Journal of Neuroinflammation

Lee et al. Journal of Neuroinflammation(2024) 21:137
https://doi.org/10.1186/s12974-024-03136-1

Open Access

RESEARCH

Hyperglycemia enhances brain
susceptibility to lipopolysaccharideinduced neuroinflammation via astrocyte
reprogramming
Kyung-Seo Lee1,2, Sung-Hyun Yoon1,2, Inhwa Hwang1, Jeong-Hwa Ma1,2, Euimo Yang2, Rebekah Hyeyoon Kim3,
Eosu Kim2,3 and Je-Wook Yu1,2*
Abstract
Hyperglycemia has been shown to modulate the immune response of peripheral immune cells and organs, but
the impact of hyperglycemia on neuroinflammation within the brain remains elusive. In the present study, we
provide evidences that streptozotocin (STZ)-induced hyperglycemic condition in mice drives a phenotypic switchof brain astrocytes to a proinflammatory state, and increases brain vulnerability to mild peripheral inflammation.
In particular, we found that hyperglycemia led to a significant increase in the astrocyte proliferation as determinedby flow cytometric and immunohistochemical analyses of mouse brain. The increased astrocyte proliferation
by hyperglycemia was reduced by Glut1 inhibitor BAY-876. Transcriptomic analysis of isolated astrocytes from
Aldh1l1CreERT2;tdTomato mice revealed that peripheral STZ injection induced astrocyte reprogramming into
proliferative, and proinflammatory phenotype. Additionally, STZ-induced hyperglycemic condition significantly
enhanced the infiltration of circulating myeloid cells into the brain and the disruption of blood-brain barrier in
response to mild lipopolysaccharide (LPS) administration. Systemic hyperglycemia did not alter the intensity andsensitivity of peripheral inflammation in mice to LPS challenge, but increased the inflammatory potential of brain
microglia. In line with findings from mouse experiments, a high-glucose environment intensified the LPS-triggered
production of proinflammatory molecules in primary astrocyte cultures. Furthermore, hyperglycemic mice exhibiteda significant impairment in cognitive function after mild LPS administration compared to normoglycemic miceas determined by novel object recognition and Y-maze tasks. Taken together, these results demonstrate that
hyperglycemia directly induces astrocyte reprogramming towards a proliferative and proinflammatory phenotype,which potentiates mild LPS-triggered inflammation within brain parenchymal regions.
Keywords Hyperglycemia, Neuroinflammation, Astrocytes, Microglia, Lipopolysaccharide, RNA-sequencing,
Cognitive function*Correspondence:
Je-Wook Yu
jewookyu@yuhs.ac
1
Department of Microbiology and Immunology, Institute for Immunology
and Immunological Diseases, Yonsei University College of Medicine,
Seoul, Korea

2

Graduate School of Medical Science, Brain Korea 21 Project, Yonsei
University College of Medicine, Seoul, Korea
3
Department of Psychiatry, Institute of Behavioral Science in Medicine,
Yonsei University College of Medicine, Seoul, Korea© The Author(s) 2024. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use,sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) andthe source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in thisarticle are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not includedin the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you willneed to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The
Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available
in this article, unless otherwise stated in a credit line to the data.

Lee et al. Journal of Neuroinflammation(2024) 21:137

Introduction
Hyperglycemia, characterized by elevated blood glucose
levels, is a hallmark feature of diabetes mellitus, a chronic
metabolic disorder that affects millions of people worldwide. While the detrimental effects of hyperglycemia onvarious peripheral organs have long been studied [1, 2],
its intricate involvement in driving brain inflammation
has gained attention in recent years. This growing interest stems from the realization that hyperglycemia canexert profound effects on the central nervous system
contributing to the pathogenesis of neuroinflammatory
and neurodegenerative diseases [3–5]. Indeed, patientswith type I or type II diabetes exhibit a heightened susceptibility to cognitive impairment and are prone toexperiencing more severe cerebral lesions than healthy
individuals [6–9]. However, the direct and specific impact
of hyperglycemia on the brain-resident cells remains
largely unknown. In particular, given the emerging role ofimmune responses in mediating neurodegenerative disorders [10–13], hyperglycemia-induced changes in brain
inflammation remain to be determined.
The brain is predominantly dependent on glucose as
its primary energy source, and the optimal maintenanceof glucose metabolism is critical for proper brain function [14]. Astrocytes, a subtype of brain glial cells, playa pivotal role in controlling the uptake of glucose fromthe bloodstream and its subsequent distribution tobrain cells [15]. Moreover, astrocytes are implicated inmany essential brain homeostatic functions such as neurotransmitter synthesis, synapse formation, and bloodbrain barrier (BBB) maintenance [16, 17]. Of interest,
astrocytes can produce proinflammatory cytokines andinteract with immune cells upon the inflammatory stimulation, thereby actively participating in the regulation ofneuroinflammation [18, 19]. In this context, we speculated that astrocytes might play a key role in modulating
the inflammatory status within the brain under hyperglycemic conditions.
Recent studies have demonstrated that hyperglycemic
conditions exacerbate neuroinflammatory responses
mainly associated with traumatic brain injury or ischemic stroke [20–22]. Hyperglycemia is prevalent in thepatients with ischemic stroke and also enhances therisk of stroke through various pathological effects [23,24]. Indeed, morphological changes in brain glial cells
have been frequently observed in hyperglycemic conditions [25]. However, the precise impact of hyperglycemia on the inflammatory status of the brain remains
largely unknown. In this context, we unexpectedly foundthat streptozotocin-induced hyperglycemia markedly
increases the proliferation of astrocytes, affecting bloodbrain barrier function and brain inflammatory status.
In the present study, we provide evidences that hyperglycemic conditions induce astrocyte reprogramming

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towards a proinflammatory phenotype, which increases
the brain’s sensitivity to peripheral or systemic inflammatory stimuli.

Materials and methods
Mice

C57BL/6 mice were purchased from Orient Bio. Aldh1l1cre/ERT2 (JAX#029655) and Rosa26-tdTomatofl/fl (Ai14,
JAX#007914) mice were obtained from The Jackson Laboratory and bred at Yonsei University College of Medicine. Aldh1l1cre/ERT2 mice and tdTomatofl/fl mice werecrossed to generate astrocyte-specific tdTomato-expressing mice. Tmem119-EGFP mice were provided by Dr. Ki
Woo Kim (Yonsei University). All mice were C57BL/6
background and maintained in the specific pathogenfree facility with temperature- and humidity-controlled
conditions on a 12 h–12 h light-dark cycle. Age-matched(8–12 weeks old) male mice were used for the experiments. All animal protocols were approved by the Institutional Ethical Committee, Yonsei University College ofMedicine (2020 − 0317). All experiments were performedin accordance with the approved guidelines of the Institutional Ethical Committee.
Mice treatment

Hyperglycemic state in mice was induced by streptozotocin (STZ) administration according to a previous study[26]. Briefly, 8-week-old male mice were fasted for 5 h
and then given a single intraperitoneal injection of STZ(150 mg/kg, Sigma-Aldrich, S0130) dissolved in sodium
citrate buffer (0.1 M, pH 4.5). The control group received
only sodium citrate buffer (vehicle). Five days after injection, blood samples were collected from the mice’s tailvein, and fasting blood glucose levels were measured
using an Accu-Chek Performa glucometer (Roche). Micewith blood glucose levels exceeding 250 mg/dl wereconsidered hyperglycemic and selected for the study.
To induce peripheral inflammation, mice were injected
intraperitoneally with lipopolysaccharide (LPS) (0.5 mg/
kg, E. coli O111:B4, Sigma-Aldrich, L3012) or an equivalent volume of PBS for the control group. Mice weresacrificed either 3–6 h post PBS or LPS injection for subsequent analysis. For the NOR and Y-maze tests, mice
were administered with LPS (0.25 mg/kg) and rested for
24 h before behavioral assessments. Tamoxifen (SigmaAldrich) in a corn oil solution was intraperitoneallyinjected (75 mg/kg) for 5 consecutive days into Aldh1l1cre/ERT2; tdTomatofl/fl mice. One week after the final
tamoxifen injection, appropriate treatments were administered to the mice.
Tissue preparation for flow cytometry

Mice were euthanized and a transcardial perfusion
with PBS was performed to remove circulating blood.

