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. 2022 Dec 6;19:100279. doi: 10.1016/j.vas.2022.100279

Determining the association between gut microbiota and its metabolites with higher intestinal Immunoglobulin A response

Mrigendra Rajput a,⁎, Tooba Momin a, Amit Singh a, Surya Banerjee b, Andrew Villasenor a, Jessica Sheldon a, Pratikshya Paudel b, Ravindra Rajput c
PMCID: PMC9755367  PMID: 36533218

Highlights

  • •

    Immunoglobulin A (IgA) is one of the important and most abundant immunoglobulins in the mucosal surface including the gastrointestinal (GI) tract. It neutralizes the invading pathogens and prevents infection.

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    IgA production is greatly influenced by the gut microbial community and their metabolites. However specific bacterial community or their metabolites, responsible for higher IgA are poorly understood. The current study with age-matched, apparently healthy, from similar litters, 26 days wean pig showed that bacterial phylum such as Bacteroidota and Desulfobacterota is directly related to higher gut IgA concentration while Firmicutes and Firmicutes/ Bacteroidota ratio is inversely related to gut IgA concentration.

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    Animals with higher IgA had comparatively lower short-chain fatty acid (SCFA) such as acetic acid, butyric, formic acid, isovaleric acid, and propionic acid.

  • •

    Bacteria or bacterial metabolites responsible for higher IgA production can be used with oral vaccines for better immune response while bacteria or bacteria metabolites responsible for lower IgA can be used to suppress gut inflammation.

Keywords: Gut microbiota, Bacterial metabolites, immunoglobulin A (IgA), Gut immune system

Abstract

Immunoglobulin A (IgA) is one of the important and most abundant immunoglobulins which neutralize invading pathogens at mucosal sites. Gut microbial community and their metabolites which are responsible for higher IgA are poorly known. The current study was carried out to determine those microbial community and their metabolites. Twenty-two healthy, 26 days wean piglets were used in the study. After 10 days of weaning, piglets were divided into two groups. Group 1 with significantly higher fecal IgA while group 2 with significantly lower IgA concentrations from each other. Both groups were analyzed for the fecal inflammatory cytokine, fecal microbial community using 16S ribosomal sequencing, and microbial metabolites using GC–MS.

Results showed that Firmicutes and Bacteroidetes constituted 90.56% of the microbiome population in the fecal matter of pigs with higher IgA concentration while pigs with lower fecal IgA had Firmicutes and Bacteroidetes abundance as of 95.56%. Pigs with higher IgA had significantly higher Bacteroidota and Desulfobacterota populations, while significantly lower Firmicutes and Firmicutes/ Bacteroidota ratio (p <0.05). Roughly at the species level, animals with higher fecal IgA concentration had significantly higher bacteria which are associated with gut inflammation and infectious such Prevotella spp and Lachnospiraceae AC2044. Pigs with higher IgA had comparatively lower short-chain fatty acid (SCFA) such as acetic acid, butyric, formic acid, isovaleric acid, and propionic acid which has been associated with gut immune tolerance and immune homeostasis.

Graphical abstract

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1. Introduction

The Gastrointestinal (GI) tract is one of the largest immune organs in the vertebrate body (Chassaing et al., 2014). It contains cells that perform barrier function, digestion, and absorption as well as cells of the nervous and immune systems (Mason et al., 2008; A. J. Moeser et al., 2017). The GI tract is constantly exposed to harmful pathogens and toxins along with beneficial food particles. The GI tract needs to perform the daunting task of differentiating harmful pathogens from beneficial food while maintaining immune homeostasis without affecting the digestion and absorption function (Mason et al., 2008; Okumura & Takeda, 2016). Specialized immune cells in the GI tract with the help of commensal microbiota maintain that homeostasis. Together they help in differentiating harmful pathogens and promote tolerance for orally introduced harmless food particles (Wu & Wu, 2012).

Gut microbiota has a broader role in gut immune system development and its activation. Studies with germ-free mice showed that these mice had small and relatively inactive immune organs such as lymph nodes, spleens, and peyer's patches (Cebra et al., 1998; Pollard & Sharon, 1970). These germ-free mics also had a low number of immunoglobulin A (IgA) secreting plasm cells in the peyer's patches and inactive CD4+ T cells in lamina propria, while supplementation of microbiota helped their activation with increased circulating antibodies (Cebra et al., 1998; Chang et al., 2014; Di Gangi et al., 2020; Pollard & Sharon, 1970; Yu et al., 2021). Gut microbiota performs that function either by direct interaction with intestinal or immune cells or through its metabolites (Hooper et al., 2002; Lin & Zhang, 2017). Different gut microbiota produces different types of metabolites either through anaerobic fermentation of exogenous undigested dietary components or molecules produced directly by the microorganisms as metabolic byproducts (Okumura & Takeda, 2016).

