The ZO-1–associated Y-box factor ZONAB regulates epithelial cell proliferation and cell density

Epithelial tight junctions regulate paracellular permeability, restrict apical/basolateral intramembrane diffusion of lipids, and have been proposed to participate in the control of epithelial cell proliferation and differentiation. Previously, we have identified ZO-1–associated nucleic acid binding proteins (ZONAB), a Y-box transcription factor whose nuclear localization and transcriptional activity is regulated by the tight junction–associated candidate tumor suppressor ZO-1. Now, we found that reduction of ZONAB expression using an antisense approach or by RNA interference strongly reduced proliferation of MDCK cells. Transfection of wild-type or ZONAB-binding fragments of ZO-1 reduced proliferation as well as nuclear ZONAB pools, indicating that promotion of proliferation by ZONAB requires its nuclear accumulation. Overexpression of ZONAB resulted in increased cell density in mature monolayers, and depletion of ZONAB or overexpression of ZO-1 reduced cell density. ZONAB was found to associate with cell division kinase (CDK) 4, and reduction of nuclear ZONAB levels resulted in reduced nuclear CDK4. Thus, our data indicate that tight junctions can regulate epithelial cell proliferation and cell density via a ZONAB/ZO-1–based pathway. Although this regulatory process may also involve regulation of transcription by ZONAB, our data suggest that one mechanism by which ZONAB and ZO-1 influence proliferation is by regulating the nuclear accumulation of CDK4

Selection of optimised ligands by fluorescence-activated bead sorting

The chemistry of aptamers is largely limited to natural nucleotides, and although modifications of nucleic acids can enhance target aptamer affinity, there has not yet been a technology for selecting the right modifications in the right locations out of the vast number of possibilities, because enzymatic amplification does not transmit sequence-specific modification information. Here we show the first method for the selection of specific nucleoside modifications that increase aptamer binding efficacy, using the oncoprotein EGFR as a model target. Using fluorescence-activated bead sorting (FABS), we have successfully selected optimized aptamers from a library of >65 000 variations. Hits were identified by tandem mass spectrometry and validated by using an EGFR binding assay and computational docking studies. Our results provide proof of concept for this novel strategy for the selection of chemically optimised aptamers and offer a new method for rapidly synthesising and screening large aptamer libraries to accelerate diagnostic and drug discovery

MOMENTUM: Microbial Optimization via Metabolic Network Minimization

We report a high-throughput metabolic engineering platform enabling the rapid optimization of microbial production strains. The platform, which bridges a gap between current in vivo and in vitro bio-production approaches, relies on dynamic minimization of the active metabolic network and is implemented in the context of standardized 2-stage bio-processes. Dynamic metabolic network minimization is accomplished using combinations of CRISPR interference and controlled proteolysis to reduce the activity of multiple enzymes in essential central metabolism. This approach not only results in a design space with greatly reduced complexity, but also in increased metabolic fluxes and production rates as well as in strains which are robust to environmental conditions. Robustness leads to predictable scalability from high-throughput µL-scale screens, to fully instrumented L-scale bioreactors. Predictive high-throughput approaches are critical for metabolic engineering programs to truly take advantage of the rapidly increasing throughput and decreasing costs of synthetic biology. We have not only demonstrated proof of principle for this approach in two common industrial microbes: E. coli and S. cerevisiae, but also have validated this approach with the rapid optimization of E. coli strains producing two important industrial chemicals: alanine and mevalonic acid, at commercially meaningful rates, titers (147 g/L and 97 g/L, respectively), and yields.1 References: Ye, Z., Burg, J.M., Poplyk, M.R., Moreb, E.A., Trahan, A.D., Rodrigiuez, D.L., Sheikh, W., Kelly, G.M., Luo, M.L., Beisel C.L., and Lynch, M.D. (2017) MOMENTuM: Microbial Optimization via MEtabolic NeTwork Minimization., Nature Biotechnology in review

