The InParanoid project gathers proteomes of completely sequenced eukaryotic species plus Escherichia coli and calculates pairwise ortholog relationships among them. The new release 7.0 of the database has grown by an order of magnitude over the previous version and now includes 100 species and their collective 1.3 million proteins organized into 42.7 million pairwise ortholog groups. The InParanoid algorithm itself has been revised and is now both more specific and sensitive. Based on results from our recent benchmarking of low-complexity filters in homology assignment, a two-pass BLAST approach was developed that makes use of high-precision compositional score matrix adjustment, but avoids the alignment truncation that sometimes follows. We have also updated the InParanoid web site (http://InParanoid.sbc.su.se). Several features have been added, the response times have been improved and the site now sports a new, clearer look. As the number of ortholog databases has grown, it has become difficult to compare among these resources due to a lack of standardized source data and incompatible representations of ortholog relationships. To facilitate data exchange and comparisons among ortholog databases, we have developed and are making available two XML schemas: SeqXML for the input sequences and OrthoXML for the output ortholog clusters.

Highlights d Robust method for proteome-wide subcellular localization analysis d Resource for subcellular location of 12,418 proteins in multiple cell lines d Analysis of protein domain-and variant-associated localization d Global analysis of protein relocalization driven by EGFR inhibition

In the growing field of genomics, multiple alignment programs are confronted with ever increasing amounts of data. To address this growing issue we have dramatically improved the running time and memory requirement of Kalign, while maintaining its high alignment accuracy. Kalign version 2 also supports nucleotide alignment, and a newly introduced extension allows for external sequence annotation to be included into the alignment procedure. We demonstrate that Kalign2 is exceptionally fast and memory-efficient, permitting accurate alignment of very large numbers of sequences. The accuracy of Kalign2 compares well to the best methods in the case of protein alignments while its accuracy on nucleotide alignments is generally superior. In addition, we demonstrate the potential of using known or predicted sequence annotation to improve the alignment accuracy. Kalign2 is freely available for download from the Kalign web site (http://msa.sbc.su.se/).

A role for Hedgehog (Hh) signalling in the development of colorectal cancer (CRC) has been proposed. In CRC and other solid tumours, Hh ligands are upregulated; however, a specific Hh antagonist provided no benefit in a clinical trial. Here we use Hh reporter mice to show that downstream Hh activity is unexpectedly diminished in a mouse model of colitis-associated colon cancer, and that downstream Hh signalling is restricted to the stroma. Functionally, stroma-specific Hh activation in mice markedly reduces the tumour load and blocks progression of advanced neoplasms, partly via the modulation of BMP signalling and restriction of the colonic stem cell signature. By contrast, attenuated Hh signalling accelerates colonic tumourigenesis. In human CRC, downstream Hh activity is similarly reduced and canonical Hh signalling remains predominantly paracrine. Our results suggest that diminished downstream Hh signalling enhances CRC development, and that stromal Hh activation can act as a colonic tumour suppressor.

Cancer-associated fibroblasts (CAF) stimulate tumor growth and metastasis. Signals supporting CAF function are thus emerging as candidate therapeutic targets in the tumor microenvironment. The chemokine CXCL14 is a potent inducer of CAF protumorigenic functions. This study is aimed at learning how the protumoral functions of CXCL14-expressing CAF are maintained. We found that the nitric oxide synthase NOS1 is upregulated in CXCL14-expressing CAF and in fibroblasts stimulated with CXCL14. Induction of Nos1 was associated with oxidative stress and occurred together with activation of NRF2 and HIF1a signaling in CXCL14-expressing CAF. Genetic or pharmacologic inhibition of NOS1 reduced the growth of CXCL14-expressing fibroblasts along with their ability to promote tumor formation following coinjection with prostate or breast cancer cells. Tumor analysis revealed reduced macrophage infiltration, with NOS1 downregulation in CXCL14-expressing CAF and lymphangiogenesis as a novel component of CXCL14-promoted tumor growth. Collectively, our findings defined key components of a signaling network that maintains the protumoral functions of CXCL14-stimulated CAF, and they identified NOS1 as intervention target for CAF-directed cancer therapy. Cancer Res; 74(11); 2999-3010. Ó2014 AACR.

FunCoup (http://FunCoup.sbc.su.se) is a database that maintains and visualizes global gene/protein networks of functional coupling that have been constructed by Bayesian integration of diverse high-throughput data. FunCoup achieves high coverage by orthology-based integration of data sources from different model organisms and from different platforms. We here present release 2.0 in which the data sources have been updated and the methodology has been refined. It contains a new data type Genetic Interaction, and three new species: chicken, dog and zebra fish. As FunCoup extensively transfers functional coupling information between species, the new input datasets have considerably improved both coverage and quality of the networks. The number of high-confidence network links has increased dramatically. For instance, the human network has more than eight times as many links above confidence 0.5 as the previous release. FunCoup provides facilities for analysing the conservation of subnetworks in multiple species. We here explain how to do comparative interactomics on the FunCoup website.

Purpose: Fibroblasts expressing the orphan chemokine CXCL14 have been previously shown to associate with poor breast cancer prognosis and promote cancer growth. This study explores the mechanism underlying the poor survival associations of stromal CXCL14. Experimental Design: Tumor cell epithelial-to-mesenchymal transition (EMT), invasion, and metastasis were studied in in vitro and in vivo models together with fibroblasts overexpressing CXCL14. An approach for CXCL14 receptor identification included loss-of-function studies followed by molecular and functional endpoints. The clinical relevance was further explored in publicly available gene expression datasets. Results: CXCL14 fibroblasts stimulated breast cancer EMT, migration, and invasion in breast cancer cells and in a xeno-graft model. Furthermore, tumor cells primed by CXCL14 fibroblasts displayed enhanced lung colonization after tailvein injection. By loss-of function experiments, the atypical G-protein-coupled receptor ACKR2 was identified to mediate CXCL14-stimulated responses. Downregulation of ACKR2, or CXCL14-induced NOS1, attenuated the pro-EMT and migratory capacity. CXCL14/ACKR2 expression correlated with EMT and survival in gene expression datasets. Conclusions: Collectively, the findings imply an autocrine fibroblast CXCL14/ACKR2 pathway as a clinically relevant stimulator of EMT, tumor cell invasion, and metastasis. The study also identifies ACKR2 as a novel mediator for CXCL14 function and thereby defines a pathway with drug target potential. See related commentary by Zhang et al., p. 3476

MotivationAnalyzing groups of functionally coupled genes or proteins in the context of global interaction networks has become an important aspect of bioinformatic investigations. Assessing the statistical significance of crosstalk enrichment between or within groups of genes can be a valuable tool for functional annotation of experimental gene sets.ResultsHere we present CrossTalkZ, a statistical method and software to assess the significance of crosstalk enrichment between pairs of gene or protein groups in large biological networks. We demonstrate that the standard z-score is generally an appropriate and unbiased statistic. We further evaluate the ability of four different methods to reliably recover crosstalk within known biological pathways. We conclude that the methods preserving the second-order topological network properties perform best. Finally, we show how CrossTalkZ can be used to annotate experimental gene sets using known pathway annotations and that its performance at this task is superior to gene enrichment analysis (GEA).Availability and ImplementationCrossTalkZ (available at http://sonnhammer.sbc.su.se/download/software/CrossTalkZ/) is implemented in C++, easy to use, fast, accepts various input file formats, and produces a number of statistics. These include z-score, p-value, false discovery rate, and a test of normality for the null distributions.