Papudeshi Bhavya, Roach Michael J, Mallawaarachchi Vijini, Bouras George, Grigson Susanna R, Giles Sarah K, Harker Clarice M, Hutton Abbey L K, Tarasenko Anita, Inglis Laura K, Vega Alejandro A, Souza Cole, Boling Lance, Hajama Hamza, Cobián Güemes Ana Georgina, Segall Anca M, Dinsdale Elizabeth A, Edwards Robert A
Flinders Accelerator for Microbiome Exploration, College of Science and Engineering, Flinders University, Adelaide, SA, 5042, Australia.
Flinders Health and Medical Research Institute, College of Medicine and Public Health, Flinders University, Adelaide, SA, 5042, Australia.
bioRxiv. 2024 Nov 18:2024.11.18.624194. doi: 10.1101/2024.11.18.624194.
Phage therapy is a viable alternative for treating bacterial infections amidst the escalating threat of antimicrobial resistance. However, the therapeutic success of phage therapy depends on selecting safe and effective phage candidates. While experimental methods focus on isolating phages and determining their lifecycle and host range, comprehensive genomic screening is critical to identify markers that indicate potential risks, such as toxins, antimicrobial resistance, or temperate lifecycle traits. These analyses are often labor-intensive and time-consuming, limiting the rapid deployment of phage in clinical settings.
We developed Sphae, an automated bioinformatics pipeline designed to streamline therapeutic potential of a phage in under ten minutes. Using Snakemake workflow manager, Sphae integrates tools for quality control, assembly, genome assessment, and annotation tailored specifically for phage biology. Sphae automates the detection of key genomic markers, including virulence factors, antimicrobial resistance genes, and lysogeny indicators like integrase, recombinase, and transposase, which could preclude therapeutic use. Benchmarked on 65 phage sequences, 28 phage samples showed therapeutic potential, 8 failed during assembly due to low sequencing depth, 22 samples included prophage or virulent markers, and the remaining 23 samples included multiple phage genomes per sample. This workflow outputs a comprehensive report, enabling rapid assessment of phage safety and suitability for phage therapy under these criteria. Sphae is scalable, portable, facilitating efficient deployment across most high-performance computing (HPC) and cloud platforms, expediting the genomic evaluation process.
Sphae is source code and freely available at https://github.com/linsalrob/sphae, with installation supported on Conda, PyPi, Docker containers.
在抗菌药物耐药性威胁不断升级的情况下，噬菌体疗法是治疗细菌感染的一种可行替代方案。然而，噬菌体疗法的治疗成功取决于选择安全有效的噬菌体候选物。虽然实验方法侧重于分离噬菌体并确定其生命周期和宿主范围，但全面的基因组筛选对于识别指示潜在风险的标记物至关重要，例如毒素、抗菌药物耐药性或温和生命周期特征。这些分析通常 labor-intensive 且耗时，限制了噬菌体在临床环境中的快速应用。
我们开发了 Sphae，这是一个自动化的生物信息学管道，旨在在十分钟内简化噬菌体的治疗潜力评估。使用 Snakemake 工作流管理器，Sphae 集成了专门针对噬菌体生物学的质量控制、组装、基因组评估和注释工具。Sphae 自动检测关键的基因组标记物，包括毒力因子、抗菌药物耐药基因以及整合酶、重组酶和转座酶等溶原性指标，这些可能会妨碍治疗用途。以 65 个噬菌体序列为基准，28 个噬菌体样本显示出治疗潜力，8 个由于测序深度低在组装过程中失败，22 个样本包含前噬菌体或毒性标记物，其余 23 个样本每个样本包含多个噬菌体基因组。此工作流程输出一份综合报告，能够根据这些标准快速评估噬菌体的安全性和适用于噬菌体疗法的程度。Sphae 具有可扩展性、便携性，便于在大多数高性能计算 (HPC) 和云平台上高效部署，加快基因组评估过程。
Sphae 的源代码可在 https://github.com/linsalrob/sphae 上免费获取，支持通过 Conda、PyPi、Docker 容器进行安装。
