Screening of differentially expressed immune-related genes from spleen of broilers fed with probiotic Bacillus cereus PAS38 based on suppression subtractive hybridization.

The aim of this study was to construct the spleen differential genes library of broilers fed with probiotic Bacillus cereus PAS38 by suppression subtractive hybridization (SSH) and screen the immune-related genes. Sixty seven-day-old broilers were randomly divided into two groups. The control group was fed with basal diet, and the treated group was fed with basal diet containing Bacillus cereus PAS38 1×106 CFU/g. Spleen tissues were taken and extracted its total RNA at 42 days old, then SSH was used to construct differential gene library and screen immune-related genes. A total of 119 differentially expressed sequence tags (ESTs) were isolated by SSH and 9 immune-related genes were screened out by Gene ontology analysis. Nine differentially expressed genes were identified by qRT-PCR. JCHAIN, FTH1, P2RX7, TLR7, IGF1R, SMAD7, and SLC7A6 were found to be significantly up-regulated in the treated group. Which was consistent with the results of SSH. These findings imply that probiotic Bacillus cereus PAS38-induced differentially expressed genes in spleen might play an important role in the improvement of immunity for broilers, which provided useful information for further understanding of the molecular mechanism of probiotics responsible to affect the poultry immunity.

Introduction

Bacillus spp. is a common probiotic and widely used in poultry industry [1]. A large number of studies have shown that Bacillus could promote the development of immune organs and activate immune-related signaling pathways serving as an immune activator, thereby stimulating the specific and non-specific immunity of the host and improving the immune ability of animals [2-4]. The research on the mechanism of Bacillus immune action, especially the molecular mechanism, is a hot spot at present. Previous papers showed that Bacillus subtilis improved the animal immunity by increasing the expression of cytokine genes such as IL-2, IL-4, IL-10 and TNF-α in cecum and ileum mucosa of broilers [5]. And it was found that Bacillus subtilis could promote the expression of tight junction protein JAM-2, mucin, ZO-1 and other zonula occludens genes in intestinal mucosa of broilers [6]. These results preliminarily explained the work mechanism of probiotics from the perspective of intestinal mucosal immunity.

Bacillus cereus is a common soil bacterium. Some of its strains have been proved to be probiotics and have been developed as probiotics and applied to animal husbandry and veterinary fields [7]. Zhao et al. added 107 CFU/g Bacillus cereus EN25 to the diet of sea cucumber, and found that it could significantly improve the immune function of sea cucumber and reduce the cumulative mortality rate after Vibrio splenovirus infection [8]. Scharek et al. added Bacillus cereus var. toyoi to the feed of sows and piglets, it was found that both jejunal epithelium and Peyer’s patch CD8 + T cells and γδ T cells increased significantly, and the frequency of pathogenic Escherichia coli in piglet feces of probiotic group was also lower, which indicates that it was beneficial to the health of piglets [9]. Pan et al. found that adding 0.1% Bacillus cereus PAS38 to the basic diet of weanling male rabbits could reduce the number of somatostatin (SS) positive cells and the expression intensity of SS cells in the small intestine of rabbits, increase the number of 5-hydroxytryptamine (5-HT) immunoreactive cells in the small intestine and increase the expression intensity of 5-HT cells, and the combination of Bacillus cereus PAS38 and β-mannanase is more effective [10]. These studies indicate that some beneficial strains of Bacillus cereus have great potential in improving animal immunity.

SSH is a technique for constructing differential gene library, and it has many advantages, such as high sensitivity, rapidity, simplicity, low false positive rate and enrichment of rare transcripts [11]. Therefore, it is widely used in screening of differentially expressed genes in animals [12]. SSH library had been used to analyze the different hair phenotype (curly and non-curly) of Chinese Tan sheep at different growth stages [13], 67 differentially expressed genes were found, and further study confirmed that KRT71 gene was highly correlated with the curly hair phenotype of Tan sheep. In the study of the molecular mechanism of ovarian development in Yellow River carp [14], 78 differentially expressed genes were obtained by comparing the second stage ovaries and mature ovaries of Yellow River carp with SSH. Furthermore, it was found that 78 differentially expressed genes were mainly involved in signal transduction, protein hydrolysis, cell differentiation, TGF-β signaling pathway and other biological reactions. In addition, it was also confirmed that BMP2B, DESMIN and FP1 genes might be the biomarkers for early ovarian development.

Previous studies on the improvement of animal immunity by probiotic Bacillus mainly focused on its effects on the development of immune organs and the expression of serum cytokines. The screening of differentially expressed genes related to immunity in spleen tissue transcriptome after feeding broilers with probiotic Bacillus cereus has not been reported. Thus, it is necessary to carry out relevant experiments to further study the work mechanism of probiotics.

In this experiment, broilers were fed with Bacillus cereus PAS38, spleens were collected and total RNA was extracted at 42 days old. Then differential expression genes library was constructed by SSH, and differential expression immune-related genes were screened. Absolute qRT-PCR was used to verify the differential genes, in order to explore the key genes regulating immunity of Bacillus cereus PAS38, and lay a foundation for wide application in broilers production.

Materials and methods

Ethics statement

All animal experiments were performed in accordance with the guidelines for the care and use of laboratory animals and approved by the Institutional Animal Care and Use Committee of Sichuan Agricultural University (approval number: DYS20174513-1).

Laboratory animals and strains

Sixty one-day-old avian white feather broilers were purchased from Sichuan Zhengda Animal and Poultry Co., Ltd. Bacillus cereus PAS38 strain was provided by Animal Microecology Institute of Sichuan Agricultural University. Bacillus cereus PAS38 preparation was obtained by solid fermentation (S1 Table) at 37°C for 48 h, collecting spores, drying at 65°C for 2 h and grinding. The number of viable spores was counted by plate dilution coating method and the number of viable spores was adjusted to 109 CFU/g by adding corn flour.

Reagents and instruments

The reagents used in this experiment mainly included RNAiso Plus (Takara, JPN), Smarter™ PCR cDNA Synthesis Kit (Takara, JPN), Advantage 2 PCR Kit (Takara, JPN), PCR Select™ cDNA Subtraction Kit (Takara, JPN), pUCm T vector (Sangon Biotech, CHN), DH5α Chemically Competent Cell (Beijing TsingKe, CHN), and iTaq Universl SYBR Green supermix (Bio-Rad, USA). The main instruments used were Microvolume Spectrophotometers Nano Drop 2000 (Thermo, USA), Real-time PCR thermal cycle instrument Bio Rad CFX 96 (Bio-Rad, USA), Thermostatic water bath oscillators SHZ A (Shanghai Boxun, CHN), Constant temperature incubator DHP 9080B (Shanghai Langgan, CHN), Gel imaging system Gel Doc™ XR+ (Bio-Rad, USA), High speed freezing centrifuge Micro 21R (Thermo, USA), PCR instrument ABI Veriti 96 Well (Thermo, USA), and Horizontal Electrophoresis System Mini Sub cell GT (Bio-Rad, USA).

