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Systematic Evaluation of Protein Reduction and Alkylation Reveals Massive Unspecific Side Effects by Iodine-containing Reagents*

  • Torsten Müller
    Footnotes
    Affiliations
    Institute for Biochemistry and Molecular Biology, University of Bonn, Germany
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  • Dominic Winter
    Correspondence
    To whom correspondence should be addressed: Institute for Biochemistry and Molecular Biology, University of Bonn, Nussallee 11, 53115 Bonn, Germany. Tel.:+49 228 737081; Fax:+49 228 732416;
    Affiliations
    Institute for Biochemistry and Molecular Biology, University of Bonn, Germany
    Search for articles by this author
  • Author Footnotes
    * This work was supported by the Marie Curie Sklodowska program of the European Union.
    This article contains supplemental material.
    § Current affiliation of TM: German Cancer Research Center, Heidelberg, Germany.
Open AccessPublished:May 24, 2017DOI:https://doi.org/10.1074/mcp.M116.064048
      Reduction and alkylation of cysteine residues is part of virtually any proteomics workflow. Despite its frequent use, up to date no systematic investigation of the impact of different conditions on the outcome of proteomics studies has been performed. In this study, we compared common reduction reagents (dithiothreitol, tris-(2-carboxyethyl)-phosphine, and β-mercaptoethanol) and alkylation reagents (iodoacetamide, iodoacetic acid, acrylamide, and chloroacetamide). Using in-gel digests as well as SAX fractionated in-solution digests of cytosolic fractions of HeLa cells, we evaluated 13 different reduction and alkylation conditions resulting in considerably varying identification rates. We observed strong differences in offsite alkylation reactions at 7 amino acids as well as at the peptide N terminus, identifying single and double adducts of all reagents. Using dimethyl labeling, mass tolerant searches, and synthetic peptide experiments, we identified alkylation of methionine residues by iodine-containing alkylation reagents as one of the major factors for the differences. We observed differences of more than 9-fold in numbers of identified methionine-containing peptide spectral matches for in-gel digested samples between iodine- and noniodine-containing alkylation reagents. This was because of formation of carbamidomethylated and carboxymethylated methionine side chains and a resulting prominent neutral loss during ESI ionization or in MS/MS fragmentation, strongly decreasing identification rates of methionine-containing peptides. We achieved best results with acrylamide as alkylation reagent, whereas the highest numbers of peptide spectral matches were obtained when reducing with dithiothreitol and β-mercaptoethanol for the in-solution and the in-gel digested samples, respectively.
      Mass spectrometry (MS) has become one of the major techniques for the qualitative and quantitative analysis of proteins. Because the introduction of electrospray ionization (ESI) and matrix-assisted laser desorption ionization (MALDI)
      The abbreviations used are: MALDI, matrix-assisted laser desorption ionization; IAA, iodoacetamide; IAC, iodoacetic acid; AA, acrylamide; CAA, chloroacetamide; DTT, dithiothreitol; TCEP, tris-2(-carboxyethyl)-phosphine; BME, β-mercaptoethanol; NEM, N-ethylmaleimide; MMTS, methyl methanethiosulfonate; PSM, peptide spectrum matches; FASP, filter aided sample preparation; can, acetonitrile; FA, formic acid; SAX, strong anion exchange; TEAB, triethylammoniumbicarbonate.
      1The abbreviations used are: MALDI, matrix-assisted laser desorption ionization; IAA, iodoacetamide; IAC, iodoacetic acid; AA, acrylamide; CAA, chloroacetamide; DTT, dithiothreitol; TCEP, tris-2(-carboxyethyl)-phosphine; BME, β-mercaptoethanol; NEM, N-ethylmaleimide; MMTS, methyl methanethiosulfonate; PSM, peptide spectrum matches; FASP, filter aided sample preparation; can, acetonitrile; FA, formic acid; SAX, strong anion exchange; TEAB, triethylammoniumbicarbonate.
