Cytological analysis and structural quantification of FtsZ1-2 and FtsZ2-1 network characteristics in Physcomitrella patens

Automatic extraction of actin networks in plants

The actin cytoskeleton is essential in eukaryotes, not least in the plant kingdom where it plays key roles in cell expansion, cell division, environmental responses and pathogen defence. Yet, the precise structure-function relationships of properties of the actin network in plants are still to be unravelled, including details of how the network configuration depends upon cell type, tissue type and developmental stage. Part of the problem lies in the difficulty of extracting high-quality, quantitative measures of actin network features from microscopy data. To address this problem, we have developed DRAGoN, a novel image analysis algorithm that can automatically extract the actin network across a range of cell types, providing seventeen different quantitative measures that describe the network at a local level. Using this algorithm, we then studied a number of cases in Arabidopsis thaliana, including several different tissues, a variety of actin-affected mutants, and cells responding to powdery mildew. In many cases we found statistically-significant differences in actin network properties. In addition to these results, our algorithm is designed to be easily adaptable to other tissues, mutants and plants, and so will be a valuable asset for the study and future biological engineering of the actin cytoskeleton in globally-important crops.

The Chloroplast Envelope of Angiosperms Contains a Peptidoglycan Layer

Plastids in plants are assumed to have evolved from cyanobacteria as they have maintained several bacterial features. Recently, peptidoglycans, as bacterial cell wall components, have been shown to exist in the envelopes of moss chloroplasts. Phylogenomic comparisons of bacterial and plant genomes have raised the question of whether such structures are also part of chloroplasts in angiosperms. To address this question, we visualized canonical amino acids of peptidoglycan around chloroplasts of Arabidopsis and Nicotiana via click chemistry and fluorescence microscopy. Additional detection by different peptidoglycan-binding proteins from bacteria and animals supported this observation. Further Arabidopsis experiments with D-cycloserine and AtMurE knock-out lines, both affecting putative peptidoglycan biosynthesis, revealed a central role of this pathway in plastid genesis and division. Taken together, these results indicate that peptidoglycans are integral parts of plastids in the whole plant lineage. Elucidating their biosynthesis and further roles in the function of these organelles is yet to be achieved.

A deeply conserved protease, acylamino acid-releasing enzyme (AARE), acts in ageing in Physcomitrella and Arabidopsis

Reactive oxygen species (ROS) are constant by-products of aerobic life. In excess, ROS lead to cytotoxic protein aggregates, which are a hallmark of ageing in animals and linked to age-related pathologies in humans. Acylamino acid-releasing enzymes (AARE) are bifunctional serine proteases, acting on oxidized proteins. AARE are found in all domains of life, albeit under different names, such as acylpeptide hydrolase (APEH/ACPH), acylaminoacyl peptidase (AAP), or oxidized protein hydrolase (OPH). In humans, AARE malfunction is associated with age-related pathologies, while their function in plants is less clear. Here, we provide a detailed analysis of AARE genes in the plant lineage and an in-depth analysis of AARE localization and function in the moss Physcomitrella and the angiosperm Arabidopsis. AARE loss-of-function mutants have not been described for any organism so far. We generated and analysed such mutants and describe a connection between AARE function, aggregation of oxidized proteins and plant ageing, including accelerated developmental progression and reduced life span. Our findings complement similar findings in animals and humans, and suggest a unified concept of ageing may exist in different life forms.

Looking at mechanobiology through an evolutionary lens

Mechanical forces were arguably among the first stimuli to be perceived by cells, and they continue to shape the evolution of all organisms. Great strides have been made in recent years in the field of plant cell and molecular mechanobiology, in part owing to focused efforts on key model systems. Here, we propose to enrich such work through evolutionary mechanobiology, or 'evo-mechano', and describe three major themes that could drive research in this area. We use plastid evo-mechano as a case study, describing how plastids from different lineages perceive their mechanical environments, how their mechanical properties vary across lineages, and their distinct roles in graviperception. Finally, we argue that future research into the biomechanical properties and mechanobiological signaling mechanisms that have been elaborated by green species over the past 1.5 billion years will help us understand both the universal and the unique adaptations of plants to their physical environment.

