Protected biofactors and antioxidants reduce the negative consequences of virus and cold challenge by modulating immunometabolism via changes in the interleukin-6 receptor signaling cascade in the liver

Abstract

Protected biofactors and antioxidants (PBA), and protected biofactors and antioxidants with protected organic acids and essential oils (PBA+POAEO) have been shown to have benefits in stressed or challenged birds. Here, we describe the immunometabolic changes observed in the liver of Ross 308 broilers during feed supplementation and brief physiological stress. These studied additives contain protected essential oils, organic acids, and vitamins which may have protective effects on the liver. Thus, we aimed to determine the signaling changes induced by these supplements and the resultant immunometabolic effects in the liver. All birds received a 2X dose of live bronchitis vaccine at d 0 and a 48-h cold challenge by reducing the temperature from 30 to 32°C, to 20 to 23°C on d 3 to 5. Control birds were fed a standard diet without supplementation. Liver samples were collected to evaluate the effects of these treatments on cytokine gene expression and protein phosphorylation via kinome peptide array. ANOVA was used for statistical analysis of the gene expression data (significance at a p-value of 0.05), and PIIKA2 was used for statistical evaluation and comparative analysis of the kinome peptide array data. At d 15, the kinome peptide array analysis and gene expression data showed stimulation of the interleukin 6 receptor (IL-6R) signal transduction for host protection via heightened immune response while inducing immune modulation and reducing inflammation in both supplement treated groups. Significant changes were observed via IL-6R signaling in the metabolic profiles of both groups compared to control and no significant differences when compared to each other. In the liver, these 2 feed additives induced immunometabolic changes predominantly via the IL-6 receptor family signaling cascade. Differences between the 2 treated groups were predominantly in the metabolic pathways, centered around the mTOR pathway and the proteins AMPK, mTOR and S6K, with a more anabolic phenotype following the addition of essential oils.

INTRODUCTION

An important approach to optimize broiler health and production efficiency to meet the growing global demand for poultry meat focuses on the inclusion of natural feed additives. Additives have taken on greater relevance due to restrictive policies on production practices and some antimicrobial feed additives globally. These natural products impart beneficial effects when used as feed additives to balance broilers’ protective immune responses (Perry et al., 2022).

The use of microbial metabolites, organic acids, vitamins, essential oils and other molecules which have beneficial properties have been investigated for their effects in poultry under various challenge models. The components of the products analyzed in this study, protected biofactors and antioxidants (PBA) and protected biofactors and antioxidants with protected organic acids and essential oils (PBA+POAEO), are considered beneficial feed additives because their components are capable of increasing immune benefits, nutrient digestibility and absorption, and improving growth performance in poultry. Research suggests that the fermentation products and extracts derived from microbes, such as organic acids, biofactors, and vitamins, have the same positive effects and less negative consequences than probiotic supplements (Aguilar-Toalá et al., 2018; Johnson et al., 2019; Mayorgas et al., 2021). Natural products are being explored as potential antibiotic, and probiotic, alternatives and analyzed for their effect on broilers under various challenge or stress conditions.

Citric and fumaric acid are organic acids shown to have positive effects on growth performance, nutrient digestibility, and immune response, by increasing antioxidant responses and reducing pathogen loads during challenges in poultry (Fazayeli-Rad et al., 2014; He et al., 2020; Reda et al., 2021). Vitamins play an important role in various cellular and systemic functions and have been a major focus in gastrointestinal- and immune-related studies for many years. Vitamins of the B complex aid enzymes in a variety of molecular and cellular processes and have been implicated in functional control of immune cells (Yoshii et al., 2019). Vitamin A, C, D, and K each have antioxidant activities and immunoregulatory functions (Vervoort et al., 1997; Ghazi Harsini et al., 2012; Padayatty and Levine, 2016; Rodriguez-Lecompte et al., 2016). Vitamin A and E supplementation mitigates inflammation in mouse models (Olivares-González et al., 2021). The dietary supplementation of antioxidants, such as vitamin E, and others, may increase birds’ growth performance and may protect the cells from reactive oxygen species (ROS; Ghazi Harsini et al., 2012) that are naturally generated due to immune responses, or exacerbated during times of stress.

Plant extracts or essential oils show antimicrobial and antioxidant activities, increase ingestion, absorption, nutrient utilization, immune health and performance metrics (Rossi et al., 2020). Specifically, thymol has inhibitory and sub-inhibitory effects on the growth of Escherichia coli and Bacillus cereus (Zarrini et al., 2010), eugenol is known to have similar effects (Bassolé and Juliani, 2012; Gholami-Ahangaran et al., 2021). Although less is known about vanillin as a feed additive in chickens, it reduces the production of inflammatory cytokines and increases regenerative potentials in non-poultry models (Kim et al., 2019; Costantini et al., 2021). In a poultry model, a mixture of vanillin and thymol improved gut morphology and reduced the count of Clostridium perfringens in the ileum (Stamilla et al., 2020).

The consideration of immune and metabolic activities as synergistic processes is known as immunometabolism. Immunometabolism investigates the cross talk between metabolic and immune systems (Mathis and Shoelson, 2011). An immunometabolic approach involves considering how the metabolic enzymes and intermediates of a cell can alter its immune state and drive inflammatory outcomes (Mathis and Shoelson, 2011). In addition, inflammatory activities can influence metabolic processes and pathways and the production of proteins and intermediates to further influence immune response and whole system processes (Mathis and Shoelson, 2011; Kogut and Arsenault, 2015). The immunometabolic approach is nascent in poultry science, but there is a long tradition of nutritional immunology in the field (Klasing, 1998, 2007; Kogut and Klasing, 2009). Integrating the concept of immunometabolism during the interpretation of the results from advanced methodologies and performance parameters will significantly complement the decision-making process in the industry and the field (Bortoluzzi et al., 2021).

