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Energy landscapes can provide intuitive depictions of population heterogeneity and dynamics. However, it is unclear whether individual cell behavior, hypothesized to be determined by initial position and noise, is faithfully recapitulated. Using the p21-/Cdk2-dependent quiescence-proliferation decision in breast cancer dormancy as a testbed, we examined single-cell dynamics on the landscape when perturbed by hypoxia, a dormancy-inducing stress. Combining trajectory-based energy landscape generation with single-cell time-lapse microscopy, we found that a combination of initial position and velocity on a p21/Cdk2 landscape, but not position alone, was required to explain the observed cell fate heterogeneity under hypoxia. This is likely due to additional cell state information such as epigenetic features and/or other species encoded in velocity but missing in instantaneous position determined by p21 and Cdk2 levels alone. Here, velocity dependence manifested as inertia: cells with higher cell cycle velocities prior to hypoxia continued progressing along the cell cycle under hypoxia, resisting the change in landscape towards cell cycle exit. Such inertial effects may markedly influence cell fate trajectories in tumors and other dynamically changing microenvironments where cell state transitions are governed by coordination across several biochemical species., (© 2024. The Author(s).)

A limited number of accessible and representative models of human trophoblast cells currently exist for the study of placentation. Current stem cell models involve either a transition through a naïve stem cell state or precise dynamic control of multiple growth factors and small-molecule cues. Here, we demonstrated that a simple five-day treatment of human induced pluripotent stem cells with two small molecules, retinoic acid (RA) and Wnt agonist CHIR 99021 (CHIR), resulted in rapid, synergistic upregulation of CDX2. Transcriptomic analysis of RA + CHIR-treated cells showed high similarity to primary trophectoderm cells. Multipotency was verified via further differentiation towards cells with syncytiotrophoblast or extravillous trophoblast features. RA + CHIR-treated cells were also assessed for the established criteria defining a trophoblast cell model, and they possess all the features necessary to be considered valid. Collectively, our data demonstrate a facile, scalable method for generating functional trophoblast-like cells in vitro to better understand the placenta., (© 2024. The Author(s).)

In the era of precision medicine, multivalent and multispecific therapeutics present a promising approach for targeted disease intervention. These therapeutics are designed to interact with multiple targets simultaneously, promising enhanced efficacy, reduced side effects, and resilience against drug resistance. We dissect the principles guiding the design of multivalent biologics, highlighting challenges and strategies that must be considered to maximize therapeutic effect. Engineerable elements in multivalent and multispecific biologic design-domain affinities, valency, and spatial presentation-must be considered in the context of the molecular targets as well as the balance of important properties such as target avidity and specificity. We illuminate recent applications of these principles in designing protein and cell therapies and identify exciting future directions in this field, underscored by advances in biomolecular and cellular engineering and computational approaches. Expected final online publication date for the Annual Review of Chemical and Biomolecular Engineering , Volume 15 is June 2024. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Low-affinity protein binders are emerging as valuable domains for therapeutic applications because of their higher specificity when presented in multivalent ligands that increase the overall strength and selectivity of receptor binding. De novo discovery of low-affinity binders would be enhanced by the large library sizes attainable with in vitro selection systems, but these platforms generally maximize recovery of high-affinity monovalent binders. Here, we present a facile technology that uses rolling circle amplification to create homomultivalent libraries. We show proof of principle of this approach in ribosome display with off-rate selections of a bivalent ligand against monovalent and bivalent targets, thereby demonstrating high enrichment (up to 166-fold) against a low-affinity target that is bivalent but not monovalent. This approach to homomultivalent library construction can be applied to any binder tolerant of N- and C-terminal fusions and provides a platform for performing in vitro display selections with controlled protein valency and orientation.

Arising through multiple binding elements, multivalency can specify the avidity, duration, cooperativity, and selectivity of biomolecular interactions, but quantitative prediction and design of these properties has remained challenging. Here we present MVsim, an application suite built around a configurational network model of multivalency to facilitate the quantification, design, and mechanistic evaluation of multivalent binding phenomena through a simple graphical user interface. To demonstrate the utility and versatility of MVsim, we first show that both monospecific and multispecific multivalent ligand-receptor interactions, with their noncanonical binding kinetics, can be accurately simulated. Further, to illustrate the conceptual insights into multivalent systems that MVsim can provide, we apply it to quantitatively predict the ultrasensitivity and performance of multivalent-encoded protein logic gates, evaluate the inherent programmability of multispecificity for selective receptor targeting, and extract rate constants of conformational switching for the SARS-CoV-2 spike protein and model its binding to ACE2 as well as multivalent inhibitors of this interaction. MVsim and instructional tutorials are freely available at https://sarkarlab.github.io/MVsim/ ., (© 2022. The Author(s).)

Site-specific recombination (SSR) is an important tool in synthetic biology, but its applications are limited by the inability to predictably tune SSR reaction rates. Facile rate manipulation could be achieved by modifying the DNA substrate sequence; however, this approach lacks rational design principles. Here, we develop an integrated experimental and computational method to engineer the DNA attachment sequence attP for predictably modulating the inversion reaction mediated by the recombinase Bxb1. After developing a qPCR method to measure SSR reaction rate, we design, select, and sequence attP libraries to inform a machine-learning model that computes Bxb1 inversion rate as a function of attP sequence. We use this model to predict reaction rates of attP variants in vitro and demonstrate their utility in gene circuit design in Escherichia coli. Our high-throughput, model-guided approach for rationally tuning SSR reaction rates enhances our understanding of recombinase function and expands the synthetic biology toolbox., (© 2022. The Author(s).)

