Summary of Study ST003219

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 PR002007. The data can be accessed directly via it's Project DOI: 10.21228/M8624Z 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.

Show all samples  |  Perform analysis on untargeted data  
Download mwTab file (text)   |  Download mwTab file(JSON)   |  Download data files (Contains raw data)
Study IDST003219
Study TitleEVALUATION OF THE INFLUENCE OF ENVIRONMENTAL CONDITIONS ON THE METABOLOME OF Psychotria viridis LEAVES Ruiz & Pav.: Metabolomics approach
Study SummaryPsychotria viridis Ruiz & Pav. has gained particular attention due to its use in the ayahuasca drink. This work aims to deepen the understanding of the composition of specialized metabolites in the leaves of Psychotria viridis Ruiz & Pav. and investigate the influence of the growing environment as well as seasonality on the composition. The specimens were grown in the open field and others in the shaded environment of rubber tree (Hevea brasiliensis L.) cultivation. These specimens make up a clonal population of the mother-plant. The collection was made in the four seasons. After a three-phase extraction method on the leaves, the aqueous phase was analyzed on an ultra-high performance liquid chromatography coupled to electrospray ionization and Orbitrap mass spectrometry (UHPLC-ESI-Orbitrap-MS) system. Acquired data were processed using MS-DIAL 4.9 and MetaboAnalyst 5.0 for multivariate and pathway activity analysis. Chemical variations were investigated employing principal component analysis (PCA), hierarchical cluster analysis (HCA) and partial least squares discriminant analysis (PLS-DA). Through PCA was shown that samples tend to differentiate according seasonality and according cultivation area. The most important identified compounds for differentiation according to the seasonality were flavonoids. The pathways with significant variation in response to the seasonality were related to energy generation through biosynthesis and consumption of carbohydrates: Ascorbate and aldarate metabolism, Pentose and glucuronate interconversions and Citrate cycle. On the other hand, Biosynthesis of flavonoid, flavones and flavonols were the biochemical pathways associated with the influence of the cultivation location in full sun or shade in an intercrop being a plant response to oxidative stress. Keywords: Psychotria viridis, seasonality, abiotic stress, liquid chromatography-mass spectrometry; metabolomics.
Institute
University of Campinas
Last NameMatos
First NameTaynara
AddressRua Josué de Castro, s/n – Cidade Universitária, 13083-970, Campinas – SP, Brazil
Emailt262827@dac.unicamp.br
Phone+5585996154192
Submit Date2024-05-22
Num Groups3
Raw Data AvailableYes
Raw Data File Type(s)raw(Thermo)
Analysis Type DetailLC-MS
Release Date2025-03-13
Release Version1
Taynara Matos Taynara Matos
https://dx.doi.org/10.21228/M8624Z
ftp://www.metabolomicsworkbench.org/Studies/ application/zip

Select appropriate tab below to view additional metadata details:


Project:

Project ID:PR002007
Project DOI:doi: 10.21228/M8624Z
Project Title:EVALUATION OF THE INFLUENCE OF ENVIRONMENTAL CONDITIONS ON THE METABOLOME OF Psychotria viridis LEAVES Ruiz & Pav.
Project Type:MS untargeted analysis
Project Summary:Elucidate the metabolic changes in the leaves of Psychotria viridis Ruiz & Pav. cultivated in different environmental conditions through a multiplatform global metabolomics and lipidomics approach. Evaluate the possibility of differentiating leaf lipidome and metabolome samples by season and place of cultivation; Identify which metabolites would be statistically significant for differentiating the samples; Establish the most altered metabolic pathways when comparing environmental conditions; Correlate the differential metabolites with the metabolic pathways altered due to the environmental conditions of collection and cultivation of P. viridis leaves.
Institute:University of Campinas
Department:Chemistry's Institute
Laboratory:Laboratory of Bioanalytics and Integrated Omics
Last Name:Matos
First Name:Taynara
Address:Rua Josué de Castro, s/n – Cidade Universitária, 13083-970, Campinas – SP, Brazil
Email:t262827@dac.unicamp.br
Phone:(85)996154192
Project Comments:Study part 1 of 2

Subject:

Subject ID:SU003338
Subject Type:Plant
Subject Species:Psychotria viridis
Species Group:Plants

Factors:

