Explore the vast range of titles available.

Genetically modified organisms (GMOs) are increasingly deployed at large scales and in open environments. Genetic biocontainment strategies are needed to prevent unintended proliferation of GMOs in natural ecosystems. Existing biocontainment methods are insufficient because they impose evolutionary pressure on the organism to eject the safeguard by spontaneous mutagenesis or horizontal gene transfer, or because they can be circumvented by environmentally available compounds. Here we computationally redesign essential enzymes in the first organism possessing an altered genetic code ( Escherichia coli strain C321.ΔA) to confer metabolic dependence on non-standard amino acids for survival. The resulting GMOs cannot metabolically bypass their biocontainment mechanisms using known environmental compounds, and they exhibit unprecedented resistance to evolutionary escape through mutagenesis and horizontal gene transfer. This work provides a foundation for safer GMOs that are isolated from natural ecosystems by a reliance on synthetic metabolites. Essential enzymes in genetically modified organisms are computationally redesigned to functionally depend on non-standard amino acids, thereby achieving biocontainment with unprecedented resistance to escape by evolution or by supplementation with environmental metabolites. Two routes to safer GMOs Two manuscripts published in this issue of Nature describe independent approaches towards generating an organism dependent on unnatural amino acids, a development which could find applications for biocontainment and exploration of previously unsampled fitness landscapes. George Church and colleagues redesigned essential enzymes in an organism ( Escherichia coli ) with an altered genetic code to make it metabolically dependent on non-standard amino acids for survival. The resulting genetically modified organisms (GMOs) cannot metabolically circumvent their biocontainment mechanisms and show unprecedented resistance to evolutionary escape. The few escapees are rapidly outcompeted by unmodified organisms. Using multiplex automated genome engineering, Farren Isaacs and colleagues construct a series of genomically recoded organisms whose growth is restricted by the expression of essential genes that depend on exogenously supplied synthetic amino acids. They constructed synthetic auxotrophs with advanced orthogonal barriers between engineered organisms and the environment, thereby creating safer GMOs.

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.

Integrins are cell adhesion receptors, which play a role in breast cancer invasion, angiogenesis, and metastasis. Moreover, it has been shown that exosomal integrins provide organotropic metastasis in a mouse model. In our study, we aimed to investigate the expression of integrins β3, β4, and αVβ5 on exosomes and tumor cells (circulating tumor cells and primary tumor) and their association with the localization of distant metastasis. We confirmed the association of exosomal integrin β4 with lung metastasis in breast cancer patients. However, we were unable to evaluate the role of integrin β3 in brain metastasis due to the rarity of this localization. We established no association of exosomal integrin αVβ5 with liver metastasis in our cohort of breast cancer patients. The further evaluation of β3, β4, and αVβ5 integrin expression on CTCs revealed an association of integrin β4 and αVβ5 with liver, but not the lung metastases. Integrin β4 in the primary tumor was associated with liver metastasis. Furthermore, an in-depth analysis of phenotypic characteristics of β4+ tumor cells revealed a significantly increased proportion of E-cadherin+ and CD44+CD24- cells in patients with liver metastases compared to patients with lung or no distant metastases.

We describe the construction and characterization of a genomically recoded organism (GRO). We replaced all known UAG stop codons in Escherichia coli MG1655 with synonymous UAA codons, which permitted the deletion of release factor 1 and reassignment of UAG translation function. This GRO exhibited improved properties for incorporation of nonstandard amino acids that expand the chemical diversity of proteins in vivo. The GRO also exhibited increased resistance to T7 bacteriophage, demonstrating that new genetic codes could enable increased viral resistance.

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.

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.

