Structuring heterogeneous biological information using fuzzy clustering of k-partite graphs

<p>Abstract</p> <p>Background</p> <p>Extensive and automated data integration in bioinformatics facilitates the construction of large, complex biological networks. However, the challenge lies in the interpretation of these networks. While most research focuses on the unipartite or bipartite case, we address the more general but common situation of <it>k</it>-partite graphs. These graphs contain <it>k </it>different node types and links are only allowed between nodes of different types. In order to reveal their structural organization and describe the contained information in a more coarse-grained fashion, we ask how to detect clusters within each node type.</p> <p>Results</p> <p>Since entities in biological networks regularly have more than one function and hence participate in more than one cluster, we developed a <it>k</it>-partite graph partitioning algorithm that allows for overlapping (fuzzy) clusters. It determines for each node a degree of membership to each cluster. Moreover, the algorithm estimates a weighted <it>k</it>-partite graph that connects the extracted clusters. Our method is fast and efficient, mimicking the multiplicative update rules commonly employed in algorithms for non-negative matrix factorization. It facilitates the decomposition of networks on a chosen scale and therefore allows for analysis and interpretation of structures on various resolution levels. Applying our algorithm to a tripartite disease-gene-protein complex network, we were able to structure this graph on a large scale into clusters that are functionally correlated and biologically meaningful. Locally, smaller clusters enabled reclassification or annotation of the clusters' elements. We exemplified this for the transcription factor MECP2.</p> <p>Conclusions</p> <p>In order to cope with the overwhelming amount of information available from biomedical literature, we need to tackle the challenge of finding structures in large networks with nodes of multiple types. To this end, we presented a novel fuzzy <it>k</it>-partite graph partitioning algorithm that allows the decomposition of these objects in a comprehensive fashion. We validated our approach both on artificial and real-world data. It is readily applicable to any further problem.</p

Differentiation of two types of mobilized peripheral blood stem cells by microRNA and cDNA expression analysis

<p>Abstract</p> <p>Background</p> <p>Mobilized-peripheral blood hematopoietic stem cells (HSCs) have been used for transplantation, immunotherapy, and cardiovascular regenerative medicine. Agents used for HSC mobilization include G-CSF and the CXCR4 inhibitor AMD3100 (plerixafor). The HSCs cells mobilized by each agent may contain different subtypes and have different functions. To characterize mobilized HSCs used for clinical applications, microRNA (miRNA) profiling and gene expression profiling were used to compare AMD3100-mobilized CD133+ cells from 4 subjects, AMD3100 plus G-CSF-mobilized CD133+ cells from 4 subjects and G-CSF-mobilized CD34+ cells from 5 subjects. The HSCs were compared to peripheral blood leukocytes (PBLs) from 7 subjects.</p> <p>Results</p> <p>Hierarchical clustering of miRNAs separated HSCs from PBLs. miRNAs up-regulated in all HSCs included hematopoiesis-associated miRNA; miR-126, miR-10a, miR-221 and miR-17-92 cluster. miRNAs up-regulated in PBLs included miR-142-3p, -218, -21, and -379. Hierarchical clustering analysis of miRNA expression separated the AMD3100-mobilized CD133+ cells from G-CSF-mobilized CD34+ cells. Gene expression analysis of the HSCs naturally segregated samples according to mobilization and isolation protocol and cell differentiation status.</p> <p>Conclusion</p> <p>HSCs and PBLs have unique miRNA and gene expression profiles. miRNA and gene expression microarrays maybe useful for assessing differences in HSCs.</p

Identification of candidate regulatory sequences in mammalian 3' UTRs by statistical analysis of oligonucleotide distributions

3' untranslated regions (3' UTRs) contain binding sites for many regulatory elements, and in particular for microRNAs (miRNAs). The importance of miRNA-mediated post-transcriptional regulation has become increasingly clear in the last few years. We propose two complementary approaches to the statistical analysis of oligonucleotide frequencies in mammalian 3' UTRs aimed at the identification of candidate binding sites for regulatory elements. The first method is based on the identification of sets of genes characterized by evolutionarily conserved overrepresentation of an oligonucleotide. The second method is based on the identification of oligonucleotides showing statistically significant strand asymmetry in their distribution in 3' UTRs. Both methods are able to identify many previously known binding sites located in 3'UTRs, and in particular seed regions of known miRNAs. Many new candidates are proposed for experimental verification.Comment: Added two reference

Effect of ret/PTC 1 rearrangement on transcription and post-transcriptional regulation in a papillary thyroid carcinoma model

BACKGROUND: microRNAs (miRNAs) are a group of non-coding single stranded RNAs measuring approximately 22 nt in length that have been found to control cell growth, differentiation and apoptosis. miRNAs negatively regulate their target genes and recently have been implicated in tumourigenesis. Furthermore, miRNA expression profiling correlates with various cancers, with these genes thought to act as both tumour suppressors and oncogenes. ret/PTC 1 is an oncogene with constitutive kinase activity implicated in the development of papillary thyroid carcinoma (PTC). This rearrangement leads to aberrant MAPK activation that is implicated in PTC tumourigenesis. AIM: The aim of this study was to identify the effect that ret/PTC 1 has on transcription and post-transcriptional regulation in PTC by using DNA microarray and microRNA analysis. RESULTS: DNA microarray analysis revealed a group of genes differentially expressed between normal thyroid cell lines and those harbouring a ret/PTC 1 rearrangement. Furthermore, a unique miRNA expression signature differentiated between PTC cell lines with ret/PTC 1 and a normal thyroid cell line. 21 miRNAs showed significant overexpression and 14 miRNAs showed underexpression in these cell lines when compared to normal thyroid. Several of these up/down regulated miRNAs may be involved in PTC pathogenesis

