Metazoan operons accelerate recovery from growth-arrested states.

Existing theories explain why operons are advantageous in prokaryotes, but their occurrence in metazoans is an enigma. Nematode operon genes, typically consisting of growth genes, are significantly upregulated during recovery from growth-arrested states. This expression pattern is anticorrelated to nonoperon genes, consistent with a competition for transcriptional resources. We find that transcriptional resources are initially limiting during recovery and that recovering animals are highly sensitive to any additional decrease in transcriptional resources. We provide evidence that operons become advantageous because, by clustering growth genes into operons, fewer promoters compete for the limited transcriptional machinery, effectively increasing the concentration of transcriptional resources and accelerating recovery. Mathematical modeling reveals how a moderate increase in transcriptional resources can substantially enhance transcription rate and recovery. This design principle occurs in different nematodes and the chordate C. intestinalis. As transition from arrest to rapid growth is shared by many metazoans, operons could have evolved to facilitate these processes.

The synaptic organization in the Caenorhabditis elegans neural network suggests significant local compartmentalized computations.

Neurons are characterized by elaborate tree-like dendritic structures that support local computations by integrating multiple inputs from upstream presynaptic neurons. It is less clear whether simple neurons, consisting of a few or even a single neurite, may perform local computations as well. To address this question, we focused on the compact neural network of Caenorhabditis elegans animals for which the full wiring diagram is available, including the coordinates of individual synapses. We find that the positions of the chemical synapses along the neurites are not randomly distributed nor can they be explained by anatomical constraints. Instead, synapses tend to form clusters, an organization that supports local compartmentalized computations. In mutually synapsing neurons, connections of opposite polarity cluster separately, suggesting that positive and negative feedback dynamics may be implemented in discrete compartmentalized regions along neurites. In triple-neuron circuits, the nonrandom synaptic organization may facilitate local functional roles, such as signal integration and coordinated activation of functionally related downstream neurons. These clustered synaptic topologies emerge as a guiding principle in the network, presumably to facilitate distinct parallel functions along a single neurite, which effectively increase the computational capacity of the neural network.

A negative feedback loop in the GPCR pathway underlies efficient coding of external stimuli.

Efficient navigation based on chemical cues is an essential feature shared by all animals. These cues may be encountered in complex spatiotemporal patterns and with orders of magnitude varying intensities. Nevertheless, sensory neurons accurately extract the relevant information from such perplexing signals. Here, we show how a single sensory neuron in Caenorhabditis elegans animals can cell-autonomously encode complex stimulus patterns composed of instantaneous sharp changes and of slowly changing continuous gradients. This encoding relies on a simple negative feedback in the G-protein-coupled receptor (GPCR) signaling pathway in which TAX-6/Calcineurin plays a key role in mediating the feedback inhibition. This negative feedback supports several important coding features that underlie an efficient navigation strategy, including exact adaptation and adaptation to the magnitude of the gradient's first derivative. A simple mathematical model explains the fine neural dynamics of both wild-type and tax-6 mutant animals, further highlighting how the calcium-dependent activity of TAX-6/Calcineurin dictates GPCR inhibition and response dynamics. As GPCRs are ubiquitously expressed in all sensory neurons, this mechanism may be a general solution for efficient cell-autonomous coding of external stimuli.

Dopamine-dependent biphasic behaviour under 'deep diving' conditions in Caenorhabditis elegans.

Underwater divers are susceptible to neurological risks due to their exposure to increased pressure. Absorption of elevated partial pressure of inert gases such as helium and nitrogen may lead to nitrogen narcosis. Although the symptoms of nitrogen narcosis are known, the molecular mechanisms underlying these symptoms have not been elucidated. Here, we examined the behaviour of the soil nematode Caenorhabditis elegans under scuba diving conditions. We analysed wild-type animals and mutants in the dopamine pathway under hyperbaric conditions, using several gas compositions and under varying pressure levels. We found that the animals changed their speed on a flat bacterial surface in response to pressure in a biphasic mode that depended on dopamine. Dopamine-deficient cat-2 mutant animals did not exhibit a biphasic response in high pressure, while the extracellular accumulation of dopamine in dat-1 mutant animals mildly influenced this response. Our data demonstrate that in C. elegans, similarly to mammalian systems, dopamine signalling is involved in the response to high pressure. This study establishes C. elegans as a powerful system to elucidate the molecular mechanisms that underly nitrogen toxicity in response to high pressure.

Cost of unneeded proteins in E. coli is reduced after several generations in exponential growth.

