Probiotic stimulation of co-cultures with bone marrow-derived dendritic cells and basophils modulate T helper responses

MSc Thesis Biotechnology

Course code: CBI-80436

Author: Chantal Deen

Registration nr: 910203 174 010

Specialisation: Biotechnology Cellular/Molecular

Supervisor: Adriaan van Beek

Examinator: Huub Savelkoul

Wageningen University and Research Centre Department Cell Biology and Immunology

Wageningen, May 2014

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AbstractProbiotic bacteria exert beneficial effects on the immune system. How probiotics establish this effect needs to be elucidated. In this study, in vitro cultures of bone marrow-derived dendritic cells (BMDCs) and basophils (BMB) were stimulated with probiotics and the modulatory effect by these cells on T helper cells was analysed by flow cytometry. Flow cytometry was used to measure surface markers, transcription factors and cytokines. BMBs stimulated with probiotics led to increased production of IL-4, which is involved in polarisation towards T helper 2 (Th2) and modulation of B cell responses. BMDCs stimulated with probiotics increasingly produce TNF, IFN-γ, IL-6 and IL-10 which are important in polarisation of naive T helper cells toward T helper 1 (Th1), T helper 17 (Th17) and regulatory T helper (Treg). Co-cultures with BMDCs and BMBs probably enhanced Th2 immune responses. The results suggest that BMBs up-regulate Th2 responses, when they were stimulated in the presence of BMDCs and CD4+ T cells. WCFS1 treatment induces stronger Th1 polarisation, compared to BL23. BMDC and BMB interact with each other during co-culture influencing the immune response upon stimulation.

IntroductionThe human body contains more microbiota than it has somatic and germ cells [1]. Not surprisingly, this microbiota fulfils several important tasks in the human body. For example, microbiota in the human intestine digest and ferment substances that the host is not able to digest by itself [2]. These microbiota also train the immune system and prevent growth of harmful pathogens [3]. The role of probiotics in the intestine is to support the function of the microbiota present in the gut and to support the human gut itself subsequently [4]. The most common probiotics are Lactobacilli and Bifidobacteria [1, 5]. Probiotics are live organisms that have a beneficial influence on the intestinal epithelial and on the immune system upon ingestion [2, 6]. There is evidence that probiotics have anti-inflammatory activities, compete with pathogens and must therefore modulate the immune system [1, 3-6]. To modulate the immune system of the host, probiotics must be able to give signals to immune cells present in the intestine [7]. Signals derived from these probiotics can be recognized by cells of the immune system [7]. Antigen presenting cells (APCs) are able to capture and present antigens obtained from probiotics at the surface of their cell to initiate and activate immune responses [8]. Although it is clear that probiotics provide signals to immune cells, the exact mechanisms how probiotics establish an immune modulatory response is not clear.

BMDCs are APCs that are dedicated to capture and present antigens [9]. In general, antigens get into contact with BMDCs in the mucosal immune areas, such as the oral cavity, lungs and intestines [3, 5, 10]. BMDCs express membrane receptors, such as Toll-like receptors (TLR), C-type lectins and NOD-like receptors that bind to these bacteria and use these receptors to capture and endocytose bacteria and their antigens [6, 11, 12]. After endocytosis, bacteria are digested and bacterial antigens are presented by MHC-class II molecules on the surface of BMDCs [13]. Activated BMDCs express high levels of MHC-II co-stimulator molecules and cytokines to attract and activate naive T helper cells [7, 14].

Depending on the available cytokines in the environment, BMDCs are able to trigger an immune response or to suppress this response by activating certain types of T helper cells [5, 8, 14]. Production of IL-12 by BMDCs induces Th1 differentiation [6]. IL-10 is described as an inhibitory

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cytokine and induces a Treg response [5, 15]. BMDCs can also polarise the immune response toward Th17 cells by producing IL-6, IL-1β and TGF-β. [16-19]. BMDCs are the major APCs to initiate Th1, Th17 and Treg responses, it is however unclear how BMDCs induce Th2 responses as BMDCs do not produce IL-4 [9, 20].

Basophils are granulocytes and are involved in allergic responses. When they get involved in allergic immune responses they secrete cytokines, like IL-4 and IL-6 that are involved in Th2 skewing [21]. Commensal bacteria in the gut can influence development of allergic reactions [3, 22]. As BMBs are involved in allergic responses, bacteria in the gut may influence BMB responses and populations [21]. Studies have not only shown that bacteria respond to BMBs, but that BMBs can respond to bacteria as well [23]. Recent studies also showed antigen presenting activities for BMBs [24-27]. The antigenic capacities of BMBs will be tested by stimulating BMBs with probiotics. Again CD4+ T cells will be used as a read out system.

Two different probiotic strains were tested in this study. The first one is Lactobacillus plantarum WCFS1 (WCFS1), a lactic acid producing bacteria and is used in a large variety of studies [28-36]. Probiotic and immune enhancing properties have been described for WCFS1 in literature. For example, a study showed treating mice with WCFS1 induces immunomodulatory effects, such as reduced pro and anti-inflammatory responses and increased splenic BMDC and T cell frequencies [30]. Another study had shown that consumption of WCFS1 alters transcription profiles of immune cells present in the small intestine [37]. Genes that were involved in immune tolerance were upregulated, while genes that were involved in amplifying inflammatory responses were not modulated [37]. Cultures that contained both WCFS1 and enteropathogens like E. coli or S. enteritidis led to inhibited growth of the enteropathogens and suggested that WCFS1 had antimicrobial capacities [38]. L. plantarum WCFS1 is used in this experimental approach as a reference strain.

The second probiotic tested in this study is another lactic acid producing bacteria called Lactobacillus casei BL23 (BL23). This bacterial strain is investigated in several studies [34, 39, 40]. For example, BL23 can reduce oxidative stress during inflammatory response and therefore decreases tissue damage during immune responses [41]. Another study demonstrates that BL23 influences the innate immunity by upregulating CD-206 and TLR-2 receptors [42].

Both WCFS1 and BL23 have been shown to interact with TLR-2 receptors on BMDCs [30, 43]. Interaction with TLR-2 receptors leads to increased cytokine expression levels of IL-1α, IL-6 and TNF, IL-10 and IL-12p70 [17, 29, 30, 42, 44, 45]. These cytokines promote activation and proliferation of effector CD4+ T cells towards Th1, Th17 and Treg [19, 40, 43]. Based on this information we expect that WCFS1 and BL23 promote activation and polarisation towards Th17, Th1 and Treg. BMBs however, are strong inducers of IL-4 and IL-6 production and cell cultures done with BMBs will probably upregulate Th2 responses [46, 47].

The characteristics of BMDCs and BMBs as APCs will be used in this project to investigate the effect of probiotics on immune cells. Maturation of BMDCs and stimulation of BMBs and subsequent polarization of different types of T-helper (Th) cells by BMDCs is assessed.

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Materials and methods

MiceNMRI mice, both female and male in the age of 5-26 weeks were obtained from the animal facility in Wageningen (NL). Male C57Bl/6Rjj mice between 8-12 weeks were obtained from Janvier labs. All mice were housed in the animal facility in Wageningen (NL). All mice used during these experiments were kept under specific pathogen-free conditions and according to federal Dutch guidelines. Bone marrow (BM) from femur, tibia and pelvis, and the spleen were collected and processed.

