This AOP is licensed under the BY-SA license. This license allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use. If you remix, adapt, or build upon the material, you must license the modified material under identical terms.

AOP: 263

Title

A descriptive phrase which references both the Molecular Initiating Event and Adverse Outcome.It should take the form “MIE leading to AO”. For example, “Aromatase inhibition leading to reproductive dysfunction” where Aromatase inhibition is the MIE and reproductive dysfunction the AO. In cases where the MIE is unknown or undefined, the earliest known KE in the chain (i.e., furthest upstream) should be used in lieu of the MIE and it should be made clear that the stated event is a KE and not the MIE.  More help

Uncoupling of oxidative phosphorylation leading to growth inhibition via decreased cell proliferation

Short name
A name that succinctly summarises the information from the title. This name should not exceed 90 characters. More help
Uncoupling of OXPHOS leading to growth inhibition 1

Graphical Representation

A graphical representation of the AOP.This graphic should list all KEs in sequence, including the MIE (if known) and AO, and the pair-wise relationships (links or KERs) between those KEs. More help
Click to download graphical representation template Explore AOP in a Third Party Tool

Authors

The names and affiliations of the individual(s)/organisation(s) that created/developed the AOP. More help

You Songa and Daniel L. Villeneuveb

a Norwegian Institute for Water Research (NIVA), Økernveien 94, NO-0579 Oslo, Norway

b U.S. Environmental Protection Agency, Great Lakes Toxicology and Ecology Division, Duluth, Minnesota 55804, USA

Acknowledgement

This project was funded by the Research Council of Norway (RCN), grant no. 301397 “RiskAOP - Quantitative Adverse Outcome Pathway assisted risk assessment of mitochondrial toxicants” (https://www.niva.no/en/projectweb/riskaop), and supported by the NIVA Computational Toxicology Program, NCTP (www.niva.no/nctp).

Point of Contact

The user responsible for managing the AOP entry in the AOP-KB and controlling write access to the page by defining the contributors as described in the next section.   More help

Contributors

Users with write access to the AOP page.  Entries in this field are controlled by the Point of Contact. More help
  • You Song
  • Dan Villeneuve

Coaches

This field is used to identify coaches who supported the development of the AOP.Each coach selected must be a registered author. More help

Status

Provides users with information concerning how actively the AOP page is being developed, what type of use or input the authors feel comfortable with given the current level of development, and whether it is part of the OECD AOP Development Workplan and has been reviewed and/or endorsed. OECD Status - Tracks the level of review/endorsement the AOP has been subjected to. OECD Project Number - Project number is designated and updated by the OECD. SAAOP Status - Status managed and updated by SAAOP curators. More help
Handbook Version OECD status OECD project
v2.0 WPHA/WNT Endorsed 1.92
This AOP was last modified on April 29, 2023 16:03

Revision dates for related pages

Page Revision Date/Time
Decrease, Coupling of oxidative phosphorylation May 28, 2021 07:59
Decrease, Growth July 06, 2022 07:36
Decrease, Adenosine triphosphate pool June 14, 2021 13:40
Decrease, Cell proliferation December 07, 2020 06:55
Decrease, Coupling of OXPHOS leads to Decrease, ATP pool July 06, 2022 07:39
Decrease, ATP pool leads to Decrease, Cell proliferation December 07, 2020 07:43
Decrease, Cell proliferation leads to Decrease, Growth July 06, 2022 07:43
2,4-Dinitrophenol November 29, 2016 18:42
Pentachlorophenol November 12, 2020 17:59
Carbonyl cyanide-p-trifluoromethoxyphenylhydrazone November 12, 2020 17:59
Carbonyl cyanide m-chlorophenyl hydrazone November 12, 2020 17:59
Triclosan November 12, 2020 18:00
Dinoseb November 12, 2020 18:00
3,5-Dichlorophenol October 10, 2017 07:47
Emodin November 20, 2020 13:48
Arsenite March 07, 2019 06:14
Niclosamide ethanolamine July 06, 2022 07:24
Oxyclozanide July 06, 2022 07:25

Abstract

A concise and informative summation of the AOP under development that can stand-alone from the AOP page. The aim is to capture the highlights of the AOP and its potential scientific and regulatory relevance. More help

Uncoupling of oxidative phosphorylation (OXPHOS) is a well-known mechanism of action of many chemicals. Mitochondrial uncoupler-mediated energetic dysfunction is known to affect growth, a critical process in most organisms and a chronic toxicity endpoint included in many OECD test guidelines. This adverse outcome pathway (AOP) causally links uncoupling of OXPHOS to growth inhibition, through ATP depletion and reduced cell proliferation as the intermediate key events (KEs), with strong weight of evidence support. The AOP is generalized to reflect its expected applicability to a broad range of taxa, ranging from microalga to human. Three out of four KEs included can be quantified using high-throughput methods, making this AOP particularly useful for screening, prioritization and hazard assessment of mitochondrial uncouplers as potential growth inhibiting chemicals. This AOP is of high regulatory relevance, as it is considered applicable to both human health and ecological risk assessments. The AOP also forms the core of a larger AOP network addressing uncoupling of OXPHOS mediated growth inhibition (AOP 263-268).

