Measuring stomatal and guard cell metrics for plant physiology and growth using StoManager1.

Automated guard cell detection and measurement are vital for understanding plant physiological performance and ecological functioning in global water and carbon cycles. Most current methods for measuring guard cells and stomata are laborious, time-consuming, prone to bias, and limited in scale. We developed StoManager1, a high-throughput tool utilizing geometrical, mathematical algorithms, and convolutional neural networks to automatically detect, count, and measure over 30 guard cell and stomatal metrics, including guard cell and stomatal area, length, width, stomatal aperture area/guard cell area, orientation, stomatal evenness, divergence, and aggregation index. Combined with leaf functional traits, some of these StoManager1-measured guard cell and stomatal metrics explained 90% and 82% of tree biomass and intrinsic water use efficiency (iWUE) variances in hardwoods, making them substantial factors in leaf physiology and tree growth. StoManager1 demonstrated exceptional precision and recall (mAP@0.5 over 0.96), effectively capturing diverse stomatal properties across over 100 species. StoManager1 facilitates the automation of measuring leaf stomatal and guard cells, enabling broader exploration of stomatal control in plant growth and adaptation to environmental stress and climate change. This has implications for global gross primary productivity (GPP) modeling and estimation, as integrating stomatal metrics can enhance predictions of plant growth and resource usage worldwide. Easily accessible open-source code and standalone Windows executable applications are available on a GitHub repository (https://github.com/JiaxinWang123/StoManager1) and Zenodo (https://doi.org/10.5281/zenodo.7686022).

Auxin-dependent regulation of growth via rolB-induced modulation of the ROS metabolism in the long-term cultivated pRiA4-transformed Rubiacordifolia L. calli.

Gene transfer from Agrobacterium to plants is the best studied example of horizontal gene transfer (HGT) between prokaryotes and eukaryotes. The rol genes of A. rhizogenes (Rhizobium rhizogenes) provide uncontrolled root growth, or "hairy root" syndrome, the main diagnostic feature. In the present study, we investigated the stable pRiA4-transformed callus culture of Rubia cordifolia L. While untransformed callus cultures need PGRs (plant growth regulators) as an obligatory supplement, pRiA4 calli is able to achieve long-term PGR-free cultivation. For the first time, we described the pRiA4-transformed callus cultures' PGR-dependent ROS status, growth, and specialized metabolism. As we have shown, expression of the rolA and rolB but not the rolC genes is contradictory in a PGR-dependent manner. Moreover, a PGR-free pRiA4 transformed cell line is characterised as more anthraquinone (AQ) productive than an untransformed cell culture. These findings pertain to actual plant biotechnology: it could be the solution to troubles in choosing the best PGR combination for the cultivation of some rare, medicinal, and woody plants; wild-type Ri-plants and tissue cultures may become freed from legal controls on genetically modified organisms in the future. We propose possible PGR-dependent relationships between rolA and rolB as well as ROS signalling targets. The present study highlighted the high importance of the rolA gene in the regulation of combined rol gene effects and the large knowledge gap in rolA action.

Improved clearing method contributes to deep imaging of plant organs.

Tissue clearing methods are increasingly essential for the microscopic observation of internal tissues of thick biological organs. We previously developed TOMEI, a clearing method for plant tissues; however, it could not entirely remove chlorophylls nor reduce the fluorescent signal of fluorescent proteins. Here, we developed an improved TOMEI method (iTOMEI) to overcome these limitations. First, a caprylyl sulfobetaine was determined to efficiently remove chlorophylls from Arabidopsis thaliana seedlings without GFP quenching. Next, a weak alkaline solution restored GFP fluorescence, which was mainly lost during fixation, and an iohexol solution with a high refractive index increased sample transparency. These procedures were integrated to form iTOMEI. iTOMEI enables the detection of much brighter fluorescence than previous methods in tissues of A. thaliana, Oryza sativa, and Marchantia polymorpha. Moreover, a mouse brain was also efficiently cleared by the iTOMEI-Brain method within 48 h, and strong fluorescent signals were detected in the cleared brain.

