Proteome and transcriptome analysis revealed florfenicol via affected drug metabolism and lipid metabolism induce liver injury of broilers.

In order to explore the mechanism of liver injury induced by florfenicol (FFC) in broilers. Sixty broilers were randomly divided into 2 groups: control group: normal drinking water and feed were given every d; FFC group: tap water containing FFC (0.15g/L) was given every d and feed was taken freely; each group was given 5 dd of continuous medication and feed was taken freely. The results showed that compared with the control group, FFC could significantly inhibit the weight gain of broilers (P < 0.05), and significantly inhibit the expression of CYP1A1 and CYP2H1 in liver tissue (P < 0.05). It was found that the expression of genes related to the effect of cytochrome P450 on the metabolism of exogenous substances, the peroxisome proliferators-activated receptors signal pathway, peroxisome pathway and glutathione metabolic pathway in the liver of broilers. The results of qPCR of UDP glucuronosyltransferase family 2A1 (UGT2A1), glutathione S-transferase-like 2 (GSTAL2), hematopoietic prostaglandin D synthase (HPGDS), glutathione S-transferase theta 1(GSTT1), isocitrate dehydrogenase (NADP(+)) 1 (IDH1), acyl-CoA oxidase 2 (ACOX2), fatty acid binding protein 1 (FABP1), adenylosuccinate lyase (ADSL), and phosphoribosyl aminoim idazolesuccino carboxamide synthase (PAICS) genes which were randomly selected from the most significant genes were consistent with those of RNA-seq. The results showed that FFC can affect the drug metabolism and lipid synthesis in the liver of broiler, thus impairing the normal function of liver and the growth and development of broiler.

INTRODUCTION

The abuse of antibiotics is widespread in every country, which causes serious harm to the safety of human and animals (Manyi-Loh et al., 2018). It has been reported that the health of humans correlates directly with the environment (i.e., their habitat and its components, including plants, animals, microorganisms, and other human beings) and the quality of food that they consume (Ames, 1983; Soto, 2013). Taking into consideration the growing human population, the changing standard of living conditions, the food shortages, and the greater demands for the intensified production of animal proteins for human consumption across the globe, essential practices to improve on the agricultural and industrial productivity are needed (Anderson et al., 1998). Of interest is the critical use of antibiotics in agriculture to meet the demands of the rising human population, as the use of antibiotics in this setting has been associated with several benefits. It is therefore anticipated that, in the future, almost all the animals slaughtered and consumed as food must have received a chemotherapeutic or a prophylactic agent of some sort (Lee et al., 2001). However, the consumption of these meats, milk, and eggs contaminated with antibiotic residues usually have tremendous impacts on the health of humans. These effects may be direct or indirect, owing to the high dose of the residues, which must have accrued over a prolonged period (Lee et al., 2001; Hanekamp and Bast, 2015). They can be exhibited as drug hypersensitivity reactions, aplastic anemia, carcinogenic, mutagenic, immunologic and teratogenic effects, nephropathy, hepatotoxicity, disruption of the normal flora of the intestines, a reproductive disorder, as well as the development of antibiotic-resistant bacteria in the gut (Nisha, 2008; Beyene, 2015).

Florfenicol (FFC), a veterinary antibiotic, as analogs of chloramphenicol that are frequently used as substitutes, FFC and thiamphenicol exhibit similar therapeutic benefits (van de Riet et al., 2019). The use of FFC has become especially prevalent, due to the appearance of fewer side effects (Lai et al., 2009). At present, in the practice of broiler breeding, FFC is often added to the feed or drinking water of broiler from 1-dd-old in a low dose to fight against intestinal bacterial infection to improve the survival rate and growth rate of chickens (Rue et al., 2011). However, in this process, there is a lot of abuse of FFC, so the side effects of FFC on broilers are inevitable (Ola et al., 2014). In recent years, the toxic and side effects of FFC in normal dosage have been widely reported, which can cause moderate myelodysplasia (Hassanin et al. 2014), and promote the apoptosis of chicken liver cells (Li et al., 2018). In addition, FFC not only causes serious damage to chicken body, leads to multiple immunosuppressive diseases, affects breeding efficiency, but also leads to drug residues in chicken body, affects the quality and safety of chicken food, and then affects human health (Donoghue, 2003; Nasim et al., 2016). Previous studies in our laboratory also found that the administration of FFC at the age of 1 dd can significantly inhibit the early weight gain of chicks, damage the hemopoietic function of chicks, and damage the liver function of chicks (Han et al., 2020). However, the mechanism of FFC on liver injury in broilers is not clear. In this project, we intend to use eukaryotic transcriptome sequencing, TMT isotope labeled quantitative proteome sequencing, PCR, and other technologies to study in detail the key targets of liver damage caused by FFC from the perspective of transcriptome and proteomics, so as to provide a basis for the rational use of FFC in broilers.

