MALDI-TOF MS Is an Effective Technique To Classify Specific Microbiota

Cholesterol Gallstones and Long-Term Use of Statins: Is Gut Microbiota Dysbiosis Bridging over Uncertainties?

A total of 300 research participants-200 consecutive patients diagnosed with dyslipidemia (100 statin (+), treated for at least five years, and 100 statin (-)) and 100 healthy controls-were included in this observational study. The aim of the study was to deliver insights into the relationship between the long-term use of statins for dyslipidemia and gallstone disease (GSD), as well as insights into the background particularities of the gut microbiota. All study participants underwent clinical examination, laboratory workups, stool microbiology/stool 16S r RNA, next-generation sequencing, and abdominal ultrasound/CT exams. Results: The research participants presented with similarities related to age, gender, and location. Patients displayed comparable heredity for GSs, metabolic issues, and related co-morbidities. Gut dysbiosis (DB) was present in 54% of the statin (-) patients vs. 35% of the statin (+) patients (p = 0.0070). GSs were present in 14% of patients in the statin (-) group vs. 5% of patients in the statin (+) group (p = 0.0304). Severe dysbiosis, with a significant reduction in biodiversity, an increase in LPS (+) bacteria, and a notable decrease in mucin-degrading bacteria, mucosa-protective bacteria, and butyrate-producing bacteria were observed in the statin (-) group. Strong positive correlations between GSD and diabetes/impaired glucose tolerance (r = 0.3368, p = 0.0006), obesity (r = 0.3923, p < 0.0001), nonalcoholic fatty liver disease (r = 0.3219, p = 0.0011), and DB (r = 0.7343, p < 0.0001), as well as significant negative correlations between GSD and alcohol use (r = -0.2305, p = 0.0211), were observed. The multiple regression equation demonstrated that only DB (95% CI: 0.3163 to 0.5670; p < 0.0001) and obesity (95% CI: 0.01431 to 0.2578; p = 0.0289) were independent risk factors predicting GSD in the group of patients treated with statins. Conclusion: The long-term use of statins in dyslipidemic patients was associated with a low risk of developing GSs. The gut microbiota associated with a long-term use of statins in dyslipidemic patients was characterized by a low risk of developing an imbalance of various functional bacteria and alterations in the metabolic microbiota. DB and obesity were found to be independent risk factors predicting GSD in statin (+) patients.

Genomic and Functional Evaluation of Two Lacticaseibacillus paracasei and Two Lactiplantibacillus plantarum Strains, Isolated from a Rearing Tank of Rotifers (Brachionus plicatilis), as Probiotics for Aquaculture

Aquaculture plays a crucial role in meeting the increasing global demand for food and protein sources. However, its expansion is followed by increasing challenges, such as infectious disease outbreaks and antibiotic misuse. The present study focuses on the genetic and functional analyses of two Lacticaseibacillus paracasei (BF3 and RT4) and two Lactiplantibacillus plantarum (BF12 and WT12) strains isolated from a rotifer cultivation tank used for turbot larviculture. Whole-genome sequencing (WGS) and bioinformatics analyses confirmed their probiotic potential, the absence of transferable antibiotic resistance genes, and the absence of virulence and pathogenicity factors. Bacteriocin mining identified a gene cluster encoding six plantaricins, suggesting their role in the antimicrobial activity exerted by these strains. In vitro cell-free protein synthesis (IV-CFPS) analyses was used to evaluate the expression of the plantaricin genes. The in vitro-synthesized class IIb (two-peptide bacteriocins) plantaricin E/F (PlnE/F) exerted antimicrobial activity against three indicator microorganisms, including the well-known ichthyopathogen Lactococcus garvieae. Furthermore, MALDI-TOF MS on colonies detected the presence of a major peptide that matches the dimeric form of plantaricins E (PlnE) and F (PlnF). This study emphasizes the importance of genome sequencing and bioinformatic analysis for evaluating aquaculture probiotic candidates. Moreover, it provides valuable insights into their genetic features and antimicrobial mechanisms, paving the way for their application as probiotics in larviculture, which is a major bottleneck in aquaculture.