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Shang, D.

Publications and source records attributed to Shang, D..

3 recordsLinked to original sources

Engineered AIM-based Selective Autophagy to Degrade Proteins and Organelles

Techniques for disrupting of protein function are essential for biological researches and therapeutics development. Though well-established, genetic perturbation strategies may have off-target effects and/or trigger compensatory mechanisms, and cannot efficiently eliminate existing protein variants or aggregates1, 2. Therefore, precise and direct protein-targeting methods are highly desired. Here we describe a novel method for targeted protein clearance by engineering an autophagy receptor with a binder to provide target specificity and an ATG8-binding motif (AIM) to link the targets to nascent autophagosomes, thus harnessing the autophagy machinery for degradation. We demonstrate its specificity and broad potentials by degrading various fluorescent-tagged proteins and peroxisome organelle, using a tobacco-based transient expression system, and by degrading endogenous proteins in transgenic Arabidopsis expressing engineered receptors. With the wide substrate scope and specificity of selective autophagy, our method provides a convenient and robust strategy for eliminating proteins and aggregates, and may enable developing new treatments for protein-related disorders.

cell biology

Synergistic Therapy of Doxorubicin with Cationic Anticancer Peptide L-K6 Reverses Multidrug Resistance in Cancer Cells in vitro via P-glycoprotein Inhibition

Multidrug resistance (MDR) is one of the major obstacles to efficient chemotherapy against cancers, resulting from the overexpression of drug efflux transporters such as P-glycoprotein (P-gP). In the present study, we aimed to evaluate the MDR reversal activity and synergistic therapeutic potential of cationic anticancer peptide L-K6 with doxorubicin (DOX) on P-gP-overexpressing and DOX-resistant MCF-7/Adr human breast cancer cells. Flow cytometry and confocal laser scanning microscopy were used to determine the intracellular accumulation of DOX and another P-gP substrate, Rho123. P-gP-Glo assay, Western blot and Biacore analysis were further performed to evaluate the P-gP function and expression. The cytotoxicity in MCF-7 or MCF-7/Adr cells was measured by MTT assay. Flow cytometry assay and confocal laser scanning microscopy observation clearly revealed an increased intracellular accumulation of DOX and Rho123 in MCF-7/Adr cells treated with L-K6, suggesting a P-gP inhibiting potential. Biacore analysis, P-gP-Glo assay and Western blot further confirmed that L-K6 could directly interact with P-gP, inhibit P-gP function and decrease P-gP expression in MCF-7/Adr cells. In addition, as expected, the data from MTT assay indicated that L-K6 restored the sensitivity of MCF-7/Adr cells to DOX, indicating a MDR reversal potential and a promising synergistic anticancer activity. All these findings may provide experimental evidence to support the promising applications and synergistic therapeutic potential of peptidic P-gP inhibitors against MDR cancer.

pharmacology and toxicology

A novel bioinformatics approach to reveal the role of circadian oscillations in AD development

Altered circadian gene expression may contribute to Alzheimers disease (AD) progression. Unfortunately, sampling the central nervous system (CNS) at multiple time points is not feasible. Moreover, there are no AD-related time-series transcriptome datasets available for studying these circadian patterns and their impacts on AD development. In this study, we introduce a novel computational platform, Event-driven Sample Ordering for Circadian Variation Detection (ESOCVD), to reveal rhythmic patterns of gene expression of AD using untimed transcriptome datasets. ESOCVD was applied to 20 untimed gene expression profiles of 16 brain regions from approximately 3000 AD patients in public transcriptome databases. Our analysis revealed five types of circadian alteration patterns in ~2,000 circadian genes in different brain regions of AD patients. Further analyses of additional databases confirmed that our analytical platform can be applied to identify the evolutionary dynamics of circadian variation during the process of AD development. Through the gene expression correlation analysis for our 8 circadian genes identified from AMP-AD MSBB cohorts, we identified stage-specifically enriched biological processes with anticipated context. Gene expression analysis of AD mouse brain tissues further substantiated the predictions of the ESOCVD model. In summary, ESOCVD is highly versatile in bridging circadian research and precision medicine.

bioinformatics