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Significance CRISPR-based gene drive systems—genetic elements which could be engineered to rapidly spread traits through wild populations—could help solve some of humanity’s greatest ecological and public health problems. However, if released, current versions might spread through a nontarget population—possibly across political borders—greatly complicating decision-making. To address this issue, we describe a self-exhausting form of CRISPR-based gene drive called a “daisy-chain drive.” We develop mathematical models which suggest that daisy-chain-drive systems will not spread indefinitely through successive populations, and we report numerous CRISPR targeting sequences which could offer enhanced stability. Particularly if combined with threshold dependence, daisy-drive approaches may become a foundational technique for local ecological engineering., If they are able to spread in wild populations, CRISPR-based gene-drive elements would provide new ways to address ecological problems by altering the traits of wild organisms, but the potential for uncontrolled spread tremendously complicates ethical development and use. Here, we detail a self-exhausting form of CRISPR-based drive system comprising genetic elements arranged in a daisy chain such that each drives the next. “Daisy-drive” systems can locally duplicate any effect achievable by using an equivalent self-propagating drive system, but their capacity to spread is limited by the successive loss of nondriving elements from one end of the chain. Releasing daisy-drive organisms constituting a small fraction of the local wild population can drive a useful genetic element nearly to local fixation for a wide range of fitness parameters without self-propagating spread. We additionally report numerous highly active guide RNA sequences sharing minimal homology that may enable evolutionarily stable daisy drive as well as self-propagating CRISPR-based gene drive. Especially when combined with threshold dependence, daisy drives could simplify decision-making and promote ethical use by enabling local communities to decide whether, when, and how to alter local ecosystems.

SummaryProtein translation using four-base codons occurs in both natural and synthetic systems. What constraints contributed to the universal adoption of a triplet-codon, rather than quadruplet-codon, genetic code? Here, we investigate the tolerance of the E. coli genetic code to tRNA mutations that increase codon size. We found that tRNAs from all twenty canonical isoacceptor classes can be converted to functional quadruplet tRNAs (qtRNAs), many of which selectively incorporate a single amino acid in response to a specified four-base codon. However, efficient quadruplet codon translation often requires multiple tRNA mutations, potentially constraining evolution. Moreover, while tRNAs were largely amenable to quadruplet conversion, only nine of the twenty aminoacyl tRNA synthetases tolerate quadruplet anticodons. These constitute a functional and mutually orthogonal set, but one that sharply limits the chemical alphabet available to a nascent all-quadruplet code. Our results illuminate factors that led to selection and maintenance of triplet codons in primordial Earth and provide a blueprint for synthetic biologists to deliberately engineer an all-quadruplet expanded genetic code.

Our understanding of complex living systems is limited by our capacity to perform experiments in high throughput. While robotic systems have automated many traditional hand‐pipetting protocols, software limitations have precluded more advanced maneuvers required to manipulate, maintain, and monitor hundreds of experiments in parallel. Here, we present Pyhamilton, an open‐source Python platform that can execute complex pipetting patterns required for custom high‐throughput experiments such as the simulation of metapopulation dynamics. With an integrated plate reader, we maintain nearly 500 remotely monitored bacterial cultures in log‐phase growth for days without user intervention by taking regular density measurements to adjust the robotic method in real‐time. Using these capabilities, we systematically optimize bioreactor protein production by monitoring the fluorescent protein expression and growth rates of a hundred different continuous culture conditions in triplicate to comprehensively sample the carbon, nitrogen, and phosphorus fitness landscape. Our results demonstrate that flexible software can empower existing hardware to enable new types and scales of experiments, empowering areas from biomanufacturing to fundamental biology., An open‐source Python platform enables advanced liquid handling robots to perform a variety of complex high‐throughput experiments that could never be performed manually.

Evolution occurs when selective pressures from the environment shape inherited variation over time. Within the laboratory, evolution is commonly used to engineer proteins and RNA, but experimental constraints have limited the ability to reproducibly and reliably explore factors such as population diversity, the timing of environmental changes and chance on outcomes. We developed a robotic system termed phage- and robotics-assisted near-continuous evolution (PRANCE) to comprehensively explore biomolecular evolution by performing phage-assisted continuous evolution in high-throughput. PRANCE implements an automated feedback control system that adjusts the stringency of selection in response to real-time measurements of each molecular activity. In evolving three distinct types of biomolecule, we find that evolution is reproducibly altered by both random chance and the historical pattern of environmental changes. This work improves the reliability of protein engineering and enables the systematic analysis of the historical, environmental and random factors governing biomolecular evolution.

