protein post - translational 
 modifications ( ptms ) play essential roles 
 in protein signaling , localization , function , degradation , and other important biological 
 processes . despite the considerable success of protein identification 
 via liquid chromatography  mass spectrometry ( lc  ms ) , 
 most studies do not provide information regarding ptms on the identified 
 proteins . this is because identifying even a single type of ptm requires 
 specialized procedures and introduces problems with the increased 
 database size required for the search . extension of such approaches to analysis of multiple ptms is generally 
 unrealistic , and consequently , there are few examples where multiple 
 types of ptms are analyzed in a single experiment . despite 
 widespread recognition of the importance of ptms , nearly all database search algorithms still rely solely 
 on primary sequence information and ignore all prior knowledge regarding 
 the presence of ptms . two notable exceptions are the prosight software 
 for top - down proteomics , which performs shotgun annotation of multiple sources of variation contained within 
 the uniprot repository , and x!tandem , which can make use of annotated 
 ptms from swiss - prot . x!tandem and prosight 
 use probabilistic algorithms for scoring of correct spectrum matches . morpheus was designed from the ground up to take advantage of the 
 specificity afforded by currently available high mass accuracy instruments 
 and distinguishes correct and incorrect identifications by counting 
 the number of matching products in conjunction with a target variable modification search ,  where a particular 
 ptm ( e.g. , phosphorylation ) is allowed to occur on any instance of 
 selected amino acid residues ( e.g. , serine , threonine , or tyrosine ) 
 in all of the theoretical peptides from the entire search database . this process is a useful and effective means to identify unknown modifications 
 in a sample ; however , the database search space is expanded enormously 
 even for just a few ptm options to say nothing of including the hundreds 
 of varieties of known ptms . a two - pass database search strategy reduces the search - space expansion but may introduce 
 bias when employed with target  decoy false discovery rate ( fdr ) 
 calculations . all such searches using 
 variable modification lead to longer search times and an increase 
 in the number of false positive identifications , both of which grow 
 with the size of the search space . these issues compromise the utility 
 of the search and cause many researchers to ignore ptms altogether 
 in their proteomics data . blind modification searches can reveal unknown 
 modifications but face challenges from increased run time and decreased 
 identification of unmodified peptides , though recent advances in this 
 area are showing promise . spectral library searching 
 for identification of post - translationally modified peptides has historically 
 been limited by the availability of tandem mass spectra from modified 
 peptides , especially those outside of the most common ptms ( e.g. , 
 phosphorylation ) . however , new approaches in this area are beginning 
 to address this challenge . a further 
 problem with library searching is that library spectra corresponding 
 to all possible modification sites may not be present in the library 
 potentially leading to site misassignment . here we report a 
 new strategy for comprehensive identification 
 of protein ptms in a single - pass database search . this global post - translational 
 modification ( g - ptm ) search strategy alters the variable modification 
 approach to consider only previously curated ptms at specific amino 
 acid residue positions . variable  aspect of these 
 searches allows for the presence or absence of the ptm at that specific 
 residue . this residue position specificity generates only a modest 
 increase in database search space , unlike variable searches that allow 
 modifications to occur at any selected amino acid residue on all protein 
 sequences in the database . we have implemented the g - ptm strategy 
 in the open - source search 
 program morpheus , which was specifically 
 designed to accommodate high - resolution mass spectra . morpheus , much 
 like its predecessors , identifies peptides by comparing tandem mass 
 spectra to theoretical spectra derived in silico from 
 primary sequence data by making use of a simple score similar to the 
