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.

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
<ol>
	<li>Precool the cryostat chamber. 
	NOTE: Every tissue requires different cryostat temperatures, which can be found in the respective vendor protocol.</li>
	<li>Clean the stainless-steel knife with 70% ethanol and install it into the blade holder.</li>
	<li>Transfer the tissue from the -80 &#176;C freezer to the cryostat using an icebox and let it adjust to the cryostat chamber temperature for 15 min.</li>
	<li>Unambiguously label membrane slides using a pencil. 
	NOTE: PET/PEN membrane slides are required for the LMD-based sample collection. Handle the PET/PEN membrane slides with care as they are extremely fragile.</li>
	<li>Apply a drop of commercial frozen section medium on the tissue holder. Before it is completely frozen, place the tissue onto the frozen section medium and let it harden, so that the tissue is connected with the tissue holder.</li>
	<li>Install the tissue holder in the cryostat chamber and adjust its orientation before you start sectioning. Optimal holder orientation depends on the orientation of the tissue. 
	NOTE: It may be necessary to trim the tissue until the section plane needed for the slices is reached.</li>
	<li>Before the tissue area of interest is reached, adjust the cutting setting to the desired tissue thickness. 
	NOTE: 5 or 10 &#181;m is the suggested thickness for this protocol as 20 &#181;m thick sections were found to be incompatible with the LMD-based sample collection22.</li>
	<li>Cut two sections and discard them.</li>
	<li>Put down the Anti-roll Plate.</li>
	<li>Cut a section of the tissue, open the Anti-roll Plate carefully, take a membrane slide, and prevent tissue folding while placing the tissue section on the membrane slide. 
	NOTE: Storing the membrane slides at room temperature prior to adhesion enables accurate sample attachment. Several sections may be placed on the same membrane slide but tissue overlapping must be prevented.</li>
	<li>Store tissue sections placed on membrane slides in the cryostat until sectioning is completed.</li>
	<li>Store the cryosected tissue at -20 &#176;C until further processing or directly proceed with the procedure below. Store the sectioned tissue slides at -80 &#176;C until further use.</li>
</ol>
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.
<ol>
	<li>Switch on the MicroBeam system and open the associated software on the computer (see Table of Materials).</li>
	<li>Place the tissue membrane slide in the SlideHolder on the RoboStage with the tissue facing upwards. 
	NOTE: Depending on the LMD device, it may be necessary to place the membrane slide such that the tissue is facing down. In general, sample collection is performed in a temperature-controlled environment to ensure optimal and reproducible conditions.</li>
	<li>Set the microscope to the desired magnification (50-fold is used here) for the overview scans.</li>
	<li>Use the Scan function, which can be found in the Navigator window of the software interface, to acquire an overview scan of the tissue section. Search for the top-left corner and the bottom-right corner of the area of interest and select them in the software interface. Then, select Scan all ROIs to perform the scans. 
	NOTE: Overview scans are not mandatory, but they enable better orientation in the slide and can be saved for later usage.</li>
	<li>Adjust the magnification of the microscope for the appropriate tissue, which is 400-fold in the present case of neuromelanin granules.</li>
	<li>Search for an area with neuromelanin granules. Select Field of View Analysis in the software interface, select Invert Result, and set the threshold for the RGB channels so that only neuromelanin granules are highlighted in red in the preview window. Click on OK to use the adjusted settings for the field of view. 
	NOTE: It may occur that smaller objects having a dark color also get selected. To account for that, discard all objects covering an area smaller than 100 &#181;m2 before isolating neuromelanin granules. To do this, open the Element List by clicking on the icon in the toolbar, select the slide under consideration and order elements by area. Select those with areas smaller than 100 &#181;m2 and delete them.</li>
	<li>Adjust laser settings using an area of the slide that is covered by the membrane only. 
	NOTE: It is suggested to use the Cut Laser Adjustment Wizard and follow the instructions of the software. Required laser settings may differ between different slides. For 5 &#181;m sections with 400-fold magnification, typical settings are 32 energy and 51 focus for cutting, and 28 energy and -1 focus for laser pulse catapulting (LPC).</li>
	<li>Adjust speed settings for positioning and cutting to ensure proper isolation. 
	NOTE: 30% speed was found to be optimal for NMG isolation.</li>
	<li>Fill the sample collection tube cap with 50 &#181;L ultrapure water and insert the cap into the collector of the RoboMover. 
	NOTE: The tube collector used for present experiments can carry one sample collection tube at a time.</li>
	<li>Position the RoboMover above the RoboStage II using the software interface to start sample collection. 