      (
      • Karas M.
      • Hillenkamp F.
      Laser desorption ionization of proteins with molecular masses exceeding 10000 daltons.
      ,
      • Fenn J.B.
      • Mann M.
      • Meng C.K.
      • Wong S.F.
      • Whitehouse C.M.
      Electrospray ionization for mass-spectrometry of large biomolecules.
      ), which paved the way for modern mass spectrometry-based proteomics, the power of mass spectrometric analyses has improved continuously. The performance of chromatography systems and mass spectrometers, as well as the development of novel sample preparation protocols are the main contributing reasons. Bottom-up proteomics is the most common method for protein identification and characterization by mass spectrometry. It is based on the enzymatic digestion of proteins followed by the subsequent analysis of proteolytic peptides.
      In current bottom-up proteomics strategies, all sample preparation protocols have several key elements in common: (1) cells or tissues are lyzed and proteins are extracted; (2) proteins are reduced in order to break disulfide bonds; (3) proteins are alkylated to covalently modify cysteine SH-groups, preventing them from forming unwanted novel disulfide bonds; and (4) proteins are enzymatically digested to peptides. Dependent on the complexity of the sample and the goal of the analysis, samples are frequently fractionated on the protein- or the peptide-level. One common approach is the separation of proteins according to their mass using SDS-PAGE followed by in-gel digestion (
      • Shevchenko A.
      • Wilm M.
      • Vorm O.
      • Mann M.
      Mass spectrometric sequencing of proteins from silver stained polyacrylamide gels.
      ). Alternatively, proteins are digested in-solution followed by the fractionation of peptides using isoelectric focusing or chromatography-based approaches (
      • Manadas B.
      • Mendes V.M.
      • English J.
      • Dunn M.J.
      Peptide fractionation in proteomics approaches.
      ). If specific modifications are to be analyzed, enrichment methods are commonly used; for example, phosphorylated peptides are enriched using antibodies or metal-ion affinity resins (
      • Thingholm T.E.
      • Jensen O.N.
      • Larsen M.R.
      Analytical strategies for phosphoproteomics.
      ).
      Cell lysis, protein purification, proteolytic digestion, and peptide fractionation have been optimized in several studies (e.g. (
      • Manadas B.
      • Mendes V.M.
      • English J.
      • Dunn M.J.
      Peptide fractionation in proteomics approaches.
      ,
      • Winter D.
      • Steen H.
      Optimization of cell lysis and protein digestion protocols for the analysis of HeLa S3 cells by LC-MS/MS.
      ,
      • Leon I.R.
      • Schwammle V.
      • Jensen O.N.
      • Sprenger R.R.
      Quantitative Assessment of In-solution Digestion Efficiency Identifies Optimal Protocols for Unbiased Protein Analysis.
      ,
      • Wisniewski J.R.
      • Zougman A.
      • Mann M.
      Combination of FASP and StageTip-Based Fractionation Allows In-Depth Analysis of the Hippocampal Membrane Proteome.
      )). The reduction and alkylation step of proteins, however, has surprisingly not been systematically investigated up to date, despite its use in virtually any proteomic experiment (excluding experiments investigating disulfide bridges or cysteine modifications, for example (
      • Sokolowska I.
      • Gawinowicz M.A.
      • Ngounou Wetie A.G.
      • Darie C.C.
      Disulfide proteomics for identification of extracellular or secreted proteins.
      )).
      The most common reducing reagent used in proteomics experiments, dithiothreitol (DTT), was introduced in 1964, as a more stable and less toxic alternative to commonly used reducing reagents such as glutathione or β-mercaptoethanol (
      • Cleland W.W.
      Dithiothreitol new protective reagent for SH groups.
      ). The second most common reducing reagent used by the community, tris-2(-carboxyethyl)-phosphine (TCEP), was introduced in 1999 (
