Abstract
Due to its specificity, fluorescence microscopy has become a quintessential imaging tool in cell biology. However, photobleaching, phototoxicity, and related artifacts continue to limit fluorescence microscopy’s utility. Recently, it has been shown that artificial intelligence (AI) can transform one form of contrast into another. We present phase imaging with computational specificity (PICS), a combination of quantitative phase imaging and AI, which provides information about unlabeled live cells with high specificity. Our imaging system allows for automatic training, while inference is built into the acquisition software and runs in real-time. Applying the computed fluorescence maps back to the quantitative phase imaging (QPI) data, we measured the growth of both nuclei and cytoplasm independently, over many days, without loss of viability. Using a QPI method that suppresses multiple scattering, we measured the dry mass content of individual cell nuclei within spheroids. In its current implementation, PICS offers a versatile quantitative technique for continuous simultaneous monitoring of individual cellular components in biological applications where long-term label-free imaging is desirable.
Highlights
Due to its specificity, fluorescence microscopy has become a quintessential imaging tool in cell biology
We show that combining quantitative phase imaging (QPI) and computational specificity allows us to quantify the growth of subcellular components over many cell cycles, nondestructively
The inference is implemented within the QPI acquisition time, such that phase imaging with computational specificity (PICS) performs in real-time (Fig. 1d)
Summary
Fluorescence microscopy has become a quintessential imaging tool in cell biology. Fluorescence signals, whether intrinsic or extrinsic, allow the investigator to study particular structures in the biospecimen with high specificity[2]. This important quality comes at an expensive price: chemical toxicity and phototoxicity disturb and may kill a live cell[3,4], while photobleaching limits the extent of the investigation window[5]. Quantitative phase imaging (QPI) has advanced labelfree microscopy with its ability to extract quantitative parameters (cell dry mass, cell mass transport, cell tomography, nanoscale morphology, topography, pathology markers, etc.) from unlabeled cells and tissues[12]. In the absence of labels, QPI cannot identify particular structures in the cell as the labelfree image lacks specificity
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