Differential immune response modulation in early Leishmania amazonensis infection of BALB/c and C57BL/6 macrophages based on transcriptome profiles

Abstract

The fate of Leishmania infection can be strongly influenced by the host genetic background. In this work, we describe gene expression modulation of the immune system based on dual global transcriptome profiles of bone marrow-derived macrophages (BMDMs) from BALB/c and C57BL/6 mice infected with Leishmania amazonensis. A total of 12,641 host transcripts were identified according to the alignment to the Mus musculus genome. Differentially expressed genes (DEGs) profiling revealed a differential modulation of the basal genetic background between the two hosts independent of L. amazonensis infection. In addition, in response to early L. amazonensis infection, 10 genes were modulated in infected BALB/c vs. non-infected BALB/c macrophages; and 127 genes were modulated in infected C57BL/6 vs. non-infected C57BL/6 macrophages. These modulated genes appeared to be related to the main immune response processes, such as recognition, antigen presentation, costimulation and proliferation. The distinct gene expression was correlated with the susceptibility and resistance to infection of each host. Furthermore, upon comparing the DEGs in BMDMs vs. peritoneal macrophages, we observed no differences in the gene expression patterns of Jun, Fcgr1 and Il1b, suggesting a similar activation trends of transcription factor binding, recognition and phagocytosis, as well as the proinflammatory cytokine production in response to early L. amazonensis infection. Analysis of the DEG profile of the parasite revealed only one DEG among the 8,282 transcripts, indicating that parasite gene expression in early infection does not depend on the host genetic background.

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Dierential immune response
modulation in early Leishmania
amazonensis infection of BALB/c
and C57BL/6 macrophages based
on transcriptome proles
Juliana Ide Aoki
1*, Sandra Marcia Muxel1, Ricardo Andrade Zampieri1, Karl Erik Müller2,3,
Audun Helge Nerland
2 & Lucile Maria Floeter-Winter1*
The fate of Leishmania infection can be strongly inuenced by the host genetic background. In
this work, we describe gene expression modulation of the immune system based on dual global
transcriptome proles of bone marrow-derived macrophages (BMDMs) from BALB/c and C57BL/6 mice
infected with Leishmania amazonensis. A total of 12,641 host transcripts were identied according to
the alignment to the Mus musculus genome. Dierentially expressed genes (DEGs) proling revealed
a dierential modulation of the basal genetic background between the two hosts independent of
L. amazonensis infection. In addition, in response to early L. amazonensis infection, 10 genes were
modulated in infected BALB/c vs. non-infected BALB/c macrophages; and 127 genes were modulated
in infected C57BL/6 vs. non-infected C57BL/6 macrophages. These modulated genes appeared to
be related to the main immune response processes, such as recognition, antigen presentation,
costimulation and proliferation. The distinct gene expression was correlated with the susceptibility and
resistance to infection of each host. Furthermore, upon comparing the DEGs in BMDMs vs. peritoneal
macrophages, we observed no dierences in the gene expression patterns of Jun, Fcgr1 and Il1b,
suggesting a similar activation trends of transcription factor binding, recognition and phagocytosis, as
well as the proinammatory cytokine production in response to early L. amazonensis infection. Analysis
of the DEG prole of the parasite revealed only one DEG among the 8,282 transcripts, indicating that
parasite gene expression in early infection does not depend on the host genetic background.
Leishmania is a protozoan parasite and the causative agent of several clinical infections, generically known as
leishmaniases. In general, these infections are characterized by cutaneous, mucosal or visceral manifestations1,2.
Leishmaniases are considered neglected tropical diseases by the World Health Organization. ere is no vaccine
available to prevent the disease due to a range of factors, such as diversity among Leishmania species and the
interaction of these parasites with the host immune system3–6. Treatment can be complicated since most of the
drugs available are expensive and toxic and may require long treatment regimens7,8. Furthermore, resistance to
several commonly used drugs has been reported9. In humans, L. amazonensis infection can cause chronic cutane-
ous lesions, although diuse cutaneous and visceral manifestations have been reported1,7.
e immune response to Leishmania involves a complex range of cells. Neutrophils and monocytes are rst
recruited to the site of the insect bite, which leads to the dierentiation of macrophages; this dierentiation is fol-
lowed by the recognition and phagocytosis of the parasite, as well as the induction of a range of inammatory sig-
nals. Other phagocytes, such as dendritic cells, also play important roles since they induce the response in other
inammatory tissues. However, macrophages that play a critical roles in the establishment of infection, as they are
the main host cells for Leishmania replication inside the phagolysosome10–13. e infection is characterized by 1
cell-mediated production of interferon gamma (IFN-γ), tumor necrosis factor alpha (TNF-α) and granulocyte
1Department of Physiology, Institute of Bioscience, University of São Paulo, São Paulo, Brazil. 2Department of
Clinical Science, University of Bergen, Bergen, Norway. 3Department of Internal Medicine, Drammen Hospital,
Drammen, Norway. *email: juaoki@usp.br; lucile@ib.usp.br
open
Corrected: Author Correction
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macrophage colony-stimulating factor (GM-CSF), which polarizes macrophages to the proinammatory M1
phenotype and increases nitric oxide synthase 2 (NOS2) and nitric oxide (NO) levels, resulting in parasite control,
or by 2 cell-mediated production of interleukin (IL) 4 (IL4), IL13, IL10, tumor growth factor beta (TGFβ) and
macrophage colony-stimulating factor (M-CSF), which polarizes macrophages to an anti-inammatory M2 phe-
notype and increases arginase 1 and polyamine production, resulting in parasite replication3,14–17. However, the
parasite is able to subvert macrophage killing mechanisms through the modication of host cytokine expression,
preventing antigen display by MHC class II molecules and reducing NO production with consequent amastigote
dierentiation and proliferation11,12.
Leishmania infection in murine models has been extensively characterized and varies according to the parasite
species and host genetic background3,18–22. Progressive disease occurs due to impaired cellular immunity, with
dysfunction of T cells, macrophages, or both23. Regulation of the host immune response to Leishmania has been
well dened in L. major model in which the BALB/c mouse strain is susceptible to infection due to early bursts of
IL4 that lead to disease progression. On the other hand, the C57BL/6 mouse strain is resistant to infection due to
a dominant 1-type response leading to infection control13,18–20,24. Experimental murine infections with L. ama-
zonensis have demonstrated distinct susceptibilities compared to those for L. major25,26. L. amazonensis induces
severe lesions upon cutaneous inoculation in susceptible BALB/c mice, while the same parasite causes only mod-
erate lesions in resistant C57BL/6 mice21,27. Such variations in infection have been observed as dierences in the
lesion size, parasite burden, cellular activation and 1/2 ratio between the dierent infected strains21,25,28.
