Ayten et al. Journal of Neuroinflammation(2024) 21:190
https://doi.org/10.1186/s12974-024-03175-8

Journal of Neuroinflammation

Open Access

RESEARCH

CD44 signaling in Müller cells impacts
photoreceptor function and survival
in healthy and diseased retinas
Monika Ayten1, Tobias Straub2, Lew Kaplan3, Stefanie M. Hauck4, Antje Grosche3 and Susanne F. Koch1*
Abstract
Retinitis pigmentosa (RP), an inherited retinal disease, affects 1,5 million people worldwide. The initial mutationdriven photoreceptor degeneration leads to chronic inflammation, characterized by Müller cell activation andupregulation of CD44. CD44 is a cell surface transmembrane glycoprotein and the primary receptor for hyaluronic
acid. It is involved in many pathological processes, but little is known about CD44’s retinal functions. CD44
expression is also increased in Müller cells from our Pde6bSTOP/STOP RP mouse model. To gain a more detailed
understanding of CD44’s role in healthy and diseased retinas, we analyzed Cd44−/− and Cd44−/−Pde6bSTOP/STOP
mice, respectively. The loss of CD44 led to enhanced photoreceptor degeneration, reduced retinal function, andincreased inflammatory response. To understand the underlying mechanism, we performed proteomic analysis on
isolated Müller cells from Cd44−/− and Cd44−/−Pde6bSTOP/STOP retinas and identified a significant downregulation of
glutamate transporter 1 (SLC1A2). This downregulation was accompanied by higher glutamate levels, suggesting
impaired glutamate homeostasis. These novel findings indicate that CD44 stimulates glutamate uptake via SLC1A2
in Müller cells, which in turn, supports photoreceptor survival and function.
Keywords CD44, Glutamate, Retinitis pigmentosa, SLC1A2, Müller cells, Gliosis, Inflammation*Correspondence:
Susanne F. Koch
Susanne.Koch@cup.uni-muenchen.de1
Department of Pharmacy, Center for Drug Research, LudwigMaximilians-Universität München, Munich 81377, Germany
2
Bioinformatics Unit, Biomedical Center Munich, Ludwig-MaximiliansUniversität München, Planegg-Martinsried 82152, Germany
3
Department of Physiological Genomics, Biomedical Center Munich,Ludwig-Maximilians-Universität München, Planegg-Martinsried
82152, Germany
4
Metabolomics and Proteomics Core, Helmholtz Zentrum München,
German Research Center for Environmental Health, Neuherberg,
Germany

Introduction
Müller cells, the main support cells in the retina, spanthe entire thickness of the tissue and envelop all retinal
neurons. Thus, Müller cells are positioned to fulfill multiple functions essential for neuronal well-being [1]. For
example, they provide metabolic support to photoreceptors, regulate retinal blood flow, and they contribute toneuronal signaling by uptake and recycling of glutamate[2–4]. In addition, Müller cells express attachment points
for the interphotoreceptor matrix, a highly organizedstructure between the photoreceptors and the retinal
pigment epithelium (RPE) [5]. An important attachment
point is the hyaluronic acid (HA)-binding motif CD44, atransmembrane glycoprotein localized in the microvilli
of Müller cells [5–9].

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Ayten et al. Journal of Neuroinflammation(2024) 21:190

CD44 is found in a variety of tissues, including thecentral nervous system, lung, epidermis, liver, pancreas,
hematopoietic and lymphatic system [10, 11]; in the lymphatic system, CD44 has been shown to play crucial roles
in T-cell differentiation in the thymus [12] and migrationof lymphocytes to lymph nodes [13, 14]. CD44 is also
involved in many pathological processes such as inflammation, immune responses, wound healing, cancer progression, and epigenetic plasticity in tumors [15, 16].
Despite the many roles described to CD44, little is known
about its function in the healthy and diseased retina.
In retinitis pigmentosa (RP), CD44 was found to bedramatically upregulated [17]. For example, in the retinal degeneration slow (rds) mouse [18] and in the Royal
College of Surgeons (RCS) rat model [19], CD44 wasincreased in Müller cells. Increased CD44 expression in
microglia was observed in the Cngb1-knockout mousemodel by FACS [20]. RP is a group of retinal degenerative diseases manifesting in adolescence or early adulthood, and the most common cause of inherited blindness[21–23]. Patients with RP initially experience night blindness, followed by a gradual narrowing of the visual field
and, ultimately, loss of daylight vision. This progressive
loss of vision occurs in parallel with the progressive lossof photoreceptor cells. The photoreceptor degeneration
activates Müller cells – a process, known as Müller cell
gliosis, marked by upregulation of glial fibrillary acidic
protein (GFAP) [24, 25].
Given the key roles played by Müller cells in healthy
retina, and the changes they undergo in many retinaldegenerative diseases [26–28], it is important to understand their role in RP pathogenesis. Here, we study theeffect of CD44 signaling on retinal morphology in healthyand diseased retinas. Using our RP Pde6bSTOP/STOP mousemodel, we confirmed that CD44 expression is upregulated in Müller cells. Interestingly, when we crossed ourRP mice with Cd44-/- mice, we discovered that retinas
exhibited significantly faster photoreceptor degeneration,
decreased retinal function, increased glutamate levels,
and, in Müller cells, decreased expression of glutamate
transporter Slc1a2. This work suggests a role of CD44 inglutamate homeostasis and emphasizes the significanceof CD44 for retinal integrity and function, both in healthyand diseased conditions.

Results
Upregulation of CD44 in Müller cells from RP mousemodelsMüller cells upregulate CD44 in response to photoreceptor degeneration in the retinal degeneration slow(rds) mouse [18]. To evaluate whether CD44 is also
upregulated in other RP mouse models, we first analyzed
CD44 expression levels in retinas from Pde6bSTOP/STOP(ST/ST) mice by RT-qPCR, immunohistochemistry, andPage 2 of 16

