1. Introduction
Tuberculosis (TB) is a chronic infectious disease caused by
Mycobacterium tuberculosis (Mtb), a bacterium that killed almost 70% of infected patients in the predrug era [
1]. Nearly 25% of the global population is infected by Mtb, and during 2019, the incidence of TB was estimated at 10 million patients, and more than 1.2 million deaths were directly caused by TB [
2]. The only currently approved vaccine for TB prevention is the attenuated form of
Mycobacterium bovis, the bacillus Calmette-Guérin (BCG). This vaccine provides approximately 80% protection against the meningeal and disseminated TB forms, but the protective effects of the vaccine against pulmonary TB in infants or pulmonary TB reactivation in adults remain controversial [
3,
4]. Although significant progress has been made toward understanding the adaptive immune response induced by varying different strains of the BCG vaccine [
5,
6], evidence regarding the innate response is lacking.
Mtb is an intracellular bacterium that is phagocytosed by the alveolar macrophage. Once internalized, the bacterium creates a niche that inhibits its degradation to allow its survival, growth and replication [
7]. The BCG vaccine requires a bacterial attenuation process to reduce
Mycobacterium virulence [
8]. However, this approach is also related to mutations that can decrease the immune system stimulation and shorten the period of protection [
9,
10]. Due to genomic heterogeneity among BCG strains, the correlation between phenotypic characteristics and the conferred immune protection level is complicated, and the ability of BCG to induce an adaptive immune response is not necessarily linked to its protective efficacy [
11,
12]. The development of an improved vaccine requires increased knowledge regarding the characteristics of the innate immune response stimulated by the BCG vaccine. During the first critical phase of human infection with BCG, the internalization of the bacteria into macrophages occurs, and the cascade of innate immune responses that follow must be more clearly described to provide better options for the vaccine development process.
The RNA microarray technology is an approach that has been used to study biological functions and pathways at the transcriptional level, probing RNA with target molecules to analyze the relative gene expression in the sample of interest [
13,
14]. Due to the complexity of crosstalk and interactions that occur between the BCG bacteria and the host macrophage [
15], the global evaluation of the macrophage response using RNA microarrays would facilitate an in-depth description of early innate immune responses generated by macrophages in response to the infection. Monocyte-derived macrophages differentiate into specific phenotypes, driven by key cytokines in the microenvironment and receptor-level interactions [
16]. One factor that affects this process is the Toll-like receptor (TLR) family, which activates multiple signaling cascades and plays fundamental roles in the host defense mechanisms by inducing the expression of inflammatory molecules, including tumor necrosis factor (TNF)-α, the proinflammatory cytokine interleukin (IL)-12 and nitric oxide (NO), which contribute to pathogen destruction [
17,
18].
Previous work by our group using a mouse model of progressive pulmonary tuberculosis induced by the MtbH37Rv strain showed differences in protection associated with different strains of the BCG vaccines. The BCG Phipps (P.BCG) strain provided the greatest protection, whereas the BCG Mexico (M.BCG) strain induced a moderate immune response [
19]. In this study, we aimed to study the transcriptional responses induced in a human macrophage derivate from monocytes of the THP-1 cell line. The usefulness of this cell line to test immune modulation [
20] and specifically BCG responses [
21,
22], following infection with either P.BCG or M.BCG, has been previously reported, We briefly performed a characterization of the innate immune responses in vitro at different hours and selected 24 h to evaluate with RNA expression microarrays the differentially expressed genes (DEGs) in infected macrophages with each BCG strain. Finally, both functional and pathway enrichment analyses were performed to describe the innate immune responses induced by BCG-infected macrophages.
3. Discussion
The innate immune response is critical for protection against infections and is involved in the protective response triggered by vaccines. The BCG vaccine offers 50% protection against pulmonary tuberculosis. Several explanations may exist for this phenomenon. One possibility is the different compositions of the cell walls in each BCG strain [
23,
24,
25], which can affect their capacities to be phagocytosed by macrophages, hampering bacterial pathogenesis [
26,
27,
28].
