Dissecting eukaryotic translation and its control by ribosome density mapping

Translation of an mRNA is generally divided into three stages: initiation, elongation and termination. The relative rates of these steps determine both the number and position of ribosomes along the mRNA, but traditional velocity sedimentation assays for the translational status of mRNA determine only the number of bound ribosomes. We developed a procedure, termed Ribosome Density Mapping (RDM), that uses site-specific cleavage of polysomal mRNA followed by separation on a sucrose gradient and northern analysis, to determine the number of ribosomes associated with specified portions of a particular mRNA. This procedure allows us to test models for translation and its control, and to examine properties of individual steps of translation in vivo. We tested specific predictions from the current model for translational control of GCN4 expression in yeast and found that ribosomes were differentially associated with the uORFs elements and coding region under different growth conditions, consistent with this model. We also mapped ribosome density along the ORF of several mRNAs, to probe basic kinetic properties of translational steps in yeast. We found no detectable decline in ribosome density between the 5′ and 3′ ends of the ORFs, suggesting that the average processivity of elongation is very high. Conversely, there was no queue of ribosomes at the termination site, suggesting that termination is not very slow relative to elongation and initiation. Finally, the RDM results suggest that less frequent initiation of translation on mRNAs with longer ORFs is responsible for the inverse correlation between ORF length and ribosomal density that we observed in a global analysis of translation. These results provide new insights into eukaryotic translation in vivo

Diffuse Optical Tomography Activation in the Somatosensory Cortex: Specific Activation by Painful vs. Non-Painful Thermal Stimuli

Background: Pain is difficult to assess due to the subjective nature of self-reporting. The lack of objective measures of pain has hampered the development of new treatments as well as the evaluation of current ones. Functional MRI studies of pain have begun to delineate potential brain response signatures that could be used as objective read-outs of pain. Using Diffuse Optical Tomography (DOT), we have shown in the past a distinct DOT signal over the somatosensory cortex to a noxious heat stimulus that could be distinguished from the signal elicited by innocuous mechanical stimuli. Here we further our findings by studying the response to thermal innocuous and noxious stimuli. Methodology/Principal Findings: Innocuous and noxious thermal stimuli were applied to the skin of the face of the first division (ophthalmic) of the trigeminal nerve in healthy volunteers (N = 6). Stimuli temperatures were adjusted for each subject to evoke warm (equivalent to a 3/10) and painful hot (7/10) sensations in a verbal rating scale (0/10 = no/max pain). A set of 26 stimuli (5 sec each) was applied for each temperature with inter-stimulus intervals varied between 8 and 15 sec using a Peltier thermode. A DOT system was used to capture cortical responses on both sides of the head over the primary somatosensory cortical region (S1). For the innocuous stimuli, group results indicated mainly activation on the contralateral side with a weak ipsilateral response. For the noxious stimuli, bilateral activation was observed with comparable amplitudes on both sides. Furthermore, noxious stimuli produced a temporal biphasic response while innocuous stimuli produced a monophasic response. Conclusions/Significance: These results are in accordance with fMRI and our other DOT studies of innocuous mechanical and noxious heat stimuli. The data indicate the differentiation of DOT cortical responses for pain vs. innocuous stimuli that may be useful in assessing objectively acute pain

Evaluating anesthetic protocols for functional blood flow imaging in the rat eye

The purpose of this study is to evaluate the suitability of five different anesthetic protocols (isoflurane, isoflurane–xylazine, pentobarbital, ketamine–xylazine, and ketamine–xylazine–vecuronium) for functional blood flow imaging in the rat eye. Total retinal blood flow was measured at a series of time points using an ultrahigh-speed Doppler OCT system. Additionally, each anesthetic protocol was qualitatively evaluated according to the following criteria: (1) time-stability of blood flow, (2) overall rate of blood flow, (3) ocular immobilization, and (4) simplicity. We observed that different anesthetic protocols produced markedly different blood flows. Different anesthetic protocols also varied with respect to the four evaluated criteria. These findings suggest that the choice of anesthetic protocol should be carefully considered when designing and interpreting functional blood flow studies in the rat eye.United States. National Institutes of Health (R01-EY011289-29)United States. National Institutes of Health (R44-EY022864)United States. National Institutes of Health (R01-CA075289-16)United States. Air Force Office of Scientific Research (FA9550-15-1-0473)United States. Air Force Office of Scientific Research (FA9550-12-1-0499

