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. 2023 Nov 30;103(2):103334. doi: 10.1016/j.psj.2023.103334

Differential cytokine profiling and microbial species involved in cecal microbiota modulations in SPF chicks immunized with a dual vaccine against Salmonella Typhimurium infection

Tong-Rong Jan *, Chen-Si Lin *,†, Wen-Yuan Yang *,†,1
PMCID: PMC10765113  PMID: 38104411

Abstract

Salmonella Typhimurium (ST) infection in laying hens is a significant threat to public health and food safety. Host resistance against enteric pathogen invasion primarily relies on immunity and gut barrier integrity. This study applied the ST infection model and a dual live vaccine containing Salmonella Enteritidis (SE) strain Sm24/Rif12/Ssq and ST strain Nal2/Rif9/Rtt to investigate the cellular cytokine expression profiles and the differential community structure in the cecal microbiota of specific-pathogen-free (SPF) chicks and field-raised layers. The results showed that ST challenge significantly upregulated expressions of IL-1β in SPF chicks. Vaccination, on the other hand, led to an elevation in IFNγ expression and restrained IL-1β levels. In the group where vaccination preceded the ST challenge (S.STvc), heightened expressions of IL-1β, IL-6, IL-10, and IL-12β were observed, indicating active involvement of both humoral and cell-mediated immunity in the defense against ST. Regarding the cecal microbiota, the vaccine did not affect alpha diversity nor induce a significant shift in the microbial community. Conversely, ST infection significantly affected the alpha and beta diversity in the cecal microbiota, reducing beneficial commensal genera, such as Blautia and Subdoligranulum. MetagenomeSeq analysis reveals a significant increase in the relative abundance of Faecalibacterium prausnitzii in the groups (S.STvc and STvc) exhibiting protection against ST infection. LEfSe further demonstrated Faecalibacterium prausnitzii as the prominent biomarker within the cecal microbiota of SPF chicks and field layers demonstrating protection. Another biomarker identified in the S.STvc group, Eubacterium coprostanoligenes, displayed an antagonistic relationship with Faecalibacterium prausnitzii, suggesting the limited biological significance of the former in reducing cloacal shedding and tissue invasion. In conclusion, the application of AviPro Salmonella DUO vaccine stimulates host immunity and modulates cecal microbiota to defend against ST infection. Among the microbial modulations observed in SPF chicks and field layers with protection, Faecalibacterium prausnitzii emerges as a significant species in the ceca. Further research is warranted to elucidate its role in protecting layers against ST infection.

Key words: Salmonella Typhimurium, layers, immune response, gut microbiota, full-length 16S rRNA metagenomics

INTRODUCTION

Nontyphoidal Salmonellae (NTS) are one of the leading pathogens of bacterial foodborne illnesses in humans. Salmonella Enteritidis (SE) and Salmonella Typhimurium (ST) are the most prevalent serovars within this group, affecting a wide range of animals (Hugas and Beloeil, 2014). Emerging evidence links human foodborne gastroenteritis to these zoonotic infections (Fearnley et al., 2011; Moffatt et al., 2016). Their contamination of eggs and poultry meat poses a significant threat to public health. In recent decades, antimicrobial agents have been extensively used to control Salmonella invasion in poultry to alleviate intestinal inflammation, barrier dysfunction, dysbiosis, and impairment of growth performance (Zhang et al., 2020). Nevertheless, concerns about bacterial resistance and antibiotic residues in chicken products have led to restrictions on the use of antimicrobials in poultry (M'Ikanatha et al., 2010). Consequently, commercial poultry operations are increasingly adopting eradication or vaccination strategies to control Salmonella infection within their flocks.

NTS vaccines aim to establish immunity in chickens against Salmonella infections, thus lowering the risk of carcass or egg contamination. Considering the capacity of Salmonella to persist extracellularly and intracellularly within hosts (Hohmann, 2001), vaccines that stimulate both humoral and cell-mediated immunity are more effective in conferring protection against Salmonella (Clark-Curtiss and Curtiss, 2018). Among various vaccine types, live attenuated vaccines can induce both humoral and cell-mediated immunity. As a result, they are regularly applied in layers to provide continuous immunity over their relatively long lifespan (Eeckhaut et al., 2018). This approach helps decrease tissue colonization, bacterial shedding, and the risk of horizontal transmission and egg contamination. Furthermore, the engagement of antibodies and T cells provides comprehensive protection (Mastroeni and Grant, 2011).

The cecal microbiome helps maintain intestinal health and optimize growth performance in poultry. It also serves as a protective barrier that hinder the colonization of zoonotic pathogens (Shini et al., 2013). In newly hatched chicks, the intestinal microbiota typically exhibits a limited microbial diversity. During this stage, Salmonella invasion and proliferation regularly leads to persistent infection and continuous shedding in fecal droppings (Van Immerseel et al., 2004). Conversely, administering probiotics to young chicks has been shown to enhance the functionality of the gut barrier. This intervention significantly reduces Salmonella colonization and alleviates gut damage (Shao et al., 2022). Hence, the modulation of the chicken gut microbiota in early stages promotes the host's resistance to pathogens. As chicks develop, their microbial composition gradually becomes more diverse. This forms a complex community structure that offers defense against opportunistic infection through competitive exclusion. In layers, cecal colonization of Salmonella often leads to intermittent shedding throughout their productive lifetime (Pande et al., 2016; McWhorter and Chousalkar, 2018). Therefore, modulation of cecal microbiota in laying hens presents a promising alternative approach to mitigating ST shedding and ensuring the production of safe chicken products.