Sea lamprey immunization can yield leucine-rich repeat (LRR) protein binders analogous to globular antibodies developed from mammals. A novel minimal LRR was discovered through lamprey immunization with human immunoglobulin G Fc domain (IgG Fc). Initial attempts to solubly express this LRR protein, VLRB.IgGFc, in Escherichia coli proved challenging, so it was analyzed using the cell-free method ribosome display. In ribosome display, VLRB.IgGFc was found to bind specifically to the Fc domain of IgG, with little observed cross-reactivity to IgA or IgM. The minimal repeat protein architecture of VLRB.IgGFc may facilitate modular LRR extensions to incorporate additional or augmented functionality within a continuous, structurally defined scaffold. We exploited this modularity to design a chimera of a well-characterized, soluble LRR repebody and the initially insoluble VLRB.IgGFc to produce soluble Repe-VLRB.IgGFc. The minimal IgG Fc-binding module, Repe-VLRB.IgGFc, and future-engineered variants thereof should be useful additions to the biotechnological toolbox for detecting, purifying, or targeting IgGs. More generally, this two-step approach of minimal LRR binder discovery via sea lamprey immunization followed by modular augmentation of functionality may be of general utility in protein engineering., (© 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Plant immune receptors are often difficult to express heterologously, hindering study of direct interactions between these receptors and their targets with traditional biochemical approaches. The cell-free method ribosome display (RD) enables expression of such recalcitrant proteins by keeping each nascent polypeptide chain tethered to its ribosome, which can enhance protein folding by virtue of its size and solubility. Moreover, in contrast to an in planta readout of receptor activity such as a hypersensitive response that conflates binding and signaling, RD enables direct probing of the interaction between plant immune receptors and their targets. Here, we demonstrate the utility of this approach using tomato recognition of Trichoderma viride ethylene-inducing xylanase (EIX) as a case study. Leveraging the modular nature of the tomato LeEIX2 and LeEIX1 leucine-rich repeat (LRR) receptors, we applied an entropy-informed algorithm to maximize the information content in our receptor segmentation RD experiments to identify segments implicated in EIX binding. Unexpectedly, two distinct EIX-binding hotspots were discovered on LeEIX2 and both hotspots are shared with decoy LeEIX1, suggesting that their contrasting receptor functions are not due to differential modes of ligand binding. Given that most plant immune receptors are thought to engage targets via their LRR sequences, this approach should be of broad utility in rapidly identifying their binding hotspots., (© 2022. The Author(s).)

Multistability and natural biological variability can result in significant heterogeneity within a cell population, leading to challenges in understanding and modulating cell behavior. Energy landscapes can offer qualitatively intuitive visualizations of cell phenotype and facilitate a more quantitative understanding of cellular dynamics, but current methods for landscape generation are mathematically involved and often require specific system properties (e.g., ergodicity or independent gene/protein probability distributions) that do not always hold. Here, we present a simple kinetic Monte Carlo-based method for landscape generation from a system of ordinary differential equations using only simulation trajectories initialized throughout the phase space of interest. The resulting landscape produces three quantitative features relevant to understanding cell behavior: stability (reflected by the depth or potential of landscape valleys), velocity (representing average directional movement on the landscape), and variance in velocity (indicative of landscape positions with heterogeneous movements). We applied this method to a genetic toggle switch, a core decision-making network in binary cellular responses, to elucidate effects of biologically relevant intrinsic and extrinsic cues. Intrinsic noise, such as stochasticity in transcription-translation and differences in cell cycle position, manifests through changes in valley width and position, reflecting increased population heterogeneity and more probabilistic cell fate transitions. The landscapes also capture the effect of an external inducer, revealing a quantitative correlation between the rate of cell fate transition and the energy barrier above a threshold inducer concentration determined by the permissivity of the valley. Further, in tracking dynamically changing landscapes under time-varying external cues, we unexpectedly found that an oscillatory inducer input can modulate cell fate heterogeneity and lead to periodic cell fate transitions entrained to the input frequency, depending on the intrinsic degradation rate of the switch. The landscape generation approach outlined herein is generalizable to other network topologies and may provide new quantitative insights into their dynamics., (Copyright © 2021 Biophysical Society. Published by Elsevier Inc. All rights reserved.)

Protein multivalency can provide increased affinity and specificity relative to monovalent counterparts, but these emergent biochemical properties and their mechanistic underpinnings are difficult to predict as a function of the biophysical properties of the multivalent binding partners. Here, we present a mathematical model that accurately simulates binding kinetics and equilibria of multivalent protein-protein interactions as a function of the kinetics of monomer-monomer binding, the structure and topology of the multidomain interacting partners, and the valency of each partner. These properties are all experimentally or computationally estimated a priori, including approximating topology with a worm-like chain model applicable to a variety of structurally disparate systems, thus making the model predictive without parameter fitting. We conceptualize multivalent binding as a protein-protein interaction network: ligand and receptor valencies determine the number of interacting species in the network, with monomer kinetics and structural properties dictating the dynamics of each species. As predicted by the model and validated by surface plasmon resonance experiments, multivalent interactions can generate several noncanonical macroscopic binding dynamics, including a transient burst of high-energy configurations during association, biphasic equilibria resulting from interligand competition at high concentrations, and multiexponential dissociation arising from differential lifetimes of distinct network species. The transient burst was only uncovered when extending our analysis to trivalent interactions due to the significantly larger network, and we were able to predictably tune burst magnitude by altering linker rigidity. This study elucidates mechanisms of multivalent binding and establishes a framework for model-guided analysis and engineering of such interactions., Competing Interests: The authors declare no competing interest.

