Biology subjects

Piorino, F.

Publications and source records attributed to Piorino, F..

5 recordsLinked to original sources

bioRxiv2025

Harnessing Plasmid Crosstalk in Transcription Factor Mediated Cell-Free Biosensors

Plasmid crosstalk--unexpected changes to protein expression levels due to interactions between genetic cassettes in cell-free systems--complicates the creation of multi-plasmid cell-free tools. While the potential underlying mechanisms for crosstalk have been previously investigated, the practical impact of crosstalk on the implementation of cell-free genetic circuits has not been thoroughly examined. Here, we contextualize plasmid crosstalk in genetic circuits by examining its impact on the design and performance of multiple, diverse transcription factor biosensors. Guided by a deeper understanding, we harness crosstalk to enhance cell-free biosensor performance. Together, these findings demonstrate that plasmid crosstalk can serve as a tunable property in the development of cell-free genetic circuits.

synthetic biology↗

bioRxiv2025

Cell-free systems enable mechanistic characterization of genetically encoded RNA strand exchange circuits for programmable protein expression

Nucleic acid circuits are powerful tools for programming biology, but the design principles for operating these circuits in complex cellular environments remain poorly understood compared to simple in vitro settings. Cell-free expression systems (CFES) are uniquely suited to address this challenge, as they can integrate measurements ideal for either in vitro or in cyto settings. Further, because CFES are open systems, they enable a level of control over component concentration unattainable in cells. Here, we use cell-free systems to characterize genetically encoded RNA circuits that operate via toehold-mediated strand exchange (TMSE). These circuits have been extensively characterized in vitro and were recently deployed as translational riboregulators in E. coli, revealing key differences between the two environments. By systematically modulating the design parameters of these RNA circuits in both purified protein and lysate-based CFES, we elucidate the mechanisms linking TMSE to protein expression. Further, we combine measurements and alterations in CFES composition that are infeasible in cells to investigate interactions between cellular components and RNA circuit components, identifying a potential interaction with ribosomes that informs circuit design. Our results establish a unified set of principles for designing and operating genetically encoded TMSE circuits across in vitro, CFE, and bacterial environments, which should catalyze the widespread adoption of this platform for new applications in molecular programming, synthetic biology, and biotechnology.

bioengineering↗

bioRxiv2025

Characterizing Cell-Free Transcription and Translation Dynamics with Nucleic Acid-Based Assays

Characterization of cell-free expression (CFE) systems must expand beyond single spectrophotometric measurements of a green fluorescent protein to provide meaningful metrics of system performance during a CFE reaction and enable the development of predictable and reproducible CFE technologies. To date, comprehensive characterization of these systems has posed a formidable measurement challenge, as it requires time-course measurements of reactions involving endogenous components in addition to transcription and translation of a target genetic circuit added exogenously to the CFE reaction. To provide more informative characterization that is still easy to conduct and complements current practices, we demonstrate a measurement framework for transcription and translation dynamics. We use different nucleic acid templates to characterize a suite of Escherichia coli extracts prepared in house, as well as extracts and reconstituted systems available commercially. Notably, we include measurements of low-performing systems to assess the sensitivity of our measurement framework and elucidate metrics indicative of system performance. For all these CFE systems, we compute reaction metrics to enable quantitative comparison. We believe this is an accessible measurement framework that can complement existing characterization, provide informative data for developing CFE technologies, and be adopted for routine characterization.

synthetic biology↗

bioRxiv2025

Experimental Evaluation of AI-Driven Protein Design Risks Using Safe Biological Proxies

Advances in machine learning are providing leaps forward for beneficial applications of protein engineering, while also raising concerns about biosecurity. Recently, Wittmann et al. described an in silico pipeline of generative AI tools to reformulate sequences of concern (SOCs) as synthetic homologs that may evade detection by biosecurity screening software (BSS) used by nucleic acid synthesis providers. Experimental testing of synthetic homologs is required to ascertain the true severity of this vulnerability. We present a generalizable framework to assess biosecurity risk consisting of testing, evaluation, validation, and verification (TEVV) of AI-assisted protein design (AIPD). We determine that common AIPD models in use at the time this study was initiated (early 2024) are not yet powerful enough to reliably rewrite the sequence of a given protein, while both maintaining activity and evading detection by BSS.

synthetic biology↗

bioRxiv2021

Metabolic Dynamics in Escherichia coli-based Cell-Free Systems

The field of metabolic engineering has yielded remarkable accomplishments in using cells to produce valuable molecules, and cell-free expression (CFE) systems have the potential to push the field even further. However, CFE systems still face some outstanding challenges, including endogenous metabolic activity that is poorly understood yet has a significant impact on CFE productivity. Here, we use metabolomics to characterize the temporal metabolic changes in CFE systems and their constituent components, including significant metabolic activity in central carbon and amino acid metabolism. We find that while changing the reaction starting state via lysate pre-incubation impacts protein production, it has a comparatively small impact on metabolic state. We also demonstrate that changes to lysate preparation have a larger effect on protein yield and temporal metabolic profiles, though general metabolic trends are conserved. Finally, while we improve protein production through targeted supplementation of metabolic enzymes, we show that the endogenous metabolic activity is fairly resilient to these enzymatic perturbations. Overall, this work highlights the robust nature of CFE reaction metabolism as well as the importance of understanding the complex interdependence of metabolites and proteins in CFE systems to guide optimization efforts. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=135 SRC="FIGDIR/small/444339v1_ufig1.gif" ALT="Figure 1"> View larger version (19K): org.highwire.dtl.DTLVardef@1afbfc3org.highwire.dtl.DTLVardef@156a23aorg.highwire.dtl.DTLVardef@b494adorg.highwire.dtl.DTLVardef@18d03dc_HPS_FORMAT_FIGEXP M_FIG Abstract Figure C_FIG

systems biology↗