The SELDI-TOF MS Approach to Proteomics: Protein Profiling and Biomarker Identification

2002 ◽  
Vol 292 (3) ◽  
pp. 587-592 ◽  
Author(s):  
Haleem J. Issaq ◽  
Timothy D. Veenstra ◽  
Thomas P. Conrads ◽  
Donna Felschow
2010 ◽  
Vol 2010 ◽  
pp. 1-15 ◽  
Author(s):  
Muriel De Bock ◽  
Dominique de Seny ◽  
Marie-Alice Meuwis ◽  
Jean-Paul Chapelle ◽  
Edouard Louis ◽  
...  

Protein profiling using SELDI-TOF-MS has gained over the past few years an increasing interest in the field of biomarker discovery. The technology presents great potential if some parameters, such as sample handling, SELDI settings, and data analysis, are strictly controlled. Practical considerations to set up a robust and sensitive strategy for biomarker discovery are presented. This paper also reviews biological fluids generally available including a description of their peculiar properties and the preanalytical challenges inherent to sample collection and storage. Finally, some new insights for biomarker identification and validation challenges are provided.


Author(s):  
Rim Abdel Samad ◽  
Zulfa Al Disi ◽  
Mohammad Ashfaq ◽  
Nabil Zouari

Occurrence of mineral forming and other bacteria in mats is well demonstrated. However, their high diversity shown by ribotyping was not explained, although it could explain the diversity of formed minerals. Common biomarkers as well as phylogenic relationships are useful tools to clustering the isolates and predict their potential role in the natural niche. In this study, combination of MALDI-TOF MS with PCA was shown a powerful tool to categorize 35 mineral forming bacterial strains isolated from Dohat Fshaikh sabkha, at northwest of Qatar (23 from decaying mats and 12 from living ones). 23 strains from decaying mats belong to Virgibacillus genus as identified by ribotyping and are shown highly involved in formation of protodolomite and a diversity of minerals. They were used as internal references in categorization of sabkha bacteria. Combination of isolation of bacteria on selective mineral forming media, their MALDI TOF MS protein profiling and PCA analysis established their relationship in a phyloproteomic based on protein biomarkers including m/z 4905, 3265, 5240, 6430, 7765, and 9815. PCA analysis clustered the studied strains into 3 major clusters, showing strong correspondence to the 3 phyloproteiomic groups that were established by the dendrogram. Both clustering analysis means have evidently demonstrated a relationship between known Virgibacillus strains and other related bacteria based on profiling of their synthesized proteins. Thus, larger populations of bacteria in mats can be easily screened for their potential to exhibit certain activities, which is of ecological, environmental and biotechnological significance.


2018 ◽  
Vol 32 (3) ◽  
pp. 388-392 ◽  
Author(s):  
P. Halada ◽  
K. Hlavackova ◽  
J. Risueño ◽  
E. Berriatua ◽  
P. Volf ◽  
...  

2008 ◽  
Vol 1 (1) ◽  
Author(s):  
Marie-Christine W Gast ◽  
Judith YMN Engwegen ◽  
Jan HM Schellens ◽  
Jos H Beijnen

2009 ◽  
Vol 3 (3) ◽  
pp. 383-393 ◽  
Author(s):  
Jakob Albrethsen ◽  
Anne Kaas ◽  
Eugen Schönle ◽  
Peter Swift ◽  
Mirjana Kocova ◽  
...  

2012 ◽  
Vol 26 (1) ◽  
pp. 1-9 ◽  
Author(s):  
Annemieke W.J. Opstal-van Winden ◽  
Jos H. Beijnen ◽  
Arnoud Loof ◽  
Waander L. van Heerde ◽  
Roel Vermeulen ◽  
...  

2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 10559-10559
Author(s):  
J. Lim ◽  
J. Cho ◽  
Y. Paik ◽  
Y. Chang ◽  
H. Kim

10559 Background: Gastric cancer is one of the most common malignancy in the world and one of the leading causes of cancer related death in Korea. Most treatments for advanced gastric cancer have limited efficacy. So early detection of gastric cancer could have profound impact on the successful treatment. Application of multiple biomarkers may improve the diagnostic prediction to distinguish cancer from non-cancer. ProteinChip Surface-Enhanced Laser Desorption/Ionization Time-of-flight Mass Spectrometry (SELDI-TOF-MS) system is one of the currently used techniques to identify biomarkers for cancers. In this study, we have explored whether the serum proteomic patterns by ProteinChip SELDI system can differentiate gastric cancers from non-cancer cohorts. Methods: We have screened protein profiles of 100 serum samples obtained from 60 gastric cancer patients and 40 healthy individuals. Protein expression profiles were expressed on ProteinChip Array and analyzed by PreoteinChip Reader. Peak intensities were normalized by total ion currency and analyzed by the Biomarker Wizard Software to identify the peaks showing significantly different intensities between normal and cancer groups. Classification analysis and construction of decision trees were done with the Biomarker Pattern Software. Results: SELDI -TOF-MS by averaging 50 laser spots collected at a laser intensity setting of 160, a detector sensitivity of 6, and mean mass range of 30 kDa. Seventeen protein peaks shown significant differences between two groups were chosen to make a protein biomarker pattern. The decision tree which gives the highest discrimination included four peaks at 5,919, 8,583, 10,286, and 13,758 as splitters. The sensitivity and the specificity for classification of with the decision tree giving the highest discrimination were 96.7% (58/60) and 97.5% (39/40), respectively. When the protein biomarker pattern was tested with the blinded test set including 30 gastric cancer patients and 20 healthy individuals and, it yielded a sensitivity of 93.3% (28/30) and a specificity of 90% (18/20). Conclusions: These results suggest that serum-protein profiling pattern by SELDI system may distinguish gastric cancer patients from normal counterparts with relatively high sensitivity and specificity. No significant financial relationships to disclose.


Parasitology ◽  
2017 ◽  
Vol 145 (5) ◽  
pp. 676-676 ◽  
Author(s):  
MAUREEN LAROCHE ◽  
JEAN-MICHEL BÉRENGER ◽  
GLADYS GAZELLE ◽  
DENIS BLANCHET ◽  
DIDIER RAOULT ◽  
...  

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