A biosensor for the direct visualization of auxin

LYCHOS is a human hybrid of a plant-like PIN transporter and a GPCR

Lysosomes have crucial roles in regulating eukaryotic metabolism and cell growth by acting as signalling platforms to sense and respond to changes in nutrient and energy availability1. LYCHOS (GPR155) is a lysosomal transmembrane protein that functions as a cholesterol sensor, facilitating the cholesterol-dependent activation of the master protein kinase mechanistic target of rapamycin complex 1 (mTORC1)2. However, the structural basis of LYCHOS assembly and activity remains unclear. Here we determine several high-resolution cryo-electron microscopy structures of human LYCHOS, revealing a homodimeric transmembrane assembly of a transporter-like domain fused to a G-protein-coupled receptor (GPCR) domain. The class B2-like GPCR domain is captured in the apo state and packs against the surface of the transporter-like domain, providing an unusual example of a GPCR as a domain in a larger transmembrane assembly. Cholesterol sensing is mediated by a conserved cholesterol-binding motif, positioned between the GPCR and transporter domains. We reveal that the LYCHOS transporter-like domain is an orthologue of the plant PIN-FORMED (PIN) auxin transporter family, and has greater structural similarity to plant auxin transporters than to known human transporters. Activity assays support a model in which the LYCHOS transporter and GPCR domains coordinate to sense cholesterol and regulate mTORC1 activation.

Efficient Generation of Protein Pockets with PocketGen

Designing protein-binding proteins is critical for drug discovery. However, the AI-based design of such proteins is challenging due to the complexity of ligand-protein interactions, the flexibility of ligand molecules and amino acid side chains, and sequence-structure dependencies. We introduce PocketGen, a deep generative model that simultaneously produces both the residue sequence and atomic structure of the protein regions where ligand interactions occur. PocketGen ensures consistency between sequence and structure by using a graph transformer for structural encoding and a sequence refinement module based on a protein language model. The bilevel graph transformer captures interactions at multiple scales, including atom, residue, and ligand levels. To enhance sequence refinement, PocketGen integrates a structural adapter into the protein language model, ensuring that structure-based predictions align with sequence-based predictions. PocketGen can generate high-fidelity protein pockets with superior binding affinity and structural validity. It operates ten times faster than physics-based methods and achieves a 95% success rate, defined as the percentage of generated pockets with higher binding affinity than reference pockets. Additionally, it attains an amino acid recovery rate exceeding 64%.

Genetically Encoded, Noise-Tolerant, Auxin Biosensors in Yeast

Auxins are crucial signaling molecules that regulate the growth, metabolism, and behavior of various organisms, most notably plants but also bacteria, fungi, and animals. Many microbes synthesize and perceive auxins, primarily indole-3-acetic acid (IAA, referred to as auxin herein), the most prevalent natural auxin, which influences their ability to colonize plants and animals. Understanding auxin biosynthesis and signaling in fungi may allow us to better control interkingdom relationships and microbiomes from agricultural soils to the human gut. Despite this importance, a biological tool for measuring auxin with high spatial and temporal resolution has not been engineered in fungi. In this study, we present a suite of genetically encoded, ratiometric, protein-based auxin biosensors designed for the model yeast Saccharomyces cerevisiae. Inspired by auxin signaling in plants, the ratiometric nature of these biosensors enhances the precision of auxin concentration measurements by minimizing clonal and growth phase variation. We used these biosensors to measure auxin production across diverse growth conditions and phases in yeast cultures and calibrated their responses to physiologically relevant levels of auxin. Future work will aim to improve the fold change and reversibility of these biosensors. These genetically encoded auxin biosensors are valuable tools for investigating auxin biosynthesis and signaling in S. cerevisiae and potentially other yeast and fungi and will also advance quantitative functional studies of the plant auxin perception machinery, from which they are built.

Enhancement of in situ detection and imaging of phytohormones in plant tissues by MALDI-MSI using 2,4-dihydroxy-5-nitrobenzoic acid as a novel matrix

Phytohormones possess unique chemical structures, and their physiological effects are regulated through intricate interactions or crosstalk among multiple phytohormones. MALDI-MSI enables the simultaneous detection and imaging of multiple hormones. However, its application for tracing phytohormones is currently restricted by low abundance of hormone in plant and suboptimal matrix selection. 2,4-Dihydroxy-5-nitrobenzoic acid (DHNBA) was reported as a new MALDI matrix for the enhanced detection and imaging of multiple phytohormones in plant tissues. DHNBA demonstrates remarkable sensitivity improvement when compared to the commonly used matrix, 2,5-dihydroxybenzoic acid (DHB), in the detection of isoprenoid cytokinins (trans-zeatin (tZ), dihy-drozeatin (DHZ), meta-topolin (mT), and N6-(Δ2-isopentenyl) adenine (iP)), jasmonic acid (JA), abscisic acid (ABA), and 1-aminocyclo-propane-1-carboxylic acid (ACC) standards. The distinctive properties of DHNBA (i.e. robust UV absorption, uniform matrix deposition, negligible background interference, and high ionization efficiency of phytohormones) make it as an ideal matrix for enhanced detection and imaging of phytohormones, including tZ, DHZ, ABA, indole-3-acetic acid (IAA), and ACC, by MALDI-MSI in various plant tissues, for example germinating seeds, primary/lateral roots, and nodules. Employing DHNBA significantly enhances our capability to concurrently track complex phytohormone biosynthesis pathways while providing precise differentiation of the specific roles played by individual phytohormones within the same category. This will propel forward the comprehensive exploration of phytohormonal functions in plant science.

AZGs: a new family of cytokinin transporters

Cytokinins (CKs) are phytohormones structurally similar to purines that play important roles in various aspects of plant physiology and development. The local and long-distance distribution of CKs is very important to control their action throughout the plant body. Over the past decade, several novel CK transporters have been described, many of which have been linked to a physiological function rather than simply their ability to transport the hormone in vitro. Purine permeases, equilibrative nucleotide transporters and ATP-binding cassette transporters are involved in the local and long-range distribution of CK. In addition, members of the Arabidopsis AZA-GUANINE RESISTANT (AZG) protein family, AZG1 and AZG2, have recently been shown to mediate CK uptake at the plasma membrane and endoplasmic reticulum. Despite sharing ∼50% homology, AZG1 and AZG2 have unique transport mechanisms, tissue-specific expression patterns, and subcellular localizations that underlie their distinct physiological functions. AZG2 is expressed in a small group of cells in the overlying tissue around the lateral root primordia, where its expression is induced by auxins and it is involved in the regulation of lateral root growth. AZG1 is ubiquitously expressed, with high levels in the division zone of the root apical meristem. Here, it binds and stabilises the auxin efflux carrier PIN1, thereby shaping root architecture, particularly under salt stress. This review highlights the latest findings on the protein properties, transport mechanisms and cellular functions of this new family of CK transporters and discusses perspectives for future research in this field.