Lee et al. Journal of Neuroinflammation(2024) 21:137

Subsequently, the brain tissue was carefully isolated withthe olfactory regions, brain stem, and meninges being
excised. Then brain was then homogenized in RPMI1640 containing DNase I and Collagenase IV, followed byan incubation at 37 °C. The resulting homogenates were
subjected to Percoll gradient centrifugation to eliminate
myelin debris. Blood samples from mice were collected
in EDTA (5 mM) using capillary tubes. Red blood cells(RBCs) were lysed using ACK lysing buffer, and the cells
were obtained through centrifugation. For bone marrowcell preparation, mouse femur bone was flushed with
PBS, followed by lysis of RBCs. The cells are resuspended
in an appropriate staining medium for flow cytometricanalysis, and cell counts were quantified using hemocytometer before analysis.
Flow cytometry

Fluorochrome-conjugated monoclonal antibodies targeting CD45 (Biolegend), CD11b (Invitrogen), ACSA2 (Miltenyi), Ly6C (Invitrogen), and Ly6G (Invitrogen) were used
to stain cells for flow cytometry analysis. DAPI counterstaining was employed to exclude dead cells. The analyses
were conducted using FACSVerse (BD Biosciences) and
FlowJo software (TreeStar). Total immune cells, encompassing both myeloid and lymphoid cells, were identified
as CD45-positive cells. CD45+ cells were further categorized into brain-resident microglia and brain-infiltrating
myeloid cells such as neutrophils and monocytes basedon CD11b expression. For the isolation of microglia andastrocytes from the mouse brain, cells were sorted fromTmem119-EGFP (microglia) and Aldh1l1-cre/ERT; tdTomatofl/fl (astrocytes) using either FACS Aria II or FACS
Aria III cell sorter (BD Biosciences).
RNA-Seq analysis

For the transcriptomic analysis of astrocytes, mousebrain samples underwent enzymatic cell dissociation
using an Adult Brain Dissociation Kit (Miltenyi Biotec), according to the manufacturer’s instructions. The
resulting dissociated samples were collected and filteredthrough a 70-µm cell strainer. Debris Removal Solution
was applied to eliminate myelin debris, and Red Blood
Cell Removal Solution was used to clear red blood cells.
Cells from three-independent brains were pooled foreach sample.
RNA sequencing was carried out by Macrogen using
the manufacturer’s reagents and protocols. Illumina
TruSeq RNA library Preparation v2 kit was employed forthe preparation of sample libraries, and SMART-Seq v4
Ultra Low Input RNA for Sequencing was used for RNAseq. The resulting count files (fastq) were downloaded
and aligned to the M.musculus mm10 genome using
HISAT2 program, with transcript assembly performed
using the StringTie program. Outliers were excluded

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from each sample’s potential outlier genes for the analysis, and genes with zero read counts in any sample were
excluded. DEG (Differentially Expressed Genes) analysis
was performed using DESeq2 program, with most comparisons and analyses conducted using an FDR-adjusted
p-value < 0.05, unless specified otherwise. Heatmaps and
PCA plots were generated using the Macrogen DEG
viewer program or R project, bar plots were generatedusing R project, and Gene Set Enrichment Analysis(GSEA) on Gene Ontology (GO) enrichment was performed using the GSEA tool (https://www.gsea-msigdb.
org/gsea/index.jsp).
Evans blue leakage assay

Evans blue (Sigma) was dissolved in PBS and intravenously administered to mice via tail vein (0.2 mg/kg).
After 1 h, mice were deeply anesthetized and transcardially perfused with PBS. Subsequently, brain tissues werecollected and homogenized using trichloroacetic acid
(Sigma, T6399). Following centrifugation, the absorbanceof the supernatants was measured at 620 nm excitation
and 680 nm emission using the Varioskan Flash 3001
microplate fluorometer (Thermo Fisher). The BBB permeability was evaluated by quantifying the amount ofEvans blue leakage.
Immunohistochemistry

Mice were euthanized, and the brains were perfusedwith PBS and subsequently fixed with 4% paraformaldehyde. After overnight fixation, brain tissue samples
were immersed in 30% sucrose at 4 °C for 2 days until thesamples sunk to the bottom. Tissues were then embedded in OCT compound fully frozen on dry ice. CoronalSect. (30 μm thickness) of the embedded brain tissues
were obtained using Leica CM1860 cryotstat. The frozen sections were mounted on glass slides, treated withpermeabilization buffer (0.3% Triton X-100 in PBS) for
30 min at room temperature (RT), and then exposed toa block solution (4% BSA in PBS) for 2 h. Subsequently,
the sections were incubated with primary antibodies
targeting GFAP (Invitrogen), Iba1 (Wako), and BrdU
(Abcam) overnight at 4 °C, followed by treatment with
Cy3-, FITC-, or Alexa 488-labeled secondary antibodies.
For BrdU detection, samples were incubated with 2 N
HCl (30 min, RT) prior to permeabilization. DAPI counterstaining was used to visualize the nuclei. Consistentregions of the hippocampus were obtained from eachsample within the mouse group. Z-stack images, with a
20 μm span at 1 μm intervals, were generated throughorthogonal projection. All images were acquired and processed with confocal microscopy (LSM980, Carl Zeiss)
and Zen blue software (v.3.6.095).

Lee et al. Journal of Neuroinflammation(2024) 21:137

Quantification of immunohistochemical images

Image post-processing and analyses of individual cellnumbers and fluorescence intensity were performed
using Image J software. Image post-processing parameters were kept consistent across all control and experimental groups for comparison. Brightness and contrast
were adjusted to allow for visualization and analyses.
Quantification of astrocytes and microglia was determined by GFAP+ and Iba1+ cells, respectively, normalized by dividing the values by DAPI+ cells per sample ofbrain hippocampal image. The threshold was optimized
to a constant value for measurement of GFAP and Iba1
mean fluorescence intensity. Morphological analyses of
microglia were performed using Imaris software (v.9.7).
For 3D reconstruction of microglia, the Z-stack images(20 μm depth, 1 μm intervals, x40 magnification) wereacquired and imported in Imaris for visualization.
Cell culture

