Mass spectrometric characterization of the crustacean ... - Core

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Mass spectrometric characterization of the crustacean neuropeptidome Qing Yu, Chuanzi OuYang, Zhidan Liang, Lingjun Li ∗ School of Pharmacy and Department of Chemistry, University of Wisconsin – Madison, Madison, WI, USA

a r t i c l e

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a b s t r a c t

Article history:

Neuropeptides (NPs) are the largest class of signaling molecules used by nervous systems.

Available online 12 March 2014

Despite their functional importance, numerous challenges exist to characterize the full

Keywords:

MS-based techniques for NP identification and quantitation, as well as sample preparation

complement of NPs – the neuropeptidome. In this review, we discuss recent advances in Neuropeptide

strategies for various applications in several crustacean model organisms. By surveying

NP

published examples of crustacean neuropeptidomic analyses, we highlight challenges and

Peptidomics

progress in this dynamic field, and summarize the current state of knowledge about crus-

Mass spectrometry

tacean NPs and MS-based methodologies for NP analysis.

Crustacean

© 2014 Published by Elsevier B.V. on behalf of European Proteomics Association (EuPA). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).

1.

Introduction

Animal behaviors are precisely controlled by the nervous system which employs a myriad of signaling molecules to mediate this control process. One of the most diverse signaling molecules are neuropeptides (NPs), which are synthesized as larger precursor proteins, and undergo extensive processing and modification to become bioactive NPs to participate in cell–cell signaling. Since they are directly involved in modulating many physiological processes, such as feeding, pain sensing and reproduction [1,2], there is growing interest in studying their structures, functions and distributions. Because of the relatively simple nervous system and accessible electrophysiology at the single-cell and neural circuit level, decapod crustacean has long been used as an attractive model preparation for neuromodulation and NP research [3,4], as evidenced by the large number of NPs discovered since 2000 (Table 1).

Traditional studies on NPs often use biochemical techniques that can be imprecise and cumbersome. Mass spectrometry (MS) has evolved as a powerful tool to characterize NPs, due to its capability to precisely determine the identity and primary structure of a NP as well as its ability to quantify these signaling molecules in a complex mixture. A new concept, peptidomics, was introduced in 2001, largely due to the rapid growth of MS-based large-scale peptide and protein analysis [5–7]. By exploring the utility of MS based methods, various NP families with multiple isoforms that differ from each other by a single amino acid can be distinguished in contrast to antibody-based immunochemical techniques. The combined use of MS and MS/MS scans enable the discovery of novel members of established NP families and the identification of new peptide families, significantly expanding the neuropeptidome in a model organism [3,8]. With their structural information available, the next step for NP study is to determine its function during various physiological processes.

∗ Corresponding author at: School of Pharmacy and Department of Chemistry, University of Wisconsin – Madison, 777 Highland Avenue, Madison, Wisconsin 53705-2222, USA. Tel.: +1 608 265 8491; fax: +1 608 262 5345. E-mail address: [email protected] (L. Li). http://dx.doi.org/10.1016/j.euprot.2014.02.015 2212-9685/© 2014 Published by Elsevier B.V. on behalf of European Proteomics Association (EuPA). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).

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Table 1 – Crustacean neuropeptidomic studies by mass spectrometric techniques. Species Ghost crab Ocypode ceratophthalma Jonah crab Cancer borealis

American lobster Homarus americanus

Blue crab Callinectes sapidus

Water flea Daphnia pulex White shrimp Litopenaeus vannamei European green crab Carcinus maenas Spinycheek crayfish Orconectes limosus Red swamp crayfish Procambarus clarkii Giant tiger prawn Penaeus monodon Common yabby Cherax destructor Red rock crab Cancer productus

Tissues studied Eyestalk ganglia (including sinus glands), brain, pericardial organ Hemolymph, stomatogastric nervous system, pericardial organ, thoracic ganglia Brain, pericardial organ, stomatogastric ganglion

Pericardial organ, stomatogastric nervous system, sinus gland Brain-optic ganglia, brain Sinus gland, brain Brain, thoracic ganglia, sinus gland, pericardial organ Sinus gland Brains, ventral nerve cord Eyestalk, brain, thoracic ganglia Stomatogastric nervous system Sinus gland, pericardial organ

The advancement of MS-based tools and tandem MS capability coupled with isotope labeling strategies and label-free approaches have accelerated several large-scale comparative neuropeptidomic analyses, enabling a global view of coordinated changes of NPs related to a physiological process.

2.

Sample preparation

2.1.

Overview of sampling strategies

Because of the biochemical complexity, high-salt contents, and endogenous proteases, sample preparation is often critical to produce the desired outcome of a peptidomic experiment. Depending on the goals and requirements of specific experiments, various sample preparation methods have been developed. As outlined in Fig. 1, samples can be prepared by homogenization and extraction of tissues, analyzed by direct tissue experiments or collected by microdialysis techniques followed by liquid chromatography (LC) coupled to MS or MS/MS analysis.

2.2.

Sample preparation for direct tissue analysis

For tissue-based study, it is crucial to avoid delocalization and degradation of analytes. Proper tissue harvest, stabilization and preservation are all important aspects in the sample preparation process. After animal sacrifice, snapfreezing dissected tissue in powdered dry ice, liquid nitrogen

MS instrumentation

References

MALDI-TOF/TOF ESI-Q-TOF

[32]

MALDI-TOF/TOF ESI-Q-TOF MALDI–FTMS

[39,45,91,104,115,187]

MALDI–FTMS ESI-Q-TOF MALDI TOF/TOF MALDI LTQ Orbitrap MALDI–FTICR ESI-Q-TOF MALDI TOF/TOF MALDI TOF/TOF MALDI-FTMS ESI-Q-TOF MALDI-FTMS ESI-Q-TOF

[36,37,40,89,135,188]

ESI-Q-TOF

[38]

ESI-Q-TOF MALDI TOF/TOF ESI-Q-TOF

[135,190]

MALDI TOF/TOF

[195]

MALDI-FTMS ESI-Q-TOF

[196]

[42,46]

[189] [44] [116]