MATERIALS AND METHODS

Drugs and Reagents

chickens (Arbor Acres broilers) were purchased from Hebei Dawu Agricultural Group Poultry Company Ltd (Baoding, China). FFC (purity≥95%) was purchased from Shenniu Biological Technical Co. Ltd (Shandong, China). Alanine aminotransferase (ALT) and aspartate aminotransferase (AST) assay kits were purchased from the Nanjing Jiancheng Bioengineering Institute (Nanjing, China). Commercial kits for detecting chicken cytochromeP450 1A1(CYP1A1) and CYP2H1 were purchased from Shanghai hengyuan Biotech CO.,Ltd (Shanghai, China). Other chemicals used in these experiments of analytical grade were from commercial sources.

Experiment Design

A total of 60 one-d-old chicks were housed in a clean well-ventilated room and kept under good sanitation and hygienic management. Feed and water were available ad libitum. After an acclimatization period of 1 dd, chicks (average body weight = 42.34g ±1.3 g/chick) were randomly allotted into 2 groups (30 chicks per group). FFC was given orally in drinking water at 0.0 g/L for control group, FFC at 0.15 g/L (Recommended dosage of Chinese Veterinary Pharmacopoeia in chick) for FFC group. The FFC treatment was from dd 1 to dd 5 of age consecutively and chicks in all groups were fed with basal diet (purchased from Hebei Dawu Agricultural Group Poultry Company Ltd). At age of dd 5, 21, and 42, chickens were sacrificed following euthanization with sodium pentobarbital. Blood samples were collected from the veinand the liver of the chickens was obtained. In addition, 3 broiler livers were randomly selected from each group used to transcriptome and proteome sequencing at age of dd 5, which was completed by PERSONAL Company (Nanjing, China). All the experimental protocols were approved by the Animal Care and Use Committee of Agricultural University of Hebei prior to the initiation of the study.

Amount of Body Weight Gain

Each group of chickens was recorded their initial body weight, and weighed each group again after feeding to 5-d-old, 21-d-old and 42-d-old chickens, and then calculated the amount of weight gain of each group.

Biochemical Parameter Measurement

At D 5, 21, and 42, the blood samples were collected from 10 birds of each group. The blood samples were left to coagulate at room temperature. The serum was separated by centrifugation of coagulated blood at 3,000 rpm for 15 min. The clear serum was kept in a freezer (-20°C) until use to detect the serum total protein, albumin, ALT and AST, superoxide dismutase (SOD), glutathione (GSH), catalase (CAT), lipid peroxidation (MDA) by Biochemical analyzer (Han et al., 2019).

ELISA Analysis

Sections of liver tissue were homogenized in 9 volumes of cold Tris buffer (0.01 M Tris-HCl, 0.1 mM EDTA-Na2, 0.01 M sucrose, 0.9% saline [pH 7.4]) and a 10% (wt/vol) tissue homogenate was prepared. The supernatant obtained from 4,000 g at 4°C for 15 min of centrifugation. The contents of CYP1A1 and CYP2H1 in the supernatant of liver homogenate were measured by ELISA kit (Shanghai hengyuan Biotech CO.,Ltd. Shanghai, China).

RNA-seq

RNA-seq was performed on livers of chickens using Illumina's sequencing platform Illumina HiSeq. Testicular tissue total RNA was extracted using the Eastep Super Total RNA Extraction Kit (Promega, LS1040, US). Sequencing libraries were generated using NEBNext Ultra RNA Library Prep Kit (New England Biolabs (Beijing) Ltd., Beijing, China) for Illumina (NEB) following manufacturer's recommendations. The library preparations were sequenced on an Illumina Hiseq platform. Reference genome and gene model annotation files were downloaded from genome website directly (https://www.ncbi.nlm.nih.gov/genome/?term=Mus+musculus). Differential expression analysis was performed using the DEGSeq R package (1.20.0). The P values were adjusted using the Benjamini & Hochberg method.

