Functional meta-analysis of double connectivity in gene coexpression networks in mammals

Coexpression Network Analysis of Benign and Malignant Phenotypes of SIV-Infected Sooty Mangabey and Rhesus Macaque

To explore the differences between the extreme SIV infection phenotypes, nonprogression (BEN: benign) to AIDS in sooty mangabeys (SMs) and progression to AIDS (MAL: malignant) in rhesus macaques (RMs), we performed an integrated dual positive-negative connectivity (DPNC) analysis of gene coexpression networks (GCN) based on publicly available big data sets in the GEO database of NCBI. The microarray-based gene expression data sets were generated, respectively, from the peripheral blood of SMs and RMs at several time points of SIV infection. Significant differences of GCN changes in DPNC values were observed in SIV-infected SMs and RMs. There are three groups of enriched genes or pathways (EGPs) that are associated with three SIV infection phenotypes (BEN⁺, MAL⁺ and mixed BEN⁺/MAL⁺). The MAL⁺ phenotype in SIV-infected RMs is specifically associated with eight EGPs, including the protein ubiquitin proteasome system, p53, granzyme A, gramzyme B, polo-like kinase, Glucocorticoid receptor, oxidative phosyphorylation and mitochondrial signaling. Mitochondrial (endosymbiotic) dysfunction is solely present in RMs. Specific BEN+ pattern changes in four EGPs are identified in SIV-infected SMs, including the pathways contributing to interferon signaling, BRCA1/DNA damage response, PKR/INF induction and LGALS8. There are three enriched pathways (PRR-activated IRF signaling, RIG1-like receptor and PRR pathway) contributing to the mixed (BEN+/MAL+) phenotypes of SIV infections in RMs and SMs, suggesting that these pathways play a dual role in the host defense against viral infections. Further analysis of Hub genes in these GCNs revealed that the genes LGALS8 and IL-17RA, which positively regulate the barrier function of the gut mucosa and the immune homeostasis with the gut microbiota (exosymbiosis), were significantly differentially expressed in RMs and SMs. Our data suggest that there exists an exo- (dysbiosis of the gut microbiota) and endo- (mitochondrial dysfunction) symbiotic imbalance (EESI) in HIV/SIV infections. Dissecting the mechanisms of the exo-endo symbiotic balance (EESB) that maintains immune homeostasis and the EESI problems in HIV/SIV infections may lead to a better understanding of the pathogenesis of AIDS and the development of novel interventions for the rational control of this disease.

CPuORF correlates with miRNA responsive elements on protein evolutionary rates

miRNA is increasingly being recognized as a key regulator of metabolism in animals. A wealth of evidence has suggested that miRNA mainly binds 3' UTR of mRNA and modulates the cell activities via repressing the mRNA translation. However, as the translation initiates at 5' UTR, cis elements like upstream open reading frame (uORF) resided in 5' UTR may also affect the translation efficiency or elongation. In this study, we performed a systematic analysis of miRNA responsive elements (MREs) and uORF of the same transcript in three model organisms (human, mouse, and Drosophila). Intriguingly, we found that the 3' UTR length grew with the complexity of species (human>mouse>Drosophila), in sharp contrast with the invariability of 5' UTR. Additionally, MRE number correlated well with the 3' UTR length, while uORF number showed a weak correlation with the 5' UTR length. Further, we found that human genes with conserved peptide upstream open reading frame (CPuORF) tend to have more MREs and lower evolutionary rates, which provides new insights into the correlation between UTR properties and translational control in animals.

Co-expression analysis of fetal weight-related genes in ovine skeletal muscle during mid and late fetal development stages

BACKGROUND

Muscle development and lipid metabolism play important roles during fetal development stages. The commercial Texel sheep are more muscular than the indigenous Ujumqin sheep.

RESULTS

We performed serial transcriptomics assays and systems biology analyses to investigate the dynamics of gene expression changes associated with fetal longissimus muscles during different fetal stages in two sheep breeds. Totally, we identified 1472 differentially expressed genes during various fetal stages using time-series expression analysis. A systems biology approach, weighted gene co-expression network analysis (WGCNA), was used to detect modules of correlated genes among these 1472 genes. Dramatically different gene modules were identified in four merged datasets, corresponding to the mid fetal stage in Texel and Ujumqin sheep, the late fetal stage in Texel and Ujumqin sheep, respectively. We further detected gene modules significantly correlated with fetal weight, and constructed networks and pathways using genes with high significances. In these gene modules, we identified genes like TADA3, LMNB1, TGF-β3, EEF1A2, FGFR1, MYOZ1, and FBP2 correlated with fetal weight.

