Dongkwan Shin

A design principle underlying the synchronization of oscillations in cellular systems.

Biological oscillations are found ubiquitously in cells and are widely variable, with periods varying from milliseconds to months, and scales involving subcellular components to large groups of organisms. Interestingly, independent oscillators from different cells often show synchronization that is not the consequence of an external regulator. What is the underlying design principle of such synchronized oscillations, and can modeling show that the complex consequences arise from simple molecular or other interactions between oscillators? When biological oscillators are coupled with each other, we found that synchronization is induced when they are connected together through a positive feedback loop. Increasing the coupling strength of two independent oscillators shows a threshold beyond which synchronization occurs within a few cycles, and a second threshold where oscillation stops. The positive feedback loop can be composed of either double-positive (PP) or double-negative (NN) interactions between a node of each of the two oscillating networks. The different coupling structures have contrasting characteristics. In particular, PP coupling is advantageous with respect to stability of period and amplitude, when local oscillators are coupled with a short time delay, whereas NN coupling is advantageous for a long time delay. In addition, PP coupling results in more robust synchronized oscillations with respect to amplitude excursions but not period, with applied noise disturbances compared to NN coupling. However, PP coupling can induce a large fluctuation in the amplitude and period of the resulting synchronized oscillation depending on the coupling strength, whereas NN coupling ensures almost constant amplitude and period irrespective of the coupling strength. Intriguingly, we have also observed that artificial evolution of random digital oscillator circuits also follows this design principle. We conclude that a different coupling strategy might have been selected according to different evolutionary requirements.

Small-world networks in individuals at ultra-high risk for psychosis and first-episode schizophrenia during a working memory task

Disturbances of functional interaction between different brain regions have been hypothesized to be the major pathophysiological mechanism underlying the cognitive deficits of schizophrenia. We investigated the small-world functional networks in individuals at ultra-high risk (UHR) for psychosis, first-episode schizophrenia (FESPR) patients, and healthy controls. All participants underwent the electroencephalogram during a control task and a working memory (WM) task. Small-world properties of the theta band were reduced in FESPR relative to controls during the WM task. Small-worldness of the UHR during the WM task exhibited intermediate value between that of controls and FESPR. These results imply that the suboptimal organization of the brain network may play a pivotal role in the schizophrenia pathophysiology.

Impaired coupling of local and global functional feedbacks underlies abnormal synchronization and negative symptoms of schizophrenia

BackgroundAbnormal synchronization of brain oscillations is found to be associated with various core symptoms of schizophrenia. However, the underlying mechanism of this association remains yet to be elucidated.ResultsIn this study, we found that coupled local and global feedback (CLGF) circuits in the cortical functional network are related to the abnormal synchronization and also correlated to the negative symptom of schizophrenia. Analysis of the magnetoencephalography data obtained from patients with chronic schizophrenia during rest revealed an increase in beta band synchronization and a reduction in gamma band power compared to healthy controls. Using a feedback identification method based on non-causal impulse responses, we constructed functional feedback networks and found that CLGF circuits were significantly reduced in schizophrenia. From computational analysis on the basis of the Wilson-Cowan model, we unraveled that the CLGF circuits are critically involved in the abnormal synchronization and the dynamical switching between beta and gamma bands power in schizophrenia. Moreover, we found that the abundance of CLGF circuits was negatively correlated with the development of negative symptoms of schizophrenia, suggesting that the negative symptom is closely related to the impairment of this circuit.ConclusionsOur study implicates that patients with schizophrenia might have the impaired coupling of inter- and intra-regional functional feedbacks and that the CLGF circuit might serve as a critical bridge between abnormal synchronization and the negative symptoms of schizophrenia.

Identification of feedback loops in neural networks based on multi-step Granger causality

MOTIVATION Feedback circuits are crucial network motifs, ubiquitously found in many intra- and inter-cellular regulatory networks, and also act as basic building blocks for inducing synchronized bursting behaviors in neural network dynamics. Therefore, the system-level identification of feedback circuits using time-series measurements is critical to understand the underlying regulatory mechanism of synchronized bursting behaviors. RESULTS Multi-Step Granger Causality Method (MSGCM) was developed to identify feedback loops embedded in biological networks using time-series experimental measurements. Based on multivariate time-series analysis, MSGCM used a modified Wald test to infer the existence of multi-step Granger causality between a pair of network nodes. A significant bi-directional multi-step Granger causality between two nodes indicated the existence of a feedback loop. This new identification method resolved the drawback of the previous non-causal impulse response component method which was only applicable to networks containing no co-regulatory forward path. MSGCM also significantly improved the ratio of correct identification of feedback loops. In this study, the MSGCM was testified using synthetic pulsed neural network models and also in vitro cultured rat neural networks using multi-electrode array. As a result, we found a large number of feedback loops in the in vitro cultured neural networks with apparent synchronized oscillation, indicating a close relationship between synchronized oscillatory bursting behavior and underlying feedback loops. The MSGCM is an efficient method to investigate feedback loops embedded in in vitro cultured neural networks. The identified feedback loop motifs are considered as an important design principle responsible for the synchronized bursting behavior in neural networks.

