Epigenetic Crosstalk Between BCG-Infected Macrophages and Naïve Monocytes Potentiates Antimycobacterial Activity

Extracellular vesicles, BCG, Mycobacterium tuberculosis, host immunity, 21 macrophages, epigenetic reprogramming, trained immunity 22 .CC-BY-NC 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted January 12, 2026. ; https://doi.org/10.64898/2026.01.12.698601doi: bioRxiv preprint 2

23 Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), remains a leading 24 cause of death from infectious disease. Infected cells secrete extracellular vesicles 25 (EVs), nanosized membrane-bound particles containing bioactive molecules known to 26 mediate intercellular communication and influence immune regulation during infection. 27 We hypothesized that EVs secreted from Mycobacterium bovis Bacillus Calmette 28 Guérin (BCG)-infected macrophages could epigenetically reprogram naïve monocytes 29 and enhance their mycobactericidal activity against Mtb. A transwell co-culture system 30 was used to enable communication via EVs and soluble factors, between BCG-31 infected macrophages and naïve monocytes (recipient macrophages). To assess the 32 impact of these factors, we examined epigenetic reprogramming and the ability to 33 control Mtb growth. BCG-infected macrophages released EVs with a distinct proteomic 34 profile mapping to multiple tuberculosis-related pathways. Recipient macrophages 35 exhibited altered DNA methylation patterns compared to those co-cultured with 36 untreated, Staphylococcus aureus -infected or hydrogen peroxide-exposed 37 macrophages. The proteomic cargo of EVs and differentially methylated genes in 38 recipient cells showed significant interactions with TNF as a central hub enriched in 39 both the phagosome and tuberculosis pathway. The epigenetic reprogramming was 40 accompanied by a trend towards improved control of Mtb in vitro . BCG infection 41 induces release of EVs that, together with soluble factors, induce targeted epigenetic 42 remodeling in recipient macrophages. 43 Words abstract: 199 44 Words manuscript: 3451 45 .CC-BY-NC 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted January 12, 2026. ; https://doi.org/10.64898/2026.01.12.698601doi: bioRxiv preprint 3

46 Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), has remained the 47 leading cause of death from a single infectious agent for most of the past decade. Its 48 global mortality burden is of the same order of magnitude as that of COVID-19 during 49 the peak years of the pandemic (2020–2022), when COVID-19 temporarily surpassed 50 TB as the foremost cause of infectious mortality. Tuberculosis primarily affects the 51 lungs and is transmitted via aerosols released when infected individuals cough or 52 sneeze. The immune responses to Mtb are highly heterogenous; although 53 approximately 25% of the global population is estimated to be infected, the majority 54 will never develop disease [1]. TB represents a spectrum ranging from exposure and 55 bacterial clearance to latent infection, subclinical disease, and ultimately active TB [2]. 56 Recent studies suggest that part of this heterogeneity may be attributed to differences 57 in trained immunity. Trained immunity is a form of innate immune memory where cells 58 are epigenetically reprogrammed after an initial microbial exposure, such as the 59 Bacillus Calmette-Guérin (BCG) vaccination, resulting in a long-lasting enhanced 60 capacity to respond to subsequent infections [3]. How these signals are transmitted 61 between cells is unclear, but one potential mediator is extracellular vesicles (EVs). EVs 62 are small lipid bilayer particles that are released by nearly all cell types and play a 63 crucial role in intercellular signalling by transferring nucleic acids, proteins and lipids 64 between cells [4]. They are secreted both under physiological and stressed conditions, 65 and their molecular cargo reflects the state of the sender cell and are capable of 66 inducing specific phenotypes in recipient cells [5, 6]. EVs can be categorized into 67 exosomes, microvesicles, and apoptotic bodies based on their biogenesis [7]. 68 However, the origin of isolated EVs is hard to determine and the most recent 69 MISEV2023 guidelines suggests two new categorize based on size instead of 70 .CC-BY-NC 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted January 12, 2026. ; https://doi.org/10.64898/2026.01.12.698601doi: bioRxiv preprint 4 biogenesis. Small EVs are 200 nm [7]. EVs are 71 increasingly recognized as potential mediators of epigenetic regulation through the 72 transfer of DNA methyltransferase (DNMT) transcripts, long non-coding RNAs 73 (lncRNAs), and microRNAs (miRNAs). These cargos are proposed to induce targeted, 74 stable changes in gene expression, thereby influencing the epigenetic landscape and 75 behaviour of the recipient cell [8]. Several studies have linked EV -associated mRNA, 76 miRNA and lncRNA to epigenetic modulation processes, reviewed in [9]. 