Metataxonomic analysis demonstrates a shift in duodenal microbiota in South African patients with obstructive jaundice: A pilot study
Hart, B.; Patel, J.; DeMaayer, P.; Nweke, E. E.; Bizos, D.
Show abstract
The human gastrointestinal tract (GIT) is home to an abundance of diverse microorganisms, and the balance of this microbiome plays a vital role in maintaining a healthy GIT. The obstruction of the flow of bile into the duodenum, resulting in obstructive jaundice (OJ), has a major impact on the health of the affected individual. This study sought to identify changes in the duodenal microbiota in South African patients with OJ compared to those without this disorder. Mucosal biopsies were taken from the duodenum of nineteen jaundiced patients undergoing endoscopic retrograde cholangiopancreatography (ERCP) and nineteen control participants (non-jaundiced patients) undergoing gastroscopy. DNA extracted from the samples was subjected to 16S rRNA amplicon sequencing using the Ion S5 TM sequencing platform. Diversity metrics and statistical correlation analyses with the clinical data were performed to compare duodenal microbial communities in both groups. Differences in the mean distribution of the microbial communities in the jaundiced and non-jaundiced samples were observed; however, this difference did not reach statistical significance. Of note, there was a statistically significant difference between the mean distributions of bacteria comparing jaundiced patients with cholangitis to those without. On further subset analysis, a significant difference was observed between patients with benign (Cholelithiasis) and malignant disease, namely head of pancreas (HOP) mass (p-values of 0.01). Beta diversity analyses further revealed a significant difference between patients with stone and non-stone related disease when factoring in the Campylobacter-Like Organisms (CLO) test status (p=0.048). This study demonstrated a shift in the microbiota in jaundiced patients, especially considering some underlying conditions of the upper GI tract. Future studies should aim to verify these findings in a larger cohort.
Matching journals
The top 6 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Molecular Characterization of Vaginal Microbiota Using a New 22-Species qRT-PCR Test to Achieve a Relative-abundance and Species-based Diagnosis of Bacterial Vaginosis 93%
- Comparative metagenome-assembled genome analysis of Lachnovaginosum genomospecies, formerly known as BVAB1 93%
- Enteropathogenic Escherichia coli (EPEC) Infection Induces Diarrhea, Intestinal Damage, Metabolic Alterations and Increased Intestinal Permeability in a Murine Model 93%
Similar papers in this journal
Similar papers in this journal
- Manually weighted taxonomy classifiers improve species-specific rumen microbiome analysis compared to unweighted or average weighted taxonomy classifiers 93%
- Using fecal immunochemical tubes for the analysis of gut microbiome has potential to improve colorectal cancer screening 93%
- Impact of HIV infection and integrase strand transfer inhibitors-based treatment on gut virome 93%
Similar papers in this journal
- Distinct patterns of microbiota and its function in end-stage liver cirrhosis correlate with antibiotic treatment, intestinal barrier impairment and systemic inflammation 94%
- Acute appendicitis manifests as two microbiome state types with oral pathogens influencing severity 94%
- Species- and strain-level assessment using rrn long-amplicons suggests donor's influence on gut microbial transference via fecal transplants in metabolic syndrome subjects 94%
Similar papers in this journal
- Restriction of the growth and biofilm formation of ESKAPE pathogens by caprine gut-derived probiotic bacteria 94%
- Nasopharyngeal microbial communities of patients infected with SARS-COV-2 that developed COVID-19. 94%
- Gut MicrobiotAware: how much do we know about gut microbiota? An international questionnaire. 93%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.