Biology subjects

Allen, J.

Publications and source records attributed to Allen, J..

5 recordsLinked to original sources

bioRxiv2018

Epigenetic changes induced by Bacteroides fragilis toxin

Enterotoxigenic Bacteroides fragilis (ETBF) is a gram negative, obligate anaerobe member of the gut microbial community in up to 40% of healthy individuals. This bacterium is found more frequently in people with colorectal cancer (CRC) and causes tumor formation in the distal colon of mice heterozygous for the adenomatous polyposis coli gene (Apc+/-); tumor formation is dependent on ETBF-secreted Bacteroides fragilis toxin (BFT). Though some of the immediate downstream effects of BFT on colon epithelial cells (CECs) are known, we still do not understand how this potent exotoxin causes changes in CECs that lead to tumor formation and growth. Because of the extensive data connecting alterations in the epigenome with tumor formation, initial experiments attempting to connect BFT-induced tumor formation with methylation in CECs have been performed, but the effect of BFT on other epigenetic processes, such as chromatin structure, remains unexplored. Here, the changes in chromatin accessibility (ATAC-seq) and gene expression (RNA-seq) induced by treatment of HT29/C1 cells with BFT for 24 and 48 hours is examined. Our data show that several genes are differentially expressed after BFT treatment and these changes correlate with changes in chromatin accessibility. Also, sites of increased chromatin accessibility are associated with a lower frequency of common single nucleotide variants (SNVs) in CRC and with a higher frequency of common differentially methylated regions (DMRs) in CRC. These data provide insight into the mechanisms by which BFT induces tumor formation. Further understanding of how BFT impacts nuclear structure and function in vivo is needed.\n\nImportanceColorectal cancer (CRC) is a major public health concern; there were approximately 135,430 new cases in 2017, and CRC is the second leading cause of cancer-related deaths for both men and women in the US (1). Many factors have been linked to CRC development, the most recent of which is the gut microbiome. Pre-clinical models support that enterotoxigenic Bacteroides fragilis (ETBF), among other bacteria, induce colon carcinogenesis. However, it remains unclear if the virulence determinants of any pro-carcinogenic colon bacterium induce DNA mutations or changes that initiate clonal CEC expansion. Using a reductionist model, we demonstrate that BFT rapidly alters chromatin structure and function consistent with capacity to contribute to CRC pathogenesis.

genomics↗

bioRxiv2018

Lung Cancer Explorer (LCE): an open web portal to explore gene expression and clinical associations in lung cancer

We constructed a lung cancer-specific database housing expression data and clinical data from over 6,700 patients in 56 studies. Expression data from 23 \"whole-genome\" based platforms were carefully processed and quality controlled, whereas clinical data were standardized and rigorously curated. Empowered by this lung cancer database, we created an open access web resource - the Lung Cancer Explorer (LCE), which enables researchers and clinicians to explore these data and perform analyses. Users can perform meta-analyses on LCE to gain a quick overview of the results on tumor vs normal differential gene expression and expression-survival association. Individual dataset-based survival analysis, comparative analysis, and correlation analysis are also provided with flexible options to allow for customized analyses from the user.

cancer biology↗

bioRxiv2017

First genome-wide analysis of an endangered lichen reveals isolation by distance and strong population structure

Lichenized fungi are evolutionarily diverse and ecologically important, but little is known about the processes driving diversification and genetic differentiation in these lineages. Though few studies have examined population genetic patterns in lichens, their geographic distributions are often assumed to be wholly shaped by ecological requirements rather than dispersal limitations. Furthermore, while their reproductive structures are observable, the lack of information about recombination mechanisms and rates can make inferences about reproductive strategies difficult. Here we investigate the population genomics of Cetradonia linearis, an endangered lichen narrowly endemic to the southern Appalachians of eastern North America, to test the relative contributions of environmental factors and geographic distance in shaping genetic structure, and to gain insights into the demography and reproductive biology of range restricted fungi. Analysis of genome-wide SNP data indicated strong evidence for both low rates of recombination and for strong isolation by distance, but did not support isolation by environment. Hindcast species distribution models and the spatial distribution of genetic diversity also suggested that C. linearis had a larger range during the last glacial maximum, especially in the southern portion of its current extent, consistent with previous findings in other southern Appalachian taxa. These results contribute to our understanding of intrinsic and extrinsic factors shaping genetic diversity and biogeographic patterns in C. linearis, and more broadly, in rare and endangered fungi.

evolutionary biology↗

bioRxiv2017

Quantitative mass imaging of single molecules in solution

The cellular processes underpinning life are orchestrated by proteins and their interactions. Structural and dynamic heterogeneity, despite being key to protein and drug function, continues to pose a fundamental challenge to existing analytical and structural methodologies used to study these associations. Here, we use interferometric scattering microscopy to mass-image single biomolecules in solution with <2% mass error, up to 19-kDa resolution and 1-kDa precision. Thereby, we resolve oligomeric distributions at high dynamic range, detect small-molecule binding, and mass-image biomolecules composed not only of amino acids, but also heterogeneous species, such as lipo- and glycoproteins. These capabilities enable us to characterize the molecular mechanisms of processes as diverse as oligomeric selfassembly, glycoprotein cross-linking, amyloidogenic protein aggregation, and actin polymerization. Interferometric scattering mass spectrometry (iSCAMS) provides spatially resolved access to the dynamics of biomolecular interactions ranging from those involving small molecules to mesoscopic assemblies, one molecule at a time.

biophysics↗

bioRxiv2017

Predicting Ligand-Dependent Tumors From Multi-Dimensional Signaling Features

Targeted therapies have shown significant patient benefit in about 5-10% of solid tumors that are addicted to a single oncogene. Here, we explore the idea of ligand addiction as a driver of tumor growth. High ligand levels in tumors have been shown to be associated with impaired patient survival, but targeted therapies have not yet shown great benefit in unselected patient populations. Using a novel approach of applying Bagged Decision Trees (BDT) to high-dimensional signaling features derived from a computational model, we can predict ligand dependent proliferation across a set of 58 cell lines. This mechanistic, multi-pathway model that features receptor heterodimerization, was trained on seven cancer cell lines and can predict signaling across two independent cell lines by adjusting only the receptor expression levels for each cell line. Interestingly, for patient samples the predicted tumor growth response correlates with high growth factor expression in the tumor microenvironment, which argues for a co-evolution of both factors in vivo.\n\nSummaryPrediction of ligand-induced growth of cancer cell lines, which correlates with ligand-blocking antibody efficacy, could be significantly improved by learning from features of a mechanistic signaling model, and was applied to reveal a correlation between growth factor expression and predicted response in patient samples.

systems biology↗