CONCLUSION

Our study revealed the complex network characteristics involved in muscle development and lipid metabolism during fetal development stages. Diverse patterns of the network connections observed between breeds and fetal stages could involve some hub genes, which play central roles in fetal development, correlating with fetal weight. Our findings could provide potential valuable biomarkers for selection of body weight-related traits in sheep and other livestock.

Dynamic modularity of host protein interaction networks in Salmonella Typhi infection

Background

Salmonella Typhi is a human-restricted pathogen, which causes typhoid fever and remains a global health problem in the developing countries. Although previously reported host expression datasets had identified putative biomarkers and therapeutic targets of typhoid fever, the underlying molecular mechanism of pathogenesis remains incompletely understood.

Methods

We used five gene expression datasets of human peripheral blood from patients suffering from S. Typhi or other bacteremic infections or non-infectious disease like leukemia. The expression datasets were merged into human protein interaction network (PIN) and the expression correlation between the hubs and their interacting proteins was measured by calculating Pearson Correlation Coefficient (PCC) values. The differences in the average PCC for each hub between the disease states and their respective controls were calculated for studied datasets. The individual hubs and their interactors with expression, PCC and average PCC values were treated as dynamic subnetworks. The hubs that showed unique trends of alterations specific to S. Typhi infection were identified.

Results

We identified S. Typhi infection-specific dynamic subnetworks of the host, which involve 81 hubs and 1343 interactions. The major enriched GO biological process terms in the identified subnetworks were regulation of apoptosis and biological adhesions, while the enriched pathways include cytokine signalling in the immune system and downstream TCR signalling. The dynamic nature of the hubs CCR1, IRS2 and PRKCA with their interactors was studied in detail. The difference in the dynamics of the subnetworks specific to S. Typhi infection suggests a potential molecular model of typhoid fever.

Conclusions

Hubs and their interactors of the S. Typhi infection-specific dynamic subnetworks carrying distinct PCC values compared with the non-typhoid and other disease conditions reveal new insight into the pathogenesis of S. Typhi.

Robust coordination of cardiac functions from gene co-expression reveals a versatile combinatorial transcriptional control

The necessary overall coordination of cardiac cellular functions is little known at the mRNA level. Focusing on energy production and cardiac contraction, we analyzed microarray data from heart tissue obtained in groups of mice and rats in normal conditions and with a left ventricular dysfunction. In each group and for each function, we identified genes positively or negatively correlated with numerous genes of the function, which were called coordinated or inversely coordinated with the function. The genes coordinated with energy production or cardiac contraction showed the coupling of these functions in all groups. Among coordinated or inversely coordinated genes common to the two functions, we proposed a fair number of transcriptional regulators as potential determinants of the energy production and cardiac contraction coupling. Although this coupling was constant across the groups and unveiled a stable gene core, the combinations of transcriptional regulators were very different between the groups, including one half that has never been linked to heart function. These results highlighted the stable coordination of energy production or cardiac contraction at the mRNA level, and the combinatorial and versatile nature of potential transcriptional regulation. In addition, this work unveiled new transcriptional regulators potentially involved in normal or altered cardiac functional coupling.

Computational identification of potential transcriptional regulators of TGF-ß1 in human atherosclerotic arteries

TGF-ß is protective in atherosclerosis but deleterious in metastatic cancers. Our aim was to determine whether TGF-ß transcriptional regulation is tissue-specific in early atherosclerosis. The computational methods included 5 steps: (i) from microarray data of human atherosclerotic carotid tissue, to identify the 10 best co-expressed genes with TGFB1 (TGFB1 gene cluster), (ii) to choose the 11 proximal promoters, (iii) to predict the TFBS shared by the promoters, (iv) to identify the common TFs co-expressed with the TGFB1 gene cluster, and (v) to compare the common TFs in the early lesions to those identified in advanced atherosclerotic lesions and in various cancers. Our results show that EGR1, SP1 and KLF6 could be responsible for TGFB1 basal expression, KLF6 appearing specific to atherosclerotic lesions. Among the TFs co-expressed with the gene cluster, transcriptional activators (SLC2A4RG, MAZ) and repressors (ZBTB7A, PATZ1, ZNF263) could be involved in the fine-tuning of TGFB1 expression in atherosclerosis.

