Sun H.,301 University Blvd |
Ray S.,301 University Blvd |
Ray S.,Sealy Center for Molecular Medicine |
Lejeune W.,301 University Blvd |
And 10 more authors.
Arteriosclerosis, Thrombosis, and Vascular Biology | Year: 2013
Objective-Dysregulated angiotensin II (Ang II) signaling induces local vascular interleukin-6 (IL-6) secretion, producing leukocyte infiltration and life-threatening aortic dissections. Precise mechanisms by which IL-6 signaling induces leukocyte recruitment remain unknown. T-helper 17 lymphocytes (Th17) have been implicated in vascular pathology, but their role in the development of aortic dissections is poorly understood. Here, we tested the relationship of IL-6-signal transducer and activator of transcription-3 signaling with Th17-induced inflammation in the formation of Ang II-induced dissections in C57BL/6 mice. Approach and Results-Ang II infusion induced aortic dissections and CD4+-interleukin 17A (IL-17A)-expressing Th17 cell accumulation in C57BL/6 mice. A blunted local Th17 activation, macrophage recruitment, and reduced incidence of aortic dissections were seen in IL-6-/- mice. To determine the pathological roles of Th17 lymphocytes, we treated Ang II-infused mice with IL-17A-neutralizing antibody or infused Ang II in genetically deficient IL-17A mice and found decreased aortic chemokine monocytic chemotactic protein-1 production and macrophage recruitment, leading to a reduction in aortic dissections. This effect was independent of blood pressure in IL-17A-neutralizing antibody experiment. Application of a cell-permeable signal transducer and activator of transcription-3 inhibitor to downregulate the IL-6 pathway decreased aortic dilation and Th17 cell recruitment. We also observed increased aortic Th17 infiltration and IL-17 mRNA expression in patients with thoracic aortic dissections. Finally, we found that Ang II-mediated aortic dissections occurred independent of blood pressure changes. Conclusions-Our results indicate that the IL-6-signal transducer and activator of transcription-3 signaling pathway converges on Th17 recruitment and IL-17A signaling upstream of macrophage recruitment, mediating aortic dissections. © 2013 American Heart Association, Inc.
PubMed | Lawrence Berkeley National Laboratory, University of Texas Medical Branch, Biochemistry and Molecular Biology and., Sealy Center for Molecular Medicine and 2 more.
Type: Journal Article | Journal: The Journal of biological chemistry | Year: 2015
Why mammalian cells possess multiple DNA glycosylases (DGs) with overlapping substrate ranges for repairing oxidatively damaged bases via the base excision repair (BER) pathway is a long-standing question. To determine the biological role of these DGs, null animal models have been generated. Here, we report the generation and characterization of mice lacking Neil2 (Nei-like 2). As in mice deficient in each of the other four oxidized base-specific DGs (OGG1, NTH1, NEIL1, and NEIL3), Neil2-null mice show no overt phenotype. However, middle-aged to old Neil2-null mice show the accumulation of oxidative genomic damage, mostly in the transcribed regions. Immuno-pulldown analysis from wild-type (WT) mouse tissue showed the association of NEIL2 with RNA polymerase II, along with Cockayne syndrome group B protein, TFIIH, and other BER proteins. Chromatin immunoprecipitation analysis from mouse tissue showed co-occupancy of NEIL2 and RNA polymerase II only on the transcribed genes, consistent with our earlier in vitro findings on NEIL2s role in transcription-coupled BER. This study provides the first in vivo evidence of genomic region-specific repair in mammals. Furthermore, telomere loss and genomic instability were observed at a higher frequency in embryonic fibroblasts from Neil2-null mice than from the WT. Moreover, Neil2-null mice are much more responsive to inflammatory agents than WT mice. Taken together, our results underscore the importance of NEIL2 in protecting mammals from the development of various pathologies that are linked to genomic instability and/or inflammation. NEIL2 is thus likely to play an important role in long term genomic maintenance, particularly in long-lived mammals such as humans.
