Pigment color patterns of molluscs as an autonomous process generated by asynchronous automata

Pigment color patterns of molluscs are studied from the viewpoint of autonomy. Brownian algebra developed by Spencer-Brown (1969) is extensively used for the expression of cellular-automaton rules. When asynchronous updating is introduced for the transition of cellular automata, various kinds of patterns such as traveling waves, kinks, oscillatory local patterns etc. are generated from the same transitional rule. The type of patterns depends more sensitively on the asynchronous updating relationship rather than the transitional rule itself. Therefore, pattern changes in ontogeny can be explained without any changes in transitional rules or reaction processes. It is proposed that asynchronousness is intrinsic to living systems and that recognition of the intrinsic time is essential in understanding living systems.     

Bringing sequences to life: how bioinformatics corporealizes sequence data

Sequence databases have become more visible through the heavy publicity associated with the Human Genome Project. This paper looks at some of the emerging artefacts and systems developed to read, write, order and visualise sequence data and other kinds of biological data retrieved from databases and databanks such as GenBank. It argues that bioinformatics software can be regarded as a symptom of a broad and powerful transformation in biological knowledges and in the biopolitical constitution of living bodies. Two facets of this transformation are emphasised. Firstly, examining bioinformatics software might help us situate how sequence data is actually circulating, and to what ends. In particular, the paper looks at the significance of sequence comparison and protein folding problems. Secondly, an emerging nexus of property relations and intellectual work can be detected within the ordering of sequence data carried out bioinformatics.     

Learning to recognize objects

Several aspects of systems for learning pattern or object recognition rules are discussed. First, how are recognition rules developed and to what extent is structural pattern information embedded into these recognition rules. Second, how are these rules applied to the recognition of complex patterns such as objects embedded in scenes and how is evidence from different rules combined into a single evidence vector. Third, how can learned rules be improved through performance evaluation and feedback to rule generation stages.     

Spatially Organized Dynamical States in Chemical Oscillator Networks: Synchronization,Dynamical Differentiation,and Chimera Patterns

Dynamical processes in many engineered and living systems take place on complex networks of discrete dynamical units. We present laboratory experiments with a networked chemical system of nickel electrodissolution in which synchronization patterns are recorded in systems with smooth periodic, relaxation periodic, and chaotic oscillators organized in networks composed of up to twenty dynamical units and 140 connections. The reaction system formed domains of synchronization patterns that are strongly affected by the architecture of the network. Spatially organized partial synchronization could be observed either due to densely connected network nodes or through the ‘chimera’ symmetry breaking mechanism. Relaxation periodic and chaotic oscillators formed structures by dynamical differentiation. We have identified effects of network structure on pattern selection (through permutation symmetry and coupling directness) and on formation of hierarchical and ‘fuzzy’ clusters. With chaotic oscillators we provide experimental evidence that critical coupling strengths at which transition to identical synchronization occurs can be interpreted by experiments with a pair of oscillators and analysis of the eigenvalues of the Laplacian connectivity matrix. The experiments thus provide an insight into the extent of the impact of the architecture of a network on self-organized synchronization patterns.     

