Coherent Feedforward Research Articles

Engineered gene networks enable non‐genetic drug resistance and enhanced cellular robustness

Drug resistance complicates the treatment of cancer and infectious diseases, and often arises from the elevated expression of a gene that neutralises or reduces drug activity. To investigate this and other expression-based mechanisms of drug resistance, the authors engineered a set of gene regulatory networks in the eukaryotic model organism Saccharomyces cerevisiae to control a homologue of the cancer-related human multidrug resistance gene MDR1. Using this system, they explored experimentally how different gene regulatory network features, also called genetic network motifs, contribute to gene expression dynamics and cellular fitness. They observed that coherent feedforward and positive feedback motifs enable rapid and self-sustained activation of gene expression, and enhance cell survival in the presence of a cytotoxic drug. These observations underscore that genetic network motifs can be critical for drug resistance and that genetic network engineering can be used to enhance cellular tolerance to cytotoxins or other environmental stresses.

Recent Advances in the Transcriptional Regulation of Secondary Cell Wall Biosynthesis in the Woody Plants

Plant cell walls provide structural support for growth and serve as a barrier for pathogen attack. Plant cell walls are also a source of renewable biomass for conversion to biofuels and bioproducts. Understanding plant cell wall biosynthesis and its regulation is of critical importance for the genetic modification of plant feedstocks for cost-effective biofuels and bioproducts conversion and production. Great progress has been made in identifying enzymes involved in plant cell wall biosynthesis, and in Arabidopsis it is generally recognized that the regulation of genes encoding these enzymes is under a transcriptional regulatory network with coherent feedforward and feedback loops. However, less is known about the transcriptional regulation of plant secondary cell wall (SCW) biosynthesis in woody species despite of its high relevance to biofuels and bioproducts conversion and production. In this article, we synthesize recent progress on the transcriptional regulation of SCW biosynthesis in Arabidopsis and contrast to what is known in woody species. Furthermore, we evaluate progress in related emerging regulatory machineries targeting transcription factors in this complex regulatory network of SCW biosynthesis.

Coherent Feedforward Regulation of Gene Expression by Caulobacter σT and GsrN during Hyperosmotic Stress.

GsrN is a conserved small RNA that is under transcriptional control of the general stress sigma factor, σT, and that functions as a posttranscriptional regulator of Caulobacter crescentus survival under multiple stress conditions. We have defined features of GsrN structure that determine survival under hyperosmotic stress, and we have applied transcriptomic and proteomic methods to identify regulatory targets of GsrN under hyperosmotic conditions. The 5' end of GsrN, which includes a conserved cytosine-rich stem-loop structure, is necessary for cell survival after osmotic upshock. GsrN both activates and represses gene expression in this stress condition. Expression of an uncharacterized open reading frame predicted to encode a glycine zipper protein, osrP, is strongly activated by GsrN. Our data support a model in which GsrN physically interacts with osrP mRNA through its 5' C-rich stem-loop to enhance OsrP protein expression. We conclude that sigT, gsrN, and osrP form a coherent feedforward loop in which σT activates gsrN and osrP transcription during stress and GsrN activates OsrP protein expression at the posttranscriptional level. This study delineates transcriptional and posttranscriptional layers of Caulobacter gene expression control during hyperosmotic stress, uncovers a new regulatory target of GsrN, and defines a coherent feedforward motif in the Caulobacter general stress response (GSR) regulatory network.IMPORTANCE Bacteria inhabit diverse niches and must adapt their physiology to constant environmental fluctuations. A major response to environmental perturbation is to change gene expression. Caulobacter and other alphaproteobacteria initiate a complex gene expression program known as the general stress response (GSR) under conditions including oxidative stress, osmotic stress, and nutrient limitation. The GSR enables cell survival in these environments. Understanding how bacteria survive stress requires that we dissect gene expression responses, such as the GSR, at the molecular level. This study is significant, as it defines transcriptional and posttranscriptional layers of gene expression regulation in response to hyperosmotic stress. We further provide evidence that a coherent feedforward motif influences the system properties of the Caulobacter GSR pathway.

One-way quantum computing in superconducting circuits

We propose a method for the implementation of one-way quantum computing in superconducting circuits. Measurement-based quantum computing is a universal quantum computation paradigm in which an initial cluster-state provides the quantum resource, while the iteration of sequential measurements and local rotations encodes the quantum algorithm. Up to now, technical constraints have limited a scalable approach to this quantum computing alternative. The initial cluster state can be generated with available controlled-phase gates, while the quantum algorithm makes use of high-fidelity readout and coherent feedforward. With current technology, we estimate that quantum algorithms with above 20 qubits may be implemented in the path towards quantum supremacy. Moreover, we propose an alternative initial state with properties of maximal persistence and maximal connectedness, reducing the required resources of one-way quantum computing protocols.

