New era of optogenetics: from the central to peripheral nervous system

Abstract

Optogenetics has recently gained recognition as a biological technique to control the activity of cells using light stimulation. Many studies have applied optogenetics to cell lines in the central nervous system because it has the potential to elucidate neural circuits, treat neurological diseases and promote nerve regeneration. There have been fewer studies on the application of optogenetics in the peripheral nervous system. This review introduces the basic principles and approaches of optogenetics and summarizes the physiology and mechanism of opsins and how the technology enables bidirectional control of unique cell lines with superior spatial and temporal accuracy. Further, this review explores and discusses the therapeutic potential for the development of optogenetics and its capacity to revolutionize treatment for refractory epilepsy, depression, pain, and other nervous system disorders, with a focus on neural regeneration, especially in the peripheral nervous system. Additionally, this review synthesizes the latest preclinical research on optogenetic stimulation, including studies on non-human primates, summarizes the challenges, and highlights future perspectives. The potential of optogenetic stimulation to optimize therapy for peripheral nerve injuries (PNIs) is also highlighted. Optogenetic technology has already generated exciting, preliminary evidence, supporting its role in applications to several neurological diseases, including PNIs.     

光敏感通道(Channelrhodopsin-2)——神经回路功能和神经系统疾病研究的新工具

光敏感通道(channelrhodopsin-2,ChR2)是一种受光脉冲控制的具有7次跨膜结构的非选择性阳离子通道蛋白,自1991年从莱茵衣藻中发现后被许多实验室所关注.依据ChR2可以快速形成光电流,使细胞发生去极化反应的电生理特性,ChR2已被广泛应用于神经系统的研究.与传统的神经系统研究方法如电生理技术、神经药理学方法相比,用光脉冲控制带有ChR2的神经元的活动,具有更高的空间选择性和特异性.ChR2作为光基因技术的核心组成部分,对神经科学是一个崭新的应用前景广泛的研究工具.近年来ChR2不仅应用于视觉、躯体感觉、听觉和嗅觉等多条感觉神经回路的形态和功能研究,还被应用于各种临床神经系统疾病的研究.本文总结了目前ChR2在神经系统中的研究进展,并对ChR2未来的应用前景作了进一步展望.     

上转换纳米颗粒介导的无线光遗传学技术的研究进展

光遗传学技术是结合基因工程和光学技术对生物体特定细胞进行精确调控的新兴生物技术,该技术可以特异性地兴奋或抑制靶神经元,成为解析介导特定行为神经环路的强有力的工具.传统技术依赖光纤,对脑组织有损伤且限制了动物的自由活动.新一代上转换纳米颗粒介导的无线光遗传学技术,借助近红外光组织穿透相对深的特性,能够对啮齿类动物脑组织深层核团进行无线调控,克服了传统技术中埋置光纤存在的缺陷.本文总结了上转换纳米颗粒介导的无线光遗传学技术的发展历程及现状,比较分析了这类无线光遗传学技术的优缺点,最后对该技术面临的挑战及未来前景进行了分析和展望.     

Illuminating neural circuits and behaviour in Caenorhabditis elegans with optogenetics

The development of optogenetics, a family of methods for using light to control neural activity via light-sensitive proteins, has provided a powerful new set of tools for neurobiology. These techniques have been particularly fruitful for dissecting neural circuits and behaviour in the compact and transparent roundworm Caenorhabditis elegans. Researchers have used optogenetic reagents to manipulate numerous excitable cell types in the worm, from sensory neurons, to interneurons, to motor neurons and muscles. Here, we show how optogenetics applied to this transparent roundworm has contributed to our understanding of neural circuits.     

Graph theoretical analysis of complex networks in the brain

Since the discovery of small-world and scale-free networks the study of complex systems from a network perspective has taken an enormous flight. In recent years many important properties of complex networks have been delineated. In particular, significant progress has been made in understanding the relationship between the structural properties of networks and the nature of dynamics taking place on these networks. For instance, the 'synchronizability' of complex networks of coupled oscillators can be determined by graph spectral analysis. These developments in the theory of complex networks have inspired new applications in the field of neuroscience. Graph analysis has been used in the study of models of neural networks, anatomical connectivity, and functional connectivity based upon fMRI, EEG and MEG. These studies suggest that the human brain can be modelled as a complex network, and may have a small-world structure both at the level of anatomical as well as functional connectivity. This small-world structure is hypothesized to reflect an optimal situation associated with rapid synchronization and information transfer, minimal wiring costs, as well as a balance between local processing and global integration. The topological structure of functional networks is probably restrained by genetic and anatomical factors, but can be modified during tasks. There is also increasing evidence that various types of brain disease such as Alzheimer's disease, schizophrenia, brain tumours and epilepsy may be associated with deviations of the functional network topology from the optimal small-world pattern.     