Furthermore, studies involving knockout mouse strains have revealed interesting data concerning the
response of the host to Leishmania infection. Targeted deletion of the Il4 and Il10 genes results in a minimal
eects on the development of L. amazonensis29 and L. major infections30, due to reduced IL12 receptor expression,
which leads to reduced IL12 responsiveness and, consequently, to impairment of the 1 response31. In Tlr4- and
MyD88- decient mice, L. amazonensis shows increased in vitro infectivity; in contrast Tlr2-decient mice exhib-
ited a decreased parasite loads, indicating that this receptor is required for disease progression32.
Based on these ndings, we analyzed the modulation of the early immune responses dened by the dual
transcriptome proles of BMDMs from the BALB/c and C57BL/6 mouse strains aer infection with L. ama-
zonensis for 4 h. Previous transcriptomic data have revealed novel information about the coordinated response
of Leishmania-infected macrophages33–36 and about parasite biology, physiology and gene expression modula-
tion37–42. In this work, we identied a total of 12,641 total mouse transcripts, and analyses of the DEGs prole
involved in immune response modulation conrmed the existence of dierences between these two hosts that can
regulate susceptibility and resistance to L. amazonensis infection. Interestingly, the parasite transcriptome prole
showed only one DEG, a noncoding RNA, indicating that the parasite presents no modulation of gene expression
in early infection regardless of the host genetic background.
Results
BMDMs from BALB/c mice exhibited a lower infection index than those from C57BL/6 mice at
4 h after infection. BMDMs from the BALB/c and C57BL/6 mouse strains were infected with L. amazon-
ensis (MOI 5:1), and the infection index was analyzed at 4 h aer infection. First, no signicant dierences were
observed in the infection rate or the number of intracellular parasites per infected macrophage (Fig.S1A,B).
However, the infection index was signicantly lower in infected BALB/c than in infected C57BL/6 macrophages
(Fig.S1C).
Host transcriptome proling revealed greater gene expression modulation in BMDMs from
C57BL/6 mice than in BALB/c mice in response to L. amazonensis infection. Transcriptomic anal-
yses were performed on ve independent biological replicates per analysis of BMDMs from BALB/c and C57BL/6
mice infected or not infected with L. amazonensis for 4 h, using Illumina NovaSeq. 6000 sequencing, which
generated millions of reads. e sequencing data are available in the NCBI BioProject database (https://www.
ncbi.nlm.nih.gov/bioproject/) under accession numbers PRJNA481041 and PRJNA481042 and in the Sequence
Read Archive (SRA) database (https://www.ncbi.nlm.nih.gov/sra) under accession numbers SRP156183 and
SRP156466. e RNA-seq data were aligned to the M. musculus reference genome, and 12,641 transcripts were
identied (TableS1).
Analysis of DEGs with a statistical signicance threshold of a fold change ≥ 2 and a p-value < 0.05 revealed
dierential basal backgrounds in non-infected BALB/c vs. non-infected C57BL/6 macrophages; specically,
313 genes were upregulated, and 254 genes were downregulated. Comparison of BALB/c_La vs. BALB/c mac-
rophages revealed only 20 upregulated genes and 2 downregulated genes. In contrast, comparison of C57BL/6_La
vs. C57BL/6 macrophages revealed 358 upregulated genes and 139 downregulated genes, and comparison of
BALB/c_La vs. C57BL/6_La macrophages revealed 318 upregulated genes and 434 downregulated genes (Fig.1).
In addition, we generated volcano plots comparing the fold changes in expression (log2) with the correspond-
ing adjusted p-values (-log10) (Fig.S2A) and volume plots comparing the fold changes in expression (log2) with
the volumes (Fig.S2B). Based on these results, we identied the ve most highly modulated transcripts among
the comparisons (TableS2). Functional annotation and gene enrichment analyses were performed using the Gene
Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. KEGG enrichment analysis
showed the 20 most dierentially regulated pathways among the samples (Fig.S2C).
RNA-seq generates a large amount of information that can be analyzed from various perspectives. According
to GO enrichment analysis of the DEGs, the most modulated subcategories were associated with biological pro-
cesses, molecular functions and cellular components (Fig.2). In this work, we focused on the immune system
process term, comprising 361 modulated transcripts (TableS3), to elucidate how the host genetic background
dierences can dene the fate of L. amazonensis infection.
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The gene expression modulation patterns revealed higher immune response activation in
BMDMs from C57BL/6 mice than in BALB/c mice in response to L. amazonensis infection.
Among the 361 modulated transcripts related to immune system processes, 150 of them appeared to dier in
expression in non-infected BALB/c vs. C57BL/6 macrophages, indicating the existence of dierential basal gene
expression in these two host backgrounds, independent of L. amazonensis infection. Aer L. amazonensis infec-
tion, we observed only 10 modulated genes in BALB/c_La vs. BALB/c macrophages; 127 modulated genes in
C57BL/6_La vs. C57BL/6 macrophages; and 221 modulated genes in C57BL/6_La vs. BALB/c_La macrophages
(Table1).
Furthermore, we categorized the identied molecules according to the main types of immune system pro-
cesses in response to L. amazonensis infection (Fig.3). In the BALB/c_La vs. BALB/c comparison, we found that
most of the modulated transcripts were immunomodulatory (Il1b, Irg1 and Tnfrsf26) and chemokine signaling
molecules (Cxcl1, Cxcl2 and Cxcl3) (Fig.3 and Table1). In the C57BL/6_La vs. C57BL/6 comparison, most of the
modulated transcripts were immunomodulatory molecules (Clec4d, Clec4e, Clec5a, Il16, Il17ra, Il1rn, Il27, Irak2,
Figure 1. Transcriptome proles of BMDMs from BALB/c and C57BL/6 mice infected with L. amazonensis.
Dierential gene expression proles of BMDMs from BALB/c and C57BL/6 mice infected with L. amazonensis,
presented as the numbers of upregulated (light gray) and downregulated (dark gray) transcripts in the following
comparisons: non-infected BALB/c vs. non-infected C57BL/6 macrophages; infected BALB/c vs. non-infected
BALB/c macrophages; infected C57BL/6 vs. non-infected C57BL/6 macrophages; and infected BALB/c vs.
infected C57BL/6 macrophages. e data are from ve independent biological replicates, considering a fold
change ≥2 and a p-value < 0.05. La, L. amazonensis.
