Protein Metrics Inc. - High-Throughput …...High-Throughput Characterization of Complex Crosslinked...

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High-Throughput Characterization of Complex Crosslinked Proteins using Byonic and Byologic

Chris Becker1; Yong Kil1; Pierre Allemand1, St John Skilton1, Eric Carlson1; Ryan D. Leib2; Christopher M. Adams2

1Protein Metrics Inc. 2Stanford University Mass Spectrometry, Stanford, CA

Introduction

Crucial structural information about protein-protein interactions can be obtained using chemical crosslinking methods in mass spectrometry. In practice, these data are incredibly complex to analyze and quantify, requiring extensive and time consuming validation to eliminate false positives or low confidence assignments. Here, we present a new rapid approach to analyze crosslink data using Byonic to identify crosslinkedpeptides and Byologic to facilitate data validation. This approach reduces the validation time for typical protein-protein systems from hours to minutes, and provides portable and robust data output to aid future investigations.

Using this strategy, we have investigated multiple cross linked protein-protein interactions to determine binding interfaces, stoichiometry, and replicability. The Byonicsearch produces lists of possible peptide linkages containing thousands of potential cross links. Byologic readily condenses these data into related peptide groups, e.g., cross linked peptides with their non-crosslinked homologs, even across replicate experiments or across experimental conditions. This facilitates rapid analysis for cross-link validation at both MS1 and MS2 levels, and easy label-free quantification using XIC analysis. We propose empirical rules, such as peptide length, number of observations, peptide assignment scores, and chromatographic profiles, and demonstrate a method to assign and filter data using ‘comment’ labels to define classes based on analyst confidence. Additionally, data that are not relevant to the current analysis (such as peptides without cross links) can be filtered without loss and investigated at later times based on new developments. Once classifications are made, Byologic produces permanent and flexible report outputs for information transfer between researchers.

This new approach to cross link analysis is rapid, flexible, and extensible to other types of analyses, such as protein-ligand interactions, surface acc

Acknowledgment

Support is gratefully acknowledged from NIH, grant GM100634 and the Stanford Dean of Research.

Byologic® Features

Workflow reduces lists of unsorted cross links that number in the 100s to a manageable list of crosslinks of links in the 10s to produce a list of solid leads for structural assignment.

The team has demonstrated one can integrate data from multiple linker types and multiple digest types.

Based on a list of strong leads, analysts can derive initial structure, and can validate either across linkers or with the ‘uncertain’ matches which fit the alignment.

Our integrated software workflow allows exhaustive analysis of these proteins. To date, these analyses have proven to be about an order of magnitude faster for interpretation (ca 1-2 hours as opposed to about ca 2 days with a traditional data analysis approach).

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Methods

Cross linked peptides are categorized into three groups: true-positives, uncertain, and false-positives, using a set of empirical criteria detailed below. “True positives” succeed on all of these rules, while “False Positives” fail least three of these rules. This strategy does not guarantee that a given cross link is-or-is-not ‘real,’ but provides an easy transferable, and repeatable framework for analysis. True positives are then used to anchor structural determination, with uncertain assignments filling in based on 3D structural limitations. Thus, only the most reliable mass spectral data is used to complement other structural measurements.

Sequence

FASTA file

MS2 Identifications

LC-MS/MS data

Inspection and quantificationPeptide-Centric sensitive crosslink analysis

Search engine Comprehensive identifications

Report

Crosslink Data Analysis in One Step

Rapid Multidimensional Validation and Classification

Unreliable Chromatography

Data analysis workflow:

Results Dashboard

Both Crosslink and Native Peptide, Above-&-BelowRapidly group, examine, and validate related variants

Discussion and Conclusions

Project Window

Protein Coverage

MS1 isotopes

MS2 annotation and m/z errors

Peptide Windows

Rules-Based Assignments, Across Range of Linkers

Co-isolated PrecursorsMS/MS Alone Looks Reasonable…

• MS/MS Spectrum Fragmentation Quality

• XIC Chromatographic Behavior

• Minimum Peptide and Crosslink Partner Length

• Observation across replicates (Both MS1 & MS/MS)

• MS1 Coelution and Possible MS/MS Contamination

Auto-populate likely crosslinked peptides

Structural Assignment

Summary tables are used to efficiently parse the True Positives, False Positives, and Uncertains for review, assignment, and reporting

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Protein Metrics Inc. - High-Throughput …...High-Throughput Characterization of Complex Crosslinked...

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