Engineering Signal Transduction Pathways

Fundamentals and Exceptions of the LysR-type Transcriptional Regulators

LysR-type transcriptional regulators (LTTRs) are emerging as a promising group of macromolecules for the field of biosensors. As the largest family of bacterial transcription factors, the LTTRs represent a vast and mostly untapped repertoire of sensor proteins. To fully harness these regulators for transcription factor-based biosensor development, it is crucial to understand their underlying mechanisms and functionalities. In the first part, this Review discusses the established model and features of LTTRs. As dual-function regulators, these inducible transcription factors exude precise control over their regulatory targets. In the second part of this Review, an overview is given of the exceptions to the "classic" LTTR model. While a general regulatory mechanism has helped elucidate the intricate regulation performed by LTTRs, it is essential to recognize the variations within the family. By combining this knowledge, characterization of new regulators can be done more efficiently and accurately, accelerating the expansion of transcriptional sensors for biosensor development. Unlocking the pool of LTTRs would significantly expand the currently limited range of detectable molecules and regulatory functions available for the implementation of novel synthetic genetic circuitry.

Developmental assembly of multi-component polymer systems through interconnected synthetic gene networks in vitro

Living cells regulate the dynamics of developmental events through interconnected signaling systems that activate and deactivate inert precursors. This suggests that similarly, synthetic biomaterials could be designed to develop over time by using chemical reaction networks to regulate the availability of assembling components. Here we demonstrate how the sequential activation or deactivation of distinct DNA building blocks can be modularly coordinated to form distinct populations of self-assembling polymers using a transcriptional signaling cascade of synthetic genes. Our building blocks are DNA tiles that polymerize into nanotubes, and whose assembly can be controlled by RNA molecules produced by synthetic genes that target the tile interaction domains. To achieve different RNA production rates, we use a strategy based on promoter "nicking" and strand displacement. By changing the way the genes are cascaded and the RNA levels, we demonstrate that we can obtain spatially and temporally different outcomes in nanotube assembly, including random DNA polymers, block polymers, and as well as distinct autonomous formation and dissolution of distinct polymer populations. Our work demonstrates a way to construct autonomous supramolecular materials whose properties depend on the timing of molecular instructions for self-assembly, and can be immediately extended to a variety of other nucleic acid circuits and assemblies.

Sequence-Based Protein Design: A Review of Using Statistical Models to Characterize Coevolutionary Traits for Developing Hybrid Proteins as Genetic Sensors

Statistical analyses of homologous protein sequences can identify amino acid residue positions that co-evolve to generate family members with different properties. Based on the hypothesis that the coevolution of residue positions is necessary for maintaining protein structure, coevolutionary traits revealed by statistical models provide insight into residue-residue interactions that are important for understanding protein mechanisms at the molecular level. With the rapid expansion of genome sequencing databases that facilitate statistical analyses, this sequence-based approach has been used to study a broad range of protein families. An emerging application of this approach is to design hybrid transcriptional regulators as modular genetic sensors for novel wiring between input signals and genetic elements to control outputs. Among many allosterically regulated regulator families, the members contain structurally conserved and functionally independent protein domains, including a DNA-binding module (DBM) for interacting with a specific genetic element and a ligand-binding module (LBM) for sensing an input signal. By hybridizing a DBM and an LBM from two different family members, a hybrid regulator can be created with a new combination of signal-detection and DNA-recognition properties not present in natural systems. In this review, we present recent advances in the development of hybrid regulators and their applications in cellular engineering, especially focusing on the use of statistical analyses for characterizing DBM-LBM interactions and hybrid regulator design. Based on these studies, we then discuss the current limitations and potential directions for enhancing the impact of this sequence-based design approach.

Structural basis for specific DNA sequence recognition by the transcription factor NFIL3

The CCAAT/enhancer-binding proteins (C/EBPs) constitute a family of pivotal transcription factors involved in tissue development, cellular function, proliferation, and differentiation. NFIL3, as one of them, plays an important role in regulating immune cell differentiation, circadian clock system, and neural regeneration, yet its specific DNA recognition mechanism remains enigmatic. In this study, we showed by the ITC binding experiments that NFIL3 prefers to bind to the TTACGTAA DNA motif. Our structural studies revealed that the α-helical NFIL3 bZIP domain dimerizes through its leucine zipper region, and binds to DNA via its basic region. The two basic regions of the NFIL3 bZIP dimer were pushed apart upon binding to DNA, facilitating the snug accommodation of the two basic regions within the major grooves of the DNA. Remarkably, our binding and structural data also revealed that both NFIL3 and C/EBPα/β demonstrate a shared preference for the TTACGTAA sequence. Furthermore, our study revealed that disease-associated mutations within the NFIL3 bZIP domain result in either reduction or complete disruption of its DNA binding ability. These discoveries not only provide valuable insights into the DNA binding mechanisms of NFIL3 but also elucidate the causal role of NFIL3 mutations in disease pathogenesis.

Artificial Protein Crosstalk with a Molecule that Exchanges Binding Partners

Drawing inspiration from allosteric signaling enzymes, whose catalytic and regulatory units are non-covalently linked, we have devised a method to establish unnatural, effector-mediated enzyme activation within native cells. The feasibility of this approach is demonstrated by introducing a synthetic regulatory unit (sRU) onto glycogen synthase kinase 3 (GSK-3) through non-covalent means. Our study reveals that this synthetic regulator mediates an unnatural crosstalk between GSK-3 and lactate dehydrogenase A (LDHA), whose expression is regulated by cellular oxygen levels. Specifically, with this approach, the constitutively active GSK-3 is transformed into an activable enzyme, whereas LDHA is repurposed as an unnatural effector protein that controls the activity of the kinase, making it unnaturally dependent on the cell's hypoxic response. These findings demonstrate a step toward imitating the function of effector-regulated cell-signaling enzymes, which play a key biological role in mediating the response of cells to changes in their environment. In addition, at the proof-of-principle level, our results indicate the potential to develop a new class of protein inhibitors whose inhibitory effect in cells is dictated by the cell's environment and consequent protein expression profile.

