Organelle-specific phase contrast microscopy enables gentle monitoring and analysis of mitochondrial network dynamics

Abstract

Mitochondria are delicate organelles that play a key role in cell fate. Current research methods rely on fluorescence labeling that introduces stress due to photobleaching and phototoxicity. Here we propose a new, gentle method to study mitochondrial dynamics, where organelle-specific three-dimensional information is obtained in a label-free manner at high resolution, high specificity, and without detrimental effects associated with staining. A mitochondria cleavage experiment demonstrates that not only do the label-free mitochondria-specific images have the required resolution and precision, but also fairly include all cells and mitochondria in downstream morphological analysis, while fluorescence images omit dim cells and mitochondria. The robustness of the method was tested on samples of different cell lines and on data collected from multiple systems. Thus, we have demonstrated that our method is an attractive alternative to study mitochondrial dynamics, connecting behavior and function in a simpler and more robust way than traditional fluorescence imaging.

Label-Free Analysis of Organelle Interactions Using Organelle-Specific Phase Contrast Microscopy (OS-PCM)

“…Further, the morphology of individual mitochondria and their dynamics were also studied automatically with the aid of deep learning. 23 Adding deep learning allows organelle-specific information to be extracted from the otherwise nonspecific phase microscopy images, thus leading us to call this technique organelle-specific phase contrast microscopy (OS-PCM). Our previous work focused on mitochondria identification alone and utilized three-dimensional (3D) datasets to accurately view the 3D mitochondrial network.…”

“…Previously we have developed a phase microscope with high spatial and temporal resolution, which can simultaneously see multiple membrane-bound organelles in unlabeled cells, including mitochondria, lysosomes, endoplasmic reticulum, etc. Further, the morphology of individual mitochondria and their dynamics were also studied automatically with the aid of deep learning . Adding deep learning allows organelle-specific information to be extracted from the otherwise nonspecific phase microscopy images, thus leading us to call this technique organelle-specific phase contrast microscopy (OS-PCM).…”

Rapid Intracellular Detection and Analysis of Lipid Droplets’ Morpho-Chemical Composition by Phase-Guided Raman Sampling

“…33 Compared to other label-free imaging modalities, such as autofluorescence, phase imaging provides high spatiotemporal resolution imaging, with the ability to panoramically visualize essentially every membrane-bound organelle within the cell, without photobleaching or phototoxicity. 34 Thus, it is an ideal imaging tool for organelle identification and tracking. Here, we will use phase imaging to guide the Raman analysis of subcellular organelles.…”

“…Previously, autofluorescence images of excised tissues highlighted regions of tissue suspicious for cancer, which were then used to guide the Raman sampling to only a small portion (typically <1%) of the original image . Compared to other label-free imaging modalities, such as autofluorescence, phase imaging provides high spatiotemporal resolution imaging, with the ability to panoramically visualize essentially every membrane-bound organelle within the cell, without photobleaching or phototoxicity . Thus, it is an ideal imaging tool for organelle identification and tracking.…”

Reflectional quantitative differential phase microscopy using polarized wavefront phase modulation

“…The invention of spatial light interference microscopy (SLIM) is a critical leap in the development of phase contrast microscopy, or specifically, an evolution from qualitative display to quantitative analysis [32][33][34][35]. Owing to the common path structure and wide-spectrum illumination, SLIM has been extensively used in cell growth, cell migration, and drug screening, etc.…”