Mouse bone marrow cells were isolated from femurs andtibias of mice and cultured in L929-conditioned Dulbecco’s modified Eagle’s medium (DMEM) for 5–7 daysfor differentiation into BMDMs [27]. To isolate resident peritoneal macrophages, we collected mouse peritoneal lavage by rinsing with PBS containing 2% FBS.
The peritoneal cells were then harvested by centrifugation, resuspended in RPMI1640 media, and allowed toadhere to a cell culture dish. Following overnight incubation, the adherent cells were washed three times withwarm PBS and employed as peritoneal macrophages.
Mouse brain mixed glial cells were prepared from thewhole brains of mouse pups on postnatal days 0–2 asdescribed previously [28] and cultured in normoglycemic(5.5 mM glucose) or hyperglycemic DMEM (25 mM glucose) supplemented with 10% FBS and antibiotics for 7
days. Astrocytes were then isolated from the mixed glial
cells by removal of microglia using mild trypsinization(150 rpm, 6 h).
Enzyme-linked immunosorbent assay (ELISA)

Serum from mice was obtained through centrifugationof whole blood samples and then appropriately diluted
for ELISA assay. In the case of cultured cells, the media
was collected and subjected to centrifugation to remove
debris and cellular components. The concentrations ofIL-1β, TNF-α, and IL-6 were determined using IL-1β,
TNF-α, IL-6 ELISA DuoSets kit (R&D systems), respectively, in accordance with manufacturer’s instructions.
Quantification of mRNAFor evaluation of the mRNA transcription level, total
RNA was isolated from sorted cells, brain tissue, andspleen tissue using TRIzol reagent (Invitrogen), and thenwas reversely transcribed using Reverse Transcriptase

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primer mix (Takara). Quantitative real-time PCR was
performed using SYBR Premix Ex Taq (Takara) for comparative analysis of gene expression, in which Rn18s wasamplified as the control gene. Primers were as follows:
5’-GCC CAT CCT CTG TGA CTC AT-3’ and 5’-AGG
CCA CAG GTA TTT TGT CG-3’ (mouse il-1𝝱); 5’-AGG
TCA TTG GTG GAG AGG TG-3’ and 5’-CCT GCTTGA GTA TGT CGC AC-3’ (mouse cox-2); 5’-CCA AGT
TCC ACC TGC TCA AC-3’ and 5’-GCC GAG CTGACA CCT TAA TG-3’ (mouse pla2g3); 5’-CGG ACTCCG CAA AGT CTA AG-3’ and 5’-CGT CAG CCG
ATT TGC TAT CT-3’ (mouse tnf-𝝰); 5’-GTT TCT GGG
GAG AGG GTG AG-3’ and 5’-TGT TCT ACT CTC CTC
GGT GC-3’ (mouse cxcl2); 5’-TTG CTT TGG ACT CAG
CAT TG -3’ and 5’-GGG AGG TGT GAC CAG GTA
GA-3’ (mouse aqp4); 5’-GGG TCT ACA CCA GCAAGA GC-3’ and 5’-ACC GAG ACA TCA GGG CAT
AC-3’ (mouse axl); 5’ -TCG ACC GAA TCC TGA GTA
GC-3’ and 3’ -CGT CCT TTG TCA CTT GCA CA -3’(mouse pfkp); 5’ -CTG GAA TGA ATG TGG CTC GG-3’
and 5’ -TAA GCG TTG TCC AGG GTG AT-3’ (mousepkm2); 5’ -TGC ATC CCA TTT CCA CCA TG-3’ and 5’-GTG TCT GCG CTC TTC TTC AG-3’ (mouse ldha);
5’ -ACC ACG GAC TAC AAC CAG TT-3’ and 5’ -CCTTGA GGC CCA GAG ACT TG-3’ (mouse lcn2); 5’-CGC
GGT TCT ATT TTG TTG GT-3’ and 5’-AGT CGG CAT
CGT TTA TGG TC-3’ (mouse Rn18s).
Behavioral test

Behavioral tests were conducted as described in previous study with slight modifications [29]. For Novel
Object Recognition (NOR) test, mice were habituatedto the open field arena one day before object exposure.
During this habituation, mice explored the empty arenafor 10 min, and their movements were recorded using avideo system. In the training phase, two identical objects
were placed in the arena, and mice were allowed tofreely explore for 10 min. During the subsequent testing
phase (one hour after the training session), one object
was replaced with a novel one, and mice were allowed to
explore for 5 min. The time spent exploring each familiar and novel object was tracked using the video recording system. The discrimination index was calculated
as follows: [time with novel object – time with familiar
object] / [time with novel object + time with familiar
object]. NOR tests were conducted both before (baseline)
and after LPS injection. Mice that did not explore bothobjects during the training phase were excluded from theanalysis.
In the Y-maze task, the three arms of the maze wereclearly designated before usage. Mice were placed at thecenter of the maze, and their spontaneous behavior wasrecorded for a period of 10 min. The maze was cleaned
between each mouse’s task run to eliminate any odor

Lee et al. Journal of Neuroinflammation(2024) 21:137

cues. An arm entry was defined as when all four paws ofa mouse crossed the threshold of the center zone into thearm, with the snout oriented toward the end of the arm.
Spontaneous alternation (%) was calculated as follows:[number of spontaneous alternations] / [total number ofarm entries – 2] × 100, where a spontaneous alternation
occurred when the mouse entered a different arm in eachof three consecutive arm entries. Mice with total arm
entries fewer than 10 were excluded from the calculation.
Statistical analysis

All values were presented as the mean and standard errorof the mean (SEM) of individual samples. Data wereanalyzed using unpaired Student’s t tests (two-tailed),
one-way or two-way analysis of variance (ANOVA) with
Bonferroni post hoc test for comparison of two or moregroups. The level of statistical significance was set at p ≤0.05. Analyses were performed using GraphPad Prism 9.

Results
Streptozotocin-induced hyperglycemia increases a
population of astrocytes in the brain

To explore the impact of hyperglycemia on brain parenchymal cells, we first induced hyperglycemia in micethrough a single administration of streptozotocin (STZ).
This resulted in the elevated blood glucose levels fivedays post-injection, which persisted for at least three
weeks (Fig. 1A). Additionally, we observed a reduction
in body weight in mice with STZ-induced hyperglycemia (Additional file 1: Fig. S1A). Subsequently, we analyzed hyperglycemia-induced changes in brain cells using
flow cytometry to assess brain cell populations (Fig. 1B).
STZ-induced hyperglycemia did not cause significant
alterations in the total number of immune cells (CD45+)
and non-immune cells (CD45−) in the brain (Fig. 1C,
D). Likewise, the populations of brain-resident microglia (CD45medCD11bmed) and brain-infiltrating myeloid
cells (CD45hiCD11bhi) remained unaffected in response
to hyperglycemic conditions (Fig. 1E, F). However, weobserved a notable and significant increase in the number of astrocytes (CD45−ACSA2+) in the hyperglycemicgroup (Fig. 1G).
Next, we examined brain glial cells by conducting
immunohistochemical analysis on the hippocampal
region of mouse brains. We used antibodies targeting
GFAP and Iba1, which specifically label astrocytes andmicroglia, respectively (Fig. 2A; Additional file 1: Fig.
S1B). In line with the findings from flow cytometric analysis, immunohistochemical staining of coronal sections revealed a marked increase in both fluorescenceintensity and cell number of GFAP-positive astrocytes
in hyperglycemic brains compared to the control group(Fig. 2B, C). Conversely, the fluorescence intensity ofIba1 and cell number of microglia remained unaffected

