https://doi.org/10.1787/9789264224179-en

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, Paris. https://doi.org/10.1787/5jlv1m9d1g32-en

OECD. (2021). Guidance Document for the Scientific Review of Adverse Outcome Pathways. OECD Series on Testing and Assessment, No. 344. OECD Publishing, Paris.

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

OECD. (2023). Oxidative DNA damage leading to chromosomal aberrations and mutations. OECD Series on Adverse Outcome Pathways, No. 29. OECD Publishing, Paris. https://doi.org/10.1787/399d2c34-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

Quevedo, A. C., Lynch, I., & Valsami-Jones, E. (2021). Cellular repair mechanisms triggered by exposure to silver nanoparticles and ionic silver in embryonic zebrafish cells. Environmental Science: Nano, 8(9), 2507-2522. https://doi.org/10.1039/D1EN00422K

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

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

Valko, M., Morris, H., & Cronin, M. T. D. (2005). Metals, toxicity and oxidative stress. Current Medicinal Chemistry, 12(10), 1161-1208. https://doi.org/10.2174/0929867053764635

Hlavová, M., Čížková, M., Vítová, M., Bišová, K., & Zachleder, V. (2011). DNA damage during G2 phase does not affect cell cycle progression of the green alga Scenedesmus quadricauda. PLoS ONE, 6(5), e19626. https://doi.org/10.1371/journal.pone.0019626

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: 1634: Increase, Oxidative DNA damage

Short Name: Increase, Oxidative DNA damage

Event Component

AOPs Including This Key Event

Stressors

Biological Context

Cell term

Organ term

Domain of Applicability

Taxonomic Applicability Life Stage Applicability Sex Applicability

Taxonomic applicability: Theoretically, DNA oxidation can occur in any cell type, in any organism. Oxidative DNA lesions have been measured in mammalian cells (human, mouse, calf, rat) in vitro and in vivo, and in prokaryotes.

Life stage applicability: This key event is not life stage specific (Mesa & Bassnett, 2013; Suman et al., 2019). 

Sex applicability: This key event is not sex specific (Mesa & Bassnett, 2013). 

Evidence for Perturbation by Prototypic Stressor: H₂O₂ and KBrO₃ – A concentration-dependent increase in oxidative lesions was observed in both Fpg- and hOGG1-modified comet assays of TK6 cells treated with increasing concentrations of glucose oxidase (an enzyme that generates H₂O₂) and potassium bromate for 4 h (Platel et al., 2011).  

Evidence indicates that oxidative DNA damage is also induced by X-rays (Bahia et al., 2018), ⁶⁰Co γ-rays, ¹²C ions, α particles, electrons (Georgakilas, 2013), UVB (Mesa and Bassnett, 2013), γ-rays, ⁵⁶Fe ions (Datta et al., 2012), and protons (Suman et al., 2019).  

Key Event Description

The nitrogenous bases of DNA are susceptible to oxidation in the presence of oxidizing agents. Oxidative adducts form mainly on C5 and to a lesser degree on C6 of thymine and cytosine, and on C8 of guanine and adenine. Guanine is most prone to oxidation due to its low oxidation potential (Jovanovic and Simic, 1986). Indeed, 8-oxo-2’-deoxyguanosine (8-oxodG)/8-hydroxy-2’-deoxyguanosine (8-OHdG) is the most abundant and well-studied oxidative DNA lesion in the cell (Swenberg et al., 2011). It causes an A(anti):8-oxo-G(syn) mispair instead of the normal C(anti):8-oxo-G(syn) pair. This pairing does not cause large structural changes to the DNA backbone, and therefore remains undetected by the polymerase’s proofreading mechanism. Consequently, one of the daughter strands will have an AT pair instead of the correct GC pair after replication (Markkanen, 2017). 

Formamidopyrimidine lesions on guanine and adenine (FaPyG and FaPyA), 8-hydroxy-2'-deoxyadenine (8-oxodA), and thymidine glycol (Tg) are other common oxidative lesions. We refer the reader to reviews on this topic to see the full set of potential oxidative DNA lesions (Whitaker et al., 2017). Oxidative DNA lesions are present in the cell at a steady state due to endogenous redox processes (Swenberg et al., 2010). Under normal conditions, cells are able to withstand the baseline level of oxidized bases through efficient repair and regulation of free radicals in the cell. However, direct chemical insult from specific compounds, exposure to various forms of radiation, or induction of reactive oxygen species (ROS) from the reduction of endogenous molecules, as well as through the release of inflammatory cell-derived oxidants, can lead to increased DNA oxidation, a state known as oxidative stress (Turner et al., 2002; Schoenfeld et al., 2012; Tangvarasittichai and Tangvarasittichai, 2019). It is worth noting that ROS must be generated near the DNA to cause damage, otherwise, if ROS was produced more distantly, then it can be removed by the cell (Nilsson & Liu, 2020). Furthermore, although cells do possess repair mechanisms to deal with oxidative DNA damage, sometimes the repair intermediates can interfere with genome function or decrease stability of the genome. This creates a balancing act between when it is best to repair damage and when it is best to leave it (Poetsch, 2020a). 

This KE describes an increase in oxidative lesions of a broad spectrum (ie. superoxide radical (O2•−), hydroxyl radical (OH), peroxyl radical (RO22), single oxygen (1O2 ) in the nuclear DNA above the steady-state level. Oxidative DNA damage can occur in any cell type with nuclear DNA under oxidative stress.

How it is Measured or Detected

Relative Quantification of Oxidative DNA Lesions

• Comet assay (single cell gel electrophoresis) with Fpg and hOGG1 modifications (Smith et al., 2006; Platel et al., 2011)
  • Oxoguanine glycosylase (hOGG1) and formamidopyrimidine-DNA glycosylase (Fpg) are base excision repair (BER) enzymes in eukaryotic and prokaryotic cells, respectively
  • Both enzymes are bi-functional; the glycosylase function cleaves the glycosidic bond between the ribose and the oxidized base, giving rise to an abasic site, and the apurinic/apymidinic (AP) site lyase function cleaves the phosphodiester bond via β-elimination reaction and creates a single strand break
  • Treatment of DNA with either enzyme prior to performing the electrophoresis step of the comet assay allows detection of oxidative lesions by measuring the increase in comet tail length when compared against untreated samples.
• Enzyme-linked immunosorbant assay (ELISA) (Dizdaroglu et al., 2002; Breton et al., 2003; Xu et al., 2008; Zhao et al. 2017)
  • 8-oxodG can be detected using immunoassays, such as ELISA, that use antibodies against 8-oxodG lesions. It has been noted that immunodetection of 8-oxodG can be interfered by certain compounds in biological samples.

Absolute Quantification of Oxidative DNA Lesions

• Quantification of 8-oxodG using HPLC-EC  (Breton et al., 2003; Chepelev et al., 2015)
  • 8-oxodG can be separated from digested DNA and precisely quantified using high performance liquid chromatography (HPLC) with electrochemical detection
• Mass spectrometry LC-MRM/MS (Mangal et al., 2009)
  • Liquid chromatography can also be coupled with multiple reaction monitoring/ mass spectrometry to detect and quantify oxidative lesions. Correlation between lesions measured by hOGG1-modified comet assay and LC-MS has been reported

Gas chromatography-mass spectrometry (GC-MS) 

• DNA is hydrolyzed to release either free bases or nucleosides and then undergoes derivatization in order to increase their volatility. Finally, samples run through a gas chromatograph and then a mass spectrometer. The mass spectrometer results are used to determine oxidative DNA damage by identifying modified bases or nucleosides (Dizdaroglu, 1994). 

Sequencing assays 

• Various markers are used to detect and highlight sites of DNA damage; the result is then processed and sequenced. This category encompasses a wide range of assays such as snAP-seq, OGG1-AP-seq, oxiDIP-seq, OG-seq, and click-code-seq (Yun et al., 2017; Wu et al., 2018; Amente et al., 2019; Poetsch, 2020b). 
• We note that other types of oxidative lesions can be quantified using the methods described above.

References

Amente, S. et al. (2019), “Genome-wide mapping of 8-oxo-7,8-dihydro-2’-deoxyguanosine reveals accumulation of oxidatively-generated damage at DNA replication origins within transcribed long genes of mammalian cells”, Nucleic Acids Research 2019, Vol. 47/1, Oxford University Press, England, https://doi.org/10.1093/nar/gky1152 

Bahia, S. et al. (2018), “Oxidative and nitrative stress-related changes in human lens epithelial cells following exposure to X-rays”, International journal of radiation biology, Vol. 94/4, England, https://doi.org/10.1080/09553002.2018.1439194 

Breton J, Sichel F, Bainchini F, Prevost V. (2003). Measurement of 8-Hydroxy-2′-Deoxyguanosine by a Commercially Available ELISA Test: Comparison with HPLC/Electrochemical Detection in Calf Thymus DNA and Determination in Human Serum. Anal Lett 36:123-134.

Cabrera, M. P., R. Chihuailaf and F. Wittwer Menge (2011), “Antioxidants and the integrity of ocular tissues”, Veterinary medicine international, Vol. 2011, SAGE-Hindawi Access to Research, United States, https://doi.org/10.4061/2011/905153 

Cadet, J. et al. (2012), “Oxidatively generated complex DNA damage: tandem and clustered lesions”, Cancer letters, Vol. 327/1, Elsevier Ireland Ltd, Ireland. https://doi.org/10.1016/j.canlet.2012.04.005 

Chepelev N, Kennedy D, Gagne R, White T, Long A, Yauk C, White P. (2015). HPLC Measurement of the DNA Oxidation Biomarker, 8-oxo-7,8-dihydro-2'-deoxyguanosine, in Cultured Cells and Animal Tissues. Journal of Visualized Experiments 102:e52697.

