The effect of external forces on discrete motion within holographic optical tweezers

Holographic optical tweezers is a widely used technique to manipulate the individual positions of optically trapped micron-sized particles in a sample. The trap positions are changed by updating the holographic image displayed on a spatial light modulator. The updating process takes a finite time, resulting in a temporary decrease of the intensity, and thus the stiffness, of the optical trap. We have investigated this change in trap stiffness during the updating process by studying the motion of an optically trapped particle in a fluid flow. We found a highly nonlinear behavior of the change in trap stiffness vs. changes in step size. For step sizes up to approximately 300 nm the trap stiffness is decreasing. Above 300 nm the change in trap stiffness remains constant for all step sizes up to one particle radius. This information is crucial for optical force measurements using holographic optical tweezers

Control and Manipulation of Pathogens with an Optical Trap for Live Cell Imaging of Intercellular Interactions

The application of live cell imaging allows direct visualization of the dynamic interactions between cells of the immune system. Some preliminary observations challenge long-held beliefs about immune responses to microorganisms; however, the lack of spatial and temporal control between the phagocytic cell and microbe has rendered focused observations into the initial interactions of host response to pathogens difficult. This paper outlines a method that advances live cell imaging by integrating a spinning disk confocal microscope with an optical trap, also known as an optical tweezer, in order to provide exquisite spatial and temporal control of pathogenic organisms and place them in proximity to host cells, as determined by the operator. Polymeric beads and live, pathogenic organisms (Candida albicans and Aspergillus fumigatus) were optically trapped using non-destructive forces and moved adjacent to living cells, which subsequently phagocytosed the trapped particle. High resolution, transmitted light and fluorescence-based movies established the ability to observe early events of phagocytosis in living cells. To demonstrate the broad applicability of this method to immunological studies, anti-CD3 polymeric beads were also trapped and manipulated to form synapses with T cells in vivo, and time-lapse imaging of synapse formation was also obtained. By providing a method to exert fine control of live pathogens with respect to immune cells, cellular interactions can be captured by fluorescence microscopy with minimal perturbation to cells and can yield powerful insight into early responses of innate and adaptive immunity.National Institute of Biomedical Imaging and Bioengineering (U.S.) (grant T32EB006348)Massachusetts General Hospital (Department of Medicine Internal Funds)Center for Computational and Integrative Biology (Development fund)Center for Computational and Integrative Biology (AI062773)Center for Computational and Integrative Biology (grant AI062773)Center for Computational and Integrative Biology (grant DK83756)Center for Computational and Integrative Biology (grant DK 043351)National Institute of Allergy and Infectious Diseases (U.S.)National Institutes of Health (U.S.) (grant AI057999

A nonlinear mixed effects approach for modeling the cell-to-cell variability of Mig1 dynamics in yeast

The last decade has seen a rapid development of experimental techniques that allow data collection from individual cells. These techniques have enabled the discovery and characterization of variability within a population of genetically identical cells. Nonlinear mixed effects (NLME) modeling is an established framework for studying variability between individuals in a population, frequently used in pharmacokinetics and pharmacodynamics, but its potential for studies of cell-to-cell variability in molecular cell biology is yet to be exploited. Here we take advantage of this novel application of NLME modeling to study cell-to-cell variability in the dynamic behavior of the yeast transcription repressor Mig1. In particular, we investigate a recently discovered phenomenon where Mig1 during a short and transient period exits the nucleus when cells experience a shift from high to intermediate levels of extracellular glucose. A phenomenological model based on ordinary differential equations describing the transient dynamics of nuclear Mig1 is introduced, and according to the NLME methodology the parameters of this model are in turn modeled by a multivariate probability distribution. Using time-lapse microscopy data from nearly 200 cells, we estimate this parameter distribution according to the approach of maximizing the population likelihood. Based on the estimated distribution, parameter values for individual cells are furthermore characterized and the resulting Mig1 dynamics are compared to the single cell times-series data. The proposed NLME framework is also compared to the intuitive but limited standard two-stage (STS) approach. We demonstrate that the latter may overestimate variabilities by up to almost five fold. Finally, Monte Carlo simulations of the inferred population model are used to predict the distribution of key characteristics of the Mig1 transient response. We find that with decreasing levels of post-shift glucose, the transient response of Mig1 tend to be faster, more extended, and displays an increased cell-to-cell variability

Allosteric regulation of phosphofructokinase controls the emergence of glycolytic oscillations in isolated yeast cells.

