Quantitative phase microscopy spatial signatures of cancer cells.

Article Figures and data Abstract Editor's evaluation Introduction Results Discussion Materials and methods Appendix 1 Data availability References Decision letter Author response Article and author information Metrics Abstract Recent studies reveal that lateral mitochondrial transfer, the movement of mitochondria from one cell to another, can affect cellular and tissue homeostasis. Most of what we know about mitochondrial transfer stems from bulk cell studies and have led to the paradigm that functional transferred mitochondria restore bioenergetics and revitalize cellular functions to recipient cells with damaged or non-functional mitochondrial networks. However, we show that mitochondrial transfer also occurs between cells with functioning endogenous mitochondrial networks, but the mechanisms underlying how transferred mitochondria can promote such sustained behavioral reprogramming remain unclear. We report that unexpectedly, transferred macrophage mitochondria are dysfunctional and accumulate reactive oxygen species in recipient cancer cells. We further discovered that reactive oxygen species accumulation activates ERK signaling, promoting cancer cell proliferation. Pro-tumorigenic macrophages exhibit fragmented mitochondrial networks, leading to higher rates of mitochondrial transfer to cancer cells. Finally, we observe that macrophage mitochondrial transfer promotes tumor cell proliferation in vivo. Collectively these results indicate that transferred macrophage mitochondria activate downstream signaling pathways in a ROS-dependent manner in cancer cells, and provide a model of how sustained behavioral reprogramming can be mediated by a relatively small amount of transferred mitochondria in vitro and in vivo. Editor's evaluation This important work demonstrates that the transfer of dysfunctional mitochondria stimulates proliferation in recipient cancer cells by serving as a signal to induce reactive oxygen species production that in turn activates signaling pathways that control cell cycle. Compelling cell biology assays including rigorous microscopy with elegant reporters track the function and fate of transferred mitochondria in recipient cells. The work is relevant to the study of mitochondria, cancer, and immune cells and will be of broad interest to cell biologists and biochemists. https://doi.org/10.7554/eLife.85494.sa0 Decision letter Reviews on Sciety eLife's review process Introduction It has been previously described that mitochondria can undergo lateral transfer between cells (Torralba et al., 2016; Antanavičiūtė et al., 2014; Lou et al., 2012; Rebbeck et al., 2011; Tan et al., 2015; Wang and Gerdes, 2012; Wang and Gerdes, 2015; Lampinen et al., 2022). Mitochondria are dynamic organelles, known to provide energy for the cell, but more recently shown to have a variety of additional essential cellular functions (Zong et al., 2016). In animal models, a series of seminal studies revealed that cancer cells void of mitochondrial DNA still form tumors by obtaining mitochondria from stromal cells, thereby restoring cancer cell mitochondrial function, cellular respiration, and tumor formation (Tan et al., 2015; Dong et al., 2017). Other experiments suggest that mitochondrial transfer not only restores bioenergetics, but can alter the metabolic state of recipient cells (Brestoff et al., 2021; Nicolás-Ávila et al., 2020; Phinney et al., 2015; Saha et al., 2022; Crewe et al., 2021; Korpershoek et al., 2022; Liu et al., 2022; van der Vlist et al., 2022; Yang et al., 2022; Liu et al., 2021), allowing recipient cells to adapt to stressors or changes in the environment, prompting the development of methods targeting mitochondrial dysfunction in disease (Patel et al., 2023; Caicedo et al., 2015). Although these studies elegantly demonstrate that mitochondrial transfer alters recipient cellular behavior, many aspects of this process remain unclear. For instance, the rescue of cellular function is commonly attributed to enhanced mitochondrial energetic or metabolic profiles; however, the fate and function of transferred mitochondria in recipient cells are under-explored. Furthermore, it is unclear how cells respond to laterally transferred mitochondria if the recipient cells already have a fully functioning mitochondrial network, and in particular, if the transferred mitochondria only comprise a small subset of the overall mitochondrial network in the recipient cell. Given that metastasis is a low-frequency event and is the consequence of changes in cellular behavior on the single-cell level, we aimed to examine the function and behavior of transferred mitochondria within individual recipient cells that have functioning endogenous mitochondrial networks. Using a combination of in vitro high-resolution microscopy, optogenetics, imaging flow cytometry, and in vivo tumor models, we demonstrate a previously undescribed mechanism of mitochondrial transfer-associated cellular reprogramming. Collectively, our data explain how a relatively small amount of transferred mitochondria can impact cellular behavior in the recipient cell with fully functioning endogenous mitochondria – Transferred macrophage mitochondria in cancer cells are dysfunctional, ROS accumulates at the site of transferred mitochondria, promoting ERK-mediated cancer cell proliferation. Results Cancer cells with macrophage mitochondria exhibit increased proliferation We previously reported that macrophages transfer cytoplasmic contents to cancer cells in vitro and in vivo (Roh-Johnson et al., 2017), and hypothesized that a macrophage/cancer cell system would be ideal for probing mitochondrial transfer in cells with functioning mitochondrial networks. Our studies employed blood-derived human macrophages and a human breast cancer cell line, MDA-MB-231 (231 cells), stably expressing a mitochondrially localized mEmerald or red fluorescent protein (mito-mEm or mito-RFP, respectively; Figure 1a). We observed mitochondrial transfer from macrophages to 231 cells using live cell confocal microscopy (Figure 1b, arrowheads) and flow cytometry (Figure 1c–d; flow cytometry scheme in Figure 1—figure supplement 1a). Control gates were set to 0.2%, based on confirmation of mitochondrial transfer by FACS-isolation of distinct mEmerald+ populations (see methods for more information). With these methods, a range of transfer efficiencies were observed, which we attribute to donor-to-donor variability (Figure 1d), yet mitochondrial transfer was consistently observed in 231 cells, as well as to another breast cancer line, MDA-MB-468, and a melanoma cell line, A375 (Figure 1—figure supplement 1b). To determine whether macrophage mitochondrial transfer was unique to cancer cells, we tested a non-malignant breast epithelial cell line, MCF10A. We observed reduced mitochondrial transfer efficiencies to MCF10A cells, with no significant differences compared to control (Figure 1—figure supplement 1c), suggesting that macrophages exhibit higher mitochondrial transfer efficiencies to malignant cells. Transferred mitochondria contain a key outer mitochondrial membrane protein, TOMM20 (Figure 1—figure supplement 1d, arrowhead) and mitochondrial DNA (Figure 1—figure supplement 1e, arrowhead), suggesting that intact organelles are transferred to 231 cells. To better define the requirements for transfer, we performed trans-well experiments in which we cultured 231 cells either physically separated from macrophages by a 0.4 μm trans-well insert or in contact with macrophages (scheme in Figure 1—figure supplement 1f), or with conditioned media (Figure 1—figure supplement 1g, h). These data showed that mitochondrial transfer increased dramatically under conditions where 231 cells could contact macrophages directly (Figure 1—figure supplement 1g and h). Taken together, these results suggest that macrophage mitochondrial transfer to cancer cells likely requires cell-to-cell contact. Furthermore, while mitochondrial transfer may not be unique to cancer cells, macrophages transfer mitochondria to cancer cells at higher frequencies. Thus, due to the low rates of mitochondrial transfer across macrophage donors (0.84%, Figure 1d), we subsequently took advantage of single-cell, high-resolution approaches – rather than bulk approaches – to follow the fate and functional status of transferred mitochondria. Figure 1 with 3 supplements see all Download asset Open asset Cell-contact-mediated transfer of macrophage mitochondria leads to increased cancer cell proliferation. (a) CD14+ monocytes harvested from human blood are transduced and differentiated for 6 days. Mito-mEm +macrophages (green) are co-cultured with MDA-MB-231 cells (231 cells) expressing mito-RFP (magenta; right image). (b) Confocal image showing transferred mitochondria (green, arrowhead) in a 231 cell (magenta, cell outline in white). (c) Representative flow cytometry plots depicting mitochondrial transfer (black box) within a population of co-cultured mito-RFP+ 231 cells (right) compared to monoculture control (left) with background level of mEmerald (mEm) fluorescence set at 0.2%. (d) Aggregate data of mitochondrial transfer rates across macrophage donors. Each data point represents one replicate (N=14 donors). (e) Analysis of proliferative capacity by quantifying Ki-67 levels and DNA content in co-cultured 231 cells after 24 hr. Percentage of cancer cells within a specific cell cycle phase with or without transfer is shown. A significantly different percent of recipient cells occupies G2/M (black) phases of the cell cycle compared to non-recipient cells (N=4 donors; statistics for G2/M only). (f) Co-cultured recipient 231 cells have a significantly higher specific growth rate compared to non-recipients (N=60 cells (control), 115 (recipient) over 4 donors indicated as shades of gray). (g) Schematic of mitochondrial isolation and bath application on MDA-MB-231 cells. Mitochondria are isolated from mito-mEmerald expressing THP-1 monocytes and bath applied at 20–30 µg/mL for 24 hr. Cancer cells which had taken up mEm+ mitochondria are then FACS-isolated and plated for 48 hr for further analyses. (h) Representative confocal image showing mito-RFP-expressing 231 cell (magenta) that had taken up macrophage mitochondria (green, grey arrow). (i) 48 hr after FACS-isolating 231 cells with macrophage mitochondria, flow cytometry was used to determine percent of daughter cells which still contain mEm+ mitochondria. N=3 biological replicates. (j), Cell cycle analysis of daughter cells 48 hr after FACS-isolation of 231 cells that had taken up macrophage mitochondria. N=3 biological replicates. For all panels, standard error of the mean (SEM) is displayed and scale bars are 10 µm. Mann-Whitney (d), two-way ANOVA (e, j), Welch's t-test (f, i), *p<0.05; **p<0.01; ****p<0.0001. To determine the effects of macrophage mitochondrial transfer on cancer cells, we performed single cell RNA-sequencing on cancer cells that received macrophage mitochondria. These data revealed that mitochondrial transfer induced significant changes in canonical cell proliferation-related pathways (Figure 1—figure supplement 2a). To follow up on the RNA-sequencing results, we used flow cytometry to evaluate proliferation changes, and found significant increases in the percent of cells within the G2 and Mitotic (M) phases of the cell cycle in recipient cells, as compared to their co-cultured counterparts that did not receive mitochondria (Figure 1e; Figure 1—figure supplement 2b-d). These cells were not undergoing cell cycle arrest, as we found that recipient cells completed cytokinesis at rates equivalent to their co-cultured non-recipient counterparts (Figure 1—figure supplement 2e). For further confirmation of this proliferative phenotype, we used quantitative phase imaging (QPI) to detect changes in dry mass of co-cultured 231 cells over time (Zangle and Teitell, 2014). With this approach, we could obtain growth rate information of a large number of cancer cells over time (n=60 control cells; n=115 recipient cancer cells). Consistent with the flow cytometry-based cell cycle analysis, the specific growth rates increased significantly in 231 cells with macrophage mitochondria compared to 231 cells that did not receive mitochondria (Figure 1f). To examine whether the effects of mitochondrial transfer was sustained in recipient cells, we also measured the growth rates of daughter cells born from recipient 231 cells containing macrophage mitochondria (Zangle et al., 2014). We identified five 'parent' cancer cells with macrophage mitochondria, for which we were able to reliably follow both daughter cells upon division. Daughter cells that inherited the 'parent's' macrophage mitochondria exhibited an increase in their rate of change of dry mass over time versus sister cells that did not inherit macrophage mitochondria (Figure 1—figure supplement 3a-c). These experiments indicate that the proliferation phenotype in recipient cancer cells is sustained. Our results so far suggest that either macrophage mitochondrial transfer increases cancer cell proliferation, or that more proliferative cells are simply more capable of receiving macrophage mitochondria. Thus, to test between these hypotheses, we first blocked cells in the G1-phase of the cell cycle by treating co-cultures with a CDK4/6 inhibitor, Palbociclib (Figure 1—figure supplement 3d), and we observed no changes in mitochondrial transfer rates (Figure 1—figure supplement 3e). These data indicate that the enhanced proliferation observed in recipient cells is not due to proliferative cells more readily receiving transfer. We then performed experiments to rigorously test whether transferred macrophage mitochondria causes cancer cell proliferation, rather than mitochondrial receipt and proliferation being correlative events in cancer cells. We also wanted to determine whether the