Free and polymerized tubulin in cultured bone cells and Chinese hamster ovary cells: the influence of cold and hormones

A low pH method of liposome-membrane fusion (Schneider et al., 1980, Proc. Natl. Acad. Sci. U. S. A. 77:442) was used to enrich the mitochondrial inner membrane lipid bilayer 30-700% with exogenous phospholipid and cholesterol. By varying the phospholipid-to- cholesterol ratio of the liposomes it was possible to incorporate specific amounts of cholesterol (up to 44 mol %) into the inner membrane bilayer in a controlled fashion. The membrane surface area increased proportionally to the increase in total membrane bilayer lipid. Inner membrane enriched with phospholipid only, or with phospholipid plus cholesterol up to 20 mol %, showed randomly distributed intramembrane particles (integral proteins) in the membrane plane, and the average distance between intramembrane particles increased proportionally to the amount of newly incorporated lipid. Membranes containing between 20 and 27 mol % cholesterol exhibited small clusters of intramembrane particles while cholesterol contents above 27 mol % resulted in larger aggregations of intramembrane particles. In phospholipid-enriched membranes with randomly dispersed intramembrane particles, electron transfer activities from NADH- and succinate-dehydrogenase to cytochrome c decreased proportionally to the increase in distance between the particles. In contrast, these electron- transfer activities increased with decreasing distances between intramembrane particles brought about by cholesterol incorporation. These results indicate that (a) catalytically interacting redox components in the mitochondrial inner membrane such as the dehydrogenase complexes, ubiquinone, and heme proteins are independent, laterally diffusible components; (b) the average distance between these redox components is effected by the available surface area of the membrane lipid bilayer; and (c) the distance over which redox components diffuse before collision and electron transfer mediates the rate of such transfer.     

EPISTASIS AND THE EFFECT OF FOUNDER EVENTS ON THE ADDITIVE GENETIC VARIANCE

Models of founder events have focused on the reduction in the genetic variation following a founder event. However, recent work (Bryant et al., 1986; Goodnight, 1987) suggests that when there is epistatic genetic variance in a population, the total genetic variance within demes may actually increase following a founder event. Since the additive genetic variance is a statistical property of a population and can change with the level of inbreeding, some of the epistatic genetic variance may be converted to additive genetic variance during a founder event. The model presented here demonstrates that some of the additive-by-additive epistatic genetic variance is converted to additive genetic variance following a founder event. Furthermore, the amount of epistasis converted to additive genetic variance is a function of the recombination rate and the propagule size. For a single founder event of two individuals, as much as 75% of the epistatic variance in the ancestral population may become additive genetic variance following the founder event. For founder events involving two individuals with free recombination, the relative contribution of epistasis to the additive genetic variance following a founder event is equal to its proportion of the total genetic variance prior to the founder event. Traits closely related to fitness are expected to have relatively little additive genetic variance but may have substantial nonadditive genetic variance. Founder events may be important in the evolution of fitness traits, not because they lead to a reduction in the genetic variance, but rather because they lead to an increase in the additive genetic variance.     

Movements and associations of ribosomal subunits in a secretory cell during growth inhibition by starvation

In Chironomus tentans salivary gland cells, the cytoplasm can be dissected into concentric zones situated at increasing distances from the nuclear envelope. After RNA labeling, the newly made ribosomal subunits are found in the cytoplasm mainly in the neighborhood of the nucleus with a gradient of increasing abundance towards the periphery of the cell. The gradient for the small subunit lasts for a few hours and disappears entirely after treatment with puromycin. The large subunit also forms a gradient but one which is only partially abolished by puromycin. The residual gradient which which is resistant to the addition of the drug is probably due to the binding of some large ribosomal units to the membranes of the endoplasmic reticulum (J.-E. Edstrom and u. Lonn. 1976. J. Cell Biol. 70:562-572, and U. Lonn and J.-E. Edstrom. 1976. J. Cell. Biol. 70:573-580). If growth is inhibited by starvation, only the puromycin-sensitive type gradient is observed for the large subunit, suggesting that the attachment of these newly made subunits to the endoplasmic reticulum membranes will not occur. If, on the other hand, the drug-resistant gradient is allowed to form in feeding animals, it is conserved during a subsequent starvation for longer periods than in control feeding animals. This observation provides a further support for an effect of starvation on the normal turnover of the large subunits associated with the endoplasmic reticulum. These results also indicate a considerable structural stability in the cytoplasm of these cells worth little or no gross redistribution of cytoplasmic structures over a period of at least 6 days.     

