Biological Communication Systems Research Articles

Whatisduality of patterning, anyway?

AbstractThe notion of duality of patterning (henceforth DoP), at least for readers of this special issue, is probably most closely associated with Charles F. Hockett's project of identifying the ‘design features’ of language in order to characterise the ways in which human language is unique among biological communication systems (Hockett 1958: chapter 64; Hockett 1960; Hockett and Ascher 1964). Roughly speaking, DoP refers to the fact that the meaningful units of language – words or morphemes – are made up of meaningless units – phonemes or features – whose only function is to distinguish the meaningful units from one another. Stated this way, the idea seems quite straightforward, and to have it explicitly stated as a property of language seems a useful insight. In fact, though, of all the design features discussed by Hockett, DoP seems to have engendered the most confusion. The idea that meaningful units are composed of meaningless ones seems simple enough, but many complications arise when we look more closely. The goal of this short paper is to document some of the complications and perhaps alleviate some of the confusion.

Engineered cell-cell communication via DNA messaging.

BackgroundEvolution has selected for organisms that benefit from genetically encoded cell-cell communication. Engineers have begun to repurpose elements of natural communication systems to realize programmed pattern formation and coordinate other population-level behaviors. However, existing engineered systems rely on system-specific small molecules to send molecular messages among cells. Thus, the information transmission capacity of current engineered biological communication systems is physically limited by specific biomolecules that are capable of sending only a single message, typically “regulate transcription.”ResultsWe have engineered a cell-cell communication platform using bacteriophage M13 gene products to autonomously package and deliver heterologous DNA messages of varying lengths and encoded functions. We demonstrate the decoupling of messages from a common communication channel via the autonomous transmission of various arbitrary genetic messages. Further, we increase the range of engineered DNA messaging across semisolid media by linking message transmission or receipt to active cellular chemotaxis.ConclusionsWe demonstrate decoupling of a communication channel from message transmission within engineered biological systems via the autonomous targeted transduction of user-specified heterologous DNA messages. We also demonstrate that bacteriophage M13 particle production and message transduction occurs among chemotactic bacteria. We use chemotaxis to improve the range of DNA messaging, increasing both transmission distance and communication bit rates relative to existing small molecule-based communication systems. We postulate that integration of different engineered cell-cell communication platforms will allow for more complex spatial programming of dynamic cellular consortia.

On the Quantification of Information Content of Flower-Insect Interaction by the Species Diversity Indices: A Case Study in Flower Visiting Hymenopterans

Several interesting views have been suggested regarding the kind of biological communication systems that exists between the insects and plant community as a whole. Our study attempts to measure the information content transmitted through different floral attributes which in turn is received by the visiting hymenopteran insects. Ten different floral patches bloomed in different times of the season for a period of 3 years had been studied in the agricultural tracts. We have used the Shannon Wiener Function and Brillouin’s Index in order to ascertain the probable information content of such interaction. Higher values of information content obtained in case of the cultivated food plants point towards the presence of a greater preference for these floral patches by the different foraging insect species compared to the wild and cultivated horticultural species.

Bioterrorism: How prepared are we?

Bioterrorism is defined as the overt or covert dispensing of disease pathogens by individuals, groups or governments for the expressed purpose of causing harm for their ideological, political, or financial gains. Centre for Disease Control, Atlanta, USA classifies bioterrorism agents/ diseases into three broad categories i.e., Category A, B and C types depending upon the severity of these agents. The global strategic plan to combat bioterrorism is based on the following five focus areas, with each area integrating training and research- Preparedness and Prevention, Detection and Surveillance, Diagnosis and Characterisation of biological agents, Responses and Communication system. Though India has established a National Institute for Disaster Management in 2003, it has no agenda specifically directed for bioterrorism and its mitigation. Early detection and control of biological attack depends on a strong and flexible public health and animal health system at local, state and national levels. Combating bioterrorism will require capitalising on advances in technology, information system and medical and veterinary sciences.

Molecular Communication Using Brownian Motion With Drift

Inspired by biological communication systems, molecular communication has been proposed as a viable scheme to communicate between nano-sized devices separated by a very short distance. Here, molecules are released by the transmitter into the medium, which are then sensed by the receiver. This paper develops a preliminary version of such a communication system focusing on the release of either one or two molecules into a fluid medium with drift. We analyze the mutual information between transmitter and the receiver when information is encoded in the time of release of the molecule. Simplifying assumptions are required in order to calculate the mutual information, and theoretical results are provided to show that these calculations are upper bounds on the true mutual information. Furthermore, optimized degree distributions are provided, which suggest transmission strategies for a variety of drift velocities.

A novel telecommunications-based approach to HIV modeling and simulation

It is well known that biological systems utilize communication in some form; one prolific example of this is the propagation of HIV (Human Immunodeficiency Virus) in the human body. By modeling HIV infection as a communication system, we hope to gain a unique insight into HIV and biological communication systems in general. Such a model would provide researchers a platform for experimenting and simulating various biological communication systems. We have previously developed a layered communication protocol for interpreting biological communication systems using telecommunications paradigms and will apply said model to HIV proliferation. We will also demonstrate the effectiveness of the model by implementing a communication-based simulation of HIV infection based on direct interpretation of this layered protocol.

