Absolute units for proteins in Arabidopsis clock models up to U2020.5
DownloadThe dataset presents mathematical models of the gene regulatory network of the circadian clock, in the plant Arabidopsis thaliana. The work will be published as Urquiza-Garcia, Molina, Halliday and Millar, title "Abundant clock proteins point to missing molecular regulation in the plant circadian clock", in Molecular Systems Biology, 2025.
Starting from the U2019.3 and U2020.3 models, this project rescales parameters to match protein levels that were predicted using a simple model from the TiMet WP1a RNA dataset of Flis et al. 2015, without global reoptimisation. New data are acquired to test these protein levels using Nano-Luciferase (NanoLUC) reporter fusion proteins in transgenic plants.
Therefore these models retain the distinction, where U2019 retains the regulation of later PRRs by activation by earlier-expressed genes from the P2011 model, and U2020 replaces this regulation with repression of earlier-expressed PRRs by later-expressed PRRs. The model development is described in more detail in the 'Model Evolution' document attached.
Some early versions of the files with internal nomenclature might remain private and not included in the static Snapshot shared with the publication. The input data files, the computational environment for model development (a Docker image in the 'Reproducibility Toolset' assay) and the relevant model files are included here, as published in Urquiza et al. The biorXiv preprint version (https://doi.org/10.1101/2024.09.03.609973) and the final publication will also be linked here: the models and analysis are identical in both.
A Snapshot of this investigation will be available here on FAIRDOMHub.org, and at Zenodo and/or the University of Edinburgh's DataShare resource. Note we often have to make the Snapshot before we have the publication DOI, so that link might not be in the Snapshot.
DOI: 10.15490/fairdomhub.1.investigation.570.1
Zenodo URL: None
Created at: 19th Dec 2024 at 14:04
Predicting absolute levels of clock proteins with a simple model
No description specified
Jupyter notebook Predicting Protein Numbers
Jupyter lab notebook that contains the models and data that for predicting protein levels based on mRNA data from TiMet projecto
Simple model protein predictions from TiMet data
This files contains the predicions generated using a simple model of translation, described in the manuscript. This synthetic data was used to rescale U219.3 resulting in U2019.4 and U2020.3 into U2020.4. The .4 models are only resceled for the mass scale of protein and still present the dynamics of the .3 version
- Urquiza2016_protein_predictions_from_TiMet.xls
Timeseries protein data from literature
This time series were obtained from the literature by perroming rough quantiftification from western blot images. In some cases the data was quantified by the authors and graphs were provided in the publications. In this case we used ImageJ or https://automeris.io/WebPlotDigitizer/
- ProteinTimeseriesDB2.xlsx
U2019.4 antimony version
Derived from [U2019.3](https://fairdomhub.org/models/728?version=3) from [Testing the inferred rate of dynamic, gene regulatory network in absolute units](https://doi.org/10.1093/insilicoplants/diab022)
- U2019.4.scaled.txt
- U2019.4.txt
U2019.4 sbml version
Sbml version of U2019.4 with reacaling factors values already incoporated in the model. This was generated autmatically using tellurium python package
- U2019.4.scaled.sbml
U2020.4 antimony version
This file was derived from U2020.3 by introducing the scalig factors in the required locations in the model. This files is used then for numerically rescaling the model for matching synthetic protein data.
- U2020.4.scaled.txt
- U2020.4.txt
U2020.4 sbml version
This is the scaled version of U2020.4 in sbml file. It already contains the scaling factors
- U2020.4.scaled.sbml
Jupyter notebook for Protein predictions and U2019.4 rescaling
The jupyter notebook contains the code that predicts the number of monomers of several clock proteins and rescales the U2019.4 model which was published https://doi.org/10.1093/insilicoplants/diab022
- PredictingProteinNumbers_new_models_UU2019.ipynb
scaling factors for U2019.4 and predicted protein from timet
This file contains the scaling factors that can be used with U2019.4 that will match synthetic protein data generated with the simple translation model.
