TreeBASE Search-Analyses for study 28058

@ARTICLE{TreeBASE2Ref31996, author = {Jingjing Chen and Sufei Tian and Hua Nian and Ruixuan Wang and Fushun Li and Ning Jiang and Yunzhuo Chu}, title = {Carbapenem-resistant Enterobacter cloacae complex in a tertiary Hospital in Northeast China, 2010?2019}, year = {2021}, keywords = {Enterobacter cloacae complex, carbapenem-resistant, molecular analyses, ST93, NDM}, doi = {10.1186/s12879-021-06250-0}, url = {http://}, pmid = {}, journal = {BMC Infectious Diseases}, volume = {21}, number = {}, pages = {611}, abstract = {Background: Carbapenem-resistant Enterobacter cloacae complex (CREC) is a new emerging threat to global public health. The objective of the study was to investigate the clinical characteristics and molecular epidemiology of CREC infections in the medical center of northeast China. Methods: Twenty-nine patients were infected/colonized with CREC during a ten-year period (2010-2019) by WHONET analysis. Antibiotic susceptibilities were tested with VITEK 2 and micro broth dilution method (for polymyxin B and tigecycline). Carbapenemase encoding genes, β-lactamase genes, and seven housekeeping genes for MLST were amplified and sequenced for 18 cryopreserved CREC isolates. Maximum likelihood phylogenetic tree was built with the concentrated sequences to show the relatedness between the 18 isolates. Results: There was a rapid increase in CREC detection rate during the ten-year period, reaching 8.11% in 2018 and 6.48% in 2019. The resistance rate of CREC isolates to imipenem and meropenem were 100.0% and 72.2%, however, they showed high sensitivity to tigecycline, polymyxin B and amikacin. The 30-day crude mortality of CREC infection/colonization was 13.8%, indicating that it may be a low-virulence bacterium. Furthermore, molecular epidemiology revealed that ST93 was the predominant sequence type followed by ST171 and ST145, with NDM-1 and NDM-5 as the main carbapenemase-encoding genes. E. hormaechei subsp. steigerwaltii and E. hormaechei subsp. oharae were the main species, which showed different resistance patterns. Conclusion: Rising detection rate of CREC was observed in a tertiary hospital, which showed heterogeneity in drug resistance patterns, resistance genes, and MLST types. Effective infection prevention and control measures should be taken to reduce the spread of CREC. } }

Delicious

Connotea

Analyses for Study 28058

Citation title: "Carbapenem-resistant Enterobacter cloacae complex in a tertiary Hospital in Northeast China, 2010?2019".

Study name: "Carbapenem-resistant Enterobacter cloacae complex in a tertiary Hospital in Northeast China, 2010?2019".

This study is part of submission 28058 (Status: Published).

Analyses

Analysis 1

Analysis details

Name

Input data

1 Input object(s)

Analysis step

Bayesian trees of scale insect species based on combined COI and 28S data --

Step details

Name

Software used

Name
Version
URL
Algorithm
Commands
begin mrbayes; set autoclose=yes nowarn=yes; log start filename=CERO_COI.log; charset 28S=1-350; charset COI=351-857; partition by_gene = 2:28S, COI; set partition = by_gene; lset applyto =(1) nst=2 rates=gamma; lset applyto =(2) Nucmodel=codon code=metmt nst=2 rates=propinv; unlink shape=(all) pinvar=(all) statefreq=(all) revmat=(all); link brlens=(all); link topology=(all); prset applyto=(1) statefreqpr=Dirichlet(1.0,1.0,1.0,1.0) tratiopr=Beta(1.0,1.0) shapepr=Uniform(0.1,50.0); prset applyto=(all) ratepr=variable; showmodel; outgroup Acanthococcus sp S3 523a; mcmc nruns=2 nchains=4 ngen=10000000 samplefreq=100 printfreq=100; sump; sumt; end;

Output data

1 Output object(s)

Analysis 2

Analysis details

Name

Input data

1 Input object(s)

Analysis step

Bayesian trees of Anicetus species based on combined COI and 28S data --

Step details

Name

Software used

Name
Version
URL
Algorithm
Commands
begin mrbayes; set autoclose=yes nowarn=yes; log start filename=CERO_COI.log; charset 28S=1-609; charset COI=610-1200; partition by_gene = 2:28S, COI; set partition = by_gene; lset applyto =(1) nst=6 rates=gamma; lset applyto =(2) Nucmodel=codon code=metmt nst=2 rates=invgamma; unlink shape=(all) pinvar=(all) statefreq=(all) revmat=(all); link brlens=(all); link topology=(all); prset applyto=(1) revmatpr=Dirichlet(1.0,1.0,1.0,1.0,1.0,1.0) statefreqpr=Dirichlet(1.0,1.0,1.0,1.0) shapepr=Uniform(0.1,50.0); prset applyto=(all) ratepr=variable; showmodel; outgroup Eusemion sp2 E3 193b; mcmc nruns=2 nchains=4 ngen=20000000 samplefreq=100 printfreq=100; sump; sumt; end;

Output data