(2024) 21:206
Grabon et al. Journal of Neuroinflammation
https://doi.org/10.1186/s12974-024-03202-8

Journal of Neuroinflammation

Open Access

RESEARCH

CB2 expression in mouse brain:from mapping to regulation in microglia
under inflammatory conditions
Wanda Grabon1,2*†, Anne Ruiz3†, Nadia Gasmi1,2, Cyril Degletagne4, Béatrice Georges1,2, Amor Belmeguenai1,2,
Jacques Bodennec1,2, Sylvain Rheims1,2, Guillaume Marcy5† and Laurent Bezin1,2*†

Abstract
Since its detection in the brain, the cannabinoid receptor type 2 (CB2) has been considered a promising therapeutic target for various neurological and psychiatric disorders. However, precise brain mapping of its expression is stilllacking. Using magnetic cell sorting, calibrated RT-qPCR and single-nucleus RNAseq, we show that CB2 is expressed
at a low level in all brain regions studied, mainly by few microglial cells, and by neurons in an even lower proportion. Upon lipopolysaccharide stimulation, modeling neuroinflammation in non-sterile conditions, we demonstratethat the inflammatory response is associated with a transient reduction in CB2 mRNA levels in brain tissue, particularly
in microglial cells. This result, confirmed in the BV2 microglial cell line, contrasts with the positive correlation observed
between CB2 mRNA levels and the inflammatory response upon stimulation by interferon-gamma, modeling neuroinflammation in sterile condition. Discrete brain CB2 expression might thus be up- or down-regulated dependingon the inflammatory context.
Highlights• Tissue level of CB2 receptor mRNA is low and uniform across the various brain regions examined.
• The use of transcription and translation inhibitors during brain dissociation and cell sorting is efficient to prevent
microglia ex vivo activation.
• CB2 mRNA was detected in scarce cells at the physiological state, was mainly detected in microglia and in someneurons.
• CB2 expression is downregulated in microglia during LPS-induced inflammatory peak and upregulated during the resolution of inflammation.
• LPS and IFNγ stimulation differently regulate CB2 expression in microglia.
Keywords Cannabinoid receptor type 2, Endocannabinoid system, Microglia, Neuroinflammation†

Wanda Grabon, Anne Ruiz, Guillaume Marcy and Laurent Bezin contributed
equally.
*Correspondence:
Wanda Grabon
wanda.grabon@univ-lyon1.fr
Laurent Bezinlaurent.bezin@univ-lyon1.fr
Full list of author information is available at the end of the article© The Author(s) 2024. Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0
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Grabon et al. Journal of Neuroinflammation(2024) 21:206

Introduction
The function of cannabinoid receptor type 2 (CB2),
mainly expressed by leukocytes, has initially been limited to its peripheral immunomodulatory role [1–3].
However, the use of CB2-specific ligands and the availability of CB2-Knock Out (KO) mice have unveiled its
potential role in central nervous system (CNS) functions
under both physiological and pathological conditions [4,5]. To gain deeper insights into its involvement in brain
functions, it is essential to identify the cells targeted byits ligands, a pursuit that holds significant therapeuticpromise in neuropsychiatric and neuroinflammatory diseases [6, 7]. Nevertheless, precise and accurate mappingof cnr2 gene expression remains difficult to establish on
the basis of CB2 protein detection, mainly because specific antibodies are still lacking [8–10]. The detection of
CB2 transcript is therefore today the reference techniqueto overcome the issue of antibody specificity, providing both highly sensitive and specific quantification. The
presence of CB2 mRNA was previously investigated andreliably detected in a few isolated regions, namely in theventral tegmental region (VTA)[11, 12], striatum [13–15]
and hippocampus [13, 16, 17].
The primary goal of this study was to quantify andcompare at the tissue level with calibrated RT-qPCR
CB2 expression and other primary cannabinoid receptors, CB1, GPR18, and GPR55, across eleven major brain
regions in three different mouse strains (C57Bl/6, Balb/c,
and Swiss). The second objective of this study was todetermine which cell types predominantly support CB2
expression in the brain. We used cell sorting techniquesfrom dissociated adult brain tissue to determine CB2mRNA level in populations enriched in microglia andneurons, but also in astrocytes/oligodendrocytes and inendothelial cells. To reach this objective, we took a particular attention in limiting microglial cell activation
throughout the whole technical procedures using transcriptional and translational inhibitors [18]. Furthermore,
we took advantage of access to a single-nucleus databaseobtained from cortex tissue collected from 10-day- oldmice to assess what might be the proportion of cells
expressing CB2 in each cell populations.
CB2 expression is known to be regulated as a functionof inflammatory state [19, 20]. Indeed, CB2 expressionin brain tissue has been shown to be induced in neurological conditions associated with an inflammatory state,such as stroke, traumatic brain injury or Alzheimer’s
disease [5, 7]. Most studies suggest that microglial cell
activation is responsible for this induction. But intriguingly, few in vitro studies in which non-sterile neuroinflammation is modelled by lipopolysaccharide (LPS)
stimulation of microglial cells report a down-regulation

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of CB2 [20, 21]. Our third objective was to better understand whether CB2 expression is similarly coordinatedwith inflammatory markers after a sterile or non-sterile
inflammatory challenge, modeled by stimulation withinterferon-gamma (IFNγ) or LPS, respectively, known
to activate different inflammatory intracellular signaling
pathways [22, 23]. Our study is the first to demonstratethat CB2 gene expression in the brain is supported by avery small number of microglial cells, and by neurons ineven smaller proportions, and that microglial CB2 transcript levels can be up- or down-regulated depending on
the inflammatory context and timing.

Results
CB2 expression in basal condition is consistent across brain
regions with minimal strain variability

Tissue transcript levels of CB2 and 3 other cannabinoid
receptors—CB1, GPR18 and GPR55—were determinedin eleven microdissected regions from the adult (8-weekold) mouse brain: olfactory bulb, neocortex, hippocampus, hypothalamus, cerebellum, brainstem, ventral limbic
region (VLR, comprising the amygdala, agranular insularcortex and piriform cortex), nucleus accumbens, substantia nigra, striatum and VTA (Fig. 1A). Comparative analysis of cannabinoid receptor mRNA levels was
performed across three commonly used mouse strains:
C57bl/6, Balb/c and Swiss (n = 3–4/group). Transcriptsof the 4 receptors were detected in all mouse strains
and in all brain regions. CB2 expression was not significantly different between mouse strains in the 11 regions
investigated (Table S2). For the other 3 receptors—CB1,
GPR55 and GPR18—only 10 isolated inter-strain differences were measured out of the 99 comparisons made(3 strains, 11 structures, 3 receptors, Table S2). To
compare the expression of CB2 with the other cannabinoid receptors in the different regions, data from the 3mouse strains were combined. For CB2 transcripts, nosignificant inter-region difference was observed, except
for levels measured in the VTA, that were significantly
lower than those of the olfactory bulb (p < 0.0001), thehippocampus (p = 0.0051), the VLR (p = 0.0136) and thesubstantia nigra (p = 0.0002) (Fig. 1B). It should be notedthat the distribution of transcript levels of the other cannabinoid receptors is much less homogenous (Kruskall
Wallis: CB1, GPR18, GPR55: p < 0.0001, Fig. S2).
CB2 was expressed at much lower levels than otherendocannabinoid receptors in all regions studied(Fig. 1C–M). Overall, CB1 and GPR18 were the two mostexpressed cannabinoid receptors among the investigatedregions, and GPR55 was expressed at intermediate levels.