- U2019_4_scaling_factors.xls
scaling factors for U2020.4 and predicted protein from timet
This scaling factors can be pluged into U2020.4. They were derived by numerically matching the synthetic protein data
- U2020_4_scaling_factors.xls
Jupyter notebook for Protein predictions and U2020.4 rescaling
The jupyter notebook contains the code that predicts the number of monomers of several clock proteins and rescales the U2019.4 model which was published https://doi.org/10.1093/insilicoplants/diab022
- PredictingProteinNumbers_new_models_UU2020.ipynb
Linking U2019.5 and U2020.5 to protein data in absolute number of molecules per cell
Jupyter notebook file that describes how the models were finally linked to produce several plots were model predictions and data are compared
- Linking_U2019_5_and_U2020_5_to_NLdata_and_timet.ipynb
Linking U2019.5 and U2020.5 to protein data in absolute number of molecules per cell and in vivo
This describes how models were linked to in vitro data and then from there also linked to in-vivo data by detrending and rescaling in vivo data to match in vitro data for CCA1 and TOC1. The detrending was also derived by performing a long LD experiemnt fro servarl days and using the expression peaks of TOC1 to extract the trend in NLUC decay and plant growth.
- Linking_U2019_5_and_U2020_5_to_NLdata_and_vivo.ipynb
TiMet RNA timeseries data
RNA timeseries data for Arabidopsis Col wild-type plants and clock mutants, as separate mean and SD files. The raw data is available on BioDare.ed.ac.uk, and is linked as 'Attribution' from elsewhere on FAIRDOMHub.
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
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- TiMet_annaFlis_240714_mean.xls
Processed TiMet WP1.1a RNA data, SD
SD 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
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- TiMet_annaFlis_240714_sd.xls
Defining the robust behaviour of the plant clock gene circuit with absolute RNA timeseries and open infrastructure
Our understanding of the complex, transcriptional feedback loops in the circadian clock mechanism has depended upon quantitative, timeseries data from disparate sources. We measure clock gene RNA profiles in Arabidopsis thaliana seedlings, grown with or without exogenous sucrose, or in soil-grown plants and in wild-type and mutant backgrounds. The RNA profiles were strikingly robust across the experimental conditions, so current mathematical models are likely to be broadly applicable in leaf
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Protein level time series
Protein time series for clock proteins colected from the literature. Protein expression profiles were derived from images of western blot or or from plots that the orignal authors derived from quantitative western blots
Arabidopsis clock protein time series profiles collected from the literature
Small data base of clock proteins profiles obtained with western blots by several authors of A. thaliana collected from the literature. This data can be fed into simple models for making prediction of abosute number of protein when combined with RNA data in absolute units. For example the TiMet data set
- UrquizaGarcia_ProteinTimeseriesDB2.xlsx
Measuring absolute levels of clock proteins with calibrated NanoLUC assays
No description specified
Clock proteins NanoLUC fusion raw data
Insertion of events that rescued mutant phenotypes were selected for performing absolute quantification using calibration curves of recombinant purified MBP-NanoLUC-3Flag-10his. Seeds were sterilised with 5% houshold bleach for 10 min and washed three time with deionised water. The seeds were then put for stratifyication at 4ºC in darkenss for 48 hours in 1.5 ml polyproplyen tubes in dionised water. After 48 hours seeds wered plated on ROBUST agar (1/2 MS salts, 1.2% Agar pH 5.8 ajudsted with
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NanoLUC clock proteins fusions plate reader raw data Tristar2 berthold