Experimental design

Sixty one-day-old avian white feather broilers were pre-fed with basic diet for 7 days to stabilize the metabolic conditions. The broilers were randomly divided into control group and treated group, each group consisted of three replicates with 10 chickens per replicate. The control group was fed the basal diet (Table 1). The treated group was fed the basal diet supplemented with 0.1% Bacillus cereus PAS38 preparation, and including Bacillus cereus 1 × 106 CFU per gram of feed. The experimental chickens were raised in single-layer cage with ten broilers in each cage. Each cage is equipped with two food troughs and one water trough. The control group and the treated group were fed to two animal houses respectively to avoid spore interference. Broiler chickens were fed the diet and water ad libitum. The chicken house was cleaned every morning and evening, and the air circulation in the chicken house was maintained. The insulation lamp was used to keep the temperature in the room at about 25°C. At the age of 42 days, two broilers were randomly selected from each repeat of each group, that was, six broilers in each group were executed and the spleens were taken and immediately stored in liquid nitrogen.

Table 1

Raw material composition and nutritional level of basic dietary (air-dry basis).

Ingredients(%)			Nutrition levels
	1d-21d	22d-42d		1d-21d	22d-42d
Corn	61.20	65.20	Metabolizable energy (MJ/kg)	12.54	12.80
Soybean meal	23.00	18.00	Crude protein	20.70	19.00
Extruded soybean	8.50	10.00	Lysine	1.12	0.96
Import fish meal	3.00	3.00	Methionine	0.53	0.43
CaHPO4	1.60	1.40	Calcium	0.99	0.89
Limestone	1.10	1.00	Available phosphorus	0.51	0.46
NaCl	0.32	0.30
DL- methionine	0.18	0.10
L- lysine	0.10
Premix	1.00	1.00
Total	100.00	100.00

Premix is provided for feed per kg: VD3 200 IU, VA 1500 IU, VE 10 IU, VK 0.5 mg, VB12 0.01 mg, VB6 3.0 mg, VB1 1.5 mg, Nicotinic acid 30 mg, D-pantothenic acid 10 mg, Folic acid 0.5 mg, Biotin 0.15 mg, Trace elements Cu, Fe, Zn, Mn, Se, I are 8 mg, 80 mg, 40 mg, 60 mg, 0.15 mg, 0.18 mg respectively. Metabolic energy was calculated and the rest was measured.

RNA extraction and construction of cDNA libraries

Spleen tissues were ground rapidly in liquid nitrogen. Total RNA was extracted by RNAiso Plus reagent and dissolved in RNase-free deionized water. And six tubes of total RNA in each group were merged into one tube. The purity and concentration of the RNA were determined by Nucleic acid analyzer NanoDrop 2000. Then the single-stranded cDNA was synthesized immediately by Smarter PCR cDNA Synthesis Kit (Clontech, USA). The synthetic system was as follows: 1.0μg total RNA, 1.0μL Smarter 3’-CDS Primer II A, 1.5μL RNase-free deionized water, 4.5μL total volume. The mixtures were incubated at 72°C for 3 min, and then incubated at 42°C for 2 min. Next, added 2.0μL 5×First-Strand buffer, 0.25μL DTT, 1.0μL dNTP mix, 0.25μL RNase inhibitor, 1μL Smarter II A oligo, 1.0μL Smart scribe reverse transcriptase to the mixtures, and they were incubated at 42°C for 1.5 h. The synthesized single-stranded cDNA was diluted 5-fold with TE buffer, and then stored at—20°C refrigerator.

Advantage 2 PCR Kit (Clontech, USA) was used for the synthesis of double-stranded cDNA. The reaction system was as follows: the 1.5μL single-stranded cDNA was added with 8.5μL deionized water to the total volume of 10μL, and added 10μL 10×Advantage 2 PCR buffer, 2μL 50×dNTP mix, 2μL 5'-PCR Primer II A, 2μL 50×Advantage 2 Polymerase mix, 74μL deionized water. The mixtures were pre-denaturated at 95°C for 1 min, denaturated at 95°C for 15 s, annealed at 65°C for 30 s, extended at 68°C for 6 min, totally 30 cycles. From the 18th cycle to the 30th cycle, the 5μL mixture was taken every three cycles for 1.2% agarose gel electrophoresis to select the optimal cycle number for constructing the cDNA libraries.

Construction of SSH libraries

The double-stranded cDNA with the optimal cycle number was taken and digested with Rsa I enzyme at 37°C for 3 hours. Then the forward and reverse SSH differential gene libraries were constructed by Smarter PCR cDNA Synthesis Kit (Clontech, USA). In the forward library, the spleen cDNA of broilers in the treated group was used as tester, and the spleen cDNA of broilers in the control group was used as driver for hybridization. On the contrary, in the reverse library, the spleen cDNA of broilers in the control group was used as tester, and the spleen cDNA of broilers in the treated group was used as driver for hybridization.

The first hybridization mixtures were incubated at 98°C for 1.5 min and then at 68°C for 10 h. Then the driver cDNA was immediately added to the mixtures, and they were incubated at 68°C for 10 h. After the two rounds of hybridization reaction, the hybridization products were diluted with 200μL dilution buffer. Then the first nested PCR was performed using PCR Primer 1 (primer sequence: 5'-CTAATACGACTCACTATAGGC-3') as primer. The reaction system was as follows: 1μL hybridization products, 1μL PCR Primer 1, 0.5μL 50×dNTP mix, 0.5μL 50×Advantage cDNA Polymerase mix, 2.5μL 10×Advantage 2 PCR buffer, 19.5μL deionized water. The mixtures were incubated at 75°C for 5 min, pre-denaturated at 94°C for 30 s, denaturated at 94°C for 30 s, annealed at 66°C for 30 s, extended at 72°C for 2 min, totally 27 cycles.

The first Nested PCR products were diluted 10-fold with deionized water for the second Nested PCR. The reaction system was as follows: 1μL first Nested PCR products, 1μL Nested PCR primer 1 (primer sequence: 5'-TCGAGCGGCCGCCCGGGCAGGT-3'), 1μL Nested PCR primer 2R (primer sequence: 5'-AGCGTGGTCGCGGCCGAGGT-3'), 0.5μL 50×dNTP mix, 0.5μL 50×Advantage cDNA Polymerase mix,2.5μL 10×Advantage 2 PCR buffer, 18.5μL deionized water. The mixtures were pre-denaturated at 94°C for 30 s, denaturated at 94°C for 30 s, annealed at 68°C for 30 s, extended at 72°C for 2 min, 12 cycles, fully extended at 72°C for 10 min.

