Faculty Bibliography

Translation initiation of most mammalian mRNAs is mediated by a 5' cap structure that binds eukaryotic initiation factor 4E (eIF4E). However, inactivation of eIF4E does not impair translation of many capped mRNAs, suggesting an unknown alternate mechanism may exist for cap-dependent but eIF4E-independent translation. We show that DAP5, an eIF4GI homolog that lacks eIF4E binding, utilizes eIF3d to facilitate cap-dependent translation of approximately 20% of mRNAs. Genome-wide transcriptomic and translatomic analyses indicate that DAP5 is required for translation of many transcription factors and receptor capped mRNAs and their mRNA targets involved in cell survival, motility, DNA repair and translation initiation, among other mRNAs. Mass spectrometry and crosslinking studies demonstrate that eIF3d is a direct binding partner of DAP5. In vitro translation and ribosome complex studies demonstrate that DAP5 and eIF3d are both essential for eIF4E-independent capped-mRNA translation. These studies disclose a widespread and previously unknown mechanism for cap-dependent mRNA translation by DAP5-eIF3d complexes.

The early-life intestinal microbiota plays a key role in shaping host immune system development. We found that a single early-life antibiotic course (1PAT) accelerated type 1 diabetes (T1D) development in male NOD mice. The single course had deep and persistent effects on the intestinal microbiome, leading to altered cecal, hepatic, and serum metabolites. The exposure elicited sex-specific effects on chromatin states in the ileum and liver and perturbed ileal gene expression, altering normal maturational patterns. The global signature changes included specific genes controlling both innate and adaptive immunity. Microbiome analysis revealed four taxa each that potentially protect against or accelerate T1D onset, that were linked in a network model to specific differences in ileal gene expression. This simplified animal model reveals multiple potential pathways to understand pathogenesis by which early-life gut microbiome perturbations alter a global suite of intestinal responses, contributing to the accelerated and enhanced T1D development.

BACKGROUND:Exploration of large data sets, such as shotgun metagenomic sequence or expression data, by biomedical experts and medical professionals remains as a major bottleneck in the scientific discovery process. Although tools for this purpose exist for 16S ribosomal RNA sequencing analysis, there is a growing but still insufficient number of user-friendly interactive visualization workflows for easy data exploration and figure generation. The development of such platforms for this purpose is necessary to accelerate and streamline microbiome laboratory research. RESULTS:We developed the Workflow Hub for Automated Metagenomic Exploration (WHAM!) as a web-based interactive tool capable of user-directed data visualization and statistical analysis of annotated shotgun metagenomic and metatranscriptomic data sets. WHAM! includes exploratory and hypothesis-based gene and taxa search modules for visualizing differences in microbial taxa and gene family expression across experimental groups, and for creating publication quality figures without the need for command line interface or in-house bioinformatics. CONCLUSIONS:WHAM! is an interactive and customizable tool for downstream metagenomic and metatranscriptomic analysis providing a user-friendly interface allowing for easy data exploration by microbiome and ecological experts to facilitate discovery in multi-dimensional and large-scale data sets.

Background. Multilevel interventions combine individual component interventions, and their design can be informed by decision analysis. Our objective was to identify the optimal combination of interventions for alcohol-using HIV+ individuals on antiretroviral drug therapy in Maharashtra, India, explicitly considering stakeholder constraints. Methods. Using an HIV simulation, we evaluated the expected net monetary benefit (ENMB), the probability of lying on the efficiency frontier (PEF), and annual program costs of 5,836 unique combinations of 15 single-focused HIV risk-reduction interventions. We evaluated scenarios of 1) no constraints (i.e., maximize expected value), 2) short-term budget constraints (limits on annual programmatic costs of US$200,000 and $400,000), and 3) a constraint stemming from risk aversion (requiring that the strategy has >50% PEF). Results. With no constraints, the combination including long individual alcohol counseling, text-message adherence support, long group counseling for sex-risk, and long individual counseling for sex-risk (annual cost = $428,886; PEF ∼27%) maximized ENMB and would be the optimal design. With a cost constraint of $400,000, the combination including long individual alcohol counseling, text-message adherence support, brief group counseling for sex-risk, and long individual counseling for sex-risk (annual cost = $374,745; PEF ∼4%) maximized ENMB. With a cost constraint of $200,000, the combination including long individual alcohol counseling, text-message adherence support, and brief group counseling for sex-risk (annual cost = $187,335; PEF ∼54%) maximized ENMB. With the risk aversion constraint, the same configuration (long individual alcohol counseling, text-message support, and brief group counseling for sex-risk) maximized health benefit. Conclusion. Evaluating the costs, risks, and projected benefits of alternatives supports informed decision making prior to initiating study; however, stakeholder constraints should be explicitly included and discussed when using decision analyses to guide study design.

