To the extent possible under law, AOP-Wiki has waived all copyright and related or neighboring rights to KER:360

Relationship: 360


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

Binding of agonist, NMDARs leads to Overactivation, NMDARs

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

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

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

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

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

NMDARs can be activated indirectly through initial activation of KA/AMPARs as it happens in the case of DomA exposure. DomA is an agonist of presynaptic and postsynaptic KARs and sustained activation of these receptors by DomA results in massive ion flux and excessive release of glutamate from excitatory terminals causing depolarization of the postsynaptic neuron (as descibed in MIE). Upon this depolarization the Mg2+ block is removed from the pore of NMDARs, resulting in their activation allowing sodium, potassium, and, importantly, calcium ions to enter into a cell. The sustained exposure to DomA causes pathological overactivation of NMDARs.

In the case of exposure to glufosinate NMDARs activation is triggered by direct, sustained binding of glufosinate to the NMDARs.

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

NMDARs are unique among ligand-gated ion channels in that their activation requires binding of two co-agonists, glycine and endogenous neurotransmitter, L-glutamate. Physiologically, however, glycine and glutamate have distinct functions. While L-glutamate is released from specific presynaptic terminals, low concentrations of ambient glycine present at the synapse are thought to be sufficient to allow receptor activation.

There is a clear understanding that binding of glutamate or its analogue will activate NMDA receptor (accepted dogma). The prolonged activation of NMDARs will lead to a pathological over-activation of a receptor leading to excitotoxicity (minor role of KA/AMPARs), allowing high levels of calcium ions to enter the cell. However, KA/AMPARs play an important role for indirect NMDAR activation since (almost always) an initial activation of these receptors triggers depolarization of postsynaptic neurons that relieves the block of the channel pore by Mg2+, resulting in NMDAR activation.

NMDA receptors are formed by a ligand binding domain (LBD) and an ion channel that are considered the core structural and functional elements of the receptors. There is a clear understanding of how agonist binding leads to channel opening that relies on structural (e.g. crystallography or NMR) and functional (e.g. UV and IR spectrometric measurements) experimental studies of the water-soluble LBD combined with functional studies of the intact receptor. After the initial agonist binding, a conformational change—so-called clam shell closure—that prevents agonist dissociation occurs followed by a conformational change in the ion channel that is tightly coupled to that in the LBD (reviewed in Traynelis et al., 2010).

Consequently it can be stated that there is a clear structural and functional mechanistic understanding in this KER between MIE (Binding of agonist to glutamate ionotropic receptors) and KE1, NMDAR overactivation that, as explained above, can be triggered by direct binding to NMDAR or indirectly, through initial activation of KA/AMPARs as it happens in the case of exposure to glufosinate and DomA respectively, two stressors described in this AOP.

Indeed, domoic acid has a very strong affinity for the ionotropic glutamate receptors, the activation of which results in excitotoxicity, initiated by an integrative action of ionotropic receptors at both sides of the synapse blocking the channel from rapid desensitization. It has a synergistic effect with endogenous glutamate and it acts mainly as an agonist for presynaptic and postsynaptic kainate receptors. Activation of ionotropic receptors leads to the influx of Na+, K+ and Ca2+, particulary after activation of NMDARs. In combination with the inhibitory GABA neurotransmitter, glutamate contributes to the control of overall neuronal excitability.

Gufosinate (GLF) triggers alterations in glutamatergic signaling through direct binding and activation of NMDARs (Lantz et al., 2014: Matsumura et al., 2001). GLF agonist action at the NMDAR is expected to occur through interaction with the glutamate binding site and requires binding of the glycine co-agonist as well as release of the magnesium block from the channel pore. Additionally, the possible inhibition by GLF of the high affinity glutamate re-uptake transporter, especially GLT-I was studied to determine whether GLF could increase the levels of endogenous glutamate at the synaptic cleft, resulting in over activation of NMDARs. Such mechanism was excluded by Lantz (Lantz et al., 2014) but suggested by other studies (Watanabe and Sano, 1998).

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 increase in MFR induced by GLF in neuronal networks was significantly blocked by MK-801 but not entirely suggesting that GLF can increase activity in the MEA system through non-synaptic NMDARs, since these are not blocked by MK-801.

It is not entirely clear whether GLF can work through an inhibition of the glutamate reuptake transporter, GLT-I, increasing the concentration of endogenous glutamate at the synaptic cleft and subsequently resulting in over activation of NMDARs (Lantz et al., 2014: Watanabe and Sano, 1998). Further studies are necessary to determine whether this alternative mechanism of GLF-induced NMDAR overactivation takes place.