Probiotic cultivationL. plantarum WCFS1 and L. casei BL23 were obtained from glycerol stocks and transferred to MRS growth medium and grown overnight at 37°C and 5% CO2, in aerobic conditions. Bacteria were re-inoculated the next day and grown at 37°C overnight again. CFU were determined by OD600 values, using a spectrophotometer (U-1500 1390-05 Hitachi). The bacteria were washed twice and diluted with PBS before added to the BM cell cultures.

BM isolationBones were flushed with sterile RPMI-1640 Glutamax, 25 mM HEPES (RPMI medium) and passed through a 40 µm cell strainer (BD Falcon) to obtain a single cell suspension. Single cell suspensions were frozen in 90% FCS and 10% DMSO and stored in liquid nitrogen until usage.

Bone marrow-derived BMDC cultureCulture medium contained RPMI-1640 Glutamax, 25 mM HEPES, 10% (vol/vol) heat inactivated FCS, 1% (vol/vol) penicillin/streptomycin (Sigma), 50 µM β-mercaptoethanol, 0.2% (vol/vol) Normocin (Invivogen) and 20 ng/ml GM-CSF (BioLegend). 2.5*105 cells/ml were cultured in culture medium for 7 days at 37°C and 5% CO2. The cells were stimulated with LPS (100 ng/ml, E. coli 055:B5, Sigma-Aldrich) or with 5*105 CFU for 3 hours or 20 hours.

Bone marrow-derived basophil cultureBone marrow cells were cultured in BMB culture medium containing RPMI-1640 Glutamax, 25 mM HEPES, 10% (vol/vol) heat inactivated FCS, 1% (vol/vol) penicillin/streptomycin (Sigma), 1mM sodium pyruvate, 50 µM β-mercaptoethanol, 0.2%(vol/vol) Normocin (Invivogen) and 2 ng/ml IL-3. At day 11-14, BMBs were purified and separated with the IMagnet System (BD Biosciences) according to manufacturer instructions. Negative selection was performed for CD11c and CD117 and positive selection for FcɛRIα. Purity of BMBs was at least 98%. BMBs were stimulated with IL-18 (50 ng/ml) with IL-33 (100 ng/ml) as positive control or with probiotics for 20 hours.

Co-culture of BMDCs and CD4+ T cellsSpleen cells were enriched for CD4+ T cells with the Imagnet (BD Biosciences). Negative selection for CD11b and positive selection for CD4 were performed. Purity of CD4+ T cells was around 80%, with in particular B cells still present. Anti-CD3 (1 µg/ml) and CD4+ T cells were added to the plate containing BMDCs in a 10:1 ratio. The cells were cultured in medium containing 1 ml DMEM, 10% (vol/vol) FCS, 1% (vol/vol) Pen/Strep, 50 µM β-mercaptoethanol and 0.2% (vol/vol) Normocin (Invivogen). The generation of Th1, Th2, Th17 and Treg cells was determined after 4 days.

BMB and BMDC co-culture

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A ratio of 1:1 BMDCs and BMBs were added to wells in a plate. Culture medium consisted of RPMI-1640 Glutamax, 25 mM HEPES, 10% (vol/vol) heat inactivated FCS, 1% (vol/vol) penicillin/streptomycin (Sigma), 1mM sodium pyruvate, 50 µM β-mercaptoethanol, 0.2% (vol/vol) Normocin (Invivogen), and 2 ng/ml IL-3. After overnight stimulation, cells were co-cultured with CD4+ T cells at a ratio of 1:10.

Cytokine bead assayCytokine levels in supernatants of BMDC cultures were measured with the CBA Mouse Inflammation Kit (BD Biosciences), according to the manufacturer’s instructions. Cytokine levels in supernatants of BMBs and CD4+T cells were measured with the CBA Mouse Th1/Th2/Th17 Kit (BD Biosciences).

FACS analysisBefore incubation with mAbs, cells were blocked with anti-CD16/CD32 (2.4G2) in FACS buffer (PBS containing 0.25% (vol/vol) BSA, 0.5mM EDTA, 10% FCS). The following mAbs were purchased from BD Pharmingen: CD3e-APC-Cy7 (145-2C11), CD4-APC-Cy7 (H129.19), CD4-APC (RM4-5), CD4-biotin (GK1.5), CD8a-PE (53-6.7), CD11b-APC-Cy7 (M1/70), CD11b-BV510 (M1/70), CD11b-BV421 (M1/70), CD11b-FITC (M1/70), CD16/CD32-FITC (2.4G2), CD44-PerCP-Cy5.5 (IM7), CD45R/B220-FITC (RA3-6B2), CD62L-APC-Cy7 (MEL-14), CD86-PE-Cy7 (GL1), CD117-biotin (2B8), CD117-PerCP-Cy5.5 (2B8), CD123-biotin (5B11), FoxP3-AlexaFluor647 (MF23), GATA3-PE (L50-823), T-bet-BV421 (O4-46).

From eBioscience, the following mAbs were obtained: CD11b-biotin (M1/70), CD11c-PE-Cy7 (N418), CD19-FITC (1D3), CD86-APC (GL1), CD115-PE (AFS98), FcεRIα-FITC (MAR-1), FcεRIα-biotin (MAR-1), MHC-II-FITC (M5/114.15.2), MHC-II-APC (M5/114.15), NK1.1-FITC (PK136), Ki-67-PE-Cy7 (SolA15), streptavidin-APC-Efluor780, streptavidin-FITC, streptavidin-PerCP-Cy5.5, streptavidin-APC and streptavidin-BV421 were obtained.

Dead cell staining was done with 7-AAD (BD Pharmingen) or with Aqua live dead-Efluor506 (eBioscience). Samples were acquired on a FACS Canto II (BD) and analysed with FlowJo vX.0.7 software (Treestar).

Statistical analysisStudent’s t test or two-way analysis of variance was used to determine significant differences between conditions tested. In figures, p-values are noted as follows: *P<0.05, **P<0.01 and ***P<0.001.

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Results

Stimulation of BMBs did not lead to upregulation of surface molecules CD11b and MHC-IIBMBs were stimulated with IL-18, IL-33 and probiotics for 20 hours in vitro. Afterwards was FACS analysis performed on surface markers CD11b, CD11c, CD62L, CD86, CD117, FcεRIα and MHC-II. Examples of the gating can be found in supplementary information I. Figure 1 summarizes the data of the stimulated BMB.

Figure 1. BMBs stimulated with IL18, IL-33, WCFS1 and BL23. Values were based on average values (+/- SEM) and ten samples. The experiment was performed twice.

The figure above shows the mean fluorescence intensity of different surface markers. No upregulation of surface markers MHC-II and CD62L was seen for probiotic stimulation with BMBs. Expression of CD11b was downregulated for the probiotics compared to the negative control. MHC-II expression was not affected by probiotic stimulation. CD86 and CD62L expression was upregulated in both probiotic stimulation, but for WCFS1 this increase is higher compared to BL23.

