Nunez-Reza, K. J. | Search bioRxiv

bioRxiv2023

Logical model of human tolerogenic dendritic cells and their participation in autoimmune disease

Tolerogenic dendritic cells (tolDC) regulate the immune response, several clinical trials focused on autoimmune diseases use tolDC to promote immune tolerance response and Treg activation. Here we built a logical model for the tolerization cellular process of dendritic cells using IL10. By combining literature knowledge, microarray gene expression, and key tolDC markers, we ensembled a logical model that describes the obtention of tolDC using the IL10 signaling cascade that spawns the most tolerogenic phenotype. The model uses IL10 as input and the signaling cascade that trigger seven transcription factors (TFs), three previously known TFs in the IL10 response (STAT3, NFKB, STAT6), and four were incorporated based on our gene expression analysis (IRF8, TCF7L2, CEBPB, and TFCP2L1). Using our model, we generated mutants in-silico and identified that even when IL10 is present the single mutants for TCF7L2, IRF8, TFCP2L1, and STAT3 were not able to reach a tolDC stable state, highlighting the relevance of these TFs in the process. The current model sets a precedent that will help in the development of tolDC for future applications.

bioinformatics↗

bioRxiv2020

Logical modeling of dendritic cells in vitro differentiation from human monocytes unravels novel transcriptional regulatory interactions

Dendritic cells are the major specialized antigen-presenting cells, thereby connecting innate and adaptive immunity. Because of their role in establishing adaptive immunity, they have been used as targets for immunotherapy. Monocytes can differentiate into dendritic cells in vitro in the presence of colony-stimulating factor 2 (CSF2) and interleukin 4 (IL4), activating four signalling pathways (MAPK, JAK/STAT, NFKB, and PI3K). However, the transcriptional regulation responsible for dendritic cell differentiation from monocytes (moDCs) remains unknown. By curating scientific literature on moDCs differentiation, we established a preliminary logical model that helped us identify missing information for the activation of genes responsible for this differentiation, including missing targets for key transcription factors (TFs). Using ChIP-seq and RNA-seq data from the Blueprint consortium, we defined active and inactive promoters, together with differentially expressed genes in monocytes, moDCs, and macrophages (which correspond to an alternative cell fate). We then used this functional genomic information to predict novel targets for the identified TFs. We established a second logical model integrating this information, which enabled us to recapitulate the main established facts regarding moDCs differentiation. Prospectively, the resulting model should be useful to develop novel immunotherapies based on moDCs regulatory network.

immunology↗