Bilateral NSF/BIO-BBSRC - Translational landscape to link cell growth with proliferation in the root meristem

Lead Research Organisation: Royal Holloway, University of London
Department Name: Biological Sciences

Abstract

Our life depends on growing plants. Projected population increases together with anticipated disruptions to agricultural production by climate change create a pressing need to achieve step-change improvements in agricultural production to guarantee security of global food supplies. Increases in the application of nitrogen fertilizers underpinned the "green revolution" but are unsustainable. Work described in this proposal will contribute to an alternative route to increased agricultural production, which could be described as a "second green revolution". According to this strategy, agricultural productivity is increased through use of crops in which growth responses are optimized to sustain the increase in biomass in what would otherwise be limiting environments. Plant growth fundamentally depends on maintaining growth and proliferation of cells, which occurs in the meristems. The rate of cell production must be aligned with developmental cues, available energy, nutrient supplies and environmental conditions. Cytoplasmic growth in meristematic cells is largely constrained by protein synthesis and is coupled to cell division to maintain cell size homeostasis. There are evolutionarily conserved sensing and intracellular signalling mechanisms that inform cells on the available nutrient supply. Central to this is the so called TARGET OF RAPAMYCIN (TOR) protein, so named after an antifungal compound produced by a bacterium that was discovered in the Easter Island, Rapa Nui. TOR is central for cell growth mainly through the regulation of protein synthesis and connecting protein synthesis and cell proliferation, but these regulatory mechanisms are not well understood in plant cells. TOR is a master regulator and also functions through other output pathways. One main route of TOR function is through stimulating ribosomes to increase the translational capacity of cells for protein synthesis. Recent findings unexpectedly show that a canonical ribosomal protein target also functions as a transcriptional regulator (repressor). We found that this is in association with a key controller of the cell cycle, the RETINOBLASTOMA RELATED (RBR) protein, named after the cancer in the eye when mutated in humans. RBR and its partner proteins are thought to constitute a switch that controls cell proliferation and cell growth and can be flicked by environmental conditions. In this project we shall use root meristematic cells to systematically uncover transcriptionally and translationally regulated genes that function to connect cell growth and proliferation. We will then design experiments through which we can precisely observe the molecular behaviour of the components of the switch in time, as we alter the growth conditions, while at the same time following changes in growth through microscopic movies. These types of experiments will produce a wealth of data that allow building a comprehensive knowledge of the regulatory network. With additional help from carefully optimized computer models, we can learn the functioning of this cellular decision making circuitry and make predictions at different environmental and nutrient conditions what is the extent of cell proliferation and therefore root growth. Having achieved to construct such a predictive model we will test its performance in different real life situations, such as what happens to root growth in dark, or under limited nitrate or sucrose. We might also find that we missed some components, and this will prompt us for further experimentation. Having perfected the model we can start adapting it to other growth-altering conditions, such as stress, or to other parts of the plant important for crop yield, such as fruits or seeds.

Technical Summary

Cell growth and protein translation constrain cell proliferation. Emerging data indicate that growth signalling pathways (e.g. TOR and S6K) affect both translation and the commitment to cell proliferation through the RETINOBLASTOMA RELATED (RBR) pathway. The hypothesis is that translational control of specific mRNAs, for example through the untranslated regions, provides important regulatory links to couple cell growth and cell proliferation. Key pieces of evidence are that mutations of translation/ribosome associated proteins such as TOR, S6K, eIF3h and EBP1 deregulate the cell cycle.
This project aims to establish how growth-stimulating regulatory pathways (TOR, S6K) affect the Arabidopsis translatome as well as cell proliferation in the seedling root. Aim 1 will yield quantitative data on cell cycle parameters and translation over time while manipulating growth by environmental and genetic perturbation. In aim 2 the translation state of mRNAs will be measured in three ways, by ribosome immunopurification targeting root meristematic cells and cells in the elongation zone, by ribosome footprinting, and by density gradient fractionation of polysomes, followed by RNA sequencing. Together with mRNA transcript data, these techniques will reveal complementary aspects of translational control by the signalling pathways. In aim 3, we derive biochemical parameters of translation for all mRNAs. Aim 4 is to computationally identify cis-regulatory sequence motifs in mRNAs. Our final aim 5 is to condense the regulatory pathway to the principal components. We will collect time/spatially resolved data on the cell proliferation switch. Together with data from previous aims, we will use graph theoretical methods to generate a Bayesian network model of the cell proliferation switch.
Establishing the integration of protein translation and cell cycle control in the root tip model system will lay the groundwork for future modelling of cell proliferation in other plant organs.

Planned Impact

Our principal aim is to deliver excellent science that will provide profound novel insights into one of the most fundamental aspects of plant biology, namely how protein synthesis drives cell growth and proliferation, and how this impacts on biomass and plant yield. Uncovering the underlying regulatory machinery, and building predictive models that test our understanding of these processes, may improve our ability to optimize plant function by genetic improvement. While our model will necessarily focus on a tractable model system, the response of the Arabidopsis root tip to photosynthate, it is clear that aspects of the model will apply to other organs, such as fruits or seeds, to crop plants, where the same machinery is highly conserved, and to other signals, such as stress, or nitrogen status.
Besides disseminating the immediate intellectual merit of the work through publication, we also propose a strategy for translating the results for the benefit of agricultural biotechnology, through partnerships with industry, joint academic-industrial grant proposals, and exploring the protection of intellectual property. The public will benefit in the long term from economic activity, market forces on consumer prices, and sustainable agricultural production.
The immediate impact of this research will be enhanced knowledge and understanding of the fundamental process, which will be communicated to public in ways that enrich societal understanding of fundamental biological processes and scientific methods, such as genetic modifications. The PIs have skills and developed channels to disseminate this knowledge in schools and during University open days. An existing partnership with a local artist will be developed to produce documentation and to engage the public in creative ways.
Finally, the training and professional mentoring of the postdocs and PhD students employed in this multidisciplinary and collaborative project will develop the scientific workforce in academia or industry in a growth area that suffers from a shortage of skilled personnel.
 