PubMed | Sealy Center for Molecular Medicine, Biomolecular Resource Facility, University of Pittsburgh, University of Texas Medical Branch and Institute for Translational science
Type: | Journal: Journal of clinical virology : the official publication of the Pan American Society for Clinical Virology | Year: 2015
Dengue virus (DENV) infection is a significant risk to over a third of the human population that causes a wide spectrum of illness, ranging from sub-clinical disease to intermediate syndrome of vascular complications called dengue fever complicated (DFC) and severe, dengue hemorrhagic fever (DHF). Methods for discriminating outcomes will impact clinical trials and understanding disease pathophysiology.We integrated a proteomics discovery pipeline with a heuristics approach to develop a molecular classifier to identify an intermediate phenotype of DENV-3 infectious outcome.121 differentially expressed proteins were identified in plasma from DHF vs dengue fever (DF), and informative candidates were selected using nonparametric statistics. These were combined with markers that measure complement activation, acute phase response, cellular leak, granulocyte differentiation and viral load. From this, we applied quantitative proteomics to select a 15 member panel of proteins that accurately predicted DF, DHF, and DFC using a random forest classifier. The classifier primarily relied on acute phase (A2M), complement (CFD), platelet counts and cellular leak (TPM4) to produce an 86% accuracy of prediction with an area under the receiver operating curve of >0.9 for DHF and DFC vs DF.Integrating discovery and heuristic approaches to sample distinct pathophysiological processes is a powerful approach in infectious disease. Early detection of intermediate outcomes of DENV-3 will speed clinical trials evaluating vaccines or drug interventions.
PubMed | Washington University in St. Louis, Graduate School for Biomedical science, Institute for Translational science, University of Texas Medical Branch and 4 more.
Type: Journal Article | Journal: FASEB journal : official publication of the Federation of American Societies for Experimental Biology | Year: 2016
Recent data shows that fibroblast growth factor 14 (FGF14) binds to and controls the function of the voltage-gated sodium (Nav) channel with phenotypic outcomes on neuronal excitability. Mutations in the FGF14 gene in humans have been associated with brain disorders that are partially recapitulated in Fgf14(-/-) mice. Thus, signaling pathways that modulate the FGF14:Nav channel interaction may be important therapeutic targets. Bioluminescence-based screening of small molecule modulators of the FGF14:Nav1.6 complex identified 4,5,6,7 -: tetrabromobenzotriazole (TBB), a potent casein kinase 2 (CK2) inhibitor, as a strong suppressor of FGF14:Nav1.6 interaction. Inhibition of CK2 through TBB reduces the interaction of FGF14 with Nav1.6 and Nav1.2 channels. Mass spectrometry confirmed direct phosphorylation of FGF14 by CK2 at S228 and S230, and mutation to alanine at these sites modified FGF14 modulation of Nav1.6-mediated currents. In 1 d in vitro hippocampal neurons, TBB induced a reduction in FGF14 expression, a decrease in transient Na(+) current amplitude, and a hyperpolarizing shift in the voltage dependence of Nav channel steady-state inactivation. In mature neurons, TBB reduces the axodendritic polarity of FGF14. In cornu ammonis area 1 hippocampal slices from wild-type mice, TBB impairs neuronal excitability by increasing action potential threshold and lowering firing frequency. Importantly, these changes in excitability are recapitulated in Fgf14(-/-) mice, and deletion of Fgf14 occludes TBB-dependent phenotypes observed in wild-type mice. These results suggest that a CK2-FGF14 axis may regulate Nav channels and neuronal excitability.-Hsu, W.-C. J., Scala, F., Nenov, M. N., Wildburger, N. C., Elferink, H., Singh, A. K., Chesson, C. B., Buzhdygan, T., Sohail, M., Shavkunov, A. S., Panova, N. I., Nilsson, C. L., Rudra, J. S., Lichti, C. F., Laezza, F. CK2 activity is required for the interaction of FGF14 with voltage-gated sodium channels and neuronal excitability.
Crosetto N.,Goethe University Frankfurt |
Crosetto N.,Massachusetts Institute of Technology |
Mitra A.,University of Texas Medical Branch |
Silva M.J.,French National Center for Scientific Research |
And 17 more authors.