Resonant spatiotemporal learning in large random recurrent networks

 Taking a global analogy with the structure of perceptual biological systems, we present a system composed of two layers of real-valued sigmoidal neurons. The primary layer receives stimulating spatiotemporal signals, and the secondary layer is a fully connected random recurrent network. This secondary layer spontaneously displays complex chaotic dynamics. All connections have a constant time delay. We use for our experiments a Hebbian (covariance) learning rule. This rule slowly modifies the weights under the influence of a periodic stimulus. The effect of learning is twofold: (i) it simplifies the secondary-layer dynamics, which eventually stabilizes to a periodic orbit; and (ii) it connects the secondary layer to the primary layer, and realizes a feedback from the secondary to the primary layer. This feedback signal is added to the incoming signal, and matches it (i.e., the secondary layer performs a one-step prediction of the forthcoming stimulus). After learning, a resonant behavior can be observed: the system resonates with familiar stimuli, which activates a feedback signal. In particular, this resonance allows the recognition and retrieval of partial signals, and dynamic maintenence of the memory of past stimuli. This resonance is highly sensitive to the temporal relationships and to the periodicity of the presented stimuli. When we present stimuli which do not match in time or space, the feedback remains silent. The number of different stimuli for which resonant behavior can be learned is analyzed. As with Hopfield networks, the capacity is proportional to the size of the second, recurrent layer. Moreover, the high capacity displayed allows the implementation of our model on real-time systems interacting with their environment. Such an implementation is reported in the case of a simple behavior-based recognition task on a mobile robot. Finally, we present some functional analogies with biological systems in terms of autonomy and dynamic binding, and present some hypotheses on the computational role of feedback connections. Received: 27 April 2001 / Accepted in revised form: 15 January 2002     

Chip devices for miniaturized biotechnology

Chip devices were introduced in chemistry and molecular biology to improve the read-out of information from molecular systems by efficient analytical procedures and to organize automated experiments. Biochips and chip reactor systems are of interest for cellular processes, too, and can be regarded as components in interfaces for the information exchange between living nature and digital electronic systems. In this minireview, different types of chip reactors for biotechnological applications like nanotiterplates, chip thermocyclers and devices for segmented flow operations are discussed. Finally, an outlook is given on the application of chip reactor systems, which are promising tools for automated experiments with highly parallelized screening procedures, for artificial microcompartmentation, cell analogue systems, micro-ecological studies, investigations on modulated morphogenesis, and for a bioanalogue molecular nanotechnology.     

Theoretical biology in the third millennium

During the 20th century our understanding of genetics and the processes of gene expression have undergone revolutionary change. Improved technology has identified the components of the living cell, and knowledge of the genetic code allows us to visualize the pathway from genotype to phenotype. We can now sequence entire genes, and improved cloning techniques enable us to transfer genes between organisms, giving a better understanding of their function. Due to the improved power of analytical tools databases of sequence information are growing at an exponential rate. Soon complete sequences of genomes and the three-dimensional structure of all proteins may be known. The question we face in the new millennium is how to apply this data in a meaningful way. Since the genes carry the specification of an organism, and because they also record evolutionary changes, we need to design a theoretical framework that can take account of the flow of information through biological systems.     

Bioassay Approach to Prescribe Safe-limits of Exposure to Non Ionizing Radiation in Ecosystems

A biological assay that quantifies hazardous response in living matter to an electromagnetic stimulus, is evolved. Considering the various susceptible aspects of physio-anatomical systems constituting a living subject, a dominance criterion to determine an optimum all-or-none response limit of exposure to electromagnetic pollutions is established. Based on the statistics of proneness and susceptibility of discrete physio-anatomical parts of living systems (biotic components) to polluting radiations (abiotic environment), the stochastic nature of damage involved is considered to formulate a quantal index which specifies a “safe” intensity-level of electromagnetic radiation to which living systems can be exposed without encountering any deleterious effects. The locations of vulnerable parts which are affected by radiation are identified through random mosaic modeling of a test subject. Using this model, a susceptance priority sequence of biotic components is constructed. This sequence is then terminated at a point of weightage proportional to the diversity of victim population. The biotic species falling within this limit of truncation are subsequently studied to assay the tolerance (optimum lethal dose) of the test subject to the radiation in question. The possibility of simulating the entire ecological system under consideration by means of a microprocessor is suggested.     

