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\begin{document}

\title{Porphyromonas gingivalis -Stimulated Hyperglycemic Microenvironment
Alters the Immunometabolism of Dendritic Cells}



\author[1]{Binchen Yao}%
\author[1]{Maryam Ghaffari}%
\author[2]{Kenneth Ting}%
\author[3]{Minna Woo}%
\author[2]{Daniel A. Winer}%
\author[1]{Annie Shrestha}%
\affil[1]{University of Toronto Faculty of Dentistry}%
\affil[2]{University of Toronto Department of Laboratory Medicine and Pathobiology}%
\affil[3]{University of Toronto Temerty Faculty of Medicine}%


\vspace{-1em}



  
  \date{May 21, 2024}


\begingroup
\let\center\flushleft
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\selectlanguage{english}
\begin{abstract}
Introduction: Periodontitis in patients with diabetes mellitus results
in chronic inflammation, which is the central issue in developing an
efficient and consistent treatment plan. Dendritic cells (DC) are
antigen presenting cells that initiate the immune inflammatory responses
and contribute to the pathogenesis of both diseases. In this study, we
investigated the impact of hyperglycemic microenvironment on DC
immunometabolism, the cell phenotypes and immunogenic functions.
Methodology: Human monocyte differentiated DC and mice bone marrow
derived DC were cultured in the presence of 5.5-, 11-, and 25- mM
glucose to simulate diabetic microenvironment. Cells were activated with
advanced-glycation-end product (AGE) and lipopolysaccharides (LPS) from
\emph{Porphyromanas gingivalis} for 24 hours and processed for
transcription, metabolic and microscopic analysis. Expression of
activation markers (CD80, CD83, CD86, HLA-DR) and proteins involved in
glycolysis (HK2, LDHA, GLUT1) in DC were calculated by qRT-PCR. Lactic
acid production and OXPHOS assays, including Seahorse metabolic flux
analyzer were utilized to determine the effects on metabolism. Impact on
the phagocytic capacity was analyzed using fluorescent microspheres
uptake. Cytokine expressions for tumor necrosis factor alpha {[}TNF- \selectlanguage{greek}α\selectlanguage{english}
{]}, interleukin {[}IL{]}-1 \selectlanguage{greek}β , \selectlanguage{english}IL-6, IL-10, and Interferon gamma
{[}IFN- \selectlanguage{greek}γ\selectlanguage{english} {]} were evaluated in cell supernatants from DC and DC-T cell
coculture. Results: Under simulated hyperglycemic microenvironment an
increase in cell dendrite extensions, and activation markers were
upregulated in both monocytes differentiated DC and BMDC. There was a
significant increase in glycolysis as evident from the gene expression,
cell metabolic flux, and lactic acid production. Cell OXPHOS activities
was reduced to compensate for the increase in glycolysis.
Pro-inflammatory cytokines (TNF- \selectlanguage{greek}α \selectlanguage{english}and IL-1 \selectlanguage{greek}β \selectlanguage{english}) were significantly
increased and this increase was directly proportional to the glucose
concentrations. Whereas, phagocytic capability of DC, and their ability
to activate T cells decreased with hyperglycemia. Conclusions:
Hyperglycemic microenvironment resulted in DC changes with increased
expressions of activation markers, glycolytic metabolism, and increased
pro-inflammatory cytokines, while impairing phagocytosis and adaptive
immunity induction. BMDC and human monocyte differentiated-DC exhibit
similar responses toward hyperglycemia, AGE, and LPS. This work
emphasizes that diabetes mellitus has an inflammatory impact on DC
immunometabolism and immunogenic functions.%
\end{abstract}%



\sloppy


\emph{Porphyromonas gingivalis}\textbf{-Stimulated Hyperglycemic
Microenvironment Alters the Immunometabolism of Dendritic Cells}

\textbf{Binchen Yao} \textsuperscript{1}, \textbf{Maryam Ghaffari}
\textsuperscript{1}, \textbf{Kenneth Ting\textsuperscript{2}}
,\textbf{Minna Woo} \textsuperscript{3,4}, \textbf{Daniel A. Winer}
\textsuperscript{2,3,4,5,6}, \textbf{Annie Shrestha}
\textsuperscript{1,2,*}

\begin{enumerate}
\tightlist
\item
  Faculty of Dentistry, University of Toronto, 124 Edward Street,
  Toronto, ON, M5G 1G6, Canada
\item
  Department of Laboratory Medicine and Pathobiology, University of
  Toronto, 1 King's College Circle, Toronto, ON M5S 1A8, Canada
\item
  Division of Cellular and Molecular Biology, Diabetes Research Group,
  Toronto General Hospital Research Institute (TGHRI), University Health
  Network, Toronto, ON M5G 1L7, Canada
\item
  Department of Immunology, University of Toronto, Toronto, ON M5S 1A8,
  Canada
\item
  Department of Pathology, University Health Network, Toronto, ON M5G
  2C4, Canada
\item
  Buck Institute for Research on Aging, 8001 Redwood Boulevard, Novato,
  CA 94945, USA
\end{enumerate}

\textbf{Correspondence:}

Annie Shrestha

Annie.Shrestha@dentistry.utoronto.ca

\textbf{Keywords: Dendritic cells, periodontitis, diabetes mellitus,
hyperglycemia, immunometabolism}

\textbf{Abstract} :

Introduction: Periodontitis in patients with diabetes mellitus results
in chronic inflammation, which is the central issue in developing an
efficient and consistent treatment plan. Dendritic cells (DC) are
antigen presenting cells that initiate the immune inflammatory responses
and contribute to the pathogenesis of both diseases. In this study, we
investigated the impact of hyperglycemic microenvironment on DC
immunometabolism, the cell phenotypes and immunogenic functions.