Figure 2. GO enrichment analysis of DEGs in BMDMs from BALB/c and C57BL/6 mice in response to L.
amazonensis infection. e GO enrichment analysis results are presented as numbers of transcripts distributed
in three main categories: biological process, molecular function and cellular component. Immune system
processes were the focus of this work.
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Irg1, Lcp2 Mefv, emis2, Tnf, Tnfaip3, Tnfaip8l2, Tnfrsf26, Tnfsf9, Tnip1 and Tnip3), transcription factors (Batf,
Bcl3, Cebpb, Foxo3, Hhex, Id2, Irf1, Jun, Lyl1, Ma, Nb1, Nb2, Nbia, Tiparp, Trim13, Trim14 and Tsc22d3),
adaptor proteins (Malt1, Mef2c, Nck1, Nfe2l2, Nr1h3, Pik3cd, Procr, Ptafr, Rbpj, Rgcc, Sh2b2, Smad6 and Src) and
members of recognition pathways (Birc3, Jag1, Lilrb4a, Mapk14, Mb21d1, Nlrp3, Nod2, Ripk2, Tlr2, Tlr8 and
Traf3) (Fig.3 and Table1).
The exclusive dierential gene expression patterns in BMDMs from C57BL/6 mice appeared to
be mostly related to proliferation signaling and transcription factor molecules. Venn diagram
analysis was performed, and based on the results, we grouped the exclusively and commonly modulated genes
involved in the immune response. We identied 28 exclusively modulated genes in the comparison of the two
host backgrounds (in non-infected macrophages). Additionally, we identied only one exclusively modulated
gene in BALB/c_La vs. BALB/c macrophages, 39 exclusively modulated genes in C57BL/6_La vs. C57BL/6 mac-
rophages, and 47 exclusively modulated genes in C57BL/6_La vs. BALB/c_La macrophages. Interestingly, only
one gene, Smad6, was common among all comparisons (Fig.4A).
Examination of the immune response modulation associated with L. amazonensis infection and the pattern
of exclusively expressed genes in the comparison of BALB/c_La vs. BALB/c macrophages revealed the downreg-
ulation of Il1b as unique (Fig.4B). In contrast, comparison of C57BL/6_La vs. C57BL/6 macrophages revealed a
set of 39 modulated genes, among which 22 were upregulated genes and 17 were downregulated. Most of these
genes appeared to be involved in the proliferation pathway, such as the downregulated Pik3cd and Mtus1 genes
comparison downregulated genes upregulated genes p-value FDR
BALB/c vs.
C57BL/6
Adgre1, AF251705, Ang, Apobec3, Asb2, Batf3,
Blnk, Bst2, C1qa, C1qb, C1qc, C5ar2, Camp,
Ccl5, Ccr2, Cd300a, Cd4, Cd40, Cd79b, Clec1b,
Clec2d, Clec4a2, Ctsh, Cxcl10, Cxcl9, Emr1,
Erbb2ip, Fcgr4, Fcna, Gbp2, Gbp3, Gbp5, Gbp7,
Hfe, It1bl1, Iigp1, Il15, Il18bp, Irf1, Irgm2,
Itga4, Itgad, Itgal, Lcn2, Lgals1, Ly86, Marco,
Mertk, Mill2, Pde4b, Pnp, Prdm1, S100a8,
Samhd1, Skil, Slamf7, Slc11a1, Slc40a1, Smad6,
Tfrc, Tgtp1, Tlr8, Tmem176a, Tmem176b,
Trim34a, Vcam1, Veg fa, Vsig4, Wwp 1
Ada, Ahcy, Alpk1, Armc6, Batf, Bcl2a1a, Bcl2a1d,
Bst1, Ccl2, Ccl24, Ccl3, Ccl4, Ccl7, Ccnb2, Ccr1,
Cd109, Cd14, Cd24a, Cd300lf, Cd86, Cdk6, Clec4n,
Clec5a, Col3a1, Colec12, Csf1, Ctse, Cx3cr1, Cxcl14,
Fam20c, Glo1, Gm8909, Gpr183, H2-Ab1, H2-
DMb1, H2-K1, H2-L, H2-Q1, H2-Q2, H2-Q4, H2-
Q6, H2-Q8, H2-Q9, H2-T22, H2-T24, Hist1h2bf,
Hist1h2bk, Hist1h2bl, Hist2h3c2, Hist1h3a,
Hist1h3b, Hist1h3d, Hist1h3g, Hist1h3h, Hist1h3i,
Hist1h4a, Hist1h4f, Hist1h4i, Hist4h4, Itm1,
Itm3, Il1rn, Irf7, Kdr, Lat2, Malt1, Mmp14, Myc,
Ndrg1, Npy, Oasl1, Pla2g7, Ripk3, Serpine1, Slpi,
Spn, Spp1, Stap1, Tnfsf13, Tnfsf8, Top2a
2.88e−79 1.00e−76
BALB/c_La
vs. BALB/c Il1b, Mef2c Cxcl1, Cxcl2, Cxcl3, Hilpda, Id2, Irg1, Smad6,
Tnfrsf26 2.43e−82.24e−6
C57BL/6_La
vs. C57BL/6
Ccr2, Ccr5, Fcgr1, Foxo3, Gcnt1, Gpr183,
Hhex, Hist1h2bc, Hist1h2be, Hist1h2bg,
Hist1h3e, Hist1h4c, Hist1h4d, Hist1h4h,
Hist1h4m, Hist2h3b, Hist2h4, Il16, Lyl1, Ma,
Mapk14, Mef2c, Mertk, Mtus1, Pik3cd, Rassf2,
emis2, Tlr8, Tnfaip8l2, Trim14, Tsc22d3,
Zfp36l1, Zfp36l2
Adora2b, Ampd3, Batf, Bcl2a1a, Bcl2a1d, Bcl3,
Birc3, Ccl3, Ccl4, Cd24a, Cd274, Cd40, Cd83,
Cd86, Cdkn1a, Cdkn2b, Cebpb, Clec4d, Clec4e,
