Modelling the onset of senescence at the G1/S cell cycle checkpoint.

BACKGROUND: DNA damage (single or double-strand breaks) triggers adapted cellular responses. These responses are elicited through signalling pathways, which activate cell cycle checkpoints and basically lead to three cellular fates: cycle arrest promoting DNA repair, senescence (permanent arrest) or cell death. Cellular senescence is known for having a tumour-suppressive function and its regulation arouses a growing scientific interest. Here, we advance a qualitative model covering DNA damage response pathways, focusing on G1/S checkpoint enforcement, supposedly more sensitive to arrest than G2/M checkpoint. RESULTS: We define a discrete, logical model encompassing ATM (ataxia telangiectasia mutated) and ATR (ATM and Rad3-related) pathways activation upon DNA damage, as well as G1/S checkpoint main components. It also includes the stress responsive protein p38MAPK (mitogen-activated protein kinase 14) known to be involved in the regulation of senescence. The model has four outcomes that convey alternative cell fates: proliferation, (transient) cell cycle arrest, apoptosis and senescence. Different levels of DNA damage are considered, defined by distinct combinations of single and double-strand breaks. Each leads to a single stable state denoting the cell fate adopted upon this specific damage. A range of model perturbations corresponding to gene loss-of-function or gain-of-function is compared to experimental mutations. CONCLUSIONS: As a step towards an integrative model of DNA-damage response pathways to better cover the onset of senescence, our model focuses on G1/S checkpoint enforcement. This model qualitatively agrees with most experimental observations, including experiments involving mutations. Furthermore, it provides some predictions.

A method to identify important dynamical states in Boolean models of regulatory networks: application to regulation of stomata closure by ABA in A. thaliana.

BACKGROUND: We introduce a method to analyze the states of regulatory Boolean models that identifies important network states and their biological influence on the global network dynamics. It consists in (1) finding the states of the network that are most frequently visited and (2) the identification of variable and frozen nodes of the network. The method, along with a simulation that includes random features, is applied to the study of stomata closure by abscisic acid (ABA) in A. thaliana proposed by Albert and coworkers. RESULTS: We find that for the case of study, that the dynamics of wild and mutant networks have just two states that are highly visited in their space of states and about a third of all nodes of the wild network are variable while the rest remain frozen in True or False states. This high number of frozen elements explains the low cardinality of the space of states of the wild network. Similar results are observed in the mutant networks. The application of the method allowed us to explain how wild and mutants behave dynamically in the SS and determined an essential feature of the activation of the closure node (representing stomata closure), i.e. its synchronization with the AnionEm node (representing anion efflux at the plasma membrane). The dynamics of this synchronization explains the efficiency reached by the wild and each of the mutant networks. CONCLUSIONS: For the biological problem analyzed, our method allows determining how wild and mutant networks differ 'phenotypically'. It shows that the different efficiencies of stomata closure reached among the simulated wild and mutant networks follow from a dynamical behavior of two nodes that are always synchronized. Additionally, we predict that the involvement of the anion efflux at the plasma membrane is crucial for the plant response to ABA. AVAILABILITY: The algorithm used in the simulations is available upon request.

ViaComplex: software for landscape analysis of gene expression networks in genomic context.

UNLABELLED: ViaComplex is an open-source application that builds landscape maps of gene expression networks. The motivation for this software comes from two previous publications (Nucleic Acids Res., 35, 1859-1867, 2007; Nucleic Acids Res., 36, 6269-6283, 2008). The first article presents a network-based model of genome stability pathways where we defined a set of genes that characterizes each genetic system. In the second article we analyzed this model by projecting functional information from several experiments onto the gene network topology. In order to systematize the methods developed in these articles, ViaComplex provides tools that may help potential users to assess different high-throughput experiments in the context of six core genome maintenance mechanisms. This model illustrates how different gene networks can be analyzed by the same algorithm. AVAILABILITY: (http://lief.if.ufrgs.br/pub/biosoftwares/viacomplex).

Evolutionary origins of human apoptosis and genome-stability gene networks.

