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Mathematical and computational models can assist in gaining an understanding of cell behavior at many levels of organization. Here, we review models in the literature that focus on eukaryotic cell motility at 3 size scales: intracellular signaling that regulates cell shape and movement, single cell motility, and collective cell behavior from a few cells to tissues. We survey recent literature to summarize distinct computational methods (phase-field, polygonal, Cellular Potts, and spherical cells). We discuss models that bridge between levels of organization, and describe levels of detail, both biochemical and geometric, included in the models. We also highlight links between models and experiments. We find that models that span the 3 levels are still in the minority. Author summary: In this review paper, we summarize the literature on computational models for cell motility, from the biochemical networks that regulate it, to the behavior of 1 and many cells. We discuss the distinct approaches used at each level, and how models can build bridges between the different size scales. We find models at many different levels of biological detail, and discuss their relative contributions to our understanding of single and collective cell behavior. Finally, we indicate how models have been linked to biological experiments in this field. [ABSTRACT FROM AUTHOR]

The dynamic interplay between cell adhesion and protrusion is a critical determinant of many forms of cell motility. When modeling cell spreading on adhesive surfaces, traditional mathematical treatments often consider passive cell adhesion as the primary, if not exclusive, mechanistic driving force of this cellular motion. To better assess the contribution of active cytoskeletal protrusion to immune-cell spreading during phagocytosis, we here develop a computational framework that allows us to optionally investigate both purely adhesive spreading ("Brownian zipper hypothesis") as well as protrusion-dominated spreading ("protrusive zipper hypothesis"). We model the cell as an axisymmetric body of highly viscous fluid surrounded by a cortex with uniform surface tension and incorporate as potential driving forces of cell spreading an attractive stress due to receptor-ligand binding and an outward normal stress representing cytoskeletal protrusion, both acting on the cell boundary. We leverage various model predictions against the results of a directly related experimental companion study of human neutrophil phagocytic spreading on substrates coated with different densities of antibodies. We find that the concept of adhesion-driven spreading is incompatible with experimental results such as the independence of the cell-spreading speed on the density of immobilized antibodies. In contrast, the protrusive zipper model agrees well with experimental findings and, when adapted to simulate cell spreading on discrete adhesion sites, it also reproduces the observed positive correlation between antibody density and maximum cell-substrate contact area. Together, our integrative experimental/computational approach shows that phagocytic spreading is driven by cellular protrusion, and that the extent of spreading is limited by the density of adhesion sites. Author summary: To accomplish many routine biological tasks, cells must rapidly spread over different types of surfaces. Here, we examine the biophysical underpinnings of immune cell spreading during phagocytosis, the process by which white blood cells such as neutrophils engulf pathogens or other foreign objects. Our computational framework models the case in which a human neutrophil spreads over a flat surface coated with antibodies, which we also test experimentally in a companion paper. Our primary purpose is to assess whether phagocytic spreading is actively driven by protrusive forces exerted by the cell, or passively by adhesive forces acting between receptors in the cell membrane and antibodies on the surface. By directly comparing our model predictions to experimental results, we demonstrate that phagocytic spreading is primarily driven by protrusion, but the extent of spreading is still limited by the availability of binding sites. Our findings improve the fundamental understanding of phagocytosis and may also pave the way for future investigations of the balance between adhesion and protrusion in other forms of cell spreading, such as wound healing or cancer cell migration. [ABSTRACT FROM AUTHOR]

Ebola virus (EBOV) targets immune cells and tries to inactivate dendritic cells and interferon molecules to continue its replication process. Since EBOV detailed mechanism has not been identified so far, it would be useful to understand the growth and spread of EBOV dynamics based on mathematical methods and simulation approaches. Computational approaches such as Cellular Automata (CA) have the advantage of simplicity over solving complicated differential equations. The spread of Ebola virus in lymph nodes is studied using a simplified Cellular Automata model with only four parameters. In addition to considering healthy and infected cells, this paper also considers T lymphocytes as well as cell movement ability during the simulation in order to investigate different scenarios in the dynamics of an EBOV system. It is shown that the value of the probability of death of T cells affects the number of infected cells significantly in the steady-state. For a special case of parameters set, the system shows oscillating dynamics. The results were in good agreement with an ordinary differential equation-based model which indicated CA method in combination with experimental discoveries could help biologists find out more about the EBOV mechanism and hopefully to control the disease. [ABSTRACT FROM AUTHOR]

The formation of neuron networks is a complex phenomenon of fundamental importance for understanding the development of the nervous system, and for creating novel bioinspired materials for tissue engineering and neuronal repair. The basic process underlying the network formation is axonal growth, a process involving the extension of axons from the cell body towards target neurons. Axonal growth is guided by environmental stimuli that include intercellular interactions, biochemical cues, and the mechanical and geometrical features of the growth substrate. The dynamics of the growing axon and its biomechanical interactions with the growing substrate remains poorly understood. In this paper, we develop a model of axonal motility which incorporates mechanical interactions between the axon and the growth substrate. We combine experimental data with theoretical analysis to measure the parameters that describe axonal growth on surfaces with micropatterned periodic geometrical features: diffusion (cell motility) coefficients, speed and angular distributions, and axon bending rigidities. Experiments performed on neurons treated Taxol (inhibitor of microtubule dynamics) and Blebbistatin (disruptor of actin filaments) show that the dynamics of the cytoskeleton plays a critical role in the axon steering mechanism. Our results demonstrate that axons follow geometrical patterns through a contact-guidance mechanism, in which high-curvature geometrical features impart high traction forces to the growth cone. These results have important implications for our fundamental understanding of axonal growth as well as for bioengineering novel substrates that promote neuronal growth and nerve repair. [ABSTRACT FROM AUTHOR]

Unicellular microscopic organisms living in aqueous environments outnumber all other creatures on Earth. A large proportion of them are able to self-propel in fluids with a vast diversity of swimming gaits and motility patterns. In this paper we present a biophysical survey of the available experimental data produced to date on the characteristics of motile behaviour in unicellular microswimmers. We assemble from the available literature empirical data on the motility of four broad categories of organisms: bacteria (and archaea), flagellated eukaryotes, spermatozoa and ciliates. Whenever possible, we gather the following biological, morphological, kinematic and dynamical parameters: species, geometry and size of the organisms, swimming speeds, actuation frequencies, actuation amplitudes, number of flagella and properties of the surrounding fluid. We then organise the data using the established fluid mechanics principles for propulsion at low Reynolds number. Specifically, we use theoretical biophysical models for the locomotion of cells within the same taxonomic groups of organisms as a means of rationalising the raw material we have assembled, while demonstrating the variability for organisms of different species within the same group. The material gathered in our work is an attempt to summarise the available experimental data in the field, providing a convenient and practical reference point for future studies. [ABSTRACT FROM AUTHOR]

In nature, protozoa play a major role in controlling bacterial populations. This paper proposes a microfluidic device for the study of protozoa behaviors change due to their chemotactic response in the presence of bacterial cells. A three-channel microfluidic device was designed using a nitrocellulose membrane into which channels were cut using a laser cutter. The membrane was sandwiched between two glass slides; a Euglena suspension was then allowed to flow through the central channel. The two side channels were filled with either, 0.1% peptone as a negative control, or a Listeria suspension respectively. The membrane design prevented direct interaction but allowed Euglena cells to detect Listeria cells as secretions diffused through the nitrocellulose membrane. A significant number of Euglena cells migrated toward the chambers near the bacterial cells, indicating a positive chemotactic response of Euglena toward chemical cues released from Listeria cells. Filtrates collected from Listeria suspension with a series of molecular weight cutoffs (3k, 10k and 100k) were examined in Euglena chemotaxis tests. Euglena cells were attracted to all filtrates collected from the membrane filtration with different molecular weight cutoffs, suggesting small molecules from Listeria might be the chemical cues to attract protozoa. Headspace volatile organic compounds (VOC) released from Listeria were collected, spiked to 0.1% peptone and tested as the chemotactic effectors. It was discovered that the Euglena cells responded quickly to Listeria VOCs including decanal, 3,5- dimethylbenzaldehyde, ethyl acetate, indicating bacterial VOCs were used by Euglena to track the location of bacteria. [ABSTRACT FROM AUTHOR]

Dendritic cells (DCs) are the most effective professional antigen-presenting cell. They ferry antigen from the extremities to T cells and are essential for the initiation of an adaptive immune response. Despite interest in how DCs respond to chemical stimuli, there have been few attempts to model DC migration. In this paper, we simulate the motility of DCs by modeling the generation of forces by filopodia and a force balance on the cell. The direction of fliopodial extension is coupled to differential occupancy of cognate chemokine receptors across the cell. Our model simulates chemokinesis and chemotaxis in a variety of chemical and mechanical environments. Simulated DCs undergoing chemokinesis were measured to have a speed of 5.1 ± 0.07 μm·min-1 and a persistence time of 3.2 ± 0.46 min, consistent with experiment. Cells undergoing chemotaxis exhibited a stronger chemotactic response when exposed to lower average chemokine concentrations, also consistent with experiment. We predicted that when placed in two opposing gradients, cells will cluster in a line, which we call the “line of equistimulation;” this clustering has also been observed. We calculated the effect of varying gradient steepness on the line of equistimulation, with steeper gradients resulting in tighter clustering. Moreover, gradients are found to be most potent when cells are in a gradient of chemokine whose mean concentration is close to the binding of the Kd to the receptor, and least potent when the mean concentration is 0.1Kd. Comparing our simulations to experiment, we can give a quantitative measure of the strength of certain chemokines relative to others. Assigning the signal of CCL19 binding CCR7 a baseline strength of 1, we found CCL21 binding CCR7 had a strength of 0.28, and CXCL12 binding CXCR4 had a strength of 0.30. These differences emerge despite both chemokines having virtually the same Kd, suggesting a mechanism of signal amplification in DCs requiring further study. [ABSTRACT FROM AUTHOR]

