To the extent possible under law, AOP-Wiki has waived all copyright and related or neighboring rights to KER:1744

Relationship: 1744

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

Increase, Premature molting leads to Increase, Mortality

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
S-adenosylmethionine depletion leading to population decline (2) adjacent You Song (send email) Under development: Not open for comment. Do not cite
S-adenosylmethionine depletion leading to population decline (1) adjacent You Song (send email) Under development: Not open for comment. Do not cite
Chitinase inhibition leading to mortality adjacent Moderate Low Simon Schmid (send email) Under development: Not open for comment. Do not cite Under Development
Chitobiase inhibition leading to mortality adjacent Moderate Low Simon Schmid (send email) Under development: Not open for comment. Do not cite Under Development
Chitin synthase 1 inhibition leading to mortality adjacent Moderate Low Simon Schmid (send email) Open for citation & comment EAGMST Approved
Sulfonylureareceptor binding leading to mortality adjacent High High Simon Schmid (send email) Under development: Not open for comment. Do not cite Under Development

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
crustaceans Daphnia magna Moderate NCBI
insects insects Moderate 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
Unspecific Moderate

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
Larvae High
Juvenile Moderate
Adult Moderate

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

During molting, arthropods pause food uptake and in certain cases also respiration (Camp et al. 2014; Song et al. 2017a). If molting is disrupted and the organism is not able to shed the old exoskeleton, the organism may eventually die of starvation, suffocation or the rupture of the exoskeleton.

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

In order to grow and develop, arthropods need to molt periodically (Heming 2018). Since molting is a determining point in arthropod development, the disruption of molting leads to increased mortality (Arakawa et al. 2008; Merzendorfer et al. 2012; Song et al. 2017a; Song et al. 2017b). During ecdysis, arthropods pause food intake and respiration (Camp et al. 2014; Song et al. 2017a). Therefore, if the molt cannot be completed, the organism may die of starvation or suffocation. Additionally, if the cuticle is immature, it may not withstand the stresses associated with ecdysis (Clarke 1957; Lee 1961; Dall et al. 1978; deFur et al. 1985), and the organism may die of desiccation or increased susceptibility to pathogens. Given the well understood biological processes, the biological plausibility of this KER was rated as high.

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 absence of studies (quantitatively) assessing premature molting constitutes a major data gap. A further data gap is the absence of studies which assess both, increase in premature molting and the increase in mortality are lacking.

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

Due to the lack of studies linking the increase in premature molting with the increase in mortality, it is not possible to describe the nature of the response-response relationship.

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

Death occurs after premature molting. However, an exact time frame in which death occurs cannot be defined yet.

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

Taxonomic: Likely, this KER is applicable to the whole phylum of arthropods as they all depend on molting in order to develop.

Life stage: This KER is applicable for organisms molting in order to grow and develop, namely larval stages of insects and all life stages of crustaceans and arachnids.

Sex: This KER is applicable to all sexes.

Chemical: Occurrence of premature molting and an increase in mortality observed after treatment with the pyrimidine nucleosides ( e.g. polyoxin D, polyoxin B and nikkomycin Z) (Gijswijt et al. 1979; Tellam et al. 2000; Tellam and Eisemann 2000; Arakawa et al. 2008; New Zealand Environmental Protection Authority 2015).  However, studies causally linking both endpoints are lacking.

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

Arakawa T, Yukuhiro F, Noda H. 2008. Insecticidal effect of a fungicide containing polyoxin B on the larvae of Bombyx mori (Lepidoptera: Bombycidae), Mamestra brassicae, Mythimna separata, and Spodoptera litura (Lepidoptera: Noctuidae). Appl Entomol Zool. 43(2):173–181. doi:10.1303/aez.2008.173.

Camp AA, Funk DH, Buchwalter DB. 2014. A stressful shortness of breath: Molting disrupts breathing in the mayfly Cloeon dipterum. Freshw Sci. 33(3):695–699. doi:10.1086/677899.

Chen, X.; Tian, H.; Zou, L.; Tang, B.; Hu, J.; Zhang, W. Disruption of Spodoptera Exigua Larval Development by Silencing Chitin Synthase Gene A with RNA Interference. Bull. Entomol. Res. 2008, 98 (6), 613–619. https://doi.org/10.1017/S0007485308005932.

Mohammed, A. M. A.; DIab, M. R.; Abdelsattar, M.; Khalil, S. M. S. Characterization and RNAi-Mediated Knockdown of Chitin Synthase A in the Potato Tuber Moth, Phthorimaea Operculella. Sci. Rep. 2017, 7 (1), 1–12. https://doi.org/10.1038/s41598-017-09858-y.

Clarke KU. 1957. On the Increase in Linear Size During Growth in Locusta Migratoria L. Proc R Entomol Soc London Ser A, Gen Entomol. 32(1–3):35–39. doi:10.1111/j.1365-3032.1957.tb00361.x.

Dall W, Smith DM, Press B. 1978. Water uptake at ecdysis in the western rock lobster. J Exp Mar Bio Ecol. 35(1960). doi:10.1016/0022-0981(78)90074-6.

deFur PL, Mangum CP, McMahon BR. 1985. Cardiovascular and Ventilatory Changes During Ecdysis in the Blue Crab Callinectes Sapidus Rathbun. J Crustac Biol. 5(2):207–215. doi:10.2307/1547867.

