Maize (Zea mays L.) is an important crop that has been widely studied for its agronomic and industrial applications and is one of the main classical model organisms for genetic research. Agrobacterium-mediated transformation of immature maize embryos is a commonly used method to introduce transgenes, but a low transformation frequency remains a bottleneck for many gene-editing applications. Previous approaches to enhance transformation included the improvement of tissue culture media and the use of morphogenic regulators such as BABY BOOM and WUSCHEL2. Here, we show that the frequency can be increased using a pVS1-VIR2 virulence helper plasmid to improve T-DNA delivery, and/or expressing a fusion protein between a GROWTH-REGULATING FACTOR (GRF) and GRF-INTERACTING FACTOR (GIF) protein to improve regeneration. Using hygromycin as a selection agent to avoid escapes, the transformation frequency in the maize inbred line B104 significantly improved from 2.3 to 8.1% when using the pVS1-VIR2 helper vector with no effect on event quality regarding T-DNA copy number. Combined with a novel fusion protein between ZmGRF1 and ZmGIF1, transformation frequencies further improved another 3.5- to 6.5-fold with no obvious impact on plant growth, while simultaneously allowing efficient CRISPR-/Cas9-mediated gene editing. Our results demonstrate how a GRF-GIF chimera in conjunction with a ternary vector system has the potential to further improve the efficiency of gene-editing applications and molecular biology studies in maize.

Redox changes of pyridine nucleotides in cellular compartments are highly dynamic and their equilibria are under the influence of various reducing and oxidizing reactions. To obtain spatiotemporal data on pyridine nucleotides in living plant cells, typical biochemical approaches require cell destruction. To date, genetically encoded fluorescent biosensors are considered to be the best option to bridge the existing technology gap, as they provide a fast, accurate, and real-time readout. However, the existing pyridine nucleotides genetically encoded fluorescent biosensors are either sensitive to pH change or slow in dissociation rate. Herein, we employed the biosensors which generate readouts that are pH stable for in planta measurement of NADH/NAD+ ratio and NADPH level. We generated transgenic Arabidopsis lines that express these biosensors in plastid stroma and cytosol of whole plants and pollen tubes under the control of CaMV 35S and LAT52 promoters, respectively. These transgenic biosensor lines allow us to monitor real-time dynamic changes in NADH/NAD+ ratio and NADPH level in the plastids and cytosol of various plant tissues, including pollen tubes, root hairs, and mesophyll cells, using a variety of fluorescent instruments. We anticipate that these valuable transgenic lines may allow improvements in plant redox biology studies.

CRISPR/Cas9 is currently the most powerful tool to generate mutations in plant genomes and more efficient tools are needed as the scale of experiments increases. In the model plant Arabidopsis, the choice of the promoter driving Cas9 expression is critical to generate germline mutations. Several optimal promoters have been reported. However, it is unclear which promoter is ideal as they have not been thoroughly tested side by side. Furthermore, most plant vectors still use one of the two Cas9 nuclear localization sequence (NLS) configurations initially reported. We genotyped more than 6000 Arabidopsis T2 plants to test seven promoters and six types of NLSs across 14 targets to systematically improve the generation of single and multiplex inheritable mutations. We found that the RPS5A promoter and bipartite NLS were individually the most efficient components. When combined, 99% of T2 plants contained at least one knockout (KO) mutation and 84% contained 4- to 7-plex KOs, the highest multiplexing KO rate in Arabidopsis to date. These optimizations will be useful to generate higher-order KOs in the germline of Arabidopsis and will likely be applicable to other CRISPR systems as well.