Coordinated activation and inhibition of F-actin supports the movements of morphogenesis. Understanding the proteins that regulate F-actin is important, since these proteins are mis-regulated in diseases like cancer. Our studies of C. elegans embryonic epidermal morphogenesis identified the GTPase CED-10/Rac1 as an essential activator of F-actin. However, we need to identify the GEF, or Guanine-nucleotide Exchange Factor, that activates CED-10/Rac1 during embryonic cell migrations. The two-component GEF, CED-5/CED-12, is known to activate CED-10/Rac1 to promote cell movements that result in the engulfment of dying cells during embryogenesis, and a later cell migration of the larval Distal Tip Cell. It is believed that CED-5/CED-12 powers cellular movements of corpse engulfment and DTC migration by promoting F-actin formation. Therefore, we tested if CED-5/CED-12 was involved in embryonic migrations, and got a contradictory result. CED-5/CED-12 definitely support embryonic migrations, since their loss led to embryos that died due to failed epidermal cell migrations. However, CED-5/CED-12 inhibited F-actin in the migrating epidermis, the opposite of what was expected for a CED-10 GEF. To address how CED-12/CED-5 could have two opposing effects on F-actin, during corpse engulfment and cell migration, we investigated if CED-12 harbors GAP (GTPase Activating Protein) functions. A candidate GAP region in CED-12 faces away from the CED-5 GEF catalytic region. Mutating a candidate catalytic Arginine in the CED-12 GAP region (R537A) altered the epidermal cell migration function, and not the corpse engulfment function. We interfered with GEF function by interfering with CED-5's ability to bind Rac1/CED-10. Mutating Serine-Arginine in CED-5/DOCK predicted to bind and stabilize Rac1 for catalysis, resulted in loss of both ventral enclosure and corpse engulfment. Genetic and expression studies strongly support that the GAP function likely acts on different GTPases. Thus, we propose CED-5/CED-12 support the cycling of multiple GTPases, by using distinct domains, to both promote and inhibit F-actin nucleation. Author summary: GTPases in their active state promote actin nucleation that drives cellular events, from cell migrations, to cell shape changes, to cell-cell interactions. To function correctly, GTPases need to cycle from the active, GTP-bound state, to the inactive, GDP-bound state. This cycle is supported by Guanine-nucleotide Exchange Factors, or GEFs, that support activation as GDP is switched for GTP, and GTPase-Activating Proteins, or GAPs that support hydrolysis back to the GDP bound state. The Rac1/CED-10 GTPase has a well-studied GEF, CED-5/CED-12, that promotes Rac1 activation during cell engulfment of dying cells. Here we tested if CED-5/CED-12 also functioned as the activator, or GEF for Rac1 during embryonic epidermal cell migrations. Surprisingly, CED-5/CED-12 behaved completely opposite to what was expected during epidermal cell migration. Therefore, we investigated if CED-5/CED-12 could harbor a GAP function. Comparing models of human and C. elegans protein structures suggested a putative GAP region, which we mutated to show that CED-12 likely functions as a GAP. Genetic and gene expression tests identify other GTPases, CDC-42 and RHO-1, as likely targets of this newly uncovered CED-12 GAP function. These findings suggest CED-5/CED-12 can support the cycling of multiple GTPases, and either promote or inhibit F-actin nucleation, using its GEF or GAP functions. [ABSTRACT FROM AUTHOR]

Melanoma showcases a complex interplay of genetic alterations and intra- and inter-cellular morphological changes during metastatic transformation. While pivotal, the role of specific mutations in dictating these changes still needs to be fully elucidated. Telomerase promoter mutations (TERTp mutations) significantly influence melanoma's progression, invasiveness, and resistance to various emerging treatments, including chemical inhibitors, telomerase inhibitors, targeted therapy, and immunotherapies. We aim to understand the morphological and phenotypic implications of the two dominant monoallelic TERTp mutations, C228T and C250T, enriched in melanoma metastasis. We developed isogenic clonal cell lines containing the TERTp mutations and utilized dual-color expression reporters steered by the endogenous Telomerase promoter, giving us allelic resolution. This approach allowed us to monitor morpholomic variations induced by these mutations. TERTp mutation-bearing cells exhibited significant morpholome differences from their wild-type counterparts, with increased allele expression patterns, augmented wound-healing rates, and unique spatiotemporal dynamics. Notably, the C250T mutation exerted more pronounced changes in the morpholome than C228T, suggesting a differential role in metastatic potential. Our findings underscore the distinct influence of TERTp mutations on melanoma's cellular architecture and behavior. The C250T mutation may offer a unique morpholomic and systems-driven advantage for metastasis. These insights provide a foundational understanding of how a non-coding mutation in melanoma metastasis affects the system, manifesting in cellular morpholome. Author summary: This work explores how specific genetic changes, known as telomerase promoter mutations, influence the shape and behavior of melanoma cells, a highly metastatic and deadly type of skin cancer. These mutations, C228T and C250T, are common in melanoma and are thought to make the cancer more aggressive and metastatic. Cell lines with these mutations were created, and advanced imaging and deep learning techniques were used to investigate them. We reveal that cells with the C250T mutation showed more significant cellular morphology and movement changes than cells with the C228T mutation or normal cells. This suggests that the C250T mutation might play a bigger role in helping melanoma spread throughout the body. Detailed changes due to these mutations were visualized and understood using cutting-edge technology to analyze the impact on single cells. This work is essential because it helps illustrate how tiny genetic changes can lead to significant differences in metastatic behavior. This could lead to better ways to improve early diagnoses and treatment of metastatic melanoma. The findings provide a clearer picture of how melanoma cells evolve and spread, which could guide future cancer research and therapy development. [ABSTRACT FROM AUTHOR]

The symbiosis between rhizobia and legumes is characterized by a complex molecular dialogue in which the bacterial NodD protein plays a major role due to its capacity to activate the expression of the nodulation genes in the presence of appropiate flavonoids. These genes are involved in the synthesis of molecules, the nodulation factors (NF), responsible for launching the nodulation process. Rhizobium tropici CIAT 899, a rhizobial strain that nodulates Phaseolus vulgaris, is characterized by its tolerance to multiple environmental stresses such as high temperatures, acidity or elevated osmolarity. This strain produces nodulation factors under saline stress and the same set of CIAT 899 nodulation genes activated by inducing flavonoids are also up-regulated in a process controlled by the NodD2 protein. In this paper, we have studied the effect of osmotic stress (high mannitol concentrations) on the R. tropici CIAT 899 transcriptomic response. In the same manner as with saline stress, the osmotic stress mediated NF production and export was controlled directly by NodD2. In contrast to previous reports, the nodA2FE operon and the nodA3 and nodD1 genes were up-regulated with mannitol, which correlated with an increase in the production of biologically active NF. Interestingly, in these conditions, this regulatory protein controlled not only the expression of nodulation genes but also the expression of other genes involved in protein folding and synthesis, motility, synthesis of polysaccharides and, surprinsingly, nitrogen fixation. Moreover, the non-metabolizable sugar dulcitol was also able to induce the NF production and the activation of nod genes in CIAT 899. [ABSTRACT FROM AUTHOR]

Recent experiments showed that engineered Escherichia coli colonies grow and self-organize into periodic stripes with high and low cell densities in semi-solid agar. The stripes develop sequentially behind a radially propagating colony front, similar to the formation of many other periodic patterns in nature. These bacteria were created by genetically coupling the intracellular chemotaxis pathway of wild-type cells with a quorum sensing module through the protein CheZ. In this paper, we develop multiscale models to investigate how this intracellular pathway affects stripe formation. We first develop a detailed hybrid model that treats each cell as an individual particle and incorporates intracellular signaling via an internal ODE system. To overcome the computational cost of the hybrid model caused by the large number of cells involved, we next derive a mean-field PDE model from the hybrid model using asymptotic analysis. We show that this analysis is justified by the tight agreement between the PDE model and the hybrid model in 1D simulations. Numerical simulations of the PDE model in 2D with radial symmetry agree with experimental data semi-quantitatively. Finally, we use the PDE model to make a number of testable predictions on how the stripe patterns depend on cell-level parameters, including cell speed, cell doubling time and the turnover rate of intracellular CheZ. [ABSTRACT FROM AUTHOR]

During clathrin-mediated endocytosis in yeast cells, short actin filaments (< 200nm) and crosslinking protein fimbrin assemble to drive the internalization of the plasma membrane. However, the organization of the actin meshwork during endocytosis remains largely unknown. In addition, only a small fraction of the force necessary to elongate and pinch off vesicles can be accounted for by actin polymerization alone. In this paper, we used mathematical modeling to study the self-organization of rigid actin filaments in the presence of elastic crosslinkers in conditions relevant to endocytosis. We found that actin filaments condense into either a disordered meshwork or an ordered bundle depending on filament length and the mechanical and kinetic properties of the crosslinkers. Our simulations also demonstrated that these nanometer-scale actin structures can store a large amount of elastic energy within the crosslinkers (up to 10kBT per crosslinker). This conversion of binding energy into elastic energy is the consequence of geometric constraints created by the helical pitch of the actin filaments, which results in frustrated configurations of crosslinkers attached to filaments. We propose that this stored elastic energy can be used at a later time in the endocytic process. As a proof of principle, we presented a simple mechanism for sustained torque production by ordered detachment of crosslinkers from a pair of parallel filaments. [ABSTRACT FROM AUTHOR]