Collins, A. R. (2014), “Measuring oxidative damage to DNA and its repair with the comet assay”, Biochimica et biophysica acta. General subjects, Vol. 1840/2, Elsevier B.V., https://doi.org/10.1016/j.bbagen.2013.04.022 

Datta, K. et al. (2012), “Exposure to heavy ion radiation induces persistent oxidative stress in mouse intestive”, PloS One, Vol. 7/8, Public Library of Science, United States, https://doi.org/10.1371/journal.pone.0042224 

Dizdaroglu, M. (1994), “Chemical determination of oxidative DNA damage by gas chromatography-mass spectrometry”, Methods in Enzymology, Vol. 234, Elsevier Science & Technology, United States, https://doi.org/ 10.1016/0076-6879(94)34072-2 

Dizdaroglu, M. et al. (2002), “Free radical-induced damage to DNA : mechanisms and measurement”, Free radical biology & medicine, Vol. 32/11, United States, pp. 1102-1115 

Eaton, J. W. (1995), “UV-mediated cataractogenesis: a radical perspective”, Documenta ophthalmologica, Vol. 88/3-4, Springer, Dordrecht, https://doi.org/10.1007/BF01203677 

Fletcher, A. E. (2010), “Free radicals, antioxidants and eye diseases: evidence from epidemiological studies on cataract and age-related macular degeneration”, Ophthalmic Research, Vol. 44/3, Karger international, Basel, https://doi.org/10.1159/000316476 

Georgakilas, A. G et al. (2013), “Induction and repair of clustered DNA lesions: what do we know so far?”, Radiation Research, Vol. 180/1, The Radiation Research Society, United States, https://doi.org/10.1667/RR3041.1 

Jose, D. et al. (2009). “Spectroscopic studies of position-specific DNA “breathing” fluctuations at replication forks and primer-template junctions”, Proceedings of the National Academy of Sciences of the United States of America, Vol. 106/11, https://doi.org/10.1073/pnas.0900803106 

Jovanovic S, Simic M. (1986). One-electron redox potential of purines and pyrimidines. J Phys Chem 90:974-978.

Kruk, J., K. Kubasik-Kladna and H. Y. Aboul-Enein (2015), “The role oxidative stress in the pathogenesis of eye diseases: current status and a dual role of physical activity”, Mini-reviews in medicinal chemistry, Vol. 16/3, Bentham Science Publishers Ltd, Netherlands, https://doi.org/10.2174/1389557516666151120114605 

Lee, J. et al. (2004), “Reactive oxygen species, aging, and antioxidative nutraceuticals”, Comprehensive reviews in food science and food safety, Vol. 3/1, Blackwell Publishing Ltd, Oxford, https://doi.org/10.1111/j.1541-4337.2004.tb00058.x 

Mangal D, Vudathala D, Park J, Lee S, Penning T, Blair I. (2009). Analysis of 7,8-Dihydro-8-oxo-2′-deoxyguanosine in Cellular DNA during Oxidative Stress. Chem Res Toxicol 22:788-797.

Markkanen, E. (2017), “Not breathing is not an option: How to deal with oxidative DNA damage”, DNA repair, Vol. 59, Elsevier B.V., Netherlands, https://doi.org/10.1016/j.dnarep.2017.09.007 

Mesa, R. and S. Bassnett (2013), “UV-B induced DNA damage and repair in the mouse lens”, Investigative ophthalmology & visual science, Vol. 54/10, the Association for Research in Vision and Ophthalmology, United States, https://doi.org/10.1167/iovs.13-12644 

Nilsson R. and Liu N. (2020), “Nuclear DNA damages generated by reactive oxygen molecules (ROS) under oxidative stress and their relevance to human cancers, including ionizing radiation-induced neoplasia part I: Physical, chemical and molecular biology aspects”, Radiation Medicine and Protection, Vol. 1/3(3), https://doi.org/10.1016/j.radmp.2020.09.002 

Pendergrass, W. et al. (2010), “X-ray induced cataract is preceded by LEC loss, and coincident with accumulation of cortical DNA, and ROS; similarities with age-related cataracts”, Molecular vision, Vol. 16, Molecular Vision, United States, pp. 1496-1513 

Platel A, Nesslany F, Gervais V, Claude N, Marzin D. (2011). Study of oxidative DNA damage in TK6 human lymphoblastoid cells by use of the thymidine kinase gene-mutation assay and the in vitro modified comet assay: Determination of No-Observed-Genotoxic-Effect-Levels. Mutat Res 726:151-159.

Poetsch, Anna R. (2020a), “The genomics of oxidative DNA damage, repair, and resulting mutagenesis”, Computational and structural biotechnology journal 2020, Vol. 18, Elsevier B.V., Netherlands https://doi.org/10.1016/j.csbj.2019.12.013 

Poetsch, A. R. (2020b), “AP-Seq: A method to measure apurinic sites and small base adducts genome-wide”, The Nucleus, Springer US, New York, Sacca, S. C. et al. (2009), “Gene-environment interactions in ocular diseases”, Mutation research – fundamental and molecular mechanisms of mutagenesis, Vol. 667/1-2, Elsevier, Amsterdam, https://doi.org/10.1016/j.mrfmmm.2008.11.002 

Schoenfeld, M. P. et al. (2012), “A hypothesis on biological protection from space radiation through the use of new therapeutic gases as medical counter measures”, Medical gas research, Vol. 2/1, BioMed Central Ltd, India, https://doi.org/10.1186/2045-9912-2-8 

Smith C, O'Donovan M, Martin E. (2006). hOGG1 recognizes oxidative damage using the comet assay with greater specificity than FPG or ENDOIII. Mutagenesis 21:185-190.

Stohs, S. J. (1995), “The role of free radicals in toxicity and disease”, Journal of Basic and Clinical Physiology and Pharmacology, Vol. 6/3-4, Freund Publishing House Ltd, https://doi.org/10.1515/JBCPP.1995.6.3-4.205 

Suman, S. et al. (2019), “Fractionated and acute proton radiation show differential intestinal tumorigenesis and DNA damage and repair pathway response in ApcMin/+ mice”, International Journal of Radiation Oncology, Biology, Physics, Vol. 105/3, Elsevier Inc, https://doi.org/10.1016/j.ijrobp.2019.06.2532 

Swenberg J. et al. (2011). "Endogenous versus Exogenous DNA Adducts: Their Role in Carcinogenesis, Epidemiology, and Risk Assessment." Toxicol Sci 120:S130-S145.

Tangvarasittichai, O and S. Tangvarasittichai (2018), “Oxidative stress, ocular disease, and diabetes retinopathy”, Current Pharmaceutical Design, Vol. 24/40, Bentham Science Publishers, https://doi.org/10.2174/1381612825666190115121531 

Turner, N. D. et al. (2002), “Opportunities for nutritional amelioration of radiation-induced cellular damage”, Nutrition, Vol. 18/10, Elsevier Inc, New York, https://doi.org/10.1016/S0899-9007(02)00945-0 

Whitaker A, Schaich M, Smith MS, Flynn T, Freudenthal B. (2017). Base excision repair of oxidative DNA damage: from mechanism to disease. Front Biosci 22:1493-1522.

Wu, J. (2018), “Nucleotide-resolution genome-wide mapping of oxidative DNA damage by click-code-seq”, Journal of the American Chemical Society 2018, American Chemical Society, United States https://doi-org.proxy.bib.uottawa.ca/10.1021/jacs.8b03715 

Xu, X. et al. (2008). “Fluorescence recovery assay for the detection of protein-DNA binding”, Analytical Chemistry, Vol. 80/14, https://doi.org/10.1021/ac8007016 

Zhao M, Howard E, Guo Z, Parris A, Yang X. (2017). p53 pathway determines the cellular response to alcohol-induced DNA damage in MCF-7 breast cancer cells. PLoS One 12:e0175121.

Event: 155: Inadequate DNA repair

Short Name: Inadequate DNA repair

Event Component

AOPs Including This Key Event

Stressors

Biological Context

Domain of Applicability

Taxonomic Applicability Life Stage Applicability Sex Applicability

The retention of adducts has been directly measured in many different types of eukaryotic somatic cells (in vitro and in vivo). In male germ cells, work has been done on hamsters, rats and mice. The accumulation of mutation and changes in mutation spectrum has been measured in mice and human cells in culture. Theoretically, saturation of DNA repair occurs in every species (prokaryotic and eukaryotic). The principles of this work were established in prokaryotic models. Nagel et al. (2014) have produced an assay that directly measures DNA repair in human cells in culture.

NHEJ is primarily used by vertebrate multicellular eukaryotes, but it also been observed in plants. Furthermore, it has recently been discovered that some bacteria (Matthews et al., 2014) and yeast (Emerson et al., 2016) also use NHEJ. In terms of invertebrates, most lack the core DNA-PK_cs and Artemis proteins; they accomplish end joining by using the RA50:MRE11:NBS1 complex (Chen et al., 2001).  HR occurs naturally in eukaryotes, bacteria, and some viruses (Bhatti et al., 2016).

