Model-based identification of cis-acting elements from microarray data

Lipopolysaccharides Improve Mesenchymal Stem Cell-Mediated Cardioprotection by MyD88 and stat3 Signaling in a Mouse Model of Cardiac Ischemia/Reperfusion Injury

Bone marrow-derived mesenchymal stem cells (MSCs) improve cardiac function after ischemia/reperfusion injury, in part, due to the release of cytoprotective paracrine factors. Toll-like receptor 4 (TLR4) is expressed in MSCs and regulates the expression of cytoprotective factors, cytokines, and chemokines. Lipopolysaccharide (LPS) stimulation of TLR4 activates two distinct signaling pathways that are either MyD88 dependent or MyD88 independent/TIR-domain-containing adapter-inducing interferon-β (TRIF) dependent. While it was reported previously that LPS treatment improved MSC-mediated cardioprotection, the mechanism underlying such improved effect remains unknown. To study the role of MyD88 signaling in MSC cardioprotective activity, wild type (WT) and MyD88^-/- MSCs were treated with LPS (200 ng/mL) for 24 h. WT and MyD88^-/- MSCs with or without LPS pretreatment were infused into the coronary circulation of isolated mouse hearts (Langendorff model) and then subjected to ischemia (25 min) and reperfusion (50 min). Saline served as a negative control. Both untreated and LPS-pretreated WT MSCs significantly improved postischemic recovery of myocardial function of isolated mouse hearts, as evidenced by improved left ventricular developed pressure and ventricular contractility assessment (ie, the rate of left ventricle pressure change over time, ± dp/dt). LPS-pretreated WT MSCs conferred better cardiac function recovery than untreated MSCs; however, such effect of LPS was abolished when using MyD88^-/- MSCs. In addition, LPS stimulated stat3 activity in WT MSCs, but not MyD88^-/- MSCs. stat3 small interfering RNA abolished the effect of LPS in improving the cardioprotection of WT MSCs. In conclusion, this study demonstrates that LPS improves MSC-mediated cardioprotection by MyD88-dependent activation of stat3.

ResSeq: Enhancing Short-Read Sequencing Alignment By Rescuing Error-Containing Reads

Next-generation short-read sequencing is widely utilized in genomic studies. Biological applications require an alignment step to map sequencing reads to the reference genome, before acquiring expected genomic information. This requirement makes alignment accuracy a key factor for effective biological interpretation. Normally, when accounting for measurement errors and single nucleotide polymorphisms, short read mappings with a few mismatches are generally considered acceptable. However, to further improve the efficiency of short-read sequencing alignment, we propose a method to retrieve additional reliably aligned reads (reads with more than a pre-defined number of mismatches), using a Bayesian-based approach. In this method, we first retrieve the sequence context around the mismatched nucleotides within the already aligned reads; these loci contain the genomic features where sequencing errors occur. Then, using the derived pattern, we evaluate the remaining (typically discarded) reads with more than the allowed number of mismatches, and calculate a score that represents the probability that a specific alignment is correct. This strategy allows the extraction of more reliably aligned reads, therefore improving alignment sensitivity.

IMPLEMENTATION

The source code of our tool, ResSeq, can be downloaded from: https://github.com/hrbeubiocenter/Resseq.

Platelet-derived growth factor-BB enhances MSC-mediated cardioprotection via suppression of miR-320 expression

