• Je něco špatně v tomto záznamu ?

Proteomic Analysis of Human Neural Stem Cell Differentiation by SWATH-MS

J. Tyleckova, J. Cervenka, I. Poliakh, J. Novak, KV. Kepkova, HK. Skalnikova, P. Vodicka

. 2022 ; 2520 (-) : 335-360. [pub] -

Jazyk angličtina Země Spojené státy americké

Typ dokumentu časopisecké články, práce podpořená grantem

Perzistentní odkaz   https://www.medvik.cz/link/bmc22025493

The unique properties of stem cells to self-renew and differentiate hold great promise in disease modelling and regenerative medicine. However, more information about basic stem cell biology and thorough characterization of available stem cell lines is needed. This is especially essential to ensure safety before any possible clinical use of stem cells or partially committed cell lines. As proteins are the key effector molecules in the cell, the proteomic characterization of cell lines, cell compartments or cell secretome and microenvironment is highly beneficial to answer above mentioned questions. Nowadays, method of choice for large-scale discovery-based proteomic analysis is mass spectrometry (MS) with data-independent acquisition (DIA). DIA is a robust, highly reproducible, high-throughput quantitative MS approach that enables relative quantification of thousands of proteins in one sample. In the current protocol, we describe a specific variant of DIA known as SWATH-MS for characterization of neural stem cell differentiation. The protocol covers the whole process from cell culture, sample preparation for MS analysis, the SWATH-MS data acquisition on TTOF 5600, the complete SWATH-MS data processing and quality control using Skyline software and the basic statistical analysis in R and MSstats package. The protocol for SWATH-MS data acquisition and analysis can be easily adapted to other samples amenable to MS-based proteomics.

Citace poskytuje Crossref.org

000      
00000naa a2200000 a 4500
001      
bmc22025493
003      
CZ-PrNML
005      
20221031100944.0
007      
ta
008      
221017s2022 xxu f 000 0|eng||
009      
AR
024    7_
$a 10.1007/7651_2022_462 $2 doi
035    __
$a (PubMed)35579839
040    __
$a ABA008 $b cze $d ABA008 $e AACR2
041    0_
$a eng
044    __
$a xxu
100    1_
$a Tyleckova, Jirina $u Institute of Animal Physiology and Genetics, Czech Academy of Sciences, Libechov, Czech Republic
245    10
$a Proteomic Analysis of Human Neural Stem Cell Differentiation by SWATH-MS / $c J. Tyleckova, J. Cervenka, I. Poliakh, J. Novak, KV. Kepkova, HK. Skalnikova, P. Vodicka
520    9_
$a The unique properties of stem cells to self-renew and differentiate hold great promise in disease modelling and regenerative medicine. However, more information about basic stem cell biology and thorough characterization of available stem cell lines is needed. This is especially essential to ensure safety before any possible clinical use of stem cells or partially committed cell lines. As proteins are the key effector molecules in the cell, the proteomic characterization of cell lines, cell compartments or cell secretome and microenvironment is highly beneficial to answer above mentioned questions. Nowadays, method of choice for large-scale discovery-based proteomic analysis is mass spectrometry (MS) with data-independent acquisition (DIA). DIA is a robust, highly reproducible, high-throughput quantitative MS approach that enables relative quantification of thousands of proteins in one sample. In the current protocol, we describe a specific variant of DIA known as SWATH-MS for characterization of neural stem cell differentiation. The protocol covers the whole process from cell culture, sample preparation for MS analysis, the SWATH-MS data acquisition on TTOF 5600, the complete SWATH-MS data processing and quality control using Skyline software and the basic statistical analysis in R and MSstats package. The protocol for SWATH-MS data acquisition and analysis can be easily adapted to other samples amenable to MS-based proteomics.
650    _2
$a buněčná diferenciace $7 D002454
650    _2
$a lidé $7 D006801
650    _2
$a hmotnostní spektrometrie $x metody $7 D013058
650    12
$a nervové kmenové buňky $x chemie $x metabolismus $7 D058953
650    _2
$a proteom $x analýza $7 D020543
650    12
$a proteomika $x metody $7 D040901
650    _2
$a řízení kvality $7 D011786
650    12
$a software $7 D012984
655    _2
$a časopisecké články $7 D016428
655    _2
$a práce podpořená grantem $7 D013485
700    1_
$a Cervenka, Jakub $u Institute of Animal Physiology and Genetics, Czech Academy of Sciences, Libechov, Czech Republic $u Department of Cell Biology, Faculty of Science, Charles University, Prague, Czech Republic
700    1_
$a Poliakh, Ievgeniia $u Institute of Animal Physiology and Genetics, Czech Academy of Sciences, Libechov, Czech Republic $u Department of Cell Biology, Faculty of Science, Charles University, Prague, Czech Republic
700    1_
$a Novak, Jaromir $u Institute of Animal Physiology and Genetics, Czech Academy of Sciences, Libechov, Czech Republic $u Department of Cell Biology, Faculty of Science, Charles University, Prague, Czech Republic
700    1_
$a Kepkova, Katerina Vodickova $u Institute of Animal Physiology and Genetics, Czech Academy of Sciences, Libechov, Czech Republic
700    1_
$a Skalnikova, Helena Kupcova $u Institute of Animal Physiology and Genetics, Czech Academy of Sciences, Libechov, Czech Republic
700    1_
$a Vodicka, Petr $u Institute of Animal Physiology and Genetics, Czech Academy of Sciences, Libechov, Czech Republic. vodicka@iapg.cas.cz
773    0_
$w MED00180389 $t Methods in molecular biology $x 1940-6029 $g Roč. 2520, č. - (2022), s. 335-360
856    41
$u https://pubmed.ncbi.nlm.nih.gov/35579839 $y Pubmed
910    __
$a ABA008 $b sig $c sign $y p $z 0
990    __
$a 20221017 $b ABA008
991    __
$a 20221031100940 $b ABA008
999    __
$a ok $b bmc $g 1854956 $s 1176783
BAS    __
$a 3
BAS    __
$a PreBMC
BMC    __
$a 2022 $b 2520 $c - $d 335-360 $e - $i 1940-6029 $m Methods in molecular biology $n Methods Mol Biol $x MED00180389
LZP    __
$a Pubmed-20221017

Najít záznam

Citační ukazatele

Možnosti archivace