Background: Modules of interacting components arranged in specific network topologies have evolved to perform a diverse array of cellular functions. For a network with a constant topological structure, its function within a cell may still be tuned by changing the number of instances of a particular component (e.g., gene copy number) or by modulating the intrinsic biochemical properties of a component (e.g., binding strength or catalytic efficiency). How such perturbations affect cellular response dynamics remains poorly understood. Here, we explored these effects in a common decision-making motif, cross-antagonism with autoregulation, by synthetically constructing this network in yeast., Results: We employed the engineering design strategy of reuse to build this topology with a single protein building block, TetR, creating necessary components through TetR mutations and fusion partners. We then studied the impact of several topology-preserving perturbations - strength of cross-antagonism, number of operator sites in a promoter, and gene dosage - on decision-making behavior. We found that reducing TetR repression strength, which hinders cross-antagonism, resulted in a loss of mutually exclusive cell responses. Unexpectedly, increasing the number of operator sites also impeded decision-making exclusivity, which may be a consequence of the averaging effect that arises when multiple transcriptional activators and repressors are accommodated at a given locus. Stochastic simulations of this topology revealed that, even for networks with high TetR repression strength and a low number of operator sites, increasing gene dosage can reduce exclusivity in response dynamics. We further demonstrated this result experimentally by quantifying gene copy numbers in selected yeast clones with differing phenotypic responses., Conclusions: Our study illustrates how parameters that do not change the topological structure of a decision-making network can nonetheless exert significant influence on its response dynamics. These findings should further inform the study of native motifs, including the effects of topology-preserving mutations, and the robust engineering of synthetic networks.

Cells have traditionally been characterized using expression levels of a few proteins that are thought to specify phenotype. This requires a priori selection of proteins, which can introduce descriptor bias, and neglects the wealth of additional molecular information nested within each cell in a population, which often makes these sparse descriptors qualitative. Recently, more unbiased and quantitative cell characterization has been made possible by new high-throughput, information-dense experimental approaches and data-driven computational methods. This review discusses such quantitative descriptors in the context of three central concepts of cell identity: definition, creation, and stability. Collectively, these concepts are essential for constructing quantitative phenotypic landscapes, which will enhance our understanding of cell biology and facilitate cell engineering for research and clinical applications., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Cell-free synthetic biology approaches enable engineering of biomolecular systems exhibiting complex, cell-like behaviors in the absence of living entities. Often essential to these systems are user-controllable mechanisms to regulate gene expression. Here we describe synthetic RNA thermometers that enable temperature-dependent translation in the PURExpress in vitro protein synthesis system. Previously described cellular thermometers lie wholly in the 5' untranslated region and do not retain their intended function in PURExpress. By contrast, we designed hairpins between the Shine-Dalgarno sequence and complementary sequences within the gene of interest. The resulting thermometers enable high-yield, cell-free protein expression in an inducible temperature range compatible with in vitro translation systems (30-37 °C). Moreover, expression efficiency and switching behavior are tunable via small variations to the coding sequence. Our approach and resulting thermometers provide new tools for exploiting temperature as a rapid, external trigger for in vitro gene regulation.

Mercury is a highly toxic heavy metal and the ability of the neurotoxin methylmercury to biomagnify in the food chain is a serious concern for both public and environmental health globally. Because thousands of tons of mercury are released into the environment each year, remediation strategies are urgently needed and prompted this study. To facilitate remediation of both organic and inorganic forms of mercury, Escherichia coli was engineered to harbor a subset of genes (merRTPAB) from the mercury resistance operon. Protein products of the mer operon enable transport of mercury into the cell, cleavage of organic C-Hg bonds, and subsequent reduction of ionic mercury to the less toxic elemental form, Hg(0). E. coli containing merRTPAB was then encapsulated in silica beads resulting in a biological-based filtration material. Performing encapsulation in aerated mineral oil yielded silica beads that were smooth, spherical, and similar in diameter. Following encapsulation, E. coli containing merRTPAB retained the ability to degrade methylmercury and performed similarly to non-encapsulated cells. Due to the versatility of both the engineered mercury resistant strain and silica bead technology, this study provides a strong foundation for use of the resulting biological-based filtration material for methylmercury remediation.

Hematopoietic lineage commitment is regulated by cytokines and master transcription factors, but it remains unclear how a progenitor cell chooses a lineage in the face of conflicting cues. Through transcript counting in megakaryocyte-erythroid progenitors undergoing erythropoiesis, we show that the expression levels of the pro-erythropoiesis transcription factor EKLF (also known as KLF1) and receptor EpoR are inversely correlated with their pro-megakaryopoiesis counterparts, FLI-1 and TpoR (also known as MPL). Notably, as progenitors commit to the erythrocyte lineage, EpoR is upregulated and TpoR is strongly downregulated, thus boosting the potency of the pro-erythropoiesis cue erythropoietin and effectively eliminating the activity of the pro-megakaryopoiesis cue thrombopoietin. Based on these findings, we propose a new model for exclusive decision making that explicitly incorporates signals from extrinsic cues, and we experimentally confirm a model prediction of temporal changes in transcript noise levels in committing progenitors. Our study suggests that lineage-specific receptor levels can modulate potencies of cues to achieve robust commitment decisions., (© 2015. Published by The Company of Biologists Ltd.)

Although cell-free directed evolution methods have been used to engineer proteins for nearly two decades, selections on more complex phenotypes have largely remained in the domain of cell-based engineering approaches. Here, we review recent conceptual advances that now enable in vitro display of multimeric proteins, integral membrane proteins, and proteins with an expanded amino acid repertoire. Additionally, we discuss methodological improvements that have enhanced the accessibility, efficiency, and robustness of cell-free approaches. Coupling these advances with the in vitro advantages of creating exceptionally large libraries and precisely controlling all experimental conditions, cell-free directed evolution is poised to contribute significantly to our understanding and engineering of more complex protein phenotypes., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

The inability to rationally design and construct circuits that robustly enable complex behaviors is perhaps the most fundamental challenge in synthetic biology. While systems modeling can aid this process and help reduce the space of design strategies, the unavailability and dynamic variability of kinetic parameters limits the utility of such models. Here, we present a general approach that employs an exhaustive enumeration of network architectures to suggest topologies that robustly enable a desired behavior.

