Highlights

  • Phagocytosis assay quantifying macrophage phenotypic behaviour during efferocytosis of apoptotic Jurkat cells
  • Livecyte combines high-contrast label-free imaging, correlative fluorescence, and robust single-cell segmentation to enable automatic measurement of phagocytosis
  • Single-cell analysis reveals how the rate of individual phagocyte activity changes over the course of the assay, quantifies when phagocytes become saturated and provides a complete picture of macrophage phenotypic behaviour

Introduction

Maintenance of tissue health and function requires high cellular turnover to replace damaged and old cells with new ones. This often results in an accumulation of apoptotic cells which need to be cleared quickly [1] as failure to remove them at an early stage can lead to development of a secondary necrotic state, prompting tissue inflammation in the local environment. Macrophages play a key role in tissue homeostasis quickly removing apoptotic cells without injuring the surrounding viable cells [2]. This process is known as efferocytosis and plays a central role in embryonic development, tissue repair and immunity [1].

The process of efferocytosis involves several steps and is a highly regulated requiring selective
communication between macrophage and apoptotic cell. Firstly, apoptotic cells release several 'find me' signals attracting and activating phagocytes triggering an increase in motility and migration to the site of cell death. Secondly, phagocytes recognize apoptotic cells from healthy cells through several 'eat me' signals on the surface of the cell. In addition, some surface proteins or 'don’t eat me' signals are used to differentiate viable cells and act to suppress phagocytosis [1]. Once detected, macrophages initiate a major cytoskeletal rearrangement allowing them to engulf dead cells [2]. As engulfment of apoptotic cells results in the attainment of a surplus of cellular material including lipids, carbohydrates, proteins and nucleic acids, regulatory degradation and efflux mechanisms are needed to adapt to this increased load [3]. Typically, this internalized material is routed to the endosomes and lysosomes eventually leading to enzymatic degradation (figure 1) [4].

There is a balanced homeostasis between the number of apoptotic cells that arise and the number and efficiency at which the surrounding macrophages engulf and process cellular material [5]. Dysregulation of phagocytosis often leads to aberrant cell clearance and an excess of apoptotic cells. These can become necrotic and lead to inflammatory signalling involved in tissue injury and infection and a variety of disease states including inflammatory diseases and atherosclerosis [5]. Thus, it is useful to understand this mechanism of regulation in more detail.

Traditionally, in vitro studies investigating phagocytosis use fluorescence, however in long-term live-cell imaging assays phototoxicity is frequently encountered which can impair sample physiology. In addition, conventional metrics typically measure total fluorescence intensity which can be misleading and inhibit the study of population heterogeneity [6].

Livecyte can utilise label-free phase imaging with intermittent fluorescence to track cells over time and measure fluorescence periodically enabling investigation of phagocytosis whilst substantially reducing phototoxic effects. The high-contrast label-free images produced by Livecyte facilitate robust segmentation of cells and phagocytosis activity can be quantified by measuring individual cell fluorescence.

In this assay we quantified phagocytosis using the RAW 264.7 macrophage-like cell line and different cell densities of pHrodo™ red treated Jurkat cells which only fluoresce in the acidic environment of the phagosome. In addition, we aimed to investigate changes inmacrophage behaviour in response to these apoptotic cells. We examined fluorescence intensity, random motility and the growth and proliferation of macrophages through Livecyte's label-free QPI mode
and in-built Analyse Software.

Method

Cell Culture

RAW 264.7 macrophages were routinely maintained in DMEM and Jurkat cells were cultured separately in RPMI-1640 supplemented with 10% FBS (complete medium hereafter) at 37°C with 5% CO2/95% humidity prior to experiments. Cells were harvested using standard techniques and cell count and viability was determined by trypan blue exclusion (ViCell; Beckman Coulter®). RAW 264.7 cells were seeded into the wells of a 96 well plate at 5000 cells/well and cultured overnight. Media was then replaced with complete medium only or containing different cell densities of pHrodo red treated Jurkat cells starting from a 1:4 (5000 RAW 264.7 cells:20,000 Jurkat cells), to 1:16 (5000 RAW 264.7 cells:80,000 Jurkat cells).

