Metagenomic-based surveillance systems for antibiotic resistance in non-clinical settings

被引:13
|
作者
Pillay, Stephanie [1 ]
Calderon-Franco, David [2 ]
Urhan, Aysun [1 ,3 ]
Abeel, Thomas [1 ,3 ]
机构
[1] Delft Univ Technol, Delft Bioinformat Lab, Delft, Netherlands
[2] Delft Univ Technol, Dept Biotechnol, Delft, Netherlands
[3] Broad Inst MIT & Harvard, Infect Dis & Microbiome Program, Cambridge, MA 02142 USA
基金
新加坡国家研究基金会;
关键词
antibiotic resistance; metagenomics; bioinformatics; microbiomes; gene transfer; WASTE-WATER TREATMENT; MOBILE GENETIC ELEMENTS; ANTIMICROBIAL RESISTANCE; TREATMENT PLANTS; FOOD-ANIMALS; MICROBIOLOGICAL CONTAMINATION; BINNING ALGORITHM; READ ALIGNMENT; FRESH PRODUCE; SINGLE-CELL;
D O I
10.3389/fmicb.2022.1066995
中图分类号
Q93 [微生物学];
学科分类号
071005 ; 100705 ;
摘要
The success of antibiotics as a therapeutic agent has led to their ineffectiveness. The continuous use and misuse in clinical and non-clinical areas have led to the emergence and spread of antibiotic-resistant bacteria and its genetic determinants. This is a multi-dimensional problem that has now become a global health crisis. Antibiotic resistance research has primarily focused on the clinical healthcare sectors while overlooking the non-clinical sectors. The increasing antibiotic usage in the environment - including animals, plants, soil, and water - are drivers of antibiotic resistance and function as a transmission route for antibiotic resistant pathogens and is a source for resistance genes. These natural compartments are interconnected with each other and humans, allowing the spread of antibiotic resistance via horizontal gene transfer between commensal and pathogenic bacteria. Identifying and understanding genetic exchange within and between natural compartments can provide insight into the transmission, dissemination, and emergence mechanisms. The development of high-throughput DNA sequencing technologies has made antibiotic resistance research more accessible and feasible. In particular, the combination of metagenomics and powerful bioinformatic tools and platforms have facilitated the identification of microbial communities and has allowed access to genomic data by bypassing the need for isolating and culturing microorganisms. This review aimed to reflect on the different sequencing techniques, metagenomic approaches, and bioinformatics tools and pipelines with their respective advantages and limitations for antibiotic resistance research. These approaches can provide insight into resistance mechanisms, the microbial population, emerging pathogens, resistance genes, and their dissemination. This information can influence policies, develop preventative measures and alleviate the burden caused by antibiotic resistance.
引用
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页数:21
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