66 research outputs found
Transcriptomic and ChIP-sequence interrogation of EGFR signaling in HER2+ breast cancer cells reveals a dynamic chromatin landscape and S100 genes as targets.
BACKGROUND:The Human Epidermal Growth Factor Receptor (EGFR/HER1) can be activated by several ligands including Transforming Growth Factor alpha (TGF-α) and Epidermal Growth Factor (EGF). Following ligand binding, EGFR heterodimerizes with other HER family members, such as HER2 (human epidermal growth factor receptor-2). Previously, we showed that the EGFR is upregulated in trastuzumab resistant HER2 positive (HER2+) breast cancer cells. This study is aimed to determine the downstream effects on transcription following EGFR upregulation in HER2+ breast cancer cells. METHODS:RNA-sequence and ChIP-sequence for H3K18ac and H3K27ac (Histone H3 lysine K18 and K27 acetylation) were conducted following an Epidermal Growth Factor (EGF) treatment time course in HER2+ breast cancer cells, SKBR3. The levels of several proteins of interest were confirmed by western blot analysis. The cellular localization of proteins of interest was examined using biochemically fractionated lysates followed by western blot analysis. RESULTS:Over the course of 24 h, EGFR stimulation resulted in the modulation of over 4000 transcripts. Moreover, our data demonstrates that EGFR/HER2 signaling regulates the epigenome, with global H3K18ac and H3K27ac oscillating as a function of time following EGF treatment. RNA-sequence data demonstrates the activation of immediate early genes (IEGs) and delayed early genes (DEGs) within 1 h of EGF treatment. More importantly, we have identified members of the S100 (S100 Calcium Binding Protein) gene family as likely direct targets of EGFR signaling as H3K18ac, H3K27ac and pol2 (RNA polymerase II) increase near the transcription start sites of some of these genes. CONCLUSIONS:Our data suggests that S100 proteins, which act as Ca2+ sensors, could play a role in EGF induced tumor cell growth and metastasis, contribute to trastuzumab resistance and cell migration and that they are likely drug targets in HER2+ breast cancer
The Casiquiare river acts as a corridor between the Amazonas and Orinoco river basins: biogeographic analysis of the genus Cichla
The Casiquiare River is a unique biogeographic corridor between the Orinoco and Amazonas basins. We investigated the importance of this connection for Neotropical fishes using peacock cichlids ( Cichla spp.) as a model system. We tested whether the Casiquiare provides a conduit for gene flow between contemporary populations, and investigated the origin of biogeographic distributions that span the Casiquiare. Using sequences from the mitochondrial control region of three focal species ( C. temensis , C. monoculus , and C. orinocensis ) whose distributions include the Amazonas, Orinoco, and Casiquiare, we constructed maximum likelihood phylograms of haplotypes and analyzed the populations under an isolation-with-migration coalescent model. Our analyses suggest that populations of all three species have experienced some degree of gene flow via the Casiquiare. We also generated a mitochondrial genealogy of all Cichla species using >2000 bp and performed a dispersal-vicariance analysis (DIVA) to reconstruct the historical biogeography of the genus. This analysis, when combined with the intraspecific results, supports two instances of dispersal from the Amazonas to the Orinoco. Thus, our results support the idea that the Casiquiare connection is important across temporal scales, facilitating both gene flow and the dispersal and range expansion of species.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/79059/1/j.1365-294X.2010.04540.x.pd
Epidemiological studies of Mansonella ozzardi (Nematoda, Onchocercidae) in indigenous communities of Pauini municipality, Amazonas, Brazil
Macrophage-dependent nitric oxide expression regulates tumor cell detachment and metastasis after IL-2/anti-CD40 immunotherapy
Immunotherapy with IL-2 and anti-CD40 induces the expression of NOS2 in tumor-associated macrophages, and its expression is required for the inhibition of tumor metastasis
Synaptic Wnt signaling—a contributor to major psychiatric disorders?