After two rounds of hybridization and nested PCR amplification, the purified forward and reverse PCR products were linked to pUCm-T clone vector and then transformed into DH5α competent cells. After transformation, positive transformants were screened by ampicillin antibiotics and blue-white spot assay. 400 white clones were randomly selected from the forward and reverse libraries, the size of the insert fragment and the uniqueness of the band were detected by bacteria liquid PCR. The reaction system of bacteria liquid PCR was as follows: 1μL bacterial fluid, 0.5μL Nested PCR primer 1, 0.5μL Nested PCR primer 2R, 5μL 2×TsingKe master mix, 3μL deionized water. The mixtures were pre-denaturated at 95°C for 1 min, denaturated at 95°C for 30 s, annealed at 60°C for 30 s, extended at 72°C for 30 s, 30 cycles, fully extended at 72°C for 10 min.

Sequencing and sequence analysis

After the positive clones were amplified in liquid medium, the sequencing reactions were entrusted to Beijing TsingKe Biological Technology Co., Ltd. The sequencing results were compared by the BLAST function of the National Center for Biotechnology Information (NCBI; http://www.ncbi.nlm.nih.gov). We counted valid ESTs and got forward and reverse SSH gene libraries after removing redundant sequences, vector sequences and sequences that were unmatched. The SSH libraries were analyzed by GO annotation through Blast2Go software version 5.2, and the immune-related genes were screened.

Verification of differentially expressed genes by qRT-PCR

The immune-related differential genes of the SSH libraries were selected, and we designed a fluorescent quantitative primer for them by the online primer design tool Primer Quest Tool (https://sg.idtdna.com). Plasmid standards of differentially expressed genes were prepared using plasmid pUCm-T. Then the copies of the plasmid standards were calculated, and they were diluted 10-fold to 7 gradients with deionized water. Bio-Rad CFX 96 was used to make the standard curve. At the same time, the differential genes were detected by absolute qPCR using single-stranded cDNA diluted 10-fold as template. β-actin was used as a reference gene to consider the variation of total input cDNA. The reaction system was as follows: 1μL diluted single-stranded cDNA, 10μL SYBR Green supermix, 1μL forward primer, 1μL reverse primer, supplemented with RNase-free water to 20μL. Each reaction was repeated three times. The mixtures were pre-denaturated at 94°C for 3 min, denaturated at 94°C for 5 s, annealed at suitable annealing temperature for 30 s, extended at 72°C for 15 s, 40 cycles. Bio-Rad CFX Manager 3.1 software was used to analyze the qPCR results, the number of copies of differential genes was calculated by standard curve. The qPCR primer sequences and optimal annealing temperature of the differential genes are shown in Table 2.

Table 2

qPCR primer design of immune-related differentially expressed genes.

Gene	Forward primer	Reverse primer	Annealing temperature (°C)	Product length (bp)
JCHAIN	5'-GGTTCGTCCTTGT GGCAGGTTATC-3'	5'-GAGGTCACCGTTA CGCACTTACAC-3'	58	88
FTH1	5'-ATGTGACCAACCT GCGGAAGATG-3'	5'-TGCATTGCTGGACC AGTGAAGTAG-3'	60	156
P2RX7	5'-AGTTCGCGTTAC CCTGAAAG-3'	5'-TCTCTTGTCTGCGT TGGTATG-3'	59	84
SLC7A6	5'-GTCTTTGGAGCT CTCTGCTATG-3'	5'-AGTGAGGTCCACA AACGAATAA-3'	58	122
TLR7	5'-ACCGTCGCCTCAA GGAAGTCC-3'	5'-ACGCAGTTGCACC TGAAGTCAATC-3'	57	145
IGF1R	5'-GGACACAGAGGA GCTTGACC-3'	5'-TGTCAGTGGGTTG GAGGGTA-3'	58	83
SMAD7	5'-CTGGTGCGTGGTG GCATACTG-3'	5'-CTGGCTTCTGTTGT CCGAGTTGAG-3'	58	145
ITGA4	5'-ACAGAAGAAGGC AGGTGAATAG-3'	5'-GGCAGAACACAGA GTATGTAGG-3'	59	124
DOCK10	5'-GGCCACAGCTCAG ATGAAGGAAC-3'	5'-TGAGAGCAGCGAT GTGAATGTAGC-3'	60	191
β-actin	5'-TGCTGTGTTCCCA TCTATCG-3'	5'-TTGGTGACAATAC CGTGTTCA-3'	58	150

Statistical analysis

All the experimental data were analyzed by one-way ANOVA with SPSS 23.0 software and Duncan’s method was used for multiple comparisons, with P < 0.05 as the statistically significant, P < 0.01 as the highly statistically significant.

Results

Construction of cDNA libraries

The results of 1.2% agarose gel electrophoresis of double-stranded cDNA products under different cycles is shown in Fig 1A and 1B (S1 Fig, S1 Raw images). Treated group have the brightest bands and the widest range in 24 cycles. Control group have the brightest bands in 27 cycles, but the widest range in 24 cycles. As can be seen from the figure, the optimal cycles for both treated group and control group was 24.

Fig 1

Agarose electrophoresis analysis of optimal cycles of double-stranded cDNA.

Electrophoresis with agarose of 1.2% concentration. The images were generated by the Gel imaging system Gel Doc™ XR+. (A) Treated group. (B) Control group. M represents DNA Marker 2000. The numbers 1, 2, 3, 4 and 5 represent 18, 21, 24, 27 and 30 PCR cycles respectively.

200 white clones were randomly selected from the forward and reverse libraries respectively. Partial result of bacteria liquid PCR is presented in Fig 2A and 2B (S2 Fig, S2 Raw images), most of them are positive clones, and the size of the bands is concentrated at 200 bp to 1000 bp, which conforms to the enzyme digestion effect and meets the requirements of the suppression subtractive hybridization libraries.

Fig 2

Detection of inserted fragments by bacteria liquid PCR.

Electrophoresis with agarose of 1.2% concentration. The images were generated by the Gel imaging system Gel Doc™ XR+. (A) Treated group. (B) Control group. M represents DNA Marker 2000. The numbers 1, 2, 3, et al. represent different bacterial clones.

In the forward and reverse libraries, 129 and 155 positive clones were successfully sequenced, respectively. Excluding the low-quality sequences, the unmatched sequences, the repeat sequences, and the unannotated protein sequences, 63 and 56 valid ESTs were obtained, respectively (S2 Table), respectively. These EST sequences were submitted to NCBI’s dbEST database with the GenBank accession numbers JZ980559-JZ980677.

