Structural studies on tobacco streak virus coat protein: Insights into the pleomorphic nature of ilarviruses

Tobacco streak virus (TSV), the type member of Ilarvirus genus, is a major plant pathogen. TSV purified from infected plants consists of a ss-RNA genome encapsidated in spheroidal particles with diameters of 27, 30 and 33 nm constructed from multiple copies of a single species of coat protein (CP) subunits. Apart from protecting the viral genome, CPs of ilarviruses play several key roles in the life cycle of these viruses. Unlike the related bromo and cucumoviruses, ilarvirus particles are labile and pleomorphic, which has posed difficulties in their crystallization and structure determination. In the current study, a truncated TSV-CP was crystallized in two distinct forms and their structures were determined at resolutions of 2.4 angstrom and 2.1 angstrom, respectively. The core of TSV CP was found to possess the canonical beta-barrel jelly roll tertiary structure observed in several other viruses. Dimers of CP with swapped C-terminal arms (C-arm) were observed in both the crystal forms. The C-arm was found to be flexible and is likely to be responsible for the polymorphic and pleomorphic nature of TSV capsids. Consistent with this observation, mutations in the hinge region of the C-arm that reduce the flexibility resulted in the formation of more uniform particles. TSV CP was found to be structurally similar to that of Alfalfa mosaic virus (AMV) accounting for similar mechanism of genome activation in alfamo and ilar viruses. This communication represents the first report on the structure of the CP from an ilarvirus. (C) 2015 Elsevier Inc. All rights reserved.

Comparison of Matching Pursuit Algorithm with Other Signal Processing Techniques for Computation of the Time-Frequency Power Spectrum of Brain Signals

Signals recorded from the brain often show rhythmic patterns at different frequencies, which are tightly coupled to the external stimuli as well as the internal state of the subject. In addition, these signals have very transient structures related to spiking or sudden onset of a stimulus, which have durations not exceeding tens of milliseconds. Further, brain signals are highly nonstationary because both behavioral state and external stimuli can change on a short time scale. It is therefore essential to study brain signals using techniques that can represent both rhythmic and transient components of the signal, something not always possible using standard signal processing techniques such as short time fourier transform, multitaper method, wavelet transform, or Hilbert transform. In this review, we describe a multiscale decomposition technique based on an over-complete dictionary called matching pursuit (MP), and show that it is able to capture both a sharp stimulus-onset transient and a sustained gamma rhythm in local field potential recorded from the primary visual cortex. We compare the performance of MP with other techniques and discuss its advantages and limitations. Data and codes for generating all time-frequency power spectra are provided.