Objective:To identify strain-specific features of Klebsiella pneumoniae by analyzing metagenomics next generation sequencing (mNGS) data, thereby expanding the downstream applications of mNGS. Methods:The sequences of K.pneumoniae strains were organized from both the self-built database of the long-term multi-center research cohort in China established by the Peking University People′s Hospital from 2009 to 2020 (with 2 345 sequences) and the public databases (with 19 648 sequences). The existing large-scale databases were compressed, and a set of strains representative of clonal groups were screened. A strain genome information library was constructed based on k-mer features, and the most matching representative sequences in the database were searched for the raw mNGS data. The search results of the self-built library and public library were merged and optimized to update the prediction of antimicrobial-resistance characteristics and avoid the impact of uneven data distribution on the results. A total of 314 clinical samples from patients with K.pneumoniae detected by mNGS in the Clinical Microbiology Laboratory of Peking University People′s Hospital from 2022 to 2024 were retrospectively collected, and 101 samples with positive clinical culture results were selected to validate the prediction results. The antimicrobial-resistance phenotypes were verified by clinical antimicrobial susceptibility test results. Whole-genome sequencing was performed on the culture strains of 14 samples randomly selected using random numbers to verify the genotypes. Single nucleotide polymorphism distance analysis was used to verify the occurrence of outbreak events. The χ2 test and Mann-Whitney U test were used for statistical analysis. Results:A representative strain sequence k-mer feature library containing self-built and public sub-libraries was constructed. The library construction required only about 1 hour with <3 GB storage, with a high compression ratio and low update cost. Using k-mer-based analysis, mNGS data achieved precise strain characterization within 4 minutes and and <5 GB memory occupation. There was a significant difference in the antimicrobial-resistance rates to more than half of the antibiotics between the self-built database (90.8%, 2 130/2 345) and the public database (22.7%, 4 457/19 648) ( χ2=4 634.1, P<0.001). After optimizing the search results, the mean category agreement, sensitivity, and specificity of the prediction for eight antibiotics reached 84.8% (323/381), 78.9% (131/166), and 91.2% (196/215), respectively. The target genotypes were successfully detected in 10 out of 12 samples, and two outbreak events (2 samples per event) were successfully identified. Conclusions:An independent analysis process adapted to the needs of identifying the features of K. pneumoniae strains in mNGS data was developed. This process requires minimal computational resources and processing time and can directly achieve the simultaneous analysis of the antimicrobial-resistance phenotypes of K. pneumoniae at the strain level and their corresponding genomic characteristic profiles based on the raw mNGS reads.

Objective:To identify strain-specific features of Klebsiella pneumoniae by analyzing metagenomics next generation sequencing (mNGS) data, thereby expanding the downstream applications of mNGS. Methods:The sequences of K.pneumoniae strains were organized from both the self-built database of the long-term multi-center research cohort in China established by the Peking University People′s Hospital from 2009 to 2020 (with 2 345 sequences) and the public databases (with 19 648 sequences). The existing large-scale databases were compressed, and a set of strains representative of clonal groups were screened. A strain genome information library was constructed based on k-mer features, and the most matching representative sequences in the database were searched for the raw mNGS data. The search results of the self-built library and public library were merged and optimized to update the prediction of antimicrobial-resistance characteristics and avoid the impact of uneven data distribution on the results. A total of 314 clinical samples from patients with K.pneumoniae detected by mNGS in the Clinical Microbiology Laboratory of Peking University People′s Hospital from 2022 to 2024 were retrospectively collected, and 101 samples with positive clinical culture results were selected to validate the prediction results. The antimicrobial-resistance phenotypes were verified by clinical antimicrobial susceptibility test results. Whole-genome sequencing was performed on the culture strains of 14 samples randomly selected using random numbers to verify the genotypes. Single nucleotide polymorphism distance analysis was used to verify the occurrence of outbreak events. The χ2 test and Mann-Whitney U test were used for statistical analysis. Results:A representative strain sequence k-mer feature library containing self-built and public sub-libraries was constructed. The library construction required only about 1 hour with <3 GB storage, with a high compression ratio and low update cost. Using k-mer-based analysis, mNGS data achieved precise strain characterization within 4 minutes and and <5 GB memory occupation. There was a significant difference in the antimicrobial-resistance rates to more than half of the antibiotics between the self-built database (90.8%, 2 130/2 345) and the public database (22.7%, 4 457/19 648) ( χ2=4 634.1, P<0.001). After optimizing the search results, the mean category agreement, sensitivity, and specificity of the prediction for eight antibiotics reached 84.8% (323/381), 78.9% (131/166), and 91.2% (196/215), respectively. The target genotypes were successfully detected in 10 out of 12 samples, and two outbreak events (2 samples per event) were successfully identified. Conclusions:An independent analysis process adapted to the needs of identifying the features of K. pneumoniae strains in mNGS data was developed. This process requires minimal computational resources and processing time and can directly achieve the simultaneous analysis of the antimicrobial-resistance phenotypes of K. pneumoniae at the strain level and their corresponding genomic characteristic profiles based on the raw mNGS reads.