      • Getz E.B.
      • Xiao M.
      • Chakrabarty T.
      • Cooke R.
      • Selvin P.R.
      A comparison between the sulfhydryl reductants tris(2-carboxyethyl)phosphine and dithiothreitol for use in protein biochemistry.
      ). In this study, the authors showed that TCEP is less susceptible to oxidation than DTT and superior in conserving enzymatic activity using myosin as an example. Finally, β-mercaptoethanol (BME) is frequently used as reducing reagent among molecular biologists, for example, as part of the standard buffer for SDS-PAGE sample preparation (Laemmli buffer (
      • Laemmli U.K.
      Cleavage of structural proteins during assembly of head of bacteriophage-T4.
      )), whereas it is rarely used in sample preparation for mass spectrometry-based proteomics.
      After reduction of disulfide bridges, alkylation of the free SH-groups is usually performed by iodoacetamide (IAA, (
      • Shevchenko A.
      • Wilm M.
      • Vorm O.
      • Mann M.
      Mass spectrometric sequencing of proteins from silver stained polyacrylamide gels.
      )). Because of a variety of side reactions that have been observed for IAA (
      • Boja E.S.
      • Fales H.M.
      Overalkylation of a protein digest with iodoacetamide.
      ) several structurally related alternatives have been introduced, including iodoacetic acid (IAC), chloroacetamide (CAA), and acrylamide (AA), as well as the structurally not related reagents N-ethylmaleimide (NEM), methyl methanethiosulfonate (MMTS), and 4-vinylpyridine (
      • Sechi S.
      • Chait B.T.
      Modification of cysteine residues by alkylation. A tool in peptide mapping and protein identification.
      ,
      • Liu F.
      • Fitzgerald M.C.
      Large-Scale Analysis of Breast Cancer-Related Conformational Changes in Proteins Using Limited Proteolysis.
      ,
      • Paulech J.
      • Solis N.
      • Cordwell S.J.
      Characterization of reaction conditions providing rapid and specific cysteine alkylation for peptide-based mass spectrometry.
      ). Early studies performed with standard protein digests and MALDI mass spectrometry did not identify differences concerning the performance of the different alkylation reagents (
      • Sechi S.
      • Chait B.T.
      Modification of cysteine residues by alkylation. A tool in peptide mapping and protein identification.
      ), whereas later studies identified several side products of the carbamylation reaction using IAA (
      • Boja E.S.
      • Fales H.M.
      Overalkylation of a protein digest with iodoacetamide.
      ,
      • Lapko V.N.
      • Smith D.L.
      • Smith J.B.
      Identification of an artifact in the mass spectrometry of proteins derivatized with iodoacetamide.
      ,
      • Kruger R.
      • Hung C.W.
      • Edelson-Averbukh M.
      • Lehmann W.D.
      Iodoacetamide-alkylated methionine can mimic neutral loss of phosphoric acid from phosphopeptides as exemplified by nano-electrospray ionization quadrupole time-of-flight parent ion scanning.
      ,
      • Nielsen M.L.
      • Vermeulen M.
      • Bonaldi T.
      • Cox J.
      • Moroder L.
      • Mann M.
      Iodoacetamide-induced artifact mimics ubiquitination in mass spectrometry.
      ). Based on these studies, one would expect that the abovementioned alternative alkylation reagents (IAC, AA, and CAA) should be used frequently to minimize the number of chemical artifacts. The authors have the impression, however, that the combination of DTT and IAA is nevertheless the most frequently used combination in the field of mass spectrometry-based proteomics (supplemental Fig. S1 and supplemental Table S1).
      In this study, we systematically evaluated reduction and alkylation of proteins using three reducing agents (DTT, TCEP, and BME) in combination with four alkylation agents (IAA, IAC, AA, and CAA). We tested these conditions using strong anion exchange (SAX) fractionated in-solution digests and in-gel digested fractions of samples enriched for cytosolic proteins of HeLa cells.