observed proliferative phenotype is due to macrophage mitochondria, and not other molecules that are passed along with the macrophage mitochondria. Thus, we biochemically purified mitochondria from a macrophage cell line, THP-1, and directly applied these macrophage mitochondria to cancer cells for 24 hr (Figure 1g). We then FACS-isolated cancer cell populations that contained purified macrophage mitochondria, and allowed this population to undergo additional rounds of cell division, and then reanalyzed the proliferative capacity of cancer cells that had retained the macrophage mitochondria versus cancer cells that had lost the macrophage mitochondria over this time. We first confirmed that cancer cells retained the macrophage mitochondria by imaging (Figure 1h). We also found that cancer cells that had retained the macrophage mitochondria exhibited an increased percentage of cells in the G2/M phase of the cell cycle compared to cancer cells that had lost the macrophage mitochondria (Figure 1i-j). Together with the QPI results, these results support the model that macrophage mitochondrial transfer promotes a sustained pro-growth and proliferative effect in both recipient and subsequent daughter cells. Transferred mitochondria are dysfunctional and accumulate ROS We next sought to understand how donated mitochondria can stimulate a proliferative response in recipient cells. We performed time-lapse confocal microscopy on co-cultures and found that in cancer cells with macrophage mitochondria, macrophage-derived mito-mEm+ mitochondria remained distinct from the recipient host mitochondrial network. Cancer cells were cocultured with macrophages for 12 hr and subjected to an additional 15 hr of timelapse microscopy, and we observed no detectable loss of the fluorescent signal at transferred mitochondria throughout the course of imaging (Figure 2a, arrowhead; Video 1). Thus, transferred macrophage mitochondria did not appear to fuse with the existing endogenous mitochondrial network in recipient cells. To probe the functional state of the donated mitochondria, we performed live imaging with MitoTracker Deep Red (MTDR), a cell-permeable dye that is actively taken up by mitochondria with a membrane potential (Poot et al., 1996). To our surprise, all of the transferred mitochondria were MTDR-negative (Figure 2b, top left). This was also confirmed using a different mitochondrial membrane potential-sensitive dye, Tetramethylrhodamine Methyl Ester (TMRM; Figure 1—figure supplement 1e). These results suggested that the transferred mitochondria lacked membrane potential. To determine whether these membrane potential-deficient transferred mitochondria were subjected to lysosomal degradation, we labeled lysosomes and acidic vesicles with a dye, LysoTracker, and found that the majority of transferred mitochondria (57%) did not co-localize with the LysoTracker signal (Figure 2b, top right). The status of transferred mitochondria was unexpected because mitochondria typically maintain strong membrane potentials, and dysfunctional mitochondria that lack membrane potential are normally degraded or repaired by fusion with healthy mitochondrial networks (Phinney et al., 2015). Next, we utilized another dye which stains cellular membranes, MemBrite, and observed that 91% of transferred mitochondria were not encapsulated by a membranous structure, thus also excluding sequestration as a mechanism for explaining the lack of degradation or interaction with the endogenous mitochondrial network (Figure 2—figure supplement 1a). These data, taken together with the long-lived observation of the transferred mitochondria in Figure 2a, suggest that transferred macrophage mitochondria lack membrane potential, yet remain as a distinct population in recipient cancer cells, not fusing with the endogenous host mitochondrial network nor subjected to degradation. Figure 2 with 2 supplements see all Download asset Open asset Transferred macrophage mitochondria are long-lived, depolarized, and accumulate reactive oxygen species, promoting cancer cell proliferation. (a) Stills from time-lapse imaging depicting the longevity of the transferred mitochondria (green, arrowhead) within a 231 cell (magenta, cell outline in white). Time elapsed listed in left corner. (b) Confocal image of a mito-RFP+ 231 cell (magenta) containing macrophage mitochondria (green, arrowhead) stained with MTDR (yellow) and LysoTracker (teal). MTDR does not accumulate in 100% of donated mitochondria (N=25 cells, 5 donors). Majority (57%) of donated mitochondria do not colocalize with LysoTracker signal (N=24 cells, 4 donors). (c) Ratiometric quantification of mito-Grx1-roGFP2 biosensor mapped onto the recipient 231 cell with fire LUT (top panel). Confocal image of mito-Grx1-roGFP2-expressing 231 cell (bottom right, green and yellow) containing a macrophage mitochondria (bottom left, red, arrowhead). (d) Ratiometric measurements of the mito-Grx1-roGFP2 sensor per 231 cell (paired dots) at a region of interest containing the host mitochondrial network (host) or a transferred mitochondria (transfer). Cells were co-cultured for 24 hr (N=27 cells, 3 donors indicated in shades of gray). (e) Exogenous purified macrophage mitochondria (green) is void of mitochondrial membrane potential (MitoTracker Deep Red-negative, yellow, arrowhead) in cancer cells. (f) Cell cycle analysis of cancer cells with exogenous purified macrophage mitochondria versus sister cells that did not take up exogenous purified mitochondria, either treated with vehicle or 100 μM mitoTEMPO (mitochondrially-targeted superoxide scavenger. N=3 donors; statistics for G2/M only). (g) Schematic of optogenetic experiments to generate data in (h). Cells expressing mito-KillerRed are photobleached in a specific ROI containing either cytoplasm only (left) or mito-KillerRed+ mitochondria (right). Following photobleaching, cells are imaged over time to quantify the amount of cell division. (h) Quantification of cell division after photobleaching. Each data point is the average within a field of view (N=13 experiments), with control (cyto) and experimental (mito) data shown as paired dots per experiment. Scale bars are 10 µm. Wilcoxon matched-pairs signed rank test (d, h), two-way ANOVA (f), *p<0.05; ****p<0.0001. Video 1 Download asset This video cannot be played in place because your browser does support HTML5 video. You may still download the video for offline viewing. Download as MPEG-4 Download as WebM Download as Ogg Macrophage mitochondria are long-lived and remain distinct in recipient cancer cells. Video depicting a recipient mito-RFP expressing 231 cell (magenta) that contains mito-mEm macrophage mitochondria (green in magenta cell, center of frame). 