Molecular correlates and prognostic significance of SATB1 expression in colorectal cancer

Background: Special AT-rich sequence-binding protein 1 (SATB1) is a global gene regulator that has been reported to confer malignant behavior and associate with poor prognosis in several cancer forms. SATB1 expression has been demonstrated to correlate with unfavourable tumour characteristics in rectal cancer, but its association with clinical outcome in colorectal cancer (CRC) remains unclear. In this study, we examined the prognostic impact of SATB1 expression in CRC, and its association with important molecular characteristics; i.e. beta-catenin overexpression, microsatellite instability (MSI) screening status, and SATB2 expression. Methods: Immunohistochemical expression of SATB1 and beta-catenin was assessed in tissue microarrays with tumours from 529 incident CRC cases in the prospective population-based Malmo Diet and Cancer Study, previously analysed for SATB2 expression and MSI screening status. Spearman's Rho and Chi-Square tests were used to explore correlations between SATB1 expression, clinicopathological and investigative parameters. Kaplan Meier analysis and Cox proportional hazards modelling were used to explore the impact of SATB1 expression on cancer specific survival (CSS) and overall survival (OS). Results: SATB1 was expressed in 222 (42%) CRC cases and negative, or sparsely expressed, in adjacent colorectal mucosa (n = 16). SATB1 expression was significantly associated with microsatellite stable tumours (p < 0.001), beta-catenin overexpression (p < 0.001) and SATB2 expression (p < 0.001). While not prognostic in the full cohort, SATB1 expression was significantly associated with poor prognosis in SATB2 negative tumours (HR = 2.63; 95% CI 1.46-4.71; p(interaction) = 0.011 for CSS and HR = 2.31; 95% CI 1.32-4.04; p(interaction) = 0.015 for OS), remaining significant in multivariable analysis. Conclusions: The results of this study demonstrate that SATB1 expression in CRC is significantly associated with beta-catenin overexpression, microsatellite stability and SATB2 expression. Furthermore, SATB1 expression is a factor of poor prognosis in SATB2 negative tumours. Altogether, these data indicate an important role for SATB1 in colorectal carcinogenesis and suggest prognostically antagonistic effects of SATB1 and SATB2. The mechanistic basis for these observations warrants further study

Genome-scale metabolic network reconstruction of model animals as a platform for translational research

Genome-scale metabolic models (GEMs) are used extensively for analysis of mechanisms underlying human diseases and metabolic malfunctions. However, the lack of comprehensive and high-quality GEMs for model organisms restricts translational utilization of omics data accumulating from the use of various disease models. Here we present a unified platform of GEMs that covers five major model animals, including Mouse1 (Mus musculus), Rat1 (Rattus norvegicus), Zebrafish1 (Danio rerio), Fruitfly1 (Drosophila melanogaster), and Worm1 (Caenorhabditis elegans). These GEMs represent the most comprehensive coverage of the metabolic network by considering both orthology-based pathways and species-specific reactions. All GEMs can be interactively queried via the accompanying web portal Metabolic Atlas. Specifically, through integrative analysis of Mouse1 with RNA-sequencing data from brain tissues of transgenic mice we identified a coordinated up-regulation of lysosomal GM2 ganglioside and peptide degradation pathways which appears to be a signature metabolic alteration in Alzheimer's disease (AD) mouse models with a phenotype of amyloid precursor protein overexpression. This metabolic shift was further validated with proteomics data from transgenic mice and cerebrospinal fluid samples from human patients. The elevated lysosomal enzymes thus hold potential to be used as a biomarker for early diagnosis of AD. Taken together, we foresee that this evolving open-source platform will serve as an important resource to facilitate the development of systems medicines and translational biomedical applications

neXtProt: a knowledge platform for human proteins

neXtProt (http://www.nextprot.org/) is a new human protein-centric knowledge platform. Developed at the Swiss Institute of Bioinformatics (SIB), it aims to help researchers answer questions relevant to human proteins. To achieve this goal, neXtProt is built on a corpus containing both curated knowledge originating from the UniProtKB/Swiss-Prot knowledgebase and carefully selected and filtered high-throughput data pertinent to human proteins. This article presents an overview of the database and the data integration process. We also lay out the key future directions of neXtProt that we consider the necessary steps to make neXtProt the one-stop-shop for all research projects focusing on human proteins

