International Journal of
            Molecular Sciences

Article
From Inflammation to the Onset of Fibrosis through
A2A Receptors in Kidneys from Deceased Donors
Elena Guillén-Gómez 1,2,3, * , Irene Silva 2,3,4 , Núria Serra 2,3,4 , Francisco Caballero 5 ,
Jesús Leal 5 , Alberto Breda 6 , Rody San Martín 7 , Marçal Pastor-Anglada 8,9 , José A. Ballarín 2,3 ,
Lluís Guirado 2,4 and Montserrat M. Díaz-Encarnación 2,3, *
 1    Molecular Biology Laboratory, Fundació Puigvert, 08025 Barcelona, Spain
 2    Nephrology Department, Fundació Puigvert, 08025 Barcelona, Spain; isilva@fundacio-puigvert.es (I.S.);
      nserra@fundacio-puigvert.es (N.S.); jballarin@fundacio-puigvert.es (J.A.B.);
      lguirado@fundacio-puigvert.es (L.G.)
 3    Institut Investigació Biosanitaria Sant Pau, Fundación Renal Iñigo Álvarez de Toledo (FRIAT), REDinREN,
      Autonomous University of Barcelona (UAB), 08025 Barcelona, Spain
 4    Renal Transplant Unit, Fundació Puigvert, 08025 Barcelona, Spain
 5    Department of Emergency Medicine and Transplant Coordination, Hospital de la Santa Creu i Sant Pau,
      Universitat Autònoma de Barcelona, 08041 Barcelona, Spain; FCaballero@santpau.cat (F.C.);
      jleal@santpau.cat (J.L.)
 6    Urology Department, Autonomous University of Barcelona (UAB), Fundació Puigvert, 08025 Barcelona,
      Spain; abreda@fundacio-puigvert.es
 7    Molecular Pathology Laboratory, Institute of Biochemistry and Microbiology, Faculty of Sciences,
      Universidad Austral de Chile, 5110566 Valdivia, Chile; rodysanmartin@uach.cl
 8    Department of Biochemistry and Molecular Biomedicine, Institute of Biomedicine (IBUB), University of
      Barcelona, National Biomedical Research Institute of Liver and Gastrointestinal Diseases (CIBER EHD),
      08028 Barcelona, Spain; mpastor@ub.edu
 9    Institut de Recerca Sant Joan de Déu (IR SJD), 08950 Esplugues de Llobregat Barcelona, Spain
 *    Correspondence: lnagugo10@gmail.com (E.G.-G.); mmdiaz@fundacio-puigvert.es (M.M.D.-E.)
                                                                                                     



 Received: 15 October 2020; Accepted: 20 November 2020; Published: 21 November 2020                  



 Abstract: Pretransplant graft inflammation could be involved in the worse prognosis of deceased
 donor (DD) kidney transplants. A2A adenosine receptor (A2A R) can stimulate anti-inflammatory
 M2 macrophages, leading to fibrosis if injury and inflammation persist. Pre-implantation biopsies
 of kidney donors (47 DD and 21 living donors (LD)) were used to analyze expression levels and
 activated intracellular pathways related to inflammatory and pro-fibrotic processes. A2A R expression
 and PKA pathway were enhanced in DD kidneys. A2A R gene expression correlated with TGF-β1 and
 other profibrotic markers, as well as CD163, C/EBPβ, and Col1A1, which are highly expressed in
 DD kidneys. TNF-α mRNA levels correlated with profibrotic and anti-inflammatory factors such
 as TGF-β1 and A2A R. Experiments with THP-1 cells point to the involvement of the TNF-α/NF-κB
 pathway in the up-regulation of A2A R, which induces the M2 phenotype increasing CD163 and
 TGF-β1 expression. In DD kidneys, the TNF-α/NF-κB pathway could be involved in the increase of
 A2A R expression, which would activate the PKA–CREB axis, inducing the macrophage M2 phenotype,
 TGF-β1 production, and ultimately, fibrosis. Thus, in inflamed DD kidneys, an increase in A2A R
 expression is associated with the onset of fibrosis, which may contribute to graft dysfunction and
 prognostic differences between DD and LD transplants.

 Keywords: fibrosis; macrophage; inflammation; transplant; kidney; purinome; adenosine receptor




Int. J. Mol. Sci. 2020, 21, 8826; doi:10.3390/ijms21228826                          www.mdpi.com/journal/ijms
Int. J. Mol. Sci. 2020, 21, 8826                                                                    2 of 17



1. Introduction
      Many factors specific to kidney transplant recipients (KTR) and donors influence the outcome
of kidney transplantation [1–3] and prognostic differences between living and deceased grafts are
well known. Despite this, little is known about the basal inflammatory status of donors at the time
of donation [4]. Immunological activation during brain death results in infiltration of leukocytes,
macrophages, and dendritic cells prior to kidney procurement [5–7], which can damage kidneys [8]
and impact on short- and long-term renal graft function [9,10]. We showed previously that circulating
monocytes from KTR are associated with prognosis in kidney transplantation [11]. Furthermore,
different studies indicated macrophages accumulation in allograft biopsies of KTR [12], which is
associated with renal interstitial fibrosis and tubular atrophy and graft outcome [13]. In fact, our group
demonstrated that macrophage infiltration into renal grafts of deceased donors before transplantation
is associated with long-term renal function [14]. Pre-implantation renal biopsies from deceased donors
showed greater inflammation than those from living donors and this appeared to be mediated by M1
macrophages, although the presence of M2 macrophages was also observed, suggesting the coexistence
of both phenotypes and even intermediate phenotypes [14]. Macrophage phenotype is modulated by
adenosine, diminishing M1 proinflammatory macrophage activation and polarizing macrophages to
an M2 anti-inflammatory phenotype [15,16]. Extracellular adenosine produced from hydrolysis of ATP
(primarily by the ectoenzymes CD39 and CD73) mediates its effects via activation of G-protein-coupled
receptors (A1, A2A, A2B, and A3). In the peritransplant period or during ischemia/reperfusion, ATP is
released early after cell damage/death, inducing activation of immune cells that migrate to the site of
injury [17,18]. Pannexin (Panx)-1 forms transmembrane channels that release ATP into the extracellular
space. It is expressed ubiquitously and, in the kidney, Panx-1 is needed for the release of intracellular
ATP from renal epithelial cells [19,20]. Subsequently, there is a decrease in the ATP/adenosine ratio to
control inflammation and initiation of wound-healing processes that can lead to fibrosis (see [21] for
a review). Adenosine is transported through nucleoside transporters (NT), being ENT1 and CNT2
good candidates, since they show high affinity for adenosine (40 µM and 8 µM, respectively) (see [22]
for a review). However, CNT2 is a Na+-dependent concentrative transporter, which makes CNT2 an
ideal candidate for regulating extracellular adenosine levels. A2A receptors (A2AR) are considered the
primary anti-inflammatory effectors of extracellular adenosine due to their high expression on immune
cells, such as monocytes/macrophages. A2ARs mainly activate the adenylate cyclase-cAMP-PKA
canonical pathway and participate in tissue remodeling and reparation. Activation of A2AR in renal
macrophages induces the expression of the anti-inflammatory cytokines and reduces kidney damage
in the acute and chronic inflammation phases of glomerulonephritis [23].
      This study was undertaken to examine the role of purinergic pathways with respect to pretransplant
inflammation of kidneys from deceased donors, and specifically to investigate the role of adenosine
A2AR and how it can influence macrophage phenotype.

