Dysfunction of the intestinal microbiome in inflammatory bowel disease and treatment

Background

The inflammatory bowel diseases (IBD) Crohn's disease and ulcerative colitis result from alterations in intestinal microbes and the immune system. However, the precise dysfunctions of microbial metabolism in the gastrointestinal microbiome during IBD remain unclear. We analyzed the microbiota of intestinal biopsies and stool samples from 231 IBD and healthy subjects by 16S gene pyrosequencing and followed up a subset using shotgun metagenomics. Gene and pathway composition were assessed, based on 16S data from phylogenetically-related reference genomes, and associated using sparse multivariate linear modeling with medications, environmental factors, and IBD status.

Results

Firmicutes and Enterobacteriaceae abundances were associated with disease status as expected, but also with treatment and subject characteristics. Microbial function, though, was more consistently perturbed than composition, with 12% of analyzed pathways changed compared with 2% of genera. We identified major shifts in oxidative stress pathways, as well as decreased carbohydrate metabolism and amino acid biosynthesis in favor of nutrient transport and uptake. The microbiome of ileal Crohn's disease was notable for increases in virulence and secretion pathways.

Conclusions

This inferred functional metagenomic information provides the first insights into community-wide microbial processes and pathways that underpin IBD pathogenesis.     

Persistent Tn polyagglutination syndrome during febrile neutropenia: a case report and review of the literature

Introduction

Crohn's disease is a chronic inflammatory bowel disease of unknown etiology which may affect any part of the bowel. Fistulas are a common and often serious complication of Crohn's disease. The treatment for fistulizing Crohn's disease can be medical, surgical or a combination of the two. Recently, adalimumab, a fully human anti-tumor necrosis factor monoclonal antibody, has been suggested as a safe and effective treatment for the induction and maintenance of remission in adult patients with moderate to severe Crohn's disease, who are refractory to conventional therapy or intolerant to infliximab. However, large studies focusing on evaluating the efficacy of adalimumab in fistulizing Crohn's disease have not yet been published.

Case presentation

We report the cases of three patients, of European Caucasian ethnicity and Greek nationality, with active luminal and fistulizing Crohn's disease. All of the cases were treated successfully with adalimumab. Patient 1 (a 44-year-old man) and patient 2 (an 18-year-old woman) developed early post-surgical enterocutaneous fistulas, while patient 3 (a 20-year-old woman) had peri-anal fistulizing Crohn's disease. Adalimumab treatment (160 mg subcutaneously at week zero, 80 mg at week two, and 40 mg every other week) was used for three different indications: (1) after the failure of other conservative medical treatments for Crohn's disease (patient 1); (2) as a monotherapy in treating a naive patient (patient 2); (3) after an intolerance to infliximab (patient 3). A remission of the active luminal and fistulizing disease was achieved soon after the initiation of adalimumab and sustained thereafter with maintenance doses. No further surgical intervention was required and no adverse effects were observed in any of the cases.

Conclusions

Fistulizing Crohn's disease remains a challenge in clinical practice. Adalimumab seems to be an effective, well-tolerated and safe treatment option for the induction and maintenance of remission in patients with moderate to severe peri-anal fistulizing Crohn's disease. Furthermore, adalimumab seems to be a promising treatment option for patients with moderate to severe fistulizing Crohn's disease with enterocutaneous fistulas. However, this clinical observation needs to be investigated in further clinical trials.     

Computing evolutionary distinctiveness indices in large scale analysis

Background

A combined quantitative trait loci (QTL) and microarray-based approach is commonly used to find differentially expressed genes which are then identified based on the known function of a gene in the biological process governing the trait of interest. However, a low cutoff value in individual gene analyses may result in many genes with moderate but meaningful changes in expression being missed.

Results

We modified a gene set analysis to identify intersection sets with significantly affected expression for which the changes in the individual gene sets are less significant. The gene expression profiles in liver tissues of four strains of mice from publicly available microarray sources were analyzed to detect trait-associated pathways using information on the QTL regions of blood concentrations of high density lipoproteins (HDL) cholesterol and insulin-like growth factor 1 (IGF-1). Several metabolic pathways related to HDL levels, including lipid metabolism, ABC transporters and cytochrome P450 pathways were detected for HDL QTL regions. Most of the pathways identified for the IGF-1 phenotype were signal transduction pathways associated with biological processes for IGF-1's regulation.

