Biology subjects

Newman, E. A.

Publications and source records attributed to Newman, E. A..

13 recordsLinked to original sources

bioRxiv2024

Structural enrichment attenuates colitis-associated colon cancer

Colorectal cancer (CRC) is a major public health concern and disproportionately impacts racial/ethnic minority populations in the US. Animal models are helpful in examining human health disparities because many stress-induced human health conditions can be recapitulated using mouse models. Azoxymethane (AOM)/ dextran sodium sulfate (DSS) treatment can be used to model colitis-associated cancers. While colitis-associated cancers account for only 2% of colon cancers, the AOM/DSS model is useful for examining links between inflammation, immunity, and colon cancer. Mice were housed in enriched and impoverished environments for 1-month prior to behavioral testing. Following behavioral testing the mice were subjected to the AOM/DSS model. While our analysis revealed no significant behavioral variances between the impoverished and enriched housing conditions, we found significant effects in tumorigenesis. Enriched mice had fewer tumors and smaller tumor volumes compared to impoverished mice. African Americans are at higher risk for early onset colorectal cancers in part due to social economic status. Furthermore, housing conditions and environment may reflect social economic status. Research aimed at understanding links between social economic status and colorectal cancer progression is important for eliminating disparities in health outcomes.

cancer biology↗

bioRxiv2023

Carcinoma-associated fibroblast-like tumor cells remodel the Ewing sarcoma tumor microenvironment

Tumor heterogeneity is a major driver of cancer progression. In epithelial-derived malignancies, carcinoma-associated fibroblasts (CAFs) contribute to tumor heterogeneity by depositing extracellular matrix (ECM) proteins that dynamically remodel the tumor microenvironment (TME). Ewing sarcomas (EwS) are histologically monomorphous, mesenchyme-derived tumors that are devoid of CAFs. Here we identify a previously uncharacterized subpopulation of transcriptionally distinct EwS tumor cells that deposit pro-tumorigenic ECM. Single cell analyses revealed that these CAF-like cells differ from bulk EwS cells by their upregulation of a matrisome-rich gene signature that is normally repressed by EWS::FLI1, the oncogenic fusion transcription factor that underlies EwS pathogenesis. Further, our studies showed that ECM-depositing tumor cells express the cell surface marker CD73, allowing for their isolation ex vivo and detection in situ. Spatial profiling of tumor xenografts and patient biopsies demonstrated that CD73+ EwS cells and tumor cell-derived ECM are prevalent along tumor borders and invasive fronts. Importantly, despite loss of EWS::FLI1-mediated gene repression, CD73+ EwS cells retain expression of EWS::FLI1 and the fusion-activated gene signature, as well as tumorigenic and proliferative capacities. Thus, EwS tumor cells can be reprogrammed to adopt CAF-like properties and these transcriptionally and phenotypically distinct cell subpopulations contribute to tumor heterogeneity by remodeling the TME.

cancer biology↗

bioRxiv2022

Targeting oncogenic Wnt/β-catenin signaling in adrenocortical carcinoma disrupts ECM expression and impairs tumor growth.

Adrenocortical carcinoma (ACC) is a rare, but highly aggressive cancer with limited treatment options and poor survival for patients with advanced disease. Improved understanding of transcriptional programs engaged in ACC will help direct rational, targeted therapies. While activating mutations in Wnt/{beta}-catenin signaling are frequently observed, the {beta}-catenin-dependent transcriptional targets that promote tumor progression are poorly understood. To address this question, we used independent component analysis and identified a novel Wnt/{beta}-catenin-associated signature in ACC predictive of poor survival. This signature was enriched for the extracellular matrix (ECM), suggesting a potential role for Wnt/{beta}-catenin in regulating the ACC microenvironment. We further investigated the minor fibrillar collagen, collagen XI alpha 1 (COL11A1), and found that COL11A1 expression strongly correlated with both Wnt/{beta}-catenin activation and poor patient survival. Inhibition of constitutively active Wnt/{beta}-catenin signaling in the human ACC cell line, NCI-H295R, significantly reduced expression of COL11A1 and other ECM components, and decreased viability of cancer cells in vitro. To investigate the preclinical potential of Wnt/{beta}-catenin inhibition in vivo, we developed and characterized a novel orthotopic xenograft model utilizing minimally invasive techniques. Treatment with the newly developed Wnt/{beta}-catenin:TBL1 inhibitor Tegavivint significantly reduced tumor growth in this preclinical model. Together, our data supports that inhibition of aberrantly active Wnt/{beta}-catenin disrupts transcriptional reprogramming of the microenvironment and reduces ACC growth and survival. Furthermore, this {beta}-catenin-dependent oncogenic program can be therapeutically targeted with a newly developed Wnt/{beta}-catenin inhibitor. These results show promise for further clinical development of Wnt/{beta}-catenin inhibitors in ACC and unveil a novel Wnt/{beta}-catenin-regulated transcriptome. Simple SummaryAdrenocortical carcinoma (ACC) is a rare, often deadly cancer arising from the adrenal gland. Mortality associated with ACC remains unchanged over the last several decades. The rarity of ACC, an incomplete understanding of its molecular basis, and limited availability of pre-clinical models have hampered the development of new effective therapies. The present work aims to address these gaps with a focus on the Wnt/{beta}-catenin cell signaling pathway, which is aberrantly activated in ~40% of ACC tumors. We discover a novel ECM program activated in ACC that is associated with Wnt/{beta}-catenin and poor survival. Wnt/{beta}-catenin inhibition disrupts expression of ECM genes and induces loss of cancer cell viability. To extend these findings, we develop a rapid orthotopic mouse model of ACC and demonstrate that disruption of the Wnt/{beta}-catenin axis with novel small molecule inhibitor Tegavivint is a potential effective therapeutic strategy to reduce ACC tumor burden in vivo.