Selection of optimised ligands by fluorescence-activated bead sorting

The chemistry of aptamers is largely limited to natural nucleotides, and although modifications of nucleic acids can enhance target aptamer affinity, there has not yet been a technology for selecting the right modifications in the right locations out of the vast number of possibilities, because enzymatic amplification does not transmit sequence-specific modification information. Here we show the first method for the selection of specific nucleoside modifications that increase aptamer binding efficacy, using the oncoprotein EGFR as a model target. Using fluorescence-activated bead sorting (FABS), we have successfully selected optimized aptamers from a library of >65 000 variations. Hits were identified by tandem mass spectrometry and validated by using an EGFR binding assay and computational docking studies. Our results provide proof of concept for this novel strategy for the selection of chemically optimised aptamers and offer a new method for rapidly synthesising and screening large aptamer libraries to accelerate diagnostic and drug discovery

Novel pharmacodynamic biomarkers for MYCN protein and PI3K/AKT/mTOR pathway signaling in children with neuroblastoma

There is an urgent need for improved therapies for children with high-risk neuroblastoma where survival rates remain low. MYCN amplification is the most common genomic change associated with aggressive neuroblastoma and drugs targeting PI3K/AKT/mTOR, to activate MYCNoncoprotein degradation, are entering clinical evaluation. Our aim was to develop and validate pharmacodynamic (PD) biomarkers to evaluate both proof of mechanism and proof of concept for drugs that block PI3K/AKT/mTOR pathway activity in children with neuroblastoma. Wehave addressed the issue of limited access to tumor biopsies for quantitative detection of protein biomarkers by optimizing a three-color fluorescence activated cell sorting (FACS) method to purify CD45?/GD2+/CD56+ neuroblastoma cells from bone marrow. We then developed a novel quantitative measurement of MYCN protein in these isolated neuroblastoma cells, providing the potential to demonstrate proof of concept for drugs that inhibit PI3K/AKT/mTOR signaling in this disease. In addition we have established quantitative detection of three biomarkers for AKT pathway activity (phosphorylated and total AKT, GSK3b and P70S6K) in surrogate platelet-rich plasma (PRP) frompediatric patients. Together ournewapproachto neuroblastomacell isolation for protein detection and suite ofPD assays provides for the first time the opportunity for robust, quantitative measurement of proteinbased PD biomarkers in this pediatric patient population. These will be ideal tools to support clinical evaluation of PI3K/AKT/mTOR pathway drugs and their ability to target MYCN oncoprotein in upcoming clinical trials in neuroblastoma

Commemorations in Congress: Options for Honoring Individuals, Groups, and Events

This report summarizes the evolution of commemorative legislation as well as the laws, rules, and procedures that have been adopted to control the types of commemoratives considered and enacted

Metabolomic changes of the multi (-AGC-) kinase inhibitor AT13148 in cells, mice and patients are associated with NOS regulation

introduction: To generate biomarkers of target engagement or predictive response for multi-target drugs is challenging. One such compound is the multi-AGC kinase inhibitor AT13148. Metabolic signatures of selective signal transduction inhibitors identified in preclinical models have previously been confirmed in early clinical studies. This study explores whether metabolic signatures could be used as biomarkers for the multi-AGC kinase inhibitor AT13148.Objectives: To identify metabolomic changes of biomarkers of multi-AGC kinase inhibitor AT13148 in cells, xenograft / mouse models and in patients in a Phase I clinical study.Methods: HILIC LC–MS/MS methods and Biocrates AbsoluteIDQ™ p180 kit were used for targeted metabolomics; followed by multivariate data analysis in SIMCA and statistical analysis in Graphpad. Metaboanalyst and String were used for network analysis.Results: BT474 and PC3 cells treated with AT13148 affected metabolites which are in a gene protein metabolite network associated with Nitric oxide synthases (NOS). In mice bearing the human tumour xenografts BT474 and PC3, AT13148 treatment did not produce a common robust tumour specific metabolite change. However, AT13148 treatment of non-tumour bearing mice revealed 45 metabolites that were different from non-treated mice. These changes were also observed in patients at doses where biomarker modulation was observed. Further network analysis of these metabolites indicated enrichment for genes associated with the NOS pathway. The impact of AT13148 on the metabolite changes and the involvement of NOS-AT13148- Asymmetric dimethylarginine (ADMA) interaction were consistent with hypotension observed in patients in higher dose cohorts (160-300 mg).Conclusion: AT13148 affects metabolites associated with NOS in cells, mice and patients which is consistent with the clinical dose-limiting hypotension