Erratum: Correction Notice: Single-step Precision Genome Editing in Yeast Using CRISPR-Cas9.

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A highly parallel strategy for storage of digital information in living cells.

BACKGROUND: Encoding arbitrary digital information in DNA has attracted attention as a potential avenue for large scale and long term data storage. However, in order to enable DNA data storage technologies there needs to be improvements in data storage fidelity (tolerance to mutation), the facility of writing and reading the data (biases and systematic error arising from synthesis and sequencing), and overall scalability. RESULTS: To this end, we have developed and implemented an encoding scheme that is suitable for detecting and correcting errors that may arise during storage, writing, and reading, such as those arising from nucleotide substitutions, insertions, and deletions. We propose a scheme for parallelized long term storage of encoded sequences that relies on overlaps rather than the address blocks found in previously published work. Using computer simulations, we illustrate the encoding, sequencing, decoding, and recovery of encoded information, ultimately demonstrating the possibility of a successful round-trip read/write. These demonstrations show that in theory a precise control over error tolerance is possible. Even after simulated degradation of DNA, recovery of original data is possible owing to the error correction capabilities built into the encoding strategy. A secondary advantage of our method is that the statistical characteristics (such as repetitiveness and GC-composition) of encoded sequences can also be tailored without sacrificing the overall ability to store large amounts of data. Finally, the combination of the overlap-based partitioning of data with the LZMA compression that is integral to encoding means that the entire sequence must be present for successful decoding. This feature enables inordinately strong encryptions. As a potential application, an encrypted pathogen genome could be distributed and carried by cells without danger of being expressed, and could not even be read out in the absence of the entire DNA consortium. CONCLUSIONS: We have developed a method for DNA encoding, using a significantly different fundamental approach from existing work, which often performs better than alternatives and allows for a great deal of freedom and flexibility of application.

Single-step Precision Genome Editing in Yeast Using CRISPR-Cas9.

Genome modification in budding yeast has been extremely successful largely due to its highly efficient homology-directed DNA repair machinery. Several methods for modifying the yeast genome have previously been described, many of them involving at least two-steps: insertion of a selectable marker and substitution of that marker for the intended modification. Here, we describe a CRISPR-Cas9 mediated genome editing protocol for modifying any yeast gene of interest (either essential or nonessential) in a single-step transformation without any selectable marker. In this system, the Cas9 nuclease creates a double-stranded break at the locus of choice, which is typically lethal in yeast cells regardless of the essentiality of the targeted locus due to inefficient non-homologous end-joining repair. This lethality results in efficient repair via homologous recombination using a repair template derived from PCR. In cases involving essential genes, the necessity of editing the genomic lesion with a functional allele serves as an additional layer of selection. As a motivating example, we describe the use of this strategy in the replacement of HEM2, an essential yeast gene, with its corresponding human ortholog ALAD.

Systematic bacterialization of yeast genes identifies a near-universally swappable pathway.

Eukaryotes and prokaryotes last shared a common ancestor ~2 billion years ago, and while many present-day genes in these lineages predate this divergence, the extent to which these genes still perform their ancestral functions is largely unknown. To test principles governing retention of ancient function, we asked if prokaryotic genes could replace their essential eukaryotic orthologs. We systematically replaced essential genes in yeast by their 1:1 orthologs from Escherichia coli. After accounting for mitochondrial localization and alternative start codons, 31 out of 51 bacterial genes tested (61%) could complement a lethal growth defect and replace their yeast orthologs with minimal effects on growth rate. Replaceability was determined on a pathway-by-pathway basis; codon usage, abundance, and sequence similarity contributed predictive power. The heme biosynthesis pathway was particularly amenable to inter-kingdom exchange, with each yeast enzyme replaceable by its bacterial, human, or plant ortholog, suggesting it as a near-universally swappable pathway.

Target-independent prediction of drug synergies using only drug lipophilicity.

Physicochemical properties of compounds have been instrumental in selecting lead compounds with increased drug-likeness. However, the relationship between physicochemical properties of constituent drugs and the tendency to exhibit drug interaction has not been systematically studied. We assembled physicochemical descriptors for a set of antifungal compounds ("drugs") previously examined for interaction. Analyzing the relationship between molecular weight, lipophilicity, H-bond donor, and H-bond acceptor values for drugs and their propensity to show pairwise antifungal drug synergy, we found that combinations of two lipophilic drugs had a greater tendency to show drug synergy. We developed a more refined decision tree model that successfully predicted drug synergy in stringent cross-validation tests based on only lipophilicity of drugs. Our predictions achieved a precision of 63% and allowed successful prediction for 58% of synergistic drug pairs, suggesting that this phenomenon can extend our understanding for a substantial fraction of synergistic drug interactions. We also generated and analyzed a large-scale synergistic human toxicity network, in which we observed that combinations of lipophilic compounds show a tendency for increased toxicity. Thus, lipophilicity, a simple and easily determined molecular descriptor, is a powerful predictor of drug synergy. It is well established that lipophilic compounds (i) are promiscuous, having many targets in the cell, and (ii) often penetrate into the cell via the cellular membrane by passive diffusion. We discuss the positive relationship between drug lipophilicity and drug synergy in the context of potential drug synergy mechanisms.