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All Journal Jurnal Ilmiah Kedokteran Wijaya Kusuma JSMARTech : Journal of Smart Bioprospecting and Technology
Sembiring, Christine
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Biochemistry, Genetics & Molecular Biology Chemistry Materials Science & Nanotechnology Medicine & Pharmacology Neuroscience Public Health

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Metagenomic Analysis of Intestinal Microbiota Derived from Stool Samples of Third-Trimester Pregnant Women Kamaruddin, Mudyawati; Zamzam, Miftahul Khairiyah; Pratama, Rahadian; Nur, AbdurRahman Shakhr; Muthiadin, Cut; Sembiring, Christine; Triananinsi, Nurhidayat; Nurisyah, Nurisyah; Dewi, Ratnasari; Fatmawati, Fatmawati; Erniawati, Erniawati; Jusni, Jusni; Basmiati, Basmiati
Jurnal Ilmiah Kedokteran Wijaya Kusuma Vol. 14 No. 1 (2025): MARET 2025
Publisher : Universitas Wijaya Kusuma Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30742/jikw.v14i1.4173

Abstract

Background: The human gut microbiota plays a unique role in metabolism, immunity, and nutrient absorption.  Various studies on the gut microbiota have identified a link between changes in bacterial abundance in the gut known as dysbiosis (imbalance) and the pathogenesis of certain disorders. It is known that an imbalance in the ratio of the phyla Firmicutes and Bacteroidetes has been associated with various chronic diseases, including inflammatory bowel disease and metabolic disorders. The Firmicutes/Bacteroidetes (F/B) ratio is a measure used to assess gut microbiota composition, which is believed to play a significant role in intestinal health and metabolism. Studies suggest that a higher F/B ratio is often associated with obesity and other metabolic conditions. Objective: This study aims to carry out metagenomic analysis of third-trimester pregnant women's faecal samples to predict degenerative diseases using third-generation whole genome sequencing, namely PromethION nanopore technology.  Method: Nanopore Technology: DNA sequencing of faecal samples from pregnant women in the third trimester was performed using the Oxford Nanopore Technology (ONT) device based on the Ligation Sequencing gDNA - Native Barcoding Kit 24 V14 and following its guidelines. Result: Based on the quality and quantity of total DNA reads from 20 stool samples from pregnant women, only 4 samples were continued for analysis (1A, 2A, 3A and 4A). The results of the abundance of intestinal microbiota based on the most abundant phylum are Proteobacteria, Bacteriodetes, and Firmicutes. Conclusion: Meanwhile, based on species abundance, it shows that Prevotella copri (phylum Bacteriodetes) is abundant in samples 2A, 3A and 4A, while in sample 1A the most abundant species is Succinivirio dextrinosolvens (phylum Proteobacteria). Bacteroidetes are a group of Gram-negative bacteria that are often found to increase in individuals with type 2 diabetes and obesity
Soil Microbiome Dataset from Rawa Aopa Watumohai National Park in the Agroforestry Region of Southeast Sulawesi Reski, Alpi Meitia; Andrianto, Dimas; Pratama, Rahadian; Verrone, Valeria; Edy, Nur; Agusti, Randi; Hafazallah, Khalid; Ahmad, Roland Putra Pribadi; Dea, Andi Amriyana; Sembiring, Christine
JSMARTech: Journal of Smart Bioprospecting and Technology Vol. 7 No. 1 (2026): JSMARTech Volume 7, No 1, 2026
Publisher : JSMARTech

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jsmartech.2026.007.01.35_2

Abstract

The soil microbiome dataset is a vital dataset to support restoration and sustainable land management. Rawa Aopa Watumohai National Park (TNRAW) is a national park located in Southeast Sulawesi Province Indonesia, which has not been analyzed for its microbiome. This research aims to characterize the diversity of soil fungal and eukaryotic communities using a dual-marker metabarcoding approach and to generate baseline data to support future biodiversity monitoring, ecosystem restoration, and sustainable agroforestry management in TNRAW. Soil samples were collected from five agroforestry plots and analyzed using a dual-marker metabarcoding approach targeting the ITS2 region for fungi and the SSU rRNA region for broader eukaryotes. DNA was extracted and checked for purity using Nanodrop and Quantus. PCR amplification was confirmed via agarose gel electrophoresis, and sequencing was conducted with Oxford Nanopore Technologies. Bioinformatics processing included basecalling, quality filtering, taxonomic classification using Kraken2, and Visualization with Krona and ampvis2. The ITS2 dataset results revealed dominant fungal taxa such as Fusarium falciforme, Talaromyces marneffei, and Aspergillus, with high read counts. In contrast, the SSU dataset complemented this by detecting non-fungal eukaryotes like Cryptophyceae, Vibrio anguillarum, and Theileria equi and filtering retained 2–16% high-quality reads per sample, sufficient for downstream ecological interpretation. The resulting dataset can serve as a starting point for future research on tropical soil biodiversity and as a local reference for conservation and agroforestry management in TNRAW.
Co-Authors Agusti, Randi Ahmad, Roland Putra Pribadi Basmiati, Basmiati Cut Muthiadin Dea, Andi Amriyana Dewi Ratnasari DIMAS ANDRIANTO Erniawati, Erniawati Fatmawati, Fatmawati Hafazallah, Khalid Jusni, Jusni Mudyawati Kamaruddin Nur Edy Nur, AbdurRahman Shakhr Nurhidayat Triananinsi Nurisyah, Nurisyah Rahadian Pratama Reski, Alpi Meitia Verrone, Valeria Zamzam, Miftahul Khairiyah