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A(2024) 21:206

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B

C

D

E

F

G

H

I

J

K

L

M

Fig. 1 Regional distribution of cannabinoid receptors mRNA in the healthy mouse brain. CB2 mRNA was quantified using calibrated RT-qPCR
and compared with other cannabinoid receptors CB1, GPR18 and GPR55 in eleven microdissected regions from adult mouse brain: the olfactory
bulb (OB), the neocortex (NCX), the hippocampus (HI), the hypothalamus (Hθ), the cerebellum (CRB), the brainstem (BS), n = 9 mice; the ventral
limbic region (VLR), the nucleus accumbens (NAc), the substantia nigra (SN), the striatum (Str) and the ventral tegmental region (VTA), n = 12
mice. A Representation of the 11 microdissected regions. B Quantification of CB2 transcript levels. Tukey’s tests following one-way ANOVA: *, VTA
vs. OB: p < 0.0001; $, VTA vs. HI: p = 0.0051; €, VTA vs. VLR: p = 0.0136; #, VTA vs. SN: p = 0.0002. C–M Quantification of CB2, CB1, GPR18 and GPR55
in each microdissected region. Transcript levels are expressed as copies of cDNA per microgram of total RNA. Values are presented as means + SEM.
Normal data were analyzed with Tukey’s post-hoc test for multiple comparisons following one-way ANOVA (Hθ, VLR, NAc, SN, Str, VTA: p < 0.0001).
Non-normal data were analyzed with Dunn’s post-hoc test for multiple comparisons following Kruskal–Wallis test (OB: p < 0.0001, NCX: p < 0.0001,
HI: p < 0.0001, CRB: p < 0.0001, BS: p < 0.0001). *, p < 0.05; **, p < 0.01; ***, p < 0.001, ****, p < 0.0001. Not significantly statistical differences are
not graphically represented

Transcription and translation inhibitors prevent microglia
ex vivo activation during tissue dissociation and cellsorting

Ex vivo activation of brain cells, in particular microglial
cells, can change the accuracy of measurements related
to the inflammatory state within brain tissue. While thisactivation can be minimized by rapid microdissection
on ice and immediate freezing of samples, it remains a

concern during tissue dissociation protocols, involving
heating, enzymes and mechanical damage, and during
cell sorting protocols [18, 24]. To prevent this activation,buffers can be supplemented with transcriptional andtranslational inhibitors such as actinomycin D (ActD),
triptolide (Trip), and anisomycine (Anis) [24]. Here,the efficacy of these inhibitors was tested in CD11benriched populations from adult C57Bl/6 mouse brains,

Grabon et al. Journal of Neuroinflammation(2024) 21:206

the purity of which reached 91.1% (Fig. 2A). Based on
quantification of IL-1β and TNFα transcripts, when thebuffer contained no inhibitor, the level of gene activation in microglial cells sorted from adult mouse brains
was the highest (Fig. 2B, C). For the IL-1β transcript,
inhibition of transcription alone using ActD resulted ina 47.4% decrease of expression level, while inhibition ofboth transcription and translation using the inhibitor
cocktail decreased it much more strongly, with a 91.6%
decrease (Fig. 2B). For the TNFα transcript, the only condition that led to a decrease in its expression level was theinhibitor cocktail (Fig. 2C). Our data support that inhibition of both transcription and translation, here applied as
early as intracardiac perfusion, is necessary to limit thelevel of gene activation in microglial cells during tissue
dissociation and cell sorting [24]. Therefore, to avoid any
bias related to ex vivo activation of microglia, all further
MACS studies were performed in the presence of theinhibitor cocktail from brain perfusion, to dissociation,
cell labelling, and cell sorting.
CB2 mRNA expression in sorted brain cells shows peaklevels in microglia at the physiological state

Different cell populations from mouse hippocampus
and neocortex were enriched using MACS after tissue dissociation and subsequently immunophenotyped
using flow cytometry (Fig. S3). High degrees of purity
were measured, with 98.2% purity in cell populationenriched in both astrocytes (­ACSA2+/O4−: 64%) andoligodendrocytes ­(O4+: 34.2%), 60.9% in a cell population enriched in ­Ly6C+/CD31+ endothelial cells, 98.2% inA

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cell population enriched in C
­ D11b+ microglial cells, and96.9% in the neuronal population negative for all tested
flow cytometry cell markers. The identity of the enrichedcell populations was further confirmed using RT-qPCR,
by detecting and quantifying transcript level of various
typical cell markers (Fig. 3A–D). Significant differencesin CB2 mRNA levels were measured between the different enriched-cell populations (Fig. 3E). The highest CB2mRNA expression was found in the microglia-enrichedcell population, showing a tenfold increase comparedto neuronal cell-enriched population and 63–153-foldincrease compared to endothelial cells and astrocytes/oligodendrocytes, respectively.
We next performed a single nucleus RNA seq experiment on 10-day-old mice to estimate what might be theproportion of CB2-expressing cells in each of the populations enriched by MACS. Neonatal brain tissue has theadvantage of being easy to dissociate for subsequent single-cell analysis, unlike adult tissue which contains a lotof debris due to myelin accumulation. Importantly, thestability of CB2 mRNA levels between neonatal brain andadulthood, in both hippocampus and neocortex (Fig. 3F),
as previously described in the hippocampus [17], facilitated a meaningful comparison between the MACS dataobtained at 8 weeks and the single-nucleus RNAseq dataobtained at 10 days.
We isolated 10k nuclei, excluded low quality nuclei,
clustered and annotated the cell types (Fig. 3H) basedon classical markers (Fig. S4). We quantified that CB2mRNA was detected in less than 1% of total cells, identified as neurons, microglia and astrocytes. The population

C

Fig. 2 Prevention of microglial activation during dissociation and cell sorting protocols using transcription and translation inhibitors. A Brain tissue
from adult mice was dissociated using Miltenyi’s ABDK protocol and CD11b-positive cells were enriched using MACS CD11b magnetic microbeads.
Purity of CD11b-positive population was controlled on a pool of cells from each sample by cytometry. B, C IL-1β (B) and TNFα (C) mRNAs were
quantified using calibrated RT-qPCR following tissue dissociation and CD11b MACS cell enrichment from adult mouse brain (n = 2). Dissociationand MACS protocols were performed with classic buffer (ø), with buffer complemented with transcription inhibitor ActD (3 µM) or with buffer
complemented with both transcription and translation inhibitors ActD, Anis and Trip (3 µM, 100 µM and 10 µM, respectively). Transcript levels are
expressed as fold change of the classic buffer (ø) condition. Individual values (dots) and average values (bars) are presented

Grabon et al. Journal of Neuroinflammation(2024) 21:206

with the highest proportion of CB2-positive cells was
microglia, with a proportion around 20-fold greater thanin neurons and tenfold greater than in astrocytes. CB2expressing nuclei are visualized in red in Fig. 3I.
CB2 mRNA levels in the neocortex and the hippocampus
following LPS

LPS administration in adult C57Bl/6 mice led to a significant inflammatory peak at 3h as reflected by high levels of
TNFα, IL-1β, IL-6, COX2, NOS2 and MCP1 transcripts
in the hippocampus and neocortex (Fig. 4A–F). The
inflammatory index calculated from the transcript levelsof these pro-inflammatory genes peaked at 13.2-fold ± 1.6
the control level (Fig. 4G). The amounts of CB2 transcript
3h after LPS administration, i.e. during the inflammatory peak, transiently decreased to 52 ± 9% of those incontrols, before rebounding 24h later, to 194 ± 19% above
controls, once inflammation had resolved (Fig. 4H). The
level of CB2 transcript was inversely correlated to the
inflammatory index after administration of LPS (Fig. 4I).
Conversely, CB1 and GPR18 transcript levels were uncorrelated, while those of GPR55 were positively correlatedwith the inflammatory index (Fig. S5).
CB2 mRNA levels in microglia following LPS

In these experiments, all steps were performed withbuffers complemented with inhibitor cocktail. Brains
were collected 3 h or 24 h post-LPS treatment. Total
RNAs were extracted from MACS sorted CD11benriched cell populations, whose purity, estimated bycytometry, ranged between 85.7% and 98.7% (Fig. 5A).
As measured in tissue homogenates, LPS administration led to a significant inflammatory peak in microglial
cells at 3h as reflected by high levels of TNFα, IL-1β,
IL-6, COX2, NOS2 and MCP1 transcripts (Fig. 5B–G).
The calculated pro-inflammatory index peaked at 43.2fold ± 6.4 the control level (Fig. 5H). CB2-mRNA level
present in microglial cells 3h after LPS administration

Page 5 of 16transiently were reduced by 84.4 ± 7.4%, before rebounding 24h later, 171 ± 19% above controls, once inflammation had resolved (Fig. 5I). The level of CB2 transcript
was inversely correlated to the pro-inflammatory index
after administration of LPS (Fig. 5J). Conversely, GPR55
and GPR18 transcript levels were not significantly correlated with the pro-inflammatory index (Fig. S6).
CB2 mRNA levels in microglia BV2 cell line following LPS
or IFNγ stimulation

