美国卡耐基梅隆大学Yun William Yu等合作利用Sylph，进行快速物种水平的宏基因组分析和污染评估。2024年10月8日出版的《自然—生物技术》发表了这项成果。

据介绍，将宏基因组与数据库进行比对，可以检测和定量微生物，即使在无法进行组装的低丰度情况下也能实现。

该课题组人员介绍了sylph，这是一种物种水平的宏基因组分析工具。它通过零膨胀泊松 k-mer 统计来估算基因组与宏基因组之间的平均核苷酸相似性（ANI），从而实现基于 ANI 的分类检测。在CAMI2海洋数据集上，sylph是7种测试中最准确的分析方法。

对于多样本分析，与Kraken2相比，sylph的中央处理单元时间减少了10倍，内存减少了30倍。Sylph的ANI估计提供了丰度的正交信号，允许对289,232个基因组进行基于ANI的帕金森病(PD)宏基因组关联研究，同时在菌株水平上确认已知的丁酸盐-PD关联。

Sylph 在对比 85,205 个原核生物基因组和 2,917,516 个病毒基因组时，仅用了不到 1 分钟和 16 GB 的随机存取内存，在人类肠道中检测到的病毒序列数量是 RefSeq 数据库的 30 倍。Sylph 提供了精确且高效的分析能力，即使对于低覆盖度的基因组，也能准确估算包含的平均核苷酸相似性（ANI）。

附：英文原文

Title: Rapid species-level metagenome profiling and containment estimation with sylph

Author: Shaw, Jim, Yu, Yun William

Issue&Volume: 2024-10-08

Abstract: 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 <1min and 16GB 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.

DOI: 10.1038/s41587-024-02412-y

Source: https://www.nature.com/articles/s41587-024-02412-y