The development of ectodermal organs begins with the formation of a stratified epithelial placode that progressively invaginates into the underlying mesenchyme as the organ takes its shape. Signaling by secreted molecules is critical for epithelial morphogenesis, but how that information leads to cell rearrangement and tissue shape changes remains an open question. Using the mouse dentition as a model, we first establish that non-muscle myosin II is essential for dental epithelial invagination and show that it functions by promoting cell-cell adhesion and persistent convergent cell movements in the suprabasal layer. Shh signaling controls these processes by inducing myosin II activation via AKT. Pharmacological induction of AKT and myosin II can also rescue defects caused by the inhibition of Shh. Together, our results support a model in which the Shh signal is transmitted through myosin II to power effective cellular rearrangement for proper dental epithelial invagination. Author summary: During embryonic development, teeth, hair follicles, and glands are examples of ectodermally-derived organs that are formed from slightly thickened epithelial layers, called placodes. These placodes undergo remarkable morphological transformations to first invaginate as an epithelial bud and later morph into a more complex structure resembling the adult organ. Movement and rearrangement of epithelial cells are thought to drive tooth invagination. But there remain key knowledge gaps in our understanding of the underlying molecular mechanisms and signaling regulation that control cell movement and epithelial morphogenesis. Here, we use the developing mouse tooth as a model to show that Shh, a signaling molecule from the early tooth signaling center, plays an important role in activating the motor protein non-muscle myosin II in dental epithelial cells. Myosin II is in turn required to promote strong adhesion between cells and power dental epithelial cells to converge towards the midline of the tooth bud to drive tooth invagination. Our results thus define the in vivo function of myosin II during epithelial invagination and explain how signaling from secreted molecules can facilitate morphogenetic cell movements via myosin II. [ABSTRACT FROM AUTHOR]

The collective migration of keratinocytes during wound healing requires both the generation and transmission of mechanical forces for individual cellular locomotion and the coordination of movement across cells. Leader cells along the wound edge transmit mechanical and biochemical cues to ensuing follower cells, ensuring their coordinated direction of migration across multiple cells. Despite the observed importance of mechanical cues in leader cell formation and in controlling coordinated directionality of cell migration, the underlying biophysical mechanisms remain elusive. The mechanically-activated ion channel PIEZO1 was recently identified to play an inhibitory role during the reepithelialization of wounds. Here, through an integrative experimental and mathematical modeling approach, we elucidate PIEZO1's contributions to collective migration. Time-lapse microscopy reveals that PIEZO1 activity inhibits leader cell formation at the wound edge. To probe the relationship between PIEZO1 activity, leader cell formation and inhibition of reepithelialization, we developed an integrative 2D continuum model of wound closure that links observations at the single cell and collective cell migration scales. Through numerical simulations and subsequent experimental validation, we found that coordinated directionality plays a key role during wound closure and is inhibited by upregulated PIEZO1 activity. We propose that PIEZO1-mediated retraction suppresses leader cell formation which inhibits coordinated directionality between cells during collective migration. Author summary: During the healing of a wound, cells called keratinocytes that make up the outer layer of the skin migrate collectively to close the wound gap. The mechanically activated ion channel PIEZO1 was previously found to inhibit wound closure. Here, through a combined modeling and experimental approach, we investigate the role of PIEZO1 in regulating collective migration. Specialized cells called leader cells, which typically form along the wound edge, are important for guiding the migration of neighboring cells. These leader cells dictate the coordinated directionality, or the cohesiveness of the migration direction between neighboring cells, through the transmission of mechanical and biochemical cues. We find that PIEZO1 activity inhibits the formation of these leader cells and, as a result, inhibits cell coordinated directionality causing the collective movement of cells to become disorganized and less effective in closing the wound. Our findings shed light on the complex mechanisms underlying collective migration, providing valuable insight into how mechanical cues affect the movement of cells during wound closure. [ABSTRACT FROM AUTHOR]

In the current era of big data, the amount of data available is continuously increasing. Both the number and types of samples, or features, are on the rise. The mixing of distinct features often makes interpretation more difficult. However, separate analysis of individual types requires subsequent integration. A tensor is a useful framework to deal with distinct types of features in an integrated manner without mixing them. On the other hand, tensor data is not easy to obtain since it requires the measurements of huge numbers of combinations of distinct features; if there are m kinds of features, each of which has N dimensions, the number of measurements needed are as many as Nm, which is often too large to measure. In this paper, I propose a new method where a tensor is generated from individual features without combinatorial measurements, and the generated tensor was decomposed back to matrices, by which unsupervised feature extraction was performed. In order to demonstrate the usefulness of the proposed strategy, it was applied to synthetic data, as well as three omics datasets. It outperformed other matrix-based methodologies. [ABSTRACT FROM AUTHOR]

Cell interaction with biomaterials is one of the keystones to developing medical devices for tissue engineering applications. Biomaterials are the scaffolds that give three-dimensional support to the cells, and are vectors that deliver the cells to the injured tissue requiring repair. Features of biomaterials can influence the behaviour of the cells and consequently the efficacy of the tissue-engineered product. The adhesion, distribution and motility of the seeded cells onto the scaffold represent key aspects, and must be evaluated in vitro during the product development, especially when the efficacy of a specific tissue-engineered product depends on viable and functional cell loading. In this work, we propose a non-invasive and non-destructive imaging analysis for investigating motility, viability and distribution of Mesenchymal Stem Cells (MSCs) on silk fibroin-based alginate microcarriers, to test the adhesion capacity of the fibroin coating onto alginate which is known to be unsuitable for cell adhesion. However, in depth characterization of the biomaterial is beyond the scope of this paper. Scaffold-loaded MSCs were stained with Calcein-AM and Ethidium homodimer-1 to detect live and dead cells, respectively, and counterstained with Hoechst to label cell nuclei. Time-lapse Light Sheet Fluorescent Microscopy (LSFM) was then used to produce three-dimensional images of the entire cells-loaded fibroin/alginate microcarriers. In order to quantitatively track the cell motility over time, we also developed an open source user friendly software tool called Fluorescent Cell Tracker in Three-Dimensions (F-Tracker3D). Combining LSFM with F-Tracker3D we were able for the first time to assess the distribution and motility of stem cells in a non-invasive, non-destructive, quantitative, and three-dimensional analysis of the entire surface of the cell-loaded scaffold. We therefore propose this imaging technique as an innovative holistic tool for monitoring cell-biomaterial interactions, and as a tool for the design, fabrication and functionalization of a scaffold as a medical device. [ABSTRACT FROM AUTHOR]

During wound healing, skin function is restored by the action of several cell types that undergo differentiation, migration, proliferation and/or apoptosis. These dynamics are tightly regulated by the evolution of the extra cellular matrix (ECM) contents along the process. Pharmacologically active flavonoids have shown to exhibit useful physiological properties interesting in pathological states. Among them, oleanolic acid (OA), a pentacyclic triterpene, shows promising properties over wound healing, as increased cell migration in vitro and improved wound resolution in vivo. In this paper, we pursued to disclose the molecular mechanisms underlying those effects, by using an in vitro scratch assay in two epithelial cell lines of different linage: non-malignant mink lung epithelial cells, Mv1Lu; and human breast cancer cells, MDA-MB-231. In every case, we observed that OA clearly enhanced cell migration for in vitro scratch closure. This correlated with the stimulation of molecular pathways related to mitogen-activated protein (MAP) kinases, as ERK1,2 and Jun N-terminal kinase (JNK) 1,2 activation and c-Jun phosphorylation. Moreover, MDA-MB-231 cells treated with OA displayed an altered gene expression profile affecting transcription factor genes (c-JUN) as well as proteins involved in migration and ECM dynamics (PAI1), in line with the development of an epithelial to mesenchymal transition (EMT) status. Strikingly, upon OA treatment, we observed changes in the epidermal growth factor receptor (EGFR) subcellular localization, while interfering with its signalling completely prevented migration effects. This data provides a physiological framework supporting the notion that lipophilic plant extracts used in traditional medicine, might modulate wound healing processes in vivo through its OA contents. The molecular implications of these observations are discussed. [ABSTRACT FROM AUTHOR]

Gliomas are malignant tumors that are commonly observed in primary brain cancer. Glioma cells migrate through a dense network of normal cells in microenvironment and spread long distances within brain. In this paper we present a two-dimensional multiscale model in which a glioma cell is surrounded by normal cells and its migration is controlled by cell-mechanical components in the microenvironment via the regulation of myosin II in response to chemoattractants. Our simulation results show that the myosin II plays a key role in the deformation of the cell nucleus as the glioma cell passes through the narrow intercellular space smaller than its nuclear diameter. We also demonstrate that the coordination of biochemical and mechanical components within the cell enables a glioma cell to take the mode of amoeboid migration. This study sheds lights on the understanding of glioma infiltration through the narrow intercellular spaces and may provide a potential approach for the development of anti-invasion strategies via the injection of chemoattractants for localization. [ABSTRACT FROM AUTHOR]

Collective invasion of cells plays a fundamental role in tissue growth, wound healing, immune response and cancer metastasis. This paper aimed to investigate cytokeratin-14 (CK14) expression and analyze its association with collective invasion in the invasive front of salivary adenoid cystic carcinoma (SACC) to uncover the role of collective invasion in SACC. Here, in the clinical data of 121 patients with SACC, the positive expression of CK14 was observed in 35/121(28.93%) of the invasive front of SACC. CK14 expression in the invasive front, local regional recurrence and distant metastasis were independent and significant prognostic factors in SACC patients. Then, we found that in an ex vivo 3D culture assay, CK14 siRNA receded the collective invasion, and in 2D monolayer culture, CK14 overexpression induced a collective SACC cell migration. These data indicated that the presence of characterized CK14+ cells in the invasive front of SACC promoted collective cell invasion of SACC and may be a biomarker of SACC with a worse prognosis. [ABSTRACT FROM AUTHOR]