By delivering payloads in response to specific exogenous stimuli, smart bacterial therapeutics have the potential to overcome many limitations of conventional therapies, including poor targeting specificity and dosage control in current cancer treatments. Although not yet explored as a trigger for bacterial drug delivery, light is an ideal induction mechanism because it offers fine spatiotemporal control and is easily and safely administered. Using recent advances in optogenetics, we have engineered two strains of Escherichia coli to secrete a potent mammalian cytotoxin in response to blue or red light. The tools in this study demonstrate the initial feasibility of light-activated bacterial therapeutics for applications such as tumor cytolysis, and their modular nature should enable simple substitution of other payloads of interest.

Granulocyte colony-stimulating factor (GCSF) drives the production of myeloid progenitor and precursor cells toward neutrophils via the GCSF receptor (GCSFR, gene name CSF3R). Children with severe congenital neutropenia chronically receive pharmacologic doses of GCSF, and ∼30% will develop myelodysplasia/acute myeloid leukemia (AML) associated with GCSFR truncation mutations. In addition to mutations, multiple isoforms of CSF3R have also been reported. We found elevated expression of the alternatively spliced isoform, class IV CSF3R in adult myelodysplastic syndrome/AML patients. Aside from its association with monosomy 7 and higher rates of relapse in pediatric AML patients, little is known about the biology of the class IV isoform. We found developmental regulation of CSF3R isoforms with the class IV expression more representative of a progenitor cell stage. Striking differences were found in phosphoprotein signaling involving Janus kinase (JAK)-signal transducer and activator of transcription (STAT) and cell cycle gene expression. Enhanced proliferation by class IV GCSFR was associated with diminished STAT3 and STAT5 activation, yet showed sensitivity to JAK2 inhibitors. Alterations in the C-terminal domain of the GCSFR result in leukemic properties of enhanced growth, impaired differentiation and resistance to apoptosis, suggesting that they can behave as oncogenic drivers, sensitive to JAK2 inhibition.

High-efficiency DNA ligation is vital for many molecular biology experiments, and it is best achieved using reactants with non-palindromic sticky ends to maximize specificity. However, optimizing such multi-parametric ligation reactions often involves extensive trial and error. We have developed a freely available Web-based ligation calculator, NP-Sticky (http://sarkarlab.umn.edu/npsticky/), that predicts product distribution for given reactant concentrations, thus enabling straightforward computational optimization of these reactions. Built-in schemes include two-piece and three-piece linear ligation, as well as insert-vector circular ligation. The only parameters needed for the underlying thermodynamic model are the free energies of ligation for each sticky end, which can be estimated by the calculator from the overhang sequences or provided by the user from direct experimental measurement. Free energies of sticky-end mismatches are also calculated for determining the extent of byproduct formation. This ligation calculator allows rapid identification of the optimal conditions for maximizing incorporation, efficiency, and/or accuracy, based on specific needs., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

While the ribosome has evolved to function in complex intracellular environments, these contexts do not easily allow for the study of its inherent capabilities. We have used a synthetic, well-defined Escherichia coli (E. coli)-based translation system in conjunction with ribosome display, a powerful in vitro selection method, to identify ribosome binding sites (RBSs) that can promote the efficient translation of messenger RNAs (mRNAs) with a leader length representative of natural E. coli mRNAs. In previous work, we used a longer leader sequence and unexpectedly recovered highly efficient cytosine-rich sequences with complementarity to the 16S ribosomal RNA (rRNA) and similarity to eukaryotic RBSs. In the current study, Shine-Dalgarno (SD) sequences were prevalent, but non-SD sequences were also heavily enriched and were dominated by novel guanine- and uracil-rich motifs that showed statistically significant complementarity to the 16S rRNA. Additionally, only SD motifs exhibited position-dependent decreases in sequence entropy, indicating that non-SD motifs likely operate by increasing the local concentration of ribosomes in the vicinity of the start codon, rather than by a position-dependent mechanism. These results further support the putative generality of mRNA-rRNA complementarity in facilitating mRNA translation but also suggest that context (e.g., leader length and composition) dictates the specific subset of possible RBSs that are used for efficient translation of a given transcript.

Glycans anchored to residue N297 of the antibody IgG Fc domain are critical in mediating binding toward FcγRs to direct both adaptive and innate immune responses. However, using a full length bacterial IgG display system, we have isolated aglycosylated Fc domains with mutations that confer up to a 160-fold increase in the affinity toward the low affinity FcγRIIa-R131 allele as well as high selectivity against binding to the remarkably homologous human inhibitory receptor, FcγRIIb. The mutant Fc domain (AglycoT-Fc1004) contained a total of 5 amino acid substitutions that conferred an activating to inhibitory ratio of 25 (A/I ratio; FcyRIIa-R131:FcγRIIb). Incorporation of this engineered Fc into trastuzumab, an anti-Her2 antibody, resulted in a 75% increase in tumor cell phagocytosis by macrophages compared to that of the parental glycosylated trastuzumab with both medium and low Her2-expressing cancer cells. A mathematical model has been developed to help explain how receptor affinity and the A/I ratio relate to improved antibody dependent cell-mediated phagocytosis. Our model provides guidelines for the future engineering of Fc domains with enhanced effector function.

mRNA display is a powerful method for in vitro directed evolution of polypeptides, but its time-consuming, technically demanding nature has hindered its widespread use. We present a streamlined protocol in which lengthy mRNA purification steps are replaced with faster precipitation and ultrafiltration alternatives; additionally, other purification steps are entirely eliminated by using a reconstituted translation system and by performing reverse transcription after selection, which also protects input polypeptides from thermal denaturation. We tested this procedure by performing affinity selection against Her2 using binary libraries containing a nonspecific designed ankyrin repeat protein (DARPin) doped with a Her2-binding DARPin (dopant fraction ranging from 1:10 to 1:10 000). The Her2-binding DARPin was recovered in all cases, with an enrichment factor of up to 2 orders of magnitude per selection round. The time required for 1 round is reduced from ∼4-7 days to 2 days with our protocol, thus simplifying and accelerating mRNA display experiments.

