RESUMO
BACKGROUND AND AIMS: The mineral compound Luvos Healing Earth (LHE) is a commercially available remedy empirically used for a variety of gastrointestinal disorders. The aim of this study was to investigate the possible effect of prolonged LHE therapy on gut microbiota in healthy individuals and in patients with diarrhea-predominant irritable bowel syndrome (IBS-D). METHODS: In this prospective exploratory study, a total of 20 participants, including 12 healthy controls and 8 patients with IBS-D, received treatment with LHE (Magenfein Granulat, 1 sachet bid) for 6 weeks. Fecal samples were collected for microbiota analysis in the morning fasting state at regular intervals at 6 different timepoints: 2 weeks before starting therapy (Screen), and every 2 weeks during LHE therapy (V0-V3). Additionally, a follow-up visit was scheduled 4 weeks after the end of treatment (V4). Microbiota analysis was performed using the GA-map® Dysbiosis Test Lx v2. Dysbiosis Index, bacterial diversity, as well as the balance or imbalance of functionally important bacteria were assessed. RESULTS: The microbiota analysis revealed an overlap in gut microbiota profiles between healthy controls and patients with IBS-D. Bacterial communities were consistently stable during the entire treatment period, and no significant variations in composition were observed 4 weeks after the end of the therapeutic intervention. There was a remarkable stability of microbiota profiles over time within each individual and a high inter-individual variation. The majority of fecal samples exhibited profiles, reflecting an eubiotic state, with no significant changes in dysbiosis index, functional bacteria profiles, or bacterial diversity. CONCLUSION: Our findings indicate intraindividual resilience of microbiota consortia during the entire study period. Prolonged intake of LHE does not cause significant alterations in fecal microbiota profiles in healthy controls and patients with IBS-D. Luvos Healing Earth does not affect the stability of gut microbial diversity and bacterial functions.
Assuntos
Microbioma Gastrointestinal , Síndrome do Intestino Irritável , Humanos , Síndrome do Intestino Irritável/diagnóstico , Síndrome do Intestino Irritável/complicações , Diarreia/diagnóstico , Diarreia/etiologia , Disbiose/complicações , Disbiose/microbiologia , Estudos Prospectivos , Fezes/microbiologia , BactériasRESUMO
BACKGROUND: Compared to their healthy counterparts, patients with type 2 diabetes (T2D) can exhibit an altered gut microbiota composition, correlated with detrimental outcomes, including reduced insulin sensitivity, dyslipidemia, and increased markers of inflammation. However, a typical T2D microbiota profile is not established. The aim of this pilot study was to explore the gut microbiota and bacteria associated with prediabetes (pre-T2D) patients, and treatment naïve T2D patients, compared to healthy subjects. METHODS: Fecal samples were collected from patients and healthy subjects (from Norway). The bacterial genomic DNA was extracted, and the microbiota analyzed utilizing the bacterial 16S rRNA gene. To secure a broad coverage of potential T2D associated bacteria, two technologies were used: The GA-map® 131-plex, utilizing 131 DNA probes complementary to pre-selected bacterial targets (covering the 16S regions V3-V9), and the LUMI-Seq™ platform, a full-length 16S sequencing technology (V1-V9). Variations in the gut microbiota between groups were explored using multivariate methods, differential bacterial abundance was estimated, and microbiota signatures discriminating the groups were assessed using classification models. RESULTS: In total, 24 pre-T2D patients, 18 T2D patients, and 52 healthy subjects were recruited. From the LUMI-Seq™ analysis, 10 and 9 bacterial taxa were differentially abundant between pre-T2D and healthy, and T2D and healthy, respectively. From the GA-map® 131-plex analysis, 10 bacterial markers were differentially abundant when comparing pre-T2D and healthy. Several of the bacteria were short-chain fatty acid (SCFA) producers or typical opportunistic bacteria. Bacteria with similar function or associated properties also contributed to the separation of pre-T2D and T2D from healthy as found by classification models. However, limited overlap was found for specific bacterial genera and species. CONCLUSIONS: This pilot study revealed that differences in the abundance of SCFA producing bacteria, and an increase in typical opportunistic bacteria, may contribute to the variations in the microbiota separating the pre-T2D and T2D patients from healthy subjects. However, further efforts in investigating the relationship between gut microbiota, diabetes, and associated factors such as BMI, are needed for developing specific diabetes microbiota signatures.
Assuntos
Diabetes Mellitus Tipo 2 , Microbioma Gastrointestinal , Estado Pré-Diabético , Humanos , Microbioma Gastrointestinal/genética , Projetos Piloto , RNA Ribossômico 16SRESUMO
Introduction: There are numerous confounding variables in the pre-analytical steps in the analysis of gut microbial composition that affect data consistency and reproducibility. This study compared two DNA extraction methods from the same faecal samples to analyse differences in microbial composition. Methods: DNA was extracted from 20 faecal samples using either (A) chemical/enzymatic heat lysis (lysis buffer, proteinase K, 95 °C + 70 °C) or (B) mechanical and chemical/enzymatic heat lysis (bead-beating, lysis buffer, proteinase K, 65 °C). Gut microbiota was mapped through the 16S rRNA gene (V3−V9) using a set of pre-selected DNA probes targeting >300 bacteria on different taxonomic levels. Apart from the pre-analytical DNA extraction technique, all other parameters including microbial analysis remained the same. Bacterial abundance and deviations in the microbiome were compared between the two methods. Results: Significant variation in bacterial abundance was seen between the different DNA extraction techniques, with a higher yield of species noted in the combined mechanical and heat lysis technique (B). The five predominant bacteria seen in both (A) and (B) were Bacteroidota spp. and Prevotella spp. (p = NS), followed by Bacillota (p = 0.005), Lachhnospiraceae (p = 0.0001), Veillonella spp. (p < 0.0001) and Clostridioides (p < 0.0001). Conclusion: As microbial testing becomes more easily and commercially accessible, a unified international consensus for optimal sampling and DNA isolation procedures must be implemented for robustness and reproducibility of the results.