      DISCUSSION

      In the current study, we show that reduction and alkylation conditions can have a strong impact on the identification of peptides because of unspecific alkylation using an acetone precipitated cytosolic fraction of HeLa cells, re-solubilized in 0.1 m TRIS-HCl/4% SDS at 95 °C. Interestingly, for in-gel and in-solution digestion of proteins, different combinations of reduction and alkylation reagent were found to give the best results. For the reducing reagents, surprisingly, TCEP and BME, the substances used least frequently by the community (in 21 and 0% of articles investigated, respectively, supplemental Fig. S1, supplemental Table S1), resulted in highest numbers of peptide and protein identifications for the in-gel digested samples. A likely reason is that they induced the lowest number of unspecific modifications in combination with the respective alkylation reagents. This could be because of DTT making either the side chains of the amino acids more susceptible to modification or by generating more reactive intermediates with the alkylation reagents as compared with TCEP or BME. We were, however, not able to detect any evidence that the reducing reagent itself resulted in unspecific modifications of peptides (e.g. by finding adducts matching its mass). For the in-gel digests, TCEP did not perform well for the identification of cysteine-containing peptides. This may be because of the removal of TCEP before adding the alkylation reagents. It is common practice to perform reduction and alkylation in the same step when using TCEP as it was the case in our in-solution digests (because we did not remove TCEP before addition of the alkylation reagent). It may therefore increase performance for in-gel digested samples if a mixture of TCEP and the alkylation reagent is used. For the experimental setup used in this study, we recommend BME for reducing proteins in SDS-PAGE gels. For in-solution digests, DTT, BME, and TCEP performed equally well and the choice should be made based on potential preferences in the alkylation reagents as AA seems to work better with DTT and BME, whereas CAA performs better in combination with TCEP. This was especially the case regarding the alkylation efficiency of cysteine-containing peptides, which may introduce inconsistencies, for example, in peptide quantification. In general, the iodine-containing alkylation reagents (IAA and IAC) resulted in the worst identification rates irrespective of the digestion condition, or reducing reagent, and should therefore be avoided. We compared in this study alkylation reagents that are structurally related. There are, however, also other iodine-free reagents, such as N-ethylmaleimide (NEM), methyl methanethiosulfonate (MMTS), or 4-vinylpyridine, which are structurally not related. These compounds will probably also result in lower numbers of side reactions compared with the iodine-containing reagents.
      Surprisingly, for both digestion strategies, the samples that were neither reduced nor alkylated resulted in good numbers of spectra and protein identifications despite the total lack of cysteine-containing peptides. This shows that disulfide bridges do not seem to hamper the proteolytic cleavage by trypsin significantly as we also could not see an increase in missed cleavage sites in these samples (data not shown). The reproducibility between the single replicates for the untreated samples ranged among the highest compared with the other conditions, further exemplifying the negative effect of random unspecific modifications on the quality of sample preparation. The complete lack of cysteine-containing peptides in these data sets indicated an efficient formation of disulfide bridges among proteins or peptides and underlines the necessity of efficient reduction and alkylation in sample preparation for proteomics experiments.
      For the in-solution digested samples the percentage of identified, nonspecifically modified peptides was lower and alkylation efficiencies better compared with the in-gel digested samples. This is most likely because of the more efficient removal of chemicals by FASP and the fact that the reduction and alkylation chemicals must diffuse into the gel pieces, which may alter accessibility of the proteins. Reduction and alkylation before gel electrophoresis would therefore most likely improve reproducibility, as it allows for better accessibility of the proteins and immediate separation of the proteins from the reactive chemicals during electrophoresis. Over all, we observed significantly higher differences in spectra identification rates between the alkylation reagents in the in-gel digests compared with the in-solution digests. There are several factors that may be responsible for this: (1) we used higher concentrations for the alkylation reagents in the gel (20 mm for the in-solution digests and 55 mm for the in-gel digests); (2) the alkylation reactions were quenched by addition of the respective reducing reagents for the in-solution digests, but not the in-gel digests; (3) because of the FASP strategy applied for the in-solution digests reactive chemicals were removed immediately after performing the reaction. Therefore, for the in-gel digests, unspecific reactions could proceed for a longer time, which also explains the higher degree of modified peptide N termini in the data set as this can only happen after tryptic cleavage. These factors influence the reaction kinetics of the alkylation reactions which is probably a major reason for the differences observed. If other protocols are applied (e.g. by different reagent conditions, altered incubation times, or different buffer systems) the differences observed may differ significantly. Additionally, the in-solution digests were analyzed with 30 min gradients whereas the in-gel digests were analyzed with 60 min gradients. This resulted in ∼100,000 spectra for the whole in-solution data set and ∼35,000 spectra for the in-gel data set, respectively. As the in-gel data set was only derived from ∼1/5 of the sample the average instrument time per number of peptides contained in the sample was higher by a factor of almost 2-fold, making it more likely to fragment and identify low abundant species in the in-gel digests. For SAX on the other hand, because of incomplete separation of highly abundant unmodified peptides between the different fractions, the effect of the alkylation reagents might have been masked because the low abundant derivatized peptide species were not fragmented at all.