Lactococcus lactis is an attractive vehicle for biotechnological production of proteins and clinical delivery of therapeutics. In many such applications using this host, it is desirable to maximize secretion of recombinant proteins into the extracellular space, which is typically achieved by using the native signal peptide from a major secreted lactococcal protein, Usp45. In order to further increase protein secretion from L. lactis, inherent limitations of the Usp45 signal peptide (Usp45sp) must be elucidated. Here, we performed extensive mutagenesis on Usp45sp to probe the effects of both the mRNA sequence (silent mutations) and the peptide sequence (amino acid substitutions) on secretion. We screened signal peptides based on their resulting secretion levels of Staphylococcus aureus nuclease and further evaluated them for secretion of Bacillus subtilis α-amylase. Silent mutations alone gave an increase of up to 16% in the secretion of α-amylase through a mechanism consistent with relaxed mRNA folding around the ribosome binding site and enhanced translation. Targeted amino acid mutagenesis in Usp45sp, combined with additional silent mutations from the best clone in the initial screen, yielded an increase of up to 51% in maximum secretion of α-amylase while maintaining secretion at lower induction levels. The best sequence from our screen preserves the tripartite structure of the native signal peptide but increases the positive charge of the n-region. Our study presents the first example of an engineered L. lactis signal peptide with a higher secretion yield than Usp45sp and, more generally, provides strategies for further enhancing protein secretion in bacterial hosts.

Signaling pathways lie at the heart of cellular responses to environmental cues. The ability to reconstruct specific signaling modules ex vivo allows us to study their inherent properties in an isolated environment, which in turn enables us to elucidate fundamental design principles for such motifs. This synthetic biology approach for analyzing natural, well-defined signaling modules will help to bridge the gap between studies on isolated biochemical reactions-which can provide great mechanistic detail but do not capture the complexity of endogenous signaling pathways-and those on entire networks of protein interactions-which offer a systems-level view of signal transduction but obscure the mechanisms that underlie signal transmission and processing. Additionally, minimal signaling modules can be tractably engineered to predictably alter cellular responses, opening up possibilities for creating biotechnologically and biomedically useful cellular devices., (Copyright © 2012 Elsevier Ltd. All rights reserved.)

DNA ligation is essential to many molecular biology manipulations, but this reaction is often carried out by following generic guidelines or by trial and error. Maximizing the desired ligation product is especially important in DNA library construction for directed evolution experiments since library diversity is directly affected by ligation efficiency. Here, we suggest that display vectors that rely on Type IIP restriction sites for cloning should be redesigned to utilize Type IIS restriction sites instead because ligation yield is significantly improved: we observed up to 15- and 2.6-fold increases in desired products for circular and linear ligation reactions, respectively. To guide ligation optimization more rationally, we developed an easily parameterized thermodynamic model that predicts product distributions based on input DNA concentrations and free energies of the ligation events. We applied this model to study ligation reactions using a ribosome display vector redesigned with Type IIS restriction sites (pRDV2). We computationally predicted and experimentally validated the relative abundance of various products in three-piece linear ligations as well as the extent of transformation from vector-insert circular ligations. Based on our results, we provide general insights into ligation and we outline guidelines for optimizing this reaction for both in vivo and in vitro display methodologies.

Progenitor cells within a clonal population show variable proclivity toward lineage commitment and differentiation. This cell-to-cell variability has been attributed to transcriptome-wide gene expression noise generated by fluctuations in the amount of cellular machinery and stochasticity in the biochemical reactions involved in protein synthesis. It therefore remains unclear how a signaling network, in the presence of such noise, can execute unequivocal cell-fate decisions from external cues. Here, we use mathematical modeling and model-guided experiments to reveal functional interplay between instructive signaling and noise in erythropoiesis. We present evidence that positive transcriptional feedback loops in a lineage-specific receptor signaling pathway can generate ligand-induced memory to engender robust, switch-like responses. These same feedback loops can also transiently amplify gene expression noise in the signaling network, suggesting that external cues can actually bias seemingly stochastic decisions during cell-fate specification. Gene expression levels among key effectors in the signaling pathway are uncorrelated in the initial population of progenitor cells but become synchronized after addition of ligand, which activates the transcriptional feedback loops. Finally, we show that this transient noise amplification and gene expression synchronization induced by ligand can directly influence cell survival and differentiation kinetics within the population., (Copyright © 2012 The Authors. Published by Elsevier Inc. All rights reserved.)

Studies of synthetic, well-defined biomolecular systems can elucidate inherent capabilities that may be difficult to uncover in a native biological context. Here, we used a minimal, reconstituted translation system from Escherichia coli to identify efficient ribosome binding sites (RBSs) in an unbiased, high-throughput manner. We applied ribosome display, a powerful in vitro selection method, to enrich only those mRNA sequences which could direct rapid protein translation. In addition to canonical Shine-Dalgarno (SD) motifs, we unexpectedly recovered highly efficient cytosine-rich (C-rich) sequences that exhibit unmistakable complementarity to the 16S rRNA of the small subunit of the ribosome, indicating that broad-specificity base-pairing may be an inherent, general mechanism for efficient translation. Furthermore, given the conservation of ribosomal structure and function across species, the broader relevance of C-rich RBS sequences identified through our in vitro evolution approach is supported by multiple, diverse examples in nature, including C-rich RBSs in several bacteriophage and plants, a poly-C consensus before the start codon in a lower eukaryote, and Kozak-like sequences in vertebrates., Competing Interests: The authors have declared that no competing interests exist.