Arginine is one of the bacterial metabolites which influences the gut immune system. l-Arginine is synthesized from glutamine, glutamate, or proline and converted to either polyamines, nitric oxide, proline, glutamate, creatine, urea, agmatine, or protein Wu et al. (2009). The final end product of arginine also has its own effect on the gut immune system (Ruth & Field, 2013). Oral administration of arginine in mice in combination with the probiotic Bifidobacteria LKM512 showed suppressed inflammation with improved longevity and protection from age-induced memory impairment (Kibe et al., 2014). Malaria infected, arginine deficient mice showed enhanced intestinal barrier dysfunction with increased susceptibility to salmonella, while oral supplementation of arginine improved intestinal barrier function and reduced inflammation (Chau et al., 2013). Nitric oxide, an arginine byproduct is essential for killing the invading pathogen by various phagocytic cells such as neutrophils and macrophages (Che et al., 2019). However, higher nitric oxide production results in intestinal inflammatory diseases such as ulcerative colitis and Crohn's disease (Chang et al., 2014; Kolios et al., 2004). Other bacterial metabolites such as format are also found associated with gut inflammation and colorectal cancer (Hughes et al., 2017; Ternes et al., 2022).

Metabolites such as short-chain fatty acids (SCFAs) which are produced in anaerobic fermentation of deity fibers by certain bacteria showed a beneficial effect on gut health, gut immune system, and barrier function (Lin & Zhang, 2017; Parada Venegas et al., 2019). SCFA such as acetic acid, butyric acid, and propionic acid, not only provide energy to gut microbiota and host cells but also help in gut immune homeostasis and shaping the immune system (Chang et al., 2014; Koh et al., 2016; Okumura & Takeda, 2016). SCFA such as butyrate and propionate perform their function either as histone deacetylases (HDACs) inhibitors (Chen et al., 2003; Thangaraju et al., 2009) or G protein-coupled receptors (GPCRs) activators (Maslowski et al., 2009; Masui et al., 2013; Yang et al., 2018). A reduced HDACs inactivated nuclear factor-κB (NF-κB) and downregulated the production of the pro-inflammatory cytokine (Vinolo et al., 2011), suppressing the activity of macrophage (Chang et al., 2014) and dendritic cell (Singh et al., 2010) while enhancing the function of regulatory T cells (Tao et al., 2007). SCFA also suppressed the migration of the immune cells such as neutrophils chemotaxis (Vinolo et al., 2011), T cell differentiation (Kim et al., 2014), increasing intestinal epithelial cell (IEC) barrier function (Peng et al., 2009; Wang et al., 2012; Willemsen et al., 2003) via GPCRs which then helps in suppressing inflammation and maintaining the immune homeostasis (Okumura & Takeda, 2016).

Bacterial metabolites also influence mucosal immunoglobulin A (IgA) production. IgA (secretory IgA) is a primary antibody that is secreted at the mucosal site (Lamm, 1988). The mucosal site is a major route of entry for many food-borne and airborne pathogens (Freihorst & Ogra, 2001). An adequate amount of IgA prevents the onset of such infection (Corthesy, 2013). Studies showed that gut microbiota and intestinal IgA influence each other (Nakajima et al., 2018; Takeuchi et al., 2021; Weis & Round, 2021). Commensal bacteria including Bacteroides fragilis utilize IgA for their colonization in the gut (Donaldson et al., 2018). A study with monocolonizing of different bacterial strains in mice showed that Bacteroides ovatus was responsible for higher fecal IgA production (Yang et al., 2020). While bacterial metabolite showed that acetate was associated with increased production of IgA in the colon with enhanced capacity of IgA to bind to specific microorganisms (Takeuchi et al., 2021). Few of the above-mentioned studies were carried out using single bacteria monocolonization. There is still a large knowledge gap to know which other bacteria or bacterial metabolites are responsible for higher IgA production in the gut. The current study was performed using weaned pigs to identify specific bacteria or bacterial metabolites responsible for higher IgA production in the gut. The results of the current study could help in reducing the adverse effect of stress in pigs (such as leaky gut) (Pohl, et al., 2015) by choosing appropriate probiotics (beneficial bacteria) or their metabolites and help in higher pig production. Pig is known as a better animal model to study human gut health (Moeser et al., 2017), Therefore, the results of this study could also be implemented in humans in suppressing gut inflammation by supplementation of certain probiotics as determined in this study or strategic use of certain bacteria with the oral vaccine could be used to enhance its immune response in humans or in animals.

