Probing intracellular biomarkers and mediators of cell activation using nanosensors and bioorthogonal chemistry

Abstract

Nanomaterials offer unique physical properties that make them ideal biosensors for scant cell populations. However, specific targeting of nanoparticles to intracellular proteins has been challenging. Here, we describe a technique to improve intracellular biomarker sensing using nanoparticles that is based on bioorthogonal chemistry. Using trans-cyclooctene-modified affinity ligands that are administered to semipermeabilized cells and revealed by cycloaddition reaction with tetrazine-conjugated nanoparticles, we demonstrate site-specific amplification of nanomaterial binding. We also show that this technique is capable of sensing protein biomarkers and phosho-protein signal mediators, both within the cytosol and nucleus, via magnetic or fluorescent modalities. We expect the described method will have broad applications in nanomaterial-based diagnostics and therapeutics.

Figure 1

Targeting nanoparticles to intracellular markers using bioorthogonal chemistry coupling. (a) Semipermeabilization of intact cells allows nanoparticle targeting to a variety of intracellular biomarkers as wells as indicators of cell growth, activation, and survival. (b) BOND targeting scheme using a TCO-modified antibody followed by Tz nanoparticle to amplify nanoparticle binding. (c) Investigation of various cell treatments to optimize secondary permeabilization (NT, no treatment; Tw20, Tween 20; TX, Triton X-100; Meth, methanol; Spn, saponin) following fixation. A freeze–thaw treatment prior to fixation was also tested along with saponin (FT/Spn). Optimal MFNP signal-to-background ratios were obtained with the free-ze–thaw/Spn treatment for both cytoplasmic (CK) and nuclear (K_i-67) targets. (d) Increasing the TCO valency on the anti-CK antibody increased MFNP signal. (e) Binding isotherms obtained for targeting CK using BOND-2 and a direct MFNP immuno-conjugate prepared using the TCO/Tz chemistry (BOND-1). Control signals were obtained using Tz-MFNP only. BOND-2 yielded higher MFNP signals at all concentrations, with differences exceeding 10-fold. Error bars represent the standard error from at least three independent experiments.

Figure 2

Nanoparticle targeting to intracellular markers is specific and representative of molecular expression level. (a) MFNP fluorescence correlated closely with molecular expression determined by antibody staining for panels of cell lines expressing various amounts of CK and K_i-67. (b) Confocal microscopy images of SK-BR-3 (i–iv) and PANC-1 (v–viii) cells targeted for CK and K_i-67, respectively. In both cases, antibodies were labeled with both TCO (3–4 per antibody) and AlexaFluor-488 fluorescent dye. Following MFNP labeling, images were captured at 488 (antibody, pseudocolored green, i and v) and 680 (MFNP, pseudocolored red, ii and vi) nm emission. Merged images reveal excellent correlation between the two signals (iii and vii). Controls determined using a nonbinding, TCO-modified control antibody were negative (iv and viii). The scale bars in (i) and (v) represent 10 μm. Error bars represent the standard error from at least three independent experiments.

Figure 3

Profiling scant tumor cell populations for key biomarkers of cancer using diagnostic magnetic resonance (DMR). (a) Detection of eight biomarkers in eight different cell lines using MFNP based on nuclear magnetic resonance signal. The transverse relaxation rate (R₂) was measured for ∼1000 cells using a miniaturized DMR device. Marker expression levels were determined based on the ratio of the positive marker (ΔR₂⁺) and control (ΔR₂^θ) signals (see Methods). (b) Magnetic measurements showed excellent correlation with marker expression levels determined independently by antibody staining (see Supporting Information Table S2). (d) Confocal images demonstrating varying cellular localizations and signal intensities obtained for each specific marker (top) and controls (bottom). PANC-1 cells were used for CK, vimentin, p-ERK, p-S6RP, K_i-67, and p53 images. A431 cells were used for both EGFR cases. All scale bars represent 10 μm. Error bars represent the standard error from at least three μNMR measurements. Abbreviations: p-, phosphorylation specific; S6RP, S6 ribosomal protein.

Figure 4

Therapeutic effects can be monitored using DMR on scant cell populations. (a) Gefitinib inhibits signaling via EGFR, ultimately leading to inhibition of the mTOR pathway and decreased cell growth. Rapamycin is a direct inhibitor of mTOR, leading to similar effects. (b,c) Three cell lines (A431, NCI-H1650, and A549) were treated with varying doses of gefitinib (1 to 1000 nM) or rapamycin (0.05 to 50 nM) for 12 h, and p-S6RP was used as a read-out of drug efficacy. (b) A431 and NCI-H1650 cell lines were highly sensitive to gefitinib, although the latter was only inhibited by 50%, and A549 cells were resistant. (d) Rapamycin inhibited all cell lines equally. Error bars represent the standard error from at least three μNMR measurements.

Figure 5

Quantum dots (QDs) can be targeted with high specificity using the described techniques. The Tz-QDs were targeted to PANC-1 cells labeled with TCO-modified, AF488 fluorescent antibodies to CK and K_i-67 as in Figure 2. Merged images demonstrate strong colocalization between the positive signals, confirming that QDs are targeted with high specificity to the intended target. The scale bar in (i) represents 10 μm.