Probing stress-regulated ordering of the plant cortical microtubule array via a computational approach.

BACKGROUND: Morphological properties of tissues and organs rely on cell growth. The growth of plant cells is determined by properties of a tough outer cell wall that deforms anisotropically in response to high turgor pressure. Cortical microtubules bias the mechanical anisotropy of a cell wall by affecting the trajectories of cellulose synthases in the wall that polymerize cellulose microfibrils. The microtubule cytoskeleton is often oriented in one direction at cellular length-scales to regulate growth direction, but the means by which cellular-scale microtubule patterns emerge has not been well understood. Correlations between the microtubule orientation and tensile forces in the cell wall have often been observed. However, the plausibility of stress as a determining factor for microtubule patterning has not been directly evaluated to date. RESULTS: Here, we simulated how different attributes of tensile forces in the cell wall can orient and pattern the microtubule array in the cortex. We implemented a discrete model with transient microtubule behaviors influenced by local mechanical stress in order to probe the mechanisms of stress-dependent patterning. Specifically, we varied the sensitivity of four types of dynamic behaviors observed on the plus end of microtubules - growth, shrinkage, catastrophe, and rescue - to local stress. Then, we evaluated the extent and rate of microtubule alignments in a two-dimensional computational domain that reflects the structural organization of the cortical array in plant cells. CONCLUSION: Our modeling approaches reproduced microtubule patterns observed in simple cell types and demonstrated that a spatial variation in the magnitude and anisotropy of stress can mediate mechanical feedback between the wall and of the cortical microtubule array.

Segmentation, tracking, and sub-cellular feature extraction in 3D time-lapse images.

This paper presents a method for time-lapse 3D cell analysis. Specifically, we consider the problem of accurately localizing and quantitatively analyzing sub-cellular features, and for tracking individual cells from time-lapse 3D confocal cell image stacks. The heterogeneity of cells and the volume of multi-dimensional images presents a major challenge for fully automated analysis of morphogenesis and development of cells. This paper is motivated by the pavement cell growth process, and building a quantitative morphogenesis model. We propose a deep feature based segmentation method to accurately detect and label each cell region. An adjacency graph based method is used to extract sub-cellular features of the segmented cells. Finally, the robust graph based tracking algorithm using multiple cell features is proposed for associating cells at different time instances. We also demonstrate the generality of our tracking method on C. elegans fluorescent nuclei imagery. Extensive experiment results are provided and demonstrate the robustness of the proposed method. The code is available on GitHub and the method is available as a service through the BisQue portal.

Tandem C2 domains mediate dynamic organelle targeting of a DOCK family guanine nucleotide exchange factor.

Multicellular organisms use dedicator of cytokinesis (DOCK) family guanine nucleotide exchange factors (GEFs) to activate Rac/Rho-of-plants small GTPases and coordinate cell shape change. In developing tissues, DOCK signals integrate cell-cell interactions with cytoskeleton remodeling, and the GEFs cluster reversibly at specific organelle surfaces to orchestrate cytoskeletal reorganization. The domain organizations among DOCK orthologs are diverse, and the mechanisms of localization control are poorly understood. Here, we use combinations of transgene complementation and live-cell imaging assays to uncover an evolutionarily conserved and essential localization determinant in the DOCK-GEF named SPIKE1. The SPIKE1-DHR3 domain is sufficient for organelle association in vivo, and displays a complicated lipid-binding selectivity for both phospholipid head groups and fatty acid chain saturation. SPIKE1-DHR3 is predicted to adopt a C2-domain structure and functions as part of a tandem C2 array that enables reversible clustering at the cell apex. This work provides mechanistic insight into how DOCK GEFs sense compositional and biophysical membrane properties at the interface of two organelle systems.

Cell twisting during desiccation reveals axial asymmetry in wall organization.

