TMT labeled comparative proteomic analysis reveals spleen active immune responses during Clostridium perfringens type C infected piglet diarrhea

Background Clostridium perfringens (C. perfringens) type C is the principal pathogenic clostridia of swine, frequently causing hemorrhagic diarrhea, even necrotic enteritis in piglets, leading to severe economic loss for swine industr ies worldwide. However, there are no specific and effective prevention measures. Therefore, clarifying the molecular mechanisms of hosts against pathogenesis infection is very important to reduce the incidence of C. perfringens type C infected piglet diarrhea disease. Methods We performed an TMT labeling-based quantitative spleen proteomic analysis of the control group (SC), tolerance group (SR) and susceptible group (SS) to identify the differentially expressed proteins (DEPs), and screened potential molecular markers of piglet spleen tissues in response to C. perfringens type C infection. Results In this study, a total of 115, 176 and 83 DEPs were identified in SR vs SC, SS vs SC, and SR vs SC, respectively, which may play the important regulatory roles in the process of piglet spleens in response toC. perfringens type C-infected diarrhea diseases. GO enrichment analysis revealed that the DEPs were mostly significantly enriched in acute inflammatory response, defense response, antimicrobial response, transporter activity, cellular metabolic process and so on, and KEGG pathway enrichment analysis showed that the significantly enriched immune related pathways of the PPAR signaling pathway, IL-17 signaling pathway, antigen processing and presentation, which hints at the immune defense process of piglet spleen against C. perfringens infection. This study helps to elucidate the protein expressional pattern of piglet spleen against C. perfringens type C-infected diarrhea disease, which can contribute to the prevention and control for pig diarrhea disease and the further development of diarrhea resistant pig breeding.


INTRODUCTION
Clostridium perfringens (C. perfringens) is the most widespread of pathogenic bacteria in environment (Labbe & Vijay, 2017), which commonly caused several diseases, such C. perfringens type C was determined by plate colony counting method, and finally an expected concentration of 1 × 10 9 CFU/mL C. perfringens type C medium was used to inoculate piglets.
Twenty-five piglets were randomly selected to suffer oral inoculate administration of 1 × 10 9 CFU/mL C. perfringens type C medium, the remaining 5 piglets were orally inoculated sterile medium as control group (SC), the experiment lasted for 5 days for the research report (Songer & Uzal, 2005) and the result of our pre-experiment. During the 5-day experimental period, all piglets were housed separately by special environmental control equipment, bodyweight, mental state, shape and color of feces and degree of diarrhea for each piglet were detailly observed and recorded detailly in every day. The degree of diarrhea was evaluated according to the diarrhea scoring standard of piglets (Huang et al., 2019): 0 point for strip or granular feces; one point for soft forming; two points for thick and unformed feces; three points for liquid and watery excrement.
At the end of the test, the total diarrhea scores of each piglet were calculated by adding each defecation score of each piglet during the test period. Finally, 3 piglets with the highest and lowest total diarrhea scores were considered as the susceptible group (SS) and t the tolerance group (SR) (Fig. S1). In general, SS represents in sensitive to C. perfringens infection with serious diarrhea, and SR represents which resistant to C. perfringens infection with mild diarrhea.
Finally, nine piglet spleen tissues of SS, SR and SC groups were rapidly collected without RNA enzyme and washed with PBS buffer frozen by liquid nitrogen and transferred to −80 • C for storage.

Protein extraction
Spleen samples were added and mixed by lysis buffer (8 M urea, 1% Protease Inhibitor Cocktail) for standing still for 30 min, then followed by sonication on ice three times using a high-intensity ultrasonic processor (Scientz). After fully lysing on ice 30 min, the remaining precipitated debris was removed by centrifugation at 12,000 g at 4 • C for 10 min. The supernatant was collected and protein concentration was determined by BCA kit (Beyotime biotechnology, Shanghai, China).

Quantification validation of MS data
Only peptides unique for a certain protein were considered for TMT relative quantification, which was normalized using the average ratio of all the unique peptides in each sample. A two-tailed Fisher's exact test was employed to test the enrichment of the differentially expressed protein against all identified proteins. A corrected P value < 0.05 was considered significant. For further hierarchical clustering based on different protein functional classification, the cluster membership was visualized by a heat map using the ''heatmap.2'' function from the ''gplots'' R-package.

