Rodrigo Assar

Calcium/calmodulin-dependent protein kinase type IV Is a target gene of the Wnt/β-catenin signaling pathway

Calcium/calmodulin‐dependent protein kinase IV (CaMKIV) plays a key role in the regulation of calcium‐dependent gene expression. The expression of CaMKIV and the activation of CREB regulated genes are involved in memory and neuronal survival. We report here that: (a) a bioinformatic analysis of 15,476 promoters of the human genome predicted several Wnt target genes, being CaMKIV a very interesting candidate; (b) CaMKIV promoter contains TCF/LEF transcription motifs similar to those present in Wnt target genes; (c) biochemical studies indicate that lithium and the canonical ligand Wnt‐3a induce CaMKIV mRNA and protein expression levels in rat hippocampal neurons as well as CaMKIV promoter activity; (d) treatment of hippocampal neurons with Wnt‐3a increases the binding of β‐catenin to the CaMKIV promoter: (e) In vivo activation of the Wnt signaling improve spatial memory impairment and restores the expression of CaMKIV in a mice double transgenic model for Alzheimers disease which shows decreased levels of the kinase. We conclude that CaMKIV is regulated by the Wnt signaling pathway and that its expression could play a role in the neuroprotective function of the Wnt signaling against the Alzheimers amyloid peptide. J. Cell. Physiol. 221: 658–667, 2009.

Genome-wide identification of new Wnt/β-catenin target genes in the human genome using CART method

BackgroundThe importance of in silico predictions for understanding cellular processes is now widely accepted, and a variety of algorithms useful for studying different biological features have been designed. In particular, the prediction of cis regulatory modules in non-coding human genome regions represents a major challenge for understanding gene regulation in several diseases. Recently, studies of the Wnt signaling pathway revealed a connection with neurodegenerative diseases such as Alzheimers. In this article, we construct a classification tool that uses the transcription factor binding site motifs composition of some gene promoters to identify new Wnt/β-catenin pathway target genes potentially involved in brain diseases.ResultsIn this study, we propose 89 new Wnt/β-catenin pathway target genes predicted in silico by using a method based on multiple Classification and Regression Tree (CART) analysis. We used as decision variables the presence of transcription factor binding site motifs in the upstream region of each gene. This prediction was validated by RT-qPCR in a sample of 9 genes. As expected, LEF1, a member of the T-cell factor/lymphoid enhancer-binding factor family (TCF/LEF1), was relevant for the classification algorithm and, remarkably, other factors related directly or indirectly to the inflammatory response and amyloidogenic processes also appeared to be relevant for the classification. Among the 89 new Wnt/β-catenin pathway targets, we found a group expressed in brain tissue that could be involved in diverse responses to neurodegenerative diseases, like Alzheimers disease (AD). These genes represent new candidates to protect cells against amyloid β toxicity, in agreement with the proposed neuroprotective role of the Wnt signaling pathway.ConclusionsOur multiple CART strategy proved to be an effective tool to identify new Wnt/β-catenin pathway targets based on the study of their regulatory regions in the human genome. In particular, several of these genes represent a new group of transcriptional dependent targets of the canonical Wnt pathway. The functions of these genes indicate that they are involved in pathophysiology related to Alzheimers disease or other brain disorders.

Leader Cells Define Directionality of Trunk, but Not Cranial, Neural Crest Cell Migration

Summary Collective cell migration is fundamental for life and a hallmark of cancer. Neural crest (NC) cells migrate collectively, but the mechanisms governing this process remain controversial. Previous analyses in Xenopus indicate that cranial NC (CNC) cells are a homogeneous population relying on cell-cell interactions for directional migration, while chick embryo analyses suggest a heterogeneous population with leader cells instructing directionality. Our data in chick and zebrafish embryos show that CNC cells do not require leader cells for migration and all cells present similar migratory capacities. In contrast, laser ablation of trunk NC (TNC) cells shows that leader cells direct movement and cell-cell contacts are required for migration. Moreover, leader and follower identities are acquired before the initiation of migration and remain fixed thereafter. Thus, two distinct mechanisms establish the directionality of CNC cells and TNC cells. This implies the existence of multiple molecular mechanisms for collective cell migration.

