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I was wondering if both all b and y ions are required to determine to order of the amio acids in a peptide.
In my opinion knowing only ALL B ions or ALL y-ions is enough to determine the sequence of the amino acids in a peptide. I was also wondering how these b and y ions are differentiated in a spectrum?
In an MS/MS spectrum, difference between the successive peaks of a b or y ion series allows one to determine the amino acids making the series/peptide. Either one of them should be enough to give you the sequence. However, an MS/MS spectrum obtained from the mass spec instrument doesnt tell fragment types. Therefore it takes some expertise and tricks to spot y or b ion series. For example: if you are analysing a sample digested by trypsin, your C-term residue will either be K or R. So you can look for a Y1 ion if there is 147 indicating K or 175 indicating R. Also, Y ions tend to be highest intensity peaks in a spectrum. For more helpful tips on this there is an excellent tutorial : http://www.ionsource.com/tutorial/DeNovo/DeNovoTOC.htm.
Also, in practice you seldom get all of the b or y ion peaks and there are often missing peaks. For this reason it is useful to have both b and y ions series so that gaps in one can be filled by the other. This is not only useful when you are dealing with denovo sequencing but also in a more typical shotgun proteomics experiment. In a typical shotgun proteomics experiment one searches their mass spec data with peptide search engines. These are software which use a protein sequence database which is in silico digested, based on the specificity of the protease used in the experiment, and from the resulting peptide sequences search engines make a library of predicted MS/MS spectra (this is done by fragmenting along the peptide backbone and listing all possible b and y ions). Then these predicted spectra are matched with the observed spectra to predict the peptide sequences that could result in the observed spectra. Again, not all of the peaks present in a predicted spectra will be found in an observed spectra. So it is best to have ions from both b and y ion series. More ions matched between the observed and predicted spectra, better is the score and confidence in identification.
Identification of membrane proteins by tandem mass spectrometry of protein ions
The most common way of identifying proteins in proteomic analyses is to use short segments of sequence (“tags”) determined by mass spectrometric analysis of proteolytic fragments. The approach is effective with globular proteins and with membrane proteins with significant polar segments between membrane-spanning α-helices, but it is ineffective with other hydrophobic proteins where protease cleavage sites are either infrequent or absent. By developing methods to purify hydrophobic proteins in organic solvents and by fragmenting ions of these proteins by collision induced dissociation with argon, we have shown that partial sequences of many membrane proteins can be deduced easily by manual inspection. The spectra from small proteolipids (1–4 transmembrane α-helices) are dominated usually by fragment ions arising from internal amide cleavages, from which internal sequences can be obtained, whereas the spectra from larger membrane proteins (5–18 transmembrane α-helices) often contain fragment ions from N- and/or C-terminal parts yielding sequences in those regions. With these techniques, we have, for example, identified an abundant protein of unknown function from inner membranes of mitochondria that to our knowledge has escaped detection in proteomic studies, and we have produced sequences from 10 of 13 proteins encoded in mitochondrial DNA. They include the ND6 subunit of complex I, the last of its 45 subunits to be analyzed. The procedures have the potential to be developed further, for example by using newly introduced methods for protein ion dissociation to induce fragmentation of internal regions of large membrane proteins, which may remain partially folded in the gas phase.
One-third of proteins encoded in genomes are hydrophobic membrane proteins, and their analysis by mass spectrometric methods is more difficult than the analysis of hydrophilic proteins. Many of the difficulties arise from their hydrophobicity and from the associated lack of procedures for purifying membrane proteins in a suitable form for mass spectrometric analysis. Usually, detergents are used to extract and purify membrane proteins, but they are incompatible with the protein ionization methods used in MS, and so they have to be removed from the purified protein (often by chromatography in organic solvents) before analysis can be undertaken (1–3). An alternative approach is to extract and fractionate the membrane proteins directly in organic solvents (3–5).
The measurement of the mass of a protein allows the presence but not the location of any posttranslational modifications to be detected, but it does not provide a reliable means of identifying a protein in sequence data-bases, as required in proteomic analyses. Usually, short segments of protein sequence (sequence tags), obtained by mass spectrometric analysis of proteolytic peptides, are used for this purpose (6). This method provides a highly effective means of generating partial sequences from globular proteins, and from membrane spanning proteins with significant polar segments between the helices and at their termini, but it is often ineffective with the more hydrophobic membrane proteins, where protease cleavage sites can be either rare or be completely absent. Another approach known as “top down” sequencing, that has been applied to globular proteins, is to fragment intact protein ions by collision induced dissociation (CID) with argon, and to deduce partial sequences from the fragment ion spectra (7–9). These spectra are complex, and often their interpretation requires the use of high resolution instruments, such as ion cyclotron resonance and linear ion trap mass spectrometers with Fourier transform capabilities, to separate the fragment ion isotopes and to determine the number of associated charges from the isotope spacings (9, 10). The expense of this instrumentation limits access to these techniques.
The top-down sequencing approach has been applied also to a few small membrane proteins in the molecular mass range 3–8 kDa, namely subunits VIIc and VIII of bovine mitochondrial cytochrome oxidase (4), subunit c of ATP synthase (11–13), and subunits of cytochrome b 6f from chloroplasts and cyanobacteria (3). The tandem mass spectra were produced by fragmentation of protein ions by CID in instruments with quadrupole or time-of-flight analyzers. They were rather simple and could be interpreted manually. However, because of the limited access to a range of membrane proteins purified in a form that is compatible with the generation of intact ion spectra, until now, no systematic study of tandem mass analysis of membrane proteins has been carried out. As described here, we have improved the procedures for solubilizing and fractionating hydrophobic membrane proteins by chromatography. We have extended the measurement of the molecular masses of membrane proteins by fragmenting the intact protein ions by CID. We have shown that, in contrast to the complex fragment ion spectra that arise from CID of globular proteins (7), the fragment ion spectra of many membrane proteins, containing from 1 to 18 transmembrane α-helices (TMHs), are relatively simple and are readily interpretable by manual inspection. Thus, they provide suitable tags for identifying unknown membrane proteins.
Top-down and bottom-up mass spectrometry methods can generate gas phase fragments and use these to identify proteins. Top-down methods, in addition, can provide the mass of the protein itself and therefore additional structural information. Despite the conceptual advantage of top-down methods, the market share advantage belongs to bottom-up methods as a result of their more robust sample preparation, fragmentation, and data processing methods. Here we report improved fragmentation and data processing methods for top-down mass spectrometry. Specifically we report the use of funnel-skimmer dissociation, a variation of nozzle-skimmer dissociation, and compare its performance with electron capture dissociation. We also debut BIG Mascot, an extended version of Mascot with incorporated top-down MS 2 search ability and the first search engine that can perform both bottom-up and top-down searches. Using BIG Mascot, we demonstrated the ability to identify proteins 1) using only intact protein MS 1 , 2) using only MS 2 , and 3) using the combination of MS 1 and MS 2 . We correctly identified proteins with a wide range of masses, including 13 amyotrophic lateral sclerosis-associated variants of the protein Cu/Zn-superoxide dismutase, and extended the upper mass limit of top-down protein identification to 669 kDa by identifying thyroglobulin.
Ionization and detection of intact proteins have been possible for 20 years (1, 2). This breakthrough, combined with the development of methods of intact protein fragmentation (3𠄹) and database searching (10), gave rise to top-down mass spectrometric approaches of protein analysis (13). Although top-down proteomics excels in the area of protein variant and post-translational modification (PTM) 1 characterization (14, 20, 21), comprehensive protein identification is an area for improvement (22). Top-down proteomics is hampered by the lack of a sample preparation technique as generally applicable as in-gel digestion (25), the lack of a fragmentation technique as robust as collisionally activated dissociation (CAD) of peptides (26), and the lack of compatibility of top-down MS data with all popular bottom-up software (27), including Mascot (28), Sequest (29), Protein Prospector (30), and Peptide Search (31). Recent improvements in these areas include the following: 1) separation techniques compatible with top-down analysis (18, 32) 2) fragmentation techniques, including nozzle-skimmer dissociation (3, 33), electron transfer dissociation (7, 8), prefolding dissociation (9), and activated ion electron capture dissociation (ECD) (5), which extended the protein upper mass limit to 229 kDa for top-down methods (9) and 3) a search engine as advanced as any bottom-up software ProSight PTM (11, 12, 36) was developed and integrated with a comprehensive MS database within the Xcalibur software suite (Thermo Finnigan, San José, CA).
