Automated Data Extraction from <i>In Situ</i> Protein-Stable Isotope Probing Studies

Protein-stable isotope probing (protein-SIP) has strong potential for revealing key metabolizing taxa in complex microbial communities. While most protein-SIP work to date has been performed under controlled laboratory conditions to allow extensive isotope labeling of the target organism(s), a key application will be in situ studies of microbial communities for short periods of time under natural conditions that result in small degrees of partial labeling. One hurdle restricting large-scale in situ protein-SIP studies is the lack of algorithms and software for automated data processing of the massive data sets resulting from such studies. In response, we developed Stable Isotope Probing Protein Extraction Resources software (SIPPER) and applied it for large-scale extraction and visualization of data from short-term (3 h) protein-SIP experiments performed in situ on phototrophic bacterial mats isolated from Yellowstone National Park. Several metrics incorporated into the software allow it to support exhaustive analysis of the complex composite isotopic envelope observed as a result of low amounts of partial label incorporation. SIPPER also enables the detection of labeled molecular species without the need for any prior identification.蛋白质稳定同位素探针技术（Protein-stable isotope probing, 简称protein-SIP）在解析复杂微生物群落中的关键代谢类群方面具有巨大应用潜力。尽管迄今为止绝大多数蛋白质-SIP实验均在可控实验室条件下开展，以实现对目标生物体的高效同位素标记，但其核心应用场景之一，是在自然环境下对微生物群落开展短期原位研究，此时仅能实现低程度的部分同位素标记。制约大规模原位蛋白质-SIP研究的一大瓶颈，在于现有算法与软件无法自动化处理此类研究产生的海量数据集。为此，我们开发了稳定同位素探针蛋白质提取资源软件（Stable Isotope Probing Protein Extraction Resources, 简称SIPPER），并将其应用于从黄石国家公园分离的光合细菌垫开展的3小时短期原位蛋白质-SIP实验数据的大规模提取与可视化分析。该软件集成了多项指标，可支持对低程度部分标记所产生的复杂复合同位素包络信号进行全面分析。此外，SIPPER无需预先进行分子物种鉴定，即可实现标记分子的检测。