glycoprotein microheterogeneity via n-glycopeptide identification kevin brown chandler, petr...

Glycoprotein Microheterogeneity via N-Glycopeptide

Identification

Kevin Brown Chandler, Petr Pompach,

Radoslav Goldman, Nathan EdwardsGeorgetown University Medical Center

The challenge

Identify glycopeptides in large-scale tandem mass-spectrometry datasets Many glycopeptide enriched fractions Many tandem mass-spectra / fraction

Good, but not great, instrumentation QStar Elite – CID, good MS1/MS2 resolution

Strive for hypothesis-generating analysis Site-specific glycopeptide characterization Glycoform occupancy in differentiated samples

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Observations

Oxonium ions (204, 366) help distinguish glycopeptides from peptides… …but do little to identify the glycopeptide

Few peptide b/y-ions to identify peptides… …but intact peptide fragments are common

If the peptide can be guessed, then… …the glycan's mass can be determined

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Observations

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Glycopeptide Search Strategy

Glycan-Peptide to Spectrum Matches Multi-Peptide, Multi-Glycan Mass (Single Peptide), Single Glycan Mass, Single Glycan (Topology)

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Compromises

Single protein / Simple protein mixture Few peptides to distinguish

Single N-glycan per peptide Subtraction from precursor

Digest may not resolve site Need peptide/glycan fragments to distinguish

Isobaric peptide-glycan pairs are not resolved Need peptide/glycan fragments to distinguish

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Glycan Databases

Link putative glycan masses to N-linked glycan structures (and organism, etc. ): Human N-linked GlycomeDB Cartoonist structure enumeration CFG Mammalian Array (v5.0) In-house database (Oxford notation)

Database(s) provide "biased" search space: Coverage vs. "Reasonableness" Trade off: Time, Specificity, Biology

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Hap

tog

lob

in (

HP

T_H

UM

AN

)

NLFLNHSE*NATAK

MVSHHNLTTGATLINE

VVLHPNYSQVDIGLIK

Haptoglobin standard

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• N-glycosylation motif (NX/ST)* Site of GluC cleavage

Pompach et al. Journal of Proteome Research 11.3 (2012): 1728–1740.

Haptoglobin standard

11 HILIC fractions enriched for glycopeptides 11 x LC-MS/MS acquisitions (≥ 15k spectra) 2887/3288 MS/MS spectra have oxonium ion(s) 317 have "intact-peptide" fragment ions

263 spectra matched to peptide-glycan pairs 52% matched single-glycan 8% matched multi-peptide

27 distinct (mass) glycans on 11 peptides Glycans identified on all 4 haptoglobin sites

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Algorithms & Infrastructure

Glycan databases indexed by composition, mass, N-linked, and motif/type Formats: IUPAC, Linear Code, GlycoCT_condensed Implemented: GlycomeDB, Cartoonist, CFG Array

Monosaccharide decomposition of glycan mass Böcker et al. Efficient mass decomposition (2005)

χ2 Goodness-of-fit test for precursor cluster Theoretical isotope cluster from composition. ICScore based on χ2 -test p-value.

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False Discovery Rate (FDR)

How confident can we be in these mass-matches?

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False Discovery Rate (FDR)

How confident can we be in these mass-matches?

FDR: 3.9% [ ~ 10 / 263 spectra ]

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False Discovery Rate (FDR)

How confident can we be in these mass-matches?

FDR: 3.9% [ ~ 10 / 263 spectra ]

Estimate the number of errors by searching with non-N-linked motif (decoy) peptides too. Count spectra matched to decoy peptide-glycan pairs. Rescale decoy counts to balance the number of motif

and non-motif peptides. 13

Tuning the filters…

Adjusting thresholds and parameters to Increase specificity (lower FDR, fewer spectra), or Increase sensitivity (more spectra, higher FDR)

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Tuning the filters…

Oxonium ions: Number & intensity Match tolerance

"Intact-peptide" fragments: Number & intensity Match tolerance

Glycan composition: ICScore Constrain search space Match tolerance

Glycan database: Constrain search space Match tolerance

Precursor ion: Non-monoisotopic selection Sodium adducts Charge state

Peptide search space: Semi-specific peptides Non-specific peptides Peptide MW range Variable modifications 15

Tuning the filters…

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Tuning the filters…

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GlycoPeptideSearch (GPS) 1.3

Freely available implementation Windows, Linux

Reads open-format spectra (mzXML, MGF) Pre-indexed Glycan databases

Human & Mammalian GlycomeDB Mammalian CFG Array (v5.0) User-Named (Oxford notation)

In silico digest and N-linked motif identification Automatic target/decoy analysis for FDR

http://edwardslab.bmcb.georgetown.edu/GPS18

Where to from here?

Demonstrate utility on new instrument platforms, proteins, samples

Develop a scoring model for fragments Re-implement Cartoonist demerits Exploit relationships between

MS2 spectra, MSn spectra Explore application to

O-glycopeptides, N-glycans, O-glycans

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Edwards Lab (Georgetown) Kevin Brown Chandler [NSF] (Poster 32)

Goldman Lab (Georgetown) Radoslav Goldman (Poster 6) Petr Pompach Miloslav Sanda (Poster 23)

Marshal Bern (Xerox PARC) Cartoonist, Peptoonist

Rene Ranzinger (CCRC) GlycomeDB

Acknowledgements

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