Stoichiometry of Saccharomyces cerevisiae Lysine Methylation

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Stoichiometry of Saccharomyces cerevisiae Lysine Methylation: Insights into Non-histone Protein Lysine Methyltransferase Activity Gene Hart-Smith, Samantha Z Chia, Jason K. K. Low, Matthew J. McKay, Mark P Molloy, and Marc R. Wilkins J. Proteome Res., Just Accepted Manuscript • DOI: 10.1021/pr401251k • Publication Date (Web): 12 Feb 2014 Downloaded from http://pubs.acs.org on February 13, 2014

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Journal of Proteome Research

Stoichiometry of Saccharomyces cerevisiae Lysine Methylation: Insights into Non-histone Protein Lysine Methyltransferase Activity Gene Hart-Smith,1* Samantha Z. Chia,1 Jason K.K. Low,1 Matthew J. McKay,2 Mark P. Molloy,2 Marc R. Wilkins1* 1

NSW Systems Biology Initiative, University of New South Wales, Sydney, New South Wales

2052, Australia 2

Australian Proteome Analysis Facility, Macquarie University, Sydney, NSW 2109, Australia.

Address reprint requests to Marc R. Wilkins, NSW Systems Biology Initiative, University of New South Wales, Sydney, New South Wales 2052, Australia. Phone: +61-2-9385-3633, Fax: +61-29385-3950, E-mail: [email protected]; Gene Hart-Smith, NSW Systems Biology Initiative, University of New South Wales, Sydney, New South Wales 2052, Australia. Phone: +61-2-93853857, Fax: +61-2-9385-3950, E-mail: [email protected]

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Abstract 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Post-translational lysine methylation is well established as a regulator of histone activity; however it is emerging that these modifications are also likely to play extensive roles outside of the histone code. Here we obtain new insights into non-histone lysine methylation and protein lysine methyltransferase (PKMT) activity by elucidating absolute stoichiometries of lysine methylation, using mass spectrometry and absolute quantification (AQUA), in wild-type and 5 PKMT gene deletion strains of Saccharomyces cerevisiae. By analyzing 8 sites of methylation in 3 non-histone proteins – elongation factor 1-α (EF1α), elongation factor 2 (EF2) and 60S ribosomal protein L42A/B (Rpl42ab) – we find that: production of preferred methylation states on individual lysine residues is commonplace, and likely occurs through processive PKMT activity; Class I PKMTs can be associated with processive methylation; lysine residues are selectively methylated by specific PKMTs; and lysine methylation exists over a broad range of stoichiometries. Together these findings suggest that specific sites and forms of lysine methylation may play specialized roles in the regulation of non-histone protein activity. We also uncover new relationships between two proteins previously characterized as PKMTs, SEE1 and EFM1, in EF1α methylation, and show that past characterizations of EFM1 as having direct PKMT activity may require reinterpretation. Key words: lysine methylation, stoichiometry, absolute quantification (AQUA), protein lysine methyltransferases, Saccharomyces cerevisiae, elongation factors, ribosomal proteins


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Introduction Recent years have witnessed a growing appreciation for the importance of lysine methylation as a post-translation modification (PTM). This class of PTM occurs on the ε-amino groups of lysine residues, and has been identified in three forms: mono-, di- and tri-methyllysine (MML, DML and TML respectively). In histone proteins, these modifications are now well established as key regulators of the transcriptional activity or inactivity of chromatin domains.1-2 Recent broad-scale characterizations of these modifications have also indicated that they play an extensive role in nonhistone protein activity,3-4 and lysine methylation has now been linked to a variety of cellular processes including RNA processing, ribosome assembly, protein nuclear trafficking and signalling.5-6 Sites of lysine methylation have, for example, been discovered on various ribosomal proteins,3-4, 7-12 whilst a number of elongation factors (EFs) – non-ribosomal proteins involved in the regulation of the ribosomal elongation cycle – have also been found to contain these modifications.34, 13-15

Though an instructive view of the landscape of lysine methylation is beginning to emerge, the functional impacts of these modifications on non-histone protein activity remain largely unknown. To better understand the roles of lysine methylation outside of the histone code, one avenue of investigation is to elucidate how the different forms of lysine methylation are produced and regulated by the enzymes responsible for their catalysis: protein lysine methyltransferases (PKMTs). The majority of PKMTs can be grouped into one of two distinct families based upon their conserved domains: the SET domain family,16 or the 7 β-strand family (PKMTs in the latter group are referred to as ‘Class I’).17-18 When these PKMTs catalyze the formation of multiple methylations on single lysine residues, it has been proposed that this can occur through two differing mechanisms: a processive mechanism, whereby successive rounds of methylation proceed without dissociation of the substrate from the enzyme; or a distributive mechanism, whereby the substrate and enzyme dissociate after each cycle of methylation. To date, all known processive PKMTs have been shown to carry a SET domain,19-22 though evidence also exists to suggest that other SET domain PKMTs ACS Paragon Plus Environment

