Table 4.
Target protein | Reference antibodies | Total no. of candidate antibodies tested | No. of good candidates chosen by expert | No. of good candidates chosen by SACT | SACT false negatives | SACT false positives |
---|---|---|---|---|---|---|
Gephyrin | GAD | 7 | 5 | 4 | 1 | 0 |
Homer | PSD95 | 4 | 1 | 1 | 0 | 0 |
IRSP53 | PSD-95, VGluT1 | 12 | 2 | 2 | 0 | 0 (+1 unclear) |
VGAT | GAD | 17 | 4 | 4 | 0 | 0 (+2 unclear) |
Collybistin | GAD | 19 | 6 | 6 | 0 | 1 |
Bassoon 1st exp. | Synapsin | 19 | 4 | 4 | 0 | 0 (+1 unclear) |
Bassoon 2nd exp. | VGluT1, PSD-95 | 10 | 5 | 5 | 0 | 0 |
Multiple candidate antibodies against the target protein were ranked using measurements from the proposed SACT. The candidate antibodies were independently evaluated by visual inspection of the immunofluorescence images. For each target protein, the reference antibodies were chosen according to the known characteristics of synapses expressing the target protein. Without an objective and automated tool to quantify antibody performance, all antibody evaluations are subjective (as is the standard today). The framework proposed in this work is a first step toward having synaptic antibody quantification be a routine part of antibody evaluation.