Understanding the impact of feed additives on the liver is extremely important for a comprehensive incorporation of immunometabolism along with standard performance measurements in poultry production. The liver breaks down, stores and metabolizes nutrients to maintain metabolic homeostasis (Whittow, 1999). For example, hepatic cells are capable of synthesizing saturated fatty acids and oxidizing them into unsaturated fatty acids (Zaefarian et al., 2019). In chickens, the liver is the primary site of fat processing and metabolism because they lack fully developed lymphatic systems (Bensadoun and Rothfeld, 1972). The liver receives nutrient rich blood from the digestive tract to be detoxified (Campbell, 2006). Detoxification and metabolism of contents in the blood received via the hepatic portal vein may expose the liver to stressors, infectious agents and/or toxins (Cullen 2016). For example, increased exposure to fats and lipids can lead to the production of ROS (Cullen and Stalker, 2016). The more stress imposed on liver cells, the harder they must work to maintain liver function. This energy expenditure takes away from growth-promoting metabolism (Zaefarian et al., 2019). Thus, the liver is an important immunometabolic organ and the dysfunction of the liver has major consequences on the performance and health of birds (Zaefarian et al., 2019).

In the present study we describe the immunometabolic changes observed in the liver of Ross 308 broilers during feed supplementation with 2 different microencapsulated feed additives and an acute physiological stress. We hypothesized that the additives would reduce the negative growth and inflammatory effects of the stressors.

MATERIALS AND METHODS

Birds, Housing, and Treatments

At the hatchery, 1,080 one-day old male Ross x Ross 308 chickens were vaccinated against Marek's disease (HVT). The trial was conducted at the experimental station of Jefo Nutrition Inc., in Saint-Hyacinthe, QC, Canada. The feeding program was divided into 2 phases: starter (0–14 d) and grower (14–35 d). A corn and soybean meal-based feed formulation was used (Table 1); feed additives were mixed separately in the feed. The experiment consisted of 3 treatment groups: treatment 1; control, treatment 2; PBA, and treatment 3; PBA+POAEO. Treatments 2 and 3 were feed additives that contain mixtures of protected biofactors and antioxidants PBA (Jefo Nutrition Inc., in Saint-Hyacinthe, QC, Canada) given to chickens from d 1 to 14. The experimental diets followed the National Research Council (1994) guidelines for all experimental diets.

Table 1.

Starter (1–21 d) and grower (21–35 d) diets formulation, and formulated energy and nutrient composition.

Ingredient, %	Starter control	Starter treatment	Grower control	Grower treatment
Corn	30.6	30.6	34.0	34.0
Soybean meal, 48% CP	26.0	26.0	18.3	18.3
Wheat	31.0	31.0	34.3	34.3
DDGS	5.0	5.0	5.0	5.0
Animal fat	2.8	2.8	4.4	4.4
Monocalcium phosphate	0.98	0.98	1.01	1.01
Calcium carbonate	2.13	2.13	1.73	1.73
NaCl	0.31	0.31	0.28	0.28
L-Lysine HCl	0.315	0.315	0.310	0.310
DL-Methionine, 99%	0.305	0.305	0.245	0.245
L-Threonine	0.090	0.090	0.045	0.045
Choline, 60%	0.076	0.076	0.076	0.076
L-Valine	0.259	0.259	0.076	0.076
L-Tryptophane	0.029	0.029	0.024	0.024
Vitamin-Mineral Premix1	0.15	0.15	0.15	0.15
Sodium bicarbonate	-	-	0.04	0.04
PBA2 or	-	0.015 or	-	0.015 or
PBA+POAEO3	-	0.015 + 0.01	-	0.015 + 0.01
Formulated energy and nutrient composition
ME Kcal/Kg	2,950	2,950	3,097	3,097
Crude Protein, %	20.5	20.5	17.5	17.5
Fat, %	5.34	5.34	6.98	6.98
Lysine, %	1.200	1.200	1.003	1.003
Thr, %	0.797	0.797	0.639	0.639
Met+Cys, total %	0.938	0.938	0.810	0.810
Non phytate P, %	0.440	0.440	0.440	0.440
Total Ca, %	1.11	1.11	0.95	0.95
Na, %	0.15	0.15	0.15	0.15

¹Supplied per kg of diet: vitamin A, 10,005 IU; vitamin D₃, 3,000 IU; vitamin E, 30 IU; vitamin K, 2.55 mg; vitamin B₁₂, 15 mg; biotin, 201 mg; thiamine, 3 mg; riboflavin, 6 mg; pantothenic acid, 14.1 mg; pyridoxine, 3.6 mg; niacin, 49.95 mg; folic acid, 1 mg; Zn, 100; Fe, 49.5 mg; Cu, 15 mg; I, 0.09 mg; Se, 0.45 mg, Mn, 100 mg.

²Supplied per kg of diet: vitamin A, 900 IU; vitamin D₃, 450 IU; vitamin E, 12 IU; vitamin K, 0.135 mg; vitamin B₁₂, 0.00525 mg; biotin, 0.03 mg; thiamine, 0.9 mg; riboflavin, 1.35 mg; pantothenic acid, 3 mg; pyridoxine, 0.75 mg; niacin, 12 mg; folic acid, 0.3 mg.

³The PBA+POAEO formulation comprised the PBA formulation plus 0.01% organic acids (citric acid, malic acid, sorbic acid, fumaric acid) and essential oils (thymol, eugenol, and vanillin) microencapsulated in a matrix of triglycerides from hydrogenated vegetable oil.

Briefly, the protected biofactors and antioxidants PBA were derived from a complex of vitamins and fermentation extract of vitamin A, vitamin D₃, vitamin E, menadione, thiamine, riboflavin, niacin, pantothenic acid, vitamin B₆, biotin, folic acid, vitamin B₁₂, L-tryptophan, and fermentation extract of dried Bacillus subtilis, Aspergillus niger and Aspergillus oryzae. The PBA+POAEO was a combination of PBA with organic acids (citric acid, malic acid, sorbic acid, fumaric acid) and essential oils (thymol, eugenol, and vanillin). PBA and PBA+POAEO active compounds were microencapsulated in a matrix of triglycerides from hydrogenated vegetable oil (Jefo Nutrition Inc., Saint-Hyacinthe, QC, Canada; Table 1).

Each treatment consisted of 12 replicate pens with 30 birds each. The birds were placed onto floor pens with new litter. Each pen was provided with supplemental heat, and ad libitum access to water and feed in mash form.