231 cells were co-cultured with macrophages for 7 hr prior to the start of imaging for a duration ~15 hr with a time interval of 5 min. Maximum intensity projections of images are displayed at 12 frames per second, timestamp in upper left corner in hours (h), and scale bar is 10 μm. Given the surprising observation that transferred mitochondria lack membrane potential, we hypothesized that instead of providing a metabolic or energetic advantage, the donated mitochondria may act as a signal source to promote sustained changes in cancer cell behavior. This hypothesis could offer insight into how this rare event, in which a relatively small amount of mitochondria is transferred, could mediate sustained changes in the proliferative capacity of recipient cancer cells. One signaling molecule associated with mitochondria is reactive oxygen species (ROS), which occur normally as byproducts of mitochondrial respiration, and can be produced at high levels during organellar dysfunction (Schieber and Chandel, 2014). Using a genetically encoded biosensor, mito-Grx1-roGFP2, as a live readout of the mitochondrial glutathione redox state (Gutscher et al., 2008), we found that after 24 and 48 hr, significantly higher ratios of oxidized:reduced protein were associated with the transferred mitochondria versus the host network (Figure 2c–d; Figure 2—figure supplement 1b). These data indicate that transferred macrophage mitochondria in recipient cells are associated with higher levels of oxidized glutathione, suggesting that they are accumulating higher amounts of ROS. Consistent with these results, a second biosensor that is specific for the reactive oxygen species H2O2, mito-roGFP2-Orp1 (Gutscher et al., 2009), also reported more oxidation at the transferred mitochondria compared to the host network (Figure 2—figure supplement 1c–d) after 48 hr of co-culture. At 24 hr, we observed a similar trend, but no statistically significant difference (Figure 2—figure supplement 1d). These results indicate that ROS accumulate at the site of transferred mitochondria in recipient cancer cells. It is unclear whether the observed ROS accumulation is generated by the transferred mitochondria themselves, or generated elsewhere in the recipient cancer cell and accumulating locally at transferred mitochondria. Regardless of the source, we observed robust ROS accumulation specifically at the site of transferred mitochondria and with this unexpected finding, we next tested whether this ROS accumulation could serve as a molecular signal, regulating cell proliferation. To rigorously test the model that transferred macrophage mitochondria accumulate ROS, promoting cancer cell proliferation, we turned toward purified macrophage mitochondria approaches as in Figure 1g and sought approaches to reduce ROS levels. First, to better model the macrophage mitochondrial transfer to cancer cells that occurs in coculture conditions, we determined conditions for cancer cells to internalize exogenous macrophage mitochondria at rates similar to in vitro mitochondrial transfer conditions at 24 hr – 0.68% ± 0.36% internalization rate, n=3 biological replicates (compare to Figure 1d). We next determined that purified mitochondria taken up by cancer cells remain distinct, are not encapsulated by membranes after 24 hr (Figure 2—figure supplement 1e), and do not exhibit membrane potential (Figure 2e). Similar to our previous proliferation results with purified macrophage mitochondrial uptake at longer time points (Figure 1j), we found that cancer cells with internalized purified macrophage mitochondria (which, under these conditions, comprise of the exhibited a significant increase in proliferative cells in the G2/M phase of the cell compared to sister cells that did not internalize mitochondria (Figure bars in and that this increase was ROS is with a mitochondrially localized superoxide mitoTEMPO (Figure bars in cancer cells that did not internalize mitochondria were not by ROS (Figure bars in These results indicate that transferred mitochondria promote proliferation in a ROS-dependent To test whether ROS accumulation can induce cancer cell proliferation we stably a mitochondrially localized which ROS photobleached with et al., mito-KillerRed+ of interest induced ROS et al., Figure 2—figure supplement 2a). We then mito-KillerRed+ of interest that the of macrophage mitochondrial transfer to induce ROS in cancer cells, and the rate of cell division by imaging these cells over hr (Figure We found that cells with induced ROS mito-KillerRed+ exhibited an increased percentage of cells compared to control photobleached cells Figure Figure 2—figure supplement These results indicate that of mitochondrially localized ROS can directly promote cancer cell proliferation. ROS accumulation leads to proliferation We next aimed to determine how ROS may cell proliferation. ROS is known to induce downstream signaling pathways (Schieber and Chandel, 2014; et al., 2021), including signaling, a known to proliferation and et al., Thus, we sought to determine if cancer cells that had received macrophage mitochondria exhibited increased ERK We stably the et al., which from the to the cytoplasm ERK is in 231 cells cells with we used the imaging flow to in of cells that had or had not received macrophage mitochondria quantification and ERK signaling described in Figure supplements These data show that cancer cells with macrophage mitochondria have significantly higher cytoplasmic to ratios compared to cells that did not receive mitochondrial transfer, increased ERK (Figure Figure supplement Figure 3 with 4 supplements see all Download asset Open asset cancer cells exhibit proliferation. (a) was used to the of an in the or cytoplasm of co-cultured 231 cells that did (right) or did not (left) receive mitochondria (green, arrowhead). of and (b) ERK from data displayed in (d) mean fluorescence intensity N=3 donors indicated as shades of gray). (c) Confocal images of 231 cells expressing (green) and (magenta) with after control cytoplasmic or mito-KillerRed+ right). of (green) and (d) Quantification of to time Each represents a from a single cell. (e) Analysis of proliferative capacity by quantifying Ki-67 and DNA levels of co-cultured 231 cells treated with vehicle or ERK with or without transfer or (f), mitochondrial internalization after mitochondrial bath application donors; statistics for G2/M only). bars and scale bars are 10 Welch's t-test Mann-Whitney (d), two-way ANOVA *p<0.05; **p<0.01; ****p<0.0001. to our that cells that receive macrophage mitochondria exhibit increased ERK and that ROS is to induce cell proliferation, we then whether cancer cell mitochondrial ROS would directly ERK expressing both mito-KillerRed and in 231 cells, we induced ROS by mito-KillerRed+ and found that ROS increased that ROS is to increase ERK in cancer cells (Figure Figure supplement We next tested whether ERK signaling is for the mitochondrial cancer cell proliferation. We first determined an of an ERK that still ERK but does not dramatically affect 231 proliferation, as we sought to determine whether ERK mitochondrial proliferation, not proliferation more We first confirmed that with this of