AOP Development Strategy

Context

Used to provide background information for AOP reviewers and users that is considered helpful in understanding the biology underlying the AOP and the motivation for its development.The background should NOT provide an overview of the AOP, its KEs or KERs, which are captured in more detail below. More help

The mitochondrial OXPHOS machinery is a key physiological process responsible for producing the primary cellular energy, adenosine triphosphate (ATP). During OXPHOS, a series of redox reactions (oxidation) are mediated by protein complexes in an electron transport chain to create a protonmotive force (PMF) across the inner mitochondrial membrane (Liberman 1969). The PMF acts as a driving force of ATP synthesis through phosphorylation of adenosine diphosphate (ADP). Mitochondrial oxidation and phosphorylation are coupled to ensure continuous ATP supply for various physiological processes. A number of chemicals can bind to the inner mitochondrial membrane and dissipate the PMF, thus leading to uncoupling of OXPHOS and reduction in ATP synthetic efficiency. Classical “uncouplers” are normally protonophores with major characteristics of bulky hydrophobic moiety, an acid dissociable group and a strong electron-withdrawing group (Terada 1990). With the rapid development of in silico (Russom 1997; Schultz 1997; Naven 2012; Dreier 2019; Troger 2020) and in vitro (Escher 2002; Attene-Ramos 2013; Attene-Ramos 2015; Xia 2018) approaches, more and more uncouplers have been identified. However, their hazards to biota remain to be assessed. Uncoupling of OXPHOS can affect many ATP-dependent biological functions. In particular, cell proliferation as a major process to achieve organismal growth is positively correlated with the cellular ATP level and highly susceptible to energy depletion (Ramaiah 1964; Bonora 2012). Therefore, a link between uncoupling of OXPHOS and growth inhibition can be established with ATP depletion and reduced cell proliferation as the intermediate steps.

Strategy

Provides a description of the approaches to the identification, screening and quality assessment of the data relevant to identification of the key events and key event relationships included in the AOP or AOP network.This information is important as a basis to support the objective/envisaged application of the AOP by the regulatory community and to facilitate the reuse of its components.  Suggested content includes a rationale for and description of the scope and focus of the data search and identification strategy/ies including the nature of preliminary scoping and/or expert input, the overall literature screening strategy and more focused literature surveys to identify additional information (including e.g., key search terms, databases and time period searched, any tools used). More help

Summary of the AOP

This section is for information that describes the overall AOP.The information described in section 1 is entered on the upper portion of an AOP page within the AOP-Wiki. This is where some background information may be provided, the structure of the AOP is described, and the KEs and KERs are listed. More help

Events:

Molecular Initiating Events (MIE)
An MIE is a specialised KE that represents the beginning (point of interaction between a prototypical stressor and the biological system) of an AOP. More help
Key Events (KE)
A measurable event within a specific biological level of organisation. More help
Adverse Outcomes (AO)
An AO is a specialized KE that represents the end (an adverse outcome of regulatory significance) of an AOP. More help
Type Event ID Title Short name
MIE 1446 Decrease, Coupling of oxidative phosphorylation Decrease, Coupling of OXPHOS
KE 1771 Decrease, Adenosine triphosphate pool Decrease, ATP pool
KE 1821 Decrease, Cell proliferation Decrease, Cell proliferation
AO 1521 Decrease, Growth Decrease, Growth

Relationships Between Two Key Events (Including MIEs and AOs)

This table summarizes all of the KERs of the AOP and is populated in the AOP-Wiki as KERs are added to the AOP.Each table entry acts as a link to the individual KER description page. More help
Title Adjacency Evidence Quantitative Understanding

Network View

This network graphic is automatically generated based on the information provided in the MIE(s), KEs, AO(s), KERs and Weight of Evidence (WoE) summary tables. The width of the edges representing the KERs is determined by its WoE confidence level, with thicker lines representing higher degrees of confidence. This network view also shows which KEs are shared with other AOPs. More help

Prototypical Stressors

A structured data field that can be used to identify one or more “prototypical” stressors that act through this AOP. Prototypical stressors are stressors for which responses at multiple key events have been well documented. More help

Life Stage Applicability

The life stage for which the AOP is known to be applicable. More help
Life stage Evidence
Embryo High
Juvenile High
Adult High

Taxonomic Applicability

Latin or common names of a species or broader taxonomic grouping (e.g., class, order, family) can be selected.In many cases, individual species identified in these structured fields will be those for which the strongest evidence used in constructing the AOP was available. More help
Term Scientific Term Evidence Link
zebrafish Danio rerio High NCBI
Lemna minor Lemna minor Moderate NCBI
human Homo sapiens Moderate NCBI
mouse Mus musculus High NCBI
rat Rattus norvegicus High NCBI
Caenorhabditis elegans Caenorhabditis elegans Moderate NCBI

Sex Applicability

The sex for which the AOP is known to be applicable. More help
Sex Evidence
Unspecific High

