A systems study of nutrient uptake in plants

The case for improving Phosphorus-Use Efficiency in crops is widely recognised. Although much is known about the underlying molecular and regulatory mechanisms, improvements have been hampered by the extreme complexity of phosphorus (P) dynamics in soil and plants (across all physical scales), including its soil chemistry and uptake, distribution and deficiency responses in plants. The urgency and direction of phosphate research is also being driven by the availability of finite P stocks to farmers and reducing environmental hazards. Thus, systems approaches become essential to identify the most potent (combinations of) target genes for improving phosphate uptake and utilisation in crops. This study has applied these approaches with the aim of increasing understanding of the regulation of phosphate uptake at three separate spatial scales, primarily in rice, but also in Arabidopsis. The first and major part of this study has focused on the cell scale, wherein novel mathematical models for molecular regulation of phosphate acquisition have been developed. Owing to the sparsity of the data, advanced techniques for parameter fitting were employed, which resulted in an original model, which accurately reflected the profiles of all the genes apart from PHO2. It was clear that miR399-mediated degradation was insufficient to explain the apparent early reduction in PHO2 mRNA levels. Five hypotheses were explored mathematically, of which the most plausible is that there is a phosphate-sensitive transcriptional repressor (PsTR) of PHO2 mRNA synthesis. To support this hypothesis, mRNA was extracted from phosphate-starved and untreated roots over a short, 12-hour time course. Quantitative Polymerase Chain Reactions (qPCR) of PHO2 mRNA both confirmed the early decline predicted by the hypothesis and also revealed a temporary restoration of mRNA levels, which points to PHO2 (a type-2 ubiquitin ligase) regulating its own transcript levels. Sensitivity analysis of these models indicates that the utilisation rate of cytosolic phosphate is the biggest influence on this system. Output from simulations with the original and PsTR models qualitatively reproduced the phenotypes of various published phosphate-research papers, with the exception of RNASEQ data in which phosphate-starved rice roots were resupplied with phosphate. In this instance, the observed rapid drop in mRNA levels for PHO2 and IPS1 were incorrectly predicted, pointing to one or more other regulatory mechanisms not represented in these models.The IPS1 gene encodes a long non-coding RNA that has a poly-A tail.Its RNA also binds to miR399 and accumulates to extremely high levels in plant roots during phosphate stress. A sudden loss of IPS1 would release the bound miR399 causing the observed rapid loss of PHO2 mRNA. The observed IPS1 profile can be explained by either the gene having a “super-promotor” that is capable of extremely high RNA synthesis under low phosphate conditions, or the transcript being protected from degradation by phosphate-sensitive RNA-binding proteins. Informatics analyses favour the latter and a revised model incorporating RNA protection was found to have parameters for IPS1 synthesis that are similar to those normally used in modelling gene regulation. The analyses also point to PUMILIO proteins playing this role. The second part of this work has explored the role of tissue geometry in determining root phosphate levels and flux. Multi-cellular vertex-based models of published Arabidopsis and rice root cross-sections were produced using CellSeT, into which equations for phosphate uptake, flux and utilistion were embedded using OpenAlea. Simulations suggest that Arabidopsis trichoblasts have lower cytosolic phosphate levels than neighbouring epidermal cells, because they have a larger area through which phosphate flows into the inner tissues. This implies that trichoblasts are more sensitive to phosphate stress and reduced phosphate levels could therefore be part of the trigger for initiating root-hair growth. Adding root hairs of varying lengths into this geometry shows that a hair does not have to grow much before the phosphate levels in this trichoblast exceeds those in the neighbouring cells and that phosphate flows to them. This potentially suppresses root-hair formation in nearby trichoblasts. The rice simulations show that aerenchyma dramatically reduces cytosolic phosphate in surrounding cells and point to a role for lacunae in rapid uptake of phosphate, without the need for large water fluxes. Alongside aerenchyma, a higher proportion of fluid-filled lacunae could be a desirable trait for improving nutrient-uptake efficiency. At the whole-plant scale for the third part of this work, a time-course dataset has been generated to record the effect of phosphate starvation over 21 days on the uptake dynamics of eleven other macro- and micro-nutrients. This dataset will be of use in future systems studies of nutrient uptake and interactions

