Multicellular Dynamics Research Articles

Prophage induction can facilitate the in vitro dispersal of multicellular Streptomyces structures.

Streptomyces are renowned for their prolific production of specialized metabolites with applications in medicine and agriculture. These multicellular bacteria present a sophisticated developmental cycle and play a key role in soil ecology. Little is known about the impact of Streptomyces phage on bacterial physiology. In this study, we investigated the conditions governing the expression and production of "Samy", a prophage found in Streptomyces ambofaciens ATCC 23877. This siphoprophage is produced simultaneously with the activation of other mobile genetic elements. Remarkably, the presence and production of Samy increases bacterial dispersal under in vitro stress conditions. Altogether, this study unveiled a new property of a bacteriophage infection in the context of multicellular aggregate dynamics.

Network representation of multicellular activity in pancreatic islets: Technical considerations for functional connectivity analysis.

Within the islets of Langerhans, beta cells orchestrate synchronized insulin secretion, a pivotal aspect of metabolic homeostasis. Despite the inherent heterogeneity and multimodal activity of individual cells, intercellular coupling acts as a homogenizing force, enabling coordinated responses through the propagation of intercellular waves. Disruptions in this coordination are implicated in irregular insulin secretion, a hallmark of diabetes. Recently, innovative approaches, such as integrating multicellular calcium imaging with network analysis, have emerged for a quantitative assessment of the cellular activity in islets. However, different groups use distinct experimental preparations, microscopic techniques, apply different methods to process the measured signals and use various methods to derive functional connectivity patterns. This makes comparisons between findings and their integration into a bigger picture difficult and has led to disputes in functional connectivity interpretations. To address these issues, we present here a systematic analysis of how different approaches influence the network representation of islet activity. Our findings show that the choice of methods used to construct networks is not crucial, although care is needed when combining data from different islets. Conversely, the conclusions drawn from network analysis can be heavily affected by the pre-processing of the time series, the type of the oscillatory component in the signals, and by the experimental preparation. Our tutorial-like investigation aims to resolve interpretational issues, reconcile conflicting views, advance functional implications, and encourage researchers to adopt connectivity analysis. As we conclude, we outline challenges for future research, emphasizing the broader applicability of our conclusions to other tissues exhibiting complex multicellular dynamics.

Graph Network-Based Simulation of Multicellular Dynamics Driven by Concentrated Polymer Brush-Modified Cellulose Nanofibers.

Manipulating the three-dimensional (3D) structures of cells is important for facilitating to repair or regenerate tissues. A self-assembly system of cells with cellulose nanofibers (CNFs) and concentrated polymer brushes (CPBs) has been developed to fabricate various cell 3D structures. To further generate tissues at an implantable level, it is necessary to carry out a large number of experiments using different cell culture conditions and material properties; however this is practically intractable. To address this issue, we present a graph-neural network-based simulator (GNS) that can be trained by using assembly process images to predict the assembly status of future time steps. A total of 24 (25 steps) time-series images were recorded (four repeats for each of six different conditions), and each image was transformed into a graph by regarding the cells as nodes and the connecting neighboring cells as edges. Using the obtained data, the performances of the GNS were examined under three scenarios (i.e., changing a pair of the training and testing data) to verify the possibility of using the GNS as a predictor for further time steps. It was confirmed that the GNS could reasonably reproduce the assembly process, even under the toughest scenario, in which the experimental conditions differed between the training and testing data. Practically, this means that the GNS trained by the first 24 h images could predict the cell types obtained 3 weeks later. This result could reduce the number of experiments required to find the optimal conditions for generating cells with desired 3D structures. Ultimately, our approach could accelerate progress in regenerative medicine.