Uncovering the function of phytopathogen effectors is crucial for understanding mechanisms of pathogen pathogenicity and for improving our ability to protect plants from diseases. An increasing number of effectors have been predicted in various plant pathogens. Functional characterization of these effectors has become a major focus in the study of plant-pathogen interactions. In this study, we designed a novel screening system that combines the TMV (tobacco mosaic virus)-GFP vector and Agrobacterium-mediated transient expression in the model plant Nicotiana benthamiana. This system enables the rapid identification of effectors that interfere with plant immunity. The biological function of these effectors can be easily evaluated by observing the GFP fluorescence signal using a UV lamp within just a few days. To evaluate the TMV-GFP system, we initially tested it with well-described virulence and avirulence type III effectors from the bacterial pathogen Ralstonia solanacearum. After proving the accuracy and efficiency of the TMV-GFP system, we successfully screened a novel virulence effector, RipS1, using this approach. Furthermore, using the TMV-GFP system, we reproduced consistent results with previously known cytoplasmic effectors from a diverse array of pathogens. Additionally, we demonstrated the effectiveness of the TMV-GFP system in identifying apoplastic effectors. The easy operation, time-saving nature, broad effectiveness, and low technical requirements of the TMV-GFP system make it a promising approach for high-throughput screening of effectors with immune interference activity from various pathogens.

Gibberellins (GAs) are major regulators of developmental and growth processes in plants. Using the degradation-based signaling mechanism of GAs, we have built transcriptional regulator (DELLA)-based, genetically encoded ratiometric biosensors as proxies for hormone quantification at high temporal resolution and sensitivity that allow dynamic, rapid and simple analysis in a plant cell system, i.e. Arabidopsis protoplasts. These ratiometric biosensors incorporate a DELLA protein as a degradation target fused to a firefly luciferase connected via a 2A peptide to a renilla luciferase as a co-expressed normalization element. We have implemented these biosensors for all five Arabidopsis DELLA proteins, GA-INSENSITIVE, GAI; REPRESSOR-of-ga1-3, RGA; RGA-like1, RGL1; RGL2 and RGL3, by applying a modular design. The sensors are highly sensitive (in the low pm range), specific and dynamic. As a proof of concept, we have tested the applicability in three domains: the study of substrate specificity and activity of putative GA-oxidases, the characterization of GA transporters, and the use as a discrimination platform coupled to a GA agonists\' chemical screening. This work demonstrates the development of a genetically encoded quantitative biosensor complementary to existing tools that allow the visualization of GA in planta.

Next-generation sequencing (NGS) library construction often involves using restriction enzymes to decrease genome complexity, enabling versatile polymorphism detection in plants. However, plant leaves frequently contain impurities, such as polyphenols, necessitating DNA purification before enzymatic reactions. To overcome this problem, we developed a PCR-based method for expeditious NGS library preparation, offering flexibility in number of detected polymorphisms. By substituting a segment of the simple sequence repeat sequence in the MIG-seq primer set (MIG-seq being a PCR method enabling library construction with low-quality DNA) with degenerate oligonucleotides, we introduced variability in detectable polymorphisms across various crops. This innovation, named degenerate oligonucleotide primer MIG-seq (dpMIG-seq), enabled a streamlined protocol for constructing dpMIG-seq libraries from unpurified DNA, which was implemented stably in several crop species, including fruit trees. Furthermore, dpMIG-seq facilitated efficient lineage selection in wheat and enabled linkage map construction and quantitative trait loci analysis in tomato, rice, and soybean without necessitating DNA concentration adjustments. These findings underscore the potential of the dpMIG-seq protocol for advancing genetic analyses across diverse plant species.

Confocal microscopy has greatly aided our understanding of the major cellular processes and trafficking pathways responsible for plant growth and development. However, a drawback of these studies is that they often rely on the manual analysis of a vast number of images, which is time-consuming, error-prone, and subject to bias. To overcome these limitations, we developed Dot Scanner, a Python program for analyzing the densities, lifetimes, and displacements of fluorescently tagged particles in an unbiased, automated, and efficient manner. Dot Scanner was validated by performing side-by-side analysis in Fiji-ImageJ of particles involved in cellulose biosynthesis. We found that the particle densities and lifetimes were comparable in both Dot Scanner and Fiji-ImageJ, verifying the accuracy of Dot Scanner. Dot Scanner largely outperforms Fiji-ImageJ, since it suffers far less selection bias when calculating particle lifetimes and is much more efficient at distinguishing between weak signals and background signal caused by bleaching. Not only does Dot Scanner obtain much more robust results, but it is a highly efficient program, since it automates much of the analyses, shortening workflow durations from weeks to minutes. This free and accessible program will be a highly advantageous tool for analyzing live-cell imaging in plants.

