In vivo selection of synthetic nucleocapsids for tissue targeting.

Controlling the biodistribution of protein- and nanoparticle-based therapeutic formulations remains challenging. In vivo library selection is an effective method for identifying constructs that exhibit desired distribution behavior; library variants can be selected based on their ability to localize to the tissue or compartment of interest despite complex physiological challenges. Here, we describe further development of an in vivo library selection platform based on self-assembling protein nanoparticles encapsulating their own mRNA genomes (synthetic nucleocapsids or synNCs). We tested two distinct libraries: a low-diversity library composed of synNC surface mutations (45 variants) and a high-diversity library composed of synNCs displaying miniproteins with binder-like properties (6.2 million variants). While we did not identify any variants from the low-diversity surface library that yielded therapeutically relevant changes in biodistribution, the high-diversity miniprotein display library yielded variants that shifted accumulation toward lungs or muscles in just two rounds of in vivo selection. Our approach should contribute to achieving specific tissue homing patterns and identifying targeting ligands for diseases of interest.

Building smart CAR T cell therapies: The path to overcome current challenges.

Successful implementation of adoptive cell therapy (ACT) of cancer requires comprehensively addressing biological and practical challenges. This approach has been largely overlooked, resulting in a gap between the potential of ACT and its actual effectiveness. We summarize the most promising technical strategies in creating an "ideal" ACT product, focusing on chimeric antigen receptor (CAR)-engineered cells. Since many requirements for effective ACT are common to most cancers, what we outline here might have a broader impact.

A split, conditionally active mimetic of IL-2 reduces the toxicity of systemic cytokine therapy.

The therapeutic potential of recombinant cytokines has been limited by the severe side effects of systemic administration. We describe a strategy to reduce the dose-limiting toxicities of monomeric cytokines by designing two components that require colocalization for activity and that can be independently targeted to restrict activity to cells expressing two surface markers. We demonstrate the approach with a previously designed mimetic of cytokines interleukin-2 and interleukin-15-Neoleukin-2/15 (Neo-2/15)-both for trans-activating immune cells surrounding targeted tumor cells and for cis-activating directly targeted immune cells. In trans-activation mode, tumor antigen targeting of the two components enhanced antitumor activity and attenuated toxicity compared with systemic treatment in syngeneic mouse melanoma models. In cis-activation mode, immune cell targeting of the two components selectively expanded CD8+ T cells in a syngeneic mouse melanoma model and promoted chimeric antigen receptor T cell activation in a lymphoma xenograft model, enhancing antitumor efficacy in both cases.

De novo design of modular and tunable protein biosensors.

Naturally occurring protein switches have been repurposed for the development of biosensors and reporters for cellular and clinical applications1. However, the number of such switches is limited, and reengineering them is challenging. Here we show that a general class of protein-based biosensors can be created by inverting the flow of information through de novo designed protein switches in which the binding of a peptide key triggers biological outputs of interest2. The designed sensors are modular molecular devices with a closed dark state and an open luminescent state; analyte binding drives the switch from the closed to the open state. Because the sensor is based on the thermodynamic coupling of analyte binding to sensor activation, only one target binding domain is required, which simplifies sensor design and allows direct readout in solution. We create biosensors that can sensitively detect the anti-apoptosis protein BCL-2, the IgG1 Fc domain, the HER2 receptor, and Botulinum neurotoxin B, as well as biosensors for cardiac troponin I and an anti-hepatitis B virus antibody with the high sensitivity required to detect these molecules clinically. Given the need for diagnostic tools to track the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)3, we used the approach to design sensors for the SARS-CoV-2 spike protein and antibodies against the membrane and nucleocapsid proteins. The former, which incorporates a de novo designed spike receptor binding domain (RBD) binder4, has a limit of detection of 15 pM and a luminescence signal 50-fold higher than the background level. The modularity and sensitivity of the platform should enable the rapid construction of sensors for a wide range of analytes, and highlights the power of de novo protein design to create multi-state protein systems with new and useful functions.

Characterizing the portability of phage-encoded homologous recombination proteins.