When E. coli cells express unneeded protein, they grow more slowly. Such penalty to fitness associated with making proteins is called protein cost. Protein cost is an important component in the cost-benefit tradeoffs that underlie the evolution of protein circuits, but its origins are still poorly understood. Here, we ask how the protein cost varies during the exponential growth phase of E. coli. We find that cells growing exponentially following an upshift from overnight culture show a large cost when producing unneeded proteins. However, after several generations, while still in exponential growth, the cells enter a phase where cost is much reduced despite vigorous unneeded protein production. We find that this reduced-cost phase depends on the ppGpp system, which adjusts the amount of ribosomes in the cell and does not occur after a downshift from rich to poor medium. These findings suggest that protein cost is a transient phenomenon that happens upon an upshift in conditions and that cost is reduced when ribosomes and other cellular systems have increased to their appropriate steady-state level in the new condition.

Hierarchical sparse coding in the sensory system of Caenorhabditis elegans.

Animals with compact sensory systems face an encoding problem where a small number of sensory neurons are required to encode information about its surrounding complex environment. Using Caenorhabditis elegans worms as a model, we ask how chemical stimuli are encoded by a small and highly connected sensory system. We first generated a comprehensive library of transgenic worms where each animal expresses a genetically encoded calcium indicator in individual sensory neurons. This library includes the vast majority of the sensory system in C. elegans. Imaging from individual sensory neurons while subjecting the worms to various stimuli allowed us to compile a comprehensive functional map of the sensory system at single neuron resolution. The functional map reveals that despite the dense wiring, chemosensory neurons represent the environment using sparse codes. Moreover, although anatomically closely connected, chemo- and mechano-sensory neurons are functionally segregated. In addition, the code is hierarchical, where few neurons participate in encoding multiple cues, whereas other sensory neurons are stimulus specific. This encoding strategy may have evolved to mitigate the constraints of a compact sensory system.

A multi-animal tracker for studying complex behaviors.

BACKGROUND: Animals exhibit astonishingly complex behaviors. Studying the subtle features of these behaviors requires quantitative, high-throughput, and accurate systems that can cope with the often rich perplexing data. RESULTS: Here, we present a Multi-Animal Tracker (MAT) that provides a user-friendly, end-to-end solution for imaging, tracking, and analyzing complex behaviors of multiple animals simultaneously. At the core of the tracker is a machine learning algorithm that provides immense flexibility to image various animals (e.g., worms, flies, zebrafish, etc.) under different experimental setups and conditions. Focusing on C. elegans worms, we demonstrate the vast advantages of using this MAT in studying complex behaviors. Beginning with chemotaxis, we show that approximately 100 animals can be tracked simultaneously, providing rich behavioral data. Interestingly, we reveal that worms' directional changes are biased, rather than random - a strategy that significantly enhances chemotaxis performance. Next, we show that worms can integrate environmental information and that directional changes mediate the enhanced chemotaxis towards richer environments. Finally, offering high-throughput and accurate tracking, we show that the system is highly suitable for longitudinal studies of aging- and proteotoxicity-associated locomotion deficits, enabling large-scale drug and genetic screens. CONCLUSIONS: Together, our tracker provides a powerful and simple system to study complex behaviors in a quantitative, high-throughput, and accurate manner.

The C. elegans Connectome Consists of Homogenous Circuits with Defined Functional Roles.

A major goal of systems neuroscience is to decipher the structure-function relationship in neural networks. Here we study network functionality in light of the common-neighbor-rule (CNR) in which a pair of neurons is more likely to be connected the more common neighbors it shares. Focusing on the fully-mapped neural network of C. elegans worms, we establish that the CNR is an emerging property in this connectome. Moreover, sets of common neighbors form homogenous structures that appear in defined layers of the network. Simulations of signal propagation reveal their potential functional roles: signal amplification and short-term memory at the sensory/inter-neuron layer, and synchronized activity at the motoneuron layer supporting coordinated movement. A coarse-grained view of the neural network based on homogenous connected sets alone reveals a simple modular network architecture that is intuitive to understand. These findings provide a novel framework for analyzing larger, more complex, connectomes once these become available.

The response to high CO2 levels requires the neuropeptide secretion component HID-1 to promote pumping inhibition.

Carbon dioxide (CO2) is a key molecule in many biological processes; however, mechanisms by which organisms sense and respond to high CO2 levels remain largely unknown. Here we report that acute CO2 exposure leads to a rapid cessation in the contraction of the pharynx muscles in Caenorhabditis elegans. To uncover the molecular mechanisms underlying this response, we performed a forward genetic screen and found that hid-1, a key component in neuropeptide signaling, regulates this inhibition in muscle contraction. Surprisingly, we found that this hid-1-mediated pathway is independent of any previously known pathways controlling CO2 avoidance and oxygen sensing. In addition, animals with mutations in unc-31 and egl-21 (neuropeptide secretion and maturation components) show impaired inhibition of muscle contraction following acute exposure to high CO2 levels, in further support of our findings. Interestingly, the observed response in the pharynx muscle requires the BAG neurons, which also mediate CO2 avoidance. This novel hid-1-mediated pathway sheds new light on the physiological effects of high CO2 levels on animals at the organism-wide level.

