The Escherichia coli outer membrane protein OmpA acquires secondary structure prior to its integration into the membrane

Almost all proteins that reside in the outer membrane (OM) of Gram-negative bacteria contain a membrane-spanning segment that folds into a unique β barrel structure and inserts into the membrane by an unknown mechanism. To obtain further insight into outer membrane protein (OMP) biogenesis, we revisited the surprising observation reported over 20 years ago that the Escherichia coli OmpA β barrel can be assembled into a native structure in vivo when it is expressed as two noncovalently linked fragments. Here, we show that disulfide bonds between β strand 4 in the N-terminal fragment and β strand 5 in the C-terminal fragment can form in the periplasmic space and greatly increase the efficiency of assembly of “split” OmpA, but only if the cysteine residues are engineered in perfect register (i.e., they are aligned in the fully folded β barrel). In contrast, we observed only weak disulfide bonding between β strand 1 in the N-terminal fragment and β strand 8 in the C-terminal fragment that would form a closed or circularly permutated β barrel. Our results not only demonstrate that β barrels begin to fold into a β-sheet-like structure before they are integrated into the OM but also help to discriminate among the different models of OMP biogenesis that have been proposed.     

Mechanistic Explanations for Restricted Evolutionary Paths That Emerge from Gene Regulatory Networks

The extent and the nature of the constraints to evolutionary trajectories are central issues in biology. Constraints can be the result of systems dynamics causing a non-linear mapping between genotype and phenotype. How prevalent are these developmental constraints and what is their mechanistic basis? Although this has been extensively explored at the level of epistatic interactions between nucleotides within a gene, or amino acids within a protein, selection acts at the level of the whole organism, and therefore epistasis between disparate genes in the genome is expected due to their functional interactions within gene regulatory networks (GRNs) which are responsible for many aspects of organismal phenotype. Here we explore epistasis within GRNs capable of performing a common developmental function – converting a continuous morphogen input into discrete spatial domains. By exploring the full complement of GRN wiring designs that are able to perform this function, we analyzed all possible mutational routes between functional GRNs. Through this study we demonstrate that mechanistic constraints are common for GRNs that perform even a simple function. We demonstrate a common mechanistic cause for such a constraint involving complementation between counter-balanced gene-gene interactions. Furthermore we show how such constraints can be bypassed by means of “permissive” mutations that buffer changes in a direct route between two GRN topologies that would normally be unviable. We show that such bypasses are common and thus we suggest that unlike what was observed in protein sequence-function relationships, the “tape of life” is less reproducible when one considers higher levels of biological organization.     

Viewing Complex,Dynamic Scenes “Through the Eyes” of Another Person: The Gaze-Replay Paradigm

We present a novel “Gaze-Replay” paradigm that allows the experimenter to directly test how particular patterns of visual input—generated from people’s actual gaze patterns—influence the interpretation of the visual scene. Although this paradigm can potentially be applied across domains, here we applied it specifically to social comprehension. Participants viewed complex, dynamic scenes through a small window displaying only the foveal gaze pattern of a gaze “donor.” This was intended to simulate the donor’s visual selection, such that a participant could effectively view scenes “through the eyes” of another person. Throughout the presentation of scenes presented in this manner, participants completed a social comprehension task, assessing their abilities to recognize complex emotions. The primary aim of the study was to assess the viability of this novel approach by examining whether these Gaze-Replay windowed stimuli contain sufficient and meaningful social information for the viewer to complete this social perceptual and cognitive task. The results of the study suggested this to be the case; participants performed better in the Gaze-Replay condition compared to a temporally disrupted control condition, and compared to when they were provided with no visual input. This approach has great future potential for the exploration of experimental questions aiming to unpack the relationship between visual selection, perception, and cognition.     

