Recent News and Publications
A novel sensor to map auxin response and distribution at high spatio-temporal resolution
Brunoud, G, Wells DM, Oliva M, Larrieu Mirabet V, Burrow AH, BeeckmanT, Kepinski S, Traas J, Bennett MJ, Vernoux T (2012)
Nature doi:10.1038/nature10791
Auxin is a key plant morphogenetic signal1 but tools to analyse dynamically its distribution and signalling during development are still limited. Auxin perception directly triggers the degradation of Aux/IAA repressor proteins. Here we describe a novel Aux/IAA-based auxin signalling sensor termed DII-VENUS that was engineered in the model plant Arabidopsis thaliana. The VENUS fast maturing form of yellow fluorescent protein7 was fused in-frame to the Aux/IAA auxin-interaction domain (termed domain II; DII)5 and expressed under a constitutive promoter. We initially show that DII-VENUS abundance is dependent on auxin, its TIR1/AFBs co-receptors and proteasome activities. Next, we demonstrate that DII-VENUS provides a map of relative auxin distribution at cellular resolution in different tissues. DII-VENUS is also rapidly degraded in response to auxin and we used it to visualize dynamic changes in cellular auxin distribution successfully during two developmental responses, the root gravitropic response and lateral organ production at the shoot apex. Our results illustrate the value of developing response input sensors such as DII-VENUS to provide high-resolution spatio-temporal information about hormone distribution and response during plant growth and development.
Homeostatic response to hypoxia is regulated by the N-end rule pathway in plants
Daniel J. Gibbs (a), Seung Cho Lee (b), Nurulhikma Md Isa (a), Silvia Gramuglia (a), Takeshi Fukao (b), George W. Bassel (a), Cristina Sousa Correia (a), Françoise Corbineau (c), Frederica L. Theodoulou (d), Julia Bailey-Serres (b) and Michael J. Holdsworth (a)
a. Division of Plant and Crop Sciences, School of Biosciences and Centre for Plant Integrative Biology, University of Nottingham, Loughborough LE12 5RD, UK
b. Center for Plant Cell Biology and Department of Botany and Plant Sciences, University of California, Riverside, California 92521, USA
c. UPMC Univ Paris 06, UR5-EAC 7180 CNRS, Boîte courrier 156, 4 place Jussieu, F-75005 Paris, France
d. Biological Chemistry Department, Rothamsted Research, Harpenden AL5 2JQ, UK
Nature (2011) doi:10.1038/nature10534. Received 13 June 2011 Accepted 05 September 2011 Published online 23 October 2011
Abstract
Plants and animals are obligate aerobes, requiring oxygen for mitochondrial respiration and energy production. In plants, an unanticipated decline in oxygen availability (hypoxia), as caused by roots becoming waterlogged or foliage submergence, triggers changes in gene transcription and messenger RNA translation that promote anaerobic metabolism and thus sustain substrate-level ATP production. In contrast to animals, oxygen sensing has not been ascribed to a mechanism of gene regulation in response to oxygen deprivation in plants. Here we show that the N-end rule pathway of targeted proteolysis acts as a homeostatic sensor of severe low oxygen levels in Arabidopsis, through its regulation of key hypoxia-response transcription factors. We found that plants lacking components of the N-end rule pathway constitutively express core hypoxia-response genes and are more tolerant of hypoxic stress. We identify the hypoxia-associated ethylene response factor group VII transcription factors of Arabidopsis as substrates of this pathway. Regulation of these proteins by the N-end rule pathway occurs through a characteristic conserved motif at the amino terminus initiating with Met-Cys. Enhanced stability of one of these proteins, HRE2, under low oxygen conditions improves hypoxia survival and reveals a molecular mechanism for oxygen sensing in plants via the evolutionarily conserved N-end rule pathway. SUB1A-1, a major determinant of submergence tolerance in rice, was shown not to be a substrate for the N-end rule pathway despite containing the N-terminal motif, indicating that it is uncoupled from N-end rule pathway regulation, and that enhanced stability may relate to the superior tolerance of Sub1 rice varieties to multiple abiotic stresses.
Bassel GW (a,b) Glaab E (c) Marquez J (a) Holdsworth MJ (a,b) Bacarditd J (e)
a Division of Plant and Crop Sciences, University of Nottingham;
b Centre for Plant Integrative Biology, University of Nottingham;
c School of Computer Science, University of Nottingham;
d ASAP Research Group, School of Computer Science;
e Multidisciplinary Centre for Integrative Biology, School of Biosciences, University of Nottingham.
(2011) Functional network construction in Arabidopsis using rule-based machine learning on large-scale data sets. Plant Cell. tpc.111.088153; First Published on September 6, 2011; doi:10.1105/tpc.111.088153
Abstract
The meta-analysis of large-scale postgenomics data sets within public databases promises to provide important novel biological knowledge. Statistical approaches including correlation analyses in coexpression studies of gene expression have emerged as tools to elucidate gene function using these data sets. Here, we present a powerful and novel alternative methodology to computationally identify functional relationships between genes from microarray data sets using rule-based machine learning. This approach, termed “coprediction,” is based on the collective ability of groups of genes co-occurring within rules to accurately predict the developmental outcome of a biological system. We demonstrate the utility of coprediction as a powerful analytical tool using publicly available microarray data generated exclusively from Arabidopsis thaliana seeds to compute a functional gene interaction network, termed Seed Co-Prediction Network (SCoPNet). SCoPNet predicts functional associations between genes acting in the same developmental and signal transduction pathways irrespective of the similarity in their respective gene expression patterns. Using SCoPNet, we identified four novel regulators of seed germination (ALTERED SEED GERMINATION5, 6, 7, and 8), and predicted interactions at the level of transcript abundance between these novel and previously described factors influencing Arabidopsis seed germination. An online Web tool to query SCoPNet has been developed as a community resource to dissect seed biology and is available at http://www.vseed.nottingham.ac.uk/.
Recently Published books
Mike Davey and Paul Anthony (2010) Plant Cell Culture - Essential Methods.
Wiley-Blackwell. ISBN 978-0-470-68648-5. See Publisher
Kevin Pyke (2009) Plastid Biology. Cambridge University Press ISBN-13: 9780521711975. See Publisher