[191–194]

or liquid nitrogen-chilled isopentane would quickly preserve the structural integrity. Storage at −80 ◦ C is required to minimize the degradation until use [9]. Longer freezing method could be achieved by loosely wrapping the tissue in aluminum foil and gently placing it into liquid nitrogen, ice-cold ethanol or isopropanol bath for 30–60 s [10]. Tissue preservation is required to prevent post mortem proteome degradation and slow down sample aging before actual MS experiments. Common methods include focusing microwave irradiation [11] and thermal denaturation by Stabilizor T1, which extensively denature active proteolytic enzymes [12,13]. Other popular method such as formaldehyde-fixed paraffin-embedding (FFPE) is not very suitable with MS imaging because of the cross-linking it caused between peptides and proteins [14]. A modified approach of formalin-fixed paraffin embedding used ethanol rather than formalin to fix the tissue. MS images generated in this way were significantly improved [15]. One significant advantage of direct tissue analysis over liquid phase LC–MS method is the ability to preserve the structural integrity and morphology of the tissue. In order to get smooth thin tissue sections around 10–20 ␮m in cryostat, tissues are usually embedded in supporting media such as optimal cutting temperature (OCT) compound, Tissuetek and carboxymethylcellulose (CMC) [10]. However, these polymer-based materials which contain polyethylene glycol (PEG), polyvinyl alcohol (PVA), or both, can cause strong background signals which mask the detection of peptides and proteins of interest. In order to eliminate the interference from

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Fig. 1 – Illustration of four major sample preparation strategies for mass spectrometric analysis of neuropeptides: (1) direct imaging of tissue sections, (2) direct profiling of isolated tissues, (3) analysis of tissue extract, and (4) in vivo microdialysis sampling.


embedding materials, ice is commonly used for analytes at low m/z [16]. At medium and high mass range, gelatin is able to provide high-quality MS images with minimal interference [17,18]. Sucrose is also a promising alternative as reported by Verhaert et al. in their study of the NPs in a cockroach brain [19]. Strohalm et al. were able to use poly[N-(2-hydroxypropyl) methacrylamide] (pHPMA) as a novel embedding/supporting material to enhance the signal intensity from bumblebee and mouse lung samples without visible background peaks [20]. Fixation of tissue slices onto sample plate is commonly achieved by thaw-mounting [10]. When the analysis is carried out on a matrix-assisted laser desorption/ionization (MALDI) TOF instrument, an electrically conductive sample plate is required, such as gold-coated, ITO-coated glass slides or stainless steel metal plates [21,22]. For MALDI linear ion trap (LIT) based mass spectrometric study, regular microscopic glass slides work as well [19]. Transparent glass slides also allow histological tissue staining after mass spectrometric imaging (MSI) studies to enable the correlation on the same tissue section. When reversible matrix-wash-up step is required for subsequent study, such as histological staining, adhesive double-sided conductive tape is preferred as the fixative approach. When the interest of study is peptides and proteins in MSI, washing the fixed tissue before matrix deposition is often carried out to remove salts and lipids. When the composition of organic washing solution is optimized for specific tissue sample, the acquired MS spectra show enhanced signal and ion yields [23]. Commonly used washing solution contains different combinations of methanol, ethanol, acetone, hexane and chloroform [24,25]. It is important to point out that the composition of the washing solution and the washing protocol is crucial to the success of the following MSI investigation. Suboptimal washing solutions could cause hydrophilic peptides and low abundance analytes to be washed off. Inappropriate washing procedure could lead to delocalization of protein and peptides on tissue surface. After the tissue section is prepared, one could do either tissue profiling or tissue imaging to acquire MS information from the sample. To intentionally and quickly make comparisons between and among distinct areas on tissue without precise spatial information, tissue profiling is usually preferred. This approach normally samples 5–20 discrete spots on the tissue to give representative MS spectra in each area [26]. For better statistical confidence, the number of acquisitions needs to be adjusted for specific studies. Under longer experimental time, tissue imaging approach obtains complete chemical and spatial information over the entire tissue with higher resolution. Depending on the definition of raster step-size in specific experiment, one tissue section is divided into a number of orderly aligned pixel fractions. The instrument samples each fraction and generates MS data with corresponding location information. By combining the results from all the fractions, peptides and proteins of interest could be plotted over the x and y axes on the 2D tissue map to show the localization pattern. A matrix with the ability to absorb and transfer laser energy is required in MALDI MS to trigger desorption and ionization of the analyte. For NP analysis, common matrices include ␣-cyano-4-hydroxy-cinnamic acid (CHCA) and

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2,5-dihydroxybenzoic acid (DHB). Peptides and proteins are extracted from thin tissue sections while matrix is deposited onto the tissue surface. The composition of solvents in the matrix solution needs to be optimized for the best extraction efficiency. To preserve the localization information of analyte on the tissue surface, two matrix application methods are common: microspotting and spray coating [27]. Several well-developed techniques are available to produce homogenous thin layer deposition for high resolution MSI experiments. Airbrush, TM sprayer and thin layer chromatography sprayer are pneumatic-spray-based, while ImagePrep from Bruker Daltonics is vibrational-spray-based. Others like acoustic, piezoelectric, ink-jet printer, capillary-deposition and mist-nebulizing spray coating techniques are robotic and commercially available. Size of the matrix solution droplet could be adjusted in most of the above approaches. Smaller droplet size results in finer spatial resolution however decrease the extraction efficiency and sensitivity of detection. Spectral quality and reproducibility is improved when matrix solution is densely spotted in arrays with the tradeoff of lower spatial resolution. When migration and diffusion of the analytes become a major concern for specific tissue samples, dry matrix application could minimize the disadvantages. However, because of the lack of efficient extraction and cocrystallizationinteraction between analytes and matrix, the sensitivity of these approaches is somewhat limited [28–30].

2.3.

Tissue extraction analysis

Many neuropeptidomic analyses employ tissue homogenization followed by extraction method. In this approach, specific tissues from multiple animals are often pooled and homogenized, followed by extraction with acidic buffer and then further separated or fractionated. The resulting extract is then analyzed by MS, generally either online or offline with electrospray ionization (ESI) type of instruments, and sometimes MALDI instruments. Advantages of this approach are the feasibility with any organism regardless of the tissue size. With pooling method, significant amounts of NPs can be extracted followed by LC–MS/MS for identifications, which is suitable for MS instruments with modest sensitivity. Homogenization and extraction are performed in the presence of solvent buffers which can deactivate proteases from degrading proteins and peptides in the sample. Acidified methanol [31,32] is most commonly used in studying crustacean NPs, with other examples being acidified acetone [33,34], a combination of acidified methanol spiked with EDTA and protease inhibitors [35]. Following the homogenization and extraction, centrifugation is typically performed to eliminate cell debris. The supernatant is then concentrated and, if necessary, a C18 desalting protocol can be applied. In many cases, reversed-phase liquid chromatography (RPLC) is adapted to fractionate complex crustacean NP mixtures as to increase neuropeptidome coverage by enabling detections of low abundance NPs [36–38]. This strategy has been successfully used to characterize NPs in many crustacean species [32,36,37,39–45]. In addition, two-dimensional reversed-phase liquid chromatography (2D

