Multi-target regulation by small RNAs synchronizes gene expression thresholds and may enhance ultrasensitive behavior

Kinetic modeling reveals additional regulation at co-transcriptional level by post-transcriptional sRNA regulators

Small RNAs (sRNAs) are important gene regulators in bacteria. Many sRNAs act post-transcriptionally by affecting translation and degradation of the target mRNAs upon base-pairing interactions. Here we present a general approach combining imaging and mathematical modeling to determine kinetic parameters at different levels of sRNA-mediated gene regulation that contribute to overall regulation efficacy. Our data reveal that certain sRNAs previously characterized as post-transcriptional regulators can regulate some targets co-transcriptionally, leading to a revised model that sRNA-mediated regulation can occur early in an mRNA’s lifetime, as soon as the sRNA binding site is transcribed. This co-transcriptional regulation is likely mediated by Rho-dependent termination when transcription-coupled translation is reduced upon sRNA binding. Our data also reveal several important kinetic steps that contribute to the differential regulation of mRNA targets by an sRNA. Particularly, binding of sRNA to the target mRNA may dictate the regulation hierarchy observed within an sRNA regulon.

Reyer et al. use fluorescent microscopy and kinetic modeling to find that two sRNAs canonically described as post-transcriptional regulators can regulate their targets co-transcriptionally and determine the in vivo kinetic parameters that dictate differential regulation efficiency.

In vitro iCLIP-based modeling uncovers how the splicing factor U2AF2 relies on regulation by cofactors

Alternative splicing generates distinct mRNA isoforms and is crucial for proteome diversity in eukaryotes. The RNA-binding protein (RBP) U2AF2 is central to splicing decisions, as it recognizes 3′ splice sites and recruits the spliceosome. We establish “in vitro iCLIP” experiments, in which recombinant RBPs are incubated with long transcripts, to study how U2AF2 recognizes RNA sequences and how this is modulated by trans-acting RBPs. We measure U2AF2 affinities at hundreds of binding sites and compare in vitro and in vivo binding landscapes by mathematical modeling. We find that trans-acting RBPs extensively regulate U2AF2 binding in vivo, including enhanced recruitment to 3′ splice sites and clearance of introns. Using machine learning, we identify and experimentally validate novel trans-acting RBPs (including FUBP1, CELF6, and PCBP1) that modulate U2AF2 binding and affect splicing outcomes. Our study offers a blueprint for the high-throughput characterization of in vitro mRNP assembly and in vivo splicing regulation.

A Robust Molecular Network Motif for Period-Doubling Devices

Life is sustained by a variety of cyclic processes such as cell division, muscle contraction, and neuron firing. The periodic signals powering these processes often direct a variety of other downstream systems, which operate at different time scales and must have the capacity to divide or multiply the period of the master clock. Period modulation is also an important challenge in synthetic molecular systems, where slow and fast components may have to be coordinated simultaneously by a single oscillator whose frequency is often difficult to tune. Circuits that can multiply the period of a clock signal (frequency dividers), such as binary counters and flip-flops, are commonly encountered in electronic systems, but design principles to obtain similar devices in biological systems are still unclear. We take inspiration from the architecture of electronic flip-flops, and we propose to build biomolecular period-doubling networks by combining a bistable switch with negative feedback modules that preprocess the circuit inputs. We identify a network motif and we show it can be "realized" using different biomolecular components; two of the realizations we propose rely on transcriptional gene networks and one on nucleic acid strand displacement systems. We examine the capacity of each realization to perform period-doubling by studying how bistability of the motif is affected by the presence of the input; for this purpose, we employ mathematical tools from algebraic geometry that provide us with valuable insights on the input/output behavior as a function of the realization parameters. We show that transcriptional network realizations operate correctly also in a stochastic regime when processing oscillations from the repressilator, a canonical synthetic in vivo oscillator. Finally, we compare the performance of different realizations in a range of realistic parameters via numerical sensitivity analysis of the period-doubling region, computed with respect to the input period and amplitude. Our mathematical and computational analysis suggests that the motif we propose is generally robust with respect to specific implementation details: functionally equivalent circuits can be built as long as the species-interaction topology is respected. This indicates that experimental construction of the circuit is possible with a variety of components within the rapidly expanding libraries available in synthetic biology.