After clustering analysis of Gene ontology on Level 2, data showed that in the forward subtracted cDNA library, within the biological process (GO:0008150) category, 63 ESTs were classified into 14 categories, comprising: cellular process (15%), metabolic process (12%), biological regulation (10%), regulation of biological process (10%), response to stimulus (9%), signaling (8%), and multicellular organismal process (6%), localization (6%), cellular component organization or biogenesis (6%), developmental process (6%), etc. (Fig 3A). Within the cellular component (GO:0005575) category, they were classified into 8 categories, comprising: cells (23%), cell part (22%), organelle (13%), membrane (12%), organelle part (9%), membrane part (9%), protein-containing complex (9%) etc. (Fig 3B). Within the molecular function (GO:0003674) category, they were classified into 5 categories, comprising: binding (54%), catalytic activity (22%), molecular transducer activity (10%), transcription regulator activity (7%) and transporter activity (6%) (Fig 3C). In the reverse subtracted cDNA library, within the biological process category, 56 ESTs were classified into 20 categories, comprising: cellular process (15%), metabolic process (13%), biological regulation (10%), regulation of biological process (10%), response to stimulus (7%), developmental process (6%), positive regulation of biological process (5%) and localization (5%) etc. (Fig 4A). Regarding the cellular component category, they were classified into 10 categories, including cells (21%), cell part (20%), organelle (18%), protein-containing complex (11%), organelle part (10%), membrane-enclosed lumen (9%) and membrane (5%) etc. (Fig 4B). In the molecular function category, they were classified into 3 categories, including binding (63%), catalytic activity (29%) and transcription regulator activity (8%) (Fig 4C).

Fig 3

Functional classification of genes in forward library.

(A) Classification of biological processes level. (B) Classification of cell component level. (C) Classification of molecular function level.

Fig 4

Functional classification of genes in reverse library.

(A) Classification of biological processes level. (B) Classification of cell component level. (C) Classification of molecular function level.

Through GO cluster analysis, immune-related genes were screened including joining chain of multimeric IgA and IgM (JCHAIN), ferritin heavy chain 1 (FTH1), purinergic receptor P2X7 (P2RX7), solute carrier family 7 member 6 (SLC7A6), toll like receptor 7 (TLR7), insulin like growth factor 1 receptor (IGF1R), SMAD family member 7 (SMAD7), integrin subunit alpha 4 (ITGA4) and dedicator of cytokinesis 10 (DOCK10) (Table 3).

Table 3

Differentially expressed genes related to immunity screened by SSH.

(Treated group vs Control group).

Gene	Accession number	Up / Down regulation
Joining chain of multimeric IgA and IgM (JCHAIN)	NM_204263.1	up
Ferritin heavy chain 1 (FTH1)	NM_205086.1	up
Purinergic receptor P2X 7 (P2RX7)	XM_001235162.5	up
Solute carrier family 7 member 6 (SLC7A6)	XM_025154295.1	up
Toll like receptor 7 (TLR7)	NM_001011688.2	up
Insulin like growth factor 1 receptor (IGF1R)	NM_205032.1	up
SMAD family member 7 (SMAD7)	XM_004949014.3	up
Integrin subunit alpha 4 (ITGA4)	XM_421974.6	down
Dedicator of cytokinesis 10 (DOCK10)	XM_015277026.2	down

Absolute qPCR was used to detect the expression levels of nine immune-related differentially expressed genes in spleen tissues. According to the standard curve of qPCR of different genes, the copies of the genes were calculated (S3–S12 Figs). The results showed that the expression level of the reference gene β-actin was almost the same (P>0.05) in the treated group and control group, and the copies of seven up-regulated genes in the treated group were obviously higher than that in the control group, the copies of the two down-regulated genes in the treated group were less than that in the control group. Among them, the expression levels of JCHAIN, FTH1, P2RX7, TLR7, IGF1R, SMAD7 in the treated group were highly significantly (P<0.01) higher than those in the control group, and SLC7A6 was significantly (P<0.05) higher than that in the control group. Meanwhile, the expression levels of DOCK10 in the treated group was highly significantly (P<0.01) lesser than that in the control group, and ITGA4 was significantly (P<0.05) lesser than that in the control group (Fig 5, S13 Fig). These results were consistent with those of SSH.

Fig 5

Detection of differentially expressed genes by absolute qPCR.

Experimental data were analyzed by one-way ANOVA with SPSS 23.0 software and Duncan’s method was used for multiple comparisons * P<0.05, ** P<0.01.

Discussion

In the field of veterinary medicine, SSH has been used to screen the differentially expressed genes related to animal immunity in recent years. Gao et al. [15] studied the immune mechanism of silkworm against Bombyxmori nuclear polyhedrosis virus (BmNPV), the differentially expressed gene libraries of resistant strains and susceptible strains were constructed by SSH technique, and they found that 17 genes were up-regulated in resistant strain BC10, which involved in cell metabolism, transmembrane transport, cytoskeleton, protease, development and immunity, and these genes may be related to resistance to BmNPV in silkworm. In order to study the effect of highly pathogenic porcine reproductive and respiratory syndrome virus (HP-PRRSV) infection on the response of pig cells, SSH was used to compare cDNA libraries of porcine alveolar macrophages (PAM) infected with HP-PRRSV and uninfected HP-PRRSV, and results showed that 21 genes including IL-16, TGF-β type 1 receptor, epidermal growth factor, MHC-I SLA, toll-like receptor, hepatoma-derived growth factor, FTH1, and MHC-II SLA-DRB1 were up-regulated in PAM infected with HP-PRRSV, by the way, this research demonstrated differential gene expression between HP-PRRSV-infected and uninfected PAMs in vivo for the first time [16].

In present study, 284 positive clones of SSH libraries were sequenced successfully and 119 valid ESTs were obtained by eliminating duplication. Among them, 63 ESTs belong to forward library and 56 ESTs belong to reverse library. Through GO cluster analysis and qPCR identification, 9 immune-related differentially expressed genes were screened out, including JCHAIN, FTH1, P2RX7, SLC7A6, TLR7, IGF1R, SMAD7, ITGA4, DOCK10. Seven of the nine genes were up-regulated and two genes were down-regulated in the broilers fed probiotic Bacillus cereus PAS38.

JCHAIN is a glycoprotein about 15 kDa in size, it can initiate the polymerization process by linking with IgM or IgA caudal cysteine and covalently bind to poly IgM or IgA stably by disulfide bond. It plays an important role in the secretion, transportation of immunoglobulin and the activation of complement [17, 18]. JCHAIN has highly conserved structural characteristics in various vertebrates and invertebrates. Study has found that the amino acid composition of JCHAIN in chickens and humans is highly similar [19]. Takahashi et al. used Northern blot hybridization to study the expression level of JCHAIN in brain, intestine, thymus, spleen, bursa of fabricius and other tissues and organs of adult chickens. It was found that the expression level of JCHAIN in spleen and rectum was relatively high, but in thymus was relatively low [20]. Previous studies have shown that after lactating women ingested daily viable Lactobacillus bulgaricus for 28 days [21], probiotics activate the lymphocytes and synthesize IgA dimers with J-chain, which increased SIgA content in both breast milk and feces obviously. In present study, JCHAIN expression in the spleen of broilers was highly significantly increased after feeding Bacillus cereus PAS38, which may play an important role in the expression of downstream cytokines, thus affecting the immunity of broilers.