Rationalizing Diverse Binding Mechanisms to the Same Protein Fold: Insights for Ligand Recognition and Biosensor Design

The engineering of novel protein-ligand binding interactions, particularly for complex drug-like molecules, is an unsolved problem, which could enable many practical applications of protein biosensors. In this work, we analyzed two engineered biosensors, derived from the plant hormone sensor PYR1, to recognize either the agrochemical mandipropamid or the synthetic cannabinoid WIN55,212-2. Using a combination of quantitative deep mutational scanning experiments and molecular dynamics simulations, we demonstrated that mutations at common positions can promote protein-ligand shape complementarity and revealed prominent differences in the electrostatic networks needed to complement diverse ligands. MD simulations indicate that both PYR1 protein-ligand complexes bind a single conformer of their target ligand that is close to the lowest free-energy conformer. Computational design using a fixed conformer and rigid body orientation led to new WIN55,212-2 sensors with nanomolar limits of detection. This work reveals mechanisms by which the versatile PYR1 biosensor scaffold can bind diverse ligands. This work also provides computational methods to sample realistic ligand conformers and rigid body alignments that simplify the computational design of biosensors for novel ligands of interest.

Light-emitting probes for in situ sensing of plant information

Monitoring plant physiological information for gaining a comprehensive understanding of plant growth and stress responses contributes to safeguarding plant health. Light-emitting probes - in terms of small-molecule, nanomaterials-based, and genetically protein-based probes - can be introduced into plants through foliar and root treatment or genetic transformation. These probes offer exciting opportunities for sensitive and in situ monitoring of dynamic plant chemical information - for example, reactive oxygen species (ROS), calcium ions, phytohormones - with spatiotemporal resolution. In this review we explore the sensing mechanisms of these light-emitting probes and their applications in monitoring various chemical information in plants in situ. These probes can be used as part of a sentinel plant approach to provide stress warning in the field or to explore plant signaling pathways.

Design and Characterization of a Generalist Biosensor for Indole Derivatives

Transcription factor (TF)-based biosensors are useful synthetic biology tools for applications in a variety of areas of biotechnology. A major challenge of biosensor circuits is the limited repertoire of identified and well-characterized TFs for applications of interest, in addition to the challenge of optimizing selected biosensors. In this work, we implement the IclR family repressor TF TtgV from Pseudomonas putida DOT-T1E as an indole-derivative biosensor in Escherichia coli. We optimize the genetic circuit utilizing different components, providing insights into biosensor design and expanding on previous studies investigating this TF. We discover novel physiologically relevant ligands of TtgV, such as skatole. The broad specificity of TtgV makes it a useful target for directed evolution and protein engineering toward desired specificity. TtgV, as an indole-derivative biosensor, is a promising genetic component for the detection of compounds with biological activities relevant to health and the gut microbiome.

A practical guide to the discovery of biomolecules with biostimulant activity

The growing demand for sustainable solutions in agriculture, which are critical for crop productivity and food quality in the face of climate change and the need to reduce agrochemical usage, has brought biostimulants into the spotlight as valuable tools for regenerative agriculture. With their diverse biological activities, biostimulants can contribute to crop growth, nutrient use efficiency, and abiotic stress resilience, as well as to the restoration of soil health. Biomolecules include humic substances, protein lysates, phenolics, and carbohydrates have undergone thorough investigation because of their demonstrated biostimulant activities. Here, we review the process of the discovery and development of extract-based biostimulants, and propose a practical step-by-step pipeline that starts with initial identification of biomolecules, followed by extraction and isolation, determination of bioactivity, identification of active compound(s), elucidation of mechanisms, formulation, and assessment of effectiveness. The different steps generate a roadmap that aims to expedite the transfer of interdisciplinary knowledge from laboratory-scale studies to pilot-scale production in practical scenarios that are aligned with the prevailing regulatory frameworks.

Additive Manufacturing Provides Infinite Possibilities for Self-Sensing Technology

Integrating sensors and other functional parts in one device can enable a new generation of integrated intelligent devices that can perform self-sensing and monitoring autonomously. Applications include buildings that detect and repair damage, robots that monitor conditions and perform real-time correction and reconstruction, aircraft capable of real-time perception of the internal and external environment, and medical devices and prosthetics with a realistic sense of touch. Although integrating sensors and other functional parts into self-sensing intelligent devices has become increasingly common, additive manufacturing has only been marginally explored. This review focuses on additive manufacturing integrated design, printing equipment, and printable materials and stuctures. The importance of the material, structure, and function of integrated manufacturing are highlighted. The study summarizes current challenges to be addressed and provides suggestions for future development directions.

Next-Generation Genetically Encoded Fluorescent Biosensors Illuminate Cell Signaling and Metabolism

Genetically encoded fluorescent biosensors have revolutionized the study of cell signaling and metabolism, as they allow for live-cell measurements with high spatiotemporal resolution. This success has spurred the development of tailor-made biosensors that enable the study of dynamic phenomena on different timescales and length scales. In this review, we discuss different approaches to enhancing and developing new biosensors. We summarize the technologies used to gain structural insights into biosensor design and comment on useful screening technologies. Furthermore, we give an overview of different applications where biosensors have led to key advances over recent years. Finally, we give our perspective on where future work is bound to make a large impact.

Biomass chitosan/sodium alginate colorimetric imprinting hydrogels with integrated capture and visualization detection for cadmium(II)

Due to Cd(II) with highly toxic, persistent and bioaccumulative, the discharge of it into the environment brings serious pollution. Developing strategies that are efficient, low-cost, pollution-free and specific to removing Cd(II) from wastewater is therefore of great urgency and prime importance. A novel chitosan/sodium alginate ionic imprinting(IICA) hydrogels with specific adsorption capacity for Cd(II) was prepared through freeze-thaw and ion imprinting, and finally the colorimetric sensor (IICAS) was prepared via introducing Rhodamine B(RhB) and Victoria blue(VBB) by immersion to achieve visual detection of Cd(II). The IICA hydrogels with imprinted hole structure had higher adsorption capacity and better specific selectivity for Cd(II). As well as internal diffusion, coordination, ion exchange, and hydrogen bonding influenced the adsorption rate. Moreover, the IICAS exhibited good selective detection ability and linearity for Cd(II) with the fitted correlation coefficient (R2) = 0.98, limit of detection (LOD) = 35 nmol/L. Combined with the smartphone platform, portable and quantitative detection of Cd(II) can be achieved, Within the 0-100 mg/L range, R2 remained 0.94, and LOD was 75 nmol/L. This strategy of preparing a novel whole biomass IICAS integrating capture and visual detection provides a new insight into the construction of a promising candidate sensor for the removal and detection of Cd(II).

A century of studying plant secondary metabolism-From "what?" to "where, how, and why?"

