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Bakalar, M. H.

Publications and source records attributed to Bakalar, M. H..

4 recordsLinked to original sources

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↗

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↗

Molecular height measurement by cell surface optical profilometry (CSOP)

The physical dimensions of proteins and glycans on cell surfaces can critically affect cell function, for example by preventing close contact between cells and limiting receptor accessibility. However, high-resolution measurements of molecular heights on native cell membranes have been difficult to obtain. Here we present a simple and rapid method that achieves nanometer height resolution by localizing fluorophores at the tip and base of cell surface molecules and determining their separation by radially averaging across many molecules. We use this method, which we call cell surface optical profilometry (CSOP), to quantify height of key multi-domain proteins on a model macrophage and cancer cell, as well as to capture average protein and glycan heights on native cell membranes. We show that average height of a protein is significantly smaller than its contour length due to thermally driven bending and rotation on the membrane and that height strongly depends on local surface and solution conditions. We find that average height increases with cell surface molecular crowding, while it decreases with solution crowding by solutes, both of which we confirm with molecular dynamics simulations. We also use experiments and simulations to determine the height of an epitope based on the location of an antibody, which allows CSOP to profile various proteins and glycans on a native cell surface using antibodies and lectins. This versatile method for profiling cell surfaces has the potential to advance understanding of the molecular landscape of cells and its role in cell function.

biophysics↗

Size-dependent segregation controls macrophage phagocytosis of antibody-opsonized targets

Macrophages protect the body from damage and disease by targeting antibody-opsonized cells for phagocytosis. Though antibodies can be raised against antigens with diverse structures, shapes, and sizes, it is unclear why some are more effective at triggering antibody-dependent phagocytosis than others. Here we quantitatively define an antigen height threshold that regulates phagocytosis of both engineered and cancer-specific antigens by macrophages. Using a reconstituted model of antibody-opsonized target cells, we find that phagocytosis is dramatically impaired for antigens that position antibodies >10 nm from the target surface. Increasing antigen height allows for co-localization of Fc receptors and the inhibitory phosphatase CD45 at the cell-cell interface, which reduces Fc receptor phosphorylation, and inhibits phagocytosis. Our work shows that close contact between macrophage and target cell is a requirement for efficient phagocytosis, suggesting that therapeutic antibodies should target short antigens in order to trigger Fc receptor activation through size-dependent physical segregation.

cell biology↗