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Han L, Nguyen L, Schmidt EN, Esmaili M, Kitova EN, Overduin M, Macauley MS, Klassen JS. How Choice of Model Membrane Affects Protein–Glycosphingolipid Interactions: Insights from Native Mass Spectrometry. Anal Chem 2022; 94:16042-16049. [PMID: 36367338 DOI: 10.1021/acs.analchem.2c03067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
Interactions between glycan-binding proteins (GBPs) and glycosphingolipids (GSLs) are involved in numerous physiological and pathophysiological processes. Many model membrane systems are available for studying GBP-GSL interactions, but a systematic investigation has not been carried out on how the nature of the model membrane affects binding. In this work, we use electrospray ionization mass spectrometry (ESI-MS), both direct and competitive assays, to measure the binding of cholera toxin B subunit homopentamer (CTB5) to GM1 ganglioside in liposomes, bilayer islands [styrene maleic acid lipid particles (SMALPs), nanodiscs (NDs), and picodiscs (PDs)], and micelles. We find that direct ESI-MS analysis of CTB5 binding to GM1 is unreliable due to non-uniform response factors, incomplete extraction of bound GM1 in the gas phase, and nonspecific CTB5-GM1 interactions. Conversely, indirect proxy ligand ESI-MS measurements show that the intrinsic (per binding site) association constants of CTB5 for PDs, NDs, and SMALPs are similar and comparable to the affinity of soluble GM1 pentasaccharide (GM1os). The observed affinity decreases with increasing GM1 content due to molecular crowding stemming from GM1 clustering. Unlike the smaller model membranes, the observed affinity of CTB5 toward GM1 liposomes is ∼10-fold weaker than GM1os and relatively insensitive to the GM1 content. GM1 glycomicelles exhibit the lowest affinity, ∼35-fold weaker than GM1os. Together, the results highlight experimental design considerations for quantitative GBP-GSL binding studies involving multisubunit GBPs and factors to consider when comparing results obtained with different membrane systems. Notably, they suggest that bilayer islands with a low percentage of GSL, wherein clustering is minimized, are ideal for assessing intrinsic strength of GBP-GSL interactions in a membrane environment, while binding to liposomes, which is sub-optimal due to extensive clustering, may be more representative of authentic cellular environments.
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Affiliation(s)
- Ling Han
- Department of Chemistry, University of Alberta, Edmonton T6G 2G2, Alberta, Canada
| | - Linh Nguyen
- Department of Chemistry, University of Alberta, Edmonton T6G 2G2, Alberta, Canada
| | - Edward N. Schmidt
- Department of Chemistry, University of Alberta, Edmonton T6G 2G2, Alberta, Canada
| | - Mansoore Esmaili
- Department of Biochemistry, University of Alberta, Edmonton T6G 2R3, Canada
| | - Elena N. Kitova
- Department of Chemistry, University of Alberta, Edmonton T6G 2G2, Alberta, Canada
| | - Michael Overduin
- Department of Biochemistry, University of Alberta, Edmonton T6G 2R3, Canada
| | - Matthew S. Macauley
- Department of Chemistry, University of Alberta, Edmonton T6G 2G2, Alberta, Canada
- Department of Medical Microbiology and Immunology, University of Alberta, Edmonton T6G 2E1, Alberta, Canada
| | - John S. Klassen
- Department of Chemistry, University of Alberta, Edmonton T6G 2G2, Alberta, Canada
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Bui D, Li Z, Kitov PI, Han L, Kitova EN, Fortier M, Fuselier C, Granger Joly de Boissel P, Chatenet D, Doucet N, Tompkins SM, St-Pierre Y, Mahal LK, Klassen JS. Quantifying Biomolecular Interactions Using Slow Mixing Mode (SLOMO) Nanoflow ESI-MS. ACS CENTRAL SCIENCE 2022; 8:963-974. [PMID: 35912341 PMCID: PMC9335916 DOI: 10.1021/acscentsci.2c00215] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2023]
Abstract
Electrospray ionization mass spectrometry (ESI-MS) is a powerful label-free assay for detecting noncovalent biomolecular complexes in vitro and is increasingly used to quantify binding thermochemistry. A common assumption made in ESI-MS affinity measurements is that the relative ion signals of free and bound species quantitatively reflect their relative concentrations in solution. However, this is valid only when the interacting species and their complexes have similar ESI-MS response factors (RFs). For many biomolecular complexes, such as protein-protein interactions, this condition is not satisfied. Existing strategies to correct for nonuniform RFs are generally incompatible with static nanoflow ESI (nanoESI) sources, which are typically used for biomolecular interaction studies, thereby significantly limiting the utility of ESI-MS. Here, we introduce slow mixing mode (SLOMO) nanoESI-MS, a direct technique that allows both the RF and affinity (K d) for a biomolecular interaction to be determined from a single measurement using static nanoESI. The approach relies on the continuous monitoring of interacting species and their complexes under nonhomogeneous solution conditions. Changes in ion signals of free and bound species as the system approaches or moves away from a steady-state condition allow the relative RFs of the free and bound species to be determined. Combining the relative RF and the relative abundances measured under equilibrium conditions enables the K d to be calculated. The reliability of SLOMO and its ease of use is demonstrated through affinity measurements performed on peptide-antibiotic, protease-protein inhibitor, and protein oligomerization systems. Finally, affinities measured for the binding of human and bacterial lectins to a nanobody, a viral glycoprotein, and glycolipids displayed within a model membrane highlight the tremendous power and versatility of SLOMO for accurately quantifying a wide range of biomolecular interactions important to human health and disease.
