Hepatocyte nuclear factor 4ß protect zebrafish from dexamethasone-induced hepatobiliary syndrome and hepatobiliary syndrome complicated with GCRV-II infection by targeting Hsp70 and inhibiting autophagy

Hepatocyte nuclear factor 4ß (Hnf4ß), a nuclear receptor superfamily member, acts as a key regulator of functional gene expression and various cellular processes. The function of Hnf4ß in metabolic diseases or infectious diseases had not yet defined in teleost. Here, we show that zebrafish Hnf4ß plays a protective role in the host defense against dexamethasone (DEX)-induced hepatobiliary syndrome and hepatobiliary syndrome complicated with GCRV-II infection. Zebrafish Hnf4ß deficiency have hepatomegaly, lipid deposition, impairs larvae survival and regulates the expression levels of many genes involved in oxidative phosphorylation and spliceosome during DEX treatment plus GCRV-II infection. In addition, Hnf4ß gene disruption in zebrafish leads to induction of oxidative stress with the increased susceptibility to dexamethasone-induced hepatobiliary syndrome complicated with GCRV-II infection. Furthermore, we show that zebrafish Hsp70 promote the translocation of Hnf4ß from the nucleus to the cytoplasm and interact with Hnf4ß in the cytoplasm and nucleus at DEX + GCRV situation. Mechanistically, zebrafish Hnf4ß mediates the beneficial effect for larvae survival and lipid metabolism in the case of DEX treatment plus GCRV-II infection is depending on the Hsp70-mediated autophagy. Collectively, our results identify that the mechanisms of zebrafish Hnf4ß through targeting Hsp70 against dexamethasone-induced hepatobiliary syndrome complicated with GCRV-II infection. Overall design: At 4 dpf, the hatched larvae from WT and hnf4ß-/- were either treated with 10 µM DEX or left untreated, or followed by either infection with 500 µL of 3.62 × 10^7 copies/mL GCRV-II. Forty larvae in triplicate per treatment at 48 hpi were collected for Illumina deep sequencing by Biomarker Technologies Ltd. Total RNA, mRNA, and cDNA libraries and were prepared following the same methods as our previous studies. The number of differentially expressed genes (DEGs) between two different samples was calculated according to the fragments per kilobase of exon per million mapped reads method. The DEGs in each group were identified via DESeq2, which was based on a fold change = 1.5 and a false discovery rate < 0.05. Functional enrichment analysis, including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, was performed according to previously published methods. Please note that WT data is available in GSE275683.