Over the past century, early advances in understanding the identity of the chemicals that collectively form a living plant have led scientists to deeper investigations exploring where these molecules localize, how they are made, and why they are synthesized in the first place. Many small molecules are specific to the plant kingdom and have been termed plant secondary metabolites, despite the fact that they can play primary and essential roles in plant structure, development, and response to the environment. The past 100 yr have witnessed elucidation of the structure, function, localization, and biosynthesis of selected plant secondary metabolites. Nevertheless, many mysteries remain about the vast diversity of chemicals produced by plants and their roles in plant biology. From early work characterizing unpurified plant extracts, to modern integration of 'omics technology to discover genes in metabolite biosynthesis and perception, research in plant (bio)chemistry has produced knowledge with substantial benefits for society, including human medicine and agricultural biotechnology. Here, we review the history of this work and offer suggestions for future areas of exploration. We also highlight some of the recently developed technologies that are leading to ongoing research advances.

Mechanism of the Pulvinus-Driven Leaf Movement: An Overview

Leaf movement is a manifestation of plant response to the changing internal and external environment, aiming to optimize plant growth and development. Leaf movement is usually driven by a specialized motor organ, the pulvinus, and this movement is associated with different changes in volume and expansion on the two sides of the pulvinus. Blue light, auxin, GA, H+-ATPase, K+, Cl-, Ca2+, actin, and aquaporin collectively influence the changes in water flux in the tissue of the extensor and flexor of the pulvinus to establish a turgor pressure difference, thereby controlling leaf movement. However, how these factors regulate the multicellular motility of the pulvinus tissues in a species remains obscure. In addition, model plants such as Medicago truncatula, Mimosa pudica, and Samanea saman have been used to study pulvinus-driven leaf movement, showing a similarity in their pulvinus movement mechanisms. In this review, we summarize past research findings from the three model plants, and using Medicago truncatula as an example, suggest that genes regulating pulvinus movement are also involved in regulating plant growth and development. We also propose a model in which the variation of ion flux and water flux are critical steps to pulvinus movement and highlight questions for future research.

Engineering Plant Cell Fates and Functions for Agriculture and Industry

Many plant species are grown to enable access to specific organs or tissues, such as seeds, fruits, or stems. In some cases, a value is associated with a molecule that accumulates in a single type of cell. Domestication and subsequent breeding have often increased the yields of these target products by increasing the size, number, and quality of harvested organs and tissues but also via changes to overall plant growth architecture to suit large-scale cultivation. Many of the mutations that underlie these changes have been identified in key regulators of cellular identity and function. As key determinants of yield, these regulators are key targets for synthetic biology approaches to engineer new forms and functions. However, our understanding of many plant developmental programs and cell-type specific functions is still incomplete. In this Perspective, we discuss how advances in cellular genomics together with synthetic biology tools such as biosensors and DNA-recording devices are advancing our understanding of cell-specific programs and cell fates. We then discuss advances and emerging opportunities for cell-type-specific engineering to optimize plant morphology, responses to the environment, and the production of valuable compounds.

Biosignals in the Gut-Brain Axis Transmission: Function and Detection

The gut-brain axis (GBA) is an important information pathway connecting the brain, the central nervous system (CNS), and the gastrointestinal (GI) tract. On the one hand, gut microbiota can influence the function brain through GBA; on the other hand, the brain can also change the structural composition of gut microbiota via GBA. It contains a myriad of biosignals, such as monoamines, inflammatory cytokines, and macro-biomolecules, as the information carriers. Highly selective, sensitive, and reliable sensing techniques are essential to resolve the specific function of individual biosignals. This review summarizes the widely reported biosignals related to GBA and their functions, and organizes the latest sensing tools to provide feasible characterization ideas for GBA-related work. In addition, these low-cost, fast-responding sensors can also be used for early identification and diagnosis of GBA-related diseases (e.g., depression). Finally, the problems and deficiencies in this field are pointed out to provide a reference for the orientation of researchers in the sensing field.

Phase transition of GvpU regulates gas vesicle clustering in bacteria

Gas vesicles (GVs) are microbial protein organelles that support cellular buoyancy. GV engineering has multiple applications, including reporter gene imaging, acoustic control and payload delivery. GVs often cluster into a honeycomb pattern to minimize occupancy of the cytosol. The underlying molecular mechanism and the influence on cellular physiology remain unknown. Using genetic, biochemical and imaging approaches, here we identify GvpU from Priestia megaterium as a protein that regulates GV clustering in vitro and upon expression in Escherichia coli. GvpU binds to the C-terminal tail of the core GV shell protein and undergoes a phase transition to form clusters in subsaturated solution. These properties of GvpU tune GV clustering and directly modulate bacterial fitness. GV variants can be designed with controllable sensitivity to GvpU-mediated clustering, enabling design of genetically tunable biosensors. Our findings elucidate the molecular mechanisms and functional roles of GV clustering, enabling its programmability for biomedical applications.

Rationalizing diverse binding mechanisms to the same protein fold: insights for ligand recognition and biosensor design

The engineering of novel protein-ligand binding interactions, particularly for complex drug-like molecules, is an unsolved problem which could enable many practical applications of protein biosensors. In this work, we analyzed two engineer ed biosensors, derived from the plant hormone sensor PYR1, to recognize either the agrochemical mandipropamid or the synthetic cannabinoid WIN55,212-2. Using a combination of quantitative deep mutational scanning experiments and molecular dynamics simulations, we demonstrated that mutations at common positions can promote protein-ligand shape complementarity and revealed prominent differences in the electrostatic networks needed to complement diverse ligands. MD simulations indicate that both PYR1 protein-ligand complexes bind a single conformer of their target ligand that is close to the lowest free energy conformer. Computational design using a fixed conformer and rigid body orientation led to new WIN55,212-2 sensors with nanomolar limits of detection. This work reveals mechanisms by which the versatile PYR1 biosensor scaffold can bind diverse ligands. This work also provides computational methods to sample realistic ligand conformers and rigid body alignments that simplify the computational design of biosensors for novel ligands of interest.

Emerging sensing, imaging, and computational technologies to scale nano-to macroscale rhizosphere dynamics - Review and research perspectives

