ABSTRACT
Staphylococcus aureus RsaG is a 3'-untranslated region (3'UTR) derived sRNA from the conserved uhpT gene encoding a glucose-6-phosphate (G6P) transporter expressed in response to extracellular G6P. The transcript uhpT-RsaG undergoes degradation from 5'- to 3'-end by the action of the exoribonucleases J1/J2, which are blocked by a stable hairpin structure at the 5'-end of RsaG, leading to its accumulation. RsaG together with uhpT is induced when bacteria are internalized into host cells or in the presence of mucus-secreting cells. Using MS2-affinity purification coupled with RNA sequencing, several RNAs were identified as targets including mRNAs encoding the transcriptional factors Rex, CcpA, SarA, and the sRNA RsaI. Our data suggested that RsaG contributes to the control of redox homeostasis and adjusts metabolism to changing environmental conditions. RsaG uses different molecular mechanisms to stabilize, degrade, or repress the translation of its mRNA targets. Although RsaG is conserved only in closely related species, the uhpT 3'UTR of the ape pathogen S. simiae harbors an sRNA, whose sequence is highly different, and which does not respond to G6P levels. Our results hypothesized that the 3'UTRs from UhpT transporter encoding mRNAs could have rapidly evolved to enable adaptation to host niches.
Subject(s)
Antiporters/metabolism , Monosaccharide Transport Proteins/metabolism , RNA, Small Untranslated/genetics , Staphylococcal Infections/microbiology , Staphylococcus aureus/genetics , Transcription Factors/metabolism , Untranslated Regions/genetics , Adaptation, Physiological , Antiporters/genetics , Bacterial Proteins/genetics , Bacterial Proteins/metabolism , Biological Transport , Gene Expression Regulation, Bacterial , Glucose-6-Phosphate/metabolism , Homeostasis , Monosaccharide Transport Proteins/genetics , Oxidation-Reduction , RNA Stability , Staphylococcus aureus/pathogenicity , Staphylococcus aureus/physiology , Transcription Factors/geneticsABSTRACT
Pathogenic bacteria must rapidly adapt to ever-changing environmental signals resulting in metabolism remodeling. The carbon catabolite repression, mediated by the catabolite control protein A (CcpA), is used to express genes involved in utilization and metabolism of the preferred carbon source. Here, we have identified RsaI as a CcpA-repressed small non-coding RNA that is inhibited by high glucose concentrations. When glucose is consumed, RsaI represses translation initiation of mRNAs encoding a permease of glucose uptake and the FN3K enzyme that protects proteins against damage caused by high glucose concentrations. RsaI also binds to the 3' untranslated region of icaR mRNA encoding the transcriptional repressor of exopolysaccharide production and to sRNAs induced by the uptake of glucose-6 phosphate or nitric oxide. Furthermore, RsaI expression is accompanied by a decreased transcription of genes involved in carbon catabolism pathway and an activation of genes involved in energy production, fermentation, and nitric oxide detoxification. This multifaceted RNA can be considered as a metabolic signature when glucose becomes scarce and growth is arrested.