We have quantified the photomovement behavior of a suspension of Euglena gracilis representing a behavioral response to a light gradient. Despite recent measurements of phototaxis and photophobicity, the details of macroscopic behavior of cell photomovements under conditions of light intensity gradients, which are critical to understand recent experiments on spatially localized bioconvection patterns, have not been fully understood. In this paper, the flux of cell number density under a light intensity gradient was measured by the following two experiments. In the first experiment, a capillary containing the cell suspension was illuminated with different light intensities in two regions. In the steady state, the differences of the cell numbers in the two regions normalized by the total number were proportional to the light difference, where the light intensity difference ranged from 0.5–2.0 μmol m−2 s−1. The proportional coefficient was positive (i.e., the bright region contained many microorganisms) when the mean light intensity was weak (1.25 μmol m−2 s−1), whereas it was negative when the mean intensity was strong (13.75 μmol m−2 s−1). In the second experiment, a shallow rectangular container of the suspension was illuminated with stepwise light intensities. The cell number density distribution exhibited a single peak at the position where the light intensity was about Ic ≃ 3.8 μmol m−2 s−1. These results suggest that the suspension of E. gracilis responded to the light gradient and that the favorable light intensity was Ic. [ABSTRACT FROM AUTHOR]

Cell intercalation is a highly directed cell rearrangement that is essential for animal morphogenesis. As such, intercalation requires orchestration of cell polarity across the plane of the tissue. CDC-42 is a Rho family GTPase with key functions in cell polarity, yet its role during epithelial intercalation has not been established because its roles early in embryogenesis have historically made it difficult to study. To circumvent these early requirements, in this paper we use tissue-specific and conditional loss-of-function approaches to identify a role for CDC-42 during intercalation of the Caenorhabditis elegans dorsal embryonic epidermis. CDC-42 activity is enriched in the medial tips of intercalating cells, which extend as cells migrate past one another. Moreover, CDC-42 is involved in both the efficient formation and orientation of cell tips during cell rearrangement. Using conditional loss-of-function we also show that the PAR complex functions in tip formation and orientation. Additionally, we find that the sole C. elegans Eph receptor, VAB-1, functions during this process in an Ephrin-independent manner. Using epistasis analysis, we find that vab-1 lies in the same genetic pathway as cdc-42 and is responsible for polarizing CDC-42 activity to the medial tip. Together, these data establish a previously uncharacterized role for polarized CDC-42, in conjunction with PAR-6, PAR-3 and an Eph receptor, during epithelial intercalation. [ABSTRACT FROM AUTHOR]

In prospective human exploration of outer space, the need to preserve a species over several generations under changed gravity conditions may arise. This paper demonstrates our results in the creation of the third generation of fruit fly Drosophila melanogaster (third-stage larvae) during the 44.5-day space flight (Foton-M4 satellite (2014, Russia)), then the fourth generation on Earth and the fifth generation again in conditions of the 12-day space flight (2014, in the Russian Segment of the ISS). The species preserves fertility despite a number of changes in the level of expression and content of cytoskeletal proteins, which are the key components of the cleavage spindle and the contractile ring of cells. The results of transcriptome screening and space analysis of cytoskeletal proteins show that the exposure to weightless conditions leads to the increased transcription of metabolic genes, cuticle components and the decreased transcription of genes involved in morphogenesis, cell differentiation, cytoskeletal organization and genes associated with the plasma membrane. “Subsequent” exposure to the microgravity for 12 days resulted in an even more significant increase/decrease in the transcription of the same genes. On the contrary, the transition from the microgravity conditions to the gravity of Earth leads to the increased transcription of genes whose products are involved in the morphogenesis, cytoskeletal organization, motility of cells and transcription regulation, and to the decreased transcription of cuticle genes and proteolytic processes. [ABSTRACT FROM AUTHOR]

With cutting-edge live microscopy and image analysis, biologists can now systematically track individual cells in complex tissues and quantify cellular behavior over extended time windows. Computational approaches that utilize the systematic and quantitative data are needed to understand how cells interact in vivo to give rise to the different cell types and 3D morphology of tissues. An agent-based, minimum descriptive modeling and analysis framework is presented in this paper to study C. elegans embryogenesis. The framework is designed to incorporate the large amounts of experimental observations on cellular behavior and reserve data structures/interfaces that allow regulatory mechanisms to be added as more insights are gained. Observed cellular behaviors are organized into lineage identity, timing and direction of cell division, and path of cell movement. The framework also includes global parameters such as the eggshell and a clock. Division and movement behaviors are driven by statistical models of the observations. Data structures/interfaces are reserved for gene list, cell-cell interaction, cell fate and landscape, and other global parameters until the descriptive model is replaced by a regulatory mechanism. This approach provides a framework to handle the ongoing experiments of single-cell analysis of complex tissues where mechanistic insights lag data collection and need to be validated on complex observations. [ABSTRACT FROM AUTHOR]

Bacteria live in social communities, where the ability to sense and respond to interspecies and environmental signals is critical for survival. We previously showed the pathogen Pseudomonas aeruginosa detects secreted peptides from bacterial competitors and navigates through interspecies signal gradients using pilus-based motility. Yet, it was unknown whether P. aeruginosa utilizes a designated chemosensory system for this behavior. Here, we performed a systematic genetic analysis of a putative pilus chemosensory system, followed by high-speed live-imaging and single-cell tracking, to reveal behaviors of mutants that retain motility but are blind to interspecies signals. The enzymes predicted to methylate (PilK) and demethylate (ChpB) the putative pilus chemoreceptor, PilJ, are necessary for cells to control the direction of migration. While these findings implicate PilJ as a bona fide chemoreceptor, such function had yet to be experimentally defined, as full-length PilJ is essential for motility. Thus, we constructed systematic genetic modifications of PilJ and found that without the predicted ligand binding domains or predicted methylation sites, cells lose the ability to detect competitor gradients, despite retaining pilus-mediated motility. Chemotaxis trajectory analysis revealed that increased probability and size of P. aeruginosa pilus-mediated steps towards S. aureus peptides, versus steps away, determines motility bias in wild-type cells. However, PilJ mutants blind to interspecies signals take less frequent steps towards S. aureus or steps of equal size towards and away. Collectively, this work uncovers the chemosensory nature of PilJ, provides insight into how cell movements are biased during pilus-based chemotaxis, and identifies chemotactic interactions necessary for bacterial survival in polymicrobial communities, revealing putative pathways where therapeutic intervention might disrupt bacterial communication. Bacteria live in social communities, where the ability to sense and respond to interspecies and environmental signals is critical for survival. This study shows that when traveling on surfaces by type IV pili mediated motility, the bacterium Pseudomonas aeruginosa uses a designated chemoreceptor, PilJ, to detect and respond to interspecies signals. [ABSTRACT FROM AUTHOR]

Amoeboid cell motility is relevant in a wide variety of biomedical processes such as wound healing, cancer metastasis, and embryonic morphogenesis. It is characterized by pronounced changes of the cell shape associated with expansions and retractions of the cell membrane, which result in a crawling kind of locomotion. Despite existing computational models of amoeboid motion, the inference of expansion and retraction components of individual cells, the corresponding classification of cells, and the a priori specification of the parameter regime to achieve a specific motility behavior remain challenging open problems. We propose a novel model of the spatio-temporal evolution of two-dimensional cell contours comprising three biophysiologically motivated components: a stochastic term accounting for membrane protrusions and two deterministic terms accounting for membrane retractions by regularizing the shape and area of the contour. Mathematically, these correspond to the intensity of a self-exciting Poisson point process, the area-preserving curve-shortening flow, and an area adjustment flow. The model is used to generate contour data for a variety of qualitatively different, e.g., polarized and non-polarized, cell tracks that visually resemble experimental data very closely. In application to experimental cell tracks, we inferred the protrusion component and examined its correlation to common biomarkers: the F-actin density close to the membrane and its local motion. Due to the low model complexity, parameter estimation is fast, straightforward, and offers a simple way to classify contour dynamics based on two locomotion types: the amoeboid and a so-called fan-shaped type. For both types, we use cell tracks segmented from fluorescence imaging data of the model organism Dictyostelium discoideum. An implementation of the model is provided within the open-source software package AmoePy, a Python-based toolbox for analyzing and simulating amoeboid cell motility. [ABSTRACT FROM AUTHOR]

Experiments of cell migration and chemotaxis assays have been classically performed in the so-called Boyden Chambers. A recent technology, xCELLigence Real Time Cell Analysis, is now allowing to monitor the cell migration in real time. This technology measures impedance changes caused by the gradual increase of electrode surface occupation by cells during the course of time and provide a Cell Index which is proportional to cellular morphology, spreading, ruffling and adhesion quality as well as cell number. In this paper we propose a macroscopic mathematical model, based on advection-reaction-diffusion partial differential equations, describing the cell migration assay using the real-time technology. We carried out numerical simulations to compare simulated model dynamics with data of observed biological experiments on three different cell lines and in two experimental settings: absence of chemotactic signals (basal migration) and presence of a chemoattractant. Overall we conclude that our minimal mathematical model is able to describe the phenomenon in the real time scale and numerical results show a good agreement with the experimental evidences. [ABSTRACT FROM AUTHOR]

The expression of cancer stemness is believed to reduce the efficacy of current therapies against hepatocellular carcinoma (HCC). Understanding of the stemness-regulating signaling pathways incurred by a specific etiology can facilitate the development of novel targets for individualized therapy against HCC. Niche environments, such as virus-induced inflammation, may play a crucial role. However, the mechanisms linking inflammation and stemness expression in HCC remain unclear. Here we demonstrated the distinct role of inflammatory mediators in expressions of stemness-related properties involving the pluripotent octamer-binding transcription factor 4 (OCT4) in cell migration and drug resistance of hepatitis B virus-related HCC (HBV-HCC). We observed positive immunorecognition for macrophage chemoattractant protein 1 (MCP-1)/CD68 and OCT4/NANOG in HBV-HCC tissues. The inflammation-conditioned medium (inflamed-CM) generated by lipopolysaccharide-stimulated U937 human leukemia cells significantly increased the mRNA and protein levels of OCT4/NANOG preferentially in HBV-active (HBV+HBsAg+) HCC cells. The inflamed-CM also increased the side population (SP) cell percentage, green fluorescent protein (GFP)-positive cell population, and luciferase activity of OCT4 promoter-GFP/luciferase in HBV-active HCC cells. Furthermore, the inflamed-CM upregulated the expressions of insulin-like growth factor-I (IGF-I)/IGF-I receptor (IGF-IR) and activated IGF-IR/Akt signaling in HBV-HCC. The IGF-IR phosphorylation inhibitor picropodophyllin (PPP) suppressed inflamed-CM-induced OCT4 and NANOG levels in HBV+HBsAg+ Hep3B cells. Forced expression of OCT4 significantly increased the secondary sphere formation and cell migration, and reduced susceptibility of HBV-HCC cells to cisplatin, bleomycin, and doxorubicin. Taking together, our results show that niche inflammatory mediators play critical roles in inducing the expression of stemness-related properties involving IGF-IR activation, and the upregulation of OCT4 contributes to cancer migration and drug resistance of HBV-HCC cells. Findings in this paper would provide potential targets for a therapeutic strategy targeting on inflammatory environment for HBV-HCC. [ABSTRACT FROM AUTHOR]

