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PCR-based Microbial Antibiotic Resistance Gene Analysis


Overview

Antibiotic resistance is a major public health threat, increasing mortality and straining healthcare systems. The identification of β-lactamase genes is crucial, as these enzymes impact the effectiveness of widely used antibiotics. PCR and its derivatives are the gold standard for ARG detection, applied in over 90% of ARG studies for pre-amplification, detection, and validation, playing a key role in resistance gene research.

Our Advantages:
  • Detailed Gene Targeting: Accurately identifies β-lactamase genes, including AmpC β-lactamases, for precise resistance profiling.
  • Phenotypic Supplement: Enhances traditional phenotypic methods for detecting multidrug-resistant microbes.
  • Efficient Surveillance: Supports large-scale surveillance and epidemiological monitoring with high-throughput PCR solutions.
  • High Sensitivity: PCR-based methods provide precise detection of low-abundance ARGs in diverse microbial samples.
  • Rapid Turnaround: Provides fast and efficient results, ideal for large-scale research studies.
  • Comprehensive Profiling: Multiplex PCR detects up to 50 ARGs simultaneously, ensuring broad resistance gene analysis.

Introduction to Antibiotic Resistance Gene Detection Methods

The detection of antibiotic resistance genes (ARGs) is paramount for the surveillance and understanding of the propagation of antibiotic-resistant bacteria. A diverse array of methodologies exists to identify and quantify these genes, each with specific strengths and applications. This article provides an overview of the primary detection methods utilized in the field.

1. Polymerase Chain Reaction (PCR)

PCR remains a foundational technique for the amplification of targeted DNA sequences and is central to ARG detection. The principal PCR-based methods include:

  • Conventional PCR: This method amplifies target ARGs, with detection typically achieved via gel electrophoresis. While effective for confirming the presence of ARGs, conventional PCR does not yield quantitative data.
  • Real-Time Quantitative PCR (qPCR): Utilizing fluorescent dyes or probes, qPCR tracks the amplification process in real-time, thus providing both qualitative and quantitative data. Its high sensitivity and accuracy render it the gold standard in ARG detection.
  • Multiplex PCR: This technique allows for the concurrent detection of multiple ARGs within a single reaction by employing multiple primer sets, thereby enabling comprehensive resistance profiling.
  • High-Throughput Quantitative PCR (HT-qPCR): This advanced method facilitates the simultaneous analysis of numerous samples and ARGs using multiple primer pairs, optimizing efficiency and throughput in large-scale studies.

2. Gene Sequencing

Gene sequencing, encompassing methods such as Sanger sequencing and Next-Generation Sequencing (NGS), offers exhaustive identification and analysis of ARGs through the determination of DNA nucleotide sequences. NGS, in particular, is notable for its capability to detect a wide array of both known and novel ARGs. Metagenomic sequencing, a subset of NGS, further enhances this by enabling the identification of ARGs directly from environmental samples, thus providing a comprehensive overview of resistance genes present in complex microbial communities.

3. Isothermal Amplification

Isothermal amplification techniques, including Loop-Mediated Isothermal Amplification (LAMP) and Recombinase Polymerase Amplification (RPA), enable DNA amplification at a constant temperature. These methods provide rapid and straightforward alternatives to traditional PCR.

4. Fluorescence-Based Techniques

Fluorescence-based techniques involve the use of fluorescent dyes or probes for the detection and quantification of ARGs. Techniques such as Fluorescence In Situ Hybridization (FISH) and fluorescent PCR fall into this category and are noted for their sensitive detection capabilities.

How does PCR detect antibiotic resistance

Principles of PCR: PCR constitutes a pivotal molecular biology technique designed for the amplification of specific DNA sequences. This technique comprises a series of repeated thermal cycles involving denaturation, annealing, and extension phases. Within the framework of antibiotic resistance gene (ARG) detection, PCR specifically targets genes that are known to confer resistance to antibiotics. By amplifying these resistance-associated genes, PCR facilitates not only their identification but also their quantification within a given biological sample.

Multiplex PCR is a sophisticated adaptation of conventional PCR that permits the concurrent detection of multiple ARGs in a single reaction. This technique employs an array of primers, each specific to distinct ARGs, thereby enabling the simultaneous amplification of several resistance genes. The resultant PCR products can be distinguished either by their respective sizes or through the use of different fluorescent dyes in real-time PCR (RT-PCR) assays. This multiplex approach is especially advantageous for comprehensive resistance profiling and is highly suited to high-throughput screening applications.

Service Specifications

Introduction to Our PCR-based Microbial Antibiotic Resistance Gene Analysis Services

At CD Genomics, we offer cutting-edge PCR-based services for the detection and analysis of ARGs. Our approach leverages the gold standard in gene amplification technology—PCR and its derivatives—to deliver precise and reliable results. This includes conventional PCR for initial screening, Real-Time Quantitative PCR (qPCR) for detailed quantitative analysis, and High-Throughput Quantitative PCR (HT-qPCR) for extensive sample processing. By integrating these advanced techniques, we provide comprehensive insights into ARGs with high accuracy and efficiency, supporting robust environmental and microbial studies.