Overall Assessment of the AOP

Addressess the relevant biological domain of applicability (i.e., in terms of taxa, sex, life stage, etc.) and Weight of Evidence (WoE) for the overall AOP as a basis to consider appropriate regulatory application (e.g., priority setting, testing strategies or risk assessment). More help

The weight of evidence (WoE) assessment of the AOP was conducted based on the evolved Bradford-Hill considerations (Becker 2015) and according to the criteria in OECD’s Guidance Document for Developing and Assessing AOPs (OECD 2018). In terms of evidence for the essentiality of the key events, the MIE (Event 1446) and KE1 (Event 1771) were scored as high, whereas KE2 (Event 1821) was scored as moderate due to a lack of solid evidence to support its essentiality. The overall WoE of KER1 (Relationship 2203) is considered high, as strong biological plausibility, empirical evidence and fairly good quantitative understanding were evidenced from multiple studies. The overall WoE of KER2 (Relationship 2204) is considered moderate, due to high biological plausibility, acceptable empirical concordance and some biological understanding. The overall WoE of KER3 (Relationship 2205) is scored as moderate, mainly due to biological plausibility, but there is presently a lack of empirical evidence and quantitative understanding to further support causality. The AOP is considered applicable to a wide range of species as well as a broad domain of chemicals. The rationales for making these judgements will be discussed in detail in the following sections.

Domain of Applicability

Addressess the relevant biological domain(s) of applicability in terms of sex, life-stage, taxa, and other aspects of biological context. More help

The taxonomic application domain of the AOP potential covers all animals, plants and some microorganisms such as fungus and protists, as mitochondrial OXPHOS is highly conserved in eukaryotes (Roger 2017).

The life stage applicability domain of the AOP mainly contains embryos and juveniles, as growth is more relevant to developing organisms. It should be noted that fully grown adults are also susceptible to uncouplers, as tissue/organ (e.g., adipose tissue) growth and regeneration still occur in adults (Yun 2015; Demine 2019). Classical uncouplers such as 2,4-DNP have been reported to cause weight loss in adult humans (Grundlingh 2011). In fact, 2,4-DNP was sold for weight loss until its legal sale was banned over toxicity and abuse concerns (Baker 2020). These suggest that adults are in the applicability domain of this AOP. 

The sex applicability domain of the AOP is unspecific, as the AOP is mainly targeting growth effects in sexually immature organisms and the KEs are therefore harmonized between male and females. However, male and females may have different sensitivities to OXPHOS uncoupling, as strategies for allocating energy for developmental processes may be gender specific (Demarest 2015).

The chemical applicability domain of the AOP mainly includes weak acids, such as phenols, benzimidazoles, N-phenylanthranilates, salicylanilides, phenylhydrazones, salicylic acids, acyldithiocarbazates, cumarines, and aromatic amines, which are well-known protonophoric uncouplers. Uncouplers typically have properties as both weak acids and hydrophobic substances. As weak acids, they are capable of gaining and losing an electron. As hydrophobic substances, they are capable of distributing a negative charge over a number of atoms (often by π-orbitals which delocalize a proton's charge when it attaches to the molecule), so that they can diffuse back and forth across the inner mitochondrial membrane in either the charged or uncharged state, thus moving protons back across the concentration gradient generated by the electron transport chain. Classical uncouplers, such as 2,4-dinitrophenol (2,4-DNP), carbonyl cyanide-p-trifluoromethoxyphenyl hydrazone (FCCP), carbonyl cyanide m-chlorophenyl hydrazone (CCCP), pentachlorophenol (PCP), 3,5-dichlorophenol (3,5-DCP), 6-sec-butyl-2,4-dinitrophenol (dinoseb), SF 6847 (3,5-di-t-butyl-4-hydroxybenzylidinemalononitrile) have been widely used as positive controls in (eco)toxicological tests, whereas the hazards of “new” uncouplers, such as triclosan, emodin and metabolites of polybrominated diphenyl ethers (PBDEs) are also under extensive assessments. Other types of uncouplers that are SH-reactive chemicals or hydrophobic ions may also be in the applicability domain of this AOP. A number of potential uncouplers have been identified by in silico (Russom 1997; Schultz 1997; Naven 2012; Dreier 2019; Troger 2020) and in vitro (Escher 2002; Attene-Ramos 2013; Attene-Ramos 2015; Xia 2018) approaches, and are considered in the chemical applicability domain of the AOP.

Essentiality of the Key Events

The essentiality of KEs can only be assessed relative to the impact of manipulation of a given KE (e.g., experimentally blocking or exacerbating the event) on the downstream sequence of KEs defined for the AOP. Consequently, evidence supporting essentiality is assembled on the AOP page, rather than on the independent KE pages that are meant to stand-alone as modular units without reference to other KEs in the sequence. The nature of experimental evidence that is relevant to assessing essentiality relates to the impact on downstream KEs and the AO if upstream KEs are prevented or modified. This includes: Direct evidence: directly measured experimental support that blocking or preventing a KE prevents or impacts downstream KEs in the pathway in the expected fashion. Indirect evidence: evidence that modulation or attenuation in the magnitude of impact on a specific KE (increased effect or decreased effect) is associated with corresponding changes (increases or decreases) in the magnitude or frequency of one or more downstream KEs. More help

Support for Essentiality of KEs

Defining Question

What is the impact on downstream KEs and/or the AO if an upstream KE is modified or prevented?