Developmental trajectory of the healthy human gut microbiota during the first 5 years of life

The gut is inhabited by a densely populated ecosystem, the gut microbiota, that is established at birth. However, the succession by which different bacteria are incorporated into the gut microbiota is still relatively unknown. Here, we analyze the microbiota from 471 Swedish children followed from birth to 5 years of age, collecting samples after 4 and 12 months and at 3 and 5 years of age as well as from their mothers at birth using 16S rRNA gene profiling. We also compare their microbiota to an adult Swedish population. Genera follow 4 different colonization patterns during establishment where Methanobrevibacter and Christensenellaceae colonize late and do not reached adult levels at 5 years. These late colonizers correlate with increased alpha diversity in both children and adults. By following the children through age-specific community types, we observe that children have individual dynamics in the gut microbiota development trajectory

Control of intestinal stem cell function and proliferation by mitochondrial pyruvate metabolism.

Most differentiated cells convert glucose to pyruvate in the cytosol through glycolysis, followed by pyruvate oxidation in the mitochondria. These processes are linked by the mitochondrial pyruvate carrier (MPC), which is required for efficient mitochondrial pyruvate uptake. In contrast, proliferative cells, including many cancer and stem cells, perform glycolysis robustly but limit fractional mitochondrial pyruvate oxidation. We sought to understand the role this transition from glycolysis to pyruvate oxidation plays in stem cell maintenance and differentiation. Loss of the MPC in Lgr5-EGFP-positive stem cells, or treatment of intestinal organoids with an MPC inhibitor, increases proliferation and expands the stem cell compartment. Similarly, genetic deletion of the MPC in Drosophila intestinal stem cells also increases proliferation, whereas MPC overexpression suppresses stem cell proliferation. These data demonstrate that limiting mitochondrial pyruvate metabolism is necessary and sufficient to maintain the proliferation of intestinal stem cells

A critical evaluation of methods for the reconstruction of tissue-specific models

Under the framework of constraint based modeling, genome-scale metabolic models (GSMMs) have been used for several tasks, such as metabolic engineering and phenotype prediction. More recently, their application in health related research has spanned drug discovery, biomarker identification and host-pathogen interactions, targeting diseases such as cancer, Alzheimer, obesity or diabetes. In the last years, the development of novel techniques for genome sequencing and other high-throughput methods, together with advances in Bioinformatics, allowed the reconstruction of GSMMs for human cells. Considering the diversity of cell types and tissues present in the human body, it is imperative to develop tissue-specific metabolic models. Methods to automatically generate these models, based on generic human metabolic models and a plethora of omics data, have been proposed. However, their results have not yet been adequately and critically evaluated and compared. This work presents a survey of the most important tissue or cell type specific metabolic model reconstruction methods, which use literature, transcriptomics, proteomics and metabolomics data, together with a global template model. As a case study, we analyzed the consistency between several omics data sources and reconstructed distinct metabolic models of hepatocytes using different methods and data sources as inputs. The results show that omics data sources have a poor overlapping and, in some cases, are even contradictory. Additionally, the hepatocyte metabolic models generated are in many cases not able to perform metabolic functions known to be present in the liver tissue. We conclude that reliable methods for a priori omics data integration are required to support the reconstruction of complex models of human cells.Acknowledgments. S.C. thanks the FCT for the Ph.D. Grant SFRH/BD/ 80925/2011. The authors thank the FCT Strategic Project of UID/BIO/04469/2013 unit, the project RECI/BBB-EBI/0179/2012 (FCOMP-01-0124-FEDER-027462) and the project “BioInd - Biotechnology and Bioengineering for improved Industrial and Agro-Food processes”, REF. NORTE-07-0124-FEDER-000028 Co-funded by the Programa Operacional Regional do Norte (ON.2 - O Novo Norte), QREN, FEDER

Automated Solid-Phase Subcloning Based on Beads Brought into Proximity by Magnetic Force

In the fields of proteomics, metabolic engineering and synthetic biology there is a need for high-throughput and reliable cloning methods to facilitate construction of expression vectors and genetic pathways. Here, we describe a new approach for solid-phase cloning in which both the vector and the gene are immobilized to separate paramagnetic beads and brought into proximity by magnetic force. Ligation events were directly evaluated using fluorescent-based microscopy and flow cytometry. The highest ligation efficiencies were obtained when gene- and vector-coated beads were brought into close contact by application of a magnet during the ligation step. An automated procedure was developed using a laboratory workstation to transfer genes into various expression vectors and more than 95% correct clones were obtained in a number of various applications. The method presented here is suitable for efficient subcloning in an automated manner to rapidly generate a large number of gene constructs in various vectors intended for high throughput applications

