Summary of Study ST002428

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 PR001562. The data can be accessed directly via it's Project DOI: 10.21228/M8SM54 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.

Study ID	ST002428
Study Title	Mass Spectrometry-based Proteomic and Metabolomic profiling of serum samples for discovery and validation of Tuberculosis diagnostic biomarker signature
Study Summary	Tuberculosis (TB) is a transmissible disease listed as one of the 10 leading causes of death worldwide (10 million infected in 2019). A swift and precise diagnosis is essential to forestall its transmission, for which is crucial the discovery of effective diagnostic biomarkers. In this study, we aimed to discover molecular biomarkers for the early diagnosis of tuberculosis. Two independent cohorts comprising 29 and 34 subjects were assayed by proteomics, and 49 were included for metabolomic analysis. All subjects were arranged into 3 experimental groups – healthy controls (Controls), Latent TB infection (LTBI) and TB patients. LC-MS/MS blood serum protein and metabolite levels were submitted to univariate, multivariate and ROC analysis. From the 149 proteins quantified in the discovery set, 25 were found to be differentially abundant between Controls and TB patients. The AUC, specificity and sensitivity, determined by ROC statistical analysis of the model composed by four of these proteins considering both proteomic sets, were 0.96; 93% and 91%, respectively. The five metabolites (9-methyluric acid, indole-3-lactic acid, trans-3-indoleacrylic acid, hexanoylglycine and N-acetyl-L-leucine) that better discriminate the control and TB patient groups (VIP > 1.75) from a total of 92 metabolites quantified in both ionization modes, were submitted to ROC analysis. An AUC=1 was determined with all samples being correctly assigned to the respective experimental group. An integrated ROC analysis enrolling 1 protein and 4 metabolites was also performed for the common control and TB patients in the proteomic and metabolomic groups. This combined signature has correctly assigned the 12 controls and 12 patients used only for prediction (AUC=1, specificity=100% and sensitivity=100%). This multi-omics approach has revealed a biomarker signature for tuberculosis diagnosis that could be potentially used for developing a point-of-care diagnosis clinical test.
Institute	ITQB NOVA
Laboratory	Proteomics of Non-Model Organisms
Last Name	Gonçalves
First Name	Luís
Address	Avenida Republica
Email	lgafeira@itqb.unl.pt
Phone	214469464
Submit Date	2022-10-04
Num Groups	3
Raw Data Available	Yes
Raw Data File Type(s)	mzML
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:	PR001562
Project DOI:	doi: 10.21228/M8SM54
Project Title:	Mass Spectrometry-based Proteomic and Metabolomic profiling of serum samples for discovery and validation of Tuberculosis diagnostic biomarker signature
Project Type:	Proteomic and metabolomic study
Project Summary:	Tuberculosis (TB) is a transmissible disease listed as one of the 10 leading causes of death worldwide (10 million infected in 2019). A swift and precise diagnosis is essential to forestall its transmission, for which is crucial the discovery of effective diagnostic biomarkers. In this study, we aimed to discover molecular biomarkers for the early diagnosis of tuberculosis. Two independent cohorts comprising 29 and 34 subjects were assayed by proteomics, and 49 were included for metabolomic analysis. All subjects were arranged into 3 experimental groups – healthy controls (Controls), Latent TB infection (LTBI) and TB patients. LC-MS/MS blood serum protein and metabolite levels were submitted to univariate, multivariate and ROC analysis. From the 149 proteins quantified in the discovery set, 25 were found to be differentially abundant between Controls and TB patients. The AUC, specificity and sensitivity, determined by ROC statistical analysis of the model composed by four of these proteins considering both proteomic sets, were 0.96; 93% and 91%, respectively. The five metabolites (9-methyluric acid, indole-3-lactic acid, trans-3-indoleacrylic acid, hexanoylglycine and N-acetyl-L-leucine) that better discriminate the control and TB patient groups (VIP > 1.75) from a total of 92 metabolites quantified in both ionization modes, were submitted to ROC analysis. An AUC=1 was determined with all samples being correctly assigned to the respective experimental group. An integrated ROC analysis enrolling 1 protein and 4 metabolites was also performed for the common control and TB patients in the proteomic and metabolomic groups. This combined signature has correctly assigned the 12 controls and 12 patients used only for prediction (AUC=1, specificity=100% and sensitivity=100%). This multi-omics approach has revealed a biomarker signature for tuberculosis diagnosis that could be potentially used for developing a point-of-care diagnosis clinical test.
Institute:	ITQB NOVA
Laboratory:	Proteomics of Non-Model Organisms
Last Name:	Gonçalves
First Name:	Luís
Address:	Avenida Republica
Email:	lgafeira@itqb.unl.pt
Phone:	214469464