immunoblot. These mice contain a floxed stop cassettein both Pde6b alleles that prevents PDE6B expression(Fig. S1A), leading to progressive photoreceptor degeneration [29]. To understand whether there is an association
between CD44 expression and photoreceptor degeneration, we analyzed retinas at 4- and 8-weeks of age (i.e., atearly- and mid-disease stage). In ST/ST retinas (vs. agematched Pde6bSTOP/WT (ST/WT) control), Cd44 mRNAwas significantly upregulated at 8 weeks of age (P ≤ .001)(Fig. 1A). Next, we analyzed retinal sections that wereco-immunostained for glutamine synthetase (GLUL) to
visualize Müller cells and CD44. In line with previous
studies [30, 31], CD44 was expressed in Müller cells, andparticularly localized to the apical microvilli of Müller
cells (Fig. 1B and S1B). Notably, in ST/ST retinas, CD44
expression was enhanced in the microvilli of Müller cells
compared to ST/WT controls (Fig. 1B). The microvilli
extend into the subretinal space between the inner segments of photoreceptors, but are not in contact withrod photoreceptor outer segments (Fig. S1C). To further validate CD44 upregulation in ST/ST compared to
ST/WT retinas, immunoblotting was performed(Fig. 1C). The immunoblot quantification demonstrated
that CD44 protein expression showed a trend of upregulation at 4 weeks (P = .1) and was significantly upregulated at 8 weeks (P ≤ .001) (Fig. 1D). These data suggest
an association between CD44 expression level and photoreceptor degeneration – the highest level of CD44 wasdetected in 8-week-old ST/ST retinas (i.e., in the retina
with the most extensive degeneration). Since CD44 isexpressed in reactive microglia cells from Cngb1-knockout retinas [20] and from retinas following endotoxin
induced uveitis [32], we analyzed retinal sections and retinal flatmounts from 12-week-old ST/ST mice that wereco-immunostained for IBA1 to visualize microglia/macrophages and CD44. At 12-weeks of age, microglia cells
have migrated into the ONL (Fig. S1D). CD44 is highly
expressed in the microvilli of Müller cells but appears
not to be expressed in microglia/macrophages (Fig.
S1D/E). To further confirm the cell-type specific expression pattern of CD44, we analyzed previously publishedsingle-cell RNA sequencing (scRNAseq) mouse datafrom control and light-damaged retinas [33]. These data
showed CD44 expression in Müller cells but not in otherretinal cells. In line with our findings, CD44 expression
was increased in light-damaged retinas (Fig. S1F).
Next, we analyzed CD44 expression in retinas from 3other retinal degeneration mouse models by immunohistochemistry and immunoblot. We investigated anotherautosomal recessive RP mouse model caused by a missense mutation in the Pde6b gene (Pde6bH620Q/H620Q)[34], an autosomal dominant RP mouse model caused by
a mutation in the rhodopsin gene (RhoP23H/+) [35], andCnga3−/−, Rho−/−, Opn4−/− triple-knockout mice [36, 37].

Ayten et al. Journal of Neuroinflammation(2024) 21:190

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Fig. 1 Progressive photoreceptor degeneration results in upregulation of CD44 expression in Müller cells. (A-D) Retinas from Pde6bSTOP/WT (ST/WT) andPde6bSTOP/STOP (ST/ST) mice were analyzed at 4 and 8 weeks of age. Expression of CD44 increases with disease progression. (A) Quantitative analysis of
Cd44 mRNA by qRT-PCR. N = 3 per group. (B) Representative images of retinal sections immunostained for glutamine synthetase (GLUL) to visualize Müller cells and for CD44. CD44 is mainly expressed in the apical microvilli of Müller cells. Scale bar, 30 μm. (C) Representative CD44 immunoblot of retinal
lysates. β-Actin was used as a loading control. (D) Quantitative analysis of CD44 immunoblots. N = 4 per group. (A, D) Data, presented as mean ± SEM, werecompared by ANOVA. *** P ≤ .001. (E-G) Retinas from 3 retinal degeneration mouse models were analyzed: Pde6bH620Q/H620Q (week 4), RhoP23H/+ (week 9) ,and Cnga3−/−, Rho−/−, Opn4−/− triple-knockout mice (week 5). (Upper panel) Representative images of retinal sections immunostained for CD44. Scalebar, 30 μm. (Lower panel) Representative CD44 immunoblots of retinal lysates. β-Actin was used as a loading control. ONL, outer nuclear layer; INL, inner
nuclear layer; GCL, ganglion cell layer

CD44 was highly expressed in all 3 other retinal degeneration mouse models (Fig. 1E-G), suggesting that photoreceptor degeneration, independent of the genetic cause,leads to upregulation of CD44 expression in Müller cells.
Loss of CD44 does not affect GFAP expression levels

After confirmation that CD44 is expressed in Müller
cells in the retina (Fig. 1B, Fig. S1B-F), we utilized a commercially available CD44 global knockout mouse line
(Cd44−/−) and crossed it with our Pde6bSTOP mouse line.

This crossbreeding strategy yielded Cd44−/−Pde6bSTOP/WT(CD44−/− ST/WT) and Cd44/−Pde6bSTOP/STOP (CD44−/−
ST/ST) mice. Incorporating CD44−/− ST/WT mice
into our study allowed us to study the impact of CD44
loss on normal retinal morphology, while the analysis ofCD44−/− ST/ST mice provided insight into the role ofCD44 in RP. We first confirmed that CD44 is absent in
retinas from 8-week-old CD44−/− ST/WT and CD44− /−ST/ST mice by RT-qPCR (Fig. 2A), immunohistochemistry (Fig. 2B), and immunoblot (Fig. 2C). In line with

Ayten et al. Journal of Neuroinflammation(2024) 21:190

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Fig. 2 Absence of CD44 does not affect GFAP expression levels. Retinas from Pde6bSTOP/WT (ST/WT), Cd44−/−Pde6bSTOP/WT(CD44−/− ST/WT), Pde6bSTOP/STOP(ST/ST), and Cd44−/−Pde6bSTOP/STOP (CD44−/− ST/ST) mice were analyzed at 8 weeks of age. (A) Quantitative analysis of Cd44 mRNA by qRT-PCR. (B) Representative images of retinal sections immunostained for CD44. Scale bar, 30 μm. (C) Representative CD44 immunoblot of retinal lysates. β-Actin wasused as a loading control. (D) Quantitative analysis of Gfap mRNA by qRT-PCR. (A, D) N = 4 per group. Data, presented as mean ± SEM, were compared by
ANOVA. * P ≤ .05; *** P ≤ .001. (E) Representative images of retinal sections immunostained for GLUL and GFAP. Scale bar, 25 μm (F) Representative GFAP
immunoblot of retinal lysates. β-Actin was used as a loading control. ONL, outer nuclear layer; INL, inner nuclear layer; GCL, ganglion cell layer

previous experiments (Fig. 1A-D), CD44 was upregulated in ST/ST retinas compared to ST/WT on both
RNA (ANOVA, *** P ≤ .001) and protein level (Fig. 2A-C).
Since Müller cells also upregulate glial fibrillary acidic
protein (GFAP) in response to photoreceptor degeneration [28], we examined GFAP expression at 8 weeks of age
in CD44−/− ST/WT and CD44− /−ST/ST mice compared
to ST/WT and ST/ST mice, respectively (Fig. 2D-F). As
expected, the mRNA levels of Gfap were upregulated inboth ST/ST and CD44/− ST/ST retinas (P ≤ .05) (vs. agematched ST/WT and CD44−/−ST/WT, respectively).
On the other hand, Gfap was neither different between
ST/WT and CD44−/− ST/WT mice nor between ST/ST
and CD44/− ST/ST mice (Fig. 2D). In retinal sections
from ST/WT and CD44−/− ST/WT mice, GFAP immunoreactivity was limited to the ganglion cell layer. In
ST/ST and CD44−/− ST/ST mice, some radially oriented
stress fibers were immunolabeled (Fig. 2E). Immunoblotting confirmed increased GFAP expression in ST/ST and
CD44−/− ST/ST mice (Fig. 2F). These data show that lossof CD44 does not alter GFAP expression.
Since CD44 is the transmembrane receptor for hyaluronic acid (HA) [38], we next quantitatively measured the HA concentration in retinal lysates at 4 and 8
weeks of age using an HA ELISA assay (Fig.S2). Interestingly, HA was significantly upregulated in 8-weekold CD44−/− ST/WT retinas compared to ST/WT, with

