Biology subjects

Taylor, D.

Publications and source records attributed to Taylor, D..

47 records · Page 3Linked to original sources

bioRxiv2020

Population history and the differential consequences of inbreeding and outcrossing in a plant metapoplation

The phenotypic consequences of inbreeding typically result in a fitness decline proportional to the increase in the inbreeding coefficient, F. This basic assumption of a predictable, inverse relationship between fitness and F has been questioned by a number of empirical studies. We explored the relationship between population history and inbreeding in a metapopulation of the plant Silene latifolia, for which long-term data are available for the historical size and spatial distribution of hundreds of local demes. We used a population genetic analysis to estimate gene flow and bi-parental inbreeding (FIS) in demes with different histories of spatial isolation. A controlled crossing experiment examined whether the effect of inbreeding and outcrossing on fitness-related traits varied with different histories of population size and isolation. Historically isolated demes experienced less gene flow and an increase in FIS, as well as significant inbreeding advantage and outbreeding depression for traits expressed early in life. The causes of variation in the F-fitness relationship among populations will include variance in the distribution of deleterious recessive alleles driven by aspects of population history, including population size, founder effects, gene flow, bi-parental inbreeding, and opportunities for the purging of genetic load. Our findings show that isolation and historical variation in population size likely contribute substantial variation in past inbreeding and the consequences of future inbreeding across the metapopulation.

evolutionary biology↗

bioRxiv2020

Cyto-nuclear linkage disequilibrium resulting from admixture

Previous studies of North American populations of the invasive plant Silene latifolia showed significant cyto-nuclear linkage disequilibrium (CNLD) between SNP variants of a mitochondrial gene (atp1) and the most common allele at nuclear microsatellite loci. Fields et al. (2014) hypothesized that this CNLD arose partially as a consequence of admixture that occurred during the colonization of North American (NA) populations of S latifolia via seed dispersal from genetically differentiated European populations that represent a portion of the native range of this species. In order to evaluate the plausibility of the admixture hypothesis, as opposed to metapopulation processes alone, we estimated CNLD for these same loci using data collected from eastern (EEU) and western (WEU) European populations of S. latifolia known to be genetically differentiated and likely sources of the spread of the study species to North America. We show that the CNLD found previously in NA populations of S. latifolia can be attributed to admixture of the previously isolated European demes coupled with decay since that time. Our applied framework allows the separation of the forces generating and dissolving statistical associations between alleles in cytoplasmic organelles and the nuclear genome and may thus be of utility in the study of plant or animal microbiomes.

evolutionary biology↗

bioRxiv2020

Multistage and transmission-blocking targeted antimalarials discovered from the open-source MMV Pandemic Response Box

New chemical matter is needed to target the divergent biology associated with the different life cycle stages of Plasmodium. Here, we report the parallel screening of the Medicines for Malaria Venture Pandemic Response Box to identify multistage-active and stage-specific compounds against various life cycle stages of Plasmodium parasites (asexual parasites, stage IV/V gametocytes, gametes, oocysts and liver stages) and for endectocidal activity. Hits displayed unique chemotypes and included two multistage-active compounds, 16 asexual-targeted, six with prophylactic potential and ten gametocyte-targeted compounds. Notably, four structurally diverse gametocyte-targeted compounds with potent transmission-blocking activity were identified: the JmjC inhibitor ML324, two azole antifungals including eberconazole, and the antitubercular clinical candidate SQ109. Besides ML324, none of these have previously attributed antiplasmodial activity, emphasizing the success of de novo parallel screening against different Plasmodium stages to deliver leads with novel modes-of-action. Importantly, the discovery of such transmission-blocking targeted compounds covers a previously unexplored base for delivery of compounds required for malaria elimination strategies.

microbiology↗

bioRxiv2020

Abl kinase deficiency promotes AKT pathway activation and prostate cancer progression and metastasis