	NOTE: To do this, open the RoboMover window, which displays the collector. Click on the sample collection tube cap displayed in the RoboMover window to move the cap to the working area. Adjust the optimal moving and working height in the RoboMover window. Otherwise, the water in the cap may drop onto the slide or the catapulted objects will not reach the cap.</li>
	<li>Start the laser. Control energy and focus settings during the laser process and adjust the settings if necessary. Ensure proper isolation and catapulting of the isolated objects into the sample collection tube cap for at least the first ten objects. 
	NOTE: Proper isolation and catapulting have to be checked visually. Both should result in a tissue-free area of the size of the pre-selected object in the tissue slice (see Figure 2C,D). Adjust the laser settings if the object stays attached to the tissue slice after cutting and catapulting. For catapulting, the CenterRoboLPC option is found to be well suited for NMG isolation. The catapulting settings can be adjusted for each selected object in the Element List.</li>
	<li>When sampling is completed, navigate the RoboMover to its starting position. Remove the sample collection tube. 
	NOTE: When the number of collected objects is rather low and objects are big enough, sample collection can be ensured by clicking on Cap Check, which will place the sample collection tube cap under the microscope so that the number of objects inside of the water in the cap can be counted (see Figure 2H).</li>
	<li>Spin down the sample using a centrifuge. Short spins of 5 s with increasing centrifugal force due to acceleration of the centrifuge were found to be sufficient. At this point, store samples at -80 &#176;C, as all samples should be further processed together. 
	NOTE: For the comparison of the proteomic profile, the tissue surrounding the NMGs was also isolated after their excision. The isolation of the surrounding tissue was performed at 50-fold magnification.</li>
	<li>Dry the samples in a vacuum concentrator. 1.5 h were found to be sufficient for 50 &#181;L of water.</li>
	<li>Solubilize and lyse the tissue in 40 &#181;L formic acid for 20 min (room temperature).</li>
	<li>Enhance tissue lysis by sonication at 45 kHz (kilohertz) for 5 min in a sonication bath. Fill the sonication bath with ice to prevent tubes from melting. Store the samples at -80 &#176;C until further processing.</li>
</ol>
3. Tryptic digestion
<ol>
	<li>Defreeze samples on ice.</li>
	<li>Completely dry the samples in a vacuum concentrator.</li>
	<li>Fill up the sample with 50 &#181;L of a suitable digestion buffer, e.g., 50 mM ammonium bicarbonate.</li>
	<li>After the addition of 1.25 &#181;L of 200 mM 1,4-dithiothreitol, incubate the samples for 30 min at 60 &#176;C and 300 rpm using a thermomixer and cool them down to room temperature (RT) afterwards.</li>
	<li>Then, incubate samples at RT for 30 min in the dark after the addition of 1.36 &#181;L 0.55 M iodoacetamide.</li>
	<li>Add a suitable amount of trypsin to the samples and incubate the samples overnight (~16 h) at 37 &#176;C. 
	NOTE: For 1,000,000 &#181;m2, 0.1 &#181;g of trypsin was found to be sufficient.</li>
	<li>Add 2.6 &#181;L of 10% trifluoroacetic acid (TFA) to the samples to stop the digestion (end concentration of 0.5% TFA).</li>
	<li>Completely dry the samples using a vacuum concentrator. Then, fill samples up to a defined final volume with 0.1% TFA. NMG samples were filled up to 20 &#181;L of which 5 &#181;L were used for one mass spectrometric (MS) experiment.</li>
	<li>Store the samples at -80 &#176;C until further usage. Determine peptide concentration by amino acid analysis or another suitable quantification method (e.g., Direct Detect). 
	&#8203;NOTE: Low sample amounts may not be quantifiable using the mentioned techniques. To ensure identical sample loading, each sample should contain the same amount of isolated tissue and every sample should be treated equally.</li>
</ol>
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.
<ol>
	<li>Using the software Xcalibur, adjust the HPLC settings as follows.
	<ol>
		<li>Trap column: Set temperature to 60 &#176;C, flow rate to 30 &#181;L/min, running buffer to 0.1% trifluoroacetic acid.</li>
		<li>Analytical C18 reversed-phase column: Set temperature to 60 &#176;C, flow rate to 30 &#181;L/min, running buffer A to 0.1% trifluoroacetic acid, running buffer B to 84% acetonitrile, and gradient to 5%-30% running buffer B over 98 min. 
		NOTE: Adaption of the gradient may be inevitable and is strongly recommended when using different tissues or cells. Total gradient time may vary due to sample loading at the beginning of the gradient and sample washing at the end of the gradient. The total gradient in this protocol consists of 7 min sample loading and additional column wash for 15 min resulting in a total gradient time of 120 min.</li>
	</ol>
	</li>
	<li>Create a data-dependent acquisition (DDA) method using the XCalibur Instrument Setup, which can be found in the HPLC software roadmap menu.</li>
	<li>In the Global Parameters tab, define the infusion mode Liquid Chromatography, the Expected LC Peak Width (30 s), and the Default charge state (2).</li>
