Rapid diversification of cell signaling phenotypes by modular domain recombination

Learning from the unknown: exploring the range of bacterial functionality

Determining the repertoire of a microbe's molecular functions is a central question in microbial biology. Modern techniques achieve this goal by comparing microbial genetic material against reference databases of functionally annotated genes/proteins or known taxonomic markers such as 16S rRNA. Here, we describe a novel approach to exploring bacterial functional repertoires without reference databases. Our Fusion scheme establishes functional relationships between bacteria and assigns organisms to Fusion-taxa that differ from otherwise defined taxonomic clades. Three key findings of our work stand out. First, bacterial functional comparisons outperform marker genes in assigning taxonomic clades. Fusion profiles are also better for this task than other functional annotation schemes. Second, Fusion-taxa are robust to addition of novel organisms and are, arguably, able to capture the environment-driven bacterial diversity. Finally, our alignment-free nucleic acid-based Siamese Neural Network model, created using Fusion functions, enables finding shared functionality of very distant, possibly structurally different, microbial homologs. Our work can thus help annotate functional repertoires of bacterial organisms and further guide our understanding of microbial communities.

Domain Architecture Based Methods for Comparative Functional Genomics Toward Therapeutic Drug Target Discovery

Genes duplicate, mutate, recombine, fuse or fission to produce new genes, or when genes are formed from de novo, novel functions arise during evolution. Researchers have tried to quantify the causes of these molecular diversification processes to know how these genes increase molecular complexity over a period of time, for instance protein domain organization. In contrast to global sequence similarity, protein domain architectures can capture key structural and functional characteristics, making them better proxies for describing functional equivalence. In Prokaryotes and eukaryotes it has proven that, domain designs are retained over significant evolutionary distances. Protein domain architectures are now being utilized to categorize and distinguish evolutionarily related proteins and find homologs among species that are evolutionarily distant from one another. Additionally, structural information stored in domain structures has accelerated homology identification and sequence search methods. Tools for functional protein annotation have been developed to discover, protein domain content, domain order, domain recurrence, and domain position as all these contribute to the prediction of protein functional accuracy. In this review, an attempt is made to summarise facts and speculations regarding the use of protein domain architecture and modularity to identify possible therapeutic targets among cellular activities based on the understanding their linked biological processes.

Real or fake? Measuring the impact of protein annotation errors on estimates of domain gain and loss events

Protein annotation errors can have significant consequences in a wide range of fields, ranging from protein structure and function prediction to biomedical research, drug discovery, and biotechnology. By comparing the domains of different proteins, scientists can identify common domains, classify proteins based on their domain architecture, and highlight proteins that have evolved differently in one or more species or clades. However, genome-wide identification of different protein domain architectures involves a complex error-prone pipeline that includes genome sequencing, prediction of gene exon/intron structures, and inference of protein sequences and domain annotations. Here we developed an automated fact-checking approach to distinguish true domain loss/gain events from false events caused by errors that occur during the annotation process. Using genome-wide ortholog sets and taking advantage of the high-quality human and Saccharomyces cerevisiae genome annotations, we analyzed the domain gain and loss events in the predicted proteomes of 9 non-human primates (NHP) and 20 non-S. cerevisiae fungi (NSF) as annotated in the Uniprot and Interpro databases. Our approach allowed us to quantify the impact of errors on estimates of protein domain gains and losses, and we show that domain losses are over-estimated ten-fold and three-fold in the NHP and NSF proteins respectively. This is in line with previous studies of gene-level losses, where issues with genome sequencing or gene annotation led to genes being falsely inferred as absent. In addition, we show that insistent protein domain annotations are a major factor contributing to the false events. For the first time, to our knowledge, we show that domain gains are also over-estimated by three-fold and two-fold respectively in NHP and NSF proteins. Based on our more accurate estimates, we infer that true domain losses and gains in NHP with respect to humans are observed at similar rates, while domain gains in the more divergent NSF are observed twice as frequently as domain losses with respect to S. cerevisiae. This study highlights the need to critically examine the scientific validity of protein annotations, and represents a significant step toward scalable computational fact-checking methods that may 1 day mitigate the propagation of wrong information in protein databases.

speedingCARs: accelerating the engineering of CAR T cells by signaling domain shuffling and single-cell sequencing

Chimeric antigen receptors (CARs) consist of an antigen-binding region fused to intracellular signaling domains, enabling customized T cell responses against targets. Despite their major role in T cell activation, effector function and persistence, only a small set of immune signaling domains have been explored. Here we present speedingCARs, an integrated method for engineering CAR T cells via signaling domain shuffling and pooled functional screening. Leveraging the inherent modularity of natural signaling domains, we generate a library of 180 unique CAR variants genomically integrated into primary human T cells by CRISPR-Cas9. In vitro tumor cell co-culture, followed by single-cell RNA sequencing (scRNA-seq) and single-cell CAR sequencing (scCAR-seq), enables high-throughput screening for identifying several variants with tumor killing properties and T cell phenotypes markedly different from standard CARs. Mapping of the CAR scRNA-seq data onto that of tumor infiltrating lymphocytes further helps guide the selection of variants. These results thus help expand the CAR signaling domain combination space, and supports speedingCARs as a tool for the engineering of CARs for potential therapeutic development.

Genomic evolution of the Coronaviridae family

The current outbreak of coronavirus disease-2019 (COVID-19) caused by SARS-CoV-2 poses unparalleled challenges to global public health. SARS-CoV-2 is a Betacoronavirus, one of four genera belonging to the Coronaviridae subfamily Orthocoronavirinae. Coronaviridae, in turn, are members of the order Nidovirales, a group of enveloped, positive-stranded RNA viruses. Here we present a systematic phylogenetic and evolutionary study based on protein domain architecture, encompassing the entire proteomes of all Orthocoronavirinae, as well as other Nidovirales. This analysis has revealed that the genomic evolution of Nidovirales is associated with extensive gains and losses of protein domains. In Orthocoronavirinae, the sections of the genomes that show the largest divergence in protein domains are found in the proteins encoded in the amino-terminal end of the polyprotein (PP1ab), the spike protein (S), and many of the accessory proteins. The diversity among the accessory proteins is particularly striking, as each subgenus possesses a set of accessory proteins that is almost entirely specific to that subgenus. The only notable exception to this is ORF3b, which is present and orthologous over all Alphacoronaviruses. In contrast, the membrane protein (M), envelope small membrane protein (E), nucleoprotein (N), as well as proteins encoded in the central and carboxy-terminal end of PP1ab (such as the 3C-like protease, RNA-dependent RNA polymerase, and Helicase) show stable domain architectures across all Orthocoronavirinae. This comprehensive analysis of the Coronaviridae domain architecture has important implication for efforts to develop broadly cross-protective coronavirus vaccines.

