A unique role for nonmuscle myosin heavy chain IIA in regulation of epithelial apical junctions

The integrity and function of the epithelial barrier is dependent on the apical junctional complex (AJC) composed of tight and adherens junctions and regulated by the underlying actin filaments. A major F-actin motor, myosin II, was previously implicated in regulation of the AJC, however direct evidence of the involvement of myosin II in AJC dynamics are lacking and the molecular identity of the myosin II motor that regulates formation and disassembly of apical junctions in mammalian epithelia is unknown. We investigated the role of nonmuscle myosin II (NMMII) heavy chain isoforms, A, B, and C in regulation of epithelial AJC dynamics and function. Expression of the three NMMII isoforms was observed in model intestinal epithelial cell lines, where all isoforms accumulated within the perijunctional F-actin belt. siRNA-mediated downregulation of NMMIIA, but not NMMIIB or NMMIIC expression in SK-CO15 colonic epithelial cells resulted in profound changes of cell morphology and cell-cell adhesions. These changes included acquisition of a fibroblast-like cell shape, defective paracellular barrier, and substantial attenuation of the assembly and disassembly of both adherens and tight junctions. Impaired assembly of the AJC observed after NMMIIA knock-down involved dramatic disorganization of perijunctional actin filaments. These findings provide the first direct non-pharmacological evidence of myosin II-dependent regulation of AJC dynamics in mammalian epithelia and highlight a unique role of NMMIIA in junctional biogenesis.     

Finding a common motif of RNA sequences using genetic programming: the GeRNAMo system

We focus on finding a consensus motif of a set of homologous or functionally related RNA molecules. Recent approaches to this problem have been limited to simple motifs, require sequence alignment, and make prior assumptions concerning the data set. We use genetic programming to predict RNA consensus motifs based solely on the data set. Our system -- dubbed GeRNAMo (Genetic programming of RNA Motifs) -- predicts the most common motifs without sequence alignment and is capable of dealing with any motif size. Our program only requires the maximum number of stems in the motif, and if prior knowledge is available the user can specify other attributes of the motif (e.g., the range of the motif's minimum and maximum sizes), thereby increasing both sensitivity and speed. We describe several experiments using either ferritin iron response element (IRE); signal recognition particle (SRP); or microRNA sequences, showing that the most common motif is found repeatedly, and that our system offers substantial advantages over previous methods.     

A statistical pattern recognition approach for determining cellular viability and lineage phenotype in cultured cells and murine bone marrow.

BACKGROUND: Cellular binding of annexin V and membrane permeability to 7-aminoactinomycin D (7AAD) are important tools for studying apoptosis and cell death by flow cytometry. Combining viability markers with cell surface marker expression is routinely used to study various cell lineages. Current classification methods using strict thresholds, or "gates," on the fluorescent intensity of these markers are subjective in nature and may not fully describe the phenotypes of interest. We have developed objective criteria for phenotypic boundary recognition through the application of statistical pattern recognition. This task was achieved using artificial neural networks (ANNs) that were trained to recognize subsets of cells with known phenotypes, and then used to determine decision boundaries based on statistical measures of similarity. This approach was then used to test the hypothesis that erythropoietin (EPO) inhibits apoptosis and cell death in erythroid precursor cells in murine bone marrow. METHODS: Our method was developed for classification of viability using an in vitro cell system and then applied to an ex vivo analysis of murine late-stage erythroid progenitors. To induce apoptosis and cell death in vitro, an EPO-dependent human leukemic cell line, UT-7(EPO) cells were incubated without recombinant human erythropoietin (rhEPO) for 72 h. Five different ANNs were trained to recognize live, apoptotic, and dead cells using a "known" subset of the data for training, and a K-fold cross validation procedure for error estimation. The ANNs developed with the in vitro system were then applied to classify cells from an ex vivo study of rhEPO treated mice. Tg197 (human tumor necrosis-alpha transgenic mice, a model of anemia of chronic disease) received a single s.c. dose of 10,000 U/kg rhEPO and femoral bone marrow was collected 1, 2, 4, and 8 days after dosing. Femoral bone marrow cells were stained with TER-119 PE, CD71 APC enable identification of erythroid precursors, and annexin V FITC and 7AAD to identify the apoptotic and dead cells. During classification forward and side angle light scatter were also input to all pattern recognition systems. RESULTS: Similar decision boundaries between live, apoptotic, and dead cells were consistently identified by the neural networks. The best performing network was a radial basis function multi-perceptron that produced an estimated average error rate of 4.5% +/- 0.9%. Using these boundaries, the following results were reached: depriving UT-7(EPO) cells of rhEPO induced apoptosis and cell death while the addition of rhEPO rescued the cells in a dose-dependent manner. In vivo, treatment with rhEPO resulted in an increase of live erythroid cells in the bone marrow to 119.8% +/- 9.8% of control at the 8 day time point. However, a statistically significant transient increase in TER-119(+) CD71(+) 7AAD(+) dead erythroid precursors was observed at the 1 and 2 day time points with a corresponding decrease in TER-119(+) CD71(+) 7AAD(-) Annexin V(-) live erythroid precursors, and no change in the number of TER-119(+) CD71(+) annexin V(+) 7AAD(-) apoptotic erythroid precursors in the bone marrow. CONCLUSIONS: A statistical pattern recognition approach to viability classification provides an objective rationale for setting decision boundaries between "positive" and "negative" intensity measures in cytometric data. Using this approach we have confirmed that rhEPO inhibits apoptosis and cell death in an EPO dependent cell line in vitro, but failed to do so in vivo, suggesting EPO may not act as a simple antiapoptotic agent in the bone marrow. Rather, homeostatic mechanisms may regulate the pharmacodynamic response to rhEPO.     