Ectopic expression of protein kinase CbetaII, -delta, and -epsilon, but not -betaI or -zeta, provide for insulin stimulation of glucose uptake in NIH-3T3 cells

Insulin regulates a diverse array of signaling pathways involved in the control of growth, differentiation, proliferation, and metabolism. Insulin increases in glucose uptake via a protein kinase C-dependent pathway in target tissues such as fat and muscle are well documented. Insulin-regulated events, however, occur in all cells. The utilization of glucose as a preferred energy source is a ubiquitous event in eukaryotic cells. In NIH-3T3 fibroblasts, insulin treatment increased levels of the cPKC and nPKC activator, diacylglycerol. Insulin-responsive 2-[(3)H]deoxyglucose uptake was stimulated in a dose-dependent manner. The overexpression of protein kinase C (PKC)betaI, -betaII, -delta, -epsilon, and -zeta was used to investigate the specificity of PKC isozymes for insulin-sensitive glucose uptake. The stable overexpression of PKCbetaII, -delta, and -epsilon resulted in increases in insulin-stimulated 2-[(3)H]deoxyglucose uptake compared to vector control cells, while basal 2-deoxyglucose uptake levels were not elevated. Overexpression of PKCbetaI and PKCzeta isozymes had no further effect on basal or insulin-stimulated 2-deoxyglucose uptake. The PKC-specific inhibitor, CGP41251, blocked insulin effects on 2-deoxyglucose uptake but not its effects on tyrosine phosphorylation of cellular substrates. Insulin-stimulated 3-O-methylglucose uptake was also greater in cells overexpressing PKCbetaII, -delta, and -epsilon, compared to control cells. The increased responsiveness was not accompanied by conversion of 3T3 cells to the adipocyte phenotype or the increased expression of insulin receptors or glucose transporters (GLUT1-type). Insulin-stimulated recruitment of GLUT1 to plasma membranes of cells overexpressing PKCbetaII, -delta, and -epsilon, was greater than that in control cells. The data suggest that more than one PKC isozyme is involved in insulin signaling pathways in fibroblasts, resulting in increased GLUT1 transporter recruitment to cell membranes.     

ESTIMATING RELATEDNESS USING GENETIC MARKERS

A new method is described for estimating genetic relatedness from genetic markers such as protein polymorphisms. It is based on Grafen's (1985) relatedness coefficient and is most easily interpreted in terms of identity by descent rather than as a genetic regression. It has several advantages over methods currently in use: it eliminates a downward bias for small sample sizes; it improves estimation of relatedness for subsets of population samples; and it allows estimation of relatedness for a single group or for a single pair of individuals. Individual estimates of relatedness tend to be highly variable but, in aggregate, can still be very useful as data for nonparametric tests. Such tests allow testing for differences in relatedness between two samples or for correlating individual relatedness values with another variable.     

Modeling <Emphasis Type="Italic">Neisseria meningitidis</Emphasis> metabolism: from genome to metabolic fluxes

Background  

Neisseria meningitidis is a human pathogen that can infect diverse sites within the human host. The major diseases caused by N. meningitidis are responsible for death and disability, especially in young infants. In general, most of the recent work on N. meningitidis focuses on potential antigens and their functions, immunogenicity, and pathogenicity mechanisms. Very little work has been carried out on Neisseria primary metabolism over the past 25 years.     

Simulation of human atherosclerotic femoral plaque tissue: the influence of plaque material model on numerical results

Background

Due to the limited number of experimental studies that mechanically characterise human atherosclerotic plaque tissue from the femoral arteries, a recent trend has emerged in current literature whereby one set of material data based on aortic plaque tissue is employed to numerically represent diseased femoral artery tissue. This study aims to generate novel vessel-appropriate material models for femoral plaque tissue and assess the influence of using material models based on experimental data generated from aortic plaque testing to represent diseased femoral arterial tissue.

