La mitochondrie est une organite ayant un rôle central dans le métabolisme énergétique de la cellule. Bien que la mitochondrie exprime son propre génome, plusieurs protéines et ARN non-codants issus du génome nucléaire sont nécessaires à la biogenèse et aux fonctions mitochondriales. Les microARNs (miRNAs) sont de petits ARN non-codants qui s'associent à la protéine Argonaute 2 (Ago2) pour moduler l'expression génique au niveau post-transcriptionnelle par ARN interférence. Classiquement, les miRNAs s’apparient à des sites de liaison complémentaires situés dans le 3’-UTR de l’ARNm cible. Nous faisons l'hypothèse que les miRNAs seraient impliqués dans la communication entre le noyau et la mitochondrie. Notre travail a donc porté sur l’étude du rôle des miRNAs dans le contexte de maladies génétiques caractérisées par une dysfonction mitochondriale. Nous avons choisi d’étudier l’ataxie de Friedreich, la plus fréquente des ataxies héréditaires, qui est causée par un déficit d’expression de la protéine mitochondriale frataxine (FXN). Nous avons montré qu'environ 90% de patients étaient homozygotes pour un haplotype spécifique des variants génétiques du 3'-UTR du gène FXN. Ce résultat a été retrouvé dans deux cohortes de patients indépendantes. Par une combinaison d’approche bioinformatique et d’expériences de co-transfections, nous avons montré que les miRNAs, et en particulier miR-124, ciblent les variants du 3’-UTR. En parallèle, nous avons évalué la possibilité que les miRNAs ciblent directement la mitochondrie. Pour cela, nous avons analysé l’expression des miRNAs dans des fractions d'ARN mitochondriale et cytosolique isolées à partir de mêmes cellules HeLa. Nous avons identifié une signature de 13 miRNAs spécifiquement enrichis dans la fraction d'ARN mitochondriale que nous avons appelé «mitomiRs». Nos prédictions ont révèle des fonctions spécifiques de ces mitomiRs à la mitochondrie, y compris la modulation de l'activité de la chaîne respiratoire. Nous avons également montré une localisation de la protéine Ago2 à l’espace inter-membranaire mitochondriale.Notre travail définit ainsi les miRNAs et Ago2 comme un nouveau niveau de communication entre le noyau et les mitochondries. Nous discutons de la possibilité que la mitochondrie agisse comme acteur du ARN interférence ou plutôt comme organite cible. Notre travail ouvre la voie à un nouveau domaine de recherche, qui pourrait avoir une utilité thérapeutique pour palier les dysfonctions mitochondriales. / Mitochondria are organelles that have a central role in the energetic metabolism of the cell. Although mitochondria express their own genome, they rely on the expression of the nuclear genome for their biogenesis and function. microRNAs (miRNAs) are small non-coding RNAs that associate with Argonaute 2 (Ago2) protein to regulate gene expression post-transcriptionallythrough RNA interference. The ‘classic’ view of RNA interference describes the pairing of miRNAs with complementary binding sites within the 3’untranslated region (3’-UTR) of the target mRNA. We hypothesized that miRNAs might be instrumental to the cross-talk between the nucleus and the mitochondria. In the first part, we assessed the role of miRNAs in the context of a rare genetic disease involving mitochondrial dysfunction. We focused on Friedreich's ataxia, the most frequent of inherited ataxia in Europe, which is caused by reduced expression of the mitochondrial protein frataxin (FXN). Intwo independent cohorts of patients, we discovered that about 90% of patients were homozygous forone specific haplotype of genetic variants of the FXN3'-UTR. By a combination of computational target prediction analysis and co-transfection experiments, we showed that miRNAs, and specifically miR-124, are involved in the regulation of the FXN.We then challenged further the relationship between the miRNAs and mitochondria through questioning their localization at mitochondria. To this end, we studied miRNAs from mitochondrial and cytosolic RNA fractions isolated from the same HeLa cells. We identified a signature of 13 miRNAs specifically enriched in the mitochondrial RNA fraction that we termed ‘mitomiRs’. Through pathway-enrichement analysis, we observed a specific mitochondrial role for mitomiRs, including regulation of ATP synthesis coupled electron trasport. We also provided the evidence of Ago2 protein location inside human mitochondria at the inter-membrane space. Our work sketches miRNAs and Ago2 as a novel layer of the interplay between the nucleus and the mitochondria. We discuss whether mitochondria may be instrumental to RNA interference or a target per se. Our work paves the way to a new field of research, which may unravel therapeutic outcomes to rescue mitochondrial dysfunction.

MicroRNAs are small non-coding RNA molecules with length of about 22 nt. These molecules participate on regulation of gene expression at the post-transcriptional level. They represent the largest group of regulators in the cell and therefore are also involved in all key processes such as proliferation, differentiation or apoptosis. Moreover, they participate in tumor transformation. These small molecules have a great potential to be diagnostic markers or assist in the treatment and prevention of diseases. This research was focused on the development of isolation method using magnetic particles with subsequent electrochemical detection of microRNA. Optimization steps were performed and then the entire method was successfully applied to real samples of HEK293 cells expressing increased levels of miR-124. The developed method proved to be sufficiently specific and applicable to the analysis of microRNA.