The expression of FTH1 in the spleen of broilers was also highly significantly increased after feeding Bacillus cereus PAS38 in this experiment. FTH1 is approximately 21kDa in size and is the major functional subunit of ferritin. It contains a Fe2+ oxidation center responsible for the oxidation and integration of iron ions to maintain balance of iron ions in the body [22, 23]. Previous studies had found that FTH1 was expressed differently in different breeds of chickens. Willson et al. found that the expression of FTH1 in laying hen strain was higher than that in broiler strain when they studied the difference in liver transcriptome between broilers and layers [24]. At the same time, Yang et al. studied the difference in ovarian transcriptome between low-yielding laying hens and high-yielding laying hens, and found that the expression of FTH1 in high-yielding laying hens was lower than that in low-yielding laying hens [25]. Which suggested that proper expression of FTH1 may play an important role in laying mechanism of chickens. FTH1 is not only related to laying traits of chickens, but also to immune defense. Matulova et al. infected chickens with Salmonella enteritidis, found that FTH1 in the spleen of chickens was significantly up-regulated [26]. On the contrary, Niroshan et al. infected chickens with Marek’s disease virus, found that FTH1 protein in the spleen of chickens was down-regulated [27]. These distinct results suggest that chickens may have different defense mechanisms against bacterial and viral infections. Zhang et al. [28] found that the expression of FTH1 in liver and spleen of Jingding duck was significantly down-regulated after infection with duck hepatitis virus 1, and the expression of antiviral marker gene MX1 was significantly up-regulated in DF-1 cells transfected with the FTH1 plasmid. Sun et al. [29] showed that after FTH1 silencing, the intracellular viability of Brucella decreased, and the apoptotic rate of macrophages increased. These studies suggest that FTH1 can play a role in resisting inflammation in the process of virus and bacteria invading the organism.

Purinergic receptor P2X7 is an important member of purine receptor family. P2RX7 is mainly involved in cell signal transduction, cytokine secretion, cell proliferation and apoptosis [30]. P2RX7 plays an important role in bone metabolism pathway [31]. Zhang et al. added 10 mg/kg icariin to drinking water of broilers with tibial cartilage dysplasia, and found that the expression of P2RX7 increased significantly, and the mortality and lameness rate of broilers were also reduced [32]. Meanwhile, it is also involved in the immune response by mediating the NF-κB pathway and the NALP3 inflammatory pathway [33]. Ren et al. [34] conducted transcriptome analysis on the liver of chickens infected with avian adenovirus type 4, and the results showed that P2RX7 was up-regulated after 21 days of infection. Similarly, Kalenik et al. [35] showed that P2RX7 in spleen was significantly up-regulated after inoculation of chickens with three H5N1 subunit vaccines. According to the results of absolute qPCR, the P2RX7 was highly significantly up-regulated after feeding with Bacillus cereus PAS38, the gene may play an important role in the spleen immune response of broilers.

SLC7A6 is one of 14 members of solute carrier family 7, it generally works with other members of the solute carrier family to transport amino acids and glycoproteins in many cells. The current research on SLC7A6 focuses on its potential applications in various types of disease in humans [36, 37]. The difference in expression of SLC7A6 in male and female broilers has also been studied by Kaminski et al. [38], the results showed that the expression of SLC7A6 in the intestine of male chickens was significantly higher than that of female chickens. However, the role of this gene in immune response is still unclear. In this experiment, the SLC7A6 of broilers fed with Bacillus cereus PAS38 was significantly up-regulated. Considering the function of amino acid transport of the gene, we speculated that SLC7A6 might improve the immune ability of broilers by promoting the development of immune organs.

TLR7 is a common toll-like receptor expressed in endosome. It can induce the secretion of cytokines such as INF-γ by mediating the signal pathway of NF-κB and play an important role in natural immunity [39]. Gupta et al. [40] found that TLR7-based adjuvants combined with the influenza A vaccine can stimulate the expression of IFN-α, IFN-β and other genes in chicken spleen cells and inhibit the replication of influenza A. And TLR7-based adjuvants combined with the S. Enteritidis antigen can reduced liver and spleen organ invasion by S. Enteritidis in chickens. Xiang et al. [41] infected mature chicken bone‑marrow‑derived dendritic cells with GM strain of Newcastle disease virus (NDV) and found that TLR7 was significantly up-regulated. Regulation of intestinal epithelial immunological function by the probiotic Lactobacillus johnsonii N6.2 was shown using human Caco-2 cell monolayers, TLR7 expression levels were upregulated by L. johnsonii N6.2 [42]. Guo et al. [43] found that the expression of TLR7 in the spleen of cherry valley duck was up-regulated by adding Bacillus subtilis into the diet. These studies are similar with the results of this experiment, indicating that Bacillus cereus PAS38 can stimulate the immune cells and make them in a high state of immune alertness.

As one of the receptors of IGF1, IGF1R has a strong role in promoting the growth and differentiation. Among chickens and other birds, IGF1R is a unique receptor of IGF-I and IGF-II. It plays a very important role in the function of IGFs and is an important candidate gene affecting chicken growth and body composition [44]. Alzaid et al. [45] found that the expression of IGF1R in head kidney and spleen of salmon was significantly down-regulated after salmonella infection, and IGF was also down-regulated. It was suggesting that IGF1R may have an important connection with immune pathways of animals. Giorgia et al. [46] found that tilapia was fed with Lactobacillus rhamnosus preparation, it could significantly increase the expression of IGF1R in muscles, which was similar with this experiment. At present, the research of IGF1R in chickens is mainly about the effect of its polymorphism on the growth and breeding of chickens. Wang et al. [47] found that selenium deficiency can decreases the growth rate of spleen and the number of splenic lymphocytes by deactivating the IGF-1R/PI3K/Akt/mTOR pathway in chickens. These studies indicate that IGF1R is also indispensable in chicken immune system.

SMAD7 is an endogenous negative feedback regulator of transforming growth factor β / bone morphogenetic protein (TGF-β / BMP) signaling pathway [48]. Studies have shown that high expression of SMAD7 can resist fibrosis and inflammation mediated by TGF-β signaling pathway [49], and the absence of SMAD7 may affect the development of splenic dendritic cells (DCs) [50]. It indicates that the expression of SMAD7 affects the immune function of the body. It was found that SMAD7 plays an important role in the differentiation of embryonic stem cells and muscle development in chicken [51,52], but there are few reports about its role in chicken immunity, which needs further study. Tohru et al. [53] found that after preterm infants were treated with Bifidobacterium breve, the expression of SMAD3 in serum increased, it is similar with this experiment, which suggested that Bacillus cereus PAS38 may play an active role in the immune process of broilers.

