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. Author manuscript; available in PMC: 2023 Jun 1.
Published in final edited form as: J Comp Neurol. 2021 Dec 1;530(8):1263–1275. doi: 10.1002/cne.25274

Ultrastructural Analysis of the Morphological Phenotypes of Microglia Associated with Neuro-inflammatory Cues

Eric Dyne a, Meghan Cawood b, Matthew Suzelis b, Reagan Russell b, Min-Ho Kim a,b
PMCID: PMC8969092  NIHMSID: NIHMS1756309  PMID: 34773250

Abstract

Microglia are the primary resident immune cells of the central nervous system that are responsible for the maintenance of brain homeostasis. There is a plethora of evidence to suggest that microglia display distinct phenotypes that are associated with the alteration of cell morphology under varying environmental cues. However, it has not been fully explored how the varying states of microglial activation are linked to the alteration of microglia morphology, especially in the microdomain. The objective of this study was to quantitatively characterize the ultrastructural morphology of human microglia under neuro-inflammatory cues. To address this, a human cell line of microglia was stimulated by anti-inflammatory (IL-4), pro-inflammatory (TNF-α), and Alzheimer’s disease (AD)-associated cues (Aβ, Aβ + TNF-α). The resulting effects on microglia morphology associated with changes in microdomain were analyzed using a high-resolution scanning electron microscopy. Our findings demonstrated that microglial activation under pro-inflammatory and AD-cues were closely linked to changes not only in cell shape, but also in cell surface topography and higher-order branching of processes. Furthermore, our results revealed that microglia under pro-inflammatory cues exhibited unique morphological features involving cell-to-cell contact and the formation of vesicle-like structures. Our study provides insight into the fine details of microglia morphology associated with varying status of microglial activation.

Keywords: Microglia, scanning electron microscopy, morphology, processes, inflammation

Graphical Abstract

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We used a high-resolution scanning electron microscopy (SEM) image analysis to characterize the ultrastructural morphology of human microglia under neuro-inflammatory cues. The C20 human microglia cell line was stimulated by anti-inflammatory (IL-4), proinflammatory (TNF-α), and Alzheimer’s disease (AD)-associated cues (Aβ), and the resulting effects on microglia morphology associated with changes in microdomain (higher-order branching of processes and surface topography) were analyzed. The use of SEM enabled the characterization of microglia morphology in resolving fine details about microglia ultrastructure that were previously unappreciated.

Introduction

Microglia are the resident phagocytes of the central nervous system and serve a critical role in maintaining homeostasis of the brain during development, aging, and neurodegeneration (Asai et al., 2015; Hickman et al., 2008; Y. Li et al., 2014). Acting as an immune regulatory cell, microglia respond rapidly to changes in the surrounding environment by undergoing a phenotypic conversion that releases either proinflammatory or anti-inflammatory cytokines (Aloisi, 2001; Sala et al., 2003). Given the dynamic functionality of microglia in homeostasis and neuroinflammation, it is important to predict the functional activation and polarization of microglia under varying microenvironments. Ransohoff (2016) demonstrated that a variety of sub-functional phenotypes are dependent upon the local environment and established greater complexity than the commonly used simplified M1/M2 phenotypes (Ransohoff, 2016). Large-scale transcriptional profiling has provided the fundamental knowledge of various transcriptional states with unique gene clusters (Das et al., 2016; Hammond et al., 2019; Holtman et al., 2015). Along with these efforts, numerous studies revealed that the functionality of microglial cells was closely related to their morphological changes (Davis et al., 1994, 2017; Laurenzi et al., 2001; Cho and Choi, 2017).

As a methodology to determine microglia morphology, light microscopy analysis of microglia has most commonly been used (T. E. Chan et al., 2018; Fernández-Arjona et al., 2017; Hopperton et al., 2018; Lawson et al., 1990; Paasila et al., 2019). Under the light microscopy, features such as cell shape and major processes can be observed and quantified using techniques like the Scholl analysis to understand the characteristic patterns of resting and activated microglial morphologies. For example, a recent study by Fernández-Arjona et al. (2017) related specific morphotypes with microglial activation status in specific brain locations using a rat inflammation model (Fernández-Arjona et al., 2017). The spatiotemporal relationship between microglia morphology and cerebral inflammation was characterized in a murine model of cerebral injury (Morrison & Filosa, 2013). However, the use of light microscopy is still limited in characterizing microglia morphology accompanied with changes in microdomain such as cell surface topography and higher-order branching of processes whose functions in microglial activation are not yet fully explored (Savage et al., 2018). Higher-order branching of processes, also referred to as minor processes, are seldom seen under traditional light microscopy due to their thickness being within a few nanometers (Torres-Platas et al., 2014). Higher resolution microscopy, such as two-photon imaging, has provided the ability to observe the minor processes on a detailed scale (Davalos et al., 2005; Gyoneva et al., 2014; Nimmerjahn et al., 2005). Electron microscopy uses electrons in a vacuum as illuminating radiation to make out structures at a higher resolution than light optic microscopes due to a shorter wavelength. The use of scanning electron microscopy (SEM) provides the clarity necessary to perform a detailed analysis of single processes. A benefit of using SEM is that it can construct high-resolution three-dimensional images at a resolution of nanometer-scale (Caballero, 2003), which enables the imaging of both microscopic and nanoscopic anatomy of microglia that are difficult to capture with traditional light microscopy.