Genetic code expansion technologies supplement the natural codon repertoire with assignable variants in vivo, but are often limited by heterologous translational components and low suppression efficiencies. Here, we explore engineered Escherichia coli tRNAs supporting quadruplet codon translation by first developing a library-cross-library selection to nominate quadruplet codon–anticodon pairs. We extend our findings using a phage-assisted continuous evolution strategy for quadruplet-decoding tRNA evolution (qtRNA-PACE) that improved quadruplet codon translation efficiencies up to 80-fold. Evolved qtRNAs appear to maintain codon-anticodon base pairing, are typically aminoacylated by their cognate tRNA synthetases, and enable processive translation of adjacent quadruplet codons. Using these components, we showcase the multiplexed decoding of up to four unique quadruplet codons by their corresponding qtRNAs in a single reporter. Cumulatively, our findings highlight how E. coli tRNAs can be engineered, evolved, and combined to decode quadruplet codons, portending future developments towards an exclusively quadruplet codon translation system., Genetic code expansion strategies are limited to specific codons that can be reassigned to new amino acids. Here the authors show that quadruplet-decoding tRNAs (qtRNAs) can be rapidly discovered and evolved to decode new quadruplet codons, enabling four independent decoding events in a single protein in living cells.

INTRODUCTIONLiquid handling robots have become a biotechnology staple1,2, allowing laborious or repetitive protocols to be executed in high-throughput. However, software narrowly designed to automate traditional hand-pipetting protocols often struggles to harness the full capabilities of robotic manipulation. Here we present Pyhamilton, an open-source Python package that eliminates these constraints, enabling experiments that could never be done by hand. We used Pyhamilton to double the speed of automated bacterial assays over current software and execute complex pipetting patterns to simulate population dynamics. Next, we incorporated feedback-control to maintain hundreds of remotely monitored bacterial cultures in log-phase growth without user intervention. Finally, we applied these capabilities to comprehensively optimize bioreactor protein production by maintaining and monitoring fluorescent protein expression of nearly 500 different continuous cultures to explore the carbon, nitrogen, and phosphorus fitness landscape. Our results demonstrate Pyhamilton’s empowerment of existing hardware to new applications ranging from biomanufacturing to fundamental biology.

It is straightforward to determine the size of the Earth and the distance to the Moon without making use of a telescope. The methods have been known since the 3rd century BC. However, few amateur or professional astronomers have worked this out from data they themselves have taken. Here we use a gnomon to determine the latitude and longitude of South Bend, Indiana, and College Station, Texas, and determine a value of the radius of the Earth of 6290 km, only 1.4 percent smaller than the true value. We use the method of Aristarchus and the size of the Earth's shadow during the lunar eclipse of 2011 June 15 to derive an estimate of the distance to the Moon (62.3 R_Earth), some 3.3 percent greater than the true mean value. We use measurements of the angular motion of the Moon against the background stars over the course of two nights, using a simple cross staff device, to estimate the Moon's distance at perigee and apogee. Finally, we use simultaneous CCD observations of asteroid 1996 HW1 obtained with small telescopes in Socorro, New Mexico, and Ojai, California, to derive a value of the Astronomical Unit of (1.59 +/- 0.19) X 10^8 km, about 6 percent too large. The data and methods presented here can easily become part of a beginning astronomy lab class., Comment: 34 pages, 11 figures, accepted for publication in American Journal of Physics

This research describes a prototype software navigation system that would allow a spacecraft with a small amount of continuous propulsion to navigate low-energy trajectories. First, the desired route is described in terms of basic orbit shapes, such as Lyapunov orbits. This sequence of orbit shapes is converted into an itinerary of spatial boundaries that a spacecraft executing the low-energy maneuver will cross in order.A software system then employs a guided optimization algorithm that identifies the thrust angle that will maintain the desired orbit. Using this software as a research tool, simulations have identified low-energy paths that could be used by a spacecraft with an ion drive to perform a Venus flyby within four or five years of its launch from Earth. This approach makes it possible to identify complex low-energy trajectories that rely on the gravitational effects of different two-body systems (for instance, Earth–moon and Earth–sun) and to study the utility of continuous propulsion in flying such trajectories from Earth.