Here, we applied the ST infection model using strain 9098 Nalres and AviPro Salmonella Duo vaccine to develop 4 treatments for comparative analysis. The purpose was to investigate the cellular cytokine expression profiles in chickens exposed to ST infection, vaccination, and the sequential administration of the vaccine followed by a challenge with ST. We also explored the differential community structure in cecal microbiota among these diverse treatments. Biomarkers involved in cecal microbiota modulations were identified through a bioinformatics analysis approach. Two distinct categories of layer chickens—specific pathogen-free (SPF) chicks and field layers—were included to assess the consistency of the observations. The discovery of microbial species linked to the suppression of ST shedding and tissue colonization in layers holds the potential to be the candidate strain for modulating the cecal microbiota of laying hens.

MATERIALS AND METHODS

Experimental Design

Two trials were conducted within the animal biosafety level (ABSL)-2 poultry facility at the Animal Resource Center of National Taiwan University (NTU). The details of the experimental design are provided in Table 1. The experimental protocol received ethical approval from the NTU Institutional Animal Care and Use Committee (NTU-109-EL-00115 and NTU-109-EL-00160).

Table 1.

Experimental designs of trial 1 and trial 2.

Trial Group N Treatment Strain and dosage
 Sampling time
Vaccine
 ST
Treatment Oral route Time Oral route Time
1 S.STvc 12 Vaccination + ST AviPro Salmonella DUO
(1 dose/chick)		 d 2 9098 Nalres
(1.3 × 109 CFU/chick)		 14 dpv 14 dpc
S.STc 12 ST - - 9098 Nalres
(1.3 × 109 CFU/chick)		 14 dpv 14 dpc
S.Vc 12 Vaccination AviPro Salmonella DUO
(1 dose/chick)		 d 2 - 14 dpc
S.Ct 12 None - - 14 dpc
2 STvc 12 Vaccination + ST AviPro Salmonella DUO
(3 vaccinations/layer)		 d 5, wk 8, and wk 18 9098 Nalres
(2.8 × 109 CFU/layer)		 14 dpa 14 dpc
STc 12 ST - - 9098 Nalres
(2.8 × 109 CFU/layer)		 14 dpa 14 dpc
Vc 12 Vaccination AviPro Salmonella DUO
(3 vaccinations/layer)		 d 5, wk 8, and wk 18 - 14 dpc
Ct 12 None - - 14 dpc
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N: numbers of chickens; ST: Salmonella Typhimurium. -: not performed. CFU: colony-forming units.

dpv: days postvaccination; dpa: days postarrival at ABSL-2 facility; dpc: days post-ST-challenge.

Cecal tissues and contents were collected on the sampling date (14 dpc).

In trial 1, 48 two-day-old SPF chicks were randomly assigned to 4 groups (S.STvc, S.STc, S.Vc, and S.Ct) with an equal number of chicks in each group. In the S.STc and S.Vc groups, SPF chicks received ST inoculation and vaccination, respectively. SPF chicks in the S.STvc group were vaccinated with the vaccine on d 2 and orally challenged with ST 14 days postvaccination. The S.Ct group served as the negative control and received a placebo. Each group was housed in a separate cage over the 28-day experimental period and provided with feed and water ad libitum. Environmental conditions were carefully controlled, with temperature and humidity maintained at 22 ± 2℃ and 60 to 80%. On the day of allocation, SPF chicks in the S.STvc and S.Vc groups received a single oral dose of 0.3 mL of AviPro Salmonella Duo (Elanco Animal Health, Greenfield, IN). Each vaccine dose included 1 to 6 × 108 colony-forming units (CFU) of SE strain Sm24/Rif12/Ssq and 1 to 6 × 108 CFU of ST strain Nal2/Rif9/Rtt. When these chicks were 16 days old, SPF chicks in the S.STvc and S.STc groups were subjected to oral challenges with ST strain 9098 Nalres. All SPF chicks were handled with utmost care throughout the trial to minimize distress. Euthanasia was performed by inducing CO2 asphyxiation 14 d after the ST challenge.

In trial 2, 48 field layers, aged 25 wk, were randomly selected from a commercial layer farm and subsequently divided into 4 groups (STvc, STc, Vc, and Ct) with an equal number of chicks in each group. Half of these layers were sourced from a nonvaccinated flock and were assigned to the STc and Ct groups, while the remaining half originated from a vaccinated flock that received identical vaccine product as the layers in trial 1 and were designated for the STvc and Vc groups. In the original layer farm, vaccinated and nonvaccinated flocks were housed separately to avoid any potential contact between them. Within the vaccinated flock, layers received vaccinations on d 5, wk 8, and wk 18. Following the practices established in trial 1, layers in trial 2 at the ABSL-2 facility were subjected to the same housing conditions and duration. Before initiating the ST challenges, cloacal swab cultures were performed on all layers in each group to confirm the absence of Salmonella. Layers in the STvc and S.STc groups were subsequently inoculated with ST strain 9098 Nalres on d 14 after arriving at the ABSL-2 facility. Concurrently, the Vc and Ct groups were administered placebos. On d 14 post-ST challenges, all field layers were humanely euthanized through CO2 asphyxiation to collect samples.

