Experimental measurement and computational prediction of bacterial Hanks-type Ser/Thr signaling system regulatory targets.

Bacteria possess diverse classes of signaling systems that they use to sense and respond to their environments and execute properly timed developmental transitions. One widespread and evolutionarily ancient class of signaling systems are the Hanks-type Ser/Thr kinases, also sometimes termed "eukaryotic-like" due to their homology with eukaryotic kinases. In diverse bacterial species, these signaling systems function as critical regulators of general cellular processes such as metabolism, growth and division, developmental transitions such as sporulation, biofilm formation, and virulence, as well as antibiotic tolerance. This multifaceted regulation is due to the ability of a single Hanks-type Ser/Thr kinase to post-translationally modify the activity of multiple proteins, resulting in the coordinated regulation of diverse cellular pathways. However, in part due to their deep integration with cellular physiology, to date, we have a relatively limited understanding of the timing, regulatory hierarchy, the complete list of targets of a given kinase, as well as the potential regulatory overlap between the often multiple kinases present in a single organism. In this review, we discuss experimental methods and curated datasets aimed at elucidating the targets of these signaling pathways and approaches for using these datasets to develop computational models for quantitative predictions of target motifs. We emphasize novel approaches and opportunities for collecting data suitable for the creation of new predictive computational models applicable to diverse species.

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

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

Stochastic feeding dynamics arise from the need for information and energy.

Animals regulate their food intake in response to the available level of food. Recent observations of feeding dynamics in small animals showed feeding patterns of bursts and pauses, but their function is unknown. Here, we present a data-driven decision-theoretical model of feeding in Caenorhabditis elegans Our central assumption is that food intake serves a dual purpose: to gather information about the external food level and to ingest food when the conditions are good. The model recapitulates experimentally observed feeding patterns. It naturally implements trade-offs between speed versus accuracy and exploration versus exploitation in responding to a dynamic environment. We find that the model predicts three distinct regimes in responding to a dynamical environment, with a transition region where animals respond stochastically to periodic signals. This stochastic response accounts for previously unexplained experimental data.

Mechanisms of fast and stringent search in homologous pairing of double-stranded DNA.

Self-organization in the cell relies on the rapid and specific binding of molecules to their cognate targets. Correct bindings must be stable enough to promote the desired function even in the crowded and fluctuating cellular environment. In systems with many nearly matched targets, rapid and stringent formation of stable products is challenging. Mechanisms that overcome this challenge have been previously proposed, including separating the process into multiple stages; however, how particular in vivo systems overcome the challenge remains unclear. Here we consider a kinetic system, inspired by homology dependent pairing between double stranded DNA in bacteria. By considering a simplified tractable model, we identify different homology testing stages that naturally occur in the system. In particular, we first model dsDNA molecules as short rigid rods containing periodically spaced binding sites. The interaction begins when the centers of two rods collide at a random angle. For most collision angles, the interaction energy is weak because only a few binding sites near the collision point contribute significantly to the binding energy. We show that most incorrect pairings are rapidly rejected at this stage. In rare cases, the two rods enter a second stage by rotating into parallel alignment. While rotation increases the stability of matched and nearly matched pairings, subsequent rotational fluctuations reduce kinetic trapping. Finally, in vivo chromosome are much longer than the persistence length of dsDNA, so we extended the model to include multiple parallel collisions between long dsDNA molecules, and find that those additional interactions can greatly accelerate the searching.

The let-7-Imp axis regulates ageing of the Drosophila testis stem-cell niche.