Yeast proteomics and protein microarrays

Our understanding of biological processes as well as human diseases has improved greatly thanks to studies on model organisms such as yeast. The power of scientific approaches with yeast lies in its relatively simple genome, its facile classical and molecular genetics, as well as the evolutionary conservation of many basic biological mechanisms. However, even in this simple model organism, systems biology studies, especially proteomic studies had been an intimidating task. During the past decade, powerful high-throughput technologies in proteomic research have been developed for yeast including protein microarray technology. The protein microarray technology allows the interrogation of protein–protein, protein–DNA, protein–small molecule interaction networks as well as post-translational modification networks in a large-scale, high-throughput manner. With this technology, many groundbreaking findings have been established in studies with the budding yeast Saccharomyces cerevisiae, most of which could have been unachievable with traditional approaches. Discovery of these networks has profound impact on explicating biological processes with a proteomic point of view, which may lead to a better understanding of normal biological phenomena as well as various human diseases.     

Development of larval motor circuits in Drosophila

How are functional neural circuits formed during development? Despite recent advances in our understanding of the development of individual neurons, little is known about how complex circuits are assembled to generate specific behaviors. Here, we describe the ways in which Drosophila motor circuits serve as an excellent model system to tackle this problem. We first summarize what has been learned during the past decades on the connectivity and development of component neurons, in particular motor neurons and sensory feedback neurons. We then review recent progress in our understanding of the development of the circuits as well as studies that apply optogenetics and other innovative techniques to dissect the circuit diagram. New approaches using Drosophila as a model system are now making it possible to search for developmental rules that regulate the construction of neural circuits.     

Principles of diffusion tensor imaging and its applications to basic neuroscience research

The brain contains more than 100 billion neurons that communicate with each other via axons for the formation of complex neural networks. The structural mapping of such networks during health and disease states is essential for understanding brain function. However, our understanding of brain structural connectivity is surprisingly limited, due in part to the lack of noninvasive methodologies to study axonal anatomy. Diffusion tensor imaging (DTI) is a recently developed MRI technique that can measure macroscopic axonal organization in nervous system tissues. In this article, the principles of DTI methodologies are explained, and several applications introduced, including visualization of axonal tracts in myelin and axonal injuries as well as human brain and mouse embryonic development. The strengths and limitations of DTI and key areas for future research and development are also discussed.     

Optogenetics in neural systems

Both observational and perturbational technologies are essential for advancing the understanding of brain function and dysfunction. But while observational techniques have greatly advanced in the last century, techniques for perturbation that are matched to the speed and heterogeneity of neural systems have lagged behind. The technology of optogenetics represents a step toward addressing this disparity. Reliable and targetable single-component tools (which encompass both light sensation and effector function within a single protein) have enabled versatile new classes of investigation in the study of neural systems. Here we provide a primer on the application of optogenetics in neuroscience, focusing on the single-component tools and highlighting important problems, challenges, and technical considerations.     

The dynamics of sparse random networks

Recurrent neural networks with full symmetric connectivity have been extensively studied as associative memories and pattern recognition devices. However, there is considerable evidence that sparse, asymmetrically connected, mainly excitatory networks with broadly directed inhibition are more consistent with biological reality. In this paper, we use the technique of return maps to study the dynamics of random networks with sparse, asymmetric connectivity and nonspecific inhibition. These networks show three qualitatively different kinds of behavior: fixed points, cycles of low period, and extremely long cycles verging on aperiodicity. Using statistical arguments, we relate these behaviors to network parameters and present empirical evidence for the accuracy of this statistical model. The model, in turn, leads to methods for controlling the level of activity in networks. Studying random, untrained networks provides an understanding of the intrinsic dynamics of these systems. Such dynamics could provide a substrate for the much more complex behavior shown when synaptic modification is allowed.     

Analysis of context dependence in social interaction networks of a massively multiplayer online role-playing game

Rapid advances in modern computing and information technology have enabled millions of people to interact online via various social network and gaming services. The widespread adoption of such online services have made possible analysis of large-scale archival data containing detailed human interactions, presenting a very promising opportunity to understand the rich and complex human behavior. In collaboration with a leading global provider of Massively Multiplayer Online Role-Playing Games (MMORPGs), here we present a network science-based analysis of the interplay between distinct types of user interaction networks in the virtual world. We find that their properties depend critically on the nature of the context-interdependence of the interactions, highlighting the complex and multilayered nature of human interactions, a robust understanding of which we believe may prove instrumental in the designing of more realistic future virtual arenas as well as provide novel insights to the science of collective human behavior.     

Neural regulation of bone remodeling: Identifying novel neural molecules and pathways between brain and bone

The metabolism and homeostasis of the skeletal system have historically been considered to be associated with the endocrine system. However, this view has been expanded with the recognition of several neural pathways playing important roles in the regulation of bone metabolism via central relays. In particular, bone metabolism and homeostasis have been reported to be precisely modulated by the central neural signaling. Initiated by the finding of leptin, the axis of neural regulation on bone expands rapidly. The semaphorin–plexin system plays an important role in the cross-talk between osteoclasts and osteoblasts; a complex system has also been identified and includes neuropeptide Y and cannabinoids. These findings facilitate our understanding of the central neuropeptides and neural factors in the modulation of bone metabolism and homeostasis, and these neuronal pathways also represent an area of research scenario that identifies the novel regulation between brain and bone. These regulatory mechanisms correlate with other homeostatic networks and demonstrate a more intricate and synergetic bone biology than previously envisioned. As such, this review summarizes the current knowledge of the neural regulation of bone metabolism and homeostasis, as well as its role in skeletal diseases and discusses the emerging challenges presented in this field.     