77 Beyond their proposed role in epigenetic modulation, EVs have important 78 immunoregulatory functions. Subsequent studies revealed that EVs contribute to 79 antigen presentation through several mechanisms, including cross-dressing, whereby 80 EVs are taken up by or attached to dendritic cells (DCs), enabling the display of 81 transferred human leukocyte antigens (HLA) class II molecules on their surface [10, 82 11]. This mechanism is particularly important in contexts where macrophages (M Φ ) or 83 DCs are infected with intracellular pathogens, such as Mtb, and exhibit a reduced 84 capacity for canonical antigen presentation [12]. Beyond antigen presentation, EVs 85 also modulate innate immune responses during host-pathogen interactions. M Φ 86 infected with intracellular pathogens, such as Mtb, Mycobacterium bovis (Bacillus 87 Calmette-Guerin BCG) or Salmonella typhimurium, release EVs containing pathogen-88 associated molecular patterns (PAMPs), which activate toll-like receptors (TLRs) and 89 myeloid differentiation factor 88 (MyD88) signalling in recipient cells [13]. Through this 90 mechanism, EVs propagate immune signalling to distal sites, activating uninfected 91 immune cells [14]. EVs derived from Mtb- or BCG-infected M Φ (BCG-I M Φ ) carry 92 mycobacterial antigens such as lipoarabinomannan (LAM), early secreted antigenic 93 target 6 kDa (ESAT-6) and antigen 85 complex (Ag85), which can stimulate M Φ , DCs 94 and T cells in vivo [13, 15]. These vesicles also promote the production of pro-95 .CC-BY-NC 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted January 12, 2026. ; https://doi.org/10.64898/2026.01.12.698601doi: bioRxiv preprint 5 inflammatory cytokines and induction of autophagy, key components of host defence 96 [16-18]. However, Mtb is known to evade host immunity by subverting immune 97 regulatory pathways to prolong its intracellular survival. EV secretion appears to be 98 part of this strategy, EVs from Mtb-infected M Φ have been shown to suppress 99 interferon- γ (IFN- γ ) production and promote M Φ polarization towards anti-100 inflammatory phenotypes in distal cells [19, 20]. 101 In this study, we investigated the epigenetic basis of stable phenotypic reprogramming 102 in naïve monocytes. We hypothesized that EVs from BCG-I M Φ induce epigenetic 103 changes that alter recipient cell functions. To model this interaction, BCG-I M Φ were 104 co-cultured with naïve monocytes during differentiation to M Φ (recipient M Φ ) allowing 105 communication via soluble factors. Functional and epigenetic outcomes were then 106 assessed. Staphylococcus aureus (SA) was included as an infectious control, and 107 hydrogen peroxide (H2O2) served as a non-infectious stressor to determine the BCG-108 specificity of the observed effects. 109 110

111 Isolation and characterization of macrophage-released EVs 112 EVs released by primary human M Φ infected with BCG, SA, or exposed to H 2O2 were 113 isolated from culture supernatants. The EVs were characterized to confirm 114 morphology, size, particle number, and surface markers in alignment with the 115 MISEV2023 guidelines [7] (Supplementary Figure 1a-c). We observed that BCG-I M Φ 116 displayed enhanced release of EVs, accompanied by an altered surface marker 117 expression (Figure 1a-b). Nanoparticle tracking analysis (NTA) revealed a significant 118 .CC-BY-NC 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted January 12, 2026. ; https://doi.org/10.64898/2026.01.12.698601doi: bioRxiv preprint 6 increase of EVs in all treatments as compared to untreated cells with the strongest 119 enhancement in BCG-I M Φ (Figure 1a) (One-way ANOVA and Dunnett’s multiple 120 comparisons test (* P < 0.05, ** P < 0.01, *** P < 0.001)). The expression of 38 EV 121 surface markers was analyzed, showing treatment-dependent differences between 122 bacterial infections (BCG, SA) and oxidative stress by H2O2 (Supplementary Figure 2). 123 Markers related to innate immune activation and antigen presentation, including 124 CD11c, CD14, CD29, CD40, CD45, CD49e, CD86, and HLA class I, showed 125 significantly higher mean fold changes in BCG- and SA- infected compared to H 2O2-126 exposed MΦ , reflecting a distinct EV phenotype under oxidative stress rather than an 127 active infection (Figure 1b) (One-way ANOVA and Dunnett’s multiple comparisons test 128 (* P < 0.05, ** P < 0.01, *** P < 0.001)). 129 130 Proteomics investigation revealed distinct protein composition for the EV 131 released by BCG-infected macrophages 132 We used quantitative proteomics to identify the protein composition of the isolated 133 EVs. A total of 935, 351, 551, and 605 peptides were identified in the EV samples 134 from BCG-I MΦ , SA-infected-, H2O2-exposed- and untreated M Φ , respectively (Figure 135 2a). EVs from BCG-I M Φ the exhibited a substantial number of unique peptides, with 136 255 detected exclusively in this condition (Figure 2b). Gene set enrichment analysis of 137 the genes corresponding to unique proteins identified in EVs released from BCG-I M Φ 138 revealed an enrichment of immune-related pathways associated with intracellular 139 infections (Figure 2c). Notably, among the top enriched were the tuberculosis 140 pathway, phagosome maturation, endocytosis, Salmonella infection, and 141 .CC-BY-NC 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted January 12, 2026. ; https://doi.org/10.64898/2026.01.12.698601doi: bioRxiv preprint 7 Leishmaniasis (Figure 2c). Network visualization of these enriched pathways 142 demonstrated dense clusters of interconnected proteins, notably including HLA class II 143 molecules (HLA-DQA1 and HLA-DQB1), TLR2, mannose receptor C-type 1 (MRC1) 144 and tumor necrosis factor (TNF) (Figure 2d). In contrast, EVs from H /i2 O/i2 -exposed 145 and SA-infected M Φ contained only 4 and 7 unique proteins, respectively, while 50 146 unique proteins were identified in EVs from untreated controls (Figure 2b). 147 Corresponding pathway enrichment analyses revealed fewer and less pronounced 148 enrichments for these proteins (Supplementary Figure 3). 