Our objectives here are (i) to help develop an extended version of Mascot that incorporates top-down MS 2 search ability and (ii) to infer its search sensitivity and selectivity. Here we present BIG Mascot, the first general use search engine that can perform both bottom-up and top-down MS 2 searches. Mascot has been one of the most widely used database search engines because of its probability-based scoring method (28), its superior performance (37, 38), and its fast operating algorithm. However, the applicability of Mascot to top-down work flows is severely limited as the commercially available version has a precursor ion mass limit of 16 kDa. Using a version of Mascot referred to as BIG Mascot that was modified to allow precursor ions of up to 110 kDa, we demonstrate that either intact protein MS 1 or MS 2 by themselves yield sufficient information for identification of many proteins. To identify variants of a single protein, including mutations or PTMs, however, the masses of both the intact protein and the fragments are required. Finally by identifying the protein thyroglobulin using a single step analysis, we extend the mass of intact protein identification beyond the previous limit of 229 kDa (9) to 669 kDa.
Are both B and Y ions required to determine the sequence of a protein by mass spectrometry? - Biology
a Department of Chemistry, University of Texas at Austin, Austin, TX 78712, USA
E-mail: [email protected]
b Division of Chemical Biology and Medicinal Chemistry, College of Pharmacy, University of Texas at Austin, Austin, TX 78712, USA
E-mail: [email protected]
c Department of Chemistry and Biochemistry, Miami University, Oxford, OH 45056, USA
d Department of Chemistry, Wesleyan University, Middletown, CT 06459, USA
We use mass spectrometry (MS), under denaturing and non-denaturing solution conditions, along with ultraviolet photodissociation (UVPD) to characterize structural variations in New Delhi metallo-β-lactamase (NDM) upon perturbation by ligands or mutation. Mapping changes in the abundances and distributions of fragment ions enables sensitive detection of structural alterations throughout the protein. Binding of three covalent inhibitors was characterized: a pentafluorphenyl ester, an O-aryloxycarbonyl hydroxamate, and ebselen. The first two inhibitors modify Lys211 and maintain dizinc binding, although the pentafluorophenyl ester is not selective (Lys214 and Lys216 are also modified). Ebselen reacts with the sole Cys (Cys208) and ejects Zn2 from the active site. For each inhibitor, native UVPD-MS enabled simultaneous detection of the closing of a substrate-binding beta-hairpin loop, identification of covalently-modified residue(s), reporting of the metalation state of the enzyme, and in the case of ebselen, observation of the induction of partial disorder in the C-terminus of the protein. Owing to the ability of native UVPD-MS to track structural changes and metalation state with high sensitivity, we further used this method to evaluate the impact of mutations found in NDM clinical variants. Changes introduced by NDM-4 (M154L) and NDM-6 (A233V) are revealed to propagate through separate networks of interactions to direct zinc ligands, and the combination of these two mutations in NDM-15 (M154L, A233V) results in additive as well as additional structural changes. Insight from UVPD-MS helps to elucidate how distant mutations impact zinc affinity in the evolution of this antibiotic resistance determinant. UVPD-MS is a powerful tool capable of simultaneous reporting of ligand binding, conformational changes and metalation state of NDM, revealing structural aspects of ligand recognition and clinical variants that have proven difficult to probe.
RESULTS AND DISCUSSION
The mobile proton hypothesis states that protonation of peptides during gas-phase ionization is mainly governed by the basic sites of the analyte. Hence, a typical tryptic peptide harboring a single basic amino acid is doubly charged (with the second proton secured on the primary amine of the N-terminus). We directly infused chemically synthesized peptide EPGLCTWQSLR into a hybrid ion trap-Orbitrap mass spectrometer using ESI-MS and observed a doubly charged precursor, as seen in Fig. 1(A). In accordance with the mobile proton hypothesis, adding an additional Arg to the N-terminus of a tryptic peptide can result in doubly and triply charged precursors. Formation of the [M+2H + ] 2+ ion is rationalized by sequestering protons on both basic amino acids, while the [M+3H + ] 3+ ion is rationalized by further securing a proton via the primary amine of the N-terminus. Indeed, directly infusing REPGLCTWQSLR into a hybrid ion trap-Orbitrap mass spectrometer results in [M+2H + ] 2+ and [M+3H + ] 3+ ions, as seen in Fig. 1(B). Furthermore, the triply charged precursor ion could be selected for subsequent ETD. Despite there being a Pro residue in the peptide sequence, a complete c-fragment ion ladder was observed in the resulting MS/MS spectrum together with a complete y-fragment ion ladder and several other product ions (see Fig. 1(C)). Hence, arginylation allows for ETD fragmentation of relatively short peptides and the resulting MS/MS spectra contain at least 2× sequence coverage for unambiguous assignment of peptides. Based on these results we decided to further pursue the application of arginylation for proteomics and to determine the robustness of the yATE1 enzyme.
Enzyme kinetics of yATE1
Arginylation is an enzymatic reaction that involves two substrates: aminoacylated tRNA Arg and (poly-)peptides with N-terminal acidic amino acids (see Fig. 2(A)). 10 To determine the Michaelis-Menten rate constants of Saccharomyces cerevisiae arginyl-tRNA protein transferase 1 (yATE1), we used a multiplexed quantitative method based on matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOFMS) and ethyl(-D5)-labelled peptide standards (short pentadeutero method for the remainder of the manuscript). 11, 13, 14 As MALDI-MS is inherently non-quantitative, i.e. the signal observed from an analyte is poorly related to the amount of analyte in the sample, quantification of the pentadeutero method is based on differential labelling of substrate and product peptides containing an internal Cys. 13, 14 The substrate peptide EPGLCTWQSLR was labelled using bromoethane-D5, resulting in a deuterated S-ethylcysteine (heavy substrate, m/z 1323). The product peptide with the sequence REPGLCTWQSLR was labelled using isotopically light bromoethane and served as a reference standard (light product, m/z 1474). Both the heavy substrate and the light product were added to the arginylation reaction, and aliquots were taken as a function of time, quenched with TFA and directly spotted onto a t-plate for mass spectral analysis. Due to the low complexity peptide mixture with known substrate and product peptide m/z values, no chromatographic separation was required prior to MALDI spotting. Figure 2(B) shows an example of the primary MALDI data: the light product (m/z 1474) is kept constant at 1, while the heavy product (m/z 1479) increases as a function of time.
To determine Michaelis-Menten rate constants for yATE1, the arginylation reaction was carried out in triplicate with an in situ aminoacylation reaction to regenerate aminoacylated Arg-tRNA Arg (see Experimental section for details). The peptide product appearance measurements 15 were carried out over a range of peptide substrate concentrations ranging from 4.48 μM to 51.5 μM, while the yATE1 and tRNA Arg concentrations were kept constant. The product appearance, plotted as a function of initial heavy substrate concentration, and the initial rate constants were determined. The end point of the initial linear velocity was determined to be 6 min. Prism (GraphPad Software, La Jolla, CA, USA) was used to plot all kinetic curves and calculate kinetic parameters. The vmax was calculated to be 2.2 μM · min –1 , Km = 39.3 μM and kcat = 16.1 min –1 in our initial yATE1 purification (see Table 1 and Fig. 2(C)). In this experiment 220 pmol of EPGLCTWQSLR (MW 1289.49) are converted per minute or 2 µg per 7 min. As a typical amount of peptide mixture analyzed per LC/MS experiment is 2–5 µg, we conclude that these enzymatic parameters are suitable to further pursue the application of arginylation at a scale that is compatible with common proteomic workflows.