ITGA4 is one of α subunits of integrin. Integrins are a class of glycoproteins, which consist of a α subunit and a β subunit. They are important cell surface receptors. They mediate adhesion of cells to extracellular matrices and adhesion of cell to cell, participate in cell proliferation, differentiation, adhesion, migration and other processes, and play an important role in the growth and development, immune response and other physiological processes of the body [54, 55]. Kim et al. [56] found that the down-regulation of ITGA4 in duodenum of chickens infected with Eimeria. On the contrary, Heidar et al. [57] infected susceptible chickens and resistant chickens respectively with Marek’s disease virus (MDV), and found that ITGA4 was up-regulated to a certain extent in duodenum, and especially in resistant chickens. As a cell adhesion related molecule, ITGA4 is involved in leukocyte migration, T cell adhesion and T cell death. These two different results may be related to the tolerance of chickens to the antigens. In this experiment, after feeding Bacillus cereus PAS38, the ITGA4 in spleen of broilers was down regulated, whether this is a positive signal of immunity is unknown, and its specific mechanism needs further study.

In this experiment, compared with the control group, the expression of DOCK10 was also down regulated. DOCK10 is a member of the dock family and can activate Rac1, a small GTP protease [58]. It has the function of regulating the activation and migration of immune cells [59]. Studies have found that the absence of DOCK10 could reduce the number of B lymphocytes in the spleen and peripheral blood, suggesting that DOCK10 may be associated with the maturation and activation of B cells [60, 61]. Monson et al. [62] studied the effect of aflatoxin B1 and probiotics on turkey spleen transcriptome, and found that the expression level of DOCK10 had no significant different in the group of aflatoxin B1 and the group of probiotics compared with the control group, but it was significantly up-regulated in the group of aflatoxin B1+probiotics compared with the control group. Ansari et al. [63] investigated the mechanisms that induce atrophy of the chicken bursa of fabricius upon lipopolysaccharide (LPS) treatment in young chicks, found that LPS treatment resulted in a significant decrease in the weight of bursa of fabricius, and the decrease of cell proliferation; at the same time, the DOCK10 was significantly up-regulated. This suggests that DOCK10, as a proinflammatory factor, its high expression can induce abnormal apoptosis. In this experiment, the decrease of DOCK10 may be related to the dosage of Bacillus cereus PAS38, on the other hand, probiotics do inhibit individual innate immune genes, but we need to know that the beneficial effect of probiotics on animal immune system has been widely proved. And next, we will continue to pay attention to and study the mechanism of DOCK10 in broiler immunity.

The effect of probiotics on the expression of immune-related genes may be related to the process of immune system stimulation by its surface antigens [64, 65]. However, the exact signaling pathway remains unknown, and there are few reports on how these nine differential genes affect the immunity of broilers. In the future, methods such as gene silencing or knockout and gene overexpression will be needed to further explore the effects of these genes on function of immune organ in broilers.

Conclusion

The differential expression of immune-related genes in spleen of broilers fed with probiotic Bacillus cereus PAS38 preparation was studied by SSH technique, nine differentially expressed immune-related genes were screened out. Absolute qRT-PCR was used to verify the immune-related differentially expressed genes, it was found that JCHAIN, FTH1, P2RX7, TLR7, IGF1R, SMAD7, and SLC7A6 were significantly up-regulated in the treated group. These results suggest that Bacillus cereus PAS38 preparation may improve the immunity of broilers by regulating the expression of some immune-related genes, and provide useful information for further understanding the molecular mechanism of probiotics affecting poultry immunity.

Electrophoresis with agarose of 1.2% concentration. The images were generated by the Gel imaging system Gel Doc™ XR+. (A) Treated group. (B) Control group. M represents DNA Marker 2000. The numbers 1, 2, 3, 4 and 5 represent 18, 21, 24, 27 and 30 PCR cycles respectively. Fig 1A was generated by S1A Fig, and Fig 1B was generated by S1B Fig.

(TIF)

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Electrophoresis with agarose of 1.2% concentration. The images were generated by the Gel imaging system Gel Doc™ XR+. (A) Treated group. (B) Control group. M represents DNA Marker 2000. The numbers 1, 2, 3, et al. represent different bacterial clones. Fig 2A was generated by S2A Fig, and Fig 2B was generated by S2B Fig.

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Standard curve of JCHAIN.

The abscissa represents the concentration of plasmid standard (Log10N copies/μL). The longitudinal coordinates denote the cycle threshold. The same below.

(TIF)

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Standard curve of FTH1.

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Standard curve of P2RX7.

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Standard curve of SLC7A6.

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Standard curve of TLR7.

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Standard curve of IGF1R.

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Standard curve of SMAD7.

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Standard curve of ITGA4.

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Standard curve of DOCK10.

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Standard curve of β-actin.

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The process of calculating the copies of differentially expressed genes in absolute qRT-PCR.

P-value is calculated by SPSS 23.0 software.

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Composition of solid fermentation medium of Bacillus cereus PAS38.

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Alignment results of sequencing clones on NCBI.

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1 Oct 2019

PONE-D-19-18103

Screening of differentially expressed immune-related genes from spleen of broilers fed with probiotic Bacillus cereus PAS38 based on suppression subtractive hybridization

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Reviewer #1: The Authors aimed to construct the spleen differential genes library of broilers fed with probiotic Bacillus cereus PAS38 by suppression subtractive hybridization and screen the immune-related genes. The Authors have investigated an interesting topic and the theme has been properly described.

I would like to congratulate authors for the good-quality of the article, the literature reported used to write the paper, and for the clear and elegant and appropriate structure. The manuscript is well written, presented and discussed, and understandable to a specialist readership.

In general, the organization and the structure of the article are satisfactory and in agreement with the journal instructions for authors. The subject is adequate with the journal scope.

The work shows a conscientious study in which a very exhaustive discussion of the literature available has been carried out. The introduction provides sufficient background, and the other sections include results clearly presented and analyzed exhaustively.

As specific comment, I suggest to supply more high-quality figures.

Reviewer #2: This manuscript used suppression subtractive hybridization to identify genes that could have differential expression in response to the oral probiotic Bacillus cereus PAS38. They identified 119 valid ESTs and focused on 9 with immune related functions. Of these, only 3 were validated by qRT-PCR to have a treatment effect.

1. Why was SSH selected as the method for predicting differentially expressed genes? Since the chicken genome is fairly well annotated, why was RNA-seq or 3’ Quant-Seq (better suited to large sample numbers) not used? These methods can be statistically tested (unlike SSH) and also screen the whole transcriptome without a priori knowledge of the treatment effect.

2. Perhaps the low confirmation rate of the qRT-PCR reflects the lack of normalization to a reference gene. Even for absolute qRT-PCR, the copy number for each test gene needs to be normalized to a reference gene to account for variation in total input RNA. Please add the reference information if already done, or complete an additional qRT-PCR using a stably expressed reference gene, adjust the copy number for the 9 target genes and run the ANOVA again.

3. Please strengthen the evidence in the introduction for Bacillus cereus as a probiotic.

4. The discussion included very few references for chicken, with none for the significant JCHAIN, FTH1, and P2RX7 genes. Please add literature for these 3 genes in chicken.

