Sign In

A subscription to JoVE is required to view this content. Sign in or start your free trial.

In This Article

  • Summary
  • Abstract
  • Introduction
  • Protocol
  • Results
  • Discussion
  • Disclosures
  • Acknowledgements
  • Materials
  • References
  • Reprints and Permissions

Summary

Mass spectrometric characterization of neuropeptides provides sequence, quantitation, and localization information. This optimized workflow is not only useful for neuropeptide studies, but also other endogenous peptides. The protocols provided here describe sample preparation, MS acquisition, MS analysis, and database generation of neuropeptides using LC-ESI-MS, MALDI-MS spotting, and MALDI-MS imaging.

Abstract

Neuropeptides are signaling molecules that regulate almost all physiological and behavioral processes, such as development, reproduction, food intake, and response to external stressors. Yet, the biochemical mechanisms and full complement of neuropeptides and their functional roles remain poorly understood. Characterization of these endogenous peptides is hindered by the immense diversity within this class of signaling molecules. Additionally, neuropeptides are bioactive at concentrations 100x - 1000x lower than that of neurotransmitters and are prone to enzymatic degradation after synaptic release. Mass spectrometry (MS) is a highly sensitive analytical tool that can identify, quantify, and localize analytes without comprehensive a priori knowledge. It is well-suited for globally profiling neuropeptides and aiding in the discovery of novel peptides. Due to the low abundance and high chemical diversity of this class of peptides, several sample preparation methods, MS acquisition parameters, and data analysis strategies have been adapted from proteomics techniques to allow optimal neuropeptide characterization. Here, methods are described for isolating neuropeptides from complex biological tissues for sequence characterization, quantitation, and localization using liquid chromatography (LC)-MS and matrix-assisted laser desorption/ionization (MALDI)-MS. A protocol for preparing a neuropeptide database from the blue crab, Callinectes sapidus, an organism without comprehensive genomic information, is included. These workflows can be adapted to study other classes of endogenous peptides in different species using a variety of instruments.

Introduction

The nervous system is complex and requires a network of neurons to transmit signals throughout an organism. The nervous system coordinates sensory information and biological response. The intricate and convoluted interactions involved in signal transmission require many different signaling molecules such as neurotransmitters, steroids, and neuropeptides. As neuropeptides are the most diverse and potent signaling molecules that play key roles in activating physiological responses to stress and other stimuli, it is of interest to determine their specific role in these physiological processes. Neuropeptide function is related to their amino acid structure, which determines mobility, receptor interaction, and affinity1. Techniques such as histochemistry, which is important because neuropeptides can be synthesized, stored, and released in different regions of the tissue, and electrophysiology have been employed to investigate neuropeptide structure and function2,3,4, but these methods are limited by throughput and specificity to resolve the vast sequence diversity of neuropeptides.

Mass spectrometry (MS) enables the high throughput analysis of neuropeptide structure and abundance. This can be performed through different MS techniques, most commonly liquid chromatography-electrospray ionization MS (LC-ESI-MS)5 and matrix-assisted laser desorption/ionization MS (MALDI-MS)6. Utilizing high accuracy mass measurements and MS fragmentation, MS provides the ability to assign amino acid sequence and post-translational modification (PTM) status to neuropeptides from complex mixtures without a priori knowledge to aid in ascertaining their function7,8. In addition to qualitative information, MS enables quantitative information of neuropeptides through label-free quantitation (LFQ) or label-based methods such as isotopic or isobaric labeling9. The main advantages of LFQ include its simplicity, low cost of analysis, and decreased sample preparation steps which can minimize sample loss. However, the disadvantages of LFQ include increased instrument time costs as it requires multiple technical replicates to address quantitative error from run-to-run variability. This also leads to a decreased ability to accurately quantify small variations. Label-based methods are subjected to less systematic variation as multiple samples can be differentially labeled using a variety of stable isotopes, combined into one sample, and analyzed through mass spectrometry simultaneously. This also increases throughput, although isotopic labels can be time consuming and costly to synthesize or purchase. Full scan mass spectra (MS1) spectral complexity also increases as multiplexing increases, which decreases the number of unique neuropeptides able to be fragmented and therefore, identified. Conversely, isobaric labeling does not increase spectral complexity at the MS1 level, although it introduces challenges for low abundance analytes such as neuropeptides. As isobaric quantitation is performed at the fragment ion mass spectra (MS2) level, low-abundance neuropeptides may be unable to be quantified as more abundant matrix components may be selected for fragmentation and those selected may not have high enough abundance to be quantified. With isotopic labeling, quantitation can be performed on every identified peptide.

In addition to identification and quantification, localization information can be obtained by MS through MALDI-MS imaging (MALDI-MSI)10. By rastering a laser across a sample surface, MS spectra can be compiled into a heat map image for each m/z value. Mapping transient neuropeptide signal intensity in different regions across conditions can provide valuable information for function determination11. Localization of neuropeptides is especially important because neuropeptide function may differ depending on location12.