2. Results

2.1. Differences in Purinome Gene Expression in Renal Biopsies from DD and LD
     Gene expression levels related to cell purinome in pre-implantation renal tissue samples were
analyzed to investigate expression differences between LD and DD. Figure 1 shows that we did not
find statistically significant differences between LD and DD regarding mRNA expression levels of
nucleoside transporters (NTs), except for hCNT2, which shows high affinity for adenosine and showed
lower basal expression in DD than in LD (p = 0.019). We did not detect mRNA expression of hCNT3 in
renal biopsy samples (data not shown).
       Int. J. Mol. Sci. 2020, 21, 8826                                                                          3 of 17
Int. J. Mol. Sci. 2020, 21, x FOR PEER REVIEW                                                                              3 of 20




           Figure 1. Relative mRNA expression of nucleoside transporters (CNT1 (A), CNT2 (B), ENT1 (C),
     FigureENT2
             1. Relative
                  (D), ENT3mRNA
                              (E), andexpression
                                       ENT4 (F)), asofdetermined
                                                       nucleoside  by transporters
                                                                      qPCR analysis,(CNT1
                                                                                     in renal (A), CNT2
                                                                                              samples from(B),   ENT1 (C),
                                                                                                            LD and
     ENT2DD.(D),Data are (E),
                  ENT3   expressed   as box-and-whisker
                               and ENT4                   plots. p value
                                            (F)), as determined          is shown
                                                                    by qPCR       when comparisons
                                                                               analysis,            are statistically
                                                                                         in renal samples    from LD and
           significant (Mann–Whitney U-test, p < 0.05) between groups. LD, living donors; DD, deceased donors.
     DD. Data are expressed as box-and-whisker plots. p value is shown when comparisons are
     statistically  significant
            Regarding            (Mann–Whitney
                         the expression            U-test,
                                        of P1 receptors    p < 0.05)
                                                        (Figure       between
                                                                 2), A1R (Figuregroups.
                                                                                 2A), andLD,
                                                                                          A3R living donors;
                                                                                                (Figure 2C) didDD,
     deceased
      not showdonors.
                  differences in mRNA levels between DD and LD, whereas A2AR (Figure 2B) showed higher
      expression levels in DD than in LD (p = 0.001). A2BR mRNA was hardly detected in renal biopsies
     Regarding
      samples (data thenot
                         expression
                           shown). of P1 receptors (Figure 2), A1R (Figure 2A), and A3R (Figure 2C) did
not show differences in gene
            Figure   3 shows    mRNA expression  levels of different
                                         levels between     DD andgenesLD, related
                                                                             whereasto purinergic
                                                                                        A2AR (Figuremetabolism
                                                                                                          2B) showed
      or  ATP    release  in  renal samples  from   LD  and   DD.   mRNA    levels of
higher expression levels in DD than in LD (p = 0.001). A2BR mRNA was hardly detected   CD73   (Figure 3A)   andin renal
      S-adenosyl-L-homocysteine hydrolase (SAHH) (Figure 3E) was lower in DD than in LD (p = 0.009 and
biopsies samples (data not shown).
      p < 0.001, respectively), whereas we did not observe any difference in CD39 (Figure 3B), adenylate cyclase
      (ADCY) (Figure 3C), or adenosine kinase (ADK) (Figure 3D) mRNA expression levels. The hemichannel
      Panx-1, showed higher mRNA levels in DD samples than in LD samples (p = 0.017) (Figure 3F).
Int. J. Mol. Sci. 2020, 21, 8826                                                                                       4 of 17
     Int. J. Mol. Sci. 2020, 21, x FOR PEER REVIEW                                                                    4 of 20




      Figure 2. Relative mRNA expression of adenosine receptors (A1R (A), A2AR (B), and A3R (C)),
         Figure 2. Relative mRNA expression of adenosine receptors (A1R (A), A2AR (B), and A3R (C)), as
      as determined by qPCR analysis, in renal samples from LD and DD. Data are expressed as
         determined by qPCR analysis, in renal samples from LD and DD. Data are expressed as
      box-and-whisker plots. p value is shown when comparisons are statistically significant (Mann–Whitney
         box-and-whisker            plots. p value is shown when comparisons are statistically significant
              p <J. 0.05)
      U-test, Int.  Mol. Sci. 2020, 21, x FOR PEER REVIEW
                           between groups. LD, living donors; DD, deceased donors.                5 of 20
         (Mann–Whitney U-test, p < 0.05) between groups. LD, living donors; DD, deceased donors.

