Nevelchuk et al.
Journal of Neuroinflammation(2024) 21:175
https://doi.org/10.1186/s12974-024-03169-6

Journal of Neuroinflammation

Open Access

RESEARCH

Morphotype‑specific calcium signalingin human microglia
Sofia Nevelchuk1, Bianca Brawek1, Niklas Schwarz2, Ariel Valiente‑Gabioud3, Thomas V. Wuttke2,4,Yury Kovalchuk1, Henner Koch5, Anke Höllig6, Frederik Steiner1, Katherine Figarella1,7, Oliver Griesbeck3 andOlga Garaschuk1*

Abstract
Background Key functions of ­Ca2+ signaling in rodent microglia include monitoring the brain state as well as the sur‑rounding neuronal activity and sensing the danger or damage in their vicinity. Microglial C­ a2+ dyshomeostasis is a dis‑2+ease hallmark in many mouse models of neurological disorders but the ­Ca signal properties of human microglia
remain unknown.
Methods We developed a novel genetically-encoded ratiometric ­Ca2+ indicator, targeting microglial cells
in the freshly resected human tissue, organotypically cultured tissue slices and analyzed in situ ongoing C­ a2+ signalingof decades-old microglia dwelling in their native microenvironment.
Results The data revealed marked compartmentalization of ­Ca2+ signals, with signal properties differing
across the compartments and resident morphotypes. The basal ­Ca2+ levels were low in ramified and high in ameboid
microglia. The fraction of cells with ongoing ­Ca2+ signaling, the fraction and the amplitude of process ­Ca2+ signals
and the duration of somatic C­ a2+ signals decreased when moving from ramified via hypertrophic to ameboid micro‑
glia. In contrast, the size of active compartments, the fraction and amplitude of somatic C­ a2+ signals and the duration2+of process C­ a signals increased along this pathway.
Keywords Human microglia, In vitro human brain tissue model, Native microglial microenvironment, Morphotypesof resident microglia, microRNA-9-assisted labeling*Correspondence:
Olga Garaschukolga.garaschuk@uni-tuebingen.de1
Department of Neurophysiology, Institute of Physiology, Eberhard Karls
University of Tübingen, Keplerstr. 15, 72074 Tübingen, Germany
2
Department of Neurology and Epileptology, Hertie Institute for ClinicalBrain Research, University of Tübingen, Tübingen, Germany
3
Tools for Bio-Imaging, Max-Planck-Institute for Biological Intelligence,
Martinsried, Germany
4
Department of Neurosurgery, University of Tübingen, Tübingen,Germany
5
Department of Epileptology, Neurology, RWTH Aachen University
Hospital, Aachen, Germany
6
Department of Neurosurgery, RWTH Aachen University, Aachen,
Germany
7
Present Address: Department of Anesthesiology, Critical Care and Pain
Medicine, University of Texas Health Science Center at Houston, Houston,
TX, USA

Background
Microglia are the principal immune cells of the central nervous system (CNS), which are implicated in
virtually all physiological (e.g., development, synaptic transmission, plasticity and sleep) and pathological(e.g., traumatic injury, glioma and neurodegenerativeor autoimmune diseases) processes of the CNS [1, 2].
A key aspect of microglial function is the ability tomonitor their microenvironment and detect dyshomeostasis by sensing DAMPs (damage-) or PAMPs(pathogen-associated molecular patterns). For thispurpose, they express a plethora of genes encoding
different membrane receptors, the sum of which isreferred to as microglial sensome [3]. In many cases,
activation of those receptors leads to an increase in the© The Author(s) 2024. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which
permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to theoriginal author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images orother third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line
to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory
regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of thislicence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecom‑mons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Nevelchuk et al. Journal of Neuroinflammation(2024) 21:175

intracellular free C­ a2+ concentration (­[Ca2+]i). Suchtransient changes in ­[Ca2+]i link the sensor and effector functions of microglia by triggering the generation/
release of cytokines and other inflammatory factors(e.g., reactive oxygen species), proliferation, differentiation, migration and phagocytosis [4, 5]. In mice, microglial ­Ca2+ transients are spatially compartmentalized
and located in subcellular domains involved in a given(patho)physiological function. The normal function ofcortical neural networks, for example, is accompanied
by infrequent ­Ca2+ transients in microglial processes,with the frequency of process transients increasing dramatically during neural network hyper- or hypoactivity [6]. Consistently, somatic ­Ca2+ transients are rare
under homeostatic conditions but much more frequent
during (neuro)inflammation, injury or damage [7–11].
Although under homeostatic conditions the mousemicroglial sensome broadly resembles that of humans[12–14], knowledge about the C­ a2+ dynamics of humanmicroglia is scarce and so far restricted to cultured primary microglia (e.g., [15]) or cultured human induced
pluripotent stem cell (iPSC)-derived microglia-likecells (e.g., [16–20]).
Moreover, the morphological appearance of microglia
in the intact human brain is indicative of a higher stateof alertness compared to the mouse microglia [21, 22].
Whereas in mice the vast majority of cortical microglia, for example, show a ramified phenotype, microglia
in the human cortex also appear in a primed, reactive,
or amoeboid morphology. The reason for the dominance of ramified microglia over other morphotypes
in mice remains unclear. This might be due to the specific pathogen-free environment of laboratory animals,
which differs a lot from the typical environment of ahuman individual, or to the fact that the turnover rateof microglia in the human CNS is lower than that in themouse CNS [23, 24]. This discrepancy, however, poses

Page 2 of 18

the question of whether human and mouse microglia
differ in terms of their ­Ca2+ signaling.
To answer this question, we studied the C­ a2+ signalingof human microglia residing in the spare cortical tissue
obtained during glioblastoma/astrocytoma surgery or
hippocampectomy (Table 1). The cells within the sliced
tissue were transduced with lentiviral vectors encoding a
newly developed ratiometric C­ a2+ indicator mCyRFP1CaNeon and the slices were organotypically cultured inhuman cerebrospinal fluid (hCSF). This preparation preserves well the cytoarchitecture and electrophysiologicalproperties of excitatory and inhibitory neurons for several weeks [25, 26].

Materials and methods
Tissue specimen

Organotypic cortical slices were prepared from the cortical tissue, surgically resected to gain access to the pathology (Table 1). Approval (# 772/2021BO2) of the ethics
committee of the University of Tübingen as well as written informed consent was obtained from all patients,
whose resected tissue was used in this study.
Immunohistochemical data shown in Supplementary
Fig. 4 were obtained from the cortical tissue, surgicallyresected to gain access to the pathology, and fixed immediately after resection (Table 2). Approval (EK067/20) of
the ethics committee of the RWTH Aachen University
as well as written informed consent for tissue donation
and approval of the use of human tissue for scientific purposes and all related experimental procedures was collected before the commencement of the study.
Slice preparation and culturing

Slice preparation and culturing were performed as
detailed previously [25, 26]. Briefly, the cortex was
resected, microdissected, and immediately transferred
into the ice-cold artificial cerebrospinal fluid (aCSF) of

Table 1  Tissue used for organotypic slice culturing
Patient no.