Oscillations are widely distributed in nature and synchronization of oscillators has been described at the cellular level (e.g. heart cells) and at the population level (e.g. fireflies). Yeast glycolysis is the best known oscillatory system, although it has been studied almost exclusively at the population level (i.e. limited to observations of average behaviour in synchronized cultures). We studied individual yeast cells that were positioned with optical tweezers in a microfluidic chamber to determine the precise conditions for autonomous glycolytic oscillations. Hopf bifurcation points were determined experimentally in individual cells as a function of glucose and cyanide concentrations. The experiments were analyzed in a detailed mathematical model and could be interpreted in terms of an oscillatory manifold in a three-dimensional state-space; crossing the boundaries of the manifold coincides with the onset of oscillations and positioning along the longitudinal axis of the volume sets the period. The oscillatory manifold could be approximated by allosteric control values of phosphofructokinase for ATP and AMP. © 2014 FEBS

Genome-wide association study of polymorphisms predisposing to bronchiolitis

Abstract Bronchiolitis is a major cause of hospitalization among infants. Severe bronchiolitis is associated with later asthma, suggesting a common genetic predisposition. Genetic background of bronchiolitis is not well characterized. To identify polymorphisms associated with bronchiolitis, we conducted a genome-wide association study (GWAS) in which 5,300,000 single nucleotide polymorphisms (SNPs) were tested for association in a Finnish–Swedish population of 217 children hospitalized for bronchiolitis and 778 controls. The most promising SNPs (n = 77) were genotyped in a Dutch replication population of 416 cases and 432 controls. Finally, we used a set of 202 Finnish bronchiolitis cases to further investigate candidate SNPs. We did not detect genome-wide significant associations, but several suggestive association signals (p < 10⁻⁵) were observed in the GWAS. In the replication population, three SNPs were nominally associated (p < 0.05). Of them, rs269094 was an expression quantitative trait locus (eQTL) for KCND3, previously shown to be associated with occupational asthma. In the additional set of Finnish cases, the association for another SNP (rs9591920) within a noncoding RNA locus was further strengthened. Our results provide a first genome-wide examination of the genetics underlying bronchiolitis. These preliminary findings require further validation in a larger sample size

Integrative analysis of osmoregulation in yeast Saccharomyces cerevisiae

Similar to other unicellular organisms, yeasts frequently encounter environmental stress such as heat shock, osmotic stress, and nutrition limitations, which challenge their growth potential. To survive, all living cells must be able to adapt to changes in their surrounding environment. A set of adaptive responses is triggered that leads to repair of cellular damage in order to overcome these stress conditions. The aim of this thesis is to determine how yeast cells respond to changes in osmolarity and water activity. Upon hyperosmotic shock, water flows out of the cell, resulting in cell shrinkage, and consequently an increase in the concentrations of all substances present in the cytoplasm. Cells adapt their internal osmolarity by gaining an appropriate cell volume as well as an internal water concentration that is optimal for biochemical processes to recover turgor pressure. Osmoregulation is an active process which is mainly regulated by the High Osmolarity Glycerol (HOG) pathway and controls the cellular water balance. The HOG pathway is one of the four yeast MAP kinase pathways. It conveys the hyper osmolarity stress stimulus into the cell machinery and instigates appropriate responses, including global readjustment of gene expression, changes in translational capacity, transient cell cycle arrest, and accumulation of the compatible solute glycerol. Together, these processes result in osmoadaptation. In this thesis I investigated the quantitative characteristics of osmoregulation in the yeast Saccharomyces cerevisiae. I applied a combination of traditional molecular approaches and frontline technologies for comprehensive and quantitative measurements, such as high throughput experiments, synthetic biology, single cell analysis and mathematical modeling to understand the interdependence and timeline of different osmoadaptation process