Biology subjects

Davis, J.

Publications and source records attributed to Davis, J..

6 recordsLinked to original sources

bioRxiv2018

Different factors shape pigmentation and other physiological trait variation within and between species in the Drosophila americana group.

BackgroundDisentangling the selective factors shaping adaptive trait variation is an important but challenging task. Many studies--especially in Drosophila--have documented trait variation along latitudinal or altitudinal clines, but frequently lack resolution about specific environmental gradients that could be causal selective agents, and often do not investigate covariation between traits simultaneously. Here we examined variation in multiple macroecological factors across geographic space and their associations with variation in three physiological traits (desiccation resistance, UV resistance, and pigmentation) at both population and species scales, to address the role of abiotic environment in shaping trait variation.\n\nResultsUsing environmental data from collection locations of three North American Drosophila species--D. americana americana, D. americana texana and D. novamexicana--we identified two primary axes of macroecological variation; these differentiated species habitats and were strongly loaded for precipitation and moisture variables. In nine focal populations (three per species) assayed for each trait, we detected significant species-level variation for both desiccation resistance and pigmentation, but not for UV resistance. Species-level trait variation was consistent with differential natural selection imposed by variation in habitat water availability, although patterns of variation differed between desiccation resistance and pigmentation, and we found little evidence for pleiotropy between traits.\n\nConclusionsOur multi-faceted approach enabled us to identify potential agents of natural selection and examine how they might influence the evolution of multiple traits at different evolutionary scales. Our findings highlight that environmental factors influence functional trait variation in ways that can be complex, and point to the importance of studies that examine these relationships at both population- and species-levels.

evolutionary biology↗

bioRxiv2018

Trafficking of Cholesterol from Lipid Droplets to Mitochondria in Bovine Luteal Cells: Acute Control of Progesterone Synthesis

The corpus luteum (CL) is a transient endocrine gland that synthesizes and secretes the steroid hormone, progesterone. Progesterone biosynthesis is a complex process, converting cholesterol via a series of enzymatic reactions, into progesterone. Lipid droplets in luteal cells store cholesterol in the form of cholesterol esters, which can be utilized for steroidogenesis. In small luteal cells, luteinizing hormone (LH) increases intracellular cAMP concentrations leading to activation of protein kinase A (PKA), which phosphorylates downstream proteins, such as hormone sensitive lipase (HSL). Phosphorylation of HSL at Ser563 leads to increased HSL activation and association with lipid droplets, events which theoretically release cholesterol, which can be used for progesterone synthesis. Bovine CL were obtained from a local abattoir, dispersed, and luteal cells were enriched for SLC via centrifugal elutriation. Our results reveal that LH, forskolin, and cAMP induce HSL phosphorylation at Ser563and Ser660. Moreover, inhibiting HSL activity attenuates LH-induced P4 synthesis. Confocal analysis revealed that LH stimulates translocation of HSL to lipid droplets and mitochondria. Furthermore, LH increased trafficking of cholesterol from the lipid droplets to the mitochondria which was dependent on both PKA and HSL activation. These results demonstrate cholesterol stored in lipid droplets are utilized for LH-induced progesterone biosynthesis. Likewise, PKA-induced activation of HSL is required for release and trafficking of cholesterol from the lipid droplets to the mitochondria. Taken together, these findings support a role for a PKA/HSL signaling pathway in response to LH and demonstrate the dynamic relationship between PKA, HSL, and the lipid droplets in the synthesis of progesterone.\n\nHighlightsO_LILH and PKA induce HSL phosphorylation at Ser563and Ser660\nC_LIO_LIHSL is required for optimal LH-induced P4 synthesis\nC_LIO_LILH stimulates translocation of HSL to lipid droplets and mitochondria\nC_LIO_LILH stimulated trafficking of cholesterol from lipid droplets to mitochondria\nC_LI

cell biology↗

bioRxiv2018

Yes-associated protein (YAP) is required in maintaining normal ovarian follicle development and function

Yes-associated protein (YAP) is one of the major components of the Hippo signaling pathway, also known as the Salvador/Warts/Hippo (SWH) pathway. Although the exact extracellular signal that controls the Hippo pathway is currently unknown, increasing evidence supports a critical role of the Hippo pathway in embryonic development, regulation of organ size, and carcinogenesis. The ovary is one of few adult tissues that exhibit cyclical changes. Ovarian follicles, the basic units of ovary, are composed of a single oocyte surrounded by expanding layers of granulosa and theca cells. Granulosa cells (GCs) produce sex steroids and growth factors, which facilitate the development of the follicle and maturation of the oocyte. It has been reported that YAP is highly expressed in human GC tumors, but the role of YAP in normal ovarian follicle development is largely unknown. In current study, we examined YAP expression in bovine ovaries. We demonstrate that downstream hippo signaling effector protein, YAP and transcription co-activator, TAZ, are present and localization of both YAP and TAZ are density-dependent. Likewise, YAP and TAZ are critically involved in granulosa cell proliferation. Furthermore, reducing YAP in granulosa cells inhibits FSH-induced aromatase expression and estradiol biosynthesis. The data suggest that YAP plays an important role in the development of ovarian follicles and estradiol synthesis, which are necessary for maintaining normal ovarian function.

