Reactive oxygen species leading to growth inhibition via protein oxidation and decreased cell proliferation

You Song, Li Xie, Knut Erik Tollefsen

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

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

AOP 332 reuses and connects established AOP-Wiki components from two major AOP contexts. The upstream ROS/oxidative stress module is associated with AOP 478, in which deposition of energy leads to oxidative stress through free radical generation and oxidative molecular damage (AOP-Wiki, 2026a). AOP 478 provides an AOP-Wiki precedent for oxidative stress as a conserved KE downstream of radical-generating stressors and for protein damage as an oxidative stress consequence. The downstream bioenergetic and growth module is directly associated with AOP 263, which causally links decreased coupling of OXPHOS to growth inhibition through ATP depletion and decreased cell proliferation (AOP-Wiki, 2026b; OECD, 2022; Song and Villeneuve, 2021). Thus, AOP 332 links an oxidative protein damage module to an OECD-endorsed OXPHOS-to-growth module. The AOP is relevant to environmental and human health contexts because ROS generation, protein oxidation, mitochondrial ATP production, cell proliferation, and organismal growth are broadly conserved in aerobic eukaryotes. Empirical support comes from studies in algae, fish, mollusks, mammalian systems, and human cells exposed to metals, hydrogen peroxide, hypoxia-reoxygenation, salinity or temperature stress, endogenous aging, and other oxidative stressors. This AOP can support mechanistic interpretation of oxidative stress-mediated growth impairment, assay selection, chemical prioritization, IATA development, and future quantitative AOP approaches for mitochondrial and oxidative stress-related toxicity.

Acknowledgement

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

AI disclosure

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

ROS are continuously formed during aerobic metabolism and can also be generated in response to environmental stressors. At controlled levels, ROS participate in redox signaling, whereas excessive ROS can disturb redox homeostasis and initiate oxidative stress (Schieber and Chandel, 2014; Sies et al., 2017). Proteins are major targets of oxidative attack because many amino acid side chains and prosthetic groups are susceptible to oxidation, carbonylation, thiol oxidation, nitration, or other oxidative modifications. Protein oxidation can alter enzyme activity, protein-protein interactions, protein folding, stability, and degradation, and it is widely used as a marker of severe oxidative damage and cellular dysfunction (Dalle-Donne et al., 2006).

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

AOP 332 was developed using the principles described in OECD AOP guidance, including modular description of KEs and KERs, reuse of existing AOP-Wiki content where appropriate, evidence evaluation using biological plausibility, empirical support, essentiality, and quantitative understanding, and clear description of the biological domain of applicability (OECD, 2018, 2021). The objective was to assemble a focused linear pathway from reusable AOP-Wiki elements rather than to create an isolated de novo pathway. This is important because AOP 332 is one branch of the broader ROS-growth AOP network and because its downstream KEs and KERs overlap with the well-developed mitochondrial bioenergetics AOP 263.

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

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

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

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

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

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

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

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