 h - score suggested by savitski et al . the 
 advantage conferred by morpheus through the improvements described 
 herein is the ability to identify a multitude of different ptms in 
 a single - pass search while maintaining a high level of confidence 
 in the identifications . we compared three types of searches 
 using the software program 
 morpheus to characterize the effectiveness of the g - ptm strategy ( figure 1 ) . two comprehensive 
 sets of proteomics data , one from human jurkat cell lysate and one 
 from mouse pancreatic islet lysate , were used to demonstrate the approach . the uniprot repository was the source of the protein sequence and 
 ptm data for all database searches . the first two types of searches 
 employed the uniprot fasta file either without allowing for any ptms , 
 referred to simply as fasta  , or by allowing variable 
 phosphorylation of every serine , threonine , and tyrosine , referred 
 to as  fasta vp . the g - ptm search utilized the uniprot 
 xml ( extensible markup language ) file , which includes the same amino 
 acid sequences as the fasta file but also contains the curated list 
 of position - specific ptms for those protein sequences . comparison of three proteomics 
 database search strategies : no ptms 
 considered ( fasta ) , conventional variable modification for phosphorylation 
 ( fasta vp ) , and consideration of a long list of residue- and protein - specific 
 ptms of numerous different types ( g - ptm ) . search space size increases 
 by 67-fold for fasta vp , but only by 10% for g - ptm . sample 
 preparation and ms analysis of the 
 jurkat cells were previously reported and similar to that described further for mouse . the ms raw files 
 for the jurkat cell lysate samples are available via ftp from the 
 peptideatlas data repository by accessing 
 the following link : http://www.peptideatlas.org/pass/pass00215 . male c57bl/6j 
 ( b6 ) and cast / eij ( cast ) mice were purchased from the jackson laboratories 
 ( bar harbor , maine ) and housed in an environmentally controlled vivarium 
 at the university of wisconsin biochemistry department . 5008 ) and water ad libitum and were maintained on a 12-h light / dark cycle 
 ( 6 am6 pm ) . at 10 weeks of age all animal procedures were preapproved 
 by the university of wisconsin animal care and use committee . a 
 5 ml volume of collagenase type xi ( sigma ) , dissolved in hanks 
 balanced salt solution ( gibco ) , was injected into the pancreas via 
 the common bile duct ( 0.45 mg / ml with 0.02% bsa ) . the pancreas was 
 removed and incubated at 37 c for 16 min with intermittent agitation . a ficoll gradient was used to partially purify islets from the digested 
 pancreas , followed by further purification by manual picking under 
 a stereomicroscope . during the purification procedure , islets were 
 maintained in krebs - ringer bicarbonate buffer containing ( mm ) : 118.41 
 nacl , 4.69 kcl , 2.52 cacl2 , 1.18 mgso4 , 1.18 
 kh2po4 , 25 nahco3 , and 5 hepes supplemented 
 with 0.2% bsa and 16.7 mm glucose . islets from two b6 mice ( and separately 
 two cast mice ) were pooled and then apportioned for protein analyses 
 ( 400 b6 islets , 470 cast islets ) . islets were washed three times in 
 ice - cold pbs , gently pelleted , and snap frozen in liquid nitrogen . protein was extracted and then digested into peptides using an 
 adaptation of the filter aided sample preparation ( fasp ) procedure . islets were thawed on ice , and the protein extracted with 90 l 
 of sdt lysis buffer , consisting of 4% sodium dodecyl sulfate ( sds , 
 bio - rad ) , 0.1 m tris - hcl ( ph 7.6 , teknova ) , and 0.1 m dithiothreitol 
 ( dtt , sigma ) . the resulting lysates were cooled in 
 an ice bath , followed by bath sonication ( fisher scientific fs20 ) 
 for three cycles of 20 s with ice bath cooling during 20 s rest periods . debris was pelleted by centrifugation at 16  000 g for 5 min , and 85 l of supernatant was collected . removal 
 of detergents and salts was accomplished by fasp using 
 multiple washes in a 30k mwco filter ( vivacon 500 from sartorius ) . the 85 l protein extract was diluted with 570 l of 8 
 m urea ( sigma ) , 0.1 m tris - hcl ph 8.0 . half of this solution was centrifuged 
 at 14  000 g through the filter ( 25 min ) , followed 
 by the other half ( 25 min ) , and then 0.2 ml of urea / tris wash ( 20 
 min ) . the proteins were alkylated in the filter with 0.1 ml of 0.05 
