
==== Front
Poult Sci
Poult Sci
Poultry Science
0032-5791
1525-3171
Elsevier

S0032-5791(24)00823-X
10.1016/j.psj.2024.104244
104244
IMMUNOLOGY, HEALTH AND DISEASE
Metabolomic analysis reveals altered amino acid metabolism and mechanisms underlying Eimeria infection in laying hens
Lee Namhee *
Sharma Milan Kumar †
Paneru Deependra †
Ward Elizabeth Delane *
Kim Woo Kyun †
Suh Joon Hyuk J.Suh@uga.edu
*1
⁎ Department of Food Science and Technology, College of Agricultural and Environmental Sciences, University of Georgia, Athens, GA 30602, USA
† Department of Poultry Science, College of Agricultural and Environmental Sciences, University of Georgia, Athens, GA 30602, USA
1 Corresponding author: J.Suh@uga.edu
22 8 2024
11 2024
22 8 2024
103 11 1042443 6 2024
18 8 2024
© 2024 The Authors
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Avian coccidiosis, caused by Eimeria spp, is a devastating disease in laying hens. Previous studies have suggested that amino acids may be involved in Eimeria infection of broiler chickens. However, their metabolic features in laying hens, as well as the effect of multiple Eimeria species challenges on poultry hosts have not been elucidated yet. Here, a targeted metabolomics approach was employed to identify altered amino acid metabolism and mechanisms in laying hens with multiple Eimeria species challenges. Laying hens, Hy-Line W-36 aged 25 wk, were randomly assigned to a control group and groups inoculated with varying levels of mixed Eimeria species (E. maxima, E. tenella, and E. acervulina). Serum samples from each group were collected at 6 d and 14 d of postinoculation (6 and 14 DPI) for metabolite profiling. Metabolomic analysis revealed notable metabolic variations between control and infected groups, especially at 6 DPI stage. Varying levels of Eimeria dosages did not show a significant metabolic difference, and metabolites were sensitive to low-level infection. With statistical analysis, differentially expressed compounds (3-methylhistidine, alanine, aspartate, lysine, asparagine, methionine, ornithine, and tryptophan) were selected, and their metabolic network was identified by pathway enrichment analysis. In the network, the lysine biosynthesis pathway was upregulated, while the arginine and proline metabolic pathway was downregulated under infection. Other pathways showed complex patterns of metabolic relationships. Based on the results, biological implications of metabolic changes were elucidated and discussed. Last, the results were further confirmed with our previous study (phenotype and gene expression results) using the same set of samples. Our finding provides in-depth information on altered amino acid metabolism and mechanisms in laying hens upon multiple Eimeria species infection.

Key words

coccidiosis
metabolomics
laying hen
amino acid
metabolism
==== Body
pmcINTRODUCTION

Avian coccidiosis is one of the enteric diseases caused by the parasite Eimeria spp. that has a strong impact on poultry industry (Santos et al., 2020). Coccidiosis targets and proliferates within the intestinal epithelial cells, resulting in the significant damages to the intestinal lining, compromising the integrity of the digestive tract of poultry (Sharma et al., 2024b). This protozoal disease can arise from several species of Eimeria (Conway and McKenzie, 2007). Eimeria maxima, Eimeria tenella, and Eimeria acervulina are the most common species in poultry (Mesa et al., 2021). Each Eimeria spp. tends to attack different areas of the gastrointestinal tract: Eimeria. tenella attacks the cecum, while Eimeria maxima and Eimeria acervulina invade the mid and upper regions of the intestinal tract, respectively (Duffy et al., 2005). The symptoms of Eimeria infection include affecting gastrointestinal permeability, malabsorption of nutrients, increased feed conversion ratios, decreased feed intake, weight loss, reduced growth performance, inflammatory responses and in severe cases, high mortality (Ruff, 1999; Conway and McKenzie, 2007; Su et al., 2014; Castro et al., 2020; Teng et al., 2020). Eimeria infection leads to not only poor health in poultry, but also a significant cost for treatment and control, resulting in a huge economic loss exceeding USD 10 billion annually across the global poultry industry (13.5% of the total cost for disease control, 4.6% of the total cost of mortality and 81.9% of the total cost of morbidity in the United States) (Blake et al., 2020).

With growing attention on poultry welfare and human health, consumers have become more interested in the production of cage-free eggs. In the United States, major retailers and restaurants have announced a transition to offer only cage-free eggs by 2025 (Lusk, 2019). However, this transition from the cage to the cage-free system can increase the risk of Eimeria infection in laying hens, because the laying hens in the cage-free system are more likely to be exposed to manure buildup and infective oocysts, with a higher chance of fecal-oral transmission of coccidiosis, than those raised in the conventional cage system (Lunden et al., 2000; Chapman, 2017). The risk of Eimeria infection in laying hens (for egg production) is as high as that in broilers (for meat production), and may be even higher during rearing and egg production (Chapman, 2017; Sharma et al., 2022), because anticoccidial drugs given to pullets (young hens) in their early life must be withdrawn before the point of egg production. Due to this, laying hens are more susceptible to Eimeria infection during the period of egg production (Lunden et al., 2000; Soares et al., 2004; Chapman, 2017). If coccidiosis is prevalent in laying hens at their peak production stage, it may lead to more adverse symptoms, potentially even a temporary cease in the egg production (Hegde and Reid, 1969; Fitz-Coy and Edgar, 1992; Sharma et al., 2024b).

Metabolomics, an analysis of metabolomes, has emerged as a powerful tool to elucidate biochemical processes and principles in organisms. For disease research, metabolomics identifies metabolic changes in hosts in response to the disease, which are linked to fundamental mechanisms behind the disease symptoms and pathogenesis (Fiehn, 2002). There have been metabolomics-based studies on the Eimeria infection of broilers. These works included changes in plasma levels of metabolites in Eimeria-infected broiler chickens (Allen and Fetterer, 2000; Fetterer and Allen, 2000; Fetterer and Allen, 2001; Rochell et al., 2016), diagnosis of Eimeria infection using metabolites in broiler feces (Wang et al., 2021), metabolic variances among different genotypes of Eimeria-infected broilers (Aggrey et al., 2019), and the effect of anticoccidial drug treatments on metabolic profiles of Eimeria-infected broilers (Li et al., 2022). With these studies, amino acids such as 3-methyl histidine and lysine have been discovered as discriminant metabolites responsible for Eimeria infection in broilers. Amino acids are important nutrients and the building block of proteins. Amino acid metabolism is involved in animal growth, development, as well as host immunity (innate defense) (Li et al., 2007; Wu, 2010). Thus, understanding the dynamics of amino acid metabolism can be crucial for the pathophysiological knowledge of Eimeria infection in poultry, which involves nutrient malabsorption and inflammatory responses in the host. Recently, our group started investigating the effect of Eimeria infection on laying hens and identified changes in genetic regulations and biochemical parameters in Eimeria-infected laying hens at different stages (Sharma et al., 2022, 2023, 2024a, 2024b). However, to date, there is no metabolomics study on Eimeria infection in laying hens. Furthermore, amino acid metabolic pathways and network rewiring in the host upon Eimeria infection have not been fully elucidated. Apart from this, current literature only used single Eimeria species to infect broiler chickens. In the real world, multiple Eimeria species likely attack chickens together, needing further research on the effect of different Eimeria species at mixture levels.

