Identifying biotic determinants of historic American eel (Anguilla rostrata) distributions

Traditionally, ecologists studying large scale patterns in species distributions emphasize abiotic variables over biotic interactions. Noting that both abiotic & biotic variables likely determine distributions of all organisms, many ecologists now aim for a more comprehensive view of species distributions, inclusive of both abiotic and biotic components (Soberón 2007)

UniRef clusters: a comprehensive and scalable alternative for improving sequence similarity searches

Motivation: UniRef databases provide full-scale clustering of UniProtKB sequences and are utilized for a broad range of applications, particularly similarity-based functional annotation. Non-redundancy and intra-cluster homogeneity in UniRef were recently improved by adding a sequence length overlap threshold. Our hypothesis is that these improvements would enhance the speed and sensitivity of similarity searches and improve the consistency of annotation within clusters. Results: Intra-cluster molecular function consistency was examined by analysis of Gene Ontology terms. Results show that UniRef clusters bring together proteins of identical molecular function in more than 97% of the clusters, implying that clusters are useful for annotation and can also be used to detect annotation inconsistencies. To examine coverage in similarity results, BLASTP searches against UniRef50 followed by expansion of the hit lists with cluster members demonstrated advantages compared with searches against UniProtKB sequences; the searches are concise (∼7 times shorter hit list before expansion), faster (∼6 times) and more sensitive in detection of remote similarities (>96% recall at e-value <0.0001). Our results support the use of UniRef clusters as a comprehensive and scalable alternative to native sequence databases for similarity searches and reinforces its reliability for use in functional annotation. Availability and implementation: Web access and file download from UniProt website at http://www.uniprot.org/uniref and ftp://ftp.uniprot.org/pub/databases/uniprot/uniref. BLAST searches against UniRef are available at http://www.uniprot.org/blast/ Contact: [email protected]

Obesity Management: Clinical Review and Update of the Pharmacologic Treatment Options

The toolbox of medications available for medical weight management is more robust than ever and includes a wide variety of mechanisms of actions and options for patients

SGLT2 Inhibitors for Type 2 Diabetes Mellitus Treatment

SGLT2 inhibitors are plausible second-line drugs that provide powerful additional A1c-lowering effects while inducing weight loss without hypoglycemia

Infrastructure for the life sciences: design and implementation of the UniProt website

<p>Abstract</p> <p>Background</p> <p>The UniProt consortium was formed in 2002 by groups from the Swiss Institute of Bioinformatics (SIB), the European Bioinformatics Institute (EBI) and the Protein Information Resource (PIR) at Georgetown University, and soon afterwards the website <url>http://www.uniprot.org</url> was set up as a central entry point to UniProt resources. Requests to this address were redirected to one of the three organisations' websites. While these sites shared a set of static pages with general information about UniProt, their pages for searching and viewing data were different. To provide users with a consistent view and to cut the cost of maintaining three separate sites, the consortium decided to develop a common website for UniProt. Following several years of intense development and a year of public beta testing, the <url>http://www.uniprot.org</url> domain was switched to the newly developed site described in this paper in July 2008.</p> <p>Description</p> <p>The UniProt consortium is the main provider of protein sequence and annotation data for much of the life sciences community. The <url>http://www.uniprot.org</url> website is the primary access point to this data and to documentation and basic tools for the data. These tools include full text and field-based text search, similarity search, multiple sequence alignment, batch retrieval and database identifier mapping. This paper discusses the design and implementation of the new website, which was released in July 2008, and shows how it improves data access for users with different levels of experience, as well as to machines for programmatic access.</p> <p><url>http://www.uniprot.org/</url> is open for both academic and commercial use. The site was built with open source tools and libraries. Feedback is very welcome and should be sent to <email>[email protected]</email>.</p> <p>Conclusion</p> <p>The new UniProt website makes accessing and understanding UniProt easier than ever. The two main lessons learned are that getting the basics right for such a data provider website has huge benefits, but is not trivial and easy to underestimate, and that there is no substitute for using empirical data throughout the development process to decide on what is and what is not working for your users.</p

The tumor suppressor TERE1 (UBIAD1) prenyltransferase regulates the elevated cholesterol phenotype in castration resistant prostate cancer by controlling a program of ligand dependent SXR target genes.

Castrate-Resistant Prostate Cancer (CRPC) is characterized by persistent androgen receptor-driven tumor growth in the apparent absence of systemic androgens. Current evidence suggests that CRPC cells can produce their own androgens from endogenous sterol precursors that act in an intracrine manner to stimulate tumor growth. The mechanisms by which CRPC cells become steroidogenic during tumor progression are not well defined. Herein we describe a novel link between the elevated cholesterol phenotype of CRPC and the TERE1 tumor suppressor protein, a prenyltransferase that synthesizes vitamin K-2, which is a potent endogenous ligand for the SXR nuclear hormone receptor. We show that 50% of primary and metastatic prostate cancer specimens exhibit a loss of TERE1 expression and we establish a correlation between TERE1 expression and cholesterol in the LnCaP-C81 steroidogenic cell model of the CRPC. LnCaP-C81 cells also lack TERE1 protein, and show elevated cholesterol synthetic rates, higher steady state levels of cholesterol, and increased expression of enzymes in the de novo cholesterol biosynthetic pathways than the non-steroidogenic prostate cancer cells. C81 cells also show decreased expression of the SXR nuclear hormone receptor and a panel of directly regulated SXR target genes that govern cholesterol efflux and steroid catabolism. Thus, a combination of increased synthesis, along with decreased efflux and catabolism likely underlies the CRPC phenotype: SXR might coordinately regulate this phenotype. Moreover, TERE1 controls synthesis of vitamin K-2, which is a potent endogenous ligand for SXR activation, strongly suggesting a link between TERE1 levels, K-2 synthesis and SXR target gene regulation. We demonstrate that following ectopic TERE1 expression or induction of endogenous TERE1, the elevated cholesterol levels in C81 cells are reduced. Moreover, reconstitution of TERE1 expression in C81 cells reactivates SXR and switches on a suite of SXR target genes that coordinately promote both cholesterol efflux and androgen catabolism. Thus, loss of TERE1 during tumor progression reduces K-2 levels resulting in reduced transcription of SXR target genes. We propose that TERE1 controls the CPRC phenotype by regulating the endogenous levels of Vitamin K-2 and hence the transcriptional control of a suite of steroidogenic genes via the SXR receptor. These data implicate the TERE1 protein as a previously unrecognized link affecting cholesterol and androgen accumulation that could govern acquisition of the CRPC phenotype