Challenge

Briefly, all the birds received a 2X dose of live bronchitis vaccine (MILDVAC-Ma5) (in addition to the Marek's vaccine) on d 0 at the hatchery (for additional detail see Bortoluzzi et al., 2021; Perry et al., 2022). Beginning on d 3, all the birds were subjected to an acute cold stress for 48 h with temperature between 20 and 23°C (or 9–12°C below the thermoneutral temperature for this age) and subsequently returned to the standard temperature range (Bortoluzzi et al., 2021).

Sample Collection

At each of 7 and 15 d, liver was collected from 6 birds per experimental group to evaluate the expression of immune-related genes. Liver samples from 3 of the d 15 birds per experimental group were harvested and immediately flash-frozen in liquid nitrogen to preserve kinase enzymatic activity and stored at -80°C prior to further processing. Samples were shipped overnight on dry ice to the Kinome Center at the University of Delaware, for kinome peptide array analysis.

Gene Expression

Liver samples were evaluated for expression of immune-related genes, per Kogut and Arsenault (2015). Briefly, the mRNA was isolated from 25 mg of tissue using the RNeasy Plus mini kit (Qiagen, Hilden, Germany). The total isolated mRNA was eluted with 50 µl of RNase-free water and stored at -80°C for qRT-PCR analysis. RNA was quantified and the quality was evaluated using a spectrophotometer (NanoDrop Products, Wilmington, DE).

The PCR was performed using the TaqMan fast universal PCR master mix and one-step RT-PCR master mix reagents (Applied Biosystems, Waltham, MA, USA). Normalization was carried out using 28S rRNA as a housekeeping gene. To correct for differences in RNA levels between samples within the experiment, the correction factor for each sample was calculated by dividing the mean threshold cycle (Ct) value for 28S rRNA-specific product for each sample by the overall mean Ct value for the 28S rRNA-specific product from all samples. The corrected cytokine mean was calculated as follows: = 40 - (average of each replicate × cytokine slope)/(28S slope × 28S correction factor). (Kogut and Arsenault, 2015; Bortoluzzi et al., 2021). Liver samples were tested for IL-6 and IL-10. The primer and probe sets used in the qRT-PCR are reported in Bortoluzzi et al. 2021.

Kinome Peptide Array

The kinome peptide array was performed on d 15 liver samples as described by Johnson et al. (2019). Forty mg of samples were lysed using bead-based homogenization in 100 μl of lysis buffer containing protease and phosphatase inhibitors. The lysed tissue samples were incubated on ice and then centrifuged in a refrigerated microcentrifuge at 14,000 g for 10 min at 4°C. An aliquot of supernatant was mixed with 10 μL of activation mix containing ATP as the phosphate group donor. Eighty μL of the supernatant-activation mix solution was applied to the peptide microarray. The custom-designed peptide arrays were obtained from JPT Peptide Technologies (Berlin, Germany), based on our sequence designs. A 25 × 60 mm, glass lifter slip was then applied to the microarray to sandwich and disperse the applied lysate.

Microarrays were then incubated in a humidity chamber at 37 to 40°C and 5% CO². Arrays were then placed in a 50 mL centrifuge tube containing phosphate-buffered saline (PBS)–1% Triton, to remove the lifter slip from the microarray surface. Arrays were then submerged in 2M NaCl-1% Triton and agitated for a minimum of 30 seconds. This process was then repeated with fresh 2M NaCl-1% Triton. Arrays were given a final wash in double distilled water with agitation.

Array slides were submerged in phosphospecific fluorescent ProQ Diamond Phosphoprotein Stain (Life Technologies, Carlsbad, CA) in a large dish and placed on a shaker table at 50 rpm for 1 h. Arrays were then placed in a new dish and submerged in destain solution (20% acetonitrile (EMD Millipore Chemicals, Billerica, MA) and 50 mM sodium acetate (Sigma Aldrich, St. Louis, MO)) for 10 minutes with agitation at 50 rpm. This process was repeated 2 times. A final wash was performed with double distilled water. The arrays were spun dried and scanned using a Tecan PowerScanner microarray scanner (Tecan Systems, San Jose, CA) at 532 to 560 nm with a 580-nm filter to detect dye fluorescence to collect the array image.

Kinome Peptide Array Data Analysis

Images were gridded using GenePix Pro software, and the spot intensity signal collected as the mean of pixel intensity using local feature background intensity calculation with the default scanner saturation level. The resultant data was then analyzed by the PIIKA2 peptide array analysis software (http://saphire.usask.ca/saphire/piika/index.html; Trost et al., 2013). Briefly, the resulting data points were normalized using variance stabilization normalization to eliminate unequal variance between peptide spots and across arrays. Using the normalized data set, comparisons between the treatment groups and control were performed, calculating fold-change and a significance p-value. The p-value was calculated by conducting a one-sided paired t-test between treatment and control values for a given peptide. The resultant fold-change and significance values were then used to generate higher order analysis (heatmaps, hierarchical clustering, principal component analysis, pathway analysis, etc.).

The kinome peptide array analysis was performed in triplicate for each group per tissue. A total of 9 samples, 3 per group were used for kinome peptide array analysis. Three treatment (cold stress and IBV vaccine challenged broilers given feed additives) versus control (cold stress and IBV vaccine challenged broilers without feed additives) combinations (Table 2) were used to generate kinome profiles of these samples.

Table 2.

Treatment versus control combination for the kinome profile analysis.

Treatment1,2	Control2
Liver PBA+POAEO day 15	Liver Control (challenge only) d 15
Liver PBA day 15	Liver Control (challenge only) d 15
Liver PBA+POAEO day 15	Liver PBA day 15

¹Protected biofactors and antioxidants (PBA), protected biofactors and antioxidants with protected organic acids and essential oils (PBA+POAEO).

²From each experimental group samples of N = 3 kinome were collected for analysis.

