1. Role of Toll-Like Receptors in the recognition of probiotics by monocyte-derived dendritic cells. Martínez-Abad, Beatriz 1 ; Garrote, Jose A. 1,2 ; Vallejo-Díez, Sara 1 ; Montalvillo, Enrique 1 ; Escudero-Hernández, Celia 1 ; Bernardo, David 3 ; Vázquez, Enrique 4 ; Rueda, Ricardo 4 ; Arranz, Eduardo 1. 1.Mucosal Immunology Lab. Paediatrics and Immunology Department. University of Valladolid. IBGM-CSIC, Spain. 2. Research Unity. Hospital Clínico Universitario-IECSCYL, Valladolid, Spain. 3. Antigen Presentation Research Group. Imperial College London, St. Mark’s and Northwick Park Hospital. UK. 4. Discovery Technology Department Abbott Nutrition R&D, Granada, Spain e-mail:colli01@hotmail.com / bea_mar@ibgm.uva.es Introduction In this assay we have studied the effect of different probiotic and pathogen bacteria on one group of pattern recognition receptors (PPRs), the Toll-like receptors (TLRs), present in dendritic cells. TLRs are specific for pathogen-associated molecular patterns (PAMPs) and trigger different responses depending on stimuli. TLR2 and TLR4 are the most studied receptors for bacteria because of recognizing two majority compounds of bacterial wall, peptidoglycan and LPS respectively. To measure the way in which dendritic cells respond to different type of bacteria we have measured the changes on gene expression of TLRs pathway and its down-stream pathways using a RT-PCR array method. Material and Methods Ficoll and Percoll solution density gradient centrifugation MonocytesDendritic cells derived from monocytes (moDCs) Four probiotic strains from genus Lactobacillus (Group 4, 5, 6 and 7) and 2 from genus Bifidobacterium (Group 8 and 9). As pathogens controls we used Escherichia coli 0111 CECT 727, Salmonella typhimurium and Clostridium perfringens CECT 376 (Group 1, 2 and 3 respectively). As basal (Control Group) we used moDCs unstimulated. Harvest and keep cells onto Trizol ® untill their extraction. IL-4 (500U/ml) GMCSF (1000U/ml) Stimulation for 4 hours RNA extraction and cleaned up and Reverse Transcription Peripheral blood from 6 healthy donors The ACTB (β-actin) was selected as housekeeping. Changes in the transcriptional expression were estimated with the ∆∆CT method using basal condition as reference (Livak and Schmittgen 2001). 1 Results Gene Symbol Fold Regulation CCL210,6119 CD802,9459 CSF21056,1719 CSF31266,2631 CXCL107,3387 IFNA13,4806 IFNB16,1087 IFNG57,6998 IL1031,3454 IL12A2,7105 IL1A193,463 IL1B587,9418 IL229,0704 IL6388,7104 IL840,6665 IRAK211,6471 IRF12,3088 Gene Symbol Fold Regulation MAP2K310,8515 NFKB15,0323 NFKBIA5,5711 PELI15,1836 PTGS2590,6094 REL4,1434 RIPK210,8368 TLR22,4273 TLR75,2061 TNF44,3334 2 Gene Symbol Fold Regulation CSF2120,8161 CSF37,543 IFNG52,9298 IL102,856 IL1A5,6403 IL1B24,8188 IL28,5137 IL64,3657 IL84,0329 MAP2K33,1299 PTGS233,215 REL2,2535 TNF28,1654 Gene Symbol Fold Regulation CXCL10-21,8607 IFNB1-3,0923 3 Gene Symbol Fold Regulation CCL23,0323 CSF250,6936 CSF34,5232 IL103,2107 IL1A21,5333 IL1B35,136 IL64,5012 IL86,5173 IRAK22,412 MAP2K34,2772 PTGS223,4233 REL2,7255 TNF7,8538 Gene Symbol Fold Regulation CXCL10-6,8258 IFNA1-3,5326 IFNB1-28,9985 IL2-3,045 IRF1-2,9194 NFKB2-2,4778 NFKBIL1-2,5962 TICAM2-2,5273 Gene Symbol Fold Regulation CCL23,5973 CSF268,8851 CSF346,295 IL105,6801 IL1A13,0701 IL1B46,0762 IL613,6141 IL85,6081 IRAK22,8214 MAP2K35,3533 PTGS231,9635 TNF5,3719 Gene Symbol Fold Regulation CXCL10-4,1539 IFNA1-4,0655 IFNB1-19,0858 IKBKB-2,2394 IL12A-2,1917 IL2-2,1888 IRF1-3,5744 MAPK8-2,4137 NFKB2-2,0968 NFKBIL1-2,1841 TICAM2-2,9914 TOLLIP-2,0092 Gene Symbol Fold Regulation CCL211,5807 CSF2132,6047 CSF3292,1396 CXCL102,1221 IL1027,0685 IL1A51,0403 IL1B129,6176 IL6100,027 IL817,5964 IRAK25,2768 MAP2K34,5248 NFKB12,1695 NFKBIA3,0298 PTGS2105,1594 RIPK25,529 TLR22,8932 TNF11,9809 