The Organization of Controller Motifs Leading to Robust Plant Iron Homeostasis

Structural identifiability of biomolecular controller motifs with and without flow measurements as model output

Controller motifs are simple biomolecular reaction networks with negative feedback. They can explain how regulatory function is achieved and are often used as building blocks in mathematical models of biological systems. In this paper we perform an extensive investigation into structural identifiability of controller motifs, specifically the so-called basic and antithetic controller motifs. Structural identifiability analysis is a useful tool in the creation and evaluation of mathematical models: it can be used to ensure that model parameters can be determined uniquely and to examine which measurements are necessary for this purpose. This is especially useful for biological models where parameter estimation can be difficult due to limited availability of measureable outputs. Our aim with this work is to investigate how structural identifiability is affected by controller motif complexity and choice of measurements. To increase the number of potential outputs we propose two methods for including flow measurements and show how this affects structural identifiability in combination with, or in the absence of, concentration measurements. In our investigation, we analyze 128 different controller motif structures using a combination of flow and/or concentration measurements, giving a total of 3648 instances. Among all instances, 34% of the measurement combinations provided structural identifiability. Our main findings for the controller motifs include: i) a single measurement is insufficient for structural identifiability, ii) measurements related to different chemical species are necessary for structural identifiability. Applying these findings result in a reduced subset of 1568 instances, where 80% are structurally identifiable, and more complex/interconnected motifs appear easier to structurally identify. The model structures we have investigated are commonly used in models of biological systems, and our results demonstrate how different model structures and measurement combinations affect structural identifiability of controller motifs.

Structures and coordination chemistry of transporters involved in manganese and iron homeostasis

A repertoire of transporters plays a crucial role in maintaining homeostasis of biologically essential transition metals, manganese, and iron, thus ensuring cell viability. Elucidating the structure and function of many of these transporters has provided substantial understanding into how these proteins help maintain the optimal cellular concentrations of these metals. In particular, recent high-resolution structures of several transporters bound to different metals enable an examination of how the coordination chemistry of metal ion-protein complexes can help us understand metal selectivity and specificity. In this review, we first provide a comprehensive list of both specific and broad-based transporters that contribute to cellular homeostasis of manganese (Mn2+) and iron (Fe2+ and Fe3+) in bacteria, plants, fungi, and animals. Furthermore, we explore the metal-binding sites of the available high-resolution metal-bound transporter structures (Nramps, ABC transporters, P-type ATPase) and provide a detailed analysis of their coordination spheres (ligands, bond lengths, bond angles, and overall geometry and coordination number). Combining this information with the measured binding affinity of the transporters towards different metals sheds light into the molecular basis of substrate selectivity and transport. Moreover, comparison of the transporters with some metal scavenging and storage proteins, which bind metal with high affinity, reveal how the coordination geometry and affinity trends reflect the biological role of individual proteins involved in the homeostasis of these essential transition metals.

ERF subfamily transcription factors and their function in plant responses to abiotic stresses

Ethylene Responsive Factor (ERF) subfamily comprise the largest number of proteins in the plant AP2/ERF superfamily, and have been most extensively studied on the biological functions. Members of this subfamily have been proven to regulate plant resistances to various abiotic stresses, such as drought, salinity, chilling and some other adversities. Under these stresses, ERFs are usually activated by mitogen-activated protein kinase induced phosphorylation or escape from ubiquitin-ligase enzymes, and then form complex with nucleic proteins before binding to cis-element in promoter regions of stress responsive genes. In this review, we will discuss the phylogenetic relationships among the ERF subfamily proteins, summarize molecular mechanism how the transcriptional activity of ERFs been regulated and how ERFs of different subgroup regulate the transcription of stress responsive genes, such as high-affinity K⁺ transporter gene PalHKT1;2, reactive oxygen species related genes LcLTP, LcPrx, and LcRP, flavonoids synthesis related genes FtF3H and LhMYBSPLATTER, etc. Though increasing researches demonstrate that ERFs are involved in various abiotic stresses, very few interact proteins and target genes of them have been comprehensively annotated. Hence, future research prospects are described on the mechanisms of how stress signals been transited to ERFs and how ERFs regulate the transcriptional expression of stress responsive genes.

Computational solutions for modeling and controlling plant response to abiotic stresses: a review with focus on iron deficiency

Computational solutions enable plant scientists to model protein-mediated stress responses and characterize novel gene functions that coordinate responses to a variety of abiotic stress conditions. Recently, density functional theory was used to study proteins active sites and elucidate enzyme conversion mechanisms involved in iron deficiency responsive signaling pathways. Computational approaches for protein homology modeling and the kinetic modeling of signaling pathways have also resolved the identity and function in proteins involved in iron deficiency signaling pathways. Significant changes in gene relationships under other stress conditions, such as heat or drought stress, have been recently identified using differential network analysis, suggesting that stress tolerance is achieved through asynchronous control. Moreover, the increasing development and use of statistical modeling and systematic modeling of transcriptomic data have provided significant insight into the gene regulatory mechanisms associated with abiotic stress responses. These types of in silico approaches have facilitated the plant science community's future goals of developing multi-scale models of responses to iron deficiency stress and other abiotic stress conditions.

