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Relationship: 1686

Title

A descriptive phrase which clearly defines the two KEs being considered and the sequential relationship between them (i.e., which is upstream, and which is downstream). More help

Glutamate dyshomeostasis leads to Cell injury/death

Upstream event

The causing Key Event (KE) in a Key Event Relationship (KER). More help

Glutamate dyshomeostasis

Downstream event

The responding Key Event (KE) in a Key Event Relationship (KER). More help

Cell injury/death

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

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	High	Moderate	Brendan Ferreri-Hanberry (send email)	Open for citation & comment	WPHA/WNT Endorsed

Taxonomic Applicability

Latin or common names of a species or broader taxonomic grouping (e.g., class, order, family) 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. More help

Term	Scientific Term	Evidence	Link
rat	Rattus norvegicus	High	NCBI
mouse	Mus musculus	High	NCBI

Sex Applicability

An indication of the the relevant sex for this KER. More help

Life Stage Applicability

An indication of the the relevant life stage(s) for this KER. More help

Term	Evidence
All life stages	High

Key Event Relationship Description

Provides a concise overview of the information given below as well as addressing details that aren’t inherent in the description of the KEs themselves. More help

Glutamate is the major excitatory neurotransmitter in the mammalian CNS, where it plays key roles in development, learning, memory and response to injury. However, glutamate at high concentrations at the synaptic cleft acts as a toxin, inducing neuronal injury and death (Meldrum, 2000; Ozawa et al., 1998). Glutamate-mediated neurotoxicity has been dubbed as “excitotoxicity”, referring to the consequence of the overactivation of the N-methyl D-aspartate (NMDA)–type glutamate receptors (cf AOP 48), leading to increased Na⁺ and Ca²⁺ influx into neurons (Choi, 1992; Pivovarova and Andrews, 2010). Increased intracellular Ca²⁺ levels are associated with the generation of oxidative stress and neurotoxicity (Lafon-Cazal et al., 1993). Accordingly, the control of extracellular levels of glutamate dictates its physiological/pathological actions and this equilibrium is maintained primarily by the action of several glutamate transporters (such as GLAST, GLT1, and EAAC1) located on astrocytic cell membranes, which remove the excitatory neurotransmitter from the synaptic cleft, keeping its extracellular concentrations below toxic levels (Anderson and Swanson, 2000; Maragakis and Rothstein, 2001; Szydlowska and Tymianski, 2010).

In addition to synaptic transmission, physiological stimulation of glutamate receptors can mediate trophic effects and promote neuronal plasticity. During development, NMDA receptors initiate a cascade of signal transduction events and gene expression changes primarily involving Ca²⁺-mediated signaling, induced by activation of either Ca²⁺- permeable receptor channels or voltage-sensitive Ca²⁺ channels. The consecutive activation of major protein kinase signaling pathways, such as Ras-MAPK/ERK and PI3-K-Akt, contributes to regulation of gene expression through the activation of key transcription factors, such as CREB, SRF, MEF-2, NF-kappaB. Metabotropic glutamate receptors can also engage these signaling pathways, in part by transactivating receptor tyrosine kinases. Indirect effects of glutamate receptor stimulation are due to the release of neurotrophic factors, such as brain derived neurotrophic factor through glutamate-induced release of trophic factors from glia. The trophic effect of glutamate receptor activation is developmental stage-dependent and may play an important role in determining the selective survival of neurons that made proper connections. During this sensitive developmental period, interference with glutamate receptor function may lead to widespread neuronal loss (Balazs, 2006).

