Background: The 16S rRNA-targeted next-generation sequencing (NGS) has been widely used as the primary tool for microbiome analysis. However, whether the sequenced microbial diversity absolutely represents the original sample composition remains unclear. This study aimed to evaluate whether 16S rRNA gene-targeted NGS accurately captures bacterial community composition. Methods: Mock communities were constructed using equal amounts of DNA from 18 bacterial strains in three formats: genomic DNA, recombinant plasmids, and polymerase chain reaction (PCR) templates. The V3V4 region of the 16S rRNA gene was amplified and sequenced using the Illumina MiSeq. Results: Data regression analysis revealed that the recombinant plasmid produced more accurate and precise correlation curve than that by the gDNA and PCR products, with a slope closest to 1 (1.0082) and the highest R² value (0.9975). Despite the same input amount of bacterial DNA, the NGS read distribution varied across all three mock communities. Using multiple regression analysis, we found that the guanine-cytosine (GC) content of the V3V4 region, 16S rRNA gene, size of gDNA, and copy number of 16S rRNA were significantly associated with the NGS output of each bacterial species. Conclusion This study demonstrated that recombinant plasmids are the preferred option for quality control and that NGS output is biased owing to certain bacterial characteristics, such as %GC content, gDNA size, and 16S rRNA gene copy number. Further research is required to develop a system that compensates for NGS process biases using mock communities.

Background: The 16S rRNA-targeted next-generation sequencing (NGS) has been widely used as the primary tool for microbiome analysis. However, whether the sequenced microbial diversity absolutely represents the original sample composition remains unclear. This study aimed to evaluate whether 16S rRNA gene-targeted NGS accurately captures bacterial community composition. Methods: Mock communities were constructed using equal amounts of DNA from 18 bacterial strains in three formats: genomic DNA, recombinant plasmids, and polymerase chain reaction (PCR) templates. The V3V4 region of the 16S rRNA gene was amplified and sequenced using the Illumina MiSeq. Results: Data regression analysis revealed that the recombinant plasmid produced more accurate and precise correlation curve than that by the gDNA and PCR products, with a slope closest to 1 (1.0082) and the highest R² value (0.9975). Despite the same input amount of bacterial DNA, the NGS read distribution varied across all three mock communities. Using multiple regression analysis, we found that the guanine-cytosine (GC) content of the V3V4 region, 16S rRNA gene, size of gDNA, and copy number of 16S rRNA were significantly associated with the NGS output of each bacterial species. Conclusion This study demonstrated that recombinant plasmids are the preferred option for quality control and that NGS output is biased owing to certain bacterial characteristics, such as %GC content, gDNA size, and 16S rRNA gene copy number. Further research is required to develop a system that compensates for NGS process biases using mock communities.

Background: The 16S rRNA-targeted next-generation sequencing (NGS) has been widely used as the primary tool for microbiome analysis. However, whether the sequenced microbial diversity absolutely represents the original sample composition remains unclear. This study aimed to evaluate whether 16S rRNA gene-targeted NGS accurately captures bacterial community composition. Methods: Mock communities were constructed using equal amounts of DNA from 18 bacterial strains in three formats: genomic DNA, recombinant plasmids, and polymerase chain reaction (PCR) templates. The V3V4 region of the 16S rRNA gene was amplified and sequenced using the Illumina MiSeq. Results: Data regression analysis revealed that the recombinant plasmid produced more accurate and precise correlation curve than that by the gDNA and PCR products, with a slope closest to 1 (1.0082) and the highest R² value (0.9975). Despite the same input amount of bacterial DNA, the NGS read distribution varied across all three mock communities. Using multiple regression analysis, we found that the guanine-cytosine (GC) content of the V3V4 region, 16S rRNA gene, size of gDNA, and copy number of 16S rRNA were significantly associated with the NGS output of each bacterial species. Conclusion This study demonstrated that recombinant plasmids are the preferred option for quality control and that NGS output is biased owing to certain bacterial characteristics, such as %GC content, gDNA size, and 16S rRNA gene copy number. Further research is required to develop a system that compensates for NGS process biases using mock communities.

Background: The 16S rRNA-targeted next-generation sequencing (NGS) has been widely used as the primary tool for microbiome analysis. However, whether the sequenced microbial diversity absolutely represents the original sample composition remains unclear. This study aimed to evaluate whether 16S rRNA gene-targeted NGS accurately captures bacterial community composition. Methods: Mock communities were constructed using equal amounts of DNA from 18 bacterial strains in three formats: genomic DNA, recombinant plasmids, and polymerase chain reaction (PCR) templates. The V3V4 region of the 16S rRNA gene was amplified and sequenced using the Illumina MiSeq. Results: Data regression analysis revealed that the recombinant plasmid produced more accurate and precise correlation curve than that by the gDNA and PCR products, with a slope closest to 1 (1.0082) and the highest R² value (0.9975). Despite the same input amount of bacterial DNA, the NGS read distribution varied across all three mock communities. Using multiple regression analysis, we found that the guanine-cytosine (GC) content of the V3V4 region, 16S rRNA gene, size of gDNA, and copy number of 16S rRNA were significantly associated with the NGS output of each bacterial species. Conclusion This study demonstrated that recombinant plasmids are the preferred option for quality control and that NGS output is biased owing to certain bacterial characteristics, such as %GC content, gDNA size, and 16S rRNA gene copy number. Further research is required to develop a system that compensates for NGS process biases using mock communities.

