Journal
ANTIBIOTICS-BASEL
Volume 11, Issue 5, Pages -Publisher
MDPI
DOI: 10.3390/antibiotics11050654
Keywords
metagenomic; metatranscriptomic; antibiotics resistance; bioinformatics; clinical practice
Categories
Funding
- Riset Mandat Top Tier 2021 Grant from Universitas Airlangga [771/UN3.15/PT/2021]
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Bacterial resistance to antibiotics has significant impacts on healthcare, government, and the economy. Culture-based methods for identifying resistant bacteria have limitations, and new approaches such as metagenomics and metatranscriptomics offer advantages in overcoming these limitations and improving diagnostic and management capabilities for resistant infectious diseases.
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.
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