Methodology: Human monocyte differentiated DC and mice bone marrow
derived DC were cultured in the presence of 5.5-, 11-, and 25- mM
glucose to simulate diabetic microenvironment. Cells were activated with
advanced-glycation-end product (AGE) and lipopolysaccharides (LPS)
from\emph{Porphyromanas gingivalis} for 24 hours and processed for
transcription, metabolic and microscopic analysis. Expression of
activation markers (CD80, CD83, CD86, HLA-DR) and proteins involved in
glycolysis (HK2, LDHA, GLUT1) in DC were calculated by qRT-PCR. Lactic
acid production and OXPHOS assays, including Seahorse metabolic flux
analyzer were utilized to determine the effects on metabolism. Impact on
the phagocytic capacity was analyzed using fluorescent microspheres
uptake. Cytokine expressions for tumor necrosis factor alpha
{[}TNF-\(\alpha\){]}, interleukin {[}IL{]}-1\(\beta\),
IL-6, IL-10, and Interferon gamma {[}IFN-\(\gamma\){]} were
evaluated in cell supernatants from DC and DC-T cell coculture.

Results: Under simulated hyperglycemic microenvironment an increase in
cell dendrite extensions, and activation markers were upregulated in
both monocytes differentiated DC and BMDC. There was a significant
increase in glycolysis as evident from the gene expression, cell
metabolic flux, and lactic acid production. Cell OXPHOS activities was
reduced to compensate for the increase in glycolysis. Pro-inflammatory
cytokines (TNF-\(\alpha\) and IL-1\(\beta\)) were
significantly increased and this increase was directly proportional to
the glucose concentrations. Whereas, phagocytic capability of DC, and
their ability to activate T cells decreased with hyperglycemia.

Conclusions: Hyperglycemic microenvironment resulted in DC changes with
increased expressions of activation markers, glycolytic metabolism, and
increased pro-inflammatory cytokines, while impairing phagocytosis and
adaptive immunity induction. BMDC and human monocyte differentiated-DC
exhibit similar responses toward hyperglycemia, AGE, and LPS. This work
emphasizes that diabetes mellitus has an inflammatory impact on DC
immunometabolism and immunogenic functions.

\textbf{Introduction} :

Periodontitis and diabetes mellitus (DM) are both chronic diseases with
a high prevalence and have a strong inter-relationship (1).
Periodontitis affects approximately 25 -- 50\% of the adult population
worldwide, and is considered as the main cause of tooth loss (2). On the
other hand, DM is a multifactorial metabolic disease affecting at least
422 million people globally (3). DM is characterized by hyperglycemia
due to impairment in either insulin secretion or its action, or both
(4). Previous clinical studies have reported that DM is a major risk
factor for periodontitis and its treatment outcome (2). DM can increase
the severity/prevalence of periodontitis by three folds (1).
Interestingly, there is a significant likelihood for periodontitis
patients to have uncontrolled DM. So it is not surprising that a strict
glycemic control and treating periodontitis can improve the treatment
outcome of periodontitis and DM (1,5).

Chronic inflammation and impaired immune cell responses are the key
linkers between the two diseases (6). Pro-inflammatory cytokines such as
TNF-\(\alpha\), IL-1\(\beta\) and IL-6, and
inflammatory molecules such as advanced glycation end products (AGE),
adipokines, RANKL, and reactive oxygen species (ROS) generated by
hyperactivated immune cells in each disease condition could exacerbate
the other and react with the immune cells to damage their respective
immunogenic responses. If this persists for long, it could result in a
negative feedback on local tissue inflammation and bone resorption in
patients with periodontitis and DM (6--8).

Recent studies have emphasized that metabolic programming of immune
cells tightly controls their expression, differentiation, and functions
(9--11). A Warburg effect is commonly adopted by both innate and
adaptive immune cells to fulfill their respective immunogenic functions,
where glycolysis is upregulated ; and this dysregulation could directly
promote pathogenesis of both periodontitis and DM (12). Innate immune
cells such as neutrophils use glycolysis for adhesion and microbicidal
activities, but systemic glucose or infectious microenvironment could
reduce this metabolic reprogramming, thereby promote bacterial
infections and insulin resistance (13,14). It is possible to determine
if adaptive T and B cells will transition to glycolysis or remains on
mitochondrial metabolism based on their effector or memory subsets. In
DM and periodontitis, the metabolism of T and B cells were altered with
attenuated effector functions via mTORC1 and AMPK related pathway
(10,15,16). Such metabolic reprograming from mitochondrial respiration
to glycolysis is also required for the activation and function of
dendritic cell (DC), the most efficient antigen presenting cells (APC)
that connect the innate and adaptive immunity (17--19).

Pathogen associated molecular patterns (PAMPs), or danger associated
molecular patterns (DAMPs) signals initiates phenotypic and functional
changes in DCs upon interacting with its surface receptors. DCs
upregulate surface co-stimulatory activation markers upon phagocytosis
of the antigens, which upregulates cytokine secretions, and migrations
to lymph node for T cell activations (20). For oral immune homeostasis,
DCs play a crucial role as their absence or dysfunction directly
promotes periodontal inflammation via uncontrolled bacterial infection
(21,22). Recent studies have also emphasized on the essential role of DC
in DM autoimmune responses and suggested its potential to be good a
therapeutic target in DM (23,24). There is enough evidence to point at
DCs in the pathogenesis of periodontitis complicated with DM.
Conflicting DC phenotypes and functions were reported in these two
diseases, with a combination of upregulated and suppressed activation
markers CD80 and CD86 and an overall upregulated pro-inflammatory
cytokine profile. However, the specific effect on DC immunometabolism in
response to periodontal pathogen complicated by diabetic
microenvironment is vague. To date, there are no reports on how the
underlying immunometabolism may govern these dysregulated phenotypes and
immunogenic functions of DC in periodontitis and DM.