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can operate via a distributive mechanism.23-26 Only two Class I PKMTs have been analyzed in 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

relation to their processivity, Dot1 and METTL-21D, and both have been shown to be distributive enzymes.27-28 In histone proteins, investigations into the PKMTs responsible for methylating specific lysine residues, and the mechanisms by which they operate, have provided insights into how different forms of lysine methylation can impart their influence. PKMTs that methylate substrates via a processive mechanism favour the production of specific forms of lysine methylation (e.g. TML in favour of DML or MML); various lines of evidence indicate that in histones, the specific forms of methylation generated at individual lysine residues by processive PKMTs have highly specialized biological functions.29-30 In contrast, PKMTs that operate via a distributive mechanism produce broader distributions of the different forms of lysine methylation; studies into Dot1 suggest that the multiple methylation states generated via its distributive mechanism are functionally redundant.27 In non-histone proteins it can be envisaged that the site specificities of PKMTs, and the mechanisms by which they operate, should carry similar implications regarding the functional roles of the different forms of lysine methylation. However our understanding of the PKMTs responsible for the methylation of specific non-histone lysine residues is still in its infancy,31 and little is currently known of the mechanisms by which these PKMTs operate, with METTL-21D being the only non-histone PKMT to have been analyzed in relation to its processivity.23 The present study aims to provide new insights into the relationships between non-histone proteins and PKMTs, and the mechanisms by which these PKMTs operate, through the elucidation of absolute stoichiometries of lysine methylation sites in wild-type and PKMT gene deletion strains of Saccharomyces cerevisiae. Existing knowledge on the absolute stoichiometries of lysine methylation sites is scarce. Though various studies have attempted to estimate the relative fractional occupancies of MML, DML or TML on individual lysine residues using mass spectrometry (MS) datae.g 24, 27-28, 32-33, these studies have been limited by the inherently non-quantitative nature of MS, which has precluded the attainment of absolute stoichiometric information.


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By obtaining such data, PKMT processivities can be investigated through a consideration of 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

the different stoichiometric levels of lysine methylation expected for each possible mechanism of PKMT activity.22,

27

For example in the processive formation of TML, the concentrations of the

reaction intermediates DML and MML should not be expected to exceed the PKMT active site concentration; a distributive formation of TML, on the other hand, should be expected to result in the formation of DML and MML at concentrations that exceed the PKMT active site concentration. To determine absolute stoichiometry levels for PTMs with high accuracy and precision, the absolute quantification (AQUA) strategy – which corrects for differing peptide ionization efficiencies during MS34-35 – is regarded as the gold standard method.e.g. 36 In the work reported here, the AQUA strategy – utilised in conjunction with both MaxQuant derived intensity data obtained from an Orbitrap Velos LTQ mass spectrometer, and selected-reaction-monitoring (SRM) on a 5500QTrap mass spectrometer – is applied towards the analysis of sites of lysine methylation for the first time. The absolute stoichiometries of 8 methylated lysine residues from 3 known Sacchoromyces cerevisiae PKMT substrates, elongation factor 1-α (EF1α), elongation factor 2 (EF2) and 60S ribosomal protein L42-A/B (Rpl42ab), are quantified in this manner in wild-type and PKMT gene deletion yeast strains. Single gene deletion strains of the following proteins are used: SEE1, EFM1, EFM2, RKM3 and RKM4. Each of the proteins deleted in these strains have verified or hypothesized PKMT activity upon EF1α, EF2 or Rpl42ab.

Experimental Yeast strains Saccharomyces cerevisiae strain BY4741 (MATa his3∆1 leu2∆0 ura3∆0 met15∆0) was used in this study (#YSC1052, Open Biosystems). For PKMT gene deletion analyses, single gene deletion mutants were obtained from the Saccharomyces cerevisiae Genome Deletion Project (Euroscarf, Frankfurt, Germany). Yeasts were grown at 30oC in YEPD media containing 2% (w/v) glucose, 2% (w/v) bactopeptone and 1% (w/v) yeast extract, and cells were harvested during mid-log phase


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growth (0.8 -1.0 OD600). Biological triplicates of each wild-type and gene deletion mutant strain 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

were prepared and analyzed.

