Dynamic reorganization of the functionally active ribosome explored by normal mode analysis and cryo-electron microscopy

Combining structural data for the ribosome from x-ray crystallography and cryo-electron microscopy with dynamic models based on elastic network normal mode analysis, an atomically detailed picture of functionally important structural rearrangements that occur during translocation is elucidated. The dynamic model provides a near-atomic description of the ratchet-like rearrangement of the 70S ribosome seen in cryo-electron microscopy, and permits the identification of bridging interactions that either facilitate the conformational switching or maintain structural integrity of the 50S/30S interface. Motions of the tRNAs residing in the A and P sites also suggest the early stages of tRNA translocation as a result of this ratchet-like movement. Displacement of the L1 stalk, alternately closing and opening the intersubunit space near the E site, is observed in the dynamic model, in line with growing experimental evidence for the role of this structural component in facilitating the exiting of tRNA. Finally, a hinge-like transition in the 30S ribosomal subunit, similar to that observed in crystal structures of this complex, is also manifest as a dynamic mode of the ribosome. The coincidence of these dynamic transitions with the individual normal modes of the ribosome and the good correspondence between these motions and those observed in experiment suggest an underlying principle of nature to exploit the shape of molecular assemblies such as the ribosome to provide robustness to functionally important motions.

The dynamics of information-driven coordination phenomena: A transfer entropy analysis

Data from social media provide unprecedented opportunities to investigate the processes that govern the dynamics of collective social phenomena. We consider an information theoretical approach to define and measure the temporal and structural signatures typical of collective social events as they arise and gain prominence. We use the symbolic transfer entropy analysis of microblogging time series to extract directed networks of influence among geolocalized subunits in social systems. This methodology captures the emergence of system-level dynamics close to the onset of socially relevant collective phenomena. The framework is validated against a detailed empirical analysis of five case studies. In particular, we identify a change in the characteristic time scale of the information transfer that flags the onset of information-driven collective phenomena. Furthermore, our approach identifies an order-disorder transition in the directed network of influence between social subunits. In the absence of clear exogenous driving, social collective phenomena can be represented as endogenously driven structural transitions of the information transfer network. This study provides results that can help define models and predictive algorithms for the analysis of societal events based on open source data.

Using Skewness and the First-Digit Phenomenon to Identify Dynamical Transitions in Cardiac Models

Disruptions in the normal rhythmic functioning of the heart, termed as arrhythmia, often result from qualitative changes in the excitation dynamics of the organ. The transitions between different types of arrhythmia are accompanied by alterations in the spatiotemporal pattern of electrical activity that can be measured by observing the time-intervals between successive excitations of different regions of the cardiac tissue. Using biophysically detailed models of cardiac activity we show that the distribution of these time-intervals exhibit a systematic change in their skewness during such dynamical transitions. Further, the leading digits of the normalized intervals appear to fit Benford's law better at these transition points. This raises the possibility of using these observations to design a clinical indicator for identifying changes in the nature of arrhythmia. More importantly, our results reveal an intriguing relation between the changing skewness of a distribution and its agreement with Benford's law, both of which have been independently proposed earlier as indicators of regime shift in dynamical systems.

Punctuated virus-driven succession generates dynamical alternations in CRISPR-mediated microbe-virus coevolution

The coevolutionary dynamics of lytic viruses and microbes with CRISPR-Cas immunity exhibit alternations between sustained host control of viral proliferation and major viral epidemics in previous computational models. These alternating dynamics have yet to be observed in other host-pathogen systems. Here, we address the breakdown of control and transition to large outbreaks with a stochastic eco-evolutionary model. We establish the role of host density-dependent competition in punctuated virus-driven succession and associated diversity trends that concentrate escape pathways during control phases. Using infection and escape networks, we derive the viral emergence probability whose fluctuations of increasing size and frequency characterize the approach to large outbreaks. We explore alternation probabilities as a function of non-dimensional parameters related to the probability of viral escape and host competition. Our results demonstrate how emergent feedbacks between host competition and viral diversification render the host immune structure fragile, potentiating a dynamical transition to large epidemics.