The global gene expression profiling of early T helper (Th) 1 and Th2 differentiation reveals that this process can be divided into two stages, activation and differentiation. The activation stage is manifested in coordinated mobilization of the replication machinery, a process that we hypothesize may be responsible for establishing genomewide opening of transcription loci. The molecular programs underlying the differentiation stage consist of highly regulated expression of functional groups of genes that are important for the biological properties of Th1͞2 cells and transcription factors that are likely important in establishing terminal differentiation of these cells. The kinetics of expression pattern of a number of transcription factors shed new light on the molecular events that shape the outcome of Th1͞2 differentiation.

BackgroundAustism spectrum disorder (ASD) is a heterogeneous behavioral disorder or condition characterized by severe impairment of social engagement and the presence of repetitive activities. The molecular etiology of ASD is still largely unknown despite a strong genetic component. Part of the difficulty in turning genetics into disease mechanisms and potentially new therapeutics is the sheer number and diversity of the genes that have been associated with ASD and ASD symptoms. The goal of this work is to use shRNA-generated models of genetic defects proposed as causative for ASD to identify the common pathways that might explain how they produce a core clinical disability.MethodsTranscript levels of Mecp2, Mef2a, Mef2d, Fmr1, Nlgn1, Nlgn3, Pten, and Shank3 were knocked-down in mouse primary neuron cultures using shRNA constructs. Whole genome expression analysis was conducted for each of the knockdown cultures as well as a mock-transduced culture and a culture exposed to a lentivirus expressing an anti-luciferase shRNA. Gene set enrichment and a causal reasoning engine was employed to identify pathway level perturbations generated by the transcript knockdown.ResultsQuantification of the shRNA targets confirmed the successful knockdown at the transcript and protein levels of at least 75% for each of the genes. After subtracting out potential artifacts caused by viral infection, gene set enrichment and causal reasoning engine analysis showed that a significant number of gene expression changes mapped to pathways associated with neurogenesis, long-term potentiation, and synaptic activity.ConclusionsThis work demonstrates that despite the complex genetic nature of ASD, there are common molecular mechanisms that connect many of the best established autism candidate genes. By identifying the key regulatory checkpoints in the interlinking transcriptional networks underlying autism, we are better able to discover the ideal points of intervention that provide the broadest efficacy across the diverse population of autism patients.

The nuclear receptor peroxisome proliferator-activated receptor ␣ (PPAR␣) is recognized as the primary target of the fibrate class of hypolipidemic drugs and mediates lipid lowering in part by activating a transcriptional cascade that induces genes involved in the catabolism of lipids. We report here the characterization of three novel PPAR␣ agonists with therapeutic potential for treating dyslipidemia. These structurally related compounds display potent and selective binding to human PPAR␣ and support robust recruitment of coactivator peptides in vitro. These compounds markedly potentiate chimeric transcription systems in cell-based assays and strikingly lower serum triglycerides in vivo. The transcription networks induced by these selective PPAR␣ agonists were assessed by transcriptional profiling of mouse liver after short-and long-term treatment. The induction of several known PPAR␣ target genes involved with fatty acid metabolism were observed, reflecting the expected pharmacology associated with PPAR␣ activation. We also noted the down-regulation of a number of genes related to immune cell function, the acute phase response, and glucose metabolism, suggesting that these compounds may have anti-inflammatory action in the mammalian liver. Whereas these compounds are efficacious in acute preclinical models, extended safety studies and further clinical testing will be required before the full therapeutic promise of a selective PPAR␣ agonist is realized.Coronary heart disease (CHD) is the single leading cause of death in the United States, representing one of every five fatalities during (Rosamond et al., 2007. Elevated serum triglycerides are an independent risk factor for CHD irrespective of HDL cholesterol (Hokanson and Austin, 1996). The fibric acid derivatives (fibrates) represent one therapeutic option for the treatment of dyslipidemia in that they display robust triglyceride lowering with modest HDL elevation. Significant effort has been put forth in the development of pharmacologic agents that demonstrate clear superiority over the first generation fibrates for the treatment of dyslipidemia and CHD.The fibrates can directly bind and activate a subclass of the nuclear receptor superfamily know as the peroxisome proliferator-activated receptors (PPARs). The PPARs are liganddependent transcription factors that are classified as three subtypes known as PPAR␣, PPAR␤ (␦), and PPAR␥. The PPARs are recognized as major regulators of systemic energy metabolism, in part by controlling the expression of numerous genes involved in lipid and glucose metabolism (Desvergne and Wahli, 1999;Huss and Kelly, 2004).

In this study, we formulate a computational reaction model following a chemical kinetic theory approach to predict the binding rate constant for the siRNA-RISC complex formation reaction. The model allowed us to study the potency difference between 2-nt 3' overhangs against bluntended siRNA molecules in an RNA interference (RNAi) system. The rate constant predicted by this model was fed into a stochastic simulation of the RNAi system (using the Gillespie stochastic simulator) to study the overall potency effect. We observed that the stochasticity in the transcription/translation machinery has no observable effects in the RNAi pathway. Sustained gene silencing using siRNAs can be achieved only if there is a way to replenish the dsRNA molecules in the cell. Initial findings show about 1.5 times more blunt-ended molecules will be required to keep the mRNA at the same reduced level compared to the 2-nt overhang siRNAs. However, the mRNA levels jump back to saturation after a longer time when blunt-ended siRNAs are used. We found that the siRNA-RISC complex formation reaction rate was 2 times slower when blunt-ended molecules were used pointing to the fact that the presence of the 2-nt overhangs has a greater effect on the reaction in which the bound RISC complex cleaves the mRNA.

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Drug-induced cardiac toxicity has been implicated in 31% of drug withdrawals in the USA. The fact that the risk for cardiac-related adverse events goes undetected in preclinical studies for so many drugs underscores the need for better, more predictive in vitro safety screens to be deployed early in the drug discovery process. Unfortunately, many questions remain about the ability to accurately translate findings from simple cellular systems to the mechanisms that drive toxicity in the complex in vivo environment. In this study, we analyzed translatability of cardiotoxic effects for a diverse set of drugs from rodents to two different cell systems (rat heart tissue-derived cells (H9C2) and primary rat cardiomyocytes (RCM)) based on their transcriptional response. To unravel the altered pathway, we applied a novel computational systems biology approach, the Causal Reasoning Engine (CRE), to infer upstream molecular events causing the observed gene expression changes. By cross-referencing the cardiotoxicity annotations with the pathway analysis, we found evidence of mechanistic convergence towards common molecular mechanisms regardless of the cardiotoxic phenotype. We also experimentally verified two specific molecular hypotheses that translated well from in vivo to in vitro (Kruppel-like factor 4, KLF4 and Transforming growth factor beta 1, TGFB1) supporting the validity of the predictions of the computational pathway analysis. In conclusion, this work demonstrates the use of a novel systems biology approach to predict mechanisms of toxicity such as KLF4 and TGFB1 that translate from in vivo to in vitro. We also show that more complex in vitro models such as primary rat cardiomyocytes may not offer any advantage over simpler models such as immortalized H9C2 cells in terms of translatability to in vivo effects if we consider the right endpoints for the model. Further assessment and validation of the generated molecular hypotheses would greatly enhance our ability to design predictive in vitro cardiotoxicity assays.

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