2. Materials and methods

2.1. Animals and experimental design

The current study was carried out as per recommendations by Arkansas Tech University Animal Care and Use Committee, Arkansas Tech University, Russellville, AR. A total of Twenty-two piglets from sows (Spp: Scrofa domesticus, Breed: Large White) were used in the study with equal males and females. Piglets were weaned at the age of 26 days and provided a standard weaning diet in the same pen. Fecal samples were aseptically collected after 10 days of weaning from sixteen piglets and at 17 days of weaning from four piglets in sterilized containers. We choose the time as 10 days post-weaning as a previous study showed that gut microbiota stabilized at 10 days of weaning (Chen et al., 2017) and 17 days of weaning to measure the timecourse effect on gut microbiota and IgA concentration. Collected samples were immediately kept on ice and transported to the laboratory. Fecal samples were quickly divided into two parts, one part was stored at −80 °C for bacterial DNA extraction and bacterial metabolic analysis while another part was immediately used for fecal IgA concentration, and the rest was stored at −80 °C.

2.2. Fecal immunoglobulin A (IgA) analysis

The concentration of fecal IgA in samples was measured by Pig IgA ELISA kit (Bethyl Laboratories, Montgomery, TX) as per manufacturer protocol. Individual 0.5-gram fecal samples were diluted in 0.5 ml sterilized phosphate-buffered saline (PBS) to get the final concentration as 1-gram fecal sample per ml of PBS. After proper mixing, samples were centrifuged at 1000X G for 5 min at 4 °C. The supernatant containing IgA was carefully collected without disturbing the pellet and diluted four times using 1X dilution buffer provided with the kit. A 100 µl diluted sample or standards were added to respective pre-coated well in ELISA plates and incubated for 1 hour at room temperature. After incubation, plates were washed with the washing buffer which was provided with the kit. A 100 µl anti-IgA detection antibody was added to each well and further incubated for 1 hour at room temperature. After incubation and four-time wash, 100 µl horseradish peroxidase (HRP) was added to each well followed by 30 min of incubation at room temperature. Plates were washed four times and a 100 µl 3,3′,5,5′-Tetramethylbenzidine (TMB) substrate was added to each well. Plates were incubated at room temperature in dark for 30 min. After 30 min, the reaction was stopped using a stopping solution, provided with the kit. Absorbance for each well was measured at 450 nm using a plate reader (Synergy LX, BioTek, Winooski, VT).  IgA concentration in samples was estimated using a standard curve which was prepared using known concentrations for standards.

Based on IgA concentration, samples which were collected at 10 days of weaning were divided into two groups, group 1 with higher IgA concentration (> 2.0 µg IgA/gram of feces) or group 2 with lower IgA concentration (<2.0 µg IgA/gram of feces). Both these groups had an equal number of piglets from three different littles. Samples in both groups were further analyzed for bacterial population and bacterial metabolites.

2.3. Determining the bacterial population using 16S ribosomal DNA analysis

Bacterial population in individual fecal sample were analyzed by 16S ribosomal DNA analysis. Bacterial DNA was isolated by QIAamp DNA mini kit (Qiagen GmbH, Hilden, Germany). High-quality DNA samples were used to amplify variable region 3 (V3) and V 4 for 16S ribosomal DNA with the help of LC Sciences LLC, Houston, TX. Amplicons of about 465 pb were generated using 341F/805R primers. The amplified amplicon library is sequenced using NovaSeq platform with 250 bp paired-end reads mode (2 × 250 bp).

Raw data files in FASTQ format were subject to reads merge by overlapping sequences with chimera filtering which produced high-quality clean data. Further, DADA2 (Divisive Amplicon Denoising Algorithm) was used for dereplication and to generate representative sequences at single-base resolution. Amplicon Sequence Variants (ASV) sequences were then used to analyze bacterial taxonomy.

2.4. Determining the Tumor necrosis factor-alpha (TNFα) concentration in the fecal sample

The fecal TNFα concentration was measured by Swine TNFα ELISA kit (Thermo Fisher Scientific, Waltham, MA) according to manufacturer protocol with little modification. Fecal samples were diluted in the standard diluent buffer to get the final concentration as 1 gram of feces in 1 ml of standard diluent buffer. 100 µl diluted fecal samples and standards were added to the appropriate well in the ELISA plate and the plate was incubated at 4 °C overnight. After incubation, the plate was washed four times with 1x wash buffer which was provided with the kit. A 100 µl 1x streptavidin-HRP solution was added to each well and the plate was incubated for 30 min at room temperature followed by a four-time wash. After washing, 100 µl chromogen was added to each well for 20 min at room temperature in dark. After 20 min of incubation, the reaction was stopped by adding 100 µl stop solution in each well. Absorbance for each well was measured at 450 nm using a plate reader (Synergy LX, BioTek, Winooski, VT).  TNFα concentration in samples was estimated using a standard curve which was prepared using known concentrations for standards.