The previous metabolomics studies on Eimeria-infected broilers demonstrated that amino acids might be the key metabolites affected by Eimeria infection. In the present work, targeted metabolomics approach was used to identify differentially expressed amino acids, their internal relationship, and rewired metabolic network in multiple Eimeria species-infected laying hens. We also aimed to confirm the metabolomics results at different biological levels by comparison with phenotype and gene expression results from our previous study using same sample sets (Sharma et al., 2024b).

MATERIALS AND METHODS

Amino Acid Standards and Materials

LC-MS grade water and acetonitrile were purchased from Fisher Scientific (Fair Lawn, NJ). For amino acid-related standards, 3-methylhistidine (3MH), alanine (Ala), arginine (Arg), arginosuccinate (Asa), asparagine (Asn), aspartate (Asp), carnosine (Car), glutamate (Glu), glutamine (Gln), glycine (Gly), histidine (His), isoleucine (Ile), leucine (Leu), lysine (Lys), methionine (Met), ornithine (Orn), phenylalanine (Phe), proline (Pro), serine (Ser), succinate (Suc), threonine (Thr), tryptophan (Trp), tyrosine (Tyr), and valine (Val) were purchased from Sigma-Aldrich (St. Louis, MO), and citrulline (Cit) and homoserine (Hsr) were purchased from Fisher Scientific (Fair Lawn, NJ). Methylphosphonic acid was acquired from Sigma-Aldrich (St. Louis, MO). For internal standards, proline-d3 (Pro-d3) and phenylalanine-13C6 (Phe-13C6) were purchased from Cayman Chemical (Ann Arbor, MI).

Birds Husbandry and Eimeria Challenge

The experiment was conducted at the Poultry Research Center of the University of Georgia (Athens, GA) and was approved by the Institutional Animal Care and Use Committee of the University of Georgia (A2021 12-012). Day-old unvaccinated Hy-Line W-36 pullets were obtained from Hy-Line International (Hy-Line International, Mansfield, GA) and reared in cages until 18 wk of age without anticoccidial drugs. At 18 wk of age, the pullets were transferred to cages and reared until 25 wk of age (775 cm²/bird). At 25 wk of age, 360 laying hens were assigned to 1 of 5 treatment groups in a completely randomized design, including a nonchallenged control (Control), low (Low), medium-low (Med-Low), medium-high (Med-High), and high (High)-dose treatment groups (biological replicate, n = 6). The dosages of mixed Eimeria oocysts used in different treatment groups were based on previous studies by Sharma et al. (2022), and Sharma et al. (2024a) are presented in Table 1. The laying hens were housed in an environmentally controlled caged facility, with each cage accommodating 2 laying hens (775 cm²/bird). Throughout the experimental period, the hens were given ad libitum access to mash feed and water (Hy-Line International, Mansfield, GA). They were also maintained under a lighting schedule of 16 h of light and 8 h of darkness. Following the Eimeria challenge at 6 DPI, lesion scoring was conducted and Eimeria infection was confirmed (Sharma et al., 2024b). At 6 and 14 DPI, 1 hen was randomly selected per replicate, and approximately 5 mL of peripheral whole blood was collected from the wing vein. Collected blood was for 1 h at room temperature for clotting, and serum was collected by centrifuging at 1,000 × g for 15 min. The serum samples were kept at −80°C until further analysis.Table 1 Information on the number of Eimeria oocysts treated in control and infected groups.

Table 1Treatments1	Eimeria maxima	Eimeria tenella	Eimeria acervulina	
Control	0	0	0	
Low	6,250	6,250	31,250	
Med-Low	12,500	12,500	62,500	
Med-High	25,000	25,000	125,000	
High	50,000	50,000	250,000	
1 Unit: number of sporulated oocysts per mL.

Control: nonchallenged group; High: the high-dose challenged group; Low: low-dose challenged group; Med-High: the medium high-dose challenged group; Med-Low: the medium low challenged group.

Preparation of Standard Solutions

Stock solutions of amino acid standards (3MH, Ala, Arg, Asa, Asn, Asp, Car, Cit, Glu, Gln, Gly, His, Hsr, Ile, Leu, Lys, Met, Orn, Phe, Pro, Ser, Suc, Thr, Trp, Tyr, and Val) and internal standards (Pro-d3 and Phe-13C6) were prepared at a concentration of 1,000 µg/mL in water-acetonitrile mixture (1:1, v/v). Standard solutions were prepared by diluting the stock solutions with acetonitrile to obtain proper concentrations for the optimization of LC–MS conditions, as well as the identification of amino acids in serum samples (details are described in ‘Targeted Metabolomics’ section). The stock solutions were stored at −80°C, and the standard solutions were prepared on the day of metabolomic analysis.

Sample Preparation

Twenty-microliters of serum were mixed with 380 µL of extraction solvent (acetonitrile:isopropanol:water = 3:3:2, v/v/v) containing internal standards (Pro-d3, Phe-13C6: 5 µg/mL each). The samples were vortexed for 10 min followed by sonication for 10 min. After centrifugation at 21,000 g for 5 min, the supernatant was filtered through a 0.2 µm PVDF membrane filter and was injected for liquid chromatography‒mass spectrometry (LC‒MS) analysis. Six biological replicates and 3 technical replicates (n = 18) were analyzed for each group (a total of 10 groups: 6 DPI-Control; 6 DPI-Low; 6 DPI-Med-Low; 6 DPI-Med-High; 6 DPI-High; 14 DPI-Control; 14 DPI-Low; 14 DPI-Med-Low; 14 DPI-Med-High; and 14 DPI-High). Pooled quality control (QC) samples were prepared by mixing equal volumes of all samples.

