Faculty Bibliography

Bullying is an intentional act that can wreak havoc in the life of an individual. With more than 1 billion users, YouTube is a powerful medium for disseminating information. The purpose of this study was to describe the extent to which content related to bullying is present on YouTube with respect to source, content, number of views, length, and year uploaded. Collectively, the videos in this sample were viewed more than half a billion times. The source of the most widely viewed videos was consumers, and none of the most widely viewed videos was posted by a governmental agency or a professional organization. The most common content in the videos was describing or depicting violence (n=89). Over one-half addressed getting help (n=56). Suicide was mentioned in 38 of the videos. Additional investment by professional agencies is warranted to improve understanding about ways to increase the dissemination of positive messages about bullying prevention, and about helping adolescents who are bullied on social media.

The goal of this talk is to introduce an integrated quantitative proteogenomic approach to comprehensively map proteomic information back to their encoding genes. We seek evidence from mass spectrometry-based large-scale proteomic data of patient populations in conjunction with patient-centric next-generation sequencing data and unbiased sequencing strategies to study breast cancer (BC) subtypes from a genomic context. We have obtained global and phosphoproteomic data with matching next generation sequencing data for 18 patient-derived xenografts (PDXs) representing the major clinical subtypes of BC. Our workflow starts with the creation of several protein sequence databases that serve as a template for mass spectrometry database identifications. These databases include 1) completely annotated reference protein sequences, 2) patient-specific databases that were created using next generation sequencing data, 3) isoform databases that contain all possible splicing combinations, and 4) amino acid sequence database resulting from a six-frame translation of the entire human reference and customized genomes. All mass spectrometry raw data are searched against the databases for obtaining identifications at the peptide level, and assembly of peptides for quantification using taxonomy-based label-free quantitation (LFQ) that can specifically quantify unique human peptide sequences found in PDXs. The peptides are then mapped to the human genome and visualized using a genome browser. Quantitative changes across PDXs are presented at the protein level or at the isoform level via peptide role-up to specific exons and visualized as a quantitative data track. By combining search results from these databases we obtain a comprehensive view of our PDXs. The complementary nature of the databases enable greater proteomic depth, i.e. databases with complete splicing combinations capture proteomic evidence when patient-specific databases fail due to possible erroneous RNA-seq reads. Similarly, 6-frame translated amino acid databases can capture potentially novel coding regions but are unable to detect splicing. Peptide maps are obtained for individual genes or specific protein isoforms covering both knowledge-driven and novel genomic annotation types. We compile peptides carrying variants, splice junctions, fusions, and new coding regions specific to each PDX or in common with a specific BC subtype. Majority of data is mapped back to the genome loci using unmodified peptides via global proteomics while phosphopeptides that contain variants and splicing are also mapped in a similar manner using phosphoproteomic data. We have currently annotated 455 novel proteogenomic hits covering many examples outlined above for genes related to breast cancer and show how these can be specifically identified and in some instances differentially quantified in the PDX models

A key component of eukaryotic lipid homeostasis is the esterification of sterols with fatty acids by sterol O-acyltransferases (SOATs). The esterification reactions are allosterically activated by their sterol substrates, the majority of which accumulate at the plasma membrane. We demonstrate that in yeast, sterol transport from the plasma membrane to the site of esterification is associated with the physical interaction of the major SOAT, acyl-coenzyme A:cholesterol acyltransferase (ACAT)-related enzyme (Are)2p, with 2 plasma membrane ATP-binding cassette (ABC) transporters: Aus1p and Pdr11p. Are2p, Aus1p, and Pdr11p, unlike the minor acyltransferase, Are1p, colocalize to sterol and sphingolipid-enriched, detergent-resistant microdomains (DRMs). Deletion of either ABC transporter results in Are2p relocalization to detergent-soluble membrane domains and a significant decrease (53-36%) in esterification of exogenous sterol. Similarly, in murine tissues, the SOAT1/Acat1 enzyme and activity localize to DRMs. This subcellular localization is diminished upon deletion of murine ABC transporters, such as Abcg1, which itself is DRM associated. We propose that the close proximity of sterol esterification and transport proteins to each other combined with their residence in lipid-enriched membrane microdomains facilitates rapid, high-capacity sterol transport and esterification, obviating any requirement for soluble intermediary proteins.-Gulati, S., Balderes, D., Kim, C., Guo, Z. A., Wilcox, L., Area-Gomez, E., Snider, J., Wolinski, H., Stagljar, I., Granato, J. T., Ruggles, K. V., DeGiorgis, J. A., Kohlwein, S. D., Schon, E. A., Sturley, S. L. ATP-binding cassette transporters and sterol O-acyltransferases interact at membrane microdomains to modulate sterol uptake and esterification.

