Introduction
The gilthead seabream is a widely consumed species in the Mediterranean and due to its extensive aquaculture, the pressure on the improvement of production has increased. One fundamental limiting factor of aquaculture production is the incidence of bacterial and viral infections. Deeper understanding of the underlying mechanisms of the immune response will help to prevent and treat these health problems. To this point, there have not been many studies on genome-wide profiling of the gene expression changes in response to specific pathogens on fish. As part of the AquaFAANG project (www.aqua-faang.eu), this work focuses on the development of genome-wide functional annotation maps (‘ImmunoMaps’) that represent host defense responses of the immune system in the presence of two distinct classes of disease agents, viruses and bacteria, in gilthead seabream (Sparus aurata) by using ATAC and RNA sequencing.
Materials and Methods
The experimental work involved first the standardization of experimental protocols for host immunity activation in the head kidney, the major lymphoid organ that plays a critical role in the generation of pro-inflammatory and anti-microbial responses. Two different pathogen associated molecular patterns (PAMP) were applied in order to study species robust innate responses, in vivo by injecting fish and in vitro in primary head kidney leukocyte cultures. A total of 12 gilthead seabream individuals were stimulated in vivo and 6 individuals in vitro with mimics of bacterial (neutralized Vibrio) and polyinosinic:polycytidylic acid (poly I:C) viral infections versus 12 control individuals. Sequencing was performed using Illumina technologies and library preparations were performed for transposase-accessible chromatin (ATAC-seq) and transcriptome (RNA-seq).
For both ATAC- and RNA-sequencing data, the bioinformatic analyses were performed using pipelines from the nf-core initiative (Krzywinski et al., 2009) was created to represent the genomic distribution of differentially expressed genes (Figure 1). To provide additional insight on the way chromatin accessibility interacts with gene expression, both ATAC-seq and RNA-seq data were integrated: the differentially accessible peaks as well as the differentially expressed genes were mapped onto the genome and the 10 closest genes within 1 Mb from the peaks were selected and Log2FoldChange information was added to explore regulatory links between over- or under-accessible peaks with up- or down- regulated genes.
Results
These analyses revealed more generic immune-related and pathogen-specific responses. Firstly, RNA-sequencing showed 1,205 up-regulated genes for all Vibrio treatments (in vitro and in vivo together) and 1,235 up-regulated genes for all PIC treatments. Similarly, 2,427 genes were down-regulated in all Vibrio treatments and 720 genes for PIC treatments. The bioinformatic data analysis also revealed virus-specific (nfkbiaa, nod2, atf3, sting1, traf3, rsad2, tlr7, tnfrsf1a, irf7, traf6, tlr3) and bacteria-specific (pglyrp5, pglyrp6) up-regulated genes in vitro and in vivo. On top of the expression profiles, the association of differentially accessible peaks with differentially expressed genes allowed the assembly of a core immune related gene network, also unveiling a potential regulatory link between the up-regulated genes next to under-accessible peaks in vivo for all treatments (Vibrio-PIC, merged together) where an over-representation for interferon-gamma response terms was present.
Discussion
We present an overall image of the immune response map of gilthead seabream on bacterial and viral stimuli on epigenetic and gene levels. Our study revealed candidate genes for the study of immune response and specifically, an over-expression of virus-related genes (nfkbiaa, nod2, atf3, sting1, traf3, rsad2, tlr7, tnfrsf1a, irf7, traf6, tlr3) and bacteria-related (pglyrp5, pglyrp6) immune response genes that lays the background for further analysis. Furthermore, integration of ATAC-seq and RNA-seq data showed silencer activity on IFN response.
Acknowledgements: The study was funded from the European Union’s Horizon 2020 research and innovation programme under grant agreement 817923 AQUA-FAANG. Computational analyses were performed at the HPC bioinformatics platform of HCMR.
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