Adult stem cells support tissue homeostasis and repair throughout the life of an individual. During ageing, numerous intrinsic and extrinsic changes occur that result in altered stem-cell behaviour and reduced tissue maintenance and regeneration. In the Drosophila testis, ageing results in a marked decrease in the self-renewal factor Unpaired (Upd), leading to a concomitant loss of germline stem cells. Here we demonstrate that IGF-II messenger RNA binding protein (Imp) counteracts endogenous small interfering RNAs to stabilize upd (also known as os) RNA. However, similar to upd, Imp expression decreases in the hub cells of older males, which is due to the targeting of Imp by the heterochronic microRNA let-7. In the absence of Imp, upd mRNA therefore becomes unprotected and susceptible to degradation. Understanding the mechanistic basis for ageing-related changes in stem-cell behaviour will lead to the development of strategies to treat age-onset diseases and facilitate stem-cell-based therapies in older individuals.

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

Small non-coding RNAs can exert significant regulatory activity on gene expression in bacteria. In recent years, substantial progress has been made in understanding bacterial gene expression by sRNAs. However, recent findings that demonstrate that families of mRNAs show non-trivial sub-cellular distributions raise the question of how localization may affect the regulatory activity of sRNAs. Here we address this question within a simple mathematical model. We show that the non-uniform spatial distributions of mRNA can alter the threshold-linear response that characterizes sRNAs that act stoichiometrically, and modulate the hierarchy among targets co-regulated by the same sRNA. We also identify conditions where the sub-cellular organization of cofactors in the sRNA pathway can induce spatial heterogeneity on sRNA targets. Our results suggest that under certain conditions, interpretation and modeling of natural and synthetic gene regulatory circuits need to take into account the spatial organization of the transcripts of participating genes.

Serotonin promotes exploitation in complex environments by accelerating decision-making.

BACKGROUND: Fast responses can provide a competitive advantage when resources are inhomogeneously distributed. The nematode Caenorhabditis elegans was shown to modulate locomotion on a lawn of bacterial food in serotonin (5-HT)-dependent manners. However, potential roles for serotonergic signaling in responding to food discovery are poorly understood. RESULTS: We found that 5-HT signaling in C. elegans facilitates efficient exploitation in complex environments by mediating a rapid response upon encountering food. Genetic or cellular manipulations leading to deficient serotonergic signaling resulted in gradual responses and defective exploitation of a patchy foraging landscape. Physiological imaging revealed that the NSM serotonergic neurons responded acutely upon encounter with newly discovered food and were key to rapid responses. In contrast, the onset of responses of ADF serotonergic neurons preceded the physical encounter with the food. The serotonin-gated chloride channel MOD-1 and the ortholog of mammalian 5-HT1 metabotropic serotonin receptors SER-4 acted in synergy to accelerate decision-making. The relevance of responding rapidly was demonstrated in patchy environments, where the absence of 5-HT signaling was detrimental to exploitation. CONCLUSIONS: Our results implicate 5-HT in a novel form of decision-making, demonstrate its fitness consequences, suggest that NSM and ADF act in concert to modulate locomotion in complex environments, and identify the synergistic action of a channel and a metabotropic receptor in accelerating C. elegans decision-making.

Sort-seq under the hood: implications of design choices on large-scale characterization of sequence-function relations.

BACKGROUND: Sort-seq is an effective approach for simultaneous activity measurements in a large-scale library, combining flow cytometry, deep sequencing, and statistical inference. Such assays enable the characterization of functional landscapes at unprecedented scale for a wide-reaching array of biological molecules and functionalities in vivo. Applications of sort-seq range from footprinting to establishing quantitative models of biological systems and rational design of synthetic genetic elements. Nearly as diverse are implementations of this technique, reflecting key design choices with extensive impact on the scope and accuracy the results. Yet how to make these choices remains unclear. Here we investigate the effects of alternative sort-seq designs and inference methods on the information output using mathematical formulation and simulations. RESULTS: We identify key intrinsic properties of any system of interest with practical implications for sort-seq assays, depending on the experimental goals. The fluorescence range and cell-to-cell variability specify the number of sorted populations needed for quantitative measurements that are precise and unbiased. These factors also indicate cases where an enrichment-based approach that uses a single sorted population can offer satisfactory results. These predications of our model are corroborated using re-analysis of published data. We explore implications of these results for quantitative modeling and library design. CONCLUSIONS: Sort-seq assays can be streamlined by reducing the number of sorted populations, saving considerable resources. Simple preliminary experiments can guide optimal experiment design, minimizing cost while maintaining the maximal information output and avoiding latent biases. These insights can facilitate future applications of this highly adaptable technique.