RNA viruses exploit host cells by co-opting host factors and lipids and escaping host antiviral responses. Previous genome-wide screens with Tomato bushy stunt virus (TBSV) in the model host yeast have identified 18 cellular genes that are part of the actin network. In this paper, we show that the p33 viral replication factor interacts with the cellular cofilin (Cof1p), which is an actin depolymerization factor. Using temperature-sensitive (ts) Cof1p or actin (Act1p) mutants at a semi-permissive temperature, we find an increased level of TBSV RNA accumulation in yeast cells and elevated in vitro activity of the tombusvirus replicase. We show that the large p33 containing replication organelle-like structures are located in the close vicinity of actin patches in yeast cells or around actin cable hubs in infected plant cells. Therefore, the actin filaments could be involved in VRC assembly and the formation of large viral replication compartments containing many individual VRCs. Moreover, we show that the actin network affects the recruitment of viral and cellular components, including oxysterol binding proteins and VAP proteins to form membrane contact sites for efficient transfer of sterols to the sites of replication. Altogether, the emerging picture is that TBSV, via direct interaction between the p33 replication protein and Cof1p, controls cofilin activities to obstruct the dynamic actin network that leads to efficient subversion of cellular factors for pro-viral functions. In summary, the discovery that TBSV interacts with cellular cofilin and blocks the severing of existing filaments and the formation of new actin filaments in infected cells opens a new window to unravel the way by which viruses could subvert/co-opt cellular proteins and lipids. By regulating the functions of cofilin and the actin network, which are central nodes in cellular pathways, viruses could gain supremacy in subversion of cellular factors for pro-viral functions. [ABSTRACT FROM AUTHOR]

There is a foundational need for quality control tools in stem cell laboratories engaged in basic research, regenerative therapies, and toxicological studies. These tools require automated methods for evaluating cell processes and quality during in vitro passaging, expansion, maintenance, and differentiation. In this paper, an unbiased, automated high-content profiling toolkit, StemCellQC, is presented that non-invasively extracts information on cell quality and cellular processes from time-lapse phase-contrast videos. Twenty four (24) morphological and dynamic features were analyzed in healthy, unhealthy, and dying human embryonic stem cell (hESC) colonies to identify those features that were affected in each group. Multiple features differed in the healthy versus unhealthy/dying groups, and these features were linked to growth, motility, and death. Biomarkers were discovered that predicted cell processes before they were detectable by manual observation. StemCellQC distinguished healthy and unhealthy/dying hESC colonies with 96% accuracy by non-invasively measuring and tracking dynamic and morphological features over 48 hours. Changes in cellular processes can be monitored by StemCellQC and predictions can be made about the quality of pluripotent stem cell colonies. This toolkit reduced the time and resources required to track multiple pluripotent stem cell colonies and eliminated handling errors and false classifications due to human bias. StemCellQC provided both user-specified and classifier-determined analysis in cases where the affected features are not intuitive or anticipated. Video analysis algorithms allowed assessment of biological phenomena using automatic detection analysis, which can aid facilities where maintaining stem cell quality and/or monitoring changes in cellular processes are essential. In the future StemCellQC can be expanded to include other features, cell types, treatments, and differentiating cells. [ABSTRACT FROM AUTHOR]

Tracking motile cells in time-lapse series is challenging and is required in many biomedical applications. Cell tracks can be mathematically represented as acyclic oriented graphs. Their vertices describe the spatio-temporal locations of individual cells, whereas the edges represent temporal relationships between them. Such a representation maintains the knowledge of all important cellular events within a captured field of view, such as migration, division, death, and transit through the field of view. The increasing number of cell tracking algorithms calls for comparison of their performance. However, the lack of a standardized cell tracking accuracy measure makes the comparison impracticable. This paper defines and evaluates an accuracy measure for objective and systematic benchmarking of cell tracking algorithms. The measure assumes the existence of a ground-truth reference, and assesses how difficult it is to transform a computed graph into the reference one. The difficulty is measured as a weighted sum of the lowest number of graph operations, such as split, delete, and add a vertex and delete, add, and alter the semantics of an edge, needed to make the graphs identical. The measure behavior is extensively analyzed based on the tracking results provided by the participants of the first Cell Tracking Challenge hosted by the 2013 IEEE International Symposium on Biomedical Imaging. We demonstrate the robustness and stability of the measure against small changes in the choice of weights for diverse cell tracking algorithms and fluorescence microscopy datasets. As the measure penalizes all possible errors in the tracking results and is easy to compute, it may especially help developers and analysts to tune their algorithms according to their needs. [ABSTRACT FROM AUTHOR]

The interactions occurring between a virus and a host cell during a viral infection are complex. The purpose of this paper was to analyze altered cellular protein levels in porcine transmissible gastroenteritis coronavirus (TGEV)-infected swine testicular (ST) cells in order to determine potential virus-host interactions. A proteomic approach using isobaric tags for relative and absolute quantitation (iTRAQ)-coupled two-dimensional liquid chromatography-tandem mass spectrometry identification was conducted on the TGEV-infected ST cells. The results showed that the 4-plex iTRAQ-based quantitative approach identified 4,112 proteins, 146 of which showed significant changes in expression 48 h after infection. At 64 h post infection, 219 of these proteins showed significant change, further indicating that a larger number of proteomic changes appear to occur during the later stages of infection. Gene ontology analysis of the altered proteins showed enrichment in multiple biological processes, including cell adhesion, response to stress, generation of precursor metabolites and energy, cell motility, protein complex assembly, growth, developmental maturation, immune system process, extracellular matrix organization, locomotion, cell-cell signaling, neurological system process, and cell junction organization. Changes in the expression levels of transforming growth factor beta 1 (TGF-β1), caspase-8, and heat shock protein 90 alpha (HSP90α) were also verified by western blot analysis. To our knowledge, this study is the first time the response profile of ST host cells following TGEV infection has been analyzed using iTRAQ technology, and our description of the late proteomic changes that are occurring after the time of vigorous viral production are novel. Therefore, this study provides a solid foundation for further investigation, and will likely help us to better understand the mechanisms of TGEV infection and pathogenesis. [ABSTRACT FROM AUTHOR]

Bacteria of the family Rickettsiaceae have always been largely studied not only for their importance in the medical field, but also as model systems in evolutionary biology. In fact, they share a recent common ancestor with mitochondria. The most studied species, belonging to genera Rickettsia and Orientia, are hosted by terrestrial arthropods and include many human pathogens. Nevertheless, recent findings show that a large part of Rickettsiaceae biodiversity actually resides outside the group of well-known pathogenic bacteria. Collecting data on these recently described non-conventional members of the family is crucial in order to gain information on ancestral features of the whole group. Although bacteria of the family Rickettsiaceae, and of the whole order Rickettsiales, are formally described as non-flagellated prokaryotes, some recent findings renewed the debate about this feature. In this paper we report the first finding of members of the family displaying numerous flagella and active movement inside their host cells. These two new taxa are hosted in aquatic environments by protist ciliates and are described here by means of ultrastructural and molecular characterization. Data here reported suggest that the ancestor of Rickettsiales displayed flagellar movement and re-evaluate the hypothesis that motility played a key-role in the origin of mitochondria. Moreover, our study highlights that the aquatic environment represents a well exploited habitat for bacteria of the family Rickettsiaceae. Our results encourage a deep re-consideration of ecological and morphological traits of the family and of the whole order. [ABSTRACT FROM AUTHOR]

Traction force microscopy (TFM) is a quantitative technique for measuring cellular traction force, which is important in understanding cellular mechanotransduction processes. Traditional TFM has a significant limitation in that it has a low measurement throughput, commonly one per TFM dish, due to a lack of cell position information. To obtain enough cellular traction force data, an onerous workload is required including numerous TFM dish preparations and heavy cell-seeding activities, creating further difficulty in achieving identical experimental conditions among batches. In this paper, we present an improved-throughput TFM method using the well-developed microcontact printing technique and chemical modifications of linking microbeads to the gel surface to address these limitations. Chemically linking the microbeads to the gel surface has no significant influence on cell proliferation, morphology, cytoskeleton, and adhesion. Multiple pairs of force loaded and null force fluorescence images can be easily acquired by means of manual microscope with the aid of a fluorescence micropattern made by microcontact printing. Furthermore, keeping the micropattern separate from cells by using gels effectively eliminates the potential negative effect of the micropattern on the cells. This novel design greatly improves the analysis throughput of traditional TFM from one to at least twenty cells per petri dish without losing unique advantages, including a high spatial resolution of traction measurements. This newly developed method will boost the investigation of cell-matrix mechanical interactions. [ABSTRACT FROM AUTHOR]

Agent-based simulation is a powerful method for investigating the complex interplay of the processes occurring in a lymph node during an adaptive immune response. We have previously established an agent-based modeling framework for the interactions between T cells and dendritic cells within the paracortex of lymph nodes. This model simulates in three dimensions the "random-walk" T cell motility observed in vivo, so that cells interact in space and time as they process signals and commit to action such as proliferation. On-lattice treatment of cell motility allows large numbers of densely packed cells to be simulated, so that the low frequency of T cells capable of responding to a single antigen can be dealt with realistically. In this paper we build on this model by incorporating new numerical methods to address the crucial processes of T cell ingress and egress, and chemotaxis, within the lymph node. These methods enable simulation of the dramatic expansion and contraction of the T cell population in the lymph node paracortex during an immune response. They also provide a novel probabilistic method to simulate chemotaxis that will be generally useful in simulating other biological processes in which chemotaxis is an important feature. [ABSTRACT FROM AUTHOR]

