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).

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.

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.

Split-HaloTag imaging assay for sophisticated microscopy of protein-protein interactions in planta.

An ever-increasing number of intracellular multi-protein networks have been identified in plant cells. Split-GFP-based protein-protein interaction assays combine the advantages of in vivo interaction studies in a native environment with additional visualization of protein complex localization. Because of their simple protocols, they have become some of the most frequently used methods. However, standard fluorescent proteins present several drawbacks for sophisticated microscopy. With the HaloTag system, these drawbacks can be overcome, as this reporter forms covalent irreversible bonds with synthetic photostable fluorescent ligands. Dyes can be used in adjustable concentrations and are suitable for advanced microscopy methods. Therefore, we have established the Split-HaloTag imaging assay in plants, which is based on the reconstitution of a functional HaloTag protein upon protein-protein interaction and the subsequent covalent binding of an added fluorescent ligand. Its suitability and robustness were demonstrated using a well-characterized interaction as an example of protein-protein interaction at cellular structures: the anchoring of the molybdenum cofactor biosynthesis complex to filamentous actin. In addition, a specific interaction was visualized in a more distinctive manner with subdiffractional polarization microscopy, Airyscan, and structured illumination microscopy to provide examples of sophisticated imaging. Split-GFP and Split-HaloTag can complement one another, as Split-HaloTag represents an alternative option and an addition to the large toolbox of in vivo methods. Therefore, this promising new Split-HaloTag imaging assay provides a unique and sensitive approach for more detailed characterization of protein-protein interactions using specific microscopy techniques, such as 3D imaging, single-molecule tracking, and super-resolution microscopy.

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.

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).

Drone-based physiological index reveals long-term acclimation and drought stress responses in trees.

Monitoring early tree physiological responses to drought is key to understanding progressive impacts of drought on forests and identifying resilient species. We combined drone-based multispectral remote sensing with measurements of tree physiology and environmental parameters over two growing seasons in a 100-y-old Pinus sylvestris forest subject to 17-y of precipitation manipulation. Our goal was to determine if drone-based photochemical reflectance index (PRI) captures tree drought stress responses and whether responses are affected by long-term acclimation. PRI detects changes in xanthophyll cycle pigment dynamics, which reflect increases in photoprotective non-photochemical quenching activity resulting from drought-induced photosynthesis downregulation. Here, PRI of never-irrigated trees was up to 10 times lower (higher stress) than PRI of irrigated trees. Long-term acclimation to experimental treatment, however, influenced the seasonal relationship between PRI and soil water availability. PRI also captured diurnal decreases in photochemical efficiency, driven by vapour pressure deficit. Interestingly, 5 years after irrigation was stopped for a subset of the irrigated trees, a positive legacy effect persisted, with lower stress responses (higher PRI) compared with never-irrigated trees. This study demonstrates the ability of remotely sensed PRI to scale tree physiological responses to an entire forest and the importance of long-term acclimation in determining current drought stress responses.

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.

Assembly of a simple scalable device for micromechanical testing of plant tissues.

Tensile testing is widely used to evaluate the mechanical properties of biological materials including soft primary plant tissues. Commercially available platforms for tensile testing are often expensive and limited in customizability. In this chapter, we provide a guide for the assembly and use of a simple and low-cost micromechanical testing apparatus suitable for research and educational purposes. The build of the setup is presented with scalability and universality in mind and is based on a do-it-yourself mind frame towards mechanical tests on plant organs and tissues. We discuss hardware and software requirements with practical details on required components, device calibration and a script to run the device. Further, we provide an example in which the device was used for the uniaxial tensile test of onion epidermis.

Saving time maintaining reliability: a new method for quantification of Tetranychus urticae damage in Arabidopsis whole rosettes.

BACKGROUND: The model species Tetranychus urticae produces important plant injury and economic losses in the field. The current accepted method for the quantification of the spider mite damage in Arabidopsis whole rosettes is time consuming and entails a bottleneck for large-scale studies such as mutant screening or quantitative genetic analyses. Here, we describe an improved version of the existing method by designing an automatic protocol. The accuracy, precision, reproducibility and concordance of the new enhanced approach are validated in two Arabidopsis accessions with opposite damage phenotypes. Results are compared to the currently available manual method. RESULTS: Image acquisition experiments revealed that the automatic settings plus 10 values of brightness and the black background are the optimal conditions for a specific recognition of spider mite damage by software programs. Among the different tested methods, the Ilastik-Fiji tandem based on machine learning was the best procedure able to quantify the damage maintaining the differential range of damage between accessions. In addition, the Ilastik-Fiji tandem method showed the lowest variability within a set of conditions and the highest stability under different lighting or background surroundings. Bland-Altman concordance results pointed out a negative value for Ilastik-Fiji, which implies a minor estimation of the damage when compared to the manual standard method. CONCLUSIONS: The novel approach using Ilastik and Fiji programs entails a great improvement for the quantification of the specific spider mite damage in Arabidopsis whole rosettes. The automation of the proposed method based on interactive machine learning eliminates the subjectivity and inter-rater-variability of the previous manual protocol. Besides, this method offers a robust tool for time saving and to avoid the damage overestimation observed with other methods.