Delivery of bone marrow-derived mesenchymal stem cells (MSCs) to myocardium protects ischemic tissue through the paracrine release of beneficial angiogenic and cytoprotective factors. Platelet-derived growth factor (PDGF)-BB, a potent mitogen of MSCs, is involved in the pathophysiology of ischemic heart disease. However, the role(s) of PDGF in MSC-mediated cardioprotection remains unknown. Here, we found that PDGF treatment of MSCs resulted in rapid activation of both Akt and ERK (central intracellular signal mediators), upregulated VEGF, and induced phosphorylation of the activator protein-1 (AP-1) transcription factor c-Jun. Examination of several microRNA genes having predicted promoter c-Jun-binding sites showed that PDGF treatment resulted in upregulation of miR-16-2 and downregulation of miRs-23b, -27b, and -320b. To examine possible PDGF augmentation of therapeutic potential, we evaluated the effects of PDGF using an ex vivo isolated mouse heart ischemia-reperfusion model. Human MSCs, with or without PDGF preconditioning, were infused into the coronary circulation of isolated mouse hearts. The hearts that received PDGF-treated MSCs exhibited a greater functional recovery compared with naïve MSC-infused hearts, following ischemia-reperfusion injury. This enhanced functional recovery was abolished by overexpression of miR-320, a microRNA we found downregulated by PDGF-activated c-Jun. Overexpression of miR-320 also resulted in upregulation of insulin-like growth factor binding protein (IGFBP) family members, suggesting PDGF "cross talk" with the mitogenic IGF signaling pathway. Collectively, we conclude that PDGF enhances MSC-mediated cardioprotection via a c-Jun/miR-320 signaling mechanism and PDGF MSC preconditioning may be an effective therapeutic strategy for cardiac ischemia.

Haemophilus ducreyi RpoE and CpxRA appear to play distinct yet complementary roles in regulation of envelope-related functions

Haemophilus ducreyi causes the sexually transmitted disease chancroid and a chronic limb ulceration syndrome in children. In humans, H. ducreyi is found in an abscess and overcomes a hostile environment to establish infection. To sense and respond to membrane stress, bacteria utilize two-component systems (TCSs) and extracytoplasmic function (ECF) sigma factors. We previously showed that activation of CpxRA, the only intact TCS in H. ducreyi, does not regulate homologues of envelope protein folding factors but does downregulate genes encoding envelope-localized proteins, including many virulence determinants. H. ducreyi also harbors a homologue of RpoE, which is the only ECF sigma factor in the organism. To potentially understand how H. ducreyi responds to membrane stress, here we defined RpoE-dependent genes using transcriptome sequencing (RNA-Seq). We identified 180 RpoE-dependent genes, of which 98% were upregulated; a major set of these genes encodes homologues of envelope maintenance and repair factors. We also identified and validated a putative RpoE promoter consensus sequence, which was enriched in the majority of RpoE-dependent targets. Comparison of RpoE-dependent genes to those controlled by CpxR showed that each transcription factor regulated a distinct set of genes. Given that RpoE activated a large number of genes encoding envelope maintenance and repair factors and that CpxRA represses genes encoding envelope-localized proteins, these data suggest that RpoE and CpxRA appear to play distinct yet complementary roles in regulating envelope homeostasis in H. ducreyi.

Data-mining the FlyAtlas online resource to identify core functional motifs across transporting epithelia

Background

Comparative analysis of tissue-specific transcriptomes is a powerful technique to uncover tissue functions. Our FlyAtlas.org provides authoritative gene expression levels for multiple tissues of Drosophila melanogaster (1). Although the main use of such resources is single gene lookup, there is the potential for powerful meta-analysis to address questions that could not easily be framed otherwise. Here, we illustrate the power of data-mining of FlyAtlas data by comparing epithelial transcriptomes to identify a core set of highly-expressed genes, across the four major epithelial tissues (salivary glands, Malpighian tubules, midgut and hindgut) of both adults and larvae.

Method

Parallel hypothesis-led and hypothesis-free approaches were adopted to identify core genes that underpin insect epithelial function. In the former, gene lists were created from transport processes identified in the literature, and their expression profiles mapped from the flyatlas.org online dataset. In the latter, gene enrichment lists were prepared for each epithelium, and genes (both transport related and unrelated) consistently enriched in transporting epithelia identified.