Abl family kinases function as proto-oncogenes in various leukemias, and pro-tumor functions have been discovered for Abl kinases in solid tumors as well. However, a growing body of evidence indicates that Abl kinases can function to suppress tumor cell proliferation, motility, and in vivo tumor growth in some settings. To investigate the role of Abl kinases in prostate cancer, we generated Abl-deficient cells in a pre-clinical model of spontaneously metastatic, androgen-indifferent prostate cancer. Loss of Abl family kinase expression resulted in a highly aggressive, metastatic phenotype in vivo that was associated with AKT pathway activation, increased growth on 3D collagen matrix, and enhanced cell motility in vitro. Treatment of Abl kinase-expressing cells with the Abl kinase inhibitor imatinib phenocopied the malignant phenotypes observed in Abl-deficient tumor cells. In addition, inhibiting AKT pathway signaling abolished the increased 3D growth of Abl-deficient cells. Our data reveal that Abl family kinases can function as suppressors of prostate cancer progression and metastasis by restraining AKT signaling, a signaling pathway known to be associated with emergence of metastatic castration-resistant prostate cancer.

cancer biology↗

bioRxiv2020

Inhibition of IL34 unveils tissue-selectivity and is sufficient to reduce microglial proliferation in chronic neurodegeneration

The proliferation and activation of microglia, the resident macrophages in the brain, is a hallmark of many neurodegenerative diseases such as Alzheimers disease (AD) and prion disease. Colony stimulating factor 1 receptor (CSF1R) is critically involved in regulating microglial proliferation, and CSF1R blocking strategies have been recently used to modulate microglia in neurodegenerative diseases. However, CSF1R is broadly expressed by many cellular types and the impact of its inhibition on the innate immune system is still unclear. CSF1R can be activated by two independent ligands, CSF1 and interleukin 34 (IL-34). Recently, it has been reported that microglia development and maintenance depend on IL-34 signalling. In this study, we evaluate the inhibition of IL-34 as a novel strategy to reduce microglial proliferation in neurodegenerative diseases, using the ME7 model of prion disease. Selective inhibition of IL-34 showed no effects on peripheral macrophages populations in healthy mice, avoiding the side effects observed after CSF1R inhibition on the systemic compartment. However, we observed a reduction in microglial proliferation after IL-34 inhibition in prion-diseased mice, indicating that microglia could be more specifically targeted by reducing IL-34 and that this ligand plays an important role in the modulation of microglia population during neurodegeneration. Overall, our results suggest that control of microglial response through IL-34 blockade could be a potential therapeutic approach in neurodegenerative diseases.

neuroscience↗

bioRxiv2019

The role of SRSF3 splicing factor in generating circular RNAs

Circular RNAs (circRNAs) represent a novel class of non-coding RNAs that are emerging as potentially important regulators of gene expression. circRNAs are typically generated from host gene transcripts through a non-canonical back-splicing mechanism, whose regulation is still not well understood. To explore regulation of circRNAs in cancer, we generated sequence data from RNase R-resistant transcripts in human p493-6 B-lymphoid cells and identified thousands of novel as well as previously identified circRNAs. Approximately 40% of expressed genes generated a circRNA, with half of them generating multiple isoforms, suggesting the involvement of alternative back-splicing and regulatory RNA-binding proteins (RBPs). We observed that genes generating circRNAs with back-spliced exonic junctions were enriched for RBP recognition motifs, including multiple splicing factors, most notably SRSF3, a splicing factor known to promote exon inclusion. To test the role of SRSF3 role in circRNA production, we performed traditional RNA-seq in p493-6 B-lymphoid cells with and without SRSF3 knockdown, and identified 926 mRNA transcripts, whose canonical splicing was affected by SRSF3. We found that a subset (205) of these SRSF3 targets served as host transcripts for circRNA, suggesting that SRSF3 may regulate exon circularization. Since this splicing factor is deregulated in hematologic malignancies, we hypothesize that SRSF3-dependent circRNAs, similar to their mRNA counterparts, might contribute to the pathogenesis of lymphomas and leukemias.