Clec5a, Cxcl1, Cxcl2, Cxcl3, Ednrb, Ezr, Fam20c,
Fas, Gadd45g, Gbp5, Gch1, Gpr68, H2-M2, Hcar2,
Hilpda, Hmox1, Hsp90aa1, Hyal2, Icam1, Icosl,
Id2, Il17ra, Il1rn, Il27, Irak2, Irf1, Irg1, Jag1, Jun,
Lcp2, Lilrb4a, Malt1, Mb21d1, Mefv, Mmp14, Nck1,
Nfe2l2, Nb1, Nb2, Nbia, Nlrp3, Nod2, Nr1h3,
Olr1, Osm, Pde4b, Pmaip1, Ppp4r2, Prdx1, Procr,
Ptafr, Rbpj, Rgcc, Ripk2, Rnf19b, Samsn1, Serpine1,
Sh2b2, Slamf7, Slc11a2, Smad6, Sod2, Sqstm1,Src,
Stx11, Tiparp, Tlr2, Tnf , Tnfaip3, Tnfrsf26, Tnfsf9,
Tnip1, Tnip3, Traf3, Trim13
1.40e−65 2.37e−63
C57BL/6_La
vs. BALB/
c_La
Adgre1, Ampd3, Ang, Apobec3, Axl, Bcl3, Bcl6,
Birc3, Blnk, Bloc1s6, C1qa, C1qb, C1qc, C5ar1,
Camp, Casp1, Ccl3, Ccl4, Ccl5, Ccl9, Ccr2,
Ccr3, Cd274, Cd38, Cd4, Cd40, Cd79b, Cd83,
Cdkn1a, Cebpb, Clec1b, Clec2d, Clec2i, Clec4e,
Cnr2, Ctsh, Cxcl1, Cxcl10, Cxcl2, Cxcl3, Cxcl9,
Ednrb, Fas, Fcgr4, Fcna, Fyb, Fzd7, Gbp2,
Gbp3, Gbp5, Gbp6, Gbp7, Gpr68, H2-Ab1, H2-
DMb1, H2-K1, H2-L, H2-M2, Hmox1, Icam1,
Icosl, Iig p1, Il10, Il17ra, Il18bp, Il1a, Il1f9,
Il27, Irak2, Irak3, Irf1, Irg1, Itgad, Itgal, Jag1,
Kdr, Lcn2, Lcp2, Malt1, Mapkapk2, Marco,
Mefv, Mertk, Mill2, Nb1, Nb2, Nbia,
Nbid, Nlrc4, Nlrp3, Nod1, Nr1h3, Olr1,
Pde4b, Pmaip1, Pnp, Ppp4r2, Prdm1, Procr,
Ptafr, Ptprj, Rab32, Rela, Relb, Rgcc, Ripk2,
Rnf19b, S100a8, Sh2b2, Skil, Slamf7, Slc40a1,
Smad6, Snx10, Sod2, Sqstm1, Stx11, Tapbpl,
Tbk1, Tgtp1, bs1, Tlr1, Tlr2, Tmem176a,
Tmem176b, Tnf, Tnfaip3, Tnfrsf1b, Tnfsf9,
Tnip3, Traf3, Treml4, Trib1, Trim13, Vcam1,
Veg fa , Vsig4
Ada, Ahcy,Aim2, Alpk1, Armc6, Bst1, Ccl2,
Ccl24, Ccl7, Ccnb2, Cd109, Cd300lf, C, Clec4n,
Csf1, Colec12, Col3a1, Ctse, Cxcl14, Gcnt1, Glo1,
Gm8909, Gpr183, H2-Q1, H2-Q2, H2-Q6, H2-
Q8, H2-Q9, H2-T22, H2-T24, Hhex, Hist1h2ba,
Hist1h2be, Hist1h2bf, Hist1h2bg, Hist1h2bk,
Hist1h2bl, Hist1h3a, Hist1h3b, Hist1h3d, Hist1h3e,
Hist1h3h, Hist1h3i, Hist1h3g, Hist1h4a, Hist1h4b,
Hist1h4d, Hist1h4f, Hist1h4h, Hist1h4i, Hist1h4j,
Hist1h4k, Hist1h4m, Hist1h4n, Hist2h3b,
Hist2h3c2, Hist2h4, Hist4h4, Itm1, Itm3, Il16,
Il1rn, Irf4, Irf7, Junb, Lgals1, Mmp9, Ndrg1, Npy,
Pdgfrb, Pla2g7, Ripk3, Serpine1, Slfn1, Slpi, Spn,
Spp1, Tacc3, Tnfsf13, Tnfsf8 , Top2a,
2.02e−125 9.61e−123
Table 1. Prole of DEGs involved in immune system processes in BMDMs from BALB/c and C57BL/6
in response to L. amazonensis infection. Gene Ontology (GO) enrichment analysis and the proling of
dierentially expressed genes (DEGs) involved in the immune system processes in bone marrow-derived
macrophages (BMDMs) from BALB/c and C57BL/6 in response to L. amazonensis (La) infection. e analysis
was based on p-values and false discovery rates (FDRs).
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and the upregulated Samsn1, Prdx1, Osm and Hsp90aa1 genes. Another group of genes contained transcription
factors, including the downregulated Tsc22d3, Trim14, Ma and Lyl1 genes and the upregulated Tiparp, Rbpj,
Nfe2l2, Jun and Foxo3 genes. We also identied genes involved in recognition and costimulation pathways, as
well as genes encoding adaptor molecules: Fcgr1, Mapk14 and emis2 were downregulated, while Mb21d1/cGas,
Nod2, Clec4d, Lilrb4a, Cdkn2b, Nck1, Src and Tnip1 were upregulated. Among apoptosis-related molecules, Rassf2
and Gadd45g appeared downregulated. e immunomodulatory molecules Tnfaip8l2 and Ccr5 were downregu-
lated. e metal transporter Slc11a2 (formerly Nramp2) was upregulated. e histones Hist1h2bc and Hist1h4c,
as well as the RNA-binding proteins Zfp36l1 and Zfp36l2, were downregulated. Poorly studied molecules, such
as Adora2b, Ezr, Gch1 and Hyal2 were upregulated and were classied as belonging to other pathways (Fig.5).
RT-qPCR validation assays were performed on some of the most modulated molecules from the RNA-seq
data: Il1b, Fcgr1, Ccr5, Smad6, Jun and Mapk14. Comparative analyses showed concordance between the RNA-seq
and RT-qPCR data with no statistically signicant dierences, thus validating the RNA-seq results (Fig.6).