Resources

  • RAW 264.7 macrophage cell line
  • Jurkat T lymphocyte cell line
  • DMEM (Gibco)
  • RPMI-1640 (Gibco)
  • Foetal Bovine Serum (FBS; Gibco)
  • pHrodo fluorescent dye (ThermoFisher)
  • 96-well culture plate (Corning® 3603)
  • Livecyte Kinetic Cytometer (Phasefocus)
  • Livecyte Acquire & Analyse software (Phasefocus)

Time-lapse Imaging

Changes in fluorescence and motility were assessed with the Livecyte™ system's unique label free Quantitative Phase Imaging (QPI). Cells were imaged with an Olympus PLN 10X (0.25NA) objective and 1mm x 1mm field of view (FOV) per well for 24 hours at 15-minute intervals. Cells were maintained inside an environmental chamber at 37°C with 5% CO2/95% humidity.

Analysis & Results

We sought to monitor the effect of apoptotic cell dose on phagocytic activity in macrophages using cell densities that ranged from a low ratio to a cell density that may initiate a saturation of macrophages and reduction in phagocytosis. In addition, it was important to monitor motility of phagocytes to better understand their migration towards the apoptotic cells. Alongside this, to investigate further howmacrophages may adapt their phenotype in response to increased phagocytic pressure we aimed to investigate changes to their proliferation and growth over the course of the experiment. This report will focus on single cell and population metrics extracted from the Fluorescence, Random Motility, Proliferation and Morphology Dashboards in Livecyte’s Analyse Software, all from the same experiment.

In order to solely investigate macrophage response within the co-culture, further analysis tools were utilised. Livecyte enables users to isolate and understand the behaviour of a subpopulation of cells within a co-culture using the Explore page in Livecyte's Analyse software. Larger macrophage cells can be distinguished from smaller Jurkat cells based on label-free characteristics such as dry mass and area and filtered accordingly (figure 2). This filter was applied to the Dashboards allowing us to exclusively examine macrophage dependant changes.

Quantitative Phase Images & Cell Segmentation

The quantitative phase images generated by Livecyte are high contrast with cells appearing as bright features on a dark background; illustrative images from the different conditions are shown below (figure 3). The high contrast images enable robust cell segmentation enabling analysis of subtle morphological and motility changes as well as tracking over long periods of time. Furthermore, Livecyte automatically correlates the quantitative phase to the corresponding fluorescence images. Figure 3 shows images at different time points during the 24-hour period and provides real-time visualisation of the internalisation of apoptotic Jurkat cells. Automated analysis of fluorescence intensity enables quantification of phagocytosis over time.

For instance, these label-free images show RAW cells accumulating fluorescence throughout the experiment as they move towards, interact with, and engulf Jurkat cells. As expected this is intensified with higher cell densities of target cells with 1:16 RAW:Jurkat cell ratio showing a marked increase in fluorescence compared to a 1:4 ratio. In particular, from the images produced, we saw an increase in the number of Jurkat cells binding to macrophages. This was comparable to previous literature investigating target cell binding capacity in J774A.1 macrophages and found on average each macrophage had ~5 to 8 sites for binding apoptotic cells and that the magnitude of binding was proportional to the target cell dose [7].

Fluorescence Intensity - Quantification of Macrophage Phagocytosis

From the time-lapse images we observed changes in fluorescence over time as macrophages appear to engulf more apoptotic cells. To gain a further insight in and quantify phagocytic activity, we used metrics derived from the Fluorescence Dashboard in Livecyte’s Analyse software. A total integrated intensity line plot showing the change in total fluorescence across the region over time revealed that fluorescence intensity of RAW cells was proportional to the number of apoptotic Jurkat cells they were incubated with, i.e RAW cells incubated with 16 times as many apoptotic Jurkat cells had a higher fluorescence intensity than cells treated with 4 times the Jurkat cells (figure 4a). This suggests the more apoptotic cells in the environment led to increased phagocytosis. However, as total fluorescence is dependent on the number of cells present, a
population-level analysis of fluorescence intensity can be misleading. Livecyte can measure fluorescence at a single-cell level and provide intensity values per cell, thus allowing calculation of the median fluorescence intensity of the macrophages over time. This is independent of phagocytic number. A comparison of median fluorescence intensity and total fluorescence intensity graphs indicated a similar trend of increasing intensity with macrophage:Jurkat ratio. However, instead of a continuous increase in fluorescence, a plateau was observed in the median fluorescence intensity graphs at ~ 12 hrs instead of a continuous increase (figure 4b). This alluded to temporal differences in phagocytosis allowing identification of the largest increase in phagocytosis events and the point at which phagocytes were most active.