BMDCs stimulated with probiotics does not lead to maturation of DCsBMDCs were stimulated with probiotics for 20h in vitro. FACS analysis was performed for CD11b, CD11c, CD62L, CD86, CD117, FcεRIα and MHC-II. Gating was performed as shown in the supplementary information I. The data is summarized in Figure 2 and shows the percentage of cells that were CD86+MHC-II+ (mature BMDCs), CD86-MHC-II- (precursor) and CD86intMHC-IIint (immature BMDCs).

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Figure 2. BMDCs were stimulated with 105 CFU BL23 or WCFS1 for 20 hours. Graph represents average percentages (+/- SEM) of each condition tested (n=10). The results are derived from two independent experiments. Figure 2A shows % mature BMDCs, Figure 2B shows % cells of immature BMDCs and figure 2C shows % cells of precursors. *P<0.05, ***P<0.001.

Compared to the medium control, probiotic stimulation led to significantly decreased maturation of BMDCs. The results suggest that maturation of BMDCs was downregulated by the probiotic stimulation with WCFS1 and BL23. Literature does confirm that mice treated with WCFS1 did not activate BMDCs in vivo [30]. Other articles describe that BL23 induces production of IL-10 Weiss, 2010 #90}[48]. Therefore T regulatory immune responses were upregulated upon stimulation and prevent maturation of BMDCs [49]. In summary, probiotic stimulation of BMDCs suppresses activation and inhibits upregulation of co-stimulatory molecules of BMDCs.

Probiotic stimulation of co-cultures does affect cell surface markers of both BMDCs and BMBsBMDCs and BMBs together in a cell culture may enhance the stimulatory effect of BMDCs. BMDCs and BMBs were stimulated with probiotics together for 20 hours in vitro. FACS analysis performed on CD11b, CD11c, CD62L, CD86, CD117, FcεRIα and MHC-II. Gating is shown in the supplementary information I. Figure 3 shows the mean fluorescence intensity (MFI) of FcεRIα+ CD11c- cells. FcεRIα+CD11c- cells were identified as BMBs and FcεRIα-CD11c+ cells were identified as (im)mature BMDCs. FcεRIα-CD11c+ cells were given in figure 4.

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Figure 3. The figure above shows mean fluorescent intensity (MFI). The experiment was performed twice and each experiment contained five replicates. The standard deviation was based on the average values of all samples (+/- SEM). **P<0.01, ***P<0.001.

Figure 1 shows the MFI values of stimulated cultures of BMBs. In general the MFI values are lower of cultures only stimulated with BMBs compared with the co-cultures. MHC-II values of BMBs during co-cultures are significant higher when they are stimulated with probiotics. In general, co-cultures performed with BMBs and DCs show significant differences between some conditions and this was not observed with the BMB cultures. All MFI values of the surface markers show an increase in surface expression upon probiotic stimulation.

FcεRIα-CD11c+ cells were gated for mature and immature BMDCs and precursor cells. Gating can be found in supplementary information I. For each population was the MFI of CD11c, CD86 and MHC-II calculated and these graphs were given below in figure 4.

Figure 4. MFI values of FcεRIα-CD11c+ cells for mature and immature BMDCs. The experiment was performed twice. The standard deviation (+/- SEM) was based on the average values of ten samples. Figure A shows MFI values of CD86. Figure B shows MFI values of MHC-II. Figure C shows MFI values of CD11c.

MFI of CD86 of the mature DC population slightly increased upon probiotic stimulation. No significant differences were found for MFI values of CD86 and MHC-II. The figure below shows MFI values of DCs stimulated with probiotics for 20 hours.

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Figure 3. MFI values of CD86, MHC-II and CD11c of BMDCs. BMDCs were separated in three different subpopulations; mature, immature and precursor. The graph shows average values and the standard deviation (n=10). Figure A shows MFI values of the co-culture with BMDCs and BMBs. Figure B shows the MFI values of BMDCs.

The expression of CD86 of mature BMDCs in figure 5A is higher in the controls compared to the probiotic stimulated BMDCs. Probiotic stimulation did not activate maturation of BMDCs (Fig. 5A).

In summary, probiotics that stimulated co-cultures of BMDCs and BMBs induces increased activation of BMBs compared to the culture containing only BMDCs or BMBs. Surface markers expression of CD86, CD62L and MHC-II increased upon stimulation.

For BMDCs in general the MFI values were higher in the co-culture condition compared to the BMDCs culture. Maturation of BMDCs during co-cultures were upregulated, both the results were not significant. The results do suggest that BMB and DCs influence each other immune responses. Cytokine measurement may reveal more of the mechanisms behind the immune response.

Probiotic BMDC stimulation leads to an increase of IL-12, TNF and IL-6 productionBMDCs were stimulated with WCFS1 and BL23 and cytokines were measured in the supernatant of the culture medium. All cytokines that were measured were given in supplementary information II. Table 1 below shows the average cytokine values measured in pg/ml.

Table 1. Cytokines measured in the supernatant of BMDC cultures. Cytokines were measured in pg/ml. BMDCs were stimulated with WCFS1 and BL23 for 20 hours. The table displayed average values and were based on 10 samples. Experiment was performed twice. ND is not detectable.

BMDCsIL-12p70 (pg/ml)

TNF (pg/ml)

IFN-γ (pg/ml)

MCP-1 (pg/ml)

IL-10 (pg/ml)

IL-6 (pg/ml)

- 0.2 22.5 ND 110.8 1.4 0.5

LPS 0.7 2098.8 ND 160.7 1 3822.3

WCFS1 ND 64.5 ND 85.1 ND 7.6

BL23 0.6 40.6 ND 85 2.2 2.2

The table shows that BMDCs stimulated with WCFS1 and with BL23 induces production of TNF, IL-6 and MCP-1. BL23 also produces IL-10. Most cytokines levels were increased compared with the negative control.

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Cytokines produced during BMB stimulation show an increase in TNF, IL-6 and IL-4 productionBMBs were stimulated with probiotics and cytokines were measured to validate the immune response. The average values of every cytokine measured in pg/ml was given in table 2.

Table 2. Cytokines measured in the supernatant of cell cultures with BMBs. BMBs were stimulated for 20 hours with probiotics. Cytokines were measured in pg/ml. Values in the table were based on averages and on ten samples. The experiment was performed twice. ND is not detectable.

BMBIL-10 (pg/ml)

IL-17 (pg/ml)

TNF (pg/ml)

IFN-γ (pg/ml)

IL-6 (pg/ml)

IL-4 (pg/ml)

IL-2 (pg/ml)

- ND 0.2 ND ND 4.9 3.8 0.5IL-18+IL-33 0.8 0.2 ND ND 22 1.9 0.5WCFS1 1.8 0.2 0.9 ND 5.9 4.3 0.4BL23 ND 0.2 0.3 ND 7.1 3.4 0.4

For WCFS1 were the cytokine values of IL-10, TNF and IL-4 higher compared to BL23. For BMBs stimulated with BL23 were cytokines levels of IL-6 higher.

