@article{SilvaOliveiraCostaTchewonpietal.2021,
  author    = {Silva, Bibiana and Oliveira Costa, Ana Carolina and Tchewonpi, Sorel Sagu and B{\"o}nick, Josephine and Huschek, Gerd and Gonzaga, Luciano Valdemiro and Fett, Roseane and Baldermann, Susanne and Rawel, Harshadrai Manilal},
  title     = {Comparative quantification and differentiation of bracatinga (Mimosa scabrella Bentham) honeydew honey proteins using targeted peptide markers identified by high-resolution mass spectrometry},
  series = {Food research international},
  volume    = {141},
  journal   = {Food research international},
  publisher = {Elsevier},
  address   = {New York, NY [u.a.]},
  issn      = {0963-9969},
  doi       = {10.1016/j.foodres.2020.109991},
  pages     = {10},
  year      = {2021},
  abstract  = {Honey traceability is an important topic, especially for honeydew honeys, due to the increased incidence of adulteration. This study aimed to establish specific markers to quantify proteins in honey. A proteomics strategy to identify marker peptides from bracatinga honeydew honey was therefore developed. The proteomics approach was based on initial untargeted identification of honey proteins and peptides by LC-ESI-Triple-TOF-MS/MS, which identified the major royal jelly proteins (MRJP) presence. Afterwards, the peptides were selected by the in silico digestion. The marker peptides were quantified by the developed targeted LC-QqQ-MS/MS method, which provided good linearity and specificity, besides recoveries between 92 and 100\% to quantify peptides from bracatinga honeydew honey. The uniqueness and high response in mass spectrometry were backed by further complementary protein analysis (SDS-PAGE). The selected marker peptides EALPHVPIFDR (MRJP 1), ILGANVK (MRJP 2), TFVTIER (MRJP 3), QNIDVVAR (MRJP 4), FINNDYNFNEVNFR (MRJP 5) and LLQPYPDWSWTK (MRJP 7), quantified by LC-QqQ-MS/MS, highlighted that the content of QNIDVVAR from MRJP 4 could be used to differentiate bracatinga honeydew honey from floral honeys (p < 0.05) as a potential marker for its authentication. Finally, principal components analysis highlighted the QNIDVVAR content as a good descriptor of the analyzed bracatinga honeydew honey samples.},
  language  = {en}
}