NEWS RELEASES

Rubisco activase is an ATP-dependent chaperone that facilitates dissociation of inhibitory sugar phosphates from the catalytic sites of Rubisco during photosynthesis. In Arabidopsis, Rubisco activase is negatively regulated by dark-dependent phosphorylation of Thr78. However, it is not clear whether this mechanism is relevant outside of Arabidopsis. To address this knowledge gap, researchers at the Center for Advanced Bioenergy and Bioproducts Innovation (CABBI) investigated the prevalence of Thr78 in Rubisco activase across 91 plant species. Their results suggest that despite conservation of Thr78 in Rubisco activase from a wide range of species, a regulatory role for phosphorylation at this site is more limited. This provides a case study for how variation in post-translational regulation can amplify functional divergence across the phylogeny of plants beyond what is explained by sequence variation in a metabolically important protein.

MIT researchers developed a fully autonomous platform that can identify, mix, and characterize novel polymer blends until it finds the optimal blend. This system could streamline the design of new composite materials for sustainable biocatalysis, better batteries, cheaper solar panels, and safer drug-delivery materials.

A new theory-guided framework could help scientists probe the properties of new semiconductors for next-generation microelectronic devices, or discover materials that boost the performance of quantum computers.

Low carbon fuel policies are intended to reduce greenhouse gas (GHG) emissions from transportation. However, rigid carbon intensity (CI) accounting procedures in current policies may limit CI responsiveness across candidate sites and facilities. This study examines how low carbon fuel programs capture or overlook spatial variability and net electricity production in biofuel carbon intensity, influencing crediting outcomes and fuel selling prices.

A newly discovered pathway in a plant process could help farmers grow more successful crops, particularly in places where harsh, high light stresses plants.

A new experimental design framework could enable scientists to efficiently estimate how combinations of interventions will affect a group of cells, reducing the cost of experiments and providing less biased data that could be used to understand disease mechanisms or develop new treatments.