Quantitative effect of target translation on small RNA efficacy reveals a novel mode of interaction.

Small regulatory RNAs (sRNAs) in bacteria regulate many important cellular activities under normal conditions and in response to stress. Many sRNAs bind to the mRNA targets at or near the 5' untranslated region (UTR) resulting in translation inhibition and accelerated degradation. Often the sRNA-binding site is adjacent to or overlapping with the ribosomal binding site (RBS), suggesting a possible interplay between sRNA and ribosome binding. Here we combine quantitative experiments with mathematical modeling to reveal novel features of the interaction between small RNAs and the translation machinery at the 5'UTR of a target mRNA. By measuring the response of a library of reporter targets with varied RBSs, we find that increasing translation rate can lead to increased repression. Quantitative analysis of these data suggests a recruitment model, where bound ribosomes facilitate binding of the sRNA. We experimentally verified predictions of this model for the cell-to-cell variability of target expression. Our findings offer a framework for understanding sRNA silencing in the context of bacterial physiology.

Large-scale mapping of sequence-function relations in small regulatory RNAs reveals plasticity and modularity.

Two decades into the genomics era the question of mapping sequence to function has evolved from identifying functional elements to characterizing their quantitative properties including, in particular, their specificity and efficiency. Here, we use a large-scale approach to establish a quantitative map between the sequence of a bacterial regulatory RNA and its efficiency in modulating the expression of its targets. Our approach generalizes the sort-seq method, introduced recently to analyze promoter sequences, in order to accurately quantify the efficiency of a large library of sequence variants. We focus on two small RNAs (sRNAs) in E. coli, DsrA and RyhB, and their regulation of both repressed and activated targets. In addition to precisely identifying functional elements in the sRNAs, our data establish quantitative relationships between structural and energetic features of the sRNAs and their regulatory activity, and characterize a large set of direct and indirect interactions between nucleotides. A core of these interactions supports a model where specificity can be enhanced by a rigid molecular structure. Both sRNAs exhibit a modular design with limited cross-interactions, dividing the requirements for structural stability and target binding among modules.

Exploring the miRNA regulatory network using evolutionary correlations.

Post-transcriptional regulation by miRNAs is a widespread and highly conserved phenomenon in metazoans, with several hundreds to thousands of conserved binding sites for each miRNA, and up to two thirds of all genes under miRNA regulation. At the same time, the effect of miRNA regulation on mRNA and protein levels is usually quite modest and associated phenotypes are often weak or subtle. This has given rise to the notion that the highly interconnected miRNA regulatory network exerts its function less through any individual link and more via collective effects that lead to a functional interdependence of network links. We present a Bayesian framework to quantify conservation of miRNA target sites using vertebrate whole-genome alignments. The increased statistical power of our phylogenetic model allows detection of evolutionary correlation in the conservation patterns of site pairs. Such correlations could result from collective functions in the regulatory network. For instance, co-conservation of target site pairs supports a selective benefit of combinatorial regulation by multiple miRNAs. We find that some miRNA families are under pronounced co-targeting constraints, indicating a high connectivity in the regulatory network, while others appear to function in a more isolated way. By analyzing coordinated targeting of different curated gene sets, we observe distinct evolutionary signatures for protein complexes and signaling pathways that could reflect differences in control strategies. Our method is easily scalable to analyze upcoming larger data sets, and readily adaptable to detect high-level selective constraints between other genomic loci. We thus provide a proof-of-principle method to understand regulatory networks from an evolutionary perspective.

Regulating the many to benefit the few: role of weak small RNA targets.

