Chrome Extension
WeChat Mini Program
Use on ChatGLM

Genetic diversity of blaKPC-gene-containing IncF plasmids from epidemiologically related and unrelated Enterobacteriaceae

biorxiv(2020)

Department of Infection Control | Department of Medical Microbiology and Infection Prevention

Cited 0|Views12
Abstract
Background Limited information is available on whether bla KPC-containing plasmids from isolates in a hospital outbreak can be differentiated from epidemiologically unrelated bla KPC-containing plasmids based on sequence data. Objective This study aimed to evaluate the performance of three approaches to distinguish epidemiologically related from unrelated bla KPC-containing IncF plasmids. Method Epidemiologically related isolates, were short- and long-read whole genome sequenced on an Illumina MiSeq and MinION sequencer. A hybrid assembly was performed and plasmid sequences were extracted from the assembly graph. Epidemiologically unrelated plasmid sequences were extracted from the GenBank. Pairwise comparisons were performed of epidemiologically related and unrelated plasmids based on SNP differences using snippy, phylogenetic distance using Roary and using a similarity index that penalizes size differences between plasmids (Stoesser-index). The percentage of pairwise comparisons misclassified as genetically related or as clonally unrelated was determined using different genetic thresholds for genetic relatedness for all three comparison methods. Results Despite the median number of SNP differences, Roary phylogenetic distance, and Stoesser-index differed between the epidemiologically related and unrelated plasmids, the range of differences overlapped between the two comparison groups for all three comparison methods. When using a genetic similarity threshold that classified 100% of epidemiologically related plasmid pairs as genetically related, the percentages of plasmids misclassified as epidemiologically related ranged from 6.7% (Roary) to 20.8% (Stoesser-index). Discussion Although epidemiologically related plasmids can be distinguished from unrelated plasmids based on genetic similarity, epidemiologically related and unrelated bla KPC-containing IncF plasmids show a high degree of sequence similarity. The phylogenetic distance as determined using Roary showed the highest degree of discriminatory power between the epidemiologically related and unrelated plasmids. Impact statement Accurately distinguishing epidemiologically related from unrelated plasmids is essential to detect nosocomial plasmid transmission in outbreaks. However, limited information is available on whether bla KPC-containing plasmids from isolates in a hospital outbreak can be differentiated from epidemiologically unrelated bla KPC-containing plasmids based on sequence data. This study aimed to evaluate the performance of three approaches to distinguish epidemiologically related from unrelated bla KPC-containing IncF plasmids. Pairwise comparisons were performed of epidemiologically related and unrelated plasmids based on SNP differences using snippy, phylogenetic distance using Roary and using a similarity index that penalizes size differences between plasmids (Stoesser-index). Based on our results, epidemiologically related plasmids can be distinguished from unrelated plasmids based on genetic similarity. Despite this, epidemiologically related and unrelated bla KPC-containing IncF plasmids show a high degree of sequence similarity and judgements on the horizontal transfer of these plasmids during hospital outbreaks based on genetic identity should be made with caution. The phylogenetic distance determined using Roary showed the highest discriminatory power between the epidemiologically related and unrelated plasmids. Data summary Short-and long-read sequence data of the epidemiologically related Enterobacteriaceae isolates included in this study are available from the publicly available European Nucleotide Archive of the European Bioinformatics Institute under study accession number: PRJEB41009. The authors confirm that all supporting data have been provided within the article and through the supplementary data files. ### Competing Interest Statement The authors have declared no competing interest. * KPC : Klebsiella pneumoniae carbapenemase SNP : Single nucleotide polymorphism wgMLST : Whole-genome MLST Stoesser-similarity index : similarity index as described by Stoesser et al.
More
Translated text
PDF
Bibtex
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
  • Pretraining has recently greatly promoted the development of natural language processing (NLP)
  • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
  • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
  • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
  • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Try using models to generate summary,it takes about 60s
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Related Papers
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
GPU is busy, summary generation fails
Rerequest