Based on the quantification of pro-inflammatory genetranscripts (Fig. 6A–F) and the calculation of the proinflammatory index (Fig. 6G), LPS treatment of murine
BV2 microglial cells led to an inflammatory responsethat peaked between 2 and 4h. At the same time, CB2mRNA levels were reduced by 92 ± 0.7%2h after LPS
treatment compared to untreated cells (Fig. 6H). As forlevels measured in brain tissue and microglia sorted cells,
CB2-mRNA level was inversely correlated with the proinflammatory index (Fig. 6I). GPR55-mRNA levels werealso inversely correlated with the pro-inflammatory
index while GPR18 expression was not regulated during
LPS-induced inflammation (Fig. S7).
Previous studies have shown that stimulation of BV2
cells with IFNγ resulted in a reverse regulation of CB2
expression compared to that induced by LPS [20].
Komorowska-Müller et al. hypothesized that this difference in regulation could be due to a much lower level ofinflammation after IFNγ compared to LPS, and to different nature of the two stimuli, IFNγ being a cytokine
released during sterile inflammation, and LPS a bacterial
toxin [7].
IFNγ treatment of BV2 cells led to an increase inmost pro-inflammatory gene transcripts, except forIL-1β, (Fig. 7A–F) and of the pro-inflammatory index(Fig. 7G), that peaked at 8h. The level of inflammation
was mostly resolved by 24h. Interestingly, CB2-mRNAlevels did not drop but increased up to twofold during(See figure on next page.)
Fig. 3 Cell distribution of CB2 mRNA in the mouse brain. A–E Adult mouse brain tissue was dissociated as in Fig. 2. Four populations wereenriched by MACS technique. Expression of specific cell markers was quantified by RT-qPCR to control for cell population identity and purity: A
Neurons, expressing NeuN mRNA; B CD11b-positive microglia, expressing CD115 and Iba1 mRNA; C Ly6C-positive endothelial cells, expressing
CD31 and Ly6C mRNA; D ACSA2-positive astrocytes and oligodendrocytes, expressing GFAP and GLAST mRNA. E CB2 mRNA was quantified using
calibrated RT-qPCR in the four MACS-enriched cell populations. Transcript levels are expressed as copies of cDNA per µg of total RNA reverse
transcribed. Values are presented as mean + SEM, analyzed with Tukey’s test for multiple comparisons following one-way ANOVA. 554,052 ± 92,463
CB2 cDNA copies/µg RNA were quantified in microglia-enriched cell population. Microglia vs. Neurons: p = 0.0004; Microglia vs. Astro/oligo:
p = 0.0002; Microglia vs. Endothelial cells: p = 0.0002. F. Levels of CB2 transcripts quantified at tissue level in the hippocampus (HI) and neocortex(NCX) are expressed as % of the mean calculated in respective adult group. CB2 mRNA levels are similar in P10 (n = 8) and adult (P56) mice(n = 6), analyzed with Tukey’s test for multiple comparisons following one-way ANOVA. HI adult vs. P10: p = 0.7796; NCX adult vs. P10: p = 0.6922.
G. Percentage of CB2-positive cells in clustered nuclei. Data are analyzed with Fisher exact test. Microglia vs. neurons, p < 0.0001; microglia vs.
astrocytes: p = 0.0114. H. Clustering of Single nuclei sorted from P10 mice neocortices I. Visualization of CB2-expressing nuclei (red) among clusteredsorted nuclei. Asterisks represent comparisons vs. microglia: *, p < 0.05; **, p < 0.01; ***, p < 0.001, ****, p < 0.0001

Grabon et al. Journal of Neuroinflammation(2024) 21:206

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Fig. 3 (See legend on previous page.)the inflammatory peak compared with untreated cells(Fig. 7H) and were positively correlated with the proinflammatory index (Fig. 7I). The main observed difference with LPS treatment was the absence of peakin IL-1β- transcripts following IFNγ treatment in BV2cells (Fig. 7A).
To determine whether the dramatic decrease in CB2mRNA level, observed only under LPS treatment, wasGrabon et al. Journal of Neuroinflammation(2024) 21:206

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Fig. 4 CB2 mRNA inversely correlated with levels of inflammatory markers in brain after LPS challenge. Transcript levels of pro-inflammatory genes
and CB2 were quantified in the neocortex and the hippocampus of adult C57Bl/6 mouse brains, 3h (n = 7), 6h (n = 7) and 24h (n = 8) following LPS
administration (5 mg/kg, IP) and compared with untreated control (CTRL) mice (n = 6). A–F Quantification of IL-1β, IL-6, TNFα, COX2, NOS2
and MCP1 transcript levels. G. Pro-inflammatory index (PI-I) was calculated from transcript levels of pro-inflammatory genes (A–F). CTRL vs. LPS + 3h:
p < 0.0001. H Quantification of CB2 mRNA. Data are expressed as the mean ± SEM, and presented as relative to control mice. CTRL vs. LPS + 3h:p = 0.0036; CTRL vs. LPS + 24h: p = 0.0008. Normal data (NOS2, MCP1, PI-I and CB2) were analyzed with Tukey’s test following one-way ANOVA.
Non-normal data (IL-1β, TNFα, IL-6, COX2) were analyzed with Dunn’s test following Kruskal–Wallis test. Asterisks represent LPS-treated groups vs.
CTRL: *, p < 0.05; **, p < 0.01; ***, p < 0.001, ****, p < 0.0001. I Relationship between CB2 transcript level and PI-I (simple linear regression, p = 0.0031,­R2 = 0.2901, y = − 0.06617x + 1.480, n = 28)(See figure on next page.)
Fig. 5 CB2 mRNA levels is inversely correlated with inflammatory markers in microglia after LPS administration. Brain tissue of adult C57Bl/6
mice was dissociated using Miltenyi’s ABDK protocol and microglia-enriched cell population was sorted as in Fig. 2. Pro-inflammatory genes
and CB2 mRNA were quantified by RT-qPCR in CD11b-positive cells sorted from mouse brain (neocortex and hippocampus) 3h (n = 5)
and 24h (n = 5) following LPS administration (5 mg/kg, IP) and compared with untreated (CTRL) mice (n = 4). A The purity of the MACS-sorted
CD11b-positive cells was estimated by quantifying the protein expression of CD11b by flow cytometry on a fraction of pooled cell suspensions
harvested before and after CD11b MACS magnetic sorting. B–G Quantification of IL-1β, IL-6, TNFα, COX2, NOS2 and MCP1 transcript levels. H.
Pro-inflammatory index (PI-I) was calculated from transcript levels of pro-inflammatory genes (A–F). CTRL vs. LPS + 3h: p < 0.0001. I. Quantificationof CB2 mRNA. CTRL vs. LPS + 3h: p = 0.0061; CTRL vs. LPS + 24h: p = 0.0132. Data are expressed as mean + SEM, and presented as relative to microglia
from control mice. Normal data (IL-1β, IL-6, COX2, MCP1, PI-I and CB2) were analyzed with Tukey’s test following one-way ANOVA. Non-normal
data (TNFα and NOS2) were analyzed with Dunn’s test following Kruskal–Wallis test. Asterisks represent LPS-treated groups vs CTRL: *, p < 0.05;**, p < 0.01; ***, p < 0.001, ****, p < 0.0001. J Relationship between CB2-mRNA levels and PI-I (simple linear regression, p = 0.0012, R­ 2 = 0.5962,
y = − 0.02596x + 1.423, n = 14)

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Fig. 5 (See legend on previous page.)

due to strong activation of IL-1R by IL-1β, BV2 cells
were incubated with IL-1RA (1–1000 ng/mL), the natural IL-1R antagonist, 30-min prior to and during LPS.
IL- 1RA did not prevent LPS-induced CB2 mRNAlevel decrease (Fig. S8).