Establishing an efficient protoplast transient expression system for investigation of floral thermogenesis in aroids.

KEY MESSAGE: Floral thermogenesis is an important reproductive strategy for attracting pollinators. We developed essential biological tools for studying floral thermogenesis using two species of thermogenic aroids, Symplocarpus renifolius and Alocasia odora. Aroids contain many species with intense heat-producing abilities in their inflorescences. Several genes have been proposed to be involved in thermogenesis of these species, but biological tools for gene functional analyses are lacking. In this study, we aimed to develop a protoplast-based transient expression (PTE) system for the study of thermogenic aroids. Initially, we focused on skunk cabbage (Symplocarpus renifolius) because of its ability to produce intense as well as durable heat. In this plant, leaf protoplasts were isolated from potted and shoot tip-cultured plants with high efficiency (ca. 1.0 × 105/g fresh weight), and more than half of these protoplasts were successfully transfected. Using this PTE system, we determined the protein localization of three mitochondrial energy-dissipating proteins, SrAOX, SrUCPA, and SrNDA1, fused to green fluorescent protein (GFP). These three GFP-fused proteins were localized in MitoTracker-stained mitochondria in leaf protoplasts, although the green fluorescent particles in protoplasts expressing SrUCPA-GFP were significantly enlarged. Finally, to assess whether the PTE system established in the leaves of S. renifolius is applicable for floral tissues of thermogenic aroids, inflorescences of S. renifolius and another thermogenic aroid (Alocasia odora) were used. Although protoplasts were successfully isolated from several tissues of the inflorescences, PTE systems worked well only for the protoplasts isolated from the female parts (slightly thermogenic or nonthermogenic) of A. odora inflorescences. Our developed system has a potential to be widely used in inflorescences as well as leaves in thermogenic aroids and therefore may be a useful biological tool for investigating floral thermogenesis.

REPRISAL: mapping lignification dynamics using chemistry, data segmentation, and ratiometric analysis.

This article describes a methodology for detailed mapping of the lignification capacity of plant cell walls that we have called "REPRISAL" for REPorter Ratiometrics Integrating Segmentation for Analyzing Lignification. REPRISAL consists of the combination of three separate approaches. In the first approach, H*, G*, and S* monolignol chemical reporters, corresponding to p-coumaryl alcohol, coniferyl alcohol, and sinapyl alcohol, are used to label the growing lignin polymer in a fluorescent triple labeling strategy based on the sequential use of three main bioorthogonal chemical reactions. In the second step, an automatic parametric and/or artificial intelligence segmentation algorithm is developed that assigns fluorescent image pixels to three distinct cell wall zones corresponding to cell corners, compound middle lamella and secondary cell walls. The last step corresponds to the exploitation of a ratiometric approach enabling statistical analyses of differences in monolignol reporter distribution (ratiometric method [RM] 1) and proportions (RM 2) within the different cell wall zones. We first describe the use of this methodology to map developmentally related changes in the lignification capacity of wild-type Arabidopsis (Arabidopsis thaliana) interfascicular fiber cells. We then apply REPRISAL to analyze the Arabidopsis peroxidase (PRX) mutant prx64 and provide further evidence for the implication of the AtPRX64 protein in floral stem lignification. In addition, we also demonstrate the general applicability of REPRISAL by using it to map lignification capacity in poplar (Populus tremula × Populus alba), flax (Linum usitatissimum), and maize (Zea mays). Finally, we show that the methodology can be used to map the incorporation of a fucose reporter into noncellulosic cell wall polymers.

Karyotype diversity in cultivated and wild Indian rice through EMA-based chromosome analysis.