In this study we investigated the potential alterations of DC
immunometabolism induced by periodontal bacterial LPS, complicated with
hyperglycemia. DCs were exposed to an \emph{in vitro} microenvironment
simulating periodontal infections and diabetic hyperglycemia by using
LPS from oral bacteria \emph{Porphyromonas gingivalis} (\emph{P.
gingivalis} ), different glucose concentrations, and AGE. We
hypothesized that these stressors could dysregulate the DC
immunometabolism, specifically the glycolysis pathway and its downstream
mitochondrial respiration, therefore impairing the cell phenotypes and
functions.

\textbf{Material \& Methods}

Monocyte-differentiated DC culture

Human monocyte cell line THP-1 were differentiated into DC using a
well-established protocol (25). THP-1 cells were cultured in complete
cell culture medium (RPMI-1640, Gibco, with 10\% FBS, Sigma-Aldrich,
antibiotic-antimycotic solution, Gibco and 2-Mercaptoethanol, Gibco)
with 5.5 mM glucose, 11 mM glucose, and 25 mM glucose and supplements of
IL-4 (20 ng/mL) and GM-CSF (20 ng/mL) for 5 days to differentiate into
immature DC. Fresh media were replenished every 2 days. On Day 5,
suspended cells were collected and cultured in RPMI with 5.5 mM glucose,
11 mM glucose, and 25 mM glucose and supplements of IL-4 (20 ng/mL,
LifeSciences), GM-CSF (20 ng/mL, LifeSciences), TNF-\(\alpha\)
(20 ng/mL, LifeSciences), and ionomycin calcium (20 ng/mL,
Sigma-Aldrich) to differentiated into mature DC for 24 hours. Dendrites
formation and cell adherences confirms the differentiation. On Day 6,
differentiated DC were seeded in a 6 well plate with a density of
1\(\times\)10\textsuperscript{6} cells/2 mL cell culture medium
per well with supplements of GM-CSF (20 ng/mL), ionomycin calcium (20
ng/mL),\emph{P. gingivalis} lipopolysaccharides (LPS, 1
\(\mu\)g/mL, Invitrogen) and advanced glycation endproduct
(AGE, 2 \(\mu\)g/mL, Sigma-Aldrich) for 24 hours. Cells were
cultured at 37 and 5\% CO\textsubscript{2}.

BMDC culture

Bone marrow cells were extracted from femur and tibia bone of 6 -- 12
weeks old C57BL/6 mice and plated on a 100 mm Petri culture dish at a
density of 4\(\times\)10\textsuperscript{6} cell/10 mL with
GM-CSF (20 ng/mL) in complete cell culture medium RPMI-1640 (Gibco) with
glucose concentration of 5.5 mM, 11 mM, and 25 mM. BM cultures were fed
on Day 3 and 6 with 10 mL cell culture medium containing fresh GM-CSF
(20 ng/mL, Biolegend). On Day 9, BMDC were seeded in a 6 well plate with
a density of 1\(\times\)10\textsuperscript{6} cells/2 mL cell
culture medium per well. \emph{P.gingivalis} lipopolysaccharides (LPS, 1
\(\mu\)g/mL, Invitrogen) and advanced glycation endproduct
(AGE, 2 \(\mu\)g/mL, Sigma-Aldrich) was added for 24 hours.
Cells were cultured at 37 and 5\% CO\textsubscript{2}.

Splenic T cell extraction

Spleens from C57BL/6 mice were minced and passed through a 40
\(\mu\)m strainer prior to T lymphocyte isolation. Mice T
cells were purified from splenic cell suspension using
EasySep\textsuperscript{TM} Mouse T Cell Isolation Kit (Stemcell
Technologies) following the manufacturer's protocol.

DC-T cell coculture

0.5\(\times\)10\textsuperscript{6} splenic T cells were cultured
in a 12 well plate with inactivated BMDC cultures at 1:1 ratio
supplemented with GM-CSG (20 ng/mL, Biolegend) for three days with or
without AGE (2\(\mu\)g/mL, Sigma-Aldrich) and LPS (1
\(\mu\)g/mL, Invitrogen). On Day 3, cell supernatant were
collect for ELISA analysis. All cells were cultured at 37 and 5\%
CO\textsubscript{2}.

Cell Morphology Assay

The differentiated mDC were grown in different glucose concentrations
with or without activation. The cells were fixed on glass coverslips at
a density of 0.8\(\times\)10\textsuperscript{6} and stained
with Hoechst dye (Sigma), TRITC-conjugated phalloidin (Sigma), CD83
primary antibody (Invitrogen), and FITC-conjugated secondary antibody
(Invitrogen). Cells were imaged using a fluorescent microscope system
(Zeiss LSM 800, Germany). Nine random areas were imaged at
40\(\times\) magnification and the images were processed with
Fiji ImageJ software.

Effect on DC Phenotype and Metabolism- Gene Expression Assays

Total RNA of inactivated or activated DC was extracted using RNeasy mini
kit (Qiagen) and the cDNA was synthesis using SensiFAST cDNA Synthesis
kit (Bioline) with random primers. Quantitative real time RT-PCR was
performed using SYBR Green Master Mix Reagent (Applied Biosystems) by
CFX Real Time System (Bio-Rad). Each sample was analyzed in triplicates
and normalized to control gene \(\beta\)-actin. Relative
expression was reported using the \(2^{\hat{}(\Delta Ct)}\) method. Table 1
and Table 2 presents the primer sequences used in the experiments.

Metabolic assay

The glycolysis activity of monocyte-differentiated DC was measured using
Agilent Seahorse XFe24 metabolic flux analyzer with glycolytic stress
test kit (Agilent Technologies). DC were seeded at a density of
1.75\(\times\)10\textsuperscript{5} in the 24-well XF Cell
Culture Microplate. The extracellular acidification rate (ECAR) of the
cells were measured in triplicate following each injection of glucose,
oligomycin, and 2-deoxy-glycose. L-lactate from cell supernatant was
quantified following the manufacturers protocol (Cayman Chemical).
OXPHOS activity was measured using a commercial kit (Thermofisher).