Advances in ligand-specific biosensing for structurally similar molecules

The specificity of biological systems makes it possible to develop biosensors targeting specific metabolites, toxins, and pollutants in complex medical or environmental samples without interference from structurally similar compounds. For the last two decades, great efforts have been devoted to creating proteins or nucleic acids with novel properties through synthetic biology strategies. Beyond augmenting biocatalytic activity, expanding target substrate scopes, and enhancing enzymes' enantioselectivity and stability, an increasing research area is the enhancement of molecular specificity for genetically encoded biosensors. Here, we summarize recent advances in the development of highly specific biosensor systems and their essential applications. First, we describe the rational design principles required to create libraries containing potential mutants with less promiscuity or better specificity. Next, we review the emerging high-throughput screening techniques to engineer biosensing specificity for the desired target. Finally, we examine the computer-aided evaluation and prediction methods to facilitate the construction of ligand-specific biosensors.

Enabling technology and core theory of synthetic biology

Synthetic biology provides a new paradigm for life science research ("build to learn") and opens the future journey of biotechnology ("build to use"). Here, we discuss advances of various principles and technologies in the mainstream of the enabling technology of synthetic biology, including synthesis and assembly of a genome, DNA storage, gene editing, molecular evolution and de novo design of function proteins, cell and gene circuit engineering, cell-free synthetic biology, artificial intelligence (AI)-aided synthetic biology, as well as biofoundries. We also introduce the concept of quantitative synthetic biology, which is guiding synthetic biology towards increased accuracy and predictability or the real rational design. We conclude that synthetic biology will establish its disciplinary system with the iterative development of enabling technologies and the maturity of the core theory.

Therapeutic cell engineering: designing programmable synthetic genetic circuits in mammalian cells

Cell therapy approaches that employ engineered mammalian cells for on-demand production of therapeutic agents in the patient's body are moving beyond proof-of-concept in translational medicine. The therapeutic cells can be customized to sense user-defined signals, process them, and respond in a programmable and predictable way. In this paper, we introduce the available tools and strategies employed to design therapeutic cells. Then, various approaches to control cell behaviors, including open-loop and closed-loop systems, are discussed. We also highlight therapeutic applications of engineered cells for early diagnosis and treatment of various diseases in the clinic and in experimental disease models. Finally, we consider emerging technologies such as digital devices and their potential for incorporation into future cell-based therapies.

Robust adaptation of PKCζ-IRS1 insulin signaling pathways through integral feedback control

Insulin signaling pathways in muscle tissue play a major role in maintaining glucose homeostasis. Dysregulation in these pathways results in the onset of serious metabolic disorders like type 2 diabetes. Robustness is an essential characteristic of insulin signaling pathways that ensures reliable signal transduction in the presence of perturbations as a result of several feedback mechanisms. Integral control, according to control engineering, provides reliable setpoint tracking and disturbance rejection. The presence of negative feedback and integrating process is crucial for biological processes to achieve integral control. The existence of an integral controller leads to the rejection of perturbations which resulted in the robust regulation of biochemical entities within acceptable levels. In the presentin silicoresearch work, the presence of integral control in the protein kinase Cζ- insulin receptor substrate-1 (PKCζ-IRS1) pathway is identified, verified mathematically and model is simulated in Cell Designer. The data is exported to Minitab software and robustness analysis is carried out statistically using the Mann-Whitney test. The p-value of the results obtained with given parameters perturbed by ±1% is greater than the significance level of 0.05 (0.2132 for 1% error in k7(rate constant of IRS1 phosphorylation), 0.2096 for -1% error in k7, 0.9037 for both ±1% error in insulin and 0.9037 for ±1% error in k1(association rate constant of the first molecule of insulin to bind the insulin receptor), indicated that our hypothesis is proved The results satisfactorily indicate that even when perturbations are present, glucose homeostasis in muscle tissue is robust due to the presence of integral regulation in the PKCζ-IRS1 insulin signaling pathways. In this paper, we have analysed the findings from the framework of robust control theory, which has allowed us to examine that how PKCζ-IRS1 insulin signaling pathways produces desired output in presence of perturbations.

"Dialogue" between Caco-2 and DCs regulated by Ganoderma atrum polysaccharide in intestinal-like Caco-2/DCs co-culture model

The previous research has indicated that Ganoderma atrum polysaccharide (PSG-1) indirectly affects the immune function of dendritic cells (DCs) in intestinal-like Caco-2/DCs co-culture model, in which NF-κB and MAPK pathway play an essential role. To explore the interaction of Caco-2 in the interaction between the intestinal epithelium and its internal immune cells, the intestinal-like Caco-2/DCs co-culture model was developed. All transcripts of Caco-2 treated with or without PSG-1 were globally screened by RNA-seq. The expression of 452 genes regulated by PSG-1 was statistically significant, the counts of up-regulated and down-regulated genes were 198 and 256, respectively. According to KEGG analysis, tumor necrosis factor (TNF)-α and NF-κB signaling pathways of Caco-2 were selected to elucidate the mechanism of interaction between Caco-2/DCs induced by PSG-1. After the addition of TNF-α inhibitor Apremilast and NF-κB inhibitor BAY11-70821 in Caco-2, expression of cytokines (TNF-α, IL-6, IL-1β, IL-10), chemokines (RANTES, MIP-1α, MCP-1), and the key proteins of MAPK and NF-κB pathways of DCs were all reduced. In summary, "dialogue" between Caco-2 and DCs was regulated by PSG-1 through TNF-α and NF-κB signaling pathways of Caco-2 in the model.

