A widespread response of Gram-negative bacterial acyl-homoserine lactone receptors to Gram-positive Streptomyces γ-butyrolactone signaling molecules

Cell-cell communication is critical for bacterial survival in natural habitats, in which miscellaneous regulatory networks are encompassed. However, elucidating the interaction networks of a microbial community has been hindered by the population complexity. This study reveals that γ-butyrolactone(GBL) molecules from Streptomyces species, the major antibiotic producers,can directly bind to the acyl-homoserine lactone(AHL) receptor of Chromobacterium violaceum and influence violacein production controlled by the quorum sensing(QS) system. Subsequently, the widespread responses of more Gram-negative bacterial AHL receptors to Gram-positive Streptomyces signaling molecules are unveiled. Based on the cross-talk between GBL and AHL signaling systems, combinatorial regulatory circuits(CRC) are designed and proved to be workable in Escherichia coli(E. coli). It is significant that the QS systems of Gram-positive and Gram-negative bacteria can be bridged via native Streptomyces signaling molecules. These findings pave a new path for unlocking the comprehensive cell-cell communications in microbial communities and facilitate the exploitation of innovative regulatory elements for synthetic biology.     

Multilayer network analyses as a toolkit for measuring social structure

The formalization of multilayer networks allows for new ways to measure sociality in complex social systems,including groups of animals.The same mathematical representation and methods are widely applicable across fields and study systems,and a network can represent drastically different types of data.As such,in order to apply analyses and interpret the results in a meaningful way the researcher must have a deep understanding of what their network is representing and what parts of it are being measured by a given analysis.Multilayer social networks can represent social structure with more detail than is often present in single layer networks,including multiple"types"of individuals,interactions,or relationships,and the extent to which these types are interdependent.Multilayer networks can also encompass a wider range of social scales,which can help overcome complications that are inherent to measuring sociality.In this paper,I dissect multilayer networks into the parts that correspond to different components of social structures.I then discuss common pitfalls to avoid across different stages of multilayer network analyses-some novel and some that always exist in social network analysis but are magnified in multi-layer representations.This paper serves as a primer for building a customized toolkit of multilayer network analyses,to probe components of social structure in animal social systems.     

Robust delay-dependent stability of uncertain inertied neural networks with impulsive effects and distributed-delay

The robust stability problem of uncertain inertial neural networks with impulsive effects and distributed-delay is considered in the present paper.The average impulsive interval and differential inequality for delay differential equations are used to obtain the global exponential stability of the inertial neural networks.The robust distributed-delaydependent stability criteria here are proposed in terms of both linear matrix inequalities and algebraic inequalities.Our results can not only be used to obtain the stability of the uncertain inertial neural network with impulsive disturbance,but also be utilized to design the impulsive control for the uncertain inertial neural networks.The novel criteria complement and extend the previous works on uncertain inertial neural network with/without impulsive effects.Typical numerical examples are used to test the validity of the developed stability criteria finally.     

Origin of cells and network information

All cells are derived from one cell, and the origin of different cell types is a subject of curiosity. Cells construct life through appropriately timed networks at each stage of development. Communication among cells and intracellular signaling are essential for cell differentiation and for life processes. Cellular molecular networks establish cell diversity and life. The investigation of the regulation of each gene in the genome within the cellular network is therefore of interest. Stem cells produce various cells that are suitable for specific purposes. The dynamics of the information in the cellular network changes as the status of cells is altered. The components of each cell are subject to investigation.     

B-cell ligand processing pathways detected by large-scale comparative analysis

The initiation of B-cell ligand recognition is a critical step for the generation of an immune response against foreign bodies.We sought to identify the biochemical pathways involved in the B-cell ligand recognition cascade and sets of ligands that trigger similar immunological responses.We utilized several comparative approaches to analyze the gene coexpression networks generated from a set of microarray experiments spanning 33 different ligands.First,we compared the degree distributions of the generated networks.Second,we utilized a pairwise network alignment algorithm,BiNA,to align the networks based on the hubs in the networks.Third,we aligned the networks based on a set of K_EGG pathways.We summarized our results by constructing a consensus hierarchy of pathways that are involved in B cell ligand recognition.The resulting pathways were further validated through literature for their common physiological responses.Collectively,the results based on our comparative analyses of degree distributions,alignment of hubs,and alignment based on KEGG pathways provide a basis for molecular characterization of the immune response states of B-cells and demonstrate the power of comparative approaches(e.g.,gene coexpression network alignment algorithms) in elucidating biochemical pathways involved in complex signaling events in cells.     

