Characterisation of highly virulent and colistin-resistant ST367-KL1 Klebsiella quasipneumoniae subsp. similipneumoniae Strain.

OBJECTIVES: To elucidate the characteristics of a colistin-resistant and hypervirulent Klebsiella quasipneumoniae subsp. similipneumoniae strain (KP8) using whole genome sequencing and various phenotypic assays. METHODS: Antimicrobial susceptibility testing was performed using broth microdilution. Whole genome sequencing and comparative genomics were utilised to elucidate genomic characteristics. Phenotypic assays to evaluate virulence factors included measurements of mucosal viscosity, biofilm production, siderophore production, infection of A549 cells, serum-killing assays, and Galleria mellonella infection models. RESULTS: Whole-genome sequencing revealed that the strain (KP8) belongs to sequence type 367 (ST367) and capsular type 1 (KL1), and it harbours several virulence genes, including regulator of mucoid phenotype (rmpA/A2), salmochelin (iroBCDN) and aerobactin (iucABCDiutA). Antibiotic susceptibility tests showed that KP8 was resistant to colistin. Genome analysis showed that the colistin resistance of KP8 might be related to amino acid insertions in pmrB (L215_D217, insL) and pagP (M1_S3, insV). Importantly, KP8 demonstrated comparable mucosal viscosity, biofilm production capacity, siderophore production levels to hvKP. Serum-killing experiments, A549 cell infection models, and G. mellonella infection models further indicated that KP8 displayed high virulence, akin to the hypervirulent strain NUTH-K2044. Notably, global genome analysis of the K. quasipneumoniae subsp. similipneumoniae strains highlighted that the ST367 lineage has a higher tendency to carry virulence-associated genes compared to other sequence types. The prevalence of virulence-associated factors concentrated within Chinese ST367 isolates reinforces this observation. CONCLUSION: These findings further enhance our understanding of the resistance and pathogenicity of ST367 K. quasipneumoniae subsp. similipneumoniae strain and also providing a broader perspective on the global epidemiological landscape.

Metagenomic next-generation sequencing for the identification of infections caused by Gram-negative pathogens and the prediction of antimicrobial resistance.

OBJECTIVE: The aim of this study was to evaluate the efficacy of metagenomic next-generation sequencing (mNGS) for the identification of Gram-negative bacteria (GNB) infections and the prediction of antimicrobial resistance. METHODS: A retrospective analysis was conducted on 182 patients with diagnosis of GNB infections who underwent mNGS and conventional microbiological tests (CMTs). RESULTS: The detection rate of mNGS was 96.15%, higher than CMTs (45.05%) with a significant difference (χ 2 = 114.46, P < .01). The pathogen spectrum identified by mNGS was significantly wider than CMTs. Interestingly, the detection rate of mNGS was substantially higher than that of CMTs (70.33% vs 23.08%, P < .01) in patients with but not without antibiotic exposure. There was a significant positive correlation between mapped reads and pro-inflammatory cytokines (interleukin-6 and interleukin-8). However, mNGS failed to predict antimicrobial resistance in 5 of 12 patients compared to phenotype antimicrobial susceptibility testing results. CONCLUSIONS: Metagenomic next-generation sequencing has a higher detection rate, a wider pathogen spectrum, and is less affected by prior antibiotic exposure than CMTs in identifying Gram-negative pathogens. The mapped reads may reflect a pro-inflammatory state in GNB-infected patients. Inferring actual resistance phenotypes from metagenomic data remains a great challenge.

Clinical Efficacy and Diagnostic Value of Metagenomic Next-Generation Sequencing for Pathogen Detection in Patients with Suspected Infectious Diseases: A Retrospective Study from a Large Tertiary Hospital.

Purpose: Metagenomic next-generation sequencing (mNGS) is a powerful yet unbiased method to identify pathogens in suspected infections. However, little is known about its clinical effectiveness. The present study aimed to assess the efficacy of mNGS in routine clinical practice. Patients and Methods: In this single-center retrospective cohort study, 518 patients with suspected infectious diseases were assessed for inclusion. Among them, each patient had undergone mNGS testing; 407 patients had undergone both microbial culture and mNGS testing. The result of mNGS testing was compared to microbial culture performed concurrently. The diagnostic performance of mNGS was evaluated using the comprehensive clinical diagnosis as the reference standard. Results: There was a significant difference in the positive detection rates of pathogens between mNGS and culture (331/407, 81.3% vs 79/407, 19.4%, P < 0.001). The sensitivity of mNGS was much higher than the culture method (79.5% vs 21.3%, P < 0.001), especially in sample types of sputum and bronchoalveolar lavage fluid (BALF). Notably, the sensitivity of blood mNGS was relatively lower than other sample types (67.4% vs 88.9-93.8%). Pathogen cfDNA load based on standardized stringently mapped read number at the species level of microorganisms (SDSMRN) was significantly lower in blood than in other sample types from the same patient (P = 0.0003). Importantly, mNGS directly led to a change of treatment regimen in 142 (27.4%) cases, including antibiotic escalation (15.3%), antibiotic de-escalation (9.1%), and early definitive diagnosis to initiate appropriate treatment (3.1%). Conclusion: Our in-house mNGS platform significantly improved the sensitivity for the diagnosis of infectious diseases. mNGS has the potential to improve clinical outcomes by optimizing antimicrobial therapy.

A pilot investigation on serum protein fingerprinting of nasopharyngeal carcinoma / 中华耳鼻咽喉头颈外科杂志

<p><b>OBJECTIVE</b>To establish a preliminary foundation for developing a serum proteomics diagnostic model of nasopharyngeal carcinoma (NPC) by comparing the differences in serum protein fingerprints between patients with NPC and healthy subjects and between different types of NPC.</p><p><b>METHODS</b>The serum samples of 41 patients with different types of NPC and 20 healthy subjects were collected. Surface-enhanced laser desorption ionization time-of-flight mass spectrometry (SELDI-TOF-MS) were used to detect the blood samples to obtain serum protein mass spectrum, i.e. serum protein fingerprinting. Biomarker Wizard and Biomarker Patterns system software were used to compare the differences in serum protein mass spectrum between NPC patients and healthy subjects and between different types of NPC, and to screen out the NPC-related serum proteins.</p><p><b>RESULTS</b>Compared with the healthy control, NPC patients emerged 9 very prominent protein peaks (P < 0.001), with the combined differential peaks. No significant difference was found in relative amount of serum proteins with different molecular mass between different types of NPC (P > 0.05).</p><p><b>CONCLUSIONS</b>The serum marker proteins and specific protein fingerprints of NPC can be screened out by SELDI-TOF-MS, which could be used to develop a serum proteomics model for clinical screening and early diagnosis of NPC.</p>