Movement Of Single Cells Research Articles

Preventing E. coli Biofilm Formation with Antimicrobial Peptide-Functionalized Surface Coatings: Recognizing the Dependence on the Bacterial Binding Mode Using Live-Cell Microscopy.

Antimicrobial peptides (AMPs) can kill bacteria by destabilizing their membranes, yet translating these molecules' properties into a covalently attached antibacterial coating is challenging. Rational design efforts are obstructed by the fact that standard microbiology methods are ill-designed for the evaluation of coatings, disclosing few details about why grafted AMPs function or do not function. It is particularly difficult to distinguish the influence of the AMP's molecular structure from other factors controlling the total exposure, including which type of bonds are formed between bacteria and the coating and how persistent these contacts are. Here, we combine label-free live-cell microscopy, microfluidics, and automated image analysis to study the response of surface-bound Escherichia coli challenged by the same small AMP either in solution or grafted to the surface through click chemistry. Initially after binding, the grafted AMPs inhibited bacterial growth more efficiently than did AMPs in solution. Yet, after 1 h, E. coli on the coated surfaces increased their expression of type-1 fimbriae, leading to a change in their binding mode, which diminished the coating's impact. The wealth of information obtained from continuously monitoring the growth, shape, and movements of single bacterial cells allowed us to elucidate and quantify the different factors determining the antibacterial efficacy of the grafted AMPs. We expect this approach to aid the design of elaborate antibacterial material coatings working by specific and selective actions, not limited to contact-killing. This technology is needed to support health care and food production in the postantibiotic era.

Phenotypic Modulation of Adipose-Derived Stem Cells and Fibroblasts Treated with Povidone-Iodine and Chlorhexidine in Mono and Coculture Models.

Topical antiseptics are essential in wound treatment, and adipose-derived stem cells (ADSCs) have recently been proven to facilitate healing. However, the impact of antiseptics on ADSCs has not been fully elucidated, especially in relation to other relevant cell types present in the wound microenvironment, e.g., fibroblasts. This study evaluated the effects of chlorhexidine and povidone-iodine on four cellular constructs in 2D and 3D in vitro culture systems. Cell constructs were treated with two concentrations of each antiseptic, after which cell migration activity, α-SMA, and Ki67 marker expressions were assessed and compared. Both tested concentrations of povidone-iodine impaired migration and sprouting compared to chlorhexidine, which had minimal effects when used in low concentrations. The gap in the wound healing assay did not close after 24 h of povidone-iodine treatment, although, at the lower concentration, cells started to migrate in a single-cell movement pattern. Similarly, in 3D culture systems, sprouting with reduced spike formation was observed at high povidone-iodine concentrations. Both antiseptics modulated α-SMA and Ki67 marker expressions at 5 days following treatment. Although both antiseptics had cytotoxic effects dependent on drug concentration and cell type, povidone-iodine contributed more substantially to the healing process than chlorhexidine, acting especially on fibroblasts.

An Optical Tweezers-Based Single-Cell Manipulation and Detection Platform for Probing Real-Time Cancer Cell Chemotaxis and Response to Tyrosine Kinase Inhibitor PD153035

We presented an approach to address cancer cell chemotaxis and response to tyrosine kinase inhibitor PD153035 at the single-cell level. We applied an optical tweezer system together with the platform at the single-cell level to manipulate an epidermal growth factor (EGF)-coated bead positioned close to the filopodia to locally stimulate HT29 cells, the human colon cancer cell line overexpressing the EGF receptor (EGFR). To address cancer cell chemotaxis, a single-cell movement model was also proposed to quantify the propagation speed at the leading and trailing edges of the cell along the chemosensing axis. This study focused on three perspectives: probing the chemosensing process mediated by EGF/EGFR signaling, investigating the mode of locomotion during the EGF-coated bead stimulation, and quantifying the effect of PD153035 on the EGF–EGFR transport pathway. The results showed that the filopodial actin filament is a sensory system for EGF detection. In addition, HT29 cells may use the filopodial actin filament to distinguish the presence or absence of the chemoattractant EGF. Furthermore, we demonstrated the high selectivity of PD153035 for EGFR and the reversibility of binding to EGFR. We anticipate that the proposed single-cell method could be applied to construct a rapid screening method for the detection and therapeutic evaluation of many types of cancer during chemotaxis.

