HIV-1 Transcription Inhibitor 1E7-03 Decreases Nucleophosmin Phosphorylation.

Transcription activation of latent human immunodeficiency virus-1 (HIV-1) occurs due to HIV-1 rebound, the interruption of combination antiretroviral therapy, or development of drug resistance. Thus, novel HIV-1 inhibitors, targeting HIV-1 transcription are needed. We previously developed an HIV-1 transcription inhibitor, 1E7-03, that binds to the noncatalytic RVxF-accommodating site of protein phosphatase 1 and inhibits HIV-1 replication in cultured cells and HIV-1-infected humanized mice by impeding protein phosphatase 1 interaction with HIV-1 Tat protein. However, host proteins and regulatory pathways targeted by 1E7-03 that contribute to its overall HIV-1 inhibitory activity remain to be identified. To address this issue, we performed label-free quantitative proteome and phosphoproteome analyses of noninfected and HIV-1-infected CEM T cells that were untreated or treated with 1E7-03. 1E7-03 significantly reprogramed the phosphorylation profile of proteins including PPARα/RXRα, TGF-ß, and PKR pathways. Phosphorylation of nucleophosmin (NPM1) at Ser-125 residue in PPARα/RXRα pathway was significantly reduced (>20-fold, p = 1.37 × 10-9), followed by the reduced phosphorylation of transforming growth factor-beta 2 at Ser-46 (TGF-ß2, >12-fold, p = 1.37 × 10-3). Downregulation of NPM1's Ser-125 phosphorylation was further confirmed using Western blot. Phosphorylation mimicking NPM1 S125D mutant activated Tat-induced HIV-1 transcription and exhibited enhanced NPM1-Tat interaction compared to NPM1 S125A mutant. Inhibition of Aurora A or Aurora B kinases that phosphorylate NPM1 on Ser-125 residue inhibited HIV-1, further supporting the role of NPM1 in HIV-1 infection. Taken together, 1E7-03 reprogrammed PPARα/RXRα and TGF-ß pathways that contribute to the inhibition of HIV-1 transcription. Our findings suggest that NPM1 phosphorylation is a plausible target for HIV-1 transcription inhibition.

Insights on the pathogenesis of type 2 diabetes as revealed by signature genomic classifiers in an African American population in the Washington, DC area.

AIMS: African Americans (AA) in the United States have a high risk of type 2 diabetes mellitus (T2DM) and suffer from disparities in the prevalence, mortality, and comorbidities of the disease compared to other Americans. The present study aimed to shed light on the molecular mechanisms of disease pathogenesis of T2DM among AA in the Washington, DC region. METHODS: We performed TaqMan Low Density Arrays (TLDA) on 24 genes of interest that belong to three categories: metabolic disease and disorders, cancer-related genes, and neurobehavioural disorders genes. The 18 genes, viz. ARNT, CYP2D6, IL6, INSR, RRAD, SLC2A2 (metabolic disease and disorders), APC, BCL2, CSNK1D, MYC, SOD2, TP53 (Cancer-related), APBA1, APBB2, APOC1, APOE, GSK3B, and NAE1 (neurobehavioural disorders), were differentially expressed in T2DM participants compared to controls. RESULTS: Our results suggest that factors including gender, smoking habits, and the severity or lack of control of T2DM (as indicated by HbA1c levels) were significantly associated with differential gene expression. APBA1 was significantly (p-value <0.05) downregulated in all diabetes participants. Upregulation of APOE and CYP2D6 genes and downregulation of the INSR gene were observed in the majority of diabetes patients. CONCLUSIONS: Tobacco smoking and gender were significantly associated with case-control differences in expression of the APBA1 and APOE genes (connected with Alzheimer's disease) and the INSR and CYP2D6 (associated with metabolic disorders). The results highlight the need for more effective management of T2DM and for tobacco smoking cessation interventions in this community, and further research on the associations of T2DM with other disease processes, including cancer and neurobehavioral pathways.

Biomarkers of metabolic disorders and neurobehavioral diseases in a PCB- exposed population: What we learned and the implications for future research.