Gene Symbol Fold Regulation IFNB1-5,424 4 5 6 Gene Symbol Fold Regulation CCL22,3257 CSF272,8291 CSF37,7066 IL106,9872 IL1A22,2682 IL1B53,6656 IL616,0568 IL84,6569 MAP2K33,5618 PTGS225,5277 TNF18,3381 Gene Symbol Fold Regulation CXCL10-10,5161 IFNB1-9,8707 IL2-2,1033 IRF1-3,3142 MAPK8-2,0913 NFKB2-2,165 NFKBIL1-2,3649 RELA-2,2775 TICAM2-2,8438 7 Gene Symbol Fold Regulation CSF218,7006 IL1A4,4368 IL1B7,9621 IL82,5512 MAP2K32,5706 PTGS27,3443 TNF6,4423 Gene Symbol Fold Regulation CXCL10-222,6368 IFNA1-3,343 IFNB1-34,1568 IKBKB-2,578 IL12A-5,8398 IL2-2,8297 IRF1-3,2827 MAP2K4-2,378 NFKB2-3,313 NFKBIL1-2,0203 RELA-2,0651 TICAM2-2,0991 TOLLIP-2,0556 Gene Symbol Fold Regulation CSF217,9123 CSF32,3981 IL1A4,92 IL1B14,1869 IL62,2965 IL82,3493 MAP2K32,0338 PTGS210,218 TNF6,5127 8 Gene Symbol Fold Regulation CXCL10-89,3227 IFNB1-41,2893 IKBKB-2,2312 IL12A-2,9637 IRF1-3,5319 MAP2K4-2,1041 RELA-2,202 TICAM2-2,4988 TOLLIP-2,1489 Gene Symbol Fold Regulation CCL210,9988 CD804,2165 CSF291,1504 CSF3107,6358 CXCL106,435 IFNB12,4435 IFNG13,8084 IL1010,4676 IL1A106,0239 IL1B235,5998 IL23,2814 IL6196,1398 IL820,2413 IRAK211,5273 MAP2K312,649 NFKB14,1605 NFKBIA4,6945 Gene Symbol Fold Regulation PELI14,8596 PTGS2198,1842 REL3,1259 RIPK29,3557 TICAM22,8365 TLR23,4999 TLR74,7245 TNF15,3839 PATHOGENSPATHOGENS LACTOBACILLILACTOBACILLI BIFIDOBACTERIABIFIDOBACTERIA S. typhimuriumE. coliC. perfringens Fig. 1-9: volcano plot graphs of each stimulus (bacterium) compared with control condition (unstimulated moDCs) in which we can observe in X-axis Log2 (Fold Change (FC) of Group “bacterium” / FC of Control Group) and in Y-axis –Log10 of p-value. Only transcriptional changes with p ≤ 0.05 and ≥ 2 folds were included in the analysis. Values and plots in red represent up-regulation and values and plots in green represent down-regulation. Although, expression of TLR genes have hardly changed, we can observe differences in the NFκB, JNK/p38, JAK/STAT, Interferon Regulatory Factor (IRF) and Cytokine mediated signalling downstream pathways. Pathogen bacteria induce a different expression pattern as regards probiotics. Gram- bacteria trigger a great amount of genes belong to these routes and Gram+ bacteria, include C. perfringens, induce a down-regulation of TLR, adaptors and interacting proteins genes expression. We can observe that pathogens not present the same behaviour, C. perfringens down-regulates a great amount of genes, and in the dendogram it is located nearer to bifidobacteria. This decrease in certain genes is common to observed in dendritic cells stimulated with bifidobacteria. However, C. perfringens induces an increase on IFNG expression so high as the other pathogen controls. Regarding to probiotics, we observe that lactobacilli trigger lesser up-regulation and induce down-regulation of several genes expression. Among lactobacilli, we can observe that Group 6 produce the biggest activation of the assayed genes in dendritic cells and is located together with E. coli and S. typhimurium in the dendogram. Furthermore, bifidobacteria increase the expression of a few genes and down-regulate a great amount of genes, specially CXCL10 and IFNB1. This assay could help to understand the probiotic’s actions not only because they trigger a weak response, but also they work in an active way down-regulating specific genes. ACKNOWLEDGEMENTS: This work has been possible thanks to the financial support from Instituto de Salud Carlos III (PI10/01647), Junta de Castilla y León (Consejería de Educación, VA016A10-2), Beca FPI-Junta de Castilla y León, Beca FPI-UVA and Phadia España. Fig. 10: clustergram and dendogram analysis of genes whose expression were modified ± 2 fold change compared to the basal condition. Rows represent genes and columns represent condition. Conclusions 9