Figure 1. Flowchart of the BioID2 application to detect in situ interactions supporting therapeutic proteins secretion.
Figure 2. Expression of bait-BirA proteins results in a substantial increase in biotinylated proteins. a) Successful secretion of the bait-BirA proteins into the culture supernatant was evaluated by Western blot using HRP-anti-flag antibody. b) The immunoblotting biotinylation profiling of the model proteins and WT control in HEK293 cells with HRP-streptavidin. When the BirA domain was fused to the model proteins, biotin addition led to the biotinylation of a subset of proteins (B+) which are not seen in WT or absence of biotin. This demonstrates that the BioID labeling system tags interactions as secreted proteins are synthesized and trafficked through the secretory pathway. A few endogenously biotinylated proteins appear in the absence of biotin and in the WT.
Figure 3. Bait-BirA fusion proteins are colocalized with biotin-staining. Co-Immunofluorescence demonstrated the intracellular colocalization of the biotin-labeled proteins (stained with Streptavidin-Dylight 594 and illustrated in green color) and bait-BirA (stained with anti-flag monoclonal antibody-Dylight 650 and illustrated in red color), while WT did not show increased biotinylation under the same experimental conditions.
Figure 4. Dozens of proteins show significantly increased biotinylation after expression of bait-BirA proteins. Volcano plot showing the distribution of the quantified biotinylated proteins by MS according to p-value and fold change. As depicted the bait-protein significantly showed the highest fold change compared to WT almost in all cases, indicating the capability of the BioID labeling system to tag the in vivo interactors within the live cells. SeAP is a truncated form of Alkaline phosphatase, placental type (ALPP).
Figure 5. Interacting proteins are enriched for secretory pathway machinery. (a) To determine if significant interactions enrich for secretory pathway-related genes, we performed an iterative enrichment analysis in which we included the most significant interactions first and iteratively added interactors with lower fold changes. The y-axis indicates the overall coverage of 3 secretory pathway-related gene sets and the x-axis the significance cutoffs (rank ordered by fold change). The coverage of the gene set (top) along with their corresponding hypergeometric enrichment p-values (bottom) are shown. The top 300 hits for each secretable BirA sample (Fig. S3 for all hits) showed significant enrichment of the secretory pathway components and co-secreted proteins among the most significant hits for all samples except Signal-BirA (which is a lone secreted BirA and not a mammalian secreted protein). (b) Quantified interactions between interactors (x-axis) and the model proteins (y-axis), where the shadowed entries indicate significant interactions. The features of the model proteins, detailed in Fig. 6, are summarized for each model protein on the left and the interactors are labeled on top based on their secretory pathway attributes.
Figure 6. The bait proteins show diversity in their PTM and structural content. Dots and lines represent known PTM sites and structural motifs in panel (a) and (b) respectively. The hills and valleys indicate protein tertiary features. Note that solvent accessibility and structural motifs are only available for regions covered by the PDB structure, whereas predicted features such as protein hydrophobicity and disorder are available for the entire protein.
Figure 7. Detected interactors correlate with protein features.Interactors were associated with specific (a) PTMs and (b) structural features of model proteins. The heatmap shows the standardized interaction affinities estimated between certain interactors and PTMs or structural features across all model proteins (see methods). Only interactors having significant associations with model protein features are shown.