The objective of this study was to quantitatively characterize the ultrastructural morphology of human microglia under neuro-inflammatory cues. The C20 human microglia cell line was stimulated by anti-inflammatory (IL-4), proinflammatory (TNF-α), and Alzheimer’s disease (AD)-associated cues (Aβ, Aβ+TNF-α), and the resulting effects on microglia morphology associated with changes in microdomain (processes characteristics and surface topography) were analyzed using a SEM image analysis.

Materials and Methods

Human microglial cell culture

C20 human microglial cells were obtained through the generosity of the Jonathan Karn laboratory at Case Western Reserve University (Cleveland, Ohio). Microglia were isolated from resected adult human brain tissue through a surgical procedure (University Hospitals, Cleveland, Ohio). The microglial cells were then immortalized using either SV40 T antigen lentiviral vector or with a combination of SVR40 T antigen and hTERT (Alvarez-Carbonell et al., 2019; Garcia-Mesa et al., 2017). The C20 cells were incubated in DMEM:F12 (50:50) with the added supplements: 10% fetal bovine serum (FBS), 100 ug/mL normocin, 1X pen/strep, 1X N2. Additional tests in serum-free conditions involved treatment of microglia cells in DMEM:F12 (50:50) + 1X pen/strep for up to two weeks.

Preparation and dosage of treatments

Recombinant TNF-α and IL-4 were purchased from Peprotech (NJ, USA) and reconstituted according to the manufacturer’s recommended protocol. Both TNF-α and IL-4 were treated to microglia cells at 100 ng/mL for 24 h. Amyloid beta (beta-amyloid) peptide (1–42) (Aβ) (#4014447), was purchased from Bachem. Beta-amyloid (1 mg) was dissolved in 1,1,1,3,3,3-Hexafluoropropan-2-ol ((CF3)2CHOH) (HFIP) (1.5 mL) by brief sonication and vortex, and then stored overnight at ambient temperature (25°C) in 100 mL aliquots covered in a fume hood to allow the HFIP to evaporate into a film. The Aβ1–42 film was reconstituted in a phosphate buffer that consisted of CH3CN/Na2CO3 (300 mM)/NaOH (250 mM) (48.3:48.3:3.4, v/v/v) alkaline solution (30 μL), 10 mM phosphate buffer (270 μL), and acetonitrile (10 μL) to stock Aβ (310 μL) (20 μM). In order to form large Aβ fibrillar plaques, freshly reconstituted Aβ (20 μM) was added to a 30°C stationary incubator for 16 h, which formed reproducible Aβ fibrillary plaques around 6 μm in size. Aβ plaque size was confirmed using dynamic light scattering analysis and transmission electron microscopy (TEM). Aβ fibrils were treated to C20 microglia at 1 μM for 24 h. This concentration was established by both performing a titration of beta-amyloid and analyzing C20 viability (Dyne et al., 2021) and by referencing the reported literature (Caldeira et al., 2017; Lue et al., 2001).

Scanning electron microscopy imaging

C20 microglia were seeded (2×104 cells) onto an uncoated cover glass in a 6-well cell culture plate for 24 h. Following adherence, the microglia received treatment. Microglia were then washed 3x with PBS, fixed in 4% glutaraldehyde for 24 h, and then stained for 1 h in 1% OsO4. The samples were then dehydrated in a series of ethanol washes at increasing concentrations for 15 min each. The samples were imaged on a FEI Quanta450 FEG Environmental Scanning Electron Microscope (ESEM) with a Nabity NPGS E-Beam Lithography (EBL). At least 25 images of each sample were captured using secondary electron detection.

Quantification of the microglia cell structures

Microglia morphological changes to the cell body and the dendritic-like processes using SEM were compared across different treatments. The cell body shape characterizations were flattened, unipolar, bipolar, and multipolar based on the number of major processes extending from the cell body (Figure 1a). The perimeter was determined by two individual investigators; results were compared and averaged. Measurements focused on the terminal ends of the cell body and omitted lamellipodia. Processes are referred to as either ‘major’ or ‘minor’ based upon the number of branches and the diameter of each process (Figure 1b). Thick processes budding off the cell body where stretching is evident are referred to as major processes. These thick processes have also been referred to as lamellipodia, as microglia are considered motile cells (Marín-Teva et al., 1999). Minor processes, also referred to as filopodia in the literature (Bernier et al., 2019), are much shorter than major processes, and were observed to bud directly off either the cell body or major processes without distortion. Major processes are thought to function primarily for the detection of signaling molecules, whereas the minor processes off the cell body seem to play a role in cellular signaling, motility, and sensation (Bernier et al., 2019). The true roles of both major and minor processes are currently unknown (Avignone et al., 2015). The scale bar was set to the provided scale bar on the SEM image file and the freehand tool was used to trace the cell body perimeter. The length was measured three times and the mean value was taken. The aspect ratio, major axis, and minor axis were analyzed to understand morphological changes of the cell body. The major axis was found by taking the pixel distance between the maximal diameter of the cell body. The minor axis was the pixel distance between the cells’ most minimal diameter. Using the major and minor axes, the aspect ratio was measured by taking the ratio of the length of the major axis to the length of the minor axis (Figure 1c). All measurements were made using Fiji ImageJ image analysis software using the freehand tool calibrated to the provided scale bar for accurate measurements.

