7 resultados para effect of cell size

em Duke University


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During bacterial growth, a cell approximately doubles in size before division, after which it splits into two daughter cells. This process is subjected to the inherent perturbations of cellular noise and thus requires regulation for cell-size homeostasis. The mechanisms underlying the control and dynamics of cell size remain poorly understood owing to the difficulty in sizing individual bacteria over long periods of time in a high-throughput manner. Here we measure and analyse long-term, single-cell growth and division across different Escherichia coli strains and growth conditions. We show that a subset of cells in a population exhibit transient oscillations in cell size with periods that stretch across several (more than ten) generations. Our analysis reveals that a simple law governing cell-size control-a noisy linear map-explains the origins of these cell-size oscillations across all strains. This noisy linear map implements a negative feedback on cell-size control: a cell with a larger initial size tends to divide earlier, whereas one with a smaller initial size tends to divide later. Combining simulations of cell growth and division with experimental data, we demonstrate that this noisy linear map generates transient oscillations, not just in cell size, but also in constitutive gene expression. Our work provides new insights into the dynamics of bacterial cell-size regulation with implications for the physiological processes involved.

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Cellular therapies have recently employed the use of small RNA molecules, particularly microRNAs (miRNAs), to regulate various cellular processes that may be altered in disease states. In this study, we examined the effect of transient muscle-specific miRNA inhibition on the function of three-dimensional skeletal muscle cultures, or bioartificial muscles (BAMs). Skeletal myoblast differentiation in vitro is enhanced by inhibiting a proliferation-promoting miRNA (miR-133) expressed in muscle tissues. As assessed by functional force measurements in response to electrical stimulation at frequencies ranging from 0 to 20 Hz, peak forces exhibited by BAMs with miR-133 inhibition (anti-miR-133) were on average 20% higher than the corresponding negative control, although dynamic responses to electrical stimulation in miRNA-transfected BAMs and negative controls were similar to nontransfected controls. Immunostaining for alpha-actinin and myosin also showed more distinct striations and myofiber organization in anti-miR-133 BAMs, and fiber diameters were significantly larger in these BAMs over both the nontransfected and negative controls. Compared to the negative control, anti-miR-133 BAMs exhibited more intense nuclear staining for Mef2, a key myogenic differentiation marker. To our knowledge, this study is the first to demonstrate that miRNA mediation has functional effects on tissue-engineered constructs.

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While the Stokes-Einstein (SE) equation predicts that the diffusion coefficient of a solute will be inversely proportional to the viscosity of the solvent, this relation is commonly known to fail for solutes, which are the same size or smaller than the solvent. Multiple researchers have reported that for small solutes, the diffusion coefficient is inversely proportional to the viscosity to a fractional power, and that solutes actually diffuse faster than SE predicts. For other solvent systems, attractive solute-solvent interactions, such as hydrogen bonding, are known to retard the diffusion of a solute. Some researchers have interpreted the slower diffusion due to hydrogen bonding as resulting from the effective diffusion of a larger complex of a solute and solvent molecules. We have developed and used a novel micropipette technique, which can form and hold a single microdroplet of water while it dissolves in a diffusion controlled environment into the solvent. This method has been used to examine the diffusion of water in both n-alkanes and n-alcohols. It was found that the polar solute water, diffusing in a solvent with which it cannot hydrogen bond, closely resembles small nonpolar solutes such as xenon and krypton diffusing in n-alkanes, with diffusion coefficients ranging from 12.5x10(-5) cm(2)/s for water in n-pentane to 1.15x10(-5) cm(2)/s for water in hexadecane. Diffusion coefficients were found to be inversely proportional to viscosity to a fractional power, and diffusion coefficients were faster than SE predicts. For water diffusing in a solvent (n-alcohols) with which it can hydrogen bond, diffusion coefficient values ranged from 1.75x10(-5) cm(2)/s in n-methanol to 0.364x10(-5) cm(2)/s in n-octanol, and diffusion was slower than an alkane of corresponding viscosity. We find no evidence for solute-solvent complex diffusion. Rather, it is possible that the small solute water may be retarded by relatively longer residence times (compared to non-H-bonding solvents) as it moves through the liquid.

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We have used analytical ultracentrifugation to characterize the binding of the methionine repressor protein, MetJ, to synthetic oligonucleotides containing zero to five specific recognition sites, called metboxes. For all lengths of DNA studied, MetJ binds more tightly to repeats of the consensus sequence than to naturally occurring metboxes, which exhibit a variable number of deviations from the consensus. Strong cooperative binding occurs only in the presence of two or more tandem metboxes, which facilitate protein-protein contacts between adjacent MetJ dimers, but weak affinity is detected even with DNA containing zero or one metbox. The affinity of MetJ for all of the DNA sequences studied is enhanced by the addition of SAM, the known cofactor for MetJ in the cell. This effect extends to oligos containing zero or one metbox, both of which bind two MetJ dimers. In the presence of a large excess concentration of metbox DNA, the effect of cooperativity is to favor populations of DNA oligos bound by two or more MetJ dimers rather than a stochastic redistribution of the repressor onto all available metboxes. These results illustrate the dynamic range of binding affinity and repressor assembly that MetJ can exhibit with DNA and the effect of the corepressor SAM on binding to both specific and nonspecific DNA.

