Department of Chemistry, University of Washington, Box 351700, Seattle, Washington 98195-1700, United States.
Anal Chem. 2020 Aug 18;92(16):11365-11373. doi: 10.1021/acs.analchem.0c02136. Epub 2020 Jul 29.
Accurate analyte peak detection from the background noise is a fundamental step in data analysis. Often, this is initially performed on the total ion current chromatogram (TIC), which is the summed signal from all mass spectral channels. Despite the detection of many of the most abundant peaks within a chromatogram, a large fraction of peaks remains undetected in the standard TIC due to their signal being below the limit of detection. To find peaks obscured by background noise, an untargeted peak detection method termed the "enhanced TIC algorithm" was developed for comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC × GC-TOFMS). The reported algorithm utilizes the entire mass spectral dimension to find regions of analytical signal above a threshold while zeroing the background noise. The resulting chromatographic data is summed together to create the enhanced TIC. The utility of the enhanced TIC algorithm is demonstrated using serial dilutions from a 10 parts-per-thousand (ppth) test mixture. For the chromatograms collected at 1 and 10 parts-per-million (ppm), the enhanced TIC algorithm recovered 62% and 93%, respectively, of the original peaks observed in the 10 ppth mixture, while the standard TIC recovered only 0% and 45%, respectively. The improvement in signal enhancement was also shown on a separation of a yeast cell metabolite extract, where the enhanced TIC found 33-64% more peaks than the standard TIC. Chromatographic simulations with increasing levels of background noise were also conducted to compare the enhanced and standard TICs in the context of statistical overlap theory (SOT). Simulated chromatograms with lower signal-to-noise were more accurately modeled by the SOT after enhanced TIC processing compared to those processed by the standard TIC. The enhanced TIC method demonstrates an immense benefit in peak discovery to improve data analysis efforts.
从背景噪声中准确地检测分析物峰是数据分析的基本步骤。通常，这最初是在总离子流色谱图（TIC）上进行的，TIC 是所有质谱通道信号的总和。尽管在色谱图中检测到了许多最丰富的峰，但由于其信号低于检测限，标准 TIC 中仍有很大一部分峰未被检测到。为了找到被背景噪声掩盖的峰，开发了一种称为“增强 TIC 算法”的非靶向峰检测方法，用于全二维气相色谱与飞行时间质谱联用（GC×GC-TOFMS）。所报道的算法利用整个质谱维度来找到高于阈值的分析信号区域，同时将背景噪声置零。将得到的色谱数据相加以创建增强 TIC。使用 1000 分之 10（ppth）测试混合物的系列稀释液来证明增强 TIC 算法的实用性。对于在 1 和 10 百万分率（ppm）下收集的色谱图，增强 TIC 算法分别恢复了在 10 ppth 混合物中观察到的原始峰的 62%和 93%，而标准 TIC 仅分别恢复了 0%和 45%。在酵母细胞代谢产物提取物的分离中也显示了信号增强的改善，其中增强 TIC 比标准 TIC 多发现了 33-64%的峰。还进行了具有不同背景噪声水平的色谱模拟，以在统计重叠理论（SOT）的背景下比较增强 TIC 和标准 TIC。与经过标准 TIC 处理的模拟色谱相比，经过增强 TIC 处理的具有较低信噪比的模拟色谱可以更准确地通过 SOT 建模。增强 TIC 方法在提高数据分析效率方面具有巨大的发现峰的优势。