In this study, the initial characterization of the immune response induced by the macrophage challenged with the strains M. BCG and P. BCG yielded results that were consistent with previous reports. The THP-1 cell line is an alternative study model that serves as a support to understand various cellular responses without assuming that the results are the same as those of macrophages obtained live from patients [
20]. The spectrophotometric absorbance values observed for each strain over time, which were used to estimate the log phase for maximal growth, were similar to those reported by other authors examining different BCG strains [
29,
30]. The differential amount of intracellular bacteria we found over time could be associated with the phenotypic characteristics of each strain and could explain both the phagocytosis process and the immune response [
23,
24,
25,
31]. Indeed, BCG Phipps possesses an 86-carbons methoxymycolic acid, which is longer that that found in BCG Mexico of 84-carbons [
23]. Although the presence of this acid could be related to the differential recognition of BCG Phipps, additional studies to decipher the implicated structures in the response are needed. Additionally, the sequencing of the BCG Mexico genome has revealed the existence of specific polymorphisms for this particular strain, such as in the RDMex02 region where a deletion of 218 amino acids of the
fadD23 gen has been reported, altering a preserved region of the protein that includes two transmembranal domains [
31]. Since this gene codifies for a probable fatty acid acyl-CoA ligase involved in the lipid degradation and in the production of sulpholipids, its disruption could increase the association of the BCG strain and the infected macrophage.
Infection with either M.BCG or P.BCG stimulates the expression of the proinflammatory molecule NF-κB in the host cell [
23], indicating the promotion of effector molecules as a response to infection. In agreement with our previous in vivo report in mice, infection with the P.BCG strain was associated with reduced IL-10 expression [
19]. In addition, the upregulation of both IL-12 and TNF-α expression has been previously described for human monocyte-derived macrophages stimulated with the BCG Tokyo strain for up to 24 h [
32]. Our results showed that the concentration of NO induced by M.BCG infection for 24 h did not increase when compared with that induced by P.BCG infection. Hayashi et al. showed that in both A549 human cells of alveolar epithelial origin and in mice bone marrow cells, NO production increased after the cells were incubated with P.BCG [
23]. Although their quantifications were performed 48 h after the challenge, the NO concentrations reported by the previous study were similar to those observed in our study at 24 h following infection. Thus, after observing similar and expected results with each strain relative to the previously reported results, we pursued a transcriptional analysis of the infected macrophages.
To our knowledge, this is the first study comparing the responses of macrophages infected with two different BCG strains at the transcriptional level. We analyzed the transcriptional signatures of macrophages infected with M.BCG and P.BCG and analyzed the results using the enrichment analysis tools GSEA, Database for Annotation, Visualization, and Integrated Discovery (DAVID) and IPA. GSEA produced a set of five consistently enriched functions induced by infections with both strains: viral response, viral defense, cytokine-mediated signaling pathway, cellular response to IFN-γ and response to type I interferon. The DAVID analysis identified three functional categories for both strains: the TNF signaling pathway, the NF-κB signaling pathway and the chemokine signaling pathway. DAVID also identified the functional pathway of cytokine–cytokine receptor interaction in M.BCG infection, whereas the P.BCG infection included the NOD-like receptor signaling pathway and the Toll-like receptor (TLR) signaling pathway. In 2015, Rienksma et al. reported that after 24 h of infection with the Danish BCG SSI 1331 strain, THP-1 cells were enriched in multiple pathways associated with the innate immune responses, with the three most upregulated pathways including those associated with IFN-α/β signaling, IFN-γ signaling, and the retinoic acid-inducible gene I (RIG-I)- melanoma differentiation-associated protein five (MDA5)-mediated induction of the IFN-α/β pathways [
33]. An additional report indicated that 4 h of infection in THP-1 cells was sufficient to stimulate the expression of multiple miRNAs related to the proinflammatory response, including miR-146a [
34]. The miR-146a is quickly activated in human monocytes to target the TNF receptor-associated factor six (TRAF6), which is a strong modulator of the TLR activity within the innate immune response [
35]. In accordance with previous studies, in our work, both the M.BCG and P.BCG strains induced the expression of genes associated with the interferon and TNF signaling pathways in THP-1 cells. The similar patterns of innate immune response-associated gene expression induced by both strains suggested that their behaviors were consistent with our previous findings, in which we compared the effectiveness of 10 BCG strains in a mouse model of pulmonary tuberculosis. In that study, BALB/c mice were subcutaneously vaccinated and 2 months later challenged with the
Mycobacterium tuberculosis H37Rv strain by intratracheal injection. After 2 and 4 months, a delayed-type hypersensitivity (DTH) response, the degree of pneumonia-affected lung tissue, CFU, T cell count, and cytokine expression (IL-2, IL-4, IL-10, and IFN-γ) were determined. Differential protective effects across the diverse BCG strains were found with P.BCG resulting in the largest and most persistent reduction in CFU counts and pneumonia at both 2 and 4 months after challenge. This protection was accompanied by a reduction in IL-10-producing T cells. Contemporary BCG strains, which are characterized by the presence of a mutated or upregulated
inhA gene that confers resistance against ethionamide and isoniazid, induced a wide range of protective effects in this animal model [
19].
