In-Depth Quantification of Cell Division and Elongation Dynamics at the Tip of Growing Arabidopsis Roots Using 4D Microscopy, AI-Assisted Image Processing and Data Sonification

Computational modeling of plant root development: the art and the science

Plant root development, like any developmental process, arises from the interplay between processes like gene expression, cell-cell signaling, cell growth and division, and tissue mechanics, which unfold over a wide range of temporal and spatial scales. Computational models are uniquely suited to integrate these different processes and spatio-temporal scales to investigate how their interplay determines developmental outcomes and have become part of mainstream plant developmental research. Still, for non-modeling experts, it often remains unclear how models are built, why a particular modeling approach was chosen, and how to interpret and value model outcomes. This review attempts to explain the science behind the art of model building, illustrating the simplifications that are often made to keep models simple to understand and when these are and are not justified. Similarly, it discusses when it is safe to ignore certain processes like growth or tissue mechanics and when it is not. Additionally, this review discusses a range of major breakthrough modeling articles. Their approaches are linked to classical concepts and models in developmental biology like the French flag positional information gradient of Lewis Wolpert and the repetitive patterning mechanism proposed by Turing, in addition to highlighting the lessons they taught us on plant root development.

Necessity for modeling hormonal crosstalk in arabidopsis root development?

Hormones play vital roles in plant root development. Mathematical models have been employed to study hormone functions. However, models developed by different research groups focus on different aspects of hormones and therefore cannot be used to study root growth as an integrative system that involves the functions of all hormones. To use modeling to study root development, the crosstalk nature of hormones requires the further development of mathematical models to understand their interplay in the context of diverse experimental data. This opinion article discusses what new insights can be developed by modeling hormonal crosstalk beyond experimental data. We propose that one integrative model should be developed to integrate all experimental data for elucidating root growth.

Deep learning image analysis for continuous single-cell imaging of dynamic processes in Plasmodium falciparum-infected erythrocytes

Continuous high-resolution imaging of the disease-mediating blood stages of the human malaria parasite Plasmodium falciparum faces challenges due to photosensitivity, small parasite size, and the anisotropy and large refractive index of host erythrocytes. Previous studies often relied on snapshot galleries from multiple cells, limiting the investigation of dynamic cellular processes. We present a workflow enabling continuous, single-cell monitoring of live parasites throughout the 48-hour intraerythrocytic life cycle with high spatial and temporal resolution. This approach integrates label-free, three-dimensional differential interference contrast and fluorescence imaging using an Airyscan microscope, automated cell segmentation through pre-trained deep-learning algorithms, and 3D rendering for visualization and time-resolved analyses. As a proof of concept, we applied this workflow to study knob-associated histidine-rich protein (KAHRP) export into the erythrocyte compartment and its clustering beneath the plasma membrane. Our methodology opens avenues for in-depth exploration of dynamic cellular processes in malaria parasites, providing a valuable tool for further investigations.

Shaping root architecture: towards understanding the mechanisms involved in lateral root development

Plants have an amazing ability to adapt to their environment, and this extends beyond biochemical responses and includes developmental changes that help them better exploit resources and survive. The plasticity observed in individual plant morphology is associated with robust developmental pathways that are influenced by environmental factors. However, there is still much to learn about the mechanisms behind the formation of the root system. In Arabidopsis thaliana, the root system displays a hierarchical structure with primary and secondary roots. The process of lateral root (LR) organogenesis involves multiple steps, including LR pre-patterning, LR initiation, LR outgrowth, and LR emergence. The study of root developmental plasticity in Arabidopsis has led to significant progress in understanding the mechanisms governing lateral root formation. The importance of root system architecture lies in its ability to shape the distribution of roots in the soil, which affects the plant's ability to acquire nutrients and water. In Arabidopsis, lateral roots originate from pericycle cells adjacent to the xylem poles known as the xylem-pole-pericycle (XPP). The positioning of LRs along the primary root is underpinned by a repetitive pre-patterning mechanism that establishes primed sites for future lateral root formation. In a subset of primed cells, the memory of a transient priming stimulus leads to the formation of stable pre-branch sites and the establishment of founder cell identity. These founder cells undergo a series of highly organized periclinal and anticlinal cell divisions and expansion to form lateral root primordia. Subsequently, LRP emerges through three overlying cell layers of the primary root, giving rise to fully developed LRs. In addition to LRs Arabidopsis can also develop adventitious lateral roots from the primary root in response to specific stress signals such as wounding or environmental cues. Overall, this review creates an overview of the mechanisms governing root lateral root formation which can be a stepping stone to improved crop yields and a better understanding of plant adaptation to changing environments.