A transcriptomic comparison of two Bambara groundnut landraces under dehydration stress

The ability to grow crops under low-water conditions is a significant advantage in relation to global food security. Bambara groundnut is an underutilised crop grown by subsistence farmers in Africa and is known to survive in regions of water deficit. This study focuses on the analysis of the transcriptomic changes in two bambara groundnut landraces in response to dehydration stress. A cross-species hybridisation approach based on the Soybean Affymetrix GeneChip array has been employed. The differential gene expression analysis of a water-limited treatment, however, showed that the two landraces responded with almost completely different sets of genes. Hence, both landraces with very similar genotypes (as assessed by the hybridisation of genomic DNA onto the Soybean Affymetrix GeneChip) showed contrasting transcriptional behaviour in response to dehydration stress. In addition, both genotypes showed a high expression of dehydration-associated genes, even under water-sufficient conditions. Several gene regulators were identified as potentially important. Some are already known, such as WRKY40, but others may also be considered, namely PRR7, ATAUX2-11, CONSTANS-like 1, MYB60, AGL-83, and a Zinc-finger protein. These data provide a basis for drought trait research in the bambara groundnut, which will facilitate functional genomics studies. An analysis of this dataset has identified that both genotypes appear to be in a dehydration-ready state, even in the absence of dehydration stress, and may have adapted in different ways to achieve drought resistance. This will help in understanding the mechanisms underlying the ability of crops to produce viable yields under drought conditions. In addition, cross-species hybridisation to the soybean microarray has been shown to be informative for investigating the bambara groundnut transcriptome

Integrated root phenotypes for improved rice performance under low nitrogen availability

Greater nitrogen efficiency would substantially reduce the economic, energy and environmental costs of rice production. We hypothesized that synergistic balancing of the costs and benefits for soil exploration among root architectural phenes is beneficial under suboptimal nitrogen availability. An enhanced implementation of the functional-structural model OpenSimRoot for rice integrated with the ORYZA_v3 crop model was used to evaluate the utility of combinations of root architectural phenes, namely nodal root angle, the proportion of smaller diameter nodal roots, nodal root number; and L-type and S-type lateral branching densities, for plant growth under low nitrogen. Multiple integrated root phenotypes were identified with greater shoot biomass under low nitrogen than the reference cultivar IR64. The superiority of these phenotypes was due to synergism among root phenes rather than the expected additive effects of phene states. Representative optimal phenotypes were predicted to have up to 80% greater grain yield with low N supply in the rainfed dry direct-seeded agroecosystem over future weather conditions, compared to IR64. These phenotypes merit consideration as root ideotypes for breeding rice cultivars with improved yield under rainfed dry direct-seeded conditions with limited nitrogen availability. The importance of phene synergism for the performance of integrated phenotypes has implications for crop breeding.Peer reviewe

BioModels: ten-year anniversary

BioModels (http://www.ebi.ac.uk/biomodels/) is a repository of mathematical models of biological processes. A large set of models is curated to verify both correspondence to the biological process that the model seeks to represent, and reproducibility of the simulation results as described in the corresponding peer-reviewed publication. Many models submitted to the database are annotated, cross-referencing its components to external resources such as database records, and terms from controlled vocabularies and ontologies. BioModels comprises two main branches: one is composed of models derived from literature, while the second is generated through automated processes. BioModels currently hosts over 1200 models derived directly from the literature, as well as in excess of 140 000 models automatically generated from pathway resources. This represents an approximate 60-fold growth for literature-based model numbers alone, since BioModels’ first release a decade ago. This article describes updates to the resource over this period, which include changes to the user interface, the annotation profiles of models in the curation pipeline, major infrastructure changes, ability to perform online simulations and the availability of model content in Linked Data form. We also outline planned improvements to cope with a diverse array of new challenges

