Engineering advanced logic and distributed computing in human CAR immune cells.

The immune system is a sophisticated network of different cell types performing complex biocomputation at single-cell and consortium levels. The ability to reprogram such an interconnected multicellular system holds enormous promise in treating various diseases, as exemplified by the use of chimeric antigen receptor (CAR) T cells as cancer therapy. However, most CAR designs lack computation features and cannot reprogram multiple immune cell types in a coordinated manner.

Author Correction: Engineering Axl specific CAR and SynNotch receptor for cancer therapy.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

High-performance chemical- and light-inducible recombinases in mammalian cells and mice.

Site-specific DNA recombinases are important genome engineering tools. Chemical- and light-inducible recombinases, in particular, enable spatiotemporal control of gene expression. However, inducible recombinases are scarce due to the challenge of engineering high performance systems, thus constraining the sophistication of genetic circuits and animal models that can be created.

Universal Chimeric Antigen Receptors for Multiplexed and Logical Control of T Cell Responses.

T cells expressing chimeric antigen receptors (CARs) are promising cancer therapeutic agents, with the prospect of becoming the ultimate smart cancer therapeutics. To expand the capability of CAR T cells, here, we present a split, universal, and programmable (SUPRA) CAR system that simultaneously encompasses multiple critical "upgrades," such as the ability to switch targets without re-engineering the T cells, finely tune T cell activation strength, and sense and logically respond to multiple antigens. These features are useful to combat relapse, mitigate over-activation, and enhance specificity.

Engineering Axl specific CAR and SynNotch receptor for cancer therapy.

Axl is a tyrosine kinase receptor that is commonly overexpressed in many cancers. As such, Axl represents an attractive therapeutic target. The transfer of engineered T cell expressing chimeric antigen receptor (CAR) is an exciting cancer therapeutic approach that shows high efficacy against cancers in clinical trials, especially for B cell malignancies.

Synthetic Biology: Immunotherapy by Design.

Cellular immunotherapy holds great promise for the treatment of human disease. Clinical evidence suggests that T cell immunotherapies have the potential to combat cancers that evade traditional immunotherapy. Despite promising results, adverse effects leading to fatalities have left scientists seeking tighter control over these therapies, which is reflected in the growing body of synthetic biology literature focused on developing tightly controlled, context-independent parts.

Coordinated regulation of acid resistance in Escherichia coli.

Background: Enteric Escherichia coli survives the highly acidic environment of the stomach through multiple acid resistance (AR) mechanisms. The most effective system, AR2, decarboxylates externally-derived glutamate to remove cytoplasmic protons and excrete GABA. The first described system, AR1, does not require an external amino acid.

Synthetic biology approaches in cancer immunotherapy, genetic network engineering, and genome editing.

Investigations into cells and their contents have provided evolving insight into the emergence of complex biological behaviors. Capitalizing on this knowledge, synthetic biology seeks to manipulate the cellular machinery towards novel purposes, extending discoveries from basic science to new applications. While these developments have demonstrated the potential of building with biological parts, the complexity of cells can pose numerous challenges.

Regularization designs for uniform spatial resolution and noise properties in statistical image reconstruction for 3-D X-ray CT.

Statistical image reconstruction methods for X-ray computed tomography (CT) provide improved spatial resolution and noise properties over conventional filtered back-projection (FBP) reconstruction, along with other potential advantages such as reduced patient dose and artifacts. Conventional regularized image reconstruction leads to spatially variant spatial resolution and noise characteristics because of interactions between the system models and the regularization. Previous regularization design methods aiming to solve such issues mostly rely on circulant approximations of the Fisher information matrix that are very inaccurate for undersampled geometries like short-scan cone-beam CT.