cancer biology↗

bioRxiv2022

Geographic Name Resolution Service: A tool for the standardization and indexing of world political division names, with applications to species distribution modeling

Massive biological databases of species occurrences, or georeferenced locations where a species has been observed, are essential inputs for modeling present and future species distributions. Location accuracy is often assessed by determining whether the observation geocoordinates fall within the boundaries of the declared political divisions. This otherwise simple validation is complicated by the difficulty of matching political division names to the correct geospatial object. Spelling errors, abbreviations, alternative codes, and synonyms in multiple languages present daunting name disambiguation challenges. The inability to resolve political division names reduces usable data and analysis of erroneous observations can lead to flawed results. Here, we present the Geographic Name Resolution Service (GNRS), an application for the correction, standardization and indexing of world political division names. The GNRS resolves political division names against a reference database that combines names and codes from GeoNames with geospatial object identifiers from the Global Administrative Areas Database (GADM). In a trial resolution of political division names extracted from >270 million species occurrences, only 1.9%, representing just 6% of occurrences, matched exactly to GADM political divisions in their original form. The GNRS was able to resolve, completely or in part, 92% of the remaining 378,568 political division names, or 86% of the full biodiversity occurrence dataset. In an assessment of geocoordinate accuracy for >239 million species occurrences, resolution of political divisions by the GNRS enabled detection of an order of magnitude more errors and an order of magnitude more error-free occurrences. By providing a novel solution to a major data quality impediment, the GNRS liberates a tremendous amount of biodiversity data for quantitative biodiversity research. The GNRS runs as a web service and can be accessed via an API, an R package, and a web-based graphical user interface. Its modular architecture is easily integrated into existing data validation workflows.

bioinformatics↗

bioRxiv2021

Disentangling the effects of climate change, landscape heterogeneity, and scale on phenological metrics

Phenology, the study of the timing of cyclical life history events and seasonal changes, is a fundamental aspect of how individual species, communities, and ecosystems will respond to climate change. Both biotic and abiotic phenological patterns are changing rapidly in response to changing seasonal temperatures and other climate-related drivers, and the consequences of these shifts for individual species and entire ecosystems are largely unknown. Landscape-scale simulations can address some of these needs for better predictions by demonstrating how phenology measures can vary with spatial and temporal grain of observations, and how phenological responses can vary with landscape heterogeneity and climate drivers. To explicitly examine the spatial and temporal scale-dependence of multiple phenology measures, we constructed simulated landscapes populated by virtual plant species with realistic phenologies and environmental sensitivities. This enabled us to examine phenology measures and environmental sensitivities along a continuum of spatial and temporal grains, while also controlling other aspects of sampling design. By relating measures of phenology calculated at a given spatiotemporal grain to average environmental conditions at that same grain size, we are able to determine observed environmental sensitivities for multiple phenological metrics at that spatial and temporal scale. We demonstrate that different phenological events change distinctly and predictably with spatial and temporal measurement scale, opening the way to incorporating scaling laws into predictions. Using plant flowering as our example, we identify that the timing of the beginnings or ends of an event (e.g., First Flower date, Last Flower date), can be especially sensitive to the spatial and temporal grain (or resolution) of observations. Our work provides an initial assessment of the role of observation scale in landscape phenology, and a general approach for incorporating scale-dependence into predictions of a variety of phenological time series.

