Nataly Maimari
Imperial College London
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Publication
Featured researches published by Nataly Maimari.
Cardiovascular Research | 2013
Jennifer Frueh; Nataly Maimari; Takayuki Homma; Sandra M. Bovens; Ryan M. Pedrigi; Leila Towhidi; Rob Krams
This review provides an overview of the effect of blood flow on endothelial cell (EC) signalling pathways, applying microarray technologies to cultured cells, and in vivo studies of normal and atherosclerotic animals. It is found that in cultured ECs, 5-10% of genes are up- or down-regulated in response to fluid flow, whereas only 3-6% of genes are regulated by varying levels of fluid flow. Of all genes, 90% are regulated by the steady part of fluid flow and 10% by pulsatile components. The associated gene profiles show high variability from experiment to experiment depending on experimental conditions, and importantly, the bioinformatical methods used to analyse the data. Despite this high variability, the current data sets can be summarized with the concept of endothelial priming. In this concept, fluid flows confer protection by an up-regulation of anti-atherogenic, anti-thrombotic, and anti-inflammatory gene signatures. Consequently, predilection sites of atherosclerosis, which are associated with low-shear stress, confer low protection for atherosclerosis and are, therefore, more sensitive to high cholesterol levels. Recent studies in intact non-atherosclerotic animals confirmed these in vitro studies, and suggest that a spatial component might be present. Despite the large variability, a few signalling pathways were consistently present in the majority of studies. These were the MAPK, the nuclear factor-κB, and the endothelial nitric oxide synthase-NO pathways.
FEBS Letters | 2012
Jennifer Frueh; Nataly Maimari; Ying Lui; Zoltán Kis; Vikram V. Mehta; Negin Pormehr; Calum Grant; Emmanuel Chalkias; Mika Falck-Hansen; Sandra M. Bovens; Ryan M. Pedrigi; Taka Homma; Gianfillippo Coppola; Rob Krams
Atherosclerosis is intimately coupled to blood flow by the presence of predilection sites. The coupling is through mechanotransduction of endothelial cells and approximately 2000 gene are associated with this process. This paper describes a new platform to study and identify new signalling pathways in endothelial cells covering an atherosclerotic plaque. The identified networks are synthesized in primary cells to study their reaction to flow. This synthetic approach might lead to new insights and drug targets.
Thrombosis and Haemostasis | 2016
Nataly Maimari; Ryan M. Pedrigi; Alessandra Russo; Krysia Broda; Rob Krams
Blood flow is an essential contributor to plaque growth, composition and initiation. It is sensed by endothelial cells, which react to blood flow by expressing > 1000 genes. The sheer number of genes implies that one needs genomic techniques to unravel their response in disease. Individual genomic studies have been performed but lack sufficient power to identify subtle changes in gene expression. In this study, we investigated whether a systematic meta-analysis of available microarray studies can improve their consistency. We identified 17 studies using microarrays, of which six were performed in vivo and 11 in vitro. The in vivo studies were disregarded due to the lack of the shear profile. Of the in vitro studies, a cross-platform integration of human studies (HUVECs in flow cells) showed high concordance (> 90 %). The human data set identified > 1600 genes to be shear responsive, more than any other study and in this gene set all known mechanosensitive genes and pathways were present. A detailed network analysis indicated a power distribution (e. g. the presence of hubs), without a hierarchical organisation. The average cluster coefficient was high and further analysis indicated an aggregation of 3 and 4 element motifs, indicating a high prevalence of feedback and feed forward loops, similar to prokaryotic cells. In conclusion, this initial study presented a novel method to integrate human-based mechanosensitive studies to increase its power. The robust network was large, contained all known mechanosensitive pathways and its structure revealed hubs, and a large aggregate of feedback and feed forward loops.
