Tracking Image Correlation: Combining Single-Particle Tracking and Image Correlation

The interactions and coordination of biomolecules are crucial for most cellular functions. The observation of protein interactions in live cells may provide a better understanding of the underlying mechanisms. After fluorescent labeling of the interacting partners and live-cell microscopy, the colocalization is generally analyzed by quantitative global methods. Recent studies have addressed questions regarding the individual colocalization of moving biomolecules, usually by using single-particle tracking (SPT) and comparing the fluorescent intensities in both color channels. Here, we introduce a new method that combines SPT and correlation methods to obtain a dynamical 3D colocalization analysis along single trajectories of dual-colored particles. After 3D tracking, the colocalization is computed at each particle’s position via the local 3D image cross correlation of the two detection channels. For every particle analyzed, the output consists of the 3D trajectory, the time-resolved 3D colocalization information, and the fluorescence intensity in both channels. In addition, the cross-correlation analysis shows the 3D relative movement of the two fluorescent labels with an accuracy of 30 nm. We apply this method to the tracking of viral fusion events in live cells and demonstrate its capacity to obtain the time-resolved colocalization status of single particles in dense and noisy environments.     

Combining Experiments and Simulations Using the Maximum Entropy Principle

A key component of computational biology is to compare the results of computer modelling with experimental measurements. Despite substantial progress in the models and algorithms used in many areas of computational biology, such comparisons sometimes reveal that the computations are not in quantitative agreement with experimental data. The principle of maximum entropy is a general procedure for constructing probability distributions in the light of new data, making it a natural tool in cases when an initial model provides results that are at odds with experiments. The number of maximum entropy applications in our field has grown steadily in recent years, in areas as diverse as sequence analysis, structural modelling, and neurobiology. In this Perspectives article, we give a broad introduction to the method, in an attempt to encourage its further adoption. The general procedure is explained in the context of a simple example, after which we proceed with a real-world application in the field of molecular simulations, where the maximum entropy procedure has recently provided new insight. Given the limited accuracy of force fields, macromolecular simulations sometimes produce results that are at not in complete and quantitative accordance with experiments. A common solution to this problem is to explicitly ensure agreement between the two by perturbing the potential energy function towards the experimental data. So far, a general consensus for how such perturbations should be implemented has been lacking. Three very recent papers have explored this problem using the maximum entropy approach, providing both new theoretical and practical insights to the problem. We highlight each of these contributions in turn and conclude with a discussion on remaining challenges.     

Concordance of Epileptic Networks Associated with Epileptic Spikes Measured by High-Density EEG and Fast fMRI

Objective

The present study aims to investigate whether a newly developed fast fMRI called MREG (magnetic resonance encephalography) measures metabolic changes related to interictal epileptic discharges (IED). For this purpose BOLD changes are correlated with the IED distribution and variability.

Methods

Patients with focal epilepsy underwent EEG-MREG using a 64 channel cap. IED voltage maps were generated using 32 and 64 channels and compared regarding their correspondence to the BOLD response. The extents of IEDs (defined as number of channels with >50% of maximum IED negativity) were correlated with the extents of positive and negative BOLD responses. Differences in inter-spike variability were investigated between interictal epileptic discharges (IED) sets with and without concordant positive or negative BOLD responses.

Results

17 patients showed 32 separate IED types. In 50% of IED types the BOLD changes could be confirmed by another independent imaging method. The IED extent significantly correlated with the positive BOLD extent (p = 0.04). In 6 patients the 64-channel EEG voltage maps better reflected the positive or negative BOLD response than the 32-channel EEG; in all others no difference was seen. Inter-spike variability was significantly lower in IED sets with than without concordant positive or negative BOLD responses (with p = 0.04).

Significance

Higher density EEG and fast fMRI seem to improve the value of EEG-fMRI in epilepsy. The correlation of positive BOLD and IED extent could suggest that widespread BOLD responses reflect the IED network. Inter-spike variability influences the likelihood to find IED concordant positive or negative BOLD responses, which is why single IED analysis may be promising.     