Methods

Novel material models based on experimental data generated from testing of atherosclerotic femoral artery tissue are developed and a computational analysis of the revascularisation of a quarter model idealised diseased femoral artery from a 90% diameter stenosis to a 10% diameter stenosis is performed using these novel material models. The simulation is also performed using material models based on experimental data obtained from aortic plaque testing in order to examine the effect of employing vessel appropriate material models versus those currently employed in literature to represent femoral plaque tissue.

Results

Simulations that employ material models based on atherosclerotic aortic tissue exhibit much higher maximum principal stresses within the plaque than simulations that employ material models based on atherosclerotic femoral tissue. Specifically, employing a material model based on calcified aortic tissue, instead of one based on heavily calcified femoral tissue, to represent diseased femoral arterial vessels results in a 487 fold increase in maximum principal stress within the plaque at a depth of 0.8 mm from the lumen.

Conclusions

Large differences are induced on numerical results as a consequence of employing material models based on aortic plaque, in place of material models based on femoral plaque, to represent a diseased femoral vessel. Due to these large discrepancies, future studies should seek to employ vessel-appropriate material models to simulate the response of diseased femoral tissue in order to obtain the most accurate numerical results.

     

Review and classification of variability analysis techniques with clinical applications

Background

Representation of independent biophysical sources using Fourier analysis can be inefficient because the basis is sinusoidal and general. When complex fractionated atrial electrograms (CFAE) are acquired during atrial fibrillation (AF), the electrogram morphology depends on the mix of distinct nonsinusoidal generators. Identification of these generators using efficient methods of representation and comparison would be useful for targeting catheter ablation sites to prevent arrhythmia reinduction.

Method

A data-driven basis and transform is described which utilizes the ensemble average of signal segments to identify and distinguish CFAE morphologic components and frequencies. Calculation of the dominant frequency (DF) of actual CFAE, and identification of simulated independent generator frequencies and morphologies embedded in CFAE, is done using a total of 216 recordings from 10 paroxysmal and 10 persistent AF patients. The transform is tested versus Fourier analysis to detect spectral components in the presence of phase noise and interference. Correspondence is shown between ensemble basis vectors of highest power and corresponding synthetic drivers embedded in CFAE.

Results

The ensemble basis is orthogonal, and efficient for representation of CFAE components as compared with Fourier analysis (p ≤ 0.002). When three synthetic drivers with additive phase noise and interference were decomposed, the top three peaks in the ensemble power spectrum corresponded to the driver frequencies more closely as compared with top Fourier power spectrum peaks (p ≤ 0.005). The synthesized drivers with phase noise and interference were extractable from their corresponding ensemble basis with a mean error of less than 10%.

Conclusions

The new transform is able to efficiently identify CFAE features using DF calculation and by discerning morphologic differences. Unlike the Fourier transform method, it does not distort CFAE signals prior to analysis, and is relatively robust to jitter in periodic events. Thus the ensemble method can provide a useful alternative for quantitative characterization of CFAE during clinical study.     

Multilevel selection: the evolution of cooperation in non-kin groups

Hamiltons (1964a, 1964b) landmark papers are rightly recognized as the formal basis for our understanding of the evolution of altruistic traits. However, Hamiltons equation as he originally expressed it is simplistic. A genetically oriented approach to studying multilevel selection can provide insights into how the terminology and assumptions used by Hamilton can be generalized. Using contextual analysis I demonstrated that Hamiltons rule actually embodies three distinct processes, group selection, individual selection, and transmission genetics or heritability. Whether an altruistic trait will evolve depends the balance of all of these factors. The genetical approach, and particularly, contextual analysis provides a means of separating these factors and examining them one at a time. Perhaps the greatest issue with Hamiltons equation is the interpretation of r. Hamilton (1964a) interpreted this as relatedness. In this paper I show that what Hamilton called relatedness is more generally interpreted as the proportion for variance among groups, and that many processes in addition to relatedness can increase the variance among groups. I also show that the evolution of an altruistic trait is driven by the ratio of the heritability at the group level to the heritability at the individual level. Under some circumstances this ratio can be greater than 1. In this situation altruism can evolve even if selection favoring selfish behavior is stronger than selection favoring altruism.