Elizabeth A. Strychalski

Design and synthesis of a minimal bacterial genome

Designing and building a minimal genome A goal in biology is to understand the molecular and biological function of every gene in a cell. One way to approach this is to build a minimal genome that includes only the genes essential for life. In 2010, a 1079-kb genome based on the genome of Mycoplasma mycoides (JCV-syn1.0) was chemically synthesized and supported cell growth when transplanted into cytoplasm. Hutchison III et al. used a design, build, and test cycle to reduce this genome to 531 kb (473 genes). The resulting JCV-syn3.0 retains genes involved in key processes such as transcription and translation, but also contains 149 genes of unknown function. Science, this issue p. 10.1126/science.aad6253 Cycles of design, building, and testing produced a 531-kilobase genome comprising 473 genes. INTRODUCTION In 1984, the simplest cells capable of autonomous growth, the mycoplasmas, were proposed as models for understanding the basic principles of life. In 1995, we reported the first complete cellular genome sequences (Haemophilus influenza, 1815 genes, and Mycoplasma genitalium, 525 genes). Comparison of these sequences revealed a conserved core of about 250 essential genes, much smaller than either genome. In 1999, we introduced the method of global transposon mutagenesis and experimentally demonstrated that M. genitalium contains many genes that are nonessential for growth in the laboratory, even though it has the smallest genome known for an autonomously replicating cell found in nature. This implied that it should be possible to produce a minimal cell that is simpler than any natural one. Whole genomes can now be built from chemically synthesized oligonucleotides and brought to life by installation into a receptive cellular environment. We have applied whole-genome design and synthesis to the problem of minimizing a cellular genome. RATIONALE Since the first genome sequences, there has been much work in many bacterial models to identify nonessential genes and define core sets of conserved genetic functions, using the methods of comparative genomics. Often, more than one gene product can perform a particular essential function. In such cases, neither gene will be essential, and neither will necessarily be conserved. Consequently, these approaches cannot, by themselves, identify a set of genes that is sufficient to constitute a viable genome. We set out to define a minimal cellular genome experimentally by designing and building one, then testing it for viability. Our goal is a cell so simple that we can determine the molecular and biological function of every gene. RESULTS Whole-genome design and synthesis were used to minimize the 1079–kilobase pair (kbp) synthetic genome of M. mycoides JCVI-syn1.0. An initial design, based on collective knowledge of molecular biology in combination with limited transposon mutagenesis data, failed to produce a viable cell. Improved transposon mutagenesis methods revealed a class of quasi-essential genes that are needed for robust growth, explaining the failure of our initial design. Three more cycles of design, synthesis, and testing, with retention of quasi-essential genes, produced JCVI-syn3.0 (531 kbp, 473 genes). Its genome is smaller than that of any autonomously replicating cell found in nature. JCVI-syn3.0 has a doubling time of ~180 min, produces colonies that are morphologically similar to those of JCVI-syn1.0, and appears to be polymorphic when examined microscopically. CONCLUSION The minimal cell concept appears simple at first glance but becomes more complex upon close inspection. In addition to essential and nonessential genes, there are many quasi-essential genes, which are not absolutely critical for viability but are nevertheless required for robust growth. Consequently, during the process of genome minimization, there is a trade-off between genome size and growth rate. JCVI-syn3.0 is a working approximation of a minimal cellular genome, a compromise between small genome size and a workable growth rate for an experimental organism. It retains almost all the genes that are involved in the synthesis and processing of macromolecules. Unexpectedly, it also contains 149 genes with unknown biological functions, suggesting the presence of undiscovered functions that are essential for life. JCVI-syn3.0 is a versatile platform for investigating the core functions of life and for exploring whole-genome design. Four design-build-test cycles produced JCVI-syn3.0. (A) The cycle for genome design, building by means of synthesis and cloning in yeast, and testing for viability by means of genome transplantation. After each cycle, gene essentiality is reevaluated by global transposon mutagenesis. (B) Comparison of JCVI-syn1.0 (outer blue circle) with JCVI-syn3.0 (inner red circle), showing the division of each into eight segments. The red bars inside the outer circle indicate regions that are retained in JCVI-syn3.0