Increases in the Numerical Density of GAT-1 Positive Puncta in the Barrel Cortex of Adult Mice after Fear Conditioning

Three days of fear conditioning that combines tactile stimulation of a row of facial vibrissae (conditioned stimulus, CS) with a tail shock (unconditioned stimulus, UCS) expands the representation of “trained” vibrissae, which can be demonstrated by labeling with 2-deoxyglucose in layer IV of the barrel cortex. We have also shown that functional reorganization of the primary somatosensory cortex (S1) increases GABAergic markers in the hollows of “trained” barrels of the adult mouse. This study investigated how whisker-shock conditioning (CS+UCS) affected the expression of puncta of a high-affinity GABA plasma membrane transporter GAT-1 in the barrel cortex of mice 24 h after associative learning paradigm. We found that whisker-shock conditioning (CS+UCS) led to increase expression of neuronal and astroglial GAT-1 puncta in the “trained” row compared to controls: Pseudoconditioned, CS-only, UCS-only and Naïve animals. These findings suggest that fear conditioning specifically induces activation of systems regulating cellular levels of the inhibitory neurotransmitter GABA.     

Fine-Scale Dissection of Functional Protein Network Organization by Statistical Network Analysis

Revealing organizational principles of biological networks is an important goal of systems biology. In this study, we sought to analyze the dynamic organizational principles within the protein interaction network by studying the characteristics of individual neighborhoods of proteins within the network based on their gene expression as well as protein-protein interaction patterns. By clustering proteins into distinct groups based on their neighborhood gene expression characteristics, we identify several significant trends in the dynamic organization of the protein interaction network. We show that proteins with distinct neighborhood gene expression characteristics are positioned in specific localities in the protein interaction network thereby playing specific roles in the dynamic network connectivity. Remarkably, our analysis reveals a neighborhood characteristic that corresponds to the most centrally located group of proteins within the network. Further, we show that the connectivity pattern displayed by this group is consistent with the notion of “rich club connectivity” in complex networks. Importantly, our findings are largely reproducible in networks constructed using independent and different datasets.     

The Walking Behaviour of Pedestrian Social Groups and Its Impact on Crowd Dynamics

Human crowd motion is mainly driven by self-organized processes based on local interactions among pedestrians. While most studies of crowd behaviour consider only interactions among isolated individuals, it turns out that up to 70% of people in a crowd are actually moving in groups, such as friends, couples, or families walking together. These groups constitute medium-scale aggregated structures and their impact on crowd dynamics is still largely unknown. In this work, we analyze the motion of approximately 1500 pedestrian groups under natural condition, and show that social interactions among group members generate typical group walking patterns that influence crowd dynamics. At low density, group members tend to walk side by side, forming a line perpendicular to the walking direction. As the density increases, however, the linear walking formation is bent forward, turning it into a V-like pattern. These spatial patterns can be well described by a model based on social communication between group members. We show that the V-like walking pattern facilitates social interactions within the group, but reduces the flow because of its “non-aerodynamic” shape. Therefore, when crowd density increases, the group organization results from a trade-off between walking faster and facilitating social exchange. These insights demonstrate that crowd dynamics is not only determined by physical constraints induced by other pedestrians and the environment, but also significantly by communicative, social interactions among individuals.     

Biological action at a distance: Correlated pattern formation in adjacent tessellation domains without communication

Tessellations emerge in many natural systems, and the constituent domains often contain regular patterns, raising the intriguing possibility that pattern formation within adjacent domains might be correlated by the geometry, without the direct exchange of information between parts comprising either domain. We confirm this paradoxical effect, by simulating pattern formation via reaction-diffusion in domains whose boundary shapes tessellate, and showing that correlations between adjacent patterns are strong compared to controls that self-organize in domains with equivalent sizes but unrelated shapes. The effect holds in systems with linear and non-linear diffusive terms, and for boundary shapes derived from regular and irregular tessellations. Based on the prediction that correlations between adjacent patterns should be bimodally distributed, we develop methods for testing whether a given set of domain boundaries constrained pattern formation within those domains. We then confirm such a prediction by analysing the development of ‘subbarrel’ patterns, which are thought to emerge via reaction-diffusion, and whose enclosing borders form a Voronoi tessellation on the surface of the rodent somatosensory cortex. In more general terms, this result demonstrates how causal links can be established between the dynamical processes through which biological patterns emerge and the constraints that shape them.     