Probing ion channel functional architecture and domain recombination compatibility by massively parallel domain insertion profiling

Protein domains are the basic units of protein structure and function. Comparative analysis of genomes and proteomes showed that domain recombination is a main driver of multidomain protein functional diversification and some of the constraining genomic mechanisms are known. Much less is known about biophysical mechanisms that determine whether protein domains can be combined into viable protein folds. Here, we use massively parallel insertional mutagenesis to determine compatibility of over 300,000 domain recombination variants of the Inward Rectifier K⁺ channel Kir2.1 with channel surface expression. Our data suggest that genomic and biophysical mechanisms acted in concert to favor gain of large, structured domain at protein termini during ion channel evolution. We use machine learning to build a quantitative biophysical model of domain compatibility in Kir2.1 that allows us to derive rudimentary rules for designing domain insertion variants that fold and traffic to the cell surface. Positional Kir2.1 responses to motif insertion clusters into distinct groups that correspond to contiguous structural regions of the channel with distinct biophysical properties tuned towards providing either folding stability or gating transitions. This suggests that insertional profiling is a high-throughput method to annotate function of ion channel structural regions.

Switching an active site helix in dihydrofolate reductase reveals limits to subdomain modularity

To what degree are individual structural elements within proteins modular such that similar structures from unrelated proteins can be interchanged? We study subdomain modularity by creating 20 chimeras of an enzyme, Escherichia coli dihydrofolate reductase (DHFR), in which a catalytically important, 10-residue α-helical sequence is replaced by α-helical sequences from a diverse set of proteins. The chimeras stably fold but have a range of diminished thermal stabilities and catalytic activities. Evolutionary coupling analysis indicates that the residues of this α-helix are under selection pressure to maintain catalytic activity in DHFR. Reversion to phenylalanine at key position 31 was found to partially restore catalytic activity, which could be explained by evolutionary coupling values. We performed molecular dynamics simulations using replica exchange with solute tempering. Chimeras with low catalytic activity exhibit nonhelical conformations that block the binding site and disrupt the positioning of the catalytically essential residue D27. Simulation observables and in vitro measurements of thermal stability and substrate-binding affinity are strongly correlated. Several E. coli strains with chromosomally integrated chimeric DHFRs can grow, with growth rates that follow predictions from a kinetic flux model that depends on the intracellular abundance and catalytic activity of DHFR. Our findings show that although α-helices are not universally substitutable, the molecular and fitness effects of modular segments can be predicted by the biophysical compatibility of the replacement segment.

Ligand Binding Domain of Estrogen Receptor Alpha Preserve a Conserved Structural Architecture Similar to Bacterial Taxis Receptors

It remains a mystery why estrogen hormone receptors (ERs), which are highly specific toward its endogenous hormones, are responsive to chemically distinct exogenous agents. Does it indicate that ERs are environmentally regulated? Here, we speculate that ERs would have some common structural features with prokaryotic taxis receptor responsive toward environmental signals. This study addresses the low specificity and high responsiveness of ERs toward chemically distinct exogenous substances, from an evolutionary point of view. Here, we compared the ligand binding domain (LBD) of ER alpha (α) with the LBDs of prokaryotic taxis receptors to check if LBDs share any structural similarity. Interestingly, a high degree of similarity in the domain structural fold architecture of ERα and bacterial taxis receptors was observed. The pharmacophore modeling focused on ligand molecules of both receptors suggest that these ligands share common pharmacophore features. The molecular docking studies suggest that the natural ligands of bacterial chemotaxis receptors exhibit strong interaction with human ER as well. Although phylogenetic analysis proved that these proteins are unrelated, they would have evolved independently, suggesting a possibility of convergent molecular evolution. Nevertheless, a remarkable sequence divergence was seen between these proteins even when they shared common domain structural folds and common ligand-based pharmacophore features, suggesting that the protein architecture remains conserved within the structure for a specific function irrespective of sequence identity.

An engineered protein-phosphorylation toggle network with implications for endogenous network discovery

Synthetic biological networks comprising fast, reversible reactions could enable engineering of new cellular behaviors that are not possible with slower regulation. Here, we created a bistable toggle switch in Saccharomyces cerevisiae using a cross-repression topology comprising 11 protein-protein phosphorylation elements. The toggle is ultrasensitive, can be induced to switch states in seconds, and exhibits long-term bistability. Motivated by our toggle's architecture and size, we developed a computational framework to search endogenous protein pathways for other large and similar bistable networks. Our framework helped us to identify and experimentally verify five formerly unreported endogenous networks that exhibit bistability. Building synthetic protein-protein networks will enable bioengineers to design fast sensing and processing systems, allow sophisticated regulation of cellular processes, and aid discovery of endogenous networks with particular functions.

Structurally distributed surface sites tune allosteric regulation

Our ability to rationally optimize allosteric regulation is limited by incomplete knowledge of the mutations that tune allostery. Are these mutations few or abundant, structurally localized or distributed? To examine this, we conducted saturation mutagenesis of a synthetic allosteric switch in which Dihydrofolate reductase (DHFR) is regulated by a blue-light sensitive LOV2 domain. Using a high-throughput assay wherein DHFR catalytic activity is coupled to E. coli growth, we assessed the impact of 1548 viable DHFR single mutations on allostery. Despite most mutations being deleterious to activity, fewer than 5% of mutations had a statistically significant influence on allostery. Most allostery disrupting mutations were proximal to the LOV2 insertion site. In contrast, allostery enhancing mutations were structurally distributed and enriched on the protein surface. Combining several allostery enhancing mutations yielded near-additive improvements to dynamic range. Our results indicate a path toward optimizing allosteric function through variation at surface sites.