Interactome Mapping: Using Protein Microarray Technology to Reconstruct Diverse Protein Networks

A major focus of systems biology is to characterize interactions between cellular components, in order to develop an accurate picture of the intricate networks within biological systems. Over the past decade, protein microarrays have greatly contributed to advances in proteomics and are becoming an important platform for systems biology. Protein microarrays are highly flexible, ranging from large-scale proteome microarrays to smaller customizable microarrays, making the technology amenable for detection of a broad spectrum of biochemical properties of proteins. In this article, we will focus on the numerous studies that have utilized protein microarrays to reconstruct biological networks including protein-DNA interactions, posttranslational protein modifications (PTMs), lectin-glycan recognition, pathogen-host interactions and hierarchical signaling cascades. The diversity in applications allows for integration of interaction data from numerous molecular classes and cellular states, providing insight into the structure of complex biological systems. We will also discuss emerging applications and future directions of protein microarray technology in the global frontier.     

Cell-to-Cell Communication during Lateral Root Development

Cell-to-cell communication plays an important role in coordinating development and specifying cell fate in all multicel lular organisms. In plants, wherein cells are immobilized and trapped within a bodice of cellulosic cell walls, exchange of positional information required for normal organogenesis has recently become the object of a growing area of research.     

A 2-bp insertion(c.67_68insCC) in MC1R causes recessive white coat color in Bama miniature pigs

<正>Coat color is an important characteristic of various breeds of domestic animal species.Variation in farm animal coat color is of considerable interest for concealment,communication and protection against solar radiation(Slominski et al.,2004).It also plays an important role in the regulation of physiological processes(Miyagi and Terai,2013).Bama miniature pigs are a native breed originally     

A survey of long‐term terrestrial ecology studies in Australia

Long‐term ecological studies (LTES) are critical for understanding and managing landscapes. To identify important research gaps, facilitate collaborations and communicate results, several countries have established long‐term ecological research networks. A few initiatives to create such a network in Australia have been undertaken, but relatively few published data exist on the current state of LTES in Australia. In this paper, we present the results of an online survey of terrestrial LTES projects sent to academic, government and non‐governmental organization‐based researchers across Australia. We asked questions pertaining to the focus, scope, support and outcomes of LTES spanning 7 years or longer. Based on the information reported from 85 Australian LTES, we: (i) identify the biomes, processes and species that are under‐represented in the current body of research; (ii) discuss important contributing factors to the successful development and survival of these projects; and (iii) make recommendations to help increase the productivity and influence of LTES across research, management and policy sectors.     

Managing data locally to answer questions globally: The role of collaborative science in ecology

Ecologists are increasingly asking large‐scale and/or broad‐scope questions that require vast datasets. In response, various top‐down efforts and incentives have been implemented to encourage data sharing and integration. However, despite general consensus on the critical need for more open ecological data, several roadblocks still discourage compliance and participation in these projects; as a result, ecological data remain largely unavailable. Grassroots initiatives (i.e. efforts initiated and led by cohesive groups of scientists focused on specific goals) have thus far been overlooked as a powerful means to meet these challenges. These bottom‐up collaborative data integration projects can play a crucial role in making high quality datasets available because they tackle the heterogeneity of ecological data at a scale where it is still manageable, all the while offering the support and structure to do so. These initiatives foster best practices in data management and provide tangible rewards to researchers who choose to invest time in sound data stewardship. By maintaining proximity between data generators and data users, grassroots initiatives improve data interpretation and ensure high‐quality data integration while providing fair acknowledgement to data generators. We encourage researchers to formalize existing collaborations and to engage in local activities that improve the availability and distribution of ecological data. By fostering communication and interaction among scientists, we are convinced that grassroots initiatives can significantly support the development of global‐scale data repositories. In doing so, these projects help address important ecological questions and support policy decisions.     

Linking Earth Observation and taxonomic,structural and functional biodiversity: Local to ecosystem perspectives

Impacts of human civilization on ecosystems threaten global biodiversity. In a changing environment, traditional in situ approaches to biodiversity monitoring have made significant steps forward to quantify and evaluate BD at many scales but still, these methods are limited to comparatively small areas. Earth observation (EO) techniques may provide a solution to overcome this shortcoming by measuring entities of interest at different spatial and temporal scales.This paper provides a comprehensive overview of the role of EO to detect, describe, explain, predict and assess biodiversity. Here, we focus on three main aspects related to biodiversity − taxonomic diversity, functional diversity and structural diversity, which integrate different levels of organization − molecular, genetic, individual, species, populations, communities, biomes, ecosystems and landscapes. In particular, we discuss the recording of taxonomic elements of biodiversity through the identification of animal and plant species. We highlight the importance of the spectral traits (ST) and spectral trait variations (STV) concept for EO-based biodiversity research. Furthermore we provide examples of spectral traits/spectral trait variations used in EO applications for quantifying taxonomic diversity, functional diversity and structural diversity. We discuss the use of EO to monitor biodiversity and habitat quality using different remote-sensing techniques. Finally, we suggest specifically important steps for a better integration of EO in biodiversity research.EO methods represent an affordable, repeatable and comparable method for measuring, describing, explaining and modelling taxonomic, functional and structural diversity. Upcoming sensor developments will provide opportunities to quantify spectral traits, currently not detectable with EO, and will surely help to describe biodiversity in more detail. Therefore, new concepts are needed to tightly integrate EO sensor networks with the identification of biodiversity. This will mean taking completely new directions in the future to link complex, large data, different approaches and models.     