Synthetic Peptides Synthetic isotopically labeled and quantified peptides were obtained for methylated peptides and unmethylated proteotypic peptides associated with EF1α, EF2 and Rpl42ab (SpikeTides TQL, JPT Peptide Technologies, Berlin, Germany; see Table 1), and used as internal standards (see Sample Preparation below, and Supporting Information: Summary of Standard Additions). Each synthetic labeled peptide contained an attached chemical tag; tags were cleaved during trypsin digestion (see Sample Preparation, below). With the exception of ASLFAQGK*, evidence for unlabeled versions of each synthetic peptide could be found in MS analyses of wild-type or overexpressed EF1α, EF2 or Rpl42ab tryptic digest samples; the presence of these peptides were reconfirmed in the EF1α, EF2 and Rpl42ab trypsin digest samples subjected to subsequent analysis. (See also Supporting Information: EF1α Overexpression and Purification and Tandem Mass Spectra associated with Methylated Peptide Characterizations). To ensure that all peptides associated with methylated residues of interest were accounted for, additional methylated peptides with differing numbers of missed cleavages to those of Table 1 were considered. Evidence for the presence of these peptides was searched for in each sample subjected to MS; that is if peptides were not identified following sequence database searching (see below), peptides eluting at theoretical m/z values corresponding to methylated peptides were manually searched for using extracted ion chromatograms (XICs). No evidence could be found for methylated peptides other than those listed in Table 1. Peptides associated with the amino acid sequences IGGIGTVPVGR, STLTDSLVQR and CKHFELGGEK were respectively used to quantify total EF1α, EF2 and Rpl42ab protein abundances (see below). Justifications for the suitabilities of the peptides listed in Table 1 for this


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purpose are provided in the Supporting Information (Analyses of Amino Acid Sequences associated 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

with Unmodified Peptides). Table 1. Synthetic labeled EF1α, EF2 and Rpl42ab peptides used in the present study; the methylated lysine residues that they are associated with; their isotopic labels; and their monoisotopic masses. MML, DML and TML are marked K*, K** and K*** respectively. Labeled amino acid residues are underlined. Alkylated cysteine residues are marked C`. ‡

No evidence for non-synthetic ASLFAQGK* was observed; the labeled version of this peptide was only used in the

quantification of ASLFAQGK*R cleavages (see Supporting Information: Tryptic Cleavages of Synthetic Labeled Peptides with Internal Lysine Residues).

Protein

Peptide

Methylated Residue

Label

Monoisotopic mass (Da)

EF1α

STTTGHLIYK*

K30

13

C(6) 15N(2)

1140.6252

GITIDIALWK***FETPK

K79

13

C(6) 15N(2)

1781.0219

NVSVK**EIR

K316

13

C(6) 15N(4)

981.5847

NVSVK*EIR

K316

13

C(6) 15N(4)

967.5691

KLEDHPK*

K390

13

C(6) 15N(1)

886.4986

KLEDHPK*FLK

K390

13

C(6) 15N(2)

1275.7432

IGGIGTVPVGR

n/a

13

C(6) 15N(4)

1034.6112

LVEGLK***R

K509

13

C(6) 15N(4)

865.5623

LVEGLK**R

K509

13

C(6) 15N(4)

851.5469

LVEGLK*R

K509

13

C(6) 15N(4)

837.5312

DDFK**AR

K613

13

C(6) 15N(4)

788.4057

DDFK*AR

K613

13

C(6) 15N(4)

774.3900

STLTDSLVQR

n/a

13

C(6) 15N(4)

1128.6014

ASLFAQGK*‡

K40

13

C(3) 15N(1)

838.4670

ASLFAQGK*R

K40

13

C(6) 15N(4)

1000.5693

QSGFGGQTK*PVFHK

K55

13

C(6) 15N(2)

1538.8086

KQSGFGGQTK*PVFHK

K55

13

C(6) 15N(2)

1666.9036

QSGFGGQTK*PVFHKK

K55

13

C(6) 15N(2)

1666.9036

HFELGGEK

n/a

13

C(6) 15N(2)

923.4593

C`KHFELGGEK

n/a

13

C(6) 15N(2)

