Cell Physician: Reading Cell Motion

Cell motility is an essential phenomenon in almost all living organisms. It is natural to think that behavioral or shape changes of a cell bear information about the underlying mechanisms that generate these changes. Reading cell motion, namely, understanding the underlying biophysical and mechanochemical processes, is of paramount importance. The mathematical model developed in this paper determines some physical features and material properties of the cells locally through analysis of live cell image sequences and uses this information to make further inferences about the molecular structures, dynamics, and processes within the cells, such as the actin network, microdomains, chemotaxis, adhesion, and retrograde flow. The generality of the principals used in formation of the model ensures its wide applicability to different phenomena at various levels. Based on the model outcomes, we hypothesize a novel biological model for collective biomechanical and molecular mechanism of cell motion.     

Stochastic models for cell motion and taxis

Certain biological experiments investigating cell motion result in time lapse video microscopy data which may be modeled using stochastic differential equations. These models suggest statistics for quantifying experimental results and testing relevant hypotheses, and carry implications for the qualitative behavior of cells and for underlying biophysical mechanisms. Directional cell motion in response to a stimulus, termed taxis, has previously been modeled at a phenomenological level using the Keller-Segel diffusion equation. The Keller-Segel model cannot distinguish certain modes of taxis, and this motivates the introduction of a richer class of models which is nevertheless still amenable to statistical analysis. A state space model formulation is used to link models proposed for cell velocity to observed data. Sequential Monte Carlo methods enable parameter estimation via maximum likelihood for a range of applicable models. One particular experimental situation, involving the effect of an electric field on cell behavior, is considered in detail. In this case, an Ornstein- Uhlenbeck model for cell velocity is found to compare favorably with a nonlinear diffusion model.     

Improving fluorescence-based assays for the in vitro analysis of cell adhesion and migration

Cell adhesion and cell migration are two primary cellular phenomena to be approached in vitro in order to allow for the effective dissection of the individual events and the unravelling of their underlying molecular mechanisms. The use of assays dedicated to the analysis of cell adhesion and migration in vitro also affords an efficient way of conducting larger basic and applied research screenings of the conditions affecting these processes and are potentially exploitable in the context of routine tests in the biological and medical fields. Therefore, there is a substantial interest in devicing more rationale such assays and major contributions in this direction have been provided by the advent of procedures based on fluorescent cell tagging. In this article we describe three fluorescence-based model assays for the qualitative and quantitative assessment of cell adhesion and cell locomotion in static and dynamic conditions. The assays are easily performed, accurate and reproducible, and can be automatized for high-throughput screenings of cell behavior in vitro. Performance of the assays involves the use of certain dedicated disposable accessories, which are commercially available, and a few instruments that, due to their versatility, can be regarded as constituents of a more generic laboratory setup.     

BIOLOGICAL TIMING AND THE CLOCK METAPHOR: OSCILLATORY AND HOURGLASS MECHANISMS

Living organisms have developed a multitude of timing mechanisms— “biological clocks.” Their mechanisms are based on either oscillations (oscillatory clocks) or unidirectional processes (hourglass clocks). Oscillatory clocks comprise circatidal, circalunidian, circadian, circalunar, and circannual oscillations—which keep time with environmental periodicities—as well as ultradian oscillations, ovarian cycles, and oscillations in development and in the brain, which keep time with biological timescales. These clocks mainly determine time points at specific phases of their oscillations. Hourglass clocks are predominantly found in development and aging and also in the brain. They determine time intervals (duration). More complex timing systems combine oscillatory and hourglass mechanisms, such as the case for cell cycle, sleep initiation, or brain clocks, whereas others combine external and internal periodicities (photoperiodism, seasonal reproduction). A definition of a biological clock may be derived from its control of functions external to its own processes and its use in determining temporal order (sequences of events) or durations. Biological and chemical oscillators are characterized by positive and negative feedback (or feedforward) mechanisms. During evolution, living organisms made use of the many existing oscillations for signal transmission, movement, and pump mechanisms, as well as for clocks. Some clocks, such as the circadian clock, that time with environmental periodicities are usually compensated (stabilized) against temperature, whereas other clocks, such as the cell cycle, that keep time with an organismic timescale are not compensated. This difference may be related to the predominance of negative feedback in the first class of clocks and a predominance of positive feedback (autocatalytic amplification) in the second class. The present knowledge of a compensated clock (the circadian oscillator) and an uncompensated clock (the cell cycle), as well as relevant models, are briefly reviewed. Hourglass clocks are based on linear or exponential unidirectional processes that trigger events mainly in the course of development and aging. An important hourglass mechanism within the aging process is the limitation of cell division capacity by the length of telomeres. The mechanism of this clock is briefly reviewed. In all clock mechanisms, thresholds at which “dependent variables” are triggered play an important role. (Chronobiology International, 18(3), 329–369, 2001)     