Assessing regulatory information in developmental gene regulatory networks

Gene regulatory networks (GRNs) provide a transformation function between the static genomic sequence and the primary spatial specification processes operating development. The regulatory information encompassed in developmental GRNs thus goes far beyond the control of individual genes. We here address regulatory information at different levels of network organization, from single node to subcircuit to large-scale GRNs and discuss how regulatory design features such as network architecture, hierarchical organization, and cis-regulatory logic contribute to the developmental function of network circuits. Using specific subcircuits from the sea urchin endomesoderm GRN, for which both circuit design and biological function have been described, we evaluate by Boolean modeling and in silico perturbations the import of given circuit features on developmental function. The examples include subcircuits encoding positive feedback, mutual repression, and coherent feedforward, as well as signaling interaction circuitry. Within the hierarchy of the endomesoderm GRN, these subcircuits are organized in an intertwined and overlapping manner. Thus, we begin to see how regulatory information encoded at individual nodes is integrated at all levels of network organization to control developmental process.

Analysis of Network Topologies Underlying Ethylene Growth Response Kinetics.

Most models for ethylene signaling involve a linear pathway. However, measurements of seedling growth kinetics when ethylene is applied and removed have resulted in more complex network models that include coherent feedforward, negative feedback, and positive feedback motifs. The dynamical responses of the proposed networks have not been explored in a quantitative manner. Here, we explore (i) whether any of the proposed models are capable of producing growth-response behaviors consistent with experimental observations and (ii) what mechanistic roles various parts of the network topologies play in ethylene signaling. To address this, we used computational methods to explore two general network topologies: The first contains a coherent feedforward loop that inhibits growth and a negative feedback from growth onto itself (CFF/NFB). In the second, ethylene promotes the cleavage of EIN2, with the product of the cleavage inhibiting growth and promoting the production of EIN2 through a positive feedback loop (PFB). Since few network parameters for ethylene signaling are known in detail, we used an evolutionary algorithm to explore sets of parameters that produce behaviors similar to experimental growth response kinetics of both wildtype and mutant seedlings. We generated a library of parameter sets by independently running the evolutionary algorithm many times. Both network topologies produce behavior consistent with experimental observations, and analysis of the parameter sets allows us to identify important network interactions and parameter constraints. We additionally screened these parameter sets for growth recovery in the presence of sub-saturating ethylene doses, which is an experimentally-observed property that emerges in some of the evolved parameter sets. Finally, we probed simplified networks maintaining key features of the CFF/NFB and PFB topologies. From this, we verified observations drawn from the larger networks about mechanisms underlying ethylene signaling. Analysis of each network topology results in predictions about changes that occur in network components that can be experimentally tested to give insights into which, if either, network underlies ethylene responses.

Defining Network Topologies that Can Achieve Biochemical Adaptation

Many signaling systems show adaptation-the ability to reset themselves after responding to a stimulus. We computationally searched all possible three-node enzyme network topologies to identify those that could perform adaptation. Only two major core topologies emerge as robust solutions: a negative feedback loop with a buffering node and an incoherent feedforward loop with a proportioner node. Minimal circuits containing these topologies are, within proper regions of parameter space, sufficient to achieve adaptation. More complex circuits that robustly perform adaptation all contain at least one of these topologies at their core. This analysis yields a design table highlighting a finite set of adaptive circuits. Despite the diversity of possible biochemical networks, it may be common to find that only a finite set of core topologies can execute a particular function. These design rules provide a framework for functionally classifying complex natural networks and a manual for engineering networks. For a video summary of this article, see the PaperFlick file with the Supplemental Data available online.

The Coherent Feedforward Loop Serves as a Sign-sensitive Delay Element in Transcription Networks

Recent analysis of the structure of transcription regulation networks revealed several “network motifs”: regulatory circuit patterns that occur much more frequently than in randomized networks. It is important to understand whether these network motifs have specific functions. One of the most significant network motifs is the coherent feedforward loop, in which transcription factor X regulates transcription factor Y, and both jointly regulate gene Z. On the basis of mathematical modeling and simulations, it was suggested that the coherent feedforward loop could serve as a sign-sensitive delay element: a circuit that responds rapidly to step-like stimuli in one direction (e.g. ON to OFF), and at a delay to steps in the opposite direction (OFF to ON). Is this function actually carried out by feedforward loops in living cells? Here, we address this experimentally, using a system with feedforward loop connectivity, the l-arabinose utilization system of Escherichiacoli. We measured responses to step-like cAMP stimuli at high temporal resolution and accuracy by means of green fluorescent protein reporters. We show that the arabinose system displays sign-sensitive delay kinetics. This type of kinetics is important for making decisions based on noisy inputs by filtering out fluctuations in input stimuli, yet allowing rapid response. This information-processing function may be performed by the feedforward loop regulation modules that are found in diverse systems from bacteria to humans.