Efficiency of neural transmission as a function of synaptic noise, threshold, and source characteristics

Abstract There has been a growing interest in the estimation of information carried by a single neuron and multiple single units or population of neurons to specific stimuli. In this paper we analyze, inspired by article of Levy and Baxter (2002), the efficiency of a neuronal communication by considering dendrosomatic summation as a Shannon-type channel (1948) and by considering such uncertain synaptic transmission as part of the dendrosomatic computation. Specifically, we study Mutual Information between input and output signals for different types of neuronal network architectures by applying efficient entropy estimators. We analyze the influence of the following quantities affecting transmission abilities of neurons: synaptic failure, activation threshold, firing rate and type of the input source. We observed a number of surprising non-intuitive effects. It turns out that, especially for lower activation thresholds, significant synaptic noise can lead even to twofold increase of the transmission efficiency. Moreover, the efficiency turns out to be a non-monotonic function of the activation threshold. We find a universal value of threshold for which a local maximum of Mutual Information is achieved for most of the neuronal architectures, regardless of the type of the source (correlated and non-correlated). Additionally, to reach the global maximum the optimal firing rates must increase with the threshold. This effect is particularly visible for lower firing rates. For higher firing rates the influence of synaptic noise on the transmission efficiency is more advantageous. Noise is an inherent component of communication in biological systems, hence, based on our analysis, we conjecture that the neuronal architecture was adjusted to make more effective use of this attribute.

Alternative paths in HIV-1 targeted human signal transduction pathways

BackgroundHuman immunodeficiency virus-1 (HIV-1) has a minimal genome of only 9 genes, which encode 15 proteins. HIV-1 thus depends on the human host for virtually every aspect of its life cycle. The universal language of communication in biological systems, including between pathogen and host, is via signal transduction pathways. The fundamental units of these pathways are protein protein interactions. Understanding the functional significance of HIV-1, human interactions requires viewing them in the context of human signal transduction pathways.ResultsIntegration of HIV-1, human interactions with known signal transduction pathways indicates that the majority of known human pathways have the potential to be effected through at least one interaction with an HIV-1 protein at some point during the HIV-1 life cycle. For each pathway, we define simple paths between start points (i.e. no edges going into a node) and end points (i.e. no edges leaving a node). We then identify the paths that pass through human proteins that interact with HIV-1 proteins. We supplement the combined map with functional information, including which proteins are known drug targets and which proteins contribute significantly to HIV-1 function as revealed by recent siRNA screens. We find that there are often alternative paths starting and ending at the same proteins but circumventing the intermediate steps disrupted by HIV-1.ConclusionA mapping of HIV-1, human interactions to human signal transduction pathways is presented here to link interactions with functions. We proposed a new way of analyzing the virus host interactions by identifying HIV-1 targets as well as alternative paths bypassing the HIV-1 targeted steps. This approach yields numerous experimentally testable hypotheses on how HIV-1 function may be compromised and human cellular function restored by pharmacological approaches. We are making the full set of pathway analysis results available to the community.

The Use of Ideas of Information Theory for Studying “Language” and Intelligence in Ants

In this review we integrate results of long term experimental study on ant "language" and intelligence which were fully based on fundamental ideas of Information Theory, such as the Shannon entropy, the Kolmogorov complexity, and the Shannon's equation connecting the length of a message ($l$) and its frequency $(p)$, i.e. $l = - \log p$ for rational communication systems. This approach, new for studying biological communication systems, enabled us to obtain the following important results on ants' communication and intelligence: i) to reveal "distant homing" in ants, that is, their ability to transfer information about remote events; ii) to estimate the rate of information transmission; iii) to reveal that ants are able to grasp regularities and to use them for "compression" of information; iv) to reveal that ants are able to transfer to each other the information about the number of objects; v) to discover that ants can add and subtract small numbers. The obtained results show that Information Theory is not only wonderful mathematical theory, but many its results may be considered as Nature laws.

Alternating synchronizability of complex clustered networks with regular local structure

Small network distance and homogeneous degree distribution have been found to be critical to efficient network synchronization. In this paper, we investigate the synchronizability of clustered networks with regular subnetworks and report a counterintuitive phenomenon: As the density of intracluster links is increased, the network exhibits strong and weak synchronizability in an alternating manner. A theory based on analyzing the eigenvalues and eigenvectors of the coupling matrix is provided to explain this phenomenon. The relevance of the network model to tissue organization for intercellular communication in biological systems is discussed. An implication is that, in order to achieve synchronization, local coupling density in the network needs to be tuned properly.