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by STZ-induced hyperglycemic conditions (Fig. 2D, E).
These results demonstrate that peripheral hyperglycemia
specifically leads to an increase in the number of brain
astrocytes in the brain.
We then examined whether hyperglycemia could
induce the proliferation of astrocytes, as determined by
the incorporation of 5’-bromo-2’-deoxyuridine (BrdU).
Using Aldh1l1CreERT2; tdTomatofl/fl mice, we labeled astrocytes with tdTomato by tamoxifen injection. Then, fivedays after STZ injection, BrdU was administered daily
for an additional five days (Fig. 2F). BrdU can only beincorporated into dividing cells. Intriguingly, STZ injection led to a significant increase in BrdU-containing
tdTomato-positive astrocytes (Fig. 2G; Additional file 1:
Fig. S2), along with the increased number of astrocytes
in the hippocampal region of the brain (Fig. 2H). STZinduced hyperglycemia significantly elevated both theintensity and the proportion of BrdU-expressing astrocytes (Fig. 2I, J). These findings provide additional confirmation that peripheral hyperglycemic conditions induce
the proliferation of astrocytes in the hippocampal regionof the brain.
Streptozotocin-induced hyperglycemia induces aphenotype change of astrocytes

To gain molecular insights into the hyperglycemiainduced alterations in brain astrocytes, we conducted a
RNA-sequencing analysis on isolated brain astrocytes
derived from Aldh1l1CreERT2; tdTomatofl/fl mice exposed
to hyperglycemic conditions (Fig. 3A). TdTomato-labeledastrocytes were isolated from both normoglycemic andhyperglycemic mouse brain using a cell sorter (Fig. 3B;
Additional file 1: Fig. S3A) and were subsequently validated through the expression of cell-specific marker
genes (aldh1l1, aqp4, and slc1a2 for astrocytes, as well as
markers for other cell types including oligodendrocytes,
microglia, neurons, and endothelial cells) (Additional file
1: Fig. S3B).
We then examined the differentially expressed genes(DEGs) and enriched gene ontologies in mouse brain
astrocytes under hyperglycemic conditions. The principal
component analysis (PCA), exhibiting the distributionof each sample, confirmed distinct transcriptional variances between vehicle-treated and STZ-treated astrocytes (Fig. 3C). A total of 234 DEGs were found between
the two groups, with 146 genes upregulated and 88 genes
downregulated in astrocytes from STZ-treated mousebrains (Fig. 3D). Gene ontology (GO) enrichment analysisof these 234 DEGs revealed diverse biological processes,
including the regulation of response to stimulus, cell proliferation, and immune system process (Fig. 3D). Notably, most of genes associated with positive regulation ofcell proliferation and inflammatory responses were significantly upregulated in STZ-treated astrocytes (Fig. 3E;

Lee et al. Journal of Neuroinflammation(2024) 21:137

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Fig. 1 Hyperglycemic condition induces a significant increase in the number of astrocytes(A) Experimental scheme for hyperglycemia induction (top) and blood glucose level of mice (bottom) subjected to streptozotocin (STZ) administration(14 mice, vehicle; 18 mice, STZ group). (B) Representative gating strategy to identify singlets, live cells (DAPI), microglia (CD45med CD11b med), infiltrated
myeloid cells (CD45hi CD11bhi), and astrocytes (CD45− ACSA2+). (C) Flow cytometric analysis of brain tissues from vehicle- or STZ-injected mice. (D)Quantification of total immune (CD45+) and non-immune (CD45−) cells from vehicle- or STZ-treated mice. (10 mice, vehicle; 11 mice, STZ group) (E-G)
Quantification of microglia (E), brain-infiltrating myeloid cells (F) and astrocytes (G) from vehicle- or STZ-treated mice. (10 mice, vehicle; 11 mice, STZ
group) Data are presented as means ± SEM. Asterisks indicate significant differences in one-way ANOVA with Bonferroni post hoc test (A) and Student’s
two-tailed, unpaired t test (D-G). **P < 0.01, ****P < 0.0001, n.s. not significant

Additional file 1: Fig. S4A, B). Furthermore, proinflammatory and neurotoxic genes, such as Pla2g3, Fkbp5,
Cxcl2, and Tnf exhibited a marked increase in expression
in hyperglycemic astrocytes compared to the control cells(Fig. 3F-H). However, neuroprotective genes crucial for
maintaining brain homeostasis, including Apln and IGF1, displayed a significant downregulation in astrocytes
under hyperglycemic conditions (Fig. 3F). Additionally,
GSEA analysis revealed an upregulation of genes associated with chemokine production and neutrophil ormonocyte chemotaxis (Fig. 3I-K), along with a downregulation of genes related to brain homeostasis, such as
nervous system regulation or synapse assembly (Fig. 3L;
Additional file 1: Fig. S4C-E) in response to hyperglycemic conditions. These observations underscore that STZinduced hyperglycemia can lead to the reprogramming ofastrocytes into proinflammatory phenotypes.
To further determine the hyperglycemia-induced phenotypic shift of astrocytes, we profiled expression patterns of astrocyte under hyperglycemic conditions inLee et al. Journal of Neuroinflammation(2024) 21:137

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Fig. 2 Hyperglycemic condition induces astrogliosis and the proliferation of astrocytes(A) Representative immunohistochemical images of hippocampal regions of vehicle- or STZ- injected mice. The coronal sections of brain were stainedwith anti-GFAP (green) and anti-Iba1 (red). DAPI represents nuclear signal (blue). Scale bars = 50 μm. (B-E) Quantification of the mean fluorescence intensity (MFI) of GFAP and Iba1 normalized with DAPI (B and D), and the number of astrocytes (GFAP+ cells, C) and microglia (Iba1+ cells, E) normalized withDAPI+ cells. (6 mice, vehicle; 7 mice, STZ group). (F) Experimental scheme for BrdU-based cell proliferation assay. TdTomatofl/fl;Aldh1l1CreERT2 mice were
subjected to tamoxifen administration for five days and injected with STZ (d10) to induce hyperglycemia. After another five days, mice were injected with
BrdU (d15, 50 mg/kg) for five consecutive days. (G) Immunohistochemical analysis of BrdU cell proliferation assay in the hippocampal region of vehicleand STZ-injected mice. (6 mice, vehicle; 7 mice, STZ group) Cells were stained with anti-BrdU (green) and astrocytes were labeled by tdTomato (red). DAPI
represents nuclear signal (blue). The boxed areas indicate the colocalization of BrdU and astrocytes. (H-I) Quantification of astrocytes (tdTomato+ cells,H) and proliferating astrocytes (BrdU+ tdTomato+ cells, I) normalized by DAPI count. (J) Quantification of relative BrdU-expressing astrocytes per total
BrdU+ cells. Scale bars = 50 μm (20X) and 20 μm (enlarged, 40X). Asterisks indicate significant differences in Student’s two-tailed, unpaired t test. *P < 0.05,**P < 0.01, n.s. not significant

