Department of Plant and Microbial Biology, North Carolina State University, Raleigh, NC, USA.
Department of Geoscience, University of Calgary, Calgary, AB, Canada.
Microbiome. 2023 Feb 9;11(1):24. doi: 10.1186/s40168-022-01454-1.
Stable isotope probing (SIP) approaches are a critical tool in microbiome research to determine associations between species and substrates, as well as the activity of species. The application of these approaches ranges from studying microbial communities important for global biogeochemical cycling to host-microbiota interactions in the intestinal tract. Current SIP approaches, such as DNA-SIP or nanoSIMS allow to analyze incorporation of stable isotopes with high coverage of taxa in a community and at the single cell level, respectively, however they are limited in terms of sensitivity, resolution or throughput.
Here, we present an ultra-sensitive, high-throughput protein-based stable isotope probing approach (Protein-SIP), which cuts cost for labeled substrates by 50-99% as compared to other SIP and Protein-SIP approaches and thus enables isotope labeling experiments on much larger scales and with higher replication. The approach allows for the determination of isotope incorporation into microbiome members with species level resolution using standard metaproteomics liquid chromatography-tandem mass spectrometry (LC-MS/MS) measurements. At the core of the approach are new algorithms to analyze the data, which have been implemented in an open-source software ( https://sourceforge.net/projects/calis-p/ ). We demonstrate sensitivity, precision and accuracy using bacterial cultures and mock communities with different labeling schemes. Furthermore, we benchmark our approach against two existing Protein-SIP approaches and show that in the low labeling range used our approach is the most sensitive and accurate. Finally, we measure translational activity using O heavy water labeling in a 63-species community derived from human fecal samples grown on media simulating two different diets. Activity could be quantified on average for 27 species per sample, with 9 species showing significantly higher activity on a high protein diet, as compared to a high fiber diet. Surprisingly, among the species with increased activity on high protein were several Bacteroides species known as fiber consumers. Apparently, protein supply is a critical consideration when assessing growth of intestinal microbes on fiber, including fiber-based prebiotics.
We demonstrate that our Protein-SIP approach allows for the ultra-sensitive (0.01 to 10% label) detection of stable isotopes of elements found in proteins, using standard metaproteomics data.
稳定同位素探测（SIP）方法是微生物组研究中的重要工具，可用于确定物种与底物之间的关联，以及物种的活性。这些方法的应用范围从研究对全球生物地球化学循环重要的微生物群落到肠道中的宿主-微生物群相互作用。目前的 SIP 方法，如 DNA-SIP 或 nanoSIMS，可以分别在群落和单细胞水平上分析具有高分类覆盖率的稳定同位素的掺入，但它们在灵敏度、分辨率或通量方面存在限制。
本文提出了一种超灵敏、高通量的基于蛋白质的稳定同位素探测方法（Protein-SIP），与其他 SIP 和 Protein-SIP 方法相比，该方法可将标记底物的成本降低 50-99%，从而能够在更大规模和更高复制水平上进行同位素标记实验。该方法允许使用标准的微生物组蛋白质组学液相色谱-串联质谱（LC-MS/MS）测量，以物种分辨率确定微生物组成员中同位素的掺入。该方法的核心是用于分析数据的新算法，这些算法已在一个开源软件（https://sourceforge.net/projects/calis-p/）中实现。我们使用不同标记方案的细菌培养物和模拟群落来证明其灵敏度、精度和准确性。此外，我们将我们的方法与两种现有的 Protein-SIP 方法进行了基准测试，并表明在使用的低标记范围内，我们的方法是最敏感和准确的。最后，我们使用 O 重水标记在源自人类粪便样本的 63 种物种群落中进行了翻译活性的测量，该群落是在模拟两种不同饮食的培养基上生长的。每个样本平均可定量 27 个物种的活性，其中 9 个物种在高蛋白饮食下的活性明显高于高纤维饮食。令人惊讶的是，在活性增加的物种中，有几个已知为纤维消费者的拟杆菌属物种。显然，在评估肠道微生物对纤维（包括纤维为基础的益生元）的生长时，蛋白质供应是一个关键因素。
我们证明，我们的 Protein-SIP 方法可以使用标准的微生物组蛋白质组学数据，对蛋白质中存在的元素的稳定同位素进行超灵敏（0.01 至 10%标记）检测。