Discussion
Main results

In this study, we demonstrated at the transcriptional levelthat the CB2 receptor exhibits consistently low and uniform expression across various brain regions examined,Grabon et al. Journal of Neuroinflammation(2024) 21:206

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Fig. 6 CB2 mRNA levels inversely correlated with inflammatory markers in BV2 cells after LPS treatment. Inflammatory genes and CB2 mRNA
were quantified by calibrated RT-qPCR in cultured BV2 murine cells following LPS 1 h, 2 h, 4 h, 8 h or 24 h application (100 ng/mL) and comparedwith levels quantified in untreated cells (CTRL, LPS + 1 h, + 2 h, + 4 h: n = 4/condition; LPS + 8 h, + 24 h: n = 3/condition). A–F Quantification of IL-1β,
IL-6, TNFα, COX2, NOS2 and MCP1 transcript levels. G Pro-inflammatory index (PI-I) was calculated from transcript levels of pro-inflammatory genes(A–F). CTRL vs. LPS + 1h: p = 0.0005; vs. + 2h: p < 0.0001; vs. + 4h, p < 0.0001; vs. + 8h: p = 0.0002. H. Quantification of CB2-mRNA. CTRL vs. LPS + 1h:
p < 0.0001; vs. + 2h: p < 0.0001; vs. + 4h, p < 0.0001; vs. + 8h: p < 0.0001; vs. + 24h: p < 0.0001. Data are expressed as the mean ± SEM, and presented
as relative to untreated BV2 cells. Normal data (TNFα, IL-6, COX2, MCP1, PI-I and CB2) were analyzed with Tukey’s test for multiple comparisonsfollowing one-way ANOVA. Non-normal data (IL-1β and NOS2) were analyzed with Dunn’s test for multiple comparisons following Kruskal–Wallis
test. Asterisks represent control (CTRL) vs. respective LPS-treated group. *, p < 0.05; **, p < 0.01; ***, p < 0.001, ****, p < 0.0001. I Relationshipbetween CB2-mRNA levels and PI-I (simple linear regression, p < 0.0001, ­R2 = 0.6426, y = − 0.02012x + 0.7688, n = 22)

including the olfactory bulb, neocortex, hippocampus,
hypothalamus, cerebellum, brainstem, VLR, nucleus
accumbens, substantia nigra, striatum and VTA. Notably, there were no significant differences in CB2 expression among the three mouse strains (C57bl/6, Balb/c, andSwiss) studied. Our findings highlighted that microglia
are the primary cell type expressing CB2 in the brain,
while neurons displayed lower levels of CB2 expression.
Additionally, we noted an inverse relationship between
CB2 expression and the degree of LPS-induced inflammation over time. This was evidenced by a decrease in
CB2 transcript levels coinciding with the peak of inflammation, as observed both at the tissue level in the hippocampus and neocortex, as well as at the cellular levelin sorted microglial populations and BV2 microglial cellline. Intriguingly, we observed the opposite relationshipafter stimulation of BV2 cells with IFNγ, which activates
different intracellular pathways from LPS.

Methodological consideration

One of the objectives of the study was to determine whichcell types contribute to the expression of CB2 measured
in brain tissue, involving the use of cell sorting protocols.
Obtaining a cell suspension from brain tissue and enriching cell populations by magnetic or fluorescent sorting
represents an assault on brain cells that can alter theirphenotypic state. Microglia are effective sentinels, continuously scanning the microenvironment in their basal
state, and entering an extremely rapid activation process
whenever cerebral homeostasis is compromised [25, 26].
Ex vivo microglial activation can introduce confounds
that can distort measurements of the transcriptomic profile in basal state or mask endogenously induced activation, as in a pathological condition [24]. Previous studies
have shown that supplementing the buffer with transcription and translation inhibitors during the enzymaticand mechanical dissociation of brain tissue limits ex vivo

Grabon et al. Journal of Neuroinflammation(2024) 21:206

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Fig. 7 CB2 mRNA levels positively correlated with inflammatory markers in BV2 cells after IFNγ treatment. Inflammatory genes and CB2 mRNA
were quantified by calibrated RT-qPCR in cultured BV2 murine cells following IFNγ 3 h, 8 h or 24 h application (100 ng/mL) and comparedwith levels quantified in untreated cells (n = 3/condition). A–F Quantification of IL-1β, IL-6, TNFα, COX2, NOS2 and MCP1 transcript levels. G
Pro-inflammatory index (PI-I) was calculated from transcript levels of pro-inflammatory genes (A–F). CTRL vs. IFNγ + 8h: p = 0.0132. H Quantificationof CB2 mRNA. CTRL vs. IFNγ + 3h: p = 0.0088; CTRL vs. IFNγ + 8h: p = 0.0002; CTRL vs IFNγ + 24h: p = 0.0097. Data are expressed as the mean ± SEM,
and presented as relative to untreated BV2 cells. Normal data (IL-1β, IL-6, TNFα, COX2, NOS2, MCP1 and CB2) were analyzed with Tukey’s
post-hoc test for multiple comparisons following one-way ANOVA. Non-normal data (PI-I) were analyzed with Dunn’s post-hoc test for multiple
comparisons following Kruskal–Wallis test. Asterisks represent control (CTRL) vs respective IFNγ-treated group. *, p < 0.05; **, p < 0.01; ***, p < 0.001,****, p < 0.0001. I Relationship between of CB2 transcript levels and pro-inflammatory index (simple linear regression, p = 0.0013, ­R2 = 0.6590,
y = 0.2545x + 0.5265, n = 12)

activation of microglial cells [18]. Here, we showed thatusing the same inhibitors from intracardiac perfusion
stage through to final cell collection indeed limited theinduction of IL-1β and TNFα pro-inflammatory markers
in microglial populations enriched from brain tissue of
healthy adult mice. As sentinel cells of the CNS, microglial cells are the most likely to be sensitive to ex vivo
activation during the cell dissociation and sorting protocol. Nevertheless, uncontrolled gene activation may
also occur in other cell types during these steps. We only
tested the effect of inhibitors on microglial cells and not
on other cell populations. We have assumed that inhibition of non-physiological activation of microglia may
also extend to other brain cell types, since the targets oftranscriptional and translational inhibitors are conservedin all eukaryotic cell types [27, 28] and are therefore notcell-specific.

CB2 basal expression in the CNS

Under physiological conditions, we showed no interstrain (C57bl/6, Balb/c and Swiss), nor any spatial regulation of cnr2 gene expression according to the brain
regions studied: the olfactory bulb, the neocortex, thehippocampus, the hypothalamus, the cerebellum, thebrainstem, the VLR, the nucleus accumbens, the substantia nigra, the striatum and the VTA. The only region
with a slightly lower level of CB2 expression than theother regions is the VTA, which is one of the areas inwhich CB2 is most studied, notably for its role in the
reward system [11, 12], suggesting that the physiologicalrole of CB2 is not limited to the dopaminergic system.
CB2 transcript levels were relatively low when compared to other main cannabinoid receptors CB1, GPR18
and GPR55. Confirmation of the presence of CB2 in
the physiological state is consistent with quantifiableGrabon et al. Journal of Neuroinflammation(2024) 21:206

behavioral outcomes in healthy mice, for example on
memory [29, 30], mood [31] or pain sensitivity [32, 33]
measured after administration of CB2-specific ligands[5]. Given the very low number of CB2-positive cells
measured by single nuclei, neurons and microglia
expressing CB2 must establish major connections with
the neuronal networks controlling the brain functions
studied.
The homogeneity of CB2 expression contrasts with thegreat heterogeneity between the regions investigated,both in terms of structural organization and function.
This may suggest that CB2 is predominantly expressedby cells with a supporting role in the CNS, rather thancells with a highly specialized role. Although subtle differences in terms of density and phenotype are beginning to be identified in certain brain regions, microglial
cells are present throughout the nervous system and playa crucial homeostatic role [34–36]. Furthermore, CB2 isknown to be mostly expressed at the periphery by leukocytes, including myeloid monocytes and macrophages [1,37, 38], leading to the hypothesis that microglia may be
one of the main cells expressing CB2 in the CNS.
In the present study, we firstly used MACS to investigate CB2 expression in enriched populations sorted
from adult mouse brain. The MACS technique enabled
to obtain interesting yields needed for downstream transcript analysis, in a short space of time. We showed thatCB2 was expressed in the brain mostly by CD11b-positive microglial cells, and to a lesser extent by neurons,
under basal conditions. This is in agreement with previous measurements in FACS-sorted mouse cortical neurons and microglia [39]. In that study, the difference inCB2 expression between neurons and microglia was evengreater than that observed in the current study, maybe
due to an activation of microglia during the dissociation
and FACS protocol, that might have resulted in induced
CB2 expression.
MACS enrichment, based on the use of a single cellmarker, is not sufficient by itself to distinguish subpopulations present in a heterogeneous population. Having verified that CB2 expression in the neocortex andhippocampus of 10-day-old mice was identical to thatof adult mice, we used data from the analysis of single
nuclei from the cortex of 10-day-old mice to gain a better understanding of how cells expressing CB2-mRNAare distributed in the neocortex. These data indicate
that, under basal conditions, less than 1% of cortical cells
express CB2. Furthermore, this analysis revealed thatmicroglia constituted the cell population with the highest
proportion of CB2-positive cells, in line with our MACS
results obtained in adult mice.
These results provide new insight on cells involvedin physiological and behavioral outcomes observed

