ORCID Profile
0000-0003-0467-104X
Current Organisation
The University of Edinburgh
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Publisher: Oxford University Press (OUP)
Date: 04-2008
Abstract: This work investigated the roles of β-amylases in the breakdown of leaf starch. Of the nine β-amylase (BAM)–like proteins encoded in the Arabidopsis thaliana genome, at least four (BAM1, -2, -3, and -4) are chloroplastic. When expressed as recombinant proteins in Escherichia coli, BAM1, BAM2, and BAM3 had measurable β-amylase activity but BAM4 did not. BAM4 has multiple amino acid substitutions relative to characterized β-amylases, including one of the two catalytic residues. Modeling predicts major differences between the glucan binding site of BAM4 and those of active β-amylases. Thus, BAM4 probably lost its catalytic capacity during evolution. Total β-amylase activity was reduced in leaves of bam1 and bam3 mutants but not in bam2 and bam4 mutants. The bam3 mutant had elevated starch levels and lower nighttime maltose levels than the wild type, whereas bam1 did not. However, the bam1 bam3 double mutant had a more severe phenotype than bam3, suggesting functional overlap between the two proteins. Surprisingly, bam4 mutants had elevated starch levels. Introduction of the bam4 mutation into the bam3 and bam1 bam3 backgrounds further elevated the starch levels in both cases. These data suggest that BAM4 facilitates or regulates starch breakdown and operates independently of BAM1 and BAM3. Together, our findings are consistent with the proposal that β-amylase is a major enzyme of starch breakdown in leaves, but they reveal unexpected complexity in terms of the specialization of protein function.
Publisher: The Royal Society
Date: 10-2015
DOI: 10.1098/RSOB.150042
Abstract: 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 tissue. In addition to providing reference data, unexpected behaviours included co-expression of PRR9 and ELF4 , and regulation of PRR5 by GI . Absolute RNA quantification revealed low levels of PRR9 transcripts (peak approx. 50 copies cell −1 ) compared with other clock genes, and threefold higher levels of LHY RNA (more than 1500 copies cell −1 ) than of its close relative CCA1 . The data are disseminated from BioDare, an online repository for focused timeseries data, which is expected to benefit mechanistic modelling. One data subset successfully constrained clock gene expression in a complex model, using publicly available software on parallel computers, without expert tuning or programming. We outline the empirical and mathematical justification for data aggregation in understanding highly interconnected, dynamic networks such as the clock, and the observed design constraints on the resources required to make this approach widely accessible.
Publisher: Proceedings of the National Academy of Sciences
Date: 02-09-2014
Abstract: Plants respond to environmental change by triggering biochemical and developmental networks across multiple scales. Multiscale models that link genetic input to the whole-plant scale and beyond might therefore improve biological understanding and yield prediction. We report a modular approach to build such models, validated by a framework model of Arabidopsis thaliana comprising four existing mathematical models. Our model brings together gene dynamics, carbon partitioning, organ growth, shoot architecture, and development in response to environmental signals. It predicted the biomass of each leaf in independent data, demonstrated flexible control of photosynthesis across photoperiods, and predicted the pleiotropic phenotype of a developmentally misregulated transgenic line. Systems biology, crop science, and ecology might thus be linked productively in a community-based approach to modeling.
Publisher: Proceedings of the National Academy of Sciences
Date: 22-04-2015
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Karen Halliday.