Abstract Background The intestinal mucosal immune system, renowned for its precise and sensitive regulation, can provide comprehensive and effective protection for the body, among which the ileum is a critical induction site for regulating mucosal immune homeostasis. Moniezia benedeni parasitizes the small intestine of sheep and can cause serious pathological damage or even death to the host when the infection is severe. In this study, 5 sheep infected with Moniezia benedeni were selected as the infected group, and 5 uninfected sheep were selected as the control group. The ileal transcriptome profile characteristics of Moniezia benedeni infection were analyzed based on RNA-seq sequencing technology, aiming to lay a foundation for further exploring the perception mechanism of sheep intestines to Moniezia benedeni infection and formulating effective prevention and control strategies. Results The results showed that a total of 3,891 differentially expressed genes (DEGs) were detected in the ileum tissues of sheep between the infected and control groups with 2,429 up-regulated genes and 1,462 down-regulated genes. GO and KEGG pathway enrichment analysis of differential genes, as well as Clue GO analysis showed that differential genes were significantly enriched in immune and metabolic-related biological processes and signaling pathways. Particularly, in immune-related signaling pathways, the B cell receptor signaling pathway was significantly down-regulated, while in metabolic regulation related signaling pathways, Bile secretion, Fat digestion and absorption and Vitamin digestion and absorption were notably up-regulated. On this basis, the differential core genes related to immune metabolism were verified by qRT-PCR method. The results showed that OVAR, CD3E, CD8A, CD4 and CD28 were significantly up-regulated (P < 0.05), while CIITA, BLNK, BCL6 and CD79A were significantly down-regulated (P < 0.05), which were consistent with transcriptome sequencing data. Conclusions The results demonstrated that Moniezia benedeni infection significantly affected the immune and metabolic processes in sheep ileum, particularly, it significantly inhibited the activation process of host B cells, and also led to an overactive function of bile acid metabolism. This finding provides a solid foundation for further elucidating the response mechanism of Peyer's patches in sheep ileum to Moniezia tapeworm infection. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-024-10853-7. Keywords: Sheep, Moniezia benedeni infection, Ileum, Immune response, RNA-seq Background The intestinal tract is connected to the external environment directly, and while digesting food and absorbing nutrients [[44]1, [45]2], it is also faced with threats from a large number of potential pathogens, such as bacteria [[46]3], viruses [[47]4], and parasites [[48]5], etc. The intestinal mucosal immune system [[49]6] can rely on multiple layers of defense barriers, such as mechanical, chemical, and immune barriers, to effectively prevent the invasion of potential pathogenic microorganisms and antigenic substances, and regulate the immune homeostasis of the digestive tract mucosa [[50]6]. Parasites are one of the most widespread pathogens affecting livestock production. Among them, helminths, as one of the most common intestinal parasites, are diverse and widespread [[51]7]. The latest estimates suggest that there are more than one million species of nematodes alone, and more than one billion people worldwide have been infected by at least one of them [[52]8]. It is also recognized as an important but often neglected tropical disease, and infections in livestock pose a serious threat to health and cause economic losses. It is estimated that the annual cost of helminth infections in livestock across 18 European Union countries alone is up to 1.8 billion euros, with 81% due to production losses and 19% is for treatment costs [[53]9]. Moniezia tapeworms primarily parasitizes the small