         Figure 3 shows gene expression levels of different genes related to purinergic metabolism or
    ATP release in renal samples from LD and DD. mRNA levels of CD73 (Figure 3A) and
    S-adenosyl-L-homocysteine hydrolase (SAHH) (Figure 3E) was lower in DD than in LD (p = 0.009
    and p < 0.001, respectively), whereas we did not observe any difference in CD39 (Figure 3B),
    adenylate cyclase (ADCY) (Figure 3C), or adenosine kinase (ADK) (Figure 3D) mRNA expression
    levels. The hemichannel Panx-1, showed higher mRNA levels in DD samples than in LD samples (p
    = 0.017) (Figure 3F).




      Figure 3. Relative mRNA expression of purinergic enzymes (CD73 (A), CD39 (B), ADCY (C), ADK (D),
                 Figure 3. Relative mRNA expression of purinergic enzymes (CD73 (A), CD39 (B), ADCY (C), ADK
                   (D), SAHH (E), PANX1 (F)), as determined by qPCR analysis, in renal samples from LD and DD.
                   Data are expressed as box-and-whisker plots. p value is shown when comparisons are statistically
                   significant (Mann–Whitney U-test, p < 0.05) between groups. LD, living donors; DD, deceased
                   donors.

              2.2. Correlations of A2AR mRNA Expression Levels
Int. J. Mol. Sci. 2020, 21, 8826                                                                        5 of 17




      SAHH (E), PANX1 (F)), as determined by qPCR analysis, in renal samples from LD and DD. Data are
      expressed as box-and-whisker plots. p value is shown when comparisons are statistically significant
      (Mann–Whitney U-test, p < 0.05) between groups. LD, living donors; DD, deceased donors.

2.2. Correlations of A2AR mRNA Expression Levels
       To explore possible associations, correlations of gene expression levels of the different genes
studied with A2AR were determined. Table 1 shows correlations (p and Spearman’s rho values)
between A2A R and enzymes involved in adenosine metabolism and nucleoside transporters.
       In general trends A2A R mRNA levels in DD samples positively correlated with the mRNA amounts
of a panel of enzymes (i.e., CD73, ADK) and transporters (i.e., hENT1, hENT2, hCNT2) known to
build up the cell purinome, likely to modulate adenosine-related biological events. Table 2 shows gene
expression positive correlations detected between M1 macrophage phenotype or inflammatory markers
(i.e., TNF-α, CD16, IL-1β), M2 macrophage phenotype or anti-inflammatory markers (i.e., IL-10, CD206,
CEBPB) and fibrotic markers (i.e., TGFB1, ACTA2) with A2A R, in renal tissue samples of DD.
       Table 2 also shows differences in expression levels of these genes between DD and LD renal samples.
Expression levels of several markers related to inflammation or phenotype change of macrophages
were up-regulated in DD (i.e., TNF-α, IL-1β, CD163), while of the fibrosis markers, TGF-β1 and col1A1
were the only ones overexpressed in DD. Interestingly, expression levels of A2A and TNF-α are higher
in DD than in LD and correlate in both donor groups. Although no association was found between
A2AR mRNA levels and factors, such as donor age or cold ischemia time, an inverse correlation was
observed between the amount of PANX1 mRNA and cold ischemia time, only in kidneys from DD
(p = 0.0023, r = −0.4522). With regard to fibrosis, we showed previously that DDs are significant older
than LDs, whereas the analysis of pre-transplant kidney biopsies using the Remuzzi score, only for
research purposes and not to determine the suitability of the graft, found that more than 80% of both,
DD and LD samples, obtained a total score ≤ 3 [14].

      Table 1. Gene expression correlations between A2A R and enzymes involved in adenosine metabolism
      and nucleoside transporters.

                                                                    A2AR Correlations
                                                              DD                          LD
                                                                   Rho                       Rho
                                                        p                           p
                                                                 Spearman                  Spearman
                                       CD39           0.065         0.272         0.311        0.246
                                       CD73          <0.001         0.635         0.705        −0.093
                          Enzymes




                                       ADK           <0.001         0.609         0.433        0.191
                                       SAHH          <0.001         0.501         0.697        0.096
                                       ADCY          <0.001         0.521         0.271        0.266
                                       ENT1          <0.001         0.603         0.170        0.328
                                       ENT2           0.003         0.426         0.507        0.162
                        transporters
                         Nucleoside




                                       ENT3          <0.001         0.563         0.673        0.104
                                       ENT4           0.002         0.441         0.459        0.181
                                       CNT1           0.049         0.288         0.792        0.065
                                       CNT2           0.017         0.347         0.665        −0.106
                                              LD, living donors; DD, deceased donors.
Int. J. Mol. Sci. 2020, 21, 8826                                                                                                   6 of 17



      Table 2. RNA expression levels of different genes in DD vs. LD and gene expression Spearman rank
      correlations coefficients between A2A R and inflammatory, anti-inflammatory and fibrosis genes.

                                                                                                  A2AR Correlations
                                                            RNA Expression                   DD                       LD
                                                                                               Rho                      Rho
                                                         DD vs. LD   Significance     p                       p
                                                                                             Spearman                 Spearman
                                              TNF            ↑          [14] *      <0.001        0.504     0.022          0.520
                     & M1 markers
                     Inflammatory



                                              NFKB           ↑        p = 0.033     <0.001        0.626     0.997          0.001
                                              CD16           ↑          [14] *      <0.001        0.507     0.131          0.359
                                              CD86          =           [14] *      <0.001        0.478     0.303          0.250
                                              IL-1β          ↑          [14] *      0.003         0.432     0.983          0.005
                                              IL10          =            n.s.       <0.001        0.492     0.265          0.269
                     Anti-inflammatory




                                                            =                       <0.001
                      & M2 markers




                                             CD206                      [14] *                    0.577     0.132          0.358
                                             CD163           ↑          [14] *      <0.001        0.502     0.209          0.302
                                             IL13RA2        =            n.s.       0.002         0.437     0.204          0.305
                                             CD209           ↑          [14] *      0.056         0.281     0.557          0.144
                                             CEBPB           ↑        p < 0.001     <0.001        0.482     0.446          0.186
                                             TGFB1           ↑          [14] *      <0.001        0.712     0.061          0.437
                      & Fibrosis markers




                                           FIBRONECTIN      =           [14] *      <0.001        0.652     0.545          0.148
                                             ACTA2          =           [14] *      <0.001        0.572     0.123          0.366
                             EMT




                                           VIMENTIN         =           [14] *      0.002         0.447     0.718          0.089
                                             COL1A1          ↑        p = 0.006     0.005         0.407     0.102          0.386
                                             COL1A2         =            n.s.       <0.001        0.511     0.158          0.337
                                             COL3A1         =            n.s.       0.015         0.354     0.051          0.454
      Significance is shown as the value of “p” when lower than 0.05 or as n.s. (not significant) when higher according to
      the Mann–Whitney U test. [14] * corresponds to the reference of the previous study in which the gene was included
      and analyzed. LD, living donors; DD, deceased donors.