HA concentrations measuring 95 ± 23 (SEM) ng/ml and
16 ± 1.2 ng/ml, respectively (ANOVA, P = .025). There
were no significant differences between the two groups
at 4 weeks of age, which might be due to low statisticalpower (low sample size and variation within the sample).
The HA levels in ST/ST retinas were 89 ± 12 ng/ml and
58 ± 20 ng/ml at 4 and 8 weeks of age, respectively, andappear to be higher compared to age-matched ST/WT;
however, these differences are not statistically significant(ANOVA, P = .2 and P = .3).
Loss of CD44 contributes to photoreceptor degeneration
and rod bipolar remodeling

To analyze the effect of CD44 on retinal morphology
and disease progression, we analyzed morphologicalchanges in photoreceptors and inner retinal neurons inretinal sections (Fig. 3). Cone arrestin (ARR3) was used
to visualize cone photoreceptors (Fig. 3A). To quantify
photoreceptor degeneration, outer nuclear layer (ONL)
thickness was measured at 3, 4, 8, and 12 weeks of age.
At 3 weeks of age, the ONL thickness of ST/WT and
CD44−/− ST/WT retinas were 65 μm ± 4.0 (SEM) µm
and 67 μm ± 2.1 μm, respectively. The mean ONL thickness was not significantly different between the twogroups, indicating that CD44 does not affect photoreceptor number before postnatal week 3 (Fig. 3B, left panel).
At 4 weeks of age, ONL thickness of ST/WT retinas

Ayten et al. Journal of Neuroinflammation(2024) 21:190

Fig. 3 (See legend on next page.)

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Ayten et al. Journal of Neuroinflammation(2024) 21:190

Page 6 of 16(See figure on previous page.)
Fig. 3 Progression of photoreceptor degeneration and inner retinal remodeling in CD44-deficient mice. Retinas from ST/WT, CD44−/− ST/WT, ST/ST, andCD44−/− ST/ST mice were analyzed. (A) Representative images of retinal sections from 12-week-old mice immunostained for ARR3 (cones). Scale bar,
25 μm. (B) ONL thickness and cone inner and outer segment length at 3, 4, 8, and 12 weeks of age. pw 3, N = 5 per group. pw 4, N = 6 per group. pw 8,
N = 5 for ST/WT, and ST/ST, N = 7 for CD44−/− ST/WT, N = 6 for CD44−/− ST/ST. pw 12, N = 8 for ST/WT, N = 6 for CD44/− ST/WT, and CD44−/− ST/ST, N = 5 for
ST/ST. (C, E, G) Representative images of retinal sections from 12-week-old mice immunostained for PKC–α (rod bipolar cells) (C), SCGN (cone bipolarcells) (E), and calbindin (horizontal cells) (G). Arrowheads indicate shorter and less-branched bipolar dendrites. Scale bars, 25 μm. (D, F, H) Quantificationof dendritic area from rod bipolar cells (D), cone bipolar cells (F), and horizontal cells (H). pw 12, N = 6 for ST/WT, CD44−/− ST/WT, and CD44−/− ST/ST, N = 7
for ST/ST. Data, presented as mean ± SEM, were compared by ANOVA. * P ≤ .05; ** P ≤ .01; *** P ≤ .001. ONL, outer nuclear layer; INL, inner nuclear layer; IS,inner segment; OS, outer segment; OPL, outer plexiform layer; IPL, inner plexiform layer

was slightly decreased to 59 μm ± 2.8 μm due to normal
programmed cell death associated with neuronal differentiation and maturation [39, 40] (Fig. 3B, left panel).
In CD44−/− ST/WT mice, the ONL thickness decreased
to 50 μm ± 1.9 μm (ANOVA, P ≤ .05; vs. age-matched
ST/WT control). These data suggest an additional CD44related photoreceptor cell death. Between weeks 4 and12, the ONL thickness was stable in both ST/WT and
CD44−/− ST/WT retinas. In contrast, in 3-week-old
ST/ST and CD44−/− ST/ST mice, the ONL thickness was
51 μm ± 1.8 μm and 60 μm ± 2.1 μm, respectively, and progressively became thinner over time. At 12 weeks of age,
the ONL thickness of ST/ST and CD44−/−- ST/ST retinas
were 17 μm ± 0.8 μm and 11 μm ± 0.8 μm, respectively(ANOVA, P = .03) (Fig. 3B, left panel). For a comprehensive histological examination, retinal sections from 3-,4-, 8-, and 12-week-old mice were analyzed using hematoxylin and eosin staining (Fig. S3A). At 3 weeks of age,
the retinal morphology was similar between the different groups, suggesting that photoreceptor cells develop
normally. At 4, 8, and 12 weeks of age, the ONL thickness from CD44−/− ST/WT retinas appeared somewhat
reduced compared to age-matched ST/WT. In ST/ST
and CD44−/− ST/ST mice, photoreceptors degenerated
over time, reflected by a progressive decrease in ONL
thickness. Consistent with Fig. 3B, the ONL thickness in
CD44−/− ST/ST retinas appeared thinner compared to
ST/ST retinas at weeks 4, 8, and 12 (Fig. S3A). We next
quantified ONL thickness at multiple positions across a
2000-µm length of the central retina at 3 and 8 weeks ofage for all groups (Fig. S3B). At 3 weeks of age, no significant differences were observed between the groups.
In line with Fig. 3B, at 8 weeks of age, the ONL thickness
was reduced in ST/ST and CD44−/−ST/ST compared to
ST/WT and CD44−/− ST/WT, respectively.
We next analyzed the effect of CD44 loss on cone outer
segments. At 3 weeks of age, the cone inner segment (IS)and outer segment (OS) length of ST/WT and CD44−/−
ST/WT mice was 21 μm ± 0.3 μm and 22 μm ± 0.7 μm,
respectively. The mean cone IS and OS length was not significantly different between the two groups, suggesting that
CD44 does not affect cone outer segment development.
At 4 weeks of age, cone IS and OS length of ST/WT retinas increased to 27 μm ± 0.8 μm. In contrast, in CD44−/−
ST/WT mice, the cone IS and OS length was