	<li>Proceed to the Scan Parameters tab and add the following scans and filters in the order mentioned: MS OT, MIPS, Intensity, Charge State, Dynamic exclusion, and ddMS2 OT HCD. 
	NOTE: The detailed parameter settings for each scan and filter can be found in Supplementary Table 1. Optimal MS and DDA settings might vary for the specific mass spectrometer used as well as the sample type and should be, therefore, adapted.</li>
	<li>Prepare samples by dissolving 200-400 ng of sample peptides in a defined volume of 0.1% TFA in inert mass spectrometric glass vial inlets. If concentration determination is not applicable due to low sample amount, verify identical sample loading by comparing the Total Ion Current (TIC). 
	NOTE: To do this, open the resulting file of mass spectrometric measurement in a suitable software, e.g., FreeStyle, and check the chromatogram. Intensities should be comparable for all samples. A representative TIC is shown in Figure 3.</li>
	<li>Analyze the raw data obtained using a proteomic suitable software, e.g., MaxQuant23, Progenesis QI for Proteomics, or Proteome Discoverer, and perform a statistical data analysis based on the research question.</li>
</ol>
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.
<ol>
	<li>Load raw files into the MaxQuant software in the raw data header by clicking Load.</li>
	<li>Assign sample names by clicking on Set Experiment.</li>
	<li>Define group-specific parameters. First, add modifications. Due to sample processing, choose Deamidation (NQ), Oxidation (M), and Carbamidomethylation (N-term) as variable modifications, and add Carbamidomethylation (C) as fixed modification.</li>
	<li>Choose Trypsin as digestion enzyme in the Digestion tab.</li>
	<li>Add the label free quantification option LFQ in the Label Free Quantification tab. If more than 10 files are to be processed, choose the Fast LFQ option to shorten the processing time. Add iBAQ option as a measure for protein quantification24.</li>
	<li>Ensure that all other group-specific parameters remain in factory settings.</li>
	<li>Proceed to the Global Parameters tab and add the FASTA file derived from uniprot.org in the Sequences tab. Modify the identifier rule accordingly and add the taxonomy ID, in this case, 9606 for homo sapiens.</li>
	<li>For protein quantification choose Unique and Razor peptides.</li>
	<li>Ensure that all other global parameters remain in factory settings.</li>
	<li>Click on Start and retrieve the proteingroups.txt output after MaxQuant analysis for further analysis in Perseus.</li>
</ol>
6. Statistical analysis using Perseus
<ol>
	<li>Load the proteingroups.txt file in Perseus, add the iBAQ values as main columns, and sort all other columns according to their type.</li>
	<li>Filter out decoys and contaminants by filtering rows based on the categorical column.</li>
	<li>Filter results based on valid values. In the present case, with only two samples included in the analysis, a minimum number of one valid value was chosen.</li>
	<li>Export the Perseus output in .txt format for further processing, for example, in Excel, and evaluate the results regarding the research question.</li>
</ol>
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.
<ol>
	<li>Select proteins for validation. Choose peptides of these proteins already detected in DDA experiments. Peptides should contain no missed cleavages or modifications to ensure a reliable quantification. 
	NOTE: There can be several reasons for the validation of one specific protein, for example, differential abundances in the investigated conditions. For the representative results, cytoplasmic dynein 1 heavy chain 1 has been selected, which was found to be equivalently abundant in NMG and SN samples and could therefore be used as a reference to ensure equal sample loading.</li>
	<li>Use the selected peptides to set up the first version of a PRM-method using the HPLC software. Keep all chromatography and global parameters settings from the DDA method.</li>
	<li>Add MS OT and tMS2 OT HCD as scan types. Ensure that the settings for MS OT are the same as for the DDA method. Detailed settings for the PRM method can be found in Supplementary Table 1.</li>
	<li>For tMS2 OT HCD, add selected peptides as an inclusion list. Therefore, add the amino acid sequence and the m/z value observed in the DDA measurements. For the first PRM experiment, do not add retention time windows or set t start to 0 and t stop to 120 (for a 120 min gradient).</li>
	<li>Evaluate the PRM method after the measurement using suitable software, for example, Skyline, and obtain the retention time of the peptides added to the inclusion list. For included peptides, check that comparable peaks are observable for at least three precursor ions in MS1 scans and five fragment ions in MS2 scans with low mass error (&#177;5 ppm).</li>
	<li>Refine the PRM method, for example, by increasing the resolution for the tMS2 OT HCD scan and adding retention time windows to the inclusion list. 
	NOTE: Retention time windows of 3 min were found to be well-suited in present experiments (observed retention time in first PRM experiment &#177; 1.5 min).</li>
	<li>With the refined PRM-method, perform quantification of peptides and proteins of interest based on the peak area both on MS1 and MS2 levels with suitable software.</li>
</ol>

