To the extent possible under law, AOP-Wiki has waived all copyright and related or neighboring rights to KER:715

Relationship: 715

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

Disruption, Microtubule dynamics leads to Disorganization, Meiotic Spindle

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
Chemical binding to tubulin in oocytes leading to aneuploid offspring adjacent Moderate Francesco Marchetti (send email) Open for citation & comment 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
Homo sapiens Homo sapiens Moderate NCBI
mouse Mus musculus 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
Mixed 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
Adult High

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

Spindle organization and function requires normal microtubule dynamics. When microtubule polymerization is affected (i.e., depolymerization), spindle organization and function is impaired.

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

Moderate.

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

The weight of evidence for this KER is moderate. Microtubule polymerization is critical for the appropriate functioning of the spindle. Mitotic and meiotic spindles differ in how they are assembled. In mitotic cells, spindle organization is controlled by centrioles [Walczak and Heald, 2008; Wadsworth et al., 2011; Wittman et al., 2011]. However, centrioles are absent in mammalian oocytes [Manandhar et al., 2005] and meiotic spindle is organized by multiple microtubule organizing centers (MTOCs). Gradually, MTOCs coalesce and surround the chromosomes and subsequently elongate in a typical barrel-shape bipolar spindle [Schuh and Ellenberg, 2007; Clift and Schuh, 2015], similar to the mitotic spindle. Assembly, elongation and function of the spindle requires proper microtubule dynamics. If microtubules become depolymerized, it affects the structural integrity of the spindle resulting in abnormal spindles that are characterized by reduction in microtubule density, loss of barrel shape, mono- or multi-polar spindle, and reduced distance between the poles [Ibanez et al., 2003; Shen et al., 2005; Eichenlaub-Ritter et al., 2007; Xu et al., 2012]. The normal biology underlying the critical role of proper microtubule polymerization for the appropriate structure and function of spindle is well established, and it is widely understood that chemicals that alter microtubule dynamics cause spindle disorganization [Manandhar et al., 2005; Schuh and Ellenberg, 2007].

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

There are not a lot of studies that have explored these two events within the same experiment. Thus, the empirical evidence is not based on a large number of papers. However, the papers that are available are of sound experimental design that address both time and incidence relationships, and span three species.

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

There are detailed dose-response relationships for microtubule depolymerisation by tubulin binders obtained using acellular tubulin polymerization assays [Zavala et al., 1980; Hamel and Lin, 1981; Verdier-Pinard et al., 1998; Miller and Wilson, 2010]. The rate of depolymerisation has been also measured in whole mitotic cells of sea urchin embryos after microinjection of different doses of colchicine or colcemid, in the range 0.01-5 mM [Salmon et al., 1984]. Comparable data are not available for mammalian oocytes. In addition, no quantitative dose-response relationship has been obtained for spindle disorganization in oocytes treated with tubulin binding chemicals. This lack of data does not allow modelling a response-response relationship between disruption of microtubule dynamics (KEupstream) and spindle disorganization (KEdownstream).

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

In sea urchin embryo cells microinjected with colchicine concentrations equal to or higher than 0.1 mM, complete depolymerization of non-kinetochore spindle microtubules (KEupstream) is reached in about 20 seconds, corresponding to a depolymerization rate of about 180-992 dimers per second [Salmon et al., 1984]. The order of magnitude of these values corresponds to the fastest rates of tubulin dissociation reported in various acellular systems [Fan’ell et al., 1983]. However, possible modifying factors of the above rates are suggested in the cells (e.g., calcium concentration), conditions that are not reproducible in acellular systems.

In vitro exposure of mouse oocytes to 67 µM nocodazole causes a gradual disorganization of the spindle (KEdownstream), which is completed within 15 min [Xu et al., 2012]. In spite of the limited amount of data on the kinetics of spindle disorganization (KEdownstream) and the further limitation that dysruption of microtubule dynamics (KEupstream) and spindle disorganization (KEdownstream) were not analyzed in the same biological systems, it can be noted that the time-scale in the KEdownstream is coherent with the time-scale of the KEupstream.

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

Due to the heterogeneity of the experimental approaches used to measure dysruption of microtubule dynamics (KEupstream) and spindle disorganization (KEdownstream) it is not feasible to identify modulating factors acting in this KER.

