Sub-cellular mRNA localization modulates the regulation of gene expression by small RNAs in bacteria

A modular RNA interference system for multiplexed gene regulation

The rational design and realisation of simple-to-use genetic control elements that are modular, orthogonal and robust is essential to the construction of predictable and reliable biological systems of increasing complexity. To this effect, we introduce modular Artificial RNA interference (mARi), a rational, modular and extensible design framework that enables robust, portable and multiplexed post-transcriptional regulation of gene expression in Escherichia coli. The regulatory function of mARi was characterised in a range of relevant genetic contexts, demonstrating its independence from other genetic control elements and the gene of interest, and providing new insight into the design rules of RNA based regulation in E. coli, while a range of cellular contexts also demonstrated it to be independent of growth-phase and strain type. Importantly, the extensibility and orthogonality of mARi enables the simultaneous post-transcriptional regulation of multi-gene systems as both single-gene cassettes and poly-cistronic operons. To facilitate adoption, mARi was designed to be directly integrated into the modular BASIC DNA assembly framework. We anticipate that mARi-based genetic control within an extensible DNA assembly framework will facilitate metabolic engineering, layered genetic control, and advanced genetic circuit applications.

Riboregulation in bacteria: From general principles to novel mechanisms of the trp attenuator and its sRNA and peptide products

Gene expression strategies ensuring bacterial survival and competitiveness rely on cis- and trans-acting RNA-regulators (riboregulators). Among the cis-acting riboregulators are transcriptional and translational attenuators, and antisense RNAs (asRNAs). The trans-acting riboregulators are small RNAs (sRNAs) that bind proteins or base pairs with other RNAs. This classification is artificial since some regulatory RNAs act both in cis and in trans, or function in addition as small mRNAs. A prominent example is the archetypical, ribosome-dependent attenuator of tryptophan (Trp) biosynthesis genes. It responds by transcription attenuation to two signals, Trp availability and inhibition of translation, and gives rise to two trans-acting products, the attenuator sRNA rnTrpL and the leader peptide peTrpL. In Escherichia coli, rnTrpL links Trp availability to initiation of chromosome replication and in Sinorhizobium meliloti, it coordinates regulation of split tryptophan biosynthesis operons. Furthermore, in S. meliloti, peTrpL is involved in mRNA destabilization in response to antibiotic exposure. It forms two types of asRNA-containing, antibiotic-dependent ribonucleoprotein complexes (ARNPs), one of them changing the target specificity of rnTrpL. The posttranscriptional role of peTrpL indicates two emerging paradigms: (1) sRNA reprograming by small molecules and (2) direct involvement of antibiotics in regulatory RNPs. They broaden our view on RNA-based mechanisms and may inspire new approaches for studying, detecting, and using antibacterial compounds. This article is categorized under: RNA Interactions with Proteins and Other Molecules > Small Molecule-RNA Interactions RNA Interactions with Proteins and Other Molecules > RNA-Protein Complexes Regulatory RNAs/RNAi/Riboswitches > Regulatory RNAs.

mLoc-mRNA: predicting multiple sub-cellular localization of mRNAs using random forest algorithm coupled with feature selection via elastic net

BACKGROUND

Localization of messenger RNAs (mRNAs) plays a crucial role in the growth and development of cells. Particularly, it plays a major role in regulating spatio-temporal gene expression. The in situ hybridization is a promising experimental technique used to determine the localization of mRNAs but it is costly and laborious. It is also a known fact that a single mRNA can be present in more than one location, whereas the existing computational tools are capable of predicting only a single location for such mRNAs. Thus, the development of high-end computational tool is required for reliable and timely prediction of multiple subcellular locations of mRNAs. Hence, we develop the present computational model to predict the multiple localizations of mRNAs.

RESULTS

The mRNA sequences from 9 different localizations were considered. Each sequence was first transformed to a numeric feature vector of size 5460, based on the k-mer features of sizes 1-6. Out of 5460 k-mer features, 1812 important features were selected by the Elastic Net statistical model. The Random Forest supervised learning algorithm was then employed for predicting the localizations with the selected features. Five-fold cross-validation accuracies of 70.87, 68.32, 68.36, 68.79, 96.46, 73.44, 70.94, 97.42 and 71.77% were obtained for the cytoplasm, cytosol, endoplasmic reticulum, exosome, mitochondrion, nucleus, pseudopodium, posterior and ribosome respectively. With an independent test set, accuracies of 65.33, 73.37, 75.86, 72.99, 94.26, 70.91, 65.53, 93.60 and 73.45% were obtained for the respective localizations. The developed approach also achieved higher accuracies than the existing localization prediction tools.