Neuropeptides are found in lower abundance in vivo than other signaling molecules, such as neurotransmitters, and thus require sensitive methods for detection13. This can be achieved through the removal of higher abundance matrix components, such as lipids11,14. Additional considerations for the analysis of neuropeptides need to be made when compared to common proteomics workflows, mainly because most neuropeptidomic analyses omit enzymatic digestion. This limits software options for neuropeptide data analysis as most were built with algorithms based on proteomics data and protein matches informed by peptide detection. However, many software such as PEAKS15 is more suited to neuropeptide analysis due to their de novo sequencing capabilities. Several factors need to be considered for the analysis of neuropeptides starting from extraction method to MS data analysis.

The protocols described here include methods for sample preparation and dimethyl isotopic labeling, data acquisition, and data analysis of neuropeptides by LC-ESI-MS, MALDI-MS, and MALDI-MSI. Through representative results from several experiments, the utility and ability of these methods to identify, quantify, and localize neuropeptides from blue crabs, Callinectes sapidus, is demonstrated. To better understand the nervous system, model systems are commonly used. Many organisms do not have a fully sequenced genome available, which prevents comprehensive neuropeptide discovery at the peptide level. In order to mitigate this challenge, a protocol for identifying novel neuropeptides and transcriptome mining to generate databases for organisms without complete genome information is included. All protocols presented here can be optimized for neuropeptide samples from any species, as well as applied for the analysis of any endogenous peptides.

Protocol

All tissue sampling described was performed in compliance with the University of Wisconsin-Madison guidelines.

