Abstract
Here, we describe a proteomic pipeline to use a human microglial cell line as a biological model to study schizophrenia. In order to maximize the proteome coverage, we apply two-dimensional liquid chromatography coupled with ultra-definition MSE mass spectrometry (LC-UDMSE) using a data-independent acquisition (DIA) approach, with an optimization of drift time collision energy.
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References
WHO (2014) WHO |(2014) WHO | Schizophrenia
Freedman R (2003) Schizophrenia. N Engl J Med 349:1738–1749
Kahn RS, Sommer IE, Murray RM et al (2015) Schizophrenia. Nat Rev Dis Primers 1:15,067
Owen MJ, O’Donovan MC, Thapar A et al (2011) Neurodevelopmental hypothesis of schizophrenia. Br J Psychiatry 198:173–175
Borrell J (2002) Prenatal immune challenge disrupts sensorimotor gating in adult rats implications for the etiopathogenesis of schizophrenia. Neuropsychopharmacology 26:204–215
Zuckerman L, Weiner I (2005) Maternal immune activation leads to behavioral and pharmacological changes in the adult offspring. J Psychiatr Res 39:311–323
Estes ML, McAllister AK (2016) Maternal immune activation: implications for neuropsychiatric disorders. Science 353:772–777
Mattei D, Ivanov A, Ferrai C et al (2017) Maternal immune activation results in complex microglial transcriptome signature in the adult offspring that is reversed by minocycline treatment. Transl Psychiatry 7:e1120
Prinz M, Jung S, Priller J (2019) Microglia biology: one century of evolving concepts. Cell 179:292–311
Bloomfield PS, Selvaraj S, Veronese M et al (2016) Microglial activity in people at ultra high risk of psychosis and in schizophrenia: an [(11)C]PBR28 PET brain imaging study. Am J Psychiatry 173:44–52
Schizophrenia Working Group of the Psychiatric Genomics Consortium (2014) Biological insights from 108 schizophrenia-associated genetic loci. Nature 511:421–427
Network and Pathway Analysis Subgroup of Psychiatric Genomics Consortium (2015) Psychiatric genome-wide association study analyses implicate neuronal, immune and histone pathways. Nat Neurosci 18:199–209
Sekar A, Bialas AR, de Rivera H et al (2016) Schizophrenia risk from complex variation of complement component 4. Nature 530:177–183
Xu J, Sun J, Chen J et al (2012) RNA-Seq analysis implicates dysregulation of the immune system in schizophrenia. BMC Genomics 13(Suppl 8):S2
Velásquez E, Martins-de-Souza D, Velásquez I et al (2019) Quantitative subcellular proteomics of the orbitofrontal cortex of schizophrenia patients. J Proteome Res 18:4240
Martins-de-Souza D, Gattaz WF, Schmitt A et al (2009) Prefrontal cortex shotgun proteome analysis reveals altered calcium homeostasis and immune system imbalance in schizophrenia. Eur Arch Psychiatry Clin Neurosci 259:151–163
de Witte L, Tomasik J, Schwarz E et al (2014) Cytokine alterations in first-episode schizophrenia patients before and after antipsychotic treatment. Schizophr Res 154:23–29
Li Y, Zhou K, Zhang Z et al (2012) Label-free quantitative proteomic analysis reveals dysfunction of complement pathway in peripheral blood of schizophrenia patients: evidence for the immune hypothesis of schizophrenia. Mol BioSyst 8:2664–2671
Zuccoli GS, Saia-Cereda VM, Nascimento JM et al (2017) The energy metabolism dysfunction in psychiatric disorders postmortem brains: focus on proteomic evidence. Front Neurosci 11:493
Saia-Cereda VM, Cassoli JS, Martins-de-Souza D et al (2017) Psychiatric disorders biochemical pathways unraveled by human brain proteomics. Eur Arch Psychiatry Clin Neurosci 267:3–17
Yates JR 3rd (2013) The revolution and evolution of shotgun proteomics for large-scale proteome analysis. J Am Chem Soc 135:1629–1640
Ludwig C, Gillet L, Rosenberger G et al (2018) Data-independent acquisition-based SWATH-MS for quantitative proteomics: a tutorial. Mol Syst Biol 14:e8126
Silva JC, Denny R, Dorschel CA et al (2005) Quantitative proteomic analysis by accurate mass retention time pairs. Anal Chem 77:2187–2200
Silva JC, Gorenstein MV, Li G-Z et al (2006) Absolute quantification of proteins by LCMSE: a virtue of parallel MS acquisition. Mol Cell Proteomics 5:144–156
Silva JC, Denny R, Dorschel C et al (2006) Simultaneous qualitative and quantitative analysis of the Escherichia coli proteome: a sweet tale. Mol Cell Proteomics 5:589–607
Geromanos SJ, Hughes C, Ciavarini S et al (2012) Using ion purity scores for enhancing quantitative accuracy and precision in complex proteomics samples. Anal Bioanal Chem 404:1127–1139
Distler U, Kuharev J, Navarro P et al (2014) Drift time-specific collision energies enable deep-coverage data-independent acquisition proteomics. Nat Methods 11:167–170
Distler U, Kuharev J, Navarro P et al (2016) Label-free quantification in ion mobility-enhanced data-independent acquisition proteomics. Nat Protoc 11:795–812
Acknowledgments
GRO and DMS would like to thank FAPESP for the
Funding (under grant numbers 18/01410-1, 18/03673-0, 17/25588-1, 19/00098-7).
Conflicts of Interest: The authors declare no conflicts of interest.
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Reis-de-Oliveira, G., Carregari, V.C., Martins-de-Souza, D. (2021). DIA-MSE to Study Microglial Function in Schizophrenia. In: Marcus, K., Eisenacher, M., Sitek, B. (eds) Quantitative Methods in Proteomics. Methods in Molecular Biology, vol 2228. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1024-4_24
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DOI: https://doi.org/10.1007/978-1-0716-1024-4_24
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