The reverse control of irreversible biological processes

Most biological processes have been considered to be irreversible for a long time, but some recent studies have shown the possibility of their reversion at a cellular level. How can we then understand the reversion of such biological processes? We introduce a unified conceptual framework based on the attractor landscape, a molecular phase portrait describing the dynamics of a molecular regulatory network, and the phenotype landscape, a map of phenotypes determined by the steady states of particular output molecules in the attractor landscape. In this framework, irreversible processes involve reshaping of the phenotype landscape, and the landscape reshaping causes the irreversibility of processes. We suggest reverse control by network rewiring which changes network dynamics with constant perturbation, resulting in the restoration of the original phenotype landscape. The proposed framework provides a conceptual basis for the reverse control of irreversible biological processes through network rewiring. WIREs Syst Biol Med 2016, 8:366–377. doi: 10.1002/wsbm.1346

Recurrent connections form a phase-locking neuronal tuner for frequency-dependent selective communication

The brain requires task-dependent interregional coherence of information flow in the anatomically connected neural network. However, it is still unclear how a neuronal group can flexibly select its communication target. In this study, we revealed a hidden routing mechanism on the basis of recurrent connections. Our simulation results based on the spike response model show that recurrent connections between excitatory and inhibitory neurons modulate the resonant frequency of a local neuronal group, and that this modulation enables a neuronal group to receive selective information by filtering a preferred frequency component. We also found that the recurrent connection facilitates the successful routing of any necessary information flow between neuronal groups through frequency-dependent resonance of synchronized oscillations. Taken together, these results suggest that recurrent connections act as a phase-locking neuronal tuner which determines the resonant frequency of a local group and thereby controls the preferential routing of incoming signals.

Percolation transition of cooperative mutational effects in colorectal tumorigenesis

Cancer is caused by the accumulation of multiple genetic mutations, but their cooperative effects are poorly understood. Using a genome-wide analysis of all the somatic mutations in colorectal cancer patients in a large-scale molecular interaction network, here we find that a giant cluster of mutation-propagating modules in the network undergoes a percolation transition, a sudden critical transition from scattered small modules to a large connected cluster, during colorectal tumorigenesis. Such a large cluster ultimately results in a giant percolated cluster, which is accompanied by phenotypic changes corresponding to cancer hallmarks. Moreover, we find that the most commonly observed sequence of driver mutations in colorectal cancer has been optimized to maximize the giant percolated cluster. Our network-level percolation study shows that the cooperative effect rather than any single dominance of multiple somatic mutations is crucial in colorectal tumorigenesis.Cancer is caused by accumulating genetic mutations. Here, the authors investigate the cooperative effect of these mutations in colorectal cancer patients and identify a giant cluster of mutation-propagating modules that undergoes percolation transition during tumorigenesis.

A positive feedback loop bi-stably activates fibroblasts

Although fibroblasts are dormant in normal tissue, they exhibit explosive activation during wound healing and perpetual activation in pathologic fibrosis and cancer stroma. The key regulatory network controlling these fibroblast dynamics is still unknown. Here, we report that Twist1, a key regulator of cancer-associated fibroblasts, directly upregulates Prrx1, which, in turn, increases the expression of Tenascin-C (TNC). TNC also increases Twist1 expression, consequently forming a Twist1-Prrx1-TNC positive feedback loop (PFL). Systems biology studies reveal that the Twist1-Prrx1-TNC PFL can function as a bistable ON/OFF switch and regulates fibroblast activation. This PFL can be irreversibly activated under pathologic conditions, leading to perpetual fibroblast activation. Sustained activation of the Twist1-Prrx1-TNC PFL reproduces fibrotic nodules similar to idiopathic pulmonary fibrosis in vivo and is implicated in fibrotic disease and cancer stroma. Considering that this PFL is specific to activated fibroblasts, Twist1-Prrx1-TNC PFL may be a fibroblast-specific therapeutic target to deprogram perpetually activated fibroblasts.Normal adult tissue fibroblasts can be activated during wound healing, pathologic fibrosis and in cancer stroma, but the regulatory network that controls its dynamics is unknown. Here the authors show that fibroblasts are activated by a positive feedback loop formed by Twist1, Prrx1, and Tenascin-C bi-stably.