The commensal bacterium Lactiplantibacillus plantarum imprints innate memory-like responses in mononuclear phagocytes

Gut Microbes ISSN: (Print) (Online) Journal homepage: https://www.tandfonline.com/loi/kgmi20 The commensal bacterium Lactiplantibacillus plantarum imprints innate memory-like responses in mononuclear phagocytes Aize Pellon, Diego Barriales, Ainize Peña-Cearra, Janire Castelo-Careaga, Ainhoa Palacios, Nerea Lopez, Estibaliz Atondo, Miguel Angel PascualItoiz, Itziar Martín-Ruiz, Leticia Sampedro, Monika Gonzalez-Lopez, Laura Bárcena, Teresa Martín-Mateos, Jose María Landete, Rafael Prados-Rosales, Laura Plaza-Vinuesa, Rosario Muñoz, Blanca de las Rivas, Juan Miguel Rodríguez, Edurne Berra, Ana M. Aransay, Leticia Abecia, Jose Luis Lavín, Hector Rodríguez & Juan Anguita To cite this article: Aize Pellon, Diego Barriales, Ainize Peña-Cearra, Janire Castelo-Careaga, Ainhoa Palacios, Nerea Lopez, Estibaliz Atondo, Miguel Angel Pascual-Itoiz, Itziar Martín-Ruiz, Leticia Sampedro, Monika Gonzalez-Lopez, Laura Bárcena, Teresa Martín-Mateos, Jose María Landete, Rafael Prados-Rosales, Laura Plaza-Vinuesa, Rosario Muñoz, Blanca de las Rivas, Juan Miguel Rodríguez, Edurne Berra, Ana M. Aransay, Leticia Abecia, Jose Luis Lavín, Hector Rodríguez & Juan Anguita (2021) The commensal bacterium Lactiplantibacillus�plantarum imprints innate memory-like responses in mononuclear phagocytes, Gut Microbes, 13:1, 1939598, DOI: 10.1080/19490976.2021.1939598 To link to this article: https://doi.org/10.1080/19490976.2021.1939598 © 2021 The Author(s). Published with license by Taylor & Francis Group, LLC. View supplementary material Published online: 05 Jul 2021. Submit your article to this journal Article views: 740 View related articles Full Terms & Conditions of access and use can be found at https://www.tandfonline.com/action/journalInformation?journalCode=kgmi20 View Crossmark data RESEARCH PAPER/REPORT The commensal bacterium Lactiplantibacillus plantarum imprints innate memory-like responses in mononuclear phagocytes Aize Pellon a # , Diego Barriales a # , Ainize Peña-Cearra a,b , Janire Castelo-Careaga a , Ainhoa Palacios a , Nerea Lopez a , Estibaliz Atondo a , Miguel Angel Pascual-Itoiz a , Itziar Martín-Ruiz a , Leticia Sampedro a , Monika Gonzalez-Lopez c , Laura Bárcena c , Teresa Martín-Mateos d , Jose María Landete e , Rafael Prados-Rosales a,k , Laura Plaza-Vinuesa f , Rosario Muñoz f , Blanca de las Rivas f , Juan Miguel Rodríguez g , Edurne Berra d , Ana M. Aransay c,h , Leticia Abecia a,b , Jose Luis Lavín i,k , Hector Rodríguez a , and Juan Anguita a,j a Inflammation and Macrophage Plasticity Laboratory, CIC bioGUNE-BRTA (Basque Research and Technology Alliance), Derio, Spain; b Faculty of Medicine and Nursing, Universidad Del Pais Vasco (UPV/EHU), Leioa, Spain; c Genomic Analysis Platform, CIC bioGUNE-BRTA, Derio, Spain; d Physiopathology of the Hypoxia-signaling Pathway Laboratory, CIC bioGUNE-BRTA, Derio, Spain; e Departamento De Tecnología De Alimentos, Instituto Nacional De Investigación Y Tecnología Agraria Y Alimentaria (INIA), Madrid, Spain; f Laboratorio De Biotecnología Bacteriana, Instituto De Ciencia Y Tecnología De Alimentos Y Nutrición (ICTAN-CSIC), Madrid, Spain; g Department of Nutrition and Food Science, Universidad Complutense De Madrid, Madrid, Spain; h CIBERehd, ISCIII, Madrid, Spain; i Bioinformatics Unit, CIC bioGUNE-BRTA, Derio, Spain; j Ikerbasque, Basque Foundation for Science, Bilbao, Bizkaia, Spain; k Centre for Host-Microbiome Interactions, Faculty of Dentistry, Oral and Craniofacial Sciences, King’s College London, United Kingdom; RPR: Department of Preventive Medicine and Public Health and Microbiology, Universidad Autónoma De Madrid, Madrid 28029, Spain; JLL: Applied Mathematics Department, Bioinformatics Unit, NEIKER-BRTA, Parque Tecnológico De Bizkaia, Derio, Spain ABSTRACT Gut microbiota is a constant source of antigens and stimuli to which the resident immune system has developed tolerance. However, the mechanisms by which mononuclear phagocytes, specifically monocytes/macrophages, cope with these usually pro-inflammatory signals are poorly understood. Here, we show that innate immune memory promotes anti-inflammatory homeostasis, using as model strains of the commensal bacterium Lactiplantibacillus plantarum. Priming of monocytes/ macrophages with bacteria, especially in its live form, enhances bacterial intracellular survival and decreases the release of pro-inflammatory signals to the environment, with lower production of TNF and higher levels of IL-10. Analysis of the transcriptomic landscape of these cells shows downregulation of pathways associated with the production of reactive oxygen species (ROS) and the release of cytokines, chemokines and antimicrobial peptides. Indeed, the induction of ROS prevents memory-induced bacterial survival. In addition, there is a dysregulation in gene expression of several metabolic pathways leading to decreased glycolytic and respiratory rates in memory cells. These data support commensal microbe-specific metabolic changes in innate immune memory cells that might contribute to homeostasis in the gut. ARTICLE HISTORY Received 14 October 2020 Revised 14 May 2021 Accepted 30 May 2021 KEYWORDS Lactiplantibacillus plantarum; Lactobacillus; monocytes; macrophages; innate immune memory; trained immunity; microbiota; immunometabolism Introduction The emergence of microbiota research has expanded our knowledge on the role of commensal microorganisms in controlling a wide variety of physiological functions both in the steady state and in disease. In the gut, where the microbial load is greater than in any other body site, microbiota components constitute a continuous source of stimuli to which the immune system has evolved tolerance, leading to the modulation of immune responses. 