Efficient genome editing methods are essential for biotechnology and fundamental research. Homologous recombination (HR) is the most versatile method of genome editing, but techniques that rely on host RecA-mediated pathways are inefficient and laborious. Phage-encoded single-stranded DNA annealing proteins (SSAPs) improve HR 1,000-fold above endogenous levels. However, they are not broadly functional. Using Escherichia coli, Lactococcus lactis, Mycobacterium smegmatis, Lactobacillus rhamnosus and Caulobacter crescentus, we investigated the limited portability of SSAPs. We find that these proteins specifically recognize the C-terminal tail of the host's single-stranded DNA-binding protein (SSB) and are portable between species only if compatibility with this host domain is maintained. Furthermore, we find that co-expressing SSAPs with SSBs can significantly improve genome editing efficiency, in some species enabling SSAP functionality even without host compatibility. Finally, we find that high-efficiency HR far surpasses the mutational capacity of commonly used random mutagenesis methods, generating exceptional phenotypes that are inaccessible through sequential nucleotide conversions.

De novo design of modular and tunable allosteric biosensors.

Naturally occurring allosteric protein switches have been repurposed for developing novel biosensors and reporters for cellular and clinical applications 1 , but the number of such switches is limited, and engineering them is often challenging as each is different. Here, we show that a very general class of allosteric protein-based biosensors can be created by inverting the flow of information through de novo designed protein switches in which binding of a peptide key triggers biological outputs of interest 2 . Using broadly applicable design principles, we allosterically couple binding of protein analytes of interest to the reconstitution of luciferase activity and a bioluminescent readout through the association of designed lock and key proteins. Because the sensor is based purely on thermodynamic coupling of analyte binding to switch activation, only one target binding domain is required, which simplifies sensor design and allows direct readout in solution. We demonstrate the modularity of this platform by creating biosensors that, with little optimization, sensitively detect the anti-apoptosis protein Bcl-2, the hIgG1 Fc domain, the Her2 receptor, and Botulinum neurotoxin B, as well as biosensors for cardiac Troponin I and an anti-Hepatitis B virus (HBV) antibody that achieve the sub-nanomolar sensitivity necessary to detect clinically relevant concentrations of these molecules. Given the current need for diagnostic tools for tracking COVID-19 3 , we use the approach to design sensors of antibodies against SARS-CoV-2 protein epitopes and of the receptor-binding domain (RBD) of the SARS-CoV-2 Spike protein. The latter, which incorporates a de novo designed RBD binder, has a limit of detection of 15pM with an up to seventeen fold increase in luminescence upon addition of RBD. The modularity and sensitivity of the platform should enable the rapid construction of sensors for a wide range of analytes and highlights the power of de novo protein design to create multi-state protein systems with new and useful functions.

Designed protein logic to target cells with precise combinations of surface antigens.

Precise cell targeting is challenging because most mammalian cell types lack a single surface marker that distinguishes them from other cells. A solution would be to target cells using specific combinations of proteins present on their surfaces. In this study, we design colocalization-dependent protein switches (Co-LOCKR) that perform AND, OR, and NOT Boolean logic operations. These switches activate through a conformational change only when all conditions are met, generating rapid, transcription-independent responses at single-cell resolution within complex cell populations. We implement AND gates to redirect T cell specificity against tumor cells expressing two surface antigens while avoiding off-target recognition of single-antigen cells, and three-input switches that add NOT or OR logic to avoid or include cells expressing a third antigen. Thus, de novo designed proteins can perform computations on the surface of cells, integrating multiple distinct binding interactions into a single output.

Conditional Recruitment to a DNA-Bound CRISPR-Cas Complex Using a Colocalization-Dependent Protein Switch.

To spatially control biochemical functions at specific sites within a genome, we have engineered a synthetic switch that activates when bound to its DNA target site. The system uses two CRISPR-Cas complexes to colocalize components of a de novo-designed protein switch (Co-LOCKR) to adjacent sites in the genome. Colocalization triggers a conformational change in the switch from an inactive closed state to an active open state with an exposed functional peptide. We prototype the system in yeast and demonstrate that DNA binding triggers activation of the switch, recruitment of a transcription factor, and expression of a downstream reporter gene. This DNA-triggered Co-LOCKR switch provides a platform to engineer sophisticated functions that should only be executed at a specific target site within the genome, with potential applications in a wide range of synthetic systems including epigenetic regulation, imaging, and genetic logic circuits.