Taxonomic applicability: Inadequate DNA repair is applicable to all species, as they all contain DNA (White & Vijg, 2016).  

Life stage applicability: This key event is not life stage specific as any life stage can have poor repair, though as individuals age their repair process become less effective (Gorbunova & Seluanov, 2016). 

Sex applicability: There is no evidence of sex-specificity for this key event, with initial rate of DNA repair not significantly different between sexes (Trzeciak et al., 2008). 

Evidence for perturbation by a stressor: Multiple studies demonstrate that inadequate DNA repair can occur as a result of stressors such as ionizing and non-ionizing radiation, as well as chemical agents (Kuhne et al., 2005; Rydberg et al., 2005; Dahle et al., 2008; Seager et al., 2012; Wilhelm, 2014; O’Brien et al., 2015).  

Key Event Description

DNA lesions may result from the formation of DNA adducts (i.e., covalent modification of DNA by chemicals), or by the action of agents such as radiation that may produce strand breaks or modified nucleotides within the DNA molecule. These DNA lesions are repaired through several mechanistically distinct pathways that can be categorized as follows:

1. Damage reversal acts to reverse the damage without breaking any bonds within the sugar phosphate backbone of the DNA. The most prominent enzymes associated with damage reversal are photolyases (Sancar, 2003) that can repair UV dimers in some organisms, and O6-alkylguanine-DNA alkyltransferase (AGT) (Pegg 2011) and oxidative demethylases (Sundheim et al., 2008), which can repair some types of alkylated bases.
2. Excision repair involves the removal of a damaged nucleotide(s) through cleavage of the sugar phosphate backbone followed by re-synthesis of DNA within the resultant gap. Excision repair of DNA lesions can be mechanistically divided into: 

   a) Base excision repair (BER) (Dianov and Hübscher, 2013), in which the damaged base is removed by a damage-specific glycosylase prior to incision of the phosphodiester backbone at the resulting abasic site. This leads to an intermediate that contains a DNA strand break, whereby DNA ligase is then recruited to seal the ends of the DNA.

   b) Nucleotide excision repair (NER) (Schärer, 2013), in which the DNA strand containing the damaged nucleotide is incised at sites several nucleotides 5’ and 3’ to the site of damage, and a polynucleotide containing the damaged nucleotide is removed prior to DNA resynthesis within the resultant gap and sealing of the ends by DNA ligase.  

   c) Mismatch repair (MMR) (Li et al., 2016)  which does not act on DNA lesions but does recognize mispaired bases resulting from replication errors. In MMR the strand containing the misincorporated base is removed prior to DNA resynthesis.

   The major pathway that removes oxidative DNA damage is base excision repair (BER), which can be either monofunctional or bifunctional; in mammals, a specific DNA glycosylase (OGG1: 8-Oxoguanine glycosylase) is responsible for excision of 8-oxoguanine (8-oxoG) and other oxidative lesions (Hu et al., 2005; Scott et al., 2014; Whitaker et al., 2017). We note that long-patch BER is used for the repair of clustered oxidative lesions, which uses several enzymes from DNA replication pathways (Klungland and Lindahl, 1997). These pathways are described in detail in various reviews e.g., (Whitaker et al., 2017). 

3. Single strand break repair (SSBR) involves different proteins and enzymes depending on the origin of the SSB (e.g., produced as an intermediate in excision repair or due to direct chemical insult) but the same general steps of repair are taken for all SSBs: detection, DNA end processing, synthesis, and ligation (Caldecott, 2014). Poly-ADP-ribose polymerase1 (PARP1) detects and binds unscheduled SSBs (i.e., not deliberately induced during excision repair) and synthesizes PAR as a signal to the downstream factors in repair. PARP1 is not required to initiate SSBR of BER intermediates. The XRCC1 protein complex is then recruited to the site of damage where a common DNA intermediate as BER was generated, and acts as a scaffold for proteins and enzymes required for repair. Depending on the nature of the damaged termini of the DNA strand, different enzymes are required for end processing to generate the substrates that DNA polymerase β (Polβ; short patch repair) or Pol δ/ε (long patch repair) can bind to synthesize over the gap, although end processing is generally done by polynucleotide kinase. Synthesis in long-patch repair displaces a single stranded flap which is excised by flap endonuclease 1 (FEN1). In short-patch repair, the XRCC1/Lig3α complex joins the two ends after synthesis. In long-patch repair, the PCNA/Lig1 complex ligates the ends. (Caldecott, 2014). 
4. Double strand break repair (DSBR) is necessary to preserve genomic integrity when breaks occur in both strands of a DNA molecule. There are two major pathways for DSBR: homologous recombination (HR), which operates primarily during the S phase of dividing cell types, and nonhomologous end joining (NHEJ), which can function in both dividing and non-dividing cell types. No repair occurs in the M phase (Teruaki Iyama and David M. Wilson III, 2013). DNA repair in mitosis is controversial (Mladenov et al., 2023).

Complex lesions can be created by a single mutagen and can be more difficult to repair, as the mechanism behind how different repair pathways cooperate to address this is still unclear (Aleksandrov et al., 2018). In higher eukaryotes such as mammals, NHEJ is usually the preferred pathway for DNA DSBR. Its use, however, is dependent on the cell type, the gene locus, and the nuclease platform (Miyaoka et al., 2016). The use of NHEJ is also dependent on the cell cycle; NHEJ is generally not the pathway of choice when the cell is in the late S or G2 phase of the cell cycle, or in mitotic cells when the sister chromatid is directly adjacent to the double-strand break (DSB) (Lieber et al., 2003). In these cases, the HR pathway is commonly used for repair of DSBs. Despite this, NHEJ is still used more commonly than HR in human cells. Classical NHEJ (C-NHEJ) is the most common NHEJ repair mechanism, but alternative NHEJ (alt-NHEJ) can also occur, especially in the absence of C-NHEJ and HR.

The process of C-NHEJ in humans requires at least seven core proteins: Ku70, Ku86, DNA-dependent protein kinase complex (DNA-PK_cs ), Artemis, X-ray cross-complementing protein 4 (XRCC4), XRCC4-like factor (XLF), and DNA ligase IV (Boboila et al., 2012). When DSBs occur, the Ku proteins, which have a high affinity for DNA ends, will bind to the break site and form a heterodimer. This protects the DNA from exonucleolytic attack and acts to recruit DNA-PK_cs, the catalytic subunit, thus forming a trimeric complex on the ends of the DNA strands. Alternative NHEJ, or alt NHEJ, uses small similar sequences in two broken DNA ends to join them together. Unlike the usual repair method (cNHEJ), aNHEJ doesn't need specific proteins like LIG4 and KU. Instead, it relies on the MRN complex to process the breaks. However, alt NHEJ tends to cause mutations by adding or removing bits of DNA during the repair (Chaudhuri and Nussenzweig, 2017). The kinase activity of DNA-PK_cs is then triggered, causing DNA-PK_cs to auto-phosphorylate and thereby lose its kinase activity; the now phosphorylated DNA-PK_cs dissociates from the DNA-bound Ku proteins. The free DNA-PK_cs phosphorylates Artemis, an enzyme that possesses 5’-3’ exonuclease and endonuclease activity in the presence of DNA-PK_cs and ATP. Artemis is responsible for ‘cleaning up’ the ends of the DNA. For 5’ overhangs, Artemis nicks the overhang, generally leaving a blunt duplex end. For 3’ overhangs, Artemis will often leave a four- or five-nucleotide single stranded overhang (Pardo et al., 2009; Fattah et al., 2010; Lieber et al., 2010). Next, the XLF and XRCC4 proteins form a complex which makes a channel to bind DNA and aligns the ends for efficient ligation via DNA ligase IV (Hammel et al., 2011).

The process of alt-NHEJ is less well understood than C-NHEJ and is a lower fidelity mechanism.  Alt-NHEJ is known to involve slightly different core proteins than C-NHEJ and required microhomology repeats, but the steps of the pathway are essentially the same between the two processes (reviewed in Chiruvella et al., 2013). It is established, however, that alt-NHEJ is more error-prone in nature than C-NHEJ, which contributes to incorrect DNA repair. Alt-NHEJ is thus considered primarily to be a backup repair mechanism (reviewed in Chiruvella et al., 2013). 

In contrast to NHEJ, HR takes advantage of similar or identical DNA sequences to repair DSBs and is not error-prone (Sung and Klein, 2006). The initiating step of HR is the creation of a 3’ single strand DNA (ss-DNA) overhang. Combinases such as RecA and Rad51 then bind to the ss-DNA overhang, and other accessory factors, including Rad54, help recognize and invade the homologous region on another DNA strand. From there, DNA polymerases are able to elongate the 3’ invading single strand and resynthesize the broken DNA strand using the corresponding sequence on the homologous strand.

 

Fidelity of DNA Repair

Most DNA repair pathways are extremely efficient. However, in principal, all DNA repair pathways can be overwhelmed when the DNA lesion burden exceeds the capacity of a given DNA repair pathway to recognize and remove the lesion. Exceeded repair capacity may lead to toxicity or mutagenesis following DNA damage. Apart from extremely high DNA lesion burden, inadequate repair may arise through several different specific mechanisms. For example, during repair of DNA containing O6-alkylguanine adducts, AGT irreversibly binds a single O6-alkylguanine lesion and as a result is inactivated (this is termed suicide inactivation, as its own action causes it to become inactivated). Thus, the capacity of AGT to carry out alkylation repair can become rapidly saturated when the DNA repair rate exceeds the de novo synthesis of AGT (Pegg, 2011).