Apoptosis is essential for complex multicellular organisms and its failure is associated with genome instability and cancer. Interactions between apoptosis and genome-maintenance mechanisms have been extensively documented and include transactivation-independent and -dependent functions, in which the tumor-suppressor protein p53 works as a 'molecular node' in the DNA-damage response. Although apoptosis and genome stability have been identified as ancient pathways in eukaryote phylogeny, the biological evolution underlying the emergence of an integrated system remains largely unknown. Here, using computational methods, we reconstruct the evolutionary scenario that linked apoptosis with genome stability pathways in a functional human gene/protein association network. We found that the entanglement of DNA repair, chromosome stability and apoptosis gene networks appears with the caspase gene family and the antiapoptotic gene BCL2. Also, several critical nodes that entangle apoptosis and genome stability are cancer genes (e.g. ATM, BRCA1, BRCA2, MLH1, MSH2, MSH6 and TP53), although their orthologs have arisen in different points of evolution. Our results demonstrate how genome stability and apoptosis were co-opted during evolution recruiting genes that merge both systems. We also provide several examples to exploit this evolutionary platform, where we have judiciously extended information on gene essentiality inferred from model organisms to human.

Impaired expression of NER gene network in sporadic solid tumors.

Nucleotide repair genes are not generally altered in sporadic solid tumors. However, point mutations are found scattered throughout the genome of cancer cells indicating that the repair pathways are dysfunctional. To address this point, in this work we focus on the expression pathways rather than in the DNA structure of repair genes related to either genome stability or essential metabolic functions. We present here a novel statistical analysis comparing ten gene expression pathways in human normal and cancer cells using serial analysis of gene expression (SAGE) data. We find that in cancer cells nucleotide-excision repair (NER) and apoptosis are the most impaired pathways and have a highly altered diversity of gene expression profile when compared to normal cells. We propose that genome point mutations in sporadic tumors can be explained by a structurally conserved NER with a functional disorder generated from its entanglement with the apoptosis gene network.

Cupin: a candidate molecular structure for the Nep1-like protein family.

BACKGROUND: NEP1-like proteins (NLPs) are a novel family of microbial elicitors of plant necrosis. Some NLPs induce a hypersensitive-like response in dicot plants though the basis for this response remains unclear. In addition, the spatial structure and the role of these highly conserved proteins are not known. RESULTS: We predict a 3d-structure for the beta-rich section of the NLPs based on alignments, prediction tools and molecular dynamics. We calculated a consensus sequence from 42 NLPs proteins, predicted its secondary structure and obtained a high quality alignment of this structure and conserved residues with the two Cupin superfamily motifs. The conserved sequence GHRHDWE and several common residues, especially some conserved histidines, in NLPs match closely the two cupin motifs. Besides other common residues shared by dicot Auxin-Binding Proteins (ABPs) and NLPs, an additional conserved histidine found in all dicot ABPs was also found in all NLPs at the same position. CONCLUSION: We propose that the necrosis inducing protein class belongs to the Cupin superfamily. Based on the 3d-structure, we are proposing some possible functions for the NLPs.

Network integration of multi-tumour omics data suggests novel targeting strategies.

We characterize different tumour types in search for multi-tumour drug targets, in particular aiming for drug repurposing and novel drug combinations. Starting from 11 tumour types from The Cancer Genome Atlas, we obtain three clusters based on transcriptomic correlation profiles. A network-based analysis, integrating gene expression profiles and protein interactions of cancer-related genes, allows us to define three cluster-specific signatures, with genes belonging to NF-κB signaling, chromosomal instability, ubiquitin-proteasome system, DNA metabolism, and apoptosis biological processes. These signatures have been characterized by different approaches based on mutational, pharmacological and clinical evidences, demonstrating the validity of our selection. Moreover, we define new pharmacological strategies validated by in vitro experiments that show inhibition of cell growth in two tumour cell lines, with significant synergistic effect. Our study thus provides a list of genes and pathways that could possibly be used, singularly or in combination, for the design of novel treatment strategies.

Computer simulation of the influence of cellular adhesion on the morphology of the interface between tissues of proliferating and quiescent cells.

