C-reactive protein-guided use of procalcitonin in COVID-19.

Background: A low procalcitonin (PCT) concentration facilitates exclusion of bacterial co-infections in COVID-19, but high costs associated with PCT measurements preclude universal adoption. Changes in inflammatory markers, including C-reactive protein (CRP), can be concordant, and predicting low PCT concentrations may avoid costs of redundant tests and support more cost-effective deployment of this diagnostic biomarker.

Objectives: To explore whether, in COVID-19, low PCT values could be predicted by the presence of low CRP concentrations.

A mechanistic model of the BLADE platform predicts performance characteristics of 256 different synthetic DNA recombination circuits.

Boolean logic and arithmetic through DNA excision (BLADE) is a recently developed platform for implementing inducible and logical control over gene expression in mammalian cells, which has the potential to revolutionise cell engineering for therapeutic applications. This 2-input 2-output platform can implement 256 different logical circuits that exploit the specificity and stability of DNA recombination. Here, we develop the first mechanistic mathematical model of the 2-input BLADE platform based on Cre- and Flp-mediated DNA excision.

Mechanistic modelling of tyrosine recombination reveals key parameters determining the performance of a CAR T cell switching circuit.

Inducible genetic switches based on tyrosine recombinase-based DNA excision are a promising platform for the regulation and control of chimeric antigen receptor (CAR) T cell activity in cancer immunotherapy. These switches exploit the increased stability of DNA excision in tyrosine recombinases through an inversion-excision circuit design. Here, the authors develop the first mechanistic mathematical model of switching dynamics in tyrosine recombinases and validate it against experimental data through both global optimisation and statistical approximation approaches.

Modeling the architecture of the regulatory system controlling methylenomycin production in .

Background: The antibiotic methylenomycin A is produced naturally by Streptomyces coelicolor A3(2), a model organism for streptomycetes. This compound is of particular interest to synthetic biologists because all of the associated biosynthetic, regulatory and resistance genes are located on a single cluster on the SCP1 plasmid, making the entire module easily transferable between different bacterial strains. Understanding further the regulation and biosynthesis of the methylenomycin producing gene cluster could assist in the identification of motifs that can be exploited in synthetic regulatory systems for the rational engineering of novel natural products and antibiotics.

Mechanistic Modeling of a Rewritable Recombinase Addressable Data Module.

Many of the most important applications predicted to arise from Synthetic Biology will require engineered cellular memory with the capability to store data in a rewritable and reversible manner upon induction by transient stimuli. DNA recombination provides an ideal platform for cellular data storage and has allowed the development of a rewritable recombinase addressable data (RAD) module, capable of efficient data storage within a chromosome. Here, we develop the first detailed mechanistic model of DNA recombination, and validate it against a new set of in vitro data on recombination efficiencies across a range of different concentrations of integrase and gp3.

Development and experimental validation of a mechanistic model of in vitro DNA recombination.

Engineering cellular memory is a key area of research in which Synthetic Biology has already begun to make significant impacts. Recent work elucidating transcriptional memory devices has paved the way for the creation of bistable genetic switches based on DNA recombination. Attempts to experimentally design and build synthetic systems using recombinases have thus far been hindered by a lack of validated computational models that capture the mechanistic basis of DNA recombination.