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.

Background: Numerous studies have examined the prevalence of Helicobacter pylori infection and clarithromycin (CLA) resistance rate of H. pylori. However, in South Korea, there is a lack of research analyzing specimens from local clinics and hospitals using molecular methods. This study aimed to assess the prevalence of H. pylori infection and CLA resistance across sex and age groups, as well as to explore regional variations in CLA resistance and its characteristics. Methods: Data from a laboratory information system from 2015 to 2018 were retrospectively analyzed to determine the prevalence of H. pylori infection and CLA resistance rate. The 23S ribosomal RNA genes of H. pylori were analyzed using a dual priming oligonucleotide-based multiplex polymerase chain reaction method. Results: The overall prevalence of H. pylori infection was 50.5%(12,000/23,773), with a significantly higher prevalence among males (53.5%) than females (47.0%). The CLA resistance rate was 28.3%, with a significantly higher rate among females (34.9%) than males (23.8%). Age group analysis revealed that the highest prevalence of H. pylori infection was among individuals in their 40s, whereas the highest CLA resistance rate was observed among those in their 60s. The CLA resistance rate exhibited an upward trend and varied among patients based on their place of residence, and A2143G mutation was the most prevalent across all regions. Conclusion The prevalence of H. pylori infection and CLA resistance rate in Korea remain high and vary according to sex, age, and region. To effectively eradicate H. pylori, it is crucial to periodically monitor regional CLA resistance patterns and conduct CLA susceptibility testing before prescription.

Background: Streptococcus pneumoniae is a serious pathogen causing various infections in humans. We evaluated the serotype distribution and antimicrobial resistance of S. pneumoniae causing invasive pneumococcal disease (IPD) after introduction of pneumococcal conjugate vaccine (PCV)13 in Korea and investigated the epidemiological characteristics of multidrug-resistant (MDR) isolates. Methods: S. pneumoniae isolates causing IPD were collected from 16 hospitals in Korea between 2017 and 2019. Serotyping was performed using modified sequential multiplex PCR and the Quellung reaction. Antimicrobial susceptibility tests were performed using the broth microdilution method. Multilocus sequence typing was performed on MDR isolates for epidemiological investigations. Results: Among the 411 S. pneumoniae isolates analyzed, the most prevalent serotype was 3 (12.2%), followed by 10A (9.5%), 34 (7.3%), 19A (6.8%), 23A (6.3%), 22F (6.1%), 35B (5.8%), 11A (5.1%), and others (40.9%). The coverage rates of PCV7, PCV10, PCV13, and pneumococcal polysaccharide vaccine (PPSV)23 were 7.8%, 7.8%, 28.7%, and 59.4%, respectively. Resistance rates to penicillin, ceftriaxone, erythromycin, and levofloxacin were 13.1%, 9.2%, 80.3%, and 4.1%, respectively. MDR isolates accounted for 23.4% of all isolates. Serotypes 23A, 11A, 19A, and 15B accounted for the highest proportions of total isolates at 18.8%, 16.7%, 14.6%, and 8.3%, respectively. Sequence type (ST)166 (43.8%) and ST320 (12.5%) were common among MDR isolates. Conclusions Non-PCV13 serotypes are increasing among invasive S. pneumoniae strains causing IPD. Differences in antimicrobial resistance were found according to the specific serotype. Continuous monitoring of serotypes and antimicrobial resistance is necessary for the appropriate management of S. pneumoniae infections.

Background: Development of an accessible method to routinely evaluate the clonality of strains is needed in microbiology laboratories. We compared the discriminatory power of the Fourier-transform infrared (FTIR) spectroscopy–based IR Biotyper (Bruker Daltonics GmbH, Bremen, Germany) to matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), using whole-genome sequencing (WGS) as the reference method. Methods: Eighty-three extended-spectrum β-lactamase–producing Escherichia coli isolates were tested using WGS, MALDI-TOF MS, and IR Biotyper. Simpson’s diversity index (SDI), a statistical analysis for testing the homogeneity of a dendrogram, and the adjusted Rand index (aRI) were used to compare the discriminatory ability between typing tests. Results: The SDI (95% confidence interval) was 0.969 (0.952–0.985) for WGS, 0.865 (0.807–0.924) for MALDI-TOF MS, and 0.974 (0.965–0.983) for IR Biotyper. Compared with WGS, IR Biotyper showed compatible diversity, whereas MALDI-TOF MS did not. The concordance and aRI improved from 66.3% to 84.3% and from 0.173 to 0.538, respectively, for IR Biotyper versus MALDI-TOF MS with WGS as the reference method. IR Biotyper showed substantially improved performance in strain typing compared with MALDI-TOF MS. Conclusions IR Biotyper is useful for diversity analysis with improved discriminatory power over MALDI-TOF MS in comparison with WGS as a reference method. IR Biotyper is an accessible method to evaluate the clonality of strains and could be applied in epidemiological analysis during an outbreak of a health care facility, as well as for research on the transmission of resistant bacteria in community settings.

Acquired fluconazole resistance (FR) in bloodstream infection (BSI) isolates of Candida albicans is rare. We investigated the FR mechanisms and clinical features of 14 fluconazole non-susceptible (FNS; FR and fluconazole-susceptible dose-dependent) BSI isolates of C. albicans recovered from Korean multicenter surveillance studies during 2006–2021. Mutations causing amino acid substitutions (AASs) in the drug-target gene ERG11 and the FR-associated transcription factor genes TAC1 , MRR1, and UPC2 of the 14 FNS isolates were compared with those of 12 fluconazole-susceptible isolates. Of the 14 FNS isolates, eight and seven had Erg11p (K143R, F145L, or G464S) and Tac1p (T225A, R673L, A736T, or A736V) AASs, respectively, which were previously described in FR isolates. Novel Erg11p, Tac1p, and Mrr1p AASs were observed in two, four, and one FNS isolates, respectively. Combined Erg11p and Tac1p AASs were observed in seven FNS isolates. None of the FR-associated Upc2p AASs were detected. Of the 14 patients, only one had previous azole exposure, and the 30-day mortality rate was 57.1% (8/14). Our data show that Erg11p and Tac1p AASs are likely to contribute to FR in C. albicans BSI isolates in Korea and that most FNS C. albicans BSIs develop without azole exposure.

Purpose: This study aimed to identify the influence of knowledge of personal information protection law and nursing patient advocacy on practice of personal information protection among nurses. Methods: The subjects were 130 nurses who have worked for six months or more in the ward of the tertiary or general hospitals. Data were collected from February 20 to March 3, 2023. Results: Factors influencing practice of personal information protection were acting as an advocate (β=.32, p=.004), environmental and educational influences (β=.21, p=.040), knowledge of personal information protection law (β=.19, p=.013) and clinical experience for five years or more but less than ten years (β=.17, p=.036). The regression model showed an explanatory power of 34.0%. Conclusion Acting as an advocate has the most effect on practice of personal information protection. To promote practice of personal information protection for nurses, it is necessary to provide education related to privacy protection and encourage nursing patient advocacy.