Genomic and phylogenetic analysis of a multidrug-resistant mcr-1-carrying Klebsiella pneumoniae recovered from a urinary tract infection in China
Bibliographic record
Abstract
OBJECTIVES: The emergence and dissemination of colistin-resistant Enterobacterales has become a major global public-health threat. Here we investigated the genomic and phylogenetic characteristics of a multidrug-resistant Klebsiella pneumoniae strain (KP4823) carrying the mcr-1 gene recovered from a urinary tract infection in China. METHODS: Antimicrobial susceptibility of K. pneumoniae KP4823 was determined by broth microdilution. Whole genomic DNA was extracted and sequenced using Oxford Nanopore MinION and Illumina NovaSeq 6000 platforms. Hybrid assembly with long and short reads was performed using Unicycler, and the genome was annotated using the NCBI Prokaryotic Genome Annotation Pipeline (PGAP). The sequence type (ST), capsular type, and antimicrobial resistance and virulence genes were identified from the genome sequence. Core genome multilocus sequence typing (cgMLST) analysis was performed by BacWGSTdb 2.0 server. RESULTS: Klebsiella pneumoniae KP4823 was resistant to colistin, ceftazidime, cefepime, cefotaxime, fosfomycin and aztreonam. The complete genome sequence of KP4823 consists of five contigs comprising 5 445 519 bp, including one chromosome and four plasmids. The isolate was assigned to ST101 with capsular serotype KL106. Several antimicrobial resistance genes were identified, including the colistin resistance gene mcr-1, which was located on a 34 685-bp IncX4 plasmid. The closest relative of K. pneumoniae KP4823 was another ST101 isolate (08EU827) recovered from Sweden in 2008, which differed by 191 cgMLST loci. CONCLUSION: Our study reports the genome sequence of a multidrug-resistant mcr-1-carrying K. pneumoniae in China. These data may help to understand the antimicrobial resistance mechanisms, genomic features and transmission dynamics of colistin resistance in clinical settings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".