These temporal effects may be the result of several factors. The rate of median integrated intensity increase was reduced at an earlier point in macrophages treated with a lower dose of target cells. As macrophages have the capacity to bind to many Jurkat cells at once, a potential deficit of target cells later in the experiment may have led to a reduction in phagocytotic activity. Further to this, over a long-term experiment apoptotic cells become necrotic. There are several differences in the cellular disintegration of these two types of cell death and therefore the recognition of these cells occurs through distinctly separate mechanisms. RAW cells
in particular have been shown to lack the ability to bind and engulf necrotic cells and therefore it may be assumed that during the later timepoints in the experiment there is an accumulation of these previously apoptotic necrotic cells which are not engulfed by macrophages [7].

In addition, an overwhelming number of apoptotic target cells may eventually be a rate limiting factor in macrophage phagocytic events. Phagocytosis experiments conducted in J774A.1 macrophages showed that binding of target cells to macrophages was saturated in the latter part of the experiment, when incubating macrophages with target cells at a ratio of 40:1 for 60 minutes [7]. Macrophages have several physical and metabolic constraints that define their finite capacity to ingest and process cellular material and thus their overall phagocytic efficiency [8]. Although our study was a longer-term experiment and had a lower macrophage:Jurkat cell ratio, this correlates well with the plateau in fluorescence intensity where macrophages were incubated with high doses of target cells as well QPI images showing multiple Jurkat cell binding at high target cell doses. This highlights how a single-cell consideration is essential for determining when phagocytes become saturated, leading to a drop off in activity.

Label-free Random Motility of Macrophages

In addition to correlative fluorescence, Livecyte automatically measures cell proliferation, morphology and motility providing an insight into changes into macrophage cell behaviour, label-free. Analysis of the motility of RAW macrophages when incubated with Jurkat cells showed an increase in track speed compared to RAW cells cultured alone (figure 5a). In addition, time-binning of the data every 6 hours showed that when RAW cells were incubated with the highest cell density of Jurkat cells (x16) a large increase in the speed of cells was observed at the first time bin, after which a plateau was reached. This differed to RAWcells treated with lower cell densities of Jurkat cells (x8 and x4) where there was an overall step-wise increase in speed of the cells. This suggests macrophages incubated with a larger number of target cells reach a maximum speed early in
the experiment, presumably because apoptotic cells are within easy reach within the immediate environment. However, when jurkat cells are in shorter supply particularly during the latter part of the experiment, macrophages increase their speed to compensate this. This was corroborated by the Mean Velocity plot showing that over time cells incubated with the highest dose of Jurkat cells had a reduced velocity and eventually plateaued earlier than other treatment groups (figure 5b). Macrophages can adapt their behaviour to accommodate their changing environment. Once apoptotic cells are detected in the immediate surroundings, they drastically increase their speed and can subtly regulate this depending on the number of cells present. Physiologically this is important in maintaining a constant removal of apoptotic cells in changeable circumstances.

It was also possible to investigate other behavioural characteristics of macrophages, such as their ability to meander and wander from their original position through Livecyte's displacement and confinement ratio metrics. RAW cells incubated with apoptotic Jurkat cells were less confined and moved further away compared to RAW cells alone indicating apoptotic cells stimulated macrophages towards more long-range movement exploring a larger area (figure 6). Apoptotic cells are known to release chemotactic factors which attract macrophages to the site of apoptosis, increasing their motility. An experiment utilising the THP-1 macrophages incubated with supernatants from different apoptotic cell lines found apoptotic cells secreted several chemotactic factors, including the phospholipid LPC, which aided in mobilising macrophages towards apoptosis. This long-range signalling allows more efficient removal of apoptotic cells [9]. Subsequently, the number of apoptotic cells in the environment influence the range of macrophage movement. In one study it was shown an excessive number of apoptotic cells perturbed macrophagemigration [10]. Although the reason behind this is not fully known, analysis of QPI images showed multiple Jurkats adhere to RAW cells which may ultimately impede their movement. Furthermore, more Jurkat cells in the immediate environment may lead to macrophages reaching full phagocytic capacity and therefore reducing the need for macrophages to move fast.