1 Co-evolution with the myriad of microbes present in the gut has led to an equilibrium between the regulation of homeostatic responses to harmless antigens, and the ability to effectively eliminate pathogens. Although the role of adaptive immune cells in the gut has been extensively described, 2 the regulation of mononuclear phagocytic function (i.e. macrophages and dendritic cells) by microbiota members remains poorly understood. 3 Importantly, gut mononuclear phagocytes show aberrant anti-inflammatory responses in antibiotic-treated mice. These cells fail to CONTACT Juan Anguita [email protected] Inflammation and Macrophage Plasticity Laboratory, CIC bioGUNE-BRTA (Basque Research and Technology Alliance), Derio 48160, Spain; Hector Rodríguez [email protected] Inflammation and Macrophage Plasticity Laboratory, CIC bioGUNE-BRTA (Basque Research and Technology Alliance), Derio 48160, Spain # Equal contribution Supplemental data for this article can be accessed on the publisher’s website. GUT MICROBES 2021, VOL. 13, NO. 1, e1939598 (16 pages) https://doi.org/10.1080/19490976.2021.1939598 © 2021 The Author(s). Published with license by Taylor & Francis Group, LLC. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. regulate T cell populations in this organ, 4 while some bacterial species such as Helicobacter hepaticus 5 or Clostridium butyricum 6 directly contribute to IL-10 homeostasis. Remarkably, small populations of gut bacteria have been found to be associated with dendritic cells in the mesenteric lymph nodes, inducing the production of specific secretory IgA and promoting anti-inflammatory responses, including the release of the immunoregulatory cytokine IL-10. 7 Additionally, microbial metabolites, such as short-chain fatty acids (SCFAs), are known to regulate both dendritic cell and macrophage function in the gut, promoting antiinflammatory/hyporesponsive states in innate immune cells and contributing to the development of intestinal homeostasis. 3 Since the discovery of phagocytic cells by Ilya Mechnikov, 8 our knowledge on monocyte and macrophage plasticity has enormously evolved. This includes phenomena described in the last decade such as the ability of different innate immune cell types, monocytes/macrophages among them, to generate long-term responses, namely innate immune memory. 9 This mechanism involves an epigenetic and metabolic reprogramming induced by the contact with an infectious agent or microbial component that leads to an enhanced (trained innate immunity) or decreased (tolerance) cytokine-mediated response to a secondary stimulation with a, usually different, microbial component. 10,11 Consequently, innate immune memory has been proven to be an important regulator not only of antimicrobial responses of innate immune cells, but of their roles in inflammatory and neurological diseases. 12 However, since all of these studies have been performed in a pathological context, no information is available to date regarding the role that innate immune memory plays in coping with the continuous exposure of innate immune cells to commensal microbes (i.e. human microbiota), and whether this phenomenon plays a role in immune modulation by commensal bacteria. 13 Lactobacillus plantarum, recently reclassified as Lactiplantibacillus plantarum, 14 is a Gram-positive species that has been extensively characterized for its adaptive ability to thrive within the human gut and the benefits of its immunomodulatory properties for the human host, with some L. plantarum strains being widely used as probiotics. 15 Therefore, we used this species as a model of a beneficial microbe to show that, while acute exposure to monocyte/macrophages allows bacterial intracellular survival and induce both proand anti-inflammatory cytokine release, a previous contact with L. plantarum reprograms the transcriptional and metabolic profiles of immune cells in the long term. This innate immune memory-like events eventually lead to enhanced bacterial intracellular survival and decreased pro-inflammatory features in pre-stimulated cells. Results Lactiplantibacillus plantarum can survive within macrophages from different origins Recent reports have shown that dendritic cells populating the mesenteric lymph nodes harbor small amounts of gut bacteria inside, which contribute to the modulation of both innate and adaptive responses. 