Genetic circuit design automation

Programming circuitry for synthetic biology As synthetic biology techniques become more powerful, researchers are anticipating a future in which the design of biological circuits will be similar to the design of integrated circuits in electronics. Nielsen et al. describe what is essentially a programming language to design computational circuits in living cells. The circuits generated on plasmids expressed in Escherichia coli required careful insulation from their genetic context, but primarily functioned as specified. The circuits could, for example, regulate cellular functions in response to multiple environmental signals. Such a strategy can facilitate the development of more complex circuits by genetic engineering. Science, this issue p. 10.1126/science.aac7341 A programming language is devised for biological regulatory circuits. INTRODUCTION Cells respond to their environment, make decisions, build structures, and coordinate tasks. Underlying these processes are computational operations performed by networks of regulatory proteins that integrate signals and control the timing of gene expression. Harnessing this capability is critical for biotechnology projects that require decision-making, control, sensing, or spatial organization. It has been shown that cells can be programmed using synthetic genetic circuits composed of regulators organized to generate a desired operation. However, the construction of even simple circuits is time-intensive and unreliable. RATIONALE Electronic design automation (EDA) was developed to aid engineers in the design of semiconductor-based electronics. In an effort to accelerate genetic circuit design, we applied principles from EDA to enable increased circuit complexity and to simplify the incorporation of synthetic gene regulation into genetic engineering projects. We used the hardware description language Verilog to enable a user to describe a circuit function. The user also specifies the sensors, actuators, and “user constraints file” (UCF), which defines the organism, gate technology, and valid operating conditions. Cello (www.cellocad.org) uses this information to automatically design a DNA sequence encoding the desired circuit. This is done via a set of algorithms that parse the Verilog text, create the circuit diagram, assign gates, balance constraints to build the DNA, and simulate performance. RESULTS Cello designs circuits by drawing upon a library of Boolean logic gates. Here, the gate technology consists of NOT/NOR logic based on repressors. Gate connection is simplified by defining the input and output signals as RNA polymerase (RNAP) fluxes. We found that the gates need to be insulated from their genetic context to function reliably in the context of different circuits. Each gate is isolated using strong terminators to block RNAP leakage, and input interchangeability is improved using ribozymes and promoter spacers. These parts are varied for each gate to avoid breakage due to recombination. Measuring the load of each gate and incorporating this into the optimization algorithms further reduces evolutionary pressure. Cello was applied to the design of 60 circuits for Escherichia coli, where the circuit function was specified using Verilog code and transformed to a DNA sequence. The DNA sequences were built as specified with no additional tuning, requiring 880,000 base pairs of DNA assembly. Of these, 45 circuits performed correctly in every output state (up to 10 regulators and 55 parts). Across all circuits, 92% of the 412 output states functioned as predicted. CONCLUSION Our work constitutes a hardware description language for programming living cells. This required the co-development of design algorithms with gates that are sufficiently simple and robust to be connected by automated algorithms. We demonstrate that engineering principles can be applied to identify and suppress errors that complicate the compositions of larger systems. This approach leads to highly repetitive and modular genetics, in stark contrast to the encoding of natural regulatory networks. The use of a hardware-independent language and the creation of additional UCFs will allow a single design to be transformed into DNA for different organisms, genetic endpoints, operating conditions, and gate technologies. Genetic programming using Cello. A user specifies the desired circuit function in Verilog code, and this is transformed into a DNA sequence. An example circuit is shown (0xF6); red and blue curves are predicted output states for populations of cells, and solid black distributions are experimental flow cytometry data. The outputs are shown for all combinations of sensor states; plus and minus signs indicate the presence or absence of input signal. RBS, ribosome binding site; RPU, relative promoter unit; YFP, yellow fluorescent protein. Computation can be performed in living cells by DNA-encoded circuits that process sensory information and control biological functions. Their construction is time-intensive, requiring manual part assembly and balancing of regulator expression. We describe a design environment, Cello, in which a user writes Verilog code that is automatically transformed into a DNA sequence. Algorithms build a circuit diagram, assign and connect gates, and simulate performance. Reliable circuit design requires the insulation of gates from genetic context, so that they function identically when used in different circuits. We used Cello to design 60 circuits for Escherichia coli (880,000 base pairs of DNA), for which each DNA sequence was built as predicted by the software with no additional tuning. Of these, 45 circuits performed correctly in every output state (up to 10 regulators and 55 parts), and across all circuits 92% of the output states functioned as predicted. Design automation simplifies the incorporation of genetic circuits into biotechnology projects that require decision-making, control, sensing, or spatial organization.