Chondrocyte hypertrophy in the growth plate promotes stress anisotropy affecting long bone development through chondrocyte column formation

The length of long bones is determined by column formation of proliferative chondrocytes and subsequent chondrocyte hypertrophy in the growth plate during bone development. Despite the importance of mechanical loading in long bone development, the mechanical conditions of the cells within the growth plate, such as the stress field, remain unclear owing to the difficulty in investigating spatiotemporal changes within dynamically growing tissues. In this study, the mechanisms of longitudinal bone growth were investigated from a mechanical perspective through column formation of proliferative chondrocytes within the growth plate before secondary ossification center formation using continuum-based particle models (CbPMs). A one-factor model, which simply describes essential aspects of a biological signaling cascade regulating cell activities within the growth plate, was developed and incorporated into CbPM. Subsequently, the developmental process and maintenance of the growth plate structure and resulting bone morphogenesis were simulated. Thus, stress anisotropy in the proliferative zone that affects bone elongation through chondrocyte column formation was identified and found to be promoted by chondrocyte hypertrophy. These results provide further insights into the mechanical regulation of multicellular dynamics during bone development.

Real-time simultaneous refractive index and thickness mapping of sub-cellular biology at the diffraction limit

Mapping the cellular refractive index (RI) is a central task for research involving the composition of microorganisms and the development of models providing automated medical screenings with accuracy beyond 95%. These models require significantly enhancing the state-of-the-art RI mapping capabilities to provide large amounts of accurate RI data at high throughput. Here, we present a machine-learning-based technique that obtains a biological specimen’s real-time RI and thickness maps from a single image acquired with a conventional color camera. This technology leverages a suitably engineered nanostructured membrane that stretches a biological analyte over its surface and absorbs transmitted light, generating complex reflection spectra from each sample point. The technique does not need pre-existing sample knowledge. It achieves 10−4 RI sensitivity and sub-nanometer thickness resolution on diffraction-limited spatial areas. We illustrate practical application by performing sub-cellular segmentation of HCT-116 colorectal cancer cells, obtaining complete three-dimensional reconstruction of the cellular regions with a characteristic length of 30 μm. These results can facilitate the development of real-time label-free technologies for biomedical studies on microscopic multicellular dynamics.

Single-cell map of dynamic cellular microenvironment of radiation-induced intestinal injury

Intestine is a highly radiation-sensitive organ that could be injured during the radiotherapy for pelvic, abdominal, and retroperitoneal tumors. However, the dynamic change of the intestinal microenvironment related to radiation-induced intestine injury (RIII) is still unclear. Using single-cell RNA sequencing, we pictured a dynamic landscape of the intestinal microenvironment during RIII and regeneration. We showed that the various cell types of intestine exhibited heterogeneous radiosensitivities. We revealed the distinct dynamic patterns of three subtypes of intestinal stem cells (ISCs), and the cellular trajectory analysis suggested a complex interconversion pattern among them. For the immune cells, we found that Ly6c+ monocytes can give rise to both pro-inflammatory macrophages and resident macrophages after RIII. Through cellular communication analysis, we identified a positive feedback loop between the macrophages and endothelial cells, which could amplify the inflammatory response induced by radiation. Besides, we identified different T cell subtypes and revealed their role in immunomodulation during the early stage of RIII through inflammation and defense response relevant signaling pathways. Overall, our study provides a valuable single-cell map of the multicellular dynamics during RIII and regeneration, which may facilitate the understanding of the mechanism of RIII.

Multicellular dynamics on structured surfaces: Stress concentration is a key to controlling complex microtissue morphology on engineered scaffolds.

Tissue engineers have utilised a variety of three-dimensional (3D) scaffolds for controlling multicellular dynamics and the resulting tissue microstructures. In particular, cutting-edge microfabrication technologies, such as 3D bioprinting, provide increasingly complex structures. However, unpredictable microtissue detachment from scaffolds, which ruins desired tissue structures, is becoming an evident problem. To overcome this issue, we elucidated the mechanism underlying collective cellular detachment by combining a new computational simulation method with quantitative tissue-culture experiments. We first quantified the stochastic processes of cellular detachment shown by vascular smooth muscle cells on model curved scaffolds and found that microtissue morphologies vary drastically depending on cell contractility, substrate curvature, and cell-substrate adhesion strength. To explore this mechanism, we developed a new particle-based model that explicitly describes stochastic processes of multicellular dynamics, such as adhesion, rupture, and large deformation of microtissues on structured surfaces. Computational simulations using the developed model successfully reproduced characteristic detachment processes observed in experiments. Crucially, simulations revealed that cellular contractility-induced stress is locally concentrated at the cell-substrate interface, subsequently inducing a catastrophic process of collective cellular detachment, which can be suppressed by modulating cell contractility, substrate curvature, and cell-substrate adhesion. These results show that the developed computational method is useful for predicting engineered tissue dynamics as a platform for prediction-guided scaffold design. STATEMENT OF SIGNIFICANCE: Microfabrication technologies aiming to control multicellular dynamics by engineering 3D scaffolds are attracting increasing attention for modelling in cell biology and regenerative medicine. However, obtaining microtissues with the desired 3D structures is made considerably more difficult by microtissue detachments from scaffolds. This study reveals a key mechanism behind this detachment by developing a novel computational method for simulating multicellular dynamics on designed scaffolds. This method enabled us to predict microtissue dynamics on structured surfaces, based on cell mechanics, substrate geometry, and cell-substrate interaction. This study provides a platform for the physics-based design of micro-engineered scaffolds and thus contributes to prediction-guided biomaterials design in the future.