"Samples of plants were collected in pre-weighed 2 ml microfuge tubes (safelock, Eppendorf) with 5 mm stainless steel grinding balls, and flash frozen in liquid nitrogen. The tissue was ground twice at 30Hz for 1 min in a Tissue Lyser (Qiagen). The samples were flash frozen between grinding steps, then placed on ice and 150 μl of BSII buffer was added to protect the samples from proteolysis, without phosphatase inhibitors (Huang et al. 2016). The tube was weighed and further BSII buffer added to
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- UrquizaGarcia_raw_plater_reader_data_NanoLUC_Clock_Proteins.xlsx
NanoLUC calibration curve Tristar2 Berthold
"Plates inoculated with Col-0 seed were grown under the same photoperiod conditions to the plants to be analysed. Plant tissue was harvested, making aliquots of 0.4 gFW. MBP-NL3F10H protein was prepared
by the method described by Urquiza-Garcia U. and Millar A.J. in Plant Methods 2019. and then quantified by the linearized Bradford assay protocol using both Bovine serum albumin BSA and Ovoalbumin as standards (Ernst & Zor 2010). Then aliquots spiked with purified enzyme to generate a curve
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- Urquiza_NanoLUC_calibration_curve.xlsx
Arabidopsis clock proteins time series in absolute units
Transformation of RLU into absolute units using a calibration curve of recombinant MBP-NanoLUC-3FLAG-10His
- protein_abs_units_timeseries_2023.xls
Calibration curve NanoLUC
Plot of linear regresion of calibration curve for inferring number of molecules from NanoLUC biolumienescence in plant extracts
- Calibration_NL.pdf
Clock protein number determination with NanoLUC calibration
Analysis for inferring the number of molecules of clock proteins using recombinant NanoLUC
Arabidopsis clock proteins time series in absolute units
Transformation of RLU into absolute units using a calibration curve of recombinant MBP-NanoLUC-3FLAG-10His
- protein_abs_units_timeseries_2023.xls
Calibration curve NanoLUC
Plot of linear regresion of calibration curve for inferring number of molecules from NanoLUC biolumienescence in plant extracts
- Calibration_NL.pdf
Clock_protein_time_series_12L_12D
4 seeds of stable NanoLUC T3 homozygous lines for LHY, PRR7, TOC1, and ELF3 were seeded in 96-well flat white plate that contained 150 µl of ROBUST media and stratified for 2 days at 4ºC. Then plates were incubated in a 2 hours pulse of white light given and transferred to 22 hours darkness at 21 ºC. Then transferred 12L:12D photoperiod for 10 days. On day 10, 50 µl of 1:50 Furimazine:0.05% Triton X-100 added to each well for tracking NanoLUC bioluminescence. A) Measurements using a Tristar plate
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- 120419t.xlsx
Jupyter notebook: Inference of clock protein numbers with NanoLUC calibration
Jupyter notebook that contains the linear regression for inferring numnber of molecules from NanoLUC biolumiescent data in plant extracts using as calibration curve recombinant MBP-NanoLUC-3FLAG-10His
- Linking_U2019_5_and_U2020_5_to_NLdata.ipynb
In vivo bioluminescence of clock protein-NanoLUC fusions: example experiment
Seedlings of the transgenic lines complemented with CCA1-NL and TOC1-NL were tested under 12L:12D cycles followed by constant light, to test how well the reporter signal in living plants reflected the expected patterns of protein expression. One example is linked below, from the BioDare2 repository record, because FAIRDOMHub's Data File is not accepting these URLs.
BioDare2 ID 11391; Plate reader experiment CCA1 TOC1 NanoLUC; permalink: https://biodare2.ed.ac.uk/experiment/11391
Recalibrating the clock models for absolute protein levels, to create models U2019.5 and U2020.5
No description specified
Reproducibility tool set
This section contains the links to the tools used for reproducing the computational results presented in Urquiza-Garcia et al. 2022. This is required in particular because the SloppyCell model optimisation software is at some risk. Using Docker we can assure persistence for the computational environment that allows you to run SloppyCell.
The associated git repository can be found in https://hub.docker.com/r/uurquiza/urquiza2019a_tellurium_sloppycell/tags which can be cloned.
