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Raster-Mode Continuous-Flow Liquid Microjunction Mass Spectrometry Imaging of Proteins in Thin Tissue Sections.
Griffiths, Rian L; Randall, Elizabeth C; Race, Alan M; Bunch, Josephine; Cooper, Helen J.
Afiliação
  • Griffiths RL; School of Biosciences, University of Birmingham , Edgbaston, Birmingham B15 2TT, U.K.
  • Randall EC; School of Biosciences, University of Birmingham , Edgbaston, Birmingham B15 2TT, U.K.
  • Race AM; PSIBS Doctoral Training Centre, University of Birmingham , Edgbaston, Birmingham B15 2TT, U.K.
  • Bunch J; National Physical Laboratory , Hampton Road, Teddington, Middlesex TW11 0LW, U.K.
  • Cooper HJ; National Physical Laboratory , Hampton Road, Teddington, Middlesex TW11 0LW, U.K.
Anal Chem ; 89(11): 5683-5687, 2017 06 06.
Article em En | MEDLINE | ID: mdl-28492310
Mass spectrometry imaging by use of continuous-flow liquid microjunction sampling at discrete locations (array mode) has previously been demonstrated. In this Letter, we demonstrate continuous-flow liquid microjunction mass spectrometry imaging of proteins from thin tissue sections in raster mode and discuss advantages (a 10-fold reduction in analysis time) and challenges (suitable solvent systems, data interpretation) of the approach. Visualization of data is nontrivial, requiring correlation of solvent-flow, mass spectral data acquisition rate, data quality, and liquid microjunction sampling area. The latter is particularly important for determining optimum pixel size. The minimum achievable pixel size is related to the scan time of the instrument used. Here we show a minimum achievable pixel size of 50 µm (x-dimension) when using an Orbitrap Elite; however a pixel size of 600 µm is recommended in order to minimize the effects of oversampling on image accuracy.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Limite: Animals / Humans Idioma: En Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Limite: Animals / Humans Idioma: En Ano de publicação: 2017 Tipo de documento: Article