Conclusion

We have developed a method of identifying pathways associated with a quantitative trait using information on QTL. Our approach provides insights into genotype-phenotype relations at the level of biological pathways which may help to elucidate the genetic architecture underlying variation in phenotypic traits.     

Comparative genomics of the pathogenic ciliate Ichthyophthirius multifiliis, its free-living relatives and a host species provide insights into adoption of a parasitic lifestyle and prospects for disease control

Background

Ichthyophthirius multifiliis, commonly known as Ich, is a highly pathogenic ciliate responsible for 'white spot', a disease causing significant economic losses to the global aquaculture industry. Options for disease control are extremely limited, and Ich's obligate parasitic lifestyle makes experimental studies challenging. Unlike most well-studied protozoan parasites, Ich belongs to a phylum composed primarily of free-living members. Indeed, it is closely related to the model organism Tetrahymena thermophila. Genomic studies represent a promising strategy to reduce the impact of this disease and to understand the evolutionary transition to parasitism.

Results

We report the sequencing, assembly and annotation of the Ich macronuclear genome. Compared with its free-living relative T. thermophila, the Ich genome is reduced approximately two-fold in length and gene density and three-fold in gene content. We analyzed in detail several gene classes with diverse functions in behavior, cellular function and host immunogenicity, including protein kinases, membrane transporters, proteases, surface antigens and cytoskeletal components and regulators. We also mapped by orthology Ich's metabolic pathways in comparison with other ciliates and a potential host organism, the zebrafish Danio rerio.

Conclusions

Knowledge of the complete protein-coding and metabolic potential of Ich opens avenues for rational testing of therapeutic drugs that target functions essential to this parasite but not to its fish hosts. Also, a catalog of surface protein-encoding genes will facilitate development of more effective vaccines. The potential to use T. thermophila as a surrogate model offers promise toward controlling 'white spot' disease and understanding the adaptation to a parasitic lifestyle.     

Genotypes and haplotypes in the insulin-like growth factors, their receptors and binding proteins in relation to plasma metabolic levels and mammographic density

Background

Chronic inflammatory diseases including inflammatory bowel disease (IBD; Crohn's disease and ulcerative colitis), psoriasis and rheumatoid arthritis (RA) afflict millions of people worldwide, but their pathogenesis is still not well understood. It is also not well known if distinct changes in gene expression characterize these diseases and if these patterns can discriminate between diseased and control patients and/or stratify the disease. The main focus of our work was the identification of novel markers that overlap among the 3 diseases or discriminate them from each other.

Methods

Diseased (n = 13, n = 15 and n = 12 in IBD, psoriasis and RA respectively) and healthy patients (n = 18) were recruited based on strict inclusion and exclusion criteria; peripheral blood samples were collected by clinicians (30 ml) in Venous Blood Vacuum Collection Tubes containing EDTA and peripheral blood mononuclear cells were separated by Ficoll gradient centrifugation. RNA was extracted using Trizol reagent. Gene expression data was obtained using TaqMan Low Density Array (TLDA) containing 96 genes that were selected by an algorithm and the statistical analyses were performed in Prism by using non-parametric Mann-Whitney U test (P-values < 0.05).

Results

Here we show that using a panel of 96 disease associated genes and measuring mRNA expression levels in peripheral blood derived mononuclear cells; we could identify disease-specific gene panels that separate each disease from healthy controls. In addition, a panel of five genes such as ADM, AQP9, CXCL2, IL10 and NAMPT discriminates between all samples from patients with chronic inflammation and healthy controls. We also found genes that stratify the diseases and separate different subtypes or different states of prognosis in each condition.

Conclusions

These findings and the identification of five universal markers of chronic inflammation suggest that these diseases have a common background in pathomechanism, but still can be separated by peripheral blood gene expression. Importantly, the identified genes can be associated with overlapping biological processes including changed inflammatory response. Gene panels based on such markers can play a major role in the development of personalized medicine, in monitoring disease progression and can lead to the identification of new potential drug targets in chronic inflammation.     