 m iodoacetamide ( sigma ) in urea / tris for 20 min at room temperature 
 in the dark , followed by centrifugation ( 15 min ) . the proteins were 
 washed three times with 0.1 ml of urea / tris and three times with 0.1 
 ml of 0.05 m ammonium bicarbonate ( abc , fluka ) with 15 min centrifugations 
 for each wash . tryptic digestion was performed at 37 c overnight 
 on the proteins in the filter by addition of 2 g of trypsin 
 ( promega ) in 75 l of 0.05 m abc . peptides were collected by 
 centrifugation ( 10 min ) into new collection tubes , followed by washing 
 the remaining peptides out of the filter with 40 l of abc , 
 10 min centrifugation , 50 l of 0.5 m nacl , and a final 10 min 
 centrifugation . the tryptic peptide digests were fractionated 
 using high - ph reverse - phase 
 chromatography on a shimadzu hplc system ( lc-10ad , scl-10a vp , spd-10a 
 vp , shimadzu , columbia , md ) and a phenomenex c18 gemini 3  , 
 110  , 3.0  150 mm column ( phenomenex , torrance , 
 ca ) . the high - ph method was adapted from gilar et al . mobile phase a ( mpa ) was 20 mm ammonium formate , ph 10 , 
 and b ( mpb ) was 20 mm ammonium formate , ph 10 , in 70% acetonitrile . the hplc flow was 1.0 ml / min , and the gradient was 0% mpb isocratic 
 for 10 min ( trapping step ) , linear ramp to 100% mpb over 20 min , hold 
 at 100% mpb for 5 min , to 0% mpb over 1 min , and equilibration at 
 0% mpb for 10 min . fractions were collected every minute using a gilson 
 203 fraction collector ( gilson , middleton , wi ) for a total of 15 fractions 
 collected during the range of peptide elution as discernible from 
 the uv  vis trace . because of the relatively low amounts near 
 the beginning and the end of the gradient , the first two fractions 
 were combined , as were the last six fractions , leading to a total 
 of nine fractions . by comparison of the uv  vis trace to that 
 of a standard , it was estimated that the b6 and cast samples contained 
 34 and 33 g of peptides , respectively . fractions were dried 
 down using vacuum centrifugal concentration ( savant speed- vac , thermo , 
 pittsburgh , pa ) and stored at 80 c . each fraction 
 was reconstituted in 10 l of 5% acetonitrile 
 and 1% formic acid in water , and then between 4 and 9.5 l of 
 each fraction was analyzed by lc ms ( using the earlier uv  vis 
 trace to estimate peptide content of each fraction and avoid injecting 
 more than 2.5 g of peptides per run ) . the hplc ms / ms 
 system consisted of a waters nanoacquity hplc ( milford , ma ) connected 
 to an electrospray ionization ( esi ) ion - trap / orbitrap mass spectrometer 
 ( ltq orbitrap velos , thermo scientific , san jose , ca ) . the lc column 
 was prepared by packing 20 cm of 3 m magic aqc18 beads ( bruker - michrom , 
 auburn , ca ) into a 100 m i.d . capillary whose tip was pulled 
 to 1 m with a p-2000 laser puller ( sutter instruments , 
 novato , ca ) . the full hplc method was 195 min long at a flow rate 
 of 0.3 l / min , and it included a 124 min gradient from 2% to 
 30% , with a brief ramp to 70% , mpb ( 0.1% formic acid in acetonitrile ) 
 with the remainder being mpa ( 0.1% formic acid in water ) . a full - mass 
 scan ( 3001500 m / z ) was performed 
 in the orbitrap at a resolution of 60  000 . the ten most intense 
 peaks with z > 1 from the full scan were selected 
 for fragmentation by higher - energy collisional dissociation ( hcd , 
 collision energy = 42 ) . the isolation width for the precursor ions 
 was 3.0 m / z , and the product ions 
 from fragmentation were analyzed in the orbitrap detector at a resolution 
 of 7500 . dynamic exclusion was enabled with a repeat count of two 
 over 30 s and an exclusion duration of 120 s. xcaliber software version 
 2.1.0 was used for data collection . ms raw files for the mouse samples 
 are available via ftp from the peptideatlas data repository by accessing the following link : http://www.peptideatlas.org/pass/pass00470 . we chose to use a subset of the available human protein sequences 
 for the jurkat sample analyses , including only those with a matching 
 mrna transcript above 0.1 transcripts per million ( tpm ) . we used the complete set of available mouse 
 protein sequences for the b6 and cast islet proteomics . both sets 
 of protein accession numbers ( 14  138 entries for jurkat and 
 43  238 entries for mouse ) included in the databases are supplied 