Subject:

Subject ID:	SU002517
Subject Type:	Human
Subject Species:	Homo sapiens
Taxonomy ID:	9606
Age Or Age Range:	18-65
Gender:	Male and female
Human Exclusion Criteria:	HIV patients, respiratory infections beside TB, diabetes, chronic renal failure history and transplanted. individuals

Factors:

Subject type: Human; Subject species: Homo sapiens (Factor headings shown in green)

mb_sample_id	local_sample_id	Label
SA242795	C47	Controls
SA242796	C46	Controls
SA242797	C45	Controls
SA242798	C49	Controls
SA242799	C51	Controls
SA242800	C4	Controls
SA242801	C53	Controls
SA242802	C40	Controls
SA242803	C38	Controls
SA242804	C8	Controls
SA242805	C7	Controls
SA242806	C5	Controls
SA242807	C9	Controls
SA242808	C16	Controls
SA242809	C37	Controls
SA242810	C31	Controls
SA242811	C25	Controls
SA242812	C21	Controls
SA242813	DE55	LTBI
SA242814	CE57	LTBI
SA242815	C28	LTBI
SA242816	CE55	LTBI
SA242817	C30	LTBI
SA242818	CE54	LTBI
SA242819	DE10	TB
SA242820	DE5	TB
SA242821	D58	TB
SA242822	D56	TB
SA242823	DE11	TB
SA242824	D59	TB
SA242825	DE51	TB
SA242826	D28	TB
SA242827	DE53	TB
SA242828	DE54	TB
SA242829	DE52	TB
SA242830	DE12	TB
SA242831	D11	TB
SA242832	D15	TB
SA242833	D16	TB
SA242834	D13	TB
SA242835	D12	TB
SA242836	D10	TB
SA242837	D19	TB
SA242838	D20	TB
SA242839	D25	TB
SA242840	D26	TB
SA242841	D23	TB
SA242842	D22	TB
SA242843	D21	TB
SA242844	D27	TB

Showing results 1 to 50 of 50

Showing results 1 to 50 of 50

Collection:

Collection ID:	CO002510
Collection Summary:	Peripheral blood samples were collected at the Vendas Novas and Almada-Seixal Pneumonologic Diagnostic Centers (CDP-). Briefly, around 7 mL of blood was collected in order to obtain 3 mL of serum. Whole blood samples were harvested using Clot Activator Tubes (Monovette Serum Gel Z – 7.5 mL, S-monovette, Sarstedt®). IGRA test (QuantiFERON®-TB Gold IT, ©QIAGEN) was used to confirm infection status in Control and Latent groups. These samples were transported at 4°C to the National Institute of Health Doctor Ricardo Jorge (INSA). Samples displaying hemolysis or with unidentified IGRA results were excluded from further analysis.
Sample Type:	Blood (serum)

Treatment:

Treatment ID:	TR002529
Treatment Summary:	Blood was allowed to clot for three hours at 4°C after collection. The blood was then centrifuged at 1000 xg at 4°C for 30 min. Serum collected after centrifugation was passed through 0.2 μm filters (Sterile Acrodisc®, syringe filters with Supor membrane, 32 mm) to remove bacteria. Finally, an anti-protease cocktail (Protease Inhibitor Cocktail, ©SIGMA) was added to the filtered serum. The samples were transported from INSA to ITQB in a liquid nitrogen container and stored at −80°C.

Treatment ID:

TR002529

Treatment Summary:

Blood was allowed to clot for three hours at 4°C after collection. The blood was then centrifuged at 1000 xg at 4°C for 30 min. Serum collected after centrifugation was passed through 0.2 μm filters (Sterile Acrodisc®, syringe filters with Supor membrane, 32 mm) to remove bacteria. Finally, an anti-protease cocktail (Protease Inhibitor Cocktail, ©SIGMA) was added to the filtered serum. The samples were transported from INSA to ITQB in a liquid nitrogen container and stored at −80°C.