As an approach to integrate the previous results, we conducted an IPA evaluation. IPA has previously shown its capacity to identify innate immune signaling pathways in macrophages stimulated with mycobacteria [
36] and those that involve pattern-recognizing molecular components [
37]. The IPA analysis showed similar biological interactions induced by M.BCG and P.BCG. The DEGs in both groups were categorized into four networks: antimicrobial response, inflammatory response and disease, dermatological diseases and conditions and connective tissue disorders. M.BCG stimulated the upregulation of
CXCL1. CXCL1 recruits and activates neutrophils, is associated with protection in
H. pylori and meningitis infections and is involved in the signaling pathways of G protein-coupled receptors [
38]. The P.BCG infection stimulated the upregulation of
OAS2, which is related to the INF-γ and NOD2 signaling pathways [
39], and which is associated with restriction of the replication of intracellular mycobacteria and promotion of cytokine secretion [
40]. We observed the downregulation of 10 genes by M.BCG only (
SUCNR1,
CYSLTR1,
TREM2,
HEY2,
CD109,
NRGN,
DTL,
VAT1L,
CD180 and
CDC20), which among other pathways, are associated with Notch signaling, succinate recognition, Th1/Th2 balance and anti-inflammatory responses. Their downregulation could imply reversion of the Th1/Th2 imbalance related with tuberculosis progression [
41], prevention of anti-inflammatory responses in macrophages [
42,
43] and promotion of TLR activity [
44]. When the IPA analysis was performed to compare gene expression in response to M.BCG relative to the response to P.BCG, we found that the only upregulated gene in M.BCG was
MPHOSPH8, which encodes a protein component of heterochromatin and whose function is related to epigenetic repression and to TNF response in monocytes [
45]. Three additional genes were downregulated in M.BCG relative to P.BCG (
MIR31HG,
SAA1 and
TRIML2).
MIR31HG is a long-noncoding RNA associated with hypoxia that forms a complex with hypoxia-inducible factor-1A [
46].
SAA1 encodes a member of the serum amyloid A family that is a major acute-phase protein and is highly expressed in response to inflammation and tissue injury [
47].
TRIML2 encodes a protein that increases the transactivation of a subset of p53 target genes associated with prolonged DNA damage and apoptosis [
48]. The expression of these genes by M.BCG leads us to theorize that M.BCG promotes macrophage proliferation by decreasing hypoxia and apoptosis.
Very recently, it has been reported in vitro assays with infected monocytes that the expression of lncRNAs is BCG strain-dependent. In such case, these molecules could play an important role in the pathogenesis of tuberculosis and could be used as potential biomarkers for this disease, as well as therapeutic targets [
49]. More specifically, the dysregulation of the lncRNA MIR31HG has been described in immune-altered environments such as cancer, modifying the cell survival by downregulating the expression of components of the Epidermal Growth Factor Receptor [
50]. In rheumatoid arthritis, it downregulates the PI
3K/AKT pathway to modulate the proinflammatory responses of associated macrophages, altering the production of IL-6, IL-8 and TNF-α [
51]. Additionally, MIR31HG has been described as a regulator of the components of the senescence-associated secretory phenotype (SASP) through the modulation of IL-1A translation in BRAF-induced senescent cells. In fact, when
MIR31HG is depleted, the cells fail to produce the innate immune mediators IL-6 and CXCL1 and are unable to migrate in transwell assays [
52]. The phenomenon of senescence has been related to oncogenic transformation, and it is not surprising that high expression of MIR31HG is linked to enrichment in TNF and type-I interferon [
53]. In THP-1 cells, the presence of exogenous pathogen-associated molecular patterns (PAMPs) engages the DNA sensor cyclic GMP-AMP synthase, which then enhances type-I interferon responses [
54]. Among other targets, type-I interferon promotes the tumor suppressor TRIML2, which also elicits antiviral and antibacterial activities [
55]; it participates in the correct development of macrophages and in the expression of nitric oxide and of the major histocompatibility complex II to present antigens [
56]. An additional type-I interferon target is MPHOSPH8 [
57], which belongs to the Human Silencing Hub (HUSH) complex, and it regulates the chromatin structure. In lung carcinoma mice models, it has been reported that low expression levels of MPHOSPH8 are linked to sensitization to anti-PD-1/CTLA-4 therapies [
58], implying a feasible association of this epigenetic regulator and the suppression of the immune evasion. To our knowledge, our use of a THP-1 model infected with either P.BCG or M.BCG marks the first time that a differential expression in
MIR31HG,
TRIML2 and
MPHOSPH8, three genes which, as indicated above, act as immune modulators, and could explain the production of cytokines and the cellular activation has been reported. Regarding SAA1, stimulated THP-1 cells have proven to increase the expression of
SAA1 [
59], and the high expression of
SAA1 in activated human monocytes has been associated with upregulation in
IL1A,
IL1B and
IL6 [
60]. Therefore, the modulation of
MIR31HG,
SAA1 and
TRIML2 could be linked to the M2 polarization seen in the infected macrophages with the Mexico strain.
