Hyphenation of sedimentation field flow fractionation with flow cytometry

Interest in the development of field flow fractionation (FFF) systems for cell sorting recently increased with the possibility of collecting and characterizing viable cellular materials. There are various tools for the analysis of cell characteristics, but the reference is small- and large-angle light scattering often coupled with fluorimetric measurements. The well-known flow cytometry (FC) cell analysis techniques can be associated with FFF leading to the possibility of collecting information provided by a remarkable separation technique for micron-sized particles (cells) operating in the steric-hyperlayer elution mode with multiparametric detection provided by flow cytometry. Moreover FFF derived cell characteristics can be correlated with FC characteristics to describe in a unique way the nature of the eluted materials. Experimental demonstrations are described herein using nucleated cells (HL-60 cell lineage) and human red blood cells (HRBC).     

Improved chip design for integrated solid-phase microextraction in on-line proteomic sample preparation

A recently introduced silicon microextraction chip (SMEC), used for on-line proteomic sample preparation, has proved to facilitate the process of protein identification by sample clean up and enrichment of peptides. It is demonstrated that a novel grid-SMEC design improves the operating characteristics for solid-phase microextraction, by reducing dispersion effects and thereby improving the sample preparation conditions. The structures investigated in this paper are treated both numerically and experimentally. The numerical approach is based on finite element analysis of the microfluidic flow in the microchip. The analysis is accomplished by use of the computational fluid dynamics-module FLOTRAN in the ANSYS software package. The modeling and analysis of the previously reported weir-SMEC design indicates some severe drawbacks, that can be reduced by changing the microextraction chip geometry to the grid-SMEC design. The overall analytical performance was thereby improved and also verified by experimental work. Matrix-assisted laser desorption/ionization mass spectra of model peptides extracted from both the weir-SMEC and the new grid-SMEC support the numerical analysis results. Further use of numerical modeling and analysis of the SMEC structures is also discussed and suggested in this work.     

Disialoganglioside GD3 is released by microglia and induces oligodendrocyte apoptosis

Increased brain ganglioside levels are a hallmark of various neuroinflammatory pathologies. Here, we provide evidence that murine microglia can secrete disialoganglioside GD3 upon exposure to inflammatory stimuli. Comparison of different neural cell types revealed a particular and specific sensitivity of oligodendrocytes towards exogenous GD3. Oligodendrocyte death triggered by GD3 was preceded by degeneration of cellular processes, and associated with typical features of apoptosis, such as chromatin condensation, exposure of phosphatidylserine, release of cytochrome c from mitochondria, and loss of mitochondrial membrane potential, followed by the loss of plasma membrane integrity and detachment of disintegrated oligodendrocytes. Overexpression of bcl-2 partially protected oligodendrocytes from death. In contrast, treatment with the pan-caspase inhibitor zVAD-fmk did not prevent phosphatidylserine exposure, chromatin margination at the nuclear periphery, and death, although caspase-3 was blocked. Thus, GD3 produced by microglia under neuroinflammatory conditions may function as a novel mediator triggering mitochondria-mediated, but caspase-independent, apoptosis-like death of oligodendrocytes.     

A Bayesian framework for combining gene predictions

MOTIVATION: Gene identification and gene discovery in new genomic sequences is one of the most timely computational questions addressed by bioinformatics scientists. This computational research has resulted in several systems that have been used successfully in many whole-genome analysis projects. As the number of such systems grows the need for a rigorous way to combine the predictions becomes more essential. RESULTS: In this paper we provide a Bayesian network framework for combining gene predictions from multiple systems. The framework allows us to treat the problem as combining the advice of multiple experts. Previous work in the area used relatively simple ideas such as majority voting. We introduce, for the first time, the use of hidden input/output Markov models for combining gene predictions. We apply the framework to the analysis of the Adh region in Drosophila that has been carefully studied in the context of gene finding and used as a basis for the GASP competition. The main challenge in combination of gene prediction programs is the fact that the systems are relying on similar features such as cod on usage and as a result the predictions are often correlated. We show that our approach is promising to improve the prediction accuracy and provides a systematic and flexible framework for incorporating multiple sources of evidence into gene prediction systems.     