7 Given its genomic similarity with some intracellular pathogens, such as Listeria monocytogenes, 16 we hypothesized that L. plantarum might also be able to survive intracellularly and that this could be associated with its immunomodulatory effects. To unveil the potential of this species to survive intracellularly in macrophages we used antibiotic protection assays (Fig. S1A). As controls, we also used the closely related species, Lactobacillus casei (recently reclassified as Lacticaseibacillus casei) as well as the enteric species, Escherichia coli. First, using a multiplicity of infection (m.o.i.) of 10, we observed that all the L. plantarum strains used in this study were able to survive inside the macrophage-like cell line, RAW264.7 for 24 h, with strains of human milk origin showing slightly higher survival rates. In contrast, the number of L. casei and E. coli inside these phagocytes was lower (Fig. S1B). In order to validate our results, we used two primary cellular models, murine bone marrowderived macrophages (mBMM) and human monocyte-derived macrophages (hMDM). Overall, intracellular survival of L. plantarum strains was observed in both cell types, although to a lesser extent in comparison with the RAW264.7 cell line (Figure 1a, b). Similar to our observations using the cell line, intracellular survival of L. casei was lower e1939598-2 A. PELLON ET AL. than that of L. plantarum strains, with the presence of viable E. coli within the macrophages being dramatically decreased from the beginning of the experiment. Similar results were observed when an m.o.i. of 1 was used (Fig. S1C, D). To detect the cellular compartment in which L. plantarum persists inside macrophages, we incubated mBMMs with mCherry-labeled bacteria and assessed their colocalization with LAMP-2, a phagolysosome marker 17 , using confocal microscopy. Notably, while heat-killed bacteria were observed surrounded by LAMP-2 positive vesicles, live bacteria did not show colocalization with the marker suggesting that they are able to evade their localization within these degradative organelles (Figure 1c). We also performed whole blood ex vivo infection assays and analyzed the presence of bacteria. We incubated EDTA-treated human blood from healthy donors with L. plantarum WCFS1 modified to constitutively express mCherry and evaluated the internalization of the bacteria and its presence over time by flow cytometry. L. plantarum was found predominantly associated with CD14 + monocytes (Figure 1d). In fact, up to 42.2% of these cells were able to internalize and maintain L. plantarum for the duration of the assay. Next, we assessed the ability of L. plantarum to escape from macrophages after its internalization. After adding bacteria and promoting phagocytosis for 45 min, extracellular bacteria were washed away, and macrophages were cultured either for 1 or 4 h in medium supplemented with antibiotics to kill remaining extracellular microbes (Fig. S1E). Then, mBMMs were washed with warm PBS and incubated in antibiotic-free medium for 24 h. Samples from supernatants and cell lysates were plated onto MRS agar plates to assess bacterial viability. Notably, high numbers of viable bacteria were found both in the intracellular (Figure 1e) and extracellular (figure 1f) compartments. Overall, L. plantarum strains survived better in comparison Figure 1. L. plantarum colonize and survive within macrophages from different origins. Bacteria were co-cultured with either mouse bone marrow-derived macrophages (mBMMs) (a) or human monocyte-derived macrophages (hMDMs) (b), and their intracellular survival at different time points was determined using antibiotic protection assays (Fig. S1A). After incubating bacteria with immune cells, wells were washed, and antibiotic-containing medium was added. After 1, 4 or 24 h cells were lysed, and suspensions plated to assess bacterial intracellular survival. (c) Distinct colocalization of live (left micrograph) and heat-killed, mCherry-expressing L. plantarum (right micrograph, red) with the phagolysosome marker, LAMP-2 (green). The nuclei were stained with DAPI (blue). The orthogonal projection of the indicated points (crosshairs) is presented at the bottom and right side of the micrographs. (d) Anticoagulated whole blood was incubated with mCherry-labeled L. plantarum WCFS1 and its association with CD14 + cells was determined by flow cytometry. Representative flow cytometry data is shown. (e, f) Bacterial ability to persist intracellularly (e) and reach the extracellular medium (f) after being engulfed by immune cells. After short incubation times (1 and 4 hours) in antibioticcontaining medium, cells were extensively washed and incubated with antibiotic-free medium for 24 h. Samples from the supernatant and immune cell lysates were plated to check bacterial viability. Data are shown as mean ± s.e.m., n ≥ 3. **; p < .01, ***; p < .001, twoway ANOVA compared to L. plantarum WCFS1. GUT MICROBES e1939598-3 with L. casei both inside and outside of mBMMs. Therefore, these data show that after colonization of macrophages, L. plantarum can escape from the phagocytes to the extracellular medium. Together, these data show that L. plantarum can be internalized by murine and human monocyte/ macrophages and survive for prolonged periods of time, compared to other commensal bacteria. Pre-exposure of macrophages to L. plantarum enhances bacterial survival and decreases pro-inflammatory outputs In the last decades, our knowledge on macrophage plasticity and ability to display long-term responses has greatly increased. Of note, research efforts have mainly focused on studying pathogenic/pathobiont microbes, partially ignoring the repertoire of longlasting responses developed by these cells in response to different stimuli. 