India is known for its diverse cultivated and wild rice germplasm. In today's crop improvement programmes, wild relatives are much-needed genetic repository of valuable traits. Analysis of genetic diversity at the chromosomal level is one cost-effective tool to unlock foundational information related to genetics and plant breeding. Presently, enzymatic maceration and air-drying method (EMA) has been applied for the first time in six cultivated and nine wild Indian rice (diploid and tetraploid). EMA method following Giemsa staining has yielded large numbers of cytoplasm free metaphase plates with distinct chromosome morphology. Detailed analysis has revealed karyotype diversities in terms of total chromatin length (TCL), chromosome morphology and location of sat chromosomes within and between the studied species. Most of the cultivated rice has gained additional amount in TCL during the period of domestication in comparison to their progenitor Oryza nivara. Morphological clarity of the small chromosomes of rice was much required and has helped to identify individual chromosomes in the diverse karyotypes. Diversity in landmark SAT chromosomes is another important observation, not reported previously in Indian rice. Present study has shown that in most of the O. sativa members, the 10th pair contains SAT except one where 6th pair is satellited. On the other hand, diversity of SAT in diploid and tetraplod wild species has been recorded on 5th, 7th and 8th chromosome pairs and on 9th, 12th, 22nd and 23rd chromosome pairs, respectively. Karyomorphometric indices has helped to construct dendrogram to elucidate intraspecies and interspecies relationships. Untapped genetic diversity recorded in Indian rice through chromosomal analysis will be useful to the breeders and genome researchers.

Plant PhysioSpace: a robust tool to compare stress response across plant species.

Generalization of transcriptomics results can be achieved by comparison across experiments. This generalization is based on integration of interrelated transcriptomics studies into a compendium. Such a focus on the bigger picture enables both characterizations of the fate of an organism and distinction between generic and specific responses. Numerous methods for analyzing transcriptomics datasets exist. Yet, most of these methods focus on gene-wise dimension reduction to obtain marker genes and gene sets for, for example, pathway analysis. Relying only on isolated biological modules might result in missing important confounders and relevant contexts. We developed a method called Plant PhysioSpace, which enables researchers to compute experimental conditions across species and platforms without a priori reducing the reference information to specific gene sets. Plant PhysioSpace extracts physiologically relevant signatures from a reference dataset (i.e. a collection of public datasets) by integrating and transforming heterogeneous reference gene expression data into a set of physiology-specific patterns. New experimental data can be mapped to these patterns, resulting in similarity scores between the acquired data and the extracted compendium. Because of its robustness against platform bias and noise, Plant PhysioSpace can function as an inter-species or cross-platform similarity measure. We have demonstrated its success in translating stress responses between different species and platforms, including single-cell technologies. We have also implemented two R packages, one software and one data package, and a Shiny web application to facilitate access to our method and precomputed models.

Optical topometry and machine learning to rapidly phenotype stomatal patterning traits for maize QTL mapping.

Stomata are adjustable pores on leaf surfaces that regulate the tradeoff of CO2 uptake with water vapor loss, thus having critical roles in controlling photosynthetic carbon gain and plant water use. The lack of easy, rapid methods for phenotyping epidermal cell traits have limited discoveries about the genetic basis of stomatal patterning. A high-throughput epidermal cell phenotyping pipeline is presented here and used for quantitative trait loci (QTL) mapping in field-grown maize (Zea mays). The locations and sizes of stomatal complexes and pavement cells on images acquired by an optical topometer from mature leaves were automatically determined. Computer estimated stomatal complex density (SCD; R2 = 0.97) and stomatal complex area (SCA; R2 = 0.71) were strongly correlated with human measurements. Leaf gas exchange traits were genetically correlated with the dimensions and proportions of stomatal complexes (rg = 0.39-0.71) but did not correlate with SCD. Heritability of epidermal traits was moderate to high (h2 = 0.42-0.82) across two field seasons. Thirty-six QTL were consistently identified for a given trait in both years. Twenty-four clusters of overlapping QTL for multiple traits were identified, with univariate versus multivariate single marker analysis providing evidence consistent with pleiotropy in multiple cases. Putative orthologs of genes known to regulate stomatal patterning in Arabidopsis (Arabidopsis thaliana) were located within some, but not all, of these regions. This study demonstrates how discovery of the genetic basis for stomatal patterning can be accelerated in maize, a C4 model species where these processes are poorly understood.

iRegNet: an integrative Regulatory Network analysis tool for Arabidopsis thaliana.

