Journal of Animal Science and Biotechnology
Research

Effects of dietaryLactobacilluspostbiotics and bacitracin on the modulation of mucosa-associated microbiota and pattern recognition receptors affecting immunocompetence of jejunal mucosa in pigs challenged with enterotoxigenic F18+Escherichia coli

1 ,1 ,1

Abstract

Background

EnterotoxigenicEscherichia coli(E. coli) is a threat to humans and animals that causes intestinal disorders. Antimicrobial resistance has urged alternatives, includingLactobacilluspostbiotics, to mitigate the effects of enterotoxigenicE. coli.

Methods

Forty-eight newly weaned pigs were allotted to NC: no challenge/no supplement; PC: F18+E. colichallenge/no supplement; ATB: F18+E. colichallenge/bacitracin; and LPB: F18+E. colichallenge/postbiotics and fed diets for 28 d. On d 7, pigs were orally inoculated with F18+E. coli. At d 28, the mucosa-associated microbiota, immune and oxidative stress status, intestinal morphology, the gene expression of pattern recognition receptors (PRR), and intestinal barrier function were measured. Data were analyzed using the MIXED procedure in SAS 9.4.

Results

PC increased (P< 0.05)Helicobacter mastomyrinuswhereas reduced (P< 0.05)Prevotella copriandP. stercoreacompared to NC. The LPB increased (P< 0.05)P. stercoreaandDialister succinatiphiluscompared with PC. The ATB increased (P< 0.05)Propionibacterium acnes,Corynebacterium glutamicum, andSphingomonas pseudosanguiniscompared to PC. The PC tended to reduce (P= 0.054)PGLYRP4and increased (P< 0.05)TLR4,CD14, MDA, and crypt cell proliferation compared with NC. The ATB reduced (P< 0.05)NOD1compared with PC. The LPB increased (P< 0.05)PGLYRP4, and interferon-γ and reduced (P< 0.05)NOD1compared with PC. The ATB and LPB reduced (P< 0.05) TNF-α and MDA compared with PC.

Conclusions

The F18+E. colichallenge compromised intestinal health. Bacitracin increased beneficial bacteria showing a trend towards increasing the intestinal barrier function, possibly by reducing the expression of PRR genes.Lactobacilluspostbiotics enhanced the immunocompetence of nursery pigs by increasing the expression of interferon-γ and PGLYRP4, and by reducing TLR4, NOD1, and CD14.

Background

The improved immunocompetency of intestinal mucosa is crucial for the overall well-being and productivity of animals [1, 2]. The intestine, specifically the mucosa, plays a pivotal role in nutrient absorption, immunological defense, and establishing a symbiotic relationship with the intestinal microbiota [3, 4]. Disruptions in the balance of the intestinal microbiota and mucosal integrity can lead to dysbiosis, impaired immune function, and increased susceptibility to enteric pathogens [5]. Enterotoxigenic Escherichia coli (E. coli) is a significant pathogen responsible for causing enteric diseases in both humans and animals [6,7,8]. In pigs, F18+ E. coli infections lead to inflammation, oxidative damages, and villus destruction in the jejunum, resulting in post-weaning diarrhea, and decreased growth [8].

Traditional approaches to combat enterotoxigenic E. coli infections have relied heavily on the use of antibiotics [8]. However, the overuse and misuse of antibiotics have contributed to the emergence of antibiotic-resistant strains, posing a serious threat to both human and animal health [9, 10]. Therefore, alternative strategies are urgently needed to mitigate the impact of enterotoxigenic E. coli infections without exacerbating the antibiotic resistance crisis [9, 11].

One potential alternative is the use of postbiotics derived from microorganisms that confer health benefits to the host [12,13,14,15]. Lactobacilli is a well-known group of bacteria that has been extensively studied for its potential to modulate the intestinal microbiota, strengthen the intestinal barrier, and regulate the immune response [15,16,17]. Lactobacillus postbiotics have shown promise in improving intestinal health and reducing the severity of various gastrointestinal disorders in both humans and animals [12, 15, 17,18,19]. The health benefits promoted by postbiotics can be associated with the non-living microbial cells, and their components, as well as the metabolites produced during fermentation [14]. Molecules in the microbial cell wall and metabolites interact with the host by pattern recognition receptors (PRR), modulating the host immune responses [20, 21]. The cell wall of Lactobacillus contains peptidoglycans that is known to modulate immune responses in the intestinal mucosa [22, 23].

The host immune system can also, modulate the microbiome within the intestine [21, 24]. The cross-talk between the immune system and the intestinal microbiota plays an essential role in immunocompetence of the host [3, 21]. Furthermore, mucosa-associated microbiota interacts more directly with the immune system compared to the luminal microbiota [25, 26]. Although the luminal microbiota differs from the mucosa-associated microbiota in composition and functions, they are not completely unrelated, and dietary interventions can modulate the microbiota in both the lumen and mucosa [27].

Therefore, it was hypothesized that dietary Lactobacillus postbiotics increases the immunocompetence of pigs by modulating the mucosa-associated microbiota and the PRR, reducing mucosal damage and inflammation in pigs challenged with F18+ E. coli. This study aimed to evaluate the role of dietary Lactobacillus postbiotics on the modulation of mucosa-associated microbiota and PRR, and its impacts on mucosal immune response in pigs challenged with F18+ E. coli.

Materials and methods

This study followed the experimental protocol revised and approved by the Institutional Animal Care and Use Committee of North Carolina State University (Raleigh, NC, USA).

Animals, experimental design, and diets

Forty-eight pigs (24 barrows and 24 gilts) with 7.9 ± 0.5 kg of body weight (BW) were randomly assigned to four treatments. Pigs were blocked based on sex (barrows and gilts) and initial BW (lighter and heavier) and allotted based on a randomized complete block design. The treatments were NC: no challenge/no supplement; PC: F18+ E. coli challenge/no supplement; ATB: F18+ E. coli challenge/antibiotic (bacitracin 30 g/t feed); and LPB: F18+ E. coli challenge/Lactobacillus postbiotics (2 kg/t feed). Bacitracin methylene disalicylate was used as a source of bacitracin. The postbiotics contained 6 × 1010/g of powder of heat-inactivated Lactobacillus (L. fermentum and L. delbrueckii) as well as the spent media (LBiotix, Adare Biome, Houdan, France). The dosage was set based on previous study conducted by Xu et al. [12] and Warda et al. [17]. Pigs were fed a basal diet formulated to meet the nutrient requirements of NRC (2012) [28], as shown in Table 1. The ATB and LPB were added to the basal diet at the expense of corn.

Table 1 Composition of experimental diet
Full size table

The strain F18ac (O147) that produces heat-stable toxin A (STa) and heat-stable toxin B (STb) was used for this study. The F18ac (O147) was selected based on its strong capacity to adhere to the small intestinal receptors in newly weaned pigs [29]. The dosage of inoculation was 2.4 × 1010 CFU and the culture of F18+ E. coli was prepared following the protocol as previously reported [12, 30].

Sample collection

Following the 28 d feeding period, the pigs were euthanized by exsanguination subsequent to a penetrating captive bolt applied to the head. Immediately after euthanasia, a section of 15 cm from mid-jejunum (3 m after the duodenojejunal junction) was rinsed with sterile saline solution (0.9% NaCl) and opened for collection of samples. The mucosa samples were obtained by gently scraping the jejunal section with a microscope slide. Subsequently, the samples were placed in 2-mL tubes (two sets per pig) and rapidly frozen using liquid nitrogen before being stored in a freezer at −80 °C for analysis of mucosa-associated microbiota, immune and oxidative stress markers. Jejunal tissue (2 cm) was collected and stored at −80 °C (after snap-freezing in liquid nitrogen, immediately after collection) for further measurements of the gene expression of intestinal biomarkers associated with microbial cell wall components and intestinal barrier function. Another jejunal section (5 cm) was fixed in 10% formalin to be used for histological evaluation.

Mucosa-associated microbiota

The DNA was extracted from the jejunal mucosa samples to analyze the mucosa-associated microbiota using the 16S rRNA sequencing as described by Duarte et al. [31]. The extraction process utilized the DNA Stool Mini Kit (#51604, Qiagen; Germantown, Maryland, USA) and followed the manufacturer’s instructions. The DNA samples were then sent to Mako Medical Laboratories (Raleigh, NC, USA) for microbial sequencing. To prepare the samples for sequencing, the Ion Chef instrument was employed, and the sequencing was conducted on the Ion S5 system (Thermo Fisher, Wilmington, DE, USA). The amplification of variable regions V2, V3, V4, V6, V7, V8, and V9 of the 16S rRNA gene was accomplished using the Ion 16S Metagenomics Kit 113 (Thermo Fisher Scientific). The obtained sequences were then processed using the Torrent Suite Software (version 5.2.2) (Thermo Fisher Scientific), resulting in raw unaligned sequence data files for subsequent analysis. For the analysis of the sequence data, including alignment to the GreenGenes and MicroSeq databases, generation of alpha and beta diversity plots, and creation of an operational taxonomic unit (OTU) table, the Ion Reporter Software Suite (version 5.2.2) of bioinformatics analysis tools (Thermo Fisher Scientific) was employed. The Ion Reporter’s Metagenomics 16S workflow powered by Qiime (version w1.1) was utilized to analyze the samples. Before statistical analysis, the OTU data were converted to relative abundance. The OTU with a relative abundance of less than 0.05% at each level were combined and labeled as “Others” as previously reported by Deng et al. [32]. The microbial diversity was evaluated by alpha-diversity (Chao1, Shannon, and Simpson) and beta-diversity (Bray–Curtis distance) following Deng et al. [33].