18 Thus, we assessed the ability of L. plantarum to induce innate immune memory-like responses in monocytes/ macrophages in vitro (Figure 2a). Pre-stimulation of mBMMs with a m.o.i. of 1 of live L. plantarum (Lp-Lp) enhanced bacterial survival in a second encounter in comparison with unstimulated cells (U-Lp), while priming with heat-killed bacteria (HkLp-Lp) did not result in a significant increase in bacterial survival (Figure 2b). Of note, no bacterial survival was detected in the Lp-Lp group before the second stimulation, suggesting that live bacteria from the first stimulus had been eliminated. Remarkably, pre-stimulation with live bacteria also led to decreased TNF release after the second stimulation, while heat-inactivated bacteria promoted a more moderate reduction. In turn, cell culture supernatants of mBMMs primed with live bacteria contained increased levels of IL-10 compared to stimulated naïve cells (Figure 2c). This effect was not restricted to the WCSF1 strain as Figure 2. Priming with L. plantarum enhances bacterial intracellular survival and reduces pro-inflammatory cytokine release. (a) Diagram showing the experimental set up of priming experiments using murine bone marrow-derived macrophages (mBMMs) and human monocytes (hMon). Priming mBMMs with L. plantarum (m.o.i. = 1), especially in its live form, increased bacterial intracellular survival over time (b) and reduced the immune cell pro-inflammatory profile (c). (d) Decreased TNF release by primed cells depends on bacterial m.o.i. used. Intracellular survival and TNF production profiles showed similar patterns in primed hMon after either 24 h (e, f) or 6 d (g, h) resting time. Priming with either L. plantarum or L. casei improves bacterial survival (i, k) but does not reduce TNF release (j, m) if the other species is used for the second stimulation. Data are shown as mean ± s.e.m., n ≥ 3. *; p < .05, **; p < .01, ***; p < .001, twoway (B,E,G,I,K) or one-way (C,D,F,H,J,M) ANOVA. e1939598-4 A. PELLON ET AL. TNF decrease was also observed when using as priming agents two different strains isolated from human breast milk, MP31 (Fig. S2A) and MP33 (Fig. S2B). Notably, induction of memory-like features in mBMMs after L. plantarum exposure was dependent on bacterial dose, showing that a minimum of m.o.i. 0.1 used as the first stimulus was necessary to induce a significant decrease in TNF release upon a secondary stimulation (Figure 2d). Finally, to determine whether the induction of memory was due to secreted factors produced by L. plantarum, we pre-stimulated mBMMs with sterile MRS medium or filtered conditioned medium obtained from an overnight culture of L. plantarum WCFS1. No changes in intracellular survival of L. plantarum were observed (Fig. S2C), suggesting that soluble factors were not responsible for the increased survival of the bacterium upon stimulation with live microorganisms. Our results were recapitulated in human CD14 + monocytes (hMon) in vitro using both 24 h or 6 d of resting time after the first stimulus, a protocol previously used to study induction of long-term responses in these cells. 19 While either live or heatkilled L. plantarum induced the same changes in bacterial intracellular survival and TNF production using a 24 h-resting time (Figure 2e and f), live L. plantarum induced higher effects when longer resting times were applied (Figure 2g and h). These changes in cytokine release profiles suggested that pre-stimulation with L. plantarum, particularly in its live form, induced long-term changes in both mBMMs and hMon featuring an anti-inflammatory profile, which may be involved in the increased bacterial intracellular survival observed. We then tested whether priming with other probiotic bacterial species, L. casei, could lead to the same immunomodulatory events observed with L. plantarum. Of note, priming of mBMMs with live L. casei enhanced bacterial intracellular survival (Fig. S2D) and reduced TNF release (Fig. S2E) compared to unprimed cells, although to a lesser extent than when L. plantarum was used. Moreover, since trained cells have shown certain non-specificity in their responses to secondary challenges (e.g. BCG stimulation protects from fungal and bacterial infections 12 ), we tested the effect of priming with one probiotic species and use the other one as the secondary stimulation. Although trends of intracellular survival rates were comparable to those previously observed (Lp-Lp v. Lc-Lp, Figure 2i; Lc-Lc v. Lp-Lc, Figure 2k), priming with different species than those used for the second stimulation did not recapitulate the reduction in TNF levels (Figure 2j and m). These data show that for these bacteria, long-term effects on phagocytic cells are, at least partly, species-specific. L. plantarum priming induces long-term changes in the transcriptional profile of human monocytes To delve into the mechanisms inducing these longterm responses by L. plantarum, we studied the transcriptional profiles of human monocytes by RNA-seq in the three experimental conditions previously analyzed after 6 d of resting time: U-Lp, LpLp and HkLp-Lp. The three conditions showed distinct transcriptional profiles, as shown