Schum Simeon K, Brown Laura E, Mazzoleni Lynn R
Department of Chemistry, Michigan Technological University, 1400, Townsend Dr., Houghton, MI, USA; Chemical Advanced Resolution Methods Laboratory, Michigan Technological University, 1400, Townsend Dr., Houghton, MI, USA.
Department of Computer Science, Michigan Technological University, 1400, Townsend Dr., Houghton, MI, USA.
Environ Res. 2020 Dec;191:110114. doi: 10.1016/j.envres.2020.110114. Epub 2020 Aug 28.
Ultrahigh resolution mass spectrometry is widely used for nontargeted analysis of complex environmental and biological mixtures, such as dissolved organic matter, due to its unparalleled ability to provide accurate mass measurements. Accurate and efficient characterization of these mixtures is critical to being better able to evaluate their effect on human health and climate. This characterization requires accurate mass signals free from isobaric interferences, instrument noise, and mass measurement biases, allowing for molecular formula identification. To address this need, an open source post-processing pipeline for ultrahigh resolution mass spectra of environmental complex mixtures software was developed. MFAssignR contains functions that perform noise estimation, C and S polyisotopic mass filtering, mass measurement recalibration, and molecular formula assignment as part of a consistent data processing environment. Novel applications of mass defect analysis were used in the functions for noise estimation and isotope pair identification. Using formula extensions, exact mass measurements are converted to unambiguous molecular formulas via data dependent pathways, reducing a priori decisions. Optional molecular formula ambiguity and multiple non-oxygen heteroatoms are provided for custom user applications, including isotopically labeled reactive species, halogen-containing species, or tandem ultrahigh resolution mass spectrometry. This represents uncommon flexibility for an open-source software package. To evaluate the performance of MFAssignR, it was used to characterize a sample of biomass burning influenced organic aerosol and the results were compared to those from other available methods of molecular formula assignment and noise estimation. The differences between the methods are described here. Overall, the inclusion of a full pipeline of data preparation functions and the data-dependent ambiguity reductions in MFAssignR render excellent results and make MFAssignR well-suited for the consistent and efficient analysis of environmental complex mixtures. MFAssignR is publicly available via GitHub.
超高分辨率质谱法因其提供精确质量测量的无与伦比的能力，被广泛用于对复杂环境和生物混合物（如溶解有机物）进行非靶向分析。准确而高效地表征这些混合物对于更好地评估它们对人类健康和气候的影响至关重要。这种表征需要无等压干扰、仪器噪声和质量测量偏差的精确质量信号，以便进行分子式鉴定。为满足这一需求，开发了一种用于环境复杂混合物超高分辨率质谱的开源后处理管道软件。MFAssignR包含在一致的数据处理环境中执行噪声估计、碳和硫多同位素质量过滤、质量测量重新校准以及分子式分配的功能。质量亏损分析的新应用被用于噪声估计和同位素对识别功能。通过公式扩展，精确质量测量通过数据依赖途径转换为明确的分子式，减少了先验决策。为自定义用户应用提供了可选的分子式模糊性和多个非氧杂原子，包括同位素标记的反应性物种、含卤素物种或串联超高分辨率质谱。这对于一个开源软件包来说代表了罕见的灵活性。为评估MFAssignR的性能，用它来表征受生物质燃烧影响的有机气溶胶样品，并将结果与其他可用的分子式分配和噪声估计方法的结果进行比较。这里描述了这些方法之间的差异。总体而言，MFAssignR中包含的完整数据准备功能管道以及数据依赖的模糊性减少带来了出色的结果，使MFAssignR非常适合对环境复杂混合物进行一致且高效的分析。MFAssignR可通过GitHub公开获取。