Stability and Responsiveness in a Self-Organized Living Architecture

Robustness and adaptability are central to the functioning of biological systems, from gene networks to animal societies. Yet the mechanisms by which living organisms achieve both stability to perturbations and sensitivity to input are poorly understood. Here, we present an integrated study of a living architecture in which army ants interconnect their bodies to span gaps. We demonstrate that these self-assembled bridges are a highly effective means of maintaining traffic flow over unpredictable terrain. The individual-level rules responsible depend only on locally-estimated traffic intensity and the number of neighbours to which ants are attached within the structure. We employ a parameterized computational model to reveal that bridges are tuned to be maximally stable in the face of regular, periodic fluctuations in traffic. However analysis of the model also suggests that interactions among ants give rise to feedback processes that result in bridges being highly responsive to sudden interruptions in traffic. Subsequent field experiments confirm this prediction and thus the dual nature of stability and flexibility in living bridges. Our study demonstrates the importance of robust and adaptive modular architecture to efficient traffic organisation and reveals general principles regarding the regulation of form in biological self-assemblies.     

Spontaneous switching of frequency-locking by periodic stimulus in oscillators of plasmodium of the true slime mold

Microfabrication technique was used to construct a model system with a living cell of plasmodium of the true slime mold, Physarum polycephalum, a living coupled oscillator system. Its parameters can be systematically controlled as in computer simulations, so that results are directly comparable to those of general mathematical models. As the first step, we investigated responses in oscillatory cells, the oscillators of the plasmodium, to periodic stimuli by temperature changes to elucidate characteristics of the cells as nonlinear systems whose internal dynamics are unknown because of their complexity. We observed that the forced oscillator of the plasmodium show 1:1, 2:1, 3:1 frequency locking inside so-called Arnold tongues regions as well as in other nonlinear systems such as chemical systems and other biological systems. In addition, we found spontaneous switching behavior from certain frequency locking states to other states, even under certain fixed parameters. This technique can be applied to more complex systems with multiple elements, such as coupled oscillator systems, and would be useful to investigate complicated phenomena in biological systems such as information processing.     

Design and construction of a double inversion recombination switch for heritable sequential genetic memory

Background

Inversion recombination elements present unique opportunities for computing and information encoding in biological systems. They provide distinct binary states that are encoded into the DNA sequence itself, allowing us to overcome limitations posed by other biological memory or logic gate systems. Further, it is in theory possible to create complex sequential logics by careful positioning of recombinase recognition sites in the sequence.

Methodology/Principal Findings

In this work, we describe the design and synthesis of an inversion switch using the fim and hin inversion recombination systems to create a heritable sequential memory switch. We have integrated the two inversion systems in an overlapping manner, creating a switch that can have multiple states. The switch is capable of transitioning from state to state in a manner analogous to a finite state machine, while encoding the state information into DNA. This switch does not require protein expression to maintain its state, and “remembers” its state even upon cell death. We were able to demonstrate transition into three out of the five possible states showing the feasibility of such a switch.

Conclusions/Significance

We demonstrate that a heritable memory system that encodes its state into DNA is possible, and that inversion recombination system could be a starting point for more complex memory circuits. Although the circuit did not fully behave as expected, we showed that a multi-state, temporal memory is achievable.     

Structural dynamics, stability and folding of proteins

The present concepts of protein folding in vitro are reviewed. According to these concepts, amino acid sequence of protein, which has appeared a result of evolutionary selection, determines the native structure of protein, the pathway of protein folding, and the existence of free energy barrier between native and denatured states of protein. The latter means that protein macromolecule can exist in either native or denatured state. And all macromolecules in the native state are identical but for structural fluctuations due to Brownian motion of their atoms. Identity of all molecules in native state is of primary importance for their correct functioning. The dependence of protein stability, which is measured as the difference between free energy of protein in native and denatured states, on temperature and denaturant concentration is discussed. The modern approaches characterizing transition state and nucleation are regarded. The role of intermediate and misfolded states in amorphous aggregate and amyloid fibril formation is discussed.     

