Biology subjects

Hazelbaker, D. Z.

Publications and source records attributed to Hazelbaker, D. Z..

6 recordsLinked to original sources

bioRxiv2025

Highly Efficient Multiplexed Genome Engineering and Clone Selection to Enable Next Generation Induced Pluripotent Stem Cell (iPSC)-based Cell Therapies

Human induced pluripotent stem cells (iPSCs) have revolutionized regenerative medicine and cellular therapies. To improve the functionality and safety of iPSC-based therapies, genome engineering has been employed to disrupt gene expression and introduce therapeutic transgenes. However, current genome editing methods face significant challenges, including labor-intensive procedures, low efficiency, and safety concerns. Here, we report a novel and efficient approach for multiplex genome engineering in iPSCs using Integrase-mediated Programmable Genomic Integration (I-PGI) technology. I-PGI combines CRISPR-mediated genome editing and site-specific integrases, enabling precise gene insertion without DNA double-strand breaks. By optimizing I-PGI components and protocols, we achieved multiple gene knockouts and knock-ins of up to five transgenes in a single process. Additionally, we developed a streamlined workflow for enrichment, deposition, and screening of single-cell clones with the desired genome edits. This approach significantly accelerates and improves the precision of multiplex iPSC engineering, paving the way for next-generation iPSC-based therapies.

genomics↗

bioRxiv2024

Large Serine Integrase Off-Target Discovery with Deep Learning for Genome Wide Prediction

Large Serine Integrases (LSIs) hold significant therapeutic promise due to their ability to efficiently incorporate gene-sized DNA into the human genome, offering a method to integrate healthy genes in patients with monogenic disorders or to insert gene circuits for the development of advanced cell therapies. To advance the application of LSIs for human therapeutic applications, new technologies and analytical methods for predicting and characterizing off-target recombination by LSIs are required. It is not experimentally tractable to validate off-target editing at all potential off-target sites in therapeutically relevant cell types because of sample limitations and genetic variation in the human population. To address this gap, we constructed a deep learning model named IntQuery that can predict LSI activity genome-wide. For Bxb1 integrase, IntQuery was trained on quantitative off-target data from 410,776 cryptic attB sequences discovered by Cryptic-seq, an unbiased in vitro discovery technology for LSI off-target recombination. We show that IntQuery can accurately predict in vitro LSI activity, providing a tool for in silico off-target prediction of large serine integrases to advance therapeutic applications.

bioinformatics↗

bioRxiv2024

Curative levels of endogenous gene replacement achieved in non-human primate liver using programmable genomic integration

The ability to efficiently place a large piece of DNA in a specific genomic location has been a goal for the gene therapy field since its inception; however, despite significant advances in gene editing technology, this had yet to be achieved. Here we describe two methods of programmable genomic integration (PGI) that overcome some of the limitations of current approaches. Using a combination of clinically validated delivery technologies (LNP, AAV), we demonstrate the ability to specifically integrate large (>2 kb) DNA sequences into endogenous introns in the liver of non-human primates (NHP). PGI was effective across multiple genomic locations and transgenes, and insertion led to expression from the endogenous promoter. PGI was highly efficient, achieving expression in >50% of liver cells after a single course of treatment, which would be curative for most monogenic recessive liver diseases. This is the first report of clinically curative level of gene insertion at endogenous loci in NHP.

bioengineering↗

bioRxiv2024

Large Serine Integrase Off-target Discovery and Validation for Therapeutic Genome Editing

