Quantitative and contextual modelling of transcriptional responses to auxin

Lead Research Organisation: University of Leeds
Department Name: Inst of Integrative & Comparative Biolog

Abstract

Auxin is a plant hormone that plays an important role in many, very different aspects of plant growth and development. For example, on one hand auxin regulates the pattern in which leaves emerge from the growing shoot tip, while on the other it mediates environmental responses such as the bending growth observed in shoots growing towards a light source. Because auxin is integral to so much of plant development, a knowledge of how auxin works is absolutely fundamental to our ability both to understand how plants grow and to improve important crop traits. Although it is unclear how auxin, a small and simple molecule, is able to regulate such a diversity of processes, it is known that changes in gene expression are important and that several hundred genes are either turned on or off in response to auxin. Work from several labs has established a network of signalling proteins whose complex interactions translate increases in auxin levels within a cell into gene expression changes. However, this model of auxin signalling is generic and contains several gaps which mean that in most cases it offers only a theoretical basis for understanding how auxin operates throughout the plant. We can identify the new information required to remedy this situation and with this work we intend to use newly available techniques to obtain these data and correct the deficiencies of the current model. The complexity of the interactions in this auxin response system mean that the data that describe it are similarly complex, and therefore we need to adopt a new approach for analysing the information that we will gather in which we build mathematical models that describe the functioning of the system. These models can then be used to test our predictions of how the auxin response system works, generate new hypotheses about its functioning, and ultimately tell us if we have understood its essential details. This higher level of understanding of auxin action will be useful to a number of groups, including plant biologists, crop scientists, and scientists studying similarly complex signalling mechanisms in other organisms.

Technical Summary

We are taking a context-specific and quantitative modelling approach to transcriptional auxin response. We will generate quantitative data sets that will parameterise mathematical models which will then be used to test hypotheses about the functioning of the auxin signalling mechanism. The main methodologies that will be used to achieve the specific objectives of the work are outlined below: Objective 1. Data describing contextual parameters To obtain cell specific information for auxin levels and transcriptional auxin response in the root we will use the combination of protoplasting and fluorescence activated cell sorting (FACS) of cell-specific GFP-marker lines. We will sample epidermal cell types both treated and untreated with the auxin, IAA and perform microarray and quantitative RT-PCR analysis of RNA extracted from these sorted cells. As well as performing the protoplasting/FACS, the Ljung lab will also quantitate IAA levels by GC-MS from samples of the same cells. Objective 2. Data describing interaction parameters We will quantify Aux/IAA-ARF and ARF-DNA interactions using surface plasmon resonance (SPR). His- and GST-tagged Aux/IAAs and ARFs will be expressed by in vitro transcription/translation in wheatgerm extract and the cis regulatory sequences of auxin-regulated genes will be amplified by PCR using a biotinylated primer to facilitate tethering the DNA to the SPR chip. Objective 3. Data describing abundance parameters Auxin-induced Aux/IAA induction will be measured by qRT-PCR and the auxin-induced destabilisation characteristics of the Aux/IAAs will be quantified by analysing Aux/IAA-luciferase fusion proteins. These data will enable us to model Aux/IAA protein abundance. Objective 4. Mathematical modelling Initially, models will be constructed using ordinary differential equations (ODEs) but partial differential equation (PDE)-based approaches will be adopted should?stochastic and/or spatial effects prove significant.

Publications

10 25 50
 
Description Key findings:

- An understanding of how the plant hormone auxin controls the development of structures called root hairs.

- An understanding of how non-vertical growth angles of lateral root and shoot branches are maintained with respect to gravity.

- Tools to manipulate both root hair growth and branch growth angle.

Detailed summary:

Almost every aspect of plant form, from the positioning and number of organs such as lateral roots, branches and flowers to the control of their angle of growth with respect to gravity, is regulated by the plant hormone auxin. For this reason, understanding how this small simple molecule is able to control so many different aspects of development is one of the central questions in plant biology.

