Helicobacter pylori (H. pylori) infection has been considered as the main causal factor in gastric carcinogenesis, but other bacterial species may also play an important role in pathophysiology of gastric cancer. The aim of the study was to explore the link between gastric cancer prognosis and the mucosal microbial community in tumorous and adjacent gastric tissue. The bacterial profile was analysed using 16S sequencing (V1–V2 region). Microbial differences were mostly characterized by lower relative abundances of H. pylori in tumorous gastric tissues. Bacterial community and outcome data analysis revealed the genus Fusobacterium and Prevotella significantly associated with worse overall survival in gastric cancer patients. In particular, Fusobacterium was associated with significant increase in hazard ratio in both univariable and multivariable analysis and independently validated using TCMA data. Phylogenetic biodiversity of Fusobacterium species in the stomach revealed F. periodonticum as the most prevalent in healthy subjects, while F. nucleatum was most abundant in patients with gastric cancer. Bacterial community network analysis in gastric cancer suggests substantial complexity and a strong interplay between F. nucleatum and Prevotella. In summary, mucosal microbial community in the stomach was associated with worse overall survival in gastric cancer patients. Strongest negative impact on prognosis was linked to the abundance of F. nucleatum in tumorous specimens, suggesting its translational relevance in management of gastric cancer patients.

Microbiome analysis has become a crucial tool for basic and translational research due to its potential for translation into clinical practice. However, there is ongoing controversy regarding the comparability of different bioinformatic analysis platforms and a lack of recognized standards, which might have an impact on the translational potential of results. This study investigates how the performance of different microbiome analysis platforms impacts the final results of mucosal microbiome signatures. Across five independent research groups, we compared three distinct and frequently used microbiome analysis bioinformatic packages (DADA2, MOTHUR, and QIIME2) on the same subset of fastQ files. The source data set encompassed 16S rRNA gene raw sequencing data (V1–V2) from gastric biopsy samples of clinically well-defined gastric cancer (GC) patients ( n = 40; with and without Helicobacter pylori [ H. pylori ] infection) and controls ( n = 39, with and without H. pylori infection). Independent of the applied protocol, H. pylori status, microbial diversity and relative bacterial abundance were reproducible across all platforms, although differences in performance were detected. Furthermore, alignment of the filtered sequences to the old and new taxonomic databases (i.e., Ribosomal Database Project, Greengenes, and SILVA) had only a limited impact on the taxonomic assignment and thus on global analytical outcomes. Taken together, our results clearly demonstrate that different microbiome analysis approaches from independent expert groups generate comparable results when applied to the same data set. This is crucial for interpreting respective studies and underscores the broader applicability of microbiome analysis in clinical research, provided that robust pipelines are utilized and thoroughly documented to ensure reproducibility. IMPORTANCE: Microbiome analysis is one of the most important tools for basic and translational research due to its potential for translation into clinical practice. However, there is an ongoing controversy about the comparability of different bioinformatic analysis platforms and a lack of recognized standards. In this study, we investigate how the performance of different microbiome analysis platforms affects the final results of mucosal microbiome signatures. Five independent research groups used three different and commonly used bioinformatics packages for microbiome analysis on the same data set and compared the results. This data set included microbiome sequencing data from gastric biopsy samples of GC patients. Regardless of the protocol used, Helicobacter pylori status, microbial diversity, and relative bacterial abundance were reproducible across all platforms. The results show that different microbiome analysis approaches provide comparable results. This is crucial for the interpretation of corresponding studies and underlines the broader applicability of microbiome analysis.

Anastomotic leakage (AL) is a potentially life-threatening complication following colorectal cancer (CRC) resection. In this study, we aimed to unravel longitudinal changes in microbial structure before, during, and after surgery and to determine if microbial alterations may be predictive for risk assessment between sufficient anastomotic healing (AS) and AL prior surgery. We analysed the microbiota of 134 colon mucosal biopsies with 16S rRNA V1-V2 gene sequencing. Samples were collected from three location sites before, during, and after surgery, and patients received antibiotics after the initial collection and during surgery. The microbial structure showed dynamic surgery-related changes at different time points. Overall bacterial diversity and the abundance of some genera such as Faecalibacterium or Alistipes decreased over time, while the genera Enterococcus and Escherichia_Shigella increased. The distribution of taxa between AS and AL revealed significant differences in the abundance of genera such as Prevotella, Faecalibacterium and Phocaeicola. In addition to Phocaeicola, Ruminococcus2 and Blautia showed significant differences in abundance between preoperative sample types. ROC analysis of the predictive value of these genera for AL revealed an AUC of 0.802 (p = 0.0013). In summary, microbial composition was associated with postoperative outcomes, and the abundance of certain genera may be predictive of postoperative complications.