149 Co-culture with BCG-infected macrophages induce epigenetic reprogramming in 150 naïve monocytes 151 To assess whether EVs released by BCG-I MΦ can influence the epigenetic landscape 152 of naïve monocytes, we employed a transwell co-culture system. MΦ were exposed to 153 BCG, SA or H 2O2, then washed to remove stimuli. Naïve monocytes in the lower 154 chamber were co-cultured for seven days, allowing differentiation under the influence 155 of soluble factors and EVs. DNA methylation profiling of these BCG-induced EV 156 recipient M Φ revealed 1500 CpG sites linked to 253 unique differentially methylated 157 genes (DMGs) (|logFC| > 0.1, P < 0.05), many involved in immune regulation (Figure 158 3a). Pathway enrichment analyses of these differentially methylated genes revealed 159 enrichment in pathways related to Hippo signaling, EGFR tyrosine kinase inhibitor 160 resistance and fatty acid biosynthesis and Th1 and Th2 cell differentiation (Figure 3b) 161 (using nominal p-values ( P < 0.05). Among the top 30 enriched pathways, we also 162 identified enrichment in the tuberculosis pathway ( P < 0.024, gene count 6) 163 (Supplementary Table 1). Further network visualization of the top 15 enriched 164 pathways shows several interconnected genes and directionality of the methylation 165 .CC-BY-NC 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted January 12, 2026. ; https://doi.org/10.64898/2026.01.12.698601doi: bioRxiv preprint 8 pattern. Enrichment in Th1 and Th2 cell differentiation resulted from hypomethylation 166 in the interferon-γ receptor 1 (IFNGR1) and interleukin-2 receptor α-chain (IL2RA) and 167 hypermethylation in interleukin-12 receptor β2 (IL12RB2) and Janus kinase 1 (JAK1). 168 Furthermore, enrichment in C-type lectin receptor signaling pathway involved in Mtb 169 recognition was identified (Figure 3c). The enriched pathways associated with DNA 170 methylation changes in co-cultures with SA-infected and H 2O2-exposed cells are 171 shown in Supplementary Figure 4. 172 Proteins in EVs interact with epigenetically regulated genes in recipient 173 macrophages 174 To further explore the connection between the proteomic cargo of BCG-induced EVs 175 and the epigenetic remodeling observed in the recipient M Φ s, we performed a 176 STRING analysis using a high confidence interaction score (>700). This analysis 177 included 255 unique proteins identified in BCG-induced EVs and 253 unique DMGs 178 (mapped to proteins) identified in the recipient M Φ s, revealing a large interactome of 179 significant protein-protein interactions (Figure 4a). TNF protein from the EVs and the 180 DMGs CD44 and AKT1 from recipient M Φ s was shown to be a central hubs with 24, 181 34 and 24 connections, respectively. The DMG CD44 was hypomethylated (|logFC| -182 0.14) proposing increased expression of this glycoprotein in the recipient MΦ . Notably, 183 seven proteins found in EVs (ACSL1, ASAH1, CLCN7, F13A1, PDXK, PRKAR1A, 184 PRKCB, SLAMF8, TTYH2) were also DMGs in the recipient cells and four were 185 present in the interactome (Figure 4a). Further KEGG pathway enrichment analysis of 186 the high-confidence interactome showed significant overrepresentation of the 187 phagosome, Leishmaniasis and tuberculosis pathways (Figure 4b), supporting a 188 .CC-BY-NC 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted January 12, 2026. ; https://doi.org/10.64898/2026.01.12.698601doi: bioRxiv preprint 9 functional link between EV-derived proteins and epigenetic regulation in the context of 189 intracellular infections. 190 Recipient macrophages exhibit a tendency of enhanced control of Mtb infection 191 compared to controls 192 To evaluate whether epigenetic reprogramming translated to functional changes, we 193 assessed the ability of recipient M Φ to control Mtb infection using a transwell system. 194 After co-culture with BCG-I MΦ , SA-infected or H2O2-exposed MΦ , recipient MΦ were 195 infected with GFP-expressing Mtb. Across four independent donors, recipient M Φ co-196 cultured with BCG-I M Φ showed a consistent trend towards reduced bacterial load 197 over five days, with a tendency toward lower bacterial burden at day five ( P = 0.125, 198 Wilcoxon signed-rank test, Figure 5a-b). In contrast, cells co-cultured with SA -infected 199 or H/i2 O/i2 -exposed MΦ showed variable responses across donors with most displaying 200 increased bacterial loads at day 5 ( P = 0.250 and 0.375, respectively; Figure 5b and 201 growth over the five days is shown in Supplementary Figure 5). To assess whether the 202 observed effects were mediated by EVs, EVs were isolated from the conditioned 203 medium using ultracentrifugation, leaving other soluble factors intact. Recipient M Φ 204 cultured in EV-depleted media showed reduced bacterial clearance compared to those 205 exposed to EV-containing media (Wilcoxon signed-rank test, P = 0.125) (Figure 5c-d). 206 In contrast, EV-removal SA- or H2O2-conditioned medium had no effect on Mtb growth 207 (Supplementary Figure 6). These results suggest that BCG-I M Φ -released EVs 208 contributes to anti-mycobacterial activity and is dependent on co-stimulation by other 209 soluble factors. 210 211

212 .CC-BY-NC 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted January 12, 2026. ; https://doi.org/10.64898/2026.01.12.698601doi: bioRxiv preprint 10 Our study provides novel insights into the role of EVs as epigenetic modulators in the 213 context of mycobacterial infections. We show that BCG infection induces the release of 214 EVs with distinct surface marker profiles and a targeted proteomic cargo enriched in 215 tuberculosis-associated proteins. When naïve monocytes were exposed to EVs and 216 soluble factors derived from BCG-I M Φ , they underwent epigenetic remodeling in 217 genes associated with immune activation and tuberculosis, suggesting a targeted and 218 biologically meaningful reprogramming of recipient cells. 