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Venny: An interactive tool for comparing lists with Venn's diagrams Available from: <a target="_blank" href="https://bioinfogp.cnb.csic.es/tools/venny/index.html">https://bioinfogp.cnb.csic.es/tools/venny/index.html</a> (2007)</li><li>Plum, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Combined+enrichment+of+neuromelanin+granules+and+synaptosomes+from+human+substantia+nigra+pars+compacta+tissue+for+proteomic+analysis.">Combined enrichment of neuromelanin granules and synaptosomes from human substantia nigra pars compacta tissue for proteomic analysis.</a> Journal of Proteomics. 94, 202-206 (2013).</li></ol>

The authors declare no conflicts of interest.

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 substa...

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&#39;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&#39;s disease is not clearly understood. Still, NMGs seem to be involved in the pathogenesis of Parkinson&#39;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.

<table><tbody><tr><td>1,4-dithiothreitol</td><td>AppliChem</td><td>A1101</td><td></td></tr><tr><td>Acetonitrile</td><td>Merck</td><td>1.00029.2500</td><td></td></tr><tr><td>Ammonium bicarbonate</td><td>Sigma-Aldrich</td><td>A6141</td><td></td></tr><tr><td>Formic acid</td><td>Sigma-Aldrich</td><td>56302</td><td></td></tr><tr><td>Iodoacetamide</td><td>AppliChem</td><td>A1666,0100</td><td></td></tr><tr><td>Micro Tube 500</td><td>Carl Zeiss</td><td>415190-9221-000</td><td></td></tr><tr><td>Orbitrap Fusion Lumos Tribrid mass spectrometer</td><td>Thermo Fisher Scientific</td><td>IQLAAEGAAPFADBMBHQ</td><td></td></tr><tr><td>PALM MicroBeam</td><td>Zeiss</td><td>494800-0014-000</td><td></td></tr><tr><td>PEN Membrane slide</td><td>Carl Zeiss</td><td>415190-9041-000</td><td></td></tr><tr><td>&lt;em&gt;substantia nigra pars compacta&lt;/em&gt; tissue slices</td><td>Navarrabiomed Biobank (Pamplona, Spain)</td><td></td><td></td></tr><tr><td>Trifluoroacetic acid</td><td>Merck</td><td>91707</td><td></td></tr><tr><td>Trypsin sequencing grade</td><td>Serva</td><td>37283.01</td><td></td></tr><tr><td>Ultimate 3000 RSLC nano LC system</td><td>Thermo Fisher Scientific</td><td>ULTIM3000RSLCNANO</td><td></td></tr><tr><td>&lt;strong&gt;Name of Software&lt;/strong&gt;</td><td>&lt;strong&gt;Weblink/Company&lt;/strong&gt;</td><td>&lt;strong&gt;Version&lt;/strong&gt;</td><td></td></tr><tr><td>FreeStyle</td><td>Thermo Fisher Scientific</td><td>1.6</td><td></td></tr><tr><td>MaxQuant</td><td>https://www.maxquant.org/</td><td>1.6.17.0</td><td></td></tr><tr><td>PALMRobo</td><td>Zeiss</td><td>4.6 pro</td><td></td></tr><tr><td>Perseus</td><td>https://www.maxquant.org/perseus/</td><td>1.6.15.0</td><td></td></tr><tr><td>Skyline</td><td>https://skyline.ms/project/home/software/Skyline/begin.view</td><td>20.2.0.343</td><td></td></tr><tr><td>XCalibur</td><td>Thermo Fisher Scientific</td><td>4.3</td><td></td></tr></tbody></table>

laser microdissection-based protocol for the lc-ms/ms analysis of the proteomic profile of neuromelanin granules

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&#39;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.

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 (<strong class="xfi...

Watch this Scientific Journal Video about Laser Microdissection-Based Protocol for the LC-MS/MS Analysis of the Proteomic Profile of Neuromelanin Granules at JoVE.com

Laser Microdissection-Based Protocol for the LC-MS/MS Analysis of the Proteomic Profile of Neuromelanin Granules

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. ...

laser-microdissection-based-protocol-for-lc-msms-analysis-proteomic

Research

JoVE Journal

Neuroscience

2.2K Views.  Ruhr-University Bochum. Onze combinatie van lasermicrodissectie en massaspectrometrie maakt het mogelijk om ruimtelijk opgeloste veranderingen op proteomisch niveau in elk soort weefsel te onderzoeken. In ons geval neuromelaninekorrels. Ons protocol maakt de proteomische analyse mogelijk op basis van beperkt monstermateriaal.Wat meestal een grote uitdaging is bij het werken met postmortaal hersenweefsel. Omdat afzonderlijke cellen kunnen worden geïsoleerd om gezonde en ziekteomstandigheden op proteomisch niv...

