Quantitative characteristics of gene regulation by small RNA

The effect of DNA-binding proteins on insertion sequence element transposition upstream of the bgl operon in Escherichia coli

The bglGFB operon in Escherichia coli K-12 strain BW25113, encoding the proteins necessary for the uptake and metabolism of β-glucosides, is normally not expressed. Insertion of either IS1 or IS5 upstream of the bgl promoter activates expression of the operon only when the cell is starving in the presence of a β-glucoside, drastically increasing transcription and allowing the cell to survive and grow using this carbon source. Details surrounding the exact mechanism and regulation of the IS insertional event remain unclear. In this work, the role of several DNA-binding proteins in how they affect the rate of insertion upstream of bgl are examined via mutation assays and protocols measuring transcription. Both Crp and IHF exert a positive effect on insertional Bgl+ mutations when present, active, and functional in the cell. Our results characterize IHF's effect in conjunction with other mutations, show that IHF's effect on IS insertion into bgl also affects other operons, and indicate that it may exert its effect by binding to and altering the DNA conformation of IS1 and IS5 in their native locations, rather than by directly influencing transposase gene expression. In contrast, the cAMP-CRP complex acts directly upon the bgl operon by binding upstream of the promoter, presumably altering local DNA into a conformation that enhances IS insertion.

RNA cis-regulators are important for Streptococcus pneumoniae in vivo success

Bacteria have evolved complex transcriptional regulatory networks, as well as many diverse regulatory strategies at the RNA level, to enable more efficient use of metabolic resources and a rapid response to changing conditions. However, most RNA-based regulatory mechanisms are not well conserved across different bacterial species despite controlling genes important for virulence or essential biosynthetic processes. Here, we characterize the activity of, and assess the fitness benefit conferred by, twelve cis-acting regulatory RNAs (including several riboswitches and a T-box), in the opportunistic pathogen Streptococcus pneumoniae TIGR4. By evaluating native locus mutants of each regulator that result in constitutively active or repressed expression, we establish that growth defects in planktonic culture are associated with constitutive repression of gene expression, while constitutive activation of gene expression is rarely deleterious. In contrast, in mouse nasal carriage and pneumonia models, strains with either constitutively active and repressed gene expression are significantly less fit than matched control strains. Furthermore, two RNA-regulated pathways, FMN synthesis/transport and pyrimidine synthesis/transport display exceptional sensitivity to mis-regulation or constitutive gene repression in both planktonic culture and in vivo environments. Thus, despite lack of obvious phenotypes associated with constitutive gene expression in vitro, the fitness benefit conferred on bacteria via fine-tuned metabolic regulation through cis-acting regulatory RNAs is substantial in vivo, and therefore easily sufficient to drive the evolution and maintenance of diverse RNA regulatory mechanisms.

Effects of microRNA-mediated negative feedback on gene expression noise

MicroRNAs (miRNAs) are small noncoding RNAs that regulate gene expression post-transcriptionally in eukaryotes by binding with target mRNAs and preventing translation. miRNA-mediated feedback motifs are ubiquitous in various genetic networks that control cellular decision making. A key question is how such a feedback mechanism may affect gene expression noise. To answer this, we have developed a mathematical model to study the effects of a miRNA-dependent negative-feedback loop on mean expression and noise in target mRNAs. Combining analytics and simulations, we show the existence of an expression threshold demarcating repressed and expressed regimes in agreement with earlier studies. The steady-state mRNA distributions are bimodal near the threshold, where copy numbers of mRNAs and miRNAs exhibit enhanced anticorrelated fluctuations. Moreover, variation of negative-feedback strength shifts the threshold locations and modulates the noise profiles. Notably, the miRNA-mRNA binding affinity and feedback strength collectively shape the bimodality. We also compare our model with a direct auto-repression motif, where a gene produces its own repressor. Auto-repression fails to produce bimodal mRNA distributions as found in miRNA-based indirect repression, suggesting the crucial role of miRNAs in creating phenotypic diversity. Together, we demonstrate how miRNA-dependent negative feedback modifies the expression threshold and leads to a broader parameter regime of bimodality compared to the no-feedback case.

Mechanisms of Regulation of Cryptic Prophage-Encoded Gene Products in Escherichia coli

The dicBF operon of Qin cryptic prophage in Escherichia coli K-12 encodes the small RNA (sRNA) DicF and small protein DicB, which regulate host cell division and are toxic when overexpressed. While new functions of DicB and DicF have been identified in recent years, the mechanisms controlling the expression of the dicBF operon have remained unclear. Transcription from dicBp, the major promoter of the dicBF operon, is repressed by DicA. In this study, we discovered that transcription of the dicBF operon and processing of the polycistronic mRNA is regulated by multiple mechanisms. DicF sRNA accumulates during stationary phase and is processed from the polycistronic dicBF mRNA by the action of both RNase III and RNase E. DicA-mediated transcriptional repression of dicBp can be relieved by an antirepressor protein, Rem, encoded on the Qin prophage. Ectopic production of Rem results in cell filamentation due to strong induction of the dicBF operon, and filamentation is mediated by DicF and DicB. Spontaneous derepression of dicBp occurs in a subpopulation of cells independent of the antirepressor. This phenomenon is reminiscent of the bistable switch of λ phage with DicA and DicC performing functions similar to those of CI and Cro, respectively. Additional experiments demonstrate stress-dependent induction of the dicBF operon. Collectively, our results illustrate that toxic genes carried on cryptic prophages are subject to layered mechanisms of control, some that are derived from the ancestral phage and some that are likely later adaptations. IMPORTANCE Cryptic or defective prophages have lost genes necessary to excise from the bacterial chromosome and produce phage progeny. In recent years, studies have found that cryptic prophage gene products influence diverse aspects of bacterial host cell physiology. However, to obtain a complete understanding of the relationship between cryptic prophages and the host bacterium, identification of the environmental, host, or prophage-encoded factors that induce the expression of cryptic prophage genes is crucial. In this study, we examined the regulation of a cryptic prophage operon in Escherichia coli encoding a small RNA and a small protein that are involved in inhibiting bacterial cell division, altering host metabolism, and protecting the host bacterium from phage infections.

Origin and functional role of antisense transcription in endogenous and exogenous retroviruses

Most proteins expressed by endogenous and exogenous retroviruses are encoded in the sense (positive) strand of the genome and are under the control of regulatory elements within the 5' long terminal repeat (LTR). A number of retroviral genomes also encode genes in the antisense (negative) strand and their expression is under the control of negative sense promoters within the 3' LTR. In the case of the Human T-cell Lymphotropic Virus 1 (HTLV-1), the antisense protein HBZ has been shown to play a critical role in the virus lifecycle and in the pathogenic process, while the function of the Human Immunodeficiency Virus 1 (HIV-1) antisense protein ASP remains unknown. However, the expression of 3' LTR-driven antisense transcripts is not always demonstrably associated with the presence of an antisense open reading frame encoding a viral protein. Moreover, even in the case of retroviruses that do express an antisense protein, such as HTLV-1 and the pandemic strains of HIV-1, the 3' LTR-driven antisense transcript shows both protein-coding and noncoding activities. Indeed, the ability to express antisense transcripts appears to be phylogenetically more widespread among endogenous and exogenous retroviruses than the presence of a functional antisense open reading frame within these transcripts. This suggests that retroviral antisense transcripts may have originated as noncoding molecules with regulatory activity that in some cases later acquired protein-coding function. Here, we will review examples of endogenous and exogenous retroviral antisense transcripts, and the ways through which they benefit viral persistence in the host.