Discovery of High-Affinity Protein Binding Ligands – Backwards

BACKGROUND: There is a pressing need for high-affinity protein binding ligands for all proteins in the human and other proteomes. Numerous groups are working to develop protein binding ligands but most approaches develop ligands using the same strategy in which a large library of structured ligands is screened against a protein target to identify a high-affinity ligand for the target. While this methodology generates high-affinity ligands for the target, it is generally an iterative process that can be difficult to adapt for the generation of ligands for large numbers of proteins. METHODOLOGY/PRINCIPAL FINDINGS: We have developed a class of peptide-based protein ligands, called synbodies, which allow this process to be run backwards--i.e. make a synbody and then screen it against a library of proteins to discover the target. By screening a synbody against an array of 8,000 human proteins, we can identify which protein in the library binds the synbody with high affinity. We used this method to develop a high-affinity synbody that specifically binds AKT1 with a K(d)<5 nM. It was found that the peptides that compose the synbody bind AKT1 with low micromolar affinity, implying that the affinity and specificity is a product of the bivalent interaction of the synbody with AKT1. We developed a synbody for another protein, ABL1 using the same method. CONCLUSIONS/SIGNIFICANCE: This method delivered a high-affinity ligand for a target protein in a single discovery step. This is in contrast to other techniques that require subsequent rounds of mutational improvement to yield nanomolar ligands. As this technique is easily scalable, we believe that it could be possible to develop ligands to all the proteins in any proteome using this approach

A New System for Profiling Drug-Induced Calcium Signal Perturbation in Human Embryonic Stem Cell–Derived Cardiomyocytes

The emergence of human stem cell–derived cardiomyocyte (hSCCM)–based assays in the cardiovascular (CV) drug discovery sphere requires the development of improved systems for interrogating the rich information that these cell models have the potential to yield. We developed a new analytical framework termed SALVO (synchronization, amplitude, length, and variability of oscillation) to profile the amplitude and temporal patterning of intra- and intercellular calcium signals in hSCCM. SALVO quantified drug-induced perturbations in the calcium signaling “fingerprint” in spontaneously contractile hSCCM. Multiparametric SALVO outputs were integrated into a single index of in vitro cytotoxicity that confirmed the rank order of perturbation as astemizole > thioridazine > cisapride > flecainide > valdecoxib > sotalol > nadolol ≈ control. This rank order of drug-induced Ca2+ signal disruption is in close agreement with the known arrhythmogenic liabilities of these compounds in humans. Validation of the system using a second set of compounds and hierarchical cluster analysis demonstrated the utility of SALVO to discriminate drugs based on their mechanisms of action. We discuss the utility of this new mechanistically agnostic system for the evaluation of in vitro drug cytotoxicity in hSCCM syncytia and the potential placement of SALVO in the early stage drug screening framework

Fifteen new risk loci for coronary artery disease highlight arterial-wall-specific mechanisms

Coronary artery disease (CAD) is a leading cause of morbidity and mortality worldwide. Although 58 genomic regions have been associated with CAD thus far, most of the heritability is unexplained, indicating that additional susceptibility loci await identification. An efficient discovery strategy may be larger-scale evaluation of promising associations suggested by genome-wide association studies (GWAS). Hence, we genotyped 56,309 participants using a targeted gene array derived from earlier GWAS results and performed meta-analysis of results with 194,427 participants previously genotyped, totaling 88,192 CAD cases and 162,544 controls. We identified 25 new SNP-CAD associations (P &lt; 5 × 10(-8), in fixed-effects meta-analysis) from 15 genomic regions, including SNPs in or near genes involved in cellular adhesion, leukocyte migration and atherosclerosis (PECAM1, rs1867624), coagulation and inflammation (PROCR, rs867186 (p.Ser219Gly)) and vascular smooth muscle cell differentiation (LMOD1, rs2820315). Correlation of these regions with cell-type-specific gene expression and plasma protein levels sheds light on potential disease mechanisms