Targeted Metabolomics

The LC–MS system consisted of an Agilent 1260 Infinity II ultra-high performance liquid chromatography coupled with a 6470 triple quadrupole mass spectrometer (Agilent Technologies, Santa Clara, CA, USA). For metabolomic analysis, all target amino acids were fully identified using corresponding standard solutions. The analytes were separated on an Agilent InfinityLab Poroshell 120 HILIC-Z column (2.1 × 100 mm, particle size 2.7 µm, Agilent Technologies, Santa Clara, CA, USA) using mobile phases of 10 mM ammonium acetate (pH 9.0) with 0.25 mM methylphosphonic acid in water (A) and 10 mM ammonium acetate (pH 9.0) in water/acetonitrile (10:90, v/v) (B). Gradient elution was performed as follows: 0-10 min, 90-40% B; 10-17 min, 40% B; 17-20 min, 40-90% B. The column was re-equilibrated for 7 min using an initial mobile phase composition before the next run. The column temperature was 30°C and a flow rate was set at 0.25 mL/min. An injection volume was 2 µL. The mass spectrometer was operated with an electrospray ionization (ESI) source in both positive (+) and negative (-) modes. The ESI parameters were as follows: gas temperature, 300°C; gas flow, 11 L/min; nebulizer, 45 psi; sheath gas, 380°C; sheath gas, 11 L/min; capillary positive, 3,500 V; capillary negative, 3,500 V; nozzle voltage, 500 V; and chamber current, 0.20 µA. Dynamic multiple reaction monitoring (D-MRM) was employed, and MS/MS parameters were optimized using flow injection analysis of individual standard solution. The optimum values including polarity, MRM transitions, fragmentors and collision energies are presented in Supplementary Table 1.

Data Processing and Statistics

Metabolomics data was processed by employing MassHunter Qualitative Analysis 10.0 software (Agilent Technologies, Santa Clara, CA, USA). Metabolic responses were calculated and normalized by the peak area ratios of analytes to internal standards. Metabolites with relative standard deviation (RSD %) higher than 30% (RSD > 30%) in the QC samples were excluded for further data interpretation and statistical analyses. One-way analysis of variance (ANOVA) followed by Tukey's honestly significant difference (Tukey's HSD) was performed for each DPI using XLSTAT software (Addinsoft, Paris, France) version 2016. The principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were conducted using SIMCA-P+ (Version 17.0; Umetrics, Umeå, Sweden) to assess metabolic differences between groups. The variable importance in projection (VIP) scores was acquired from PLS-DA results. The PLS-DA model was validated by a 999x permutation test and ANOVA of the cross-validated residuals (CV-ANOVA) test (Eriksson et al., 2008). Differentially expressed compounds for Eimeria infection were identified using 3 criteria including univariate statistical parameters (p-value < 0.05), multivariate statistical parameters (VIP score > 1.0), and absolute fold changes (|FC| > 1.5). The hierarchical clustering heat maps were generated based on Pearson's distance measure and Ward's clustering algorithm with log-transformed and mean-centered data using MetaboAnalyst version 6.0 (http://metaboanalyst.ca). For pathway enrichment analysis and metabolite mapping, Kyoto Encyclopedia of Genes and Genomes (KEGG, http://genome.jp/kegg) was employed as a metabolite and pathway database (Kanehisa and Goto, 2000), and MBRole Ver 3.0 (https://csbg.cnb.csic.es/mbrole3/) was utilized to identify metabolic pathways of target compounds potentially involved in Eimeria infection in laying hens (López-Ibáñez et al., 2016). Heatmaps derived from canonical correlation analysis (CCA) between metabolomic results (this study) and phenotype and gene expression results (our previous study) were acquired with Pearson's correlation coefficient (- 1 < value < + 1) using R 4.3.3 software (http://www.r-project.org) equipped with the packages of CCA and mixOmics (Rajasundaram and Selbig, 2016).

RESULTS

Metabolic Variations in Control and Eimeria-Infected Laying Hens

Amino acid profiles were examined in serum samples from control and Eimeria-infected laying hens at 2 different DPIs (6 and 14 DPI) with varying Eimeria challenge doses (Low, Med-Low, Med-High, and High). The analytical results of each treatment group at 6 and 14 DPI stages are presented in Table 2, and graphically shown in Supplementary Figure 1. An unsupervised method, PCA based on metabolic variations could separate the control and 6 DPI-infected group, while it did not completely separate the control from 14 DPI-infected group (Figure 1). This indicated metabolic alterations mainly occurred at 6 DPI, but not at 14 DPI. Another observation is that PCA was not able to distinguish varying doses of the Eimeria challenge at the same DPI, because metabolite levels were not significantly changed (p-value > 0.05) by Eimeria dosages (Table 2, Supplementary Figure 1). A supervised method, PLS-DA, was further employed, while samples of different Eimeria dosages were not clearly distinguished (Supplementary Figure 2). The PLS-DA plot was validated by 999× permutation test (y-intercepts of R2 and Q2 were 0.0074 and -0.197, respectively). Thus, for differentially expressed compound selection, the average values of infected groups (Low, Med-Low, Med-High, and High) at each stage were used and compared with those of the control group.Table 2 The level of amino acids in different treatment groups.