Many proteins exhibit a property called ‘allostery’. In allostery, an input signal at a specific site of a protein – such as a molecule binding, or the protein absorbing a photon of light – leads to a change in output at another site far away. For example, the protein might catalyze a chemical reaction faster or bind to another molecule more tightly in the presence of the input signal. This protein ‘remote control’ allows cells to sense and respond to changes in their environment. An ability to rapidly engineer new allosteric mechanisms into proteins is much sought after because this would provide an approach for building biosensors and other useful tools. One common approach to engineering new allosteric regulation is to combine a ‘sensor’ or input region from one protein with an ‘output’ region or domain from another.

When researchers engineer allostery using this approach of combining input and output domains from different proteins, the difference in the output when the input is ‘on’ versus ‘off’ is often small, a situation called ‘modest allostery’. McCormick et al. wanted to know how to optimize this domain combination approach to increase the difference in output between the ‘on’ and ‘off’ states.

More specifically, McCormick et al. wanted to find out whether swapping out or mutating specific amino acids (each of the individual building blocks that make up a protein) enhances or disrupts allostery. They also wanted to know if there are many possible mutations that change the effectiveness of allostery, or if this property is controlled by just a few amino acids. Finally, McCormick et al. questioned where in a protein most of these allostery-tuning mutations were located.

To answer these questions, McCormick et al. engineered a new allosteric protein by inserting a light-sensing domain (input) into a protein involved in metabolism (a metabolic enzyme that produces a biomolecule called a tetrahydrofolate) to yield a light-controlled enzyme. Next, they introduced mutations into both the ‘input’ and ‘output’ domains to see where they had a greater effect on allostery.

After filtering out mutations that destroyed the function of the output domain, McCormick et al. found that only about 5% of mutations to the ‘output’ domain altered the allosteric response of their engineered enzyme. In fact, most mutations that disrupted allostery were found near the site where the ‘input’ domain was inserted, while mutations that enhanced allostery were sprinkled throughout the enzyme, often on its protein surface. This was surprising in light of the commonly-held assumption that mutations on protein surfaces have little impact on the activity of the ‘output’ domain. Overall, the effect of individual mutations on allostery was small, but McCormick et al. found that these mutations can sometimes be combined to yield larger effects.

McCormick et al.’s results suggest a new approach for optimizing engineered allosteric proteins: by introducing mutations on the protein surface. It also opens up new questions: mechanically, how do surface sites affect allostery? In the future, it will be important to characterize how combinations of mutations can optimize allosteric regulation, and to determine what evolutionary trajectories to high performance allosteric ‘switches’ look like.

Conjugated Protein Domains as Engineered Scaffold Proteins

Assembly of proteins into higher-order complexes generates specificity and selectivity in cellular signaling. Signaling complex formation is facilitated by scaffold proteins that use modular scaffolding domains, which recruit specific pathway enzymes. Multimerization and recombination of these conjugated native domains allows the generation of libraries of engineered multidomain scaffold proteins. Analysis of these engineered proteins has provided molecular insight into the regulatory mechanism of the native scaffold proteins and the applicability of these synthetic variants. This topical review highlights the use of engineered, conjugated multidomain scaffold proteins on different length scales in the context of synthetic signaling pathways, metabolic engineering, liquid-liquid phase separation, and hydrogel formation.

Enzyme Assembly for Compartmentalized Metabolic Flux Control

Enzyme assembly by ligand binding or physically sequestrating enzymes, substrates, or metabolites into isolated compartments can bring key molecules closer to enhance the flux of a metabolic pathway. The emergence of enzyme assembly has provided both opportunities and challenges for metabolic engineering. At present, with the development of synthetic biology and systems biology, a variety of enzyme assembly strategies have been proposed, from the initial direct enzyme fusion to scaffold-free assembly, as well as artificial scaffolds, such as nucleic acid/protein scaffolds, and even some more complex physical compartments. These assembly strategies have been explored and applied to the synthesis of various important bio-based products, and have achieved different degrees of success. Despite some achievements, enzyme assembly, especially in vivo, still has many problems that have attracted significant attention from researchers. Here, we focus on some selected examples to review recent research on scaffold-free strategies, synthetic artificial scaffolds, and physical compartments for enzyme assembly or pathway sequestration, and we discuss their notable advances. In addition, the potential applications and challenges in the applications are highlighted.

Targeted insertional mutagenesis libraries for deep domain insertion profiling

Domain recombination is a key principle in protein evolution and protein engineering, but inserting a donor domain into every position of a target protein is not easily experimentally accessible. Most contemporary domain insertion profiling approaches rely on DNA transposons, which are constrained by sequence bias. Here, we establish Saturated Programmable Insertion Engineering (SPINE), an unbiased, comprehensive, and targeted domain insertion library generation technique using oligo library synthesis and multi-step Golden Gate cloning. Through benchmarking to MuA transposon-mediated library generation on four ion channel genes, we demonstrate that SPINE-generated libraries are enriched for in-frame insertions, have drastically reduced sequence bias as well as near-complete and highly-redundant coverage. Unlike transposon-mediated domain insertion that was severely biased and sparse for some genes, SPINE generated high-quality libraries for all genes tested. Using the Inward Rectifier K⁺ channel Kir2.1, we validate the practical utility of SPINE by constructing and comparing domain insertion permissibility maps. SPINE is the first technology to enable saturated domain insertion profiling. SPINE could help explore the relationship between domain insertions and protein function, and how this relationship is shaped by evolutionary forces and can be engineered for biomedical applications.

De novo emergence of adaptive membrane proteins from thymine-rich genomic sequences

Recent evidence demonstrates that novel protein-coding genes can arise de novo from non-genic loci. This evolutionary innovation is thought to be facilitated by the pervasive translation of non-genic transcripts, which exposes a reservoir of variable polypeptides to natural selection. Here, we systematically characterize how these de novo emerging coding sequences impact fitness in budding yeast. Disruption of emerging sequences is generally inconsequential for fitness in the laboratory and in natural populations. Overexpression of emerging sequences, however, is enriched in adaptive fitness effects compared to overexpression of established genes. We find that adaptive emerging sequences tend to encode putative transmembrane domains, and that thymine-rich intergenic regions harbor a widespread potential to produce transmembrane domains. These findings, together with in-depth examination of the de novo emerging YBR196C-A locus, suggest a novel evolutionary model whereby adaptive transmembrane polypeptides emerge de novo from thymine-rich non-genic regions and subsequently accumulate changes molded by natural selection.

