Expression analysis of G Protein-coupled receptors in mouse macrophages

Background. Monocytes and macrophages express an extensive repertoire of G Protein-Coupled Receptors (GPCRs) that regulate inflammation and immunity. In this study we performed a systematic micro-array analysis of GPCR expression in primary mouse macrophages to identify family members that are either enriched in macrophages compared to a panel of other cell types, or are regulated by an inflammatory stimulus, the bacterial product lipopolysaccharide (LPS). Results. Several members of the P2RY family had striking expression patterns in macrophages; P2ry6 mRNA was essentially expressed in a macrophage-specific fashion, whilst P2ry1 and P2ry5 mRNA levels were strongly down-regulated by LPS. Expression of several other GPCRs was either restricted to macrophages (e.g. Gpr84) or to both macrophages and neural tissues (e.g. P2ry12, Gpr85). The GPCR repertoire expressed by bone marrow-derived macrophages and thioglycollate- elicited peritoneal macrophages had some commonality, but there were also several GPCRs preferentially expressed by either cell population. Conclusion. The constitutive or regulated expression in macrophages of several GPCRs identified in this study has not previously been described. Future studies on such GPCRs and their agonists are likely to provide important insights into macrophage biology, as well as novel inflammatory pathways that could be future targets for drug discovery

Bioinformatic analyses identifies novel protein-coding pharmacogenomic markers associated with paclitaxel sensitivity in NCI60 cancer cell lines

<p>Abstract</p> <p>Background</p> <p>Paclitaxel is a microtubule-stabilizing drug that has been commonly used in treating cancer. Due to genetic heterogeneity within patient populations, therapeutic response rates often vary. Here we used the NCI60 panel to identify SNPs associated with paclitaxel sensitivity. Using the panel's GI50 response data available from Developmental Therapeutics Program, cell lines were categorized as either sensitive or resistant. PLINK software was used to perform a genome-wide association analysis of the cellular response to paclitaxel with the panel's SNP-genotype data on the Affymetrix 125 k SNP array. FastSNP software helped predict each SNP's potential impact on their gene product. mRNA expression differences between sensitive and resistant cell lines was examined using data from BioGPS. Using Haploview software, we investigated for haplotypes that were more strongly associated with the cellular response to paclitaxel. Ingenuity Pathway Analysis software helped us understand how our identified genes may alter the cellular response to paclitaxel.</p> <p>Results</p> <p>43 SNPs were found significantly associated (FDR < 0.005) with paclitaxel response, with 10 belonging to protein-coding genes (<it>CFTR</it>, <it>ROBO1</it>, <it>PTPRD</it>, <it>BTBD12</it>, <it>DCT</it>, <it>SNTG1</it>, <it>SGCD</it>, <it>LPHN2</it>, <it>GRIK1</it>, <it>ZNF607</it>). SNPs in <it>GRIK1</it>, <it>DCT</it>, <it>SGCD </it>and <it>CFTR </it>were predicted to be intronic enhancers, altering gene expression, while SNPs in <it>ZNF607 </it>and <it>BTBD12 </it>cause conservative missense mutations. mRNA expression analysis supported these findings as <it>GRIK1</it>, <it>DCT</it>, <it>SNTG1</it>, <it>SGCD </it>and <it>CFTR </it>showed significantly (p < 0.05) increased expression among sensitive cell lines. Haplotypes found in <it>GRIK1, SGCD, ROBO1, LPHN2</it>, and <it>PTPRD </it>were more strongly associated with response than their individual SNPs.</p> <p>Conclusions</p> <p>Our study has taken advantage of available genotypic data and its integration with drug response data obtained from the NCI60 panel. We identified 10 SNPs located within protein-coding genes that were not previously shown to be associated with paclitaxel response. As only five genes showed differential mRNA expression, the remainder would not have been detected solely based on expression data. The identified haplotypes highlight the role of utilizing SNP combinations within genomic loci of interest to improve the risk determination associated with drug response. These genetic variants represent promising biomarkers for predicting paclitaxel response and may play a significant role in the cellular response to paclitaxel.</p

Macrophage Activation and Differentiation Signals Regulate Schlafen-4 Gene Expression: Evidence for Schlafen-4 as a Modulator of Myelopoiesis