Oral delivery of insulin to diabetic patients is highly desirable because it would be non-invasive and more closely mimic normal physiology, but this route of administration typically results in low bioavailability due to low pH and enzymatic degradation along the gastrointestinal tract. To explore an alternative approach that may mitigate these obstacles and also facilitate local synthesis of new therapeutic protein molecules in the small intestine, we engineered the food-grade bacterium Lactococcus lactis (NZ9000) for nisin-inducible expression and secretion of a bioactive single-chain insulin (SCI) analog, SCI-57. We show that the addition of nisin during early-log phase has a modest inhibitory effect on cell growth but induction during mid-log phase has a negligible impact on proliferation, suggesting a tradeoff between cell growth rate and duration of induction. We find that a signal peptide such as usp45 is necessary for secretion of SCI-57 into the medium; furthermore, we demonstrate that this secreted SCI-57 is biologically active, as assessed by the ability of conditioned L. lactis medium to stimulate Akt signaling in differentiated 3T3-L1 adipocytes. Finally, we show that the biological activity of SCI-57 was enhanced by near-neutral or slightly alkaline pH during induction, which is comparable to the pH in the small intestine, and by removal of a C-terminal purification tag. This study demonstrates that food-grade bacteria can be engineered to secrete bioactive insulin analogs and opens up the possibility of oral insulin delivery using live microorganisms., (Copyright © 2011 Wiley Periodicals, Inc.)

Signaling networks that convert graded stimuli into binary, all-or-none cellular responses are critical in processes ranging from cell-cycle control to lineage commitment. To exhaustively enumerate topologies that exhibit this switch-like behavior, we simulated all possible two- and three-component networks on random parameter sets, and assessed the resulting response profiles for both steepness (ultrasensitivity) and extent of memory (bistability). Simulations were used to study purely enzymatic networks, purely transcriptional networks, and hybrid enzymatic/transcriptional networks, and the topologies in each class were rank ordered by parametric robustness (i.e., the percentage of applied parameter sets exhibiting ultrasensitivity or bistability). Results reveal that the distribution of network robustness is highly skewed, with the most robust topologies clustering into a small number of motifs. Hybrid networks are the most robust in generating ultrasensitivity (up to 28%) and bistability (up to 18%); strikingly, a purely transcriptional framework is the most fragile in generating either ultrasensitive (up to 3%) or bistable (up to 1%) responses. The disparity in robustness among the network classes is due in part to zero-order ultrasensitivity, an enzyme-specific phenomenon, which repeatedly emerges as a particularly robust mechanism for generating nonlinearity and can act as a building block for switch-like responses. We also highlight experimentally studied examples of topologies enabling switching behavior, in both native and synthetic systems, that rank highly in our simulations. This unbiased approach for identifying topologies capable of a given response may be useful in discovering new natural motifs and in designing robust synthetic gene networks.

The ability to engineer an all-or-none cellular response to a given signaling ligand is important in applications ranging from biosensing to tissue engineering. However, synthetic gene network 'switches' have been limited in their applicability and tunability due to their reliance on specific components to function. Here, we present a strategy for reversible switch design that instead relies only on a robust, easily constructed network topology with two positive feedback loops and we apply the method to create highly ultrasensitive (n(H)>20), bistable cellular responses to a synthetic ligand/receptor complex. Independent modulation of the two feedback strengths enables rational tuning and some decoupling of steady-state (ultrasensitivity, signal amplitude, switching threshold, and bistability) and kinetic (rates of system activation and deactivation) response properties. Our integrated computational and synthetic biology approach elucidates design rules for building cellular switches with desired properties, which may be of utility in engineering signal-transduction pathways.

The flexibility of MAPK cascade responses enables regulation of a vast array of cell fate decisions, but elucidating the mechanisms underlying this plasticity is difficult in endogenous signaling networks. We constructed insulated mammalian MAPK cascades in yeast to explore how intrinsic and extrinsic perturbations affect the flexibility of these synthetic signaling modules. Contrary to biphasic dependence on scaffold concentration, we observe monotonic decreases in signal strength as scaffold concentration increases. We find that augmenting the concentration of sequential kinases can enhance ultrasensitivity and lower the activation threshold. Further, integrating negative regulation and concentration variation can decouple ultrasensitivity and threshold from the strength of the response. Computational analyses show that cascading can generate ultrasensitivity and that natural cascades with different kinase concentrations are innately biased toward their distinct activation profiles. This work demonstrates that tunable signal processing is inherent to minimal MAPK modules and elucidates principles for rational design of synthetic signaling systems., (Copyright © 2011 Elsevier Inc. All rights reserved.)

Directed evolution is a powerful approach for isolating high-affinity binders from complex libraries. In affinity maturation experiments, binders with the highest affinities in the library are typically isolated through selections for decreased off rate using a suitable selection platform (e.g. phage display or ribosome display). In such experiments, the library is initially exposed to biotinylated antigen and the binding reaction is allowed to proceed. A large excess of unbiotinylated antigen is then added as a competitor to capture the vast majority of rapidly dissociating molecules; the slowly dissociating library members can subsequently be rescued by capturing the biotin-carrying complexes. To optimize the parameters for such affinity maturation experiments, we performed both deterministic and stochastic simulations of off-rate selection experiments using different input libraries. Our results suggest that the most critical parameters for achieving the lowest off rates after selection are the ratio of competitor antigen to selectable antigen and the selection time. Furthermore, the selection time has an optimum that depends on the experimental setup and the nature of the library. Notably, if selections are carried out for times much longer than the optimum, equilibrium is reached and the selection pressure is weakened or lost. Comparison of different selection strategies revealed that sequential selection rounds with lower stringency are favored over high-stringency selection experiments due to enhanced diversity in the selected pools. Such simulations may be helpful in optimizing affinity maturation strategies and off-rate selection experiments.

