Hyperspectral Image Analysis of Live Cells in Various Cell Cycle Stages

Abstract

In this study we have explored the use of hyperspectral imaging (HSI) to determine the cell cycle status of live cells in culture. Live cancer cell lines in culture were either synchronized by release from nocodazole or arrested in various cell cycle phases with serum starvation (G 1 ), aphidicolin (S), or nocodazole (G 2 /M). The live cells were then stained with the fluorescent DNA binding dyes Heochst 33342 or DCO along with propidium iodide or MTR. Samples were examined using fluorescence microscopy and entire spectral emission profiles were acquired for each sample using a PARISS HSI system. Classified spectra were incorporated into spectral libraries. All spectra acquired from each sample were correlated with library spectra to a user-determined confidence threshold, generating unique spectral signatures for each sample. Examination of these spectral signatures revealed that all cell cycle phases could be objectively differentiated. Ongoing studies employing other viable cell fluorescent dyes, and dyes in combination may provide more robust spectral signatures defining the status and condition of living cells.

Thin-film tunable filters for hyperspectral fluorescence microscopy

“…21,22 The spectral filter is a key component of a hyperspectral imaging system. Unlike traditional fluorescence microscopy, hyperspectral microscopy systems have utilized a variety of spectral filtering technologies, including gratings, 23,24 prisms, 25,26 and tunable filters. 3,7,27,28 Garini et al and Lerner et al offer overviews of many commercially available filtering technologies.…”

Interactive hyperspectral approach for exploring and interpreting DESI-MS images of cancerous and normal tissue sections

“…18 It has also been successfully applied to spectroscopic data in order to investigate physiological and pathological changes in living tissue, both animal and human, and to provide information on the health and disease state of tissue. 1,[19][20][21][22][23] Multivariate methods have previously been applied to hyperspectral MS imaging data and showed their potential in different applications. [24][25][26] In this type of imaging techniques, the hyperspectral data matrix contains, for each pixel of the image, hundreds of variables the values of which constitute the mass spectra.…”

Spectral imaging-based methods for quantifying autophagy and apoptosis

“…The specifications of the PARISS system were described previously. 4 A correlation coefficient of 0.99 was used to generate a library of distinct spectra for 2.5X-magnified images. Data were collected in 10 micron slices.…”

“…In the field of biomedical research, spectral analysis has been used for discerning malignant from normal tissue, 1 separating vascular from non-vascular regions in skin and tumors, 2,3 and identifying cultured cells in different phases of the cell cycle. 4 Spectral imaging systems are highly versatile with endless applicability. Their quantitative nature and high resolving power make them ideal for use in cellular assays that measure autophagy and apoptosis, two forms of programmed cell death (PCD) that are critical to normal biological development, 5,6 but also contribute to pathological conditions including neurodegenerative disease, 7 heart disease 8 and especially cancer.…”