scholarly journals Soil bacteriological pollution in pig farm vicinity: Assessment of bacterial dynamics and detection of antimicrobial resistance gene

2016 ◽  
Vol 10 (38) ◽  
pp. 1625-1636 ◽  
Author(s):  
Shirley-may Matjuda Dikonketso ◽  
Ayobami Aiyegoro Olayinka
Keyword(s):  
Antimicrobial Resistance ◽  
Resistance Gene ◽  
Bacterial Dynamics ◽  
Antimicrobial Resistance Gene ◽  
Pig Farm

Author response for "Faecal microbiota and antimicrobial resistance gene profiles of healthy foals"

2020 ◽  
Author(s):  
Yuhong Liu ◽  
Kirsten E. Bailey ◽  
Michael Dyall‐Smith ◽  
Marc S. Marenda ◽  
Laura Y. Hardefeldt ◽  
...  
Keyword(s):  
Antimicrobial Resistance ◽  
Resistance Gene ◽  
Author Response ◽  
Faecal Microbiota ◽  
Gene Profiles ◽  
Antimicrobial Resistance Gene

scholarly journals Faecal microbiota and antimicrobial resistance gene profiles of healthy foals

2020 ◽  
Author(s):  
Yuhong Liu ◽  
Kirsten E. Bailey ◽  
Michael Dyall‐Smith ◽  
Marc S. Marenda ◽  
Laura Y. Hardefeldt ◽  
...  
Keyword(s):  
Antimicrobial Resistance ◽  
Resistance Gene ◽  
Faecal Microbiota ◽  
Gene Profiles ◽  
Antimicrobial Resistance Gene

Rapid detection and antimicrobial resistance gene profiling of Yersinia pestis using pyrosequencing technology

2012 ◽  
Vol 90 (3) ◽  
pp. 228-234 ◽  
Author(s):  
Kingsley K. Amoako ◽  
Matthew C. Thomas ◽  
Fanliang Kong ◽  
Timothy W. Janzen ◽  
Kristen R. Hahn ◽  
...  
Keyword(s):  
Antimicrobial Resistance ◽  
Yersinia Pestis ◽  
Resistance Gene ◽  
Rapid Detection ◽  
Gene Profiling ◽  
Antimicrobial Resistance Gene ◽  
Pyrosequencing Technology

scholarly journals Antimicrobial resistance gene prevalence in a population of patients with advanced dementia is related to specific pathobionts

2019 ◽  
Author(s):  
Aislinn D. Rowan-Nash ◽  
Rafael Araos ◽  
Erika M.C. D’Agata ◽  
Peter Belenky
Keyword(s):  
Antimicrobial Resistance ◽  
Resistance Gene ◽  
Resistance Genes ◽  
High Frequency ◽  
Multidrug Resistant ◽  
Advanced Dementia ◽  
Dementia Patients ◽  
Antimicrobial Resistance Genes ◽  
Antimicrobial Resistance Gene ◽  
Multidrug Resistant Organisms

ABSTRACTBackgroundThe issue of antimicrobial resistance continues to grow worldwide, and long-term care facilities are significant reservoirs of antimicrobial-resistant organisms, in part due to high frequency of antimicrobial use. Patients with advanced dementia are particularly vulnerable to multidrug-resistant organism acquisition and antimicrobial overuse, which has negative consequences for the gut microbiome and can contribute to the selection and propagation of antimicrobial resistance genes. In this study, we longitudinally examined a group of advanced dementia patients treated with the fluoroquinolone antimicrobial levofloxacin, finding a correlation between abundance of pathogens and antimicrobial resistance genes, which we confirmed in a larger cohort of subjects with advanced dementia.ResultsWe observed significant inter- and intra-subject heterogeneity in the composition of the microbiota of the longitudinal levofloxacin cohort, suggesting temporal instability. Within this dataset, we did not find significant impacts of levofloxacin on the diversity, composition, function, or resistome of the gut microbiota of this population. However, we were able to link the antimicrobial resistance gene burden in a sample with the relative abundance of several pathobionts – particularly Escherichia coli, Proteus mirabilis, and Enterococcus faecalis, as well as less-prevalent species including Providencia stuartii and Staphylococcus haemolyticus. Furthermore, we used metagenomic assembly and binning to demonstrate that these species had higher genomic resistance gene levels than common gut commensals, and we were able to predict antimicrobial resistance gene burden from the relative abundances of these species in a separate, larger cohort from the same population.ConclusionsWe found that the relative abundances of several pathobionts were correlated with and were even predictive of the level of antimicrobial resistance genes in corresponding samples, and that these species carried high levels of resistances genes in their assembled genomes. In order to test this observation, we utilized a larger metagenomics dataset from a similar population and confirmed the association between pathobiont abundance and antimicrobial resistance genes. Given the high frequency with which these species were found at high levels in this population and the underlying vulnerability to infection with multidrug resistant organisms of advanced dementia patients, attention to microbial blooms of these species may be warranted. Additionally, in this study, we were able to utilize genomic assembly from metagenomic data to more definitively associate antimicrobial resistance gene levels with specific assembled species; as this technology continues to develop, assembly could prove to be a valuable method to monitor both specific resistance genes and blooms of multidrug-resistant organisms.

scholarly journals Carbapenem-Resistant Klebsiella pneumoniae Infections among ICU Admission Patients in Central China: Prevalence and Prediction Model

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Yi Li ◽  
Hui Shen ◽  
Cheng Zhu ◽  
Yuetian Yu
Keyword(s):  
Risk Factors ◽  
Antimicrobial Resistance ◽  
Klebsiella Pneumoniae ◽  
Prediction Model ◽  
Resistance Gene ◽  
Characteristic Curve ◽  
Central China ◽  
Icu Admission ◽  
Carbapenem Resistant ◽  
Antimicrobial Resistance Gene

Objective. To investigate the prevalence of infections due to carbapenem-resistant Klebsiella pneumoniae (CRKP) among ICU admission patients in central China and develop a reliable prediction model. Methods. Five hundred and seven consecutive ICU admission patients with Klebsiella pneumoniae (KP) infection were enrolled in this retrospective multicenter case-control study from January 2014 to June 2018. The prevalence and antimicrobial susceptibility pattern were analyzed. Multivariate analysis was performed by logistic regression modeling to determine the risk factors. A prediction model was developed and verified using data from six hospitals in central China. Results. Of the total 507 isolates of KP, 244 (48.1%) strains were carbapenem resistant. The majority of these isolates were from sputum (30.9%) and blood (20.9%) samples. Tigecycline had good activity against CRKP (95.5%). The most common sequence type (ST) of CRKP was ST11 (84.4%), and 98.6% of them had the blaKPC-2 antimicrobial resistance gene. Thirteen variables were identified as independent risk factors for CRKP infection, including KP colonization or infection in the preceding year (OR=3.32, 95% CI 2.01-4.38), CD4/CD8 ratio <1 (OR=2.98, 95% CI 2.02-4.19), and parenteral nutrition ⩾48 h (OR=1.88, 95% CI 1.22-3.04). The model developed to predict CRKP infection was effective, with an area under the receiver-operating characteristic curve of 0.854 (95% CI 0.821-0.884, p<0.001). Conclusions. ST11 carrying the blaKPC-2 antimicrobial resistance gene was the most common type of CRKP among the ICU admission patients in central China. The model demonstrated excellent predictive performance and exhibited good discrimination.

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