Engineering of Biological Pathways: Complex Formation and Signal Transduction

The rational in silico design of interface mutations within protein complexes is a synthetic biology tool that enables-when introduced into biological systems-the artificial rewiring of biological pathways. Here we describe the three-dimensional structure-based design of "rewiring" mutations using the FoldX force field. Specifically, we provide the protocol for the design and selection of interface mutations in three Ras-effector complex structures (PDB entries 3KUD, 4K81, and 6AMB). Ras mutations that impair binding to some but not all interacting partners are selected.

Intelligent microbial cell factory with genetic pH shooting (GPS) for cell self-responsive base/acid regulation

BACKGROUND

In industrial fermentation, pH fluctuation resulted from microbial metabolism influences the strain performance and the final production. The common way to control pH is adding acid or alkali after probe detection, which is not a fine-tuned method and often leads to increased costs and complex downstream processing. Here, we constructed an intelligent pH-sensing and controlling genetic circuits called "Genetic pH Shooting (GPS)" to realize microbial self-regulation of pH.

RESULTS

In order to achieve the self-regulation of pH, GPS circuits consisting of pH-sensing promoters and acid-/alkali-producing genes were designed and constructed. Designed pH-sensing promoters in the GPS can respond to high or low pHs and generate acidic or alkaline substances, achieving endogenously self-responsive pH adjustments. Base shooting circuit (BSC) and acid shooting circuit (ASC) were constructed and enabled better cell growth under alkaline or acidic conditions, respectively. Furthermore, the genetic circuits including GPS, BSC and ASC were applied to lycopene production with a higher yield without an artificial pH regulation compared with the control under pH values ranging from 5.0 to 9.0. In scale-up fermentations, the lycopene titer in the engineered strain harboring GPS was increased by 137.3% and ammonia usage decreased by 35.6%.

CONCLUSIONS

The pH self-regulation achieved through the GPS circuits is helpful to construct intelligent microbial cell factories and reduce the production costs, which would be much useful in industrial applications.

Synthetic protein switches: Combinatorial linker engineering with iFLinkC

Linker engineering constitutes a critical, yet frequently underestimated aspect in the construction of synthetic protein switches and sensors. Notably, systematic strategies to engineer linkers by predictive means remain largely elusive to date. This is primarily due to our insufficient understanding how the biophysical properties that underlie linker functions mediate the conformational transitions in artificially engineered protein switches and sensors. The construction of synthetic protein switches and sensors therefore heavily relies on experimental trial-and-error. Yet, methods for effectively generating linker diversity at the genetic level are scarce. Addressing this technical shortcoming, iterative functional linker cloning (iFLinkC) enables the combinatorial assembly of linker elements with functional domains from sequence verified repositories that are developed and stored in-house. The assembly process is highly scalable and given its recursive nature generates linker diversity in a combinatorial and exponential fashion based on a limited number of linker elements.

Dynamic Transcriptomic and Phosphoproteomic Analysis During Cell Wall Stress in Aspergillus nidulans

The fungal cell-wall integrity signaling (CWIS) pathway regulates cellular response to environmental stress to enable wall repair and resumption of normal growth. This complex, interconnected, pathway has been only partially characterized in filamentous fungi. To better understand the dynamic cellular response to wall perturbation, a β-glucan synthase inhibitor (micafungin) was added to a growing A. nidulans shake-flask culture. From this flask, transcriptomic and phosphoproteomic data were acquired over 10 and 120 min, respectively. To differentiate statistically-significant dynamic behavior from noise, a multivariate adaptive regression splines (MARS) model was applied to both data sets. Over 1800 genes were dynamically expressed and over 700 phosphorylation sites had changing phosphorylation levels upon micafungin exposure. Twelve kinases had altered phosphorylation and phenotypic profiling of all non-essential kinase deletion mutants revealed putative connections between PrkA, Hk-8-4, and Stk19 and the CWIS pathway. Our collective data implicate actin regulation, endocytosis, and septum formation as critical cellular processes responding to activation of the CWIS pathway, and connections between CWIS and calcium, HOG, and SIN signaling pathways.

Phosphoregulated orthogonal signal transduction in mammalian cells

Orthogonal tools for controlling protein function by post-translational modifications open up new possibilities for protein circuit engineering in synthetic biology. Phosphoregulation is a key mechanism of signal processing in all kingdoms of life, but tools to control the involved processes are very limited. Here, we repurpose components of bacterial two-component systems (TCSs) for chemically induced phosphotransfer in mammalian cells. TCSs are the most abundant multi-component signal-processing units in bacteria, but are not found in the animal kingdom. The presented phosphoregulated orthogonal signal transduction (POST) system uses induced nanobody dimerization to regulate the trans-autophosphorylation activity of engineered histidine kinases. Engineered response regulators use the phosphohistidine residue as a substrate to autophosphorylate an aspartate residue, inducing their own homodimerization. We verify this approach by demonstrating control of gene expression with engineered, dimerization-dependent transcription factors and propose a phosphoregulated relay system of protein dimerization as a basic building block for next-generation protein circuits.

Phosphoregulation is a key mechanism of signal processing. Here the authors build a phosphoregulated relay system in mammalian cells for orthogonal signal transduction.