by principal component analysis (PCA) (Figure 3a) and clustering of the most regulated genes (Figure 3b). Overall, we found 1030 differentially expressed genes (using cut off values of 1 for the absolute log 2 Fold Change and p adj <0.05) between unprimed and live bacteria-primed monocytes (U-Lp v. Lp-Lp, 514 up and 516 down; Figure 3c), and 326 when unprimed controls were compared with cells pre-stimulated with heat-killed bacteria (U-Lp v. HkLp-Lp, 93 up and 233 down; Figure 3d), showing that pre-exposure to live L. plantarum cells induced a greater impact on monocytes in the long term. Pathway analysis using PantherDB 20,21 (Table S1) showed a significant enrichment of several cytokine and chemokine pathways among the downregulated genes in monocytes primed either with live or heat-killed bacteria. Among others, genes as IL1A, IL1B, IL6 or CCL20 were found downregulated in both conditions compared to unstimulated cells (Figure 3e, f). In addition, pathway analysis showed downregulated functions related to organism killing and production of reactive oxygen and nitrogen species (Table S1). In this regard, several genes coding for antimicrobial peptides/proteins, such as calprotectin (S100A8 and S100A9) and calgranulin (S100A12), were found downregulated only in the Lp-Lp group (Figure 3e, f), which may be linked to the increased bacterial intracellular survival observed in these cells. Notably, TNF and other six members of this GUT MICROBES e1939598-5 cytokine signaling pathway were observed downregulated only in Lp-Lp monocytes, in addition to the four found in monocytes primed either with live or heat-killed bacteria (Figure 3g), which confirmed the profiles of TNF release previously detected by ELISA. Moreover, we found changes in the expression of KAT2A (upregulated in both Lp-Lp and HkLp-Lp) and HDAC9 (downregulated in Lp-Lp), both of which are related to histone modifications and activation of transcription and might be involved in epigenetic modifications associated with innate immune memory. Next, we carried out a comparative transcription factor enrichment analysis of the differentially expressed genes in Lp-Lp and HkLp-Lp using the HOMER package. 22 For upregulated genes, only the p53 motif was found as regulator of 1.46% of genes in the Lp-Lp condition, while no significant results were found for the HkLp-Lp gene set (Figure 3h). On the other hand, motifs associated with NFκB-p65 contributed to the highest percentage of downregulated genes in both live (Lp-Lp condition) and heat-killed (HkLp-Lp condition) bacteria-primed cells, with minor contributions from interferon-regulated transcription factors (IRF2, ISRE) and CBEP under live bacteria priming conditions (Figure 3h). Transcriptional reprogramming in L. plantarum-stimulated monocytes induce changes in cell metabolism Analysis of monocyte transcriptomic profiles also allowed us to identify the impact of priming in U-Lp v. Lp-Lp U-Lp v. HkLp-Lp U-Lp Lp-Lp HkLp-Lp U-Lp Lp-Lp HkLp-Lp PC1: 51% variance -10 0 10 PC2: 20% variance 10 5 0 -5 AB CD E CD22 CD244 KHK PHGDH KAT2A LDHD TLR5 SLC40A1 SLC45A3 SLC46A1 TRIB3 ACSS ALDOC ASNS ASRGL1 ATP6VOD2 ATP6VOE2 CD180 CERKL CHDH CHPT1 CR1 FAAH FFAR4 FOLR2 GALM GPT2 IDH2 IL1R2 LY86 ME3 MRC2 PDK2 PDK3 PDK4 PHYH SLC16A5 SLC22A5 SLC2A1 TLR7 ACO1 ACOD1 ACSL4 ACSL5 CLEC4A CLEC4E CLEC4G CSFRA CSFRB GZMB HDAC9 IL18 IRF1 NLRP7 S100A8 S100A9 S100A12 SGMS2 SLC16A10 SLC2A6 SLC41A2 TLR2 TLR8 TNF TNFRSF4 TNFRSF6B TNFRSF9 TNFRSF10A TNIP1 CCL20 CD55 CLEC5A CLEC12A CSF2 IL1A IL1B IL6 IL23A IL24 ITGB3 ITGB8 SLC1A2 SLC28A3 SLC5A3 SOCS3 TGFA TNFRSF18 TNFSF16 TNIP3 TRAF1 Upregulated genes HkLp-LpLp-Lp Downregulated genes HkLp-LpLp-Lp IL1B CXCL8 CXCL16 S100A9 CCL3 CXCL9 CCL8 IL1A CCL4 CCL18 S100A8 CXCR4 CSF3R HAMP DEF6 CCL1 IL18 CXCL12 PPBP CSF2 CXCL11 CXCL6 CCL19 AZU1 S100A12 IL23A CSF3 CXCR5 CCL23 CCL20 CXCL10 IL6 TNF CCL3L1 CXCL2 CCL4L2 CCL24 CCL22 IL24 CCL5 CCL7 CXCL3 CTSL CXCL5 U-Lp Lp-Lp HkLp-Lp F TNIP1 TNF TNFSF13B TNFSF15 EDA2R TNFSF18 TNFSF6B TNFSF4 TNFSF12A TNFSF8 TNFSF10A TNFSF9 TNFSF14 CD40 TRAF1 TNIP3 U-Lp Lp-Lp HkLp-Lp G H No significant results Gene set Upregulated in Lp-Lp Upregulated in HkLp-Lp Downregulated in Lp-Lp Downregulated in HkLp-Lp Motif C T G A A G C G C T A C G A T G G T C A T C G A T C C T A G C A G C A G A C G C T A C A G T C G T A A T G G T G T A G T C G A G C A T C G A T C T T C T C G T A C G A T G T A G A T A A G C T C T A C T C G A C C T A G T C G A C T G A C G T A T A C G G A C T T C A G T C G A G T C A T G C A T A C G A G C T T G A A T C G T C T G T G C C T G A T A C G A T T A C T G T C T G C A T G T T A G G A T C C T A G A T C C A A A G T C C G T A A T G G T G T A G T C G A G C A T C G A T C T T C T C G T A C G A T G T A G A T A A G C T C T A C T C G A C Rank 1 1 2 3 4 5 1 2 Name p53 NFκB-p65 NFκB-p65-Rel IRF2 ISRE CEBP NFκB-p65 NFκB-p65-Rel 0.0485 0 0.0008 0.0021 0.0021 0.0021 0.0033 0.0145 (Benjamini) q-value 1.46% 16.74% 3.70% 5.22% 3.91% 12.39% 18.01% 4.74% Targets % of 0.21% 8.13% 0.95% 1.90% 1.18% 6.89% 8.43% 1.30% Background % of CXCL1 Figure 3. Broad transcriptional remodeling is induced in human monocytes after L. plantarum priming. (a) Principal Component Analysis of human monocytes (hMon) unprimed (U-Lp) or primed with either live (Lp-Lp) or heat-killed (HkLp-Lp) L. plantarum. Heatmap (b) and