{
"METABOLOMICS WORKBENCH":{"STUDY_ID":"ST002428","ANALYSIS_ID":"AN003951","VERSION":"1","CREATED_ON":"January 5, 2023, 4:30 pm"},

"PROJECT":{"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"},

"STUDY":{"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","NUM_GROUPS":"3"},

"SUBJECT":{"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"},
"SUBJECT_SAMPLE_FACTORS":[
{
"Subject ID":"-",
"Sample ID":"C4",
"Factors":{"Label":"Controls"},
"Additional sample data":{"RAW_FILE_NAME":"C4.mzML"}
},
{
"Subject ID":"-",
"Sample ID":"C5",
"Factors":{"Label":"Controls"},
"Additional sample data":{"RAW_FILE_NAME":"C5.mzML"}
},
{
"Subject ID":"-",
"Sample ID":"C7",
"Factors":{"Label":"Controls"},
"Additional sample data":{"RAW_FILE_NAME":"C7.mzML"}
},
{
"Subject ID":"-",
"Sample ID":"C8",
"Factors":{"Label":"Controls"},
"Additional sample data":{"RAW_FILE_NAME":"C8.mzML"}
},
{
"Subject ID":"-",
"Sample ID":"C9",
"Factors":{"Label":"Controls"},
"Additional sample data":{"RAW_FILE_NAME":"C9.mzML"}
},
{
"Subject ID":"-",
"Sample ID":"C16",
"Factors":{"Label":"Controls"},
"Additional sample data":{"RAW_FILE_NAME":"C16.mzML"}
},
{
"Subject ID":"-",
"Sample ID":"C21",
"Factors":{"Label":"Controls"},
"Additional sample data":{"RAW_FILE_NAME":"C21.mzML"}
},
{
"Subject ID":"-",
"Sample ID":"C25",
"Factors":{"Label":"Controls"},
"Additional sample data":{"RAW_FILE_NAME":"C25.mzML"}
},
{
"Subject ID":"-",
"Sample ID":"C31",
"Factors":{"Label":"Controls"},
"Additional sample data":{"RAW_FILE_NAME":"C31.mzML"}
},
{
"Subject ID":"-",
"Sample ID":"C37",
"Factors":{"Label":"Controls"},
"Additional sample data":{"RAW_FILE_NAME":"C37.mzML"}
},
{
"Subject ID":"-",
"Sample ID":"C38",
"Factors":{"Label":"Controls"},
"Additional sample data":{"RAW_FILE_NAME":"C38.mzML"}
},
{
"Subject ID":"-",
"Sample ID":"C40",
"Factors":{"Label":"Controls"},
"Additional sample data":{"RAW_FILE_NAME":"C40.mzML"}
},
{
"Subject ID":"-",
"Sample ID":"C45",
"Factors":{"Label":"Controls"},
"Additional sample data":{"RAW_FILE_NAME":"C45.mzML"}
},
{
"Subject ID":"-",
"Sample ID":"C46",
"Factors":{"Label":"Controls"},
"Additional sample data":{"RAW_FILE_NAME":"C46.mzML"}
},
{
"Subject ID":"-",
"Sample ID":"C47",
"Factors":{"Label":"Controls"},
