Systems biology. Customized signaling circuits

Predictive network modeling in human induced pluripotent stem cells identifies key driver genes for insulin responsiveness

Insulin resistance (IR) precedes the development of type 2 diabetes (T2D) and increases cardiovascular disease risk. Although genome wide association studies (GWAS) have uncovered new loci associated with T2D, their contribution to explain the mechanisms leading to decreased insulin sensitivity has been very limited. Thus, new approaches are necessary to explore the genetic architecture of insulin resistance. To that end, we generated an iPSC library across the spectrum of insulin sensitivity in humans. RNA-seq based analysis of 310 induced pluripotent stem cell (iPSC) clones derived from 100 individuals allowed us to identify differentially expressed genes between insulin resistant and sensitive iPSC lines. Analysis of the co-expression architecture uncovered several insulin sensitivity-relevant gene sub-networks, and predictive network modeling identified a set of key driver genes that regulate these co-expression modules. Functional validation in human adipocytes and skeletal muscle cells (SKMCs) confirmed the relevance of the key driver candidate genes for insulin responsiveness.

Insulin resistance is characterized by a defective response (“resistance”) to normal insulin concentrations to uptake the glucose present in the blood, and is the underlying condition that leads to type 2 diabetes (T2D) and increases the risk of cardiovascular disease. It is estimated that 25–33% of the US population are insulin resistant enough to be at risk of serious clinical consequences. For more than a decade, large population studies have tried to discover the genes that participate in the development of insulin resistance, but without much success. It is now increasingly clear that the complex genetic nature of insulin resistance requires novel approaches centered in patient specific cellular models. To fill this gap, we have generated an induced pluripotent stem cell (iPSC) library from individuals with accurate measurements of insulin sensitivity, and performed gene expression and key driver analyses. Our work demonstrates that iPSCs can be used as a revolutionary technology to model insulin resistance and to discover key genetic drivers. Moreover, they can develop our basic knowledge of the disease, and are ultimately expected to increase the therapeutic targets to treat insulin resistance and type 2 diabetes.

Heterosis Is a Systemic Property Emerging From Non-linear Genotype-Phenotype Relationships: Evidence From in Vitro Genetics and Computer Simulations

Heterosis, the superiority of hybrids over their parents for quantitative traits, represents a crucial issue in plant and animal breeding as well as evolutionary biology. Heterosis has given rise to countless genetic, genomic and molecular studies, but has rarely been investigated from the point of view of systems biology. We hypothesized that heterosis is an emergent property of living systems resulting from frequent concave relationships between genotypic variables and phenotypes, or between different phenotypic levels. We chose the enzyme-flux relationship as a model of the concave genotype-phenotype (GP) relationship, and showed that heterosis can be easily created in the laboratory. First, we reconstituted in vitro the upper part of glycolysis. We simulated genetic variability of enzyme activity by varying enzyme concentrations in test tubes. Mixing the content of "parental" tubes resulted in "hybrids," whose fluxes were compared to the parental fluxes. Frequent heterotic fluxes were observed, under conditions that were determined analytically and confirmed by computer simulation. Second, to test this model in a more realistic situation, we modeled the glycolysis/fermentation network in yeast by considering one input flux, glucose, and two output fluxes, glycerol and acetaldehyde. We simulated genetic variability by randomly drawing parental enzyme concentrations under various conditions, and computed the parental and hybrid fluxes using a system of differential equations. Again we found that a majority of hybrids exhibited positive heterosis for metabolic fluxes. Cases of negative heterosis were due to local convexity between certain enzyme concentrations and fluxes. In both approaches, heterosis was maximized when the parents were phenotypically close and when the distributions of parental enzyme concentrations were contrasted and constrained. These conclusions are not restricted to metabolic systems: they only depend on the concavity of the GP relationship, which is commonly observed at various levels of the phenotypic hierarchy, and could account for the pervasiveness of heterosis.

The study on the material basis and the mechanism for anti-renal interstitial fibrosis efficacy of rhubarb through integration of metabonomics and network pharmacology

The cooperative material basis of the multi-component and multi-target mechanism of action of Traditional Chinese Medicine (TCM) is difficult to elucidate because of the current lack of appropriate techniques and strategies.