Results

A key set of transport genes, comprising V-ATPases, cation exchangers, aquaporins, potassium and chloride channels, and carbonic anhydrase, was found to be highly enriched across the epithelial tissues, compared with the whole fly. Additionally, a further set of genes that had not been predicted to have epithelial roles, were co-expressed with the core transporters, extending our view of what makes a transporting epithelium work. Further insights were obtained by studying the genes uniquely overexpressed in each epithelium; for example, the salivary gland expresses lipases, the midgut organic solute transporters, the tubules specialize for purine metabolism and the hindgut overexpresses still unknown genes.

Conclusion

Taken together, these data provide a unique insight into epithelial function in this key model insect, and a framework for comparison with other species. They also provide a methodology for function-led datamining of FlyAtlas.org and other multi-tissue expression datasets.

Molecular basis for impaired collateral artery growth in the spontaneously hypertensive rat: insight from microarray analysis

Analysis of global gene expression in mesenteric control and collateral arteries was used to investigate potential molecules, pathways, and mechanisms responsible for impaired collateral growth in the Spontaneously Hypertensive Rat (SHR). A fundamental difference was observed in overall gene expression pattern in SHR versus Wistar Kyoto (WKY) collaterals; only 6% of genes altered in collaterals were similar between rat strains. Ingenuity® Pathway Analysis (IPA) identified major differences between WKY and SHR in networks and biological functions related to cell growth and proliferation and gene expression. In SHR control arteries, several mechano-sensitive and redox-dependent transcription regulators were downregulated including JUN (-5.2×, P = 0.02), EGR1 (-4.1×, P = 0.01), and NFĸB1 (-1.95×, P = 0.04). Predicted binding sites for NFĸB and AP-1 were present in genes altered in WKY but not SHR collaterals. Immunostaining showed increased NFĸB nuclear translocation in collateral arteries of WKY and apocynin-treated SHR, but not in untreated SHR. siRNA for the p65 subunit suppressed collateral growth in WKY, confirming a functional role of NFkB. Canonical pathways identified by IPA in WKY but not SHR included nitric oxide and renin-angiotensin system signaling. The angiotensin type 1 receptor (AGTR1) exhibited upregulation in WKY collaterals, but downregulation in SHR; pharmacological blockade of AGTR1 with losartan prevented collateral luminal expansion in WKY. Together, these results suggest that collateral growth impairment results from an abnormality in a fundamental regulatory mechanism that occurs at a level between signal transduction and gene transcription and implicate redox-dependent modulation of mechano-sensitive transcription factors such as NFĸB as a potential mechanism.

Comprehensive genomic profiling in diabetic nephropathy reveals the predominance of proinflammatory pathways

Despite advances in the treatment of diabetic nephropathy (DN), currently available therapies have not prevented the epidemic of progressive chronic kidney disease (CKD). The morbidity of CKD, and the inexorable increase in the prevalence of end-stage renal disease, demands more effective approaches to prevent and treat progressive CKD. We undertook next-generation sequencing in a rat model of diabetic nephropathy to study in depth the pathogenic alterations involved in DN with progressive CKD. We employed the obese, diabetic ZS rat, a model that develops diabetic nephropathy, characterized by progressive CKD, inflammation, and fibrosis, the hallmarks of human disease. We then used RNA-seq to examine the combined effects of renal cells and infiltrating inflammatory cells acting as a pathophysiological unit. The comprehensive systems biology analysis of progressive CKD revealed multiple interactions of altered genes that were integrated into morbid networks. These pathological gene assemblies lead to renal inflammation and promote apoptosis and cell cycle arrest in progressive CKD. Moreover, in what is clearly a major therapeutic challenge, multiple and redundant pathways were found to be linked to renal fibrosis, a major cause of kidney loss. We conclude that systems biology applied to progressive CKD in DN can be used to develop novel therapeutic strategies directed to restore critical anomalies in affected gene networks.