A Service Approach for Architecting Application Independent Wireless Sensor Networks

The current sensor networks are assumed to be designed for specific applications, having data communication protocols strongly coupled to applications. The future sensor networks are envisioned as comprising heterogeneous devices assisting to a large range of applications. To achieve this goal, a new architecture approach is needed, having application specific features separated from the data communication protocol, while influencing its behavior. We propose a Web Services approach for the design of sensor network, in which sensor nodes are service providers and applications are clients of such services. Our main goal is to enable a flexible architecture in which sensor networks data can be accessed by users spread all over the world.     

Workflows and extensions to the Kepler scientific workflow system to support environmental sensor data access and analysis

Environmental sensor networks are now commonly being deployed within environmental observatories and as components of smaller-scale ecological and environmental experiments. Effectively using data from these sensor networks presents technical challenges that are difficult for scientists to overcome, severely limiting the adoption of automated sensing technologies in environmental science. The Realtime Environment for Analytical Processing (REAP) is an NSF-funded project to address the technical challenges related to accessing and using heterogeneous sensor data from within the Kepler scientific workflow system. Using distinct use cases in terrestrial ecology and oceanography as motivating examples, we describe workflows and extensions to Kepler to stream and analyze data from observatory networks and archives. We focus on the use of two newly integrated data sources in Kepler: DataTurbine and OPeNDAP. Integrated access to both near real-time data streams and data archives from within Kepler facilitates both simple data exploration and sophisticated analysis and modeling with these data sources.     

Ecoinformatics using wireless sensor networks: An overview

Wireless sensor networks have the potential to become significant subsystems of ecological experiment. Sensor networks consist of large number of tiny sensor nodes, all of which have sensing capabilities. These networks allow coordinated signal detection, monitoring, and tracking to enable sensor nodes to simultaneously capture geographically distinct measurements. Sensor nodes do not require predetermined positioning making such networks especially useful for applications in remote, inhospitable environments. In this paper we have tried to see the various ecological experimental scenarios, and how wireless sensor networks can be used in that field. One of the most challenging bottlenecks in the usage of wireless sensor networks in large scale experiments is the energy constraint. Various routing protocols which have tried to optimize the energy usage are also studied in the paper.     

大数据时代下的生态系统观测发展趋势与挑战

随着观测技术的发展, 生态学研究尺度不断扩大。生态系统观测从小规模合作、短时间个人观测向大规模、长时间、跨学科、多因子联合观测转变。传感器技术的革新带来了生态观测在时空尺度的扩展与精确度上的提升, 致使生态学观测数据的容量、产生速度与数据种类飞速增长。对生态系统数据获取、存储与管理的传统方法无疑不再能满足现代生态学研究的要求。因此, 我们建议以大数据时代的数据存储、管理与处理技术为基础, 整合生态物联观测网络(Internet of Ecology)、公民科学观测网络以及基于标准化数据管理的研究者网络互联, 建立整合生态系统观测平台来应对这一困境。为生态学研究者打造一站式生态观测服务, 是大数据时代下生态系统观测的大势所趋。     

Stories from Below: Subject-generated Comics

This article discusses the efficacy of grassroots comics as a practical and affordable method of realizing localized subject-generated development communication goals that focus explicitly on the interests and capacities of the subject community. The Khwe San, living in Platfontein in South Africa's Northern Cape Province, constitute the subject community. The study is informed by contemporary shifts in development theory, particularly that of participatory communication, which values individuals who live in a community as active participants in the research process. The use of grassroots comics is based on theoretical concepts in current literature regarding the field of development communication that are critical of older, top-down theories of development. My analysis and findings are presented in terms of possible implications that they might have for broader discussions regarding contemporary development theory or visual methodologies with respect to participatory communication practices.     

Advancing glycomics: implementation strategies at the consortium for functional glycomics

Glycomics-an integrated approach to study structure-function relationships of complex carbohydrates (or glycans)-is an emerging field in this age of post-genomics. Realizing the importance of glycomics, many large scale research initiatives have been established to generate novel resources and technologies to advance glycomics. These initiatives are generating and cataloging diverse data sets necessitating the development of bioinformatic platforms to acquire, integrate, and disseminate these data sets in a meaningful fashion. With the consortium for functional glycomics (CFG) as the model system, this review discusses databases and the bioinformatics platform developed by this consortium to advance glycomics.