Probiotic stimulation of co-cultures leads to increase production of cytokine involved in inflammatory responsesFor co-cultures with BMDC and BMBs were also cytokines measured. Co-cultures of BMBs and BMDCs were performed in vitro and stimulated for 20 hours with WCFS1 or with BL23. The cytokines measured were summarized in table 3.

Table 3. Co-cultures of BMDCs and BMBs were stimulated with probiotics. Supernatant was analysed for inflammatory cytokines and cytokines were measured in pg/ml. The table shows average values based on ten samples. The experiment was performed twice.

BMDCs and BMB

IL-12p70 (pg/ml)

TNF (pg/ml)

IFN-γ (pg/ml)

MCP-1 (pg/ml)

IL-10 (pg/ml)

IL-6 (pg/ml)

IL-17 (pg/ml)

IL-4 (pg/ml)

IL-2 (pg/ml)

- ND 14.8 ND 85.3 2 5.5 0.2 0.2 0.4

LPS/IL-18+IL-33 ND 632.9 0.1 117.4 1.7 1766.8 0.9 1.7 0.3

WCFS1 0.8 94.7 0.4 102.4 2.1 15.1 0.4 ND 0.1

BL23 1.3 36 0.1 97.4 3.3 8.5 0.2 0.2 0.2

Co-cultures that were stimulated with probiotics show in both cases production of IL-12, TNF, MCP-1, IL-10 and IL-6. WCFS1 had higher cytokine levels of TNF, MCP-1 and IL-6 compared to BL23. BL23 had higher values measured for cytokines IL-12 and IL-10 compared to WCFS1.

In summary, TNF values measured in both probiotics conditions tested showed an increase in production compared to the negative control. This is shown in all tables (Table 1-4). This was also the case for MCP-1 and IL-6. These cytokines are involved in pro-inflammatory immune response towards Th1 and Th17 [19, 40, 43]. The results suggest that the probiotics regulate the pro-inflammatory immune response, but regulatory immune response was not induced either.

Co-culture experiment of stimulated BMDCs, BMBs and CD4+ TcellsBMDCs and BMBs were stimulated in vitro for 3h and co-cultured with CD4+ T cells for 4 days. After 3 hours was FACS analysis performed on the surface markers of BMDCs and BMBs. No differences in up- or down regulation of surface markers of BMDCs and BMBs were found. After 4 days of co-

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culture with CD4+ T cells was FACS analysis performed on extra- and intracellular markers of these T cells. Gating was performed to determine the amount of FoxP3, T-bet and GATA3 positive cells. The gating can be found in the supplementary information I. Proliferation of CD4+ T cells were measured with Ki-67 and cell viability was measured with aqua live-dead staining.

CD4+ T cells were purified with magnetic cell sorting, but still contained cells that were not CD4 positive. Therefore, the percentage of CD4- cells was determined. The percentage of CD19+ cells (B cells) varied between 15 and 25%. These cells had proliferated and had high Ki-67 values at the time of measurement. This population has to be kept in mind and may have influenced our results.

The CD4+ T cells were gated for FoxP3, T-bet and GATA3 positive populations. Figure 11 shows a bar graph, showing the quantity of positive values of FoxP3, T-bet and GATA3 cells after 4 days of co-culture. FoxP3 values were measured to determine the polarization towards regulatory T cells, T-bet positive cells were measured to determine polarization towards Th1 cells and GATA3 was measured to determine polarization towards Th2 cells.

Figure 4. Percentage of cells those were positive for expression markers of CD4+ T cells. CD4+ T cells were cultured for 4 days with BMDCs. Average values ( +/- SEM) were based on ten sample and given in the graph. Figure A shows percentage of cells positive for FoxP3. Figure B shows percentage of cells positive for GATA3. Figure C shows percentage of cells positive for T-bet.

Probiotic stimulation of BMDCs upregulate FoxP3 expression, while GATA3 expression was downregulated.

Figure 5. Percentage of cells those were positive for expression markers of CD4+ T cells. CD4+ T cells were cultured for 4 days with BMBs. Average values ( +/- SEM) were based on ten sample and given in the graph. Figure A shows percentage of cells positive for FoxP3. Figure B shows percentage of cells positive for GATA3. Figure C shows percentage of cells positive for T-bet.

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Probiotic stimulation of BMBs and CD4+ T cells leads to upregulation of GATA3. FoxP3 and T-bet expression was upregulated for BMBs stimulated with BL23, but downregulated for WCFS1.

Figure 6. FoxP3, GATA3 and T-bet measurements of stimulated CD4+ T cells. BMDCs and BMBs were stimulated for 3 hours, CD4+ T cells were added and 4 days later analysis was performed. The experiment was only performed once. The bars in the graph show average values (+/- SEM) based on three samples. Figure A shows percentage of cells positive for FoxP3. Figure B shows percentage of cells positive for GATA3. Figure C shows percentage of cells positive for T-bet.

In figure 8B, probiotic stimulation does decrease GATA3 compared to the other conditions tested. WCFS1 increases expression of T-bet, but BL23 decreases T-bet expression. Expression of FoxP3 was increased for both probiotics.

In summary, BMBs increase GATA3 expression and BMDCs increase FoxP3 expression of CD4+ T cells upon probiotic stimulation. Remarkable is the difference in T-bet expression between the two probiotics we tested. T-bet expression was higher for BMDCs stimulated with WCFS1 compared to BL23 stimulation, but for BMBs this seemed to be the opposite. Although for BMBs the deviation was larger.

DiscussionThe purpose of this research was to investigate the effect of probiotics on immune cells. Cell cultures of BMDCs and BMBs were cultured under in vitro conditions and stimulated with L. plantarum WCFS1 and L. casei BL23. CD4+ T cells were used as a read out system to investigate polarisation of the immune response by stimulated BMDCs and BMBs.

BMDCs stimulated induce a stronger immune response with WCFS1 compared to BL23BMDCs that were stimulated with probiotics induce immune responses towards Th1, Th17 and Treg. For WCFS1 this was clearer than for BL23. The cytokine levels of TNF and IL-6 were measured in higher levels and T-bet expression was upregulated for WCFS1, but not for BL23. We found that BL23 induces IL-10 production. Studies were performed earlier whereby BMDCs were stimulated with BL23 and WCFS1 [29, 45, 50]. These studies found that BL23 can induce high levels of IL-10 and can induce regulatory immune responses [5, 29, 40]. However, one of the studies was performed in vitro with immune cells obtained from human blood, but the results were similar [29]. WCFS1 can induce inflammatory responses towards Th1 and Th17 by production of TNF and IL-12 in vitro [30, 37, 51]. The studies also consist of in vivo experiments in mice and human and these studies suggested that lactobacillus induce anti-inflammatory responses [30, 37]. For WCFS1 the results in relation to regulatory immune responses were contradictory as FoxP3 expression was observed during the BMDC and CD4+ T cell co-culture, but IL-10 was not detected during cytokine measurements of the BMDC culture. Maybe IL-10 production needs more time before it is released in the supernatant. For

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future experiments we can try to detect IL-10 intracellular, or measure at a later time point (after 24 hours of stimulation for example).