TRPC1 protein channel is major regulator of epidermal growth factor receptor signaling

TRP channels have been associated with cell proliferation and aggressiveness in several cancers. In particular, TRPC1 regulates cell proliferation and motility, two processes underlying cancer progression. We and others have described the mechanisms of TRPC1-dependent cell migration. However, the involvement of TRPC1 in cell proliferation remains unexplained. In this study, we show that siRNA-mediated TRPC1 depletion in non small cell lung carcinoma cell lines induced G(0)/G(1) cell cycle arrest resulting in dramatic decrease in cell growth. The expression of cyclins D1 and D3 was reduced after TRPC1 knockdown, pointing out the role of TRPC1 in G(1)/S transition. This was associated with a decreased phosphorylation and activation of EGFR and with a subsequent disruption of PI3K/Akt and MAPK downstream pathways. Stimulation of EGFR by its natural ligand, EGF, induced Ca(2+) release from the endoplasmic reticulum and Ca(2+) entry through TRPC1. Ca(2+) entry through TRPC1 conversely activated EGFR, suggesting that TRPC1 is a component of a Ca(2+)-dependent amplification of EGF-dependent cell proliferation.     

Epigenome-Metabolome-Epigenome signaling cascade in cell biological processes

Cell fate determination as a fundamental question in cell biology has been extensively studied at different regulatory levels for many years. However, the mechanisms of multilevel regulation of cell fate determination remain unclear. Recently, we have proposed an Epigenome-Metabolome-Epigenome (E-M-E) signaling cascade model to describe the cross-over cooperation during mouse somatic cell reprogramming. In this review, we summarize the broad roles of E-M-E signaling cascade in different cell biological processes, including cell differentiation and dedifferentiation, cell specialization, cell proliferation, and cell pathologic processes. Precise E-M-E signaling cascades are critical in these cell biological processes, and it is of worth to explore each step of E-M-E signaling cascade. E-M-E signaling cascade model sheds light on and may open a window to explore the mechanisms of multilevel regulation of cell biological processes.     

Cell memory of epithelial-mesenchymal plasticity in cancer

Fundamental biological processes of cell identity and cell fate determination are controlled by complex regulatory networks. These processes require molecular mechanisms that confer cellular phenotypic memory and state persistence. In this minireview, we will summarize mechanisms of cell memory based on regulatory hysteretic feedback loops and explore epigenetic mechanisms widely represented in nature, with special focus on epithelial-to-mesenchymal plasticity. We will also discuss the functional consequences of cell memory and epithelial-to-mesenchymal plasticity dynamics during development and cancer metastasis.     

Butyrate-induced GPR41 activation inhibits histone acetylation and cell growth

Butyrate has been recently identified as a natural ligand of the G-protein-coupled receptor 41(GPR41).In addition,it is an inhibitor of histone deacetylase(HDAC).Butyrate treatment results in the hyperacetylation of histones,with resultant multiple biological effects including inhibition of proliferation,induction of cell cycle arrest,and apoptosis,in a variety of cultured mammalian cells.However,it is not clear whether GPR41 is actively involved in the above-mentioned processes.In this study,we generated a stable cell line expressing the hGPR41 receptor in order to investigate the involvement of GPR41 on butyrate-induced biochemical and physiologic processes.We found that GPR41 activation may be a compensatory mechanism to counter the increase in histone H3 acetylation levels induced by butyrate treatment.Moreover,GPR41 had an inhibitory effect on the anti-proliferative,pro-apoptotic effects of butyrate.GPR41 expression induced cell cycle arrest at the G1-stage,while its activation by butyrate can cause more cells to pass the G1 checkpoint.These results indicated that GPR41 was associated with histone acetylation and might be involved in the acetylation-related regulation of cell processes including proliferation,apoptosis,and the cell cycle.     