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RP-LC) has been used by Hui et al. to characterize the neuropeptidome of the pericardial organ in blue crab Callinectes sapidus [46]. Alternative multidimensional chromatographic separation, which employs strong cation-exchange (SCX) chromatography followed by reversed phase liquid chromatography (RPLC) has been developed and used in studying peptides and proteins in other organisms, such as Caenorbabditis elegans and Rattus norvegicus [47,48]. Most recently, another integration of two chromatographic techniques, hydrophilic interaction liquid chromatography (HILIC) and RPLC, was introduced as a promising addition [49,50]. Another approach to enrich NP content in samples is immuno-based methodology. For example, specific antibodies that recognize consensus sequence in a peptide family can enrich the target NP family from complex sample background [45,51].

2.4.

Microdialysis

Tissue-based sample preparation coupled with mass spectrometric analysis could provide important information about peptide sequence and post-translational modifications (PTM) [46,52]. However, several disadvantages also exist, including the inability to determine whether a peptide is secreted and the high complexity of extract associated with tissue homogenization [53]. In contrast to tissue-based NP sampling technique, fluidbased method samples NPs from stimuli evoked neuronal releasate [54–57], blood or hemolymph [35,58–60]. Signaling molecules could be collected from such media, and detected to confirm its presence. It allows direct analysis of signaling neuromodulators under physiological condition manipulations and has the ability to distinguish biologically active molecules from NP precursor processing intermediates. Marder and co-workers [56] were able to detect electrically stimulated neuronal release of NPs from the allatostatin and tachykininrelated peptide families from the stomatogastric nervous system of Jonah crab, Cancer borealis. Recently, Zhong et al. [57] reported a quantitative measurement of peptide content in cell releasate in a microfluidic device with MALDI mass spectrometry. Despite the requirement for sophisticated sample handling, technical difficulties, including very small volume of releasate (␮L level), NP degradation due to the presence of peptidases, become the major issue for wide application of such techniques. Hemolymph sampling is often achieved by using a needle attached to a syringe and withdrawing certain amount of biofluid from the animal followed by NP extraction and clean-up steps. Kwok and co-workers [61] extracted and identified allatostatin-like peptides from freshwater crayfish, Procambarus clarkii. We were able to identify members of several NP families, such as RFamide, allatostatin, orcokinin, tachykinin-related peptides and crustacean cardioactive peptide from the hemolymph of Cancer borealis with MALDI MS [35]. Recently, novel members of oxytocin/vasopressin-related peptides have been detected in the cuttlefish, Sepia offininalis, by Henry et al. [62] The presence of abundant proteins in hemolymph, however, could suppress the identification of trace level NPs. Protein degradation products are believed to exist in hemolymph as nicely summarized by Fredrick and Ravichandran [63]. Moreover, the needle sampling

process could be disturbing to the animal, and cause artificial release of NPs which would result in misleading results. The limitations imposed by these methods could be overcome by employing alternative sample preparation strategies. Several sampling techniques offer the capability to collect analytes from the extracellular space, thus enable monitoring the release and dynamic changes of substances in vivo upon a defined behavior or stimuli of interest. Characterizing the concentration changes of such compounds would provide valuable insights into their potential functional role. Push–pull perfusion and microdialysis (MD) are two most commonly used in vivo sampling techniques. In the push–pull perfusion sampling process, two concentric tubes were applied while pushing liquid through one tube and pulling out sample from the other one [64,65]. It could provide a better recovery rate as a result of faster infusion flow rate compared to MD. However, the infusion tube is directly exposed to the tissue, so one of the major downsides of this technique is potential tissue damage. Shippy and co-workers [66] had worked to minimize the tissue damage problem by operating it at very low flow rates (10–50 nL/min), but longer duration is necessary to collect enough sample to be detected. This has become a more serious concern when it comes to NPs, with the estimated concentration in circulation at the pM to nM level [67]. A longer sampling time would affect the temporal resolution. MD is preferred over push–pull perfusion in the past few decades, which has been well established to measure a wide range of substances in vivo, from low-mass-substances such as electrolytes [68], amines and amino acids [69] to larger molecules such as NPs [39,70]. MD sampling was well established to collect samples from almost any human tissue but it has also been successfully applied in invertebrates, such as from the pericardial region of crustaceans [39]. Since first reported by Bito et al. [71] in 1966, MD has extended its applications in both the pharmacology and neuroscience fields. To perform MD sampling, a dialysis probe is implanted into the tissue area of interest. Perfusing liquid is pumping at a steady rate of 0.1–10 ␮L/min through the inlet and biofluid is collected from the outlet at the same time. MD sampling is based on passive diffusion, so it has minimal disturbance to the animal. The animal is alert and freely moving, which allows for long-term study [72] and the animal serves as its own control. There are several different kinds of probes designed to sample fluids from different tissue types, but they all follow similar principle [73]. The tip of the MD probe has a pre-defined molecular weight cut-off pore size which only allows molecules smaller than that to be diffused into the probe and collected according to concentration gradient. This offers a cleaner sample to work with compared to tissue extraction since large molecules such as proteins could be excluded. This feature benefits the study of neurotransmitters by real-time monitoring of the dynamic changes during behavior or upon stimulation. Circulating peptide hormones are present at extremely low concentrations, pM to nM, in extracellular space as indicated in other studies [60], and low recovery rate made the analysis of NP content in dialysis very challenging. High