High

Direct evidence from specifically designed experimental studies illustrating prevention or impact on downstream KEs and/or the AO if upstream KEs are blocked or modified.

Moderate

Indirect evidence that modification of one or more upstream KEs is associated with a corresponding (increase or decrease) in the magnitude or frequency of downstream KEs.

Low

No or contradictory experimental evidence of the essentiality of any of the KEs.

Event 1446:

(Decrease, Coupling of OXPHOS)

Essentiality of Event 1446 is high.

Rationale: There is direct evidence from several specifically designed studies showing that removal of an uncoupler from exposure, or addition of a “recoupler” can lead to recovery of the mitochondrial membrane potential (MMP) and total ATP caused by the uncoupler.

Evidence:

  • Removal of the classical uncoupler carbonyl cyanide-p-trifluoromethoxyphenylhydrazone (FCCP) led to recovery of both MMP and ATP in rat cerebellar granule cells (Weisová 2012).
  • In the red abalone (Haliotis rufescens) larvae, removal of the uncoupler pentachlorophenol also led to recovery of the ATP level (Shofer 2002).
  • Addition of the recoupler GDP led to a rapid increase in ATP/ADP ratio in isolated guinea pig brown-adipose-tissue mitochondria where high activities of natural coupling by the UCPs were expected (Rafael 1976).
  • Addition of octanoate to 2,4-DNP exposed rat hepatocytes mitigated the uncoupling effect and partial restored the ATP/ADP ratio (Sibille 1995).
  • Removal of FCCP led to recovery from FCCP-mediated MMP and ATP reduction in Swiss mouse embryos (Zander-Fox 2015).

Event 1771:

(Decrease, ATP pool)

 

Essentiality of Event 1771 is moderate.

Rationale: There is limited direct evidence from specifically designed studies. However, multiple lines of indirect evidence show that modulation of ATP levels by uncouplers can also lead to corresponding changes in cell proliferation.

Evidence:

  • Addition of emodin blunted ATP-induced cell proliferation in a concentration-dependent manner in human lung adenocarconoma (A549) cells (Wang 2017), hence providing direct evidence to support the essentiality of this KE.
  • Positive relationships between uncoupler-mediated ATP depletion and reduced cell proliferation have been documented by multiple studies(Sweet 1999; Fine 2009; Guimarães 2012; Sugiyama 2019).

Event 1821:

(Decrease, Cell proliferation)

Essentiality of Event 1821  is moderate.

Rationale: There is no direct evidence from specifically designed studies to support this KE. However, there are multiple lines of indirect evidence showing positive relationships between cell proliferation and growth.

Evidence:

  • Indirect evidence can be obtained from a limited number of relevant studies showing a positive role of cell proliferation in mammalian tumor (Figarola 2018) zebrafish embryo growth(Bestman 2015).
  • Indirect evidence showing that the mitochondrial uncouplers niclosamide ethanolamine and oxyclozanide either completely prevented or drastically reduced hepatic metastasis of colon cancer cells from spleen (Alasadi et al., 2018).

Inconsistencies & uncertainties

There is an uncertainty related to KE1446 that mild uncoupling of OXPHOS may also increase the ATP pool in some cases (Desquiret 2006), possibly as a compensatory response. The underlying mechanism remains to be further elucidated.

Evidence Assessment

Addressess the biological plausibility, empirical support, and quantitative understanding from each KER in an AOP. More help

Biological plausibility

Support for Biological Plausibility of KERs

Defining Question

Is there a mechanistic (i.e., structural or functional) relationship between KEup and KEdown consistent with established biological knowledge?

High

Extensive understanding based on extensive previous documentation and broad acceptance -Established mechanistic basis.

Moderate

The KER is plausible based on analogy to accepted biological relationships but scientific understanding is not completely established.

Low

There is empirical support for a statistical association between KEs, but the structural or functional relationship between them is not understood.

Relationship 2203:

(Decrease, Coupling of OXPHOS leads to Decrease, ATP pool)

Biological Plausibility of Relationship 2203 is high.

Rationale: In eukaryotic cells, the major metabolic pathways responsible for ATP production are OXPHOS, citric acid (TCA) cycle, glycolysis and photosynthesis. Oxidative phosphorylation is much (theoretically 15-18 times) more efficient than the rest due to high energy derived from oxygen during aerobic respiration (Schmidt-Rohr 2020). As the ATP level is relatively balanced between production and consumption (Bonora 2012), ATP depletion is a plausible consequence of reduced ATP synthetic efficiency following uncoupling of OXPHOS.

Relationship 2204:

(Decrease, ATP pool leads to Decrease, Cell proliferation)

Biological Plausibility of Relationship 2204 is high.

