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MB Sample ID: SA343085
| Local Sample ID: | 21100943 |
| Subject ID: | SU003290 |
| Subject Type: | Human |
| Subject Species: | Homo sapiens |
| Taxonomy ID: | 9606 |
| Age Or Age Range: | >14 days, |
| Gender: | Male and female |
| Human Inclusion Criteria: | >14 days, MSUD sick patients DBS |
| Human Exclusion Criteria: | </=14 days, any IEM's sick other than MSUD, unknown gender |
Select appropriate tab below to view additional metadata details:
Subject:
| Subject ID: | SU003290 |
| Subject Type: | Human |
| Subject Species: | Homo sapiens |
| Taxonomy ID: | 9606 |
| Age Or Age Range: | >14 days, |
| Gender: | Male and female |
| Human Inclusion Criteria: | >14 days, MSUD sick patients DBS |
| Human Exclusion Criteria: | </=14 days, any IEM's sick other than MSUD, unknown gender |
Factors:
| Local Sample ID | MB Sample ID | Factor Level ID | Level Value | Factor Name |
|---|---|---|---|---|
| 21100943 | SA343085 | FL040533 | Whole blood | Sample source |
| 21100943 | SA343085 | FL040533 | F | Sex |
| 21100943 | SA343085 | FL040533 | MSUD | sample_type |
Collection:
| Collection ID: | CO003283 |
| Collection Summary: | Twenty-eight DBS samples were collected from biochemically and genetically confirmed MSUD sick patients (n=14) at King Faisal Specialist Hospital and Research Center (KFSHRC) and healthy controls (n=14). These healthy individuals were almost age-sex matched with MSUD's group (Female 50%). Samples from newborn patients and controls less than 14 days were excluded from this study, as well as any IEM other than MSUD excluded. |
| Sample Type: | Blood (whole) |
| Storage Conditions: | -80℃ |
Treatment:
| Treatment ID: | TR003299 |
| Treatment Summary: | No treatment used. |
Sample Preparation:
| Sampleprep ID: | SP003297 |
| Sampleprep Summary: | One punch, of size 3.3mm, DBS from MSUD newborn and healthy controls were distributed in 96 V-shaped plate wells, then immersed with 250 μL of extraction solvent composed of 20% Water: 20% MeOH:40% ACN. The samples were vortexed in thermomixer (Eppendrof, Germany) at 600 rpm, 25˚C, for 2hrs. The samples were spun down at 16.000 rpm, 4˚C, for 10 min. The supernatants were transferred into new 96 V-shaped plate and the punches discarded, and then the samples were dried in a vacuum concentrator SpeedVac (Christ, City, Germany). Dry residue was re-dissolved in 100 μL of methanol/water with a ratio (1:1) prior to LC-MS analysis. |
| Sampleprep Protocol Filename: | MSUD_Metabolites_Extraction.pdf |
| Processing Storage Conditions: | Room temperature |
| Extract Storage: | Room temperature |
Combined analysis:
| Analysis ID | AN005204 | AN005205 |
|---|---|---|
| Analysis type | MS | MS |
| Chromatography type | Reversed phase | Reversed phase |
| Chromatography system | Waters Acquity UPLC | Waters Acquity UPLC |
| Column | Waters XSelect CSH C18 (100 x 2.1mm 2.5um) | Waters XSelect CSH C18 (100 x 2.1mm 2.5um) |
| MS Type | ESI | ESI |
| MS instrument type | QTOF | QTOF |
| MS instrument name | Waters Xevo-G2-S | Waters Xevo-G2-S |
| Ion Mode | POSITIVE | NEGATIVE |
| Units | Peak area | Peak area |
Chromatography:
| Chromatography ID: | CH003938 |
| Methods Filename: | MSUD_LC_MS_Metabolomics.pdf |
| Instrument Name: | Waters Acquity UPLC |
| Column Name: | Waters XSelect CSH C18 (100 x 2.1mm 2.5um) |
| Column Temperature: | 55 |
| Flow Gradient: | 95–5% A [0–16 min], 5% A [16–19 min], 5–95% A [19–20 min], and 95–95% A [20–22 min]. |
| Flow Rate: | 300 μL/min |
| Solvent A: | 100% water; 0.1% formic acid |
| Solvent B: | 50% MeOH/50% ACN; 0.1% formic acid |
| Chromatography Type: | Reversed phase |
MS:
| MS ID: | MS004937 |
| Analysis ID: | AN005204 |
| Instrument Name: | Waters Xevo-G2-S |
| Instrument Type: | QTOF |
| MS Type: | ESI |