Exploring the genetic potential of a fosmid metagenomic library from an oil-impacted mangrove sediment for metabolism of aromatic compounds

Aromatic hydrocarbons (AH) are widely distributed in nature, and many of them have been reported as relevant environmental pollutants and valuable carbon sources for different microorganisms. In this work, high-throughput sequencing of a metagenomic fosmid library was carried out to evaluate the functional and taxonomic diversity of genes involved in aromatic compounds degradation in oil-impacted mangrove sediments. In addition, activity-based approach and gas chromatography were used to assess the degradation potential of fosmid clones. Results indicated that AH degradation genes, such as monooxygenases and dioxygenases, were grouped into the following categories: anaerobic degradation of aromatic compounds (20.34%), metabolism of central aromatic intermediates (35.40%) and peripheral pathways for catabolism of aromatic compounds (22.56%). Taxonomic affiliation of genes related to aromatic compounds metabolism revealed the prevalence of the classes Alphaproteobacteria, Actinobacteria, Betaproteobacteria, Gammaproteobacteria and Deltaproteobacteria. Aromatic hydrocarbons (phenol, naphthalene, phenanthrene, pyrene and benzopyrene) were used as the only carbon source to screen clones with degradation potential. Of the 2500 clones tested, 48 showed some respiratory activity in at least one of the five carbon sources used. The hydrocarbon degradation ability of the top ten fosmid clones was confirmed by GC-MS. Further, annotation of assembled metagenomic fragments revealed ORFs corresponding to proteins and functional domains directly or indirectly involved in the aromatic compound metabolism, such as catechol 2,3-dioxygenase and ferredoxin oxidoreductase. Finally, these data suggest that the indigenous mangrove sediment microbiota developed essential mechanisms towards ecosystem remediation of petroleum hydrocarbon impact.

Metabolic perceptrons for neural computing in biological systems

Synthetic biological circuits are promising tools for developing sophisticated systems for medical, industrial, and environmental applications. So far, circuit implementations commonly rely on gene expression regulation for information processing using digital logic. Here, we present a different approach for biological computation through metabolic circuits designed by computer-aided tools, implemented in both whole-cell and cell-free systems. We first combine metabolic transducers to build an analog adder, a device that sums up the concentrations of multiple input metabolites. Next, we build a weighted adder where the contributions of the different metabolites to the sum can be adjusted. Using a computational model fitted on experimental data, we finally implement two four-input perceptrons for desired binary classification of metabolite combinations by applying model-predicted weights to the metabolic perceptron. The perceptron-mediated neural computing introduced here lays the groundwork for more advanced metabolic circuits for rapid and scalable multiplex sensing.

Building a synthetic mechanosensitive signaling pathway in compartmentalized artificial cells

To date, reconstitution of one of the fundamental methods of cell communication, the signaling pathway, has been unaddressed in the bottom-up construction of artificial cells (ACs). Such developments are needed to increase the functionality and biomimicry of ACs, accelerating their translation and application in biotechnology. Here, we report the construction of a de novo synthetic signaling pathway in microscale nested vesicles. Vesicle-cell models respond to external calcium signals through activation of an intracellular interaction between phospholipase A2 and a mechanosensitive channel present in the internal membranes, triggering content mixing between compartments and controlling cell fluorescence. Emulsion-based approaches to AC construction are therefore shown to be ideal for the quick design and testing of new signaling networks and can readily include synthetic molecules difficult to introduce to biological cells. This work represents a foundation for the engineering of multicompartment-spanning designer pathways that can be utilized to control downstream events inside an AC, leading to the assembly of micromachines capable of sensing and responding to changes in their local environment.

Conceptual Evolution of Cell Signaling

During the last 100 years, cell signaling has evolved into a common mechanism for most physiological processes across systems. Although the majority of cell signaling principles were initially derived from hormonal studies, its exponential growth has been supported by interdisciplinary inputs, e.g., from physics, chemistry, mathematics, statistics, and computational fields. As a result, cell signaling has grown out of scope for any general review. Here, we review how the messages are transferred from the first messenger (the ligand) to the receptor, and then decoded with the help of cascades of second messengers (kinases, phosphatases, GTPases, ions, and small molecules such as cAMP, cGMP, diacylglycerol, etc.). The message is thus relayed from the membrane to the nucleus where gene expression ns, subsequent translations, and protein targeting to the cell membrane and other organelles are triggered. Although there are limited numbers of intracellular messengers, the specificity of the response profiles to the ligands is generated by the involvement of a combination of selected intracellular signaling intermediates. Other crucial parameters in cell signaling are its directionality and distribution of signaling strengths in different pathways that may crosstalk to adjust the amplitude and quality of the final effector output. Finally, we have reflected upon its possible developments during the coming years.

Cell Factory Engineering

Rational approaches to modifying cells to make molecules of interest are of substantial economic and scientific interest. Most of these efforts aim at the production of native metabolites, expression of heterologous biosynthetic pathways, or protein expression. Reviews of these topics have largely focused on individual strategies or cell types, but collectively they fall under the broad umbrella of a growing field known as cell factory engineering. Here we condense >130 reviews and key studies in the art into a meta-review of cell factory engineering. We identified 33 generic strategies in the field, all applicable to multiple types of cells and products, and proven successful in multiple major cell types. These apply to three major categories: production of native metabolites and/or bioactives, heterologous expression of biosynthetic pathways, and protein expression. This meta-review provides general strategy guides for the broad range of applications of rational engineering of cell factories.

