Skip to main content
NCBI home page
MicrobiologyOpen logoLink to MicrobiologyOpen
. 2019 Sep 9;8(12):e923. doi: 10.1002/mbo3.923

Longitudinal development of the gut microbiota in healthy and diarrheic piglets induced by age‐related dietary changes

Qiaoli Yang 1, Xiaoyu Huang 1, Pengfei Wang 1, Zunqiang Yan 1, Wenyang Sun 1, Shengguo Zhao 1, Shuangbao Gun 1,2,✉
PMCID: PMC6925166  PMID: 31496126

Abstract

Diarrhea is one of the most common enteric diseases in young piglets. Diverse factors such as an unstable gut microenvironment, immature intestinal immune system, early supplementary feeding, and weaning often induce dysfunction of gut microbiota, thus leading to a continuing high incidence of diarrhea in piglets. However, few studies have characterized the gut microbiota of diarrheic piglets following changes in diet and during the development of intestinal physiology. In this study, we used 16S rRNA gene sequencing to analyze the dynamic establishment of fecal microbiota in six healthy piglets in response to age‐related changes in the diet: sow‐reared, early supplementary creep‐feeding (sow‐reared + starter diet), and weaning (solid nursery diet). We compared the gut microbiota of these six healthy piglets with those of diarrheic piglets during each of the three dietary stages (n = 10 sow‐reared, n = 10 early supplementary creep‐feeding, and n = 5 weaning). We found that weaning (solid nursery feeding) was the primary factor leading to dynamic colonization by microbiota in healthy piglets, and diarrhea primarily affected the microbial communities of piglets before weaning. Healthy piglets showed a continuous decrease in Lactobacillus and Escherichia, as well as a gradual increase in Prevotella with the transition to solid food. An altered relationship between Prevotella and Escherichia may be the main cause of diarrhea in preweaned piglets, whereas reduced numbers of Bacteroides, Ruminococcus, Bulleidia, and Treponema that are responsible for the digestion and utilization of solid feeds may be related to the onset of postweaning piglet diarrhea. The Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) functional analysis indicated that a reduction in genes involved in carbohydrate metabolism induced by intestinal dysbacteriosis in diarrheic piglets was one of the major causes of diarrhea at the three dietary stages. These findings provide insights into developing an intervention strategy for better management of diarrhea in piglets.

Keywords: carbohydrate metabolism, diarrhea, diet, gut microbiota, piglets, weaning

We characterized changing microbial populations in neonatal piglets from suckling the sow, to sow‐suckled plus supplemental creep feeding, and through weaning of piglets to a solid nursery diet in healthy piglets and piglets with diarrhea. Post‐weaning feed is a primary factor influencing the dynamic colonization by microflora in healthy piglets, an obvious continuous decrease in Lactobacillus and Escherichia, as well as a gradual increase in Prevotella in healthy piglets with the transition to solid food. An altered relationship between Prevotella and Escherichia may be the main cause of diarrhea in pre‐weaning piglets, while reduced numbers of Bacteroides, Ruminococcus, Bulleidia, and Treponema may be related to the onset of post‐weaning piglet diarrhea. These findings provide insights for developing an intervention strategy for better management of diarrhea in piglets.

graphic file with name MBO3-8-e923-g010.jpg

1. INTRODUCTION

The gastrointestinal microbiota of mammals play numerous roles in maintaining host health, such as regulating intestinal nutrient metabolism, synthesizing vitamins, promoting the development and maturation of the gut‐associated immune system, and protecting against pathogenic bacteria (Buffie & Pamer, 2013; Kabat, Srinivasan, & Maloy, 2014; Richards, Gong, & Lange, 2005). Diarrhea and gut microbial dysbiosis show reciprocal causation (Zoetendal, Akkermans, Vliet, Visser, & Vos, 2000). In the diarrheic condition, some normal indigenous microflora are discharged and invasive pathogens are abnormally increased, which preferentially lead to a disproportionate amount of beneficial microbes in the gastrointestinal tract; conversely, harmful substances produced by abnormal flora cause abnormalities in the intestinal function and immune response, which in turn cause the development of diarrhea and enteritis (Ward et al., 2016).

Piglet diarrhea is the most common enteric disease in swine, which leads to low growth rates and high mortality rates in neonatal and young piglets. Morris, Davies, and Lawton (2002) reported that almost half (49%) of piglet deaths are caused by diarrhea, which has a detrimental economic impact on the swine industry. To improve the utilization efficiency of sows on modern, intensive pig farms, piglets are usually given supplementary feeding at 1–2 weeks of age and weaned (with a solid nursery diet) at 3 or 4 weeks of age. However, the microenvironment of the gastrointestinal tract is particularly vulnerable to disruptions during the dynamic development of the intestinal mucosal structure and function in young piglets (Isaacson & Kim, 2012). Furthermore, the immune system of piglets undergoes significant postnatal development and has been suggested as a factor influencing the structure of intestinal community (Bailey et al., 2001). These diverse factors often induce the dysfunction of intestinal microflora, thus resulting in the high incidence of diarrhea in piglets.

Several investigations on intestinal microbiota have been focused on dynamic colonization at different ages or following dietary changes in healthy piglets, particularly at weaning (Frese, Parker, Calvert, & Mills, 2015; Slifierz, Friendship, & Weese, 2015). These studies provide evidence that the switch from sows' milk to solid diets critically influences microbial colonization in the immature gastrointestinal tract. Furthermore, several lines of evidence suggest that both specific bacterial species and microbial communities exert either pathogenic effects that facilitate diarrheal disease or probiotic effects that enhance intestinal health (Azcarate‐Peril et al., 2011; Jonach, Boye, Stockmarr, & Jensen, 2014). For instance, the occurrence of neonatal piglet diarrhea is closely related to increases in Prevotella, Sutterella, Campylobacter, and Fusobacteriaceae, as well as a decrease in several members of the phylum Firmicutes (Hermann‐Bank et al., 2015; Yang et al., 2017). The development of mucohemorrhagic diarrhea in Brachyspira hyodysenteriae‐infected piglets was associated with the perturbation of intestinal microbiota, with inoculated diarrheic pigs having lower bacterial numbers and a lower Bacteroidetes:Firmicutes ratio than uninoculated pigs (Costa, Chaban, Harding, & Hill, 2014). Dietary supplements of Enterococcus faecalis LAB31 in weaned piglets may increase the numbers of Lactobacillus and consequently reduce the incidence of diarrhea (Hu et al., 2015).

Given these crucial implications, animal scientists have started to perform microbial intervention strategies to improve animal health status, as well as prevent or treat enteric diseases. Zhang et al. (2017) revealed that oral administration of a Bacillus mix reprograms the gut microbiota and enhances goblet cell function to ameliorate pig diarrhea caused by enterotoxigenic Escherichia coli infection. A recent study indicated that fecal microbiota transplantation (FMT) could reduce susceptibility to epithelial injury and modulate tryptophan metabolism in the microbial community of a piglet model (Geng et al., 2018). Hu, Geng, et al. (2018) and Hu, Ma, et al. (2018) established a standardized model of exogenous FMT in pigs and subsequently found that FMT and oral administration of Lactobacillus gasseri LA39 and Lactobacillus frumenti strains could modulate the structure of gut microbiota and prevent diarrhea induced by early weaning stress in recipient piglets. In children, microbiota reconstitution has been used to prevent and treat diarrhea caused by Clostridium difficile infection (Buffie et al., 2015). Thus, it is conceivable that identification of the gut microbiota in diet‐matched diarrheic piglets could also provide translatable knowledge regarding digestive physiological mechanisms, as well as microbial prevention and therapy for diarrheic disease. However, very few studies have characterized the intestinal microbiota of diarrheic piglets during intestinal development and the associated dietary changes.

In this study, we first characterized the dynamic establishment of individual microbiota in healthy piglets following age‐related dietary changes: sow‐reared (sows' milk), early supplementary creep‐feeding (sows' milk + starter diet), and weaning (solid nursery diet). Second, we examined the differences in the intestinal microbial balance between diarrheic and healthy piglets during these dietary changes. We demonstrated an obvious continuous decrease in Lactobacillus and Escherichia, as well as a gradual increase in Prevotella in healthy piglets with the transition to solid food. An altered relationship between Prevotella and Escherichia may be the main cause of diarrhea in preweaned piglets, while reduced numbers of Bacteroides, Ruminococcus, Bulleidia, and Treponema may be related to the onset of postweaning piglet diarrhea. These findings provide insights for the development of an intervention strategy for better management of diarrhea in piglets.

2. MATERIALS AND METHODS

2.1. Animals and sample collection

Piglets were the progeny of six third‐parity, healthy Large White sows that were subjected to artificial insemination within 2 days and maintained under identical husbandry practices and epidemic prevention systems on a commercial farm in Gansu province, China, during July 2015. The farm had no previous history of bacterial or viral infections. At birth, the piglets were marked by ear notching for individual identification. They all received identical standards of housing and management, and were exclusively sow‐reared during the first 2 weeks, followed by supplementation with piglet early starter diets at 2 weeks of age. After weaning at 4 weeks of age, piglets were raised on solid nursery feed. The starter diet provided 14.6 MJ/kg digestible energy (DE), 21.0% crude protein, 4.0% crude fiber, 7.0% crude ash, 0.5%–1.2% calcium, 0.55% total phosphorus, 0.3%–1.2% salt, and 1.3% lysine from the 15th to 28th days. For the next 2 weeks after weaning, the diet contained 14.6 MJ/kg DE, 20% crude protein, 4.0% crude fiber, 7.0% crude ash, 0.5%–1.2% calcium, 0.55% total phosphorus, 0.3%–1.2% salt, and 1.45% lysine. The piglets were given ad libitum access to water throughout the experimental period. The general health of each piglet was closely monitored with special attention to fecal consistency and disease history. According to these observations, piglets were defined as diarrheic or healthy and their feces were collected as described previously (Yang et al., 2017). Briefly, diarrheic piglets were those showing signs of diarrhea for at least two consecutive days with thickened and watery feces; healthy piglets never experienced diarrhea or other diseases. Diarrheic samples were collected directly using sterile tools (week 1) or sterile cotton swabs (week 3 and week 5) and immediately frozen in liquid nitrogen.