BMB induce Th2 responses after BL23 and WCFS1 stimulationProbiotic stimulation was also performed on BMBs and on co-cultures with BMBs and CD4+ T cells. BMBs induced Th2 responses after BL23 and WCFS1 stimulation. BMBs are known to induce Th2 responses upon stimulation, because BMBs are efficient producers of IL-4 [21, 46, 47]. However we found different IL-4 levels in our different probiotic conditions tested. Previous studies shown that the ratio of BMDCs and BMBs influence the quantity of IL-4 produced, but this does not explain why we measure different IL-4 levels for our different probiotics [21]. Apart from the IL-4 production it seems that the stimulation of BMBs with BL23 induces Th1 and Th17 polarization, while this was not the case for WCFS1. In general, our measurements make it difficult to distinguish if the immune response was polarised towards Th1 or towards Th17. IL-17A was not detected and suggest the immune response was not towards Th17, but for future experiments expression of RORγt can be measured with flowcytometry to have more reliability.

In case of surface marker expression, basophils have been shown to express MHC-II in both in vivo and in vitro settings in studies. Both studies mention that MHC-II expression of basophils respond to th2 immune responses [22, 52]. This does not explain why MHC-II expression was not affected in our culture. However the other surface markers were upregulated, suggesting that BMBs do respond upon probiotic stimulation.

BMBs stimulated with BL23 induce Treg responses, but IL-10 was not measured for this condition. The lack of IL-10 production is contradictory with the high expression of FoxP3 we found when BMBs were co-cultured with CD4+ T cells and stimulated with BL23. One study were human PBMCs where basophils activated and stimulated with L.casei [53]. They found that L.casei inhibits activation of basophils in an IgE dependent way [53]. This may explain the lower levels of cytokines we measured for BL23 and the upregulation of FoxP3, but not the upregulation of GATA3 and T-bet. However, in the experiment they did not perform co-cultures with T-cells.

Most of the studies in which BMBs were stimulated with probiotics concluded that the production of cytokines was regulated by the MyD88-dependent pathway [23, 46, 54]. This signalling pathway plays an important role for induction of T cell proliferation [55]. MyD88 is also needed for TLR signalling and TLR receptors are often involved in recognizing antigens, like bacterial compounds [11]. The signalling between probiotics, BMDCs and BMBs is likely to be influenced by this pathway.

BMBs enhance CD4+ T cell responses toward Th2 and BMDCs enhance the immune response toward Th1 and Th17 upon probiotic stimulationCo-cultures done with BMDCs, BMBs and CD4+ T cells were stimulated with probiotics and analysed. Co-cultures with BMBs skew CD4+ T cell towards Th2. Treatment with WCFS1 increases the Th1 polarisation, while BL23 treatment decreases the skewing towards Th1. Studies that were performed earlier found that when BMBs were co-cultured with BMDCs and CD4+ T cells, BMBs induce Th2 differentiation, but they are also able to suppress Th1 differentiation [21, 56]. One of the studies illustrates that BMBs influence CD4+ T cells and splenic DCs by supporting Th2 immune responses. However, this study obtained basophils by implanting mice with IL-3 and harvest cells from bone marrow and liver. CD4+ T cell were obtained from the lymph nodes and DCs from the spleen [21].

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BMDCs and BMBs influence each other when they are cultured together. Surface expression of BMB were not altered upon probiotic stimulation. But when cocultured with DCs the surface expression of BMBs increases. This increase is higher for WCFS1 compared to BL23 and suggest a stronger immune response towards WCFS1, but it also suggest that DCs enhance the immune response of BMBs.

During coculture were cytokines MCP-1, IL-10 and IL-17a upregulated while IL-4 and IL-2 were downregulated in the co-cultures compared to cell cultures that only contained BMDCs or BMBs. But addition of CD4+ T cells enhances GATA3 expression in the co-culture. Expression of FoxP3 and T-bet was generally lower in the co-culture compared to the BMDCs and BMB culture. Our results suggest that BMDCs induce inflammatory responses towards Th1 and Th17 and BMB induce immune responses towards Th2. WCFS1 induces a stronger T-bet expression and thus may induce stronger inflammatory responses compared to BL23.

The results might indicate that BMBs and DCs communicate with each other. Surface markers of BMBs were upregulated under influence of DCs in combination with probiotics. FoxP3 and Tbet expression were downregulated during cocultures under influence of BMBs, while GATA-3 expression was upregulated. We hypothesised that BMBs upregulate Th2 polarisation and this is in line with our results. We also hypothesized that probiotic stimulation of BMDCs would lead to Th1, Th17 and Treg polarisation. This is the case for BMDCs cell cultures, but co-cultures with both BMDCs and BMBs this is not the case.

Future recommendationsFinally, we have several recommendations for the future. First, for all experiments we performed, the T cell responses were not very strong. This can be caused by the fact the T cells are part of the adaptive immune system. No immunization was done for our immune cells, so T memory cells were not developed. In some experiments T cells were restimulated to induce a stronger CD4+ T cells response [57].

Second, the cell amounts we used were not tested beforehand. The cell amounts and ratios could be tested to obtain optimal immune responses between BMDCs or BMBs and CD4+ T cells. Several studies mentioned that cell ratios may influence cell viability and an efficient immune response [21, 57].

Another future recommendation is to test more probiotics since we only tested two different probiotic strains, which are both gram-positive and aerobes. The majority of the microbiota in the human intestine and probiotics are anaerobes [1, 3]. To get a better understanding of the mechanisms of probiotics on immune cells we recommend testing probiotics that are gram negative and/ or anaerobe, like Akkermansia muciniphila and Bifidobacterium breve.

Also, we only tested the effect of probiotics on co-cultures of CD4+ T cells, but BMDCs respond to more types of immune cells, like CD8+ T cells and B cells. For example B cells can be used to investigate what antibodies will be produced (or not) upon stimulation with probiotics. And last, BMB responses on CD8+ T cells can be tested in future experiments as BMBs may be able to act as APCs for CD8+ T cells [56]. BMBs may also play a role in generation of FoxP3 Treg cells and B cells [57, 58].

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AcknowledgementsI would like to thank Adriaan van Beek for supervising me and Joanne Hoogerland for her support and for the time we spent together in and outside the lab. I also would like to thank Ben Meijer for his help for the flow cytometer. Thanks to Huub Savelkoul and Edwin Tijhaar for their advice during my project and everybody present at the Wednesday morning meetings.

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Supplementary information I-Gating

Gating of BMDC culturesThe figure below shows gating performed on all FACS data containing BMDCs. Gating was performed in the following order: Lymphocytes and singlets. Singlets were gated for living and dead cells and for CD86+MHC-II+ cells.

Figure 7. Example how Gating of BMDC cultures was performed is showed above. Mature BMDCs were identified as CD86+MHC-II+, immature BMDCs as intermediate CD86 MHC-II and precursor BMDCs were identified as CD86-MHC-II-.

Gating of BMB culturesThe figure below shows gating performed on all FACS data containing BMBs. On all samples was gating performed in the following order: Lymphocytes, Singlets, CD117- 7-AAD- cells, FcεRIα+ cells. Singlets were not shown, but same was done as shown for gating of BMDCs.

