KAUST research scientist Dr. Ram Karan won two awards at the International Congress of Extremophiles 2018 for his work on extremozymes from Red Sea brine pools. His research focuses on understanding how life is possible under extreme conditions using culture-independent methods to evaluate the structure and function of polyextremophilic enzymes. Crystal structure analysis provided insights into how enzymes adapt to extreme conditions. Why it matters: This research provides insights into the possibilities of life in extreme conditions and has implications for astrobiology.
KAUST Research Scientist Dr. Ram Karan received a Young Scientist Award at the 15th International Congress on Thermophiles in Japan for his work on extremozymes from Red Sea brine pools. His research focuses on identifying, purifying, and bioengineering microbial proteins from these pools. He utilizes single-amplified genomes (SAGs) to produce extremozyme proteins without needing to grow cells in the lab. Why it matters: This award recognizes KAUST's innovative research into extremophiles, which have the potential to develop novel, sustainable biotechnical processes for industrial applications.
Researchers from King Abdullah University of Science and Technology (KAUST), in collaboration with Universidad de los Andes and others, investigated mangrove ecosystems for enzymes capable of degrading plastics like PET. They discovered that adding agricultural residues to mangrove soils increased the number of potential PET-degrading enzymes and identified a previously unknown group of salt-tolerant enzymes. The team employed metagenomics, artificial intelligence, and 3D structural analysis to study these enzymes, publishing their findings in Nature Communications. Why it matters: This research offers potential new enzymatic solutions for global plastic waste management, particularly for high-salinity industrial applications, by leveraging the unique biodiversity of environments like Saudi Arabia's Red Sea mangroves.
KAUST researchers have developed a CRISPR-Cas system using a heat-stable Cas13 protein (TccCas13a) from Thermoclostridium caenicola, compatible with RT-LAMP for rapid viral detection. The new assay, named OPTIMA-dx, enhances the specificity of RT-LAMP tests by reducing false positives in SARS-CoV-2 detection. The team, led by Dr. Magdy Mahfouz and doctoral student Ahmed Mahas, is transitioning the product to a startup phase for commercialization. Why it matters: This innovation could significantly improve point-of-care diagnostics for COVID-19 and other infections by providing a more accurate and easier-to-use testing method.
KAUST researchers used cryogenic electron microscopy (cryo-EM) to study the 3D structure of protein complexes involved in DNA replication and repair. They investigated the interaction between the Y-family TLS polymerase Pol K and mono-ubiquitylated PCNA. The study revealed that DNA binding is required for Pol K to form a rigid, active complex with PCNA. Why it matters: Understanding these structural interactions may provide insights into cancer development and drug resistance mechanisms.
KAUST researchers discovered that the red algae strain Galdieria yellowstonesis can convert sugars from chocolate-processing waste into C-phycocyanin, a valuable blue pigment. The study found that high levels of carbon dioxide promote Galdieria growth, and the resulting phycocyanin was deemed food-safe by the U.S. FDA. Mars supported the research by providing chocolate samples. Why it matters: This research offers a sustainable method for waste management and contributes to a circular economy in the region, with potential applications in food, cosmetics, and pharmaceuticals.
KAUST Vice Provost Suzana Nunes has been appointed as an Honorary Member of the European Membrane Society (EMS). This appointment recognizes Nunes' contributions to education, science, and technology in the field of membranes. Nunes has been a KAUST professor since 2009, focusing on polymeric materials for membrane applications. Why it matters: The recognition highlights KAUST's contributions to advanced materials science and engineering, enhancing its reputation as a research hub.
A recent study questions the necessity of deep ensembles, which improve accuracy and match larger models. The study demonstrates that ensemble diversity does not meaningfully improve uncertainty quantification on out-of-distribution data. It also reveals that the out-of-distribution performance of ensembles is strongly determined by their in-distribution performance. Why it matters: The findings suggest that larger, single neural networks can replicate the benefits of deep ensembles, potentially simplifying model deployment and reducing computational costs in the region.