Similar to BMDMs, peritoneal macrophages were collected and infected with L. amazonensis, and the gene
expression modulation of selected genes was analyzed by RT-qPCR to evaluate whether a similar trend occurred
in another macrophage subtype. e infection index appeared signicantly lower in C57BL/6_La macrophages
than in BALB/c_La macrophages (Fig.S3A), indicating a distinct phenotypic dierence between BMDMs and
peritoneal macrophages in response to L. amazonensis infection. Comparison of the gene expression in BMDMs
and peritoneal macrophage subtypes from BALB/c_La mice revealed lower expression of Smad6 and Mapk14. No
modulation of Il1b, Ccr5, Fcgr1 or Jun was observed. On the other hand, we observed lower expression of Smad6,
higher expression of Ccr5 and no modulation of Il1b, Mapk14, Fcgr1 and Jun expression in BMDMs compared
with peritoneal macrophage subtype from C57BL/6_La (Fig.S3B).
e transcriptomic data presented here corroborate the ndings of previous studies on how dierential genetic
backgrounds from dierent hosts dene susceptibility or resistance to Leishmania infection. e DEGs proles
described in this work represents new knowledge obtained from transcriptome analyses of immune responses
between two dierent host genetic backgrounds. e analyses identied molecular markers that could be linked to
susceptibility and resistance to L. amazonensis infection, as illustrated by the schematic representation of the exclu-
sively and DEGs in BMDMs from BALB/c and C57BL/6 mice in response to early L. amazonensis infection (Fig.7).
Parasite transcriptome proling revealed only one DEG between L. amazonensis infecting
BALB/c and L. amazonensis infecting C57BL/6 macrophages. We also analyzed the gene expression
of L. amazonensis via alignment to the L. mexicana genome database (TableS1). e sequencing data are available
in the NCBI BioProject and SRA databases, as previously described.
Aer initial assembly, 8,282 parasite transcripts were identied. Analysis of DEGs with signicant threshold
of a fold change ≥ 2 and a p-value < 0.05, as statistically signicant, revealed only one DEG, a noncoding RNA
(ncRNA) (LmxM.32.ncRNA:rfamscan:912871–912976), which showed higher expression in infected BALB/c
than in infected C57BL/6 macrophages.
Additionally, we performed RT-qPCR validation assays of our RNA-seq data for Amastin-like gene (LmxM.33.0960).
Similar to the case for the host comparative analyses, we observed concordance between the RNA-seq and RT-qPCR
data (Fig.6), thus validating the RNA-seq results.
Finally, we observed lower expression of the Amastin-like gene (LmxM.33.0960) in peritoneal macrophages
than in BMDMs from BALB/c and C57BL/6 mice (Fig.S3B).
Figure 3. Immune response analysis of DEGs in BMDMs from BALB/c and C57BL/6 mice in response to
L. amazonensis infection. Pie chart of the modulated molecules involved in the immune response processes
grouped into main immune signaling pathways.
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Discussion
e 1/2 paradigm correlating resistance/susceptibility to Leishmania infection has been extensively stud-
ied3,14,18–21,23,35,41. Identication of potential biomarkers for leishmaniases can be useful for dierent approaches,
such as diagnosis, prognosis, disease progression monitoring, clinical intervention and host immune response
characterization33,34,41,43–45. e host-parasite interaction depends on both host genetic backgrounds33,35,36,41 and
the genetic complexity of Leishmania species39,40,46.
L. amazonensis infection elicits dierent immune responses than those previously described for L. major
infection25,26,28,29,31,35. In this work, we present the global transcriptome proles of BMDMs from BALB/c and
Figure 4. Venn diagram analysis of DEGs in BMDMs from BALB/c and C57BL/6 mice in response to L.
amazonensis infection. (A) Venn diagram of the 361 DEGs involved in the immune response processes, showing
the numbers of exclusively and common genes for each comparison. (B) List of exclusively and common genes
according for each comparison in the Venn diagram.
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C57BL/6 mice non-infected and infected with L. amazonensis, focusing on the modulation of the immune
response. In the absence of L. amazonensis infection, we identied signicantly dierent basal gene expression
patterns between the two hosts, corroborating with previous ndings47. Analysis of the immune response in early
L. amazonensis infection revealed 361 modulated genes among the comparisons. Comparison of infected BALB/c
to non-infected BALB/c BMDMs revealed low levels of gene expression modulation; this pattern could be related
to limited immune response activation, leading to susceptibility of this host to L. amazonensis infection, as previ-
ously described21,48. e DEGs involved in immune response modulation comprised mostly immunomodulatory
and chemokine signaling molecules, suggesting a link to the inammation process. In contrast, we observed high
levels of gene expression modulation in infected C57BL/6 compared to non-infected C57BL/6 BMDMs. is
pattern could be related to increased immune response activation via augmentation of recognition processes
and, consequently, activation of signaling cascades, leading to moderate resistance of this host to L. amazonensis
infection. Dierent proles associated with dierent host genetic backgrounds have previously been described as
being due to dierent parasite burdens, inammatory cell populations and cytokine production21,48.
e infection index of BMDMs from BALB/c mice appeared smaller than that of BMDMs from C57BL/6
mice aer 4 h of infection. As the infection index represents the number of intracellular parasites multiplied by
the percentage of infected macrophages, the biological impact of this dierence indicates that at an early stage of
infection, C57BL/6 macrophages exhibit greater phagocytosis, which in subsequent times of infections may ena-
ble control of parasite replication. Previous studies by our group have demonstrated increased infection index val-
ues in BALB/c macrophages aer 24 and 48 h of infection; in contrast, the index values of C57BL/6 macrophages
appeared to remain stable49,50. However, most gene expression modulation has been described to occur during
early Leishmania infection33,38,41,50,51.
e fact that Il1b appeared to be downregulated and was an exclusively modulated gene involved in the
immune response in infected BALB/c compared to non-infected BALB/c BMDMs corroborates the important
role of this molecule in Leishmania infection. IL1β has previously been identied as an important signaling fac-
tor for host resistance to C57BL/6 infection, since this cytokine signals through IL1R and MyD88 to induce
NOS2-mediated NO production, which is a major host defense mechanism against Leishmania52. Furthermore,
polymorphisms in the Il1b gene are associated with the severity of the disease in patients infected with L. mex-
icana53. Given these ndings, we reinforce the importance of this molecule in Leishmania infection in both
hosts52–54.
e 39 exclusively modulated immune response-related genes in infected C57BL/6 compared to non-infected
C57BL/6 BMDMs were associated with important signaling pathways, suggesting enhancement of immune
response activation resulting in moderated resistance against L. amazonensis infection. e recognition signa-
ling cascade included a large number of modulated molecules, highlighting the importance of the host genetic
background in the initial steps of macrophage activation55. Among these molecules, NOD-like receptors play
protective roles during Leishmania infection52,56,57. e upregulation of Nod2 in infected C57BL/6 compared
Figure 5. DEGs prole of the exclusively modulated genes involved in the immune response processes in
infected C57BL/6 vs. non-infected C57BL/6 BMDMs. e proles of DEGs are presented as the log2-fold
changes in the expression of the 39 exclusively modulated genes involved in the immune response processes
in BMDMs from C57BL/6 infected with L. amazonensis vs. non-infected C57BL/6 BMDMs. e genes were
classied by their involvement in main immune response signaling pathways or by their identities as regulatory
molecules of the immune response pathways. La, L. amazonensis.