E. coli allantoinase is activated by the downstream metabolic enzyme, glycerate kinase, and stabilizes the putative allantoin transporter by direct binding

Allantoin is a good source of ammonium for many organisms, and in Escherichia coli it is utilized under anaerobic conditions. We provide evidence that allantoinase (AllB) is allosterically activated by direct binding of the allantoin catabolic enzyme, glycerate 2-kinase (GlxK) in the presence of glyoxylate. Glyoxylate is known to be an effector of the AllR repressor which regulates the allantoin utilization operons in E. coli. AllB has low affinity for allantoin, but its activation by GlxK leads to increased affinity for its substrate. We also show that the predicted allantoin transporter YbbW (re-named AllW) has allantoin specificity and the protein-protein interaction with AllB. Our results show that the AllB-dependent allantoin degradative pathway is subject to previously unrecognized regulatory mechanisms involving direct protein-protein interactions.

Antisense transcription and its roles in adaption to environmental stress in E. coli

It has been reported that a highly varying proportion (1% ∼ 93%) of genes in various prokaryotes have antisense RNA (asRNA) transcription. However, the extent of the pervasiveness of asRNA transcription in the well-studied E. coli K12 strain has thus far been an issue of debate. Furthermore, very little is known about the expression patterns and functions of asRNAs under various conditions. To fill these gaps, we determined the transcriptomes and proteomes of E. coli K12 at multiple time points in five culture conditions using strand-specific RNA-seq, differential RNA-seq, and quantitative mass spectrometry methods. To reduce artifacts of possible transcriptional noise, we identified asRNA using stringent criteria with biological replicate verification and transcription start sites (TSSs) information included. We identified a total of 660 asRNAs, which were generally short and largely condition-dependently transcribed. We found that the proportions of the genes which had asRNA transcription highly depended on the culture conditions and time points. We classified the transcriptional activities of the genes in six transcriptional modes according to their relative levels of asRNA to mRNA. Many genes changed their transcriptional modes at different time points of the culture conditions, and such transitions can be described in a well-defined manner. Intriguingly, the protein levels and mRNA levels of genes in the sense-only/sense-dominant mode were moderately correlated, but the same was not true for genes in the balanced/antisense-dominant mode, in which asRNAs were at a comparable or higher level to mRNAs. These observations were further validated by western blot on candidate genes, where an increase in asRNA transcription diminished gene expression in one case and enhanced it in another. These results suggest that asRNAs may directly or indirectly regulate translation by forming duplexes with cognate mRNAs. Thus, asRNAs may play an important role in the bacterium's responses to environmental changes during growth and adaption to different environments.

IMPORTANCE

The cis -antisense RNA (asRNA) is a type of understudied RNA molecules in prokaryotes, which is believed to be important in regulating gene expression. Our current understanding of asRNA is constrained by inconsistent reports about its identification and properties. These discrepancies are partially caused by a lack of sufficient samples, biological replicates, and culture conditions. This study aimed to overcome these disadvantages and identified 660 putative asRNAs using integrated information from strand-specific RNA-seq, differential RNA-seq, and mass spectrometry methods. In addition, we explored the relative expression between asRNAs and sense RNAs and investigated asRNA regulated transcriptional activity changes over different culture conditions and time points. Our work strongly suggests that asRNAs may play a crucial role in bacterium's responses to environmental changes during growth and adaption to different environments.

Tailored Polypeptide Star Copolymers for 3D Printing of Bacterial Composites Via Direct Ink Writing

Hydrogels hold much promise for 3D printing of functional living materials; however, challenges remain in tailoring mechanical robustness as well as biological performance. In addressing this challenge, the modular synthesis of functional hydrogels from 3-arm diblock copolypeptide stars composed of an inner poly(l-glutamate) domain and outer poly(l-tyrosine) or poly(l-valine) blocks is described. Physical crosslinking due to ß-sheet assembly of these star block copolymers gives mechanical stability during extrusion printing and the selective incorporation of methacrylate units allows for subsequent photocrosslinking to occur under biocompatible conditions. This permits direct ink writing (DIW) printing of bacteria-based mixtures leading to 3D objects with high fidelity and excellent bacterial viability. The tunable stiffness of different copolypeptide networks enables control over proliferation and colony formation for embedded Escherichia coli bacteria as demonstrated via isopropyl ß-d-1-thiogalactopyranoside (IPTG) induction of green fluorescent protein (GFP) expression. This translation of molecular structure to network properties highlights the versatility of these polypeptide hydrogel systems with the combination of writable structures and biological activity illustrating the future potential of these 3D-printed biocomposites.

Periodic spatial patterning with a single morphogen

During multicellular development, periodic spatial patterning systems generate repetitive structures, such as digits, vertebrae, and teeth. Turing patterning provides a foundational paradigm for understanding such systems. The simplest Turing systems are believed to require at least two morphogens to generate periodic patterns. Here, using mathematical modeling, we show that a simpler circuit, including only a single diffusible morphogen, is sufficient to generate long-range, spatially periodic patterns that propagate outward from transient initiating perturbations and remain stable after the perturbation is removed. Furthermore, an additional bistable intracellular feedback or operation on a growing cell lattice can make patterning robust to noise. Together, these results show that a single morphogen can be sufficient for robust spatial pattern formation and should provide a foundation for engineering pattern formation in the emerging field of synthetic developmental biology.

Dynamic feedback regulation for efficient membrane protein production using a small RNA-based genetic circuit in Escherichia coli

BACKGROUND

Membrane proteins (MPs) are an important class of molecules with a wide array of cellular functions and are part of many metabolic pathways. Despite their great potential-as therapeutic drug targets or in microbial cell factory optimization-many challenges remain for efficient and functional expression in a host such as Escherichia coli.

RESULTS

A dynamically regulated small RNA-based circuit was developed to counter membrane stress caused by overexpression of different MPs. The best performing small RNAs were able to enhance the maximum specific growth rate with 123%. On culture level, the total MP production was increased two-to three-fold compared to a system without dynamic control. This strategy not only improved cell growth and production of the studied MPs, it also suggested the potential use for countering metabolic burden in general.

CONCLUSIONS

A dynamically regulated feedback circuit was developed that can sense metabolic stress caused by, in casu, the overexpression of an MP and responds to it by balancing the metabolic state of the cell and more specifically by downregulating the expression of the MP of interest. This negative feedback mechanism was established by implementing and optimizing simple-to-use genetic control elements based on post-transcriptional regulation: small non-coding RNAs. In addition to membrane-related stress when the MP accumulated in the cytoplasm as aggregates, the sRNA-based feedback control system was still effective for improving cell growth but resulted in a decreased total protein production. This result suggests promiscuity of the MP sensor for more than solely membrane stress.