Nature Methods | Year: 2013
We present a genome-wide approach to map DNA double-strand breaks (DSBs) at nucleotide resolution by a method we termed BLESS (direct in situ breaks labeling, enrichment on streptavidin and next-generation sequencing). We validated and tested BLESS using human and mouse cells and different DSBs-inducing agents and sequencing platforms. BLESS was able to detect telomere ends, Sce endonuclease-induced DSBs and complex genome-wide DSB landscapes. As a proof of principle, we characterized the genomic landscape of sensitivity to replication stress in human cells, and we identified >2,000 nonuniformly distributed aphidicolin-sensitive regions (ASRs) overrepresented in genes and enriched in satellite repeats. ASRs were also enriched in regions rearranged in human cancers, with many cancer-associated genes exhibiting high sensitivity to replication stress. Our method is suitable for genome-wide mapping of DSBs in various cells and experimental conditions, with a specificity and resolution unachievable by current techniques. © 2013 Nature America, Inc. All rights reserved.
PubMed | Brown University, MiraVista Laboratories, Institute for Translational science, University of Florida and 7 more.
Type: Journal Article | Journal: PloS one | Year: 2015
Invasive pulmonary aspergillosis (IPA) is an opportunistic fungal infection in patients undergoing chemotherapy for hematological malignancy, hematopoietic stem cell transplant, or other forms of immunosuppression. In this group, Aspergillus infections account for the majority of deaths due to mold pathogens. Although early detection is associated with improved outcomes, current diagnostic regimens lack sensitivity and specificity. Patients undergoing chemotherapy, stem cell transplantation and lung transplantation were enrolled in a multi-site prospective observational trial. Proven and probable IPA cases and matched controls were subjected to discovery proteomics analyses using a biofluid analysis platform, fractionating plasma into reproducible protein and peptide pools. From 556 spots identified by 2D gel electrophoresis, 66 differentially expressed post-translationally modified plasma proteins were identified in the leukemic subgroup only. This protein group was rich in complement components, acute-phase reactants and coagulation factors. Low molecular weight peptides corresponding to abundant plasma proteins were identified. A candidate marker panel of host response (9 plasma proteins, 4 peptides), fungal polysaccharides (galactomannan), and cell wall components (-D glucan) were selected by statistical filtering for patients with leukemia as a primary underlying diagnosis. Quantitative measurements were developed to qualify the differential expression of the candidate host response proteins using selective reaction monitoring mass spectrometry assays, and then applied to a separate cohort of 57 patients with leukemia. In this verification cohort, a machine learning ensemble-based algorithm, generalized pathseeker (GPS) produced a greater case classification accuracy than galactomannan (GM) or host proteins alone. In conclusion, Integration of host response proteins with GM improves the diagnostic detection of probable IPA in patients undergoing treatment for hematologic malignancy. Upon further validation, early detection of probable IPA in leukemia treatment will provide opportunities for earlier interventions and interventional clinical trials.
Zhao Y.,Sealy Center for Molecular Medicine |
Brasier A.R.,Sealy Center for Molecular Medicine |
Brasier A.R.,University of Texas Medical Branch
Current Proteomics | Year: 2011
Recent advances in global-scale proteomic technology enable identification of hundreds of candidate biomarkers. However, very few candidates so identified can reach the high bar of FDA approval for clinical use. The low efficiency of biomarker approval reflects the challenges of taking candidate biomarkers identified in discovery research through the long and difficult pipeline required for biomarker development. The greatest challenge in biomarker development is the lack of reliable assays for use in the verification and validation phases. This paper reviews methodologies and challenges for biomarker assay development with emphasis on stable isotope dilution coupled with multiple reaction monitoring-mass spectrometry (SID-MRM-MS). Because of its sensitivity, quantification abilities, and specificity, SIDMRM- MS has the potential to bridge the critical rate-limiting gaps between the biomarker discovery- and validation phases. A workflow for generation of a specific SID-MRM-MS assay is presented. We conclude that currently, SIDMRM- MS assay is a promising technology for biomarker verification and validation. To move the technology toward an FDA-approvable platform, more stringent evaluation must be performed and these future studies will require a joint effort of the clinical proteomics community, the regulatory agency and major mass spectrometer manufacturers. © 2011 Bentham Science Publishers Ltd.
Spratt H.,University of Texas Medical Branch |
Spratt H.,Sealy Center for Molecular Medicine |
Spratt H.,Institute for Translational science |
Ju H.,University of Texas Medical Branch |
And 3 more authors.