2.5. Bacterial metabolites

Frozen fecal samples for both groups were analyzed for fecal metabolites analysis using Gas Chromatography Mass Spectrometry (GC–MS) at West Coast Metabolomics Center, UC Davis, CA. Fecal metabolites analysis provided the absolute concentrations of SCFA such as acetic acid, butyric acid, formic acid, isovaleric acid, propionic acid and valeric acid, while relative concentrations for over 280 other metabolites.

3. Statistical analysis

A paired t-test was used to determine difference in IgA concentration, bacterial population (phylum and species),bacterial metabolites and TNFα concentration between group one (1) and two (2).

4. Results

4.1. Fecal IgA concentration

Based on IgA concentration, samples collected at 10 days of weaning were divided into two groups, group 1 with higher IgA concentration (> 2.0 µg IgA/gram of feces) or group 2 with lower IgA concentration (<2.0 µg IgA/gram of feces). Fecal samples in group 1 had the IgA concentration as 4.10±0.46 µg IgA/gram of feces which was significantly higher than IgA concertation in group 2 which has 1.96±0.26 µg IgA/gram of feces (Fig. 1) (p<0.05). Further, these samples were analyzed for bacterial population and bacterial metabolites.

Fig. 1.

Fig 1

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Fecal immunoglobulin A concentration. Fecal samples were aseptically collected after 10 days of weaning. Freshly collected samples were analyzed for IgA concentration by ELISA kit. The significant difference in IgA concentration between groups 1 and 2 was estimated using paired T-test. Asterisks are showing a significant difference (p < 0.05).

Similarly, fecal samples collected at 17 days post-weaning were also divided into two groups with higher (2.71±0.41 µg IgA/gram of feces): group 3 and lower IgA concentrations (1.14±0.0.11 µg IgA/gram of feces): group 4 and analyzed for bacterial population.

4.2. Difference in bacterial population in fecal matter with high IgA

The bacterial population in fecal samples were analyzed using V3 and V4 regions of 16S rDNA. Results showed that 90.56% of the microbiome population in pigs with higher IgA concentration is composed of Firmicutes (72.51±3.40) and Bacteroidetes (18.05±2.56) while these two phyla (Firmicutes: 81.87±3.64, Bacteroidetes: 13.68±3.09) contributed 95.56% of their total microbiome population in group 2 pigs which had lower fecal IgA concentration (Fig. 2A).

Fig. 2.

Fig 2

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Bacterial abundance in the fecal matter of Group 1 and Group 2. Fecal matter collected at 10 days of weaning from group1 and group 2 animals were used to isolate bacterial DNA. Isolated DNA were amplified for the 3 and V 4 regions of 16S ribosomal DNA. The final ASV sequences were used to analyze bacterial taxonomy and calculate the percent abundance of bacteria between group 1 and group 2 (A), the difference in Firmicutes/Bacteroidota ratio between group 1 and group 2 (B), and the percent difference in gut Firmicutes and Bacteroidota (C). Significantly different bacterial phylum or Firmicutes/Bacteroidota ratio was estimated using paired T-test. Asterisks are showing a significant difference (p < 0.05).

Group 1 also had a significantly higher abundance of bacteria with phylum Bacteroidota and Desulfobacterota as compared to group 2 while group 2 had significantly higher Firmicutes as compared to group 1 (p<0.05) (Fig. 2A). There percent abundance of Bacteroidota and Desulfobacterota in group 1 were 18.05±2.56% and 0.12±0.03% as compared to13.68±0.08% and 0.06±0.01% respectively in group 2 (P<0.05). The percent abundance of Firmicutes in group 2 was 81.87±3.64% which was significantly higher than group 1 which has percent abundance of Firmicutes as 72.51±3.40% (p<0.05) (Fig. 2A and Fig. 2C). Similarly, group 2 has a significantly higher Firmicutes/Bacteroidota ratio (7.71±0.03) as compared to group 1 (4.85±0.97) (p<0.05) (Fig. 2B).

Higher abundance of Bacteroidota and Desulfobacterota and lower abundance of Firmicutes was consistent with higher IgA at 17 days of weaning (p<0.05) (Fig. 3A, Fig. 3B and Figure C), indicating that bacteria population stabilized and showed its effect of IgA concentration.

Fig. 3.

