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Issue 1, 2017
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Checkpoints for preliminary identification of small molecules found enriched in autophagosomes and activated mast cell secretions analyzed by comparative UPLC/MSe

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Abstract

We report the use of ultra high performance liquid chromatography (UPLC) coupled with acquisition of low- and high-collision energy mass spectra (MSe) to explore small molecule compositions that are unique to either enriched-autophagosomes or secretions of chemically activated murine mast cells. Starting with thousands of features, each defined by a chromatographic retention time, m/z value and ion intensity, manual examination of the extracted ion chromatograms (XIC) of chemometrically selected features was essential to eliminate false positives, occurring at rates of 33, 14 and 37% in samples of three biological systems. Forty-six percent of features that passed the XIC-based checkpoint, had IDs in compound databases used here. From these, 19% of IDs had experimental high-collision energy MSe spectra that were in agreement with in silico fragmentation. The importance of this second checkpoint was highlighted through validation with selected commercially available standards. This work illustrates that checkpoints in data processing are essential to ascertain reliability of unbiased metabolomic studies, thereby reducing the risk of generating ‘false identifications’ which is a major concern as ‘omics’ data continue to proliferate and be used as platforms to launch novel biological hypotheses.

Graphical abstract: Checkpoints for preliminary identification of small molecules found enriched in autophagosomes and activated mast cell secretions analyzed by comparative UPLC/MSe

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Publication details

The article was received on 05 Sep 2016, accepted on 10 Oct 2016 and first published on 11 Oct 2016


Article type: Paper
DOI: 10.1039/C6AY02500E
Citation: Anal. Methods, 2017,9, 46-54
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    Checkpoints for preliminary identification of small molecules found enriched in autophagosomes and activated mast cell secretions analyzed by comparative UPLC/MSe

    C. P. Satori, M. Ramezani, J. S. Koopmeiners, A. F. Meyer, J. A. Rodriguez-Navarro, M. M. Kuhns, T. H. Taylor, C. L. Haynes, J. J. Dalluge and E. A. Arriaga, Anal. Methods, 2017, 9, 46
    DOI: 10.1039/C6AY02500E

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