{
"METABOLOMICS WORKBENCH":{"STUDY_ID":"ST002430","ANALYSIS_ID":"AN003955","VERSION":"1","CREATED_ON":"January 5, 2023, 5:06 pm"},

"PROJECT":{"PROJECT_TITLE":"Insights from a Multi-Omics Integration (MOI) Study in Oil Palm (Elaeis guineensis Jacq.) Response to Abiotic Stresses: Part Two—Drought","PROJECT_TYPE":"Multi-Omics Integration (MOI) Study","PROJECT_SUMMARY":"Drought and salinity are two of the most severe abiotic stresses affecting agriculture Worldwide and bear some similarities in the response of plants to them. The first is also known as osmotic stress and shows similarities mainly with the osmotic effect, the first phase of salinity stress. Multi-Omics Integration (MOI) offers a new opportunity for the non-trivial challenge of unraveling the mechanisms behind multigenic traits, such as drought and salinity resistance. The current study carried out a comprehensive, large-scale, single-omics analysis (SOA) and MOI studies on the leaves of young oil palm plants submitted to water deprivation. After performing SOA, 1,955 DE enzymes from transcriptomics analysis, 131 DE enzymes from proteomics analysis, and 269 DE metabolites underwent MOI analysis, revealing several pathways affected by this stress, with at least one DE molecule in all three omics platforms used. Besides, the similarities and dissimilarities in the molecular response of those plants to those two abiotic stresses underwent mapping. Cysteine and methionine metabolism (map00270) was the most affected pathway in all scenarios evaluated. The correlation analysis revealed that 91.55% of those enzymes expressed under both stresses had similar qualitative profiles, corroborating the already known fact that plant responses to drought and salinity show several similarities. At last, the results shed light on some candidate genes for engineering crop species resilient to both abiotic stresses.","INSTITUTE":"The Brazilian Agricultural Research Corporation (Embrapa)","DEPARTMENT":"Embrapa Agroenergy","LABORATORY":"Genetics and Plant Biotechnology","LAST_NAME":"Souza Jr","FIRST_NAME":"Manoel Teixeira","ADDRESS":"Parque Estacao Biologica, Final Avenida W3 Norte - Asa Norte, Brasilia, Distrito Federal, 70770901, Brazil","EMAIL":"manoel.souza@embrapa.br","PHONE":"+55.61.3448.3210","FUNDING_SOURCE":"FINEP (01.13.0315.00)","PROJECT_COMMENTS":"DendêPalm Project","PUBLICATIONS":"https://doi.org/10.1038/s41598-021-97835-x"},

"STUDY":{"STUDY_TITLE":"Insights from a Multi-Omics Integration (MOI) Study in Oil Palm (Elaeis guineensis Jacq.) Response to Abiotic Stresses: Part Two—Drought","STUDY_TYPE":"Multi-Omics Integration (MOI) Study","STUDY_SUMMARY":"Drought and salinity are two of the most severe abiotic stresses affecting agriculture Worldwide and bear some similarities in the response of plants to them. The first is also known as osmotic stress and shows similarities mainly with the osmotic effect, the first phase of salinity stress. Multi-Omics Integration (MOI) offers a new opportunity for the non-trivial challenge of unraveling the mechanisms behind multigenic traits, such as drought and salinity resistance. The current study carried out a comprehensive, large-scale, single-omics analysis (SOA) and MOI studies on the leaves of young oil palm plants submitted to water deprivation. After performing SOA, 1,955 DE enzymes from transcriptomics analysis, 131 DE enzymes from proteomics analysis, and 269 DE metabolites underwent MOI analysis, revealing several pathways affected by this stress, with at least one DE molecule in all three omics platforms used. Besides, the similarities and dissimilarities in the molecular response of those plants to those two abiotic stresses underwent mapping. Cysteine and methionine metabolism (map00270) was the most affected pathway in all scenarios evaluated. The correlation analysis revealed that 91.55% of those enzymes expressed under both stresses had similar qualitative profiles, corroborating the already known fact that plant responses to drought and salinity show several similarities. At last, the results shed light on some candidate genes for engineering crop species resilient to both abiotic stresses.","INSTITUTE":"The Brazilian Agricultural Research Corporation (Embrapa)","DEPARTMENT":"Embrapa Agroenergy","LABORATORY":"Genetics and Plant Biotechnology","LAST_NAME":"Souza Jr","FIRST_NAME":"Manoel Teixeira","ADDRESS":"Parque Estacao Biologica, Final Avenida W3 Norte - Asa Norte, Brasilia, Distrito Federal, 70770901, Brazil","EMAIL":"manoel.souza@embrapa.br","PHONE":"+55.61.3448.3210","PUBLICATIONS":"https://doi.org/10.1038/s41598-021-97835-x"},