Modelling contractile ring formation and division to daughter cells for simulating proliferative multicellular dynamics.

Cell proliferation is a fundamental process underlying embryogenesis, homeostasis, wound healing, and cancer. The process involves multiple events during each cell cycle, such as cell growth, contractile ring formation, and division to daughter cells, which affect the surrounding cell population geometrically and mechanically. However, existing methods do not comprehensively describe the dynamics of multicellular structures involving cell proliferation at a subcellular resolution. In this study, we present a novel model for proliferative multicellular dynamics at the subcellular level by building upon the nonconservative fluid membrane (NCF) model that we developed in earlier research. The NCF model utilizes a dynamically-rearranging closed triangular mesh to depict the shape of each cell, enabling us to analyze cell dynamics over extended periods beyond each cell cycle, during which cell surface components undergo dynamic turnover. The proposed model represents the process of cell proliferation by incorporating cell volume growth and contractile ring formation through an energy function and topologically dividing each cell at the cleavage furrow formed by the ring. Numerical simulations demonstrated that the model recapitulated the process of cell proliferation at subcellular resolution, including cell volume growth, cleavage furrow formation, and division to daughter cells. Further analyses suggested that the orientation of actomyosin stress in the contractile ring plays a crucial role in the cleavage furrow formation, i.e., circumferential orientation can form a cleavage furrow but isotropic orientation cannot. Furthermore, the model replicated tissue-scale multicellular dynamics, where the successive proliferation of adhesive cells led to the formation of a cell sheet and stratification on the substrate. Overall, the proposed model provides a basis for analyzing proliferative multicellular dynamics at subcellular resolution.

Cellular gradient flow structure linking single-cell-level rules and population-level dynamics

In multicellular systems, single-cell behaviors should be coordinated consistently with the overall population dynamics and functions. However, the interrelation between single-cell rules and the population-level goal is still elusive. In this work, we reveal that these two levels are naturally connected via a gradient flow structure of heterogeneous cellular populations and that biologically prevalent single-cell rules, such as unidirectional type switching and hierarchical order in types, emerge from this structure. We also demonstrate the gradient flow structure in a standard model of the T-cell immune response. This theoretical framework works as a basis for understanding multicellular dynamics and functions.Received 26 May 2022Accepted 11 May 2023DOI:https://doi.org/10.1103/PhysRevResearch.5.L022052Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.Published by the American Physical SocietyPhysics Subject Headings (PhySH)Research AreasBiological complexityCell processes & propertiesPopulation dynamicsPhysical SystemsCellsPopulationsNonlinear DynamicsStatistical PhysicsBiological Physics

Underlying mechanisms that ensure actomyosin-mediated directional remodeling of cell-cell contacts for multicellular movement: Tricellular junctions and negative feedback as new aspects underlying actomyosin-mediated directional epithelial morphogenesis: Tricellular junctions and negative feedback as new aspects underlying actomyosin-mediated directional epithelial morphogenesis.

