The worldwide SARS-CoV-2 outbreak poses a serious challenge to human societies and economies. SARS-CoV-2 proteins orchestrate complex pathogenic mechanisms that underlie COVID-19 disease. Thus, understanding how viral polypeptides rewire host protein networks enables better-founded therapeutic research. In complement to existing proteomic studies, in this study we define the first proximal interaction network of SARS-CoV-2 proteins, at the whole proteome level in human cells. Applying a proximity-dependent biotinylation (BioID)-based approach greatly expanded the current knowledge by detecting interactions within poorly soluble compartments, transient, and/or of weak affinity in living cells. Our BioID study was complemented by a stringent filtering and uncovered 2,128 unique cellular targets (1,717 not previously associated with SARS-CoV-1 or 2 proteins) connected to the N- and C-ter BioID-tagged 28 SARS-CoV-2 proteins by a total of 5,415 (5,236 new) proximal interactions. In order to facilitate data exploitation, an innovative interactive 3D web interface was developed to allow customized analysis and exploration of the landscape of interactions (accessible at http://www.sars-cov-2-interactome.org/). Interestingly, 342 membrane proteins including interferon and interleukin pathways factors, were associated with specific viral proteins. We uncovered ORF7a and ORF7b protein proximal partners that could be related to anosmia and ageusia symptoms. Moreover, comparing proximal interactomes in basal and infection-mimicking conditions (poly(I:C) treatment) allowed us to detect novel links with major antiviral response pathway components, such as ORF9b with MAVS and ISG20; N with PKR and TARB2; NSP2 with RIG-I and STAT1; NSP16 with PARP9-DTX3L. Altogether, our study provides an unprecedented comprehensive resource for understanding how SARS-CoV-2 proteins orchestrate host proteome remodeling and innate immune response evasion, which can inform development of targeted therapeutic strategies.
Due
to their ease of use and high binding affinity, streptavidin-based
purification tools have become widely used for isolating biotinylated
compounds from complex mixtures. We and others routinely use streptavidin–sepharose
matrices to isolate biotinylated polypeptides generated in proximity-dependent
biotinylation approaches, such as BioID or APEX. However, we noted
sporadic, substantial variation in the quality of BioID experiments
performed in the same laboratories over time, using seemingly identical
protocols. Identifying the source of this problem, here, we highlight
considerable variability in streptavidin contamination derived from
different production lots of streptavidin–sepharose beads from
the same manufacturer and demonstrate that high levels of streptavidin
peptide contamination can have detrimental effects on BioID data.
We also describe two simple, rapid approaches to assess the degree
of streptavidin “shedding” from individual lots of the
sepharose matrix before use to avoid the use of lower quality reagent.
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