The fact that auxin accumulation in, say, particular cells of the root results in the initiation of a new lateral root while similar accumulations of auxin at the shoot tip prompts the initiation of a leaf underlines the importance tissue- or 'context'-specific responses to auxin. In this project we focused on the how the network of proteins that translates changes in auxin concentration into changes in gene expression-the AFB-Aux/IAA-ARF system-contributes to the generation of these context-specific responses and auxin's remarkable influence on development. The fact that this system is composed of many interacting auxin receptor and transcription factor proteins, the abundance of which are in several instances regulated by positive and negative feedback loops between the components, required that we take an approach that involved the extensive the use of mathematical models, enabling us to capture the complexity of the system.

Our models were based on the cells in the outer layer of the arabidopsis root, the epidermis, which is made up of two cell-types, those that usually make long thin projections called root hairs (H cells) and those that don't (NH cells). In obtaining the data to paramterise our models it quickly became apparent that H and NH cells have very different auxin response capacities; NH cells have a highly suppressed auxin response, something consistent with the fact that auxin promotes hair growth. Using gene expression markers we showed that the suppressed auxin response in NH cells was due to the high relative levels of Aux/IAA and ARF repressor protein. Indeed, in mutant arabidopsis plants that lacked some of these negative regulators we observed an increase in root hairs developing at NH positions and an overall increase in root hair lengths.

Using these expression data and information on the binding preferences between system components we built a variety of mathematical models that enabled us to uncover two significant features of the behaviour of the system. The first is that the complex interactions between AFB-Aux/IAA-ARF components mean that graded changes in auxin levels will not always be reflected in graded changes signalling response. Indeed, a gradual change in auxin levels can be translated into a stark off/on switch in signalling output (in this case a bistable switch). This finding has important implcations for the understanding of how cells interpret gradients of auxin concentration which have been proposed to underlie virtually every aspect of auxin-regulated development.

The second key finding was that the AFB-Aux/IAA-ARF system in H cells, as well as 'turning on' auxin responses leading root hair growth, also turns them off, regardless of how much auxin is present. From this finding we went on to identify a novel auxin-regulated transcription factor controlling root hair elongation. This self-regulatory switching behaviour also offers a explanation for the general robustness of auxin-regulated plant development to wide variations in auxin concentration, something observed in a range of processes from embryogenesis to lateral root development.

These findings are significant for a number of reasons; as well as offering important insights into how auxin can simultaneously control so much of plant development, they also provide new opportunities for the targeted optimisation of agronomically important architectural traits such as lateral rooting and root hair growth, both of which are crucial for the acquisition of nutrients and water.

In addition to these insights, tools and resources developed during this project contributed to the understanding of the mechanism that underpins the growth angle of lateral root and shoot branches. Many branches are maintained at non-vertical angles with respect to gravity. These angles are known as gravitropic setpoint angles and we were able to show that gravity-dependent non-vertical growth was the result of a new growth component, the antigravitropic offset or AGO, that acts to counteract the underlying gravitropic response in the branch.
Exploitation Route All of the findings of this work could be used to alter root hair and branch angle traits in crop plants. In addition, some of the conceptual advances made, particularly in the understanding of the self-regulating nature of auxin response and the control of gravitropic set point angle, should be of use to researchers working in this area.
Sectors Agriculture, Food and Drink

URL http://www.bbsrc.ac.uk/news/food-security/2013/130726-pr-secret-of-plant-geometry.aspx
 
Description To date impacts have been principally academic although attempts to commercialise the technologies that have arisen from the work are in progress. This has included the submission of a patent application in December 2013.
First Year Of Impact 2012
Sector Agriculture, Food and Drink
Impact Types Societal,Economic

 
Description Member of the Advisory Committee of the UK Plant Science Federation
Geographic Reach National 
Policy Influence Type Participation in a advisory committee
 
Description BBSRC responsive mode
Amount £576,766 (GBP)
Funding ID BB/N010124/1 
Organisation Biotechnology and Biological Sciences Research Council (BBSRC) 
Sector Public
Country United Kingdom
Start 07/2016 
End 06/2019
 
Description University of Leeds 'Leeds International Research Scholarship"
Amount £81,000 (GBP)
Organisation University of Leeds 
Sector Academic/University
Country United Kingdom
Start 10/2012 
End 09/2015
 