|Substrate peptide concentration (μM)||Initial rate (μM min –1 )||Rate constants|
Extending arginylation to 13 chemically synthesized and calibrated peptides
The pentadeutero method is based on MS1 m/z value measurements using MALDI-MS and requires internal Cys for labelling. For more complex peptide mixtures, MS1 m/z values are not sufficient to unequivocally identify peptide substrates and products. Furthermore, not all peptides contain an internal Cys. Hence, to apply arginylation beyond a single peptide substrate, we chose 13 chemically synthesized and amino acid analysis calibrated peptides with N-terminal aspartate or glutamate. These 13 substrate peptides were arginylated in varying concentrations ranging from 5 to 405 pmol per enzyme reaction and a single 90 min end point was analyzed by ESI-LC/MS (see Experimental section, and Supporting Information, 13-substrate-peptides 28 ). Due to the conjugation of the arginyl moiety onto the N-terminus of the substrate peptide, there was a clear retention time shift between the substrate peptide and the arginylated product peptide, on average 10% earlier in the linear gradient on a reversed-phase C18 column. Overall, the arginylation reaction of 13 substrate peptides was near quantitative at 5 and 45 pmol substrate peptide. Once the arginylation reaction was challenged with 405 pmol of peptide per reaction, the arginylation efficiency after 90 min was no longer quantitative (see Figs. 3(A) and 3(B)). For example, peptide DAGVVCTDETR elutes at 13.3 min and its arginylated version elutes at 11.7 min. Overall, the peptide has a very high degree of arginylation (Fig. 3(A)). This is in contrast to the substrate peptide EAQISSAIVSSVQSK, reacted under the same conditions, where a large fraction of substrate peptide (eluting at 23.3 min) was still unreacted (Fig. 3(B)). To further investigate this substrate bias using a more complex sample, we performed the arginylation reaction using a proteolytic digest of the Universal Protein Standard 1 (UPS1) comprised of 50 proteins in equimolar ratio (5 pmol each per vial).
Protease digestion optimization and labelling bias investigation
To obtain suitable substrate peptides for arginylation, the UPS1 proteins were digested using Asp-N, resulting in N-terminal aspartate or glutamate, but unspecific C-termini. The proteolytic peptides were arginylated for 90 min and subsequently desalted using a standard C18 clean-up procedure. Using LC/MS, 149 peptides with N-terminal aspartate or glutamate were detected as being arginylated. In some cases, where no arginylation of peptides with acidic amino acids was detected, manual inspection of the MS1 ion chromatograms using Skyline 16 revealed many pairs of substrate and product peptide precursor ion masses corresponding to the theoretical values (see Supporting Information, UPS1_AspN_digest 28 ). In some cases, only substrate peptides eluted very early in the LC gradient. As arginylation will result in a chromatographic shift (see Fig. 3), we assume that some arginylated peptides might be too polar to bind to the C18 column material used. Hence, we conclude that all the substrate peptides were arginylated and that the stochastic sampling approach of shotgun MS/MS or chromatographic performance is probably the reason why MS/MS spectra for the arginylated version of some substrate peptides are lacking. Examining the Asp-N digest of 50 UPS1 peptides reveals that only 35 proteins were detected.
To increase the number of detectable proteins, the single Asp-N protease digest was further optimized by using a double digest, e.g. Lys-C. A double digest of Lys-C and Asp-N results in substrate peptides for arginylation and peptides with C-terminal Lys. In addition, these peptides would allow for a direct comparison between MS/MS fragmentation of non-arginylated and arginylated peptides. Hence, the UPS1 protein standard was first digested using Lys-C followed by an Asp-N digest. The resulting peptide mixture was arginylated and peptides analyzed by LC/MS. Subsequent in silico annotation of the MS/MS spectra resulted in experimental evidence for 45 proteins, an increase of 20% over the mono Asp-N digest. On the peptide level, 156 peptides with an N-terminal acidic amino acid were detected. The majority of these peptides were quantitatively arginylated or both arginylated and non-arginylated forms were detected (see Supporting Information, UPS1_LysC_AspN_digest 28 ).
To further illustrate the influence of arginylation on peptide fragmentation, we selected peptides from the UPS1 Lys-C/Asp-N double digest. As can be seen in Fig. 4(A), peptide DDHFLF precursor [M+2H + ] 2+ ion fragments into six annotated product ions. However, upon arginylation of the peptide, the [M+2H + ] 2+ precursor ion fragments and the number of annotated ions doubles (Fig. 4(B)) although only a single amino acid was added to the N-terminus of the peptide. Figure 4(C) shows the MS/MS spectrum of [DDTVCLAK+2H + ] 2+ with enhanced cleavage C-terminal to two Asp residues. This enhanced cleavage is overcome upon arginylation, resulting in a more balanced fragmentation of the [RDDTVCLAK+2H + ] 2+ ion. The resulting MS/MS spectrum is comprised of b- and y-fragment ion ladders (Fig. 4(D)). A third example illustrating the contribution of arginylation to precursor ion fragmentation is peptide EGVVGAVEK. The [EGVVGAVEK+2H + ] 2+ precursor ion fragmentation results in very few annotated product ions (Fig. 4(E)) while, upon arginylation, complete b- and y-fragment ion ladders were annotated (Fig. 4(F)). As all the MS/MS spectra are charge state matched, it is possible to study the influence of arginylation on peptide fragmentation. Non-arginylated peptides (Figs. 4(A), 4(C) and 4(E)) secure two protons, one to the primary amine of the N-terminus and the second to the side chain of a basic amino acid within the peptide sequence. This is in contrast to arginylated peptides (Figs. 4(B), 4(D) and 4(F)) securing two protons, where both reside with the side chain of basic amino acids. The side chain sequestered protons allow for a more stochastic fragmentation of the peptide backbone to generate fragment ion ladders. Upon introduction of an additional proton, presumably on the primary amine of the peptide's N-terminus, the product ions are again distributed unevenly. Peptide EPISVSSEQVLK was detected three times in the UPS1 double digest dataset: non-arginylated [M+2H + ] 2+ (Fig. 5(A)), arginylated [M+2H + ] 2+ (Fig. 5(B)) and arginylated [M+3H + ] 3+ (Fig. 5(C)). The most dominant product ion in [EPISVSSEQVLK+2H + ] 2+ (Fig. 5(A)) is y7 + generated by peptide backbone cleavage between Val5 and Ser6. Upon arginylation, in the formation of the [REPISVSSEQVLK+2H + ] 2+ ion (Fig. 5(B)) each amino acid side chain of Arg and Lys sequesters a proton resulting in an evenly distributed fragmentation pattern of b-fragment and y-fragment ions during the ion trap CID. However, upon adding an additional proton to the primary amine of the peptide's N-terminus, the [REPISVSSEQVLK+3H + ] 3+ ion (Fig. 5(C)) fragments again at preferred sites, e.g. between Glu and Gln. From these results (and others found in the Supporting Information, UPS1_LysC_AspN_digest 28 ), we conclude that arginylation enhances peptide fragmentation and allows for the detection of relatively short peptides.
No mid-chain arginylation detectable on the peptide level
There are reports not only that N-terminal acidic amino acids are substrates of ATE1, but also that mid-chain Asp or Glu could be arginylated through their side-chain carboxyl groups. 17, 18 To test for mid-chain arginylation of peptides, we re-analyzed the 90 min end-point reactions of the UPS1 experiments using the Mascot error tolerant search option (Matrix Science, London, UK), which is especially useful for detecting unexpected chemical or post-translational modifications. As expected, an additional mass of +156.10 (equivalent to an Arg moiety) was only detected at N-terminal residues, but not mid-chain residues (see Supporting Information, error-tolerant-search.csv 28 ). We cannot rule out that on the protein level ATE1 might arginylate mid-chain acidic amino acids, but in our peptide level experiments yATE1 only arginylated N-terminal residues.
MALDI-TOF Mass Spectrometry
Mass spectrometry is an analytical technique in which samples are ionized into charged molecules and ratio of their mass-to-charge (m/z) can be measured. In MALDI-TOF mass spectrometry, the ion source is matrix-assisted laser desorption/ionization (MALDI), and the mass analyzer is time-of-flight (TOF) analyzer.