2.3. Protein Expression in Renal Biopsies from DD and LD
         Protein levels were measured in pre-implantation renal tissue of both DD and LD, and these data
are summarized in Figure 4. It shows that the expression of the active dimer form ofA2A R (p = 0.004)
(Figure 4A), CD163 (p = 0.012) (Figure 4B), and pPKA (p = 0.018) (Figure 4C) proteins was significantly
 Int. J. Mol. Sci. 2020, 21, x FOR PEER REVIEW                                                     8 of 20
higher     in kidney extracts from DD compared with LD samples. Levels of pCREB were also marginally
higher in DD, although statistical significance was not reached (p = 0.070) (Figure 4D).




       Figure 4. Western blot analysis of protein expression of A2A R (A), CD163 (B), phospho PKA (pPKA)
       Figure 4. Western blot analysis of protein expression of A2AR (A), CD163 (B), phospho PKA (pPKA)
       (C) and phospho CREB (pCREB) (D) in renal samples from DD and LD. Total protein was isolated
       from kidney tissues, as described in Materials and Methods, and separated by SDS-PAGE. Protein
       expression semiquantitation performed by densitometric analysis of Western blots. (E)
       Representative Western blots for A2AR, CD163, pPKA and pCREB. Data are expressed as
Int. J. Mol. Sci. 2020, 21, 8826                                                                                         7 of 17



      (C) and phospho CREB (pCREB) (D) in renal samples from DD and LD. Total protein was isolated from
      kidney tissues, as described in Materials and Methods, and separated by SDS-PAGE. Protein expression
      semiquantitation performed by densitometric analysis of Western blots. (E) Representative Western
      blots for A2A R, CD163, pPKA and pCREB. Data are expressed as box-and-whisker plots. p value is
      shown when comparisons are statistically significant (unpaired Student’s t-test, p < 0.05) between
      groups. LD, living donors; DD, deceased donors.

2.4. TNF-α Increases Expression of CD163 and TGF-β1 through A2AR in THP-1 Cells
        THP-1 is a human leukemia monocytic cell line, which has been extensively used to study
monocyte/macrophage functions. In the present study, regulation of the A2A R pathway and monocyte
activation by TNF-α was examined using the in vitro model of undifferentiated THP-1 monocytes.
TNF-α addition increased A2A R mRNA expression levels in THP-1 cells (Figure 5A) as previously
reported [24]. This increase was significant at all time points analyzed, although the results showed a
dependence on TNF-α incubation time and concentration, showing the maximum increase 3 h after
10 ng/mL TNF-α addition. CD163 and TGF-β1 gene mRNA levels were up-regulated at 18 and 24 h of
treatment (Figure 5B). Shorter treatments (3 and 6 h) did not result in changes in mRNA levels.
        Figure 6 shows that pretreatment with 1 µM ZM241385 (A2A R antagonist) abolished the effect of
TNF-α on CD163 (Figure 6A) and TGF-β1 (Figure 6B) mRNA up-regulation, providing evidence that
the A2A receptor is involved in M2 macrophage activation by TNF-α. Treatment of THP-1 cells with a
known CD163 inducer, IL-10, similarly increased CD163 mRNA expression levels in a manner that was
also dependent upon A2AR signaling, as demonstrated by its blockade by ZM241385, showing the
role of the A2A R in the shift to M2 phenotype (Figure 6C). There was no observed effect of IL-10 on the
expression of TGF-β1 (Figure 6D).
        To know the potential involvement of the NF-κB signaling-pathway in these events, cells were
pre-treated with BMS345541, a highly selective inhibitor of IκB Kinase. Figure 7 shows this inhibition
blocked the up-regulation of gene expression levels of A2A R (Figure 7A), CD163 (Figure 7B) and
 Int. J. Mol. Sci. 2020, 21, x FOR PEER REVIEW                                                    9 of 20
TGF-β1      (Figure 7C), triggered by TNF-α.




      Figure 5. TNF-α enhances A2AR, CD163, and TGF-β1 levels in THP-1 cells. The time course of TNF-α
        Figure 5.A2AR
      induced       TNF-α   enhances
                         (A),          A2AR,
                               CD163 (B),  andCD163,
                                                TGF-β1and (C) TGF-β1
                                                               expressionlevels in THP-1
                                                                            in THP-1    cellscells. The time course
                                                                                               as quantitated         of
                                                                                                                by qPCR.
      *,TNF-α
         ** and induced   A2AR
                 *** denote      (A), CD163
                             significant differences  (p <
                                               (B), and  TGF-β1     < 0.01
                                                           0.05, p(C)      and p <in
                                                                       expression      THP-1
                                                                                     0.001,     cells as quantitated
                                                                                            respectively)             by
                                                                                                            as compared
        qPCR.
      with   the*,DMSO
                   ** andgroup
                          *** denote
                                using significant  differences
                                       unpaired Student’s        (p <All
                                                             t-test.  0.05, p < 0.01
                                                                         values       and p < 0.001,
                                                                                 are expressed              ± SD (n =as
                                                                                                        respectively)
                                                                                                  as means             3).
        compared with the DMSO group using unpaired Student’s t-test. All values are expressed as means ±
        SD (n = 3).

