HD desktop: an integrated platform for the analysis and visualization of H/D exchange data

Abstract

Here we describe an integrated software platform titled HD Desktop designed specifically to enhance the analysis of hydrogen/deuterium exchange (HDX) mass spectrometry data. HD Desktop integrates tools for data extraction with visualization components within a single web-based application. The interface design enables users to navigate from the peptide view to the sample and experiment levels, tracking all manipulations while updating the aggregate graphs in real time. HD Desktop is integrated with a relational database designed to provide performance enhancements, as well as a robust model for data storage and retrieval. Additional features of the software include retention time determination, which is achieved with the use of theoretical isotope fitting; here, we assume that the best theoretical fit will occur at the correct retention time for any given peptide. Peptide data consolidation for the rendering of data in 2D was realized by automating known and novel approaches. Designed to address broad needs of the HDX community, the platform presented here provides an efficient and manageable workflow for HDX data analysis and is freely available as a web tool at the project home page http://hdx.florida.scripps.edu.

Figure 1. HDX Workflow Integration

(a) The protein of interest is digested with an enzyme and the resulting peptides are analyzed by LC MS/MS. (b) Peptide identity is then established with database search tools such as Sequest or Mascot (note that the method for determining peptide identity is left to the user), and converted into PepXML and CSV formats to facilitate editing. (c) The user then selects the peptides of interest from the search results to create the peptide set. (d) The protein is incubated with D₂O at multiple time points, digested with an enzyme and the resulting peptides are analyzed by LC MS. (e) The binary MS files, sequence file (in fasta format), and the peptide set are imported into the appropriate file store or LIMs. (f) The raw files are converted to mzXML, and HD Desktop pre-processing is conducted and the results are stored within a MySQL database. (g) Data are made available through interactive tools for HDX data curation and visualization components within the Grails framework.

Figure 2. The Data Hierarchy

Hierarchical structure of the data outlines the relationships between data components. Each experiment contains one or more samples, and each sample has multiple datapoints. The boxes outline the relationships between the data structure and the corresponding software application. The “Perturbation view” application presents the comparison between samples and the “Datapoint view” presents the data from all datapoints for a given sample. The “Peptide view” allows users to view and manuipulate the data related to the peptide.

Figure 3. Retention Time Determination

To establish the optimal retention time (RT) for each peptide, a 0.05 digital minute RT window is combined with our chi-squared fitting algorithm and moved across the target RT value ± 1 minute. The RT that generates the theoretical plot with the lowest fit score is assumed to represent the correct retention time for each peptide. In this example, the target RT value was 7.85 minutes. In panels (a) and (c), the chi-squared scores were inferior to the score obtained from (b), which is a result of the difference between the observed co-added spectrum (illustrated in red)and the theoretical plot (shown in blue). The best score was found in panel (b) and the optimal RT range is therefore determined to be 7.05 – 7.25 minutes.

Figure 4. HDX Data Consolidation

To generate a condensed data set for display over a three dimensional structure we have automated the following process. 1) Peptides with shared start and end positions (twin peptides) are identified, averaged and consolidated (peptides A and B). 2) The remaining peptides are examined for “sibling peptides” which share either start or end position (peptides C and D), and a theoretical peptide is created from the non-overlapping portion (D–C). This theoretical peptide is assigned the difference between the %D values. 3) The process is repeated with all non consolidated peptides (real and theoretical). 4) In cases where the sum of two (or more) peptides equals another peptide, the larger peptide is removed from the list. 5) Peptides that do not meet the previous criteria “overlapping peptides” are either discarded (peptide E) or preserved if they do not overlap with the previously consolidated group (peptide F). 6) The “condensed data” illustrates the result of the process.

Figure 5. Peptide View

H/D exchange data are presented in the grid view, with each row representing a peptide. Selection of a peptide loads the associated data into the main spectral and extracted ion viewers. Tree navigation facilitates browsing to replicates; spectral and extracted ion data are presented in lower pane; measured isotopic envelope is shown in red. While the above example presents high-resolution spectral data, other resolutions are supported within the same interface. For high-resolution data, correct peak data is extracted from calculated sub-ranges only, displayed as yellow bars.

Figure 6. Datapoint/Perturbation Views

The Datapoint View (left), presents a heat map grid view with the %D results for all datapoints. Selection of a row in this view displays the deuterium uptake curves for the selected peptide for each datapoint. In the Perturbation View (right), for each peptide, perturbation data is presented in a color-coded grid. A number of automated rendering methods are available both of these views.