Automating data analysis for hydrogen/deuterium exchange mass spectrometry using data-independent acquisition methodology.

We present a hydrogen/deuterium exchange workflow coupled to tandem mass spectrometry (HX-MS2) that supports the acquisition of peptide fragment ions alongside their peptide precursors. The approach enables true auto-curation of HX data by mining a rich set of deuterated fragments, generated by collisional-induced dissociation (CID), to simultaneously confirm the peptide ID and authenticate MS1-based deuteration calculations. The high redundancy provided by the fragments supports a confidence assessment of deuterium calculations using a combinatorial strategy. The approach requires data-independent acquisition (DIA) methods that are available on most MS platforms, making the switch to HX-MS2 straightforward. Importantly, we find that HX-DIA enables a proteomics-grade approach and wide-spread applications. Considerable time is saved through auto-curation and complex samples can now be characterized and at higher throughput. We illustrate these advantages in a drug binding analysis of the ultra-large protein kinase DNA-PKcs, isolated directly from mammalian cells.

All-in-One Pseudo-MS3 Method for the Analysis of Gas-Phase Cleavable Protein Crosslinking Reactions.

Crosslinking mass spectrometry (XL-MS) supports structure analysis of individual proteins and highly complex whole-cell interactomes. The identification of crosslinked peptides from enzymatic digests remains challenging, especially at the cell level. Empirical methods that use gas-phase cleavable crosslinkers can simplify the identification process by enabling an MS3-based strategy that turns crosslink identification into a simpler problem of detecting two separable peptides. However, the method is limited to select instrument platforms and is challenged by duty cycle constraints. Here, we revisit a pseudo-MS3 concept that incorporates in-source fragmentation, where a fast switch between gentle high-transmission source conditions and harsher in-source fragmentation settings liberates peptides for standard MS2-based peptide identification. We present an all-in-one method where retention time matches between the crosslink precursor and the liberated peptides establish linkage, and MS2 sequencing identifies the source-liberated peptides. We demonstrate that DC4, a very labile cleavable crosslinker, generates high-intensity peptides in-source. Crosslinks can be identified from these liberated peptides, as they are chromatographically well-resolved from monolinks. Using bovine serum albumin (BSA) as a crosslinking test case, we detect 27% more crosslinks with pseudo-MS3 over a best-in-class MS3 method. While performance is slightly lower for whole-cell lysates (generating two-thirds of the identifications of a standard method), we find that 60% of these hits are unique, highlighting the complementarity of the method.

High-Sensitivity Proteome-Scale Searches for Crosslinked Peptides Using CRIMP 2.0.

Crosslinking mass spectrometry (XL-MS) is a valuable technique for generating point-to-point distance measurements in protein space. However, cell-based XL-MS experiments require efficient software that can detect crosslinked peptides with sensitivity and controlled error rates. Many algorithms implement a filtering strategy designed to reduce the size of the database prior to mounting a search for crosslinks, but concern has been expressed over the possibility of reduced sensitivity using these strategies. We present a new scoring method that uses a rapid presearch method and a concept inspired by computer vision algorithms to resolve crosslinks from other conflicting reaction products. Searches of several curated crosslink datasets demonstrate high crosslink detection rates, and even the most complex proteome-level searches (using cleavable or noncleavable crosslinkers) can be completed efficiently on a conventional desktop computer. The detection of protein-protein interactions is increased twofold through the inclusion of compositional terms in the scoring equation. The combined functionality is made available as CRIMP 2.0 in the Mass Spec Studio.

Doublecortin engages the microtubule lattice through a cooperative binding mode involving its C-terminal domain.

Doublecortin (DCX) is a microtubule (MT)-associated protein that regulates MT structure and function during neuronal development and mutations in DCX lead to a spectrum of neurological disorders. The structural properties of MT-bound DCX that explain these disorders are incompletely determined. Here, we describe the molecular architecture of the DCX-MT complex through an integrative modeling approach that combines data from X-ray crystallography, cryo-electron microscopy, and a high-fidelity chemical crosslinking method. We demonstrate that DCX interacts with MTs through its N-terminal domain and induces a lattice-dependent self-association involving the C-terminal structured domain and its disordered tail, in a conformation that favors an open, domain-swapped state. The networked state can accommodate multiple different attachment points on the MT lattice, all of which orient the C-terminal tails away from the lattice. As numerous disease mutations cluster in the C-terminus, and regulatory phosphorylations cluster in its tail, our study shows that lattice-driven self-assembly is an important property of DCX.