Title Artist in residence Kerry Lemon 
Description Drawing of plants with increased understanding how development shapes growth 
Type Of Art Artwork 
Year Produced 2014 
Impact Stimulating discussions with students. Media release. Planned exhibition. 
URL http://www.kerrylemon.co.uk/
 
Title Exhibition Hidden/revealed 
Description Hidden/Revealed exhibition accompanied by a series of short talks, 'Talking Triptychs,' 
Type Of Art Artistic/Creative Exhibition 
Year Produced 2017 
Impact Art work well recieved by the public visitors. Loads of comments in the visitors book. 
URL https://www.royalholloway.ac.uk/staff/news-events/event-articles/hiddenrevealed-talking-triptychs.as...
 
Description 1. How photosynthates are utilised for plant growth is fundamental for crop productivity. We have discovered two novel pathways in this process involving the regulation of protein translation. On the top of both pathways is an evolutionary conserved signalling protein called TOR. We showed that TOR through the S6K regulates the phosphorylation of the RETINOBLASTOMA RELATED protein and cell proliferation. We have discovered together with our US collaborator a key translational regulator, the eIF3h which is targeted by the TOR-S6K pathway and regulates the translation initiation of mRNAs central for maintenance of cell proliferation in shoot and root meristems. We focussed on two of the most important targets that have translational control with detailed experimental work, the PLETHORA (PLT2) and TCP proteins (TCP8, TCP14, TCP15). We showed that PLT2 and TCP14 physically and genetically interact in the root to determine meristem maintenance and cell proliferation.
2. Plants and crops grow in a naturally fluctuating environment. Within this project we discovered how photosynthates and light through TOR signalling tune both shoot and root growth through the regulation of protein translation. Unexpectedly we found that photosynthates through TOR, RBR and E2F transcription factors provide an input to the circadian clock to determine the day-night rhythm of plants. We mapped two inputs, one in the morning and one in the evening with two opposing E2Fs that both negatively regulate each other and contribute to maintain the central oscillation mechanism of the clock. Our US collaborator focussed on the circadian control of protein translation, and found key translational targets that links with cell cycle control.
3. Understanding the diurnal cycle of Arabidopsis via network-based analysis of translatomics data (Paccanaro- Cheng Ye). Analysing the data came from our US collaborator, the Vonarnim Lab we constructed two time-varying networks for wildtype Arabidopsis and circadian-clock-interrupted Arabidopsis (CCA1-ox), respectively. The nodes in the networks are genes and remain the same across different time points. The weighted edges in the network represent the co-translation correlations between genes and are varying over time. A positive weight indicates that the translational states of two genes change in a similar manner, i.e., either both increase or both decrease, while a negative weight implies the opposite.
We performed a well-developed network module detection technique, namely Louvain algorithm on both wildtype and CCA1-ox networks to find clusters of genes which are densely connected in the network and whose translational states peak at different times during the diurnal cycle. We found that the day cluster genes (peak at 12am) found in the wildtype network show significant overlap with night cluster genes (peak at 6pm) found in CCA1-ox network. This implies that there is an approximately 6-hour shift in the gene translational states between wildtype and CCA1-ox Arabidopsis, which can be supported by experimental results. We further performed Gene Set Enrichment Analysis (GSEA) on the clusters of genes we have detected and identified a list of GO terms which are statistically enriched in these clusters.
4. In collaboration with the US partner we have shown that TOR regulates the Erb3 binding protein (EBP1) and thereby ribosome biogenesis and translation initiation. EBP1 recently came to the forefront as a conserved central growth controller in yeast, human and plants. In this collaborative project we could show that EBP1 antagonising the RBR pathway to maintain cell proliferation in the meristem. Importantly, this genetic interaction is converging on the regulation of ribosome biogenesis.
5. Acceleration of cell cycle through TOR signalling poses a threat of frequent of DNA damage, and to prevent passage of damaged genome to the next generations, cell cycle must be halted. We found that the RBR-E2FA complex localise on damaged heterochromatin foci and together they act as transcriptional repressor of the orthologue of the human breast cancer susceptibility gene 1 as well as a chromatin modifier to non-transcriptionally facilitate DNA repair. Biologically, it makes sense that RBR, being a master cell cycle regulator, also has a role in safeguarding the genome and thus ensuring genome integrity during proliferation.
6. Studying how light activates the shoot meristem and how it relies on TOR and hormone signalling we uncovered the role of a MAPK pathway (MKK7-MPK6) that arrest meristem in the dark by direct phosphorylation of the PIN1 auxin transporter.
7. Detecting critical timings of Chlamydomonas cell growth using dynamic network analysis (Paccanaro- Cheng Ye). To identify the critical time points when the cell growth procedure changes fundamentally, we compared the proteomics data between two types of Chlamydomonas: control and rapamycin in which the TOR (target of rapamycin) gene is inhibited. We obtained a high time resolution dataset through a collaboration with the Giavalisco group in the Max Planck Institute for Molecular Plant Physiology, Golm. We built two dynamic networks from the proteomics data for control and rapamycin, respectively. The nodes in the network are genes, while the links between nodes represent the protein intensity correlation between genes and are varying through time.
We used four robust network measurements to assess the structural complexity of the control and rapamycin networks, at each time point, which allows us to understand how the overall pattern of gene connections changes during cell growth. The four measurements are: 1) degree distribution, which shows the strength of connections in the network, e.g., how many genes are strongly connected to others and how many genes are weakly connected; 2) average shortest path length, which is the mean of the lengths of shortest paths between all possible pairs of genes in the network; 3) average clustering coefficient, which measures to which degree genes are forming tight groups in the network; 4) graph von Neumann entropy, which assesses to what degree a network deviates from the structures of randomized networks. One of the most important findings from the time series of the four measurements is that the control network undergoes a fundamental structural change around the 4th hour since the start of the experiment, while the rapamycin network changes around 2 or 3 hours later. This conforms to biological ground truth and these time points appear to be the commitment moments of the cell growth of control and rapamycin Chlamydomonas.
8. The Corrected Gene Proximity map for the analysis of the 3D genome organization (Paccanaro- Cheng Ye). The different types of cells in a tissue have an identical one-dimensional (1D) genome, i.e., a linear sequence of nucleotides, yet their genomes have different underlying 3D architectures. The spatial proximity between genomic elements plays a central role in gene regulation and cell fate determination, and its disruption might lead to dysregulation. RBR-E2Fs are centrally important for chromatin regulation, but how these regulation is happening in time and space is not understood. Over the last decade, genome-wide ligation-based assays such as Hi-C have provided an unprecedented opportunity to investigate the 3D organization of the genome, and thus the spatial proximity between any genomic elements of interest.
We propose a novel graph-theoretical framework, the Corrected Gene Proximity (CGP) map, to study the effect of the 3D spatial organization of genes in regulation. The starting point of the CGP map is a weighted network, the gene proximity map, whose weights are based on the contact frequencies extracted from genome-wide Hi-C data. The CGP map is then obtained from the gene proximity map by reducing high contact frequencies that are due to small genomic distances between genes. Using Hi-C data and transcriptomics data from 12 human cancer cell lines, we show that the CGP map can detect and quantify to what degree co-expressed genes are tightly clustered more effectively than when using the raw contact frequencies. As a proof of concept for this methodology, we analyzed the expression pattern of 186 metabolic pathways of both normal and cancer cell lines, we further find that the relative positioning between genes, as captured and quantified by CGP, is highly correlated with their expression change. We also show that the CGP map can be renormalized to form an inter-chromosomal proximity map, allowing distinct chromosomal translocations in human leukemic cells to be identified.
Exploitation Route 1. Map the TOR-dependent phosphorylation sites on RBR and modify them for better growth characteristics.
2. EBP1 expression was correlated by hybrid vigour in the literature. Knowing the molecular mechanism how EBP1 controls growth will allow to investigate and exploit EBP1 regulation to attain better hybrids in crops.
3. The novel computational method for the analysis of time series molecular data is powerful to uncover biological transition points and drivers of these transitions. This method can be utilised wherever high resolution time series data are available.
4. Computational method to analyse Hi-C data to uncover the role of chromatin in bringing together genes for regulation in time and space.
Sectors Agriculture, Food and Drink