As described by Perry et al. (2020), post PIIKA2 analysis was performed using the following online databases and tools; STRING database (Szklarczyk et al., 2019), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and KEGG color and search pathways (Kanehisa and Sato, 2020), PhosphoSitePlus (Hornbeck et al., 2015), Uniprot (The UniProt Consortium, 2021), and Venny 2.1 (Oliveros, 2007). False discovery rate (FDR) correction is applied to the STRING database pathway outputs. False discovery rate is a multiple testing correction applied for large datasets (Hochberg and Benjamini, 1995). The FDR is the rate the proteins in the indicated as significant are actually null. An FDR of 5% means that, among all proteins called significant, 5% of these are truly null. Similar to how an alpha threshold is set for p-value cut off, a similar value is set for the q-value of FDR. The q-value is the expected proportion of false positives among all proteins listed.

Statistical Analysis

A one-way ANOVA and Tukey's post-hoc tests were used for statistical analysis of the gene expression data via the JMP software (JMP Pro 16). All P-values lower than or equal to 0.05 were considered statistically significant, and p-values up to 0.1 were considered relevant.

RESULTS

Treatments Effect on Signaling Profile

A previous study showed major immunometabolic differences in the jejunum of PBA+POAEO and PBA treated birds, as well as the performance of these birds (Perry et al., 2022). To further understand the effects of these treatments in the digestive organs of broiler chickens, kinome peptide array and gene expression analysis with a focus on immunometabolism were performed on liver samples of challenged birds supplemented with PBA+POAEO and PBA. The list of all significantly phosphorylated proteins for each treatment versus control pair was entered into the STRING database (Szklarczyk et al., 2019). The lists of KEGG pathways (Kanehisa and Sato, 2020) were extracted from the STRING database. Based on false discovery rate (FDR), the lists of top 20 KEGG pathways for each treatment compared to control are reported in Tables 3 and 4. An FDR of 0.05 or less indicates greater confidence that the pathway is truly represented in the data, an FDR of 0.05 means that, among all features called significant, 5% of these are truly null. Both treatments significantly altered multiple different regulatory pathways. For example, T cell receptor signaling was observed for both PBA+POAEO and PBA compared to control (Tables 3 and 4).

Table 3.

The top 20 list of KEGG pathways in PBA+POAEO treated liver relative to control.

Liver PBA+POAEO1 D 15 Top 20 KEGG pathways2	Observed protein count3	False discovery rate4
MAPK signaling pathway	49	3.42E-33
Pathways in cancer	54	8.03E-28
PI3K-Akt signaling pathway	46	1.79E-27
Insulin signaling pathway	33	5.09E-27
ErbB signaling pathway	26	1.82E-23
Neurotrophin signaling pathway	28	9.34E-23
Focal adhesion	33	1.42E-22
MicroRNAs in cancer	30	1.48E-22
Ras signaling pathway	34	6.12E-22
Central carbon metabolism in cancer	23	6.12E-22
T cell receptor signaling pathway	25	6.27E-21
Proteoglycans in cancer	30	9.44E-20
mTOR signaling pathway	27	1.78E-19
EGFR tyrosine kinase inhibitor resistance	22	2.24E-19
Hepatitis B	26	7.64E-19
Chemokine signaling pathway	27	1.46E-17
Regulation of actin cytoskeleton	28	2.46E-17
AMPK signaling pathway	23	4.02E-17
Insulin resistance	22	5.71E-17
Rap1 signaling pathway	27	1.55E-16

Boldface pathways are discussed in further detail in this paper.

¹Protected biofactors and antioxidants with protected organic acids and essential oils (PBA+POAEO)

²The significantly phosphorylated peptides generated from the T-test performed by PIIKA2 were entered into the STRING database. The list of Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were downloaded and analyzed for common and/or relevant immune or metabolic pathways.

³Observed protein count refers to the number of proteins represented in the peptide array data that are members of the indicated KEGG pathway.

⁴FDR is the false discovery rate generated by the STRING database. It is a measure of pathway representation statistical significance.

Table 4.

The top 20 list of KEGG pathways in PBA treated liver relative to control.

Liver PBA1 D 15 Top 20 KEGG pathways2	Observed protein count3	False discovery rate4
Pathways in cancer	44	1.15E-22
MAPK signaling pathway	34	3.13E-21
Insulin signaling pathway	25	6.55E-20
EGFR tyrosine kinase inhibitor resistance	19	6.08E-17
Central carbon metabolism in cancer	18	6.08E-17
Proteoglycans in cancer	25	1.09E-16
Insulin resistance	20	3.85E-16
PI3K-Akt signaling pathway	30	7.49E-16
Neurotrophin signaling pathway	20	1.20E-15
ErbB signaling pathway	18	1.22E-15
AMPK signaling pathway	20	1.77E-15
Kaposi's sarcoma-associated herpesvirus infection	22	2.17E-14
Osteoclast differentiation	19	3.61E-14
MicroRNAs in cancer	20	5.85E-14
FoxO signaling pathway	19	6.79E-14
Focal adhesion	22	6.79E-14
Ras signaling pathway	23	1.06E-13
T cell receptor signaling pathway	17	1.55E-13
Hepatitis B	19	2.28E-13
Adipocytokine signaling pathway	15	2.55E-13

Boldface pathways are discussed in further detail in this paper.

¹Protected biofactors and antioxidants (PBA).

²The significantly phosphorylated peptides generated from the T-test performed by PIIKA2 were entered into the STRING database. The list of Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were downloaded and analyzed for common and/or relevant immune or metabolic pathways.

³Observed protein count refers to the number of proteins represented in the peptide array data that are members of the indicated KEGG pathway.

⁴FDR is the false discovery rate generated by the STRING database. It is a measure of pathway representation statistical significance.

However, there were some significant differences between the liver samples of each treatment group. The signaling pathways Osteoclast differentiation, FoxO and Adipocytokine signaling pathways were observed in the top 20 list of the liver PBA KEGG pathways but not in PBA+POAEO (Figure 1, Table 3). Despite their names, these pathways include proteins involved in immunometabolism via their effects on MAPK, PI3K and insulin signaling cascades. In the top 20 KEGG pathways in the liver of PBA+POAEO treated birds, we observed mTOR, Chemokine, Regulation of actin cytoskeleton, and Rap1 signaling pathways (Figure 1, Table 4). These pathways were not observed in the top 20 KEGG pathways in the liver of PBA treated birds, however, MAPK and PI3K are also the common signal transduction cascades that link their roles in immunometabolism. Thus, similar but not identical signaling profiles are induced by both treatments in the liver. Generally, we observed higher protein counts in the PBA+POAEO KEGG pathways than the PBA KEGG pathways (Tables 3 and 4).

