From Stained Plant Tissues to Quantitative Cell Segmentation Analysis with MorphoGraphX

Soybean symbiotic-nodule zonation and cell differentiation are defined by NIN2 signaling and GH3-dependent auxin homeostasis

Symbiotic nodules comprise two classes, indeterminate and determinate, defined by the presence/absence of apical meristem and developmental zonation. Why meristem and zonation are absent from determinate nodules remains unclear. Here, we define cell types in developing soybean nodules, highlighting the undifferentiated infection zones and differentiated nitrogen-fixation zones. Auxin governs infection zone maintenance. GRETCHEN HAGEN 3 (GH3) enzymes deactivate auxin by conjugation and promote cell differentiation. gh3 mutants increased undifferentiated cells and enlarged infection zones. The central symbiosis-transcription factor NIN2a activates GH3.1 to reduce auxin levels and facilitates cell differentiation. High auxin promotes NIN2a protein accumulation and enhances signaling, further deactivating auxin and depleting infection zones. Our findings shed light on the NIN2a-GH3-auxin module that drives soybean nodule cell differentiation. This study challenges our understanding of determinate nodule development and proposes that the regulation of nodule zonation offers valuable insights into broader mechanisms of cell differentiation across plant species.

Auxin-dependent control of cytoskeleton and cell shape regulates division orientation in the Arabidopsis embryo

Premitotic control of cell division orientation is critical for plant development, as cell walls prevent extensive cell remodeling or migration. While many divisions are proliferative and add cells to existing tissues, some divisions are formative and generate new tissue layers or growth axes. Such formative divisions are often asymmetric in nature, producing daughters with different fates. We have previously shown that, in the Arabidopsis thaliana embryo, developmental asymmetry is correlated with geometric asymmetry, creating daughter cells of unequal volume. Such divisions are generated by division planes that deviate from a default “minimal surface area” rule. Inhibition of auxin response leads to reversal to this default, yet the mechanisms underlying division plane choice in the embryo have been unclear. Here, we show that auxin-dependent division plane control involves alterations in cell geometry, but not in cell polarity axis or nuclear position. Through transcriptome profiling, we find that auxin regulates genes controlling cell wall and cytoskeleton properties. We confirm the involvement of microtubule (MT)-binding proteins in embryo division control. Organization of both MT and actin cytoskeleton depends on auxin response, and genetically controlled MT or actin depolymerization in embryos leads to disruption of asymmetric divisions, including reversion to the default. Our work shows how auxin-dependent control of MT and actin cytoskeleton properties interacts with cell geometry to generate asymmetric divisions during the earliest steps in plant development.

•

Auxin responses regulate directional cell expansion in Arabidopsis embryos

•

Cell shape and division orientation are tightly coupled

•

Transcriptome analysis identifies MT-associated IQD proteins in division control

•

Cytoskeletal dynamics control division orientation

A reflux-and-growth mechanism explains oscillatory patterning of lateral root branching sites

Modular, repetitive structures are a key component of complex multicellular body plans across the tree of life. Typically, these structures are prepatterned by temporal oscillations in gene expression or signaling. Although a clock-and-wavefront mechanism was identified and plant leaf phyllotaxis arises from a Turing-type patterning for vertebrate somitogenesis and arthropod segmentation, the mechanism underlying lateral root patterning has remained elusive. To resolve this enigma, we combined computational modeling with in planta experiments. Intriguingly, auxin oscillations automatically emerge in our model from the interplay between a reflux-loop-generated auxin loading zone and stem-cell-driven growth dynamics generating periodic cell-size variations. In contrast to the clock-and-wavefront mechanism and Turing patterning, the uncovered mechanism predicts both frequency and spacing of lateral-root-forming sites to positively correlate with root meristem growth. We validate this prediction experimentally. Combined, our model and experimental results support that a reflux-and-growth patterning mechanism underlies lateral root priming.

A Sight on Single-Cell Transcriptomics in Plants Through the Prism of Cell-Based Computational Modeling Approaches: Benefits and Challenges for Data Analysis

Single-cell technology is a relatively new and promising way to obtain high-resolution transcriptomic data mostly used for animals during the last decade. However, several scientific groups developed and applied the protocols for some plant tissues. Together with deeply-developed cell-resolution imaging techniques, this achievement opens up new horizons for studying the complex mechanisms of plant tissue architecture formation. While the opportunities for integrating data from transcriptomic to morphogenetic levels in a unified system still present several difficulties, plant tissues have some additional peculiarities. One of the plants' features is that cell-to-cell communication topology through plasmodesmata forms during tissue growth and morphogenesis and results in mutual regulation of expression between neighboring cells affecting internal processes and cell domain development. Undoubtedly, we must take this fact into account when analyzing single-cell transcriptomic data. Cell-based computational modeling approaches successfully used in plant morphogenesis studies promise to be an efficient way to summarize such novel multiscale data. The inverse problem's solutions for these models computed on the real tissue templates can shed light on the restoration of individual cells' spatial localization in the initial plant organ-one of the most ambiguous and challenging stages in single-cell transcriptomic data analysis. This review summarizes new opportunities for advanced plant morphogenesis models, which become possible thanks to single-cell transcriptome data. Besides, we show the prospects of microscopy and cell-resolution imaging techniques to solve several spatial problems in single-cell transcriptomic data analysis and enhance the hybrid modeling framework opportunities.