Page 11 of 16

following pharmacological activation of CB2 in healthy
mice. Neuronal CB2 may directly modulate behavioral
outcomes [4, 5]. Microglia has been shown to have anindirect role on neuronal activity and in the regulation of
behavioral outcomes [40]. Microglial CB2 may thus be inpart responsible for some outcomes reported at the physiological state.
CB2 expression in activated microglia

Numerous studies have presented CB2 as a molecule totarget in microglial cells/monocytes in different models of pathological conditions to efficiently resolve neuroinflammation [5, 7, 41, 42]. In addition, while CB2transcript level has been found to be increased in many
pathological conditions at the brain tissue level [20, 43–46], it has been speculated that this induction mainly
occurred in microglial cells [20, 45, 47]. We have provided strong evidence that CB2 expression is inversely
regulated by LPS-induced inflammatory state, both attissue level, in microglial cells sorted from brain tissue
and in the BV2 microglial cell line, and is induced during the resolution phase of inflammation, rather than the
inflammatory peak. These results are consistent with the
few studies that have demonstrated that CB2 transcriptlevels are downregulated in microglia cell lines stimulated with LPS [19, 20] or LPS + IFNγ [21, 48]. However,they contrast with the general idea that CB2 is inducedin the brain in many pathological models involving neuroinflammation [7, 9]. One potential explanation is thedistinct nature of the inflammatory stimulus, which,by engaging various intracellular pathways, may lead todifferent effects on the regulation of CB2 expression. A
previous study demonstrated that the stimulation of BV2
cells with IFNγ leads to an opposite regulation of CB2
expression when compared to the effect induced by LPS.
However, the inflammatory responses elicited by LPS andIFNγ were not assessed, rendering it challenging to ascertain whether this discrepancy stemmed from variationsin the intensity of inflammation or the characteristics of
the inflammatory response [20]. LPS mimics non-sterile inflammation by activating the Toll like receptor 4(TLR4) and numerous subsequent intracellular pathways
including NF-κB [49], and IFNγ models sterile inflammation and binds to the interferon-gamma receptor(IFNGR) protein complex, which activates intracellular
JAK/STAT pathways [50]. In this study, we showed that
CB2 transcript levels exhibited an inverse regulation in
BV2 cells when stimulated with a similar dose of LPS and
IFNγ. We demonstrated that BV2 cells exhibited distinct
responses to LPS and IFNγ, with differences in terms ofthe temporal pattern, magnitude, and cytokine profile.
The inflammatory response triggered by IFNγ exhibiteda slower onset, lower magnitude, and did not result inGrabon et al. Journal of Neuroinflammation(2024) 21:206

an upregulation of IL-1β transcript levels. To investigate
whether the substantial decrease in CB2 mRNA levels,
observed exclusively with LPS treatment, was a consequence of potent IL-1R activation by IL-1β, we stimulated BV2 cells with LPS in the presence of the natural
IL-1R antagonist IL-1RA. Interestingly, we observed nodifference in the LPS-induced decrease in CB2 mRNAlevels, suggesting that LPS-induced CB2 downregulation
is not driven by IL-1β. Subsequent investigations are necessary to clarify these mechanisms.
It is worth noting that the upregulation of CB2 transcripts observed in the brain in several experimental
models linked to neuroinflammatory processes could
also be attributed to the infiltration of circulating leukocytes, which are known to exhibit robust CB2 expression [1], into the brain parenchyma. Notably, substantial
upregulation of CB2 at the transcriptional level has been
documented in brain tissue from rodent models of stroke[46], traumatic brain injury [43] or Parkinson’s disease[44, 45], for which strong leukocyte infiltration has beenreported [43, 51–54].

Conclusion
These results represent a significant advance in our
understanding of CB2 expression and the role it mightplay in the CNS, in both physiological and pathological conditions. Our findings highlight the fact that CB2
expression can be differently regulated in distinct inflammatory environments. It is therefore mandatory to measure CB2 expression in each experimental model before
considering pharmacological interventions, with the viewto identifying precise target cells and optimal therapeutic
windows.
Methods
Full details of the methods are given in the supplementary material.
Experimental design

Experiment 1. To assess mRNA level of CB2, CB1,
GPR55 and GPR18 in different mouse strains and brain
regions, brains from adult male Balb/c, C57Bl/6 andSwiss mice (n = 3–4/group) were collected after transcardiac perfusion of saline. Olfactory bulbs, neocortices,
hippocampi, hypothalamus, cerebellum and brainstemfrom 9 mice (3/strain) were microdissected. Ventral limbic regions (comprising the piriform cortex, the amygdala
and the insular agranular cortex), nuclei accumbens, substantia nigra, striatum and ventral tegmental areas weremicrodissected from 12 other mice (4/strain). All microdissections were performed on ice and samples were thenquickly flash-frozen in liquid nitrogen. Transcript levels
were determined by RT-qPCR.

Page 12 of 16

Experiment 2. To validate the efficacy of transcription
and translation inhibitors in limiting ex vivo microglial
cell activation induced during tissue dissociation andmagnetic sorting, the protocol was run in parallel using 3
different buffer conditions applied to all steps of the protocol, from intracardiac perfusion to collection of sorted
cells. Experiment was performed on adult C57Bl/6 malemice (n = 2/buffer condition). Transcript levels of inflammatory genes were determined by RT-qPCR.
Experiment 3. To determine in which brain cell types
CB2 is expressed under physiological state, brains of
C57Bl/6 mice were collected after transcardiac perfusion of the buffer selected in experiment 2 (n = 3). Neocortices and hippocampi were microdissected on ice
and immediately processed for magnetic cell separation.
Transcript levels were determined by RT-qPCR. Furthermore, a single-nucleus database obtained from cortex
tissue collected from 10-day-old mice was used to estimate the proportion of CB2-expressing cells in each cell
population.
Experiment 4. To measure the effect of inflammationon CB2 expression in brain microglia, adult C57Bl/6 mice
were treated intra-peritoneally (IP) with LPS (Escherichia
coli O55:B5, Sigma, L2880) at 5 mg/kg and brains werecollected 3h (n = 5) or 24 h (n = 5) later after transcardiac
perfusion of saline. Mice treated with 0.9% NaCl wereused as controls (n = 4). Neocortices and hippocampi
were microdissected on ice. Transcript levels were determined by RT-qPCR.
Experiment 5. To investigate CB2 expression in microglial cells under physiological and inflammatory condition, murine BV2 cells were cultured with or without
LPS (100 ng/mL) or IFNγ (100 ng/mL) and harvested
1h-24h later for further RT-qPCR analysis (CTRL,
LPS + 1 h, + 2 h, + 4 h: 4 wells/condition; LPS + 8 h, + 24 h:
3 wells/condition; CTRL, IFNγ + 3h, + 8h, + 24h: 3 wells/
condition). To determine the role of IL-1R signaling in
regulating CB2 expression, BV2 cells incubated with LPS(100 ng/mL) were pre-treated for 30 min and co-cultured
for 2 h with IL1-RA, before harvesting and further RTqPCR analysis.
Animals

Adult male mice (Balb/c, C57Bl/6 and Swiss, 8-weeksold, Envigo, France) were used in this study. The experimental procedures were conducted in accordance with
the European Community guidelines for care in animal research and approved by the CELYNE local Ethics
Research Committee (protocol #24302). Every effort wasmade to minimize animal suffering.

