Ilya Akberdin

Projects: ZucAt, Modelling COVID-19 epidemics

Institutions: Institute of Cytology and Genetics, Novosibirsk State University

Reproducibility tool set

This section contains the links to the tools used for reproducing the computational results presented in U2019. This is required because SloppyCell is under the risk of becoming rotting code. Using Docker we can assure some persistence for the computational environment that allows to run SloppyCell.

The associated git repository can be found in https://github.com/jurquiza/Urquiza2019a.git which can be cloned.

The docker image can either be pulled from the docker hub site

docker pull ...

Submitter: Uriel Urquiza Garcia

Biological problem addressed: Model Analysis Type

Investigation: Absolute units in Arabidopsis clock models up t...

Study: P2011, U2019 and U2020 models and modelling res...

U2019/U2020 models

Collection of clock models that rescale transcript variables to account for absolute units. The relationship between models is summarised in the attached 'model evolution' document and in more detail in the linked publications (preprint version linked in the Snapshot; publication Urquiza and Millar, In Silico Plants 2021 did not have a DOI when Snapshot was created).

Each model is presented three times,

    • without a light:dark cycle,
    • with an ISSF (Adams et al. JBR 2012) that is set up for ...

Submitter: Uriel Urquiza Garcia

Biological problem addressed: Gene Regulatory Network

Investigation: Absolute units in Arabidopsis clock models up t...

Study: P2011, U2019 and U2020 models and modelling res...

Bottom up creation of the network from literature

The main input is the ENA review paper (Function and Regulation of the Saccharomyces cerevisiae ENA Sodium ATPase System, Ruiz&Ariño 2007) and the papers referenced. Another source are the papers linked from the ENA page of SGD http://www.yeastgenome.org/cgi-bin/locus.fpl?locus=ENA1

Submitter: Falko Krause

Biological problem addressed: Gene Expression

Investigation: ENA1 Transcription in Saccharomyces cerevisiae

Study: Modelling of the Signaling network regulating t...

Processed TiMet WP1.1a RNA data, mean

Mean values of clock gene RNA data in absolute units of RNA copies per cell (calculated from copies per gFW, / 25 million cells/gFW) from TiMet WP1.1, RNA dataset ros (from rosettes). Note the Col data are from WP1.1, not substituted with Col from the LD12:12 of the WP1.2 photoperiod data set, as they were in Flis et al. 2015. Note also that cL_m in these data is taken from CCA1 only, not the average of CCA1 and LHY as in the data sets used for optimisation of P2011.2.1 in Flis et al. 2015.

The ...

Creators: Andrew Millar, Uriel Urquiza Garcia

Submitter: Andrew Millar

Download
P2011.1.2_directupload

Exactly the same as model 243, but uploaded as a file rather than copied from PlaSMo.

Creator: Andrew Millar

Submitter: Andrew Millar

Download
Testing the inferred transcription rates of a dynamic, gene network model in absolute units (in silico Plants 2021)

Abstract (Expand)

The circadian clock coordinates plant physiology and development. Mathematical clock models have provided a rigorous framework to understand how the observed rhythms emerge from disparate, molecular … processes. However, models of the plant clock have largely been built and tested against RNA timeseries data in arbitrary, relative units. This limits model transferability, refinement from biochemical data and applications in synthetic biology. Here, we incorporate absolute mass units into a detailed model of the clock gene network in Arabidopsis thaliana. We re-interpret the established P2011 model, highlighting a transcriptional activator that overlaps the function of REVEILLE 8/LHY-CCA1-LIKE 5. The U2020 model incorporates the repressive regulation of PRR genes, a key feature of the most detailed clock model KF2014, without greatly increasing model complexity. We tested the experimental error distributions of qRT-PCR data calibrated for units of RNA transcripts/cell and of circadian period estimates, in order to link the models to data more appropriately. U2019 and U2020 models were constrained using these data types, recreating previously-described circadian behaviours with RNA metabolic processes in absolute units. To test their inferred rates, we estimated a distribution of observed, transcriptome-wide transcription rates (Plant Empirical Transcription Rates, PETR) in units of transcripts/cell/hour. The PETR distribution and the equivalent degradation rates indicated that the models’ predicted rates are biologically plausible, with individual exceptions. In addition to updated clock models, FAIR data resources and a software environment in Docker, this validation process represents an advance in biochemical realism for models of plant gene regulation.