The cytosol-facing outer membrane (OM) of organelles communicates with other cellular compartments to exchange proteins, metabolites, and signaling molecules. Cellular surveillance systems also target OM-resident proteins to control organellar homeostasis and ensure cell survival under stress. However, the OM proximity proteomes have never been mapped in plant cells since using traditional approaches to discover OM proteins and identify their dynamically interacting partners remains challenging. In this study, we developed an OM proximity labeling (OMPL) system using biotin ligase-mediated proximity biotinylation to identify the proximity proteins of the OMs of mitochondria, chloroplasts, and peroxisomes in living Arabidopsis (Arabidopsis thaliana) cells. Using this approach, we mapped the OM proximity proteome of these three organelles under normal conditions and examined the effects of the ultraviolet-B (UV-B) or high light (HL) stress on the abundances of OM proximity proteins. We demonstrate the power of this system with the discovery of cytosolic factors and OM receptor candidates potentially involved in local protein translation and translocation. The candidate proteins that are involved in mitochondrion-peroxisome, mitochondrion-chloroplast, or peroxisome-chloroplast contacts, and in the organellar quality control system are also proposed based on OMPL analysis. OMPL-generated OM proximity proteomes are valuable sources of candidates for functional validation and suggest directions for further investigation of important questions in cell biology.

Phenotyping of model organisms grown on Petri plates is often carried out manually, despite the procedures being time-consuming and laborious. The main reason for this is the limited availability of automated phenotyping facilities, whereas constructing a custom automated solution can be a daunting task for biologists. Here, we describe SPIRO, the Smart Plate Imaging Robot, an automated platform that acquires time-lapse photographs of up to four vertically oriented Petri plates in a single experiment, corresponding to 192 seedlings for a typical root growth assay and up to 2500 seeds for a germination assay. SPIRO is catered specifically to biologists\' needs, requiring no engineering or programming expertise for assembly and operation. Its small footprint is optimized for standard incubators, the inbuilt green LED enables imaging under dark conditions, and remote control provides access to the data without interfering with sample growth. SPIRO\'s excellent image quality is suitable for automated image processing, which we demonstrate on the example of seed germination and root growth assays. Furthermore, the robot can be easily customized for specific uses, as all information about SPIRO is released under open-source licenses. Importantly, uninterrupted imaging allows considerably more precise assessment of seed germination parameters and root growth rates compared with manual assays. Moreover, SPIRO enables previously technically challenging assays such as phenotyping in the dark. We illustrate the benefits of SPIRO in proof-of-concept experiments which yielded a novel insight on the interplay between autophagy, nitrogen sensing, and photoblastic response.

Sorghum is an important crop for food, forage, wine and biofuel production. To enhance its transformation efficiency without negative developmental by-effects, we investigated the impact of GRF4-GIF1 chimaera and GRF5 on sorghum transformation. Both GRF4-GIF1 and GRF5 effectively improved the transformation efficiency of sorghum and accelerated the transformation process of sorghum to less than 2 months which was not observed when using BBM-WUS. As agrobacterium  effectors increase the ability of T-DNA transfer into plant cells, we checked whether ternary vector system can additively enhance sorghum transformation. The combination of GRF4-GIF1 with helper plasmid pVS1-VIR2 achieved the highest transformation efficiency, reaching 38.28%, which is 7.71-fold of the original method. Compared with BBM-WUS, overexpressing GRF4-GIF1 caused no noticeable growth defects in sorghum. We further developed a sorghum CRISPR/Cas9 gene-editing tool based on this GRF4-GIF1/ternary vector system, which achieved an average gene mutation efficiency of 41.36%, and null mutants were created in the T0 generation.