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A new 3D tool for screening and measuring intracellular lipid droplets using flow tomography

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fig 1

image: Tomographic reconstruction of LDs in live suspended cells by TPM-FC. A Opto-fluidic configuration of the TPM-FC system. PBS – Polarizing Beam Splitter; HWP – Half Wave Plate; M – Mirror; MO – Microscope Objective; MC – Microfluidic Channel; MP – Microfluidic Pump; TL – Tube Lens; BS – Beam Splitter; CMOS – Camera. B Pseudo-3D visualization of the phase-contrast map of an ovarian cancer cell, in which LDs are localized at the highest peaks (i.e., phase values). C 3D RI tomogram of a monocyte cell, in which LDs are evident at the highest RIs (from yellow to white). D Isolevels representation of the monocyte cell in C, in which LDs (red particles) have been segmented at the highest RIs. view more 

Credit: OEA

A new publication from Opto-Electronic Advances; DOI 10.29026/oea.2023.220048 discuss a new 3D tool for screening and measuring intracellular lipid droplets using flow tomography.


Tomographic Phase Microscopy (TPM) is an intriguing technology being developed for analyzing single cells. It has great potential in biomedical science as it can furnish a very powerful tool in providing early disease detection and driving the clinical applications toward the personalized medicine. TPM allows to get three-dimensional (3D) morphology of a single cell. The most important feature of TPM is that such 3D information of single cell is quantitative and is achieved without chemical markers, as instead occurs in conventional fluorescent and confocal microscopy. This implies that TPM is a non-destructive microscopy technique, and thus a cell can survive to the measurement. Secondly, cells can be observed and analyzed in their natural state without being affected by toxic effects of exogenous agents that can alter their morphology and/or functions.


The quantitative 3D imaging attained by TPM furnishes the spatial distribution of the refractive index (RI) of the single cells. From such 3D data assay various information about the cell can be retrieved or inferred. Cancer cells can be distinguished among the healthy tissue, or it can be discovered if a drug has the expected effects on cell diseases. Subcellular structures can be visualized and measured by getting information on cells phenotypes, morphogenesis, or some of their functionalities can be inferred by evaluating their number and size. Nevertheless, to date, the current modality of TPM is made for analyzing cells in plate or cell-culture dish. Single cells can be analyzed one at a time. However, what is important in personalized medicine is to have single cell information for a high number of cells to have significant statistical data too. Flow cytometry (FC) systems are currently adopted for this purpose in combination with fluorescent microscopy. In fact, in the last decade, imaging FC aroused much interest in the scientific community due to its ability in catching the intra-cellular variability inside heterogeneous populations by collecting thousands of single-cells in few seconds. However, combining a TPM with a FC system is still challenging to date. Consequently, flowing cells cannot be analyzed through TPM, putting it among methods having intrinsic low-throughput and thus limiting its exploitations in biomedical fields. Instead, recently the potentiality of TPM and FC have been combined, thus creating the TPM-FC imaging technique. In the present research a significant step-forward along the path of development of TPM-FC method in biomedical science is performed. In fact, a key biological issue is afforded and solved by TPM-FC, i.e. the 3D high-throughput visualization and RI-based quantitative measurement of Lipid Droplets (LDs) in each live suspended cells.


Analysis of LDs is a growing field, especially since these organelles have been recognized as dynamic particles with key roles in several cell regulation processes. It has been suggested that LDs number, size and interactions with other organelles reflect their functions, but dissecting these parameters in a non-destructive, high-throughput mode has been elusive up to date, especially in terms of evaluating LD 3D spatial organization. Gold standard techniques for LDs analysis, namely transmission electron microscopy (TEM) and fluorescent microscopy (FM), while being highly specific and sensitive, present the main drawback to supply only 2D images on a small portion of the cell volume. Furthermore, both approaches are destructive and low-throughput.


The method proposed here retrieves significant parameters on spatial correlations and LDs 3D positioning inside the volume of each live flowing cell in micro-channels, allowing high-throughput detection and investigation of LDs in cell populations. In order to test the robustness and reliability of this strategy, human ovarian cancer cells and monocytes have been investigated and the results compared with TEM and FM imaging techniques. On the basis of the attained results, it will be possible to investigate high number of cells and thus accomplish significant statistical analysis in label-free and non-destructive mode.


Thanks to the results reported in the present work, it is evident that TPM-FC has advanced in terms of both experimental recording and numerical processing for addressing successfully real-world biomedical issues, while pushing into the direction of label-free intracellular imaging.

The proposed non-destructive imaging method, able to analyze large cell numbers and provide quantifiable information related to LDs inner distribution, is expected to greatly contribute to the field of LDs biology, allowing to dissect their roles with more detail and consequently take full advantage of their clinical potential.


