A strategy for the identification of protein architectures directly from ion mobility mass spectrometry data reveals stabilizing subunit interactions in light harvesting complexes

Exploring snake venoms beyond the primary sequence: From proteoforms to protein-protein interactions

Snakebite envenomation has been a long-standing global issue that is difficult to treat, largely owing to the flawed nature of current immunoglobulin-based antivenom therapy and the complexity of snake venoms as sophisticated mixtures of bioactive proteins and peptides. Comprehensive characterisation of venom compositions is essential to better understanding snake venom toxicity and inform effective and rationally designed antivenoms. Additionally, a greater understanding of snake venom composition will likely unearth novel biologically active proteins and peptides that have promising therapeutic or biotechnological applications. While a bottom-up proteomic workflow has been the main approach for cataloguing snake venom compositions at the toxin family level, it is unable to capture snake venom heterogeneity in the form of protein isoforms and higher-order protein interactions that are important in driving venom toxicity but remain underexplored. This review aims to highlight the importance of understanding snake venom heterogeneity beyond the primary sequence, in the form of post-translational modifications that give rise to different proteoforms and the myriad of higher-order protein complexes in snake venoms. We focus on current top-down proteomic workflows to identify snake venom proteoforms and further discuss alternative or novel separation, instrumentation, and data processing strategies that may improve proteoform identification. The current higher-order structural characterisation techniques implemented for snake venom proteins are also discussed; we emphasise the need for complementary and higher resolution structural bioanalytical techniques such as mass spectrometry-based approaches, X-ray crystallography and cryogenic electron microscopy, to elucidate poorly characterised tertiary and quaternary protein structures. We envisage that the expansion of the snake venom characterisation "toolbox" with top-down proteomics and high-resolution protein structure determination techniques will be pivotal in advancing structural understanding of snake venoms towards the development of improved therapeutic and biotechnology applications.

Collision induced unfolding and molecular dynamics simulations of norovirus capsid dimers reveal strain-specific stability profiles

Collision induced unfolding (CIU) is a method used with ion mobility mass spectrometry to examine protein structures and their stability. Such experiments yield information about higher order protein structures, yet are unable to provide details about the underlying processes. That information can however be provided using molecular dynamics simulations. Here, we investigate the gas-phase unfolding of norovirus capsid dimers from the Norwalk and Kawasaki strains by employing molecular dynamics simulations over a range of temperatures, representing different levels of activation, together with CIU experiments. The dimers have highly similar structures, but their CIU reveals different stability that can be explained by the different dynamics that arises in response to the activation seen in the simulations, including a part of the sequence with previously observed strain-specific dynamics in solution. Our findings show how similar protein variants can be examined using mass spectrometric techniques in conjunction with atomistic molecular dynamics simulations to reveal differences in stability as well as differences in how and where unfolding takes place upon activation.

Predicting ion mobility collision cross sections using projection approximation with ROSIE-PARCS webserver

Ion mobility coupled to mass spectrometry informs on the shape and size of protein structures in the form of a collision cross section (CCSIM). Although there are several computational methods for predicting CCSIM based on protein structures, including our previously developed projection approximation using rough circular shapes (PARCS), the process usually requires prior experience with the command-line interface. To overcome this challenge, here we present a web application on the Rosetta Online Server that Includes Everyone (ROSIE) webserver to predict CCSIM from protein structure using projection approximation with PARCS. In this web interface, the user is only required to provide one or more PDB files as input. Results from our case studies suggest that CCSIM predictions (with ROSIE-PARCS) are highly accurate with an average error of 6.12%. Furthermore, the absolute difference between CCSIM and CCSPARCS can help in distinguishing accurate from inaccurate AlphaFold2 protein structure predictions. ROSIE-PARCS is designed with a user-friendly interface, is available publicly and is free to use. The ROSIE-PARCS web interface is supported by all major web browsers and can be accessed via this link (https://rosie.graylab.jhu.edu).