1. LC-ESI-MS analysis of neuropeptides

  1. Neuropeptide extraction and desalting
    1. Prior to tissue acquisition, prepare acidified methanol (acMeOH) (90:9:1 MeOH:water:acetic acid) as described in16.
    2. Collect brain tissue from the crustacean17 and use forceps to immediately place one tissue each in a 0.6 mL tube containing 20 µL of acMeOH.
      NOTE: Tissue dissection protocols vary greatly for different animals and different tissue types. The reader is referred to protocol17 for a detailed description on how to dissect brain tissue and multiple other tissue types from the crustacean. Samples can be stored at -80 °C until use (ideally within 6 months). The volumes described are used for a single brain from Callinectes sapidus. Volumes should be scaled for tissue size. Tissue may be flash frozen immediately without solvent, although this is not recommended as endogenous proteolytic enzymes will not be inhibited and remain active, though at a slower rate when cold.
    3. Add 150 µL of acMeOH to the sample. Set the total sonication time to 24 s, pulse time to 8 s, pause time to 15 s, and amplitude to 50% on an ultrasonic homogenizer and homogenize the samples on ice.
      NOTE: There are different homogenization systems available. Adjust the settings and conditions according to sample type and equipment.
    4. Centrifuge the sample at 4 °C at 20,000 x g for 20 min. With a pipette, transfer the supernatant in a tube and dry it in a vacuum concentrator (266 x g, 1 x 10-4 Torr) at approximately 35 °C.
      NOTE: The dried samples can be stored at -80 °C until use (ideally within 6 months). Heating the vacuum concentrator must be performed with caution. While heat shortens the dry time, the sample must be removed from the concentrator immediately after all the liquid has evaporated to minimize peptide degradation. To avoid this, heating may be omitted from this and all subsequent steps.
    5. For desalting, reconstitute the extracted tissue sample in 20 µL of 0.1% formic acid (FA), vortex well, and sonicate in a water bath at room temperature for 1 min.
      NOTE: There are different desalting materials available. Adjust the solutions and volumes according to the resin identity and neuropeptide amount. Total peptide amount may be estimated using a commercial peptide quantitation assay (see Table of Materials) .
    6. Apply 0.5 µL of sample to a pH strip to confirm that pH < 4. If the pH is higher, add 1 µL aliquots of 10% FA until pH < 4.
    7. Follow manufacturer's protocol for desalting18. Prepare a wetting solution containing 100 µL of 50% acetonitrile (ACN), equilibration solution containing 100 µL of 0.1% FA, wash solution containing 100 µL of 0.1% FA, and elution solutions containing 20 µL of 25% ACN/0.1% FA, 20 µL of 50% ACN/0.1% FA, and 20 µL of 75% ACN/0.1% FA.
    8. Obtain a 10 μL desalting tip with C18 resin (see Table of Materials).
    9. Place the desalting tip on a 20 μL pipette that is set to 15 μL. Once the desalting tip is wet, prevent air from passing through by keeping the pipette depressed when out of solution until it will be discarded.
    10. Aspirate the tip 3x with wetting solution and 3x with equilibration solution. Aspirate in the sample 10x followed by washing 3x in wash solution, discarding each wash. Elute by aspirating 10x in each of the elution solutions in order of increasing ACN.
      NOTE: Elution fractions can be kept separate or combined for further analyses.
    11. Discard the used desalting tip and dry the eluted neuropeptides in a vacuum concentrator (266 x g, 1 x 10-4 Torr) at approximately 35 °C.
      NOTE: This can be stored at -80 °C until use (ideally within 6 months).
  2. Isotopic labeling of neuropeptides in tissue extract
    NOTE: This step is optional and only used when quantification is desired.
    1. Prepare the 2-plex isotopic dimethyl labeling solution in a fume hood: 1% CH2OH2 (13.5 µL of stock 37 weight/weight percentage (wt. %) in water solution in 486.5 µL of water), 1% CH2OD2 (25 µL of stock 20 wt. % solution in 475 µL of water), and 0.03 M borane pyridine (3.75 µL of stock 8 M solution in 996.25 µL of water).
      CAUTION: Formaldehyde is toxic, so all solutions should be kept in a ventilated hood. Wear gloves, a lab coat, eye protection, and impervious footwear. Contact lenses should not be worn when working with this material.
      NOTE: There are different isotopic reagents; select the appropriate ones based on sample type and number of labeling channels desired.
    2. Dissolve crude neuropeptide extract in 10 µL of water and sonicate for 10 min.
    3. Add 10 µL of a different isotopic formaldehyde solution (i.e., CH2OH2, CH2OD2, etc.) to each different experimental condition to be measured quantitatively. Vortex to mix well and briefly centrifuge each sample at 2,000 x g.
    4. Add 10 µL of 0.03 M borane pyridine to each sample tube. Vortex to mix well and briefly centrifuge each sample at 2,000 x g.
    5. Incubate the samples for 15 min at 37 °C in a water bath.