intestine of lambs and calves [[54]10, [55]11]. Infections generally occur during the warmer temperatures of summer or autumn, fluctuates with the active period of the intermediate host, the oribatid mites. Infection occurs when ruminants ingest oribatid mites containing cysticercoid larvae, which then develop into adult worms and parasitize the small intestine. It was found that Moniezia tapeworms grow rapidly and have a very high body fat content within the host’s intestine, but they lack some key genes for fatty acid synthesis [[56]12]. Transcriptome analysis revealed that the 13 genes related to lipid transport proteins were highly expressed, leading to the speculation that Expansa Moniezia can directly utilize the lipid transport-related proteins to seize host lipids, thereby obtaining energy promoting their growth [[57]13]. In addition, Moniezia tapeworms cause pathological damage to the host, such as intestinal obstruction, severe catarrhal enteritis, intestinal mucosal villous atrophy, infiltration of eosinophils in the lamina propria, and inflammatory hyperplasia of Peyer's patches [[58]14]. Moreover, the parasite can also regulate the host's immune system by releasing a variety of metabolites, and even causing permanent damage to the host [[59]15]. Our previous study found that Moniezia benedeni tapeworm infection could significantly decrease the densities of IgG^+, SIgA^+, and IgM^+ cells in the sheep small intestine [[60]16], as well as significantly increase the densities of small intestinal CD3^+ T cells [[61]17] and IgE^+ cells [[62]18], and significantly promote the secretion of NMU [[63]19]. On this basis, the present study used RNA-seq and bioinformatics analysis to reveal the effects of Moniezia benedeni parasitism on the gene expression profiles of sheep ileum tissue, in order to lay a foundation for further research on the host digestive tract mucosal immune system perceiving the infection of parasites. Materials and methods Experimental design and sample preparation All sheep were sourced from Wenkui Slaughterhouse in Liangzhou District, Wuwei City, Gansu Province, China. Eggs in the feces of sheep observed through a microscope were quadrangular, and a large number of yellowish-white rice grain-shaped gravid proglottids attached to the feces. Five sheep naturally infected with Moniezia benedeni and five uninfected sheep were selected. The sheep were administered sodium pentobarbital (20 mg/kg) intravenously to alleviate pain, followed by euthanasia via exsanguination through the carotid artery. Every effort was made to minimize the pain of the animals. After dissecting the abdomen, the ileum tissues were quickly collected, rapidly frozen in liquid nitrogen, and stored in a -80 °C refrigerator for RNA extraction experiments. The anatomical feature of the sheep ileum is about 30 cm from the ileocecal orifice. To ensure the representativeness of the collected samples, in this study, the samples collected were about 10 cm away from the ileocecal orifice and about 1 cm in length. In addition, some ileum samples were fixed with 4% paraformaldehyde for histopathological examination. Histopathological observation After fixation in 4% paraformaldehyde for more than 7 days, the tissue samples were embedded in paraffin, sectioned at 4 μm, stained with hematoxylin and eosin (H&E), observed under an optical microscope, and then photographs were collected. RNA extraction and library preparation Total RNA was extracted using TRIzol reagent (Accurate Biology, AG21101, Changsha, China), strictly following the manufacturer's protocol. The purity and content of RNA were assayed using a NanoDrop 2000 spectrophotometer (Thermo Science, USA). The integrity of RNA was assessed using an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). Subsequently, libraries were constructed using the TruSeq Stranded mRNA LT Sample Prep Kit (Illumina, San Diego, CA, USA) according to the manufacturer's instructions. Transcriptome sequencing and