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Biology subjects

Lin, H.-T.

Publications and source records attributed to Lin, H.-T..

2 recordsLinked to original sources

Impacts on the structure-function relationship of SARS-CoV-2 spike by B.1.1.7 mutations

The UK variant of the severe acute respiratory syndrome coronavirus (SARS-CoV-2), known as B.1.1.7, harbors several point mutations and deletions on the spike (s) protein, which potentially alter its structural epitopes to evade host immunity while enhancing host receptor binding. Here we report the cryo-EM structures of the S protein of B.1.1.7 in its apo form and in the receptor ACE2-bound form. One or two of the three receptor binding domains (RBDs) were in the open conformation but no fully closed form was observed. In the ACE-bound form, all three RBDs were engaged in receptor binding. The B.1.1.7-specific A570D mutation introduced a salt bridge switch that could modulate the opening and closing of the RBD. Furthermore, the N501Y mutation in the RBD introduced a favorable {pi}-{pi} interaction manifested in enhanced ACE2 binding affinity. The N501Y mutation abolished the neutralization activity of one of the three potent neutralizing antibodies (nAbs). Cryo-EM showed that the cocktail of other two nAbs simultaneously bound to all three RBDs. Furthermore, the nAb cocktail synergistically neutralized different SARS-CoV-2 pseudovirus strains, including the B.1.1.7.

biochemistry

Complete neuroanatomy and sensor maps of Odonata wings for fly-by-feel flight control

Can mechanosensors in animal wings allow reconstruction of the wing aeroelastic states? Little is known about how flying animals utilize wing mechanosensation to monitor the dynamic state of their highly deformable wings. Odonata, dragonflies and damselflies, are a basal lineage of flying insects with excellent flight performance, and their wing mechanics have been studied extensively. Here, we present a comprehensive map of the wing sensory system for two Odonata species, including both the external sensor morphologies and internal neuroanatomy. We identified eight morphological classes of sensors; most were mechanosensors innervated by a single neuron. Their innervation patterns and morphologies minimize axon length and allow morphological latency compensation. We further mapped the major veins of another 13 Odonata species across 10 families and identified consistent sensor distribution patterns, with sensor count scaling with wing length. Finally, we constructed a high-fidelity finite element model of a dragonfly wing for structural analysis. Our dynamic loading simulations revealed features of the strain fields that wing sensor arrays could detect to encode different wing deformation states. Taken together, this work marks the first step toward an integrated understanding of fly-by-feel control in animal flight.

neuroscience