Wnt signaling is a key pathway that helps organize development of the nervous system. It influences cell proliferation, cell fate, and cell migration in the developing nervous system, as well as axon guidance, dendrite development, and synapse formation. Given this wide range of roles, dysregulation of Wnt signaling could have any number of deleterious effects on neural development and thereby contribute in many different ways to the pathogenesis of neurodevelopmental disorders. Some major psychiatric disorders, including schizophrenia, bipolar disorder, and autism spectrum disorders, are coming to be understood as subtle dysregulations of nervous system development, particularly of synapse formation and maintenance. This review will therefore touch on the importance of Wnt signaling to neurodevelopment generally, while focusing on accumulating evidence for a synaptic role of Wnt signaling. These observations will be discussed in the context of current understanding of the neurodevelopmental bases of major psychiatric diseases, spotlighting schizophrenia, bipolar disorder, and autism spectrum disorder. In short, this review will focus on the potential role of synapse formation and maintenance in major psychiatric disorders and summarize evidence that defective Wnt signaling could contribute to their pathogenesis via effects on these late neural differentiation processes
Role and task allocation framework for Multi-Robot Collaboration with latent knowledge estimation
In this work a novel framework for modeling role and task allocation in Cooperative Heterogeneous Multi-Robot Systems (CHMRSs) is presented. This framework encodes a CHMRS as a set of multidimensional relational structures (MDRSs). This set of structure defines collaborative tasks through both temporal and spatial relations between processes of heterogeneous robots. These relations are enriched with tensors which allow for geometrical reasoning about collaborative tasks. A learning schema is also proposed in order to derive the components of each MDRS. According to this schema, the components are learnt from data reporting the situated history of the processes executed by the team of robots. Data are organized as a multirobot collaboration treebank (MRCT) in order to support learning. Moreover, a generative approach, based on a probabilistic model, is combined together with nonnegative tensor decomposition (NTD) for both building the tensors and estimating latent knowledge. Preliminary evaluation of the performance of this framework is performed in simulation with three heterogeneous robots, namely, two Unmanned Ground Vehicles (UGVs) and one Unmanned Aerial Vehicle (UAV)
Regulation of Coronary Blood Flow
The heart is uniquely responsible for providing its own blood supply through the coronary circulation. Regulation of coronary blood flow is quite complex and, after over 100 years of dedicated research, is understood to be dictated through multiple mechanisms that include extravascular compressive forces (tissue pressure), coronary perfusion pressure, myogenic, local metabolic, endothelial as well as neural and hormonal influences. While each of these determinants can have profound influence over myocardial perfusion, largely through effects on end-effector ion channels, these mechanisms collectively modulate coronary vascular resistance and act to ensure that the myocardial requirements for oxygen and substrates are adequately provided by the coronary circulation. The purpose of this series of Comprehensive Physiology is to highlight current knowledge regarding the physiologic regulation of coronary blood flow, with emphasis on functional anatomy and the interplay between the physical and biological determinants of myocardial oxygen delivery. © 2017 American Physiological Society. Compr Physiol 7:321-382, 2017
Robust estimation of bacterial cell count from optical density
Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data
Applications of the hexanic fraction of Agave sisalana Perrine ex Engelm (Asparagaceae): control of inflammation and pain screening
Unraveling Amazon tree community assembly using Maximum Information Entropy: a quantitative analysis of tropical forest ecology
In a time of rapid global change, the question of what determines patterns in species abundance distribution remains a priority for understanding the complex dynamics of ecosystems. The constrained maximization of information entropy provides a framework for the understanding of such complex systems dynamics by a quantitative analysis of important constraints via predictions using least biased probability distributions. We apply it to over two thousand hectares of Amazonian tree inventories across seven forest types and thirteen functional traits, representing major global axes of plant strategies. Results show that constraints formed by regional relative abundances of genera explain eight times more of local relative abundances than constraints based on directional selection for specific functional traits, although the latter does show clear signals of environmental dependency. These results provide a quantitative insight by inference from large-scale data using cross-disciplinary methods, furthering our understanding of ecological dynamics
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