Understanding Actions of Others: The Electrodynamics of the Left and Right Hemispheres. A High-Density EEG Neuroimaging Study

Background

When we observe an individual performing a motor act (e.g. grasping a cup) we get two types of information on the basis of how the motor act is done and the context: what the agent is doing (i.e. grasping) and the intention underlying it (i.e. grasping for drinking). Here we examined the temporal dynamics of the brain activations that follow the observation of a motor act and underlie the observer''s capacity to understand what the agent is doing and why.

Methodology/Principal Findings

Volunteers were presented with two-frame video-clips. The first frame (T0) showed an object with or without context; the second frame (T1) showed a hand interacting with the object. The volunteers were instructed to understand the intention of the observed actions while their brain activity was recorded with a high-density 128-channel EEG system. Visual event-related potentials (VEPs) were recorded time-locked with the frame showing the hand-object interaction (T1). The data were analyzed by using electrical neuroimaging, which combines a cluster analysis performed on the group-averaged VEPs with the localization of the cortical sources that give rise to different spatio-temporal states of the global electrical field. Electrical neuroimaging results revealed four major steps: 1) bilateral posterior cortical activations; 2) a strong activation of the left posterior temporal and inferior parietal cortices with almost a complete disappearance of activations in the right hemisphere; 3) a significant increase of the activations of the right temporo-parietal region with simultaneously co-active left hemispheric sources, and 4) a significant global decrease of cortical activity accompanied by the appearance of activation of the orbito-frontal cortex.

Conclusions/Significance

We conclude that the early striking left hemisphere involvement is due to the activation of a lateralized action-observation/action execution network. The activation of this lateralized network mediates the understanding of the goal of object-directed motor acts (mirror mechanism). The successive right hemisphere activation indicates that this hemisphere plays an important role in understanding the intention of others.     

3d Trosy-HncaCodedcb and Trosy-HncaCodedco Experiments: Triple Resonance nmr Experiments With two Sequential Connectivity Pathways and High Sensitivity

The concept of chemical shift-coding monitors chemical shifts in multi-dimensional NMR experiments without additional polarization transfer elements and evolution periods. The chemical shifts are coded in the line-shape of the cross-peak through an apparent scalar coupling dependent upon the chemical shift. This concept is applied to the three-dimensional triple-resonance experiment HNCA adding the information of (13)C(beta) or (13)C' chemical shifts. On average, the proposed TROSY-HNCA(coded)CB experiment is a factor of 2 less sensitive than the HNCA experiment. However, it contains correlations via the chemical shifts of both (13)C(alpha) and (13)C(beta), and provides up to three times higher resolution along the (13)C(alpha) chemical shift axis. Thus, it dramatically reduces ambiguities in linking the spin systems of adjacent residues in the protein sequence during the sequential assignment. The TROSY-HNCA(coded)CO experiment which is conceptually similar contains correlations via the chemical shifts of (13)C(alpha) and (13)C' without major signal losses. The proposed triple resonance experiments are applied to a approximately 70% (2)H, approximately 85% (13)C,(15)N labeled protein with a molecular weight of 25 kDa.     

Identifying and Tracking Simulated Synaptic Inputs from Neuronal Firing: Insights from In Vitro Experiments

Accurately describing synaptic interactions between neurons and how interactions change over time are key challenges for systems neuroscience. Although intracellular electrophysiology is a powerful tool for studying synaptic integration and plasticity, it is limited by the small number of neurons that can be recorded simultaneously in vitro and by the technical difficulty of intracellular recording in vivo. One way around these difficulties may be to use large-scale extracellular recording of spike trains and apply statistical methods to model and infer functional connections between neurons. These techniques have the potential to reveal large-scale connectivity structure based on the spike timing alone. However, the interpretation of functional connectivity is often approximate, since only a small fraction of presynaptic inputs are typically observed. Here we use in vitro current injection in layer 2/3 pyramidal neurons to validate methods for inferring functional connectivity in a setting where input to the neuron is controlled. In experiments with partially-defined input, we inject a single simulated input with known amplitude on a background of fluctuating noise. In a fully-defined input paradigm, we then control the synaptic weights and timing of many simulated presynaptic neurons. By analyzing the firing of neurons in response to these artificial inputs, we ask 1) How does functional connectivity inferred from spikes relate to simulated synaptic input? and 2) What are the limitations of connectivity inference? We find that individual current-based synaptic inputs are detectable over a broad range of amplitudes and conditions. Detectability depends on input amplitude and output firing rate, and excitatory inputs are detected more readily than inhibitory. Moreover, as we model increasing numbers of presynaptic inputs, we are able to estimate connection strengths more accurately and detect the presence of connections more quickly. These results illustrate the possibilities and outline the limits of inferring synaptic input from spikes.     