Objective:Investigate the characteristics of hospitalized patients infected with parvovirus B19 (B19V) and the potential impact of B19V on disease progression and clinical outcomes in patients.Methods:The subjects of this observational retrospective study were 62 hospitalized patients who tested positive for B19V among 3 129 inpatients who visited Peking University People′s Hospital between April 1, 2022, and August 31, 2023, and underwent metagenomic next-generation sequencing (mNGS) for pathogens. Patient data regarding pathogen detection, clinical characteristics, and outcomes were collected, along with other laboratory test results, to assess hospitalization duration, incidence of mixed infections during hospitalization, and clinical outcomes within 30 days. The chi-square test was utilized to analyze differences in patient mortality rates and other relevant factors.Results:B19V infection waspobserved in patients with hematological disorders and solid organ transplant recipients (79.03%, 49/62). Additionally, B19V frequently coexists with other pathogens (40/62), with the highest rates of mixed infections involving human herpesvirus 6, cytomegalovirus, and Epstein-Barr virus, having 20, 9, and 8 cases respectively. The most common site of B19V detection is peripheral blood (χ 2=0.000 3, P<0.001), although it can also be detected in other bodily fluid samples. The 30 day mortality rate among B19V infected patients was 19.35% (12/62) 10 out of 12 deceased patients had concurrent mixed infections with other pathogens. Moreover, patients with mixed B19V infections exhibited a higher mortality rate compared to those with B19V infection alone (χ 2=4.546, P=0.033). Comparative analysis of 24 patients who underwent multiple mNGS tests revealed that patients with chronic B19V infection (12 cases) had a higher mortality rate compared to those with transient B19V infection (12 cases) (χ 2=12, P<0.001). Conclusions:Parvovirus B19 (B19V) infection is more commonly observed in patients with hematological disorders and solid organ transplant recipients, often coexisting with other pathogens. The mortality rate within 30 days of B19V infection is elevated, particularly when accompanied by concurrent mixed infections with other pathogens. Moreover, patients with chronic and persistent B19V infection face an increased risk of mortality.

Objective:To predict the pathogens of bloodstream infection (BSI) in hematopoietic stem cell transplantation (HSCT) patients by plasma microbial cell-free DNA (mcfDNA) sequencing with and without additional amplification.Methods:A total of 978 HSCT patients were enrolled in Peking University People′s Hospital from March to July 2021, and the 7 428 blood samples were prospectively collected from pretransplant conditioning period to 4 months after transplantation. The plasma samples were separated and then cryopreserved. According to blood culture results and whether there were plasma samples before BSI onset, twenty-eight HSCT patients with positive blood culture (39 plasma samples within 1-8 days before BSI onset) and 9 HSCT patients with negative blood culture (9 plasma samples) were filtered. The 39 samples were performed with mcfDNA additional and non-additional amplification sequencing, and the 9 samples were only performed with additional amplification sequencing. With the blood culture results as the gold standard, the consistency between the sequencing and the blood culture results was observed. Student t test and Wilcoxon test were used for statistical analysis. Results:Without additional amplification sequencing, only 7 samples sequencing results were consistent with the blood culture results, and the total pathogen detection rate was 17.95% (7/39). The rates within 3 days and 4-8 days were 23.81% (5/21) and 2/18, respectively. The main pathogenic type detected was gram-negative bacteria (5/7). With additional amplification sequencing, the total pathogen detection rate was 59.26% (16/27) and the rate within 3 days was 8/13. The number of gram-positive bacteria detected was elevated (13/16) and the number of additional microorganisms in additional amplification sequencing was increased significantly ( P=0.001 0), compared with non-additional amplification sequencing. Moreover, additional sequencing analysis of 9 samples from patients with negative culture result showed that no pathogen was detected in six samples, and the common Torque teno virus in HSCT patients was detected in only three samples. Conclusion:The pathogen detection rate of plasma mcfDNA additional amplification sequencing was better than that of non-additional amplification sequencing in HSCT patients before BSI onset, especially in the first three days, which has the potential to predict BSI pathogens.

Nosocomial infections caused by gram-negative opportunistic pathogens, including Acinetobacter baumannii ( A. baumannii) and Klebsiella pneumoniae ( K. pneumoniae), pose a great challenge to health care management and human health. New treatment strategies are urgently needed to tackle with the spread of multi-drug resistant strains and the increase in bacterial virulence. Type Ⅵ secretion system (T6SS), a conservative secretory apparatus encoded in a variety of gram-negative bacteria, can inject effectors into other prokaryotic or eukaryotic cells in a contact-dependent manner to achieve antibacterial and anti-host properties. It is closely related to the environmental adaptability, competitiveness and colonization ability of bacteria in hosts. The T6SS gene cluster is composed of core genes, effector genes and associated genes, and the effectors encoded by it are highly diverse and play an important role in pathogen infection. This review summarized the advances in A. baumannii and K. pneumoniae T6SS in terms of competition, host colonization, interaction between conjugative plasmids and expression regulation, aiming to provide reference for future study on T6SS-related antimicrobial activity, virulence and resistance.