Central nervous system (CNS) diseases are difficult to treat due to the blood-brain barrier (BBB), which prevents many therapeutics from reaching the brain. Receptor-mediated transcytosis (RMT) shows promise for transporting macromolecules across the BBB, but current targeting methods lack CNS specificity and cell-type selectivity. The number of validated \"Portals\" (BBB receptors with demonstrated RMT in vivo) is limited due to historical screening constraints. We conducted the most comprehensive in vivo evaluation of BBB shuttles and Portals to date, screening over 3,000 candidates against 68 potential Portal targets in mice. Our novel pooled in vivo screening technology, mCodes™, allowed us to simultaneously assess quantitative tissue distribution for up to 100 molecules per animal with high precision. This approach revealed the \"Transcytosome,\" an expanded set of Portal targets capable of facilitating RMT across the BBB. Detailed pharmacokinetic and biodistribution analyses of select novel Portals demonstrate distinct properties compared to well-characterized targets like transferrin receptor (TfR) and CD98. Novel portals were discovered that demonstrated optimal characteristics for therapeutic strategies targeting extracellular pathologies like Abeta, as well as intracellular pathologies like Tau. These portals offer promising avenues for further research and development in the pursuit of effective treatments for Alzheimer's disease. These newly identified Portal receptors may enable unprecedented control over biodistribution, enhancing CNS delivery, cell-type specificity, regional targeting, and reduced peripheral effects. By substantially expanding the known Portal landscape, our work provides a foundation for developing biologics with precisely engineered tissue distribution profiles that are sculpted to meet the intended product profiles for specific therapeutic approaches. The Transcytosome represents a crucial step toward realizing the full therapeutic potential of biologics in CNS diseases such as Alzheimer's.

Background Central nervous system (CNS) diseases are difficult to treat due to the blood‐brain barrier (BBB), which prevents many therapeutics from reaching the brain. Receptor‐mediated transcytosis (RMT) shows promise for transporting macromolecules across the BBB, but current targeting methods lack CNS specificity and cell‐type selectivity. The number of validated \"Portals\" (BBB receptors with demonstrated RMT in vivo) is limited due to historical screening constraints. Method We conducted the most comprehensive in vivo evaluation of BBB shuttles and Portals to date, screening over 3,000 candidates against 68 potential Portal targets in mice. Our novel pooled in vivo screening technology, mCodes™, allowed us to simultaneously assess quantitative tissue distribution for up to 100 molecules per animal with high precision. Result This approach revealed the \"Transcytosome,\" an expanded set of Portal targets capable of facilitating RMT across the BBB. Detailed pharmacokinetic and biodistribution analyses of select novel Portals demonstrate distinct properties compared to well‐characterized targets like transferrin receptor (TfR) and CD98. Novel portals were discovered that demonstrated optimal characteristics for therapeutic strategies targeting extracellular pathologies like Abeta, as well as intracellular pathologies like Tau. These portals offer promising avenues for further research and development in the pursuit of effective treatments for Alzheimer's disease. Conclusion These newly identified Portal receptors may enable unprecedented control over biodistribution, enhancing CNS delivery, cell‐type specificity, regional targeting, and reduced peripheral effects. By substantially expanding the known Portal landscape, our work provides a foundation for developing biologics with precisely engineered tissue distribution profiles that are sculpted to meet the intended product profiles for specific therapeutic approaches. The Transcytosome represents a crucial step toward realizing the full therapeutic potential of biologics in CNS diseases such as Alzheimer’s.

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.

Evolution has shown that mutation and selection over billions of years can produce complex molecules and organisms that thrive in a diverse range of environments. As biological engineers, we would like to systematize the navigation of genetic landscapes to find solutions to urgent health and technological needs. In this thesis, I approach the engineering of biological systems from the perspective of design. I illustrate the view of design as an iterative framework of satisfying engineering constraints while discovering and testing degrees of freedom in biological systems. Beginning at the genome scale, I describe a software framework for encoding design rules for recoding genomes and its application to the design of an E. coli strain using only 57 of 64 codons. The genome is being assembled and tested in 50-kilobase segments and we have verified that over 50% of the recoded genome design can functionally complement. Where design rules break down, we leverage DNA synthesis and genome editing to generate targeted diversity and update the design rules. Next, I describe how a model-guided approach that prioritizes mutations to test can augment adaptive laboratory evolution. A 63-codon genomically recoded organism that we previously engineered suffered from impaired fitness and we used our approach to discover a minimal set of high-impact edits that recover 59% of the fitness defect. Finally, I discuss ongoing work to augment design and evolution of proteins by training machine learning models that learn from and guide high-throughput mapping of fitness landscapes. I describe lessons learned in a proof-of-concept study mapping the fitness landscape of the green fluorescent protein and implications for engineering of other proteins. The unifying contribution of this dissertation is a demonstration at multiple scales of how to systematically integrate DNA synthesis, sequencing, high-throughput assays, and computational methods to interrogate biological systems and learn design principles that expand our engineering capabilities.