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Affiliation(s)
- Duong
T. Bui
- Department
of Chemistry, University of Alberta, Edmonton, Alberta T6G 2G2, Canada
| | - Zhixiong Li
- Department
of Chemistry, University of Alberta, Edmonton, Alberta T6G 2G2, Canada
| | - Pavel I. Kitov
- Department
of Chemistry, University of Alberta, Edmonton, Alberta T6G 2G2, Canada
| | - Ling Han
- Department
of Chemistry, University of Alberta, Edmonton, Alberta T6G 2G2, Canada
| | - Elena N. Kitova
- Department
of Chemistry, University of Alberta, Edmonton, Alberta T6G 2G2, Canada
| | - Marlène Fortier
- Centre
Armand-Frappier Santé Biotechnologie, Institut National de la Recherche Scientifique (INRS), Université
du Québec, Laval, Québec H7V 1B7, Canada
| | - Camille Fuselier
- Centre
Armand-Frappier Santé Biotechnologie, Institut National de la Recherche Scientifique (INRS), Université
du Québec, Laval, Québec H7V 1B7, Canada
| | - Philippine Granger Joly de Boissel
- Centre
Armand-Frappier Santé Biotechnologie, Institut National de la Recherche Scientifique (INRS), Université
du Québec, Laval, Québec H7V 1B7, Canada
| | - David Chatenet
- Centre
Armand-Frappier Santé Biotechnologie, Institut National de la Recherche Scientifique (INRS), Université
du Québec, Laval, Québec H7V 1B7, Canada
| | - Nicolas Doucet
- Centre
Armand-Frappier Santé Biotechnologie, Institut National de la Recherche Scientifique (INRS), Université
du Québec, Laval, Québec H7V 1B7, Canada
| | - Stephen M. Tompkins
- Center
for Vaccines and Immunology, University
of Georgia, Athens, Georgia 30605, United States
- Emory-UGA
Centers of Excellence for Influenza Research and Surveillance (CEIRS), Emory University School of Medicine, Athens, Georgia 30322, United States
| | - Yves St-Pierre
- Centre
Armand-Frappier Santé Biotechnologie, Institut National de la Recherche Scientifique (INRS), Université
du Québec, Laval, Québec H7V 1B7, Canada
| | - Lara K. Mahal
- Department
of Chemistry, University of Alberta, Edmonton, Alberta T6G 2G2, Canada
| | - John S. Klassen
- Department
of Chemistry, University of Alberta, Edmonton, Alberta T6G 2G2, Canada
- . Telephone: (780) 492-3501. Fax: (780) 492-8231
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Abstract
Native mass spectrometry (MS) is aimed at preserving and determining the native structure, composition, and stoichiometry of biomolecules and their complexes from solution after they are transferred into the gas phase. Major improvements in native MS instrumentation and experimental methods over the past few decades have led to a concomitant increase in the complexity and heterogeneity of samples that can be analyzed, including protein-ligand complexes, protein complexes with multiple coexisting stoichiometries, and membrane protein-lipid assemblies. Heterogeneous features of these biomolecular samples can be important for understanding structure and function. However, sample heterogeneity can make assignment of ion mass, charge, composition, and structure very challenging due to the overlap of tens or even hundreds of peaks in the mass spectrum. In this review, we cover data analysis, experimental, and instrumental advances and strategies aimed at solving this problem, with an in-depth discussion of theoretical and practical aspects of the use of available deconvolution algorithms and tools. We also reflect upon current challenges and provide a view of the future of this exciting field.
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Affiliation(s)
- Amber D Rolland
- Department of Chemistry and Biochemistry, University of Oregon, Eugene, Oregon 97403-1253, United States
| | - James S Prell
- Department of Chemistry and Biochemistry, University of Oregon, Eugene, Oregon 97403-1253, United States.,Materials Science Institute, University of Oregon, Eugene, Oregon 97403-1252, United States
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