Grabon et al. Journal of Neuroinflammation(2024) 21:206

BV2 cell culture

The immortalized murine BV2 cell line (BV2 cells) was
kindly provided by Dr. Nadia Soussi (NeuroDiderot,
Paris University). Cells at passage 9–15 were treated withLPS (from Escherichia coli O55:B5, 100 ng/mL, Sigma#L6529) or with IFNγ (100 ng/mL, Gibco #PMC4031)
for the indicated time, and harvested for further RTqPCR analysis. Blockade of IL-1R was performed using
the recombinant mouse IL1-RA protein (1–1000 mg/mL,
abcam #ab283475).
Reverse transcription and real‑time quantitative PCR

After extraction, total RNAs were reverse transcribed
to complementary DNA (cDNA) using both oligo dT
and random primers with PrimeScript RT Reagent Kit(Takara, #RR037A) according to manufacturer’s instructions in the presence of a synthetic external non-homologous poly(A) standard messenger RNA (SmRNA; A.
Morales and L. Bezin, patent WO2004.092414) to normalize the RT step, as previously described [55]. Each
cDNA of interest was amplified using the Rotor-Gene Q
thermocycler (Qiagen), the SYBR Green PCR kit (Qiagen,#208052) and oligonucleotide primers (Eurogentec) specific to the targeted cDNA. cDNA copy number detected
was determined using a calibration curve, and results
were expressed as cDNA copy number/µg tot RNA.
Pro-inflammatory index (PI-I) was calculated using
a specific set of pro-inflammatory genes: IL-1β, IL-6,
TNFα, COX2, NOS2 and MPC1. For each sample, thenumber of copies of each transcript has been expressedin percent of the averaged number of copies measured in
the whole considered group of samples. Once each transcript was expressed in percent, an index was calculated
by adding the percent of each transcript involved in thecomposition of the index and expressed in arbitrary units(A.U.), using the formula given in the supplementarymaterial.
Brain dissociation and magnetic cell sorting (MACS studies)

To prevent any artifactual ex vivo gene expression
changes during brain dissociation and cell sorting
procedures, all buffers and solutions used during theprocess (from animal perfusion to sorted cells flash
freezing) were supplemented with a cocktail composedof Actinomycin D (3 µM, Tocris #1229/10), Anisomycin(100 µM, Tocris #1290/50) and Triptolide (10 µM, Tocris#3253/10)[18]. All steps were performed on ice or using
pre-chilled refrigerated centrifuge set to 4 °C with all
buffers/solutions pre-chilled before addition to samples
to further limit cell activation. The general workflow ofbrain dissociation and magnetic cell sorting is illustrated
in supplementary data (Fig. S1).

Page 13 of 16

Neocortices and hippocampi were quickly dissected,
cut in smaller pieces and processed for dissociation using
Miltenyi’s Adult Brain Dissociation Kit (#130-107-677)
according to manufacturer’s instruction. To enhance cell
yields, distinct mice were used for the isolation of neurons (n = 3) and for the isolation of the other cell types(microglia, endothelial cells and astrocytes, n = 3). Neurons were enriched using Adult Neuron Isolation Kit(Miltenyi #130-126-602). Endothelial cells, microglia andastrocytes were magnetically sorted successively, using
the anti-Ly-6C biotin antibody (Miltenyi #130-111-914)
and Anti-Biotin MicroBeads (Miltenyi #130-090-485),
the CD11b MicroBeads (Miltenyi #130-093-634), and the
ACSA-2 MicroBeads (Miltenyi #130-097-679), respectively. Sorted cells were counted manually, spun and dry
cell pellets were flash frozen and stored at − 80 °C.
Flow cytometry

To control purity of enriched cell populations, a fraction of cell suspensions was collected before and after
each sorting. The following antibodies were added to cellsuspensions at 1:50 concentration in B2 buffer: ACSA2APC (Miltenyi #130-116-245), CD11b-PE Vio770(Miltenyi #130-113-808), CD31-PE (Miltenyi #130-111540), Ly6C-APC Vio770 (Miltenyi #130-111-919) andO4-VioBright515 (Miltenyi #130-120-102). DAPI (2.5µg/mL, Sigma #D9542) was added as a viability marker
right before flow cytometry analysis. Cells were analyzed
with the BD FACS Canto II Flow Cytometer (Becton–
Dickinson) and data files with FlowJo software V10.7.2(Becton–Dickinson).
Brain dissociation and single nucleus RNAseq (single
nucleus study)
Tissue dissociation

Nuclei from whole cortex were obtained from one mouseat age P10, anesthetized with isoflurane and sacrificed bydecapitation. The dissected cortex tissue was immediately placed in a dry-ice-cold tube for immediate freezing
until processing for nuclei isolation.
Single‑nucleus isolation

Dissected frozen cortex was resuspended and mechanically homogenized using dounce homogeneizer torelease nuclei following the Salty EZ 10 protocol (dx.doi.
org/https://​doi.​org/​10.​17504/​proto ​cols.​io.​bx64p​rgw).
Dissected frozen cortex was resuspended into 600µL of
cold homogenization buffer that consisted of 10 mM Tris
HCl pH 7.5, 146 mM NaCl, 1 mM C
­ aCl2, 21 mM ­MgCl2,
0.03% Tween 20, 0.01% BSA, 10% EZ buffer (Sigma) and
0.2 U/µL Protector RNase Inhibitor (Roche). Tissues

Grabon et al. Journal of Neuroinflammation(2024) 21:206

were then transferred into 2 mL dounce (Kimble) andhomogenized using 10 strokes of the loose pestle followed by 8 strokes of the tight pestle to release nuclei, on
ice. Homogenate was then strained through a 70 μm cellstrainer (Pluriselect) and centrifuged at 500 g for 5 min
to pellet nuclei. After removing supernatant, nuclei were
washed in 1 ml resuspension buffer containing 10 mM
Tris HCl pH 7.5, 10 mM NaCl, 3 mM ­MgCl2, 1% BSA and
0.2 U/µL Protector RNase Inhibitor and centrifuged at
500xg for 5 min. Nuclei were then resuspended in 500µLof resuspension buffer and 5.105 of the best singlet nuclei
were sorted (BD ARIA) based on DAPI intensity before
counting using the LUNA automated cell counter. Nuclei
were finally centrifuged at 500xg for 5 min and diluted inresuspension buffer to a concentration of 1200 nuclei/µl
before encapsulation in 10 × Chromium. All steps werecarried on ice or at 4 °C.
Single‑nucleus capture and sequencing

Single-nuclei capture and sequencing were performed at
the Cancer Genomics Platform of the Cancer ResearchCenter of Lyon (CRCL). Nuclei suspension (1200 nuclei/µL) were loaded onto a Chromium iX (10X Genomics) to capture 10,000 single nuclei. cDNA synthesis andlibrary preparation were done following the manufacturer’s instructions (chemistry V3.1) and library has beensequenced using the Novaseq 6000 (Illumina) to reach
30 k reads per nucleus. Cell Ranger version 6.1.1 (10X
Genomics) was used to align reads on the mouse reference genome gex-mm10-2020-A and to produce thecount matrix.
Single‑nucleus RNA‑seq data analysis

The gene expression matrices from Cell Ranger wereused for downstream analysis using the software R (version 4.1.2) and the R toolkit Seurat (version 4.1.0). Nuclei
were excluded from downstream analysis when they
had more than 3% mitochondrial genes, fewer than 300
unique genes, more than 20,000 unique molecular identifiers (UMIs) and detected as doublets using scdblFinder R
package. A total of 8530 cells were selected. Gene expression was normalized using the standard Seurat workflow and the 2000 most variable genes were identified
and used for principal component analysis (PCA). The
top most significant principal components (PCs) wereselected for generating the UMAP, based on the ElbowPlot method in Seurat. Clustering of cells was obtained
following Seurat graph-based clustering approach withthe default Louvain algorithm for community detection.
We then performed differential expression analysis using

Page 14 of 16

the FindMarkers function of Seurat with the default Wilcoxon rank sum test and annotated clusters based on
expression of marker genes (Fig. S4). We then manuallyannotated the major classes of cells: Neurons, Microglia, Astrocytes, Oligodendrocytes and vascular cells(Fig. 3H-I).
Statistical analysis

Statistical analyses were performed using Prism 10.0
software (GraphPad, USA). Results are presented asmean ± SEM (standard error of the mean). Differences with a p-value < 0.05 (p < 0.05) were considered
to be statistically significant. The Shapiro–Wilk test
and quantile–quantile plot were used to assess normal distribution of the data. For normal data, the statistical significance was assessed by two-tailed t-test or
one-way ANOVA, followed with Tukey’s post-hoc test
for multiple comparisons. For non-normal data, thestatistical significance was assessed by Kruskal–Wallis test, followed with Dunn’s post-hoc test for multiple
comparisons.
Abbreviations
ACSA2	Astrocyte cell surface antigen-2
ActD	Actinomycin D
Anis	Anisomycine
AU	Arbitrary units
BS	Brainstem
CB1	Cannabinoid receptor type 1
CB2	Cannabinoid receptor type 2
CD	Cluster of differentiation
cDNA	Complementary DNA
CNS	Central nervous system
COX2	Cyclooxygenase-2
CTRL	Control
GPR	G protein-coupled receptor
HI	Hippocampus
IFNGR	Interferon-gamma receptor
IFNγ	Interferon-gamma
IL-1RA	Interleukin-1 receptor antagonist
IL	Interleukine
IP	Intra-peritoneally
KO	Knock out
LPS	Lipopolysaccharide
MACS	Magnetic activated cell sorting
MCP1	Monocyte chemoattractant protein 1
mRNA	Messenger ribonucleic acidNAc	Nucleus accumbens
NCX	Neocortex
NOS2	Nitric Oxide Synthase 2OB	Olfactory bulb
PCA	Principal component analysis
PI-I	Pro-inflammatory index
RNAseq	RNA sequencing
RT-qPCR	Reverse transcription quantitative polymerase chain reaction
SEM	Standard error of the mean
SN	Substantia nigra
TLR4	Toll like receptor 4
TNFα	Tumor necrosis factor α
Trip	Triptolide

Grabon et al. Journal of Neuroinflammation(2024) 21:206

UMIs	Unique molecular identifiers
VLR	Ventral limbic region
VTA	Ventral tegmental region

Page 15 of 16

3.