Kinematics of the Coordination of Pointing during Locomotion

In natural motor behaviour arm movements, such as pointing or reaching, often need to be coordinated with locomotion. The underlying coordination patterns are largely unexplored, and require the integration of both rhythmic and discrete movement primitives. For the systematic and controlled study of such coordination patterns we have developed a paradigm that combines locomotion on a treadmill with time-controlled pointing to targets in the three-dimensional space, exploiting a virtual reality setup. Participants had to walk at a constant velocity on a treadmill. Synchronized with specific foot events, visual target stimuli were presented that appeared at different spatial locations in front of them. Participants were asked to reach these stimuli within a short time interval after a “go” signal. We analysed the variability patterns of the most relevant joint angles, as well as the time coupling between the time of pointing and different critical timing events in the foot movements. In addition, we applied a new technique for the extraction of movement primitives from kinematic data based on anechoic demixing. We found a modification of the walking pattern as consequence of the arm movement, as well as a modulation of the duration of the reaching movement in dependence of specific foot events. The extraction of kinematic movement primitives from the joint angle trajectories exploiting the new algorithm revealed the existence of two distinct main components accounting, respectively, for the rhythmic and discrete components of the coordinated movement pattern. Summarizing, our study shows a reciprocal pattern of influences between the coordination patterns of reaching and walking. This pattern might be explained by the dynamic interactions between central pattern generators that initiate rhythmic and discrete movements of the lower and upper limbs, and biomechanical factors such as the dynamic gait stability.     

Local cortical interactions determine the form of cortical plasticity.

Competitive interactions between left and right eye inputs to visual cortex during development are usually explained by the thalamocortical axons competing more or less well for cortical territory during retraction into eye specific domains. Here we review the evidence for competitive and co-operative interactions between cortical columns in barrel cortex which are present several weeks after retraction of thalamocortical axons into barrels. Sensory responses in barrel cortex can be altered by a period of vibrissa deprivation. It was found that responses to previously deprived vibrissae (that had been allowed to regrow) were depressed more if neighboring vibrissae were spared than if all vibrissae were removed simultaneously. Depression of the deprived vibrissa response was greater the closer the cell lay to a spared barrel. It was also found that spared vibrissae responses were potentiated more if several neighboring vibrissae were left intact than if only a single vibrissae was spared. These results suggest a mechanism of cooperative potentiation, perhaps due to intracortical summation of excitation evoked by neighbouring vibrissa stimulation. Thalamic responses to vibrissa stimulation were unaffected by deprivation indicating a cortical origin. One of the consequences of deprivation was that the speed of transmission between barrels was increased for spared and decreased for deprived vibrissa. These results imply that inherent interactions between cortical columns give rise to a property of competition and co-operativity which amplify the effects of sensory deprivation.     

PFIT and PFRIT: bioinformatic algorithms for detecting glycosidase function from structure and sequence

The identification of the enzymes involved in the metabolism of simple and complex carbohydrates presents one bioinformatic challenge in the post-genomic era. Here, we present the PFIT and PFRIT algorithms for identifying those proteins adopting the alpha/beta barrel fold that function as glycosidases. These algorithms are based on the observation that proteins adopting the alpha/beta barrel fold share positions in their tertiary structures having equivalent sets of atomic interactions. These are conserved tertiary interaction positions, which have been implicated in both structure and function. Glycosidases adopting the alpha/beta barrel fold share more conserved tertiary interactions than alpha/beta barrel proteins having other functions. The enrichment pattern of conserved tertiary interactions in the glycosidases is the information that PFIT and PFRIT use to predict whether any given alpha/beta barrel will function as a glycosidase or not. Using as a test set a database of 19 glycosidase and 45 nonglycosidase alpha/beta barrel proteins with low sequence similarity, PFIT and PFRIT can correctly predict glycosidase function for 84% of the proteins known to function as glycosidases. PFIT and PFRIT incorrectly predict glycosidase function for 25% of the nonglycosidases. The program PSI-BLAST can also correctly identify 84% of the 19 glycosidases, however, it incorrectly predicts glycosidase function for 50% of the nonglycosidases (twofold greater than PFIT and PFRIT). Overall, we demonstrate that the structure-based PFIT and PFRIT algorithms are both more selective and sensitive for predicting glycosidase function than the sequence-based PSI-BLAST algorithm.     