Label-free Growth and Proliferation of Macrophages

In addition to motility, Livecyte can independently measure growth and proliferation of the cell population and collate this information within the Proliferation Dashboard. Here we report that macrophage phagocytosis of apoptotic cells caused a reduction in the proliferation of these cells compared to control through measuring cell count and cell doubling time and this was primarily influenced by apoptotic cell dose (figure 7a&c). In contrast with control RAWcells, cells incubated with Jurkat cells showed a slight plateau in cell count at around 8-12 hours (figure 7a). A similar trend was observed in previous proinflammatory activation studies with RAW 264.7 cells (see “AN017 - Quantifying Macrophage Activation and Proliferation” application note) suggesting activation of macrophages. Moreover, Livecyte is also able to measure cell growth through the unique metric Dry Mass. We observed a reduction in total dry mass in response to increasing number of apoptotic cells. However this was disproportionate to the overall reduction in cell count and cell doubling time (figure 7b). This observation suggests an uncoupling of cell growth and proliferation pathways and, despite a reduction in macrophage proliferation, macrophage growth continued.

To scrutinise this further, we utilized the Morphology Dashboard to investigate single-cell Dry Mass changes. Investigating Median Cell Dry Mass over time showed a target cell dose dependant increase, the larger the target cell dose the higher the increase in Cell Dry Mass (figure 8). This may suggest an accumulation of cellular material within RAW cells from the phagocytosis of apoptotic Jurkat cells. However, as the rate of proliferation was reduced, this phenomenon may also result in the accumulation of cell dry mass. A decline in dry mass was then observed in the latter 8 hours of the experiment correlating with the reduction in phagocytic events alongside possible initiation of phagocytic degradation pathways. This decline was observed earlier in cells
treated with lower Jurkat cell dose, correlating with a deficit in the number of target cells limiting phagocytosis. This corresponds with earlier median fluorescence intensity plots showing a plateau in single-cell fluorescent signal in the latter part of the experiment.

Figure 1: Phagocytosis and degradation of apoptotic Jurkat cells treated with pHrodo red.

Figure 2: A screenshot of the Explore page of Livecyte's Analyse software. A rectangular gate has been defined to exclude Jurkat cells which have a lower dry mass and area than RAW macrophages. This gate can then be applied to the Dashboards to independently analyse these two subpopulations.

Figure 3: Quantitative phase images with fluorescence overlay illustrating the accumulation of fluorescence over time in RAW
cells treated with 1:4 (top row) and a 1:16 (bottom row) ratio of macrophage: target cell. Images were taken at x10 magnification.

Figure 4: Graphs taken from the Livecyte Analyse Fluorescence Dashboard illustrating changes in total (a) and median integrated intensity (b) in response to increasing apoptotic Jurkat cells ranging from 1:4 (turquoise) to 1:16 (purple) ratio compared to raw cells alone (pink).

Figure 5: Graphs taken from the Livecyte Analyse Random Motility Dashboard. RAW cells were treated with increasing concentrations of apoptotic jurkat cells ranging from 1:4 (turquoise) to 1:16 (purple). Data was timebinned every 6 hours to show when macrophages were most motile in each treatment group and showed an increase in (a) track speed compared to RAW cells alone. (b) Mean Velocity line plot showed temporal changes in velocity in the latter part of the experiment.

Figure 6: Graphs taken from the Livecyte Analyse Random Motility Dashboard illustrating changes in the displacement (a) and confinement ratio (b)of RAWcells alone(pink) andtreatedwith dosesof apoptotic Jurkat cells ranging from 1:4 (turquoise) to 1:16 (purple). Compared to the control, RAW cells were less confined and more motile.

Figure 7: Graphs taken from the Livecyte Analyse Proliferation Dashboard illustrating changes in the (a) Cell Count, (b) Dry Mass, (c) Cell Doubling Time and (d) Dry Mass Doubling Time of RAW cells alone (pink) and treated with doses of apoptotic
Jurkat cells ranging from 1:4 (turquoise) to 1:16 (purple) Both a reduction in proliferation and overall growth of cells was observed however Total Dry Mass values were notably less pronounced.

Figure 8: Median Cell Dry Mass plot from the Livecyte Analyse Morphology Dashboard illustrating changes in RAW cells in response to dosesof apoptotic Jurkat cells ranging from1:4 (turquoise) to 1:16 (purple). A target cell dose dependant increase in cell dry mass was observed after which there was a decline in latter 8 hours of the experiment.

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Summary

Macrophages are a major part of the innate immune system and play a key role in the phagocytosis of apoptotic bodies before they become necrotic, ameliorating the initiation of inflammatory pathways. This coordinated response is tightly controlled by several mechanisms including the balance between the number of apoptotic cells in the surrounding space and macrophage efficiency. Macrophage behaviour can adapt to apoptotic load to increase this efficiency, for instance, by an increase in motility. However if the number of apoptotic cells becomes excessive it can lead to saturation and a significant reduction in phagocytosis.

