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.

OBJECTIVES: We estimated the population prevalence of antibodies to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), including unreported infections, through a Korea Seroprevalence Study of Monitoring of SARS-CoV-2 Antibody Retention and Transmission (K-SEROSMART) in 258 communities throughout Korea. METHODS: In August 2022, a survey was conducted among 10,000 household members aged 5 years and older, in households selected through two stage probability random sampling. During face-to-face household interviews, participants self-reported their health status, COVID-19 diagnosis and vaccination history, and general characteristics. Subsequently, participants visited a community health center or medical clinic for blood sampling. Blood samples were analyzed for the presence of antibodies to spike proteins (anti-S) and antibodies to nucleocapsid proteins (anti-N) SARS-CoV-2 proteins using an electrochemiluminescence immunoassay. To estimate the population prevalence, the PROC SURVEYMEANS statistical procedure was employed, with weighting to reflect demographic data from July 2022. RESULTS: In total, 9,945 individuals from 5,041 households were surveyed across 258 communities, representing all basic local governments in Korea. The overall population-adjusted prevalence rates of anti-S and anti-N were 97.6% and 57.1%, respectively. Since the Korea Disease Control and Prevention Agency has reported a cumulative incidence of confirmed cases of 37.8% through July 31, 2022, the proportion of unreported infections among all COVID-19 infection was suggested to be 33.9%. CONCLUSIONS The K-SEROSMART represents the first nationwide, community-based seroepidemiologic survey of COVID-19, confirming that most individuals possess antibodies to SARS-CoV-2 and that a significant number of unreported cases existed. Furthermore, this study lays the foundation for a surveillance system to continuously monitor transmission at the community level and the response to COVID-19.

Background/aims: Circulating tumor cells (CTCs) with cancer stemness have been demonstrated to be a direct cause of tumor recurrence, and only few studies have reported the role of CTCs in liver transplantation (LT) for hepatocellular carcinoma (HCC). Methods: Epithelial cell adhesion molecule+ (EpCAM+), cluster of differentiation 90+ (CD90+) and EpCAM+/CD90+ CTCs were sorted via fluorescence-activated cell sorting, and transcripts level of EpCAM, K19 and CD90 in the peripheral blood were analyzed via real-time polymerase chain reaction preoperatively and on postoperative days 1 and 7 in 25 patients who underwent living donor liver transplantation (LDLT) for HCC. EpCAM protein was assessed in HCC tissue using immunohistochemical staining. The median follow-up duration was 40 months. Results: HCC after LDLT recurred in four out of 25 patients. Detection of EpCAM+ or CD90+ CTCs correlated well with their messenger RNA levels (p<0.05). EpCAM+ CTCs were readily detected in HCC tissue expressing EpCAM protein. The detection of EpCAM+ CTCs or EpCAM+/CD90+ CTCs before surgery and on postoperative day 1 was significantly associated with HCC recurrence after LT (all p<0.05). Pretransplant serum PIVKA-II >100 mAU/mL and postoperative day 1 EpCAM+/CD90+ CTCs were independent risk factors for HCC recurrence (hazard ratio, 14.64; 95% confidence interval, 1.08 to 198.20; p=0.043 and hazard ratio, 26.88; 95% confidence interval, 1.86 to 387.51; p=0.016, respectively). Conclusions EpCAM+/CD90+ CTCs can be used preoperatively and 1 day after LDLT as key biological markers in LT candidate selection and post-LDLT management.