Figure 8. FACS profiles and gating performed on BMB cells. Figure above functions as an example. Gating performed for singlets was not shown, but was similar as shown in figure 1. BMB cells were identified as FceRIa positive.

Gating of co-cultures of BMDC and BMBGating of co-cultures containing both BMDCs and BMBs was done as shown in the figure below. Every sample was gated for lymphocytes and singlets. Singlets were gated for living and dead cells and for FcεRIα+CD11c+ cells. FcεRIα positive cells were identified as BMBs, CD11c positive cells were identified as BMDCs. CD11c positive cells were gated for mature BMDCs, immature BMDCs and precursor cells.

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Figure 9. Example of gating of co-cultures containing BMDCs and BMBs. Gating was performed in the following order; lymphocytes and singlets. Singlets were gated for living and dead cells, for FceRIa positive and CD11c positive cells.

Gating of CD4+ TcellsGating of the stimulated CD4+ T cells is shown in the figure below. All samples were gated for lymphocytes, and singlets. Singlets were gated for living and dead cells and for CD4+CD19+ cells. CD4+ cells were gated for T-bet+FoxP3+ and GATA3+ cells. Ki-67 was used to determine the amount of proliferating cells and for used after gating for living/dead cells, for CD4+ cells and for CD19+ cells.

Figure 10. FACS profiles and gating performed on CD4+ T cells. All samples were gated for Lymphocytes, singlets, live/dead and CD4 positive cells. Remained population were gated separately for T-bet, GATA3 and FoxP3 positive cells. Ki-67 gating was performed for live/dead cells and for CD4 positive and CD19 positive cells.

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Supplementary information II-Cytokine measurements

Supernatant from BMDCs and BMBs 20 hoursCo-cultures with BMDCs and BMBs that were stimulated for 20 hours were measured. Also cultures with CD4+T cells were measured. The first set of figures represent BMBs stimulated for 20 hours with probiotics.

Figure 11. Cytokine levels of IL-2 measured in the supernatant of BMB cell cultures. Average values and the standard deviation is shown in the graph. Average values were based on ten samples and the experiment was performed twice.

Figure 12. Cytokine levels of IL-6 measured in the supernatant of BMB cell cultures. Average values and the standard deviation is shown in the graph. Average values were based on ten samples and the experiment was performed twice.

Figure 13. Cytokine levels of IL-17A measured in the supernatant of BMB cell cultures. Average values and the standard deviation is shown in the graph. Average values were based on ten samples and the experiment was performed twice.

Figure 14. Cytokine levels of IL-4 measured in the supernatant of BMB cell cultures. Average values and the standard deviation is shown in the graph. Average values were based on ten samples and the experiment was performed twice.

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Cytokine measurements BMDCsCytokine were also measured for the cell cultures containing BMDCs. The second set of figures shows cytokines levels (pg/ml) measured in the supernatant of BMDCs.

Figure 15. Cytokine levels of TNF measured in supernatant of BMDC cell cultures. The average values and the standard deviation was shown in the figure. This value was based on ten samples obtained in from two experiments.

Figure 16. Cytokine levels of MCP-1 measured in supernatant of BMDC cell cultures. The average values and the standard deviation was shown in the figure. This value was based on ten samples obtained in from two experiments.

Figure 17.Cytokine levels of IL-10 measured in supernatant of BMDC cell cultures. The average values and the standard deviation was shown in the figure. This value was based on ten samples obtained in from two experiments.

Figure 18.Cytokine levels of IL-6 measured in supernatant of BMDC cell cultures. The average values and the standard deviation was shown in the figure. This value was based on ten samples obtained in from two experiments.

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Supernatant of co-cultures of BMDCs and BMBsCo-cultures of BMDCs and BMBs were stimulated for 20 hours. Supernatant was collected to measure cytokine levels. The next set of figures represents the results of the cytokines measured.

Figure 19. Cytokines levels measured of TNF in the supernatant from cell cultures of BMDCs and BMBs. Each values measured was given in the figure as well as the average values and the standard deviation.

Figure 20.Cytokines levels measured of MCP-1 in the supernatant from cell cultures of BMDCs and BMBs. Each values measured was given in the figure as well as the average values and the standard deviation.

Figure 21. Cytokines levels measured of IL-10 in the supernatant from cell cultures of BMDCs and BMBs. Each values measured was given in the figure as well as the average values and the standard deviation.

Figure 22. Cytokines levels measured of IL-6 in the supernatant from cell cultures of BMDCs and BMBs. Each values measured was given in the figure as well as the average values and the standard deviation.

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Figure 23.Cytokines levels measured of IL-17A in the supernatant from cell cultures of BMDCs and BMBs. Each values measured was given in the figure as well as the average values and the standard deviation.

Figure 24.Cytokines levels measured of IL-10 in the supernatant from cell cultures of BMDCs and BMBs. Each values measured was given in the figure as well as the average values and the standard deviation.

Figure 25.Cytokines levels measured of IL-4 in the supernatant from cell cultures of BMDCs and BMBs. Each values measured was given in the figure as well as the average values and the standard deviation.

Figure 26. Cytokines levels measured of IL-2 in the supernatant from cell cultures of BMDCs and BMBs. Each values measured was given in the figure as well as the average values and the standard deviation.

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Supernatant of stimulated CD4+ T cellsCo-cultures of BMBs, BMDCs and CD4+ T cells were performed. Surface markers were measured but also cytokines. Below are all cytokines measured with T cell polarization control experiment.

Figure 27. Cytokine levels of IL-10 were measured with the mouse Th1/Th2/Th17 Kit. CD4+ Tcells were stimulated four days with interleukins. Two samples were measured per condition tested and the experiment was performed only once.

Figure 28. Levels of IFN-γ were measured with the mouse Th1/Th2/Th17 Kit. CD4+ Tcells were stimulated four days with interleukins. The figure shows the cytokine level of every sample that was measured (N=2).

Figure 29. IL-17A cytokine levels were measured with the mouse Th1/Th2/Th17 Kit. CD4+ Tcells were stimulated four days with interleukins. The figure shows the cytokine level of every sample that was measured (N=2).

Figure 30. Levels of IL-2 were measured with mouse Th1/Th2/Th17 Kit CD4+ Tcells were stimulated for four days with interleukins. The figure shows the cytokine level of every sample that was measured. Figure shows the cytokine level of every sample measured (N=2).

Figure 31. IL-4 cytokine levels were measured with the mouse Th1/Th2/Th17 Kit. CD4+ Tcells were stimulated four days with interleukins. The figure shows the

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cytokine level of every sample that was measured (N=2).

Figure 32. Cytokine levels of IL-6 were measured with the mouse Th1/Th2/Th17 Kit. CD4+ Tcells were stimulated four days with interleukins. The figure shows the cytokine level of every sample that was measured (N=2).

Figure 33. Cytokine levels of TNF were measured with the mouse Th1/Th2/Th17 Kit. CD4+ Tcells were stimulated four days with interleukins. The figure shows the cytokine level of every sample that was measured (N=2).