Cdc42p-interacting protein Bem4p regulates the filamentous-growth mitogen-activated protein kinase pathway

The ubiquitous Rho (Ras homology) GTPase Cdc42p can function in different settings to regulate cell polarity and cellular signaling. How Cdc42p and other proteins are directed to function in a particular context remains unclear. We show that the Cdc42p-interacting protein Bem4p regulates the mitogen-activated protein kinase (MAPK) pathway that controls filamentous growth in Saccharomyces cerevisiae. Bem4p controlled the filamentous-growth pathway but not other MAPK pathways (mating or high-osmolarity glycerol response [HOG]) that also require Cdc42p and other shared components. Bem4p associated with the plasma membrane (PM) protein, Sho1p, to regulate MAPK activity and cell polarization under nutrient-limiting conditions that favor filamentous growth. Bem4p also interacted with the major activator of Cdc42p, the guanine nucleotide exchange factor (GEF) Cdc24p, which we show also regulates the filamentous-growth pathway. Bem4p interacted with the pleckstrin homology (PH) domain of Cdc24p, which functions in an autoinhibitory capacity, and was required, along with other pathway regulators, to maintain Cdc24p at polarized sites during filamentous growth. Bem4p also interacted with the MAPK kinase kinase (MAPKKK) Ste11p. Thus, Bem4p is a new regulator of the filamentous-growth MAPK pathway and binds to general proteins, like Cdc42p and Ste11p, to promote a pathway-specific response.

Customizing the therapeutic response of signaling networks to promote antitumor responses by drug combinations

Drug resistance, de novo and acquired, pervades cellular signaling networks (SNs) from one signaling motif to another as a result of cancer progression and/or drug intervention. This resistance is one of the key determinants of efficacy in targeted anti-cancer drug therapy. Although poorly understood, drug resistance is already being addressed in combination therapy by selecting drug targets where SN sensitivity increases due to combination components or as a result of de novo or acquired mutations. Additionally, successive drug combinations have shown low resistance potential. To promote a rational, systematic development of combination therapies, it is necessary to establish the underlying mechanisms that drive the advantages of combination therapies, and design methods to determine drug targets for combination regimens. Based on a joint systems analysis of cellular SN response and its sensitivity to drug action and oncogenic mutations, we describe an in silico method to analyze the targets of drug combinations. Our method explores mechanisms of sensitizing the SN through a combination of two drugs targeting vertical signaling pathways. We propose a paradigm of SN response customization by one drug to both maximize the effect of another drug in combination and promote a robust therapeutic response against oncogenic mutations. The method was applied to customize the response of the ErbB/PI3K/PTEN/AKT pathway by combination of drugs targeting HER2 receptors and proteins in the down-stream pathway. The results of a computational experiment showed that the modification of the SN response from hyperbolic to smooth sigmoid response by manipulation of two drugs in combination leads to greater robustness in therapeutic response against oncogenic mutations determining cancer heterogeneity. The application of this method in drug combination co-development suggests a combined evaluation of inhibition effects together with the capability of drug combinations to suppress resistance mechanisms before they become clinically manifest.

Inhibition of EGF-induced ERK/MAP kinase-mediated astrocyte proliferation by mu opioids: integration of G protein and beta-arrestin 2-dependent pathways

Although micro, kappa, and delta opioids activate extracellular signal-regulated kinase (ERK)/mitogen-activated protein (MAP) kinase, the mechanisms involved in their signaling pathways and the cellular responses that ensue differ. Here we focused on the mechanisms by which micro opioids rapidly (min) activate ERK and their slower (h) actions to inhibit epidermal growth factor (EGF)-induced ERK-mediated astrocyte proliferation. The micro-opioid agonists ([d-ala(2), mephe(4), gly-ol(5)] enkephalin and morphine) promoted the phosphorylation of ERK/MAP kinase within 5 min via G(i/o) protein, calmodulin (CaM), and beta-arrestin2-dependent signaling pathways in immortalized and primary astrocytes. This was based on the attenuation of the micro-opioid activation of ERK by pertussis toxin (PTX), the CaM antagonist, W-7, and siRNA silencing of beta-arrestin2. All three pathways were shown to activate ERK via an EGF receptor transactivation-mediated mechanism. This was disclosed by abolishment of micro-opioid-induced ERK phosphorylation with the EGF receptor-specific tyrosine phosphorylation inhibitor, AG1478, and micro-opioid-induced reduction of EGF receptor tyrosine phosphorylation by PTX, and beta-arrestin2 targeting siRNA in the present studies and formerly by CaM antisense. Long-term (h) treatment of primary astrocytes with [d-ala(2),mephe(4),gly-ol(5)] enkephalin or morphine, attenuated EGF-induced ERK phosphorylation and proliferation (as measured by 5'-bromo-2'-deoxy-uridine labeling). PTX and beta-arrestin2 siRNA but not W-7 reversed the micro-opioid inhibition. Unexpectedly, beta-arrestin-2 siRNA diminished both EGF-induced ERK activation and primary astrocyte proliferation suggesting that this adaptor protein plays a novel role in EGF signaling as well as in the opioid receptor phase of this pathway. The results lend insight into the integration of the different micro-opioid signaling pathways to ERK and their cellular responses.