Experimental effect of inclination on the process of melting paraffin in a square cavity

Phase change material PCM is a promising strategy for reducing energy consumption in various applications. Among the large number of PCMs studied in the literature, paraffin are considered to be promising for latent heat thermal energy storage LHTES due to its appropriate thermal properties and their chemical stability. The interest of this work is to carry out an experimental procedure to visualize the phase change process of paraffin in a square cavity at different inclination angles. This article reveals how the melting rate could be affected by changing three orientations 90° (vertical heating), 0° (bottom horizontal heating) and 45° (inclined heating). The enclosure is heated on one side while the other walls are thermally insulated. The numerical photos, infrared thermal image and thermocouples-temperatures recorded during the melting processing are used to calculate the melting fractions and to estimate the intensity of heat transfer in different angles. The results show that the inclination angle has a great influence on the behavior of natural convection, affecting the front melting propagation and heat transfer rate. When the inclination angle decreases from 90° to 0° the convection currents in the cavity progressively evolve from a dominant single-cell movement to an unstable Rayleigh-Benard movement. The total melting time for the bottom and inclined heating cavities were, on average, 56% and 45% less than that of the vertical heating, respectively.

Self-organized cell migration across scales - from single cell movement to tissue formation.

Self-organization is a key feature of many biological and developmental processes, including cell migration. Although cell migration has traditionally been viewed as a biological response to extrinsic signals, advances within the past two decades have highlighted the importance of intrinsic self-organizing properties to direct cell migration on multiple scales. In this Review, we will explore self-organizing mechanisms that lay the foundation for both single and collective cell migration. Based on in vitro and in vivo examples, we will discuss theoretical concepts that underlie the persistent migration of single cells in the absence of directional guidance cues, and the formation of an autonomous cell collective that drives coordinated migration. Finally, we highlight the general implications of self-organizing principles guiding cell migration for biological and medical research.

Ciliary motors locked closed by Shulin

Molecular Motors Motile cilia and flagella are vital cellular organelles with functions that include setting up the left-right body axis, clearing airways of mucus, and driving single-cell movements. Cilia beating is powered by arrays of dynein motors, the key force generators being the outer dynein arm (ODA) complexes. Using the protozoan Tetrahymena , Mali et al. identified a factor, which they name Shulin, that binds newly synthesized ODAs. Cryo–electron microscopy revealed how Shulin locks the dynein motors together by shutting off motor activity and facilitating delivery of ODAs from the cytoplasm to their final position in the cilia. Science , this issue p. [910][1] [1]: /lookup/doi/10.1126/science.abe0526

C-Jun N-terminal kinase 2 suppresses pancreatic cancer growth and invasion and is opposed by c-Jun N-terminal kinase 1

The c-Jun N-terminal protein kinases (JNKs) JNK1 and JNK2 can act as either tumor suppressors or pro-oncogenic kinases in human cancers. The isoform-specific roles for JNK1 and JNK2 in human pancreatic cancer are still unclear, the question which should be addressed in this project. Human pancreatic cancer cell lines MIA PaCa-2 and PANC-1 clones were established either expressing either JNK1 or -2 shRNA in a stable manner. Basal anchorage-dependent and –independent cell growth, single-cell movement, and invasion using the Boyden chamber assay were analyzed. Xenograft growth was assessed using an orthotopic mouse model. All seven tested pancreatic cancer cell lines expressed JNKs as did human pancreatic cancer samples determined by immunohistochemistry. Pharmacological, unspecific JNK inhibition (SP600125) reduced cell growth of all cell lines but PANC-1. Especially inhibition of JNK2 resulted in overall increased oncogenic potential with increased proliferation and invasion, associated with alterations in cytoskeleton structure. Specific inhibition of JNK1 revealed opposing functions. Overall, JNK1 and JNK2 can exert different functions in human pancreatic cancer and act as counter players for tumor invasion. Specifically modulating the activity of JNKs may be of potential therapeutic interest in the future.

An Integrative and Modular Framework to Recapitulate Emergent Behavior in Cell Migration

Cell migration has been a subject of study in a broad variety of biological systems, from morphogenetic events during development to cancer progression. In this work, we describe single-cell movement in a modular framework from which we simulate the collective behavior of glioblastoma cells, the most prevalent and malignant primary brain tumor. We used the U87 cell line, which can be grown as a monolayer or spatially closely packed and organized in 3D structures called spheroids. Our integrative model considers the most relevant mechanisms involved in cell migration: chemotaxis of attractant factor, mechanical interactions and random movement. The effect of each mechanism is integrated into the overall probability of the cells to move in a particular direction, in an automaton-like approach. Our simulations fit and reproduced the emergent behavior of the spheroids in a set of migration assays where single-cell trajectories were tracked. We also predicted the effect of migration inhibition on the colonies from simple experimental characterization of single treated cell tracks. The development of tools that allow complementing molecular knowledge in migratory cell behavior is relevant for understanding essential cellular processes, both physiological (such as organ formation, tissue regeneration among others) and pathological perspectives. Overall, this is a versatile tool that has been proven to predict individual and collective behavior in U87 cells, but that can be applied to a broad variety of scenarios.

