The genotype-phenotype landscape of an allosteric protein.

Allostery is a fundamental biophysical mechanism that underlies cellular sensing, signaling, and metabolism. Yet a quantitative understanding of allosteric genotype-phenotype relationships remains elusive. Here, we report the large-scale measurement of the genotype-phenotype landscape for an allosteric protein: the lac repressor from Escherichia coli, LacI. Using a method that combines long-read and short-read DNA sequencing, we quantitatively measure the dose-response curves for nearly 105 variants of the LacI genetic sensor. The resulting data provide a quantitative map of the effect of amino acid substitutions on LacI allostery and reveal systematic sequence-structure-function relationships. We find that in many cases, allosteric phenotypes can be quantitatively predicted with additive or neural-network models, but unpredictable changes also occur. For example, we were surprised to discover a new band-stop phenotype that challenges conventional models of allostery and that emerges from combinations of nearly silent amino acid substitutions.

Genome-wide engineering of an infectious clone of herpes simplex virus type 1 using synthetic genomics assembly methods.

Here, we present a transformational approach to genome engineering of herpes simplex virus type 1 (HSV-1), which has a large DNA genome, using synthetic genomics tools. We believe this method will enable more rapid and complex modifications of HSV-1 and other large DNA viruses than previous technologies, facilitating many useful applications. Yeast transformation-associated recombination was used to clone 11 fragments comprising the HSV-1 strain KOS 152 kb genome. Using overlapping sequences between the adjacent pieces, we assembled the fragments into a complete virus genome in yeast, transferred it into an Escherichia coli host, and reconstituted infectious virus following transfection into mammalian cells. The virus derived from this yeast-assembled genome, KOSYA, replicated with kinetics similar to wild-type virus. We demonstrated the utility of this modular assembly technology by making numerous modifications to a single gene, making changes to two genes at the same time and, finally, generating individual and combinatorial deletions to a set of five conserved genes that encode virion structural proteins. While the ability to perform genome-wide editing through assembly methods in large DNA virus genomes raises dual-use concerns, we believe the incremental risks are outweighed by potential benefits. These include enhanced functional studies, generation of oncolytic virus vectors, development of delivery platforms of genes for vaccines or therapy, as well as more rapid development of countermeasures against potential biothreats.

Simultaneous non-contiguous deletions using large synthetic DNA and site-specific recombinases.

Toward achieving rapid and large scale genome modification directly in a target organism, we have developed a new genome engineering strategy that uses a combination of bioinformatics aided design, large synthetic DNA and site-specific recombinases. Using Cre recombinase we swapped a target 126-kb segment of the Escherichia coli genome with a 72-kb synthetic DNA cassette, thereby effectively eliminating over 54 kb of genomic DNA from three non-contiguous regions in a single recombination event. We observed complete replacement of the native sequence with the modified synthetic sequence through the action of the Cre recombinase and no competition from homologous recombination. Because of the versatility and high-efficiency of the Cre-lox system, this method can be used in any organism where this system is functional as well as adapted to use with other highly precise genome engineering systems. Compared to present-day iterative approaches in genome engineering, we anticipate this method will greatly speed up the creation of reduced, modularized and optimized genomes through the integration of deletion analyses data, transcriptomics, synthetic biology and site-specific recombination.

Automation protocol for high-efficiency and high-quality genomic DNA extraction from Saccharomyces cerevisiae.

Although many protocols have been previously developed for genomic DNA (gDNA) extraction from S. cerevisiae, to take advantage of recent advances in laboratory automation and DNA-barcode sequencing, there is a need for automated methods that can provide high-quality gDNA at high efficiency. Here, we describe and demonstrate a fully automated protocol that includes five basic steps: cell wall and RNA digestion, cell lysis, DNA binding to magnetic beads, washing with ethanol, and elution. Our protocol avoids the use of hazardous reagents (e.g., phenol, chloroform), glass beads for mechanical cell disruption, or incubation of samples at 100°C (i.e., boiling). We show that our protocol can extract gDNA with high efficiency both from cells grown in liquid culture and from colonies grown on agar plates. We also show results from gel electrophoresis that demonstrate that the resulting gDNA is of high quality.

Precision engineering of biological function with large-scale measurements and machine learning.

As synthetic biology expands and accelerates into real-world applications, methods for quantitatively and precisely engineering biological function become increasingly relevant. This is particularly true for applications that require programmed sensing to dynamically regulate gene expression in response to stimuli. However, few methods have been described that can engineer biological sensing with any level of quantitative precision. Here, we present two complementary methods for precision engineering of genetic sensors: in silico selection and machine-learning-enabled forward engineering. Both methods use a large-scale genotype-phenotype dataset to identify DNA sequences that encode sensors with quantitatively specified dose response. First, we show that in silico selection can be used to engineer sensors with a wide range of dose-response curves. To demonstrate in silico selection for precise, multi-objective engineering, we simultaneously tune a genetic sensor's sensitivity (EC50) and saturating output to meet quantitative specifications. In addition, we engineer sensors with inverted dose-response and specified EC50. Second, we demonstrate a machine-learning-enabled approach to predictively engineer genetic sensors with mutation combinations that are not present in the large-scale dataset. We show that the interpretable machine learning results can be combined with a biophysical model to engineer sensors with improved inverted dose-response curves.