analysis were performed by Shanghai OE Biotech. Co., Ltd. (Shanghai, China). RNA sequencing and differentially expressed gene analysis The libraries were sequenced on the Illumina HiSeqTM 2500 platform and 150 bp paired-end reads were generated. The Raw data in FASTQ format (RAW reads) were first processed using Trimomatic, and then the low-quality reads were removed to obtain clean reads. Clean Reads were mapped to the sheep genome (NCBI: ARS-UI_Ramb_v2.0, [64]https://www.ncbi.nlm.nih.gov/datasets/genome/GCA_016772045.1/) using HISAT2. FPKM of each gene was calculated for and read counts for each gene were obtained using HTSeqcount. Differential expression analysis was performed using the DESeq (2012) R package. |Fold-change| > 1.8 and P < 0.05 was used as the thresholds for differential expression. Systematic cluster analysis was conducted on differentially expressed genes (DEGs) to reveal the gene expression patterns of genes among different groups and samples. All the sequencing data were deposited in the National Center for Biotechnology Information Sequence Read Archive (NCBI SRA) under accession no. PRJNA1120578. GO and KEGG pathway enrichment analysis To further explore the biological functions of DEGs, GO and KEGG enrichment analyses were performed. Enrichment analysis of DEGs was conducted using the GOseq R package. All DEGs were mapped to the GO terms in the database ([65]http://www.geneontology.org/), the number of DEGs included in each GO term was counted, and the significance of enrichment of DEGs in each GO term was calculated using the hypergeometric distribution algorithm. The online software KOBAS v.2.0 ([66]http://kobas.cbi.pku.edu.cn/home.do) was used to perform KEGG pathway database ([67]http://www.genome.jp/kegg/) functional annotation enrichment analysis of DEGs. The number of DEGs in each KEGG pathway was calculated, and the significance of enrichment of DEGs in each KEGG pathway was calculated using the hypergeometric distribution algorithm. GO and KEGG enrichment analyses with P < 0.05 were considered significantly enriched. And the GO and KEGG enrichment analyses were visualized through the online platform MicrobiomeAnalyst ([68]http://www.bioinformatics.com.cn/). ClueGO analysis of differentially expressed genes The enriched up- and down-regulated DEGs were subjected to KEGG enrichment analysis and visualization using the Cytoscape (3.8.2) plugin ClueGO (2.5.9) [[69]20]. Real-time PCR analysis of differentially expressed genes RNA sequencing results were verified by qRT-PCR method. All primers for the validated genes were designed using the NCBI database and aligned with Primer-Blast using. The primers were synthesized by Beijing TsingkeBiotech Co.,Ltd. and are listed in Table [70]1. Total cDNA was synthesized using a reverse transcriptase kit (Accurate Biology, AG11705, Changsha, Hunan). qRT-PCR was performed on the Roche Applied Science LightCycler® 96 (Roche, Switzerland). Each 20 μL reaction volume contained 10 μL 2X SYBR Buffer, 1 μL Forward primer, 1 μL Reverse primer, 1 μL cDNA Template, and 7 μL ddH[2]O (Selleck Biotechnology). Reaction conditions: denaturation at 95 ℃ for 15 s, annealing at 60 ℃ for 30 s, extension at 72 ℃ for 30 s, a total of 45 cycles; lysis curve: 95℃ for 10 s, 65 ℃ for 1 min, 97 ℃ for 1 s; Cooling: 37 ℃ for 30 s. The relative expression of mRNA was represented by 2^−∆∆Ct, where ∆∆Ct = [ (Ct[target gene] - Ct[β-actin])[test group] - (Ct[target gene] - Ct[β-actin])[Control group]]. Significant differences in gene expression were analyzed using SPSS 26.0. Table 1. The primer sequences of qRT-PCR Primer name Primer sequence (5' to 3') Annealing temperature (℃) Product length (bp) BCL6 F GAAGGGTCTGGTTAGCCCAC 60.04 108 BCL6 R GACCCAGAGGTCTGGAGGAT 60.03 CD79A F TGCCACCATCTCTCTCCTCC 59.38 148 CD79A R GTTGGTGTTGCTGCCGTTG 60.59 CIITA F GTTCAGCAGGCTGTTGTGTG 59.97 123 CIITA R ATGTCTTTGCTCAGGCCCTC 60.03 BLNK F TCAGATGACTTCGACAGCGAC 60.14 189 BLNK R CCTCTGGCTTGATCGGTTGT 60.14 OVAR F