IMProv: A Resource for Cross-link-Driven Structure Modeling that Accommodates Protein Dynamics.

Proteomics methodology has expanded to include protein structural analysis, primarily through cross-linking mass spectrometry (XL-MS) and hydrogen-deuterium exchange mass spectrometry (HX-MS). However, while the structural proteomics community has effective tools for primary data analysis, there is a need for structure modeling pipelines that are accessible to the proteomics specialist. Integrative structural biology requires the aggregation of multiple distinct types of data to generate models that satisfy all inputs. Here, we describe IMProv, an app in the Mass Spec Studio that combines XL-MS data with other structural data, such as cryo-EM densities and crystallographic structures, for integrative structure modeling on high-performance computing platforms. The resource provides an easily deployed bundle that includes the open-source Integrative Modeling Platform program (IMP) and its dependencies. IMProv also provides functionality to adjust cross-link distance restraints according to the underlying dynamics of cross-linked sites, as characterized by HX-MS. A dynamics-driven conditioning of restraint values can improve structure modeling precision, as illustrated by an integrative structure of the five-membered Polycomb Repressive Complex 2. IMProv is extensible to additional types of data.

Improving Spectral Validation Rates in Hydrogen-Deuterium Exchange Data Analysis.

The data analysis practices associated with hydrogen-deuterium exchange mass spectrometry (HX-MS) lag far behind that of most other MS-based protein analysis tools. A reliance on external tools from other fields and a persistent need for manual data validation restrict this powerful technology to the expert user. Here, we provide an extensive upgrade to the HX data analysis suite available in the Mass Spec Studio in the form of two new apps (HX-PIPE and HX-DEAL), completing a workflow that provides an HX-tailored peptide identification capability, accelerated validation routines, automated spectral deconvolution strategies, and a rich set of exportable graphics and statistical reports. With these new tools, we demonstrate that the peptide identifications obtained from undeuterated samples generated at the start of a project contain information that helps predict and control the extent of manual validation required. We also uncover a large fraction of HX-usable peptides that remains unidentified in most experiments. We show that automated spectral deconvolution routines can identify exchange regimes in a project-wide manner, although they remain difficult to accurately assign in all scenarios. Taken together, these new tools provide a robust and complete solution suitable for the analysis of high-complexity HX-MS data.

Harmonizing structural mass spectrometry analyses in the mass spec studio.

Structural Mass Spectrometry (SMS) provides a comprehensive toolbox for the analysis of protein structure and function. It offers multiple sources of structural information that are increasingly useful for integrative structural modeling of complex protein systems. As MS-based structural workflows scale to larger systems, consistent and coherent data interpretation resources are needed to better support modeling. Unlike the proteomics community, practitioners of SMS lack adequate computational tools. Here, we review new developments in the Mass Spec Studio: an expandable ecosystem of workflows for the analysis of complementary SMS techniques with linkages to modeling. Current functionality in the Studio (version 2) supports three major SMS workflows (crosslinking, hydrogen/deuterium exchange and covalent labelling) and two pipelines for structural modeling, with a special focus on data integration. The Mass Spec Studio is an architecture focused on rapid and robust extension of functionality by a community of developers. SIGNIFICANCE: This review surveys the new data analysis capabilities within the Mass Spec Studio, a rich framework for rapid software development specifically targeting the community of structural proteomics and structural mass spectrometry. Updates to crosslinking, hydrogen/deuterium-exchange and covalent labeling apps are provided as well as a utility for translating such analyses into restraints that support integrative structural modeling. These new capabilities, together with the underlying design tools and content, provide the community with a wealth of resources to tackle complex structural problem and design new approaches to data analysis.