Structure of the lipopolysaccharide core of Vibrio vulnificus type strain 27562

The structure of the lipopolysaccharide core of Vibrio vulnificus type strain 27562 is presented. LPS hydrolysis gave two oligosaccharides, OS-1 and OS-2, as well as lipid A. NMR spectroscopic data corresponded to the presence of one Kdo residue, one β-glucopyranose, three heptoses, one glyceric acid, one acetate, three PEtN, and one 5,7-diacylamido-3,5,7,9-tetradeoxynonulosonic acid residue (pseudaminic acid, Pse) in OS1. OS2 differed form OS 1 by the absence of glyceric acid, acetate, and Pse residues. Lipid A was analyzed for fatty acid composition and the following fatty acids were found: C14:0, C12:0-3OH, C16:0, C16:1, C14:0-3OH, C18:0, C18:1 in a ratio of 1:3:3:1:2.5:0.6:0.8.     

Improved abundance prediction from presence–absence data

Aim   Many ecological surveys record only the presence or absence of species in the cells of a rectangular grid. Ecologists have investigated methods for using these data to predict the total abundance of a species from the number of grid cells in which the species is present. Our aim is to improve such predictions by taking account of the spatial pattern of occupied cells, in addition to the number of occupied cells.
Innovation   We extend existing prediction models to include a spatial clustering variable. The extended models can be viewed as combining two macroecological regularities, the abundance–occupancy regularity and a spatial clustering regularity. The models are estimated using data from five tropical forest censuses, including three Panamanian censuses (4, 6 and 50 ha), one Costa Rican census (16 ha) and one Puerto Rican census (16 ha). A serpentine grassland census (8 × 8 m) from northern California is also studied.
Main conclusions   Taking account of the spatial clustering of occupied cells improves abundance prediction from presence–absence data, reducing the mean square error of log-predictions by roughly 54% relative to a benchmark Poisson predictor and by roughly 34% relative to current prediction methods. The results have high statistical significance.     

High Efficiency Differentiation of Human Pluripotent Stem Cells to Cardiomyocytes and Characterization by Flow Cytometry

There is an urgent need to develop approaches for repairing the damaged heart, discovering new therapeutic drugs that do not have toxic effects on the heart, and improving strategies to accurately model heart disease. The potential of exploiting human induced pluripotent stem cell (hiPSC) technology to generate cardiac muscle “in a dish” for these applications continues to generate high enthusiasm. In recent years, the ability to efficiently generate cardiomyogenic cells from human pluripotent stem cells (hPSCs) has greatly improved, offering us new opportunities to model very early stages of human cardiac development not otherwise accessible. In contrast to many previous methods, the cardiomyocyte differentiation protocol described here does not require cell aggregation or the addition of Activin A or BMP4 and robustly generates cultures of cells that are highly positive for cardiac troponin I and T (TNNI3, TNNT2), iroquois-class homeodomain protein IRX-4 (IRX4), myosin regulatory light chain 2, ventricular/cardiac muscle isoform (MLC2v) and myosin regulatory light chain 2, atrial isoform (MLC2a) by day 10 across all human embryonic stem cell (hESC) and hiPSC lines tested to date. Cells can be passaged and maintained for more than 90 days in culture. The strategy is technically simple to implement and cost-effective. Characterization of cardiomyocytes derived from pluripotent cells often includes the analysis of reference markers, both at the mRNA and protein level. For protein analysis, flow cytometry is a powerful analytical tool for assessing quality of cells in culture and determining subpopulation homogeneity. However, technical variation in sample preparation can significantly affect quality of flow cytometry data. Thus, standardization of staining protocols should facilitate comparisons among various differentiation strategies. Accordingly, optimized staining protocols for the analysis of IRX4, MLC2v, MLC2a, TNNI3, and TNNT2 by flow cytometry are described.     