Subject type: Plant; Subject species: Psychotria viridis (Factor headings shown in green)

mb_sample_id local_sample_id Season collection Treatment cultivation Sample source
SA351836FE6A_NFall Shade Leaves
SA351837FE1A_NFall Shade Leaves
SA351838FF1A_NFall Shade Leaves
SA351839FC6A_PFall Shade Leaves
SA351840FE6A_PFall Shade Leaves
SA351841FA6A_PFall Shade Leaves
SA351842FC1A_PFall Shade Leaves
SA351843FC1A_NFall Shade Leaves
SA351844FA6A_NFall Shade Leaves
SA351845FB1A_NFall Shade Leaves
SA351846FD1A_NFall Shade Leaves
SA351847FB6A_NFall Shade Leaves
SA351848FD6A_NFall Shade Leaves
SA351849FA1A_NFall Shade Leaves
SA351850FF6A_NFall Shade Leaves
SA351851FA1A_PFall Shade Leaves
SA351852FC6A_NFall Shade Leaves
SA351853FF6A_PFall Shade Leaves
SA351854FD1A_PFall Shade Leaves
SA351855FB1A_PFall Shade Leaves
SA351856FF1A_PFall Shade Leaves
SA351857FE1A_PFall Shade Leaves
SA351858FB6A_PFall Shade Leaves
SA351859FD6A_PFall Shade Leaves
SA351860FG1A_PFall Sun Leaves
SA351861FH1A_NFall Sun Leaves
SA351862FK6A_NFall Sun Leaves
SA351863FG1A_NFall Sun Leaves
SA351864FG6A_NFall Sun Leaves
SA351865FJ1A_NFall Sun Leaves
SA351866FH6A_PFall Sun Leaves
SA351867FJ1A_PFall Sun Leaves
SA351868FG6A_PFall Sun Leaves
SA351869FH1A_PFall Sun Leaves
SA351870FJ6A_PFall Sun Leaves
SA351871FI1A_PFall Sun Leaves
SA351872FI6A_NFall Sun Leaves
SA351873FL1A_NFall Sun Leaves
SA351874FH6A_NFall Sun Leaves
SA351875FK1A_NFall Sun Leaves
SA351876FL6A_NFall Sun Leaves
SA351877FK6A_PFall Sun Leaves
SA351878FL6A_PFall Sun Leaves
SA351879FI1A_NFall Sun Leaves
SA351880FK1A_PFall Sun Leaves
SA351881FL1A_PFall Sun Leaves
SA351882FI6A_PFall Sun Leaves
SA351883FJ6A_NFall Sun Leaves
SA351884BExt2_PNot applicable Not applicable Blank
SA351885BCor2_PNot applicable Not applicable Blank
SA351886BExt1_PNot applicable Not applicable Blank
SA351887BExt2_NNot applicable Not applicable Blank
SA351888BCor1_NNot applicable Not applicable Blank
SA351889BCor2_NNot applicable Not applicable Blank
SA351890BCor1_PNot applicable Not applicable Blank
SA351891BExt1_NNot applicable Not applicable Blank
SA351892QC1_PNot applicable Not applicable Leaves
SA351893QC2_PNot applicable Not applicable Leaves
SA351894QC4_PNot applicable Not applicable Leaves
SA351895QCEq_4_PNot applicable Not applicable Leaves
SA351896QC3_NNot applicable Not applicable Leaves
SA351897QCEq_3_PNot applicable Not applicable Leaves
SA351898QC4_NNot applicable Not applicable Leaves
SA351899QCEq_1_PNot applicable Not applicable Leaves
SA351900QCEq_2_PNot applicable Not applicable Leaves
SA351901QC2_NNot applicable Not applicable Leaves
SA351902QC5_PNot applicable Not applicable Leaves
SA351903QC8_PNot applicable Not applicable Leaves
SA351904QCEq_2_NNot applicable Not applicable Leaves
SA351905QCEq_1_NNot applicable Not applicable Leaves
SA351906QCEq_3_NNot applicable Not applicable Leaves
SA351907QCEq_4_NNot applicable Not applicable Leaves
SA351908QC6_PNot applicable Not applicable Leaves
SA351909QC1_NNot applicable Not applicable Leaves
SA351910QC7_PNot applicable Not applicable Leaves
SA351911QC8_NNot applicable Not applicable Leaves
SA351912QC3_PNot applicable Not applicable Leaves
SA351913QC5_NNot applicable Not applicable Leaves
SA351914QC7_NNot applicable Not applicable Leaves
SA351915QC6_NNot applicable Not applicable Leaves
SA351916SE6A_NSummer Shade Leaves
SA351917SC6A_NSummer Shade Leaves
SA351918SD1A_PSummer Shade Leaves
SA351919SC6A_PSummer Shade Leaves
SA351920SF6A_NSummer Shade Leaves
SA351921SE6A_PSummer Shade Leaves
SA351922SA1A_PSummer Shade Leaves
SA351923SB6A_NSummer Shade Leaves
SA351924SD6A_NSummer Shade Leaves
SA351925SC1A_PSummer Shade Leaves
SA351926SF1A_NSummer Shade Leaves
SA351927SA6A_PSummer Shade Leaves
SA351928SE1A_NSummer Shade Leaves
SA351929SB1A_PSummer Shade Leaves
SA351930SB6A_PSummer Shade Leaves
SA351931SD6A_PSummer Shade Leaves
SA351932SF1A_PSummer Shade Leaves
SA351933SE1A_PSummer Shade Leaves
SA351934SF6A_PSummer Shade Leaves
SA351935SA1A_NSummer Shade Leaves
Showing page 1 of 2     Results:    1  2  Next     Showing results 1 to 100 of 176