The soil region influenced by plant roots, i.e., the rhizosphere, is one of the most complex biological habitats on Earth and significantly impacts global carbon flow and transformation. Understanding the structure and function of the rhizosphere is critically important for maintaining sustainable plant ecosystem services, designing engineered ecosystems for long-term soil carbon storage, and mitigating the effects of climate change. However, studying the biological and ecological processes and interactions in the rhizosphere requires advanced integrated technologies capable of decoding such a complex system at different scales. Here, we review how emerging approaches in sensing, imaging, and computational modeling can advance our understanding of the complex rhizosphere system. Particularly, we provide our perspectives and discuss future directions in developing in situ rhizosphere sensing technologies that could potentially correlate local-scale interactions to ecosystem scale impacts. We first review integrated multimodal imaging techniques for tracking inorganic elements and organic carbon flow at nano- to microscale in the rhizosphere, followed by a discussion on the use of synthetic soil and plant habitats that bridge laboratory-to-field studies on the rhizosphere processes. We then describe applications of genetically encoded biosensors in monitoring nutrient and chemical exchanges in the rhizosphere, and the novel nanotechnology-mediated delivery approaches for introducing biosensors into the root tissues. Next, we review the recent progress and express our vision on field-deployable sensing technologies such as planar optodes for quantifying the distribution of chemical and analyte gradients in the rhizosphere under field conditions. Moreover, we provide perspectives on the challenges of linking complex rhizosphere interactions to ecosystem sensing for detecting biological traits across scales, which arguably requires using the best-available model predictions including the model-experiment and image-based modeling approaches. Experimental platforms relevant to field conditions like SMART (Sensors at Mesoscales with Advanced Remote Telemetry) soils testbed, coupled with ecosystem sensing and predictive models, can be effective tools to explore coupled ecosystem behavior and responses to environmental perturbations. Finally, we envision that with the advent of novel high-resolution imaging capabilities at nano- to macroscale, and remote biosensing technologies, combined with advanced computational models, future studies will lead to detection and upscaling of rhizosphere processes toward ecosystem and global predictions.

De novo protein design-From new structures to programmable functions

Methods from artificial intelligence (AI) trained on large datasets of sequences and structures can now "write" proteins with new shapes and molecular functions de novo, without starting from proteins found in nature. In this Perspective, I will discuss the state of the field of de novo protein design at the juncture of physics-based modeling approaches and AI. New protein folds and higher-order assemblies can be designed with considerable experimental success rates, and difficult problems requiring tunable control over protein conformations and precise shape complementarity for molecular recognition are coming into reach. Emerging approaches incorporate engineering principles-tunability, controllability, and modularity-into the design process from the beginning. Exciting frontiers lie in deconstructing cellular functions with de novo proteins and, conversely, constructing synthetic cellular signaling from the ground up. As methods improve, many more challenges are unsolved.

Advances in ligand-specific biosensing for structurally similar molecules

The specificity of biological systems makes it possible to develop biosensors targeting specific metabolites, toxins, and pollutants in complex medical or environmental samples without interference from structurally similar compounds. For the last two decades, great efforts have been devoted to creating proteins or nucleic acids with novel properties through synthetic biology strategies. Beyond augmenting biocatalytic activity, expanding target substrate scopes, and enhancing enzymes' enantioselectivity and stability, an increasing research area is the enhancement of molecular specificity for genetically encoded biosensors. Here, we summarize recent advances in the development of highly specific biosensor systems and their essential applications. First, we describe the rational design principles required to create libraries containing potential mutants with less promiscuity or better specificity. Next, we review the emerging high-throughput screening techniques to engineer biosensing specificity for the desired target. Finally, we examine the computer-aided evaluation and prediction methods to facilitate the construction of ligand-specific biosensors.

Hormonal Status of Transgenic Birch with a Pine Glutamine Synthetase Gene during Rooting In Vitro and Budburst Outdoors

Improving nitrogen use efficiency (NUE) is one of the main ways of increasing plant productivity through genetic engineering. The modification of nitrogen (N) metabolism can affect the hormonal content, but in transgenic plants, this aspect has not been sufficiently studied. Transgenic birch (Betula pubescens) plants with the pine glutamine synthetase gene GS1 were evaluated for hormone levels during rooting in vitro and budburst under outdoor conditions. In the shoots of the transgenic lines, the content of indoleacetic acid (IAA) was 1.5-3 times higher than in the wild type. The addition of phosphinothricin (PPT), a glutamine synthetase (GS) inhibitor, to the medium reduced the IAA content in transgenic plants, but it did not change in the control. In the roots of birch plants, PPT had the opposite effect. PPT decreased the content of free amino acids in the leaves of nontransgenic birch, but their content increased in GS-overexpressing plants. A three-year pot experiment with different N availability showed that the productivity of the transgenic birch line was significantly higher than in the control under N deficiency, but not excess, conditions. Nitrogen availability did not affect budburst in the spring of the fourth year; however, bud breaking in transgenic plants was delayed compared to the control. The IAA and abscisic acid (ABA) contents in the buds of birch plants at dormancy and budburst depended both on N availability and the transgenic status. These results enable a better understanding of the interaction between phytohormones and nutrients in woody plants.

PINOID and PIN-FORMED Paralogous Genes Are Required for Leaf Morphogenesis in Rice

Auxin plays an essential role in modulating leaf development. However, its role in leaf development in rice (Oryza sativa L.) remains largely unknown. In this study, we found that PINOID (OsPID) and two Sister-of-PIN1s, termed PIN-FORMED1c (OsPIN1c) and OsPIN1d, are necessary for rice leaf development. The ospin1c ospin1d null mutant lines presented severe defects in leaf morphogenesis, including drooping and semi-drooping blades, an abnormally thickened sheath and lamina joint, and fused leaves with absent ligules and auricles. Loss-of-function ospid mutants displayed generally similar leaf morphology but lacked leaf fusion. Interestingly, misshaped leaf genesis displayed a preference for being ipsilateral. In addition, OsPIN1c and OsPID were commonly localized in the initiating leaf primordia. Furthermore, accompanied by the more severe organ morphogenesis in the ospin1c ospin1d ospid triple mutant, RNA sequencing analysis revealed that many genes essential for leaf development have an altered expression level. Together, this study furthers our understanding of the role auxin transport plays during leaf development in monocot rice.

Spatial regulation of plant hormone action

Although many plant cell types are capable of producing hormones, and plant hormones can in most cases act in the same cells in which they are produced, they also act as signaling molecules that coordinate physiological responses between different parts of the plant, indicating that their action is subject to spatial regulation. Numerous publications have reported that all levels of plant hormonal pathways, namely metabolism, transport, and perception/signal transduction, can help determine the spatial ranges of hormone action. For example, polar auxin transport or localized auxin biosynthesis contribute to creating a differential hormone accumulation across tissues that is instrumental for specific growth and developmental responses. On the other hand, tissue specificity of cytokinin actions has been proposed to be regulated by mechanisms operating at the signaling stages. Here, we review and discuss current knowledge about the contribution of the three levels mentioned above in providing spatial specificity to plant hormone action. We also explore how new technological developments, such as plant hormone sensors based on FRET (fluorescence resonance energy transfer) or single-cell RNA-seq, can provide an unprecedented level of resolution in defining the spatial domains of plant hormone action and its dynamics.