1211.5849

EF2

Rpl42ab


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Sample Preparation Saccharomyces cerevisiae cells were lysed, and proteins were separated using 1D SDSPAGE and stained with Biosafe Coomassie G250 (Bio-Rad) following techniques described previously.15 Polyacrylamide gel slices associated with EF1α, EF2 and Rpl42ab were removed and prepared independently. Gel slices were destained, reduced and alkylated following the procedure described by Shevchenko et al.37 Synthetic labeled peptides were then added as internal standards; the specific peptides and molar quantities used for each sample are summarised in Table S2. Samples were made up to 120 µL using 0.1 M NH4HCO3, and 40 ng of trypsin (Promega) was added to each gel slice; samples were incubated for 16 h at 37oC. Each digest solution was removed to a new microfuge tube and the gel slices treated with the following solutions sequentially for 30 min each: 80 µL 0.1% (v/v) formic acid/67% (v/v) acetonitrile; and 80 µL 100% acetonitrile. The pooled digest and peptide extraction solutions for each sample were then dried (Savant SPD1010, Thermofisher Scientific) before resuspending in 20 µL of 0.1% (v/v) formic acid. Additional samples were prepared to test the precision of internal standard additions; to explore the propensities for synthetic labeled peptides with internal (methylated or unmethylated) lysine residues to undergo tryptic cleavages at these sites; and to explore the relative ionization efficiencies of the synthetic labeled peptides. Full details regarding these samples are provided in the Supporting Information.

Orbitrap Mass Spectrometry and MaxQuant Analysis For each replicate of EF1α, EF2 and Rpl42ab prepared for quantitative MS analysis, 0.4 µL, 1.0 µL and 5.0 µL of the digest solutions were respectively loaded for LC-MS/MS analysis using an LTQ Orbitrap Velos Pro (Thermo Electron, Bremen, Germany) hybrid linear ion trap and Orbitrap mass spectrometer. Peptides were separated by nano-LC using an UltiMate 3000 HPLC and autosampler system (Dionex, Amsterdam, Netherlands), and eluting peptides were ionized using positive ion mode nano-


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ESI following experimental procedures described previously.38 MS and MS/MS were performed 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

using the following parameters: Survey scans m/z 350–2000 were acquired in the Orbitrap (resolution = 30 000 at m/z 400, with an initial accumulation target value of 1,000,000 ions in the linear ion trap; lock mass was applied to polycyclodimethylsiloxane background ions of exact m/z 445.1200 and 429.0887). Up to the 15 most abundant ions (>5000 counts) with charge states of >+2 were sequentially isolated and fragmented via collision induced dissociation (CID) with an activation q = 0.25, an activation time of 30 ms, normalized collision energy of 30% and at a target value of 10 000 ions; fragment ions were mass analyzed in the linear ion trap. To ensure that peptide carryover between samples was minimal, 3 blank injections were run between each digest sample. Blanks run before each digest sample were inspected for the presence of peptides of interest, which revealed that peptide carryover was negligible. For peptide quantification, MaxQuant (version 1.1.1.36) was run using standard parameters;39 intensity values for doubly charged peptides of interest were extracted from the allpeptides.txt output (with the exception of data for TML at K79 of EF1a, for which values were extracted for triply charged peptides). For peptides that were not amenable to MaxQuant analysis (see main text), XICs were instead used for peptide quantification. XICs were obtained using Thermo Xcalibur 2.2 SP1.48; mass ranges were set as the theoretical m/z for the monoisotopic peak of the peptide ion of interest ±4 ppm. To calculate absolute stoichiometries for individual lysine methylation sites, the following pieces of data were obtained: (1) the absolute abundances of each protein being investigated, and (2) the absolute abundances of each form of the methylated lysine residues being investigated. For (1), absolute abundances for EF1α, EF2 and Rpl42ab were obtained by quantifying their respective unmethylated proteotypic peptides of interest (i.e. unlabeled versions of the unmethylated peptides of Table 1). For Rpl42ab, for example, where χsubscript refers to the absolute abundance of the subscripted protein or peptide, MQsubscript refers to the MaxQuant derived intensity value for the subscripted peptide, and labeled amino acids are underlined, this was performed as follows:


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χRpl42ab = [χHFELGGEK × (MQHFELGGEK / MQHFELGGEK)] + [χC’KHFELGGEK × (MQ 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

C’KHFELGGEK

/ MQ

C’KHFELGGEK)]

For (2), absolute abundances for individual methylated residues were determined in an analogous manner to the above using the methylated peptides of Table 1. For K55 of Rpl42ab, for example, this was performed as follows:

χRpl42ab_K55 = [χKQSGFGGQTK*PVFHK × (MQKQSGFGGQTK*PVFHK / MQKQSGFGGQTK*PVFHK)] + [χQSGFGGQTK*PVFHK × (MQQSGFGGQTK*PVFHK

/

MQQSGFGGQTK*PVFHK)]

