Comparison of two algorithmic data processing strategies for metabolic fingerprinting by comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry
Comparison of two algorithmic data processing strategies for metabolic fingerprinting by comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry
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DOI：
10.1016/j.chroma.2011.08.006
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发表时间：
2011-09-28
影响因子：
4.1
通讯作者：
Oefner, Peter J.
中科院分区：
文献类型：
--
作者：
Almstetter, Martin F.;Appel, Inka J.;Oefner, Peter J.
对LECO公司开发的用于处理综合二维气相色谱-飞行时间质谱仪(GC x GC-TOFMS)数据的比对算法统计比较(SC)进行了验证，并与内部开发的保留时间校正和数据比对工具INCA(一体化归一化和比较分析)进行了验证和比较，通过添加实验和比较野生型和双突变菌株的代谢指纹图谱。从Leco的ChromaTOF软件生成的相同峰列表开始，通过将20种标准化合物添加到大肠杆菌的水甲醇提取物中，评估了代谢物浓度1.1至4倍变化的峰对齐和检测的准确性。为了为两种配准程序提供相同质量的输入信号，使用三甲基硅基(TMS)基团的通用m/z 73迹线作为所有特征的定量测量。通过ROC曲线对数据处理和比对的性能进行了评价和说明。统计比较在较低的折叠变化上表现略好，而印加在较高的折叠变化上表现较好。使用SC，可以通过利用特定代谢物特有的(U)m/z离子示踪的信号强度而不是通用的m/z 73示踪来显著提高定量精度。通过使用m/z U的SC比对获得了区分这两个大肠杆菌菌株的56个特征的列表，估计错误发现率(FDR)为
The alignment algorithm Statistical Compare (SC) developed by LECO Corporation for the processing of comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry (GC x GC-TOFMS) data was validated and compared to the in-house developed retention time correction and data alignment tool INCA (Integrative Normalization and Comparative Analysis) by a spike-in experiment and the comparative metabolic fingerprinting of a wild type versus a double mutant strain of Escherichia coli (E. coli). Starting with the same peak lists generated by LECO's ChromaTOF software, the accuracy of peak alignment and detection of 1.1- to 4-fold changes in metabolite concentration was assessed by spiking 20 standard compounds into an aqueous methanol extract of E. coli. To provide the same quality input signals for both alignment routines, the universal m/z 73 trace of the trimethylsilyl (TMS) group was used as a quantitative measure for all features. The performance of data processing and alignment was evaluated and illustrated by ROC curves. Statistical Compare performed marginally better at the lower fold changes, while INCA did so at the higher fold changes. Using SC, quantitative precision could be improved substantially by exploiting the signal intensities of metabolite-specific unique (U) m/z ion traces rather than the universal m/z 73 trace. A list of 56 features that distinguished the two E. coli strains was obtained by the SC alignment using m/z U with an estimated false discovery rate (FDR) of