Video: Laser Microdissection-Based Protocol for the LC-MS/MS Analysis of the Proteomic Profile of Neuromelanin Granules

Laser Capture Microdissection of Drosophila Peripheral Neurons

The dendritic arborization (da) neurons of the Drosophila peripheral nervous system (PNS) provide an excellent model system in which to investigate the molecular mechanisms underlying class-specific dendrite morphogenesis1,2. To facilitate molecular analyses of class-specific da neuron development, it is vital to obtain these cells in a pure population. Although a range of different cell, and tissue-specific RNA isolation techniques exist for Drosophila cells, including magnetic bead based cell purification3,4, Fluorescent Activated Cell Sorting (FACS)5-8, and RNA binding protein based strategies9, none of these methods can be readily utilized for isolating single or multiple class-specific Drosophila da neurons with a high degree of spatial precision. Laser Capture Microdissection (LCM) has emerged as an extremely powerful tool that can be used to isolate specific cell types from tissue sections with a high degree of spatial resolution and accuracy. RNA obtained from isolated cells can then be used for analyses including qRT-PCR and microarray expression profiling within a given cell type10-16. To date, LCM has not been widely applied in the analysis of Drosophila tissues and cells17,18, including da neurons at the third instar larval stage of development. 
Here we present our optimized protocol for isolation of Drosophila da neurons using the infrared (IR) class of LCM. This method allows for the capture of single, class-specific or multiple da neurons with high specificity and spatial resolution. Age-matched third instar larvae expressing a UAS-mCD8::GFP19 transgene under the control of either the class IV da neuron specific ppk-GAL420 driver or the pan-da neuron specific 21-7-GAL421 driver were used for these experiments. RNA obtained from the isolated da neurons is of very high quality and can be directly used for downstream applications, including qRT-PCR or microarray analyses. Furthermore, this LCM protocol can be readily adapted to capture other Drosophila cell types a various stages of development dependent upon the cell type specific, GAL4-driven expression pattern of GFP.

Laser Capture Microdissection of Drosophila Peripheral Neurons

In this video-article we present a method for isolating single or multiple Drosophila da neurons from third instar larvae using the infrared capture (IR) class of Laser Capture Microdissection (LCM). RNA obtained from the isolated neurons can be readily used for downstream applications including qRT-PCR or microarray analyses.

The dendritic arborization (da) neurons of the Drosophila peripheral nervous system (PNS) provide an excellent model system in which to investigate the ...

MALDI Imaging Mass Spectrometry of Neuropeptides in Parkinson's Disease

MALDI imaging mass spectrometry (IMS) is a powerful approach that facilitates the spatial analysis of molecular species in biological tissue samples2 (Fig.1). A 12 &mu;m thin tissue section is covered with a MALDI matrix, which facilitates desorption and ionization of intact peptides and proteins that can be detected with a mass analyzer, typically using a MALDI TOF/TOF mass spectrometer. Generally hundreds of peaks can be assessed in a single rat brain tissue section. In contrast to commonly used imaging techniques, this approach does not require prior knowledge of the molecules of interest and allows for unsupervised and comprehensive analysis of multiple molecular species while maintaining high molecular specificity and sensitivity2. Here we describe a MALDI IMS based approach for elucidating region-specific distribution profiles of neuropeptides in the rat brain of an animal model Parkinson's disease (PD). 
PD is a common neurodegenerative disease with a prevalence of 1% for people over 65 of age3,4. The most common symptomatic treatment is based on dopamine replacement using L-DOPA5. However this is accompanied by severe side effects including involuntary abnormal movements, termed L-DOPA-induced dyskinesias (LID)1,3,6. One of the most prominent molecular change in LID is an upregulation of the opioid precursor prodynorphin mRNA7. The dynorphin peptides modulate neurotransmission in brain areas that are essentially involved in movement control7,8. However, to date the exact opioid peptides that originate from processing of the neuropeptide precursor have not been characterized. Therefore, we utilized MALDI IMS in an animal model of experimental Parkinson's disease and L-DOPA induced dyskinesia. 
MALDI imaging mass spectrometry proved to be particularly advantageous with respect to neuropeptide characterization, since commonly used antibody based approaches targets known peptide sequences and previously observed post-translational modifications. By contrast MALDI IMS can unravel novel peptide processing products and thus reveal new molecular mechanisms of neuropeptide modulation of neuronal transmission. While the absolute amount of neuropeptides cannot be determined by MALDI IMS, the relative abundance of peptide ions can be delineated from the mass spectra, giving insights about changing levels in health and disease. In the examples presented here, the peak intensities of dynorphin B, alpha-neoendorphin and substance P were found to be significantly increased in the dorsolateral, but not the dorsomedial, striatum of animals with severe dyskinesia involving facial, trunk and orolingual muscles (Fig. 5). Furthermore, MALDI IMS revealed a correlation between dyskinesia severity and levels of des-tyrosine alpha-neoendorphin, representing a previously unknown mechanism of functional inactivation of dynorphins in the striatum as the removal of N-terminal tyrosine reduces the dynorphin's opioid-receptor binding capacity9. This is the first study on neuropeptide characterization in LID using MALDI IMS and the results highlight the potential of the technique for application in all fields of biomedical research.

Dopamine replacement pharmacotherapy using L-DOPA is the most commonly used symptomatic treatment of Parkinson&#x2019;s disease, but is accompanied by side effects including involuntary abnormal movements, termed dyskinesia 1. Here, a protocol for MALDI imaging mass spectrometry is presented that detects changes in rat brain neuropeptide levels related to dyskinesia.