Label-free imaging of immune cell dynamics in the living retina using adaptive optics.

Our recent work characterized the movement of single blood cells within the retinal vasculature (Joseph et al. 2019) using adaptive optics ophthalmoscopy. Here, we apply this technique to the context of acute inflammation and discover both infiltrating and tissue-resident immune cells to be visible without any labeling in the living mouse retina using near-infrared light alone. Intravital imaging of immune cells can be negatively impacted by surgical manipulation, exogenous dyes, transgenic manipulation and phototoxicity. These confounds are now overcome, using phase contrast and time-lapse videography to reveal the dynamic behavior of myeloid cells as they interact, extravasate and survey the mouse retina. Cellular motility and differential vascular responses were measured noninvasively and in vivo across hours to months at the same retinal location, from initiation to the resolution of inflammation. As comparable systems are already available for clinical research, this approach could be readily translated to human application.

Rapid Assessment of Water Toxicity by Plasmonic Nanomechanical Sensing.

The ability to rapidly and accurately detect water toxicity is crucial for monitoring water quality and assessing toxic risk, but such detection remains a great challenge. Here, we present a plasmonic nanomechanical sensing (PNMS) system for the rapid assessment of water toxicity. This technique is based on the plasmonic sensing of the nanomechanical movement of single bacterial cells, which could be inhibited upon exposure to potential toxicants. By correlating the amplitude of nanomechanical movement with bacterial activity, we detected a variety of toxic substances in water. The direct readout of bacterial activity via PNMS allowed for a high sensitivity to toxicants in water, thereby enabling us to evaluate the acute toxicological effect of chemical compounds rapidly. The PNMS method is promising for online alerts of water quality safety and for assessing chemical hazards. We anticipate that PNMS is also suitable for a wide range of other applications, including bacterial detection and high-throughput screening of antibacterial materials.

Interaction of Pregnancy-Specific Glycoprotein 1 With Integrin Α5β1 Is a Modulator of Extravillous Trophoblast Functions.

Human pregnancy-specific glycoproteins (PSGs) serve immunomodulatory and pro-angiogenic functions during pregnancy and are mainly expressed by syncytiotrophoblast cells. While PSG mRNA expression in extravillous trophoblasts (EVTs) was reported, the proteins were not previously detected. By immunohistochemistry and immunoblotting, we show that PSGs are expressed by invasive EVTs and co-localize with integrin α5. In addition, we determined that native and recombinant PSG1, the most highly expressed member of the family, binds to α5β1 and induces the formation of focal adhesion structures resulting in adhesion of primary EVTs and EVT-like cell lines under 21% oxygen and 1% oxygen conditions. Furthermore, we found that PSG1 can simultaneously bind to heparan sulfate in the extracellular matrix and to α5β1 on the cell membrane. Wound healing assays and single-cell movement tracking showed that immobilized PSG1 enhances EVT migration. Although PSG1 did not affect EVT invasion in the in vitro assays employed, we found that the serum PSG1 concentration is lower in African-American women diagnosed with early-onset and late-onset preeclampsia, a pregnancy pathology characterized by shallow trophoblast invasion, than in their respective healthy controls only when the fetus was a male; therefore, the reduced expression of this molecule should be considered in the context of preeclampsia as a potential therapy.

Functions of p38 mitogen-activated protein kinase alpha and beta in human pancreatic cancer cells

Objective To elucidate possible functions of p38α and p38β in human pancreatic cancer. Methods Expression of p38α, p38β, p38γ and p38δ were determined by immunoblot in 7 cultured human pancreatic cancer cell lines. To selectively inhibit p38α or p38β, cell clones were established in a stable manner expression either p38α short hairpin RNA (shRNA) or p38β shRNA. Proliferation, single cell movement, in vitro migration, colony forming ability as well as in vivo tumorigenicity were determined by methyl thiazol tetrazolium (MTT) assay, video-time laps microscopy, boyden-chamber, soft-agar assay, tumor formation and growth in nude mice respectively. Results All pancreatic cancer cells showed p38 isoforms protein expression at various levels. Selective inhibition of p38α or p38β in Mia Paca-2 and Panc-1 cells revealed that both kinases enhance cell proliferation and anchorage-independent growth. Single cell movement and cell invasion were markedly reduced in p38α shRNA expressing clones, but not altered in p38β shRNA expressing clones. Inhibition of p38α enhanced in vivo tumorigenicity profoundly in Mia Paca-2 and Panc-1 cells. In Mia Paca-2 cell, the in vivo tumor formation rate of two p38β shRNA expressing clones is 18.3% and 50.0% respectively, which decreased significantly comparing to the wild type cell and null vector transfection cell. The tumor volume decreased significantly either (P<0.05). In Panc-1 cell, the in vivo tumor formation rate of two p38β shRNA expressing clones is 25.0% and 12.5% respectively. Conclusion p38 mitogen activated protein kinases (p38MAPKs) are expressed in pancreatic cancer cells and the isoforms may exert different functions. Key words: p38 mitogen-activated protein kinase; Pancreatic cancer; p38α; p38β

