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Relationship: 1685

Title

The title of the KER should clearly define the two KEs being considered and the sequential relationship between them (i.e., which is upstream and which is downstream). Consequently all KER titles take the form “upstream KE leads to downstream KE”.  More help

Oxidative Stress leads to Glutamate dyshomeostasis

Upstream event
Upstream event in the Key Event Relationship. On the KER page, clicking on the Event name under Upstream Relationship will bring the user to that individual KE page. More help
Downstream event
Downstream event in the Key Event Relationship. On the KER page, clicking on the Event name under Upstream Relationship will bring the user to that individual KE page. More help

Key Event Relationship Overview

The utility of AOPs for regulatory application is defined, to a large extent, by the confidence and precision with which they facilitate extrapolation of data measured at low levels of biological organisation to predicted outcomes at higher levels of organisation and the extent to which they can link biological effect measurements to their specific causes. Within the AOP framework, the predictive relationships that facilitate extrapolation are represented by the KERs. Consequently, the overall WoE for an AOP is a reflection in part, of the level of confidence in the underlying series of KERs it encompasses. Therefore, describing the KERs in an AOP involves assembling and organising the types of information and evidence that defines the scientific basis for inferring the probable change in, or state of, a downstream KE from the known or measured state of an upstream KE. More help

AOPs Referencing Relationship

This table is automatically generated upon addition of a KER to an AOP. All of the AOPs that are linked to this KER will automatically be listed in this subsection. Clicking on the name of the AOP in the table will bring you to the individual page for that AOP. More help
AOP Name Adjacency Weight of Evidence Quantitative Understanding Point of Contact Author Status OECD Status
Binding of electrophilic chemicals to SH(thiol)-group of proteins and /or to seleno-proteins involved in protection against oxidative stress during brain development leads to impairment of learning and memory adjacent Low Low Marie-Gabrielle Zurich (send email) Under development: Not open for comment. Do not cite EAGMST Under Review

Taxonomic Applicability

Select one or more structured terms that help to define the biological applicability domain of the KER. In general, this will be dictated by the more restrictive of the two KEs being linked together by the KER. Authors can indicate the relevant taxa for this KER in this subsection. The process is similar to what is described for KEs (see pages 30-31 and 37-38 of User Handbook) More help
Term Scientific Term Evidence Link
rat Rattus norvegicus High NCBI
mouse Mus musculus High NCBI

Sex Applicability

Authors can indicate the relevant sex for this KER in this subsection. The process is similar to what is described for KEs (see pages 31-32 of the User Handbook). More help
Sex Evidence
Male High
Female High

Life Stage Applicability

Authors can indicate the relevant life stage for this KER in this subsection. The process is similar to what is described for KEs (see pages 31-32 of User Handbook). More help
Term Evidence
All life stages

Key Event Relationship Description

Provide a brief, descriptive summation of the KER. While the title itself is fairly descriptive, this section can provide details that aren’t inherent in the description of the KEs themselves (see page 39 of the User Handbook). This description section can be viewed as providing the increased specificity in the nature of upstream perturbation (KEupstream) that leads to a particular downstream perturbation (KEdownstream), while allowing the KE descriptions to remain generalised so they can be linked to different AOPs. The description is also intended to provide a concise overview for readers who may want a brief summation, without needing to read through the detailed support for the relationship (covered below). Careful attention should be taken to avoid reference to other KEs that are not part of this KER, other KERs or other AOPs. This will ensure that the KER is modular and can be used by other AOPs. More help

In the central nervous system (CNS), glutamate (Glu) is rapidly taken up at the synaptic cleft to mitigate potential excitotoxicity (Meldrum, 2000). Reuptake is carried out by the electrochemical gradient of Glu across the plasma membrane and is accomplished by Glu transporter proteins, referred to as excitatory amino acid transporters (EAATs). These transporter proteins are predominantly expressed in astrocytes, but they are also be found in other neural cells, such as oligodendrocyte, neuron, and microglia membranes (Danbolt, 2001). Functional Glu transporters are located on cell surface membranes. The activities of these transporters are regulated by a redistribution of these proteins to or from the plasma membrane (Robinson 2002), under the control of several signaling pathways. Five different families of EAATs have been recognized (EAAT1–EAAT5). They vary in Na+ and/or K+ coupling abilities. Their names differ based on the presence of the transporter in human or in other mammals (see Table 1).