Supplementary Information

4.

The online version contains supplementary material available at https://​doi.​
org/​10.​1186/​s12974-​024-​03202-8.

5.

Additional file 1.
Acknowledgements
We acknowledge the contribution of SFR Santé Lyon-Est (UAR3453 CNRS, US7
Inserm, UCBL) CyLE cytometry platform facilities, especially Thibault Andrieu
and Priscillia Battiston-Montagne for their valuable help. We are grateful foranimal care provided by the zootechnicians of the CRNL’s animal facility.
Author contributions
LB and WG conceived and designed the study. WG, AR, NG, BG, SR, AB and JB
participated in data collection and analysis. GM and CD performed RNAseq
single nucleus experiments and analysis. WG, LB and GM interpreted the data.
WG drafted the manuscript. LB provided critical revisions. All authors read andapproved the final manuscript.
Funding
Nadia Gasmi was granted a PhD fellowship from the Fondation pour la
Recherche Médicale. Wanda Grabon was granted a PhD fellowship from
France Alzheimer.
Availability of data and materials
All data generated or analysed during this study are included in this publishedarticle and its supplementary information files. The single nucleus RNAseq
data for this study have been deposited in the GEO database under the accession number GSE247268.

6.
7.
8.
9.
10.

11.

12.

13.
14.

Declarations
Ethics approval and consent to participate
Not applicable.

15.

Consent for publication
Not applicable.

16.

Competing interests
The authors declare that they have no competing interests.

17.

Author details
1
CNRS UMR5292, Inserm U1028, TIGER Team, Université Claude Bernard Lyon
1, Centre de Recherche en Neurosciences de Lyon, 69500 Bron, France. 2 Epilepsy Institute IDEE, 59 Boulevard Pinel, 69500 Bron, France. 3 CNRS UMR5292,
Inserm U1028, Université Claude Bernard Lyon 1, Centre de Recherche en
Neurosciences de Lyon, GenCyTi Platform, 69500 Bron, France. 4 Cancer
Genomic Platform, Inserm 1052, CNRS 5286, Centre Léon Bérard, Centre deRecherche en Cancérologie de Lyon (CRCL), Université de Lyon, Université
Claude Bernard Lyon 1, 69008 Lyon, France. 5 Université Claude Bernard Lyon 1,
Bioinformatic Platform of the Labex Cortex, 69008 Lyon, France.
Received: 16 January 2024 Accepted: 12 August 2024

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References
1. Galiègue S, Mary S, Marchand J, Dussossoy D, Carrière D, Carayon P,
et al. Expression of central and peripheral cannabinoid receptors inhuman immune tissues and leukocyte subpopulations. Eur J Biochem.
1995;232:54–61.
2. Schatz AR, Lee M, Condie RB, Pulaski JT, Kaminski NE. Cannabinoid
receptors CB1 and CB2: a characterization of expression and adenylate

23.
24.

cyclase modulation within the immune system. Toxicol Appl Pharmacol.
1997;142:278–87.
Turcotte C, Blanchet M-R, Laviolette M, Flamand N. The CB2 receptor andits role as a regulator of inflammation. Cell Mol Life Sci. 2016;73:4449–70.
Jordan CJ, Xi Z-X. Progress in brain cannabinoid CB2 receptor research:from genes to behavior. Neurosci Biobehav Rev. 2019;98:208–20.
Grabon W, Rheims S, Smith J, Bodennec J, Belmeguenai A, Bezin L. CB2
receptor in the CNS: from immune and neuronal modulation to behavior.
Neurosci Biobehav Rev. 2023;150:105226.
Onaivi ES. Editorial: unravelling the role of CB2r in neuropsychiatricdiseases. Front Psychiatry. 2023. https://​doi.​org/​10.​3389/​fpsyt.​2023.​11719​
59.
Komorowska-Müller JA, Schmöle A-C. CB2 receptor in microglia: theguardian of self-control. Int J Mol Sci. 2020. https://​doi.​org/​10.​3390/​ijms2​
20100​19.
Atwood BK, Mackie K. CB2: a cannabinoid receptor with an identity crisis.
Br J Pharmacol. 2010;160:467–79.
Grabon W, Bodennec J, Rheims S, Belmeguenai A, Bezin L. Update on
the controversial identity of cells expressing cnr2 gene in the nervous
system. CNS Neurosci Ther. 2023. https://​doi.​org/​10.​1111/​cns.​13977.
Zhang H, Shen H, Jordan CJ, Liu Q, Gardner EL, Bonci A, et al. CB2 receptor
antibody signal specificity: correlations with the use of partial CB2knockout mice and anti-rat CB2 receptor antibodies. Acta Pharmacol Sin.
2019;40:398–409.
Liu Q-R, Canseco-Alba A, Zhang H-Y, Tagliaferro P, Chung M, Dennis E,
et al. Cannabinoid type 2 receptors in dopamine neurons inhibits psychomotor behaviors, alters anxiety, depression and alcohol preference.
Sci Rep. 2017. https://​doi.​org/​10.​1038/​s41598-​017-​17796-y.
Zhang H-Y, Gao M, Liu Q-R, Bi G-H, Li X, Yang H-J, et al. Cannabinoid CB2 receptors modulate midbrain dopamine neuronal activity
and dopamine-related behavior in mice. Proc Natl Acad Sci U S A.
2014;111:E5007–15.
Onaivi ES, Ishiguro H, Gong J-P, Patel S, Perchuk A, Meozzi PA, et al.
Discovery of the presence and functional expression of cannabinoid CB2
receptors in brain. Ann N Y Acad Sci. 2006;1074:514–36.
Zhang H-Y, Bi G-H, Li X, Li J, Qu H, Zhang S-J, et al. Species differences incannabinoid receptor 2 and receptor responses to cocaine self-administration in mice and rats. Neuropsychopharmacology. 2015;40:1037–51.
Zhang H-Y, De Biase L, Chandra R, Shen H, Liu Q-R, Gardner E, et al.
Repeated cocaine administration upregulates CB2 receptor expression
in striatal medium-spiny neurons that express dopamine D1 receptors inmice. Acta Pharmacol Sin. 2022;43:876–88.
Stempel AV, Stumpf A, Zhang H-Y, Özdoğan T, Pannasch U, Theis A-K, et al.
Cannabinoid type 2 receptors mediate a cell type-specific plasticity in the
hippocampus. Neuron. 2016;90:795–809.
Li Y, Kim J. Neuronal expression of CB2 cannabinoid receptor mRNAs in
the mouse hippocampus. Neuroscience. 2015;311:253–67.
Ocañas SR, Pham KD, Blankenship HE, Machalinski AH, Chucair-Elliott AJ,
Freeman WM. Minimizing the Ex Vivo confounds of cell-isolation techniques on transcriptomic and translatomic profiles of purified microglia.
eNeuro. 2022;9:ENEURO.0348-21.2022.
Carlisle SJ, Marciano-Cabral F, Staab A, Ludwick C, Cabral GA. Differential
expression of the CB2 cannabinoid receptor by rodent macrophages andmacrophage-like cells in relation to cell activation. Int Immunopharmacol. 2002;2:69–82.
Maresz K, Carrier EJ, Ponomarev ED, Hillard CJ, Dittel BN. Modulation of
the cannabinoid CB2 receptor in microglial cells in response to inflammatory stimuli. J Neurochem. 2005;95:437–45.
Schmöle A-C, Lundt R, Ternes S, Albayram Ö, Ulas T, Schultze JL, et al. Cannabinoid receptor 2 deficiency results in reduced neuroinflammation inan Alzheimer’s disease mouse model. Neurobiol Aging. 2015;36:710–9.
Bauermeister K, Burger M, Almanasreh N, Knopf HP, Schumann RR,
Schollmeyer P, et al. Distinct regulation of IL-8 and MCP-1 by LPS andinterferon-gamma-treated human peritoneal macrophages. Nephrol Dial
Transplant. 1998;13:1412–9.
Schroder K, Sweet MJ, Hume DA. Signal integration between IFNγ
and TLR signalling pathways in macrophages. Immunobiology.
2006;211:511–24.
Marsh SE, Walker AJ, Kamath T, Dissing-Olesen L, Hammond TR, deSoysa TY, et al. Dissection of artifactual and confounding glial signatures

Grabon et al. Journal of Neuroinflammation

25.
26.
27.
28.
29.
30.

