Stress-Induced Immunosuppression Affects Immune Response to Newcastle Disease Virus Vaccine via Circulating miRNAs

Simple Summary Circulating miRNAs play important roles in immune response and stress-induced immunosuppression, but the function and mechanism of stress-induced immunosuppression affecting the NDV vaccine immune response remain unknown. In our study, key timepoints, functions, mechanisms, and potential biomarkers of circulating miRNAs involved in immune response and immunosuppression were discovered, providing a theoretical basis for studying the roles of circulating miRNAs in immune regulation. Abstract Studies have shown that circulating microRNAs (miRNAs) are important players in the immune response and stress-induced immunosuppression. However, the function and mechanism of stress-induced immunosuppression affecting the immune response to the Newcastle disease virus (NDV) vaccine remain largely unknown. This study analyzed the changes of 15 NDV-related circulating miRNAs at different immune stages by qRT-PCR, aiming to explore the key timepoints, potential biomarkers, and mechanisms for the functional regulation of candidate circulating miRNAs under immunosuppressed conditions. The results showed that stress-induced immunosuppression induced differential expressions of the candidate circulating miRNAs, especially at 2 days post immunization (dpi), 14 dpi, and 28 dpi. In addition, stress-induced immunosuppression significantly affected the immune response to NDV vaccine, which was manifested by significant changes in candidate circulating miRNAs at 2 dpi, 5 dpi, and 21 dpi. The featured expressions of candidate circulating miRNAs indicated their potential application as biomarkers in immunity and immunosuppression. Bioinformatics analysis revealed that the candidate circulating miRNAs possibly regulated immune function through key targeted genes, such as Mg2+/Mn2+-dependent 1A (PPM1A) and Nemo-like kinase (NLK), in the MAPK signaling pathway. This study provides a theoretical reference for studying the function and mechanism of circulating miRNAs in immune regulation.


Introduction
Stress has a negative impact on poultry as a result of its associated health problems, and the poultry industry is often plagued with stress-induced immunosuppression. Common stress factors are transportation, crowding, unsuited temperature, beak and toe breakage, and ammonia [1,2]. Studies have shown that microRNAs (miRNAs) are involved in the regulation of immunosuppression in the chicken thymus [3] and bursa of Fabricius [4], Large White pig lung [5], and rat heart [6]. Chickens are known to be frequently affected by stressors and immunosuppressive agents that impair organisms' immunity in poultry industry [7]. However, the effect and mechanism of stress-induced immunosuppression affecting the immune response to vaccines have not been reported yet.

Experimental Grouping and Tissues Collection
A total of 160 1 day old nonimmunized Hy-Line Brown chickens were obtained from the Xiangfang hatchery in Harbin city, and equally divided into four groups: control group, Dex group, ND group, and Dex + ND group. A commercial diet and water were offered ad libitum, and different treatment groups were reared in isolation. From 7 to 11 days of age, chickens of the Dex group and Dex + ND group drank Dex every day (1.5 mg/kg). At 12 days old, chickens from the ND group and Dex + ND group were vaccinated with the NDV LaSota vaccine strain (Harbin Veterinary Research Institute, Harbin, China) via eye drop, and the control group and Dex group received the salt solution used to dilute the freeze-dried vaccine (Harbin Veterinary Research Institute, Harbin, China). At 1,2,3,4,5,7,14,21,28, and 35 days post immunization (dpi), the thymus, bursa of Fabricius, spleen, and blood samples were collected from three randomly selected chickens of each group. The blood was placed at a 45 • tilt and 4 • C overnight in sterile round-bottom centrifuge tubes, and then centrifuged at 4 • C, 3000 rpm for 15 min to obtain serum. Other samples were frozen in liquid nitrogen and stored at −80 • C for subsequent analysis.

Antibody Level Determination and Organ Coefficient Analysis
Hemagglutination (HA) and hemagglutination inhibition (HI) assays were used to determine antibody levels of chicken serum with standard antigen of NDV LaSota strain (Harbin Veterinary Research Institute, Harbin, China) according to the method of Lukas Kaufmann et al. [18], and antibody titers were expressed as a reciprocal log 2 value. The body weight, thymus, bursa of Fabricius, and spleen of three chickens were weighed, and organ coefficients were calculated according to the following formula: tissue weight (g)/body weight (g) × 100%.