Age atsurgery(y)

Sex

Resected brain area

Surgery cause

DIV*

Number of cells analyzed

1

56

F

Left temporal cortex

Glioblastoma, WHO grade IV

9110 (Fig. 1C, D)

2

54

M

Left temporal cortex

Anaplastic astrocytoma, WHO grade III

9

5 (Fig. 2D)
2 (Fig. 2D, 3, 4, 5, S5)

3

45

F

Right temporal cortex

Diffuse astrocytoma, WHO grade II

7–13

17 (Figs. 3, 4, 5, S5)

4

37

M

Right frontal cortex

Astrocytoma, WHO grade III

7–12

4 (Fig. 2D)
11 (Figs. 2D, 3, 4, 5, S5)
14 (Figs. 3, 4, 5, S5)

5

11

F

Right temporal cortex

Hippocampal sclerosis right

7–9

21 (Figs. 3, 4, 5, S5)

6

41

M

Right parietal cortex

Intraventricular glioneuronal tumor (high grade)

7–9

16 (Figs. 3, 4, 5, S5)*DIV days in vitroNevelchuk et al. Journal of Neuroinflammation(2024) 21:175

the following composition (in mM): 110 choline chloride,26 ­NaHCO3, 10 D-glucose, 11.6 Na-ascorbate, 7 M­ gCl2,
3.1 Na-pyruvate, 2.5 KCl, 1.25 ­NaH2PO4, und 0.5 C­ aCl2,pH 7.4, when bubbled with 95% O­ 2, 5% ­CO2. The tissue
was kept submerged in cool and oxygenated aCSF at all
times. Slices (thickness 250–350 µm) were cut using avibratome (Microm HM 650 V, Thermo Fisher ScientificInc, USA) and transferred onto culture membranes forcultivation. For the first hour following the slicing procedure, the slices were cultured in 1.5 ml neural stem cell
media (48% DMEM/F-12 (Life Technologies), 48% Neurobasal (Life Technologies), 1 × N-2 (Capricorn Scientific), 1 × B-27 (Capricorn Scientific), 1 × Glutamax (LifeTechnologies), 1 × NEAA (Life Technologies), 20 mM
HEPES) before changing to 1.5 ml hCSF per well without
any supplements. For transduction with lentiviral vectors, encoding either a combination of 3 different fluorophores (mCherry, mVenus, mTurquoise) or the novel
genetically encoded ­Ca2+ indicator mCyRFP1-CaNeon(see below), 1–2 µl of the respective virus or virus mixture solution was added to the surface of each section
within the first 24 h after resection. Thereafter, the slices
were cultured for 9 ± 1.5 days on culture membranes(uncoated 30 mm Millicell-CM tissue culture inserts with
0.4 mm pores, Merck Millipore, Germany) in six-welldishes (BD Biosciences) each containing 1.5 ml of hCSF.
The dishes were kept in an incubator (Thermo Scientific)
running at 37 °C, 5% C
­ O2 and 100% humidity and hCSF
was replaced every 3 days. When taken out of a six-welldish, each slice was imaged for 3–4 h and then fixed with
4% formaldehyde in PBS as described below.
Human CSF (for ionic composition see ref. [27]) wascollected from lumbar punctures for pressure relief ofpatients with idiopathic intracranial hypertension or
diagnostics of normal pressure hydrocephalus. Written
and informed consent was obtained for every patientunder the approval of the local ethics committee (#772/2021BO2). Thereafter the hCSF was centrifuged at
4 ºC and 2000 g for 10 min, filtered through the sterile
filter (Ø 0.2 μm), the osmolarity (280 ± 20 mOsm/l) was
controlled and the hCSF was frozen at -80 ºC in 10 ml aliquots until further use (for details see [25, 28]).
Novel ­Ca2+ indicator CaNeon

When developing the ultralow affinity C­a2+ sensor
GreenT-EC [29], we also obtained the crystal structureof an intermediate variant named NRS 1.2 (PDB 8COT).
Starting from NRS 1.2 we developed CaNeon via several iterative rounds of optimizations and screenings.
Compared to NRS1.2, CaNeon incorporates the following additional mutations: C159Y, D198G, G248D, S255C,
I258R. These amino acid changes improved the ­Ca2+binding properties of the sensor, as well as its expression

Page 3 of 18

in mammalian cells. The full protein sequence of CaNeon
is displayed in Supplementary Fig. 1A. For designing aratiometric version of the sensor, we used the red fluorescent protein mCyRFP1 as a reference fluorophore.
The spectroscopic properties of mCyRFP1 allow simultaneous one- and two-photon-based excitation of bothmCyRFP1 and CaNeon with an efficient spectral separation of the emission channels [30]. The mCyRFP1 wascloned at the N-terminus of CaNeon using a 20 aminoacid-long flexible hydrophobic linker (GGTGGSGSSGGSLEVLFQGP, Fig. 2A). All cloning steps were done using
the homology-based SliCE method [31]. In the absenceof ­Ca2+, the fluorescence of CaNeon is low (Supplementary Fig. 1B). The binding of ­Ca2+ ions causes conformational changes in CaNeon, resulting in a strong increasein fluorescence. The spectroscopic in vitro properties of
CaNeon and the fusion protein mCyRFP1-CaNeon aresummarized in Supplementary Fig. 1D.
Protein purification and biophysical characterizationof CaNeon

His-tagged proteins were expressed in E.coli BL21 (Invitrogen) overnight at 37 °C in 50 mL auto-inductive
Luria–Bertani medium, supplemented with 0.05%
D-( +)- glucose (w/v), 0.2% lactose (w/v), 0.6% glycerol(v/v). Bacteria were harvested by centrifugation (4 °C,
10 min, 6000 g) and re-suspended in 10 mL resuspension buffer (20 mM N
­ a2PO4, 300 mM NaCl, 20 mM
imidazole; Sigma Aldrich) supplemented with proteaseinhibitors (4 μM PMSF, 20 μg/mL Pepstatin A, 4 μg/
mL Leupeptin; Sigma Aldrich), 5 μg/mL DNase and10 μg/mL RNase (Sigma Aldrich). Resuspended bacteria
were lysed through sonication on ice for 7 min (80% of
the time on; Bandelin Sonoplus). Insoluble components
were removed through centrifugation (4 °C, 30 min at
20,000 g). The supernatant was incubated with 150 μL
6% (v/v) Nickel-IDA agarose bead suspension (Jena Bioscience) for 1 h at 4 °C under mild agitation. Agarose
beads were collected in 1 mL propylene gravity flow columns (Qiagen) and washed with 10 mL resuspension
buffer. The proteins were collected using 800 μL elution
buffer (20 mM N
­ a2PO4, 300 mM NaCl, 300 mM imidazole; Sigma Aldrich) and dialyzed against MOPS buffer(30 mM MOPS (3-morpholinopropane-1-sulfonic acid),
100 mM KCl, pH 7.2) for further measurements.
The ratio change (ΔR/R0) of purified mCyRFP1CaNeon was determined by measuring the fluorescenceat 520 and 650 nm upon excitation at 488 nm in MOPS
buffer supplemented with 10 mM EGTA or 0.2 mM C
­ a2+
(Supplementary Fig. 1D). The molar extinction coefficients (EC) were determined via quantifying protein
concentrations using the absorption of the denatured
chromophore at 452 nm (with an EC of 44 ­mM−1 ­cm−1).