Predicting targeted drug combinations based on Pareto optimal patterns of coexpression network connectivity

Background

Molecularly targeted drugs promise a safer and more effective treatment modality than conventional chemotherapy for cancer patients. However, tumors are dynamic systems that readily adapt to these agents activating alternative survival pathways as they evolve resistant phenotypes. Combination therapies can overcome resistance but finding the optimal combinations efficiently presents a formidable challenge. Here we introduce a new paradigm for the design of combination therapy treatment strategies that exploits the tumor adaptive process to identify context-dependent essential genes as druggable targets.

Methods

We have developed a framework to mine high-throughput transcriptomic data, based on differential coexpression and Pareto optimization, to investigate drug-induced tumor adaptation. We use this approach to identify tumor-essential genes as druggable candidates. We apply our method to a set of ER⁺ breast tumor samples, collected before (n = 58) and after (n = 60) neoadjuvant treatment with the aromatase inhibitor letrozole, to prioritize genes as targets for combination therapy with letrozole treatment. We validate letrozole-induced tumor adaptation through coexpression and pathway analyses in an independent data set (n = 18).

Results

We find pervasive differential coexpression between the untreated and letrozole-treated tumor samples as evidence of letrozole-induced tumor adaptation. Based on patterns of coexpression, we identify ten genes as potential candidates for combination therapy with letrozole including EPCAM, a letrozole-induced essential gene and a target to which drugs have already been developed as cancer therapeutics. Through replication, we validate six letrozole-induced coexpression relationships and confirm the epithelial-to-mesenchymal transition as a process that is upregulated in the residual tumor samples following letrozole treatment.

Conclusions

To derive the greatest benefit from molecularly targeted drugs it is critical to design combination treatment strategies rationally. Incorporating knowledge of the tumor adaptation process into the design provides an opportunity to match targeted drugs to the evolving tumor phenotype and surmount resistance.

Clinical Study of Effects of Jian Ji Ning, a Chinese Herbal Medicine Compound Preparation, in Treating Patients with Myasthenia Gravis via the Regulation of Differential MicroRNAs Expression in Serum

Myasthenia gravis (MG) is an autoimmune disease, of which the pathogenesis has remained unclear. At present, MG does not have any effective treatment with minor side effects. Jian Ji Ning (JJN), a traditional Chinese medicine formula consisting of 11 medicinal plants, has been used in the treatment of MG for many years. The present study aims to determine if the Chinese herbal medicine JJN could lighten the clinical symptoms of patients with MG via the regulation of differential microRNAs (miRNAs) expression in serum. JJN should be orally administered twice a day for 6 months. In the efficacy evaluation adopting the Quantitative Myasthenia Gravis Score (QMG), we found that JJN could improve the clinical symptoms of patients with MG more effectively. Besides, we found that JJN could regulate differential miRNAs expression in serum of patients with MG. Accordingly, we speculate that the effects of JJN on improving clinical symptoms and blood test indicators of patients with MG may be due to its inhibition of apoptotic pathways of some immune cells and its connection with the regulation of serum miRNAs of some patients. In conclusion, we believe that JJN has a reliable curative effect on patients with MG-induced neuropathologic changes.

Aryl hydrocarbon receptor-induced adrenomedullin mediates cigarette smoke carcinogenicity in humans and mice

Cigarette smoking (CS) is a leading cause of death worldwide. The aryl hydrocarbon receptor (AHR) is partially responsible for tobacco-induced carcinogenesis although the underlying mechanisms involving early effector genes have yet to be determined. Here, we report that adrenomedullin (ADM) significantly contributes to the carcinogenicity of tobacco-activated AHR. CS and AHR activating ligands induced ADM in vitro and in vivo but not in AHR-deficient fibroblasts and mice. Ectopic transfection of AHR rescued ADM expression in AHR(-/-) fibroblasts whereas AHR blockage with siRNA in wild type cells significantly decreased ADM expression. AHR regulates ADM expression through two intronic xenobiotic response elements located close to the start codon in the ADM gene. Using tissue microarrays we showed that ADM and AHR were coupregulated in lung tumor biopsies from smoker patients. Microarray meta-analysis of 304 independent microarray experiments showed that ADM is elevated in smokers and smokers with cancer. In addition, ADM coassociated with a subset of AHR responsive genes and efficiently differentiated patients with lung cancer from nonsmokers. In a novel preclinical model of CS-induced tumor progression, host exposure to CS extracts significantly elevated tumor ADM although systemic treatment with the ADM antagonist NSC16311 efficiently blocked tobacco-induced tumor growth. In conclusion, ADM significantly contributes the carcinogenic effect of AHR and tobacco combustion products. We suggest that therapeutics targeting the AHR/ADM axis may be of clinical relevance in the treatment of tobacco-induced pulmonary malignancies.