The experimental design of this study is illustrated in Figure 1. To analyze the microbial structure and diversity of healthy piglets at the sow‐reared (sows' milk), early supplementary creep‐feeding (sows' milk + starter diet) and weaning (solid nursery diet) stages, fecal samples from six healthy piglets with similar birth weights and from different litters were collected using sterile cotton swabs at 1 week (H_week1), 3 weeks (H_week3), and 5 weeks (H_week5) of age, respectively. A case–control study was conducted to investigate the fecal microbial profiles of diet‐matched diarrheic and healthy piglets. Diarrheic samples collected at 7–9 days were classified as week 1 (D_week1, n = 10), those at 24–28 days were classified as week 3 (D_week3, n = 10), and those at 35–40 days were classified into week 5 (D_week5, n = 5). The six H_week1 samples and 10 D_week1 samples were also used in our previous study (Yang et al., 2017).

Figure 1.

Figure 1

Open in a new tab

Experimental design of this study

2.2. 16S rRNA gene sequencing

16S rRNA gene sequencing was used to characterize microbial community diversity and composition in 27 fecal samples of week 3 and week 5 piglets (D_week3 vs. H_week3; D_week5 vs. H_week5). Briefly, bacterial genomic DNA was extracted from fecal samples using a TIANamp stool DNA kit (TIANGEN) according to the manufacturer's instructions. The quality and concentration of samples were estimated using 1% agarose gels and a NanoDrop 2000 spectrophotometer (Thermo Scientific), respectively. The extracted DNA was diluted to 1 ng/μl as a template for PCR using barcoded primers flanking the V4 hypervariable region of bacterial 16S rRNA gene; primer sequences were 515F (5′‐GTGCCAGCMGCCGCGGTAA‐3′) and 806R (5′‐GGACTACHVGGGTWTCTAAT‐3′). PCR reactions were carried out in 25 μl volumes using Phusion® High‐Fidelity PCR Master Mix (New England Biolabs) under the following thermal cycling conditions: one predenaturation cycle at 98°C for 1 min; 30 cycles of denaturation at 98°C for 10 s, annealing at 50°C for 30 s and elongation at 72°C for 60 s; and one postelongation cycle at 72°C for 5 min.

PCR products were purified using the Qiagen Gel Extraction kit (Qiagen). Sequencing libraries were generated using a TruSeq®DNA PCR‐Free Sample Preparation kit (Illumina) following the manufacturer's recommendations. Sequencing was performed on an Illumina HiSeq 2500 platform for 2 × 250 bp paired‐end reads at Novogene Bioinformatics Technology Co., Ltd. Paired‐end reads were merged using FLASH (Fast Length Adjustment of SHort reads, Version 1.2.11: http://ccb.jhu.edu/software/FLASH/), and quality filtering of raw reads was performed using the Quantitative Insights into Microbial Ecology (QIIME) pipeline (Caporaso et al., 2010). The acquired sequences were chimera filtered using the UCHIME algorithm (Haas et al., 2011) by aligning them to the reference database (Gold database, http://drive5.com/uchime/uchime_download.html).

2.3. Bioinformatics and statistical analyses

High‐quality sequences were assigned to distinct operational taxonomic units (OTUs) using the UPARSE pipeline (v7.0.1001) with a 97% similarity threshold (Edgar, 2013). Representative sequences of each OTU were then taxonomically classified at different levels (phylum, class, order, family, genus, and species) by comparing them to sequences in the GreenGene database (Desantis et al., 2006) using the RDP 3 classifier algorithm (v2.2). The OTU abundance was normalized using a standard with sequence number corresponding to the sample with the least number of sequences.

Alpha diversity measurements (i.e., observed species, Shannon index, Chao1, and ACE) and beta diversity were calculated using QIIME (Caporaso et al., 2010). Intergroup differences in alpha and beta diversity of bacterial communities among treatments (diarrheic vs. healthy) and weeks (1, 3, and 5) were analyzed by a nonparametric test: the Mann–Whitney U test was chosen for analysis of two groups, while the Wilcoxon rank‐sum test was chosen for analysis among more than two groups. Dissimilarity matrices of intragroup and intergroup beta distances were visualized using principal coordinate analysis (PCoA) and the unweighted pair‐group method with arithmetic means (UPGMA) analysis. A one‐way analysis of similarity (ANOSIM) test was performed to determine significant differences in bacterial communities among groups using the R software (v3.2.2) (Clarke & Gorley, 2006).

Linear discriminant analysis (LDA) coupled with effect size (LEfSe) was performed to identify the core bacterial taxa differentially represented among healthy piglet groups at the species or higher taxonomic levels. A size‐effect threshold of 4.0 for the logarithmic LDA score was used for discriminative functional biomarkers. Differentially abundant bacterial taxa between diarrheic and healthy piglets at each age (week) stage were detected using the Kruskal–Wallis test, and only taxa with a mean relative abundance >0.1% in at least one group were considered. Significance was considered at p < .05.

Functional gene content of the fecal microbiota was predicted using Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) (Langille et al., 2013) based on taxonomy obtained from the Greengenes (v.13.5) database (DeSantis et al., 2006). Predicted genes were normalized by the 16S rDNA copy number, and their metagenomic contributions were then hierarchically clustered and categorized using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database (Kanehisa et al., 2014).

2.4. Quantitative PCR (qPCR)

To assess the results of 16S rRNA gene sequencing, E. coli, Lactobacillus spp., and Prevotella spp., which have been reported to perform crucial functions in maintaining the intestinal health or disease of newborn animals (Bordin et al., 2013; Larsen et al., 2010), were selected for absolute quantification qPCR using previously validated bacterial group‐specific 16S primers (Table A1). The qPCR reactions were conducted in 25 µl volumes containing 12.5 µl 2 × PCR Master Mix, 0.5 µl of each primer, and 1.0 µl template DNA. The reaction conditions included one predenaturation cycle at 94°C for 5 min, 35 cycles of denaturation at 94°C for 30 s, annealing at optimum temperature for 30 s, and elongation at 72°C for 30 s, and one postelongation cycle at 72°C for 10 min. PCR products were purified using a DNA Fragment Quick Recovery Kit (Axygen), ligated into a pMD™19‐T vector (TaKaRa) and transformed into the E. coli DH 5a strains according to the manufacturer's instructions. Extraction of plasmid DNA and restriction enzyme digestion from positive clones were used to generate standard recombinant plasmids for each bacterial group. The concentration of standard plasmids was measured using ultraviolet spectrophotometer, and original copy number was calculated.

Standard curves for each target bacteria were generated from the data obtained from qPCR amplification using 10‐fold (i.e., 102–107) serial dilutions of standard recombinant plasmids as templates on an ABI 7500 real‐time PCR system (Applied Biosystems). All amplifications were performed in triplicate. Reactions were conducted in 20 µl volumes containing 10.0 µl SYBR® Premix Ex Taq (2×) Green Master Mix (SYBR green Master Mix, Applied Biosystems), 0.8 µl of each primer, and 1.0 µl template DNA. Amplification curve analyses were performed under with one predenaturation cycle at 94°C for 30 s, 45 cycles of denaturation at 94°C for 10 s, annealing at 60°C for 12 s, and elongation at 72°C for 30 s, and then single‐point signal detection at 72°C. Melt curve analysis was performed immediately after the amplification protocol under the following conditions: 95°C for 15 s, 60°C for 1 min, 95°C for 15 s with acquisition signal detection.

Data obtained from the amplification were transformed to give the number of bacterial log copies/µl feces according to the copy number of recombinant DNA plasmids. The Mann–Whitney U test was used for comparisons between two groups.

2.5. Spearman's correlation analysis

To capture extreme exclusion relationships among key microbial taxa, Spearman's correlation coefficient (r) was analyzed among marker bacterial genera for diarrheic and healthy piglets at week 3 and week 5 stages using the SPSS 18.0 software (SPSS Inc., 2009). Taxa with r > .6 or <−.6, and p < .05 were considered to have a strong correlation.

3. RESULTS

3.1. Description of sequencing data

We acquired 2,354,153 high‐quality paired‐end sequences, with an average of 253 bp read length per sample. Based on a 97% species similarity threshold, 1,342 OTUs were identified from all samples, resulting in the classification of 20 phyla, 34 classes, 62 orders, 81 families, and 151 genera. The number of effective tags and OTUs in each fecal sample and the number of sequences in each sample at each taxonomic level are illustrated in Figures A1 and A2. Across all samples, we assigned 99.21% and 68.61% of the total sequences to bacterial phyla and genera, respectively.