Cytokine profile

The supernatants from monocyte-differentiated DC culture and BMDC
culture were collected on Day 7 and stored at -20 until further use.
Cytokine production by the DC were assessed using ELISA
(IFN-\(\gamma\), IL-6, IL-17, and IL-10) (Biolegend,
California, United States) following manufacturers protocol.

Phagocytosis assay

Inactivated BMDC were used in phagocytosis assay. Approximately
1\(\times\)10\textsuperscript{6} cells were seeded in a 6 well
plate (Corning) with 2 mL complete cell culture medium RPMI-1640 (Gibco)
supplemented with GM-CSF (20 ng/mL, Biolegend). Cells were cultured with
5.68\(\times\)10\textsuperscript{7} Fluoresbrite carboxylate
microspheres for 3 hours to assess cell phagocytosis. Cells were washed
and stained with Hoechst dye (Sigma) and imaged using a fluorescent
microscope system (Zeiss LSM 800, Germany). Six random areas were imaged
at 10\(\times\) magnification and the images were processed
with Fiji ImageJ software.

Statistical Analysis

The experiments were done in triplicates and repeated minimum of three
times. All data were analyzed with GraphPad Prism with unpaired t test
and ANOVA test. The difference between experimental groups was set to be
statistically significant at \emph{P} \(<\) 0.05.

\textbf{Results}

\textbf{High glucose modulates DC morphology}

Impact of hyperglycemia (11- or 25-mM glucose) was examined on
inactivated or \emph{P. gingivalis} LPS and AGE-product activated mDC
differentiated from human monocytes using immunofluorescence staining.
At the glucose concentration of 5.5 mM, inactivated mDCs had a spherical
or elliptical morphology with few dendrites (Figure 1A). Without
stimulation, or by increasing the glucose concentrations alone increased
dendrites on the surface of cells, indicating cell spread and maturation
(Figure 1. C, E). However, in presence of LPS and AGE, dendrites
formation on activated mDC was stimulated in all three glucose
concentrations, yet the cells in 11- and 25-mM glucose had more extended
dendrites in comparison to the 5.5 mM glucose culture (Figure 1. B, D,
F). Both inactivated and activated mDCs in all three glucose
concentrations expressed CD83 (Figure 1. A-F).

\textbf{DC phenotypes are modulated under hyperglycemia}

To assess the impact of glucose on BMDC activation, we next performed
RT-qPCR for surface markers CD80, CD86, CD83, and MHC-II
complex\emph{.}The relative mRNA expressions are reported as fold change
in comparison to the inactivated cells cultured in 11 mM glucose (Figure
2. A -- D). The co-stimulatory markers CD80, CD83, and MHC-II were
significantly upregulated in the presence of AGE and LPS in 11 mM
glucose cell cultures. These three genes' expression were also increased
upon activation in 25 mM glucose but with this difference was not
statistically significant except for MHC-II (Figure 2. A, C, D).
Elevated CD86 was observed in both 11 mM and 25 mM glucose cultures with
not statistical difference (Figure 2. B). Human monocyte
differentiated-mDC demonstrated comparable findings, which LPS and AGE
significantly upregulated expression of CD80, CD86, and HLA-DR (Figure 2
E -- H). Expression level of CD83 was not statistically different
(Figure G).

\textbf{Hyperglycemia upregulates DC glycolysis activity}

We then examined the expression of genes involved in glycolysis under
different glucose concentrations in BMDC. All gene expressions were
adjusted relative to the inactivated cells cultured in 11 mM glucose. A
glucose dose-dependent increase was observed in mRNA of all three
analyzed genes in inactivated and activated DC (Figure 3. A -- C). Cells
cultured in 11 mM glucose were significant elevation in HK2 and LDHA but
not GLUT1 upon activation by AGE and LPS, while cell activation
significantly upregulated LDHA in 25 mM glucose culture, but not a
statistical increase for HK2 and GLUT1 levels, (Figure 3 A -- C).
Similar increase in the expression of genes associated with glycolysis
in response to increasing glucose levels was observed in
monocyte-differentiated DC. Furthermore, these glycolysis genes were
significantly up in the presence of AGE and LPS (Figure 3 D -- F).

To further corroborate the effect on DC glycolysis, we utilized Seahorse
Glycolysis Street Test to measure the glycolysis activity under 5.5 mM,
11 mM, and 25 mM glucose with or without LPS and AGE stimulations. In
the absence of AGE and LPS, the inactivated mDC previously cultured in
higher glucose concentrations exhibited high extracellular acidification
rate (ECAR) that was proportional to the relative glycolysis activity
when glucose was supplemented (Figure 3G). This increase in ECAR value
was observed to be directly dependent on glucose concentrations.
Activation of mDC by AGE and LPS further upregulated the ECAR and the
cell glycolysis, such that higher ECAR values was observed with the
similar glucose dose-dependent increasing trend, except for the
activated mDC cultured in 25 mM glucose (Figure 3H). This alteration in
cell metabolic flux was also reflected on the glycolysis rate and
maximal glycolytic capacity (Figure 3I -- J).

Extracellular L-Lactate secreted from the cells also demonstrated a
dose-dependent increase with the increasing glucose concentration in
both inactivated and activated DC, and the cell activations resulted in
a higher L-Lactate release under all glucose conditions (Figure 3K). On
the other hand, the DC OXPHOS activity, measured by the relative
intensity of the cell membrane potential, gradually decreased with the
increasing glucose concentrations, with or without the stimulation of
AGE and LPS (Figure 3L).