Reverse Transcription and Quantitative Real-Time PCR (qRT-PCR)
Total RNA was extracted from different tissues using TRIzol (Invitrogen, Carlsbad, CA, USA) following the manufacturer's instructions. Agarose gel electrophoresis (AGE) was used to estimate the integrity of total RNA, and a DU800 spectrophotometer (Beckman Coulter, Miami, FL, USA) was used to quantify the total RNA. Briefly, 300 ng of RNA of each sample was reverse-transcribed using the reverse transcription kit FSQ-301 (TOYOBO, Shanghai, China) following the manufacturer's instructions. qRT-PCR amplification efficiency was assessed by varying the cDNA template concentration to obtain a relative quantitative standard curve, and specificity was assessed by melting curve. qRT-PCR was performed in three technical iterations with a 10 µL reaction mixture, which contained 5 µL of 2× SYBR Green I (TOYOBO, Shanghai, China), 0.2 µL of 50× ROX reference dye (TOYOBO, Shanghai, China), 0.3 µL of each primer, 1 µL of cDNA, and 3.2 µL of RNA-free water. U6 was chosen as an endogenous control for miRNAs. The qRT-PCR procedure was as follows: 95 • C for 1 min, followed by 40 cycles at 95 • C for 15 s, 60 • C for 30 s, 72 • C for 30 s, and s final extension for 30 s at 72 • C. All primer sequences are provided in Table 1.

Bioinformatics Analysis
Only potential targeted genes that were predicted by TargetScan website v8.0 (www. targetscan.org, accessed on 14 July 2022) for each miRNA were further considered. These predicted target genes were subjected to enrichment analysis. TopGO was used for Gene Ontology (GO) annotation, and clusterProfiler R package v3.4.4 was used for Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Graphs were generated using the ggplot package in R.

Statistical Analysis
The 2 −∆∆Ct method was used to calculate the relative expression changes of the candidate miRNAs. The statistical significance was analyzed using an independent-sample t-test and one-way ANOVA in SPSS software v20.0 (IBM Inc., Armonk, NY, USA) after using Shapiro-wilk (SW) test to check the normality of distribution for each group of data samples. Charts were plotted using GraphPad Prism software (San Diego, CA, USA). In all analyses, p < 0.05 was taken to indicate statistical significance.

Analysis of Organ Coefficient and Serum Antibody
The results of the organ coefficients showed that the body weight, thymus, spleen, and bursa of Fabricius in the Dex + ND group were significantly lower than those in the ND group (p < 0.05) (Figure 1a-d). HI results showed that antibody titers in the ND group and Dex + ND group started to increase from 7 dpi onward, peaked on 21 dpi, and then decreased. Throughout the whole process, the antibody titers in the ND group were always higher than those in the Dex + ND group, while no NDV antibody was detected in the Dex group and control group ( Figure 1e).

Bioinformatics Analysis
Only potential targeted genes that were predicted by TargetScan website v8.0 (www.targetscan.org, accessed on 14 July 2022) for each miRNA were further considered. These predicted target genes were subjected to enrichment analysis. TopGO was used for Gene Ontology (GO) annotation, and clusterProfiler R package v3.4.4 was used for Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Graphs were generated using the ggplot package in R.

Statistical Analysis
The 2 −∆∆Ct method was used to calculate the relative expression changes of the candidate miRNAs. The statistical significance was analyzed using an independent-sample ttest and one-way ANOVA in SPSS software v20.0 (IBM Inc., Armonk, NY, USA) after using Shapiro-wilk (SW) test to check the normality of distribution for each group of data samples. Charts were plotted using GraphPad Prism software (San Diego, CA, USA). In all analyses, p < 0.05 was taken to indicate statistical significance.

Analysis of Organ Coefficient and Serum Antibody
The results of the organ coefficients showed that the body weight, thymus, spleen, and bursa of Fabricius in the Dex + ND group were significantly lower than those in the ND group (p < 0.05) (Figure 1a-d). HI results showed that antibody titers in the ND group and Dex + ND group started to increase from 7 dpi onward, peaked on 21 dpi, and then decreased. Throughout the whole process, the antibody titers in the ND group were always higher than those in the Dex + ND group, while no NDV antibody was detected in the Dex group and control group (Figure 1e).  Figure 1. The identification results of immunosuppressed chicken model. (a-d) Comparison results of body weight and organ coefficient between ND group and Dex + ND group, respectively. * Significant difference between the two groups (p < 0.05); ** very significant difference between the two groups (p < 0.01). (e) Serum Newcastle disease virus (NDV) antibody titers in different treatment groups.