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

To our knowledge, there are no feedback loops influencing this KER.

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

Data were produced in sea urchins, mice and human eggs and embryos. This KER should be applicable to any eukaryotic organism.

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

Clift D, Schuh M. 2015. A three-step MTOC fragmentation mechanism facilitate bipolar spindle assembly in mouse oocytes. Nat Commun 6:7217.

Eichenlaub-Ritter U, Winterscheidt U, Vogt E, Shen Y, Tinneberg HR, Sorensen R. 2007. 2-methoxyestradiol induces spindle aberrations, chromosome congression failure, and nondisjunction in mouse oocytes. Biol Reprod 76:784–793.

Fan'ell KW, Himes RH, Jordon MA,Wilson L. 1983. On the nonlinear relationship between the initial rates of dilution induced microtubule disassembly and the initial free subunit concentration. J Biol Chem 258:14148-14156.

Hamel E, Lin CM. 1981. Stabilization of the colchicine-binding activity of tubulin by organic acids. Biochim Biophys Acta 675:226-231.

Ibanez E, Albertini DF, Overstrom EW. 2003. Demecolcine-induced oocyte enucleation for somatic cell cloning: Coordination between cell-cycle egress, kinetics of cortical cytoskeletal interactions, and second polar body extrusion. Biol Reprod 68:1249–1258.

Liu S, Li Y, Feng HL, Yan JH, Li M, Ma SY, Chen ZJ. 2010. Dynamic modulation of cytoskeleton during in vitro maturation in human oocytes. Am J Obstet Gynecol 151:e1–7.

Manandhar G, Schatten H, Sutovsky P. 2005. Centrosome reduction during gametogenesis and its significance. Biol Reprod 72:2-13.

Miller HP, Wilson L. 2010. Chapter 1 - Preparation of Microtubule Protein and Purified Tubulin from Bovine Brain by Cycles of Assembly and Disassembly and Phosphocellulose Chromatography. In: Leslie W, John JC, editors. Methods Cell Biol: Academic Press. p 2-15.

Salmon ED, McKeel M, Hays T. 1984. Rapid rate of tubulin dissociation from microtubules in the mitotic spindle in vivo measured by blocking polymerization with colchicine. J Cell Biol 99:1066-1075.

Schuh M, Ellenberg J. 2007. Self-organization of MTOCs replaces centrosome function during acentrosomal spindle assembly in live mouse oocytes. Cell 130:484-498.

Shen Y, Betzendahl I, Sun F, Tinneberg HR, Eichenlaub-Ritter U. 2005. Non-invasive method to assess genotoxicity of nocodazole interfering with spindle formation in mammalian oocytes. Reprod Toxicol 19:459-471.

Verdier-Pinard P, Lai JY, Yoo HD, Yu J, Marquez B, Nagle DG, Nambu M, White JD, Falck JR, Gerwick WH, Day PW, Hamel E. 1998. Structure-activity analysis of the interaction of curacin A, the potent colchicine site antimitotic agent, with tubulin and effects of analogs on the growth of MCF-7 breast cancer cells. Mol Pharmacol 53:62-76.

Wadsworth P, Lee WL, Murata T, Baskin TI. 2011. Variations on a theme: spindle assembly in diverse cells. Protoplasma 248:439-446.

Walczak CE and R Heald. 2008. Mechanisms of mitotic spindle assembly and function. Int. Rev Cytol 265:111-158.

Wittman T, Hyman A, Desai A. 2011. The spindle: a dynamic assembly of microtubules and motors. Nat Cell Biol 3:e28-234.

Xu XL, Ma W, Zhu YB, Wang C, Wang BY, An N, An L, Liu Y, Wu ZH, Tian JH. 2012. The microtubule-associated protein ASPM regulates spindle assembly and meiotic progression in mouse oocytes. PLoS One 7:e49303.

Zavala F, Guenard D, Robin JP, Brown E. 1980. Structure--antitubulin activity relationship in steganacin congeners and analogues. Inhibition of tubulin polymerization in vitro by (+/-)-isodeoxypodophyllotoxin. J Med Chem 23:546-549.