Table 2	Control	Low	Med-Low	Med-High	High	P-value		Control	Low	Med-Low	Med-High	High	P-value	
6DPI							14DPI							
3MH	0.29c	0.45b	0.65a	0.51b	0.70a	<0.0001		0.22a	0.18ab	0.90ab	0.17b	0.18ab	0.065	
Ala	0.75c	1.04b	1.28a	1.20a	1.29a	<0.0001		0.86a	0.62b	0.66b	0.64b	0.63b	<0.0001	
Arg	1.97bc	1.87c	2.00bc	2.26ab	2.48a	0.0003		2.84a	2.23b	2.09b	2.16b	2.16b	<0.0001	
Asa	N.D.	N.D.	N.D.	0.00a	N.D.	N.A.		N.D.	N.D.	N.D.	N.D.	N.D.	N.A.	
Asn	0.13a	0.02bc	0.02bc	0.01c	0.04b	<0.0001		0.11a	0.07bc	0.08b	0.05c	0.06bc	<0.0001	
Asp	0.03b	0.13a	0.13a	0.15a	0.12a	<0.0001		0.20a	0.22a	0.22a	0.29a	0.27a	0.031	
Car	0.02c	0.03c	0.03b	0.03ab	0.04a	<0.0001		0.03a	0.02ab	0.02b	0.03a	0.02b	0.003	
Cit	0.02b	0.02b	0.02b	0.03a	0.02a	<0.0001		0.02a	0.01a	0.01a	0.02a	0.01a	0.020	
Glu	0.39a	0.39a	0.36a	0.38a	0.41a	0.713		0.37a	0.39a	0.42a	0.44a	0.41a	0.375	
Gln	1.62a	0.84c	0.88c	1.01bc	1.17b	<0.0001		0.92a	1.05a	1.00a	0.88a	0.93a	0.083	
Gly	0.00a	N.D.	N.D.	N.D.	N.D.	N.A.		N.D.	N.D.	N.D.	N.D.	N.D.	N.A.	
His	0.58a	0.50a	0.42a	0.47a	0.65a	0.034		0.73a	0.54b	0.52b	0.55b	0.49b	<0.0001	
Hsr	0.29c	0.25c	0.43b	0.44b	0.71a	<0.0001		0.35a	0.22b	0.24b	0.34a	0.26b	<0.0001	
Ile	9.93b	7.96b	9.32b	9.55b	11.82a	<0.0001		8.67c	11.57b	12.47ab	14.43a	11.69b	<0.0001	
Leu	9.63b	10.63b	10.80b	12.81a	13.07a	<0.0001		12.38a	7.44c	7.14c	9.11b	7.35c	<0.0001	
Lys	0.94c	1.32b	2.31a	2.50a	2.95a	<0.0001		1.09a	0.70b	0.61b	0.61b	0.58b	<0.0001	
Met	2.38a	1.36b	1.32b	1.39b	1.56b	<0.0001		1.74ab	1.52b	1.63ab	1.86a	1.62ab	0.007	
Orn	0.21a	0.08c	0.10c	0.10c	0.14b	<0.0001		0.35a	0.18b	0.26b	0.33a	0.20b	<0.0001	
Phe	13.17b	12.48b	13.99b	14.19b	16.70a	<0.0001		13.40a	11.04b	11.59b	11.71b	10.94b	<0.0001	
Pro	7.46a	4.24c	5.89b	5.38b	7.33a	<0.0001		8.50ab	7.05b	8.40ab	9.50a	7.27b	0.003	
Ser	0.65b	0.75b	1.05a	0.96a	1.02a	<0.0001		0.45a	0.42ab	0.37bc	0.34c	0.38bc	0.002	
Suc	0.00b	0.00ab	0.00ab	0.00ab	0.00a	0.029		N.D.	N.D.	N.D.	N.D.	N.D.	N.A.	
Thr	0.01ab	0.00b	0.00ab	0.00ab	0.01a	0.040		0.00ab	0.00ab	0.01a	0.00b	0.01a	0.002	
Trp	5.80a	2.77c	2.55c	2.82c	3.44b	<0.0001		5.41a	5.73a	6.20a	6.44a	5.82a	0.083	
Tyr	0.98a	0.93a	0.64b	0.63b	0.57b	<0.0001		0.91a	0.79b	0.80b	0.92a	0.87ab	0.006	
Val	0.41b	0.35b	0.47b	0.44b	0.63a	<0.0001		0.47ab	0.36c	0.41bc	0.51a	0.39bc	0.001	
All values are means of 6 samples in each treatment group (3 replications). Different letters (a-c) indicate statistically significant differences at each DPI (P-value < 0.05); Control: nonchallenged group; Low: low-dose challenged group (6,250 E. maxima; 6,250 E. tenella; and 31,250 E. acervulina sporulated oocysts per mL); Med-Low: the medium low challenged group (12,500 E. maxima; 12,500 E. tenella; and 62,500 E. acervulina sporulated oocysts per mL); Med-High: the medium high-dose challenged group (25,000 E. maxima; 25,000 E. tenella; and 125,000 E. acervulina sporulated oocysts per mL); High: the high-dose challenged group (50,000 E. maxima, 50,000 E. tenella, and 250,000 E. acervulina sporulated oocysts per mL); DPI: days postinoculation; N.D.: not detected; N.A.: not available

Figure 1 Principal component analysis score plot of control (green), 6 d of postinoculation (DPI)-infected (blue) and 14 DPI-infected (red) groups.

Figure 1

Student's t-test results revealed amino acids that were statistically differentially expressed (p < 0.05) in control and infected groups (Table 3). The VIP scores for each analyte were acquired from the PLS-DA results. Metabolites with absolute fold changes (|FC|) were shown in Supplementary Figure 3. Among the target compounds, only those with p-value < 0.05, VIP score > 1.0 and |FC| > 1.5 were considered as differentially expressed compounds related to Eimeria infection. The differentially expressed compounds are presented in Table 4. Eight (3MH, Ala, Asn, Asp, Lys, Met, Orn and Trp) and 3 compounds (Asn, Leu and Lys) were chosen as differentially expressed compounds at 6 and 14 DPI, respectively (Table 4). On 6 DPI, plasma concentrations of 3MH, Ala, Asp, Lys were increased in Eimeria-challenged laying hens, whereas others (Asn, Met, Orn and Trp) were decreased. The differentially expressed compounds selected at 14 DPI were all reduced in the infected groups. PCA and hierarchical clustering heatmap were further utilized to see if control and infected groups were discriminated at each stage (6 and 14 DPI), based on metabolic differences (Supplementary Figure 4). The PCA again separated control from infected groups at 6 DPI, explained by 59.7% on PC1 axis and 21.5% on PC2 axis (Supplementary Figure 4A). The heatmap also classified samples into control and infected groups at 6 DPI, confirming there were significant metabolic differences between the control and infected groups at this stage (Supplementary Figure 4B). However, metabolic differences at 14 DPI were not completely distinguished into control and infected groups in PCA and also in the heatmap (Supplementary Figures 4C and D).Table 3 The level of amino acids in control and infected groups.

Table 3	Control	Infected	P-value		Control	Infected	P-value	
6DPI				14DPI				
3MH	0.29b	0.58a	<0.0001		0.22a	0.18b	0.008	
Ala	0.75b	1.20a	<0.0001		0.86a	0.64b	<0.0001	
Arg	1.97b	2.48a	0.000		2.84a	2.18b	<0.0001	
Asa	N.D.	0.00	0.216		N.D.	N.D.	N.A.	
Asn	0.13a	0.22b	<0.0001		0.11a	0.07b	<0.0001	
Asp	0.03b	0.13a	<0.0001		0.20a	0.25a	0.094	
Car	0.02b	0.03a	0.001		0.03a	0.03b	0.018	
Cit	0.02b	0.02a	<0.0001		0.02a	0.01a	0.063	
Glu	0.39a	0.49b	0.005		0.37a	0.41a	0.143	
Gln	1.62a	1.26b	0.000		0.92a	0.96a	0.438	
Gly	0.00a	0.00a	0.370		N.D.	N.D.	N.A.	
His	0.58a	0.55a	0.458		0.73a	0.52b	<0.0001	
Hsr	0.29b	0.46a	0.004		0.35a	0.26b	0.001	
Ile	9.93b	9.66a	0.242		8.67b	12.54a	<0.0001	
Leu	9.63b	11.83a	0.001		12.38a	7.74b	<0.0001	
Lys	0.94b	2.28a	<0.0001		1.09a	0.62b	<0.0001	
Met	2.38a	1.41b	<0.0001		1.74a	1.65a	0.243	
Orn	0.21a	0.10b	<0.0001		0.35a	0.24b	0.001	
Phe	13.17a	14.34a	0.075		13.40a	11.31b	<0.0001	
Pro	7.46a	5.71b	0.000		8.50a	8.03a	0.408	
Ser	0.65b	0.94a	<0.0001		0.45a	0.38b	0.002	
Suc	0.00b	0.00a	0.045		N.D.	N.D.	N.A.	
Thr	0.01a	0.00a	0.407		0.00a	0.00a	0.182	
Trp	5.80a	2.89b	<0.0001		5.41b	6.04a	0.043	
Tyr	0.98a	0.69b	<0.0001		0.91a	0.84a	0.057	
Val	0.41a	0.47a	0.139		0.47a	0.42a	0.105	
All values are means of 6 samples in each treatment group (3 replications). Different letters (a-b) indicate statistically significant differences within each DPIs; Control: nonchallenged group; Infected: the average values of infected groups (Low, Med-Low, Med-High, and High) DPI: days post inoculation; N.D.: not detected; N.A.: not available

Table 4 Differentially expressed compounds selected from comparison between control and infected groups (criteria: VIP score > 1.0, P-value < 0.05 and |FC| > 1.5).