There is increasing evidence that protein-coding genes can emerge de novo from noncoding genomic regions. Vakirlis et al. propose that sequences encoding transmembrane polypeptides can emerge de novo in thymine-rich genomic regions and provide organisms with fitness benefits.

Synthetic GPCRs and signal transduction cascades

G protein-coupled receptors (GPCRs) are a large and diverse group of membrane proteins that constitute over 30% of FDA approved drug targets. Despite their importance, much remains unknown about GPCR signaling at a system's level. Efforts to engineer receptors with orthogonal components have attempted to provide tools to parse signaling and resultant phenotypes. Recent advances in synthetic biology provide opportunities to engineer receptors at scale and with additional properties that could further inform GPCR biology at a system's level, and enhance the ability to engineer complex signal transduction.

Chimeric dihydrofolate reductases display properties of modularity and biophysical diversity

While reverse genetics and functional genomics have long affirmed the role of individual mutations in determining protein function, there have been fewer studies addressing how large-scale changes in protein sequences, such as in entire modular segments, influence protein function and evolution. Given how recombination can reassort protein sequences, these types of changes may play an underappreciated role in how novel protein functions evolve in nature. Such studies could aid our understanding of whether certain organismal phenotypes related to protein function-such as growth in the presence or absence of an antibiotic-are robust with respect to the identity of certain modular segments. In this study, we combine molecular genetics with biochemical and biophysical methods to gain a better understanding of protein modularity in dihydrofolate reductase (DHFR), an enzyme target of antibiotics also widely used as a model for protein evolution. We replace an integral α-helical segment of Escherichia coli DHFR with segments from a number of different organisms (many nonmicrobial) and examine how these chimeric enzymes affect organismal phenotypes (e.g., resistance to an antibiotic) as well as biophysical properties of the enzyme (e.g., thermostability). We find that organismal phenotypes and enzyme properties are highly sensitive to the identity of DHFR modules, and that this chimeric approach can create enzymes with diverse biophysical characteristics.

Classification of human Herpesviridae proteins using Domain-architecture Aware Inference of Orthologs (DAIO)

We developed a computational approach called Domain-architecture Aware Inference of Orthologs (DAIO) for the analysis of protein orthology by combining phylogenetic and protein domain-architecture information. Using DAIO, we performed a systematic study of the proteomes of all human Herpesviridae species to define Strict Ortholog Groups (SOGs). In addition to assessing the taxonomic distribution for each protein based on sequence similarity, we performed a protein domain-architecture analysis for every protein family and computationally inferred gene duplication events. While many herpesvirus proteins have evolved without any detectable gene duplications or domain rearrangements, numerous herpesvirus protein families do exhibit complex evolutionary histories. Some proteins acquired additional domains (e.g., DNA polymerase), whereas others show a combination of domain acquisition and gene duplication (e.g., betaherpesvirus US22 family), with possible functional implications. This novel classification system of SOGs for human Herpesviridae proteins is available through the Virus Pathogen Resource (ViPR, www.viprbrc.org).

The discovered chimeric protein plays the cohesive role to maintain scallop byssal root structural integrity

Adhesion is essential for many marine sessile organisms. Unraveling the compositions and assembly of marine bioadheisves is the fundamental to understand their physiological roles. Despite the remarkable diversity of animal bioadhesion, our understanding of this biological process remains limited to only a few animal lineages, leaving the majority of lineages remain enigmatic. Our previous study demonstrated that scallop byssus had distinct protein composition and unusual assembly mechanism apart from mussels. Here a novel protein (Sbp9) was discovered from the key part of the byssus (byssal root), which contains two Calcium Binding Domain (CBD) and 49 tandem Epidermal Growth Factor-Like (EGFL) domain repeats. Modular architecture of Sbp9 represents a novel chimeric gene family resulting from a gene fusion event through the acquisition of CBD2 domain by tenascin like (TNL) gene from Na⁺/Ca²⁺exchanger 1 (NCX1) gene. Finally, free thiols are present in Sbp9 and the results of a rescue assay indicated that Sbp9 likely plays the cohesive role for byssal root integrity. This study not only aids our understanding of byssus assembly but will also inspire biomimetic material design.

Ras and Rap Signal Bidirectional Synaptic Plasticity via Distinct Subcellular Microdomains

How signaling molecules achieve signal diversity and specificity is a long-standing cell biology question. Here we report the development of a targeted delivery method that permits specific expression of homologous Ras-family small GTPases (i.e., Ras, Rap2, and Rap1) in different subcellular microdomains, including the endoplasmic reticulum, lipid rafts, bulk membrane, lysosomes, and Golgi complex, in rodent hippocampal CA1 neurons. The microdomain-targeted delivery, combined with multicolor fluorescence protein tagging and high-resolution dual-quintuple simultaneous patch-clamp recordings, allows systematic analysis of microdomain-specific signaling. The analysis shows that Ras signals long-term potentiation via endoplasmic reticulum PI3K and lipid raft ERK, whereas Rap2 and Rap1 signal depotentiation and long-term depression via bulk membrane JNK and lysosome p38MAPK, respectively. These results establish an effective subcellular microdomain-specific targeted delivery method and unveil subcellular microdomain-specific signaling as the mechanism for homologous Ras and Rap to achieve signal diversity and specificity to control multiple forms of synaptic plasticity.