Phytoplankton assemblages across the marine to low-salinity transition zone in a blackwater dominated estuary

Along the salinity gradient between the freshwater reach ofthe Suwannee River and the marine waters of the Gulf of Mexico,the spatial and temporal composition and abundance of phytoplanktonwas examined in relation to physical and chemical water-columnvariables (i.e. salinity, nutrient and light availability andtemperature). The goal of this study was to explore the applicabilityof the concepts of ecotone and ecocline to the distributionof phytoplankton. This was undertaken in a relatively open estuarydominated by a tannin-colored river, the Suwannee River, alongthe central northwest coast of Florida, USA. Hierarchical clusteranalysis and non-metric multi-dimensional scaling (MDS) wasused to define biologically distinct regions within the estuarybased on the composition of phytoplankton. Variations in phytoplanktonassemblages in relation to environmental variables were investigatedusing a canonical correspondence analysis. The results indicatethat in addition to the alignment of phytoplankton compositionalong a salinity gradient, several key environmental factorsinfluence phytoplankton assemblages within hydrologically distinctregions of the estuary supporting an ecocline view. However,the distribution of dinoflagellate assemblages were in contrastto the more temporally fluid spatial distributions of cyanobacteriaand diatoms in the Suwannee River estuary. The spatially definednature of the dinoflagellate assemblages was more characteristicof an ecotone rather than an ecocline.     

Differential expression of porcine sperm microRNAs and their association with sperm morphology and motility

MicroRNAs (miRNAs) are involved in nearly every biological process examined to date, but little is known of the identity or function of miRNA in sperm cells or their potential involvement in spermatogenesis. The objective was to identify differences in miRNA expression between normal porcine sperm samples and those exhibiting high percentages of morphological abnormalities or low motility. Quantitative RT-PCR was performed on sperm RNA to compare expression levels of 10 specific miRNAs that are predicted to target genes that code for proteins involved in spermatogenesis, sperm structure, motility, or metabolism. There were increases in the expression of four miRNAs, let-7a, -7d, -7e, and miR-22, in the abnormal group (P < 0.05), whereas miR-15b was decreased compared to controls (P < 0.05). Two miRNAs, let-7d and let-7e, were increased in the low motility group when compared to controls (P < 0.05). Bioinformatic analyses revealed that messenger RNA targets of the differentially expressed miRNAs encode proteins previously described to play roles in sperm function. Although the precise role of miRNA in sperm remains to be determined, their changes as associated with morphology and motility signify a critical biological function. Perhaps they are remnants of spermatogenesis, stored for a later role in fertilization, or are delivered to the oocyte to influence early embryonic development. Although there is no single cause of male infertility, the identification of miRNAs associated with sperm motility, structural integrity, or metabolism could lead to the development of a microarray or real time-based diagnostic assay to provide an assessment of male fertility status.     

SNP-SNP Interactions Discovered by Logic Regression Explain Crohn's Disease Genetics

In genome-wide association studies (GWAS), the association between each single nucleotide polymorphism (SNP) and a phenotype is assessed statistically. To further explore genetic associations in GWAS, we considered two specific forms of biologically plausible SNP-SNP interactions, ‘SNP intersection’ and ‘SNP union,’ and analyzed the Crohn''s Disease (CD) GWAS data of the Wellcome Trust Case Control Consortium for these interactions using a limited form of logic regression. We found strong evidence of CD-association for 195 genes, identifying novel susceptibility genes (e.g., ISX, SLCO6A1, TMEM183A) as well as confirming many previously identified susceptibility genes in CD GWAS (e.g., IL23R, NOD2, CYLD, NKX2-3, IL12RB2, ATG16L1). Notably, 37 of the 59 chromosomal locations indicated for CD-association by a meta-analysis of CD GWAS, involving over 22,000 cases and 29,000 controls, were represented in the 195 genes, as well as some chromosomal locations previously indicated only in linkage studies, but not in GWAS. We repeated the analysis with two smaller GWASs from the Database of Genotype and Phenotype (dbGaP): in spite of differences of populations and study power across the three datasets, we observed some consistencies across the three datasets. Notable examples included TMEM183A and SLCO6A1 which exhibited strong evidence consistently in our WTCCC and both of the dbGaP SNP-SNP interaction analyses. Examining these specific forms of SNP interactions could identify additional genetic associations from GWAS. R codes, data examples, and a ReadMe file are available for download from our website: http://www.ualberta.ca/~yyasui/homepage.html.