Transcriptional network inference and master regulator analysis of the response to ribosome-inactivating proteins in leukemia cells

Gene-regulatory networks reconstruction has become a very popular approach in applied biology to infer and dissect functional interactions of Transcription Factors (TFs) driving a defined phenotypic state, termed as Master Regulators (MRs). In the present work, cutting-edge bioinformatic methods were applied to re-analyze experimental data on leukemia cells (human myelogenous leukemia cell line THP-1 and acute myeloid leukemia MOLM-13 cells) treated for 6 h with two different Ribosome-Inactivating Proteins (RIPs), namely Shiga toxin type 1 (400 ng/mL) produced by Escherichia coli strains and the plant toxin stenodactylin (60 ng/mL), purified from the caudex of Adenia stenodactyla Harms. This analysis allowed us to identify the common early transcriptional response to 28S rRNA damage based on gene-regulatory network inference and Master Regulator Analysis (MRA). Both toxins induce a common response at 6 h which involves inflammatory mediators triggered by AP-1 family transcriptional factors and ATF3 in leukemia cells. We describe for the first time the involvement of MAFF, KLF2 and KLF6 in regulating RIP-induced apoptotic cell death, while receptor-mediated downstream signaling through ANXA1 and TLR4 is suggested for both toxins.

Keywords: Bioinformatics; Gene regulatory network; Master regulator analysis; Plant toxin; Shiga toxin.