Plant interactions with microbes and insects: from molecular mechanisms to ecology

Plants are members of complex communities and interact both with antagonists and beneficial organisms. An important question in plant defense-signaling research is how plants integrate signals induced by pathogens, beneficial microbes and insects into the most appropriate adaptive response. Molecular and genomic tools are now being used to uncover the complexity of the induced defense signaling networks that have evolved during the arms races between plants and their attackers. Molecular biologists and ecologists are joining forces to place molecular mechanisms of plant defense into an ecological perspective. Here, we review our current understanding of the molecular mechanisms of induced plant defense and their potential ecological relevance in nature.     

A Computational Framework for 3D Mechanical Modeling of Plant Morphogenesis with Cellular Resolution

The link between genetic regulation and the definition of form and size during morphogenesis remains largely an open question in both plant and animal biology. This is partially due to the complexity of the process, involving extensive molecular networks, multiple feedbacks between different scales of organization and physical forces operating at multiple levels. Here we present a conceptual and modeling framework aimed at generating an integrated understanding of morphogenesis in plants. This framework is based on the biophysical properties of plant cells, which are under high internal turgor pressure, and are prevented from bursting because of the presence of a rigid cell wall. To control cell growth, the underlying molecular networks must interfere locally with the elastic and/or plastic extensibility of this cell wall. We present a model in the form of a three dimensional (3D) virtual tissue, where growth depends on the local modulation of wall mechanical properties and turgor pressure. The model shows how forces generated by turgor-pressure can act both cell autonomously and non-cell autonomously to drive growth in different directions. We use simulations to explore lateral organ formation at the shoot apical meristem. Although different scenarios lead to similar shape changes, they are not equivalent and lead to different, testable predictions regarding the mechanical and geometrical properties of the growing lateral organs. Using flower development as an example, we further show how a limited number of gene activities can explain the complex shape changes that accompany organ outgrowth.     

Plant multiscale networks: charting plant connectivity by multi-level analysis and imaging techniques

In multicellular and even single-celled organisms, individual components are interconnected at multiscale levels to produce enormously complex biological networks that help these systems maintain homeostasis for development and environmental adaptation. Systems biology studies initially adopted network analysis to explore how relationships between individual components give rise to complex biological processes. Network analysis has been applied to dissect the complex connectivity of mammalian brains across different scales in time and space in The Human Brain Project. In plant science, network analysis has similarly been applied to study the connectivity of plant components at the molecular, subcellular, cellular, organic, and organism levels. Analysis of these multiscale networks contributes to our understanding of how genotype determines phenotype. In this review, we summarized the theoretical framework of plant multiscale networks and introduced studies investigating plant networks by various experimental and computational modalities. We next discussed the currently available analytic methodologies and multi-level imaging techniques used to map multiscale networks in plants. Finally, we highlighted some of the technical challenges and key questions remaining to be addressed in this emerging field.     

Mobility of Molecular Motors Regulates Contractile Behaviors of Actin Networks

Cells generate mechanical forces primarily from interactions between F-actin, cross-linking proteins, myosin motors, and other actin-binding proteins in the cytoskeleton. To understand how molecular interactions between the cytoskeletal elements generate forces, a number of in vitro experiments have been performed but are limited in their ability to accurately reproduce the diversity of motor mobility. In myosin motility assays, myosin heads are fixed on a surface and glide F-actin. By contrast, in reconstituted gels, the motion of both myosin and F-actin is unrestricted. Because only these two extreme conditions have been used, the importance of mobility of motors for network behaviors has remained unclear. In this study, to illuminate the impacts of motor mobility on the contractile behaviors of the actin cytoskeleton, we employed an agent-based computational model based on Brownian dynamics. We find that if motors can bind to only one F-actin like myosin I, networks are most contractile at intermediate mobility. In this case, less motor mobility helps motors stably pull F-actins to generate tensile forces, whereas higher motor mobility allows F-actins to aggregate into larger clustering structures. The optimal intermediate motor mobility depends on the stall force and affinity of motors that are regulated by mechanochemical rates. In addition, we find that the role of motor mobility can vary drastically if motors can bind to a pair of F-actins. A network can exhibit large contraction with high motor mobility because motors bound to antiparallel pairs of F-actins can exert similar forces regardless of their mobility. Results from this study imply that the mobility of molecular motors may critically regulate contractile behaviors of actin networks in cells.     