Functional enrichment analysis
The different expressed proteins were performed to Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways analysis using DAVID (version 6.7). The protein functional annotation was derived from the UniProt-GOA database (http://www.ebi.ac.uk/GOA/) (Ashburner et al., 2000). The functional annotation and descriptions of identified protein domains were annotated by InterProScan (a sequence analysis application) based on protein sequence the InterPro (http://www.ebi.ac.uk/interpro/) domain database. The identified proteins domain functional description was annotated by InterProScanbased (http://www.ebi.ac.uk/interpro/) on protein sequence alignment.

Protein-protein interaction network
All differentially expressed proteins interactions, were analyzed against the Sus scrofa database by STRING version 10. Only the confidence score ≥ 0.7 (high confidence) of interactions was fetched. Interaction network form STRING was visualized in R package ''networkD3''. Cytoscape was used for the visualization of the networks.

Statistical analysis
One-way ANOVA and Duncan's multiple comparisons in SPSS 26.0 software were used to test the significance of difference between diarrhea scores of piglets, the weight of piglets before euthanasia, and the weight of heart, liver, spleen, lung and kidney after euthanasia in the groups of SR, SS and SC, Differences with a P < 0.05, the log2-transformed ratio is larger than 1.3 were considered as significant difference. Results were shown as the means and standard errors (mean ± SE).

Phenotypic characterization of piglets infected with C. perfringens type C
After the infection of C. perfringens type C, the inoculated piglets presented the varying degrees of diarrhea symptom. As shown in Fig. 1, the bodyweight, heart, liver, spleen, and kidney of inoculated piglets in the SS and SR groups were significantly lower than those of control group (SC) (P < 0.01). Meanwhile, the weights of body and heart, spleen, kidney and liver in SS group were the lightest. In addition, lung weight in SS and SR groups were significantly higher than that in SC group (P < 0.01, P < 0.05), and SS group has the heaviest lung weight. ** ** * Figure 1 The difference of bodyweight, heart, liver, spleen, lung and kidney of the piglets in SS, SR and SC groups. * P < 0. 05, representing meaningful difference; ** P < 0.01, representing a significant difference.

Quantitative identification of spleen proteins for piglets
To comprehensively profile the landscape of spleen protein expression before and after C. perfringens infection, we had identified and quantified the differential proteome dynamics in three replicates during the C. perfringens infection. According to the experimental workflow ( Fig. S1), we achieved comprehensive proteome profiling with deep coverage using TMT-labeled LC-MS/MS combined with pre-fractionation by HPLC, allowing for identification and quantification simultaneously. In total, 6,145 proteins can be identified, among which 4,958 proteins were quantified in the global proteome (Supplemental Table  S1). In addition, many uncharacterized proteins were identified according to bioinformatics comparison results and the comprehensive annotation (Supplemental Table S2).

QC validation of MS data
To validate the quality of MS and MS/MS profiling, the mass error of all the identified peptides were checked, results demonstrated that the mass accuracy of the MS data and sample preparation fit the experiment requirement standard. The repeatability among the three groups was assessed by principal component analysis (PCA), relative standard deviation (RSD) and Pearson correlation coefficient, results indicated that there were the higher aggregation degree and correlation among SS, SR and SC groups (Figs. S2A, S2B, S2C), which proved that the proteomic analysis was robust and all data would be used for the following analysis with high quality.

Differentially quantified proteins identified among SC, SR and SS
The differentially expressed proteins and specific number for differential proteins between SR, SS and SC were analyzed. The proteins exhibiting a log 2 (fold change) > 1.3 and a P value < 0.05 were regarded as DEPs, then a total of 115 DEPs were identified in SR vs SC, of which 48 were up-regulated proteins and 67 were down-regulated proteins, 176 DEPs were identified with 83 up-regulated proteins and 93 down-regulated proteins in SS vs SC, 83 DEPs were identified, with 40 were up-regulated proteins and 43 down-regulated proteins in SR vs SC (Fig. 2, Table S3). The above differentiation of protein expression indicated molecular changes and potential functional transformation underlined C. perfringens infected piglets.

Bioinformatic analysis of differentially expressed proteins
The proteins with diverse biological processes and distinct subcellular locations performed significantly different molecular functions. There was a wide range of functional distribution of the DEPs among SS, SR and SS groups for each module, the three top were mainly located in extracellular, cytoplasm and nucleus, and detailly, extracellular enriched the most differential proteins for SR vs SC, cytoplasm for SS vs SC, and nucleus for SS vs SR (Fig. 3). The heatmap comparisons of SS vs SC, SR vs SC, SS vs SR groups were shown in Fig. 4 and Table S4, which divided into biological process, cellular component and molecular function. The DEPs with same expression pattern were clustered together.