Inferring Latent States and Refining Force Estimates via Hierarchical Dirichlet Process Modeling in Single Particle Tracking Experiments

Understanding the basis for intracellular motion is critical as the field moves toward a deeper understanding of the relation between Brownian forces, molecular crowding, and anisotropic (or isotropic) energetic forcing. Effective forces and other parameters used to summarize molecular motion change over time in live cells due to latent state changes, e.g., changes induced by dynamic micro-environments, photobleaching, and other heterogeneity inherent in biological processes. This study discusses limitations in currently popular analysis methods (e.g., mean square displacement-based analyses) and how new techniques can be used to systematically analyze Single Particle Tracking (SPT) data experiencing abrupt state changes in time or space. The approach is to track GFP tagged chromatids in metaphase in live yeast cells and quantitatively probe the effective forces resulting from dynamic interactions that reflect the sum of a number of physical phenomena. State changes can be induced by various sources including: microtubule dynamics exerting force through the centromere, thermal polymer fluctuations, and DNA-based molecular machines including polymerases and protein exchange complexes such as chaperones and chromatin remodeling complexes. Simulations aiming to show the relevance of the approach to more general SPT data analyses are also studied. Refined force estimates are obtained by adopting and modifying a nonparametric Bayesian modeling technique, the Hierarchical Dirichlet Process Switching Linear Dynamical System (HDP-SLDS), for SPT applications. The HDP-SLDS method shows promise in systematically identifying dynamical regime changes induced by unobserved state changes when the number of underlying states is unknown in advance (a common problem in SPT applications). We expand on the relevance of the HDP-SLDS approach, review the relevant background of Hierarchical Dirichlet Processes, show how to map discrete time HDP-SLDS models to classic SPT models, and discuss limitations of the approach. In addition, we demonstrate new computational techniques for tuning hyperparameters and for checking the statistical consistency of model assumptions directly against individual experimental trajectories; the techniques circumvent the need for “ground-truth” and/or subjective information.     

Keep Your Opponents Close: Social Context Affects EEG and fEMG Linkage in a Turn-Based Computer Game

In daily life, we often copy the gestures and expressions of those we communicate with, but recent evidence shows that such mimicry has a physiological counterpart: interaction elicits linkage, which is a concordance between the biological signals of those involved. To find out how the type of social interaction affects linkage, pairs of participants played a turn-based computer game in which the level of competition was systematically varied between cooperation and competition. Linkage in the beta and gamma frequency bands was observed in the EEG, especially when the participants played directly against each other. Emotional expression, measured using facial EMG, reflected this pattern, with the most competitive condition showing enhanced linkage over the facial muscle-regions involved in smiling. These effects were found to be related to self-reported social presence: linkage in positive emotional expression was associated with self-reported shared negative feelings. The observed effects confirmed the hypothesis that the social context affected the degree to which participants had similar reactions to their environment and consequently showed similar patterns of brain activity. We discuss the functional resemblance between linkage, as an indicator of a shared physiology and affect, and the well-known mirror neuron system, and how they relate to social functions like empathy.     

Effect of EEG Biofeedback on Cognitive Flexibility in Children with Attention Deficit Hyperactivity Disorder With and Without Epilepsy

