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The opportunistic fungal pathogen Candida albicans frequently produces genetically altered variants to adapt to environmental changes and new host niches in the course of its life-long association with the human host. Gain-of-function mutations in zinc cluster transcription factors, which result in the constitutive upregulation of their target genes, are a common cause of acquired resistance to the widely used antifungal drug fluconazole, especially during long-term therapy of oropharyngeal candidiasis. In this study, we investigated if C. albicans also can develop resistance to the antimicrobial peptide histatin 5, which is secreted in the saliva of humans to protect the oral mucosa from pathogenic microbes. As histatin 5 has been shown to be transported out of C. albicans cells by the Flu1 efflux pump, we screened a library of C. albicans strains that contain artificially activated forms of all zinc cluster transcription factors of this fungus for increased FLU1 expression. We found that a hyperactive Mrr1, which confers fluconazole resistance by upregulating the multidrug efflux pump MDR1 and other genes, also causes FLU1 overexpression. Similarly to the artificially activated Mrr1, naturally occurring gain-of-function mutations in this transcription factor also caused FLU1 upregulation and increased histatin 5 resistance. Surprisingly, however, Mrr1-mediated histatin 5 resistance was mainly caused by the upregulation of MDR1 instead of FLU1, revealing a previously unrecognized function of the Mdr1 efflux pump. Fluconazole-resistant clinical C. albicans isolates with different Mrr1 gain-of-function mutations were less efficiently killed by histatin 5, and this phenotype was reverted when MRR1 was deleted. Therefore, antimycotic therapy can promote the evolution of strains that, as a consequence of drug resistance mutations, simultaneously have acquired increased resistance against an innate host defense mechanism and are thereby better adapted to certain host niches.
Many pathogenic bacteria utilize specialized secretion systems to deliver proteins called effectors into eukaryotic cells for manipulation of host pathways. The vast majority of known effector targets are host proteins, whereas a potential targeting of host nucleic acids remains little explored. There is only one family of effectors known to target DNA directly, and effectors binding host RNA are unknown. Here, we take a two-pronged approach to search for RNA-binding effectors, combining biocomputational prediction of RNA-binding domains (RBDs) in a newly assembled comprehensive dataset of bacterial secreted proteins, and experimental screening for RNA binding in mammalian cells. Only a small subset of effectors were predicted to carry an RBD, indicating that if RNA targeting was common, it would likely involve new types of RBDs. Our experimental evaluation of effectors with predicted RBDs further argues for a general paucity of RNA binding activities amongst bacterial effectors. We obtained evidence that PipB2 and Lpg2844, effector proteins of Salmonella and Legionella species, respectively, may harbor novel biochemical activities. Our study presenting the first systematic evaluation of the RNA-targeting potential of bacterial effectors offers a basis for discussion of whether or not host RNA is a prominent target of secreted bacterial proteins.
Analysis of host microRNA function uncovers a role for miR-29b-2-5p in Shigella capture by filopodia
(2017)
MicroRNAs play an important role in the interplay between bacterial pathogens and host cells, participating as host defense mechanisms, as well as exploited by bacteria to subvert host cellular functions. Here, we show that microRNAs modulate infection by Shigella flexneri, a major causative agent of bacillary dysentery in humans. Specifically, we characterize the dual regulatory role of miR-29b-2-5p during infection, showing that this microRNA strongly favors Shigella infection by promoting both bacterial binding to host cells and intracellular replication. Using a combination of transcriptome analysis and targeted high-content RNAi screening, we identify UNC5C as a direct target of miR-29b-2-5p and show its pivotal role in the modulation of Shigella binding to host cells. MiR-29b-2-5p, through repression of UNC5C, strongly enhances filopodia formation thus increasing Shigella capture and promoting bacterial invasion. The increase of filopodia formation mediated by miR-29b-2-5p is dependent on RhoF and Cdc42 Rho-GTPases. Interestingly, the levels of miR-29b-2-5p, but not of other mature microRNAs from the same precursor, are decreased upon Shigella replication at late times post-infection, through degradation of the mature microRNA by the exonuclease PNPT1. While the relatively high basal levels of miR-29b-2-5p at the start of infection ensure efficient Shigella capture by host cell filopodia, dampening of miR-29b-2-5p levels later during infection may constitute a bacterial strategy to favor a balanced intracellular replication to avoid premature cell death and favor dissemination to neighboring cells, or alternatively, part of the host response to counteract Shigella infection. Overall, these findings reveal a previously unappreciated role of microRNAs, and in particular miR-29b-2-5p, in the interaction of Shigella with host cells.
RNA-binding proteins (RBPs) have been established as core components of several post-transcriptional gene regulation mechanisms. Experimental techniques such as cross-linking and co-immunoprecipitation have enabled the identification of RBPs, RNA-binding domains (RBDs) and their regulatory roles in the eukaryotic species such as human and yeast in large-scale. In contrast, our knowledge of the number and potential diversity of RBPs in bacteria is poorer due to the technical challenges associated with the existing global screening approaches. We introduce APRICOT, a computational pipeline for the sequence-based identification and characterization of proteins using RBDs known from experimental studies. The pipeline identifies functional motifs in protein sequences using position-specific scoring matrices and Hidden Markov Models of the functional domains and statistically scores them based on a series of sequence-based features. Subsequently, APRICOT identifies putative RBPs and characterizes them by several biological properties. Here we demonstrate the application and adaptability of the pipeline on large-scale protein sets, including the bacterial proteome of Escherichia coli. APRICOT showed better performance on various datasets compared to other existing tools for the sequence-based prediction of RBPs by achieving an average sensitivity and specificity of 0.90 and 0.91 respectively. The command-line tool and its documentation are available at https://pypi.python.org/pypi/bio-apricot.