Evidence Collection Strategy

Include a description of the approach for identification and assembly of the evidence base for the KER. For evidence identification, include, for example, a description of the sources and dates of information consulted including expert knowledge, databases searched and associated search terms/strings. Include also a description of study screening criteria and methodology, study quality assessment considerations, the data extraction strategy and links to any repositories/databases of relevant references.Tabular summaries and links to relevant supporting documentation are encouraged, wherever possible. More help

Evidence Supporting this KER

Addresses the scientific evidence supporting KERs in an AOP setting the stage for overall assessment of the AOP. More help

Biological Plausibility

Addresses the biological rationale for a connection between KEupstream and KEdownstream. This field 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. More help

Glutamate dyshomeostasis and in particular excess of glutamate in the synaptic cleft will lead to overactivation of ionotropic glutamate receptors and cause cell injury/death, as described in AOP 48. The excess of glutamate can result from decreased uptake in astrocytes (Aschner et al., 2000; Brookes and Kristt, 1989), or neurons (Moretto et al., 2005; Porciuncula et al., 2003). But also from the increased release (Reynolds and Racz, 1987). This neurotoxic cascade involves calcium overload and ROS production leading to oxidative stress (Ceccatelli et al., 2010; Lafon-Cazal, 1993; Meldrum, 2000; Ozawa, 1998). Chemicals binding to sulfhydryl (SH)-/seleno-proteins cause a direct oxidative stress by perturbing mitochondrial respiratory chain proteins and by decreasing anti-oxidant defense mechanism (see KER : MIE to KEdown oxidative stress) and an indirect oxidative stress via perturbation of glutamate homeostasis/excitotoxicity. Thus, there may be some redundancy in the empirical support between this KER and the KER linking KEup oxidative stress and KEdown cell injury/death.

Glutamate has been shown to regulate BDNF production (Tao et al., 2002). Accordingly, glutamate may also indirectly contribute to cell injury/death by inducing modifications in the brain levels of trophic factors, since it is known that changes in trophic support can lead to cell injury/death, as well as to perturbation in the physiological establishment of neuronal network (Zhao et al., 2017).

Empirical Evidence

Provides specific (citable) evidence that supports the idea of a change in the upstream KE (KEupstream) leading to, or being associated with, a subsequent change in the downstream KE (KEdownstream), assuming the perturbation of KEupstream is sufficient. More help

KE_up Glutamate dyshomeostasis	KE_down Cell injury/death	species; developmental stage of exposure to stressor	Stressor	Dose or conc. Duration	Protective/ aggravating evidence	Reference
Dose-dependent increase in glutamate content in cerebral cortex (+ 60% at 12 µmol kg-¹)	Increased apoptosis rate measured by flow cytometry (+ 1100% at 12 µmol kg-¹)	Rat adult exposure	MeHgCl	4 µmol kg-¹ 12 µmol kg-¹ i.p injection 5 injections per week during 4 weeks	Pretreatment with dextro-methorphan (low-affinity, noncompetitive NMDAR antagonist) partially decreased Glu content and apoptosis induced by MeHgCl	(Feng et al., 2014)
Dose-dependent increase in glutamate content in cerebral cortex (+ 22% at 12 µmol kg-¹)	Increased apoptosis rate measured by flow cytometry (+ 850% at 12 µmol kg-¹)	Rat adult exposure	MeHgCl	4 µmol kg-¹ 12 µmol kg-¹ i.p injection 5 injections per week during 4 weeks	Pretreatment with memantine (low-affinity, noncompetitive NMDAR antagonist) partially decreased Glu content and apoptosis induced by MeHgCl	(Liu et al., 2013)
Increase in glutamate content in cerebral cortex (1.12 fold at 12 µmol kg-¹)	Increased apoptosis rate measured by flow cytometry (+ 630% at 12 µmol kg-¹)	Rat adult exposure	MeHgCl	4 µmol kg-¹ 12 µmol kg-¹ i.p injection 5 injections per week during 4 weeks	Pretreatment with MK801 (noncompetitive NMDAR antagonist) partially decreased apoptosis induced by MeHgCl	(Xu et al., 2012)
Decreased glutamine uptake	Reduction in inner mitochondrial membrane potential	Rat astrocyte cultures	MeHg	1, 5, 10 µM 1 and 5 min		(Yin et al., 2007)
Changes in intracellular glutamate concentration	Cell death measured by MTT reduction and LDH release	Mouse astrocytes, neurons in mono- or co-cultures	MeHg	1-50 µM 24h		(Morken et al., 2005)
Concentration-dependent inhibition of glutamate uptake and stimulation of glutamate release	Cell death measured by MTT reduction	Mouse cerebellar granule cells in culture	HgCl₂ MeHgCl	10^-7-10^-4 M 10 min		(Fonfria et al., 2005)
Dose-dependent decreased cortical glutamate concentration	Dose-dependent abnormal neuronal morphology	Rat Young (3-4 weeks)	Acrylamide	5, 15, 30 mg kg^-1 5 injections per week during 4 weeks gavage		(Tian et al., 2015)