219 220 Proteomic analysis revealed a significant increase in EV secretion from BCG-infected 221 macrophages compared to those exposed to S. aureus, H2O2, or left untreated. These 222 EVs carried a unique set of proteins and showed marked differences in surface marker 223 expression. Among the identified proteins were HLA class II molecules (HLA-DQA1, 224 HLA-DQB1), several innate immune receptors including TLR2, MRC1, Fc ε receptor Ig 225 (FCER1G), Fc γ receptor Ia (FCGR1A), complement C3b/C4b receptor 1 (CR1) and 226 TNF, molecules known to participate in pathogen recognition, antigen presentation, 227 and inflammatory signaling. These proteins were enriched in pathways related to 228 phagosome maturation, leishmaniasis, and tuberculosis, supporting the established 229 role of EVs in immune activation. 230 231 Integration of EV proteomic and DNA methylation data revealed a strong interactome 232 linking EV-derived proteins to DMGs in recipient macrophages. Several hub nodes, 233 including TNF and CD44 occupied central positions bridging the two datasets. Immune 234 regulatory nodes such as TNF and IFNGR1 were positioned within major hubs. 235 Notably, the interactome was significantly enriched in the phagosome and tuberculosis 236 pathways, underscoring the functional relevance of these molecular interactions. TNF, 237 .CC-BY-NC 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted January 12, 2026. ; https://doi.org/10.64898/2026.01.12.698601doi: bioRxiv preprint 11 a key cytokine in tuberculosis, plays a central role in macrophage activation and 238 phagosome maturation. It enhances antimicrobial activity by modulating the 239 recruitment of Rab GTPases and other trafficking regulators, facilitating phagosome–240 lysosome fusion and pathogen degradation, key processes for antigen presentation 241 and activation of T cell immunity [21, 22]. CD44 has been identified as a receptor for 242 Mtb, along with upregulated expression in Mtb infection [23, 24]. Building on this, we 243 observed hypomethylation of CD44 in recipient M Φ co-cultured with BCG-I M Φ , 244 indicating increased expression of this receptor and a potential role in EV-mediated 245 priming. These findings suggest that EVs may actively shape the functional state of 246 recipient cells to promote effective immune responses. 247 248 These observations align with the concept of trained immunity, a hallmark of BCG 249 vaccination, which refers to the long-term enhancement of innate immune responses 250 through epigenetic and metabolic reprogramming [3, 25, 26]. We have previously 251 shown that this can be induced by stimuli such as β -glucans, leading to improved 252 control of Mtb [27]. Our current findings build on this concept by showing that EVs and 253 soluble mediators from BCG-I M Φ , can transmit epigenetic signals to uninfected 254 bystander cells. This supports a model in which trained immunity extends beyond the 255 initially stimulated population via EV-mediated intercellular communication. 256 257 To explore the epigenetic landscape of recipient MΦ , we performed a DNA methylation 258 analysis, which revealed enrichment in several immune-related and metabolic 259 pathways. We observed enrichment in fatty acid biosynthesis, consistent with the 260 metabolic reprogramming of activated M Φ [28]. Mtb exploits this shift by manipulating 261 hosts lipid metabolism, promoting the formation of lipid-laden foamy M Φ , and TB 262 .CC-BY-NC 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted January 12, 2026. ; https://doi.org/10.64898/2026.01.12.698601doi: bioRxiv preprint 12 patients display elevated glycerophospholipid levels [28-30]. Notably, we identified 263 enrichment in the Th1 and Th2 cell differentiation pathway. The differentiation on 264 naïve CD4+ T cells is crucial for mounting an efficient immune response against Mtb 265 [31]. Interestingly, this pathway enrichment was associated with hypomethylation in the 266 IL2RA gene, a known TNF-inducible gene that promote differentiation of T cells [32], 267 and hypermethylation of JAK1, a kinase activated by TNF-induced phosphorylation 268 [33, 34]. This finding suggests a mechanistic link between the TNF present in BCG-269 induced EVs and the epigenetically regulated immune responses in recipient M Φ . The 270 Hippo signaling pathway, known to enhance ROS production and neutrophil 271 recruitment [35-37], was among the top enriched. Additionally, we identified enrichment 272 in the EGFR tyrosine kinase inhibitor resistance pathway. In infected M Φ , EGFR 273 activation lead to STAT3 signaling which repress key antimicrobial responses including 274 nitric oxide synthesis and the expression of pro-inflammatory cytokines such as IL-6, 275 TNF-α , IFN-γ [38, 39]. Furthermore, genetic mutations increasing EGFR expression is 276 associated with increased susceptibility to TB [40, 41]. Notably, we observed 277 pronounced hypomethylation of the RBCK1 (also known as HOIL-1L) gene. Mtb 278 protein kinase PknG has recently been shown to phosphorylate RBCK1 to block 279 NLRP3 inflammasome assembly [42]. Together, these findings suggest that EV-280 mediated epigenetic remodeling affects key pathways involved in host defense, 281 including phagosome maturation, metabolic adaptation, and cytokine regulation. 