Gene expression is delicately controlled via multilayered genetic and/or epigenetic regulatory mechanisms. Rapid development of the high-throughput sequencing (HTS) technology and its derivative methods including chromatin immunoprecipitation sequencing (ChIP-seq) and DNA affinity purification sequencing (DAP-seq) have generated a large volume of data on DNA-protein interactions (DPIs) and histone modifications on a genome-wide scale. However, the ability to comprehensively retrieve empirically validated upstream regulatory networks of genes of interest (GOIs) and genomic regions of interest (ROIs) remains limited. Here, we present integrative Regulatory Network (iRegNet), a web application that analyzes the upstream regulatory network for user-queried GOIs or ROIs in the Arabidopsis (Arabidopsis thaliana) genome. iRegNet covers the largest empirically proven DNA-binding profiles of Arabidopsis transcription factors (TFs) and non-TF proteins, and histone modifications obtained from all currently available Arabidopsis ChIP-seq and DAP-seq data. iRegNet not only catalogs upstream regulomes and epigenetic chromatin states for single-query gene/genomic region but also suggests significantly overrepresented upstream genetic regulators and epigenetic chromatin states of user-submitted multiple query genes/genomic regions. Furthermore, gene-to-gene coexpression index and protein-protein interaction information were also integrated into iRegNet for a more reliable identification of upstream regulators and realistic regulatory networks. Thus, iRegNet will help discover upstream regulators as well as molecular regulatory networks of GOI(s) and/or ROI(s), and is freely available at http://chromatindynamics.snu.ac.kr:8082/iRegNet_main.

GridFree: a python package of imageanalysis for interactive grain counting and measuring.

Grain characteristics, including kernel length, kernel width, and thousand kernel weight, are critical component traits for grain yield. Manual measurements and counting are expensive, forming the bottleneck for dissecting these traits' genetic architectures toward ultimate yield improvement. High-throughput phenotyping methods have been developed by analyzing images of kernels. However, segmenting kernels from the image background and noise artifacts or from other kernels positioned in close proximity remain as challenges. In this study, we developed a software package, named GridFree, to overcome these challenges. GridFree uses an unsupervised machine learning approach, K-Means, to segment kernels from the background by using principal component analysis on both raw image channels and their color indices. GridFree incorporates users' experiences as a dynamic criterion to set thresholds for a divide-and-combine strategy that effectively segments adjacent kernels. When adjacent multiple kernels are incorrectly segmented as a single object, they form an outlier on the distribution plot of kernel area, length, and width. GridFree uses the dynamic threshold settings for splitting and merging. In addition to counting, GridFree measures kernel length, width, and area with the option of scaling with a reference object. Evaluations against existing software programs demonstrated that GridFree had the smallest error on counting seeds for multiple crop species. GridFree was implemented in Python with a friendly graphical user interface to allow users to easily visualize the outcomes and make decisions, which ultimately eliminates time-consuming and repetitive manual labor. GridFree is freely available at the GridFree website (https://zzlab.net/GridFree).

DIRT/3D: 3D root phenotyping for field-grown maize (Zea mays).