GACCAGAGGATTGCGAGTCA 59.47 119 OVAR R ACACGCCGGTGTAGACATAC 59.83 CD3E F AACCTCTGGCAAGTTCTGGG 59.89 125 CD3E R TCTTTAGGGCACGTCAGCTC 59.75 CD4 F AAGCAGTGGTGCTGGGTAAG 60.25 161 CD4 R TCGATGGCTCAGTTCAGTGT 59.03 CD8A F GTATCTCTCGTCCCAACGGG 59.62 109 CD8A R GCGGAAGTTTCTCAGGGTGA 59.97 CD28 F TGGTGGTGGTAAACGGAGTG 59.89 162 CD28 R CATAGGGCTGGTAGTGCCTT 59.16 GAPDH F GGCGTGAACCACGAGAAGTA 60.04 141 GAPDH R GGCGTGGACAGTGGTCATAA 60.04 β-actin F CCCTGGAGAAGAGCTACGAG 58.97 131 β-actin R GGTAGTTTCGTGAATGCCGC 59.90 [71]Open in a new tab Statistical analysis Statistical analysis was carried out using SPSS 23.0 (SPSS Inc, Chicago, USA). One-way ANOVA was used to analyze the differences among sites within the same group, and the independent t-test was used to analyze the differences between the infected and control groups for the same part, respectively. P < 0.05 was considered a statistically significant difference. Results Histopathological observations Histopathological examination revealed significant proliferation of enterocytes in the ileum of infected sheep, along with a substantial infiltration of inflammatory cells, predominantly eosinophils, within the intestinal epithelium and lamina propria of the ileum. The lymphoid follicles of the ileum in the infected group were larger than those in the control group, and there were a large number of inflammatory cells, primarily eosinophils, in the interfollicular areas of the infected group (Fig. [72]1). Fig. 1. [73]Fig. 1 [74]Open in a new tab Histologic observations on the pathology of the ileum in sheep. A Pathologic tissue sections of sheep ileum epithelium H&E; B Pathologic tissue sections of sheep ileum lymphoid follicle H&E Analysis of transcriptome sequencing data The sequencing data of all samples were processed by SOAPnuke filtering software from Shanghai OE Biotech. Co., Ltd. (Table [75]2). On average, each sample yielded 49.943 M raw reads, with 48.727 M clean reads remaining after quality control, resulting in an average clean reads ratio of 97.56% for the 10 samples. The average value of GC content for the 10 samples was 52.26%, which is consistent with the base composition rules. Q30 (99.9% base accuracy) >= 92.31%. This indicates that the sequencing results of this experiment are of high quality and the valid sequences can be used for subsequent experimental analysis. Table 2. Quality control table for transcriptome sequencing data Sample Raw Reads Raw Bases Clean Reads Clean Bases Valid Bases Map Rate Q30 GC Control 1 50.69M 7.60G 49.52M 6.98G 91.76% 97.78% 92.53% 51.80% Control 2 48.61M 7.29G 47.59M 6.71G 92.03% 97.95% 92.71% 51.38% Control 3 48.61M 7.29G 47.30M 6.69G 91.71% 97.45% 91.80% 52.07% Control 4 48.69M 7.30G 47.45M 6.62G 90.69% 96.86% 92.10% 52.39% Control 5 48.64M 7.30G 47.34M 6.63G 90.93% 96.90% 92.01% 52.12% Infect 1 50.66M 7.60G 49.44M 6.87G 90.47% 97.08% 92.39% 52.46% Infect 2 51.45M 7.72G 50.24M 7.05G 91.38% 96.58% 92.42% 52.53% Infect 3 51.61M 7.74G 50.33M 7.15G 92.35% 95.93% 92.31% 53.76% Infect 4 49.07M 7.36G 47.88M 6.71G 91.16% 97.36% 92.30% 51.94% Infect 5 51.40M 7.71G 50.18M 7.03G 91.21% 97.58% 92.56% 52.13% [76]Open in a new tab Screening and cluster analysis of differentially expressed genes A total of 3891 DEGs were screened in this experiment, including 2429 up-regulated and 1462 down-regulated genes. The volcano plots showed the distribution of DEGs between the infected and control groups (Fig. [77]2A), and heatmaps showed the expression change and clustering relationship of DEGs between every sample (Fig. [78]2B). It can be seen from Fig. [79]2A that the distribution of DEGs between the two groups is significantly different, and Fig. [80]2B shows that there are differences in the expression levels of DEGs between the two groups, with good clustering within each group. Fig. 2. [81]Fig. 2 [82]Open in a new tab Analysis of differentially expressed genes. A Volcano map of differentially expressed genes. B Heat maps of differentially expressed genes. Blue