Small regulatory RNAs are central players in the regulation of many cellular processes across all kingdoms of life. Experiments in mouse and human have shown that a typical small RNA may regulate the expression of many different genes, suggesting that small RNAs act as global regulators. It is noted though that most targets respond only weakly to the presence of the small RNA. At the same time, evidence in bacteria and animals suggest that the phenotypes associated with small RNA mutants are only due to a few of their targets. Here we assume that targets regulated by a small RNA to control function is in fact small, and propose that the role of the many other weak targets is to confer robustness to the regulation of these few principal targets. Through mathematical modeling we show that auxiliary targets may significantly buffer both number and kinetic fluctuations of the principal targets, with only minor slowdown in the kinetics of response. Analysis of genomic data suggests that auxiliary targets experience a nonspecific evolutionary pressure, playing a role at the system level. Our work is of importance for studies on small RNA functions, and impacts on the understanding of small RNA evolution.

Primer on Mathematical Modeling in C. elegans.

Recently, applications of mathematical and computational models to biological processes have helped investigators to systematically interpret data, test hypotheses built on experimental data, generate new hypotheses, and guide the design of new experiments, protocols, and synthetic biological systems. Availability of diverse quantitative data is a prerequisite for successful mathematical modeling. The ability to acquire high-quality quantitative data for a broad range of biological processes and perform precise perturbation makes C. elegans an ideal model system for such studies. In this primer, we examine the general procedure of modeling biological systems and demonstrate this process using the heat-shock response in C. elegans as a case study. Our goal is to facilitate the initial discussion between worm biologists and their potential collaborators from quantitative disciplines.

Lessons Learned from Two Decades of Modeling the Heat-Shock Response.

The Heat Shock Response (HSR) is a highly conserved genetic system charged with protecting the proteome in a wide range of organisms and species. Experiments since the early 1980s have elucidated key elements in these pathways and revealed a canonical mode of regulation, which relies on a titration feedback. This system has been subject to substantial modeling work, addressing questions about resilience, design and control. The compact core regulatory circuit, as well as its apparent conservation, make this system an ideal 'hydrogen atom' model for the regulation of stress response. Here we take a broad view of the models of the HSR, focusing on the different questions asked and the approaches taken. After 20 years of modeling work, we ask what lessons had been learned that would have been hard to discover without mathematical models. We find that while existing models lay strong foundations, many important questions that can benefit from quantitative modeling are still awaiting investigation.

Quantitative characteristics of gene regulation by small RNA.

An increasing number of small RNAs (sRNAs) have been shown to regulate critical pathways in prokaryotes and eukaryotes. In bacteria, regulation by trans-encoded sRNAs is predominantly found in the coordination of intricate stress responses. The mechanisms by which sRNAs modulate expression of its targets are diverse. In common to most is the possibility that interference with the translation of mRNA targets may also alter the abundance of functional sRNAs. Aiming to understand the unique role played by sRNAs in gene regulation, we studied examples from two distinct classes of bacterial sRNAs in Escherichia coli using a quantitative approach combining experiment and theory. Our results demonstrate that sRNA provides a novel mode of gene regulation, with characteristics distinct from those of protein-mediated gene regulation. These include a threshold-linear response with a tunable threshold, a robust noise resistance characteristic, and a built-in capability for hierarchical cross-talk. Knowledge of these special features of sRNA-mediated regulation may be crucial toward understanding the subtle functions that sRNAs can play in coordinating various stress-relief pathways. Our results may also help guide the design of synthetic genetic circuits that have properties difficult to attain with protein regulators alone.

Microfluidic approaches for Caenorhabditis elegans research.

In the last decade, microfluidic methods have proven to be powerful tools for Caenorhabditis elegans research, offering advanced manipulation of worms and precise control of experimental conditions. The advantages of microfluidic chips include their capability of immobilization, automated sorting, and longitudinal measurement, and more. In this review, we focus on control components that are widely used in the design of microfluidic devices, and discuss their functions and working principles that enable advanced manipulation on a chip. Understanding these components will ease the onboarding of researchers inexperienced with microfluidics and help them bring the power of microfluidics to new applications.