Adaptive information processing of network modules to dynamic and spatial stimuli

BACKGROUND

Adaptation and homeostasis are basic features of information processing in cells and seen in a broad range of contexts. Much of the current understanding of adaptation in network modules/motifs is based on their response to simple stimuli. Recently, there have also been studies of adaptation in dynamic stimuli. However a broader synthesis of how different circuits of adaptation function, and which circuits enable a broader adaptive behaviour in classes of more complex and spatial stimuli is largely missing.

RESULTS

We study the response of a variety of adaptive circuits to time-varying stimuli such as ramps, periodic stimuli and static and dynamic spatial stimuli. We find that a variety of responses can be seen in ramp stimuli, making this a basis for discriminating between even similar circuits. We also find that a number of circuits adapt exactly to ramp stimuli, and dissect these circuits to pinpoint what characteristics (architecture, feedback, biochemical aspects, information processing ingredients) allow for this. These circuits include incoherent feedforward motifs, inflow-outflow motifs and transcritical circuits. We find that changes in location in such circuits where a signal acts can result in non-adaptive behaviour in ramps, even though the location was associated with exact adaptation in step stimuli. We also demonstrate that certain augmentations of basic inflow-outflow motifs can alter the behaviour of the circuit from exact adaptation to non-adaptive behaviour. When subject to periodic stimuli, some circuits (inflow-outflow motifs and transcritical circuits) are able to maintain an average output independent of the characteristics of the input. We build on this to examine the response of adaptive circuits to static and dynamic spatial stimuli. We demonstrate how certain circuits can exhibit a graded response in spatial static stimuli with an exact maintenance of the spatial mean-value. Distinct features which emerge from the consideration of dynamic spatial stimuli are also discussed. Finally, we also build on these results to show how different circuits which show any combination of presence or absence of exact adaptation in ramps, exact mainenance of time average output in periodic stimuli and exact maintenance of spatial average of output in static spatial stimuli may be realized.

CONCLUSIONS

By studying a range of network circuits/motifs on one hand and a range of stimuli on the other, we isolate characteristics of these circuits (structural) which enable different degrees of exact adaptive and homeostatic behaviour in such stimuli, how they may be combined, and also identify cases associated with non-homeostatic behaviour. We also reveal constraints associated with locations where signals may act to enable homeostatic behaviour and constraints associated with augmentations of circuits. This consideration of multiple experimentally/naturally relevant stimuli along with circuits of adaptation of relevance in natural and engineered biology, provides a platform for deepening our understanding of adaptive and homeostatic behaviour in natural systems, bridging the gap between models of adaptation and experiments and in engineering homeostatic synthetic circuits.

Cloning and characterization of novel cyclotides genes from South American plants

Cyclotides are multifunctional plant cyclic peptides containing 28-37 amino acid residues and a pattern of three disulfide bridges, forming a motif known as the cyclic cystine knot. Due to their high biotechnological potential, the sequencing and characterization of cyclotide genes are crucial not only for cloning and establishing heterologous expression strategies, but also to understand local plant evolution in the context of host-pathogen relationships. Here, two species from the Brazilian Cerrado, Palicourea rigida (Rubiaceae) and Pombalia lanata (A.St.-Hil.) Paula-Souza (Violaceae), were used for cloning and characterizing novel cyclotide genes. Using 3' and 5' RACE PCR and sequencing, two full cDNAs, named parigidin-br2 (P. rigida) and hyla-br1 (P. lanata), were isolated and shown to have similar genetic structures to other cyclotides. Both contained the conserved ER-signal domain, N-terminal prodomain, mature cyclotide domain and a C-terminal region. Genomic sequencing of parigidin-br2 revealed two different gene copies: one intronless allele and one presenting a rare 131-bp intron. In contrast, genomic sequencing of hyla-br1 revealed an intronless gene-a common characteristic of members of the Violaceae family. Parigidin-br2 5' and 3' UTRs showed the presence of 12 putative candidate sites for binding of regulatory proteins, suggesting that the flanking and intronic regions of the parigidin-br2 gene must play important roles in transcriptional rates and in the regulation of temporal and spatial gene expression. The high degree of genetic similarity and structural organization among the cyclotide genes isolated in the present study from the Brazilian Cerrado and other well-characterized plant cyclotides may contribute to a better understanding of cyclotide evolution.