"Additional sample data":{"RAW_FILE_NAME":"C47.mzML"}
},
{
"Subject ID":"-",
"Sample ID":"C49",
"Factors":{"Label":"Controls"},
"Additional sample data":{"RAW_FILE_NAME":"C49.mzML"}
},
{
"Subject ID":"-",
"Sample ID":"C51",
"Factors":{"Label":"Controls"},
"Additional sample data":{"RAW_FILE_NAME":"C51.mzML"}
},
{
"Subject ID":"-",
"Sample ID":"C53",
"Factors":{"Label":"Controls"},
"Additional sample data":{"RAW_FILE_NAME":"C53.mzML"}
},
{
"Subject ID":"-",
"Sample ID":"C28",
"Factors":{"Label":"LTBI"},
"Additional sample data":{"RAW_FILE_NAME":"C28.mzML"}
},
{
"Subject ID":"-",
"Sample ID":"C30",
"Factors":{"Label":"LTBI"},
"Additional sample data":{"RAW_FILE_NAME":"C30.mzML"}
},
{
"Subject ID":"-",
"Sample ID":"CE54",
"Factors":{"Label":"LTBI"},
"Additional sample data":{"RAW_FILE_NAME":"CE54.mzML"}
},
{
"Subject ID":"-",
"Sample ID":"CE55",
"Factors":{"Label":"LTBI"},
"Additional sample data":{"RAW_FILE_NAME":"CE55.mzML"}
},
{
"Subject ID":"-",
"Sample ID":"CE57",
"Factors":{"Label":"LTBI"},
"Additional sample data":{"RAW_FILE_NAME":"CE57.mzML"}
},
{
"Subject ID":"-",
"Sample ID":"DE55",
"Factors":{"Label":"LTBI"},
"Additional sample data":{"RAW_FILE_NAME":"DE55.mzML"}
},
{
"Subject ID":"-",
"Sample ID":"D10",
"Factors":{"Label":"TB"},
"Additional sample data":{"RAW_FILE_NAME":"D10.mzML"}
},
{
"Subject ID":"-",
"Sample ID":"D11",
"Factors":{"Label":"TB"},
"Additional sample data":{"RAW_FILE_NAME":"D11.mzML"}
},
{
"Subject ID":"-",
"Sample ID":"D12",
"Factors":{"Label":"TB"},
"Additional sample data":{"RAW_FILE_NAME":"D12.mzML"}
},
{
"Subject ID":"-",
"Sample ID":"D13",
"Factors":{"Label":"TB"},
"Additional sample data":{"RAW_FILE_NAME":"D13.mzML"}
},
{
"Subject ID":"-",
"Sample ID":"D15",
"Factors":{"Label":"TB"},
"Additional sample data":{"RAW_FILE_NAME":"D15.mzML"}
},
{
"Subject ID":"-",
"Sample ID":"D16",
"Factors":{"Label":"TB"},
"Additional sample data":{"RAW_FILE_NAME":"D16.mzML"}
},
{
"Subject ID":"-",
"Sample ID":"D19",
"Factors":{"Label":"TB"},
"Additional sample data":{"RAW_FILE_NAME":"D19.mzML"}
},
{
"Subject ID":"-",
"Sample ID":"D20",
"Factors":{"Label":"TB"},
"Additional sample data":{"RAW_FILE_NAME":"D20.mzML"}
},
{
"Subject ID":"-",
"Sample ID":"D21",
"Factors":{"Label":"TB"},