Small regulatory RNAs may sharpen spatial expression patterns.

The precise establishment of gene expression patterns is a crucial step in development. Formation of a sharp boundary between high and low spatial expression domains requires a genetic mechanism that exhibits sensitivity, yet is robust to fluctuations, a demand that may not be easily achieved by morphogens alone. Recently, it has been demonstrated that small RNAs (and, in particular, microRNAs) play many roles in embryonic development. Whereas some RNAs are essential for embryogenesis, others are limited to fine-tuning a predetermined gene expression pattern. Here, we explore the possibility that small RNAs participate in sharpening a gene expression profile that was crudely established by a morphogen. To this end, we study a model in which small RNAs interact with a target gene and diffusively move from cell to cell. Though diffusion generally smoothens spatial expression patterns, we find that intercellular mobility of small RNAs is actually critical in sharpening the interface between target expression domains in a robust manner. This sharpening occurs as small RNAs diffuse into regions of low mRNA expression and eliminate target molecules therein, but cannot affect regions of high mRNA levels. We discuss the applicability of our results, as examples, to the case of leaf polarity establishment in maize and Hox patterning in the early Drosophila embryo. Our findings point out the functional significance of some mechanistic properties, such as mobility of small RNAs and the irreversibility of their interactions. These properties are yet to be established directly for most classes of small RNAs. An indirect yet simple experimental test of the proposed mechanism is suggested in some detail.

A Microfluidic Platform for Longitudinal Imaging in Caenorhabditis elegans.

In the last decade, microfluidic techniques have been applied to study small animals, including the nematode Caenorhabditis elegans, and have proved useful as a convenient live imaging platform providing capabilities for precise control of experimental conditions in real time. In this article, we demonstrate live imaging of individual worms employing WormSpa, a previously-published custom microfluidic device. In the device, multiple worms are individually confined to separate chambers, allowing multiplexed longitudinal surveillance of various biological processes. To illustrate the capability, we performed proof-of-principle experiments in which worms were infected in the device with pathogenic bacteria, and the dynamics of expression of immune response genes and egg laying were monitored continuously in individual animals. The simple design and operation of this device make it suitable for users with no previous experience with microfluidic-based experiments. We propose that this approach will be useful for many researchers interested in longitudinal observations of biological processes under well-defined conditions.

Target-specific and global effectors in gene regulation by MicroRNA.

MicroRNAs are responsible for post-transcriptional gene silencing as part of critical cellular pathways and intercellular coordination, for example during embryonic development. Yet, the basic mechanism by which this silencing is accomplished is still not understood. For example, it is not known to what extent and through what process does the suppression of protein accumulation accompany a reduction in mRNA level. Here we present a simple quantitative modeling approach to microRNA mediated silencing. We show how differential responses of the mRNA- and protein levels may be tuned by target-specific parameters and how global effectors may alter this behavior for some-but not all-miRNA targets in the cell.

Serotonin-dependent kinetics of feeding bursts underlie a graded response to food availability in C. elegans.

Animals integrate physiological and environmental signals to modulate their food uptake. The nematode C. elegans, whose food uptake consists of pumping bacteria from the environment into the gut, provides excellent opportunities for discovering principles of conserved regulatory mechanisms. Here we show that worms implement a graded feeding response to the concentration of environmental bacteria by modulating a commitment to bursts of fast pumping. Using long-term, high-resolution, longitudinal recordings of feeding dynamics under defined conditions, we find that the frequency and duration of pumping bursts increase and the duration of long pauses diminishes in environments richer in bacteria. The bioamine serotonin is required for food-dependent induction of bursts as well as for maintaining their high rate of pumping through two distinct mechanisms. We identify the differential roles of distinct families of serotonin receptors in this process and propose that regulation of bursts is a conserved mechanism of behaviour and motor control.