Intraspecific difference of Latilactobacillus sakei in inflammatory bowel diseases: Insights into potential mechanisms through comparative genomics and metabolomics analyses

Abstract

Inflammatory bowel diseases (IBDs) are chronic inflammatory diseases of the gastrointestinal tract that have become a global health burden. Studies have revealed that Latilactobacillus sakei can effectively alleviate various immune diseases, including colitis, rheumatoid arthritis, and metabolic disorders. Here, we obtained 72 strains of L. sakei from 120 fermentation and fecal samples across China. In total, 16 strains from different sources were initially screened in an in vitro Caco-2 model induced by dextran sulfate sodium. Subsequently, six strains (four exhibiting effectiveness and two exhibiting ineffectiveness) were selected for further validation in an in vivo colitis mouse model. The results demonstrated that L. sakei strains exhibited varying degrees of amelioration of the colitis disease process. Notably, L. sakei CCFM1267, the most effective strain, significantly restored colon length and tight-junction protein expression, and reduced the levels of cytokines and associated inflammatory enzymes. Moreover, L. sakei CCFM1267 upregulated the abundance of Enterorhabdus, Alloprevotella, and Roseburia, leading to increased levels of acetic acid and propionic acid. Conversely, the other four strains (L. sakei QJSSZ1L4, QJSSZ4L10, QGZZYRHMT1L6, and QGZZYRHMT2L6) only exhibited a partial remission effect, while L. sakei QJSNT1L10 displayed minimal impact. Therefore, L. sakei CCFM1267 and QJSNT1L10 were selected for further exploration of the mechanisms underlying their differential mitigating effects. Comparative genomics analysis revealed significant variations between the two strains, particularly in genes associated with carbohydrate-active enzymes, such as the glycoside hydrolase family, which potentially contribute to the diverse profiles of short-chain fatty acids in vivo. Additionally, metabolome analysis demonstrated that acetylcholine and indole-3-acetic acid were the main differentiating metabolites of the two strains. Therefore, the strains of L. sakei exhibited varying degrees of effectiveness in alleviating IBD-related symptoms, and the possible reasons for these variations were attributed to discrepancies in the carbohydrate-active enzymes and metabolites among the strains.

Keywords: Latilactobacillus sakei; comparative genomics; gut microbiota; inflammatory bowel disease; metabolomics; probiotic.

Figure 1

Screening of Latilactobacillus sakei in vitro. (A) Flowchart of screening of L. sakei in vitro. (B) Impact of L. sakei on Caco‐2 cell viability after dextran sulfate sodium (DSS) stimulation. (C) Effects of L. sakei on TJ protein in Caco‐2 cells after DSS stimulation. (D) Influence of L. sakei on the expression of Caco‐2 cell‐related immune pathway after DSS stimulation. Different lowercase letters as superscripts (a–c) in the graph signify significant differences between groups (p < 0.05), determined by Tukey's multiple comparisons test (n = 6). JNK, c‐Jun N‐terminal kinase; NF‐κB, nuclear factor kappa B; TAK1, transforming growth factor beta‐activated kinase 1; TJ, tight junction; TRAF6, tumor necrosis factor receptor‐associated factor 6.

Figure 2

Latilactobacillus sakei ameliorates DSS‐induced murine colitis. (A) Flowchart of animal experiment. (B, C) Effects of L. sakei on physiological indexes of mice with colitis. (D) Effects of L. sakei on the histological morphology of colonics in mice with colitis. (E) Effects of L. sakei on colon TJ protein content in colitis mice. (F–H) Effects of L. sakei on inflammatory enzyme content in colitis mice. (I–M) Effects of L. sakei on cytokine content in colitis mice. Different lowercase letters as superscripts (a–c) in the graph signify significant differences between groups (p < 0.05), determined by Tukey's multiple comparisons test (n = 8). CFU, colony‐forming units; DSS, dextran sulfate sodium; SCFA, short‐chain fatty acid; TJ, tight junction.

Figure 3

Influence of Latilactobacillus sakei on gut microbiota in colitis mice. (A) α‐Diversity of gut microbiota in colitis mice. (B) β‐Diversity of the gut microbiota in colitis mice. (C) Effects of L. sakei on SCFAs content in colitis mice. (D, F) Effects of L. sakei on the phylum level of the gut microbiota in colitis mice. (E) LEfSe difference of gut microbiota in colitis mice after intervention by L. sakei. (G) The relative abundance of different bacterial species after L. sakei intervention. Different superscript lowercase letters (a–c) in the graph indicate significant differences between groups (p < 0.05) within the row by the Kruskal–Wallis test (Control, n = 7; DSS, n = 5; CCFM1267, n = 6; QJSNT1L10, n = 7). DSS, dextran sulfate sodium; LDA, linear discriminant analysis; PC, principal component; PCA, principal component analysis; SCFA, short‐chain fatty acid.

Figure 4

Comparative genomic analysis and metabolome analysis of differential genera. (A) Flowchart of comparative genomic analysis and metabolome analysis of different genera. (B) Analysis of homologous genes of Latilactobacillus sakei. (C) Heat map of average nucleotide consistency analysis of L. sakei. (D) Phylogenetic analysis of L. sakei. (E, F) Carbohydrate‐active enzyme analysis of L. sakei from different sources. (G) OPLS‐DA score plot of all metabolites in L. sakei. (H) Volcanic map of differential metabolites. AAs, auxiliary activities; CEs, carbohydrate esterases; GHs, glycoside hydrolases; GTs, glycosyl transferases; LC‐MS, liquid chromatography–mass spectrometry; OPLS‐DA, orthogonal partial least squares‐discriminant analysis.