Improved bacterial recombineering by parallelized protein discovery.

Exploiting bacteriophage-derived homologous recombination processes has enabled precise, multiplex editing of microbial genomes and the construction of billions of customized genetic variants in a single day. The techniques that enable this, multiplex automated genome engineering (MAGE) and directed evolution with random genomic mutations (DIvERGE), are however, currently limited to a handful of microorganisms for which single-stranded DNA-annealing proteins (SSAPs) that promote efficient recombineering have been identified. Thus, to enable genome-scale engineering in new hosts, efficient SSAPs must first be found. Here we introduce a high-throughput method for SSAP discovery that we call "serial enrichment for efficient recombineering" (SEER). By performing SEER in Escherichia coli to screen hundreds of putative SSAPs, we identify highly active variants PapRecT and CspRecT. CspRecT increases the efficiency of single-locus editing to as high as 50% and improves multiplex editing by 5- to 10-fold in E. coli, while PapRecT enables efficient recombineering in Pseudomonas aeruginosa, a concerning human pathogen. CspRecT and PapRecT are also active in other, clinically and biotechnologically relevant enterobacteria. We envision that the deployment of SEER in new species will pave the way toward pooled interrogation of genotype-to-phenotype relationships in previously intractable bacteria.

De novo design of bioactive protein switches.

Allosteric regulation of protein function is widespread in biology, but is challenging for de novo protein design as it requires the explicit design of multiple states with comparable free energies. Here we explore the possibility of designing switchable protein systems de novo, through the modulation of competing inter- and intramolecular interactions. We design a static, five-helix 'cage' with a single interface that can interact either intramolecularly with a terminal 'latch' helix or intermolecularly with a peptide 'key'. Encoded on the latch are functional motifs for binding, degradation or nuclear export that function only when the key displaces the latch from the cage. We describe orthogonal cage-key systems that function in vitro, in yeast and in mammalian cells with up to 40-fold activation of function by key. The ability to design switchable protein functions that are controlled by induced conformational change is a milestone for de novo protein design, and opens up new avenues for synthetic biology and cell engineering.

Codon usage of highly expressed genes affects proteome-wide translation efficiency.

Although the genetic code is redundant, synonymous codons for the same amino acid are not used with equal frequencies in genomes, a phenomenon termed "codon usage bias." Previous studies have demonstrated that synonymous changes in a coding sequence can exert significant cis effects on the gene's expression level. However, whether the codon composition of a gene can also affect the translation efficiency of other genes has not been thoroughly explored. To study how codon usage bias influences the cellular economy of translation, we massively converted abundant codons to their rare synonymous counterpart in several highly expressed genes in Escherichia coli This perturbation reduces both the cellular fitness and the translation efficiency of genes that have high initiation rates and are naturally enriched with the manipulated codon, in agreement with theoretical predictions. Interestingly, we could alleviate the observed phenotypes by increasing the supply of the tRNA for the highly demanded codon, thus demonstrating that the codon usage of highly expressed genes was selected in evolution to maintain the efficiency of global protein translation.

Evolution of a designed protein assembly encapsulating its own RNA genome.