MALDI is a soft ionization that involves a laser striking a matrix of small molecules to make the analyte molecules into the gas phase without fragmenting or decomposing them. Some biomolecules are too large and can decompose when heated, and traditional techniques will fragment or destroy macromolecules. MALDI is appropriate to analyze biomolecules like peptides, lipids, saccharides, or other organic macromolecules.
Figure 1. Ionization of analytes by MALDI
In Figure 1, the analyte is embedded in a very large excess of a matrix compound deposited on a solid surface called a target, usually made of a conducting metal and having spots for several different samples to be applied. After a very brief laser pulse, the irradiated spot is rapidly heated and becomes vibrationally excited. The matrix molecules energetically ablated from the surface of the sample, absorb the laser energy and carry the analyte molecules into the gas phase as well. During the ablation process, the analyte molecules are usually ionized by being protonated or deprotonated with the nearby matrix molecules. The most common MALDI ionization format is for analyte molecules to carry a single positive charge.
Lasers of both ultraviolet (UV) and infrared (IR) wavelengths are in use, but UV lasers are by far the most important light sources in analytical MALDI. Among these, nitrogen lasers and frequency-tripled or quadrupled Nd: Yag lasers often serve for the majority of applications. IR-MALDI is dominated by Er:Yag lasers while TEA-CO2 lasers are rarely used.
It is believed that the first function of the matrix essentially is to dilute and isolate analyte molecules from each other. This occurs during solvent evaporation and concomitant formation of a solid solution. Then, upon laser irradiation, it functions as a mediator for energy absorption. The choice of the right matrix is key to the success in MALDI. In general, highly polar analytes work better with highly polar matrices, and nonpolar analytes are preferably combined with nonpolar matrices. As shown in Table 1, different matrixes have been sought and widely used. Currently, the most commonly used matrixes are α-cyano-4-hydroxycinnamic acid, 2,5-dihydroxybenzoic acid, 3,5-dimethoxy-4-hydroxycinnamic acid, and 2,6-dihydroxyacetophenone.
Table 1. UV-MALDI matrices (Gross J. H., 2006)
|Nicotinic acid||NA||Peptides, proteins|
|Picolinic acid||PA||Oligonucleotides, DNA|
|3-Hydroxypicolinic acid||HPA, 3-HPA||Oligonucleotides, DNA|
|3-Aminopicolinic acid||3-APA||Oligonucleotides, DNA|
|2,5-Dihydroxybenzoic acid||DHB||Proteins, oligosaccharides|
|DHB-based mixtures||DHB/XY and super-DHB||Proteins, oligosaccharides|
|α-Cyano-4-hydroxycinnamic acid||α-CHC, α-CHCA, 4-HCCA, CHCA||Peptides, smaller proteins, triacylglycerols, numerous other compounds|
|2-(4-Hydroxyphenylazo) benzoic acid||HABA||Peptides, proteins, glycoproteins, polystyrene|
|2-Mercaptobenzothiazole||MBT||Peptides, proteins, synthetic polymers|
|5-Chloro-2-mercaptobenzothiazole||CMBT||Glycopeptides, phosphopeptides, and proteins|
|2,6-Dihydroxyacetophenone||DHAP||Glycopeptides, phosphopeptides, proteins|
|Dithranol (1,8,9-anthracenetriol)||None||Synthetic polymers|
|9-Nitroanthracene||9-NA||Fullerenes and derivatives|
|Benzo[a]pyrene||None||Fullerenes and derivatives|
|2-[(2E)-3-(4-tert-Butylphenyl)-2-methylprop-2-enylidene]malonitrile||DCTB||Oligomers, polymers, dendrimers, small molecules|
Time of Flight (TOF) analyzer
Figure 2. General schematic for TOF analyzer. (A) Liner TOF analyzer (B) Reflector TOF analyzer (C) The derivation process of the time that ions pass through field free region in the liner TOF analyzer.
As shown in Figure 2, the basic principle of TOF is that ions of different m/z are dispersed in time during their flight along a field-free drift path of known length. Provided that all the ions start their journey at the same time or at least within a sufficiently short time interval, the lighter ones will arrive earlier at the detector than the heavier ones.
Theoretically, all the ions are given the same initial kinetic energy, so that after drifting along the field free region, the ions of the same m/z at the detector at the time. However, in practice, the pulse is not felt by all ions to the same intensity and so not all the ions of the same m/z values reach their ideal velocities. To correct this problem, a reflection is often applied to the end of the drift zone. The reflectron consists of a series of ring electrodes with high voltage, which can repulse the ions back along the flight tube usually at a slightly displaced angle.
Ions of different kinetic energy penetrate the reflectron to different depths before they get expelled from the reflectron into the opposite direction. Faster ions carrying more kinetic energy will travel a longer path than slower ones, and thus spend more time within the reflectron than slower ions carrying less energetic. In that way, the detector receives ions of the same mass at (about) the same time. Thereby, this design for TOF mass analyzer has increased their resolution significantly. However, reflectron TOF analyzer is not suitable for analytes that are not stable enough to survive the electric field.
The process of MALDI-TOF mass spectrometry
Figure 3. The process of MALDI-TOF mass spectrometry (Clark A. E., et al. 2013)
The analyte should be soluble to at least about 0.1 mg/ml in some solvent. And the matrix is dissolved to yield either a saturated solution or a concentration of about 10 mg/ml. The solution of the analyte is then admixed to that of the matrix. For optimized MALDI spectra, the molar matrix-to-analyte ratio is normally adjusted as to fall into the range from 1000: 1 to 100,000: 1. And then the mixture is then spotted onto a metal target plate for analysis. After drying, the mixture of the sample and matrix co-crystallizes and forms a solid deposit of sample embedded into the matrix. The plate is subsequently loaded into the MALDI-TOF instrument and analyzed by software associated with the respective system. The MALDI leads to the sublimation and ionization of both the sample and matrix. These generated ions are separated depending on m/z through a TOF analyzer, and a spectral representation of these ions is generated and analyzed by the MS software, generating an MS profile.
Application of MALDI-TOF mass spectrometry
The intact mass determination is basic and important for protein characterization, due to the correct molecular weight of a protein can indicate the intact structure. MALDI, a soft ionization technique, is suitable for proteins which tend to be fragile and fragment when ionized by other ionization methods. The performance of MALDI-TOF MS is less affected by buffer components, detergents, and contaminants. In addition, it permits intact protein mass determination with sufficient accuracy (≤ 500 ppm) for sequence validation. After protein digestion, MALDI-TOF MS can be also used to analyze the obtained peptides for further primary sequence confirmation by peptide mass fingerprinting.
MALDI-TOF mass spectrometry has simple operation, good mass accuracy, as well as high resolution and sensitivity. Therefore, it has widespread uses in proteomics to identify proteins from simple mixtures by a method called peptide mass fingerprinting, which are often used with two-dimensional gel electrophoresis (2-DE). In this approach, peptides are generated by digesting proteins of interest with a sequence-specific enzyme like trypsin. And then peptides are analyzed by MALDI-TOF mass spectrometry to get the peptide masses. The experimental masses are compared against a database containing theoretical peptide masses from a given organism with the same sequence-specific protease.
MALDI-TOF mass spectrometers equipped with reflectrons can analyze fragment ions produced from precursor ions that spontaneously decompose in the flight. Such ions are generally referred to as metastable ions, and the process of decomposition in the field free region between the ion source and the reflectron is commonly referred to as PSD. PSD fragment ions are formed within the field free region before entering the reflectron. PSD fragment ions can be separated, collected, and recorded on the detector by continuously changing the reflector voltage to form a PSD mass spectrum that provides very rich and effective structural information for the primary structure of peptides and proteins. In the proteomics study, some 2DE-separated protein samples cannot be identified by PMF or the results of identification are not clear. The PSD sequencing function can be applied to the identification of these proteins. Using PSD spectroscopy, combined with a database search, proteins can be identified quickly and with high specificity.