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Supplementary information III- Cryopreservation

The effect of cryopreservation on differentiation and maturation of BMDCsFor practical reasons bone marrow cells obtained from mice were frozen in cryovials. Fresh bone marrow (fBM) and cryopreserved bone marrow (cBM) cells were cultured with GM-CSF and stimulated with LPS and after 8 days the development of the different BMDC populations was analyzed by flow cytometry. Examples of the gating performed on FACS profiles are shown in figure 7. Every sample was gated for singlets (FCS-A vs FCS-H) before gating the different BMDC populations in the figure.

Figure 42A shows the cell amounts of the mature, immature and precursor BMDC populations of NMRI mice. Figure 42B shows the percentages of the different BMDC populations of Black 6 mice. In both figures stimulated fBM shows a decrease in the percentage of precursor BMDCs, compared to the unstimulated fBM. Stimulated fBM also shows an increase in the percentage of immature BMDCs, compared to the unstimulated fBM. All stimulated BM cells were able to form mature BMDCs, but only for Black6 fBM the mature BMDC population increases significantly. Another remarkable difference between cBM from both mice strains was the percentages of precursor BMDCs. In NMRI mice this percentage is much higher compared to Black 6.

Figure 34. BMDCs derived from freshly isolated BM and from cryopreserved BM. NMRI and B6 mice strains were tested. BMDC populations were measured with FACS and populations were gated for singlets and gating of precursor, immature and mature BMDCs as shown in figure 1. The different BMDC populations in the graph represent the average values (n=3). The experiment was performed once. A) BM isolated freshly from C57Bl/6Rjj mice and cryopreserved at liquid nitrogen. B) BM isolated freshly from NMRI mice and cryopreserved at liquid nitrogen.

Freezing of bone marrow leads to increased population of precursor cellsWhen comparing both mice strains it was remarkable that cBM cell cultures induce larger mature BMDC populations upon stimulation compared to the fBM. fBM contains a larger variety of cell types compared to the cBM. Freezing of cellular tissue affect cells that are not robust, either by ice crystals formed or by using DMSO [50, 59]. In case of bone marrow, hematopoietic stem cells are the most robust cells, while cells like granulocytes are not and will eventually die upon freezing [60]. All our BMDC cultures did start with the same amount of cells per well. In the cBM the portion of stem cells that will develop into BMDCs was larger compared to the freshly harvested cell tissues and this did lead to a larger mature BMDC population.

Another remarkable result was the quantity of precursor BMDCs between the different mice strains. One of the explanations could be that our experiment was performed once, with only three replicates. Also the age between the two mice differs; Black6 mice were 8-12 weeks and NMRI mice were 26 weeks old. But there is not a clear explanation for this finding, literature we found did not underpin our findings.

Most importantly, bone marrow cells stored in cryovials were able to form mature BMDCs. F.M. Marim [59] used bone-marrow derived cells and froze them in cryovials using DMSO. They concluded that fBM and cBM cells equally respond to LPS and also maintain differentiation competence over time. Another article also confirms that cryopreservation of human iBMDCs does not affect expression of maturation markers [50]. Concluded; cryopreservation does not affect differentiation and maturation of BMDCs.

Supplementary information IV- IL-3 stimulation of BMDCs Effect of IL-3 on BMDCsTo ensure survival of BMBs after stimulation and during co-culture with BMDCs and CD4+ T cells, IL-3 needs to be added to the medium. We tested if IL-3 may affect the immune response of BMDCs by adding IL-3 to BMDCs after 7 days of in vitro culture. The results in figure 43 summarize the data. The data suggest that BMDCs that were not stimulated and BMDCs that were stimulated with IL-3 show similar quantities of the different BMDC populations.

Figure 353. BMDCs derived from freshly isolated BM and from male B6 mice (n=5). Populations were gated for singlets. The figure represents average values of the different BMDC populations. Gating was performed as shown in figure 1. Every condition was tested in duplicate and the experiment was performed once.

IL-3 has no effect on maturation of BMDCsThe cell quantity of the different BMDC populations of the negative control was virtually equal compared with the IL-3 stimulated BMDCs. In other words, IL-3 does not induce maturation of BMDCs. Literature confirms that generation of BMDCs was not affected by IL-3 [61]. However, in BM cultures with IL-3, BMDC develop together with mast cells [62]. Also protocols exist using IL-3 to generate BMDC precursors from murine hematopoietic progenitor cells [63]. IL-3 may induce differentiation of BMDCs, but activated T cells also produce IL-3 which may enhance BMDC differentiation [10, 46]. To prevent development of mast cells, but ensure survival of BMBs IL-3 will be added to the co-culture with BMDCs, BMBs and CD4+ T cells when we start with stimulation.

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Supplementary information V- Salmonella stimulation of BMDCsStimulation of BMDC with salmonellaTo investigate if there are differences in immune responses between probiotic bacteria and non-probiotic bacteria, BMDCs are stimulated with salmonella strain SL3261. According to literature, this salmonella strain is able to rapidly kill BMDCs [64-66]. To solve this problem we will also use a salmonella mutant called ΔsipB, which is used in literature before[65]. In this strain the sipB gene is replaced by a kanamycin resistance gene.

Cultivation of salmonella Strain SL3261 and SL3261 ΔsipB were obtained from a glycerol stock at -80°C and streaked out on Brilliant Green plates. The plates were put overnight in an incubator at 37°C. The next day a single colony from the plates was picked and put in liquid LB for SL3261 and liquid LB containing 15 µg/ml kanamycin for SL3261 ΔsipB and put back overnight at 37°C. The day after, BMDCs were washed with RPMI medium without pen/strep and 5*10^7, 5*10^6 or 5*10^5, bacteria (CFU) were added to wells containing BMDCs. After one hour at 37 °C the bacteria were washed away with RPMI medium with 50 ng/ml gentamicin. Another hour at 37°C and the medium was replaced with complete culture medium containing 20 µg/ml gentamicin. Analysis was done after overnight culture with flow cytometry.

Strain SL3261 allows less BMDCs to mature compared to SL3261 SipBΔExtracellular membrane molecules were measured via flow cytometry. Figure 44 below shows an example of the gating used of the conditions tested and the response of BMDCs on the different salmonella strains.

Figure 36. Flow cytometer figures shows gating performed and stimulation of BMDCs with A) salmonella mutant strain SL3261ΔsipB (5*105 CFU) and with B) salmonella strain SL3261 (5*105 CFU). BMDC populations were divided into precursor, immature and mature BMDCs.

The figure above shows that SL3261 strain lead to less mature BMDCs compared to the mutant strain. Most notable is the difference in quantity of mature BMDCs. The quantity of mature BMDCs is smaller when BMDCs were treated with SL3261, compared to ΔSipB. Figure 45 shows an overview of all different conditions tested.

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Figure 37. Average populations of BMDCs stimulated with strain sl3261 or sl3261 ΔsipB. Average values (± SD) are based on samples amounts varying 2-5 and on three experiments. Figure A) Populations of BMDCs stimulated with SL3261. Figure B) Populations of BMDCs stimulated with SL3261 ΔsipB.