3.2. Bacterial composition and community diversity associated with age‐related dietary changes in diarrheic and healthy piglets

The relative abundances of the top 10 phyla and top 10 genera present in diarrheic and healthy piglets at different dietary stages are displayed in Figure 2. Bacteroidetes, Firmicutes, and Proteobacteria were the dominant phyla in both diarrheic and healthy piglets; proportions of these reads accounted for more than 95% of reads in healthy piglets at the three dietary stages (H_week1, H_week3, and H_week5), and the weaning diarrheic piglets at week 5 (D_week5). Bacteroidetes, Firmicutes, and Fusobacteria were the dominant microflora in diarrheic piglets before weaning (D_week1 and D_week3) (Figure 2a). Among the annotated genera, 41 had a mean relative abundance of more than 0.1%, accounting for 67.34% of the total bacteria. The dominant phyla and genera in 3‐week‐old piglets were the same as those in 1‐week‐old piglets. Bacteroides and Escherichia were the most prevalent genera present in healthy piglets at week 3 (H_week3), while Prevotella was most prevalent in weaning healthy piglets (H_week5) and diarrheic piglets at week 3 and week 5 (D_week3 and D_week5) (Figure 2b).

Figure 2.

Figure 2

Open in a new tab

Average relative abundance of the top 10 phyla (a) and the top 10 genera (b) in each piglet group

The alpha diversity of the fecal microbiota varied considerably following dietary changes in healthy pigs. The richness index (observed species, Chao1 and ACE) of healthy piglets subjected to supplementary creep‐feeding (H_week3) was significantly lower than that of either healthy piglets that were sow‐reared (H_week1) or those subjected to full solid feeding (H_week5) (p < .01, Table 1), indicating that sudden dietary changes may perturb the balance in the bacterial community diversity. When compared with healthy piglets that were sow‐reared (H_week1) and supplementary creep‐fed (H_week3), Chao1 and ACE of diarrheic piglets that were sow‐reared (D_week1) and supplementary creep‐fed (D_week3) were both increased (p < .05), while the observed species, Chao1, and ACE of diarrheic piglets after weaning (D_week5) were significantly decreased compared with those of healthy piglets (H_week5) (p < .01, Table 2).

Table 1.

Comparison of fecal bacterial α diversity among healthy piglet groups at three age‐related dietary stages

Alpha diversity index Mean ± SEM

Kruskal–Wallis test

(p‐value)

 Mann–Whitney U test (p‐value)
H_week1 H_week3 H_week5 H_week1 versus H_week3 H_week1 versus H_week5 H_week3 versus H_week5
Observed species 499.667 ± 25.264 423.667 ± 11.170 644.667 ± 13.073 0.0009 0.0129 0.0081 0.0050
Shannon 5.854 ± 0.194 5.641 ± 0.174 6.919 ± 0.077 0.0031 0.5887 0.0022 0.0022
Chao1 595.009 ± 23.543 520.983 ± 17.225 777.185 ± 26.145 0.0013 0.0411 0.0022 0.0022
ACE 602.102 ± 24.649 520.659 ± 11.531 783.788 ± 21.174 0.0008 0.0087 0.0022 0.0022
Open in a new tab

Table 2.

Comparison of fecal bacterial α diversity between diarrheic and healthy piglet groups at three age‐related dietary stages

Alpha diversity index Mean ± SEM

Mann–Whitney U test

(p‐value)

 Mean ± SEM

Mann–Whitney U test

(p‐value)

 Mean ± SEM

Mann–Whitney U test

(p‐value)
H_week1 D_week1 H_week3 D_week3 H_week5 D_week5
Observed species 499.667 ± 25.264 544.700 ± 14.403 0.1179 423.667 ± 11.170 484.700 ± 20.365 0.0824 644.667 ± 13.073 546.400 ± 19.057 0.0080
Shannon 5.854 ± 0.194 6.024 ± 0.160 0.6354 5.641 ± 0.174 5.635 ± 0.251 0.8749 6.919 ± 0.077 6.377 ± 0.196 0.0519
Chao1 595.009 ± 23.543 682.561 ± 18.776 0.0160 520.983 ± 17.225 611.110 ± 21.807 0.0075 777.185 ± 26.145 641.164 ± 23.778 0.0087
ACE 602.102 ± 24.649 680.636 ± 16.073 0.0420 520.659 ± 11.531 610.335 ± 21.146 0.0075 783.788 ± 21.174 644.361 ± 2.176 0.0043
Open in a new tab

We found no significant difference in beta diversity of the OTU community structure in healthy piglets among the different sampling stages (Wilcoxon rank‐sum test, p > .05). Beta diversity was lower in healthy piglets than in diarrheic piglets at the different sampling stages (Wilcoxon rank‐sum test, p < .01; Figure 3a), indicating that diarrhea causes variance in fecal microbial structure and diversity in individual piglets. The principal coordinate analysis (PCoA)‐based trajectory plot also revealed distinct structures among healthy piglets of different ages as well as diarrheic and healthy piglets of the same age, and the ANOSIM for differences was significant (R‐value > .5, p < .01; Figure 3b). The structure of the gut microbiota became increasingly similar with age and the transition to solid food; before weaning, diarrheic and healthy piglets had distinct microbiota, while there was little difference between the two groups after weaning. Similarity cluster analysis using the UPGMA showed good agreement with PCoA analysis (Figure 3c), indicating the fecal microflora in healthy piglets is ever changing with progressive change of dietary stage, and diarrhea primarily affects the microbial communities in piglets before weaning.

Figure 3.

Figure 3

Open in a new tab

Comparison of fecal microbial community structure of diarrheic and healthy piglets among groups. (a) Boxplot of fecal bacterial β‐diversity (Wilcoxon rank‐sum test, p < .01). (b) PCoA analysis of piglet fecal samples based on weighted UniFrac distances (ANOSIM R‐value > .5, p < .01). (c) Similarity cluster analysis of piglet fecal samples using UPGMA

3.3. Bacterial biomarkers in healthy piglets at different age‐related dietary stages

We performed LEfSe analysis to reveal the significant ranking of abundant bacterial taxa among H_week1, H_week3, and H_week5 samples. The cladogram in Figure 4a highlights 15 important bacterial taxa, and their significant effects are displayed using LDA scores (Figure 4b). The biomarkers in healthy piglets at 1 week of age were Bacilli (h), Lactobacillales (g), Lactobacillaceae (f), Lactobacillus, and Lactobacillus delbrueckii, forming one branch; and Gammaproteobacteria (o), Enterobacteriales (n), Enterobacteriaceae (m), Escherichia, and E. coli forming a second branch. Clostridium and Bacteroides were biomarkers in healthy piglets at 3 weeks of age. In healthy piglets at 5 weeks of age, the genera Prevotella/[Prevotella], Phascolarctobacterium and the classes Veillonellaceae and [Paraprevotellaceae] were important biomarkers.

Figure 4.

Figure 4

Open in a new tab

Core biomarkers in healthy piglet groups by LEfSe analysis. (a) The cladogram shows the microbial species exhibiting significant differences in the three groups. Red, green, and blue nodes in the phylogenetic tree represent microbial species that play an important role in the week 1, week 3, and week 5 groups, respectively. (b) Species with significant differences in abundance that have an LDA score > 4.0. The length of the histogram represents the LDA score

3.4. Microbial taxa increased or decreased in diarrheic piglets at different age‐related dietary stages

We analyzed differences in the major microbial taxa (mean relative abundance > .1% in either of the two groups) between diarrheic and healthy piglets at 3 and 5 weeks of age using the Kruskal–Wallis test (Figure 5).

Figure 5.

Figure 5

Open in a new tab

Bacterial taxa showing differences between diarrheic and healthy piglets at 3 weeks (a) and 5 weeks (b) of age. Bacterial taxa with mean relative abundances >0.1% in at least one group are included

For piglets at 3 weeks of age, three phyla, 11 families, and 20 genera showed significant differences between healthy and diarrheic piglets (Figure 5a). The relative abundances of the phyla Firmicutes (D_week3 vs. H_week3: 0.2269 vs. 0.4435, p < .001) and Euryarchaeota (D_week3 vs. H_week3: 0.0006 vs. 0.0049, p = .04) were significantly decreased in piglets with diarrhea, while the relative abundance of the phylum Fusobacteria (D_week3 vs. H_week3: 0.2097 vs. 0.0223, p = .006) was significantly elevated in diarrheic piglets compared to healthy piglets. At the genus level, seven genera, Prevotella, Sutterella, Anaerovibrio, Odoribacter, Pasteurella, CF231, and Anaerobiospirillum, showed a higher relative abundance in diarrheic piglets than in healthy piglets at 3 weeks of age; Escherichia, and nine genera, including Clostridium, Oscillospira, Ruminococcus/[Ruminococcus], Faecalibacterium, Dorea, 02d06, [Eubacterium], Desulfovibrio, SMB53, and Blautia, showed lower relative abundance in 3‐week‐old diarrheic piglets than in healthy piglets at 3 weeks of age (p < .05).

For piglets at 5 weeks of age, only the phylum Spirochaetes (D_week5 vs. H_week5: 0.0027 vs. 0.0135, p = .035); the four families Bacteroidaceae, Enterococcaceae, Pasteurellaceae, and Spirochaetaceae; and the five genera Bacteroides, Clostridium, Ruminococcus/[Ruminococcus], Bulleidia, and Treponema showed significant differences between healthy and diarrheic piglets (Figure 5b). The relative abundances of all these bacterial taxa were decreased in diarrheic piglets compared with healthy piglets.

