Literature DB >> 26333406

Approaches for targeted proteomics and its potential applications in neuroscience.

Sumit Sethi1, Dipti Chourasia, Ishwar S Parhar.   

Abstract

An extensive guide on practicable and significant quantitative proteomic approaches in neuroscience research is important not only because of the existing overwhelming limitations but also for gaining valuable understanding into brain function and deciphering proteomics from the workbench to the bedside. Early methodologies to understand the functioning of biological systems are now improving with high-throughput technologies, which allow analysis of various samples concurrently, or of thousand of analytes in a particular sample. Quantitative proteomic approaches include both gel-based and non-gel-based methods that can be further divided into different labelling approaches. This review will emphasize the role of existing technologies, their advantages and disadvantages, as well as their applications in neuroscience. This review will also discuss advanced approaches for targeted proteomics using isotope-coded affinity tag (ICAT) coupled with laser capture microdissection (LCM) followed by liquid chromatography tandem mass spectrometric (LC-MS/MS) analysis. This technology can further be extended to single cell proteomics in other areas of biological sciences and can be combined with other 'omics' approaches to reveal the mechanism of a cellular alterations. This approach may lead to further investigation in basic biology, disease analysis and surveillance, as well as drug discovery. Although numerous challenges still exist, we are confident that this approach will increase the understanding of pathological mechanisms involved in neuroendocrinology, neuropsychiatric and neurodegenerative disorders by delivering protein biomarker signatures for brain dysfunction.

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Year:  2015        PMID: 26333406     DOI: 10.1007/s12038-015-9537-1

Source DB:  PubMed          Journal:  J Biosci        ISSN: 0250-5991            Impact factor:   1.826


  166 in total

1.  CysTRAQ - A combination of iTRAQ and enrichment of cysteinyl peptides for uncovering and quantifying hidden proteomes.

Authors:  Vojtech Tambor; Christie L Hunter; Sean L Seymour; Marian Kacerovsky; Jiri Stulik; Juraj Lenco
Journal:  J Proteomics       Date:  2011-10-08       Impact factor: 4.044

Review 2.  A perspective on the use of iTRAQ reagent technology for protein complex and profiling studies.

Authors:  Lynn R Zieske
Journal:  J Exp Bot       Date:  2006-03-30       Impact factor: 6.992

3.  Quantitative phosphoproteomic analysis using iTRAQ method.

Authors:  Tomoya Asano; Takumi Nishiuchi
Journal:  Methods Mol Biol       Date:  2014

4.  Genetic imprinting during impaired spermatogenesis.

Authors:  Sonja Hartmann; Martin Bergmann; Rainer M Bohle; Wolfgang Weidner; Klaus Steger
Journal:  Mol Hum Reprod       Date:  2006-04-11       Impact factor: 4.025

5.  Quantitative proteomic analysis of primary neurons reveals diverse changes in synaptic protein content in fmr1 knockout mice.

Authors:  Lujian Liao; Sung Kyu Park; Tao Xu; Peter Vanderklish; John R Yates
Journal:  Proc Natl Acad Sci U S A       Date:  2008-09-30       Impact factor: 11.205

Review 6.  Laser-capture microdissection: opening the microscopic frontier to molecular analysis.

Authors:  N L Simone; R F Bonner; J W Gillespie; M R Emmert-Buck; L A Liotta
Journal:  Trends Genet       Date:  1998-07       Impact factor: 11.639

7.  Immuno-LCM: laser capture microdissection of immunostained frozen sections for mRNA analysis.

Authors:  F Fend; M R Emmert-Buck; R Chuaqui; K Cole; J Lee; L A Liotta; M Raffeld
Journal:  Am J Pathol       Date:  1999-01       Impact factor: 4.307

8.  Stable isotopic labeling by amino acids in cultured primary neurons: application to brain-derived neurotrophic factor-dependent phosphotyrosine-associated signaling.

Authors:  Daniel S Spellman; Katrin Deinhardt; Costel C Darie; Moses V Chao; Thomas A Neubert
Journal:  Mol Cell Proteomics       Date:  2008-02-06       Impact factor: 5.911

9.  Investigating the correspondence between transcriptomic and proteomic expression profiles using coupled cluster models.

Authors:  Simon Rogers; Mark Girolami; Walter Kolch; Katrina M Waters; Tao Liu; Brian Thrall; H Steven Wiley
Journal:  Bioinformatics       Date:  2008-10-30       Impact factor: 6.937

10.  Quantitative proteomics analysis of maternal plasma in Down syndrome pregnancies using isobaric tagging reagent (iTRAQ).

Authors:  Varaprasad Kolla; Paul Jenö; Suzette Moes; Sevgi Tercanli; Olav Lapaire; Mahesh Choolani; Sinuhe Hahn
Journal:  J Biomed Biotechnol       Date:  2009-11-05
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  5 in total

1.  Characterizing the proteome of bullous pemphigoid blister fluid utilizing tandem mass tag labeling coupled with LC-MS/MS.

Authors:  Farzan Solimani; Dario Didona; Jing Li; Lei Bao; Payal M Patel; Giulia Gasparini; Khalaf Kridin; Emanuele Cozzani; Michael Hertl; Kyle T Amber
Journal:  Arch Dermatol Res       Date:  2021-06-21       Impact factor: 3.033

2.  Protocol for the Bottom-Up Proteomic Analysis of Mouse Spleen.

Authors:  Paul Dowling; Stephen Gargan; Margit Zweyer; Michael Henry; Paula Meleady; Dieter Swandulla; Kay Ohlendieck
Journal:  STAR Protoc       Date:  2020-12-03

Review 3.  Omics-Based Biomarkers: Application of Metabolomics in Neuropsychiatric Disorders.

Authors:  Sumit Sethi; Elisa Brietzke
Journal:  Int J Neuropsychopharmacol       Date:  2015-10-09       Impact factor: 5.176

4.  A new SWATH ion library for mouse adult hippocampal neural stem cells.

Authors:  Clarissa Braccia; Meritxell Pons Espinal; Mattia Pini; Davide De Pietri Tonelli; Andrea Armirotti
Journal:  Data Brief       Date:  2018-02-27

5.  Quantitative proteomic analysis of intracerebral hemorrhage in rats with a focus on brain energy metabolism.

Authors:  Tao Liu; Jing Zhou; Hanjin Cui; Pengfei Li; Haigang Li; Yang Wang; Tao Tang
Journal:  Brain Behav       Date:  2018-10-11       Impact factor: 2.708

  5 in total

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