Coordination of gene expression with cell size enables Escherichia coli to efficiently maintain motility across conditions

To swim and navigate, motile bacteria synthesize a complex motility machinery involving flagella, motors, and a sensory system. A myriad of studies has elucidated the molecular processes involved, but less is known about the coordination of motility expression with cellular physiology: In Escherichia coli, motility genes are strongly up-regulated in nutrient-poor conditions compared to nutrient-replete conditions; yet a quantitative link to cellular motility has not been developed. Here, we systematically investigated gene expression, swimming behavior, cell growth, and available proteomics data across a broad spectrum of exponential growth conditions. Our results suggest that cells up-regulate the expression of motility genes at slow growth to compensate for reduction in cell size, such that the number of flagella per cell is maintained across conditions. The observed four or five flagella per cell is the minimum number needed to keep the majority of cells motile. This simple regulatory objective allows E. coli cells to remain motile across a broad range of growth conditions, while keeping the biosynthetic and energetic demands to establish and drive the motility machinery at the minimum needed. Given the strong reduction in flagella synthesis resulting from cell size increases at fast growth, our findings also provide a different physiological perspective on bacterial cell size control: A larger cell size at fast growth is an efficient strategy to increase the allocation of cellular resources to the synthesis of those proteins required for biomass synthesis and growth, while maintaining processes such as motility that are only needed on a per-cell basis.

Riboswitch-inspired toehold riboregulators for gene regulation in Escherichia coli

Regulatory RNA molecules have been widely investigated as components for synthetic gene circuits, complementing the use of protein-based transcription factors. Among the potential advantages of RNA-based gene regulators are their comparatively simple design, sequence-programmability, orthogonality, and their relatively low metabolic burden. In this work, we developed a set of riboswitch-inspired riboregulators in Escherichia coli that combine the concept of toehold-mediated strand displacement (TMSD) with the switching principles of naturally occurring transcriptional and translational riboswitches. Specifically, for translational activation and repression, we sequestered anti-anti-RBS or anti-RBS sequences, respectively, inside the loop of a stable hairpin domain, which is equipped with a single-stranded toehold region at its 5' end and is followed by regulated sequences on its 3' side. A trigger RNA binding to the toehold region can invade the hairpin, inducing a structural rearrangement that results in translational activation or deactivation. We also demonstrate that TMSD can be applied in the context of transcriptional regulation by switching RNA secondary structure involved in Rho-dependent termination. Our designs expand the repertoire of available synthetic riboregulators by a set of RNA switches with no sequence limitation, which should prove useful for the development of robust genetic sensors and circuits.

Reassembling a cannon in the DNA defense arsenal: Genetics of StySA, a BREX phage exclusion system in Salmonella lab strains

Understanding mechanisms that shape horizontal exchange in prokaryotes is a key problem in biology. A major limit on DNA entry is imposed by restriction-modification (RM) processes that depend on the pattern of DNA modification at host-specified sites. In classical RM, endonucleolytic DNA cleavage follows detection of unprotected sites on entering DNA. Recent investigation has uncovered BREX (BacteRiophage EXclusion) systems. These RM-like activities employ host protection by DNA modification, but immediate replication arrest occurs without evident of nuclease action on unmodified phage DNA. Here we show that the historical stySA RM locus of Salmonella enterica sv Typhimurium is a variant BREX system. A laboratory strain disabled for both the restriction and methylation activity of StySA nevertheless has wild type sequence in pglX, the modification gene homolog. Instead, flanking genes pglZ and brxC each carry multiple mutations (μ) in their C-terminal domains. We further investigate this system in situ, replacing the mutated pglZμ and brxCμ genes with the WT counterpart. PglZ-WT supports methylation in the presence of either BrxCμ or BrxC-WT but not in the presence of a deletion/insertion allele, ΔbrxC::cat. Restriction requires both BrxC-WT and PglZ-WT, implicating the BrxC C-terminus specifically in restriction activity. These results suggests that while BrxC, PglZ and PglX are principal components of the BREX modification activity, BrxL is required for restriction only. Furthermore, we show that a partial disruption of brxL disrupts transcription globally.

Horizontal gene transfer is a major driver of evolution and adaptation in bacteria. Genes from outside may be beneficial or dangerous to the receiving cell. Benefits include new food sources such as sugars, or new homes by adhesion, or new resistances, as to antibiotics. Dangers are posed by bacteriophages--viruses that take over the cell machinery, multiply, and release progeny to kill sister cells. Host-dependent restriction-modification systems enable defense that distinguishes relatives from strangers: using a modification pattern (M) carried by DNA bases added by the host cell to prevent restriction (R). Sisters and cousin cells will have the same protective pattern on DNA, while DNA of foreign origin will have the wrong M pattern and be restricted (R, rejected). Typically, restriction involves nuclease digestion. Here we address the enigmatic StySA RM system, one of the earliest to be genetically characterized. It is a variant of the newly recognized defense mechanism, BREX. BREX systems also track DNA history via modification pattern, but restrict by a novel, uncharacterized mechanism. Like other BREX family systems, StySA-BREX modification requires multiple components. When StySA-BREX transcription is unbalanced, we find global disruption of gene transcription. The disruption pattern does not suggest SOS-inducing damage to DNA.

Synthetic fused sRNA for the simultaneous repression of multiple genes

Efficient control over multiple gene expression still presents a major challenge. Synthetic sRNA enables targeted gene expression control in trans without directly modifying the chromosome, but its use to simultaneously target multiple genes can often cause cell growth defects because of the need for additional energy for transcription and lowering of their repression efficiency by limiting the amount of Hfq protein. To address these limitations, we present fusion sRNA (fsRNA) that simultaneously regulates the translation of multiple genes efficiently. It is constructed by linking the mRNA-binding modules for multiple targeted genes in one sRNA scaffold via one-pot generation using overlap extension PCR. The repression capacity of fsRNA was demonstrated by the construction of sRNAs to target four endogenous genes: caiF, hybG, ytfR and minD in Escherichia coli. Their cross-reactivity and the effect on cell growth were also investigated. As practical applications, we applied fsRNA to violacein- and protocatechuic acid-producing strains, resulting in increases of 13% violacein and 81% protocatechuic acid, respectively. The developed fsRNA-mediated multiple gene expression regulation system thus enables rapid and efficient development of optimised cell factories for valuable chemicals without cell growth defects and limiting cellular resources.Key points• Synthetic fusion sRNA (fsRNA)-based system was constructed for the repression of multiple target genes.• fsRNA repressed multiple genes by only expressing a single sRNA while minimising the cellular burden.• The application of fsRNA showed the increased production titers of violacein (13%) and protocatechuic acid (81%).