The Differential Regulation of Circulating miRNAs in the Process of Stress-Induced Immunosuppression Affecting Immune Response to NDV Vaccine
It must be noted that the expressions of miR-19b-3p, miR-126-5p, and miR-199-5p at 2 dpi, 7 dpi, and 14 dpi, miR-29b-3p at 5 dpi, 7 dpi, 14 dpi, and 21 dpi, and miR-124a-3p at all timepoints were not detected in the ND group; therefore, it was not possible to calculate normalized results for them at these timepoints. Through comparing the normalized expression results between the ND group and Dex + ND group, we found that the candidate circulating miRNAs showed a high degree of consistency at some timepoints ( Figure 3).
Animals 2022, 12, x 7 of 12 Figure 3. Comparison of the relative expression levels of serum circulating miRNAs between ND group and Dex + ND group. * Significant difference between the two groups (p < 0.05); ** very significant difference between the two groups (p < 0.01).

Functional Analysis and Pathway Prediction of Candidate Circulating miRNAs
A total of 2233 genes targeted by the 12 candidate miRNAs (miR-34a-5p, miR-20a-5p, miR-22-3p, miR-375, miR-122-5p, miR-30b-5p, miR-19b-3p, miR-126-5p, miR-199-5p, miR-451, miR-29b-3p, and miR-124a-3p) were predicted using Targetscan software, and GO and KEGG analyses were performed on the basis of these genes (p < 0.05). GO analysis showed that the top 20 significantly enriched GO terms were mainly involved in the biological process (BP) of regulation of transcription by RNA polymerase II (Figure 4a). KEGG analysis found that these genes were enriched in multiple immune-related signaling pathways, including the MAPK signaling pathway, FoxO signaling pathway, Wnt signaling pathway, TGF-beta signaling pathway, Notch signaling pathway, mTOR signaling Comparison of the relative expression levels of serum circulating miRNAs between ND group and Dex + ND group. * Significant difference between the two groups (p < 0.05); ** very significant difference between the two groups (p < 0.01).

Discussion
Intensive modern production models have resulted in animals being exposed to various forms of stresses, and stress can cause the body to produce glucocorticoids, which in turn lead to immunosuppression [21][22][23]. It has been demonstrated that Dex can be used as an immunosuppressant to explore the negative effects of high concentrations of glucocorticoids; therefore, using Dex to simulate stress-induced immunosuppression in poultry is reliable [24]. In this study, the change trends of body weight, organ coefficients, and antibody titers proved that the NDV immunity model and Dex-induced immunosuppressed model were successfully established. Interestingly, miR-198, miR-31-5p, and miR-200b-3p were not detected in the serum of either group; however, the expression changes of the three miRNAs after NDV infection was previously demonstrated [9,17]. The reason for their absence deserves further investigation. Hence, only the remaining 12 NDV-related miRNAs were used for follow-up studies.
To explore the dynamic changes of candidate circulating miRNAs after Dex treatment, we compared the expression levels of miRNAs between the Dex group and control group, and the results showed that 2 dpi, 14 dpi, and 28 dpi were the key timepoints with circulating miRNAs upregulated significantly, indicating that Dex had a stimulating effect on the expression levels of candidate miRNAs in serum. Furthermore, the effect of Dexinduced immunosuppression affecting the NDV immune response can be drawn from the expression changes of serum circulating miRNAs. In detail, almost all candidate miRNAs had similar expression trends in the Dex + ND group; 2 dpi, 4 dpi, and 5 dpi showed significant upregulation, while 14 dpi and 21 dpi showed significant downregulation. Among them, 2 dpi, 5 dpi, and 21 dpi were the most critical timepoints for Dex-induced immunosuppression affecting the NDV immune response because of their large change range. In addition, in a normal NDV immune response, 21 dpi in the acquired immune phase represented the relative expression peak of candidate circulating miRNAs. However, after Dex treatment, the expression levels of circulating miRNAs in the Dex + ND group were suppressed at this timepoint, and 2 dpi and 5 dpi became new expression