Rationale: Cell proliferation is a well-known ATP-dependent process. Cell division processes, such as the mitotic cell cycle uses ATP for chromosome movements and DNA replication (Kingston 1999). The synthetic processes of major cellular components that are necessary for cell structure and growth, such as proteins and lipids, also require sufficient ATP supply (Bonora 2012). Depletion of ATP therefore has a negative impact on these processes.

Relationship 2205:

(Decrease, Cell proliferation leads to Decrease, Growth)

Biological Plausibility of Relationship 2205 is high.

Rationale: The biological causality between cell proliferation and growth has also been well established. It is commonly accepted that the size of an organism, organ or tissue is dependent on the total number and volume of the cells it contains, and the amount of extracellular matrix and fluids (Conlon 1999). Impairment to cell proliferation can logically affect tissue and organismal growth.

Inconsistencies & uncertainties

There are currently no inconsistencies and uncertainties identified by the authors.

Empirical support

Empirical Support for KERs

Defining Question

Does KEup occur at lower doses and earlier time points than KE down and at the same dose of stressor, is the incidence of KEup >than that for KEdown? Are there inconsistencies in empirical support across taxa, species and stressors that don’t align with expected pattern for hypothesized AOP?

High

Multiple studies showing dependent change in both events following exposure to a wide range of specific stressors. (Extensive evidence for temporal, dose- response and incidence concordance) and no or few critical data gaps or conflicting data.

Moderate

Demonstrated dependent change in both events following exposure to a small number of specific stressors and some evidence inconsistent with expected pattern that can be explained by factors such as experimental design, technical considerations, differences among laboratories, etc.

Low

Limited or no studies reporting dependent change in both events following exposure to a specific stressor (i.e., endpoints never measured in the same study or not at all); and/or significant inconsistencies in empirical support across taxa and species that don’t align with expected pattern for hypothesised AOP.

Relationship 2203:

(Decrease, Coupling of OXPHOS leads to Decrease, ATP pool)

Empirical support of Relationship 2203 is high.

Rationale: The majority of relevant studies show good incidence, temporal and/or dose concordance in different organisms and cell types after exposure to known uncouplers, with relatively few exceptions (see the Relationship 2203 page and concordance table for detailed evidence).

Relationship 2204:

(Decrease, ATP pool leads to Decrease, Cell proliferation)

Empirical support of Relationship 2204 is moderate.

Rationale: Although only a few studies were found to be relevant, incidence concordance was found for mammalian cells (see the Relationship 2204 page and concordance table for detailed evidence).

Relationship 2205:

(Decrease, Cell proliferation leads to Decrease, Growth)

Empirical support of Relationship 2205 is low.

Rationale: This KER was included in a very limited number of studies, as it addresses effects occurring at the apical level that in vitro studies cannot cover. There is one zebrafish study reporting concordant relationship between reduced cell proliferation and embryo growth with some inconsistencies (see the Relationship 2205 page and concordance table for detailed evidence).

Inconsistencies & uncertainties

There are some inconsistencies regarding temporal and dose concordance:

  • A significant decrease followed by a significant increase of total ATP (KE1) was observed in human RD cells during a 48h exposure to the uncoupler FCCP(Kuruvilla 2003), possibly due to the enhancement of other ATP synthetic pathways (e.g., glycolysis) as a compensatory action to impaired OXPHOS (Jose 2011).
  • In zebrafish embryos exposed to 2,4-DNP, significant growth inhibition (AO) was identified after 21h, whereas non-significant reductions in ATP (KE1) and cell proliferation (KE2) were reported(Bestman 2015).

Known Modulating Factors

Modulating factors (MFs) may alter the shape of the response-response function that describes the quantitative relationship between two KES, thus having an impact on the progression of the pathway or the severity of the AO.The evidence supporting the influence of various modulating factors is assembled within the individual KERs. More help

Quantitative Understanding

Optional field to provide quantitative weight of evidence descriptors.  More help

Quantitative understanding of the KERs

High

Change in KEdownstream can be precisely predicted based on a relevant measure of KEupstream. Uncertainty in the quantitative prediction can be precisely estimated from the variability in the relevant measure of KEupstream. Known modulating factors and feedback/feedforward mechanisms are accounted for in the quantitative description. There is evidence that the quantitative relationship between the KEs generalises across the relevant applicability domain of the KER.

Moderate

Change in KEdownstream can be precisely predicted based on a relevant measure of KEupstream. Uncertainty in the quantitative prediction is influenced by factors other than the variability in the relevant measure of KEupstream. Quantitative description does not account for all known modulating factors and/or known feedback/feedforward mechanisms. The quantitative relationship has only been demonstrated for a subset of the overall applicability domain of the KER (e.g., based on a single species).

Low

Only a qualitative or semi-quantitative prediction of the change in KEdownstream can be determined from a measure of KEupstream. Known modulating factors and/or known feedback/feedforward mechanisms are not accounted for. The quantitative relationship has only been demonstrated for a narrow subset of the overall applicability domain of the KER (e.g., based on a single species).