Application of water-soluble conjugated polymers in intelligent measurement and control of food microbial fermentation process

In order to reduce the difficulty of measurement and control (MAC) during food fermentation, this paper applies water-soluble conjugated polymers to sensors, conducts data modeling and prediction, and integrates the sensors into intelligent MAC systems. This article uses fermentation rate, product yield, and energy consumption efficiency as evaluation indicators to analyze the effectiveness of smart MAC. By comparing and analyzing the MAC method based on water-soluble conjugated polymers with the traditional MAC method, this article found that the MAC method based on water-soluble conjugated polymers can improve product yield, fermentation efficiency and energy utilization compared with traditional MAC methods. The MAC accuracy, timeliness, stability, speed and security of the MAC system based on water-soluble conjugated polymers are higher than those of traditional MAC systems. Among them, the average test stability of the traditional MAC system is 19.93% lower than that of the smart MAC system based on water-soluble conjugated polymers. Research shows that the intelligent MAC method based on water-soluble conjugated polymers can effectively improve the fermentation environment of food microorganisms and improve product quality, and is worthy of further promotion.

Ratiometric fluorescent probes for pH mapping in cellular organelles

The intracellular pH (pHi) in organelles, including mitochondria, endoplasmic reticulum, lysosomes, and nuclei, differs from the cytoplasmic pH, and thus maintaining the pH of these organelles is crucial for cellular homeostasis. Alterations in the intracellular pH (ΔpHi) in organelles lead to the disruption of cell proliferation, ion transportation, cellular homeostasis, and even cell death. Hence, accurately mapping the pH of organelles is crucial. Accordingly, the development of fluorescence imaging probes for targeting specific organelles and monitoring their dynamics at the molecular level has become the forefront of research in the last three decades. Among them, ratiometric fluorescent probes minimize the interference from the excitation wavelength of light, auto-fluorescence from probe concentration, environmental fluctuations, and instrument sensitivity through self-correction compared to monochromatic fluorescent probes, which are known as turn-on/off fluorescent probes. Small-molecular ratiometric fluorescent probes for detecting ΔpHi are challenging yet demanding. To date, sixty-two ratiometric pH probes have been reported for monitoring internal pH alterations in cellular organelles. However, a critical review on organelle-specific ratiometric probes for pH mapping is still lacking. Thus, in the present review, we report the most recent advances in ratiometric pH probes and the previous data on the role of mapping the ΔpHi of cellular organelles. The development strategy, including ratiometric fluorescence with one reference signal (RFRS) and ratiometric fluorescence with two reversible signals (RFRvS), is systematically illustrated. Finally, we emphasize the major challenges in developing ratiometric probes that merit further research in the future.

A Connected World: System-Level Support Through Biosensors

The goal of protecting the health of future generations is a blueprint for future biosensor design. Systems-level decision support requires that biosensors provide meaningful service to society. In this review, we summarize recent developments in cyber physical systems and biosensors connected with decision support. We identify key processes and practices that may guide the establishment of connections between user needs and biosensor engineering using an informatics approach. We call for data science and decision science to be formally connected with sensor science for understanding system complexity and realizing the ambition of biosensors-as-a-service. This review calls for a focus on quality of service early in the design process as a means to improve the meaningful value of a given biosensor. We close by noting that technology development, including biosensors and decision support systems, is a cautionary tale. The economics of scale govern the success, or failure, of any biosensor system.

The emerging role of auxins as bacterial signal molecules: Potential biotechnological applications

Microorganisms are exposed in their natural niches to a wide diversity of signal molecules. Specific detection of these signals results in alterations in microbial metabolism and physiology. Auxins like indole-3-acetic acid are key phytohormones that regulate plant growth and development. Nonetheless, auxin biosynthesis is not restricted to plants but is ubiquitous in all kingdoms of life. This wide phylogenetic distribution of auxins production, together with the diversity of regulated cellular processes, have made auxins key intra- and inter-kingdom signal molecules in life modulating, for example microbial physiology, metabolism and virulence. Despite their increasing importance as global signal molecules, the mechanisms by which auxins perform their regulatory functions in microorganisms are largely unknown. In this article, we outline recent research that has advanced our knowledge of the mechanisms of bacterial auxin perception. We also highlight the potential applications of this research in aspects such as antibiotic production, biosensor design, plant microbiome engineering and antivirulence therapies.

Novel insights into maize (Zea mays) development and organogenesis for agricultural optimization

In maize, intrinsic hormone activities and sap fluxes facilitate organogenesis patterning and plant holistic development; these hormone movements should be a primary focus of developmental biology and agricultural optimization strategies. Maize (Zea mays) is an important crop plant with distinctive life history characteristics and structural features. Genetic studies have extended our knowledge of maize developmental processes, genetics, and molecular ecophysiology. In this review, the classical life cycle and life history strategies of maize are analyzed to identify spatiotemporal organogenesis properties and develop a definitive understanding of maize development. The actions of genes and hormones involved in maize organogenesis and sex determination, along with potential molecular mechanisms, are investigated, with findings suggesting central roles of auxin and cytokinins in regulating maize holistic development. Furthermore, investigation of morphological and structural characteristics of maize, particularly node ubiquity and the alternate attachment pattern of lateral organs, yields a novel regulatory model suggesting that maize organ initiation and subsequent development are derived from the stimulation and interaction of auxin and cytokinin fluxes. Propositions that hormone activities and sap flow pathways control organogenesis are thoroughly explored, and initiation and development processes of distinctive maize organs are discussed. Analysis of physiological factors driving hormone and sap movement implicates cues of whole-plant activity for hormone and sap fluxes to stimulate maize inflorescence initiation and organ identity determination. The physiological origins and biogenetic mechanisms underlying maize floral sex determination occurring at the tassel and ear spikelet are thoroughly investigated. The comprehensive outline of maize development and morphogenetic physiology developed in this review will enable farmers to optimize field management and will provide a reference for de novo crop domestication and germplasm improvement using genome editing biotechnologies, promoting agricultural optimization.

Application of Data Modeling, Instrument Engineering and Nanomaterials in Selected Medid the Scientific Recinal Plant Tissue Culture

At present, most precious compounds are still obtained by plant cultivation such as ginsenosides, glycyrrhizic acid, and paclitaxel, which cannot be easily obtained by artificial synthesis. Plant tissue culture technology is the most commonly used biotechnology tool, which can be used for a variety of studies such as the production of natural compounds, functional gene research, plant micropropagation, plant breeding, and crop improvement. Tissue culture material is a basic and important part of this issue. The formation of different plant tissues and natural products is affected by growth conditions and endogenous substances. The accumulation of secondary metabolites are affected by plant tissue type, culture method, and environmental stress. Multi-domain technologies are developing rapidly, and they have made outstanding contributions to the application of plant tissue culture. The modes of action have their own characteristics, covering the whole process of plant tissue from the induction, culture, and production of natural secondary metabolites. This paper reviews the induction mechanism of different plant tissues and the application of multi-domain technologies such as artificial intelligence, biosensors, bioreactors, multi-omics monitoring, and nanomaterials in plant tissue culture and the production of secondary metabolites. This will help to improve the tissue culture technology of medicinal plants and increase the availability and the yield of natural metabolites.

