Search

Background Rheumatoid Arthritis (RA) is a progressive autoimmune disease characterised by synovial hyperplasia resulting in destruction of adjacent articular cartilage and bone. While new therapeutic strategies over the last 15 years represent an advance in treatment, a significant proportion of patients do not respond, have sub-optimal responses or suffer adverse effects. Therefore identification of baseline markers that can predict clinical response along with new therapies will allow for better treatment stratification for RA patients. Materials and methods Peripheral blood mononuclear cells were obtained from patients with RA at baseline. Patients were followed clinically and categorised into responders (n=10) vs non responders (n=9) based on clinical disease outcome. mRNA was isolated from PBMC and RNAseq performed. Ingenuity® Pathway Analysis (IPA) software was used to examine gene enrichment within differentially expressed genes. Interaction network analysis and identification of key hub nodes was performed using InnateDB and Cytoscape. Results Initial analysis identified differential expression of 155 genes between responders vs non responders. IPA pathway and Gene Ontology analysis demonstrated these were associated with several relevant pathways eg, antigen presentation, with top GO functions related to autoimmune disease, specifically RA. Differential gene expression was associated with leukocyte trafficking and alterations in extracellular matrix components, which was further confirmed by additional IPA network analysis of the RA dataset, identifying a key Inflammatory response/cell movement network. Potential upstream target regulators of these pathways incude TREM-1, IL-17A and HIF1A, which are known to be significantly involved in regulating synovial proliferation in the RA joint. Finally an interaction network analysis identifed CXCL5, ADAMTSL4, CSTB, PPBP, CBLB, ELANE, PTGDS, CXCL2, SP1, CXCL1 as key hub genes preferentially connected to the 155 differentially expressed genes. Conclusion These data demonstrate differential gene expression and gene networks in responders vs non responder patients, specifically associated with leukocyte trafficking and synovial extravasation. However, given the small sample size, these results need to be validated in independent cohorts. Understanding differences in responder vs nonresponder patients at baseline represents an opportunity to both better understand the mechanisms of current drugs and investigate new therapeutic targets in those who don’t respond to current treatment.

Lactobacillus salivarius subsp. salivarius strain UCC118 is a bacteriocin-producing strain with probiotic characteristics. The 2.13-Mb genome was shown by sequencing to comprise a 1.83 Mb chromosome, a 242-kb megaplasmid (pMP118), and two smaller plasmids. Megaplasmids previously have not been characterized in lactic acid bacteria or intestinal lactobacilli. Annotation of the genome sequence indicated an intermediate level of auxotrophy compared with other sequenced lactobacilli. No single-copy essential genes were located on the megaplasmid. However, contingency amino acid metabolism genes and carbohydrate utilization genes, including two genes for completion of the pentose phosphate pathway, were megaplasmid encoded. The megaplasmid also harbored genes for the Abp118 bacteriocin, a bile salt hydrolase, a presumptive conjugation locus, and other genes potentially relevant for probiotic properties. Two subspecies of L. salivarius are recognized, salivarius and salicinius , and we detected megaplasmids in both subspecies by pulsed-field gel electrophoresis of sizes ranging from 100 kb to 380 kb. The discovery of megaplasmids of widely varying size in L. salivarius suggests a possible mechanism for genome expansion or contraction to adapt to different environments.

The number of possible gap placements in even small sequences is vast and processing requirements grow expotentially with the number of sequences. Handling genome data needs raw computing power and clear thought.

Inflammation plays a key role in the development of Colorectal Cancer (CRC), but the underlying regulatory mechanisms are yet to be fully elucidated. The K-homology splicing regulatory protein (KHSRP) is a multifunctional RNA-binding protein which regulates translation of transcripts containing ARE sequences in their 3’-UTR, affecting RNA fate at different levels. KHSRP has been implicated in different functions associated with cancer cell biology, such as inflammation and cell-fate determination. Importantly, KHSRP regulates expression of pro-tumorigenic and anti-inflammatory cytokines, potentially impacting on the tumor microenvironment. We have previously shown that knockdown of KHSRP expression in CRC cell lines regulates cell proliferation and clonogenic survival. KHSRP is also required for the secretion of the pro-angiogenic cytokines, IL-8 and VEGF, impacting on endothelial tube formation. To understand the global impact of KHSRP in regulation of CRC cell function we used Affimetrix Human Transcriptome array to investigate gene expression upon KHSRP silencing in SW480 CRC cells. A total of 210 genes were differentially expressed, 155 of which were up-regulated (100 coding and 55 non-coding genes) and 55 were down-regulated (34 coding and 21 non-coding genes). Among these were genes involved in RNA biology, inflammation, immunity, cell signaling and tumor-stroma interaction, shedding light on the potential mechanisms of action of KHSRP in epithelial cells. Representative targets have been selected for validation and further mechanistic studies. These data builds upon our previous findings suggesting a role for KHSRP in creating a tumor-permissive microenvironment in CRC. Citation Format: Francesco Caiazza, Robert Power, Kate Killick, Des Higgins, Walter Kolch, Laura Breen, Sinead Aherne, Sudipto Das, Darran O’Connor, Miriam Tosetto, Blathnaid Nolan, David Fennelly, Kieran Sheahan, Glen Doherty, Elizabeth J. Ryan. The tumor-permissive role of KHSRP in colorectal cancer: Mechanistic insights from a gene expression study. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 2878.