Fig 3

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Bacterial abundance in the fecal matter of Group 1 and Group 2. Fecal matter was collected at 17 days of weaning from group 3 (higher fecal IgA) and group 4 (higher fecal IgA) animals were used to isolate bacterial DNA. Isolated DNA were amplified for the 3 and V 4 regions of 16S ribosomal DNA. The final ASV sequences were used to analyze bacterial taxonomy and calculate the percent abundance of bacteria between group 3 and group 4 (A), the difference in Firmicutes/Bacteroidota ratio between group 3 and group 4 (B), and the percent difference in gut Firmicutes and Bacteroidota (C). Significantly different bacterial phylum or Firmicutes/Bacteroidota ratio was estimated using paired T-test. Asterisks are showing a significant difference (p < 0.05).

At species level, group 2 has significantly higher Streptococcus equinus (1.37± 0.47) (group 1: 0.30±0.10%), Fusicatenibacter spp (unclassified group) 0.12±0.05% (group 1: 0.0025±0.00%), Roseburia spp (unclassified group) 0.13±0.06% (group 1: 0.01±0.00%), Lactobacillus sp. l-YJ, 13.41±4.86% (group1: 1.88±1.45%), Blautia spp. (unclassified group) 5.49±2.41% (group 1: 0.78±0.27%), Solobacterium spp. (unclassified group) 2.04±0.78% (group 1: 0.05±0.11%), Ruminococcus torques 3.86±1.72 (group 1: 0.12±0.06), Alloprevotella spp. (unclassified group) 1.65±0.56 (group 1: 0.39±0.12%), Bacteroides pectinophilus (unclassified group) 0.01±0.00% (group 1: 0.001±0.00%). While group 2 has lower Lachnospiraceae AC2044 0.01±0.00% (group 1:0.07±0.01%), Prevotella sp. 0.001±0.00% (group 1: 0.04±0.01%), Papillibacter spp. (unclassified group) 0.001±0.00% (group 1: 0.1 ± 0.00%), Muribaculaceae spp (unclassified) 2.58±0.66% (group1: 9.89±2.55%), Oscillospiraceae UCG-002 1.37±0.35% (group 1: 4.20±1.00%), Family XIII AD3011 0.70±0.25% (group 1: 1.61±0.24%), Clostridiaceae spp. (unclassified group) 0.01±0.00% (group 1: 0.13±0.05%), Oscillospirales spp (unclassified group) 0.00±0.00% (group1: 0.01±0.00%) (Table 1 and Supplement Table 1)

Table 1.

Percent abundance of significantly different bacterial species between groups 1and 2. Bacterial DNA was isolated from the fecal matter of group 1 and group 2 animals. Isolated DNA was used to amplify the 3 and V 4 regions of 16S ribosomal DNA. The final ASV sequences were used to analyze bacterial taxonomy. Percent abundance of significantly different bacterial species in group 1 and group 2 along with p values are mentioned in the table.

Bacterial species Group 1 Group 2 P-value
Streptococcus equinus 0.30 ± 0.10 1.36 ± 0.47 0.03
Fusicatenibacte spp. 0.0025 ± 0.00 0.12 ± 0.05 0.03
RosebUria spp. 0.01 ± 0.00 0.13 ± 0.06 0.05
Lactobacillus sp. l-YJ 1.88 ± 1.45 13.40 ± 4.86 0.03
Blautia spp. 0.78 ± 0.27 5.48 ± 2.41 0.05
Solobacterium spp. 0.50 ± 11 2.03 ± 0.78 0.05
Ruminococcus torques 0.12 ± 0.06 3.85 ± 1.71 0.03
Alloprevotella spp. 0.39 ± 0.12 1.64 ± 0.56 0.03
Bacteroide pectinophilus 0.00 ± 0.00 0.01 ± 0.00 0.04
Lachnospiraceae AC2044 0.07 ± 0.01 0.007 ± 0.00 0.01
Prevotella_sp. 0.04 ± 0.01 0.001 ± 0.00 0.04
Papillibacter spp 0.1 ± 0.00 0.001 ± 0.00 0.04
Muribaculaceae spp. 9.89 ± 2.55 2.57 ± 0.66 0.03
Oscillospiraceae UCG-002 4.20 ± 1.00 1.37 ± 0.35 0.02
Family XIII AD3011 1.61 ± 0.24 0.70 ± 0.25 0.02
Clostridiaceae spp. 0.13 ± 0.05 0.01 ± 0.00 0.04
Oscillospirales spp 0.01 ± 0.00 0.00 ± 0.00 0.05
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4.3. There was no difference in Tumor necrosis factor-alpha (TNFα) concentration in the fecal sample with higher or lower IgA concentration

TNFα ELISA result showed 118.07±9.78 ng TNAα/ gram of fecal sample in group 1 (the group with higher IgA concentration) as compared to 100.86±11.68 ng TNAα/ gram of fecal sample in group 2 (the group with lower IgA concentration) (Fig. 4). Both of these concentrations were non-significant different from each other (p<0.05) indicating that weaning mediated inflammation was subsided at 10 days of weaning.