Living Organisms Author Their Read-Write Genomes in Evolution

Evolutionary variations generating phenotypic adaptations and novel taxa resulted from complex cellular activities altering genome content and expression: (i) Symbiogenetic cell mergers producing the mitochondrion-bearing ancestor of eukaryotes and chloroplast-bearing ancestors of photosynthetic eukaryotes; (ii) interspecific hybridizations and genome doublings generating new species and adaptive radiations of higher plants and animals; and, (iii) interspecific horizontal DNA transfer encoding virtually all of the cellular functions between organisms and their viruses in all domains of life. Consequently, assuming that evolutionary processes occur in isolated genomes of individual species has become an unrealistic abstraction. Adaptive variations also involved natural genetic engineering of mobile DNA elements to rewire regulatory networks. In the most highly evolved organisms, biological complexity scales with "non-coding" DNA content more closely than with protein-coding capacity. Coincidentally, we have learned how so-called "non-coding" RNAs that are rich in repetitive mobile DNA sequences are key regulators of complex phenotypes. Both biotic and abiotic ecological challenges serve as triggers for episodes of elevated genome change. The intersections of cell activities, biosphere interactions, horizontal DNA transfers, and non-random Read-Write genome modifications by natural genetic engineering provide a rich molecular and biological foundation for understanding how ecological disruptions can stimulate productive, often abrupt, evolutionary transformations.

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.

Fundamental CRISPR-Cas9 tools and current applications in microbial systems

Derived from the bacterial adaptive immune system, CRISPR technology has revolutionized conventional genetic engineering methods and unprecedentedly facilitated strain engineering. In this review, we outline the fundamental CRISPR tools that have been employed for strain optimization. These tools include CRISPR editing, CRISPR interference, CRISPR activation and protein imaging. To further characterize the CRISPR technology, we present current applications of these tools in microbial systems, including model- and non-model industrial microorganisms. Specially, we point out the major challenges of the CRISPR tools when utilized for multiplex genome editing and sophisticated expression regulation. To address these challenges, we came up with strategies that place emphasis on the amelioration of DNA repair efficiency through CRISPR-Cas9-assisted recombineering. Lastly, multiple promising research directions were proposed, mainly focusing on CRISPR-based construction of microbial ecosystems toward high production of desired chemicals.

Adaptive evolution by spontaneous domain fusion and protein relocalization

Knowledge of adaptive processes encompasses understanding the emergence of new genes. Computational analyses of genomes suggest that new genes can arise by domain swapping; however, empirical evidence has been lacking. Here we describe a set of nine independent deletion mutations that arose during selection experiments with the bacterium Pseudomonas fluorescens in which the membrane-spanning domain of a fatty acid desaturase became translationally fused to a cytosolic di-guanylate cyclase, generating an adaptive 'wrinkly spreader' phenotype. Detailed genetic analysis of one gene fusion shows that the mutant phenotype is caused by relocalization of the di-guanylate cyclase domain to the cell membrane. The relative ease by which this new gene arose, along with its functional and regulatory effects, provides a glimpse of mutational events and their consequences that are likely to have a role in the evolution of new genes.

Evolution of complex adaptations in molecular systems

A central challenge in evolutionary biology concerns the mechanisms by which complex adaptations arise. Such adaptations depend on the fixation of multiple, highly specific mutations, where intermediate stages of evolution seemingly provide little or no benefit. It is generally assumed that the establishment of complex adaptations is very slow in nature, as evolution of such traits demands special population genetic or environmental circumstances. However, blueprints of complex adaptations in molecular systems are pervasive, indicating that they can readily evolve. We discuss the prospects and limitations of non-adaptive scenarios, which assume multiple neutral or deleterious steps in the evolution of complex adaptations. Next, we examine how complex adaptations can evolve by natural selection in changing environment. Finally, we argue that molecular 'springboards', such as phenotypic heterogeneity and promiscuous interactions facilitate this process by providing access to new adaptive paths.

Synthetic Biology: Engineering Living Systems from Biophysical Principles

Synthetic biology was founded as a biophysical discipline that sought explanations for the origins of life from chemical and physical first principles. Modern synthetic biology has been reinvented as an engineering discipline to design new organisms as well as to better understand fundamental biological mechanisms. However, success is still largely limited to the laboratory and transformative applications of synthetic biology are still in their infancy. Here, we review six principles of living systems and how they compare and contrast with engineered systems. We cite specific examples from the synthetic biology literature that illustrate these principles and speculate on their implications for further study. To fully realize the promise of synthetic biology, we must be aware of life's unique properties.

Differential manipulation of arrestin-3 binding to basal and agonist-activated G protein-coupled receptors

Non-visual arrestins interact with hundreds of different G protein-coupled receptors (GPCRs). Here we show that by introducing mutations into elements that directly bind receptors, the specificity of arrestin-3 can be altered. Several mutations in the two parts of the central "crest" of the arrestin molecule, middle-loop and C-loop, enhanced or reduced arrestin-3 interactions with several GPCRs in receptor subtype and functional state-specific manner. For example, the Lys139Ile substitution in the middle-loop dramatically enhanced the binding to inactive M₂ muscarinic receptor, so that agonist activation of the M₂ did not further increase arrestin-3 binding. Thus, the Lys139Ile mutation made arrestin-3 essentially an activation-independent binding partner of M₂, whereas its interactions with other receptors, including the β₂-adrenergic receptor and the D₁ and D₂ dopamine receptors, retained normal activation dependence. In contrast, the Ala248Val mutation enhanced agonist-induced arrestin-3 binding to the β₂-adrenergic and D₂ dopamine receptors, while reducing its interaction with the D₁ dopamine receptor. These mutations represent the first example of altering arrestin specificity via enhancement of the arrestin-receptor interactions rather than selective reduction of the binding to certain subtypes.

Introduction of Premature Stop Codons as an Evolutionary Strategy To Rescue Signaling Network Function

The cellular concentrations of key components of signaling networks are tightly regulated, as deviations from their optimal ranges can have negative effects on signaling function. For example, overexpression of the yeast mating pathway mitogen-activated protein kinase (MAPK) Fus3 decreases pathway output, in part by sequestering individual components away from functional multiprotein complexes. Using a synthetic biology approach, we investigated potential mechanisms by which selection could compensate for a decrease in signaling activity caused by overexpression of Fus3. We overexpressed a library of random mutants of Fus3 and used cell sorting to select variants that rescued mating pathway activity. Our results uncovered that one remarkable way in which selection can compensate for protein overexpression is by introducing premature stop codons at permitted positions. Because of the low efficiency with which premature stop codons are read through, the resulting cellular concentration of active Fus3 returns to values within the range required for proper signaling. Our results underscore the importance of interpreting genotypic variation at the systems rather than at the individual gene level, as mutations can have opposite effects on protein and network function.

