Phyllosphere microbial associations improve plant reproductive success

The above-ground (phyllosphere) plant microbiome is increasingly recognized as an important component of plant health. We hypothesized that phyllosphere bacterial recruitment may be disrupted in a greenhouse setting, and that adding a bacterial amendment would therefore benefit the health and growth of host plants. Using a newly developed synthetic phyllosphere bacterial microbiome for tomato (Solanum lycopersicum), we tested this hypothesis across multiple trials by manipulating microbial inoculation of leaves and measuring subsequent plant growth and reproductive success, comparing results from plants grown in both greenhouse and field settings. We confirmed that greenhouse-grown plants have a relatively depauperate phyllosphere bacterial microbiome, which both makes them an ideal system for testing the impact of phyllosphere communities on plant health and important targets for microbial amendments as we move towards increased agricultural sustainability. We find that the addition of..., For 16s Sequencing related data, paired-end reads were filtered and trimmed to 230(F) and 160(R) base pairs (bps), using DADA2 with default parameters (Callahan et al., 2016). Following denoising, merging reads and removing chimeras, DADA2 was used to infer amplicon sequence variants (ASVs), which are analogous to operational taxonomic units (OTUs), and taxonomy was assigned using the DADA2-trained SILVA database. Using DNA extraction and PCR negative controls from 16S sequencing, the decontam package was implemented using default settings to identify and remove potential contamination from the samples (Davis et al., 2018). The assigned ASVs, read count data, and sample metadata were combined in a phyloseq object (McMurdie & Holmes, 2013) for downstream analyses. The phyloseq package was used to calculate beta diversity (using Bray-Curtis distance), and a permutational analysis (PERMANOVA) was performed on data rarified to 400 reads (Weiss et al., 2017) (to account for extraordinari..., All data is provided as either `.csv` files, or as `.rds` files, which can be opened and processed in R., # Phyllosphere microbial associations improve plant reproductive success These data represent the processed sequencing data (mostly in the form of phyloseq objects) and the greenhouse and field tomato plant harvest results associated with the study. Data includes sequencing results, with both bacterial absolute and relative abundance, as well as tomato number, and tomato weight, either as weight per tomato or weight harvested per plant. ## Description of the data and file structure Data is presented as one of two file types, either a `.csv` or a `.rds`. Most sequencing related data is presented as `.rds` files, which must be loaded into R in order to be utilized. Further, these data are formatted as `phyloseq` objects, and require the package `phyloseq` in order to be processed. Some sequencing related data (ie. absolute, `Trial_1_Greenhouse_Bacterial_Abundance.csv`, and relative abundance, `Trial_3_Greenhouse_and_Field_Bacterial_Abundance.csv`) are `.csv` files. All of the greenhou...地上部分（叶围，phyllosphere）植物微生物组日益被视为植物健康的关键组成部分。我们提出假说：温室环境可能干扰叶围细菌的定殖过程，因此添加细菌菌剂将有益于宿主植物的健康与生长。我们针对番茄（Solanum lycopersicum）新开发了一种合成型叶围细菌微生物组，通过调控叶片的微生物接种处理并测定后续植物的生长状况与繁殖成效，开展多组重复试验，对比了温室与田间种植植株的实验结果。 我们证实，温室种植的植物其叶围细菌微生物组相对匮乏，这使其既成为验证叶围群落对植物健康影响的理想研究体系，也是在提升农业可持续性进程中微生物菌剂应用的重要靶标。我们发现，添加[原文未完整呈现]。针对16S测序相关数据，我们使用默认参数的DADA2工具（Callahan等，2016）将双端测序读数过滤并修剪至正向230、反向160个碱基对（bp）。在降噪、合并读数并去除嵌合序列后，我们使用DADA2推断扩增子序列变异体（amplicon sequence variants, ASVs，与操作分类单元（operational taxonomic units, OTUs）功能类似），并使用经DADA2训练的SILVA数据库进行分类注释。借助16S测序过程中的DNA提取与PCR阴性对照，我们使用默认参数运行decontam工具包（Davis等，2018）以识别并去除样本中的潜在污染。我们将得到的ASVs、读数计数数据与样本元数据整合为phyloseq对象（McMurdie与Holmes，2013）以用于后续分析。我们使用phyloseq包计算β多样性（beta diversity，采用Bray-Curtis距离（Bray-Curtis distance）算法），并对抽平至400条读数的数据集进行置换多元方差分析（PERMANOVA，Weiss等，2017）[原文未完整呈现]。所有数据以`.csv`文件或`.rds`文件形式提供，可在R语言环境中打开并处理。 # 叶围微生物共生关系可提升植物繁殖成功率 本数据集包含本研究相关的经处理测序数据（多以phyloseq对象形式存储）以及温室与田间番茄植株的收获结果数据。数据涵盖测序结果（包含细菌绝对丰度与相对丰度）、番茄果实数量以及单果重量或单株总收获重量。 ## 数据描述与文件结构 数据分为两种文件格式：`.csv`与`.rds`。多数测序相关数据以`.rds`文件形式存储，需加载至R语言环境后方可使用。此外，此类数据被格式化为`phyloseq`对象，需依赖`phyloseq`工具包进行处理。部分测序相关数据（如绝对丰度数据`Trial_1_Greenhouse_Bacterial_Abundance.csv`、相对丰度数据`Trial_3_Greenhouse_and_Field_Bacterial_Abundance.csv`）为`.csv`格式文件。所有温室[原文未完整呈现]