Electronic control of Ca2+ signalling in neuronal cells using an organic electronic ion pump

Cells and tissues use finely regulated ion fluxes for their intra- and intercellular communication. Technologies providing spatial and temporal control for studies of such fluxes are however, limited. We have developed an electrophoretic ion pump made of poly(3,4-ethylenedioxythiophene) doped with poly(styrene sulphonate) (PEDOT:PSS) to mediate electronic control of the ion homeostasis in neurons. Ion delivery from a source reservoir to a receiving electrolyte via a PEDOT:PSS thin-film channel was achieved by electronic addressing. Ions are delivered in high quantities at an associated on/off ratio exceeding 300. This induces physiological signalling events that can be recorded at the single-cell level. Furthermore, miniaturization of the device to a 50-microm-wide channel allows for stimulation of individual cells. As this technology platform allows for electronic control of ion signalling in individual cells with proper spatial and temporal resolution, it will be useful in further studies of communication in biological systems.

Reliable biological communication with realistic constraints

Communication in biological systems must deal with noise and metabolic or temporal constraints. We include these constraints into information theory to obtain the distributions of signal usage corresponding to a maximal rate of information transfer given any noise structure and any constraints. Generalized versions of the Boltzmann, Gaussian, or Poisson distributions are obtained for linear, quadratic and temporal constraints, respectively. These distributions are shown to imply that biological transformations must dedicate a larger output range to the more probable inputs and less to the outputs with higher noise and higher participation in the constraint. To show the general theory of reliable communication at work, we apply these results to biochemical and neuronal signaling. Noncooperative enzyme kinetics is shown to be suited for transfer of a high signal quality when the input distribution has a maximum at low concentrations while cooperative kinetics for near-Gaussian input statistics. Neuronal codes based on spike rates, spike times or bursts have to balance signal quality and cost-efficiency and at the network level imply sparseness and uncorrelation within the limits of noise, cost, and processing operations.

Estimating the afferent and efferent temporal interval entropy of neuronal discharge for single spike trains

We define a biological communication system at the level of a single neuron and quantify the temporal variability of afferent and efferent impulse patterns by means of an interval entropy measure. Two signal transmission conditions which bound a physiologically plausible range of transmission possibilities are explored. The number of efferent synapses is predicted by matching estimates of the mean efferent entropy to the total afferent entropy.

Identification of G protein-coupled receptors in insect cells.

Communication processes lay at the very basis of physiological functioning and therefore, probably at the true basis of Life itself (as outlined by De Loof and Vanden Broeck1). All communication systems, including modern forms of human communication as well as biological communication systems, are based on similar fundamental principles or requirements and typically consist of the following three main parts: (1) the environment or a “sender-encoder” system which produces a signal or a message that is transmitted via a (2) “communication channel” towards a (3) “receiver-decoder-amplifier-responder.”2 In biological systems, physiological responses to extracellular signals and messages are generated by a process called signal transduction which is elicited by activation of specific receptor proteins. Interestingly, the four main classes of signaltransducing receptor proteins (ligand-gated ion channels, single-transmembrane proteins, seven-transmembrane G protein–coupled receptors [GPCRs], and nuclear receptors) are present in all metazoans.3 This review deals with the different kinds of GPCRs already identified in insect cells.

Non-linear analysis of a linear-non-linear-linear system

Abstract There are many non-linear systems in the field of biological systems, control systems and communication systems. The identification of non-linear system is a fundamental problem in these fields. Many investigations of non-linear systems have been carried out from the viewpoint of parameter identification. The so-called general model has been well studied in non-linear identification problems. The general model is a memoryless non-linearity sandwiched between two linear time-invariant subsystems. In biological systems, this model is applicable to retinal neurons in visual information processing. In physically realizable systems, we need to consider a causal system. Based on input-output causality, we develop a new complete identification method for the general model in the discrete time domain. Further, we derive a new formula for the estimation of non-linear parameters in the general model. The method developed here is simpler than conventional identification procedures. Finally, the results are simulated to verify our identification method.

A physical characterization of biological information and communication system model of ecosystems

What is information for living organisms? An answer to this question is given on a physical basis and a contrast between genetic information and sensory information is stressed with a relation to information theory. A simple model of an environment of living organisms is investigated on the basis of communication systems model proposed by the author and a cost of information transmission is taken into consideration through capacity cost theory. It is shown that channel capacity of information theory can be interpreted as an environment, and furthermore that a large diversity of genetic messages needs a large capacity of the environment. In addition, a definition of life in terms of information is proposed and a unified view on life processes is suggested.

Monolayer coupling in sphingomyelin bilayer systems

THE transmission of information across biological membranes is of obvious importance. In the past, discussions of possible mechanisms for transmembrane linkage, in the absence of transport or permeation, have centred on the role of the integral membrane proteins, which function as receptors1. When the lipids have been discussed in this context, the speculations have centred on their influence on the proteins, by way of a ‘viscotropic’ effect2, induced by changes in ionic strength3 or temperature; that is, it has generally been implicitly assumed that the two lipid monolayers act independently of each other4. A detailed nuclear magnetic resonance (NMR) study of the thermal behaviour of small single-walled vesicles composed of synthetic phosphatidylcholines has shown that this is indeed the case for these systems5. In this report, we present evidence that vesicles composed of another class of phospholipid, sphingomyelin, do exhibit coupling between the two monolayers, and thus could be involved in transmembrane communication in biological systems.