Attention deficit hyperactivity disorder (ADHD) is one of the most common developmental disorders in school-aged children. Symptoms consistent with ADHD have been observed in 8–77 % of children with epilepsy. Researchers have been motivated to search for alternative forms of treatment because 30 % of patients with ADHD cannot be treated by psychostimulants. Several studies support the use of a multimodal treatment approach that includes neurofeedback (NF) for the long-term management of ADHD. These studies have shown that NF provides a sustained effect, even without concurrent treatment with stimulants. We aimed to assess cognitive flexibility in ADHD children with and without temporal lobe epilepsy (TLE), and to evaluate the effects of NF on cognitive flexibility in these groups of children. We prospectively evaluated 69 patients with ADHD aged 9–12 years. The control group was 26 ADHD children without TLE who received no treatment. The first experimental group comprised 18 children with ADHD. The second experimental group comprised 25 age-matched ADHD children with TLE. This group was further divided in two subgroups. One subgroup comprised those with mesial temporal lobe epilepsy (16 patients, 9 with hippocampal sclerosis and 7 with hippocampal atrophy), and the other with lateral temporal lobe epilepsy (9 patients, 5 with temporal lobe dysplasia, 3 with temporal lobe cysts, and 1 with a temporal lobe cavernoma). We treated their ADHD by conducting 30 sessions of EEG NF. Reaction time and error rates on the Trail Making Test Part B were compared before and after treatment, and significant differences were found for all groups of patients except those who had mesial temporal lobe epilepsy with hippocampal atrophy. Our results demonstrate that in most cases, NF can be considered an alternative treatment option for ADHD children even if they have TLE. Additional studies are needed to confirm our results.     

Eye Tracking,Cortisol, and a Sleep vs. Wake Consolidation Delay: Combining Methods to Uncover an Interactive Effect of Sleep and Cortisol on Memory

Although rises in cortisol can benefit memory consolidation, as can sleep soon after encoding, there is currently a paucity of literature as to how these two factors may interact to influence consolidation. Here we present a protocol to examine the interactive influence of cortisol and sleep on memory consolidation, by combining three methods: eye tracking, salivary cortisol analysis, and behavioral memory testing across sleep and wake delays. To assess resting cortisol levels, participants gave a saliva sample before viewing negative and neutral objects within scenes. To measure overt attention, participants’ eye gaze was tracked during encoding. To manipulate whether sleep occurred during the consolidation window, participants either encoded scenes in the evening, slept overnight, and took a recognition test the next morning, or encoded scenes in the morning and remained awake during a comparably long retention interval. Additional control groups were tested after a 20 min delay in the morning or evening, to control for time-of-day effects. Together, results showed that there is a direct relation between resting cortisol at encoding and subsequent memory, only following a period of sleep. Through eye tracking, it was further determined that for negative stimuli, this beneficial effect of cortisol on subsequent memory may be due to cortisol strengthening the relation between where participants look during encoding and what they are later able to remember. Overall, results obtained by a combination of these methods uncovered an interactive effect of sleep and cortisol on memory consolidation.     

Computer Aided Study of Ligand Binding With Catalytic Domain of Avian Sarcoma Virus Integrase and Its Ligand Binding Loops

Abstract

We have carried out 1 nanosecond (ns) Molecular Dynamics (MD) simulations of the drug Y3 (4-acetylamino-5-hydroxynaphthalene-2, 7-disulfonic acid) complexed with catalytic domain of Avian sarcoma virus Integrase (ASV-IN), both in vacuum and in the presence of explicit solvent. Starting models were obtained on the basis of PDB co-ordinates (1A5X) of ASV-IN-Y3 complex, by Lubkowski et al [1]. Mn²⁺ cation was present in the active site. To neutralize the positive charge in the presence of explicit solvent, eight Cl^? anions were added. Energy Minimization (EM) and MD simulations, for both the systems, were carried out using Sander's module of AMBER5.0 [2] with all atom force field. Analysis of ligand- protein interaction in both environments is discussed in the paper. We also carried out 1 ns MD simulation on two flexible loops—L1 (Gly54-Gln62) and L2 (Trp138-Met155) playing crucial role in interaction of IN with the drug [3], under differing environmental conditions (vacuum, aqueous and organic solvent methanol). Comparison of the conformational changes in the loops, monomer and dimer is presented in the paper. Our results showed that the conformation of the loop region was closest to crystallographic data in case of monomer and constrained loops in aqueous environment. However, the dimer in vacuum was more stable than monomer. The β sheet structure of the monomer in aqueous environment was unstable. Latter also took long time for equilibration. The box formed by loops L1 and L2 from two sub units IINA and INB) of the dimer satisfies prerequisites for ligand recognition site and seems to be the functional biological unit.