The development of crops with deeper roots holds substantial promise to mitigate the consequences of climate change. Deeper roots are an essential factor to improve water uptake as a way to enhance crop resilience to drought, to increase nitrogen capture, to reduce fertilizer inputs, and to increase carbon sequestration from the atmosphere to improve soil organic fertility. A major bottleneck to achieving these improvements is high-throughput phenotyping to quantify root phenotypes of field-grown roots. We address this bottleneck with Digital Imaging of Root Traits (DIRT)/3D, an image-based 3D root phenotyping platform, which measures 18 architecture traits from mature field-grown maize (Zea mays) root crowns (RCs) excavated with the Shovelomics technique. DIRT/3D reliably computed all 18 traits, including distance between whorls and the number, angles, and diameters of nodal roots, on a test panel of 12 contrasting maize genotypes. The computed results were validated through comparison with manual measurements. Overall, we observed a coefficient of determination of r2>0.84 and a high broad-sense heritability of Hmean2> 0.6 for all but one trait. The average values of the 18 traits and a developed descriptor to characterize complete root architecture distinguished all genotypes. DIRT/3D is a step toward automated quantification of highly occluded maize RCs. Therefore, DIRT/3D supports breeders and root biologists in improving carbon sequestration and food security in the face of the adverse effects of climate change.

Gas exchange measurements in the unsteady state.

Leaf level gas exchange is a widely used technique that provides real-time measurement of leaf physiological properties, including CO2 assimilation (A), stomatal conductance to water vapour (gsw ) and intercellular CO2 (Ci ). Modern open-path gas exchange systems offer greater portability than the laboratory-built systems of the past and take advantage of high-precision infrared gas analyzers and optimized system design. However, the basic measurement paradigm has long required steady-state conditions for accurate measurement. For CO2 response curves, this requirement has meant that each point on the curve needs 1-3 min and a full response curve generally requires 20-35 min to obtain a sufficient number of points to estimate parameters such as the maximum velocity of carboxylation (Vc,max ) and the maximum rate of electron transport (Jmax ). For survey measurements, the steady-state requirement has meant that accurate measurement of assimilation has required about 1-2 min. However, steady-state conditions are not a strict prerequisite for accurate gas exchange measurements. Here, we present a new method, termed dynamic assimilation, that is based on first principles and allows for more rapid gas exchange measurements, helping to make the technique more useful for high throughput applications.

Identifying the scene of a crime through pollen analysis.

The forensic analysis of pollen involves the comparison of crime scene and reference pollen samples. Successful matches are frequently used to solve time- or location-related crimes. Despite its prospects in criminal investigation, forensic palynology is still underused in casework due to inherent shortcomings such as its limited evidential weighting, scarcity of skilled palynologists dedicated to forensic casework and the laborious nature of analytical procedures. To address these challenges, the current state-of-the-art in forensic palynology is transiting from the traditional light microscopic methods that dominated the early days of palynology to more contemporary approaches like Raman spectroscopy, stable isotope analysis and DNA metabarcoding. The major challenges of these methods, however, include a lack of optimisation to forensic expectations and the unavailability of robust databases to permit accurate data interpretation, and quests to resolve these problems constitute the theme of current research. While reiterating the usefulness of pollen analysis in criminal investigation, this report recommends orthogonal testing as a way of improving the evidential weighting of forensic palynology.

A Three-Dimensional Scanning System for Digital Archiving and Quantitative Evaluation of Arabidopsis Plant Architectures.

A plant's architecture contributes to its ability to acquire resources and reduce mechanical load. Arabidopsis thaliana is the most common model plant in molecular biology, and there are several mutants and transgenic lines with modified plant architecture regulation, such as lazy1 mutants, which have reversed angles of lateral branches. Although some phenotyping methods have been used in larger agricultural plants, limited suitable methods are available for three-dimensional reconstruction of Arabidopsis, which is smaller and has more uniform surface textures and structures. An inexpensive, easily adopted three-dimensional reconstruction system that can be used for Arabidopsis is needed so that researchers can view and quantify morphological changes over time. We developed a three-dimensional reconstruction system for A. thaliana using the visual volume intersection method, which uses a fixed camera to capture plant images from multiple directions while the plant slowly rotates. We then developed a script to autogenerate stack images from the obtained input movie and visualized the plant architecture by rendering the output stack image using the general bioimage analysis software. We successfully three-dimensionally and time-sequentially scanned wild-type and lazy1 mutant A. thaliana plants and measured the angles of the lateral branches. This non-contact, non-destructive method requires no specialized equipment and is space efficient, inexpensive and easily adopted by Arabidopsis researchers. Consequently, this system will promote three- and four-dimensional phenotyping of this model plant, and it can be used in combination with molecular genetics to further elucidate the molecular mechanisms that regulate Arabidopsis architecture.