"SUBJECT":{"SUBJECT_TYPE":"Plant","SUBJECT_SPECIES":"Elaeis guineensis Jacq.","TAXONOMY_ID":"NCBI:txid51953"},
"SUBJECT_SAMPLE_FACTORS":[
{
"Subject ID":"-",
"Sample ID":"OilPalm_Drought_Control_R1_POS",
"Factors":{"Group":"Control"},
"Additional sample data":{"RAW_FILE_NAME":"OilPalm_Drought_Control_R1_POS.mzXML"}
},
{
"Subject ID":"-",
"Sample ID":"OilPalm_Drought_Control_R2_POS",
"Factors":{"Group":"Control"},
"Additional sample data":{"RAW_FILE_NAME":"OilPalm_Drought_Control_R2_POS.mzXML"}
},
{
"Subject ID":"-",
"Sample ID":"OilPalm_Drought_Control_R3_POS",
"Factors":{"Group":"Control"},
"Additional sample data":{"RAW_FILE_NAME":"OilPalm_Drought_Control_R3_POS.mzXML"}
},
{
"Subject ID":"-",
"Sample ID":"OilPalm_Drought_Control_R4_POS",
"Factors":{"Group":"Control"},
"Additional sample data":{"RAW_FILE_NAME":"OilPalm_Drought_Control_R4_POS.mzXML"}
},
{
"Subject ID":"-",
"Sample ID":"OilPalm_Drought_Stressed_R1_POS",
"Factors":{"Group":"Stressed"},
"Additional sample data":{"RAW_FILE_NAME":"OilPalm_Drought_Stressed_R1_POS.mzXML"}
},
{
"Subject ID":"-",
"Sample ID":"OilPalm_Drought_Stressed_R2_POS",
"Factors":{"Group":"Stressed"},
"Additional sample data":{"RAW_FILE_NAME":"OilPalm_Drought_Stressed_R2_POS.mzXML"}
},
{
"Subject ID":"-",
"Sample ID":"OilPalm_Drought_Stressed_R3_POS",
"Factors":{"Group":"Stressed"},
"Additional sample data":{"RAW_FILE_NAME":"OilPalm_Drought_Stressed_R3_POS.mzXML"}
},
{
"Subject ID":"-",
"Sample ID":"OilPalm_Drought_Stressed_R4_POS",
"Factors":{"Group":"Stressed"},
"Additional sample data":{"RAW_FILE_NAME":"OilPalm_Drought_Stressed_R4_POS.mzXML"}
},
{
"Subject ID":"-",
"Sample ID":"OilPalm_Drought_Control_R1_NEG",
"Factors":{"Group":"Control"},
"Additional sample data":{"RAW_FILE_NAME":"OilPalm_Drought_Control_R1_NEG.mzXML"}
},
{
"Subject ID":"-",
"Sample ID":"OilPalm_Drought_Control_R2_NEG",
"Factors":{"Group":"Control"},
"Additional sample data":{"RAW_FILE_NAME":"OilPalm_Drought_Control_R2_NEG.mzXML"}
},
{
"Subject ID":"-",
"Sample ID":"OilPalm_Drought_Control_R3_NEG",
"Factors":{"Group":"Control"},
"Additional sample data":{"RAW_FILE_NAME":"OilPalm_Drought_Control_R3_NEG.mzXML"}
},
{
"Subject ID":"-",
"Sample ID":"OilPalm_Drought_Control_R4_NEG",
"Factors":{"Group":"Control"},
"Additional sample data":{"RAW_FILE_NAME":"OilPalm_Drought_Control_R4_NEG.mzXML"}
},
{
"Subject ID":"-",
"Sample ID":"OilPalm_Drought_Stressed_R1_NEG",
"Factors":{"Group":"Stressed"},
"Additional sample data":{"RAW_FILE_NAME":"OilPalm_Drought_Stressed_R1_NEG.mzXML"}
},
{
"Subject ID":"-",
"Sample ID":"OilPalm_Drought_Stressed_R2_NEG",
"Factors":{"Group":"Stressed"},
"Additional sample data":{"RAW_FILE_NAME":"OilPalm_Drought_Stressed_R2_NEG.mzXML"}
},
{
"Subject ID":"-",
"Sample ID":"OilPalm_Drought_Stressed_R3_NEG",
"Factors":{"Group":"Stressed"},
"Additional sample data":{"RAW_FILE_NAME":"OilPalm_Drought_Stressed_R3_NEG.mzXML"}
},
{
"Subject ID":"-",
"Sample ID":"OilPalm_Drought_Stressed_R4_NEG",
"Factors":{"Group":"Stressed"},
"Additional sample data":{"RAW_FILE_NAME":"OilPalm_Drought_Stressed_R4_NEG.mzXML"}
}
],
"COLLECTION":{"COLLECTION_SUMMARY":"The oil palm plants used in this study are clones of the ones used in the Bittencourt et al. (2022) study. All plants—from both studies—came from the same embryogenic calluses. The young oil palm plants used in both studies were clones regenerated out of embryogenic calluses obtained from the leaves of an adult plant—genotype AM33, a Deli x Ghana from ASD Costa Rica; and were subjected to treatments when they were in the growth stage known as “bifid” saplings. Before starting the experiments, plants were standardized according to their developmental stage, size, and the number of leaves. The experiment consisted of two water availability levels (field capacity—control and water deprivation—stressed), with four replicates in a completely randomized design. For the metabolomics analysis, we collected the apical leaves from control and stressed plants 14 days after imposing the treatments (DAT).","SAMPLE_TYPE":"Plant"},