OBJECTIVE: The recent Ebola virus disease (EVD) outbreak in 2014-2015 has been the largest and longest lasting to date. Media coverage about the outbreak has been extensive, but there are large gaps in our understanding of the ways in which widely accessed social media sites are used during times of public health crisis. The purpose of this study was to analyze widely viewed videos about EVD on the YouTube video-sharing site. METHODS: We coded the source, content, and characteristics of the 100 most widely viewed videos about EVD on YouTube. RESULTS: The videos included in the sample were viewed more than 73 million times. The death toll in West Africa was mentioned in nearly one-third of the videos. Over one-third of the videos mentioned how EVD was generally transmitted. There was little mention of treatment and no mention of the need for US funding of disaster preparedness; coordination between local, state, and federal governments; or beds ready for containment. No significant differences in the number of views were identified between video sources with the exception of a significantly higher number of views for "consumer videos" compared with "commercial television videos." CONCLUSIONS: With 1 billion unique users a month, YouTube has potential for both enhancing education and spreading misinformation. (Disaster Med Public Health Preparedness. 2015;0:1-5).

BACKGROUND: The purpose of this study was to describe the prevalence of aggressive and violent behaviors in the context of the school environment in a nationally representative sample of adolescent youth and to illustrate these patterns during 2001-2011. METHODS: We analyzed data from 84,734 participants via the Youth Risk Behavior Surveillance System (YRBSS). Frequencies were visualized using heatmaps. One-way analyses of variance and corresponding post hoc tests helped to identify if differences in prevalence fluctuated significantly across all years. RESULTS: Rates of youth feeling unsafe in their school environment, bringing weapons to school, and engaging in physical fighting on school property continue to persist. Findings illustrated that Hispanic youth and youth classified as "other" have emerged as particularly high-risk demographic subgroups over the past decade. Peer victimization and sexual victimization continue to affect girls disproportionately. CONCLUSIONS: Though some variation within demographic subgroups exists, rates of aggressive and violent behaviors in the context of the school environment continue to persist. Implications for the coordinated prevention of aggressive and violent behaviors among adolescent youth are discussed and recommendations for school-based prevention efforts are identified.

We describe integrated strategies that employ both translation of ENCODE data and major proteomic technology pillars to improve the identification of the missing proteins, protein isoforms, and PTMs. The results from proteoENCODEdb searches with experimental mass spectral data indicate that some novel splice forms detected at the transcript level are in fact translated to proteins. Our results provide a step toward the directives of the C-HPP initiative and related biomedical research.

OBJECTIVE: To apply discovery-based computational methods to nationally representative data from the Centers for Disease Control and Preventions' Youth Risk Behavior Surveillance System to better understand and visualize the behavioral factors associated with gun possession among adolescent youth. RESULTS: Our study uncovered the multidimensional nature of gun possession across nearly five million unique data points over a ten year period (2001-2011). Specifically, we automated odds ratio calculations for 55 risk behaviors to assemble a comprehensive table of associations for every behavior combination. Downstream analyses included the hierarchical clustering of risk behaviors based on their association "fingerprint" to 1) visualize and assess which behaviors frequently co-occur and 2) evaluate which risk behaviors are consistently found to be associated with gun possession. From these analyses, we identified more than 40 behavioral factors, including heroin use, using snuff on school property, having been injured in a fight, and having been a victim of sexual violence, that have and continue to be strongly associated with gun possession. Additionally, we identified six behavioral clusters based on association similarities: 1) physical activity and nutrition; 2) disordered eating, suicide and sexual violence; 3) weapon carrying and physical safety; 4) alcohol, marijuana and cigarette use; 5) drug use on school property and 6) overall drug use. CONCLUSIONS: Use of computational methodologies identified multiple risk behaviors, beyond more commonly discussed indicators of poor mental health, that are associated with gun possession among youth. Implications for prevention efforts and future interdisciplinary work applying computational methods to behavioral science data are described.