A Bayesian Analysis for Identifying DNA Copy Number Variations Using a Compound Poisson Process

To study chromosomal aberrations that may lead to cancer formation or genetic diseases, the array-based Comparative Genomic Hybridization (aCGH) technique is often used for detecting DNA copy number variants (CNVs). Various methods have been developed for gaining CNVs information based on aCGH data. However, most of these methods make use of the log-intensity ratios in aCGH data without taking advantage of other information such as the DNA probe (e.g., biomarker) positions/distances contained in the data. Motivated by the specific features of aCGH data, we developed a novel method that takes into account the estimation of a change point or locus of the CNV in aCGH data with its associated biomarker position on the chromosome using a compound Poisson process. We used a Bayesian approach to derive the posterior probability for the estimation of the CNV locus. To detect loci of multiple CNVs in the data, a sliding window process combined with our derived Bayesian posterior probability was proposed. To evaluate the performance of the method in the estimation of the CNV locus, we first performed simulation studies. Finally, we applied our approach to real data from aCGH experiments, demonstrating its applicability.     

Analysis of conformational motions and related key residue interactions responsible for a specific function of proteins with elastic network model

Protein collective motions play a critical role in many biochemical processes. How to predict the functional motions and the related key residue interactions in proteins is important for our understanding in the mechanism of the biochemical processes. Normal mode analysis (NMA) of the elastic network model (ENM) is one of the effective approaches to investigate the structure-encoded motions in proteins. However, the motion modes revealed by the conventional NMA approach do not necessarily correspond to a specific function of protein. In the present work, a new analysis method was proposed to identify the motion modes responsible for a specific function of proteins and then predict the key residue interactions involved in the functional motions by using a perturbation approach. In our method, an internal coordinate that accounts for the specific function was introduced, and the Cartesian coordinate space was transformed into the internal/Cartesian space by using linear approximation, where the introduced internal coordinate serves as one of the axes of the coordinate space. NMA of ENM in this internal/Cartesian space was performed and the function-relevant motion modes were identified according to their contributions to the specific function of proteins. Then the key residue interactions important for the functional motions of the protein were predicted as the interactions whose perturbation largely influences the fluctuation along the internal coordinate. Using our proposed methods, the maltose transporter (MalFGK₂) from E. Coli was studied. The functional motions and the key residue interactions that are related to the channel-gating function of this protein were successfully identified.     

A Novel Mechanism for NF-κB-activation via IκB-aggregation: Implications for Hepatic Mallory-Denk-Body Induced Inflammation

1. Download : Download high-res image (254KB)
2. Download : Download full-size image

Highlights

• •Liver Mallory-Denk-Body inducers elicited an IκBα-loss and NF-κB-activation.
• •IκBα-loss was due to its sequestration into insoluble cytoplasmic aggregates.
• •Four proteomic approaches identified 10 IκBα-interacting/aggregating proteins.
• •Nup153/RanBP2-aggregation prevented IκBα nuclear entry for ending NF-κB-activation.

     

CircNr1h4 regulates the pathological process of renal injury in salt‐sensitive hypertensive mice by targeting miR‐155‐5p

Circular RNAs are a class of widespread and diverse endogenous RNAs that may regulate gene expression in various diseases, but their regulation and function in hypertensive renal injury remain unclear. In this study, we generated ribosomal‐depleted RNA sequencing data from normal mouse kidneys and from injured mouse kidneys induced by deoxycorticosterone acetate‐salt hypertension and identified at least 4900 circRNA candidates. A total of 124 of these circRNAs were differentially expressed between the normal and injured kidneys. Furthermore, we characterized one abundant circRNA, termed circNr1h4, which is derived from the Nr1h4 gene and significantly down‐regulated in the injured kidneys. RNA sequencing data and qPCR analysis also showed many microRNAs and mRNAs, including miR‐155‐5p and fatty acid reductase 1 (Far1), were differentially expressed between the normal and injured kidney and related to circNr1h4. In vitro, the silencing of circNr1h4 or overexpression of miR‐155‐5p significantly decreased Far1 levels and increased reactive oxygen species. Mechanistic investigations indicated that circNr1h4 acts as a competing endogenous RNA for miR‐155‐5p, leading to regulation of its target gene Far1. Our study provides novel insight into the molecular mechanisms underlying kidney injury in hypertension, which will be required to develop therapeutic strategies of targeting circRNAs for hypertensive kidney injury.     

Model-Based Analysis of HER Activation in Cells Co-Expressing EGFR,HER2 and HER3

The HER/ErbB family of receptor tyrosine kinases drives critical responses in normal physiology and cancer, and the expression levels of the various HER receptors are critical determinants of clinical outcomes. HER activation is driven by the formation of various dimer complexes between members of this receptor family. The HER dimer types can have differential effects on downstream signaling and phenotypic outcomes. We constructed an integrated mathematical model of HER activation, and trafficking to quantitatively link receptor expression levels to dimerization and activation. We parameterized the model with a comprehensive set of HER phosphorylation and abundance data collected in a panel of human mammary epithelial cells expressing varying levels of EGFR/HER1, HER2 and HER3. Although parameter estimation yielded multiple solutions, predictions for dimer phosphorylation were in agreement with each other. We validated the model using experiments where pertuzumab was used to block HER2 dimerization. We used the model to predict HER dimerization and activation patterns in a panel of human mammary epithelial cells lines with known HER expression levels in response to stimulations with ligands EGF and HRG. Simulations over the range of expression levels seen in various cell lines indicate that: i) EGFR phosphorylation is driven by HER1-HER1 and HER1-HER2 dimers, and not HER1-HER3 dimers, ii) HER1-HER2 and HER2-HER3 dimers both contribute significantly to HER2 activation with the EGFR expression level determining the relative importance of these species, and iii) the HER2-HER3 dimer is largely responsible for HER3 activation. The model can be used to predict phosphorylated dimer levels for any given HER expression profile. This information in turn can be used to quantify the potencies of the various HER dimers, and can potentially inform personalized therapeutic approaches.