Experimental and mathematical approaches to modeling plant metabolic networks

To support their sessile and autotrophic lifestyle higher plants have evolved elaborate networks of metabolic pathways. Dynamic changes in these metabolic networks are among the developmental forces underlying the functional differentiation of organs, tissues and specialized cell types. They are also important in the various interactions of a plant with its environment. Further complexity is added by the extensive compartmentation of the various interconnected metabolic pathways in plants. Thus, although being used widely for assessing the control of metabolic flux in microbes, mathematical modeling approaches that require steady-state approximations are of limited utility for understanding complex plant metabolic networks. However, considerable progress has been made when manageable metabolic subsystems were studied. In this article, we will explain in general terms and using simple examples the concepts underlying stoichiometric modeling (metabolic flux analysis and metabolic pathway analysis) and kinetic approaches to modeling (including metabolic control analysis as a special case). Selected studies demonstrating the prospects of these approaches, or combinations of them, for understanding the control of flux through particular plant pathways are discussed. We argue that iterative cycles of (dry) mathematical modeling and (wet) laboratory testing will become increasingly important for simulating the distribution of flux in plant metabolic networks and deriving rational experimental designs for metabolic engineering efforts.     

Evidence for an independent radiation of endosymbiotic litostome ciliates within Australian marsupial herbivores

Observations from molecular marker studies on recently diverged species indicate that substitution patterns in DNA sequences can often be complex and poorly described by tree-like bifurcating evolutionary models. These observations might result from processes of species diversification and/or processes of sequence evolution that are not tree-like. In these cases, bifurcating tree representations provide poor visualization of phylogenetic signals in sequence data. In this paper, we use median networks to study DNA sequence substitution patterns in plant nuclear and chloroplast markers. We describe how to prune median networks to obtain so called pruned median networks. These simpler networks may help to provide a useful framework for investigating the phylogenetic complexity of recently diverged taxa with hybrid origins.     

Soft tissue mechanotransduction in wound healing and fibrosis

Recent evidence suggests that mechanical forces can significantly impact the biologic response to injury. Integrated mechanical and chemical signaling networks have been discovered that enable physical cues to regulate disease processes such as pathologic scar formation. Distinct molecular mechanisms control how tensional forces influence wound healing and fibrosis. Conceptual frameworks to understand cutaneous repair have expanded beyond traditional cell-cytokine models to include dynamic interactions driven by mechanical force and the extracellular matrix. Strategies to manipulate these biomechanical signaling networks have tremendous therapeutic potential to reduce scar formation and promote skin regeneration.     

Plant resistance to mechanical stress: evidence of an avoidance-tolerance trade-off

External mechanical forces resulting from the pressure exerted by wind or water movement are a major stress factor for plants and may cause regular disturbances in many ecosystems. A plant's ability to resist these forces relies either on minimizing the forces encountered by the plant (avoidance strategy), or on maximizing its resistance to breakage (tolerance strategy). We investigated plant resistance strategies using aquatic vegetation as a model, and examined whether avoidance and tolerance are negatively correlated. We tested the avoidance-tolerance correlation across 28 species using a phylogenetically corrected analysis, after construction of a molecular phylogeny for the species considered. Different species demonstrated contrasting avoidance and tolerance and we demonstrated a significant negative relationship between the two strategies, which suggests an avoidance-tolerance trade-off. Negative relationships may result from costs that each strategy incurs or from constraints imposed by physical laws on plant tissues. The existence of such a trade-off has important ecological and evolutionary consequences. It would lead to constraints on the evolution and variation of both strategies, possibly limiting their evolution and may constrain many morphological, anatomical and architectural traits that underlie avoidance and tolerance.     

CML9, a multifunctional Arabidopsis thaliana calmodulin-like protein involved in stress responses and plant growth?

Plants have evolved complex signaling networks to respond to their fluctuating environment and adapt their growth and development. Calcium-dependent signaling pathways play key role in the onset of these adaptive responses. In plant cells, the intracellular calcium transients are triggered by numerous stimuli and it is supposed that the large repertory of calcium sensors present in higher plants could contribute to integrate these signals in physiological responses. Here, we present data on CML9, a calmodulin-like protein that appears to be involved in plant responses to both biotic and abiotic stress. Using a reverse genetic approach based on gain and loss of function mutants, we present here data indicating that this CML might also be involved in root growth control in response to the flagellin, a pathogen-associated molecular pattern (PAMP) also involved in plant immunity.     

Crosslinkers and motors organize dynamic microtubules to form stable bipolar arrays in fission yeast

Microtubule (MT) nucleation not only occurs from centrosomes, but also in large part from dispersed nucleation sites. The subsequent sorting of short MTs into networks like the mitotic spindle requires molecular motors that laterally slide overlapping MTs and bundling proteins that statically connect MTs. How bundling proteins interfere with MT sliding is unclear. In bipolar MT bundles in fission yeast, we found that the bundler ase1p localized all along the length of antiparallel MTs, whereas the motor klp2p (kinesin-14) accumulated only at MT plus ends. Consequently, sliding forces could only overcome resistant bundling forces for short, newly nucleated MTs, which were transported to their correct position within bundles. Ase1p thus regulated sliding forces based on polarity and overlap length, and computer simulations showed these mechanisms to be sufficient to generate stable bipolar bundles. By combining motor and bundling proteins, cells can thus dynamically organize stable regions of overlap between cytoskeletal filaments.     