Actomyosin (actin-myosin II complex)-mediated contractile forces are central to the generation of multifaceted uni- and multi-cellular material properties and dynamics such as cell division, migration, and tissue morphogenesis. In the present article, we summarize our recent researches addressing molecular mechanisms that ensure actomyosin-mediated directional cell-cell junction remodeling, either shortening or extension, driving cell rearrangement for epithelial morphogenesis. Genetic perturbation clarified two points concerning cell-cell junction remodeling: an inhibitory mechanism against negative feedback in which actomyosin contractile forces, which are well known to induce cell-cell junction shortening, can concomitantly alter actin dynamics, oppositely leading to perturbation of the shortening; and tricellular junctions as a point that organizes extension of new cell-cell junctions after shortening. These findings highlight the notion that cells develop underpinning mechanisms to transform the multi-tasking property of actomyosin contractile forces into specific and proper cellular dynamics in space and time.

A review of computational modeling, machine learning and image analysis in cancer metastasis dynamics

AbstractCancer is a life‐threatening process that stems from genetic mutations in cells, which leads to the formation of tumors, and is a major cause of deaths in the United States, with secondary metastasis being a major driver of fatality. The development of an optimal metastatic environment is an essential process prior to tumor metastasis. This process, called pre‐metastatic niche formation, involves the activation of resident fibroblast‐like cells and macrophages. Tumor‐mediated factors introduced to this environment transform resident cells that secrete additional growth factors and remodel the extracellular matrix, which is thought to promote tumor colonization and metastasis in the secondary environment. Furthermore, an important component of metastasis is the biological process of epithelial–mesenchymal transition, which can be exploited by cancer cells to change their phenotype, to migrate and proliferate as necessary. In this review, we discuss recent advances in the investigation of cancer growth and migration. Computational models that focus on biochemical signaling and multicellular dynamics are examined. Machine learning models and image analysis that classify cancer‐related data are also explored. Through this review, we highlight advances in the study of important aspects of cancer and metastasis signaling and computational tools to study these dynamics.

Multicellular immune dynamics implicate PIM1 as a potential therapeutic target for uveitis

Uveitis is a severe autoimmune disease, and a common cause of blindness; however, its individual cellular dynamics and pathogenic mechanism remain poorly understood. Herein, by performing single-cell RNA sequencing (scRNA-seq) on experimental autoimmune uveitis (EAU), we identify disease-associated alterations in cell composition and transcriptional regulation as the disease progressed, as well as a disease-related molecule, PIM1. Inhibiting PIM1 reduces the Th17 cell proportion and increases the Treg cell proportion, likely due to regulation of PIM1 to the protein kinase B (AKT)/Forkhead box O1 (FOXO1) pathway. Moreover, inhibiting PIM1 reduces Th17 cell pathogenicity and reduces plasma cell differentiation. Importantly, the upregulation of PIM1 in CD4+ T cells and plasma cells is conserved in a human uveitis, Vogt-Koyanagi-Harada disease (VKH), and inhibition of PIM1 reduces CD4+ T and B cell expansion. Collectively, a dynamic immune cellular atlas during uveitis is developed and implicate that PIM1 may be a potential therapeutic target for VKH.

Probing the rules of cell coordination in live tissues by interpretable machine learning based on graph neural networks.

Robustness in developing and homeostatic tissues is supported by various types of spatiotemporal cell-to-cell interactions. Although live imaging and cell tracking are powerful in providing direct evidence of cell coordination rules, extracting and comparing these rules across many tissues with potentially different length and timescales of coordination requires a versatile framework of analysis. Here we demonstrate that graph neural network (GNN) models are suited for this purpose, by showing how they can be applied to predict cell fate in tissues and utilized to infer the cell interactions governing the multicellular dynamics. Analyzing the live mammalian epidermis data, where spatiotemporal graphs constructed from cell tracks and cell contacts are given as inputs, GNN discovers distinct neighbor cell fate coordination rules that depend on the region of the body. This approach demonstrates how the GNN framework is powerful in inferring general cell interaction rules from live data without prior knowledge of the signaling involved.

Multicellular Dynamics Associated with Clinical Outcome Were Discovered in PDAC.

Multicellular dynamics, including neoadjuvant treatment-associated changes, were uncovered in PDAC.

Single-nucleus and spatial transcriptome profiling of pancreatic cancer identifies multicellular dynamics associated with neoadjuvant treatment.