molecular biology↗

bioRxiv2019

Transient crosslinking kinetics optimize gene cluster interactions

Our understanding of how chromosomes structurally organize and dynamically interact has been revolutionized through the lens of long-chain polymer physics. Major protein contributors to chromosome structure and dynamics are condensin and cohesin that stochastically generate loops within and between chains, and entrap proximal strands of sister chromatids. In this paper, we explore the ability of transient, protein-mediated, gene-gene crosslinks to induce clusters of genes, thereby dynamic architecture, within the highly repeated ribosomal DNA that comprises the nucleolus of budding yeast. We implement three approaches: live cell microscopy; computational modeling of the full genome during G1 in budding yeast, exploring four decades of timescales for transient crosslinks between 5kbp domains (genes) in the nucleolus on Chromosome XII; and, temporal network models with automated community (cluster) detection algorithms applied to the full range of 4D modeling datasets. The data analysis tools detect and track gene clusters, their size, number, persistence time, and their plasticity (deformation). Of biological significance, our analysis reveals an optimal mean crosslink lifetime that promotes pairwise and cluster gene interactions through \"flexible\" clustering. In this state, large gene clusters self-assemble yet frequently interact (merge and separate), marked by gene exchanges between clusters, which in turn maximizes global gene interactions in the nucleolus. This regime stands between two limiting cases each with far less global gene interactions: with shorter crosslink lifetimes, \"rigid\" clustering emerges with clusters that interact infrequently; with longer crosslink lifetimes, there is a dissolution of clusters. These observations are compared with imaging experiments on a normal yeast strain and two condensin-modified mutant cell strains. We apply the same image analysis pipeline to the experimental and simulated datasets, providing support for the modeling predictions.\n\nAuthor SummaryThe spatiotemporal organization of the genome plays an important role in cellular processes involving DNA, but remains poorly understood, especially in the nucleolus, which does not facilitate conventional techniques. Polymer chain models have shown ability in recent years to make accurate predictions of the dynamics of the genome. We consider a polymer bead-chain model of the full yeast genome during the interphase portion of the cell cycle, featuring special dynamic crosslinking to model the effects of structural maintenance proteins in the nucleolus, and investigate how the kinetic timescale on which the crosslinks bind and unbind affects the resulting dynamics inside the nucleolus. It was previously known that when this timescale is sufficiently short, large, stable clusters appear, but when it is long, there is no resulting structure. We find that there additionally exists a range of timescales for which flexible clusters appear, in which beads frequently enter and leave clusters. Furthermore, we demonstrate that these flexible clusters maximize the cross-communication between beads in the nucleolus. Finally, we apply network temporal community detection algorithms to identify what beads are in what communities at what times, in a way that is more robust and objective than conventional visual-based methods.

genomics↗

bioRxiv2018

Characterization of novel inhibition of indoleamine 2,3-dioxygenase by targeting its apo form.

Indoleamine-2,3-dioxygenase 1 (IDO1) is a heme-containing enzyme that catalyzes the rate-limiting step in the kynurenine pathway of tryptophan (TRP) metabolism. As an inflammation-induced immunoregulatory enzyme, pharmacological inhibition of IDO1 activity is currently being pursued as a potential therapeutic tool for the treatment of cancer and other disease states. As such, a detailed understanding of the mechanism of action of established and novel IDO1 inhibitors remains of great interest. Comparison of a newly-developed IDO1 inhibitor (GSK5628) to the existing best-in-class compound, epacadostat (Incyte), allows us to report on a unique inhibition mechanism for IDO1. Here, we demonstrate that GSK5628 inhibits IDO1 by competing with heme for binding to a heme-free conformation of the enzyme (apo-IDO1) while epacadostat coordinates its binding with the iron atom of the IDO1 heme cofactor. Comparison of these two compounds in cellular systems reveals a long-lasting inhibitory effect of GSK5628, undescribed for other known IDO1 inhibitors. Detailed characterization of this apo-binding mechanism for IDO1 inhibition may help design superior inhibitors or may confer a unique competitive advantage over other IDO1 inhibitors vis-a-vis specificity and pharmacokinetic parameters.

