Ibrahim2008_MCC_assembly_model_KDM
Ontology highlight
ABSTRACT:
SUBMITTER: 
Bashar Ibrahim
PROVIDER: BIOMD0000000193 | BioModels | 2008-11-27
REPOSITORIES: BioModels
Publications
In silico study of kinetochore control, amplification, and inhibition effects in MCC assembly.
Ibrahim Bashar B Schmitt Eberhard E Dittrich Peter P Diekmann Stephan S
Bio Systems 20080712 1
Eukaryotic cells rely on a surveillance mechanism, the "Spindle Assembly Checkpoint"SACM in order to ensure accurate chromosome segregation by preventing anaphase initiation until all chromosomes are correctly attached to the mitotic spindle. In different organisms, a mitotic checkpoint complex (MCC) composed of Mad2, Bub3, BubR1/Mad3, and Cdc20 inhibits the anaphase promoting complex (APC/C) to initiate promotion into anaphase. The mechanism of MCC formation and its regulation by the kinetochor ...[more]
Similar Datasets
Project description:Biophysical Chemistry 134 (2008) 93-100
Mad2 binding is not sufficient for complete Cdc20 sequestering in mitotic transition control (an in silico
study)
Bashar Ibrahim, Peter Dittrich, Stephan Diekmann, Eberhard Schmitt
This model originates from BioModels Database: A Database of Annotated Published Models. It is copyright (c) 2005-2009 The BioModels Team.
For more information see the terms of use
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To cite BioModels Database, please use Le Novère N., Bornstein B., Broicher A., Courtot M., Donizelli M., Dharuri H., Li L., Sauro H., Schilstra M., Shapiro B., Snoep J.L., Hucka M. (2006) BioModels Database: A Free, Centralized Database of Curated, Published, Quantitative Kinetic Models of Biochemical and Cellular Systems Nucleic Acids Res., 34: D689-D691.
2008-09-11 | BIOMD0000000194 | BioModels
Project description:Ibrahim2008 - Mitotic Spindle Assembly Checkpoint - Convey variant
The Mitotic Spindle Assembly Checkpoint ((M)SAC) is an evolutionary conserved mechanism. This model incorporates the perspectives of three central control pathways, namely Mad1/Mad2 induced Cdc20 sequestering based on the Template Model, MCC formation, and APC inhibition. MCC:APC dissociation is described by two alternatives models, namely the "Dissociation" and the "Convey" model variants. Both these model are available in BioModels Database. This model corresponds to the "Convey" variant.
This model is described in the article:
In-silico modeling of the mitotic spindle assembly checkpoint.
Ibrahim B, Diekmann S, Schmitt E, Dittrich P
PLoS One. 2008 Feb 6;3(2):e1555.
Abstract:
BACKGROUND: The Mitotic Spindle Assembly Checkpoint ((M)SAC) is an evolutionary conserved mechanism that ensures the correct segregation of chromosomes by restraining cell cycle progression from entering anaphase until all chromosomes have made proper bipolar attachments to the mitotic spindle. Its malfunction can lead to cancer.
PRINCIPLE FINDINGS: We have constructed and validated for the human (M)SAC mechanism an in silico dynamical model, integrating 11 proteins and complexes. The model incorporates the perspectives of three central control pathways, namely Mad1/Mad2 induced Cdc20 sequestering based on the Template Model, MCC formation, and APC inhibition. Originating from the biochemical reactions for the underlying molecular processes, non-linear ordinary differential equations for the concentrations of 11 proteins and complexes of the (M)SAC are derived. Most of the kinetic constants are taken from literature, the remaining four unknown parameters are derived by an evolutionary optimization procedure for an objective function describing the dynamics of the APC:Cdc20 complex. MCC:APC dissociation is described by two alternatives, namely the "Dissociation" and the "Convey" model variants. The attachment of the kinetochore to microtubuli is simulated by a switching parameter silencing those reactions which are stopped by the attachment. For both, the Dissociation and the Convey variants, we compare two different scenarios concerning the microtubule attachment dependent control of the dissociation reaction. Our model is validated by simulation of ten perturbation experiments.
CONCLUSION: Only in the controlled case, our models show (M)SAC behaviour at meta- to anaphase transition in agreement with experimental observations. Our simulations revealed that for (M)SAC activation, Cdc20 is not fully sequestered; instead APC is inhibited by MCC binding.
This model describes the controlled dissociation variant of the mitotic spindle assembly checkpoint. If the tool you use has problems with events, you can uncomment the assignment rules for u and u_prime and comment out the list of events.