MALDI imaging mass spectrometry (IMS) is a powerful approach that facilitates the spatial analysis of molecular species in biological tissue samples2 ...

Medicine

Laser Capture Microdissection of Enriched Populations of Neurons or Single Neurons for Gene Expression Analysis After Traumatic Brain Injury

Long-term cognitive disability after TBI is associated with injury-induced neurodegeneration in the hippocampus-a region in the medial temporal lobe that is critical for learning, memory and executive function.1,2 Hence our studies focus on gene expression analysis of specific neuronal populations in distinct subregions of the hippocampus. The technique of laser capture microdissection (LCM), introduced in 1996 by Emmert-Buck, et al.,3 has allowed for significant advances in gene expression analysis of single cells and enriched populations of cells from heterogeneous tissues such as the mammalian brain that contains thousands of functional cell types.4 We use LCM and a well established rat model of traumatic brain injury (TBI) to investigate the molecular mechanisms that underlie the pathogenesis of TBI. Following fluid-percussion TBI, brains are removed at pre-determined times post-injury, immediately frozen on dry ice, and prepared for sectioning in a cryostat. The rat brains can be embedded in OCT and sectioned immediately, or stored several months at -80 &deg;C before sectioning for laser capture microdissection. Additionally, we use LCM to study the effects of TBI on circadian rhythms. For this, we capture neurons from the suprachiasmatic nuclei that contain the master clock of the mammalian brain. Here, we demonstrate the use of LCM to obtain single identified neurons (injured and degenerating, Fluoro-Jade-positive, or uninjured, Fluoro-Jade-negative) and enriched populations of hippocampal neurons for subsequent gene expression analysis by real time PCR and/or whole-genome microarrays. These LCM-enabled studies have revealed that the selective vulnerability of anatomically distinct regions of the rat hippocampus are reflected in the different gene expression profiles of different populations of neurons obtained by LCM from these distinct regions. The results from our single-cell studies, where we compare the transcriptional profiles of dying and adjacent surviving hippocampal neurons, suggest the existence of a cell survival rheostat that regulates cell death and survival after TBI.

We describe how to use laser capture microdissection (LCM) to obtain enriched populations of hippocampal neurons or single neurons from frozen sections of the injured rat brain for subsequent gene expression analysis using quantitative real time PCR and/or whole-genome microarrays.

Long-term cognitive disability after TBI is associated with injury-induced neurodegeneration in the hippocampus-a region in the medial temporal lobe that ...

Laser Capture Microdissection of Neurons from Differentiated Human Neuroprogenitor Cells in Culture

Neuroprogenitor cells (NPCs) isolated from the human fetal brain were expanded under proliferative conditions in the presence of epidermal growth factor (EGF) and fibroblast growth factor (FGF) to provide an abundant supply of cells. NPCs were differentiated in the presence of a new combination of nerve growth factor (NGF), brain-derived neurotrophic factor (BDNF), dibutyryl cAMP (DBC) and retinoic acid on dishes coated with poly-L-lysine and mouse laminin to obtain neuron-rich cultures. NPCs were also differentiated in the absence of neurotrophins, DBC and retinoic acid and in the presence of ciliary neurotrophic factor (CNTF) to yield astrocyte-rich cultures. Differentiated NPCs were characterized by immunofluorescence staining for a panel of neuronal markers including NeuN, synapsin, acetylcholinesterase, synaptophysin and GAP43. Glial fibrillary acidic protein (GFAP) and STAT3, astrocyte markers, were detected in 10-15% of differentiated NPCs. To facilitate cell-type specific molecular characterization, laser capture microdissection was performed to isolate neurons cultured on polyethylene naphthalate (PEN) membrane slides. The methods described in this study provide valuable tools to advance our understanding of the molecular mechanism of neurodegeneration.

Human neuroprogenitor cells (NPCs) were expanded under proliferating conditions. NPCs were differentiated into neuron-rich cultures in the presence of a combination of neurotrophins. Neuronal markers were detected by immunofluorescence staining. To isolate a pure population of neurons, NPCs were differentiated on PEN membrane slides and laser capture microdissection was performed.

Neuroprogenitor cells (NPCs) isolated from the human fetal brain were expanded under proliferative conditions in the presence of epidermal growth factor ...