282 283 To assess the functional relevance of these epigenetic changes, we challenged 284 recipient M Φ with Mtb. Cells exposed to soluble factors, including EVs, from BCG-I 285 MΦ showed a consistent trend toward enhanced bacterial control. Although not 286 statistically significant, this trend aligns with previous studies linking metabolic and 287 .CC-BY-NC 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted January 12, 2026. ; https://doi.org/10.64898/2026.01.12.698601doi: bioRxiv preprint 13 epigenetic reprogramming to improved antimicrobial activity. When EVs were depleted 288 from the conditioned media, this effect was diminished, suggesting that both EVs and 289 other soluble factors are required for full reprogramming. This is consistent with 290 findings by Cheng et al., who reported that EVs from Mtb-infected M Φ enhanced 291 bacterial clearance only in the presence of IFN- γ [17]. These results support the idea 292 that EVs act as messengers of trained immunity, priming neighboring or newly 293 recruited monocytes for enhanced antimicrobial readiness even before direct pathogen 294 contact. Moreover, recent studies have identified the bone marrow as a central site for 295 the induction of trained immunity via epigenetic reprogramming of hematopoietic stem 296 and progenitor cells (HSPCs) [43, 44]. Our results raise the possibility that EVs 297 contribute to this systemic process by delivering immunomodulatory signals to distant 298 compartments such as the bone marrow. 299 300 In summary, our study shows that BCG infection triggers the release of EVs with 301 distinct surface markers and a proteomic cargo enriched in tuberculosis-associated 302 proteins. Exposure of recipient M Φ to these EVs and soluble factors leads to 303 epigenetic remodeling in genes related to immune activation and metabolic 304 reprogramming. Integration of proteomic and methylation data revealed a TNF-305 centered interactome enriched in the phagosome and tuberculosis pathways. These 306 findings suggest that EV uptake contributes to the establishment of trained immunity 307 by shaping the epigenetic landscape of recipient cells. 308 309 .CC-BY-NC 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted January 12, 2026. ; https://doi.org/10.64898/2026.01.12.698601doi: bioRxiv preprint 14

310 Study Design 311 This study investigated how BCG-I M Φ modulate healthy M Φ responses against Mtb, 312 focusing on the role of EVs released by infected MΦ . A transwell co-culture model was 313 used, where differentiated M Φ were stimulated with BCG, SA, or H 2O2 on the upper 314 chamber. Naïve monocytes in the lower chamber matured into differentiated M Φ 315 influenced by EVs and soluble factors released by stimulated M Φ from the upper 316 chamber. These recipient M Φ were then infected with Mtb to assess antimicrobial 317 activity via live-cell imaging. Further analyses included profiling EVs released by 318 infected/stimulated M Φ and epigenetic profiling of the recipient M Φ . Further 319 methodological details can be found in the Supplementary Methods. 320 321 Ethics Statement 322 Buffy coat preparations were obtained from healthy volunteers at Linköping University 323 Hospital Blood Bank. Informed, written consent was obtained from all donors in 324 accordance with ethical standards of the Helsinki Declaration. No ethical approval was 325 required for this study in accordance with local and national guidelines. 326 327 Bacterial Culture Preparation 328 BCG cultures were grown for 3 weeks; SA was prepared from overnight cultures with a 329 2-hour subculture. Bacterial suspensions were centrifuged, washed, and resuspended 330 in antibiotic-free media. Bacterial concentrations were calculated based on optical 331 density measurements. 332 333 Monocyte Isolation and Macrophage Differentiation 334 .CC-BY-NC 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted January 12, 2026. ; https://doi.org/10.64898/2026.01.12.698601doi: bioRxiv preprint 15 Peripheral blood mononuclear cells (PBMCs) were isolated by density gradient 335 centrifugation. Monocytes adhered to culture dishes and differentiated into MΦ over six 336 days in complete DMEM supplemented with 10% FBS and M-CSF . 337 338 Preparation of Recipient Macrophages by Co-culture 339 On day 6, M Φ were reseeded into transwell inserts and stimulated with BCG, SA, or 340 H2O2. Naïve monocytes were seeded in the lower chamber, cultured together for 3 341 days to allow maturation. 342 343 Control Experiments 344 Conditioned media were ultracentrifuged to deplete EVs. Naïve monocytes were 345 cultured in EV-depleted or untreated media prior to Mtb infection. 346 347 Mtb Infection and Live-Cell Microscopy 348 Mtb H37Rv-GFP cultured to logarithmic phase was used at MOI 1. Infected M Φ were 349 monitored via IncuCyte live-cell imaging every 6 hours for up to 5 days, quantifying 350 bacterial growth by fluorescence intensity. 351 352 DNA Extraction and Methylation Profiling 353 DNA was extracted and DNA methylation profiling was performed using the Illumina 354 MethylationEPIC array. Data preprocessing included normalization, filtering, batch 355 effect correction, and identification of differentially methylated CpG sites. Pathway 356 enrichment analyses were conducted for functional insight. 357 358 Extracellular Vesicle Isolation and Characterization 359 .CC-BY-NC 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted January 12, 2026. ; https://doi.org/10.64898/2026.01.12.698601doi: bioRxiv preprint 16 EVs were isolated from conditioned media by size exclusion chromatography with 360 IZON qEV columns after concentration and filtration. EV size and concentration were 361 analyzed by NTA. Morphology was assessed by TEM, and surface markers profiled 362 using multiplex bead-based flow cytometry. 363 364 Proteomics of Extracellular Vesicles 365 Proteins were extracted from EVs, prepared by ultrasonic filter-assisted sample 366 preparation (FASP) [45], and digested with trypsin. Peptides were analyzed via high-367 resolution LC-MS/MS. Protein identification utilized Spectronaut software [46]. 368 Functional annotation and pathway enrichment were performed for proteins unique to 369 treatment conditions. 