Pulsed magneto-motive ultrasound imaging using ultrasmall magnetic nanoprobes

Nano-sized particles are widely regarded as a tool to study biologic events at the cellular and molecular levels. However, only some imaging modalities can visualize interaction between nanoparticles and living cells. We present a new technique, pulsed magneto-motive ultrasound imaging, which is capable of in vivo imaging of magnetic nanoparticles in real time and at sufficient depth. In pulsed magneto-motive ultrasound imaging, an external high-strength pulsed magnetic field is applied to induce the motion within the magnetically labeled tissue and ultrasound is used to detect the induced internal tissue motion. Our experiments demonstrated a sufficient contrast between normal and iron-laden cells labeled with ultrasmall magnetic nanoparticles. Therefore, pulsed magneto-motive ultrasound imaging could become an imaging tool capable of detecting magnetic nanoparticles and characterizing the cellular and molecular composition of deep-lying structures.     

Probing degeneracy in antigen-antibody recognition at the immunodominant site of foot-and-mouth disease virus.

Antigen-antibody binding is regarded as one of the most representative examples of specific molecular recognition in nature. The simplistic view of antigenic recognition in terms of a lock-and-key mechanism is obsolete, as it is evident that both antigens and antibodies are flexible and can undergo substantial mutual adaptation. This flexibility is the source of complexities such as degeneracy and nonadditivity in antigenic recognition. We have used surface plasmon resonance to study the effects of combining multiple amino acid replacements within the sequence of the antigenic GH loop of foot-and-mouth disease virus. Our aim was 2-fold: to explore the extent to which antigenic degeneracy can be extended in this particular case, and to search for potential nonadditive effects in introducing multiple amino acid replacements. Combined analysis of one such multiply substituted peptide by SPR, solution NMR and X-ray diffraction shows that antigenic degeneracy can be expected as long as residues directly interacting with the paratope are conserved and the peptide bioactive folding is unaltered.     

The manipulation of calcium oscillations by harnessing self-organisation

This paper investigates how self-organisation might be harnessed for the manipulation and control of calcium oscillations. Calcium signalling mechanisms are responsible for a number of important functions within biological systems, such as fertilization, secretion, contraction, neuronal signalling and learning. In this paper, calcium oscillations are investigated as a biological periodic process. Within biological systems such periodic behaviour is one of the outcomes from self-organisation. The understanding of periodic processes in living systems can enable more accurate diagnosis and physiologically suitable clinical therapies to be proposed, for diseases such as cancer, epilepsy, cardiac diseases and other dynamic diseases. In this paper these ideas are investigated by means of the calcium-induced calcium release (CICR) model and a number of representative simulations of intra and inter-cellular calcium oscillations are used to illustrate the manipulation and control of these oscillations in normal and pathological situations.     

The Positive Inside Rule Is Stronger When Followed by a Transmembrane Helix

The translocon recognizes transmembrane helices with sufficient level of hydrophobicity and inserts them into the membrane. However, sometimes less hydrophobic helices are also recognized. Positive inside rule, orientational preferences of and specific interactions with neighboring helices have been shown to aid in the recognition of these helices, at least in artificial systems. To better understand how the translocon inserts marginally hydrophobic helices, we studied three naturally occurring marginally hydrophobic helices, which were previously shown to require the subsequent helix for efficient translocon recognition. We find no evidence for specific interactions when we scan all residues in the subsequent helices. Instead, we identify arginines located at the N-terminal part of the subsequent helices that are crucial for the recognition of the marginally hydrophobic transmembrane helices, indicating that the positive inside rule is important. However, in two of the constructs, these arginines do not aid in the recognition without the rest of the subsequent helix; that is, the positive inside rule alone is not sufficient. Instead, the improved recognition of marginally hydrophobic helices can here be explained as follows: the positive inside rule provides an orientational preference of the subsequent helix, which in turn allows the marginally hydrophobic helix to be inserted; that is, the effect of the positive inside rule is stronger if positively charged residues are followed by a transmembrane helix. Such a mechanism obviously cannot aid C-terminal helices, and consequently, we find that the terminal helices in multi-spanning membrane proteins are more hydrophobic than internal helices.