Kefir peptides mitigate bleomycin-induced pulmonary fibrosis in mice through modulating oxidative stress, inflammation and gut microbiota.

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a progressive and life-threatening lung disease with high mortality rates. The limited availability of effective drugs for IPF treatment, coupled with concerns regarding adverse effects and restricted responsiveness, underscores the need for alternative approaches. Kefir peptides (KPs) have demonstrated antioxidative, anti-inflammatory, and antifibrotic properties, along with the capability to modulate gut microbiota. This study aims to investigate the impact of KPs on bleomycin-induced pulmonary fibrosis. METHODS: Mice were treated with KPs for four days, followed by intratracheal injection of bleomycin for 21 days. Comprehensive assessments included pulmonary functional tests, micro-computed tomography (µ-CT), in vivo image analysis using MMPsense750, evaluation of inflammation- and fibrosis-related gene expression in lung tissue, and histopathological examinations. Furthermore, a detailed investigation of the gut microbiota community was performed using full-length 16 S rRNA sequencing in control mice, bleomycin-induced fibrotic mice, and KPs-pretreated fibrotic mice. RESULTS: In KPs-pretreated bleomycin-induced lung fibrotic mice, notable outcomes included the absence of significant bodyweight loss, enhanced pulmonary functions, restored lung tissue architecture, and diminished thickening of inter-alveolar septa, as elucidated by morphological and histopathological analyses. Concurrently, a reduction in the expression levels of oxidative biomarkers, inflammatory factors, and fibrotic indicators was observed. Moreover, 16 S rRNA sequencing demonstrated that KPs pretreatment induced alterations in the relative abundances of gut microbiota, notably affecting Barnesiella_intestinihominis, Kineothrix_alysoides, and Clostridium_viride. CONCLUSIONS: Kefir peptides exerted preventive effects, protecting mice against bleomycin-induced lung oxidative stress, inflammation, and fibrosis. These effects are likely linked to modifications in the gut microbiota community. The findings highlight the therapeutic potential of KPs in mitigating pulmonary fibrosis and advocate for additional exploration in clinical settings.

Prebiotic potential of green banana flour: impact on gut microbiota modulation and microbial metabolic activity in a murine model.

Introduction: Green banana flour can be used as a prebiotic due to its ability to promote gut health and provide several health benefits. In this study, we investigated whether feeding mice green banana flour at different doses would alter intestinal microbiota composition. Methods: We fed C57BL/6N mice either a Low-dose (500 mg/kg/day) or High-dose (2000 mg/kg/day) of green banana flour daily for 3 weeks, and fecal samples were collected on days 0, 14, and 21 for microbiota analysis. Results: Our results showed that the composition of intestinal microbiota was significantly altered by day 21, regardless of the dose. Notably, the consumption of green banana flour increased the presence of beneficial bacteria, including Coriobacteriaceae_UCG-002, Turicibacter, Parasutterella, Gastranaerophilales_ge, and RF39_ge. These changes in the intestinal microorganisms were accompanied by increased biological processes such as amino acid biosynthesis and secondary metabolite biosynthesis. Conversely, the consumption of green banana flour resulted in a decrease in biological processes related to carbohydrate degradation, glycerol degradation, and similar functions. Discussion: These results emphasize the potential of green banana flour as a prebiotic that can benefit the gut microbiome.

Dietary Supplementation of Limosilactobacillus mucosae LM1 Enhances Immune Functions and Modulates Gut Microbiota Without Affecting the Growth Performance of Growing Pigs.

