RNA-guided gene drive elements could address many ecological problems by altering the traits of wild organisms, but the likelihood of global spread tremendously complicates ethical development and use. Here we detail a localized form of CRISPR-based gene drive composed of genetic elements arranged in a daisy-chain such that each element drives the next. "Daisy drive" systems can duplicate any effect achievable using an equivalent global drive system, but their capacity to spread is limited by the successive loss of non-driving elements from the base of the chain. Releasing daisy drive organisms constituting a small fraction of the local wild population can drive a useful genetic element to local fixation for a wide range of fitness parameters without resulting in global spread. We additionally report numerous highly active guide RNA sequences sharing minimal homology that may enable evolutionary stable daisy drive as well as global CRISPR-based gene drive. Daisy drives could simplify decision-making and promote ethical use by enabling local communities to decide whether, when, and how to alter local ecosystems.

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.

The exponential increase in data over the last decade presents a significant challenge to analytics efforts that seek to process and interpret such data for various applications. Neural-inspired computing approaches are being developed in order to leverage the computational properties of the analog, low-power data processing observed in biological systems. Analog resistive memory crossbars can perform a parallel read or a vector-matrix multiplication as well as a parallel write or a rank-1 update with high computational efficiency. For an N × N crossbar, these two kernels can be O(N) more energy efficient than a conventional digital memory-based architecture. If the read operation is noise limited, the energy to read a column can be independent of the crossbar size (O(1)). These two kernels form the basis of many neuromorphic algorithms such as image, text, and speech recognition. For instance, these kernels can be applied to a neural sparse coding algorithm to give an O(N) reduction in energy for the entire algorithm when run with finite precision. Sparse coding is a rich problem with a host of applications including computer vision, object tracking, and more generally unsupervised learning.

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.

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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 opensource 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.

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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 Escherichia 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 these selectively incorporate a single amino acid in response to a specified four-base codon, as confirmed with mass spectrometry. However, efficient quadruplet codon translation often requires multiple tRNA mutations. Moreover, while tRNAs were largely amenable to quadruplet conversion, only nine of the twenty aminoacyl tRNA synthetases tolerate quadruplet anticodons. These may constitute a functional and mutually orthogonal set, but one that sharply limits the chemical alphabet available to a nascent all-quadruplet code. Our results suggest that the triplet codon code was selected because it is simpler and sufficient, not because a quadruplet codon code is unachievable. These data provide a blueprint for synthetic biologists to deliberately engineer an all-quadruplet expanded genetic code.