The noncoding RNA CcnA modulates the master cell cycle regulators CtrA and GcrA in Caulobacter crescentus

Bacteria are powerful models for understanding how cells divide and accomplish global regulatory programs. In Caulobacter crescentus, a cascade of essential master regulators supervises the correct and sequential activation of DNA replication, cell division, and development of different cell types. Among them, the response regulator CtrA plays a crucial role coordinating all those functions. Here, for the first time, we describe the role of a novel factor named CcnA (cell cycle noncoding RNA A), a cell cycle–regulated noncoding RNA (ncRNA) located at the origin of replication, presumably activated by CtrA, and responsible for the accumulation of CtrA itself. In addition, CcnA may be also involved in the inhibition of translation of the S-phase regulator, GcrA, by interacting with its 5′ untranslated region (5′ UTR). Performing in vitro experiments and mutagenesis, we propose a mechanism of action of CcnA based on liberation (ctrA) or sequestration (gcrA) of their ribosome-binding site (RBS). Finally, its role may be conserved in other alphaproteobacterial species, such as Sinorhizobium meliloti, representing indeed a potentially conserved process modulating cell cycle in Caulobacterales and Rhizobiales.

During cell cycle progression in the bacterium Caulobacter crescentus, the master cell cycle regulator CtrA is controlled by CcnA, a cell cycle-regulated non-coding RNA transcribed from a gene located at the origin of replication.

Insertion Sequence (IS) Element-Mediated Activating Mutations of the Cryptic Aromatic β-Glucoside Utilization (BglGFB) Operon Are Promoted by the Anti-Terminator Protein (BglG) in Escherichia coli

The cryptic β-glucoside GFB (bglGFB) operon in Escherichia coli (E. coli) can be activated by mutations arising under starvation conditions in the presence of an aromatic β-glucoside. This may involve the insertion of an insertion sequence (IS) element into a "stress-induced DNA duplex destabilization" (SIDD) region upstream of the operon promoter, although other types of mutations can also activate the bgl operon. Here, we show that increased expression of the bglG gene, encoding a well-characterized transcriptional antiterminator, dramatically increases the frequency of both IS-mediated and IS-independent Bgl⁺ mutations occurring on salicin- and arbutin-containing agar plates. Both mutation rates increased with increasing levels of bglG expression but IS-mediated mutations were more prevalent at lower BglG levels. Mutations depended on the presence of both BglG and an aromatic β-glucoside, and bglG expression did not influence IS insertion in other IS-activated operons tested. The N-terminal mRNA-binding domain of BglG was essential for mutational activation, and alteration of BglG's binding site in the mRNA nearly abolished Bgl⁺ mutant appearances. Increased bglG expression promoted residual bgl operon expression in parallel with the increases in mutation rates. Possible mechanisms are proposed explaining how BglG enhances the frequencies of bgl operon activating mutations.

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.

A pathogen-specific sRNA influences enterohemorrhagic Escherichia coli fitness and virulence in part by direct interaction with the transcript encoding the ethanolamine utilization regulatory factor EutR

Enterohemorrhagic Escherichia coli (EHEC) O157:H7 relies on sRNAs to coordinate expression of metabolic and virulence factors to colonize the host. Here, we focus on the sRNA, named MavR (metabolism and virulence regulator), that is conserved among pathogenic Enterobacteriaceae. MavR is constitutively expressed under in vitro conditions that promote EHEC virulence gene expression. Using MS2-affinity purification coupled with RNA sequencing, the eutR transcript was identified as a putative target of MavR. EutR is a transcription factor that promotes expression of genes required for ethanolamine metabolism as well as virulence factors important for host colonization. MavR binds to the eutR coding sequence to protect the eutR transcript from RNase E-mediated degradation. Ultimately, MavR promotes EutR expression and in turn ethanolamine utilization and ethanolamine-dependent growth. RNAseq analyses revealed that MavR also affected expression of genes important for other metabolic pathways, motility, oxidative stress and attaching and effacing lesion formation, which contribute to EHEC colonization of the gastrointestinal tract. In support of the idea that MavR-dependent gene expression affects fitness during infection, deletion of mavR resulted in significant (∼10- to 100-fold) attenuation in colonization of the mammalian intestine. Altogether, these studies reveal an important, extensive, and robust phenotype for a bacterial sRNA in host-pathogen interactions.

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.

Post-Transcriptional Control in the Regulation of Polyhydroxyalkanoates Synthesis

The large production of non-degradable petrol-based plastics has become a major global issue due to its environmental pollution. Biopolymers produced by microorganisms such as polyhydroxyalkanoates (PHAs) are gaining potential as a sustainable alternative, but the high cost associated with their industrial production has been a limiting factor. Post-transcriptional regulation is a key step to control gene expression in changing environments and has been reported to play a major role in numerous cellular processes. However, limited reports are available concerning the regulation of PHA accumulation in bacteria, and many essential regulatory factors still need to be identified. Here, we review studies where the synthesis of PHA has been reported to be regulated at the post-transcriptional level, and we analyze the RNA-mediated networks involved. Finally, we discuss the forthcoming research on riboregulation, synthetic, and metabolic engineering which could lead to improved strategies for PHAs synthesis in industrial production, thereby reducing the costs currently associated with this procedure.

The essential role of mRNA degradation in understanding and engineering E. coli metabolism

Metabolic engineering strategies are crucial for the development of bacterial cell factories with improved performance. Until now, optimal metabolic networks have been designed based on systems biology approaches integrating large-scale data on the steady-state concentrations of mRNA, protein and metabolites, sometimes with dynamic data on fluxes, but rarely with any information on mRNA degradation. In this review, we compile growing evidence that mRNA degradation is a key regulatory level in E. coli that metabolic engineering strategies should take into account. We first discuss how mRNA degradation interacts with transcription and translation, two other gene expression processes, to balance transcription regulation and remove poorly translated mRNAs. The many reciprocal interactions between mRNA degradation and metabolism are also highlighted: metabolic activity can be controlled by changes in mRNA degradation and in return, the activity of the mRNA degradation machinery is controlled by metabolic factors. The mathematical models of the crosstalk between mRNA degradation dynamics and other cellular processes are presented and discussed with a view towards novel mRNA degradation-based metabolic engineering strategies. We show finally that mRNA degradation-based strategies have already successfully been applied to improve heterologous protein synthesis. Overall, this review underlines how important mRNA degradation is in regulating E. coli metabolism and identifies mRNA degradation as a key target for innovative metabolic engineering strategies in biotechnology.

Oncogenic Landscape of Somatic Mutations Perturbing Pan-Cancer lncRNA-ceRNA Regulation

Competing endogenous RNAs (ceRNA) are transcripts that communicate with and co-regulate each other by competing for the binding of shared microRNAs (miRNAs). Long non-coding RNAs (lncRNAs) as a type of ceRNA constitute a competitive regulatory network determined by miRNA response elements (MREs). Mutations in lncRNA MREs destabilize their original regulatory pathways. Study of the effects of lncRNA somatic mutations on ceRNA mechanisms can clarify tumor mechanisms and contribute to the development of precision medicine. Here, we used somatic mutation profiles collected from TCGA to characterize the role of lncRNA somatic mutations in the ceRNA regulatory network in 33 cancers. The 31,560 mutation sites identified by TargetScan and miRanda affected the balance of 70,811 ceRNA regulatory pathways. Putative mutations were categorized as high or low based on mutation frequencies. Multivariate multiple regression revealed a significant effect of 162 high-frequency mutations in six cancer types on the expression levels of target mRNAs (ceMs) through the ceRNA mechanism. Low-frequency mutations in multiple cancers perturbing 1624 ceM have been verified by Student’s t-test, indicating a significant mechanism of changes in the expression level of oncogenic genes. Oncogenic signaling pathway studies involving ceMs indicated functional heterogeneity of multiple cancers. Furthermore, we identified that lncRNA, perturbing ceMs associated with patient survival, have potential as biomarkers. Our collective findings revealed individual differences in somatic mutations perturbing ceM expression and impacting tumor heterogeneity.