Analysis of sucrose-induced small RNAs in Streptococcus mutans in the presence of different sucrose concentrations

Streptococcus mutans (S. mutans) is the major pathogen contributing to dental caries. Sucrose is an important carbohydrate source for S. mutans and is crucial for dental caries. Small RNAs (sRNAs) are key post-transcriptional regulators of stress adaptation and virulence in bacteria. Here, for the first time, we created three replicate RNA libraries exposed to either 1 or 5% sucrose. The expression levels of sRNAs and target genes (gtfB, gtfC, and spaP) related to virulence were assessed. In addition, some phenotypic traits were evaluated. We obtained 2125 sRNA candidates with at least 100 average reads in 1% sucrose or 5% sucrose. Of these candidates, 2 were upregulated and 20 were downregulated in 1% sucrose. Six of these 22 differentially expressed sRNAs were validated by qRT-PCR. The expression level of target gene gtfB was higher in 1% sucrose. The adherence ratio of S. mutans was higher in 1% sucrose than in 5% sucrose. The synthesis of water-insoluble glucans (WIGs) was significantly higher in 5% sucrose than in 1% sucrose. These data suggest that a series of sRNAs can be induced in response to sucrose, and that some sRNAs might be involved in the regulation of phenotypes, providing new insight into the prevention of caries.

Retargeting a Dual-Acting sRNA for Multiple mRNA Transcript Regulation

Multitargeting small regulatory RNAs (sRNAs) represent a potentially useful tool for metabolic engineering applications. Natural multitargeting sRNAs govern bacterial gene expression by binding to the translation initiation regions of protein-coding mRNAs through base pairing. We designed an Escherichia coli based genetic system to create and assay dual-acting retargeted-sRNA variants. The variants can be assayed for coordinate translational regulation of two alternate mRNA leaders fused to independent reporter genes. Accordingly, we began with the well-characterized E. coli native DsrA sRNA. The merits of using DsrA include its well-characterized separation of function into two independently folded stem-loop domains, wherein alterations at one stem do not necessarily abolish activity at the other stem. Expression of the sRNA and each reporter mRNA was independently controlled by small inducer molecules, allowing precise quantification of the regulatory effects of each sRNA:mRNA interaction in vivo with a microtiter plate assay. Using this system, we semirationally designed DsrA variants screened in E. coli for their ability to regulate key mRNA leader sequences from the Clostridium acetobutylicum n-butanol synthesis pathway. To coordinate intervention at two points in a metabolic pathway, we created bifunctional sRNA prototypes by combining sequences from two singly retargeted DsrA variants. This approach constitutes a platform for designing sRNAs to specifically target arbitrary mRNA transcript sequences, and thus provides a generalizable tool for retargeting and characterizing multitarget sRNAs for metabolic engineering.

Hierarchical Post-transcriptional Regulation of Colicin E2 Expression in Escherichia coli

Post-transcriptional regulation of gene expression plays a crucial role in many bacterial pathways. In particular, the translation of mRNA can be regulated by trans-acting, small, non-coding RNAs (sRNAs) or mRNA-binding proteins, each of which has been successfully treated theoretically using two-component models. An important system that includes a combination of these modes of post-transcriptional regulation is the Colicin E2 system. DNA damage, by triggering the SOS response, leads to the heterogeneous expression of the Colicin E2 operon including the cea gene encoding the toxin colicin E2, and the cel gene that codes for the induction of cell lysis and release of colicin. Although previous studies have uncovered the system's basic regulatory interactions, its dynamical behavior is still unknown. Here, we develop a simple, yet comprehensive, mathematical model of the colicin E2 regulatory network, and study its dynamics. Its post-transcriptional regulation can be reduced to three hierarchically ordered components: the mRNA including the cel gene, the mRNA-binding protein CsrA, and an effective sRNA that regulates CsrA. We demonstrate that the stationary state of this system exhibits a pronounced threshold in the abundance of free mRNA. As post-transcriptional regulation is known to be noisy, we performed a detailed stochastic analysis, and found fluctuations to be largest at production rates close to the threshold. The magnitude of fluctuations can be tuned by the rate of production of the sRNA. To study the dynamics in response to an SOS signal, we incorporated the LexA-RecA SOS response network into our model. We found that CsrA regulation filtered out short-lived activation peaks and caused a delay in lysis gene expression for prolonged SOS signals, which is also seen in experiments. Moreover, we showed that a stochastic SOS signal creates a broad lysis time distribution. Our model thus theoretically describes Colicin E2 expression dynamics in detail and reveals the importance of the specific regulatory components for the timing of toxin release.