Lee et al. Journal of Neuroinflammation

Fig. 3 (See legend on next page.)(2024) 21:137

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Page 9 of 19(See figure on previous page.)
Fig. 3 Hyperglycemic condition induces a phenotypic change of astrocytes(A) Experimental scheme for RNA-seq analysis of astrocytes from control and STZ-treated mice (n = 3 per experimental group, each sample was pooled
from 3-independent mice). (B) Representative image of tdTomato+ astrocytes from brain single cell suspensions of tdTomatoflfl;Aldh1l1-CreERT mice. (C)Distribution of transcriptional differences of vehicle- and STZ-treated astrocytes using 3-dimensional principal component analysis (PCA). (D) RNA-seq
analysis of differentially expressed genes (DEGs) (FDR adjusted p-value < 0.05, |fold change| > 1.5) in STZ-induced hyperglycemic astrocytes. Top 15 Gene
Ontology (GO) terms associated with biological processes changed in astrocytes upon hyperglycemic condition in the order of increasing FDR adjusted
p-value; gene ratio = intersection size/ query size. (E) Heatmaps of selected GO terms, positive regulation of cell proliferation (GO:0008284) and inflammatory response (GO:0006954) with colors indicating Z scores. (F) Volcano plot depicting the upregulated and downregulated DEGs in astrocytes of
STZ-treated mice. Genes associated with inflammatory responses are colored in red and blue. (G-H) Quantification of mRNA levels of Pla2g3 (G) and Cxcl2(H) in the whole brain extracts of vehicle- and STZ- treated mice. (7 mice, vehicle; 9 mice, STZ group) (I-L) GSEA (gene set enrichment analysis) analysis of
hyperglycemic astrocytes in relation to the control group. (M) Heatmap of pan-reactive, A1 reactive, and A2 reactive genes in vehicle- and STZ- treatedastrocytes based on RNA-seq analysis. Data are presented as means ± SEM. (G, H, M) Asterisks indicate significant differences. *P < 0.05

terms of A1 reactive and A2 reactive genes in accordancewith the previous study [30, 31]. Of notice, the majorityof pan-reactive and A1 reactive genes were upregulated
in astrocytes of hyperglycemic group, while there wereless significant changes in A2 reactive genes in response
to hyperglycemic conditions (Fig. 3M). This analysis
revealed that STZ-induced hyperglycemia drives a reprogramming of astrocytes into neuroinflammatory A1 reactive phenotype.
Hyperglycemia enhances the sensitivity to peripheral LPSinduced brain inflammation

As transcriptomic analysis exhibited a notable increase inchemokines or chemotaxis-associated genes in astrocytes
under hyperglycemic conditions, we examined the infiltration of circulating myeloid cells, such as neutrophils or
monocytes, into the brain in the presence of mild intraperitoneal lipopolysaccharide (LPS) stimulation (Fig. 4A).
Systemic LPS administration did not induce a significant
increase in the total immune cells (CD45+) and brainresident microglia (CD45med CD11bmed) in the brains ofboth control and STZ-treated mice (Fig. 4B, C). However,
LPS treatment alone significantly elevated the infiltration of circulating myeloid cells (CD45hi CD11bhi) into
the brain, and this LPS-triggered myeloid cell infiltration
was markedly enhanced in hyperglycemic mice (Fig. 4D).
These findings indicate that hyperglycemia enhances therecruitment of myeloid cells into the brain in the context of mild peripheral inflammation. Regarding astrocytes, the cell number of astrocytes was increased by
STZ treatment as observed in Fig. 1G, but remained
unaffected by LPS injection in both groups (Fig. 4E). To
further assess the inflammatory status in the hyperglycemic brain, we examined the mRNA levels of proinflammatory cytokines. Following LPS injection, we observed
elevated expression levels of proinflammatory cytokines
IL-1𝝱 and TNF-𝝰 in the brain (Fig. 4F-G), and the elevation in Tnf-𝝰 mRNA was significantly amplified under
hyperglycemic conditions. However, STZ-induced elevation in IL-1𝝱 mRNA did not reach statistical significance(Fig. 4F, P = 0.0547).

Along with the increased myeloid cell infiltration in
hyperglycemic condition, we assessed the blood-brain
barrier’s (BBB) integrity by examining the leakage ofEvans Blue dye. Interestingly, STZ treatment alone did
not induce a significant increase in BBB permeability,
but significantly potentiated the disruption of the BBB
induced by peripheral LPS (Fig. 4H-I). In line withthese observations, RNA-seq analysis revealed that STZ
treatment led to a decrease in the expression levels of
astrocytic endfoot genes including aquaporin 4 (Aqp4)(Fig. 4J). The reduced expression of Aqp4 in hyperglycemia was further confirmed in mouse brain tissue(Fig. 4K), suggesting that hyperglycemia may disrupt the
integrity of astrocyte endfeet, which are crucial for maintaining the homeostatic function of the BBB.
To further investigate the impact of hyperglycemiaon the inflammatory status of the brain, we conducted
immunohistochemical analysis to assess gliosis in the
hippocampal region. In the presence of peripheral LPS
stimulation, STZ treatment resulted in a significant
increase in the fluorescence intensity of Iba1+ and GFAP+
cells in the brain hippocampus (Fig. 4L-N; Additional file
1: Fig. S5). Notably, STZ-induced hyperglycemia did notaffect the number of microglia in LPS-inflamed brains(Fig. 4O). These findings suggest that hyperglycemic conditions induce morphological changes in brain glial cells,
leading to subsequent gliosis in response to mild peripheral inflammation.
Hyperglycemia does not affect LPS-induced peripheral
inflammation

To explore how hyperglycemia can enhance the susceptibility to peripheral inflammation-induced neuroinflammation, we examined notable changes in the myeloid cell
population in peripheral regions, including bone marrowand blood (Fig. S6). STZ treatment alone did not resultin a significant alteration in the number of myeloid cells(CD45+CD11b+), monocytes (CD45+CD11b+Ly6C+),
and neutrophils (CD45+CD11b+Ly6G+Ly6Clow) in thebone marrow (Fig. 5A). Following intraperitoneal LPS
injection, both control and STZ groups exhibited adecrease in the number of myeloid cells and neutrophils

Lee et al. Journal of Neuroinflammation

Fig. 4 (See legend on next page.)(2024) 21:137

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Lee et al. Journal of Neuroinflammation(2024) 21:137

Page 11 of 19(See figure on previous page.)
Fig. 4 Hyperglycemic condition increases the vulnerability of brain to peripheral inflammatory stimulation(A) Representative flow cytometric analysis of brain cell populations in vehicle- and STZ-treated mice followed by an intraperitoneal injection of LPS(0.5 mg/kg, 6 h). (B-E) Quantification of each cell population in (A). (6 mice, STZ-LPS; 7 mice, other groups) (F-G) Quantification of mRNA levels of IL-1𝝱
and TNF-𝝰 in the brain extracts of veh- or STZ-treated mice upon PBS or LPS injection (0.5 mg/kg, 3 h). (5 mice, veh-PBS; 6 mice, veh-LPS, STZ-LPS; 8 mice,
STZ-PBS) (H-I) Representative brain images (H) and quantification (I) of relative Evans blue extravasation into brain of veh- or STZ-treated mice upon LPS
administration (0.5 mg/kg, 6 h). Evans blue was intravenously injected one hour before sacrifice. (5 mice, veh-PBS; 13 mice, veh-LPS; 12 mice, STZ-PBS; 11
mice, STZ-LPS) (J) Heatmap of astrocytes endfoot genes (GO:0097450) in RNA-seq data from veh- or STZ-treated mice. Asterisk indicates genes of FDR
adjusted p-value < 0.05. (K) Quantification of mRNA level of Aqp4 (aquaporin 4) in the brain extracts of veh- or STZ-treated mice. (5 mice, vehicle; 8 mice,
STZ group) (L) Representative immunohistochemical images of hippocampal region of veh- or STZ- treated mice followed by LPS administration (0.5 mg/
kg, 6 h). The coronal brain sections were stained with anti-GFAP (red) and anti-Iba1 (green). DAPI represents nuclear signal (blue). Scale bars = 50 μm. (M-O)
Quantification of mean fluorescence intensity of Iba1 (M) or GFAP (N), and the number of Iba1 cells (O) per DAPI. (7 mice, veh-LPS; 8 mice, STZ-LPS) Data
are presented as means ± SEM. Asterisks indicate significant differences between the groups as determined by two-way ANOVA with Bonferroni post hoc
test (B-G and I) or Student’s two-tailed, unpaired t test (K and M-O); *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001, n.s. not significant