In this study we aimed to investigate the effects of apoptotic cell dose on macrophage phagocytic activity and analyse subtle changes in phagocyte behaviour. The interaction between apoptotic cells and macrophages, and the subsequent phenotypic transformation of effector cells is intricate, requiring a combination of both time-lapse and single-cell measurements to achieve a full physiological perspective. Through analysing median fluorescence intensity, we were able to identify temporal changes in phagocytotic activity and identify when phagocytes were their most active. It also enabled us to establish a levelling-off period when macrophages reached full phagocytic capability.

Fluorescence metrics enabled us to quantify phagocytosis. However, we also investigated howmacrophages adapt their phenotypic behaviour to enhance functionality, label-free. We observed an overall increase in macrophage motility in response to the apoptotic Jurkat cells. Comparison between different target cell doses showed subtle differences in macrophage speed, suggesting those cultured with a lower number of target cells increased their movement speed more to compensate.

Furthermore, wewere able to gain quantitative insight into growth and proliferation changes during this period and independently evaluate the uncoupling of these two pathways. A reduction in the rate of proliferation is synonymous with macrophage activation [11] and this was seen to a greater extent with higher doses of Jurkat cells. However individual cell Dry Mass showed a target dose dependant increase. This could be suggestive of macrophages accumulating mass through apoptotic cell engulfment. However, another contributing factor may arise from a reduction in cellular proliferation whilst maintaining consistent cell growth.

In this Application Note, Livecyte has enabled us to reliably investigate time-sensitive changes of immune cells in response to target cells to enhance our understanding of efferocytosis regulation. From a single experiment, it is possible to generate a host of quantitative insights to both substantiate and validate existing data as well bring new facets to investigate the complex mechanisms that make up a biological response. Livecyte is a crucial tool in bringing a new dimension to traditional in vitro immune assays, advancing the knowledge, and understanding of these pathways.


References

  1. Elliott, M.R. and Ravichandran, K.S., 2016. The dynamics of apoptotic cell clearance. Developmental cell, 38(2), pp.147-160.
  2. Arandjelovic, S. and Ravichandran, K.S., 2015. Phagocytosis of apoptotic cells in homeostasis. Nature immunology, 16(9), pp.907-917.
  3. Elliott, M.R., Koster, K.M. and Murphy, P.S., 2017. Efferocytosis signaling in the regulation of macrophage inflammatory responses. The Journal of Immunology, 198(4), pp.1387-1394.
  4. Lemke, G., 2019. How macrophages deal with death. Nature Reviews Immunology, 19(9), pp.539-549.
  5. Morioka, S., Maueröder, C. and Ravichandran, K.S., 2019. Living on the edge: efferocytosis at the interface of homeostasis and pathology. Immunity, 50(5), pp.1149-1162.
  6. Icha, Weber, Waters and Norden, 2017. Phototoxicity in live fluorescence microscopy, and how to avoid it. Bioessays. 39(8).
  7. Cocco, R.E. andUcker, D.S., 2001. Distinctmodes of macrophagerecognition for apoptotic andnecrotic cells are not specified exclusively by phosphatidylserine exposure. Molecular biology of the cell, 12(4), pp.919-930.
  8. Zent, C.S. and Elliott, M.R., 2017. Maxed out macs: physiologic cell clearance as a function of macrophage phagocytic capacity. The FEBS journal, 284(7), pp.1021-1039.
  9. Lauber, K., Bohn, E., Kröber, S.M., Xiao, Y.J., Blumenthal, S.G., Lindemann, R.K.,Marini, P., Wiedig, C., Zobywalski, A., Baksh, S. and Xu, Y., 2003. Apoptotic cells induce migration of phagocytes via caspase-3-mediated release of a lipid attraction signal. Cell, 113(6), pp.717-730.
  10. Roddie, H.G., Armitage, E.L., Coates, J.A., Johnston, S.A. and Evans, I.R., 2019. Simu-dependent clearance of dying cells regulates macrophage function and inflammation resolution. PLoS biology, 17(5), p.e2006741.
  11. Liu, L., Lu, Y.,Martinez, J., Bi, Y., Lian, G.,Wang, T.,Milasta, S.,Wang, J., Yang, M., Liu, G. and Green,D.R., 2016. Proinflammatory signal suppresses proliferation and shifts macrophagemetabolism fromMyc-dependent toHIF1α-dependent. Proceedings of the National Academy of Sciences, 113(6), pp.1564-1569.