 
Description 1. Hybrid vigour is outstandingly important for crop productivity in modern agriculture, but the molecular basis is purely understood. Previously we discovered that a gene called Erb3 binding protein (EBP1) dose-dependently regulates growth in potato. EBP1 was also linked as a major component behind hybrid vigour. Within this project in collaboration with our US partner we showed that the molecular function of EBP1 is to boost protein translation through two independent routes, regulating ribosome biogenesis in the nucleolus and regulating translation initiation in the cytoplasm. We also show that EBP1 antagonises the differentiation promoting function of the RETINOBLASTOMA RELATED and thereby maintain meristematic function to promote plant growth. We used Arabidopsis as a model for these mechanistic discoveries of EBP1 function. To realise this important discovery we are starting to collaborate with Prof Gerrit Beemster working on maize. Proposed collaboration on this topic with the seed company KWS. We have expanded the work on seed development, seed germination and how EBP1 amount effect this process. 2. A second lead developed from the project is the realisation that the E2F transcription factors and the S6K upstream regulator are repressors of organ growth in environmentally limiting conditions. Because it is feasible to genetically alter these genes to attain growth benefits of crop plants we are looking into ways to transfer this knowledge to crop plants, focusing on wheat, barley and maize.
First Year Of Impact 2019
Sector Agriculture, Food and Drink
Impact Types Economic

 
Description Advisory Board of Agricultural Biotechnology Institute
Geographic Reach Europe 
Policy Influence Type Participation in a advisory committee
Impact Influence the governance and funding and research evaluation of the Institute
URL http://www.abc.hu/en/
 
Description Doctor Honoris Causa degree at the Semmelweis Medical University, Budapest
Geographic Reach Europe 
Policy Influence Type Influenced training of practitioners or researchers
Impact Involvement in the governing bodies of the University
URL http://semmelweis.hu/english/
 