Suggestive Linkage Detected for Blood Pressure Related Traits on 2q and 22q in the Population on the Samoan Islands

Background High blood pressure or hypertension is a major risk factor involved in the development of cardiovascular diseases. We conducted genome-wide variance component linkage analyses to search for loci influencing five blood pressure related traits including the quantitative traits systolic blood pressure (SBP), diastolic blood pressure (DBP) and pulse pressure (PP), the dichotomous trait hypertension (HT) and the bivariate quantitative trait SBP-DBP in families residing in American Samoa and Samoa, as well as in the combined sample from the two polities. We adjusted the traits for a number of environmental covariates such as smoking, alcohol consumption, physical activity and material life style. Results We found suggestive univariate linkage for SBP on chromosome 2q35-q37 (LOD 2.4) and for PP on chromosome 22q13 (LOD 2.2), two chromosomal regions that recently have been associated with SBP and PP, respectively. Conclusion We have detected additional evidence for a recently reported locus associated with SBP on chromosome 2q and a susceptibility locus for PP on chromosome 22q. However, differences observed between the results from our three partly overlapping genetically homogenous study samples from the Samoan islands suggest that additional studies should be performed in order to verify these results

PcG Proteins, DNA Methylation, and Gene Repression by Chromatin Looping

Many DNA hypermethylated and epigenetically silenced genes in adult cancers are Polycomb group (PcG) marked in embryonic stem (ES) cells. We show that a large region upstream (∼30 kb) of and extending ∼60 kb around one such gene, GATA-4, is organized—in Tera-2 undifferentiated embryonic carcinoma (EC) cells—in a topologically complex multi-loop conformation that is formed by multiple internal long-range contact regions near areas enriched for EZH2, other PcG proteins, and the signature PcG histone mark, H3K27me3. Small interfering RNA (siRNA)–mediated depletion of EZH2 in undifferentiated Tera-2 cells leads to a significant reduction in the frequency of long-range associations at the GATA-4 locus, seemingly dependent on affecting the H3K27me3 enrichments around those chromatin regions, accompanied by a modest increase in GATA-4 transcription. The chromatin loops completely dissolve, accompanied by loss of PcG proteins and H3K27me3 marks, when Tera-2 cells receive differentiation signals which induce a ∼60-fold increase in GATA-4 expression. In colon cancer cells, however, the frequency of the long-range interactions are increased in a setting where GATA-4 has no basal transcription and the loops encompass multiple, abnormally DNA hypermethylated CpG islands, and the methyl-cytosine binding protein MBD2 is localized to these CpG islands, including ones near the gene promoter. Removing DNA methylation through genetic disruption of DNA methyltransferases (DKO cells) leads to loss of MBD2 occupancy and to a decrease in the frequency of long-range contacts, such that these now more resemble those in undifferentiated Tera-2 cells. Our findings reveal unexpected similarities in higher order chromatin conformation between stem/precursor cells and adult cancers. We also provide novel insight that PcG-occupied and H3K27me3-enriched regions can form chromatin loops and physically interact in cis around a single gene in mammalian cells. The loops associate with a poised, low transcription state in EC cells and, with the addition of DNA methylation, completely repressed transcription in adult cancer cells

Stratified randomization controls better for batch effects in 450K methylation analysis: a cautionary tale

Background: Batch effects in DNA methylation microarray experiments can lead to spurious results if not properly handled during the plating of samples. Methods: Two pilot studies examining the association of DNA methylation patterns across the genome with obesity in Samoan men were investigated for chip- and row-specific batch effects. For each study, the DNA of 46 obese men and 46 lean men were assayed using Illumina's Infinium HumanMethylation450 BeadChip. In the first study (Sample One), samples from obese and lean subjects were examined on separate chips. In the second study (Sample Two), the samples were balanced on the chips by lean/obese status, age group, and census region. We used methylumi, watermelon, and limma R packages, as well as ComBat, to analyze the data. Principal component analysis and linear regression were respectively employed to identify the top principal components and to test for their association with the batches and lean/obese status. To identify differentially methylated positions (DMPs) between obese and lean males at each locus, we used a moderated t-test.Results: Chip effects were effectively removed from Sample Two but not Sample One. In addition, dramatic differences were observed between the two sets of DMP results. After removing'' batch effects with ComBat, Sample One had 94,191 probes differentially methylated at a q-value threshold of 0.05 while Sample Two had zero differentially methylated probes. The disparate results from Sample One and Sample Two likely arise due to the confounding of lean/obese status with chip and row batch effects.Conclusion: Even the best possible statistical adjustments for batch effects may not completely remove them. Proper study design is vital for guarding against spurious findings due to such effects