Polychlorinated biphenyls (PCBs) are one of the original twelve classes of toxic chemicals covered by the Stockholm Convention on Persistent Organic Pollutants (POP), an international environmental treaty signed in 2001. PCBs are present in the environment as mixtures of multiple isomers at different degree of chlorination. These compounds are manmade and possess useful industrial properties including extreme longevity under harsh conditions, heat absorbance, and the ability to form an oily liquid at room temperature that is useful for electrical utilities and in other industrial applications. They have been widely used for a wide range of industrial purposes over the decades. Despite a ban in production in 1979 in the US and many other countries, they remain persistent and ubiquitous in environment as contaminants due to their improper disposal. Humans, independent of where they live, are therefore exposed to PCBs, which are routinely found in random surveys of human and animal tissues. The prolonged exposures to PCBs have been associated with the development of different diseases and disorders, and they are classified as endocrine disruptors. Due to its ability to interact with thyroid hormone, metabolism and function, they are thought to be implicated in the global rise of obesity diabetes, and their potential toxicity for neurodevelopment and disorders, an example of gene by environmental interaction (GxE). The current review is primarily intended to summarize the evidence for the association of PCB exposures with increased risks for metabolic dysfunctions and neurobehavioral disorders. In particular, we present evidence of gene expression alterations in PCB-exposed populations to construct the underlying pathways that may lead to those diseases and disorders in course of life. We conclude the review with future perspectives on biomarker-based research to identify susceptible individuals and populations.

Transcriptional Profiling and Biological Pathway(s) Analysis of Type 2 Diabetes Mellitus in a Pakistani Population.

The epidemic of type 2 diabetes mellitus (T2DM) is an important global health concern. Our earlier epidemiological investigation in Pakistan prompted us to conduct a molecular investigation to decipher the differential genetic pathways of this health condition in relation to non-diabetic controls. Our microarray studies of global gene expression were conducted on the Affymetrix platform using Human Genome U133 Plus 2.0 Array along with Ingenuity Pathway Analysis (IPA) to associate the affected genes with their canonical pathways. High-throughput qRT-PCR TaqMan Low Density Array (TLDA) was performed to validate the selected differentially expressed genes of our interest, viz., ARNT, LEPR, MYC, RRAD, CYP2D6, TP53, APOC1, APOC2, CYP1B1, SLC2A13, and SLC33A1 using a small population validation sample (n = 15 cases and their corresponding matched controls). Overall, our small pilot study revealed a discrete gene expression profile in cases compared to controls. The disease pathways included: Insulin Receptor Signaling, Type II Diabetes Mellitus Signaling, Apoptosis Signaling, Aryl Hydrocarbon Receptor Signaling, p53 Signaling, Mitochondrial Dysfunction, Chronic Myeloid Leukemia Signaling, Parkinson's Signaling, Molecular Mechanism of Cancer, and Cell Cycle G1/S Checkpoint Regulation, GABA Receptor Signaling, Neuroinflammation Signaling Pathway, Dopamine Receptor Signaling, Sirtuin Signaling Pathway, Oxidative Phosphorylation, LXR/RXR Activation, and Mitochondrial Dysfunction, strongly consistent with the evidence from epidemiological studies. These gene fingerprints could lead to the development of biomarkers for the identification of subgroups at high risk for future disease well ahead of time, before the actual disease becomes visible.

Capturing 3D large-strain Euler-bending filament dynamics in fibrous media simulations; sample case of compression collapse in dendritic actin network.

Cytoskeletal networks to transmission towers are comprised of slender elements. Slender filaments bend and buckle more easily than stretch. Therefore a deforming network is expected to exhaust all possible bending-based modes before engaging filament stretch. While the large-strain bending critically determines fibrous-media response, simulations use small-strain and jointed approximations. At low resolution, these approximations inflate bending resistance and delay buckling onset. The proposed string-of-continuous-beams (SOCB) approach captures 3D nonlinear Euler bending of filaments with high fidelity at low cost. Bending geometry (i.e. angles and its differentials) is solved as primary variables, to fit a 5th order polynomial of the contour angle. Displacement, solved simultaneously as length conservation, is predicted with C3 and C6 smoothness between and within segments, using only 2 nodes. In the chosen analysis frame, in-plane and out-plane moments can be decoupled for arbitrarily-curved segments. Complex crosslink force-transfers can be specified. Simulations show that when a daughter branch is appended, the buckling resistance of a filament changes from linear to nonlinear before reversible collapse. An actin outcrop with 8 generations of mother-daughter branching produced the linear, nonlinear, and collapse regimes observed in compression experiments. 'Collapse' was a redistribution of outcrop forces following the buckling of few strands.