Summary of Study ST002430

This data is available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench, https://www.metabolomicsworkbench.org, where it has been assigned Project ID PR001563. The data can be accessed directly via it's Project DOI: 10.21228/M8NX4M This work is supported by NIH grant, U2C- DK119886.

See: https://www.metabolomicsworkbench.org/about/howtocite.php

This study contains a large results data set and is not available in the mwTab file. It is only available for download via FTP as data file(s) here.

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Study ID	ST002430
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
Submit Date	2022-09-28
Publications	https://doi.org/10.1038/s41598-021-97835-x
Raw Data Available	Yes
Raw Data File Type(s)	mzXML
Analysis Type Detail	LC-MS
Release Date	2023-01-20
Release Version	1

Select appropriate tab below to view additional metadata details:

Project:

Project ID:	PR001563
Project DOI:	doi: 10.21228/M8NX4M
Project Title:	Insights from a Multi-Omics Integration (MOI) Study in Oil Palm (Elaeis guineensis Jacq.) Response to Abiotic Stresses: Part One—Salinity
Project Type:	Multi-Omics Integration (MOI) Study
Project Summary:	Oil palm (Elaeis guineensis Jacq.) is the number one source of consumed vegetable oil nowadays. It is cultivated in areas of tropical rainforest, where it meets its natural condition of high rainfall throughout the year. The palm oil industry faces criticism due to a series of practices that was considered not environmentally sustainable, and it finds itself under pressure to adopt new and innovative procedures to reverse this negative public perception. Cultivating this oilseed crop outside the rainforest zone is only possible using artificial irrigation. Close to 30% of the world’s irrigated agricultural lands also face problems due to salinity stress. Consequently, the research community must consider drought and salinity together when studying to empower breeding programs in order to develop superior genotypes adapted to those potential new areas for oil palm cultivation. Multi-Omics Integration (MOI) offers a new window of opportunity for the non-trivial challenge of unraveling the mechanisms behind multigenic traits, such as drought and salinity tolerance. The current study carried out a comprehensive, large-scale, single-omics analysis (SOA), and MOI study on the leaves of young oil palm plants submitted to very high salinity stress. Taken together, a total of 1239 proteins were positively regulated, and 1660 were negatively regulated in transcriptomics and proteomics analyses. Meanwhile, the metabolomics analysis revealed 37 metabolites that were upreg- ulated and 92 that were downregulated. After performing SOA, 436 differentially expressed (DE) full-length transcripts, 74 DE proteins, and 19 DE metabolites underwent MOI analysis, revealing sev- eral pathways affected by this stress, with at least one DE molecule in all three omics platforms used. The Cysteine and methionine metabolism (map00270) and Glycolysis/Gluconeogenesis (map00010) pathways were the most affected ones, each one with 20 DE molecules.
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/10.3390/plants11131755

Subject:

Subject ID:	SU002519
Subject Type:	Plant
Subject Species:	Elaeis guineensis Jacq.
Taxonomy ID:	NCBI:txid51953
Species Group:	Plants

Factors:

Subject type: Plant; Subject species: Elaeis guineensis Jacq. (Factor headings shown in green)

mb_sample_id	local_sample_id	Group
SA242925	OilPalm_Drought_Control_R2_NEG	Control
SA242926	OilPalm_Drought_Control_R3_NEG	Control
SA242927	OilPalm_Drought_Control_R4_NEG	Control
SA242928	OilPalm_Drought_Control_R1_POS	Control
SA242929	OilPalm_Drought_Control_R1_NEG	Control
SA242930	OilPalm_Drought_Control_R2_POS	Control
SA242931	OilPalm_Drought_Control_R4_POS	Control
SA242932	OilPalm_Drought_Control_R3_POS	Control
SA242933	OilPalm_Drought_Stressed_R3_NEG	Stressed
SA242934	OilPalm_Drought_Stressed_R4_NEG	Stressed
SA242935	OilPalm_Drought_Stressed_R4_POS	Stressed
SA242936	OilPalm_Drought_Stressed_R2_NEG	Stressed
SA242937	OilPalm_Drought_Stressed_R1_NEG	Stressed
SA242938	OilPalm_Drought_Stressed_R2_POS	Stressed
SA242939	OilPalm_Drought_Stressed_R3_POS	Stressed
SA242940	OilPalm_Drought_Stressed_R1_POS	Stressed

Showing results 1 to 16 of 16

Showing results 1 to 16 of 16

Collection:

Collection ID:	CO002512
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 ID:	TR002531
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).

Treatment ID:

TR002531

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).

Sample Preparation:

Sampleprep ID:	SP002525
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).

Sampleprep ID:

SP002525

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).

Combined analysis:

Analysis ID	AN003955	AN003956
Analysis type	MS	MS
Chromatography type	Reversed phase	Reversed phase
Chromatography system	Shimadzu Nexera X2	Shimadzu Nexera X2
Column	Waters Acquity BEH C18 (150 x 2mm, 1.7um)	Waters Acquity BEH C18 (150 x 2mm, 1.7um)
MS Type	ESI	ESI
MS instrument type	QTOF	QTOF
MS instrument name	Bruker maXis Impact qTOF	Bruker maXis Impact qTOF
Ion Mode	POSITIVE	NEGATIVE
Units	Peak intensity	Peak intensity

Chromatography:

Chromatography ID:	CH002927
Instrument Name:	Shimadzu Nexera X2
Column Name:	Waters Acquity BEH C18 (150 x 2mm, 1.7um)
Column Temperature:	-
Flow Gradient:	-
Flow Rate:	-
Solvent A:	-
Solvent B:	-
Chromatography Type:	Reversed phase

MS:

MS ID:	MS003690
Analysis ID:	AN003955
Instrument Name:	Bruker maXis Impact qTOF
Instrument Type:	QTOF
MS Type:	ESI
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).
Ion Mode:	POSITIVE

MS ID:	MS003691
Analysis ID:	AN003956
Instrument Name:	Bruker maXis Impact qTOF
Instrument Type:	QTOF
MS Type:	ESI
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).
Ion Mode:	NEGATIVE