CAD-IA for traumatic brain injury (TBI) diagnostics

Introduction

The glial fibrillary acidic protein (GFAP) is an intermediate protein released by astrocytes and has value as a  serum-based biomarker of neurological abnormalities including traumatic brain injury¹. Inspired by the CAD-LB method for digital assessment of biomarkers on small extracellular vesicles, we sought to create a digital immunoassay for the detection of protein biomarkers. The approach which we call “Catch-and-Display immunoassay” (CAD-IA) uses nanoparticles and antibodies for the capture and detection of  GFAP as a example biomarker. As with CAD-LB, quantification of biomarkers in CAD-IA occurs from imaging fluorescent species captured in the pores of NPN using the µSiM as an imaging platform. We hypothesize that CAD-IA will be an ultra-sensitive and rapid assay for the detection of antibodies in biological samples.

Methods

Generally, the proposed CAD-IA is composed of the “catch” of nanoparticles by uSiM and the “display” of the particle-based immunocomplex under a confocal microscope. The current protocol is stated below (Figure 1),

• 2×10¹⁰ streptavidin-labeled dragon green polystyrene nanoparticles (d.nm=200, ex / em = 480 / 520) are washed with 100uL PBS (1x) for 3 times to remove pre-added EDTA, anti-microbial, and surfactants. The washed beads are resuspended in 100 uL of PBS in a low protein-binding tube.
• 10 uL of biotinylated capture antibody solution (2×10¹⁰ capture ab / uL in PBS so the total capture ab : beads would be 10:1) is added in the tube and reacts for 2 hrs. The capture ab would be conjugated to nanoparticles based on the sensitive and stable interaction of streptavidin-biotin².
• 4×10⁵ capture ab labeled nanoparticles are injected through one port of the uSiM by blocking the other. Remove the tape and wash away free capture ab by rushing 100 uL of PBS through the bottom channel and replace solvent in the well with 100 uL fresh PBS.
• Rush 100 uL of reaction solution with 10¹² alexa fluor 647 (ex / em = 652 / 668) labeled detection ab and 10¹¹ GFAP through bottom channel and preserve the last 10 uL. This will make the total detection ab: GFAP: beads = 10⁵:10⁴:1. Let the reaction go for 2 hrs.
• Wash away free detection ab and GFAP by rushing 100 uL of PBS through the bottom channel for 3 times and replace solvent in the well with 100 uL fresh PBS.
• Imaging the uSiM. Switch the laser resource / filters and calculate the colocalization percentage of “red dots” (immunocomplex linked nanoparticles) to “green dots” (all nanoparticles) (Figure 2).

 

Figure 1. General procedure of CAD-IA.

 

Figure 2. Confocal microscope images uSiM under (a) green channel, green dots are nanoparticles, (b) red channel, red dots are immunocomplex linked nanoparticles, (c) merged channel for colocalization percentage calculation.

 

Results

We also conducted GFAP negative as a control for non-specific binding of antibodies and tried other alternative secondary antibodies to compare with the anti-GFAP detection antibody. For the anti-GFAP detection ab, ~90% of colocalization was seen for GFAP positive and ~20% was seen for GFAP negative which seemed pretty promising. However, there was a ~ 60% colocalization if we substitute our anti-GFAP detection ab with a Alexa fluor 568 labeled anti-rabbit igG, suggesting the great sensitivity of the assay might greatly come from non-specific binding of antibodies (Figure 3).

 

 

Figure 3. Colocalization percentage of “red dots” to “green dots” using (a) anti-GFAP detection ab or (b) anti-rabbit igG control detection ab. N=6 (6 different regions within the same device).

 

Struggling with non-specific binding with different strategies

To reduce the non-specific binding of antibodies, we added 0.1% pluronic f-127 to the reaction solution as surfactants. The colocalization of the anti-rabbit igG group was reduced to a very low level. However, the colocalization of the anti-GFAP detection ab bounced back to a same level for GFAP negative vs positive (Figure 4). We also tried 0.1% BSA as another blocking reagent but a similar result was seen (Figure 5).

To test whether this non-specific binding came from an exclusive non-specific binding ability of our anti-GFAP detection ab, we conducted GFAP negative tests for our Alexa fluor 647 labeled anti-GFAP detection antibody and two control antibodies, Alexa fluor 647 labeled anti-rat igG2a isotype control and Alexa fluor 568 labeled anti-rabbit igG. We also conducted the same tests using nanoparticles before capturing antibody labeling. 0.1% pluronic were still added for blocking. Results shown that 1) for particles before capture antibody conjugation, all 3 detection abs have a very low non-specific binding level, 2) for particles after capture antibody, the two control detection antibodies still remained a low level but our anti-GFAP detection had a sharply increased level (Figure 6).

 

Figure 4. Reduce non-specific binding by adding 0.1% pluronic f-127. Colocalization percentage of “red” to “green” using (a) anti-GFAP detection ab or (b) anti-rabbit igG control detection ab. N=6 (6 different regions within the same device).

 

Figure 5. Reduce non-specific binding by adding 0.1% BSA. Colocalization percentage of “red” to “green” using (a) anti-GFAP detection ab or (b) anti-rabbit igG control detection ab. N=6 (6 different regions within the same device).

 

Figure 6. Non-specific binding of different Alexa fluor labeled antibodies. N=6 (6 different regions within the same device).

 

Conclusions and Future directions

The data we’ve had so far suggests that our anti-GFAP detection antibody has an exclusive non-specific binding ability to the capture ab-conjugated particles, which was not able to be alleviated by blocking with BSA or pluronic f-127. This might be because of a specific interaction within this antibody pair even without the presence of antigen. We will start to look for other resources of antibody pairs for GFAP.

References

1. Button, E. B. et al. Development of a novel, sensitive translational immunoassay to detect plasma glial fibrillary acidic protein (GFAP) after murine traumatic brain injury. Alzheimers. Res. Ther. 13, 58 (2021).
2. Dundas, C. M., Demonte, D. & Park, S. Streptavidin–biotin technology: improvements and innovations in chemical and biological applications. Appl. Microbiol. Biotechnol. 97, 9343–9353 (2013).