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Figure 6. RT-qPCR validation of some modulated genes in BALB/c and C57BL/6 BMDMs in response to L.
amazonensis infection. Comparative analysis of the relative expression levels of selected genes determined by
RNA-seq and validated by RT-qPCR. e bars represent the mean ± SD values of the fold changes in Il1b, Fcgr1,
Ccr5, Smad6, Jun and Mapk14 expression determined with ve independent biological replicates analyzed
in duplicate. e fold changes were calculated through relative quantication using the ΔΔCt method. e
data were normalized to Gapdh expression and the relative gene expression was set to 1 for the control (non-
infected) samples. Statistical analysis was performed using the t-tests, and no signicant dierences were
observed (p-value < 0.05) between the RT-qPCR and RNA-seq results for the BALB/c_La and C57BL/6_La
groups. e bars for Amastin-like (LmxM.33.0960) show the mean aer normalization to Gapdh in L.
amazonensis infecting BALB/c and L. amazonensis infecting C57BL/6 macrophages. La, L. amazonensis.
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to non-infected BMDMs indicates greater macrophage activation in C57BL/6 mice. NOD2 mediates the
parasite-induced production of cytokines, such as IL-17 and IFN-γ production, in L. infantum and L. amazonen-
sis infections, whereas NOD1 is not relevant to these infections56,57. Recognition signaling also involves MAPKs,
which play important roles against parasitic infections58, driving the switch in macrophage activation from proin-
ammatory IL12 to anti-inammatory IL10 cytokines59. Previous studies have demonstrated that signaling dur-
ing L. amazonensis infection leads to the activation of MAPK1 and MAPK358. MAPK14 has been poorly studied
in the context of Leishmania infection, although downregulation of Mapk14 has previously been described to
occur in L. braziliensis and L. major infections41,60. Most molecules from the recognition pathway were upregu-
lated, indicating the activation of the downstream steps in recognition signaling cascades.
Immunomodulatory molecules play important roles in macrophage activation and the induction of adaptive
immune responses via cytokine production in response to Leishmania infection13,20,61. Among the main cytokines
studied, TNF is a multipotent cytokine implicated in a wide range of immune responses occuring in response
to many infections62,63. In particular, the TNF-related molecules Tnip1 and Tnfaip8l2 appeared upregulated and
downregulated, respectively, indicating signaling cascade activation and repression to maintain immune home-
ostasis. Leishmania infection can also induce the expression of numerous chemokines26,51,64,65. is event could
potentially benet the parasite due the ability to repress the induction of proinammatory cytokine expression66.
e downregulation of Ccr5 in infected C57BL/6 vs. non-infected C57BL/6 BMDMs could be correlated with the
fact that this receptor directs the 1 immune response and is thus associated with inammation, cell inltra-
tion and the development of infectious disease67. Previous studies have demonstrated that CCR5 knockout mice
exhibit increased resistance to L. major infection68.
Similarly, human macrophage infections with L. amazonensis, L. major and L. panamensis have been shown to
elicit immune response modulation of TNF, NF-kB and NOD-like receptor signaling pathways, oxidative stress
pathways and proliferation signaling pathways41,69.
e expression of proliferation signals and transcription factor-related molecules was highly modulated
according to our data. ere are limited descriptions of these molecules; however, they are known to control the
expression of many genes required for the eective activation of the immune responses, such as transcriptional
activators or repressors, as well as for FOXO transcriptional activity, NF-kB recruitment and Notch signaling70–73.
e release and activation of histones occur in response to stress, leading to Toll-like receptor binding and
triggering the activation of multiple signaling pathways74. e downregulation of Hist1h4c and Hist1h2bc could
be related to the negative modulation of transcription factors listed above that are involved in macrophage
activation.
e metal transporter natural resistance-associated macrophage protein (Nramp) has been associated with
resistance to intracellular pathogens due to enhanced NOS2 expression and NO production75,76. Point mutations
in Nramp1 promote susceptibility to Leishmania infection by modulating iron acquisition from intracellular com-
partments76,77, starving pathogens of this essential nutrient and impacting parasite survival and replication78.
Although Nramp2 shares a conserved structure and iron transport functions with Nramp1, its role in Leishmania
infection has been poorly studied. e upregulation of Slc11a2 (formerly Nramp2) was upregulated in infected
C57BL/6 macrophages could be correlated with increased NO production and resistance to L. amazonensis
infection.
Apoptosis induced by Leishmania may permit successful infection through modulation of host immunity79.
RASSF2 and GADD45G are involved in the regulation of growth and apoptotic processes. Consistent with these
ndings, we identied downregulation of Rassf2 and the upregulation of Gadd45g as important factors in the
modulation of the host immunity in response to L. amazonensis infection.
Molecules not acting in any of the described pathways were classied as “other” due to their limited descrip-
tions in Leishmania infection. Further studies and functional validation could implicate the role of these
Figure 7. Schematic representation of the exclusive genes and DEGs in BALB/c and C57BL/6 BMDMs in
response to L. amazonensis infection. Summary of the data of the exclusive genes and DEGs in BMDMs derived
from BALB/c and C657BL/6 mice in response to early L. amazonensis infection.
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molecules in host immune modulation in response to L. amazonensis infection, but this study provides only a
global transcriptomic view based on the prole of the DEGs involved in immune response modulation in the two
dierent host genetic backgrounds.