Background: The ten mouse and six human members of the Schlafen (Slfn) gene family all contain an AAA domain. Little is known of their function, but previous studies suggest roles in immune cell development. In this report, we assessed Slfn regulation and function in macrophages, which are key cellular regulators of innate immunity

Expression analysis of G Protein-Coupled Receptors in mouse macrophages-1

Of 91 murine cell types and tissues. Data points show normalised values and similar cell types are grouped according to bar colour; blue indicates primary macrophage cell types, purple indicates bone-related cell types, red indicates other immune cell types, green indicates stem cell populations, orange indicates whole tissue samples, yellow indicates neuronal and retinal cell types and pink indicates cell lines. Additional file gives details of the 91 cell types and tissues profiled.<p><b>Copyright information:</b></p><p>Taken from "Expression analysis of G Protein-Coupled Receptors in mouse macrophages"</p><p>http://www.immunome-research.com/content/4/1/5</p><p>Immunome Research 2008;4():5-5.</p><p>Published online 29 Apr 2008</p><p>PMCID:PMC2394514.</p><p></p

Expression analysis of G Protein-Coupled Receptors in mouse macrophages-2

over a timecourse of 0, 2, 6, and 24 h, and 0, 1 and 7 h, respectively. Data points show gene expression relative to untreated control for each cell population (0 h).<p><b>Copyright information:</b></p><p>Taken from "Expression analysis of G Protein-Coupled Receptors in mouse macrophages"</p><p>http://www.immunome-research.com/content/4/1/5</p><p>Immunome Research 2008;4():5-5.</p><p>Published online 29 Apr 2008</p><p>PMCID:PMC2394514.</p><p></p

Expression analysis of G Protein-Coupled Receptors in mouse macrophages-0

Of 91 murine cell types and tissues. Data points show normalised values and similar cell types are grouped according to bar colour; blue indicates primary macrophage cell types, purple indicates bone-related cell types, red indicates other immune cell types, green indicates stem cell populations, orange indicates whole tissue samples, yellow indicates neuronal and retinal cell types and pink indicates cell lines. Additional file gives details of the 91 cell types and tissues profiled.<p><b>Copyright information:</b></p><p>Taken from "Expression analysis of G Protein-Coupled Receptors in mouse macrophages"</p><p>http://www.immunome-research.com/content/4/1/5</p><p>Immunome Research 2008;4():5-5.</p><p>Published online 29 Apr 2008</p><p>PMCID:PMC2394514.</p><p></p

Slfn4 over-expression caused splenomegaly.

<p>(A) Macroscopic appearance of spleens from <i>Slfn4</i> over-expressing mice (right) and from MacBlue littermate controls (left). (B) Organ weights are expressed as percentage of body weight. Data are combined from four independent experiments and are displayed as mean + SEM.</p

Putative regulatory elements within the <i>Slfn4</i> promoter.

<p>The <i>Slfn4</i> proximal promoter is a TATA-containing promoter with putative binding sites for STAT1, IRF family members, PU.1 and AP1. The TSS, designated +1, is marked with an arrow.</p

Macrophage-specific expression of the UAS-<i>Slfn4</i>-V5 transgene.

<p>(A) Elements of the UAS-<i>Slfn4</i>-V5 transgene include six UAS, a kozak sequence, and the open reading frame of <i>Slfn4</i> followed by a V5-tag. Upon crossing of the UAS-<i>Slfn4</i>-V5 mouse with the MacBlue mouse, the offspring (MacBlue/UAS-<i>Slfn4</i>-V5 mice) contain the GAL4-expressing module, the GAL4-reporting module, and the UAS-<i>Slfn4</i>-V5 transgene. GAL4/VP16 protein binding to both the UAS induces the expression of ECFP and <i>Slfn4</i>-V5 specifically in cells of the myeloid lineage. (B and C) RNA from bone marrow (BM) or BMM from the offspring of four UAS-<i>Slfn4</i>-V5 founder lines (F1–F4) was extracted and cDNA was prepared. <i>Slfn4</i> mRNA levels relative to <i>hprt</i> were determined by quantitative real-time PCR. Data are combined from at least two independent experiments (mean + range) and are presented as expression relative to BM controls to enable normalization across different the transgenic lines (B), or as expression relative to <i>hprt</i> (no normalization across the transgenic lines) (C).</p