Figure 1.

Schematic of immunometabolic pathways processes induced by feed additives in the Liver. This schema illustrates the different immunometabolic pathways altered by each feed additive and the signal transduction cascades these pathways have in common that lead to changes in key immunometabolic processes. PBA+POAEO activates MAPK and PI3K signaling hubs through the pathways; chemokine signaling, Rap1 signaling, regulation of actin cytoskeleton and mTOR signaling. PBA activates the signaling hubs MAPK, PI3K and insulin signaling through the pathways; adipocytokine signaling, FoxO signaling and Osteoclast differentiation. The signaling hubs then modulate common phenotypic responses including immune regulation, cell growth and energy metabolism. The pathways in this schema were derived by comparing the list of top 20 KEGG pathways for each feed additive in the liver for differences.

To further elucidate the changes PBA+POAEO induces compared to PBA, the data was run through pathway overrepresentation analysis using PBA+POAEO as the treatment and PBA as the control (Table 2) (i.e. any statistically significant differences between the 2 treatment groups will indicate differences in effect of the treatments on liver). The top 20 KEGG pathways from the comparison are shown in Table 5. The results in Table 5 show a more elaborate immune response via cell growth, adaptive and innate immunity pathways such as PD-L1 expression and PD-1 checkpoint pathway in cancer, T cell receptor signaling pathway, Yersinia infection, growth hormone synthesis, secretion and action, and some energy metabolism pathways like the AMPK signaling pathway.

Table 5.

The top 20 list of KEGG pathways in the liver PBA+POAEO treatment groups relative to PBA.

Liver PBA+POAEO1 treatment groups relative to PBA2KEGG Pathways3	Observed Protein Count4	False Discovery Rate5
MAPK signaling pathway	44	4.78E-31
PD-L1 expression and PD-1 checkpoint pathway in cancer	26	3.70E-24
Hepatitis B	30	2.62E-23
T cell receptor signaling pathway	26	3.79E-23
Pathways in cancer	45	4.91E-23
Ras signaling pathway	33	6.45E-23
Yersinia infection	26	2.44E-21
ErbB signaling pathway	23	2.82E-21
PI3K-Akt signaling pathway	36	1.42E-20
MicroRNAs in cancer	27	3.07E-20
Central carbon metabolism in cancer	21	3.20E-20
Growth hormone synthesis, secretion and action	24	1.14E-19
EGFR tyrosine kinase inhibitor resistance	21	2.20E-19
Proteoglycans in cancer	28	2.20E-19
Insulin signaling pathway	24	1.08E-18
Human cytomegalovirus infection	28	2.33E-18
Autophagy – animal	23	8.82E-18
Shigellosis	27	2.28E-17
AMPK signaling pathway	22	2.47E-17
Human immunodeficiency virus 1 infection	26	4.93E-17

Boldface pathways are discussed in further detail in this paper.

¹Protected biofactors and antioxidants with protected organic acids and essential oils (PBA+POAEO).

²Protected biofactors and antioxidants (PBA).

³The significantly phosphorylated peptides generated from the T-test performed by PIIKA2 were entered into the STRING database. The list of Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were downloaded and analyzed for common and/or relevant immune or metabolic pathways.

⁴Observed protein count refers to the number of proteins represented in the peptide array data that are members of the indicated KEGG pathway.

⁵FDR is the false discovery rate generated by the STRING database. It is a measure of pathway representation statistical significance.

Effects on Immunoregulation and Hepatic Protection

The list of top 20 KEGG pathways for each treatment vs control pair contained several pathways that involve immune response and regulation such as the chemokine and T cell receptor signaling pathways (Tables 3 and 4). Because phosphorylation of proteins can have a variety of effects on protein activity, the proteins involved in these inflammatory and immunoregulatory pathways were further analyzed for a better understanding of how these treatments affected liver immunoregulation. It is not possible for us to know if a greater or lesser magnitude of relative phosphorylation change resulted in a greater physiological effect. Thus, in our analysis we consider only if a phosphorylation event was statistically significant, and the number of those that contribute to a pathway or physiological response. When compared to the control diet, both treatment groups showed some critical changes in the activation status of proteins involved in inflammation, programmed cell death, and hepatic protection and regeneration via the increased phosphorylation on the active sites of MAPK and insulin signaling cascades proteins (Taub, 2003; Cong et al., 2012) (Table 6). Unlike gene expression, phosphorylation can activate or deactivate (or result in another change) the protein function. Just reporting the relative phosphorylation status does not provide information on effect, Table 6 provides this information for several key proteins. For example, Jak and STAT were active in both treatments. We also observed a mixture of adaptive and innate immune signaling in the top 20 KEGG pathways of the liver when PBA+POAEO was compared against PBA (Table 5). Further analysis of the immune pathways shown in Table 5 revealed that the immune changes observed in the liver due to PBA+POAEO treatment relies heavily on proteins that link the innate and adaptive immune systems (Supplemental 1). Some of these proteins include NFAT, Jak2, BCL10, IRS and more (Supplemental 1).

Table 6.

Effect of phosphorylation changes on major immunoregulation and cell death proteins.

Protein name	PBA+POAEO1,2	PBA1,3
B-ARRESTIN	P	P
BLNK	Inactive	Inactive
BTK	Inactive	Active
Caspase 3	Active	No change
Caspase 6	Inactive	No change
C-JUN	Active	Active
JAK	Active	Active
JNKK	Active	Active
MEKK3	Active	Active
NFAT	Inactive	P
NF-Kappa-B p100	Inactive	Inactive
P38	No change	No change
PERK	P	No change
SMAD2/3	Active	Active
STAT	Active	Active
SYK	Active	Active
TAK1	Active	Active
TBK	Active	Inactive

¹The phosphorylation status of proteins in this table was determined by entering each protein's respective Uniprot accession into phosphosite, finding the annotation of the site of interest and accounting for the phosphorylation fold change (increased or decreased) of that site. Active denotes increased phosphorylation of an inducing site or decreased phosphorylation on an inhibitory site. Inactive denotes decreased phosphorylation of an inducing site or increased phosphorylation on an inhibitory site. P denotes that the function of the site is unknown and the data shows increased phosphorylation. No change denotes there were no statistically significant difference observe between treatment and control for that protein.