Activation of phosphoinositide 3-kinase (PI3K) signaling is frequently observed in triple-negative breast cancer (TNBC), yet PI3K inhibitors have shown limited clinical activity. To investigate intrinsic and adaptive mechanisms of resistance, we analyzed a panel of patient-derived xenograft models of TNBC with varying responsiveness to buparlisib, a pan-PI3K inhibitor. In a subset of patient-derived xenografts, resistance was associated with incomplete inhibition of PI3K signaling and upregulated MAPK/MEK signaling in response to buparlisib. Outlier phosphoproteome and kinome analyses identified novel candidates functionally important to buparlisib resistance, including NEK9 and MAP2K4. Knockdown of NEK9 or MAP2K4 reduced both baseline and feedback MAPK/MEK signaling and showed synthetic lethality with buparlisib in vitro. A complex in/del frameshift in PIK3CA decreased sensitivity to buparlisib via NEK9/MAP2K4-dependent mechanisms. In summary, our study supports a role for NEK9 and MAP2K4 in mediating buparlisib resistance and demonstrates the value of unbiased omic analyses in uncovering resistance mechanisms to targeted therapy.

OBJECTIVES/OBJECTIVE:We identified the prevalence of nonmedical prescription drug use and its relationship to heroin and injection drug use in 4 nationally representative samples of adolescents. METHODS:We used the most recent data (2009-2015) from the Youth Risk Behavior Surveillance System (Ntotal= 61,132). Prevalence rates and 95% confidence intervals for prescription drug misuse, heroin use, and injection drug use were calculated across time points, sex, and race/ethnicity subgroups. Using odds ratios, we determined the likelihood of youth reporting nonmedical prescription drug use also reporting heroin and drug injection. RESULTS:In 2015, one in 6 adolescents reported recent prescription drug misuse. High rates of nonmedical prescription drug use persisted or increased among Hispanic boys, black boys, and "other" youth, while declining among white youth. Youth who used prescription drugs nonmedically at least once were 17.5 times more likely to have used heroin (CI: 13.7, 22.4) and 14.6 times more likely to have injected drugs (CI: 11.2, 19.2) in their lifetime. CONCLUSIONS:Public health programming focused on reducing prescription drug misuse also may reduce youth engagement in heroin and/or injection drug use. Preventive efforts to support communities of color in reducing rates of prescription drug misuse are crucial.

Diverse environmental and biological systems interact to influence individual differences in response to environmental stress. Understanding the nature of these complex relationships can enhance the development of methods to: (1) identify risk, (2) classify individuals as healthy or ill, (3) understand mechanisms of change, and (4) develop effective treatments. The Research Domain Criteria (RDoC) initiative provides a theoretical framework to understand health and illness as the product of multiple inter-related systems but does not provide a framework to characterize or statistically evaluate such complex relationships. Characterizing and statistically evaluating models that integrate multiple levels (e.g. synapses, genes, environmental factors) as they relate to outcomes that a free from prior diagnostic benchmarks represents a challenge requiring new computational tools that are capable to capture complex relationships and identify clinically relevant populations. In the current review, we will summarize machine learning methods that can achieve these goals.