Taken together, these data open the possibility of a regulatory network involving type-I interferon and the four reported genes in THP-1-infected cells. Surprisingly, in the microarray data obtained in the comparative M.BCG vs. P.BCG, we did not identify differentially expressed genes such as
TNF,
IL10 and
IL12, as well as genes involved in pathways associated with nitric oxide. A plausible explanation for this result could be transcript buffering, which secures an adjustment in mRNA synthesis and degradation to ensure a balance in total cellular mRNA depots [
61]. Since close to half of all the protein concentration variation is regulated at the translational level [
62], and because the translation of
TNF,
IL10 and
IL12 are modulated by DEAD-box helicases such as eIF4A in monocytes [
63], this statement is possible. However, to correctly identify alterations in translational regulation, further experiments such as polysome profiling are required to explore mRNA efficiently bound to ribosomes. With our current results, we could hypothesize that the reported DEGs, therefore, suggest fine physiological changes in the infected macrophages. It is possible that the DEGs we found could be related to senescence, like
MIR31HG, which could be determinant for the survival of the macrophage and the bacteria, and for the adaptive response as well. Overall, the differential expression of
MPHOSPH8,
MIR31HG,
SAA1 and
TRIML2 could show us the subtle changes that occur in the infection between M.BCG and P.BCG. We also identified the stimulated expression of TLR members, of NOD, of TNF, of chemokines, of cytokines and of type I interferons, which, together with the activation of NF-κB, indicate an inflammatory environment.
In conclusion, our data suggested that both strains stimulated a proinflammatory response at the levels of cytokines and transcripts. It should be noted that the inflammatory response of M. BCG was observed more pronounced compared to P. BCG at 24 hours of analysis. These data seem to indicate that M. BCG takes greater control of the macrophage response since it responds with greater intensity to the infection. On the other hand, P. BCG appears to be controlled from the beginning of the infection, secondary to the upregulation of the OAS2 gene that controls intracellular replication. The changes observed at this time may vary with a longer time of infection of the macrophage with BCG strains, secondary to the plasticity and reversibility of the macrophage’s polarization capacity. However, longer time analyzes are required, as well as the verification that changes at the gene level translate into changes in protein expression.
4. Materials and Methods
4.1. BCG Strains
Marcel Behr from the McGill International Tuberculosis Centre (Montréal, QC, Canada) kindly donated the BCG Phipps strain. The BCG Mexico strain was obtained from the Ministry of Health (México).
4.2. Bacterial Growth Curve
The BCG strains were grown separately in Middlebrook medium (Difco Laboratories, Detroit, MI, USA) supplemented with 10% ADC (5% bovine serum albumin [fraction V], 2% dextrose, and 0.005% catalase) and 0.05% Tween 80 and were incubated under conditions of constant agitation at 37°C with 5% CO2. Optical density was measured every 24 h with a Magellan spectrophotometer (TECAN GENios Plus, Grödig, Austria) until the bacterial concentration reached 1 × 108 bacteria/mL.
