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Jensen, K. S.

Publications and source records attributed to Jensen, K. S..

2 recordsLinked to original sources

N-terminal acetylation of superoxide dismutase 1 accelerates amyloid formation without general destabilization of the apo-state

Co- and posttranslational modifications can significantly impact the structure, dynamics and function of proteins. In this study we investigate how N-terminal acetylation affects misfolding and self-assembly of the enzyme superoxide dismutase 1 (SOD1), implicated in amyotrophic lateral sclerosis (ALS). Studies of protein inclusions in patient samples and animal models have shown that wild-type SOD1 can form amyloid fibrils even when no mutations are found in the sod1-gene. This has identified SOD1 amyloid formation as a possible common denominator of ALS and may suggest that co- and posttranslational modifications, like N-terminal acetylation found in human SOD1, can be a factor in disease development. In this work the impact of N-terminal acetylation of SOD1 on stability and aggregation is characterized. Results show that the structure and thermal stability of the apo-state are unaffected by the modification while the amyloid formation rate is significantly enhanced. This is caused by a shortening of the nucleation phase together with an increase of fibril elongation by more than 10-fold upon N-terminal acetylation of SOD1. Collectively the findings demonstrate how regulation by co- and posttranslational modifications can influence protein misfolding and self-assembly.

biochemistry↗

Expanding the biotechnological scope of metabolic sensors through computation-aided designs

Metabolic sensors are microbial strains modified so that biomass formation correlates with the availability of specific metabolites. These sensors are essential for bioengineering (e.g. in growth-coupled designs) but creating them is often a time-consuming and low-throughput process that can potentially be streamlined by in silico analysis. Here, we present the systematic workflow of designing, implementing, and testing versatile Escherichia coli metabolic sensor strains. Glyoxylate, a key metabolite in (synthetic) CO2 fixation and carbon-conserving pathways, served as the test molecule. Through iterative screening of a compact metabolic model, we identified non-trivial growth-coupled designs that resulted in six metabolic sensors with a wide sensitivity range for glyoxylate, spanning three orders of magnitude in detected concentrations. We further adapted these E. coli strains for sensing glycolate and demonstrated their utility in both pathway engineering (testing a key metabolic module via glyoxylate) and applications in environmental monitoring (quantifying glycolate produced by photosynthetic microalgae). The versatility and ease of implementation of this workflow make it suitable for designing and building multiple metabolic sensors for diverse biotechnological applications. TeaserA streamlined workflow enables the rapid design of versatile E. coli metabolic sensors for detecting key metabolites in bioengineering and monitoring.

synthetic biology↗