Antibiotic resistance represents a formidable challenge to global health, driven extensively by the selective pressure that enables bacteria to acquire antibiotic resistance genes (ARGs). In response to this pressing issue, CD Genomics offers advanced, genome-focused analysis services aimed at searching for antibiotic resistance genes. These rigorous services not only pinpoint existing ARGs but also play a pivotal role in uncovering novel ARGs, and in decoding the intricate molecular mechanisms that facilitate the transfer of these genes.
The relentless rise of antibiotic resistance (AR) poses a profound and growing threat to global public health, driven by the adaptive evolution of bacterial pathogens under the selective pressures of antimicrobial exposure. Understanding the molecular underpinnings of resistance is paramount, necessitating the accurate identification and thorough characterization of ARGs. These genetic determinants are pivotal in the ability of bacteria to withstand and proliferate in environments saturated with antibiotics.
ARGs are critical genetic components that can be inherited vertically through clonal expansion or acquired horizontally via mechanisms such as conjugation, transformation, or transduction. The rapid and widespread propagation of ARGs, often mediated by mobile genetic elements including plasmids and transposons, has exacerbated the global challenge of antibiotic resistance. This dissemination has rendered numerous conventional antimicrobial therapies increasingly ineffective, necessitating urgent and sophisticated approaches to detection and management.
At CD Genomics, we provide an extensive array of ARG screening services, leveraging state-of-the-art technologies such as quantitative PCR (qPCR) and next-generation sequencing (NGS), including techniques like metagenomic sequencing and whole genome sequencing. These methodologies facilitate the precise detection and in-depth characterization of ARGs, delivering critical insights that are integral to both academic research and clinical application, and ultimately, to the strategic control of antibiotic resistance.
The detection of ARGs employs various methodologies that enhance the understanding and management of antibiotic resistance. Key techniques include:
1. Traditional Culture-Based Methods: These methods, such as antimicrobial susceptibility testing (AST), involve culturing bacteria to assess resistance. While informative, they require specialized labs and are limited to culturable organisms.
2. Molecular Techniques:
3. Mass Spectrometry: Techniques such as MALDI-TOF-MS can identify bacterial species and their resistance profiles based on protein patterns, though they require accurate databases and pure cultures.
4. Emerging Techniques: Innovations like metagenomics, long-read sequencing, and WGS, along with mscRNA-seq technologies, enhance the detection of ARGs in complex samples, facilitating the study of resistance mechanisms in diverse microbial communities.
The applications of antibiotic resistance genes screening include, but are not limited to, the following areas:
The WGS detection method is as follows:
We have a standard bioinformatics pipeline for antibiotic resistance genes screening, however, we can also customize the bioinformatics pipeline to your needs.
Pipeline | Details |
---|---|
Sequence alignment | Raw data filtering and trimming, sequencing coverage, sequence alignment, and genome assembly |
Genome annotation | Open reading frames (ORFs) annotation and comparative gene clusters analysis using tools like RAST |
ARGs detection | Reveal distribution and localization of ARGs, discover novel ARGs; visualization of ARGs |
Comparative genomics | Reveal molecular mechanisms of the evolution of resistant strains |
Note: The above content includes only a portion of the bioinformatics analysis. For more information or to customize the analysis, please contact us directly.
Note:
Partial results of our Antibiotic Resistance Genes Screening Sequencing service are shown below:
Impact of the surrounding environment on antibiotic resistance genes carried by microplastics in mangroves
Journal: Science of the Total Environment
Impact factor: 9.8
Published: 1 September 2022
Background
Plastic waste contributes to environmental pollution by degrading into microplastics (MPs) that can absorb harmful pollutants and harbor antibiotic-resistant bacteria. The rising prevalence of ARGs poses a significant public health threat. This study investigates the distribution of ARGs on MPs in Zhanjiang's mangroves using real-time quantitative PCR (qRT-PCR) to assess environmental influences and potential risks to food safety and human health.
Materials & Methods
Sample preparation:
Method:
Data Analysis
Results
Types of Microplastics (MPs) Influence ARG Abundance: Different MPs in mangroves show varying levels of ARGs abundance based on surrounding environments, with PP and PE MPs generally carrying more ARGs due to their large surface area.
Fig 1. Spatial distribution of ARGs on MPs in different surrounding environments of mangroves.
Enrichment Factors of ARGs: The abundance of ARGs on MPs often surpasses that in sediments, particularly for PET MPs in GQ mangroves, indicating a higher risk of antibiotic resistance gene transfer to bacteria associated with humans.
Fig 2. Distribution characteristics of ARGs on the surfaces of five different MPs.
Correlation Analysis of ARGs, MGEs, and Microbial Communities: Spearman correlation analysis reveals significant relationships between ARGs and mobile genetic elements (MGEs) in different mangrove regions, with GH mangroves showing the strongest association, suggesting a higher risk of horizontal gene transfer of ARGs.
Conclusions
This study reveals that ARGs are most abundant on MPs in GH mangroves, particularly on PP, PS, and PET. MPs can transport ARGs, with PET showing enrichment for nine genes. Pathogenic bacteria on MPs pose risks to food safety and health. GH mangroves also have the highest potential for horizontal gene transfer of multidrug-resistant ARGs. Controlling PP and PE waste and reducing their use are recommended to mitigate these risks.
References
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