Identification of putative coral pathogens in endangered Caribbean staghorn coral using machine learning,Environmental Microbiology

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Identification of putative coral pathogens in endangered Caribbean staghorn coral using machine learning
Environmental Microbiology ( IF 4.3 ) Pub Date : 2024-09-18 , DOI: 10.1111/1462-2920.16700
Jason D Selwyn _{1,

2} , Brecia A Despard _{1,

2} , Miles V Vollmer _{1,

2} , Emily C Trytten _{1,

2} , Steven V Vollmer _{1,

2}

Affiliation

Coral diseases contribute to the rapid decline in coral reefs worldwide, and yet coral bacterial pathogens have proved difficult to identify because 16S rRNA gene surveys typically identify tens to hundreds of disease‐associate bacteria as putative pathogens. An example is white band disease (WBD), which has killed up to 95% of the now‐endangered Caribbean Acropora corals since 1979, yet the pathogen is still unknown. The 16S rRNA gene surveys have identified hundreds of WBD‐associated bacterial amplicon sequencing variants (ASVs) from at least nine bacterial families with little consensus across studies. We conducted a multi‐year, multi‐site 16S rRNA gene sequencing comparison of 269 healthy and 143 WBD‐infected Acropora cervicornis and used machine learning modelling to accurately predict disease outcomes and identify the top ASVs contributing to disease. Our ensemble ML models accurately predicted disease with greater than 97% accuracy and identified 19 disease‐associated ASVs and five healthy‐associated ASVs that were consistently differentially abundant across sampling periods. Using a tank‐based transmission experiment, we tested whether the 19 disease‐associated ASVs met the assumption of a pathogen and identified two pathogenic candidate ASVs—ASV25 Cysteiniphilum litorale and ASV8 Vibrio sp. to target for future isolation, cultivation, and confirmation of Henle‐Koch's postulate via transmission assays.

中文翻译：

使用机器学习识别濒临灭绝的加勒比鹿角珊瑚中假定的珊瑚病原体

珊瑚疾病导致全球珊瑚礁迅速衰退，但事实证明，珊瑚细菌病原体很难识别，因为 16S rRNA 基因调查通常会将数十到数百种与疾病相关的细菌识别为假定的病原体。一个例子是白带病 (WBD)，自 1979 年以来，该病已导致目前濒临灭绝的加勒比鹿角珊瑚中 95% 死亡，但其病原体仍然未知。 16S rRNA 基因调查已经从至少九个细菌家族中识别出数百个与 WBD 相关的细菌扩增子测序变体 (ASV)，但各研究之间几乎没有达成共识。我们对 269 只健康鹿和 143 只感染 WBD 的鹿角珊瑚进行了多年、多位点 16S rRNA 基因测序比较，并使用机器学习模型准确预测疾病结果并确定导致疾病的主要 ASV。我们的整体 ML 模型以超过 97% 的准确度准确预测了疾病，并识别了 19 种与疾病相关的 ASV 和 5 种与健康相关的 ASV，这些 ASV 在整个采样期间的丰度始终存在差异。通过基于罐的传播实验，我们测试了 19 种与疾病相关的 ASV 是否符合病原体的假设，并确定了两种致病性候选 ASV——ASV25 Cysteiniphilum litorale 和 ASV8 Vibrio sp。以未来通过传播测定进行分离、培养和确认亨利-科赫假设为目标。

更新日期：2024-09-18

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