BACKGROUND:Cancers induce gene expression alterations in stroma surrounding tumors that supports cancer progression. However, it is actually not at all known the extent of altered stromal gene expression enacted by tumors nor the extent to which altered stromal gene expression penetrates the stromal tissue. Presently, post-surgical "tumor-free" stromal tissue is determined to be cancer-free based on solely on morphological normality-a criteria that has not changed in more than 100 years despite the existence of sophisticated gene expression data to the contrary. We therefore investigated the extent to which breast tumors alter stromal gene expression in three dimensions in women undergoing mastectomy with the intent of providing a genomic determination for development of future risk of recurrence criteria, and to inform the need for adjuvant full-breast irradiation. METHODS AND FINDINGS/RESULTS:Genome-wide gene expression changes were determined in histopathologically normal breast tissue in 33 women undergoing mastectomy for stage II and III primary invasive ductal carcinoma at serial distances in three dimensions from the tumor. Gene expression was determined by genome-wide mRNA analysis and subjected to metagene mRNA characterization. Tumor-like gene expression signatures in stroma were identified that surprisingly transitioned to a plastic, normalizing homeostatic signature with distance from tumor. Stroma closest to tumor displayed a pronounced tumor-like signature enriched in cancer-promoting pathways involved in disruption of basement membrane, cell migration and invasion, WNT signaling and angiogenesis. By 2 cm from tumor in all dimensions, stromal tissues were in transition, displaying homeostatic and tumor suppressing gene activity, while also expressing cancer supporting pathways. CONCLUSIONS:The dynamics of gene expression in the post-tumor breast stroma likely co-determines disease outcome: reversion to normality or transition to transformation in morphologically normal tissue. Our stromal genomic signature may be important for personalizing surgical and adjuvant therapeutic decisions and risk of recurrence.

Drug and alcohol use have been associated with increased risk for sexual violence, but there is little research on sexual violence within the context of drug use among young adult opioid users. The current mixed-methods study explores young adult opioid users' sexual experiences in the context of their drug use. Forty-six New York City young adults (ages 18-32) who reported lifetime nonmedical use of prescription opioids (POs) completed in-depth, semistructured interviews, and 164 (ages 18-29) who reported heroin and/or nonmedical PO use in the past 30 days completed structured assessments that inquired about their drug use and sexual behavior and included questions specific to sexual violence. Participants reported frequent incidents of sexual violence experienced both personally and by their opioid using peers. Participants described sexual violence, including sexual assault, as occurring within a context characterized by victimization of users who were unconscious as a result of substance use, implicit and explicit exchanges of sex for drugs and/or money that increased risk for sexual violence, negative sexual perceptions ascribed to drug users, and participants' own internalized stigma. Recommendations to reduce sexual violence among young adult opioid users include education for users and service providers on the risk of involvement in sexual violence within drug using contexts and efforts to challenge perceptions of acceptability regarding sexual violence.

Background: Multiple bacterial species are capable of degrading oxalate in vitro. Certain taxa degrade oxalate as their sole source of energy and carbon (e.g. Oxalobacter formigenes), whereas others use oxalate as an auxiliary carbon source. For oxalate metabolism, it is not yet well-understood how genomic potential relates to transcriptional regulation. We asked whether the human gut could have a community of oxalatedegrading taxa working synergistically to diminish the effects of this toxic metabolite. Our hypothesis is that oxalate metabolism is regulated by a multi-organism oxalatedegrading community (oxalobiome) that is dominated by specialist oxalate degraders.
Method(s): We used data from 2 public databases: (i)8 healthy subjects in the USA; and (ii)471 healthy subjects in the Netherlands as part of the Human Functional Genomic Project (HFGP). Both collected fecal samples for metagenomic and/or metatranscriptomic high throughput sequencing. Using HUMAnN2 with customized settings, we profiled the metabolic activity of oxalate-degrading bacterial species. Output from these analyses was expressed as Reads per Kilobase per Million mapped reads (RPKM).
Result(s): We identified the oxalate degradation pathway (ODP) in the metagenome and metatranscriptome of all 8 subjects. Mean ODP is 35.3+/-28.1 and 90.1+/-43.5 RPKM in the metagenome and the metatranscriptome, respectively, indicating active expression. O. formigenes, E. coli, and unclassified bacteria were present in metagenomic and metatranscriptomic reads. B. dentium had detectable ODP in its genome but was not transcribing it. In the HFGP database, we identified ODP in 328 subjects of the 471 tested (70%) (Mean=18.1+/-2.1 RPKM). ODP was detected in B. animalis, B. dentium, B. pseudocatenulatum, E.coli/Shigella, L. acidophilus, L. gasseri, L. mucosae, O. formigenes and unclassified bacteria. ODP was examined in the metagenome of 265 females (Mean ODP= 21.7+/-3.3) and 200 males (Mean ODP=13.3+/-1.9 RPKM; p=0.04 by unpaired t test).
Conclusion(s): We have identified a community of bacteria with the potential to degrade oxalate in healthy humans and species actively transcribing ODP. These include E.coli, which might be a common contributor of oxalate degradation in humans. The sex differences in ODP is consistent with the ~ 2:1 male/female incidence and prevalence of calcium oxalate stones