Label-free LC-MS/MS quantitative proteomics for large-scale biomarker discovery in complex samples

2007 ◽  
Vol 30 (14) ◽  
pp. 2198-2203 ◽  
Author(s):  
Yishai Levin ◽  
Emanuel Schwarz ◽  
Lan Wang ◽  
F. Markus Leweke ◽  
Sabine Bahn
Keyword(s):  
Quantitative Proteomics ◽  
Large Scale ◽  
Biomarker Discovery ◽  
Label Free ◽  
Complex Samples

scholarly journals Current Status and Advances in Quantitative Proteomic Mass Spectrometry

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Valerie C. Wasinger ◽  
Ming Zeng ◽  
Yunki Yau
Keyword(s):  
Mass Spectrometry ◽  
Quantitative Proteomics ◽  
Biomarker Discovery ◽  
Current Status ◽  
Label Free ◽  
Stable Isotope Labelling ◽  
Complex Samples ◽  
Bioinformatic Tools ◽  
Critical Overview ◽  
Proteins And Peptides

The accurate quantitation of proteins and peptides in complex biological systems is one of the most challenging areas of proteomics. Mass spectrometry-based approaches have forged significant in-roads allowing accurate and sensitive quantitation and the ability to multiplex vastly complex samples through the application of robust bioinformatic tools. These relative and absolute quantitative measures using label-free, tags, or stable isotope labelling have their own strengths and limitations. The continuous development of these methods is vital for increasing reproducibility in the rapidly expanding application of quantitative proteomics in biomarker discovery and validation. This paper provides a critical overview of the primary mass spectrometry-based quantitative approaches and the current status of quantitative proteomics in biomedical research.

scholarly journals Deciphering the major metabolic pathways associated with aluminum tolerance in popcorn roots using label-free quantitative proteomics

2021 ◽  
Author(s):  
Vitor B. Pinto ◽  
Vinícius C. Almeida ◽  
Italo A. P. Lima ◽  
Ellen M. Vale ◽  
Wagner L. Araújo ◽  
...  
Keyword(s):  
Inbred Line ◽  
Quantitative Proteomics ◽  
Large Scale ◽  
Citrate Synthase ◽  
Al Toxicity ◽  
Soluble Form ◽  
Starch Degradation ◽  
Label Free ◽  
Al Stress ◽  
Proteomic Data

Aluminum toxicity is one of the most important abiotic stresses that affect crop production worldwide. The soluble form (Al3+) inhibits root growth by altering water and nutrients uptake, which also reduces plant growth and development. Under a long term Al3+ exposure, plants can activate several tolerance mechanisms, and to date, there are no reports of large-scale proteomic data of maize in response to this ion. To investigate the post-transcriptional regulation in response to Al toxicity, we performed a label-free quantitative proteomics for comparative analysis of two Al-contrasting popcorn inbred lines and an Al-tolerant commercial hybrid during 72 h under Al-stress. A total of 489 differentially accumulated proteins (DAPs) were identified in the Al-sensitive inbred line, 491 in the Al-tolerant inbred line, and 277 in the commercial hybrid. Among them, 120 DAPs were co-expressed in both Al tolerant genotypes. Bioinformatics analysis indicated that starch and sucrose metabolism, glycolysis/gluconeogenesis, and carbohydrate metabolism were significant biochemical processes regulated in response to Al toxicity. The up accumulation of sucrose synthase and the increase of sucrose content and starch degradation suggest that these components may enhance popcorn tolerance to Al stress. The up-accumulation of citrate synthase suggests a key role of this enzyme in the detoxification process in the Al-tolerant inbred line. The integration of transcriptomic and proteomic data indicated that the Al tolerance response presents a complex regulatory network into the transcription and translation dynamics of popcorn roots development.

scholarly journals Large Scale Profiling of Protein Isoforms Using Label-Free Quantitative Proteomics Revealed the Regulation of Nonsense-Mediated Decay in Moso Bamboo (Phyllostachys edulis)

Cells ◽  
2019 ◽  
Vol 8 (7) ◽  
pp. 744 ◽  
Author(s):  
Xiaolan Yu ◽  
Yongsheng Wang ◽  
Markus V. Kohnen ◽  
Mingxin Piao ◽  
Min Tu ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Quantitative Proteomics ◽  
Large Scale ◽  
Gene Annotation ◽  
Function Analysis ◽  
Moso Bamboo ◽  
Protein Isoforms ◽  
Label Free ◽  
Total Proteins ◽  
Protein Coding