 in supplemental table s1 , and the summarized 
 list of target ptm types from the xml file is in supplemental table s2 . the database used for the jurkat samples 
 was the homo sapiens ( human ) reference proteome from 
 uniprot release 2013_12 ( downloaded february 25 , 2015 ) , limited to 
 those proteins with mrna transcript abundances exceeding 0.1 tpm . the database used for the mouse samples was 
 the mus musculus ( mouse ) reference proteome from 
 uniprot release 2015_02 ( downloaded february 25 , 2015 ) . the software program morpheus ( revision 
 142 ) was used for all database searching . it can be obtained at http://morpheus - ms.sourceforge.net/. for this work , it was 
 modified to accept uniprot xml in addition to fasta protein databases . 
 when a uniprot xml database is specified , all curated modifications 
 are extracted . details of each modification ( name , mass shift , target ) 
 are read from a local copy of http://www.uniprot.org/docs/ptmlist . all valid modifications are added to the variable modifications 
 box in the morpheus graphical user interface with the prefix  uniprot  
 and selected by default . during each search , all protein sequences 
 are read along with the locations of selected uniprot variable modifications . the order of the unmodified and modified amino acid residues is reversed 
 during on - the - fly generation of decoy protein sequences . for example , the phosphorylated tetrapeptide , 
 tes(uniprot : phosphoserine)q , becomes qs(uniprot : phosphoserine)et . a critical routine in the code takes a base peptide sequence and 
 generates all of the isoform combinations possible given the variable 
 modifications selected , up to a user - defined limit ( 1024 by default ) . this code was modified slightly to consider uniprot modifications 
 only at their location as reported in the database . otherwise , the 
 logic for combinatorially generating all possible peptide isoforms 
 is identical . searches were performed on a dell precision t7610 
 workstation with 
 a xeon 2.70 ghz processor and 32.0 gb of ram using 12 cores . the following 
 settings were used in all searches : protease = trypsin ( no proline 
 rule ) ; maximum missed cleavages = 2 ; initiator methionine behavior 
 = variable ; fixed modifications = carbamidomethylation of c ; variable 
 modifications = oxidation of m ; maximum variable modification isoforms 
 per peptide = 1024 ; precursor mass tolerance = 10.0 ppm ( monoisotopic ) ; 
 precursor monoisotopic peak correction = disabled ; product mass tolerance 
 = 0.01 da ( monoisotopic ) ; maximum 
 false discovery rate = 1% . fasta vp searches used additionally variable 
 phosphorylation of s , t , and y. g - ptm searches used xml database files 
 rather than fasta files . counts of post - translationally modified peptides 
 do not include the oxidation of methionine or the carbamidomethylation 
 of cysteine as these occur during sample handling and therefore are 
 somewhat uninteresting . summary 
 lists of identified proteins including numbers of psms ( total and 
 modified ) are provided in supplemental table s3 for both jurkat and mouse , where b6 and cast mouse data are segregated 
 to allow for their comparison . ; jurkat variable phosphorylation , 
 367 min . ; b6 and cast mouse fasta , 63 min . ; b6 and cast mouse g - ptm , 
 62 min . ; b6 and cast mouse variable phosphorylation , 471 min . the g - ptm search strategy limits the expansion 
 of the target and 
 decoy databases , as shown by the sizes of the circles in figure 1 and by the data 
 in supplemental table s4 . despite including 
 22  540 site - specific human ptms from 104 different ptm types , the search space for g - ptm increased by only 10% compared to the fasta 
 search , which did not consider any ptms . in contrast , the fasta vp 
 search , with only three variable modifications ( phosphorylation of 
 serine , threonine , and tyrosine ) increased the search space by 67-fold 
 ( see figure 1 ) . the 
 number of variable modifications per peptide isoforms was limited 
 to 1024 for this comparison , which is the value often allowed in database 
 searches of this type . this massive , 67-fold expansion of the database 
 for variable phosphorylation substantially increases both the search 
 time ( 6- to 10-fold ) and the error rate for phosphopeptide identification . we applied the g - ptm search strategy to a large proteomic data 