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Transient overexpression of defined combinations of master regulator genes can effectively induce cellular reprogramming: the acquisition of an alternative predicted phenotype from a differentiated cell lineage. This can be of particular importance in cardiac regenerative medicine wherein the heart lacks the capacity to heal itself, but simultaneously contains a large pool of fibroblasts. In this study we determined the cardio-inducing capacity of ten transcription factors to actuate cellular reprogramming of mouse embryonic fibroblasts into cardiomyocyte-like cells. Overexpression of transcription factors MYOCD and SRF alone or in conjunction with Mesp1 and SMARCD3 enhanced the basal but necessary cardio-inducing effect of the previously reported GATA4, TBX5, and MEF2C. In particular, combinations of five or seven transcription factors enhanced the activation of cardiac reporter vectors, and induced an upregulation of cardiac-specific genes. Global gene expression analysis also demonstrated a significantly greater cardio-inducing effect when the transcription factors MYOCD and SRF were used. Detection of cross-striated cells was highly dependent on the cell culture conditions and was enhanced by the addition of valproic acid and JAK inhibitor. Although we detected Ca(2+) transient oscillations in the reprogrammed cells, we did not detect significant changes in resting membrane potential or spontaneously contracting cells. This study further elucidates the cardio-inducing effect of the transcriptional networks involved in cardiac cellular reprogramming, contributing to the ongoing rational design of a robust protocol required for cardiac regenerative therapies.

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The fundamental phenotypes of growth rate, size and morphology are the result of complex interactions between genotype and environment. We developed a high-throughput software application, WormSizer, which computes size and shape of nematodes from brightfield images. Existing methods for estimating volume either coarsely model the nematode as a cylinder or assume the worm shape or opacity is invariant. Our estimate is more robust to changes in morphology or optical density as it only assumes radial symmetry. This open source software is written as a plugin for the well-known image-processing framework Fiji/ImageJ. It may therefore be extended easily. We evaluated the technical performance of this framework, and we used it to analyze growth and shape of several canonical Caenorhabditis elegans mutants in a developmental time series. We confirm quantitatively that a Dumpy (Dpy) mutant is short and fat and that a Long (Lon) mutant is long and thin. We show that daf-2 insulin-like receptor mutants are larger than wild-type upon hatching but grow slow, and WormSizer can distinguish dauer larvae from normal larvae. We also show that a Small (Sma) mutant is actually smaller than wild-type at all stages of larval development. WormSizer works with Uncoordinated (Unc) and Roller (Rol) mutants as well, indicating that it can be used with mutants despite behavioral phenotypes. We used our complete data set to perform a power analysis, giving users a sense of how many images are needed to detect different effect sizes. Our analysis confirms and extends on existing phenotypic characterization of well-characterized mutants, demonstrating the utility and robustness of WormSizer.

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Genome-wide association studies (GWASs) have characterized 13 loci associated with melanoma, which only account for a small part of melanoma risk. To identify new genes with too small an effect to be detected individually but which collectively influence melanoma risk and/or show interactive effects, we used a two-step analysis strategy including pathway analysis of genome-wide SNP data, in a first step, and epistasis analysis within significant pathways, in a second step. Pathway analysis, using the gene-set enrichment analysis (GSEA) approach and the gene ontology (GO) database, was applied to the outcomes of MELARISK (3,976 subjects) and MDACC (2,827 subjects) GWASs. Cross-gene SNP-SNP interaction analysis within melanoma-associated GOs was performed using the INTERSNP software. Five GO categories were significantly enriched in genes associated with melanoma (false discovery rate ≤ 5% in both studies): response to light stimulus, regulation of mitotic cell cycle, induction of programmed cell death, cytokine activity and oxidative phosphorylation. Epistasis analysis, within each of the five significant GOs, showed significant evidence for interaction for one SNP pair at TERF1 and AFAP1L2 loci (pmeta-int  = 2.0 × 10(-7) , which met both the pathway and overall multiple-testing corrected thresholds that are equal to 9.8 × 10(-7) and 2.0 × 10(-7) , respectively) and suggestive evidence for another pair involving correlated SNPs at the same loci (pmeta-int  = 3.6 × 10(-6) ). This interaction has important biological relevance given the key role of TERF1 in telomere biology and the reported physical interaction between TERF1 and AFAP1L2 proteins. This finding brings a novel piece of evidence for the emerging role of telomere dysfunction into melanoma development.