Collection:

Collection ID:CO003331
Collection Summary:4 leaves from different regions of each specimen were collected and stored in paper bags. The collection was carried out in the four seasons of the year: summer, winter, spring, and autumn. The spring samples remained in a paper bag longer than the other samples. Due to this difference in storage, it was decided not to continue the analyzes with them.
Sample Type:Plant
Storage Conditions:-80℃

Treatment:

Treatment ID:TR003347
Treatment Summary:After 24 h of collection, the samples were dried in an oven (40 ºC, 48 h), macerated with a mortar and pestle with the aid of liquid nitrogen, transferred to a glass tube and stored at -80 ºC until analysis.

Sample Preparation:

Sampleprep ID:SP003345
Sampleprep Summary:The biological material underwent a 3-phase extraction method. The separated and dried phases were stored at -80 ºC until chromatographic analysis. For metabolomics, the aqueous phase was resuspended in 1 mL mixture of solvents corresponding to the initial of the chromatographic run: 60% mobile phase A and 40% mobile phase B and filtered in 0.22 µL PVDF filter.
Processing Storage Conditions:-80℃

Combined analysis:

Analysis ID AN005278 AN005279
Analysis type MS MS
Chromatography type Reversed phase Reversed phase
Chromatography system Thermo UltiMate 3000 RSLCnano Thermo UltiMate 3000 RSLCnano
Column Merck Supelco Titan C18 (100 × 2.1 mm, 1.9 µm) Merck Supelco Titan C18 (100 × 2.1 mm, 1.9 µm)
MS Type ESI ESI
MS instrument type Orbitrap Orbitrap
MS instrument name Thermo Q Exactive Orbitrap Thermo Q Exactive Orbitrap
Ion Mode POSITIVE NEGATIVE
Units Peak area Peak area

Chromatography:

Chromatography ID:CH003993
Instrument Name:Thermo UltiMate 3000 RSLCnano
Column Name:Merck Supelco Titan C18 (100 × 2.1 mm, 1.9 µm)
Column Temperature:40
Flow Gradient:0.20 mL/min: 0-2 min, 3% B; 3.7-5.6 min, 20 % B; 7.4 min, 45% B; 9.3-14 65% and 16-20 min; 3% B.
Flow Rate:0.20 mL/min
Solvent A:100% Water; 0.1% formic acid
Solvent B:100% Acetronitrile; 0.1% formic acid
Chromatography Type:Reversed phase

MS:

MS ID:MS005009
Analysis ID:AN005278
Instrument Name:Thermo Q Exactive Orbitrap
Instrument Type:Orbitrap
MS Type:ESI
MS Comments:Data-dependent acquisition mode of the 5 most intense peaks. Full scan data were acquired between m/z 100 and 1500 in profile mode and at resolution 70000 (at m/z = 200). The automatic gain control was set as automatic gain control target at 1E6, 1 scan s-1, and injection time at 100 ms. Pre-processing data on MS-DIAL 4.9 software. The parameter analysis were setting with MS1 tolerance of 0.02 Da, MS2 tolerance 0.06 Da, MS1 and MS2 m/z 100-1500 range, maximum charged number 1; peak detection with 10000 of minimum peak height and mass slice width of 0.1 Da; deconvolution with MS/MS abundance cut off of 30 amplitude and sigma window value of 0.5; alignment parameters with retention time tolerance 0.5 min, MS1 tolerance of 0.02 Da and removed features based on blank information.
Ion Mode:POSITIVE
Spray Voltage:+3.5
  
MS ID:MS005010
Analysis ID:AN005279
Instrument Name:Thermo Q Exactive Orbitrap
Instrument Type:Orbitrap
MS Type:ESI
MS Comments:Data-dependent acquisition mode of the 5 most intense peaks. Full scan data were acquired between m/z 100 and 1500 in profile mode and at resolution 70000 (at m/z = 200). The automatic gain control was set as automatic gain control target at 1E6, 1 scan s-1, and injection time at 100 ms. Pre-processing data on MS-DIAL 4.9 software. The parameter analysis were setting with MS1 tolerance of 0.02 Da, MS2 tolerance 0.06 Da, MS1 and MS2 m/z 100-1500 range, maximum charged number 1; peak detection with 10000 of minimum peak height and mass slice width of 0.1 Da; deconvolution with MS/MS abundance cut off of 30 amplitude and sigma window value of 0.5; alignment parameters with retention time tolerance 0.5 min, MS1 tolerance of 0.02 Da and removed features based on blank information.
Ion Mode:NEGATIVE
Spray Voltage:-3.2
  logo