sensitivity detection methods, which handle ␮L volumes, are usually coupled with MD sampling. Immunoassays, usually radioimmunoassays (RIA), were used to measure NP release collected from MD [74], but it has limited specificity due to cross reactivity, which is not suitable for complex sample analysis and novel peptide discovery. Mass spectrometry offers an attractive tool to be coupled with MD to detect NPs at pM or even lower concentrations [39,75], and it enables simultaneous identification and quantitation. The recovery rate is calculated by dividing the concentration of the substance collected in the probe over its concentration in the extracellular space. According to in vitro experiments, MD recovery rate for NPs is at 20–30% [70]. There are several factors that could affect the recovery rate such as molecular size and flow rate, which could be manipulated to improve the recovery rate. Significant improvement in recovery rate has been achieved for amines and drugs using ultraslow flow rate [76,77]. However, improving recovery could be challenging for larger molecules, like NPs. Roy and co-workers [78] have constructed a microdialysis probe using material with a larger pore size (molecular weight cutoff 50 kDa and 100 kDa) to get better recovery. But it is more suitable for sampling proteins instead of NPs whose mass range is around 500–10 kDa [79–83]. Affinity-enhanced MD, where an affinity agent is added into the perfusing liquid to increase the recovery rate, has been applied in a wide range of studies [70,81,84,85], including a recent study from our group using RFamide antibody linked magnetic nanoparticles as affinity agents to enhance recovery of RFamide-related peptides in microdialysate from Jonah crab, Cancer borealis [75]. Temporal resolution is defined as the shortest time duration over which a dynamic change event can be observed. High temporal resolution could be achieved by MD, which is critical for the functional study targeted compounds. To be able to accurately correlate the concentration of analytes with behavior or stimuli, the analysis time must be shorter than the duration of measured events. Working with high sensitivity analysis assay, temporal resolution is defined by flow rate and detection limit. If the flow rate is 1 ␮L/min, and the analyte concentration in the perfusate is around ␮M, then a few minutes or even seconds of sampling duration interval can be reached with LC–MS coupling to MD [86–88].

3.

Structural elucidation

The structures of NPs were previously determined by the combination of chromatographic separation and Edman degradation, which would require a large amount of pure sample and is very time-consuming. However, MS-based techniques enable high throughput acquisition of NP fragment information. Even without available genome information, mass spectrometry can still be used to profile and characterize the neuropeptidome of a specific organism.

3.1.

Characterization of the neuropeptidome

With its multifaceted capabilities, mass spectrometry has greatly shifted discovery of NPs from the identification of a

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single peptide to the characterization of the entire peptidome. MALDI-based mass spectrometers feature high sensitivity, tolerance to contaminants and convenient sample preparations. The ability to do in situ sequencing of NPs, mapping the spatial distribution and localization offers unique advantages compared to other MS techniques and has enabled characterization of NP sequences and distributions [89–91]. Preference to generate singly charged ions in MALDI-MS simplifies spectra interpretation [92]. MALDI MS also enables detection of some NPs that otherwise could be missed in ESI quadrupole timeof-flight (Q-TOF) mass spectrometry because of sample loss or dilution during LC separations. ESI interfaced mass spectrometers, on the other hand, are advantageous in that they can produce multiply charged ions, effectively extending the mass range of the analyzer to accommodate proteins and peptides with masses up to MDa. ESI-based MS platforms work well with pooled samples and upstream online LC separation. Due to the reduced sample complexity, multiple charging effects and resulting efficient fragmentation, the ESI source in general offers greater coverage of the peptidome. ESI is a soft ionization process so that intact molecular ions are observed. Thermally labile bio-molecules or some non-covalent interactions that are not amenable to traditional ionization methods could be well preserved in ESI [93,94]. While it is feasible to predict peptide sequences from a genome sequence and match with accurate mass, fragmentation of multiply charged ions yields more detectable fragment ions [95]. Fragmentation fingerprints are especially necessary when working with crustaceans as little genomic information is known about these organisms. Traditionally, collision-induced dissociation (CID) is employed for fragmentation. Upon collision with neutral gas molecules, increased vibrational energy redistributes over the peptide. Fragmentation ideally occurs along the backbone amide bond leading to the formation of b- and y-type daughter ions. The CID process is highly effective, or somewhat biased, for small (∼20 amino acid residues), low-charged peptides (∼+3). Additionally the fragmentation efficiency highly depends on mobile protons, yet the presence of several basic amino acids in the sequence can prevent the random protonation and therefore produce more site specific fragments rather than sequence-specific fragment ions covering the whole sequence [96]. Another drawback of CID is that several PTMs, such as phosphorylation and glycosylation, are labile to collisions and thus result in incomplete or even wrong sequence assignment. Higher-energy collision dissociation (HCD) [97] and electron transfer dissociation (ETD) [98] serve as two alternatives to CID to solve these problems. HCD employs higher energy dissociations than those used in ion trap CID, enabling a wider range of fragmentation pattern including the low-mass region diagnostic immonium ions. ETD induces fragmentation of cations by transferring electrons to them via an anion reagent. In contrast to CID, ETD can preserve labile PTMs, and has no preferred cleavage sites except for resistance to cleavage at proline, which leads to a more uniform fragment ions following a lower energy pathway and it outperforms CID in fragmenting higher charged parent ions [99] which will be discussed below. ETD generates a different set of fragment ions, that is c- and z-ions [100–102] compared to CID and HCD which generate b- and y-ions.

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Strategies combining multiple mass spectral platforms, including MALDI-TOF/TOF-MS, MALDI-FTMS and nanoLC-ESIQ-TOF MS/MS, were used to study the neuropeptidome of crustaceans [39,40,44–46,103–105]. Since peptides have varying numbers of amino acids and these fragmentationt modes work best for different size of peptides, an emerging technique combines the orthogonal data by alternating between CID and ETD (and sometimes HCD) for acquisition of multiple MS/MS spectra from each peptide [106]. This alternate mode shows great potential to provide extensive peptide sequence information. Another conditional mode is to switch between them for different types of peptides according to preset parameters (e.g. different charge states and m/z). In 2008, a data dependent decision tree (ddDT) algorithm was developed to automatically determine if CID or ETD should be utilized to fragment a specific precursor. It was tested on Saccharomyces cerevisiae and human cells with an improved sequencing success rate and more identifications [99,107]. Therefore these different mass spectrometric approaches showed complementary capabilities in expanding the crustacean neuropeptidome coverage, which is greater than any single instrument could reach.

3.2.