Functional enrichment analysis of DEPs
To explore the function of DEPs among SS, SR and SC groups, GO and KEGG functional enrichment analysis were performed. GO catalogs analysis of the DEPs among SR vs SC, SS vs SC and SR vs SS groups revealed that the most significantly enriched biological    kinase binding, kinase binding, iron ion transmembrane transporter activity, Toll-like receptor 4 binding, RAGE receptor binding, nucleosomal DNA binding (Fig. 5, Table S4). Specially, in the SS vs SR groups, the biological process included many immune and metabolism associated functions, such as defense response to virus, inflammatory response, regulation of response to virus immune response, defense response to other organism, antimicrobial humoral response, regulation of cytokine-mediated signaling pathway, regulation of apoptotic process and so on. The cellular components were mainly cell and organelle. And the molecular function mainly enriched in binding and enzyme catalytic activity of methyltransferase, enzyme regulator, peptidase regulator and endopeptidase inhibitor, translation initiation factor receptor binding. Functional domains related to immunoglobulin-like fold, MHC classes I/II-like antigen recognition protein, calcium S100/CaBP-9k-type, Ferritin/DPS protein domain, Fibrinogen were conspicuously enriched in these DEPs (Fig. 6, Table S5).
KEGG analysis was performed to investigate the enriched pathways participated by the DEPs. A total of 30 KEGG signaling pathways were enriched among them, detailly, 13 signaling pathways for SR vs SC, 20 signaling pathways for SS vs SC and 5 signaling pathways for SS vs SR (Fig. 7, Table S6). In which, PPAR signaling pathway, IL-17 signaling pathway were highly enriched in SR vs SC and SS vs SC after C. perfringens infection, antigen processing and presentation, intestinal immune network for IgA production, hematopoietic cell lineage was specifically significantly in SS vs SC, RIG-I-like receptor signaling pathway were specifically significantly enriched in SS vs SR, these identified significantly signaling pathways were involved in the process of piglet spleen immune responses against C. perfringens infection.

Analysis of protein interaction network
In order to clearly display the interactions between proteins, a network constitute of top 50 closest interactions proteins of functional protein-protein interactions was built using STRING v.10.0 online software against the Sus scrofa database (Ashburner et al., 2000). A total of 34, 47 and 10 known or predicted interactions (PPI enrichment P-value < 1.0e −16 ) were formed among DEPs in the PPI network (Fig. 8)