Plant cell size and shape are tuned to their function and specified primarily by cellulose microfibril (CMF) patterning of the cell wall. Arabidopsis thaliana leaf trichomes are unicellular structures that act as a physical defense to deter insect feeding. This highly polarized cell type employs a strongly anisotropic cellulose wall to extend and taper, generating sharply pointed branches. During elongation, the mechanisms by which shifts in fiber orientation generate cells with predictable sizes and shapes are unknown. Specifically, the axisymmetric growth of trichome branches is often thought to result from axisymmetric CMF patterning. Here, we analyzed the direction and degree of twist of branches after desiccation to reveal the presence of an asymmetric cell wall organization with a left-hand bias. CMF organization, quantified using computational modeling, suggests a limited reorientation of microfibrils during growth and a maximum branch length limited by the wall axial stiffness. The model provides a mechanism for CMF asymmetry, which occurs after the branch bending stiffness becomes low enough that ambient bending affects the principal stresses. After this stage, the CMF synthesis results in a constant bending stiffness for longer branches. The bending vibration natural frequencies of branches with respect to their length are also discussed.

Protocol for mapping the variability in cell wall mechanical bending behavior in living leaf pavement cells.

Mechanical properties, size and geometry of cells, and internal turgor pressure greatly influence cell morphogenesis. Computational models of cell growth require values for wall elastic modulus and turgor pressure, but very few experiments have been designed to validate the results using measurements that deform the entire thickness of the cell wall. New wall material is synthesized at the inner surface of the cell such that full-thickness deformations are needed to quantify relevant changes associated with cell development. Here, we present an integrated, experimental-computational approach to analyze quantitatively the variation of elastic bending behavior in the primary cell wall of living Arabidopsis (Arabidopsis thaliana) pavement cells and to measure turgor pressure within cells under different osmotic conditions. This approach used laser scanning confocal microscopy to measure the 3D geometry of single pavement cells and indentation experiments to probe the local mechanical responses across the periclinal wall. The experimental results were matched iteratively using a finite element model of the experiment to determine the local mechanical properties and turgor pressure. The resulting modulus distribution along the periclinal wall was nonuniform across the leaf cells studied. These results were consistent with the characteristics of plant cell walls which have a heterogeneous organization. The results and model allowed the magnitude and orientation of cell wall stress to be predicted quantitatively. The methods also serve as a reference for future work to analyze the morphogenetic behaviors of plant cells in terms of the heterogeneity and anisotropy of cell walls.

A co-fractionation mass spectrometry-based prediction of protein complex assemblies in the developing rice aleurone-subaleurone.

Multiprotein complexes execute and coordinate diverse cellular processes such as organelle biogenesis, vesicle trafficking, cell signaling, and metabolism. Knowledge about their composition and localization provides useful clues about the mechanisms of cellular homeostasis and system-level control. This is of great biological importance and practical significance in heterotrophic rice (Oryza sativa) endosperm and aleurone-subaleurone tissues, which are a primary source of seed vitamins and stored energy. Dozens of protein complexes have been implicated in the synthesis, transport, and storage of seed proteins, lipids, vitamins, and minerals. Mutations in protein complexes that control RNA transport result in aberrant endosperm with shrunken and floury phenotypes, significantly reducing seed yield and quality. The purpose of this study was to broadly predict protein complex composition in the aleurone-subaleurone layers of developing rice seeds using co-fractionation mass spectrometry. Following orthogonal chromatographic separations of biological replicates, thousands of protein elution profiles were subjected to distance-based clustering to enable large-scale multimerization state measurements and protein complex predictions. The predicted complexes had predicted functions across diverse functional categories, including novel heteromeric RNA binding protein complexes that may influence seed quality. This effective and open-ended proteomics pipeline provides useful clues about system-level posttranslational control during the early stages of rice seed development.

Real-time conversion of tissue-scale mechanical forces into an interdigitated growth pattern.