19 μm ± 0.9 μm (ANOVA, P ≤ .001; vs. age-matched
ST/WT control). There was a significant increase to
25 μm ± 1 μm in cone IS and OS length at 8 weeks(ANOVA, P ≤ .001; week 4 vs. week 8 in CD44−/− ST/WTmice), even if the ST/WT cone IS and OS length was notreached. At 8 and 12 weeks of age, the cone IS and OS
lengths were significantly reduced in CD44−/− ST/WT
mice compared to ST/WT (ANOVA, P ≤ .05). In ST/ST
and CD44−/− ST/ST mice, the cone IS and OS length progressively degenerated over time (Fig. 3B, right panel).
Photoreceptor degeneration is accompanied bychanges in downstream neurons [41]. To evaluate
the effect of CD44 loss on rod bipolar, cone bipolar,
and horizontal neurons, we visualized these cells by
immunostaining for protein kinase c alpha (PKC-α),
secretagogin(SCGN),andcalbindin,respectively.InCD44−/−
ST/WT retinas, rod bipolar cell dendrites were shorterand less bushy (vs. age-matched ST/WT control). In
ST/ST and CD44−/−ST/ST retinas, the retraction of rod
bipolar cell dendrites was further progressed (Fig. 3C).
We next quantified the observed changes in rod bipolar cell dendrites. In CD44−/−ST/WT mice, the dendrite
area was significantly reduced compared with ST/WT
mice (ANOVA, * P ≤ .05). In ST/ST and CD44−/−ST/ST
mice, the dendritic area was also significantly reduced
compared to age-matched ST/WT and CD44−/−
ST/WT mice, respectively (ANOVA, * P ≤ .05). There wasno significant difference between CD44−/− ST/ST and
ST/ST mice. (Fig. 3D). Cone bipolar cell dendrites weresimilar between CD44−/− ST/WT and ST/WT retinas.
In ST/ST and CD44−/− ST/ST retinas, the cone bipolarcell dendrites were modestly retracted (Fig. 3E). We next
quantified the observed changes in cone bipolar cell dendrites. In ST/ST and CD44−/− ST/ST mice, the dendritic
area was significantly reduced compared to age-matched
ST/WT and CD44−/− ST/WT mice, respectively(ANOVA, * P ≤ .05). There were no significant differences between CD44−/− ST/WT and ST/WT retinas
as well as between CD44−/− ST/ST and ST/ST retinas(Fig. 3F). In CD44−/− ST/WT and ST/WT retinas, horizontal cell processes were bushy. In ST/ST and CD44−/−
ST/ST retinas, the horizontal cell processes wereretracted (Fig. 3G). We next quantified the observedchanges in horizontal cell processes. In ST/ST and
CD44−/− ST/ST mice, the area was significantly reduced

Ayten et al. Journal of Neuroinflammation(2024) 21:190

compared to age-matched ST/WT and CD44−/−
ST/WT mice, respectively (ANOVA, *** P ≤ .001). There
were no significant differences between CD44−/− ST/WT
and CD44−/− ST/ST retinas compared to ST/WT and
ST/ST retinas, respectively (Fig. 3H). In conclusion, lossof CD44 results in a slight decrease in ONL thickness,cone IS and OS length, and dendritic retraction of rod
bipolar neurons.
Loss of CD44 impairs scotopic and mesopic retinal function

To test whether CD44 impacts retinal function, fullfield single-flash electroretinography (ERG) responses
were recorded in 8-week-old mice. In CD44−/− ST/WT
mice (vs. age-matched ST/WT control), the a-wave

Page 7 of 16(negative deflection), generated by photoreceptor cells,
was significantly decreased at light intensities of 0.5
and 1.0 log (cd*s/m2) (P ≤ .001). In both CD44−/− ST/ST
and ST/ST mice (vs. age-matched CD44−/− ST/WT and
ST/WT, respectively), the a-wave was reduced (Fig. 4A,
C). The a-wave of CD44−/− ST/ST mice was significantly smaller compared to ST/ST mice at lightintensities of 0.5 and 1.0 log (cd*s/m2) (Fig. 4A). In CD44−/−
ST/WT mice, the b-wave amplitude (positive deflection),
generated by bipolar cells, was significantly decreased
at a light intensity of 1.0 log (cd*s/m2) compared to
ST/WT mice (ANOVA, P = .03). The b-wave amplitudesof CD44−/− ST/ST mice were not significantly decreased
at all light intensities compared to ST/ST mice (Fig. 4B).

Fig. 4 Decreased scotopic and mesopic retinal function in CD44-deficient mice. (A-E) ERGs were recorded from 8-week-old ST/WT, CD44−/− ST/WT,
ST/ST, and CD44−/− ST/ST mice. (A) Scotopic and mesopic a-wave amplitudes. A-wave amplitudes of CD44−/− ST/WT and CD44−/− ST/ST at 0.5 and 1.0 log(cd*s/m2) were significantly decreased compared to ST/WT and ST/ST, respectively. (B) Scotopic and mesopic b-wave amplitudes. At the highest measured light intensity of 1.0 log (cd*s/m2), the b-wave amplitude of CD44−/− ST/WT mice was significantly decreased compared to ST/WT mice. (C) Representative ERG responses in the scotopic and mesopic range. (D) Photopic b-wave amplitudes. B-wave amplitudes were similar between all groups. (A, B,
D) Data, presented as mean ± SEM, were compared by ANOVA, * P < .05; ** P < .01. N = 7 per group. (E) Representative ERG responses in the photopic range

Ayten et al. Journal of Neuroinflammation(2024) 21:190

After light-adaption, to derive cone-response, the b-wave
amplitude was measured. There was no significant difference between the groups. ERG recordings of 8-week-old
ST/WT, CD44−/− ST/WT, ST/ST, and CD44−/− ST/ST
mice showed an increase in the b-wave amplitude witheach increased intensity (Fig. 4D, E). In summary, theabsence of CD44 leads to a decreased scotopic and mesopic ERG response.
Loss of CD44 results in downregulation of the SLC1A2
glutamate transporter in Müller cells

Since Müller cells make up only a small fraction of cells in
the murine retina [42], proteomic studies of whole retinas
cannot provide Müller cell-specific information. Therefore, to identify proteins dysregulated in Müller cells, we
performed proteomic analysis on Müller cells and neurons isolated from 8-week-old ST/WT, ST/ST, CD44−/−
ST/WT, and CD44−/−ST/ST retinas using a multistep
magnetic-activated cell sorting (MACS) procedure. To
assess the purity and morphology, freshly isolated Müller cells and neurons were immunostained for GLUL
and Recoverin, respectively. Almost all of the cells weredouble positive for Hoechst and the cell type-specificantibody GLUL or Recoverin (Fig. 5A, B), demonstrating
the high purity of the respective fractions. Importantly,
isolated Müller cells retained their characteristic polarmorphology (Fig. 5A, insert).
The label-free quantitative LC-MS/MS-based proteomic analysis revealed a total of approximately 5200
different proteins in both the Müller cell and neuronalfraction. To assess the quality of both the proteomic data
and the MACS, we quantitatively compared the abundance of GLUL, Rhodopsin (RHO), CD44, and PDE6B
across the 4 groups and the two cell fractions (Fig. 5C-F).
GLUL, a Müller cell marker, was highly expressed in Müller cells of all groups and reduced in neurons (Fig. 5C).
Rhodopsin (RHO), a rod photoreceptor marker, washighly expressed in neurons and reduced in Müller cells(Fig. 5D). RHO expression was highest in neurons from
ST/WT and CD44−/− ST/WT mice and slightly reduced
in ST/ST and CD44−/− ST/ST mice because of the diminished number of rods. PDE6B was highly expressed inneurons from ST/WT and CD44−/− ST/WT mice andabsent in neurons from ST/ST and CD44−/− ST/ST mice,
confirming the loss of PDE6B. PDE6B was not detectedin Müller cells (Fig. 5E). CD44 was expressed in Müller cells from ST/WT, increased in Müller cells from
ST/ST mice and absent in Müller cells from CD44−/−
ST/WT and CD44−/− ST/ST mice, confirming on the one
hand the upregulation of CD44 in ST/ST retinas and on
the other hand the loss of CD44 in CD44−/− ST/WT and
CD44−/− ST/ST retinas. CD44 was not detected in neurons (Fig. 5F).