Structural determination of larger NPs

MS based studies on crustacean NPs generally focus on small peptides with a sequence of ∼20 amino acids. Yet there is still a portion of larger peptides, namely the crustacean hyperglycemic hormone (CHH) precursor-related peptide (CPRP) (30+ aa) and the CHH family peptides (70+ aa), including CHH, molt-inhibiting hormone (MIH), vitellogenesis-inhibiting hormone (VIH) and mandibular organ-inhibiting hormone (MOIH). CHH may have several isoforms in one or more neurosecretory organs such as the sinus glands (SG), the stomatogastric nervous system (STNS) and the pericardial organs (PO) [108] regulating many physiological processes, such as energy homeostasis involving blood glucose level and metabolism of lipids, reproduction, molting [109]. However, because of their large size which results in inefficient fragmentation, multiple post-translational modifications, such as disulfide linkages and N-terminal pyroglutamylation, it is extremely challenging to de novo sequence peptides from the CHH family. The very low abundances (usually nM-pM) and absence of genome information could further complicate this situation. Previously sequence elucidation of such large peptides was typically done with the help of Edman degradation [110,111]. Some other efforts trying to sequence them depend on truncated parts of the full length peptides present in tissue extract, which are shorter and always come with lower charge states, and that is what CID could handle [112,113]. The application of ETD greatly facilitates de novo sequencing of larger peptides like CPRP and CHH. By taking advantage of ETD, which outperforms CID in fragmenting highly charged precursors, intact CPRP was fragmented and successfully sequenced solely by mass spectrometry [42]. In the following studies concerned with CHH peptide family, ETD (or electron capture dissociation (ECD)) was used as a so-called ‘top-down’ method to gain sequence information about the intact peptide. While CID works best for small tryptic peptides, it was employed to solve the sequence from the other direction, namely ‘bottom-up’. The hybrid combination of ‘top-down’

and ‘bottom-up’ approach was reported to de novo sequence CHH by Ma et al. for the first time [43]. In this work, the intact CHH was fragmented by collision activated dissociation (CAD), infrared multiphoton dissociation (IRMPD), and ECD as multi-pronged MS/MS analysis of CHH. Merging information together from ‘top-down’ and ‘bottom-up’ approaches made the attempt to sequence CHH peptide by mass spectrometry alone succeed. This workflow was further developed by Jia et al. by including one more off-line top-down analysis to achieve increased confidence in determining each residue. Six CHH-family NPs, including two novel peptides, were fully sequenced. With the complete sequence information, the spatial distribution of CHH peptides were mapped and conformational changes caused by the N-terminal pyroglutamate were explored for the first time [52].

3.3. Chemical derivatization enhanced peptide sequencing and identification High quality MS/MS fragmentation is essential to determine peptide sequences. However, challenges exist due to possible incompleteness of MS/MS fragmentation or extensive internal fragmentations. Multiple derivatization reactions have been introduced to overcome such difficulties and resolve ambiguities in mass spectrometric sequencing, allowing easier interpretation. These derivatization reactions including methyl esterification, reductive methylation, and acetylation were utilized to facilitate de novo sequencing and resolve sequence ambiguities. Formaldehyde labeling has been developed [114] and later applied for improved sequencing of the crustacean neuropeptidome [104,115,116]. It increases the signals of a/b ion series, resulting in the confirmation of N-terminal sequence with the a1 ion, and reduces the complexity of the MS/MS spectra. Another advantage lies in that the number of lysine residues and N-terminal blockage where modifications in a peptide can be deduced from mass increments. Fig. 2 shows two examples of reductive methylation assisted de novo sequencing of neuropeptides. N,N-Dimethyl leucine (DiLeu) was reported for the first time by Xiang et al. [117] as an effective labeling reagent, offering substantially improved peptide b/y fragment ions and convincing fragment assignments. Additionally, increased basicity by DiLeu labeling reagents improves ionization efficiency compared to non-derivatized peptides. More peptides were observed. DiLeu was therefore employed to assist sequencing NPs in crustaceans [46,118]. Fig. 3 highlights an example of improved de novo sequencing and fragmentation of DiLeu labeled B-type allatostatin neuropeptide. As aspartic acid and glutamic acid can serve as proton donators when there is no proton available for fragmentation or the proton is trapped by arginine, preferential cleavage adjacent to the acidic amino acid always happen and results in incomplete fragmentation information. This preferential cleavage poses challenges in sequencing a peptide [119,120]. Cterminal derivatization with methyl esterification was proven to improve fragmentation efficiency and generate uniform cleavages along peptide backbones by limiting preferential cleavage at these acidic residues [121].


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Fig. 2 – ESI-Q-TOF MS/MS spectra of an A-type AST peptide AGLYSYGLamide (842.461+ ) before (a) and after (b) reductive methylation. In panel B, the a-, b-, and y-ion series are labeled according to the MS/MS of (CH3)2 AGLYSYGLamide (870.491+ ). (c) ESI-Q-TOF MS/MS spectra of an A-type AST peptide after reductive methylation (967.511+ ). No mass shift is observed for this peptide after the reaction, which indicates the pyroglutamylation (pyr) at the N-terminus. Adapted with permission from Ref. [14]. Copyright (2009) American Chemical Society.

In addition to the reactions described above, there are still other derivatization strategies reported to be beneficial for de novo sequencing, either by reacting with N-terminus [122,123] or C-terminus [124,125], not yet applied to crustaceans. It is highly possible to use them for crustacean neuropeptidomic studies.

3.4. Database searching and software assisted NP identification To identify peptides present in a sample, MS/MS data can be searched against a sequence database or a database consisting of predicted sequences from an organism’s genome. Since

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though the crustacean genome has not fully been sequenced [44,135].

4.

Fig. 3 – ESI QTOF MS2 fragmentation (a) before and (b) after DiLeu labeling of B-type allatostatin NP (GNWNKFQGSW-NH2 ). Adapted with permission from Ref. [117]. Copyright (2010) American Chemical Society.

there is little known genomic information for crustacean species, direct de novo sequencing of MS/MS data is often needed, which follows peak centroiding, charge deconvolution and deisotoping. Sometimes a database exists and an agreement between database search results and de novo sequencing can provide cross-validation. Several platforms are developed to perform de novo sequencing, either manually or automatically. Several examples generally used are Lutefisk ([126], http://www.hairyfatguy.com/lutefisk/), PepSeq (packaged with Waters’ MassLynx software http://www. waters.com), PepNovo ([127], http://proteomics.ucsd.edu/ Software/PepNovo.html), Mascot Distiller (http://www. and PEAKS ([55], matrixscience.com/distiller.html), http://www.bioinfor.com/peaks/features/denovo.html), and there is still increasing interest in developing new algorithms in recent years [128–131]. De novo sequencing greatly helps with interpreting MS/MS data, but it is hard to ignore sequencing errors that might occur due to, for example, isobaric effect or low mass accuracy. The candidate sequences generated by de novo sequencing can then be evaluated for homology with previously known peptides via BLAST homology search (http://www.ncbi.nlm.nih.gov/BLAST/). Homology search may provide an evolutionary view concerning the peptide of interest among different species. BLAST still does not consider de novo sequencing errors that might cause sequence mismatches. As one step ahead, SPIDER, MEME and OpenSea use optimized methods which are more tolerant to de novo sequencing errors than BLAST and this feature makes them generate correct sequences more easily [132–134]. In addition to comparing proteins or peptides between species, it is now possible to use peptides from one species to search against an expressed sequence tag (EST) database of another species of interest, predicting putative peptides encoding ESTs which could be leads for further mass spectrometric validations. It has been effective in discovering NPs even

