scholarly journals Structural Characteristics and Proton Conductivity of the Gel Within the Electrosensory Organs of Cartilaginous Fishes

2021 ◽  
Author(s):  
Molly Phillips ◽  
Alauna Wheeler ◽  
Matthew J. Robinson ◽  
Valerie Leppert ◽  
Manping Jia ◽  
...  

AbstractThe Ampullae of Lorenzini (AoL) of cartilaginous fishes are sensory organs used to detect environmental electric fields. The proximal ends of the organs are externally visible as pores in the skin that lead into gel-filled tubular canals which terminate in rounded chambers filled with highly specialized electrosensory cells. The viscoelastic gel that fills the organs is composed of proteins and polysaccharides that are not yet completely characterized but are thought to play a critical role in the electrosensing mechanism. Although recent studies have identified various components of AoL gel, it has remained unclear how the component molecules are structurally arranged and how their structure influences the overall function of the AoL. Here we present the first microscopic descriptions and x-ray scattering data from AoL gel extracted from spotted ratfish (Hydrolagus colliei). Our results suggest that AoL gel is colloidal in nature and composed of spherical globules that are approximately 10-100 nm in size. We investigated the structural influence of the protein components of the gel specifically by analyzing gel that had been digested in situ via enzymatic proteolysis. By comparing gel before and after digestion using microscopy, x-ray scattering analyses, and proton conductivity measurements, we directly observed the structural and functional influence of proteins in AoL gel. The findings described here represent the first detailed structural analysis of AoL gel and lay the groundwork for more detailed studies into the specific interactions of molecules inside AoL gel at the nanoscale, with particular reference to their mechanistic role in electrosensing.

2018 ◽  
Vol 122 (45) ◽  
pp. 10320-10329 ◽  
Author(s):  
Amin Sadeghpour ◽  
Marjorie Ladd Parada ◽  
Josélio Vieira ◽  
Megan Povey ◽  
Michael Rappolt

1995 ◽  
Author(s):  
Yibin Zheng ◽  
Peter C. Doerschuk ◽  
John E. Johnson

2020 ◽  
Author(s):  
Steve P. Meisburger ◽  
Da Xu ◽  
Nozomi Ando

AbstractMixtures of biological macromolecules are inherently difficult to study using structural methods, as increasing complexity presents new challenges for data analysis. Recently, there has been growing interest in studying evolving mixtures using small-angle X-ray scattering (SAXS) in conjunction with time-resolved, high-throughput, or chromatography-coupled setups. Deconvolution and interpretation of the resulting datasets, however, are nontrivial when neither the scattering components nor the way in which they evolve are known a priori. To address this issue, we introduce the REGALS method (REGularized Alternating Least Squares), which incorporates simple expectations about the data as prior knowledge and utilizes parameterization and regularization to provide robust deconvolution solutions. The restraints used by REGALS are general properties such as smoothness of profiles and maximum dimensions of species, which makes it well-suited for exploring datasets with unknown species. Here we apply REGALS to analyze experimental data from four types of SAXS experiment: anion-exchange (AEX) coupled SAXS, ligand titration, time-resolved mixing, and time-resolved temperature jump. Based on its performance with these challenging datasets, we anticipate that REGALS will be a valuable addition to the SAXS analysis toolkit and enable new experiments. The software is implemented in both MATLAB and python and is available freely as an open-source software package.


2008 ◽  
Vol 95 (5) ◽  
pp. 2356-2367 ◽  
Author(s):  
Norbert Kučerka ◽  
John F. Nagle ◽  
Jonathan N. Sachs ◽  
Scott E. Feller ◽  
Jeremy Pencer ◽  
...  

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