The authors of this article propose a novel biomedical application based on a recently developed tool, i.e. the Tomographic Phase Microscopy in Flow Cytometry (TPM-FC). TPM is an optical microscopy technique that allows reconstructing the 3D spatial distribution of the RIs of a single cell without using exogenous labels. Therefore, it provides a quantitative characterization of the cell biophysical properties (mechanical, electrical, and optical) that can be inferred from the fully 3D morphological and RI-based tomographic information. Moreover, its label-free aspect avoids the common limitations related to cell staining, than can be costly, labor-intensive, operator-dependent, and time-consuming, and can also alter the overall imaging (photobleaching) or change the cell physiology (photodamaging), thus hindering applications for disease diagnosis or screening. On the other side, conventional TPM systems work in static conditions, which limit the possibility of performing high-throughput experiments. As cellular populations are often heterogeneous with respect to cell cycle phase, size, volume, physiological state, etc., a low-throughput analysis risks discarding the intra-cellular variability, which is instead essential for assaying diversity and searching for rare cells with specific features (e.g., tumor cells, stem cells, etc.). In this context, imaging FC represents the gold standard technique since it combines the single-cell imaging capabilities of microscopy with the high-throughput capabilities of FC. In conventional imaging FC, thousands of 2D images per second are collected, but their informative content is often limited to the cell morphology and the fluorescence-based signature. For this reason, the combination between the 3D label-free and quantitative single-cell analysis of TPM and the high-throughput single-cell recording of imaging FC is expected to open new powerful applications in biomedicine or strengthen the existing ones. Among them, in this research the 3D identification and quantitative characterization of lipid droplets (LDs) by TPM-FC is investigated. Initially described exclusively as fat storage organelles, LDs are now recognized as dynamic entities that play several other pivotal roles inside cells. Consequently, their dysregulation may have implications in diseases, and evaluation of LD-related parameters may be exploited as a biomarker. Indeed, LDs have been described to have a role in various pathologies, including diabetes, atherosclerosis, fatty liver disease, pathogen infections, neurodegenerative diseases, and cancer. Moreover, they are recognized as structural markers of inflammation, since a remarkable increase in LD number and size rapidly occurs in immune cells in response to inflammatory stimuli. Most recent evidence shows that monocytes from COVID-19 affected patients display an increased LD accumulation with respect to healthy blood donors, suggesting a possible involvement of these organelles in the SARS-CoV-2 pathogenesis. Although the mechanisms linking specific LD structural characteristics to a certain function are still not completely understood, a vast number of evidences shows that variation in LD number, size, ultrastructure, motility, lipid/protein content and interactions with other organelles significantly influences many cellular processes. Furthermore, LDs dynamically interact with most intracellular organelles, including mitochondria, peroxisome, lysosomes, Golgi apparatus, and nuclei, therefore their 3D spatial organization inside the cellular volume could be a potential disease biomarker.


In this research, for the first time LDs are visualized and quantitatively measured in 3D in live suspended cell while they are flowing along a simple and commercially available microfluidic channel. The presented approach, based on TPM-FC, allows to retrieve both the 3D morphological and RI-based features of LDs and their 3D locations. Numerical image processing is implemented for retrieving the phenotype of each detected LD and their spatial correlations and positioning into the 3D cell volume. The reported results show that a new avenue for achieving high-throughput investigation of the presence and the distribution of intracellular LDs in flowing samples can be achieved. This makes viable the development of novel diagnostic or therapeutical tools in biomedicine capable to furnish exact 3D location of the LDs inside the cells, their volume, shape, RI-based statistics and dry mass at the single-cell level.


Article reference: Pirone D, Sirico D, Miccio L, Bianco V, Mugnano M et al. 3D imaging lipidometry in single cell by in-flow holographic tomography. Opto-Electron Adv 6, 220048 (2023). doi: 10.29026/oea.2023.220048 

Keywords: Lipid droplets / label-free phase-contrast imaging / in-flow tomography / 3D imaging.


The results of this research have been achieved thanks to synergic interdisciplinary fruitful cooperation among different Italian groups, i.e. the Ferraro’s group at Institute of Applied Sciences and Intelligence Systems (ISASI) – National Research Council (CNR) of Italy and three research units from University of Bologna (Department of Medical and Surgical Sciences, Department of Pharmacy and Biotechnologies and Department of Experimental, Diagnostic and Specialty Medicine). The research group at ISASI-CNR is among the leaders worldwide about digital holography and it has developed the concept behind Tomographic Phase Microscopy in Flow Cytometry (TPM-FC). The research team from University of Bologna includes cancer biologists and a medical doctor, covering expertise in molecular genetics, biochemistry, cell biology and pathology. In particular, the University of Bologna team is interested in understanding how metabolic reprogramming contributes to cancer development. This synergic effort among the involved groups has allowed to reach a significant result. In fact, the TPM-FC technology for lipid droplet analysis will undoubtedly allow uncovering novel findings, since these organelles have been in part neglected also due to the lack of appropriate methods for their investigation.

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