\textbf{Elevated glucose concentration attenuates DC phagocytosis}

By coculturing the inactivated BMDC with Fluoresbrite carboxylate
microspheres and staining the cell nucleus, we next the impact of
glucose on DC phagocytosis capability using fluorescent microscopy. A
reduction in inactivated BMDC phagocytosed-Fluoresbrite microspheres was
observed with the increase in glucose concentration from 5.5 mM to 25 mM
(Figure 4. A -- C). Quantification of relative fluorescent microsphere
to cell nucleus ratio significant decreased from 1.2 to 0.5 according to
glucose concentrations (Figure 4. D).

\textbf{Hyperglycemia boost pro-inflammatory cytokine production in DC}

An increase in pro-inflammatory cytokines TNF-\(\alpha\) and
IL-1\(\beta\) was observed for the inactivated and activated
BMDC and human monocyte differentiated DC in presence of high glucose
concentrations (Figure 5). Activation of the cells by AGE and LPS
significantly upregulated both inflammatory cytokines (Figure 5. A, B,
D, E). On the other hand, anti-inflammatory cytokine, IL-10, showed a
similar trending but no significant elevation was observed upon
activation in BMDC, while it was significantly up in human monocyte
differentiated DC (Figure 5. C, F). Stimulation of human monocyte
differentiated DC with AGE alone demonstrated limited impact, while the
stimulation with LPS alone induced potent upregulation of
TNF-\(\alpha\). TNF-\(\alpha\) levels under these
separate stimulation also increased with increasing glucose
concentrations, and AGE and LPS together showed an additive effect on
TNF-\(\alpha\) secretions with glucose (Supplementary Figure 1).

\textbf{T cell function is impaired when primed with DC cultured in
hyperglycemic conditions}

We co-cultured mouse BMDC with mouse splenic T cells to investigate the
impact of hyperglycemia on DC priming and T cell functions. T cells
incubated with BMDC in the absence of AGE and LPS gradually reduced the
levels of pro-inflammatory cytokines, IFN-\(\gamma\) and IL-17,
which was inversely relative to the increasing glucose concentration
(Figure 6. A, C). AGE and LPS resulted in activation of DC that further
activated T cells. In comparison to the unstimulated cells, levels of
both cytokines significantly increased in all glucose concentrations
upon AGE and LPS-stimulation. Cytokines released from these activated
cells showed an inverse correlation with the glucose concentrations. The
level of IL-6 from T cells also decreased with increasing glucose
concentration in the unstimulated culture. However, upon stimulation,
IL6 significantly increased to approximately 1020 pg/mL in 5.5 mM, 11
mM, and 25 mM glucose concentrations. (Figure 6. B).

\textbf{Discussion}

In this study, we have demonstrated that the stimulation of AGE,
hyperglycemia, and LPS from oral bacterial \emph{P. gingivalis} can
synergistically dysregulate the DC phenotype, immunometabolism, and
effector functions. Hyperglycemia and infection-activated immune cells
together induce inflammation, which is the key to connect periodontitis
and DM, two chronic inflammatory diseases with a bidirectional
relationship to each other. The Warburg effect-like transition from
mitochondrial oxidative phosphorylation to aerobic glycolysis as the
main pathway for ATP generation is one critical step for DC activation
upon interaction between antigen and TLR (26). Interaction between LPS
and surface TLR on DCs could activate the glycolysis transition via
Akt-induced signaling, initiated by TLR-associated TBK1 and
IKK\(\varepsilon\) proteins, thus the Akt downstream protein mTORC1
is also determined to be involve in the glucose-sensitive transduction
circuit for glycolysis metabolism transition (27,28). PFKFB3, an major
driver of glycolysis pathway, is identified as a direct target mTOR
under LPS stimulation (29). Our data showed a significant increase in
gene expression of enzymes such as HK2, LDHA, and GLUT that catalyzes
different steps of glycolysis. In the presence of LPS, levels of
L-lactate, which is the final product of glycolysis, increased in DC.
The induction of glycolytic activity by LPS has been well reported in
other immune cells such as macrophages, monocytes, and neutrophils
(30--32). LPS can attenuate mitochondrial OXPHOS activity. In
macrophages LPS suppresses isocitrate dehydrogenase and succinate
dehydrogenase in the citric acid cycle, and blocks the mitochondrial
respiration while promoting glycolysis (33,34). Excessive citrate and
succinate, both upregulate inflammatory molecules such as NO and
IL-1\(\beta\) (33). On the other hand, cells under
hyperglycemia shunt glycolytic intermediates into pentose phosphate
pathway as a protective mechanism, which limits the glycolytic activity
(35,36). As macrophages and DC are closely inter-related in pro- and
anti-inflammatory phenotypes, similar pathways could be involved in DC.
Moreover, AGE can also reduce glycolysis and mitochondrial respiration
through HIF-1\(\alpha\)/PDK4 pathway, thereby reducing ECAR and
OCR (37,38). This may explain the observed inhibition of glycolysis
pathway in the LPS and AGE-stimulated group under hyperglycemia in the
cell metabolic efflux assay. An inhibitory effect of hyperglycemia and
AGE on glycolysis could reduce the stimulating effect from LPS. Under
diabetic microenvironment, glycolysis is not only disrupted by
hyperglycemia, AGE, and LPS, rather other DM-associated metabolites such
as ROS, free fatty acid, and cholesterol could also impact cell
immunometabolism transitions by regulating different signaling pathways
(31).

