Stephen A. Ramsey

Function of C/EBPdelta in a regulatory circuit that discriminates between transient and persistent TLR4-induced signals.

The innate immune system is like a double-edged sword: it is absolutely required for host defense against infection, but when uncontrolled, it can trigger a plethora of inflammatory diseases. Here we use systems-biology approaches to predict and confirm the existence of a gene-regulatory network involving dynamic interaction among the transcription factors NF-κB, C/EBPδ and ATF3 that controls inflammatory responses. We mathematically modeled transcriptional regulation of the genes encoding interleukin 6 and C/EBPδ and experimentally confirmed the prediction that the combination of an initiator (NF-κB), an amplifier (C/EBPδ) and an attenuator (ATF3) forms a regulatory circuit that discriminates between transient and persistent Toll-like receptor 4–induced signals. Our results suggest a mechanism that enables the innate immune system to detect the duration of infection and to respond appropriately.

DIZZY: STOCHASTIC SIMULATION OF LARGE-SCALE GENETIC REGULATORY NETWORKS

We describe Dizzy, a software tool for stochastically and deterministically modeling the spatially homogeneous kinetics of integrated large-scale genetic, metabolic, and signaling networks. Notable features include a modular simulation framework, reusable modeling elements, complex kinetic rate laws, multi-step reaction processes, steady-state noise estimation, and spatial compartmentalization.

Uncovering a Macrophage Transcriptional Program by Integrating Evidence from Motif Scanning and Expression Dynamics

Macrophages are versatile immune cells that can detect a variety of pathogen-associated molecular patterns through their Toll-like receptors (TLRs). In response to microbial challenge, the TLR-stimulated macrophage undergoes an activation program controlled by a dynamically inducible transcriptional regulatory network. Mapping a complex mammalian transcriptional network poses significant challenges and requires the integration of multiple experimental data types. In this work, we inferred a transcriptional network underlying TLR-stimulated murine macrophage activation. Microarray-based expression profiling and transcription factor binding site motif scanning were used to infer a network of associations between transcription factor genes and clusters of co-expressed target genes. The time-lagged correlation was used to analyze temporal expression data in order to identify potential causal influences in the network. A novel statistical test was developed to assess the significance of the time-lagged correlation. Several associations in the resulting inferred network were validated using targeted ChIP-on-chip experiments. The network incorporates known regulators and gives insight into the transcriptional control of macrophage activation. Our analysis identified a novel regulator (TGIF1) that may have a role in macrophage activation.

Gene expression dynamics in the macrophage exhibit criticality

Cells are dynamical systems of biomolecular interactions that process information from their environment to mount diverse yet specific responses. A key property of many self-organized systems is that of criticality: a state of a system in which, on average, perturbations are neither dampened nor amplified, but are propagated over long temporal or spatial scales. Criticality enables the coordination of complex macroscopic behaviors that strike an optimal balance between stability and adaptability. It has long been hypothesized that biological systems are critical. Here, we address this hypothesis experimentally for system-wide gene expression dynamics in the macrophage. To this end, we have developed a method, based on algorithmic information theory, to assess macrophage criticality, and we have validated the method on networks with known properties. Using global gene expression data from macrophages stimulated with a variety of Toll-like receptor agonists, we found that macrophage dynamics are indeed critical, providing the most compelling evidence to date for this general principle of dynamics in biological systems.

Enhanced sensitivity of lateral flow tests using a two-dimensional paper network format.

Point-of-care diagnostic assays that are rapid, easy-to-use, and low-cost are needed for use in low-resource settings; the lateral flow test has become the standard bioassay format in such settings because it meets those criteria. However, for a number of analytes, conventional lateral flow tests lack the sensitivity needed to have clinical utility. To address this limitation, we are developing a paper network platform that extends the conventional lateral flow test to two dimensions. The two-dimensional structures allow incorporation of multistep processes for improved sensitivity, while still retaining the positive aspects of conventional lateral flow tests. Here we create an easy-to-use, signal-amplified immunoassay based on a modified commercial strip test for human chorionic gonadotropin, the hormone used to detect pregnancy, and demonstrate an improved limit of detection compared to a conventional lateral flow assay. These results highlight the potential of the paper network platform to enhance access to high-quality diagnostic capabilities in low-resource settings in the developed and developing worlds.

