A robust protocol is presented here for isolating neuromelanin granules from human post-mortem substantia nigra pars compacta tissue via laser microdissection. This revised and optimized protocol massively minimizes the required time for sample collection, reduces the required sample amount, and enhances the identification and quantification of proteins by LC-MS/MS analysis.
Neuromelanin is a black-brownish pigment, present in so-called neuromelanin granules (NMGs) in dopaminergic neurons of the substantia nigra pars compacta. Besides neuromelanin, NMGs contain a variety of proteins, lipids, and metals. Although NMGs-containing dopaminergic neurons are preferentially lost in neurodegenerative diseases like Parkinson's disease and dementia with Lewy bodies, only little is known about the mechanism of NMG formation and the role of NMGs in health and disease. Thus, further research on the molecular characterization of NMGs is essential. Unfortunately, standard protocols for the isolation of proteins are based on density gradient ultracentrifugation and therefore require high amounts of human tissue. Thus, an automated laser microdissection (LMD)-based protocol is established here which allows the collection of NMGs and surrounding substantia nigra (SN) tissue using minimal amounts of tissue in an unbiased, automatized way. Excised samples are subsequently analyzed by mass spectrometry to decipher their proteomic composition. With this workflow, 2,079 proteins were identified of which 514 proteins were exclusively identified in NMGs and 181 in SN. The present results have been compared with a previous study using a similar LMD-based approach reaching an overlap of 87.6% for both proteomes, verifying the applicability of the revised and optimized protocol presented here. To validate current findings, proteins of interest were analyzed by targeted mass spectrometry, e.g., parallel reaction monitoring (PRM)-experiments.
Every tissue consists of a heterogeneous mixture of different cell types, but the specific isolation of one cell type often is indispensable for a more precise characterization. Laser microdissection (LMD), coupling a microscope with a laser application, is a powerful tool for the specific isolation of tissue areas, single cells, or cellular substructures out of a complex composite. The application of LMD in combination with mass spectrometry (LMD-MS) has already been successfully implemented for several research questions, including isolation of DNA1, RNA2 and proteins3,4,5. In this protocol, a revised and optimized LMD-MS protocol is described for the proteomic analysis of human post-mortem brain tissue and sub-cellular components to decipher novel pathomechanisms of Parkinson's disease.
Neuromelanin is a black, nearly-insoluble pigment found in the catecholaminergic, dopamine-producing neurons of the substantia nigra pars compacta6. Together with proteins and lipids, it accumulates in organelle-like granules surrounded by a double membrane, called neuromelanin granules (NMGs)7,8,9. NMGs can be observed from the age of three years in humans increasing in quantity and density during the aging process10,11. To date, there is no definite hypothesis on neuromelanin formation, but one assumption is that neuromelanin is formed through the oxidation of dopamine12. Other hypotheses are based on enzymatic production of neuromelanin (e.g., tyrosinase)13. Neuromelanin itself was found to have a high binding affinity to lipids, toxins, metal ions, and pesticides. Based on these findings, the formation of NMGs is assumed to protect the cell from the accumulation of toxic and oxidative substances and from environmental toxins14,15. Besides this neuroprotective function, there is evidence that neuromelanin may cause neurodegenerative effects, e.g., by iron saturation and the subsequent catalysis of free radicals16,17. Furthermore, neuromelanin released during neurodegenerative processes can be decomposed by hydrogen peroxide, which could accelerate necrosis by reactive metals and other toxic compounds previously bound to neuromelanin and may contribute to neuroinflammation and cellular damage18. However, until now the exact role of NMGs in neurodegenerative processes like in the course of Parkinson's disease is not clearly understood. Still, NMGs seem to be involved in the pathogenesis of Parkinson's disease and their specific analysis is of utmost importance to unravel their role in neurodegeneration. Unfortunately, common laboratory animals (e.g., mice and rats) and cell lines lack NMGs19. Therefore, researchers especially rely on post-mortem brain tissue for their analysis. In the past, NMG isolation by density gradient centrifugation relied on the availability of high amounts of substantia nigra tissue20,21. Today, LMD presents a versatile tool to specifically isolate NMGs from human brain samples to then analyze them by LC-MS/MS.