 set obtained from human jurkat cells . about 490  000 tandem 
 mass spectra were obtained from a highly fractionated sample of jurkat 
 cell lysate , and counts of the modified peptides resulting from the 
 g - ptm search are listed in table 1 . within this single - pass database search , over 2200 unique post - translationally modified peptides were identified , encompassing 
 26 different types of ptms from five categories ( phosphorylation , 
 methylation , acetylation , hydroxylation , and assorted ) . these modified 
 peptides would have gone undetected using a typical proteomics database 
 search , but the g - ptm search readily revealed this rich array of ptms 
 present in the jurkat cells . we also applied the g - ptm search strategy 
 to proteomics data sets 
 from mouse pancreatic islets . about 430  000 tandem mass spectra 
 were obtained from a highly fractionated samples of cast and b6 mouse 
 islet lysate , and the counts of modified peptides resulting from the 
 g - ptm search are listed in supplemental table s5 . within this single - pass database search , 1100 unique 
 post - translationally modified peptides were identified , encompassing 
 32 different types of ptms from five categories ( phosphorylation , 
 methylation , acetylation , hydroxylation , and assorted ) . these modified 
 peptides would also have gone undetected using a typical proteomics 
 database search , but the g - ptm search readily revealed this rich array 
 of ptms present in the mouse islets . these same tandem mass 
 spectra were searched using morpheus with 
 the two other search strategies , fasta and fasta vp . the results for 
 the three types of searches , for both human and mouse data , are shown 
 in figure 2 . the tabular data 
 within the figure lists the total number of identified proteins , unique 
 peptides , and peptide spectral matches ( psms ) . the  all  
 columns ( orange ) include both unmodified and post - translationally 
 modified peptides . these total identifications show similar results 
 across the three search strategies , although the g - ptm search consistently 
 produced more identifications than either the fasta or fasta vp searches . as expected for samples such as these without a ptm enrichment step , 
 the majority of identified peptides are unmodified ( 100% , 97% , and 
 97% for the fasta , fasta vp , and g - ptm search results , respectively ; 
 see supplemental table s6 , which categorizes 
 the identifications by the number of ptms per peptide ) . nonetheless , 
 there are hundreds of modified peptides identified in these samples ; 
 see figure 2 ( purple 
 data columns ) and supplemental tables s7 and s8 . the g - ptm search produces substantially 
 more modified peptide spectral matches than the fasta vp search , and 
 furthermore , these ptm identifications are of much higher confidence 
 ( vide infra ) . results are shown for the three search types 
 for both human and mouse proteomics data sets . the tabulated results 
 are given for  all  ( unmodified and modified peptides ) 
 and for  modified  only peptides . peptides was calculated from the numbers of decoy and target identifications 
 meeting the global 1% fdr cutoff ( i.e. , the fdr for  all  
 peptide identifications ) . the fdr values for fasta vp are > 1% , 
 indicating 
 substantially poorer confidence , whereas the fdrs are < 1% for the 
 g - ptm searches , indicating high confidence in these ptm peptide assignments . the pep plots corroborate this result by showing higher error probabilities 
 for phosphorylated peptides in the fasta vp search but lower error 
 probabilities for modified peptides identified with g - ptm . the results for all peptide identifications were 
 uploaded to protein 
 prospector s ms - viewer tool ( http://prospector2.ucsf.edu/prospector/cgi-bin/msform.cgi?form=msviewer ) , and supplemental table s9 provides 
 hyperlinks to the ms - viewer report for each sample . for ease of examining 
 the ptm identifications , hyperlinks to the ms - viewer report containing 
 each modified peptide are provided in supplemental tables s7 and s8 along with detailed 
 instructions on how to access a specific spectrum or to filter the 
 data to look at all peptides containing a particular ptm . note that 
 morpheus , in its current implementation , does not export peak lists , 
 but this capability may be added in future versions . fdr is 
 a common measure of the confidence of peptide identifications . 
