摘要
出身背景
宏基因组数据可用于分析微生物群中的高重要性基因。然而，目前的宏基因组工作流程产生的数据灵敏度低，无法准确重建部分或全部基因组，尤其是低丰度的基因组。这些限制排除了共定位分析，即表征宏基因组样本中基因和功能的基因组背景。基因组背景对于通过可移动遗传元件（MGE）进行水平基因转移（HGT）的相关功能尤其重要，例如抗微生物耐药性（AMR）。为了克服宏基因组学目前的局限性，我们提出了一种从宏基因组DNA中全面准确地重建抗微生物耐药性基因（ARGs）和MGE的方法，称为靶点富集长读测序（TELSeq）。
后果
使用不同样本类型的技术复制，我们将TELSeq的性能与非富集PacBio和短读Illumina测序的性能进行了比较。在不同的宏基因组中，TELSeq实现了比其他方法高得多的ARG回收率（>1000倍）和灵敏度，揭示了包括许多低丰度ARG的广泛耐药谱，包括一些具有公共卫生重要性的ARG。利用TELSeq产生的长读数，我们鉴定了低丰度ARG侧翼的许多MGE和货物基因，表明这些ARG可以通过HGT在细菌分类群中转移。
结论
TELSeq可以对微生物耐药性的基因组背景提供细致的了解，因此在公共、动物和人类健康以及AMR的环境监测和监测中具有广泛的应用。因此，这项技术代表了微生物组研究和应用的根本进步。
Abstract
Background
Metagenomic data can be used to profile high-importance genes within microbiomes. However, current metagenomic workflows produce data that suffer from low sensitivity and an inability to accurately reconstruct partial or full genomes, particularly those in low abundance. These limitations preclude colocalization analysis, i.e., characterizing the genomic context of genes and functions within a metagenomic sample. Genomic context is especially crucial for functions associated with horizontal gene transfer (HGT) via mobile genetic elements (MGEs), for example antimicrobial resistance (AMR). To overcome this current limitation of metagenomics, we present a method for comprehensive and accurate reconstruction of antimicrobial resistance genes (ARGs) and MGEs from metagenomic DNA, termed target-enriched long-read sequencing (TELSeq).

Results
Using technical replicates of diverse sample types, we compared TELSeq performance to that of non-enriched PacBio and short-read Illumina sequencing. TELSeq achieved much higher ARG recovery (>1,000-fold) and sensitivity than the other methods across diverse metagenomes, revealing an extensive resistome profile comprising many low-abundance ARGs, including some with public health importance. Using the long reads generated by TELSeq, we identified numerous MGEs and cargo genes flanking the low-abundance ARGs, indicating that these ARGs could be transferred across bacterial taxa via HGT.

Conclusions
TELSeq can provide a nuanced view of the genomic context of microbial resistomes and thus has wide-ranging applications in public, animal, and human health, as well as environmental surveillance and monitoring of AMR. Thus, this technique represents a fundamental advancement for microbiome research and application.

https://link.springer.com/article/10.1186/s40168-022-01368-y