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Thirstrup, D. J.

Publications and source records attributed to Thirstrup, D. J..

2 recordsLinked to original sources

Mapping Protein Numbers in Living Cells

We introduce a new, robust method to map the numbers of proteins in living cells. The method can be applied to laser scanning, spinning disk, and lattice light-sheet microscopes in a robust, reproducible, and scalable fashion. The method uses calibrated EGFP solutions that are imaged with the appropriate microscope modality to create a calibration curve that is then applied to convert the fluorescence intensities from 3D microscope images into molecule numbers. We applied this method to human induced pluripotent stem cells in which proteins representing key cellular structures were endogenously tagged with mEGFP. We used the ratio of mEGFP-tagged proteins to total proteins to create 3D maps of live cells showing the density of total proteins measured in molecules per {micro}m3. The method opens the door to new quantitative single cell analyses of cellular protein numbers in the context of single cell gene expression, associations with cellular complexes, and changes in cellular behaviors. The method is capable of quantifying protein numbers, over three orders of magnitude, in the cytoplasm or within various cellular structures while offering the unique advantages of each microscopy modality.

cell biology

Automated hiPSC culture and sample preparation for 3D live cell microscopy

Our goal is to identify and understand cellular behaviors using 3D live imaging of cell organization. To do this, we image human inducible pluripotent stem cell (hiPSC) lines expressing fluorescently tagged protein representing specific cellular organelles and structures. To produce large numbers of standardized cell images, we developed an automated hiPSC culture procedure, to maintain, passage and Matrigel coat 6-well plastic plates and 96-well glass plates compatible with high-resolution 3D microscopy. Here we describe this system including optimization procedures and specific values for plate movement, angle of tips, speed of aspiration and dispense, seeding strategies and timing of every step. We validated this approach through a side-by-side comparison of quality control results obtained from manual and automated methods. Additionally, we developed an automated image-based colony segmentation and feature extraction pipeline to predict cell count and select wells with consistent morphology for high resolution 3D microscopy.

cell biology