The increasing role of structural proteomics in cyanobacteria

Cyanobacteria, also known as blue–green algae, are ubiquitous organisms on the planet. They contain tremendous protein machineries that are of interest to the biotechnology industry and beyond. Recently, the number of annotated cyanobacterial genomes has expanded, enabling structural studies on known gene-coded proteins to accelerate. This review focuses on the advances in mass spectrometry (MS) that have enabled structural proteomics studies to be performed on the proteins and protein complexes within cyanobacteria. The review also showcases examples whereby MS has revealed critical mechanistic information behind how these remarkable machines within cyanobacteria function.

Extraction and purification of phycobiliproteins from algae and their applications

Microalgae, macroalgae and cyanobacteria are photosynthetic microorganisms, prokaryotic or eukaryotic, living in saline or freshwater environments. These have been recognized as valuable carbon sources, able to be used for food, feed, chemicals, and biopharmaceuticals. From the range of valuable compounds produced by these cells, some of the most interesting are the pigments, including chlorophylls, carotenoids, and phycobiliproteins. Phycobiliproteins are photosynthetic light-harvesting and water-soluble proteins. In this work, the downstream processes being applied to recover fluorescent proteins from marine and freshwater biomass are reviewed. The various types of biomasses, namely macroalgae, microalgae, and cyanobacteria, are highlighted and the solvents and techniques applied in the extraction and purification of the fluorescent proteins, as well as their main applications while being fluorescent/luminescent are discussed. In the end, a critical perspective on how the phycobiliproteins business may benefit from the development of cost-effective downstream processes and their integration with the final application demands, namely regarding their stability, will be provided.

Methods to improve quantitative glycoprotein coverage from bottom-up LC-MS data

Advances in mass spectrometry instrumentation, methods development, and bioinformatics have greatly improved the ease and accuracy of site-specific, quantitative glycoproteomics analysis. Data-dependent acquisition is the most popular method for identification and quantification of glycopeptides; however, complete coverage of glycosylation site glycoforms remains elusive with this method. Targeted acquisition methods improve the precision and accuracy of quantification, but at the cost of throughput and discoverability. Data-independent acquisition (DIA) holds great promise for more complete and highly quantitative site-specific glycoproteomics analysis, while maintaining the ability to discover novel glycopeptides without prior knowledge. We review additional features that can be used to increase selectivity and coverage to the DIA workflow: retention time modeling, which would simplify the interpretation of complex tandem mass spectra, and ion mobility separation, which would maximize the sampling of all precursors at a giving chromatographic retention time. The instrumentation and bioinformatics to incorporate these features into glycoproteomics analysis exist. These improvements in quantitative, site-specific analysis will enable researchers to assess glycosylation similarity in related biological systems, answering new questions about the interplay between glycosylation state and biological function.

Protein shape sampled by ion mobility mass spectrometry consistently improves protein structure prediction

Ion mobility (IM) mass spectrometry provides structural information about protein shape and size in the form of an orientationally-averaged collision cross-section (CCS_IM). While IM data have been used with various computational methods, they have not yet been utilized to predict monomeric protein structure from sequence. Here, we show that IM data can significantly improve protein structure determination using the modelling suite Rosetta. We develop the Rosetta Projection Approximation using Rough Circular Shapes (PARCS) algorithm that allows for fast and accurate prediction of CCS_IM from structure. Following successful testing of the PARCS algorithm, we use an integrative modelling approach to utilize IM data for protein structure prediction. Additionally, we propose a confidence metric that identifies near native models in the absence of a known structure. The results of this study demonstrate the ability of IM data to consistently improve protein structure prediction.

Collision cross sections (CCS) from ion mobility mass spectrometry provide information about protein shape and size. Here, the authors develop an algorithm to predict CCS and integrate experimental ion mobility data into Rosetta-based molecular modelling to predict protein structures from sequence.

Rapid Cyanobacteria Species Identification with High Sensitivity Using Native Mass Spectrometry

Cyanobacteria have evolved over billions of years to adapt and survive in diverse climates. Environmentally, this presents a huge challenge because cyanobacteria can now rapidly form algae blooms that are detrimental to aquatic life. In addition, many cyanobacteria produce toxins, making them hazardous to animals and humans that they encounter. Rapid identification of cyanobacteria is essential to monitor and prevent toxic algae blooms. Here, we show for the first time how native mass spectrometry can quickly and precisely identify cyanobacteria from diverse aquatic environments. By monitoring phycobiliproteins, abundant protein complexes within cyanobacteria, simple, easy-to-understand mass spectral "fingerprints" were created that were unique to each species. Moreover, our method is 10-fold more sensitive than the current MALDI-TOF mass spectrometric methods, meaning that cyanobacteria can be monitored using this technology prior to bloom formation. Together, the data show great promise for the simultaneous detection and identification of co-existing cyanobacteria in situ.

