Biology subjects

Szymanski, D.

Publications and source records attributed to Szymanski, D..

4 recordsLinked to original sources

bioRxiv2024

Developmental variability in cotton fiber cell wall properties linked to important agronomic traits

The economic value of cotton is based on its long, thin, strong, and twisted trichoblasts that emerge from the ovule epidermis. The mature dried fiber cell reflects the outcome of a rapid tapering of the nascent trichoblast, weeks of polarized diffuse growth, followed by a transition to persistent secondary cell wall synthesis. Highly conserved and dynamic microtubule and cellulose microfibril-based anisotropic growth control modules are central to all of these phases. In this paper, we developed novel quantitative phenotyping and computational modeling pipelines to analyze fiber growth behaviors at a daily resolution. We uncovered unexpected variability in growth rate, cell wall properties, and cell geometry across a critical window of fiber development. Finite element computational modeling of fiber growth was used to analyze the instability of cell diameter control and predict how spatial gradients of fiber and matrix material properties can interact to dictate the patterns of shape change. As an initial step toward gaining insight into the molecular orchestration of cellulose biosynthesis, expression profiles of a broad set of relevant genes were quantified across the same developmental timeline and correlated with fiber phenotypes. This analysis identified specific candidate genes that may serve as targets for fiber quality improvement.

plant biology↗

bioRxiv2023

A machine learning-based approach to identify reliable gold standards for protein complex composition prediction

Co-Fractionation Mass Spectrometry (CFMS) enables the discovery of protein complexes and the systems-level analyses of multimer dynamics that facilitate responses to environmental and developmental conditions. A major challenge in the CFMS analyses, and other omics approaches in general, is to conduct validation experiments at scale and develop precise methods to evaluate the performance of the analyses. For protein complex composition predictions, CORUM is commonly used as a source of known complexes; however, the subunit pools in cell extracts are very rarely in the assumed fully assembled states. Therefore, a fundamental conflict exists between the assumed multimerization of the CORUM "gold standards" and the CFMS experimental datasets to be evaluated. In this paper, we develop a machine learning-based "small world" data analysis method. This method uses size exclusion chromatography profiles of predicted CORUM complex subunits to identify relatively rare instances of fully assembled complexes, as well as bona fide stable CORUM subcomplexes. Our method involves a two-stage machine learning approach that is designed to leverage evolutionarily conserved sequences among CORUM subunits and integrate it with size exclusion chromatography profile data from CFMS experiments. The generated gold standards are evaluated by both statistical significance and size comparison between calculated and predicted complexes. We expect these gold standards to serve as improved benchmarks to assess the overall reliability of CFMS-based protein complex composition predictions.

bioinformatics↗

bioRxiv2022

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

Functional properties of cells, tissues, and organs rely on predictable growth outputs. A shape change in plant cells is determined by properties of a tough cell wall that deforms anisotropically in response to high turgor pressure. This morphogenesis requires tight coordination and feedback controls among cytoskeleton-dependent wall patterning, its material properties, and stresses in the wall. Cortical microtubules bias the mechanical anisotropy of cell wall by defining the trajectories of cellulose synthase motility as they polymerize bundled microfibrils in their wake. Cortical microtubules could locally align and orient relative to cell geometry; however, the means by this orientation occurs is not known. Correlations between the microtubule orientation, cell geometry, and predicted tensile forces are strongly established, and here we simulate how different attributes of tensile force can orient and pattern the microtubule array in the cortex. We implemented a discrete model with three-state transient microtubule behaviors influenced by local mechanical stress in order to probe the mechanisms of stress-dependent patterning. We varied the sensitivity of four types of dynamic behaviors observed on the plus ends of microtubules - growth, shrinkage, catastrophe, and rescue - to local stress and then evaluated the extent and rate of microtubule alignments in a square computational domain. We optimized constitutive relationships between local stress and the plus-end dynamics and employed a biomechanically well-characterized cell wall to analyze how stress can influence the density and orientation of microtubule arrays. Our multiscale modeling approaches predict that spatial variability in stress magnitude and anisotropy mediate mechanical feedback between the wall and organization of the cortical microtubule array. Author SummaryPlant cell growth involve multiple steps and processes. During growth, cell shape changes continuously while responding to external cues from the surroundings. Since growth is mainly driven by pressure, mechanical properties of cell wall are crucial in regulating multiple biological processes that underlie cell expansion and growth. Cell wall assembly is dynamically coupled to the remodeling of subcellular proteins. Experimental evidence has confirmed there exists potential mechanical feedback between wall assembly and protein-protein interactions. However, the actual mechanism remains unknown. In this study, we develop a computational model to study how mechanical stress could affect subcellular protein dynamics or interactions and lead to their reorganization, reminiscent of continuous changes in global pattern and cell morphology. Our results identify key parameters that can respond to external mechanical stimuli at the cellular scale. We also show that a biological stress pattern could induce protein filament organization and bundles that mimic real subcellular structure from experimental images. These computational results could benefit design of experiments for studying and discovering the potential protein candidates that underlie the mechanical feedback between multiple cellular components. In this way, a more systematic understanding about plant cell growth could be achieved, with an integrated theory that combine biology, chemistry, mechanics, and genetics.

plant biology↗

bioRxiv2021

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 responsible for protecting plants against environmental elements and are unicellular structures that employ a highly anisotropic cellulose wall to extend and taper, generating 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 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 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 resulting natural frequency of branches after a length of 200 m falls within the range of the sounds associated with many insects. Statement of significanceThe growth of plant cell walls is governed by the direction of cellulose synthesis but the factors that influence the overall wall anisotropy are only partially understood. The twist of leaf trichome branches after desiccation reveals a left-handed asymmetry in cell wall organization even though the geometry is axisymmetric. This surprising behavior provides information about the directionality of cellulose synthesis control in plant cells.

plant biology↗