Serotype distribution, antibiotic resistance, multilocus sequence typing, and virulence factors of invasive and non-invasive Streptococcus pneumoniae in Northeast China from 2000 to 2021.

Streptococcus pneumoniae infection is a major public health concern with high morbidity and mortality rates. This study aimed to evaluate the serotype distribution, antimicrobial resistance changes, clonal composition, and virulence factors of S. pneumoniae isolates causing pneumococcal disease in northeast China from 2000 to 2021. A total of 1,454 S. pneumoniae isolates were included, with 568 invasive strains and 886 non-invasive strains. The patients from whom the S. pneumoniae were isolated ranged in age from 26 days to 95 years, with those ≤ 5 years old comprising the largest group (67.19%). 19 F, 19 A, 23 F, 14, and 6B were the most common serotypes, of which 19 A and 19 F were the main serotypes of invasive and non-invasive S. pneumoniae, respectively. CC271 was the most common multilocus sequence type. Serotype 14 had the lowest expression of cbpA, rrgA, and psrP genes, but expression levels of 19 A and 19 F genes were similar. All isolates were sensitive to ertapenem, moxifloxacin, linezolid, and vancomycin but highly resistant to macrolides, tetracyclines, and cotrimoxazole. Simultaneous resistance to erythromycin, clindamycin, tetracyclines, and trimethoprim/sulfamethoxazole was common pattern among multidrug-resistant isolates. Non-invasive S. pneumoniae had higher resistance to ß-lactam antibiotics than invasive strains. 19 A and 19 F were the main strains of penicillin-resistant S. pneumoniae. The resistance rate of ß-lactam antibiotics decreased from 2017 to 2021 compared to previous periods. Including PCV13 in the national immunization program can reduce the morbidity and mortality rates of pneumococcal disease effectively.

sRNA expression profile of KPC-2-producing carbapenem-resistant Klebsiella pneumoniae: Functional role of sRNA51.

The emergence of carbapenem-resistant Klebsiella pneumoniae (CRKP) has significant challenges to human health and clinical treatment, with KPC-2-producing CRKP being the predominant epidemic strain. Therefore, there is an urgent need to identify new therapeutic targets and strategies. Non-coding small RNA (sRNA) is a post-transcriptional regulator of genes involved in important biological processes in bacteria and represents an emerging therapeutic strategy for antibiotic-resistant bacteria. In this study, we analyzed the transcription profile of KPC-2-producing CRKP using RNA-seq. Of the 4693 known genes detected, the expression of 307 genes was significantly different from that of carbapenem-sensitive Klebsiella pneumoniae (CSKP), including 133 up-regulated and 174 down-regulated genes. Both the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment and Gene Ontology (GO) analysis showed that these differentially expressed genes (DEGs) were mainly related to metabolism. In addition, we identified the sRNA expression profile of KPC-2-producing CRKP for the first time and detected 115 sRNAs, including 112 newly discovered sRNAs. Compared to CSKP, 43 sRNAs were differentially expressed in KPC-2-producing CRKP, including 39 up-regulated and 4 down-regulated sRNAs. We chose sRNA51, the most significantly differentially expressed sRNA in KPC-2-producing CRKP, as our research subject. By constructing sRNA51-overexpressing KPC-2-producing CRKP strains, we found that sRNA51 overexpression down-regulated the expression of acrA and alleviated resistance to meropenem and ertapenem in KPC-2-producing CRKP, while overexpression of acrA in sRNA51-overexpressing strains restored the reduction of resistance. Therefore, we speculated that sRNA51 could affect the resistance of KPC-2-producing CRKP by inhibiting acrA expression and affecting the formation of efflux pumps. This provides a new approach for developing antibiotic adjuvants to restore the sensitivity of CRKP.

Molecular epidemiology and antimicrobial resistance profiles of Klebsiella pneumoniae isolates from hospitalized patients in different regions of China.

Introduction: The increasing incidence of Klebsiella pneumoniae and carbapenem-resistant Klebsiella pneumoniae (CRKP) has posed great challenges for the clinical anti-infective treatment. Here, we describe the molecular epidemiology and antimicrobial resistance profiles of K. pneumoniae and CRKP isolates from hospitalized patients in different regions of China. Methods: A total of 219 K. pneumoniae isolates from 26 hospitals in 19 provinces of China were collected during 2019-2020. Antimicrobial susceptibility tests, multilocus sequence typing were performed, antimicrobial resistance genes were detected by polymerase chain reaction (PCR). Antimicrobial resistance profiles were compared between different groups. Results: The resistance rates of K. pneumoniae isolates to imipenem, meropenem, and ertapenem were 20.1%, 20.1%, and 22.4%, respectively. A total of 45 CRKP isolates were identified. There was a significant difference in antimicrobial resistance between 45 CRKP and 174 carbapenem-sensitive Klebsiella pneumoniae (CSKP) strains, and the CRKP isolates were characterized by the multiple-drug resistance phenotype.There were regional differences among antimicrobial resistance rates of K. pneumoniae to cefazolin, chloramphenicol, and sulfamethoxazole,which were lower in the northwest than those in north and south of China.The mostcommon sequence type (ST) was ST11 (66.7% of the strains). In addition, we detected 13 other STs. There were differences between ST11 and non-ST11 isolates in the resistance rate to amikacin, gentamicin, latamoxef, ciprofloxacin, levofloxacin, aztreonam, nitrofurantoin, fosfomycin, and ceftazidime/avibactam. In terms of molecular resistance mechanisms, the majority of the CRKP strains (71.1%, 32/45) harbored blaKPC-2, followed by blaNDM (22.2%, 10/45). Strains harboring blaKPC or blaNDM genes showed different sensitivities to some antibiotics. Conclusion: Our analysis emphasizes the importance of surveilling carbapenem-resistant determinants and analyzing their molecular characteristics for better management of antimicrobial agents in clinical use.