Fig. 4.

Fig 4

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Fecal TNFα concentration in Group 1 and Group 2. Fecal matter was collected at 10 days of weaning from group 1 and group 2 animals and diluted in the standard diluent buffer to get the final concentration as 1 gram feces/ml. Diluted sample were analyzed TNFα concentration using Swine TNFα ELISA kit. The significant difference in TNFα concentration between groups 1 and 2 was estimated using paired T-test.

4.4. Short-chain fatty acids were negatively regulated with fecal IgA concentration

Short-chain fatty acid (SCFA) analysis showed that fecal samples of group 2 animals, which have lower IgA concentration, had comparatively higher SCFA such as acetic acid (3189±14.04 ng/mg of fecal matter, group 1: 2600±15.21 ng/mg of fecal matter), butyric acid (651±8.19 ng/mg of fecal matter, group 1: 505±7.45 ng/mg of fecal matter), formic acid (425±6.72 ng/mg of fecal matter, group 1: 262±3.52 ng/mg of fecal matter), isovaleric acid (4196±35.35 ng/mg of fecal matter, group 1: 3514±26.63 ng/mg of fecal matter) and propionic acid (1894±12.46 ng/mg of fecal matter, group 1: 933±9.62 ng/mg of fecal matter) while group 2 had lower valeric acid (280±3.50 ng/mg of fecal matter) as compared to group 1, which has 760±9.70 ng valeric acid /mg of fecal matter. However, such difference was nonsignificant different (p<0.05) (Fig. 5)

Fig. 5.

Fig 5

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The concentration of Short-chain fatty acid (SCFA) in the fecal matter. Fecal samples collected from group 1 and group 2 were analyzed for Short-chain fatty acids (SCFA) such as acetic acid, butyric acid, formic acid, isovaleric acid, propionic acid, and valeric acid using Chromatography-Mass Spectrometry (GC–MS). A significant difference in the SCFA between group 1 and group 2 was estimated using paired T-test. Asterisks are showing a significant difference (p < 0.05).

4.5. Primary metabolites

Primary metabolites analysis using GC–MS showed that fecal matter of group 1 has significantly higher xylitol, tocopherol alpha, pimelic acid, pimelic acid, phenylalanine, palmitic acid, nicotinamide, myristic acid, myo-inositol, isopentadecanoic acid, heptadecanoic acid, glycine, deoxycholic acid, adenine and 1-hexadecanol as compared to group 2 while fecal matter of group 2 animals had significantly higher 4-aminobutyric acid and, 3-aminoisobutyric acid (p<0.05) (Table 2 and Supplement Table 2).

Table 2.

Fold change in significantly different primary bacterial metabolites between group1 and group 1. Fecal matter was collected from pigs with higher IgA (Group1) and lower IgA (Group 2) and was analyzed for 280 different bacterial metabolites using GC–MS. Relative concentrations of significantly different metabolites were converted to fold change between group 1 and group 2.

Metabolites Fold change in metabolites concentration
 P-value
Group 1 Group2
Xylitol 1.00 ± 0.15 0.62 ± 0.06 0.04
Tocopherol alpha 1.00 ± 0.21 0.44 ± 0.11 0.03
Pimelic acid 1.00 ± 0.25 0.38 ± 0.06 0.03
Phenylalanine 1.00 ± 0.07 0.69 ± 0.09 0.01
Palmitic acid 1.00 ± 0.11 0.63 ± 0.08 0.02
Nicotinamide 1.00 ± 0.59 0.66 ± 0.11 0.01
Myristic acid 1.00 ± 0.25 0.39 ± 0.05 0.03
Myo-inositol 1.00 ± 0.10 0.68 ± 0.05 0.01
Isopentadecanoic acid 1.00 ± 0.27 0.41 ± 0.05 0.05
Heptadecanoic acid 1.00 ± 0.05 0.70 ± 0.13 0.04
Glycine 1.00 ± 0.15 0.56 ± 0.07 0.02
Deoxycholic acid 1.00 ± 0.33 0.17 ± 0.02 0.02
Adenine 1.00 ± 0.20 0.54 ± 0.07 0.05
1-Hexadecanol 1.00 ± 0.25 0.38 ± 0.08 0.03
4-Aminobutyric acid 1.00 ± 0.19 2.15 ± 0.55 0.05
3-Aminoisobutyric acid 1.00 ± 0.26 3.42 ± 0.123 0.05
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5. Discussion