in the bone marrow, likely due to their egress from thebone marrow (Fig. 5B, C). Importantly, there was no
significant difference in the number of bone marrow
myeloid cells between control and hyperglycemic miceupon LPS administration (Fig. 5B, C). Similarly, STZ
treatment alone did not cause significant changes in
the number of myeloid cells and neutrophils in the circulating blood (Fig. 5D). While LPS treatment induced
a substantial increase in circulating myeloid cells andneutrophils, there was no significant difference observed
between control and hyperglycemic conditions (Fig. 5E,
F).
We then examined the impact of hyperglycemia on
the proinflammatory cytokine levels in the periphery.
LPS administration led to a robust increase in IL-1β and
TNF𝝰 production in both the serum (Fig. 5G, H) andspleen (Fig. 5I, J) of mice. However, the hyperglycemic
condition did not affect this LPS-induced productionof proinflammatory cytokines (Fig. 5G-J). These results
collectively indicate that our hyperglycemic conditions
do not alter the LPS-induced myeloid cells’ populationand their immune responses in the periphery, suggestingthat the heightened susceptibility of the brain to hyperglycemia is not likely attributed to increased peripheral
inflammation.
Hyperglycemia induces a specific increase in the
responsiveness of brain microglia

To explore the significant influence of hyperglycemiaon the responsiveness of peripheral macrophages, we
isolated bone marrow cells from both control and STZtreated mice and induced their differentiation into bonemarrow-derived macrophages (BMDMs). Additionally,
we isolated peritoneal macrophages from peritoneal
lavage collected from control and STZ mice (Fig. 5A).
Subsequently, we analyzed in vitro IL-6 production fromthese macrophages following stimulation with poly(I: C)or LPS. In BMDMs, STZ-induced hyperglycemia did notalter the IL-6 production induced by LPS or poly(I: C)(Fig. 6B).Similarly, the level of LPS-induced IL-6 production in peritoneal macrophages was not affected by STZinduced hyperglycemia (Fig. 6C). These results indicatethat the sensitivity of peripheral macrophages to toll-likereceptor signaling remained unchanged under hyperglycemic conditions.
Then, to examine potential alterations in the responsiveness of brain microglia following STZ treatment, weused Tmem119-EGFP mice, where microglia are specifically labeled with GFP. Tmem119-EGFP mice wereadministered with STZ, and following a 21-day interval, they received an intraperitoneal injection of LPS(Fig. 6D). Brain microglia were then isolated based on
GFP fluorescence (Additional file 1: Fig. S7) and examined for the expression of inflammation-related genes.
Notably, we observed a significant increase in the expression of inflammatory genes such as IL-1β and CCL2 inmicroglia from STZ-treated mice compared to microglia from control mice, following peripheral LPS injection (Fig. 6E, F). Additionally, the expression level of Axl,a representative gene associated with dysfunctional orneurodegenerative microglia [32], was also elevated in
the STZ-treated microglia, regardless of LPS stimulation(Fig. 6G).
To further characterize the phenotypic changes of
microglia induced by hyperglycemia, we examined themorphology of microglia under normal and hyperglycemic conditions (Fig. 6H). Consequently, STZ treatment
led to a significant increase in the soma volume and adecrease in the length and the number of endpoints of
microglia in the presence of LPS stimulation (Fig. 6I-K;
Additional file 1: Fig. S8). These morphological analyses
demonstrate that peripheral hyperglycemia induces aphenotypic shift in brain microglia towards an enhanced
innate immune-active state in the context of peripheral
LPS stimulation.
High extracellular glucose induces Glut1-dependent
phenotypic changes in primary astrocyte culture

To explore how systemic hyperglycemic conditions drive
brain astrocyte proliferation, we checked the potent roleof glucose transporter Glut1. Of interest, RNA-seq analysis revealed that STZ treatment significantly increased
Slc2a1 mRNA expression in astrocyte (Fig. 7A). Then,
we assessed STZ-induced astrocyte proliferation in theLee et al. Journal of Neuroinflammation(2024) 21:137

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Fig. 5 Hyperglycemic condition does not augment peripheral inflammation in response to systemic LPS administration(A-C) Flow cytometric analyses of bone marrow cells from vehicle- and STZ-injected mice followed by LPS injection (0.5 mg/kg, 6 h). (4 mice per group)(D-F) Flow cytometric analyses of circulating blood cells from vehicle- and STZ-injected mice followed by LPS injection (0.5 mg/kg, 6 h). (5 mice, vehicle
groups; 4 mice, STZ groups) (G-H) Quantification of IL-1𝝱 (G) and TNF-𝝰 (H) protein level in the serum from vehicle- and STZ-injected mice followed by
LPS injection (0.5 mg/kg, 6 h) using ELISA. (5 mice, veh-PBS; 6 mice, veh-LPS, STZ-LPS; 8 mice, STZ-PBS) (I-J) Quantification of mRNA levels of IL-1𝝱 (I) andTNF-𝝰 (J) from spleen extracts of vehicle- and STZ-injected mice followed by LPS injection (0.5 mg/kg, 6 h). (5 mice, veh-PBS; 6 mice, veh-LPS, STZ-LPS;
8 mice, STZ-PBS) Data are presented as means ± SEM. Significant differences between the groups were determined by two-way ANOVA with Bonferroni
post hoc test. n.s. not significant

Lee et al. Journal of Neuroinflammation(2024) 21:137

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Fig. 6 Hyperglycemic condition increases the sensitivity of microglia to systemic LPS administration(A) Experimental scheme of in vitro experiment using bone marrow-derived macrophages (BMDMs) and peritoneal macrophages (MP) isolated from
normoglycemic (vehicle) and hyperglycemic (STZ-injected) mice. (B-C) Quantification of extracellular IL-6 levels from cultured BMDMs (B, 2 mice, vehicle;
3 mice, STZ) or peritoneal macrophages (C, 4 mice, vehicle; 5 mice, STZ) upon LPS (0.25 µg/ml, 3 h) or poly I: C (30 µg/ml, 3 h) treatment using ELISA.
(D) Experimental scheme of microglia (GFP+) isolation from Tmem119-EGFP mice subjected to veh- or STZ-injection followed by LPS injection (0.5 mg/
kg, 3 h). (E-G) Quantification of mRNA levels of IL-1𝝱 (E), CCL-2 (F) and Axl (G) from isolated microglia using real-time qPCR. (n = 3, STZ-LPS group; n = 4,other groups; each RNA sample was pooled from 5-independent mice) (H) Representative images of morphological analysis of microglia in veh- and
STZ- injected mice upon LPS administration (0.5 mg/kg, 6 h) using Imaris software. (I-K) Quantification of soma volume (I), filament length (J), and end
point counts (K) of microglia. (I, 5 mice, veh-PBS; 13 mice, veh-LPS; 6 mice, STZ-PBS; 12 mice, STZ-LPS; J-K, 4 mice, veh-PBS, STZ-PBS; 8 mice, veh-LPS; 7
mice, STZ-LPS) Three or four cells were randomly selected and averaged for each mouse brain section. Data are presented as means ± SEM. Asterisks indicate significant differences between the groups as determined by two-way ANOVA with Bonferroni post hoc test (B-C, E-G and I-K) *P < 0.05, **P < 0.01,***P < 0.001, ****P < 0.0001, n.s. not significant

