Table_4_DiTing: A Pipeline to Infer and Compare Biogeochemical Pathways From Metagenomic and Metatranscriptomic Data.XLSX

Metagenomics and metatranscriptomics are powerful methods to uncover key micro-organisms and processes driving biogeochemical cycling in natural ecosystems. Databases dedicated to depicting biogeochemical pathways (for example, metabolism of dimethylsulfoniopropionate (DMSP), which is an abundant organosulfur compound) from metagenomic/metatranscriptomic data are rarely seen. Additionally, a recognized normalization model to estimate the relative abundance and environmental importance of pathways from metagenomic and metatranscriptomic data has not been organized to date. These limitations impact the ability to accurately relate key microbial-driven biogeochemical processes to differences in environmental conditions. Thus, an easy-to-use, specialized tool that infers and visually compares the potential for biogeochemical processes, including DMSP cycling, is urgently required. To solve these issues, we developed DiTing, a tool wrapper to infer and compare biogeochemical pathways among a set of given metagenomic or metatranscriptomic reads in one step, based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) and a manually created DMSP cycling gene database. Accurate and specific formulae for over 100 pathways were developed to calculate their relative abundance. Output reports detail the relative abundance of biogeochemical pathways in both text and graphical format. DiTing was applied to simulated metagenomic data and resulted in consistent genetic features of simulated benchmark genomic data. Subsequently, when applied to natural metagenomic and metatranscriptomic data from hydrothermal vents and the Tara Ocean project, the functional profiles predicted by DiTing were correlated with environmental condition changes. DiTing can now be confidently applied to wider metagenomic and metatranscriptomic datasets, and it is available at https://github.com/xuechunxu/DiTing.

宏基因组学（Metagenomics）与宏转录组学（Metatranscriptomics）是揭示自然生态系统中驱动生物地球化学循环的关键微生物与过程的有力手段。目前，专门针对从宏基因组/宏转录组数据中解析生物地球化学通路（例如，作为一类丰富有机硫化合物的二甲基巯基丙酸内盐（dimethylsulfoniopropionate, DMSP）的代谢过程）的数据库却极为罕见。此外，尚无被广泛认可的标准化模型，可用于从宏基因组和宏转录组数据中估算通路的相对丰度及其环境重要性。这些局限阻碍了研究者将关键微生物驱动的生物地球化学过程与环境条件差异进行精准关联的能力。因此，亟需一款易用的专业工具，用于推断并可视化比较包括二甲基巯基丙酸内盐循环在内的生物地球化学过程的潜在活性。为此，我们基于京都基因与基因组百科全书（Kyoto Encyclopedia of Genes and Genomes, KEGG）以及手动整理的二甲基巯基丙酸内盐循环基因数据库，开发了DiTing——一款可一键完成给定宏基因组或宏转录组测序读段间生物地球化学通路推断与比较的工具封装程序。研究针对100余条通路开发了精准且特异性的计算公式，用于计算其相对丰度。输出报告以文本与可视化图形两种格式，详细呈现生物地球化学通路的相对丰度信息。将DiTing应用于模拟宏基因组数据后，得到的遗传特征与模拟基准基因组数据的特征一致。随后，将其应用于热液喷口及塔拉海洋计划（Tara Ocean project）的自然宏基因组与宏转录组数据时，DiTing预测的功能谱与环境条件变化呈现显著相关性。目前，DiTing可放心应用于更广泛的宏基因组与宏转录组数据集，其开源地址为https://github.com/xuechunxu/DiTing。