Auxin signaling is essential for organogenesis but not for cell survival in the liverwort Marchantia polymorpha

Auxin plays pleiotropic roles in plant development via gene regulation upon its perception by the receptors TRANSPORT INHIBITOR RESPONSE 1/AUXIN SIGNALING F-BOX (TIR1/AFBs). This auxin-regulated transcriptional control mechanism originated in the common ancestor of land plants. Although the complete loss of TIR1/AFBs causes embryonic lethality in Arabidopsis thaliana, it is unclear whether the requirement for TIR1-mediated auxin perception in cell viability can be generalized. The model liverwort Marchantia polymorpha has a minimal auxin signaling system with only a single TIR1/AFB, MpTIR1. Here we show by genetic, biochemical, and transcriptomic analyses that MpTIR1 functions as an evolutionarily conserved auxin receptor. Null mutants and conditionally knocked-out mutants of MpTIR1 were viable but incapable of forming any organs and grew as cell masses. Principal component analysis performed using transcriptomes at various developmental stages indicated that MpTIR1 is involved in the developmental transition from spores to organized thalli, during which apical notches containing stem cells are established. In Mptir1 cells, stem cell- and differentiation-related genes were up- and downregulated, respectively. Our findings suggest that, in M. polymorpha, auxin signaling is dispensable for cell division but is essential for three-dimensional patterning of the plant body by establishing pluripotent stem cells for organogenesis, a derived trait of land plants.

Nucleic acid aptamers as aptasensors for plant biology

Our knowledge of cell- and tissue-specific quantification of phytohormones is heavily reliant on laborious mass spectrometry techniques. Genetically encoded biosensors have allowed spatial and some temporal quantification of phytohormones intracellularly, but there is still limited information on their intercellular distributions. Here, we review nucleic acid aptamers as an emerging biosensing platform for the detection and quantification of analytes with high affinity and specificity. Options for DNA aptamer technology are explained through selection, sequencing analysis and techniques for evaluating affinity and specificity, and we focus on previously developed DNA aptamers against various plant analytes. We suggest how these tools might be applied in planta for quantification of molecules of interest both intracellularly and intercellularly.

Emergence of an Auxin Sensing Domain in Plant-Associated Bacteria

Bacteria have evolved a sophisticated array of signal transduction systems that allow them to adapt their physiology and metabolism to changing environmental conditions. Typically, these systems recognize signals through dedicated ligand binding domains (LBDs) to ultimately trigger a diversity of physiological responses. Nonetheless, an increasing number of reports reveal that signal transduction receptors also bind antagonists to inhibit responses mediated by agonists. The mechanisms by which antagonists block the downstream signaling cascade remain largely unknown. To advance our knowledge in this field, we used the LysR-type transcriptional regulator AdmX as a model. AdmX activates the expression of an antibiotic biosynthetic cluster in the rhizobacterium Serratia plymuthica. AdmX specifically recognizes the auxin phytohormone indole-3-acetic acid (IAA) and its biosynthetic intermediate indole-3-pyruvic acid (IPA) as signals. However, only IAA, but not IPA, was shown to regulate antibiotic production in S. plymuthica. Here, we report the high-resolution structures of the LBD of AdmX in complex with IAA and IPA. We found that IAA and IPA compete for binding to AdmX. Although IAA and IPA binding does not alter the oligomeric state of AdmX, IPA binding causes a higher degree of compactness in the protein structure. Molecular dynamics simulations revealed significant differences in the binding modes of IAA and IPA by AdmX, and the inspection of the three-dimensional structures evidenced differential agonist- and antagonist-mediated structural changes. Key residues for auxin binding were identified and an auxin recognition motif defined. Phylogenetic clustering supports the recent evolutionary emergence of this motif specifically in plant-associated enterobacteria. IMPORTANCE Although antagonists were found to bind different bacterial signal transduction receptors, we are still at the early stages of understanding the molecular details by which these molecules exert their inhibitory effects. Here, we provide insight into the structural changes resulting from the binding of an agonist and an antagonist to a sensor protein. Our data indicate that agonist and antagonist recognition is characterized by small conformational differences in the LBDs that can be efficiently transmitted to the output domain to modulate the final response. LBDs are subject to strong selective pressures and are rapidly evolving domains. An increasing number of reports support the idea that environmental factors drive the evolution of sensor domains. Given the recent evolutionary history of AdmX homologs, as well as their narrow phyletic distribution within plant-associated bacteria, our results are in accordance with a plant-mediated evolutionary process that resulted in the emergence of receptor proteins that specifically sense auxin phytohormones.

Computational Biomaterials: Computational Simulations for Biomedicine

With the flourishing development of material simulation methods (quantum chemistry methods, molecular dynamics, Monte Carlo, phase field, etc.), extensive adoption of computing technologies (high-throughput, artificial intelligence, machine learning, etc.), and the invention of high-performance computing equipment, computational simulation tools have sparked the fundamental mechanism-level explorations to predict the diverse physicochemical properties and biological effects of biomaterials and investigate their enormous application potential for disease prevention, diagnostics, and therapeutics. Herein, the term "computational biomaterials" is proposed and the computational methods currently used to explore the inherent properties of biomaterials, such as optical, magnetic, electronic, and acoustic properties, and the elucidation of corresponding biological behaviors/effects in the biomedical field are summarized/discussed. The theoretical calculation of the physiochemical properties/biological performance of biomaterials applied in disease diagnosis, drug delivery, disease therapeutics, and specific paradigms such as biomimetic biomaterials is discussed. Additionally, the biosafety evaluation applications of theoretical simulations of biomaterials are presented. Finally, the challenges and future prospects of such computational simulations for biomaterials development are clarified. It is anticipated that these simulations would offer various methodologies for facilitating the development and future clinical translations/utilization of versatile biomaterials.

Plant Hormonomics: A Key Tool for Deep Physiological Phenotyping to Improve Crop Productivity

Agriculture is particularly vulnerable to climate change. To cope with the risks posed by climate-related stressors to agricultural production, global population growth, and changes in food preferences, it is imperative to develop new climate-smart crop varieties with increased yield and environmental resilience. Molecular genetics and genomic analyses have revealed that allelic variations in genes involved in phytohormone-mediated growth regulation have greatly improved productivity in major crops. Plant science has remarkably advanced our understanding of the molecular basis of various phytohormone-mediated events in plant life. These findings provide essential information for improving the productivity of crops growing in changing climates. In this review, we highlight the recent advances in plant hormonomics (multiple phytohormone profiling) and discuss its application to crop improvement. We present plant hormonomics as a key tool for deep physiological phenotyping, focusing on representative plant growth regulators associated with the improvement of crop productivity. Specifically, we review advanced methodologies in plant hormonomics, highlighting mass spectrometry- and nanosensor-based plant hormone profiling techniques. We also discuss the applications of plant hormonomics in crop improvement through breeding and agricultural management practices.