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A volcano plot was used to visualize proteins withstatistical differences in expression (adj. P-value < 0.5)
between ST/ST and CD44−/− ST/ST Müller cells. Solute carrier family 1 member 2 (SLC1A2), also known as
excitatory amino acid transporter 2 (EAAT2) or glutamate transporter 1 (GLT-1) [43], was significantly downregulated in Müller cells from CD44−/− ST/ST mice (vs.
ST/ST) (Fig. 5G). Since SLC1A2 is essential for glutamate
homeostasis and metabolism, we visualized the expression of Müller cell-specific genes involved in metabolic
processes as identified by the gene ontology (GO) term
0008152 (Fig. 5H). Importantly, proteins related to metabolic processes were highly expressed in ST/WT and
ST/ST (Fig. 5H). SLC1A2 is significantly downregulated in the Müller cell fractions of CD44−/− ST/WT and
CD44−/− ST/ST retinas compared to ST/WT and ST/ST
retinas, respectively (ANOVA, P ≤ .001), whereas it was
not altered in the neuron fraction (Fig. 5I). Since CD44
signaling leads to activation of the MAPK pathway [44],we analyzed MAPK3 expression in Müller cells andneurons. Interestingly, MAPK3 was significantly downregulated in Müller cells of CD44−/− ST/WT and CD44−/−
ST/ST retinas compared to ST/WT and ST/ST retinas,
respectively (ANOVA, P ≤ .001 and P = .001, respectively).
Furthermore, we found that MAPK3 was slightly but notsignificantly upregulated in ST/ST compared to ST/WTneurons (ANOVA, P = .3) (Fig. 5J). These results may
indicate that CD44 regulates SLC1A2 via the MAPK3
pathway.
Next, we validated the decreased expression of SLC1A2
found by proteome analysis of Müller cells using immunoblots, which confirmed SLC1A2 downregulation in
CD44−/− ST/WT and CD44−/− ST/ST retinas (Fig. 6A).
The quantitative analysis indicates a trend consistent
with the immunoblot results; however, the differences
observed were not statistically significant (Fig. 6B). Additionally, SLC1A2 also appeared to be downregulated
in the immunohistochemistry analysis (Fig. 6C). Coimmunostaining for GLUL (Müller cells) and SLC1A2 in
retinal sections from 12-week-old CD44−/− ST/WT mice
showed that SLC1A2 is expressed in Müller cells (Fig.
S4A). Based on the expression pattern and previous studies [45, 46], SLC1A2 seems to be also expressed in cones,
bipolar, and amacrine cells. To determine whether theobserved downregulation of the glutamate transporter
SLC1A2 impacts retinal glutamate levels, a fluorometricglutamate assay was utilized. The highest glutamate levelof 260 nmol/mg was detected in CD44−/− ST/WT retinas
compared to 169 nmol/mg in ST/WT retinas (ANOVA,P < .05). Glutamate concentration in CD44−/− ST/ST retinas was also increased to 217 nmol/mg compared to 148
nmol/mg in ST/ST retinas, but this difference was not
significant (ANOVA, P = .1) (Fig. 6D).

Ayten et al. Journal of Neuroinflammation(2024) 21:190

Page 9 of 16

Fig. 5 Proteomic profiling of Müller cells and neurons. MACS enriched Müller cells and neuron cell fractions were subjected to label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based proteomics. ST/WT N = 4, CD44−/− ST/WT, CD44−/− ST/ST N = 5, ST/ST N = 6. (A) Representative
image of Müller cell fraction immunostained for glutamine synthetase (GLUL) and counterstained with Hoechst 33,342. (B) Representative image ofneuron fraction immunostained for recoverin and counterstained with Hoechst 33,342. Scale bar, 50 μm. (C-F) Quantitative analysis of GLUL (Müller cellmarker) (C), rhodopsin (RHO) (rod photoreceptor marker) (D), PDE6B (E) and CD44 (F). (G) Volcano plot showing differentially expressed proteins between
ST/ST and CD44−/− ST/ST Müller cells. Red dot, solute carrier family 1 member 2 (SLC1A2) with fold change > 5, and FDR < 0.1. (H) Heat map representationof Müller cell-specific proteins involved in metabolic processes. (I, J) Quantitative analysis of SLC1A2 (I) and MAPK3 (J). Data, presented as mean ± SEM,
were compared by ANOVA. * P ≤ .05; ** P ≤ .01; *** P ≤ .001

Ayten et al. Journal of Neuroinflammation(2024) 21:190

Page 10 of 16

Fig. 6 Validation of decreased SLC1A2 expression in CD44-deficient mice. (A-D) Retinas from ST/WT, CD44−/− ST/WT, ST/ST, and CD44−/− ST/ST wereanalyzed at 8 weeks of age. (A) Representative SLC1A2 immunoblot of retinal lysates. β-Actin was used as a loading control. (B) Quantitative analysis of
SLC1A2 immunoblots. Data are presented as mean ± SEM. N = 5 per group. (C) Representative images of retinal sections immunostained for the glutamate
transporter SLC1A2. SLC1A2 is expressed in Müller cells and cones. Scale bar, 35 μm. (D) Fluorometric glutamate assay revealed a significantly higher glutamate concentration in CD44−/− ST/WT retinas compared to ST/WT. Data, presented as mean ± SEM, were compared by ANOVA, * P ≤ .05; ST/WT, CD44−/−
ST/WT, CD44−/− ST/ST N = 3, ST/ST N = 4. ONL, outer nuclear layer; INL, inner nuclear layer; GCL, ganglion cell layer

