利用 sylph 快速绘制物种级元基因组图谱并估算遏制率

IF 33.1 1区 生物学 Q1 BIOTECHNOLOGY & APPLIED MICROBIOLOGY Nature biotechnology Pub Date : 2024-10-08 DOI:10.1038/s41587-024-02412-y
Jim Shaw, Yun William Yu
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引用次数: 0

摘要

根据数据库分析元基因组可以检测和量化微生物,即使是在无法组装的低丰度情况下。我们介绍的 sylph 是一种物种级的元基因组剖析器,它通过零膨胀泊松 k-mer 统计估计基因组到元基因组包含的平均核苷酸同一性(ANI),从而实现基于 ANI 的类群检测。在元基因组解读关键评估 II(CAMI2)海洋数据集上,sylph 是所测试的七种剖析方法中最准确的一种。与Kraken2相比,sylph在多样本剖析方面花费的中央处理单元时间减少了10倍,使用的内存减少了30倍。Sylph的ANI估计值提供了与丰度正交的信号,从而可以针对289,232个基因组进行基于ANI的帕金森病(PD)全基因组关联研究,同时在菌株水平上确认已知的丁酸盐-PD关联。Sylph 只用了 1 分钟和 16 GB 的随机存取内存,就对照 85,205 个原核生物基因组和 2,917,516 个病毒基因组分析了元基因组,与 RefSeq 相比,在人类肠道中检测到的病毒序列多出 30 倍。Sylph 提供精确、高效的剖析,即使对低覆盖率基因组也能进行精确的包含 ANI 估算。
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Rapid species-level metagenome profiling and containment estimation with sylph

Profiling metagenomes against databases allows for the detection and quantification of microorganisms, even at low abundances where assembly is not possible. We introduce sylph, a species-level metagenome profiler that estimates genome-to-metagenome containment average nucleotide identity (ANI) through zero-inflated Poisson k-mer statistics, enabling ANI-based taxa detection. On the Critical Assessment of Metagenome Interpretation II (CAMI2) Marine dataset, sylph was the most accurate profiling method of seven tested. For multisample profiling, sylph took >10-fold less central processing unit time compared to Kraken2 and used 30-fold less memory. Sylph’s ANI estimates provided an orthogonal signal to abundance, allowing for an ANI-based metagenome-wide association study for Parkinson disease (PD) against 289,232 genomes while confirming known butyrate–PD associations at the strain level. Sylph took <1 min and 16 GB of random-access memory to profile metagenomes against 85,205 prokaryotic and 2,917,516 viral genomes, detecting 30-fold more viral sequences in the human gut compared to RefSeq. Sylph offers precise, efficient profiling with accurate containment ANI estimation even for low-coverage genomes.

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来源期刊
Nature biotechnology
Nature biotechnology 工程技术-生物工程与应用微生物
CiteScore
63.00
自引率
1.70%
发文量
382
审稿时长
3 months
期刊介绍: Nature Biotechnology is a monthly journal that focuses on the science and business of biotechnology. It covers a wide range of topics including technology/methodology advancements in the biological, biomedical, agricultural, and environmental sciences. The journal also explores the commercial, political, ethical, legal, and societal aspects of this research. The journal serves researchers by providing peer-reviewed research papers in the field of biotechnology. It also serves the business community by delivering news about research developments. This approach ensures that both the scientific and business communities are well-informed and able to stay up-to-date on the latest advancements and opportunities in the field. Some key areas of interest in which the journal actively seeks research papers include molecular engineering of nucleic acids and proteins, molecular therapy, large-scale biology, computational biology, regenerative medicine, imaging technology, analytical biotechnology, applied immunology, food and agricultural biotechnology, and environmental biotechnology. In summary, Nature Biotechnology is a comprehensive journal that covers both the scientific and business aspects of biotechnology. It strives to provide researchers with valuable research papers and news while also delivering important scientific advancements to the business community.
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One-step nanoscale expansion microscopy reveals individual protein shapes A circularly permuted CasRx platform for efficient, site-specific RNA editing Rapid species-level metagenome profiling and containment estimation with sylph Author Correction: The cost of drug patent expiration date errors Publisher Correction: Multistate and functional protein design using RoseTTAFold sequence space diffusion
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