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lysate-based cell-free systems have gained traction for a variety of point-of-use biological applications. Lysate-based cell-free reactions can be freeze-dried, deployed without requiring cold chain, and have a high ease of use through simple rehydration. To maximize their potential, it is of interest to stabilize these reactions to withstand a variety of conditions for long-term storage and use, including stabilization to UV exposure. To address this issue and aid in point-of-use applications, we investigate the use of synthetic melanin nanoparticles as UV-protective additives that are compatible with cell-free reactions. These particles have broadband absorption properties and radical scavenging activity that allow for protection from free radical generation during prolonged UV exposure. Stabilizing cell-free reactions in this way may prolong the stability for use in the field where exposure to sunlight is inevitable.
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http://dx.doi.org/10.1021/acssynbio.5c00212 | DOI Listing |
Clin Transplant Res
September 2025
Department of Laboratory Medicine, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.
Donor-derived cell-free DNA (dd-cfDNA) has emerged as a valuable noninvasive biomarker for detecting allograft injury in solid organ transplantation. It is released into the bloodstream from the transplanted organ as a result of cell injury and immune activation, with baseline levels influenced by organ type, tissue turnover, and posttransplant physiological changes. Several analytical platforms are available, including quantitative polymerase chain reaction (PCR), digital droplet PCR, and next-generation sequencing, each differing in sensitivity, throughput, and reporting format.
View Article and Find Full Text PDFIn this work, we present a streamlined one-pot cloning and protein expression platform that integrates mutagenesis, plasmid assembly, and functional protein testing in a single reaction. By combining Golden Gate cloning with cell-free transcription-translation, we demonstrate efficient generation and screening of genetic variants without the need for intermediate purification or bacterial amplification. Using fluorescent proteins, luciferase enzymes, antibiotic-converting enzymes, and the violacein biosynthetic pathway, we validate the versatility of this approach for single-and multi-site mutagenesis, combinatorial variant libraries, metabolic pathway programming, and whole-plasmid assembly.
View Article and Find Full Text PDFACS Synth Biol
September 2025
Department of Chemical and Biological Engineering, Northwestern University, Evanston, Illinois 60208, United States.
Cell-free biosensing systems are being engineered as versatile and programmable diagnostic technologies. A core component of cell-free biosensors is programmable molecular circuits that improve biosensor speed, sensitivity, and specificity by performing molecular computations such as logic evaluation and signal amplification. In previous work, we developed one such circuit system called Polymerase Strand Recycling (PSR), which amplifies cell-free molecular circuits by using T7 RNA polymerase off-target transcription to recycle nucleic acid inputs.
View Article and Find Full Text PDFScand J Gastroenterol
September 2025
Department of Gastrointestinal Surgery, Aalborg University Hospital, Aalborg, Denmark.
Background: Chronic pancreatitis (CP) is an inflammatory disease characterized by pain, functional deficits and increased mortality. The clinical course is unpredictable, and there are no classification systems or biomarkers to predict this. Identifying patients with high mortality risk is crucial for guiding clinical management and improving outcomes.
View Article and Find Full Text PDFbioRxiv
August 2025
Department of Bioengineering, Stanford University, Stanford, CA 94305, USA.
Point-of-use diagnostics based on allosteric transcription factors (aTFs) are promising tools for environmental monitoring and human health. However, biosensors relying on natural aTFs rarely exhibit the sensitivity and selectivity needed for real-world applications, and traditional directed evolution struggles to optimize multiple biosensor properties at once. To overcome these challenges, we develop a multi-objective, machine learning (ML)-guided cell-free gene expression workflow for engineering aTF-based biosensors.
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