Biology subjects

Farzadfard, F.

Publications and source records attributed to Farzadfard, F..

3 recordsLinked to original sources

bioRxiv2020

High throughput functional variant screens via in-vivo production of single-stranded DNA

Tremendous genetic variation exists in nature, but our ability to create and characterize individual genetic variants remains far more limited in scale. Likewise, engineering proteins and phenotypes requires the introduction of synthetic variants, but design of variants outpaces experimental measurement of variant effect. Here, we optimize efficient and continuous generation of precise genomic edits in Escherichia coli, via in-vivo production of single-stranded DNA by the targeted reverse-transcription activity of retrons. Greater than 90% editing efficiency can be obtained using this method, enabling multiplexed applications. We introduce Retron Library Recombineering (RLR), a system for high-throughput screens of variants, wherein the association of introduced edits with their retron elements enables a targeted deep sequencing phenotypic output. We use RLR for pooled, quantitative phenotyping of synthesized variants, characterizing antibiotic resistance alleles. We also perform RLR using sheared genomic DNA of an evolved bacterium, experimentally querying millions of sequences for antibiotic resistance variants. In doing so, we demonstrate that RLR is uniquely suited to utilize non-designed sources of variation. Pooled experiments using ssDNA produced in vivo thus present new avenues for exploring variation, both designed and not, across the entire genome.

synthetic biology↗

bioRxiv2020

Efficient Retroelement-Mediated DNA Writing in Bacteria

The ability to efficiently and dynamically change information stored in genomes would enable powerful strategies for studying cell biology and controlling cellular phenotypes. Current recombineering-mediated DNA writing platforms in bacteria are limited to specific laboratory conditions, often suffer from suboptimal editing efficiencies, and are not suitable for in situ applications. To overcome these limitations, we engineered a retroelement-mediated DNA writing system that enables efficient and precise editing of bacterial genomes without the requirement for target-specific elements or selection. We demonstrate that this DNA writing platform enables a broad range of applications, including efficient, scarless, and cis-element-independent editing of targeted microbial genomes within complex communities, the high-throughput mapping of spatial information and cellular interactions into DNA memory, and the continuous evolution of cellular traits. One Sentence SummaryHighly-efficient, dynamic, and conditional genome writers are engineered for DNA memory, genome engineering, editing microbial communities, high-resolution mapping of cellular connectomes, and modulating cellular evolution.

synthetic biology↗

bioRxiv2018

Single-Nucleotide-Resolution Computing and Memory in Living Cells

Computing and memory in living cells are central to encoding next-generation therapies and studying in situ biology, but existing strategies have limited encoding capacity and are challenging to scale. To overcome this bottleneck, we developed a highly scalable, robust and compact platform for encoding logic and memory operations in living bacterial and human cells. This platform, named DOMINO for DNA-based Ordered Memory and Iteration Network Operator, converts DNA in living cells into an addressable, readable, and writable computation and storage medium via a single-nucleotide resolution read-write head that enables dynamic and highly efficient DNA manipulation. We demonstrate that the order and combination of DNA writing events can be programmed by biological cues and multiple molecular recorders can be coordinated to encode a wide range of order-independent, sequential, and temporal logic and memory operations. Furthermore, we show that these operators can be used to perform both digital and analog computation, and record signaling dynamics and cellular states in a long-term, autonomous, and minimally disruptive fashion. Finally, we show that the platform can be functionalized with gene regulatory modules and interfaced with cellular circuits to continuously monitor cellular phenotypes and engineer gene circuits with artificial learning capacities. We envision that highly scalable, compact, and modular DOMINO operators will lay the foundation for building robust and sophisticated synthetic gene circuits for numerous biotechnological and biomedical applications.\n\nOne Sentence SummaryA programmable read-write head with single-nucleotide-resolution for genomic DNA enables robust and scalable computing and memory operations in living cells.

synthetic biology↗