High-Resolution Native Mass Spectrometry

Native mass spectrometry (MS) involves the analysis and characterization of macromolecules, predominantly intact proteins and protein complexes, whereby as much as possible the native structural features of the analytes are retained. As such, native MS enables the study of secondary, tertiary, and even quaternary structure of proteins and other biomolecules. Native MS represents a relatively recent addition to the analytical toolbox of mass spectrometry and has over the past decade experienced immense growth, especially in enhancing sensitivity and resolving power but also in ease of use. With the advent of dedicated mass analyzers, sample preparation and separation approaches, targeted fragmentation techniques, and software solutions, the number of practitioners and novel applications has risen in both academia and industry. This review focuses on recent developments, particularly in high-resolution native MS, describing applications in the structural analysis of protein assemblies, proteoform profiling of—among others—biopharmaceuticals and plasma proteins, and quantitative and qualitative analysis of protein–ligand interactions, with the latter covering lipid, drug, and carbohydrate molecules, to name a few.

THE IMS PARADOX: A PERSPECTIVE ON STRUCTURAL ION MOBILITY-MASS SPECTROMETRY

Studies of large proteins, protein complexes, and membrane protein complexes pose new challenges, most notably the need for increased ion mobility (IM) and mass spectrometry (MS) resolution. This review covers evolutionary developments in IM-MS in the authors' and key collaborators' laboratories with specific focus on developments that enhance the utility of IM-MS for structural analysis. IM-MS measurements are performed on gas phase ions, thus "structural IM-MS" appears paradoxical-do gas phase ions retain their solution phase structure? There is growing evidence to support the notion that solution phase structure(s) can be retained by the gas phase ions. It should not go unnoticed that we use "structures" in this statement because an important feature of IM-MS is the ability to deal with conformationally heterogeneous systems, thus providing a direct measure of conformational entropy. The extension of this work to large proteins and protein complexes has motivated our development of Fourier-transform IM-MS instruments, a strategy first described by Hill and coworkers in 1985 (Anal Chem, 1985, 57, pp. 402-406) that has proved to be a game-changer in our quest to merge drift tube (DT) and ion mobility and the high mass resolution orbitrap MS instruments. DT-IMS is the only method that allows first-principles determinations of rotationally averaged collision cross sections (CSS), which is essential for studies of biomolecules where the conformational diversities of the molecule precludes the use of CCS calibration approaches. The Fourier transform-IM-orbitrap instrument described here also incorporates the full suite of native MS/IM-MS capabilities that are currently employed in the most advanced native MS/IM-MS instruments. © 2020 John Wiley & Sons Ltd. Mass Spec Rev.

Predicting the Shapes of Protein Complexes through Collision Cross Section Measurements and Database Searches

In structural biology, collision cross sections (CCSs) from ion mobility mass spectrometry (IM-MS) measurements are routinely compared to computationally or experimentally derived protein structures. Here, we investigate whether CCS data can inform about the shape of a protein in the absence of specific reference structures. Analysis of the proteins in the CCS database shows that protein complexes with low apparent densities are structurally more diverse than those with a high apparent density. Although assigning protein shapes purely on CCS data is not possible, we find that we can distinguish oblate- and prolate-shaped protein complexes by using the CCS, molecular weight, and oligomeric states to mine the Protein Data Bank (PDB) for potentially similar protein structures. Furthermore, comparing the CCS of a ferritin cage to the solution structures in the PDB reveals significant deviations caused by structural collapse in the gas phase. We then apply the strategy to an integral membrane protein by comparing the shapes of a prokaryotic and a eukaryotic sodium/proton antiporter homologue. We conclude that mining the PDB with IM-MS data is a time-effective way to derive low-resolution structural models.