Corrected P value of 0.005 and Log2(Fold change) of 1 were set as the threshold for significantly differential expression. Gene Ontology (GO) enrichment analysis of differentially expressed genes was implemented by the GOseq R package. KOBAS software was used to test the statistical enrichment of differential expression genes in KEGG pathways.

Protein Extraction and TMT Labeling

All samples were homogenized in lysis buffer (4% SDS, 1 mM DTT, 150 mM Tris-HCl pH 8.0, protease inhibitor). After 3 min incubation in boiling water, the homogenate was sonicated on ice. The crude extract was then incubated in boiling water again and clarified by centrifugation at 16,000 x g at 25°C for 10 min. Protein content was determined with the BCA protein assay reagent (Beyotime). 200 μg of proteins for each sample was incorporated into 30 μL SDT buffer (4% SDS, 100 mM DTT, 150 mM Tris-HCl pH 8.0). The detergent, DTT and other low-molecular-weight components were removed using UA buffer (8 M Urea, 150 mM Tris-HCl pH 8.0) by repeated ultrafiltration (Pall units, 10 kD). Then 100 μL 0.05 M iodoacetamide in UA buffer was added to block reduced cysteine residues and the samples were incubated for 20 min in darkness. The filters were washed with 100 μL UA buffer 3 times and then 100 μL DS buffer (50 mM triethylammoniumbicarbonate at pH 8.5) twice. Finally, the protein suspensions were digested with 2 μg trypsin (Promega) in 40 μL DS buffer overnight at 37°C, and the resulting peptides were collected as a filtrate. The peptide content was estimated by UV light spectral density at 280 nm using an extinctions coefficient of 1.1 of 0.1% (g/L) solution that was calculated on the basis of the frequency of tryptophan and tyrosine in vertebrate proteins.

UPLC-QTOF-MS/MS Analysis

TMT labeled peptides were fractionated by SCX chromatography using the AKTA Purifier system (GE Healthcare). The fractioned peptides were collected and combined into 20 final fractions, which were applied to LC-MS/MS. In brief, the prepared sample was loaded on an EASY-nLC 1,000 nano HPLC (Thermo Fisher Scientific Inc., Waltham, MA). The peptides were eluted onto an analytical C18 column (10 cm × 75 μm). The peptides were subjected to electrospray ionization followed by tandem mass spectrometry (MS/MS) in a Q-Exactive (Termo scientifc). Intact peptides were detected in the Orbitrap. Te electrospray voltage applied was 2.1 kV. Automatic gain control (AGC) was used to optimize the spectra generated by the orbitrap. For MS scans, the m/z scan range was 350 to 2,000.

Sequence Database Searching and Data Analysis

LC-embedded into Proteome Discoverer 1.4 (Thermo Electron, San Jose, CA) against uniport Gallus gallus 32641 20190702 (32641 sequences, download at 20190702) and the decoy database. For protein identification, the following options were used. Peptide mass tolerance = 20 ppm, MS/MS tolerance = 0.1 Da, Enzyme = Trypsin, Missed cleavage = 2, Fixed modification: Carbamidomethyl (C), TMT10(K), TMT10(N-term), Variable modification:Oxidation(M), FDR ≤ 0.01.

Bioinformatics

Functional analysis was conducted using gene ontology (GO) annotations by Blast2GO sofware (v4.5 pipeline 5), and the proteins were categorized according to their biological processes, molecular functions, and cellular localizations. Te diferentially expressed proteins were further assigned to the Kyoto Encyclopedia of genes and genomes (KEGG) database (http://www.genome.jp/kegg/pathway.html). The most important is the integrated analysis of the pathway. According to the results of pathway analysis of different genes and proteins, the genes and proteins involved in the same pathway were screened, and the corresponding data were analyzed comprehensively. In addition, the ID of gene and protein was transformed according to KEGG format by using transformation ID method, and the ID was mapped into KEGG database to obtain the path map after gene and protein integration. Protein-protein interaction networks were analyzed using the publicly available program STRING (http://string-db.org/)and minimum required interaction score set 0.400.