Hydroprinted Liquid-Alloy-Based Morphing Electronics for Fast-Growing/Tender Plants: From Physiology Monitoring to Habit Manipulation.

Monitoring physiological signals and manipulating growth habits of living plants in real time are important for botany research, biohybrid plant robots, and precision agriculture. Although emerging epidermal electronics that can conveniently acquire vital signals of living organisms exhibit a high potential for such scenarios, it is a significant challenge to adapt such devices for plants, because they are fragile and usually have complex surfaces that can change significantly during rapid growth. A gentle fabrication process is critical in order to employ compliant electronic systems to adapt to this highly dynamic situation. In this study, a hydroprinted liquid-alloy-based morphing electronics (LAME) process is employed for fast-growing plants that will sense physiological signals and even function as a biohybrid to determine plant behavior on demand. Besides various surfaces of inorganic targeting substrates, pinning liquid alloy circuits onto the complex plant epidermis is enhanced by introducing high-surface-energy liquid. Functionally, the new developed LAME can be used to monitor leaf moisture content and length, and manipulate leaf and bean sprout orientation. This study lays the foundation for a new form of morphing electronics for botany or biohybrid plant robots, potentially impacting the next generation of precision agriculture and smart hybrid robots.

Visualising spatio-temporal distributions of assimilated carbon translocation and release in root systems of leguminous plants.

The release of rhizodeposits differs depending on the root position and is closely related to the assimilated carbon (C) supply. Therefore, quantifying the C partitioning over a short period may provide crucial information for clarifying root-soil carbon metabolism. A non-invasive method for visualising the translocation of recently assimilated C into the root system inside the rhizobox was established using 11CO2 labelling and the positron-emitting tracer imaging system. The spatial distribution of recent 11C-photoassimilates translocated and released in the root system and soil were visualised for white lupin (Lupinus albus) and soybean (Glycine max). The inputs of the recently assimilated C in the entire root that were released into the soil were approximately 0.3%-2.9% for white lupin within 90 min and 0.9%-2.3% for soybean within 65 min, with no significant differences between the two plant species; however, the recently assimilated C of lupin was released at high concentrations in specific areas (hotspots), whereas that of soybean was released uniformly in the soil. Our method enabled the quantification of the spatial C allocations in roots and soil, which may help to elucidate the relationship between C metabolism and nutrient cycling at specific locations of the root-soil system in response to environmental conditions over relatively short periods.

Using Different Forms of Nitrogen to Study Hypersensitive Response Elicited by Avirulent Pseudomonas syringae.

Nitrate, ammonium, or a combination of both is the form of N available for nitrogen assimilation from soil by the plants. Nitrogen is an important and integral part of amino acids, nucleotides, and defense molecules. Hence it is very important to study the role of nitrate and ammonium nutrition in plant defense via hypersensitive response (HR). Shifting plants from ammonium nitrate Hoagland solution to nitrate Hoagland nutrition slightly enhances root length and leaf area. HR phenotype is different in nitrate and ammonium grown plants when challenged with avirulent Pseudomonas syringae DC3000 avrRpm1. HR is also associated with increased production of reactive oxygen species (ROS) and nitric oxide (NO). Hence to understand HR development it is essential to measure HR lesions, cell death, ROS, NO, and bacterial growth. Here we provide a stepwise protocol of various parameters to study HR in Arabidopsis in response to nitrate and ammonium nutrition.

A novel approach for real-time monitoring of leaf wounding responses demonstrates unprecedently fast and high emissions of volatiles from cut leaves.

Wounding is a key plant stress that results in a rapid, within seconds to a few minutes, release of ubiquitous stress volatiles and stored volatiles in species with storage structures. Understanding the timing and extent of wound-dependent volatile elicitation is needed to gain an insight into different emission controls, but real-time monitoring of plant emissions through wounding treatments has been hampered by the need to stop the measurements to perform the wounding, slow stabilization of gas flows upon chamber closure and smearing out the signal by large chambers and long sampling lines. We developed a novel leaf cutter that allows to rapidly perform highly precise leaf cuts within the leaf chamber. The cutter was fitted to the standard Walz GFS-3000 portable gas-exchange system leaf chamber and chamber exhaust air for analysis with a proton transfer reaction time-of-flight mass-spectrometer (PTR-TOF-MS) was taken right at the leaf chamber outlet. Wounding experiments in four species of contrasting leaf structure demonstrated significant species differences in timing, extent and blend of emitted volatiles, and showed unprecedently high emission rates of several stress volatiles and stored monoterpenes. In light of the rapid rise of release of de novo synthesized and stored volatiles, the results of this study suggest that past studies have underestimated the rate of elicitation and maximum emission rates of wound-dependent volatiles.