Small RNA-driven feed-forward loop: fine-tuning of protein synthesis through sRNA-mediated crosstalk

Often in bacterial regulatory networks, small non-coding RNAs (sRNA) interact with several mRNA species. The competition among mRNAs for binding to the common pool of sRNA might lead to crosstalk between the mRNAs. This is similar to the competing endogenous RNA effect that leads to complex gene regulation with stabilized gene expression in Eukaryotes. Here, we study an sRNA-driven feed-forward loop (sFFL) where the top-tier regulator, an sRNA, translationally activates the target protein (TP) as well as a transcriptional activator of the TP through binding to the respective mRNAs. We show that the sRNA-mediated crosstalk between the two mRNA species enables the sFFL to function in three different regimes depending on the synthesis rate of the transcriptional activator mRNA. Of these three regimes, there exists a sensitive regime where the TP level shows interesting features depending on the precise mechanism of target translation. In the case of translation entirely from sRNA-mRNA bound complexes, the TP level becomes maximum around the sensitive regime. Through stochastic analysis and simulations, we show that relative fluctuations in the TP level is minimized here. For translation both from mRNA and sRNA-mRNA bound complexes, the target expression shows a threshold response across the sensitive regime.

A Novel Coupled Reaction-Diffusion System for Explainable Gene Expression Profiling

Machine learning (ML)-based algorithms are playing an important role in cancer diagnosis and are increasingly being used to aid clinical decision-making. However, these commonly operate as 'black boxes' and it is unclear how decisions are derived. Recently, techniques have been applied to help us understand how specific ML models work and explain the rational for outputs. This study aims to determine why a given type of cancer has a certain phenotypic characteristic. Cancer results in cellular dysregulation and a thorough consideration of cancer regulators is required. This would increase our understanding of the nature of the disease and help discover more effective diagnostic, prognostic, and treatment methods for a variety of cancer types and stages. Our study proposes a novel explainable analysis of potential biomarkers denoting tumorigenesis in non-small cell lung cancer. A number of these biomarkers are known to appear following various treatment pathways. An enhanced analysis is enabled through a novel mathematical formulation for the regulators of mRNA, the regulators of ncRNA, and the coupled mRNA-ncRNA regulators. Temporal gene expression profiles are approximated in a two-dimensional spatial domain for the transition states before converging to the stationary state, using a system comprised of coupled-reaction partial differential equations. Simulation experiments demonstrate that the proposed mathematical gene-expression profile represents a best fit for the population abundance of these oncogenes. In future, our proposed solution can lead to the development of alternative interpretable approaches, through the application of ML models to discover unknown dynamics in gene regulatory systems.

smiFISH and embryo segmentation for single-cell multi-gene RNA quantification in arthropods

Recently, advances in fluorescent in-situ hybridization techniques and in imaging technology have enabled visualization and counting of individual RNA molecules in single cells. This has greatly enhanced the resolution in our understanding of transcriptional processes. Here, we adapt a recently published smiFISH protocol (single-molecule inexpensive fluorescent in-situ hybridization) to whole embryos across a range of arthropod model species, and also to non-embryonic tissues. Using multiple fluorophores with distinct spectra and white light laser confocal imaging, we simultaneously detect and separate single RNAs from up to eight different genes in a whole embryo. We also combine smiFISH with cell membrane immunofluorescence, and present an imaging and analysis pipeline for 3D cell segmentation and single-cell RNA counting in whole blastoderm embryos. Finally, using whole embryo single-cell RNA count data, we propose two alternative single-cell variability measures to the commonly used Fano factor, and compare the capacity of these three measures to address different aspects of single-cell expression variability.

Here, the authors combine single-molecule inexpensive FISH (smiFISH) with cell membrane immunofluorescence and mathematical methods to enable whole embryo segmentation in 3D image stacks and mRNA quantification of multiple genes in each cell of the embryo.

Effects of individual base-pairs on in vivo target search and destruction kinetics of bacterial small RNA

Base-pairing interactions mediate many intermolecular target recognition events. Even a single base-pair mismatch can cause a substantial difference in activity but how such changes influence the target search kinetics in vivo is unknown. Here, we use high-throughput sequencing and quantitative super-resolution imaging to probe the mutants of bacterial small RNA, SgrS, and their regulation of ptsG mRNA target. Mutations that disrupt binding of a chaperone protein, Hfq, and are distal to the mRNA annealing region still decrease the rate of target association, k_on, and increase the dissociation rate, k_off, showing that Hfq directly facilitates sRNA-mRNA annealing in vivo. Single base-pair mismatches in the annealing region reduce k_on by 24-31% and increase k_off by 14-25%, extending the time it takes to find and destroy the target by about a third. The effects of disrupting contiguous base-pairing are much more modest than that expected from thermodynamics, suggesting that Hfq buffers base-pair disruptions.

Inference of Bacterial Small RNA Regulatory Networks and Integration with Transcription Factor-Driven Regulatory Networks

Small noncoding RNAs (sRNAs) are key regulators of bacterial gene expression. Through complementary base pairing, sRNAs affect mRNA stability and translation efficiency. Here, we describe a network inference approach designed to identify sRNA-mediated regulation of transcript levels. We use existing transcriptional data sets and prior knowledge to infer sRNA regulons using our network inference tool, the Inferelator. This approach produces genome-wide gene regulatory networks that include contributions by both transcription factors and sRNAs. We show the benefits of estimating and incorporating sRNA activities into network inference pipelines using available experimental data. We also demonstrate how these estimated sRNA regulatory activities can be mined to identify the experimental conditions where sRNAs are most active. We uncover 45 novel experimentally supported sRNA-mRNA interactions in Escherichia coli, outperforming previous network-based efforts. Additionally, our pipeline complements sequence-based sRNA-mRNA interaction prediction methods by adding a data-driven filtering step. Finally, we show the general applicability of our approach by identifying 24 novel, experimentally supported, sRNA-mRNA interactions in Pseudomonas aeruginosa, Staphylococcus aureus, and Bacillus subtilis. Overall, our strategy generates novel insights into the functional context of sRNA regulation in multiple bacterial species.

IMPORTANCE Individual bacterial genomes can have dozens of small noncoding RNAs with largely unexplored regulatory functions. Although bacterial sRNAs influence a wide range of biological processes, including antibiotic resistance and pathogenicity, our current understanding of sRNA-mediated regulation is far from complete. Most of the available information is restricted to a few well-studied bacterial species; and even in those species, only partial sets of sRNA targets have been characterized in detail. To close this information gap, we developed a computational strategy that takes advantage of available transcriptional data and knowledge about validated and putative sRNA-mRNA interactions for inferring expanded sRNA regulons. Our approach facilitates the identification of experimentally supported novel interactions while filtering out false-positive results. Due to its data-driven nature, our method prioritizes biologically relevant interactions among lists of candidate sRNA-target pairs predicted in silico from sequence analysis or derived from sRNA-mRNA binding experiments.

