Varied solutions to multicellularity: The biophysical and evolutionary consequences of diverse intercellular bonds

Echinobase: a resource to support the echinoderm research community

Echinobase (www.echinobase.org) is a model organism knowledgebase serving as a resource for the community that studies echinoderms, a phylum of marine invertebrates that includes sea urchins and sea stars. Echinoderms have been important experimental models for over 100 years and continue to make important contributions to environmental, evolutionary, and developmental studies, including research on developmental gene regulatory networks. As a centralized resource, Echinobase hosts genomes and collects functional genomic data, reagents, literature, and other information for the community. This third-generation site is based on the Xenbase knowledgebase design and utilizes gene-centric pages to minimize the time and effort required to access genomic information. Summary gene pages display gene symbols and names, functional data, links to the JBrowse genome browser, and orthology to other organisms and reagents, and tabs from the Summary gene page contain more detailed information concerning mRNAs, proteins, diseases, and protein-protein interactions. The gene pages also display 1:1 orthologs between the fully supported species Strongylocentrotus purpuratus (purple sea urchin), Lytechinus variegatus (green sea urchin), Patiria miniata (bat star), and Acanthaster planci (crown-of-thorns sea star). JBrowse tracks are available for visualization of functional genomic data from both fully supported species and the partially supported species Anneissia japonica (feather star), Asterias rubens (sugar star), and L. pictus (painted sea urchin). Echinobase serves a vital role by providing researchers with annotated genomes including orthology, functional genomic data aligned to the genomes, and curated reagents and data. The Echinoderm Anatomical Ontology provides a framework for standardizing developmental data across the phylum, and knowledgebase content is formatted to be findable, accessible, interoperable, and reusable by the research community.

Complementing Cell Taxonomies with a Multicellular Analysis of Tissues

The application of single-cell molecular profiling coupled with spatial technologies has enabled charting of cellular heterogeneity in reference tissues and in disease. This new wave of molecular data has highlighted the expected diversity of single-cell dynamics upon shared external queues and spatial organizations. However, little is known about the relationship between single-cell heterogeneity and the emergence and maintenance of robust multicellular processes in developed tissues and its role in (patho)physiology. Here, we present emerging computational modeling strategies that use increasingly available large-scale cross-condition single-cell and spatial datasets to study multicellular organization in tissues and complement cell taxonomies. This perspective should enable us to better understand how cells within tissues collectively process information and adapt synchronized responses in disease contexts and to bridge the gap between structural changes and functions in tissues.

Computational mesoscale framework for biological clustering and fractal aggregation

Hierarchical clustering due to diffusion and reaction is a widespread occurrence in natural phenomena, displaying fractal behavior with non-integer size scaling. The study of this phenomenon has garnered interest in both biological systems such as morphogenesis and blood clotting, and synthetic systems such as colloids and polymers. The modeling of biological clustering can be difficult, as it can occur on a variety of scales and involve multiple mechanisms, necessitating the use of various methods to capture its behavior. Here, we propose a novel framework, the generalized-mesoscale-clustering (GMC), for the study of complex hierarchical clustering phenomena in biological systems. The GMC framework incorporates the effects of hydrodynamic interactions, bonding, and surface tension, and allows for the analysis of both static and dynamic states of cluster development. The framework is applied to a range of biological clustering mechanisms, with a focus on blood-related clustering from fibrin network formation to platelet aggregation. Our study highlights the importance of a comprehensive characterization of the structural properties of the cluster, including fractal dimension, pore-scale diffusion, initiation time, and consolidation time, in fully understanding the behavior of biological clustering systems. The GMC framework also provides the potential to investigate the temporal evolution and mechanical properties of the clusters by tracking bond density and including hydrodynamic interactions.

Multicellularity and the Need for Communication-A Systematic Overview on (Algal) Plasmodesmata and Other Types of Symplasmic Cell Connections

In the evolution of eukaryotes, the transition from unicellular to simple multicellular organisms has happened multiple times. For the development of complex multicellularity, characterized by sophisticated body plans and division of labor between specialized cells, symplasmic intercellular communication is supposed to be indispensable. We review the diversity of symplasmic connectivity among the eukaryotes and distinguish between distinct types of non-plasmodesmatal connections, plasmodesmata-like structures, and 'canonical' plasmodesmata on the basis of developmental, structural, and functional criteria. Focusing on the occurrence of plasmodesmata (-like) structures in extant taxa of fungi, brown algae (Phaeophyceae), green algae (Chlorophyta), and streptophyte algae, we present a detailed critical update on the available literature which is adapted to the present classification of these taxa and may serve as a tool for future work. From the data, we conclude that, actually, development of complex multicellularity correlates with symplasmic connectivity in many algal taxa, but there might be alternative routes. Furthermore, we deduce a four-step process towards the evolution of canonical plasmodesmata and demonstrate similarity of plasmodesmata in streptophyte algae and land plants with respect to the occurrence of an ER component. Finally, we discuss the urgent need for functional investigations and molecular work on cell connections in algal organisms.

Looking outside the box: a comparative cross-kingdom view on the cell biology of the three major lineages of eukaryotic multicellular life

Many cell biological facts that can be found in dedicated scientific textbooks are based on findings originally made in humans and/or other mammals, including respective tissue culture systems. They are often presented as if they were universally valid, neglecting that many aspects differ-in part considerably-between the three major kingdoms of multicellular eukaryotic life, comprising animals, plants and fungi. Here, we provide a comparative cross-kingdom view on the basic cell biology across these lineages, highlighting in particular essential differences in cellular structures and processes between phyla. We focus on key dissimilarities in cellular organization, e.g. regarding cell size and shape, the composition of the extracellular matrix, the types of cell-cell junctions, the presence of specific membrane-bound organelles and the organization of the cytoskeleton. We further highlight essential disparities in important cellular processes such as signal transduction, intracellular transport, cell cycle regulation, apoptosis and cytokinesis. Our comprehensive cross-kingdom comparison emphasizes overlaps but also marked differences between the major lineages of the three kingdoms and, thus, adds to a more holistic view of multicellular eukaryotic cell biology.

R-PTP-κ Inhibits Contact-Dependent Cell Growth by Suppressing E2F Activity

Density-dependent regulation of cell growth is presumed to be caused by cell-cell contact, but the underlying molecular mechanism is not yet clearly defined. Here, we report that receptor-type protein tyrosine phosphatase-kappa (R-PTP-κ) is an important regulator of cell contact-dependent growth inhibition. R-PTP-κ expression increased in proportion to cell density. siRNA-mediated R-PTP-κ downregulation led to the loss of cell contact-mediated growth inhibition, whereas its upregulation reduced anchorage-independent cell growth in soft agar as well as tumor growth in nude mice. Expression profiling and luciferase reporter system-mediated signaling pathway analysis revealed that R-PTP-κ induced under cell contact conditions distinctly suppressed E2F activity. Among the structural domains of R-PTP-κ, the cytoplasmic domain containing the tandemly repeated PTP motif acts as a potent downregulator of the E2F pathway. Specifically, R-PTP-κ suppressed CDK2 activity through the induction of p21Cip1/WAF-1 and p27Kip1, resulting in cell cycle arrest at the G1 phase. In transcriptome-based public datasets generated from four different tumor types, R-PTP-κ expression was negatively correlated with the expression pattern and prognostic value of two known E2F1 target genes (CCNE1 and CDC25A). Therefore, our results indicate that the R-PTP-κ-E2F axis plays a crucial role in cell growth-inhibitory signaling arising from cell-cell contact conditions.