Abstract

The intestine is the largest mucosal tissue in fish and an important antibacterial site. The pathogenic Streptococcus agalactiae (Gram-positive) is a major bacterial threat to fish intestine health. However, antibacterial molecular mechanisms in the fish intestine, particularly gene expression at genomic scale, in response to S. agalactiae challenge remains largely unknown. With the purpose of investigating this issue, this study performed RNA-seq for control and pathogenic S. agalactiae-challenged intestines of zebrafish. A total of 952 differentially expressed genes (DEGs) were identified. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis showed that DEGs were primarily related to immunity, metabolism, and enzyme activity. These include complement and coagulation cascades, cytokine-cytokine receptor interaction, and metabolic pathways. In particular, the Staphylococcus aureus (Gram-positive bacteria) infection pathway was detected in the KEGG pathway enrichment analysis. The RNA-seq results were validated by assessing the expression levels of 12 key genes of this pathway and 10 randomly selected DEGs using quantitative real-time PCR. Expression patterns of 12 key genes in the Staphylococcus aureus infection pathway were further surveyed across 0, 6, 12, 24, and 48 h after S. agalactiae challenge. It is worth noting that 53 immune related genes, belonging to 9 categories, were systematically identified in response to S. agalactiae challenge, such as antigen processing and presentation (e.g., mr1l, tnfa, and cd4), chemokine and receptors (e.g., ccr2, ccr6, and cxcl18b), and complement and coagulation cascades (e.g., cd59, c3, and c6). This study provides valuable genomic information for better comprehension of genes and signaling pathways involved in the intestinal antibacterial response in zebrafish, pointing out genes potentially involved in the intestinal antibacterial response, and affording relevant information to be applied in further fish disease control.

Full Text
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