Molecular Engineering of the TGF-β Signaling Pathway

Transforming growth factor beta (TGF-β) is an important growth factor that plays essential roles in regulating tissue development and homeostasis. Dysfunction of TGF-β signaling is a hallmark of many human diseases. Therefore, targeting TGF-β signaling presents broad therapeutic potential. Since the discovery of the TGF-β ligand, a collection of engineered signaling proteins have been developed to probe and manipulate TGF-β signaling responses. In this review, we highlight recent progress in the engineering of TGF-β signaling for different applications and discuss how molecular engineering approaches can advance our understanding of this important pathway. In addition, we provide a future outlook on the opportunities and challenges in the engineering of the TGF-β signaling pathway from a quantitative perspective.

Transcriptome Profiling and Molecular Therapeutic Advances in Cystic Fibrosis: Recent Insights

In cystic fibrosis (CF), mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) gene disrupt the capacity of the encoded protein to function as a channel to transport chloride ions and water across cell membranes. The consequences are deleterious, system-wide, and immensely variable, even among patients with the same CFTR genotype. This underscores the need to characterize the mechanisms contributing to CF pathophysiology. Gene replacement and gene editing therapies have been pursued intensively and are expected to provide a one-time treatment for CF. However, gene replacement therapy is limited by the lack of efficient vectors to deliver functional copies of CFTR to cells without immunological complications, while gene editing technologies such as CRISPR/Cas9 are still in their infancy, mainly useful in somatic cells and limited by off-target insertions. Small molecule treatments targeted at potentiating or correcting CFTR have shown clinical benefits, but they are limited to a few CFTR mutations and insufficient to overcome challenges related to clinical heterogeneity. Transcriptome profiling approaches have emerged as robust tools capable of characterizing phenotypic variability and revealing novel molecular targets with therapeutic potential for CF. We summarize current insights gained through transcriptome profiling approaches in CF studies and recent advances in molecular therapeutics.

Biofunctionalized Materials Featuring Feedforward and Feedback Circuits Exemplified by the Detection of Botulinum Toxin A

Feedforward and feedback loops are key regulatory elements in cellular signaling and information processing. Synthetic biology exploits these elements for the design of molecular circuits that enable the reprogramming and control of specific cellular functions. These circuits serve as a basis for the engineering of complex cellular networks, opening the door for numerous medical and biotechnological applications. Here, a similar principle is applied. Feedforward and positive feedback circuits are incorporated into biohybrid polymer materials in order to develop signal-sensing and signal-processing devices. This concept is exemplified by the detection of the proteolytic activity of the botulinum neurotoxin A. To this aim, site-specific proteases are incorporated into receiver, transmitter, and output materials, and their release, diffusion, and/or activation are wired according to a feedforward or a positive feedback circuit. The development of a quantitative mathematical model enables analysis and comparison of the performance of both systems. The flexible design could be easily adapted to detect other toxins or molecules of interest. Furthermore, cellular signaling or gene regulatory pathways could provide additional blueprints for the development of novel biohybrid circuits. Such information-processing, material-embedded biological circuits hold great promise for a variety of analytical, medical, or biotechnological applications.

Plant Chromatin Catches the Sun

Plants use solar radiation as energy source for photosynthesis. They also take advantage of the information provided by the varying properties of sunlight, such as wavelength, orientation, and periodicity, to trigger physiological and developmental adaptations to a changing environment. After more than a century of research efforts in plant photobiology, multiple light signaling pathways converging onto chromatin-based mechanisms have now been identified, which in some instances play critical roles in plant phenotypic plasticity. In addition to locus-specific changes linked to transcription regulation, light signals impact higher-order chromatin organization. Here, we summarize current knowledge on how light can affect the global composition and the spatial distribution of chromatin domains. We introduce emerging questions on the functional links between light signaling and the epigenome, and further discuss how different chromatin regulatory layers may interconnect during plant adaptive responses to light.

Synthesizing artificial devices that redirect cellular information at will

Natural signaling circuits could be rewired to reprogram cells with pre-determined procedures. However, it is difficult to link cellular signals at will. Here, we describe signal-connectors—a series of RNA devices—that connect one signal to another signal at the translational level. We use them to either repress or enhance the translation of target genes in response to signals. Application of these devices allows us to construct various logic gates and to incorporate feedback loops into gene networks. They have also been used to rewire a native signaling pathway and even to create novel pathways. Furthermore, logical AND gates based on these devices and integration of multiple signals have been used successfully for identification and redirection of the state of cancer cells. Eventually, the malignant phenotypes of cancers have been reversed by rewiring the oncogenic signaling from promoting to suppressing tumorigenesis. We provide a novel platform for redirecting cellular information.

Cells respond to signals from their surrounding environment. External signals activate a sequence of events inside the cell that can change how it behaves. These events are often called signaling pathways and they typically change the cell’s behavior by changing the activity of its genes.

A major objective of the field of genetic engineering is to customize or artificially create new signaling pathways to make cells behave in certain ways. The ability to control a cell’s behavior is likely to have a major impact on human health and medicine. For instance, it may be possible to reprogram signaling events in cancer cells so that they die rather than grow rapidly.

Researchers are developing artificial genetic devices to manipulate signaling pathways. Molecules of ribonucleic acid (or RNA) are widely used to design such devices. In nature, RNA molecules are highly versatile: messenger RNA molecules carry genetic information in a form that can be translated into protein, while other RNA molecules fine-tune gene expression and perform a host of other roles. RNA is apt for artificial devices because it can be tailored to detect signals and convert this information into a predictable outcome, such as turning specific genes on or off.