Lee et al. Journal of Neuroinflammation(2024) 21:137

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Fig. 7 High extracellular glucose increases the expression of glycolytic and proinflammatory molecules in astrocytes. (A) The relative expression level(fold change) of slc2a1 in hyperglycemic (STZ-treated) astrocytes in relation to normoglycemic astrocytes based on TPM read counts obtained from bulk
RNA-seq data. (B) Experimental scheme of BAY-876 and minocycline administration in normoglycemic or hyperglycemic mice. Mice were given daily
intravenous injections of BAY-876 (1.0 mg/kg) or minocycline (45 mg/kg) from day 5 to day 21. (C) Representative flow cytometric analysis of brain cell
populations in STZ-treated mice followed by vehicle, BAY-876, or minocycline injection. (D-E) Quantification of astrocytes (D) or microglia (E) populationin (C). (8 mice, vehicle; 6 mice, STZ; 7 mice, STZ + minocycline; 9 mice, STZ + BAY-876 group) (F) Experimental scheme of in vitro primary mixed glial cells
and astrocytes cultured in normal glucose (5.5 mM) or high glucose (25 mM) DMEM, followed by LPS treatment (0.2 µg/ml, 2 h) (G-I) Quantification ofmRNA levels of Il6 (G), Tnfa (H), and Lcn2 (I) from primary astrocytes cultured in normal or high glucose-DMEM following LPS stimulation (n = 4 for allgroups). (J-L) Quantification of mRNA levels of glycolytic genes of primary astrocytes cultured in normal or high glucose DMEM (n = 4 for all groups). Data
are presented as means ± SEM. Asterisks indicate significant differences in one-way ANOVA with Bonferroni post hoc test (D-E), two-way ANOVA with
Bonferroni post hoc test (G-I), and Student’s two-tailed, unpaired t test (J-L). *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001, n.s. not significant

Lee et al. Journal of Neuroinflammation(2024) 21:137

presence of Glut1 inhibitor BAY-876 (Fig. 7B). In addition, we also administered minocycline, commonly used
to inhibit microglial activation, into STZ-treated mice toexamine the effect of microglia on the astrocyte proliferation. Consequently, STZ-induced increase in astrocyte
population was significantly reduced by BAY-876, but not
by minocycline (Fig. 7C, D). In contrast, both chemicals
had no effect on the number of microglia (Fig. 7E). Theseobservations indicate that STZ-induced hyperglycemic
conditions modulate astrocyte proliferation in a Glut1dependent manner.
To further confirm the glucose-driven reprogramming of astrocytes, primary mouse astrocytes were cultured in normal or high glucose medium for one week
(Fig. 7F). Then, we checked the responsiveness of astrocytes to LPS stimulation. Notably, high glucose medium
led to an enhanced production of proinflammatory andreactive genes in astrocytes following LPS treatment(Fig. 7G-I). Given that hyperglycemia induces training ofmacrophages via glycolysis-dependent epigenetic modifications [33], we examined the expression levels of glycolytic enzymes in astrocytes under normal or high glucose
medium. Intriguingly, high glucose medium-exposed
astrocytes exhibited an increased expression of glycolytic enzymes compared to astrocytes in normal glucose

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environments (Fig. 7J-L). These findings suggest that highextracellular glucose can drive astrocyte reprogramming
via inducing glycolysis-dependent alterations of chromatin accessibility of proinflammatory genes.
Hyperglycemia potentiates peripheral LPS-induced
cognitive impairment

To determine the impact of hyperglycemia on the brain
functions in the context of inflammatory stimuli, we conducted behavioral tests to assess the cognitive functions(Fig. 8A). Of note, novel object recognition (NOR) task
demonstrated that mild LPS administration significantly
impaired cognitive functions of hyperglycemic micecompared with control mice, whereas hyperglycemia
alone did not cause baseline cognitive impairment ofmice (Fig. 8B). Additionally, there were no significant differences in total exploration time between the two groups
upon LPS injection, implying the locomotor function was
not affected in hyperglycemic mice (Fig. 8C). Similarly,
Y-maze task revealed a reduced spontaneous alternationand total arm entries in hyperglycemic mice upon LPS
injection compared with the control mice (Fig. 8D, E),suggesting that hyperglycemic condition can impair brain
performances upon a mild inflammatory stimulus. In thevehicle- and PBS-treated group, both the discrimination

Fig. 8 Hyperglycemic conditions impair cognitive function upon mild peripheral LPS stimulation(A) Experimental scheme for Novel object recognition (NOR) and Y-maze behavioral tests. Control and STZ-treated mice were intraperitoneally administered with LPS (0.25 mg/kg) and rested for 24 h before the tasks. (B-C) NOR task conducted for vehicle- and STZ- treated mice followed by PBS or LPS
injection. (14 mice, veh-PBS; 13 mice, all other groups) The discrimination index calculation (B) and total exploration measurement (C) were shown. Micethat did not explore both objects during the training phase were excluded from the analysis. (D-E) Y-maze task conducted for vehicle- and STZ- treatedmice followed by PBS or LPS treatment. The spontaneous alternation calculation (D) and total arm entries count (E) were shown. (13 mice, veh-PBS; 14
mice, veh-LPS; 14 mice, STZ-PBS; 16 mice, STZ-LPS group) Mice with total arm entries fewer than 10 were excluded from the calculation. Data are presented as means ± SEM. Asterisks indicate significant differences between the groups as calculated by two-way ANOVA with Bonferroni post hoc test.
*P < 0.05, **P < 0.01, n.s. not significant

Lee et al. Journal of Neuroinflammation(2024) 21:137

index and spontaneous alternations significantly diverged
from their respective theoretical mean values of 0 (nodiscrimination) and 50% (random behavior), substantiating the biological relevance of the cognitive evaluation(Additional file 1: Fig. S9A-B).
The diminished total number of arm entries also indicates a decreased willingness of hyperglycemic mice toexplore unfamiliar environments. Collectively, theseresults demonstrate that hyperglycemia can enhance
the brain’s vulnerability to mild peripheral inflammatory
stimulation, ultimately impairing its function through amechanism involving hyperglycemia-induced alterationsof astrocytes.