A solid-state nanopore-based single-molecule approach for label-free characterization of plant polysaccharides.

Polysaccharides are important biomacromolecules existing in all plants, most of which are integrated into a fibrillar structure called the cell wall. In the absence of an effective methodology for polysaccharide analysis that arises from compositional heterogeneity and structural flexibility, our knowledge of cell wall architecture and function is greatly constrained. Here, we develop a single-molecule approach for identifying plant polysaccharides with acetylated modification levels. We designed a solid-state nanopore sensor supported by a free-standing SiN x membrane in fluidic cells. This device was able to detect cell wall polysaccharide xylans at concentrations as low as 5 ng/µL and discriminate xylans with hyperacetylated and unacetylated modifications. We further demonstrated the capability of this method in distinguishing arabinoxylan and glucuronoxylan in monocot and dicot plants. Combining the data for categorizing polysaccharide mixtures, our study establishes a single-molecule platform for polysaccharide analysis, opening a new avenue for understanding cell wall structures, and expanding polysaccharide applications.

Proximity labeling: an emerging tool for probing in planta molecular interactions.

Protein-protein interaction (PPI) networks are key to nearly all aspects of cellular activity. Therefore, the identification of PPIs is important for understanding a specific biological process in an organism. Compared with conventional methods for probing PPIs, the recently described proximity labeling (PL) approach combined with mass spectrometry (MS)-based quantitative proteomics has emerged as a powerful approach for characterizing PPIs. However, the application of PL in planta remains in its infancy. Here, we summarize recent progress in PL and its potential utilization in plant biology. We specifically summarize advances in PL, including the development and comparison of different PL enzymes and the application of PL for deciphering various molecular interactions in different organisms with an emphasis on plant systems.

Proposal of an index of stability for evaluating plant drought memory: A case study in sugarcane.

Stability is a key trait for plant growth and development in a changing environment, involving homeostasis and resilience. While homeostasis refers to the maintenance of the internal structural and functional plant integrity, resilience is associated with the plant ability in returning to the initial conditions after a given disturbance. Such concepts are especially relevant for perennial and semi-perennial plants facing seasonal and frequent stress conditions. Although plant memory is closely associated with plant performance under recurrent stresses, to date, there is no study evaluating how stress memory is linked to stability under varying water conditions. Herein, we evaluated the association between drought stability and memory in sugarcane plants and proposed a new stability index to evaluate plant memory. Two datasets were analyzed, the first deals with leaf gas exchange and photochemistry of sugarcane plants grown in nutrient solution and exposed to one, two or three water deficit cycles. The second takes into account the physiological performance of sugarcane propagules obtained by vegetative propagation from plants that faced drought. To quantify sugarcane stability, we estimated the drought impact, the disturbance rate (DR), drought perturbation, and recovery rate (RR) for plants from both datasets. Drought memory - given by improved performance after previous stress events or when origin material faced drought - was detected in both datasets, changing either DR or RR. Based on these indices, we proposed the overall stability (OSt), defined as the ratio between RR and DR. While DR is associated to plant homeostasis, RR is a measure of plant resilience. Sugarcane plants exposed to three cycles of water deficit or those propagules originated from stressed plants presented the highest OSt values, showing higher RR and/or lower DR when compared to well-watered plants or to propagules from well-watered plants. Regarding the physiological traits evaluated, leaf CO2 assimilation and stomatal conductance were the most consistent variables in revealing drought stability and memory. Concluding, OSt revealed consistently patterns of response associated with plant memory, besides quantifying plant stability under stressful conditions.