Solvent effects on differentiation of mouse brain tissue using laser microdissection ‘cut and drop’ sampling with direct mass spectral analysis

John F. Cahill; Vilmos Kertesz; Tiffany Porta; J. C.Yves LeBlanc; Ron M.A. Heeren; Gary J. Van Berkel

doi:10.1002/rcm.8053

Solvent effects on differentiation of mouse brain tissue using laser microdissection ‘cut and drop’ sampling with direct mass spectral analysis

John F. Cahill
, Vilmos Kertesz
, Tiffany Porta
, J. C.Yves LeBlanc
, Ron M.A. Heeren
, Gary J. Van Berkel

Bioanalytical Mass Spectrometry

Research output: Contribution to journal › Article › peer-review

11 Scopus citations

Abstract

Rationale: Laser microdissection-liquid vortex capture/electrospray ionization mass spectrometry (LMD-LVC/ESI-MS) has potential for on-line classification of tissue but an investigation into what analytical conditions provide best spectral differentiation has not been conducted. The effects of solvent, ionization polarity, and spectral acquisition parameters on differentiation of mouse brain tissue regions are described. Methods: Individual 40 × 40 μm microdissections from cortex, white, grey, granular, and nucleus regions of mouse brain tissue were analyzed using different capture/ESI solvents, in positive and negative ion mode ESI, using time-of-flight (TOF)-MS and sequential window acquisitions of all theoretical spectra (SWATH)-MS (a permutation of tandem-MS), and combinations thereof. Principal component analysis-linear discriminant analysis (PCA-LDA), applied to each mass spectral dataset, was used to determine the accuracy of differentiation of mouse brain tissue regions. Results: Mass spectral differences associated with capture/ESI solvent composition manifested as altered relative distributions of ions rather than the presence or absence of unique ions. In negative ion mode ESI, 80/20 (v/v) methanol/water yielded spectra with low signal/noise ratios relative to other solvents. PCA-LDA models acquired using 90/10 (v/v) methanol/chloroform differentiated tissue regions with 100% accuracy while data collected using methanol misclassified some samples. The combination of SWATH-MS and TOF-MS data improved differentiation accuracy. Conclusions: Combined TOF-MS and SWATH-MS data differentiated white, grey, granular, and nucleus mouse tissue regions with greater accuracy than when solely using TOF-MS data. Using 90/10 (v/v) methanol/chloroform, tissue regions were perfectly differentiated. These results will guide future studies looking to utilize the potential of LMD-LVC/ESI-MS for tissue and disease differentiation.

Original language	English
Pages (from-to)	414-422
Number of pages	9
Journal	Rapid Communications in Mass Spectrometry
Volume	32
Issue number	5
DOIs	https://doi.org/10.1002/rcm.8053
State	Published - Mar 15 2018

Funding

The original advancement of the LMD‐LVC/ESI‐MS system was supported at ORNL by the U.S. Department of Energy, Office of Science, Basic Energy Sciences, Chemical Sciences, Geosciences, and Biosciences Division. T. Porta and R.M.A. Heeren acknowledge support of the LINK program of the Dutch Province of Limburg. We are grateful to Audrey Jongen (General Surgery, MUMC+) for providing us with the mouse brain sample and Lieke Lamont (M4I) for her technical assistance. The present application of the technology was supported at ORNL by, and the SCIEX TripleTOF® 5600+ mass spectrometer used in this work was provided on loan through, a Cooperative Research and Development Agreement with Sciex (CRADA NFE‐10‐02966). Julian Burke (Leica Microsystems) is thanked for the loan of the LMD7000 instrument. This manuscript has been authored by UT‐Battelle, LLC under Contract No. DE‐AC05‐ 00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non‐exclusive, paid‐up, irrevocable, world‐wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe‐public‐access‐plan). U. S. Department of Energy, Office of Science, Basic Energy Sciences, Chemical Sciences, Geosciences, and Biosciences Division; LINK program of the Dutch Province of Limburg; U.S. Department of Energy, Grant/Award Number: DE‐AC05‐00OR22725; Cooperative Research and Development Agreement with Sciex, Grant/Award Number: CRADA NFE‐10‐ 02966

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10.1002/rcm.8053

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@article{f1bb09c1e3fa4835b39985ded6954908,

title = "Solvent effects on differentiation of mouse brain tissue using laser microdissection {\textquoteleft}cut and drop{\textquoteright} sampling with direct mass spectral analysis",

abstract = "Rationale: Laser microdissection-liquid vortex capture/electrospray ionization mass spectrometry (LMD-LVC/ESI-MS) has potential for on-line classification of tissue but an investigation into what analytical conditions provide best spectral differentiation has not been conducted. The effects of solvent, ionization polarity, and spectral acquisition parameters on differentiation of mouse brain tissue regions are described. Methods: Individual 40 × 40 μm microdissections from cortex, white, grey, granular, and nucleus regions of mouse brain tissue were analyzed using different capture/ESI solvents, in positive and negative ion mode ESI, using time-of-flight (TOF)-MS and sequential window acquisitions of all theoretical spectra (SWATH)-MS (a permutation of tandem-MS), and combinations thereof. Principal component analysis-linear discriminant analysis (PCA-LDA), applied to each mass spectral dataset, was used to determine the accuracy of differentiation of mouse brain tissue regions. Results: Mass spectral differences associated with capture/ESI solvent composition manifested as altered relative distributions of ions rather than the presence or absence of unique ions. In negative ion mode ESI, 80/20 (v/v) methanol/water yielded spectra with low signal/noise ratios relative to other solvents. PCA-LDA models acquired using 90/10 (v/v) methanol/chloroform differentiated tissue regions with 100\% accuracy while data collected using methanol misclassified some samples. The combination of SWATH-MS and TOF-MS data improved differentiation accuracy. Conclusions: Combined TOF-MS and SWATH-MS data differentiated white, grey, granular, and nucleus mouse tissue regions with greater accuracy than when solely using TOF-MS data. Using 90/10 (v/v) methanol/chloroform, tissue regions were perfectly differentiated. These results will guide future studies looking to utilize the potential of LMD-LVC/ESI-MS for tissue and disease differentiation.",

