An important goal of synthetic biology involves the extension and standardization of novel biological elements for applications in medicine and biotechnology. Transcriptional interference, occurring in sets of convergent promoters, offers a promising mechanism for building elements for the design of tunable gene regulation. Here, we investigate the transcriptional interference mechanisms of antisense roadblock and RNA polymerase traffic in a set of convergent promoters as novel modules for synthetic biology. We show examples of elements, including antisense roadblock, relative promoter strengths, interpromoter distance, and sequence content that can be tuned to give rise to repressive as well as cooperative behaviors, therefore resulting in distinct gene expression patterns. Our approach will be useful toward engineering new biological devices and will bring new insights to naturally occurring cis-antisense systems. Therefore, we are reporting a new biological tool that can be used for synthetic biology.
Background
Mass testing for early identification and isolation of infectious COVID-19 individuals is efficacious for reducing disease spread. Antigen-detecting rapid diagnostic tests (Ag-RDT) may be suitable for testing strategies; however, benchmark comparisons are scarce.
Methods
We used 286 nasopharyngeal specimens from unexposed asymptomatic individuals collected between December 2020 and January 2021 to assess five Ag-RDTs marketed by Abbott, Siemens, Roche Diagnostics, Lepu Medical, and Surescreen.
Results
For the overall sample, the performance parameters of Ag-RDTs were as follows: Abbott assay, sensitivity 38.6% (95%CI 29.1–48.8) and specificity 99.5% (97–100%); Siemens, sensitivity 51.5% (41.3–61.6) and specificity 98.4% (95.3–99.6); Roche, sensitivity 43.6% (33.7–53.8) and specificity 96.2% (92.4–98.5); Lepu, sensitivity 45.5% (35.6–55.8) and specificity 89.2% (83.8–93.3%); Surescreen, sensitivity 28.8% (20.2–38.6) and specificity 97.8% (94.5–99.4%). For specimens with cycle threshold (Ct) <30 in RT-qPCR, all Ag-RDT achieved a sensitivity ≥70%. The modelled negative- and positive-predictive value for 1% prevalence were >99% and <50%, respectively.
Conclusions
When screening unexposed asymptomatic individuals, two Ag-RDTs achieved sensitivity ≥80% for specimens with Ct<30 and specificity ≥96%. The estimated negative predictive value suggests the suitability of Ag-RDTs for mass screenings of SARS-CoV-2 infection in the general population.
Antisense transcription has been extensively recognized as a regulatory mechanism for gene expression across all kingdoms of life. Despite the broad importance and extensive experimental determination of cis-antisense transcription, relatively little is known about its role in controlling cellular switching responses. Growing evidence suggests the presence of non-coding cis-antisense RNAs that regulate gene expression via antisense interaction. Recent studies also indicate the role of transcriptional interference in regulating expression of neighboring genes due to traffic of RNA polymerases from adjacent promoter regions. Previous models investigate these mechanisms independently, however, little is understood about how cells utilize coupling of these mechanisms in advantageous ways that could also be used to design novel synthetic genetic devices. Here, we present a mathematical modeling framework for antisense transcription that combines the effects of both transcriptional interference and cis-antisense regulation. We demonstrate the tunability of transcriptional interference through various parameters, and that coupling of transcriptional interference with cis-antisense RNA interaction gives rise to hypersensitive switches in expression of both antisense genes. When implementing additional positive and negative feed-back loops from proteins encoded by these genes, the system response acquires a bistable behavior. Our model shows that combining these multiple-levels of regulation allows fine-tuning of system parameters to give rise to a highly tunable output, ranging from a simple-first order response to biologically complex higher-order response such as tunable bistable switch. We identify important parameters affecting the cellular switch response in order to provide the design principles for tunable gene expression using antisense transcription. This presents an important insight into functional role of antisense transcription and its importance towards design of synthetic biological switches.
The coronavirus disease 2019 (COVID-19) pandemic has affected the world radically since 2020. Spain was one of the European countries with the highest incidence during the first wave. As a part of a consortium to monitor and study the evolution of the epidemic, we sequenced 2,170 samples, diagnosed mostly before lockdown measures. Here, we identified at least 500 introductions from multiple international sources and documented the early rise of two dominant Spanish epidemic clades (SECs), probably amplified by superspreading events. Both SECs were related closely to the initial Asian variants of SARS-CoV-2 and spread widely across Spain. We inferred a substantial reduction in the effective reproductive number of both SECs due to public-health interventions (
R
e
< 1), also reflected in the replacement of SECs by a new variant over the summer of 2020. In summary, we reveal a notable difference in the initial genetic makeup of SARS-CoV-2 in Spain compared with other European countries and show evidence to support the effectiveness of lockdown measures in controlling virus spread, even for the most successful genetic variants.
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