Table 4	VIP score	P-value	|FC|*	
6DPI				
 3MH	1.04	1.71E-07	2.01	
 Ala	1.55	2.82E-14	1.62	
 Asn	1.54	1.55E-20	−5.78	
 Asp	1.06	9.66E-08	4.06	
 Lys	1.40	8.57E-06	2.42	
 Met	1.66	7.77E-20	−1.69	
 Orn	1.05	1.10E-10	−1.99	
 Trp	1.79	8.29E-31	−2.00	
14DPI				
 Asn	1.51	4.27E-08	−1.63	
 Leu	2.19	1.63E-15	−1.60	
 Lys	1.23	7.67E-11	−1.75	
⁎ Infected/Control

VIP: variable importance in projection; FC: fold change; DPI: days postinoculation

Metabolic Network Related to Eimeria Infection in Laying Hens

To identify the metabolic network related to Eimeria infection in laying hens, pathway enrichment analysis was conducted using target metabolites. A total of 8 pathways exhibited high matched/total metabolites with low adjusted p-values (< 0.05) and false discovery rate (FDR) values (< 0.05) (Table 5). They included alanine, aspartate and glutamate metabolism (AAGM), arginine and proline metabolism (APM), glycine, serine and threonine metabolism (GSTM), cysteine and methionine metabolism (CMM), valine, leucine and isoleucine biosynthesis (VLIB), histidine metabolism (HM), phenylalanine, tyrosine and tryptophan biosynthesis (PTTB) and lysine biosynthesis (LB). These pathways were inter-connected each other, and could be integrated into a single metabolic network rewiring in Eimeria infection. Figure 2 displays the network of the 8 pathways, their connections, and related metabolites. Metabolite mapping was conducted on the pathways based on the metabolic responses of control and infected groups on 6 DPI. Metabolic pathways involving differentially expressed compounds were considered to be significant pathways altered by Eimeria infection in laying hens. The mapping result clearly showed internal relationships between metabolites as well as their changes throughout the pathways (Figure 3).Table 5 Metabolic pathways related to target metabolites in this work.

Table 5Pathway	Abbreviation	Matching Score (matched/input)	P-value	FDR correction	
Alanine, aspartate and glutamate metabolism	AAGM	7/26	1.95E-11	3.04E-10	
Arginine and proline metabolism	APM	6/26	6.56E-09	7.32E-08	
Glycine, serine and threonine metabolism	GSTM	6/26	1.71E-07	1.48E-06	
Cysteine and methionine metabolism	CMM	6/26	1.03E-05	6.69E-05	
Valine, leucine and isoleucine biosynthesis	VLIB	4/26	1.32E-05	7.92E-05	
Histidine metabolism	HM	6/26	8.25E-05	4.29E-04	
Phenylalanine, tyrosine and tryptophan biosynthesis	PTTB	3/26	3.91E-04	1.88E-03	
Lysine biosynthesis	LB	4/26	6.52E-04	2.67E-03	
Abbreviation: FDR, false discovery rate.

Figure 2 Metabolic network associated with Eimeria infection in laying hens. The network involves 8 metabolic pathways including aspartate and glutamate metabolism (AAGM), arginine and proline metabolism (APM), glycine, serine and threonine metabolism (GSTM), cysteine and methionine metabolism (CMM), valine, leucine and isoleucine biosynthesis (VLIB), histidine metabolism (HM), phenylalanine, tyrosine and tryptophan biosynthesis (PTTB) and lysine biosynthesis (LB). Red denotes differentially expressed compounds (p-value < 0.05, VIP score > 1.0 and |FC| > 1.5) selected in this study. Black indicates target metabolites. Gray denotes intermediate metabolites within the network.

Figure 2

Figure 3 Metabolite mapping on the metabolic network associated with Eimeria infection. The mapped pathways include (A) cysteine and methionine metabolism (CMM), (B) alanine, aspartate and glutamate metabolism (AAGM) and lysine biosynthesis (LB), (C) histidine metabolism (HM), and (D) arginine and proline metabolism (APM). Bar graph: mean value ± standard error.

Figure 3

Correlation Between Metabolomic Results and Phenotypic and Genetic Results

Statistical correlation analysis was conducted to explore the relationship between metabolomic results (this study) and phenotype and gene expression results (our previous study) of Eimeria infected laying hens (Figure 4). Both studies used the same set of samples. Phenotype profiles included body weight gain, average daily feed intake, hen-day egg production and villus height to crypto depth ratio (VH:CD) of duodenum, jejunum and ileum. Gene expression parameters included relative gene expression of tight junction proteins (occludin; OCLN and mucin; MUC-2), nutrient transporters (bo,+AT, boAT, EAAT-3 and y+ LAT-1), inflammatory cytokines including IL-1β, IL-10 and IFN-γ, and tumor necrosis factor-alpha (TNF-α). Among differentially expressed compounds, Asn, Met, Orn, and Trp were overall positively correlated with phenotype profiles, while others (Ala, Asp, Lys, 3MH) had negative correlations with the phenotype profiles (Figure 4A). Metabolites positively correlated with the phenotype profiles (Asn, Met, Orn, and Trp) were also positively correlated with the gene expression of tight junction proteins, nutrient transporters, and TNF-α (Figure 4B). While, metabolites negatively correlated with the phenotype profiles (Ala, Asp, Lys, 3MH) had negative correlations with these genes (tight junction proteins, nutrient transporters, and tumor necrosis factor-alpha). They were positively correlated with IL-1β, IL-10 and IFN-γ (Figure 4B).Figure 4 Correlation analysis between metabolic responses and (A) phenotype and (B) gene expression profiles. Heatmap displays positive correlations (red) and negative correlations (blue) based on Pearson's correlation coefficient. Asterisk: data obtained from our previous study.

Figure 4

DISCUSSION

In this study, using targeted metabolomics approach, the alteration of amino acids was investigated in the serum of Eimeria-infected laying hens. Metabolic difference was clearly observed in amino acids between control and infected groups at any dosage of Eimeria challenge (Table 2). This implies differentially expressed amino acid are significantly altered by Eimeria infection even at a low level of infection, revealing their potential as sensitive markers at the early stage of Eimeria infection. In our previous work, we found differences in intestinal lesion scores between the control and infected laying hens, but not with varying doses of Eimeria challenge (Sharma et al., 2024b). This phenotypic data supports the metabolomic result showing no significant variation in metabolites by Eimeria challenge dosages.