An improved centrifuge method for determining water extraction curves and vulnerability curves in the long-vessel species Robinia pseudoacacia.

Significant improvements to the centrifuge water-extraction method of measuring the percentage loss volume of water (PLV) and corresponding vulnerability curves (VCs) are reported. Cochard and Sperry rotors are both incapable of measuring the VCs of species with long vessels because of premature embolism induced by hypothetical nanoparticles that can be drawn into segments during flow measurement. In contrast, water extraction pushes nanoparticles out of the sample. This study focuses on a long-vessel species, Robinia pseudoacacia, for which many VCs have been constructed by different methods, and the daily water relations have been quantified. PLV extraction curves have dual Weibull curves, and this paper focuses on the second Weibull curve because it involves the extraction of water from vessels, as proven by staining methods. We demonstrate an improved water extraction method after evaporation correction that has accuracy to within 0.5%, shows good agreement with two traditional methods that are slower and less accurate, and is immune to nanoparticle artefacts. Using Poiseuille's Law and the geometry of vessels, we argue that the percentage loss of conductivity (PLC) equals 2PLV-PLV2 in a special case where all vessels, regardless of size, have the same vulnerability curve. In this special case, this equation predicts the data reasonably well.

Multi-species test and calibration of an improved transient thermal dissipation system of sap flow measurement with a single probe.

Transient thermal dissipation (TTD) systems provide a simple way to measure xylem sap flow with dual or single Granier-type probe, which gives lower energy consumption and higher accuracy due to its lessor sensitivity to thermal interferences. A new system, TTD heat within 5 min (TTD5), proposed on the reduction of the heating duration. This evolution captured interest through decreased energy consumption and increased temporal resolution. Within our study, the first objective was to test and calibrate this new system with a single probe for young rubber tree - Hevea brasiliensis. The second objective was to explore the sources of variability in calibration such as species, individual cut-stems and probe-wood contact. The complementary species consisted of two diffuse-porous species (mango tree - Mangifera indica, eucalyptus tree - Eucalyptus camaldulensis) and one ring-porous species (teak tree - Tectonia grandis). Twenty-eight response curves were assessed over a large range of flux densities from 0.5 to 10 l dm-2 h-1. The incremental rise of temperature from 30 to 300 s (T300-30) after commencement of heating was sensitive to flux density over the complete range. Compared with the full signal at 300 s, the incremental signal markedly reduced the variability between response curves within species and between species. Moreover, a new index K2, defined as (T0 - Tu)/T0, normalized the responses between 0 and 1. However, the responses had a non-linear trend above 5 l dm-2 h-1. Within diffuse-porous wood type, the species did not differ in calibration, whereas the ring-porous species was markedly different. A sigmoid function provided the best fit for the diffuse-porous species. Individual stems were identified as the main source of within-species variability in calibration. The normalizing K2 index removed the influence of probe-wood contacts, controlled through drilling difference; however, there was still an effect of individual stems interacting with flux density (P = 0.019). Replications of cut-stems and response curves are necessary to assess a reliable averaged calibration. In conclusion, the applicability of the TTD5 system with a single probe has been confirmed and several sources of variability in calibration have been evaluated.

Depolarizing metrics for plant samples imaging.

Optical methods, as fluorescence microscopy or hyperspectral imaging, are commonly used for plants visualization and characterization. Another powerful collection of optical techniques is the so-called polarimetry, widely used to enhance image contrast in multiple applications. In the botanical applications framework, in spite of some works have already highlighted the depolarizing print that plant structures left on input polarized beams, the potential of polarimetric methods has not been properly exploited. In fact, among the few works dealing with polarization and plants, most of them study light scattered by plants using the Degree of Polarization (DoP) indicator. Other more powerful depolarization metrics are nowadays neglected. In this context, we highlight the potential of different depolarization metrics obtained using the Mueller matrix (MM) measurement: the Depolarization Index and the Indices of Polarimetric Purity. We perform a qualitative and quantitative comparison between DoP- and MM-based images by studying a particular plant, the Hedera maroccana. We show how Mueller-based metrics are generally more suitable in terms of contrast than DoP-based measurements. The potential of polarimetric measurements in the study of plants is highlighted in this work, suggesting they can be applied to the characterization of plants, plant taxonomy, water stress in plants, and other botanical studies.