The leaf epidermis is a dynamic biomechanical shell that integrates growth across spatial scales to influence organ morphology. Pavement cells, the fundamental unit of this tissue, morph irreversibly into highly lobed cells that drive planar leaf expansion. Here, we define how tissue-scale cell wall tensile forces and the microtubule-cellulose synthase systems dictate the patterns of interdigitated growth in real time. A morphologically potent subset of cortical microtubules span the periclinal and anticlinal cell faces to pattern cellulose fibres that generate a patch of anisotropic wall. The subsequent local polarized growth is mechanically coupled to the adjacent cell via a pectin-rich middle lamella, and this drives lobe formation. Finite element pavement cell models revealed cell wall tensile stress as an upstream patterning element that links cell- and tissue-scale biomechanical parameters to interdigitated growth. Cell lobing in leaves is evolutionarily conserved, occurs in multiple cell types and is associated with important agronomic traits. Our general mechanistic models of lobe formation provide a foundation to analyse the cellular basis of leaf morphology and function.

Spatial and temporal localization of SPIRRIG and WAVE/SCAR reveal roles for these proteins in actin-mediated root hair development.

Root hairs are single-cell protrusions that enable roots to optimize nutrient and water acquisition. These structures attain their tubular shapes by confining growth to the cell apex, a process called tip growth. The actin cytoskeleton and endomembrane systems are essential for tip growth; however, little is known about how these cellular components coordinate their activities during this process. Here, we show that SPIRRIG (SPI), a beige and Chediak Higashi domain-containing protein involved in membrane trafficking, and BRK1 and SCAR2, subunits of the WAVE/SCAR (W/SC) actin nucleating promoting complex, display polarized localizations in Arabidopsis thaliana root hairs during distinct developmental stages. SPI accumulates at the root hair apex via post-Golgi compartments and positively regulates tip growth by maintaining tip-focused vesicle secretion and filamentous-actin integrity. BRK1 and SCAR2 on the other hand, mark the root hair initiation domain to specify the position of root hair emergence. Consistent with the localization data, tip growth was reduced in spi and the position of root hair emergence was disrupted in brk1 and scar1234. BRK1 depletion coincided with SPI accumulation as root hairs transitioned from initiation to tip growth. Taken together, our work uncovers a role for SPI in facilitating actin-dependent root hair development in Arabidopsis through pathways that might intersect with W/SC.

Multimerization variants as potential drivers of neofunctionalization.

Whole-genome duplications are common during evolution, creating genetic redundancy that can enable cellular innovations. Novel protein-protein interactions provide a route to diversified gene functions, but, at present, there is limited proteome-scale knowledge on the extent to which variability in protein complex formation drives neofunctionalization. Here, we used protein correlation profiling to test for variability in apparent mass among thousands of orthologous proteins isolated from diverse species and cell types. Variants in protein complex size were unexpectedly common, in some cases appearing after relatively recent whole-genome duplications or an allopolyploidy event. In other instances, variants such as those in the carbonic anhydrase orthologous group reflected the neofunctionalization of ancient paralogs that have been preserved in extant species. Our results demonstrate that homo- and heteromer formation have the potential to drive neofunctionalization in diverse classes of enzymes, signaling, and structural proteins.

Basic Proline-Rich Protein-Mediated Microtubules Are Essential for Lobe Growth and Flattened Cell Geometry.

Complex cell shapes are generated first by breaking symmetry, and subsequent polar growth. Localized bending of anticlinal walls initiates lobe formation in the epidermal pavement cells of cotyledons and leaves, but how the microtubule cytoskeleton mediates local cell growth, and how plant pavement cells benefit from adopting jigsaw puzzle-like shapes, are poorly understood. In Arabidopsis (Arabidopsis thaliana), the basic Pro-rich protein (BPP) microtubule-associated protein family comprises seven members. We analyzed lobe morphogenesis in cotyledon pavement cells of a BPP1;BPP2;BPP5 triple knockout mutant. New image analysis methods (MtCurv and BQuant) showed that anticlinal microtubule bundles were significantly reduced and cortical microtubules that fan out radially across the periclinal wall did not enrich at the convex side of developing lobes. Despite these microtubule defects, new lobes were initiated at the same frequency as in wild-type cells, but they did not expand into well-defined protrusions. Eventually, mutant cells formed nearly polygonal shapes and adopted concentric microtubule patterns. The mutant periclinal cell wall bulged outward. The radius of the calculated inscribed circle of the pavement cells, a proposed proxy for maximal stress in the cell wall, was consistently larger in the mutant cells during cotyledon development, and correlated with an increase in cell height. These bpp mutant phenotypes provide genetic and cell biological evidence that initiation and growth of lobes are distinct morphogenetic processes, and that interdigitated cell geometry effectively suppresses large outward bulging of pavement cells.