DISCUSSION
Piglet Diarrhea is an important factor affecting the healthy development of the pig industries worldwide (Zhao et al., 2016), C. perfringens type C has become the increasing threaten bacterial infections to lead pig diarrhea with characteristic of high morbidity and mortality, especially in newborn and suckling piglets (Uzal & McClane, 2011), even in domestic animals and humans (Diab et al., 2016), resulting in great economic loss. Our previous studies found that C. perfringens type C infection caused to the significantly up-regulations of immune genes TLR4, TNF-α and NF-κB, inflammatory cytokine factors IFN-γ , IL-1β, IL-6 and IL-12, and serum immunoglobulin IgA and IgG in tolerance and susceptible piglets (Shi et al., 2019). Histopathological findings the morphology of the intestines and spleens of piglets infected by C. perfringens type C were abnormal obviously, such as infection caused edema of the lamina propria and submucosa, inflammatory cell and neutrophile granulocytes infiltration in piglet intestines (Yan et al., 2019), and infiltration with neutrophilic granulocytes in the red pulp of spleen tissues (Yan et al., 2018). These studies had provided that there were significantly immune and inflammatory responses of piglet spleen in response to C. perfringens type C infection. However, it is still limited that the molecular mechanism of piglet spleen immune responses against to C. perfringens type C-infected diarrhea disease, which can improve to understand mechanism of piglet resistance to C. perfringens type C infection and may help to prevent and control pig bacterium diarrhea. Therefore, we had comprehensively profiled and characteristed the spleen proteomic dynamics of piglet against to C. perfringens infection by the TMT-labeled LC-MS/MS combined with pre-fractionation by HPLC.
In this study, a total of 6,145 identified proteins, including 4,958 quantified proteins were in piglet spleen tissues from SR, SS and SC groups suffered from C. perfringens infection. Differential expression analysis totally identified 115 DEPs (48 upregulated and 67 down-regulated proteins) identified in SR vs SC group, 176 DEPs (83 upregulated and 93 down-regulated proteins) in SS vs SC group, 83 DEPs (40 upregulated and 43 downregulated proteins) in SR vs SC group, in which, some immune-related proteins also identified, including P80310 (coded by S100A12) and C3S7K6 (coded by S100A9) both up-expressed in SR vs SC and SS vs SC groups, Q764N2 (coded by CD3D) up-expressed in SR vs SC group, F1SNY4 (coded by TAB1) down-expressed in SS vs SC group, K7GPC8 (Leukocyte receptor LENG8), and P49932 (antibacterial peptide PMAP37) down-expressed in SR vs SS group, which may play the important regulatory roles in the process of piglet spleens in response to C. perfringens type C-infected diarrhea diseases.
GO enrichment analysis of DEPs suggested that the biological processes of immune response, regulation of cytokine, acute inflammatory response, programmed cell death, antimicrobial humoral response, apoptotic, defense response, transport and metabolic process were enriched. In addition, as shown in Fig. 5, the biological processes of the immune and inflammatory response might play core role in the development of piglet against C. perfringens type C infected diarrhea, as it could interact more with the remaining other biological processes. These results may hint that host immune responses were highly active against inflammation. Meanwhile, metabolic processes and transport were gradually complemented to supply the needs for materials and energy consumption, showing dynamic responses of piglet spleen during C. perfringens type C infection. Consistent with the biological process, the enrichment of cellular component and molecular function apoptosis in the lungs of LPS-challenged mice, S100A9 protein downregulation mitigated LPS-induced inflammation in vitro (Zhao et al. 2021), which were in accordance with our study, the S100A9 protein was expressed in piglet spleen tissue in SR and SS groups, the protein change level of S100A9 protein in SS group was higher than that in SR group, which may indicate that S100A9 protein could be considered as a potential candidate in infection disease.
Protein function can be predicted by using a database of protein domains and functional sites, in which, protein domain is applied to annotation of proteins with unknown function. Similarly, according to the enrichment of protein domain in Fig. 6, immunoglobulin subtype, heat shock protein and MHC class I-like antigen were significantly enriched in SR vs SC and SS vs SC, as well as GTPase domain and cytosolic fatty-acid binding. Further, many Immune inflammatory related functions were identified in SR vs SC, SS vs SC, and SS vs SR comparative groups, such as T-cell surface glycoprotein CD3, serotransferrin, serum albumin, MHC class I antigen 2 precursor, interferon-induced GTP-binding protein, lysozyme, haptoglobin.
Many studies have reported that PPAR-γ played a key role in mediating the anti-inflammatory effects (Mohamed et al. 2021;Choi et al., 2017;Chung et al. 2003). Specifically, the PPAR signaling pathway was the most significantly higher and activated in the SR and SS groups than SC group, the results suggested that PPAR signaling pathway was sustained to relatively high level, when resistant to C. perfringens infection. which may be a potential target against C. perfringens infection. Study had reported that PPAR-γ agonist seemed to enhance Fas-mediated apoptosis by affecting the way between caspase-8 and caspase-3, which was is also related to regulation of inflammation and cell proliferation (Chung et al. 2003). PPAR has the important regulation of cytokine production and cytokine-mediated signal transduction pathways in immune cells and cancer (Yang et al., 2008). Manoharan et al. (2016) had demonstrated that the PPAR pathway in innate immune cells orchestrates gut mucosal immunity and commensal homeostasis by regulating the expression of IL-22 and the antimicrobial peptides and calprotectin, suggesting that the PPAR signaling pathway played important innate immune function in regulating intestinal inflammation, mucosal immunity, and commensal homeostasis (Manoharan et al. 2016).
Further, according to bioinformatics comparison results, we identified many uncharacterized proteins (Table S3). These proteins identified possible genes by comparison. However, the bioinformatic analysis could not identify the roles of these proteins, and their functions remain unclear. Moreover, further studies of the molecular mechanism need to be performed to examine the underlying mechanism of the regulation of immune response networks and other biological processes.

CONCLUSION
To summarize, we first analyzed the comparative proteomics in piglets after of C. perfringens infection, and found that PPAR signaling pathway and haptoglobin may play an important role in C. perfringens infection. This study offers information towards a deeper understanding of the immune inflammatory response of piglets to C. perfringens infection.