The challenges of evolution in a complex biochemical environment, coupling genotype to phenotype and protecting the genetic material, are solved elegantly in biological systems by the encapsulation of nucleic acids. In the simplest examples, viruses use capsids to surround their genomes. Although these naturally occurring systems have been modified to change their tropism and to display proteins or peptides, billions of years of evolution have favoured efficiency at the expense of modularity, making viral capsids difficult to engineer. Synthetic systems composed of non-viral proteins could provide a 'blank slate' to evolve desired properties for drug delivery and other biomedical applications, while avoiding the safety risks and engineering challenges associated with viruses. Here we create synthetic nucleocapsids, which are computationally designed icosahedral protein assemblies with positively charged inner surfaces that can package their own full-length mRNA genomes. We explore the ability of these nucleocapsids to evolve virus-like properties by generating diversified populations using Escherichia coli as an expression host. Several generations of evolution resulted in markedly improved genome packaging (more than 133-fold), stability in blood (from less than 3.7% to 71% of packaged RNA protected after 6 hours of treatment), and in vivo circulation time (from less than 5 minutes to approximately 4.5 hours). The resulting synthetic nucleocapsids package one full-length RNA genome for every 11 icosahedral assemblies, similar to the best recombinant adeno-associated virus vectors. Our results show that there are simple evolutionary paths through which protein assemblies can acquire virus-like genome packaging and protection. Considerable effort has been directed at 'top-down' modification of viruses to be safe and effective for drug delivery and vaccine applications; the ability to design synthetic nanomaterials computationally and to optimize them through evolution now enables a complementary 'bottom-up' approach with considerable advantages in programmability and control.

Rewriting the Genetic Code.

The genetic code-the language used by cells to translate their genomes into proteins that perform many cellular functions-is highly conserved throughout natural life. Rewriting the genetic code could lead to new biological functions such as expanding protein chemistries with noncanonical amino acids (ncAAs) and genetically isolating synthetic organisms from natural organisms and viruses. It has long been possible to transiently produce proteins bearing ncAAs, but stabilizing an expanded genetic code for sustained function in vivo requires an integrated approach: creating recoded genomes and introducing new translation machinery that function together without compromising viability or clashing with endogenous pathways. In this review, we discuss design considerations and technologies for expanding the genetic code. The knowledge obtained by rewriting the genetic code will deepen our understanding of how genomes are designed and how the canonical genetic code evolved.

Optimizing complex phenotypes through model-guided multiplex genome engineering.

We present a method for identifying genomic modifications that optimize a complex phenotype through multiplex genome engineering and predictive modeling. We apply our method to identify six single nucleotide mutations that recover 59% of the fitness defect exhibited by the 63-codon E. coli strain C321.∆A. By introducing targeted combinations of changes in multiplex we generate rich genotypic and phenotypic diversity and characterize clones using whole-genome sequencing and doubling time measurements. Regularized multivariate linear regression accurately quantifies individual allelic effects and overcomes bias from hitchhiking mutations and context-dependence of genome editing efficiency that would confound other strategies.

Millstone: software for multiplex microbial genome analysis and engineering.

Inexpensive DNA sequencing and advances in genome editing have made computational analysis a major rate-limiting step in adaptive laboratory evolution and microbial genome engineering. We describe Millstone, a web-based platform that automates genotype comparison and visualization for projects with up to hundreds of genomic samples. To enable iterative genome engineering, Millstone allows users to design oligonucleotide libraries and create successive versions of reference genomes. Millstone is open source and easily deployable to a cloud platform, local cluster, or desktop, making it a scalable solution for any lab.

An orthogonalized platform for genetic code expansion in both bacteria and eukaryotes.

In this study, we demonstrate the feasibility of expanding the genetic code of Escherichia coli using its own tryptophanyl-tRNA synthetase and tRNA (TrpRS-tRNATrp) pair. This was made possible by first functionally replacing this endogenous pair with an E. coli-optimized counterpart from Saccharomyces cerevisiae, and then reintroducing the liberated E. coli TrpRS-tRNATrp pair into the resulting strain as a nonsense suppressor, which was then followed by its directed evolution to genetically encode several new unnatural amino acids (UAAs). These engineered TrpRS-tRNATrp variants were also able to drive efficient UAA mutagenesis in mammalian cells. Since bacteria-derived aminoacyl-tRNA synthetase (aaRS)-tRNA pairs are typically orthogonal in eukaryotes, our work provides a general strategy to develop additional aaRS-tRNA pairs that can be used for UAA mutagenesis of proteins expressed in both E. coli and eukaryotes.

Emergent rules for codon choice elucidated by editing rare arginine codons in Escherichia coli.