Description ERC activities in Hungary
Geographic Reach Europe 
Policy Influence Type Participation in a national consultation
 
Description Hungarian Higher Education Accreditation Committee
Geographic Reach Europe 
Policy Influence Type Membership of a guideline committee
Impact Giving advice on establishing and functioning of doctoral training programs, university professor appointments, higher education teaching programs
URL http://tir.mab.hu/
 
Description Pilot project to support subsistence farming in sub-Saharan Africa
Geographic Reach Africa 
Policy Influence Type Influenced training of practitioners or researchers
Impact A team of researchers, NGO organisation and stakeholder were brought together to design projects that enable to increase the efficiency and profitability of subsistence farming in sub Saharan Africa. This project combines basic science knowledge with available practices to improve farming and enable to develop water saving practices, focusing on vegetable farming.
 
Description REF Czech Republic
Geographic Reach National 
Policy Influence Type Membership of a guideline committee
Impact Advice on Academic Institute structures, research directions
 
Description 11. Ara-MKK-D: A bioinformatics and systems biology approach for the functional analysis of a growth-regulating MAP kinase pathway in Arabidopsis.
Amount € 189,670 (EUR)
Funding ID 41909 
Organisation European Commission 
Sector Public
Country European Union (EU)
Start 10/2007 
End 10/2009
 
Description ABI innovation
Amount $1,203,514 (USD)
Organisation National Science Foundation (NSF) 
Sector Public
Country United States
Start 09/2017 
End 09/2020
 
Description Inference of RBR network and dynamic RBR complexes during leaf development.
Amount € 319,888 (EUR)
Funding ID 330789 
Organisation European Commission 
Sector Public
Country European Union (EU)
Start 03/2013 
End 03/2015
 
Description Molecular signatures: a systems biology tool to understand how leaf development is constrained by drought.
Amount € 121,869 (EUR)
Funding ID 255035 
Organisation European Commission 
Sector Public
Country European Union (EU)
Start 08/2010 
End 07/2011
 
Title Identifying protein interactions for the E2F and RBR 
Description Generating GFP-tagged lines for the RBR and E2F proteins and developed a pull down and mass spectrometry identification method for protein interactors 
Type Of Material Technology assay or reagent 
Year Produced 2017 
Provided To Others? Yes  
Impact Identification of the full components of the DREAM complex in plants. Identification of functional differences among the plant E2F transcription factors. Realising the involvement of E2Fs in DNA damage response 
 
Title Purification of protein complexes 
Description Use genomic tagged GFP lines for rapid purification of protein complexes and identification of protein complex components 
Type Of Material Biological samples 
Year Produced 2016 
Provided To Others? Yes  
Impact Established collaborations and accepted manuscript in EMBO J in 2017 
 
Title Root cell type-specific tagging of RBR-E2F components 
Description GFP and FLAG tagging of RBR, E2FA, E2FB, E2FC, S6K1, S6K2 under the root cell type specific promoters in stem cell progenitors and elongation zone to be able to analyse these proteins during root development 
Type Of Material Cell line 
Provided To Others? No  
Impact Enable us to purify RBR, E2Fs cell type specifically 
 
Title mutant lines, antibodies, GFP-tagged lines 
Description Tools for lipid signalling kinases, MAPKs, E2F-RBR such as antibodies, mutant lines, GFP-tagged lines 
Type Of Material Cell line 
Provided To Others? Yes  
Impact shared research material facilitate research in other groups 
 
Title Disease Similarity 
Description We introduce a MeSH-based method that accurately quantifies similarity between heritable diseases at molecular level. This method effectively brings together the existing information about diseases that is scattered across the vast corpus of biomedical literature. We prove that sets of MeSH terms provide a highly descriptive representation of heritable disease and that the structure of MeSH provides a natural way of combining individual MeSH vocabularies. We show that our measure can be used effectively in the prediction of candidate disease genes. 
Type Of Material Computer model/algorithm 
Year Produced 2015 
Provided To Others? Yes  
Impact There are no impacts yet, this work appeared only about 3 months ago. 
 
Title Landis 
Description Disease similarity measures quantify the distance between disease modules on the interactome. These measures can provide a starting point for in-depth exploration of the diseases at molecular level, and are of particular relevance for orphan diseases. LanDis is an explorable database, containing the disease similarities of 28.5 million pairs of heritable diseases. These are calculated by summarising the existing phenotype information about diseases through large scale analysis of hand curated data. 
Type Of Material Database/Collection of data 
Year Produced 2016 
Provided To Others? Yes  
Impact The paper presenting this database/model is still under review, so most scientist are not aware of its existence yet. However, I have already presented to conferences and meetings, receiving an extremely good feedback from everyone who tried it, especially clinician scientists. 
URL http://www.paccanarolab.org/landis/
 
Title mutation3d 
Description A new algorithm and Web server, mutation3D (http://mutation3d.org), proposes driver genes in cancer by identifying clusters of amino acid substitutions within tertiary protein structures. We demonstrated the feasibility of using a 3D clustering approach to implicate proteins in cancer based on explorations of single proteins using the mutation3D Web interface. 
Type Of Material Computer model/algorithm 
Year Produced 2016 
Provided To Others? Yes  
Impact No notable impacts yet, the paper only appeared about a month ago. 
URL http://mutation3d.org/
 