"Additional sample data":{"RAW_FILE_NAME":"D21.mzML"}
},
{
"Subject ID":"-",
"Sample ID":"D22",
"Factors":{"Label":"TB"},
"Additional sample data":{"RAW_FILE_NAME":"D22.mzML"}
},
{
"Subject ID":"-",
"Sample ID":"D23",
"Factors":{"Label":"TB"},
"Additional sample data":{"RAW_FILE_NAME":"D23.mzML"}
},
{
"Subject ID":"-",
"Sample ID":"D25",
"Factors":{"Label":"TB"},
"Additional sample data":{"RAW_FILE_NAME":"D25.mzML"}
},
{
"Subject ID":"-",
"Sample ID":"D26",
"Factors":{"Label":"TB"},
"Additional sample data":{"RAW_FILE_NAME":"D26.mzML"}
},
{
"Subject ID":"-",
"Sample ID":"D27",
"Factors":{"Label":"TB"},
"Additional sample data":{"RAW_FILE_NAME":"D27.mzML"}
},
{
"Subject ID":"-",
"Sample ID":"D28",
"Factors":{"Label":"TB"},
"Additional sample data":{"RAW_FILE_NAME":"D28.mzML"}
},
{
"Subject ID":"-",
"Sample ID":"D56",
"Factors":{"Label":"TB"},
"Additional sample data":{"RAW_FILE_NAME":"D56.mzML"}
},
{
"Subject ID":"-",
"Sample ID":"D58",
"Factors":{"Label":"TB"},
"Additional sample data":{"RAW_FILE_NAME":"D58.mzML"}
},
{
"Subject ID":"-",
"Sample ID":"D59",
"Factors":{"Label":"TB"},
"Additional sample data":{"RAW_FILE_NAME":"D59.mzML"}
},
{
"Subject ID":"-",
"Sample ID":"DE5",
"Factors":{"Label":"TB"},
"Additional sample data":{"RAW_FILE_NAME":"DE5.mzML"}
},
{
"Subject ID":"-",
"Sample ID":"DE10",
"Factors":{"Label":"TB"},
"Additional sample data":{"RAW_FILE_NAME":"DE10.mzML"}
},
{
"Subject ID":"-",
"Sample ID":"DE11",
"Factors":{"Label":"TB"},
"Additional sample data":{"RAW_FILE_NAME":"DE11.mzML"}
},
{
"Subject ID":"-",
"Sample ID":"DE12",
"Factors":{"Label":"TB"},
"Additional sample data":{"RAW_FILE_NAME":"DE12.mzML"}
},
{
"Subject ID":"-",
"Sample ID":"DE51",
"Factors":{"Label":"TB"},
"Additional sample data":{"RAW_FILE_NAME":"DE51.mzML"}
},
{
"Subject ID":"-",
"Sample ID":"DE52",
"Factors":{"Label":"TB"},
"Additional sample data":{"RAW_FILE_NAME":"DE52.mzML"}
},
{
"Subject ID":"-",
"Sample ID":"DE54",
"Factors":{"Label":"TB"},
"Additional sample data":{"RAW_FILE_NAME":"DE54.mzML"}
},
{
"Subject ID":"-",
"Sample ID":"DE53",
"Factors":{"Label":"TB"},
"Additional sample data":{"RAW_FILE_NAME":"DE53.mzML"}
}
],
"COLLECTION":{"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_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."},

