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"Infeksi tuberkulosis (TB) masih menjadi masalah kesehatan global, termasuk di Indonesia. Pada pasien TB infeksi jamur paru sering terlewat karena kurangnya manifestasi klinis yang spesifik. Terapi obat anti-TB (OAT) dapat mengakibatkan perubahan profil mikrobiota jamur maupun bakteri di dalam tubuh pasien. Identifikasi mikrobiota jamur dan bakteri dengan metode mikroskopik dan kultur kurang sensitif, memerlukan waktu lama, dan kurang spesifik sehingga berpotensi menyebabkan diagnosis yang kurang optimal. Pemeriksaan berbasis molekular, termasuk metode sekuensing nanopore, memberikan hasil lebih sensitif, cepat dan akurat. Penelitian ini adalah bagian dari penelitian sebelumnya dan bertujuan untuk mengetahui komposisi mikrobiom bakteri dan jamur pada pasien terkait TB paru menggunakan sekuensing nanopore. Pemilihan pasien dilakukan secara consecutive sampling pada kasus TB paru dan bekas TB sesuai kriteria inklusi. Ekstraksi DNA sputum pasien dilakukan di laboratorium Parasitologi FKUI, dilanjutkan dengan pemeriksaan sekuensing menggunakan nanopore. Analisis bioinformatika menggunakan pipeline Kraken 2 dan Minimap 2 dilakukan pada 22 sampel sputum yang diteliti. Komposisi mikrobiom bakteri terdapat 3 spesies dominan, yaitu Haemophilus parainfluenzae, Neisseria perflava dan Streptococcus toyakuensis. Analisis sekuensing jamur belum dapat menentukan identifikasinya karena keterbatasan teknis penelitian, belum ada metode standar yang baku, serta kemungkinan kompetisi alamiah bakteri yang lebih mendominasi. Hasil identifikasi jamur berdasarkan pemeriksaan mikologi klasik menunjukkan Candida albicans, Candida glabrata, dan Aspergillus fumigatus sebagai spesies jamur terbanyak, diikuti Aspergillus niger, Talaromyces sp., Candida parapsilosis, Candida krusei, dan Candida tropicalis. Hubungan antara komposisi mikrobiom jamur dengan hasil pemeriksaan mikologi klasik pada penelitian ini belum dapat diketahui sehingga diperlukan penelitian lebih lanjut.

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Tuberculosis (TB) infection is still a global health problem, including in Indonesia. In TB patients, pulmonary fungal infections are often missed because of the lack of specific clinical manifestations. Anti-TB drug therapy can cause changes in the fungal and bacterial microbiome profile in the patient's body. Identifying fungal and bacterial microbiomes using microscopic and culture methods is less sensitive, time-consuming, and less specific, potentially leading to an inadequate diagnosis. Molecular-based examinations, including the nanopore sequencing method, provide more sensitive, fast and accurate results. This study is part of previous study that aims to determine the composition of fungal and bacterial microbiome in related-pulmonary TB patients using nanopore sequencing. The patients recruitment was conducted by consecutive sampling on pulmonary TB and previous TB cases according to the inclusion criteria. Sputum DNA extraction was carried out in the Parasitology Laboratory FMUI, followed by nanopore sequencing assay. Bioinformatics analysis using the Kraken 2 and Minimap 2 pipeline was carried out on the 22 sputum samples studied. The bacterial microbiome composition showed three dominant species: Haemophilus parainfluenzae, Neisseria perflava dan Streptococcus toyakuensis. The sequencing analysis has not been able to determine fungal identification due to technical limitations, the absence of an agreed standard method, and the possibility of bacterial dominance. The classical mycological assay revealed Candida albicans, Candida glabrata, and Aspergillus fumigatus as the most common fungal species identified, followed by Aspergillus niger, Talaromyces, Candida parapsilosis, Candida krusei, and Candida tropicalis. The correlation of fungal microbiome composition and classical mycological results cannot yet be determined, so further study is mandatory."

"Keseimbangan berbagai jenis bakteri pada kulit sangat penting dalam menjaga kesehatan kulit. Permasalahan pada kulit wajah yang muncul salah satunya disebabkan oleh disbiosis mikroba. Penelitian dilakukan untuk menganalisis keberagaman mikrobiom bakteri yang terdapat pada kulit wajah dengan kondisi pH dan kelembaban beragam. Metode analisis diversitas dengan Next Generation Sequencing 16s rRNA. Jumlah responden yang digunakan pada penelitian ini sebanyak 144 sampel. Hasil analisis pada penelitian ini ditemukan bahwa kelas filum bakteri tertinggi Actinobacterium (49,72%), Proteobacterium (29,86%) dan Firmicutes (18,64%). Pada genus Cutibacterium (41,48%), Neisseriaceae (20,29), Staphylococcus (10,16%) ditemukan terbanyak pada kulit wajah dengan nilai kondisi pH dan kelembaban berbeda. Analisis diversitas alfa dengan indeks Chao1 (p=0,05) dan Faith PD(p=0.004) menunjukan kelimpahan mikrobiom signifikan lebih tinggi ditemukan pada pH tinggi dibandingkan pH normal. Analisis diversitas Alfa pada kelembaban tidak ditemukan signifikan terhadap kelimpahan bakteri mikrobiom wajah. Hasil diversitas beta ditemukan perbedaan kelimpahan mikrobiom bakteri pada sepuluh genus tertinggi yang ditemukan pada pH normal dan pH tinggi serta kelompok kelembaban dengan sangat lembab, lembab dan kering. Kesimpulan penelitian profil genus Cutibacterium, Neisseriaceae, Staphylococcus bakteri paling banyak ditemukan pada pH tinggi dan pH normal seta kelembaban sangat lembab, lembab dan kering. Cutibacterium, Neisseriaceae dan Staphylococcus menunjukan adanya peningkatan pH kulit maka kelimpahan bakteri tersebut semakin meningkat. Pada kelembaban kulit, kelimpahan Cutibacterium dan Staphylococcus menurun seiring penurunan nilai kelembaban kulit.

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Balancing various types of bacteria on the skin is crucial for maintaining skin health. One of the issues that arise with facial skin is caused by microbial dysbiosis. Research was conducted to analyze the diversity of bacterial microbiomes on the facial skin with varying pH and moisture conditions. The diversity analysis method used Next Generation Sequencing 16s rRNA, and the study included 144 samples. The results of this research revealed that the highest bacterial phylum classes were Actinobacterium (49.72%), Proteobacterium (29.86%), and Firmicutes (18.64%). The genera Cutibacterium (41.48%), Neisseriaceae (20.29%), and Staphylococcus (10.16%) were the most abundant on the facial skin with different pH and moisture conditions. Alpha diversity analysis using Chao1 index (p=0.05) and Faith PD (p=0.004) indicated significantly higher microbial abundance found in high pH compared to normal pH. However, there was no significant difference in alpha diversity concerning the moisture level and facial bacterial microbiome abundance. Beta diversity analysis showed differences in bacterial microbiome abundance in the top ten genera found between normal pH and high pH, as well as between moisture groups categorized as very moist, moist, and dry. In conclusion, the research profiled the genera Cutibacterium, Neisseriaceae, and Staphylococcus as the most found bacteria in high pH and normal pH conditions, as well as very moist, moist, and dry moisture levels. Cutibacterium, Neisseriaceae, and Staphylococcus showed an increase in skin pH resulting in an increase in the abundance of these bacteria. On the other hand, the abundance of Cutibacterium and Staphylococcus decreased with decreasing skin moisture levels."