Background Klebsiella pneumoniae, as a global priority pathogen, is well known for its capability of acquiring mobile genetic elements that carry resistance and/or virulence genes. Its virulence plasmid, previously deemed nonconjugative and restricted within hypervirulent K. pneumoniae (hvKP), has disseminated into classic K. pneumoniae (cKP), particularly carbapenem-resistant K. pneumoniae (CRKP), which poses alarming challenges to public health. However, the mechanism underlying its transfer from hvKP to CRKP is unclear. Methods A total of 28 sequence type (ST) 11 bloodstream infection-causing CRKP strains were collected from Ruijin Hospital in Shanghai, China, and used as recipients in conjugation assays. Transconjugants obtained from conjugation assays were confirmed by XbaI and S1 nuclease pulsed-field gel electrophoresis, PCR detection and/or whole-genome sequencing. The plasmid stability of the transconjugants was evaluated by serial culture. Genetically modified strains and constructed mimic virulence plasmids were employed to investigate the mechanisms underlying mobilization. The level of extracellular polysaccharides was measured by mucoviscosity assays and uronic acid quantification. An in silico analysis of 2608 plasmids derived from 814 completely sequenced K. pneumoniae strains available in GenBank was performed to investigate the distribution of putative helper plasmids and mobilizable virulence plasmids. Results A nonconjugative virulence plasmid was mobilized by the conjugative plasmid belonging to incompatibility group F (IncF) from the hvKP strain into ST11 CRKP strains under low extracellular polysaccharide-producing conditions or by employing intermediate E. coli strains. The virulence plasmid was mobilized via four modes: transfer alone, cotransfer with the conjugative IncF plasmid, hybrid plasmid formation due to two rounds of single-strand exchanges at specific 28-bp fusion sites or homologous recombination. According to the in silico analysis, 31.8% (242) of the putative helper plasmids and 98.8% (84/85) of the virulence plasmids carry the 28-bp fusion site. All virulence plasmids carry the origin of the transfer site. Conclusions The nonconjugative virulence plasmid in ST11 CRKP strains is putatively mobilized from hvKP or E. coli intermediates with the help of conjugative IncF plasmids. Our findings emphasize the importance of raising public awareness of the rapid dissemination of virulence plasmids and the consistent emergence of hypervirulent carbapenem-resistant K. pneumoniae (hv-CRKP) strains.

Nowadays, the underlying mobilization mechanism and evolutionary processes of nonconjugative virulence or resistance plasmids in Klebsiella pneumoniae remain poorly understood. Our study revealed the high conjugation ability of IncN3 plasmid isolated from carbapenem-resistant K. pneumoniae and confirmed its capability to mobilize the nonconjugative virulence or resistance plasmids.

Bacterial integrative and conjugative elements (ICEs) are highly modular mobile genetic elements critical to the horizontal transfer of antibiotic resistance and virulence factor genes. To better understand and analyze the ongoing increase of ICEs, we developed an Integrative and Conjugative Element Ontology (ICEO) to represent the gene components, functional modules, and other information of experimentally verified ICEs. ICEO is aligned with the upper-level Basic Formal Ontology and reuses existing reliable ontologies. There are 31,081 terms, including 26,814 classes from 14 ontologies and 4128 ICEO-specific classes, representing the information of 271 known experimentally verified ICEs from 235 bacterial strains in ICEO currently and 311 predicted ICEs of 272 completely sequenced Klebsiella pneumoniae strains. Three ICEO use cases were illustrated to investigate complex joins of ICEs and their harboring antibiotic resistance or virulence factor genes by using SPARQL or DL query. ICEO has been approved as an Open Biomedical Ontology library ontology. It may be dedicated to facilitating systematical ICE knowledge representation, integration, and computer-assisted queries.

Class style is an important indicator affecting the quality of talent training in colleges and universities. How to establish an effective class style evaluation model is of great significance to promote the formation of excellent class style and provide decision support for university personnel training programs. Compared with previous studies, this paper comprehensively considers the factors affecting the evaluation based on the principle of combining subjectivity with objectivity. With the changes of higher education reform, we have prospectively incorporated the indicators that may reflect the status of the work style into the evaluation system. On the basis of these innovative principles, this paper realized low-cost data collection with digital campus, and combined entropy weight method, high-order factor analysis method and similarity cosine calculation method to build a class evaluation analysis model based on big data.