    6. Remove the samples from the water bath and add 10 µL of 100 mM ammonium bicarbonate. Vortex to mix well and briefly centrifuge each sample at 2,000 x g.
    7. Combine the labeled samples for one 2-plex sample and dry the neuropeptides in a vacuum concentrator (266 x g, 1 x 10-4 Torr) at approximately 35 °C.
    8. Desalt the labeled neuropeptides by reperforming steps 1.1.5 - 1.1.10 and store them until ready for data acquisition.
  3. Data Acquisition
    1. Reconstitute the dried desalted neuropeptides in 12 µL of 3% ACN/0.1% FA, vortex well, sonicate in 37 °C water bath for 1 min, and briefly centrifuge at 2,000 x g. Transfer each sample into autosampler vials.
      ​NOTE: Adjust the sample volume according to neuropeptide amount to a concentration of ~1 µg peptide per µL. Total peptide amount may be estimated using a commercial peptide quantitation assay (see Table of Materials) .
    2. Use an autosampler to inject 1 µL of sample into a high-resolution nano-LC-MS/MS instrument (see Table of Materials).
    3. Use an approximately 15 cm long reversed-phase (RP) C18 column (see Table of Materials) for running the sample with 0.1% FA in water as mobile phase A and 0.1% FA in ACN as mobile phase B. Run the samples with a gradient of 3% - 95% of B at a rate of 300 nL/min for over 11 min.
    4. For the MS instrument used here, use common MS conditions of 2.00 kV for spray voltage and 275 °C for capillary temperature.
    5. Acquire MS spectra in the range of 200 - 2,000 m/z with a resolution of 60,000, automatic gain control (AGC) target of 1 x 106, and max ion injection time (IT) of 150 ms.
    6. Select the 15 most intense ions (minimum intensity of 3.2 x 104) for higher-energy collision dissociation (HCD) fragmentation using a normalized collision energy of 30, isolation window of 2.0 m/z, resolution of 15,000, an AGC target of 2 x 105, and max IT of 250 ms.
    7. Set a dynamic exclusion window of 30 s. Exclude ions with a charge of 1 or ≥ 8 and ions with unrecognized charge states.
  4. Neuropeptide identification and quantification
    NOTE: Many software for database searching and peptide quantification (both open-source and commercial) are available. Here, PEAKS Studio (proteomics software)15 will be used.
    1. Perform database searching using the steps outlined in 1.4.2 - 1.4.6.
    2. Create a new project and add the LC-MS data selecting None for the enzyme, Orbitrap for the instrument, HCD for the fragment, and data-dependent acquisition (DDA) for acquisition.
      NOTE: Select the appropriate parameters based on data acquisition parameters.
    3. Select Identifications and select Correct Precursor [DDA] and Mass only.
    4. Select Database Search and set an error tolerance of 20.0 ppm using monoisotopic mass for precursor mass and 0.02 Da for fragment ion mass, None for enzyme type, Unspecific for digest mode, 100 for max missed cleavages, and the following variable PTMs with the max allowed variable PTM per peptide of 3: Amidation, Oxidation (M), Pyro-glu from E, and Pyro-glu from Q.
    5. Select the Neuropeptide Database, estimate false discovery rate (FDR) with decoy-fusion.
      NOTE: The mass tolerance error should be adjusted to match the data collected. Use the appropriate database for the sample type. When no enzyme is selected, the max missed cleavages parameter does not affect the search. However, a large number of missed cleavages is required if the software does not have the Unspecified digest mode as an option.
    6. If label-free quantification is desired, select Quantification, select Label-Free and set an error tolerance of 20.0 ppm and retention time tolerance of 1.0 min.
    7. Perform precursor ion quantification if step 1.2 for isotopic labeling was performed.
      1. Select Quantification, select Precursor Ion Quantification, use a retention time range of 1.0 min, and use an FDR threshold of 1%.
      2. Select a preset or custom quantification method from the Select Method drop-down menu.
      3. To create a new custom method, click Window > Configuration > Label Q Method > New. Name the new method and select Precursor Ion Quantification for Method Type. Select Add Row and select modification from the PTM Options list.
      4. Add the LC-MS data and select Reference Condition to be the modification on neuropeptides from the control condition of the experiment.
    8. Evaluate the search results as described in steps 1.4.9 - 1.4.11.
    9. Filter the results through the summary tab for peptides and proteins with -10lgP ≥ 20, select ≥ 1 unique peptide, and select box labeled With Significant Peptides.
    10. Evaluate the database search results where Protein.csv represents neuropeptide identifications and Peptide.csv represents neuropeptide fragment identifications.
    11. Inspect the database search for protein and peptide scores, mass accuracy, and sequence coverage.
      ​NOTE: Each database search software uses unique scoring algorithms and may need to be evaluated accordingly. Identifications can be evaluated by manually inspecting the observed spectra for identified peptides containing the complete fragment ion series.