Uncertainties and Inconsistencies

Addresses inconsistencies or uncertainties in the relationship including the identification of experimental details that may explain apparent deviations from the expected patterns of concordance. More help

No uncertainty or inconsistency reported yet.

Known modulating factors

This table captures specific information on the MF, its properties, how it affects the KER and respective references.1.) What is the modulating factor? Name the factor for which solid evidence exists that it influences this KER. Examples: age, sex, genotype, diet 2.) Details of this modulating factor. Specify which features of this MF are relevant for this KER. Examples: a specific age range or a specific biological age (defined by...); a specific gene mutation or variant, a specific nutrient (deficit or surplus); a sex-specific homone; a certain threshold value (e.g. serum levels of a chemical above...) 3.) Description of how this modulating factor affects this KER. Describe the provable modification of the KER (also quantitatively, if known). Examples: increase or decrease of the magnitude of effect (by a factor of...); change of the time-course of the effect (onset delay by...); alteration of the probability of the effect; increase or decrease of the sensitivity of the downstream effect (by a factor of...) 4.) Provision of supporting scientific evidence for an effect of this MF on this KER. Give a list of references. More help

Quantitative Understanding of the Linkage

Captures information that helps to define how much change in the upstream KE, and/or for how long, is needed to elicit a detectable and defined change in the downstream KE. More help

See table of empirical evidence.

Response-response Relationship

Provides sources of data that define the response-response relationships between the KEs. More help

Time-scale

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?). More help

Known Feedforward/Feedback loops influencing this KER

Define whether there are known positive or negative feedback mechanisms involved and what is understood about their time-course and homeostatic limits. More help

Domain of Applicability

A free-text section of the KER description that the developers can use to explain their rationale for the taxonomic, life stage, or sex applicability structured terms. More help

Support for the link between glutamate dyshomeostasis and cell injury /death can be found in rats, and mouse. However, as the neurotransmitter glutamate is already found in insects, it is plausible that this KER is valid throughout taxa (Harris et al., 2014).

References

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

Albrecht, J., Talbot, M., Kimelberg, H.K., Aschner, M. (1993) The role of sulfhydryl groups and calcium in the mercuric chloride-induced inhibition of glutamate uptake in rat primary astrocyte cultures. Brain Res 607, 249-254.

Anderson, C.M., Swanson, R.A. (2000) Astrocyte glutamate transport: review of properties, regulation, and physiological functions. Glia 32, 1-14.

Aschner, M., Yao, C.P., Allen, J.W., Tan, K.H. (2000) Methylmercury alters glutamate transport in astrocytes. Neurochem Int 37, 199-206.

Balazs, R. (2006) Trophic effect of glutamate. Curr Top Med Chem 6, 961-968.

Brookes, N., Kristt, D.A. (1989) Inhibition of amino acid transport and protein synthesis by HgCl2 and methylmercury in astrocytes: selectivity and reversibility. J Neurochem 53, 1228-1237.

Ceccatelli, S., Dare, E., Moors, M. (2010) Methylmercury-induced neurotoxicity and apoptosis. Chem Biol Interact 188, 301-308.