    Figure 6 shows that pretreatment with 1 μM ZM241385 (A2AR antagonist) abolished the effect of
 TNF-α on CD163 (Figure 6A) and TGF-β1 (Figure 6B) mRNA up-regulation, providing evidence that
 Int. J. Mol. Sci. 2020, 21, 8826                                                                                            8 of 17
Int. J. Mol. Sci. 2020, 21, x FOR PEER REVIEW                                                                           10 of 20




         Figure 6. Effect of the A2A R receptor antagonist ZM241385 on CD163 (A) and TGF-β1 (B) gene expression
        Figure
         induced  6. by
                      Effect
                        TNF-α of in
                                  the  A2ARcells.
                                    THP-1     receptor  antagonist
                                                  Cells were         ZM241385
                                                             also treated           on CD163
                                                                            with IL-10          (A) andtoTGF-β1
                                                                                         and ZM241385        evaluate(B)  gene on
                                                                                                                      its effect
        expression     induced    by  TNF-α    in THP-1  cells.  Cells  were   also  treated  with IL-10   and
         CD163 (C) and TGF-β1 (D) gene expression. THP-1 cells were treated with ZM241385 (1 µM) 30 min before  ZM241385      to
        evaluate    its effect
         adding TNF-α       (10 on   CD163
                                ng/mL)        (C) and
                                          or IL-10     TGF-β1for
                                                   (10 ng/mL)    (D)18gene   expression.
                                                                        h. Cells            THP-1and
                                                                                 were collected,    cells were
                                                                                                       total  RNAtreated  with
                                                                                                                    was extracted
        ZM241385      (1 μM) 30 min
         and retrotranscribed            beforeResults
                                    to cDNA.     addingare
                                                         TNF-α    (10 ng/mL)
                                                           expressed     as meanor±IL-10
                                                                                      SD; p(10 ng/mL)
                                                                                            value        for 18
                                                                                                  is shown      h. Cells
                                                                                                              when        were
                                                                                                                    comparisons
Int. J. Mol.
         are Sci.
        collected,2020,
                     and21,
             statistically  x FOR
                          total RNA  PEER
                            significant wasREVIEW
                                             extracted
                                         (unpaired              t-test, p < 0.05),
                                                       and retrotranscribed
                                                     Student’s                        = 3 forResults
                                                                                 toncDNA.            are expressed as mean 11 of 20
                                                                                             each point.
        ± SD; p value is shown when comparisons are statistically significant (unpaired Student’s t-test, p <
        0.05), n = 3 for each point.

     To know the potential involvement of the NF-κB signaling-pathway in these events, cells were
pre-treated with BMS345541, a highly selective inhibitor of IκB Kinase. Figure 7 shows this inhibition
blocked the up-regulation of gene expression levels of A2AR (Figure 7A), CD163 (Figure 7B) and
TGF-β1 (Figure 7C), triggered by TNF-α.




                                                          Figure 7. Cont.
Int. J. Mol. Sci. 2020, 21, 8826                                                                                           9 of 17




       Figure 7. Effect of the NF-κB inhibitor BMS354451 on the A2AR (A), CD163 (B) and TGF-β1 (C) mRNA
      Figure
       levels in7.THP-1
                   Effect cells
                           of the  NF-κB inhibitor
                                stimulated           BMS354451
                                              with TNF-α            on the
                                                           (10 ng/mL).      A2AR (A),
                                                                        BMS354451     (1, CD163    (B)5and
                                                                                          2.5, 4 and     µM)TGF-β1
                                                                                                               was added(C)
      mRNA      levels
       to the cells  1 hinbefore
                           THP-1cytokine
                                   cells stimulated
                                            treatmentwith
                                                      andTNF-α     (10for
                                                            cultured   ng/mL).   BMS354451
                                                                          20 h. Results        (1, 2.5, 4 and
                                                                                         are expressed         5 μM)±was
                                                                                                           as mean      SD;
      added
       p valuetoisthe  cells when
                   shown     1 h before  cytokine treatment
                                   comparisons                and cultured
                                                  are statistically          for (unpaired
                                                                    significant  20 h. Results            t-test, pas<mean
                                                                                                 are expressed
                                                                                             Student’s                0.05),
         = 4–8
      ±n SD; p value    is shown
                 for each  point. when comparisons are statistically significant (unpaired Student’s t-test, p <
      0.05), n = 4–8 for each point.
3. Discussion
3. Discussion
     This study highlights different activated processes in kidney allografts from DD versus LD before
transplantation.
      This study Renal     transplant
                    highlights         recipients
                                 different         show
                                            activated     higher concentrations
                                                        processes                    of proinflammatory
                                                                     in kidney allografts     from DD versus  cytokines
                                                                                                                    LD
in grafts from    DD  than  in those from   LD  [25]. We   recently  reported   that inflammatory
before transplantation. Renal transplant recipients show higher concentrations of proinflammatory      and  reparative
responses in
cytokines   coexist
               graftsinfrom
                         DD kidney
                             DD than grafts,  indicating
                                       in those  from LD  that  pre-implantation
                                                             [25].                 kidneythat
                                                                   We recently reported     grafts  from DD exhibit
                                                                                                  inflammatory     and
more   inflammation      than  those from   LD  [14]. Inflammation      can  be  modulated    by
reparative responses coexist in DD kidney grafts, indicating that pre-implantation kidney grafts   adenosine    [26,27],
whichDD
from    exerts its anti-inflammatory
           exhibit   more inflammation  activity
                                             thanmainly
                                                   those through
                                                           from LD  A2A R [28–30].
                                                                      [14].          Our results
                                                                            Inflammation     can indicate    that A2A
                                                                                                   be modulated     byR
expression    is increased   in DD  kidney   grafts,  which   would   induce   anti-inflammatory
adenosine [26,27], which exerts its anti-inflammatory activity mainly through A2AR [28–30]. Our        responses   that
eventually
results      could lead
         indicate   that toAthe  onset of renal fibrosis if uncontrolled or persistent inflammation occurs [31].
                             2AR expression is increased in DD kidney grafts, which would induce
Monocytes     and   macrophages
anti-inflammatory responses that    synthesize   and could
                                        eventually    releaselead
                                                                TNF-α,
                                                                   to thea potent
                                                                           onset ofmediator    of inflammation
                                                                                     renal fibrosis                that
                                                                                                      if uncontrolled
induces
or        A2A Rinflammation
   persistent     activity [24,32].  A2A[31].
                                 occurs  R expression
                                               Monocytes canandbe up-regulated
                                                                   macrophages directly
                                                                                  synthesizeby TNF-α      [33] because
                                                                                                and release     TNF-α,
of the presence of NF-κB binding sites in the upstream regions of the A2A R gene [24,34], but it has
also been suggested that TNF-α may inhibit desensitization of A2A R and enhance the functions of the
receptor [35].
      Evidence suggests a role of TNF-α in renal interstitial fibrosis and collagen deposition [36],
which may be mediated by TGF-β1 increase [37,38]. In our study, renal samples from DD showed
higher gene expression of A2A R, TNF-α and TGF-β1 than LD and correlated positively with each
other. Neutralization of TNF-α was found to reduce TGF-β1 production, myofibroblast activation,
and collagen deposition, and therefore diminished renal interstitial fibrosis [39]. Our results with THP-1
cells confirm that TNF-α increases A2A R gene expression through the NF-κβ pathway, which can
induce M2 phenotype and fibrosis.
      Up-regulation of A2A R is likely to be the beginning of a reduction in inflammatory response.
A2A R downregulates classic macrophage activation, reducing the production of proinflammatory
cytokines such as TNF-α and increasing the expression of the anti-inflammatory cytokine IL-10 [40].
In addition, it was reported that A2A R antagonists promote the M1 phenotype of macrophages
infiltrating nephritic glomeruli [41]. A2A R signaling through G proteins is based on the stimulation
of adenylate cyclase (AC), which induces intracellular cAMP and activates protein kinase A (PKA).
Moreover, A2A R and AC mRNA expression showed a positive correlation in DD samples and p-PKA
was increased in DD samples compared with LD samples. Chronic inflammatory tissue injury is
accompanied by the accumulation of extracellular adenosine released by immune and non-immune
cells. Adenosine receptor expression in macrophages appears to change upon inflammatory activation,
since A2A Rfunction in human THP-1 monocytes has been shown to be up-regulated by IL-1β and
TNF-α [24]. Indeed, our results show that A2A R gene expression in THP-1 monocytes is rapidly
Int. J. Mol. Sci. 2020, 21, 8826                                                                    10 of 17