Gut microbiota and their metabolites orchestrate the gut immune response (Brun et al., 2021; Levy, Thaiss & Elinav, 2016). Current study was carried out to determine the specific bacteria and bacterial metabolites for higher fecal IgA concentration. Healthy piglets were weaned at 26 days of age with the aim to induce weaning stress. After 10 days of weaning when gut microbiota stabilizes (Donaldson et al., 2018). Fecal samples of piglets were analyzed for IgA concentration and divided into groups. Group 1 had significantly higher fecal IgA ass compared to group 2 . Both groups were analyzed for inflammatory cytokines (e.g. TNFα), bacterial population, and bacterial metabolites. TNFα concentration between these two groups was non-significant different, indicating that the effect of weaning stress was subsided at 10 days of weaning. That post weaning cytokine analysis was similar to previous findings (Pié et al., 2004). Results also that about 90.56% of the microbiome population in pigs with higher IgA concentration is composed of Firmicutes (72.51±3.40) and Bacteroidetes (18.05±2.56) while these two phyla (Firmicutes: 81.87±3.64, Bacteroidetes: 13.68±3.09) contributed 95.56% of their total microbiome population in group 2 pigs which had lower fecal IgA concentration. However, the previous study with crossbred pigs (Duroc × [Landrace × Yorkshire]) showed a similar higher abundance of Firmicutes and Bacteroidetes in overall gut microbiota but they contributed 50.36 and 36.08%, respectively (Chen et al., 2017). These differences may be due to different breeds, feed, or other factors in these two different studies. However, that previousstudy showed there wasno or very little difference in bacterial population between 10 days and 21 days of weaning (Chen et al., 2017) which was similar to our current finding. Our study also showed no difference in gut bacterial population from 10 days of weaning to 17 days of weaning, indicating that microbiota stabilized after 10 days of weaning. Our study also. Our study showed a higher fecal IgA concentration was directly correlated with higher Bacteroidota and Desulfobacterota phylum abundance while negatively correlated with Firmicutes phylum and Firmicutes /Bacteroidota ratio (p<0.05). The results of our study were in agreement with previous study in mice where Bacteroides ovatus was found responsible for higher fecal IgA production (Yang et al., 2020).

Bacteroidota (also known as Bacteroidetes) is a phylum that comprise gram-negative, non-sporeforming, rod-shaped bacteria (Wexler, 2007). Bacteroidetes are the main contributors for LPS biosynthesis in the human gut (d'Hennezel et al., 2017), However LPS from Bacteroides is structurally distinct from the LPS of other gram-negative bacteria in gut such as E. coli and play an important role in innate immune inhibition (Vatanen et al., 2016). Bacteria of Bacteroidota phylum such as B. fragilis has shown a positive effect in developing gut-associated lymphoid tissue (GALT) in rabbit with increased antibody repertoire (Rhee et al., 2004). Previous studies showed that polysaccharides produced by B. fragilis activated CD4+ T cells and B-Cells (Mazmanian & Kasper, 2006; Mazmanian et al., 2005). A higher B cell activation may be the cause of higher IgA concentration in the fecal matter of group 1 animals which has higher Bacteroidota abundance.

Our results also showed more abundance of Desulfobacterota in animals with higher fecal IgA concentration. Desulfobacterota is a sulfate-reducing bacteria (Langwig et al., 2022) and has been associated with increased immune response and gut inflammation (Figliuolo et al., 2017; Tamargo et al., 2022), which may be the reason for higher fecal IgA concentration on those animals.

Results of current study showed a negative correlation of Firmicutes and Firmicutes/ Bacteroidota ratio with fecal IgA concentration. Firmicutes are gram positive bacteria with low guanine + cytosine (G + C) content in their DNA with rigid cell wall (Briggs et al., 2012). Firmicutes consisted of seven classes of bacteria such as Bacilli, Clostridia, Erysipelotrichia, Limnochordia, Negativicutes, Thermolithobacteria, and Tissierellia (Seong et al., 2018). Firmicutes play an important role in the anaerobic fermentation of deity fibers and generating SCFA (den Besten et al., 2013). Along all SCFA, acetate, propionate and butyrate comprise about 95% of total SCFA (Cook & Sellin, 1998), and are generally present with ratio of 60: 20: 20 at the lower intestine and fecal matter (Hijova & Chmelarova, 2007). Firmicutes are one of the main phyla which as been identifies as main butyrate producer in gut (Ohira et al., 2017). Butyrate suppresses the interferon-gamma (IFN-γ) signaling and enhancing peroxisome proliferator-activated receptor-γ response and thus suppresses the inflammation (Kinoshita et al., 2002; Klampfer et al., 2003). Reduced inflammation by butyrate or other SCFA can be the reason for having lower IgA concentration in group 2 in the current study which has higher SCFA. While Desulfobacterota which was significantly higher in group 1 participate in butyrate degradation by carrying out a butyrate beta-oxidation (Janssen & Schink, 1995) could be the cause for having higher IgA in fecal matter of group 1 animals. Group 1 animals have other bacteria such as Prevotella spp (Iljazovic et al., 2021, 2021), Lachnospiraceae AC2044 (Kameyama & Itoh, 2014; Kostic et al., 2015) which are associated with infection and inflammatory diseases and could be reason for higher IgA in group 1 animals.