volcano plots (c, d) showing differentially regulated genes. Blue dots represent upregulated genes, whereas red dots indicate downregulated genes. (e) Venn diagrams depicting upor down-regulated genes shared between Lp-Lp and HkLp-Lp compared to U-Lp. Heat-maps of selected differentially expressed genes involved in immune responses (f) and belonging to the TNF signaling pathway (g). (h) Comparative transcription factor enrichment analysis of differentially expressed genes using the HOMER package. The differential expression of genes was set at an absolute log 2 Fold Induction value of 1 and Padj < 0.05. e1939598-6 A. PELLON ET AL. several metabolic pathways of monocytes in comparison with cells acutely exposed to L. plantarum, especially in those monocytes pre-stimulated with live bacteria (Figure 4a). Although we did not find great changes in the expression levels within members of central metabolic pathways, we observed that some adjacent metabolic pathways were enriched in our functional study. Indeed, our data showed the upregulation of folic acid metabolism, amino acid and carboxylic acid biosynthesis, and monocarboxylic acid catabolism, and the downregulation of hyaluronan biosynthesis, negative regulation of lipid storage, and glycerol transport (Table S1). Specifically, we observed the upregulation of three pyruvate dehydrogenase kinases genes (PDK2, PDK3, PDK4) in cells primed with live bacteria, as well as a decreased expression of ACO1 and ACOD1, coding for aconitase and aconitate decarboxylase, suggesting a reduction in the integrity of the tricarboxylic acid (TCA) cycle and the itaconate pathway. We also found the differential regulation of several genes coding for metabolite transporters (Figure 3e), including those for glucose (SLC2A1), other hexoses and monocarboxylic compounds (SLC2A6, SLC45A3, SLC16A5), and amino acids (SLC1A2, SLC16A10), which possibly contribute to changes in cellular metabolism. To assess whether these alterations in the transcriptional landscape had physiological consequences in primed cells, we analyzed the metabolic profiles of human monocytes by Figure 4. L. plantarum priming promotes a metabolic rewiring resulting in decreased oxidative burst. (a) Heat-map depicting selected differentially expressed genes with functions related to cellular metabolism. Seahorse extracellular flux analyzer was used to determine OCR (b) and ECAR (c) profiles of human monocytes (hMon). Data are shown for a representative experiment out of two independently performed. (d) Phenogram showing OCR/ECAR ratio of unprimed hMon, and cells primed with either live (Lp-Lp) or heat-killed (HkLp-Lp) L. plantarum. (e) ROS production after the second bacterial encounter. Phorbol-12-myristate-13-acetate (PMA) was used to increase ROS production in mBMMs (f), which induced a decrease in L. plantarum intracellular survival in memory macrophages (g). Data are shown as mean ± s.e.m., n ≥ 3. *; p < .05, **; p < .01, ***; p < .001, One-way ANOVA (E) and Student’s t test (f, g). GUT MICROBES e1939598-7 References 1. Belkaid Y, Harrison OJ. Homeostatic immunity and the microbiota. Immunity. 2017;46:562–576. doi:10.1016/j. immuni.2017.04.008. 2. Honda K, Littman DR. The microbiota in adaptive immune homeostasis and disease. Nature. 2016;535:75–84. doi:10.1038/nature18848. 3. Scott NA, Mann ER. Regulation of mononuclear phagocyte function by the microbiota at mucosal sites. Immunology. 2020;159:26–38. doi:10.1111/ imm.13155. 4. Kim M, Galan C, Hill AA, Wu W-J, Fehlner-Peach H, Song HW, Schady D, Bettini ML, Simpson KW, Longman RS, et al. Critical role for the microbiota in CX3CR1+ intestinal mononuclear phagocyte regulation of intestinal T cell responses. Immunity. 2018;49:151–163. doi:10.1016/j.immuni.2018.05.009. 5. Danne C, Ryzhakov G, Martínez-López M, Ilott NE, Franchini F, Cuskin F, Lowe EC, Bullers SJ, Arthur JSC, Powrie F. A large polysaccharide produced by Helicobacter hepaticus induces an anti-inflammatory gene signature in macrophages. Cell Host Microbe. 2017;22:733–745. doi:10.1016/j.chom.2017.11.002. 6. Hayashi A, Sato T, Kamada N, Mikami Y, Matsuoka K, Hisamatsu T, Hibi T, Roers A, Yagita H, Ohteki T, et al. A single strain of Clostridium butyricum induces intestinal IL-10-producing macrophages to suppress acute experimental colitis in mice. Cell Host Microbe. 2013;13:711–722. doi:10.1016/j.chom.2013.05.013. 7. Fung TC, Bessman NJ, Hepworth MR, Kumar N, Shibata N, Kobuley D, Wang K, Ziegler CGK, Goc J, Shima T, et al. Lymphoid-tissue-resident commensal bacteria promote members of the IL-10 cytokine family to establish mutualism. Immunity. 2016;44:634–646. doi:10.1016/j.immuni.2016.02.019. 8. Tauber AI. Metchnikoff and the phagocytosis theory. Nat Rev Mol Cell Biol. 2003;4:897–901. doi:10.1038/ nrm1244. 9. Gourbal B, Pinaud S, Beckers GJM, Van Der Meer JWM, Conrath U, Netea MG. Innate immune memory: an evolutionary perspective. Immunol Rev. 2018;283:21–40. doi:10.1111/imr.12647. 10. Domínguez-Andrés J, Fanucchi S, Joosten LAB, Mhlanga MM, Netea MG. Advances in understanding molecular regulation of innate immune memory. Curr Opin Cell Biol. 2020;63:68–75. doi:10.1016/j. ceb.2019.12.006. 11. Netea MG, Joosten LAB, Latz E, Mills KHG, Natoli G, Stunnenberg HG, Oneill LAJ, Xavier RJ. Trained immunity: a program of innate immune memory in health and disease. Science. 