Genetic diversity and virulence determinants of Escherichia coli strains isolated from patients with Crohn's disease in Spain and Chile

Adherent-invasive Escherichia coli (AIEC) strains are genetically variable and virulence factors for AIEC are non-specific. FimH is the most studied pathogenicity-related protein, and there have been few studies on other proteins, such as Serine Protease Autotransporters of Enterobacteriacea (SPATEs). The goal of this study is to characterize E. coli strains isolated from patients with Crohns disease (CD) in Chile and Spain, and identify genetic differences between strains associated with virulence markers and clonality. We characterized virulence factors and genetic variability by pulse field electrophoresis (PFGE) in 50 E. coli strains isolated from Chilean and Spanish patients with CD, and also determined which of these strains presented an AIEC phenotype. Twenty-six E. coli strains from control patients were also included. PFGE patterns were heterogeneous and we also observed a highly diverse profile of virulence genes among all E. coli strains obtained from patients with CD, including those strains defined as AIEC. Two iron transporter genes chuA, and irp2, were detected in various combinations in 68–84% of CD strains. We found that the most significant individual E. coli genetic marker associated with CD E. coli strains was chuA. In addition, patho-adaptative fimH mutations were absent in some of the highly adherent and invasive strains. The fimH adhesin, the iron transporter irp2, and Class-2 SPATEs did not show a significant association with CD strains. The V27A fimH mutation was detected in the most CD strains. This study highlights the genetic variability of E. coli CD strains from two distinct geographic origins, most of them affiliated with the B2 or D E. coli phylogroups and also reveals that nearly 40% of Chilean and Spanish CD patients are colonized with E.coli with a characteristic AIEC phenotype.

Reconciling competing models: a case study of wine fermentation kinetics

Mathematical models of wine fermentation kinetics promise early diagnosis of stuck or sluggish winemaking processes as well as better matching of industrial yeast strains to specific vineyards. The economic impact of these challenges is significant: worldwide losses from stuck or sluggish fermentations are estimated at 7 billion € annually, and yeast starter production is a highly competitive market estimated at 40 million € annually. Additionally, mathematical models are an important tool for studying the biology of wine yeast fermentation through functional genomics, and contribute to our understanding of the link between genotype and phenotype for these important cell factories. We have developed an accurate combined model that best matches experimental observations over a wide range of initial conditions. This model is based on mathematical analysis of three competing ODE models for wine fermentation kinetics and statistical comparison of their predictions with a large set of experimental data. By classifying initial conditions into qualitative intervals and by systematically evaluating the competing models, we provide insight into the strengths and weaknesses of the existing models, and identify the key elements of their symbolic representation that most influence the accuracy of their predictions. In particular, we can make a distinction between main effects and secondary quadratic effects, that model interactions between cellular processes. We generalize our methodology to the common case where one wishes to combine competing models and refine them to better agree with experimental data. The first step is symbolic, and rewrites each model into a polynomial form in which main and secondary effects are conveniently expressed. The second step is statistical, classifying the match of each models predictions with experimental data, and identifying the key terms in its equations. Finally, we use a combination of those terms to instantiate the combined model expressed in polynomial form. We show that this procedure is feasible for the case of wine fermentation kinetics, allowing predictions which closely match experimental observations in normal and problematic fermentation.

Aging and Health Policies in Chile: New Agendas for Research

Abstract—Population aging is among the most important global transformations. Compared to European and North American countries, Chile is among the countries with the fastest growth of life expectancy at birth during recent decades. The aging of Chiles population is related to the improvement of living conditions, but also entails risks that tend to be associated with a rapid economic growth accompanied by large income inequalities and a chronic deficit of basic social benefits. The rapid demographic transition towards an aged population has unfolded in a context of poor development of public policies to tackle the opportunities and needs associated with an aging society. This article provides a brief overview of current Chilean public policy on aging, with a focus on healthy aging as defined by World Health Organization. The discussion addresses core challenges to successfully achieve healthy aging in Chile.