2. MALDI-MS spotting analysis of neuropeptides

  1. Sample Preparation
    1. Follow step 1.1 or steps 1.1 - 1.2 if quantification is desired, excluding step 1.2.8 (desalting after isotopic labeling is not required prior to MALDI-MS analysis).
    2. Reconstitute the dried desalted neuropeptides in 5 µL of 0.1% FA, vortex well, sonicate in a 37 °C water bath for 1 min, and briefly centrifuge at 2,000 x g.
    3. For spotting of neuropeptides in crustacean tissues, prepare 150 mg/mL 2,5-dihydroxybenzoic acid (DHB) in 50% methanol (MeOH)/0.1% FA (v/v) as the matrix.
    4. Pipette a 3 µL droplet of sample onto a hydrophobic film (see Table of Materials) and pipette 3 µL of the matrix directly on the sample droplet. Pipette up and down to mix.
    5. Pipette 1 µL of the 1:1 sample: matrix mixture into a well of the MALDI stainless steel target plate. Use the pipette tip to spread each mixture out to the edges of the sample well. The sample must touch the edges of the well engraving to facilitate uniform distribution (Figure 4A).
    6. Spot 1 µL of 1:1 calibrant:matrix mixture (commercial or custom calibration mix, polymer materials (i.e., red phosphorus dissolved in MeOH), or common matrix cluster ions)12 into a well near the sample.
      ​NOTE: Red phosphorus does not need to be mixed with matrix before spotting.
  2. Data acquisition
    1. Insert target plate containing dried sample spots into MALDI Tandem Time-of-Flight (TOF/TOF) instrument (see Table of Materials).
    2. For DHB matrix, set laser power to 95%, select Automatic Optimal Detector Gain, and Smart - Complete Sample sample carrier movement mode. Acquire MS spectra in the range of 200 - 3200 m/z and add multiple spectra from each spot together to increase neuropeptide signal-to-noise ratio.
      NOTE: Optimize the percent laser power, detector gain, and select the appropriate sample carrier movement mode so that every acquisition covers roughly the entire spot and subsequent acquisitions do not go to the previous positions. 
    3. Calibrate the instrument. 
      ​NOTE: Adjust the mass range to encompass desired neuropeptide range.
  3. Data analysis
    1. Open the MALDI-MS file in data analysis software (see Table of Materials) and click Baseline Subtraction for the software used here.
    2. Perform peak picking by clicking Find Mass List. If there are too few peaks, edit the mass list manually by selecting Edit Mass List and click on peaks in the spectrum to add them to the mass list.
    3. Perform accurate mass matching by comparing mass list with neuropeptide database containing [M+H]+ m/z values (± 200 ppm error).
      NOTE: Common salt adducts, such as [M+K]+, [M+Na]+, and [M+NH4]+, should also be included in the accurate mass matching target list.
    4. To verify the identified peaks, generate a list of m/z of interest and perform MS/MS experiments.