Coupling of proadipocyte growth arrest and differentiation. II. A cell cycle model for the physiological control of cell proliferation

Experimental evidence is presented that supports a cell cycle model showing that there are five distinct biological processes involved in proadipocyte differentiation. These include: (a) growth arrest at a distinct state in the G1 phase of the cell cycle; (b) nonterminal differentiation; (c) terminal differentiation; (d) loss of the differentiated phenotype; and (e) reinitiation of cell proliferation. Each of these events is shown to be regulated by specific human plasma components or other physiological factors. At two states designated GD and GD', coupling of growth arrest and differentiation is shown to occur. We propose that these mechanisms for the coupling of growth arrest and differentiation are physiologically significant and mimic the regulatory processes that control stem cell proliferation in vivo.     

A novel supervised trajectory segmentation algorithm identifies distinct types of human adenovirus motion in host cells

Biological trajectories can be characterized by transient patterns that may provide insight into the interactions of the moving object with its immediate environment. The accurate and automated identification of trajectory motifs is important for the understanding of the underlying mechanisms. In this work, we develop a novel trajectory segmentation algorithm based on supervised support vector classification. The algorithm is validated on synthetic data and applied to the identification of trajectory fingerprints of fluorescently tagged human adenovirus particles in live cells. In virus trajectories on the cell surface, periods of confined motion, slow drift, and fast drift are efficiently detected. Additionally, directed motion is found for viruses in the cytoplasm. The algorithm enables the linking of microscopic observations to molecular phenomena that are critical in many biological processes, including infectious pathogen entry and signal transduction.     

Different roles of TGF-β in the multi-lineage differentiation of stem cells

Stem cells are a population of cells that has infinite or long-term self-renewal ability and can produce various kinds of descendent cells.Transforming growth factor β(TGF-β) family is a superfamily of growth factors,including TGF-β1,TGF-β2 and TGF-β3,bone morphogenetic proteins,activin/inhibin,and some other cytokines such as nodal,which plays very important roles in regulating a wide variety of biological processes,such as cell growth,differentiation,cell death.TGF-β,a pleiotropic cytokine,has been proved to be differentially involved in the regulation of multi-lineage differentiation of stem cells,through the Smad pathway,non-Smad pathways including mitogen-activated protein kinase pathways,phosphatidylinositol-3-kinase/AKT pathways and Rholike GTPase signaling pathways,and their cross-talks.For instance,it is generally known that TGF-β promotes the differentiation of stem cells into smooth muscle cells,immature cardiomyocytes,chondrocytes,neurocytes,hepatic stellate cells,Th17 cells,and dendritic cells.However,TGF-β inhibits the differentiation of stem cells into myotubes,adipocytes,endothelial cells,and natural killer cells.Additionally,TGF-β can provide competence for early stages of osteoblastic differentiation,but at late stages TGF-β acts as an inhibitor.The three mammalian isoforms(TGF-β1,2 and 3) have distinct but overlapping effects on hematopoiesis.Understanding the mechanisms underlying the regulatory effect of TGF-β in the stem cell multi-lineage differentiation is of importance in stem cell biology,and will facilitate both basic research and clinical applications of stem cells.In this article,we discuss the current status and progress in our understanding of different mechanisms by which TGF-β controls multi-lineage differentiation of stem cells.     

Feed-back regulation of successive meiotic cytokinesis

The paper considers a number of abnormal phenotypes with impaired temporal regulation of cytokinesis during the meiotic division of pollen mother cells. The phenomenon of “non-stop” cytokinesis with blocked arrest of the phragmoplast centrifugal motion and cell plate growth as well as incomplete and premature cytokinesis are described. The obtained data suggested a model for regulation of the processes involved in the arrest of the main cytokinesis processes during its completion in the plant meiosis.     

Do lipids shape the eukaryotic cell cycle?