Industrialized, Artificial Intelligence-guided Laser Microdissection for Microscaled Proteomic Analysis of the Tumor Microenvironment

The tumor microenvironment (TME) represents a complex ecosystem comprised of dozens of distinct cell types, including tumor, stroma, and immune cell populations. To characterize proteome-level variation and tumor heterogeneity at scale, high-throughput methods are needed to selectively isolate discrete cellular populations in solid tumor malignancies. This protocol describes a high-throughput workflow, enabled by artificial intelligence (AI), that segments images of hematoxylin and eosin (H&#38;E)-stained, thin tissue sections into pathology-confirmed regions of interest for selective harvest of histology-resolved cell populations using laser microdissection (LMD). This strategy includes a novel algorithm enabling the transfer of regions denoting cell populations of interest, annotated using digital image software, directly to laser microscopes, thus enabling more facile collections. Successful implementation of this workflow was performed, demonstrating the utility of this harmonized method to selectively harvest tumor cell populations from the TME for quantitative, multiplexed proteomic analysis by high-resolution mass spectrometry. This strategy fully integrates with routine histopathology review, leveraging digital image analysis to support enrichment of cellular populations of interest and is fully generalizable, enabling harmonized harvests of cell populations from the TME for multiomic analyses.

This protocol describes a high-throughput workflow for artificial intelligence-driven segmentation of pathology-confirmed regions of interest from stained, thin tissue section images for enrichment of histology-resolved cell populations using laser microdissection. This strategy includes a novel algorithm enabling the transfer of demarcations denoting cell populations of interest directly to laser microscopes.

The tumor microenvironment (TME) represents a complex ecosystem comprised of dozens of distinct cell types, including tumor, stroma, and immune cell ...

Cancer Research

Microsampling in Targeted Mass Spectrometry-Based Protein Analysis of Low-Abundance Proteins

This paper presents a protocol with detailed descriptions for efficient sample cleanup of low-abundance proteins from dried samples. This is performed using bead-based proteolysis prior to proteotypic peptide affinity-capture and liquid chromatography tandem mass spectrometry (LC-MS/MS) determination. The procedure can be applied to both conventional dried samples using paper cards (e.g., dried blood spots [DBSs] and dried serum spots [DSSs]), as well as samples collected with newer sampling methods such as volumetric absorptive microsampling (VAMS). In addition to describing this procedure, the preparation of both trypsin beads and antibody-coated beads is presented in a step-by-step manner in this work. The advantages of the presented procedure are time-efficient proteolysis using beads and selective robust cleanup using peptide affinity-capture. The current procedure describes the determination of the low-abundance small-cell lung cancer (SCLC) biomarker, progastrin-releasing peptide (ProGRP), in dried serum (both DSSs and VAMS). Detailed procedures for bead preparation make it easier to implement the workflow in new applications or other laboratories. It is demonstrated that the results may be dependent on the sampling material; for the present project, higher signal intensities were seen for samples collected using VAMS compared to DSSs.

A protocol is presented for the determination of low-abundance biomarkers from dried serum samples exemplified with the biomarker progastrin-releasing peptide (ProGRP). Antibody-coated magnetic beads are used for the selective cleanup and enrichment of a proteotypic ProGRP peptide. The captured peptide is subsequently analyzed by liquid chromatography-tandem mass spectrometry.

This paper presents a protocol with detailed descriptions for efficient sample cleanup of low-abundance proteins from dried samples. This is performed ...

Chemistry

A Streamlined Approach for Mass Spectrometry-Based Proteomics Using Selected Tissue Regions

Mass spectrometry (MS)-based proteomics enables comprehensive proteome analysis across a wide range of biological samples, including cells, tissues, and body fluids. Formalin-fixed, paraffin-embedded (FFPE) tissue sections, commonly used for long-term archiving, have emerged as valuable resources for proteomic studies. Beyond their storage benefits, researchers can isolate regions of interest (ROIs) from normal tissue regions through collaborative efforts with pathologists. Despite this potential, a streamlined approach for proteomic experiments encompassing ROI isolation, proteomic sample preparation, and MS analysis remains lacking. In this protocol, an integrated workflow that combines macrodissection of ROIs, suspension trapping-based sample preparation, and high-throughput MS analysis is presented. Through this approach, the ROIs of patients' FFPE tissues, consisting of benign serous cystic neoplasms (SCN) and precancerous intraductal papillary mucinous neoplasms (IPMN) diagnosed by pathologists, were macrodissected, collected, and analyzed, resulting in high proteome coverage. Furthermore, molecular differences between the two distinct pancreatic cystic neoplasms were successfully identified, thus demonstrating the applicability of this approach for advancing proteomic research with FFPE tissues.

Here, we establish a mass spectrometry-based proteomic method using isolated regions of interest in formalin-fixed, paraffin-embedded tissue sections. This protocol is used to analyze proteome from specific tissue areas in archived formalin-fixed, paraffin-embedded tissue sections.

Mass spectrometry (MS)-based proteomics enables comprehensive proteome analysis across a wide range of biological samples, including cells, tissues, and ...