Choi, D.W. (1992) Excitotoxic cell death. J Neurobiol 23, 1261-1276.

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.

Fonfria, E., Vilaro, M.T., Babot, Z., Rodriguez-Farre, E., Sunol, C. (2005) Mercury compounds disrupt neuronal glutamate transport in cultured mouse cerebellar granule cells. J Neurosci Res 79, 545-553.

Harris, K.D., Weiss, M., Zahavi, A. (2014) Why are neurotransmitters neurotoxic? An evolutionary perspective. F1000Res 3, 179.

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

Lafon-Cazal, M., Pietri, S., Culcasi, M., Bockaert, J. (1993) NMDA-dependent superoxide production and neurotoxicity. Nature 364, 535-537.

Liu, W., Xu, Z., Deng, Y., Xu, B., Wei, Y., Yang, T. (2013) Protective effects of memantine against methylmercury-induced glutamate dyshomeostasis and oxidative stress in rat cerebral cortex. Neurotox Res 24, 320-337.

LoPachin, R.M., Schwarcz, A.I., Gaughan, C.L., Mansukhani, S., Das, S. (2004) In vivo and in vitro effects of acrylamide on synaptosomal neurotransmitter uptake and release. Neurotoxicology 25, 349-363.

Maragakis, N.J., Rothstein, J.D. (2001) Glutamate transporters in neurologic disease. Arch Neurol 58, 365-370.

Meldrum, B.S. (2000) Glutamate as a neurotransmitter in the brain: review of physiology and pathology. J Nutr 130, 1007S-1015S.

Moretto, M.B., Funchal, C., Santos, A.Q., Gottfried, C., Boff, B., Zeni, G., Pureur, R.P., Souza, D.O., Wofchuk, S., Rocha, J.B. (2005) Ebselen protects glutamate uptake inhibition caused by methyl mercury but does not by Hg2+. Toxicology 214, 57-66.

Morken, T.S., Sonnewald, U., Aschner, M., Syversen, T. (2005) Effects of methylmercury on primary brain cells in mono- and co-culture. Toxicol Sci 87, 169-175.

Ozawa, S., Kamiya, H., Tsuzuki, K. (1998) Glutamate receptors in the mammalian central nervous system. Prog Neurobiol 54, 581-618.

Pivovarova, N.B., Andrews, S.B. (2010) Calcium-dependent mitochondrial function and dysfunction in neurons. FEBS J 277, 3622-3636.

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

Reynolds, J.N., Racz, W.J. (1987) Effects of methylmercury on the spontaneous and potassium-evoked release of endogenous amino acids from mouse cerebellar slices. Can J Physiol Pharmacol 65, 791-798.

Szydlowska, K., Tymianski, M. (2010) Calcium, ischemia and excitotoxicity. Cell Calcium 47, 122-129.

Tao, X., West, A.E., Chen, W.G., Corfas, G., Greenberg, M.E. (2002) A calcium-responsive transcription factor, CaRF, that regulates neuronal activity-dependent expression of BDNF. Neuron 33, 383-395.

Tian, S.M., Ma, Y.X., Shi, J., Lou, T.Y., Liu, S.S., Li, G.Y. (2015) Acrylamide neurotoxicity on the cerebrum of weaning rats. Neural Regen Res 10, 938-943.

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.

Yin, Z., Milatovic, D., Aschner, J.L., Syversen, T., Rocha, J.B., Souza, D.O., Sidoryk, M., Albrecht, J., Aschner, M. (2007) Methylmercury induces oxidative injury, alterations in permeability and glutamine transport in cultured astrocytes. Brain Res 1131, 1-10.

Zhao, H., Alam, A., San, C.Y., Eguchi, S., Chen, Q., Lian, Q., Ma, D. (2017) Molecular mechanisms of brain-derived neurotrophic factor in neuro-protection: Recent developments. Brain Res 1665, 1-21.