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.

Diverse two-dimensional input functions control bacterial sugar genes.

Cells respond to signals by regulating gene expression. The relation between the level of input signals and the transcription rate of the gene is called the gene's input function. Because most genes are regulated by more than one signal, the input functions are usually multidimensional. To understand cellular responses, it is essential to know the shapes of these functions. Here, we map the two-dimensional input functions of 19 sugar-utilization genes at high resolution in living E. coli cells. We find diverse, intricately shaped input functions, despite the similarity in the regulatory circuitry of these genes. Surprisingly, some of the input functions are nonmonotonic, peaking at intermediate signal levels. Furthermore, most of the input functions show separation of variables, in the sense that they can be described as the product of simple functions that depend on a single input. This first broad survey of two-dimensional input functions can be extended to map the logic of gene regulation in other systems.

A modular library of small molecule signals regulates social behaviors in Caenorhabditis elegans.

The nematode C. elegans is an important model for the study of social behaviors. Recent investigations have shown that a family of small molecule signals, the ascarosides, controls population density sensing and mating behavior. However, despite extensive studies of C. elegans aggregation behaviors, no intraspecific signals promoting attraction or aggregation of wild-type hermaphrodites have been identified. Using comparative metabolomics, we show that the known ascarosides are accompanied by a series of derivatives featuring a tryptophan-derived indole moiety. Behavioral assays demonstrate that these indole ascarosides serve as potent intraspecific attraction and aggregation signals for hermaphrodites, in contrast to ascarosides lacking the indole group, which are repulsive. Hermaphrodite attraction to indole ascarosides depends on the ASK amphid sensory neurons. Downstream of the ASK sensory neuron, the interneuron AIA is required for mediating attraction to indole ascarosides instead of the RMG interneurons, which previous studies have shown to integrate attraction and aggregation signals from ASK and other sensory neurons. The role of the RMG interneuron in mediating aggregation and attraction is thought to depend on the neuropeptide Y-like receptor NPR-1, because solitary and social C. elegans strains are distinguished by different npr-1 variants. We show that indole ascarosides promote attraction and aggregation in both solitary and social C. elegans strains. The identification of indole ascarosides as aggregation signals reveals unexpected complexity of social signaling in C. elegans, which appears to be based on a modular library of ascarosides integrating building blocks derived from lipid ß-oxidation and amino-acid metabolism. Variation of modules results in strongly altered signaling content, as addition of a tryptophan-derived indole unit to repellent ascarosides produces strongly attractive indole ascarosides. Our findings show that the library of ascarosides represents a highly developed chemical language integrating different neurophysiological pathways to mediate social communication in C. elegans.

Measuring the effects of high CO2 levels in Caenorhabditis elegans.

Carbon dioxide (CO2) is an important molecule in cell metabolism. It is also a byproduct of many physiological processes. In humans, impaired lung function and lung diseases disrupt the body's ability to dispose of CO2 and elevate its levels in the body (hypercapnia). Animal models allow further understanding of how CO2 is sensed in the body and what are the physiological responses to high CO2 levels. This information can provide new strategies in the battle against the detrimental effects of CO2 accumulation in lung diseases. The nematode Caenorhabditis elegans provides us with such a model animal due to its natural ability to sense and navigate through varying concentrations of CO2, as well as the fact that it can be genetically manipulated with ease. Here we describe the different methods used to measure the effects elevated levels of CO2 have on the molecular sensing mechanism and physiology of C. elegans.

A genome-wide analysis of promoter-mediated phenotypic noise in Escherichia coli.

Gene expression is subject to random perturbations that lead to fluctuations in the rate of protein production. As a consequence, for any given protein, genetically identical organisms living in a constant environment will contain different amounts of that particular protein, resulting in different phenotypes. This phenomenon is known as "phenotypic noise." In bacterial systems, previous studies have shown that, for specific genes, both transcriptional and translational processes affect phenotypic noise. Here, we focus on how the promoter regions of genes affect noise and ask whether levels of promoter-mediated noise are correlated with genes' functional attributes, using data for over 60% of all promoters in Escherichia coli. We find that essential genes and genes with a high degree of evolutionary conservation have promoters that confer low levels of noise. We also find that the level of noise cannot be attributed to the evolutionary time that different genes have spent in the genome of E. coli. In contrast to previous results in eukaryotes, we find no association between promoter-mediated noise and gene expression plasticity. These results are consistent with the hypothesis that, in bacteria, natural selection can act to reduce gene expression noise and that some of this noise is controlled through the sequence of the promoter region alone.

Just-in-time transcription program in metabolic pathways.