Background: Although respiratory tract infection is one of the most important factors triggering acute exacerbation of chronic obstructive pulmonary disease (AE-COPD), limited data are available to suggest an epidemiologic pattern of microbiology in South Korea. Methods: A multicenter observational study was conducted between January 2015 and December 2018 across 28 hospitals in South Korea. Adult patients with moderate-to-severe acute exacerbations of COPD were eligible to participate in the present study. The participants underwent all conventional tests to identify etiology of microbial pathogenesis. The primary outcome was the percentage of different microbiological pathogens causing AE-COPD. A comparative microbiological analysis of the patients with overlapping asthma–COPD (ACO) and pure COPD was performed. Results: We included 1,186 patients with AE-COPD. Patients with pure COPD constituted 87.9% and those with ACO accounted for 12.1%. Nearly half of the patients used an inhaled corticosteroid-containing regimen and one-fifth used systemic corticosteroids. Respiratory pathogens were found in 55.3% of all such patients. Bacteria and viruses were detected in 33% and 33.2%, respectively. Bacterial and viral coinfections were found in 10.9%. The most frequently detected bacteria were Pseudomonas aeruginosa (9.8%), and the most frequently detected virus was influenza A (10.4%). Multiple bacterial infections were more likely to appear in ACO than in pure COPD (8.3% vs. 3.6%, p=0.016). Conclusion Distinct microbiological patterns were identified in patients with moderate-to-severe AE-COPD in South Korea. These findings may improve evidence-based management of patients with AE-COPD and represent the basis for further studies investigating infectious pathogens in patients with COPD.

Background: The coronavirus disease 2019 (COVID-19) pandemic caused disruptions to healthcare systems, consequently endangering tuberculosis (TB) control. We investigated delays in TB treatment among notified patients during the first wave of the COVID-19 pandemic in Korea. Methods: We systemically collected and analyzed data from the Korea TB cohort database from January to May 2020. Groups were categorized as ‘before-pandemic’ and ‘during-pandemic’ based on TB notification period. Presentation delay was defined as the period between initial onset of symptoms and the first hospital visit, and healthcare delay as the period between the first hospital visit and anti-TB treatment initiation. A multivariate logistic regression analysis was performed to evaluate factors associated with delays in TB treatment. Results: Proportion of presentation delay > 14 days was not significantly different between two groups (48.3% vs. 43.7%, P = 0.067); however, proportion of healthcare delay > 5 days was significantly higher in the during-pandemic group (48.6% vs. 42.3%, P = 0.012). In multivariate analysis, the during-pandemic group was significantly associated with healthcare delay > 5 days (adjusted odds ratio = 0.884, 95% confidence interval = 0.715–1.094). Conclusion The COVID-19 pandemic was associated with healthcare delay of > 5 days in Korea. Public health interventions are necessary to minimize the pandemic’s impact on the national TB control project.

Purpose: Inhalation of air containing high amounts of particular matter (PM) causes various respiratory disorders including asthma, chronic obstructive pulmonary disease, and lung cancer. The changes of expression of inflammatory factors by polydeoxyribonucleotide (PDRN) administration in the PM10-exposed trachea inflammation model were evaluated. Methods: PM10 was administered to mouse trachea to induce acute inflammatory damage, and changes in inflammatory factors were observed after administration of PDRN and 3,7-dimethyl-1-propargylxanthine (DMPX) for 3 days daily. Expression of inflammatory cytokines, adenosine A2A receptor (A2AR), protein kinase A (PKA), 3΄,5΄-cyclic adenosine monophosphate responsive element binding protein (CREB) were detected by enzyme‐linked immunosorbent assay, immunofluorescence, and western blot assay. Results: PM-exposed trachea showed increased tumor necrosis factor (TNF)-α and interleukin (IL)-1β expression, and expression of TNF-α and IL-1β was inhibited by PDRN treatment in PM-exposed mice. PM-exposed trachea showed increased nuclear factor (NF)-κB phosphorylation, and phosphorylation of nuclear factor-kappa B was inhibited by PDRN treatment in PM-exposed mice. PM-exposed trachea showed increased expression of A2AR, but PDRN treatment more enhanced A2AR expression in PM-exposed mice. PKA phosphorylation was not changed and CREP phosphorylation was decreased, however PDRN treatment increased phosphorylation of PKA and CREB in PM-exposed mice. DMPX treatment blocked all the effects of PDRN on PM-exposed mice, demonstrating that the action of PDRN occurs via A2AR. Conclusions PDRN treatment attenuated inflammation in the trachea of the PM10-exposed mice. This improving effect of PDRN can be ascribed to the activation of A2AR through the cAMP-PKA pathway.