With the development of molecular biology techniques and antisense nucleic acid drug technologies, more and more oligonucleotide fragments have been synthesized to be used as primers, probes and antisense drugs. It is entirely necessary to quickly detect these fragments to determine whether the synthesis is complete and whether the synthesized sequence is correct. Mass spectrometry, including MALDI-TOF-MS, is by far the best means of doing this. Oligonucleotide analysis using MALDI-TOF-MS was simple, rapid, accurate, and sensitive, which can be used to determine the complete oligonucleotide sequence.
The MALDI-TOF can be used in profiling and imaging proteins directly from thin tissue sections, known as MALDI imaging mass spectrometry (MALDI-IMS). It provides specific information about the local molecular composition, relative abundance and spatial distribution of peptides and proteins in the analyzed section. MALDI-IMS can analyze multiple unknown compounds in biological tissue sections simultaneously through a single measurement that can obtain molecule imaging of the tissue while maintaining the integrity of cells and molecules in tissues.
MALDI-TOF mass spectrometry can analyze a wide variety of biomolecules, such as peptides, proteins, carbohydrate, oligonucleotide, and so on. Due to the fact that formed ions have low internal energy, a great advantage of MALDI-TOF is that the process of soft-ionization enables observation of ionized molecules with little to fragmentation of analytes, allowing the molecular ions of analytes to be identified, even within mixtures. And it is easy to use and maintain with fast data acquisition. Choosing the appropriate matrix substance is important for successful MALDI-TOF mass spectrometry.
At Creative Proteomics, we can provide various services based on our advanced MALDI-TOF mass spectrometry platforms, including:
1. Gross J H. Mass spectrometry: a textbook. Springer Science & Business Media, 2006.
2. Boesl U. Time - of - flight mass spectrometry: Introduction to the basics. Mass spectrometry reviews, 2017, 36(1): 86-109.
3. Guerrera I C, Kleiner O. Application of mass spectrometry in proteomics. Bioscience Reports, 2005, 25(1-2): 71-93.
4. Fuchs B, Schiller J. Application of MALD - TOF mass spectrometry in lipidomics. European Journal of Lipid Science and Technology, 2009, 111(1): 83-98.
5. Duncan M W, Roder H, Hunsucker S W. Quantitative matrix-assisted laser desorption/ionization mass spectrometry. Briefings in functional genomics and proteomics, 2008, 7(5): 355-370.
6. Kenny D J, Brown J M, Palmer M E, et al. A parallel approach to post source decay MALDI-TOF analysis. Journal of the American Society for Mass Spectrometry, 2006, 17(1): 60-66.
Please submit a detailed description of your project. We will provide you with a customized project plan to meet your research requests. You can also send emails directly to for inquiries.
Comparison of Peptide Levels in Sperm Total Protein Digests
The goal of this research was to analyze changes in phosphorylation that occur as a result of sperm capacitation. For this purpose, cauda epididymal mouse sperm were incubated in conditions that support (+BSA, +HCO3 − ) or do not support (𢄫SA, −HCO3 − ) capacitation. A necessary requirement for any attempt at the differential analysis of protein phosphorylation is that identical amounts of protein be compared between dissimilar sample types. To determine if the same amount of protein was present in the capacitated (Cap) and noncapacitated (NCap) aliquots and to confirm that both samples had been subjected to identical digestion conditions, a separate analysis of each of the digests (not subjected to Fisher esterification (Cap5 and NCap5)) was conducted on the LTQ-FT mass spectrometer. The peak areas corresponding to a tryptic peptide from a nuclear protein constitutively expressed in mouse testis (RDGFVTSKRKK m/z = 441.28) and a peptide resulting from the autodigestion of trypsin (VATVSLPR m/z = 421.76) were compared and found to have a ratio of 0.92 and 1.26, respectively ( Figure 1 ) demonstrating similar protein levels and extent of digestion.
Comparison of peptides identified in noncapacitated (A) and capacitated (B) sperm total protein digests. The peak at m/z = 421.76 was identified through MS/MS analysis to be the tryptic peptide VATVSLPR from the autodigestion of trypsin, while the peak at m/z = 441.28 was identified through MS/MS analysis to be the tryptic peptide RDGFVTSKRKK from a sperm nuclear protein. The ratio of the peak areas between the noncapacitated and capacitated digests is 1.26 and 0.92, respectively.
Intrasample Comparison of Phosphopeptide Levels in Protein Digests
The selective IMAC enrichment of phosphorylated peptides from the highly complex capacitated and noncapacitated solution digests was expected to be problematic due to the fact that acidic residues (i.e., glutamic and aspartic acid) have been shown to bind to immobilized iron atoms. 15 To prevent nonphosphorylated, acidic residue-containing peptides from interfering with the analysis, peptide carboxylic acids in each sample were converted to their corresponding methyl esters using either unlabeled or deuterium-labeled methanol as a reagent in two separate sets of reactions. While this was crucial for the subsequent quantification of differential phosphopeptide expression in each sample, these separate reactions added another variable that had to be considered before a differential analysis could be conducted. To determine if each reaction had proceeded to the same extent, Fisher esterification on equal amounts of each sample was conducted using both d0- and d4-reagent. The differentially modified peptides from the same sample types, either capacitated or noncapacitated (NCap (d0 esters) and NCap (d3 esters) or Cap (d0 esters) and Cap (d3 esters)), were then combined and analyzed using the IMAC-nRPLC-MS/MS analysis described above. The peak areas corresponding to a tryptic phosphopeptide from the calcium binding tyrosine phosphorylation regulated protein (CABYR) (TKIpSIepSLK m/z = 603.79 (d0 labeled) and 606.81 (d3 labeled)) were compared in both sample types and found at a ratio of 0.99 in the noncapacitated samples and at 0.95 in the capacitated samples ( Figure 2 ). These results confirmed that the differential labeling proceeded to the same extent in each modification reaction. Importantly, these experiments also served as controls for the subsequent experiments in which differentially labeled, dissimilar sample types (NCap (d0 esters) versus Cap (d3 esters) or NCap (d3 esters) versus Cap (d0 esters)) were compared.
Intrasample comparison of noncapacitated and capacitated digests. Comparison of differentially labeled phosphopeptide peak areas identified in an IMAC analysis of a combination of equal amounts of CH3 and CD3 Fisher esterified noncapacitated (A) and capacitated (B) sperm total protein digests. The d0/d3 peak ratio was 0.99 in the noncapacitated sample and 0.95 in the capacitated sample, confirming equal amounts of this peptide in the CH3 and CD3 Fisher esterified samples from similar capacitation states.
Value of Differential Isotopic Labeling for Phosphopeptide Identification
The assignment of peptide sequences to phosphopeptide spectra is often hindered by the fact that phosphoserine and phosphothreonine residues demonstrate the neutral loss of phosphoric acid, not only from the intact peptide, but also from phosphate-containing fragments generated during CAD, the process whereby peptides are fragmented along the backbone as a result of collisions with an inert bath gas inside the ion trap. 16 This results in a crowded MS/MS spectrum dominated by peaks that do not correspond to sequence-informative ions and which result in spurious peptide sequence assignments. A convenient consequence of the Fisher esterification protocol followed in this study is that comparison of the MS and MS/MS data acquired for the identical, but differentially labeled phosphopeptides, is of remarkable utility in assigning their proper sequences. First, a visual inspection of the isotopic patterns from each phosphopeptide reveals their charge state and, by comparing the mass shift between the two different isotopic envelopes, allows for the determination of the number of acidic residues in the peptide. For example, as shown in Figure 3 , the difference of 0.5 amu between the 12 C and 13 C isotopes for m/z = 603.79 and m/z = 606.81 indicates that these peptides both have a charge of +2. In addition, the mass shift of 3.02 amu between m/z = 603.79 and m/z = 606.81 reveals that this peptide contains 2 modifications, one at the C-terminus (always present) and one on either a glutamic or aspartic acid residue. Both observations agree with the assigned sequence of TKIpSIepSLK, which can be further confirmed by comparison of the MS/MS spectra from each peptide. As Figure 4 demonstrates, b- and y-type ions are easily picked out of each spectrum based upon their respective mass shifts: y-ions will always be shifted by at least 3 amu in the deuterium labeled peptide due to the presence of the carboxy-terminus, while b-ions will only reveal a shift once they contain a modified acidic residue. The information gained in this manner by FT-ICR analysis (accurate mass and number of carboxyl groups) can be coupled with the complementary information provided by the MS/MS analyses (fragment ions, sequence tags, and minimum number of phosphorylated residues from neutral losses of phosphoric acid) to rapidly identify the correct peptide sequence.