Biomarkers associated with microbial cell wall

The mid-jejunal tissue was used to extract the total RNA using TRIzol reagent (Thermo Fisher Scientific) as previously described by Duarte and Kim [34]. The concentration of total RNA was measured using a nano-volume spectrophotometer. The complementary DNA was synthesized using 1 µg of total RNA and the oligo dT and M-MLV Reverse Transcriptase (Thermo Fisher Scientific) according to the manufacturer’s instructions. Relative levels of messenger ribonucleic acid (mRNA) were measured by quantitative real-time polymerase chain reaction (PCR) using Applied Biosystems SYBR Green PCR Master Mix (Thermo Fisher Scientific) and a QS5 Real-Time PCR System. The Ct of housekeeping gene β-actin or Villin did not differ among dietary treatments. The relative expression of each gene was normalized to β-actine or Villin using the delta–delta–Ct method as described previously [35] and expressed as the level relative to β-actine or Villin. All primers (Table 2) were verified for melting curve, efficiency (100% ± 10%), and linearity (r2 ≥ 0.99) of amplification.

Table 2 Sequence of primers for intestinal markers in the jejunum
Full size table

Immune parameters and oxidative stress

Before assays, 1 g of the jejunal mucosa samples was mixed with 1 mL of phosphate-buffered saline (PBS) and homogenized on ice using a tissue homogenizer. The mixture was subjected to centrifugation at 13,000 × g for 15 min. The resulting supernatant was carefully collected and divided into five sets, each containing 150 µL of the sample, and subsequently stored at −80 °C to maintain their integrity for subsequent analysis.

The concentrations of protein, tumor necrosis factor-alpha (TNF-α), interleukin 8 (IL-8), malondialdehyde (MDA), and protein carbonyl were determined using colorimetric methods. Commercially available assay kits were employed, following the instructions provided by the manufacturers. Absorbance readings were obtained using an ELISA plate reader (Synergy HT, BioTek Instruments, Winooski, VT, USA) and analyzed with Gen5 Data Analysis Software (BioTek Instruments). The concentrations were calculated based on the standard curve generated from the known concentrations and corresponding absorbance values of the standards.

The concentration of total protein in the jejunum mucosa was determined using the BCA (bicinchoninic acid) Protein Assay (23225#, Thermo Fisher Scientific) following the protocol described by Cheng et al. [36]. Before analysis, the samples were diluted (1:60) in PBS to ensure they fell within the working range of 0 to 2,000 µg/mL. The absorbance was then measured at 562 nm. The obtained total protein concentration was utilized to normalize the concentrations of TNFα, IL-8, MDA, and protein carbonyl.

The concentration of TNF-α in the mucosa was measured using the Porcine TNF-alpha Quantikine ELISA Kit (PTA00; R&D System Inc., Minneapolis, MN, USA), following the method described by Deng et al. [32]. The standard was used within a working range of 0 to 1,500 pg/mL. Absorbance readings were taken at 450 and 550 nm, and the TNF-a concentration in the mucosa was expressed as pg/mg protein. The concentration of IL-8 in the mucosa was measured using the Porcine IL-8/CXCL8 Quantikine ELISA Kit (P8000; R&D System), following the method described by Jang et al. [37]. The standard was used within a working range of 0 to 2,000 pg/mL. Absorbance readings were taken at 450 and 550 nm, and the IL-8 concentration in the mucosa was expressed as ng/mg protein.

For the measurement of MDA concentrations in the mucosa, the OxiSelect TBARS Assay Kit (STA-330, Cell Biolabs, San Diego, CA, USA) was utilized. The MDA standard was used within a working range of 0 to 125 mmol/L. The absorbance at 532 nm was measured, and the MDA concentration was expressed as nmol/mg protein. The concentration of protein carbonyl was determined using the OxiSelect Protein Carbonyl ELISA Kit (STA-310, Cell Biolabs, CA, USA). Before measurement, mucosa samples were diluted in PBS to achieve a protein concentration of 10 µg/mL. The standard was prepared by combining oxidized BSA and reduced BSA, resulting in a working range of 0 to 7.5 nmol/mg protein. The absorbance at 450 nm was measured, and the protein carbonyl concentration was expressed as nmol/mg protein for both serum and mucosa.

Jejunal morphology and crypt cell proliferation

Mid-jejunal tissues were used to determine intestinal morphology and crypt cell proliferation. The samples were initially fixed in 10% buffered formaldehyde for 48 h. Two sections, approximately 2 mm each, were cut from the fixed tissue, placed in a cassette, and transferred to a 70% ethanol solution. Subsequently, the samples were sent to the Histology Laboratory at the University of North Carolina (UNC School of Medicine, Chapel Hill, NC, USA) for dehydration, embedding, and Ki-67 staining. Automated Ki-67 staining was performed using the Biocare Intellipath Stainer (Biocare Medical, Pacheco, CA, USA). The primary monoclonal antibody for Ki-67 (#ACR325, Biocare Medical) was diluted 1:100 and incubated with the slides at room temperature for 30 min. Detection was done by utilizing Vector ImmPress Rabbit polymer, with staining processed by using the chromogen diaminobenzidine (DAB).

Intestinal morphology, including villus height, villus width, and crypt depth, was assessed at 40× magnification using an Olympus CX31 microscope (Lumenera Corporation, Ottawa, Canada) and Infinity 2–2 digital CCD software. Ten representative villi and crypts were selected from each pig for analysis. Villus height (VH) was measured from the tip to the junction with the crypt, while villus width was recorded at the midpoint. Crypt depth (CD) was measured from the base of the villus to the bottom of the crypt [38]. The villus height to crypt depth ratio (VH:CD) was calculated by dividing VH by CD. The percentage of Ki-67 positive cells, indicating cell proliferation within the crypts, was determined from images of 10 complete crypts captured at 100× magnification [39]. All morphological analyses were performed by the same individual, with the average of 10 measurements per sample reported as a single value.

Growth performance and fecal score

Growth performance was evaluated by measuring average daily gain (ADG), average daily feed intake (ADFI), and the gain to feed ratio (G:F) on d 0, 7, 14, 21, and 28. Health status was assessed through fecal scores recorded throughout the study. Daily fecal scores for each pig were averaged weekly (d 0 to 7, d 7 to 14, d 14 to 21, and d 21 to 28) before statistical analysis. The fecal score was based on 1 to 5 scale [40] as follows: (1) very hard and dry stool, (2) firm stool, (3) normal stool, (4) loose stool, and (5) watery stool with no shape.

Statistical analysis

Data were analyzed using the Proc mixed of SAS 9.4 software (SAS Inc., Cary, NC, USA). Dietary treatments were defined as fixed effects and the random effects were blocks. The experimental unit was the pig, individually housed and fed. The analysis of similarities (ANOSIM) was performed to evaluate the beta diversity of mucosa-associated microbiota. The data were visualized using principal coordinates analysis (PCA) based on Bray-Curtis distance. Statistical differences were considered significant with P < 0.05 and tendency with 0.05 ≤ P < 0.10.

Results

Mucosa-associated microbiota

The relative abundance of mucosa-associated microbiota at the phylum level in pigs on LPB did not differ from pigs on PC (Table 3). The relative abundances of Firmicutes and Bacteroidetes in the jejunal mucosa of pigs on PC were lower (P < 0.05) than in pigs on NC. The relative abundance of Proteobacteria in the jejunal mucosa of pigs on PC was greater (P < 0.05) than in pigs on NC. The relative abundance of Actinobacteria in the jejunal mucosa of pigs on PC was lower (P < 0.05) than in pigs on ATB.

Table 3 Relative abundance of the jejunal mucosa-associated microbiota at the phylum level in pigs challenged with F18+ Escherichia coli (E. coli) and fed diets supplemented with bacitracin or Lactobacillus postbiotics
Full size table

The relative abundance of Helicobacteraceae in the jejunal mucosa of pigs on PC was greater (P < 0.05) than in pigs on NC (Table 4). The relative abundance of Prevotellaceae and Lactobacillaceae in the jejunal mucosa of pigs on PC was lower (P < 0.05) than in pigs on NC. The relative abundance of Sphingomonadaceae, Propionibacteriaceae, Comamonadaceae, and Corynebacteriaceae in the jejunal mucosa of pigs on PC was lower (P < 0.05) than in pigs on ATB. The relative abundance of Pseudomonadaceae, Campylobacteraceae, and Others in the jejunal mucosa of pigs on PC tended to be lower (P = 0.052; 0.087; 0.083, respectively) than in pigs on ATB. The relative abundance of Lachnospiraceae in the jejunal mucosa of pigs on PC tended to be lower than in pigs on NC (P = 0.062) and LPB (P = 0.097). The relative abundance of Campylobacteraceae in the jejunal mucosa of pigs on PC tended to be lower than in pigs on NC (P = 0.062) and ATB (P = 0.087).