Nevelchuk et al. Journal of Neuroinflammation(2024) 21:175

Proteins were prepared in MOPS buffer supplemented
with 0.2 mM C
­ aCl2 and the absorbance spectrum was
acquired before and after the addition of NaOH to a final
concentration of 0.1 M. The quantum yield of CaNeon in
mCyRFP1-CaNeon was determined relative to mNeonGreen using the slope method, measuring the absorbanceand emission spectra of serial dilution of the proteins.
For the quantum yield and extinction coefficient measurements, the formation of CyRFP1 chromophore wasprevented by incorporating the mutation Y68C. This
allowed us to determine the structural effect of the N-terminal tag on CaNeon without the spectral interferenceof mCyRFP1. The brightness was calculated as extinction
coefficient ˣ quantum yield.
The ­Ca2+ affinity of the sensors was determined using
MOPS buffer supplemented with 10 mM EGTA and
1 mM ­Mg2+ by increasing concentrations of C
­ a2+ aspreviously described [31, 32]. The dissociation constant(Kd) values were determined by plotting the log10 valuesof the free ­Ca2+ concentrations against the corresponding ΔF/F0 or ΔR/R0 values (normalized to the response at
39.8 μM ­Ca2+) and fitting a sigmoidal curve to the plot.
The kinetic rates of the ­Ca2+ indicators were measured
in a Varian Cary Eclipse fluorescence spectrophotometer
fitted with an Applied Photophysics RX pneumatic drive
unit. For obtaining the macroscopic off-rate constant­(Koff), two stock solutions were prepared as follows: a­Ca2+-saturated indicator solution (30 mM MOPS, 1 mM
­CaCl2, 2 mM ­MgCl2, 100 mM KCl, ∼ 0.2–1 μM indicator,
pH 7.2) and a BAPTA solution (30 mM MOPS, 100 mM
KCl, 20 mM BAPTA, pH 7.2). The stopped-flow experiment was carried out at room temperature (∼23 °C) andthe two solutions were mixed with an injection pressure of 3.5 bar. Excitation was set to 480 nm and emission was detected at 520 nm. The decay time (τ, s) was
determined by fitting a double-exponential curve to thefluorescence response using GraphPad Prism version
9.5.1 for Windows (GraphPad Software). Macroscopic
on-rate kinetics (­Kobs) were obtained both for CaNeon
and mCyRFP1-CaNeon by mixing the ­Ca2+-free buffer
containing the protein (30 mM MOPS, 100 mM KCl,
1 mM ­MgCl2, 10 mM EGTA, ∼ 0.2–1 μM indicator, pH
7.2) and solutions containing increasing concentrationsof ­CaCl2 (30 mM MOPS, 100 mM KCl, 8–20 mM ­CaCl2,
1 mM ­MgCl2, 10 mM EGTA, ∼ 0.2–1 μM indicator, pH
7.2). Concentrations of free ­Ca2+ were calculated using
WEBMAXC STANDARD.
For measuring the pKa of the sensors a series of MOPS/MES (2-N-morpholino-ethane sulfonic acid) buffered
solutions, supplemented with 1 mM C
­ a2+, were prepared.
The pH values were adjusted in 0.5 pH steps from pH
5.5 to pH 8.5 using NaOH and HCl. In a bottom 96 wellplate, triplicates of 200 μl of buffer containing 0.5–1 μM

Page 4 of 18

of protein were prepared for each pH value and all emission spectra were recorded. The relative fluorescence values at the emission maximum were plotted against thepH values and a sigmoidal fit was applied.
Creation of the viral vector carrying mCyRFP1‑CaNeon

We used the LV.Twitch-2B.miR-9.T construct containing
the cytomegalovirus (CMV) promoter and four microRNA-9 target sequences [10] as the parental vector to
produce the LV. mCyRFP1-CaNeon.miR-9.T. We replaced
Twitch-2B with mCyRFP1-CaNeon using a homologous recombination-based assembly molecular cloning
approach. For this purpose, we propagated mCyRFP1CaNeon by PCR amplification from a donor vector
using primers that contain both mCyRFP1-CaNeon specific sequences and the flanking regions (15 nucleotidesin length) located exactly up- and down-stream of theTwitch-2B sequence in the parenteral vector (forward
primer: 5ʹ-CTC​TAC​TAG​AGG​ATC​CGC​CAC​CAT​GGT​
GAG​CAA​GGG​C-3ʹ, reverse primer: 5ʹ-GAG​GTT​GAT​TGT​C GA​C TC​AGT​G GT​ATT​TGT​GAG​C CA​G GG-3ʹ).
The PCR product was digested with Dpn I, affinity-purified, and reserved for assembly molecular cloning. Then,the parental vector LV.Twitch-2B.miR-9.T was digested
with the restriction enzymes BamH I and Sal I to remove
the Twitch-2B sequence. The homologous recombination reaction was performed at a 1:2 ratio with 200 ng of
the digested parenteral vector using the NEBuilder® HiFi
DNA Assembly Cloning Kit from New England BioLabs.
Production of microRNA‑9‑regulated lentiviral vectors

MicroRNA-9 (miR-9) is a microRNA that promotes thedegradation of mRNA with a specific complementary
sequence. Because in mice miR-9 is expressed in virtually all CNS cells except microglia, it can be used forcell type-specific labeling of microglia [10, 33, 34]. This
cell type specificity, however, relies on the interaction
between the endogenous miR-9 and the exogenous substrate and thus can be overridden, if the concentration ofexogenous mRNA is high or the concentration of endogenous miR-9 is low.
Production of miR9-regulated lentiviral vectors was
described previously [34, 35]. In brief, cell-free supernatants containing viral particles were produced by transient transfection of HEK293T packaging cells with therespective lentiviral construct along with the packing
plasmids psPAX2 and pMD2G, following standard procedures. After 48 h the virus-containing culture supernatant was collected, filtered through a 0.45 µm pore-sized
filter to remove cell debris and concentrated by centrifugation at 100,000 g for 2 h at 4 °C (Thermofisher WX

Nevelchuk et al. Journal of Neuroinflammation(2024) 21:175

Ultra80 centrifuge, Waltham, MA, USA). Pellets were
resuspended in sterile PBS and stored at − 80 °C.
Four different miR-9-regulated lentiviral constructs
were used in this study. Constructs containing the PGK
promotor (Fig. 1B) enabled the expression of 3 different
fluorophores (mCherry, Venus, or mTurquoise2) and thestochastic combination thereof [34]. The LV.mCyRFP1CaNeon.miR-9.T construct contained a CMV promotor

Page 5 of 18(Fig. 2C) and was used to label human microglia with aratiometric ­Ca2+ indicator mCyRFP1-CaNeon. For thisstudy, viral suspensions with 2.5–4 × ­108 virus particles
per ml were used.
Two‑photon imaging

Two-photon imaging was performed using a laser scanning microscope (Olympus Fluoview 1000 or Olympus

Fig. 1 miR-9-assisted labeling of human microglia. A Schematics illustrating preparation, culturing and RGB labeling of human organotypic brainslices. B Scheme of the miR-9-regulated viral constructs inducing expression of mCherry (red), mVenus (green) and mTurquoise (blue) in microglia. C
Maximum intensity projection (MIP) images (2–20 µm depth, here and below step size 1 µm) showing RGB-labeled human microglia in organotypicslices. D Pie chart showing the fractions of different colors in the RGB-labeled microglial population (n = 110 cells)

Nevelchuk et al. Journal of Neuroinflammation(2024) 21:175

Page 6 of 18

Fig. 2 Functional properties of the new ratiometric ­Ca2+ sensor mCyRFP1-CaNeon. A Schematics of the sensor design (see Materials and methods
for details). B The excitation and emission spectra of purified mCyRFP1 (red) and CaNeon (green). Note that the excitation spectra show significant
overlap, enabling the efficient one-photon excitation of the fluorophore by a single light source, and the emission spectra can be well separated.
C Scheme of the miR-9-regulated viral construct for expressing mCyRFP1-CaNeon in in situ microglia. D Sample ­Ca2+ transients (lower panel)
evoked by pressure application (12 psi, 200 ms) of 5 mM ATP (dissolved in the standard pipette solution: 150 mM NaCl, 2.5 mM KCl, 10 mM HEPES,
pH 7.4) to a mCyRFP1-CaNeon-expressing cell (upper panel). E MIP (6–16 µm depth) image of a fixed organotypic slice, labeled with antibodies
against a microglia/macrophage marker Iba-1 (green) and mCyRFP1-CaNeon (red). F Box plot showing the fraction of double-positive cells
among the cells, positive for mCyRFP1-CaNeon (n = 254 mCyRFP1-CaNeon -positive cells, 41 FOVs)Nevelchuk et al. Journal of Neuroinflammation(2024) 21:175

