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Proteomic profiling of serum from patients with tuberculosis.

ABSTRACT: BACKGROUND: Effective treatment and monitoring of tuberculosis (TB) requires biomarkers that can be easily evaluated in blood samples. The aim of this study was to analyze the serum proteome of patients with TB and to identify protein biomarkers for TB. METHODS: Serum samples from 26 TB patients and 31 controls were analyzed by using nano-flow ultra-performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry in data-independent mode, and protein and peptide amounts were calculated by using a label-free quantitative approach. The generated data were analyzed by using principal component analysis and partial least squares discriminant analysis, a multivariate statistical method. RESULTS: Of more than 500 proteins identified, alpha-1-antitrypsin was the most discriminative, which was 4.4 times higher in TB patients than in controls. Peptides from alpha-1-antitrypsin and antithrombin III increased in TB patients and showed a high variable importance in the projection scores and coefficient in partial least square discriminant analysis. CONCLUSIONS: Sera from patients with TB had higher alpha-1-antitrypsin levels than sera from control participants. Alpha-1-antitrypsin levels may aid in the diagnosis of TB.

SUBMITTER: Song SH

PROVIDER: S-EPMC4151002 | biostudies-literature | 2014 Sep

REPOSITORIES: biostudies-literature

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Proteomic profiling of serum from patients with tuberculosis.

Song Sang Hoon SH Han Minje M Choi Yang Seon YS Dan Ki Soon KS Yang Man Gil MG Song Junghan J Park Sung Sup SS Lee Jae Ho JH

Annals of laboratory medicine 20140821 5

<h4>Background</h4>Effective treatment and monitoring of tuberculosis (TB) requires biomarkers that can be easily evaluated in blood samples. The aim of this study was to analyze the serum proteome of patients with TB and to identify protein biomarkers for TB.<h4>Methods</h4>Serum samples from 26 TB patients and 31 controls were analyzed by using nano-flow ultra-performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry in data-independent mode, and protein and pept ...[more]

PMID: 25187886

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Project description:AimTo explore the diagnostic models of Crohn's disease (CD), Intestinal tuberculosis (ITB) and the differential diagnostic model between CD and ITB by analyzing serum proteome profiles.MethodsSerum proteome profiles from 30 CD patients, 21 ITB patients and 30 healthy controls (HCs) were analyzed by using weak cationic magnetic beads combined with MALDI-TOF-MS technique to detect the differentially expressed proteins of serum samples. Three groups were made and compared accordingly: group of CD patients and HCs, group of ITB patients and HCs, group of CD patients and ITB patients. Wilcoxon rank sum test was used to screen the ten most differentiated protein peaks (P < 0.05). Genetic algorithm combining with support vector machine (SVM) was utilized to establish the optimal diagnostic models for CD, ITB and the optimal differential diagnostic model between CD and ITB. The predictive effects of these models were evaluated by Leave one out (LOO) cross validation method.ResultsThere were 236 protein peaks differently expressed between group of CD patients and HCs, 305 protein peaks differently expressed between group of ITB patients and HCs, 332 protein peaks differently expressed between group of CD patients and ITB patients. Ten most differentially expressed peaks were screened out between three groups respectively (P < 0.05) to establish diagnostic models and differential diagnostic model. A diagnostic model comprising of four protein peaks (M/Z 4964, 3029, 2833, 2900) can well distinguish CD patients and HCs, with a specificity and sensitivity of 96.7% and 96.7% respectively. A diagnostic model comprising four protein peaks (M/Z 3030, 2105, 2545, 4210) can well distinguish ITB patients and HCs, with a specificity and sensitivity of 93.3% and 95.2% respectively. A differential diagnostic model comprising three potential biomarkers protein peaks (M/Z 4267, 4223, 1541) can well distinguish CD patients and ITB patients, with a specificity and sensitivity of 76.2% and 80.0% respectively. Among the eleven protein peaks from the diagnostic models and differential diagnostic model, two have been successfully purified and identified, Those two peaks were M/Z 2900 from the diagnostic model between CD and HCs and M/Z 1541 from the differential diagnostic model between CD and ITB. M/Z 2900 was identified as appetite peptide, M/Z 1541 was identified as Lysyl oxidase-like 2 (LOXL-2).ConclusionThe differently expressed protein peaks analyzed by serum proteome with weak cationic magnetic beads combined MALDI-TOF-MS technique can effectively distinguish CD patients and HCs, ITB patients and HCs, CD patients and ITB patients. The diagnostic model between CD patients and HCs consisting of four protein peaks (M/Z 4964, 3029, 2833, 2900), the diagnostic model between ITB patients and HCs comprising four protein peaks (M/Z 3030, 2105, 2545, 4210) and the differential diagnostic model between CD patients and ITB patients comprising three protein peaks (M/Z 4267, 4223, 1541) had high specificity and sensitivity and can contribute to diagnoses of CD, ITB and the differential diagnosis between CD and ITB. Two proteins from the diagnostic model of CD and the differential diagnostic model between CD and ITB were identified. Further experiments are required using a larger cohort of samples.

Project description:Background: Clinical management of metastatic gastric cancer (mGC) remains a major challenge due to a lack of specific biomarkers and effective therapeutic targets. Recently, accumulating evidence has suggested that exosomes play an essential role in cancer metastasis and can be an excellent reservoir of novel biomarkers and candidate therapeutic targets for cancer. Therefore, in this study, we aimed to reveal the proteomic profile of mGC-derived exosomes. Methods: Exosomes were isolated from pooled serum samples of 20 mGC patients and 40 healthy controls (HC) by ultracentrifugation. Next, quantitative proteomic analyses were applied to analyze the protein profiles of the exosomes, and bioinformatic analyses were conducted on the proteomic data. Finally, the expression of exosomal protein candidates was selectively validated in individual subjects by western blot analysis. Results: We isolated exosomes from serum samples. The size of the serum derived exosomes ranged from 30 to 150 nm in diameter. The exosomal markers CD9 and CD81 were observed in the serum exosomes. However, the exosomal negative marker calnexin, an endoplasmic reticulum protein, was not detected in exosomes. Overall, 443 exosomal proteins, including 110 differentially expressed proteins (DEPs) were identified by quantitative proteomics analyses. The bioinformatics analyses indicated that the upregulated proteins were enriched in the process of protein metabolic, whereas the downregulated proteins were largely involved in cell-cell adhesion organization. Surprisingly, 10 highly vital proteins (UBA52, PSMA1, PSMA5, PSMB6, PSMA7, PSMA4, PSMA3, PSMB1, PSMA6, and FGA) were filtered from DEPs, most of which are proteasome subunits. Moreover, the validation data confirmed that PSMA3 and PSMA6 were explicitly enriched in the serum derived exosomes from patients with mGC. Conclusion: The present study provided a comprehensive description of the serum exosome proteome of mGC patients, which could be an excellent resource for further studies of mGC.

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Proteomic profiling of serum from patients with tuberculosis.

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Proteomic profiling of serum from patients with tuberculosis.

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