 for any given score cutoff , it is common to set the 
 score threshold at a 1% fdr level where 1% of the assignments are 
 decoys . as an example , the g - ptm search of the human data ( upper right 
 panel of figure 2 ) 
 shows 2104 decoy and 210  307 target psms resulting in an fdr 
 of 1% . one can take a subset 
 of the psms meeting the 1% global fdr cutoff and calculate an fdr 
 for just this subset of psms . since the ptm - containing peptides are 
 of particular interest , we used the 17 decoy and 7278 target psms 
 assigned to modified peptides to calculate an fdr of 0.23% for modified 
 peptides . thus , the g - ptm search actually identified peptides with 
 ptms more confidently than peptides without ptms , as indicated by 
 0.23% being less than the 1% global fdr . in contrast , the fasta vp 
 search yielded much lower confidence for modified peptides ( 11.0% 
 fdr ) than for all peptides ( 1% global fdr ) . it is likely that the 
 fdr of 0.23% for modified peptides underestimates the actual error 
 rate . certain labile ptms such as phosphorylation or glcnacylation 
 present the possibility that the localization of ptms on high scoring 
 peptides may be incorrect . we performed a second search of the jurkat 
 data that allowed variable phosphorylation on all s , t , and y amino 
 acid residues of phosphopeptides identified in the original g - ptm 
 search . we found 127 instances ( out of 3425 possible ) on 88 different 
 sequences where the morpheus score improved with the phosphorylation 
 at an alternative position ( see supplemental table s10 ) . the fdr for the positioning of the ptm on phosphopeptides 
 considered in this manner is thus 127/3425 = 3.7% . this source of 
 error is reduced as soon as these positions of phosphorylation get 
 added to the search database . the posterior error probability 
 ( pep ) is another measure of peptide 
 identification confidence . pep is often referred to as a local fdr because it is calculated 
 from spectral matches to target and decoy peptides having the same 
 or nearly the same identification score . plots of pep values as a 
 function of score are shown in figure 2 for the list of peptides meeting the 1% global fdr 
 cutoff . high - scoring peptides have pep values of zero because there 
 were no decoy peptides with these high scores . , unmodified peptides 
 in the g - ptm search of human data ( orange dots in upper right panel 
 of figure 2 ) have a 
 pep value of 0.04 for the relatively low score of 9 , indicating that 
 any given psm with a score of 9 has a 4% chance of being incorrect . modified peptides ( purple dots ) from that same g - ptm search were identified 
 with the same or lower pep scores ( 2% chance of being incorrect at 
 a score of 9 ) , meaning their confidence is at least as high as for 
 the unmodified peptides . in contrast , modified peptides from the variable 
 phosphorylation search ( middle panels in figure 2 ) have dramatically higher pep scores ( 60% 
 chance of being incorrect at a score of 9 ) than their unmodified counterparts , 
 indicating lower confidence . the observation that pep values for modified 
 peptides were consistently lower at all scores for both mouse and 
 human samples in the g - ptm approach ( right panels in figure 2 ) suggests that correct identifications 
 of modified peptides are statistically more likely than for unmodified 
 peptides . both fdr and pep 
 calculations reveal that the g - ptm search strategy 
 identifies modified peptides with high confidence , whereas the variable 
 modification approach identifies modified peptides with much lower 
 confidence . the 67-fold increase in search space for variable phosphorylation 
 ( supplemental table s4 ) means that 98.5% 
 of peptide targets in the database are modified , which lies in stark 
 contrast to the actual low level of phosphorylation in typical unenriched 
 mammalian samples . consequently , the set of target peptides in the 