cell biology↗

bioRxiv2018

New inhibitors of Mycobacterium tuberculosis identified using systems chemical biology

New antibiotics are needed to combat rising resistance, with new Mycobacterium tuberculosis (Mtb) drugs of highest priority. Conventional whole-cell and biochemical antibiotic screens have failed. We developed a novel strategy termed PROSPECT (PRimary screening Of Strains to Prioritize Expanded Chemistry and Targets) in which we screen compounds against pools of strains depleted for essential bacterial targets. We engineered strains targeting 474 Mtb essential genes and screened pools of 100-150 strains against activity-enriched and unbiased compounds libraries, measuring > 8.5-million chemical-genetic interactions. Primary screens identified >10-fold more hits than screening wild-type Mtb alone, with chemical-genetic interactions providing immediate, direct target insight. We identified > 40 novel compounds targeting DNA gyrase, cell wall, tryptophan, folate biosynthesis, and RNA polymerase, as well as inhibitors of a novel target EfpA. Chemical optimization yielded EfpA inhibitors with potent wild-type activity, thus demonstrating PROSPECTs ability to yield inhibitors against novel targets which would have eluded conventional drug discovery.

microbiology↗

bioRxiv2018

Vesicular delivery of the antifungal antibiotics of Lysobacter enzymogenes C3

Lysobacter enzymogenes C3 is a predatory strain of gram-negative gliding bacteria that produces antifungal antibiotics by the polyketide synthetic pathway. Outer membrane vesicles (OMV) are formed as a stress response and can deliver virulence factors to host cells. The production of OMV by C3 and their role in antifungal activity are reported here. Vesicles in the range of 130-150 nm in diameter were discovered in the cell-free supernatants of C3 cultures. These OMV contain molecules characteristic of bacterial outer membranes, such as lipopolysaccharide and phospholipids. In addition, they contain chitinase activity and essentially all of the heat stable antifungal activity in cell supernatants. We show here that C3 OMV can directly inhibit growth of the yeast Saccharomyces cerevisiae as well as the filamentous fungus Fusarium subglutinans. The activity is dependent on physical contact between OMV and the cells. Furthermore, fluorescent lipid labeling of C3 OMV demonstrated transfer of the membrane-associated probe to yeast cells, suggesting the existence of a mechanism of delivery for membrane-associated molecules. Mass spectrometric analysis of C3 OMV extracts indicates the presence of molecules with molecular weights identical to some of the previously identified antifungal products of C3. These data together suggest that OMV act as an important remote mobile component of predation by Lysobacter.\n\nImportanceThe data presented here suggest a newly discovered function of outer membrane vesicles (OMV) that are produced from the outer membrane of the bacterial species Lysobacter enzymogenes C3. We show that these OMV can be released from the surface of the cells to deliver antibiotics to target fungal organisms as a mechanism of killing or growth inhibition. Understanding the role of OMV in antibiotic delivery can generally lead to improved strategies for dealing with antibiotic-resistant organisms. These results also add to the evidence that some bacterially produced antibiotics can be discovered and purified using methods designed for isolation of nanoscale vesicles. Information on these systems can lead to better identification of active molecules or design of delivery vehicles for these molecules.

microbiology↗

bioRxiv2017

Developing an in silico minimum inhibitory concentration panel test for Klebsiella pneumoniae

Antimicrobial resistant infections are a serious public health threat worldwide. Whole genome sequencing approaches to apidly identify pathogens and predict antibiotic resistance phenotypes are becoming more feasible and may offer a way to reduce clinical test turnaround times compared to conventional culture-based methods, and in turn, improve patient outcomes. In this study, we use whole genome sequence data from 1668 clinical isolates of Klebsiella pneumoniae to develop a XGBoost-based machine learning model that accurately predicts minimum inhibitory concentrations (MICs) for 20 antibiotics. The overall accuracy of the model, within {+/-}1 two-fold dilution factor, is 92%. Individual accuracies are[≥]90% for 15/20 antibiotics. We show that the MICs predicted by the model correlate with known antimicrobial resistance genes. Importantly, the genome-wide approach described in this study offers a way to predict MICs for isolates without knowledge of the underlying gene content. This study shows that machine learning can be used to build a complete in silico MIC prediction panel for K. pneumoniae and provides a framework for building MIC prediction models for other pathogenic bacteria.

bioinformatics↗