author = "Cahill, \{John F.\} and Vilmos Kertesz and Tiffany Porta and LeBlanc, \{J. C.Yves\} and Heeren, \{Ron M.A.\} and \{Van Berkel\}, \{Gary J.\}",

note = "Publisher Copyright: Copyright {\textcopyright} 2018 John Wiley \& Sons, Ltd.",

year = "2018",

month = mar,

day = "15",

doi = "10.1002/rcm.8053",

language = "English",

volume = "32",

pages = "414--422",

journal = "Rapid Communications in Mass Spectrometry",

issn = "0951-4198",

publisher = "wiley",

number = "5",

}

TY - JOUR

T1 - Solvent effects on differentiation of mouse brain tissue using laser microdissection ‘cut and drop’ sampling with direct mass spectral analysis

AU - Cahill, John F.

AU - Kertesz, Vilmos

AU - Porta, Tiffany

AU - LeBlanc, J. C.Yves

AU - Heeren, Ron M.A.

AU - Van Berkel, Gary J.

PY - 2018/3/15

Y1 - 2018/3/15

N2 - Rationale: Laser microdissection-liquid vortex capture/electrospray ionization mass spectrometry (LMD-LVC/ESI-MS) has potential for on-line classification of tissue but an investigation into what analytical conditions provide best spectral differentiation has not been conducted. The effects of solvent, ionization polarity, and spectral acquisition parameters on differentiation of mouse brain tissue regions are described. Methods: Individual 40 × 40 μm microdissections from cortex, white, grey, granular, and nucleus regions of mouse brain tissue were analyzed using different capture/ESI solvents, in positive and negative ion mode ESI, using time-of-flight (TOF)-MS and sequential window acquisitions of all theoretical spectra (SWATH)-MS (a permutation of tandem-MS), and combinations thereof. Principal component analysis-linear discriminant analysis (PCA-LDA), applied to each mass spectral dataset, was used to determine the accuracy of differentiation of mouse brain tissue regions. Results: Mass spectral differences associated with capture/ESI solvent composition manifested as altered relative distributions of ions rather than the presence or absence of unique ions. In negative ion mode ESI, 80/20 (v/v) methanol/water yielded spectra with low signal/noise ratios relative to other solvents. PCA-LDA models acquired using 90/10 (v/v) methanol/chloroform differentiated tissue regions with 100% accuracy while data collected using methanol misclassified some samples. The combination of SWATH-MS and TOF-MS data improved differentiation accuracy. Conclusions: Combined TOF-MS and SWATH-MS data differentiated white, grey, granular, and nucleus mouse tissue regions with greater accuracy than when solely using TOF-MS data. Using 90/10 (v/v) methanol/chloroform, tissue regions were perfectly differentiated. These results will guide future studies looking to utilize the potential of LMD-LVC/ESI-MS for tissue and disease differentiation.

AB - Rationale: Laser microdissection-liquid vortex capture/electrospray ionization mass spectrometry (LMD-LVC/ESI-MS) has potential for on-line classification of tissue but an investigation into what analytical conditions provide best spectral differentiation has not been conducted. The effects of solvent, ionization polarity, and spectral acquisition parameters on differentiation of mouse brain tissue regions are described. Methods: Individual 40 × 40 μm microdissections from cortex, white, grey, granular, and nucleus regions of mouse brain tissue were analyzed using different capture/ESI solvents, in positive and negative ion mode ESI, using time-of-flight (TOF)-MS and sequential window acquisitions of all theoretical spectra (SWATH)-MS (a permutation of tandem-MS), and combinations thereof. Principal component analysis-linear discriminant analysis (PCA-LDA), applied to each mass spectral dataset, was used to determine the accuracy of differentiation of mouse brain tissue regions. Results: Mass spectral differences associated with capture/ESI solvent composition manifested as altered relative distributions of ions rather than the presence or absence of unique ions. In negative ion mode ESI, 80/20 (v/v) methanol/water yielded spectra with low signal/noise ratios relative to other solvents. PCA-LDA models acquired using 90/10 (v/v) methanol/chloroform differentiated tissue regions with 100% accuracy while data collected using methanol misclassified some samples. The combination of SWATH-MS and TOF-MS data improved differentiation accuracy. Conclusions: Combined TOF-MS and SWATH-MS data differentiated white, grey, granular, and nucleus mouse tissue regions with greater accuracy than when solely using TOF-MS data. Using 90/10 (v/v) methanol/chloroform, tissue regions were perfectly differentiated. These results will guide future studies looking to utilize the potential of LMD-LVC/ESI-MS for tissue and disease differentiation.

UR - https://www.scopus.com/pages/publications/85042118855

U2 - 10.1002/rcm.8053

DO - 10.1002/rcm.8053

M3 - Article

C2 - 29297944

AN - SCOPUS:85042118855

SN - 0951-4198

VL - 32

SP - 414

EP - 422

JO - Rapid Communications in Mass Spectrometry

JF - Rapid Communications in Mass Spectrometry

IS - 5

ER -

Solvent effects on differentiation of mouse brain tissue using laser microdissection ‘cut and drop’ sampling with direct mass spectral analysis

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