Activation of CpxRA in Haemophilus ducreyi primarily inhibits the expression of its targets, including major virulence determinants

Haemophilus ducreyi causes chancroid, a genital ulcer disease that facilitates the transmission of human immunodeficiency virus type 1. In humans, H. ducreyi is surrounded by phagocytes and must adapt to a hostile environment to survive. To sense and respond to environmental cues, bacteria frequently use two-component signal transduction (2CST) systems. The only obvious 2CST system in H. ducreyi is CpxRA; CpxR is a response regulator, and CpxA is a sensor kinase. Previous studies by Hansen and coworkers showed that CpxR directly represses the expression of dsrA, the lspB-lspA2 operon, and the flp operon, which are required for virulence in humans. They further showed that CpxA functions predominantly as a phosphatase in vitro to maintain the expression of virulence determinants. Since a cpxA mutant is avirulent while a cpxR mutant is fully virulent in humans, CpxA also likely functions predominantly as a phosphatase in vivo. To better understand the role of H. ducreyi CpxRA in controlling virulence determinants, here we defined genes potentially regulated by CpxRA by using RNA-Seq. Activation of CpxR by deletion of cpxA repressed nearly 70% of its targets, including seven established virulence determinants. Inactivation of CpxR by deletion of cpxR differentially regulated few genes and increased the expression of one virulence determinant. We identified a CpxR binding motif that was enriched in downregulated but not upregulated targets. These data reinforce the hypothesis that CpxA phosphatase activity plays a critical role in controlling H. ducreyi virulence in vivo. Characterization of the downregulated genes may offer new insights into pathogenesis.

Regulatory mechanisms in bone following mechanical loading

Bone responds with increased bone formation to mechanical loading, and the time course of bone formation after initiating mechanical loading is well characterized. However, the regulatory activities governing the loading-dependent changes in gene expression are not well understood. The goal of this study was to identify the time-dependent regulatory mechanisms that governed mechanical loading-induced gene expression in bone using a predictive bioinformatics algorithm. A standard model for bone loading in rodents was employed in which the right forelimb was loaded axially for three minutes per day, while the left forearm served as a non-loaded, contralateral control. Animals were subjected to loading sessions every day, with 24 hours between sessions. Ulnas were sampled at 11 time points, from 4 hours to 32 days after beginning loading. Using a predictive bioinformatics algorithm, we created a linear model of gene expression and identified 44 transcription factor binding motifs and 29 microRNA binding sites that were predicted to regulate gene expression across the time course. Known and novel transcription factor binding motifs were identified throughout the time course, as were several novel microRNA binding sites. These time-dependent regulatory mechanisms may be important in controlling the loading-induced bone formation process.

Repeated measures semiparametric regression using targeted maximum likelihood methodology with application to transcription factor activity discovery

In longitudinal and repeated measures data analysis, often the goal is to determine the effect of a treatment or aspect on a particular outcome (e.g., disease progression). We consider a semiparametric repeated measures regression model, where the parametric component models effect of the variable of interest and any modification by other covariates. The expectation of this parametric component over the other covariates is a measure of variable importance. Here, we present a targeted maximum likelihood estimator of the finite dimensional regression parameter, which is easily estimated using standard software for generalized estimating equations. The targeted maximum likelihood method provides double robust and locally efficient estimates of the variable importance parameters and inference based on the influence curve. We demonstrate these properties through simulation under correct and incorrect model specification, and apply our method in practice to estimating the activity of transcription factor (TF) over cell cycle in yeast. We specifically target the importance of SWI4, SWI6, MBP1, MCM1, ACE2, FKH2, NDD1, and SWI5. The semiparametric model allows us to determine the importance of a TF at specific time points by specifying time indicators as potential effect modifiers of the TF. Our results are promising, showing significant importance trends during the expected time periods. This methodology can also be used as a variable importance analysis tool to assess the effect of a large number of variables such as gene expressions or single nucleotide polymorphisms.