Challenge Strain and Vaccine

The ST strain 9098 Nalres was provided by Elanco Animal Health Co., Ltd. (Elanco Animal Health, Greenfield, IN) and it was used for oral challenges in 2 trials. The original ST stock (3.2 × 1010 CFU/mL) was diluted with a phosphate-buffered saline (PBS) solution (Sigma, St. Louis, MO) to achieve a final concentration of109 CFU/mL per layer. Serotyping and serial dilution cultures on xylose lysine deoxycholate (XLD) agar (Sigma, St. Louis, MO) was used to confirm the serovar of strain and cell concentration of the oral challenge. Regarding immunization, a commercial dual vaccine, AviPro Salmonella DUO (Elanco Animal Health, Greenfield, IN), was applied in the present study. Each vaccine dose included 1 to 6 × 108 CFU of SE strain Sm24/Rif12/Ssq and 1 to 6 × 108 CFU of ST strain Nal2/Rif9/Rtt. The ST vaccine strain displayed susceptibility to erythromycin but resistance to nalidixic acid and rifampicin. The serovar of the vaccine strain and its viable cell concentration were further validated through serotyping and serial dilution cultures. AviPro Plate (Elanco Animal Health, Greenfield, IN) was conducted to determine antibiotic resistance profiles of the vaccine strain.

Microbiological Analysis

The isolation of Salmonella was executed in accordance with the procedures specified in ISO 6579:2002 (Microbiology of food and animal feeding stuff—horizontal method for detecting Salmonella spp.). In summary, the sample was introduced into buffered peptone water (Sigma, St. Louis, MO) and incubated at 37°C for 18 h. Subsequently, the solution underwent enrichment through Rappaport Vassiliadis (RV) medium (Sigma, St. Louis, MO) at 41.5°C for 24 h. The cultured broth was then streaked onto xylose lysine deoxycholate (XLD) agar (Sigma, St. Louis, MO) to facilitate the cultivation of single colonies at 41.5°C for 24 h. Serotyping was performed using plate agglutination assays with antisera targeting O and H antigens. Salmonella strains that yielded positive results in the O5, Hi, and H1 tests were identified as ST.

Sample Collection

A random sample of 6 chickens was selected from each group in each trial. Cecal contents were extracted from these selected chickens, immediately flash-frozen using dry ice and subsequently stored at −80°C for 16S rRNA metagenomic analysis. For the assessment of inflammatory-related cytokine profiles, the ceca were thoroughly dissected to expose their surfaces. The dissected tissues (n = 6 per group) were gently rinsed with a PBS solution (Sigma, St. Louis, MO) and trimmed to 0.5 cm × 0.5 cm. The cecal tissues were then submerged in 0.5 mL of RNALater (ThermoFisher Scientific, Inc., Waltham, MA) at 4℃ overnight.

Total RNA Extraction and Quantitative Reverse Transcription PCR

Cecal tissues were subjected to homogenization for RNA extraction using the MagNA Lyser (Roche, Basel, Switzerland) and MagNA pure compact RNA isolation kit (Roche, Basel, Switzerland). Subsequently, the MagNA pure compact system (Roche, Basel, Switzerland) was applied to isolate the total RNA content from the tissue solution. The concentration and quality of the isolated RNA samples were assessed using a Nanodrop One (ThermoFisher Scientific, Inc., Waltham, MA). Quantitative reverse transcription PCR (RT-qPCR) assessed the expression levels of cytokines, including interleukin-1 beta (IL-1β), interleukin-6 (IL-6), interleukin-10 (IL-10), interleukin-12 beta (IL-12β), interferon-alpha (IFNα), interferon-gamma (IFNγ), lipopolysaccharide-induced tumor necrosis factor alpha factor (LITAF), and nuclear factor-kappa-B-inhibitor alpha (NFkB1α). The extracted RNA samples underwent reverse transcription at 37℃ utilizing a high-capacity cDNA reverse transcription kit (ThermoFisher Scientific, Inc., Waltham, MA) for 120 min, following the manufacturer's instructions. The primer sequences and amplicon sizes are presented in Table 2. The qPCR reaction mixture was prepared using a 2× Power SYBR Green PCR master mix (ThermoFisher Scientific, Inc., Waltham, MA) with 200 nM of primers and the template. Three technical replicates of each mixture were concurrently applied on the Applied Biosystems 7900 HT real-time PCR system (ThermoFisher Scientific, Inc., Waltham, MA). Glyceraldehyde 3-phosphate dehydrogenase served as an internal control. Log-transformed relative quantity (Log-RQ) was calculated using the comparative CT method based on the results.