The relative expression of DC surface markers can reflect the cell
activation status. Upregulation of protein CD80, CD86, and MHC-II
complex is a key evidence of DC activation. Here we have shown that
depending on glucose concentration these three co-stimulatory molecules
can polarize the cells toward a hyperactivated status in both
inactivated and activated DC. Similar results were reported in DC
obtained from various lineages under \emph{in vitro} and \emph{in
vivo}stimulations (27,39,40). Thomas \emph{et al} demonstrated that
brief exposure of hyperglycemic culture could significantly elevate
co-stimulatory surface markers in all immature, mature, and tolerogenic
DC (39). BMDC retrieved from streptozotocin induced-diabetic mice showed
comparable phenotypes as well (27,39). Such increase in CD80, CD86,
CD1\(\alpha\), and MHC-II was also observed when comparing the
hyperglycemia treated-human monocyte derived DC to the normoglycemia
cell culture (40). Glucose and LPS activated-Akt pathway that initiate
glycolysis transition may also upregulate the expression of these DC
surface markers. The transcription factor NF-\(\kappa\)B
directly regulates the receptor genes that are involved in the cell
immunogenic functions (41,42). Note that the HIF-1\(\alpha\)
activated by Akt pathway during DC metabolic reprogramming is also a
transcription factor that regulate CD80 and CD86 expression (43,44).

The metabolic reprogramming in innate immune cells is a TLR induced
event paired with phagocytosis, which is a critical for rapid infection
clearance by APCs. Our data demonstrated that hyperglycemia
significantly impairs the phagocytosis by immature DC in a
glucose-dose-dependent manner. Similar results have been reported in DC
differentiated from human PBMC obtained from T2DM patients, where cells
were unable to take up the FITC-dextran fluorescein, or this uptake was
significantly reduced in hyperglycemic media (45). Similarly, in other
phagocytes such as macrophages and monocytes the phagocytotic abilities
were reduced in both \emph{in vitro} and \emph{in vivo} hyperglycemic
environment. High glucose locks the cell in their pro-inflammatory
phenotype that is characterized by dysregulated activation markers and
upregulated pro-inflammatory cytokines (46--48). Similar results were
seen in the present study where hyperglycemia induced a pro-inflammatory
DC with compromised phagocytic effect. Reduced phagocytosis in these
innate immune cells collectively under hyperglycemia can completely
impair the infection clearance; thus leading to the chronic
immune-inflammatory responses seen in periodontitis and DM patients (6).
Such lowered phagocytotic capability could also result from
hyperglycemia induced altered cell surface receptors. Under
hyperglycemia and hypoxia conditions, in the expression of genes
encoding CD36 and SCARB-1 in human monocyte-differentiated macrophages
is reduced. CD36 and SCARB-1 are proteins responsible for phagocytosis
(47). Expression of FC\(\gamma\) receptor CD32 and CD64 that
mediate phagocytosis with antigen recognition receptor CR3 in monocytes
were also reported to be reduced with increasing HbA\textsubscript{1c}
level and body mass index in DM patients (48). Interestingly, no
significant differences were observed in phagocytosis protein CD36 on DC
from DM patient but MFGE8, another phagocytosis protein was
significantly reduced (49). MFGE8 is frequently associated with impaired
phagocytosis of various phagocytes generally and under DM conditions
(50--52). However, there is limited knowledge to associate the reduced
MFGE8 levels with the aerobic glycolysis transition upon DC activation.
Either way, correcting the expression levels of this protein can result
in profound wound healing potential by promoting DC and macrophages into
immune suppressive phenotypes, which favors mitochondrial respiration
rather than glycolysis (53,54). The antigen presentation ability beyond
phagocytosis mechanism could also be impacted by hyperglycemia. High
glucose evidently delays antigen processing and impairs antigen
presentation in human monocyte-derived macrophages via repressed Rab and
Cathepsin, leading to reduced T cell activation (55). Defect in antigen
presentation has been reported in splenic macrophages from NOD mice
(56).

Exaggerated cytokine secretion is a characterized functional change upon
DC activation. Significant levels of pro-inflammatory cytokine,
TNF-\(\alpha\) and IL-1\(\beta\) from the activated DC
indicates that hyperglycemia, AGE, and LPS could together stress DC to
exert a more immunogenic state. Similar cytokine profiles were reported
in other studies from human and mice DC as each of the three stressors
are known to be pro-inflammatory (40,57,58). Besides their role in
interconnecting the chronic inflammatory states in periodontitis and DM,
such increase in these pro-cytokines may help in developing other
autoimmunity in innate immune cells as well. Recent studies have shown
that TNF-\(\alpha\) could stimulate the synovial fibroblast
cells to increase the glycolysis related-proton efflux and promote
rheumatoid arthritis, which is another risk factors associated with both
periodontitis and DM (59). Similarly, in autoimmune disease Sj\selectlanguage{ngerman}ögren
syndrome as well the inflammatory response between
TNF-\(\alpha\) and DC via TLR-7 and TLR-9 has been confirmed
(60). IL-1\(\beta\) can induce autocrine responses during
bacterial infection and reprogram the immunometabolism through
glycolysis (61). If this immunometabolism transition to aerobic
glycolysis can play a role in the trained immunity of DC under
hyperglycemic stress remains unclear, yet it is an important question
worth investigating.

DC have a unique capacity to induce activation and proliferation of
antigen specific T cell responses as its APC function in adaptive
immunity. The presence of co-stimulatory molecules CD80, CD86, and
MHC-II complex play an important role in T-cell activation; wherein,
signals from DC synergistically interact with both the T cell receptor
and CD28 on T cells for complete activation (62). On the other hand,
lack of any one of the co-stimulatory signals can result in immune
tolerance or ignorance of activation to prevent aberrant response of T
cells. Increase in the expression of DC co-stimulatory markers should
lead to hyperactivation of the T cell lymphocytes (63); however,
contradictory results were observed in our study. Although DC stimulated
with hyperglycemia, AGE, and LPS had high expression of co-stimulatory
markers , which increases with increase in glucose levels. T cells
cocultured with DC in higher glucose showed attenuated proliferation and
Th-1 type cytokine secretions, indicating a lowered T cell priming
capability. This was expected as the DC cultured in high glucose
concentration were more activated and matured while the phagocytosis
ability of immature DC is only optimal (64). Samuel \emph{et al} had
also indicated that Th1 is only secondary predominant while Th17 is the
predominant pathway in DM mice (65). Such impairment in the DC function
could also be due to compromised phagocytosis and antigen presentation
capability in hyperglycemia. Antigen presentation on DC is required for
the effective physical interaction and T cell activation \emph{in vivo}
, whereas unpulsed DC fail to induce lymphocyte responses as shown by
Ingulli \emph{et al} (66). Also, a minimum threshold antigen dose is
required for a stable DC-T cell priming (67). With attenuated
phagocytosis ability and therefore the lowered antigen presentation on
DC in hyperglycemia, the T cell activation is weak, and this may lead to
a prolonged inflammation in DM and periodontitis. However, the antigen
presentation using LPS model is a non-specific or bystander response
from T cells, as presence of LPS could induce inflammatory responses
from a wide array of cells. Extension of the adaptive immune responses
using OT-II mice may could help in further understand such compromised
antigen presentation from DC by pulsing DC and T cells co-culture with
specific antigens like ovalbumin (67).