ecology↗

bioRxiv2020

Areas of global importance for terrestrial biodiversity, carbon, and water

Summary paragraphTo meet the ambitious objectives of biodiversity and climate conventions, countries and the international community require clarity on how these objectives can be operationalized spatially, and multiple targets be pursued concurrently1. To support governments and political conventions, spatial guidance is needed to identify which areas should be managed for conservation to generate the greatest synergies between biodiversity and natures contribution to people (NCP). Here we present results from a joint optimization that maximizes improvements in species conservation status, carbon retention and water provisioning and rank terrestrial conservation priorities globally. We found that, selecting the top-ranked 30% (respectively 50%) of areas would conserve 62.4% (86.8%) of the estimated total carbon stock and 67.8% (90.7%) of all clean water provisioning, in addition to improving the conservation status for 69.7% (83.8%) of all species considered. If priority was given to biodiversity only, managing 30% of optimally located land area for conservation may be sufficient to improve the conservation status of 86.3% of plant and vertebrate species on Earth. Our results provide a global baseline on where land could be managed for conservation. We discuss how such a spatial prioritisation framework can support the implementation of the biodiversity and climate conventions.

ecology↗

bioRxiv2020

Assessing trait driver theory along abiotic gradients in a tropical plant communities

O_LIDespite the many studies using trait-based approaches to assess the impact of environmental gradients in forest trait composition, the relative roles of (i) intraspecific variation in community assembly and (ii) microclimatic or fine scale abiotic variation in shaping local trait diversity remain poorly understood. To advance their understanding we tested several assumptions and predictions of trait driver theory (TDT). We quantified the shape of trait distributions related to tree carbon, nutrient economics and stem hydraulics across a small-scale but steep gradient of soil water availability. C_LIO_LIWe utilized a unique and steep environmental gradient in the coastal Brazilian Atlantic forest (restinga) communities that spans a very short distance (207 {+/-}60 meters). We collected leaf and wood samples of tree species across 42 patches (or plots) of restinga forest. Furthermore, to detect if species directionally shift in niche space, we analyzed species composition in multidimensional hypervolume space. C_LIO_LIDespite short geographic distances, we observed large shifts in species replacement and intraspecific variation reflected by a directional shift in plant function. Consistent with TDT, we observe (i) trait distributions that are skewed in directions consistent with a forest responding to recent hotter and drier; (ii) peaked trait distributions, indicating strong functional convergence; and (iii) conditions decreasing means and variances of several leaf carbon and nutrient economic traits as well as stem hydraulic traits. C_LIO_LISynthesis. Observed species replacements along the water table gradient and interspecific measures of functional diversity (community kurtosis and skewness) are consistent with strong phenotype/environmental matching of plant carbon, nutrient, and hydraulic strategies. We observe environmental filtering in both extremities of the gradient, selecting for acquisitive (wet) to conservative (dry) setup of traits. Similarly, species that span the entire water availability gradient are characterized by directional intraspecific shifts in multi-trait space that mirror interspecific shifts. Strong environmental gradients across short spatial scales provide unique systems to accurately assess assembly processes and address long-held assumptions and timely hypothesis predicted by trait driver theory. C_LI

ecology↗

bioRxiv2019

Drivers of plant traits and forest functional composition in coastal plant communities of the Atlantic Forest

The severe deforestation of Brazils Atlantic Forest and increasing effects of climate change underscore the need to understand how tree species respond to climate and soil drivers. We studied 42 plots of coastal restinga forest, which is highly diverse and spans strong environmental gradients. We determined the forest physiognomy and functional composition, which are physical properties of a community that respond to climate and soil properties, to elucidate which factors drive community-level traits. To identify the most important environmental drivers of coastal Atlantic forest functional composition, we performed a forest inventory of all plants of diameter 5 cm and above. We collected wood samples and leaves from [~]85% of the most abundant plant species and estimated height, aboveground biomass (AGB), and basal area of individual plants, and the community-weighted specific leaf area (SLA). In addition to plant traits, we measured water table depth and 25 physicochemical soil parameters. We then parameterized several models for different hypotheses relating the roles of nutrients and soil to tropical forest diversity and functioning, as represented by plant traits. Hypotheses were formalized via generalized additive models and piecewise structural equation models. Water table depth, soil coarseness, potential acidity, sodium saturation index (SSI) and aluminum concentration were all components of the best models for AGB, height, basal area, and trait composition. Among the 25 environmental parameters measured, those related to water availability (water table depth and coarse sand), followed by potential acidity, SSI, and aluminum consistently emerged as the most important drivers of forest physiognomy and functional composition. Increases in water table depth, coarse sand, and soil concentration of aluminum negatively impacted all the measured functional traits, whereas SSI had a positive effect on AGB and plant height. These results suggest that sodium is not merely tolerated by Atlantic Forest restinga plant communities, but is important to their structure and functioning. Presence of aluminum in the soil had a complex relationship to overall basal area, possibly mediated by soil organic matter.