Automated and semi-automated enhancement, segmentation and tracing of cytoskeletal networks in microscopic images: A review

Cytoskeletal filaments are structures of utmost importance to biological cells and organisms due to their versatility and the significant functions they perform. These biopolymers are most often organised into network-like scaffolds with a complex morphology. Understanding the geometrical and topological organisation of these networks provides key insights into their functional roles. However, this non-trivial task requires a combination of high-resolution microscopy and sophisticated image processing/analysis software. The correct analysis of the network structure and connectivity needs precise segmentation of microscopic images. While segmentation of filament-like objects is a well-studied concept in biomedical imaging, where tracing of neurons and blood vessels is routine, there are comparatively fewer studies focusing on the segmentation of cytoskeletal filaments and networks from microscopic images. The developments in the fields of microscopy, computer vision and deep learning, however, began to facilitate the task, as reflected by an increase in the recent literature on the topic. Here, we aim to provide a short summary of the research on the (semi-)automated enhancement, segmentation and tracing methods that are particularly designed and developed for microscopic images of cytoskeletal networks. In addition to providing an overview of the conventional methods, we cover the recently introduced, deep-learning-assisted methods alongside the advantages they offer over classical methods.

Review: Morphology, behaviour and interactions of organelles

High quality transmission electron micrographs have played a major role in shaping our views on organelles in plant cells. However, these snapshots of dead, fixed and sectioned tissue do not automatically convey an appreciation of the dynamic nature of organelles in living cells. Advances in the imaging of subcellular structures in living cells using multicoloured, targeted fluorescent proteins reveal considerable changes in organelle pleomorphy that might be limited to small regions of the cell. The fresh data and insights also challenge several existing ideas on organelle behaviour and interactivity. Here, using succinct examples from plastids, mitochondria, peroxisomes, and the endoplasmic reticulum I present an evolving view of subcellular dynamics in the plant cell.

A NanoFE simulation-based surrogate machine learning model to predict mechanical functionality of protein networks from live confocal imaging

Sub-cellular mechanics plays a crucial role in a variety of biological functions and dysfunctions. Due to the strong structure-function relationship in cytoskeletal protein networks, light can be shed on their mechanical functionality by investigating their structures. Here, we present a data-driven approach employing a combination of confocal live imaging of fluorescent tagged protein networks, in silico mechanical experiments and machine learning to investigate this relationship. Our designed image processing and nanoFE mechanical simulation framework resolves the structure and mechanical behaviour of cytoskeletal networks and the developed gradient boosting surrogate models linking network structure to its functionality. In this study, for the first time, we perform mechanical simulations of Filamentous Temperature Sensitive Z (FtsZ) complex protein networks with realistic network geometry depicting its skeletal functionality inside organelles (here, chloroplasts) of the moss Physcomitrella patens. Training on synthetically produced simulation data enables predicting the mechanical characteristics of FtsZ network purely based on its structural features (R2⩾0.93), therefore allowing to extract structural principles enabling specific mechanical traits of FtsZ, such as load bearing and resistance to buckling failure in case of large network deformation.

Mosses in biotechnology

Biotechnological exploitation of mosses has several aspects, for example, the use of moss extracts or the whole plant for diverse industrial applications as well as their employment as production platforms for valuable metabolites or pharmaceutical proteins, especially using the genetically and developmentally best-characterised model moss Physcomitrella patens. Whole moss plants, in particular peat mosses (Sphagnum spec.), are useful for environmental approaches, biomonitoring of environmental pollution and CO₂-neutral 'farming' on rewetted bogs to combat climate change. In addition, the lifestyle of mosses suggests the evolution of genes necessary to cope with biotic and abiotic stress situations, which could be applied to crop plants, and their structural features bear an inspiring potential for biomimetics approaches.