biochemistry↗

bioRxiv2017

Aberrant splicing in B-cell acute lymphoblastic leukemia

Aberrant splicing is a hallmark of leukemias with mutations in splicing factor (SF)-encoding genes. Here we investigated its prevalence in pediatric B-cell acute lymphoblastic leukemias (B-ALL), where SFs are not mutated. By comparing them to normal pro-B cells, we found thousands of aberrant local splice variations (LSVs) per sample, with 279 LSVs in 241 genes present in every comparison. These genes were enriched in RNA processing pathways and encoded ~100 SFs, e.g. hnRNPA1. hnRNPA1 3UTR was pervasively misspliced, yielding the transcript subject to nonsense-mediated decay. Thus, we knocked it down in B-lymphoblastoid cells, identified 213 hnRNPA1-dependent splicing events, and defined the hnRNPA1 splicing signature in pediatric leukemias. One of its elements was DICER1, a known tumor suppressor gene; its LSVs were consistent with reduced translation of DICER1 mRNA. Additionally, we searched for LSVs in other leukemia and lymphoma drivers and discovered 81 LSVs in 41 genes. 77 LSVs were confirmed using two large independent B-ALL RNA-seq datasets. In fact, the twenty most common B-ALL drivers showed higher prevalence of aberrant splicing than of somatic mutations. Thus, post-transcriptional deregulation of SF can drive widespread changes in B-ALL splicing and likely contribute to disease pathogenesis.

cancer biology↗

bioRxiv2017

GSA-Genie: a web application for gene set analysis

Gene set analysis is often used to interpret results from upstream analysis through predefined gene sets that are linked to biological features such as cell cycle or tumorgenesis. Gene sets have been defined in the literature via various criteria and are archived by numerous databases. We compiled over 2.3 million gene sets from 17 sources, and made them accessible through a web application, GSA-Genie. Selected gene sets can be analyzed online using one of 16 statistical methods. These methods can be grouped into two strategies: test of gene set over-representation within a gene list, or comparison of a gene-level statistics between gene set and background. GSA-Genie operates on a Shiny web server, hosted in a cloud instance within Amazon Web Services. GSA-Genie offers a broad selection of gene sets and statistical methods comparing to existing tools. GSA-Genie is freely available at http://gsagenie.awsomics.org.

bioinformatics↗

bioRxiv2017

RNA-Seq 2G: Online Analysis Of Differential Gene Expression With Comprehensive Options Of Statistical Methods

RNA-seq has become the most prevalent technology for measuring genome-wide gene expression, but the best practices for processing and analysing RNA-seq data are still an open question. Many statistical methods have been developed to identify genes differentially expressed between sample groups from RNA-seq data. These methods differ by their data distribution assumptions, choice of statistical test, and computational resource requirements. Over 25 methods of differential expression detection were validated and made available through a user-friendly web portal, RNA-seq 2G. All methods are suitable for analysing differential gene expression between two groups of samples. They commonly use a read count matrix derived from RNA-seq data as input and statistically compare groups for each gene. The web portal uses a Shiny app front-end and is hosted by a cloud-based server provided by Amazon Web Service. The comparison of methods showed that the data distribution assumption is the major determinant of differences between methods. Most methods are more likely to find that longer genes are differentially expressed, which substantially impacts downstream gene set-level analysis. Combining results from multiple methods can potentially diminish this bias. RNA-seq 2G makes the analysis of RNA-seq data more accessible and efficient, and is freely available at http://rnaseq2g.awsomics.org.

bioinformatics↗