370 371 Statistical analysis 372 The number of EVs and surface marker expressions from different conditions were 373 compared using one-way ANOVA and Dunnett’s multiple comparisons test. Statistical 374 analyses on Mtb growth experiments were performed using Wilcoxon signed-rank test 375 with GraphPad Prism (version 10.5.0). We used linear modeling followed by empirical 376 Bayes moderation, as implemented in the limma package for differential analysis of 377 methylation data. P-values were adjusted for multiple testing using the Benjamini-378 Hochberg procedure for False Discovery Rate (FDR) correction at 5%. In case no 379 significant FDR was reached, we used nominal p-value < 0.05. 380 381 Data/code Availability: 382 The datasets generated during the current study are not publicly available due to 383 ethical dilemmas in traceability of DNA methylation data, but processed 384 .CC-BY-NC 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted January 12, 2026. ; https://doi.org/10.64898/2026.01.12.698601doi: bioRxiv preprint 17 pseudonymized data depleted of genetic variant information (beta matrixes with 385 Illumina probe IDs and beta values) will be available upon request through the 386 Federated European Genome-phenome Archive (FEGA) Sweden controlled-access 387 repository, upon publication 388 Bioinformatic pipelines used to analyze the data and to generate graphs and figures 389 will be available on the following https://github.com/Lerm-Lab/Epigenetic-Crosstalk 390 391 .CC-BY-NC 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted January 12, 2026. ; https://doi.org/10.64898/2026.01.12.698601doi: bioRxiv preprint 18 392 Funding 393 This work was supported by the Swedish Heart Lung Foundation and the Swedish 394 Research Council [grant number 20220034, grant number 201802961] 395 396

397 We would like to acknowledge Clinical Genomics Linköping, Science for Life 398 Laboratory, Linköping University for DNA methylation analysis. We would like to 399 acknowledge the staff at Linköping Blood Bank and the anonymous blood donors. 400 401 Author contributions 402 L.E, S.D.A and M.L conceptualized the study. L.E and S.A.D performed method 403 optimizations. S.A.D and S.K performed experiments. S.A.D and L.E performed data 404 analysis. S.D.A performed and S.S guided the bioinformatic analysis. M.L funded the 405 study. L.E and S.D.A wrote the manuscript, and all authors contributed to the final 406 version. 407 .CC-BY-NC 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted January 12, 2026. ; https://doi.org/10.64898/2026.01.12.698601doi: bioRxiv preprint 19

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Mol Cell Proteomics 2023; 22:100623. 528 529 .CC-BY-NC 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted January 12, 2026. ; https://doi.org/10.64898/2026.01.12.698601doi: bioRxiv preprint 24 Figure legends 530 531 Figure 1. Extracellular vesicle secretion from human primary macrophages is 532 influenced by infection with BCG or SA and exposure to H 2O2. (a) Number of 533 extracellular vesicle (EV) released by primary human macrophages stimulated with 534 Mycobacterium bovis (BCG), Staphylococcus aureus (SA), hydrogen peroxide (H 2O2) 535 normalized to control. Stimulation with BCG, H 2O2, and SA increased EV production 536 compared to control, with BCG-treated cells exhibiting the highest level of EV release 537 (One-way ANOVA and Dunnett’s multiple comparisons test (* P < 0.05, ** P < 0.01, *** 538 P < 0.001)). (b) Surface marker expression of EVs from cells stimulated with BCG, 539 H2O2, or SA, shown as fold change relative to control . Surface markers were detected 540 by flow cytometry. Bar graph depicts the levels of indicated EV surface markers in the 541 different stimulation conditions compared to unstimulated control. BCG and SA 542 infection induce a distinct EV surface marker profile characterized by increased 543 immune and antigen-presenting cell markers, different from oxidative stress-induced 544 EVs in H 2O2 condition. HLA-DRDPDQ is a combined bead that detects all three 545 classical MHC class II antigens (DR, DP, DQ) and HLA-ABC targets MHC class I (A, B, 546 C) antigens. Surface markers showing a fold change greater than 5 in at least one 547 condition are displayed. Statistical analysis was performed using one-way ANOVA and 548 Dunnett’s multiple comparisons test (* P < 0.05, ** P < 0.01, *** P < 0.001). The 549 experiments were performed on macrophages isolated from healthy blood donors 550 (n=10). Each donor´s cells were treated with the respective agent (BCG, H 2O2, or SA) 551 or as control in three replicates, EVs isolated from five donors were pooled and 552 analyzed in two consecutive experiments. 553 554 .CC-BY-NC 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted January 12, 2026. ; https://doi.org/10.64898/2026.01.12.698601doi: bioRxiv preprint 25 Figure 2. Proteomic profiles of EVs released from primary human macrophages 555 infected with BCG, SA or exposed to H2O2. (a) Total number of peptides detected in 556 each condition. Proteomic analysis was performed on extracellular vesicles (EVs) 557 released by macrophages following stimulation with Mycobacterium bovis (BCG), 558 Staphylococcus aureus (SA), hydrogen peroxide (H2O2), or as well as in the untreated 559 control condition. Peptide identification was conducted using BLAST against a human 560 cell library. The bar plot illustrates the total number of peptides identified in each 561 condition. The experiments were performed on primary human macrophages isolated 562 from healthy blood donors (n=5). Each donor cells were treated with the respective 563 agent (BCG, H2O2, or SA) or left untreated as control. (b) Venn diagram of the protein 564 