4.3. Bacterial Cultures
BCG strains were grown as described for the bacterial growth curve experiments. When the bacteria reached a concentration of 1 × 108 bacteria/mL, the CFU was determined. Bacteria were stored in aliquots of 1 × 107 bacteria/mL at −70 °C until use. The viability of each BCG strain was determined by measuring the bacterial ATP content using an ATP Kit SL Luminescent Assay (BioThema AB, Handen, Sweden), and the determination of CFU was performed after 3 weeks of growth on incubation plates consisting of Middlebrook 7H10 agar (Difco Laboratories, Detroit, MI, USA) supplemented with 10% OADC (oleic acid-albumin-dextrose-catalase acid) (Sigma–Aldrich; Merck Millipore, Darmstadt, Germany).
4.4. Human Cell Line
The THP-1 cell line (ATCC, TIB-202 (Thermo Fisher Scientific Inc, MA, USA) of human leukemia monocyte origin was maintained in RPMI-1640 medium (Sigma–Aldrich; Merck Millipore, Darmstadt, Germany) supplemented with 10% fetal bovine serum (Sigma–Aldrich; Merck Millipore, Darmstadt, Germany) at 37 °C and 5% CO
2. After reaching confluence of 1 × 10
6 THP-1 cells/well in 12-well plates, monocytes were stimulated using 50 ng/mL of Phorbol 12-myristate 13-acetate (PMA) (Sigma–Aldrich; Merck Millipore, Darmstadt, Germany) for 48 h [
64]. Later, macrophages were cultivated in medium Differentiation into M1 or M2 phenotypes was performed in noninfected macrophages, as previously described [
65]. Briefly, macrophages were incubated for 24 h with 20 ng/mL of human IFN-γ (PeproTech, NJ, USA) plus 100 ng/mL LPS (Sigma–Aldrich; Merck Millipore, Darmstadt, Germany), or with 20 ng/mL of human IL-4 plus 20 ng/mL of human IL-13 (both from PeproTech, NJ, USA), to polarize into M1 or M2 phenotypes, respectively. The polarization of macrophages was confirmed by flow cytometry. Briefly, cells were incubated for 24 h as explained before, and the concentrations of IFN-γ, TNF-α, IL-1β and IL-10 were measured in a flow cytometer, testing either supernatants from nontreated THP-1 cells (monocytes) or from each one of the polarized macrophages following the manufacturer’s instructions (Milliplex Map Human Human Cytokine/Chemokine Magnetic Bead Panel; Millipore) and Veinalde R. et al. [
66] (
Figure S1).
4.5. Macrophage Infection with the BCG Strains
The bacterial culture was resuspended, and macrophages were infected at a 1:10 ratio (1 × 10
6 THP-1 cells with 1 × 10
7 bacteria) with each BCG strain in 12 well-plates. At 3 h postchallenge (time 0), macrophages were washed, and nonphagocytosed bacteria were removed by incubation with 200 µg/mL amikacin for 2 h, which represents a previously reported bactericidal concentration [
67]. Macrophages at 3 h, 24 h and 72 h postchallenge were lysed with a lytic solution (0.15 M NaCl, 0.0013 M EDTA, 0.05 M Tris, 0.5% Triton X-100, 0.5% SDS), and the number of intracellular bacteria was calculated by quantifying bacterial ATP contents using the ATP SL Luminescent Assay Kit (BioThema AB, Handen, Sweden ) at 560 nm in the Magellan spectrophotometer. Quantitative culture to determine bacterial numbers was performed using 10-fold serial dilutions on Middlebrook 7H10 agar plates supplemented with 10% OADC.
4.6. Nitrite Quantification
NO secreted into the supernatant by infected THP-1-derived macrophages was evaluated at times 0 (3 h postchallenge), 24 h and 72h postchallenge with the Measure-iT Nitrite Assay Kit (Molecular Probes), according to the manufacturer’s instructions. NaNO2, at 200 µM/100 µL, was used as a control. Fluorescence was measured at 360/430 nm in a Magellan spectrophotometer.
4.7. Cytokine Quantification
IL-10, IL-12 and TNF-α were measured in the supernatant of THP-1-derived macrophages 24 h and 72 h after infection with the BCG strains. Noninfected macrophages were used as controls for comparison. The concentration of each cytokine was quantified by enzyme-linked immunosorbent assay (ELISA) using commercial sandwich assays and performed according to the manufacturer’s instructions (DuoSet ELISA Development System (R&D Systems, Minneapolis, MN, USA)).