Gijswijt MJ, Deul DH, de Jong BJ. 1979. Inhibition of chitin synthesis by benzoyl-phenylurea insecticides, III. Similarity in action in Pieris brassicae (L.) with Polyoxin D. Pestic Biochem Physiol. 12(1):87–94. doi:10.1016/0048-3575(79)90098-1.

Heming BS. 2018. Insect development and evolution. Ithaca: Cornell University Press.

Lee RM. 1961. The variation of blood volume with age in the desert locust (Schistocerca gregaria Forsk.). J Insect Physiol. 6(1):36–51. doi:10.1016/0022-1910(61)90090-7.

Merzendorfer H, Kim HS, Chaudhari SS, Kumari M, Specht CA, Butcher S, Brown SJ, Robert Manak J, Beeman RW, Kramer KJ, et al. 2012. Genomic and proteomic studies on the effects of the insect growth regulator diflubenzuron in the model beetle species Tribolium castaneum. Insect Biochem Mol Biol. 42(4):264–276. doi:10.1016/j.ibmb.2011.12.008. http://dx.doi.org/10.1016/j.ibmb.2011.12.008.

New Zealand Environmental Protection Authority. 2015. Application for approval to import ESTEEM for release. https://www.epa.govt.nz/assets/FileAPI/hsno-ar/APP202334/fbce9a39e6/APP202334-APP202334-Staff-Report-Final-updated.pdf.

Shang, F.; Xiong, Y.; Xia, W. K.; Wei, D. D.; Wei, D.; Wang, J. J. Identification, Characterization and Functional Analysis of a Chitin Synthase Gene in the Brown Citrus Aphid, Toxoptera Citricida (Hemiptera, Aphididae). Insect Mol. Biol. 2016, 25 (4), 422–430. https://doi.org/10.1111/imb.12228.

Song Y, Evenseth LM, Iguchi T, Tollefsen KE. 2017b. Release of chitobiase as an indicator of potential molting disruption in juvenile Daphnia magna exposed to the ecdysone receptor agonist 20-hydroxyecdysone. J Toxicol Environ Heal - Part A Curr Issues. 80(16–18):954–962. doi:10.1080/15287394.2017.1352215. https://doi.org/10.1080/15287394.2017.1352215.

Song Y, Villeneuve DL, Toyota K, Iguchi T, Tollefsen KE. 2017a. Ecdysone Receptor Agonism Leading to Lethal Molting Disruption in Arthropods: Review and Adverse Outcome Pathway Development. Environ Sci Technol. 51(8):4142–4157. doi:10.1021/acs.est.7b00480.

Tellam RL, Eisemann C. 2000. Chitin is only a minor component of the peritrophic matrix from larvae of Lucilia cuprina. Insect Biochem Mol Biol. 30(12):1189–1201. doi:10.1016/S0965-1748(00)00097-7.

Tellam RL, Vuocolo T, Johnson SE, Jarmey J, Pearson RD. 2000. Insect chitin synthase. cDNA sequence, gene organization and expression. Eur J Biochem. 267(19):6025–6043. doi:10.1046/j.1432-1327.2000.01679.x.

Wang, Z.; Yang, H.; Zhou, C.; Yang, W. J.; Jin, D. C.; Long, G. Y. Molecular Cloning, Expression, and Functional Analysis of the Chitin Synthase 1 Gene and Its Two Alternative Splicing Variants in the White-Backed Planthopper, Sogatella Furcifera (Hemiptera: Delphacidae). Sci. Rep. 2019, 9 (1), 1–14. https://doi.org/10.1038/s41598-018-37488-5.

Wang, Y.; Fan, H. W.; Huang, H. J.; Xue, J.; Wu, W. J.; Bao, Y. Y.; Xu, H. J.; Zhu, Z. R.; Cheng, J. A.; Zhang, C. X. Chitin Synthase 1 Gene and Its Two Alternative Splicing Variants from Two Sap-Sucking Insects, Nilaparvata Lugens and Laodelphax Striatellus (Hemiptera: Delphacidae). Insect Biochem. Mol. Biol. 2012, 42 (9), 637–646. https://doi.org/10.1016/j.ibmb.2012.04.009.

Yang, W. J.; Xu, K. K.; Cong, L.; Wang, J. J. Identification, mRNA Expression, and Functional Analysis of Chitin Synthase 1 Gene and Its Two Alternative Splicing Variants in Oriental Fruit Fly, Bactrocera Dorsalis. Int. J. Biol. Sci. 2013, 9 (4), 331–342. https://doi.org/10.7150/ijbs.6022.

Ye, C.; Jiang, Y. Di; An, X.; Yang, L.; Shang, F.; Niu, J.; Wang, J. J. Effects of RNAi-Based Silencing of Chitin Synthase Gene on Moulting and Fecundity in Pea Aphids (Acyrthosiphon Pisum). Sci. Rep. 2019, 9 (1), 1–10. https://doi.org/10.1038/s41598-019-39837-4.

Zhai, Y.; Fan, X.; Yin, Z.; Yue, X.; Men, X.; Zheng, L.; Zhang, W. Identification and Functional Analysis of Chitin Synthase A in Oriental Armyworm, Mythimna Separata. Proteomics 2017, 17 (21), 1–11. https://doi.org/10.1002/pmic.201700165.

Zhang, J. et al. Silencing of two alternative splicing-derived mRNA variants of chitin synthase 1 gene by RNAi is lethal to the oriental migratory locust, Locusta migratoria manilensis (Meyen). Insect Biochem. Mol. Biol. 40, 824–833 (2010).