Distribution analysis by MS imaging

The functions of different NPs are highly related to their localizations. The application of MALDI MSI, first demonstrated by Caprioli [136,137], greatly facilitates the localization of NPs in an entire tissue slices. Mass spectra are acquired according to a predefined grid across the sample while a coordinate system is superimposed on the tissue. After a series of spectra is collected, hundreds of ions can be assigned to different coordinates, therefore relating their identities and potential functions to locations. Our group pioneered in the MSI characterization of crustacean using various MS platforms on different species. The goal of the MSI studies is to reveal the relationship between the biological function and the location of biomolecules, such as lipids, NPs and proteins. DeKeyser et al. [17] found more than 30 NPs from 10 different families using MALDI-TOF/TOF MS instrument to perform MSI study on both pericardial organ (PO) and brain of the Jonah crab, Cancer borealis. Selected NPs were also in situ fragmented via post-source decay (PSD) and collisional-induced dissociation (CID) to confidently characterize their identities. NPs from the same family presented similar spatial localization respectively while several exceptions existed in RFamide-family and orcokinin-family. This study also reported the relative distribution of NP families and provided useful insights into the positive correlation between biological location and function. For example, NPs from ASTA and AST-B family were known to have inhibitory effects on the pyloric rhythm in the stomach [138,139]. Despite the unique chemical structures of these two NP families, MSI study showed remarkable overlapping of their localization. Chen et al. [140] mapped the distribution of several major NP families in the brain of the lobster Homarus americanus using both MALDI TOF/TOF and MALDI LTQ Orbitrap MS. The latter platform provided high mass resolution and accuracy for the detection of NPs with unambiguous assignment of the ion signals. By combining the distribution information from MSI and previous biological understanding of the structure of nervous system, potential functional roles of these NPs were elucidated. MSI results showed that both CabTRP 1a and Val-SIFamide were highly concentrated in olfactory lobe (OL) and accessory lobe (AL) of the brain. While OL and AL are the two most important neuropils in the olfactory system of lobster [141], the finding suggested the potential regulatory roles of CabTRP 1a and Val-SIFamide in the olfactory system. Orcokinins were localized in the area of antenna II neuropil (AnN) and lateral antennular neuropil (LAN) with higher signal intensities, suggesting their function in the tactile sensory. Another tachykinin-related novel NP CalsTRP was detected in a different crustacean system, C. sapidus, by Hui et al. [142] MSI study from MALDI TOF/TOF suggested the colocalization of CalsTRP with the previously identified CabTRP 1a in the brain of the animals. Comparative distribution and expression level studies were performed between fed and unfed animals. The up-regulation and colocalization of both CabTRP 1a and CalsTRP indicated the same preprotachykinin they were encoded


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Fig. 4 – Reconstructed 3D images of the distribution of (a) CabTRP 1a and (b) lipid PC 38:6 in the brain of Cancer borealis by MALDI MSI using (a) regular matrix coating and (b) dry matrix spraying which favors the detection of lipids. Adapted with permission from Ref. [18].

by and supported their functions in the gastric mill and pyloric rhythm. For a complex tissue like the brain of crustacean, 2D MS imaging is not sufficient to represent the global distribution of bio-functional compounds inside its heterogeneous structure consisting of various neuropils and neuronal clusters. Chen et al. [18] were able to build up a 3D map of NP distribution in the brain of a Cancer borealis using 2D information from serial sections. More than 20 NPs from 8 families were reconstructed throughout the brain. A comparison of the 3D distribution between NPs and phospholipids reflected their distinct localization pattern as shown in Fig. 4. Findings from this study provided another dimension beyond 2D MSI to display more in-depth information of the molecular distribution in crustacean tissue. Readers are referred to a more comprehensive review of 3D MSI for detailed development in the area [143]. As a result of the development of instrumentation, researchers were able to look into neuronal structures that are complex yet with minute size. Ye et al. [31] studied the distribution of NPs in the stomatogastric nervous system of C. sapidus using both MALDI TOF/TOF and MALDI FT-ICR, where the former platform provides high spatial resolution and the latter provides high mass spectral resolution. With these sensitive, accurate and high-throughput platforms, it was possible to unambiguously discover novel NPs and map their biological distribution at trace level simultaneously. In this study, 55 NPs from 10 families were characterized from major ganglia in C. sapidus stomatogastric nervous system for the first time. Representative results of the localization of NPs inside the stomatogastric ganglion (STG) were shown in Fig. 5. Their comprehensive distribution throughout the ganglia and connecting nerves provided useful insights about potential biological functions as well.

5.

Quantitation of NPs

Another aspect in determining NP functions is to assess their quantitative information in response to a physiological change.

5.1.

Crustacean NP MS quantitation

The crustacean nervous system has long served as an excellent model system for novel NP discovery and neuronal regulation of physiological studies. A key advantage of using the crustacean model system is that the role of specific NPs in neuromodulation can be assessed at the neural circuit and single cell level. Accurate and reliable quantitative measurement of NPs in different biological samples is an important way to help address functionality related questions [144]. Reviews by Keller [8] and Christie et al. [3] nicely summarized different crustacean NP families, including their general structures, and their bioactivities. However, most MS-based quantitation strategies are for protein level quantitation, which can be categorized into labelfree and stable-isotope-labeling approaches, where absolute or relative quantitation could be accomplished upon different demands. Despite the rapid growth in protein quantitation strategies, quantitative studies on crustacean NPs, on the other hand, still need to be further explored. The study on quantitation of crustacean NPs is very limited. Our lab has established a multi-faceted mass spectrometrybased platform to study crustacean NPs, and has contributed several successful methodologies and generated new information about neuropeptide families and their organization [43,44,52,90,113,115,117,121]. Isotopic formaldehyde labeling has been used in NP quantitation by N-terminal dimethylation or dimethylation of the lysine side-chain. It has been proven to enhance peptide fragmentation with the production of intensive immonium ions after tandem mass fragmentation by Fu and Li [145]. By labeling NPs with light or heavy formaldehyde, a 28 Da or 32 Da mass shift will be generated. The 4 Da mass difference between light and heavy labeled peptides allows the direct comparison of same peptide in different samples. Hui et al. [146] used this method to identify a novel feeding related tachykinin-related peptide. Wang and co-workers also measured the salinity stress induced NP changes in two crab species using formaldehyde labeling coupled with capillary electrophoresis (CE)-MS [118]. Another in-house developed isobaric labeling strategy, DiLeu, by Xiang et al. [117], allows the simultaneous

