Waskito Langgeng Agung, Rezkitha Yudith Annisa Ayu, Vilaichone Ratha-Korn, Wibawa I Dewa Nyoman, Mustika Syifa, Sugihartono Titong, Miftahussurur Muhammad
Department of Internal Medicine, Faculty of Medicine, Universitas Airlangga, Surabaya 60132, Indonesia.
Helicobacter pylori and Microbiota Study Group, Institute of Tropical Diseases, Universitas Airlangga, Surabaya 60115, Indonesia.
Antibiotics (Basel). 2022 May 13;11(5):654. doi: 10.3390/antibiotics11050654.
The burden of bacterial resistance to antibiotics affects several key sectors in the world, including healthcare, the government, and the economic sector. Resistant bacterial infection is associated with prolonged hospital stays, direct costs, and costs due to loss of productivity, which will cause policy makers to adjust their policies. Current widely performed procedures for the identification of antibiotic-resistant bacteria rely on culture-based methodology. However, some resistance determinants, such as free-floating DNA of resistance genes, are outside the bacterial genome, which could be potentially transferred under antibiotic exposure. Metagenomic and metatranscriptomic approaches to profiling antibiotic resistance offer several advantages to overcome the limitations of the culture-based approach. These methodologies enhance the probability of detecting resistance determinant genes inside and outside the bacterial genome and novel resistance genes yet pose inherent challenges in availability, validity, expert usability, and cost. Despite these challenges, such molecular-based and bioinformatics technologies offer an exquisite advantage in improving clinicians' diagnoses and the management of resistant infectious diseases in humans. This review provides a comprehensive overview of next-generation sequencing technologies, metagenomics, and metatranscriptomics in assessing antimicrobial resistance profiles.
细菌对抗生素的耐药负担影响着世界上几个关键领域,包括医疗保健、政府和经济部门。耐药细菌感染与住院时间延长、直接成本以及因生产力损失导致的成本相关,这将促使政策制定者调整其政策。目前广泛采用的鉴定耐抗生素细菌的方法依赖于基于培养的方法。然而,一些耐药决定因素,如耐药基因的游离DNA,位于细菌基因组之外,在抗生素暴露下可能会发生转移。宏基因组学和宏转录组学分析抗生素耐药性的方法具有若干优势,可克服基于培养方法的局限性。这些方法提高了检测细菌基因组内外耐药决定因素基因和新耐药基因的可能性,但在可用性、有效性、专家易用性和成本方面存在固有挑战。尽管存在这些挑战,但此类基于分子的生物信息学技术在改善临床医生对人类耐药传染病的诊断和管理方面具有显著优势。本综述全面概述了下一代测序技术、宏基因组学和宏转录组学在评估抗菌药物耐药谱方面的应用。