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.

Codon optimization underpins generalist parasitism in fungi

The range of hosts that parasites can infect is a key determinant of the emergence and spread of disease. Yet, the impact of host range variation on the evolution of parasite genomes remains unknown. Here, we show that codon optimization underlies genome adaptation in broad host range parasites. We found that the longer proteins encoded by broad host range fungi likely increase natural selection on codon optimization in these species. Accordingly, codon optimization correlates with host range across the fungal kingdom. At the species level, biased patterns of synonymous substitutions underpin increased codon optimization in a generalist but not a specialist fungal pathogen. Virulence genes were consistently enriched in highly codon-optimized genes of generalist but not specialist species. We conclude that codon optimization is related to the capacity of parasites to colonize multiple hosts. Our results link genome evolution and translational regulation to the long-term persistence of generalist parasitism.

Small-Molecule-Induced and Cooperative Enzyme Assembly on a 14-3-3 Scaffold

Scaffold proteins regulate cell signalling by promoting the proximity of putative interaction partners. Although they are frequently applied in cellular settings, fundamental understanding of them in terms of, amongst other factors, quantitative parameters has been lagging behind. Here we present a scaffold protein platform that is based on the native 14-3-3 dimeric protein and is controllable through the action of a small-molecule compound, thus permitting study in an in vitro setting and mathematical description. Robust small-molecule regulation of caspase-9 activity through induced dimerisation on the 14-3-3 scaffold was demonstrated. The individual parameters of this system were precisely determined and used to develop a mathematical model of the scaffolding concept. This model was used to elucidate the strong cooperativity of the enzyme activation mediated by the 14-3-3 scaffold. This work provides an entry point for the long-needed quantitative insights into scaffold protein functioning and paves the way for the optimal use of reengineered 14-3-3 proteins as chemically inducible scaffolds in synthetic systems.

Synthetic Protein Switches: Theoretical and Experimental Considerations

Synthetic protein switches with tailored response functions are finding increasing applications as tools in basic research and biotechnology. With a number of successful design strategies emerging, the construction of synthetic protein switches still frequently necessitates an integrated approach that combines detailed biochemical and biophysical characterization in combination with high-throughput screening to construct tailored synthetic protein switches. This is increasingly complemented by computational strategies that aim to reduce the need for costly empirical optimization and thus facilitate the protein design process. Successful computational design approaches range from analyzing phylogenetic data to infer useful structural, biophysical, and biochemical information to modeling the structure and function of proteins ab initio. The following chapter provides an overview over the theoretical considerations and experimental approaches that have been successful applied in the construction of synthetic protein switches.

Directed Evolution Methods to Rewire Signaling Networks

The ability to sense and process cues about changing environments is fundamental to life. Cells have evolved elaborate signaling pathways in order to respond to both internal and external stimuli appropriately. These pathways combine protein receptors, signal transducers, and effector genes in highly connected networks. The numerous interactions found between signaling proteins are essential to maintain strict regulation and produce a suitable cellular response. As a result, a signaling protein's activity in isolation can differ greatly from its activity in a native context. This is an important consideration when studying or engineering signaling pathways. Fortunately, the difficulty of studying network interactions is fading thanks to advances in library construction and cell sorting. In this chapter, we describe two methods for generating libraries of mutant proteins that exhibit altered network interactions: whole-gene point mutagenesis and domain shuffling. We then provide a protocol for using fluorescence-activated cell sorting to isolate interesting variants in live cells by focusing on the unicellular eukaryotic model organism Saccharomyces cerevisiae, using as an example recent work that we have done on its G protein-coupled receptor Ste2.

Engineering dynamical control of cell fate switching using synthetic phospho-regulons

Many cells can sense and respond to time-varying stimuli, selectively triggering changes in cell fate only in response to inputs of a particular duration or frequency. A common motif in dynamically controlled cells is a dual-timescale regulatory network: although long-term fate decisions are ultimately controlled by a slow-timescale switch (e.g., gene expression), input signals are first processed by a fast-timescale signaling layer, which is hypothesized to filter what dynamic information is efficiently relayed downstream. Directly testing the design principles of how dual-timescale circuits control dynamic sensing, however, has been challenging, because most synthetic biology methods have focused solely on rewiring transcriptional circuits, which operate at a single slow timescale. Here, we report the development of a modular approach for flexibly engineering phosphorylation circuits using designed phospho-regulon motifs. By then linking rapid phospho-feedback with slower downstream transcription-based bistable switches, we can construct synthetic dual-timescale circuits in yeast in which the triggering dynamics and the end-state properties of the ON state can be selectively tuned. These phospho-regulon tools thus open up the possibility to engineer cells with customized dynamical control.

The Die Is Cast: Precision Electrophilic Modifications Contribute to Cellular Decision Making

This perspective sets out to critically evaluate the scope of reactive electrophilic small molecules as unique chemical signal carriers in biological information transfer cascades. We consider these electrophilic cues as a new volatile cellular currency and compare them to canonical signaling circulation such as phosphate in terms of chemical properties, biological specificity, sufficiency, and necessity. The fact that nonenzymatic redox sensing properties are found in proteins undertaking varied cellular tasks suggests that electrophile signaling is a moonlighting phenomenon manifested within a privileged set of sensor proteins. The latest interrogations into these on-target electrophilic responses set forth a new horizon in the molecular mechanism of redox signal propagation wherein direct low-occupancy electrophilic modifications on a single sensor target are biologically sufficient to drive functional redox responses with precision timing. We detail how the various mechanisms through which redox signals function could contribute to their interesting phenotypic responses, including hormesis.

Ultrasensitive Negative Feedback Control: A Natural Approach for the Design of Synthetic Controllers

Many of the most important potential applications of Synthetic Biology will require the ability to design and implement high performance feedback control systems that can accurately regulate the dynamics of multiple molecular species within the cell. Here, we argue that the use of design strategies based on combining ultrasensitive response dynamics with negative feedback represents a natural approach to this problem that fully exploits the strongly nonlinear nature of cellular information processing. We propose that such feedback mechanisms can explain the adaptive responses observed in one of the most widely studied biomolecular feedback systems—the yeast osmoregulatory response network. Based on our analysis of such system, we identify strong links with a well-known branch of mathematical systems theory from the field of Control Engineering, known as Sliding Mode Control. These insights allow us to develop design guidelines that can inform the construction of feedback controllers for synthetic biological systems.