PCR-based Microbial Antibiotic Resistance Gene Analysis Workflow

The Workflow of PCR-based Microbial Antibiotic Resistance Gene Analysis.

Technical Parameters

  • qPCR
  • Multiplex PCR
  • HT-qPCR

Note: The above content includes only a portion of the bioinformatics analysis. For more information or to customize the analysis, please contact us directly.

Bioinformatics Analysis

Our bioinformatics analysis services are flexible to your specific projects.

ANALYSIS CONTENTS DETAILS
Multiplex Real-time PCR Identification of β-lactamase genes
β-Lactamase Identifies 9 distinct families of carbapenemases, ESBLs and plasmid-mediated ampC genes
ampC Aims 6 plasmid-mediated genes of ampC resistance and can distinguish resistance of plasmid-mediated ampC β-lactamase from chromosomal resistance
Sequence alignment Filtering and trimming of raw data, coverage of sequencing, sequence alignment, and genome assembly
Genome annotation Annotation of open reading frames (ORFs) and analysis of comparative gene clusters using equipment such as RAST
ARGs detection Disclose ARG distribution and localization, discover new ARGs; visualize ARGs
Comparative genomics Uncover the molecular processes of resistant strain evolution

Sample Requirement

Note: If you wish to obtain more accurate and detailed information regarding sample requirements, please feel free to contact us directly.

Deliverables

  • Raw data
  • Detected ARGs
  • Quantitative results
  • Resistance profile
  • Your designated bioinformatics result report
Demo

Demo

Partial results of our PCR-based antibiotic resistance gene analysis service are shown below:

The PCR-based Microbial Antibiotic Resistance Gene Analysis Results Display.

FAQs

PCR-based Antibiotic Resistance Gene Analysis FAQ

Please feel free to reach out if you have any further inquiries or require additional information.

Case Study

Case Study

Customer Case

Network complexity of bacterial community driving antibiotic resistome in the microbiome of earthworm guts under different land use patterns
Journal: Journal of Hazardous Materials
Impact factor: 12.2
Published: 5 January 2024

Find out more

Backgrounds

Recent studies on antibiotic resistance genes (ARGs) in soil and earthworms highlight higher ARG levels in soil compared to earthworms. Different land uses impact ARG abundance and patterns, with pH negatively affecting ARG profiles and bacterial network complexity positively influencing them. This research provides new insights into ARG distribution across various land use types.

Methods

Sample preparation:

  • Soil
  • Earthworm
  • DNA extraction

Method:

Data Analysis:

  • Correlation analysis
  • RAD analysis
  • Network analysis

Results

Variation in ARGs Across Land Use Types:

ARG abundance and number vary by land use, with the highest levels found in farmland samples. Earthworms exhibit lower ARG levels compared to soil, with different land uses affecting ARG profiles significantly. Farmland shows the highest ARG diversity and abundance, likely due to frequent use of antibiotic-treated animal manure.

Figure 1. The relative abundance (a) and quantity (c) of ARGs found in the microbiomes of soil and earthworms across various land use types. (Luo F et al., 2024)Figure 1. Relative abundance (a) and quantity (c) of ARGs in soil and earthworm microbiomes across different land use types.

Shared and Unique ARGs Among Land Use Types:

ARGs vary widely by land use, with specific ARGs showing high uniqueness in certain environments, particularly in farmland. Earthworms have unique ARGs distinct from soil, but also share many ARGs with soil samples. Multidrug-resistant ARGs are most common across all land use types, indicating widespread resistance patterns, with earthworms having fewer shared ARGs, suggesting their role in reducing ARG spread.

Figure 2. (a) Profiles of ARGs distribution in each habitat type; (b) Venn diagrams illustrating the number of ARGs shared between different earthworm and soil samples; (c) Bipartite network analysis representing the shared ARGs among different land use types in the microbiomes of soil and earthworms. (Luo F et al., 2024)Figure 2. (a) Distribution of ARGs profiles in each habitat type; (b) Venn diagrams showing the number of shared ARGs between different earthworm and soil samples; (c) Bipartite network analysis depicting shared ARGs among different land use types in soil and earthworm microbiomes.

Conclusions

In this study, ARGs were more abundant in soil than in earthworm guts, with earthworms showing a more varied ARG profile. Land use and factors like pH affect ARG abundance and patterns. The findings offer insights into ARG networks in soil and earthworms.

References

  1. Donà V, Kasraian S, Lupo A, et al. Multiplex real-time PCR assay with high-resolution melting analysis for characterization of antimicrobial resistance in Neisseria gonorrhoeae. Journal of clinical microbiology. 2016, 54(8).
  2. Sundsfjord A, Simonsen GS, HALDORSEN BC, et al. Genetic methods for detection of antimicrobial resistance. Apmis. 2004.
  3. Luo F, Zhao Y, Xu JY, Wang HT, Zhu D. Network complexity of bacterial community driving antibiotic resistome in the microbiome of earthworm guts under different land use patterns. Journal of Hazardous Materials. 2024, 461:132732.
* For Research Use Only. Not for use in diagnostic procedures or other clinical purposes.



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