Mapping the global landscape of HIV protein complexes in CD4+ T-Cells and macrophages using Size Exclusion Chromatography Mass Spectrometry (SEC-MS)

Human immunodeficiency virus (HIV) relies on host-virus protein-protein interactions (PPIs) to establish viral replication and latency. Comprehensive analyses of protein complex assembly and composition are crucial to understanding how HIV-infected cells coordinate diverse functions, underscoring the need for techniques to dynamically map PPIs¹. Here, we propose size exclusion chromatography mass spectrometry (SEC-MS) as an unbiased method to identify and map endogenous HIV-host PPIs associated with host innate immune responses in primary human immune cells². Our method provides a streamlined experimental and computational workflow for rapid profiling of protein complex organization in primary human CD4+ T-Cells and macrophages (M0, M1, and M2) using SEC-MS in combination with Data-Independent Acquisition (DIA) and Sequential Windowed Acquisition of All Theoretical Mass Spectra (SWATH-MS)^1,3. This pipeline offers a fast, condition-specific methodology to study global protein complex dynamics in the context of HIV infection of primary human immune cells. We also demonstrate that complexing SEC-MS with previously established methods including affinity purification mass spectrometry (AP-MS), crosslinking mass spectrometry (XL-MS), and CRISPRa/n genetic screens provides a powerful multi-pronged approach to characterizing elusive endogenous host-HIV PPIs in CD4+ T-Cells and macrophages^4,5,6. Our study highlights the advantages of using SEC-MS, in conjunction with other established proteomics techniques, to dynamically investigate host-virus PPIs involved in HIV infection of primary human innate immune cells, potentially unveiling novel targets for future therapeutic intervention.

References

¹Hiatt et al. Nat Commun. 2022.

²Fossati et al. Methods Mol Biol. 2021.

³Rathore et al. mBio. 2024.

⁴Jäger et al. Nature. 2011.

⁵Kaake et al. Mol Cell Proteomics. 2011.

⁶Kao et al. Mol Cell Proteomics. 2011.