In 2016, researchers constructed an RNA device to control the expression of genes in response to particular signals. However, this device was too large to deliver efficiently inside cells. Now, Liu, Li, Chen et al. – including some of the researchers involved the 2016 study – design smaller RNA devices to overcome this limitation. Each new device consists of two RNA components: one that recognizes the signal, and another that recognizes the messenger RNA of a target gene. Together the two components trigger the desired change in gene expression in response to a specific signal.

The devices were shown to have multiple uses such as making new connections in a signaling pathway and creating new signaling networks. Furthermore, Liu, Li, Chen et al. engineered one device such that it was able to specifically turn off genes in a particular signaling pathway that allows human bladder cancer cells to divide. By silencing these genes, the cancer cells were less able to grow.

These newly developed RNA devices should allow other researchers to customize cellular information and may have future therapeutic applications as well.

Design of Tunable Oscillatory Dynamics in a Synthetic NF-κB Signaling Circuit

Although oscillatory circuits are prevalent in transcriptional regulation, it is unclear how a circuit's structure and the specific parameters that describe its components determine the shape of its oscillations. Here, we engineer a minimal, inducible human nuclear factor κB (NF-κB)-based system that is composed of NF-κB (RelA) and degradable inhibitor of NF-κB (IκBα), into the yeast, Saccharomyces cerevisiae. We define an oscillation's waveform quantitatively as a function of signal amplitude, rest time, rise time, and decay time; by systematically tuning RelA concentration, the strength of negative feedback, and the degradation rate of IκBα, we demonstrate that peak shape and frequency of oscillations can be controlled in vivo and predicted mathematically. In addition, we show that nested negative feedback loops can be employed to specifically tune the frequency of oscillations while leaving their peak shape unchanged. In total, this work establishes design principles that enable function-guided design of oscillatory signaling controllers in diverse synthetic biology applications.

Piconewton-Scale Analysis of Ras-BRaf Signal Transduction with Single-Molecule Force Spectroscopy

Intermolecular interactions dominate the behavior of signal transduction in various physiological and pathological cell processes, yet assessing these interactions remains a challenging task. Here, this study reports a single-molecule force spectroscopic method that enables functional delineation of two interaction sites (≈35 pN and ≈90 pN) between signaling effectors Ras and BRaf in the canonical mitogen-activated protein kinase (MAPK) pathway. This analysis reveals mutations on BRaf at Q257 and A246, two sites frequently linked to cardio-faciocutaneous syndrome, result in ≈10-30 pN alterations in RasBRaf intermolecular binding force. The magnitude of changes in RasBRaf binding force correlates with the size of alterations in protein affinity and in α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA)-sensitive glutamate receptor (-R)-mediated synaptic transmission in neurons expressing replacement BRaf mutants, and predicts the extent of learning impairments in animals expressing replacement BRaf mutants. These results establish single-molecule force spectroscopy as an effective platform for evaluating the piconewton-level interaction of signaling molecules and predicting the behavior outcome of signal transduction.

Developing an Inositol-Phosphate-Actuated Nanochannel System by Mimicking Biological Calcium Ion Channels

In eukaryotic cells, ion channels, which ubiquitously present as polypeptides or proteins, usually regulate the ion transport across biological membranes by conformational switching of the channel proteins in response to the binding of diverse signaling molecules (e.g., inositol phosphate, abbreviated to InsP). To mimic the gating behaviors of natural Ca²⁺ channels manipulated by InsPs, a smart poly[(N-isopropylacrylamide-co-4-(3-acryloylthioureido) benzoic acid)_0.2] (denoted as PNI-co-ATBA_0.2) was integrated onto a porous anodic alumina (PAA) membrane, building an InsP-actuated nanochannel system. Driven by the intensive hydrogen bonding complexation of ATBA monomer with InsP, the copolymer chains displayed a remarkable and reversible conformational transition from a contracted state to a swollen one, accompanied with significant changes in surface morphology, wettability, and viscoelasticity. Benefiting from these features, dynamic gating behaviors of the nanochannels located on the copolymer-modified PAA membrane could be precisely manipulated by InsPs, reflected as a satisfactory linear relationship between real-time variation in transmembrane ionic current and the InsP concentration over a wide range from 1 nmol L^-1 to 10 μmol L^-1, as well as a clear discrimination among InsP₂, InsP₃, and InsP₆. This study indicates the great potential of biomolecule-responsive polymers in the fabrication of biomimetic ion nanochannels and other nanoscale biodevices.

Enabling tools for high-throughput detection of metabolites: Metabolic engineering and directed evolution applications

Within the Design-Build-Test Cycle for strain engineering, rapid product detection and selection strategies remain challenging and limit overall throughput. Here we summarize a wide variety of modalities that transduce chemical concentrations into easily measured absorbance, luminescence, and fluorescence signals. Specifically, we cover protein-based biosensors (including transcription factors), nucleic acid-based biosensors, coupled enzyme reactions, bioorthogonal chemistry, and fluorescent and chromogenic dyes and substrates as modalities for detection. We focus on the use of these methods for strain engineering and enzyme discovery and conclude with remarks on the current and future state of biosensor development for application in the metabolic engineering field.

ACRE: Absolute concentration robustness exploration in module-based combinatorial networks

To engineer cells for industrial-scale application, a deep understanding of how to design molecular control mechanisms to tightly maintain functional stability under various fluctuations is crucial. Absolute concentration robustness (ACR) is a category of robustness in reaction network models in which the steady-state concentration of a molecular species is guaranteed to be invariant even with perturbations in the other molecular species in the network. Here, we introduce a software tool, absolute concentration robustness explorer (ACRE), which efficiently explores combinatorial biochemical networks for the ACR property. ACRE has a user-friendly interface, and it can facilitate efficient analysis of key structural features that guarantee the presence and the absence of the ACR property from combinatorial networks. Such analysis is expected to be useful in synthetic biology as it can increase our understanding of how to design molecular mechanisms to tightly control the concentration of molecular species. ACRE is freely available at https://github.com/ramzan1990/ACRE.