CONCLUSIONS

This study presents a novel computational tool for predicting the multiple localization of mRNAs. Based on the proposed approach, an online prediction server "mLoc-mRNA" is accessible at http://cabgrid.res.in:8080/mlocmrna/ . The developed approach is believed to supplement the existing tools and techniques for the localization prediction of mRNAs.

Effects of spatial heterogeneity on bacterial genetic circuits

Intracellular spatial heterogeneity is frequently observed in bacteria, where the chromosome occupies part of the cell's volume and a circuit's DNA often localizes within the cell. How this heterogeneity affects core processes and genetic circuits is still poorly understood. In fact, commonly used ordinary differential equation (ODE) models of genetic circuits assume a well-mixed ensemble of molecules and, as such, do not capture spatial aspects. Reaction-diffusion partial differential equation (PDE) models have been only occasionally used since they are difficult to integrate and do not provide mechanistic understanding of the effects of spatial heterogeneity. In this paper, we derive a reduced ODE model that captures spatial effects, yet has the same dimension as commonly used well-mixed models. In particular, the only difference with respect to a well-mixed ODE model is that the association rate constant of binding reactions is multiplied by a coefficient, which we refer to as the binding correction factor (BCF). The BCF depends on the size of interacting molecules and on their location when fixed in space and it is equal to unity in a well-mixed ODE model. The BCF can be used to investigate how spatial heterogeneity affects the behavior of core processes and genetic circuits. Specifically, our reduced model indicates that transcription and its regulation are more effective for genes located at the cell poles than for genes located on the chromosome. The extent of these effects depends on the value of the BCF, which we found to be close to unity. For translation, the value of the BCF is always greater than unity, it increases with mRNA size, and, with biologically relevant parameters, is substantially larger than unity. Our model has broad validity, has the same dimension as a well-mixed model, yet it incorporates spatial heterogeneity. This simple-to-use model can be used to both analyze and design genetic circuits while accounting for spatial intracellular effects.

RNA localization in prokaryotes: Where, when, how, and why

Only recently has it been recognized that the transcriptome of bacteria and archaea can be spatiotemporally regulated. All types of prokaryotic transcripts-rRNAs, tRNAs, mRNAs, and regulatory RNAs-may acquire specific localization and these patterns can be temporally regulated. In some cases bacterial RNAs reside in the vicinity of the transcription site, but in many others, transcripts show distinct localizations to the cytoplasm, the inner membrane, or the pole of rod-shaped species. This localization, which often overlaps with that of the encoded proteins, can be achieved either in a translation-dependent or translation-independent fashion. The latter implies that RNAs carry sequence-level features that determine their final localization with the aid of RNA-targeting factors. Localization of transcripts regulates their posttranscriptional fate by affecting their degradation and processing, translation efficiency, sRNA-mediated regulation, and/or propensity to undergo RNA modifications. By facilitating complex assembly and liquid-liquid phase separation, RNA localization is not only a consequence but also a driver of subcellular spatiotemporal complexity. We foresee that in the coming years the study of RNA localization in prokaryotes will produce important novel insights regarding the fundamental understanding of membrane-less subcellular organization and lead to practical outputs with biotechnological and therapeutic implications. This article is categorized under: RNA Export and Localization > RNA Localization Regulatory RNAs/RNAi/Riboswitches > Regulatory RNAs RNA Interactions with Proteins and Other Molecules > Protein-RNA Interactions: Functional Implications.

Spatiotemporal Organization of the E. coli Transcriptome: Translation Independence and Engagement in Regulation

RNA localization in eukaryotes is a mechanism to regulate transcripts fate. Conversely, bacterial transcripts were not assumed to be specifically localized. We previously demonstrated that E. coli mRNAs may localize to where their products localize in a translation-independent manner, thus challenging the transcription-translation coupling extent. However, the scope of RNA localization in bacteria remained unknown. Here, we report the distribution of the E. coli transcriptome between the membrane, cytoplasm, and poles by combining cell fractionation with deep-sequencing (Rloc-seq). Our results reveal asymmetric RNA distribution on a transcriptome-wide scale, significantly correlating with proteome localization and prevalence of translation-independent RNA localization. The poles are enriched with stress-related mRNAs and small RNAs, the latter becoming further enriched upon stress in an Hfq-dependent manner. Genome organization may play a role in localizing membrane protein-encoding transcripts. Our results show an unexpected level of intricacy in bacterial transcriptome organization and highlight the poles as hubs for regulation.

