Biology subjects

Castillo-Hair, S.

Publications and source records attributed to Castillo-Hair, S..

3 recordsLinked to original sources

bioRxiv2024

Quantitative design of cell type-specific mRNA stability from microRNA expression data

Limiting expression to target cell types or states is a longstanding goal in gene therapy, which could be met by sensing endogenous microRNA. However, an unclear association between microRNA expression and activity currently hampers such an approach. Here, we probe this relationship by measuring the stability of synthetic microRNA-responsive 3UTRs across 10 cell lines in a library format. By systematically addressing biases in microRNA expression data and confounding factors such as microRNA crosstalk, we demonstrate that a straightforward model can quantitatively predict the stability of reporters containing full microRNA target sites purely from expression data. We use this model to design constructs with previously unattainable response patterns across our cell lines. We then generalize this approach to primary tissues and cells and show that mRNA can be engineered to be differentially active between rested and exhausted T cell states. The rules we derive for microRNA expression data selection and processing should apply to microRNA-responsive devices for any environment with available expression data.

synthetic biology↗

bioRxiv2023

BatCRISPRi: Bacillus titratable CRISPRi for dynamic control in Bacillus subtilis

The discovery of new genes regulating essential biological processes has become increasingly important, and CRISPRi has emerged as a powerful tool for achieving this goal. This method has been used in many model organisms to decrease the expression of specific genes and assess their impact on phenotype. Pooled CRISPRi libraries in bacteria have been particularly useful in discovering new regulators of growth, division, and other biological processes. However, these libraries rely on the induction of dCas9 via an inducible promoter, which can be problematic due to promoter leakiness. This is a widespread phenomenon of any inducible promoter that can result in the unwanted downregulation of genes and the emergence of genetic suppressors when essential genes are knocked down. To overcome this issue, we have developed a novel strategy that eliminates dCas9 leakiness and enables reversible knockdown control using the rapamycin-dependent degron system in Bacillus subtilis. This degron system causes rapid degradation of dCas9, resulting in an almost instant reset of the system. Our results demonstrate that it is possible to achieve zero CRISPRi activity in the uninduced state and full activity in the induced state. This improved CRISPRi system will enable researchers to investigate phenotypic changes more effectively while reducing the undesirable effects of leaky expression and noise in their phenotypic data. Moreover, a rapid degradation system could serve as a tool for dynamic perturbation before compensation mechanisms or stress responses kick in. Finally, this approach can be adapted to other organisms and other promoter-inducible systems, potentially opening up strategies for tighter control of gene expression.

synthetic biology↗

bioRxiv2021

Meeting Measurement Precision Requirements for Effective Engineering of Genetic Regulatory Networks

Reliable, predictable engineering of cellular behavior is one of the key goals of synthetic biology. As the field matures, biological engineers will become increasingly reliant on computer models that allow for the rapid exploration of design space prior to the more costly construction and characterization of candidate designs. The efficacy of such models, however, depends on the accuracy of their predictions, the precision of the measurements used to parameterize the models, and the tolerance of biological devices for imperfections in modeling and measurement. To better understand this relationship, we have derived an Engineering Error Inequality that provides a quantitative mathematical bound on the relationship between predictability of results, model accuracy, measurement precision, and device characteristics. We apply this relation to estimate measurement precision requirements for engineering genetic regulatory networks given current model and device characteristics, recommending a target standard deviation of 1.5-fold. We then compare these requirements with the results of an interlaboratory study to validate that these requirements can be met via flow cytometry with matched instrument channels and an independent calibrant. Based on these results, we recommend a set of best practices for quality control of flow cytometry data and discuss how these might be extended to other measurement modalities and applied to support further development of genetic regulatory network engineering.

synthetic biology↗