Quantitative model for inferring dynamic regulation of the tumour suppressor gene p53

Background: The availability of various "omics" datasets creates a prospect of performing the study of genome-wide genetic regulatory networks. However, one of the major challenges of using mathematical models to infer genetic regulation from microarray datasets is the lack of information for protein concentrations and activities. Most of the previous researches were based on an assumption that the mRNA levels of a gene are consistent with its protein activities, though it is not always the case. Therefore, a more sophisticated modelling framework together with the corresponding inference methods is needed to accurately estimate genetic regulation from "omics" datasets. Results: This work developed a novel approach, which is based on a nonlinear mathematical model, to infer genetic regulation from microarray gene expression data. By using the p53 network as a test system, we used the nonlinear model to estimate the activities of transcription factor (TF) p53 from the expression levels of its target genes, and to identify the activation/inhibition status of p53 to its target genes. The predicted top 317 putative p53 target genes were supported by DNA sequence analysis. A comparison between our prediction and the other published predictions of p53 targets suggests that most of putative p53 targets may share a common depleted or enriched sequence signal on their upstream non-coding region. Conclusions: The proposed quantitative model can not only be used to infer the regulatory relationship between TF and its down-stream genes, but also be applied to estimate the protein activities of TF from the expression levels of its target genes

Knowledge-based gene expression classification via matrix factorization

Motivation: Modern machine learning methods based on matrix decomposition techniques, like independent component analysis (ICA) or non-negative matrix factorization (NMF), provide new and efficient analysis tools which are currently explored to analyze gene expression profiles. These exploratory feature extraction techniques yield expression modes (ICA) or metagenes (NMF). These extracted features are considered indicative of underlying regulatory processes. They can as well be applied to the classification of gene expression datasets by grouping samples into different categories for diagnostic purposes or group genes into functional categories for further investigation of related metabolic pathways and regulatory networks. Results: In this study we focus on unsupervised matrix factorization techniques and apply ICA and sparse NMF to microarray datasets. The latter monitor the gene expression levels of human peripheral blood cells during differentiation from monocytes to macrophages. We show that these tools are able to identify relevant signatures in the deduced component matrices and extract informative sets of marker genes from these gene expression profiles. The methods rely on the joint discriminative power of a set of marker genes rather than on single marker genes. With these sets of marker genes, corroborated by leave-one-out or random forest cross-validation, the datasets could easily be classified into related diagnostic categories. The latter correspond to either monocytes versus macrophages or healthy vs Niemann Pick C disease patients.Siemens AG, MunichDFG (Graduate College 638)DAAD (PPP Luso - Alem˜a and PPP Hispano - Alemanas

Bone morphogenetic protein 7 sensitizes O6-methylguanine methyltransferase expressing-glioblastoma stem cells to clinically relevant dose of temozolomide.

BackgroundTemozolomide (TMZ) is an oral DNA-alkylating agent used for treating patients with glioblastoma. However, therapeutic benefits of TMZ can be compromised by the expression of O6-methylguanine methyltransferase (MGMT) in tumor tissue. Here we used MGMT-expressing glioblastoma stem cells (GSC) lines as a model for investigating the molecular mechanism underlying TMZ resistance, while aiming to explore a new treatment strategy designed to possibly overcome resistance to the clinically relevant dose of TMZ (35 μM).MethodsMGMT-expressing GSC cultures are resistant to TMZ, and IC50 (half maximal inhibitory concentration) is estimated at around 500 μM. Clonogenic GSC surviving 500 μM TMZ (GSC-500 μM TMZ), were isolated. Molecular signatures were identified via comparative analysis of expression microarray against parental GSC (GSC-parental). The recombinant protein of top downregulated signature was used as a single agent or in combination with TMZ, for evaluating therapeutic effects of treatment of GSC.ResultsThe molecular signatures characterized an activation of protective stress responses in GSC-500 μM TMZ, mainly including biotransformation/detoxification of xenobiotics, blocked endoplasmic reticulum stress-mediated apoptosis, epithelial-to-mesenchymal transition (EMT), and inhibited growth/differentiation. Bone morphogenetic protein 7 (BMP7) was identified as the top down-regulated gene in GSC-500 μM TMZ. Although augmenting BMP7 signaling in GSC by exogenous BMP7 treatment did not effectively stop GSC growth, it markedly sensitized both GSC-500 μM TMZ and GSC-parental to 35 μM TMZ treatment, leading to loss of self-renewal and migration capacity. BMP7 treatment induced senescence of GSC cultures and suppressed mRNA expression of CD133, MGMT, and ATP-binding cassette drug efflux transporters (ABCB1, ABCG2), as well as reconfigured transcriptional profiles in GSC by downregulating genes associated with EMT/migration/invasion, stemness, inflammation/immune response, and cell proliferation/tumorigenesis. BMP7 treatment significantly prolonged survival time of animals intracranially inoculated with GSC when compared to those untreated or treated with TMZ alone (p = 0.0017), whereas combination of two agents further extended animal survival compared to BMP7 alone (p = 0.0489).ConclusionsThese data support the view that reduced endogenous BMP7 expression/signaling in GSC may contribute to maintained stemness, EMT, and chemoresistant phenotype, suggesting that BMP7 treatment may provide a novel strategy in combination with TMZ for an effective treatment of glioblastoma exhibiting unmethylated MGMT