²Protected biofactors and antioxidants with protected organic acids and essential oils (PBA+POAEO).

³Protected biofactors and antioxidants (PBA).

The phosphorylation status of some cytokines and immune receptors were also analyzed (Tables 7 and 8). These tables show that PBA treatment in the liver resulted in more changes in phosphorylation of cytokines and immune receptors as compared to PBA+POAEO. PBA+POAEO treatment resulted in decreased phosphorylation of cytokines and immune receptors that showed increased phosphorylation in PBA (Tables 7 and 8). The activating and/or inhibiting effects of phosphorylation remain unknown for many of these proteins and their phosphorylation sites, therefore gene expression analysis was conducted on key cytokines to further understand the effects of these treatments on the immune status of chickens.

Table 7.

Phosphorylation changes in major cytokines and immune receptors in liver PBA¹ at day 15.

Uniprot accession	Protein name	Human site	Chicken site	Fold Change2	P -value
P10914	Interferon regulatory factor 1; IRF-1;	Y109	Y109	−1.111	0.003
P29460	Interleukin-12 subunit beta; IL-12B;	Y314	Y304	−1.055	0.044
Q5VWK5	Interleukin-23 receptor; IL-23R;	S121	S118	1.063	0.005
P40189	Interleukin-6 receptor subunit beta; IL-6R-beta;	S782	S757	1.074	0.013
Q15750	TGF-beta-activated kinase 1 and MAP3K7-binding protein 1; TAK1-binding protein 1;	S423	S573	−1.088	0.003
Q8N5C8	TAK1-binding protein 3; TAB-3;	S60	S60	−1.078	0.007
Q7L0×0	TLR4 interactor with leucine rich repeats;	T753	T721	1.089	0.030
P58753	Toll/interleukin-1 receptor domain-containing adapter protein; TIR domain-containing adapter protein;	Y86	Y77	−1.103	0.002
Q9H0E2	Toll-interacting protein;	Y68	Y68	1.075	0.001
Q9Y2C9	Toll-like receptor 6;	S647	S653	1.058	0.022
Q9NYK1	Toll-like receptor 7;	S610	T608	1.148	0.005
Q9UKE5	TRAF2 and NCK-interacting protein kinase;	S764	V730	−1.052	0.046
Q9UKE5	TRAF2 and NCK-interacting protein kinase;	S678	S644	−1.051	0.048
Q08881	Interleukin-2-inducible T-cell kinase; Tyrosine-protein kinase Lyk;	Y512	Y511	1.069	0.021

¹Protected biofactors and antioxidants (PBA). Response compared to vaccine and cold stress control.

²Fold change is calculated by comparing normalized phosphorylation signal generated from PBA vs. vaccine and stress control for each peptide. Positive fold change means increased phosphorylation in the PBA group, negative means decreased phosphorylation relative to positive stressor control.

Table 8.

Phosphorylation changes in major cytokines and immune receptors in liver PBA+POAEO¹ at day 15.

Uniprot accession	Protein name	Human site	Chicken site	Fold Change2	P -value
P10914	Interferon regulatory factor 1; IRF-1;	Y109	Y109	−1.075	0.020
Q5VWK5	Interleukin-23 receptor; IL-23 receptor; IL-23R;	S121	S118	1.063	0.041
P40189	Interleukin-6 receptor subunit beta; IL-6R-beta;	Y915	Y886	−1.087	0.006
Q16649	Interleukin-3-binding protein 1; Transcriptional activator NF-IL3A;	S286	S283	−1.074	0.000
Q15750	TGF-beta-activated kinase 1 and MAP3K7-binding protein 1; TAK1-binding protein 1;	S423	S573	−1.082	0.001
Q8N5C8	TAK1-binding protein 3; TAB-3;	S60	S60	−1.074	0.008
Q7L0×0	TLR4 interactor with leucine rich repeats;	T753	T721	1.100	0.010
Q9Y4K3	TNF receptor-associated factor 6; TRAF6; Interleukin-1 signal transducer;	Y353	Y379	−1.080	0.002
O15455	Toll-like receptor 3;	Y858	Y854	−1.067	0.045
Q9NYK1	Toll-like receptor 7;	S610	T608	1.216	0.001
Q9UKE5	TRAF2 and NCK-interacting protein kinase;	S678	S644	−1.072	0.010
Q9UKE5	TRAF2 and NCK-interacting protein kinase;	S764	V730	−1.060	0.012

¹Protected biofactors and antioxidants with protected organic acids and essential oils (PBA+POAEO). Response compared to vaccine and cold stress control.

²Fold change is calculated by comparing normalized phosphorylation signal generated from PBA vs. vaccine and stress control for each peptide. Positive fold change means increased phosphorylation in the PBA group, negative means decreased phosphorylation relative to positive stressor control.

The kinome peptide array data showed significant changes in the phosphorylation of IL-6 receptor (IL-6R) compared to control. In the liver, there was increased phosphorylation of IL-6 receptor (p = 0.01349) in PBA treated samples while there was a decrease (p = 0.00569) for PBA+POAEO (Tables 7 and 8). These changes were observed on different phosphorylation sites in each treatment. However, only an increasing trend (p = 0.06) in IL-6 gene expression was observed in liver PBA samples compared to control at d 15 (Table 9). In the earlier time point, we did not observe any significant changes in IL-6 gene expression for either PBA+POAEO and PBA samples when compared to control (Table 9). The gene expression results also showed decreased gene expression of the immunomodulatory cytokine, IL-10 (p = 0.05) for PBA+POAEO and PBA liver groups when compared to the control at d 7 (Table 9). No other significant trends were observed for IL-10 expression. Here, we observed that PBA treatment may have the greatest impact on the inflammatory proteins in the liver.

Table 9.

mRNA cytokine gene expression in the liver.