3. MALDI-MS imaging analysis of neuropeptides

  1. Sample preparation
    NOTE: Embedding and sectioning steps are not necessary for tissues that are too thin to be sectioned.
    1. Fill half a cryostat cup with gelatin (37 °C, 100 mg/mL in deionized water) and allow it to solidify at room temperature. Keep leftover liquid gelatin warm in a 37 °C water bath.
    2. Collect desired neuronal tissue from the animal and use forceps to immediately dip the tissue into a 0.6 mL tube containing deionized water for 1 s.
      NOTE: Refer to Step 1.1.2 NOTE for neuronal tissue dissection.
    3. Place the tissue on top of the solid gelatin and fill the rest of the cryostat cup with liquid gelatin. Use forceps to position the tissue.
    4. Place the cryostat cup on a flat surface and freeze with dry ice.
      NOTE: Store samples at -80 °C until use (ideally within 6 months).
    5. For sectioning preparation, separate the gelatin-embedded sample from the cryostat mold by cutting the mold away.
    6. Mount the embedded tissue onto a cryostat chuck by pipetting a 1 mL droplet of deionized water onto the chuck and immediately pressing the embedded tissue onto the droplet.
    7. Once frozen, pipette more deionized water around the tissue to further secure it to the chuck. Perform these steps inside the cryostat box (see Table of Materials) set at -20 °C.
    8. Section the tissue at an approximate thickness of one cell (8-20 µm depending on the sample type) and thaw mount each section onto an indium tin oxide (ITO)-coated glass slide by placing one side of the slide near the section and placing a finger on the other side of the slide to slowly warm the glass and allow the section to stick to the slide.
      NOTE: Tissue sections may also be thaw-mounted by picking up one edge of the gelatin with tweezers (chilled to -20 °C), placing it on the ITO-coated glass slide, and placing a finger on the other side of the slide to slowly warm the glass and allow the section to stick to the slide.
    9. Spot the sample to be used as a calibrant (see step 2.1.6 for calibrant options) by drawing a small circle near the tissue section using a hydrophobic pen and spotting the calibrant inside the circle.
    10. Mark each corner of the slide with a whiteout pen with a small shape containing sharp edges (i.e., x) to be used as teach points.
    11. Place the glass slide into the MALDI slide adapter plate and take a high resolution (≥2400 DPI) optical image scan using a scanner.
    12. Spray matrix on the tissue section using an automated sprayer (see Table of Materials for sprayer details and instructions).
    13. For MSI of neuropeptides in crustacean tissues use 40 mg/mL DHB in 50% methanol/0.1% FA (v/v) as the matrix, set the nozzle temperature to 80 °C, velocity to 1,250 mm/min, flow rate to 0.1 mL/min, number of passes to 12, and 30 s in between each pass for the automatic sprayer.
  2. Data acquisition
    1. Insert the completely dried target plate containing thaw-mounted tissue sections that were sprayed with the matrix.
    2. Set up the MS imaging acquisition file parameters so that the laser diameter is smaller than the raster step size.
    3. Load the scanned optical image and calibrate the sample plate using the x teach points. Define the tissue areas of interest to be measured slightly larger than the actual tissue section to also include areas containing only matrix.
    4. Calibrate the instrument and acquire spectra in the range of 200 - 3200 m/z. Adjust the mass range to encompass desired neuropeptide range.
  3. Data analysis
    1. To process data, import MS imaging dataset into desired software, select a baseline removal algorithm, and normalize data using the Total Ion Count.
      NOTE: Selection of different normalization algorithms, such as median, root mean square (RMS) value, or the intensity of a reference m/z value, will likely change the spatial distribution of many m/z values. Choose the normalization algorithm best suited for desired analytes.
    2. To generate an image for each m/z value from a theoretical peak list, upload a comma-separated values (CSV) file containing neuropeptide [M+H]+, [M+Na]+, [M+NH4]+, etc. Obtain m/z values by clicking File > Import > Peak List. Name the peak list.
    3. To estimate the appropriate ppm error threshold, first manually identify a neuropeptide peak in the MS spectrum and compare it with the neuropeptide theoretical mass. Calculate the ppm error and click File > File Properties > Interval Width and input ppm error.
    4. Select the peak list from the drop-down menu and click Create m/z Images For Every Interval of The Peak List.
    5. Save each m/z image by clicking Save Screenshot of Each m/z Image.
      ​NOTE: Putative neuropeptide identification can be performed by identifying m/z images where the analyte signal is only localized within the tissue and not in the surrounding matrix.
    6. To verify peak identity, generate a list of m/z of interest and perform MS/MS experiments.

4. Discovering novel putative neuropeptides using de novo sequencing

  1. Perform steps 1.4.2 - 1.4.5.
  2. Export de novo only peptides.csv from PEAKS software with an average of local confidence (ALC) score of ≥ 75.
    NOTE: There are many software available to perform de novo sequencing, each with its own scoring algorithms and should be evaluated accordingly.
  3. Search the peptide list for known sequence motifs indicative of neuropeptides belonging to specific neuropeptide families19.
    ​NOTE: While motifs are commonly well conserved across species, the motifs searched for should be selected with consideration to the sample organism.

5. Transcriptome mining for predicted neuropeptide sequences

NOTE: This step is optional and only used to add to an existing neuropeptide database or build a new neuropeptide database.