Programmable Potentials: Approximate N-body potentials from coarse-level logic

This paper gives a systematic method for constructing an N-body potential, approximating the true potential, that accurately captures meso-scale behavior of the chemical or biological system using pairwise potentials coming from experimental data or ab initio methods. The meso-scale behavior is translated into logic rules for the dynamics. Each pairwise potential has an associated logic function that is constructed using the logic rules, a class of elementary logic functions, and AND, OR, and NOT gates. The effect of each logic function is to turn its associated potential on and off. The N-body potential is constructed as linear combination of the pairwise potentials, where the “coefficients” of the potentials are smoothed versions of the associated logic functions. These potentials allow a potentially low-dimensional description of complex processes while still accurately capturing the relevant physics at the meso-scale. We present the proposed formalism to construct coarse-grained potential models for three examples: an inhibitor molecular system, bond breaking in chemical reactions, and DNA transcription from biology. The method can potentially be used in reverse for design of molecular processes by specifying properties of molecules that can carry them out.

Triggering signaling pathways using F-actin self-organization

The spatiotemporal organization of proteins within cells is essential for cell fate behavior. Although it is known that the cytoskeleton is vital for numerous cellular functions, it remains unclear how cytoskeletal activity can shape and control signaling pathways in space and time throughout the cell cytoplasm. Here we show that F-actin self-organization can trigger signaling pathways by engineering two novel properties of the microfilament self-organization: (1) the confinement of signaling proteins and (2) their scaffolding along actin polymers. Using in vitro reconstitutions of cellular functions, we found that both the confinement of nanoparticle-based signaling platforms powered by F-actin contractility and the scaffolding of engineered signaling proteins along actin microfilaments can drive a signaling switch. Using Ran-dependent microtubule nucleation, we found that F-actin dynamics promotes the robust assembly of microtubules. Our in vitro assay is a first step towards the development of novel bottom-up strategies to decipher the interplay between cytoskeleton spatial organization and signaling pathway activity.

Controllability analysis of the directed human protein interaction network identifies disease genes and drug targets

The protein-protein interaction (PPI) network is crucial for cellular information processing and decision-making. With suitable inputs, PPI networks drive the cells to diverse functional outcomes such as cell proliferation or cell death. Here, we characterize the structural controllability of a large directed human PPI network comprising 6,339 proteins and 34,813 interactions. This network allows us to classify proteins as "indispensable," "neutral," or "dispensable," which correlates to increasing, no effect, or decreasing the number of driver nodes in the network upon removal of that protein. We find that 21% of the proteins in the PPI network are indispensable. Interestingly, these indispensable proteins are the primary targets of disease-causing mutations, human viruses, and drugs, suggesting that altering a network's control property is critical for the transition between healthy and disease states. Furthermore, analyzing copy number alterations data from 1,547 cancer patients reveals that 56 genes that are frequently amplified or deleted in nine different cancers are indispensable. Among the 56 genes, 46 of them have not been previously associated with cancer. This suggests that controllability analysis is very useful in identifying novel disease genes and potential drug targets.

Engineering Synthetic Multistress Tolerance in Escherichia coli by Using a Deinococcal Response Regulator, DR1558

Cellular robustness is an important trait for industrial microbes, because the microbial strains are exposed to a multitude of different stresses during industrial processes, such as fermentation. Thus, engineering robustness in an organism in order to push the strains toward maximizing yield has become a significant topic of research. We introduced the deinococcal response regulator DR1558 into Escherichia coli (strain Ec-1558), thereby conferring tolerance to hydrogen peroxide (H2O2). The reactive oxygen species (ROS) level in strain Ec-1558 was reduced due to the increased KatE catalase activity. Among four regulators of the oxidative-stress response, OxyR, RpoS, SoxS, and Fur, we found that the expression of rpoS increased in Ec-1558, and we confirmed this increase by Western blot analysis. Electrophoretic mobility shift assays showed that DR1558 bound to the rpoS promoter. Because the alternative sigma factor RpoS regulates various stress resistance-related genes, we performed stress survival analysis using an rpoS mutant strain. Ec-1558 was able to tolerate a low pH, a high temperature, and high NaCl concentrations in addition to H2O2, and the multistress tolerance phenotype disappeared in the absence of rpoS. Microarray analysis clearly showed that a variety of stress-responsive genes that are directly or indirectly controlled by RpoS were upregulated in strain Ec-1558. These findings, taken together, indicate that the multistress tolerance conferred by DR1558 is likely routed through RpoS. In the present study, we propose a novel strategy of employing an exogenous response regulator from polyextremophiles for strain improvement.

Protein engineering: a new frontier for biological therapeutics

Protein engineering holds the potential to transform the metabolic drug landscape through the development of smart, stimulusresponsive drug systems. Protein therapeutics are a rapidly expanding segment of Food and Drug Administration approved drugs that will improve clinical outcomes over the long run. Engineering of protein therapeutics is still in its infancy, but recent general advances in protein engineering capabilities are being leveraged to yield improved control over both pharmacokinetics and pharmacodynamics. Stimulus- responsive protein therapeutics are drugs which have been designed to be metabolized under targeted conditions. Protein engineering is being utilized to develop tailored smart therapeutics with biochemical logic. This review focuses on applications of targeted drug neutralization, stimulus-responsive engineered protein prodrugs, and emerging multicomponent smart drug systems (e.g., antibody-drug conjugates, responsive engineered zymogens, prospective biochemical logic smart drug systems, drug buffers, and network medicine applications).