Increased pro-inflammatory response inCd44−/−Pde6bSTOP/STOPmice

Inflammation, a common feature of retinal degeneration [47], is characterized by reactive microglia, and an
upregulation of several pro-inflammatory molecules [48].
To evaluate whether loss of CD44 leads to changes in the
pro-inflammatory response, we quantified the total number of reactive microglia in retinal sections of 4-, 8-, and12-week-old-mice immunostained for IBA1 (microglia/
macrophages) [49, 50] and CD68 (reactive microglia/
macrophages) [51]. At 12 weeks of age, microglia had aramified morphology and were located between the IPL
and the OPL of ST/WT and CD44−/− ST/WT mice. In
contrast, in retinas from 12-week-old CD44−/− ST/ST
and ST/ST mice, microglia were reactive with extending processes and were located in the ONL (Fig. 7A). For
quantification, microglia positive for Hoechst 33,342,
Iba1, and CD68 were counted. CD44−/− ST/ST retinas showed higher numbers of reactive microglia than
ST/ST retinas at 4, 8, and 12 weeks of age(ANOVA, P = .056, P = .043, and P = .027, respectively). In
CD44−/− ST/ST mice, the number of microglia increasedin parallel with disease progression (Fig. 7B).
Reactive phagocytic microglia release pro-inflammatory factors such as TNFα, which activate NF-κB signaling, leading to a cascade of downstream effects [52, 53].
The mRNA level of Tnfα was significantly elevated in
8-week-old CD44−/− ST/ST retinas compared to ST/WT
and CD44−/− ST/WT retinas (Fig. 7C). Additionally, Tnfα
was also increased in CD44−/− ST/ST retina compared
to ST/ST, although this difference was not significant(Fig. 7C). The mRNA level of NF-κB was significantly
higher in 8-week-old CD44−/− ST/ST retinas compared
to ST/WT and CD44−/− ST/WT retinas. There wereno significant differences between CD44−/− ST/ST and
ST/ST retinas (Fig. 7D). In conclusion, increased activation of microglia in CD44−/− ST/ST mice was associatedwith increased expression of the proinflammatory factors
TNFα and NF-kB.

Ayten et al. Journal of Neuroinflammation(2024) 21:190

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Fig. 7 Increased neuroinflammation in CD44−/−ST/ST mice. (A) Representative images of retinal sections from 12-week-old mice immunostained for Iba1
and CD68 to visualize reactive microglia/ macrophages. Scale bar, 35 μm. (B) Quantification of reactive microglia at 4, 8, and 12 weeks of age. pw 4, N = 5
for ST/WT, N = 6 for CD44−/− ST/WT, ST/ST, and CD44−/− ST/ST. pw 8, N = 4 for ST/WT, N = 5 for CD44−/− ST/WT, ST/ST, and CD44−/− ST/ST. pw 12, N = 8 for
ST/WT, N = 6 for CD44−/− ST/WT, and CD44−/− ST/ST, N = 5 for ST/ST. (C-D) Quantitative mRNA analysis of TNFα (C), and NFκB (D) by qRT-PCR at 8 weeks
of age. N = 4 per group. (E-F) Quantitative analysis of NFκB2 (E) and IL-16 (F) in isolated Müller cells. ST/WT N = 4, CD44−/− ST/WT, CD44−/− ST/ST N = 5,
ST/ST N = 6. (B-F) Data, presented as mean ± SEM, were compared by ANOVA. ** P ≤ .01; *** P < .001. (G) Heat map representation of Müller cell-specificproteins involved in immune system processes. ONL, outer nuclear layer; OPL, outer plexiform layer; INL, inner nuclear layer; IPL, inner plexiform layer;
GCL, ganglion cell layer

To understand the inflammatory response of Müller
cells [54], we analyzed NFkB2 and pro-interleukin-16(IL-16) in our MAC-sorted proteome data. We foundthat pro-inflammatory NFkB2 and IL-16 were significantly increased in Müller cells of CD44−/− ST/ST retinas
compared to ST/ST (Fig. 7E, F). We also visualized theexpression of genes involved in immune system processes(GO term: 0002376) (Fig. 7G). There were no significant
changes between ST/WT and CD44/− ST/WT retinas.
Most of the proteins were highly upregulated in Müller cells of CD44−/− ST/ST retinas (Fig. 7G). These data

Ayten et al. Journal of Neuroinflammation(2024) 21:190

show that CD44 reduces the retinal pro-inflammatory
response to photoreceptor degeneration.

Discussion
Our data demonstrate that CD44 is dramatically upregulated in various RP mouse models. CD44 is the primary
receptor for hyaluronic acid (HA) [55], which is a critical component of the extracellular matrix (ECM) [55,56]. HA often accumulates in neurodegenerative diseases(e.g., multiple sclerosis, Alzheimer’s diseases) [57]. The
HA concentration also appeared to be increased in our
RP mouse model, indicating a positive feedback loop anda restructuring of the ECM composition in response tophotoreceptor degeneration. Changes in the ECM composition might be important to meet the requirementsof adjacent retinal cells and to enhance the connectivity
between the ECM and the cytoskeleton of Müller cells[6]. Alterations in the interphotoreceptor matrix, theECM between the outer limiting membrane and the RPE,
might also impair the exchange of metabolites between
Müller cells, photoreceptors, and RPE [5, 23]. The greater
HA accumulation in Cd44-deficient retinas might be
a compensatory mechanism for the loss of CD44; in
inflamed joint tissue from CD44-deficient mice following
collagen-induced arthritis, HA concentration was also
increased [58].
Regarding the downstream effects of CD44, our findings reveal a previously unknown role for CD44 in theretinal glutamate homeostasis. In healthy retinas, Müller
cells contribute to the removal of extracellular glutamate,
thereby protecting neurons from excitotoxicity [59–61].
The uptake and metabolization of glutamate are also partof the glutamate-glutamine cycle and is linked to themetabolic support of photoreceptors [2, 62]. In Cd44deficient mice, we observed a significant downregulation of the glutamate transporter SLC1A2 in Müller cells
and increased retinal glutamate levels. We also observedsome photoreceptor loss in these mice, which might bedue to glutamate-driven neurotoxic effects and/or inadequate matching of metabolic needs [59–61]. Although theperformed glutamate assay does not distinguish between
intracellular and extracellular glutamate, we assume that
downregulation of SLC1A2 results in impaired glutamate
uptake and thus, significant accumulation of extracellular glutamate. Moreover, Müller cells rapidly convert
glutamate to glutamine and α-ketoglutarate after uptake,minimizing their intracellular glutamate concentration[62]. It has been suggested that SLC1A2 is not expressedin Müller cells but in cones, bipolar, and amacrine cells[45, 46, 63] and that glutamate aspartate transporter 1(GLAST1) is the most abundant and significant glutamate transporter in Müller cells [45, 59, 64]. However,
our MAC-sorted proteomics and immunohistochemistry