+

[χQSGFGGQTK*PVFHKK

×

(MQQSGFGGQTK*PVFHKK

/

MQQSGFGGQTK*PVFHKK)]

For amino acid sequences observed across multiple peptides (e.g. peptides containing 0 and 1 missed cleavages), such as those described in the above examples, tryptic cleavages of synthetic labeled peptides with internal (methylated or unmethylated) lysine residues during sample preparation had to be considered. Experiments were conducted to determine the propensities for these cleavages to occur; these are decribed in detail in the Supporting Information. The impacts of these cleavages on the absolute abundances of individual peptides are summarised in Table S1. Methylation stoichiometry was determined by calculating the ratio between the absolute abundance of a given methylated residue and the absolute abundance of the protein associated with the residue. For example, the absolute fractional occupancy of methylation at K55 of Rpl42ab (% K55 methylation) was calculated as follows:

% K55 methylation = (χRpl42ab_K55 / χRpl42ab) × 100


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5500QTrap Mass Spectrometry and SRM Analysis For each replicate of EF1α prepared for quantitative MS analysis, 5.0 µL of the digest solution was loaded for LC-SRM-MS analysis using a QTRAP5500 (AB Sciex, Foster City, Califronia, USA) hybrid triple quadrupole and linear ion trap mass spectrometer. Peptides were separated by nano-LC using a nanoACQUITY UPLC system (Waters, Milford, Massachusetts). Samples were loaded using partial loop injection onto a Waters Symmetry C18 trapping column (180 µm × 20 mm, 5 µm particle size), and peptides were separated on a Waters BEH C18 nano UPLC column (100 µm × 100 mm, 1.7 µm particle size) using the following elution solvents: H2O in 0.1% formic acid and CH3CN in 0.1% formic acid (solvent A and B respectively). The following elution gradient was utilised: 3% solvent B for 1 minute; 3–50% solvent B in 30 minutes; 50-85% solvent B in 2 minutes holding for 3 minutes; returning to 3% solvent B in 1 minute. Eluting peptides were ionized using positive ion mode nano-ESI using a spray voltage of 2.5 kV; an interface heater temperature of 150°C was employed. Curtain gas was set to 20 psi, declustering potential at 70 V, collision cell exit potential at 13V and both Q1/Q3 were set at unit resolution. Each of the EF1α peptides of Table 1, as well as their unlabeled versions, were targeted using the SRM transition list described in Table S4 with a cycle time of 2.83 seconds and dwell times of 20 milliseconds. Collision energies were calculated based on the following equations: CE(2+) = 0.050 × m/z + 5; CE(3+) = 0.029 × m/z + 4. Preliminary SRM transitions (not shown) were derived from MS/MS spectra collected on the LTQ Orbitrap Velos Pro. These transitions were incorporated into SRM-triggered IDA MS/MS methods that were implemented on the QTRAP5500; the resultant MS/MS spectra were subjected to sequence database searching (see Sequence Database Searches); spectra confirmed to be associated with peptides of interest were used in the determination of the final SRM transitions listed in Table S4.


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To ensure that peptide carryover between samples was minimal, 2 blank injections were run 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

between each digest sample. Blanks were subjected to SRM as described above, and inspected for the presence of peptide carryover. Signals potentially associated with peptide carryover were unable to be differentiated from noise. For peptide quantification, SRM data were processed using Multiquant 2.1 (AB Sciex) with the MQ4 integration algorithm. Absolute abundances for EF1α and its methylated residues were calculated using Multiquant-derived peak areas; this was performed in an analogous manner to the calculations described in the Orbitrap Mass Spectrometry and MaxQuant Analysis section.

Sequence Database Searches Peak lists derived from LC-MS/MS were submitted to the database search program Mascot (version 2.3, Matrix Science). The following search parameters were employed: instrument type was ESI-TRAP for LTQ Orbitrap Velos Pro derived data, and ESI-QUAD for QTRAP5500 derived data; precursor ion and peptide fragment mass tolerances were ±4 ppm and ±0.4 Da respectively for LTQ Orbitrap Velos Pro derived data, and ±1.2 Da and ±0.6 Da respectively for QTRAP5500 derived data; variable modifications included were acrylamide (C), carbamidomethyl (C), oxidation (M), methyl (K), dimethyl (K) and trimethyl (K); enzyme specificity was trypsin with up to 2 missed cleavages; and all taxonomies in the Swiss-Prot database (July 2012 release, 536789 sequence entries) were searched. Peptide identifications were considered to be high confidence if they were statistically significant (p

Stoichiometry of Saccharomyces cerevisiae Lysine Methylation

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