Differential sensing with arrays of de novo designed peptide assemblies

Differential sensing attempts to mimic the mammalian senses of smell and taste to identify analytes and complex mixtures. In place of hundreds of complex, membrane-bound G-protein coupled receptors, differential sensors employ arrays of small molecules. Here we show that arrays of computationally designed de novo peptides provide alternative synthetic receptors for differential sensing. We use self-assembling α-helical barrels (αHBs) with central channels that can be altered predictably to vary their sizes, shapes and chemistries. The channels accommodate environment-sensitive dyes that fluoresce upon binding. Challenging arrays of dye-loaded barrels with analytes causes differential fluorophore displacement. The resulting fluorimetric fingerprints are used to train machine-learning models that relate the patterns to the analytes. We show that this system discriminates between a range of biomolecules, drink, and diagnostically relevant biological samples. As αHBs are robust and chemically diverse, the system has potential to sense many analytes in various settings.

Optical Sensing Technologies to Elucidate the Interplay between Plant and Microbes

Plant-microbe interactions are critical for ecosystem functioning and driving rhizosphere processes. To fully understand the communication pathways between plants and rhizosphere microbes, it is crucial to measure the numerous processes that occur in the plant and the rhizosphere. The present review first provides an overview of how plants interact with their surrounding microbial communities, and in turn, are affected by them. Next, different optical biosensing technologies that elucidate the plant-microbe interactions and provide pathogenic detection are summarized. Currently, most of the biosensors used for detecting plant parameters or microbial communities in soil are centered around genetically encoded optical and electrochemical biosensors that are often not suitable for field applications. Such sensors require substantial effort and cost to develop and have their limitations. With a particular focus on the detection of root exudates and phytohormones under biotic and abiotic stress conditions, novel low-cost and in-situ biosensors must become available to plant scientists.

Metabolomics-centered mining of plant metabolic diversity and function: Past decade and future perspectives

Plants are natural experts in organic synthesis, being able to generate large numbers of specific metabolites with widely varying structures that help them adapt to variable survival challenges. Metabolomics is a research discipline that integrates the capabilities of several types of research including analytical chemistry, statistics, and biochemistry. Its ongoing development provides strategies for gaining a systematic understanding of quantitative changes in the levels of metabolites. Metabolomics is usually performed by targeting either a specific cell, a specific tissue, or the entire organism. Considerable advances in science and technology over the last three decades have propelled us into the era of multi-omics, in which metabolomics, despite at an earlier developmental stage than genomics, transcriptomics, and proteomics, offers the distinct advantage of studying the cellular entities that have the greatest influence on end phenotype. Here, we summarize the state of the art of metabolite detection and identification, and illustrate these techniques with four case study applications: (i) comparing metabolite composition within and between species, (ii) assessing spatio-temporal metabolic changes during plant development, (iii) mining characteristic metabolites of plants in different ecological environments and upon exposure to various stresses, and (iv) assessing the performance of metabolomics as a means of functional gene identification , metabolic pathway elucidation, and metabolomics-assisted breeding through analyzing plant populations with diverse genetic variations. In addition, we highlight the prominent contributions of joint analyses of plant metabolomics and other omics datasets, including those from genomics, transcriptomics, proteomics, epigenomics, phenomics, microbiomes, and ion-omics studies. Finally, we discuss future directions and challenges exploiting metabolomics-centered approaches in understanding plant metabolic diversity.

PocketOptimizer 2.0: A modular framework for computer-aided ligand-binding design

The ability to design customized proteins to perform specific tasks is of great interest. We are particularly interested in the design of sensitive and specific small molecule ligand-binding proteins for biotechnological or biomedical applications. Computational methods can narrow down the immense combinatorial space to find the best solution and thus provide starting points for experimental procedures. However, success rates strongly depend on accurate modeling and energetic evaluation. Not only intra- but also intermolecular interactions have to be considered. To address this problem, we developed PocketOptimizer, a modular computational protein design pipeline, that predicts mutations in the binding pockets of proteins to increase affinity for a specific ligand. Its modularity enables users to compare different combinations of force fields, rotamer libraries, and scoring functions. Here, we present a much-improved version--PocketOptimizer 2.0. We implemented a cleaner user interface, an extended architecture with more supported tools, such as force fields and scoring functions, a backbone-dependent rotamer library, as well as different improvements in the underlying algorithms. Version 2.0 was tested against a benchmark of design cases and assessed in comparison to the first version. Our results show how newly implemented features such as the new rotamer library can lead to improved prediction accuracy. Therefore, we believe that PocketOptimizer 2.0, with its many new and improved functionalities, provides a robust and versatile environment for the design of small molecule-binding pockets in proteins. It is widely applicable and extendible due to its modular framework. PocketOptimizer 2.0 can be downloaded at https://github.com/Hoecker-Lab/pocketoptimizer.

Identification and function of miRNA-mRNA interaction pairs during lateral root development of hemi-parasitic Santalum album L. seedlings

Sandalwood (Santalum album L.) is a hemi-parasitic tree species famous for its santalol and santalene, which are extracted from its heartwood and roots. The ability to understand root functionality within its branched root system would benefit the regulation of sandalwood growth and enhance the commercial value of sandalwood. Phenotypic and anatomical evidence in this study indicated that seed germination stage 4 (SG4) seemed pivotal for lateral root (LR) morphogenesis. Small RNA (sRNA) high-throughput sequencing of root tissues at three sub-stages of SG4 (lateral root primordia initiation (LRPI), lateral root primordia development (LRPD), and lateral root primordia emergence (LRPE)) was performed to identify microRNAs (miRNAs) associated with LR development. A total of 135 miRNAs, including 70 differentially expressed miRNAs (DEMs), were screened. Ten DEMs were selected to investigate transcript abundance in different organs or developmental stages. Among 100 negative DEM-mRNA interaction pairs, four targets (Sa-miR166m_2, 408d, 858a, and novel_Sa-miR8) were selected for studying cleavage sites by 5' RLM-RACE validation. The expression mode of the four miRNA-mRNA pairs was investigated after indole-3-acetic acid (IAA) treatment. IAA enhanced the abundance of homeobox-leucine-zipper protein 32 (HOX32), laccase 12 (LAC12), myeloblastosis86 (MYB86), and pectin methylesterase inhibitor6 (PMEI6) target transcripts by reducing the expression of Sa-miR166m_2, 408d, 858a, and novel_Sa-miR8 in the first 10 min. A schematic model of miRNA-regulated LR development is proposed for this hemi-parasitic species. This novel genetic information for improving sandalwood root growth and development may allow for the cultivation of fast-growing and high-yielding plantations.

Metabolic Engineering: Methodologies and Applications

Metabolic engineering aims to improve the production of economically valuable molecules through the genetic manipulation of microbial metabolism. While the discipline is a little over 30 years old, advancements in metabolic engineering have given way to industrial-level molecule production benefitting multiple industries such as chemical, agriculture, food, pharmaceutical, and energy industries. This review describes the design, build, test, and learn steps necessary for leading a successful metabolic engineering campaign. Moreover, we highlight major applications of metabolic engineering, including synthesizing chemicals and fuels, broadening substrate utilization, and improving host robustness with a focus on specific case studies. Finally, we conclude with a discussion on perspectives and future challenges related to metabolic engineering.