To confirm the results of 16S rRNA gene sequencing, three specific microbial communities (E. coli, Lactobacillus, and Prevotella) were subjected to qPCR (Figure 6). Significant differences in the absolute abundance of Lactobacillus, E. coli, and Prevotella were compared between preweaned and postweaned healthy piglets (Figure 6a). After weaning, the abundance of Lactobacillus and E. coli was markedly decreased, while the abundance of Prevotella was increased in healthy piglets (p < .05). The absolute abundance of Prevotella in preweaned diarrheic piglets was greater than that in preweaned healthy piglets (p < .05), while the abundance of Lactobacillus and E. coli was significantly lower in preweaned diarrheic piglets than in preweaned healthy piglets (p < .05) (Figure 6b). These data were consistent with the results of 16S rRNA gene sequencing, indicating our differential bacterial taxonomy and abundance estimations are highly reliable.

Figure 6.

Figure 6

Open in a new tab

Fecal bacterial concentrations of Lactobacillus, Escherichia coli, and Prevotella quantified by qPCR. (a) Differences in relative abundance between preweaning and postweaning healthy piglets. (b) Differences in relative abundance between healthy and diarrheic piglets before weaning. Significance is considered at p < .05

3.5. Correlations among bacterial genera in healthy and diarrheic piglets

We performed Spearman's correlation analysis of different bacterial genera of diarrheic and healthy piglets at week 3 and week 5.

For piglets given early supplementary creep‐feed (week 3), a strong negative correlation was observed between Prevotella and Escherichia in healthy samples (r < −.6, p < .05), while this correlation was relatively weaker in diarrheic piglets. Diarrhea also caused the correlation between Lactobacillus and [Ruminococcus] seen in healthy piglets to change from negative to positive (r > .6, p < .05) (Table 3). This transformation in correlation may be ascribed to the aberration of microbial balance in the diarrheic condition. More understandably, numerous obligate anaerobes with highly similar phylogenic relationships and functions, such as members of the class Clostridia (Ruminococcus/[Ruminococcus], Blautia, Eubacterium, Faecalibacterium, Oscillospira, and Dorea), showed strong positive correlations in both diarrheic and healthy groups (r > .6, p < .05). However, only Clostridium was positively correlated with [Ruminococcus] in postweaned healthy piglets (r = .9, p < .05), and no significant correlation was noted among other bacterial genera (p > .05).

Table 3.

Spearman's correlation analysis among maker bacterial genera in diarrheic and healthy piglets at 3 weeks of age

Genus Spearman's correlation coefficient Genus Spearman's correlation coefficient
Healthy Diarrhea Healthy Diarrhea
Prevotella Escherichia −0.829* −0.442 Odoribacter 02d06 0.829* 0.439
Prevotella Clostridium 0.543 −0.665* Odoribacter CF231 0.257 0.802**
Prevotella [Eubacterium] −0.257 0.659* Odoribacter [Ruminococcus] 0.714 0.711*
Prevotella [Ruminococcus] −0.086 0.675* Odoribacter Blautia 0.543 0.771**
Escherichia Clostridium −0.371 0.689* Ruminococcus Dorea 0.086 0.948**
Escherichia Pasteurella 0.143 0.689* Ruminococcus [Eubacterium] 0.829* 0.756*
Lactobacillus Sutterella 0.143 −0.733* Ruminococcus CF231 −0.657 0.766**
Lactobacillus Anaerovibrio 0.883* −0.103 Sutterella Oscillospira −0.543 −0.733*
Lactobacillus Oscillospira −0.829* 0.333 Sutterella [Prevotella] −0.371 −0.709*
Lactobacillus [Prevotella] −0.086 0.770** Sutterella Odoribacter 0.086 −0.939**
Lactobacillus Odoribacter −0.657 0.830** Sutterella Ruminococcus 0.257 −0.818**
Lactobacillus Faecalibacterium −0.754 0.709* Sutterella Faecalibacterium 0.058 −0.709*
Lactobacillus CF231 −0.714 0.802** Sutterella Dorea −0.029 −0.644*
Lactobacillus [Ruminococcus] −0.829* 0.632* Sutterella CF231 −0.143 −0.851**
Lactobacillus SMB53 −0.943** −0.197 Sutterella [Ruminococcus] −0.086 −0.772**
Lactobacillus Blautia −0.886* 0.489 Sutterella Anaerobiospirillum 0.265 0.644*
Oscillospira CF231 0.486 0.748* Sutterella Blautia −0.314 −0.838**
Oscillospira SMB53 0.943** 0.185 Clostridium Anaerovibrio −0.853* 0.506
Oscillospira Blautia 0.886* 0.973** Anaerovibrio Faecalibacterium −0.851* −0.321
[Prevotella] Odoribacter −0.257 0.794** Anaerovibrio SMB53 −0.765 −0.745*
[Prevotella] Ruminococcus −0.486 0.648* Anaerovibrio Blautia −0.853* −0.367
Odoribacter Ruminococcus 0.371 0.794** Oscillospira Odoribacter 0.486 0.636*
Odoribacter Dorea 0.886* 0.644* Oscillospira Ruminococcus −0.086 0.636*
Oscillospira 02d06 0.771 0.854** 02d06 CF231 0.143 0.731*
Ruminococcus [Ruminococcus] 0.486 0.942** 02d06 [Ruminococcus] 0.886* 0.465
Ruminococcus Blautia 0.257 0.722* 02d06 SMB53 0.829* 0.328
Pasteurella Desulfovibrio 0.829* −0.25 02d06 Anaerobiospirillum −0.912* −0.41
Dorea [Eubacterium] −0.257 0.765* 02d16 Blautia 0.771 0.822**
Dorea [Ruminococcus] 0.6 0.845** [Ruminococcus] [Eubacterium] 0.486 0.755*
CF231 [Ruminococcus] 0.2 0.841** [Ruminococcus] SMB53 0.886* −0.086
CF232 Blautia 0.371 0.831** [Ruminococcus] Anaerobiospirillum −0.853* −0.284
CF231 Faecalibacterium 0.812* 0.821** [Ruminococcus] Blautia 0.943** 0.672*
[Ruminococcus] Faecalibacterium 0.406 0.644* SMB53 Blautia 0.943** 0.134
Open in a new tab

Correlation coefficients ≥ .6 or ≤−.6 either one group with p < .05 are showed.

*

p < .05.

**

p < .01.

3.6. Functional differences of fecal microbiota between diarrheic and healthy piglets

We compared the functional gene composition of fecal microbiota between diarrheic and healthy piglets using the PICRUSt software. As shown in Figure 7a, notable differences in KEGG pathways between 3‐week‐old diarrheic and healthy piglets included the enrichment of functional genes involved in metabolic pathways, and genetic and environmental information processing (p < .05). The metabolic functional genes showing a significantly increased presence in diarrheic piglets were involved in energy metabolism, metabolism of cofactors and vitamins, glycan biosynthesis and metabolism, metabolism of terpenoids and polyketides, and the biosynthesis of other secondary metabolites. In addition, genes associated with nucleotide metabolism were enriched in diarrheic piglets. However, crucial carbohydrate metabolism was reduced in diarrheic piglets. For the genetic and environmental information processing category, functional genes for signal transduction and membrane transport were decreased in diarrheic piglets compared with healthy piglets. At the postweaning stage (week 5), only the functional pathways of carbohydrate metabolism and the excretory system exhibited different gene abundances between diarrheic and healthy piglets (p < .05; Figure 7b). These findings suggest that one of the major causes of diarrhea is the reduced uptake and fermentation of available carbohydrates caused by enteric dysbacteriosis in diarrheic piglets.

Figure 7.

Figure 7

Open in a new tab

PICRUST analysis of KEGG metabolic pathways at the second level. Graphs show the abundance ratios of different functions between diarrheic and healthy piglets at 3 weeks old (a) and 5 weeks old (b). p < .05 represents a significant difference

4. DISCUSSION

4.1. Microbiota variations in healthy piglets at different age‐related dietary stages

Several studies have shown that the gut microbiome of piglets is rapidly colonized with increasing age and dietary changes (Pajarillo, Chae, Balolong, Bum Kim, & Kang, 2014; Slifierz et al., 2015). In the present study, we analyzed microbial composition and diversity in six healthy piglets at 1, 3, and 5 weeks of age. Alpha diversity was first decreased at 3 weeks of age and then increased at 5 weeks of age, in agreement with the results of Frese et al. (2015), and this is likely linked to the reduction in maternal antibodies absorbed in piglets by 3 weeks old. After weaning, however, with immune system development and the establishment of intestinal microflora of piglets, microbial diversity was increased to accommodate digestion and absorption solid food.