Periodontitis is a chronic disease caused by a multispecies bacterial
biofilm, and DM is a systemic autoimmune disease that involves numerous
inflammatory molecules and immune cells. Therefore, the simple use of
bacterial LPS and hyperglycemia may not comprehensively mimic the
complicated disease microenvironment. \emph{In vivo} studies utilizing
diabetic mice with induced periodontitis could provide better
understanding of the diseased state and immune responses. While we
performed the transcription analysis of DC surface markers in this
study, it is possible that the hyperglycemia could affect the cell
translation mechanism. Furthermore, the intracellular localization of
the phagocytosed fluorescent microspheres would be an enticing next step
to understand the DC phagocytosis mechanism.

In conclusion, this study highlights that hyperglycemia with AGE and LPS
can polarize DC toward a more pro-inflammatory phenotype and cytokine
profile by upregulating glycolysis, but its phagocytosis and T cell
priming is compromised. Together, this DC function dysregulation may
explain the conflicting adaptive immune cell profiles observed in DM and
periodontitis.

\textbf{Data availability statement}

The raw data supporting the conclusion of this article will be made
availability by the authors, without undue reservation.

\textbf{Ethics statement}

The animal study was reviewed and approved by University of Toronto
animal use protocol (AUP) number 20012294.

\textbf{Author contributions}

BY and AS designed the experiments and analyzed data. BY and AS wrote
the paper. BY and MG performed the experiments and organized data. AS
and DW helped in overall study design and manuscript formation. All
authors contribute to the article and approve the submitted version.

\textbf{Acknowledgement}

Immunofluorescence imaging was performed at the CAMILOD Imaging Facility
of Dental Research Institute, University of Toronto, Toronto, ON,
Canada.

\textbf{Funding}

This study was supported by funding from the Foundation for Endodontics,
American Association of Endodontists (\#510174).

\textbf{Conflict of interest}

The authors deny any conflicts of interest related to this study.

\textbf{Contribution to the field statement}

Presence of hyperglycemia related to diabetes mellitus can negatively
impact immune inflammatory responses in chronic periodontitis by
influencing the antigen presenting dendritic cells. This study
highlighted that hyperglycemia impacted immunometabolism of dendritic
cells towards glycolysis and subsequent pro-inflammatory phenotypes.
Understanding dendritic cells' dysregulation may explain the conflicting
adaptive immune cell profiles observed in diabetes mellitus and chronic
periodontitis.

Figure 1.

A B\selectlanguage{english}
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C D\selectlanguage{english}
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\includegraphics[width=0.70\columnwidth]{figures/image4/image4}

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E F\selectlanguage{english}
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\includegraphics[width=0.70\columnwidth]{figures/image5/image5}

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\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image6/image6}

\end{center}
\end{figure}

\textbf{Figure 1.} Immunofluorescence image of inactivated mDC in 5.5-
(A), 11- (B), and 25 mM glucose (C); and immunofluorescence image of AGE
\& LPS-activated mDC in 5.5 mM glucose-(B), 11- (D) and 25 mM glucose
(F). The cell nucleus was stained with Hoechst dye (blue), the F-actin
was stained with TRITC-conjugated phalloidin (red), and the CD83 was
stained with FITC-conjugated antibody (green). Images were captured at
40\(\times\) magnification. Magnified areas from the respective
images are displayed on the top right corner to demonstrate cell
morphologies and dendrites formation.

Figure 2.

A B C

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D

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\textbf{Figure 2.} Relative gene expression of surface markers CD80,
CD86, CD83, and MHC-II in inactivated and AGE \& LPS-activated BMDC (A
-- D) and human monocyte differentiated mDC (E -- L) in 11 mM and 25 mM
glucose. Values were normalized to mRNA level of inactivated mDC in 11
mM glucose. (ns = not significant, *P\(<\)0.05,
**P\(<\)0.01, ***P\(<\)0.001).

Figure 3.

A B C

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G

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H

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I J\selectlanguage{english}
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K L

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\textbf{Figure 3.} Relative gene expression of glycolysis genes HK2,
LDHA, and GLUT1 in inactivated and AGE \& LPS-activated BMDC (A -- C)
and human monocyte differentiated-mDC (D -- F) in 5.5-, 11-, and 25-mM
glucose. Values were normalized to mRNA level of inactivated mDC in 11
mM glucose. (ns = not significant, *P\(<\)0.05,
**P\(<\)0.01, ***P\(<\)0.001). Overall rate
curves of metabolic flux of inactivated monocyte differentiated-DC (G)
and AGE \& LPS-activated monocyte differentiated-DC (H) in 5.5-, 11-,
and 25-mM glucose (plated in 75000 cells/well). Glycolysis rate (I) and
glycolytic capacity (J) of DC. Data demonstrated in units of
extracellular acidification rate (ECAR). (**P\(<\)0.01,
***P\(<\)0.001). Lactate production (K) and OXPHOS
activities (L) of inactivated and AGE \& LPS-activated BMDC in 5.5-,
11-, and 25-mM glucose. (ns = not significant,
*P\(<\)0.05).