Quantitative phase measurements at multiple wavelengths has created an opportunity for exploring new avenues in phase microscopy such as enhancing imaging-depth (1), measuring hemoglobin concentrations in erythrocytes (2), and more recently in tomographic mapping of the refractive index of live cells (3). To this end, quantitative phase imaging has been demonstrated both at few selected spectral points as well as with high spectral resolution (4,5). However, most of these developed techniques compromise imaging speed, field of view, or the spectral resolution to perform interferometric measurements at multiple colors. In the specific application of quantitative phase in studying blood diseases and red blood cells, current techniques lack the required sensitivity to quantify biological properties of interest at individual cell level. Recently, we have set out to develop a stable quantitative interferometric microscope allowing for measurements of such properties for red cells without compromising field of view or speed of the measurements. The feasibility of the approach will be initially demonstrated in measuring dispersion curves of known solutions, followed by measuring biological properties of red cells in sickle cell anemia.

Motility, or co-ordinated movement, of cells is fundamental for the development of many processes, such as formation of the embryo, the immune response, inflammation, wound healing, and metastasis of cancer cells 1. Cells often migrate in response to specific external signals, but they can also move spontaneously. Aberrant cell motility can be fatal in cancer diseases when cells start to metastasize 2. Metastasis is strictly associated with tissue invasion of the primary tumor cells, and occurs as a multistep progress 3. The first phase of cancer cell metastasis involves the physical translocation of the cell to a distant organ, whereas the second phase implicates the ability of the cancer cell to develop into a metastatic lesion at that distant site 4. For skin cancer melanoma, the main cause of death is widespread metastases 5. Melanoma cells may travel along external vessel lattices. After settling in the metastatic sites, melanoma cells develop mechanisms that protect them against the attack of the immune system. It is, therefore, of great interest and importance to investigate, monitor, and understand the principles of tumor cell invasion and migration. The development of novel therapeutic applications that have the ability to block migratory processes is crucial. For in vitro studies, the cell culture wound-closure, and the transwell migration and invasion assays can provide data for an understanding how well a particular cell type can migrate 6. The wound healing assay is also called a scratch assay because it is performed by making a scratch in the cell monolayer (Fig. 1A). The transwell migration assay is a commonly used test to study the migratory response of endothelial cells to angiogenic inducers or inhibitors (Fig. 1B). This assay is also known as the Boyden or modified Boyden chamber assay. These assays have been frequently used to study movement of cells. Weckmann et al. developed an interesting system to monitor and quantify neutrophils on single cell level, by utilizing commercially available tissue culture hardware, simple video microscopic equipment, and standardized tracking 7. However, the interest for novel standardized real-time analyses using quantitative phase imaging (QPI) for cell tracking is growing (Fig. 2). More than 10 years ago, the digital holographic (DH) microscopy methodology of QPI became known to a larger audience and the technique has since then successfully been applied for label-free monitoring of live cells undergoing cell division, cell proliferation, cell death, and cell migration over time 8-10. By QPI, studies associated with both cellular thickness and refractive index fluctuations have been performed. The possibilities for utilizing QPI for cancer diagnostics have increased 11. Cellular behavior and phenotypes are other parameters that can be measured 12. For two human osteosarcoma cell types, the motility pattern, but not the proliferative pattern, was different. Early migration studies using DH microscopy showed fibroblast migration 13 and HT-1080 fibrosarcoma cells embedded in a 3D collagen gel 14. Alm et al. and Persson et al. also presented data on movement of different cell types and cell sizes 15 as well as demonstrated the correlation of cell movement with cell morphology 16. In the recent article published in the November 2018 issue of Cytometry Part A by Zhang et al., (pages 1125–1131) commercially available DH cytometry platforms equipped with semi-automated image acquisition, segmentation, and analysis software packages for assessing cell behavior are used and discussed. The motility data was obtained with QPI/cytometry using "Track cells module" and "Wound healing module," respectively, and with transwell migration assays determining migration and invasion, respectively. The different techniques assessing motility were compared. The two melanoma cell lines, WM793 and 1205Lu, used in the study were reported to have different metastatic capacity, resulting in differences in proliferation and motility. The motility measured with the "Track cells module" and "Wound healing module," using DH cytometry equipment housed in an incubator, produced highly correlated relative motilities, even when compared to the standard transwell migration and invasion assays. Images acquired with DH are from the same position in a cell culture vessel, making it possible to study individual cells. This is a strong advantage, since most studies of effects of new drugs on proliferation and migration of cancer cells in culture are performed on a population level. In a recent study by Kamlund et al., cell images were captured every fifth minute for a total of up to 72 h 17. For cell movement studies, the semi-automated algorithm attempts to find each tracked cell in the next frame by selecting the closest cell based on the centroid position. The advantages of the Track cells and Wound healing modules over the transwell migration and invasion assays in the paper by Zhang et al., included the possibility to use the cells in the experiment for other purposes after completing the measurement. DH microscopy also benefits from the fact that morphology analysis can be performed of each cell. Indeed, this opens up for almost unlimited possibilities to perform cell morphology analysis using the QPI methodology, since each image is very rich in cellular information. As discussed in a review by El-Schich et al., automated analysis and machine learning is one approach to handle the large amount of morphological data that can now be generated when analyzing cells with QPI 8. Only the computer resources and the training speed will set the limitations.