QRT-PCR Detection of mRNA Transcription in Liver Tissue

At age of d 5, 21, and 42, ten chickens were sacrificed following euthanization with sodium pentobarbital and the liver samples were obtained from each chicken. The total RNA Extraction Kit (Promega, Beijing, China) was used to extract RNA from the liver and reverse transcription to obtain cDNA. The mRNA levels of CYP1A1, CYP2H1, UGT2A1, GSTAL2, HPGDS, GSTT1, IDH1, ACOX2, FABP1, ADSL and PAICS were detected by real-time quantitative PCR. Primers were designed and synthesized by Takara (Dalian, China) (Table 1). The pre denaturation was at 95 °C for 120 s, and the amplification was carried out in 45 cycles, including 5 s at 95 °C and 30 s at 64 °C. Then 72 °C for 30s. The internal reference gene is β - actin, and the relative transcription level of each gene is calculated by 2−ΔΔ CT(Livak and Schmittgen, 2001).

Table 1

Primers used for qRT-PCR.

Gene	Primer sequence (5’-3’)	Product length (bp)	Accession number
CYP1A1	F: AGGACGGAGGCTGACAAGGT R:CAGGATGGTGGTGAGGAAGAG	136	NM_205147.1
CYP2H1	F: ATCCCCATCATTGGAAATGT R: TCGTAGCCATACAGCACCAC	148	NM_001001616.1
UGT2A1	F: CCAGCTTCCACAAAATGTCCTC	150	XM_004941194.3
	R: CCATTGGTCCCACCATGAGTAA
GSTAL2	F: GGGTGGTTGAAGGATCGAACT	157	XM_025148955.1
	R: CTTCACTGGTTCCATTCGGC
HPGDS	F: GCAGAAATCTGCCGCTACCT	199	NM_205011.1
	R: TCTGACCTGCCAGACCTGAT
GSTT1	F: CCATGTGGATCAAGGTGCTGA	158	NM_205365.1
	R: CAAGGAAATCTCGCTCCCGA
IDH1	F: CTCTGTTGCACAAGGTTATGGC	154	XM_004942682.3
	R: AATGGGGTTCGTGGAGGTTT
ACOX2	F: TGAATTCTGCACTCGGCAGT	100	XM_015293306.2
	R: TCATAGGCTGGGCTTATCTGC
FABP1	F: CAGGAGAGAAGGCCAAGTGTAT	100	NM_204192.3
	R: GTGTCTCCGTTGAGTTCGGT
ADSL	F: TCACTCACTACCAACCTGCAC	131	NM_205529.1
	R: GCCTTTCACACCCCGAAAAC
PAICS	F: ATGCGTTCTGATGCAGTCCA	141	NM_205524.2
	R: GCCGTTTTGATTCCTGCTTCC
β-actin	F: ATTGTCCACCGCAAATGCTTC	124	NM_205518.1
	R:AAATAAAGCCATGCCAATCTCGTC

Statistical Analysis

Using SPSS21.0 software (IBM Corporation, Armonk, NY) to test the normality of the counting data. Then the differences among groups were compared by T test, the data in this experiment were mean ± SD and significant differences among groups were set at a value of P < 0.05, P < 0.01.

RESULTS

Effect of FFC on Weight Gain in Broilers

As shown in Figure 1, compared with the control group, 0.15g/L FFC significantly reduced the weight gain of broilers at age of 5 dd, 21 dd and 42 dd (P < 0.05).

Figure 1

weight gain of broilers of different ages. *P < 0.05, compared with the control group.

Effect of FFC on ALT and AST in Serum of Chickens

As shown in Figure 2, compared with the control group, FFC significantly increased AST and ALT content in serum of broilers and decreased TP and ALB content in serum of broilers at age of d 5 and 21 (P < 0.05); while at age of d 42, compared with the control group, FFC only significantly reduced Alb content in serum of broilers (P < 0.05), However, FFC did not significantly cause changes of AST, ALT and TP contents (P > 0.05).

Figure 2

Contents of alt, AST, TP and ALB in broilers serum of different ds. *P < 0.05, compared with the control group.