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal and treatment-refractory cancer. Molecular stratification in pancreatic cancer remains rudimentary and does not yet inform clinical management or therapeutic development. Here, we construct a high-resolution molecular landscape of the cellular subtypes and spatial communities that compose PDAC using single-nucleus RNA sequencing and whole-transcriptome digital spatial profiling (DSP) of 43 primary PDAC tumor specimens that either received neoadjuvant therapy or were treatment naive. We uncovered recurrent expression programs across malignant cells and fibroblasts, including a newly identified neural-like progenitor malignant cell program that was enriched after chemotherapy and radiotherapy and associated with poor prognosis in independent cohorts. Integrating spatial and cellular profiles revealed three multicellular communities with distinct contributions from malignant, fibroblast and immune subtypes: classical, squamoid-basaloid and treatment enriched. Our refined molecular and cellular taxonomy can provide a framework for stratification in clinical trials and serve as a roadmap for therapeutic targeting of specific cellular phenotypes and multicellular interactions.

CytoNet: Spatiotemporal network analysis of cell communities.

We introduce cytoNet, a cloud-based tool to characterize cell populations from microscopy images. cytoNet quantifies spatial topology and functional relationships in cell communities using principles of network science. Capturing multicellular dynamics through graph features, cytoNet also evaluates the effect of cell-cell interactions on individual cell phenotypes. We demonstrate cytoNet’s capabilities in four case studies: 1) characterizing the temporal dynamics of neural progenitor cell communities during neural differentiation, 2) identifying communities of pain-sensing neurons in vivo, 3) capturing the effect of cell community on endothelial cell morphology, and 4) investigating the effect of laminin α4 on perivascular niches in adipose tissue. The analytical framework introduced here can be used to study the dynamics of complex cell communities in a quantitative manner, leading to a deeper understanding of environmental effects on cellular behavior. The versatile, cloud-based format of cytoNet makes the image analysis framework accessible to researchers across domains.

Multicellular dynamics of zonal liver regeneration mapped in space and time

In this issue, Ben-Moshe etal. (2022) use spatiotemporally resolved single-cell and spatial transcriptomic profiling to dissect the multicellular dynamics enabling zonal liver regeneration. They highlight how pan-zonal compensatory hepatocyte proliferation, transient reprogramming of peri-injury hepatocytes, and concerted zonated action of different liver cell types orchestrate the healing process.

Polarized interfacial tension induces collective migration of cells, as a cluster, in a 3D tissue

In embryogenesis and cancer invasion, cells collectively migrate as a cluster in 3D tissues. Many studies have elucidated mechanisms of either individual or collective cell migration on 2D substrates; however, it remains unclear how cells collectively migrate as a cluster through 3D tissues. To address this issue, we considered the interfacial tension at cell-cell boundaries expressing cortical actomyosin contractions and cell-cell adhesive interactions. The strength of this tension is polarized; i.e., spatially biased within each cell according to a chemoattractant gradient. Using a 3D vertex model, we performed numerical simulations of multicellular dynamics in 3D space. The simulations revealed that the polarized interfacial tension enables cells to migrate collectively as a cluster through a 3D tissue. In this mechanism, interfacial tension induces unidirectional flow of each cell surface from the front to the rear along the cluster surface. Importantly, this mechanism does not necessarily require convection of cells, i.e., cell rearrangement, within the cluster. Moreover, several migratory modes were induced, depending on the strengths of polarity, adhesion, and noise; i.e., cells migrate either as single cells, as a cluster, or aligned like beads on a string, as occurs in embryogenesis and cancer invasion. These results indicate that the simple expansion and contraction of cell-cell boundaries enables cells to move directionally forward and to produce the variety of collective migratory movements observed in living systems.

