Stigma/Style Cell-Cycle Inhibitor 1, a Regulator of Cell Proliferation, Interacts With a Specific 14-3-3 Protein and Is Degraded During Cell Division

The final shape and size of plant organs are determined by a network of genes that modulate cell proliferation and expansion. Among those, SCI1 (Stigma/style Cell-cycle Inhibitor 1) functions by inhibiting cell proliferation during pistil development. Alterations in SCI1 expression levels can lead to remarkable stigma/style size changes. Recently, we demonstrated that SCI1 starts to be expressed at the specification of the Nicotiana tabacum floral meristem and is expressed at all floral meristematic cells. To elucidate how SCI1 regulates cell proliferation, we screened a stigma/style cDNA library through the yeast two-hybrid (Y2H) system, using SCI1 as bait. Among the interaction partners, we identified the 14-3-3D protein of the Non-Epsilon group. The interaction between SCI1 and 14-3-3D was confirmed by pulldown and co-immunoprecipitation experiments. 14-3-3D forms homo- and heterodimers in the cytoplasm of plant cells and interacts with SCI1 in the nucleus, as demonstrated by Bimolecular Fluorescence Complementation (BiFC). Analyses of SCI1-GFP fluorescence through the cell-cycle progression revealed its presence in the nucleoli during interphase and prophase. At metaphase, SCI1-GFP fluorescence faded and was no longer detected at anaphase, reappearing at telophase. Upon treatment with the 26S proteasome inhibitor MG132, SCI1-GFP was stabilized during cell division. Site-directed mutagenesis of seven serines into alanines in the predicted 14-3-3 binding sites on the SCI1 sequence prevented its degradation during mitosis. Our results demonstrate that SCI1 degradation at the beginning of metaphase is dependent on the phosphorylation of serine residues and on the action of the 26S proteasome. We concluded that SCI1 stability/degradation is cell-cycle regulated, consistent with its role in fine-tuning cell proliferation.

Plant Biosystems Design Research Roadmap 1.0

Human life intimately depends on plants for food, biomaterials, health, energy, and a sustainable environment. Various plants have been genetically improved mostly through breeding, along with limited modification via genetic engineering, yet they are still not able to meet the ever-increasing needs, in terms of both quantity and quality, resulting from the rapid increase in world population and expected standards of living. A step change that may address these challenges would be to expand the potential of plants using biosystems design approaches. This represents a shift in plant science research from relatively simple trial-and-error approaches to innovative strategies based on predictive models of biological systems. Plant biosystems design seeks to accelerate plant genetic improvement using genome editing and genetic circuit engineering or create novel plant systems through de novo synthesis of plant genomes. From this perspective, we present a comprehensive roadmap of plant biosystems design covering theories, principles, and technical methods, along with potential applications in basic and applied plant biology research. We highlight current challenges, future opportunities, and research priorities, along with a framework for international collaboration, towards rapid advancement of this emerging interdisciplinary area of research. Finally, we discuss the importance of social responsibility in utilizing plant biosystems design and suggest strategies for improving public perception, trust, and acceptance.

Populus trichocarpa encodes small, effector-like secreted proteins that are highly induced during mutualistic symbiosis

During symbiosis, organisms use a range of metabolic and protein-based signals to communicate. Of these protein signals, one class is defined as ‘effectors’, i.e., small secreted proteins (SSPs) that cause phenotypical and physiological changes in another organism. To date, protein-based effectors have been described in aphids, nematodes, fungi and bacteria. Using RNA sequencing of Populus trichocarpa roots in mutualistic symbiosis with the ectomycorrhizal fungus Laccaria bicolor, we sought to determine if host plants also contain genes encoding effector-like proteins. We identified 417 plant-encoded putative SSPs that were significantly regulated during this interaction, including 161 SSPs specific to P. trichocarpa and 15 SSPs exhibiting expansion in Populus and closely related lineages. We demonstrate that a subset of these SSPs can enter L. bicolor hyphae, localize to the nucleus and affect hyphal growth and morphology. We conclude that plants encode proteins that appear to function as effector proteins that may regulate symbiotic associations.

A roadmap for research on crassulacean acid metabolism (CAM) to enhance sustainable food and bioenergy production in a hotter, drier world

Crassulacean acid metabolism (CAM) is a specialized mode of photosynthesis that features nocturnal CO2 uptake, facilitates increased water-use efficiency (WUE), and enables CAM plants to inhabit water-limited environments such as semi-arid deserts or seasonally dry forests. Human population growth and global climate change now present challenges for agricultural production systems to increase food, feed, forage, fiber, and fuel production. One approach to meet these challenges is to increase reliance on CAM crops, such as Agave and Opuntia, for biomass production on semi-arid, abandoned, marginal, or degraded agricultural lands. Major research efforts are now underway to assess the productivity of CAM crop species and to harness the WUE of CAM by engineering this pathway into existing food, feed, and bioenergy crops. An improved understanding of CAM has potential for high returns on research investment. To exploit the potential of CAM crops and CAM bioengineering, it will be necessary to elucidate the evolution, genomic features, and regulatory mechanisms of CAM. Field trials and predictive models will be required to assess the productivity of CAM crops, while new synthetic biology approaches need to be developed for CAM engineering. Infrastructure will be needed for CAM model systems, field trials, mutant collections, and data management.