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Comparative proteomics: assessment of biological variability and dataset comparability.
Kim, Sa Rang; Nguyen, Tuong Vi; Seo, Na Ri; Jung, Seunghup; An, Hyun Joo; Mills, David A; Kim, Jae Han.
Afiliação
  • Kim SR; Department of Food and Nutrition, Chungnam National University, Daejeon, 305-764, South Korea. ksr7744@cnu.ac.kr.
  • Nguyen TV; Department of Food and Nutrition, Chungnam National University, Daejeon, 305-764, South Korea. t.vi.nguyen@gmail.com.
  • Seo NR; Graduate School of Analytical Science and Technology, Chungnam National University, Daejeon, 305-764, South Korea. snr85@cnu.ac.kr.
  • Jung S; Graduate School of Analytical Science and Technology, Chungnam National University, Daejeon, 305-764, South Korea. shjeong0512@gmail.com.
  • An HJ; Graduate School of Analytical Science and Technology, Chungnam National University, Daejeon, 305-764, South Korea. hjan@cnu.ac.kr.
  • Mills DA; Robert Mondavi Institute for Wine and Food Science, Department of Food Science, University of California, Davis, CA, 95616, USA. damills@ucdavis.edu.
  • Kim JH; Department of Food and Nutrition, Chungnam National University, Daejeon, 305-764, South Korea. jaykim@cnu.ac.kr.
BMC Bioinformatics ; 16: 121, 2015 Apr 17.
Article em En | MEDLINE | ID: mdl-25888384
ABSTRACT

BACKGROUND:

Comparative proteomics in bacteria are often hampered by the differential nature of dataset quality and/or inherent biological deviations. Although common practice compensates by reproducing and normalizing datasets from a single sample, the degree of certainty is limited in comparison of multiple dataset. To surmount these limitations, we introduce a two-step assessment criterion using (1) the relative number of total spectra (R TS ) to determine if two LC-MS/MS datasets are comparable and (2) nine glycolytic enzymes as internal standards for a more accurate calculation of relative amount of proteins. Lactococcus lactis HR279 and JHK24 strains expressing high or low levels (respectively) of green fluorescent protein (GFP) were used for the model system. GFP abundance was determined by spectral counting and direct fluorescence measurements. Statistical analysis determined relative GFP quantity obtained from our approach matched values obtained from fluorescence measurements.

RESULTS:

L. lactis HR279 and JHK24 demonstrates two datasets with an R TS value less than 1.4 accurately reflects relative differences in GFP levels between high and low expression strains. Without prior consideration of R TS and the use of internal standards, the relative increase in GFP calculated by spectral counting method was 3.92 ± 1.14 fold, which is not correlated with the value determined by the direct fluorescence measurement (2.86 ± 0.42 fold) with the p = 0.024. In contrast, 2.88 ± 0.92 fold was obtained by our approach showing a statistically insignificant difference (p = 0.95).

CONCLUSIONS:

Our two-step assessment demonstrates a useful approach to (1) validate the comparability of two mass spectrometric datasets and (2) accurately calculate the relative amount of proteins between proteomic datasets.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Proteínas de Bactérias / Bases de Dados de Proteínas / Proteômica / Lactobacillus Tipo de estudo: Guideline / Prognostic_studies Idioma: En Revista: BMC Bioinformatics Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2015 Tipo de documento: Article País de afiliação: Coréia do Sul

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Proteínas de Bactérias / Bases de Dados de Proteínas / Proteômica / Lactobacillus Tipo de estudo: Guideline / Prognostic_studies Idioma: En Revista: BMC Bioinformatics Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2015 Tipo de documento: Article País de afiliação: Coréia do Sul