We investigate the influence of cellular adhesion on the morphology of the interface between a tissue of proliferating and quiescent cells using the cellular Potts model. We show that a decrease in surface tension changes the morphology of the interface and that only for negative surface tensions cell detachment from the proliferative tissue occurs suggesting that this might be a necessary condition for metastatization in malignant neoplasies.

Bioinformatics analysis of mycoplasma metabolism: important enzymes, metabolic similarities, and redundancy.

In this work we apply a bioinformatics approach to determine the most important enzymes of the metabolic network of mycoplasmas. The genomes of several mycoplasmas shared predicted important enzymes. Our method allows us to determine both enzymes that are isolated from the metabolic network of the organism and those that are redundant. We also compare the similarities of the mycoplasmas metabolic networks with the phylogenetic relationships predicted from their 16s rRNA sequences.

The R implementation of the CRAN package PATHChange, a tool to study genetic pathway alterations in transcriptomic data.

Tools that extract phenotype alterations from transcriptomic data are important to improve the interpretation of biological studies. PATHChange is a statistical CRAN package designed to work with data downloaded from the Gene Expression Omnibus database (GEO) to determine differential pathway expression in comparative studies including control samples. In this paper we present details of the structure, implementation and an example of use of the package.

An integrated model for cellular analysis.

We present the MOlecular NETwork (MONET) ontology as a model to integrate data from different networks that govern cell function. To achieve this, different existing ontologies were analyzed and an integrated ontology was built in a way to make it possible to share and reuse knowledge, support interoperability between systems, and also allow the formulation of hypotheses through inferences. By studying the cell as an entity of a myriad of elements and networks of interactions, we aim to offer a means to understand the large-scale characteristics responsible for the behavior of the cell and to enable new biological insights.

A Model for p38MAPK-Induced Astrocyte Senescence.

Experimental evidence indicates that aging leads to accumulation of senescent cells in tissues and they develop a secretory phenotype (also known as SASP, for senescence-associated secretory phenotype) that can contribute to chronic inflammation and diseases. Recent results have showed that markers of senescence in astrocytes from aged brains are increased in brains with Alzheimer's disease. These studies strongly involved the stress kinase p38MAPK in the regulation of the secretory phenotype of astrocytes, yet the molecular mechanisms underlying the onset of senescence and SASP activation remain unclear. In this work, we propose a discrete logical model for astrocyte senescence determined by the level of DNA damage (reparable or irreparable DNA strand breaks) where the kinase p38MAPK plays a central role in the regulation of senescence and SASP. The model produces four alternative stable states: proliferation, transient cycle arrest, apoptosis and senescence (and SASP) computed from its inputs representing DNA damages. Perturbations of the model were performed through gene gain or loss of functions and compared with results concerning cultures of normal and mutant astrocytes showing agreement in most cases. Moreover, the model allows some predictions that remain to be tested experimentally.

Essentiality and damage in metabolic networks.

Understanding the architecture of physiological functions from annotated genome sequences is a major task for postgenomic biology. From the annotated genome sequence of the microbe Escherichia coli, we propose a general quantitative definition of enzyme importance in a metabolic network. Using a graph analysis of its metabolism, we relate the extent of the topological damage generated in the metabolic network by the deletion of an enzyme to the experimentally determined viability of the organism in the absence of that enzyme. We show that the network is robust and that the extent of the damage relates to enzyme importance. We predict that a large fraction (91%) of enzymes causes little damage when removed, while a small group (9%) can cause serious damage. Experimental results confirm that this group contains the majority of essential enzymes. The results may reveal a universal property of metabolic networks.

Using the FORESTS and KEGG databases to investigate the metabolic network of Eucalyptus

In this work we apply a bioinformatics approach to determine the most important enzymes of the metabolic network of Eucalyptus to determine the coverage of the genome in the FORESTS library. We conclude that the library does not cover completely the metabolism of the organism. However, some important pathways could be analyzed, especially the lignin synthesis. We found that four of the most important enzymes predicted are involved in this pathway