Mechanism of arginine sensing by CASTOR1 upstream of mTORC1

The mechanistic Target of Rapamycin Complex 1 (mTORC1) is a major regulator of eukaryotic growth that coordinates anabolic and catabolic cellular processes with inputs such as growth factors and nutrients, including amino acids. In mammals arginine is particularly important, promoting diverse physiological effects such as immune cell activation, insulin secretion, and muscle growth, largely mediated through activation of mTORC1 (refs 4, 5, 6, 7). Arginine activates mTORC1 upstream of the Rag family of GTPases, through either the lysosomal amino acid transporter SLC38A9 or the GATOR2-interacting Cellular Arginine Sensor for mTORC1 (CASTOR1). However, the mechanism by which the mTORC1 pathway detects and transmits this arginine signal has been elusive. Here, we present the 1.8 Å crystal structure of arginine-bound CASTOR1. Homodimeric CASTOR1 binds arginine at the interface of two Aspartate kinase, Chorismate mutase, TyrA (ACT) domains, enabling allosteric control of the adjacent GATOR2-binding site to trigger dissociation from GATOR2 and downstream activation of mTORC1. Our data reveal that CASTOR1 shares substantial structural homology with the lysine-binding regulatory domain of prokaryotic aspartate kinases, suggesting that the mTORC1 pathway exploited an ancient, amino-acid-dependent allosteric mechanism to acquire arginine sensitivity. Together, these results establish a structural basis for arginine sensing by the mTORC1 pathway and provide insights into the evolution of a mammalian nutrient sensor.

Evolution of a G protein-coupled receptor response by mutations in regulatory network interactions

All cellular functions depend on the concerted action of multiple proteins organized in complex networks. To understand how selection acts on protein networks, we used the yeast mating receptor Ste2, a pheromone-activated G protein-coupled receptor, as a model system. In Saccharomyces cerevisiae, Ste2 is a hub in a network of interactions controlling both signal transduction and signal suppression. Through laboratory evolution, we obtained 21 mutant receptors sensitive to the pheromone of a related yeast species and investigated the molecular mechanisms behind this newfound sensitivity. While some mutants show enhanced binding affinity to the foreign pheromone, others only display weakened interactions with the network's negative regulators. Importantly, the latter changes have a limited impact on overall pathway regulation, despite their considerable effect on sensitivity. Our results demonstrate that a new receptor–ligand pair can evolve through network-altering mutations independently of receptor–ligand binding, and suggest a potential role for such mutations in disease.

Co-evolution of a new receptor-ligand pair will affect the downstream signal transduction network. Here, the authors use experimental evolution of yeast mating receptor Ste2 to show the effect of enhanced binding affinity and weakened interactions with the network's negative regulators on protein evolution.

Enzyme Sequestration as a Tuning Point in Controlling Response Dynamics of Signalling Networks

Signalling networks result from combinatorial interactions among many enzymes and scaffolding proteins. These complex systems generate response dynamics that are often essential for correct decision-making in cells. Uncovering biochemical design principles that underpin such response dynamics is a prerequisite to understand evolved signalling networks and to design synthetic ones. Here, we use in silico evolution to explore the possible biochemical design space for signalling networks displaying ultrasensitive and adaptive response dynamics. By running evolutionary simulations mimicking different biochemical scenarios, we find that enzyme sequestration emerges as a key mechanism for enabling such dynamics. Inspired by these findings, and to test the role of sequestration, we design a generic, minimalist model of a signalling cycle, featuring two enzymes and a single scaffolding protein. We show that this simple system is capable of displaying both ultrasensitive and adaptive response dynamics. Furthermore, we find that tuning the concentration or kinetics of the sequestering protein can shift system dynamics between these two response types. These empirical results suggest that enzyme sequestration through scaffolding proteins is exploited by evolution to generate diverse response dynamics in signalling networks and could provide an engineering point in synthetic biology applications.

Profiling of engineering hotspots identifies an allosteric CRISPR-Cas9 switch

The CRISPR-associated protein Cas9 from Streptococcus pyogenes is an RNA-guided DNA endonuclease with widespread utility for genome modification. However, the structural constraints limiting the engineering of Cas9 have not been determined. Here we experimentally profile Cas9 using randomized insertional mutagenesis and delineate hotspots in the structure capable of tolerating insertions of a PDZ domain without disrupting the enzyme’s binding and cleavage functions. Orthogonal domains or combinations of domains can be inserted into the identified sites with minimal functional consequence. To illustrate the utility of the identified sites, we construct an allosterically regulated Cas9 by insertion of the Estrogen Receptor α Ligand Binding Domain. This protein displayed robust, ligand-dependent activation in prokaryotic and eukaryotic cells, establishing a versatile one-component system for inducible and reversible Cas9 activation. Thus, domain insertion profiling facilitates the rapid generation of new Cas9 functionalities and provides useful data for future engineering of Cas9.

BioJazz: in silico evolution of cellular networks with unbounded complexity using rule-based modeling

Systems biologists aim to decipher the structure and dynamics of signaling and regulatory networks underpinning cellular responses; synthetic biologists can use this insight to alter existing networks or engineer de novo ones. Both tasks will benefit from an understanding of which structural and dynamic features of networks can emerge from evolutionary processes, through which intermediary steps these arise, and whether they embody general design principles. As natural evolution at the level of network dynamics is difficult to study, in silico evolution of network models can provide important insights. However, current tools used for in silico evolution of network dynamics are limited to ad hoc computer simulations and models. Here we introduce BioJazz, an extendable, user-friendly tool for simulating the evolution of dynamic biochemical networks. Unlike previous tools for in silico evolution, BioJazz allows for the evolution of cellular networks with unbounded complexity by combining rule-based modeling with an encoding of networks that is akin to a genome. We show that BioJazz can be used to implement biologically realistic selective pressures and allows exploration of the space of network architectures and dynamics that implement prescribed physiological functions. BioJazz is provided as an open-source tool to facilitate its further development and use. Source code and user manuals are available at: http://oss-lab.github.io/biojazz and http://osslab.lifesci.warwick.ac.uk/BioJazz.aspx.