ecology↗

bioRxiv2019

Maximum entropy models elucidate the contribution of metabolic traits to patterns of community assembly

Aim: Maximum entropy (MaxEnt) models promise a novel approach for understanding community assembly and species abundance patterns. One of these models, the \"Maximum Entropy Theory of Ecology\" (METE) reproduces many observed species abundance patterns, but is based on an aggregated representation of community structure that does not resolve species identity or explicitly represent species-specific functional traits. In this paper, METE is compared to \"Very Entropic Growth\" (VEG), a MaxEnt model with a less aggregated representation of community structure that represents species (more correctly, functional types) in terms of their per capita metabolic rates. We examine the contribution of metabolic traits to the patterns of community assembly predicted by VEG and, through aggregation, compare the results with METE predictions in order to gain insight into the biological factors underlying observed patterns of community assembly. Innovation: We formally compare two MaxEnt-based community models, METE and VEG, that differ as to whether or not they represent species-specific functional traits. We empirically test and compare the metabolic predictions of both models, thereby elucidating the role of metabolic traits in patterns of community assembly. Main Conclusions: Our analysis reveals that a key determinant of community metabolic patterns is the \"density of species\" distribution, defined as the intrinsic number of species with metabolic rates in a given range that are available to a community prior to filtering by environmental constraints. Our analysis suggests that appropriate choice of of the density of species in VEG may lead to more realistic predictions than METE, for which this distribution is not defined, and thus opens up new ways to understanding the link between functional traits and patterns of community assembly.

ecology↗

bioRxiv2018

Revealing biases in the sampling of ecological interaction networks

The structure of ecological interactions is commonly understood through analyses of interaction networks. However, these analyses may be sensitive to sampling biases in both the interactors (the nodes of the network) and interactions (the links between nodes), because the detectability of species and their interactions is highly heterogeneous. These issues may affect the accuracy of empirically constructed ecological networks. Yet statistical biases introduced by sampling error are difficult to quantify in the absence of full knowledge of the underlying ecological networks structure. To explore properties of large-scale modular networks, we developed EcoNetGen, which constructs and samples networks with predetermined topologies. These networks may represent a wide variety of communities that vary in size and types of ecological interactions. We sampled these networks with different sampling designs that may be employed in field observations. The observed networks generated by each sampling process were then analyzed with respect to the number of components, size of components and other network metrics. We show that the sampling effort needed to estimate underlying network properties accurately depends both on the sampling design and on the underlying network topology. In particular, networks with random or scale-free modules require more complete sampling to reveal their structure, compared to networks whose modules are nested or bipartite. Overall, the modules with nested structure were the easiest to detect, regardless of sampling design. Sampling according to species degree (number of interactions) was consistently found to be the most accurate strategy to estimate network structure. Conversely, sampling according to module (representing different interaction types or taxa) results in a rather complete view of certain modules, but fails to provide a complete picture of the underlying network. We recommend that these findings be incorporated into field sampling design of projects aiming to characterize large species interactions networks to reduce sampling biases.\n\nAuthor SummaryEcological interactions are commonly modeled as interaction networks. Analyses of such networks may be sensitive to sampling biases and detection issues in both the interactors and interactions (nodes and links). Yet, statistical biases introduced by sampling error are difficult to quantify in the absence of full knowledge of the underlying networks structure. For insight into ecological networks, we developed software EcoNetGen (available in R and Python). These allow the generation and sampling of several types of large-scale modular networks with predetermined topologies, representing a wide variety of communities and types of ecological interactions. Networks can be sampled according to designs employed in field observations. We demonstrate, through first uses of this software, that underlying network topology interacts strongly with empirical sampling design, and that constructing empirical networks by starting with highly connected species may be the give the best representation of the underlying network.