Effect of FFC on the Content of GSH, MDA and CAT in Chicken Liver

As shown in Figure 3, compared with the control group, FFC significantly reduce the content of SOD and CAT in the broilers liver tissue at age of d 5 and 21 (P < 0.05), and significantly reduce the content of GSH in the broilers liver tissue at age of d 5 and 21 (P < 0.05). compared with the control group, FFC significantly increased the content of MDA in broilers liver tissue at age of d 5, 21 and 42 (P < 0.05).

Figure 3

Contents of SOD, GSH, MDA and cat in liver tissues of broilers of different ages. *P < 0.05, compared with the control group.

Effect of FFC on the Contents of CYP1A1 and CYP2H1 and mRNA Transcription in Chicken Liver

As shown in Figure 4, compared with the control group, FFC induced the CYP1A1 content and mRNA transcription level in the broilers liver tissue decreased significantly at the age of d 5 and 21 (P < 0.05); while at the age of d 42, the CYP1A1 content and mRNA transcription level of the broilers liver tissue in the control group and FFC group had no significant difference (P > 0.05). At age of d 21 and 42, compared with the control group, FFC also significantly reduced the content of CYP2H1 in chicken liver; but, at age of d 5, 21, and 42, the mRNA transcription level of CYP2H1 of broilers liver tissue in FFC group was significantly lower than that in control group (P < 0.05).

Figure 4

(A) the content of CYP1A1 and CYP2H1 in liver tissue of each group; (B) the transcription level of CYP1A1 and CYP2H1 mRNA in liver tissue of each group. *P < 0.05, compared with the control group.

Expression of Differential Genes and Proteins

Principal component analysis (PCA) showed large variations in transcript and protein (Figure 5A) abundance between chicken liver in FFC group and liver in control group. The results of transcriptome group showed that compared with the control group, FFC caused 1278 mRNA expression differences, 344 of which were up-regulated genes and 934 of which were down-regulated genes (Figure 5B), Figure 5D showed the clustering of these 1,278 genes; while the results of proteome group showed that compared with the control group, FFC caused 917 protein expression differences, There are 488 up-regulated proteins and 429 down-regulated proteins of those 917 proteins (Figure 5C), and Figure 5E shows the clustering of 917 proteins.

Figure 5

Transcriptomic and proteomic mapping of broilers liver. (A) PCA for RNA-seq or proteomics data, the points represent biological replicates. (B, C) Volcano plots showing the relative abundances of transcripts (B) or proteins (C). Transcripts were considered differentially expressed at FDR <1% and fold change > 3 between proximal and distal regions, whereas proteins were considered differentially expressed at FDR < 5%. (D, E) Heat maps of 1278 transcripts or 917 proteins.

We also explored the expression of proteins and its corresponding mRNA, as shown in Figures 6A and 6B, compared with the control group, the expression of 1,106 mRNA and 824 proteins in broiler liver treated by FFC was different. There were 93 differences in the expression of protein and corresponding mRNA. As shown in Table 2, there are 49 up-regulated and 44 down-regulated mRNA and protein expressions in the 93 differentially expressed proteins and mRNA, while there are 47 up-regulated and 42 down-regulated proteins and related mRNA, 2 up-regulated and 2 down regulated proteins and corresponding mRNA. Figure 6C shows the expression of the top 20 proteins and their corresponding mRNA in the liver tissue of broilers induced by FFC.

Figure 6

(A) For the correlation analysis of protein and gene expression quantity, the abscissa and ordinate are the multiple of protein and gene expression difference, red represents the result of significant difference expression at transcripts and protein level, blue represents the result of significant difference expression only at protein level, green represents the result of significant difference expression only at transcription level, black represents the result of no significant difference between the 2 levels results. (B) Venn map of total differential proteins and corresponding differential transcripts; (C) Figure 3 results of differential expression of proteins and related transcripts. Abscissa is the corresponding gene name of related proteins and transcripts, ordinate is the multiple of differential expression, red is the transcripts, and blue is the egg white matter.