Macrophages form a vast and diverse population with considerable plasticity to adapt to dierent tissues
and change in response to environmental variations80–83. e dierences between peritoneal macrophages and
BMDMs are believed to arise from dierential physiological conditions and organ specicity along with the het-
erogeneity of macrophages83,84. us, we compared BMDMs and peritoneal macrophages with regard to some
of the modulated genes to reinforce our ndings and provide a representation of the in vivo scenario. According
to our results, the infection index appeared lower in peritoneal macrophages from C57BL/6 mice than in those
from BALB/c mice, indicating a distinct phenotypic dierence between the macrophage subtypes in response
to early L. amazonensis infection and suggesting that BALB/c mice are more susceptible models than C57BL/6
mice, as previously described21,48. Analyses of gene expression have shown a similar gene expression proles in
the comparison of BMDMs and pre-existing populations, although some dierences have also been reported,
suggesting that tissue environments dictate the macrophage phenotype required to trigger an eective immune
response80,81. In our comparisons we observed nondierential and dierential modulation patterns, indicating
that some of the analyzed genes were involved in distinct signaling cascades that lead to a distinct network activ-
ity. Smad6 showed a lower gene expression pattern in peritoneal macrophages than in BMDMs in both BALB/c
and C57BL/6 mice. Since Smad6 is a regulator of myeloid dierentiation85, this expression pattern conrms the
dierences between the macrophage subtypes. ere were no dierences in the gene expression patterns of Jun,
Fcgr1 and Il1b between macrophage subtypes, suggesting similar trends of activation of transcription factor bind-
ing, recognition, phagocytosis and proinammatory cytokines production. Ccr5 showed high modulation only
in peritoneal macrophages from infected C57BL/6 mice, indicating upregulation of this chemokine receptor in
this macrophage subtype. Mapk14 showed low modulation only in peritoneal macrophages from infected BALB/c
mice, indicating low activation of the cellular response cascade in this macrophage subtype.
Altogether, our ndings indicate the need to be cautious in extrapolating ndings to in vivo scenarios that may
or may not dier from those observed in the present study, especially considering that other immune cells, such
as monocytes, neutrophils and lymphocytes, migrates to local cutaneous lesions with Leishmania86–88. Both host
and parasite genetic backgrounds also need to be considered in translational approaches to identify biomarkers
for the prognosis determination and treatment of the leishmaniases.
Finally, the transcriptome proling of the parasite revealed only one DEG between L. amazonensis infecting
BALB/c macrophages and L. amazonensis infecting C57BL/6 macrophages, a noncoding RNA (LmxM.32.ncR-
NA:rfamscan:912871–912976). ncRNAs have several functions; for example, they mediate transcription by RNA
polymerase II, polyadenylate 3´-ends, regulate transcript expression and are potentially associated with small
ribonucleoprotein complexes89. Our observations indicate that during early infection, the parasite exhibits the
same gene expression pattern regardless of the host genetic background.
Methods
Animals. Female BALB/c and C57BL/6 mice (6–8 weeks old) were obtained from the Animal Center of the
Medical School of the University of São Paulo and were maintained at the Animal Center of the Department of
Physiology of the Institute of Bioscience of the University of São Paulo with access to food and water ad libitum.
Leishmania culture. L. amazonensis (MHOM/BR/1973/M2269) was grown at 25 °C in M199 medium
(Gibco, Grand Island NY, USA), pH 7.0, supplemented with L-glutamine, 10% heat-inactivated fetal bovine
serum, 0.25% hemin, 40 mM NaHCO3, 100 μM adenine, 40 mM HEPES, 100 U/mL penicillin and 100 μg/mL
streptomycin, as previously described37–39. e parasites were counted in a Neubauer chamber.
In vitro macrophage infections. BMDMs were obtained from the femurs of BALB/c and C57BL/6 mice
through PBS washing, and the cells were collected by centrifugation at 500 x g for 10 min at 4 °C. Lysis of eryth-
rocytes was performed with NH4Cl (145 mM) and Tris-base (200 mM), pH 7.0, followed by incubation on ice for
20 min. Aer lysis, the cells were washed with cold PBS, centrifuged at 500 x g for 10 min at 4 °C and incubated in
RPMI 1640 medium supplemented with penicillin (100 U/mL), streptomycin (100 µg/mL), 2-mercaptoethanol
(50 µM), L-glutamine (2 mM), sodium pyruvate (1 mM), 10% fetal bovine serum and 10% L929 conditioned
medium as a macrophage stimulating factor source. e cells were dierentiated for 7 days at 34 °C in 5% CO2. e
BMDMs were used aer phenotypic analysis by ow cytometry showed at least 95% F4/80 and CD11b-positive
cells, as previously described50. Aer macrophage dierentiation, cellular viability was evaluated with Trypan
blue staining (1:1 (v:v)), and the cells were counted in a Neubauer chamber. Approximately 5 × 106 BMDMs from
BALB/c and C57BL/6 mice were incubated in sterile 6-well plates (SPL Life Sciences, Korea) overnight at 34 °C in
5% CO2. Non-adherent cells were removed by washing with PBS, and infection was performed with L. amazonen-
sis promastigotes in the stationary growth phase (MOI 5:1). Aer 4 h of infection, the cultures were washed with
PBS; then, RNA was extracted, or the infection index was determinated. Non-infected macrophages maintained
in culture under the same conditions were used as the controls. e infections were evaluated by determining
the percentage of infected cells aer counting 400 panoptic-stained (Laborclin, Parana, Brazil) macrophages.
e infection index was determined by multiplying the percentage of infected macrophages by the mean num-
ber of intracellular parasites per infected cell90,91. Statistical analyses were performed using Student´s t-test and
p-value < 0.05 was considered to indicate a signicant dierence between infected C57BL/6 macrophages or
infected BALB/c macrophages and the corresponding non-infected macrophages.
Peritoneal macrophages were collected from BALB/c and C57BL/6 mice by injection and recovery of 5 mL of
RPMI 1640 medium supplemented, as previously described. e cells were recovered by centrifugation at 500 × g
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for 10 min at 4 °C. Cellular viability was evaluated with Trypan blue staining (1:1 (v:v)), and the cells were counted
in a Neubauer chamber. Approximately, 1 × 106 peritoneal macrophages were incubated in sterile 6-well plates
(SPL Life Sciences, Korea) overnight at 34 °C in 5% CO2. Non-adherent cells were removed by washing with PBS,
and infection was performed with L. amazonensis promastigotes in the stationary growth phase (MOI 5:1). Aer
4 h of infection, cultures were washed with PBS; then, RNA was extracted or the infection index was determined.
Non-infected macrophages maintained in culture under the same conditions were used as the controls. e infec-
tions were evaluated as previously described for BMDMs.