Page 12 of 16

data demonstrate that SLC1A2 is indeed expressed in
Müller cells and impacts glutamate homeostasis.
CD44 has previously been linked to inflammation[65–67]. For example, CD44 can facilitate the recruitment of neutrophils and macrophages to sites of inflammation [68, 69]. Administration of anti-CD44 antibodies
inhibited inflammation in mouse models of inflammatory bowel disease, collagen- and proteoglycan-induced
arthritis, cutaneous inflammation, and IL-2-induced
vascular leak [70]. In addition, CD44 deficiency in a Parkinson’s disease mouse model decreased activation of
microglia and astrocytes [71]. This has led to the suggestion that CD44 should be considered as a target in
inflammatory diseases. However, results of studies using
Cd44-deficient mice showed increased lung inflammation in response to E. coli-induced pneumonia [72]. In
line with this finding, we show that loss of CD44 in RP
retinas leads to an increased immune response, characterized by activation of microglia and Müller cells, theinitiation of the inflammatory NFκB pathway, and therelease of proinflammatory cytokines (e.g., IL-16). The
significantly upregulated proinflammatory factor NF-κB
in CD44−/− ST/ST retinas may also further impede Müller cell glutamate uptake [73, 74]. It has also been suggested that increased numbers of reactive microglia may
increase synaptic glutamate levels [75, 76] while downregulating the expression and functionality of glutamate
transporters such as SLC1A2 [75].
Since we used a global CD44 knockout mouse model
rather than a Müller cell-specific knockout, it is important to note that CD44, while predominantly expressedin Müller cells, may also have functional implications inother retinal cell types. Thus, while the observed phenotype likely involves alterations in Müller cell function due
to CD44 loss, contributions from additional retinal cells
cannot be discounted. Further investigations, perhaps
utilizing cell-specific knockout models, are necessary todelineate the precise roles of CD44 in different retinal
cell types and their collective impact on the observed
phenotype.

Materials and methods
Animals

All animal experiments were performed in accordancewith the ARVO statement on the use of animals in ophthalmic and vision research and were approved by the
local authorities (Regierung von Oberbayern, ROB-55.22532.Vet_02-18-143). Mice were kept under standard
conditions on a 12 h light/ dark cycle with access to waterand food ad libitum. Pde6bSTOP mice were generated
in the Barbara & Donald Jonas Stem Cells Laboratory,
Columbia University, USA [77]. B6.129(Cg)-Cd44tm1Hbg/J
mice (referred to as CD44−/−) were purchased fromthe Jackson Laboratory (#005085). These mice carry aAyten et al. Journal of Neuroinflammation(2024) 21:190

Page 13 of 16

neomycin resistance/lacZ cassette that disrupts exon
1 and part of intron 1, resulting in a complete loss ofCD44 transcription [14]. Cd44−/− mice were crossedwith Pde6bSTOP mice to generate Cd44−/−Pde6bSTOP/STOP(referred to as CD44−/− ST/ST) and Cd44−/−Pde6bSTOP/+(referred to as CD44−/− ST/WT) mice.
Immunohistochemistry

Retinal sections were incubated in primary antibodies(Table 1) in blocking solution (5% chemiblocker #2170,
MerckMillipore; and 0.3% Triton® X-100 diluted in PBS)
overnight at 4 °C. Subsequently, sections were incubatedin secondary antibodies (Table 1) in PBS containing 3%
chemiblocker for 1.5 h at room temperature. For nuclear
counterstaining, sections were incubated for 5 min in
5 µg/ml Hoechst 33,342 (#H1399, Invitrogen).
Hematoxylin and eosin staining

Retinal sections were sequentially incubated for 5 minin 100% ethanol, followed by 5 min in 96% ethanol, andthen 5 min in 70% ethanol. Subsequently, sections werebriefly immersed in desalted water for 3 s before being
incubated for 5 min in hematoxylin solution (Sigma
Aldrich #MHS32-1 L). Slides were then washed for 5 minin desalted water. Following this, slides were incubatedfor 5 min in eosin Y solution (Sigma Aldrich #HT110216500ML). Afterward, slides were dipped several times indesalted water and subsequently sequentially immersed
for 3 s each in 70% ethanol, 96% ethanol, and finally100% ethanol. Lastly, slides were dipped in xylene several

times and mounted directly using Eukitt quick-hardening
mounting medium (Sigma Aldrich #03989 − 100).
Imaging and quantification

For quantitative analyses, the retinal images wereacquired with the compact fluorescence microscope
KEYENCE BZ-X800. Outer nuclear layer (ONL) thickness was measured at 300 μm from the optic nerve on
the ventral side using the Fiji software. For the quantification of cone inner (IS) and outer segment (OS) length,
the lengths of three cone IS and OS were measured at
a distance of around 300 μm from the optic nerve. Rod
bipolar cell, horizontal cell, and cone bipolar cell dendrite
areas close to the optic nerve were quantified as pixels in
the outer plexiform layer using Fiji. To visualize the ONL
thickness, spider plots were generated. Retinal images
were acquired from both the ventral and dorsal sides,
and ONL thickness was measured at 250 μm, 500 μm,
750 μm, and 1000 μm from the optic nerve on bothsides. For the quantification of reactive microglia, cells
that were positive for Hoechst, IBA1, and CD68 werecounted in areas close to the optic nerve. All data wereplotted using GraphPad Prism 9.3. Data are expressed asmean ± standard error of mean using an ANOVA analysis. P < .05 was considered statistically significant (*P < .05;**P < .01; ***P < .001). The N values refer to the number ofindividual animals for the respective genotype and arelisted in the respective figure legends.

Table 1 Primary and secondary antibodies
Antibody
Β-Actin-Peroxidase
Calbindin D-28k
CD44
CD44
CD68
Cone Arrestin (ARR3)
GFAP
GLUL
Iba1
Pde6b
PKCα
Recoverin
Secretagogin
Slc1a2488-Goat anti-Rat
488-Goat anti-Rabbit
555-Goat anti-Mouse
555-Goat anti-Rat
647-Goat anti-Rabbit
anti-Rabbit HRP
anti-Mouse HRP

Host species
Mouse
Mouse
Rat
RabbitRat
RabbitMouse
RabbitRabbitMouse
Mouse
RabbitRabbitRabbit
Goat
Goat
Goat
Goat
Goat
Mouse
Mouse

Dilution (IHC)
1:800
1:400
1:500
1:1000
1:10001:2000
1:1000
1:1000
1:10001:5000
1:50
1:1000
1:1000
1:1000
1:1000
1:1000-

Dilution (WB)
1:60001:2000
1:800
1:2000
1:400
1:10001:20001:2000

Supplier
Sigma-Aldrich
Swant
BD Pharmingen
Abcam
Bio-RadMerck
Sigma-Aldrich
Abcam
VWR / Fujifilm Wako
Santa Cruz
Santa Cruz
Sigma-Aldrich
Prof. Dr. Wagner (University of Vienna)
Cell Signaling
Thermo Fisher
Thermo Fisher
Thermo Fisher
Jackson
Thermo Fisher
Santa Cruz
Santa Cruz

Catalog number
A3854-200UL
300
550,538
ab28364
MCA1957T
AB15282
G3893
ab228590
WAKO019-19741
sc77486
sc-8393
AB5585
20,848
A-11,006
A-11,070
A-21,425
112-165-143
A-21,245
sc-2357
sc-516,102

