Adaptation of pineal expressed teleost exo-rod opsin to non-image forming photoreception through enhanced Meta II decay

Photoreception by vertebrates enables both image-forming vision and non-image-forming responses such as circadian photoentrainment. Over the recent years, distinct non-rod non-cone photopigments have been found to support circadian photoreception in diverse species. By allowing specialization to this sensory task a selective advantage is implied, but the nature of that specialization remains elusive. We have used the presence of distinct rod opsin genes specialized to either image-forming (retinal rod opsin) or non-image-forming (pineal exo-rod opsin) photoreception in ray-finned fish (Actinopterygii) to gain a unique insight into this problem. A comparison of biochemical features for these paralogous opsins in two model teleosts, Fugu pufferfish (Takifugu rubripes) and zebrafish (Danio rerio), reveals striking differences. While spectral sensitivity is largely unaltered by specialization to the pineal environment, in other aspects exo-rod opsins exhibit a behavior that is quite distinct from the cardinal features of the rod opsin family. While they display a similar thermal stability, they show a greater than tenfold reduction in the lifetime of the signaling active Meta II photoproduct. We show that these features reflect structural changes in retinal association domains of helices 3 and 5 but, interestingly, not at either of the two residues known to define these characteristics in cone opsins. Our findings suggest that the requirements of non-image-forming photoreception have lead exo-rod opsin to adopt a characteristic that seemingly favors efficient bleach recovery but not at the expense of absolute sensitivity

Continuous population-level monitoring of SARS-CoV-2 seroprevalence in a large European metropolitan region.

Effective public health measures against SARS-CoV-2 require granular knowledge of population-level immune responses. We developed a Tripartite Automated Blood Immunoassay (TRABI) to assess the IgG response against three SARS-CoV-2 proteins. We used TRABI for continuous seromonitoring of hospital patients and blood donors (n = 72'250) in the canton of Zurich from December 2019 to December 2020 (pre-vaccine period). We found that antibodies waned with a half-life of 75 days, whereas the cumulative incidence rose from 2.3% in June 2020 to 12.2% in mid-December 2020. A follow-up health survey indicated that about 10% of patients infected with wildtype SARS-CoV-2 sustained some symptoms at least twelve months post COVID-19. Crucially, we found no evidence of a difference in long-term complications between those whose infection was symptomatic and those with asymptomatic acute infection. The cohort of asymptomatic SARS-CoV-2-infected subjects represents a resource for the study of chronic and possibly unexpected sequelae

Modeling GPCRs

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Ligand and structure-based methodologies for the prediction of the activity of G protein-coupled receptor ligands

Accurate in silico models for the quantitative prediction of the activity of G protein-coupled receptor (GPCR) ligands would greatly facilitate the process of drug discovery and development. Several methodologies have been developed based on the properties of the ligands, the direct study of the receptor-ligand interactions, or a combination of both approaches. Ligand-based three-dimensional quantitative structure-activity relationships (3D-QSAR) techniques, not requiring knowledge of the receptor structure, have been historically the first to be applied to the prediction of the activity of GPCR ligands. They are generally endowed with robustness and good ranking ability; however they are highly dependent on training sets. Structure-based techniques generally do not provide the level of accuracy necessary to yield meaningful rankings when applied to GPCR homology models. However, they are essentially independent from training sets and have a sufficient level of accuracy to allow an effective discrimination between binders and nonbinders, thus qualifying as viable lead discovery tools. The combination of ligand and structure-based methodologies in the form of receptor-based 3D-QSAR and ligand and structure-based consensus models results in robust and accurate quantitative predictions. The contribution of the structure-based component to these combined approaches is expected to become more substantial and effective in the future, as more sophisticated scoring functions are developed and more detailed structural information on GPCRs is gathered