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
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

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

Various studies suggest the existence of functional NMDA-like receptors in invertebrates (Xia et al., 2005). Fly and rodent NMDARs exhibit several important differences (Murphy and Glanzman, 1997). The expression and function of NMDA receptors in rodent and primates is well characterized in the existing literature.


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

Babot Z, Cristofol R, Sun˜ol C.,Excitotoxic death induced by released glutamate in depolarized primary cultures of mouse cerebellar granule cells is dependent on GABAA receptors and niflumic acidsensitive chloride channels. Eur J Neurosci., 2005, 21: 103–112.

Blanke ML, VanDongen AMJ., Activation Mechanisms of the NMDA Receptor. In: Van Dongen AM, editor. Biology of the NMDA Receptor. Boca Raton (FL): CRC Press; 2009. Chapter 13. Frontiers in Neuroscience.

Berman FW, Murray TF., Domoic acid neurotoxicity in cultured cerebellar granule neurons is mediated predominantly by NMDA receptors that are activated as a consequence of excitatory amino acid release. J Neurochem., 1997, 69: 693–703.

Blanke ML., and Antonius M.J. VanDongen, Activation Mechanisms of the NMDA Receptor in Biology of the NMDA Receptor,2009, Chapter 13, Van Dongen AM, editor. Boca Raton (FL): CRC Press.

Enoki R, et al., NMDAR-mediated depolarizing after-potentials in the basal dendrites of CA1 pyramidal neurons. Neurosci Res., 2004, 48: 325-337.

Gibb AJ, Colquhoun D. Glutamate activation of a single NMDAR-channel produces a cluster of channel openings. Proc. R. Soc. Lond. (Biol.) 1991, 243: 39-47.

Giordano G, White CC, McConnachie LA, Fernandez C, Kavanagh TJ, Costa LG., Neurotoxicity of domoic Acid in cerebellar granule neurons in a genetic model of glutathione deficiency. Mol Pharmacol., 2006, 70: 2116–2126.

Jakobsen B, Tasker A, Zimmer J., Domoic acid neurotoxicity in hippocampal slice cultures. Amino Acids, 2002, 23: 37–44.

Lantz Stephen R , Cina M. Mack , Kathleen Wallace, Ellen F. Key , Timothy J. Shafer , John E. Casida, Glufosinate binds to N-methyl-D-aspartate receptors and increases neuronal network activity in vitro. NeuroToxicology, 2014, 45: 38–47.

Matsumura N1, Takeuchi C, Hishikawa K, Fujii T, Nakaki T., Glufosinate ammonium induces convulsion through N-methyl-D-aspartate receptors in mice. Neurosci Lett., 2001, 304(1-2): 123-5.

Murphy GG, Glanzman DL., Mediation of classical conditioning in Aplysia californica by long-term potentiation of sensorimotor synapses. Science, 1997, 278: 467-78.

Popescu G, et al. Reaction mechanism determines NMDAR response to repetitive stimulation. Nature. 2004, 430: 790-799.

Qiu S, Curras-Collazo MC., Histopathological and molecular changes produced by hippocampal microinjection of domoic acid. Neurotoxicol Teratol., 2006a, 28: 354–362.

Qiu S, Pak CW, Curras-Collazo MC., Sequential involvement of distinct glutamate receptors in domoic acid-induced neurotoxicity in rat mixed cortical cultures: Effect of multiple dose/duration paradigms, chronological age, and repeated exposure. Toxicol Sci., 2006b, 89: 243–256.

Traynelis SF, Wollmuth LP, McBain CJ, Menniti FS, Vance KM, Ogden KK, Hansen KB, Yuan H, Myers SJ, Dingledine R., Glutamate receptor ion channels: structure, regulation, and function. Pharmacol Rev., 2010, 62(3):405-96.

Vale-Gonzalez C, Alfonso A, Sun˜ol C, Vieytes MR, Botana LM., Role of the plasma membrane calcium adenosine triphosphatase on domoate-induced intracellular acidification in primary cultures of cerebellar granule cells. J Neurosci Res., 2006, 84: 326–337.

Watanabe T1, Sano T., Neurological effects of glufosinate poisoning with a brief review. Hum Exp Toxicol. 1998, 17: 35-9.

Xia S, et al., NMDARs mediate olfactory learning and memory in Drosophila. Curr Biol., 2005, 15:603-618.