The development of an organism is accompanied by various cellular morphogenetic movements, changes in cellular as well as nuclear morphology and transcription programs. Recent evidence suggests that intra and inter-cellular connections mediated by various adhesion proteins contribute to defining nuclear morphology. In addition, three dimensional organization of the cell nucleus regulate the transcription programs. However the link between cellular morphogenetic movements and its coupling to nuclear function in a developmental context is poorly understood. In this paper we use a point perturbation by tissue level laser ablation and sheet perturbation by application of force using magnetic tweezers to alter cellular morphogenetic movements and probe its impact on nuclear morphology and segmental gene expression patterns. Mechanical perturbations during blastoderm stage in a developing Drosophila embryo resulted in localized alterations in nuclear morphology and cellular movement. In addition, global defects in germ-band (GB) extension and retraction are observed when external force is applied during morphogenetic movements, suggesting a long-range physical coupling within the GB layer of cells. Further local application of force resulted in redistribution of non muscle myosin-II in the GB layer. Finally these perturbations lead to altered segmental gene (engrailed) expression patterns later during the development. Our observations suggest that there exists a tight regulation between nuclear morphology and cellular adhesive connections during morphogenetic movement of cells in the embryo. The observed spatial changes in patterning genes, with perturbation, highlight the importance of nuclear integrity to cellular movement in establishing gene expression program in a developmental system. [ABSTRACT FROM AUTHOR]

Random walks on networks are widely used to model stochastic processes such as search strategies, transportation problems or disease propagation. A prominent example of such process is the dynamics of naive T cells within the lymph node while they are scanning for antigens. The observed T cells trajectories in small sub-volumes of the lymph node are well modeled as a random walk and they have been shown to follow the lymphatic conduit network as substrate for migration. One can then ask how does the connectivity patterns of the lymph node conduit network affect the T cells collective exploration behavior. In particular, does the network display properties that are uniform across the whole volume of the lymph node or can we distinguish some heterogeneities? We propose a workflow to accurately and efficiently define and compute these quantities on large networks, which enables us to characterize heterogeneities within a very large published dataset of Lymph Node Conduit Network. To establish the significance of our results, we compared the results obtained on the lymph node to null models of varying complexity. We identified significantly heterogeneous regions characterized as "remote regions" at the poles and next to the medulla, while a large portion of the network promotes uniform exploration by T cells. Author summary: Lymph nodes are organs in which actors of the immune system meet. In particular, the encounter between the naive T cells and their specific antigens occurs in lymph nodes. This event triggers the adaptive immune response. T cells movement has been shown to be well described as a random walk, at least when they are measured on small sub-volumes of the lymph node. In parallel, it was shown that T-cells migrate following the lymphatic conduit network that span the lymph nodes. In this study, we ask, how does the connectivity pattern of the conduit network on which T cells move influences their collective exploration behavior? Are there regions in the lymph node conduit network which have distinct random walk related properties? The topological reconstruction of the lymph node conduit network was recently made available. The network is very large (about 200 000 nodes) and appears very regular, with most nodes being connected to three neighbours. We propose a workflow to detect heterogeneities in such large and quasi-regular networks, building on random walk on network tools, and the measure of two features which we interpret using a series of generated null models for comparison. We show that the lymph node conduit network displays remotely accessible regions at both poles and near medulla, with however most of the network promoting uniform exploration. [ABSTRACT FROM AUTHOR]

Living cells utilize signaling pathways to sense, transduce, and process information. As the extracellular stimulation often has rich temporal characteristics which may govern dynamic cellular responses, it is important to quantify the rate of information flow through the signaling pathways. In this study, we used an epithelial cell line expressing a light-activatable FGF receptor and an ERK activity reporter to assess the ability of the MAPK/ERK pathway to transduce signal encoded in a sequence of pulses. By stimulating the cells with random light pulse trains, we demonstrated that the MAPK/ERK channel capacity is at least 6 bits per hour. The input reconstruction algorithm detects the light pulses with 1-min accuracy 5 min after their occurrence. The high information transmission rate may enable the pathway to coordinate multiple processes including cell movement and respond to rapidly varying stimuli such as chemoattracting gradients created by other cells. Author summary: To respond to external stimulation, living cells need to transfer information from membrane receptors to downstream proteins that regulate physiological outcomes. In this study we used cells expressing a light-activatable receptor that transmits signals to MAPK/ERK transduction pathway, which regulates numerous physiological processes including proliferation, differentiation and cell motility. By stimulating these cells with various sequences of short light pulses we found that ERK, the last component of the considered signal transduction pathway, may receive at least 6 bits per hour. This bitrate allows 6 binary decisions per hour, enabling rapid responses to varied extracellular stimuli. [ABSTRACT FROM AUTHOR]

Nowadays, the appetite for the investment and mergers and acquisitions (M&A) activity in RFID companies is growing rapidly. Although the huge number of papers have addressed the topic of business valuation models based on statistical methods or neural network methods, only a few are dedicated to constructing a general framework for business valuation that improves the performance with network graph (NG) and the corresponding community mining (CM) method. In this study, an NG based business valuation model is proposed, where real options approach (ROA) integrating CM method is designed to predict the company’s net profit as well as estimate the company value. Three improvements are made in the proposed valuation model: Firstly, our model figures out the credibility of the node belonging to each community and clusters the network according to the evolutionary Bayesian method. Secondly, the improved bacterial foraging optimization algorithm (IBFOA) is adopted to calculate the optimized Bayesian posterior probability function. Finally, in IBFOA, bi-objective method is used to assess the accuracy of prediction, and these two objectives are combined into one objective function using a new Pareto boundary method. The proposed method returns lower forecasting error than 10 well-known forecasting models on 3 different time interval valuing tasks for the real-life simulation of RFID companies. [ABSTRACT FROM AUTHOR]

Muscle contractions are generated by cyclical interactions of myosin heads with actin filaments to form the actomyosin complex. To simulate actomyosin complex stable states, mathematical models usually define an energy landscape with a corresponding number of wells. The jumps between these wells are defined through rate constants. Almost all previous models assign these wells an infinite sharpness by imposing a relatively simple expression for the detailed balance, i.e., the ratio of the rate constants depends exponentially on the sole myosin elastic energy. Physically, this assumption corresponds to neglecting thermal fluctuations in the actomyosin complex stable states. By comparing three mathematical models, we examine the extent to which this hypothesis affects muscle model predictions at the single cross-bridge, single fiber, and organ levels in a ceteris paribus analysis. We show that including fluctuations in stable states allows the lever arm of the myosin to easily and dynamically explore all possible minima in the energy landscape, generating several backward and forward jumps between states during the lifetime of the actomyosin complex, whereas the infinitely sharp minima case is characterized by fewer jumps between states. Moreover, the analysis predicts that thermal fluctuations enable a more efficient contraction mechanism, in which a higher force is sustained by fewer attached cross-bridges. [ABSTRACT FROM AUTHOR]

Microtubules and their post-translational modifications are involved in major cellular processes. In severe diseases such as neurodegenerative disorders, tyrosinated tubulin and tyrosinated microtubules are in lower concentration. We present here a mechanistic mathematical model of the microtubule tyrosination cycle combining computational modeling and high-content image analyses to understand the key kinetic parameters governing the tyrosination status in different cellular models. That mathematical model is parameterized, firstly, for neuronal cells using kinetic values taken from the literature, and, secondly, for proliferative cells, by a change of two parameter values obtained, and shown minimal, by a continuous optimization procedure based on temporal logic constraints to formalize experimental high-content imaging data. In both cases, the mathematical models explain the inability to increase the tyrosination status by activating the Tubulin Tyrosine Ligase enzyme. The tyrosinated tubulin is indeed the product of a chain of two reactions in the cycle: the detyrosinated microtubule depolymerization followed by its tyrosination. The tyrosination status at equilibrium is thus limited by both reaction rates and activating the tyrosination reaction alone is not effective. Our computational model also predicts the effect of inhibiting the Tubulin Carboxy Peptidase enzyme which we have experimentally validated in MEF cellular model. Furthermore, the model predicts that the activation of two particular kinetic parameters, the tyrosination and detyrosinated microtubule depolymerization rate constants, in synergy, should suffice to enable an increase of the tyrosination status in living cells. Author summary: Microtubules, cytoskeletal proteins, are involved in essential biological processes such as mitosis, cardiomyocyte contraction and cell motility. The tyrosination reaction, a microtubule post-translational modification is dysregulated in cancer, cardiomyopathies and neuronal diseases. Despite significant advances in recent years, the precise mechanisms regulating the tyrosination cycle and the microtubule dynamics still lack an integrative approach with predictive mathematical modeling. We present a mathematical model of the detyrosination/tyrosination cycle parameterized for neurons and proliferative cells using literature and image-based screening data. The model first explains the inability to increase the tyrosination status by activating the Tubulin Tyrosine Ligase enzyme in those cellular models, second captures the inhibition effect of the Tubulin Carboxy Peptidase enzyme, and third predicts the necessity to combine two drugs to increase the tyrosination status in living cells. Overall, our mathematical model enhances the early drug research by providing critical mechanistic insights and identifying promising targets. [ABSTRACT FROM AUTHOR]