  1. Choose a known preprohormone amino acid sequence of interest and use tBLASTn (http://blast.ncbi.nlm.nih.gov/Blast.cgi?PROGRAM=tblastn&BLAST_PROGRAMS=tblastn&PAGE
    _TYPE=BlastSearch&SHOW_DEFAULTS=on&LINK
    _LOC=blasthome) to search query preprohormone sequence against databases including nr/nt, Refseq_genomes, EST and TSA.
    NOTE: To search query sequences against protein database, use BLASTp (http://blast.ncbi.nlm.nih.gov/Blast.cgi?PROGRAM=blastp&BLAST_PROGRAMS=blastp&PAGE
    _TYPE=BlastSearch&SHOW_DEFAULTS=on&BLAST
    _SPEC=&LINK_LOC=blasttab&LAST_PAGE=tblastn).
    1. Select the target organism (tax id) and change Expect Threshold algorithm parameters to 1000 to include low score alignments.
    2. Run BLAST program and then check the results for high homology scores between query and subject sequences producing significant alignments. Save FASTA file containing nucleotide sequence.
      NOTE: If there are several subject sequences with similar homology scores, carry out a MAFFT alignment to narrow down putative sequences20,21.
  2. Translate preprohormone nucleotide sequence into preprohormone peptide sequences using Expasy Translate tool (https://web.expasy.org/translate/). For C. sapidus, select Invertebrate Mitochondrial for genetic code.
  3. Check for signal peptide sequence and prohormone cleavage sites in the peptide sequences using SignalP (https://services.healthtech.dtu.dk/service.php?SignalP). 
    NOTE: Homology to known preprohormone processing schemes can also be used to identify prohormone cleavage sites. Possible post-translational modifications for signal peptides may be predicted if desired. Sulfinator (https://web.expasy.org/sulfinator/) can be used to predict sulfation state of tyrosine residues. DiANNA (http://clavius.bc.edu/~clotelab/DiANNA/) can be used to predict disulfide bond connectivity.

Results

The workflow for sample preparation and MS analysis is depicted in Figure 1. After the dissection of neuronal tissue, homogenization, extraction, and desalting are performed to purify neuropeptide samples. If isotopic label-based quantification is desired, samples are then labeled and desalted once again. The resulting sample is analyzed through LC-MS/MS for neuropeptide identification and quantification.

Neuropeptides identified through the proteomics software sh...

Discussion

The accurate identification, quantification, and localization of neuropeptides and endogenous peptides found in the nervous system are crucial toward understanding their function23,24. Mass spectrometry is a powerful technique that can allow all of this to be accomplished, even in organisms without a fully sequenced genome. The ability of this protocol to detect, quantify, and localize neuropeptides from tissue collected from C. sapidus through a combina...

Disclosures

The authors have nothing to disclose.

Acknowledgements

This research was supported by National Science Foundation (CHE-1710140 and CHE-2108223) and National Institutes of Health (NIH) through grant R01DK071801. A.P. was supported in part by the NIH Chemistry-Biology Interface Training Grant (T32 GM008505). N.V.Q. was supported in part by the National Institutes of Health, under the Ruth L. Kirschstein National Research Service Award from the National Heart Lung and Blood Institute to the University of Wisconsin-Madison Cardiovascular Research Center (T32 HL007936). L.L. would like to acknowledge NIH grants R56 MH110215, S10RR029531, and S10OD025084, as well as funding support from a Vilas Distinguished Achievement Professorship and Charles Melbourne Johnson Professorship with funding provided by the Wisconsin Alumni Research Foundation and University of Wisconsin-Madison School of Pharmacy.

Materials

NameCompanyCatalog NumberComments
Chemicals, Reagents, and Consumables
2,5-Dihydroxybenzoic acid (DHB) matrixSupelco39319
Acetic acidFisher ChemicalA38S-500
Acetonitrile Optima LC/MS gradeFisher ChemicalA955-500
Ammonium bicarbonateSigma-Aldrich9830
Borane pyridineSigma-Aldrich179752
Bruker peptide calibration mixBruker DaltonicsNC9846988
CapillaryPolymicro1068150019to make nanoflow column (75 µm inner diameter x 360 µm outer diameter)
Cryostat cupSigma-AldrichE6032any cup or mold should work
 Microcentrifuge TubesEppendorf30108434
FormaldehydeSigma-Aldrich252549
Formaldehyde - D2Sigma-Aldrich492620
Formic acid Optima LC/MS gradeFisher ChemicalA117-50
GelatinDifco214340place in 37 °C water bath to melt
Hydrophobic barrier penVector Labs15553953
Indium tin oxide (ITO)-coated glass slidesDelta TechnologiesCB-90IN-S10725 mm x 75 mm x 0.8 mm (width x length x thickness)
LC-MS vialsThermoTFMSCERT5000-30LVW
Methanol Optima LC/MS GradeFisher ChemicalA456-500
ParafilmSigma-AldrichP7793Hydrophobic film
pH-Indicator stripsSupelco109450
Red phosphorus clustersSigma-Aldrich343242
Reversed phase C18 materialWaters186002350manually packed into nanoflow column
Wite-out penBIC150810
ZipTipMilliporeZ720070
Instruments and Tools
Automatic matrix sprayer system- M5HTX Technologies, LLC
Centrifuge - 5424 REppendorf05-401-205
Cryostat- HM 550Thermo Fisher Scientific956564A
DesiccantDrierite2088701
ForcepsWPI501764
MALDI stainless steel target plateBruker Daltonics8280781
Pipet-Lite XLSRainin17014391200 µL
Q Exactive Plus Hybrid Quadrupole-OrbitrapThermo Fisher ScientificIQLAAEGAAPFALGMBDK
RapifleX MALDI-TOF/TOFBruker Daltonics
SpeedVac - SVC100SavantSVC-100D
Ultrasonic CleanerBransonic2510R-MTHfor sonication
Ultrasonic homogenizerFisher ScientificFB120110FB120 Sonic Dismembrator with CL-18 Probe
Vaccum pump- Alcatel 2008 AIdeal Vacuum ProductsP10976ultimate pressure = 1 x 10-4 Torr
Vortex MixerCorning6775
Water bath (37C) - Isotemp 110Fisher Scientific15-460-10
Data Analysis Software
Expasyhttps://web.expasy.org/translate/
FlexAnalysisBruker Daltonics
FlexControlBruker Daltonics
FlexImagingBruker Daltonics
PEAKS StudioBioinformatics Solutions, Inc.
SCiLS Labhttps://scils.de/
SignalP 5.0https://services.healthtech.dtu.dk/service.php?SignalP-5.0
tBLASTnhttp://blast.ncbi.nlm.nih.gov/Blast.cgi?PROGRAM=tblastn&BLAST_
PROGRAMS=tblastn&PAGE_
TYPE=BlastSearch&SHOW_
DEFAULTS=on&LINK_LOC
=blasthome

