Biology subjects

Zhai, R.

Publications and source records attributed to Zhai, R..

3 recordsLinked to original sources

bioRxiv2023

Distinct activation mechanisms of β-arrestin 1 revealed by 19F NMR spectroscopy

{beta}-Arrestins ({beta}arrs) are functionally versatile proteins that play critical roles in the G-protein-coupled receptor (GPCR) signaling pathways. While the classical theory of GPCR-mediated {beta}arr activation centers around the formation of a stable complex between {beta}arr and the phosphorylated receptor tail, emerging evidences highlight the indispensable contribution from membrane lipids for many receptors. Due to the intrinsic complexity of {beta}arr conformational dynamics, detailed molecular mechanisms of its activation by different binding partners remain elusive. Herein we present a comprehensive study of the structural changes of {beta}arr1 in critical structural regions during activation using 19F NMR method. We demonstrate that phosphopeptides derived from different classes of GPCRs show distinct abilities in inducing {beta}arr1 activation. We further show that the membrane phosphoinositide PIP2 independently modulates {beta}arr1 conformational dynamics without displacing its autoinhibitory carboxyl tail, leading to a distinct partially activated state. Our results delineate two activation mechanisms of {beta}arr1 by different binding partners, uncovering a highly multifaceted conformational energy landscape for this protein family.

biochemistry↗

bioRxiv2022

Pathobionts from chemically disrupted gut microbiota induce insulin-dependent diabetes in mice

BackgroundDysbiotic gut microbiome, genetically predisposed or chemically disrupted, has been linked with insulin-dependent diabetes (IDD) including autoimmune type 1 diabetes (T1D) in both humans and animal models. However, specific IDD-inducing gut bacteria remain to be identified and their casual role in disease development demonstrated via experiments that can fulfill Kochs postulates. ResultsHere, we show that novel gut pathobionts in the Muribaculaceae family, enriched by a low-dose dextran sulfate sodium (DSS) treatment, translocated to the pancreas and caused local inflammation, beta cell destruction and IDD in C57BL/6 mice. Antibiotic removal and transplantation of gut microbiota showed that this low DSS disrupted gut microbiota was both necessary and sufficient to induce IDD. Reduced butyrate content in the gut and decreased gene expression levels of an antimicrobial peptide in the pancreas allowed for the enrichment of members in the Muribaculaceae family in the gut and their translocation to the pancreas. Pure isolate of one such members induced IDD in wildtype germ-free mice on normal diet either alone or in combination with normal gut microbiome after gavaged into stomach and translocated to pancreas. ConclusionThe pathobionts that are chemically enriched in dysbiotic gut microbiota are sufficient to induce insulin-dependent diabetes after translocation to the pancreas. This indicates that IDD can be mainly a microbiome-dependent disease, inspiring the need to search for novel pathobionts for IDD development in humans.

microbiology↗

bioRxiv2021

4DPhenoMVS: A Low-Cost 3D Tomato Phenotyping Pipeline Using a 3D Reconstruction Point Cloud Based on Multiview Images

Manual phenotyping of tomato plants is time consuming and labor intensive. Due to the lack of low-cost and open-access 3D phenotyping tools, the dynamic 3D growth of tomato plants during all growth stages has not been fully explored. In this study, based on the 3D structural data points generated by employing structures from motion algorithms on multiple-view images, we proposed a dynamic 3D phenotyping pipeline, 4DPhenoMVS, to calculate and analyze 14 phenotypic traits of tomato plants covering the whole life cycle. The results showed that the R2 values between the phenotypic traits and the manual measurements stem length, plant height, and internode length were more than 0.8. In addition, to investigate the environmental influence on tomato plant growth and yield in the greenhouse, eight tomato plants were chosen and phenotyped during 7 growth stages according to different light intensities, temperatures, and humidities. The results showed that stronger light intensity and moderate temperature and humidity contribute to a higher growth rate and higher yield. In conclusion, we developed a low-cost and open-access 3D phenotyping pipeline for tomato plants, which will benefit tomato breeding, cultivation research, and functional genomics in the future. HighlightsBased on the 3D structural data points generated by employing structures from motion algorithms on multiple-view images, we developed a low-cost and open-access 3D phenotyping tool for tomato plants during all growth stages.

plant biology↗