Nature Communications | 2016
Jennifer C. Erasmus; Susann Bruche; L. Pizarro; Nataly Maimari; T. Pogglioli; Christopher Tomlinson; J. Lees; I. Zalivina; Ann P. Wheeler; A. Alberts; Alessandra Russo; Vania M. M. Braga
In spite of extensive recent progress, a comprehensive understanding of how actin cytoskeleton remodelling supports stable junctions remains to be established. Here we design a platform that integrates actin functions with optimized phenotypic clustering and identify new cytoskeletal proteins, their functional hierarchy and pathways that modulate E-cadherin adhesion. Depletion of EEF1A, an actin bundling protein, increases E-cadherin levels at junctions without a corresponding reinforcement of cell–cell contacts. This unexpected result reflects a more dynamic and mobile junctional actin in EEF1A-depleted cells. A partner for EEF1A in cadherin contact maintenance is the formin DIAPH2, which interacts with EEF1A. In contrast, depletion of either the endocytic regulator TRIP10 or the Rho GTPase activator VAV2 reduces E-cadherin levels at junctions. TRIP10 binds to and requires VAV2 function for its junctional localization. Overall, we present new conceptual insights on junction stabilization, which integrate known and novel pathways with impact for epithelial morphogenesis, homeostasis and diseases.
Physiological Reports | 2016
Leila Towhidi; Delaram Khodadadi; Nataly Maimari; Ryan M. Pedrigi; Henry Ip; Zoltán Kis; Brenda R. Kwak; Tatiana W. Petrova; Mauro Delorenzi; Rob Krams
The discovery of the human genome has unveiled new fields of genomics, transcriptomics, and proteomics, which has produced paradigm shifts on how to study disease mechanisms, wherein a current central focus is the understanding of how gene signatures and gene networks interact within cells. These gene function studies require manipulating genes either through activation or inhibition, which can be achieved by temporarily permeabilizing the cell membrane through transfection to deliver cDNA or RNAi. An efficient transfection technique is electroporation, which applies an optimized electric pulse to permeabilize the cells of interest. When the molecules are applied on top of seeded cells, it is called “direct” transfection and when the nucleic acids are printed on the substrate and the cells are seeded on top of them, it is termed “reverse” transfection. Direct transfection has been successfully applied in previous studies, whereas reverse transfection has recently gained more attention in the context of high‐throughput experiments. Despite the emerging importance, studies comparing the efficiency of the two methods are lacking. In this study, a model for electroporation of cells in situ is developed to address this deficiency. The results indicate that reverse transfection is less efficient than direct transfection. However, the model also predicts that by increasing the concentration of deliverable molecules by a factor of 2 or increasing the applied voltage by 20%, reverse transfection can be approximately as efficient as direct transfection.
international conference on logic programming | 2013
Calin-Rares Turliuc; Nataly Maimari; Alessandra Russo; Krysia Broda
Abduction is a type of logical inference that can be successfully combined with probabilistic reasoning. However, the role of integrity constraints has not received much attention when performing logical-probabilistic inference. The contribution of our paper is a probabilistic abductive framework based on the distribution semantics for normal logic programs that handles negation as failure and integrity constraints in the form of denials. Integrity constraints are treated as evidence from the perspective of probabilistic inference. An implementation is provided that computes alternative (non-minimal) abductive solutions, using an appropriately modified abductive system, and generates the probability of a query, for given solutions. An example application of the framework is given, where gene network topologies are abduced according to biological expert knowledge, to probabilistically explain observed gene expressions. The example shows the practical utility of the proposed framework.
Nature Communications | 2017
Jennifer C. Erasmus; Susann Bruche; L. Pizarro; Nataly Maimari; T. Poggioli; Christopher Tomlinson; J. Lees; I. Zalivina; Ann P. Wheeler; A. Alberts; Alessandra Russo; Vania M. M. Braga
Nature Communications 7: Article number: 13542 (2016); Published: 6 December 2016; Updated: 5 January 2017 The original version of this Article contained an error in the spelling of the author Tommaso Poggioli, which was incorrectly given as Tommaso Pogglioli. This has now been corrected in both thePDF and HTML versions of the Article.
Logical Modeling of Biological Systems | 2014
Nataly Maimari; Krysia Broda; Antonis C. Kakas; Rob Krams; Alessandra Russo
Atherosclerosis | 2014
Nataly Maimari; Leila Towhidi; D. Oh; Krysia Broda; Alessandra Russo; Rob Krams
Atherosclerosis | 2014
Leila Towhidi; Nataly Maimari; Zoltán Kis; Delaram Khodadadi; Rob Krams