Relationship 2203:

(Decrease, Coupling of OXPHOS leads to Decrease, ATP pool)

Quantitative understanding of Relationship 2203 is high.

Rationale: The theoretical quantitative relationship between OXPHOS and ATP yield has been well established. There are also published computational/mathematical models in which modulating factors known to affect OXPHOS and ATP synthesis are considered.

Evidence:

  • A biophysical computational model developed for mitochondrial respiration and OXPHOS (Beard 2005).
  • Continuous development of the mitochondrial energy transduction models since 1967 (Schmitz 2011).
  • A comprehensive mathematical model developed for OXPHOS and ATP production under different physiological and pathological conditions (Heiske 2017).
  • A comprehensive analysis of the quantitative relationships between protonmotive force, ATP synthase rotation, ATP synthesis and hydrolysis (Kubo 2020).
  • A regression based response-response relationship for uncoupling of OXPHOS and ATP depletion (Song 2020).

Relationship 2204:

(Decrease, ATP pool leads to Decrease, Cell proliferation)

Quantitative understanding of Relationship 2204 is moderate.

Rationale: The total ATP level has been used as an indicator of cell proliferation. Several studies have reported the quantitative relationships between the two events, as well as a threshold value for KE1 to trigger KE2. However, not all modulating factors have been accounted and no well-established computational/mathematical models are found.

Evidence:

  • Quantitative understanding of ATP level, cell viability and colony growth (Ahmann 1987).
  • Quantitative relationship between ATP level and cell proliferation (Crouch 1993).
  • Thresholds for ATP depletion (85-90% reduction) to determine cell cycle arrest (<85-90%) or cell death (>85-90%) (Nieminen 1994).

Relationship 2205:

(Decrease, Cell proliferation leads to Decrease, Growth)

Quantitative understanding of Relationship 2205 is moderate.

Rationale: Multiple mathematical models describing the quantitative relationships between cell proliferation and tissue growth exist for both animals (Binder 2008) and plants (Mosca 2018). There are also numerous models that are specifically developed for predicting tumor growth based on the proliferation rate (Jarrett 2018). However, there is currently a lack of quantitative model to link cell proliferation and individual growth in the presence of uncouplers.

Evidence:

  • A mathematical model developed for describing the quantitative relationship between cell proliferation and tissue growth (Binder 2008).
  • A mathematical model developed for cell division and plant tissue growth (Mosca 2018).
  • Multiple mathematical models developed for cell proliferation and tumor growth (Jarrett 2018).

Considerations for Potential Applications of the AOP (optional)

Addressess potential applications of an AOP to support regulatory decision-making.This may include, for example, possible utility for test guideline development or refinement, development of integrated testing and assessment approaches, development of (Q)SARs / or chemical profilers to facilitate the grouping of chemicals for subsequent read-across, screening level hazard assessments or even risk assessment. More help

The present AOP has several potential applications. First, the AOP anchors a recognized endpoint of regulatory concern (i.e., growth), at least in OECD member countries, and is directly relevant for a number of OECD test guidelines (e.g., TG206, 208, 201, 210, 211, 212, 215, 221, 228, 241, 407, 408, 416, 422, 443 and 453). These guidelines cover a diversity of taxonomic groups including mammals, birds, fish, amphibians, terrestrial plants, aquatic plants and algae, and various invertebrates. Second, the AOP anchors an important molecular initiating event (e.g., uncoupling of oxidative phosphorylation) and can be used to support several initiatives (e.g., Tox21 and ToxCast) for identification of mitochondrial toxicants. The present AOP helps establish the utility of such assays for identifying chemicals with potential to cause growth impacts. Third, three out of four key events in this AOP can be measured using high-throughput in vitro assays, hence offering a tiered testing strategy (i.e., in silicoin vitroin vivo) or integrated approaches to testing and assessment (IATA) for efficient screening, classification and assessment of potential mitochondrial uncouplers and growth-regulating chemicals. The key events can be considered as useful biomarkers in (eco)toxicological studies. However, it is not recommended to use a single key event (e.g., ATP level alone) as a biomarker for classification and hazard assessment of chemicals, as key events such as decreased ATP pool and cell proliferation can also be the consequences of other biological processes.  A combined measurement of 2-3 key events can normally yield more reliable results.  Finally, the quantitative relationships of the key events in this AOP have been relatively well defined, allowing it to be further developed into quantitative prediction models for higher tier assessments. This is a range of potential applications that were conceived during the development of the present AOP. However, it is neither an exhaustive list of potential applications, nor can explicit examples of these applications in practice be cited at this time. 

We invite users of this AOP to share their applications of this AOP via the Discussion so that practical examples of use can be added.

References

List of the literature that was cited for this AOP. More help

Ahmann FR, Garewal HS, Schifman R, Celniker A, Rodney S. 1987. Intracellular adenosine triphosphate as a measure of human tumor cell viability and drug modulated growth. In Vitro Cellular & Developmental Biology 23:474-480. DOI: 10.1007/BF02628417.