Functional asymmetries in the rodent barrel cortex

Neurophysiological and 2-deoxyglucose (2DG) studies of the rodent whisker barrel cortex have demonstrated asymmetries in its functional organization. To examine the possibility that the activity gradients observed in metabolic studies can be attributed to subtle rostral-caudal and dorsal-ventral asymmetries in electrophysiologically measured surround or cross-whisker inhibition, we compared 2DG results with predictions generated from quantitative single-cell receptive field data. Despite differences in the two experimental approaches, there is remarkable agreement between the findings. (1) The distribution of 2DG activity declines across the barrel cortex of the behaving animal from anteromedial barrels to posterolateral barrels, and is qualitatively and quantitatively similar to the values predicted from neurophysiology. (2) The strength of surround inhibition in barrel neurons predicts the twofold increase in activation of the C3 barrel following acute clipping of adjacent whiskers. And (3) within a cortical column, the decrease in metabolic activity associated with adjacent whisker stimulation is greatest in layer IV and least in the infragranular layers; this corresponds to the laminar distribution of inhibitory interactions observed electrophysiologically.     

BDNF and trkB mRNA Expression in Neurons of the Neonatal Mouse Barrel Field Cortex: Normal Development and Plasticity after Cauterizing Facial Vibrissae

Development of the central somatosensory system is profoundly modulated by the sensory periphery. Cauterization of facial whiskers alters the segregation pattern of barrels in rodents only during a few days just after birth (critical period). Although a molecular basis of the segregation of barrel neurons and the critical period for the anatomical plasticity observed in layer IV barrel neuron is not clear yet, the accumulating evidence suggests that neurotrophins modulate synaptic connections including central nervous system. In this study, we showed by in situ hybridization that mouse barrel side neurons express brain-derived neurotrophic factor (BDNF) mRNA and both catalytic and non-catalytic forms of trkB mRNA. Cautery of row C vibrissae on the right side of the face within 24 h after birth (post natal day 0, PND0) reduced the expression of BDNF and trkB mRNA from the division region between the contralateral row C barrels at PND7. The vibrissae in row A, C, and E were cauterized at PND0 followed by quantitative RT-PCR for BDNF and trkB mRNA with total RNA isolated from the barrel region at PND7. The result showed that BDNF, but not trkB, mRNA was increased several-fold in the contralateral barrel region. These data suggest that the expression of BDNF mRNA is differentially regulated between injured barrels and actively innervated barrels. The differential expression of the mRNA encoding neurotrophins and their receptors may be important in regulating the injury-dependent re-segregation of barrels.     

Understanding Recurrent Crime as System-Immanent Collective Behavior

Containing the spreading of crime is a major challenge for society. Yet, since thousands of years, no effective strategy has been found to overcome crime. To the contrary, empirical evidence shows that crime is recurrent, a fact that is not captured well by rational choice theories of crime. According to these, strong enough punishment should prevent crime from happening. To gain a better understanding of the relationship between crime and punishment, we consider that the latter requires prior discovery of illicit behavior and study a spatial version of the inspection game. Simulations reveal the spontaneous emergence of cyclic dominance between “criminals”, “inspectors”, and “ordinary people” as a consequence of spatial interactions. Such cycles dominate the evolutionary process, in particular when the temptation to commit crime or the cost of inspection are low or moderate. Yet, there are also critical parameter values beyond which cycles cease to exist and the population is dominated either by a stable mixture of criminals and inspectors or one of these two strategies alone. Both continuous and discontinuous phase transitions to different final states are possible, indicating that successful strategies to contain crime can be very much counter-intuitive and complex. Our results demonstrate that spatial interactions are crucial for the evolutionary outcome of the inspection game, and they also reveal why criminal behavior is likely to be recurrent rather than evolving towards an equilibrium with monotonous parameter dependencies.     