Microfluidic Analysis of Complex Samples with Minimal Sample Preparation Using Gradient Elution Moving Boundary Electrophoresis

Sample-in answer-out analytical tools remain the goal of much lab on a chip research, but miniaturized methods capable of examining minimally prepared samples have proven elusive. Complex samples, including whole milk, various types of dirt and leaves, coal fly ash, and blood serum, were analyzed quantitatively for dissolved potassium, calcium, sodium, magnesium, lithium, and melamine using gradient elution moving boundary electrophoresis (GEMBE) and contactless conductivity detection with the single preparatory step of dilution or suspension in sample buffer. GEMBE is a simple, robust analytical technique, well-suited to microfluidic analysis of complex samples containing material, such as particulates or proteins, that would confound the majority of other microfluidic techniques. GEMBE utilizes electrophoretic flow to drive electrically charged analytes into a microfluidic channel or capillary for detection, while opposing electro-osmotic and variable pressure-driven flows prevent the remainder of the sample from entering the channel. Contactless conductivity detection further simplifies device construction and operation, positioning GEMBE for inexpensive and facile multiplexed implementation outside laboratory settings.

Expanding the capabilities of microfluidic gradient elution moving boundary electrophoresis for complex samples.

Gradient elution moving boundary electrophoresis (GEMBE) is a robust, continuous injection separation technique that uses electrophoresis to drive electrically charged analytes into a capillary or microfluidic channel for detection, while opposing electroosmosis and controlled variable pressure-driven flow prevent other sample components-for example, cells, proteins, or particulates in complex samples that can interfere with analysis-from entering the channel. This work expands the sample-in/answer-out analytical capabilities of GEMBE for complex samples by demonstrating the quantitative analysis of anions, implementing aqueous background electrolyte (BGE) solutions at neutral pH, and introducing the use of additives to the sample solution to optimize performance. Dirt was analyzed quantitatively, with the sole preparatory step of suspension in an aqueous BGE solution at neutral pH, for dissolved chloride, nitrite, nitrate, sulfate, and oxalate using GEMBE with capacitively-coupled contactless conductivity detection. In addition to altering the pH of the BGE solution, optimization of the analysis of dirt and whole blood was achieved using various commercially available additives. These results, taken together with previous demonstrations of GEMBE for the analysis of complex samples, underscore the uncomplicated versatility of GEMBE, facilitate effective analysis of biological complex samples using BGE solutions at physiological pH, and offer a sufficient set of techniques and tools to build a foundation for the analysis of a broad range of complex samples.

DNA purification from crude samples for human identification using gradient elution isotachophoresis

Gradient elution isotachophoresis (GEITP) was demonstrated for DNA purification, concentration, and quantification from crude samples, represented here by soiled buccal swabs, with minimal sample preparation prior to human identification using STR analysis. During GEITP, an electric field applied across leading and trailing electrolyte solutions resulted in isotachophoretic focusing of DNA at the interface between these solutions, while a pressure‐driven counterflow controlled the movement of the interface from the sample reservoir into a microfluidic capillary. This counterflow also prevented particulates from fouling or clogging the capillary and reduced or eliminated contamination of the delivered DNA by PCR inhibitors. On‐line DNA quantification using laser‐induced fluorescence compared favorably with quantitative PCR measurements and potentially eliminates the need for quantitative PCR prior to STR analysis. GEITP promises to address the need for a rapid and robust method to deliver DNA from crude samples to aid the forensic community in human identification.