In accordance with the authors due to typos in the original publication some initial conditions and parameters were slightly changed in the model:
article
model
[O-Mad2]
1.5e-7 M
1.3e-7 M
[BubR1:Bub3]
1.30e-7 M
1.27e-7 M
k -4
0.01 M -1
s -1
0.02 M -1
s -1
k -5
0.1 M -1
s -1
0.2 M -1
s -1
This model is hosted on BioModels Database
and identified by: MODEL6655578762
.
To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models
.
To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication
for more information.
2008-09-01 | BIOMD0000000187 | BioModels
Project description:Ibrahim2008 - Mitotic Spindle Assembly Checkpoint - Dissociation variant
The Mitotic Spindle Assembly Checkpoint ((M)SAC) is an evolutionary conserved mechanism. This model incorporates the perspectives of three central control pathways, namely Mad1/Mad2 induced Cdc20 sequestering based on the Template Model, MCC formation, and APC inhibition. MCC:APC dissociation is described by two alternatives models, namely the "Dissociation" and the "Convey" model variants. Both these model are available in BioModels Database. This model corresponds to the "Dissociation" variant.
This model is described in the article:
In-silico modeling of the mitotic spindle assembly checkpoint.
Ibrahim B, Diekmann S, Schmitt E, Dittrich P
PLoS One. 2008 Feb 6;3(2):e1555.
Abstract:
BACKGROUND: The Mitotic Spindle Assembly Checkpoint ((M)SAC) is an evolutionary conserved mechanism that ensures the correct segregation of chromosomes by restraining cell cycle progression from entering anaphase until all chromosomes have made proper bipolar attachments to the mitotic spindle. Its malfunction can lead to cancer.
PRINCIPLE FINDINGS: We have constructed and validated for the human (M)SAC mechanism an in silico dynamical model, integrating 11 proteins and complexes. The model incorporates the perspectives of three central control pathways, namely Mad1/Mad2 induced Cdc20 sequestering based on the Template Model, MCC formation, and APC inhibition. Originating from the biochemical reactions for the underlying molecular processes, non-linear ordinary differential equations for the concentrations of 11 proteins and complexes of the (M)SAC are derived. Most of the kinetic constants are taken from literature, the remaining four unknown parameters are derived by an evolutionary optimization procedure for an objective function describing the dynamics of the APC:Cdc20 complex. MCC:APC dissociation is described by two alternatives, namely the "Dissociation" and the "Convey" model variants. The attachment of the kinetochore to microtubuli is simulated by a switching parameter silencing those reactions which are stopped by the attachment. For both, the Dissociation and the Convey variants, we compare two different scenarios concerning the microtubule attachment dependent control of the dissociation reaction. Our model is validated by simulation of ten perturbation experiments.
CONCLUSION: Only in the controlled case, our models show (M)SAC behaviour at meta- to anaphase transition in agreement with experimental observations. Our simulations revealed that for (M)SAC activation, Cdc20 is not fully sequestered; instead APC is inhibited by MCC binding.
This model describes the controlled dissociation variant of the mitotic spindle assembly checkpoint. If the tool you use has problems with events, you can uncomment the assignment rules for u and u_prime and comment out the list of events.
In accordance with the authors due to typos in the original publication some initial conditions and parameters were slightly changed in the model:
article
model
[O-Mad2]
1.5e-7 M
1.3e-7 M
[BubR1:Bub3]
1.30e-7 M
1.27e-7 M
k -4
0.01 M -1
s -1
0.02 M -1
s -1
k -5
0.1 M -1
s -1
0.2 M -1
s -1
This model is hosted on BioModels Database
and identified by: MODEL6655615431
.
To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models
.
To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication
for more information.