The docker image can
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docker-compose.yml
With this file the user can type
docker-compose up
and will be able to run the operating system were the modelling and analysis took place
- docker-compose.yml
Propagating scaling factors into model parameters for U2019.4->U2019.5 and U2020.4->U2020.5
This script take the scaling paramters using synthetic protein data updates model paramaters
Clock_protein_time_series_12L_12D
4 seeds of stable NanoLUC T3 homozygous lines for LHY, PRR7, TOC1, and ELF3 were seeded in 96-well flat white plate that contained 150 µl of ROBUST media and stratified for 2 days at 4ºC. Then plates were incubated in a 2 hours pulse of white light given and transferred to 22 hours darkness at 21 ºC. Then transferred 12L:12D photoperiod for 10 days. On day 10, 50 µl of 1:50 Furimazine:0.05% Triton X-100 added to each well for tracking NanoLUC bioluminescence. A) Measurements using a Tristar plate
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- 120419t.xlsx
NanoLUC clock lines 3x12L:12D into LL Tristar measurments
4 seeds of stable NanoLUC T3 homozygous lines for LHY, TOC1 and ELF3 were seeded in 96-well flat white plate that contained 150 µl of ROBUST media and stratified for 2 days at 4ºC. Then a 2 hours pulse of white light given and transferred to 22 hours darkness at 21 ºC. Then transferred 12L:12D photoperiod for 10 days at which 50 µl of 1:50 Furimazine:0.05% Triton X-100 added to each well for tracking NanoLUC bioluminescence. Measurements using a Tristar plate reader were performed automatically
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- 290319t.xlsx
Model rescaling of U2019.4 and U2020.4 jupyter notebook
Documents the model paramter rescaling and set the scaling factors to 1
- Model_rescaling_analysis_U2019_U2020.ipynb
Estimating DNA-binding affinities for Arabidopsis proteins
No description specified
promoter binding affinity calculations on the genome based on PBMs and EMA for CCA1 and LUX
The promoter regions for clock genes that present a ChIP-seq signal were extracted from TAIR10 using costume python scripts using the gene list for Kamioka et al CCA1 or Daphne Ezer et al for LUX. The promoter was considered from the TSS of the gene until the annotated end of the upstream gene. Then, this region was scanned using the Energy Matrix derived using EMA working as a classifier for bound or unbound. After classification the calibrated PBM data calibrated using in vitro data was used
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LUX ensemble of matrices
The file contains the matrices that come from the MCMH sampling during the inference process from PBMs
- LUX_ensemble.npy
CCA1 ensemble of matrices
The file contains the matrices that come from the MCMH sampling during the inference process from PBMs
- cca1_ensemble.npy
CCA1 PBM E-score data Franco-Zorrilla et al
https://doi.org/10.1073/pnas.1316278111
- CCA1_intensity_ready.txt
LUX genomic regulation using PBMs and EMA
The promoter regions for clock genes that present a ChIP-seq signal were extracted from TAIR10 using costume python scripts using the gene list for Kamioka et al CCA1 or Daphne Ezer et al for LUX. The promoter was considered from the TSS of the gene until the annotated end of the upstream gene. Then, this region was scanned using the Energy Matrix derived using EMA working as a classifier for bound or unbound. After classification the calibrated PBM data calibrated using in vitro data was used
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- LUX_genomic_Regulation.ipynb
Reproducibility documentation
Files required for reproducibility of computational results. This include Docker file and python packages
Python packages
The list of python packages used was obtained by typing inside the Docker image
pip list -- format==columns > python_packages_pip_installed.txt
This list the version of packages installed as we have observed issues related to the use of the most current version of some python packaged for example scipy
Python packages pip installed
List of python packages for reproducing the modelling and data analysis results
- python_packages_pip_installed.txt
Construction of NanoLUC-tagged plants
Clock mutants for lhy-1/cca1-11, prr9/7, toc1, lux-4, elf3-1 were transformed with the genomic regions of the associated clock genes tagged with NanoLUC-3FLAG-10His. The tagged genomic constructs were transformed in the mutants using Agrobcterium ABI strain (kindly donated by Prof. Seth Davis University of York). T3 plants resistant to homozygous for BASTA resistance were phenotyped by luciferase imaging asessing period phenotype or plant architecture. Rescuing lines were then used for performing
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Gatway maps of genomic regions of clock genes
Maps of cloned genes for rescuing selected clock mutants
pDONR221:CCA1pro::CCA1
Donor plasmid for Gatway cloning for CCA1 genomic region
https://benchling.com/s/HcUdo0bf?m=slm-v3TyQ8AupdMj0SCqtZ2J
- pDONR221CCA1proCCA1.gb
pDONR221:LHYpro::LHY
Donor plasmid for Gatway cloning
https://benchling.com/s/PpY2tH3D?m=slm-pRd1S0YhNNVNUhMkT4N1
- pDONR221LHYproLHY.gb
pDONR221:PRR7pro::PRR7
Donor plasmid for Gatway cloning
https://benchling.com/s/g08AhXBj?m=slm-bGbYOjeh3kiwQQUdokaH
- pDONR221PRR7proPRR7.gb
pDONR221:TOC1pro::TOC1
Donor plasmid for Gatway cloning
https://benchling.com/s/02xiS4zk?m=slm-xxhynNMU6VkdMdqdfpFr
- pDONR221TOC1proTOC1.gb
pDONR221:LUXpro::LUX
Donor plasmid for Gatway cloning
https://benchling.com/s/3OtoUun0?m=slm-pL4lmqV9bCWOW3WvoSFL
- pDONR221LUXproLUX.gb
pGWB601:CCA1pro::CCA1-NL3F10H
Binary vector used for transforming with Agro ABI the cca1-1/lhy-1p:LUC for rescuing cca1-1 mutation.