Table 2.

Nucleotide sequences of primers for quantitative reverse transcription PCR (RT-qPCR).

Target gene GenBank accession number Forward sequence (5ʹ–3ʹ) Reverse sequence (5ʹ–3ʹ) Amplicon size (bp)
IFNα AB021154 GACATCCTTCAGCATCTCTTCA AGGCGCTGTAATCGTTGTCT 238
IFNγ NM205149 AGCTGACGGTGGACCTATTATT GGCTTTGCGCTGGATTC 259
IL-1β Y15006 TGGGCATCAAGGGCTACA TCGGGTTGGTTGGTGATG 244
IL-6 NM204628 AAATCCCTCCTCGCCAATCT CCCTCACGGTCTTCTCCATAAA 106
IL-10 AJ621614 AATCACGGGCTGACTTTCAC AACTCCCCCATGGCTTTGTA 64
IL-12β NM213571 CTGTGGCTCGCACTGATAAA GGTGCTCTTCGGCAAATGG 84
LITAF NM204267 GGAATGAACCCTCCGCAGTA CTGAACTGGGCGGTCATAGA 114
NFκB1A NM001001472 GCAGATACTGCCCGAAAGTG TGTCAGCTGTCTTCCTCCAA 109
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DNA Extraction and Full-Length 16S rRNA Sequencing

CatchGene Stool DNA Kit (QIAGEN, Valencia, CA) was used to extract genomic DNA from the cecal contents according to the manufacturer's instructions. The quality of the isolated DNA was assessed through agarose gel electrophoresis and then adjusted to a concentration of 1 ng/µl using the Qubit 4.0 fluorometer (ThermoFisher Scientific, Waltham, MA). Barcoded primers (forward: 5ʹ GCATC/barcode/AGRGTTYGATYMTGGCTCAG 3ʹ, reverse: 5ʹ GCATC/barcode/RGYTACCTTGTTACGACTT 3ʹ) were utilized with the KAPA HiFi HotStart ReadyMix PCR kit (Roche, Basel, Switzerland) to amplify the entire 16S rRNA gene. The PCR program consisted of an initial denaturation at 95°C for 3 min, followed by 25 cycles of denaturation at 95°C for 30 s, annealing at 57°C for 30 s, and extension at 72°C for 60 s. After an additional extension cycle at 72°C for 5 min, PCR amplicons of approximately 1.5 kb were collected and purified using AMPure PB Beads (Pacific Biosciences, Menlo Park, CA). Subsequently, equal molar amounts of each barcoded PCR product were combined, and 500 to 1,000 ng of the pooled amplicon was used to construct libraries with the SMRTbell prep kit 3.0 (Pacific Biosciences, Menlo Park, CA). Thermocycler programs were initiated to introduce universal hairpin adapters onto DNA fragments, involving end-repair at 37℃ for 30 min, A-tailing at 65℃ for 5 min, adapter ligation at 20℃ for 30 min, and nuclease treatment at 37℃ for 15 min. The adapter dimers were purified from libraries with AMPure PB beads (Pacific Biosciences, Menlo Park, CA). Primer annealing and polymerase binding were conducted by incubating libraries with sequencing primer v4 and sequel II Binding Kit 2.1 (Pacific Biosciences, Menlo Park, CA). Finally, the circular consensus sequence (CCS) mode was launched on the PacBio Sequel IIe System (Pacific Biosciences, Menlo Park, CA) for sequencing. Highly authentic reads with a Phred scale of 30 were selected for analysis.

Statistical and Bioinformatics Analysis

Differential cytokine expression was determined using SAS software version 9.4 (SAS Institute, Inc., Cary, NC) with ANOVA or the Kruskal-Wallis test depending on the normality of the dataset. Statistical significance was set at P ≤ 0.05.

The initial polymerase reads (raw sequences) underwent quality control procedures in the bioinformatics analysis. Original sequences with overlapping counts exceeding 3 were retained to generate consensus reads. For accuracy enhancement, consensus reads were used to correct random sequencing errors on individual redundant sequences (subreads). High-quality and sufficiently long sequences (Read quality > 20) were called HiFi reads. In this study, bioinformatics processes were performed using high-quality HiFi reads (RQ > 30) achieving a base-level sequencing accuracy of 99.9%. These high-quality reads were initially analyzed using divisive amplicon denoising algorithm 2 (DADA2 version 1.14), thus generating Amplicon Sequence Variants (ASVs) (Callahan et al., 2016). The ASVs were then aligned against NCBI databases to obtain species information and to produce a species abundance table (ASVs table). This procedure was accomplished using the feature-classifier (Bokulich et al., 2018) and classify-consensus-blast algorithm (Camacho et al., 2009) in quantitative insights into microbial ecology (QIIME) software v2. Multiple sequence alignment was performed to assess the similarities of sequences among ASVs using the QIIME v2 alignment MAFFT (Katoh and Standley, 2013). The overall microbial composition within the groups was determined based on the quantity of ASVs and their corresponding sequence abundances. The top 10 taxa in relative abundance were visualized at the genus and species levels. Alpha diversity analysis evaluated species diversity, evenness, and community richness within groups using Shannon, Simpson, Pielou, and Margalef indices. Beta diversity analyses were conducted to assess the similarity in microbial community composition among different groups. The multiple response permutation procedure (MRPP) was performed to assess statistical differences in microbial community structures among groups. Principal coordinate analysis (PCoA) was used to visualize the relative positions of data points representing samples or groups, in turn facilitating assessment of their similarity. Closer data points indicate a higher degree of similarity. Hierarchical principal component analysis (PCA) was further conducted to identify the top 5 species that significantly contributed to component differences at the species level. The differential abundance of contributing species among groups was compared using QIIME v2 with the metagenomeSeq package. An analysis algorithm, linear discriminant analysis effect size (LEfSe), with a linear discriminant analysis (LDA) score of 4.0 was applied to identify biomarkers that display statistical significance and biological relevance at various taxonomic levels between groups (Segata et al., 2011).