Spatiotemporal and Multicellular Intravital Microscopy Analysis during Cardiac Injury and Repair

BackgroundUnderstanding the response to cardiac injury across multiple cell types and timescales has relied on techniques that reduce the complexity of the in vivo environment to provide a step‐by‐step picture of heart function. These models do not recapitulate the temporal and spatial complexities of the true in vivo environment. We have developed a suite of in vivo imaging methods that enable the study of cardiac injury, and here demonstrate intravital cardiac multiphoton microscopy (MPM) to assess cardiomyocyte function and the dynamics of heart and inflammatory cell types in response to cardiac injury and repair.MethodsIntravital cardiac MPM of male and female mice was performed in the anesthetized mechanically ventilated mouse following left thoracotomy and placement of a customized imaging window on the left ventricle. Fast image acquisition (30 frame/sec) and simultaneous electrocardiogram and respiratory pressure recording enable volumetric image reconstruction throughout the cardiac cycle and quantitative measures of tissue motion and deformation. To demonstrate tracking of acute cellular changes over 1‐2 h, we performed focal sterile injury (FSI; non‐scanning high‐power laser exposure causing capillary and cell disruption) and measured cardiomyocyte calcium dynamics, as well as neutrophil and macrophage/monocyte trafficking in αMHC‐GCaMP8, Rosa26‐Cre‐Ly6G+/TdTom, and Cx3Cr1+/GFP‐CCR2+/RFP mice, respectively. To demonstrate monitoring of inflammatory cell interactions and tissue function in actively repairing heart, we performed left ventricle cryoinfarction (CI) or sham in the same mouse strains and imaged after 7‐days. To explore the behavior of a recently focused upon cell class expressing c‐Kit, we performed FSI and CI in c‐KitBAC‐EGFP and c‐Kit‐rtTA/H2B‐EGFP mice. Intravenous injection of fluorescent dyes labelled vasculature (Texas Red or fluoresceine conjugated 70kDa‐dextran, or Q‐dot 655 or 705) and nuclei (Hoechst).ResultsIntravital cardiac MPM and FSI, enabled the visualization and quantification of non‐cyclical and uncoordinated cardiomyocyte calcium activity associated with a 40% reduction in cell motion and deformation, increased Ly6G+ neutrophil trafficking and Cx3Cr+ resident macrophage polarity over 2 h (p<0.05). Resident c‐Kit+ cell morphology and position did not change over 150 min in both c‐KitBAC‐EGFP and c‐Kit‐rtTA/H2B‐EGFP mouse strains. Imaging 7‐days after‐CI, our approaches were able to identify reduced cardiomyocyte calcium activity within the infarct zone associated with a 90% reduction in tissue motion and deformation, morphological alterations in the microvasculature (wider, reduced bifurcations; p<0.05), increased tissue Cx3Cr1+ macrophage number, Ly6G+ neutrophil arrest in vasculature (p<0.05), and punctate perivascular c‐kit expression that shifts to a vascular phenotype.ConclusionWe have demonstrated the ability to image and quantify the spatiotemporal and multicellular dynamics of cardiac injury and repair using intravital cardiac MPM. These techniques provide a powerful tool to investigate active phases of cardiac repair post‐injury in the true in vivo environment.

Characterization of red fluorescent reporters for dual-color in vivo three-photon microscopy.

.SignificanceThree-photon (3P) microscopy significantly increases the depth and resolution of in vivo imaging due to decreased scattering and nonlinear optical sectioning. Simultaneous excitation of multiple fluorescent proteins is essential to studying multicellular interactions and dynamics in the intact brain.AimWe characterized the excitation laser pulses at a range of wavelengths for 3P microscopy, and then explored the application of tdTomato or mScarlet and EGFP for dual-color single-excitation structural 3P imaging deep in the living mouse brain.ApproachWe used frequency-resolved optical gating to measure the spectral intensity, phase, and retrieved pulse widths at a range of wavelengths. Then, we performed in vivo single wavelength-excitation 3P imaging in the 1225- to 1360-nm range deep in the mouse cerebral cortex to evaluate the performance of tdTomato or mScarlet in combination with EGFP.ResultsWe find that tdTomato and mScarlet, expressed in oligodendrocytes and neurons respectively, have a high signal-to-background ratio in the 1300- to 1360-nm range, consistent with enhanced 3P cross-sections.ConclusionsThese results suggest that a single excitation wavelength source is advantageous for multiple applications of dual-color brain imaging and highlight the importance of empirical characterization of individual fluorophores for 3P microscopy.