Differentially expressed compounds were selected by comparison between control and infected groups (Table 3, Table 4). Some differentially expressed compounds initially varying at 6 DPI seemed to be recovered at 14 DPI. This may be explained by host's status and responses to the disease at different stages of infection. Our previous work found the ongoing recovery process in Eimeria-infected laying hens at 14 DPI (Sharma et al., 2022, 2023, 2024a) This suggested metabolites at 14 DPI (recovery stage) are not suitable to serve as sensitive biomarkers for Eimeria infection. For this reason, metabolites at 6 DPI were further used for pathway enrichment analysis and correlation analysis.

With pathway enrichment analysis, the metabolic network of target metabolites was identified with 8 pathways (AAGM, APM, GSTM, CMM, VLIB, HM, PTTB and LB) (Figure 2). Metabolite mapping on the network revealed differentially regulated pathways as well as metabolic variation within the pathways between the control and infected group. Among the pathways, 5 pathways (AAGM, APM, CMM, HM and LB) were found to include differentially expressed compounds, indicating they are majorly affected by Eimeria infection (Figure 3). Overall, LB pathway was upregulated and the APM pathway was downregulated in the infected group, while others (AAGM, CMM and HM) showed a complex pattern of metabolic relationships between precursors and products.

In CMM pathway, the levels of precursors and intermediates (Asp, Ala, Hsr, Ser) were increased in the infected group, whereas products (Met and Trp) were decreased in the infected groups (Figure 3A). Ala was found to alleviate negative intestinal health from weaning stress in piglets (Chen et al., 2023). Similarly, the accumulation of Ala in the infected group might be a part of processes to mitigate deteriorated gastrointestinal health in laying hens induced by coccidiosis. Asp, a precursor of Ala, was also accumulated in the infected group, supporting why the level of Ala could be elevated in this group. With changing metabolic flux in the intermediate pathway, diminished Met was observed in the infected group. Malabsorption of Met was demonstrated in broiler chickens inoculated with Eimeria spp (Ruff and Wilkins, 1980; Teng et al., 2021). This can lead to a decreased serum level of Met in the host. There is another possibility of variation in Met. Met is a precursor of polyamines responsible for the proliferation of immune cells against biotic and abiotic stress (Ren et al., 2020). If Met is actively converted to these defense compounds during infection, it can be depleted over time. Similar reduction was found in Trp, another differentially expressed compound in this pathway. Trp is known to play a role in the regulation of appetite in animals (Le Floc'h and Seve, 2007). Given that laying hens experience decreased feed intake upon Eimeria infection with modified appetite, it may affect the level of Trp.

Differentially expressed compounds in AAGM and LB pathways were upregulated in Eimeria infection, except for Asn (Figure 3B). The pathways shared 2 differentially expressed compounds (Asp and Asn). Interestingly, these 2 compounds showed opposite metabolic responses against Eimeria infection, although they are closely connected in the pathway. Asp was increased in the infected group, while Asn was decreased. A reduction of plasma Asn levels in Eimeria-infected hens was previously observed (Rochell et al., 2016). Asn is responsible for the function of mineral absorption in animals (Kiela and Ghishan, 2016). Since Eimeria infection impedes the process of nutrient absorption including minerals, it may affect the level of Asn in infected laying hens. The opposite trend in the metabolic response of Asp is likely related to its innate function, as well as the activity of asparagine synthetase. Asp is associated with leukocyte-mediated immune responses, which can be upregulated by pathogen attack (Li et al., 2007). Asparagine synthetase is an enzyme that generates Asn from Asp. The activity of this enzyme was reported to be adjusted by immune responses (Li et al., 2007). If this enzyme was differentially expressed in laying hens by Eimeria infection, it would impact both Asp and Asn levels, e.g., accumulation of Asp and depletion of Asn. Follow-up research will be required with the confirmation of enzyme activity using asparagine synthetase. Meanwhile, Lys derived from Asp was accumulated similar to Asp in the infected group. Lys is involved in antibody responses and cell-mediated immunity (Kidd et al., 1997; Konashi et al., 2000; Chen et al., 2003). The upregulation of Lys may reflect a cellular response of laying hens to coccidiosis, supported by similar findings in broiler chickens (Rochell et al., 2016; Yazdanabadi et al., 2020).

In the HM pathway, 3MH is a differentially expressed compound notably increased in the infected group (Figure 3C). 3MH is a well-known compound derived from muscle catabolism (Hillgartner et al., 1981; Saunderson and Leslie, 1983; Hayashi et al., 1985; Jones et al., 1986; Saunderson and Leslie, 1988; Tomas et al., 1988; Fetterer and Allen, 2000). An increase in 3MH formation can be explained as a consequence of muscle degradation occurring in Eimeria infection of the host. Previous studies showing similar trends of elevated 3MH levels in Eimeria-infected poultry support our result (Fetterer and Allen, 2000; 2001). As aforementioned, the APM pathway was overall downregulated in the infected group (Figure 3D). Except for 1 compound (Cit), all other metabolites in the pathway were decreased upon infection. Remarkable reduction was observed in Orn which is a differentially expressed compound in this pathway. Metabolic variation in the APM pathway seems to be associated with a urea cycle of laying hens. Poultry possess an incomplete urea cycle due to the absence and/or limited activities of certain enzymes involved in urea synthesis (Liu and Kim, 2023). In the incomplete cycle, a precursor Arg can be converted to either Cit or Orn. Nitric oxide, a by-product produced with Cit, is a key mediator of immune responses to Eimeria. spp (Lillehoj and Li, 2004; Castro and Kim, 2020). Hence, if metabolic flux increased towards Cit formation in the infected group, it would lead to diminished flux towards the counterpart Orn formation, as indicated in our result. Arg is also a precursor of Glu, Gln and Pro in the APM pathway. Thus, these downstream metabolites and their levels can be affected by Cit production, as well. This suggests the downregulation of the APM pathway might be a strategic response of the host to combat the disease.

From the comparison of the metabolomics results and our previous results (Figure 4), the positive correlation between differentially expressed compounds (Asn, Met, Trp) and phenotype (body weight gain, average daily feed intake, hen-day egg production, VH:CD ratio of duodenum, jejunum and ileum) and gene expression (tight junction proteins, nutrient transporter) parameters supported our assumption on the involvement of these metabolites in modified appetite signaling and malabsorption under infection. Among the differentially expressed compounds, Met was reported to contribute to egg production and egg mass, coinciding with the correlation result (Alagawany et al., 2020). Another set of differentially expressed compounds (Ala, Asp, Lys, 3MH) showing the opposite correlation trend with the above parameters were likely associated with other mechanisms rather than appetite/malabsorption. This may be explained by their positive correlation with inflammation-related cytokines (IL-1β, IFN-γ and IL-10) which are released in response to protozoal infection; IL-1β arouses the production of chemokines at the site of infection, IFN- γ suppresses the intracellular progression of Eimeria and IL-10 alleviates the inflammation (Giansanti et al., 2006; Lee et al., 2022). The potential role of Ala, Asp and Lys as defense molecules against Eimeria infection was discussed earlier. Interestingly, the positive correlation of 3MH and cytokines implied that 3MH might be involved in defense signaling, in addition to participation in muscle catabolism as a consequence of infection.