Discussion
Intensive modern production models have resulted in animals being exposed to various forms of stresses, and stress can cause the body to produce glucocorticoids, which in turn lead to immunosuppression [21][22][23]. It has been demonstrated that Dex can be used as an immunosuppressant to explore the negative effects of high concentrations of glucocorticoids; therefore, using Dex to simulate stress-induced immunosuppression in poultry is reliable [24]. In this study, the change trends of body weight, organ coefficients, and antibody titers proved that the NDV immunity model and Dex-induced immunosuppressed model were successfully established. Interestingly, miR-198, miR-31-5p, and miR-200b-3p were not detected in the serum of either group; however, the expression changes of the three miRNAs after NDV infection was previously demonstrated [9,17]. The reason for their absence deserves further investigation. Hence, only the remaining 12 NDV-related miRNAs were used for follow-up studies.
To explore the dynamic changes of candidate circulating miRNAs after Dex treatment, we compared the expression levels of miRNAs between the Dex group and control group, and the results showed that 2 dpi, 14 dpi, and 28 dpi were the key timepoints with circulating miRNAs upregulated significantly, indicating that Dex had a stimulating effect on the expression levels of candidate miRNAs in serum. Furthermore, the effect of Dex-induced immunosuppression affecting the NDV immune response can be drawn from the expression changes of serum circulating miRNAs. In detail, almost all candidate miRNAs had similar expression trends in the Dex + ND group; 2 dpi, 4 dpi, and 5 dpi showed significant upregulation, while 14 dpi and 21 dpi showed significant downregulation. Among them, 2 dpi, 5 dpi, and 21 dpi were the most critical timepoints for Dex-induced immunosuppression affecting the NDV immune response because of their large change range. In addition, in a normal NDV immune response, 21 dpi in the acquired immune phase represented the relative expression peak of candidate circulating miRNAs. However, after Dex treatment, the expression levels of circulating miRNAs in the Dex + ND group were suppressed at this timepoint, and 2 dpi and 5 dpi became new expression peaks, providing new temporal clues for the detection of NDV vaccine efficacy in the immunosuppressed state.
In the phase of acquired immunity, Dex led to a significant downregulation of candidate circulating miRNA expression. Studies have shown that a variety of miRNAs play roles in the regulation of immune cells, including proliferation, activation, and differentiation. For example, miR-20a-5p alters T-cell proliferation by targeting mitogen-activated protein kinase 1 (MAPK1) [34], and miR-375 induces DC maturation through the JAK2-STAT3 signaling pathway, indirectly increasing CD4 + T cells and CD8 + T cells [35]; miR-34a-5p and miR-22-3p downregulate the expressions of programmed cell death 1 ligand 1 (PD-L1) and phosphatase and tensin homolog (PTEN) in T cells and B cells, thereby improving the reactivities of T cells [36] and B cells [37], respectively. Furthermore, miR-22-3p as a signature of the maturation of T follicular helper (Tfh) cells, is upregulated during the differentiation of Tfh cells [38], while miR-126-5p enhances the Notch1 signaling pathwaymediated differentiation of CD4 + T cells by targeting delta-like noncanonical Notch ligand 1 (DLK1) [39]. Thus, we speculated that stress-induced immunosuppression affected NDV acquired immune response by downregulating the expression levels of these circulating miRNAs, thus suppressing the immune response. Interestingly, miR-20a-5p, miR-22-3p, miR-375, and miR-34a-5p emerged as the best candidates for biomarkers, because they had highly similar significant changes and a strong association with immunity.
Bioinformatics analysis showed that multiple candidate miRNAs were predicted to target PPM1A and NLK genes. PPM1A, a member of intracellular serine/threonine protein phosphatases, is an important regulator of host immunity in response to pathogens [40,41]. PPM1A was identified as the first known phosphatase of mitochondrial antiviral signaling protein (MAVS), which can silence cytosolic RNA sensing and antiviral defense through direct dephosphorylation of MAVS and TANK-binding kinase 1 (TBK1) [42], while also inhibiting the NF-κB pathway [43], leading to virus escape from host immune surveillance of viral replication. NLK, an evolutionarily conserved serine/threonine mitogen-activated protein kinase (MAPK), is established as an important regulator in diverse cellular processes [44]. Studies have shown that NLK suppresses antiviral immune responses by phosphorylating MAVS, leading to its degradation [45,46], in addition to negatively regulating the NF-κB pathway [47]. In short, PPM1A and NLK are essential regulators in stress response pathways. Therefore, we speculated that our candidate miRNAs can potentially target PPM1A and NLK to regulate immune function through the NF-κB and MAPK signaling pathways, representing an important mechanism of stress-induced immunosuppression negatively regulating the NDV adaptive immune response.

Conclusions
In conclusion, Dex-induced immunosuppression can significantly affect the expression levels of candidate circulating miRNAs in the NDV vaccine immune response, which were upregulated at 2 dpi and 5 dpi but downregulated at 21 dpi. Our data suggest that the possible mechanism of stress-induced immunosuppression affecting the immune response