Inflammatory bowel disease (IBD) is a chronic recurrent inflammatory disease with unknown etiology. Dextran sulfate sodium (DSS) induced colitis is a widely used mouse model in IBD research. DSS colitis involves activation of the submucosal immune system and can be used to study IBD-like disease characteristics in acute, chronic, remission and transition phases. Insight into colon inflammatory parameters is needed to understand potentially irreversible adaptations to the chronification of colitis, determining the baseline and impact of further inflammatory episodes. We performed analyses of non-invasive and invasive colitis parameters in acute, chronic and remission phases of the DSS colitis in C57BL/6 mice. Non-invasive colitis parameters poorly reflected inflammatory aspects of colitis in chronic remission phase. We found invasive inflammatory parameters, positively linked to repeated DSS-episodes, such as specific colon weight, inflamed colon area, spleen weight, absolute cell numbers of CD4+ and CD8+ T cells as well as B cells, blood IFN-γ level, colonic chemokines BLC and MDC as well as the prevalence of Turicibacter species in feces. Moreover, microbial Lactobacillus species decreased with chronification of disease. Our data point out indicative parameters of recurrent gut inflammation in context of DSS colitis.

Background/Objectives: Postoperative pneumonia and other infectious complications after robotic-assisted minimally invasive esophagectomy still contribute to morbidity and mortality. Selective oral decontamination of the esophagus prior to surgery might reduce the rate of infectious complications. However, its impact on the esophageal microbiota is unknown. Therefore, this study aimed to analyze whether selective oral decontamination of the esophagus prior to surgery reduces postoperative pneumonia rates and alters the esophageal microbiome. Methods: We conducted a proof-of-principle study including 22 patients who underwent robotic-assisted minimally invasive esophagectomy. Thirteen patients were treated with 50 mg amphotericin B, 8 mg tobramycin, and 10 mg colistin orally 7 days prior to surgery, intraoperatively, and 5 days postoperatively. The remaining nine patients received standard-of-care treatment (no oral decontamination). The esophageal microbiome was assessed using 16S rRNA gene amplicon libraries which were annotated using the Ribosomal Data Project. The incidence of postoperative (at discharge from hospital or 30 days, whichever was later) infectious complications was assessed. Results: Selective oral decontamination was associated with reduced overall rates of infectious complications (7.7% vs. 55.5%, p = 0.008) and postoperative pneumonia (0% vs. 33.3%, p = 0.007). Alterations in the esophageal microbiome depending on selective oral decontamination were detectable. The microbiomes of patients with infectious complications showed higher abundances of Neisseria and lower abundances of Streptococcus than samples without infectious complications. Conclusions: Selective oral decontamination reduced the rate of postoperative complications, postoperative pneumonia in particular, after robot-assisted esophagectomy. Alterations in the microbiome were also evident following decontamination. Further studies with larger sample sizes are necessary to confirm these data.

Background/Objectives: Obstruction of the biliary duct may be caused by various conditions ranging from chronic inflammation to neoplasia, including cholangiocarcinoma (CCA). While the definite histological diagnosis of intrahepatic lesions is relatively straightforward, the diagnostic workup of biliary duct stenosis can be challenging, despite the availability of novel tools for intraductal diagnosis. This proof-of-principle study aimed to investigate whether microRNAs (miRNAs) from bile duct stents may be used as biomarkers to differentiate between various bile duct diseases. Methods: For this purpose, we included 100 patients with one or more bile duct stents for various reasons, including malignant disease (n = 40), stenosis due to liver transplantation or surgery (n = 60), and cholangitis (n = 42). During endoscopic retrograde cholangiography, the stents were collected, and miRNA analyses were performed to evaluate miR-16, miR-21, and miR-223. Results: All studied miRNAs were successfully detected from the specimens obtained from the bile duct stents and were comparable in different stents from the same subjects. Following normalization, significant increases in miR-16, -21, and -223 levels were identified in patients with cholangitis compared to specimens from a non-inflammatory cohort. However, when comparing the data from patients in the malignant and non-malignant cohorts, the individual levels of miR-16, miR-21, and miR-223 showed high variation, without reaching a statistically significant difference. Conclusions: In summary, bile duct stents can be considered as potential sources of intraductal biomarkers, specifically miRNAs. Further profiling and validation analyses are necessary to identify the most appropriate miRNA targets for differentiating bile duct diseases.