Estimates of the number of species of bacteria per gram of soil vary between 2000 and 8.3 million (Gans et al., 2005; Schloss and Handelsman, 2006). The highest estimate suggests that the number may be so large as to be impractical to test by amplification and sequencing of the highly conserved 16S rRNA gene from soil DNA (Gans et al., 2005). Here we present the use of high throughput DNA pyrosequencing and statistical inference to assess bacterial diversity in four soils across a large transect of the western hemisphere. The number of bacterial 16S rRNA sequences obtained from each site varied from 26 140 to 53 533. The most abundant bacterial groups in all four soils were the Bacteroidetes, Betaproteobacteria and Alphaproteobacteria. Using three estimators of diversity, the maximum number of unique sequences (operational taxonomic units roughly corresponding to the species level) never exceeded 52 000 in these soils at the lowest level of dissimilarity. Furthermore, the bacterial diversity of the forest soil was phylum rich compared to the agricultural soils, which are species rich but phylum poor. The forest site also showed far less diversity of the Archaea with only 0.009% of all sequences from that site being from this group as opposed to 4%–12% of the sequences from the three agricultural sites. This work is the most comprehensive examination to date of bacterial diversity in soil and suggests that agricultural management of soil may significantly influence the diversity of bacteria and archaea.

MicroRNAs (miRNAs) are small noncoding RNAs that posttranscriptionally regulate gene expression by binding to 3′-untranslated regions (3′UTRs) of target mRNAs. Kaposi's sarcoma-associated herpesvirus (KSHV), a virus linked to malignancies including primary effusion lymphoma (PEL), encodes 12 miRNA genes, but only a few regulatory targets are known. We found that KSHV-miR-K12-11 shares 100% seed sequence homology with hsa-miR-155, an miRNA frequently found to be up-regulated in lymphomas and critically important for B-cell development. Based on this seed sequence homology, we hypothesized that both miRNAs regulate a common set of target genes and, as a result, could have similar biological activities. Examination of five PEL lines showed that PELs do not express miR-155 but do express high levels of miR-K12-11. Bioinformatic tools predicted the transcriptional repressor BACH-1 to be targeted by both miRNAs, and ectopic expression of either miR-155 or miR-K12-11 inhibited a BACH-1 3′UTR-containing reporter. Furthermore, BACH-1 protein levels are low in cells expressing either miRNA. Gene expression profiling of miRNA-expressing stable cell lines revealed 66 genes that were commonly down-regulated. For select genes, miRNA targeting was confirmed by reporter assays. Thus, based on our in silico predictions, reporter assays, and expression profiling data, miR-K12-11 and miR-155 regulate a common set of cellular targets. Given the role of miR-155 during B-cell maturation, we speculate that miR-K12-11 may contribute to the distinct developmental phenotype of PEL cells, which are blocked in a late stage of B-cell development. Together, these findings indicate that KSHV miR-K12-11 is an ortholog of miR-155.

MicroRNAs (miRNAs) are 19 to 23 nucleotide–long RNAs that post-transcriptionally regulate gene expression. Human cells express several hundred miRNAs which regulate important biological pathways such as development, proliferation, and apoptosis. Recently, 12 miRNA genes have been identified within the genome of Kaposi sarcoma–associated herpesvirus; however, their functions are still unknown. To identify host cellular genes that may be targeted by these novel viral regulators, we performed gene expression profiling in cells stably expressing KSHV-encoded miRNAs. Data analysis revealed a set of 81 genes whose expression was significantly changed in the presence of miRNAs. While the majority of changes were below 2-fold, eight genes were down-regulated between 4- and 20-fold. We confirmed miRNA-dependent regulation for three of these genes and found that protein levels of thrombospondin 1 (THBS1) were decreased >10-fold. THBS1 has previously been reported to be down-regulated in Kaposi sarcoma lesions and has known activity as a strong tumor suppressor and anti-angiogenic factor, exerting its anti-angiogenic effect in part by activating the latent form of TGF-β. We show that reduced THBS1 expression in the presence of viral miRNAs translates into decreased TGF-β activity. These data suggest that KSHV-encoded miRNAs may contribute directly to pathogenesis by down-regulation of THBS1, a major regulator of cell adhesion, migration, and angiogenesis. Kaposi sarcoma–associated herpesvirus (KSHV) is a gamma-herpesvirus associated with Kaposi sarcoma, primary effusion lymphoma, and a subset of muticentric Castleman disease. Recently, it was found that KSHV encodes 12 microRNAs (miRNAs) within its latency-associated region. miRNAs are small ∼22 nucleotide-long single-stranded RNA molecules that act to inhibit gene expression by binding to target messenger RNAs (mRNAs). Because miRNAs bind to these targets with limited base pairing, it has been difficult to find targets. The goal of our study was to identify cellular mRNAs targeted by KSHV-encoded miRNAs. Microarray analysis of cells expressing the KSHV miRNAs revealed a set of 81 genes that were changed. Several genes are regulators of important functions such as blood vessel growth, cell proliferation, and cell death. One target, thrombospondin 1, is a potent inhibitor of blood vessel growth and is known to be down-regulated in Kaposi sarcoma tumors. Thrombospondin 1, which is targeted by multiple miRNAs, also showed reduced protein levels in our study. To our knowledge, our data describe the first targets for tumorvirus-encoded miRNAs and suggest that these novel regulators may have roles in pathogenesis.

Recent studies suggest that NOTCH signaling can promote epithelial-mesenchymal transitions and augment signaling through AKT, an important growth and survival pathway in epithelial cells and prostate cancer in particular. Here we show that JAGGED1, a NOTCH receptor ligand, is significantly more highly expressed in metastatic prostate cancer as compared with localized prostate cancer or benign prostatic tissues, based on immunohistochemical analysis of JAGGED1 expression in human tumor samples from 154 men. Furthermore, high JAGGED1 expression in a subset of clinically localized tumors was significantly associated with recurrence, independent of other clinical parameters. These findings support a model in which dysregulation of JAGGED1 protein levels plays a role in prostate cancer progression and metastasis and suggest that JAGGED1 may be a useful marker in distinguishing indolent and aggressive prostate cancers.

Background: Cis-regulatory modules are combinations of regulatory elements occurring in close proximity to each other that control the spatial and temporal expression of genes. The ability to identify them in a genome-wide manner depends on the availability of accurate models and of search methods able to detect putative regulatory elements with enhanced sensitivity and specificity. Results: We describe the implementation of a search method for putative transcription factor binding sites (TFBSs) based on hidden Markov models built from alignments of known sites. We built 1,079 models of TFBSs using experimentally determined sequence alignments of sites provided by the TRANSFAC and JASPAR databases and used them to scan sequences of the human, mouse, fly, worm and yeast genomes. In several cases tested the method identified correctly experimentally characterized sites, with better specificity and sensitivity than other similar computational methods. Moreover, a large-scale comparison using synthetic data showed that in the majority of cases our method performed significantly better than a nucleotide weight matrix-based method. Conclusion: The search engine, available at http://mapper.chip.org, allows the identification, visualization and selection of putative TFBSs occurring in the promoter or other regions of a gene from the human, mouse, fly, worm and yeast genomes. In addition it allows the user to upload a sequence to query and to build a model by supplying a multiple sequence alignment of binding sites for a transcription factor of interest. Due to its extensive database of models, powerful search engine and flexible interface, MAPPER represents an effective resource for the large-scale computational analysis of transcriptional regulation.