Transporter (Human)

Transporter (Mammals)

Occurrence (Cell)

EAAT1

GLAST

Astrocyte, oligodendrocyte, microglia

EAAT2

GLT-1

Astrocyte, oligodendrocyte

EAAT3

EAAC1

Neuron (somatodendritic), astrocyte (low)

EAAT4

EAAT4

Purkinje cell, astrocyte

EAAT5

EAAT5

Müller cell (retina)

Table 1: Glu transporters in human and mammals and their occurrence in CNS cells. From Rajda et al., 2017

These transporters co-localize with, form physical (co-immunoprecipitable) interactions with, and functionally couple to various 'energy-generating' systems, including the Na(+)/K(+)-ATPase, the Na+/Ca2+ exchanger, glycogen metabolizing enzymes, glycolytic enzymes, and mitochondria/mitochondrial proteins. This functional coupling is bi-directional with many of these systems both being regulated by glutamate transport and providing the 'fuel' to support glutamate uptake (Robinson and Jackson, 2016). The Na+ gradient, which depends on Na/K ATPase pump and consequently of ATP production and intracellular levels, provides the energy to move Glu from the outside into the cells, accompanied by two Na+ and an H+ ; at the same time, K+ moves in the opposite direction (Boron and Boulpaep, 2003). Mitochondrial dysfunction leads to a decrease in ATP synthesis, impaired Ca2+ content, and concomitant increase in the levels of ROS (Reactive Oxygen Species) and RNS (Reactive Nitrogen Species) (Beal, 2005). Free radicals, which are electrically unstable, have a central role in several physiological and pathological processes. Both ROS and RNS originate from endogenous and exogenous sources. Mitochondria, endoplasmic reticulum, peroxisomes, phagocytic cells, and others serve as endogenous sources, and environmental factors, such as alcohol, tobacco, pollution, industrial solvents, pesticides, heavy metals, specified medicines, etc. make up the prepondarance of exogenous factors. Significant amounts of reactive oxygen species (ROS) and reactive nitrogen species (RNS,) are formed during oxidative phosphorylation, when the greatest amount of ATP is produced. Cellular antioxidants production serves as a countermeasure against this process (Su et al., 2013; Szalardi et al., 2015). Most cells, including astrocytes, have protective mechanisms against ROS, predominantly in the form of the tripeptide thiol, glutathione (GSH) (Hsie et al., 1996). This process stays in a highly sensitive balance. In the specific case when ROS and RNS synthesis exceeds antioxidant synthesis it results in oxidative stress (Reddy, 2006; Ghafouribar et al., 2008; Su et al., 2013; Szalardi et al., 2015; Valko et al., 2007; Yankovskaya et al., 2003; Senoo-Matsuda et al., 2003;  Schon and Manfredi, 2003).

Evidence Supporting this KER

Assembly and description of the scientific evidence supporting KERs in an AOP is an important step in the AOP development process that sets the stage for overall assessment of the AOP (see pages 49-56 of the User Handbook). To do this, biological plausibility, empirical support, and the current quantitative understanding of the KER are evaluated with regard to the predictive relationships/associations between defined pairs of KEs as a basis for considering WoE (page 55 of User Handbook). In addition, uncertainties and inconsistencies are considered. More help
Biological Plausibility
Define, in free text, the biological rationale for a connection between KEupstream and KEdownstream. What are the structural or functional relationships between the KEs? For example, there is a functional relationship between an enzyme’s activity and the product of a reaction it catalyses. Supporting references should be included. However, it is recognised that there may be cases where the biological relationship between two KEs is very well established, to the extent that it is widely accepted and consistently supported by so much literature that it is unnecessary and impractical to cite the relevant primary literature. Citation of review articles or other secondary sources, like text books, may be reasonable in such cases. The primary intent is to provide scientifically credible support for the structural and/or functional relationship between the pair of KEs if one is known. The description of biological plausibility can also incorporate additional mechanistic details that help inform the relationship between KEs, this is useful when it is not practical/pragmatic to represent these details as separate KEs due to the difficulty or relative infrequency with which it is likely to be measured (see page 40 of the User Handbook for further information).   More help

Due to the tight coupling of Glu transporters with energy production, and to the important role of Glu transporters in Glu homeostasis, perturbations of energy metabolism such as mitochondrial dysfunction and increased production of ROS lead to Glu dyshomeostasis  (Boron and Boulpaep, 2003). In particular, it was shown that ROS inhibit glutamate uptake by astrocytes (Sorg et al., 1997), and that  glutamate release is mediated by ROS-activated volume-sensitive outwardly rectifying anion channels (Liu et al., 2009).