Combinatorial regulation of transcription factors and microRNAs

Background

Gene regulation is a key factor in gaining a full understanding of molecular biology. Cis-regulatory modules (CRMs), consisting of multiple transcription factor binding sites, have been confirmed as the main regulators in gene expression. In recent years, a novel regulator known as microRNA (miRNA) has been found to play an important role in gene regulation. Meanwhile, transcription factor and microRNA co-regulation has been widely identified. Thus, the relationships between CRMs and microRNAs have generated interest among biologists.

Results

We constructed new combinatorial regulatory modules based on CRMs and miRNAs. By analyzing their effect on gene expression profiles, we found that genes targeted by both CRMs and miRNAs express in a significantly similar way. Furthermore, we constructed a regulatory network composed of CRMs, miRNAs, and their target genes. Investigating its structure, we found that the feed forward loop is a significant network motif, which plays an important role in gene regulation. In addition, we further analyzed the effect of miRNAs in embryonic cells, and we found that mir-154, as well as some other miRNAs, have significant co-regulation effect with CRMs in embryonic development.

Conclusions

Based on the co-regulation of CRMs and miRNAs, we constructed a novel combinatorial regulatory network which was found to play an important role in gene regulation, particularly during embryonic development.

Motif prediction to distinguish LPS-stimulated pro-inflammatory vs. antibacterial macrophage genes

BACKGROUND

Innate immunity is the first line of defence offered by host cells to infections. Macrophage cells involved in innate immunity are stimulated by lipopolysaccharide (LPS), found on bacterial cell surface, to express a complex array of gene products. Persistent LPS stimulation makes a macrophage tolerant to LPS with down regulation of inflammatory genes ("pro-inflammatory") while continually expressing genes to fight the bacterial infection ("antibacterial"). Interactions of transcription factors (TF) at their cognate TF binding sites (TFBS) on the expressed genes are important in transcriptional regulatory networks that control these pro-inflammatory and antibacterial expression paradigms involved in LPS stimulation.

RESULTS

We used differential expression patterns in a public domain microarray data set from LPS-stimulated macrophages to identify 228 pro-inflammatory and 18 antibacterial genes. Employing three different motif search tools, we predicted respectively four and one statistically significant TF-TFBS interactions from the pro-inflammatory and antibacterial gene sets. The biological literature was utilized to identify target genes for the four pro-inflammatory profile TFs predicted from the three tools, and 18 of these target genes were observed to follow the pro-inflammatory expression pattern in the original microarray data.

CONCLUSIONS

Our analysis distinguished pro-inflammatory vs. antibacterial transcriptomic signatures that classified their respective gene expression patterns and the corresponding TF-TFBS interactions in LPS-stimulated macrophages. By doing so, this study has attempted to characterize the temporal differences in gene expression associated with LPS tolerance, a major immune phenomenon implicated in various pathological disorders.

Signal transducers and activators of transcription-1 (STAT1) regulates microRNA transcription in interferon gamma-stimulated HeLa cells

Background

Constructing and modeling the gene regulatory network is one of the central themes of systems biology. With the growing understanding of the mechanism of microRNA biogenesis and its biological function, establishing a microRNA-mediated gene regulatory network is not only desirable but also achievable.

Methodology

In this study, we propose a bioinformatics strategy to construct the microRNA-mediated regulatory network using genome-wide binding patterns of transcription factor(s) and RNA polymerase II (RPol II), derived using chromatin immunoprecipitation following next generation sequencing (ChIP-seq) technology. Our strategy includes three key steps, identification of transcription start sites and promoter regions of primary microRNA transcripts using RPol II binding patterns, selection of cooperating transcription factors that collaboratively function with the transcription factors targeted by ChIP-seq assay, and construction of the network that contains regulatory cascades of both transcription factors and microRNAs.

Principal Findings

Using CAMDA (Critical Assessment of Massive Data Analysis) 2009 data set that includes ChIP-seq data on RPol II and STAT1 (signal transducers and activators of transcription 1) in HeLa S3 cells in control condition and with interferon γ stimulation, we first identified promoter regions of 83 microRNAs in HeLa cells. We then identified two potential STAT1 collaborating factors, AP-1 and C/EBP (CCAAT enhancer-binding proteins), and further established eight feedback network elements that may regulate cellular response during interferon γ stimulation.