Development of the human gut microbiota commences at birth, with bifidobacteria being among the first colonizers of the sterile newborn gastrointestinal tract. To date, the genetic basis of Bifidobacterium colonization and persistence remains poorly understood. Transcriptome analysis of the Bifidobacterium breve UCC2003 2.42-Mb genome in a murine colonization model revealed differential expression of a type IVb tight adherence (Tad) pilus-encoding gene cluster designated “ tad 2003 .” Mutational analysis demonstrated that the tad 2003 gene cluster is essential for efficient in vivo murine gut colonization, and immunogold transmission electron microscopy confirmed the presence of Tad pili at the poles of B. breve UCC2003 cells. Conservation of the Tad pilus-encoding locus among other B. breve strains and among sequenced Bifidobacterium genomes supports the notion of a ubiquitous pili-mediated host colonization and persistence mechanism for bifidobacteria.

Multiple sequence alignment is a central problem in Bioinformatics. A known integer programming approach is to apply branch-and-cut to exponentially large graph-theoretic models. This paper describes a new integer program formulation that generates models small enough to be passed to generic solvers. The formulation is a hybrid relating the sparse alignment graph with a compact encoding of the alignment matrix via channelling constraints. Alignments obtained with a SAT-based local search algorithm are competitive with those of state-of-the-art algorithms, though execution times are much longer.

The Clustal programs are widely used for carrying out automatic multiple alignment of nucleotide or amino acid sequences. The most familiar version is ClustalW, which uses a simple text menu system that is portable to more or less all computer systems. ClustalX features a graphical user interface and some powerful graphical utilities for aiding the interpretation of alignments and is the preferred version for interactive usage. Users may run Clustal remotely from several sites using the Web or the programs may be downloaded and run locally on PCs, Macintosh, or Unix computers. The protocols in this unit discuss how to use ClustalX and ClustalW to construct an alignment, and create profile alignments by merging existing alignments.

Publisher Summary This chapter discusses various aspects of multiple sequence alignment. Dynamic programming can be generalized to more than two sequences where one finds the multiple alignments with the best score according to the scoring scheme. Gaps are scored according to their length and the number of sequences that they occur in and the method will find a multiple alignment with the best possible score. Clustal W is perhaps the most widely used program for carrying out automatic multiple alignments. It uses a simple text menu system or command-line interface that is reasonably self-explanatory and simple to use. It allows one to carry out fully automatic and rapid alignments of dozens of sequences of moderate length using the progressive alignment method. The main menu leads to submenus for calculating phylogenetic trees from multiple alignments and for the alignment of existing alignments. The trees cannot be displayed by Clustal W but can be viewed using dedicated tree-viewing programs. The alignments that are produced by Clustal W and X are sent to simple text files. These show the sequences aligned in blocks and use symbols to indicate residues that are exactly conserved in columns or which show some degree of biochemical conservation in the columns. It is found that dedicated alignment editors can move large gaps quickly and can be persuaded to color the columns of residues depending on the degree of conservation and/or residue type.

Resistance to endocrine-directed therapy represents a significant problem in the management of breast cancer. Here we describe an integrated bioinformatics and translational pathology approach to identifying novel microRNAs (miRNA) controlling this phenomenon. Differential gene expression can, in part, be attributed to the activity of specific miRNAs. Given a database of miRNA binding site motifs and gene expression levels determined by transcriptomic profiling, correspondence analysis, between group analysis and co-inertia analysis can be combined to produce a ranked list of miRNAs associated with a specific gene signature and phenotype. We have applied this approach to examine gene expression data from 69 breast cancer patients treated with tamoxifen (1) and have identified miR-187 as the principle miRNA associated with poor response to anti-estrogen therapy. Expression of miR-187 was subsequently evaluated in a cohort of breast cancer patients (n=111), by locked nucleic acid in situ hybridisation (LNA-ISH) on tissue microarrays, and quantified by automated image analysis. LNA-ISH signal was validated by miR-187-specific Taqman PCR in a subset of tumours. High miR-187 expression was significantly associated with poor outcome in ER+ breast cancer patients (p = 0.05) and correlated with increased tumour size (p=0.009), higher grade (p=0.005) and PR negativity (p=0.014). Additionally, the prognostic significance of the miR-187 target genes OCA2 and HIPK3 was examined in an independent dataset comprising 155 breast cancer patients treated with adjuvant tamoxifen (2). Low mRNA expression of both OCA2 (p=0.0001) and HIPK3 (p=0.016) was found to be significantly associated with poor outcome. These data support the hypothesis that miR-187 and its targets play an important role in anti-estrogen resistance and may be useful as biomarkers to aid treatment options and as potential drug targets to restore tamoxifen sensitivity in resistant patients. 1. Kok M et al. Comparison of gene expression profiles predicting progression in breast cancer patients treated with tamoxifen. Breast Cancer Res Treat 2009;113(2):275 2. Chanrion M et al., A gene expression signature that can predict the recurrence of tamoxifen-treated primary breast cancer. Clin Cancer Res 2008;14(6):1744-52. Note: This abstract was not presented at the AACR 101st Annual Meeting 2010 because the presenter was unable to attend. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 4049.

Systematic validation of novel breast cancer progression-associated biomarkers via high-throughput antibody generation and application of tissue microarray technology : an initial report