RESULTS

Immunomodulatory Effects of Vaccination and ST Challenge in SPF Chicks

There was an upregulation of IFNα, IFNγ, IL-1β, IL-12β, and NFκB1A expression in the ceca of the S.STc group when compared to the control group (S.Ct). A statistically significant increase was observed in IL-1β levels. In comparison to the control group (S.Ct), SPF chicks receiving the vaccine (S.Vc group) increased IFNγ and IL-1β levels while simultaneously downregulating the expression of IFNα, IL-6, IL-10, and LITAF. In the group where vaccination was administered prior to the ST challenge (S.STvc), the cytokine expression profiles resembled that observed in the ST-challenged group (S.STc), except for elevated levels of IL-6 and IL-10, along with reductions in the levels of LITAF and NFκB1A. Detailed probability data are presented in Figure 1.

Figure 1.

Figure 1

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Comparative analysis of cytokine expression among groups (n = 6 per group) of specific pathogen-free (SPF) chicks. The data are presented as the log-transformed relative quantity (Log-RQ). Statistical analyses were performed using the analysis of variance (ANOVA) test or Kruskal-Wallis test based on the results of the Shapiro-Wilk test. Significance levels are denoted as * for P ≤ 0.05 and ** for P ≤ 0.01.

Microbial Community Structure Following Treatments

At the species level, Blautia hominis, Lacrimispora saccharolytica, and Negativibacillus massiliensis emerged as the most predominant taxa in the cecal microbiota of SPF chicks within the S.Ct group, as illustrated in Figure 2A. Faecalibacterium prausnitzii, Blautia hominis, and Subdoligranulum variabile were identified as the top 3 dominant species in the S.Vc group. Meanwhile, in the S.STc group, Faecalibacterium prausnitzii, Blautia hominis, and Oscillibacter valericigenes exhibited the highest abundance in the cecal microbiota. As for the S.STvc group, the cecal microbiota was characterized by Faecalibacterium prausnitzii, Blautia hominis, and Eubacterium coprostanoligenes as the top 3 dominant species. Vaccination resulted in an increase in the relative abundance of Faecalibacterium prausnitzii and Subdoligranulum variabile. When the corresponding treatments were conducted in the S.STvc group, there was an elevation in the relative abundance of Faecalibacterium prausnitzii, Blautia hominis, and Eubacterium coprostanoligenes within the cecal microbiota.

Figure 2.

Figure 2

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Microbial composition of cecal microbiota in chickens (n = 6 per group). The 10 most abundant taxa at the level of genus and species in the cecal microbiota are demonstrated. (A) SPF chicks (trial 1). (B) Field layers (trial 2). Each bar denotes the mean relative abundance of a respective taxon within a group.

In field layers within the Ct group, Lactobacillus gallinarum, Negativibacillus massiliensis, and Oscillibacter valericigenes were the top 3 abundant species in the ceca (see Figure 2B). Vaccination induced a microbial shift in bacterial composition, leading to the predominance of Subdoligranulum variabile, Negativibacillus massiliensis, and Mediterraneibacter glycyrrhizinilyticus in the cecal microbiota of the Vc group. ST challenge promoted the relative abundance of Subdoligranulum variabile, Mediterraneibacter glycyrrhizinilyticus, and Oscillibacter_valericigenes. These data establish them as the most dominant species in the STc group. Within the STvc group, Mediterraneibacter glycyrrhizinilyticus, Subdoligranulum variabile, and Negativibacillus massiliensis were ranked as the top 3 abundant taxa in the cecal microbiota. Notably, there was a decrease in the abundance of Lactobacillus gallinarum in the Vc, STc, and STvc groups.

Impact of ST Challenge on Alpha and Beta Diversity in Cecal Microbiota of SPF Chicks and Field Layers

In the S.STc group, significant reductions were observed in alpha diversity indices, including the Margalef, Pielou Evenness, Shannon Entropy, and Simpson indices, as presented in Figure 3A. ST challenge resulted in a notable decrease in community richness, evenness, and diversity in the cecal microbiota of SPF chicks. Conversely, vaccination (S.Vc) did not yield statistically significant differences in community richness, evenness, and diversity. The S.STvc group (SPF chicks received vaccination followed by a subsequent ST challenge) had a notable decrease in community richness, evenness, and diversity within the cecal microbiota. In field layers (Figure 3B), neither vaccination, ST challenge, nor their combination exhibited statistically significant impacts on the alpha diversity within the cecal microbiota.