Multiseriate cortical sclerenchyma enhance root penetration in compacted soils

Mechanical impedance limits soil exploration and resource capture by plant roots. We examine the role of root anatomy in regulating plant adaptation to mechanical impedance and identify a root anatomical phene in maize (Zea mays) and wheat (Triticum aestivum) associated with penetration of hard soil: multiseriate cortical sclerenchyma (MCS). We characterize this trait and evaluate the utility of MCS for root penetration in compacted soils. Roots with MCS had a greater cell wall to lumen ratio and a distinct UV emission spectrum in outer cortical cells. Genome-wide association mapping revealed that MCS is heritable and genetically controlled. We identified a candidate gene associated with MCS. Across all root classes and nodal positions, maize genotypes with MCS had 13% greater root lignin concentration compared to genotypes without MCS. Genotypes without MCS formed MCS upon exogenous ethylene exposure. Genotypes with MCS had greater lignin concentration and bending strength at the root tip. In controlled environments, MCS in maize and wheat was associated improved root tensile strength and increased penetration ability in compacted soils. Maize genotypes with MCS had root systems with 22% greater depth and 39% greater shoot biomass in compacted soils in the field compared to lines without MCS. Of the lines we assessed, MCS was present in 30-50% of modern maize, wheat, and barley cultivars but was absent in teosinte and wild and landrace accessions of wheat and barley. MCS merits investigation as a trait for improving plant performance in maize, wheat, and other grasses under edaphic stress

An integrative systems perspective on plant phosphate research

The case for improving crop phosphorus-use-efficiency is widely recognized. Although much is known about the molecular and regulatory mechanisms, improvements have been hampered by the extreme complexity of phosphorus (P) dynamics, which involves soil chemistry; plant-soil interactions; uptake, transport, utilization and remobilization within plants; and agricultural practices. The urgency and direction of phosphate research is also dependent upon the finite sources of P, availability of stocks to farmers and reducing environmental hazards. This work introduces integrative systems approaches as a way to represent and understand this complexity, so that meaningful links can be established between genotype, environment, crop traits and yield. It aims to provide a large set of pointers to potential genes and research practice, with a view to encouraging members of the plant-phosphate research community to adopt such approaches so that, together, we can aid efforts in global food security

Reconstructing promoter activity from Lux bioluminescent reporters

The bacterial Lux system is used as a gene expression reporter. It is fast, sensitive and non-destructive, enabling high frequency measurements. Originally developed for bacterial cells, it has also been adapted for eukaryotic cells, and can be used for whole cell biosensors, or in real time with live animals without the need for euthanasia. However, correct interpretation of bioluminescent data is limited: the bioluminescence is different from gene expression because of nonlinear molecular and enzyme dynamics of the Lux system. We have developed a computational approach that, for the first time, allows users of Lux assays to infer gene transcription levels from the light output. This approach is based upon a new mathematical model for Lux activity, that includes the actions of LuxAB, LuxEC and Fre, with improved mechanisms for all reactions, as well as synthesis and turn-over of Lux proteins. The model is calibrated with new experimental data for the LuxAB and Fre reactions from Photorhabdus luminescens --- the source of modern Lux reporters --- while literature data has been used for LuxEC. Importantly, the data show clear evidence for previously unreported product inhibition for the LuxAB reaction. Model simulations show that predicted bioluminescent profiles can be very different from changes in gene expression, with transient peaks of light output, very similar to light output seen in some experimental data sets. By incorporating the calibrated model into a Bayesian inference scheme, we can reverse engineer promoter activity from the bioluminescence. We show examples where a decrease in bioluminescence would be better interpreted as a switching off of the promoter, or where an increase in bioluminescence would be better interpreted as a longer period of gene expression. This approach could benefit all users of Lux technology