The degeneracy of the genetic code allows nucleic acids to encode amino acid identity as well as noncoding information for gene regulation and genome maintenance. The rare arginine codons AGA and AGG (AGR) present a case study in codon choice, with AGRs encoding important transcriptional and translational properties distinct from the other synonymous alternatives (CGN). We created a strain of Escherichia coli with all 123 instances of AGR codons removed from all essential genes. We readily replaced 110 AGR codons with the synonymous CGU codons, but the remaining 13 "recalcitrant" AGRs required diversification to identify viable alternatives. Successful replacement codons tended to conserve local ribosomal binding site-like motifs and local mRNA secondary structure, sometimes at the expense of amino acid identity. Based on these observations, we empirically defined metrics for a multidimensional "safe replacement zone" (SRZ) within which alternative codons are more likely to be viable. To evaluate synonymous and nonsynonymous alternatives to essential AGRs further, we implemented a CRISPR/Cas9-based method to deplete a diversified population of a wild-type allele, allowing us to evaluate exhaustively the fitness impact of all 64 codon alternatives. Using this method, we confirmed the relevance of the SRZ by tracking codon fitness over time in 14 different genes, finding that codons that fall outside the SRZ are rapidly depleted from a growing population. Our unbiased and systematic strategy for identifying unpredicted design flaws in synthetic genomes and for elucidating rules governing codon choice will be crucial for designing genomes exhibiting radically altered genetic codes.

Design, synthesis, and testing toward a 57-codon genome.

Recoding--the repurposing of genetic codons--is a powerful strategy for enhancing genomes with functions not commonly found in nature. Here, we report computational design, synthesis, and progress toward assembly of a 3.97-megabase, 57-codon Escherichia coli genome in which all 62,214 instances of seven codons were replaced with synonymous alternatives across all protein-coding genes. We have validated 63% of recoded genes by individually testing 55 segments of 50 kilobases each. We observed that 91% of tested essential genes retained functionality with limited fitness effect. We demonstrate identification and correction of lethal design exceptions, only 13 of which were found in 2229 genes. This work underscores the feasibility of rewriting genomes and establishes a framework for large-scale design, assembly, troubleshooting, and phenotypic analysis of synthetic organisms.

Performance of optimized noncanonical amino acid mutagenesis systems in the absence of release factor 1.

Site-specific incorporation of noncanonical amino acids (ncAAs) into proteins expressed in E. coli using UAG-suppression competes with termination mediated by release factor 1 (RF1). Recently, unconditional deletion of RF1 was achieved in a genomically recoded E. coli (C321), devoid of all endogenous UAG stop codons. Here we evaluate the efficiency of ncAA incorporation in this strain using optimized suppression vectors. Even though the absence of RF1 does not benefit the suppression efficiency of a single UAG codon, multi-site incorporation of a series of chemically distinct ncAAs was significantly improved.

Multiplex pairwise assembly of array-derived DNA oligonucleotides.

While the cost of DNA sequencing has dropped by five orders of magnitude in the past decade, DNA synthesis remains expensive for many applications. Although DNA microarrays have decreased the cost of oligonucleotide synthesis, the use of array-synthesized oligos in practice is limited by short synthesis lengths, high synthesis error rates, low yield and the challenges of assembling long constructs from complex pools. Toward addressing these issues, we developed a protocol for multiplex pairwise assembly of oligos from array-synthesized oligonucleotide pools. To evaluate the method, we attempted to assemble up to 2271 targets ranging in length from 192-252 bases using pairs of array-synthesized oligos. Within sets of complexity ranging from 131-250 targets, we observed error-free assemblies for 90.5% of all targets. When all 2271 targets were assembled in one reaction, we observed error-free constructs for 70.6%. While the assembly method intrinsically increased accuracy to a small degree, we further increased accuracy by using a high throughput 'Dial-Out PCR' protocol, which combines Illumina sequencing with an in-house set of unique PCR tags to selectively amplify perfect assemblies from complex synthetic pools. This approach has broad applicability to DNA assembly and high-throughput functional screens.