Isotopic distributions of the doubly charged deuterated and nondeuterated TKIpSIepSLK peptides from a single scan, where both peptides were eluting from the HPLC column. The accurate mass measurements (5 ppm in this case) provided by using the FT-ICR cell as the detector on the LTQ-FT instrument revealed these peptides to be doubly charged (mass difference of 0.5 amu within individual isotopic envelopes) and related (mass difference of 3.020 amu between isotopic envelopes). The number of carboxyl groups contained in the peptides was determined using the equation indicated in Figure 3. Mass difference refers to the difference between the monoisotopic masses of related deuterated and nondeuterated peptides, and charge state refers to the reciprocal of the mass difference between 12 C and 13 C peaks in the same charge envelope.
MS/MS spectra of the tryptic deuterated (A) and nondeuterated (B) phosphopeptide TKIpSIepSLK. Predicted monoisotopic masses for the ions of type b and y are shown above and below the sequence, respectively. Ions observed in the spectrum are underlined and those that lose phosphoric acid are presented in bold type. The label, Δ, denotes loss of phosphoric acid from the corresponding ion of type b or y. K-OMe represents the Fisher esterified C-terminal lysine, while 𠇎” represents the Fisher esterified glutamic acid. Masses for b and y ions which are shifted by +3 amu in the deuterated spectra are presented in blue, while those ions shifted by +6 amu are presented in red.
Identification of Phosphopeptides from Sperm Total Protein Digests
Once each sample type was determined to contain the same amount of protein, and that the alternative labeling experiments had not disturbed this ratio, a differential analysis of phosphopeptide expression, using two similar, but not identical, experiments was conducted. In the first experiment, the heavy isotope-labeled capacitated protein digest was combined with the light isotope-labeled noncapacitated digest (Cap (d3 esters) vs NCap (d0 esters)), while in the second experiment, the d3 modified noncapacitated sample was combined with the d0 modified capacitated sample (Cap (d0 esters) vs NCap (d3 esters)). These combined samples were then subjected to IMAC for phosphopeptide enrichment and independently analyzed on the LTQ-FT hybrid linear ion trap-Fourier Transform mass spectrometer. While the total ion chromatograms (TIC) for each analysis were remarkably similar, as expected, the relative intensities of pairs of peaks were reversed between analyses ( Figure 5 ). Visual comparison of the MS spectra acquired during each chromatographic gradient identified hundreds of phosphopeptide pairs, but software designed to analyze these pairs and identify differences automatically has not yet been completed. Instead, all MS/MS spectra were confirmed by manual interpretation of the corresponding MS/MS sequence(s). Importantly, every carboxylic acid-containing residue in every identified phosphopeptide had been modified, suggesting that our derivatization method proceeded to completion, effectively preventing the binding of carboxylic acid-containing peptides to the IMAC column.
Total ion chromatograms and single ion chromatograms for the differentially labeled tryptic phosphopeptides TKIpSIepSLK and YLpYAMR from the d0 noncapacitated/d3 capacitated analysis (A) and the d0 capacitated/d3 noncapacitated analysis (B). Note that the peak areas for the peptides from the capacitated sample are greater in each analysis, demonstrating that this phenomenon is sample specific and not an artifact of the differential labeling.
Intersample Comparison of Phosphopeptide Levels in Protein Digests
Peak ratios of the corresponding deuterated and nondeuterated phosphopeptides were used to derive relative levels of each peptide in the respective samples. As we were primarily interested in the level of the phosphopeptides identified in the capacitated sample relative to the phosphopeptides identified in the noncapacitated samples, the capacitated peak area was divided by the noncapacitated peak area for each peptide in each analysis ( Figure 6 ). The design of the overall experimental scheme (Cap (d0 esters) vs NCap (d3 esters) and Cap (d3 esters) vs NCap (d0 esters)) also permitted the calculation of the square of the odds ratio, or ratio of ratios, for each peptide pair, which compensated for differences in the creation or detection of d0 labeled peptides in relation to d3 labeled peptides. With the use of this technique, the relative abundances of 42 of the 44 phosphopeptides identified above were determined and represented a range of values ( Table 1 ). While several of these peptides do not appear to vary significantly, others were found to have an increased representation in the capacitated sample, strongly suggesting the phosphorylation of these sequences as a result of the capacitation process. For example, the phosphopeptide LIpSSeNFeNYVR from fatty acid binding protein 9, also known as PERF15, 17 was only detected in the capacitated sample. Contrary to the increased representation observed in some cases, other phosphopeptides were found to be more abundant in the noncapacitated sample, suggesting that these sequences undergo dephosphorylation during sperm capacitation. One example of this is the phosphorylated peptide AIVpSPPVeMVeeIpSK which was determined to be highly upregulated in the noncapacitated sample. Our data also indicate that several peptides undergo proline-directed phosphorylation this finding is in agreement with previous results from our laboratory demonstrating that proline-directed phosphorylation is upregulated in mouse sperm as a result of the capacitation process. 11 In addition, hexokinase, a highly abundant sperm protein which has been shown to be tyrosine-phosphorylated to the same extent in both noncapacitated and capacitated mouse sperm using alternative biochemical techniques, 3 , 18 was shown to be phosphorylated at Tyr31 in this study and the relative extent of phosphorylation at this site between capacitated and noncapacitated sperm was determined to be 1.15. This observation further confirms the usefulness of differential isotopic labeling for the relative quantitation of phosphorylation in a cell exposed to a particular stimulus.
Single ion chromatograms for the differentially labeled tryptic phosphopeptides TKIpSIepSLK and YLpYAMR from the d0 noncapacitated/d3 capacitated analysis (A and C, respectively) and the d0 capacitated/d3 noncapacitated analysis (B and D, respectively). The square root of the ratio of the d3/d0 ratios (odds ratio) for each peptide was calculated as indicated, in order to remove potential errors associated with the comparison of the deuterated and a nondeuterated peptide species.
