The enzyme Rubisco, largely found in plants, algae, and photosynthetic bacteria, is responsible for the majority of biological carbon fixation on Earth. However, it has slow kinetics and has resisted decades of protein engineering efforts to improve its catalytic rate. UC Berkeley researchers have designed an in-vivo system that allows large libraries of Rubisco sequences to be functionally screened for improved enzymatic properties. They generated an E. coli strain whose growth rate is linked to Rubisco performance, allowing for pooled assays and the use of deep sequencing as a readout. This system allows for much higher throughput screening of Rubisco than any previous method and significantly increases opportunities to identify catalytically superior Rubisco sequences. 

AI infrastructure that collects, transcribes, and analyzes student audio responses to deliver actionable insights on learning experiences.

CAPTaINs provide a novel, selective, and stable method for selective degradation of protein targets.

Genetic therapies often suffer from low delivery efficiency to cancer cells. To address this, UC Berkeley researchers designed a therapy delivery system that targets and kills cancer cells despite low delivery efficiencies. In this system, nucleic acid cargo encoding a secreted toxin and non-secreted anti-toxin are delivered to cancer cells. The small population of cells that receives and expresses the cargo survives due to the presence of the anti-toxin, while the majority of cancer cells that do not have the cargo die from the secreted toxin. The cargo-containing cells are subsequently eliminated using an encoded kill-switch. The invention also describes screening methods in organoids and methods of using compounds identified in screens. When used in vivo, this technology presents an attractive method for curing solid tumor cancers via gene therapy.

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