Figure 1: Representative SEM images of various morphological parameters used for the quantitative analysis of human microglia.

Figure 1:

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The morphological feature for (a) cell shapes, (b) processes, (c) aspect ratio, and (d) surface topography defined in SEM images of microglia. The surface topography of the microglia was characterized by varying surface patterns (smooth, blebbed, ruffled, pitted).

Microglia topographical examination

The surface of the microglia was assessed across groups for distinct anatomical differences such as surface topographic description and cavities. Cells were classified as either smooth, blebbed, ruffled, or pitted (Figure 1d). Smooth surface topography had few cavities and a glossy surface lacking topographic features. Blebbed surfaces demonstrated multiple bulges on the cell surface. Ruffled morphology was characterized by a rocky cell surface appearance with numerous cavities. Pitted cells were those which displayed prominent cavities across the cell body surface. Images were analyzed using Fiji ImageJ image analysis software. Images were analyzed across each group by two blinded investigators and then the results were analyzed for the percent of representative morphologies from each treatment group.

qPCR assay for quantifying mRNA expression in microglia

Human C20 microglia were grown overnight at 2.5 × 105 cells in DMEM:F12 media in a 6-well plate overnight. Total RNA was isolated using an E.Z.N.A. total RNA kit (Omega Bio-Tek) and then RNA quality and content were measured on a Nanodrop microvolume spectrophotometer (Thermo Fisher). mRNA (1 μg) was reverse transcribed into cDNA and the subsequent qPCR reaction was performed using a Mastercycler® Realplex2 (Eppendorf) by at least three independent tests. The genes screened included pro-inflammatory (TNF-α, IL-1β, IL-6) and anti-inflammatory (TGF-β, Arg1, IL-4,) genes normalized to GAPDH, a housekeeping gene, and expressed as a fold-change in mRNA. The primer sequences used in this study are provided in Table 1.

Table 1.

Primers used for RT-qPCR analysis of cDNA from human microglia.

Primer Name Forward (5’ to 3’) Reverse (5’ to 3’)
TNF-α CTTCTGCCTGCTGCACTTTGGA TCCCAAAGTAGACCTGCCCAGA
IL-1β ATGATGGCTTATTACAGTGGCAA GTCGGAGATTCGTAGCTGGA
IL-6 GTAGCCGCCCCACACAGACAGCC GCCATCTTTGGAAGGTTC
TGF-β CTGGATTGTGGTTCCATGCA TCCCCGAATGCCTCACAT
Arg1 GTG G AAACTTG CATGGACAAC AATCCTGGCACATCGGGAATC
IL-4 AACGGCTCGACAGGAACCT ACTCTGGTTGGCTTCCTTCCA
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Statistical Analysis

Data analysis was performed using GraphPad Prism 9 (California, US). Unless noted, all treatments are compared to control microglia. Two-tailed unpaired t-tests and 1-way ANOVA with Tukey’s post-hoc analysis across multiple comparisons were used to determine statistical significance between groups. For all analyses, p-values of less than 0.05 (p<0.05) were considered to be statistically significant. For all analyses, each treatment was carried out in three independent trials and a mixture of images used from all three trials were analyzed. All statistical data represents data averaged from each individual cell in their respective treatment group, then averaged again to represent the entire treatment group sample data. Data are presented as means +/− standard deviation (SD).

Results

Effects of anti-inflammatory cue (IL-4) on the ultrastructural morphology of human microglia.