Cloning whole bacterial genomes in yeast.

Most microbes have not been cultured, and many of those that are cultivatable are difficult, dangerous or expensive to propagate or are genetically intractable. Routine cloning of large genome fractions or whole genomes from these organisms would significantly enhance their discovery and genetic and functional characterization. Here we report the cloning of whole bacterial genomes in the yeast Saccharomyces cerevisiae as single-DNA molecules. We cloned the genomes of Mycoplasma genitalium (0.6 Mb), M. pneumoniae (0.8 Mb) and M. mycoides subspecies capri (1.1 Mb) as yeast circular centromeric plasmids. These genomes appear to be stably maintained in a host that has efficient, well-established methods for DNA manipulation.

Best Practices for DNA Template Preparation Toward Improved Reproducibility in Cell-Free Protein Production.

Performance variability is a common challenge in cell-free protein production and hinders a wider adoption of these systems for both research and biomanufacturing. While the inherent stochasticity and complexity of biology likely contributes to variability, other systematic factors may also play a role, including the source and preparation of the cell extract, the composition of the supplemental reaction buffer, the facility at which experiments are conducted, and the human operator (Cole et al. ACS Synth Biol 8:2080-2091, 2019). Variability in protein production could also arise from differences in the DNA template-specifically the amount of functional DNA added to a cell-free reaction and the quality of the DNA preparation in terms of contaminants and strand breakage. Here, we present protocols and suggest best practices optimized for DNA template preparation and quantitation for cell-free systems toward reducing variability in cell-free protein production.

Effects of DNA template preparation on variability in cell-free protein production.

DNA templates for protein production remain an unexplored source of variability in the performance of cell-free expression (CFE) systems. To characterize this variability, we investigated the effects of two common DNA extraction methodologies, a postprocessing step and manual versus automated preparation on protein production using CFE. We assess the concentration of the DNA template, the quality of the DNA template in terms of physical damage and the quality of the DNA solution in terms of purity resulting from eight DNA preparation workflows. We measure the variance in protein titer and rate of protein production in CFE reactions associated with the biological replicate of the DNA template, the technical replicate DNA solution prepared with the same workflow and the measurement replicate of nominally identical CFE reactions. We offer practical guidance for preparing and characterizing DNA templates to achieve acceptable variability in CFE performance.

Multicolor plate reader fluorescence calibration.

Plate readers are commonly used to measure cell growth and fluorescence, yet the utility and reproducibility of plate reader data is limited by the fact that it is typically reported in arbitrary or relative units. We have previously established a robust serial dilution protocol for calibration of plate reader measurements of absorbance to estimated bacterial cell count and for green fluorescence from proteins expressed in bacterial cells to molecules of equivalent fluorescein. We now extend these protocols to calibration of red fluorescence to the sulforhodamine-101 fluorescent dye and blue fluorescence to Cascade Blue. Evaluating calibration efficacy via an interlaboratory study, we find that these calibrants do indeed provide comparable precision to the prior calibrants and that they enable effective cross-laboratory comparison of measurements of red and blue fluorescence from proteins expressed in bacterial cells.

Single-cell measurement of plasmid copy number and promoter activity.

Accurate measurements of promoter activities are crucial for predictably building genetic systems. Here we report a method to simultaneously count plasmid DNA, RNA transcripts, and protein expression in single living bacteria. From these data, the activity of a promoter in units of RNAP/s can be inferred. This work facilitates the reporting of promoters in absolute units, the variability in their activity across a population, and their quantitative toll on cellular resources, all of which provide critical insights for cellular engineering.

Comparison of bias and resolvability in single-cell and single-transcript methods.

Single-cell and single-transcript measurement methods have elevated our ability to understand and engineer biological systems. However, defining and comparing performance between methods remains a challenge, in part due to the confounding effects of experimental variability. Here, we propose a generalizable framework for performing multiple methods in parallel using split samples, so that experimental variability is shared between methods. We demonstrate the utility of this framework by performing 12 different methods in parallel to measure the same underlying reference system for cellular response. We compare method performance using quantitative evaluations of bias and resolvability. We attribute differences in method performance to steps along the measurement process such as sample preparation, signal detection, and choice of measurand. Finally, we demonstrate how this framework can be used to benchmark different methods for single-transcript detection. The framework we present here provides a practical way to compare performance of any methods.

Cloning, Assembly, and Modification of the Primary Human Cytomegalovirus Isolate Toledo by Yeast-Based Transformation-Associated Recombination.

