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Review
. 2019 Jan 3;24(1):163.
doi: 10.3390/molecules24010163.

Contributions and Challenges of High Throughput qPCR for Determining Antimicrobial Resistance in the Environment: A Critical Review

Affiliations
Review

Contributions and Challenges of High Throughput qPCR for Determining Antimicrobial Resistance in the Environment: A Critical Review

Hassan Waseem et al. Molecules. .

Abstract

Expansion in whole genome sequencing and subsequent increase in antibiotic resistance targets have paved the way of high throughput qPCR (HT-qPCR) for analyzing hundreds of antimicrobial resistance genes (ARGs) in a single run. A meta-analysis of 51 selected studies is performed to evaluate ARGs abundance trends over the last 7 years. WaferGenTM SmartChip is found to be the most widely used HT-qPCR platform among others for evaluating ARGs. Up till now around 1000 environmental samples (excluding biological replicates) from different parts of the world have been analyzed on HT-qPCR. Calculated detection frequency and normalized ARGs abundance (ARGs/16S rRNA gene) reported in gut microbiome studies have shown a trend of low ARGs as compared to other environmental matrices. Disparities in the HT-qPCR data analysis which are causing difficulties to researchers in precise interpretation of results have been highlighted and a possible way forward for resolving them is also suggested. The potential of other amplification technologies and point of care or field deployable devices for analyzing ARGs have also been discussed in the review. Our review has focused on updated information regarding the role, current status and future perspectives of HT-qPCR in the field of antimicrobial resistance.

Keywords: AMR; ARGs; MGEs; gut microbiome; high throughput qPCR.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
World map showing no. of samples of different environmental matrices analyzed by HT-qPCR over last 7 years in different regions of the world.
Figure 2
Figure 2
Number of publications using different HT-qPCR platforms over last 7 years.
Figure 3
Figure 3
Reaction Volume and High throughput capacity of various HT-qPCR platforms used for ARGs analysis.
Figure 4
Figure 4
Detection Frequency of different environmental matrices from all included studies.
Figure 5
Figure 5
Box and whisker plot depicting the log transformed ARG copies per 16S rRNA gene for different environmental samples, (n) represents no. of studies.
Figure 6
Figure 6
Bar graph showing Ct cut-off values used for the analysis of HT-qPCR data in the included studies.

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