Sample Preparation:

Sampleprep ID:	SP002523
Sampleprep Summary:	Serum samples (100 µL) were extracted with 300 µL of methanol overnight at 4°C. The morning after, the samples were centrifuged for 5 min at 16.000 ×g and 4°C. The supernatant was transferred to a new tube, evaporated in the speedvac, and the pellet was stored at −20°C until further analysis. Previous to LC-MS/MS analysis the pellets were resuspended in 99.16 µL of H2O 0.1%FA. The Internal Standard (IS) – 3-Nitro-L-tyrosine – was added to a final concentration of 42 µM. In addition, four pools of samples were used for metabolite identification.

Sampleprep ID:

SP002523

Sampleprep Summary:

Serum samples (100 µL) were extracted with 300 µL of methanol overnight at 4°C. The morning after, the samples were centrifuged for 5 min at 16.000 ×g and 4°C. The supernatant was transferred to a new tube, evaporated in the speedvac, and the pellet was stored at −20°C until further analysis. Previous to LC-MS/MS analysis the pellets were resuspended in 99.16 µL of H2O 0.1%FA. The Internal Standard (IS) – 3-Nitro-L-tyrosine – was added to a final concentration of 42 µM. In addition, four pools of samples were used for metabolite identification.

Combined analysis:

Analysis ID	AN003951	AN003952
Analysis type	MS	MS
Chromatography type	Reversed phase	Reversed phase
Chromatography system	Dionex UltiMate 3000 UHPLC	Dionex UltiMate 3000 UHPLC
Column	Waters XBridge C18 (50 x 2.1mm, 3um)	Waters XBridge C18 (50 x 2.1mm, 3um)
MS Type	ESI	ESI
MS instrument type	Orbitrap	Orbitrap
MS instrument name	Thermo Q Exactive Focus	Thermo Q Exactive Focus
Ion Mode	POSITIVE	NEGATIVE
Units	ua	au

Chromatography:

Chromatography ID:	CH002925
Instrument Name:	Dionex UltiMate 3000 UHPLC
Column Name:	Waters XBridge C18 (50 x 2.1mm, 3um)
Chromatography Type:	Reversed phase

MS:

MS ID:	MS003686
Analysis ID:	AN003951
Instrument Name:	Thermo Q Exactive Focus
Instrument Type:	Orbitrap
MS Type:	ESI
MS Comments:	Full-MS scan spectra were acquired in the m/z range 75 – 1125, at a resolution of 70,000 (full width at half maximum (FWHM) at m/z 200) and 1×106 automatic gain control (AGC). MS/MS scan spectra were acquired at 17,500 resolution (FWHM at m/z 200), with 1×105 AGC, maximum injection time of 100 ms and dynamic exclusion of 6 s. Raw data files were independently processed by Compound Discoverer™ 3.1 (ThermoFisher Scientific) software for metabolomics data analysis. The preferred database used for metabolite identification was mzCloud – since the "Search mzCloud '' node searches this database for matching fragmentation spectra (MS2) – followed by ChemSpider. For both databases the mass tolerance that the software used to search for matching mass peaks was set at 3 ppm. In the case of the mzCloud search the parameter "FT Fragment Mass Tolerance"was set to 5 ppm. The Human Metabolome Database (HMDB) was selected as the primary source for the ChemSpider search.
Ion Mode:	POSITIVE

MS ID:	MS003687
Analysis ID:	AN003952
Instrument Name:	Thermo Q Exactive Focus
Instrument Type:	Orbitrap
MS Type:	ESI
MS Comments:	Full-MS scan spectra were acquired in the m/z range 75 – 1125, at a resolution of 70,000 (full width at half maximum (FWHM) at m/z 200) and 1×106 automatic gain control (AGC). MS/MS scan spectra were acquired at 17,500 resolution (FWHM at m/z 200), with 1×105 AGC, maximum injection time of 100 ms and dynamic exclusion of 6 s. Raw data files were independently processed by Compound Discoverer™ 3.1 (ThermoFisher Scientific) software for metabolomics data analysis. The preferred database used for metabolite identification was mzCloud – since the "Search mzCloud '' node searches this database for matching fragmentation spectra (MS2) – followed by ChemSpider. For both databases the mass tolerance that the software used to search for matching mass peaks was set at 3 ppm. In the case of the mzCloud search the parameter "FT Fragment Mass Tolerance"was set to 5 ppm. The Human Metabolome Database (HMDB) was selected as the primary source for the ChemSpider search.
Ion Mode:	NEGATIVE