ecology↗

bioRxiv2018

Disturbance macroecology: integrating disturbance ecology and macroecology in different-age post-fire stands of a closed-cone pine forest as a case study

Macroecological studies have generally restricted their scope to relatively steady-state systems, and as a result, how biodiversity and abundance metrics are expected to scale in disturbance-dependent ecosystems is unknown. We examine macroecological patterns in a fire-dependent forest of Bishop pine (Pinus muricata). We target two different-aged stands in a stand-replacing fire regime, one a characteristically mature stand with a diverse understory, and one more recently disturbed by a stand-replacing fire (17 years prior to measurement). We compare the stands using macroecological metrics of species richness, abundance and spatial distributions that are predicted by the Maximum Entropy Theory of Ecology (METE), an information-entropy based theory that has proven highly successful in predicting macroecological metrics across a wide variety of systems and taxa. Ecological patterns in the mature stand more closely match METE predictions than do data from the recently disturbed stand. This suggests METEs predictions are more robust in late-successional, slowly changing, or steady-state systems than those in rapid flux with respect to species composition, abundances, and organisms sizes. Our findings highlight the need for a macroecological theory that incorporates natural disturbance and other ecological perturbations into its predictive capabilities, because most natural systems are not in a steady state.

ecology↗

bioRxiv2017

Foxd1 is required for terminal differentiation of anterior hypothalamic neuronal subtypes.

Although the hypothalamus functions as a master homeostat for many behaviors, little is known about the transcriptional networks that control its development. To investigate this question, we analyzed mice deficient for the Forkhead domain transcription factor Foxd1. Foxd1 is selectively expressed in neuroepithelial cells of the prethalamus and hypothalamus prior to the onset of neurogenesis, and is later restricted to neural progenitors of the prethalamus and anterior hypothalamus. During early stages of neurogenesis, we observed that Foxd1-deficient mice showed reduced expression of Six3 and Vax1 in anterior hypothalamus, but overall patterning of the prethalamus and hypothalamus is unaffected. After neurogenesis is complete, however, a progressive reduction and eventual loss of expression of molecular markers of the suprachiasmatic, paraventricular and periventricular hypothalamic is observed. These findings demonstrate that Foxd1 acts in hypothalamic progenitors to allow sustained expression of a subset of genes selectively expressed in mature neurons of the anterior hypothalamus.\n\nHighlightsO_LIFoxd1 is broadly expressed in neuroepithelial cells of the hypothalamus and prethalamus.\nC_LIO_LIFoxd1 mutants show severe defects in anterior hypothalamic development, although prethalamic development is only modestly affected.\nC_LIO_LILoss of Foxd1 results does not affect initial patterning of the hypothalamus, but leads to a progressive loss of expression of markers specific to neurons of the suprachiasmatic, paraventricular and periventricular nuclei.\nC_LIO_LIFoxd1 regulates expression of multiple transcription factors expressed in developing anterior hypothalamus.\nC_LI

developmental biology↗

bioRxiv2017

Effects of anthropogenic wildfire activity in low elevation Pacific island vegetation communities in French Polynesia

Anthropogenic (or human-caused) wildfire is an increasingly important driver of ecological change on Pacific islands including southeastern Polynesia, but fire ecology studies are almost completely absent for this region. Where observations do exist, they mostly represent descriptions of fire effects on plant communities before the introduction of invasive species in the modern era. Understanding the effects of wildfire in southeastern Polynesian island vegetation communities can elucidate which species may become problematic invasives with continued wildfire activity. We investigate the effects of wildfire on vegetation in three low-elevation sites (45-379 m) on the island of Moorea in the Society Islands, French Polynesia, which are already heavily impacted by past human land use and invasive exotic plants, but retain some native flora. In six study areas (3 burned and 3 unburned comparisons), we placed 30 transects across sites and collected species and abundance information at 390 points. We analyzed each local community of plants in three categories: natives, those introduced by Polynesians before European contact (1767 C.E.), and those introduced since European contact. Burned areas had the same or lower mean species richness than paired comparison sites. Although wildfire did not affect the proportions of native and introduced species, it may increase the abundance of introduced species on some sites. Non-metric multidimensional scaling indicates that (not recently modified) comparison plant communities are more distinct from one another than are those on burned sites. We discuss conservation concerns for particular native plants absent from burned sites, as well as invasive species (including Lantana camara and Paraserianthes falcataria) that may be promoted by fire in the Pacific.

ecology↗