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On Comprehensive Mass Spectrometry Data Analysis for Proteome Profiling of Human Blood Samples

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Abstract

To guarantee meaningful interpretation of data in basic and translational medicine, it is critical to ensure the quality of biological samples. Mass spectrometers have become promising instruments to acquire proteomic information that is known to be associated with the quality of samples. However, a universally applicable mass spectrometry data analysis platform for quality assessment remains of great need. We present a comprehensive pattern recognition study to facilitate the development of such a platform. This study involves feature extraction, binary classification, and feature ranking. In this study, we develop classifiers with classification accuracy higher than 90% in distinguishing human serum samples stored for different amounts of time. We also derive fingerprint patterns of serum peptides that can be conveniently used for temporal classification.

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Funding

This study received financial support from NSF grant DMS#1246818 and an industry grant from the Chinese Academy of Sciences Holding Co., Ltd.

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Authors and Affiliations

  1. Department of Computer Science, Purdue University, West Lafayette, USA

    Sameer Manchanda

  2. Department of Statistics and Mathematics, Purdue University, West Lafayette, IN, USA

    Mikaela Meyer

  3. Institute of Biophysics, Chinese Academy of Sciences, Beijing, China

    Qianqian Li, Kai Liang & Yan Li

  4. Weldon School of Biomedical Engineering, Purdue University, 206 S. Martin Jischke Dr, West Lafayette, IN, 47906, USA

    Nan Kong

Authors
  1. Sameer Manchanda
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  2. Mikaela Meyer
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  3. Qianqian Li
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  4. Kai Liang
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  5. Yan Li
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  6. Nan Kong
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Corresponding author

Correspondence to Nan Kong.

Appendix

Appendix

Before storage, the samples were left at room temperature for 1 h in order to allow coagulation and then centrifuged at 4° C for 15 min at 1400×g. In order to avoid fluid in the buffy-coat layer, serum was aspirated and collected in polypropylene tubes. After aliquoting, the samples were then stored in one of two conditions, room temperature or 4° C. For both cohorts, each sample’s mass spectrometer data was collected the day the sample was taken and then 1, 2, 5, and 10 days after that. This data was collected using a 1-μL sample that was processed by a mesoporous silicon wafer that was prepared by pre-baking in an oven at 120° C. This sample was spotted on the MALDI target plate and then allowed to air-dry. Afterwards, a 1-μL matrix in 50% acetonitrile containing 0.1% TFA was spotted on the dried sample spot. This sample was allowed to co-crystallize. The mass spectrum data was obtained by using a SHIMADZU AXIMA Resonance MALDI-IT-TOF equipped with a nitrogen laser emitting light at 337 nm. It had an adjustable mass range of 800 to 4000 Da. The positive ion was detected under reflective mode. After taking 500 laser shots, the spectra were usually averaged to find the final sample spectrum. The optimized accelerating voltage was 50 kV.

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Manchanda, S., Meyer, M., Li, Q. et al. On Comprehensive Mass Spectrometry Data Analysis for Proteome Profiling of Human Blood Samples. J Healthc Inform Res 2, 305–318 (2018). https://doi.org/10.1007/s41666-018-0022-0

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  • DOI: https://doi.org/10.1007/s41666-018-0022-0

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