A second mechanism relates to cell specific differences in the cellular levels or activity of some DNA repair proteins. For example, XPA is an essential component of the NER complex. The level of XPA that is active in NER is low in the testes, which may reduce the efficiency of NER in testes as compared to other tissues (Köberle et al., 1999). Likewise, both NER and BER have been reported to be deficient in cells lacking functional p53 (Adimoolam and Ford, 2003; Hanawalt et al., 2003; Seo and Jung, 2004). A third mechanism relates to the importance of the DNA sequence context of a lesion in its recognition by DNA repair enzymes. For example, 8-oxoguanine (8-oxoG) is repaired primarily by BER; the lesion is initially acted upon by a bifunctional glycosylase, OGG1, which carries out the initial damage recognition and excision steps of 8-oxoG repair. However, the rate of excision of 8-oxoG is modulated strongly by both chromatin components (Menoni et al., 2012) and DNA sequence context (Allgayer et al., 2013) leading to significant differences in the repair of lesions situated in different chromosomal locations.

DNA repair is also remarkably error-free. However, misrepair can arise during repair under some circumstances. DSBR is notably error prone, particularly when breaks are processed through NHEJ, during which partial loss of genome information is common at the site of the double strand break (Iyama and Wilson, 2013). This is because NHEJ rejoins broken DNA ends without the use of extensive homology; instead, it uses the microhomology present between the two ends of the DNA strand break to ligate the strand back into one. When the overhangs are not compatible, however, indels (insertion or deletion events), duplications, translocations, and inversions in the DNA can occur. These changes in the DNA may lead to significant issues within the cell, including alterations in the gene determinants for cellular fatality (Moore et al., 1996).

Activation of mutagenic DNA repair pathways to withstand cellular or replication stress either from endogenous or exogenous sources can promote cellular viability, albeit at a cost of increased genome instability and mutagenesis (Fitzgerald et al., 2017). These salvage DNA repair pathways including, Break-induced Replication (BIR) and Microhomology-mediated Break-induced Replication (MMBIR). BIR repairs one-ended DSBs and has been extensively studied in yeast as well as in mammalian systems. BIR and MMBIR are linked with heightened levels of mutagenesis, chromosomal rearrangements and ensuing genome instability (Deem et al., 2011; Sakofsky et al., 2015; Saini et al., 2017; Kramara et al., 2018). In mammalian genomes BIR-like synthesis has been proposed to be involved in late stage Mitotic DNA Synthesis (MiDAS) that predominantly occurs at so-called Common Fragile Sites (CFSs) and maintains telomere length under s conditions of replication stress that serve to promote cell viability (Minocherhomji et al., 2015; Bhowmick et al., 2016; Dilley et al., 2016).       

Misrepair may also occur through other repair pathways. Excision repair pathways require the resynthesis of DNA and rare DNA polymerase errors during gap resynthesis will result in mutations (Brown et al., 2011). Errors may also arise during gap resynthesis when the strand that is being used as a template for DNA synthesis contains DNA lesions (Kozmin and Jinks-Robertson, 2013). In addition, it has been shown that sequences that contain tandemly repeated sequences, such as CAG triplet repeats, are subject to expansion during gap resynthesis that occurs during BER of 8-oxoG damage (Liu et al., 2009).

How it is Measured or Detected

There is no test guideline for this event. The event is usually inferred from measuring the retention of DNA adducts or the creation of mutations as a measure of lack of repair or incorrect repair. These ‘indirect’ measures of its occurrence are crucial to determining the mechanisms of genotoxic chemicals and for regulatory applications (i.e., determining the best approach for deriving a point of departure). More recently, a fluorescence-based multiplex flow-cytometric host cell reactivation assay (FM-HCR) has been developed to directly measure the ability of human cells to repair plasmid reporters (Nagel et al., 2014).

Indirect Measurement

In somatic and spermatogenic cells, measurement of DNA repair is usually inferred by measuring DNA adduct formation/removal. Insufficient repair is inferred from the retention of adducts and from increasing adduct formation with dose. Insufficient DNA repair is also measured by the formation of increased numbers of mutations and alterations in mutation spectrum. The methods will be specific to the type of DNA adduct that is under study.

Some EXAMPLES are given below for alkylated DNA.

DOSE-RESPONSE CURVE FOR ALKYL ADDUCTS/MUTATIONS: It is important to consider that some adducts are not mutagenic at all because they are very effectively repaired. Others are effectively repaired, but if these repair processes become overwhelmed mutations begin to occur. The relationship (shape of dose-response curve) between exposure to mutagenic agents and mutations provide an indication of whether the removal of adducts occurs, and whether it is more efficient at low doses. Sub-linear dose-response curves (hockey stick or j-shape curves) for mutation induction indicates that adducts are not converted to mutations at low doses. This suggests the effective repair of adducts at low doses, followed by saturation of repair at higher doses (Clewell et al., 2019). Thus, measurement of a clear point of inflection in the dose-response curve for mutations suggests that repair does occur, at least to some extent, at low dosees but that reduced repair efficiency arises above the inflection point. A lack of increase in mutation frequencies (i.e., flat line for dose-response) for a compound showing a dose-dependent increase in adducts would imply that the adducts formed are either not mutagenic or are effectively repaired.

RETENTION OF ALKYL ADDUCTS: Alkylated DNA can be found in cells long after exposure has occurred. This indicates that repair has not effectively removed the adducts. For example, DNA adducts have been measured in hamster and rat spermatogonia several days following exposure to alkylating agents, indicating lack of repair (Seiler et al., 1997; Scherer et al., 1987).

MUTATION SPECTRUM: Shifts in mutation spectrum (i.e., the specific changes in the DNA sequence) following a chemical exposure (relative to non-exposed mutation spectrum) indicates that repair was not operating effectively to remove specific types of lesions. The shift in mutation spectrum is indicative of the types of DNA lesions (target nucleotides and DNA sequence context) that were not repaired. For example, if a greater proportion of mutations occur at guanine nucleotides in exposed cells, it can be assumed that the chemical causes DNA adducts on guanine that are not effectively repaired.

Direct Measurement

Nagel et al. (2014) we developed a fluorescence-based multiplex flow-cytometric host cell reactivation assay (FM-HCR) to measures the ability of human cells to repair plasmid reporters. These reporters contain different types and amounts of DNA damage and can be used to measure repair through by NER, MMR, BER, NHEJ, HR and MGMT.

Please refer to the table below for additional details and methodologies for detecting DNA damage and repair.

Assay Name	References	Description	DNA Damage/Repair Being Measured	OECD Approved Assay
Dose-Response Curve for Alkyl Adducts/ Mutations	Lutz 1991   Clewell 2016	Creation of a curve plotting the stressor dose and the abundance of adducts/mutations; Characteristics of the resulting curve can provide information on the efficiency of DNA repair	Alkylation, oxidative damage, or DSBs	N/A
Retention of Alkyl Adducts	Seiler 1997   Scherer 1987	Examination of DNA for alkylation after exposure to an alkylating agent; Presence of alkylation suggests a lack of repair	Alkylation	N/A
Mutation Spectrum	Wyrick 2015	Shifts in the mutation spectrum after exposure to a chemical/mutagen relative to an unexposed subject can provide an indication of DNA repair efficiency, and can inform as to the type of DNA lesions present	Alkylation, oxidative damage, or DSBs	N/A
DSB Repair Assay (Reporter constructs)	Mao et al., 2011	Transfection of a GFP reporter construct (and DsRed control) where the GFP signal is only detected if the DSB is repaired; GFP signal  is quantified using fluorescence microscopy or flow cytometry	DSBs	N/A
Primary Rat Hepatocyte DNA Repair Assay	Jeffrey and Williams, 2000   Butterworth et al., 1987	Rat primary hepatocytes are cultured with a 3H-thymidine solution in order to measure DNA synthesis in response to a stressor in non-replicating cells; Autoradiography is used to measure the amount of 3H incorporated in the DNA post-repair	Unscheduled DNA synthesis in response to DNA damage	N/A
Repair synthesis measurement by 3H-thymine incorporation	Iyama and Wilson, 2013	Measure DNA synthesis in non-dividing cells as indication of gap filling during excision repair	Excision repair	N/A
Comet Assay with Time-Course	Olive et al., 1990   Trucco et al., 1998 - Dunkenberger et al., 2022	Comet assay is performed with a time-course under alkaline conditions to detect SSBs and DSBs. Quantity of DNA in the tail should decrease as DNA repair progresses	DSBs	Yes (No. 489)
Flow Cytometry	Corneo et al., 2007	The alt-NHEJ flow cytometer method involves utilizing an extrachromosomal substrate. Green fluorescent protein (GFP) expression is indicative of successful alt-NHEJ activity, contingent on the removal of 10 nucleotides from each end of the DNA and subsequent rejoining within a 9-nucleotide microhomology region. This approach provides a quantitative and visual means to measure the efficiency of alternative non-homologous end joining in cellular processes.	Alt NHEJ	No
Pulsed Field Gel Electro-phoresis (PFGE) with Time-Course	Biedermann et al., 1991	PFGE assay with a time-course; Quantity of small DNA fragments should decrease as DNA repair  progresses	DSBs	N/A
Fluorescence -Based Multiplex Flow-Cytometric Host Reactivation Assay (FM-HCR)	Nagel et al., 2014	Measures the ability of human cells to repair plasma reporters, which contain different types and amounts of DNA damage; Used to measure repair processes including HR, NHEJ, BER, NER, MMR, and MGMT	HR, NHEJ, BER, NER, MMR, or MGMT	N/A
Alkaline Unwinding Assay with Time Course	Nacci et al. 1991	DNA is stored in alkaline solutions with DNA-specific dye and allowed to unwind following removal from tissue, increased strand damage associated with increased unwinding. Samples analyzed at different time points to compare remaining damage following repair opportunities	DSBs	Yes (No. 489)
Sucrose Density Gradient Centrifugation with Time Course	Larsen et al. 1982	Strand breaks alter the molecular weight of the DNA piece. DNA in alkaline solution centrifuged into sugar density gradient, repeated set time apart. The less DNA breaks identified in the assay repeats, the more repair occurred	SSBs	N/A
y-H2AX Foci Staining with Time Course	Mariotti et al. 2013  Penninckx et al. 2021	Histone H2AX is phosphorylated in the presence of DNA strand breaks, the rate of its disappearance over time is used as a measure of DNA repair	DSBs	N/A
Alkaline Elution Assay with Time Course	Larsen et al. 1982	DNA with strand breaks elute faster than DNA without, plotted against time intervals to determine the rate at which strand breaks repair	SSBs	N/A
53BP1 foci Detection with Time Course	Penninckx et al. 2021	53BP1 is recruited to the site of DNA damage, the rate at which its level decreases over time is used to measure DNA repair	DSBs	N/A