Alasadi, A., Chen, M., Swapna, G.V.T. et al. Effect of mitochondrial uncouplers niclosamide ethanolamine (NEN) and oxyclozanide on hepatic metastasis of colon cancer. Cell Death Dis 9, 215 (2018). DOI: 10.1038/s41419-017-0092-6.

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

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

Baker J, Baker M. 2020. Case Report: A Hyperthermic Death from the Diet Pill DNP. ACEP Now. Available from: https://www.acepnow.com/article/case-report-a-hyperthermic-death-from-the-diet-pill-dnp/

Beard DA. 2005. A biophysical model of the mitochondrial respiratory system and oxidative phosphorylation. PLOS Computational Biology 1:e36. DOI: 10.1371/journal.pcbi.0010036.

Becker RA, Ankley GT, Edwards SW, Kennedy SW, Linkov I, Meek B, Sachana M, Segner H, Van der Burg B, Villeneuve DL, Watanabe H, Barton-Maclaren TS. 2015. Increasing scientific confidence in Adverse Outcome Pathways: application of tailored Bradford-Hill considerations for evaluating weight of evidence. Regul Toxicol Pharm 72:514-537. DOI: 10.1016/j.yrtph.2015.04.004.

Bestman JE, Stackley KD, Rahn JJ, Williamson TJ, Chan SS. 2015. The cellular and molecular progression of mitochondrial dysfunction induced by 2,4-dinitrophenol in developing zebrafish embryos. Differentiation 89:51-69. DOI: 10.1016/j.diff.2015.01.001.

Binder BJ, Landman KA, Simpson MJ, Mariani M, Newgreen DF. 2008. Modeling proliferative tissue growth: a general approach and an avian case study. Phys Rev E Stat Nonlin Soft Matter Phys 78:031912. DOI: 10.1103/PhysRevE.78.031912.

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

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

Crouch SPM, Kozlowski R, Slater KJ, Fletcher J. 1993. The use of ATP bioluminescence as a measure of cell proliferation and cytotoxicity. Journal of Immunological Methods 160:81-88. DOI: 10.1016/0022-1759(93)90011-U.

Demarest TG, McCarthy MM. 2015. Sex differences in mitochondrial (dys)function: Implications for neuroprotection. Journal of Bioenergetics and Biomembranes 47:173-188. DOI: 10.1007/s10863-014-9583-7.

Demine S, Renard P, Arnould T. 2019. Mitochondrial uncoupling: a key controller of biological processes in physiology and diseases. Cells 8. DOI: 10.3390/cells8080795.

Desquiret V, Loiseau D, Jacques C, Douay O, Malthièry Y, Ritz P, Roussel D. 2006. Dinitrophenol-induced mitochondrial uncoupling in vivo triggers respiratory adaptation in HepG2 cells. Biochimica et Biophysica Acta (BBA) - Bioenergetics 1757:21-30. DOI: 10.1016/j.bbabio.2005.11.005.

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

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

Figarola JL, Singhal J, Singhal S, Kusari J, Riggs A. 2018. Bioenergetic modulation with the mitochondria uncouplers SR4 and niclosamide prevents proliferation and growth of treatment-naive and vemurafenib-resistant melanomas. Oncotarget 9:36945-36965. DOI: 10.18632/oncotarget.26421.

Fine EJ, Miller A, Quadros EV, Sequeira JM, Feinman RD. 2009. Acetoacetate reduces growth and ATP concentration in cancer cell lines which over-express uncoupling protein 2. Cancer Cell International 9:14. DOI: 10.1186/1475-2867-9-14.

Grundlingh J, Dargan PI, El-Zanfaly M, Wood DM. 2011. 2,4-dinitrophenol (DNP): a weight loss agent with significant acute toxicity and risk of death. J Med Toxicol 7:205-212. DOI: 10.1007/s13181-011-0162-6.

Guimarães EL, Best J, Dollé L, Najimi M, Sokal E, van Grunsven LA. 2012. Mitochondrial uncouplers inhibit hepatic stellate cell activation. BMC Gastroenterology 12:68. DOI: 10.1186/1471-230X-12-68.

Heiske M, Letellier T, Klipp E. 2017. Comprehensive mathematical model of oxidative phosphorylation valid for physiological and pathological conditions. The FEBS Journal 284:2802-2828. DOI: 10.1111/febs.14151.

Jarrett AM, Lima EABF, Hormuth DA, McKenna MT, Feng X, Ekrut DA, Resende ACM, Brock A, Yankeelov TE. 2018. Mathematical models of tumor cell proliferation: A review of the literature. Expert Review of Anticancer Therapy 18:1271-1286. DOI: 10.1080/14737140.2018.1527689.

Jose C, Bellance N, Rossignol R. 2011. Choosing between glycolysis and oxidative phosphorylation: A tumor's dilemma? Biochimica et Biophysica Acta (BBA) - Bioenergetics 1807:552-561. DOI: 10.1016/j.bbabio.2010.10.012.

Kingston RE, Narlikar GJ. 1999. ATP-dependent remodeling and acetylation as regulators of chromatin fluidity. Genes Dev 13:2339-2352. DOI: 10.1101/gad.13.18.2339.