A tight cold-inducible switch built by coupling thermosensitive transcriptional and proteolytic regulatory parts

Natural organisms have evolved intricate regulatory mechanisms that sense and respond to fluctuating environmental temperatures in a heat- or cold-inducible fashion. Unlike dominant heat-inducible switches, very few cold-inducible genetic switches are available in either natural or engineered systems. Moreover, the available cold-inducible switches still have many shortcomings, including high leaky gene expression, small dynamic range (<10-fold) or broad transition temperature (>10°C). To address these problems, a high-performance cold-inducible switch that can tightly control target gene expression is highly desired. Here, we introduce a tight and fast cold-inducible switch that couples two evolved thermosensitive variants, TF_ts and TEV_ts, as well as an additional Mycoplasma florum Lon protease (mf-Lon) to effectively turn-off target gene expression via transcriptional and proteolytic mechanisms. We validated the function of the switch in different culture media and various Escherichia coli strains and demonstrated its tightness by regulating two morphogenetic bacterial genes and expressing three heat-unstable recombinant proteins, respectively. Moreover, the additional protease module enabled the cold-inducible switch to actively remove the pre-existing proteins in slow-growing cells. This work establishes a high-performance cold-inducible system for tight and fast control of gene expression which has great potential for basic research, as well as industrial and biomedical applications.

microRNA-mediated noise processing in cells: A fight or a game?

In the past decades, microRNAs (miRNA) have much attracted the attention of researchers at the interface between life and theoretical sciences for their involvement in post-transcriptional regulation and related diseases. Thanks to the always more sophisticated experimental techniques, the role of miRNAs as "noise processing units" has been further elucidated and two main ways of miRNA noise-control have emerged by combinations of theoretical and experimental studies. While on one side miRNAs were thought to buffer gene expression noise, it has recently been suggested that miRNAs could also increase the cell-to-cell variability of their targets. In this Mini Review, we focus on the role of miRNAs in molecular noise processing and on the advantages as well as current limitations of theoretical modelling.

Small RNAs OmrA and OmrB promote class III flagellar gene expression by inhibiting the synthesis of anti-Sigma factor FlgM

Bacteria can move by a variety of mechanisms, the best understood being flagella-mediated motility. Flagellar genes are organized in a three-tiered cascade allowing for temporally regulated expression that involves both transcriptional and post-transcriptional control. The class I operon encodes the master regulator FlhDC that drives class II gene transcription. Class II genes include fliA and flgM, which encode the Sigma factor σ²⁸, required for class III transcription, and the anti-Sigma factor FlgM, which inhibits σ²⁸ activity, respectively. The flhDC mRNA is regulated by several small regulatory RNAs (sRNAs). Two of these, the sequence-related OmrA and OmrB RNAs, inhibit FlhD synthesis. Here, we report on a second layer of sRNA-mediated control downstream of FhlDC in the flagella pathway. By mutational analysis, we confirm that a predicted interaction between the conserved 5ʹ seed sequences of OmrA/B and the early coding sequence in flgM mRNA reduces FlgM expression. Regulation is dependent on the global RNA-binding protein Hfq. In vitro experiments support a canonical mechanism: binding of OmrA/B prevents ribosome loading and decreases FlgM protein synthesis. Simultaneous inhibition of both FlhD and FlgM synthesis by OmrA/B complicated an assessment of how regulation of FlgM alone impacts class III gene transcription. Using a combinatorial mutation strategy, we were able to uncouple these two targets and demonstrate that OmrA/B-dependent inhibition of FlgM synthesis liberates σ²⁸ to ultimately promote higher expression of the class III flagellin gene fliC.

RNA-Sequencing Analyses of Small Bacterial RNAs and their Emergence as Virulence Factors in Host-Pathogen Interactions

Proteins have long been considered to be the most prominent factors regulating so-called invasive genes involved in host-pathogen interactions. The possible role of small non-coding RNAs (sRNAs), either intracellular, secreted or packaged in outer membrane vesicles (OMVs), remained unclear until recently. The advent of high-throughput RNA-sequencing (RNA-seq) techniques has accelerated sRNA discovery. RNA-seq radically changed the paradigm on bacterial virulence and pathogenicity to the point that sRNAs are emerging as an important, distinct class of virulence factors in both gram-positive and gram-negative bacteria. The potential of OMVs, as protectors and carriers of these functional, gene regulatory sRNAs between cells, has also provided an additional layer of complexity to the dynamic host-pathogen relationship. Using a non-exhaustive approach and through examples, this review aims to discuss the involvement of sRNAs, either free or loaded in OMVs, in the mechanisms of virulence and pathogenicity during bacterial infection. We provide a brief overview of sRNA origin and importance, and describe the classical and more recent methods of identification that have enabled their discovery, with an emphasis on the theoretical lower limit of RNA sizes considered for RNA sequencing and bioinformatics analyses.

Digitalizing heterologous gene expression in Gram-negative bacteria with a portable ON/OFF module

While prokaryotic promoters controlled by signal-responding regulators typically display a range of input/output ratios when exposed to cognate inducers, virtually no naturally occurring cases are known to have an OFF state of zero transcription-as ideally needed for synthetic circuits. To overcome this problem, we have modelled and implemented a simple digitalizer module that completely suppresses the basal level of otherwise strong promoters in such a way that expression in the absence of induction is entirely impeded. The circuit involves the interplay of a translation-inhibitory sRNA with the translational coupling of the gene of interest to a repressor such as LacI. The digitalizer module was validated with the strong inducible promoters Pm (induced by XylS in the presence of benzoate) and PalkB (induced by AlkS/dicyclopropyl ketone) and shown to perform effectively in both Escherichia coli and the soil bacterium Pseudomonas putida. The distinct expression architecture allowed cloning and conditional expression of, e.g. colicin E3, one molecule of which per cell suffices to kill the host bacterium. Revertants that escaped ColE3 killing were not found in hosts devoid of insertion sequences, suggesting that mobile elements are a major source of circuit inactivation in vivo.

Self-replenishment cycles generate a threshold response

Many metabolic cycles, including the tricarboxylic acid cycle, glyoxylate cycle, Calvin cycle, urea cycle, coenzyme recycling, and substrate cycles, are well known to catabolize and anabolize different metabolites for efficient energy and mass conversion. In terms of stoichiometric structure, this study explicitly identifies two types of metabolic cycles. One is the well-known, elementary cycle that converts multiple substrates into different products and recycles one of the products as a substrate, where the recycled substrate is supplied from the outside to run the cycle. The other is the self-replenishment cycle that merges multiple substrates into two or multiple identical products and reuses one of the products as a substrate. The substrates are autonomously supplied within the cycle. This study first defines the self-replenishment cycles that many scientists have overlooked despite its functional importance. Theoretical analysis has revealed the design principle of the self-replenishment cycle that presents a threshold response without any bistability nor cooperativity. To verify the principle, three detailed kinetic models of self-replenishment cycles embedded in an E. coli metabolic system were simulated. They presented the threshold response or digital switch-like function that steeply shift metabolic status.