The developing fecal microbiota of piglets in our study was similar to that observed in previous studies, which found Firmicutes, Proteobacteria, Bacteroidetes, Fusobacteria, and Actinobacteria as the predominant and stable bacterial phyla in piglets (Slifierz et al., 2015). Bacterial diversity and the core microflora of piglets varied with age, with the relative abundance of Firmicutes increasing, and the relative abundance of Proteobacteria, Fusobacteria, and Actinobacteria decreasing as piglet age increased (Slifierz et al., 2015). At the genus level, we found that Lactobacillus, Escherichia, and Clostridium were more abundant in preweaned healthy piglets than in postweaned piglets. Escherichia and Lactobacilli are commonly found in newborn animal intestines (Collado, Cernada, Baüerl, Vento, & Pérez‐Martínez, 2012). Escherichia coli is a representative species of the genus Escherichia; most E. coli strains are harmless and exert a barrier effect against colonization by intestinal pathogenic bacteria (Hudault, Guignot, & Servin, 2001), producing vitamin B and K2 for their hosts (Meganathan, 2001). Lactobacilli can protect against enteric pathogens by competing for nutrients and mucosal binding sites, and producing antibacterial substances (i.e., lactic acid, bacteriocin, etc.) (Li et al., 2012; Mann et al., 2014). Liu et al. (2017) reported that Lactobacillus casei can improve porcine intestinal immunologic function and consequently reduce the number of cases of piglet diarrhea and death. After weaning, the proportion of Lactobacillus in the gut microbiome of piglets declines (Pajarillo, Chae, Balolong, Kim, et al., 2014; Su, Yao, Perez‐Gutierrez, Smidt, & Zhu, 2008). In the present study, Lactobacillus and Escherichia were the core microflora of piglets at 1 week of age, indicating that they play crucial roles in establishing and maintaining the intestinal flora of piglets after birth.

Several strains representing the genus Clostridium are butyrate producers, which convert oligosaccharides (i.e., soybean fibers, fructo‐oligosaccharide, and maltose) to organic acids and alcohols, and thus maintain the balance of intestinal microflora (Louis & Flint, 2009). Additionally, Clostridium can modulate systemic immune responses by inducing the expansion of regulatory Tregs and the production of inflammatory cytokines, and is associated with colitis resistance (Atarashi et al., 2011). Similar to the finding of Gorham, Williams, Gidley, and Mikkelsen (2016), we found that Clostridium was a core bacterial genus in piglets after supplementary creep‐feeding (3 weeks), suggest that an increase of Clostridium is conducive for the digestion of cellulose and hemicellulose substrates in piglets. Alternatively, certain dietary constituents provide main energy source or affect gastrointestinal acidity for the growth of gut microbiota, and it is likely a more pH neutral digesta is more conducive for Clostridium to thrive in the intestine.

Although Slifierz et al. (2015) found that Megasphaera and Lactobacillus were the predominant genera in postweaned healthy piglets, there is evidence that Prevotella spp. dominate swine fecal microbial communities and gradually increase in numbers with age (Lamendella, Domingo, Ghosh, Martinson, & Oerther, 2011; Pajarillo, Chae, Balolong, Bum Kim, et al., 2014). Prevotella is a key microbial member of the gastrointestinal tracts of adult animals; it is crucial for the degradation of starch and plant polysaccharides but also has a strong capacity for mucoprotein catabolism (Ivarsson, Roos, Liu, & Lindberg, 2014; Rho et al., 2005). Frese et al. (2015) revealed that the relative abundance of Prevotellaceae increased nearly 50‐fold from an average of 0.3% in suckling piglets to 14.8% in weaned piglets. We found a low relative abundance of Prevotella in preweaned healthy piglets and, typically, a much higher abundance in postweaned healthy piglets. This difference is believed to be linked to a diet containing less‐digestible solid feed after weaning, suggesting that the increase in Prevotella is likely conducive to digestion and the utilization of feed nutrients in weaned piglets.

4.2. Differences in fecal microbiota between diarrheic and healthy piglets

Abundant evidence has revealed an intimate biological interaction between host animals and their gut microbiota. Pop et al. (2014) showed that fecal microbial diversity gradually increases with age and that children with diarrhea have lower microbial diversity than healthy children. In this study, analysis of microbial diversity revealed a higher diversity index in preweaned diarrheic piglets (D_week1 and D_week3) than in preweaned healthy piglets (H_week1 and H_week3). However, the diversity index in postweaned diarrheic piglets (D_week5) was lower than that in postweaned healthy piglets (H_week5). These results suggest that early supplementary creep‐feeding has little effect on microbial diversity and composition before weaning, while the imbalanced microbial diversity observed in diarrheic piglets is correlated with particular changes in their solid feed after weaning.

Earlier findings underscore the importance of microbial composition variation during the development and progression of intestinal diseases (Kamada, Seo, Chen, & Núñez, 2013). In this study, differences were also observed in bacterial species and their relative abundance between diarrheic and healthy piglets at three age‐related dietary stages, especially in those receiving early supplementary creep‐feed (H_week3 vs. D_week3). Furthermore, most of these major differences in bacteria coincided with those identified in our previous study in healthy and diarrheic piglets receiving full sows' milk (H_week1 vs. D_week1) (Yang et al., 2017). Diarrheic piglets showed decreased relative abundance of Firmicutes, the major genera being Ruminococcus/[Ruminococcus], Anaerovibrio, and Clostridium, which is consistent with previous research on neonatal healthy and diarrheic piglets (Hermann‐Bank et al., 2015). Several members of the phylum Firmicutes are believed to produce short‐chain fatty acids (SCFAs), related to energy acquisition and immune regulation (Atarashi et al., 2011). For instance, several members of Clostridiales are metabolized to produce butyrate (Devillard, Mcintosh, Duncan, & Wallace, 2007; Louis & Flint, 2009). Reduced abundance of these main Firmicutes types in the fecal microbiome of diarrheic piglets may concomitantly affect their digestive physiology and immune functions.

The phylum Proteobacteria including members of the genera Sutterella and Campylobacter is reportedly associated with intestinal inflammatory disease (Minamoto et al., 2014). In dogs with acute diarrhea, the relative abundances of Sutterella and Clostridium perfringens are decreased while those of Blautia, Faecalibacterium, and Turicibacter are increased when compared with levels in healthy dogs (Suchodolski et al., 2012). These findings concur with our results that Sutterella and Campylobacter showed increased relative abundance in preweaned diarrheic piglets, suggesting these two genera may be considered potential pathogens in the etiology of piglet diarrhea.

Research has shown that the co‐occurrence of E. coli and Enterococcus increases the risk of neonatal piglet diarrhea (Hermann‐Bank et al., 2015; Jonach et al., 2014). The predominant bacterial clades containing Gammaproteobacteria, Escherichia, and E. coli were significantly reduced in diarrheic piglets receiving both early supplementary creep‐feed and sows' milk; thus, we believe this may cause the reduced numbers of Proteobacteria. Furthermore, E. coli have been reported to have unique functions in cell adhesion, oxidative phosphorylation modulation, and protein synthesis (Vlasblom et al., 2015). For instance, the probiotic E. coli Nissle 1917 has been demonstrated to limit the expansion of competitors such as adherent‐invasive E. coli and the related pathogen Salmonella enterica in the inflamed intestine and prevent infectious diarrhea (Sassone‐Corsi et al., 2016). Based on these findings, it is understandable that the E. coli identified in the preweaned piglets of the present study is a nonpathogenic microorganism that confers benefits to the host.

Although Prevotella has important roles in nutrient digestion and absorption (Ivarsson et al., 2014; Sandberg, Kovatcheva‐Datchary, Björck, Bäckhed, & Nilsson, 2018), its pro‐inflammatory effect of Prevotella has been gaining increasing attention as it is correlated with enhanced susceptibility to arthritis (Hofer, 2013). Increases in the abundance of Prevotella copri correlate with reduction in the abundance of several beneficial microbes, such as Bacteroides, Clostridium cluster XIV, Blautia, and Lachnospiraceae, resulting in reduced resistance to colitis (Atarashi et al., 2011; Scher et al., 2013). Intriguingly, we obtained similar results to Scher et al. (2013) in that Prevotella had a greater relative abundance in diarrheic piglets than healthy piglets receiving early supplementary creep‐feed or sows' milk. This appears to be much easier for the colonies of Prevotella to become established in conditions of enteric disease than in normal intestinal conditions. Studies have indicated that Prevotella can help to reduce the risk of gastrointestinal disorders in children by inhibiting pathogenic Escherichia (De et al., 2010), particularly in diarrhea (Kang et al., 2013; Pop et al., 2014).

The disruption of competitive relationships between Prevotella and Escherichia was found to be associated with neonatal piglet diarrhea (Yang et al., 2017). These observations highlight attenuated or altered bacterial inter‐relationships in individuals with diarrheal disease; thus, synergistic or competitive relationships of intestinal bacteria are closely related to microbial diversity and health status in the intestinal microenvironment. Indeed, our evaluation of correlations among marker genera associated with piglet diarrhea during early supplementary creep‐feeding showed consistent results with the study of neonatal piglets receiving sows' milk (Yang et al., 2017). Therefore, we consider that Prevotella confers a high risk for preweaning piglet diarrhea, resulting in decreases in E. coli and beneficial Firmicutes, which maintain both a balance in the gastrointestinal microecological environment, and the normal function of the mucosal barrier and immunity.

The current consensus is that Fusobacterium is a common pathogen of the gastrointestinal mucosa, the high abundance of which is associated with increased expression of inflammatory factors (Nosho et al., 2016). The relative abundance of Fusobacteriaceae was higher in animals with neonatal porcine diarrhea or horse colitis than in healthy subjects (Costa et al., 2012; Hermann‐Bank et al., 2015). It is noteworthy that Fusobacterium is a small group with low abundance in the intestinal tract of humans and animals, and this is possibly the reason it has not been specifically reported in these studies possibly. Uniformly, we found that the proportion of members of the Fusobacteriaceae family in the fecal microbiome of diarrheic piglets was higher than that in both neonatal healthy piglets (Yang et al., 2017) and healthy piglets receiving early supplementary creep‐feed. This suggests that the Fusobacteriaceae group may be a valuable diagnostic indicator of preweaning piglet diarrhea.