Table 4 Relative abundance of the jejunal mucosa-associated microbiota at the family level in pigs challenged with F18+ Escherichia coli (E. coli) and fed diets supplemented with bacitracin or Lactobacillus postbiotics
Full size table

The relative abundance of Helicobacter mastomyrinus in the jejunal mucosa of pigs on PC was greater (P < 0.05) than in pigs on NC and tended to be greater (P = 0.078) than in pigs on ATB (Table 5). The relative abundance of Prevotella copri and Prevotella stercorea in the jejunal mucosa of pigs on PC was lower (P < 0.05) than in pigs on NC, whereas the relative abundance of Prevotella stercorea in the jejunal mucosa of pigs on PC was lower (P < 0.05) than in pigs on LPB. The relative abundance of Pelomonas puraquae in the jejunal mucosa of pigs on PC tended to be lower (P = 0.070) than in pigs on ATB. The relative abundance of Lactobacillus delbrueckii in the jejunal mucosa of pigs on PC tended to be greater than in pigs on ATB (P = 0.065) and LPB (P = 0.085). The relative abundance of Propionibacterium acnes, Corynebacterium glutamicum, and Sphingomonas pseudosanguinis in the jejunal mucosa of pigs on PC was lower (P < 0.05) than in pigs on ATB. The relative abundance of Roseburia faecis in the jejunal mucosa of pigs on PC tended to be lower (P = 0.050) than in pigs on NC. The relative abundance of Dialister succinatiphilus in the jejunal mucosa of pigs on PC was lower (P < 0.05) than in pigs on LPB.

Table 5 Relative abundance of the jejunal mucosa-associated microbiota at the species level in pigs challenged with F18+ Escherichia coli (E. coli) and fed diets supplemented with bacitracin or Lactobacillus postbiotics
Full size table

The alpha diversity of mucosa-associated microbiota estimated with Chao1 in pigs on PC was lower (P < 0.05) than in pigs on NC (Fig. 1) and tended to be lower (P = 0.076) than in pigs on LPB. The alpha diversity of mucosa-associated microbiota estimated with Shannon in pigs on PC tended to be lower (P = 0.081) than in pigs on ATB. The alpha diversity of mucosa-associated microbiota estimated with Simpson in pigs on PC tended to be lower (P = 0.078) than in pigs on ATB. The microbial community was visualized using PCA based on Bray-Curtis distance, which confirmed PC changed (P < 0.05) microbiota composition in the jejunal mucosa of nursery pigs compared to NC (Fig. 2). The ATB and LPB did not affect beta diversity in pigs challenged with F18+ E. coli.

Fig. 1
figure 1

Alpha diversity (Chao1, Shannon, Simpson) of the jejunal mucosa-associated microbiota in pigs challenged with F18+ Escherichia coli (E. coli) and fed diets supplemented with bacitracin or Lactobacillus postbiotics. **P < 0.05; *0.05 ≤ P < 0.10

Fig. 2
figure 2

Principal component analysis (PCA) plot at genus level. The X-axis and Y-axis represent the principal component axes, with the percentages indicating the proportion of variation explained by each component. Points of different colors correspond to samples from different treatments, and the closer two points are, the more similar their species composition

Intestinal markers

The PC tended to reduce (P = 0.097) the relative expression of PGLYRP2A in the jejunum of nursery pigs when compared with NC, however, the ATB tended to increase (P = 0.074) PGLYRP2A when compared with PC (Fig. 3). The ATB tended to reduce (P = 0.099) the relative expression of PGLYRP3 when compared with PC. The LPB increased (P < 0.05) the relative expression of PGLYRP4 when compared with PC. The PC increased (P < 0.05) the relative expression of TLR4 when compared with NC, however, the ATB tended to reduce (P = 0.085) TLR4 when compared with PC. The PC increased (P < 0.05) the relative expression of NOD1 when compared with NC, however, the ATB and the LPB reduced (P < 0.05) when compared with PC. The PC tended to increase (P = 0.079) the relative expression of CD14 when compared with NC, however, the LPB tended to reduce (P = 0.091) when compared with PC. The ATB increased (P < 0.05) the relative expression of interferon-γ and the LPB tended to increase (P = 0.096) when compared with PC. The relative expressions of PGLYRP1, PGLYRP2B, TLR2, NOD2, CD14, CD3, and NF-κB were not affected by the treatments.

Fig. 3
figure 3

Relative gene expression of pattern recognition receptors in the jejunal mucosa of pigs challenged with F18+ Escherichia coli (E. coli) and fed diets supplemented with bacitracin or Lactobacillus postbiotics. PGLYRP, peptidoglycan recognition protein; TLR, toll-like receptor; NOD, nucleotide-binding oligomerization domain-containing protein; CD, cluster of differentiation; NF-κB, nuclear factor kappa B. **P < 0.05; *0.05 ≤ P < 0.10

Immune parameters and oxidative stress

The concentration of IL-8 in the jejunal mucosa of pigs was not affected by treatments (Table 6). The concentration of TNF-α in the jejunal mucosa of pigs fed PC tended to be higher (P = 0.084) than pigs fed NC and was higher (P < 0.05) than pigs fed ATB and LPB. The concentration of MDA in the jejunal mucosa of pigs fed PC was higher (P < 0.05) than pigs fed NC, ATB, and LPB, whereas the concentration of protein carbonyl was not affected by the treatments.

Table 6 Oxidative stress and immune parameters of pigs challenged with F18+ Escherichia coli (E. coli) and fed diets supplemented with bacitracin or Lactobacillus postbiotics
Full size table

Jejunal barrier function

The ATB tended to increase the relative expression of claudin-1 in the jejunum of pigs when compared with PC (Fig. 4). However, the relative expressions of ZO-1, occludens, and MUC2 were not affected by the treatments.

Fig. 4
figure 4

Relative gene expression of intestinal tight junction proteins and mucin in pigs challenged with F18+ Escherichia coli (E. coli) and fed diets supplemented with bacitracin or Lactobacillus postbiotics. ZO-1, zonula occluden-1; MUC2, mucin 2. **P < 0.05; *0.05 ≤ P < 0.10

Jejunal morphology and crypt cell proliferation

The villus height, villus width, crypt depth, and VH:CD in the jejunum of pigs were not affected by treatments (Table 7; Fig. 5 and 6). The crypt cell proliferation rate in pigs fed PC was higher (P < 0.05) than in pigs fed NC. The LPB did not affect the crypt cell proliferation rate in pigs challenged with F18+ E. coli.

Table 7 Jejunal morphology and crypt cell proliferation in pigs challenged with F18+ Escherichia coli (E. coli) and fed diets supplemented with bacitracin or Lactobacillus postbiotics
Full size table
Fig. 5
figure 5

Representative images of the immunohistochemistry (Ki67) staining for the jejunal morphology. A–D were representative images of intestinal morphology from treatment NC, PC, ATB, and LPB; Ten images at 40× of well-oriented villi and their associated crypts were obtained to measure villus height (from the top to the base of villus, indicated by a red double arrow line) and crypt depth (from the base of villus to the bottom of the crypt, indicated by a blue double arrow line)

Fig. 6
figure 6

Representative images of the immunohistochemistry (Ki67) staining for the proliferation cells in crypt. A–D were representative images of intestinal morphology from treatment NC, PC, ATB, and LPB. Ten images at 100× of the crypts were obtained to measure the percentage of positive Ki67 staining cells (red)

Fecal score

The fecal score of pigs was not affected by the treatments at d 7 (prior to F18+ E. coli challenge; pre-challenge), however, immediately after the challenge on d 7, pigs fed PC had higher (P < 0.05) fecal score than pigs fed NC (Table 8). At d 14 pigs fed LPB tended to have lower (P = 0.078) fecal scores than pigs fed PC, whereas the fecal score of pigs fed PC tended to be higher than pigs fed ATB at d 21 (P = 0.057) and 28 (P = 0.057).

Table 8 Fecal score of pigs challenged with F18+ Escherichia coli (E. coli) and fed diets supplemented with bacitracin or Lactobacillus postbiotics
Full size table

Growth performance

The BW of pigs was not affected by the treatments during the experimental period (Table 9). The ADG of pigs was not affected by the treatments at the pre-challenge period (d 0 to 7). However, from d 7 to 14 (post-challenge) the ADG of pigs fed PC diet tended to be lower than pigs fed NC diet (P = 0.067), whereas, in overall, no differences were found between PC vs. ATB, or PC vs. LPB. Overall, the ADFI of pigs was not affected by the treatments. However, the ADFI of pigs fed LPB was lower (P < 0.05) than pigs fed PC at d 14 to 21 and tended to be lower (P = 0.088) at d 7 to 21. The G:F of pigs was not affected by the treatments at the pre-challenge period (d 0 to 7). However, from d 7 to 14 (post-challenge) the G:F of pigs fed PC diet tended to be lower than pigs fed NC diet (P = 0.054), whereas the G:F of pigs fed LPB tended to greater than pigs fed PC in overall (P = 0.069).