Defined factors to reactivate cell cycle activity in adult mouse cardiomyocytes.

Adult mammalian cardiomyocytes exit the cell cycle during the neonatal period, commensurate with the loss of regenerative capacity in adult mammalian hearts. We established conditions for long-term culture of adult mouse cardiomyocytes that are genetically labeled with fluorescence. This technique permits reliable analyses of proliferation of pre-existing cardiomyocytes without complications from cardiomyocyte marker expression loss due to dedifferentiation or significant contribution from cardiac progenitor cell expansion and differentiation in culture. Using this system, we took a candidate gene approach to screen for fetal-specific proliferative gene programs that can induce proliferation of adult mouse cardiomyocytes. Using pooled gene delivery and subtractive gene elimination, we identified a novel functional interaction between E2f Transcription Factor 2 (E2f2) and Brain Expressed X-Linked (Bex)/Transcription elongation factor A-like (Tceal) superfamily members Bex1 and Tceal8. Specifically, Bex1 and Tceal8 both preserved cell viability during E2f2-induced cell cycle re-entry. Although Tceal8 inhibited E2f2-induced S-phase re-entry, Bex1 facilitated DNA synthesis while inhibiting cell death. In sum, our study provides a valuable method for adult cardiomyocyte proliferation research and suggests that Bex family proteins may function in modulating cell proliferation and death decisions during cardiomyocyte development and maturation

Salivary biomarker development using genomic, proteomic and metabolomic approaches.

The use of saliva as a diagnostic sample provides a non-invasive, cost-efficient method of sample collection for disease screening without the need for highly trained professionals. Saliva collection is far more practical and safe compared with invasive methods of sample collection, because of the infection risk from contaminated needles during, for example, blood sampling. Furthermore, the use of saliva could increase the availability of accurate diagnostics for remote and impoverished regions. However, the development of salivary diagnostics has required technical innovation to allow stabilization and detection of analytes in the complex molecular mixture that is saliva. The recent development of cost-effective room temperature analyte stabilization methods, nucleic acid pre-amplification techniques and direct saliva transcriptomic analysis have allowed accurate detection and quantification of transcripts found in saliva. Novel protein stabilization methods have also facilitated improved proteomic analyses. Although candidate biomarkers have been discovered using epigenetic, transcriptomic, proteomic and metabolomic approaches, transcriptomic analyses have so far achieved the most progress in terms of sensitivity and specificity, and progress towards clinical implementation. Here, we review recent developments in salivary diagnostics that have been accomplished using genomic, transcriptomic, proteomic and metabolomic approaches

A Cereal Chemist's Quick Guide to Genetics, Plant Breeding and BioIT

This book is intended as a guide for cereal chemists in quality testing laboratories and grain product development companies, to help them in their understanding of fundamental genetics, functional genomics and other concepts of relevance during their interactions with crop breeding programs. Consequently the emphasis is on quick definitions of terms and concepts, assuming that the expertise of the reader is predominantly in another field.Established and supported under the Australian Government’s Cooperative Research Centre Progra