Spatiotemporal Proteomic Profiling of Human Cerebral Development

Mass spectrometry (MS) analysis of human post-mortem central nervous system (CNS) tissue and induced pluripotent stem cell (iPSC)-based directed differentiations offer complementary avenues to define protein signatures of neurodevelopment. Methodological improvements of formalin-fixed, paraffin-embedded (FFPE) protein isolation now enable widespread proteomic analysis of well-annotated archival tissue samples in the context of development and disease. Here, we utilize a shotgun label-free quantification (LFQ) MS method to profile magnetically enriched human cortical neurons and neural progenitor cells (NPCs) derived from iPSCs. We use these signatures to help define spatiotemporal protein dynamics of developing human FFPE cerebral regions. We show that the use of high resolution Q Exactive mass spectrometers now allow simultaneous quantification of >2700 proteins in a single LFQ experiment and provide sufficient coverage to define novel biomarkers and signatures of NPC maintenance and differentiation. Importantly, we show that this abbreviated strategy allows efficient recovery of novel cytoplasmic, membrane-specific and synaptic proteins that are shared between both in vivo and in vitro neuronal differentiation. This study highlights the discovery potential of non-comprehensive high-throughput proteomic profiling of unfractionated clinically well-annotated FFPE human tissue from a diverse array of development and diseased states.

LC-MSE, Multiplex MS/MS, Ion Mobility, and Label-Free Quantitation in Clinical Proteomics

Proteomic tools can only be implemented in clinical settings if high-throughput, automated, sensitive, and accurate methods are developed. This has driven researchers to the edge of mass spectrometry (MS)-based proteomics capacity. Here we provide an overview of recent achievements in mass spectrometric technologies and instruments. This includes development of high and ultra definition-MS^E (HDMS^E and UDMS^E) through implementation of ion mobility (IM) MS towards sensitive and accurate label-free proteomics using ultra performance liquid chromatography (UPLC). Label free UPLC-HDMS^E is less expensive than labeled-based quantitative proteomics and has no limits regarding the number of samples that can be analyzed and compared, which is an important requirement for supporting clinical applications.

Neuroproteomic profiling of human body fluids

Analysis of protein expression and abundance provides a possibility to extend the current knowledge on disease-associated processes and pathways. The human brain is a complex organ and dysfunction or damage can give rise to a variety of neurological diseases. Although many proteins potentially reflecting disease progress are originating from brain, the scarce availability of human tissue material has lead to utilization of body fluids such as cerebrospinal fluid and blood in disease-related research. Within the most common neurological disorders, much effort has been spent on studying the role of a few hallmark proteins in disease pathogenesis but despite extensive investigation, the signatures they provide seem insufficient to fully understand and predict disease progress. In order to expand the view the field of neuroproteomics has lately emerged alongside developing technologies, such as affinity proteomics and mass spectrometry, for multiplexed and high-throughput protein profiling. Here, we provide an overview of how such technologies have been applied to study neurological disease and we also discuss some important considerations concerning discovery of disease-associated profiles.

New insights into the human brain proteome: Protein expression profiling of deep brain stimulation target areas

Deep brain stimulation (DBS) is a neurosurgical procedure that provides therapeutic benefits for movement and affective disorders. The nucleus basalis of Meynert (NBM) and substantia nigra (SN) are considered target areas to apply DBS. Even though the degeneration of NBM and SN underlies the cognitive decline observed in neurological diseases, the protein knowledge derived from both areas is scarce. We have characterized the proteome present in both subcortical brain areas using the Triple TOF 5600 mass spectrometer, identifying 2775 and 3469 proteoforms in NBM and SN respectively. Data mining of MS-generated proteomic data have revealed that: i) 675 proteins tend to localize to synaptic ending, ii) 61% of the global dataset is also present in human CSF and/or plasma, and iii) 894 proteins have not been previously identified in healthy brain by MS. The correlation of NBM and SN proteomic expression profiles with human brain transcriptome data available at Allen Brain Atlas has revealed protein evidence for 250 genes considered with brain-wide expression and 112 genes with region-specific expression in human brain. In addition, protein datasets have been classified according to their chromosomal origin, increasing the current proteome coverage in healthy human brain.

BIOLOGICAL SIGNIFICANCE

The nucleus basalis of Meynert and substantia nigra are brain areas of clinical interest to apply the deep brain stimulation (DBS) technology in neurosurgery. Our proteomic characterization has revealed 675 proteins involved in the regulation of synaptic transmission, electrical machinery, and neurotransmitter release in both DBS target areas. Moreover, 2599 identified proteins present capacity to be secreted to the CSF and plasma. Our data contribute to a further step towards the characterization of the anatomical atlas of the human brain proteome, detecting 652 proteins that are common between different basal ganglia structures. This article is part of a Special Issue entitled: HUPO 2014.

Toward defining the anatomo-proteomic puzzle of the human brain: An integrative analysis

The human brain is exceedingly complex, constituted by billions of neurons and trillions of synaptic connections that, in turn, define ∼900 neuroanatomical subdivisions in the adult brain (Hawrylycz et al. An anatomically comprehensive atlas of the human brain transcriptome. Nature 2012, 489, 391-399). The human brain transcriptome has revealed specific regional transcriptional signatures that are regulated in a spatiotemporal manner, increasing the complexity of the structural and molecular organization of this organ (Kang et al. Spatio-temporal transcriptome of the human brain. Nature 2011, 478, 483-489). During the last decade, neuroproteomics has emerged as a powerful approach to profile neural proteomes using shotgun-based MS, providing complementary information about protein content and function at a global level. Here, we revise recent proteome profiling studies performed in human brain, with special emphasis on proteome mapping of anatomical macrostructures, specific subcellular compartments, and cerebrospinal fluid. Moreover, we have performed an integrative functional analysis of the protein compilation derived from these large-scale human brain proteomic studies in order to obtain a comprehensive view of human brain biology. Finally, we also discuss the potential contribution of our meta-analysis to the Chromosome-centric Human Proteome Project initiative.