represents down-regulated genes; Red represents up-regulated genes; Gray indicates no change in genes GO enrichment analysis GO enrichment analysis were performed on 2429 up-regulated and 1462 down-regulated DEGs (Fig. [83]3), respectively. The main changes in biological processes (BP) of up-regulated DEGs’ GO analysis include: protein localization to plasma membrane, regulation of immune response, fatty acid beta-oxidation using acyl-CoA oxidase, lipoprotein metabolic process, immune response, brown fat cell differentiation, bicellular tight junction assembly, positive regulation of actin filament polymerization, inflammatory response and regulation of transcription involved in cell fate commitment. Fig. 3. [84]Fig. 3 [85]Open in a new tab Differentially expressed genes GO analysis. A Up-regulated differential gene GO analysis.B Down-regulated differential gene GO analysis. The size of black dots represents the number of differential genes in each GO classification The main changes in the BP of down-regulated DEGs’ GO analysis include: cell division, DNA replication, CENP-A containing nucleosome assembly, mitotic cell cycle, chromosome segregation, DNA repair, cell cycle, mitotic sister chromatid segregation, DNA replication initiation and mitotic spindle organization. Enrichment analysis of KEGG pathway KEGG Pathway enrichment analysis was performed separately on 2429 up-regulated and 1492 down-regulated DEGs (Fig. [86]4), respectively. The up-regulated DEGs were mainly enriched: Bile secretion, PPAR signaling pathway, Peroxisome, ABC transporters, Retinol metabolism, Chemical carcinogenesis-DNA adducts, Steroid hormone biosynthesis, Adherens junction, Fat digestion and absorption, Vitamin digestion and absorption, Mineral absorption, Arachidonic acid metabolism, Regulation of lipolysis in adipocytes, Ether lipid metabolism, Linoleic acid metabolism, Proximal tubule bicarbonate reclamation, Cholesterol metabolism, Tight junction, alpha-Linolenic acid metabolism and Arrhythmogenic right ventricular cardiomyopathy. Fig. 4. [87]Fig. 4 [88]Open in a new tab Differentially expressed genes KEGG Pathway analysis. A Up-regulated differential gene KEGG Pathway analysis. B Down-regulated differential gene KEGG Pathway analysis. Dot size represents the number of differential genes in each KEGG Pathway The down-regulated DEGs were predominantly enriched: Cell cycle, DNA replication, Mismatch repair, Fanconi anemia pathway, Base excision repair, Homologous recombination, Nucleotide excision repair, Cellular senescence, p53 signaling pathway, B cell receptor signaling pathway, Oocyte meiosis, Progesterone-mediated oocyte maturation, Primary immunodeficiency, Viral carcinogenesis, Human T-cell leukemia virus 1 infection, Neutrophil extracellular trap formation, Pyrimidine metabolism, NF-kappa B signaling pathway, Systemic lupus erythematosus and Transcriptional misregulation in cancer. ClueGO analysis results of differentially expressed genes The 3891 DEGs (2429 up-regulated and 1462 down-regulated) were analyzed by ClueGO for KEGG pathway enrichment. The up-regulated DEGs in KEGG pathway were enriched in Bile secretion, Fat digestion and absorption, Arachidonic acid metabolism, Retinol metabolism, Ether lipid metabolism, Cholesterol metabolism, Mineral absorption, Regulation of lipolysis in adipocytes, Steroid hormone biosynthesis, Chemical carcinogenesis, Metabolism of xenobiotics by cytochrome P450, Peroxisome, ABC transporters, PPAR signaling pathway, Adherens junction, Tight junction,Salivary secretion, Insulin secretion, Insulin resistance, Herpes simplex virus 1 infection, Arrhythmogenic right ventricular cardiomyopathy (ARVC) signaling pathway (Fig. [89]5). The down-regulated DEGs in KEGG pathway were enriched in B cell receptor signaling pathway, Primary immunodeficiency, Human T-cell leukemia virus 1 infection, p53 signaling pathway, Homologous recombination, Base excision repair, Mismatch repair, DNA replication, Nucleotide excision