Data supporting manuscript submitted to PNAS: Video-Rate Raman-based Metabolic Imaging by Airy Light-Sheet Illumination and Photon-Sparse Detection. The data set includes: [1] raw data and [2] related images used in the analyses described within the manuscript.

Despite its massive potential, Raman imaging represents just a modest fraction of all research and clinical microscopy to-date. This is due to the ultralow Raman scattering cross-sections of most biomolecules that impose low-light or photon-sparse conditions. Bioimaging under such conditions is suboptimal, as it either results in ultralow frame-rates or requires increased levels of irradiance. Here, we overcome this tradeoff by introducing Raman imaging that operates at both video-rates and 1000-fold lower irradiance than state-of-the-art methods. To accomplish this, we deployed a judicially de-signed Airy light-sheet microscope to efficiently image large specimen regions. Further, we implemented sub-photon per pixel image acquisition and reconstruction to confront issues arising from photon sparsity at just msec integrations. We demonstrate the versatility of our approach by imaging a variety of samples, including the 3D metabolic activity of single microbial cells and the underlying cell-to-cell variability. To image such small-scale targets, we again harnessed photon-sparsity to increase magnification with-out a field-of-view penalty, thus, overcoming another key limitation in modern light-sheet microscopy.

Data Use:
License: CC-BY 4.0
Recommended Citation: Vasdekis AE (2022) Data from: Video-rate raman-based metabolic imaging by airy light-sheet illumination and photon-sparse detection [Dataset]. University of Idaho.