Genetic engineering of cytomegalovirus (CMV) currently relies on generating a bacterial artificial chromosome (BAC) by introducing a bacterial origin of replication into the viral genome using in vivo recombination in virally infected tissue culture cells. However, this process is inefficient, results in adaptive mutations, and involves deletion of viral genes to avoid oversized genomes when inserting the BAC cassette. Moreover, BAC technology does not permit the simultaneous manipulation of multiple genome loci and cannot be used to construct synthetic genomes. To overcome these limitations, we adapted synthetic biology tools to clone CMV genomes in Saccharomyces cerevisiae. Using an early passage of the human CMV isolate Toledo, we first applied transformation-associated recombination (TAR) to clone 16 overlapping fragments covering the entire Toledo genome in Saccharomyces cerevisiae. Then, we assembled these fragments by TAR in a stepwise process until the entire genome was reconstituted in yeast. Since next-generation sequence analysis revealed that the low-passage-number isolate represented a mixture of parental and fibroblast-adapted genomes, we selectively modified individual DNA fragments of fibroblast-adapted Toledo (Toledo-F) and again used TAR assembly to recreate parental Toledo (Toledo-P). Linear, full-length HCMV genomes were transfected into human fibroblasts to recover virus. Unlike Toledo-F, Toledo-P displayed characteristics of primary isolates, including broad cellular tropism in vitro and the ability to establish latency and reactivation in humanized mice. Our novel strategy thus enables de novo cloning of CMV genomes, more-efficient genome-wide engineering, and the generation of viral genomes that are partially or completely derived from synthetic DNA. IMPORTANCE The genomes of large DNA viruses, such as human cytomegalovirus (HCMV), are difficult to manipulate using current genetic tools, and at this time, it is not possible to obtain, molecular clones of CMV without extensive tissue culture. To overcome these limitations, we used synthetic biology tools to capture genomic fragments from viral DNA and assemble full-length genomes in yeast. Using an early passage of the HCMV isolate Toledo containing a mixture of wild-type and tissue culture-adapted virus. we directly cloned the majority sequence and recreated the minority sequence by simultaneous modification of multiple genomic regions. Thus, our novel approach provides a paradigm to not only efficiently engineer HCMV and other large DNA viruses on a genome-wide scale but also facilitates the cloning and genetic manipulation of primary isolates and provides a pathway to generating entirely synthetic genomes.

Synthetic generation of influenza vaccine viruses for rapid response to pandemics.

During the 2009 H1N1 influenza pandemic, vaccines for the virus became available in large quantities only after human infections peaked. To accelerate vaccine availability for future pandemics, we developed a synthetic approach that very rapidly generated vaccine viruses from sequence data. Beginning with hemagglutinin (HA) and neuraminidase (NA) gene sequences, we combined an enzymatic, cell-free gene assembly technique with enzymatic error correction to allow rapid, accurate gene synthesis. We then used these synthetic HA and NA genes to transfect Madin-Darby canine kidney (MDCK) cells that were qualified for vaccine manufacture with viral RNA expression constructs encoding HA and NA and plasmid DNAs encoding viral backbone genes. Viruses for use in vaccines were rescued from these MDCK cells. We performed this rescue with improved vaccine virus backbones, increasing the yield of the essential vaccine antigen, HA. Generation of synthetic vaccine seeds, together with more efficient vaccine release assays, would accelerate responses to influenza pandemics through a system of instantaneous electronic data exchange followed by real-time, geographically dispersed vaccine production.

Creating bacterial strains from genomes that have been cloned and engineered in yeast.

We recently reported the chemical synthesis, assembly, and cloning of a bacterial genome in yeast. To produce a synthetic cell, the genome must be transferred from yeast to a receptive cytoplasm. Here we describe methods to accomplish this. We cloned a Mycoplasma mycoides genome as a yeast centromeric plasmid and then transplanted it into Mycoplasma capricolum to produce a viable M. mycoides cell. While in yeast, the genome was altered by using yeast genetic systems and then transplanted to produce a new strain of M. mycoides. These methods allow the construction of strains that could not be produced with genetic tools available for this bacterium.

Genome transplantation in bacteria: changing one species to another.

As a step toward propagation of synthetic genomes, we completely replaced the genome of a bacterial cell with one from another species by transplanting a whole genome as naked DNA. Intact genomic DNA from Mycoplasma mycoides large colony (LC), virtually free of protein, was transplanted into Mycoplasma capricolum cells by polyethylene glycol-mediated transformation. Cells selected for tetracycline resistance, carried by the M. mycoides LC chromosome, contain the complete donor genome and are free of detectable recipient genomic sequences. These cells that result from genome transplantation are phenotypically identical to the M. mycoides LC donor strain as judged by several criteria.

Essential genes of a minimal bacterium.

Mycoplasma genitalium has the smallest genome of any organism that can be grown in pure culture. It has a minimal metabolism and little genomic redundancy. Consequently, its genome is expected to be a close approximation to the minimal set of genes needed to sustain bacterial life. Using global transposon mutagenesis, we isolated and characterized gene disruption mutants for 100 different nonessential protein-coding genes. None of the 43 RNA-coding genes were disrupted. Herein, we identify 382 of the 482 M. genitalium protein-coding genes as essential, plus five sets of disrupted genes that encode proteins with potentially redundant essential functions, such as phosphate transport. Genes encoding proteins of unknown function constitute 28% of the essential protein-coding genes set. Disruption of some genes accelerated M. genitalium growth.