up-regulated by TNF-α, suggesting that anti-inflammatory A2A R is up-regulated following classic
activation of macrophages, possibly to initiate resolution of inflammation [26].
      It is worth noting that the induction of A2A R by TNF-α is relatively fast and persistent whereas
induction of CD163 and TGF-β1 occurs later and is A2A R-dependent. These results support that
fibrotic processes are initiated through A2A R-activation when monocytes/macrophages are exposed to
prolonged inflammation. Although CD73 expression is lower in DD than in LD samples, indicating that
extracellular synthesis of adenosine might be somehow reduced, hCNT2 expression is downregulated
in DD samples, which is consistent with reduced adenosine clearance from the extracellular milieu.
Indeed, as recently reviewed [22], hCNT2 may be a major player in regulating extracellular adenosine
levels and there is evidence of CNT2 being regulated at the post-translational level [42]. Interestingly,
the hCNT2-encoding gene (SLC28A2) is by far the most dramatically down-regulated one among
the purinome-related genes in inflamed ileal mucosa samples from Crohn’s disease patients [43].
Furthermore, A2A Rs are known to up-regulate CNT2 activity in differentiated PC12 cells [43]. Moreover,
it was also observed that hypoxia downregulated CNT2 function without affecting ENT1 activity,
which suggests, as mentioned above, an important role of CNT2 in the modulation of extracellular
adenosine concentrations [43,44]. In this regard, A2A R signaling again emerges as an important
mechanism for limiting inflammatory responses [45–47]. Although some authors observed that
CD73 expression and function were upregulated by proinflammatory mediators [48,49], Zanin et al.
provided evidence that proinflammatory M1 macrophages decrease both the expression and the
activity of CD39 and CD73, leading to reduced ATP degradation [50]. Moreover, TNF-α was found
to reduce the surface expression and activity of CD73 [51]. By contrast, M2 macrophages showed
increased expression and activity of both enzymes, followed quickly by the conversion of ATP into
adenosine. Our findings on pre-implant kidney grafts from DD confirmed overexpression of TNF-α
and decreased expression of CD73. Chronic lack of CD73 was associated with an autoimmune
inflammatory phenotype, which at the renal level affects the glomerular endothelium, leading to
glomerular inflammation, injury, and interstitial cellular infiltrate, with consequent proteinuria and
decreased kidney function [52]. Our results also show a little—but significantly increased—expression
of Panx-1 and an inverse correlation with ischemic time in kidneys from DD. This could be due
to a known regulation of the channel by the released ATP itself that can bind to a binding site in
aPanx-1 extracellular loop to prevent persistent excitatory signaling of Panx1-mediated ATP release [53].
Moreover, increased extracellular ATP levels can induce the internalization of Panx1, avoiding further
release of excitatory ATP [54].
      In our study, low intracellular SAHH gene expression in DD grafts may contribute to the
accumulation of S-adenosylhomocysteine (SAH) and to a decrease in intracellular adenosine and
homocysteine production. Barroso et al. showed that an excess of SAH in response to NF-kB activation
leads to the expression of adhesion molecules and cytokines such as IL-1β and TNF-α in endothelial
cells, resulting in an inflammatory response [55].
      During an inflammatory process, adenosine can activate A2A R to attenuate inflammation and
tissue injury. Adenosine reduces the M1 macrophage phenotype and activation of A2A R shifts
macrophages towards the M2 phenotype [16,56], and promotes wound healing in mice [57,58].
Thus, extracellular adenosine appears to facilitate a macrophage switch characteristic for an alternatively
activated phenotype [59]. We have shown that A2A RmRNA expression correlates with the M2
macrophage marker CD163 and that both proteins are augmented in DD samples compared with LD.
Our results are in accordance with the hypothesis that the onset of anti-inflammatory activity induces
the M2 phenotype and is driven by A2A R signaling.
      Stimulation of IL-10 production in RAW264.7 macrophages by adenosine was regulated by the
transcription factor C/EBPβ [60]. In our study, A2A R expression in DD correlated with C/EBPβ and
IL-10. During macrophage activation, C/EBPβ is induced by the CREB transcriptional activator,
and Ruffell and co-workers found that deletion of CREB-binding sites from Cebpb promoter avoided
macrophage activation and blocked specific M2 genes [61]. Our results suggest the activation of CREB,
Int. J. Mol. Sci. 2020, 21, 8826                                                                        11 of 17