The anti-inflammatory cytokine IL-4 was used to demonstrate the morphological behavior of microglia when exposed to an anti-inflammatory cue. The surface topography in microglia treated with IL-4 demonstrated a glossy smooth surface with few cavities, but no major cavities were observed (Figure 2a). Among the total number of cells analyzed, the majority of control cells displayed a smooth surface (47%), and other cells displayed either blebbed (20%), ruffled (20%), or pitted surface morphology (13%). IL-4-associated microglia mainly demonstrated a glossy smooth surface with few cavities (85%) and only 8% of cells demonstrated both ruffled and pitted morphology and no blebbed surface topography. Compared to the control cells, the IL-4 treated microglia had no significant change in cell body perimeter (33.881± 5.196 μm, n=15 for control microglia to 36.087± 4.753 μm, n=28 for IL-4-associated microglia, p>0.05) (Figure 2b). However, the aspect ratio in IL-4 treated microglia was significantly less than the control microglia (p<0.05) associated with a decrease in the major axis length, resulting in more rounded morphology than control cells (Figure 2c). The major process length observed in the IL-4 treated microglia was significantly decreased compared to control cells (46.941 ± 16.989 μm, n=15 in control microglia to 27.151 ± 12.564 μm, n=25 for IL-4-associated microglia, p<0.0001) (Figure 2d), while the average number of major processes remained unchanged (3.000 ± 0.882 processes, n=18 for control microglia to 3.074 ± 1.152 processes, n=27 for IL-4-associated microglia) (Figure 2e). The lengths of the minor processes off the cell body for the IL-4 group also significantly decreased (6.437 ± 1.120 μm, n=15 for control microglia to 4.573 ± 1.247 μm, n=25 for IL-4-associated microglia, p<0.0001) (Figure 2f), while the average number of minor processes off the cell body remained unchanged (30.462 ± 18.454 processes, n=13 for control microglia to 23.769 ± 13.098 processes, n=26 for IL-4-associated microglia) (Figure 2g). The average number of minor processes off major processes were significantly decreased (33.625 ± 9.313 processes, n=8 for control microglia to 16.333 ± 11.711 processes, n= 24 for IL-4-associated microglia, p<0.001) (Figure 2h), but there was no change in the minor process length off the major processes (5.177 ± 2.080 μm n=15 for control microglia to 5.503 ± 2.861 μm, n=25 for IL-4-associated microglia, p>0.05) (Figure 2i). The thickness of the major processes was not significantly changed compared to control microglia (p>0.05) (Figure 2j). The anti-inflammatory effect of IL-4 was validated with an increase of anti-inflammatory gene, Arg 1, but no change in the expression of proinflammatory genes including TNF-α and IL-1β (Figure 2k). Taken together, the cell body became more rounded with smooth surface topography, associated with a decrease in the lengths of major processes and minor processes off of the cell body, following the exposure to IL-4.

Figure 2. Effects of IL-4 on the ultrastructural morphology of microglial cells.

Figure 2.

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(a) Representative SEM images of microglial cells for untreated control (left panel) and treated with IL-4 (right panel). Top: low magnification, Bottom: high magnification. (b-j) Quantifications of (b) cell body perimeter, (c) aspect ratio, (d) major process length, (e) number of major processes, (f) minor process length off cell body, (g) number of minor processes off cell body, (h) minor process length off major process, (i) number of minor processes off the major process in control and IL-4-treated microglial cells, and (j) major process thickness. Number of cells analyzed: n=8–15 for the control group and n=24–28 for the IL-4 group. (k) Expression of pro-inflammatory (TNF-α, IL-1β, IL-6) and anti-inflammatory (TGF-β, Arg1) genes for the control and IL-4-treated microglial cells. Number of biological replicates, n=3 per group. *: p<0.05, ***: p<0.0005, ****: p<0.0001.

Effects of proinflammatory cue (TNF-α) on the ultrastructural morphology of human microglia.

Recognition of proinflammatory cytokines is a potent catalyst of microglia morphological change (Lively & Schlichter, 2018; Wang et al., 2015). TNF-α is a major proinflammatory cytokine for neuroinflammation and is commonly upregulated by microglia when exposed to stimuli like a misfolded protein or bacterial pathogens (Béraud et al., 2013; Goos et al., 2007; Michaud et al., 2013). The surface topography of the TNF-α-associated microglia appeared to form cavities and blebs with highly ruffled (47% of total cells analyzed) and pitted (22%) morphology, which were not as commonly observed in control microglia. (Figure 3a). The cell body perimeter showed a significant increase (33.881 ± 5.196 μm, n=15 for control microglia to 42.749 ± 8.110 μm, n=25 for TNF-α-associated microglia, p<0.001) (Figure 3b). The aspect ratio in TNF-α treated microglia was significantly increased compared to control cells (p<0.05), associated with a significant increase in the major axis length (Figure 3c). The average length of major processes of TNF-α-associated microglia was significantly shorter than control microglia (46.941 ± 16.989 μm, n=15 in control microglia to 25.217 ± 16.340 μm, n=24 in TNF-α-associated microglia, p<0.001) (Figure 3d), while the average number of major processes remained unchanged (3.000 ± 0.882 processes, n=18 for control microglia to 2.389 ± 0.891 processes, n=18 for TNF-α-associated microglia) (Figure 3e). The length of minor processes off the cell body in TNF-α-associated microglia was significantly decreased compared to control microglia processes (6.437 ± 1.120 μm, n=15 for control microglia to 4.610 ± 1.457 μm, n=24 for TNF-α-associated microglia, p<0.001) (Figure 3f). The average number of minor processes off the cell body demonstrated a significant increase (30.462 ± 18.454 processes, n=13 for control microglia to 23.037 ± 10.779 processes, n=27 for TNF-α-associated microglia) (Figure 3g). Like the IL-4 response, TNF-α treatment significantly decreased the average number of minor processes off the major processes in C20 microglia (33.625 ± 9.313 processes, n=8 for control microglia to 12.385 ± 12.039 processes, n=26 for TNF-α-associated microglia, p<0.0001) (Figure 3h), while the length of the minor processes off the major processes was unchanged (5.179 ± 2.080 μm, n=15 for control microglia to 5.527 ± 3.709 μm, n=24 for TNF-α-associated microglia, p>0.05) (Figure 3i). The thickness of the major processes was not significantly changed compared to control microglia (p>0.05) (Figure 3j). The proinflammatory effect of TNF-α was validated by the upregulation of proinflammatory genes IL-1β and IL-6 (p<0.0001) (Figure 3k). Taken together, our results showed that microglia activated by TNF-α displayed an increased cell body with highly ruffled surface topography and decreased process length, which is in line with a phenotype of an activated microglial cell associated with the retraction of processes and increase in cell body size (Avignone et al., 2015; B. M. Davis et al., 2017; Stence et al., 2001).