Corrected Cytokine Mean 40 - Ct Values1
Day 7	Control	PBA	PBA+POAEO	SEM	P Value
IL6	10.70ab	12.54a	10.71ab	0.72	0.12
IL10	10.80 a	6.93b	6.47b	1.14	0.01
Day 15	Control	PBA	PBA+POAEO	SEM	P Value
IL6	8.18b	10.01a	9.60ab	0.51	0.06
IL10	7.48	8.65	7.01	0.56	0.23

¹Corrected cytokine 40 - Ct value means of IL-6 and IL-10 expression in liver samples at day 15. Calculated by the ratio between the mean = 40 - Ct*slope of the standard curve of the target cytokine/slope of the standard curve of the 28S gene*differential factor of the 28S gene; SEM: Standard error of mean.

^a,bP < 0.05.

Effects on Cell Growth and Metabolism

PBA+POAEO and PBA induced changes in cell growth and metabolic proteins in the liver samples compared to control. Both PBA+POAEO and PBA treatments showed changes in energy metabolism related proteins like AMPK, mTOR, HIF1-alpha, etc (Table 10). The treatments also induced changes in glucose and lipid metabolism compared to control via pyruvate dehydrogenase kinase (PDHK), lactate dehydrogenase (LDH), glucose-6-phosphate isomerase (G6PI), glycogen synthase kinase (GSK), LIPIN, 5-lipoxygenase (5-LO), UDP-glucose-4-epimerase (GALE) (Table 10). These treatments also showed significant changes in proteins involved in growth, specifically growth factor receptors (Table 11). These receptors and growth-related proteins which have been shown to be crucial in maintaining a healthy liver and aid in regeneration (Gupta and Venugopal, 2018). Moreover, the comparison of PBA+POAEO vs PBA showed that PBA+POAEO induced significantly more activity in growth and metabolic signaling than PBA (Supplemental 2). The top 20 KEGG pathways of PBA+POAEO compared to PBA clearly suggested that PBA+POAEO had induced critical changes in cell cycle regulation and growth via PD-L1 signaling, mTOR, AMPK and growth synthesis signaling pathways (Table 5).

Table 10.

Effects of phosphorylation changes on major growth and metabolic proteins.

Protein	PBA+POAEO1,2	PBA1,3
AMPK	Active	Active
GALE	Inactive	No change
GSK	Inactive	Inactive
G6PI	P	P
HIF	Active	Inactive
IRS	Inactive	Inactive
LDH	No change	Active
LKB1	Inactive	Inactive
LIPIN	Active	Active
MTOR	Active	Active
PDHK	Active	Inactive
PDK1	Active	No change
PKA	No change	Active
PKC	Active	Active
PKC-D	Inactive	Inactive
PP2A	Active	Active
PTEN	Active	No change
S6K1	Active	Active
TSC2	Active	No change
5-LO	Inactive	Active

¹The phosphorylation status of proteins in this table was determined by entering each protein's respective Uniprot accession into phosphosite, finding the annotation of the site of interest and accounting for the phosphorylation fold change (increased or decreased) of that site. Active denotes increased phosphorylation of an inducing site or decreased phosphorylation on an inhibitory site. Inactive denotes decreased phosphorylation of an inducing site or increased phosphorylation on an inhibitory site. P denotes that the function of the site is unknown and the data shows increased phosphorylation. No change denotes there were no statistically significant difference observe between treatment and control for that protein.

²Protected biofactors and antioxidants with protected organic acids and essential oils (PBA+POAEO).

³Protected biofactors and antioxidants (PBA).

Table 11.

Number of peptides altered in major growth receptors via phosphorylation.

Protein	PBA+POAEO1,2	PBA1,3
FGFR2	1	1
FGFR3	2	2
FGFR4	2	1
TGFBR1	1	1
VEGFR	2	2
HGFR	1	2
CI-MPR	1	2
PDGFR	1	1

¹Each protein has multiple peptides in the array, this table shows the number of the peptides significantly differentially phosphorylated for each growth receptor.

²Protected biofactors and antioxidants with protected organic acids and essential oils (PBA+POAEO).

³Protected biofactors and antioxidants (PBA).

DISCUSSION

The aim of this study was to define some of the immunometabolic effects of 2 feed additives in the liver of immunologically- and environmentally-stressed broilers. The liver is the major site of lipid and vitamin metabolism in birds, and is susceptible to ROS formation (Emami, et al., 2020). Feed supplements such as vitamins and essential oils have antioxidant activity and act to protect the liver (Cullen and Stalker, 2016; Luna et al., 2017). Analysis of the immune-related pathways observed from the kinome peptide array data indicated a strong effect of the 2 treatments on cellular response to stress in liver samples of broilers (Table 6), perhaps, as a counter to the physiological challenges. Collectively, the proteins in Table 6 are involved in cellular response to stress via MAPK signaling. Analysis of Tables 4 and 5 showed that PBA treatment had positive impact on proteins involved in immune-related stress response, suggesting that the PBA treatment may have heightened the birds’ immune responses in the liver specifically via MAPK and T-cell receptor pathways. This is also evident in the PBA treated birds IL-6 signaling profile through increased phosphorylation of the receptor (Table 7) and cytokine expression in the liver at d 15 (Table 9). Immunologically, the signaling of IL-6 can lead to RankL expression which initiates the signaling of TRAF2 and downstream inflammatory factors (Table 7) (Camara et al., 2019). The changes in phosphorylation of toll-like receptors (TLRs) and TAK1 in PBA liver samples (Table 7) indicate the initiation of an innate immune response (Liew et al., 2005). Note that PBA did not promote a proinflammatory profile in birds and these results should not be interpreted as such. Rather, PBA had an immunomodulatory effect that engages elements of the innate immune response, perhaps via IL-6 receptor.