Scientists have traditionally studied complex biologic systems by reducing them to simple building blocks. Genome sequencing, high-throughput screening, and proteomics have, however, generated large datasets, revealing a high level of complexity in components and interactions. Systems biology embraces this complexity with a combination of mathematical, engineering, and computational tools for constructing and validating models of biologic phenomena. The validity of mathematical modeling in hematopoiesis was established early by the pioneering work of Till and McCulloch. In reviewing more recent papers, we highlight deterministic, stochastic, statistical, and network-based models that have been used to better understand a range of topics in hematopoiesis, including blood cell production, the periodicity of cyclical neutropenia, stem cell production in response to cytokine administration, and the emergence of imatinib resistance in chronic myeloid leukemia. Future advances require technologic improvements in computing power, imaging, and proteomics as well as greater collaboration between experimentalists and modelers. Altogether, systems biology will improve our understanding of normal and abnormal hematopoiesis, better define stem cells and their daughter cells, and potentially lead to more effective therapies.

Autoregulation of transcription factors and cross-antagonism between lineage-specific transcription factors are a recurrent theme in cell differentiation. An equally prevalent event that is frequently overlooked in lineage commitment models is the upregulation of lineage-specific receptors, often through lineage-specific transcription factors. Here, we use a minimal model that combines cell-extrinsic and cell-intrinsic elements of regulation in order to understand how both instructive and stochastic events can inform cell commitment decisions in hematopoiesis. Our results suggest that cytokine-mediated positive receptor feedback can induce a "switch-like" response to external stimuli during multilineage differentiation by providing robustness to both bipotent and committed states while protecting progenitors from noise-induced differentiation or decommitment. Our model provides support to both the instructive and stochastic theories of commitment: cell fates are ultimately driven by lineage-specific transcription factors, but cytokine signaling can strongly bias lineage commitment by regulating these inherently noisy cell-fate decisions with complex, pertinent behaviors such as ligand-mediated ultrasensitivity and robust multistability. The simulations further suggest that the kinetics of differentiation to a mature cell state can depend on the starting progenitor state as well as on the route of commitment that is chosen. Lastly, our model shows good agreement with lineage-specific receptor expression kinetics from microarray experiments and provides a computational framework that can integrate both classical and alternative commitment paths in hematopoiesis that have been observed experimentally.

We describe here the selection and characterization of designed ankyrin repeat proteins (DARPins) that bind specifically to the rat neurotensin receptor 1 (NTR1), a G-protein coupled receptor (GPCR). The selection procedure using ribosome display and the initial clone analysis required <10 microg of detergent-solubilized, purified NTR1. Complex formation with solubilized GPCR was demonstrated by ELISA and size-exclusion chromatography; additionally, the GPCR could be detected in native membranes of mammalian cells using fluorescence microscopy. The main binding epitope in the GPCR lies within the 33 amino acids following the seventh transmembrane segment, which comprise the putative helix 8, and additional binding interactions are possibly contributed by the cytoplasmic loop 3, thus constituting a discontinuous epitope. Since the selected binders recognize the GPCR both in detergent-solubilized and in membrane-embedded forms, they will be potentially useful both in co-crystallization trials and for signal transduction experiments.

We outline a powerful method for the directed evolution of integral membrane proteins in the inner membrane of Escherichia coli. For a mammalian G protein-coupled receptor, we arrived at a sequence with an order-of-magnitude increase in functional expression that still retains the biochemical properties of wild type. This mutant also shows enhanced heterologous expression in eukaryotes (12-fold in Pichia pastoris and 3-fold in HEK293T cells) and greater stability when solubilized and purified, indicating that the biophysical properties of the protein had been under the pressure of selection. These improvements arise from multiple small contributions, which would be difficult to assemble by rational design. In a second screen, we rapidly pinpointed a single amino acid substitution in wild type that abolishes antagonist binding while retaining agonist-binding affinity. These approaches may alleviate existing bottlenecks in structural studies of these targets by providing sufficient quantities of stable variants in defined conformational states.

Cytokines and lineage-specific transcription factors are critical molecular effectors for terminal differentiation during hematopoiesis. Intrinsic transcription factor activity is often believed to drive commitment and differentiation, whereas cytokine receptor signals have been implicated in the regulation of cell proliferation, survival, and differentiation. In erythropoiesis, recent experimental findings provide direct evidence that erythropoietin (Epo) can generate commitment cues via the erythropoietin receptor (EpoR); specifically, EpoR signaling leads to activation of the transcription factor GATA-1, which then triggers transcription of erythrocyte-specific genes. In particular, activated GATA-1 induces two positive feedback loops in the system through the enhanced expression of both inactive GATA-1 and EpoR, the latter of which is externally regulatable by Epo. Based upon this network architecture, we present a mathematical model of GATA-1 activation by EpoR, which bidirectionally links a lineage-specific receptor and transcription factor. Our deterministic model offers insight into stimulus-response relationships between Epo and several downstream effectors. In addition to the survival signals that EpoR provides, steady-state analysis of our model suggests that receptor upregulation during lineage commitment can also generate ultrasensitivity to Epo and bistability in GATA-1 activity. These system-level properties can induce a switch-like characteristic during differentiation and provide robustness to the mature state. The topology also suggests a novel mechanism for achieving robust bistability in a purely deterministic manner without molecular cooperativity. The analytical solution of a generalized, minimal model is provided and the significance of each of the two positive feedback loops is elucidated through bifurcation analysis. This network topology, or variations thereof, may link other receptor-transcription factor pairs and may therefore be of general relevance in cellular decision-making.

PEGylation is an attractive strategy to enhance the therapeutic efficacy of proteins with a short serum half-life. It can be used to extend the serum persistence and to reduce the immunogenicity of proteins. However, PEGylation can also lead to a decrease in the functional activity of the molecule to which it is applied. We constructed site-specifically PEGylated variants of anti-p185(HER-2) antibody fragments in the format of a monovalent single-chain variable fragment and a divalent miniantibody and characterized the antigen binding properties in detail. Mass-transport limited BIAcore measurements and binding assays on HER-2-overexpressing cells demonstrated that the immunoreactivity of the antibody fragments is fully maintained after PEGylation. Nevertheless, we found that the attachment of a 20-kDa polyethylene glycol (PEG) moiety led to a reduction in apparent affinity of approximately 5-fold, although in both formats, the attachment site was most distal to the antigen binding regions. This decrease in affinity was observed in kinetic BIAcore measurements as well as in equilibrium binding assays on whole cells. By analysis of the binding kinetics, we could pinpoint this reduction exclusively to slower apparent on rates. Through both experimental and computational analyses, we demonstrate that these reduced on-rates do not arise from diffusion limitations. We show that a mathematical model accounting for both intramolecular and intermolecular blocking mechanisms of the PEG moiety can robustly explain the observed binding kinetics. The results suggest that PEGylation can significantly alter the binding-competent fraction of both ligands and receptors and may help to explain some of the beneficial effects of PEGylation in vivo.

