ABSTRACT
The CRISPR-Cas type V-I is a family of Cas12i-containing programmable nuclease systems guided by a short crRNA without requirement for a tracrRNA. Here we present an engineered Type V-I CRISPR system (Cas12i), ABR-001, which utilizes a tracr-less guide RNA. The compact Cas12i effector is capable of self-processing pre-crRNA and cleaving dsDNA targets, which facilitates versatile delivery options and multiplexing, respectively. We apply an unbiased mutational scanning approach to enhance initially low editing activity of Cas12i2. The engineered variant, ABR-001, exhibits broad genome editing capability in human cell lines, primary T cells, and CD34+ hematopoietic stem and progenitor cells, with both robust efficiency and high specificity. In addition, ABR-001 achieves a high level of genome editing when delivered via AAV vector to HEK293T cells. This work establishes ABR-001 as a versatile, specific, and high-performance platform for ex vivo and in vivo gene therapy.
Subject(s)
CRISPR-Cas Systems , Gene Editing , CRISPR-Cas Systems/genetics , Endonucleases/genetics , Endonucleases/metabolism , Gene Editing/methods , HEK293 Cells , Humans , RNA/metabolism , RNA, Guide, Kinetoplastida/genetics , RNA, Guide, Kinetoplastida/metabolismABSTRACT
Metastasis, the leading cause of death in cancer patients, requires the invasion of tumor cells through the stroma in response to migratory cues, in part provided by the extracellular matrix (ECM). Recent advances in proteomics have led to the identification of hundreds of ECM proteins, which are more abundant in tumors relative to healthy tissue. Our goal was to develop a pipeline to easily predict which ECM proteins are more likely to have an effect on cancer invasion and metastasis. We evaluated the effect of four ECM proteins upregulated in breast tumor tissue in multiple human breast cancer cell lines in three assays. There was no linear relationship between cell adhesion to ECM proteins and ECM-driven 2D cell migration speed, persistence, or 3D invasion. We then used classifiers and partial-least squares regression analysis to identify which metrics best predicted ECM-driven 2D migration and 3D invasion responses. We find that ECM-driven 2D cell migration speed or persistence did not predict 3D invasion in response to the same cue. However, cell adhesion, and in particular cell elongation and shape irregularity, accurately predicted the magnitude of ECM-driven 2D migration and 3D invasion. Our models successfully predicted the effect of novel ECM proteins in a cell-line specific manner. Overall, our studies identify the cell morphological features that determine 3D invasion responses to individual ECM proteins. This platform will help provide insight into the functional role of ECM proteins abundant in tumor tissue and help prioritize strategies for targeting tumor-ECM interactions to treat metastasis.