Signaling via the IL-6R also allows the induction of the adaptive immune system, this is evident in the phosphorylation status of BTK and NFAT (Table 6) which are involved in T-cell and B- cell mediated responses. T-cell and B-cell activation can also be stimulated by IL-2 and IL-4 signaling, which have been shown to reverse inflammation (Antony et al., 2004; Zhou et al., 2021). The anti-inflammatory characteristic of PBA was reported in a previous study that showed PBA decreased ROS activity by increasing the serum levels of glutathione reductase (Bortoluzzi et al., 2021). Thus, PBA does not promote inflammatory responses, instead, this treatment promotes innate and adaptive signaling as indicated by the decreased IL-10 expression at d 7 and increased IL-6 expression at d 7 and 15. Although the regulatory mechanisms of IL-10 are not fully understood, IL-10 is secreted as a homeostatic measure to limit the effects of proinflammatory factors (Murray, 2005). However, this decrease in IL-10 expression compared to control suggests a decrease in proinflammatory effects and/or injury in the liver as a result of supplementing broiler chickens with these protected biofactors (Geginat et. al., 2016). The birds did not present any clinical sign of damage on liver and present better performance than control (Bortoluzzi et al 2021).

PBA+POAEO induced changes in the linkers of adaptive and innate immune proteins and IL-10 expression, which is indicative of an immune response when compared to the control (Tables 6 and 8). In addition, PBA+POAEO activity in the liver shows reduction of inflammation via increased TBK and SYK activity (Antony et al., 2004; Greenhill, 2018) and detoxification of ROS via PERK activation (Krishnamoorthy et al., 2018) when compared to PBA and control (Table 6 and Supplemental 1). This is supported by T cell receptor signaling, the increased activity of lymphoid and non-lymphoid cell immune regulators and Yersinia infection signaling (Tables 3, 4, and 5). Yersinia infection signaling is a pathway that indicates a host response to bacteria. The presence of this pathway does not suggest Yersinia infection, but the overlap of proteins in the samples that are common to the pathway. Another signaling pathway with overlapping proteins is the Hepatitis B signaling pathway because it is a signaling pathway that contains immune response proteins of the liver (Tables 3, 4, and 5). Again, this does not indicate a hepatitis infection, rather, the relevance of the proteins in the pathway to the organ in this study.

We hypothesize that the balance of anti-inflammatory and pro-inflammatory immune signaling, immune modulation, is due to IL-6 receptor family's role in metabolism (Cron et al., 2016; Giraldez et al., 2021); specifically, IL-6R's signaling cascade. The metabolic changes induced in the liver were similar between PBA and PBA+POAEO treatment when compared to the control. Many of these changes can be seen downstream of IL-6R and the gp130 receptor subunit of the IL-6R is known for its critical role in metabolism (Giraldez et al., 2021). IL-6 is known to induce changes in glucose and lipid metabolism specifically, increased glucose utilization and lipolysis (Giraldez et al., 2021). Unlike lipolysis in adipose tissue, increased hepatic lipolysis reduces hepatic fat accumulation and damaged organelles (Galsgaard, 2020). There was evidence of increased hepatic lipolysis, especially in the PBA treatment group via increased activity of proteins essential to the lipid breakdown process including lipin, AMPK, 5-LO and PKA (Bosch and Pol, 2022; Table 10). Although we observed changes in glucose metabolism, these changes were insufficient to declare an increase or a decrease in glucose utilization in the liver. The proteins involved in glucose metabolism in which these changes in phosphorylation were observed for both treatments included GSK, PDHK, and G6PI: GALE for PBA+POAEO and LDH for PBA.

Both treatments induce changes via the IL-6R gp130 subunit signaling cascade. The increase in proteins responsible for growth and proliferation suggests that these treatments may positively influence growth and regeneration which is important for maintaining a healthy liver (Table 11). A systematic review by Hoffman et al 2020 showed that IL-6 along with other growth factors are essential stimulants of liver regeneration (Hoffmann et al., 2020). This implies signaling of these ligands through their respective receptors thus their downstream proteins. The kinome peptide array data showed changes in many growth receptors, some of which can be stimulated by cytokines (Table 11). Cytokines are also capable of stimulating many growth receptors just as growth ligands or factors can stimulate many cytokine receptors (Rose-John and Heinrich, 1994; Grötzinger, 2002). For example, in the PBA+POAEO treatment, there were no significant changes observed in IL-6 expression when compared to control and PBA; however, we observed changes in IL-6R phosphorylation. The changes in phosphorylation of IL-6R and the increased activities of downstream proteins involved in liver regeneration, protection and acute immune response (Taub, 2003; Cong et al., 2012; which include JAK, STAT, mTOR, MAPKs, etc.; Table 6) support signaling via this receptor cascade for both treatments. We observed similar signaling profiles between the 2 treatments, perhaps both treatments act to stimulate signal transduction that leads to signaling via IL-6 receptor proteins, thus the similar downstream signaling.

In summary, the PBA treatment showed evidence of host protection via heightened immune responses and reduction of inflammation via adaptive immune mediated signaling; thus, PBA has a more significant impact on the immune signaling of the liver than did PBA+POAEO. While the changes induced by PBA+POAEO did not show signs of a more robust immune response than PBA. It was observed that PBA+POAEO induced protection of the host via changes in immune response proteins while modulating inflammatory responses. The similarity in changes induced by both treatments in the liver is due to signaling via IL-6 receptor family cascade which induces immune response, host defense, metabolic regulation, growth, regeneration and homeostasis in the liver (Figure 2). PBA+POAEO induced significantly more activity in growth and metabolic signaling than PBA. PBA+POAEO treatment showed increased activity of AMPK, mTOR, PGC-1 alpha, PTEN, HIF, S6K and more (Table 10 and Supplemental 2), suggesting that it may have stronger effects on anabolic metabolism proteins in the liver compared to the PBA treatment. However, PBA+POAEO treatment did not showed the elaborate immunometabolic effect observed in the jejunum (Perry et al., 2022), suggesting that these 2 treatments distinctly influence the jejunum and the liver; and that the composition of PBA+POAEO may have more metabolic impacts in the gut than the liver.

Figure 2.

Summary of IL-6R signaling cascade in the liver of broiler chickens after supplementation with PBA and PBA+POAEO. Shown here are the changes in phosphorylation and gene expression via kinome peptide array and qPCR cytokine gene expression.

DISCLOSURES

L. Lahaye, is an employee at Jefo Nutrition Inc. The other authors declare no conflict of interest.