When compared to postweaned healthy piglets, only the Spirochaetes phylum and five genera (Bacteroides, Clostridium, Ruminococcus/[Ruminococcus], Bulleidia, and Treponema) showed lower relative abundance in postweaned diarrheic piglets. These genera are all key participants in nutrient metabolism, including carbohydrate fermentation, and polysaccharide and steroid metabolism, and are crucial for maintaining normal physiological function of the intestine (Flint, Bayer, Rincon, Lamed, & White, 2008; Hess et al., 2011; Louis & Flint, 2009). Treponema and Bulleidia are low‐abundance microflora in the intestinal tracts of animals and humans. Our results concur with those of a previous study in which the relative abundance of Treponema accounted for 3%–4% of the fecal microbiome of 6‐month‐old healthy pigs (Lamendella et al., 2011). Taken together, a large discrepancy was noted in the fecal microflora associated with diarrhea between preweaned (sow‐reared and early supplementary creep‐fed) and postweaned piglets. As the diet of piglets is completely transformed to solid foodstuffs after weaning, a reduction in the numbers of beneficial bacteria reduces the ability of intestinal epithelial cells to digest and absorb proteins and carbohydrates, which in turn leads to permeability disorders and diarrhea.

The PICRUSt analysis of the fecal microbial function between diarrheic and healthy piglets gave similar results to the aforementioned analyses. Diarrhea caused by an intestinal microbiota disorder significantly changed the specific metabolic pathways present in preweaned piglets, which is consistent with the results of another study on diarrheic captive musk deer (Li et al., 2018). Compared with healthy piglets, the most obvious change in diarrheic piglets was the reduced abundance of functional genes involved in carbohydrate metabolism at all three age‐related dietary stages. Many of the bacterial taxa that showed reduced numbers in piglets with diarrhea are associated with the production of SCFAs from carbohydrates, which has also been observed in humans with Crohn's disease (Erickson et al., 2012), suggesting that carbohydrate dysmetabolism may be an important feature of piglet diarrheal disease. It may be as a consequence of increased levels of other important functions like energy metabolism, the metabolism of vitamins, cofactors, or terpenoids and polyketides, or glycan biosynthesis in preweaned diarrheic piglets.

5. CONCLUSIONS

Our study identified additional characteristics of the gut microbiota in diarrheic piglets during age‐related dietary changes and the development of intestinal physiology. Postweaning feed is a primary factor influencing the dynamic colonization by microflora in healthy piglets. Obvious changes include a continuous decrease of Lactobacillus and Escherichia, as well as a gradual increase of Prevotella during the transition to a solid diet. Piglets receiving sows' milk or early supplementary creep‐feed had identical major microbial communities that were associated with diarrhea. An altered relationship between Prevotella and Escherichia may be the main cause of diarrhea. Reduced numbers of Bacteroides, Ruminococcus, Bulleidia, and Treponema may be related to the onset of postweaning piglet diarrhea. These findings provide insights for the development of intervention strategies for better management of diarrhea in piglets. However, further studies should be considered that are focused on the reciprocal interactions between gut microbiota and host genetics and/or metabolic substances or the intestinal immune system in response to microbial alterations.

CONFLICT OF INTERESTS

None declared.

AUTHOR CONTRIBUTIONS

Conceptualization: Shuangbao Gun. Funding Acquisition: Shuangbao Gun. Investigation: Qiaoli Yang, Xiaoyu Huang, Pengfei Wang, Zunqiang Yan, Wenyang Sun. Writing – Original Draft Preparation: Qiaoli Yang. Writing – Review & Editing: Qiaoli Yang, Shengguo Zhao.

ETHICS STATEMENT

All animal experimental protocols were conducted according to the guidelines for the care and use of experimental animals established by the Ministry of Science and Technology of China (Approval number 2006‐398). The project was approved by the Institutional Animal Care and Use Committee (IACUC) of Gansu Agricultural University.

ACKNOWLEDGMENTS

This work was supported by the special funds for the discipline construction project of Gansu Agricultural University (Grant No. GAU‐XKJS‐2018‐042).

APPENDIX 1.

Table A1.

Specific primer targeting bacteria used for real‐time quantitative PCR

Bacteria Name Sequence (5′–3′) Size (bp)
Prevotella Prev_F CACCAAGGCGACGATCA 283
Prev_R GGATAACGCCYGGACCT
Escherichia coli E.coli_F GTTAATACCTTTGCTCATTGA 340
E.coli_R ACCAGGGTATCTAATCCTGTT
Lactobacillus Lab_F362 AGCAGTAGGGAATCTTCCA 341
Lab_R677 CACCGCTACACATGGAG
Open in a new tab

Figure A1.

Figure A1

Open in a new tab

Number of effective tags and OTUs in each fecal sample. The data of six H_week1 samples and ten D_week1 samples were obtained from our previously study (Yang et al., 2017)

Figure A2.

Figure A2

Open in a new tab

Number of sequences in piglet fecal samples at each taxonomic level. The data of six H_week1 samples and ten D_week1 samples were obtained from our previously study (Yang et al., 2017)

Yang Q, Huang X, Wang P, et al. Longitudinal development of the gut microbiota in healthy and diarrheic piglets induced by age‐related dietary changes. MicrobiologyOpen. 2019;8:e923 10.1002/mbo3.923

Data Availability Statement: The datasets generated and/or analyzed during the current study are available in the NCBI sequence read archive (SRA) database at https://trace.ncbi.nlm.nih.gov/ under BioProject number of SRP083116 and BioSample number of SRS2068524 and SRS1651658.

DATA AVAILABILITY STATEMENT

The datasets generated and/or analyzed during the current study are available in the NCBI sequence read archive (SRA) database at https://trace.ncbi.nlm.nih.gov/ under BioProject number of SRP083116 and BioSample number of SRS2068524 and SRS1651658.