since phospho-CREB is up-regulated in DD renal biopsies, although statistical significance was not
reached. Other models support involvement of C/EBPB in M2 macrophage differentiation and fibrosis
after damage [62–64].
      In summary, DD kidney grafts display more inflammation than LD and produce higher levels
of TNF-α. Our results suggest that CD163 and TGF-β1 are regulated, at least in part, by TNF-α via
A2A R to initiate anti-inflammatory processes and promote M2 macrophage phenotype. Our work also
indicates that, in kidney biopsies from DD, the cAMP/PKA/CREB/C/EBPβ pathway could be activated,
which would also favor the switch from macrophages M1 to M2. A proposed integrated mechanistic
model explaining the dual inflammatory and anti-inflammatory conditions of DD kidneys is shown in
Figure 8.
      Although further research is needed, our results unequivocally show differences in purinergic
signaling in grafts from DD and from LD which highlights the possibility of targeting purinome
elements for therapeutic management of early and persistent inflammation associated with renal graft
dysfunction. Adenosine signaling is considered protective in ischemic lesions with immunomodulatory
properties. Our observations, although focused on kidney transplantation, show crucial changes in
the immunomodulation of transplanted organs, highlighting a key role for the purinome in kidney
graft inflammation and the onset of fibrosis. Our results confirm the growing evidence that purinergic
signaling is involved in the inflammatory response that can be associated with rejection and chronic
allograft dysfunction. Our contribution also raises the possibility of purinergic biology playing a more
general     roleSci.
    Int. J. Mol. in the
                     2020,clinics  derived
                           21, x FOR       from organ transplantation in humans.
                                     PEER REVIEW                                                     14 of 20




      Figure 8. Schematic representation of the proposed mechanism of inflammation/anti-inflammation in
      DD kidneys. After an injury, such as hypoxia or ischemia, ATP is released and the production
      of the  inflammatory
          Figure  8. Schematiccytokine   TNF-α of
                                representation  is the
                                                    induced.
                                                       proposedVia the NF-κB
                                                                mechanism    of pathway,  TNF-α stimulates
                                                                                inflammation/anti-inflammation
      A2A R expression although the formation and uptake of extracellular adenosine are restricted.
          in DD kidneys. After an injury, such as hypoxia or ischemia, ATP is released and the production of
      Thus, the cAMP-PKA-CREB signaling pathway could be initiated and promote anti-inflammatory
          the inflammatory cytokine TNF-α is induced. Via the NF-κB pathway, TNF-α stimulates A2AR
      immune responses, e.g., through the induction of IL-10 and the switch to the M2 macrophage phenotype
          expression although the formation and uptake of extracellular adenosine are restricted. Thus, the
      (CD163). If injury or inflammation persists, this can lead to the generation of TGF-β1, which may
          cAMP-PKA-CREB signaling pathway could be initiated and promote anti-inflammatory immune
      mediate the onset of fibrosis.
          responses, e.g., through the induction of IL-10 and the switch to the M2 macrophage phenotype
          (CD163). If injury or inflammation persists, this can lead to the generation of TGF-β1, which may
          mediate the onset of fibrosis.

    4. Materials and Methods

    4.1. Donors, Patients, and Kidney Samples
Int. J. Mol. Sci. 2020, 21, 8826                                                                  12 of 17



4. Materials and Methods

4.1. Donors, Patients, and Kidney Samples
      This study was approved by the ethics committee of Fundació Puigvert. Participants were from the
study population for a previous work [14] in which patients characteristics are described [14]. In brief,
94 renal donors (60DD/34LD) were included. We obtained renal biopsies for gene expression analysis
from 47 DD and 21 LD. Two living donors’ samples were missing. We collected pre-implantation biopsies
from kidney donors and clinical information for donors and KTR who underwent transplantation in our
institution between 2008 and 2011. All of them signed an informed consent form. Tissue samples from
biopsy cores were processed for mRNA extraction and gene expression analysis by qPCR. Total protein
was also obtained for Western blot.

4.2. Cell Culture and Treatments
      Human monocytic leukemia THP-1 cells (ATCC) were cultured in RPMI (Lonza, Bassel, Switzerland)
supplemented with 10% fetal bovine serum (Life Technologies, Carlsbad, CA, USA), 2 mM glutamine,
and antibiotic (Lonza). Cells were grown in complete medium and then growth arrested in serum-free
medium for 24 h. All experiments were performed under serum-free conditions. THP-1 cells were
seeded at 37 ◦ C in a humidified 5% CO2 /95% air atmosphere in the presence of 5, 10, and 20 ng/mL of
TNF-α (R&D Systems, Minneapolis, MN, USA) at different time points (3, 6, 18, and 24 h). When needed
and at the times selected, cells were pretreated for 30 min with 1µM of the A2A R antagonist ZM241385
(Tocris, Bristol, UK) or for 60 min with the NF-κβ blocker BMS345541 (Sigma, Saint Louis, MO, USA)
(1, 2.5, 4, and 5 µM) before the addition of TNF-α. Control samples always contained the same amount
of vehicle (DMSO) to exclude any interference in cell responses. After the incubation period, cells were
centrifuged and pellets were resuspended in TriReagent (Sigma).