Using quantitative methods to understand leaf epidermal development

As the interface between plants and the environment, the leaf epidermis provides the first layer of protection against drought, ultraviolet light, and pathogen attack. This cell layer comprises highly coordinated and specialised cells such as stomata, pavement cells and trichomes. While much has been learned from the genetic dissection of stomatal, trichome and pavement cell formation, emerging methods in quantitative measurements that monitor cellular or tissue dynamics will allow us to further investigate cell state transitions and fate determination in leaf epidermal development. In this review, we introduce the formation of epidermal cell types in Arabidopsis and provide examples of quantitative tools to describe phenotypes in leaf research. We further focus on cellular factors involved in triggering cell fates and their quantitative measurements in mechanistic studies and biological patterning. A comprehensive understanding of how a functional leaf epidermis develops will advance the breeding of crops with improved stress tolerance.

Design and engineering of genetically encoded protein biosensors for small molecules

Genetically encoded protein biosensors controlled by small organic molecules are valuable tools for many biotechnology applications, including control of cellular decisions in living cells. Here, we review recent advances in protein biosensor design and engineering for binding to novel ligands. We categorize sensor architecture as either integrated or portable, where portable biosensors uncouple molecular recognition from signal transduction. Proposed advances to improve portable biosensor development include standardizing a limited set of protein scaffolds, and automating ligand-compatibility screening and ligand-protein-interface design.

Plant synthetic biology innovations for biofuels and bioproducts

Plant-based biosynthesis of fuels, chemicals, and materials promotes environmental sustainability, which includes decreases in greenhouse gas emissions, water pollution, and loss of biodiversity. Advances in plant synthetic biology (synbio) should improve precision and efficacy of genetic engineering for sustainability. Applicable synbio innovations include genome editing, gene circuit design, synthetic promoter development, gene stacking technologies, and the design of environmental sensors. Moreover, recent advancements in developing spatially resolved and single-cell omics contribute to the discovery and characterization of cell-type-specific mechanisms and spatiotemporal gene regulations in distinct plant tissues for the expression of cell- and tissue-specific genes, resulting in improved bioproduction. This review highlights recent plant synbio progress and new single-cell molecular profiling towards sustainable biofuel and biomaterial production.

Biological and Molecular Components for Genetically Engineering Biosensors in Plants

Plants adapt to their changing environments by sensing and responding to physical, biological, and chemical stimuli. Due to their sessile lifestyles, plants experience a vast array of external stimuli and selectively perceive and respond to specific signals. By repurposing the logic circuitry and biological and molecular components used by plants in nature, genetically encoded plant-based biosensors (GEPBs) have been developed by directing signal recognition mechanisms into carefully assembled outcomes that are easily detected. GEPBs allow for in vivo monitoring of biological processes in plants to facilitate basic studies of plant growth and development. GEPBs are also useful for environmental monitoring, plant abiotic and biotic stress management, and accelerating design-build-test-learn cycles of plant bioengineering. With the advent of synthetic biology, biological and molecular components derived from alternate natural organisms (e.g., microbes) and/or de novo parts have been used to build GEPBs. In this review, we summarize the framework for engineering different types of GEPBs. We then highlight representative validated biological components for building plant-based biosensors, along with various applications of plant-based biosensors in basic and applied plant science research. Finally, we discuss challenges and strategies for the identification and design of biological components for plant-based biosensors.

Prospects of genetics and breeding for low-phosphate tolerance: an integrated approach from soil to cell

Improving phosphorus (P) crop nutrition has emerged as a key factor toward achieving a more resilient and sustainable agriculture. P is an essential nutrient for plant development and reproduction, and phosphate (Pi)-based fertilizers represent one of the pillars that sustain food production systems. To meet the global food demand, the challenge for modern agriculture is to increase food production and improve food quality in a sustainable way by significantly optimizing Pi fertilizer use efficiency. The development of genetically improved crops with higher Pi uptake and Pi-use efficiency and higher adaptability to environments with low-Pi availability will play a crucial role toward this end. In this review, we summarize the current understanding of Pi nutrition and the regulation of Pi-starvation responses in plants, and provide new perspectives on how to harness the ample repertoire of genetic mechanisms behind these adaptive responses for crop improvement. We discuss on the potential of implementing more integrative, versatile, and effective strategies by incorporating systems biology approaches and tools such as genome editing and synthetic biology. These strategies will be invaluable for producing high-yielding crops that require reduced Pi fertilizer inputs and to develop a more sustainable global agriculture.

Leaf vein patterning is regulated by the aperture of plasmodesmata intercellular channels

To form tissue networks, animal cells migrate and interact through proteins protruding from their plasma membranes. Plant cells can do neither, yet plants form vein networks. How plants do so is unclear, but veins are thought to form by the coordinated action of the polar transport and signal transduction of the plant hormone auxin. However, plants inhibited in both pathways still form veins. Patterning of vascular cells into veins is instead prevented in mutants lacking the function of the GNOM (GN) regulator of auxin transport and signaling, suggesting the existence of at least one more GN-dependent vein-patterning pathway. Here we show that in Arabidopsis such a pathway depends on the movement of auxin or an auxin-dependent signal through plasmodesmata (PDs) intercellular channels. PD permeability is high where veins are forming, lowers between veins and nonvascular tissues, but remains high between vein cells. Impaired ability to regulate PD aperture leads to defects in auxin transport and signaling, ultimately leading to vein patterning defects that are enhanced by inhibition of auxin transport or signaling. GN controls PD aperture regulation, and simultaneous inhibition of auxin signaling, auxin transport, and regulated PD aperture phenocopies null gn mutants. Therefore, veins are patterned by the coordinated action of three GN-dependent pathways: auxin signaling, polar auxin transport, and movement of auxin or an auxin-dependent signal through PDs. Such a mechanism of tissue network formation is unprecedented in multicellular organisms.

How do plants form vein networks, in the absence of cellular migration or direct cell-cell interaction? This study shows that a GNOM-dependent combination of polar auxin transport, auxin signal transduction, and movement of an auxin signal through plasmodesmata patterns leaf vascular cells into veins.

Genetic Circuit Design in Rhizobacteria

Genetically engineered plants hold enormous promise for tackling global food security and agricultural sustainability challenges. However, construction of plant-based genetic circuitry is constrained by a lack of well-characterized genetic parts and circuit design rules. In contrast, advances in bacterial synthetic biology have yielded a wealth of sensors, actuators, and other tools that can be used to build bacterial circuitry. As root-colonizing bacteria (rhizobacteria) exert substantial influence over plant health and growth, genetic circuit design in these microorganisms can be used to indirectly engineer plants and accelerate the design-build-test-learn cycle. Here, we outline genetic parts and best practices for designing rhizobacterial circuits, with an emphasis on sensors, actuators, and chassis species that can be used to monitor/control rhizosphere and plant processes.