Subject(s)
Bacterial Proteins/metabolism , Biofilms/growth & development , Glucose/deficiency , RNA, Bacterial/genetics , RNA, Small Untranslated/genetics , Repressor Proteins/metabolism , Staphylococcus aureus/metabolism , Bacterial Proteins/genetics , Binding Sites , Biofilms/drug effects , Gene Expression Regulation, Bacterial , Glucose/administration & dosage , Metabolic Networks and Pathways , Protein Biosynthesis , RNA, Messenger/genetics , RNA, Messenger/metabolism , Repressor Proteins/genetics , Ribosomes/metabolism , Staphylococcus aureus/drug effects , Staphylococcus aureus/genetics , Staphylococcus aureus/growth & development , Sweetening Agents/administration & dosage , TranscriptomeABSTRACT
L. monocytogenes causes listeriosis, a foodborne disease that is particularly dangerous for immunocompromised individuals and fetuses. Several virulence factors of this bacterial pathogen belong to a family of leucine-rich repeat (LRR)-containing proteins called internalins. Among these, InlP is known for its role in placental infection. We report here a function of InlP in mammalian cell nucleus organization. We demonstrate that bacteria do not produce InlP under in vitro culture conditions. When ectopically expressed in human cells, InlP translocates into the nucleus and changes the morphology of nuclear speckles, which are membrane-less organelles storing splicing factors. Using yeast two-hybrid screen, immunoprecipitation and pull-down experiments, we identify the tumor suppressor and splicing factor RBM5 as a major nuclear target of InlP. InlP inhibits RBM5-induced cell death and stimulate the formation of RBM5-induced nuclear granules, where the SC35 speckle protein redistributes. Taken together, these results suggest that InlP acts as a nucleomodulin controlling compartmentalization and function of RBM5 in the nucleus and that L. monocytogenes has developed a mechanism to target the host cell splicing machinery.
Subject(s)
RNA-Binding Proteins , Tumor Suppressor Proteins , Virulence Factors , Humans , Bacteria/metabolism , Cell Cycle Proteins/metabolism , Cell Nucleus/metabolism , DNA-Binding Proteins/metabolism , RNA Splicing Factors , RNA-Binding Proteins/metabolism , Tumor Suppressor Proteins/metabolism , Virulence Factors/metabolism , Listeria monocytogenesABSTRACT
Discovered in the 1980s, small regulatory RNAs (sRNAs) are now considered key actors in virtually all aspects of bacterial physiology and virulence. Together with transcriptional and translational regulatory proteins, they integrate and often are hubs of complex regulatory networks, responsible for bacterial response/adaptation to various perceived stimuli. The recent development of powerful RNA sequencing technologies has facilitated the identification and characterization of sRNAs (length, structure and expression conditions) and their RNA targets in several bacteria. Nevertheless, it could be very difficult for non-experts to understand the advantages and drawbacks related to each offered option and, consequently, to make an informed choice. Therefore, the main goal of this review is to provide a guide to navigate through the twists and turns of high-throughput RNA sequencing technologies, with a specific focus on those applied to the study of sRNAs. This article is part of a Special Issue entitled: RNA and gene control in bacteria edited by Dr. M. Guillier and F. Repoila.
Subject(s)
RNA, Bacterial/chemistry , RNA, Bacterial/metabolism , RNA, Small Untranslated/chemistry , RNA, Small Untranslated/metabolism , Sequence Analysis, RNA , Genome, Bacterial , High-Throughput Nucleotide Sequencing , Nucleic Acid ConformationABSTRACT
Staphylococcus aureus is a Gram-positive major human pathogen involved in a wide range of human infectious diseases (from minor skin infections to septicemia, endocarditis or toxic shock syndrome). The treatment of S. aureus infections is very challenging due to the emergence of multiple antibiotic-resistant isolates. The high diversity of clinical symptoms caused by S. aureus depends on the precise expression of numerous virulence factors and stress response pathways, which are tightly regulated at every level (transcriptional, posttranscriptional, translational, and posttranslational). During the last two decades, it has become evident that small regulatory RNAs (sRNAs) play a major role in fast adaptive responses, mainly by targeting mRNA translation. sRNAs act as antisense RNAs by forming noncontiguous pairings with their target mRNAs and their mechanisms of action vary according to the interaction site. To obtain a global and detailed view of the regulatory networks involved in the adaptive processes of S. aureus, we have adapted the MAPS approach to get individual sRNA targetomes. We also set up different strategies to validate MAPS results and establish sRNA regulatory activities. As this method has been first developed in Gram-negative bacteria, we provide here a protocol for its application in S. aureus and highlight underlying differences. Finally, we discuss several points that have been and could be further improved and provide a workflow file for the automatic analysis of the sequencing in Galaxy.