A prospective cohort-based artificial intelligence evaluation system for the protective efficacy and immune response of SARS-CoV-2 inactivated vaccines.

BACKGROUND: Novel coronaviruses constitute a significant health threat, prompting the adoption of vaccination as the primary preventive measure. However, current evaluations of immune response and vaccine efficacy are deemed inadequate. OBJECTIVES: The study sought to explore the evolving dynamics of immune response at various vaccination time points and during breakthrough infections. It aimed to elucidate the synergistic effects of epidemiological factors, humoral immunity, and cellular immunity. Additionally, regression curves were used to determine the correlation between the protective efficacy of the vaccine and the stimulated immune response. METHODS: Employing LASSO for high-dimensional data analysis, the study utilised four machine learning algorithms-logistical regression, random forest, LGBM classifier, and AdaBoost classifier-to comprehensively assess the immune response following booster vaccination. RESULTS: Neutralising antibody levels exhibited a rapid surge post-booster, escalating to 102.38 AU/mL at one week and peaking at 298.02 AU/mL at two weeks. Influential factors such as sex, age, disease history, and smoking status significantly impacted post-booster antibody levels. The study further constructed regression curves for neutralising antibodies, non-switched memory B cells, CD4+T cells, and CD8+T cells using LASSO combined with the random forest algorithm. CONCLUSION: The establishment of an artificial intelligence evaluation system emerges as pivotal for predicting breakthrough infection prognosis after the COVID-19 booster vaccination. This research underscores the intricate interplay between various components of immunity and external factors, elucidating key insights to enhance vaccine effectiveness. 3D modelling discerned distinctive interactions between humoral and cellular immunity within prognostic groups (Class 0-2). This underscores the critical role of the synergistic effect of humoral immunity, cellular immunity, and epidemiological factors in determining the protective efficacy of COVID-19 vaccines post-booster administration.

An update on our understanding of Gram-positive bacterial membrane vesicles: discovery, functions, and applications.

Extracellular vesicles (EVs) are nano-sized particles released from cells into the extracellular environment, and are separated from eukaryotic cells, bacteria, and other organisms with cellular structures. EVs alter cell communication by delivering their contents and performing various functions depending on their cargo and release into certain environments or other cells. The cell walls of Gram-positive bacteria have a thick peptidoglycan layer and were previously thought to be unable to produce EVs. However, recent studies have demonstrated that Gram-positive bacterial EVs are crucial for health and disease. In this review, we have summarized the formation, composition, and characteristics of the contents, resistance to external stress, participation in immune regulation, and other functions of Gram-positive bacterial EVs, as well as their application in clinical diagnosis and treatment, to provide a new perspective to further our understanding of Gram-positive bacterial EVs.

Altered profile of glycosylated proteins in serum samples obtained from patients with Hashimoto's thyroiditis following depletion of highly abundant proteins.

Objectives: Hashimoto's thyroiditis (HT) is one of the most common autoimmune disorders; however, its underlying pathological mechanisms remain unclear. Although aberrant glycosylation has been implicated in the N-glycome of immunoglobulin G (IgG), changes in serum proteins have not been comprehensively characterized. This study aimed to investigate glycosylation profiles in serum samples depleted of highly abundant proteins from patients with HT and propose the potential functions of glycoproteins for further studies on the pathological mechanisms of HT. Methods: A lectin microarray containing 70 lectins was used to detect and analyze glycosylation of serum proteins using serum samples (N=27 HT; N=26 healthy control [HC]) depleted of abundant proteins. Significant differences in glycosylation status between HT patients and the HC group were verified using lectin blot analysis. A lectin-based pull-down assay combined with mass spectrometry was used to investigate potential glycoproteins combined with differentially present lectins, and an enzyme-linked immunosorbent assay (ELISA) was used to identify the expression of targeted glycoproteins in 131 patients with papillary thyroid carcinoma (PTC), 131 patients with benign thyroid nodules (BTN) patients, 130 patients with HT, and 128 HCs. Results: Compared with the HC group, the majority of the lectin binding signals in HT group were weakened, while the Vicia villosa agglutinin (VVA) binding signal was increased. The difference in VVA binding signals verified by lectin blotting was consistent with the results of the lectin microarray. A total of 113 potential VVA-binding glycoproteins were identified by mass spectrometry and classified by gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) analyses. Using ELISA, we confirmed that lactoferrin (LTF) and mannan-binding lectin-associated serine protease 1 (MASP-1) levels were elevated in the serum of patients with HT and PTC. Conclusion: Following depletion of abundant proteins, remaining serum proteins in HT patients exhibited lower glycosylation levels than those observed in HCs. An increased level of potential VVA-binding glycoproteins may play an important role in HT development. LTF and MASP-1 expression was significantly higher in the serum of HT and PTC patients, providing novel insight into HT and PTC.