| MS Comments: | The DIA data were gathered with a Masslynx™ V4.1 Software (Waters Inc., Milford, MA, USA) in continuum mode. Quality control samples (QCs) were made with aliquots from all samples and introduced to the instrument after the randomization of each group, after 10 samples to validate the stability of the system (Aldubayan, Rodan, Berry, & Levy, 2017). Data and Statistical Analyses: The raw MS data were processed using a standard pipeline, beginning from an alignment depending on the mass to charge ratio (m/s) and the retention time (RT) of ion signals’, picking the best peak, followed by the filtering of signal depending on the quality of peak by utilizing the Progenesis QI (v.3.0) software (Waters Technologies, Milford, MA, USA). A multivariate statistics was applied by using MetaboAnalyst (v.5.0) (McGill University, Montreal, QB, Canada) (http://www.metaboanalyst.ca) (Pang et al., 2021). All the imported data-groups (compounds’ names also their raw abundances information) were Pareto scaled, log transformed and applied for creating partial least squares discriminant analysis (PLS-DA) and orthogonal partial least squares discriminant analysis (OPLS-DA) models. The generated OPLS-DA model was measured through R2Y and Q2 values, that represents the fitness of the model and predictive ability, respectively (Worley & Powers, 2013). A univariate analysis was applied through Mass Profiler Professional (MPP) (v. 15.0) software (Agilent, Santa Clara, CA, USA). A volcano plot was applied to uncover significantly changed mass features based on a Moderated T-test, cut-off: no correction, p <0.05, FC 1.5. Heatmap analysis for altered features was performed using the Pearson distance measure according to the Pearson similarity test (Gu et al., 2020). |
| Ion Mode: | POSITIVE |
| Analysis Protocol File: | Metabolomics_Pos_and_Neg.pdf |
| MS ID: | MS004938 |
| Analysis ID: | AN005205 |
| Instrument Name: | Waters Xevo-G2-S |
| Instrument Type: | QTOF |
| MS Type: | ESI |
| MS Comments: | The DIA data were gathered with a Masslynx™ V4.1 Software (Waters Inc., Milford, MA, USA) in continuum mode. Quality control samples (QCs) were made with aliquots from all samples and introduced to the instrument after the randomization of each group, after 10 samples to validate the stability of the system (Aldubayan, Rodan, Berry, & Levy, 2017). Data and Statistical Analyses: The raw MS data were processed using a standard pipeline, beginning from an alignment depending on the mass to charge ratio (m/s) and the retention time (RT) of ion signals’, picking the best peak, followed by the filtering of signal depending on the quality of peak by utilizing the Progenesis QI (v.3.0) software (Waters Technologies, Milford, MA, USA). A multivariate statistics was applied by using MetaboAnalyst (v.5.0) (McGill University, Montreal, QB, Canada) (http://www.metaboanalyst.ca) (Pang et al., 2021). All the imported data-groups (compounds’ names also their raw abundances information) were Pareto scaled, log transformed and applied for creating partial least squares discriminant analysis (PLS-DA) and orthogonal partial least squares discriminant analysis (OPLS-DA) models. The generated OPLS-DA model was measured through R2Y and Q2 values, that represents the fitness of the model and predictive ability, respectively (Worley & Powers, 2013). A univariate analysis was applied through Mass Profiler Professional (MPP) (v. 15.0) software (Agilent, Santa Clara, CA, USA). A volcano plot was applied to uncover significantly changed mass features based on a Moderated T-test, cut-off: no correction, p <0.05, FC 1.5. Heatmap analysis for altered features was performed using the Pearson distance measure according to the Pearson similarity test (Gu et al., 2020). |
| Ion Mode: | NEGATIVE |
| Analysis Protocol File: | Metabolomics_Pos_and_Neg.pdf |