Characterization of the adhesive mucilages secreted by live diatom cells using atomic force microscopy

Atomic Force Microscopy (AFM) resolved the topography and mechanical properties of two distinct adhesive mucilages secreted by the marine, fouling diatom Craspedostauros australis. Tapping mode images of live cells revealed a soft and cohesive outer mucilage layer that encased most of the diatom's siliceous wall, and force curves revealed an adhesive force of 3.58 nN. High loading force, contact mode imaging resulted in cantilever 'cleaned' cell walls, which enabled the first direct observation of the active secretion of soft mucilage via pore openings. A second adhesive mucilage consisted of strands secreted at the raphe, a distinct slit in the silica wall involved in cell-substratum attachment and motility. Force measurements revealed a raphe adhesive strand(s) resistant to breaking forces up to 60 nN, and these strands could only be detached from the AFM cantilever probe using the manual stepper motor.     

Oncostatin M induces tissue-type plasminogen activator and plasminogen activator inhibitor-1 in Calu-1 lung carcinoma cells

Oncostatin M (OSM) is a glycoprotein cytokine that is produced by activated T-lymphocytes, monocytes, and macrophages. In a DNA synthesis assay, OSM reduced tritiated thymidine incorporation by 53% in Calu-1 lung carcinoma cells. Radiolabeled cDNAs from untreated Calu-1 cells and 30-h OSM-treated cells were used to probe duplicate nylon membrane cDNA expression arrays. This study revealed OSM-mediated expression of mRNAs encoding tissue-type plasminogen activator (tPA) and plasminogen activator inhibitor-1 (PAI-1). Northern blot analysis showed that the steady-state level of tPA mRNA is nearly undetectable in Calu-1 cells. Exposure of these cells to OSM for 30 h increased tPA mRNA expression by 20-fold and PAI-1 mRNA expression by 5-fold. Exposure of these cells to other gp130 receptor family cytokines, including leukemia inhibitory factor (LIF), interleukin-6 (IL-6), and IL-11, do not significantly affect DNA synthesis or induction of tPA/PAI-1. Western blot studies demonstrated that OSM mediates a marked increase in secretion of the tPA protein. Secreted tPA was present in the conditioned medium almost exclusively as tPA/PAI-1 complexes. Inhibitor studies demonstrated that OSM-mediated induction of tPA and PAI-1 mRNAs is largely dependent upon activation of the MEK1/2 pathway. The JAK3/STAT3 pathway potentially serves a secondary role in these regulatory events.     

Combined data, Bayesian phylogenetics, and the origin of the New Zealand cicada genera

We have applied Bayesian and maximum likelihood methods of phylogenetic estimation to data from four mitochondrial genes (COI, COII, 12S, and 16S) and a single nuclear gene (EF1alpha) from several genera of New Zealand, Australian, and New Caledonian cicada taxa. We specifically focused on the heterogeneity of phylogenetic signal among the different data partitions and the biogeographic origins of the New Zealand cicada fauna. The Bayesian analyses circumvent many of the problems associated with other statistical tests for comparing data partitions. We took an information-theoretic approach to model selection based on the Akaike Information Criterion (AIC). This approach indicated that there was considerable uncertainty in identifying the best-fit model for some of the partitions. Additionally, a large amount of uncertainty was associated with many parameter estimates from the substitution model. However, a sensitivity analysis on the combined dataset indicated that the model selection uncertainty had little effect on estimates of topology because these estimates were largely insensitive to changes in the assumed model. This outcome suggests strong signal in our data. Our analyses support a New Caledonian affiliation of the New Zealand cicada genera Maoricicada, Kikihia, and Rhodopsalta and Australian affinities for the genera Amphipsalta and Notopsalta. This result was surprising, given that previous cicada biologists suspected a close relationship between Amphipsalta, Notopsalta, and Rhodopsalta based on genitalic characters. Relationships among the closely related genera Maoricicada, Kikihia, and Rhodopsalta were poorly resolved, the mitochondrial data and the EF1alpha data favoring different arrangements within this clade.