https://benchling.com/s/Zu0nJONs?m=slm-5zxnih8JIOujB9nYIG8E
- pGWB601CCA1proCCA1-NL3F10H.gb
pGWB635:CCA1pro::CCA1-LUC+
CCA1 genomic fusion with LUC+ for comparision between NanoLUC and Firfly luciferase
https://benchling.com/s/ctB45lUQ?m=slm-ZYj5TlnFsbJeTkd2f9Aa
- pGWB635CCA1proCCA1-LUC.gb
pGWB601:LHYpro::LHY-NL3F10H
Binary vector used for transforming with Agro ABI the cca1-11/lhy-1 CCA1p:LUC for rescuing lhy-1 mutation.
https://benchling.com/s/GP25kROo?m=slm-ocCyiEfwuTW5mJsbNQGn
- pGWB601LHYproLHY-NL3F10H.gb
pGWB635:LHYpro::LHY-LUC+
Binary vector used for transforming with Agro ABI the cca1-1/lhy-1p:LUC for rescuing lhy-11 mutation. This was an alternative to NanoLUC and also for testing the behaviour of LHY.
- pGWB635LHYproLHY-LUC.gb
pGWB601:PRR7pro::PRR7-NL3F10H
Binary vector used for transforming with Agro ABI the prr9/7-9 CCR2:LUC for rescuing prr7-9 mutation.
- pGWB601PRR7proPRR7NL3F10H.gb
pGWB635:PRR7pro::PRR7-LUC+
Binary vector for transformation with Agro. This construct was intended for comparision with NanoLUC
- pGWB635PRR7proPRR7-LUC.gb
pGWB601:TOC1pro::TOC1-NL3F10H
Binary vector used for transforming with Agro ABI the toc1-2 CCA1p:LUC for rescuing the toc1-2 mutant.
- pgwb601toc1protoc1nl3f10h.gb
pGWB635:TOC1pro::TOC1-LUC+
Construct fof TOC1 for comparision with NanoLUC
- pGWB635TOC1proTOC1-LUC.gb
pGWB601:ELF3pro::ELF3-NL3F10H
Binary vector used for transforming with Agro ABI the elf3-2 CCA1p:LUC for rescuing elf3-2 mutation. In this particular case the plants selected were based on hypocotyl length. Based on the data of LUX in which we observed that rhytmicity was rescued in all lines, hypocotyl elongation varied between lines. Therefore, we used hypocotyl length for assesing complementation
- pgwb601elf3pelf3nl3f10h.gb
Selection of complemented transgenic lines
The reporter fusion constructs expressing clock proteins fused to NanoLUC or firefly FLUC were transformed into the cognate, clock-mutant host plants. Each host also contained a transcriptional FLUC fusion that was used to score the circadian period of each transgenic line in constant light. Transformants that expressed a functionally normal level of clock protein were selected by choosing lines that complemented the mutant's period defect back close to the wild type period. Note that the reporters
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Created: 19th Dec 2024 at 14:04
Last updated: 19th Dec 2024 at 14:05