Table 9 Growth performance of pigs challenged with F18+ Escherichia coli (E. coli) and fed diets supplemented with bacitracin or Lactobacillus postbiotics
Full size table

Discussion

The gastrointestinal tract is a complex ecosystem where the composition of the microbiota plays a pivotal role in shaping the immune responses of the host. The primary objective of this study was to provide a comprehensive understanding of the impact of an F18+ E. coli infection on the mucosa-associated microbiota and the immune responses in the jejunum of nursery pigs. The F18+ E. coli primarily targets the mucosa of the jejunum causing inflammation and mucosal damages in nursery pigs [7, 8, 27, 31]. The mucosa-associated microbiota plays an important role on the intestinal immune system [3, 20, 21]. On the other hand, however, the host immune system can also, modulate the microbiome within the intestine [21, 24]. Additionally, this study investigated the potential efficacy of dietary bacitracin and Lactobacillus postbiotics in mitigating or preventing the detrimental consequences induced by the infection. Understanding these interactions can provide valuable insights into strategies for promoting intestinal health and enhancing immune competence in young animals.

In the current study, pigs challenged with F18+ E. coli had modulated mucosa-associated microbiota by increasing the abundance of Proteobacteria, whereas reducing Firmicutes and Bacteroidetes. Previous studies have reported that E. coli infection can disrupt the intestinal microbiota in pigs [12, 27, 41,42,43] and humans [44, 45]. Duarte et al. [31] challenged nursery pigs with F18+ E. coli and demonstrated that F18+ E. coli counts were increased in the jejunal mucosa and fecal samples showing effectiveness of F18+ E. coli challenge. The changes in the composition of the mucosa-associated microbiota have been attributed to the disturbance of the fluidity of the intestinal electrolytes [5], characterized by the increased fecal score in this study. Enterotoxigenic E. coli secretes enterotoxins, including STa and STb, that bind to Guanylyl Cyclase C (GC-C) and sulfatide, respectively, in the enterocytes [46,47,48]. The interaction between enterotoxins and receptors on the intestinal mucosa triggers the production of cellular cyclic adenosine monophosphate (cAMP), initiating reactions that disturb the balance of electrolyte fluid in the intestine, consequently resulting in watery diarrhea [7, 49,50,51].

The disturbed electrolyte fluidity in the intestine creates favorable conditions for the proliferation of bacteria from the phylum Proteobacteria, including Helicobacter spp. [5, 29]. The high abundance of Helicobacter mastomyrinus observed in the jejunal mucosa in this study is in line with the findings reported by Duarte and Kim [27]. Helicobacter spp. are Gram-negative, aerobic microorganisms exhibiting notable motility and adherence properties [52, 53] which contribute to their advantageous establishment within the mucosal lining of the small intestine of challenged pigs. The overgrowth of Helicobacter spp., consequently resulted in reduced microbial diversity. Previous studies reported that Helicobacter is positively correlated with pro-inflammatory cytokines in the jejunal mucosa [12, 27]. Moreover, the observed increase in inflammatory microbiota and reduced microbial diversity in response to the E. coli challenge aligns with previous research that demonstrated the disruption of intestinal microbiota during pathogenic infections leading to detrimental effects on intestinal health markers [54, 55].

The use of dietary bacitracin increased the abundance of Propionibacteriaceae, Comamonadaceae, Corynebacteriaceae, and Sphingomonadaceae increasing microbial diversity. Bacitracin is a peptide produced by Bacillus subtilis that interferes with the synthesis of peptidoglycan in the growing bacterial cell [56, 57]. Recent studies have demonstrated that bacitracin can alleviate the deleterious effects of F18+ E. coli in nursery pigs under experimental conditions [12, 31]. These results are possibly due to the presence of peptidoglycan in the cell wall of Gram-negative bacteria, although at a lower level when compared with Gram-positive bacteria [58].

Similar to bacitracin, the postbiotics modulated the mucosa-associated microbiota by increasing the abundance of Prevotella stercorea, and Dialister succinatiphilus which also resulted in increased microbial diversity. Lactobacillus postbiotics have long been used to promote intestinal health, modulating the intestinal microbiota and preventing or mitigating the effects of pathogenic infection [12, 17, 59,60,61,62]. Postbiotics have been defined as a formulation of non-living microorganisms and their constituents that provide health benefits to the target host [14]. The postbiotics used in the current study contains heat-stabilized Lactobacillus fermentum and L. delbrueckii, their metabolites produced during fermentation, and bacterial debris from the spent culture. It can be speculated that these components can modulate the microbiota by increasing the competitiveness for receptors within the intestine, by directly affecting the growth of commensal bacteria, or by triggering immune responses that prevent the adherence of pathogens [63]. One component in the postbiotics used in the present study is peptidoglycan, present in the cell wall of Lactobacillus spp. Peptidoglycans can induce the production of immunoglobulins through the activation of TLR2 [22, 23]. The immunoglobulins secreted into the intestinal lumen can coat bacterial cell walls, limiting their attachment and preventing translocation to the mucosal epithelium [64,65,66].

The mucosa-associated microbiota is one of the first lines of defense against opportunistic pathogens [67, 68]. Previous studies have demonstrated that the mucosa-associated microbiota plays a significant role in shaping the immune function of the intestinal system [25,26,27, 69]. It is noteworthy that many of the genes linked to the mucosa-associated microbiota are associated with immune responses, indicating that the immune system, on the other hand, actively influences the composition of the intestinal microbiota, fostering the development of beneficial microbial communities [24, 70, 71]. Under homeostasis status, commensal bacteria, including those from the phylum Proteobacteria, can trigger the immune system and help protect the barrier integrity of the intestine [3]. However, during stressful events including weaning, or under challenging conditions, the balance of the microbiota can be disturbed, increasing the chances of opportunistic pathogens overgrowth and leading to intestinal inflammation or enteric diseases [5, 27].

The intestinal microbiota and their metabolites are sensed by PRR in epithelial cells, including enterocytes, dendritic cells, and microfold cells triggering immune responses, consequently affecting the composition of intestinal microbiota [64, 72,73,74]. In this study, pigs challenged with F18+ E. coli had increased gene expression of TLR4, CD14, and NOD1, suggesting an active host response to microbial endotoxins. Toll-like receptor 4 and CD14 are PRR expressed in epithelial cells that recognize the endotoxins produced by Gram-negative bacteria, including LPS, facilitating the production of NF-κB, TNF-α, and IL-8 [75, 76]. In addition, NOD1, a cytosolic receptor, has been shown a synergistic interaction with TLR4 playing a central role in the recognition of Gram-negative bacteria and the activation of immune responses [77, 78]. Collectively, the upregulation of PRR genes in response to the F18+ E. coli challenge suggests an activated immune response triggering a pro-inflammatory cascade. These genes are crucial components of the innate immune system, which plays a pivotal role in recognizing and responding to pathogens. The subsequent trend of increase in the concentration of TNF-α in the jejunal mucosa associated with pro-inflammatory responses further confirms the efforts of the host to combat the pathogenic challenge.

Interestingly, the bacitracin showed a trend to upregulate the gene expression of PGLYRP2A, interferon-γ, and downregulated TLR4 and NOD1. These results can be related to the modulation of the intestinal microbiota toward a more diverse and balanced composition. The postbiotics enhanced the immunocompetence of nursery pigs by increasing the expression of interferon-γ and PGLYRP4, reducing the expression of PRR genes including NOD1 and CD14, which may indicate a reduction of the pathogen invasion. The gene PGLYRP4 is mainly expressed in epithelial tissues and is been associated with changes on microbiota due to their bactericidal properties against Gram-negative and Gram-positive bacteria [79,80,81]. Interferon-γ is a vital immunoregulatory cytokine that plays a central role in combating bacterial infections [82, 83]. The increased expression of interferon-γ, PGLYRP2A, and PGLYRP4 following bacitracin and postbiotic treatments indicates an enhancement of immune responses, whereas the reduction in the expression of PRR genes including NOD1 and CD14, implies higher protection against pathogen invasion. Duarte et al. [31]. reported that the bacitracin enhanced intestinal health of nursery pigs by reducing the F18+ E. coli population and the relative abundance of Helicobacter spp. in the jejunal mucosa. Lactobacillus spp. has been associated with reduced inflammation and epithelial damage [84, 85]. The heightened inflammatory state in the challenged pigs led to an increase in oxidative damage in the jejunum. The inflammation caused by the E. coli infection can cause an unbalance in the antioxidant capacity by over-producing reactive oxygen species (ROS), resulting in oxidative damage in the intestinal mucosa [12, 29, 86]. In the current study, the concentration of MDA, a product of lipid oxidation, was increased in challenged pigs. Furthermore, an increased abundance of Proteobacteria has been associated with increased oxidative damage in the jejunal epithelium [12, 27, 29, 36]. Conversely, bacitracin and postbiotics reduced the concentration of MDA in the jejunal mucosa, possibly due to the reduction of inflammation.