Fluoview 300, Olympus, Tokyo, Japan) equipped with a
40 × water-immersion objective (0.80 NA, Nikon, Tokyo,
Japan) and coupled to a tunable titanium-sapphire laser(690–1040 nm excitation wavelength; MaiTai DeepSee,
Spectra Physics, Santa Clara, CA, USA). During imaging the human slices were continuously perfused with
Ringer’s solution (125 mM NaCl, 4.5 mM KCl, 26 mM­NaHCO3, 1.25 mM N
­ aH2PO4, 2.5 mM C
­ aCl2, 1 mM
­MgCl2, and 20 mM glucose) at 32 °C and pH 7.4, whenbubbled with 95% ­O2 and 5% ­CO2.
mTurquoise and mCherry were excited at 800 nm
and mVenus at 990 nm. The emitted light was split by a
570 nm dichroic mirror and filtered with SP 570 nm or
BP 630/92 nm, respectively. mCyRFP1-CaNeon was
excited at 930 nm and a 570 nm dichroic mirror was utilized to split the emitted light into two separate channels
for CaNeon (SP 570 nm) and mCyRFP1 (BP 630/92 nm),respectively. Microglial C­ a2+ transients were recorded
from cells located 3–60 µm below the surface of the slice
in 4D for 15 min with a resolution of 0.31 μm/pixel in the
XY plane, Z step size of 2 µm and a sampling rate of 2 μs/
pixel (0.3 to 0.5 Hz). 3D stacks were acquired at a spatial
resolution of 0.31 μm/pixel and a Z step size of 1–2 μm.
Microglial morphotypes were defined based on visualinspection of high-resolution cell images using wellestablished morphological criteria [21, 36–38]. Cells withsmall cell bodies with long, thin, and highly branchedprocesses were considered ramified, cells with enlarged
cell bodies and thick, sparsely branched processes wereconsidered hypertrophic, and cells with rounded cellbodies, few very short or no processes were consideredameboid (see Fig. 3A, Supplementary Fig. 4A, B).
Ca2+ signal detection and analyses

Ca2+ signals were detected using the active voxels detection algorithm of the MATLAB (MathWorks) Begonia
framework [39]. Within this framework, the fluorescencevalue F of each pixel is converted into a binary timeseries, where pixels with values other than 0 represent
events (Supplementary Fig. 2A). These events correspondto pixel grayscale values that exceed a user-determinedthreshold τi , which is a function of the baseline grayscalevalues and the standard deviation of noise:τi = µi + κ · σiwhere κ is an empirically obtained coefficient that determines the height of the threshold, µi is the baseline valueof fluorescence for each pixel, and σi is the standard deviation of noise [39]. Depending on the image quality andthe fluorescence intensity of CaNeon, κ values between
4 and 5 were chosen. The binary matrix of active pixels(Supplementary Fig. 2B) was then exported from MATLAB and further analyses were performed using a Python

Page 7 of 18

routine [40]. A map of all active pixels was obtained bysumming up all time points that contain active pixels
along the t-axis. As the value of active pixels is 1 andthe value of inactive pixels is 0, the resulting image consists of the non-zero pixels that were active at any given
point during the recording. Next, the active pixels weregrouped into separate regions by connecting an active
pixel to its immediate horizontal and vertical active
neighbors. This procedure resulted in separate localized
regions of activity (ROAs) that did not overlap in space
throughout the entire registration (e.g., Fig. 4A).
To understand whether the given ROA was localized tothe (i) soma, (ii) process or (iii) covered both soma andprocesses, the somatic area was identified by applying the
Otsu threshold [41], which works by analyzing the histogram of pixel intensities in the averaged cell image andautomatically selecting a threshold value that minimizes
the variance within the two resulting groups: foreground(cell soma) and background (Supplementary Fig. 2C).
Next, the somatic area determined in this way was overlayed with the ROA of interest to determine whether(i) the ROA is located within the somatic area (somatic
ROA), (ii) outside the somatic area (process ROA) or (iii)
covers the somatic area and largely extends beyond it(soma and process ROA; e.g., cyan ROA in Supplementary Fig. 2D).
Then, for both CaNeon and mCyRFP1 fluorescence,a mean intensity value for every frame in the area corresponding to each previously obtained ROA was calculated. The background-subtracted fluorescence ratio
and the relative ratio change (ΔR/R) were calculated asfollows:
R = (FCaNeon − BCaNeon )/ FmCyRFP1 − BmCyRFP1

�R/R0 = (R − R0 )/R0
where the background fluorescence (B) for both channels was calculated as the mean intensity of a 10 × 10 pixels region located outside the analyzed cell and ­R0 is thebaseline value of R. The baseline was approximated witha third-order weighted polynomial function. The peaks of
ΔR/R traces were detected by utilizing the Python scipysignal module [42]. Only those peaks that exceeded the
4 × σnoise threshold were considered.
Immunohistochemistry

After imaging experiments, human organotypic slices
were fixed with 4% formaldehyde in PBS for 2 h at 4 °C,
washed in PBS, and permeabilized using 0.25% Triton
X in PBS for 15 min. Antibody staining was performed
with free-floating slices at room temperature. Slices weretreated with a blocking solution (5% normal goat serum,Nevelchuk et al. Journal of Neuroinflammation(2024) 21:175

Page 8 of 18

A
Ramified

Cell 1

Cell 2
10 µm

Cell 350 s

Hypertrophic

Cell 1

Cell 2
10 µm
Cell 350 s

Ameboid

Cell 1
Cell 2
10 µm
Cell 350 s

B

C
Active cells

Fraction of active cells

Median baseline ratio

5

d
hic
oid
fie
mi rtrop meb
a
R
A
pe
Hy

ns

4

ns

3
2
1

0

ifie

m
Ra

d
p

Hy

hic

op

tr
er

oid

eb

Am

2+

Fig. 3 Ongoing ­Ca signaling in microglia of different morphology. A MIP images showing examples of mCyRFP1-CaNeon-positive microglia
with ramified, hypertrophic, and amoeboid morphology (left; 8–32 µm, 7–30 µm, and 3–16 µm depth, respectively) as well as whole-cell ΔR/R
traces, recorded from these (Cell 1 of each morphotype) as well as other cells during an ~ 15-min-long recording period (right). B Bar graphsummarizing the fractions of active cells of different morphologies (n = 38 ramified, 25 hypertrophic and 18 ameboid microglia). C Box plot
illustrating the distributions of the median (per cell) basal ratios of ramified, hypertrophic and ameboid microglia (P = 1.2*10–2 for comparison
between ramified and ameboid microglia, Kruskal–Wallis test; n = 31, 20, 5 active cells, respectively)

3% bovine serum albumin (BSA) and 1% Triton X-100
in PBS) for one hour and incubated overnight with theprimary antibodies (rabbit-anti-Iba-1, 1:200; Wako, USA;
rat-anti-mCherry, 1:2000, Thermo Fisher Scientific).
After washing in PBS, the slices were incubated with

Alexa Fluor (AF) 488- and AF-594-conjugated secondary antibodies (1:1000, Invitrogen, Waltham, MA, USA)for 2 h in darkness and later mounted on fluorescencefree Superfrost Plus microscope slides (Langenbrinck,
Emmendingen, Germany) with Vectashield Mounting