A Label-free Mass Spectrometry Method to Predict Endogenous Protein Complex Composition.

Information on the composition of protein complexes can accelerate mechanistic analyses of cellular systems. Protein complex composition identifies genes that function together and provides clues about regulation within and between cellular pathways. Cytosolic protein complexes control metabolic flux, signal transduction, protein abundance, and the activities of cytoskeletal and endomembrane systems. It has been estimated that one third of all cytosolic proteins in leaves exist in an oligomeric state, yet the composition of nearly all remain unknown. Subunits of stable protein complexes copurify, and combinations of mass-spectrometry-based protein correlation profiling and bioinformatic analyses have been used to predict protein complex subunits. Because of uncertainty regarding the power or availability of bioinformatic data to inform protein complex predictions across diverse species, it would be highly advantageous to predict composition based on elution profile data alone. Here we describe a mass spectrometry-based protein correlation profiling approach to predict the composition of hundreds of protein complexes based on biochemical data. Extracts were obtained from an intact organ and separated in parallel by size and charge under nondenaturing conditions. More than 1000 proteins with reproducible elution profiles across all replicates were subjected to clustering analyses. The resulting dendrograms were used to predict the composition of known and novel protein complexes, including many that are likely to assemble through self-interaction. An array of validation experiments demonstrated that this new method can drive protein complex discovery, guide hypothesis testing, and enable systems-level analyses of protein complex dynamics in any organism with a sequenced genome.

Multi-scale regulation of cell branching: Modeling morphogenesis.

Plant growth and development are driven by extended phases of irreversible cell expansion generating cells that increase in volume from 10- to 100-fold. Some specialized cell types define cortical sites that reinitiate polarized growth and generate branched cell morphology. This structural specialization of individual cells has a major importance for plant adaptation to diverse environments and practical importance in agricultural contexts. The patterns of cell shape are defined by highly integrated cytoskeletal and cell wall systems. Microtubules and actin filaments locally define the material properties of a tough outer cell wall to generate complex shapes. Forward genetics, powerful live cell imaging experiments, and computational modeling have provided insights into understanding of mechanisms of cell shape control. In particular, finite element modeling of the cell wall provides a new way to discover which cell wall heterogeneities generate complex cell shapes, and how cell shape and cell wall stress can feedback on the cytoskeleton to maintain growth patterns. This review focuses on cytoskeleton-dependent cell wall patterning during cell branching, and how combinations of multi-scale imaging experiments and computational modeling are being used to unravel systems-level control of morphogenesis.

Microtubule-Dependent Confinement of a Cell Signaling and Actin Polymerization Control Module Regulates Polarized Cell Growth.