5. The GO term results in lines 149-152 are not interpreted clearly. As analyzed, the biological process, molecular function and cell component terms are considered as if they are mutually exclusive and each EST can only have 1 type of term. It would be better to report this information as the percentage of the total ESTs in each category (so each EST can be represented 0-3 times) rather than a percentage of total GO terms.

6. Figure S6 and S8 show that IGF1R and ITGA4 primers have really low efficiency (60%). Were any other primer pairs tested for these genes? Perhaps an alternate would amplify better and better discriminate between the treated and control groups.

7. A gene set enrichment analysis (such as with PANTHER or GSEA) might be more informative than the top level GO terms from DAVID.

8. Based on the feeding protocol, there were 30 control and 30 treated birds. How many spleens from each group were used to perform the SSH and were the samples pooled? How many individual samples/group were used in the qRT-PCR validation? Add to the text and to figure legends. Also note that if all 60 birds were used, the phrase “randomly selected” in line 81 doesn’t make sense.

9. There are many other experimental details missing from the methods section, including:

a. What is the “basic diet”? Please move Table S3 into the main manuscript, as the composition of the diet is important to the interpretation of this study.

b. Please put the information in Table S1 and S2 into the text of the methods and not supplemental tables, so that the company and reagent information is complete in the text.

c. What type of housing (floor pens, cages, etc.) was used for the birds?

d. Please add the bacterial growth conditions (media, temp, etc.), and how the bacteria concentration was determined to line 72-74.

e. In line 87, “diluted 5 times” is not clear. Please clarify if this means a 5-fold (1:5) dilution or 5 serial dilutions to what final dilution factor.

f. How much input RNA was used for cDNA synthesis in line 87 and 93-94? How much cDNA was used as input for the qRT-PCR reactions in line 116?

g. In line 98, what were the hybridization conditions? Also add to this section, the enzyme and condition used for digestion, as mentioned in line 138.

h. For all reactions (cDNA synthesis in line 87 and 93-94, nested PCR in line 98, liquid-culture treated PCR in line 102-103, and qRT-PCR in line 116), the components of the reactions and the cycling conditions (i.e. the program) need to be described. For the qRT-PCR, please also include a description of how the standard curves were generated/used and reference the supplemental figures.

i. Were amplicons from the qRT-PCR confirmed by sequencing?

j. In line 110, what version of the DAVID database was used?

k. What were the positive and negative controls for the SSH and qRT-PCR validation?

l. The percentage agarose used for electrophoresis is not consistent. Is it 1.2% (line 90 and 128) or 1.5% (line 133 and 141)?

10. Other comments:

a. There are English grammar errors in the manuscript, please check.

b. In Figure 2, how was the subset of samples shown selected?

c. Figure 3 and 4 are blurry. Please improve image resolution.

d. In Table 2, clarify if up/down references treated vs control or control vs treated.

e. There are no references to the supplemental figures in the text. Please add.

f. In line 70 and 76, the birds are listed as “Avian broilers”. Was this supposed to reference an Aviagen broiler

line? If so, please correct. If “Avian” is just referring to bird, remove this word.

g. In line 41-42, reference 5 is cited for using appendix, which is not a tissue in birds. Are they referring to the ceca?

h. In line 109, what does “not matched” mean? No hit to chicken genome?

i. The number of valid ESTs are reported in line 147 but how many of the failed clones were low quality sequence, unmatched sequence, repeat sequence, or unannotated protein sequence?

j. ITGA4 and DOCK10 should not be highlighted in the abstract and conclusions as these were not confirmed by qRT-PCR (p>0.05).

**********

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Reviewer #1: No

Reviewer #2: No

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29 Oct 2019

Dear academic editor and reviewers,

Thank you very much for giving us an opportunity to revise our manuscript. We appreciate the editor and reviewers very much for their constructive comments and suggestions on our manuscript entitled “Screening of differentially expressed immune-related genes from spleen of broilers fed with probiotic Bacillus cereus PAS38 based on suppression subtractive hybridization”.

We have studied reviewers’ comments carefully. According to the reviewers’ detailed suggestions, we have made a careful revision on the original manuscript. All revised portions are marked in red in the revised manuscript which we would like to submit for your kind consideration.

Kind regards.

Jiajun Li

E-mail: 18227585635@163.com

Corresponding author: Kangcheng Pan

E-mail: pankangcheng71@126.com

Reviewer #1:

Thank you for your sincere suggestion. I've replaced the blurred images with high-quality figures.

Reviewer #2:

1. Why was SSH selected as the method for predicting differentially expressed genes? Since the chicken genome is fairly well annotated, why was RNA-seq or 3’ Quant-Seq (better suited to large sample numbers) not used? These methods can be statistically tested (unlike SSH) and also screen the whole transcriptome without a priori knowledge of the treatment effect.

Firstly, a large number of previous studies have shown that SSH is a good method for constructing transcriptomes and screening differentially expressed genes. Secondly, this research is part of the National Natural Science Foundation (China) that our research group applied for in 2014. At that time, RNA-seq or 3'Quant-Seq technology was not mature. Third, although RNA-seq or 3’ Quant-Seq has been widely used in the determination of large Numbers of samples, it is inconvenient for the determination of a small number of samples. Furthermore, using different methods, the results of different genes can be different or the same. So, SSH was used to complete the experiment in our study.

2. Perhaps the low confirmation rate of the qRT-PCR reflects the lack of normalization to a reference gene. Even for absolute qRT-PCR, the copy number for each test gene needs to be normalized to a reference gene to account for variation in total input RNA. Please add the reference information if already done, or complete an additional qRT-PCR using a stably expressed reference gene, adjust the copy number for the 9 target genes and run the ANOVA again.

We have supplemented the absolute qRT-PCR for reference genes as required. The results showed that the expression of the reference gene β-actin was almost the same between the treated group and the control group, and there was no significant difference (P>0.05). At the same time, we also add the corresponding figures and data to the manuscript. In addition, in the process of revising the manuscript, we found that the calculation of plasmid standard concentration was wrong, so we used the Bio-Rad CFX Manager 3.1 software to reset the concentration of plasmid standard, rebuild the standard curve, and recalculate the copies of the differential genes. Then we compared the differences of the new calculation results again, and modified the corresponding discussion part and figures in the manuscript.

3. Please strengthen the evidence in the introduction for Bacillus cereus as a probiotic.

We have added the introduction of Bacillus cereus as a probiotic as required.

4. The discussion included very few references for chicken, with none for the significant JCHAIN, FTH1, and P2RX7 genes. Please add literature for these 3 genes in chicken.

We have added these three genes to the discussion in chicken as required.

5. The GO term results in lines 149-152 are not interpreted clearly. As analyzed, the biological process, molecular function and cell component terms are considered as if they are mutually exclusive and each EST can only have 1 type of term. It would be better to report this information as the percentage of the total ESTs in each category (so each EST can be represented 0-3 times) rather than a percentage of total GO terms.

We have reinterpreted the results as required.