 database used for spectral matching is a poor reflection of reality , 
 and the probability of producing false spectral identifications of 
 phosphorylated peptides is quite high . the g - ptm strategy , however , 
 employs site - specific addition of ptms to the peptide target database , 
 thereby avoiding a large increase in search space and resulting in 
 a similar or even lower level of false identifications for modified 
 as for unmodified peptides . g - ptm searches deliver confident 
 ptm identifications from proteomics 
 data , but they currently have a few limitations . the identified ptm 
 location within a peptide is limited to the one(s ) assigned in the 
 xml file . thus , it is possible to get a relatively confident assignment 
 of a modified peptide where the residue position of the ptm is erroneously 
 assigned because its true position was not a considered option . it 
 is also possible that a mass shift assigned to a rare ptm in the xml 
 file also corresponds to a more common ptm not listed within the file . for example , citrulline is an uncommon ptm that has the same mass 
 shift as asparagine deamidation , which commonly occurs during sample 
 handling and thus is not usually listed in the xml database . we believe that there is substantial value in the ability to identify 
 a multitude of ptms in a single - pass search , despite the possibility 
 that a few ptm locations or identities will be incorrectly assigned 
 within the correct peptide sequences . prior to assigning biological 
 importance to a particular post - translationally modified peptide , 
 researchers should evaluate whether alternative possibilities are 
 more likely . of course , the best solution to this issue is a more 
 complete and accurate compilation of ptm sites . several ptm repositories 
 exist , but the current incarnation of g - ptm within morpheus requires 
 an xml version of the fasta database , formatted according to uniprot 
 guidelines . in an excellent recent review of large - scale analysis 
 of ptms , olsen and mann described the current status of the major 
 ptm repositories and called upon the community  to establish 
 more refined ways of integrating and presenting the ptm data that 
 it generates  . since the 
 curated list of ptms used in g - ptm searches remains incomplete 
 at present , there is still a need for ptm discovery experiments employing 
 sample enrichment or variable modification searches . over time , the 
 curated list of ptms will continue to expand and improve , especially 
 with the advent of tools such as this g - ptm search that enable easy 
 and effective use of that data . researchers are encouraged to provide 
 data supporting identification of novel ptms to uniprot ( http://www.uniprot.org/update ) to the benefit of the entire proteomics community . the g - ptm 
 search strategy enables researchers to confidently identify 
 numerous types of ptms in bottom - up proteomics data sets . we have 
 made g - ptm available in the open - source morpheus software ; in future 
 work , we hope to see the strategy implemented in other search packages 
 as well to increase accessibility and ease - of - use to the broader research 
 community . the g - ptm approach helps to reveal the myriad ways by which 
 ptms define and control biological systems . implementing this approach 
 in standard proteomics
bottom - up 
 proteomics database search algorithms used for peptide 
 identification can not comprehensively identify post - translational 
 modifications ( ptms ) in a single - pass because of high false discovery 
 rates ( fdrs ) . a new approach to database 
 searching enables global 
 ptm ( g - ptm ) identification by exclusively looking for curated ptms , 
 thereby avoiding the fdr penalty experienced during conventional variable 
 modification searches . 
 we identified over 2200 unique , high - confidence 
 modified peptides comprising 26 different ptm types in a single - pass 
 database search .