Proteome analysis for 3T3-L1 adipocyte differentiation and biomarker discovery in adipogenesis

2008 ◽  
Vol 136 ◽  
pp. S441-S442
Author(s):  
Kim Hyun Ah ◽  
Md. Atiar Rahman ◽  
Suresh G. Kumar ◽  
Lee Sung Hak ◽  
Hwang Hee Sun ◽  
...  
2012 ◽  
Vol 2012 ◽  
pp. 1-14 ◽  
Author(s):  
Robert Klopfleisch ◽  
Achim D. Gruber

In recent years several technologies for the complete analysis of the transcriptome and proteome have reached a technological level which allows their routine application as scientific tools. The principle of these methods is the identification and quantification of up to ten thousands of RNA and proteins species in a tissue, in contrast to the sequential analysis of conventional methods such as PCR and Western blotting. Due to their technical progress transcriptome and proteome analyses are becoming increasingly relevant in all fields of biological research. They are mainly used for the explorative identification of disease associated complex gene expression patterns and thereby set the stage for hypothesis-driven studies. This review gives an overview on the methods currently available for transcriptome analysis, that is, microarrays, Ref-Seq, quantitative PCR arrays and discusses their potentials and limitations. Second, the most powerful current approaches to proteome analysis are introduced, that is, 2D-gel electrophoresis, shotgun proteomics, MudPIT and the diverse technological concepts are reviewed. Finally, experimental strategies for biomarker discovery, experimental settings for the identification of prognostic gene sets and explorative versus hypothesis driven approaches for the elucidation of diseases associated genes and molecular pathways are described and their potential for studies in veterinary research is highlighted.


2013 ◽  
Vol 7 (1-2) ◽  
pp. 123-135 ◽  
Author(s):  
Thomas Krüger ◽  
Janin Lautenschläger ◽  
Julian Grosskreutz ◽  
Heidrun Rhode

2006 ◽  
Vol 5 (1) ◽  
pp. 177-182 ◽  
Author(s):  
John M. Koomen ◽  
Christopher R. Wilson ◽  
Patrick Guthrie ◽  
Matthew J. Androlewicz ◽  
Ryuji Kobayashi ◽  
...  

2020 ◽  
Vol 11 ◽  
Author(s):  
Reema Bansal ◽  
Amod Gupta

The diseases affecting the retina or uvea (iris, ciliary body, or choroid) generate changes in the biochemical or protein composition of ocular fluids/tissues due to disruption of blood-retinal barrier. Ocular infections and inflammations are sight-threatening diseases associated with various infectious and non-infectious etiologies. Several etiological entities cause uveitis, a complex intraocular inflammatory disease. These causes of uveitis differ in different populations due to geographical, racial, and socioeconomic variations. While clinical appearance is sufficiently diagnostic in many diseases, some of the uveitic entities manifest nonspecific or atypical clinical presentation. Identification of biomarkers in such diseases is an important aid in their diagnostic armamentarium. Different diseases and their different severity states release varying concentrations of proteins, which can serve as biomarkers. Proteomics is a high throughput technology and a powerful screening tool for serum biomarkers in various diseases that identifies proteins by mass spectrometry and helps to improve the understanding of pathogenesis of a disease. Proteins determine the biological state of a cell. Once identified as biomarkers, they serve as future diagnostic and pharmaceutical targets. With a potential to redirect the diagnosis of idiopathic uveitis, ocular proteomics provide a new insight into the pathophysiology and therapeutics of various ocular inflammatory diseases. Tears, aqueous and vitreous humor represent potential repositories for proteomic biomarkers discovery in uveitis. With an extensive proteomics work done on animal models of uveitis, various types of human uveitis are being subjected to proteome analysis for biomarker discovery in different ocular fluids (vitreous, aqueous, or tears).


2018 ◽  
Vol 1 (2) ◽  
pp. e201800042 ◽  
Author(s):  
Tiannan Guo ◽  
Li Li ◽  
Qing Zhong ◽  
Niels J Rupp ◽  
Konstantina Charmpi ◽  
...  

It remains unclear to what extent tumor heterogeneity impacts on protein biomarker discovery. Here, we quantified proteome intra-tissue heterogeneity (ITH) based on a multi-region analysis of prostate tissues using pressure cycling technology and Sequential Windowed Acquisition of all THeoretical fragment ion mass spectrometry. We quantified 6,873 proteins and analyzed the ITH of 3,700 proteins. The level of ITH varied depending on proteins and tissue types. Benign tissues exhibited more complex ITH patterns than malignant tissues. Spatial variability of 10 prostate biomarkers was validated by immunohistochemistry in an independent cohort (n = 83) using tissue microarrays. Prostate-specific antigen was preferentially variable in benign prostatic hyperplasia, whereas growth/differentiation factor 15 substantially varied in prostate adenocarcinomas. Furthermore, we found that DNA repair pathways exhibited a high degree of variability in tumorous tissues, which may contribute to the genetic heterogeneity of tumors. This study conceptually adds a new perspective to protein biomarker discovery: it suggests that recent technological progress should be exploited to quantify and account for spatial proteome variation to complement biomarker identification and utilization.


2010 ◽  
Vol 25 (1) ◽  
pp. 27-35 ◽  
Author(s):  
Cécile Caubet ◽  
Chrystelle Lacroix ◽  
Stéphane Decramer ◽  
Jens Drube ◽  
Jochen H. H. Ehrich ◽  
...  

2020 ◽  
Author(s):  
Jesse Meyer ◽  
Natalie M. Niemi ◽  
David J. Pagliarini ◽  
Joshua J. Coon

<p>Liquid chromatography mass spectrometry (LC-MS) delivers sensitive peptide analysis for proteomics, but the methodology requires extensive analysis time, hampering throughput. Here, we demonstrate that flow injection analysis data-independent acquisition (FIA-DIA), using gas-phase peptide separation instead of LC, offers extremely fast proteome analysis. Incorporating ion mobility with FIA-DIA, we demonstrate the targeted quantification of over 500 proteins within minutes of MS data collection (~3.5 proteins/second). We show the utility of this technology to perform a complex multifactorial proteome study of interactions between nutrients, genotype, and mitochondrial toxins in a collection of cultured human cells. More than 45,000 quantitative protein measurements from 132 samples were achieved in only 4.4 hours of MS data collection. Enabling fast, unbiased proteome quantification without LC, FIA-DIA offers a new approach to boosting throughput critical to drug and biomarker discovery studies that require analysis of thousands of proteomes.</p>


2010 ◽  
Vol 9 (7) ◽  
pp. 3574-3582 ◽  
Author(s):  
Chan-Kyung J. Cho ◽  
Christopher R. Smith ◽  
Eleftherios P. Diamandis

2007 ◽  
Vol 4 (4) ◽  
pp. 531-538 ◽  
Author(s):  
Shen Hu ◽  
Joseph A Loo ◽  
David T Wong

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