 

References

Adimoolam, S. & J.M. Ford (2003), "p53 and regulation of DNA damage recognition during nucleotide excision repair" DNA Repair (Amst), 2(9): 947-54.

Aleksandrov, Radoslav et al. (2018), “Protein Dynamics in Complex DNA Lesions.” Molecular cell,69(6): 1046-1061.e5. doi:10.1016/j.molcel.2018.02.016 

Allgayer, J. et al. (2013), "Modulation of base excision repair of 8-oxoguanine by the nucleotide sequence", Nucleic Acids Res, 41(18): 8559-8571. Doi: 10.1093/nar/gkt620.

Beranek, D.T. (1990), "Distribution of methyl and ethyl adducts following alkylation with monofunctional alkylating agents", Mutation Research, 231(1): 11-30. Doi: 10.1016/0027-5107(90)90173-2.

Bhatti, A. et al., (2016), “Homologous Recombination Biology.”, Encyclopedia Britannica.

Bhowmick, R., S. et al. (2016), "RAD52 Facilitates Mitotic DNA Synthesis Following Replication Stress", Mol Cell, 64:1117-1126. Doi: 10.1016/j.molcel.2016.10.037.

Biedermann, A. K. et al. (1991), “SCID mutation in mice confers hypersensitivity to ionizing radiation and a deficiency in DNA double-strand break repair”, Cell Biology, 88(4): 1394-7. Doi: 10.1073/pnas.88.4.1394.

Boboila, C., F. W. Alt & B. Schwer. (2012), “Classical and alternative end-joining pathways for repair of lymphocyte-specific and general DNA double-strand breaks.” Adv Immunol, 116, 1-49. doi:10.1016/B978-0-12-394300-2.00001-6

Bronstein, S.M. et al. (1991), "Toxicity, mutagenicity, and mutational spectra of N-ethyl-N-nitrosourea in human cell lines with different DNA repair phenotypes", Cancer Research, 51(19): 5188-5197.

Bronstein, S.M. et al. (1992), "Efficient repair of O6-ethylguanine, but not O4-ethylthymine or O2-ethylthymine, is dependent upon O6-alkylguanine-DNA alkyltransferase and nucleotide excision repair activities in human cells", Cancer Research, 52(7): 2008-2011. 

Brown, J.A. et al. (2011), "Efficiency and fidelity of human DNA polymerases λ and β during gap-filling DNA synthesis", DNA Repair (Amst)., 10(1):24-33.

Butterworth, E. B. et al., (1987), A protocol and guide for the in vitro rat hepatocyte DNA-repair assay. Mutation Research. 189, 113-21. Doi: 10.1016/0165-1218(87)90017-6.

Caldecott, K. W. (2014), "DNA single-strand break repair", Exp Cell Res, 329(1): 2-8.

Chaudhuri, R.A. and Nussenzweig, A. (2017), “The multifaceted roles of PARP1 in DNA repair and chromatin remodelling”. Nat Rev Mol Cell Biol 18, 610–621. https://doi.org/10.1038/nrm.2017.53   

Chen, L. et al., (2001), Promotion of DNA ligase IV-catalyzed DNA end-joining by the Rad50/Mre11/Xrs2 and Hdf1/Hdf2 complexes. Mol Cell. 8(5), 1105-15.

Chiruvella, K. K., Z. Liang & T. E. Wilson, (2013), Repair of Double-Strand Breaks by End Joining. Cold Spring Harbor Perspectives in Biology, 5(5):127-57. Doi: 10.1101/cshperspect.a012757.

Clewell, R. A. et al. (2019). “Dose-dependence of chemical carcinogenicity: Biological mechanisms for thresholds and implications for risk assessment”. Chem Biol Interact. 2019 Mar 1;301:112-127. doi: 10.1016/j.cbi.2019.01.025. 

Corneo, B. et al., 2007, "Rag mutations reveal robust alternative end joining”. Nature 449, 483–486 (2007). https://doi.org/10.1038/nature06168   

Dahle, J., et al. (2008), “Overexpression of human OGG1 in mammalian cells decreases ultraviolet A induced mutagenesis”, Cancer Letters, Vol.267, Elsevier, Amsterdam, https://doi.org/10.1016/j.canlet.2008.03.002. 

Deem, A. et al. (2011), "Break-Induced Replication Is Highly Inaccurate.", PLoS Biol.  9:e1000594. Doi: 10.1371/journal.pbio.1000594.

Dianov, G.L. & U. Hübscher (2013), "Mammalian base excision repair: the forgotten archangel", Nucleic Acids Res., 41(6):3483-90. Doi: 10.1093/nar/gkt076.

Dilley, R.L. et al.  Greenberg (2016), "Break-induced telomere synthesis underlies alternative telomere maintenance", Nature, 539:54-58. Doi: 10.1038/nature20099.

Douglas, G.R. et al.  (1995), "Temporal and molecular characteristics of mutations induced by ethylnitrosourea in germ cells isolated from seminiferous tubules and in spermatozoa of lacZ transgenic mice", Proceedings of the National Academy of Sciences of the United States of America, 92(16):7485-7489. Doi: 10.1073/pnas.92.16.7485.

Dunkenberger, Logan et al. (2022), “Comet Assay for the Detection of Single and Double-Strand DNA Breaks.” Methods in molecular biology (Clifton, N.J.), 2422: 263-269. doi:10.1007/978-1-0716-1948-3_18 

Fattah, F. et al., (2010), Ku regulates the non-homologous end joining pathway choice of DNA double-strand break repair in human somatic cells. PLoS Genet, 6(2), doi:10.1371/journal.pgen.1000855

Fitzgerald, D.M., P.J. Hastings, and S.M. Rosenberg (2017), "Stress-Induced Mutagenesis: Implications in Cancer and Drug Resistance", Ann Rev Cancer Biol, 1:119-140. Doi: 10.1146/annurev-cancerbio-050216-121919.

Gorbunova, V. and A. Seluanov. (2016), “DNA double strand break repair, aging and the chromatin connection”, Mutation Research/Fundamental and Molecular Mechanisms of Mutagenesis, Vol.788/1-2, Elsevier, Amsterdam, http://dx.doi.org/10.1016/j.mrfmmm.2016.02.004. 

Hammel, M. et al., (2011), XRCC4 protein interactions with XRCC4-like factor (XLF) create an extended grooved scaffold for DNA ligation and double strand break repair. J Biol Chem, 286(37), 32638-32650. doi:10.1074/jbc.M111.272641.

Hanawalt, P.C., J.M. Ford and D.R. Lloyd (2003), "Functional characterization of global genomic DNA repair and its implications for cancer", Mutation Research, 544(2-3): 107–114.

Harbach, P. R. et al., (1989), “The in vitro unscheduled DNA synthesis (UDS) assay in rat primary hepatocytes”, Mutation Research, 216(2):101-10. Doi:10.1016/0165-1161(89)90010-1.

Iyama, T. and D.M. Wilson III (2013), "DNA repair mechanisms in dividing and non-dividing cells", DNA Repair, 12(8): 620– 636.

Jeffrey, M. A.& M. G. Williams, (2000), “Lack of DNA-damaging Activity of Five Non-nutritive Sweeteners in the Rat Hepatocyte/DNA Repair Assay”,  Food and Chemical Toxicology, 38: 335-338. Doi: 10.1016/S0278-6915(99)00163-5.

Köberle, B. et al. (1999), "Defective repair of cisplatin-induced DNA damage caused by reduced XPA protein in testicular germ cell tumours", Curr. Biol., 9(5):273-6. Doi: 10.1016/s0960-9822(99)80118-3.