6. Figure S6 and S8 show that IGF1R and ITGA4 primers have really low efficiency (60%). Were any other primer pairs tested for these genes? Perhaps an alternate would amplify better and better discriminate between the treated and control groups.

We have redesigned the primers, and re-tested the absolute qRT-PCR of these two genes and changed the relevant data in the article.

7. A gene set enrichment analysis (such as with PANTHER or GSEA) might be more informative than the top level GO terms from DAVID.

According to your suggestion, we use blast2go software to re-analyze the data and change the relevant content of the article.

8. Based on the feeding protocol, there were 30 control and 30 treated birds. How many spleens from each group were used to perform the SSH and were the samples pooled? How many individual samples/group were used in the qRT-PCR validation? Add to the text and to figure legends. Also note that if all 60 birds were used, the phrase “randomly selected” in line 81 doesn’t make sense.

We randomly selected two chickens from each repeat of each group, that is, a total of six chickens in each group. We extracted the total RNA of each spleen separately and aggregated the total RNA of each group.

We used the total RNA collected from the treated group and the control group for reverse transcription and a total cDNA was obtained respectively. And then we use this total cDNA for qRT-PCR validation.

We have supplemented the relevant content in the article as required.

9. There are many other experimental details missing from the methods section, including:

a. What is the “basic diet”? Please move Table S3 into the main manuscript, as the composition of the diet is important to the interpretation of this study.

We have moved the basic diet ingredient list to the manuscript as required.

b. Please put the information in Table S1 and S2 into the text of the methods and not supplemental tables, so that the company and reagent information is complete in the text.

We have moved the contents of two supplemental tables into the manuscript as required.

c. What type of housing (floor pens, cages, etc.) was used for the birds?

We have supplemented the notes in the manuscript as required.

d. Please add the bacterial growth conditions (media, temp, etc.), and how the bacteria concentration was determined to line 72-74.

We have added relevant content to the manuscript as required.

e. In line 87, “diluted 5 times” is not clear. Please clarify if this means a 5-fold (1:5) dilution or 5 serial dilutions to what final dilution factor.

We have clarified in the manuscript as required.

f. How much input RNA was used for cDNA synthesis in line 87 and 93-94? How much cDNA was used as input for the qRT-PCR reactions in line 116?

We have supplemented the manuscript as required.

g. In line 98, what were the hybridization conditions? Also add to this section, the enzyme and condition used for digestion, as mentioned in line 138.

We have added relevant content to the manuscript as required.

h. For all reactions (cDNA synthesis in line 87 and 93-94, nested PCR in line 98, liquid-culture treated PCR in line 102-103, and qRT-PCR in line 116), the components of the reactions and the cycling conditions (i.e. the program) need to be described. For the qRT-PCR, please also include a description of how the standard curves were generated/used and reference the supplemental figures.

We have added relevant content to the manuscript as required.

We have explained how the standard curve is generated/used in the manuscript as required, as well as the reference supplementary figures.

i. Were amplicons from the qRT-PCR confirmed by sequencing?

When we prepared the plasmid standard, we sent the plasmid standard to be sequenced and confirmed that there was no problem. The primers used for qRT-PCR are the same as those used for preparation of plasmid standard. We don't think it is necessary to send them for sequencing confirmation, so the amplicons from the qRT-PCR were not sequenced.

j. In line 110, what version of the DAVID database was used?

We used version 6.8 of DAVID before, but now we have changed it to blsat2go software.

k. What were the positive and negative controls for the SSH and qRT-PCR validation?

Based on the SSH test method and previous references, we believe that it does not require positive and negative controls.

The positive control of qRT-PCR was the standard plasmid diluted 10-fold, while the negative control was the system with RNase-free water as template.

l. The percentage agarose used for electrophoresis is not consistent. Is it 1.2% (line 90 and 128) or 1.5% (line 133 and 141)?

We apologized for the incorrect concentration of agarose gel electrophoresis in the manuscript. In fact, we used 1.2% concentration agarose gel in the experiment. We have corrected the relevant information in the manuscript.

10. Other comments:

a. There are English grammar errors in the manuscript, please check.

We have checked and corrected English grammar errors as much as possible according to the requirements.

b. In Figure 2, how was the subset of samples shown selected?

We randomly selected 400 white clones from plate Petri dishes for PCR. Then, the PCR products were electrophoretized and many electrophoretic results were obtained. We randomly selected some electrophoretic results for display.

c. Figure 3 and 4 are blurry. Please improve image resolution.

We use blast2go software to re-analyze the data and get new high-quality figures. We will re-upload the new figures.

d. In Table 2, clarify if up/down references treated vs control or control vs treated.

We have made it clear in the manuscript as required.

e. There are no references to the supplemental figures in the text. Please add.

We have mentioned the supplemental figures in the manuscript as required.

f. In line 70 and 76, the birds are listed as “Avian broilers”. Was this supposed to reference an Aviagen broiler line? If so, please correct. If “Avian” is just referring to bird, remove this word.

“Avian broilers” is an avian white feather broiler, we have made it clear in the manuscript as required.

g. In line 41-42, reference 5 is cited for using appendix, which is not a tissue in birds. Are they referring to the ceca?

I'm sorry we didn't read that reference carefully before. After careful reading, we found that "appendix" is their writing error, it should be "cecum", we have corrected the relevant content in the manuscript.

h. In line 109, what does “not matched” mean? No hit to chicken genome?

"Not matched" means that no sequence can be compared in NCBI databases. These sequences may be erroneous sequences that occur during sequencing or new gene sequences.

i. The number of valid ESTs are reported in line 147 but how many of the failed clones were low quality sequence, unmatched sequence, repeat sequence, or unannotated protein sequence?

We have added the result table of sequence alignment to the supplementary file.

j. ITGA4 and DOCK10 should not be highlighted in the abstract and conclusions as these were not confirmed by qRT-PCR (p>0.05).

We have deleted the content of these two genes in abstract and conclusions as required.

Submitted filename: Response to Reviewers.docx

Click here for additional data file.

9 Dec 2019

Screening of differentially expressed immune-related genes from spleen of broilers fed with probiotic Bacillus cereus PAS38 based on suppression subtractive hybridization

PONE-D-19-18103R1

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Reviewer #1: The Authors have revised their paper according to the comments received, so in my opinion the revised paper merits the final acceptance.

Reviewer #2: Thank you to the authors for their detailed work addressing the comments in their response letter and revised manuscript.

Two tiny comments:

In the new Blast2Go pie charts, there are watermarks behind the images. The images would be clearer without these.

As the corrected qPCR analysis now confirmed (p-value<0.05) the down-regulation of ITGA4 and DOCK10, these genes can be put back in the abstract and conclusions (contrary to the previous suggestion to remove them).

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Reviewer #1: No

Reviewer #2: No

11 Dec 2019

PONE-D-19-18103R1

Screening of differentially expressed immune-related genes from spleen of broilers fed with probiotic Bacillus cereus PAS38 based on suppression subtractive hybridization

Dear Dr. PAN:

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