Schaible George A, Cliff John B, Crandall Jennifer A, Bougoure Jeremy J, Mathuri Michael N, Sessions Alex L, Atwood Joseph, Hatzenpichler Roland
Department of Chemistry and Biochemistry, Montana State University, Bozeman, Montana, USA.
Center for Biofilm Engineering, Montana State University, Bozeman, Montana, USA.
Microbiol Spectr. 2025 May 30:e0165924. doi: 10.1128/spectrum.01659-24.
Stable isotope probing (SIP) experiments in conjunction with Raman microspectroscopy (Raman) or nano-scale secondary ion mass spectrometry (NanoSIMS) are frequently used to explore single cell metabolic activity in pure cultures as well as complex microbiomes. Despite the increasing popularity of these techniques, the comparability of isotope incorporation measurements using both Raman and NanoSIMS directly on the same cell remains largely unexplored. This knowledge gap creates uncertainty about the consistency of single-cell SIP data obtained independently from each method. Here, we conducted a comparative analysis of 543 cells grown in M9 minimal medium in the absence or presence of heavy water (HO) using correlative Raman and NanoSIMS measurements to quantify the results between the two approaches. We demonstrate that Raman and NanoSIMS yield highly comparable measurements of H incorporation, with varying degrees of similarity based on the mass ratios analyzed using NanoSIMS. The CH/CH and CH/CH mass ratios provide targeted measurements of C-H bonds but may suffer from biases and background interference, while the H/H ratio captures all hydrogen with lower detection limits, making it suitable for applications requiring comprehensive H quantification. Importantly, despite its higher mass resolution requirements, the use of CH/CH may be a viable alternative to the use of CH/CH due to lower background and higher overall count rates. Furthermore, using an empirical approach in determining Raman wavenumber ranges via the second derivative improved the data equivalency of H quantification between Raman and NanoSIMS, highlighting its potential for enhancing cross-technique comparability. These findings provide a robust framework for leveraging both techniques, enabling informed experimental design and data interpretation. By enhancing cross-technique comparability, this work advances SIP methodologies for investigating microbial metabolism and interactions in diverse systems.IMPORTANCEAccurate and reliable measurements of cellular properties are fundamental to understand the function and activity of microbes. This study addresses to what extent Raman microspectroscopy and nano-scale secondary ion mass spectrometry (NanoSIMS) measurements of single cell anabolic activity can be compared. Here, we study the relationship of the incorporation of a stable isotope (H through incorporation of HO) as determined by the two techniques and calculate a correlation coefficient to support the use of either technique when analyzing cells incubated with HO. The ability to discern between the comparative strengths and limitations of these techniques is invaluable in refining experimental protocols, enhancing data comparability between studies, data interpretation, and ultimately advancing the quality and reliability of outcomes in microbiome research.
稳定同位素探测(SIP)实验结合拉曼光谱(Raman)或纳米二次离子质谱(NanoSIMS),常用于探索纯培养物以及复杂微生物群落中的单细胞代谢活性。尽管这些技术越来越受欢迎,但直接在同一细胞上使用拉曼光谱和纳米二次离子质谱进行同位素掺入测量的可比性在很大程度上仍未得到探索。这一知识空白使得独立于每种方法获得的单细胞SIP数据的一致性存在不确定性。在这里,我们使用相关的拉曼光谱和纳米二次离子质谱测量方法,对在M9基本培养基中在有无重水(D₂O)的情况下生长的543个细胞进行了比较分析,以量化两种方法之间的结果。我们证明,拉曼光谱和纳米二次离子质谱对氘掺入的测量结果具有高度可比性,根据使用纳米二次离子质谱分析的质量比,相似程度各不相同。¹³C/¹²C和¹⁵N/¹⁴N质量比提供了对C-H键的靶向测量,但可能存在偏差和背景干扰,而D/H比以较低的检测限捕获所有氢,使其适用于需要全面氢定量的应用。重要的是,尽管¹³C/¹²C对质量分辨率要求更高,但由于背景较低和总计数率较高,使用¹³C/¹²C可能是使用¹⁵N/¹⁴N的可行替代方法。此外,通过二阶导数确定拉曼波数范围的经验方法提高了拉曼光谱和纳米二次离子质谱之间氢定量的数据等效性,突出了其增强跨技术可比性的潜力。这些发现为利用这两种技术提供了一个强大的框架,有助于进行明智的实验设计和数据解释。通过提高跨技术可比性,这项工作推动了用于研究不同系统中微生物代谢和相互作用的SIP方法的发展。
重要性
准确可靠地测量细胞特性是理解微生物功能和活性的基础。本研究探讨了拉曼光谱和纳米二次离子质谱(NanoSIMS)对单细胞合成代谢活性的测量在多大程度上可以进行比较。在这里,我们研究了通过这两种技术确定的稳定同位素(通过掺入D₂O的氘)掺入之间的关系,并计算了相关系数,以支持在分析与D₂O孵育的细胞时使用这两种技术中的任何一种。能够区分这些技术的比较优势和局限性,对于完善实验方案、提高研究之间的数据可比性、数据解释以及最终提高微生物组研究结果的质量和可靠性具有不可估量的价值。