Figure 3. Effects of TNF-α on the ultrastructural morphology of microglial cells.

Figure 3.

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(a) Representative SEM images of microglial cells for untreated control (left panel) and treated with TNF-α (right panel). Top: low magnification, Bottom: high magnification. (b-j) Quantifications of (b) cell body perimeter, (c) aspect ratio, (d) major process length, (e) number of major processes, (f) minor process length off cell body, (g) number of minor processes off cell body, (h) minor process length off major process, (i) number of minor processes off the major process in control and TNF-α-treated microglial cells, and (j) major process thickness. Number of cells analyzed: n=8–18 for the control group and n=24–27 for the TNF-α group. (k) Expression of pro-inflammatory (IL-1β, IL-6) and anti-inflammatory (TGF-β, IL-4, Arg1) genes for control and TNF-α-treated microglial cells. Number of biological replicates, n=3 per group. *: p<0.05, **: p<0.001, ***: p<0.0005, ****: p<0.0001.

Effects of AD-associated cues (Aβ+TNF-α) on the ultrastructural morphology of human microglia.

Accumulation of Aβ, a classical hallmark of AD, has been shown to promote proinflammatory activation of microglia and contribute to neuroinflammation (Dani et al., 2018; Hansen et al., 2018; Heurtaux et al., 2010; Mandrekar-Colucci & Landreth, 2010). To understand the morphological changes of microglia associated with AD, C20 microglia were treated with Aβ (1μM) and changes in morphological parameters were characterized. The surface topography of the Aβ-associated microglia appeared as either blebbed (20% of total cells), pitted (45%), or ruffled (35%); a similar surface topography to the TNF-α associated microglia morphology, but appears to experience amoeboid transition following the exposure of Aβ (Figure 4a and Figure 5a). Notably, the small cavities observed on control and IL-4-associated microglia seem to enlarge across the cell surface in Aβ-associated microglia, especially near the processes of the cell body (Figure 5b). Compared to control, the average perimeter size of the Aβ-associated microglia increased significantly (33.881± 5.196 μm, n=15 for control microglia to 44.672 ± 12.631 μm, n=22 for Aβ-associated microglia, p<0.001) (Figure 4b), but there was no change in the aspect ratio of the cell body compared to control microglia (Figure 4c). The length of the major processes significantly decreased from the control values (46.941 ± 16.989 μm, n=15 in control microglia to 23.210 ± 14.304 μm, n=20 in Aβ-associated microglia, p=0.0005, Figure 4d); however, the average number of major processes for Aβ-associated microglia did not significantly change compared to the control (3.000 ± 0.882 processes n=18 for control microglia to 2.920 ± 1.547 processes n=25 in Aβ-associated microglia, Figure 4e). Both the length of the minor processes off the cell body (6.437 ± 1.120 μm, n=15 for control microglia to 3.793 ± 1.525 μm, n=20 for Aβ-associated microglia, p<0.0001, Figure 4f) and the average number of minor processes off the cell body (30.462 ± 18.454 processes, n=13 for control microglia to 16.444 ± 12.006 processes, n=18 for Aβ-associated microglia, p<0.05, Figure 4g) were significantly decreased compared to the control group. The average number of minor processes off the major processes of microglia treated with Aβ significantly decreased (33.625 ± 9.313 processes, n=8 for control microglia to 12.800 ± 17.394 processes, n=20 for Aβ-associated microglia, p<0.01, Figure 4h), while the length of minor processes off the major processes remained unchanged (Figure 4i).

Figure 4. Effects of beta-amyloid (Aβ) on the ultrastructural morphology of microglial cells.

Figure 4.

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(a) Representative SEM images of microglial cells for untreated control (left panel), treated with Aβ (top right panel), and treated with TNF-α+Aβ (bottom panel). In each group, top: low magnification, bottom: high magnification. (b-j) Quantifications of (b) cell body perimeter, (c) aspect ratio, (d) major process length, (e) number of major processes, (f) minor process length off cell body, (g) number of minor processes off cell body, (h) minor process length off major process, (i) number of minor processes off the major process in control and TNF-α-treated microglial cells, and (j) major process thickness. Number of cells analyzed: n=8–18 for the control group, n=20–25 for the Aβ group, and n=12–17 for (TNF-α + Aβ) group. (k) Expression of pro-inflammatory (TNF-α, IL-1β, IL-6) and anti-inflammatory (TGF-β, IL-4, Arg1) genes for control, Aβ-treated and (TNF-α + Aβ)-treated microglial cells. Number of biological replicates, n=3 per group. *: p<0.05, **: p<0.001, ***: p<0.0005, ****: p<0.0001.