Successful passage through the cell cycle presents a number of structural challenges to the cell. Inceptive studies carried out in the last five years have produced clear evidence of modulations in the lipid profile (sometimes referred to as the lipidome) of eukaryotes as a function of the cell cycle. This mounting body of evidence indicates that lipids play key roles in the structural transformations seen across the cycle. The accumulation of this evidence coincides with a revolution in our understanding of how lipid composition regulates a plethora of biological processes ranging from protein activity through to cellular signalling and membrane compartmentalisation. In this review, we discuss evidence from biological, chemical and physical studies of the lipid fraction across the cell cycle that demonstrate that lipids are well-developed cellular components at the heart of the biological machinery responsible for managing progress through the cell cycle. Furthermore, we discuss the mechanisms by which this careful control is exercised.     

Reactive-oxygen-species-mediated Cdc25C degradation results in differential antiproliferative activities of vanadate, tungstate, and molybdate in the PC-3 human prostate cancer cell line

The differential antiproliferative effects of vanadate, tungstate, and molybdate on human prostate cancer cell line PC-3 were compared and the underlying mechanisms were investigated. The results demonstrate that all of the three oxoanions can cause G₂/M cell cycle arrest, which is evidenced by the increase in the level of phosphorylated Cdc2 at its inactive Tyr-15 site. Moreover, even if the difference in cellular uptake among the three oxoanions is excluded from the possible factors affecting their antiproliferative activity, vanadate exerted a much more potent effect in PC-3 cells than the other two oxoanions. Our results also reveal that reactive oxygen species (ROS)-mediated degradation of Cdc25C rather than Cdc25A or Cdc25B is responsible for vanadate-induced G₂/M cell cycle arrest. We propose a possible mechanism to clarify the differential effect of the three oxoanions in biological systems beyond just considering that they are structural analogs of phosphate. We suggest that ROS formation is unlikely to be involved in the biological function of tungstate and molybdate, whereas the redox properties of vanadium may be important factors for it to exert pharmacological effects. Further, given the evidence from epidemiology studies of the association between diabetes and prostate cancer, the possibility of vanadate as a good candidate as both an antidiabetic and an anticancer agent or a chemopreventive agent is indicated.     

MicroRNA-15a fine-tunes the level of Delta-like 1 homolog (DLK1) in proliferating 3T3-L1 preadipocytes

Delta like 1 homolog (Dlk1) exists in both transmembrane and soluble molecular forms, and is implicated in cellular growth and plays multiple roles in development, tissue regeneration, and cancer. Thus, DLK1 levels are critical for cell function, and abnormal DLK1 expression can be lethal; however, little is known about the underlying mechanisms. We here report that miR-15a modulates DLK1 levels in preadipocytes thus providing a mechanism for DLK1 regulation that further links it to cell cycle arrest and cancer since miR-15a is deregulated in these processes.In preadipocytes, miR-15a increases with cell density, and peaks at the same stage where membrane DLK1^M and soluble DLK1^S are found at maximum levels. Remarkably, miR-15a represses the amount of all Dlk1 variants at the mRNA level but also the level of DLK1^M protein while it increases the amount of DLK1^S supporting a direct repression of DLK1 and a parallel effect on the protease that cleaves off the DLK1 from the membrane. In agreement with previous studies, we found that miR-15a represses cell numbers, but additionally, we report that miR-15a also increases cell size. Conversely, anti-miR-15a treatment decreases cell size while increasing cell numbers, scenarios that were completely rescued by addition of purified DLK1^S.Our data thus imply that miR-15a regulates cell size and proliferation by fine-tuning Dlk1 among others, and further emphasize miR-15a and DLK1 levels to play important roles in growth signaling networks.     

Prion proteins from susceptible and resistant sheep exhibit some distinct cell biological features

It is well established that natural polymorphisms in the coding sequence of the PrP protein can control the expression of prion disease. Studies with a cell model of sheep prion infection have shown that ovine PrP allele associated with resistance to sheep scrapie may confer resistance by impairing the multiplication of the infectious agent. To further explore the biochemical and cellular mechanisms underlying the genetic control of scrapie susceptibility, we established permissive cells expressing two different PrP variants. In this study, we show that PrP variants with opposite effects on prion multiplication exhibit distinct cell biological features. These findings indicate that cell biological properties of ovine PrP can vary with natural polymorphisms and raise the possibility that differential interactions of PrP variants with the cellular machinery may contribute to permissiveness or resistance to prion multiplication.