Nevelchuk et al. Journal of Neuroinflammation(2024) 21:175

Medium (Vector Laboratories, Burlingame, CA, USA).
Freshly resected cortical samples (Table 2) were fixed in
4% paraformaldehyde for 1 h at 4 °C and subsequently
washed 3 × 15 min in PBS. The slices were transferred
to a 15% sucrose solution for 90 min and then incubatedin a 30% sucrose solution overnight. After washing theslices 3 × 15 min in PBS, they were incubated for 2 days
at 4 °C with the rabbit-anti-Iba-1 antibody (1:1000, Wako,
USA). After washing with PBS, the slices were incubatedfor 24 h at 4 °C with Alexa Fluor 488 secondary antibody(1:750, Thermo Fisher Scientific). Finally, the slices were
washed with PBS and mounted using Fluoromount-G(Thermo Fisher Scientific).
For immunolabeling of cortical slices of NG2-DsRed
transgenic mice (Tg(Cspg4-DsRed.T1)1Akik/J), we used
the brain tissue from our biobank, which was previously
isolated and fixed with 4% formaldehyde in PBS for 2 h
at 4 °C, cryoprotected in 25% sucrose in PBS overnightat 4 °C, embedded in Tissue Tek (Sakura Finetek, Torrance, CA, USA) and stored at -80 °C. Antibody staining
was performed with free-floating 50-μm-thick coronal
sections at room temperature. The sections were rinsed
in PBS, blocked in 1% bovine serum albumin (BSA)
containing 0.3% Triton X-100 in PBS for 1 h at room
temperature, followed by incubation with primary antibodies (rabbit-anti RFP, Rockland, 1:1500 and goat antiPDGFRα, R&D Systems, 1:500) in 1% BSA, 0.1% Triton
X-100 in PBS overnight. After washing in PBS, the slices
were incubated with Alexa Fluor (AF) 488- and AF594-conjugated secondary antibodies (1:1000, Invitrogen, Waltham, MA, USA) for 2 h in darkness; and later
mounted on fluorescence-free Superfrost Plus microscope slides (Langenbrinck, Emmendingen, Germany)with Vectashield Mounting Medium (Vector Laboratories, Burlingame, CA, USA).
Analyses of cell density, the distance to the nearest
neighbor and the soma size

The "Spots" feature of the Imaris software (version
10.1.1; Bitplane, Oxford Instruments) was employed todetect and mark individual cells within 3D image stacks.

Page 9 of 18

Intensity thresholds were manually adjusted to ensure
accurate detection of Iba-1-labeled microglia. Following
cell identification, the statistics feature of Imaris was utilized to extract the distance to the nearest neighbors foreach detected cell and the total number of cells. Cell density was then calculated by dividing the total number ofcells by the stack volume.
For the reconstruction of microglial somata, cell bodies
were manually identified and the surface creation feature
with manual adjustment of thresholds was used to delineate the boundaries of microglial somata. Morphological and intensity segmentation features were employed
to exclude adjacent extracellular components (e.g. lipofuscin grains). Cells were only included in the analyses
if a clear separation from the surrounding extracellularmaterial was possible. Following reconstruction, several
parameters including 3 bounding box dimensions (i.e.
cell diameters in X, Y, Z), the surface area and volume aswell as sphericity were extracted from Imaris software.
Statistical analyses and data presentation

Statistical tests were performed in Python using the Scipy
library. The one-sample Shapiro–Wilk test was used totest for the normality of the data distribution and theLevene’s test was used to test for homoscedasticity. Comparisons of more than two independent variables were
performed using the Kruskal–Wallis test followed by theHolm-Bonferroni post hoc test for multiple comparisons.
All statistical tests were two-sided. The P values ≤ 0.05
were considered significant. If not otherwise indicated,data is presented as median ± interquartile range. Lines ofboxes in box plots represent 25th and 75th, and whiskers
10th and 90th percentiles.

Results

New genetically encoded indicator for ­Ca2+ imaging
in human microglia

To extend the methodology, previously developed for
mice, to human tissue, we first transduced the organotypic cortical slices (Fig. 1A) with the 1:1:1 mixture of
miR9-regulated lentiviral vectors encoding mCherry(See figure on next page.)
Fig. 4 Subcellular compartmentalization of ROAs in human microglia. A Left: 4D average intensity projection (24 µm depth)of a mCyRFP1-CaNeon-expressing ramified microglial cell alone (upper panel) and with the overlayed sample ROAs, shown in different colors (lower
panel). Right: spontaneous ongoing ­Ca2+ signals (asterisks) recorded from ROAs, labeled with the respective number in the lower left panel. B Piecharts showing the spatial distribution of ROAs in ramified (left panel), hypertrophic (middle panel), and amoeboid (right panel) microglia. C Box
plots showing the morphotype-specific distributions of ROA areas. ROAs were significantly smaller in ramified compared to amoeboid microglia(P = ­10–3; here and below: the Kruskal–Wallis test followed by the Holm-Bonferroni post hoc test for multiple comparisons). D Box plots illustrating
the frequencies per cell of ­Ca2+ transients in ramified, hypertrophic and ameboid microglia (n = 31, 20, 5 cells, respectively). E Schematic, defining
the parameters of ­Ca2+ transients analyzed in this study. F–H Box plots showing amplitudes (F; P = 3.4*10–4 and 0.02 for comparison of ramified
to hypertrophic and hypertrophic to ameboid microglia, respectively), FWHM (G; P = 8.7*10–3 for comparison of ramified to hypertrophic microglia)
and AUC (H; P = 3.3*10–3 for comparison of ramified to hypertrophic microglia) of ­Ca2+ transients for microglia of different morphologies

Nevelchuk et al. Journal of Neuroinflammation

Fig. 4 (See legend on previous page.)(2024) 21:175

Page 10 of 18

Nevelchuk et al. Journal of Neuroinflammation(2024) 21:175(red = R), mVenus (green = G), and mTurquoise2(blue = B) by adding 1–2 µl of the virus mixture (Fig. 1B)to the surface of brain slices during culturing. Because of
the high endogenous activity of miR9 in most brain cells
except microglia, this approach favors the specific labeling of microglial cells [33, 34]. As shown in Fig. 1C, thisprotocol resulted in strong labeling of cells with microglia-like morphology. Due to the stochastic nature of viraltransduction, individual cells expressed either one of thethree fluorophores or any combination thereof (Fig. 1C
and D).
Next, we set out to develop an indicator suited forassessing the [­Ca2+]i in human microglia. We opted fora ratiometric red/green indicator (Fig. 2A), which is lesssensitive to movement artifacts and thus facilitates theidentification of thin mobile processes, and engineered it
to enable simultaneous fluorophore excitation in single(Fig. 2B; excitation wavelength 488 nm) and two-photon
modes.
Thus, we first constructed CaNeon, a non-ratiometric­Ca2+ indicator consisting of the yellow-green fluorescentprotein mNeonGreen [43] and a minimal ­Ca2+ binding
domain derived from Troponin C (TnCmin) with only
2 ­Ca2+ binding sites (versus 4 in GCaMPs), thus lowering the buffer capacity of the indicator (Supplementary
Fig. 1A–D). We started from GreenT-EC, which is tuned
to monitor ­Ca2+ levels in interstitial fluids [29], andderived a variant that binds ­Ca2+ with high affinity while
retaining large fractional fluorescence changes (Supplementary Fig. 1). We then conjugated this indicator to
the red fluorescent protein mCyRFP1 [30] (Fig. 2A). For
benchmarking, the spectroscopic in vitro properties of
CaNeon and mCyRFP1-CaNeon were compared to theestablished ­Ca2+ sensor GCaMP6f [44]. The extinction
coefficient, quantum yield and ­Ca2+ sensitivity of bothindicators (Supplementary Fig. 1D) were similar to thatof GCaMP6f but with better linearity (Hill coefficient
1.5–1.6 instead of 2.3).
Taking into account our previous experience in mice[10], when preparing miR9-regulated lentiviral vectors
encoding mCyRFP1-CaNeon we switched to a stronger
promotor (CMV instead of PGK; Fig. 2C vs. Fig. 1B).
From such a vector, the sensor expressed well both in
Human Embryonic Kidney (HEK) 293 cells in culture(Supplementary Fig. 1E–H) and human cortical microglia in organotypic slices (Fig. 2D–F). For initial testingof the new construct, HEK 293 cells were stimulated bya bath application of caffeine (Supplementary Fig. 1F–H),
an agonist of ryanodine receptors releasing ­Ca2+ fromthe intracellular C­ a2+ stores [45], and microglia – by alocal pressure application (250 ms, 12 psi) of the purinergic receptor agonist ATP (Fig. 2D), resulting in both casesin large ­Ca2+ transients.