Conclusions

This study offers a bioinformatics strategy to provide testable hypotheses on the mechanisms of microRNA-mediated transcriptional regulation, based upon genome-wide protein-DNA interaction data derived from ChIP-seq experiments.

Activation of the CpxRA system by deletion of cpxA impairs the ability of Haemophilus ducreyi to infect humans

Haemophilus ducreyi must adapt to the environment of the human host to establish and maintain infection in the skin. Bacteria generally utilize stress response systems, such as the CpxRA two-component system, to adapt to hostile environments. CpxRA is the only obvious two-component system contained in the H. ducreyi genome and negatively regulates the lspB-lspA2 operon, which encodes proteins that enable the organism to resist phagocytosis. We constructed an unmarked, in-frame H. ducreyi cpxA deletion mutant, 35000HPDeltacpxA. In human inoculation experiments, 35000HPDeltacpxA formed papules at a rate and size that were significantly less than its parent and was unable to form pustules compared to the parent. CpxA usually has kinase and phosphatase activities for CpxR, and the deletion of CpxA leads to the accumulation of activated CpxR due to the loss of phosphatase activity and the ability of CpxR to accept phosphate groups from other donors. Using a reporter construct, the lspB-lspA2 promoter was downregulated in 35000HPDeltacpxA, confirming that CpxR was activated. Deletion of cpxA downregulated DsrA, the major determinant of serum resistance in the organism, causing the mutant to become serum susceptible. Complementation in trans restored parental phenotypes. 35000HPDeltacpxA is the first H. ducreyi mutant that is impaired in its ability to form both papules and pustules in humans. Since a major function of CpxRA is to control the flow of protein traffic across the periplasm, uncontrolled activation of this system likely causes dysregulated expression of multiple virulence determinants and cripples the ability of the organism to adapt to the host.

AKT alters genome-wide estrogen receptor alpha binding and impacts estrogen signaling in breast cancer

Estrogen regulates several biological processes through estrogen receptor alpha (ERalpha) and ERbeta. ERalpha-estrogen signaling is additionally controlled by extracellular signal activated kinases such as AKT. In this study, we analyzed the effect of AKT on genome-wide ERalpha binding in MCF-7 breast cancer cells. Parental and AKT-overexpressing cells displayed 4,349 and 4,359 ERalpha binding sites, respectively, with approximately 60% overlap. In both cell types, approximately 40% of estrogen-regulated genes associate with ERalpha binding sites; a similar percentage of estrogen-regulated genes are differentially expressed in two cell types. Based on pathway analysis, these differentially estrogen-regulated genes are linked to transforming growth factor beta (TGF-beta), NF-kappaB, and E2F pathways. Consistent with this, the two cell types responded differently to TGF-beta treatment: parental cells, but not AKT-overexpressing cells, required estrogen to overcome growth inhibition. Combining the ERalpha DNA-binding pattern with gene expression data from primary tumors revealed specific effects of AKT on ERalpha binding and estrogen-regulated expression of genes that define prognostic subgroups and tamoxifen sensitivity of ERalpha-positive breast cancer. These results suggest a unique role of AKT in modulating estrogen signaling in ERalpha-positive breast cancers and highlights how extracellular signal activated kinases can change the landscape of transcription factor binding to the genome.

Transcription factor and microRNA regulation in androgen-dependent and -independent prostate cancer cells

Background

Prostate cancer is one of the leading causes of cancer death in men. Androgen ablation, the most commonly-used therapy for progressive prostate cancer, is ineffective once the cancer cells become androgen-independent. The regulatory mechanisms that cause this transition (from androgen-dependent to androgen-independent) remain unknown. In this study, based on the microarray data comparing global gene expression patterns in the prostate tissue between androgen-dependent and -independent prostate cancer patients, we indentify a set of transcription factors and microRNAs that potentially cause such difference, using a model-based computational approach.