Bacteria such as Lactobacillus sp. l-YJ (Xu et al., 2019), Lachnospiraceae AC2044 (Lemaire et al., 2018) or Bacteroides pectinophilus (Larsen et al., 2019) which were significantly higher in group 2, either have abundance in healthy individuals (Xu et al., 2019) or negatively correlated with bacteria which cause inflammation (Lemaire et al., 2018) or aid in breaking down of dietary pectins for a better gut health (Larsen et al., 2019). The current study also showed a significantly higher Blautia spp in group 2 animals (animals with lower fecal IgA concertation). Firmicutes and Blautia spp in gut microbiota has been associated with suppressed chronic liver diseases and hepatocellular carcinoma patients (Chen et al., 2021), a immunomodulatory/immune suppressive properties of Firmicutes or Blautia spp may be one of the cause for having lower IgA in group 2 animals. A higher Firmicutes/Bacteroidetes Ratio is directly correlated with obesity (Magne et al., 2020) while in the current study we found the pigs with higher Firmicutes/Bacteroidetes Ratio had lower IgA concentration, indicating that obese individual may have lower mucosal humoral immunity which need to be further examined.

However, there may be multiple factors that could influence the production of IgA in the current study. To reach any conclusion regarding which bacterial phylum/spp or bacterial metabolites are responsible for higher IgA. Multiple control studies are needed using germ-free pigs to evaluate the individual or combined effect of these bacterial phylum/spp or bacterial metabolites are responsible for higher IgA production.

Nevertheless, our current study showed that animals in group 1, which has higher IgA fecal concentration, had a higher abundance of bacteria that has been associated with inflammation while group 2 which had a lower fecal IgA concentration also had bacteria that suppress inflammation or produces metabolites such as SCFA which suppress gut inflammation. However, animals in both groups were apparently healthy and did not show any abnormality. It is interpreted that higher IgA provides better protection from invading pathogens and animals with higher IgA without any diseases have comparatively higher resistance against the pathogen. The animals which have low IgA may be more susceptible to the invading pathogen. The invading pathogen may provide stimulation to produce higher IgA and could change their microbiota and microbial metabolite composition. Primary metabolites, which were identified higher in group 1 should be analyzed for their gut inflammatory properties. If those metabolites transiently actively mucosal immunity then they could be used with oral vaccines to improve their efficiency in humans and animals.

6. Conclusions

Current study was carried out to determine the gut microbiota and their metabolites responsible for highest IgA concentration in pig. Healthy, 26 days wean pigs were divided into groups with higher (group 1) and lower (group 2) concentrationstion. Results showed that higher fecal IgA concentration was directly correlated with a higher abundance of Bacteroidota and Desulfobacterota phylum while the lower abundance of Firmicutes and Firmicutes /Bacteroidota ratio. Lower fecal IgA was associated with bacteria which are associated with reduced inflammation or present in higher abundance in healthy individuals such as Lactobacillus sp. l-YJ, Lachnospiraceae AC2044 or Bacteroides pectinophilus. Higher fecal IgA was also negatively associated with SCFA which are characterized by reduced gut inflammation. Animals in both groups were apparently healthy, and results with higher IgA in group 1 may indicate that these animals may have better resistance to the invading pathogen, however, these animals may also be prone to gut inflammatory disorders. On the other hand, animals with lower fecal IgA concentrations may have more susceptibility to the invading pathogens but the such pathogen can stimulate the immune response and shift the microbiome and bacterial metabolites concentration to induce more IgA.

Ethical statement for veterinary and animal science

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    The paper reflects the authors' own research and analysis in a truthful and complete manner.

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    The paper properly credits the meaningful contributions of co-authors and co-researchers.

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Declaration of Competing Interest

The authors have no conflict of interest to declare

Acknowledgements

The authors want to thank and acknowledge the Department of Biology, University of Dayton, and Arkansas INBRE-NIGMS-P20 GM103429 funding to Dr. M Rajput and Dr. S. Banerjee for providing financial support to carry out the project.

Footnotes

Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.vas.2022.100279.

Appendix. Supplementary materials

mmc1.pdf (299.3KB, pdf)
mmc2.pdf (181.7KB, pdf)

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