overlaps among conditions. The Venn diagram shows the number of peptides shared 565 or unique to each treatment (BCG-infection, SA-infection, H 2O2-exposure or untreated 566 controls. Each ellipse represents one condition, and overlapping regions indicate 567 peptides shared between two or more conditions. Non-overlapping regions correspond 568 to peptides uniquely identified in a single condition. (c) Bar plot showing the top 569 enriched KEGG pathways among genes associated with peptides uniquely identified in 570 the EVs released by BCG-infected macrophages. The top 10 pathways are presented 571 in the graph. The x-axis indicates the number of genes associated with each pathway, 572 and the color represents the adjusted p-value for enrichment. (d) Network plot 573 illustrating the relationships between enriched pathways and their associated genes. 574 Pathways are shown as red nodes, and genes are shown as purple nodes; edges 575 indicate gene membership in pathways. 576 577 578 .CC-BY-NC 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted January 12, 2026. ; https://doi.org/10.64898/2026.01.12.698601doi: bioRxiv preprint 26 Figure 3: DNA methylation changes in naïve monocytes differentiated during co-579 cultured with BCG-infected macrophages . (a) Volcano plot of differentially 580 methylated CpG sites annotated to genes showing genes (log fold change |logFC| > 581 0.1, P < 0.05). (b) Bar plot showing the 10 top enriched KEGG pathways among 582 genes associated with the differentially methylated CpG sites identified in the recipient 583 macrophages co-cultured with the Mycobacterium bovis (BCG)-infected macrophages 584 (the top 10 pathways are shown). The x-axis indicates the number of genes associated 585 with each pathway, and the color represents the adjusted p-value for enrichment. 586 (c) Network visualization of the top 15 enriched pathways including the associated 587 genes from DMC analysis. The network visualizes the relationships between enriched 588 biological pathways and their associated genes. Each colored node (circle) represents 589 either a pathway (in red) or a gene, with the gene nodes color-coded according to their 590 logFC values. The logFC scale indicates methylation levels. Edges (lines) indicate 591 which genes are involved in which pathways, illustrating that individual genes can 592 contribute to multiple biological processes. 593 594 Figure 4: Interactome of proteomic cargo of EVs and differentially methylated 595 genes highlighting immune regulatory hubs linked to TNF. (a) Protein-protein 596 interaction network showing high-confidence (score >700) interactome of EVs protein 597 and DNA methylation (DNAm) associated genes. Node size corresponds to degree 598 centrality, indicating connectivity within the network. Edge transparency reflects 599 interaction confidence. Nodes are color-coded by molecular origin: purple for EV 600 proteins, orange for DNAm-associated genes, and green for genes shared between 601 both datasets. 602 .CC-BY-NC 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted January 12, 2026. ; https://doi.org/10.64898/2026.01.12.698601doi: bioRxiv preprint 27 (b) Pathway enrichment analysis of interactome. A bar plot of top 10 KEGG enriched 603 pathways. 604 605 Figure 5: Naïve monocytes differentiated during co-culture with BCG-infected 606 macrophages displayed an enhanced Mycobacterium tuberculosis clearance. (a) 607 Macrophages from 4 independent donors were either untreated (control, black lines) or 608 conditioned with EVs and soluble factors released by Mycobacterium bovis (BCG)-609 infected macrophages (BCG-I MΦ ) in a transwell co-culture model (blue dashed lines) 610 and infected with GFP-expressing Mycobacterium tuberculosis (Mtb). Bacterial load 611 was monitored by live-cell imaging of GFP fluorescence over 5 days, expressed as 612 fold change relative to the initial timepoint (day 0). (b) Co-culture with BCG-I MΦ lead 613 to a tendency of decreased bacterial load at day 5 ( P = 0.125) compared to control. 614 Co-culture with SA infected and H 2O2 exposed M Φ lead to increased Mtb load 615 compared to controls, however, no significant differences between these conditions 616 were detected ( P = 0.250 and 0.375, respectively, wilcoxon signed rank test). (c) 617 Monocytes from four donors were differentiated in the presence of either; 618 ultracentrifugated EV depleted conditioned media (orange line and square) or 619 conditioned media (blue line and dot) isolated from M Φ -cultures infected with BCG. 620 Conditioned media contain both Evs and cytokines specifically secreted during BCG-621 infection. M Φ subsequently infected with GFP-expressing M. tuberculosis (H37Rv). 622 Bacterial burden was assessed by quantifying the fold change in H37Rv-GFP 623 fluorescence over five days. (d) At five days post-infection, M Φ cultured with EV-624 depleted conditioned media showed a tendency towards higher bacterial loads 625 compared to MΦ cultured in conditioned media containing EVs (Wilcoxon signed-rank 626 .CC-BY-NC 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted January 12, 2026. ; https://doi.org/10.64898/2026.01.12.698601doi: bioRxiv preprint 28 test, p = 0.125). Experiments were performed using cells from four donors, with four 627 and three technical replicates for two donors, respectively. 