Epithelial tissues constitute an exotic type of active matter with non-linear properties reminiscent of amorphous materials. In the context of a proliferating epithelium, modeled by the quasistatic vertex model, we identify novel discrete tissue scale rearrangements, i.e. cellular rearrangement avalanches, which are a form of collective cell movement. During the avalanches, the vast majority of cells retain their neighbors, and the resulting cellular trajectories are radial in the periphery, a vortex in the core. After the onset of these avalanches, the epithelial area grows discontinuously. The avalanches are found to be stochastic, and their strength is correlated with the density of cells in the tissue. Overall, avalanches redistribute accumulated local spatial pressure along the tissue. Furthermore, the distribution of avalanche magnitudes is found to obey a power law, with an exponent consistent with sheer induced avalanches in amorphous materials. To understand the role of avalanches in organ development, we simulate epithelial growth of the Drosophila eye disc during the third instar using a computational model, which includes both chemical and mechanistic signaling. During the third instar, the morphogenetic furrow (MF), a ~10 cell wide wave of apical area constriction propagates through the epithelium. These simulations are used to understand the details of the growth process, the effect of the MF on the growth dynamics on the tissue scale, and to make predictions for experimental observations. The avalanches are found to depend on the strength of the apical constriction of cells in the MF, with a stronger apical constriction leading to less frequent and more pronounced avalanches. The results herein highlight the dependence of simulated tissue growth dynamics on relaxation timescales, and serve as a guide for in vitro experiments. Author summary: Epithelial tissues have interesting properties. They are often described as viscoelastic materials, behaving like an elastic solid on short time scales and as a liquid on long time scales. When tissues proliferate, cell division requires the cells to rearrange and displace each other. To relieve proliferative stress, cells are equipped with machinery that allows them to respond to mechanical cues and rearrange. Herein, we perform computational simulations, based on the vertex model, to investigate epithelial growth. In our simulations, when the tissue size reaches thousands of cells, we observe the prevalence of stochastic step-like growth discontinuities. These newly identified events, which we term avalanches, involve the collective rearrangement of all cells in the tissue, and they are accompanied with localized cellular pressure redistribution and a collective net radial displacement of cells. We study their properties in the simple setting of a spatially uniform and time independent growth model and in the context of an experimentally calibrated Drosophila eye disc growth model. Utilizing the eye disc growth model, we also investigate the relationship between localized cellular mechanical deformations and global growth dynamics. We conclude that avalanches constitute a macroscopic pathway for epithelial tissues to release accumulated proliferative stress when local processes are insufficient. [ABSTRACT FROM AUTHOR]

Lymphocytes have been described to perform different motility patterns such as Brownian random walks, persistent random walks, and Lévy walks. Depending on the conditions, such as confinement or the distribution of target cells, either Brownian or Lévy walks lead to more efficient interaction with the targets. The diversity of these motility patterns may be explained by an adaptive response to the surrounding extracellular matrix (ECM). Indeed, depending on the ECM composition, lymphocytes either display a floating motility without attaching to the ECM, or sliding and stepping motility with respectively continuous or discontinuous attachment to the ECM, or pivoting behaviour with sustained attachment to the ECM. Moreover, on the long term, lymphocytes either perform a persistent random walk or a Brownian-like movement depending on the ECM composition. How the ECM affects cell motility is still incompletely understood. Here, we integrate essential mechanistic details of the lymphocyte-matrix adhesions and lymphocyte intrinsic cytoskeletal induced cell propulsion into a Cellular Potts model (CPM). We show that the combination of de novo cell-matrix adhesion formation, adhesion growth and shrinkage, adhesion rupture, and feedback of adhesions onto cell propulsion recapitulates multiple lymphocyte behaviours, for different lymphocyte subsets and various substrates. With an increasing attachment area and increased adhesion strength, the cells' speed and persistence decreases. Additionally, the model predicts random walks with short-term persistent but long-term subdiffusive properties resulting in a pivoting type of motility. For small adhesion areas, the spatial distribution of adhesions emerges as a key factor influencing cell motility. Small adhesions at the front allow for more persistent motility than larger clusters at the back, despite a similar total adhesion area. In conclusion, we present an integrated framework to simulate the effects of ECM proteins on cell-matrix adhesion dynamics. The model reveals a sufficient set of principles explaining the plasticity of lymphocyte motility. Author summary: During immunosurveillance, lymphocytes patrol through tissues to interact with cancer cells, other immune cells, and pathogens. The efficiency of this process depends on the kinds of trajectories taken, ranging from simple Brownian walks to Lévy walks. The composition of the extracellular matrix (ECM), a network of macromolecules, affects the formation of cell-matrix adhesions, thus strongly influencing the way lymphocytes move. Here, we present a model of lymphocyte motility driven by adhesions that grow, shrink and rupture in response to the ECM and cellular forces. Compared to other models, our model is computationally light making it suitable for generating long term cell track data, while still capturing actin dynamics and adhesion turnover. Our model suggests that cell motility is affected by the force required to break adhesions and the rate at which new adhesions form. Adhesions can promote cell protrusion by inhibiting retrograde actin flow. After introducing this effect into the model, we found that it reduces the cellular diffusivity and that it promotes stick-slip behaviour. Furthermore, location and size of adhesion clusters determined cell persistence. Overall, our model explains the plasticity of lymphocyte behaviour in response to the ECM. [ABSTRACT FROM AUTHOR]

Chemotactic bacteria form emergent spatial patterns of variable cell density within cultures that are initially spatially uniform. These patterns are the result of chemical gradients that are created from the directed movement and metabolic activity of billions of cells. A recent study on pattern formation in wild bacterial isolates has revealed unique collective behaviors of the bacteria Enterobacter cloacae. As in other bacterial species, Enterobacter cloacae form macroscopic aggregates. Once formed, these bacterial clusters can migrate several millimeters, sometimes resulting in the merging of two or more clusters. To better understand these phenomena, we examine the formation and dynamics of thousands of bacterial clusters that form within a 22 cm square culture dish filled with soft agar over two days. At the macroscale, the aggregates display spatial order at short length scales, and the migration of cell clusters is superdiffusive, with a merging acceleration that is correlated with aggregate size. At the microscale, aggregates are composed of immotile cells surrounded by low density regions of motile cells. The collective movement of the aggregates is the result of an asymmetric flux of bacteria at the boundary. An agent-based model is developed to examine how these phenomena are the result of both chemotactic movement and a change in motility at high cell density. These results identify and characterize a new mechanism for collective bacterial motility driven by a transient, density-dependent change in motility. Author summary: Bacteria growing and swimming in soft agar often aggregate to form elaborate spatial patterns. Here we examine the patterns formed by the bacteria Enterobacter cloacae. An unusual behavior of these bacteria is the collective movement of cells after the initial aggregation into a tiny spot. Despite the majority of the cells within an aggregate being immotile at any point in the time, the flux of cells entering and leaving the aggregate, as motility is lost and regained in individual cells, led to a net, collective movement of the aggregate. These spots sometimes run into each other and combine. By looking at the cells within these spots under a microscope, we find that cells within each spot stop swimming. The process of switching back and forth between swimming and not swimming causes the movement and fusion of the spots. A numerical simulation shows that the migration and merging of these spots can be expected if the cells swim towards regions of space with high concentrations of attractant molecules and stop swimming in locations crowded with many cells. This work identifies a novel process through which populations of bacteria cooperate and control the movement of large groups of cells. [ABSTRACT FROM AUTHOR]

Predictive approaches such as virtual screening have been used in drug discovery with the objective of reducing developmental time and costs. Current machine learning and network-based approaches have issues related to generalization, usability, or model interpretability, especially due to the complexity of target proteins' structure/function, and bias in system training datasets. Here, we propose a new method "DRUIDom" (DRUg Interacting Domain prediction) to identify bio-interactions between drug candidate compounds and targets by utilizing the domain modularity of proteins, to overcome problems associated with current approaches. DRUIDom is composed of two methodological steps. First, ligands/compounds are statistically mapped to structural domains of their target proteins, with the aim of identifying their interactions. As such, other proteins containing the same mapped domain or domain pair become new candidate targets for the corresponding compounds. Next, a million-scale dataset of small molecule compounds, including those mapped to domains in the previous step, are clustered based on their molecular similarities, and their domain associations are propagated to other compounds within the same clusters. Experimentally verified bioactivity data points, obtained from public databases, are meticulously filtered to construct datasets of active/interacting and inactive/non-interacting drug/compound–target pairs (~2.9M data points), and used as training data for calculating parameters of compound–domain mappings, which led to 27,032 high-confidence associations between 250 domains and 8,165 compounds, and a finalized output of ~5 million new compound–protein interactions. DRUIDom is experimentally validated by syntheses and bioactivity analyses of compounds predicted to target LIM-kinase proteins, which play critical roles in the regulation of cell motility, cell cycle progression, and differentiation through actin filament dynamics. We showed that LIMK-inhibitor-2 and its derivatives significantly block the cancer cell migration through inhibition of LIMK phosphorylation and the downstream protein cofilin. One of the derivative compounds (LIMKi-2d) was identified as a promising candidate due to its action on resistant Mahlavu liver cancer cells. The results demonstrated that DRUIDom can be exploited to identify drug candidate compounds for intended targets and to predict new target proteins based on the defined compound–domain relationships. Datasets, results, and the source code of DRUIDom are fully-available at: https://github.com/cansyl/DRUIDom. Author summary: Drug development comprises several interlinked steps from designing drug candidate molecules to running clinical trials, with the aim to bring a new drug to market. A critical yet costly and labor-intensive stage is drug discovery, in which drug candidate molecules that specifically interact with the intended biomolecular target (mostly proteins) are identified. Lately, data-centric computational methods have been proposed to aid experimental procedures in drug discovery. These methods have the ability to rapidly assess large molecule libraries and reduce the time and cost of the process; however, most of them suffer from problems related to producing reliable biologically relevant results, preventing them from gaining real-world usage. Herein, we have developed a new method called DRUIDom (DRUg Interacting Domain prediction) to identify unknown interactions between drugs/drug candidate compounds and biological targets by utilizing the modular structure of proteins. For this, we identify the domains, i.e., the evolutionary and functional building blocks of proteins, where these potential drug compounds can bind, and utilize this information along with protein domain annotations to predict new drug targets. We have tested the biological relevance of DRUIDom on selected proteins that play critical roles in the progression of numerous types of cancer. Cell-based experimental results indicated that predicted inhibitors are effective even on drug-resistant cancer cells. Our results suggest DRUIDom produces novel and biologically relevant results that can be directly used in the early steps of the drug discovery process. [ABSTRACT FROM AUTHOR]