In this protocol, an improved and automated version of a previous protocol22 is presented for the isolation of NMGs and surrounding tissue (SN), enabling a faster sample generation, higher numbers of identified and quantified proteins, and a severe reduction of required tissue amounts.
The use of human brain tissue was approved by the ethics committee of the Ruhr-University Bochum, Germany (file number 4760-13), according to German regulations and guidelines. This protocol has been applied on commercially obtained substantia nigra pars compacta tissue slices. A graphical overview of the presented protocol is shown in Figure 1.
1. Tissue sectioning
2. Laser Microdissection and Pressure Catapulting
NOTE: As neuromelanin granules are visible without any staining due to their black-brownish color, no staining is necessary for this protocol. Nevertheless, different staining procedures can be combined with this protocol if required. Keep in mind that the use of blocking solutions or antibodies will influence the LC-MS/MS analyses.
3. Tryptic digestion
4. High-performance liquid chromatography and mass spectrometry
NOTE: The following high-performance liquid chromatography (HPLC) mass spectrometric (MS) analysis are optimized for the specific LC system with a trapping column device and mass spectrometer used here (see Table of Materials). For other LC and MS systems, adaption of parameters is recommended.
5. Analysis of proteomic raw data using MaxQuant
NOTE: A detailed information on MaxQuant parameters is provided in Supplementary Table 2. They are briefly described below.
6. Statistical analysis using Perseus
7. Validation of selected proteins
NOTE: Commonly used methods for validation of MS data are, for example, immunological staining or Western Blot. Due to the dark color and the autofluorescence of neuromelanin, immunological staining of proteins inside of neuromelanin granules either with horseradish peroxidase- or fluorophore-conjugated antibodies are not applicable. For Western Blot analysis, very large amounts of post-mortem tissue would be necessary. Therefore, selected proteins are validated by targeted mass spectrometry, and in the present case, parallel reaction monitoring (PRM)-experiments were set up.
The specific isolation of NMGs and SN tissue is the most important step for the successful application of this protocol. Using the Field of View Analysis function in the vendor-provided software of the LMD, NMGs can be automatically selected in a color-dependent manner. Therefore, tissue areas containing NMGs (Figure 2A) have to be identified and a Field of View Analysis with adjusted color thresholds has to be performed, resulting in the labeling of NMGs (Figure 2B). After filtering of objects covering an area below 100 µm², only NMGs should remain labeled for isolation (Figure 2C). Precise isolation of the labeled NMGs is achieved after laser settings were adjusted (Figure 2D). After the isolation of NMGs (Figure 2E), SN tissue can be selected with 50-fold magnification (Figure 2F) and isolated (Figure 2G) for comparison of the proteomic profile. For SN tissue, isolated objects can be visualized using the Cap Check function (Figure 2H). For both sample types, NMG and SN, isolation of 500,000 µm2 of brain tissue was found to be sufficient for this protocol, enabling a minimum of three MS runs per sample.
A representative example of a 120 min DDA experiment is shown in Figure 3 (as the main column is washed in the last 15 min of the measurement, the chromatogram is cropped just before 105 min). The applied method should allow a sample elution over the complete gradient, creating sharp and concise peaks and the intensity of the Total Ion current (TIC) should be comparable across all samples.
Application of the presented protocol on one sample of 500,000 µm² of NMG and one sample of 1,000,000 µm² SN tissue with adjusted volumes for MS samples (5 µL for NMG and 2.5 µL for SN) to ensure identical peptide load, resulted in the identification of 1,898 protein groups (PGs) in the NMG sample and 1,565 PGs in the SN sample. Further comparison revealed 1,384 PGs to be identified in both samples, while 514 PGs were exclusively identified in NMG and 181 PGs in SN tissue (Figure 4). In total, 2,079 PGs were identified in this representative experiment. Comparison with a reference dataset from a former study22 showed that 87.6% of the PGs reported in that study could also be identified by the present revised and automated protocol, proving its applicability. Furthermore, the number of identified PGs could be improved by 1,143.