Molecular Titration Promotes Oscillations and Bistability in Minimal Network Models with Monomeric Regulators

Molecular titration is emerging as an important biochemical interaction mechanism within synthetic devices built with nucleic acids and the CRISPR/Cas system. We show that molecular titration in the context of feedback circuits is a suitable mechanism to enhance the emergence of oscillations and bistable behaviors. We consider biomolecular modules that can be inhibited or activated by input monomeric regulators; the regulators compete with constitutive titrating species to determine the activity of their target. By tuning the titration rate and the concentration of titrating species, it is possible to modulate the delay and convergence speed of the transient response, and the steepness and dead zone of the stationary response of the modules. These phenomena favor the occurrence of oscillations when modules are interconnected to create a negative feedback loop; bistability is favored in a positive feedback interconnection. Numerical simulations are supported by mathematical analysis showing that the capacity of the closed loop systems to exhibit oscillations or bistability is structural.

A comprehensive expression profile of micrornas in rat's pituitary

MicroRNAs (miRNAs) are a class of small, non-coding RNA molecules that act as a negative regulator of most mRNAs. miRNAs influence the gene expression as transcriptional regulators and play an important role in many fundamental biological processes. It is generally acknowledged that miRNAs have a very important affection on mammalian pituitary. However, the answers of which role miRNAs play in the development of sexual function or how much they contribute to the pituitary function are not exactly. In our study, we used three female 21-day-old rats and three female 12-month-old rats to analysis the function of miRNAs. By the analyses of microarray data, we finished the stem-loop real-time RT-PCR for the differentially expressed miRNAs. We detected a total of 93 differentially expressed miRNAs between 21-day-old rats' pituitary and 12-month-old rats'. Stem-loop real-time RT-PCR suggests that the obtained data is of high credibility. Among these miRNAs, 7 miRNAs' expression (rno-miR-880, rno-miR-503, rno-miR-125a-3p, rno-miR-3596b, rno-miR-30e, rno-miR-214 and rno-miR-22) are significant different (P≤0.05). In a word, this study identified a number of specific changes in the expression of miRNAs, in rats by detecting the expression profile of miRNAs in rat's pituitary, and all of that lay the foundation for elucidating the regulatory mechanisms of miRNAs in rat's reproduction process. These differentially expressed miRNAs may play a very important role in rat's reproduction process.

Forging patterns and making waves from biology to geology: a commentary on Turing (1952) 'The chemical basis of morphogenesis'

Alan Turing was neither a biologist nor a chemist, and yet the paper he published in 1952, 'The chemical basis of morphogenesis', on the spontaneous formation of patterns in systems undergoing reaction and diffusion of their ingredients has had a substantial impact on both fields, as well as in other areas as disparate as geomorphology and criminology. Motivated by the question of how a spherical embryo becomes a decidedly non-spherical organism such as a human being, Turing devised a mathematical model that explained how random fluctuations can drive the emergence of pattern and structure from initial uniformity. The spontaneous appearance of pattern and form in a system far away from its equilibrium state occurs in many types of natural process, and in some artificial ones too. It is often driven by very general mechanisms, of which Turing's model supplies one of the most versatile. For that reason, these patterns show striking similarities in systems that seem superficially to share nothing in common, such as the stripes of sand ripples and of pigmentation on a zebra skin. New examples of 'Turing patterns' in biology and beyond are still being discovered today. This commentary was written to celebrate the 350th anniversary of the journal Philosophical Transactions of the Royal Society.