In the present work, a targeted metabolomics approach was employed to explore differentially expressed amino acids and rewired metabolic network under multiple Eimeria species (Eimeria maxima, Eimeria tenella, and Eimeria acervulina) challenge in laying hens. Discriminant amino acids (6 DPI: 3MH, Ala, Asn, Asp, Lys, Met, Orn and Trp; 14 DPI: Asn, Leu and Lys) were identified, and their internal relationships, as well as related metabolic pathways and network were elucidated. Correlation analysis between metabolomics and previous (phenotype, gene expression) results revealed amino acids such as 3MH, Ala, Asp and Lys are positively correlated with host defense mechanisms (e.g., inflammatory cytokines), while others such as Asn, Met, Orn and Trp are more likely related to intestinal integrity and nutritional absorption (e.g., VH:CD ratio, tight junction proteins, nutrient transporter gene) affecting the overall performance of laying hens. Our findings provide in-depth information on altered amino acid metabolism and mechanisms in Eimeria infected laying hens, which may be useful to come up with amino acid-involved nutritional strategies in the infected laying hens.

DISCLOSURES

The authors declare no conflict of interest.

Appendix Supplementary materials

Image, application 1

Supplementary material associated with this article can be found in the online version at doi:10.1016/j.psj.2024.104244.
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REFERENCES