Moso bamboo is an important forest species with a variety of ecological, economic, and cultural values. However, the gene annotation information of moso bamboo is only based on the transcriptome sequencing, lacking the evidence of proteome. The lignification and fiber in moso bamboo leads to a difficulty in the extraction of protein using conventional methods, which seriously hinders research on the proteomics of moso bamboo. The purpose of this study is to establish efficient methods for extracting the total proteins from moso bamboo for following mass spectrometry-based quantitative proteome identification. Here, we have successfully established a set of efficient methods for extracting total proteins of moso bamboo followed by mass spectrometry-based label-free quantitative proteome identification, which further improved the protein annotation of moso bamboo genes. In this study, 10,376 predicted coding genes were confirmed by quantitative proteomics, accounting for 35.8% of all annotated protein-coding genes. Proteome analysis also revealed the protein-coding potential of 1015 predicted long noncoding RNA (lncRNA), accounting for 51.03% of annotated lncRNAs. Thus, mass spectrometry-based proteomics provides a reliable method for gene annotation. Especially, quantitative proteomics revealed the translation patterns of proteins in moso bamboo. In addition, the 3284 transcript isoforms from 2663 genes identified by Pacific BioSciences (PacBio) single-molecule real-time long-read isoform sequencing (Iso-Seq) was confirmed on the protein level by mass spectrometry. Furthermore, domain analysis of mass spectrometry-identified proteins encoded in the same genomic locus revealed variations in domain composition pointing towards a functional diversification of protein isoform. Finally, we found that part transcripts targeted by nonsense-mediated mRNA decay (NMD) could also be translated into proteins. In summary, proteomic analysis in this study improves the proteomics-assisted genome annotation of moso bamboo and is valuable to the large-scale research of functional genomics in moso bamboo. In summary, this study provided a theoretical basis and technical support for directional gene function analysis at the proteomics level in moso bamboo.

Real-time evaluation of experimental variation in large-scale LC–MS/MS-based quantitative proteomics of complex samples☆

2009 ◽  
Vol 877 (13) ◽  
pp. 1299-1305 ◽  
Author(s):  
Yishai Levin ◽  
Lan Wang ◽  
Erin Ingudomnukul ◽  
Emanuel Schwarz ◽  
Simon Baron-Cohen ◽  
...  
Keyword(s):  
Real Time ◽  
Quantitative Proteomics ◽  
Large Scale ◽  
Complex Samples ◽  
Experimental Variation ◽  
Time Evaluation

scholarly journals Quantitative Proteomics Identify Urinary Hgfl Protein As a Potential Marker for the Development of Chronic Kidney Disease in Sickle Cell Disease Patients

Blood ◽  
2017 ◽  
Vol 130 (Suppl_1) ◽  
pp. 967-967
Author(s):  
Xionghao Lin ◽  
Santosh L. Saraf ◽  
Simran Soni ◽  
Nowah Kokou Apeadoufia Afangbedji ◽  
Victor R. Gordeuk ◽  
...  
Keyword(s):  
Quantitative Proteomics ◽  
Biomarker Discovery ◽  
Internal Standard ◽  
Urine Samples ◽  
Healthy Controls ◽  
Label Free ◽  
Cell Disease ◽  
Selected Ion Monitoring ◽  
Ckd Stage ◽  
Peptide M