ATF3, an adaptive-response gene, enhances TGFβ signaling and cancer-initiating cell features in breast cancer cells

The activating transcription factor 3 (ATF3) gene is induced by a variety of signals, including many of those encountered by cancer cells. We present evidence that ATF3 is induced by TGFβ in the MCF10CA1a breast cancer cells and plays an integral role for TGFβ to upregulate its target genes snail, slug and twist, and to enhance cell motility. Furthermore, ATF3 upregulates the expression of the TGFb gene itself, forming a positive-feedback loop for TGFβ signaling. Functionally, ectopic expression of ATF3 leads to morphological changes and alterations of markers consistent with epithelial-to-mesenchymal transition (EMT). It also leads to features associated with breast-cancer-initiating cells: increased CD24low–CD44high population of cells, mammosphere formation and tumorigenesis. Conversely, knockdown of ATF3 reduces EMT, CD24low–CD44high cells and mammosphere formation. Importantly, knocking down twist, a downstream target, reduces the ability of ATF3 to enhance mammosphere formation, indicating the functional significance of twist in ATF3 action. To our knowledge, this is the first report demonstrating the ability of ATF3 to enhance breast cancer-initiating cell features and to feedback on TGFβ. Because ATF3 is an adaptive-response gene and is induced by various stromal signals, these findings have significant implications for how the tumor microenvironment might affect cancer development.

Cholesterol Loading Reprograms the MicroRNA-143/145–Myocardin Axis to Convert Aortic Smooth Muscle Cells to a Dysfunctional Macrophage-Like Phenotype

Objective— We previously showed that cholesterol loading in vitro converts mouse aortic vascular smooth muscle cells (VSMC) from a contractile state to one resembling macrophages. In human and mouse atherosclerotic plaques, it has become appreciated that ≈40% of cells classified as macrophages by histological markers may be of VSMC origin. Therefore, we sought to gain insight into the molecular regulation of this clinically relevant process. Approach and Results— VSMC of mouse (or human) origin were incubated with cyclodextrin–cholesterol complexes for 72 hours, at which time the expression at the protein and mRNA levels of contractile-related proteins was reduced and of macrophage markers increased. Concurrent was downregulation of miR-143/145, which positively regulate the master VSMC differentiation transcription factor myocardin. Mechanisms were further probed in mouse VSMC. Maintaining the expression of myocardin or miR-143/145 prevented and reversed phenotypic changes caused by cholesterol loading. Reversal was also seen when cholesterol efflux was stimulated after loading. Notably, despite expression of macrophage markers, bioinformatic analyses showed that cholesterol-loaded cells remained closer to the VSMC state, consistent with impairment in classical macrophage functions of phagocytosis and efferocytosis. In apoE-deficient atherosclerotic plaques, cells positive for VSMC and macrophage markers were found lining the cholesterol-rich necrotic core. Conclusions— Cholesterol loading of VSMC converts them to a macrophage-appearing state by downregulating the miR-143/145–myocardin axis. Although these cells would be classified by immunohistochemistry as macrophages in human and mouse plaques, their transcriptome and functional properties imply that their contributions to atherogenesis would not be those of classical macrophages.

Dual feedback loops in the GAL regulon suppress cellular heterogeneity in yeast.

Transcriptional noise is known to be an important cause of cellular heterogeneity and phenotypic variation. The extent to which molecular interaction networks may have evolved to either filter or exploit transcriptional noise is a much debated question. The yeast genetic network regulating galactose metabolism involves two proteins, Gal3p and Gal80p, that feed back positively and negatively, respectively, on GAL gene expression. Using kinetic modeling and experimental validation, we demonstrate that these feedback interactions together are important for (i) controlling the cell-to-cell variability of GAL gene expression and (ii) ensuring that cells rapidly switch to an induced state for galactose uptake.

ATF3 protects against atherosclerosis by suppressing 25-hydroxycholesterol–induced lipid body formation

The transcription factor ATF3 inhibits lipid body formation in macrophages during atherosclerosis in part by dampening the expression of cholesterol 25-hydroxylase.

A systems biology approach to understanding atherosclerosis

Atherosclerosis, a chronic inflammatory disease of the vascular system, presents significant challenges to developing effective molecular diagnostics and novel therapies. A systems biology approach integrating data from large‐scale measurements (e.g. transcriptomics, proteomics and genomics) is successfully contributing to deciphering regulatory networks underlying the response of many different cellular systems to perturbations. Such a network analysis strategy using pathway information and data from multiple measurement platforms, tissues and species is a promising approach to elucidate the mechanistic underpinnings of complex diseases. Here, we present our views on the contributions that a systems approach can bring to the study of atherosclerosis, propose ways to tackle the complexity of the disease in a systems manner and review recent systems‐level studies of the disease.