Discussion
Diabetic condition poses a risk of severe complications
and often worsens existing brain pathologies. Nevertheless, the direct impact of hyperglycemic burden on
brain cells and their contribution to the progression ofbrain diseases remain unclear. In the present study, we
attempted to elucidate hyperglycemia-induced changes
in brain glial cells using flow cytometric and immunohistochemical analyses. In particular, we conducted an
RNA-sequencing-based transcriptomic analysis of brain
astrocytes under hyperglycemic stress. Our findings
revealed that hyperglycemia stimulates the proliferationof astrocytes, the central regulators of brain glucose andenergy metabolism, leading to the reprogramming ofastrocytes. Furthermore, our results demonstrate thatthe hyperglycemia-induced shift in astrocyte phenotype enhances the brain’s sensitivity to mild peripheral
inflammation. (Fig. 9) This contrasts with most previous
studies, which primarily focused on understanding theimpact of hyperglycemia in acute stroke or reperfusion/ischemic conditions [34–37].
Astrocytes, the most abundant and diverse type of
glial cells, play crucial roles in mediating a wide range ofbrain functions and immune regulation within the brain[38, 39]. Recent studies have revealed that proliferative
astrocytes represent a distinct reactive subtype, differing from mature astrocytes, which remain quiescent andnon-proliferative, and are observed in response to physical injuries such as traumatic brain injury or spinal cord
injury [40–42]. These proliferating astrocytes can exert
both protective and detrimental function in the brain[43]. For instance, in the traumatic brain injury or spinal cord injury, reactive astrocytes undergo proliferationand exhibit neuroprotective or scar-forming properties
to impede the spread of inflammation [44, 45]. Conversely, astrocyte proliferation has also been linked tobrain pathologies, such as neuroinflammation and gliosis [46, 47]. Therefore, the specific effects of proliferative
astrocytes may vary depending on the circumstances,
warranting further investigation for a comprehensive

Page 16 of 19

understanding. Our findings in this study demonstratethat astrocyte reprogramming induced by hyperglycemia
involves heightened reactivity, neurotoxicity, and proliferation. In contrast to our observations, Li et al. proposed that hyperglycemia inhibits astrocyte proliferation[48]. However, it’s important to note that this study was
conducted using in vitro astrocyte cultures exposed toelevated extracellular glucose levels. While the discrepancy might be influenced by differences in in vivo and invitro observations, it remains crucial to verify the effects
of high glucose levels on astrocytes in an in vivo setting.
Notably, our findings demonstrate that hyperglycemia
facilitates the disruption of BBB in response to peripheral inflammatory stimulation. While astrocytic endfeet
structure is crucial for maintaining BBB integrity [49], we
also observed a downregulation of Aqp4, a pivotal geneof astrocytic endfeet, and an upregulation of chemotaxisassociated genes in astrocytes under hyperglycemic condition. These alterations in astrocytes may contributeto the increased permeability of the BBB in response to
mild peripheral inflammation. Supporting these findings,
the hyperglycemic condition significantly intensified
the infiltration of myeloid cells into the brain triggeredby peripheral LPS. Regarding the substantial impact ofhyperglycemia on other BBB components, such as endothelial cells and pericytes, further investigations will bevaluable to enhance our understanding.
Several previous studies have explored the effects
of prolonged hyperglycemia on peripheral immune
responses [50–53]. Notably, a recent investigation uncovered that hyperglycemia induces a trained immune
response in peripheral myeloid cells, resulting in proinflammatory and pro-atherosclerotic phenotypes [33].
However, under our hyperglycemic conditions, we did
not observe any changes in the reactivity of peripheral
inflammatory cells. The discrepancy in previous studies may be attributed to their consideration of long-term
hyperglycemic effects. Nevertheless, our relatively shortterm hyperglycemic condition led to the reprogrammingof astrocytes into a proinflammatory phenotype without
impacting peripheral immune cells. Supporting thesefindings, our in vitro results from astrocyte cultures also
demonstrated that a high-glucose medium induces theexpression of glycolytic enzymes and increases the LPS
responsiveness of astrocytes. It will be thus intriguing to
examine the epigenetic modifications in astrocytes under
hyperglycemic conditions. Consequently, our study sheds
light on the crucial role of astrocytes in the context ofhyperglycemia-mediated brain pathological conditions.
Concerning the direct influence of hyperglycemia on
the brain, our observations reveal that hyperglycemia
triggers both functional and morphological changes in
microglia, alongside astrocytes. Notably, hyperglycemia
significantly potentiates the innate immune potential

Lee et al. Journal of Neuroinflammation(2024) 21:137

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Fig. 9 Proposed mechanisms for how hyperglycemia amplifies neuroinflammation sensitivity. Hyperglycemic conditions induced by streptozotocin
promote astrocyte proliferation and reprogram homeostatic astrocytes into inflammatory phenotype in brains. Upon peripheral inflammation inducedby lipopolysaccharide (LPS), reactive astrocytes augment LPS-induced blood-brain barrier (BBB) damages and myeloid cell infiltration into brains, whichlead to neuroinflammation and the subsequent cognitive dysfunctionof microglia to mild peripheral inflammation. This
unexpected finding implies that hyperglycemia has thepotential to reprogram both microglia and astrocytes.
Since microglia are the major cell type engaged in brain
immune responses and are substantially influenced
by astrocytes [54], further transcriptomic and epigenetic analyses of microglia will be crucial to unravel thehyperglycemia-induced sensitization of brain glial cells toneuroinflammation.
In conclusion, the present study reveals the proliferation of reactive astrocytes exhibiting proinflammatory characteristics under hyperglycemic conditions.
This transformation in astrocytes increases the susceptibility of brain immune responses, making it moreLee et al. Journal of Neuroinflammation(2024) 21:137

vulnerable to mild peripheral stimulations. Given that we
did not explore the function of candidate genes inducedby hyperglycemia in astrocytes, further investigationis necessary to comprehend their functional relevance.
Our findings highlight the potential roles of astrocytes inexacerbating diabetes-associated brain diseases, and thehyperglycemia-induced alterations in astrocytes could
serve as a therapeutic target to alleviate brain pathologies
associated with diabetic complications.

Supplementary Information

The online version contains supplementary material available at https://doi.
org/10.1186/s12974-024-03136-1.
Supplementary Material 1
Acknowledgements
We would like to thank Dr. Eunji Cheong (Yonsei University) for technicalsupport.
Author Contributions
K.-S.L. and J.-W.Y. conceived and designed the study. K.-S.L, I.H., S.-H.Y., J.-H.M.,
E.Y. and R.K. performed and analyzed the experiments. E.K. provided a criticaltechnical advice for behavioral tests. J.-W.Y. supervised the entire project.
K.-S.L. and J.-W.Y. wrote the manuscript. All authors read and approved thefinal version of the manuscript.

Page 18 of 19

4.
5.
6.

7.
8.
9.
10.

11.
12.
13.
14.

Funding
This work was supported by the National Research Foundation of Korea Grant
funded by the Korean Government (2022R1A2C2007569, RS-2023-00207834).

15.

Data availability
All data needed to evaluate the conclusions in the paper are present in thepaper or the Supplementary Materials. RNA-Seq data are available throughthe National Center for Biotechnology Information Gene Expression Omnibus.
(GSE247033)

17.

Declarations
Ethics approval and consent to participate
All animal protocols were approved by the Institutional Ethical Committee,
Yonsei University College of Medicine (2020 − 0317). All experiments were
performed in accordance with the approved guidelines of the Institutional
Ethical Committee.

16.

18.
19.
20.

21.
22.

Consent for publication
Not applicable.
Competing interests
The authors declare no competing financial interests.

23.
24.

Received: 17 December 2023 / Accepted: 20 May 2024
25.
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