4.3. Real Time PCR

4.3.1. Renal Tissue
     Kidney biopsies were processed as described previously [14]. Briefly, samples were homogenized
with Tissuelyser LT (Qiagen, Hilden, Germany). Aqueous phase containing RNA was transferred into
an RNeasy column (AllPrep DNA/RNA/Protein Mini Kit, Qiagen) and was eluted with RNAse-free
water. The integrity of total RNA was assessed on a denaturing agarose gel, allowing visual assessment
of the 28S and 18S rRNA bands. Retrotranscription of total RNA to cDNA was done according to the
user guide of the Applied Biosystems™ QuantStudio™ 12K Flex Real-Time PCR System, OpenArray®
Experiments (Life Technologies, Carlsbad, CA, USA). Briefly, 10 µL of 2X reverse transcription mix of
the High Capacity cDNA Reverse Transcription kit (Life Technologies) was mixed with 10 µL of total
RNA in a 96-well reaction plate. Plates were incubated at room temperature for 10 min, then incubated
at 37 ◦ C for 2 h and placed on ice for 5 min, incubated at 75 ◦ C for 10 min, placed on ice for 5 min,
and spun down. Real-time PCR was done in accordance with the TaqMan® gene expression assays
protocol (Life Technologies). A mix containing 2X TaqMan OpenArray Real Time PCR Master Mix
(Cat No. 4.462.159 Life Technologies) and cDNA was loaded on each OpenArray plate. These plates
were run on the computer QuantStudio 12 K Flex Real-Time PCR system. Relative quantification
of gene expression was performed using the expression of three internal controls: human GAPDH,
β-actin, and β-glucuronidase.

4.3.2. THP-1 Cells
     Total RNA was isolated from THP-1 cells with TriReagent (Sigma, St. Louis, MO, USA) and 1 µg
RNA was retrotranscribed to cDNA with the MultiScribe Reverse Transcriptase kit (Applied Biosystems,
Carlsbad, CA, USA) according to the manufacturer’s instructions. Real-time amplification of cDNAs
was carried out with the TaqMan Universal Master Mix (Applied Biosystems) in the StepOne Sequence
Int. J. Mol. Sci. 2020, 21, 8826                                                                            13 of 17



Detection System (Applied Biosystems). Assays used for amplification of human CD163, A2AR,
and TGF-β1 were predesigned inventoried TaqMan Gene Expression Assays (Applied Biosystems,
Foster City, CA, USA). Relative quantification of gene expression was performed as described in the
TaqMan instruction manual using human GAPDH as an internal control. The PCR arbitrary units
of the genes analyzed were defined as the mRNA levels of these genes normalized to the GAPDH
expression level in order to quantify these transcripts in relative terms.

4.4. Western Blot
     Protein samples were obtained from kidney biopsies with AllPrep DNA/RNA/Protein Mini
Kit (Qiagen, Venlo, The Netherlands). Total protein pellets were dissolved in 8M urea lysis buffer,
centrifuged to eliminate cell debris, and supernatant was stored to −80 ◦ C.
     Thirty micrograms of total proteins were fractionated by SDS-PAGE and transferred to a
polyvinylidene difluoride membrane using a Trans-blot turbo (Bio-Rad, Hercules, CA, USA).
After incubation with 5% BSA in TBST (10 mM Tris, pH 8.0, 150 mM NaCl, 0.5% Tween 20), the membrane
was washed with TBST and incubated with antibodies against phospho (p)-CREB (Cell Signaling,
Danvers, MA, USA; dilution 1/1000), CREB (Cell Signaling; 1/500), phospho (p)-PKA (Cell Signaling;
1/1000), PKA (Cell Signaling; 1/500), A2A R(St John’s Laboratory, London, UK; 1/500), CD163 (Pierce,
Waltham, MA, USA; 1/1000), and GAPDH (Sta. Cruz Biotechnology, Santa Cruz, CA, USA; 1/2000),
the last as loading control, at 4 ◦ C O/N under agitation. Membranes were washed with TBST and
incubated with a 1:20,000 dilution of horseradish peroxidase-conjugated anti-mouse or anti-rabbit
antibody (Bio-Rad, Hercules, CA, USA) for 1 h. Membranes were washed again and blots were exposed
to highly sensitive films and developed using an ECL® technique (Pierce).

4.5. Statistics
      GraphPad Prism software (GraphPad Software, San Diego, CA, USA)was used to perform
statistical analysis. Results are expressed as the mean ± standard deviation (lower and upper
extremities) and percentages, as appropriate. Student’s t-test was applied to compare means. When our
data did not follow a Gaussian distribution, nonparametric tests such as the Mann–Whitney U test
and Spearman correlation were used for data analysis. All p values were two-sided, and p < 0.05
was considered significant. Spearman test significance was confirmed by p-value analysis using the
Benjamini–Hochberg procedure with a criterion of <5% False Discovery Rate [65].

Author Contributions: M.M.D.-E. conceived and designed the study, supervised experiments, interpreted results
and edited the paper, L.G. and N.S. performed the patient selection and participated in results interpretation; F.C.
and J.L. participated in patient selection and acquisition of data. I.S. managed the sample database, collected the
data, and performed some experiments; A.B., R.S.M. and M.P.-A. provided manuscript writing support and
conceptual advice; J.A.B. revised and edited the paper; E.G.-G. participated in the study design, carried out
experiments, analyzed the data, interpreted results and wrote the manuscript. All authors have read and agreed
to the published version of the manuscript.
Funding: This study was funded by a grant (PI17/01566, Plan Estatal 2017–2020) from Instituto de Salud Carlos III
(ISCIII) and FEDER.
Acknowledgments: We thank all the patients who agreed to participate in this study. We would like to thank Jordi
Bover for his expert advice and assistance in manuscript review. Many thanks also to Beatriz Bardají-de-Quixano
for her valuable advice and recommendations and to Rick Mills for his help in manuscript proofreading.
Our nephrology research group belongs to a Consolidated Research Catalan Group (AGAUR 2009/SGR-1116) and
to REDinREN (RD12/0021/0033). We are also grateful to Sandoz Farmaceutica S.A. for its support.
Conflicts of Interest: The authors declare no conflict of interest.

Abbreviations
DD              Deceased donor
LD              Living donor
A2A R           A2A adenosine receptor
KTR             Kidney transplant recipient
Int. J. Mol. Sci. 2020, 21, 8826                                                                                  14 of 17



NT              Nucleoside transporter
SAHH            S-adenosyl-L-homocysteine hydrolase
AC              Adenylate cyclase
ADK             Adenosine kinase
PKA             Protein kinase A
SAH             S-adenosylhomocysteine
ENT             Equilibrative nucleoside transporter
CNT             Concentrative nucleoside transporter
hENT            Human ENT
hCNT            Human CNT

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