Chemical imaging of cellular ultrastructure by null-deflection infrared spectroscopic measurements

Nearfield spectroscopic imaging techniques can be a powerful tool to map both cellular ultrastructure and molecular composition simultaneously but are currently limited in measurement capability. Resonance enhanced (RE) atomic force microscopy infrared (AFM-IR) spectroscopic imaging offers high-sensitivity measurements, for example, but probe-sample mechanical coupling, nonmolecular optical gradient forces, and noise overwhelm recorded chemical signals. Here, we analyze the key factors limiting AFM-IR measurements and propose an instrument design that enables high-sensitivity nanoscale IR imaging by combining null-deflection measurements with RE sensitivity. Our developed null-deflection scanning probe IR (NDIR) spectroscopic imaging provides similar to 24x improvement in signal-to-noise ratio (SNR) compared with the state of the art, enables optimal signal recording by combining cantilever resonance with maximum laser power, and reduces background nonmolecular signals for improved analytical accuracy. We demonstrate the use of these properties for high-sensitivity, hyperspectral imaging of chemical domains in 100-nm-thick sections of cellular acini of a prototypical cancer model cell line, MCF-10A. NDIR chemical imaging enables facile recording of label-free, chemically accurate, high-SNR vibrational spectroscopic data from nanoscale domains, paving the path for routine studies of biomedical, forensic, and materials samples.

Automated summary

Nearfield spectroscopic imaging techniques can be a powerful tool to simultaneously map cellular ultrastructure and molecular composition, but their current capabilities are limited. This study proposes an instrument design that combines null-deflection measurements with resonance enhancement to achieve high-sensitivity nanoscale infrared imaging. Experimental results using cellular acini samples demonstrate the ability of this method to easily record high-quality chemical imaging data.