Description Albrecht Von Arnim 
Organisation University of Tennessee
Department Department of Geography
Country United States 
Sector Academic/University 
PI Contribution TOR and S6K signalling, EBP1
Collaborator Contribution regulation of translation, making constructs for root meristem specific analysis of translatome and translational regulation
Impact project partner, manuscripts in preparation
Start Year 2015
 
Description Cancer genomics -- Haiyuan Yu (Cornell University) 
Organisation Cornell University
Country United States 
Sector Academic/University 
PI Contribution We recently started a collaboration with Yu lab in the field of cancer genomics, where we contributed to the development of a clustering method to predict cancer mutation hotspots in proteins. We used our expertise in clustering methods to provide an efficient solution an integrate it into a comprehensive analysis pipeline.
Collaborator Contribution Prof Yu and his lab have great expertise in the field of cancer genomics. They have contributed the biological question and the data.
Impact A journal paper describing the method is currently under review in BMC Biology. The collaboration is multi-disciplinary involving biologists and computational scientists.
Start Year 2013
 
Description Csaba Koncz 
Organisation Max Planck Society
Department Max Planck Institute for Plant Breeding Research
Country Germany 
Sector Academic/University 
PI Contribution Working on S6K
Collaborator Contribution Working on SnRK1, providing mutants and tool
Impact Joint projects, research papers
 
Description Development of a web resource for protein functional annotation -- Raj Sasidharan (BASF) 
Organisation BASF
Country Germany 
Sector Private 
PI Contribution We developed ConSAT, a tool for protein functional annotation using protein consensus domain architectures. In this project a new algorithm was developed and a web resource (ConSAT) with precomputed results was created (available at http://paccanarolab.org/consat ). The method includes three different types of functional prediction methods, two assigning Gene Ontology terms from the protein architecture, and one assigning English weighted words.
Collaborator Contribution Rajkumar Sasidharan's help was very important for the development of this project, mainly in two different fields: first, he provided expert knowledge in structural biology; second, he helped giving feedback on the usability of the web server, leading to its improvement.
Impact The project main output is the above referenced website. Publications are currently being written. The collaboration is multi-disciplinary involving biologists and computational scientists.
Start Year 2012
 
Description Disease gene prioritisation by the combination of gene networks -- Giorgio Valentini (Milan) 
Organisation University of Milan
Country Italy 
Sector Academic/University 
PI Contribution We preprocessed, cleaned and provided a set of biological datasets to Giorgio Valentini to assist in the development of several methods of gene networks combination for disease-gene prioritisation (that is, finding new causative genes for diseases). We provided, among others, several semantic similarity networks among sets of human genes. We also suggested new evaluation measures for this task.
Collaborator Contribution Giorgio Valentini developed a set of algorithms for finding new disease-gene associations. In that context he proposed many different ways in which different gene networks (both weighted and unweighted) could be combined to produce a resulting network resembling a relation based on the fact that two linked genes are supposed to share an underlying disease. The new predictions are given as an output of the paper (available at http://homes.di.unimi.it/re/suppmat/genesmeshnetwpred/supmatTBL1.html ).
Impact Apart from the above mentioned URL, the collaboration led to the following publication: G Valentini, A Paccanaro, H Caniza, AE Romero, M Re An extensive analysis of disease-gene associations using network integration and fast kernel-based gene prioritization methods Artificial Intelligence in Medicine 61 (2), 63-78
Start Year 2013
 
Description Dr Tamas Meszaros 
Organisation Semmelweiss University
Country Hungary 
Sector Academic/University 
PI Contribution In vitro translation of RBR and E2Fs and CDK kinases for protein-protein interaction and phosphorylation studies. In vitro translation of MAPKs and MKKs. Study protein-protein interaction and activation.
Collaborator Contribution In vitro protein interaction and phosphorylation screen
Impact Joined publications, projects
Start Year 2015
 
Description Dr Zoltan Magyar 
Organisation Hungarian Academy of Sciences (MTA)
Department Biological Research Centre (BRC)
Country Hungary 
Sector Academic/University 
PI Contribution Working on RBR-E2F, connecting translational regulation and cell cycle
Collaborator Contribution Providing antibodies and mutants in the RBR-E2F pathway
Impact research papers, collaboration with Bayern Crop Science
 
Description Dream complex roles and transcriptional targets 
Organisation Nagoya University
Country Japan 
Sector Academic/University 
PI Contribution We made GFP-tagged lines for RBR, E2FA, E2FB, E2FC and characterised single and multiple KO lines for E2Fs. We performed GFP pull down mass spec experiments for RBR, E2Fs and MYB3Rs to identify DREAM complex components. Made ChIP experiments for E2Fs
Collaborator Contribution Made GFP-tagged lines for MYB3Rs, KO lines. Made RNAsec for e2f and myb3r KO lines. Made ChIPsec for MYB3Rs
Impact 3 publications, Visit and seminar of Dr Ito to RHUL. Planned joined grant application.
Start Year 2006
 
Description Drug side effect prediction (with Mark Gerstein and Shantao Li, Yale University) 
Organisation Yale University
Country United States 
Sector Academic/University 
PI Contribution We have developed a new method for predicting side effects of drugs. Our preliminary results show that our method represents a great improvement with respect to the existing state of the art in terns of side effect prediction. Moreover, it is the first method that can predict the expected frequency of side effects in the population.
Collaborator Contribution They are helping us to provide an explanation of some aspects of our models in terms of the biology/biochemistry/pharmacology.
Impact A journal article is in preparation.The collaboration is multi-disciplinary involving biologists and computer scientists.
Start Year 2017
 