Proteobacteria, including Helicobacter spp., are known to degrade the intestinal mucus layer [87, 88] further increasing inflammation and oxidative damage by reducing the physical protection from the intestine [27, 89, 90]. The reduced mucus layer in combination with the increased inflammatory response and the oxidative damage can increase the need for increased cell proliferation to promote epithelial repair. In this study, increased MUC2 gene expression in the challenged group was observed, which indicates that the challenged pigs attempted to repair the damaged mucus layer. The cell proliferation rate in the crypt, reported as Ki67+, was increased in pigs challenged with F18+ E. coli. This result agrees with previous reports [12, 37] that reported increased cell proliferation in the jejunum of pigs challenged with F18+ E. coli. However, other parameters of intestinal morphology did not differ among treatments. In this study, crypt depth was not influenced by the treatment regardless of increased percentage of cells newly proliferating. Crypt cell proliferation was expressed by the percentage of proliferating cells, and it does not indicate the number of proliferating cells. Crypt depth could be extended if the number of proliferating cells increases whereas changes of the percentage of proliferating cells may not directly affect the crypt depth.

The growth performance reported in this study was not affected by the treatments, possibly due to the mild diarrhea caused by the F18+ E. coli challenge. Furthermore, it is important to mention that the results reported in the current study are from 21 d after the inoculation, indicating a long-lasting effect of F18+ E. coli infection on the mucosa-associated microbiota, as previously reported [27, 29]. The F18+ E. coli challenge employed is representative of a common pathogenic threat faced by nursery pigs around the world. Therefore, the findings presented in this study shed light on the significant impact of dietary interventions on mucosa-associated microbiota composition, immune responses through the modulation of PRR, and oxidative damage in nursery pigs challenged with F18+ E. coli. Furthermore, the understanding of the microbial and immunological responses in nursery pigs when exposed to F18+ E. coli infection suggests practical approaches for managing and preventing the deleterious effects of infections. The utilization of dietary Lactobacillus postbiotics emerges as a promising avenue for preventing enteric infection.

Conclusion

The F18+ E. coli challenge increased harmful bacteria associated with the jejunal mucosa, upregulating the expression of pathogen recognition genes, including TLR4, CD14, and NOD1, increasing the production of cytokines associated with pro-inflammatory response. Bacitracin increased the abundance of beneficial bacteria showing a trend towards increasing the intestinal barrier function, possibly by reducing the expression of genes associated with pathogen recognition. Lactobacillus postbiotics enhanced the immunocompetence of nursery pigs by increasing the expression of interferon-γ and PGLYRP4, and by reducing the expression of genes associated with pathogen recognition (TLR4, NOD1, and CD14), which indicates reduced pathogen invasions.

Data Availability

All data generated or analyzed during this study are available from the corresponding author upon reasonable request.

Abbreviations

  • CD:: Cluster of differentiation
  • E. coli :: Escherichia coli
  • GC-C:: Guanylyl cyclase C
  • IL-8:: Interleukin 8
  • MDA:: Malondialdehyde
  • NF-κB:: Nuclear factor kappa B
  • NOD:: Nucleotide-binding oligomerization domain-containing protein
  • OTU:: Operational taxonomic unit
  • PRR:: Pattern recognition receptors
  • PGLYRP:: Peptidoglycan recognition protein
  • TLR:: Toll-like receptor
  • TNF-α:: Tumor necrosis alpha