Evolution of synthetic signaling scaffolds by recombination of modular protein domains

Signaling scaffolds are proteins that interact via modular domains with multiple partners, regulating signaling networks in space and time and providing an ideal platform from which to alter signaling functions. However, to better exploit scaffolds for signaling engineering, it is necessary to understand the full extent of their modularity. We used a directed evolution approach to identify, from a large library of randomly shuffled protein interaction domains, variants capable of rescuing the signaling defect of a yeast strain in which Ste5, the scaffold in the mating pathway, had been deleted. After a single round of selection, we identified multiple synthetic scaffold variants with diverse domain architectures, able to mediate mating pathway activation in a pheromone-dependent manner. The facility with which this signaling network accommodates changes in scaffold architecture suggests that the mating signaling complex does not possess a single, precisely defined geometry into which the scaffold has to fit. These relaxed geometric constraints may facilitate the evolution of signaling networks, as well as their engineering for applications in synthetic biology.

Function-selective domain architecture plasticity potentials in eukaryotic genome evolution

To help evaluate how protein function impacts on genome evolution, we introduce a new concept of ‘architecture plasticity potential’ – the capacity to form distinct domain architectures – both for an individual domain, or more generally for a set of domains grouped by shared function. We devise a scoring metric to measure the plasticity potential for these domain sets, and evaluate how function has changed over time for different species. Applying this metric to a phylogenetic tree of eukaryotic genomes, we find that the involvement of each function is not random but highly selective. For certain lineages there is strong bias for evolution to involve domains related to certain functions. In general eukaryotic genomes, particularly animals, expand complex functional activities such as signalling and regulation, but at the cost of reducing metabolic processes. We also observe differential evolution of transcriptional regulation and a unique evolutionary role of channel regulators; crucially this is only observable in terms of the architecture plasticity potential. Our findings provide a new layer of information to understand the significance of function in eukaryotic genome evolution. A web search tool, available at http://supfam.org/Pevo, offers a wide spectrum of options for exploring functional importance in eukaryotic genome evolution.

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A new concept to measure domain architecture plasticity potential in a genome.

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We reveal the function-selective role in eukaryotic genome evolution.

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Eukaryotic genomes expand signalling and regulations but reduce metabolism.

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We observe differential evolution between trans- and cis-acting regulations.

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We observe a unique role of channel regulators in separating eukaryotic kingdoms.

The robustness of a signaling complex to domain rearrangements facilitates network evolution

The broad tolerance of domain-rearranging mutations by a yeast signaling network suggests that signaling complexes have loose spatial constraints, making manipulation and perhaps evolution easier.

The rearrangement of protein domains is known to have key roles in the evolution of signaling networks and, consequently, is a major tool used to synthetically rewire networks. However, natural mutational events leading to the creation of proteins with novel domain combinations, such as in frame fusions followed by domain loss, retrotranspositions, or translocations, to name a few, often simultaneously replace pre-existing genes. Thus, while proteins with new domain combinations may establish novel network connections, it is not clear how the concomitant deletions are tolerated. We investigated the mechanisms that enable signaling networks to tolerate domain rearrangement-mediated gene replacements. Using as a model system the yeast mitogen activated protein kinase (MAPK)-mediated mating pathway, we analyzed 92 domain-rearrangement events affecting 11 genes. Our results indicate that, while domain rearrangement events that result in the loss of catalytic activities within the signaling complex are not tolerated, domain rearrangements can drastically alter protein interactions without impairing function. This suggests that signaling complexes can maintain function even when some components are recruited to alternative sites within the complex. Furthermore, we also found that the ability of the complex to tolerate changes in interaction partners does not depend on long disordered linkers that often connect domains. Taken together, our results suggest that some signaling complexes are dynamic ensembles with loose spatial constraints that could be easily re-shaped by evolution and, therefore, are ideal targets for cellular engineering.

Cells use complex protein interaction networks to sense and process external signals. Proteins involved in signaling are often composed of multiple functional units called domains. Because domains are modular, mutations that rearrange domains among proteins have the potential to result in the creation of novel proteins with altered functions. At an evolutionary timescale, domain rearrangements contribute to the functional diversification of signaling networks; at the shorter timescale of the life of an individual, domain rearrangements can impair cellular functions and lead to disease. Here, we investigated how domain-rearranging mutations alter the function of signaling networks, in particular when these mutations disrupt pre-existing proteins. We used as a model system the yeast mating signaling pathway, which shares many properties with more complex pathways active in human cells. Our results demonstrate that signaling networks are often robust to domain rearrangements that disrupt pre-existing genes. In addition, our experiments suggest a possible mechanism to explain this robustness: rather than being a rigid multi-protein machine, the yeast mating signaling complex is a dynamic ensemble with loose spatial constraints. Because of this, the changes in protein interaction partners caused by domain-rearrangement mutations can be accommodated without disrupting network function.

Protease-based synthetic sensing and signal amplification

The bottom-up design of protein-based signaling networks is a key goal of synthetic biology; yet, it remains elusive due to our inability to tailor-make signal transducers and receptors that can be readily compiled into defined signaling networks. Here, we report a generic approach for the construction of protein-based molecular switches based on artficially autoinhibited proteases. Using structure-guided design and directed protein evolution, we created signal transducers based on artificially autoinhibited proteases that can be activated following site-specific proteolysis and also demonstrate the modular design of an allosterically regulated protease receptor following recombination with an affinity clamp peptide receptor. Notably, the receptor's mode of action can be varied from >5-fold switch-OFF to >30-fold switch-ON solely by changing the length of the connecting linkers, demonstrating a high functional plasticity not previously observed in naturally occurring receptor systems. We also create an integrated signaling circuit based on two orthogonal autoinhibited protease units that can propagate and amplify molecular queues generated by the protease receptor. Finally, we present a generic two-component receptor architecture based on proximity-based activation of two autoinhibited proteases. Overall, the approach allows the design of protease-based signaling networks that, in principle, can be connected to any biological process.