Synthetic Biology | Genomics | Biotechnology
	Farren Isaacs, Ph.D. Molecular, Cellular & Developmental Biology; Yale Systems Biology Institute Room: KBT 802; B-31, Room 319 Phone: 203.737.3156 Email: farren.isaacs@yale.edu Lab Website B.S.E., University of Pennsylvania; Ph.D., Boston University

Advances in high-throughput biology and biotechnology have led to an array of biological insights in medicine, agriculture, evolutionary biology and studies of diverse organisms. Harnessing the potential of species diversity makes biological systems ideal to address global challenges, such as producing new drugs to alleviate human disease and generating biologically derived fuels, chemicals and materials to ensure environmental sustainability. In addition to a thorough understanding of biological systems, achieving these goals requires safe and programmable control of biological systems. In this regard, our ability to measure and modify genetic and biochemical components and understand their interactions in pathways, cells and the environment remain defining challenges.

We are focused on developing foundational cellular and biomolecular engineering technologies to understand and engineer biological systems. Our approach is designed to integrate engineering and evolution through the construction of genes, networks and whole genomes alongside quantitative models to gain a better understanding of whole biological systems. In turn, we utilize these insights to design and evolve organisms with new and desired function. We seek to uncover new properties of biological systems and generate new phenotypes with the ultimate goal of applying these insights to address global challenges in medicine, energy supply and the environment.

Engineering and Evolving Biology. An integrated approach to better understand, engineer and harness biological systems.

	MAGE: Multiplex automated genome engineering enables the rapid and continuous generation of sequence diversity at many targeted chromosomal locations across a large population of cells through the repeated introduction of synthetic DNA.

Genome engineering
With the advent of next-generation DNA sequencing, our ability to sequence genomes has greatly outpaced our ability to modify genomes. One of the key cellular engineering challenges is the development of high-throughput and automated methodologies for precise manipulation of genomes from the nucleotide to megabase scales. To address these challenges, we develop methods for versatile genome modification and evolution of cells. Multiplex Automated Genome Engineering (MAGE) simultaneously targets many locations on the chromosome for modification in a single cell or across a population of cells, thus producing combinatorial genomic diversity. Hierarchical Conjugative Assembly Genome Engineering (CAGE) facilitates the large-scale assembly of many modified genomes. These methods are broadly being used to program new cellular function. Areas of research include the generation of genetic diversity for strain and pathway engineering and the construction of organisms with new genetic codes.

	Engineered Riboregulation. The engineered riboregulation system contains a short sequence (cis-repressed, cr, red) inserted downstream of a promoter (Pcr) and upstream of the ribosome binding site (RBS. blue). Following transcription, the cr sequence, which is complementary to the RBS, drives the formation of a stem-loop in the 5'-UTR that prevents ribosome docking and represses translation (cis-repression). The resulting mRNA is referred to as cis-repressed RNA (crRNA). A second independent promoter (Pta) is responsible for the transcription of a small, noncoding RNA (trans-activating RNA, taRNA), which targets its cognate crRNA with high specificity. The subsequent RNA-RNA linear-loop interaction promotes structural rearrangement of the crRNA, thus exposing the obstructed RBS and enabling translation.

Engineered RNAs
Our ability to measure changes in the cellular environment and, in turn, probe and regulate genetic, biochemical or metabolic components remain critical challenges in biology. Exploiting the structural and functional diversity of RNA molecules, we design and construct RNA-based systems that can be integrated into biological networks to address such challenges. For example, post-transcriptional regulatory systems have been constructed from highly specific RNA molecules that can function with any promoter or gene to directly control gene expression in response to specific biomolecules or chemical inputs. These engineered riboregulators serve as modular, RNA-based elements in genetic circuits to control and study gene regulation. The design of such functional RNA-based networks could lead to new modes of cellular control and new classes of in vivo probes and sensors that are scalable and applicable to many organisms.

Computational insights to uncover & program complex biological behavior
To complement our experiments in genome and RNA engineering, we apply computational studies to reveal insights and design principles of natural and synthetic biological systems. We develop systems-specific models both to guide experimental design and for detailed quantitative comparisons of targeted pathways, genomes and cell populations. Such integrated approaches could lead to refined descriptions of network-cell behavior and ultimately lead to the elucidation of the organization and functioning of natural and engineered biological systems.

Selected Publications

Precise Manipulation of Chromosomes in vivo enables genome-wide codon replacement. F. Isaacs*, P. Carr*, H. Wang*, et. al. (in revision).

Programming Cells by Multiplex Genome Engineering and Accelerated Evolution. H. Wang*, F. Isaacs*, P. Carr, Z. Peng, G. Xu, C. Forest, G. Church. Nature 460(7257):894-8 (2009).

RNA Synthetic Biology. F. Isaacs, D. Dwyer and J. Collins. Nature Biotechnology 24:545-554 (2006).

Engineered Riboregulators Enable Post-Transcriptional Control of Gene Expression. F. Isaacs, D. Dwyer, C. Ding, D. Pervouchine, C. Cantor and J. Collins. Nature Biotechnology 22: 841-847 (2004).

Prediction and Measurement of an Autoregulatory Genetic Module. F. Isaacs*, J. Hasty*, C. Cantor and J. Collins. Proceedings of the National Academy of Sciences USA 100:7714-7719 (2003).

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