References

  1. 1.Kim SW, Duarte ME. Understanding intestinal health in nursery pigs and the relevant nutritional strategies. Anim Biosci. 2021;34(3).(2021)21.0010.: 338.
    10.5713/ab.21.0010
    Article|CAS|PubMed|Google Scholar
  2. 2.Smith F, Clark JE, Overman BL, Tozel CC, Huang JH, Rivier JEF, et al. Early weaning stress impairs development of mucosal barrier function in the porcine intestine. Am J Physiol Liver Physiol. 2010;298(3).(2010)00081.2009.
    10.1152/ajpgi.00081.2009
    Article|CAS|PubMed|Google Scholar
  3. 3.Duarte ME, Kim SW. Intestinal microbiota and its interaction to intestinal health in nursery pigs. Anim Nutr. 2022;8(1).(2022)05.001.: 169.
    10.1016/j.aninu.2021.05.001
    Article|CAS|PubMed|Google Scholar
  4. 4.Melkebeek V, Rasschaert K, Bellot P, Tilleman K, Favoreel H, Deforce D, et al. Targeting aminopeptidase N, a newly identified receptor for F4ac fimbriae, enhances the intestinal mucosal immune response. Mucosal Immunol. 2012;5(6).(2012)635–45. https://doi. org/10.1038/mi.: 635.
    10.1038/mi.2012.37
    Article|CAS|PubMed|Google Scholar
  5. 5.Gresse R, Chaucheyras-Durand F, Van de Fleury MA, Forano E, Blanquet-Diot S. Gut microbiota dysbiosis in postweaning piglets.(2017)understanding thekeys to health.Trends Microbiol.: 851.
    10.1016/j.tim.2017.05.004
    Article|CAS|PubMed|Google Scholar
  6. 6.Frömmel U, Lehmann W, Rödiger S, Böhm A, Nitschke J, Weinreich J, et al. Adhesion of human and animalEscherichia colistrains in association with their virulence-associated genes and phylogenetic origins. Appl Environ Microbiol. 2013;79(19).(2013)1128/AEM.01384-13.: 5814.
    10.1128/AEM.01384-13
    Article|CAS|PubMed|Google Scholar
  7. 7.Sun Y, Kim SW. Intestinal challenge with enterotoxigenicEscherichia coliin pigs, and nutritional intervention to prevent postweaning diarrhea. Anim Nutr. 2017;3(4).(2017)322–30. https://doi. org/10. 1016/j.aninu.: 322.
    10.1016/j.aninu.2017.10.001
    Article|CAS|PubMed|Google Scholar
  8. 8.Duarte ME, Garavito-Duarte Y, Kim SW. Impacts of F18+Escherichia colion intestinal health of nursery pigs and dietary interventions. Animals. 2023;13(17).(2023)org/10.3390/ani13172791.: 2791.
    10.3390/ani13172791
    Article|CAS|PubMed|Google Scholar
  9. 9.Sneeringer S, Bowman M, Clancy M. The US and EU animal pharmaceutical industries in the age of antibiotic resistance. ERR-264, U.S. Department of Agriculture, Economic Research Service; 2019.
    Article|CAS|PubMed|Google Scholar
  10. 10.Schoenmakers K. How China is getting its farmers to kick their antibiotics habit. Nature. 2020;586(7830).(2020)org/10.1038/d41586-020-02889-y.
    10.1038/d41586-020-02889-y
    Article|CAS|PubMed|Google Scholar
  11. 11.Pluske JR. Feed- and feed additives-related aspects of gut health and development in weanling pigs. J Anim Sci Biotechnol. 2013;4.(2013)org/10.1186/2049-1891-4-1.: 1.
    10.1186/2049-1891-4-1
    Article|CAS|PubMed|Google Scholar
  12. 12.Xu X, Duarte ME, Kim SW. Postbiotic effects ofLactobacillusfermentate on intestinal health, mucosa-associated microbiota, and growth efficiency of nursery pigs challenged with F18+Escherichia coli. J Anim Sci. 2022;100(8).(2022)org/10.1093/jas/skac210.
    10.1093/jas/skac210
    Article|CAS|PubMed|Google Scholar
  13. 13.Laird TJ, Abraham S, Jordan D, Pluske JR, Hampson DJ, Trott DJ, et al. Porcine enterotoxigenicEscherichia coli.(2021)antimicrobial resistance and development of microbial-based alternative control strategies.Vet Microbiol.: 109117.
    10.1016/j.vetmic.2021.109117
    Article|CAS|PubMed|Google Scholar
  14. 14.Salminen S, Collado MC, Endo A, Hill C, Lebeer S, Quigley EMM, et al. The International Scientific Association of Probiotics and Prebiotics (ISAPP) consensus statement on the definition and scope of postbiotics. Nat Rev Gastroenterol Hepatol. 2021;18(9).(2021)org/10.1038/s41575-021-00440-6.: 649.
    10.1038/s41575-021-00440-6
    Article|CAS|PubMed|Google Scholar
  15. 15.Gao J, Li Y, Wan Y, Hu T, Liu L, Yang S, et al. A novel postbiotic fromLactobacillus rhamnosusGG with a beneficial effect on intestinal barrier function. Front Microbiol. 2019;10.(2019)477. https://doi. org/10.3389/fmicb.: 477.
    10.3389/fmicb.2019.00477
    Article|CAS|PubMed|Google Scholar
  16. 16.Teame T, Wang A, Xie M, Zhang Z, Yang Y, Ding Q, et al. Paraprobiotics and postbiotics of probiotic lactobacilli, their positive effects on the host and action mechanisms.(2020)a review.Front Nutr.: 7.
    10.3389/fnut.2020.570344
    Article|CAS|PubMed|Google Scholar
  17. 17.Warda AK, Clooney AG, Ryan F, de Almeida Bettio PH, Di Benedetto G, Ross RP, et al. A postbiotic consisting of heat-treated lactobacilli has a bifidogenic effect in pure culture and in human fermented fecal communities. Appl Environ Microbiol. 2021;87(8).(2021)1128/AEM.02459-20.
    Article|CAS|PubMed|Google Scholar
  18. 18.Arimori Y, Nakamura R, Hirose Y, Murosaki S, Yamamoto Y, Shidara O, et al. Daily intake of heat-killedLactobacillus plantarumL-137 enhances type I interferon production in healthy humans and pigs. Immunopharmacol Immunotoxicol. 2012;34(6).(2012)937–43. https://doi. org/10.3109/08923973.: 937.
    10.3109/08923973.2012.672425
    Article|CAS|PubMed|Google Scholar
  19. 19.Canducci F, Armuzzi A, Cremonini F, Cammarota G, Bartolozzi F, Pola P, et al. A lyophilized and inactivated culture ofLactobacillus acidophilusincreases Helicobacter pylori eradication rates. Aliment Pharmacol Ther. 2000;14(12).(2000)1625–9. https://doi. org/10. 1046/j.1365-2036.: 1625.
    10.1046/j.1365-2036.2000.00885.x
    Article|CAS|PubMed|Google Scholar
  20. 20.Li D, Wu M. Pattern recognition receptors in health and diseases. Signal Transduct Target Ther. 2021;6.(2021)org/10.1038/s41392-021-00687-0.: 291.
    10.1038/s41392-021-00687-0
    Article|CAS|PubMed|Google Scholar
  21. 21.Thomson CA, Morgan SC, Ohland C, McCoy KD. From germ-free to wild.(2022)modulating microbiome complexity to understand mucosal immunology.Mucosal Immunol.: 1085.
    10.1038/s41385-022-00562-3
    Article|CAS|PubMed|Google Scholar
  22. 22.Gutzeit C, Magri G, Cerutti A. Intestinal IgA production and its role in host-microbe interaction. Immunol Rev. 2014;260(1).(2014)1111/imr.12189.: 76.
    10.1111/imr.12189
    Article|CAS|PubMed|Google Scholar
  23. 23.Ha S, Tsuji M, Suzuki K, Meek B, Yasuda N, Kaisho T, et al. Regulation of B1 cell migration by signals through Toll-like receptors. J Exp Med. 2006;203(11).(2006)2541–50. https://doi. org/10.1084/jem.: 2541.
    10.1084/jem.20061041
    Article|CAS|PubMed|Google Scholar
  24. 24.Honda K, Littman DR. The microbiota in adaptive immune homeostasis and disease. Nature. 2016;535(7610).(2016)org/10.1038/nature18848.: 75.
    10.1038/nature18848
    Article|CAS|PubMed|Google Scholar
  25. 25.Leshem A, Liwinski T, Elinav E. Immune-Microbiota interplay and colonization resistance in infection. Mol Cell. 2020;78(4).(2020)597–613. https://doi. org/10. 1016/j.molcel.: 597.
    10.1016/j.molcel.2020.03.001
    Article|CAS|PubMed|Google Scholar
  26. 26.Paone P, Cani PD. Mucus barrier, mucins and gut microbiota: the expected slimy partners? Gut. 2020;69(12):2232–43.https://doi.org/10.1136/gutjnl-2020-322260.
    Article|CAS|PubMed|Google Scholar
  27. 27.Duarte ME, Kim SW. Significance of mucosa-associated microbiota and its impacts on intestinal health of pigs challenged with F18+E. coli. Pathogens. 2022;11(5).(2022)org/10.3390/pathogens11050589.: 589.
    10.3390/pathogens11050589
    Article|CAS|PubMed|Google Scholar
  28. 28.National Research Council. Nutrient requirements of swine.(2012)Eleventh Revised Edition.Washington, DC: The National Academies Press;.
    10.17226/13298
    Article|CAS|PubMed|Google Scholar
  29. 29.Duarte ME, Tyus J, Kim SW. Synbiotic effects of enzyme and probiotics on intestinal health and growth of newly weaned pigs challenged with enterotoxigenic F18+Escherichia coli. Front Vet Sci. 2020;7.(2020)7. https://doi. org/10.3389/fvets.: 7.
    10.3389/fvets.2020.00573
    Article|CAS|PubMed|Google Scholar
  30. 30.Sun Y, Duarte ME, Kim SW. Dietary inclusion of multispecies probiotics to reduce the severity of post-weaning diarrhea caused byEscherichia coliF18+in pigs. Anim Nutr. 2021;7(2).(2021)08.012.: 326.
    10.1016/j.aninu.2020.08.012
    Article|CAS|PubMed|Google Scholar
  31. 31.Duarte ME, Stahl CH, Kim SW. Intestinal damages by F18+Escherichia coliand its amelioration with an antibacterial bacitracin fed to nursery pigs. Antioxidants. 2023;12(5).(2023)org/10.3390/antiox12051040.: 1040.
    10.3390/antiox12051040
    Article|CAS|PubMed|Google Scholar
  32. 32.Deng Z, Duarte ME, Kim SW. Efficacy of soy protein concentrate replacing animal protein supplements in mucosa-associated microbiota, intestinal health, and growth performance of nursery pigs. Anim Nutr. 2023;14.(2023)235–48. https://doi. org/10. 1016/j.aninu.: 235.