Kozmin, S.G. & S. Jinks-Robertson S. (2013), “The mechanism of nucleotide excision repair-mediated UV-induced mutagenesis in nonproliferating cells”, Genetics, 193(3): 803-17. Doi: 10.1534/genetics.112.147421.

Kramara, J., B. Osia, and A. Malkova (2018), "Break-Induced Replication: The Where, The Why, and The How", Trends Genet, 34:518-531. Doi: 10.1016/j.tig.2018.04.002.

Kuhne, M., G. Urban and M. Lo (2005), "DNA Double-Strand Break Misrejoining after Exposure of Primary Human Fibroblasts to CK Characteristic X Rays, 29 kVp X Rays and 60Co γ Rays", Radiation. Research, Vol.164/5, Radiation Research Society, Indianapolis, https://doi.org/10.1667/RR3461.1. 

Larsen, K.H. et al. (1982), “DNA repair assays as tests for environmental mutagens: A report of the U.S. EPA gene-tox program”, Mutation Research, Vol.98/3, Elsevier, Amsterdam, https://doi.org/10.1016/0165-1110(82)90037-9. 

Li Z, A. H. Pearlman, and P. Hsieh (2016), "DNA mismatch repair and the DNA damage response", DNA Repair (Amst), 38:94-101.

Lieber, M. R., (2010), “The mechanism of double-strand DNA break repair by the nonhomologous DNA end-joining pathway.” Annu Rev Biochem. 79:181-211. doi:10.1146/annurev.biochem.052308.093131.

Lieber, M. R. et al., (2003), “Mechanism and regulation of human non-homologous DNA end-joining”, Nat Rev Mol Cell Biol. 4(9):712-720. doi:10.1038/nrm1202.

Liu, Y. et al. (2009), "Coordination between polymerase beta and FEN1 can modulate CAG repeat expansion", J. Biol. Chem., 284(41): 28352-28366. Doi: 10.1074/jbc.M109.050286.

Mao, Z. et al., (2011), “SIRT6 promotes DNA repair under stress by activating PARP1”, Science. 332(6036): 1443-1446. doi:10.1126/science.1202723.

Mariotti, L.G. et al. (2013), “Use of the γ-H2AX Assay to Investigate DNA Repair Dynamics Following Multiple Radiation Exposures”, PLoS ONE, Vol.8/11, PLoS, San Francisco, https://doi.org/10.1371/journal.pone.0079541. 

Matthews, L. A., & L. A. Simmons, (2014), “Bacterial nonhomologous end joining requires teamwork”, J Bacteriol. 196(19): 3363-3365. doi:10.1128/JB.02042-14.

Menoni, H. et al. (2012), "Base excision repair of 8-oxoG in dinucleosomes", Nucleic Acids Res. ,40(2): 692-700. Doi: 10.1093/nar/gkr761.

Minocherhomji, S. et al. (2015), "Replication stress activates DNA repair synthesis in mitosis", Nature, 528:286-290. Doi: 10.1038/nature16139.

Miyaoka, Y. et al., (2016), “Systematic quantification of HDR and NHEJ reveals effects of locus, nuclease, and cell type on genome-editing”, Sci Rep, 6, 23549. doi:10.1038/srep23549/.

Mladenov. et al.  (2023), . “New Facets of DNA Double Strand Break Repair: Radiation Dose as Key Determinant of HR versus c-NHEJ Engagement”. International journal of molecular sciences, 24(19), 14956. https://doi.org/10.3390/ijms241914956 

Moore, J. K., & J. E. Haber, (1996), “Cell cycle and genetic requirements of two pathways of nonhomologous end-joining repair of double-strand breaks in Saccharomyces cerevisiae”, Molecular and Cellular Biology, 16(5), 2164–73.  Doi: 10.1128/MCB.16.5.2164.

Nacci, D. et al. (1992), “Application of the DNA alkaline unwinding assay to detect DNA strand breaks in marine bivalves”, Marine Environmental Research, Vol.33/2, Elsevier BV, Amsterdam, https://doi.org/10.1016/0141-1136(92)90134-8. 

Nagel, Z.D. et al. (2014), "Multiplexed DNA repair assays for multiple lesions and multiple doses via transcription inhibition and transcriptional mutagenesis", Proc. Natl. Acad. Sci. USA, 111(18):E1823-32. Doi: 10.1073/pnas.1401182111.

O’Brien, J.M. et al. (2015), "Sublinear response in lacZ mutant frequency of Muta™ Mouse spermatogonial stem cells after low dose subchronic exposure to N-ethyl-N-nitrosourea", Environ. Mol. Mutagen., 56(4): 347-55. Doi: 10.1002/em.21932.

Olive, L. P., J. P. Bnath & E. R. Durand, (1990), “Heterogeneity in Radiation-Induced DNA Damage and Repairing Tumor and Normal Cells Measured Using the "Comet" Assay”, Radiation Research. 122: 86-94. Doi: 10.1667/rrav04.1.

Pardo, B., B. Gomez-Gonzalez & A. Aguilera, (2009), “DNA repair in mammalian cells: DNA double-strand break repair: how to fix a broken relationship”, Cell Mol Life Sci, 66(6), 1039-1056. doi:10.1007/s00018-009-8740-3.

Pegg, A.E. (2011), "Multifaceted roles of alkyltransferase and related proteins in DNA repair, DNA damage, resistance to chemotherapy, and research tools", Chem. Res. Toxicol., 4(5): 618-39. Doi: 10.1021/tx200031q.

Penninckx, S. et al. (2021), “Quantification of radiation-induced DNA double strand break repair foci to evaluate and predict biological responses to ionizing radiation”, NAR Cancer, Vol.3/4, Oxford University Press, Oxford, https://doi.org/10.1093/narcan/zcab046. 

Rydberg, B. et al. (2005), "Dose-Dependent Misrejoining of Radiation-Induced DNA Double-Strand Breaks in Human Fibroblasts: Experimental and Theoretical Study for High- and Low-LET Radiation", Radiation Research, Vol.163/5, Radiation Research Society, Indianapolis, https://doi.org/10.1667/RR3346.  

Sancar, A. (2003), "Structure and function of DNA photolyase and cryptochrome blue-light photoreceptors", Chem Rev., 103(6): 2203-37. Doi: 10.1021/cr0204348.

Saini, N. et al. (2017), "Migrating bubble during break-induced replication drives conservative DNA synthesis", Nature, 502:389-392. Doi: 10.1038/nature12584.

Sakofsky, C.J. et al. (2015), "Translesion Polymerases Drive Microhomology-Mediated Break-Induced Replication Leading to Complex Chromosomal Rearrangements", Mol Cell, 60:860-872. Doi: 10.1016/j.molcel.2015.10.041.

Schärer, O.D. (2013), "Nucleotide excision repair in eukaryotes", Cold Spring Harb. Perspect. Biol., 5(10): a012609. Doi: 10.1101/cshperspect.a012609.

Scherer, E., A.A. Jenner and L. den Engelse (1987), "Immunocytochemical studies on the formation and repair of O6-alkylguanine in rat tissues", IARC Sci Publ., 84: 55-8.

Seiler, F., K. Kamino, M. Emura, U. Mohr and J. Thomale (1997), "Formation and persistence of the miscoding DNA alkylation product O6-ethylguanine in male germ cells of the hamster", Mutat Res., 385(3): 205-211. Doi: 10.1016/s0921-8777(97)00043-8.

Shelby, M.D. and K.R. Tindall (1997), "Mammalian germ cell mutagenicity of ENU, IPMS and MMS, chemicals selected for a transgenic mouse collaborative study", Mutation Research, 388(2-3): 99-109. Doi: 10.1016/s1383-5718(96)00106-4.

Seo, Y.R. and H.J. Jung (2004), "The potential roles of p53 tumor suppressor in nucleotide excision repair (NER) and base excision repair (BER)", Exp. Mol. Med., 36(6): 505-509. Doi: 10.1038/emm.2004.64.

Sundheim, O. et al. (2008), "AlkB demethylases flip out in different ways", DNA Repair (Amst)., 7(11): 1916-1923. Doi: 10.1016/j.dnarep.2008.07.015.

Sung, P., & H. Klein, (2006), “Mechanism of homologous recombination: mediators and helicases take on regulatory functions”,  Nat Rev Mol Cell Biol, 7(10), 739-750. Doi:10. 1038/nrm2008.

Trucco, C., et al., (1998), “DNA repair defect i poly(ADP-ribose) polymerase-deficient cell lines”, Nucleic Acids Research. 26(11): 2644–2649. Doi: 10.1093/nar/26.11.2644.

Trzeciak, A.R. et al. (2008), “Age, sex, and race influence single-strand break repair capacity in a human population”, Free Radical Biology & Medicine, Vol. 45, Elsevier, Amsterdam, https://doi.org/10.1016/j.freeradbiomed.2008.08.031. 

White, R.R. and J. Vijg. (2016), “Do DNA Double-Strand Breaks Drive Aging?”, Molecular Cell, Vol.63, Elsevier, Amsterdam, http://doi.org/10.1016/j.molcel.2016.08.004. 