Differential phase contrast (DPC) is a non-interferometric quantitative phase imaging method achieved by using an asymmetric imaging procedure. We report a pupil modulation differential phase contrast (PMDPC) imaging method by filtering a sample's Fourier domain with half-circle pupils. A phase gradient image is captured with each half-circle pupil, and a quantitative high resolution phase image is obtained after a deconvolution process with a minimum of two phase gradient images. Here, we introduce PMDPC quantitative phase image reconstruction algorithm and realize it experimentally in a 4f system with an SLM placed at the pupil plane. In our current experimental setup with the numerical aperture of 0.36, we obtain a quantitative phase image with a resolution of 1.73μm after computationally removing system aberrations and refocusing. We also extend the depth of field digitally by 20 times to ±50μm with a resolution of 1.76μm.

Inflammatory bowel diseases (IBD) are inflammatory disorders of the gastrointestinal tract characterized by a chronic relapsing disease course. As uncontrolled intestinal inflammation can result in severe disease complications, recent treatment targets of IBD evolved toward seeking the absence of mucosal and histological inflammation. However, this approach requires adequate histological evaluation of IBD disease activity. The diagnostic challenge of histological examination of intestinal inflammation is documented by the multitude of proposed histological scoring systems. In this context, we review quantitative phase imaging (QPI) techniques such as digital holographic microscopy (DHM) for characterizing intestinal inflammation. DHM determines optical path-length delays in a stain-free manner, thereby providing the tissue refractive index as a biophysical marker that directly correlates to tissue density. Recently, DHM has been successfully applied in cell biology, cancer cell research and infectious-induced cellular alterations. We summarized the capabilities of DHM and related QPI techniques to assess the severity of intestinal inflammation in experimental colitis as well as in colonic samples from human IBD patients. Moreover, we illustrate major advantages of DHM facilitated multimodal evaluation of epithelial wound healing processes as assessed by physical parameters like cell volume, density, thickness and dry mass in vitro. Furthermore, potential limitations of DHM and future utilities of QPI are discussed. In conclusion, DHM represents a promising, easy-to-use quantitative tool to provide accurate and objective assessment of intestinal inflammation and may pave the way towards automated label-free digital pathology and related in vitro cell culture analysis in future.

We propose a lensfree on-chip microscopy approach for wide-field quantitative phase imaging (QPI) based on wavelength scanning. Unlike previous methods, we found that a relatively large-range wavelength diversity not only provides information to overcome spatial aliasing of the image sensor but also creates sufficient diffraction variations that can be used to achieve motion-free, pixel-super-resolved phase recovery. Based on an iterative phase retrieval and pixel-super-resolution technique, the proposed wavelength-scanning approach uses only eight undersampled holograms to achieve a half-pitch lateral resolution of 691 nm across a large field-of-view of 29.85mm2, surpassing 2.41 times the theoretical Nyquist-Shannon sampling resolution limit imposed by the pixel size of the sensor (1.67 µm). We confirmed the effectiveness of this technique in QPI and resolution enhancement by measuring the benchmark quantitative phase microscopy target. We also showed that this method can track HeLa cell growth within an incubator, revealing cellular morphologies and subcellular dynamics of a large cell population over an extended period of time.

Digital holographic microscopy (DHM) is an important technique that may be used for quantitative phase imaging of unstained biological cell samples. Since the DHM technology is not commonly used in clinics or bioscience research labs, at present there is no well-accepted focusing criterion for unstained samples that users can follow while recording image plane digital holograms of cells. The usual sharpness metrics that are useful for auto-focusing of stained cells do not work well for unstained cells as there is no amplitude contrast. In this work, we report a practical method for estimating the best focus plane for unstained cells in the digital hologram domain. The method is based on an interesting observation that for the best focus plane the fringe pattern associated with individual unstained cells predominantly shows phase modulation effect in the form of bending of fringes and minimal amplitude modulation. This criterion when applied to unstained red blood cells shows that the central dip in the doughnut-like phase profile of cells is maximal in this plane. The proposed methodology is helpful for standardizing the usage of DHM technology across different users and application developmentefforts. LAY DESCRIPTION: Digital holographic microscopy (DHM) is slowly but steadily becoming an important microscopy modality and gaining acceptability for basic bio-science research as well as clinical usage. One of the important features of DHM is that it allows users to perform quantitative imaging of unstained transparent cells. Instead of using dyes or fluorescent labelling, DHM systems use quantitative phase as a contrast mechanism which depends on the natural refractive index variation within the cell samples. Since minimal wet lab processing is required in order to image cell samples with a DHM, cells can be imaged in their natural state. While DHM is gaining popularity among users, the imaging protocols across the labs or users need to be standardized in order to make sure that the same quantitative phase parameters are used for tasks such as quantitative phased based cellclassification. One of the important operational tasks for any microscopy work is to focus the sample under study. While focusing comes naturally to users of brightfield microscopes based on image contrast, the focusing is not straightforward when samples are unstained so that they do not offer any amplitude contrast. When performing quantitative phase imaging, defocus can actually change the phase profile of the cell due to near-zone (Fresnel) diffraction effects. So unless a standardized focusing methodology is used, it will be difficult for multiple DHM users (potentially at different sites) to agree on quantitative results out of their phase images. DHM literature has prior works which perform numerical focusing of recovered complex wave-field in the hologram plane to find the best focus plane. However such methods are not user friendly and do not allow user the same focusing experience as in a brightfield microscope. The numerical focusing is therefore a reasonably good method for an optics researcher but not necessarily so for a microscopy technician looking at cell samples with a DHM system in a clinicalsetting. The present work provides a simple focusing criterion for unstained samples that works directly in the hologram domain. The technique is based on an interesting observation that the when an unstained cell sample is in the best-focus plane, its corresponding hologram (or fringe pattern) predominantly shows phase modulation manifested by bending of fringes at the location of the cell. This criterion can be converted into a simple numerical method as we have used to find the best-focus plane using a stack of through focus holograms. We believe that the technique can be used manually by visually observing the holograms or can be converted to an auto-focus algorithm for a motorized DHMsystem.

Dielectric metasurfaces have recently attracted much attention due to their ability to efficiently control light propagation, that is, its amplitude, phase and polarization, on micro- and macro- levels. Such metasurfaces also naturally allow for integration in compact optical setups due to their small sizes. An important issue of energy losses is also addressed by employing all-dielectric platform. Advancements in nanofabrication have enabled realization of metasurface-based high-resolution wavefront engineering devices, which have been employed in different imaging applications, for example, as metalenses, polarization filters, metaholograms, etc. Quantitative phase imaging is a powerful tool for the optical inspection of transparent samples in connection with biological and technical applications. By measuring thickness and/or refractive index profiles, phase imaging facilitates, for example, the observation of dynamic events in unstained cells. As such, it has become indispensable in biological imaging, wavefront correction and metrology. However, conventional cameras and photodetectors are inherently not sensitive to the phase of an incident lightwave. As a consequence, direct phase detection is challenging. Only by multiple intensity measurements or application of specialized interferometric schemes, the phase profile of an object can be in principle reconstructed. In this paper, we report on the ability of metasurfaces to contribute to quantitative phase imaging by independent control of the phase profiles in two orthogonal polarization states of an incident beam.