repair, Cellular senescence, Progesterone-mediated oocyte maturation, Cell cycle, Oocyte meiosis, Fanconi anemia pathway signaling pathway (Fig. [90]6). Fig. 5. [91]Fig. 5 [92]Open in a new tab Functional annotation of upregulated DEGs by ClueGO. The size of the nodes of the signaling pathways reflects the statistical significance of each item, the larger the node the smaller the P-value, and the shaded portion represents the percentage of DEGs in different signaling pathways, the larger the shadow the more DEGs. Genes are colored the same as the enriched signaling pathways, and genes that function in different signaling pathways are jointly represented by the color of each pathway. Lines represent correlations between pathways and genes Fig. 6. [93]Fig. 6 [94]Open in a new tab Functional annotation of down-regulated DEGs by ClueGO. The size of the nodes of the signaling pathways reflects the statistical significance of each item, the larger the node the smaller the P-value, and the shaded portion represents the percentage of DEGs in different signaling pathways, the larger the shadow the more DEGs. Genes are colored the same as the enriched signaling pathways, and genes that function in different signaling pathways are jointly represented by the color of each pathway. Lines represent correlations between pathways and genes qRT-PCR validation results A set of immune-related differential genes screened from transcriptome sequencing data, which were significantly up-regulated in the infected group included OVAR, CD3E, CD8A, CD4 and CD28, and significantly down-regulated included CIITA, BLNK, BCL6 and CD79A (Fig. [95]7). These genes were subjected to qRT-PCR validation, and the results showed that OVAR, CD3E, CD8A, CD4 and CD28 were significantly up-regulated (P < 0.05), while CIITA, BLNK, BCL6, and CD79A were significantly down-regulated (P < 0.05) (Fig. [96]8). The qRT-PCR validation results were consistent with the transcriptome sequencing data. Fig. 7. [97]Fig. 7 [98]Open in a new tab Screening results of immune-related genes in transcriptome sequencing data. Red: significant up-regulation of differential genes; Blue: significant down-regulation of differential genes Fig. 8. [99]Fig. 8 [100]Open in a new tab Validation results of qRT-PCR for immune-related genes. Black: relative expression of genes in control group; Red: relative expression of genes in infected group. P < 0.05 means significant difference Discussion A total of 3891 DEGs were screened in this study, including 2429 up-regulated and 1462 down-regulated genes. KEGG pathway analysis revealed that the significantly up-regulated differential genes were significantly enriched in the pathways such as bile secretion, fat digestion and absorption, vitamin digestion and absorption, mineral absorption, and cholesterol metabolism pathways. The ileum is an important site for the absorption of bile acids and vitamin B[12]. Bile acids are amphipathic steroids synthesized from cholesterol in the liver and enter the intestine through bile [[101]21]. The intestinal flora can convert primary bile acids into secondary bile acids, thereby increasing the chemical diversity of bile acids in the body [[102]22]. Bile acids act as "intestinal soaps", promoting the intestinal absorption of fat-soluble nutrients. In addition to their role in fat absorption, bile acids also exert hormone-like functions through nuclear and membrane receptors involved in the regulation of fat, glucose and energy metabolism [[103]23]. Bile acids are natural ligands for the transcription factor Farnesoid X receptor (FXR), an important factor in bile acid signaling that regulates the expression of many genes involved in bile acid synthesis, transport, and metabolism [[104]24, [105]25]. Many physiological effects of bile acids are mediated by Fibroblast Growth Factor 19 (FGF19), which is mainly expressed in the terminal ileum [[106]26], and bile acids induce the expression of the FGF19 gene through FXR in