Wyrick, J.J. & S. A. Roberts, (2015), “Genomic approaches to DNA repair and mutagenesis”, DNA Repair (Amst). 36:146-155. doi: 10.1016/j.dnarep.2015.09.018.

van Zeeland, A.A., A. de Groot and A. Neuhäuser-Klaus (1990), "DNA adduct formation in mouse testis by ethylating agents: a comparison with germ-cell mutagenesis", Mutat. Res., 231(1): 55-62.

Event: 1635: Increase, DNA strand breaks

Short Name: Increase, DNA strand breaks

Event Component

AOPs Including This Key Event

Stressors

Biological Context

Domain of Applicability

Taxonomic Applicability Life Stage Applicability Sex Applicability

Taxonomic applicability: DNA strand breaks are relevant to all species, including vertebrates such as humans, that contain DNA (Cannan & Pederson, 2016).  

Life stage applicability: This key event is not life stage specific as all life stages display strand breaks. However, there is an increase in baseline levels of DNA strand breaks seen in older individuals though it is unknown whether this change due to increased break induction or a greater retention of breaks due to poor repair (White & Vijg, 2016). 

Sex applicability: This key event is not sex specific as both sexes display evidence of strand breaks. In some cell types, such as peripheral blood mononuclear cells, males show higher levels of single strand breaks than females (Garm et al., 2012). 

Evidence for perturbation by a stressor: There are studies demonstrating that increased DNA strand breaks can result from exposure to multiple stressor types including ionizing & non-ionizing radiation, chemical agents, and oxidizing agents (EPRI, 2014; Hamada, 2014; Cencer et al., 2018; Cannan & Pederson, 2016; Yang et al., 1998).  

Key Event Description

DNA strand breaks are a type of damage resulting from the hydrolysis of phosphodiester groups in the backbone of DNA molecules (Gates, 2009) and can occur on a single strand (single strand breaks; SSBs) or both strands (double strand breaks; DSBs). SSBs arise when the sugar phosphate backbones connecting adjacent nucleotides in DNA are simultaneously hydrolyzed such that the hydrogen bonds between complementary bases are not able to hold the two strands together. DSBs are generated when both strands are simultaneously broken at sites that are sufficiently close to one another that base-pairing and chromatin structure are insufficient to keep the two DNA ends juxtaposed. As a consequence, the two DNA ends generated by a DSB can physically dissociate from one another, becoming difficult to repair and increasing the chance of inappropriate recombination with other sites in the genome (Jackson, 2002). SSB can turn into DSB if the replication fork stalls at the lesion leading to fork collapse. Strand breaks are intermediates in various biological events, including DNA repair (e.g., excision repair), as well as other normal cellular processes where DSBs act as genetic shufflers to generate genetic diversity for V(D)J recombination in lymphoid cells, and chromatin remodeling in both somatic cells and germ cells, and meiotic recombination in gametes. 

Strand breaks are intermediates in various biological events, including DNA repair (e.g., excision repair), V(D)J recombination in developing lymphoid cells and chromatin remodeling in both somatic cells and germ cells. The spectrum of damage can be complex, particularily if the stressor is from large amounts of deposited energy which can result in complex lesions and clustered damage defined as two or more oxidized bases, abasic sites or strand breaks on opposing DNA strands within a few helical turns. These lesions are more difficult to repair and have been studied in many types of models (Barbieri et al., 2019 and Asaithamby et al., 2011). DSBs and complex lesions are of particular concern, as they are considered the most lethal and deleterious type of DNA lesion. If misrepaired or left unrepaired, DSBs may drive the cell towards genomic instability, apoptosis or tumorigenesis (Beir, 1999). 

How it is Measured or Detected

Please refer to the table below for details regarding these and other methodologies for detecting DNA DSBs. 

Method of Measurement	References	Description	OECD Approved Method?
Comet Assay (Single Cell Gel Eletrophoresis - Alkaline)	Collins, 2004; Olive and Banath, 2006; Platel et al., 2011; Nikolova et al., 2017	To detect SSBs or DSBs, single cells are encapsulated in agarose on a slide, lysed, and subjected to gel electrophoresis at an alkaline pH (pH >13); DNA fragments are forced to move, forming a "comet"-like appearance	Yes
γ-H2AX Foci Quantification - Flow Cytometry	Rothkamm and Horn, 2009; Bryce et al., 2016	Measurement of γ-H2AX immunostaining in cells by flow cytometry, normalized to total levels of H2AX	No
γ-H2AX Foci Quantification - Western Blot	Burma et al., 2001; Revet et al., 2011	Measurement of γ-H2AX immunostaining in cells by Western blotting, normalized to total levels of H2AX	No
γ-H2AX Foci Quantification - Microscopy	Redon et al., 2010; Mah et al., 2010; Garcia-Canton et al., 2013	Quantification of γ-H2AX immunostaining by counting γ-H2AX foci visualized with a microscope	No
γ-H2AX Foci Quantification - ELISA	Ji et al., 2017	Measurement of γ-H2AX in cells by ELISA, normalized to total levels of H2AX	No
Pulsed Field Gel Electrophoresis (PFGE)	Ager et al., 1990; Gardiner et al., 1985; Herschleb et al., 2007; Kawashima et al., 2017	To detect DSBs, cells are embedded and lysed in agarose, and the released DNA undergoes gel electrophoresis in which the direction of the voltage is periodically alternated; Large DNA fragments are thus able to be separated by size	No
The TUNEL (Terminal Deoxynucleotidyl Transferase dUTP Nick End Labeling) Assay	Loo, 2011	To detect strand breaks, dUTPs added to the 3’OH end of a strand break by the DNA polymerase terminal deoxynucleotidyl transferase (TdT) are tagged with a fluorescent dye or a reporter enzyme to allow visualization	No
In Vitro DNA Cleavage Assays using Topoisomerase	Nitiss, 2012	Cleavage of DNA can be achieved using purified topoisomerase; DNA strand breaks can then be separated and quantified using gel electrophoresis	No
PCR assay	Figueroa‑González & Pérez‑Plasencia, 2017	Assay of strand breaks through the observation of DNA amplification prevention. Breaks block Taq polymerase, reducing the number of DNA templates, preventing amplification	No
Sucrose density gradient centrifuge	Raschke et al. 2009	Division of DNA pieces by density, increased fractionation leads to lower density pieces, with the use of a sucrose cushion	No
Alkaline Elution Assay	Kohn, 1991	Cells lysed with detergent-solution, filtered through membrane to remove all but intact DNA	No
Unwinding Assay	Nacci et al. 1992	DNA is stored in alkaline solutions with DNA-specific dye and allowed to unwind following removal from tissue, increased strand damage associated with increased unwinding	Yes
STRIDE assay	Zilio and Ulrich, 2021	STRIDE (SensiTive Recognition of Individual DNA Ends) combines in situ nick translation with the proximity ligation assay (PLA) to detect single-strand breaks (sSTRIDE) or double-strand breaks (dSTRIDE). In this process, lesions labeled through nick translation with biotinylated nucleotides are identified by a PLA signal, which arises from the interaction of two anti-biotin antibodies from different species.	No
sBLISS	Bouwmann et al. 2020	sBLISS (in-suspension breaks labeling in situ and sequencing)  labels double-strand breaks (DSBs) in cells immobilized on glass coverslips, using double-stranded oligonucleotide adaptors that facilitate selective linear amplification through T7-mediated in vitro transcription (IVT), followed by next-generation sequencing (NGS) library preparation	No

References

Ager, D. D., et al. (1990). Measurement of radiation-induced DNA double-strand breaks by pulsed-field gel electrophoresis. Radiation research, 122/(2), 181–187. 

Anderson, D. & Laubenthal J. (2013), “Analysis of DNA Damage via Single-Cell Electrophoresis. In: Makovets S, editor. DNA Electrophoresis. Totowa.”, NJ: Humana Press. p 209-218. 

Asaithamby, A., B. Hu and D.J. Chen. (2011) “Unrepaired clustered DNA lesions induce chromosome breakage in human cells.” Proc Natl Acad Sci U S A 108(20): 8293-8298 . 

Barbieri, S., G. Babini, J. Morini et a l (2019). . Predicting DNA damage foci and their experimental readout with 2D microscopy: a unified approach applied to photon and neutron exposures. Scientific Reports 9(1): 14019 

Bouwman, B. et al. (2020), “Genome-wide detection of DNA double-strand breaks by in-suspension BLISS”, Nature protocols,.15/12, Springer Nature, London, https://doi.org/10.1038/s41596-020-0397-2  

Bryce, S. et al. (2016), “Genotoxic mode of action predictions from a multiplexed flow cytometric assay and a machine learning approach.”, Environ Mol Mutagen. 57:171-189. Doi: 10.1002/em.21996. 

Burma, S. et al. (2001), “ATM phosphorylates histone H2AX in response to DNA double-strand breaks.”, J Biol Chem, 276(45): 42462-42467. doi:10.1074/jbc.C100466200 

Cannan, W.J. and D.S. Pederson (2016), "Mechanisms and Consequences of Double-Strand DNA Break Formation in Chromatin.", Journal of Cellular Physiology, Vol.231(/1), Wiley, New York, https://doi.org/10.1002/jcp.25048.  

Cencer, C. et al. (2018), “PARP-1/PAR Activity in Cultured Human Lens Epithelial Cells Exposed to Two Levels of UVB Light”, Photochemistry and Photobiology, Vol.(94/1), Wiley-Blackwell, Hoboken, https://doi.org/10.1111/php.12814.  