Plant coloration undermines herbivorous insect camouflage

The main point of our hypothesis "coloration undermines camouflage" is that many color patterns in plants undermine the camouflage of invertebrate herbivores, especially insects, thus exposing them to predation and causing them to avoid plant organs with unsuitable coloration, to the benefit of the plants. This is a common case of "the enemy of my enemy is my friend" and a visual parallel of the chemical signals that plants emit to call wasps when attacked by caterpillars. Moreover, this is also a common natural version of the well-known case of industrial melanism, which illustrates the great importance of plant-based camouflage for herbivorous insects and can serve as an independent test for our hypothesis. We claim that the enormous variations in coloration of leaves, petioles and stems as well as of flowers and fruits undermine the camouflage of invertebrate herbivores, especially insects. We assume that the same principle might operate in certain animal-parasite interactions. Our hypothesis, however, does not contrast or exclude other previous or future explanations of specific types of plant coloration. Traits such as coloration that have more than one type of benefit may be selected for by several agents and evolve more rapidly than ones with a single type of advantage.     

Coevolving solutions to the shortest common superstring problem

The shortest common superstring (SCS) problem, known to be NP-Complete, seeks the shortest string that contains all strings from a given set. In this paper we compare four approaches for finding solutions to the SCS problem: a standard genetic algorithm, a novel cooperative-coevolutionary algorithm, a benchmark greedy algorithm, and a parallel coevolutionary-greedy approach. We show the coevolutionary approach produces the best results, and discuss directions for future research.     

Follicular dynamics and concentrations of steroids and gonadotropins in lactating cows and nulliparous heifers

Differences in follicular development and circulating hormone concentrations, between lactating cows and nulliparous heifers, that may relate to differences in fertility between the groups, were examined. Multiparous, cyclic, lactating Holstein cows (n=19) and cyclic heifers (n=20) were examined in the winter, during one estrous cycle. The examinations included ultrasound monitoring and daily blood sampling. Distributions of two-wave and three-wave cycles were similar in the two groups: 79 and 21% in cows, 70 and 30% in heifers, respectively. Cycle lengths were shorter by 2.6 days in heifers than in cows, and in two-wave than in three-wave cycles. The ovulatory follicle was smaller in heifers than in cows (13.0+/-0.3 mm versus 16.5+/-0.05 mm). The greater numbers of large follicles in cows than in heifers corresponded well to the higher concentrations of FSH in cows. The duration of dominance of the ovulatory follicle tended to be longer in cows than in heifers. Estradiol concentrations around estrus and the preovulatory LH surge were higher in heifers than in cows (20 versus 9 ng/ml). Progesterone concentrations were higher in heifers than in cows from Day 3 to Day 16 of the cycle. Circulating progesterone did not differ between two-wave and three-wave cycles. The results revealed differences in ovarian follicular dynamics, and in plasma concentrations of steroids and gonadotropins; these may account for the differences in fertility between nulliparous heifers and multiparous lactating cows.     

The ternary complex of Pseudomonas aeruginosa alcohol dehydrogenase with NADH and ethylene glycol

Pseudomonas aeruginosa alcohol dehydrogenase (PaADH; ADH, EC 1.1.1.1) catalyzes the reversible oxidation of primary and secondary alcohols to the corresponding aldehydes and ketones, using NAD as coenzyme. We crystallized the ternary complex of PaADH with its coenzyme and a substrate molecule and determined its structure at a resolution of 2.3 A, using the molecular replacement method. The PaADH tetramer comprises four identical chains of 342 amino acid residues each and obeys ~222-point symmetry. The PaADH monomer is structurally similar to alcohol dehydrogenase monomers from vertebrates, archaea, and bacteria. The stabilization of the ternary complex of PaADH, the coenzyme, and the poor substrate ethylene glycol (k(cat) = 4.5 sec(-1); Km > 200 mM) was due to the blocked exit of the coenzyme in the crystalline state, combined with a high (2.5 M) concentration of the substrate. The structure of the ternary complex presents the precise geometry of the Zn coordination complex, the proton-shuttling system, and the hydride transfer path. The ternary complex structure also suggests that the low efficiency of ethylene glycol as a substrate results from the presence of a second hydroxyl group in this molecule.