4.8. Immunophenotype of the Infected Macrophages
Noninfected M0, M1 and M2 macrophages and infected macrophages by either the BCG Mexico or BCG Phipps strains were tested in order to identify the immune phenotype induced by each strain. Briefly, 1 × 10
6 noninfected M0, M1 or M2 macrophages were collected after the cytokine stimulation, as described in
Section 4.4; for infected macrophages, 1 × 10
6 THP-1 cells were infected with 1 × 10
7 bacteria, as described in
Section 4.5. Next, macrophages were collected, and the CD11b
+/CD14 (BioLegend, San Diego, CA, USA) cellular population was selected using the flow cytometer Attune Acoustic Focusing Cytometer (Life Technologies, Carlsbad, CA, USA). The surface markers CD16, CD80, CD206 and CD209 (BioLegend, CA, USA) [
68,
69,
70] were tested on this population using the fluorochromes indicated in
Table 6 to identify the immunophenotype of the macrophages. The resulting data was analyzed with FlowJo v10, and the expression data was normalized versus M0 macrophages.
4.9. RNA Isolation from Macrophages, Evaluation of RNA Integrity, and Microarray Assay
THP-1-derived macrophages were infected with either M.BCG or P.BCG at a 1:10 ratio, using noninfected macrophages as a negative control. After 24 h, macrophages were homogenized, and total RNA was recovered using the TRIzol reagent (Sigma–Aldrich; Merck Millipore, Darmstadt, Germany), following the manufacturer’s instructions. The RNA concentration and purity were determined using a NanoDrop 1000 (Thermo Scientific, Waltham, MA, USA). RNA integrity was evaluated by electrophoresis using 1% agarose gels embedded in TE buffer (100 V, 25 min) (High-Performance UV Transilluminator, UVP). A Eukaryote Total RNA Nano Chip (Agilent Technologies, Palo Alto, CA, USA) was used, following the manufacturer’s instructions. The chips were read with an Agilent 2100 Bioanalyzer (Agilent Technologies, Palo Alto, CA, USA ), and an RNA integrity number (RIN) value with a mean of 8 was accepted. RNA aliquots (20 μL/each) were evaluated with expression microarrays in the Genotyping and Expression Analysis Unit (INMEGEN, UNAM), using the Gene Chip®Human Gene 1.0ST Array (Affymetrix, Santa Clara, CA, USA).
4.10. Microarray Gene Expression Analysis
Samples were classified into three groups: (1) BCG Mexico-infected macrophages (M.BCG), (2) BCG Phipps-infected macrophages (P.BCG) and (3) noninfected macrophages as a control (Ctrl). All possible pairwise comparisons between the three groups generated three contrasts of interest: M.BCG vs. Ctrl, P.BCG vs. Ctrl and M.BCG vs. P.BCG. We performed a low-level data analysis in which the raw microarray data were background-corrected using the Robust Multi-array Average method and normalized using the quantile normalization approach [
71,
72], which were both executed in R, V3.1.3 (
http://www.cran.r-project.org, accessed on 4 March 2022). DEGs were determined by fitting a linear model to each gene using the Limma package with an empirical Bayesian approach [
73,
74]. The correction for multiple hypotheses was applied by controlling the FDR. Genes were selected as differentially expressed based on |log fold-change| ≥ 0.3, and significance was determined based on a B-statistic ≥ 0 with associated FDR adjusted
p-values ≤ 0.01. The expression matrix created was employed for enrichment analyses and the selection of DEGs. Three tools were used to evaluate functional properties and perform pathway analyses for the DEGs. We used gene annotation enrichment analysis within the set of significant genes, employing the DAVID bioinformatics tool, V6.7 (
http://david.abcc.ncefcrf.gov/, accessed on 4 March 2022) [
75,
76]. Enrichment analysis was also conducted using the IPA platform Ingenuity, v.26127183 (Redwood City, CA, USA), and the Gene Set Enrichment Analysis software tool (GSEA) of the Broad Institute of Harvard and M.I.T. [
77,
78].
4.11. Statistical Analysis
All experiments were performed in three independent replicates. The counts of intracellular bacteria, as well as the measurements of nitrites, cytokines and surface markers of infected macrophages were analyzed using a two-way analysis of variance (ANOVA) with Tukey’s correction. Data are presented as the mean and standard deviation. All statistical analyses were conducted using GraphPad Prism Software, v9.0. A p-value ≤ 0.05 was considered statistically significant.