Determinants of cell-to-cell variability in protein kinase signaling

Cells reliably sense environmental changes despite internal and external fluctuations, but the mechanisms underlying robustness remain unclear. We analyzed how fluctuations in signaling protein concentrations give rise to cell-to-cell variability in protein kinase signaling using analytical theory and numerical simulations. We characterized the dose-response behavior of signaling cascades by calculating the stimulus level at which a pathway responds (‘pathway sensitivity’) and the maximal activation level upon strong stimulation. Minimal kinase cascades with gradual dose-response behavior show strong variability, because the pathway sensitivity and the maximal activation level cannot be simultaneously invariant. Negative feedback regulation resolves this trade-off and coordinately reduces fluctuations in the pathway sensitivity and maximal activation. Feedbacks acting at different levels in the cascade control different aspects of the dose-response curve, thereby synergistically reducing the variability. We also investigated more complex, ultrasensitive signaling cascades capable of switch-like decision making, and found that these can be inherently robust to protein concentration fluctuations. We describe how the cell-to-cell variability of ultrasensitive signaling systems can be actively regulated, e.g., by altering the expression of phosphatase(s) or by feedback/feedforward loops. Our calculations reveal that slow transcriptional negative feedback loops allow for variability suppression while maintaining switch-like decision making. Taken together, we describe design principles of signaling cascades that promote robustness. Our results may explain why certain signaling cascades like the yeast pheromone pathway show switch-like decision making with little cell-to-cell variability.

Cells sense their surroundings and respond to soluble factors in the extracellular space. Extracellular factors frequently induce heterogeneous responses, thereby restricting the biological outcome to a fraction of the cell population. However, the question arises how such cell-to-cell variability can be controlled, because some cellular systems show a very homogenous response at a defined level of an extracellular stimulus. We derived an analytical framework to systematically characterize the cell-to-cell variability of intracellular signaling pathways which transduce external signals. We analyzed how heterogeneity arises from fluctuations in the total concentrations of signaling proteins because this is the main source of variability in eukaryotic systems. We find that signaling pathways can be highly variable or inherently invariant, depending on the kinetic parameters and the structural features of the cascade. Our results indicate that the cell-to-cell variability can be reduced by negative feedback in the cascade or by signaling crosstalk between parallel pathways. We precisely define the role of negative feedback loops in variability suppression, and show that different aspects of the dose-response curve can be controlled, depending on the feedback kinetics and site of action in the cascade. This work constitutes a first step towards a systematic understanding of cell-to-cell variability in signal transduction.

RNA-Seq of Bacillus licheniformis: active regulatory RNA features expressed within a productive fermentation

BACKGROUND

The production of enzymes by an industrial strain requires a complex adaption of the bacterial metabolism to the conditions within the fermenter. Regulatory events within the process result in a dynamic change of the transcriptional activity of the genome. This complex network of genes is orchestrated by proteins as well as regulatory RNA elements. Here we present an RNA-Seq based study considering selected phases of an industry-oriented fermentation of Bacillus licheniformis.

RESULTS

A detailed analysis of 20 strand-specific RNA-Seq datasets revealed a multitude of transcriptionally active genomic regions. 3314 RNA features encoded by such active loci have been identified and sorted into ten functional classes. The identified sequences include the expected RNA features like housekeeping sRNAs, metabolic riboswitches and RNA switches well known from studies on Bacillus subtilis as well as a multitude of completely new candidates for regulatory RNAs. An unexpectedly high number of 855 RNA features are encoded antisense to annotated protein and RNA genes, in addition to 461 independently transcribed small RNAs. These antisense transcripts contain molecules with a remarkable size range variation from 38 to 6348 base pairs in length. The genome of the type strain B. licheniformis DSM13 was completely reannotated using data obtained from RNA-Seq analyses and from public databases.

CONCLUSION

The hereby generated data-sets represent a solid amount of knowledge on the dynamic transcriptional activities during the investigated fermentation stages. The identified regulatory elements enable research on the understanding and the optimization of crucial metabolic activities during a productive fermentation of Bacillus licheniformis strains.