Authors: Uriel Urquiza Garcia, Andrew J Millar

Date Published: 5th Aug 2021

Publication Type: Journal

Testing the inferred transcription rates of a dynamic, gene network model in absolute units

Abstract (Expand)

The circadian clock coordinates plant physiology and development. Mathematical clock models have provided a rigorous framework to understand how the observed rhythms emerge from disparate, molecular … processes. However, models of the plant clock have largely been built and tested against RNA timeseries data in arbitrary, relative units. This limits model transferability, refinement from biochemical data and applications in synthetic biology. Here, we incorporate absolute mass units into a detailed, gene circuit model of the clock in Arabidopsis thaliana. We re-interpret the established P2011 model, highlighting a transcriptional activator that overlaps the function of REVEILLE 8/LHY-CCA1-LIKE 5, and refactor dynamic equations for the Evening Complex. The U2020 model incorporates the repressive regulation of PRR genes, a key feature of the most detailed clock model F2014, without greatly increasing model complexity. We tested the experimental error distributions of qRT-PCR data calibrated for units of RNA transcripts/cell and of circadian period estimates, in order to link the models to data more appropriately. U2019 and U2020 models were constrained using these data types, recreating previously-described circadian behaviours with RNA metabolic processes in absolute units. To test their inferred rates, we estimated a distribution of observed, transcriptome-wide transcription rates (Plant Empirical Transcription Rates, PETR) in units of transcripts/cell/hour. The PETR distribution and the equivalent degradation rates indicated that the models’ predicted rates are biologically plausible, with individual exceptions. In addition to updated, explanatory models of the plant clock, this validation process represents an advance in biochemical realism for models of plant gene regulation.

Authors: Uriel Urquiza-Garcia, Andrew J Millar

Date Published: 20th Mar 2021

Publication Type: Tech report

Disturbed hepatic carbohydrate management during high metabolic demand in medium-chain acyl-CoA dehydrogenase (MCAD)-deficient mice.

Abstract (Expand)

UNLABELLED: Medium-chain acyl-coenzyme A (CoA) dehydrogenase (MCAD) catalyzes crucial steps in mitochondrial fatty acid oxidation, a process that is of key relevance for maintenance of energy homeostasis, … especially during high metabolic demand. To gain insight into the metabolic consequences of MCAD deficiency under these conditions, we compared hepatic carbohydrate metabolism in vivo in wild-type and MCAD(-/-) mice during fasting and during a lipopolysaccharide (LPS)-induced acute phase response (APR). MCAD(-/-) mice did not become more hypoglycemic on fasting or during the APR than wild-type mice did. Nevertheless, microarray analyses revealed increased hepatic peroxisome proliferator-activated receptor gamma coactivator-1alpha (Pgc-1alpha) and decreased peroxisome proliferator-activated receptor alpha (Ppar alpha) and pyruvate dehydrogenase kinase 4 (Pdk4) expression in MCAD(-/-) mice in both conditions, suggesting altered control of hepatic glucose metabolism. Quantitative flux measurements revealed that the de novo synthesis of glucose-6-phosphate (G6P) was not affected on fasting in MCAD(-/-) mice. During the APR, however, this flux was significantly decreased (-20%) in MCAD(-/-) mice compared with wild-type mice. Remarkably, newly formed G6P was preferentially directed toward glycogen in MCAD(-/-) mice under both conditions. Together with diminished de novo synthesis of G6P, this led to a decreased hepatic glucose output during the APR in MCAD(-/-) mice; de novo synthesis of G6P and hepatic glucose output were maintained in wild-type mice under both conditions. APR-associated hypoglycemia, which was observed in wild-type mice as well as MCAD(-/-) mice, was mainly due to enhanced peripheral glucose uptake. CONCLUSION: Our data demonstrate that MCAD deficiency in mice leads to specific changes in hepatic carbohydrate management on exposure to metabolic stress. This deficiency, however, does not lead to reduced de novo synthesis of G6P during fasting alone, which may be due to the existence of compensatory mechanisms or limited rate control of MCAD in murine mitochondrial fatty acid oxidation.

Authors: H. Herrema, T. G. Derks, T. H. van Dijk, V. W. Bloks, A. Gerding, R. Havinga, U. J. Tietge, M. Muller, G. P. Smit, F. Kuipers, D. J. Reijngoud

Date Published: 7th May 2008

Publication Type: Not specified

Mechanistic model of temperature influence on flowering through whole-plant accumulation of FT

Abstract

BioRxiv preprint:

Authors: Hannah A Kinmonth-Schultz, Melissa J MacEwen, Daniel D Seaton, Andrew J Millar, Takato Imaizumi, Soo-Hyung Kim

Date Published: No date defined

Publication Type: Not specified

TFInfer: a tool for probabilistic inference of transcription factor activities

Abstract (Expand)

SUMMARY: TFInfer is a novel open access, standalone tool for genome-wide inference of transcription factor activities from gene expression data. Based on an earlier MATLAB version, the software has now … been extended in a number of ways. It has been significantly optimised in terms of performance, and it was given novel functionality, by allowing the user to model both time series and data from multiple independent conditions. With a full documentation and intuitive graphical user interface, together with an in-built data base of yeast and Escherichia coli transcription factors, the software does not require any mathematical or computational expertise to be used effectively. AVAILABILITY: http://homepages.inf.ed.ac.uk/gsanguin/TFInfer.html CONTACT: gsanguin@staffmail.ed.ac.uk SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Authors: H M Shahzad Asif, , , Neil D Lawrence, Magnus Rattray,

Date Published: 24th Aug 2010

Publication Type: Not specified

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