Biology subjects

Laohakunakorn, N.

Publications and source records attributed to Laohakunakorn, N..

6 recordsLinked to original sources

bioRxiv2025

Horseradish peroxidase as an electrochemical reporter protein for cell-free biosensors

Cell-free biosensor systems offer a promising platform for portable diagnostics. However, most employ fluorescent reporter proteins that require complex instrumentation and can be affected by photo-bleaching and auto-fluorescence, limiting translatability. Electrochemical reporters do not suffer from these drawbacks. Here, we evaluate horseradish peroxidase (HRP) as a redox enzyme reporter for cell-free biosensor systems. HRP was synthesized in an E. coli cell-free transcription-translation system supplemented with hemin, calcium acetate, and commercial disulfide bond enhancers. The electrochemical detection of its activity was established by chronoamperometry, with H2O2 as a substrate and tetramethylbenzidine as a redox mediator. Cell-free expressed HRP produced a strong steady state current compared to a catalytically inactive mutant and a no-template control. Kinetic analysis showed a Km for the cell-free expressed HRP close to that of the native enzyme. To explore the potential of HRP as an electrochemical reporter, we placed it under the control of a tetracycline-responsive regulatory promoter and demonstrated a 3-fold current increase in the presence of anhydrotetracycline. These results support HRP as an electrochemical reporter for cell-free biosensors, offering a practical alternative to optical reporters for future use in handheld analytical devices. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=46 SRC="FIGDIR/small/694927v1_ufig1.gif" ALT="Figure 1"> View larger version (10K): org.highwire.dtl.DTLVardef@1b39294org.highwire.dtl.DTLVardef@5c3578org.highwire.dtl.DTLVardef@1ba827forg.highwire.dtl.DTLVardef@1cd8bd1_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗

bioRxiv2025

Cell-free protein synthesis as a method to rapidly screen machine learning-directed protease variants

Machine learning (ML) tools have revolutionised protein structure prediction, engineering and design, but the best ML tool is only as good as the training data it learns from. To obtain high quality structural or functional data, protein purification is typically required, which is both time and resource consuming - especially at the scale required to train ML tools. Here, we showcase cell-free protein synthesis (CFPS) as a straightforward and fast tool for screening and scoring the activity of protein variants for ML workflows. We demonstrate the utility of the system by improving the kinetic qualities of a protease. By rapidly screening just 48 random variants to initially sample the fitness landscape, followed by 32 more targeted variants, we identified several protease variants with improved kinetic properties.

synthetic biology↗

bioRxiv2024

ATP Regeneration from Pyruvate in the PURE System

The Protein synthesis Using Recombinant Elements ( PURE) system is a minimal biochemical system capable of carrying out cell-free protein synthesis using defined enzymatic components. This study extends PURE by integrating an ATP regeneration system based on pyruvate oxidase, acetate kinase, and catalase. The new pathway generates acetyl phosphate from pyruvate, phosphate, and oxygen, which is used to rephosphorylate ATP in situ. Successful ATP regeneration requires a high initial concentration of[~] 10 mM phosphate buffer, which surprisingly does not affect the protein synthesis activity of PURE. The pathway can function independently or in combination with the existing creatine-based system in PURE; the combined system produces up to 233 {micro}g/ml of mCherry, an enhancement of 78% compared to using the creatine system alone. The results are reproducible across multiple batches of homemade PURE, and importantly also generalise to commercial systems such as PURExpress(R) from New England Biolabs. These results demonstrate a rational bottom-up approach to engineering PURE, paving the way for applications in cell-free synthetic biology and synthetic cell construction.

synthetic biology↗

bioRxiv2024

Large scale analysis of predicted protein structures links model features to in vivo behaviour

Rapid advancements in protein structure prediction methods have ushered in a new era of abundant and accurate structural data, providing opportunities to analyse proteins at a scale that has not been possible before. Here we show that features derived solely from predicted structures can be used to understand in vivo protein behaviour using data-driven methods. We found that these features were predictive of in vivo protein production for a set of designed antibodies, enabling identification of high-quality designs. Following on from this result, we calculated these features for a diverse set of {approx}500,000 predicted structures, and our analysis showed systematic variation between proteins from different organisms to such an extent that the tree of life could be recapitulated from these data. Given the high degree of functional constraint around the chemistry of proteins, this result is surprising, and could have important implications for the design and engineering of novel proteins.

bioinformatics↗

bioRxiv2020

A self-regenerating synthetic cell model

Self-regeneration is a fundamental function of all living systems. Here we demonstrate molecular self-regeneration in a synthetic cell model. By implementing a minimal transcription-translation system within microfluidic reactors, the system was able to regenerate essential protein components from DNA templates and sustained synthesis activity for over a day. By mapping genotype-phenotype landscapes combined with computational modeling we found that minimizing resource competition and optimizing resource allocation are both critically important for achieving robust system function. With this understanding, we achieved simultaneous regeneration of multiple proteins by determining the required DNA ratios necessary for sustained self-regeneration. This work introduces a conceptual and experimental framework for the development of a self-replicating synthetic cell.

synthetic biology↗

bioRxiv2018

Cell-free gene regulatory network engineering with synthetic transcription factors

Gene regulatory networks are ubiquitous in nature and critical for bottom-up engineering of synthetic networks. Transcriptional repression is a fundamental function that can be tuned at the level of DNA, protein, and cooperative protein - protein interactions, necessitating high-throughput experimental approaches for in-depth characterization. Here we used a cell-free system in combination with a high-throughput microfluidic device to comprehensively study the different tuning mechanisms of a synthetic zinc-finger repressor library, whose affinity and cooperativity can be rationally engineered. The device is integrated into a comprehensive workflow that includes determination of transcription factor binding energy landscapes and mechanistic modeling, enabling us to generate a library of well-characterized synthetic transcription factors and corresponding promoters, which we then used to build gene regulatory networks de novo. The well-characterized synthetic parts and insights gained should be useful for rationally engineering gene regulatory networks and for studying the biophysics of transcriptional regulation.

synthetic biology↗