      When we investigated the data sets for unwanted side reactions, searches of the in-solution digests, considering multiple variable modifications, produced in almost all cases lower numbers of PSMs compared with the searches without offsite alkylation, which we performed initially. This was most likely because of the increased cutoff for peptide acceptance in order to maintain an FDR of 1% with the higher numbers of variable modifications (and therefore a strong increase in search space). This leads to lower total numbers of PSMs, even though a high number of modified peptides is identified. Therefore, it is difficult to assess how far the identified offsite alkylations can compensate for the lack of identified PSMs in the initial data sets of the in-solution digests. For the in-gel digests, searching for offsite alkylation resulted in greatly increased numbers of peptide identifications for the iodine-containing reagents almost reaching PSM numbers of the iodine-free alkylation reagents. For the latter, however, including the offsite alkylation in the searches always reduced the number of identified peptides presenting a similar picture as for the in-solution digests. For the samples alkylated with iodine-containing reagents, the searches including offsite alkylation where never able to match the numbers of unique peptide sequences obtained in the searches without any offsite alkylation. Even though resulting in almost twice the numbers of PSMs they stayed significantly below the iodine-free alkylation reagents. This is probably because of high abundant modified peptides preventing fragmentation of lower abundant unmodified species. It is therefore in our eyes not reasonable to continue using iodine-containing alkylation reagents and trying to compensate for their unspecific side reactions by altering the database search strategy.
      When we investigated identification efficiencies in our data sets, we realized that it was possible to increase identification rates tremendously for the in-gel digests (from 24% in case of DTT/IAA to 54% for BME/CAA). Given that currently the majority of laboratories still work with DTT/IAA and it was recently estimated that on average only 25% of the spectra are identified in proteomics experiments (
      • Griss J.
      • Perez-Riverol Y.
      • Lewis S.
      • Tabb D.L.
      • Dianes J.A.
      • del-Toro N.
      • Rurik M.
      • Walzer M.
      • Kohlbacher O.
      • Hermjakob H.
      • Wang R.
      • Vizcaino J.A.
      Recognizing millions of consistently unidentified spectra across hundreds of shotgun proteomics data sets.
      ,
      • Vizcaino J.A.
      • Csordas A.
      • del-Toro N.
      • Dianes J.A.
      • Griss J.
      • Lavidas I.
      • Mayer G.
      • Perez-Riverol Y.
      • Reisinger F.
      • Ternent T.
      • Xu Q.W.
      • Wang R.
      • Hermjakob H.
      2016 update of the PRIDE database and its related tools.
      ) it may be sufficient to simply change reduction and alkylation conditions to increase identification efficiency in proteomics experiments considerably.
      Surprisingly, one of the amino acids which was affected most in our data sets was methionine. So far, in studies which dealt with the investigation of unspecific modifications by alkylation in proteomic sample preparation, alkylated methionine was not detected at all. In Unimod (www.unimod.org), which is a database containing modifications used for database searching in proteomics experiments, carbamidomethylation or carboxymethylation at methionine is not even defined. To our knowledge, there are only 2 studies which mentioned alkylation at methionine and in both the alkylation was performed with IAA. One dealt with the analysis of an intact protein (
      • Lapko V.N.
      • Smith D.L.
      • Smith J.B.
      Identification of an artifact in the mass spectrometry of proteins derivatized with iodoacetamide.
      ) and determined the mass of the carbamidomethylation at methionine to be 58 Da, whereas the second study was focused on the analysis of peptides (
      • Kruger R.
      • Hung C.W.
      • Edelson-Averbukh M.
      • Lehmann W.D.
      Iodoacetamide-alkylated methionine can mimic neutral loss of phosphoric acid from phosphopeptides as exemplified by nano-electrospray ionization quadrupole time-of-flight parent ion scanning.
      ) and identified the modification to be 57 Da. We confirmed in our experiments the mass value of 57 Da. Interestingly, we had the impression that the iodine-containing alkylation reagents seem to preferentially alkylate methionine in the synthetic peptide we used rather than the peptide N terminus, which we found to be alkylated most frequently in other peptides. In the experiments with the synthetic peptide, we only found the methionine alkylated peptide (resulting in a neutral loss of 105 Da or 48 Da relative to the unmodified molecular ion) but no additional offsite alkylation on this peptide at all. Neither on the one alkylated at the methionine, nor on the non-alkylated in the same sample. If we, however, oxidized the methionine in the peptide with H2O2 before performing the alkylation reaction, we observed prominent offsite alkylation at other residues. It therefore seems that the alkylation at methionine prevents the other residues in the peptide to be alkylated because we applied the alkylation reagent in a vast excess for this experiment and depletion of the reagent by the methionine residues is therefore highly unlikely. Along this line, also in the general data sets, we observed in the majority singly offsite alkylated peptides. This could be because of a change in the charge of the peptide or maybe interactions of the alkylated residue with other side chains that would usually be susceptible to modification.

      CONCLUSION

      Our systematic comparison of reduction and alkylation procedures shows that the reagents used can have a strong impact on the outcome of a proteomic experiment. Reduction reagents do have an effect; it is, however, rather moderate compared with the alkylation reagents as only the latter result in unspecific modifications of amino acids. Basically, all functional groups can react with the used alkylation reagents with different efficiencies. Especially iodine-containing reagents are prone to unspecific side reactions and should be completely avoided. The non-iodine-containing reagents result in similar cysteine alkylation efficiencies but markedly increased performance in the identification of peptides. To maximize performance and minimize unwanted side reactions, we suggest the usage of DTT and AA for in-solution digests and BME with AA for in-gel digests.

      DATA AVAILABILITY

      The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE (35) partner repository (https://www.ebi.ac.uk/pride/archive/) with the data set identifier PXD005183.

      Acknowledgments

      We thank the Marie Curie Sklodowska program of the European Union for financial support, Wolf Dieter Lehmann for the synthetic peptide and valuable discussions, Sven Milker for computational support, and Edgar Kaade for help with MALDI-MS analyses.

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