A systems study of nutrient uptake in plants

The case for improving Phosphorus-Use Efficiency in crops is widely recognised. Although much is known about the underlying molecular and regulatory mechanisms, improvements have been hampered by the extreme complexity of phosphorus (P) dynamics in soil and plants (across all physical scales), including its soil chemistry and uptake, distribution and deficiency responses in plants. The urgency and direction of phosphate research is also being driven by the availability of finite P stocks to farmers and reducing environmental hazards. Thus, systems approaches become essential to identify the most potent (combinations of) target genes for improving phosphate uptake and utilisation in crops. This study has applied these approaches with the aim of increasing understanding of the regulation of phosphate uptake at three separate spatial scales, primarily in rice, but also in Arabidopsis. The first and major part of this study has focused on the cell scale, wherein novel mathematical models for molecular regulation of phosphate acquisition have been developed. Owing to the sparsity of the data, advanced techniques for parameter fitting were employed, which resulted in an original model, which accurately reflected the profiles of all the genes apart from PHO2. It was clear that miR399-mediated degradation was insufficient to explain the apparent early reduction in PHO2 mRNA levels. Five hypotheses were explored mathematically, of which the most plausible is that there is a phosphate-sensitive transcriptional repressor (PsTR) of PHO2 mRNA synthesis. To support this hypothesis, mRNA was extracted from phosphate-starved and untreated roots over a short, 12-hour time course. Quantitative Polymerase Chain Reactions (qPCR) of PHO2 mRNA both confirmed the early decline predicted by the hypothesis and also revealed a temporary restoration of mRNA levels, which points to PHO2 (a type-2 ubiquitin ligase) regulating its own transcript levels. Sensitivity analysis of these models indicates that the utilisation rate of cytosolic phosphate is the biggest influence on this system. Output from simulations with the original and PsTR models qualitatively reproduced the phenotypes of various published phosphate-research papers, with the exception of RNASEQ data in which phosphate-starved rice roots were resupplied with phosphate. In this instance, the observed rapid drop in mRNA levels for PHO2 and IPS1 were incorrectly predicted, pointing to one or more other regulatory mechanisms not represented in these models.The IPS1 gene encodes a long non-coding RNA that has a poly-A tail.Its RNA also binds to miR399 and accumulates to extremely high levels in plant roots during phosphate stress. A sudden loss of IPS1 would release the bound miR399 causing the observed rapid loss of PHO2 mRNA. The observed IPS1 profile can be explained by either the gene having a “super-promotor” that is capable of extremely high RNA synthesis under low phosphate conditions, or the transcript being protected from degradation by phosphate-sensitive RNA-binding proteins. Informatics analyses favour the latter and a revised model incorporating RNA protection was found to have parameters for IPS1 synthesis that are similar to those normally used in modelling gene regulation. The analyses also point to PUMILIO proteins playing this role. The second part of this work has explored the role of tissue geometry in determining root phosphate levels and flux. Multi-cellular vertex-based models of published Arabidopsis and rice root cross-sections were produced using CellSeT, into which equations for phosphate uptake, flux and utilistion were embedded using OpenAlea. Simulations suggest that Arabidopsis trichoblasts have lower cytosolic phosphate levels than neighbouring epidermal cells, because they have a larger area through which phosphate flows into the inner tissues. This implies that trichoblasts are more sensitive to phosphate stress and reduced phosphate levels could therefore be part of the trigger for initiating root-hair growth. Adding root hairs of varying lengths into this geometry shows that a hair does not have to grow much before the phosphate levels in this trichoblast exceeds those in the neighbouring cells and that phosphate flows to them. This potentially suppresses root-hair formation in nearby trichoblasts. The rice simulations show that aerenchyma dramatically reduces cytosolic phosphate in surrounding cells and point to a role for lacunae in rapid uptake of phosphate, without the need for large water fluxes. Alongside aerenchyma, a higher proportion of fluid-filled lacunae could be a desirable trait for improving nutrient-uptake efficiency. At the whole-plant scale for the third part of this work, a time-course dataset has been generated to record the effect of phosphate starvation over 21 days on the uptake dynamics of eleven other macro- and micro-nutrients. This dataset will be of use in future systems studies of nutrient uptake and interactions

Figure 5

Observed and predicted profiles of PHO2 and IPS1 under Pi-depletion and repletion conditions. Panels A and B correspond to PHO2, and C and D to IPS1. Panels A and C show predicted profiles of PiOM and PsTR models, while panels B and D depict models incorporating RNA-protection. The blue dashed lines show the fold change in RNA-SEQ values from [20]. The red and black lines denote PsTR and PiOM models, respectively. The grey zones denote the period of Pi-resupply

Figure 4

<p>Fitting of different hypothesis models to PHO2 data. Panel A represents the fits of PiOM model. Panel B-F depicts the fit offered by individual hypothesis, labelled in the respective panel. Red dashed lines represent the 80% prediction interval of the respective hypothesis model. These simulations have been carried out by sampling parameter values from normal (Gaussian) distributions with means and standard deviations given from the parameter fitting in Monolix. Circle represents the qRT-PCR data. Square and triangles denotes fold change mRNA-seq data, respectively.</p