Figure 3.

Figure 3

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Alpha diversity in the cecal microbiota. The Margalef, Pielou_evenness, Shannon_entropy, and Simpson indices (from right to left) are used for the analysis. (A) Comparisons between SPF layer groups (n = 6 per group). (B) Comparisons between field layer groups (n = 6 per group). Results are shown as mean ± SEM. The P values obtained from the Kruskal-Wallis test are annotated on the graphs.

The results of beta diversity revealed significant dissimilarities between several groups: S.Ct - S.STc, S.Ct - S.STvc, S.Vc - S.STc, and S.Vc - S.STvc, as summarized in Table 3. However, no statistically significant differences in cecal community structure were observed in the comparisons between S.Vc and S.Ct groups or between S.STc and S.STvc groups. Principal coordinates analysis (PCoA) further provided visual confirmation of these disparities (Figure 4A; trial 1). Conversely, beta diversity analyses within the field layer groups demonstrated high similarity among treatment groups (see Figure 4A; trial 2). Statistically significant differences were primarily detected in the comparisons between Vc and Ct groups or between STvc and Ct groups (MRPP: P < 0.01; P < 0.01).

Table 3.

Pairwise comparison of species composition by multiple response permutation procedure (MRPP).

Group A Observed-delta Expected-delta P value
S.Ct-S.Vc 0.020 0.625 0.638 0.068
S.Ct-S.STc 0.155 0.566 0.670 0.004*
S.Ct-S.STvc 0.137 0.568 0.659 0.004*
S.Vc-S.STc 0.108 0.580 0.650 0.005*
S.Vc-S.STvc 0.086 0.582 0.636 0.004*
S.STc-S.STvc 0.027 0.523 0.537 0.057
Ct-Vc 0.009 0.891 0.899 0.004*
Ct-STc 0.006 0.893 0.898 0.091
Ct-STvc 0.022 0.890 0.911 0.003*
Vc-STc −0.002 0.928 0.926 0.600
Vc-STvc 0.000 0.925 0.925 0.423
STc-STvc 0.001 0.928 0.929 0.385
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A stand for the effect size of within-group homogeneity compared to the random expectation.

A >0 represents that the difference between groups is higher than within groups.

A <0 demonstrates that the difference between groups is lower than within groups.

The observed delta and expected delta indicate the level of difference within groups and between groups.

P value ≤0.01 is represented by *.

Figure 4.

Figure 4

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Beta diversity analysis of cecal microbiota (n = 6 per group). (A) Principal coordinates analysis (PCoA) is applied to plot the beta diversity profile of microbial communities using the weighted UniFrac matrix in SPF chicks (trial 1) and field layers (trial 2). (B) Principal component analysis (PCA) is used to cluster the top 5 contributory species in response to treatments in SPF chicks (trial 1) and field layers (trial 2).

Species Contribute to Microbial Community Structure in Ceca of SPF Chicks and Field Layers

Hierarchical PCA identified the top 5 contributory species to the cecal microbiota in SPF chicks of S.Ct group: Blautia glucerasea, Blautia hominis, Faecalibacterium prausnitzii, Subdoligranulum variabile, and Syntrophococcus sucromutans (Figure 4B; trial 1). Conversely, Bacteroides coprocola, Bacteroides plebeius, Megamonas hypermegale, Megamonas rupellensis, and Subdoligranulum variabile were determined as the principal contributors to the microbial communities in the ceca of field layers within the Ct group (Figure 4B; trial 2). The results of metagenomeSeq analysis revealed a significantly higher abundance of Faecalibacterium prausnitzii in the cecal microbiota of the S.STc and S.STvc groups compared to the S.Ct group (Figure 5A). A notable increase in the abundance of Subdoligranulum variabile was observed in the S.Vc group when compared to the ST-challenged groups (S.STc and S.STvc). In addition, a significant reduction in the abundance of Syntrophococcus sucromutans was evident in the S.STvc group in contrast to the S.Ct group. The cecal abundance of Faecalibacterium prausnitzii within the STvc group of field layers significantly increased compared to that of the Ct group (Figure 5B). No statistically significant differences were detected in the comparisons among other bacterial species.

Figure 5.

Figure 5

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MetagenomeSeq analysis of cecal microbiota in chickens subjected to treatments (n = 6 per group). (A) Comparative analysis of contributory species and Eubacterium_coprostanoligenes across SPF chick groups. (B) Comparative analysis of contributory species and Faecalibacterium_prausnitzii across field layer groups. The results are presented as mean ± SEM. Statistical significance was determined using the Tukey test, with * indicating P ≤ 0.05 and ** indicating P ≤ 0.01.