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The specificity of the miR9-regulated microglial labeling was assessed in fixed organotypic slices, labeledwith antibodies against a microglia/macrophage-specificmarker Ionized ­Ca2+-binding adaptor molecule 1 (Iba-1)
and mCherry, because mCherry has 63% homology withmCyRFP1 and 33% homology with CaNeon, thus enabling good visualization of mCyRFP1-CaNeon (Fig. 2E).
In fixed tissue, the native fluorescence of CaNeon was
too low to be visible in the green channel. Our transfection protocol (1:1000 virus dilution in hCSF) enabled
the expression of mCyRFP1-CaNeon in 52.38 ± 0.9%
(mean ± SEM) of Iba-1-positive cells (316 cells/23 fields ofview (FOVs)), while 91.67 ± 32.29% (254 cells/41 FOVs) ofmCyRFP1-CaNeon-positive cells were also Iba-1-positive(Fig. 2F). In contrast to our previous experiments in mice[10], in the human brain we did identify another weaklylabeled Iba-1-negative population of spindle-shaped cells,
often associated with blood vessels (presumed pericytes,
arrows in Fig. 2E and Supplementary Fig. 3). The latter,
however, were dim and therefore hardly visible in situ
and were morphologically too different to be mistaken
for microglia. These cells were excluded from further
analyses.
Taken together, the novel technique described above
enables real-time morphological and functional analysesof human microglia, including longitudinal analyses ofprocess/cell body motility (Supplementary Movie 1) as
well as ­Ca2+ imaging.
Morphotype‑specific properties of microglial ­Ca2+ signals

In contrast to the mouse cerebral cortex, in which underhomeostatic conditions more than 90% of microglia haveramified morphology, in the human postmortem cortex
microglial cells appear much more heterogeneous, with
only half of the population showing ramified morphology and another half being composed of hypertrophic(also called reactive; 32%) and ameboid (18%) cells [21].
Consistently, out of 81 cells analyzed in this study, 46.91%
were ramified, 30.86% hypertrophic and 22.22% ameboid(Fig. 3A). All 3 microglial morphotypes were also present
in freshly resected human cortical tissue (Supplementary Fig. 4). Although at the first glance the density of
microglia, the median distance to the nearest neighbor,the mean cell diameter and the soma shape in freshly
resected and organotypically cultured slices looked similar, a detailed examination revealed significant differences between the two groups for all but last parameters(Supplementary Fig. 4). Besides, the parameters related
to cell diameter (the cell surface area and cell volume)
also differed between the groups (Mann–Whitney Test,
P < ­10–4 for both comparisons). The median distanceto the nearest neighbor was 30.5 for acute and 45.2 forNevelchuk et al. Journal of Neuroinflammation(2024) 21:175

cultured slices, with the latter being much closer to thein vivo mouse data (~ 50 µm, [46]). This is surprising, as
the density of microglia was reported to be higher in themouse compared to the human cortex [24].
Different morphotypes differed in terms of their ­Ca2+
signaling. Like their mouse counterparts in vivo [7, 8],
human microglia in organotypic slices showed ongoing­Ca2+ signaling (Fig. 3A). While the fractions of active
cells (showing at least one ­Ca2+ transient at any subcellular location during the 15-min-long recording period)
were approximately similar among ramified and hypertrophic microglia (Fig. 3B), the patterns of C
­ a2+ transients sampled over the entire cell looked different, withan increase in the amplitude and/or frequency of thesetransients from ramified to ameboid microglia and a significant reduction in the fraction of active cells for ameboid microglia (Fig. 3A-B; P = 3*10–4, Chi-squared test).
Moreover, the median basal ratios (proportional to thebasal ­[Ca2+]i) of active cells increased gradually fromramified through hypertrophic to ameboid cells, with thedifference between the ramified and ameboid cells reaching the level of statistical significance (Fig. 3C; P = 1.2*10–
2, Kruskal–Wallis test). In 3 hypertrophic and 1 ameboid
cell, ongoing C­ a2+ transients showed oscillatory behavior(e.g., ameboid Cell 1 in Fig. 3A) with a median frequencyof 12.33*10–3 ­s−1. In 4 recorded cells the microglial processes formed structures, reminiscent of phagocytic
cups, with cups often showing compartmentalized ­Ca2+
transients (Supplementary Movie 2). Although we did
not observe any somatic movements over a 15-min-longrecording period, many ramified and hypertrophic cells
showed vivid process motility, also often associated withcompartmentalized ­Ca2+ transients (Supplementary
Movie 1).
Therefore, the subsequent analyses of ­Ca2+ signaling were conducted based on active subcellular compartments (regions of activity, ROA) using the Begonia
ROA detection algorithm [39]; see Materials and methods for details). On average, individual microglial cells
contained 2.53 ± 0.35 (mean ± SEM; n = 56 cells) active

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subcellular compartments, some of which are exemplified in Fig. 4A. Out of 78 ROA detected in ramified cells,
75.6% were localized to the processes, 11.5% covered
soma and processes and 12.8% covered cell somata only
(Fig. 4B). Surprisingly, we have rarely observed global­Ca2+ signals invading the entire cell. The spatial distribution of ­Ca2+ signals in hypertrophic cells was similar tothat in ramified microglia (P = 0.31, Chi-squared test). In
ameboid cells, however, the spatial pattern of C
­ a2+ signals was entirely different, with 66.7% of ROA localized
to cell somata (P < ­10–3, Chi-squared test). Consistently,
the areas of individual ROAs were small in ramified,somewhat larger and heterogeneous in hypertrophic
and significantly larger in ameboid cells (P = 2.3*10–3,
Kruskal–Wallis test; Fig. 4C), whereas the morphotypespecific frequencies of ongoing ­Ca2+ signals were similar(Fig. 4D). Next, we characterized the properties of ­Ca2+
transients derived from different ROA in the 3 morphotypes (Fig. 4E–H). The median amplitudes of ­Ca2+
transients were significantly smaller in hypertrophic,
compared to ramified and ameboid, microglia (Fig. 4F).
The durations (full width at half maximum, FWHM)
were larger and the total C­ a2+ load (area under the curve,
AUC) was smaller in hypertrophic compared to ramified
cells (Fig. 4G, H).
Detailed analyses of individual ­C a2+ transients
revealed that although the majority of ROAs in ameboid cells were located in cell somata (Fig. 4B), thesoma and process ROAs showed many more ­Ca2+transients (Fig. 5A). Moreover, for ramified and hypertrophic morphotypes process ­C a2+ transients had thehighest amplitudes and AUCs, whereas their durations varied between the morphotypes (Supplementary Fig. 5). In ramified microglia, the durations ofprocess ­C a2+ transients were the shortest (Supplementary Fig. 5B), whereas in hypertrophic and ameboid
microglia the durations of ­C a2+ transients localized tosoma and processes became gradually longer than thatof somatic C­ a2+ transients, reaching the level of significance in ameboid microglia (Supplementary Fig. 5E(See figure on next page.)
Fig. 5 Characteristics of microglial ­Ca2+ transients in different subcompartments. A Pie charts showing the distribution of ­Ca2+ transientsamong different subcompartments in ramified (left panel), hypertrophic (middle panel), and amoeboid (right panel) human microglia. B–D
Box plots comparing amplitude (B; P = 6*10–3 for comparison of hypertrophic to ameboid microglia (here and below: the Kruskal–Wallis test
followed by the Holm-Bonferroni post hoc test for multiple comparisons)), FWHM (C; 1.4*10–3 and 0.01 for comparison of ramified to ameboid
and hypertrophic to ameboid microglia, respectively), and AUC (D; P = 0.03 and 2.2*10–4 for comparison of ramified to ameboid and ramified
to hypertrophic microglia, respectively) of somatic ­Ca2+ transients in ramified, hypertrophic and amoeboid microglia. E–G Box plots comparing
amplitude (E; P = 4.8*10–5, 2.1*10–6 and 4.6*10–7 for comparison of ramified to hypertrophic, ramified to ameboid and hypertrophic to ameboid
microglia, respectively), FWHM (F; P = 0.01 for comparison of hypertrophic to ameboid microglia), and AUC (G; P = 3.7*10–2, 4.4*10–6 and 1.8*10–8
for comparison of ramified to hypertrophic, ramified to ameboid and hypertrophic to ameboid microglia, respectively) of ­Ca2+ transients in soma
and processes of ramified, hypertrophic and amoeboid microglia. H–J Box plots comparing amplitude (H; P = 3.1*10–5), FWHM (I; P = 1.3*10–3),
and AUC (J; P = 0.02) of process ­Ca2+ transients of ramified and hypertrophic microglia