References

  1. Hökfelt, T., et al. Neuropeptides - an overview. Neuropharmacology. 39 (8), 1337-1356 (2000).
  2. Radhakrishnan, V., Henry, J. L. Electrophysiology of neuropeptides in the sensory spinal cord. Progress in Brain Research. 104, 175-195 (1995).
  3. Nässel, D. R., Ekström, P. Detection of neuropeptides by immunocytochemistry. Methods in Molecular Biology. 72, 71-101 (1997).
  4. Martins, J., et al. Activation of Neuropeptide Y Receptors Modulates Retinal Ganglion Cell Physiology and Exerts Neuroprotective Actions In Vitro. ASN Neuro. 7 (4), 1759091415598292 (2015).
  5. Racaityte, K., Lutz, E. S. M., Unger, K. K., Lubda, D., Boos, K. S. Analysis of neuropeptide Y and its metabolites by high-performance liquid chromatography-electrospray ionization mass spectrometry and integrated sample clean-up with a novel restricted-access sulphonic acid cation exchanger. Journal of Chromatography. A. 890 (1), 135-144 (2000).
  6. Salisbury, J. P., et al. A rapid MALDI-TOF mass spectrometry workflow for Drosophila melanogaster differential neuropeptidomics. Molecular Brain. 6, 60 (2013).
  7. Schmerberg, C. M., Li, L. Function-driven discovery of neuropeptides with mass spectrometry-based tools. Protein and Peptide Letters. 20 (6), 681-694 (2013).
  8. Lee, J. E. Neuropeptidomics: Mass Spectrometry-Based Identification and Quantitation of Neuropeptides. Genomics & Informatics. 14 (1), 12-19 (2016).
  9. Sauer, C. S., Phetsanthad, A., Riusech, O. L., Li, L. Developing mass spectrometry for the quantitative analysis of neuropeptides. Expert Review of Proteomics. 18 (7), 607-621 (2021).
  10. Pratavieira, M., et al. MALDI Imaging Analysis of Neuropeptides in Africanized Honeybee ( Apis mellifera) Brain: Effect of Aggressiveness. Journal of Proteome Research. 17 (7), 2358-2369 (2018).
  11. Buchberger, A. R., Vu, N. Q., Johnson, J., DeLaney, K., Li, L. A Simple and Effective Sample Preparation Strategy for MALDI-MS Imaging of Neuropeptide Changes in the Crustacean Brain Due to Hypoxia and Hypercapnia Stress. Journal of the American Society for Mass Spectrometry. 31 (5), 1058-1065 (2020).
  12. Vu, N. Q., DeLaney, K., Li, L. Neuropeptidomics: Improvements in Mass Spectrometry Imaging Analysis and Recent Advancements. Current Protein & Peptide Science. 22 (2), 158-169 (2021).
  13. Li, L., Sweedler, J. V. Peptides in the brain: mass spectrometry-based measurement approaches and challenges. Annual Review of Analytical Chemistry (Palo Alto, Calif). 1, 451-483 (2008).
  14. Li, N., et al. Sequential Precipitation and Delipidation Enables Efficient Enrichment of Low-Molecular Weight Proteins and Peptides from Human Plasma. Journal of Proteome Research. 19 (8), 3340-3351 (2020).
  15. Zhang, J., et al. PEAKS DB: de novo sequencing assisted database search for sensitive and accurate peptide identification. Molecular & Cellular Proteomics : MCP. 11 (4), (2012).
  16. Sturm, R. M., Greer, T., Woodards, N., Gemperline, E., Li, L. Mass spectrometric evaluation of neuropeptidomic profiles upon heat stabilization treatment of neuroendocrine tissues in crustaceans. Journal of Proteome Research. 12 (2), 743-752 (2013).
  17. Gutierrez, G. J., Grashow, R. G. Cancer borealis stomatogastric nervous system dissection. Journal of Visualized Experiments: JoVE. (25), e1207 (2009).
  18. DeLaney, K., et al. PRESnovo: Prescreening Prior to de novo Sequencing to Improve Accuracy and Sensitivity of Neuropeptide Identification. Journal of the American Society for Mass Spectrometry. 31 (7), 1358-1371 (2020).
  19. Oleisky, E. R., Stanhope, M. E., Hull, J. J., Christie, A. E., Dickinson, P. S. Differential neuropeptide modulation of premotor and motor neurons in the lobster cardiac ganglion. Journal of Neurophysiology. 124 (4), 1241-1256 (2020).
  20. Ma, M., et al. Combining in silico transcriptome mining and biological mass spectrometry for neuropeptide discovery in the Pacific white shrimp Litopenaeus vannamei. Peptides. 31 (1), 27-43 (2010).
  21. Christie, A. E., Stemmler, E. A., Dickinson, P. S. Crustacean neuropeptides. Cellular and Molecular Life Sciences : CMLS. 67 (24), 4135-4169 (2010).
  22. DeLaney, K., et al. New techniques, applications and perspectives in neuropeptide research. The Journal of Experimental Biology. 221, (2018).
  23. Habenstein, J., et al. Transcriptomic, peptidomic, and mass spectrometry imaging analysis of the brain in the ant Cataglyphis nodus. Journal of Neurochemistry. 158 (2), 391-412 (2021).
  24. Maes, K., et al. Improved sensitivity of the nano ultra-high performance liquid chromatography-tandem mass spectrometric analysis of low-concentrated neuropeptides by reducing aspecific adsorption and optimizing the injection solvent. Journal of Chromatography. A. 1360, 217-228 (2014).
  25. Li, G., et al. Nanosecond photochemically promoted click chemistry for enhanced neuropeptide visualization and rapid protein labeling. Nature Communications. 10 (1), 4697 (2019).
  26. Corbière, A., et al. Strategies for the Identification of Bioactive Neuropeptides in Vertebrates. Frontiers in Neuroscience. 13, 948 (2019).
  27. Chen, R., Ma, M., Hui, L., Zhang, J., Li, L. Measurement of neuropeptides in crustacean hemolymph via MALDI mass spectrometry. Journal of American Society for Mass Spectrometry. 20 (4), 708-718 (2009).
  28. Fridjonsdottir, E., Nilsson, A., Wadensten, H., Andrén, P. E. Brain Tissue Sample Stabilization and Extraction Strategies for Neuropeptidomics. Peptidomics: Methods and Strategies. , 41-49 (2018).
  29. Buchberger, A. R., DeLaney, K., Johnson, J., Li, L. Mass Spectrometry Imaging: A Review of Emerging Advancements and Future Insights. Analytical Chemistry. 90 (1), 240-265 (2018).
  30. Phetsanthad, A., et al. Recent advances in mass spectrometry analysis of neuropeptides. Mass Spectrometry Reviews. , 21734 (2021).
  31. Pérez-Cova, M., Bedia, C., Stoll, D. R., Tauler, R., Jaumot, J. MSroi: A pre-processing tool for mass spectrometry-based studies. Chemometrics and Intelligent Laboratory Systems. 215, 104333 (2021).
  32. Christie, A. E., Chi, M. Prediction of the neuropeptidomes of members of the Astacidea (Crustacea, Decapoda) using publicly accessible transcriptome shotgun assembly (TSA) sequence data. General and Comparative Endocrinology. 224, 38-60 (2015).
  33. Livnat, I., et al. A d-Amino Acid-Containing Neuropeptide Discovery Funnel. Analytical Chemistry. 88 (23), 11868-11876 (2016).
  34. Lehrer, R. I., Ganz, T. Defensins: endogenous antibiotic peptides from human leukocytes. Ciba Foundation Symposium. 171, 276-290 (1992).

Reprints and Permissions

Request permission to reuse the text or figures of this JoVE article

Request Permission

Explore More Articles

Mass SpectrometryNeuropeptidesCallinectes SapidusPeptide TherapeuticsNeuropeptide BiomarkersPeptide ExtractionAcidified MethanolUltrasonic HomogenizerSupernatantDesaltingC18 ResinElution SolutionsAcetonitrileVacuum Concentrator

This article has been published

Video Coming Soon

JoVE Logo

Privacy

Terms of Use

Policies

Research

Education

ABOUT JoVE

Copyright © 2025 MyJoVE Corporation. All rights reserved