Biomarkers in the Cecal Microbiota in Response to Treatments

The cladogram of LEfSe analysis is shown in Figure 6A. Biomarkers within the cecal microbiota of the S.Ct group were Syntrophococcus sucromutans, Alistipes putredinis, Negativibacillus massiliensis, and Ruminococcus torques. Subdoligranulum variabile was the biomarker identified in the S.Vc group, while Faecalibacterium prausnitzii and Eubacterium coprostanoligenes were recognized as biomarkers within the S.STvc group (Figure 6B). The relative abundance of these biomarkers across groups is represented in Figure 6C. Correlation analysis revealed that Faecalibacterium prausnitzii exhibited an antagonistic relationship with Eubacterium coprostanoligenes, Lacrimispora saccharolytica, and Oscillibacter valericigenes; it showed a dependency with Blautia coccoides and Merdimonas faecist (Figure 6D). In the cecal microbiota of the filed layers, Lactobacillus gallinarum emerged as a biomarker specific to the Ct group, while Faecalibacterium prausnitzii served as the biomarker for the STvc group. Neither the Vc nor STc groups had statistically significant biomarkers in the overall group comparison (Figure 7A). Intergroup comparisons of the relative abundance of these biomarkers at different taxonomic levels are presented in Figure 7B.

Figure 6.

Figure 6

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Differential biomarker analysis and correlation analysis in SPF chicks. (A) Linear discriminant analysis (LDA) cladogram is established to illustrate differential taxa among groups. Concentric circles radiating from the center outward represent taxonomic hierarchies from phylum to species. Each small circle at different hierarchical levels represents a taxon within that level. The diameter of each circle indicates the relative abundance. (B) Results of linear discriminant analysis effect size (LEfSe) with an LDA score of 4.0 among groups (n = 6 per group). The biomarkers are shown at all taxonomic levels. (C) Heat map of biomarkers (n = 6 per group). (D) Spearman correlation analysis is conducted using the top 30 abundant species selected from the ASVs species abundance table. Blue color indicates positive correlations, while red color represents negative dependence. The color intensity reflects the strength of these correlations among the species.

Figure 7.

Figure 7

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LEfSe analysis of cecal microbiota in field layers. (A) Biomarkers identified with an LDA score of 4.0 in the treatment group (n = 6 per group). (B) Relative abundance bar plot of biomarkers at all taxonomic levels.

DISCUSSION

Although Salmonella enterica can affect chickens of all ages, newly hatched chicks have the highest susceptibility to infections. Our investigation focused on day-old SPF chicks to evaluate differential cytokine profiles between groups, thus avoiding the potential confounding effects of the immunological resistance developed in older chickens (Beal et al., 2004). The substantial upregulation of IL-1β following the ST challenge can be attributed to the role of lipopolysaccharide as a pattern recognition molecule for immune cells. This, in turn, triggers the induction of proinflammatory cytokines, such as tumor necrosis factor-alpha (TNF-α), IL-6, and IL-1β, as reported in previous research (Erridge et al., 2002). IFNγ and interleukins are vital immune system elements. They facilitate communication between the innate and adaptive systems. Previous studies have demonstrated significant upregulation of both IFNγ and IL-12 in response to ST infection in chickens (Sijben et al., 2003; Bai et al., 2015; Dar et al., 2019). The upregulation of IFNγ and IL-12 primarily promotes a T-helper (Th) 1 cytokine response, thereby stimulating protective immunity against invading pathogens (Eckmann and Kagnoff, 2001; Trinchieri, 2003). Importantly, ST infection showed less induction of IL-12β in SPF chicks compared to the infection of SE in our earlier investigation (Lin et al., 2022). This is consistent with observations reported by Berndt et al. (2007). Regarding the S.STvc group, our previous data demonstrated effectiveness in reducing the prevalence of pathogenic ST strain and cloacal shedding in layers (Lin et al., 2022). An increase in IL-1β and IFNγ mRNA in Th1 cells in the internal organs of chickens confers protection against Salmonella through a systemic immune response (Shanmugasundaram et al., 2021). The overexpression of IL-1β and IL-12β triggers systemic cell-mediated immunity of immunized chickens against ST invasions. It is well-established that IL-6 and IL-10 are linked to Th2 cell-mediated immune responses. Genetic disruption of the IL-6 gene can lead to a deficiency of IgA-plasma cells in mucosa-associated tissues (Yamamoto et al., 1996). In addition, IL-10 is known to be involved in IgA B-cell differentiation and regulation of mucosal IgA responses (Brière et al., 1994, Yamamoto et al., 1996, Zhang, 2007). The elevation of both cytokines demonstrated participation of mucosal immune responses in Salmonella infection. These findings collectively indicate that AviPro Salmonella Duo can promote humoral and cell-mediated immunity in vaccinated chickens, thus conferring protection against ST infection.