Psychotherapy and Genetic Neuroscience: An Emerging Dialog

Recent research in psychiatric genetics has led to a move away from simple diathesis-stress models to more complex models of psychopathology incorporating a focus on gene–environment interactions and epigenetics. Our increased understanding of the way biology encodes the impact of life events on organisms has also generated more sophisticated theoretical models concerning the molecular processes at the interface between “nature” and “nurture.” There is also increasing consensus that psychotherapy entails a specific type of learning in the context of an emotional relationship (i.e., the therapeutic relationship) that may also lead to epigenetic modifications across different therapeutic treatment modalities. This paper provides a systematic review of this emerging body of research. It is concluded that, although the evidence is still limited at this stage, extant research does indeed suggest that psychotherapy may be associated with epigenetic changes. Furthermore, it is argued that epigenetic studies may play a key role in the identification of biomarkers implicated in vulnerability for psychopathology, and thus may improve diagnosis and open up future research opportunities regarding the mechanism of action of psychotropic drugs as well as psychotherapy. We review evidence suggesting there may be important individual differences in susceptibility to environmental input, including psychotherapy. In addition, given that there is increasing evidence for the transgenerational transmission of epigenetic modifications in animals and humans exposed to trauma and adversity, epigenetic changes produced by psychotherapy may also potentially be passed on to the next generation, which opens up new perspective for prevention science. We conclude this paper stressing the limitations of current research and by proposing a set of recommendations for future research in this area.

Methotrexate pharmacogenetics in Uruguayan adults with hematological malignant diseases

Background: Individual variability is among the causes of toxicity and interruption of treatment in acute lymphoblastic leukemia (ALL) and severe non‐Hodgkin lymphoma (NHL) patients under protocols including Methotrexate (MTX): 2,4‐diamino‐N10‐methyl propyl‐glutamic acid. Methods: 41 Uruguayan patients were recruited. Gene polymorphisms involved in MTX pathway were analyzed and their association with treatment toxicities and outcome was evaluated. Results: Genotype distribution and allele frequency were determined for SLC19A1 G80A, MTHFR C677T and A1298C, TYMS 28 bp copy number variation, SLCO1B1 T521C, DHFR C−1610G/T, DHFR C‐680A, DHFR A‐317G and DHFR 19 bp indel. Multivariate analysis showed that DHFR‐1610G/T (OR = 0.107, p = 0.018) and MTHFR677T alleles (OR = 0.12, p = 0.026) had a strong protective effect against hematologic toxicity, while DHFR‐1610CC genotype increased this toxicity (OR = 9, p = 0.045). No more associations were found. Conclusions: The associations found between gene polymorphisms and toxicities in this small cohort are encouraging for a more extensive research to gain a better dose individualization in adult ALL and NHL patients. Besides, genotype distribution showed to be different from other populations, reinforcing the idea that genotype data from other populations should not be extrapolated to ours. Graphical Abstract Figure. No caption available.

Predicting the Metagenomics Content with Multiple CART Trees

Metagenomics is a technique for the characterization and identification of microbial genomes using direct isolation of genomic DNA from the environment without cultivation. One of the key step in this process is the taxonomic classification and clustering of the DNA fragments, process also known as binning. To date, the most common practice is classifying through alignments to public databases. When a representing specie is present in this database the process is simple and successful, if not, an underestimation of taxonomic abundances is produced. In this work we propose a alignment-free method capable of assign taxa to each read in the sample by analyzing the statistical properties of the reads. Given an environment, we collect genomes from public available databases and generate genomic fragments libraries. Then, statistics of k-mer frequencies, GC ratio and GC skew are computed for each read and stored in an environment-associated dataset used to build a robust machine learning procedure based on multiple CART trees. Finally, for each read the CART trees are asked about their taxa and the most voted ones are selected. The method was tested using simulated and public human gut microbiome data sets. The database was constructed using 98 genera present in Gastrointestinal Tract available at Human Microbiome Project. A multiple CART tree with 558-trees predictor was generated, capable to estimate the genus and abundance in the sample with 47 % of accuracy in read assignments. Performance rates are comparable with those from semi-supervised methods and also the computation times were reduced due to alignment-free methodology. Restricted to 17 early considered genera, our method increases its accuracy to 77 %.

Modeling acclimatization by hybrid systems: Condition changes alter biological system behavior models

In order to describe the dynamic behavior of a complex biological system, it is useful to combine models integrating processes at different levels and with temporal dependencies. Such combinations are necessary for modeling acclimatization, a phenomenon where changes in environmental conditions can induce drastic changes in the behavior of a biological system. In this article we formalize the use of hybrid systems as a tool to model this kind of biological behavior. A modeling scheme called strong switches is proposed. It allows one to take into account both minor adjustments to the coefficients of a continuous model, and, more interestingly, large-scale changes to the structure of the model. We illustrate the proposed methodology with two applications: acclimatization in wine fermentation kinetics, and acclimatization of osteo-adipo differentiation system linking stimulus signals to bone mass.