Figure 5. Representative SEM images of a multitude of surface topographies in Aβ-associated microglia.

Figure 5.

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(a) Aβ-associated microglia demonstrated a variety of different surface topographies including blebbed, pitted, and ruffled morphologies. Bottom row: high magnification. (b) Representative SEM images of pitted morphology in C20 microglia treated with IL-4 or Aβ. Both IL-4-associated microglia and Aβ-associated microglia showed pits on the surface of the cell body, but the pit size become larger in the Aβ-associated microglia. Bottom row: high magnification.

AD environment is associated with not only the accumulation of Aβ plaques but also the increased level of TNF-α (R. Li, 2004; Perry et al., 2010). Thus, we sought to examine how the ultrastructural morphology of microglia would be altered in the presence of both TNF-α and Aβ. The surface of the cells treated with TNF-α+Aβ appeared to retain a similar appearance to the TNF-α associated microglia rather than Aβ-associated microglia. The majority displayed a highly ruffled (53% of cells analyzed) surface morphology, along with blebbed (24%) or pitted (6%) morphology (Figure 4a). The cell body perimeter of (TNF-α+Aβ)-associated microglia (56.197 ± 14.663 μm, n=12) was significantly larger than the control (33.881± 5.196 μm, n=15, p<0.0001) and Aβ-associated microglia (44.672 ± 12.631 μm, n=22, p<0.01) (Figure 4b). The aspect ratio was significantly larger for (TNF-α+Aβ)-associated microglia than control or Aβ-associated microglia (p<0.0001) (Figure 4c). The length of the major processes for (TNF-α+Aβ)-associated microglia was significantly decreased compared to control microglia (46.941 ± 16.989 μm, n=15 in control microglia to 21.988 ± 16.805 μm, n=17 for (TNF-α + Aβ)-associated microglia, p<0.001) (Figure 4d). The average number of minor processes off the cell body (8.529 ± 5.370 processes n=17) was also significantly decreased compared to both the control (30.462 ± 18.454 processes n=13, p<0.0001) and Aβ-associated microglia (16.444 ± 12.006 processes n=18, p<0.0001) (Figure 4g). The major processes of (TNF-α+Aβ)-associated microglia were significantly thicker than both the control (p<0.0005) and the Aβ-associated microglia (p<0.0001) (Figure 4j). The treatment of Aβ significantly increased the expression of proinflammatory genes such as TNF-α (p<0.01), IL-1β (p<0.05), and IL-6 (p<0.01) in C20 microglia, with no change in anti-inflammatory genes such as TGF-β, IL-4, and Arg1 (Figure 4k). The responses were further increased when the cells were treated with both TNF-α and Aβ compared to Aβ alone. Taken together, our results showed that microglia activated by Aβ displayed drastically reduced the length and number of processes and increased cell body perimeter compared to control microglia, supporting a reported phenotype of an activated microglial cell (Avignone et al., 2015; B. M. Davis et al., 2017; Stence et al., 2001). The combined treatment of TNF-α and Aβ significantly amplified the pro-inflammatory phenotype of microglia, which was accompanied by a further increase in cell body perimeter and major process thickness and a decrease in the number of minor processes off the cell body, compared to Aβ treatment alone.

The proinflammatory cue was associated with microglia processes in direct contact with neighboring cells and the formation of vesicle-like structures.

A previous study suggested that microglia processes repel each other (Nimmerjahn et al., 2005). However, our ultrastructural findings suggest that both the major and minor processes in microglia associated with the proinflammatory cues of TNF-α or Aβ are in direct contact with each other (Figure 6a,b), which appears to involve cell-to-cell communication or cargo trafficking. This phenomenon was not observed in either untreated or IL-4 treated cells, suggesting that this may be linked to proinflammatory conditions. Intriguingly, microglia exposed to either TNF-α or (TNF-α+Aβ) displayed a unique flattened vesicle-like structure in minor processes (Figure 6c), which appeared to be a site of coupling of minor processes between neighboring cells. This phenomenon was also not observed in either untreated or IL-4 treated cells. It is speculated that the structure might play a role in trafficking or clearance mechanisms that are associated with the proinflammatory phenotype of immune cells (A. Chan et al., 2003; Neher et al., 2011; Russo et al., 2014; Stow et al., 2006). Interestingly, these bodies contained vacuole-like components-typically 1 to 3 aggregations within the body, which appeared to be multivesicular bodies with autophagic vacuoles. Cells under nutrient deprivation were shown to form autophagosomes (Ikari et al., 2020; Mejlvang et al., 2018; Mizushima et al., 2004; Takeshige et al., 1992). To further confirm this, we examined whether C20 microglia under serum starvation would form similar vesicle-like structures. The C20 microglia cultured under serum-free conditions displayed vesicle-like structures on the minor processes similar to those seen in TNF-α or (TNF-α+Aβ)-associated microglia (Figure 7), supporting the autophagosomic nature of the vesicle-like structure. Interestingly, (TNF-α+Aβ)-associated microglia displayed areas where multiple vesicle-like structures accumulated together, whereas the structures in TNF-α-associated microglia were mostly in a singular form. The size of the vesicle diameter for (TNF-α+Aβ)-associated microglia (0.57 μm ± 0.11 μm, n=27) was significantly smaller than that for TNF-α-associated microglia (1.14 μm ± 0.28 μm, n=44, p<0.0001) (Figure 6d).