Fluorescence imaging flow cytometry is an emerging technique for analyzing a large number of cells with high accuracy over conventional flow cytometry by virtue of its imaging capability. Unfortunately, the cell throughput of conventional fluorescence imaging flow cytometers (~1,000 cells/sec) is much lower than that of standard non-imaging flow cytometers due to the use of a CCD image sensor having a limited data transfer rate, making it difficult to analyze a large population of cells. Here we report our experimental demonstration of highly accurate classification of microalgae with a frequency-division-multiplexed confocal imaging flow cytometer (IFC) that enables imaging of every single microalgal cell with an unprecedentedly high throughput of 20,000 cells/sec. The high-speed imaging performance of the IFC is enabled by employing frequency-division-multiplexed confocal microscopy, which uses a sensitive single-pixel photodetector such as an avalanche photodetector or a photomultiplier tube to obtain images of flowing cells. We stained three species of microalgae (Chlamydomonas reinhardtii, Haematococcus lacustris, and Euglena gracilis) with SYTO16 and obtained three-color images of the cells (bright-field, fluorescence staining of nuclei, and autofluorescence of chlorophyll). We extracted 243-dimensional features from each three-color image and employed a support vector machine to classify the cells with the obtained multi-dimensional data. As a result, the cells were successfully classified with an accuracy of 99.7%. Due to the IFC’s multi-color imaging capability with an unprecedentedly high throughput, our technique has a wide variety of potential applications other than microalga classification, such as accurate blood screening and liquid biopsy.

Event Abstract Back to Event Dendritic pro-drug for local and selective treatment of locally advanced breast cancer Nuria Oliva1, Mariana Atilano1, 2*, João Conde1, 3*, Elazer R. Edelman1, 4* and Natalie Artzi1, 5* 1 MIT, IMES, United States 2 IQS, Chemical Engineering, Spain 3 Queen Mary University of London, School of Engineering and Materials Science, United Kingdom 4 BWH, Harvard Medical School, Cardiovascular Division, United States 5 BWH, Harvard Medical School, Department of Medicine, United States Introduction: Systemic neoadjuvant therapy has been established as the preferred therapeutic approach for locally advanced breast cancer, downstaging the disease and preventing mastectomy. However, complications of systemic chemotherapy are devastating. Local therapy would prevent high concentrations of circulating drug and reduce off-target tissue retention. Yet, the means to attain ideal release kinetics and selective uptake remain elusive. We have developed a novel class of biocompatible and biodegradable adhesive materials based on dendrimers and dextrans[1] that can coat the tumor and locally release drugs in a controlled manner. In this work, I have developed and optimized a dendritic pro-drug capable of discerning between healthy and cancer cells. It selectively enters EGFR-overexpressing breast cancer cells through receptor-mediated endocytosis (RME) and releases doxorubicin inside the cells. They will be added to our adhesive hydrogel for local and sustained delivery. Materials and Methods: PAMAM dendrimer generation 5 (Dendritech) was conjugated to EGF-mimicking peptides[2] (Biopolymer Lab, MIT) and also to doxorubicin (Cayman) through a pH-sensitive linker[3]. Cancer cells (MDA-MB-468, ATCC) and healthy mammary epithelial cells (HMEpC, ATCC) were cultured in their recommended media. Cells were treated with 10 uM tagged-dendrimer solutions and uptake was assessed by FACS. Doxorubicin release from the dendrimer was monitored through UV-VIS spectroscopy in PBS (pH 7.4) and acetate buffer (pH 5.5). Cancer and healthy cells were incubated with 10 uM dendritic pro-drug for 48 hours to study cytotoxicity. Results and Discussion: Fluorescence microscopy showed indiscriminate uptake of naked dendrimer independent of cell type (Fig. 1a-b), while dendrimer-peptide uptake was higher in EGFR+ cancer cells than in EGFR- healthy cells (Fig. 1d-e). Blocking of the receptor using an antibody caused abrogation of dendrimer-peptide uptake, but not naked dendrimer (Fig 1c and f). These results were corroborated by FACS (not shown). Taken together, these data prove that our dendrimer conjugates are being uptaken by RME through EGFR, as opposed to diffusion-driven uptake observed for naked dendrimer. Doxorubicin was conjugated to dendrimer-peptide through a cis-aconityl pH-sensitive linker to form the dendritic pro-drug. Incubation of the dendritic pro-drug in PBS (pH 7.4) showed no statistically significant doxorubicin release over 12 hours, while 45% of the drug was released in acetate buffer (pH 5.5) in the first 3 hours (not shown), thus corroborating pH-triggered release. The dendritic pro-drug showed 86% cytotoxicity after 48 hours in cancer cells, while no toxicity was observed in healthy cells (Fig. 1g-k). Conclusions: We have demonstrated that we can successfully develop a dendritic pro-drug that selectively treats EGFR-overexpressing tumors while minimizing side effects in healthy cells surrounding the tumor. The dendritic pro-drug will be incorporated to our adhesive hydrogel and release kinetics and in vivo efficacy will be assessed. Generalization of this platform with peptides targeting other commonly overexpressed growth factor receptors in cancer (FGF2R, VEGFR or PDGFR) will expand the targeting capabilities of our delivery system. We aim to develop a delivery platform capable of treating tumors in a local and selective manner. Marie Curie International Outgoing Fellowship and Funding (FP7-PEOPLE-2013-IOF, Project 626386); Dr. Dong Soo Yun for cryo-TEM assistance at the Peterson Nanotechnology Materials Core Facility; KI MIT Biopolymers Lab; Dr. Glenn Paradis for FACS assistance with Cancer Center Support (FACS core); KI Genomics Core/ MIT BioMicro Center; Timothy E. Cheng for assistance with computation of methods