ileum, thereby regulating glucose, lipid, and fat-soluble vitamin absorption and energy metabolism [[107]27, [108]28]. In this study, FXR and FGF19 were significantly upregulated, and other genes related to bile secretion, such as ABCB1, ABCC2, ABCC3, ABCG2, ABCG5, ABCG8, ADCY1, ADCY5, ADCY6, ADCY9 and AQP1 were also significantly upregulated. And it has been found that Moniezia expansa has a high fat content, but lacks key genes for fatty acid synthesis, so it cannot synthesize any lipids, but it can metabolize most lipids through the relatively intact fatty acid β-oxidation pathway [[109]12]. Moreover, recent studies have shown that FXR and others can also be expressed in a variety of immune cells, such as Treg cells [[110]29], macrophages [[111]30], dendritic cells [[112]31], and innate lymphoid cells [[113]32], to regulate immune response. It is speculated that Moniezia benedeni infection significantly affects the host’s bile secretion and promotes the absorption of glucose, lipids, fat-soluble vitamins, and energy metabolism to compensate for its own impaired lipid synthesis. The Moniezia expansa genome encodes a variety of lipid-transporting and lipid-binding proteins that are able to utilize lipids in the host’s intestinal lumen to promote its growth [[114]15]. It also has a broad impact on immunity. Significantly downregulated differential genes were found to be significantly enriched in the B cell receptor signaling pathway through KEGG pathway analysis. These differential genes were BLNK, BTK, CD22, CD72, CD79A, CD79B, CR2, DAPP1, INPP5D, LOC101113211 (Ig mu chain C region membrane-bound form, partial), NFATC1, PIK3AP1, PIK3CA, PLCG2, RASGRP3, SYK, VAV1. CD79 A and CD79 B are expressed from the pre-B cell stage and continue to be down-regulated until the plasma cell stage, which are essential for B cell signal transduction and could be used as markers for mature B cells [[115]33]. Both CD79 A and CD79 B contain ITAM and thus play important roles in coupling with cytoplasmic signaling cascades and transmembrane receptor signal transduction processes [[116]34]. BLNK (B cell linker protein) plays a key role in the B cell receptor signaling pathway and B cell development [[117]35]. The SH2 structural domain of BLNK co-localizes BTK, Syk, and PLCG2 on BLNK, resulting in the activation of PLCG2 [[118]36]. Activated PLCG2 can hydrolyze phosphatidylinositol diphosphate 2 (PIP2) on the cell membrane surface to generate the second messengers inositol triphosphate (IP3) and diacylglycerol (DAG) [[119]37]. IP3 is a calcium-regulated signal that regulates intracellular calcium pathways, and DAG can activate protein kinase C (PKC) to promote B cell maturation and differentiation. In the present study, several key genes in the B cell receptor signaling pathway were significantly downregulated, indicating that B cell development was significantly inhibited. In our previous study, we found that Moniezia benedeni infection in sheep significantly suppressed IgA^+, IgG^+, and IgM^+ cells residing in the small intestine, with a significantly greater reduction of IgG^+ and IgM^+ cells residing in the ileum than that in the duodenum and jejunum [[120]16]. Therefore, it is speculated that the downregulation of plasma cell numbers may be directly related to the obstruction of the B cell differentiation process. CD4^+ T cells play an important role in the process of stimulating T cell-dependent antibodies. Follicular helper T cells (TFH cells), a subset of CD4^+ helper T cells, play a key role in the germinal center response, which is the site where B cells undergo affinity maturation of antibodies [[121]38]. Therefore, TFH cells play an important role in the regulation of plasma cell differentiation [[122]39]. Bcl6 is a transcription factor that is required for the development and maintenance of TFH cells as well as for the formation of TFH cell-supported GCs [[123]40]. Bcl6 could inhibit the expression of the transcription factor Id2, thereby