Broadening the Definition of Bacterial Small RNAs: Characteristics and Mechanisms of Action

The first report of trans-acting RNA-based regulation in bacterial cells dates back to 1984. Subsequent studies in diverse bacteria unraveled shared properties of trans-acting small regulatory RNAs, forming a clear definition of these molecules. These shared characteristics have been used extensively to identify new small RNAs (sRNAs) and their interactomes. Recently however, emerging technologies able to resolve RNA-RNA interactions have identified new types of regulatory RNAs. In this review, we present a broader definition of trans-acting sRNA regulators and discuss their newly discovered intrinsic characteristics.

RNA Localization in Bacteria

Diverse mechanisms and functions of posttranscriptional regulation by small regulatory RNAs and RNA-binding proteins have been described in bacteria. In contrast, little is known about the spatial organization of RNAs in bacterial cells. In eukaryotes, subcellular localization and transport of RNAs play important roles in diverse physiological processes, such as embryonic patterning, asymmetric cell division, epithelial polarity, and neuronal plasticity. It is now clear that bacterial RNAs also can accumulate at distinct sites in the cell. However, due to the small size of bacterial cells, RNA localization and localization-associated functions are more challenging to study in bacterial cells, and the underlying molecular mechanisms of transcript localization are less understood. Here, we review the emerging examples of RNAs localized to specific subcellular locations in bacteria, with indications that subcellular localization of transcripts might be important for gene expression and regulatory processes. Diverse mechanisms for bacterial RNA localization have been suggested, including close association to their genomic site of transcription, or to the localizations of their protein products in translation-dependent or -independent processes. We also provide an overview of the state of the art of technologies to visualize and track bacterial RNAs, ranging from hybridization-based approaches in fixed cells to in vivo imaging approaches using fluorescent protein reporters and/or RNA aptamers in single living bacterial cells. We conclude with a discussion of open questions in the field and ongoing technological developments regarding RNA imaging in eukaryotic systems that might likewise provide novel insights into RNA localization in bacteria.

Kinetic Modelling of Competition and Depletion of Shared miRNAs by Competing Endogenous RNAs

Non-coding RNAs play a key role in the post-transcriptional regulation of mRNA translation and turnover in eukaryotes. miRNAs, in particular, interact with their target RNAs through protein-mediated, sequence-specific binding, giving rise to extended and highly heterogeneous miRNA-RNA interaction networks. Within such networks, competition to bind miRNAs can generate an effective positive coupling between their targets. Competing endogenous RNAs (ceRNAs) can in turn regulate each other through miRNA-mediated crosstalk. Albeit potentially weak, ceRNA interactions can occur both dynamically, affecting, e.g., the regulatory clock, and at stationarity, in which case ceRNA networks as a whole can be implicated in the composition of the cell's proteome. Many features of ceRNA interactions, including the conditions under which they become significant, can be unraveled by mathematical and in silico models. We review the understanding of the ceRNA effect obtained within such frameworks, focusing on the methods employed to quantify it, its role in the processing of gene expression noise, and how network topology can determine its reach.

Dynamics of translation can determine the spatial organization of membrane-bound proteins and their mRNA

Unlike most macromolecules that are homogeneously distributed in the bacterial cell, mRNAs that encode inner-membrane proteins can be concentrated near the inner membrane. Cotranslational insertion of the nascent peptide into the membrane brings the translating ribosome and the mRNA close to the membrane. This suggests that kinetic properties of translation can determine the spatial organization of these mRNAs and proteins, which can be modulated through posttranscriptional regulation. Here we use a simple stochastic model of translation to characterize the effect of mRNA properties on the dynamics and statistics of its spatial distribution. We show that a combination of the rate of translation initiation, the availability of secretory apparatuses, and the composition of the coding region determines the abundance of mRNAs near the membrane, as well as their residence time. We propose that the spatiotemporal dynamics of mRNAs can give rise to protein clusters on the membrane and determine their size distribution.