Predicting gene ontology from a global meta-analysis of 1-color microarray experiments

Abstract

Inequalities and duality in gene coexpression networks of HIV-1 infection revealed by the combination of the double-connectivity approach and the Gini's method

The symbiosis (Sym) and pathogenesis (Pat) is a duality problem of microbial infection, including HIV/AIDS. Statistical analysis of inequalities and duality in gene coexpression networks (GCNs) of HIV-1 infection may gain novel insights into AIDS. In this study, we focused on analysis of GCNs of uninfected subjects and HIV-1-infected patients at three different stages of viral infection based on data deposited in the GEO database of NCBI. The inequalities and duality in these GCNs were analyzed by the combination of the double-connectivity (DC) approach and the Gini's method. DC analysis reveals that there are significant differences between positive and negative connectivity in HIV-1 stage-specific GCNs. The inequality measures of negative connectivity and edge weight are changed more significantly than those of positive connectivity and edge weight in GCNs from the HIV-1 uninfected to the AIDS stages. With the permutation test method, we identified a set of genes with significant changes in the inequality and duality measure of edge weight. Functional analysis shows that these genes are highly enriched for the immune system, which plays an essential role in the Sym-Pat duality (SPD) of microbial infections. Understanding of the SPD problems of HIV-1 infection may provide novel intervention strategies for AIDS.

Comprehensive gene and microRNA expression profiling reveals the crucial role of hsa-let-7i and its target genes in colorectal cancer metastasis

Accumulating evidence has demonstrated that miRNAs play important roles in the occurrence and development of colorectal cancer (CRC). However, whether miRNAs are associated with the metastasis of CRC remains largely unexplored. The aim of the current study is to profile miRNAs in different CRC metastatic cell lines to identify the biomarkers in CRC metastasis. Gene and miRNA expression profiling was performed to analyze the global expression of mRNAs and miRNAs in the four human CRC cell lines (LoVo, SW480, HT29 and Caco-2) with different potential of metastasis. Expression patterns of mRNAs and miRNAs were altered in different CRC cell lines. By developing an integrated bioinformatics analysis of gene and miRNA expression patterns, hsa-let-7i was identified to show the highest degree in the microRNA-GO-network and microRNA-Gene-network. The expression level of hsa-let-7i was further validated by qRT-PCR in CRC cells. In addition, the targets of hsa-let-7i were predicted by two programs TargetScan and PicTar, and target genes were validated by expression profiling in the most epresentative LoVo and Caco-2 cell lines. Eight genes including TRIM41, SOX13, SLC25A4, SEMA4F, RPUSD2, PLEKHG6, CCND2, and BTBD3 were identified as hsa-let-7i targets. Our data showed the power of comprehensive gene and miRNA expression profiling and the application of bioinformatics tools in the identification of novel biomarkers in CRC metastasis.

Disease progression and solid tumor survival: a transcriptome decoherence model

Networks of genes are typically generated from expression changes observed between control and test conditions. Nevertheless, within a single control state many genes show expression variance across biological replicates. These transcripts, typically termed unstable, are usually excluded from analyses because their behavior cannot be reconciled with biological constraints. Grouped as pairs of covariant genes they can however show a consistent response to the progression of a disease. We present a model of coherence arising from sets of covariant genes that was developed in-vitro then tested against a range of solid tumors. DGPMs, Decoherence Gene Pair Models, showed changes in network topology reflective of the metastatic transition. Across a range of solid tumor studies the model generalizes to reveal a richly connected topology of networks in healthy tissues that becomes sparser as the disease progresses reaching a minimum size in the advanced tumors with minim survivability.

