Biology subjects

Westbrook, A.

Publications and source records attributed to Westbrook, A..

4 recordsLinked to original sources

bioRxiv2018

The Subjective Value of Cognitive Effort is Encoded by a Domain-General Valuation Network

Cognitive control is necessary for goal-directed behavior, yet people treat control as costly, discounting goal value by cognitive demands in a similar manner as they would for delayed or risky outcomes. It is unclear, however, whether a putatively domain-general valuation network implicated in other cost domains also encodes the subjective value (SV) of cognitive effort. Here, we demonstrate that a valuation network, centered on the ventromedial prefrontal cortex and ventral striatum, also encodes SV during cognitive effort-based decision-making. We doubly dissociate this network from a primarily frontoparietal network recruited as a function of decision difficulty. We also find evidence that SV signals predict choice and are influenced by state and trait motivation, including sensitivity to reward and anticipated task performance. These findings unify cognitive effort with other cost domains, and inform physiological mechanisms of SV representations underlying the willingness to expend cognitive effort.

neuroscience↗

bioRxiv2018

Distinct timescales of RNA regulators enable the construction of a genetic pulse generator

To build complex genetic networks with predictable behaviours, synthetic biologists use libraries of modular parts that can be characterized in isolation and assembled together to create programmable higher-order functions. Characterization experiments and computational models for gene regulatory parts operating in isolation are routinely employed to predict the dynamics of interconnected parts and guide the construction of new synthetic devices. Here, we individually characterize two modes of RNA-based transcriptional regulation, using small transcription activating RNAs (STARs) and CRISPR interference (CRISPRi), and show how their distinct regulatory timescales can be used to engineer a composed feedforward loop that creates a pulse of gene expression. We use a cell-free transcription-translation system (TXTL) to rapidly characterize the system, and we apply Bayesian inference to extract kinetic parameters for an ODE-based mechanistic model. We then demonstrate in simulation and verify with TXTL experiments that the simultaneous regulation of a single gene target with STARs and CRISPRi leads to a pulse of gene expression. Our results suggest the modularity of the two regulators in an integrated genetic circuit, and we anticipate that construction and modeling frameworks that can leverage this modularity will become increasingly important as synthetic circuits increase in complexity.

synthetic biology↗

bioRxiv2017

Computational design of Small Transcription Activating RNAs (STARs) for versatile and dynamic gene regulation

A longstanding goal of synthetic biology has been the programmable control of cellular functions. Central to this goal is the creation of versatile regulatory toolsets that allow for programmable control of gene expression. Of the many regulatory molecules available, RNA regulators offer the intriguing possibility of de novo design - allowing for the bottom-up molecular-level design of genetic control systems. Here we present a computational design approach for the creation of a bacterial regulator called Small Transcription Activating RNAs (STARs) and create a library of high-performing and orthogonal STARs that achieve up to [~]9000-fold gene activation. We then demonstrate the versatility of RNA-based transcription control by showing the broad utility of STARs - from acting synergistically with existing constitutive and inducible regulators, to reprogramming cellular phenotypes and controlling multigene metabolic pathway expression. Finally, we combine these new STARs with themselves and CRISPRi transcriptional repressors to deliver new types of RNA-based genetic circuitry that allow for sophisticated and temporal control of gene expression.

synthetic biology↗

bioRxiv2016

Comparative genomics of beetle-vectored fungal pathogens reveals a reduction in genome size and independent evolution of pathogenicity of two tree pathogens

O_LIGeosmithia morbida is an emerging fungal pathogen which serves as a paradigm for examining the evolutionary processes behind pathogenicity because it is one of two known pathogens within a genus of mostly saprophytic, beetle-associated, fungi. This pathogen causes thousand cankers disease in black walnut trees and is vectored into the host via the walnut twig beetle. G. morbida was first detected in western US and currently threatens the timber industry concentrated in eastern US.\nC_LIO_LIWe sequenced the genomes of G. morbida and two non-pathogenic Geosmithia species and compared these species to other fungal pathogens and nonpathogens to identify genes under positive selection in G. morbida that may be associated with pathogenicity.\nC_LIO_LIG. morbida possesses one of the smallest genomes among the fungal species observed in this study, and one of the smallest fungal pathogen genomes to date. The enzymatic profile is this pathogen is very similar to its relatives.\nC_LIO_LIOur findings indicate that genome reduction is an important adaptation during the evolution of a specialized lifestyle in fungal species that occupy a specific niche, such as beetle vectored tree pathogens. We also present potential genes under selection in G. morbida that could be important for adaptation to a pathogenic lifestyle.\nC_LI

evolutionary biology↗