Kubo S, Niina T, Takada S. 2020. Molecular dynamics simulation of proton-transfer coupled rotations in ATP synthase FO motor. Scientific Reports 10:8225. DOI: 10.1038/s41598-020-65004-1.

Kuruvilla S, Qualls CW, Jr., Tyler RD, Witherspoon SM, Benavides GR, Yoon LW, Dold K, Brown RH, Sangiah S, Morgan KT. 2003. Effects of minimally toxic levels of carbonyl cyanide P-(trifluoromethoxy) phenylhydrazone (FCCP), elucidated through differential gene expression with biochemical and morphological correlations. Toxicol Sci 73:348-361. DOI: 10.1093/toxsci/kfg084.

Liberman EA, Topaly VP, Tsofina LM, Jasaitis AA, Skulachev VP. 1969. Mechanism of coupling of oxidative phosphorylation and the membrane potential of mitochondria. Nature 222:1076-1078. DOI: 10.1038/2221076a0.

Mosca G, Adibi, M., Strauss, S., Runions, A., Sapala, A., Smith, R.S. 2018. Modeling Plant Tissue Growth and Cell Division. In Morris R., ed, Mathematical Modelling in Plant Biology. Springer, Cham.

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

Nieminen AL, Saylor AK, Herman B, Lemasters JJ. 1994. ATP depletion rather than mitochondrial depolarization mediates hepatocyte killing after metabolic inhibition. Am J Physiol 267:C67-74. DOI: 10.1152/ajpcell.1994.267.1.C67.

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.

Rafael J, Wrabetz E. 1976. Brown adipose tissue mitochondria recoupling caused by substrate level phosphorylation and extramitochondrial adenosine phosphates. European Journal of Biochemistry 61:551-561. DOI: 10.1111/j.1432-1033.1976.tb10050.x.

Ramaiah A, Hathaway JA, Atkinson DE. 1964. Adenylate as a metabolic regulator. Effect on yeast phosphofructokinase kinetics. J Biol Chem 239:3619-3622.

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

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

Schmidt-Rohr K. 2020. Oxygen is the high-energy molecule powering complex multicellular life: fundamental corrections to traditional bioenergetics. ACS Omega 5:2221-2233. DOI: 10.1021/acsomega.9b03352.

Schmitz JPJ, Vanlier J, van Riel NAW, Jeneson JAL. 2011. Computational modeling of mitochondrial energy transduction.  39:363-377. DOI: 10.1615/CritRevBiomedEng.v39.i5.20.

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

Shofer SL, Tjeerdema RS. 2002. Sublethal effects of pentachlorophenol in abalone (Haliotis rufescens) veliger larvae as measured by (31)P-NMR. Ecotoxicology and Environmental Safety 51:155-160. DOI: 10.1006/eesa.2002.2141.

Sibille B, Keriel C, Fontaine E, Catelloni F, Rigoulet M, Leverve XM. 1995. Octanoate affects 2,4-dinitrophenol uncoupling in intact isolated rat hepatocytes. European Journal of Biochemistry 231:498-502. DOI: 10.1111/j.1432-1033.1995.tb20724.x.

Song Y, Xie L, Lee Y, Tollefsen KE. 2020. De novo development of a quantitative adverse outcome pathway (qAOP) network for ultraviolet B (UVB) radiation using targeted laboratory tests and automated data mining. Environmental Science & Technology 54:13147-13156. DOI: 10.1021/acs.est.0c03794.

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

Sweet S, Singh G. 1999. Changes in mitochondrial mass, membrane potential, and cellular adenosine triphosphate content during the cell cycle of human leukemic (HL-60) cells. Journal of Cellular Physiology 180:91-96. DOI: https://doi.org/10.1002/(SICI)1097-4652(199907)180:1<91::AID-JCP10>3.0.CO;2-6.

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

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

Wang X, Li L, Guan R, Zhu D, Song N, Shen L. 2017. Emodin inhibits ATP-induced proliferation and migration by suppressing P2Y receptors in human lung adenocarcinoma cells. Cellular Physiology and Biochemistry 44:1337-1351. DOI: 10.1159/000485495.

Weisová P, Anilkumar U, Ryan C, Concannon CG, Prehn JHM, Ward MW. 2012. ‘Mild mitochondrial uncoupling’ induced protection against neuronal excitotoxicity requires AMPK activity. Biochimica et Biophysica Acta (BBA) - Bioenergetics 1817:744-753. DOI: 10.1016/j.bbabio.2012.01.016.

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

Yun MH. 2015. Changes in regenerative capacity through lifespan. International Journal of Molecular Sciences 16:25392-25432.

Zander-Fox DL, Fullston T, McPherson NO, Sandeman L, Kang WX, Good SB, Spillane M, Lane M. 2015. Reduction of mitochondrial function by FCCP during mouse cleavage stage embryo culture reduces birth weight and impairs the netabolic health of offspring1. Biology of Reproduction 92. DOI: 10.1095/biolreprod.114.123489.