REFERENCES

  1. Atarashi, K. , Tanoue, T. , Shima, T. , Imaoka, A. , Kuwahara, T. , Momose, Y. , … Honda, K. (2011). Induction of colonic regulatory T cells by indigenous Clostridium species. Science, 331, 337–341. 10.1126/science.1198469 [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Azcarate‐Peril, M. A. , Foster, D. M. , Cadenas, M. B. , Stone, M. R. , Jacobi, S. K. , Stauffer, S. H. , … Gookin, J. L. (2011). Acute necrotizing enterocolitis of preterm piglets is characterized by dysbiosis of ileal mucosa‐associated bacteria. Gut Microbes, 2, 234–243. 10.4161/gmic.2.4.16332 [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Bailey, M. , Plunkett, F. J. , Rothkotter, H. J. , Vega‐Lopez, M. A. , Haverson, K. , & Stokes, C. R. (2001). Regulation of mucosal immune responses in effector sites. Proceedings of the Nutrition Society, 60, 427–435. 10.1079/PNS2001118 [DOI] [PubMed] [Google Scholar]
  4. Bordin, A. I. , Suchodolski, J. S. , Markel, M. E. , Weaver, K. B. , Steiner, J. M. , Dowd, S. E. , … Cohen, N. D. (2013). Effects of administration of live or inactivated virulent Rhodococccus equi and age on the fecal microbiome of neonatal foals. PLoS ONE, 8, e66640 10.1371/journal.pone.0066640 [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Buffie, C. G. , Bucci, V. , Stein, R. R. , McKenney, P. T. , Ling, L. , Gobourne, A. , … Pamer, E. G. (2015). Precision microbiome reconstitution restores bile acid mediated resistance to Clostridium difficile . Nature, 517, 205–208. 10.1038/nature13828 [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Buffie, C. G. , & Pamer, E. G. (2013). Microbiota‐mediated colonization resistance against intestinal pathogens. Nature Reviews Immunology, 13, 790–801. 10.1038/nri3535 [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Caporaso, J. G. , Kuczynski, J. , Stombaugh, J. , Bittinger, K. , Bushman, F. D. , Costello, E. K. , … Knight, R. (2010). QIIME allows analysis of high‐throughput community sequencing data. Nature Methods, 7, 335–336. 10.1038/nmeth.f.303 [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Clarke, K. R. , & Gorley, R. N. (2006). PRIMER v6: User manual‐tutorial (pp. 192–193). Plymouth, UK: Plymouth Routine in Multivariate Ecological Research. Marine Laboratory. [Google Scholar]
  9. Collado, M. C. , Cernada, M. , Baüerl, C. , Vento, M. , & Pérez‐Martínez, G. (2012). Microbial ecology and host‐microbiota interactions during early life stages. Gut Microbes, 3, 352–365. 10.4161/gmic.21215 [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Costa, M. C. , Arroyo, L. G. , Allen‐Vercoe, E. , Stämpfli, H. R. , Kim, P. T. , Sturgeon, A. , & Weese, J. S. (2012). Comparison of the fecal microbiota of healthy horses and horses with colitis by high throughput sequencing of the V3–V5 region of the 16S rRNA gene. PLoS ONE, 7, e41484 10.1371/journal.pone.0041484 https://doi.org/ [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Costa, M. O. , Chaban, B. , Harding, J. C. S. , & Hill, J. E. (2014). Characterization of the fecal microbiota of pigs before and after inoculation with “Brachyspira hampsonii”. PLoS ONE, 9, e106399 10.1371/journal.pone.0106399 [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. De Filippo, C. , Cavalieri, D. , Di Paola, M. , Ramazzotti, M. , Poullet, J. B. , Massart, S. , … Lionetti, P. (2010). Impact of diet in shaping gut microbiota revealed by a comparative study in children from Europe and Rural Africa. Proceedings of the National Academy of Sciences of the United States of America, 107, 14691–14696. 10.1073/pnas.1005963107 [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. DeSantis, T. Z. , Hugenholtz, P. , Larsen, N. , Rojas, M. , Brodie, E. L. , Keller, K. , … Andersen, G. L. (2006). Greengenes, a chimera‐checked 16SrRNA gene database and workbench compatible with ARB. Applied and Environmental Microbiology, 72, 5069–5072. 10.1128/AEM.03006-05 [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Devillard, E. , Mcintosh, F. M. , Duncan, S. H. , & Wallace, R. J. (2007). Metabolism of linoleic acid by human gut bacteria: Different routes for biosynthesis of conjugated linoleic acid. Journal of Bacteriology, 189, 2566–2570. 10.1128/JB.01359-06 [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Edgar, R. C. (2013). UPARSE: Highly accurate OTU sequences from microbial amplicon reads. Nature Methods, 10, 996–998. 10.1038/nmeth.2604 [DOI] [PubMed] [Google Scholar]
  16. Erickson, A. R. , Cantarel, B. L. , Lamendella, R. , Darzi, Y. , Mongodin, E. F. , Pan, C. , … Jansson, J. K. (2012). Integrated metagenomics/metaproteomics reveals human host‐microbiota signatures of Crohn's disease. PLoS ONE, 7, e49138 10.1371/journal.pone.0049138 [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Flint, H. J. , Bayer, E. A. , Rincon, M. T. , Lamed, R. , & White, B. A. (2008). Polysaccharide utilization by gut bacteria: Potential for new insights from genomic analysis. Nature Reviews Microbiology, 6, 121–131. 10.1038/nrmicro1817 [DOI] [PubMed] [Google Scholar]
  18. Frese, S. A. , Parker, K. , Calvert, C. C. , & Mills, D. A. (2015). Diet shapes the gut microbiome of pigs during nursing and weaning. Microbiome, 3, 28 10.1186/s40168-015-0091-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Geng, S. , Cheng, S. , Li, Y. , Wen, Z. , Ma, X. , Jiang, X. , … Han, X. (2018). Fecal microbiota transplantation reduces susceptibility to epithelial injury and modulates tryptophan metabolism of microbial community in a piglet model. Journal of Crohn's and Colitis, 12(11), 1359–1374. 10.1093/ecco-jcc/jjy103 [DOI] [PubMed] [Google Scholar]
  20. Gorham, J. B. , Williams, B. A. , Gidley, M. J. , & Mikkelsen, D. (2016). Visualization of microbe‐dietary remnant interactions in digesta from pigs, by fluorescence in situ hybridization and staining methods; effects of a dietary arabinoxylan‐rich wheat fraction. Food Hydrocolloids, 52, 952–962. 10.1016/j.foodhyd.2015.09.011 [DOI] [Google Scholar]
  21. Haas, B. J. , Gevers, D. , Earl, A. M. , Feldgarden, M. , Ward, D. V. , Giannoukos, G. , … Birren, B. W. (2011). Chimeric 16S rRNA sequence formation and detection in Sanger and 454‐pyrosequenced PCR amplicons. Genome Research, 21, 494–504. 10.1101/gr.112730.110 [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Hermann‐Bank, M. L. , Skovgaard, K. , Stockmarr, A. , Strube, M. L. , Larsen, N. , Kongsted, H. , … Boye, M. (2015). Characterization of the bacterial gut microbiota of piglets suffering from new neonatal porcine diarrhoea. BMC Veterinary Research, 11, 139 10.1186/s12917-015-0419-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Hess, M. , Sczyrba, A. , Egan, R. , Kim, T.‐W. , Chokhawala, H. , Schroth, G. , … Rubin, E. M. (2011). Metagenomic discovery of biomass‐degrading genes and genomes from cow rumen. Science, 331, 463–467. 10.1126/science.1200387 [DOI] [PubMed] [Google Scholar]
  24. Hofer, U. (2013). Microbiome: Pro‐inflammatory Prevotella? Nature Reviews Microbiology, 12, 5 10.1038/nrmicro3180 [DOI] [PubMed] [Google Scholar]
  25. Hu, J. , Ma, L. , Nie, Y. , Chen, J. , Zheng, W. , Wang, X. , … Yan, X. (2018). A microbiota‐derived bacteriocin targets the host to confer diarrhea resistance in early‐weaned piglets. Cell Host & Microbe, 24, 817–832. 10.1016/j.chom.2018.11.006 [DOI] [PubMed] [Google Scholar]
  26. Hu, L. , Geng, S. , Li, Y. , Cheng, S. , Fu, X. , Yue, X. , & Han, X. (2018). Exogenous fecal microbiota transplantation from local adult pigs to crossbred newborn piglets. Frontiers in Microbiology, 8, 2663 10.3389/fmicb.2017.02663 [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Hudault, S. , Guignot, J. , & Servin, A. L. (2001). Escherichia coli strains colonising the gastrointestinal tract protect germfree mice against Salmonella typhimurium infection. Gut, 49, 47–55. 10.1136/gut.49.1.47 [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Hu, Y. , Dun, Y. , Li, S. , Zhang, D. , Peng, N. , Zhao, S. , & Liang, Y. (2015). Dietary Enterococcus faecalis LAB31 improves growth performance, reduces diarrhea, and increases fecal Lactobacillus number of weaned piglets. PLoS ONE, 10, e0116635 10.1371/journal.pone.0116635 [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Isaacson, R. , & Kim, H. B. (2012). The intestinal microbiome of the pig. Animal Health Research Reviews, 13, 100–109. 10.1017/S1466252312000084 [DOI] [PubMed] [Google Scholar]
  30. Ivarsson, E. , Roos, S. , Liu, H. Y. , & Lindberg, J. E. (2014). Fermentable non‐starch polysaccharides increases the abundance of Bacteroides‐Prevotella‐Porphyromonas in ileal microbial community of growing pigs. Animal, 8, 1777–1787. 10.1017/S1751731114001827 [DOI] [PubMed] [Google Scholar]
  31. Jonach, B. , Boye, M. , Stockmarr, A. , & Jensen, T. K. (2014). Fluorescence in situ hybridization investigation of potentially pathogenic bacteria involved in neonatal porcine diarrhea. BMC Veterinary Research, 10, 68 10.1186/1746-6148-10-68 [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Kabat, A. M. , Srinivasan, N. , & Maloy, K. J. (2014). Modulation of immune development and function by intestinal microbiota. Trends in Immunology, 35, 507–517. 10.1016/j.it.2014.07.010 [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Kamada, N. , Seo, S. U. , Chen, G. Y. , & Núñez, G. (2013). Role of the gut microbiota in immunity and inflammatory disease. Nature Reviews Immunology, 13, 321–335. 10.1038/nri3430 https://doi.org/ [DOI] [PubMed] [Google Scholar]