Figure 6. The proinflammatory cue was associated with microglia processes in direct contact with neighboring cells and the formation of vesicle-like structures.

Figure 6.

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(a) The major processes of Aβ-associated microglia have direct interaction with each other through their major processes (denoted by the white arrow). (b) The minor processes off both the cell body and major processes interact with other major and minor processes of adjacent cells in TNF-α-associated microglia (denoted by white arrows). (c) The appearance of vesicle-like structures in the minor processes of TNF-α (left panel) and (TNF-α+Aβ)-associated microglia (right panel). The majority of these structures are localized at the terminal ends for TNF-α-associated microglia (denoted by white arrows), whereas they are distributed throughout the process for (TNF-α+Aβ)-associated microglia (white arrow, right panel). (d) Comparison of the mean diameter of all vesicle-like structures associated with TNF-α-associated and (TNF-α + Aβ)-associated microglia (TNF-α-associated microglia: 1.14 μm ± 0.28 μm, n=44, (TNF-α+Aβ)-associated microglia: 0.57 μm ± 0.11 μm, n=27, p<0.0001). ****: p<0.0001.

Figure 7. The formation of vesicle-like structures in microglia culture on nutrient-deprivation.

Figure 7.

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Culturing microglia in serum-free conditions generated vesicle-like structures on the minor processes (denoted by white arrows), which are suspected to be either multivesicular bodies or autophagosomes, both associated with low nutrient conditions.

Discussion

Despite our increased understanding of the relationship between the change in microglia morphology and the varying status of microglia activation, it has not been fully explored how the varying microglia activation is linked to the alteration of microglia morphology, especially in the microdomain. In this study, using a high-resolution SEM image analysis, we demonstrated that varying status of microglia activation was closely linked to the cellular morphology associated with changes in microdomain such as surface topography and higher-order branching of processes (summarized in Table 2). Our study provides an important insight into the fine details of microglia morphology associated with the varying status of microglia activation.

Table 2.

Summary of the changes in morphological parameters in microglia for varying treatment conditions compared to untreated control.


IL-4 TNF-α Aβ TNF-α + Aβ
Cell body perimeter No change Increase Increase Further increase
Aspect ratio Decrease Increase No change Increase
Major process length Decrease Decrease Decrease Decrease
Number of major process No change No change No change No change
Minor process length off cell body Decrease Decrease Decrease Decrease
Number of minor process off cell body No change No change Decrease Further decrease
Minor process length off major process No change Increase No change No change
Number of minor process off major process Decrease Decrease Decrease Decrease
Major process thickness No change No change No change Increase
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In this study, to characterize morphological phenotypes of microglia, we focused on analyzing morphological parameters of cell shape, surface topography, and processes. Each of these is suspected to have a distinct functional role, which remains relatively unknown despite several hypotheses. A striking difference in microglia morphology observed between anti-inflammatory and proinflammatory cues was the cell shape characterized by aspect ratio. The microglia treated with proinflammatory factor (TNF-α) exhibited an elongated morphology associated with an increase of aspect ratio, while cells treated with anti-inflammatory factor (IL-4) exhibited a more rounded morphology than control cells. Interestingly, the treatment of either anti-inflammatory cytokine or proinflammatory factors was associated with a significant decrease in the length of both major and minor processes, likely a generalized response of process retraction to a stimulus sensed by microglia. For example, C20 microglial cells exposed to anti-inflammatory cytokine (IL-4) did not significantly alter the cell surface topography but were associated with decreases of both major and minor process lengths. Major processes have been suggested to be involved with synaptic modeling, cell-to-cell communication, and chemotactic sensors (Hanisch & Kettenmann, 2007; Tremblay et al., 2010; Wake et al., 2011). Microglia can undergo directed motility while surveilling for cues, where the cell body remains relatively stationary while the processes extend towards biochemical cues (Khurana, 2002; Madry & Attwell, 2015). In our study, microglia activated by TNF-α and Aβ were observed to display one or two lengthy processes towards one direction, while other processes were significantly retracted. Although the highly ramified processes of surveilling cortical microglia observed in vivo are not comparable to those seen in vitro, our observation supports the hypothesis that major processes may play a role in detecting surrounding cues. While the function of the minor processes is unknown, they are believed to be critical for the continuous chemo surveillance of the brain parenchyma (Bernier et al., 2019), which may be a shared role with major processes.

