Biology subjects

Hillenmeyer, M. E.

Publications and source records attributed to Hillenmeyer, M. E..

3 recordsLinked to original sources

bioRxiv2020

Identification of polyketide biosynthetic gene clusters that harbor self-resistance target genes

BackgroundPolyketide secondary metabolites have been a rich source of antibiotic discovery for decades. Thousands of novel polyketide synthase (PKS) gene clusters have been identified in recent years with advances in DNA sequencing. However, experimental characterization of novel and useful PKS activities remains complicated. As a result, computational tools to analyze sequence data are essential to identify and prioritize potentially novel PKS activities. Here we exploit the concept of genetically-encoded self-resistance to identify and rank biosynthetic gene clusters for their potential to encode novel antibiotics. ResultsTo identify PKS genes that are likely to produce an antibacterial compound, we developed an automated method to identify and catalog clusters that harbor potential self-resistance genes. We manually curated a list of known self-resistance genes and searched all NCBI genome databases for homologs of these self-resistance genes in biosynthetic gene clusters. The algorithm takes into account (1) the distance of the potential self-resistance gene to a core enzyme in the biosynthetic gene cluster; (2) the presence of a duplicated housekeeping copy of the self-resistance gene; (3) the presence of close homologs of the biosynthetic gene cluster in diverse species also harboring the putative self-resistance gene; (4) evidence for coevolution of the self-resistance gene and core biosynthetic gene; and (5) self-resistance gene ubiquity. We generated a catalog of 190 unique PKS clusters whose products likely target known enzymes of antibacterial importance. We also present an expanded set of putative self-resistance genes that may be useful in identifying small molecules active against novel microbial targets. ConclusionsWe developed a bioinformatic approach to identify and rank biosynthetic gene clusters that likely harbor self-resistance genes and may produce compounds with antibacterial properties. We compiled a list of putative self-resistance genes for novel antibacterial targets, and of orphan PKS clusters harboring these targets. These catalogues are a resource for discovery of novel antibiotics.

bioinformatics↗

bioRxiv2018

Dissection of yeast pleiotropic drug resistance regulation reveals links between cell cycle regulation and control of drug pump expression

Eukaryotes utilize a highly-conserved set of drug efflux transporters to confer pleiotropic drug resistance (PDR). Despite decades of effort interrogating this process, multiple aspects of the PDR process, in particular PDR regulation, remain mysterious. In order to interrogate the regulation of this critical process, we have developed a small-molecule responsive biosensor that couples PDR transcriptional induction to growth rate in Saccharomyces cerevisiae. We applied this system to genome-wide screens for potential PDR regulators using the homozygous diploid deletion collection. These screens identified and characterized a series of genes with significant but previously uncharacterized roles in the modulation of the yeast PDR in addition to recapitulating previously-known factors involved in PDR regulation. Furthermore, we demonstrate that disruptions of the mitotic spindle checkpoint assembly lead to elevated PDR response in response to exposure to certain compounds. These results not only establish our biosensor system as a viable tool to investigate PDR in high-throughput, but also uncovers novel control mechanisms governing PDR response and a previously uncharacterized link between this process and cell cycle regulation.\n\nSignificancePleiotropic drug resistance (PDR) is a conserved mechanism by which cells utilize membrane bound pumps to transport chemicals out of the cell. Here, we develop a growth-based biosensor system in yeast that enables high-throughput identification of factors that transcriptionally regulate PDR. Among the novel PDR regulators identified here, we show that spindle assembly checkpoint (SAC) proteins, which are important for cell cycle regulation, inhibit hyperactivation of PDR upon drug treatment. This result provides insights into PDR regulation, as well as potential targets for therapeutic intervention, particularly in chemoresistant cancers where the cell cycle regulation is often disrupted.

genetics↗

bioRxiv2018

HEx: a heterologous expression platform for the discovery of fungal natural products

For decades, fungi have been a source of FDA-approved natural products such as penicillin, cyclosporine, and the statins. Recent breakthroughs in DNA sequencing suggest that millions of fungal species exist on Earth with each genome encoding pathways capable of generating as many as dozens of natural products. However, the majority of encoded molecules are difficult or impossible to access because the organisms are uncultivable or the genes are transcriptionally silent. To overcome this bottleneck in natural product discovery, we developed the HEx (Heterologous EXpression) synthetic biology platform for rapid, scalable expression of fungal biosynthetic genes and their encoded metabolites in Saccharomyces cerevisiae. We applied this platform to 41 fungal biosynthetic gene clusters from diverse fungal species from around the world, 22 of which produced detectable compounds. These included novel compounds with unexpected biosynthetic origins, particularly from poorly studied species. This result establishes the HEx platform for rapid discovery of natural products from any fungal species, even those that are uncultivable, and opens the door to discovery of the next generation of natural products.\n\nSummaryHere we present the largest scale effort reported to date toward the complete refactoring and heterologous expression of fungal biosynthetic gene clusters utilizing HEx, a novel synthetic biology platform.

synthetic biology↗