Divergence of protamine gene sequences in fish

Complementary DNA to trout protamine mRNA was hybridized to excess genomic DNA from trout, salmon and yellow perch. Although there was extensive hybridization of the cDNA to trout DNA, no cross-reaction with yellow perch DNA was observed and the hybridization to salmon DNA was noticeably less than in the homologous reaction. To confirm these results, yellow perch protamine mRNA was purified and compared directly to trout protamine mRNA. Yellow perch protamine mRNA was shorter than trout protamine mRNA, when measured by agarose gel electrophoresis in the presence of methyl mercury hydroxide. The two mRNAs did not cross-react in cDNA/RNA hybridizations, although the homologous reactions went to 90% of completion. This lack of sequence homology was confirmed when the oligopyrimidine tracts from the cDNAs were compared. No sequences longer than tetranucleotides were common to both species. Trout protamine cDNA contained oligopyrimidines of composition C₇T₄, C₄T₂, C₃T₂, C₂T₄, C₂T₃, C₁T₅ and C₁T whereas yellow perch protamine cDNA contained C₆T₃ and C₄T₃.     

Testing the precision and sensitivity of density estimates obtained with a camera‐trap method revealed limitations and opportunities

The use of camera traps in ecology helps affordably address questions about the distribution and density of cryptic and mobile species. The random encounter model (REM) is a camera‐trap method that has been developed to estimate population densities using unmarked individuals. However, few studies have evaluated its reliability in the field, especially considering that this method relies on parameters obtained from collared animals (i.e., average speed, in km/h), which can be difficult to acquire at low cost and effort. Our objectives were to (1) assess the reliability of this camera‐trap method and (2) evaluate the influence of parameters coming from different populations on density estimates. We estimated a reference density of black bears (Ursus americanus) in Forillon National Park (Québec, Canada) using a spatial capture–recapture estimator based on hair‐snag stations. We calculated average speed using telemetry data acquired from four different bear populations located outside our study area and estimated densities using the REM. The reference density, determined with a Bayesian spatial capture–recapture model, was 2.87 individuals/10km² [95% CI: 2.41–3.45], which was slightly lower (although not significatively different) than the different densities estimated using REM (ranging from 4.06–5.38 bears/10km² depending on the average speed value used). Average speed values obtained from different populations had minor impacts on REM estimates when the difference in average speed between populations was low. Bias in speed values for slow‐moving species had more influence on REM density estimates than for fast‐moving species. We pointed out that a potential overestimation of density occurs when average speed is underestimated, that is, using GPS telemetry locations with large fix‐rate intervals. Our study suggests that REM could be an affordable alternative to conventional spatial capture–recapture, but highlights the need for further research to control for potential bias associated with speed values determined using GPS telemetry data.     

Distribution of lung density after strenuous, prolonged exercise.

The postexercise alteration in pulmonary gas exchange in high-aerobically trained subjects depends on both the intensity and the duration of exercise (G. Manier, J. Moinard, and H. Sto?cheff. J. Appl. Physiol. 75: 2580-2585, 1993; G. Manier, J. Moinard, P. Techoueyres, N. Varène, and H. Guénard. Respir. Physiol. 83: 143-154, 1991). In a recent study that used lung computerized tomography (CT), evidence was found for accumulation of water within the lungs after exercise (C. Caillaud, O. Serre-Cousine, F. Anselme, X. Capdevilla, and C. Prefaut. J. Appl. Physiol. 79: 1226-1232, 1995). On representative slices of the lungs, mean lung density increased by 0.040 +/- 0.007 g/cm(3) (19%, P < 0.001) in athletes after a triathlon. To verify and quantify the mechanism, we determined the change in pulmonary density and mass after strenuous and prolonged exercise using another exercise protocol and methodology for CT scanning. Nine trained runners (age 30-46 yr) volunteered to participate in the study. Each subject ran for 2 h on a treadmill at a rate corresponding to 75% of maximum O(2) consumption. CT measurements were made before and immediately after the exercise test with the subject supine and holding his breath at a point close to functional residual capacity. The lungs were scanned from the apex to the diaphragm and reconstructed in 8-mm-thick slices. Attenuation values of X-rays in each part of the lung were expressed in Hounsfield units (HU), which are related to density (D): D = 1 + HU/1,000. No significant alteration in pulmonary density (0.37 +/- 0.04 vs. 0.35 +/- 0.03, not significant) was observed after the 2-h run test. Although lung volume slightly increased (change of 166 +/- 205 ml, P < 0.05), lung mass remained stable because of a change in density distribution. We failed to detect any changes in postexercise lung mass, suggesting that other mechanisms need to be considered to explain the observed alterations in pulmonary gas exchange after prolonged strenuous exercise.     

A Chemical Proteomics Approach for the Search of Pharmacological Targets of the Antimalarial Clinical Candidate Albitiazolium in Plasmodium falciparum Using Photocrosslinking and Click Chemistry

Plasmodium falciparum is responsible for severe malaria which is one of the most prevalent and deadly infectious diseases in the world. The antimalarial therapeutic arsenal is hampered by the onset of resistance to all known pharmacological classes of compounds, so new drugs with novel mechanisms of action are critically needed. Albitiazolium is a clinical antimalarial candidate from a series of choline analogs designed to inhibit plasmodial phospholipid metabolism. Here we developed an original chemical proteomic approach to identify parasite proteins targeted by albitiazolium during their native interaction in living parasites. We designed a bifunctional albitiazolium-derived compound (photoactivable and clickable) to covalently crosslink drug–interacting parasite proteins in situ followed by their isolation via click chemistry reactions. Mass spectrometry analysis of drug–interacting proteins and subsequent clustering on gene ontology terms revealed parasite proteins involved in lipid metabolic activities and, interestingly, also in lipid binding, transport, and vesicular transport functions. In accordance with this, the albitiazolium-derivative was localized in the endoplasmic reticulum and trans-Golgi network of P. falciparum. Importantly, during competitive assays with albitiazolium, the binding of choline/ethanolamine phosphotransferase (the enzyme involved in the last step of phosphatidylcholine synthesis) was substantially displaced, thus confirming the efficiency of this strategy for searching albitiazolium targets.     

Somatosensory-Motor Adaptation of Orofacial Actions in Posterior Parietal and Ventral Premotor Cortices

Recent studies have provided evidence for sensory-motor adaptive changes and action goal coding of visually guided manual action in premotor and posterior parietal cortices. To extend these results to orofacial actions, devoid of auditory and visual feedback, we used a repetition suppression paradigm while measuring neural activity with functional magnetic resonance imaging during repeated intransitive and silent lip, jaw and tongue movements. In the motor domain, this paradigm refers to decreased activity in specific neural populations due to repeated motor acts and has been proposed to reflect sensory-motor adaptation. Orofacial movements activated a set of largely overlapping, common brain areas forming a core neural network classically involved in orofacial motor control. Crucially, suppressed neural responses during repeated orofacial actions were specifically observed in the left ventral premotor cortex, the intraparietal sulcus, the inferior parietal lobule and the superior parietal lobule. Since no visual and auditory feedback were provided during orofacial actions, these results suggest somatosensory-motor adaptive control of intransitive and silent orofacial actions in these premotor and parietal regions.