2016;352:aaf1098–aaf1098. doi:10.1126/science.aaf1098. 12. Netea MG, Domínguez-Andrés J, Barreiro LB, Chavakis T, Divangahi M, Fuchs E, Joosten LAB, van der Meer JWM, Mhlanga MM, Mulder WJM, et al. Defining trained immunity and its role in health and disease. Nat Rev Immunol. 2020;20:375–388. doi:10.1038/s41577-020-0285-6. 13. Negi S, Das DK, Pahari S, Nadeem S, Agrewala JN. Potential role of gut microbiota in induction and regulation of innate immune memory. Front Immunol. 2019;10:2441. doi:10.3389/fimmu.2019.02441. 14. Zheng J, Wittouck S, Salvetti E, Franz CMAP, Harris HMB, Mattarelli P, O’Toole PW, Pot B, Vandamme P, Walter J, et al. A taxonomic note on the genus Lactobacillus: description of 23 novel genera, emended description of the genus Lactobacillus Beijerinck 1901, and union of Lactobacillaceae and Leuconostocaceae. Int J Syst Evol Microbiol. 2020;70:2782–2858. doi:10.1099/ijsem.0.004107. 15. van den Nieuwboer M, van Hemert S, Claassen E, de Vos WM. Lactobacillus plantarum WCFS1 and its host interaction: a dozen years after the genome. Microb Biotechnol. 2016;9:452–465. doi:10.1111/1751-7915.12368. 16. Kleerebezem M, Boekhorst J, van Kranenburg R, Molenaar D, Kuipers OP, Leer R, Tarchini R, Peters SA, Sandbrink HM, Fiers MWEJ, et al. Complete genome sequence of Lactobacillus plantarum WCFS1. Proc National Acad Sci. 2003;100:1990–1995. doi:10.1073/pnas.0337704100. 17. Carreras-Gonzalez A, Barriales D, Palacios A, Montesinos-Robledo M, Navasa N, Azkargorta M, PenaCearra A, Tomas-Cortazar J, Escobes I, Pascual-Itoiz MA, et al. Regulation of macrophage activity by surface receptors contained within Borrelia burgdorferi-enriched phagosomal fractions. PLoS Pathog. 2019;15:e1008163. doi:10.1371/journal.ppat.1008163. 18. Ifrim DC, Quintin J, Joosten LAB, Jacobs C, Jansen T, Jacobs L, Gow NAR, Williams DL, van der Meer JWM, Netea MG. Trained immunity or tolerance: opposing functional programs induced in human monocytes after engagement of various pattern recognition receptors. Clin Vaccine Immunol. 2014;21:534–545. doi:10.1128/ CVI.00688-13. 19. Bekkering S, Blok BA, Joosten LAB, Riksen NP, Van Crevel R, Netea MG. In vitro experimental model of trained innate immunity in human primary monocytes. Clin Vaccine Immunol. 2016;23:926–933. doi:10.1128/ CVI.00349-16. 20. Mi H, Muruganujan A, Ebert D, Huang X, Thomas PD. PANTHER version 14: more genomes, a new PANTHER GO-slim and improvements in enrichment analysis tools. Nucleic Acids Res. 2019;47:D419–D426. doi:10.1093/nar/gky1038. 21. Thomas PD. PANTHER: a library of protein families and subfamilies indexed by function. Genome Res. 2003;13:2129–2141. doi:10.1101/gr.772403. 22. Heinz S, Benner C, Spann N, Bertolino E, Lin YC, Laslo P, Cheng JX, Murre C, Singh H, Glass CK. Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol Cell. 2010;38:576–589. doi:10.1016/j.molcel.2010.05.004. e1939598-14 A. PELLON ET AL. 23. Holmström KM, Finkel T. Cellular mechanisms and physiological consequences of redox-dependent signalling. Nat Rev Mol Cell Biol. 2014;15:411–421. doi:10.1038/nrm3801. 24. Netea MG, Quintin J, van der Meer JM. van der Meer JWM. Trained immunity: a memory for innate host defense. Cell Host Microbe. 2011;9(5):355–361. doi:10.1016/j.chom.2011.04.006. 25. Foster SL, Hargreaves DC, Medzhitov R. Gene-specific control of inflammation by TLR-induced chromatin modifications. Nature. 2007;447:972–978. doi:10.1038/ nature05836. 26. Quintin J, Saeed S, Martens JHA, GiamarellosBourboulis EJ, Ifrim DC, Logie C, Jacobs L, Jansen T, Kullberg B-J, Wijmenga C, et al. Candida albicans infection affords protection against reinfection via functional reprogramming of monocytes. Cell Host Microbe. 2012;12:223–232. doi:10.1016/j.chom.2012.06.006. 27. Saeed S, Quintin J, Kerstens HHD, Rao NA, Aghajanirefah A, Matarese F, Cheng SC, Ratter J, Berentsen K, van der Ent MA, et al. Epigenetic programming of monocyte-to-macrophage differentiation and trained innate immunity. Science. 2014;345:1251086. doi:10.1126/science.1251086. 28. Sánchez-Ramón S, Conejero L, Netea MG, Sancho D, Ó P, Subiza JL. Trained immunity-based vaccines: a new paradigm for the development of broad-spectrum anti-infectious formulations. Front Immunol. 2018;9. doi:10.3389/fimmu.2018.02936. 29. Pasco ST, Anguita J. Lessons from Bacillus Calmette-Guerin: harnessing trained immunity for vaccine development. Cells. 2020;9:2109. doi:10.3390/ cells9092109. 30. Pizarro-Cerdá J, Cossart P. Listeria monocytogenes: cell biology of invasion and intracellular growth. Microbiol Spectr. 2018;6. doi:10.1128/microbiolspec.GPP3-00132018. 31. Yeung PSM, Na Y, Kreuder AJ, Marquis H. Compartmentalization of the broad-range phospholipase C activity to the spreading vacuole is critical for Listeria monocytogenes virulence. Infect Immun. 2007;75:44–51. doi:10.1128/IAI.01001-06. 32. Kang B, Alvarado LJ, Kim T, Lehmann ML, Cho H, He J, Li P, Kim B-H, Larochelle A, Kelsall BL. Commensal microbiota drive the functional diversification of colon macrophages. Mucosal Immunol. 2020;13:216–229. doi:10.1038/s41385-019-0228-3. 33. Muller PA, Matheis F, Mucida D. Gut macrophages: key players in intestinal immunity and tissue physiology. Curr Opin Immunol. 2020;62:54–61. doi:10.1016/j. coi.2019.11.011. 