Nevelchuk et al. Journal of Neuroinflammation

Fig. 5 (See legend on previous page.)(2024) 21:175

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Nevelchuk et al. Journal of Neuroinflammation(2024) 21:175

Page 14 of 18

Table 2 Tissue used for immediate fixation
Patient no.

Age at surgery (y)Sex

Resected brain area

Surgery cause

1

74

F

Right frontal cortex

Metastasis (non-small cell lung cancer)

2

34

M

Left orbitofrontal cortex

Diffuse glioneuronal tumor with oligo‑
dendroglioma-like features and nuclear
clusters

3

75

F

Right frontal cortex

Glioblastoma

4

73

M

Left temporal cortex

Glioblastoma

and H). The data also revealed the compartmentspecific heterogeneity of ­C a2+ transients in ramified,
hypertrophic and ameboid microglia and prompted
the compartment-specific comparison across morphotypes (Fig. 5B–J). In general, somatic C­ a2+ transients ofameboid cells had the largest amplitude and the shortest duration (Fig. 5B, C), whereas ramified cells had
the largest AUCs (Fig. 5D). For ROA located in soma
and processes, the amplitudes and AUCs increased
gradually from ramified through hypertrophic to ameboid cells (Fig. 5E and G). The process ­C a2+ transients
had higher amplitudes and shorter durations in ramified microglia (Fig. 5H, I).
Thus, our data revealed the marked compartmentalization of ­Ca2+ transients in human microglia. Interestingly, the basic properties of these ­C a2+ transientsdiffered dramatically across the compartments as well
as morphotypes.

Ramified

Discussion
In this study, we introduced a new approach for functional analyses of in situ human microglia cultured inhCSF and applied it to characterize the ongoing ­Ca2+
signaling in microglial morphotypes (i.e., ramified, hypertrophic and ameboid microglia), present in the humanbrain. Our data revealed distinct functional properties ofeach morphotype. Whereas in ramified microglia basal­[Ca2+]i was low and ongoing ­Ca2+ transients were mostly
compartmentalized in microglial processes, having large
amplitudes and short durations, the ameboid microglia
had significantly higher basal ­[Ca2+]i and the vast majority of large amplitude ­Ca2+ signals invaded cell somata.
Moreover, the fraction of cells with ongoing ­Ca2+ signaling, the fraction and the amplitude of process C­ a2+ sig2+
nals and the duration of somatic C­ a signals decreased
when moving along the microglia activation pathway,
i.e. from ramified via hypertrophic to ameboid microglia (Fig. 6). In contrast, the size of active compartments,

Hypertrophic

Ameboid

Ca2+ transient

Process

Soma

Ca2+ signaling
Lo

Fraction of cells with ongoing Ca2+ signaling
Fraction of process Ca2+ signals
Amplitude of process Ca2+ signals
Duration of somatic Ca2+ signals

Hi

ROA size
Fraction of somatic Ca2+ signals
Amplitude of somatic Ca2+ signals
Duration of process Ca2+ signals
Oscillatory somatic Ca2+ signaling

Fig. 6 Ongoing ­Ca2+ signals in human microglia are subcompartment- and morphotype-specific. Graphical summary of main findings. See
discussion for details

Nevelchuk et al. Journal of Neuroinflammation(2024) 21:175

the fraction and the amplitude of somatic ­Ca2+ signals
and the duration of process ­Ca2+ signals increased withmicroglial activation (Fig. 6). While imaged microglial
cells often showed overt process movement associatedwith localized C­ a2+ signals, within the framework of thepresent study (15-min-long recording period) we have
not observed any translocations of cell somata.
To enable ­Ca2+ imaging of human microglia, we combined several cutting-edge techniques, recently developed by our laboratories. Thus, organotypic brain slices
derived from fresh human biopsies were cultured inhuman CSF. This approach preserves well not only neurons [25, 26] but also different morphotypes of humanmicroglia (Fig. 1). Contrary to in vivo mouse cortex withor without transplanted human cortical organoids, whichcontains ramified human or mouse microglia [46–48],
and cultured human iPSC-derived microglial cells,
which are largely ameboid [16–20], our model harbors
all morphotypes, thus allowing their comparative study.
Moreover, throughout the experiment, the microglia
dwell in their native microenvironment. This is important because of the well-known environment-induced
cell-non-autonomous shifts in microglial phenotype[13, 48]. The distribution of ramified, hypertrophic andameboid microglia in our preparation was close to thatfound in fresh-frozen postmortem cortical samples [21,22]. Accordingly, we have also found all 3 morphotypes inacutely resected human cortical tissue.
The use of RGB labeling provides each microglial cellwith a unique color tag and enables the longitudinalmonitoring of its behavior, including cell death or division, phagocytosis, somatic dislocation or process movement under control conditions and, in the future, also inhuman disease models [49]. Finally, the development of
a novel genetically encoded C­ a2+ indicator mCyRFP1CaNeon, well-suited for single- as well as two-photonbased ratiometric ­Ca2+ imaging, adds to the versatile
microglia analyses toolbox and has enabled us to measure the morphotype-specific basal C­ a2+ levels. Comparedto popular GCaMPs, CaNeon employs a brighter fluorophore (mNeonGreen versus GFP) and has only 2 (vs. 4)­Ca2+ binding sites, thus providing better linearity of thesensor and reducing the overall burden of ­Ca2+ buffering.
Furthermore, it enables ratiometric ­Ca2+ imaging in conditions of one-photon excitation (e.g. a ratiometric miniscope-based (deep-brain) ­Ca2+ imaging in freely moving
animals [50, 51]).
Careful identification of all active pixels within thecell (Fig. 4), allowed us to analyze the spatial dimension of microglial ­Ca2+ signaling. The data revealed2+that microglial C­ a signals are highly compartmentalized and rarely spread over the entire cell. Moreover, in
ramified microglia, the amplitudes and time courses ofPage 15 of 18­Ca2+ transients differed significantly between different
subcompartments (Fig. 6), with large and short process­Ca2+ transients likely targeting different signaling pathways compared to small but prolonged somatic C­ a2+
signals [52, 53].
This study uniquely analyzed C­ a2+ signaling in microglia stemming from decades-old brains, in sharp contrast to recent analyses of iPSC-derived microglia,
generated, on average, 30–50 days before the experiment [17, 19, 20]. Consistently, the properties of thetwo cell populations differed substantially both in morphology (largely ameboid iPSC-derived microglia vs.
3 different morphotypes analyzed in our study) andfunction. While iPSC-derived microglia moved vividly
around the dish with the mean speed of 5 µm/min [17,19], we did not observe any translocation of microglial
somata over the 15-min-long recording period, reminiscent to in vivo data from adult mice [34, 54, 55].
Consistent with their morphology and similar to ourameboid cells, iPSC-derived microglia showed global­Ca2+ signals invading both somata and processes [20],quite in contrast to much more compartmentalized­Ca2+ signaling patterns of ramified and hypertrophic
microglia studied here. It also has to be kept in mind
that in contrast to iPSCs, microglia stem from theextra-embryonic yolk sack macrophages [56].
So far, C­ a2+ signaling of ramified microglia was exclusively studied in mice under in situ [57, 58] or in vivo
[6–10, 59] conditions. However, recent comparative
mouse-human studies revealed several functional differences between the human and mouse microglia. First,
human microglia renew at a median rate of 28% peryear [23], which means that some microglia dwell in thehuman brain for more than two decades, whereas mice
live ~ 2 years and the oldest mouse microglia in which­Ca2+ signaling was studied were 18–21-month-old [60].
Secondly, despite the overall similarity between thegenes expressed by human and mouse microglia, several
immune genes do not have a clear 1:1 mouse ortholog(e.g., complement receptor type 1, HLA-DRB1, HLADRB5, TLR, Fcγ and SIGLEC receptors) or display < 60%
identity between human and mouse at the primary aminoacid sequence (e.g. TREM2), and several rodent gene
modules, including complement, phagocytic and neurodegeneration-susceptibility genes, differed substantiallyfrom primate microglia [14, 47, 61]. Moreover, whereas
in most species microglia showed a single dominant transcriptional state, human microglia displayed substantial
heterogeneity [61] and, for example, responded to neurodegeneration and Alzheimer’s disease pathology byupregulation of TMEM119, P2RY12 and CX3CR1 genes,
contrary to their downregulation in mouse models of thedisease [62, 63].