After a cytokine binds to its receptor on the cell surface (pH approximately 7), the complex is internalized into acidic endosomal compartments (pH approximately 5-6), where partially unfolded intermediates can form. The nature of these structural transitions was studied for wild-type interleukin-2 (IL-2) and wild-type granulocyte colony-stimulating factor (G-CSF). A noncoincidence of denaturation transitions in the secondary and tertiary structure of IL-2 and tertiary structural perturbations in G-CSF suggest the presence of an intermediate state for each, a common feature of this structural family of four-helical bundle proteins. Unexpectedly, both IL-2 and G-CSF display monotonic increases in stability as the pH is decreased from 7 to 4. We hypothesize that such cytokines with cell-based clearance mechanisms in vivo may have evolved to help stabilize endosomal complexes for sorting to lysosomal degradation. We show that mutants of both IL-2 and G-CSF have differential stabilities to their wild-type counterparts as a function of pH, and that these differences may explain the differences in ligand trafficking and depletion. Further understanding of the structural changes accompanying unfolding may help guide cytokine design with respect to ligand binding, endocytic trafficking, and, consequently, therapeutic efficacy.

The pharmacodynamic potency of a therapeutic cytokine interacting with a cell-surface receptor can be attributed primarily to three central properties: [1] cytokine/receptor binding affinity, [2] cytokine/receptor endocytic trafficking dynamics, and [3] cytokine/receptor signaling. Thus, engineering novel or second-generation cytokines requires an understanding of the contribution of each of these to the overall cell response. We describe here an efficient method toward this goal in demonstrated application to the clinically important cytokine granulocyte colony-stimulating factor (GCSF) with a chemical analogue and a number of genetic mutants. Using a combination of simple receptor-binding and dose-response proliferation assays we construct an appropriately scaled plot of relative mitogenic potency versus ligand concentration normalized by binding affinity. Analysis of binding and proliferation data in this manner conveniently indicates which of the cytokine properties-binding, trafficking, and/or signaling-are contributing substantially to altered potency effects. For the GCSF analogues studied here, two point mutations as well as a poly(ethylene glycol) chemical conjugate were found to have increased potencies despite comparable or slightly lower affinities, and trafficking was predicted to be the responsible mechanism. A third point mutant exhibiting comparable binding affinity but reduced potency was predicted to have largely unchanged trafficking properties. Surprisingly, another mutant possessing an order-of-magnitude weaker binding affinity displayed enhanced potency, and increased ligand half-life was predicted to be responsible for this net beneficial effect. Each of these predictions was successfully demonstrated by subsequent measurements of depletion of these five analogues from cell culture medium. Thus, for the GCSF system we find that ligand trafficking dynamics can play a major role in regulating mitogenic potency. Our results demonstrate that cytokine analogues can exhibit pharmacodynamic behaviors across a diverse spectrum of "binding-potency space" and that our analysis through normalization can efficiently elucidate hypotheses for the underlying mechanisms for further dedicated testing. We have also extended the Black-Leff model of pharmacological agonism to include trafficking effects along with binding and signaling, and this model provides a framework for parsing the effects of these factors on pharmacodynamic potency.

The cytokine granulocyte colony-stimulating factor (GCSF) is of great clinical importance, with primary application to rapidly elevate the peripheral neutrophil levels of chemotherapy patients through accelerated granulopoiesis. However, these mature bloodstream neutrophils express the GCSF receptor (GCSFR), presenting a significant and specific clearance mechanism of circulating GCSF that increases with time. Here, we formulate a mathematical model that describes these cell-level GCSF/GCSFR dynamics and correlate the effect of these endocytic trafficking processes to ligand depletion in an in vitro culture. We further incorporate this cell-level model into an existing pharmacokinetic/pharmacodynamic (PK/PD) model, to gain insight into the effects that specific molecular and cellular parameters may have on overall PK/PD effects in vivo. Our cell-level model suggests that ligand depletion may be reduced in vitro by decreasing the endosomal affinity of endocytosed GCSF/GCSFR complexes, matching experimental findings. Additionally, our modified PK/PD model suggests that a GCSF analog with a modification that effectively eliminates renal clearance should have a significantly longer half-life in vivo and should therefore improve peripheral neutrophil counts. This is consistent with clinical studies on a polyethylene glycol chemical conjugate of GCSF termed SD/01. The model predicts that a GCSF analog that eliminates renal clearance and has reduced endosomal binding affinity may result in an even longer ligand half-life and increased neutrophil counts at a lower dose than either wild-type GCSF or SD/01. More generally, this type of hierarchical model provides a correlation between the molecular and pharmacological properties of a drug and may elucidate design goals for such protein therapeutics.

We describe a method for the rational design of more effective therapeutic proteins using amino acid substitutions that reduce receptor binding affinity in intracellular endosomal compartments, thereby leading to increased recycling in the ligand-sorting process and consequently resulting in longer half-life in extracellular medium. We demonstrate this approach for granulocyte colony-stimulating factor by using computationally predicted histidine substitutions that switch protonation states between cell-surface and endosomal pH. Molecular modeling of binding electrostatics indicates two different single-histidine mutants that fulfill our design requirements; experimental assays demonstrate that each mutant indeed exhibits an order-of-magnitude increase in medium half-life along with enhanced potency due to increased endocytic recycling.