Mechanical Detection of a Long-Range Actin Network Emanating from a Biomimetic Cortex

Actin is ubiquitous globular protein that polymerizes into filaments and forms networks that participate in the force generation of eukaryotic cells. Such forces are used for cell motility, cytokinesis, and tissue remodeling. Among those actin networks, we focus on the actin cortex, a dense branched network beneath the plasma membrane that is of particular importance for the mechanical properties of the cell. Here we reproduce the cellular cortex by activating actin filament growth on a solid surface. We unveil the existence of a sparse actin network that emanates from the surface and extends over a distance that is at least 10 times larger than the cortex itself. We call this sparse actin network the “actin cloud” and characterize its mechanical properties with optical tweezers. We show, both experimentally and theoretically, that the actin cloud is mechanically relevant and that it should be taken into account because it can sustain forces as high as several picoNewtons (pN). In particular, it is known that in plant cells, actin networks similar to the actin cloud have a role in positioning the nucleus; in large oocytes, they play a role in driving chromosome movement. Recent evidence shows that such networks even prevent granule condensation in large cells.     

Seeing is believing? Comparing plant–herbivore networks constructed by field co‐occurrence and DNA barcoding methods for gaining insights into network structures

Plant–herbivore interaction networks provide information about community organization. Two methods are currently used to document pairwise interactions among plants and insect herbivores. One is the traditional method that collects plant–herbivore interaction data by field observation of insect occurrence on host plants. The other is the increasing application of newly developed molecular techniques based on DNA barcodes to the analysis of gut contents. The second method is more appealing because it documents realized interactions. To construct complete interaction networks, each technique of network construction is urgent to be assessed. We addressed this question by comparing the effectiveness and reliability of the two methods in constructing plant–Lepidoptera larval network in a 50 ha subtropical forest in China. Our results showed that the accuracy of diet identification by observation method increased with the number of observed insect occurrences on food plants. In contrast, the molecular method using three plant DNA markers were able to identify food residues for 35.6% larvae and correctly resolved 77.3% plant (diet) species. Network analysis showed molecular networks had threefold more unique host plant species but fewer links than the traditional networks had. The molecular method detected plants that were not sampled by the traditional method, for example, bamboos, bryophytes and lianas in the diets of insect herbivores. The two networks also possessed significantly different structural properties. Our study indicates the traditional observation of co‐occurrence is inadequate, while molecular method can provide higher species resolution of ecological interactions.     

Mechanical Detection of a Long-Range Actin Network Emanating from a Biomimetic Cortex

Actin is ubiquitous globular protein that polymerizes into filaments and forms networks that participate in the force generation of eukaryotic cells. Such forces are used for cell motility, cytokinesis, and tissue remodeling. Among those actin networks, we focus on the actin cortex, a dense branched network beneath the plasma membrane that is of particular importance for the mechanical properties of the cell. Here we reproduce the cellular cortex by activating actin filament growth on a solid surface. We unveil the existence of a sparse actin network that emanates from the surface and extends over a distance that is at least 10 times larger than the cortex itself. We call this sparse actin network the “actin cloud” and characterize its mechanical properties with optical tweezers. We show, both experimentally and theoretically, that the actin cloud is mechanically relevant and that it should be taken into account because it can sustain forces as high as several picoNewtons (pN). In particular, it is known that in plant cells, actin networks similar to the actin cloud have a role in positioning the nucleus; in large oocytes, they play a role in driving chromosome movement. Recent evidence shows that such networks even prevent granule condensation in large cells.     

Loading history determines the velocity of actin-network growth

Directional polymerization of actin filaments in branched networks is one of the most powerful force-generating systems in eukaryotic cells. Growth of densely cross-linked actin networks drives cell crawling, intracellular transport of vesicles and organelles, and movement of intracellular pathogens such as Listeria monocytogenes. Using a modified atomic force microscope (AFM), we obtained force-velocity (Fv) measurements of growing actin networks in vitro until network elongation ceased at the stall force. We found that the growth velocity of a branched actin network against increasing forces is load-independent over a wide range of forces before a convex decline to stall. Surprisingly, when force was decreased on a growing network, the velocity increased to a value greater than the previous velocity, such that two or more stable growth velocities can exist at a single load. These results demonstrate that a single Fv relationship does not capture the complete behaviour of this system, unlike other molecular motors in cells, because the growth velocity depends on loading history rather than solely on the instantaneous load.