"SAMPLEPREP":{"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."},

"CHROMATOGRAPHY":{"CHROMATOGRAPHY_TYPE":"Reversed phase","INSTRUMENT_NAME":"Dionex UltiMate 3000 UHPLC","COLUMN_NAME":"Waters XBridge C18 (50 x 2.1mm, 3um)"},

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

"MS":{"INSTRUMENT_NAME":"Thermo Q Exactive Focus","INSTRUMENT_TYPE":"Orbitrap","MS_TYPE":"ESI","ION_MODE":"POSITIVE","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 Tolerancewas set to 5 ppm. The Human Metabolome Database (HMDB) was selected as the primary source for the ChemSpider search."},

"MS_METABOLITE_DATA":{
"Units":"au",

"Data":[{"Metabolite":"1-Methylhistidine","C4":"0.08105362056","C5":"0.007876834817","C7":"0.006511612943","C8":"0.01776595078","C9":"0.005132356652","C16":"0.004600107381","C21":"0.03567500058","C25":"0.01398978763","C31":"0.01155666229","C37":"0.009460582802","C38":"0.02243024001","C40":"0.0111492083","C45":"0.01660449995","C46":"0.02198977797","C47":"0.005459288342","C49":"0.006332867661","C51":"0.005364361707","C53":"0.003352103963","C28":"0.005011552597","C30":"0.02099468791","CE54":"0.01062458448","CE55":"0.01018654131","CE57":"0.01124071283","DE55":"0.01075997887","D10":"0.01124410724","D11":"0.009257611887","D12":"0.03309557681","D13":"0.01400488122","D15":"0.007298445048","D16":"0.007750042538","D19":"0.0147254241","D20":"0.00696933199","D21":"0.01192465551","D22":"0.007054141183","D23":"0.00407493646","D25":"0.01840585021","D26":"0.01951551909","D27":"0.01086043277","D28":"0.01992816434","D56":"0.01553284634","D58":"0.007775861113","D59":"0.008420896973","DE5":"0.007199537018","DE10":"0.009465295839","DE11":"0.00988765314","DE12":"0.0146865931","DE51":"0.01281388902","DE52":"0.01258782563","DE54":"0.01544753037","DE53":"0.01090461745"},{"Metabolite":"2-Hydroxycinnamic 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[min]":"15.329","PubChem":"69421","KEGG":"NA"},{"Metabolite":"Hexanoylcarnitine","Molecular Weight":"259.17839","RT [min]":"7.282","PubChem":"6426853","KEGG":"NA"},{"Metabolite":"Hippuric acid","Molecular Weight":"179.05812","RT [min]":"6.479","PubChem":"464","KEGG":"C01586"},{"Metabolite":"Hypoglycin A","Molecular Weight":"141.079","RT [min]":"5.503","PubChem":"9081","KEGG":"C08287"},{"Metabolite":"Hypoxanthine","Molecular Weight":"136.03845","RT [min]":"1.288","PubChem":"790","KEGG":"C00262"},{"Metabolite":"Indole-3-acetic acid","Molecular Weight":"175.06326","RT [min]":"8.089","PubChem":"802","KEGG":"C00954"},{"Metabolite":"Inosine","Molecular Weight":"268.08062","RT [min]":"3.303","PubChem":"6021","KEGG":"C00294"},{"Metabolite":"L(-)-Carnitine","Molecular Weight":"161.10504","RT [min]":"1.019","PubChem":"3612","KEGG":"C00318"},{"Metabolite":"L-(-)-Methionine","Molecular Weight":"149.051","RT [min]":"1.327","PubChem":"6137","KEGG":"C00073"},{"Metabolite":"L(+)-Ornithine","Molecular 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[min]":"6.513","PubChem":"306137","KEGG":"C04148"},{"Metabolite":"Oleamide","Molecular Weight":"281.27187","RT [min]":"15.451","PubChem":"5283387","KEGG":"C19670"},{"Metabolite":"Palmitoylcarnitine","Molecular Weight":"399.33446","RT [min]":"12.6","PubChem":"11953816","KEGG":"C02990"},{"Metabolite":"Piperine","Molecular Weight":"285.13645","RT [min]":"11.094","PubChem":"638024","KEGG":"C03882"},{"Metabolite":"Pyridoxine","Molecular Weight":"169.07381","RT [min]":"5.428","PubChem":"1054","KEGG":"C00314"},{"Metabolite":"trans-3-Indoleacrylic acid","Molecular Weight":"187.06321","RT [min]":"5.885","PubChem":"5375048","KEGG":"C21283"},{"Metabolite":"Trigonelline","Molecular Weight":"137.04759","RT [min]":"0.956","PubChem":"5570","KEGG":"C01004"},{"Metabolite":"Uric acid","Molecular Weight":"168.0282","RT [min]":"1.209","PubChem":"1175","KEGG":"C00366"},{"Metabolite":"Urocanic acid","Molecular Weight":"138.04282","RT [min]":"1.552","PubChem":"736715","KEGG":"C00785"},{"Metabolite":"Valine","Molecular Weight":"117.07878","RT [min]":"1.283","PubChem":"6287","KEGG":"C00183"},{"Metabolite":"α-Aspartylphenylalanine","Molecular Weight":"280.10585","RT [min]":"5.961","PubChem":"93078","KEGG":"NA"},{"Metabolite":"β-Alanine","Molecular Weight":"89.04759","RT [min]":"0.891","PubChem":"239","KEGG":"C00099"}]
}

}