As minimal sample amounts do not allow the application of classic validation methods such as Western Blots, validation of proteins of interest can be achieved by targeted mass spectrometric approaches, e.g., PRM. Representative results for the peptide ESPEVLLTLDILK of the protein cytoplasmic dynein 1 heavy chain 1 are shown in Figure 5. The iBAQ value of this protein was found to be slightly higher in NMGs compared to SN in the DDA measurements, which could be verified by PRM-experiments based on the peak area on MS1- (Figure 5A,B,E) and MS2-level (Figure 5C,D,F).
Figure 1: Workflow for the proteomic characterization of neuromelanin granules (NMGs) and surrounding tissue (SN). NMG and SN samples were isolated from tissue slices via laser microdissection (LMD). Proteins were isolated and tryptic in-solution digestion was performed. The resulting peptides were analyzed via LC-MS/MS measurements in data-dependent acquisition (DDA) mode. Data analysis was performed using MaxQuant and Perseus software. Validation of selected proteins was carried out with parallel reaction monitoring (PRM) experiments. PRM-data was analyzed using Skyline software. Please click here to view a larger version of this figure.
Figure 2: Selection and LMD-based isolation of NMG and SN samples. At first, an area containing NMGs, visible without further staining at 400-fold magnification, is placed under the microscope (A). After performing a Field of View Analysis, NMGs and other dark areas are selected (B). Only NMGs remain selected after filtering (C) and are isolated after laser settings are adjusted (D). After all NMGs are isolated (E), SN tissue is selected with 50-fold magnification (F) and isolated (G). As objects isolated for SN samples are quite big, they can be observed in the sample collection cap using the Cap Check function (H). Please click here to view a larger version of this figure.
Figure 3: Total Ion Current (TIC) of a 120 min DDA measurement. The chromatogram shows the relative abundance of the ions corresponding to the eluting peptides over the retention time range from 0 to ~105 min. As the main column is washed between 105th and 120th min, the chromatogram is cropped at the 105th min. The intensity of the highest peak is 2.86 x 108. Numbers above peaks indicate the retention time and the most abundant ion of that specific peak (BP=base peak). Please click here to view a larger version of this figure.
Figure 4: Venn Diagram showing the correspondence of protein groups (PGs) identified in NMGs and SN tissue. In total, 1,898 PGs were identified in NMGs and 1,565 PGs in SN tissue, of which 1,384 PGs were identified in both tissue areas. 514 PGs were exclusively identified in NMG tissue, while 181 PGs were exclusively identified in SN tissue. The diagram was created using the online tool Venny25. Please click here to view a larger version of this figure.
Figure 5: Results of PRM-experiments for the peptide ESPEVLLTLDILK (cytoplasmic dynein 1 heavy chain 1, ++). Chromatograms on MS1- (A,B) and MS2-level (C,D), as well as peak areas on MS1- (E) and MS2-level (F), are shown for an exemplary sample of NMGs and SN tissue. Different colors are used to denote different precursors (on MS1-level) or product ions (on MS2-level). Chromatograms are displayed after Savitzky-Golay Smoothing was performed. Intensities and peak areas were comparable on MS1- (A,B,E) and MS2-level (C,D,F). Please click here to view a larger version of this figure.
Supplementary Table 1: Parameters of the mass spectrometry experiments. Please click here to download this Table.
Supplementary Table 2: Parameters of the MaxQuant analysis. Please click here to download this Table.
LMD is a widely applicable technique for the isolation of specific tissue areas, single cells, or subcellular structures. In the revised and automated protocol presented here, this technique is applied for the specific isolation of neuromelanin granules (NMGs) and NMG-surrounding tissue (SN). Until now, two different approaches for the isolation of NMGs out of human post-mortem brain tissue were published and widely used:
a) A discontinuous sucrose gradient consuming 1 g of substantia nigra tissue20. As human post-mortem substantia nigra tissue is rare and of high interest for several research questions, it is unfortunately quite challenging to set up a large cohort study if high amounts of tissue are required per patient. Therefore, this approach was further improved reducing the required tissue amount to 0.15 g for sufficient isolation of NMGs26. However, still, at least one-half of a complete substantia nigra pars compacta was required.
b) The excision of NMGs using LMD. In 2016, Plum et al established a new protocol based on the precise excision of NMGs via LMD. With this protocol, the required sample amount could be reduced to ten 10 µm tissue sections, resulting in an impressive reduction of the required tissue sample from 150 mg to 16.6 mg22.