Biomaterial-driven modulation of cell adhesion and migration is a challenging aspect of tissue engineering. Here, we investigated the impact of surface-bound microgel arrays with variable geometry and adjustable cross-linking properties on cell adhesion and migration. We show that cell migration is inversely correlated with microgel array spacing, whereas directionality increases as array spacing increases. Focal adhesion dynamics is also modulated by microgel topography resulting in less dynamic focal adhesions on surface-bound microgels. Microgels also modulate the motility and adhesion of Sertoli cells used as a model for cell migration and adhesion. Both focal adhesion dynamics and speed are reduced on microgels. Interestingly, Gas2L1, a component of the cytoskeleton that mediates the interaction between microtubules and microfilaments, is dispensable for the regulation of cell adhesion and migration on microgels. Finally, increasing microgel cross-linking causes a clear reduction of focal adhesion turnover in Sertoli cells. These findings not only show that spacing and rigidity of surface-grafted microgels arrays can be effectively used to modulate cell adhesion and motility of diverse cellular systems, but they also form the basis for future developments in the fields of medicine and tissue engineering. [ABSTRACT FROM AUTHOR]

The dispersal or mixing of cells within cellular tissue is a crucial property for diverse biological processes, ranging from morphogenesis, immune action, to tumor metastasis. With the phenomenon of 'contact inhibition of locomotion,' it is puzzling how cells achieve such processes within a densely packed cohesive population. Here we demonstrate that a proper degree of cell-cell adhesiveness can, intriguingly, enhance the super-diffusive nature of individual cells. We systematically characterize the migration trajectories of crawling MDA-MB-231 cell lines, while they are in several different clustering modes, including freely crawling singles, cohesive doublets of two cells, quadruplets, and confluent population on two-dimensional substrate. Following data analysis and computer simulation of a simple cellular Potts model, which faithfully recapitulated all key experimental observations such as enhanced diffusivity as well as periodic rotation of cell-doublets and cell-quadruplets with mixing events, we found that proper combination of active self-propelling force and cell-cell adhesion is sufficient for generating the observed phenomena. Additionally, we found that tuning parameters for these two factors covers a variety of different collective dynamic states. Author summary: Dispersal or movement of cells within dense biological tissue is essential for diverse biological processes, ranging from pattern formation, immune action, to tumor metastasis. However, it is quite puzzling how cells acquire such ability when they are supposedly "caged" by neighboring cells. Here, we report an unusual property of (MDA-MB-231) breast cancer cells that diffuse more persistently within a densely packed population than when they are free to crawl around with little interference. This property is rather surprising since they prefer to stick together, forming clusters. Interestingly, however, we find that having sticky neighbors not only makes two active cells in contact periodically rotate, reminiscent of a ballroom dance, but also enhances the persistence of the cells within a dense population. These intriguing phenomena appear to be universal as they can be generated by a simple cellular Potts model with appropriate combination of active self-propulsion and cell-cell adhesion force. [ABSTRACT FROM AUTHOR]

Amoeboid cell motility is essential for a wide range of biological processes including wound healing, embryonic morphogenesis, and cancer metastasis. It relies on complex dynamical patterns of cell shape changes that pose long-standing challenges to mathematical modeling and raise a need for automated and reproducible approaches to extract quantitative morphological features from image sequences. Here, we introduce a theoretical framework and a computational method for obtaining smooth representations of the spatiotemporal contour dynamics from stacks of segmented microscopy images. Based on a Gaussian process regression we propose a one-parameter family of regularized contour flows that allows us to continuously track reference points (virtual markers) between successive cell contours. We use this approach to define a coordinate system on the moving cell boundary and to represent different local geometric quantities in this frame of reference. In particular, we introduce the local marker dispersion as a measure to identify localized membrane expansions and provide a fully automated way to extract the properties of such expansions, including their area and growth time. The methods are available as an open-source software package called AmoePy, a Python-based toolbox for analyzing amoeboid cell motility (based on time-lapse microscopy data), including a graphical user interface and detailed documentation. Due to the mathematical rigor of our framework, we envision it to be of use for the development of novel cell motility models. We mainly use experimental data of the social amoeba Dictyostelium discoideum to illustrate and validate our approach. Author summary: Amoeboid motion is a crawling-like cell migration that plays an important key role in multiple biological processes such as wound healing and cancer metastasis. This type of cell motility results from expanding and simultaneously contracting parts of the cell membrane. From fluorescence images, we obtain a sequence of points, representing the cell membrane, for each time step. By using regression analysis on these sequences, we derive smooth representations, so-called contours, of the membrane. Since the number of measurements is discrete and often limited, the question is raised of how to link consecutive contours with each other. In this work, we present a novel mathematical framework in which these links are described by regularized flows allowing a certain degree of concentration or stretching of neighboring reference points on the same contour. This stretching rate, the so-called local dispersion, is used to identify expansions and contractions of the cell membrane providing a fully automated way of extracting properties of these cell shape changes. We applied our methods to time-lapse microscopy data of the social amoeba Dictyostelium discoideum. [ABSTRACT FROM AUTHOR]

The trajectory of moving eukaryotic cells depends on the kinetics and direction of extending pseudopods. The direction of pseudopods has been well studied to unravel mechanisms for chemotaxis, wound healing and inflammation. However, the kinetics of pseudopod extension–when and why do pseudopods start and stop- is equally important, but is largely unknown. Here the START and STOP of about 4000 pseudopods was determined in four different species, at four conditions and in nine mutants (fast amoeboids Dictyostelium and neutrophils, slow mesenchymal stem cells, and fungus B.d. chytrid with pseudopod and a flagellum). The START of a first pseudopod is a random event with a probability that is species-specific (23%/s for neutrophils). In all species and conditions, the START of a second pseudopod is strongly inhibited by the extending first pseudopod, which depends on parallel filamentous actin/myosin in the cell cortex. Pseudopods extend at a constant rate by polymerization of branched F-actin at the pseudopod tip, which requires the Scar complex. The STOP of pseudopod extension is induced by multiple inhibitory processes that evolve during pseudopod extension and mainly depend on the increasing size of the pseudopod. Surprisingly, no differences in pseudopod kinetics are detectable between polarized, unpolarized or chemotactic cells, and also not between different species except for small differences in numerical values. This suggests that the analysis has uncovered the fundament of cell movement with distinct roles for stimulatory branched F-actin in the protrusion and inhibitory parallel F-actin in the contractile cortex. [ABSTRACT FROM AUTHOR]

It is well recognized that isolated cardiac muscle cells beat in a periodic manner. Recently, evidence indicates that other, non-muscle cells, also perform periodic motions that are either imperceptible under conventional lab microscope lens or practically not easily amenable for analysis of oscillation amplitude, frequency, phase of movement and its direction. Here, we create a real-time video analysis tool to visually magnify and explore sub-micron rhythmic movements performed by biological cells and the induced movements in their surroundings. Using this tool, we suggest that fibroblast cells perform small fluctuating movements with a dominant frequency that is dependent on their surrounding substrate and its stiffness. [ABSTRACT FROM AUTHOR]

Infection with the influenza virus triggers an innate immune response that initiates the adaptive response to halt viral replication and spread. However, the metabolic response fueling the molecular mechanisms underlying changes in innate immune cell homeostasis remain undefined. Although influenza increases parasitized cell metabolism, it does not productively replicate in dendritic cells. To dissect these mechanisms, we compared the metabolism of dendritic cells to that of those infected with active and inactive influenza A virus and those treated with toll-like receptor agonists. Using quantitative mass spectrometry, pulse chase substrate utilization assays and metabolic flux measurements, we found global metabolic changes in dendritic cells 17 hours post infection, including significant changes in carbon commitment via glycolysis and glutaminolysis, as well as mitochondrial respiration. Influenza infection of dendritic cells led to a metabolic phenotype distinct from that induced by TLR agonists, with significant resilience in terms of metabolic plasticity. We identified c-Myc as one transcription factor modulating this response. Restriction of c-Myc activity or mitochondrial substrates significantly changed the immune functions of dendritic cells, such as reducing motility and T cell activation. Transcriptome analysis of inflammatory dendritic cells isolated following influenza infection showed similar metabolic reprogramming occurs in vivo. Thus, early in the infection process, dendritic cells respond with global metabolic restructuring, that is present in inflammatory lung dendritic cells after infection, and this is important for effector function. These findings suggest metabolic switching in dendritic cells plays a vital role in initiating the immune response to influenza infection. Author summary: Dendritic cells are critical in mounting an effective immune response to influenza infection by initiating the immune response to influenza and activating the adaptive response to mediate viral clearance and manifest immune memory for protection against subsequent infections. We found dendritic cells undergo a profound metabolic shift after infection. They alter the concentration and location of hundreds of proteins, including c-Myc, facilitating a shift to a highly glycolytic phenotype that is also flexible in terms of fueling respiration. Nonetheless, we found limiting access to specific metabolic pathways or substrates diminished key immune functions. We previously described an immediate, fixed hypermetabolic state in infected respiratory epithelial cells. Here we present data indicating the metabolic response of dendritic cells is increased yet flexible, distinct from what we previously showed for epithelial cells. Additionally, we demonstrate dendritic cells tailor their metabolic response to the pathogen or TLR stimulus. This metabolic reprogramming occurs rapidly in vitro and is sustained in inflammatory dendritic cells in vivo for at least 9 days following influenza infection. These studies introduce the possibility of modulating the immune response to viral infection using customized metabolic therapy to enhance or diminish the function of specific cells. [ABSTRACT FROM AUTHOR]