    10.1016/j.aninu.2023.06.007
    Article|CAS|PubMed|Google Scholar
  33. 33.Deng Z, Duarte ME, Jang KB, Kim SW. Soy protein concentrate replacing animal protein supplements and its impacts on intestinal immune status, intestinal oxidative stress status, nutrient digestibility, mucosa-associated microbiota, and growth performance of nursery pigs. J Anim Sci. 2022;100(10).(2022)org/10.1093/jas/skac255/6661257.
    10.1093/jas/skac255/6661257
    Article|CAS|PubMed|Google Scholar
  34. 34.Duarte ME, Kim SW. Phytobiotics from oregano extracts enhance the intestinal health and growth performance of pigs. Antioxidants. 2022;11(10).(2022)org/10.3390/antiox11102066.: 2066.
    10.3390/antiox11102066
    Article|CAS|PubMed|Google Scholar
  35. 35.Jang KB, Kim JH, Purvis JM, Chen J, Ren P, Vazquez-Anon M, et al. Effects of mineral methionine hydroxy analog chelate in sow diets on epigenetic modification and growth of progeny. J Anim Sci. 2020;98(9).(2020)org/10.1093/jas/skaa271.
    10.1093/jas/skaa271
    Article|CAS|PubMed|Google Scholar
  36. 36.Cheng Y-C, Duarte ME, Kim SW. Nutritional and functional values of lysedCorynebacterium glutamicumcell mass for intestinal health and growth of nursery pigs. J Anim Sci. 2021;99(12).(2021)org/10.1093/jas/skab331.
    10.1093/jas/skab331
    Article|CAS|PubMed|Google Scholar
  37. 37.Jang KB, Moita VHC, Martinez N, Sokale A, Kim SW. Efficacy of zinc glycinate reducing zinc oxide on intestinal health and growth of nursery pigs challenged with F18+Escherichia coli. J Anim Sci. 2023;101.(2023)org/10.1093/jas/skad035.: 101.
    10.1093/jas/skad035
    Article|CAS|PubMed|Google Scholar
  38. 38.Chen H, Zhang S, Park I, Kim SW. Impacts of energy feeds and supplemental protease on growth performance, nutrient digestibility, and gut health of pigs from 18 to 45 kg body weight. Anim Nutr. 2017;3.(2017)359–65. https://doi. org/10. 1016/j.aninu.: 359.
    10.1016/j.aninu.2017.09.005
    Article|CAS|PubMed|Google Scholar
  39. 39.Duarte ME, Zhou FX, Dutra WM, Kim SW. Dietary supplementation of xylanase and protease on growth performance, digesta viscosity, nutrient digestibility, immune and oxidative stress status, and gut health of newly weaned pigs. Anim Nutr. 2019;5.(2019)351–8. https://doi. org/10. 1016/j.aninu.: 351.
    10.1016/j.aninu.2019.04.005
    Article|CAS|PubMed|Google Scholar
  40. 40.Jang KB, Purvis JM, Kim SW. Dose–response and functional role of whey permeate as a source of lactose and milk oligosaccharides on intestinal health and growth of nursery pigs. J Anim Sci. 2021;99(1).(2021)org/10.1093/jas/skab008/6089171.
    10.1093/jas/skab008/6089171
    Article|CAS|PubMed|Google Scholar
  41. 41.Kim K, Song M, Liu Y, Ji P. EnterotoxigenicEscherichia coliinfection of weaned pigs.(2022)intestinal challenges and nutritional intervention to enhance disease resistance.Front Immunol.: 13.
    10.3389/fimmu.2022.885253
    Article|CAS|PubMed|Google Scholar
  42. 42.Barba-Vidal E, Castillejos L, López-Colom P, Rivero Urgell M, Moreno Muñoz JA, Martín-Orúe SM. Evaluation of the probiotic strainBifidobacterium longumsubsp. infantis CECT 7210 capacities to improve health status and fight digestive pathogens in a piglet model. Front Microbiol. 2017;8.(2017)8. https://doi. org/10.3389/fmicb.: 8.
    10.3389/fmicb.2017.00533
    Article|CAS|PubMed|Google Scholar
  43. 43.Bin P, Tang Z, Liu S, Chen S, Xia Y, Liu J, et al. Intestinal microbiota mediates EnterotoxigenicEscherichia coli-induced diarrhea in piglets. BMC Vet Res. 2018;14.(2018)org/10.1186/s12917-018-1704-9.: 385.
    10.1186/s12917-018-1704-9
    Article|CAS|PubMed|Google Scholar
  44. 44.Sauvaitre T, Van Landuyt J, Durif C, Roussel C, Sivignon A, Chalancon S, et al. Role of mucus-bacteria interactions in EnterotoxigenicEscherichia coli(ETEC) H10407 virulence and interplay with human microbiome. Npj Biofilms Microbiomes. 2022;8.(2022)org/10.1038/s41522-022-00344-6.: 86.
    10.1038/s41522-022-00344-6
    Article|CAS|PubMed|Google Scholar
  45. 45.Youmans BP, Ajami NJ, Jiang Z-D, Campbell F, Wadsworth WD, Petrosino JF, et al. Characterization of the human gut microbiome during travelers’ diarrhea. Gut Microbes. 2015;6(2).(2015)110–9. https://doi. org/10.1080/19490976.: 110.
    10.1080/19490976.2015.1019693
    Article|CAS|PubMed|Google Scholar
  46. 46.Butt S, Saleh M, Gagnon J. Impact of theEscherichia coliheat-stable enterotoxin b (STb) on gut health and function. Toxins (Basel). 2020;12(12).(2020)org/10.3390/toxins12120760.: 760.
    10.3390/toxins12120760
    Article|CAS|PubMed|Google Scholar
  47. 47.Wang H, Zhong Z, Luo Y, Cox E, Devriendt B. Heat-stable enterotoxins of enterotoxigenicEscherichia coliand their impact on host immunity. Toxins (Basel). 2019;11(1).(2019)org/10.3390/toxins11010024.: 24.
    10.3390/toxins11010024
    Article|CAS|PubMed|Google Scholar
  48. 48.Loos M, Geens M, Schauvliege S, Gasthuys F, van der Meulen J, Dubreuil JD, et al. Role of heat-stable enterotoxins in the induction of early immune responses in piglets after infection with enterotoxigenicEscherichia coli. PLoS ONE. 2012;7(7).(2012)pone.0041041.
    10.1371/journal.pone.0041041
    Article|CAS|PubMed|Google Scholar
  49. 49.Nagy B, Fekete PZ. EnterotoxigenicEscherichia coliin veterinary medicine. Int J Med Microbiol. 2005;295(6–7).(2005)443–54. https://doi. org/10. 1016/j.ijmm.: 443.
    10.1016/j.ijmm.2005.07.003
    Article|CAS|PubMed|Google Scholar
  50. 50.Kaper JB, Nataro JP, Mobley HLT. PathogenicEscherichia coli. Nat Rev Microbiol. 2004;2(2).(2004)org/10.1038/nrmicro818.: 123.
    10.1038/nrmicro818
    Article|CAS|PubMed|Google Scholar
  51. 51.Dubreuil JD, Isaacson RE, Schifferli DM. Animal enterotoxigenicEscherichia coli. EcoSal Plus. 2016;7(1).https.(2016)//doi. org/10. 1128/ecosalplus.esp-0006-.
    Article|CAS|PubMed|Google Scholar
  52. 52.Leser TD, Mølbak L. Better living through microbial action.(2009)the benefits of the mammalian gastrointestinal microbiota on the host.Environ Microbiol.: 2194.
    10.1111/j.1462-2920.2009.01941.x
    Article|CAS|PubMed|Google Scholar
  53. 53.Beeby M. Motility in the epsilon-proteobacteria. Curr Opin Microbiol. 2015;28.(2015)115–21. https://doi. org/10. 1016/j.mib.: 115.
    10.1016/j.mib.2015.09.005
    Article|CAS|PubMed|Google Scholar
  54. 54.Fouhse JM, Zijlstra RT, Willing BP. The role of gut microbiota in the health and disease of pigs. Anim Front. 2016;6(3).(2016)30–6. https://doi. org/10.2527/af.: 30.
    10.2527/af.2016-0031
    Article|CAS|PubMed|Google Scholar
  55. 55.Daniel H. Diet and the gut microbiome.(2020)from hype to hypothesis.Br J Nutr.: 521.
    10.1017/S0007114520001142
    Article|CAS|PubMed|Google Scholar
  56. 56.Tay WM, Epperson JD, da Silva GFZ, Ming L-J. H NMR, mechanism, and mononuclear oxidative activity of the antibiotic metallopeptide bacitracin.(2010)the role of D-Glu-4, interaction with pyrophosphate moiety, DNA binding and cleavage, and bioactivity.J Am Chem Soc.: 5652.
    10.1021/ja910504t
    Article|CAS|PubMed|Google Scholar
  57. 57.Mascher T, Margulis NG, Wang T, Ye RW, Helmann JD. Cell wall stress responses inBacillus subtilis.(2003)the regulatory network of the bacitracin stimulon.Mol Microbiol.: 1591.
    10.1046/j.1365-2958.2003.03786.x
    Article|CAS|PubMed|Google Scholar
  58. 58.Cheng Y-C, Kim SW. Use of microorganisms as nutritional and functional feedstuffs for nursery pigs and broilers. Animals. 2022;12(22).(2022)org/10.3390/ani12223141.: 3141.
    10.3390/ani12223141
    Article|CAS|PubMed|Google Scholar
  59. 59.Coconnier M-H, Liévin V, Lorrot M, Servin AL. Antagonistic activity ofLactobacillus acidophilusLB against intracellularSalmonella entericaserovar Typhimurium infecting human enterocyte-like Caco-2/TC-7 cells. Appl Environ Microbiol. 2000;66(3).(2000)1152–7. https://doi. org/10. 1128/AEM. 66. 3.1152-1157.: 1152.
    10.1128/AEM.66.3.1152-1157.2000
    Article|CAS|PubMed|Google Scholar
  60. 60.Warda AK, de Almeida Bettio PH, Hueston CM, Di Benedetto G, Clooney AG, Hill C. Oral administration of heat-treated lactobacilli modifies the murine microbiome and reducesCitrobacterinduced colitis. Front Microbiol. 2020;11.(2020)11. https://doi. org/10.3389/fmicb.: 11.
    10.3389/fmicb.2020.00069
    Article|CAS|PubMed|Google Scholar
  61. 61.Murosaki S, Yamamoto Y, Ito K, Inokuchi T, Kusaka H, Ikeda H, et al. Heat-killedLactobacillus plantarumL-137 suppresses naturally fed antigen–specific IgE production by stimulation of IL-12 production in mice. J Allergy Clin Immunol. 1998;102(1).(1998)org/10.1016/S0091-6749(98)70055-7.: 57.
    10.1016/S0091-6749(98)70055-7
    Article|CAS|PubMed|Google Scholar
