Biology subjects

Zorn, K.

Publications and source records attributed to Zorn, K..

3 recordsLinked to original sources

bioRxiv2024

Delineation of the Complete Reaction Cycle of a Natural Diels-Alderase

The Diels-Alder reaction is one of the most effective methods for the synthesis of substituted cyclohexenes. The development of protein catalysts for this reaction remains a major priority, affording new sustainable routes to high value target molecules. Whilst a small number of natural enzymes have been shown capable of catalysing [4+2] cycloadditions, there is a need for significant mechanistic understanding of how these prospective Diels-Alderases promote catalysis to underpin their development as biocatalysts for use in synthesis. Here we present a molecular description of the complete reaction cycle of the bona fide natural Diels-Alderase AbyU, which catalyses formation of the spirotetronate skeleton of the antibiotic abyssomicin C. This description is derived from X-ray crystallographic studies of AbyU in complex with a non-transformable synthetic substrate analogue, together with transient kinetic analyses of the AbyU catalysed reaction and computational reaction simulations. These studies reveal the mechanistic intricacies of this enzyme system and establish a foundation for the informed reengineering of AbyU and related biocatalysts.

biochemistry↗

bioRxiv2024

Ancestral versus Modern Substrate Scope in Family-1 Glycosidases

Experimental studies support that protein engineering based on ancestral sequence reconstruction often leads to variants with biotechnologically useful biomolecular properties. These may include high stability, enhanced conformational flexibility and a modified catalysis range. Carbohydrate-active enzymes have numerous applications related with the degradation and synthesis of carbohydrates and glycoconjugates. Here, we explore how ancestral reconstruction may impact substrate scope in glycosidases, highly diverse enzymes that catalyze the hydrolysis of glycosidic bonds in all living cells and find applications as catalysts of the reverse reaction. To this end, we screen a library of [~]500 potential glycosidase substrates for degradation by both, a modern family-1 glycosidase from Halothermothrix orenii and a putative ancestral family-1 glycosidase derived from sequence reconstruction at a bacterial-eukaryotic common ancestor. The modern enzyme is the better catalyst for most substrates. But the ancestral glycosidase is more efficient with flavonoid glycosides bearing large aglycon moieties. Analysis of the catalytic parameters for a selected set of substrates, alongside analysis of the library data using a supervised learning algorithm, support the hypothesis that the modern enzyme tends to become less catalytically efficient with increasing substrate size, while this trend is not observed for the ancestral glycosidase. Molecular simulations support that the ancestral catalysis pattern is linked to the existence of a highly flexible region of the ancestral structure and a cavity capable of accommodating large aglycons. Our results provide guidelines for the engineering of enzymes for the synthesis and hydrolysis of large glycoconjugates.

biochemistry↗

bioRxiv2022

Autoantibody discovery across monogenic, acquired, and COVID19-associated autoimmunity with scalable PhIP-Seq

Phage Immunoprecipitation-Sequencing (PhIP-Seq) allows for unbiased, proteome-wide autoantibody discovery across a variety of disease settings, with identification of disease-specific autoantigens providing new insight into previously poorly understood forms of immune dysregulation. Despite several successful implementations of PhIP-Seq for autoantigen discovery, including our previous work (Vazquez et al. 2020), current protocols are inherently difficult to scale to accommodate large cohorts of cases and importantly, healthy controls. Here, we develop and validate a high throughput extension of PhIP-seq in various etiologies of autoimmune and inflammatory diseases, including APS1, IPEX, RAG1/2 deficiency, Kawasaki Disease (KD), Multisystem Inflammatory Syndrome in Children (MIS-C), and finally, mild and severe forms of COVID19. We demonstrate that these scaled datasets enable machine-learning approaches that result in robust prediction of disease status, as well as the ability to detect both known and novel autoantigens, such as PDYN in APS1 patients, and intestinally expressed proteins BEST4 and BTNL8 in IPEX patients. Remarkably, BEST4 antibodies were also found in 2 patients with RAG1/2 deficiency, one of whom had very early onset IBD. Scaled PhIP-Seq examination of both MIS-C and KD demonstrated rare, overlapping antigens, including CGNL1, as well as several strongly enriched putative pneumonia-associated antigens in severe COVID19, including the endosomal protein EEA1. Together, scaled PhIP-Seq provides a valuable tool for broadly assessing both rare and common autoantigen overlap between autoimmune diseases of varying origins and etiologies.

immunology↗