Nonmotile Single-Cell Migration as a Random Walk in Nonuniformity: The "Extreme Dumping Limit" for Cell-to-Cell Communications.

In the present work, we model single-cell movement as a random walk in an external potential observed within the extreme dumping limit, which we define herein as the extreme nonuniform behavior observed for cell responses and cell-to-cell communications. Starting from the Newton–Langevin equation of motion, we solve the corresponding Fokker–Planck equation to compute higher moments of the displacement of the cell, and then we build certain quantities that can be measurable experimentally. We show that, each time, the dynamics depend on the external force applied, leading to predictions distinct from the standard results of a free Brownian particle. Our findings demonstrate that cell migration viewed as a stochastic process is still compatible with biological and experimental observations without the need to rely on more complicated or sophisticated models proposed previously in the literature.

A hybrid computational model for collective cell durotaxis.

Collective cell migration is regulated by a complex set of mechanical interactions and cellular mechanisms. Collective migration emerges from mechanisms occurring at single cell level, involving processes like contraction, polymerization and depolymerization, of cell-cell interactions and of cell-substrate adhesion. Here, we present a computational framework which simulates the dynamics of this emergent behavior conditioned by substrates with stiffness gradients. The computational model reproduces the cell's ability to move toward the stiffer part of the substrate, process known as durotaxis. It combines the continuous formulation of truss elements and a particle-based approach to simulate the dynamics of cell-matrix adhesions and cell-cell interactions. Using this hybrid approach, researchers can quickly create a quantitative model to understand the regulatory role of different mechanical conditions on the dynamics of collective cell migration. Our model shows that durotaxis occurs due to the ability of cells to deform the substrate more in the part of lower stiffness than in the stiffer part. This effect explains why cell collective movement is more effective than single cell movement in stiffness gradient conditions. In addition, we numerically evaluate how gradient stiffness properties, cell monolayer size and force transmission between cells and extracellular matrix are crucial in regulating durotaxis.

Accurately tracking single-cell movement trajectories in microfluidic cell sorting devices.

Microfluidics are routinely used to study cellular properties, including the efficient quantification of single-cell biomechanics and label-free cell sorting based on the biomechanical properties, such as elasticity, viscosity, stiffness, and adhesion. Both quantification and sorting applications require optimal design of the microfluidic devices and mathematical modeling of the interactions between cells, fluid, and the channel of the device. As a first step toward building such a mathematical model, we collected video recordings of cells moving through a ridged microfluidic channel designed to compress and redirect cells according to cell biomechanics. We developed an efficient algorithm that automatically and accurately tracked the cell trajectories in the recordings. We tested the algorithm on recordings of cells with different stiffness, and showed the correlation between cell stiffness and the tracked trajectories. Moreover, the tracking algorithm successfully picked up subtle differences of cell motion when passing through consecutive ridges. The algorithm for accurately tracking cell trajectories paves the way for future efforts of modeling the flow, forces, and dynamics of cell properties in microfluidics applications.

Correlation and Differentiation Based Algorithms for Cell Mobility Quantification

Quantification of cell mobility in confluent cell cultures or on coverslips with high cell density is a challenge, because tracking of individual cells is not readily possible. Two procedures have been developed and tested to solve this problem, namely a differential (MoveDif) and a correlation (MoveCor) algorithm. Both compare successive image frames and calculate a difference parameter between them. Image preprocessing was required to neutralize brightness changes and inhomogeneous illumination. Additionally, structures and membranes in the images had to be enhanced and standardized by edge-detection filters. We showed that both algorithms had advantages in different experimental setups, depending of the complexity of the cellular movement. Besides the determination of global cell mobility, the membrane contractility and movement of single cells, small cell groups and intracellular structures could be quantified, if individual cells were separated and magnified. The discriminatory potency and sensitivity of both algorithms were tested by drug induced changes of cellular movement speeds and their robustness against brightness changes were analyzed too. To demonstrate the mobility effects of ketamine on dexamethasone-treated hippocampal neurons, we found that the correlation algorithm MoveCor could quantify the ketamine-dependent increase in cell movement speed after prior treatment with dexamethasone had reduced it distinctively. We also could measure how staurosporine slowed down the mobility of acidic intracellular organelles in highly magnified glial cells from chicken telencephalon. The differentiation algorithm MoveDif was employed to demonstrate that the contractility of pericyte membranes slowed down after induction of oxygen glucose deprivation. The limitations of both methods were given by their inability to produce absolute mobility values but these drawbacks can be solved by appropriate image preprocessing.