34. Ding Y-H, Qian L-Y, Pang J, Lin J-Y, Xu Q, Wang L-H, Huang D-S, Zou H. The regulation of immune cells by Lactobacilli: a potential therapeutic target for anti-atherosclerosis therapy. Oncotarget. 2017;8:59915–59928. doi:10.18632/oncotarget.18346. 35. Wells JM. Immunomodulatory mechanisms of lactobacilli. Microb Cell Fact. 2011;10:S17–S17. doi:10.1186/1475-2859-10-S1-S17. 36. Bain CC, Schridde A. Origin, differentiation, and function of intestinal macrophages. Front Immunol. 2018;9:2733. doi:10.3389/fimmu.2018.02733. 37. Bain CC, Bravo-Blas A, Scott CL, Perdiguero EG, Geissmann F, Henri S, Malissen B, Osborne LC, Artis D, Mowat AM. Constant replenishment from circulating monocytes maintains the macrophage pool in the intestine of adult mice. Nat Immunol. 2014;15:929–937. doi:10.1038/ni.2967. 38. Chong C, Bost KL, Clements JD. Differential production of interleukin-12 mRNA by murine macrophages in response to viable or killed Salmonella spp. Infect Immun. 1996;64:1154–1160. doi:10.1128/iai.64.4.11541160.1996. 39. Cruz AR, Moore MW, La Vake CJ, Eggers CH, Salazar JC, Radolf JD. Phagocytosis of Borrelia burgdorferi, the Lyme disease spirochete, potentiates innate immune activation and induces apoptosis in human monocytes. Infect Immun. 2008;76:56–70. doi:10.1128/IAI.01039-07. 40. Ilinskaya ON, Ulyanova VV, Yarullina DR, Gataullin IG. Secretome of Intestinal Bacilli: a natural guard against pathologies. Front Microbiol. 2017;8:1666. doi:10.3389/fmicb.2017.01666. 41. Nanjundaiah YS, Wright DA, Baydoun AR, Khaled Z, Ali Z, Dean P, Sarker MH. Modulation of Macrophage Function by Lactobacillus-Conditioned Medium. Front Cell Dev Biol. 2020;8:723. doi:10.3389/fcell.2020.00723. 42. van der Meer JWM, Joosten LAB, Riksen N, Netea MG. Trained immunity: a smart way to enhance innate immune defence. Mol Immunol. 2015;68:40–44. doi:10.1016/j.molimm.2015.06.019. 43. West MA, Heagy W. Endotoxin tolerance: a review. Crit Care Med. 2002;30:S64–73. doi:10.1097/00003246200201001-00009. 44. Van den Bossche J, O’Neill LA, Menon D. Macrophage immunometabolism: where are we (going)? Trends Immunol. 2017;38:395–406. doi:10.1016/j.it.2017.03.001. 45. Ferreira AV, Domiguez-Andres J, Netea MG. The Role of Cell Metabolism in Innate Immune Memory. J Innate Immun. 2020;1–9. doi:10.1159/000512280. 46. Sugden MC, Holness MJ. Recent advances in mechanisms regulating glucose oxidation at the level of the pyruvate dehydrogenase complex by PDKs. Am J Physiol Endocrinol Metab. 2003;284:E855–E862. doi:10.1152/ajpendo.00526.2002. 47. O’Neill LAJ, Artyomov MN. Itaconate: the poster child of metabolic reprogramming in macrophage function. Nat Rev Immunol. 2019;19:273–281. doi:10.1038/ s41577-019-0128-5. 48. Domínguez-Andrés J, Novakovic B, Li Y, Scicluna BP, Gresnigt MS, Arts RJW, Oosting M, Moorlag SJCFM, Groh LA, Zwaag J, et al. The itaconate pathway is a central regulatory node linking innate immune GUT MICROBES e1939598-15 tolerance and trained immunity. Cell Metab. 2019;29:211–220.e215. doi:10.1016/j.cmet.2018.09.003. 49. Fensterheim BA, Guo Y, Sherwood ER, Bohannon JK. The cytokine response to lipopolysaccharide does not predict the host response to infection. J Immunol. 2017;198:3264–3273. doi:10.4049/jimmunol.1602106. 50. Cheng SC, Quintin J, Cramer RA, Shepardson KM, Saeed S, Kumar V, Giamarellos-Bourboulis EJ, Martens JHA, Rao NA, Aghajanirefah A, et al. mTORand HIF-1-mediated aerobic glycolysis as metabolic basis for trained immunity. Science. 2014;345:1250684. doi:10.1126/science.1250684. 51. Arts RJW, Carvalho A, La Rocca C, Palma C, Rodrigues F, Silvestre R, Kleinnijenhuis J, Lachmandas E, Gonçalves LG, Belinha A, et al. Immunometabolic pathways in BCG-induced trained immunity. Cell Rep. 2016;17:2562–2571. doi:10.1016/j.celrep.2016.11.011. 52. Soto A, Martín V, Jiménez E, Mader I, Rodríguez JM, Fernández L. Lactobacilli and Bifidobacteria in human breast milk. J Pediatr Gastroenterol Nutr. 2014;59:78–88. doi:10.1097/MPG.0000000000000347. 53. Carreras-Gonzalez A, Navasa N, Martin-Ruiz I, Lavin JL, Azkargorta M, Atondo E, Barriales D, MaciasCamara N, Pascual-Itoiz MA, Sampedro L, et al. A multi-omic analysis reveals the regulatory role of CD180 during the response of macrophages to Borrelia burgdorferi. Emerg Microbes Infect. 2018;7:19. doi:10.1038/s41426-017-0018-5. 54. Aribi M. Macrophage bactericidal assays. Methods Mol Biol. 2018;1784:135–149. 55. Saftig P, Beertsen W, Eskelinen EL. LAMP-2: a control step for phagosome and autophagosome maturation. Autophagy. 2008;4:510–512. doi:10.4161/auto.5724. 56. Hünniger K, Lehnert T, Bieber K, Martin R, Figge MT, Kurzai O. A virtual infection model quantifies innate effector mechanisms and Candida albicans immune escape in human blood. PLoS Comput Biol. 2014;10:e1003479–e1003479. doi:10.1371/journal.pcbi.1003479. 57. Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, Batut P, Chaisson M, Gingeras TR. STAR: ultrafast universal RNA-seq aligner. Bioinformatics. 2013;29:15–21. doi:10.1093/bioinformatics/bts635. 58. Liao Y, Smyth GK, Shi W. The Subread aligner: fast, accurate and scalable read mapping by seed-and-vote. Nucleic Acids Res. 2013;41:e108–e108. doi:10.1093/nar/ gkt214. 59. Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15:550. doi:10.1186/ s13059-014-0550-8. e1939598-16 A. PELLON ET AL.