BioID2 Mass Spectrometry Service for Target Discovery

BioID2 is a proximity‑dependent biotin ligase. You fuse it to your protein of interest, add biotin, and the enzyme tags everything within roughly a 10‑nanometer radius. That cloud of biotinylated neighbors—transient binders, membrane‑adjacent partners, even proteins that only touch yours for a few seconds—can then be pulled down on streptavidin beads and identified by high‑resolution mass spectrometry.

Because the labeling happens in living cells, the interactions are captured in their native environment. There is no crosslinking step that can lock in artifacts, and the covalent biotin tag is tough enough that you can use stringent wash conditions to get rid of non‑specific binders. Later methods like TurboID and APEX give you faster labeling kinetics, and we work with those too. But BioID2 remains the go‑to when you need a smaller, less toxic enzyme that performs well in whole‑organism models.

The outcome that matters for target discovery is a shortlist of context‑specific interactors that you can take straight into functional validation—whether that's a co‑IP, a PLA, or a phenotypic readout.

Some groups just need a mass spectrometry readout; others need help from the very beginning. We are comfortable jumping in at any point.

When you work with us, you get:

• Full‑workflow coverage. We can design the BioID2 fusion construct, generate stable cell lines or work with transient expression, optimize biotin labeling, perform the enrichment, run the LC‑MS/MS, and deliver the analyzed data. You can hand off one step or the full pipeline.
• Rigorous negative control design. Every project includes a matched control strategy—empty vector, non‑targeting bait, or a catalytically dead enzyme—so that we can distinguish real neighbors from endogenous biotinylated background.
• QC checkpoints you can see. At the protein level, we verify biotinylation efficiency by streptavidin‑HRP western blot. At the peptide level, we monitor enrichment quality and digestion completeness before committing samples to deep mass spectrometry runs.
• Complex samples are welcome. We routinely handle adherent and suspension cell lines, primary cells, and tissue‑derived material. If your model is difficult, we will figure out the right lysis and enrichment conditions during a small‑scale pilot before scaling up.
• A single scientific point of contact. From method development through final data interpretation, you talk to the same PhD‑level scientist who understands the biology, not a triage desk.

The path from a sample to an interaction network has several steps. Here is how it flows in our lab—and where we check progress.

1

Bait expression and biotin labeling

Your BioID2‑tagged protein of interest is expressed in the cell model. We add biotin and incubate for the labeling window you choose (typically 6–24 hours for BioID2). At this point, we confirm expression by western blot and biotinylation by streptavidin‑HRP. If the labeling signal is weak, we adjust biotin concentration or incubation time before proceeding.

2

Cell lysis and streptavidin enrichment

Cells are lysed under denaturing or semi‑native conditions (depending on the bait). Biotinylated proteins are captured on streptavidin‑conjugated beads and washed stringently. We check a small aliquot on SDS‑PAGE with streptavidin‑HRP or silver stain to confirm that the enrichment has worked and that the pattern differs visibly from the negative control.

3

On‑bead digestion and peptide QC

Proteins are reduced, alkylated, and digested directly on the beads with trypsin. Peptide concentration is measured, and a quick LC‑MS/MS test run confirms that the sample complexity and chromatographic quality meet our internal thresholds.

4

LC‑MS/MS data acquisition

Peptides are separated on a nano‑flow UPLC system coupled to a high‑resolution mass spectrometer operating in data‑dependent acquisition (DDA) mode. We use label‑free quantification (LFQ) to compare enrichment across conditions.

5

Data analysis and interactor calling

Raw files are searched against the appropriate protein database. Significantly enriched proteins are identified by comparing the bait condition to the negative control using statistical scoring such as SAINTexpress. The output is a ranked list of high‑confidence proximity interactors.

To give you a sense of what you receive, here are the three types of data views we deliver for a typical BioID2 experiment. The example reflects a comparison between a wild‑type bait and a mutant bait, but the same formats apply regardless of your experimental design.

Differential enrichment volcano plot, interaction network, and GO enrichment

1. Differential enrichment volcano plot. Each point is a protein. The x‑axis shows the log₂ fold‑change between conditions, and the y‑axis shows the statistical significance (−log₁₀ p‑value). Proteins that pass the significance and enrichment thresholds are color‑coded. The plot gives you a single‑glance view of which candidates are worth following up.

2. Protein–protein interaction network. High‑confidence interactors are visualized as nodes, with edges representing known or predicted associations. Clusters often resolve into functional modules—a transcriptional complex here, a trafficking machinery there—which helps you prioritize hits that fall into pathways relevant to your biology.

3. GO enrichment and pathway analysis. Enriched gene ontology terms (biological process, molecular function, cellular component) are shown as a bar or bubble chart. This annotation answers the question: "What processes are over‑represented among my hits?" It is particularly useful when you are exploring an uncharacterized bait and need a compass for functional follow‑up.

Because BioID2 projects often start with a cell model you have already built, the most common submission is live cells or snap‑frozen cell pellets. The table below covers the typical cases.

For samples not listed here, reach out through the inquiry form. We regularly work with primary neurons, organoids, and xenograft material; the preparation protocol just needs a quick feasibility check first.

Every BioID2 project includes a core set of deliverables. We also offer optional add‑ons depending on how far along your analysis pipeline is.

Minimum deliverables — included with every project:

• Raw MS files (.raw and .mzML formats)
• Protein identification and label‑free quantification matrix (.csv or .xlsx)
• List of proteins significantly enriched over the negative control, with fold‑change, p‑value, and confidence score
• QC summary: biotinylation blot image, enrichment gel image, chromatographic quality metrics

Optional add‑ons — available on request:

• Cytoscape‑ready interaction network files and publication‑quality figures
• GO, KEGG, and Reactome pathway enrichment analysis with downloadable result tables
• Custom volcano plots, heatmaps, and Venn diagrams
• Extended statistical analysis, including SAINTexpress scoring and permutation‑based FDR estimation
• A written methods section that you can drop directly into your manuscript

All deliverables are transferred through a secure file‑sharing portal, and we keep your raw data archived for at least 12 months after project close.

Not every proximity labeling enzyme is right for every experiment. The table below pulls together the key differences so you can align the method to your model system and biological question.

How to choose:

• In vivo models and low‑toxicity requirement? Start with BioID2. Its smaller size and lower biotin demand make it the gentlest option for whole‑organism work.
• Fast signaling events in cell culture? TurboID gives you a snapshot in minutes. That speed is worth the extra biotin if your question is time‑sensitive.
• Sub‑minute resolution or EM‑level localization? APEX is the answer. The H₂O₂ pulse is harsh but ultra‑precise.
• Still unsure? Describe your model in the inquiry form. We routinely help teams pick the right enzyme during the feasibility review.