Department of Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China.
Key Laboratory of Bio-Resources and Eco-Environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, Sichuan 610065, China.
Chin Med J (Engl). 2024 Sep 5;137(17):2092-2098. doi: 10.1097/CM9.0000000000003182. Epub 2024 Jun 27.
Accurately and efficiently extracting microbial genomic sequences from complex metagenomic data is crucial for advancing our understanding in fields such as clinical diagnostics, environmental microbiology, and biodiversity. As sequencing technologies evolve, this task becomes increasingly challenging due to the intricate nature of microbial communities and the vast amount of data generated. Especially in intensive care units (ICUs), infections caused by antibiotic-resistant bacteria are increasingly prevalent among critically ill patients, significantly impacting the effectiveness of treatments and patient prognoses. Therefore, obtaining timely and accurate information about infectious pathogens is of paramount importance for the treatment of patients with severe infections, which enables precisely targeted anti-infection therapies, and a tool that can extract microbial genomic sequences from metagenomic dataset would be of help.
We developed MetaGeneMiner to help with retrieving specific microbial genomic sequences from metagenomes using a k-mer-based approach. It facilitates the rapid and accurate identification and analysis of pathogens. The tool is designed to be user-friendly and efficient on standard personal computers, allowing its use across a wide variety of settings. We validated MetaGeneMiner using eight metagenomic samples from ICU patients, which demonstrated its efficiency and accuracy.
The software extensively retrieved coding sequences of pathogens Acinetobacter baumannii and herpes simplex virus type 1 and detected a variety of resistance genes. All documentation and source codes for MetaGeneMiner are freely available at https://gitee.com/sculab/MetaGeneMiner .
It is foreseeable that MetaGeneMiner possesses the potential for applications across multiple domains, including clinical diagnostics, environmental microbiology, gut microbiome research, as well as biodiversity and conservation biology. Particularly in ICU settings, MetaGeneMiner introduces a novel, rapid, and precise method for diagnosing and treating infections in critically ill patients. This tool is capable of efficiently identifying infectious pathogens, guiding personalized and precise treatment strategies, and monitoring the development of antibiotic resistance, significantly impacting the diagnosis and treatment of severe infections.
准确高效地从复杂的宏基因组数据中提取微生物基因组序列对于推进临床诊断、环境微生物学和生物多样性等领域的研究至关重要。随着测序技术的发展，由于微生物群落的复杂性和生成的数据量庞大，这项任务变得越来越具有挑战性。特别是在重症监护病房（ICU），抗生素耐药菌引起的感染在重症患者中越来越普遍，严重影响了治疗效果和患者预后。因此，及时准确地获取有关感染病原体的信息对于严重感染患者的治疗至关重要，这有助于实施精准靶向抗感染治疗。能够从宏基因组数据集中提取微生物基因组序列的工具将很有帮助。
我们开发了 MetaGeneMiner 来帮助使用基于 k-mer 的方法从宏基因组中检索特定的微生物基因组序列。它促进了病原体的快速准确识别和分析。该工具旨在在标准个人计算机上实现用户友好和高效，允许在各种环境中使用。我们使用来自 ICU 患者的八个宏基因组样本验证了 MetaGeneMiner，证明了它的效率和准确性。
该软件广泛检索了鲍曼不动杆菌和单纯疱疹病毒 1 的编码序列，并检测到多种耐药基因。MetaGeneMiner 的所有文档和源代码均可在 https://gitee.com/sculab/MetaGeneMiner 上免费获取。
可以预见，MetaGeneMiner 具有在多个领域应用的潜力，包括临床诊断、环境微生物学、肠道微生物组研究以及生物多样性和保护生物学。特别是在 ICU 环境中，MetaGeneMiner 为重症患者的感染提供了一种新颖、快速和精确的诊断和治疗方法。该工具能够高效识别感染病原体，指导个性化和精确的治疗策略，并监测抗生素耐药性的发展，对严重感染的诊断和治疗产生重大影响。