  34. Kanehisa, M. , Goto, S. , Sato, Y. , Kawashima, M. , Furumichi, M. , & Tanabe, M. (2014). Data, information, knowledge and principle: Back to metabolism in KEGG. Nucleic Acids Research, 42, D199–D205. 10.1093/nar/gkt1076 [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Kang, D. W. , Jin, G. P. , Ilhan, Z. E. , Wallstrom, G. , Labaer, J. , Adams, J. B. , & Krajmalnik‐Brown, R. (2013). Reduced incidence of Prevotella and other fermenters in intestinal microflora of autistic children. PLoS ONE, 8, e68322 10.1371/journal.pone.0068322 [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Lamendella, R. , Domingo, J. W. S. , Ghosh, S. , Martinson, J. , & Oerther, D. B. (2011). Comparative fecal metagenomics unveils unique functional capacity of the swine gut. BMC Microbiology, 11, 103 10.1186/1471-2180-11-103 [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Langille, M. G. , Zaneveld, J. , Caporaso, J. G. , McDonald, D. , Knights, D. , Reyes, J. A. , Huttenhower, C. (2013). Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences. Nature Biotechnology, 31(9), 814–821. 10.1038/nbt.2676 [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Larsen, N. , Vogensen, F. K. , van den Berg, F. W. J. , Nielsen, D. S. , Andreasen, A. S. , Pedersen, B. K. , … Jakobsen, M. (2010). Gut microbiota in human adults with type 2 diabetes differs from non‐diabetic adults. PLoS ONE, 5, e9085 10.1371/journal.pone.0009085 [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Li, X.‐Q. , Zhu, Y.‐H. , Zhang, H.‐F. , Yue, Y. , Cai, Z.‐X. , Lu, Q.‐P. , … Wang, J.‐F. (2012). Risks associated with high‐dose Lactobacillus rhamnosus in an Escherichia coli model of piglet diarrhoea: Intestinal microbiota and immune imbalances. PLoS ONE, 7, e40666 10.1371/journal.pone.0040666 [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Li, Y. , Hu, X. , Yang, S. , Zhou, J. , Qi, L. , Sun, X. , … Hu, D. (2018). Comparison between the fecal bacterial microbiota of healthy and diarrheic captive musk deer. Frontiers in Microbiology, 9, 300 10.3389/fmicb.2018.00300 [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Liu, C. , Zhu, Q. , Chang, J. , Yin, Q. , Song, A. , Li, Z. , … Lu, F. (2017). Effects of lactobacillus casei and Enterococcus faecalis on growth performance, immune function and gut microbiota of suckling piglets. Archives of Animal Nutrition, 71, 120–133. 10.1080/1745039X.2017.1283824 [DOI] [PubMed] [Google Scholar]
  42. Louis, P. , & Flint, H. J. (2009). Diversity, metabolism and microbial ecology of butyrate‐producing bacteria from the human large intestine. FEMS Microbiology Letters, 294, 1–8. 10.1111/j.1574-6968.2009.01514.x [DOI] [PubMed] [Google Scholar]
  43. Mann, E. , Schmitzesser, S. , Zebeli, Q. , Wagner, M. , Ritzmann, M. , & Metzler‐Zebeli, B. U. (2014). Mucosa‐associated bacterial microbiome of the gastrointestinal tract of weaned pigs and dynamics linked to dietary calcium‐phosphorus. PLoS ONE, 9, e86950 10.1371/journal.pone.0086950 [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Meganathan, R. (2001). Biosynthesis of menaquinone (vitamin K2) and ubiquinone (coenzyme Q): A perspective on enzymatic mechanisms. Vitamins and Hormones‐Advances in Research and Applications, 61, 173–218. 10.1016/S0083-6729(01)61006-9 [DOI] [PubMed] [Google Scholar]
  45. Minamoto, Y. , Otoni, C. C. , Steelman, S. M. , Büyükleblebici, O. , Steiner, J. M. , Jergens, A. E. , & Suchodolski, J. S. (2014). Alteration of the fecal microbiota and serum metabolite profiles in dogs with idiopathic inflammatory bowel disease. Gut Microbes, 6, 33–47. 10.1080/19490976.2014.997612 [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Morris, R. S. , Davies, P. R. , & Lawton, D. E. (2002). Evolution of diseases in the world's pig industry. 17th International pig veterinary society congress proceedings, Ames, IA, USA. [Google Scholar]
  47. Nosho, K. , Sukawa, Y. , Adachi, Y. , Ito, M. , Mitsuhashi, K. , Kurihara, H. , … Shinomura, Y. (2016). Association of Fusobacterium nucleatum with immunity and molecular alterations in colorectal cancer. World Journal of Gastroenterology, 22, 557–566. 10.3748/wjg.v22.i2.557 [DOI] [PMC free article] [PubMed] [Google Scholar]
  48. Pajarillo, E. A. B. , Chae, J.‐P. , Balolong, M. P. , Bum Kim, H. , & Kang, D.‐K. (2014). Assessment of fecal bacterial diversity among healthy piglets during the weaning transition. Journal of General and Applied Microbiology, 60, 140–146. 10.2323/jgam.60.140 [DOI] [PubMed] [Google Scholar]
  49. Pajarillo, E. A. , Chae, J. P. , Balolong, M. P. , Kim, H. B. , Seo, K.‐S. , & Kang, D.‐K. (2014). Pyrosequencing‐based analysis of fecal microbial communities in three purebred pig lines. Journal of Microbiology, 52(8), 646–651. 10.1007/s12275-014-4270-2 [DOI] [PubMed] [Google Scholar]
  50. Pop, M. , Walker, A. W. , Paulson, J. , Lindsay, B. , Antonio, M. , Hossain, M. , … Stine, O. (2014). Diarrhea in young children from low‐income countries leads to large‐scale alterations in intestinal microbiota composition. Genome Biology, 15, R76 10.1186/gb-2014-15-6-r76 [DOI] [PMC free article] [PubMed] [Google Scholar]
  51. Rho, J. , Wright, D. P. , Christie, D. L. , Clinch, K. , Furneaux, R. H. , & Roberton, A. M. (2005). A novel mechanism for desulfation of mucin: Identification and cloning of a mucin‐desulfating glycosidase (sulfoglycosidase) from Prevotella strain RS2. Journal of Bacteriology, 187, 1543–1551. 10.1128/JB.187.5.1543-1551.2005 [DOI] [PMC free article] [PubMed] [Google Scholar]
  52. Richards, J. D. , Gong, J. , & de Lange, C. F. M. (2005). The gastrointestinal microbiota and its role in monogastric nutrition and health with an emphasis on pigs: Current understanding, possible modulations, and new technologies for ecological studies. Canadian Journal of Animal Science, 85, 421–435. 10.4141/A05-049 [DOI] [Google Scholar]
  53. Sandberg, J. , Kovatcheva‐Datchary, P. , Björck, I. , Bäckhed, F. , & Nilsson, A. (2018). Abundance of gut Prevotella at baseline and metabolic response to barley prebiotics. European Journal of Nutrition, 25, 1–12. 10.1007/s00394-018-1788-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
  54. Sassone‐Corsi, M. , Nuccio, S.‐P. , Liu, H. , Hernandez, D. , Vu, C. T. , Takahashi, A. A. , … Raffatellu, M. (2016). Microcins mediate competition among Enterobacteriaceae in the inflamed gut. Nature, 540, 280–283. 10.1038/nature20557 [DOI] [PMC free article] [PubMed] [Google Scholar]
  55. Scher, J. U. , Sczesnak, A. , Longman, R. S. , Segata, N. , Ubeda, C. , Bielski, C. , … Littman, D. R. (2013). Expansion of intestinal Prevotella copri correlates with enhanced susceptibility to arthritis. Elife Sciences, 2, e01202 10.7554/eLife.01202 [DOI] [PMC free article] [PubMed] [Google Scholar]
  56. Slifierz, M. J. , Friendship, R. M. , & Weese, J. S. (2015). Longitudinal study of the early‐life fecal and nasal microbiotas of the domestic pig. BMC Microbiology, 15, 184 10.1186/s12866-015-0512-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
  57. SPSS Inc. (2009). PASW statistics for windows, version 18.0. Chicago, IL: SPSS Inc. [Google Scholar]
  58. Su, Y. , Yao, W. , Perez‐Gutierrez, O. N. , Smidt, H. , & Zhu, W. Y. (2008). Changes in abundance of Lactobacillus spp. and Streptococcus suis in the stomach, jejunum and ileum of piglets after weaning. FEMS Microbiology Ecology, 66, 546–555. 10.1111/j.1574-6941.2008.00529.x [DOI] [PubMed] [Google Scholar]
  59. Suchodolski, J. S. , Markel, M. E. , Garcia‐Mazcorro, J. F. , Unterer, S. , Heilmann, R. M. , Dowd, S. E. , … Toresson, L. (2012). The fecal microbiome in dogs with acute diarrhea and idiopathic inflammatory bowel disease. PLoS ONE, 7, e51907 10.1371/journal.pone.0051907 [DOI] [PMC free article] [PubMed] [Google Scholar]
  60. Vlasblom, J. , Zuberi, K. , Rodriguez, H. , Arnold, R. , Gagarinova, A. , Deineko, V. , … Babu, M. (2015). Novel function discovery with GeneMANIA: A new integrated resource for gene function prediction in Escherichia coli . Bioinformatics, 31, 306–310. 10.1093/bioinformatics/btu671 [DOI] [PMC free article] [PubMed] [Google Scholar]
  61. Ward, D. V. , Scholz, M. , Zolfo, M. , Taft, D. H. , Schibler, K. R. , Tett, A. , … Morrow, A. L. (2016). Metagenomic sequencing with strain‐level resolution implicates uropathogenic E. coli in necrotizing enterocolitis and mortality in preterm infants. Cell Reports, 14, 2912–2924. 10.1016/j.celrep.2016.03.015 [DOI] [PMC free article] [PubMed] [Google Scholar]
  62. Yang, Q. , Huang, X. , Zhao, S. , Sun, W. , Yan, Z. , Wang, P. , … Gun, S. (2017). Structure and function of the fecal microbiota in diarrheic neonatal piglets. Frontiers in Microbiology, 8, 502 10.3389/fmicb.2017.00502 [DOI] [PMC free article] [PubMed] [Google Scholar]
  63. Zhang, W. , Zhu, Y. H. , Zhou, D. , Wu, Q. , Song, D. , Dicksved, J. , & Wang, J. F. (2017). Oral administration of a select mixture of Bacillus probiotics affects the gut microbiota and goblet cell function following Escherichia coli challenge in newly weaned pigs of genotype MUC4 that are supposed to be enterotoxigenic E. coli F4ab/ac receptor negative. Applied and Environmental Microbiology, 83, e02747‐16 10.1128/AEM.02747-16 [DOI] [PMC free article] [PubMed] [Google Scholar]
  64. Zoetendal, E. G. , Akkermans, A. D. L. , Vliet, W. M. A. , Visser, J. A. G. M. D. , & Vos, W. M. D. (2000). The host genotype affects the bacterial community in the human gastronintestinal tract. Microbial Ecology in Health and Disease, 13, 129–134. 10.1080/089106001750462669 [DOI] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The datasets generated and/or analyzed during the current study are available in the NCBI sequence read archive (SRA) database at https://trace.ncbi.nlm.nih.gov/ under BioProject number of SRP083116 and BioSample number of SRS2068524 and SRS1651658.

Articles from MicrobiologyOpen are provided here courtesy of Wiley

RESOURCES