Abstract BACKGROUND: Chronic kidney disease (CKD) is common in patients with sickle cell disease (SCD). However, the progression of CKD in SCD and factors associated with such progression remain poorly defined. Liquid chromatography mass spectrometry (LC-MS) based quantitative proteomics has become a highly potent method for biomarker discovery due to growing capabilities for broad proteome coverage and good accuracy and precision in quantification. OBJECTIVES: The purpose of this study was to identify the potential markers associated with CKD progression in patients with SCD using quantitative proteomics. METHODS: Urine samples were collected from healthy controls and SCD patients with different CKD stages from University of Illinois at Chicago (UIC). Mass-spectrometry analysis was performed on an LTQ Orbitrap XL mass spectrometer (Thermo Fisher Scientific) coupled to a Prominence Nano LC (Shimadzu) using the Xcalibur version 2.7.0 (Thermo Scientific). Proteome Discoverer 1.4 and SIEVE 2.1 programs were used for protein identification and label-free quantification. Heavy isotope labeled peptide EDQTSPAPGLR(13C6, 15N) was used as an internal standard for high resolution/selected ion monitoring (HR/SIM) analysis of HGFL. Urinary HGFL protein together wiht creatinine and albumin were also measured by ELISA. RESULTS: Since glomerular hyperfiltration is an early stage of renal dysfunction. We performed label-free quantitative proteomic analysis for urine samples collected from SCD patients with hyperfiltration (N=3) and normal (N=3). Hepatocyte growth factor-like (HGFL) protein was found to be significantly downregulated (5.52-fold, p=8.05 × 10-5) in samples with glomerular hyperfiltration compared to normal group. Next, we developed a high resolution/selected ion monitoring (HR/SIM) method by measuring the HGFL peptide (m/z 585.79) with isotope labeled-HGFL peptide (m/z 590.80) as internal standard (IS). HR/SIM quantification was performed for 19 urine samples from SCD patients and 12 urine samples from healthy controls. HGFL levels were found to be significantly downregulated (p=0.0084) in the SCD urine samples compared to samples from healthy controls (Figure 1). To further assess the correlation between HGFL level and CDK stage, we expanded the analysis to SCD patients with different CKD stage ranging from 0 to 5 and 19 healthy individuals by ELISA. The result confirmed the finding of HR/SIM quantification, moreover, showed that urinary HGFL level highly correlated with CKD stage (r= ̶ 0.4106, p=0.002, Figure 1) and showed high sensitivity and specificity by Receiver Operating Characteristic (ROC) curve analysis (AUC=0.78). CONCLUSIONS: HGFL protein has been identified as a negative regulator of phosphatidylinositol 3-kinase (PI3K), and PI3K/Akt pathway was found to be activated in the progress of CKD. Therefore, the decrease of HGFL level in urines from SCD patients may indicate the development of CKD. Combination of LC-MS based quantitative proteomics and ELISA validation is an useful approach for biomarker discovery. ACKNOWLEDGMENTS: This work was supported by NIH Research Grants 1P50HL118006, 1R01HL125005, 5G12MD007597 and K23HL125984. The content is solely the responsibility of the authors and does not necessarily represent the official view of NHLBI, NIMHD or NIH. Disclosures Gordeuk: Emmaus Life Sciences: Consultancy.

scholarly journals Large-Scale Label-Free Quantitative Proteomics of the Pea aphid-BuchneraSymbiosis

2011 ◽  
Vol 10 (6) ◽  
pp. M110.007039 ◽  
Author(s):  
Anton Poliakov ◽  
Calum W. Russell ◽  
Lalit Ponnala ◽  
Harold J. Hoops ◽  
Qi Sun ◽  
...  
Keyword(s):  
Quantitative Proteomics ◽  
Large Scale ◽  
Pea Aphid ◽  
Label Free

Development of Algorithms for Mass Spectrometry-based Label-free Quantitative Proteomics*

2011 ◽  
Vol 38 (6) ◽  
pp. 506-518 ◽  
Author(s):  
Wei ZHANG ◽  
Ji-Yang ZHANG ◽  
Hui LIU ◽  
Han-Chang SUN ◽  
Chang-Ming XU ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Quantitative Proteomics ◽  
Label Free

scholarly journals The combined detection of Amphiregulin, Cyclin A1 and DDX20/Gemin3 expression predicts aggressive forms of oral squamous cell carcinoma

2021 ◽  
Author(s):  
Ekaterina Bourova-Flin ◽  
Samira Derakhshan ◽  
Afsaneh Goudarzi ◽  
Tao Wang ◽  
Anne-Laure Vitte ◽  
...  
Keyword(s):  
Gene Expression ◽  
Squamous Cell ◽  
Large Scale ◽  
Biomarker Discovery ◽  
Gene Expression Signature ◽  
Predictive Biomarkers ◽  
Specific Gene ◽  
Specific Expression ◽  
Intrinsic Nature ◽  
Independent Cohort

Abstract Background Large-scale genetic and epigenetic deregulations enable cancer cells to ectopically activate tissue-specific expression programmes. A specifically designed strategy was applied to oral squamous cell carcinomas (OSCC) in order to detect ectopic gene activations and develop a prognostic stratification test. Methods A dedicated original prognosis biomarker discovery approach was implemented using genome-wide transcriptomic data of OSCC, including training and validation cohorts. Abnormal expressions of silent genes were systematically detected, correlated with survival probabilities and evaluated as predictive biomarkers. The resulting stratification test was confirmed in an independent cohort using immunohistochemistry. Results A specific gene expression signature, including a combination of three genes, AREG, CCNA1 and DDX20, was found associated with high-risk OSCC in univariate and multivariate analyses. It was translated into an immunohistochemistry-based test, which successfully stratified patients of our own independent cohort. Discussion The exploration of the whole gene expression profile characterising aggressive OSCC tumours highlights their enhanced proliferative and poorly differentiated intrinsic nature. Experimental targeting of CCNA1 in OSCC cells is associated with a shift of transcriptomic signature towards the less aggressive form of OSCC, suggesting that CCNA1 could be a good target for therapeutic approaches.

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