Aggrey S.E. Milfort M.C. Fuller A.L. Yuan J. Rekaya R. Effect of host genotype and Eimeria acervulina infection on the metabolome of meat-type chickens PLoS One 14 2019 e0223417
Alagawany M. El-Hindawy M.M. El-Hack M.E. Arif M. El-Sayed S.A. Influence of low-protein diet with different levels of amino acids on laying hen performance, quality and egg composition Acad. Bras. Ciênc. 92 2020 1 11
Allen P. Fetterer R. Effect of Eimeria acervulina infections on plasma L-arginine Poult. Sci. 79 2000 1414 1417 11055846
Blake D.P. Knox J. Dehaeck B. Huntington B. Rathinam T. Ravipati V. Ayoade S. Gilbert W. Adebambo A.O. Jatau I.D. Re-calculating the cost of coccidiosis in chickens Vet. Res. 51 2020 1 14 31924264
Castro F.L.S. Teng P. Yadav S. Gould R.L. Craig S. Pazdro R. Kim W.K. The effects of L-Arginine supplementation on growth performance and intestinal health of broiler chickens challenged with Eimeria spp Poult. Sci. 99 2020 5844 5857 33142502
Castro F.L.d.S. Kim W.K. Secondary functions of arginine and sulfur amino acids in poultry health Animals 10 2020 2106 33202808
Chapman H.D. Coccidiosis in egg laying poultry Egg innovations and strategies for improvements 2017 Elsevier Inc. London, UK 571 579
Chen C. Sander J. Dale N. The effect of dietary lysine deficiency on the immune response to Newcastle disease vaccination in chickens Avian Dis 47 2003 1346 1351 14708981
Chen L. Zhong Y. Ouyang X. Wang C. Yin L. Huang J. Li Y. Wang Q. Xie J. Huang P. Effects of β-alanine on intestinal development and immune performance of weaned piglets Anim. Nutr. 12 2023 398 408 36788928
Conway D.P. McKenzie M.E. Poultry coccidiosis: diagnostic and testing procedures 2007 Blackwell Publishing Professional Ames, IA
Duffy C. Mathis G. Power R. Effects of Natustat™ supplementation on performance, feed efficiency and intestinal lesion scores in broiler chickens challenged with Eimeria acervulina, Eimeria maxima and Eimeria tenella Vet. Parasitol. 130 2005 185 190 15905033
Eriksson L. Trygg J. Wold S. CV-ANOVA for significance testing of PLS and OPLS models J. Chemon. 22 2008 594 600
Fetterer R. Allen P. Eimeria acervulina infection elevates plasma and muscle 3-methylhistidine levels in chickens J. Parasitol. 86 2000 783 791 10958457
Fetterer R. Allen P. Eimeria tenella infection in chickens: effect on plasma and muscle 3-methylhistidine Poult. Sci. 80 2001 1549 1553 11732670
Fiehn O. Metabolomics–the link between genotypes and phenotypes Plant Mol. Biol. 48 2002 155 171 11860207
Fitz-Coy S. Edgar S. Effects of Eimeria mitis on egg production of single-comb white leghorn hens Avian Dis 36 1992 718 721 1417602
Giansanti F. Giardi M. Botti D. Avian cytokines-an overview Curr. Pharm. Des. 12 2006 3083 3099 16918436
Hayashi K. Tomita Y. Maeda Y. Shinagawa Y. Inoue K. Hashizume T. The rate of degradation of myofibrillar proteins of skeletal muscle in broiler and layer chickens estimated by Nr-methylhistidine in excreta Br. J. Nutr. 54 1985 157 163 4063300
Hegde K. Reid W. Effects of six single species of coccidia on egg production and culling rate of susceptible layers Poult. Sci. 48 1969 928 932
Hillgartner F.B. Williams A.S. Flanders J.A. Morin D. Hansen R.J. Myofibrillar protein degradation in the chicken 3-Methylhistidine release in vivo and in vitro in normal and genetically muscular-dystrophic chickens Biochem. J. 196 1981 591 601 7316997
Jones S. Aberle E. Judge M. Estimation of the fractional breakdown rates of myofibrillar proteins in chickens from quantitation of 3-methylhistidine excretion Poult. Sci. 65 1986 2142 2147 3822994
Kanehisa M. Goto S. KEGG: kyoto encyclopedia of genes and genomes Nucleic Acids Res 28 2000 27 30 10592173
Kidd M. Kerr B. Anthony N. Dietary interactions between lysine and threonine in broilers Poult. Sci. 76 1997 608 614 9106889
Kiela P.R. Ghishan F.K. Physiology of intestinal absorption and secretion Best Pract. Res. Clin. Gastroenterol. 30 2016 145 159 27086882
Konashi S. Takahashi K. Akiba Y. Effects of dietary essential amino acid deficiencies on immunological variables in broiler chickens Br. J. Nutr. 83 2000 449 456 10858703
Le Floc'h N. Seve B. Biological roles of tryptophan and its metabolism: Potential implications for pig feeding Livest Sci 112 2007 23 32
Lee Y. Lu M. Lillehoj H.S. Coccidiosis: recent progress in host immunity and alternatives to antibiotic strategies Vaccines 10 2022 215 35214673
Li P. Yin Y.-L. Li D. Kim S.W. Wu G. Amino acids and immune function Br. J. Nutr. 98 2007 237 252 17403271
Li X. Jiang X. Qi D. Wang X. Wang C. Fei C. Zhou W. Li J. Zhang K. Effects of ethanamizuril, sulfachlorpyridazine or their combination on cecum microbial community and metabolomics in chickens infected with Eimeria tenella Microb. Pathog. 173 2022 105823
Lillehoj H.S. Li G. Nitric oxide production by macrophages stimulated with coccidia sporozoites, lipopolysaccharide, or interferon-γ, and its dynamic changes in SC and TK strains of chickens infected with Eimeria tenella Avian Dis 48 2004 244 253 15283411
Liu G. Kim W.K. The Functional Roles of Methionine and Arginine in Intestinal and Bone Health of Poultry Animals 13 2023 2949 37760349
López-Ibáñez J. Pazos F. Chagoyen M. MBROLE 2.0—functional enrichment of chemical compounds Nucleic Acids Res 44 2016 W201 W204 27084944
Lunden A. Thebo P. Gunnarsson S. Hooshmand-Rad P. Tauson R. Uggla A. Eimeria infections in litter-based, high stocking density systems for loose-housed laying hens in Sweden Br. J. Nutr. 41 2000 440 447
Lusk J.L. Consumer preferences for cage-free eggs and impacts of retailer pledges Agribusiness 35 2019 129 148
Mesa C. Gómez-Osorio L. López-Osorio S. Williams S. Chaparro-Gutiérrez J. Survey of coccidia on commercial broiler farms in Colombia: frequency of Eimeria species, anticoccidial sensitivity, and histopathology Poult. Sci. 100 2021 101239
Rajasundaram D. Selbig J. More effort—more results: recent advances in integrative ‘omics’ data analysis Plant Biol 30 2016 57 61
Ren Z. Bütz D.E. Whelan R. Naranjo V. Arendt M.K. Ramuta M.D. Yang X. Crenshaw T.D. Cook M.E. Effects of dietary methionine plus cysteine levels on growth performance and intestinal antibody production in broilers during Eimeria challenge Poult. Sci. 99 2020 374 384 32416822
Rochell S. Parsons C. Dilger R. Effects of Eimeria acervulina infection severity on growth performance, apparent ileal amino acid digestibility, and plasma concentrations of amino acids, carotenoids, and α1-acid glycoprotein in broilers Poult. Sci. 95 2016 1573 1581 26933234
Ruff M. Wilkins G. Total intestinal absorption of glucose and L-methionine in broilers infected with Eimeria acervulina, E. mivati, E. maxima or E. brunetti Parasitology 80 1980 555 569 7393622
Ruff M.D. Important parasites in poultry production systems Vet. Parasitol. 84 1999 337 347 10456422
Santos T.S. Teng P.Y. Yadav S. de Souza Castro F.L. Gould R.L. Craig S.W. Chen C. Fuller A.L. Pazdro R. Sartori J.R. Kim W.K. Effects of Inorganic Zn and Cu supplementation on gut health in broiler chickens challenged with Eimeria spp Front. Vet. Sci. 7 2020 230 32426385
Saunderson C.L. Leslie S. NT-methyl histidine excretion by poultry: not all species excrete NT-methyl histidine quantitatively Br. J. Nutr. 50 1983 691 700 6639927
Saunderson C.L. Leslie S. Muscle growth and protein degradation during early development in chicks of fast and slow growing strains Comp. Biochem. Physiol. Part A: Physiol. 89 1988 333 337
Sharma M.K. Liu G. White D.L. Tompkins Y.H. Kim W.K. Effects of mixed Eimeria challenge on performance, body composition, intestinal health, and expression of nutrient transporter genes of Hy-Line W-36 pullets (0-6 wks of age) Poult. Sci. 101 2022 102083
Sharma M.K. Liu G. White D.L. Tompkins Y.H. Kim W.K. Graded levels of Eimeria challenge altered the microstructural architecture and reduced the cortical bone growth of femur of Hy-Line W-36 pullets at early stage of growth (0-6 wks of age) Poult. Sci. 102 2023 102888
Sharma M.K. Liu G. White D.L. Kim W.K. Graded levels of Eimeria infection linearly reduced the growth performance, altered the intestinal health, and delayed the onset of egg production of Hy-Line W-36 laying hens when infected at the prelay stage Poult. Sci. 103 2024 103174
Sharma M.K. Singh A.K. Goo D. Choppa V.S.R. Ko H. Shi H. Kim W.K. Graded levels of Eimeria infection modulated gut physiology and temporarily ceased the egg production of laying hens at peak production Poult. Sci. 103 2024 103229
Soares R. Cosstick T. Lee E. Control of coccidiosis in caged egg layers: A paper plate vaccination method J. Appl. Poult. Res. 13 2004 360 363
Su S. Miska K. Fetterer R. Jenkins M. Wong E. Expression of digestive enzymes and nutrient transporters in Eimeria acervulina-challenged layers and broilers Poult. Sci. 93 2014 1217 1226 24795315
Teng P.-Y. Yadav S. Shi H. Kim W.K. Evaluating endogenous loss and standard ileal digestibility of amino acids in response to the graded severity levels of E. maxima infection Poult. Sci. 100 2021 101426
Teng P.-Y. Yadav S. de Souza Castro F.L. Tompkins Y.H. Fuller A.L. Kim W.K. Graded Eimeria challenge linearly regulated growth performance, dynamic change of gastrointestinal permeability, apparent ileal digestibility, intestinal morphology, and tight junctions of broiler chickens Poult. Sci. 99 2020 4203 4216 32867964
Tomas F. Jones L. Pym R. Rates of muscle protein breakdown in chickens selected for increased growth rate, food consumption or efficiency of food utilisation as assessed by Nτ-methylhistidine excretion Br. J. Nutr. 29 1988 359 370
Wang W.-C. Chung H.-H. Dutkiewicz E.P. Wong J.-Y. Yang W.-C. Chang C.L.-T. Hsu C.-C. On-site diagnosis of poultry coccidiosis by a miniature mass spectrometer and machine learning ACS Agric. Sci. Technol. 2 2021 17 21
Wu G. Functional amino acids in growth, reproduction, and health Adv. Nutr. 1 2010 31 37 22043449
Yazdanabadi F.I. Mohebalian H. Moghaddam G. Abbasabadi M. Sarir H. Vashan S.J.H. Haghparast A. Influence of Eimeria spp. infection and dietary inclusion of arginine on intestine histological parameters, serum amino acid profile and ileal amino acids digestibility in broiler chicks Vet. Parasitol. 286 2020 109241
