Antifungal bacteria on woodland salamander skin exhibit high taxonomic diversity and geographic variability

<b>Metadata for each anti-Bd bacteria: </b>(AntiBdBac_meta_final.csv) File contains information for each bacterial isolate identified as anti-Bd. Metadata includes inhibition score, visual observation inhibition score, locality and salamander information, OTU designation, taxonomic assignment, pairwise alignment value to Woodhams et al. (2015) database, and the consensus sequence (also deposited in Genbank).<br><b>Anti-Bd bacterial richness with metadata:</b> (Richness_anti-BdBac.csv) The file includes salamander ID number and all metadata used in the statistical analyses specified in the paper: "To determine if the number of anti-Bd bacteria per salamander was related to host or environmental characteristics, we used a generalized linear mixed-effects model (GLMM) with a binomial distribution in the R package ‘lme4’. We included species and locality as the main explanatory variables, along with additional covariates of host (sex, body condition, cover object) and site (leaf litter depth, soil pH, substrate temperature). As the response variable, we used proportion of anti-Bd bacteria per salamander (i.e., total anti-Bd bacteria divided by total bacteria isolated) to account for variation in the number of isolates cultured per individual."<br><b>Sequence alignment of 119 anti-Bd bacterial isolates: </b>(119_RDP_alignment_FINAL.fa) As specified in the paper: "We aligned the bacterial isolate sequences using the Ribosomal Database Project’s (http://rdp.cme.msu.edu) alignment tools following Dunitz et al. (2015)." The alignment was used to build the phylogenetic tree presented in Figure 1.<br><br>

**每株抗Bd细菌的元数据：**（AntiBdBac_meta_final.csv）本文件收录了所有经鉴定具有抗Bd活性的细菌分离株的相关信息。元数据涵盖抑菌评分、目视观察抑菌评分、采样地点与蝾螈相关信息、操作分类单元（OTU, Operational Taxonomic Unit）编号、分类学归属、与Woodhams等（2015）数据库的双序列比对值，以及共有序列（该序列已提交至GenBank）。<br>**带元数据的抗Bd细菌丰富度：**（Richness_anti-BdBac.csv）本文件包含蝾螈ID编号以及论文中统计分析所用的全部元数据："为探究每只蝾螈的抗Bd细菌数量是否与宿主或环境特征相关，我们在R包‘lme4’中采用拟合二项分布的广义线性混合效应模型（GLMM, Generalized Linear Mixed-Effects Model）开展分析。我们将物种与采样地点作为主要解释变量，同时纳入宿主相关协变量（性别、身体状况、隐蔽物）以及生境相关协变量（枯落物厚度、土壤pH值、基质温度）。响应变量采用每只蝾螈的抗Bd细菌占比（即抗Bd细菌总数除以分离获得的总细菌数），以校正不同个体分离菌株数量的差异。"<br>**119株抗Bd细菌分离株的序列比对：**（119_RDP_alignment_FINAL.fa）如论文所述："我们参照Dunitz等（2015）的方法，使用核糖体数据库项目（RDP, Ribosomal Database Project，http://rdp.cme.msu.edu）的比对工具完成细菌分离株序列的比对工作。该比对结果用于构建图1所示的系统发育树。"