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Fig. 5 – Representative MSI results of the NPs distributions in Callinectes sapidus STG by MALDI TOF/TOF. (a) An optical image of the STG subjected to subsequent IMS preparation. Nine NPs form five different families were shown above. AST-Bs: (b) AGWSSMRGAWa (m/z 1107.52), (c) SGDWSSLRGAWa (m/z 1220.58), and (d) VPNDWAHFRGSWa (m/z 1470.70). SIFamide: SIFamide GYRKPPFNGSIFa (m/z 1381.74). RFamides: (f) NRNFLRFa (m/z 965.54), (g) SQPSKNYLRFa (m/z 1238.66), and (h) pQDLDHVFLRFa (m/z 1271.64). CabTRP 1a: APSGFLGMRa (m/z 934.49). Orcokinin: NFDEIDRSSFGFN (m/z 1547.68). For comparison, the distribution of (k) a lipid PC (38:6) (m/z 806.57) is shown. (l) is an overlaid image of (c), (h), and (k), displayed in green, red, and blue, respectively. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.) Adapted with permission from Ref. [31].

comparison of 4 biological samples with comparable if not better performance comparing with the commercially available isobaric tag, iTRAQ, with a much reduced cost per experiment. It has been proven to provide accurate and reliable quantitative comparison in proteomic studies, as shown by Jiang et al. [89] in the study of neuropeptidomic expression changes in the stamotagastric ganglion at multiple development stages of the lobster H. americanus. Label-free quantitative strategies can also be used in crustacean NP studies. The chromatographic peak area [147,148] or ion intensity can be used to represent the concentrations of corresponding peptides. The assumption behind this strategy is that the concentration of the peptide of interest is linearly proportional to the area under the curve (AUC) measured. Schmerberg and Li [70] have characterized the concentration changes of 7 NPs upon feeding by comparing the corresponding area under the curve of extracted ion chromatogram in Jonah crabs, Cancer borealis. An internal standard was added to normalize the possible instrumental variations. Reproducible and accurate measurements of analytes across different samples could be tricky for various reasons. Despite the variation in biological samples, some technical variations need to be taken into careful consideration. Only

the same peptide-ion pairs could be compared between different samples, which are assigned based on retention time and mass accuracy. Not only could the retention time and mass accuracy be variable among different LC–MS/MS runs, but other factors such as signal intensity and background interference could affect the accuracy of quantitative comparison [149,150]. Different data normalization strategies could be applied to improve quantitation accuracy. Spectral counting [151,152] is another well-established label-free quantitative strategy for relative quantitation. It is based on the observation that the more abundant the protein, the more abundant its peptides, which could generate more MS/MS spectra upon fragmentation. As demonstrated by Liu et al. [153], spectral counting exhibited a good linear correlation within the dynamic range of 2 orders of magnitude in yeast. One disadvantage is the suppression of lower abundance proteins from high abundance proteins, which could lead to poor performance for low-abundance proteins. Since Mann and co-workers [154] described the protein quantitation using SILAC, it has been a popular quantitative proteomics technique. The incorporation of isotopes relies on providing isotopically labeled essential amino acids in growth media. Recently, NeuCode SILAC, described by the Coon group


[155,156], was shown to reduce precursor ion interference on the MS1 level and allow high-plexed protein quantitation. Stable isotopic labeling strategies allow simultaneous comparison of multiple samples by introducing a mass difference tag to the protein or peptide. The labeled proteins/peptides will exhibit the same or similar chromatographic characteristics with unlabeled samples. In general, different tags would have similar composition: a reporter group, a balance group and a reactive group [157,158]. Each reporter has its unique m/z, where the balance group is designed to balance out the mass difference between each reporter and reactive group and aids the labeling reaction after which it gets cleaved. The same labeled peptide across different samples will have the same mass shift. The quantitative comparison can be realized after MS/MS fragmentation when each specific reporter gets exposed and detected with the mass analyzer. Quantitation is achieved at the MS/MS level. Isotope Coded Affinity Tag (ICAT), introduced by Gygi and Aebersold in 1999 [159], was cysteine specific with two different forms of reporter groups which are 8 Da apart. In 2003, a newer version of ICAT, cICAT was developed to reduce the deuterium effect and to resolve the possible confusion caused by double labeling or oxidation [160,161]. The original 4-plex isobaric Tags for Relative and Absolute Quantification (iTRAQ) technique was published in 2004 by Ross et al. [162]. The advantages of iTRAQ over ICAT are as follows. First, iTRAQ has an amine-reactive group which targets the N-terminus of peptide or protein, so it has a wider application range than ICAT. Second, it overcomes the limitation of binary quantification by offering multiplexing capability. Being one of the only two commercially available isobaric labeling tags, iTRAQ gains its popularity quickly and has shown its value in multiple areas. Now with 8-plex iTRAQ [163,164], the capability and analytical throughput of such isotopic tags has been improved greatly. Mass differential Tags for Relative and Absolute Quantification (mTRAQ) is a new amine-reactive labeling tag, which is an extension of the iTRAQ technique. After labeling, for arginine C-terminated peptides, precursor mass will shift 0, 4 and 8 Da, respectively. For C-terminal lysine peptides, 0, 8 and 16 Da mass difference will be generated. It is designed for biomarker validation serving as an alternative strategy to isotopic synthetic peptide standards in MRM assays [165–167]. Tandem mass tags (TMT) are commercially available from Thermo Scientific; two-plex and six-plex sets are available. Iodo-TMT is also available for targeting cysteine containing proteins/peptides. These quantitation methods can be readily extended to neuropeptide quantitation with the exception that Iodo-TMT would have limited utility only for Cyscontaining NPs.

5.2.

Isobaric labeling quantitation on MS3 level

In isobaric labeling strategy, interference from cofragmentation of targeted-peptide and neighboring isobaric ions could compromise the accuracy and precision of quantitation results [168–170]. Recently, Ting et al. [171] reported on eliminating interference at the MS3 level where an additional isolation and fragmentation event was performed. Another gas-phase purification strategy described by Wenger et al.