Table 2

Expression of differential protein and its corresponding differential transcription.

terms	mRNA (up)	mRNA (down)	Total
Protein (up)	47	2	49
Protein (down)	2	42	44
Total	49	44	93

Bioinformatics Analysis of Differentially Expressed Genes and Proteins

The functions of differential genes are divided into 3 categories: biological process, cell composition and molecular function. The results showed that the difference genes in broilers liver were related to the process of biosynthesis and metabolism after FFC exposure. The results of enrichment analysis will give the directed acyclic graphs of 3 Ontology (cell composition, molecular function and biological process) of GO respectively (Figure 7A). Enrichment analysis results will give the directed acyclic graph of 3 go ontologies (cell composition, molecular function and biological process) respectively. It can be seen from the graph that the genes with significant changes in the liver caused by FFC are mainly enriched to a more detailed level and perform specific biological functions (Figure 7B). From the KEGG enrichment result, we also found that the expression of genes related to the effect of cytochrome P450 on the metabolism of exogenous substances (UGT2A1, GSTAL2, HPGDS, GSTT1) was significantly changed by FFC, and the genes related to PPAR signal pathway (ACOX2, ACAA1, FABP1) were also significantly changed. FFC also caused changes in the expression of peroxisome related genes and glutathione metabolic pathway (ACOX2, ACAA1, FABP1) related genes in the liver of broilers (Figure 7C, Table 3). To explore the direct and indirect interaction between these expressed significant target proteins, to generate the interaction network and analyze the network, we found that: GSTT1, UGT2A1, HPGDS, ACOX2 and other genes can be used as the target molecules of meat and liver damage caused by FFC (Figure 7D).

Figure 7

(A) Go enrichment analysis histogram; (B) gene ontology DAG enrichment diagram, each node represents a go term, branch represents inclusion relationship, the functional scope defined from top to bottom is getting smaller and smaller, the box represents the GO term with top 10 enrichment degree, and the darker the color, the higher the enrichment degree; (C) KEGG pathway enrichment result histogram, abscissa is pathway The vertical coordinate is the diagram of - log10 (P value); (D) PPI network enriched by each pathway - gene expression.

Table 3

List of genes involved in the most significant pathway of KEGG enrichment.

Pathway ID	Pathway	Gene list
gga00982	Drug metabolism - cytochrome P450	UGT2A1, GSTAL2, HPGDS, GSTT1, DM5L
gga00480	Glutathione metabolism	GSTAL2, IDH1, HPGDS, GSTT1, GCLC
gga03320	PPAR signaling pathway	ACOX2, FADS2, FABP7, ACAA1, ACSBG2, FABP1
gga00980	Metabolism of xenobiotics by cytochrome P450	UGT2A1, GSTAL2, HPGDS, GSTT1,
gga00100	Steroid biosynthesis	LSS, NSDHL, DHCR24, DHCR7
gga00983	Drug metabolism - other enzymes	UGT2A1, GSTAL2, GSTT1, NAT
gga00140	Steroid hormone biosynthesis	UGT2A1, AKR1D1, CYP2D6, CYP3A4
gga04146	Peroxisome	RCJMB04_1j22, IDH1,ACOX2,ACAA1, NUDT12

Validation of Differentially Expressed Genes Using qRT-PCR

As shown in Table 2, the qPCR results of UGT2A1, GASTAL2, HPGDS, GSTT1, IDH1, ACOX2, FABP1, ADSL, and PAICS genes screened from the transcriptome are consistent with the RNA-seq results and the content of TMT protein (Table 4, Figure 8A). At the same time, we detected the expression of UGT2A1 and GSTT1 mRNA and ACOX2 and FABP1 mRNA related to lipid metabolism, and found that at the age of d 5, 21 and 42, compared with the control group, FFC significantly increased the transcription level of UGT2A1, GSTT1 and ACOX2 mRNA (P < 0.05); The transcription level of FABP1 mRNA was significantly inhibited (P < 0.05) (Figure 8B).

Table 4

Correlated protein and mRNA pair expression comparisons.