31.

32.

33.
34.
35.
36.

37.
38.

39.
40.
41.
42.
43.

44.
45.

46.

(2024) 21:206

by single-cell sequencing of mouse and human brain. Nat Neurosci.
2022;25:306–16.
Augusto-Oliveira M, Arrifano GP, Lopes-Araújo A, Santos-Sacramento L,
Takeda PY, Anthony DC, et al. What do microglia really do in healthy adultbrain? Cells. 2019;8:1293.
Paolicelli RC, Sierra A, Stevens B, Tremblay M-E, Aguzzi A, Ajami B, et al.
Microglia states and nomenclature: a field at its crossroads. Neuron.
2022;110:3458–83.
Bensaude O. Inhibiting eukaryotic transcription. Which compound tochoose? How to evaluate its activity? Transcription. 2011;2:103–8.
Grollman AP. Inhibitors of protein biosynthesis: II. Mode of action of
Anisomycin. J Biol Chem. 1967;242:3226–33.
Kruk-Slomka M, Dzik A, Biala G. The influence of CB2-receptor ligands onthe memory-related responses in connection with cholinergic pathways
in mice in the passive avoidance test. Molecules. 2022;27:4252.
García-Gutiérrez MS, Ortega-Álvaro A, Busquets-García A, Pérez-Ortiz JM,
Caltana L, Ricatti MJ, et al. Synaptic plasticity alterations associated withmemory impairment induced by deletion of CB2 cannabinoid receptors.
Neuropharmacology. 2013;73:388–96.
Onaivi ES, Ishiguro H, Gong J-P, Patel S, Meozzi PA, Myers L, et al. Brainneuronal CB2 cannabinoid receptors in drug abuse and depression: frommice to human subjects. PLoS ONE. 2008. https://​doi.​org/​10.​1371/​journ​al.​pone.​00016​40.
Cortez IL, Silva NR, Rodrigues NS, Pedrazzi JFC, Del Bel EA, Mechoulam
R, et al. HU-910, a CB2 receptor agonist, reverses behavioral changes inpharmacological rodent models for schizophrenia. Prog Neuropsychopharmacol Biol Psychiatry. 2022;117:110553.
Grenald SA, Young MA, Wang Y, Ossipov MH, Ibrahim MM, Largent-Milnes
TM, et al. Synergistic attenuation of chronic pain using mu opioid andcannabinoid receptor 2 agonists. Neuropharmacology. 2017;116:59–70.
Bridlance C, Thion MS. Multifaceted microglia during brain development:
models and tools. Front Neurosci. 2023. https://​doi.​org/​10.​3389/​fnins.​
2023.​11257​29.
Tan Y-L, Yuan Y, Tian L. Microglial regional heterogeneity and its role in thebrain. Mol Psychiatry. 2020;25:351–67.
Dos Santos SE, Medeiros M, Porfirio J, Tavares W, Pessôa L, Grinberg
L, et al. Similar microglial cell densities across brain structures andmammalian species: implications for brain tissue function. J Neurosci.
2020;40:4622–43.
Munro S, Thomas KL, Abu-Shaar M. Molecular characterization of aperipheral receptor for cannabinoids. Nature. 1993;365:61–5.
Graham ES, Angel CE, Schwarcz LE, Dunbar PR, Glass M. Detailed
characterisation of CB2 receptor protein expression in peripheral blood
immune cells from healthy human volunteers using flow cytometry. Int J
Immunopathol Pharmacol. 2010;23:25–34.
Liu Q-R, Canseco-Alba A, Liang Y, Ishiguro H, Onaivi ES. Low basal CB2R in
dopamine neurons and microglia influences cannabinoid tetrad effects.
Int J Mol Sci. 2020;21:9763.
Wake H, Moorhouse AJ, Nabekura J. Functions of microglia in the central
nervous system—beyond the immune response. Neuron Glia Biol.
2011;7:47–53.
Ashton JC, Glass M. The Cannabinoid CB2 receptor as a target for
inflammation-dependent neurodegeneration. Curr Neuropharmacol.
2007;5:73–80.
Cabral GA, Raborn ES, Griffin L, Dennis J, Marciano-Cabral F. CB2 receptors in the brain: role in central immune function. Br J Pharmacol.
2008;153:240–51.
Braun M, Khan ZT, Khan MB, Kumar M, Ward A, Achyut BR, et al. Selective
activation of cannabinoid receptor-2 reduces neuroinflammation after
traumatic brain injury via alternative macrophage polarization. Brain
Behav Immun. 2018;68:224–37.
Concannon RM, Okine BN, Finn DP, Dowd E. Differential upregulation of
the cannabinoid CB2 receptor in neurotoxic and inflammation-driven rat
models of Parkinson’s disease. Exp Neurol. 2015;269:133–41.
Gómez-Gálvez Y, Palomo-Garo C, Fernández-Ruiz J, García C. Potentialof the cannabinoid CB2 receptor as a pharmacological target against
inflammation in Parkinson’s disease. Prog Neuropsychopharmacol Biol
Psychiatry. 2016;64:200–8.
Zarruk JG, Fernández-López D, García-Yébenes I, García-Gutiérrez MS,
Vivancos J, Nombela F, et al. Cannabinoid type 2 receptor activation
downregulates stroke-induced classic and alternative brain macrophage/

Page 16 of 16

47.

48.
49.
50.
51.
52.
53.
54.
55.

microglial activation concomitant to neuroprotection. Stroke.
2012;43:211–9.
Ashton JC, Rahman RMA, Nair SM, Sutherland BA, Glass M, Appleton I.
Cerebral hypoxia-ischemia and middle cerebral artery occlusion induce
expression of the cannabinoid CB2 receptor in the brain. Neurosci Lett.
2007;412:114–7.
Young AP, Denovan-Wright EM. Synthetic cannabinoids reduce theinflammatory activity of microglia and subsequently improve neuronalsurvival in vitro. Brain Behav Immun. 2022;105:29–43.
Lu Y-C, Yeh W-C, Ohashi PS. LPS/TLR4 signal transduction pathway.
Cytokine. 2008;42:145–51.
Schroder K, Hertzog PJ, Ravasi T, Hume DA. Interferon-gamma: an overview of signals, mechanisms and functions. J Leukoc Biol. 2004;75:163–89.
Alam A, Thelin EP, Tajsic T, Khan DZ, Khellaf A, Patani R, et al. Cellular
infiltration in traumatic brain injury. J Neuroinflammation. 2020;17:328.
Gao L, Brenner D, Llorens-Bobadilla E, Saiz-Castro G, Frank T, Wieghofer P,
et al. Infiltration of circulating myeloid cells through CD95L contributes toneurodegeneration in mice. J Exp Med. 2015;212:469–80.
Kronenberg G, Uhlemann R, Richter N, Klempin F, Wegner S, Staerck L,
et al. Distinguishing features of microglia- and monocyte-derived macrophages after stroke. Acta Neuropathol. 2018;135:551–68.
Rajan WD, Wojtas B, Gielniewski B, Gieryng A, Zawadzka M, Kaminska B.
Dissecting functional phenotypes of microglia and macrophages in the
rat brain after transient cerebral ischemia. Glia. 2019;67:232–45.
Morales A, Bonnet C, Bourgoin N, Touvier T, Nadam J, Laglaine A, et al.
Unexpected expression of orexin-B in basal conditions and increased
levels in the adult rat hippocampus during pilocarpine-induced epileptogenesis. Brain Res. 2006;1109:164–75.

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