Data-independent MS/MS quantification of neuropeptides for determination of putative feeding-related neurohormones in microdialysate

Food consumption is an important behavior that is regulated by an intricate array of neuropeptides (NPs). Although many feeding-related NPs have been identified in mammals, precise mechanisms are unclear and difficult to study in mammals, as current methods are not highly multiplexed and require extensive a priori knowledge about analytes. New advances in data-independent acquisition (DIA) MS/MS and the open-source quantification software Skyline have opened up the possibility to identify hundreds of compounds and quantify them from a single DIA MS/MS run. An untargeted DIA MS^E quantification method using Skyline software for multiplexed, discovery-driven quantification was developed and found to produce linear calibration curves for peptides at physiologically relevant concentrations using a protein digest as internal standard. By using this method, preliminary relative quantification of the crab Cancer borealis neuropeptidome (<2 kDa, 137 peptides from 18 families) was possible in microdialysates from 8 replicate feeding experiments. Of these NPs, 55 were detected with an average mass error below 10 ppm. The time-resolved profiles of relative concentration changes for 6 are shown, and there is great potential for the use of this method in future experiments to aid in correlation of NP changes with behavior. This work presents an unbiased approach to winnowing candidate NPs related to a behavior of interest in a functionally relevant manner, and demonstrates the success of such a UPLC-MS^E quantification method using the open source software Skyline.

Brain quantitative proteomics combining GeLC-MS and isotope-coded protein labeling (ICPL)

Proteomics has been revolutionized by the rapid advance of mass spectrometric instrumentations and techniques. Parallel methodologies for the quantification of proteomes also evolved, including in vitro stable isotope labeling. Here, we present a protocol for employing isotope-coded protein labeling (ICPL) as part of a shotgun proteomics workflow denoting its advantages and disadvantages. This protocol is suitable to studying any proteome of interest, only requiring a specific sample preparation and protein identification. Given our expertise, descriptions here are centered on the study of brain disorders.

Recent advances in quantitative neuroproteomics

The field of proteomics is undergoing rapid development in a number of different areas including improvements in mass spectrometric platforms, peptide identification algorithms and bioinformatics. In particular, new and/or improved approaches have established robust methods that not only allow for in-depth and accurate peptide and protein identification and modification, but also allow for sensitive measurement of relative or absolute quantitation. These methods are beginning to be applied to the area of neuroproteomics, but the central nervous system poses many specific challenges in terms of quantitative proteomics, given the large number of different neuronal cell types that are intermixed and that exhibit distinct patterns of gene and protein expression. This review highlights the recent advances that have been made in quantitative neuroproteomics, with a focus on work published over the last five years that applies emerging methods to normal brain function as well as to various neuropsychiatric disorders including schizophrenia and drug addiction as well as of neurodegenerative diseases including Parkinson's disease and Alzheimer's disease. While older methods such as two-dimensional polyacrylamide electrophoresis continued to be used, a variety of more in-depth MS-based approaches including both label (ICAT, iTRAQ, TMT, SILAC, SILAM), label-free (label-free, MRM, SWATH) and absolute quantification methods, are rapidly being applied to neurobiological investigations of normal and diseased brain tissue as well as of cerebrospinal fluid (CSF). While the biological implications of many of these studies remain to be clearly established, that there is a clear need for standardization of experimental design and data analysis, and that the analysis of protein changes in specific neuronal cell types in the central nervous system remains a serious challenge, it appears that the quality and depth of the more recent quantitative proteomics studies is beginning to shed light on a number of aspects of neuroscience that relates to normal brain function as well as of the changes in protein expression and regulation that occurs in neuropsychiatric and neurodegenerative disorders.

Combining redox-proteomics and epigenomics to explain the involvement of oxidative stress in psychiatric disorders

Psychiatric disorders affect approximately 10% of adults in North-America. The complex nature of these illnesses makes the search for their pathophysiology a challenge. However, studies have consistently shown that mitochondrial dysfunction and oxidative stress are common features across major psychiatric disorders, including bipolar disorder and schizophrenia. Nevertheless, little is known about specific targets of oxidation in the brain. The search for redox sensors (protein targets for oxidation) will offer information about which pathways are regulated by oxidation in psychiatric disorders. Additionally, DNA is also a target for oxidative damage and recently, studies have suggested that oxidation of cytosine and guanosine can serve as an epigenetic modulator by decreasing or preventing further DNA methylation. Therefore, this review aims to discuss how we can use redox-proteomics and epigenomics to help explain the role of oxidative damage in major psychiatric disorders, which may ultimately lead to the identification of targets for development of new medications.

Mass Spectrometry-based Proteomics and Peptidomics for Systems Biology and Biomarker Discovery

The scientific community has shown great interest in the field of mass spectrometry-based proteomics and peptidomics for its applications in biology. Proteomics technologies have evolved to produce large datasets of proteins or peptides involved in various biological and disease progression processes producing testable hypothesis for complex biological questions. This review provides an introduction and insight to relevant topics in proteomics and peptidomics including biological material selection, sample preparation, separation techniques, peptide fragmentation, post-translation modifications, quantification, bioinformatics, and biomarker discovery and validation. In addition, current literature and remaining challenges and emerging technologies for proteomics and peptidomics are presented.