A primary goal of systems biology is to understand the design principles of the transcription networks that govern the timing of gene expression. Here we measured promoter activity for approximately 100 genes in parallel from living cells at a resolution of minutes and accuracy of 10%, based on GFP and Lux reporter libraries. Focusing on the amino-acid biosynthesis systems of Escherichia coli, we identified a previously unknown temporal expression program and expression hierarchy that matches the enzyme order in unbranched pathways. We identified two design principles: the closer the enzyme is to the beginning of the pathway, the shorter the response time of the activation of its promoter and the higher its maximal promoter activity. Mathematical analysis suggests that this 'just-in-time' (ref. 5) transcription program is optimal under constraints of rapidly reaching a production goal with minimal total enzyme production. Our findings suggest that metabolic regulation networks are designed to generate precision promoter timing and activity programs that can be understood using the engineering principles of production pipelines.

Inheritance of associative memories and acquired cellular changes in C. elegans.

Experiences have been shown to modulate behavior and physiology of future generations in some contexts, but there is limited evidence for inheritance of associative memory in different species. Here, we trained C. elegans nematodes to associate an attractive odorant with stressful starvation conditions and revealed that this associative memory was transmitted to the F1 progeny who showed odor-evoked avoidance behavior. Moreover, the F1 and the F2 descendants of trained animals exhibited odor-evoked cellular stress responses, manifested by the translocation of DAF-16/FOXO to cells' nuclei. Sperm, but not oocytes, transmitted these odor-evoked cellular stress responses which involved H3K9 and H3K36 methylations, the small RNA pathway machinery, and intact neuropeptide secretion. Activation of a single chemosensory neuron sufficed to induce a serotonin-mediated systemic stress response in both the parental trained generation and in its progeny. Moreover, inheritance of the cellular stress responses increased survival chances of the progeny as exposure to the training odorant allowed the animals to prepare in advance for an impending adversity. These findings suggest that in C. elegans associative memories and cellular changes may be transferred across generations.

Principles for coding associative memories in a compact neural network.

A major goal in neuroscience is to elucidate the principles by which memories are stored in a neural network. Here, we have systematically studied how four types of associative memories (short- and long-term memories, each as positive and negative associations) are encoded within the compact neural network of Caenorhabditis elegans worms. Interestingly, sensory neurons were primarily involved in coding short-term, but not long-term, memories, and individual sensory neurons could be assigned to coding either the conditioned stimulus or the experience valence (or both). Moreover, when considering the collective activity of the sensory neurons, the specific training experiences could be decoded. Interneurons integrated the modulated sensory inputs and a simple linear combination model identified the experience-specific modulated communication routes. The widely distributed memory suggests that integrated network plasticity, rather than changes to individual neurons, underlies the fine behavioral plasticity. This comprehensive study reveals basic memory-coding principles and highlights the central roles of sensory neurons in memory formation.

A Fusion PCR Method for Expressing Genetic Tools in C. elegans.

C. elegans offer a unique opportunity for understanding computation in neural networks. This is largely due to their relatively compact neural network for which a wiring diagram is available. Recent advances in genetic tools for interrogating neural activity (e.g., optogenetics) make C. elegans particularly compelling as they can be expressed in many different combinations in target individual neurons. Thus, the prospect to decipher principles underlying functionality in neural networks largely depends on the ease by which transgenic animals can be generated. Traditionally, to generate transgenic animals one would inject a plasmid containing the gene of interest under the regulation of the cell- or lineage-specific promoter. This often requires laborious cloning steps of both the gene and the promoter. The Hobert lab has developed a simpler protocol in which linear PCR fragments can be injected to generate transgenic animals. Relying on this PCR fusion-based method, here we provide a detailed protocol that we have optimized for expressing various genetically encoded calcium indicators and optogenetic tools in individual or sets of neurons. We use these simple procedures to generate multiple constructs within a very short time frame (typically 1-2 days).

Invariant distribution of promoter activities in Escherichia coli.

Cells need to allocate their limited resources to express a wide range of genes. To understand how Escherichia coli partitions its transcriptional resources between its different promoters, we employ a robotic assay using a comprehensive reporter strain library for E. coli to measure promoter activity on a genomic scale at high-temporal resolution and accuracy. This allows continuous tracking of promoter activity as cells change their growth rate from exponential to stationary phase in different media. We find a heavy-tailed distribution of promoter activities, with promoter activities spanning several orders of magnitude. While the shape of the distribution is almost completely independent of the growth conditions, the identity of the promoters expressed at different levels does depend on them. Translation machinery genes, however, keep the same relative expression levels in the distribution across conditions, and their fractional promoter activity tracks growth rate tightly. We present a simple optimization model for resource allocation which suggests that the observed invariant distributions might maximize growth rate. These invariant features of the distribution of promoter activities may suggest design constraints that shape the allocation of transcriptional resources.

Author Correction: Concerted pulsatile and graded neural dynamics enables efficient chemotaxis in C. elegans.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.