Cell types with wildly varying shapes use many of the same signaling and cytoskeletal proteins to dynamically pattern their geometry [1-3]. Plant cells are encased in a tough outer cell wall, and growth patterns are indirectly controlled by the cytoskeleton and its ability to locally specify the material properties of the wall [4, 5]. Broad and non-overlapping domains of actin and microtubules are predicted to create sharp cell-wall boundaries with distinct mechanical properties [6] that are often proposed to direct growth patterns and cell shape [1, 6, 7]. However, mechanisms by which the cytoskeleton is patterned at the spatial and temporal scales that dictate cell morphology are not known. Here, we used combinations of live-cell imaging probes and unique morphology mutants in Arabidopsis to discover how the microtubule and actin systems are spatially coordinated to pattern polarized growth in leaf epidermal cells. The DOCK family guanine nucleotide exchange factor (GEF) SPIKE1 [8, 9] clusters and activates conserved heteromeric WAVE/SCAR and ARP2/3 complexes at the cell apex to generate organized actin networks that define general cytoplasmic flow patterns. Cortical microtubules corral punctate SPIKE1 signaling nodules and restrict actin polymerization within a broad microtubule-depletion zone at the cell apex. Our data provide a useful model for cell-shape control, in which a GEF, actin filament nucleation complexes, microtubules, and the cell wall function as interacting systems that dynamically pattern polarized growth.

Reassessing the Roles of PIN Proteins and Anticlinal Microtubules during Pavement Cell Morphogenesis.

The leaf epidermis is a biomechanical shell that influences the size and shape of the organ. Its morphogenesis is a multiscale process in which nanometer-scale cytoskeletal protein complexes, individual cells, and groups of cells pattern growth and define macroscopic leaf traits. Interdigitated growth of neighboring cells is an evolutionarily conserved developmental strategy. Understanding how signaling pathways and cytoskeletal proteins pattern cell walls during this form of tissue morphogenesis is an important research challenge. The cellular and molecular control of a lobed cell morphology is currently thought to involve PIN-FORMED (PIN)-type plasma membrane efflux carriers that generate subcellular auxin gradients. Auxin gradients were proposed to function across cell boundaries to encode stable offset patterns of cortical microtubules and actin filaments between adjacent cells. Many models suggest that long-lived microtubules along the anticlinal cell wall generate local cell wall heterogeneities that restrict local growth and specify the timing and location of lobe formation. Here, we used Arabidopsis (Arabidopsis thaliana) reverse genetics and multivariate long-term time-lapse imaging to test current cell shape control models. We found that neither PIN proteins nor long-lived microtubules along the anticlinal wall predict the patterns of lobe formation. In fields of lobing cells, anticlinal microtubules are not correlated with cell shape and are unstable at the time scales of cell expansion. Our analyses indicate that anticlinal microtubules have multiple functions in pavement cells and that lobe initiation is likely controlled by complex interactions among cell geometry, cell wall stress patterns, and transient microtubule networks that span the anticlinal and periclinal walls.

Global Analysis of Membrane-associated Protein Oligomerization Using Protein Correlation Profiling.

Membrane-associated proteins are required for essential processes like transport, organelle biogenesis, and signaling. Many are expected to function as part of an oligomeric protein complex. However, membrane-associated proteins are challenging to work with, and large-scale data sets on the oligomerization state of this important class of proteins is missing. Here we combined cell fractionation of Arabidopsis leaves with nondenaturing detergent solubilization and LC/MS-based profiling of size exclusion chromatography fractions to measure the apparent masses of >1350 membrane-associated proteins. Our method identified proteins from all of the major organelles, with more than 50% of them predicted to be part of a stable complex. The plasma membrane was the most highly enriched in large protein complexes compared with other organelles. Hundreds of novel protein complexes were identified. Over 150 proteins had a complicated localization pattern, and were clearly partitioned between cytosolic and membrane-associated pools. A subset of these dual localized proteins had oligomerization states that differed based on localization. Our data set is an important resource for the community that includes new functionally relevant data for membrane-localized protein complexes that could not be predicted based on sequence alone. Our method enables the analysis of protein complex localization and dynamics, and is a first step in the development of a method in which LC/MS profile data can be used to predict the composition of membrane-associated protein complexes.

Analysis of protein complexes in Arabidopsis leaves using size exclusion chromatography and label-free protein correlation profiling.

