Lipid metabolism between Shaziling and Yorkshire pigs
Exogenous intake and free lipids are assembled in the liver and distributed to the tissues of the body. Therefore, the lipid levels were analyzed between Shaziling and Yorkshire pigs and the concentrations of TC and LDL were distinctly higher in Shaziling pig at 30, 60 and 300 days, GLU was notedly increased in Shaizling pig at 30, 60 and 150 days, whereas TG was lowered in Shaziling pig at 90 and 150 days (Fig 1).
The absorption and transport of lipids in the gut and the assembly and metabolism in the liver are important components of lipid metabolism. Then, we analyzed the expression of several genes associated with lipid metabolism in the mucosa (i.e., MOGAT2, DGAT1/2, CD36, and FABP1-4) and liver (i.e., ACC, PPARα/γ, SREBP1/2, and LXRα/β). Compared with the Yorkshire pigs, the expressions of SREBP1, LXRα, and SREBP2 were higher at 90 days and 300 days in Shaziling pigs (Fig 2A), while LXRβ mRNA abundance was lower at 30 days (Fig 2A). In the mucosa, DGAT1, FABP1, FABP2, and FABP3 expressions were lower at 90 days in Shaziling pigs (Fig 2B), while DGAT2 was higher at 30 days (Fig 2B). Summary, lipid metabolism and absorption related genes were differentiated between Shaziling and Yorkshire pigs, which might be by explained by the microbial and genetic difference.
Together, Shaziling pigs showed a marked difference in lipid metabolism compared with the Yorkshire pigs, the mechanisms might be associated with the genetic and environmental factors, especially for gut microbiota.
Bacterial development in the ileal cavity
To understand the relationship between gut microbes and lipid metabolism, we firstly aimed to compare bacterial alterations at different ages between Shaziling and Yorkshire pigs. The results showed that the alpha diversity (observed_species, shannon, chao1, ACE, and PD_whole_tree) of Shaziling pig was significantly higher at day 90 and 150 compared with the lean subjects (Fig 3A). Next, we analyzed the bacterial changes at the phylum level and found that 14 out of 15 phyla were altered and exhibited a time-dependent pattern, including Firmicutes, Chlamydiae, Bacteroidota, Fusobacteriota, Actinobacteriota, Campilobacterota, Verrucomicrobiota, Cyanobacteria, unidentiffied_Bacteria, Desulfbacterota, Choroflexi, Spirochaetota, Acidobacteriota, and Planctomycetes (Fig 3B), and 17 out of 20 species were identified to be differentiated between two datasets, such as Lactobacillus_amylovorus, Chlamydia_suis, Escherichia_coli, Turicibacter_sp_H121, Romboutsia_ilealis, Streptococcus_gallolyticus, Fusobacterium_mortiferum, Lactobacillus_delbrueckii, Limnobacter_thiooxidans, Campylobacter_jejuni, Brevundimonas_vesicularis, Trueperella_pyogenes, Acinetobacter_wuhouensis, Rothia_endophytica, Lactobacillus_teuteri, Prevotella_stercorea, and Alloprevotella_tannerae (supplementary fig 1A).
Commensal bacteria profiles between Shaziling and Yorkshire pigs
Previous study indicated that gut barrier function and host metabolism are mainly govern by mucosal commensal bacteria, which has not been well studied compared with the chymous and fecal microbiota Thus, we further explored the commensal bacteria in the mucosa between Shaziling and Yorkshire pigs. Similarly, the results showed that the α-diversity of Shaziling pig was significantly higher at 90 and 150 days (Fig 4A) and principal component was markedly differentiated between Shaziling and Yorkshire pigs (Fig 4A). Next, we analyzed the top 10 phyla, which were markedly altered, including Firmicutes, Proteobacteria, Chlamydiae, Fusobacteriota, Bacteroidota, Actinobacteriota, Campilobacterota, Verrucomicrobiota, Cyanobacteria, and unidentified_Bacteria (Fig 4B). At the species level, we found that 13 out of 20 species were markedly changed at entire stage, including Lactobacillus_johnosonii, Lactobacillus_amylovorus, Chlamydia_suis, Escherichia_coli, Romboutsia_ilealis, Turicibacter_sp_H121, Fusobacterium_mortiferum, Lactobacillus_delbrueckii, Actinobacillus_porcitonsillarum, Limnobacter_thiooxidans, Clostridium_butyricum, Campylobacter_jejuni, and Acinetobacter_wuhouensis (supplementary fig 1B). At 300 days, 7 species out of 15 species were markedly altered, including Lactobacillus_johnosonii, Lactobacillus_amylovorus, Chlamydia_suis, Turicibacter_sp_H121, Fusobacterium_mortiferum, Clostridium_butyricum and Campylobacter_jejuni (Fig 4C). Together, there was a marked difference in gut microbiota between Shaziling and Yorkshire pigs, which might contribute to the different metabolic phenotypes.
Ileal metabolic profiles between Shaziling and Yorkshire pigs
Microbial metabolites are one of the important factors affecting host lipid metabolism . Thus, we further analyzed the metabolic profiles of the mucosa at 300 days of age between Shaziling and Yorkshire pigs (Fig 5). First, we screened 86 different metabolites using VIP>1, P<0.05 as the standard (supplementary table 1), and then we further identified 35 metabolites using VIP>2, P<0.05, including naringenin, levan, vaccenic acid, 4-Hydroxytamoxifen, ricinoleic acid, deoxyguanosine LysoPA(16:0/0:0), 13S-hydroxyoctadecadienoic acid, 11Z-eicosenoic acid, deoxyinosine, glucosamine, sphingosine, propionic acid, pseudouridine, allopurinol riboside, N-acetylmannosamine, pectic acid, D-glucose, D-galactose, ferulic acid, 4-sulfate, L-norleucine, L-proline, 4-hydroxybenzaldehyde, m-coumaric acid, 2-phenylacetamide, phenylacetic acid, trans-cinnamic acid, L-histidine, indoleacrylic acid, asymmetric dimethylarginine, 4-hydroxycinnamic acid, sulfolithocholic acid, 3beta,7alpha-dihydroxy-5-cholestenoate, I-urobilin, 24-hydroxycholesterol (Fig 5). KEGG metabolic pathway enrichment showed that these differentiated metabolites were mainly related to carbohydrates, protein digestion and absorption, glucose and amino acid metabolism, and bile acid biosynthesis (supplementary table 2).
Pearson correlation analysis showed that the significant positive correlations were inentified between Lactobacillus_johnsonii and LsyoPA(16:0/0:0), Lactobacillus_amylovorus and LsyoPA(16:0/0:0), Chlamydia_suis and levan, deoxyinosine, Turicibacter_oxi_H121 and levan, 4-hydroxytam deoxyguanosine, deoxyinosine, allopurinol riboside, Fusobacterium_mortiferum and L-norleucine, trans-cinnamic acid, indoleacrylic acid, asymmetric dimethylarginine, 3beta,7alpha-dihydroxy-5-cholestenoate, I-urobilin, 24-hydroxydium_sool, Clostridium_butyricum and LsyoPA(16:0/0:0), Campylobacter_jejuni and L-proline. The negative correlations were noticed between Turicibacter_sp_H121 and 4-hydroxybenzaldehyde, m-coumaric acid, 2-phenylacetamide, phenylacetic acid, trans-cinnamic acid, asymmetric dimethylarginine, Fusobacterium_mortiferum and propionic acid and D-galactose (Fig 5). Summary, the current data indicated that gut microbiota were highly associated with metabolic profiles, which further targeted the different metabolic phenotypes.