Ayten et al. Journal of Neuroinflammation(2024) 21:190

Immunoblot

Retinas were homogenized using M-PER MammalianProtein Extraction Reagent (Thermo #78,503) containing protease inhibitor (Sigma #11,697,498,001) andPhosphatase Inhibitor Cocktail (Cell Signaling; #5870)
with a Branson Sonifier W-450D at 40% amplitude. Proteins (20 µg per sample) were separated by SDS-PAGE
and transferred to a 0.45 μm polyvinylidene difluoride(PVDF) membrane for 90 min at 90 V. Membranes were
blocked in 5% non-fat dry milk in Tris-buffered salinewith Tween®20 (TBS-T) for 1 h at RT. Primary antibodies (Table 1) were incubated in 5% non-fat dry milk overnight at 4 °C. Membranes were washed and incubatedwith corresponding HRP secondary antibody (Table 1)
for 1 h at RT. Proteins were detected using Immobilon
Forte Western HRP substrate (Millipore #WBLUF0100)
and imaged using a Bio-Rad ChemiDoc MP imager.
RT-qPCR

RNA was isolated from retinas with the NucleoSpin®
RNA kit (Macherey-Nagel) according to the manufacturer’s protocol. 0.5–1 µg of total RNA was used for
cDNA synthesis using the RevertAid First Strand cDNA
Synthesis Kit (Therme Fisher Scientific) following the
manufacturer’s instructions. The obtained cDNA was
diluted 1:5 with distilled water and used for quantitative
real-time PCR using the PowerUp™ SYBR™ Green Master Mix (Thermo Fisher Scientific) on a QuantStudio™
5 Real-Time PCR System (Thermo Fisher Scientific).
Exon-spanning primer pairs were designed to hybridize
exclusively to the desired transcript and to avoid genomic
contamination using the UCSC genome browser. Primer
specificity was verified by melting curve analysis and gelelectrophoresis of qPCR products. The following primers were used: Cd44 5’-​A​C​G​A​G​G​A​G​G​A​G​G​T​G​T​G​A​T​G​
T- 3’ (Forward), 5’-​G​T​G​G​C​T​T​T​T​T​G​A​G​G​G​G​T​T​C-3’(Reverse); Gapdh 5’-​C​A​T​C​A​C​T​G​C​C​A​C​C​C​A​G​A​A​G​A​C​
T​G-3‘ (Forward), 5’-​A​T​G​C​C​A​G​T​G​A​G​C​T​T​C​C​C​G​T​T​C​A​
G-3‘ (Reverse); Gfap 5’-​C​A​C​C​T​A​C​A​G​G​A​A​A​T​T​G​C​T​G​G​
A​G​G-3‘ (Forward), 5’-​C​C​A​C​G​A​T​G​T​T​C​C​T​C​T​T​G​A​G​G​T​
G-3‘ (Reverse); NF-κB 5’-​G​C​T​G​C​C​A​A​A​G​A​A​G​G​A​C​A​C​G​A​C​A-3’ (Forward), 5’-​G​G​C​A​G​G​C​T​A​T​T​G​C​T​C​A​T​C​A​C​
A​G-3’ (Reverse); Tnf-α 5’-​T​C​T​T​C​T​C​A​T​T​C​C​T​G​C​T​T​G​T​
G​G-3’ (Forward), 5’-​G​G​T​C​T​G​G​G​C​C​A​T​A​G​A​A​C​T​G​A-3’(Reverse).
ERG

ERG analysis was performed at 8 weeks of age according
to previously described procedures [29].
Hyaluronan ELISA

Retinas were homogenized in 95 µl M-PER Mammalian Protein Extraction Reagent (Thermo #78,503), 4 µl
protease inhibitor (Sigma #11,697,498,001), and 1 µl

Page 14 of 16

Phosphatase Inhibitor Cocktail (Cell Signaling; #5870)
with a Branson Sonifier W-450D. The lysates werediluted 1:4 with distilled water and 50 µl of the sample
lysates were used per well. The Quantikine™ Hyaluronan
ELISA assay (R&D Systems) was conducted according to
the manufacturer’s protocol.
Statistics

All data were plotted using GraphPad Prism 9.3. ANOVA
was used to analyze data. P < .05 was considered statistically significant (*P < .05; **P < .01; ***P < .001). The N
values refer to the number of individual animals for therespective genotype.
Proteomic profiling of MACS enriched retinal cell types

MACS was performed according to previously described
procedures [78]. Isolated retinal cell populations wereanalyzed with label-free quantitative liquid chromatography coupled-mass spectrometry (LC-MSMS), followedby processing of raw data with Proteome Discoverer 2.4
SP1 software as described [78, 79]. Quantification of proteins, after precursor recalibration, was based on intensity values (at RT apex) for the top three unique peptides
per protein. Peptide abundance values were normalizedon the total peptide amount. The protein abundanceswere calculated averaging the abundance values foradmissible peptides. The final protein ratio was calculated using median abundance values of three to five biological replicates in a non-nested design.
Glutamate assay

After protein extraction from retinal lysates and quantification (as described in Immunoblot), 2 µl of the lysate
was diluted with 18 µl distilled water. Subsequently, 1.5 µlof the diluted samples were added into wells of a 96-wellplate. The glutamate concentration per retina was measured using the PicoProbe™ Glutamate Assay Kit (Fluorometric) (BioVision) according to the manufacturer’s
protocol.

Supplementary Information

The online version contains supplementary material available at https://doi.
org/10.1186/s12974-024-03175-8.
Supplementary Material 1
Supplementary Material 2
Acknowledgements
The authors thank Dr. Hanaa Ghanawi for her support and insightful
discussions. We also thank Prof. Dr Ludwig Wagner for sharing thesecretagogin antibody.
Author contributions
MA performed experiments. TS analyzed proteomics data. SMH performedlabel-free liquid chromatography-tandem mass spectrometry (LC-MS/MS)based proteomics. LK analyzed the single-cell data. AG helped to performAyten et al. Journal of Neuroinflammation(2024) 21:190

a multistep magnetic-activated cell sorting (MACS) procedure. MA and SK
designed experiments, analyzed data, and wrote the manuscript.
Funding
This work was supported by the German Research Foundation [EmmyNoether grant KO 5719/1–1 and 513025799 - KO 5719/3 − 1, GR 4403/9 − 1,
and HA 6014/8 − 1] and, the Daimler and Benz Foundation and the Bayerische
Forschungsstiftung (1597-23) to S.F.K.
Open Access funding enabled and organized by Projekt DEAL.
Data availability
No datasets were generated or analysed during the current study.

Declarations
Ethical approval
All animal experiments were performed in accordance with the ARVO
statement on the use of animals in ophthalmic and vision research and wereapproved by the local authorities (Regierung von Oberbayern).
Competing interests
The authors declare no competing interests.
Received: 29 April 2024 / Accepted: 15 July 2024

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