摘要

       多年来，我们无法在实验室培养大多数微生物，特别是细菌，这限制了我们对所有生物和非生物环境中细菌元抗性组的看法和理解。因此，抗生素抗性基因（ARGS）和抗生素生产者的储存库、来源和分布，以及人类活动和抗生素对ARGs选择和传播的影响都没有得到很好的理解。随着宏基因组学和宏转录组学领域的进步，许多迄今为止鲜为人知的概念变得越来越清晰。此外，从人类微生物群中发现的抗生素，如卢丁宁和乳青霉素，加强了这些新领域的重要性。宏基因组学和宏转录组学正在成为重要的临床诊断工具，用于筛选和检测病原体和 ARGs，评估抗生素、其他外源性物质和人类活动对环境的影响，以更短的周转时间和降低成本来表征微生物组和环境抵抗组，以及发现抗生素生产者。然而，准确分箱、倾斜的 ARG 数据库、检测较少丰度的 ARG 和等位基因变体以及有效的移动组表征等挑战仍然存在。在长读长、分阶段和单细胞测序、菌株解析分箱、染色体构象捕获、DNA 甲基化分箱和深度学习生物信息学方法方面的持续努力为从宏基因组重建完整的菌株级基因组和移动组提供了广阔的前景。

       Our inability to cultivate most microorganisms, specifically bacteria, in the laboratory has for many years restricted our view and understanding of the bacterial meta-resistome in all living and nonliving environments. As a result, reservoirs, sources and distribution of antibiotic resistance genes (ARGS) and antibiotic-producers, as well as the effects of human activity and antibiotics on the selection and dissemination of ARGs were not well comprehended. With the advances made in the fields of metagenomics and metatranscriptomics, many of the hitherto little-understood concepts are becoming clearer. Further, the discovery of antibiotics such as lugdinin and lactocillin from the human microbiota, buttressed the importance of these new fields. Metagenomics and metatranscriptomics are becoming important clinical diagnostic tools for screening and detecting pathogens and ARGs, assessing the effects of antibiotics, other xenobiotics and human activity on the environment, characterizing the microbiome and the environmental resistome with lesser turnaround time and decreasing cost, as well as discovering antibiotic-producers. However, challenges with accurate binning, skewed ARGs databases, detection of less abundant and allelic variants of ARGs and efficient mobilome characterization remain. Ongoing efforts in long-read, phased- and single-cell sequencing, strain-resolved binning, chromosomal-conformation capture, DNA-methylation binning and deep-learning bioinformatic approaches offer promising prospects in reconstructing complete strain-level genomes and mobilomes from metagenomes.

https://sfamjournals.onlinelibrary.wiley.com/doi/abs/10.1111/1758-2229.12735