Phosphopeptides Identified in Capacitated (Cap) and Noncapacitated (NCap) Mouse Sperm Total Protein Digests, and Their Relative Quantitation Based upon the Square of the Odds Ratio (OR) a
|phosphopeptide sequence||charge||exp. m/z||calc. m/z||phosphosites||NCBI accession number||protein name||OR Cap/Ncap|
|K.NIdLTAIIpSdLR.S||2||733.39||733.39||1||<"type":"entrez-protein","attrs":<"text":"AAH57001","term_id":"34784205","term_text":"AAH57001">> AAH57001||Outer Dense fiber 2 (Odf2) protein||Only in Ncap|
|K.AIVpSPPVeMVeeIpSK.D||2||922.44||922.43||2||<"type":"entrez-protein","attrs":<"text":"XP_139384","term_id":"38077031","term_text":"XP_139384">> XP_139384||Recently removed from NCBI database||0.04|
|K.TSApTeIQSeLSSMR.Y||3||554.58||554.59||1||<"type":"entrez-protein","attrs":<"text":"NP_080569","term_id":"21312846","term_text":"NP_080569">> NP_080569||Sperm acrosome associated 1||0.56|
|K.(pTpS)ATeIQSeLSSMR.C||2||831.38||831.38||1||<"type":"entrez-protein","attrs":<"text":"NP_080569","term_id":"21312846","term_text":"NP_080569">> NP_080569||Sperm acrosome associated 1||0.62|
|K.(pTpS)ATeIQpSeLSpSMR.Y||2||911.35||911.34||3||<"type":"entrez-protein","attrs":<"text":"NP_080569","term_id":"21312846","term_text":"NP_080569">> NP_080569||Sperm acrosome associated 1||0.74|
|R.deMVAGpSQepSIK.V||2||755.30||755.30||2||<"type":"entrez-protein","attrs":<"text":"NP_780347","term_id":"227330593","term_text":"NP_780347">> NP_780347||Dynein, axonemal, intermediate chain 1||0.74|
|R.TLpSdYNIQK.E||2||595.28||595.28||1||<"type":"entrez-protein","attrs":<"text":"CAI24672","term_id":"220808512","term_text":"CAI24672">> CAI24672||Ubiquitin B||1.12|
|R.TTpSMSHVGpSAIMVdLPR.T||3||663.95||663.96||2||<"type":"entrez-protein","attrs":<"text":"XP_355541","term_id":"82896089","term_text":"XP_355541">> XP_355541||Hypothetical Protein LOC381580||1.27|
|K.eIeQpSPPGpSPK.A||2||685.79||685.79||2||<"type":"entrez-protein","attrs":<"text":"AAK49990","term_id":"13936908","term_text":"AAK49990">> AAK49990||Calcium Binding Protein CBP86𠄶||1.39|
|K.(pTpS)ATeIQpSeLpSpSMR.C||2||951.33||951.33||4||Sperm acrosome associated 1||1.44|
|K.(pTpS)AQVVVGPVSeAePPK.A||2||908.97||908.96||1||<"type":"entrez-protein","attrs":<"text":"AAK49990","term_id":"13936908","term_text":"AAK49990">> AAK49990||Calcium Binding Protein CBP86𠄶||1.58|
|K.SepSLQALQdK.V||2||620.80||620.80||1||<"type":"entrez-protein","attrs":<"text":"AAH50799","term_id":"29747766","term_text":"AAH50799">> AAH50799||Spata18 protein||1.60|
|R.pSPSHpSPATSApSYIGPIR.N||2||991.40||991.40||3||<"type":"entrez-nucleotide","attrs":<"text":"EU937514","term_id":"218931545","term_text":"EU937514">> EU937514||Testis-specific serine/proline-rich protein b||1.61|
|R.SIpSQTGpSR.Q||2||505.19||505.19||2||<"type":"entrez-protein","attrs":<"text":"NP_001074565","term_id":"124487360","term_text":"NP_001074565">> NP_001074565||Hypothetical Protein LOC75811||1.63|
|K.TKIpSIepSLK.T||2||603.79||603.79||2||<"type":"entrez-protein","attrs":<"text":"AAK49990","term_id":"13936908","term_text":"AAK49990">> AAK49990||Calcium Binding Protein CBP86𠄶||1.73|
|R.pSPSHpSPATpSASYIGPIR.N||2||991.40||991.40||3||<"type":"entrez-nucleotide","attrs":<"text":"EU937514","term_id":"218931545","term_text":"EU937514">> EU937514||Testis-specific serine/proline-rich protein b||1.77|
|K.ApSLLpSNPIPeVK.T||2||728.35||728.35||2||<"type":"entrez-protein","attrs":<"text":"CAB57454","term_id":"6015589","term_text":"CAB57454">> CAB57454||Testicular Haploid Expressed Gene (THEG) protein||1.91|
|K.SPpSQTGLK.N||2||456.22||456.22||1||<"type":"entrez-nucleotide","attrs":<"text":"CB273841","term_id":"28464164","term_text":"CB273841">> CB273841||McCarry Eddy round spermatid cDNA||1.91|
|R.SPpSHpSPATSApSYIGPIR.N||2||991.40||991.40||3||<"type":"entrez-nucleotide","attrs":<"text":"EU937514","term_id":"218931545","term_text":"EU937514">> EU937514||Testis-specific serine/proline-rich protein b||1.96|
|R.ASpSQpSPpSPHVQHVPR.G||2||934.37||934.37||3||Testis-specific serine/proline-rich protein b||1.99|
|R.ApSpSQpSPSPHVQHVPR.G||2||934.37||934.37||3||Testis-specific serine/proline-rich protein b||1.99|
|R.dLLpSIpSdGR.G||2||589.25||589.25||2||<"type":"entrez-protein","attrs":<"text":"AAH27526","term_id":"20380318","term_text":"AAH27526">> AAH27526||Myeloid Leukemia Factor 1 (Mlf1)||2.06|
|R.(pYpS)KepSLdAeK.R||2||693.29||693.29||2||<"type":"entrez-protein","attrs":<"text":"AAK39109","term_id":"13774963","term_text":"AAK39109">> AAK39109||Autoimmune Infertility-related Protein||2.09|
|R.pSPSHpSPATSASYIGPIR.N||2||951.42||951.41||2||Testis-specific serine/proline-rich protein b||2.19|
|R.(pSpY)epSpSIdeNeGYQK.S||2||979.85||979.84||3||<"type":"entrez-protein","attrs":<"text":"AAH06583","term_id":"13879232","term_text":"AAH06583">> AAH06583||Ccdc136 protein||2.28|
|K.GYpSVGdLLQeVMK.F||2||780.88||780.87||1||<"type":"entrez-protein","attrs":<"text":"AAM18540","term_id":"20271174","term_text":"AAM18540">> AAM18540||A Kinase Anchoring Protein 4 (AKAP4)||2.29|
|R.SPpSHpSPATpSASYIGPIR.N||2||991.40||991.40||3||Testis-specific serine/proline-rich protein b||2.49|
|R.SPpSHpSPATSASYIGPIR.N||2||951.41||951.41||2||Testis-specific serine/proline-rich protein b||3.13|
|R.pSeGeLNLeTLeeK.E||2||827.90||827.90||1||<"type":"entrez-protein","attrs":<"text":"AAM18540","term_id":"20271174","term_text":"AAM18540">> AAM18540||A Kinase Anchoring Protein 4 (AKAP4)||3.27|
|R.pSPpSHpSPATSASYIGPIR.N||2||991.40||991.40||3||Testis-specific serine/proline-rich protein b||3.30|
|R.KKpSPTpSAeLLLIdPR.Y||2||935.49||935.48||2||<"type":"entrez-protein","attrs":<"text":"NP_083218","term_id":"58037373","term_text":"NP_083218">> NP_083218||Organic anion transporter, member 6c1||3.34|
|R.SRpSPpSPIR.C||2||537.23||537.23||2||<"type":"entrez-protein","attrs":<"text":"AAH50799","term_id":"29747766","term_text":"AAH50799">> AAH50799||Spata18 protein||3.81|
|K.IRpSPpSPNR.S||2||550.74||550.74||2||<"type":"entrez-protein","attrs":<"text":"AAH50799","term_id":"29747766","term_text":"AAH50799">> AAH50799||Spata18 protein||3.86|
|R.ASpSQpSPSPHVQHVPR.G||2||894.39||894.39||2||Testis-specific serine/proline-rich protein b||3.98|
|K.TPTGQTHQpSPVSK.R||2||731.86||731.34||1||<"type":"entrez-protein","attrs":<"text":"AAA40413","term_id":"201923","term_text":"AAA40413">> AAA40413||Testis-specific protein||4.01|
|R.LSpSLVIQMAR.K||2||606.31||606.32||1||<"type":"entrez-protein","attrs":<"text":"AAM18540","term_id":"20271174","term_text":"AAM18540">> AAM18540||A Kinase Anchoring Protein 4 (AKAP4)||4.62|
|K.KMpSpSMSLLFK.R||2||673.29||673.29||2||<"type":"entrez-protein","attrs":<"text":"XP_573518","term_id":"62659784","term_text":"XP_573518">> XP_573518||Recently removed from NCBI database||6.03|
|R.RLTLPpSLSLQYdGAGR.S||3||618.99||618.99||1||Testis-specific serine/proline-rich protein b||14.93|
|K.LIpSSeNFeNYVR.E||2||796.88||796.87||1||<"type":"entrez-protein","attrs":<"text":"AAH48437","term_id":"28913395","term_text":"AAH48437">> AAH48437||Fatty acid binding protein 9 (testis)||Only in Cap|
Discovery vs. targeted proteomics
Strategies to improve the sensitivity and scope of proteomic analysis generally require large sample quantities and multi-dimensional fractionation, which sacrifices throughput. Alternatively, efforts to improve the sensitivity and throughput of protein quantification limit the number of features that can be monitored.