Results

From 335 position weight matrices in the TRANSFAC database and 564 microRNAs in the microRNA registry, our model identify 5 transcription factors and 7 microRNAs to be potentially responsible for the level of androgen dependency. Of these transcription factors and microRNAs, the estimated function of all the 5 transcription factors are predicted to be inhibiting transcription in androgen-independent samples comparing with the dependent ones. Six out of 7 microRNAs, however, demonstrated stimulatory effects. We also find that the expression levels of three predicted transcription factors, including AP-1, STAT3 (signal transducers and activators of transcription 3), and DBP (albumin D-box) are significantly different between androgen-dependent and -independent patients. In addition, microRNA microarray data from other studies confirm that several predicted microRNAs, including miR-21, miR-135a, and miR-135b, demonstrate differential expression in prostate cancer cells, comparing with normal tissues.

Conclusion

We present a model-based computational approach to identify transcription factors and microRNAs influencing the progression of androgen-dependent prostate cancer to androgen-independent prostate cancer. This result suggests that the capability of transcription factors to initiate transcription and microRNAs to facilitate mRNA degradation are both decreased in androgen-independent prostate cancer. The proposed model-based approach indicates that considering combinatorial effects of transcription factors and microRNAs in a unified model provides additional transcriptional and post-transcriptional regulatory mechanisms on global gene expression in the prostate cancer with different hormone-dependency.

Model-based comparative prediction of transcription-factor binding motifs in anabolic responses in bone

Understanding the regulatory mechanism that controls the alteration of global gene expression patterns continues to be a challenging task in computational biology. We previously developed an ant algorithm, a biologically-inspired computational technique for microarray data, and predicted putative transcription-factor binding motifs (TFBMs) through mimicking interactive behaviors of natural ants. Here we extended the algorithm into a set of web-based software, Ant Modeler, and applied it to investigate the transcriptional mechanism underlying bone formation. Mechanical loading and administration of bone morphogenic proteins (BMPs) are two known treatments to strengthen bone. We addressed a question: Is there any TFBM that stimulates both “anabolic responses of mechanical loading” and “BMP-mediated osteogenic signaling”? Although there is no significant overlap among genes in the two responses, a comparative model-based analysis suggests that the two independent osteogenic processes employ common TFBMs, such as a stress responsive element and a motif for peroxisome proliferator-activated receptor (PPAR). The post-modeling in vitro analysis using mouse osteoblast cells supported involvements of the predicted TFBMs such as PPAR, Ikaros 3, and LMO2 in response to mechanical loading. Taken together, the results would be useful to derive a set of testable hypotheses and examine the role of specific regulators in complex transcriptional control of bone formation.

Identification of transcription factor and microRNA binding sites in responsible to fetal alcohol syndrome

This is a first report, using our MotifModeler informatics program, to simultaneously identify transcription factor (TF) and microRNA (miRNA) binding sites from gene expression microarray data. Based on the assumption that gene expression is controlled by combinatorial effects of transcription factors binding in the 5'-upstream regulatory region and miRNAs binding in the 3'-untranslated region (3'-UTR), we developed a model for (1) predicting the most influential cis-acting elements under a given biological condition, and (2) estimating the effects of those elements on gene expression levels. The regulatory regions, TF and miRNA, which mediate the differential genes expression in fetal alcohol syndrome were unknown; microarray data from alcohol exposure paradigm was used. The model predicted strong inhibitory effects of 5' cis-acting elements and stimulatory effects of 3'-UTR under alcohol treatment. Current predictive model derived a key hypothesis for the first time a novel role of miRNAs in gene expression changes associated with abnormal mouse embryo development after alcohol exposure. This suggests that disturbance of miRNA functions may contribute to the alcohol-induced developmental deficiencies.