Charlton, E. D. et al. (1989), “Calculation of Initial Yields of Single and Double Stranded Breaks in Cell Nuclei from Electrons, Protons, and Alpha Particles.”, Int. J. Radiat. Biol. 56(1): 1-19. doi: 10.1080/09553008914551141. 

Collins, R. A. (2004), “The Comet Assay for DNA Damage and Repair. Molecular Biotechnology.”, Mol Biotechnol. 26(3): 249-61. doi:10.1385/MB:26:3:249 

EPRI (2014), Epidemiology and mechanistic effects of radiation on the lens of the eye: Review and scientific appraisal of the literature, EPRI, California. 

Figueroa‑González, G. and C. Pérez‑Plasencia. (2017), “Strategies for the evaluation of DNA damage and repair mechanisms in cancer”, Oncology Letters, Vol.133(/6), Spandidos Publications, Athens, https://doi.org/10.3892/ol.2017.6002. 

Garcia-Canton, C. et al. (2013), “Assessment of the in vitro p-H2AX assay by High Content Screening asa novel genotoxicity test.”, Mutat Res. 757:158-166. Doi: 10.1016/j.mrgentox.2013.08.002 

Gardiner, K. et al. (1986), “Fractionation of Large Mammalian DNA Restriction Fragments Using Vertical Pulsed-Field Gradient Gel Electrophoresis.”, Somatic Cell and Molecular Genetics. 12(2): 185-95.Doi: 10.1007/bf01560665. 

Garm, C. et al. (2012), “Age and gender effects on DNA strand break repair in peripheral blood mononuclear cells”, Aging Cell, Vol.12/1, Blackwell Publishing Ltd, Oxford, https://doi.org/10.1111/acel.12019. 

Hamada, N. (2014), “What are the intracellular targets and intratissue target cells for radiation effects?”, Radiation research, Vol. 181/1, The Radiation Research Society, Indianapolis, https://doi.org/10.1667/RR13505.1. 

Herschleb, J. et al. (2007), “Pulsed-field gel electrophoresis.”, Nat Protoc. 2(3): 677-684. doi:10.1038/nprot.2007.94 

Iliakis, G. et al. (2015), “Alternative End-Joining Repair Pathways Are the Ultimate Backup for Abrogated Classical Non-Homologous End-Joining and Homologous Recombination Repair: Implications for the Formation of Chromosome Translocations.”, Mutation Research/Genetic Toxicology and Environmental Mutagenesis. 2(3): 677-84. doi: 10.1038/nprot.2007.94 

Jackson, S. (2002). “Sensing and repairing DNA double-strand breaks.”, Carcinogenesis. 23:687-696. Doi:10.1093/carcin/23.5.687. 

Ji, J. et al. (2017), “Phosphorylated fraction of H2AX as a measurement for DNA damage in cancer cells and potential applications of a novel assay.”, PLoS One. 12(2): e0171582. doi:10.1371/journal.pone.0171582 

Kawashima, Y.(2017), “Detection of DNA double-strand breaks by pulsed-field gel electrophoresis.”, Genes Cells 22:84-93. Doi: 10.1111/gtc.12457. 

Khoury, L. et al. (2013), “Validation of high-throughput genotoxicity assay screening using cH2AX in-cell Western assay on HepG2 cells.”, Environ Mol Mutagen, 54:737-746. Doi: 10.1002/em.21817. 

Khoury, L. et al. (2016), “Evaluation of four human cell lines with distinct biotransformation properties for genotoxic screening.”, Mutagenesis, 31:83-96. Doi: 10.1093/mutage/gev058. 

Kohn, K.W. (1991), “Principles and practice of DNA filter elution”, Pharmacology & Therapeutics, Vol.49(/1), Elsevier, Amsterdam, https://doi.org/10.1016/0163-7258(91)90022-E. 

Loo, DT. (2011), “In Situ Detection of Apoptosis by the TUNEL Assay: An Overview of Techniques. In: Didenko V, editor. DNA Damage Detection In Situ, Ex Vivo, and In Vivo. Totowa.”, NJ: Humana Press. p 3-13.doi: 10.1007/978-1-60327-409-8_1. 

Mah, L. J. et al. (2010), “Quantification of gammaH2AX foci in response to ionising radiation.”, J Vis Exp(38). doi:10.3791/1957. 

Nacci, D. et al. (1992), “Application of the DNA alkaline unwinding assay to detect DNA strand breaks in marine bivalves”, Marine Environmental Research, Vol.33(/2), Elsevier BV, Amsterdam, https://doi.org/10.1016/0141-1136(92)90134-8. 

Nikolova, T., F. et al. (2017), “Genotoxicity testing: Comparison of the γH2AX focus assay with the alkaline and neutral comet assays.”, Mutat Res 822:10-18. Doi: 10.1016/j.mrgentox.2017.07.004. 

Nitiss, J. L. et al. (2012), “Topoisomerase assays. ”, Curr Protoc Pharmacol. Chapter 3: Unit 3 3. 

OECD. (2014). Test No. 489: “In vivo mammalian alkaline comet assay.” OECD Guideline for the Testing of Chemicals, Section 4 . 

Olive, P. L., & Banáth, J. P. (2006), “The comet assay: a method to measure DNA damage in individual cells.”, Nature Protocols. 1(1): 23-29. doi:10.1038/nprot.2006.5. 

Platel A. et al. (2011), “Study of oxidative DNA damage in TK6 human lymphoblastoid cells by use of the thymidine kinase gene-mutation assay and the in vitro modified comet assay: Determination of No-Observed-Genotoxic-Effect-Levels.”, Mutat Res 726:151-159. Doi: 10.1016/j.mrgentox.2011.09.003. 

Raschke, S., J. Guan and G. Iliakis. (2009), “Application of alkaline sucrose gradient centrifugation in the analysis of DNA replication after DNA damage”, Methods in Molecular Biology, Vol.521, Humana Press, Totowa, https://doi.org/10.1007/978-1-60327-815-7_18. 

Redon, C. et al. (2010), “The use of gamma-H2AX as a biodosimeter for total-body radiation exposure in non-human primates.”, PLoS One. 5(11): e15544. doi:10.1371/journal.pone.0015544 

Revet, I. et al. (2011), “Functional relevance of the histone γH2Ax in the response to DNA damaging agents.” Proc Natl Acad Sci USA.108:8663-8667. Doi: 10.1073/pnas.1105866108 

Rogakou, E.P. et al. (1998), “DNA Double-stranded Breaks Induce Histone H2AX Phosphorylation on Serine 139.” , J Biol Chem, 273:5858-5868. Doi: 10.1074/jbc.273.10.5858 

Rothkamm, K. & Horn, S. (2009), “γ-H2AX as protein biomarker for radiation exposure.”, Ann Ist Super Sanità, 45(3): 265-71. 

White, R.R. and J. Vijg. (2016), “Do DNA Double-Strand Breaks Drive Aging?”, Molecular Cell, Vol.63, Elsevier, Amsterdam, http://doi.org/10.1016/j.molcel.2016.08.004. 

Yang, Y. et al. (1998), “The effect of catalase amplification on immortal lens epithelial cell lines”, Experimental Eye Research, Vol.67(/6), Academic Press Inc, Cambridge, https://doi.org/10.1006/exer.1998.0560.  

Zilio, N. and H. D. Ulrich (2021), “Exploring the SSBreakome: genome-wide mapping of DNA single-strand breaks by next-generation sequencing”, The FEBS journal, 288(13), Wiley, Hoboken, https://doi.org/10.1111/febs.15568 

 

Event: 1505: Increase, Cell cycle disruption

Short Name: Cell cycle disruption

Event Component

AOPs Including This Key Event

Biological Context

Cell term

Organ term

Domain of Applicability

Taxonomic Applicability Life Stage Applicability Sex Applicability

The histone gene expression alters in each phase of the cell cycle in human HeLa cells (Homo sapiens) [Heintz et al., 1982].

Key Event Description

The disruption of the cell cycle leads to a decrease in cell number. The cell cycle consists of G₁, S, G₂, M, and G₀ phases. The cell cycle regulation is disrupted by the cell cycle arrest in certain cell cycle phases. The histone gene expression is regulated in cell cycle phases [Heintz et al., 1983].

How it is Measured or Detected

The percentage of cells at G₁, G₀, S, and G₂/M phases can be detected by flow cytometry  [Li et al., 2013]. Cell cycle distribution was analyzed by fluorescence-activated cell sorter (FACS) analysis with a Partec PAS-II sorter [Zupkovitz et al., 2010]. The four cell-cycle phases in living cells can be measured with four-color fluorescent proteins using live-cell imaging [Bajar et al., 2016]. The incorporation of [³H]deoxycytidine or [³H]thymidine into cell DNA during the S phase can be monitored as DNA synthesis [Heintz et al., 1982].

References

Bajar, B.T. et al. (2016), "Fluorescent indicators for simultaneous reporting of all four cell cycle phases", Nat Methods 13:993-996 

Heintz, N. et al. (1983), "Regulation of human histone gene expression: Kinetics of accumulation and changes in the rate of synthesis and in the half-lives of individual histone mRNAs during the HeLa cell cycle", Molecular and Cellular Biology 3:539-550

Li, Q. et al. (2013), "Glyphosate and AMPA inhibit cancer cell growth through inhibiting intracellular glycine synthesis", Drug Des Devel Ther 7:635-643

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