Mechanical stretch induced transcriptomic profiles in cardiac myocytes

Mechanical forces are able to activate hypertrophic growth of cardiomyocytes in the overloaded myocardium. However, the transcriptional profiles triggered by mechanical stretch in cardiac myocytes are not fully understood. Here, we performed the first genome-wide time series study of gene expression changes in stretched cultured neonatal rat ventricular myocytes (NRVM)s, resulting in 205, 579, 737, 621, and 1542 differentially expressed (> 2-fold, P < 0.05) genes in response to 1, 4, 12, 24, and 48 hours of cyclic mechanical stretch. We used Ingenuity Pathway Analysis to predict functional pathways and upstream regulators of differentially expressed genes in order to identify regulatory networks that may lead to mechanical stretch induced hypertrophic growth of cardiomyocytes. We also performed micro (miRNA) expression profiling of stretched NRVMs, and identified that a total of 8 and 87 miRNAs were significantly (P < 0.05) altered by 1-12 and 24-48 hours of mechanical stretch, respectively. Finally, through integration of miRNA and mRNA data, we predicted the miRNAs that regulate mRNAs potentially leading to the hypertrophic growth induced by mechanical stretch. These analyses predicted nuclear factor-like 2 (Nrf2) and interferon regulatory transcription factors as well as the let-7 family of miRNAs as playing roles in the regulation of stretch-regulated genes in cardiomyocytes.Peer reviewe

Heme metabolism genes Downregulated in COPD Cachexia.

IntroductionCachexia contributes to increased mortality and reduced quality of life in Chronic Obstructive Pulmonary Disease (COPD) and may be associated with underlying gene expression changes. Our goal was to identify differential gene expression signatures associated with COPD cachexia in current and former smokers.MethodsWe analyzed whole-blood gene expression data from participants with COPD in a discovery cohort (COPDGene, N = 400) and assessed replication (ECLIPSE, N = 114). To approximate the consensus definition using available criteria, cachexia was defined as weight-loss &gt; 5% in the past 12 months or low body mass index (BMI) (&lt; 20 kg/m2) and 1/3 criteria: decreased muscle strength (six-minute walk distance &lt; 350 m), anemia (hemoglobin &lt; 12 g/dl), and low fat-free mass index (FFMI) (&lt; 15 kg/m2 among women and &lt; 17 kg/m2 among men) in COPDGene. In ECLIPSE, cachexia was defined as weight-loss &gt; 5% in the past 12 months or low BMI and 3/5 criteria: decreased muscle strength, anorexia, abnormal biochemistry (anemia or high c-reactive protein (&gt; 5 mg/l)), fatigue, and low FFMI. Differential gene expression was assessed between cachectic and non-cachectic subjects, adjusting for age, sex, white blood cell counts, and technical covariates. Gene set enrichment analysis was performed using MSigDB.ResultsThe prevalence of COPD cachexia was 13.7% in COPDGene and 7.9% in ECLIPSE. Fourteen genes were differentially downregulated in cachectic versus non-cachectic COPD patients in COPDGene (FDR &lt; 0.05) and ECLIPSE (FDR &lt; 0.05).DiscussionSeveral replicated genes regulating heme metabolism were downregulated among participants with COPD cachexia. Impaired heme biosynthesis may contribute to cachexia development through free-iron buildup and oxidative tissue damage

Analysis of Integrin α6β4 Function in Breast Carcinoma: A Dissertation

The development and survival of multicellular organisms depends upon the ability of cells to move. Embryogenesis, immune surveillance, wound healing, and metastatic disease are all processes that necessitate effective cellular locomotion. Central to the process of cell motility is the family of integrins, transmembrane cell surface receptors that mediate stable adhesions between cells and their extracellular environment. Many human diseases are associated with aberrant integrin function. Carcinoma cells in particular can hijack integrins, harnessing their mechanical and signaling potential to propagate cell invasion and metastatic disease, one example being integrin α6β4. This integrin, often referred to simply as β4, is defined as an adhesion receptor for the laminin family of extracellular matrix proteins. The role of integrin β4 in potentiating carcinoma invasion is well established, during which it serves both a mechanical and signaling function. miRNAs are short non-coding RNAs that regulate gene expression posttranscriptionally, and data describing the role of extracellular stimuli in governing their expression patterns are sparse. This observation coupled to the increasingly significant role of miRNAs in tumorigenesis prompted us to examine their function as downstream effectors of β4, an integrin closely linked to aggressive disease in breast carcinoma. The work presented in this dissertation documents the first example that integrin expression correlates with specific miRNA patterns. Moreover, integrin β4 status in vitro and in vivo is associated with decreased expression of distinct miRNA families in breast cancer, namely miR-25/32/92abc/363/363-3p/367 and miR-99ab/100, with purported roles in cell motility. Another miRNA, miR-29a, is significantly downregulated in response to de novo expression of β4 in a breast carcinoma cell line, and β4-mediated repression of the miRNA is required for invasion. Another major conclusion of this study is that β4 integrin expression and ligation can regulate the expression of SPARC in breast carcinoma cells. These data reveal distinct mechanisms by which β4 promotes SPARC expression, involving both a miR-29a-mediated process and a TOR-dependent translational mechanism. Our observations establish a link between miRNA expression patterns and cell motility downstream of β4 in the context of breast cancer, and uncover a novel effector of β4-mediated invasion