Decoding and Repairing Genetic Disease

Decoding human genetic disease allows us to develop models of the pathology that can be directly tested with gene correction or targeted drug therapy. Dominant negative mutations are particularly promising therapeutic targets since they are resistant to traditional therapies, yet precise excision of disease-causing allele could provide a cure. We are using patient-derived induced pluripotent stem cells (iPSCs) to model diseases in tissues that are particularly susceptible to dominant negative mutations: cardiomyocytes, motor neurons and retinal pigment epithelial (RPE) cells. By developing CRISPR genome surgery in human cells, we hope to devise improved cellular models as well as human therapies.

Stem cell models of genome surgery: By focusing on allele-specific gene excision we can select gene mutations that are highly penetrant, with clear phenotypes in cell types that can be readily derived from iPSCs. We use whole genome sequencing to identify common genetic polymorphisms that can be used to selectively inactivate the disease allele with CRISPR nucleases. The diseased cell types allow us to decode the cellular signatures of disease and determine if the excision of the disease allele restores cellular functioning. Genome surgery is a rapidly advancing field that uses state-of-the-art techniques that pushes the boundaries of cell and molecular biology. We use advanced microscopy, tissue engineering and single cell genomics to optimize precise editing. We are developing computational methods to select optimal CRISPR/Cas9 combinations in diverse populations. We aim to produce therapies that are safe and cost effective so that they can benefit the maximal number of people. In collaboration with clinical scientists and the Innovative Genomics Institute (https://innovativegenomics.org/) we are preparing large animal models and clinical grade reagents to prepare for human clinical trials.

Insights into cellular and molecular mechanisms: A major benefit of our approach to genome surgery is the mechanistic insights that we gain. The reversion of a cellular phenotype is proof that dominant negative allele was causative and that the disease process is reversible. Detailed cellular analysis often provides new insights into the mechanism of the disease. Genomic deletions require detailed knowledge of the non-coding elements that are often poorly understood (e.g., enhancers, LncRNAs, microRNAs). Each cell type allows us to probe the 3D architecture and epigenetic state of the gene region, since distant DNA can be in close proximity, allowing efficient excision of larger genomic segments. Finally, the DNA repair machinery of each cell type will be better understood as we learn to orchestrate precise repair. Genome surgery is a new field of medicine that will drive a new level investigation into the molecular physiology of diverse cell types such as cardiomyocytes, motor neurons and RPE. Only by understanding the basic cellular and molecular physiology of these cells can me meet the challenges ahead.

Future directions: Genome engineering and stem cell biology have been the most disruptive technologies of this millennia. Advances in iPSC-differentiation and cell modeling will allow more cell types and sophisticated multicellular models of disease. Molecular insights into many diseases are likely to lead to insights into improved drug therapy without gene correction. We also predict increasing sophisticated methods to intervene in genetic disease with epigenetic modification, or base editing that will expand the field of genome surgery. We are confident that these new advances will help us reach our goal of decoding and repairing genetic disease.


Selected Recent Publications

  1. Judge LM, Perez-Bermejo JA, Truong A, Ribeiro AJ, Yoo JC, Jensen CL, Mandegar MA, Huebsch N, Kaake RM, So PL, Srivastava D, Pruitt BL, Krogan NJ, Conklin BR. A (2017) BAG3 chaperone complex maintains cardiomyocyte function during proteotoxic stress. JCI Insight. 2(14). pii: 94623. July 20; PMID: 28724793
  2. Mandegar MA, Huebsch N, Frolov E, SHin E, Weissman JS, Qi LS, So P-L, Conklin BR. (2016) CRISPR interference efficiently induces gene knockdown and models disease in iPSCs. Cell Stem Cell. 18 1-13, April 7, 2016, PMID: 26971820
  3. Miyaoka Y, Berman JR, Cooper SB, Mayerl SJ, Chan AH, Zhang B, Karlin-Neumann GA, Conklin BR. (2016) Systematic quantification of HDR and NHEJ reveals effects of locus, nuclease, and cell type on genome-editing. Sci Rep. Mar 31;6:23549. PMID: 27030102,
  4. Huebsch N, Loskill P, Deveshwar N, Spencer CI, Judge LM, Mandegar MA, Fox CB, Mohamed TM, Ma Z, Mathur A, Sheehan AM, Truong A, Saxton M, Yoo J, Srivastava D, Desai TA, So PL, Healy KE, Conklin BR. (2016) Miniaturized iPS-Cell-Derived Cardiac Muscles for Physiologically Relevant Drug Response Analyses. Sci Rep. Apr 20;6:24726. PMID: 27095412
  5. Miyaoka Y, Chan AH, Judge LM, Yoo J, Huang M, Nguyen TD, Lizarraga PP, So PL, Conklin BR. (2014) Isolation of single-base genome-edited human iPS cells without antibiotic selection. Nat Methods, 11(3):291-3. PMID: 24509632


Five Overall Publications

  1. Conklin BR, Farfel Z, Lustig KD, Julius D, Bourne HR. (1993) Substitution of three amino acids switches receptor specificity of Gq alpha to that of Gi alpha. Nature, 363(6426):274-6.
  2. Conklin BR, Hsiao EC, Claeysen S, Dumuis A, Srinivasan S, Forsayeth JR, Guettier JM, Chang WC, Pei Y, McCarthy KD, Nissenson RA, Wess J, Bockaert J, Roth BL. (2008) Engineering GPCR signaling pathways with RASSLs. Nat Methods, 5(8):673-8
  3. Dahlquist KD, Salomonis N, Vranizan K, Lawlor SC, Conklin BR. (2002) GenMAPP, a new tool for viewing and analyzing microarray data on biological pathways. Nat Genetics, 31(1):19-20.
  4. Federman AD, Conklin BR, Schrader KA, Reed RR, Bourne HR. (1992) Hormonal stimulation of adenylyl cyclase through Gi-protein βγ subunits. Nature 356:159.
  5. Redfern CH, Coward P, Degtyarev MY, Lee ED, Kwa AT, Hennighausen L, Bujard H, Fishman GI, Conklin BR. (1999) Conditional expression and signaling of a specifically designed Gi-coupled receptor in transgenic mice. Nat Biotechnology, 17(2):165-9.