Migration of Q Cells in Caenorhabditis elegans.

During C. elegans larval development, the Q neuroblasts produce their lineage by three rounds of divisions along with continuous cell migrations. Their neuronal progeny is dispersed from the pharynx to the anus. This in vivo system to study cell migration is appealing for several reasons. The lineage development is stereotyped; functional analysis and genomic screens are rendered easy and powerful thanks to powerful tools; transgenic manipulations and genome engineering are efficient and can be conveniently combined with live-cell imaging. Here we describe a series of protocols in Q cell migration studies, including quantifications of progeny position, genetic screening strategies, preparation of migration mutants or transgenic worms expressing related fluorescent proteins, multipositional time-lapse tracking of Q cell migration using confocal microscopy and image analyses of single cell movements and dynamics.

Live-imaging of Breast Epithelial Cell Migration After the Transient Depletion of TIP60.

The wound-healing assay is efficient and one of the most economical ways to study cell migration in vitro. Conventionally, images are taken at the beginning and end of an experiment using a phase-contrast microscope, and the migration abilities of cells are evaluated by the closure of wounds. However, cell movement is a dynamic phenomenon, and a conventional method does not allow for tracking single-cell movement. To improve current wound-healing assays, we use live-cell imaging techniques to monitor cell migration in real time. This method allows us to determine the cell migration rate based on a cell tracking system and provides a clearer distinction between cell migration and cell proliferation. Here, we demonstrate the use of live-cell imaging in wound-healing assays to study the different migration abilities of breast epithelial cells influenced by the presence of TIP60. As cell motility is highly dynamic, our method provides more insights into the processes of wound healing than a snapshot of wound closure taken with the traditional imaging techniques used for wound-healing assays.

Extracting cellular automaton rules from physical Langevin equation models for single and collective cell migration

Cellular automata (CA) are discrete time, space, and state models which are extensively used for modeling biological phenomena. CA are "on-lattice" models with low computational demands. In particular, lattice-gas cellular automata (LGCA) have been introduced as models of single and collective cell migration. The interaction rule dictates the behavior of a cellular automaton model and is critical to the model's biological relevance. The LGCA model's interaction rule has been typically chosen phenomenologically. In this paper, we introduce a method to obtain lattice-gas cellular automaton interaction rules from physically-motivated "off-lattice" Langevin equation models for migrating cells. In particular, we consider Langevin equations related to single cell movement (movement of cells independent of each other) and collective cell migration (movement influenced by cell-cell interactions). As examples of collective cell migration, two different alignment mechanisms are studied: polar and nematic alignment. Both kinds of alignment have been observed in biological systems such as swarms of amoebae and myxobacteria. Polar alignment causes cells to align their velocities parallel to each other, whereas nematic alignment drives cells to align either parallel or antiparallel to each other. Under appropriate assumptions, we have derived the LGCA transition probability rule from the steady-state distribution of the off-lattice Fokker-Planck equation. Comparing alignment order parameters between the original Langevin model and the derived LGCA for both mechanisms, we found different areas of agreement in the parameter space. Finally, we discuss potential reasons for model disagreement and propose extensions to the CA rule derivation methodology.

The Mechanics of Single Cell and Collective Migration of Tumor Cells.

Metastasis is a dynamic process in which cancer cells navigate the tumor microenvironment, largely guided by external chemical and mechanical cues. Our current understanding of metastatic cell migration has relied primarily on studies of single cell migration, most of which have been performed using two-dimensional (2D) cell culture techniques and, more recently, using three-dimensional (3D) scaffolds. However, the current paradigm focused on single cell movements is shifting toward the idea that collective migration is likely one of the primary modes of migration during metastasis of many solid tumors. Not surprisingly, the mechanics of collective migration differ significantly from single cell movements. As such, techniques must be developed that enable in-depth analysis of collective migration, and those for examining single cell migration should be adopted and modified to study collective migration to allow for accurate comparison of the two. In this review, we will describe engineering approaches for studying metastatic migration, both single cell and collective, and how these approaches have yielded significant insight into the mechanics governing each process.