The optimized and automated LMD-based protocol presented here requires even lower sample amounts as thinner (5 µm compared to 10 µm) and fewer tissue sections (maximum of 7 compared to 8) had to be used and requires less time for sample generation (4 h per sample compared to 1-2 days) through the use of automatized NMG detection. Thus, the required sample collection time was shortened massively and the number of identified PGs could be drastically enhanced by applying an optimized LC-MS method and state-of-the-art instrumentation. This protocol can easily be adapted to other research questions and tissues.
For the adaptation of the presented protocol concerning user-defined research questions, the following aspects are highlighted based on experience:
a) Isolation of comparable sample amounts: As the expected peptide yield of this protocol is rather low compared to, for instance, cell culture or tissue lysates, determination of peptide concentration may not be possible. Thus, it is crucial that equal amounts of tissue are isolated via LMD, which can be estimated based on the tissue area of the selected objects. In the current setup, tissue areas of 500,000 µm² are sufficient for the generation of peptides for at least three MS measurements.
b) Trypsin-digestion: The duration of digestion and the trypsin concentration should be comparable across samples.
c) Adaption of parameters for different tissues: Depending on the tissue to analyze, the collected tissue amount needs to be adjusted thereby making it necessary to adjust the amount of added trypsin as well. The trypsin to protein ratio should not be lower than 1:40.
d) Limitation of the LMD process: For the LMD-based isolation of objects of interest, there are limitations when it comes to the size of selected objects and the thickness of slices. Due to tissue loss during the laser-based cutting of the tissue, objects smaller than 100 µm² were considered too small for isolation.
e) Adaption of LC and MS parameters: Depending on the LC and MS systems used, the amount of isolated tissue has to be increased (e.g., when operating with a microflow system) and MS parameters have to be adapted (e.g., when working with an ion-trap-based detector system).
The authors have nothing to disclose.
This work was supported by de.NBI, a project of the German Federal Ministry of Education and Research (BMBF) (grant number FKZ 031 A 534A) and P.U.R.E. (Protein Research Unit Ruhr within Europe) and Center for Protein Diagnostics (ProDi) grants, both from the Ministry of Innovation, Science and Research of North-Rhine Westphalia, Germany.
1,4-dithiothreitol | AppliChem | A1101 | |
Acetonitrile | Merck | 1.00029.2500 | |
Ammonium bicarbonate | Sigma-Aldrich | A6141 | |
Formic acid | Sigma-Aldrich | 56302 | |
Iodoacetamide | AppliChem | A1666,0100 | |
Micro Tube 500 | Carl Zeiss | 415190-9221-000 | |
Orbitrap Fusion Lumos Tribrid mass spectrometer | Thermo Fisher Scientific | IQLAAEGAAPFADBMBHQ | |
PALM MicroBeam | Zeiss | 494800-0014-000 | |
PEN Membrane slide | Carl Zeiss | 415190-9041-000 | |
substantia nigra pars compacta tissue slices | Navarrabiomed Biobank (Pamplona, Spain) | ||
Trifluoroacetic acid | Merck | 91707 | |
Trypsin sequencing grade | Serva | 37283.01 | |
Ultimate 3000 RSLC nano LC system | Thermo Fisher Scientific | ULTIM3000RSLCNANO | |
Name of Software | Weblink/Company | Version | |
FreeStyle | Thermo Fisher Scientific | 1.6 | |
MaxQuant | https://www.maxquant.org/ | 1.6.17.0 | |
PALMRobo | Zeiss | 4.6 pro | |
Perseus | https://www.maxquant.org/perseus/ | 1.6.15.0 | |
Skyline | https://skyline.ms/project/home/software/Skyline/begin.view | 20.2.0.343 | |
XCalibur | Thermo Fisher Scientific | 4.3 |