Abstract
Intravacuolar bacterial pathogens have evolved a variety of strategies to subvert host cell functions during infection. In the past two decades, cellular microbiology has focused on the interplay between bacterial proteins with host cell proteins, lipids and DNA. However, over the same period, small noncoding bacterial RNAs have emerged as central players in gene expression regulation and pathogenesis. Moreover, the translocation of microRNA-like sRNAs (miRNAs) from intracellular bacteria into the host cell cytoplasm to manipulate cellular functions has been recently reported. Using the izMiR miRNA detection algorithm, we bioinformatically identified sequences encoding candidate pre-miRNAs, and which were similar to human pre-miRNAs, in the genomes of several intravacuolar bacterial pathogens. To validate bioinformatics predictions, we immuno-precipitated the RNA-induced silencing complex (RISC) from RAW 264.7 murine macrophages infected or not by Brucella suis 1330. Following RNA extractions, samples from infected and non-infected cells were differentially analyzed by small RNA-Seq. This approach led to the identification of six RISC-associated transcripts specifically aligning with the B. suis genome, matching the izMiR-based predictions, and showing the characteristics expected for authentic miRNA. Among these, B. suis MIR6325 and MIR11484 are of particular interest, since bioinformatics analysis using the MR-microT algorithm led to the identification of highly-ranked candidate eukaryotic targets. Ongoing work is aiming at the experimental validation of host cell target mRNAs for miRNAs MIR6325 and MIR11484, using a RISC-Trap approach. In parallel, we are generating B. suis deletion mutants for several validated pre-miRNAs to evaluate their phenotypes and possible impact in the context of host cell infections by using next-generation sequencing, cellular microbiology, high-resolution microscopy and screening approaches. Our study will shed light on an emerging, yet poorly explored domain of host/pathogen interactions, and may help to identify targets for the development of new biomarkers and antimicrobials.