A benefit of SEM cell analysis is the ability to resolve ultrastructural details of cells. Several studies have used TEM to characterize microglia in homeostatic and diseased states (Kitamura et al., 1977; Mori & Leblond, 1969; Savage et al., 2018; Uranova et al., 2020). However, aside from select applications like reconstruction analysis and the fine details that TEM resolves at the organelle level, the use of TEM still has a limitation in analyzing morphological parameters such as surface topography and processes. Utilizing this property of SEM, our results demonstrate that there is discernible cell surface morphology for each treatment condition that can be used to identify a distinctive cellular phenotype. Pores or cavities seen in the control group and IL-4-associated cells were small and homologous across the surface. However, Aβ-associated microglial cells displayed the enlargement of these pores. Although the functional implication for this change in surface morphology remains to be further elucidated, we speculate that this may be associated with the activation of phagocytic pathways. We recently showed that C20 microglia exposed to Aβ could readily phagocytose Aβ aggregates (Dyne et al., 2021). Our results in this study showed that Aβ-associated microglia transitioned into the activated state associated with a larger cell body, retracted minor processes, and observable crevices on the surface when compared to the control group. It has been noted that the enlarged or amoeboid cell body and process retraction is indicative of phagocytic microglia (Bohatschek et al., 2001; Shobin et al., 2017). Microglia analyzed in post-mortem AD brains were shown to migrate towards accumulated Aβ, offering further evidence of the scavenging and prophagocytic nature of activated microglia (Franco-Bocanegra et al., 2019). Previous analysis of microglia using high-resolution microscopy has shown that ‘phagocytic cups’ appear after microglia activation as a result of active interaction with the local environment (Rotterman & Alvarez, 2020). Microglia exposed to Aβ demonstrated a similar surface topography as the TNF-α treated cells; however, there was an appearance of surface blebs that was not observed previously. The combined treatment of TNF-α and Aβ, which may provide a limited model of the AD environment, showed a major transition towards the larger cell body, shorter major processes, and a rougher cell body surface than Aβ alone. Additionally, our results indicate that TNF-α and (TNF-α+Aβ)-associated microglia contain vesicle-like structures on their processes that require further examination. Based on the sizes of the vesicles observed in both treatment groups, it is possible these structures may be autophagosomes, whose vacuole size ranges from a couple hundred nanometers to just over a micrometer (Backues et al., 2014; Jin & Klionsky, 2014), microvesicles (100nm-1μm), or multivesicular bodies (100 – 600nm) (Paolicelli et al., 2019). It is unlikely these are exosomes due to their size exceeding the typical exosome size (20–150nm) (Paolicelli et al., 2019). Multivesicular bodies are required for autophagic clearance of misfolded proteins in neurodegenerative diseases (Lee et al., 2007). C20 microglia cultured without serum, which was shown to form autophagosomes, displayed the formation of similar structures as the vesicle-like structures, further implicating that the structure is likely to be autophagosomes.

One of the limitations of this study was maintaining the native brain environment where in vitro culture of human microglia would alter cellular morphology from the in vivo environment. Literature has shown that serum, among other supplements, alters the morphology of microglia (Liddelow et al., 2017). Depending upon the fixation method, cells may shrink from their normal size in vivo. In vitro microglia can be activated during the isolation process and may not closely reciprocate the behaviors of in vivo microglia (Hurley et al., 1999). Several studies have shown that, transcriptionally, in vitro microglia have different profiles than what is observed in vivo (Butovsky et al., 2014). However, it should be noted that some of our observations from activated microglia are in line with findings from in vivo studies. For example, microglia activated by LPS administration exhibited an increased cell body size in a concentration-dependent manner in vivo (Kozlowski & Weimer, 2012). Jonas et al. (2012) observed that in vivo microglia undergo specific activation patterns associated with process retraction and process thickening (Jonas et al., 2012), which was also observed in our study, particularly in (TNF-α+Aβ)-associated microglia. In our study, all samples included were standardized by using the same fixation protocol, and all data were representative of the baseline environment. Microglia processes are observed to rapidly change (Davalos et al., 2005). Therefore, our study offers a snapshot approach to the microglia, but further exploration into the process dynamics using live two-photon imaging would supplement this study.

In summary, this study provides an important insight into how the ultrastructural morphology of human microglia is altered under varying inflammatory cues. The use of SEM enabled the characterization of microglia morphology in resolving details about microglia ultrastructure that were previously unappreciated. Our study supports that the morphological alterations occurring at a nanoscopic level may exhibit a multitude of phenotypic states. As technology advances and the ability to observe ultrastructural alterations in real-time is enhanced, the findings from this study may be used to correlate morphological changes to functional changes in microglia.

Main Points:

This study characterized the ultrastructural morphology of human microglia under inflammatory cues and revealed that microglial activation is closely linked to the cell surface topography and higher-order branching of processes.

Acknowledgments

This research was supported in part by the National Institutes of Health (3R01NR015674-04S1) and a Kent State BHRI pilot grant. We thank Dr. David Alvarez-Carbonell (Case Western Reserve University, Cleveland, Ohio) for providing the C20 human microglial cell line. We also thank Dr. Min Gao and Dr. Lu Zou for training, maintaining, and providing access to the SEM. The SEM used in this study was conducted at Advanced Materials and Liquid Crystal Institute at Kent State University.

Funding support:

This study was funded by a grant from the National Institute of Health (3R01NR015674-04S1).

Footnotes

Conflict of interest

All authors declare no conflict of interest for this study.

Data Availability

The data sets generated during the current study are available from the corresponding author (M.K.) upon reasonable request.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The data sets generated during the current study are available from the corresponding author (M.K.) upon reasonable request.

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