Proteomics, metabolomics, and transcriptomics generate comprehensive data sets, and current biocomputational capabilities allow their efficient integration for systems biology analysis. Published multiomics studies cover methodological advances as well as applications to biological questions. However, few studies have focused on the development of a high-throughput, unified sample preparation approach to complement high-throughput omic analytics. This report details the automation, benchmarking, and application of a strategy for transcriptomic, proteomic, and metabolomic analyses from a common sample. The approach, sample preparation for multi-omics technologies (SPOT), provides equivalent performance to typical individual omic preparation methods but greatly enhances throughput and minimizes the resources required for multiomic experiments. SPOT was applied to a multiomics time course experiment for zinc-treated HL-60 cells. The data reveal Zn effects on NRF2 antioxidant and NFkappaB signaling. High-throughput approaches such as these are critical for the acquisition of temporally resolved, multicondition, large multiomic data sets such as those necessary to assess complex clinical and biological concerns. Ultimately, this type of approach will provide an expanded understanding of challenging scientific questions across many fields.

中文翻译：

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用于多组学系统水平分析的集成式高通量策略

蛋白质组学，代谢组学和转录组学可生成全面的数据集，而当前的生物计算功能可对其进行高效集成以进行系统生物学分析。出版的多组学研究涵盖方法学的进步以及对生物学问题的应用。但是，很少有研究专注于开发高通量，统一的样品制备方法来补充高通量的眼科分析。该报告详细介绍了从一个普通样本进行转录组学，蛋白质组学和代谢组学分析的策略的自动化，基准测试和应用。这种方法，即用于多组学技术（SPOT）的样品制备，可提供与典型的单个组学制备方法相同的性能，但可大大提高通量，并最大程度地减少了多组学实验所需的资源。将SPOT应用于锌处理的HL-60细胞的多组学时间过程实验。数据揭示了锌对NRF2抗氧化剂和NFkappaB信号传导的影响。诸如此类的高通量方法对于获取时间分辨的多条件大型多组学数据集（例如评估复杂的临床和生物学问题所必需的数据集）至关重要。最终，这种方法将在许多领域提供对挑战性科学问题的扩展理解。大型多组学数据集，例如评估复杂的临床和生物学问题所必需的数据集。最终，这种方法将在许多领域提供对挑战性科学问题的扩展理解。大型多组学数据集，例如评估复杂的临床和生物学问题所必需的数据集。最终，这种方法将在许多领域提供对挑战性科学问题的扩展理解。