Background: The 16S rRNA-targeted next-generation sequencing (NGS) has been widely used as the primary tool for microbiome analysis. However, whether the sequenced microbial diversity absolutely represents the original sample composition remains unclear. This study aimed to evaluate whether 16S rRNA gene-targeted NGS accurately captures bacterial community composition. Methods: Mock communities were constructed using equal amounts of DNA from 18 bacterial strains in three formats: genomic DNA, recombinant plasmids, and polymerase chain reaction (PCR) templates. The V3V4 region of the 16S rRNA gene was amplified and sequenced using the Illumina MiSeq. Results: Data regression analysis revealed that the recombinant plasmid produced more accurate and precise correlation curve than that by the gDNA and PCR products, with a slope closest to 1 (1.0082) and the highest R² value (0.9975). Despite the same input amount of bacterial DNA, the NGS read distribution varied across all three mock communities. Using multiple regression analysis, we found that the guanine-cytosine (GC) content of the V3V4 region, 16S rRNA gene, size of gDNA, and copy number of 16S rRNA were significantly associated with the NGS output of each bacterial species. Conclusion This study demonstrated that recombinant plasmids are the preferred option for quality control and that NGS output is biased owing to certain bacterial characteristics, such as %GC content, gDNA size, and 16S rRNA gene copy number. Further research is required to develop a system that compensates for NGS process biases using mock communities.

Objective: The objective of this prospective, observational multicenter study (NCT03264703) was to compare the effectiveness of single conventional disease-modifying anti-rheumatic drug (cDMARD) plus anti-tumor necrosis factor (TNF) therapy versus multiple cDMARD treatments in patients with moderate-to-severe rheumatoid arthritis (RA) following cDMARD failure in the real-world setting in South Korea. Methods: At the treating physicians’ discretion, patients received single cDMARD plus anti-TNF therapy or multiple cDMARDs. Changes from baseline in disease activity score 28-joint count with erythrocyte sedimentation rate (DAS28-ESR), corticosteroid use, and Korean Health Assessment Questionnaire (KHAQ-20) scores were evaluated at 3, 6, and 12 months. Results: Of 207 enrollees, the final analysis included 45 of 73 cDMARD plus anti-TNF and 91 of 134 multiple-cDMARD recipients. There were no significant between-group differences (BGDs) in ANCOVA-adjusted changes from baseline in DAS28-ESR at 3, 6 (primary endpoint), and 12 months (BGDs −0.18, −0.38, and −0.03, respectively). More cDMARD plus anti-TNF than multiple-cDMARD recipients achieved a >50% reduction from baseline in corticosteroid dosage at 12 months (35.7% vs 14.6%; p=0.007). Changes from baseline in KHAQ-20 scores at 3, 6, and 12 months were significantly better with cDMARD plus antiTNF therapy than with multiple cDMARDs (BGD −0.18, −0.19, and −0.19 points, respectively; all p≤0.024). Conclusion In the real-world setting, relative to multiple cDMARDs, single cDMARD plus anti-TNF therapy significantly improved quality-of-life scores and reduced corticosteroid use, with no significant BGD in disease activity, in RA patients in whom previous cDMARD therapy had failed.

Background: We aimed to investigate the characteristics of pediatric ulcerative colitis (UC) at diagnosis in Korea. Methods: This was a multicenter, registry-based, inception cohort study conducted in Korea between 2021 and 2023. Children and adolescents newly diagnosed with UC < 18 years were included. Baseline clinicodemographics, results from laboratory, endoscopic exams, and Paris classification factors were collected, and associations between factors at diagnosis were investigated. Results: A total 205 patients with UC were included. Male-to-female ratio was 1.59:1, and the median age at diagnosis was 14.7 years (interquartile range 11.9–16.2). Disease extent of E1 comprised 12.2% (25/205), E2 24.9% (51/205), E3 11.2% (23/205), and E4 51.7% (106/205) of the patients. S1 comprised 13.7% (28/205) of the patients. The proportion of patients with a disease severity of S1 was significantly higher in patients with E4 compared to the other groups (E1: 0% vs. E2: 2% vs. E3: 0% vs. E4: 24.5%, P < 0.001). Significant differences between disease extent groups were also observed in Pediatric Ulcerative Colitis Activity Index (median 25 vs. 35 vs. 40 vs. 45, respectively, P < 0.001), hemoglobin (median 13.5 vs.13.2 vs. 11.6 vs. 11.4 g/dL, respectively, P < 0.001), platelet count (median 301 vs. 324 vs. 372 vs. 377 × 103 /μL, respectively, P = 0.001), C-reactive protein (median 0.05 vs. 0.10 vs. 0.17 vs. 0.38 mg/dL, respectively, P < 0.001), and Ulcerative Colitis Endoscopic Index of Severity (median 4 vs. 4 vs. 4 vs. 5, respectively, P = 0.006). No significant differences were observed in factors between groups divided according to sex and diagnosis age. Conclusion This study represents the largest multicenter pediatric inflammatory bowel disease cohort in Korea. Disease severity was associated with disease extent in pediatric patients with UC at diagnosis.