Uncertainties and Inconsistencies
In addition to outlining the evidence supporting a particular linkage, it is also important to identify inconsistencies or uncertainties in the relationship. Additionally, while there are expected patterns of concordance that support a causal linkage between the KEs in the pair, it is also helpful to identify experimental details that may explain apparent deviations from the expected patterns of concordance. Identification of uncertainties and inconsistencies contribute to evaluation of the overall WoE supporting the AOPs that contain a given KER and to the identification of research gaps that warrant investigation (seep pages 41-42 of the User Handbook).Given that AOPs are intended to support regulatory applications, AOP developers should focus on those inconsistencies or gaps that would have a direct bearing or impact on the confidence in the KER and its use as a basis for inference or extrapolation in a regulatory setting. Uncertainties that may be of academic interest but would have little impact on regulatory application don’t need to be described. In general, this section details evidence that may raise questions regarding the overall validity and predictive utility of the KER (including consideration of both biological plausibility and empirical support). It also contributes along with several other elements to the overall evaluation of the WoE for the KER (see Section 4 of the User Handbook).  More help

The relationship between oxidative stress associated to mitochondrial dysfunction and glutamate dyshomeostasis is complex and may be bidirectional. Glutamate dysfunction, due to decreased glutamate uptake, can secondarly induce increased ROS production and consequently oxidative stress.

The astrocytic enzyme glutamine synthetase (GS), transforming glutamate in glutamine, which is taken up by neurons, is also a SH-containing protein, which is inhibited by mercury binding (Kwon and Park, 2003). This participate to glutamate dyshomeostasis  linking this KE directly to the MIE.

Response-response Relationship
This subsection should be used to define sources of data that define the response-response relationships between the KEs. In particular, information regarding the general form of the relationship (e.g., linear, exponential, sigmoidal, threshold, etc.) should be captured if possible. If there are specific mathematical functions or computational models relevant to the KER in question that have been defined, those should also be cited and/or described where possible, along with information concerning the approximate range of certainty with which the state of the KEdownstream can be predicted based on the measured state of the KEupstream (i.e., can it be predicted within a factor of two, or within three orders of magnitude?). For example, a regression equation may reasonably describe the response-response relationship between the two KERs, but that relationship may have only been validated/tested in a single species under steady state exposure conditions. Those types of details would be useful to capture.  More help
Time-scale
This sub-section should be used to provide information regarding the approximate time-scale of the changes in KEdownstream relative to changes in KEupstream (i.e., do effects on KEdownstream lag those on KEupstream by seconds, minutes, hours, or days?). This can be useful information both in terms of modelling the KER, as well as for analyzing the critical or dominant paths through an AOP network (e.g., identification of an AO that could kill an organism in a matter of hours will generally be of higher priority than other potential AOs that take weeks or months to develop). Identification of time-scale can also aid the assessment of temporal concordance. For example, for a KER that operates on a time-scale of days, measurement of both KEs after just hours of exposure in a short-term experiment could lead to incorrect conclusions regarding dose-response or temporal concordance if the time-scale of the upstream to downstream transition was not considered. More help
Known modulating factors
This sub-section presents information regarding modulating factors/variables known to alter the shape of the response-response function that describes the quantitative relationship between the two KEs (for example, an iodine deficient diet causes a significant increase in the slope of the relationship; a particular genotype doubles the sensitivity of KEdownstream to changes in KEupstream). Information on these known modulating factors should be listed in this subsection, along with relevant information regarding the manner in which the modulating factor can be expected to alter the relationship (if known). Note, this section should focus on those modulating factors for which solid evidence supported by relevant data and literature is available. It should NOT list all possible/plausible modulating factors. In this regard, it is useful to bear in mind that many risk assessments conducted through conventional apical guideline testing-based approaches generally consider few if any modulating factors. More help
Known Feedforward/Feedback loops influencing this KER
This subsection should define whether there are known positive or negative feedback mechanisms involved and what is understood about their time-course and homeostatic limits? In some cases where feedback processes are measurable and causally linked to the outcome, they should be represented as KEs. However, in most cases these features are expected to predominantly influence the shape of the response-response, time-course, behaviours between selected KEs. For example, if a feedback loop acts as compensatory mechanism that aims to restore homeostasis following initial perturbation of a KE, the feedback loop will directly shape the response-response relationship between the KERs. Given interest in formally identifying these positive or negative feedback, it is recommended that a graphical annotation (page 44) indicating a positive or negative feedback loop is involved in a particular upstream to downstream KE transition (KER) be added to the graphical representation, and that details be provided in this subsection of the KER description (see pages 44-45 of the User Handbook).  More help