A fungicide-responsive kinase as a tool for synthetic cell fate regulation

Engineered biological systems that precisely execute defined tasks have major potential for medicine and biotechnology. For instance, gene- or cell-based therapies targeting pathogenic cells may replace time- and resource-intensive drug development. Engineering signal transduction systems is a promising, yet presently underexplored approach. Here, we exploit a fungicide-responsive heterologous histidine kinase for pathway engineering and synthetic cell fate regulation in the budding yeast Saccharomyces cerevisiae. Rewiring the osmoregulatory Hog1 MAPK signalling system generates yeast cells programmed to execute three different tasks. First, a synthetic negative feedback loop implemented by employing the fungicide-responsive kinase and a fungicide-resistant derivative reshapes the Hog1 activation profile, demonstrating how signalling dynamics can be engineered. Second, combinatorial integration of different genetic parts including the histidine kinases, a pathway activator and chemically regulated promoters enables control of yeast growth and/or gene expression in a two-input Boolean logic manner. Finally, we implemented a genetic ‘suicide attack’ system, in which engineered cells eliminate target cells and themselves in a specific and controllable manner. Taken together, fungicide-responsive kinases can be applied in different constellations to engineer signalling behaviour. Sensitizing engineered cells to existing chemicals may be generally useful for future medical and biotechnological applications.

Dynamic signal processing by ribozyme-mediated RNA circuits to control gene expression

Organisms have different circuitries that allow converting signal molecule levels to changes in gene expression. An important challenge in synthetic biology involves the de novo design of RNA modules enabling dynamic signal processing in live cells. This requires a scalable methodology for sensing, transmission, and actuation, which could be assembled into larger signaling networks. Here, we present a biochemical strategy to design RNA-mediated signal transduction cascades able to sense small molecules and small RNAs. We design switchable functional RNA domains by using strand-displacement techniques. We experimentally characterize the molecular mechanism underlying our synthetic RNA signaling cascades, show the ability to regulate gene expression with transduced RNA signals, and describe the signal processing response of our systems to periodic forcing in single live cells. The engineered systems integrate RNA–RNA interaction with available ribozyme and aptamer elements, providing new ways to engineer arbitrary complex gene circuits.

Boolean network model for GPR142 against Type 2 diabetes and relative dynamic change ratio analysis using systems and biological circuits approach

Systems biology addresses challenges in the analysis of genomics data, especially for complex genes and protein interactions using Meta data approach on various signaling pathways. In this paper, we report systems biology and biological circuits approach to construct pathway and identify early gene and protein interactions for predicting GPR142 responses in Type 2 diabetes. The information regarding genes, proteins and other molecules involved in Type 2 diabetes were retrieved from literature and kinetic simulation of GPR142 was carried out in order to determine the dynamic interactions. The major objective of this work was to design a GPR142 biochemical pathway using both systems biology as well as biological circuits synthetically. The term 'synthetically' refers to building biological circuits for cell signaling pathway especially for hormonal pathway disease. The focus of the paper is on logical components and logical circuits whereby using these applications users can create complex virtual circuits. Logic gates process represents only true or false and investigates whether biological regulatory circuits are active or inactive. The basic gates used are AND, NAND, OR, XOR and NOT gates and Integrated circuit composition of many such basic gates and some derived gates. Biological circuits may have a futuristic application in biomedical sciences which may involve placing a micro chip in human cells to modulate the down or up regulation of hormonal disease.

Quantitative Analysis of Robustness of Dynamic Response and Signal Transfer in Insulin mediated PI3K/AKT Pathway

Robustness is a critical feature of signaling pathways ensuring signal propagation with high fidelity in the event of perturbations. Here we present a detailed quantitative analysis of robustness in insulin mediated PI3K/AKT pathway, a critical signaling pathway maintaining self-renewal in human embryonic stem cells. Using global sensitivity analysis, we identified robustness promoting mechanisms that ensure (1) maintenance of a first order or overshoot dynamics of self-renewal molecule, p-AKT and (2) robust transfer of signals from oscillatory insulin stimulus to p-AKT in the presence of noise. Our results indicate that negative feedback controls the robustness to most perturbations. Faithful transfer of signal from the stimulating ligand to p-AKT occurs even in the presence of noise, albeit with signal attenuation and high frequency cut-off. Negative feedback contributes to signal attenuation, while positive regulators upstream of PIP₃ contribute to signal amplification. These results establish precise mechanisms to modulate self-renewal molecules like p-AKT.

Multi-layered global gene regulation in mouse embryonic stem cells

Embryonic stem (ES) cells derived from the inner cell mass of developing embryos have tremendous potential in regenerative medicine due to their unique properties: ES cells can be maintained for a prolonged time without changes in their cellular characteristics in vitro (self-renewal), while sustaining the capacity to give rise to all cell types of adult organisms (pluripotency). In addition to the development of protocols to manipulate ES cells for therapeutic applications, understanding how such unique properties are maintained has been one of the key questions in stem cell research. During the past decade, advances in high-throughput technologies have enabled us to systematically monitor multiple layers of gene regulatory mechanisms in ES cells. In this review, we briefly summarize recent findings on global gene regulatory modes in ES cells, mainly focusing on the regulatory factors responsible for transcriptional and epigenetic regulations as well as their modular regulatory patterns throughout the genome.