While numerous technologies for the characterization of potential off-target editing by CRISPR/Cas9 have been described, the development of new technologies and analytical methods for off-target recombination by Large Serine Integrases (LSIs) are required to advance the application of LSIs for therapeutic gene integration. Here we describe a suite of off-target recombination discovery technologies and a hybrid capture validation approach as a comprehensive framework for off-target characterization of LSIs. HIDE- Seq (High-throughput Integrase-mediated DNA Event Sequencing) is a PCR-free unbiased genome-wide biochemical assay capable of discovering sites with LSI- mediated free DNA ends (FDEs) and off-target recombination events. Cryptic-Seq is a PCR-based unbiased genome-wide biochemical or cellular-based assay that is more sensitive than HIDE-Seq but is limited to the discovery of sites with off-target recombination. HIDE-Seq and Cryptic-Seq discovered 38 and 44,311 potential off-target sites respectively. 2,455 sites were prioritized for validation by hybrid capture NGS in LSI- edited K562 cells and off-target integration was detected at 52 of the sites. We benchmarked the sensitivity of our LSI off-target characterization framework against unbiased whole genome sequencing (WGS) on LSI-edited samples, and off-target integration was detected at 5 sites with an average genome coverage of 40x. This reflects a greater than 10-fold increase in sensitivity for off-target detection compared to WGS, however only 4 of the 5 sites detected by WGS were also validated by hybrid capture NGS. The dissemination of these technologies will help advance the application of LSIs in therapeutic genome editing by establishing methods and benchmarks for the sensitivity of off-target detection.

genomics↗

bioRxiv2021

The 22q11.2 region regulates presynaptic gene-products linked to schizophrenia

To study how the 22q11.2 deletion predisposes to psychiatric disease, we generated induced pluripotent stem cells from deletion carriers and controls, as well as utilized CRISPR/Cas9 to introduce the heterozygous deletion into a control cell line. Upon differentiation into neural progenitor cells, we found the deletion acted in trans to alter the abundance of transcripts associated with risk for neurodevelopmental disorders including Autism Spectrum Disorder. In more differentiated excitatory neurons, altered transcripts encoded presynaptic factors and were associated with genetic risk for schizophrenia, including common (per-SNP heritability p ({tau}c)= 4.2 x 10-6) and rare, loss of function variants (p = 1.29x10-12). These findings suggest a potential relationship between cellular states, developmental windows and susceptibility to psychiatric conditions with different ages of onset. To understand how the deletion contributed to these observed changes in gene expression, we developed and applied PPItools, which identifies the minimal protein-protein interaction network that best explains an observed set of gene expression alterations. We found that many of the genes in the 22q11.2 interval interact in presynaptic, proteasome, and JUN/FOS transcriptional pathways that underlie the broader alterations in psychiatric risk gene expression we identified. Our findings suggest that the 22q11.2 deletion impacts genes and pathways that may converge with risk loci implicated by psychiatric genetic studies to influence disease manifestation in each deletion carrier.

neuroscience↗

bioRxiv2019

Multiplexed and Inducible Gene Modulation in Human Pluripotent Stem Cells by CRISPR Interference and Activation

CRISPR-Cas9-mediated gene interference (CRISPRi) and activation (CRISPRa) approaches hold promise for functional genomic studies and genome-wide screens in human pluripotent stem cells (hPSCs). However, in contrast to CRISPR-Cas9 nuclease approaches, the efficiency of CRISPRi/a depends on continued expression of the dead Cas9 (dCas9) effector and guide RNA (gRNA), which can vary substantially depending on transgene design and delivery. Here, we design new fluorescently labeled piggyBac (PB) vectors to deliver robust and stable expression of multiplexed gRNAs. In addition, we generate hPSC lines harboring AAVS1-integrated, inducible and fluorescent dCas9-KRAB and dCas9-VPR transgenes to allow for accurate quantification and tracking of cells that express both the dCas9 effectors and gRNAs. We then employ these systems to target the TCF4 gene and conduct a rigorous assessment of expression levels of the dCas9 effectors, gRNAs and targeted gene. Collectively, these data provide proof-of-principle application of a stable, multiplexed PB gRNA delivery system that can be widely exploited to further enable genome engineering studies in hPSCs. Paired with diverse CRISPR tools including our dual fluorescence CRISPRi/a cell lines, this system would facilitate functional dissection of individual genes and pathways as well as larger-scale screens for studies of development and disease.

molecular biology↗