Successful establishment of primary small airway cell cultures in human lung transplantation

Background: The study of small airway diseases such as post-transplant bronchiolitis obliterans syndrome (BOS) is hampered by the difficulty in assessing peripheral airway function either physiologically or directly. Our aims were to develop robust methods for sampling small airway epithelial cells (SAEC) and to establish submerged SAEC cultures for downstream experimentation

rMotifGen: random motif generator for DNA and protein sequences

<p>Abstract</p> <p>Background</p> <p>Detection of short, subtle conserved motif regions within a set of related DNA or amino acid sequences can lead to discoveries about important regulatory domains such as transcription factor and DNA binding sites as well as conserved protein domains. In order to help assess motif detection algorithms on motifs with varying properties and levels of conservation, we have developed a computational tool, rMotifGen, with the sole purpose of generating a number of random DNA or protein sequences containing short sequence motifs. Each motif consensus can be user-defined, randomly generated, or created from a position-specific scoring matrix (PSSM). Insertions and mutations within these motifs are created according to user-defined parameters and substitution matrices. The resulting sequences can be helpful in mutational simulations and in testing the limits of motif detection algorithms.</p> <p>Results</p> <p>Two implementations of rMotifGen have been created, one providing a graphical user interface (GUI) for random motif construction, and the other serving as a command line interface. The second implementation has the added advantages of platform independence and being able to be called in a batch mode. rMotifGen was used to construct sample sets of sequences containing DNA motifs and amino acid motifs that were then tested against the Gibbs sampler and MEME packages.</p> <p>Conclusion</p> <p>rMotifGen provides an efficient and convenient method for creating random DNA or amino acid sequences with a variable number of motifs, where the instance of each motif can be incorporated using a position-specific scoring matrix (PSSM) or by creating an instance mutated from its corresponding consensus using an evolutionary model based on substitution matrices. rMotifGen is freely available at: <url>http://bioinformatics.louisville.edu/brg/rMotifGen/</url>.</p

Using quantile regression to investigate racial disparities in medication non-adherence

<p>Abstract</p> <p>Background</p> <p>Many studies have investigated racial/ethnic disparities in medication non-adherence in patients with type 2 diabetes using common measures such as medication possession ratio (MPR) or gaps between refills. All these measures including MPR are quasi-continuous and bounded and their distribution is usually skewed. Analysis of such measures using traditional regression methods that model mean changes in the dependent variable may fail to provide a full picture about differential patterns in non-adherence between groups.</p> <p>Methods</p> <p>A retrospective cohort of 11,272 veterans with type 2 diabetes was assembled from Veterans Administration datasets from April 1996 to May 2006. The main outcome measure was MPR with quantile cutoffs Q1-Q4 taking values of 0.4, 0.6, 0.8 and 0.9. Quantile-regression (QReg) was used to model the association between MPR and race/ethnicity after adjusting for covariates. Comparison was made with commonly used ordinary-least-squares (OLS) and generalized linear mixed models (GLMM).</p> <p>Results</p> <p>Quantile-regression showed that Non-Hispanic-Black (NHB) had statistically significantly lower MPR compared to Non-Hispanic-White (NHW) holding all other variables constant across all quantiles with estimates and p-values given as -3.4% (p = 0.11), -5.4% (p = 0.01), -3.1% (p = 0.001), and -2.00% (p = 0.001) for Q1 to Q4, respectively. Other racial/ethnic groups had lower adherence than NHW only in the lowest quantile (Q1) of about -6.3% (p = 0.003). In contrast, OLS and GLMM only showed differences in mean MPR between NHB and NHW while the mean MPR difference between other racial groups and NHW was not significant.</p> <p>Conclusion</p> <p>Quantile regression is recommended for analysis of data that are heterogeneous such that the tails and the central location of the conditional distributions vary differently with the covariates. QReg provides a comprehensive view of the relationships between independent and dependent variables (i.e. not just centrally but also in the tails of the conditional distribution of the dependent variable). Indeed, without performing QReg at different quantiles, an investigator would have no way of assessing whether a difference in these relationships might exist.</p

Selection against Spurious Promoter Motifs Correlates with Translational Efficiency across Bacteria