Mucilage secretion from the root cap requires the NAC family transcription factor BEARSKIN2

The root cap secretes mucilage and sheds border cells (border-like cells, BLCs) in Arabidopsis (Arabidopsis thaliana). These mucilage and root cap-derived cells form a defensive barrier against soil pathogens. BEARSKIN1 (BRN1) and BRN2 are 2 homologous NAM, ATAF1/2, and CUC2 (NAC) family transcription factors of Arabidopsis, and mucilage secretion is inhibited in the brn1/2 double mutant. BRN1 and BRN2 are also involved in the expression of a pectin-digesting enzyme, POLYGALACTURONASE (RCPG), that facilitates BLC shedding. To further explore the connection between mucilage secretion and BLC shedding, we examined mucilage production in Arabidopsis lines displaying altered BLC detachment. Inactivation of BRN2 blocked mucilage synthesis and secretion, while inactivation of BRN1 and RCPG did not. Interestingly, RCPG sorted into mucilage-carrying vesicles budding from the Golgi and inhibited mucilage secretion in brn2-delayed BLC detachment. The root cap of a germinating seedling is initially covered with a cuticle, which is replaced by mucilage from BLCs as the seedling begins to shed these cells. Ectopic expression of RCPG in germinating seedlings caused early BLC formation and accelerated the cuticle-to-mucilage transition, indicating that RCPG expression and mucilage secretion are co-regulated. Furthermore, brn2 roots exhibited slower growth and increased cell death when subjected to salt or osmotic stress. Our research suggests that BRN2-mediated mucilage secretion contributes to BLC release to build an extracellular defense zone surrounding the root cap.

Effect of solution pH on root architecture of four apple rootstocks grown in an aeroponics nutrient misting system

The pH of the solution in the rhizosphere is an important factor that determines the availability and mobility of nutrients for plant uptake. Solution pH may also affect the root distribution and architecture of apple rootstocks. In this study, we evaluated the effect of solution pH on root system development of apple rootstocks using an aeroponics system designed and developed at Cornell AgriTech Geneva, USA. Four Geneva® apple rootstocks (G.210, G.214, G.41, and G.890) were grown in an aeroponic system under nutrient solution misting featuring continuously adjusted pH levels to three pH treatments (5.5, 6.5, and 8.0). Root development was monitored for 30 days and evaluated regularly for distribution and root mass. Images of the developed roots grown in the aeroponic system were collected at the end of the experiment using a high-resolution camera and analyzed using GiA Roots® software, which generates root architecture parameter values in a semi-automated fashion. The resulting root architecture analysis showed that the Geneva® rootstocks were significantly different for two architecture parameters. The length-to-width ratio analysis represented by two GiA Roots parameters (minor-to-major ellipse ratio and network width-to-depth ratio) showed that G.210 was flatter than G.890, which had a greater tendency to grow downward. Rootstocks G.214 and G.41 displayed similar growth values. The solution pH affected most root architecture parameter measurements where overall root growth was higher at pH 8 than at pH 5.5 and 6.5, which showed similar growth. In general, the average root width tended to decrease at higher pH values. While there were no significant differences in the leaf nutrient concentrations of P, K, Ca, Mg, S, B, Zn, Cu, and Fe within the four rootstocks, the pH level of the solution had a significant effect on P, Ca, and Mn. This study is the first of its kind to investigate the effect of pH on root architecture in a soil-free (aeroponic) environment and may have implications for apple root behavior under field conditions where pH levels are different.