A reference database for tumor-related genes co-expressed with interleukin-8 using genome-scale in silico analysis

Background

The EST database provides a rich resource for gene discovery and in silico expression analysis. We report a novel computational approach to identify co-expressed genes using EST database, and its application to IL-8.

Results

IL-8 is represented in 53 dbEST cDNA libraries. We calculated the frequency of occurrence of all the genes represented in these cDNA libraries, and ranked the candidates based on a Z-score. Additional analysis suggests that most IL-8 related genes are differentially expressed between non-tumor and tumor tissues. To focus on IL-8's function in tumor tissues, we further analyzed and ranked the genes in 16 IL-8 related tumor libraries.

Conclusions

This method generated a reference database for genes co-expressed with IL-8 and could facilitate further characterization of functional association among genes.     

Highly interconnected genes in disease-specific networks are enriched for disease-associated polymorphisms

Background

Complex diseases are associated with altered interactions between thousands of genes. We developed a novel method to identify and prioritize disease genes, which was generally applicable to complex diseases.

Results

We identified modules of highly interconnected genes in disease-specific networks derived from integrating gene-expression and protein interaction data. We examined if those modules were enriched for disease-associated SNPs, and could be used to find novel genes for functional studies. First, we analyzed publicly available gene expression microarray and genome-wide association study (GWAS) data from 13, highly diverse, complex diseases. In each disease, highly interconnected genes formed modules, which were significantly enriched for genes harboring disease-associated SNPs. To test if such modules could be used to find novel genes for functional studies, we repeated the analyses using our own gene expression microarray and GWAS data from seasonal allergic rhinitis. We identified a novel gene, FGF2, whose relevance was supported by functional studies using combined small interfering RNA-mediated knock-down and gene expression microarrays. The modules in the 13 complex diseases analyzed here tended to overlap and were enriched for pathways related to oncological, metabolic and inflammatory diseases. This suggested that this union of the modules would be associated with a general increase in susceptibility for complex diseases. Indeed, we found that this union was enriched with GWAS genes for 145 other complex diseases.

Conclusions

Modules of highly interconnected complex disease genes were enriched for disease-associated SNPs, and could be used to find novel genes for functional studies.     

FragIdent - Automatic identification and characterisation of cDNA-fragments

Background

The ubiquitin 26S/proteasome system (UPS), a serial cascade process of protein ubiquitination and degradation, is the last step for most cellular proteins. There are many genes involved in this system, but are not identified in many species. The accumulating availability of genomic sequence data is generating more demands in data management and analysis. Genomics data of plants such as Populus trichocarpa, Medicago truncatula, Glycine max and others are now publicly accessible. It is time to integrate information on classes of genes for complex protein systems such as UPS.

Results

We developed a database of higher plants' UPS, named 'plantsUPS'. Both automated search and manual curation were performed in identifying candidate genes. Extensive annotations referring to each gene were generated, including basic gene characterization, protein features, GO (gene ontology) assignment, microarray probe set annotation and expression data, as well as cross-links among different organisms. A chromosome distribution map, multi-sequence alignment, and phylogenetic trees for each species or gene family were also created. A user-friendly web interface and regular updates make plantsUPS valuable to researchers in related fields.

Conclusion

The plantsUPS enables the exploration and comparative analysis of UPS in higher plants. It now archives > 8000 genes from seven plant species distributed in 11 UPS-involved gene families. The plantsUPS is freely available now to all users at http://bioinformatics.cau.edu.cn/plantsUPS.     

miRNA signature associated with outcome of gastric cancer patients following chemotherapy

Background

Resistance to chemotherapy severely limits the effectiveness of chemotherapy drugs in treating cancer. Still, the mechanisms and critical pathways that contribute to chemotherapy resistance are relatively unknown. This study elucidates the chemoresistance-associated pathways retrieved from the integrated biological interaction networks and identifies signature genes relevant for chemotherapy resistance.

Methods

An integrated network was constructed by collecting multiple metabolic interactions from public databases and the k-shortest path algorithm was implemented to identify chemoresistant related pathways. The identified pathways were then scored using differential expression values from microarray data in chemosensitive and chemoresistant ovarian and lung cancers. Finally, another pathway database, Reactome, was used to evaluate the significance of genes within each filtered pathway based on topological characteristics.