For this reason, proteomics research is typically divided into two categories: discovery proteomics and targeted proteomics. Discovery proteomics optimizes protein identification by spending more time and effort per sample and reducing the number of samples analyzed. In contrast, targeted proteomics strategies limit the number of features that will be monitored and then optimize the chromatography, instrument tuning, and acquisition methods to achieve the highest sensitivity and throughput for hundreds or thousands of samples.
The balance between scope, sensitivity and scalability of discovery and targeted proteomics. Due to the broad-scope nature and sensitivity of discovery proteomics, the ability to perform a comprehensive analysis of hundreds or thousands of samples is limited. Conversely, targeted proteomic analysis entails the quantitation of discrete subsets of peptides, which allows researchers to analyze these peptides across thousands of samples with the highest level of sensitivity.
Discovery proteomics experiments are intended to identify as many proteins as possible across a broad dynamic range and often require depletion of highly abundant proteins, enrichment of relevant components (e.g., subcellular compartments or protein complexes), and fractionation to decrease sample complexity (e.g., SDS-PAGE or chromatography). These strategies can reduce the dynamic range between components in a fraction and reduce the competition between proteins or peptides for ionization and MS duty cycle time. Quantitative discovery proteomics experiments add a further challenge because they seek to identify and quantify protein levels across multiple fractionated samples.
Targeted proteomics experiments are typically designed to quantify less than 100 proteins with very high precision, sensitivity, specificity and throughput. Indeed, this approach typically minimizes the amount of sample preparation to improve precision and throughput. Targeted MS quantitation strategies use specialized workflows and instruments to improve the specificity and quantification of a limited number of features across hundreds or thousands of samples, including directed sequencing by inclusion lists and selected (or multiple) reaction monitoring (SRM or MRM, respectively).
While discovery proteomics analysis is most often used to inventory proteins in a sample or detect differences in the abundance of proteins between multiple samples, targeted quantitative proteomic experiments are increasingly used in pharmaceutical and diagnostic applications to quantify proteins and metabolites in complex samples. Additionally, targeted proteomics often follows discovery proteomics to quantitate specific proteins found during discovery screening.
The characteristics of specific mass spectrometers make them more amenable to use with either discovery or targeted proteomic analysis. For example, because discovery proteomics emphasizes identification of all peptides in a limited number of samples, high-resolution instruments, including Thermo Scientific Orbitrap mass analyzers, are used to maximize the detection of peptides with minute mass-to-charge ratio (m/z) differences. Conversely, because targeted proteomics emphasizes sensitivity and throughout, instruments including triple quadrupoles and ion traps are used.
Figure 1. Optical images of the pituitary gland post-SIMS measurements. (a) H&E-stained pituitary gland with the anterior, intermediate, and posterior lobes labeled. (b–d) SEM images at 100× (b), 8000× (c), and 10 000× (d) magnification. The sizes of the matrix crystals were ∼2 μm on-tissue (c) and 0.5–1 μm off-tissue (d).
The Koch Institute Proteomics Core Facility provides mass spectrometry-based analyses of protein samples for which one or more of the following is desired: Protein identification, protein characterization (including modifications), intact protein MW determination, protein quantitation. Samples which are not proteins or peptides, for which structural or MW information is needed, may also be submitted, as long as they are amenable to analysis with the instrumentation and methods currently available.
- PROTEIN IDENTIFICATION
Proteins separated by gel electrophoresis
Protein identification from gel bands is generally routine and as long as there&rsquos enough protein and the keratin contamination is kept under control it yields results. In general Coomassie-stained bands contain enough protein to identify it, unless the keratin contamination is very high. A weakly stained Coomassie band may contain a 200-300 fmol protein (10s of ng) whereas a strongly-stained Coomassie band may contain pmol amounts of protein (100s of ng). Although the more protein there is the more confident the protein identifications will be, consider that by overloading a gel you may end up obscuring some of the weaker bands, especially if these are close to the bands of the major proteins.
Silver-stained gel bands contain less protein, typically 100 fmol or less (low ng range) and the sensitivity of fluorescent stains is in-between that of Coomassie and silver.
There are several staining kits available commercially from the major suppliers of biochemicals, which are compatible with mass spectrometric analysis (not all gel staining methods are). If you (or others in your lab) have submitted samples before and obtained useful results then obviously continue doing what you (or your colleagues) did before. Otherwise please talk to us before submitting samples so that we can help you increase the chances of success and avoid wasting time, effort and money.
Issues to consider are keratin contamination and how to minimize it and the use of staining protocols that are compatible with mass spectrometric analysis. Keratin comes primarily from skin, wool clothing and dust. While handling samples and gels wear a lab coat and gloves (nitrile is said to be better than latex) and avoid touching samples, gels, etc. with bare hands. Rinse all containers, tubes, with HPLC-grade methanol and HPLC-grade water. If available, run the gel in a laminar flow hood, such as a tissue culture hood, if not available use a clean surface in an dust-free area (e.g. away from an air vent). After running and staining the gel place it in a rinsed Petri dish (avoid Ziplock bags) in 1-2% acetic acid, cover it and bring it over to our lab so we can cut the gel band(s) of interest in our laminar flow hood (if the timing doesn't work the gel can be stored overnight in the refrigerator in the covered Petri and this should not cause problems to its subsequent analysis). If you need to scan the gel ensure that the scanner surfaces have been rinsed with clean methanol and water and wiped clean. By the way, &ldquoold style&rdquo gel fixing (e.g. using glutaraldehyde or formaldehyde or similar protein cross-linking rteagents) must be avoided as it makes it impossible to digest proteins in gels and recover proteolytic peptides.
For staining you can use any of the "mass spectrometry compatible" stains sold by several vendors. For Commassie, Gel Code Blue (Pierce/ThermoFisher) or Commassie Brilliant Blue R-250 and G-250 (Pierce or Bio-Rad) are all fine, if you follow the instructions that come with the staining kits. For silver, SilverQuest from Invitrogen or Silver Snap from Pierce are fine. Fluorescent gel stains (e.g. SYPRO Ruby, SYPRO Tangerine) are also mass spectrometry compatible. If you plan to use a stain and you cannot determine (e.g. from the product description) whether it is compatible with mass spectrometry please let us know and we can make inquiries.
Although cutting gel bands is straight forward, it is important to do it in a clean area such as a laminar flow hood. If you have not done this before please talk to us before excising gel bands for analysis. We can arrange for you to bring your gels to our lab and we can cut gel bands you wish to identify.
We prefer to carry out the in-gel digestions, under conditions that reduce sample contamination and optimize digestion and recovery of peptides, using protocols that have been applied successfully to thousands of samples. However we will accept already-digested samples, but if you have not submitted digested sample before please talk to us before doing this for the first time as we may be able to offer some helpful suggestions. We use trypsin for digestion if you need your protein digested with another enzyme please discuss this with us.
Proteins in solution
We routinely identify proteins in solutions, from a few to several hundreds. The same caveats apply as with in-gel digestion with regard to contamination (keratin is also a problem with solution samples, as proteolytic peptides from keratin often obscure or suppress signals from peptides from the less abundant proteins). Excessive amounts of salts can also be problematic, so using a method such as acetone precipitation to prepare protein samples may be necessary please talk to us about this if you have not done this sort of thing before. In addition there are certain other materials and chemicals, such as detergents and polymers, which are much more problematic with solution samples compared to gel bands,. This is because excised gel bands are washed extensively prior to digestion so that many buffers and detergents can be removed without protein loss, but solution samples are not readily amenable to washing. Although methods such as MW filtration or dialysis can be used, they result in some protein loss and also some detergents and polymers stay with the protein anyway. Please talk to us regarding the use of detergents as we may be able to recommend alternative ways of preparing samples as well as some &ldquomass spectrometry friendly&rdquo detergents.
For on-gel protein sample it would be helpful to run a silver stained gel using
10-15% of the sample if you see bands, even weak ones, this means that there&rsquos probably enough material in the sample remaining to identify some proteins.