Methods | Year: 2013
Biological experiments in the post-genome era can generate a staggering amount of complex data that challenges experimentalists to extract meaningful information. Increasingly, the success of an appropriately controlled experiment relies on a robust data analysis pipeline. In this paper, we present a structured approach to the analysis of multidimensional data that relies on a close, two-way communication between the bioinformatician and experimentalist. A sequential approach employing data exploration (visualization, graphical and analytical study), pre-processing, feature reduction and supervised classification using machine learning is presented. This standardized approach is illustrated by an example from a proteomic data analysis that has been used to predict the risk of infectious disease outcome. Strategies for model selection and post hoc model diagnostics are presented and applied to the case illustration. We discuss some of the practical lessons we have learned applying supervised classification to multidimensional data sets, one of which is the importance of feature reduction in achieving optimal modeling performance. © 2013 Elsevier Inc.
Ju H.,University of Texas Medical Branch |
Ju H.,Institute for Translational science |
Brasier A.R.,Sealy Center for Molecular Medicine |
Brasier A.R.,Institute for Translational science
BMC Research Notes | Year: 2013
Background: The choice of selection methods to identify important variables for binary classification modeling is critical to produce stable models that are interpretable, that generate accurate predictions and have minimum bias. This work is motivated by data on clinical and laboratory features of severe dengue infections (dengue hemorrhagic fever, DHF) obtained from 51 individuals enrolled in a prospective observational study of acute human dengue infections. Results: We carry out a comprehensive performance comparison using several classification models for DHF over the dengue data set. We compared variable selection results by Multivariate Adaptive Regression Splines, Learning Ensemble, Random Forest, Bayesian Moving Averaging, Stochastic Search Variable Selection, and Generalized Regularized Logistics Regression. Model averaging methods (bagging, boosting and ensemble learners) have higher accuracy, but the generalized regularized regression model has the highest predictive power because the linearity assumptions of candidate predictors are strongly satisfied via deviance chi-square testing procedures. Bootstrapping applications for evaluating predictive regression coefficients in regularized regression model are performed. Conclusions: Feature reduction methods introduce inherent biases and therefore are data-type dependent. We propose that these limitations can be overcome using an exhaustive approach for searching feature space. Using this approach, our results suggest that IL-10, platelet and lymphocyte counts are the major features for predicting dengue DHF on the basis of blood chemistries and cytokine measurements. © 2013 Ju and Brasier; licensee BioMed Central Ltd.
PubMed | Sealy Center for Molecular Medicine and University of Texas Medical Branch
Type: | Journal: Journal of proteomics | Year: 2016
The airway epithelium is a semi-impermeable barrier whose disruption by growth factor reprogramming is associated with chronic airway diseases of humans. Transforming growth factor beta (TGF)-induced epithelial mesenchymal transition (EMT) plays important roles in airway remodeling characteristic of idiopathic lung fibrosis, asthma and chronic obstructive pulmonary disease (COPD). Inflammation of the airways leads to airway injury and tumor necrosis factor alpha (TNF) plays an important pro-inflammatory role. Little systematic information about the effects of EMT on TNF signaling is available. Using an in vitro model of TGF-induced EMT in primary human small airway epithelial cells (hSAECs), we applied quantitative proteomics and phosphoprotein profiling to understand the molecular mechanism of EMT and the impact of EMT on innate inflammatory responses. We quantified 7925 proteins and 1348 phosphorylation sites by stable isotope labeling with iTRAQ technology. We found that cellular response to TNF is cell state dependent and the relative TNF response in mesenchymal state is highly compressed. Combined bioinformatics analyses of proteome and phosphoproteome indicate that the EMT state is associated with reprogramming of kinome, signaling cascade of upstream transcription regulators, phosphor-networks, and NF-B dependent cell signaling.Epithelial mesenchymal transition and inflammation have important implications for clinical and physiologic manifestations of chronic airway diseases such as severe asthma, COPD, and lung fibrosis. Little systematic information on the interplay between EMT and innate inflammation is available. This study combined quantitative proteomics and phosphorproteomics approach to obtain systems-level insight into the upstream transcription regulators involved in the TGF-induced EMT in primary human small airway epithelial cells and to elucidate how EMT impacts on the TNF signaling pathways. The proteomics and phosphoproteomics analysis indicates that many signaling pathways involved in TGF-induced EMT and EMT has profound reprogramming effects on innate inflammation response.