Total RNA isolation and library construction. Total RNA was isolated from ve independent biological
replicates of each infected and non-infected group using TRIzol reagent (Life Technologies, Carlsbad, CA, USA)
according to the manufacturer’s instructions and as previously described39. e RNA samples were treated with
DNase I (1 U per µg of RNA) (ermo Scientic, Lithuania, EU) at 37 °C for 1 h, and the RNA concentration was
determined from the A260/A280 ratio using a NanoDrop ND1000 (ermo Scientic, USA). In addition, RNA
integrity was evaluated using an Agilent 2100 Bioanalyzer and a Pico Agilent RNA 6000 kit (Agilent Technologies,
Santa Clara, CA, USA) according to the manufacturer’s instructions. rRNA depletion was performed using a
poly(A) magnetic bead capture protocol and a TrueSeq Stranded Total RNA Sample Prep kit (Illumina) according
to the manufacturer´s instructions. Libraries were prepared using a TrueSeq Stranded RNA-seq Library Prep Kit
(Illumina), according to the manufacturer’s instructions.
RNA-seq and data analysis. Paired end reads (100 bp) were obtained using an Illumina NovaSeq. 6000
platform at Macrogen Inc. (Seoul, South Korea). Quality control was performed on the sequenced raw reads
based on the read quality, total bases, total reads, GC content (%) and basic statistics. e quality of the reads
was analyzed using FastQC according to the Phred quality score92. Reads with Phred quality scores lower than
20 were discarded. To reduce bias in the analysis and artifacts, such as low-quality reads and adaptor sequences,
Trimmomatic was used93. e trimmed reads were mapped to the reference genome L. mexicana reference
genome (MHOMGT2001U1103) with genomic data obtained from TriTrypDB version 36 (www.tritryp.org) and
to the M. musculus genome using the TopHat splice-aware aligner94,95. A maximum of two mismatches were
allowed. e transcripts were assembled in Cuinks through read alignment, providing information on the
known transcripts. e expression proles of the assembled transcripts and the abundance estimates for each
sample were generated by Cuinks96. e expression values were calculated as fragments per kilobase of tran-
script per million mapped reads (FPKM) and are represented as normalized values based on the transcript length
and coverage depth97. Gene expression level values were calculated from the transcript counts. DEG analysis was
performed for the following comparisons: (1) C57BL/6 vs. BALB/c, (2) BALB/c infected with L. amazonensis vs.
BALB/c, (3) C57BL/6 infected with L. amazonensis vs. C57BL/6, and (4) C57BL/6 infected with L. amazonensis
vs. BALB/c infected with L. amazonensis. Genes with FPKM values of zero were excluded. Groups under dierent
conditions or with dierent DEGs were ltered out through statistical hypothesis tests. e false discovery rate
(FDR) was controlled by adjusting the p-value using the Benjamini-Hochberg algorithm98. Functional annota-
tion was performed using GO and KEGG analyses. All analyses were performed by Macrogen Inc. (Seoul, South
Korea).
RT-qPCR validation. RT-qPCR validation assays were performed using total RNA isolated as previ-
ously described above from ve biological replicates. Reverse transcription was performed using 2 µg of total
RNA as a template, reverse transcriptase and random primers (RevertAid H Minus Reverse Transcriptase Kit,
ermo-Scientic, Canada), according to the manufacturer’s instructions. Equal amounts of cDNA were assessed
in total volumes of 25 μL containing Maxima SYBR Green qPCR Master Mix (ermo Scientic, Lithuania, EU)
and primers (200 nM) (TableS4). e mixtures were incubated at 94 °C for 5 min, followed by 40 cycles at 94 °C
for 30 s, 60 °C for 30 s and 72 °C for 30 s. A negative control in the absence of reverse transcriptase was included
in the RT-qPCR assays to detect DNA contamination in the RNA samples. e reactions were carried out using
a PikoReal Real-time PCR System (ermo Scientic, Finland). e reactions were performed in duplicate, and
analyses were performed using PikoReal Soware 2.2 (ermo Scientic). e fold changes were calculated by
relative quantication using the ΔΔCt method99. e data were normalized by Gapdh expression, and the relative
gene expression was set to 1 for the control (non-infected) samples. e normalized absolute copy number of the
amastin-like gene (LmxM.33.0960) was calculated based on the normalization to a reference, considering the
molar mass concentration, according to a standard curve generated from a ten-fold dilution of a quantied PCR
product. e normalized Amastin/Gapdh ratio of the absolute number of molecules was used as an expression
parameter according to a standard curve generated from a ten-fold serial dilution of a quantied and linearized
plasmid containing the target fragment.
Statistical analysis. e experiments were performed with ve biological replicates per group and the
results are presented as the means ± SDs. DEGs were considered statistically significant considering fold
changes ≥ 2, p-value < 0.05 and FDR analysis. RT-qPCR validation assays were performed with ve biological
replicates, and the results are presented the means ± SDs. Statistical analysis was based on Student´s t-test with
p-value < 0.05 indicating statistical signicance.
Ethics statement. e experimental protocols for animals were approved by the Animal Care and Use Committee
at the Institute of Bioscience of the University of São Paulo (CEUA 233/2015). is study was carried out in strict
accordance with the recommended guidelines and the policies for the care and use of laboratory animals of São Paulo
State (Lei Estadual 11.977, de 25/08/2005) and the Brazilian government (Lei Federal 11.794, de 08/10/2008).
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Received: 1 March 2019; Accepted: 10 December 2019;
Published online: 27 December 2019
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Acknowledgements
We would like to thank Juliane Cristina Ribeiro Fernandes and Stephanie Maia Acuña for their comments and
suggestions.
Author contributions
Conceived and designed the experiments: J.I.A., S.M.M., L.M.F.W. Performed the experiments: J.I.A., S.M.M.,
R.A.Z. Analyzed the data: J.I.A., S.M.M., L.M.F.W. Contributed reagents/materials/analysis tools: J.I.A., K.E.M.,
A.H.N., L.M.F.W. Wrote the dra of the manuscript: J.I.A., S.M.M. and L.M.F.W. Revised the manuscript: J.I.A.,
S.M.M., R.A.Z., K.E.M., A.H.N., L.M.F.W.
Competing interests
e authors declare no competing interests.
Additional information
Supplementary information is available for this paper at https://doi.org/10.1038/s41598-019-56305-1.
Correspondence and requests for materials should be addressed to J.I.A. or L.M.F.-W.
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