  62. 62.Warda AK, Rea K, Fitzgerald P, Hueston C, Gonzalez-Tortuero E, Dinan TG, et al. Heat-killed lactobacilli alter both microbiota composition and behaviour. Behav Brain Res. 2019;362.(2019)12.047.: 213.
    10.1016/j.bbr.2018.12.047
    Article|CAS|PubMed|Google Scholar
  63. 63.de Almada CN, Almada CN, Martinez RCR, Sant’Ana AS. Paraprobiotics.(2016)evidences on their ability to modify biological responses, inactivation methods and perspectives on their application in foods.Trends Food Sci Technol.: 96.
    10.1016/j.tifs.2016.09.011
    Article|CAS|PubMed|Google Scholar
  64. 64.Rios D, Wood MB, Li J, Chassaing B, Gewirtz AT, Williams IR. Antigen sampling by intestinal M cells is the principal pathway initiating mucosal IgA production to commensal enteric bacteria. Mucosal Immunol. 2016;9(4).(2016)2015.121.: 907.
    10.1038/mi.2015.121
    Article|CAS|PubMed|Google Scholar
  65. 65.Brandtzaeg P. Induction of secretory immunity and memory at mucosal surfaces. Vaccine. 2007;25(30).(2007)12.001.: 5467.
    10.1016/j.vaccine.2006.12.001
    Article|CAS|PubMed|Google Scholar
  66. 66.Macpherson AJ, Geuking MB, McCoy KD. Immune responses that adapt the intestinal mucosa to commensal intestinal bacteria. Immunology. 2005;115(2).(2005)153–62. https://doi. org/10. 1111/j.1365-2567.: 153.
    10.1111/j.1365-2567.2005.02159.x
    Article|CAS|PubMed|Google Scholar
  67. 67.Ma N, Guo P, Zhang J, He T, Kim SW, Zhang G, et al. Nutrients mediate intestinal bacteria-mucosal immune crosstalk. Front Immunol. 2018;9.(2018)5. https://doi. org/10.3389/fimmu.: 5.
    10.3389/fimmu.2018.00005
    Article|CAS|PubMed|Google Scholar
  68. 68.Shi N, Li N, Duan X, Niu H. Interaction between the gut microbiome and mucosal immune system. Mil Med Res. 2017;4(1).(2017)org/10.1186/s40779-017-0122-9.: 14.
    10.1186/s40779-017-0122-9
    Article|CAS|PubMed|Google Scholar
  69. 69.Bouskra D, Brézillon C, Bérard M, Werts C, Varona R, Boneca IG, et al. Lymphoid tissue genesis induced by commensals through NOD1 regulates intestinal homeostasis. Nature. 2008;456(7221).(2008)org/10.1038/nature07450.: 507.
    10.1038/nature07450
    Article|CAS|PubMed|Google Scholar
  70. 70.Frantz AL, Rogier EW, Weber CR, Shen L, Cohen DA, Fenton LA, et al. Targeted deletion of MyD88 in intestinal epithelial cells results in compromised antibacterial immunity associated with downregulation of polymeric immunoglobulin receptor, mucin-2, and antibacterial peptides. Mucosal Immunol. 2012;5(5).(2012)501–12. https://doi. org/10.1038/mi.: 501.
    10.1038/mi.2012.23
    Article|CAS|PubMed|Google Scholar
  71. 71.Daniel N, Lécuyer E, Chassaing B. Host/microbiota interactions in health and diseases—time for mucosal microbiology! Mucosal Immunol. 2021;14(5).(2021)org/10.1038/s41385-021-00383-w.: 1006.
    10.1038/s41385-021-00383-w
    Article|CAS|PubMed|Google Scholar
  72. 72.Royet J, Gupta D, Dziarski R. Peptidoglycan recognition proteins.(2011)modulators of the microbiome and inflammation.Nat Rev Immunol.: 837.
    10.1038/nri3089
    Article|CAS|PubMed|Google Scholar
  73. 73.Wolf AJ, Underhill DM. Peptidoglycan recognition by the innate immune system. Nat Rev Immunol. 2018;18(4).(2018)2017.136.: 243.
    10.1038/nri.2017.136
    Article|CAS|PubMed|Google Scholar
  74. 74.Ruemmele FM, Beaulieu JF, Dionne S, Levy E, Seidman EG, Cerf-Bensussan N, et al. Lipopolysaccharide modulation of normal enterocyte turnover by toll-like receptors is mediated by endogenously produced tumour necrosis factor α. Gut. 2002;51(6).(2002)6.842.: 842.
    10.1136/gut.51.6.842
    Article|CAS|PubMed|Google Scholar
  75. 75.von der Stephens M. Lipopolysaccharides modulate intestinal epithelial permeability and inflammation in a species-specific manner. Gut Microbes. 2020;11(3).(2020)2019.1629235.: 421.
    10.1080/19490976.2019.1629235
    Article|CAS|PubMed|Google Scholar
  76. 76.Jin J, Jia J, Zhang L, Chen Q, Zhang X, Sun W, et al. Jejunal inflammatory cytokines, barrier proteins and microbiome-metabolome responses to early supplementary feeding of Bamei suckling piglets. BMC Microbiol. 2020;20.(2020)org/10.1186/s12866-020-01847-y.: 169.
    10.1186/s12866-020-01847-y
    Article|CAS|PubMed|Google Scholar
  77. 77.Trindade BC, Chen GY. NOD1 and NOD2 in inflammatory and infectious diseases. Immunol Rev. 2020;297(1).(2020)1111/imr.12902.: 139.
    10.1111/imr.12902
    Article|CAS|PubMed|Google Scholar
  78. 78.Wang J, Pan ZY, Zheng XR, Wu ZC, Su XM, Zhu GQ, et al. TLR4 gene expression in pig populations and its association with resistance toEscherichia coliF18. Genet Mol Res. 2013;12(3).(2013)2625–32. https://doi. org/10.4238/.: 2625.
    10.4238/2013.July.30.1
    Article|CAS|PubMed|Google Scholar
  79. 79.Dziarski R, Gupta D. The peptidoglycan recognition proteins (PGRPs). Genome Biol. 2006;7(8).(2006)232. https://doi. org/10.1186/gb-.: 232.
    10.1186/gb-2006-7-8-232
    Article|CAS|PubMed|Google Scholar
  80. 80.Lu X, Wang M, Qi J, Wang H, Li X, Gupta D, et al. Peptidoglycan recognition proteins are a new class of human bactericidal proteins. J Biol Chem. 2006;281(9).(2006)1074/jbc.M511631200.: 5895.
    10.1074/jbc.M511631200
    Article|CAS|PubMed|Google Scholar
  81. 81.Wang M, Liu L-H, Wang S, Li X, Lu X, Gupta D, et al. Human peptidoglycan recognition proteins require zinc to kill both gram-positive and gram-negative bacteria and are synergistic with antibacterial peptides. J Immunol. 2007;178(5).(2007)5.3116.: 3116.
    10.4049/jimmunol.178.5.3116
    Article|CAS|PubMed|Google Scholar
  82. 82.Flynn JL, Chan J, Triebold KJ, Dalton DK, Stewart TA, Bloom BR. An essential role for interferon gamma in resistance toMycobacterium tuberculosisinfection. J Exp Med. 1993;178(6).(1993)6.2249.: 2249.
    10.1084/jem.178.6.2249
    Article|CAS|PubMed|Google Scholar
  83. 83.Schaut RG, Palmer MV, Boggiatto PM, Kudva IT, Loving CL, Sharma VK. Mucosal IFNγ production and potential role in protection inEscherichia coliO157.(2021)H7 vaccinated and challenged cattle.Sci Rep.: 9769.
    10.1038/s41598-021-89113-7
    Article|CAS|PubMed|Google Scholar
  84. 84.Zhang L, Li N, Caicedo R, Neu J. Alive and deadLactobacillus rhamnosusGG decrease tumor necrosis factor-α–induced interleukin-8 production in Caco-2 cells. J Nutr. 2005;135(7).(2005)7.1752.: 1752.
    10.1093/jn/135.7.1752
    Article|CAS|PubMed|Google Scholar
  85. 85.Ko JS.Lactobacillus plantaruminhibits epithelial barrier dysfunction and interleukin-8 secretion induced by tumor necrosis factor-α. World J Gastroenterol. 2007;13(13).(2007)i13.1962.: 1962.
    10.3748/wjg.v13.i13.1962
    Article|CAS|PubMed|Google Scholar
  86. 86.Gagné F. Oxidative stress. Biochem Ecotoxicol.(2014)Principles and Methods.Elsevier;.
    Article|CAS|PubMed|Google Scholar
  87. 87.Zhang W, Zhu Y-H, Zhou D, Wu Q, Song D, Dicksved J, et al. Oral administration of a select mixture ofBacillusprobiotics affects the gut microbiota and goblet cell function followingEscherichia colichallenge in newly weaned pigs of genotype MUC4 that are supposed to be enterotoxigenicE. ColiF4ab/ac receptor. Appl Environ Microbiol. 2017;83(3).https.(2017)1128/AEM.02747-16.
    Article|CAS|PubMed|Google Scholar
  88. 88.Pan M, Barua N, Ip M. Mucin-degrading gut commensals isolated from healthy faecal donor suppress intestinal epithelial inflammation and regulate tight junction barrier function. Front Immunol. 2022;13.(2022)13. https://doi. org/10.3389/fimmu.: 13.
    10.3389/fimmu.2022.1021094
    Article|CAS|PubMed|Google Scholar
  89. 89.Flynn JM, Niccum D, Dunitz JM, Hunter RC. Evidence and role for bacterial mucin degradation in cystic fibrosis airway disease. PLOS Pathog. 2016;12(8).(2016)ppat.1005846.
    10.1371/journal.ppat.1005846
    Article|CAS|PubMed|Google Scholar
  90. 90.Belzer C. Nutritional strategies for mucosal health.(2022)the interplay between microbes and mucin glycans.Trends Microbiol.: 13.
    10.1016/j.tim.2021.06.003
    Article|CAS|PubMed|Google Scholar

Acknowledgements

The authors acknowledge Dr. Erik Eckhardt at Adare Biome (Houdan, France) and all the member of Kim Lab at North Carolina State University for their technical supports.

Funding

This study was awarded and funded by USDA-NIFA Hatch Fund (#02636, Washington DC, USA), North Carolina Agricultural Foundation (#660101, Raleigh, NC, USA), and Adare Biome (Houdan, France).

Ethics Declaration

Ethics approval and consent to participate

The Institutional Animal Care and Use Committee of North Carolina State University (Raleigh, NC, USA) revised and approved the protocol used for this study.

Consent for publication

Not applicable.

Competing interests

All authors have no conflict of interest.

Rights and Permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ . The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/ ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Reprints and permissions