Estimating divergence times from DNA sequences

The patterns of genetic variation within and among individuals and populations can be used to make inferences about the evolutionary forces that generated those patterns. Numerous population genetic approaches have been developed in order to infer evolutionary history. Here, we present the “Two-Two (TT)” and the “Two-Two-outgroup (TTo)” methods; two closely related approaches for estimating divergence time based in coalescent theory. They rely on sequence data from two haploid genomes (or a single diploid individual) from each of two populations. Under a simple population-divergence model, we derive the probabilities of the possible sample configurations. These probabilities form a set of equations that can be solved to obtain estimates of the model parameters, including population split times, directly from the sequence data. This transparent and computationally efficient approach to infer population divergence time makes it possible to estimate time scaled in generations (assuming a mutation rate), and not as a compound parameter of genetic drift. Using simulations under a range of demographic scenarios, we show that the method is relatively robust to migration and that the TTo method can alleviate biases that can appear from drastic ancestral population size changes. We illustrate the utility of the approaches with some examples, including estimating split times for pairs of human populations as well as providing further evidence for the complex relationship among Neandertals and Denisovans and their ancestors.     

Quantifying Collective Attention from Tweet Stream

Online social media are increasingly facilitating our social interactions, thereby making available a massive “digital fossil” of human behavior. Discovering and quantifying distinct patterns using these data is important for studying social behavior, although the rapid time-variant nature and large volumes of these data make this task difficult and challenging. In this study, we focused on the emergence of “collective attention” on Twitter, a popular social networking service. We propose a simple method for detecting and measuring the collective attention evoked by various types of events. This method exploits the fact that tweeting activity exhibits a burst-like increase and an irregular oscillation when a particular real-world event occurs; otherwise, it follows regular circadian rhythms. The difference between regular and irregular states in the tweet stream was measured using the Jensen-Shannon divergence, which corresponds to the intensity of collective attention. We then associated irregular incidents with their corresponding events that attracted the attention and elicited responses from large numbers of people, based on the popularity and the enhancement of key terms in posted messages or “tweets.” Next, we demonstrate the effectiveness of this method using a large dataset that contained approximately 490 million Japanese tweets by over 400,000 users, in which we identified 60 cases of collective attentions, including one related to the Tohoku-oki earthquake. “Retweet” networks were also investigated to understand collective attention in terms of social interactions. This simple method provides a retrospective summary of collective attention, thereby contributing to the fundamental understanding of social behavior in the digital era.     

Design of multi-specificity in protein interfaces

Interactions in protein networks may place constraints on protein interface sequences to maintain correct and avoid unwanted interactions. Here we describe a “multi-constraint” protein design protocol to predict sequences optimized for multiple criteria, such as maintaining sets of interactions, and apply it to characterize the mechanism and extent to which 20 multi-specific proteins are constrained by binding to multiple partners. We find that multi-specific binding is accommodated by at least two distinct patterns. In the simplest case, all partners share key interactions, and sequences optimized for binding to either single or multiple partners recover only a subset of native amino acid residues as optimal. More interestingly, for signaling interfaces functioning as network “hubs,” we identify a different, “multi-faceted” mode, where each binding partner prefers its own subset of wild-type residues within the promiscuous binding site. Here, integration of preferences across all partners results in sequences much more “native-like” than seen in optimization for any single binding partner alone, suggesting these interfaces are substantially optimized for multi-specificity. The two strategies make distinct predictions for interface evolution and design. Shared interfaces may be better small molecule targets, whereas multi-faceted interactions may be more “designable” for altered specificity patterns. The computational methodology presented here is generalizable for examining how naturally occurring protein sequences have been selected to satisfy a variety of positive and negative constraints, as well as for rationally designing proteins to have desired patterns of altered specificity.