Dynamics and regulation of contractile actin-myosin networks in morphogenesis

Contractile actin-myosin networks generate forces that drive cell shape changes and tissue remodeling during development. These forces can also actively regulate cell signaling and behavior. Novel features of actin-myosin network dynamics, such as pulsed contractile behaviors and the regulation of myosin localization by tension, have been uncovered in recent studies of Drosophila. In vitro studies of single molecules and reconstituted protein networks reveal intrinsic properties of motor proteins and actin-myosin networks, while in vivo studies have provided insight into the regulation of their dynamics and organization. Analysis of the complex behaviors of actin-myosin networks will be crucial for understanding force generation in actively remodeling cells and the coordination of cell shape and movement at the tissue level.     

Decoding defensive systems

Our understanding of the neuronal circuits and mechanisms of defensive systems has been primarily dominated by studies focusing on the contribution of individual cells in the processing of threat-predictive cues, defensive responses, the extinction of such responses and the contextual modulation of threat-related behavior. These studies have been key in establishing threat-related circuits and mechanisms. Yet, they fall short in answering long-standing questions related to the integrative processing of distinct threatening cues, behavioral states induced by threat-related events, or the bridging from sensory processing of threat-related cues to specific defensive responses. Recent conceptual and technical developments has allowed the monitoring of large populations of neurons, which in addition to advanced analytic tools, have improved our understanding of how collective neuronal activity supports threat-related behaviors. In this review, we discuss the current knowledge of neuronal population codes within threat-related networks, in the context of aversive motivated behavior and the study of defensive systems.     

Pump-like channelrhodopsins: Not just bridging the gap between ion pumps and ion channels

Channelrhodopsins are microbial rhodopsins that work as light-gated ion channels. Their importance has become increasingly recognized due to their ability to control the membrane potential of specific cells in a light-dependent manner. This technology, termed optogenetics, has revolutionized neuroscience, and numerous channelrhodopsin variants have been isolated or engineered to expand the utility of optogenetics. Pump-like channelrhodopsins (PLCRs), one of the recently discovered channelrhodopsin subfamilies, have attracted broad attention due to their high sequence similarity to ion-pumping rhodopsins and their distinct properties, such as high light sensitivity and ion selectivity. In this review, we summarize the current understanding of the structure-function relationships of PLCRs and discuss the challenges and opportunities of channelrhodopsin research.     

光遗传学

虽然＂光遗传学＂只是一种技术方法,但它在文献中正愈来愈多地被提到。光遗传学结合了重组DNA技术与光学技术,对细胞生物学的研究非常有用。它被广泛应用于活细胞内目标蛋白质的跟踪以及选择性地控制脑中某类细胞的特定的神经活动从而推动了神经科学研究的深入。近来光遗传学的应用扩展到了信号转导的研究,也开始有医学临床的应用的报道。进一步发展光遗传学无疑将推动合成生理学的研究。光遗传学被《自然-方法学》期刊评为2010年年度方法。     

Organization of excitable dynamics in hierarchical biological networks

This study investigates the contributions of network topology features to the dynamic behavior of hierarchically organized excitable networks. Representatives of different types of hierarchical networks as well as two biological neural networks are explored with a three-state model of node activation for systematically varying levels of random background network stimulation. The results demonstrate that two principal topological aspects of hierarchical networks, node centrality and network modularity, correlate with the network activity patterns at different levels of spontaneous network activation. The approach also shows that the dynamic behavior of the cerebral cortical systems network in the cat is dominated by the network's modular organization, while the activation behavior of the cellular neuronal network of Caenorhabditis elegans is strongly influenced by hub nodes. These findings indicate the interaction of multiple topological features and dynamic states in the function of complex biological networks.     

The graph theoretical analysis of the SSVEP harmonic response networks

Steady-state visually evoked potentials (SSVEP) have been widely used in the neural engineering and cognitive neuroscience researches. Previous studies have indicated that the SSVEP fundamental frequency responses are correlated with the topological properties of the functional networks entrained by the periodic stimuli. Given the different spatial and functional roles of the fundamental frequency and harmonic responses, in this study we further investigated the relation between the harmonic responses and the corresponding functional networks, using the graph theoretical analysis. We found that the second harmonic responses were positively correlated to the mean functional connectivity, clustering coefficient, and global and local efficiencies, while negatively correlated with the characteristic path lengths of the corresponding networks. In addition, similar pattern occurred with the lowest stimulus frequency (6.25 Hz) at the third harmonic responses. These findings demonstrate that more efficient brain networks are related to larger SSVEP responses. Furthermore, we showed that the main connection pattern of the SSVEP harmonic response networks originates from the interactions between the frontal and parietal–occipital regions. Overall, this study may bring new insights into the understanding of the brain mechanisms underlying SSVEP.