Figure 44 shows the mature, immature and precursor populations of BMDCs. Stimulation was done with 100 ng/ml LPS, 0 ng/ml LPS and different CFU of SL3261 or with SL3261 ΔSipB. As been indicated in the FACS profile in figure 12, the amount of mature BMDCs treated with ΔSipB is larger compared to BMDCs treated with SL3261. This difference was in all concentrations tested significant (P<0.05) except SL3261 105 CFU. If we compared same CFU of SL3261 and ΔSipB with each other, the P-values of the mature BMDCs tested were all significant (P<0.05).

Salmonella SL3261 SipB is not able to kill BMDCs rapidlyΔWhen salmonella get into contact with immature BMDC, the BMDCs quickly respond by taking up the antigen and presenting it on the surface. Maturation of BMDCs is characterized by upregulation of surface markers including CD80, CD86, MHC-I and MHC-II occurs, which is also shown in figure 45 [64, 66]. The results in figure 13 above show that salmonella strain SL3261 does not cause maturation of BMDCs. This is caused by the ability of SL3261 to kill BMDCs within a few hours and is also confirmed by literature [65, 66]. Literature also describes a mutation in SL3261 that prevents salmonella from killing BMDCs [65]. Our results show that when BMDCs are stimulated with the mutant strain SL3261 ΔsipB, 15-20% of the entire BMDC population becomes mature. Concluding, the mutation in salmonella strain ΔSipB does not kill BMDCs and allows BMDCs to reach a mature stage. Salmonella mutant Δ sipB may be used in future experiments where BMDCs are stimulated with this mutant and co-cultured with CD4+ T cells. In this way it may become clearer if there are differences in immune response between probiotic bacteria and non-probiotic bacteria.

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Supplementary Information VI- CD4+ T cell differentiationTesting the effect of CD4+ T cell differentiationTo test the proliferation and differentiation of the CD4+ T cells a test experiment with CD4+ T cells only was performed. All CD4+ T cells were cultured with anti-CD3 (0.5 µg/ml) and anti-CD28 (1 µg/ml) and tested for their proliferation capacity by adding different mixture of antibodies. For Th1 polarization IFN-γ (50 ng/ml) anti-IL4 (10 µg/ml); for Th2 skewing IL-4 (50 ng/ml) and anti-INF-γ (5 µg/ml); for Th17 skewing IL-10 (1 µg/ml), anti-IFN-γ (5 µg/ml), anti-IL4 (10 µg/ml) were added to test differentiation towards Th2, Th17 and Th1 cells. After 4 days, FACS analysis was performed on extracellular and intracellular markers. Each sample obtained was gated for singlets, lymphocytes, and CD4+ T cells. Figure 10 shows an example of the gating that was applied.

Figure 38. The graph shows the polarization of CD4+ T cells. Values in the graph were based on mean of two samples. Experiment was performed once. Of every condition tested the quantity of FoxP3, T-bet and GATA3 positive cells were given.

Figure 46 above shows different conditions tested for T cell polarization. T cells stimulated with CD28 and CD3 were considered as a positive control and T cells only stimulated with CD3 were considered as negative control, although this is not entirely true. The quantity of FoxP3 positive cells is high compared to the T-bet and GATA3 positive cells. This is seen in all conditions tested. For Th2 and Treg polarization the FoxP3 population is significantly higher compared to both controls added (P<0.05). GATA3 positive and T-bet positive cell quantity different compared to the controls and values were also not significant.

Most cytokines were measured at CD4+ T cells used for Th1 polarizationCytokine assays may show if cytokines were released in the supernatant. Cytokines of the CD4+ T cells were measured. Based on the results above, we do not expect to see upregulation of cytokines involved in inflammatory responses (IL-12, TNF, IL-6), but expect to measure cytokines involved in regulatory immune responses (IL-10). All cytokines measured were given in supplementary information.

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Table 4. Average levels of cytokines measured. Values were based on two samples and the experiment was performed only once.

T cell polarization

IL-10 (pg/ml)

IL-2 (pg/ml)

IFN (pg/ml)

IL-6 (pg/ml)

IL-17A (pg/ml)

IL-4 (pg/ml)

TNF (pg/ml)

Th1 49.0 424.9 6604.3 ND 36.6 ND 159.4Th2 ND 4.5 1.0 ND 0.5 3282.4 18.4Treg 3209.1 3.1 0.4 0.2 0.9 0.3 13.2anti-CD3+CD28 228.0 2718.3 1129.2 4.9 96.1 10.5 327.3anti-CD3 83.0 12.7 87.4 3.3 58.5 2.6 46.3

For Th1 polarization was the following cytokines measured: TNF (170 pg/ml), IFN-γ, IL-17A (40 pg/ml) and IL-2 (500 pg/ml). IFN-γ was added by us to the wells. The production of other cytokines suggests that the polarization towards Th1 was successful. The production of IL-6 and IL-2 indicated that also Treg cells were developed. For Th2 was only IL-4 measured (3300 pg/ml). This cytokine was added by us. Active Th2 cells also produce IL-5 and IL-13, we did not measure these cytokines and this makes it difficult to say that Th2 polarization succeeded or failed. For Treg were cytokine levels of IL-10 measured. This cytokine was added by us. Adding of IL-10 should leads to Th17 and Treg differentiation. IL-2 and TGF-β are needed for Treg development and IL-17A for Th17 development. IL-2 and IL-17A were not detected in the supernatant. For the positive control were levels of TNF (350 pg/ml), IFN-γ (1800 pg/ml), IL-17A (100 pg/ml), IL-2 (3000 pg/ml) and IL-6 (5 pg/ml) measured. Adding anti-CD3 and CD28 leads to an inflammatory response of Tcells and this is clearly visible in the positive control. For the negative control were levels of IL-17A (70 pg/ml) and IL-6 (3.5 pg/ml) measured. These cytokines were involved in Treg responses. Most upregulation of cytokines were found for the positive control and in lesser amount for the negative control.

Th1 and Treg polarization did occur, but not Th2 polarizationThe results of the surface markers did not show a strong Th polarization. Only upregulation of FoxP3 was convincing and significant. For GATA3 and T-bet populations no upregulation was observed. But the cytokine bead assay does show that Th1 polarization took place as TNF, IFN-γ, IL-17A and IL-2 cytokines was measured. For the Treg population was only IL-10 measured and for Th2 was only IL-4 measured. Concluded, polarization for Th1 and Treg cells did occur and does prove that our CD4+ T cells were functioning properly. Polarization for Th2 was not very convincing. An explanation could be that literature describes that BMDCs are able to polarize CD4+ T cells [61]. The lack of BMDCs could explain the poor polarization for th2. Another explanation of the poor polarization could be the lack of a true negative control. Our negative control received α-CD3, which can also activate CD4+ T cells [67].

Also Ki-67 values were low, indicating the T-cells were not proliferating at the moment we measured. This was caused by the fact that most T cells were dead at the time of measurement. The high death rate could be caused by the lack of (anti- apoptotic) signals T cells normally get from other immune cells that prevent T cell apoptosis. The ratio of T cells we used was not tested beforehand. It could be the medium volume was too high and the cell density was too low for T cells to receive proper signals needed to keep them alive.

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