Multidrug Resistance Regulators MarA, SoxS, Rob, and RamA Repress Flagellar Gene Expression and Motility in Salmonella enterica Serovar Typhimurium

Production of flagella is costly and subject to global multilayered regulation, which is reflected in the hierarchical control of flagellar production in many bacterial species. For Salmonella enterica serovar Typhimurium and its relatives, global regulation of flagellar production primarily occurs through the control of flhDC transcription and mRNA translation. In this study, the roles of the homologous multidrug resistance regulators MarA, SoxS, Rob, and RamA (constituting the mar-sox-rob regulon in S Typhimurium) in regulating flagellar gene expression were explored. Each of these regulators was found to inhibit flagellar gene expression, production of flagella, and motility. To different degrees, repression via these transcription factors occurred through direct interactions with the flhDC promoter, particularly for MarA and Rob. Additionally, SoxS repressed flagellar gene expression via a posttranscriptional pathway, reducing flhDC translation. The roles of these transcription factors in reducing motility in the presence of salicylic acid were also elucidated, adding a genetic regulatory element to the response of S Typhimurium to this well-characterized chemorepellent. Integration of flagellar gene expression into the mar-sox-rob regulon in S Typhimurium contrasts with findings for closely related species such as Escherichia coli, providing an example of plasticity in the mar-sox-rob regulon throughout the Enterobacteriaceae family.IMPORTANCE The mar-sox-rob regulon is a large and highly conserved stress response network in the Enterobacteriaceae family. Although it is well characterized in E. coli, the extent of this regulon in related species is unclear. Here, the control of costly flagellar gene expression is connected to the mar-sox-rob regulon of S Typhimurium, contrasting with the E. coli regulon model. These findings demonstrate the flexibility of the mar-sox-rob regulon to accommodate novel regulatory targets, and they provide evidence for its broader regulatory role within this family of diverse bacteria.

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.

Determinants of target prioritization and regulatory hierarchy for the bacterial small RNA SgrS

Small RNA (sRNA) regulators promote efficient responses to stress, but the mechanisms for prioritizing target mRNA regulation remain poorly understood. This study examines mechanisms underlying hierarchical regulation by the sRNA SgrS, found in enteric bacteria and produced under conditions of metabolic stress. SgrS posttranscriptionally coordinates a nine-gene regulon to restore growth and homeostasis. An in vivo reporter system quantified SgrS-dependent regulation of target genes and established that SgrS exhibits a clear target preference. Regulation of some targets is efficient even at low SgrS levels, whereas higher SgrS concentrations are required to regulate other targets. In vivo and in vitro analyses revealed that RNA structure and the number and position of base pairing sites relative to the start of translation impact the efficiency of regulation of SgrS targets. The RNA chaperone Hfq uses distinct modes of binding to different SgrS mRNA targets, which differentially influences positive and negative regulation. The RNA degradosome plays a larger role in regulation of some SgrS targets compared to others. Collectively, our results suggest that sRNA selection of target mRNAs and regulatory hierarchy are influenced by several molecular features and that the combination of these features precisely tunes the efficiency of regulation of multi-target sRNA regulons.

Translational thresholds in a core circadian clock model

Organisms have evolved in a daily cyclic environment, developing circadian cell-autonomous clocks that temporally organize a wide range of biological processes. Translation is a highly regulated process mainly associated with the activity of microRNAs (miRNAs) at the translation initiation step that impacts on the molecular circadian clock dynamics. Recently, a molecular titration mechanism was proposed to explain the interactions between some miRNAs and their target mRNAs; new evidence also indicates that regulation by miRNA is a nonlinear process such that there is a threshold level of target mRNA below which protein production is drastically repressed. These observations led us to use a theoretical model of the circadian molecular clock to study the effect of miRNA-mediated translational thresholds on the molecular clock dynamics. We model the translational threshold by introducing a phenomenological Hill equation for the kinetics of PER translation and show how the parameters associated with translation kinetics affect the period, amplitude, and time delays between clock mRNA and clock protein expression. We show that our results are useful for analyzing experiments related to the translational regulation of negative elements of transcriptional-translational feedback loops. We also provide new elements for thinking about the translational threshold as a mechanism that favors the emergence of circadian rhythmicity, the tuning of the period-delay relationship and the cell capacity to control the protein oscillation amplitude with almost negligible changes in the mRNA amplitudes.

The number of titrated microRNA species dictates ceRNA regulation

microRNAs (miRNAs) play key roles in cancer, but their propensity to couple their targets as competing endogenous RNAs (ceRNAs) has only recently emerged. Multiple models have studied ceRNA regulation, but these models did not account for the effects of co-regulation by miRNAs with many targets. We modeled ceRNA and simulated its effects using established parameters for miRNA/mRNA interaction kinetics while accounting for co-regulation by multiple miRNAs with many targets. Our simulations suggested that co-regulation by many miRNA species is more likely to produce physiologically relevant context-independent couplings. To test this, we studied the overlap of inferred ceRNA networks from four tumor contexts-our proposed pan-cancer ceRNA interactome (PCI). PCI was composed of interactions between genes that were co-regulated by nearly three-times as many miRNAs as other inferred ceRNA interactions. Evidence from expression-profiling datasets suggested that PCI interactions are predictive of gene expression in 12 independent tumor- and non-tumor contexts. Biochemical assays confirmed ceRNA couplings for two PCI subnetworks, including oncogenes CCND1, HIF1A and HMGA2, and tumor suppressors PTEN, RB1 and TP53. Our results suggest that PCI is enriched for context-independent interactions that are coupled by many miRNA species and are more likely to be context independent.

Synthetic negative feedback circuits using engineered small RNAs

Negative feedback is known to enable biological and man-made systems to perform reliably in the face of uncertainties and disturbances. To date, synthetic biological feedback circuits have primarily relied upon protein-based, transcriptional regulation to control circuit output. Small RNAs (sRNAs) are non-coding RNA molecules that can inhibit translation of target messenger RNAs (mRNAs). In this work, we modelled, built and validated two synthetic negative feedback circuits that use rationally-designed sRNAs for the first time. The first circuit builds upon the well characterised tet-based autorepressor, incorporating an externally-inducible sRNA to tune the effective feedback strength. This allows more precise fine-tuning of the circuit output in contrast to the sigmoidal, steep input–output response of the autorepressor alone. In the second circuit, the output is a transcription factor that induces expression of an sRNA, which inhibits translation of the mRNA encoding the output, creating direct, closed-loop, negative feedback. Analysis of the noise profiles of both circuits showed that the use of sRNAs did not result in large increases in noise. Stochastic and deterministic modelling of both circuits agreed well with experimental data. Finally, simulations using fitted parameters allowed dynamic attributes of each circuit such as response time and disturbance rejection to be investigated.

Realizing 'integral control' in living cells: how to overcome leaky integration due to dilution?

