Iterative library generation and FACS screening for increased production of the pharmaceutical precursor L-DOPA in yeast

Optimizing microbial hosts for large-scale production of valuable metabolites has two main challenges: (i) maximizing the expression and function of the proteins needed to perform the desired reactions; and, (ii) adapting host metabolism to support these new reactions and remove unwanted or toxic side products. Although considerable effort has been focused on the first challenge, the methodology developed and described in this dissertation addresses the second challenge. As a test case, I sought to increase production of L-DOPA, a pharmaceutically-relevant metabolite and precursor to the benzylisoquinoline (BIA) class of medicinal molecules, in the yeast S. cerevisiae. Production of L-DOPA and derived BIAs in yeast can be accomplished through the action of CYP76AD1, a heterologously-expressed cytochrome P450 enzyme from beet. Hence, I sought to devise strategies for isolating strain variants that carry genome modifications that improve CYP76AD1-dependent L-DOPA production. My approach was based on the assumption that endogenous factors in yeast restrain or impede this process. To perform multiple rounds of mutagenesis and screening, we constructed an in vitro barcoded transposon-disruption library. This library was introduced and integrated into the host genome by homologous recombination. The resulting variants were screened using a biosensor in which L-DOPA produced by the cells is converted to a fluorescent derivative via the action of the enzyme DOPA dioxygenase (DOD). Thus, I was able to use high-throughput fluorescence-activated cell sorting (FACS) to enrich for the desired variants. I conducted this approach, iteratively, for three rounds, i.e. improved strains obtained from the preceding rounds were transformed with the transposon-disruption library and re-screened. In the first two rounds of screening, I identified deletions that improved biosensor compartmentalization and, consequently, improved the reliability of the read-out for L-DOPA production. In the final round, I discovered that deletion of the gene encoding a heme oxygenase (HMX1) that is localized to the endoplasmic reticulum and involved in heme degradation increased both total cellular heme content and L-DOPA production (as monitored by measuring its derivative dopamine as a proxy). I demonstrated further that deleting HMX1 may represent a general strategy for improving the performance of heterologous P450 enzymes in yeast because the absence of Hmx1 also enhanced the ability of a second P450 enzyme, BM3, to generate its product

NeuroElectro: a window to the world's neuron electrophysiology data

The behavior of neural circuits is determined largely by the electrophysiological properties of the neurons they contain. Understanding the relationships of these properties requires the ability to first identify and catalog each property. However, information about such properties is largely locked away in decades of closed-access journal articles with heterogeneous conventions for reporting results, making it difficult to utilize the underlying data. We solve this problem through the NeuroElectro project: a Python library, RESTful API, and web application (at http://neuroelectro.org) for the extraction, visualization, and summarization of published data on neurons' electrophysiological properties. Information is organized both by neuron type (using neuron definitions provided by NeuroLex) and by electrophysiological property (using a newly developed ontology). We describe the techniques and challenges associated with the automated extraction of tabular electrophysiological data and methodological metadata from journal articles. We further discuss strategies for how to best combine, normalize and organize data across these heterogeneous sources. NeuroElectro is a valuable resource for experimental physiologists attempting to supplement their own data, for computational modelers looking to constrain their model parameters, and for theoreticians searching for undiscovered relationships among neurons and their properties

NeuroElectro: a window to the world's neuron electrophysiology data.

<p>The behavior of neural circuits is determined largely by the electrophysiological properties of the neurons they contain. Understanding the relationships of these properties requires the ability to first identify and catalog each property. However, information about such properties is largely locked away in decades of closed-access journal articles with heterogeneous conventions for reporting results, making it difficult to utilize the underlying data. We solve this problem through the NeuroElectro project: a Python library, RESTful API, and web application (at http://neuroelectro.org) for the extraction, visualization, and summarization of published data on neurons' electrophysiological properties. Information is organized both by neuron type (using neuron definitions provided by NeuroLex) and by electrophysiological property (using a newly developed ontology). We describe the techniques and challenges associated with the automated extraction of tabular electrophysiological data and methodological metadata from journal articles. We further discuss strategies for how to best combine, normalize and organize data across these heterogeneous sources. NeuroElectro is a valuable resource for experimental physiologists attempting to supplement their own data, for computational modelers looking to constrain their model parameters, and for theoreticians searching for undiscovered relationships among neurons and their properties.</p

Expanding the diversity of mycobacteriophages: insights into genome architecture and evolution.

Mycobacteriophages are viruses that infect mycobacterial hosts such as Mycobacterium smegmatis and Mycobacterium tuberculosis. All mycobacteriophages characterized to date are dsDNA tailed phages, and have either siphoviral or myoviral morphotypes. However, their genetic diversity is considerable, and although sixty-two genomes have been sequenced and comparatively analyzed, these likely represent only a small portion of the diversity of the mycobacteriophage population at large. Here we report the isolation, sequencing and comparative genomic analysis of 18 new mycobacteriophages isolated from geographically distinct locations within the United States. Although no clear correlation between location and genome type can be discerned, these genomes expand our knowledge of mycobacteriophage diversity and enhance our understanding of the roles of mobile elements in viral evolution. Expansion of the number of mycobacteriophages grouped within Cluster A provides insights into the basis of immune specificity in these temperate phages, and we also describe a novel example of apparent immunity theft. The isolation and genomic analysis of bacteriophages by freshman college students provides an example of an authentic research experience for novice scientists