Results

By this method, we discovered pathways specific to chemoresistance. Many of these pathways were consistent with or supported by known involvement in chemotherapy. Experimental results also indicated that integration of pathway structure information with gene differential expression analysis can identify dissimilar modes of gene reactions between chemosensitivity and chemoresistance. Several identified pathways can increase the development of chemotherapeutic resistance and the predicted signature genes are involved in drug resistant during chemotherapy. In particular, we observed that some genes were key factors for joining two or more metabolic pathways and passing down signals, which may be potential key targets for treatment.

Conclusions

This study is expected to identify targets for chemoresistant issues and highlights the interconnectivity of chemoresistant mechanisms. The experimental results not only offer insights into the mode of biological action of drug resistance but also provide information on potential key targets (new biological hypothesis) for further drug-development efforts.     

Integrative analysis of neuroblastoma and pheochromocytoma genomics data

Background

Pheochromocytoma and neuroblastoma are the most common neural crest-derived tumors in adults and children, respectively. We have performed a large-scale in silico analysis of altogether 1784 neuroblastoma and 531 pheochromocytoma samples to establish similarities and differences using analysis of mRNA and microRNA expression, chromosome aberrations and a novel bioinformatics analysis based on cooperative game theory.

Methods

Datasets obtained from Gene Expression Omnibus and ArrayExpress have been subjected to a complex bioinformatics analysis using GeneSpring, Gene Set Enrichment Analysis, Ingenuity Pathway Analysis and own software.

Results

Comparison of neuroblastoma and pheochromocytoma with other tumors revealed the overexpression of genes involved in development of noradrenergic cells. Among these, the significance of paired-like homeobox 2b in pheochromocytoma has not been reported previously. The analysis of similar expression patterns in neuroblastoma and pheochromocytoma revealed the same anti-apoptotic strategies in these tumors. Cancer regulation by stathmin turned out to be the major difference between pheochromocytoma and neuroblastoma. Underexpression of genes involved in neuronal cell-cell interactions was observed in unfavorable neuroblastoma. By the comparison of hypoxia- and Ras-associated pheochromocytoma, we have found that enhanced insulin like growth factor 1 signaling may be responsible for the activation of Src homology 2 domain containing transforming protein 1, the main co-factor of RET. Hypoxia induced factor 1?? and vascular endothelial growth factor signaling included the most prominent gene expression changes between von Hippel-Lindau- and multiple endocrine neoplasia type 2A-associated pheochromocytoma.

Conclusions

These pathways include previously undescribed pathomechanisms of neuroblastoma and pheochromocytoma and associated gene products may serve as diagnostic markers and therapeutic targets.     

Fitting hidden Markov models of protein domains to a target species: application to Plasmodium falciparum

Background

The identification of gene sets that are significantly impacted in a given condition based on microarray data is a crucial step in current life science research. Most gene set analysis methods treat genes equally, regardless how specific they are to a given gene set.

Results

In this work we propose a new gene set analysis method that computes a gene set score as the mean of absolute values of weighted moderated gene t-scores. The gene weights are designed to emphasize the genes appearing in few gene sets, versus genes that appear in many gene sets. We demonstrate the usefulness of the method when analyzing gene sets that correspond to the KEGG pathways, and hence we called our method P athway A nalysis with D own-weighting of O verlapping G enes (PADOG). Unlike most gene set analysis methods which are validated through the analysis of 2-3 data sets followed by a human interpretation of the results, the validation employed here uses 24 different data sets and a completely objective assessment scheme that makes minimal assumptions and eliminates the need for possibly biased human assessments of the analysis results.

Conclusions

PADOG significantly improves gene set ranking and boosts sensitivity of analysis using information already available in the gene expression profiles and the collection of gene sets to be analyzed. The advantages of PADOG over other existing approaches are shown to be stable to changes in the database of gene sets to be analyzed. PADOG was implemented as an R package available at: http://bioinformaticsprb.med.wayne.edu/PADOG/or http://www.bioconductor.org.