Limosilactobacillus mucosae LM1 (LM1) is previously isolated from the intestine of piglets, but its potential as a probiotic supplement has not yet been assessed in growing pigs. In this study, we analyzed the probiotic effect of LM1 on the growth performance, apparent total tract digestibility (ATTD) of nutrients, immune properties, intestinal morphology, and gut microbiota and their metabolites in growing pigs. The experiment included 145 Duroc × (Landrace × Yorkshire) pigs (average body weight: 21.21 ± 1.14 kg) distributed into five treatment groups. The pigs were fed either a control diet (CON), or the control diet supplemented with incremental doses of LM1, namely low-dose LM1 (LL, 8.3 × 108 CFU/kg), moderate-low dose LM1 (ML, 4.2 × 109 CFU/kg), moderate-high dose LM1 (MH, 8.3 × 109 CFU/kg), and high-dose LM1 (HH, 2.1 × 1010 CFU/kg) for 42 d. On d 42, 12 pigs from each of the CON and MH groups were slaughtered. The results indicated that the ATTD of nitrogen (N, P = 0.038) was improved with MH supplementation. In addition, increasing dose of LM1 improved the immune response in pigs by reducing serum pro-inflammatory cytokines (interleukin-1ß and tumor necrosis factor-alpha) and increasing anti-inflammatory cytokines (interleukin-10). Pigs fed with MH LM1 also had higher jejunal villus height and ileal villus height: crypt depth ratio, demonstrating improved intestinal morphology. Moreover, moderate-high LM1 supplementation enriched SCFA-producing taxa such as Lactobacillus, Holdemanella, Peptococcus, Bifidobacterium, Eubacterium_hallii_group, and Lachnospiraceae_AC2044_group, which correlated positively with increased fecal levels of butyrate and iso-valerate. These results strongly suggest the probiotic potential of LM1 on growing pigs. Overall, the current study provides insights on the use of L. mucosae LM1 as a novel livestock probiotic to improve pig gut health.

Typing of the Gut Microbiota Community in Japanese Subjects.

Gut microbiota are involved in both host health and disease and can be stratified based on bacteriological composition. However, gut microbiota clustering data are limited for Asians. In this study, fecal microbiota of 1803 Japanese subjects, including 283 healthy individuals, were analyzed by 16S rRNA sequencing and clustered using two models. The association of various diseases with each community type was also assessed. Five and fifteen communities were identified using partitioning around medoids (PAM) and the Dirichlet multinominal mixtures model, respectively. Bacteria exhibiting characteristically high abundance among the PAM-identified types were of the family Ruminococcaceae (Type A) and genera Bacteroides, Blautia, and Faecalibacterium (Type B); Bacteroides, Fusobacterium, and Proteus (Type C); and Bifidobacterium (Type D), and Prevotella (Type E). The most noteworthy community found in the Japanese subjects was the Bifidobacterium-rich community. The odds ratio based on type E, which had the largest population of healthy subjects, revealed that other types (especially types A, C, and D) were highly associated with various diseases, including inflammatory bowel disease, functional gastrointestinal disorder, and lifestyle-related diseases. Gut microbiota community typing reproducibly identified organisms that may represent enterotypes peculiar to Japanese individuals and that are partly different from those of indivuals from Western countries.

Metabolic Dependencies Underlie Interaction Patterns of Gut Microbiota During Enteropathogenesis.

In recent decades, increasing evidence has strongly suggested that gut microbiota play an important role in many intestinal diseases including inflammatory bowel disease (IBD) and colorectal cancer (CRC). The composition of gut microbiota is thought to be largely shaped by interspecies competition for available resources and also by cooperative interactions. However, to what extent the changes could be attributed to external factors such as diet of choice and internal factors including mutual relationships among gut microbiota, respectively, are yet to be elucidated. Due to the advances of high-throughput sequencing technologies, flood of (meta)-genome sequence information and high-throughput biological data are available for gut microbiota and their association with intestinal diseases, making it easier to gain understanding of microbial physiology at the systems level. In addition, the newly developed genome-scale metabolic models that cover significant proportion of known gut microbes enable researchers to analyze and simulate the system-level metabolic response in response to different stimuli in the gut, providing deeper biological insights. Using metabolic interaction network based on pair-wise metabolic dependencies, we found the same interaction pattern in two IBD datasets and one CRC datasets. We report here for the first time that the growth of significantly enriched bacteria in IBD and CRC patients could be boosted by other bacteria including other significantly increased ones. Conversely, the growth of probiotics could be strongly inhibited from other species, including other probiotics. Therefore, it is very important to take the mutual interaction of probiotics into consideration when developing probiotics or "microbial based therapies." Together, our metabolic interaction network analysis can predict majority of the changes in terms of the changed directions in the gut microbiota during enteropathogenesis. Our results thus revealed unappreciated interaction patterns between species could underlie alterations in gut microbiota during enteropathogenesis, and between probiotics and other microbes. Our methods provided a new framework for studying interactions in gut microbiome and their roles in health and disease.