In case of glutamate dyshomeostasis, when extracellular concentrations are very high (5 – 10 mM), a mechanism of toxicity called oxidative glutamate toxicity can be observed. It is mediated by an inhibition of cystein uptake leading to a depletion of GSH (Kritis et al., 2015). The GSH depletion decreases the protection against oxidative stress and exacerbates oxidative stress, which, in turn, exacerbates glutamate dyshomeostasis.

Domain of Applicability

As for the KEs, there is also a free-text section of the KER description that the developer can use to explain his/her rationale for the structured terms selected with regard to taxonomic, life stage, or sex applicability, or provide a more generalizable or nuanced description of the applicability domain than may be feasible using standardized terms. More help

Experimental evidences has been observed mainly in rodent, but due to occurrence of oxidative stress and the presence of glutamate in different taxa, it may be much broader, as suggested by similar observations in C. elegans (Wu et al., 2015).

References

List of the literature that was cited for this KER description using the appropriate format. Ideally, the list of references should conform, to the extent possible, with the OECD Style Guide (OECD, 2015). More help

Allen, J. W., H. El-Oqayli, M. Aschner, T. Syversen and U. Sonnewald (2001). "Methylmercury has a selective effect on mitochondria in cultured astrocytes in the presence of [U-(13)C]glutamate." Brain Res 908(2): 149-154.

Beal M.F. Mitochondria take center stage in aging and neurodegeneration. Ann. Neurol. 2005;58:495–505.

Boron WF, Boulpaep EL. 2003. A cellular and molecular approach. Medical Physiology. Updated Edition. Elsevier, Saunders.

Danbolt NC. Glutamate uptake. Prog Neurobiol. 2001;65:1–105.

Feng, S., Xu, Z., Liu, W., Li, Y., Deng, Y., Xu, B., 2014. Preventive effects of dextromethorphan on methylmercury-induced glutamate dyshomeostasis and oxidative damage in rat cerebral cortex. Biol Trace Elem Res 159, 332-345.

Hediger MA. Glutamate transporters in kidney and brain. Am J Physiol. 1999;277:F487–F492.

 Hsie AW, Recio L, Katz DS, Lee CQ, Wagner M, et al. (1986) Evidence for reactive oxygen species inducing mutations in mammalian cells. Proc Natl Acad Sci U S A 83: 9616–9620

Juarez, B. I., M. L. Martinez, M. Montante, L. Dufour, E. Garcia and M. E. Jimenez-Capdeville (2002). "Methylmercury increases glutamate extracellular levels in frontal cortex of awake rats." Neurotoxicol Teratol 24(6): 767-771.

Kritis AA, Stamoula EG, Paniskaki KA, Vavilis TD (2015) Researching glutamate - induced cytotoxicity in different cell lines: a comparative/collective analysis/study. Front Cell Neurosci 9:91 doi:10.3389/fncel.2015.00091

Kwon, O.-S., Park, Y.-J. In vitro and in vivo dose-dependent inhibition of methylmercury on glutamine synthetase in the brain of different species (2003) Environmental Toxicology and Pharmacology, 14 (1-2), pp. 17-24.

Liu HT, Akita T, Shimizu T, Sabirov RZ, Okada Y. 2009. Bradykinin-induced astrocyte–neuron signalling: glutamate release is mediated by ROS-activated volume-sensitive outwardly rectifying anion channels. J Physiol. 587(Pt 10): 2197–2209.