positively promoting the expression of CXCR5 [[124]41], and the migration of activated TFH cells to the follicles depends on the chemokine receptor CXCR5 [[125]42]. The gene expression of Bcl6 and CXCR5 were both significantly downregulated in this study. Studies have shown that B cells can mediate a protective response against nematodes by supporting the development of Th2 cells and/or by producing antibodies [[126]43], but the immunoprotective role of B cells against the host varies among different nematodes infections [[127]44]. In the present study, we found that humoral immunity centered on B cells was significantly suppressed, suggesting that the downregulation of IgA^+, IgG^+, and IgM^+ cell numbers in the sheep small intestine [[128]16] is related to the obstruction of TFH cells differentiation and migration. The major histocompatibility complex receptor class I (MHC-I) and MHC-II are the two receptor families involved in the recognition of endogenous antibodies and monitoring of exogenous antigens [[129]45]. MHC-I are expressed by the majority of nucleated cells and predominantly present endogenously derived peptide antigens to CD8^+ T cells [[130]46]. CD8^+ T cells are activated by recognizing pMHC-I complexes via TCRs [[131]47]. Activated CD8^+ T cells kill the target cells by releasing cytotoxic particles such as granzymes and perforins through directs contact [[132]48]. CD8^+ T cells play an important role in helping hosts to generate protective immunity [[133]48]. MHC-II is mainly expressed in specialized antigen presenting cells (pAPCs) such as dendritic cells (DCs) [[134]49], B cells [[135]50], and predominantly present exogenous antigens to CD4^+ T cells [[136]51]. CIITA (MHC2TA, MHC-II trans-activator) is an MHC-II trans-activator that is essential for B lymphocytes to express MHC-II [[137]52]. And during B cells differentiating to plasma cells, mice lacking CIITA show a significant reduction in MHC-II expression [[138]53], and the loss of MHC-II expression is a consequence of the silencing of CIITA [[139]54]. CIITA not only induces the expression of the MHC-II, but also regulates the presentation of antigens to the acquired immune system [[140]55]. CD4^+ T cells are activated by recognizing the pMHC-II complexes through TCR, and the instability of the MHC-II molecules would lead to inadequate CD4^+ T cell responses and increased susceptibility [[141]56]. In the present study, CD4, CD8A, OVAR (MHC class I antigen), GZMA (granzyme A), CGL2 (granzyme H-like) and MET1 (granzyme M) were all significantly upregulated, whereas CIITA was significantly downregulated. Therefore, it is speculated that after infection with Moniezia benedeni, the host promotes the anti-parasite immune response through the upregulation of MHC-I-like molecules and the release of granzyme by CD8^+ T cells. On the other hand, Moniezia benedeni induces the down-regulation of the expression of the host CIITA gene through releasing the molecular and extracellular vesicles development, thereby reducing the expression of MHC-II gene facilitate the stable parasitism of the worm. Conclusion In this study, transcriptome sequencing analysis was performed by RNA-Seq sequencing technology on the ileal tissues of sheep infected with Moniezia benedeni. The total of 3,891 DEGs were identified, of which 2,429 were up-regulated and 1,462 were down-regulated by comparative analyses. GO and KEGG pathway enrichment analyses revealed that Moniezia benedeni infection significantly altered host nutrient metabolism, mainly related to bile secretion, fatty acid metabolism, and vitamin synthesis and uptake. The host humoral and cellular immunity were differentially regulated, with a focus on the inhibition of the B cell receptor signaling pathway. The results of the present study provide a basis for further research on the immune evasion strategy and energy metabolism of the parasite. Supplementary Information [142]Supplementary Material 1.^ (4.1MB, pdf) Acknowledgements