			Log2 (fold change)
Protein ID	Protein name	Gene name	Protein	gene
F1NMB3	UDP-glucuronosyltransferase	UGT2A1	1.158	1.898
A0A0A0MQ61	Uncharacterized protein	GSTAL2	1.566	4.047
O73888	Hematopoietic prostaglandin D synthase	HPGDS	1.232	3.851
P20135	Glutathione S-transferase theta-1	GSTT1	0.785	1.471
F1NPG2	Isocitrate dehydrogenase [NADP]	IDH1	0.568	1.780
E1C5V6	Acyl-coenzyme A oxidase	ACOX2	0.694	1.693
Q90WA9	Fatty acid-binding protein	FABP1	-0.919	-2.148
P21265	Adenylosuccinate lyase	ADSL	0.326	1.739
P38024	Multifunctional protein ADE2	AIRC	0.381	1.740

Figure 8

(A) The mRNA transcription level of the selected key genes in the liver tissue of 5-d-old broilers, (B) the mRNA transcription level of UGT2A1, GSTT1, ACOX2 and FABP1 in the liver tissue of different d-old broilers. *P < 0.05, compared with the control group.

DISCUSSION

Our previous study found that: the normal recommended treatment dose (0.15g/L) of FFC has certain damage effect on growth performance, hematopoietic function and liver function of broilers within 7 dd of age. In this study, we further explored the toxic side effects of FFC on 21 d old broilers and 42 d old broilers, the result showed that at age of d 21 and 42, the normal recommended dose (0.15g/L) and higher dose of FFC still significantly inhibited the weight gain of broilers (P < 0.05). The results show that during the whole growing period the inhibitory effect of FFC on the growth and development of broilers was always existed. In addition, the results showed that FFC still caused liver damage at age d 21, However, effects of FFC induce broilers liver injure were alleviated when the age of d 42.

In order to further explore the mechanism of FFC on liver injury in broilers, we used transcriptome and proteomics to analyze the key targets of FFC on liver injury in broilers, in order to reveal the mechanism of action of FFC on liver toxicity. The results showed that FFC could induce drug metabolism - cytochrome P450, glutamate metabolism, PPAR signaling pathway, metabolism of xenobiotics by cytochrome P450, steroid biosynthesis, drug metabolism - other enzymes, steroid hormone biosynthesis, peroxisome and other pathways have different expression of related proteins, indicating that FFC can affect the normal liver function of Broilers by causing abnormal expression of these genes or proteins.

The most common causes of Drug-induce liver injury (DILI) in broilers are antibiotics, aflatoxins, heavy metals, etc. most of their metabolites have hepatotoxic (Leise et al., 2014). There are 2 steps of drug reaction in liver, that is, phase I and phase II (Hellriegel et al., 1996). Phase I reaction: the drug is hydrolyzed, oxidized and reduced to produce metabolites. The main metabolic enzymes are cytochrome P450 (CYP), CYP1A1 and CYP2H1, which are key enzymes related to drug-induced liver injury (Dohnal et al., 2014). Therefore, the content of liver drug enzymes in hepatocytes is directly related to the detoxification ability of liver. Our results showed that the contents of CYP1A1 and CYP2H1 in the liver of d21-d-old broilers fed with FFC decreased significantly, and showed a certain dose dependence. It is suggested that FFC can increase the concentration of FFC in the liver and cause liver damage by inhibiting the activity of liver drug enzymes. Glutathione S-transferase (GSTs) is a group of enzymes related to the detoxification function of liver (Sun et al., 2012). Its glutathione and free radicals combine to promote the elimination of toxic substances from the body and reduce the potential toxicity of drugs. GSTs dysfunction will lead to the occurrence of DILI (Roy et al., 2008). Glutathione S-transferase (GST) is one of the important metabolizing enzymes. GST has high concentration in the solute of hepatocytes. It can reduce toxicity and promote urine excretion by catalyzing the combination of glutathione (GSH) and active metabolites in the liver. When the liver is seriously damaged, GST and GSH will be released from the liver cytoplasm into the plasma, resulting in the decrease of GST activity in the liver cytoplasm (Zhang et al., 2017). Therefore, the gene regulation of GST plays a decisive role in the metabolism of GSH. The monitoring of GST activity in liver tissue may be a potential strategy for the diagnosis of DILI (Tian et al., 2019). Our study found that FFC can significantly improve the expression of GSTT1 mRNA and protein, which indicates that FFC can accelerate the metabolism of drugs in the liver, cause a large number of drug metabolites in the liver, and then damage the liver function. In addition, UDP-glucuronosyl transferase (UGT), as another important transferase in phase II reaction, is a large family of enzymes that can catalyze the combination of glucuronic acid and nucleophilic substrate (Alkharfy et al., 2017). It mainly exists in the liver and combines with the microparticle membrane to catalyze the glucuronide combination reaction in phase II reaction of liver biotransformation. Several studies have shown that genes UGT1A9 and UGT147 are significantly correlated with DILI (Jiang et al., 2015; Stickel, 2015; Terelius, et al., 2016). In this study, FFC significantly promoted the expression of ugt2a1, indicating that FFC can affect the phase II response of drug metabolism in liver through ugt2a1, and then affect the function of liver. In addition, a large number of metabolites will be produced due to the excessive metabolism of drugs in the liver. The accumulation of these metabolites may affect the secretion of bile and cause cholestasis. The accumulation of bile acids may cause indirect damage to liver cells and bile duct cells (Zollner and Trauner, 2006).