Transmission optical coherence tomography (tOCT) is gaining interest for imaging biological samples; however, so far, quantitative phase information has not been directly obtained. This study introduces SOPHAST-OCT, an approach for integrated 2D phase recovery in Off-Axis Full-Field Swept-Source tOCT. It uses phase-shifting to leverage OCT’s inherent phase changes between recorded interferograms. SOPHAST-OCT demonstrates promising phase agreement with the simulated ground truth phase. This approach represents a first step toward quantitative imaging in tOCT. Full Text: PDF References Y. Park, C. Depeursinge, G. Popescu, "Quantitative phase imaging in biomedicine", Nature Photon 12, 578 (2018). CrossRef K. Alm, H. Cirenajwis, L. Gisselsson, A.G. Wingren, B. Janicke, A. Mölder, et al., in Holography, Research and Technologies (IntechOpen, 2011). CrossRef W. Drexler, J. Fujimoto, editors , Optical Coherence Tomography: Technology and Applications, 2nd ed. (Springer Cham, 2015). CrossRef W. Krauze, P. Ossowski, M. Nowakowski, M. Szkulmowski, M. Kujawińska, "Enhanced QPI functionality by combining OCT and ODT methods", Quantitative Phase Imaging VII, 11653, 19 (2021). CrossRef B.C. Wilson, S.L. Jacques, "Optical reflectance and transmittance of tissues: principles and applications", IEEE J. Quantum Electron. 26, 2186 (1990). CrossRef J. van der Horst, A.K. Trull, J. Kalkman, "Deep-tissue label-free quantitative optical tomography", Optica 7, 1682 (2020). CrossRef P. Hosseini, Y. Sung, Y. Choi, N. Lue, Z. Yaqoob, P. So, "Scanning color optical tomography (SCOT)", Opt. Expr. 23, 19752 (2015). CrossRef P. de Groot, "Phase Shifting Interferometry" in Optical Measurement of Surface Topography, edited by R. Leach (Springer, Berlin, Heidelberg, 2011). CrossRef M. Wojtkowski, A. Kowalczyk, R. Leitgeb, A.F. Fercher, "Full range complex spectral optical coherence tomography technique in eye imaging", Opt. Lett. 27, 1415 (2002). CrossRef Q. Zhang, S. Zhong, J. Lin, W. Chen, M. Luo, J. Zhong, Y. Yu, Z. Peng, S. Cheng, "Full-range Fourier-domain optical coherence tomography based on Mach–Zehnder interferometer", Opt. Lasers Engin. 124, 105794 (2020). CrossRef R. Juarez-Salazar, C. Robledo-Sanchez, F. Guerrero-Sanchez, A. Rangel-Huerta, "Generalized phase-shifting algorithm for inhomogeneous phase shift and spatio-temporal fringe visibility variation", Opt. Express 22, 4738 (2014). CrossRef R. Juarez-Salazar, C. Robledo-Sánchez, C. Meneses-Fabian, F. Guerrero-Sánchez, L. M. Arévalo Aguilar, "Generalized phase-shifting interferometry by parameter estimation with the least squares method", Opt. Lasers Engin. 51, 626 (2013). CrossRef M.A. Herráez, D.R. Burton, M.J. Lalor, M.A. Gdeisat, "Fast two-dimensional phase-unwrapping algorithm based on sorting by reliability following a noncontinuous path", Appl. Opt. 41, 7437 (2002). CrossRef Z. Wang, A.C. Bovik, "A universal image quality index", IEEE Signal Proc. Lett. 9, 81 (2002). CrossRef

Hybrid Random Walk-Linear Discriminant Analysis Method for Unwrapping Quantitative Phase Images of Biological Samples

Ovarian cancer is the deadliest gynecological cancer in women. It is a highly metastatic disease with pelvis, regional lymph nodes, and peritoneal cavity as major sites for tumor deposits. Mechanical properties of ovarian cancer cells can play a major role in metastasis as the cells detach from the ovaries and undergo deformation during the metastatic process. Herein, we have characterized the viscoelastic properties of the plasma membrane of normal epithelial (IOSE364) and cancerous (SKOV3) ovarian cells by optical tweezers and quantitative phase imaging. Using optical tweezers, we obtained time-resolved force profiles associated with membrane tethers pulled from the cells. We used quantitative phase imaging to measure the diameter of membrane tethers, and subsequently, estimated the membrane bending modulus and membrane tension in the tether. Our results indicate that the force (190 ± 76 pN) (mean ± standard deviation) required to separate the membrane of SKOV3 cells from the cytoskeleton was significantly lower (p = 0.0004) than the force (350 ± 81 pN) for IOSE364 cells. The mean stiffness (2.8 ± 0.8 pN/μm) of membrane tethers pulled from SKOV3 cells was significantly lower (p = 0.032) than the value for IOSE 364 cells (3.7 ± 0.8 pN/μm). Mean value of the force relaxation characteristic time associated with diffusive flow of lipids was also significantly lower (p = 0.018) for SKOV3 membranes (12.9 ± 6.9 s) as compared to the value for IOSE 364 membranes (20.4 ± 6.2 s). Similarly, the mean value of the membrane bending modulus for SKOV3 cells [(0.51 ± 0.23) × 10–18 J] was significantly lower (p = 0.007) than the value for IOSE364 cells [(1.29 ± 0.32) × 10–18 J]. Overall, our results suggest that the membranes of SKOV3 cells are less resistant to mechanical deformation. Increased membrane susceptibility to mechanical deformation may be a facilitating factor in the metastatic behavior of cancerous ovarian cells. Characterization of membrane biomechanics may provide a useful diagnostic biomarker for assessment of the metastatic potential of ovarian cancer, and a target for development of therapeutics.

A new method of phase derivative extracting for off-axis quantitative phase imaging

In this study, we utilized polarization-sensitive holotomography and Raman imaging to analyze prostate healthy (PNT2) and cancer (PC3) cells treated with glucose. After 48-hour incubation, distinct morphological differences were observed in cancer cells, including changes in volume, number, and refractive index of lipid droplets (LDs). Raman imaging confirmed the glucose uptake of these LDs. Cancer cells exhibited larger and more numerous LDs, with higher mean refractive-index and birefringence, compared to healthy cells. The study achieved over 90% accuracy in discriminating between cell types, highlighting its potential in cancer diagnostics. The research contributes to biomedical spectroscopy, offering a valuable tool for understanding cancer cell morphology and enabling early and precise cancer detection.