Because binding of RNAP to misplaced sites could compromise the efficiency of transcription, natural selection for the optimization of gene expression should regulate the distribution of DNA motifs capable of RNAP-binding across the genome. Here we analyze the distribution of the −10 promoter motifs that bind the σ70 subunit of RNAP in 42 bacterial genomes. We show that selection on these motifs operates across the genome, maintaining an over-representation of −10 motifs in regulatory sequences while eliminating them from the nonfunctional and, in most cases, from the protein coding regions. In some genomes, however, −10 sites are over-represented in the coding sequences; these sites could induce pauses effecting regulatory roles throughout the length of a transcriptional unit. For nonfunctional sequences, the extent of motif under-representation varies across genomes in a manner that broadly correlates with the number of tRNA genes, a good indicator of translational speed and growth rate. This suggests that minimizing the time invested in gene transcription is an important selective pressure against spurious binding. However, selection against spurious binding is detectable in the reduced genomes of host-restricted bacteria that grow at slow rates, indicating that components of efficiency other than speed may also be important. Minimizing the number of RNAP molecules per cell required for transcription, and the corresponding energetic expense, may be most relevant in slow growers. These results indicate that genome-level properties affecting the efficiency of transcription and translation can respond in an integrated manner to optimize gene expression. The detection of selection against promoter motifs in nonfunctional regions also confirms previous results indicating that no sequence may evolve free of selective constraints, at least in the relatively small and unstructured genomes of bacteria

Selective C-Rel Activation via Malt1 Controls Anti-Fungal TH-17 Immunity by Dectin-1 and Dectin-2

C-type lectins dectin-1 and dectin-2 on dendritic cells elicit protective immunity against fungal infections through induction of TH1 and TH-17 cellular responses. Fungal recognition by dectin-1 on human dendritic cells engages the CARD9-Bcl10-Malt1 module to activate NF-κB. Here we demonstrate that Malt1 recruitment is pivotal to TH-17 immunity by selective activation of NF-κB subunit c-Rel, which induces expression of TH-17-polarizing cytokines IL-1β and IL-23p19. Malt1 inhibition abrogates c-Rel activation and TH-17 immunity to Candida species. We found that Malt1-mediated activation of c-Rel is similarly essential to induction of TH-17-polarizing cytokines by dectin-2. Whereas dectin-1 activates all NF-κB subunits, dectin-2 selectively activates c-Rel, signifying a specialized TH-17-enhancing function for dectin-2 in anti-fungal immunity by human dendritic cells. Thus, dectin-1 and dectin-2 control adaptive TH-17 immunity to fungi via Malt1-dependent activation of c-Rel

Identification of Trypanosoma brucei RMI1/BLAP75 Homologue and Its Roles in Antigenic Variation

At any time, each cell of the protozoan parasite Trypanosoma brucei expresses a single species of its major antigenic protein, the variant surface glycoprotein (VSG), from a repertoire of >2,000 VSG genes and pseudogenes. The potential to express different VSGs by transcription and recombination allows the parasite to escape the antibody-mediated host immune response, a mechanism known as antigenic variation. The active VSG is transcribed from a sub-telomeric polycistronic unit called the expression site (ES), whose promoter is 40–60 kb upstream of the VSG. While the mechanisms that initiate recombination remain unclear, the resolution phase of these reactions results in the recombinational replacement of the expressed VSG with a donor from one of three distinct chromosomal locations; sub-telomeric loci on the 11 essential chromosomes, on minichromosomes, or at telomere-distal loci. Depending on the type of recombinational replacement (single or double crossover, duplicative gene conversion, etc), several DNA-repair pathways have been thought to play a role. Here we show that VSG recombination relies on at least two distinct DNA-repair pathways, one of which requires RMI1-TOPO3α to suppress recombination and one that is dependent on RAD51 and RMI1. These genetic interactions suggest that both RAD51-dependent and RAD51-independent recombination pathways operate in antigenic switching and that trypanosomes differentially utilize recombination factors for VSG switching, depending on currently unknown parameters within the ES

Candidate Glutamatergic Neurons in the Visual System of Drosophila

The visual system of Drosophila contains approximately 60,000 neurons that are organized in parallel, retinotopically arranged columns. A large number of these neurons have been characterized in great anatomical detail. However, studies providing direct evidence for synaptic signaling and the neurotransmitter used by individual neurons are relatively sparse. Here we present a first layout of neurons in the Drosophila visual system that likely release glutamate as their major neurotransmitter. We identified 33 different types of neurons of the lamina, medulla, lobula and lobula plate. Based on the previous Golgi-staining analysis, the identified neurons are further classified into 16 major subgroups representing lamina monopolar (L), transmedullary (Tm), transmedullary Y (TmY), Y, medulla intrinsic (Mi, Mt, Pm, Dm, Mi Am), bushy T (T), translobula plate (Tlp), lobula intrinsic (Lcn, Lt, Li), lobula plate tangential (LPTCs) and lobula plate intrinsic (LPi) cell types. In addition, we found 11 cell types that were not described by the previous Golgi analysis. This classification of candidate glutamatergic neurons fosters the future neurogenetic dissection of information processing in circuits of the fly visual system