A major problem in the design of synthetic genetic circuits is robustness to perturbations and uncertainty. Because of this, there have been significant efforts in recent years in finding approaches to implement integral control in genetic circuits. Integral controllers have the unique ability to make the output of a process adapt perfectly to disturbances. However, implementing an integral controller is challenging in living cells. This is because a key aspect of any integral controller is a 'memory' element that stores the accumulation (integral) of the error between the output and its desired set-point. The ability to realize such a memory element in living cells is fundamentally challenged by the fact that all biomolecules dilute as cells grow, resulting in a 'leaky' memory that gradually fades away. As a consequence, the adaptation property is lost. Here, we propose a general principle for designing integral controllers such that the performance is practically unaffected by dilution. In particular, we mathematically prove that if the reactions implementing the integral controller are all much faster than dilution, then the adaptation error due to integration leakiness becomes negligible. We exemplify this design principle with two synthetic genetic circuits aimed at reaching adaptation of gene expression to fluctuations in cellular resources. Our results provide concrete guidance on the biomolecular processes that are most appropriate for implementing integral controllers in living cells.

Stochastic Modeling of Gene Regulation by Noncoding Small RNAs in the Strong Interaction Limit

Noncoding small RNAs (sRNAs) are known to play a key role in regulating diverse cellular processes, and their dysregulation is linked to various diseases such as cancer. Such diseases are also marked by phenotypic heterogeneity, which is often driven by the intrinsic stochasticity of gene expression. Correspondingly, there is significant interest in developing quantitative models focusing on the interplay between stochastic gene expression and regulation by sRNAs. We consider the canonical model of regulation of stochastic gene expression by sRNAs, wherein interaction between constitutively expressed sRNAs and mRNAs leads to stoichiometric mutual degradation. The exact solution of this model is analytically intractable given the nonlinear interaction term between sRNAs and mRNAs, and theoretical approaches typically invoke the mean-field approximation. However, mean-field results are inaccurate in the limit of strong interactions and low abundances; thus, alternative theoretical approaches are needed. In this work, we obtain analytical results for the canonical model of regulation of stochastic gene expression by sRNAs in the strong interaction limit. We derive analytical results for the steady-state generating function of the joint distribution of mRNAs and sRNAs in the limit of strong interactions and use the results derived to obtain analytical expressions characterizing the corresponding protein steady-state distribution. The results obtained can serve as building blocks for the analysis of genetic circuits involving sRNAs and provide new insights into the role of sRNAs in regulating stochastic gene expression in the limit of strong interactions.

Spatiotemporal establishment of dense bacterial colonies growing on hard agar

The physical interactions of growing bacterial cells with each other and with their surroundings significantly affect the structure and dynamics of biofilms. Here a 3D agent-based model is formulated to describe the establishment of simple bacterial colonies expanding by the physical force of their growth. With a single set of parameters, the model captures key dynamical features of colony growth by non-motile, non EPS-producing E. coli cells on hard agar. The model, supported by experiment on colony growth in different types and concentrations of nutrients, suggests that radial colony expansion is not limited by nutrients as commonly believed, but by mechanical forces. Nutrient penetration instead governs vertical colony growth, through thin layers of vertically oriented cells lifting up their ancestors from the bottom. Overall, the model provides a versatile platform to investigate the influences of metabolic and environmental factors on the growth and morphology of bacterial colonies.

Small RNA-Based Regulation of Bacterial Quorum Sensing and Biofilm Formation

Quorum sensing is a vital property of bacteria that enables community-wide coordination of collective behaviors. A key example of such a behavior is biofilm formation, in which groups of bacteria invest in synthesizing a protective, joint extracellular matrix. Quorum sensing involves the production, release, and subsequent detection of extracellular signaling molecules called autoinducers. The architecture of quorum-sensing signal transduction pathways is highly variable among different species of bacteria, but frequently involves posttranscriptional regulation carried out by small regulatory RNA molecules. This review illustrates the diverse roles small trans-acting regulatory RNAs can play, from constituting a network's core to auxiliary roles in adjusting the rate of autoinducer synthesis, mediating cross talk among different parts of a network, or integrating different regulatory inputs to trigger appropriate changes in gene expression. The emphasis is on describing how the study of small RNA-based regulation in quorum sensing and biofilm formation has uncovered new general properties or expanded our understanding of bacterial riboregulation.

Bacterial Small RNAs in Mixed Regulatory Networks

Small regulatory RNAs are now recognized as key regulators of gene expression in bacteria. They accumulate under specific conditions, most often because their synthesis is directly controlled by transcriptional regulators, including but not limited to alternative sigma factors and response regulators of two-component systems. In turn, small RNAs regulate, mostly at the posttranscriptional level, expression of multiple genes, among which are genes encoding transcriptional regulators. Small RNAs are thus embedded in mixed regulatory circuits combining transcriptional and posttranscriptional controls, and whose properties are discussed here.

Modeling slow-processing of toxin messenger RNAs in type-I toxin-antitoxin systems: post-segregational killing and noise filtering

In type-I toxin-antitoxin (TA) systems, the action of growth-inhibiting toxin proteins is counteracted by the antitoxin small RNAs (sRNAs) that prevent the translation of toxin messenger RNAs (mRNAs). When a TA module is encoded on a plasmid, the short lifetime of antitoxin sRNA compared to toxin mRNAs mediates post-segregational killing (PSK) that contribute the plasmid maintenance, while some of the chromosomal encoded TA loci have been reported to contribute to persister formation in response to a specific upstream signal. Some of the well studied type-I TA systems such as hok/sok are known to have a rather complex regulatory mechanism. Transcribed full-length toxin mRNAs fold such that the ribosome binding site is not accessible and hence cannot be translated. The mRNAs are slowly processed by RNases, and the truncated mRNAs can be either translated or bound by antitoxin sRNA to be quickly degraded. We analyze the role of this extra processing by a mathematical model. We first consider the PSK scenario, and demonstrate that the extra processing compatibly ensures the high toxin expression upon complete plasmid loss, without inducing toxin expression upon acquisition of a plasmid or decrease of plasmid number to a non-zero number. We further show that the extra processing help filtering the transcription noise, avoiding random activation of toxins in transcriptionally regulated TA systems as seen in chromosomal ones. The present model highlights impacts of the slow processing reaction, offering insights on why the slow processing reactions are commonly identified in multiple type-I TA systems.

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.

Quantitative Characteristic of ncRNA Regulation in Gene Regulatory Networks

RNA is mostly known for its role in protein synthesis, where it encodes information for protein sequence in its messenger RNA (mRNA) form (translation). Yet, RNA molecules regulate several cellular processes other than translation. Here, we present an overview of several mathematical models that help understanding and characterizing the role of noncoding RNA molecules (ncRNAs) in regulating gene expression and protein synthesis. First, we discuss relatively simple models where ncRNAs can modulate protein synthesis via targeting a mRNA. Then, we consider the case of feedback interactions between ncRNAs and their target proteins, and discuss several biological applications where these feedback architectures modulate a cellular phenotype and control the levels of intrinsic and extrinsic noise. Building from these simple circuit motifs, we examine feed-forward circuit motifs involving ncRNAs that generate precise spatial and temporal patterns of protein expression. Further, we investigate the competition between ncRNAs and other endogenous RNA molecules and show that the cross talk between coding and noncoding RNAs can form large genetic circuits that involve up to hundreds of chemical species. Finally, we discuss the role of ncRNAs in modulating cell-cell signaling pathways and therefore the dynamics of spatiotemporal pattern formation in a tissue.