2008-09-02 | BIOMD0000000186 | BioModels
Project description:The Applied Biosystems Tissue Gene Expression Database, known as the Human Body Map, is a collection of gene expression profiles from 31 normal tissues and a Universal Human Reference RNA (Stratagene). The Human BodyMap was created using the Applied Biosystems Expression Array System. There were three replicates per tissue for a total of 96 microarrays. Keywords: Human tissue whole genome survey
2007-06-04 | GSE7905 | GEO
Project description:In a previous study we applied a quantitative proximity-labeling technique called Biotin Identification (BioID, Roux et al., 2012) to analyze the microenvironment of the Gβ-like scaffold protein Asc1 (Opitz et al., 2017). The WD40-repeat protein Asc1 binds to the head region of the small 40S ribosomal (hr40S) subunit. In this study, we analyzed the hr40S from the perspective of Rps2, a ribosomal neighbor of Asc1. We intended to confirm proteins of the Asc1 proxiOME at the hr40S and to observe changes when Asc1 was absent. References: Roux K.J., Kim D.I., Raida M., Burke B. 2012. A promiscuous biotin ligase fusion protein identifies proximal and interacting proteins in mammalian cells. J Cell Biol 196:801-810 Opitz N., Schmitt K., Hofer-Pretz V., Neumann B., Krebber H., Braus G.H., Valerius O. 2017. Capturing the Asc1p/RACK1 microenvironment at the head region of the 40S ribosome with quantitative BioID in yeast. Mol Cell Proteomics 16:2199-2218
2019-11-07 | PXD015611 | Pride
Project description:The Applied Biosystems Tissue Gene Expression Database, known as the Human Body Map, is a collection of gene expression profiles from 31 normal tissues and a Universal Human Reference RNA (Stratagene). The Human BodyMap was created using the Applied Biosystems Expression Array System. There were three replicates per tissue for a total of 96 microarrays. Keywords: Human tissue whole genome survey 31 human tissues from Clontech and 1 from Stratagene (UHR) were used to create the Applied Biosystems Human BodyMap (a.k.a.Tissue Gene Expression Database ). Digoxigenin-UTP-labeled cRNA was generated and linearly amplified from 1 µg of total RNA with three replicates per tissue, using the Applied Biosystems Chemiluminescent RT-IVT Labeling Kit v 2.0 and kit protocol. Microarray hybridization, chemiluminescence detection, image acquisition, and analysis were performed on the on the Applied Biosystems 1700 Chemiluminescent Microarray Analyzer using the Applied Biosystems Chemiluminescence Detection Kit and kit protocol. This dataset is part of the TransQST collection.
2007-06-04 | E-GEOD-7905 | biostudies-arrayexpress
Project description:<p>The biomarker development study consisted of two parts: discovery and validation. The first part was the discovery and verification phase of biomarkers using two different platforms: transcriptomic and miRNA. The salivary transcriptomes of 63 GC samples and 31 non-GC controls were profiled using Affymetrix HG U133+2.0 microarrays (Affymetrix, Santa Clara, CA). The identified exRNA candidates were verified by quantitative real-time PCR (RT-qPCR) using all 94 of the original samples. In the discovery phase for the miRNA biomarkers, 10 early-stage GC samples and 10 non-GC controls were selected. The salivary miRNAs of these samples (n=20) were profiled using the TaqMan MicroRNA Array (Applied Biosystems, Foster City, CA). MicroRNA candidates were verified using TaqMan miRNA Assay (Thermo Scientific, Grand Island, NY). The second part of the study was to validate these verified exRNA biomarker candidates with exRNA samples extracted from an independent cohort of 100 GC and 100 non-GC saliva samples. The cohort was not balanced for demographics on gender and smoking history but more accurately reflected the diagnostic setting where our proposed final model could be implemented.</p> <p>Reprinted from "Li F, Yoshizawa MJ, Kim K, Kanjanapangka J, Grogan T, Wang X, Elashoff D, Ishikawa S, Chia D, Liao W, Akin D, Yan X, Lee M, Choi R, Kim S, Kang S, Bae J, Sohn T, Lee J, Choi M, Min B, Lee J, Kim J, Kim Y, Kim S, Wong D. (2018) Development and Validation of Salivary Extracellular RNA Biomarkers for Noninvasive Detection of Gastric Cancer. Clin Chem. PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/30097497">30097497</a> DOI: 10.1373/clinchem.2018.290569", with permission from American Association for Clinical Chemistry (United States). </p>
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Project description:Massilia sp. KIM Genome sequencing and assembly
| PRJNA373823 | ENA
Project description:Here we modified a single cell whole transcriptome amplification method to make it capable of amplifying cDNAs as long as 3kb efficiently and unbiasedly. We combined this modified single cell cDNA amplification method with Applied Biosystems next generation sequencing SOLiD™ System to set up a single cell whole transcriptome assay. The modified amplification strategy allows us to amplify full-length cDNAs for most of the expressed genes. We show that it is feasible to get digital gene expression profiles at single cell resolution. This allows us to ask fundamental biological questions that could not be addressed previously, especially in the early embryonic development field, and to understand transcriptome complexity at the resolution of a single cell.
2009-02-23 | GSE14605 | GEO
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