Meldrum BS. 2000. Glutamate as a neurotransmitter in the brain: review of physiology and pathology. J. Nutr. 130(4S Suppl):1007S–1015S.

Porciuncula, L. O., J. B. Rocha, R. G. Tavares, G. Ghisleni, M. Reis and D. O. Souza (2003). "Methylmercury inhibits glutamate uptake by synaptic vesicles from rat brain." Neuroreport 14(4): 577-580.

Rajda C, Pukoli D, Bende Z, Majalath Z, Vécsei L. 2017. Excitotoxins, Mitochondrial and Redox Disturbances in Multiple Sclerosis. Int J Mol Sci. 2017 Feb; 18(2): 353. doi:  10.3390/ijms18020353.

Reddy P.H. 2006. Mitochondrial oxidative damage in aging and Alzheimer’s disease: Implications for mitochondrially targeted antioxidant therapeutics. J. Biomed. Biotechnol.  doi: 10.1155/JBB/2006/31372.

Robinson MB. 2002. Regulated trafficking of neurotransmitter transporters: common notes but different melodies. J Neurochem. 80(1):1-11.

Robinson, M. B. and J. G. Jackson (2016). "Astroglial glutamate transporters coordinate excitatory signaling and brain energetics." Neurochem Int 98: 56-71.

Roos, D. H., R. L. Puntel, M. M. Santos, D. O. Souza, M. Farina, C. W. Nogueira, M. Aschner, M. E. Burger, N. B. Barbosa and J. B. Rocha (2009). "Guanosine and synthetic organoselenium compounds modulate methylmercury-induced oxidative stress in rat brain cortical slices: involvement of oxidative stress and glutamatergic system." Toxicol In Vitro 23(2): 302-307.

Roos, D. H., R. L. Puntel, M. Farina, M. Aschner, D. Bohrer, J. B. Rocha and N. B. de Vargas Barbosa (2011). "Modulation of methylmercury uptake by methionine: prevention of mitochondrial dysfunction in rat liver slices by a mimicry mechanism." Toxicol Appl Pharmacol 252(1): 28-35.

Senoo-Matsuda N., Hartman P.S., Akatsuka A., Yoshimura S., Ishii N. 2003. A complex II defect affects mitochondrial structure, leading to ced-3- and ced-4-dependent apoptosis and aging. J. Biol. Chem. 278:22031–22036. doi: 10.1074/jbc.M211377200.

Schon E.A., Manfredi G. 2003. Neuronal degeneration and mitochondrial dysfunction. J. Clin Investig. 111:303–312. doi: 10.1172/JCI200317741.

Sorg O, Horn TF, Yu N, Gruol DL, Bloom FE. 1997.Inhibition of astrocyte glutamate uptake by reactive oxygen species: role of antioxidant enzymes.Mol Med. 3(7): 431–440.

Valko M., Leibfritz D., Moncol J., Cronin M.T., Mazur M., Telser J. 2007. Free radicals and antioxidants in normal physiological functions and human disease. Int. J. Biochem. Cell Biol. 39:44–84. doi: 10.1016/j.biocel.2006.07.001.

Wu T, He K, Zhan Q, et al. (2015) MPA-capped CdTe quantum dots exposure causes neurotoxic effects in nematode Caenorhabditis elegans by affecting the transporters and receptors of glutamate, serotonin and dopamine at the genetic level, or by increasing ROS, or both. Nanoscale 7(48):20460-73 doi:10.1039/c5nr05914c

Xu, B., Xu, Z.F., Deng, Y., Liu, W., Yang, H.B., Wei, Y.G., 2012. Protective effects of MK-801 on methylmercury-induced neuronal injury in rat cerebral cortex: involvement of oxidative stress and glutamate metabolism dysfunction. Toxicology 300, 112-120.

Yankovskaya V., Horsefield R., Törnroth S., Luna-Chavez C., Miyoshi H., Léger C., Byrne B., Cecchini G., Iwata S. 2003. Architecture of succinate dehydrogenase and reactive oxygen species generation. Science.299:700–704. doi: 10.1126/science.1079605.