163

[172] could remove interfering ions with different charge states by integrating proton-transfer ion–ion reactions (PTR). However, the cost with these methods is the data acquisition speed and sensitivity due to sample loss at every fragmentation event. Another method to minimize interference and quantify sample difference at the MS2 level was proposed by Wuhr et al. [173] using isotopic labeling tag fragment ion clusters instead of reporters. Although more accurate quantitation could be achieved with this method, fragmentation efficiency is still a big concern.

5.3.

Neutron-encoded labels

Developed by Herbert et al. [174], neutron-encoded labeling technique quantifies proteins by taking advantage of high resolution and high mass accuracy mass spectrometers. It is based on the subtle mass differences in neutron-binding energy between stable isotopes and allows high-plex MS1 level proteomic quantitation. NeuCode has been combined with SILAC and also been incorporated in a novel set of aminereactive chemical labeling tags [155,156,175]. NeuCode based methods, however, require the use of mass spectrometer with a resolving power of more than 200,000 because the mass difference generated by NeuCode tags is only at mDa level.

5.4.

Data-independent acquisition (DIA)

In a typical MS/MS experiment, where data-dependent acquisition (DDA) is often utilized, precursor ion survey scans (MS) and top N most intensive fragment ions scans (MS/MS) are cycled to result in a final chromatogram. The balance between MS and MS/MS scans need to be optimized in order to achieve maximal peptide identifications and better quantitation accuracy. Alternatively, data-independent acquisition (DIA) could be utilized, where all ions are fragmented without choosing specific precursor ions. DIA has been available in multiple instruments and gained its popularity in quantitative studies. This has been termed as MSE in Waters Q-TOF instrument, which works by alternating low and high collision energies, while in Thermo Orbitraps, it is named as all-ion fragmentation (AIF), and SWATH in AB ScieX instruments.

5.5.

MRM based quantitation

Quantitation of targeted analytes with an isotopically labeled analog as internal standard has been used in LC–MS since 1987 [176,177]. With advances in mass spectrometry, selected reaction monitoring (SRM) or multiple reactions monitoring (MRM) based quantification technology became the gold standard in targeted quantitative proteomic studies. Specific peptides for targeted protein quantification were selected for fragmentation after protein digestion was carried out. Characteristic band y-ions were generated in MS/MS analysis for the peptide, respectively. The intact peptide ion (precursor) and its specific b-/y-ion pairs are called transitions. MRM experiments monitor such selected transitions and compare parallel with corresponding ion pairs from the isotopically labeled analog to give specific and highly sensitive quantitative information. Spiked-in isotopic peptide standards could help differentiate targeted peptides from background interference and offer

164


more accurate quantitative information. Targeted peptides would co-elute with heavy peptide analogs, and share similar fragmentation pattern with a mass shift in precursor and fragment ions. Such mass difference can confirm the identity of targeted peptides, especially when other co-eluting transitions exist. The key step for a successful MRM quantitation assay is the selection of target peptides. Prior knowledge of proteins of interest is required for such selection. The selected peptides have to be unique for the proteins of interest and proven to be detectable by MS/MS from previous experiments. Peptide fragmentation conditions need to be optimized to ensure the performance of the assay. Transitions can be selected based on previous studies, predicted fragments from computational simulation, or analysis of synthetic peptide standards. Introduced firstly by Gygi et al. [178] in 2003, MRM based techniques have been applied in absolute quantitation (AQUA) of proteins. The protein’s concentration is determined by measuring its corresponding tryptic peptide concentrations. In this method, absolute quantitation is reached by adding a known amount of isotopically labeled peptide standard into the sample to monitor the quantity changes. Numerous protein quantitation studies [179] have been published based on the general AQUA protocol [180]. One limitation with the triple quadrupole instruments is the low resolution measurements in which interference may become a major concern for complex mixtures. A new targeted proteomics quantitation strategy, parallel reaction monitoring (PRM), is proposed to restrict interference based on using a newer high resolution quadrupole-Orbitrap hybrid MS platform [181,182]. It allows the parallel identification and quantification of proteins by replacing the third quadrupole in a triple quadrupole instrument with a high resolution, high mass accuracy orbitrap mass analyzer. Preliminary results suggest that PRM could provide comparable quantitative performance to MRM assays on triple quadrupole instruments, yet offers fast scanning and high resolution mass spectra to aid in specifically extracting signals of targeted peptides.

6.

Summary

The field of peptidomics has gone far beyond just peptide identification. The ability to accurately and reliably measure changing protein/peptide concentrations in biological samples under different conditions is in high demand. The development of quantitation techniques could help address important biological questions. Both label-free and isotopic labeling approaches have been widely utilized to achieve absolute or relative quantitation and their performances have been compared [183]. The label-free approach could bypass the isobaric tags, which are normally very expensive, and there is no limitation on the number of samples that could be compared. However, due to the nature of sample handling, and mass spectrometry instrumentation, variations and interference are the main obstacles to gain accurate and reproducible quantitation [184–186]. Isotopic labeling strategies, however, are often considered more accurate. Nonetheless, an additional labeling step is needed and the labeling efficiency could

be a concern. Due to the availability of isobaric labeling tags, the number of samples that can be analyzed in one experiment is limited. Some labeling strategies are limited to only certain types of samples. Significant advances in mass spectrometry instrumentation and associated methodologies have greatly accelerated the progress in the field of crustacean neuropeptidomics. More than twenty NP families, with different numbers of NPs ranging from several to hundreds, have been discovered and assigned to biological functions. The MS-based technique possesses high speed, high sensitivity, increasing accuracy and impressive chemical information at the same time. With chemical, spatial and temporal information, a more complete picture of peptidergic signaling can be generated for various model organisms under a variety of physiological processes. However, much development is still needed for every step of the peptidomics pipeline, ranging from sample preparation, structural elucidation, to spatial localization and quantitation, to address the remaining challenges of neuropeptidomic analysis and to fully understand the diverse roles of NPs. At the same time, the evolving new generations of MS instrumentation and bioinformatics tools are also expected to propel the advancement of this highly dynamic and rapidly growing field of research.

Acknowledgments Preparation of this manuscript is supported in part by National Science Foundation (CHE-0957784) and National Institutes of Health through grant 1R01DK071801. L.L. acknowledges an H. I. Romnes Faculty Fellowship.

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