"TREATMENT":{"TREATMENT_SUMMARY":"The experiment consisted of treatments—control and drought-stressed plants—with four plants kept in a substrate in the field capacity (control), and four plants submitted to drought stress. The young oil palm plants were subjected to treatments when they were in the growth stage known as “bifid” saplings. Drought stress consisted of total suppression of irrigation for 14 consecutive days. At the end of this period, the substrate water potential, as measured by the water potential meter Decagon mod. WP4C (Decagon Devices, Pullman, WA, USA), was 0.19 ± 0.03 MPa (control) and − 13.61 ± 1.79 MPa (drought stress), while the relative water content of leaves was 90.50 ± 0.95% (control) and 49.18 ± 9.76% (stressed plants). Before the onset of drought stress, oil palm leaves had the highest gas exchange rates, as measured by an infrared gas analyzer Li-Cor model 6400XT (Li-Cor, Lincoln, NE, USA). Under drought, leaf gas exchange rates in drought-stressed plants dropped to negligible values (data not shown)."},

"SAMPLEPREP":{"SAMPLEPREP_SUMMARY":"Leaf samples with approximately 50 mg were collected for the metabolomics analysis; four replicates per plant. After harvesting, samples were immediately frozen in liquid nitrogen and stored at − 80 °C until metabolites extraction and analysis. Each sample was ground in a ball mill (Biospec Products, USA) before solvent extraction. Metabolites were extracted using an adapted protocol from The Max Planck Institute, called All-in-One, which provides a polar fraction for secondary metabolite analysis, a nonpolar fraction for lipidomics, and a protein pellet for proteomics; all obtained from the same plant sample. Each ground sample was added to a microtube and mixed with 1 mL of a methanol and methyl-tert-butyl-ether (1:3) solution at − 20°C. After homogenization, they were incubated at 4 °C for 10 min. Each microtube was ultrasonicated in an ice bath for another 10 min. Then, 500 μL of a methanol and water (1:3) solution was added to the microtube before centrifugation (12,000 rpm at 4 °C for 5 min). Three phases were separate: an upper non-polar (green), a lower polar (brown), and a remaining protein pellet. Samples were transferred to fresh microtubes and vacuum-dried in a speed vac (Centrivap, Labconco, Kansas City, MO, USA) overnight at room temperature (~ 22 °C)."},

"CHROMATOGRAPHY":{"CHROMATOGRAPHY_TYPE":"Reversed phase","INSTRUMENT_NAME":"Shimadzu Nexera X2","COLUMN_NAME":"Waters Acquity BEH C18 (150 x 2mm, 1.7um)","SOLVENT_A":"-","SOLVENT_B":"-","FLOW_GRADIENT":"-","FLOW_RATE":"-","COLUMN_TEMPERATURE":"-"},

"ANALYSIS":{"ANALYSIS_TYPE":"MS"},

"MS":{"INSTRUMENT_NAME":"Bruker maXis Impact qTOF","INSTRUMENT_TYPE":"QTOF","MS_TYPE":"ESI","ION_MODE":"POSITIVE","MS_COMMENTS":"High-resolution mass spectrometry (HRMS) was performed in a MaXis 4G Q-TOF MS system (Bruker Daltonics, Germany) using an electrospray source in the positive and negative ion modes (ESI(+)–MS and ESI(−)–MS). The MS instrument settings used were: endplate offset, 500 V; capillary voltage, 3800 V; nebulizer pressure, 4 bar; dry gas flow, 9 L/min, dry temperature, 200 °C; and column temperature, 40 °C. The acquisition spectra rate was 3.00 Hz, monitoring a mass range from 70 to 1200 m/z. Sodium formate solution (10 mM NaOH solution in 50/50 v/v isopropanol/water containing 0.2% formic acid) was directly injected through a 6-port valve at the beginning of each chromatographic run to external calibration. UHPLC–MS data was acquired by the HyStar Application version 3.2 (Bruker Daltonics, Germany), and data processing was done using Data Analysis 4.2 (Bruker Daltonics, Germany).","MS_RESULTS_FILE":"ST002430_AN003955_Results.txt UNITS:Peak intensity Has m/z:Yes Has RT:No RT units:No RT data"}

}