Description Enhancer prediction using epigenetic signals in different mouse tissues (with Mark Gerstein and Mengting Gu, Yale University) 
Organisation Yale University
Department Department of Molecular Biophysics and Biochemistry
Country United States 
Sector Academic/University 
PI Contribution Apply machine learning, signal processing and pattern recognition methods for improving the performance of the enhancer prediction for different tissues in the mouse genome. Preliminary results indicate that ensemble methods perform better than other classifiers. More advanced methods for feature extraction such as deep learning are going to be tested on the data.
Collaborator Contribution Members of the Gerstein Lab developed a pattern recognition method called matched filters for enhancer prediction. However, our preliminary results show that advanced machine learning may improve prediction accuracy. The Gerstein Lab supplied the data and will interpret the results in the context of enhancer and promoters in the genome.
Impact The collaboration is multi-disciplinary involving biologists and computer scientists.
Start Year 2017
 
Description Finding evolutionary relations between plant MAPKs -- Laszlo Bogre (Royal Holloway) 
Organisation Royal Holloway, University of London
Department School of Biological Sciences
Country United Kingdom 
Sector Academic/University 
PI Contribution We collaborated with the Bogre lab in the elucidation of the evolutionary relations between the different Mitogen-activated protein kinases (MAPKs) in different model plants. Using computational techniques we were able to depict some of this relations, ultimately leading to the construction of the 'Plant MAPK Network Resource', available at http://www.paccanarolab.org/static_content/MAPKevol/ .
Collaborator Contribution Prof Bogre and his team provided us with their MAPK dataset, their expert knowledge in the field and their biological questions. This lead to the improvement of our methods for ortholog detection. The collaboration is still ongoing and we are currently developing new computational methods to detect relations between MAPKs and substrates.
Impact The outputs of this project are two: one web resource (the plant MAPK network resource, see above) and one joint publication: R. Dóczi, L. Ökrész, A. E. Romero, A. Paccanaro, and L. Bögre Exploring the evolutionary path of plant MAPK networks Trends in Plant Science, vol. 17, iss. 9, pp. 518-525, 2012. The collaboration is multi-disciplinary involving biologists and computational scientists.
Start Year 2011
 
Description Functional prediction for Macrophomina phaseolina -- Pablo Sotelo (Universidad Nacional de Asuncion) 
Organisation National University of Asuncion
Country Paraguay 
Sector Academic/University 
PI Contribution We have provided the Sotelo lab with a complete functional annotation of the fungus Macrophomina phaseolina. This was done using both S2F and CONSAT, our systems for protein function prediction. Macrophomina phaseolina has been recently sequenced and is responsible for a plague affecting many crops and particularly soya, of which Paraguay is one of the largest producers in the world. Our contribution will help, in ultimate analysis, both the development of new pesticides to fight this fungus, and in the research of genetically modified varieties of soya, resistant to this plague.
Collaborator Contribution The Sotelo lab has been providing us with feedback to improve our system and on the accuracy of our predictions. This is very helpful for us in order to improve our system.
Impact This is a multidisciplinary collaboration, between computational scientists (Paccanaro lab) and life scientists (Sotelo lab). We expect to produce a joint publication in the near future as an output of this collaboration. The collaboration is multi-disciplinary involving biologists and computational scientists.
Start Year 2014
 
Description Gene prioritisation for lymphoma growth on mutagenesis study 
Organisation Medical Research Council (MRC)
Department MRC Clinical Sciences Centre (CSC)
Country United Kingdom 
Sector Public 
PI Contribution Prediction of lymphoma growth stage by analysis of gene clonality values from a sample. Prioritisation of genes selected from broad loci sources involved in lymphomagenesis. This process yielded a set of about 20 genes selected for further studies.
Collaborator Contribution Mutagenesis developed lymphoma studies on over 500 mice, with the corresponding sample clonality analysis. Ongoing gene relevance analysis.
Impact Studies are still ongoing on the relevance of the selected genes. We expect to obtain a publication about this work when the process finishes. The study is multi-disciplinary and it comprises the following disciplines: cancer genomics, molecular biotechnology, systems biology, computer science, big data analysis, bioinformatics.
Start Year 2015
 
Description GoSSTo, a Tool for computing Gene Ontology Semantic Similarites -- Giorgio Valentini (University of Milan) 
Organisation University of Milan
Country Italy 
Sector Academic/University 
PI Contribution We developed GoSSTo a command line based-tool to compute semantic similarities between gene products. The tool implemented an algorithm previously published in our group, trying to make it accessible to any possible researcher. We also implemented GoSSToWeb, a web server providing easier access to this tool for biological researchers.
Collaborator Contribution Giorgio Valentini and his lab provided help for the development of the web interface of our tool for computing semantic similarities which was recently published, and also provided user feedback on the command line tool.
Impact The output is constituted by our software tools (GoSSTo and GoSSToWeb). Our web tool, available at www.paccanarolab.org/gosstoweb has had over 50 registered users and 70 submitted jobs thus far. Moreover, the collaboration is manifested in the following publication: H. Caniza, A. E. Romero, S. Heron, H. Yang, A. Devoto, M. Frasca, M. Mesiti, G. Valentini, and A. Paccanaro, GOssTo: a user-friendly stand-alone and web tool for calculating semantic similarities on the Gene Ontology Bioinformatics, vol. 30, iss. pp. 2235-2236, 2014. A preliminary version of this paper was submitted and accepted to the ISMB conference in 2013: H. Caniza, A. E. Romero, S. Heron, H. Yang, M. Frasca, M. Mesiti, G. Valentini, and A. Paccanaro. 'GOssTo and GOssToWeb: user-friendly tools for calculating semantic similarities on the Gene Ontology.' Bio-Ontologies SIG 2013-ISMB 2013 (2013).
Start Year 2012
 