Figure 4.

A B C\selectlanguage{english}
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D

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\textbf{Figure 4.} Immunofluorescence image of phagocytosed Fluoresbrite
carboxylate microspheres in inactivated BMDC in 5.5-(A), 11- (B) and 25
mM glucose (C). The cell nucleus was stained with Hoechst dye (blue).
Images were captured at 10\(\times\) magnification. (D)
Quantified relative ratio between fluorescent particle and Hoechst
stains. Values were normalized to ratio in 11 mM glucose culture.
(***P\(<\)0.001).

Figure 5.

A B C

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\textbf{Figure 5.} Cytokine profile of pro-inflammatory
TNF-\(\alpha\), IL-1\(\beta\), and anti-inflammatory
IL-10 secreted from inactivated and AGE \& LPS-activated BMDC (A -- C)
and human monocyte differentiated-mDC (D -- F) in 5.5-, 11-, and 25-mM
glucose. Cytokine concentrations were quantified using ELISA. (ns = not
significant, *P\(<\)0.05, ***P\(<\)0.001).

Figure 6.

A B C

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\textbf{Figure 6.} Cytokine profile of IFN-\(\gamma\) (A), IL-6
(B), and IL-17 (C) secreted from splenic T cells primed by inactivated
and AGE \& LPS-activated BMDC in 5.5-, 11-, and 25-mM glucose. Cytokine
concentrations were quantified using ELISA. (ns = not significant,
*P\(<\)0.05, ***P\(<\)0.001).

\textbf{Table 1.} Primers used in RT-PCR experiments for BMDC.

Oligonucleotides\selectlanguage{english}
\begin{longtable}[]{@{}llll@{}}
\toprule
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Primers used for qPCR\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Primers used for qPCR\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Source\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Reference\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
HK2\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
Forward primer CTTACCGTCTGGCTGACCAACAC\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
ThermoFisher Scientific\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
(68)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Reverse primer CTCCATTTCCACCTTCATCCTTCT\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
LDHA\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
Forward primer TGCGTGCTGGAGCCACT\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
ThermoFisher Scientific\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
(69)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Reverse primer GCGAGGAGAAGCAGCGTG\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
GLUT1\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
Forward primer GGCCTGACTACTGGCTTTGT\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
ThermoFisher Scientific\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
(70)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Reverse primer TGCATTGCCCATGATGGAGT\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
\(\beta\)-actin\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
Forward primer CGTGCGTGACATCAAAGAGAA\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
ThermoFisher Scientific\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
(71)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Reverse primer TGGATGCCACAGGATTCCAT\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Oligonucleotides\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Oligonucleotides\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Oligonucleotides\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Oligonucleotides\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Primers used for qPCR\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Primers used for qPCR\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Source\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Reference\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
CD80\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
Forward primer ACCCCCAACATAACTGAGTCT\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
ThermoFisher Scientific\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
(72)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Reverse primer TTCCAACCAAGAGAAGCGAGG\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
CD83\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
Forward primer CGCAGCTCTCCTATGCAGTG\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
ThermoFisher Scientific\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
(72)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Reverse primer GTGTTTTGGATCGTCAGGGAATA\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
CD86\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
Forward primer CTGGACTCTACGACTTCACAATG\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
ThermoFisher Scientific\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
(72)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Reverse primer AGTTGGCGATCACTGACAGTT\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
MHC-II\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
Forward primer AGCCCCATCACACTGTGGAGT\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
ThermoFisher Scientific\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
(73)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Reverse primer GATGCCGCTCAACATCTTGC\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}

\textbf{Table 2.} Primers used in RT-PCR experiments for human monocyte
differentiated-DC.

Oligonucleotides\selectlanguage{english}
\begin{longtable}[]{@{}llll@{}}
\toprule
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Primers used for qPCR\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Primers used for qPCR\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Source\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Reference\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
HK2\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
Forward primer GAGTTTGACCTGGATGTGGTTGC\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
ThermoFisher Scientific\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
(74)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Reverse primer CCTCCATGTAGCAGGCATTGCT\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
LDHA\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
Forward primer ATGGCAACTCTAAAGGATCAGC\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
ThermoFisher Scientific\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
(75)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Reverse primer CCAACCCCAACAACTGTAATCT\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
GLUT1\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
Forward primer CTGCTCATCAACCGCAAC\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
ThermoFisher Scientific\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
(76)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Reverse primer CTTCTTCTCCCGCATCATCT\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
\(\beta\)-actin\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
Forward primer CGGGACCTGACTGACTAC\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
ThermoFisher Scientific\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
(77)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Reverse primer GAAGGAAGGCTGGAAGAG\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Oligonucleotides\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Oligonucleotides\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Oligonucleotides\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Oligonucleotides\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Primers used for qPCR\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Primers used for qPCR\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Source\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Reference\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
CD80\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
Forward primer CTCTTGGTGCTGGCTGGTCTTT\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
ThermoFisher Scientific\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
(78)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Reverse primer GCCAGTAGATGCGAGTTTGTGC\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
CD83\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
Forward primer TACAGAGCGGAGATTGTCCTGC\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
ThermoFisher Scientific\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
(79)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Reverse primer GCTCGTTCCATGCCAGCTTTAG\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
CD86\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
Forward primer CCATCAGCTTGTCTGTTTCATTCC\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
ThermoFisher Scientific\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
(80)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Reverse primer GCTGTAATCCAAGGAATGTGGTC\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
HLA-DR\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
Forward primer GTCTGGCGGCTTGAAGAATT\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
ThermoFisher Scientific\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
(81)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Reverse primer ACCTTGAGCCTCAAAGCTGG\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}

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