Protein complexes are fundamentally important for diverse cellular functions, and create functionalities that could never be achieved by a single polypeptide. Knowledge of the protein complex assemblies that exist in plant cells are limited. To close this gap, we applied an integrative proteomic approach that combines cell fractionation, protein chromatography and quantitative mass spectrometry (MS) to analyze the oligomerization state of thousands of proteins in a single experiment. Soluble extracts from intact Arabidopsis leaves were fractionated using size exclusion chromatography (SEC), and abundance profiles across the column fractions were quantified using label-free precursor ion (MS1) intensity. In duplicate experiments, we reproducibly detected 1693 proteins, of which 983 proteins were cytosolic. Based on the SEC profiles, approximately one third of all of the soluble proteins were predicted to be oligomeric. Our dataset includes both subunits of previously known complexes as well as hundreds of new protein complexes. The label-free MS1-based quantification method described here produced a highly useful dataset for the plant biology community, and provided a foundation to incorporate orthogonal protein complex separation methods so the composition and dynamics of protein complexes can be analyzed based on LC/MS profile data alone.

LobeFinder: A Convex Hull-Based Method for Quantitative Boundary Analyses of Lobed Plant Cells.

Dicot leaves are composed of a heterogeneous mosaic of jigsaw puzzle piece-shaped pavement cells that vary greatly in size and the complexity of their shape. Given the importance of the epidermis and this particular cell type for leaf expansion, there is a strong need to understand how pavement cells morph from a simple polyhedral shape into highly lobed and interdigitated cells. At present, it is still unclear how and when the patterns of lobing are initiated in pavement cells, and one major technological bottleneck to addressing the problem is the lack of a robust and objective methodology to identify and track lobing events during the transition from simple cell geometry to lobed cells. We developed a convex hull-based algorithm termed LobeFinder to identify lobes, quantify geometric properties, and create a useful graphical output of cell coordinates for further analysis. The algorithm was validated against manually curated images of pavement cells of widely varying sizes and shapes. The ability to objectively count and detect new lobe initiation events provides an improved quantitative framework to analyze mutant phenotypes, detect symmetry-breaking events in time-lapse image data, and quantify the time-dependent correlation between cell shape change and intracellular factors that may play a role in the morphogenesis process.

CellECT: cell evolution capturing tool.

BACKGROUND: Robust methods for the segmentation and analysis of cells in 3D time sequences (3D+t) are critical for quantitative cell biology. While many automated methods for segmentation perform very well, few generalize reliably to diverse datasets. Such automated methods could significantly benefit from at least minimal user guidance. Identification and correction of segmentation errors in time-series data is of prime importance for proper validation of the subsequent analysis. The primary contribution of this work is a novel method for interactive segmentation and analysis of microscopy data, which learns from and guides user interactions to improve overall segmentation. RESULTS: We introduce an interactive cell analysis application, called CellECT, for 3D+t microscopy datasets. The core segmentation tool is watershed-based and allows the user to add, remove or modify existing segments by means of manipulating guidance markers. A confidence metric learns from the user interaction and highlights regions of uncertainty in the segmentation for the user's attention. User corrected segmentations are then propagated to neighboring time points. The analysis tool computes local and global statistics for various cell measurements over the time sequence. Detailed results on two large datasets containing membrane and nuclei data are presented: a 3D+t confocal microscopy dataset of the ascidian Phallusia mammillata consisting of 18 time points, and a 3D+t single plane illumination microscopy (SPIM) dataset consisting of 192 time points. Additionally, CellECT was used to segment a large population of jigsaw-puzzle shaped epidermal cells from Arabidopsis thaliana leaves. The cell coordinates obtained using CellECT are compared to those of manually segmented cells. CONCLUSIONS: CellECT provides tools for convenient segmentation and analysis of 3D+t membrane datasets by incorporating human interaction into automated algorithms. Users can modify segmentation results through the help of guidance markers, and an adaptive confidence metric highlights problematic regions. Segmentations can be propagated to multiple time points, and once a segmentation is available for a time sequence cells can be analyzed to observe trends. The segmentation and analysis tools presented here generalize well to membrane or cell wall volumetric time series datasets.