Description Learning disease-gene associations by exploiting disease similarities (with Mark Gerstein, Yale University) 
Organisation Yale University
Department Department of Molecular Biophysics and Biochemistry
Country United States 
Sector Academic/University 
PI Contribution We recently developed a disease similarity measure and calculated all the disease-disease similarities between OMIM diseases. We established a prior disease-gene association probability and provided training and testing datasets for the learning. We fitted the model.
Collaborator Contribution Developed a Lipschitz diffusion model, that we used to spread the disease-gene association through the interactome, and a fully functional fast implementation of the algorithm.
Impact The collaboration is multi-disciplinary involving biologists and computer scientists.
Start Year 2017
 
Description Network-based Genome Analysis Reveals Structural and Functional Properties of Genes (with Mark Gerstein and Koon-Kiu Yan, Yale University) 
Organisation Yale University
Country United States 
Sector Academic/University 
PI Contribution We have analysed the spatial proximity of all pathway genes (KEGG Database) across various cancer cell lines. Our preliminary results provide strong evidence for a relationship between disease pathways and cancer. The study also helps identify candidate genes for a number of diseases.
Collaborator Contribution They have successfully applied network community detection techniques to Hi-C data (three-dimensional architecture of genomes) in order to identify topologically associating domains (TADs) of genomic regions.
Impact The collaboration is multi-disciplinary involving biologists and computer scientists.
Start Year 2017
 
Description Objective of the project is to elucidate the mechanism of action of a drug for multiple sclerosis 
Organisation Imperial College London
Department Faculty of Medicine
Country United Kingdom 
Sector Academic/University 
PI Contribution To analyse transcriptomics data obtained from a trial on human patients using network medicine approaches.
Collaborator Contribution They hosted a trial with human patients and extracted transcriptomics data at different times..
Impact No outputs yet. This collaboration is multidisciplinary involving: computer science, network science, machine learning, medicine, biology and pharmacology.
Start Year 2015
 
Description Patrick Giavalisco 
Organisation Max Planck Society
Department Max Planck Institute of Molecular Plant Physiology
Country Germany 
Sector Charity/Non Profit 
PI Contribution Connecting TOR-S6K to RBR
Collaborator Contribution TOR silenced lines
Impact Joined project proposal
Start Year 2010
 
Description Pavla Binarova 
Organisation Academy of Sciences of the Czech Republic
Country Czech Republic 
Sector Academic/University 
PI Contribution Analysing RBR phosphorylation and interaction with microtubules.
Collaborator Contribution Microtubules, cell biology
Impact research papers, joined projects
Start Year 2010
 
Description RBR phosphorylation mapping by mass spec 
Organisation University of Warwick
Department Institute for Employment Research
Country United Kingdom 
Sector Academic/University 
PI Contribution providing phosphorylated RBR samples
Collaborator Contribution Start mapping RBR phosphosites by mass spec
Impact initial results of 7 new RBR phopsho-sites and 2 related kinases
Start Year 2015
 
Description Robert Doczi. MAPK evolutionary network, MAPK substrate prediction. 
Organisation Hungarian Academy of Sciences (MTA)
Department Centre for Agricultural Research (ATK)
Country Hungary 
Sector Academic/University 
PI Contribution The Paccanaro group analysed MAPK docking sites, and MAPK-MKK interaction surfaces when there is no canonical docking site.
Collaborator Contribution Developed a high throughput in vivo MAPK activation screen
Impact publications. Multidisciplinary collaboration. Computer Science, Biology
Start Year 2010
 
Description Role of chromatin in DNA damage 
Organisation University of Paris-Saclay
Country France 
Sector Academic/University 
PI Contribution Knock out mutants in the DNA damage response pathway brca1, parp1, parp2, lifering. GFP fusions with these line. Discovery of the connection between BRCA1 and RBR. Direct role of RBR in DNA damage and repair
Collaborator Contribution Development of chromatin regulation experimental platform with NGS sequencing. ChIPsec and Hi-sec experiments.
Impact Exchange of materials and experimental protocols. Plan for joined grant applications
Start Year 2018
 
Description Rossana Henriques 
Organisation Catalan Institution for Research and Advanced Studies (ICREA)
Department ICREA Centre for Research in Agricultural Genomics (CRAG)
Country Spain 
Sector Academic/University 
PI Contribution Connect S6K to cell cycle
Collaborator Contribution S6K circadian regulation, providing tagged S6K1 and S6K2 constructs. The post doc on the award, Dr Csaba Papdi visited her lab in the frame of a 3 month short term EMBO fellowship to work on S6K connection to cell cycle and circadian rhythm.
Impact Manuscript in preparation
Start Year 2015
 