The Sonic Hedgehog pathway stimulates prostate tumor growth by paracrine signaling and recapitulates embryonic gene expression in tumor myofibroblasts

The Hedgehog (Hh) pathway contributes to prostate cancer growth and progression. The presence of robust Sonic Hedgehog (Shh) expression in both normal prostate and localized cancer challenged us to explain the unique growth-promoting effect in cancer. We show here that paracrine Hh signaling exerts a non-cell autonomous effect on xenograft tumor growth and that Hh pathway activation in myofibroblasts alone is sufficient to stimulate tumor growth. Nine genes regulated by Hh in the mesenchyme of the developing prostate were found to be regulated in the stroma of Hh overexpressing xenograft tumors. Correlation analysis of gene expression in matched specimens of benign and malignant human prostate tissue revealed a partial five-gene fingerprint of Hh-regulated expression in stroma of all cancers and the complete nine-gene fingerprint in the subset of tumors exhibiting a reactive stroma. No expression fingerprint was observed in benign tissues. We conclude that changes in the prostate stroma due to association with cancer result in an altered transcriptional response to Hh that mimics the growth-promoting actions of the fetal mesenchyme. Patients with an abundance of myofibroblasts in biopsy tissue may comprise a subgroup that will exhibit a particularly good response to anti-Hh therapy.

Weighted gene co-expression network analysis of the peripheral blood from Amyotrophic Lateral Sclerosis patients

Background

Amyotrophic Lateral Sclerosis (ALS) is a lethal disorder characterized by progressive degeneration of motor neurons in the brain and spinal cord. Diagnosis is mainly based on clinical symptoms, and there is currently no therapy to stop the disease or slow its progression. Since access to spinal cord tissue is not possible at disease onset, we investigated changes in gene expression profiles in whole blood of ALS patients.

Results

Our transcriptional study showed dramatic changes in blood of ALS patients; 2,300 probes (9.4%) showed significant differential expression in a discovery dataset consisting of 30 ALS patients and 30 healthy controls. Weighted gene co-expression network analysis (WGCNA) was used to find disease-related networks (modules) and disease related hub genes. Two large co-expression modules were found to be associated with ALS. Our findings were replicated in a second (30 patients and 30 controls) and third dataset (63 patients and 63 controls), thereby demonstrating a highly significant and consistent association of two large co-expression modules with ALS disease status. Ingenuity Pathway Analysis of the ALS related module genes implicates enrichment of functional categories related to genetic disorders, neurodegeneration of the nervous system and inflammatory disease. The ALS related modules contain a number of candidate genes possibly involved in pathogenesis of ALS.

Conclusion

This first large-scale blood gene expression study in ALS observed distinct patterns between cases and controls which may provide opportunities for biomarker development as well as new insights into the molecular mechanisms of the disease.

MicroRNA: a new entrance to the broad paradigm of systems molecular medicine

Systems molecular medicine is the science of combining systems biology with molecular analysis and intervention to address clinically relevant questions. MicroRNAs (miRNAs) appear particularly suitable to serve as hubs of regulatory networks underlying complex diseases. Clear experimental evidence for coordinated regulation of a large number of genes by miRNAs, however, is still rare. It leaves open several fundamental questions that are important for determining the value of miRNA in complex regulatory networks and in systems molecular medicine. Physiological genomics is a powerful approach for addressing these open questions.

A global meta-analysis of microarray expression data to predict unknown gene functions and estimate the literature-data divide

MOTIVATION

Approximately 9334 (37%) of human genes have no publications documenting their function and, for those that are published, the number of publications per gene is highly skewed. Furthermore, for reasons not clear, the entry of new gene names into the literature has slowed in recent years. If we are to better understand human/mammalian biology and complete the catalog of human gene function, it is important to finish predicting putative functions for these genes based upon existing experimental evidence.

RESULTS

A global meta-analysis (GMA) of all publicly available GEO two-channel human microarray datasets (3551 experiments total) was conducted to identify genes with recurrent, reproducible patterns of co-regulation across different conditions. Patterns of co-expression were divided into parallel (i.e. genes are up and down-regulated together) and anti-parallel. Several ranking methods to predict a gene's function based on its top 20 co-expressed gene pairs were compared. In the best method, 34% of predicted Gene Ontology (GO) categories matched exactly with the known GO categories for approximately 5000 genes analyzed versus only 3% for random gene sets. Only 2.4% of co-expressed gene pairs were found as co-occurring gene pairs in MEDLINE.

CONCLUSIONS

Via a GO enrichment analysis, genes co-expressed in parallel with the query gene were frequently associated with the same GO categories, whereas anti-parallel genes were not. Combining parallel and anti-parallel genes for analysis resulted in fewer significant GO categories, suggesting they are best analyzed separately. Expression databases contain much unexpected genetic knowledge that has not yet been reported in the literature. A total of 1642 Human genes with unknown function were differentially expressed in at least 30 experiments.

AVAILABILITY

Data matrix available upon request.