Nevelchuk et al. Journal of Neuroinflammation(2024) 21:175

Against this backdrop, we have compared the ongoing ­Ca2+ signaling in human and mouse microglia andhave spotted several major similarities. First, the studied human cells seemed to belong to a continuum of
microglial functional states with ramified and ameboid
microglia building the two extremes and hypertrophic
microglia spreading among multiple intermediate states[64]. Moreover, (i) the basal ­[Ca2+]i increased with thedegree of activation both in human (Fig. 3C) and mouse[10] microglia; (ii) both species showed spontaneousongoing ­Ca2+ signaling; (iii) microglial C­ a2+ transients inboth species were highly compartmentalized (Fig. 4; [5,6]) and (iv) the spatial distribution of ongoing C­ a2+ signals switched from process- to soma-dominated patterns
during microglial activation (Figs. 3, 4, 5; [6, 7, 9]).
Limitations of the study

Analyses of the resected human tissue provide a unique
opportunity to study decades-old human microglia intheir native microenvironment. However, because thistissue stems from epilepsy or tumor surgeries it cannot a priori be considered normal. In the current study,
the postoperative histologic examination of the resected
tissue was only done for the epilepsy patient (Table 1,
patient 5), showing no evidence of focal cortical dysplasia or other pathology. In the case of the intraventricularglioneuronal tumor (Table 1, patient 6), the resected andthe tumor tissues were far (~ 2 cm) apart, suggesting thatthe resected access tissue was healthy. In all other cases
resected and tumor tissues were located closer. Of note,electrophysiological and plasticity properties of temporal
cortex pyramidal cells from healthy rats and patient epilepsy/tumor resection tissues were shown to be similar[65]. Recently, the same was shown to be true for basic
electrophysiological properties of healthy mouse microglia and human microglia stemming from epilepsy resection tissue [66]. We cannot exclude, however, that otherproperties of analyzed microglia might have been modified by the preexisting brain pathology.
Furthermore, expression of the genetically encoded­Ca2+ indicator in microglia requires organotypic slice
culturing, which might also change their functional properties. This drawback our approach shares with all otheravailable techniques analyzing C­ a2+ signaling in humanmicroglia [15–20]. Organotypic slice culturing in hCSF
was established several years ago, and our previous data
revealed striking similarities between the propertiesof pyramidal cells and interneurons recorded in acuteor organotypically cultured (for 7–14 days) slices [25,26]. Both cell types showed stable action potential (AP)firing frequencies, the AP half widths, resting membrane potentials, sag potential amplitudes, input resistances as well as cell-type specific firing properties (e.g.

Page 16 of 18

spike frequency adaptation in pyramidal cells). Moreover, reconstructions of 24 pyramidal cells cultured for
0–14 days revealed a surprising stability of their morphological features, including dendritic spines, pointing
to the absence of overt inflammation. Finally, the highdensity microelectrode array recordings showed that
hypersynchronous or epileptiform-like activity is not
typical for this kind of preparation [28, 67]. Concerning
microglia, a comparison of freshly resected and hCSFcultured tissue (Supplementary Fig. 4) revealed that
although the cell density, median distance to the nearest
neighbors, mean microglial cell diameter, volume, surface
area, and soma shape (sphericity) were within the similar range, a detailed examination revealed significant differences between the cells of the two groups for all but
last parameters. Although the compared tissue stemmed
from different donors, the results were consistent within
the groups suggesting that the observed difference isdue to slice culturing rather than inter-individual or surgery-related variability. Thus, although organotypic slice
culturing in hCSF prevents the development of overt
inflammation and preserves the in vivo-like distributionof microglial morphotypes, some differences in functional properties between in situ and in vivo microglia
can’t be excluded.

Conclusions
Our data establish biopsy-derived organotypic humanbrain slices, cultured in human CSF, as a valid in situ
model for analyses of human microglia thus increasing
the versatility of the available toolbox. This model provides a unique possibility to study adult, decades-old
microglia in their natural microenvironment and reveals
that many functional properties of these cells, including
vivid process motility and compartmentalized ongoing­Ca2+ signaling, the pattern of which is morphotype-specific, are reminiscent of that seen in vivo in rodent microglia. The latter cells, however, are ramified underhomeostatic conditions, while much longer-lived humanmicroglia express a continuum of different morphotypes.
Supplementary Information
The online version contains supplementary material available at https://​doi.​
org/​10.​1186/​s12974-​024-​03169-6.
Supplementary Material 1.
Supplementary Material 2.
Supplementary Material 3.
Acknowledgements
We thank E. Zirdum, B. Gittel and K. Schmidt for technical assistance, RaduGabriel Copie and Friederike Pfeiffer for the data shown in Supplementary
Fig. 3B, and Kuang Pan for the help with data acquisition.

Nevelchuk et al. Journal of Neuroinflammation(2024) 21:175

Author contributions
S. Nevelchuk: data analysis, visualization; B. Brawek: visualization, writing; N.
Schwarz: slice preparation and culturing, provided critical reagents, writing;
A. Valiente-Gabioud: generation of the C­ a2+ sensor; T.V. Wuttke: tissue resec‑tion, provided critical reagents; Y. Kovalchuk: investigation; H. Koch: provided
critical reagents; A. Höllig: tissue resection; F. Steiner: investigation, cloning; K.
Figarella: prepared all viral vectors; O. Griesbeck: experimental design, genera‑tion of ­Ca2+ sensor, writing; Olga Garaschuk: conceptualization, experimental
design, investigation, supervision, visualization, and writing.
Funding
Open Access funding enabled and organized by Projekt DEAL. This work waspartially supported by the DFG, grant number GA 654/13-2 (FOR2715) to O.G.
Data availability
All relevant data are included in the manuscript and supplementary files. Any
further inquiries can be directed to the corresponding author.

Declarations

Page 17 of 18

12.
13.

14.

15.
16.

17.

Ethics approval and consent to participate
Approval (# 772/2021BO2) of the ethics committee of the University of Tübin‑gen, Approval (EK067/20) of the ethics committee of the RWTH Aachen Uni‑
versity as well as written informed consent from all patients, whose resected
tissue was used in this study.

18.

Consent for publication
Not applicable.

19.

Competing interests
The authors declare no competing financial interests.

20.

Received: 25 May 2024 Accepted: 9 July 2024

21.
22.

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