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Neuromelanin is a complex polymer pigment found primarily in the dopaminergic neurons of human substantia nigra. Neuromelanin pigment is stored in granules including a protein matrix and lipid droplets. Neuromelanin granules are yet only partially characterised regarding their structure and function. To clarify the exact function of neuromelanin granules in humans, their enrichment and in-depth characterization from human substantia nigra is necessary. Previously published global proteome studies of neuromelanin granules in human substantia nigra required high tissue amounts. Due to the limited availability of human brain tissue we established a new method based on laser microdissection combined with mass spectrometry for the isolation and analysis of neuromelanin granules. With this method it is possible for the first time to isolate a sufficient amount of neuromelanin granules for global proteomics analysis from ten 10 μm tissue sections. In total 1,000 proteins were identified associated with neuromelanin granules. More than 68% of those proteins were also identified in previously performed studies. Our results confirm and further extend previously described findings, supporting the connection of neuromelanin granules to iron homeostasis and lysosomes or endosomes. Hence, this method is suitable for the donor specific enrichment and proteomic analysis of neuromelanin granules.

Cerebrospinal fluid (CSF) is in direct contact with the brain and serves as a valuable specimen to examine diseases of the central nervous system through analyzing its components. These include the analysis of metabolites, cells as well as proteins. For identifying new suitable diagnostic protein biomarkers bottom-up data-dependent acquisition (DDA) mass spectrometry-based approaches are most popular. Drawbacks of this method are stochastic and irreproducible precursor ion selection. Recently, data-independent acquisition (DIA) emerged as an alternative method. It overcomes several limitations of DDA, since it combines the benefits of DDA and targeted methods like selected reaction monitoring (SRM). We established a DIA method for in-depth proteome analysis of CSF. For this, four spectral libraries were generated with samples from native CSF ( n = 5), CSF fractionation (15 in total) and substantia nigra fractionation (54 in total) and applied to three CSF DIA replicates. The DDA and DIA methods for CSF were conducted with the same nanoLC parameters using a 180 min gradient. Compared to a conventional DDA method, our DIA approach increased the number of identified protein groups from 648 identifications in DDA to 1574 in DIA using a comprehensive spectral library generated with DDA measurements from five native CSF and 54 substantia nigra fractions. We also could show that a sample specific spectral library generated from native CSF only increased the identification reproducibility from three DIA replicates to 90% (77% with a DDA method). Moreover, by utilizing a substantia nigra specific spectral library for CSF DIA, over 60 brain-originated proteins could be identified compared to only 11 with DDA. In conclusion, the here presented optimized DIA method substantially outperforms DDA and could develop into a powerful tool for biomarker discovery in CSF. Data are available via ProteomeXchange with the identifiers PXD010698, PXD010708, PXD010690, PXD010705, and PXD009624.

Cerebrospinal fluid is investigated in biomarker studies for various neurological disorders of the central nervous system due to its proximity to the brain. Currently, only a limited number of biomarkers have been validated in independent studies. The high variability in the protein composition and protein abundance of cerebrospinal fluid between as well as within individuals might be an important reason for this phenomenon. To evaluate this possibility, we investigated the inter- and intraindividual variability in the cerebrospinal fluid proteome globally, with a specific focus on disease biomarkers described in the literature. Cerebrospinal fluid from a longitudinal study group including 12 healthy control subjects was analyzed by label-free quantification (LFQ) via LC-MS/MS. Data were quantified via MaxQuant. Then, the intra- and interindividual variability and the reference change value were calculated for every protein. We identified and quantified 791 proteins, and 216 of these proteins were abundant in all samples and were selected for further analysis. For these proteins, we found an interindividual coefficient of variation of up to 101.5% and an intraindividual coefficient of variation of up to 29.3%. Remarkably, these values were comparably high for both proteins that were published as disease biomarkers and other proteins. Our results support the hypothesis that natural variability greatly impacts cerebrospinal fluid protein biomarkers because high variability can lead to unreliable results. Thus, we suggest controlling the variability of each protein to distinguish between good and bad biomarker candidates, e.g., by utilizing reference change values to improve the process of evaluating potential biomarkers in future studies.

Brain function in normal aging and neurological diseases has long been a subject of interest. With current technology, it is possible to go beyond descriptive analyses to characterize brain cell populations at the molecular level. However, the brain comprises over 100 billion highly specialized cells, and it is a challenge to discriminate different cell groups for analyses. Isolating intact neurons is not feasible with traditional methods, such as tissue homogenization techniques. The advent of laser microdissection techniques promises to overcome previous limitations in the isolation of specific cells. Here, we provide a detailed protocol for isolating and analyzing neurons from postmortem human brain tissue samples. We describe a workflow for successfully freezing, sectioning and staining tissue for laser microdissection. This protocol was validated by mass spectrometric analysis. Isolated neurons can also be employed for western blotting or PCR. This protocol will enable further examinations of brain cell-specific molecular pathways and aid in elucidating distinct brain functions.

The analysis of brain function in normal aging and neurodegenerative, psychiatric, and neurological diseases has long been a subject of interest and has historically been investigated through descriptive analysis of macroscopic or microscopic observations. It is now possible to characterize brain cells, such as neurons and glial cells, or even their subcellular components, at the molecular level. This ability enables researchers to more closely examine brain cell specific molecular pathways to elucidate distinct brain functions. Furthermore, the analysis of neuronal maintenance and disease-causing effects is a central component of neurological investigations, which include proteomic approaches. Proteomics allows the identification of thousands of proteins through descriptive and comparative analyses and can provide a detailed overview of a distinct cellular state. Such analyses often require the isolation of individual cell types or subcellular components to investigate specific questions. This review provides an overview of the currently applied state-of-the-art prefractionation strategies in this field.

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Humans age and the ageing process affects cells in all areas of the human body, including nerve cells within the brain. With advancing age there is also a rise in the probability of developing a neurodegenerative disorder such as, e.g., amyotrophic lateral sclerosis, Huntington's disease, Parkinson's disease, or Alzheimer's disease. In all these age-related neurodegenerative disorders, distinct neuron populations within specific brain regions are primarily affected. For example, Parkinson's disease is characterized by a slowly progressive degeneration of dopaminergic neurons in the substantia nigra whereas the entorhinal cortex is first affected in Alzheimer's disease. In patients suffering from Huntington's disease, neurons in both striatum and cortex undergo substantial cell loss and in amyotrophic lateral sclerosis the neurodegeneration arises from the spinal cord and the motor cortex. For the investigation of the differences in neuronal vulnerability, it is important to examine the protein expression pattern in these specific neural populations. By this, conclusions about the origination process of these diseases can be achieved. In order to obtain this objective, specific isolation of distinct neurons from the surrounding brain tissue is indispensable. However, discrimination as well as isolation of distinct types of neurons can be challenging, due to the brain tissue's complexity. With traditional methods such as the homogenization of tissue samples, a specific isolation of single neuron populations is not feasible because homogenization results into a mixture containing all cell types. Laser microdissection can overcome this technical limitation. First, this method enables visualization of tissues via a microscopic unit and therefore an enhanced discrimination of different brain cells. Second, a laser device guarantees a contact-free and consequently a contamination-free separation of distinct neurons from the surrounding brain tissue. In the following, we present a detailed protocol that includes a workflow for the isolation and analysis of neurons from freshly frozen post mortem human brain tissue samples. During this procedure, the brain tissue is sectioned, stained, laser microdissected, and ultimately analyzed by high-performance liquid chromatography-mass spectrometry.