Peroxisome proliferator-activated receptors (PPARs), as one of the important nuclear transcription factors involved in the regulation of lipid metabolism in vivo, can be activated by binding with ligands, regulate the oxidation of fatty acids, increase insulin sensitivity of the body, regulate the storage of triacylglycerol in adipose tissue(Silva and Peixoto, 2018; Goto, 2019), which is highly expressed in liver, skeletal muscle, heart muscle, renal cortex and other tissues with strong energy metabolism, and regulate glucose and lipid metabolism, energy balance, inhibit inflammation and anti-inflammation It should be closely related(Liao et al., 2017; Liss and Finck, 2017; Li and Liu, 2018). In this study, we found that 6 proteins and their corresponding mRNA expressed differentially enriched in PPAR signaling pathway, they are acyl-coenzyme A oxidase-2 (ACOX2), delta-6 fatty acid destination (FADS2), fatty acid binding protein 7 (FABP7), acyl CoA acyltransferase 1 (ACAA1), long chain fatty acid – CoA ligase acsbg2 (ACSBG2), fatty acid binding Protein 1 (FABP1) and so on indicate that FFC can damage the normal function of liver by affecting the metabolism of lipid in liver. FABP1 is located downstream of PPAR α in PPAR α signaling pathway, which is closely related to fatty acid transport. Studies have shown that FABP1 plays an important role in free fatty acid transport and metabolism of liver cells (Yi et al., 2016). A research has showed that overexpression of chicken FABP gene can induce high lipolysis rate and decrease abdominal fat content (Shi et al., 2010). The results of this study showed that FFC could significantly reduce the expression of FABP1 gene mRNA in the liver of broilers. This may be because the liver of broilers was damaged after exposure to FFC, breaking the normal expression of FABP1, causing oxidative stress in the liver, and further aggravating the liver damage. In addition, PPARs can regulate the transcription of a variety of target genes (such as ACAA1 and ACOX2) that have peroxisome proliferative response elements in the promoter region (Hariya et al., 2015), these genes encode key enzymes or proteins involved in lipid metabolism (Osumi and Hashimoto, 1978; Wanders et al., 2001), abnormal expression of these genes can interfere with the synthesis of fat in the liver, and then mediate liver damage. Our results show that florfenicol can significantly increase the expression of ACOX2 mRNA and protein, and then affect the synthesis of fatty acids in the liver. In conclusion, FFC can affect the synthesis and metabolism of lipids in liver, and then damage the function of liver.

CONCLUSION

Feeding young broilers with FFC can inhibit the weight gain and damage the liver function during the whole growth cycle. The mechanism of FFC induced broilers liver injury were that: on the one hand, FFC disrupts the expression of UGT2A1, GSTT1 and their regulated proteins, thus affecting the drug metabolism ability of broiler liver, causing drugs to accumulate in the liver and further damage the liver function; on the other hand, FFC damages broilers by affecting the expression of acox2, FABP1 and other genes and their regulated proteins, and then affecting the lipid metabolism of broiler liver.

Acknowledgments

This study was financially supported by Subsidized Project for Cultivating Innovative Ability of Postgraduates of Hebei province (no. CXZZBS2019096) Hebei Province Innovation Capacity Promotion Project-Hebei Veterinary Biotechnology Innovation Center Open Project (no. 20567668H), Precision Animal Husbandry Discipline Group Construction Project of Hebei Agricultural University (1090064).

DISCLOSURES

The authors have no conflicts of interest.