628 629 .CC-BY-NC 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted January 12, 2026. ; https://doi.org/10.64898/2026.01.12.698601doi: bioRxiv preprint 29 Supplementary figure legends 630 631 Supplementary figure 1. Extracellular vesicles (EVs) released by human primary 632 macrophages characterized by morphology, size and surface markers. (a) 633 Transmission electron microscopy (TEM) image showing a spherical to cup-shaped 634 morphology with a visible lipid bilayer membrane in all samples. (b) Nanoparticle 635 Tracking Analysis (NTA) of extracellular vesicles isolated from macrophage culture 636 supernatants, showing particle size distribution with an average size of 114 ± 3.8 nm 637 across the samples. (c) Bead-based flow cytometry analysis of EVs demonstrating 638 surface marker expression of CD9, CD63, and CD81. EVs were isolated by Izon size 639 exclusion chromatography columns. The results shown are representative of three 640 independent experiments conducted with macrophages derived from five different 641 donors. Macrophages were infected with M. bovis (BCG), S. aureus (SA), exposed to 642 hydrogen peroxide (H2O2) or left untreated. 643 644 Supplementary figure 2. Surface marker expression of EVs from human primary 645 macrophages infected with BCG, S. aureus or exposed to H 2O2 shown as fold 646 change relative to control. Surface markers were detected by flow cytometry. Bar 647 graph depicts the levels of indicated extracellular vesicle (EV) surface markers in the 648 different stimulation groups compared to unstimulated control. Infection with M. bovis 649 (BCG) and S. aureus (SA) induced a distinct EV surface marker profile characterized 650 by increased immune and antigen-presenting cell markers, different from H 2O2-651 induced EVs. HLA-DRDPDQ is a combined bead that detects all three classical MHC 652 class II antigens (DR, DP, DQ) and HLA-ABC targets MHC class I (A, B, C) antigens. 653 .CC-BY-NC 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted January 12, 2026. ; https://doi.org/10.64898/2026.01.12.698601doi: bioRxiv preprint 30 Experiments were performed on EVs isolated from cells of ten donors, EVs from five 654 donors were pooled before flow cytometry analysis. 655 656 Supplementary figure 3. Pathway enrichment of proteomic data from 657 extracellular vesicles released by macrophages under different conditions. 658 KEGG pathway enrichment analysis on genes associated to peptides identified in 659 extracellular vesicles released by human primary macrophages infected with M. bovis 660 (BCG), S. aureus (SA), exposed to hydrogen peroxide (H 2O2) or left untreated. Dot 661 plot showing the top 5 enriched KEGG pathways for each group. 662 663 Supplementary figure 4. DNA methylation changes in recipient macrophages 664 following co-culture with S. aureus infected or H 2O2-exposed macrophages. Bar 665 plot showing the top enriched KEGG pathways among genes associated with the 666 differentially methylated CpG sites (top 10 pathways) for macrophages co-cultured 667 with (a) S. aureus-infected macrophages. (b) H2O2-exposed macrophages. 668 669 Supplementary figure 5. Macrophage control of Mycobacterium tuberculosis 670 growth after co-culture with BCG-infected, S. aureus- infected or H 2O2-exposed 671 macrophages. Experiments were performed on macrophages isolated from blood of 672 four donors. Naïve macrophage was co-cultured with M. bovis (BCG)-infected, S. 673 aureus (SA)-infected or H 2O2-exposed macrophages during differentiation and 674 subsequently infected with M. tuberculosis (H37Rv) expressing GFP. Bacterial growth 675 was measured in a live cell imaging microscope by fluorescent intensity over five days. 676 The values are normalized to day 0. 677 678 .CC-BY-NC 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted January 12, 2026. ; https://doi.org/10.64898/2026.01.12.698601doi: bioRxiv preprint 31 Supplementary figure 6. Effect of conditioned media from macrophages under 679 different exposures depleted of extracellular vesicles (EVs) by 680 ultracentrifugation compared to conditioned media containing EVs on the 681 mycobacterial control. Monocytes from two donors were differentiated in the 682 presence of either; ultracentrifugated EV depleted conditioned media (black line and 683 square) or conditioned media containing EVs (colored line and circle). Condition media 684 was obtained from macrophage cultures infected with S. aureus (SA), exposed to 685 H2O2 or left untreated. After differentiation, the macrophages were subsequently 686 infected with GFP-expressing M. tuberculosis (H37Rv). Bacterial burden was 687 assessed by quantifying the fold change in H37Rv-GFP fluorescence over five days. 688 689 .CC-BY-NC 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted January 12, 2026. ; https://doi.org/10.64898/2026.01.12.698601doi: bioRxiv preprint 32 Conflict of interests 690 Maria Lerm is founder and CEO of PredictME AB. Shumaila Sayyab is co-founder and 691 a bioinformatician at PredictME AB. Remaining authors declare no conflict of interest. 692 693 Corresponding author 694 Maria Lerm, Div. of Inflammation and Infection, Lab 1, floor 12 695 Dept. of Biomedical and Clinical Sciences, Faculty of Medicine and Health Sciences 696 Linköping University, SE-58185 Linköping, Sweden 697 Phone: +46-732707786, E-mail: [email protected] 698 699 .CC-BY-NC 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted January 12, 2026. ; https://doi.org/10.64898/2026.01.12.698601doi: bioRxiv preprint .CC-BY-NC 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted January 12, 2026. ; https://doi.org/10.64898/2026.01.12.698601doi: bioRxiv preprint .CC-BY-NC 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. 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It is made The copyright holder for this preprintthis version posted January 12, 2026. ; https://doi.org/10.64898/2026.01.12.698601doi: bioRxiv preprint .CC-BY-NC 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted January 12, 2026. ; https://doi.org/10.64898/2026.01.12.698601doi: bioRxiv preprint