A balanced gut microbiota is a crucial contributor to the overall health, immune competence, productivity, and resistance to pathogenic infections in layers (Khan et al., 2020). The management of the intestinal microbiome is an effective strategy for enhancing immune function (Rogers et al., 2016). In contrast to the limited effects of SE infection on microbiome diversity observed previously, ST challenge induced a notable reduction in community evenness and diversity. Additionally, ST led to significant changes and dissimilarities in microbial composition within the cecal environment. Similar findings have been reported elsewhere (Joat et al., 2021; Sheets et al., 2022). The disparities in the effects on cecal microbiota between SE and ST inoculations align with the observation that ST infection at a younger age results in severe intestinal pathology, whereas SE infections typically manifest without overt clinical symptoms. Interestingly, despite the inclusion of live ST strains in the administered vaccine, oral vaccination did not yield significant effects on either alpha or beta diversity within the cecal microbiota. Following the invasion of pathogenic ST, the homeostasis in the cecal microbiota of vaccinated chickens was disrupted. It showed differences in microbial modulation between vaccine and pathogenic ST strains within the cecal microbiota.

The primary objectives of this study were to investigate the dynamics of the gut microbiota in SPF chicks and layers exhibiting resistance to ST infection and to explore the specific microbial populations contributing to the microbiome. Vaccination with AviPro Salmonella Duo modulated the abundance of specific taxa with particular emphasis on Faecalibacterium prausnitzii and Subdoligranulum variabile. Conversely, ST challenge decreased the amounts of Blautia glucerasea and Subdoligranulum variabile. Bacteria belonging to the Blautia and Subdoligranulum genera are vital for maintaining gut health by producing organic acids and vitamins (Khan and Chousalkar, 2020). The depletion of these beneficial genera can have adverse effects on both health and growth performance. Previous studies have suggested that SE infection leads to a reduction in the abundance of Faecalibacterium within the ceca of chickens (Liu et al., 2018; Lin et al., 2022). Here, the vaccine and pathogenic strains of ST could elevate the abundance of Faecalibacterium prausnitzii within the same intestinal region. Nevertheless, the group with immune protection against ST (S.STvc) manifested the highest abundance and a distinct role of Faecalibacterium prausnitzii compared to the other groups. Faecalibacterium prausnitzii is recognized as the most prevalent gut microbe residing in the healthy colons of humans (Qin et al., 2010). As a member of Clostridium cluster IV microorganisms known for butyrate production (De Cesare et al., 2020), Faecalibacterium prausnitzii plays a critical role in maintaining the immune system (Zhou et al., 2018) and exerts immune response modulation through the production of anti-inflammatory metabolites (Ferreira-Halder et al., 2017). A higher abundance of Faecalibacterium prausnitzii is associated with improved growth performance in chickens (Broom, 2018) and protection against Salmonella in layers (Khan and Chousalkar, 2020). The involvement of Eubacterium coprostanoligenes in the cecum of the ST-protected group was also noted. Eubacterium coprostanoligenes is a cholesterol-reducing anaerobe involved in cholesterol metabolism within the intestines of layers (Li et al., 1996). However, the role of this bacterium in gut microbiome modulation remains elusive. The antagonistic correlation between Eubacterium coprostanoligenes and Faecalibacterium prausnitzii suggests a limited biological significance in the reduction of cloacal shedding and tissue invasion. Based on these findings, vaccination might enhance intestinal resistance against ST infection by promoting the abundance of beneficial commensals, such as Blautia hominis and Subdoligranulum variabile; it can establish the dominance of Faecalibacterium prausnitzii in the ceca of SPF chicks.

As for the cecal microbiota of field layers, ST challenges failed to elicit significant effects on both alpha and beta diversities. This observation can be attributed to a more complex and developed microbiota in older chickens (Videnska et al., 2014), which confer resistance to ST infection. Although we identified the top 5 contributory taxa within the cecal microbiota, no statistically significant differences were observed among group comparisons. Further analysis revealed a notably higher abundance of Faecalibacterium prausnitzii in the STvc group, which displayed protective effects in our previous observations. Despite the fact that the abundance of this species decreased to approximately one-tenth of that observed in SPF chicks, the involvement of this bacterium in this group was statistically significant. These findings suggest that Faecalibacterium prausnitzii may play a pivotal role in the long-term protection against ST shedding in the ceca of older layers. Notably, the use of live attenuated vaccines had an adverse impact on the abundance of Lactobacillus gallinarum, which has previously been shown to inhibit the development of pathogenic infection (Dempsey and Corr, 2022). Nonetheless, the modulatory effects of vaccination on cecal microbiota, including Faecalibacterium prausnitzii and other commensals, appear to confer benefits to layers in their defense against ST infection.

In summary, the application of a live dual vaccine not only enhances host immunity but also promotes intestinal resilience against ST infection within the ceca of layer chickens. Multiple bioinformatics analyses showed that Faecalibacterium prausnitzii is a statistically and biologically significant key species that may offer protection within the cecal microbiota of both SPF chicks and field layers. Given its positive associations with immune modulation, growth promotion, and pathogen resistance, Faecalibacterium prausnitzii harbors the potential to modulate cecal microbiota, thus defending against ST. Further research is warranted to elucidate its role in protecting layers against Salmonella infection.

ACKNOWLEDGMENTS

This study received support from the National Science and Technology Council and Ministry of Agriculture, Taiwan (grant numbers 110-2313-B-002-006-MY2, 111-2313-B-002-020-MY2, and 112AS-2.2.2-AD-U3).

DISCLOSURES

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in the present study.

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