Description Scheres 
Organisation Utrecht University
Department Cancer, Stem Cells and Developmental Biology
Country Netherlands 
Sector Academic/University 
PI Contribution Functional characterisation of E2F transcription factors during root growth and development
Collaborator Contribution Methodologies and tools to study root development, collaboration on RBR phospho-mutants
Impact Modulating RBR-E2F levels to increase plant growth
 
Title Landis 
Description Disease similarity measures quantify the distance between disease modules on the interactome. These measures can provide a starting point for in-depth exploration of the diseases at molecular level, and are of particular relevance for orphan diseases. LanDis is a freely available web-based interactive tool that allows domain experts, medical doctors and the larger community to graphically navigate the landscape of human disease similarities. LanDis is designed to explore the similarity landscape of over 28.5 million pairs of heritable diseases, introducing a fully interactive and navigable plot in which diseases are represented as nodes and their pairwise similarity as the links joining them. 
Type Of Technology Webtool/Application 
Year Produced 2016 
Impact The paper presenting this webtool is still under review, so most scientist are not aware of its existence yet. However, I have already presented to conferences and meetings, receiving an extremely good feedback from everyone who tried it, especially clinician scientists. 
URL http://www.paccanarolab.org/landis
 
Title mutation3D 
Description mutation3D is a functional prediction and visualization tool for studying the spatial arrangement of amino acid substitutions on protein models and structures. It is intended to be used to identify clusters of amino acid substitutions arising from somatic cancer mutations across many patients in order to identify functional hotspots and fuel downstream hypotheses. It is also useful for clustering other kinds of mutational data, or simply as a tool to quickly assess relative locations of amino acids in proteins. 
Type Of Technology Webtool/Application 
Year Produced 2016 
Impact It is still too early, the tool was released about a month ago. 
URL http://mutation3d.org/
 
Description Artist in Residence Kerry Lemon 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach Local
Primary Audience Public/other audiences
Results and Impact Stimulating discussions to bridge the gap between science and artistic thinking

Artistic drawing with understanding of plant development
Year(s) Of Engagement Activity 2014,2015,2016,2017
URL http://www.kerrylemon.co.uk/
 
Description Biology Master Class Slough 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Schools
Results and Impact Organise the Biology Master Class at Slough. Purpose: Enthuse pupils in broad areas of biology and current research challenges
Expose pupils to university-level teaching and learning
Provide links between exciting, contemporary science and A-level syllabus
Help pupils to be successful in the A-level exam, university entry and the transition to university.
Talks from academics on big ideas in biology, linked to the A-level syllabus.
Dissertation by the pupils supervised and marked by academics.
Conference at RHUL where pupils present and discuss the best dissertations.
Year(s) Of Engagement Activity 2018
URL http://www.uptoncourtgrammar.org.uk/
 
Description Biology Masterclass 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Schools
Results and Impact A lecture series of 10 was organised covering a broad range of topics complementing A-level biology on current research topics from climate change to sustainable agriculture and health.
Year(s) Of Engagement Activity 2019,2020
URL https://sites.google.com/view/uc-rhul-master-class/home
 
Description Fascination of Plants Day 2017 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach Local
Primary Audience Schools
Results and Impact Organising the Fascination of Plants Day at RHUL, Introduce history, teaching, research on plants at RHUL. Organise 6 activities on 1. creative drawing of plants (Kerry Lemon), 2. Bees, 3. plant molecular biology, 4. seeds, 5. Botanic Garden, 6. herbarium
Year(s) Of Engagement Activity 2017
URL https://www.royalholloway.ac.uk/biologicalsciences/news-and-events/events/fascination-of-plants-day....
 
Description Invited participation in experts' roundtable at the The Bioinformatics Strategy Meeting in London 
Form Of Engagement Activity A formal working group, expert panel or dialogue
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Industry/Business
Results and Impact I participated in an Experts' roundtable together with other academics and members of Industry
Year(s) Of Engagement Activity 2016
 
Description School visit (Upton Court Grammar School) 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Schools
Results and Impact Biology Master Class for A level students, organised 10 talks
Year(s) Of Engagement Activity 2018,2019
URL https://sites.google.com/view/uc-rhul-master-class/home
 
Description School visits 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Schools
Results and Impact increase awareness in plant research

Increased interest, motivation of school kids
Year(s) Of Engagement Activity Pre-2006,2006,2007,2008,2009,2010,2011,2012,2013,2014
 
Description Talk at BenevolentAI, London 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Industry/Business
Results and Impact I gave a seminar presenting my latest results on drug side effects prediction at BenevolentAI
Year(s) Of Engagement Activity 2019
 
Description Talks to the groups of Martin Wilkins and Paul Matthews -- summer 2015 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Other audiences
Results and Impact I presented our recent results in the area of Network Medicine to Prof Martin Wilkins and Prof Paul Matthews and their groups (I gave two separate talks) at the Department of Medicine, Imperial College, Hammersmith Hospital. The talk sparked interesting discussions and it was the beginning of a very interesting collaboration with the lab of Prof Matthews in the area of Multiple Sclerosis.
Year(s) Of Engagement Activity 2015
 
Description talk at Galway -- May 2015 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Other audiences
Results and Impact I presented my work at the School of Mathematics, Statistics and Applied Mathematics at Galway University, Ireland. The talk sparked discussions with other scientists. The feedback I obtained was useful for my current research. The talk was important to advertise my research and to make contacts for future collaborations.
Year(s) Of Engagement Activity 2015