Description Bennett lab collaboration 
Organisation University of Nottingham
Department School of Biomedical Sciences Nottingham
Country United Kingdom 
Sector Academic/University 
PI Contribution We have provided research materials and shared data ahead of publication.
Collaborator Contribution They have provided research materials and shared data ahead of publication.
Impact Brunoud, G., Wells, D.M., Larrieu, A., Oliva, M., Burrow, A., Beeckman, T., Kepinski, S., Traas, J., Bennett, M., Vernoux, T. (2012) A novel sensor to map auxin response and distribution at high spatio-temporal resolution. Nature 482: 103-6 Vernoux, T., Brunoud, G., Farcot, E., Morin, M., Van den Daele, H., Legrand, J., Oliva, M., Das, P., Larrieu, A., Wells, D., Guédon, Y., Armitage, L., Picard, F., Guyomarc'h, S., - Estelle, M., Godin, C., Kepinski, S., Bennett, M.J., De Veyler, L., Traas, J. (2011) The auxin signalling network translates dynamic input into robust patterning at the shoot apex. Molecular Systems Biology. 7:508 [10.1038/msb.2011.39].
Start Year 2010
 
Description Estelle lab collaboration 
Organisation University of California, San Diego (UCSD)
Country United States 
Sector Academic/University 
PI Contribution We have provided research materials and shared data ahead of publication. We performed biochemical/biophysical experiments for the papers listed below.
Collaborator Contribution They have provided research materials and shared data ahead of publication.
Impact alderon Villalobos, L-I., Lee, S., Armitage, L., Parry, G., Mao, H., De Oliveira, C., Ivetac, A., Brandt, W., McCammonn, A., Zheng, N., Napier, R., Kepinski, S., Estelle, M. (2012) TIR1/AFBs and Aux/IAAs constitute a combinatorial co-receptor system to perceive auxin with differential sensitivities. Nature Chemical Biology 8: 477-485
Start Year 2007
 
Description Vernoux lab collaboration 
Organisation École normale supérieure de Lyon (ENS Lyon)
Country France 
Sector Academic/University 
PI Contribution We have provided research materials and shared data ahead of publication. We performed biochemical experiments for the papers listed below.
Collaborator Contribution They have provided research materials and shared data ahead of publication.
Impact Brunoud, G., Wells, D.M., Larrieu, A., Oliva, M., Burrow, A., Beeckman, T., Kepinski, S., Traas, J., Bennett, M., Vernoux, T. (2012) A novel sensor to map auxin response and distribution at high spatio-temporal resolution. Nature 482: 103-6 Vernoux, T., Brunoud, G., Farcot, E., Morin, M., Van den Daele, H., Legrand, J., Oliva, M., Das, P., Larrieu, A., Wells, D., Guédon, Y., Armitage, L., Picard, F., Guyomarc'h, S., - Estelle, M., Godin, C., Kepinski, S., Bennett, M.J., De Veyler, L., Traas, J. (2011) The auxin signalling network translates dynamic input into robust patterning at the shoot apex. Molecular Systems Biology. 7:508 [10.1038/msb.2011.39].
Start Year 2010
 
Description Weijers lab collaboration 
Organisation University of Wageningen
Country Netherlands 
Sector Academic/University 
PI Contribution We have shared research materials and data ahead of publication. We also performed SPR analysis for the paper listed below.
Collaborator Contribution They have shared research materials and data ahead of publication.
Impact Boer, D.R., Freire-Rios, A., van den Berg W.A., Saaki, T., Manfield, I.W., Kepinski, S., López- Vidrieo, I., Franco-Zorrilla, J.M., de Vries, S.C., Solano, R., Weijers, D., Coll, M. (2014) Structural basis for DNA binding specificity by the auxin-dependent ARF transcription factors. Cell 30;156(3):577-89.
Start Year 2010
 
Description Discovery Zone 
Form Of Engagement Activity Participation in an open day or visit at my research institution
Part Of Official Scheme? Yes
Geographic Reach Regional
Primary Audience Schools
Results and Impact The feedback from schools is always positive.

None
Year(s) Of Engagement Activity 2006,2007,2008,2009,2010,2011,2012,2013,2014,2015