COMPUTED TOMOGRAPHY BASED PREDICTION OF ANGIOGRAPHIC DEPLOYMENT ANGLES MAY REDUCE PROCEDURE TIME AND CONTRAST MEDIUM VOLUME FOR TRANSCATHETER AORTIC VALVE REPLACEMENT

Planas Calvet, LluísPrimer pla d'edifici unifamiliar, de dos habitatges adossats.De planta baixa, planta pis i golfes, i una torrassa adossada. Són de gran qualitat els esgrafiats del número 8 i les elaborades reixes de ferro forjat del número 10

Morphine Attenuates fNIRS Signal Associated With Painful Stimuli in the Medial Frontopolar Cortex (medial BA 10)

Functional near infrared spectroscopy (fNIRS) is a non-invasive optical imaging method that provides continuous measure of cortical brain functions. One application has been its use in the evaluation of pain. Previous studies have delineated a deoxygenation process associated with pain in the medial anterior prefrontal region, more specifically, the medial Brodmann Area 10 (BA 10). Such response to painful stimuli has been consistently observed in awake, sedated and anesthetized patients. In this study, we administered oral morphine (15 mg) or placebo to 14 healthy male volunteers with no history of pain or opioid abuse in a crossover double blind design, and performed fNIRS scans prior to and after the administration to assess the effect of morphine on the medial BA 10 pain signal. Morphine is the gold standard for inhibiting nociceptive processing, most well described for brain effects on sensory and emotional regions including the insula, the somatosensory cortex (the primary somatosensory cortex, S1, and the secondary somatosensory cortex, S2), and the anterior cingulate cortex (ACC). Our results showed an attenuation effect of morphine on the fNIRS-measured pain signal in the medial BA 10, as well as in the contralateral S1 (although observed in a smaller number of subjects). Notably, the extent of signal attenuation corresponded with the temporal profile of the reported plasma concentration for the drug. No clear attenuation by morphine on the medial BA 10 response to innocuous stimuli was observed. These results provide further evidence for the role of medial BA 10 in the processing of pain, and also suggest that fNIRS may be used as an objective measure of drug-brain profiles independent of subjective reports

Physics-based design of protein -ligand binding

Different potential energy functions have been used in protein dynamics simulations, protein design calculations, and protein structure prediction. Clearly, the same physics applies in all three cases, so the variation in potential energy functions reflects differences in how the calculations are performed. With improvements in computer power and algorithms, the same potential energy function should be applicable to all three problems. Here we show that a standard molecular-mechanics potential energy function without any modifications can be used to engineer protein-ligand binding. A molecular-mechanics potential is used to reconstruct the coordinates of various binding sites with an average root mean square error of 0.61 Å, and to reproduce known ligand-induced side-chain conformational shifts. Within a series of 34 mutants, the calculation can always distinguish weak ( Kd > 1 mM) and tight (Kd < 10 μM) binding sequences. Starting from partial coordinates of the ribose binding protein lacking the ligand and the ten primary contact residues, the molecular-mechanics potential is used to redesign a ribose binding site. Out of a search space of 2 × 1012 sequences, the calculation selects a point mutant of the native protein as the top solution (experimental Kd = 17 μM), and the native protein as the second best solution (experimental Kd = 210 nM). The quality of the predictions depends on the accuracy of the generalized Born electrostatics model, treatment of protonation equilibria, high resolution rotamer sampling, a final local energy minimization step, and explicit modeling of the bound, unbound, and unfolded states. After this initial proof of principle experiment, we next used a standard molecular mechanics potential energy function to redesign ribose binding protein to bind a series of ligands: L-arabinose, D-xylose, indole-3-acetic acid, and estradiol. The resulting proteins have 5–10 mutations from the native, are stable, the predicted structures have good hydrogen bonds and shape complementarity, and they use motifs similar to natural binding proteins. All of the designed proteins bind to their target ligands with measurable but weak affinity. The affinity was improved by random mutagenesis and screening. The application of unmodified molecular-mechanics potentials to protein design links two fields in a mutually beneficial way. Design provides a new avenue to test molecular-mechanics energy functions, and future improvements in these energy functions will presumably lead to more accurate design results. This is the first time a single model has been used to predict structures, binding constants, and to design new small-molecule binding sites. Using a standard model should improve the generality of protein design, which could enable the creation of custom proteins for a wide variety of applications, including sensors, enzymes, and protein therapeutics