TY - JOUR
T1 - An efficient method for medium throughput screening of cuticular wax composition in different plant species
AU - Fernandez-Moreno, JP
AU - Malitsky, Sergey
AU - Lashbrooke, Justin
AU - Biswal, AK
AU - Racovita, RC
AU - Mellerowicz, EJ
AU - Jetter, R
AU - Orzaez, D
AU - Aharoni, Asaph
AU - Granell, A
N1 - MINECO [BIO2013-42193-R]; EC [SFS7a-2014, 634561]; FPU-MECD [AP-2007-01905]; Israel Science Foundation (ISF) [646/11]; COST [FA1106]
PY - 2016/3/8
Y1 - 2016/3/8
N2 - Introduction: Most aerial plant organs are covered by a cuticle, which largely consists of cutin and wax. Cuticular waxes are mixtures of dozens of compounds, mostly very-long-chain aliphatics that are easily extracted by solvents. Over the last four decades, diverse cuticular wax analysis protocols have been developed, most of which are complex and time-consuming, and need to be adapted for each plant species or organ. Plant genomics and breeding programs often require mid-throughput metabolic phenotyping approaches to screen large numbers of individuals and obtain relevant biological information. Objectives: To generate a fast, simple and user-friendly methodology able to capture most wax complexity independently of the plant, cultivar and organ. Methods: Here we present a simple GC–MS method for screening relatively small wax amounts, sampled by short extraction with a versatile, uniform solvent. The method will be tested and validated in leaves and fruits from three different crop species: tomato (Solanum lycopersicum), apple (Malus domestica) and hybrid aspen (Populus tremula × tremuloides). Results: Consistent results were obtained in tomato cultivar M82 across three consecutive years (2010–2012), two organs (leaf and fruit), and also in two different tomato (M82 and MicroTom) and apple (Golden Delicious and Granny Smith) cultivars. Our results on tomato wax composition match those reported previously, while our apple and hybrid aspen analyses provide the first comprehensive cuticular wax profile of these species. Conclusion: This protocol allows standardized identification and quantification of most cuticular wax components in a range of species.
AB - Introduction: Most aerial plant organs are covered by a cuticle, which largely consists of cutin and wax. Cuticular waxes are mixtures of dozens of compounds, mostly very-long-chain aliphatics that are easily extracted by solvents. Over the last four decades, diverse cuticular wax analysis protocols have been developed, most of which are complex and time-consuming, and need to be adapted for each plant species or organ. Plant genomics and breeding programs often require mid-throughput metabolic phenotyping approaches to screen large numbers of individuals and obtain relevant biological information. Objectives: To generate a fast, simple and user-friendly methodology able to capture most wax complexity independently of the plant, cultivar and organ. Methods: Here we present a simple GC–MS method for screening relatively small wax amounts, sampled by short extraction with a versatile, uniform solvent. The method will be tested and validated in leaves and fruits from three different crop species: tomato (Solanum lycopersicum), apple (Malus domestica) and hybrid aspen (Populus tremula × tremuloides). Results: Consistent results were obtained in tomato cultivar M82 across three consecutive years (2010–2012), two organs (leaf and fruit), and also in two different tomato (M82 and MicroTom) and apple (Golden Delicious and Granny Smith) cultivars. Our results on tomato wax composition match those reported previously, while our apple and hybrid aspen analyses provide the first comprehensive cuticular wax profile of these species. Conclusion: This protocol allows standardized identification and quantification of most cuticular wax components in a range of species.
UR - http://www.scopus.com/inward/record.url?scp=84960418281&partnerID=8YFLogxK
U2 - https://doi.org/10.1007/s11306-016-0982-0
DO - https://doi.org/10.1007/s11306-016-0982-0
M3 - مقالة
SN - 1573-3882
VL - 12
JO - Metabolomics
JF - Metabolomics
M1 - 73
ER -