Biochemistry

Laser Capture Microdissection of Glioma Subregions for Spatial and Molecular Characterization of Intratumoral Heterogeneity, Oncostreams, and Invasion

Gliomas are primary brain tumors characterized by their invasiveness and heterogeneity. Specific histological patterns such as pseudopalisades, microvascular proliferation, mesenchymal transformation and necrosis characterize the histological heterogeneity of high-grade gliomas. Our laboratory has demonstrated that the presence of high densities of mesenchymal cells, named oncostreams, correlate with tumor malignancy. We have developed a unique approach to understand the mechanisms that underlie glioma&#39;s growth and invasion. Here, we describe a comprehensive protocol that utilizes laser capture microdissection (LMD) and RNA sequencing to analyze differential mRNA expression of intra-tumoral heterogeneous multicellular structures (i.e., mesenchymal areas or areas of tumor invasion). This method maintains good tissue histology and RNA integrity. Perfusion, freezing, embedding, sectioning, and staining were optimized to preserve morphology and obtain high-quality laser microdissection samples. The results indicate that perfusion of glioma bearing mice using 30% sucrose provides good morphology and RNA quality. In addition, staining tumor sections with 4% Cresyl violet and 0.5% eosin results in good nuclear and cellular staining, while preserving RNA integrity. The method described is sensitive and highly reproducible and it can be utilized to study tumor morphology in various tumor models. In summary, we describe a complete method to perform LMD that preserves morphology and RNA quality for sequencing to study the molecular features of heterogeneous multicellular structures within solid tumors.

Laser microdissection (LMD) is a sensitive and highly reproducible technique that can be used to uncover pathways that mediate glioma heterogeneity and invasion. Here, we describe an optimized protocol to isolate discrete areas from glioma tissue using laser LMD followed by transcriptomic analysis.

Gliomas are primary brain tumors characterized by their invasiveness and heterogeneity. Specific histological patterns such as pseudopalisades, ...

Characterization of Neuronal Lysosome Interactome with Proximity Labeling Proteomics

Lysosomes frequently communicate with a variety of biomolecules to achieve the degradation and other diverse cellular functions. Lysosomes are critical to human brain function, as neurons are postmitotic and rely heavily on the autophagy-lysosome pathway to maintain cellular homeostasis. Despite advancements in the understanding of various lysosomal functions, capturing the highly dynamic communications between lysosomes and other cellular components is technically challenging, particularly in a high-throughput fashion. Here, a detailed protocol is provided for the recently published endogenous (knock-in) lysosome proximity labeling proteomic method in human induced pluripotent stem cell (hiPSC)-derived neurons. 
Both lysosomal membrane proteins and proteins surrounding lysosomes within a 10-20 nm radius can be confidently identified and accurately quantified in live human neurons. Each step of the protocol is described in detail, i.e., hiPSC-neuron culture, proximity labeling, neuron harvest, fluorescence microscopy, biotinylated protein enrichment, protein digestion, LC-MS analysis, and data analysis. In summary, this unique endogenous lysosomal proximity labeling proteomics method provides a high-throughput and robust analytical tool to study the highly dynamic lysosomal activities in live human neurons.

A neuronal lysosome proximity labeling proteomics protocol is described here to characterize the dynamic lysosomal microenvironment in human induced pluripotent stem cell-derived neurons. Lysosomal membrane proteins and proteins that interact with lysosomes (stably or transiently) can be accurately quantified in this method with excellent intracellular spatial resolution in live human neurons.

Lysosomes frequently communicate with a variety of biomolecules to achieve the degradation and other diverse cellular functions. Lysosomes are critical to ...

Fluorescence-Guided Matrix-assisted Laser Desorption/Ionization with Laser-Induced Postionization Mass Spectrometry of Individual Rat Neural Cells

Single-cell measurements are critical to understanding the rich spatiochemical heterogeneity of the brain. Matrix-assisted laser/desorption ionization (MALDI) mass spectrometry (MS) is capable of label-free, high-throughput characterization of endogenous molecules in individual cells. The recent advances in the development of MALDI mass spectrometers with laser-induced post-ionization (MALDI-2) provide greatly enhanced sensitivity of detection for a variety of lipids and other small molecules. However, MS imaging of large samples with MALDI-2 at cellular resolution is prohibitively slow for most applications. In this protocol, primary cells are isolated and dispersed onto conductive slides. Relative cell locations are determined by whole-slide fluorescence microscopy, followed by accurate coregistration of the microscopy coordinates to the stage coordinates of the MALDI-2 mass spectrometer. Targeted MS analysis of only cell locations provides high-throughput, single-cell measurements with high analyte coverage and reduced data size as compared to MS imaging of the entire sample. We describe the critical steps necessary for single-cell preparation, whole-slide fluorescence imaging, matrix application, and MALDI-2 mass spectrometry.

This protocol outlines the use of microMS for fluorescence-guided, single-cell MALDI-2 mass spectrometry, enabling enhanced molecular profiling of primary rat neuronal cells.

Single-cell measurements are critical to understanding the rich spatiochemical heterogeneity of the brain. Matrix-assisted laser/desorption ionization ...

Laser Microdissection-Based Protocol for the LC-MS/MS Analysis of the Proteomic Profile of Neuromelanin Granules

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