Hybrid Feature Detection and Information Accumulation Using High-Resolution LC–MS Metabolomics Data

Feature detection is a critical step in the preprocessing of liquid chromatography–mass spectrometry (LC–MS) metabolomics data. Currently, the predominant approach is to detect features using noise filters and peak shape models based on the data at hand alone. Databases of known metabolites and historical data contain information that could help boost the sensitivity of feature detection, especially for low-concentration metabolites. However, utilizing such information in targeted feature detection may cause large number of false positives because of the high levels of noise in LC–MS data. With high-resolution mass spectrometry such as liquid chromatograph–Fourier transform mass spectrometry (LC–FTMS), high-confidence matching of peaks to known features is feasible. Here we describe a computational approach that serves two purposes. First it boosts feature detection sensitivity by using a hybrid procedure of both untargeted and targeted peak detection. New algorithms are designed to reduce the chance of false-positives by nonparametric local peak detection and filtering. Second, it can accumulate information on the concentration variation of metabolites over large number of samples, which can help find rare features and/or features with uncommon concentration in future studies. Information can be accumulated on features that are consistently found in real data even before their identities are found. We demonstrate the value of the approach in a proof-of-concept study. The method is implemented as part of the R package apLCMS at http://www.sph.emory.edu/apLCMS/

Additional file 9: of High resolution metabolomics to discriminate compounds in serum of male lung cancer patients in South Korea

Relative concentrations of three compounds in 2nd and 3rd analysis. BPA, with its increasing abundance, was detected only in 3rd analysis while retinol, with its decreasing abundance, was detected only in 2nd analysis. L-proline was found to be lowered in both 2nd and 3rd analysis. *shows significant difference (p < 0.05) (TIF 1390 kb

Fritillaria camtschatcensis Ker Gawl.

原著和名: クロユリ科名: ユリ科 = Liliaceae採集地: 北海道 厚岸郡 浜中町 霧多布湿原 (北海道 釧路 浜中町 霧多布湿原)採集日: 1975/6/17採集者: 古瀬 義整理番号: JH014722国立科学博物館整理番号: TNS-VS-96472

Mitochondrial metabolites from AE that were found to discriminate male from female mitochondria using false discovery rate analysis (q = 0.1).

<p>Metabolites with greater ion intensity in male mitochondria include (A) leucine/isoleucine, (B) glutamate and (C) methionine. Metabolites with greater ion intensity in female mitochondria include (D) adenosine, (E) amino octadecanoic acid and (F) unknown metabolite (<i>m/z</i> 537.789). Data was analyzed using one-way ANOVA and Tukey's post hoc test (* p<0.05, ** p<0.01, *** p<0.001).</p

A breakdown of the animals used for mitochondrial isolation and metabolic profiling studies.

<p>A total of 40 animals were used, 20 wild type and 20 thiroredoxin-2 transgenic (Trx2TG). These groups were further broken down into subgroups of 5 based on age and sex.</p

Distribution of metabolites resolved by anion exchange (A) and reverse phase (B) chromatography.

<p>To determine if a metabolite was present in the mitochondrial isolation and not a buffer contaminant, a ratio of ion intensity (sample ion intensity/buffer ion intensity) was calculated for each metabolite. A metabolite was determined to be “mitochondrial” if this ratio (s/b) was greater than or equal to 4. Additionally, employment of two chromatographic techniques resulted in the detection of 2127 mitochondrial metabolites (C).</p

Mitochondrial metabolites from C18 that were found to discriminate male from female mitochondria using false discovery rate analysis (q = 0.1).

<p>Metabolites with greater ion intensity in male mitochondria include (A) leucine/isoleucine, (B) glutamate and (C) methionine. Metabolites with greater ion intensity in female mitochondria include (D) adenosine, (E) sphinganine and (F) unknown metabolite (<i>m/z</i> 442.759). Data was analyzed using one-way ANOVA and Tukey's post hoc test (* p<0.05, *** p<0.001).</p

Most metabolic pathways are represented in metabolites isolated from liver mitochondria.

<p>Ten pathways containing the most matches are plotted.</p

The results of correct proportion from quadratic discriminant analysis.

<p>The descriptors precisely separate the SAA insufficiency from the SAA sufficiency for subjects 1, 2, 4 and 5.</p

Association of multifractal descriptors with plasma lipid parameters.

<p>Coefficients of response for <i>H</i>, LS and Std with <i>p</i>-values in parentheses, for a regression model of response in which <i>H</i>, LS, and Std are quantitative variables and subject is a qualitative variable in SAA deletion-repletion study. The underlined values represent the significance of the model at a 95% confidence level. The last column represents the coefficient of determination R² for the model.</p