Identification of Potential Metabolites Mediating Bird's Selective Feeding on Flowers
Authors: Gesang Pingcuo
Jian Shi
Xiuli Zeng
Hong Ying
Shuo Wang
Yongning Cui
Hu Zeng
Fan Zhao
Shanshan Zhang
Journal: BioMed research international (2019)
Discipline: BIOLOGY & BIOCHEMISTRY
Keywords: peach orchards; birds; Prunus mira; flower metabolites; selective feeding behavior
Affiliations: The Ministry of Agriculture of Qinghai-Tibet Plateau Fruit Trees Scientific Observation Test Station, Lhasa, Tibet 850032, China., Institute of Vegetables, Tibet Academy of Agricultural and Animal Husbandry Sciences, Lhasa, Tibet 850002, China., Wuhan Metware Biotechnology Co., Ltd, Wuhan 430070, China.

Abstract:  In peach orchards, birds severely damage flowers during blossom season, decreasing the fruit yield potential. However, the wild peach species Prunus mira shows intraspecific variations of bird damage, indicating that some of the wild trees have developed strategies to avert bird foraging. Motivated by this observation, we formulated the present study to identify the potential flower metabolites mediating the bird's selective feeding behavior in P. mira flowers. The birds' preferred (FG) and avoided (BFT) flowers were collected from wild P. mira trees at three different locations, and their metabolite contents were detected, quantified, and compared. The widely-targeted metabolomics approach was employed to detect a diverse set of 603 compounds, predominantly, organic acids, amino acid derivatives, nucleotide and its derivatives, and flavones. By quantitatively comparing the metabolite contents between FG and BFT, three candidate metabolites, including Eriodictiol 6-C-hexoside 8-C-hexoside-O-hexoside, Luteolin O-hexosyl-O-hexosyl-O-hexoside, and Salvianolic acid A, were differentially accumulated and showed the same pattern across the three sampling locations. Distinctly, Salvianolic acid A was abundantly accumulated in FG but absent in BFT, implying that it may be the potential metabolite attracting birds in some P. mira flowers. Overall, this study sheds light on the diversity of the floral metabolome in P. mira and suggests that the bird's selective feeding behavior may be mediated by variations in floral metabolite contents. 

Retracted: No

PubPeer comments:
 The retention time of 105 detected metabolites is less than 1 minute uff1fuff08HPLC:column, Waters ACQUITY UPLC HSS T3 C18 (2.1 mmu2217100 mm); solvent system, water (0.04% acetic acid):acetonitrile (0.04% acetic acid); gradient program, 100:0V V at 0 min, 5:95V V at 11 min, 5:95V V at 12 min, 95:5V V at 12.1 min, 95:5V V at 15 minuff09. It is difficult to understand how to accurately identify metabolitesuff0cmany metabolites have the same Q1,Q3 and RTuff0chow to distinguish these metabolitesuff1fuff08Supplementary Materials uff09uff0cThe author didnu2018t show the original mass spectrum data.   , 
 $**The retention time of 105 detected metabolites is less than 1 minute uff1fuff08HPLC:column, Waters ACQUITY UPLC HSS T3 C18 (2.1 mmu2217100 mm); solvent system, water (0.04% acetic acid):acetonitrile (0.04% acetic acid); gradient program, 100:0V V at 0 min, 5:95V V at 11 min, 5:95V V at 12 min, 95:5V V at 12.1 min, 95:5V V at 15 minuff09. It is difficult to understand how to accurately identify metabolitesuff0cmany metabolites have the same Q1,Q3 and RTuff0chow to distinguish these metabolitesuff1fuff08Supplementary Materials uff09uff0cThe author didnu2018t show the original mass spectrum data.**$  , 
 Papers from **Wuhan Metware Biotechnology** Co., Ltd, Wuhan 430070, China...... 672 metabolites were identified, retention time of 120 detected metabolites is less than 1 minute,metabolites have the same Q1,Q3 and RT?  , 
 #3 u3010The retention time of 105 detected metabolites is less than 1 minute uff1fuff08HPLC:column, Waters ACQUITY UPLC HSS T3 C18 (2.1 mmu2217100 mm); solvent system, water (0.04% acetic acid):acetonitrile (0.04% acetic acid); gradient program, 100:0V V at 0 min, 5:95V V at 11 min, 5:95V V at 12 min, 95:5V V at 12.1 min, 95:5V V at 15 minuff09. It is difficult to understand how to accurately identify metabolitesuff0cmany metabolites have the same Q1,Q3 and RTuff0chow to distinguish these metabolitesuff1fuff08Supplementary Materials uff09uff0cThe author didnu2018t show the original mass spectrum data.u3011 1.Wuhan mware biotechnology adopts MRM detection mode, 1) In theory, qtrap 6500 only needs 0.8 seconds in one cycle, and 75 points (60 seconds 0.8 seconds) can be collected in one minute; 2) An ion needs 5-10 milliseconds, and 80-160 ions (0.8 0.01-0.8 0.05) can be collected at one point; 3) A compound needs 3 ions, so 26-53 metabolic material information (80 3-160 3) can be collected at one point 4) 4) So theoretically, more than 2000 metabolites (75 * 30) can be collected in one minuteuff1b So it is possible to detect 120 metabolites in one minuteu3002 We use RT, Q1, Q3, DP, CE to detect metabolic substances; at present, we can t distinguish isomers.But the key of biological problems in this paper is Salvianolic acid A. We have further targeted detection research, and new results will be published in the near future. u3010Papers from Wuhan Metware Biotechnology Co., Ltd, Wuhan 430070, China...... 672 metabolites were identified, retention time of 120 detected metabolites is less than 1 minute,metabolites have the same Q1,Q3 and RT? u3011 The question of wh testing 120 metabolites in one minute has been answered in the above 1.Wuhan Metware Biotechnology Co., Ltd, first established a metabolism database MWDB1uff0c2, which has been used in many research articles3uff0c4uff0c5. 1.Chen W , Gong L , Guo Z , et al. A Novel Integrated Method for Large-Scale Detection, Identification, and Quantification of Widely Targeted Metabolites: Application in the Study of Rice Metabolomics[J]. Molecular plantuff0c 2013, 006(006):1769-1780. 2.(2014). Genome-wide association analyses provide genetic and biochemical insights into natural variation in rice metabolism. Nature Genetics, 46(7), 714-721. 3.Liu Y, Lv J, Liu Z, et al. Integrative analysis of metabolome and transcriptome reveals the mechanism of color formation in pepper fruit (Capsicum annuum L.)[J]. Food Chemistry, 2020, 306: 125629. 4.Transcriptomeu2002andu2002metabolomeu2002profilingu2002unveilu2002theu2002mechanismsu2002ofu2002Ziziphusu2002jujubau2002Mill.u2002peelu2002colorationFood ChemistryVolume 31215 May 2020Article 125903 5.Ying, S., Su, M., Wu, Y., Zhou, L., Fu, R., Li, Y., Guo, H., Luo, J., Wang, S.# and Zhang, Y#. (2020)Trichome regulator SlMIXTAu2010like directly manipulates primary metabolism in tomato fruit. Plant Biotechnology Journal18:354-363 ,