No description available.

Virus-infected cells can regulate non-permissive bystander cells, but the precise mechanisms remain incompletely understood. Here we report that this process can be mediated by transfer of viral RNA-loaded exosomes shed from infected cells to myeloid-derived suppressor cells (MDSCs), which in turn regulate the differentiation and function of T cells during viral infection. Specifically, we demonstrated that patients with chronic hepatitis C virus (HCV) infection exhibited significant increases in T follicular regulatory (TFR) cells and decreases in T follicular helper (TFH) cells. These MDSC-mediated T-cell dysregulations resulted in an increased ratio of TFR/TFH and IL-10 production in peripheral blood. Specifically, co-culture of MDSCs derived from HCV patients with healthy peripheral blood mononuclear cells (PBMCs) induced expansion of TFR, whereas depletion of MDSCs from PBMCs of HCV patients reduced the increases in TFR frequency and IL-10 production, and promoted the differentiation of IFN-γ-producing TFH cells. Importantly, we found that exosomes isolated from the plasma of HCV patients and supernatant of HCV-infected hepatocytes could drive monocytic myeloid cell differentiation into MDSCs. These exosomes were enriched in tetraspanins, such as CD63 and CD81, and contained HCV RNA, but exosomes isolated from patients with antiviral treatment contained no HCV RNA and could not induce MDSC differentiation. Notably, these HCV RNA-containing exosomes (HCV-Exo) were sufficient to induce MDSCs. Furthermore, incubation of healthy myeloid cells with these HCV-Exo inhibited the expression of miR−124, whereas reconstitution of PBMCs with miR−124 abolished the effects of HCV−Exo on MDSC induction. Taken together, these results indicate that HCV-associated exosomes can transfer immunomodulatory viral RNA from infected cells to neighboring immune cells and trigger MDSC expansion, which subsequently promotes TFR differentiation and inhibits TFH function. This study reveals a previously unrecognized path that represents a novel mechanism of immune dysregulation during chronic viral infection.

Molecular biology has entered an era of systematic and automated experimentation. High-throughput techniques have moved biology from small-scale experiments focused on specific genes and proteins to genome and proteome-wide screens. One result of this endeavor is the compilation of complex networks of interacting proteins. Molecular biologists hope to understand life's complex molecular machines by studying these networks. This thesis addresses tree open problems centered upon their analysis and quality assessment. First, we introduce power graph analysis as a novel approach to the representation and visualization of biological networks. Power graphs are a graph theoretic approach to lossless and compact representation of complex networks. It groups edges into cliques and bicliques, and nodes into a neighborhood hierarchy. We demonstrate power graph analysis on five examples, and show its advantages over traditional network representations. Moreover, we evaluate the algorithm performance on a benchmark, test the robustness of the algorithm to noise, and measure its empirical time complexity at O (e1.71)- sub-quadratic in the number of edges e. Second, we tackle the difficult and controversial problem of data quality in protein interaction networks. We propose a novel measure for accuracy and completeness of genome-wide protein interaction networks based on network compressibility. We validate this new measure by i) verifying the detrimental effect of false positives and false negatives, ii) showing that gold standard networks are highly compressible, iii) showing that authors' choice of confidence thresholds is consistent with high network compressibility, iv) presenting evidence that compressibility is correlated with co-expression, co-localization and shared function, v) showing that complete and accurate networks of complex systems in other domains exhibit similar levels of compressibility than current high quality interactomes. Third, we apply power graph analysis to networks derived from text-mining as well to gene expression microarray data. In particular, we present i) the network-based analysis of genome-wide expression profiles of the neuroectodermal conversion of mesenchymal stem cells. ii) the analysis of regulatory modules in a rare mitochondrial cytopathy: emph{Mitochondrial Encephalomyopathy, Lactic acidosis, and Stroke-like episodes} (MELAS), and iii) we investigate the biochemical causes behind the enhanced biocompatibility of tantalum compared with titanium.

Molecular biology has entered an era of systematic and automated experimentation. High-throughput techniques have moved biology from small-scale experiments focused on specific genes and proteins to genome and proteome-wide screens. One result of this endeavor is the compilation of complex networks of interacting proteins. Molecular biologists hope to understand life's complex molecular machines by studying these networks. This thesis addresses tree open problems centered upon their analysis and quality assessment. First, we introduce power graph analysis as a novel approach to the representation and visualization of biological networks. Power graphs are a graph theoretic approach to lossless and compact representation of complex networks. It groups edges into cliques and bicliques, and nodes into a neighborhood hierarchy. We demonstrate power graph analysis on five examples, and show its advantages over traditional network representations. Moreover, we evaluate the algorithm performance on a benchmark, test the robustness of the algorithm to noise, and measure its empirical time complexity at O (e1.71)- sub-quadratic in the number of edges e. Second, we tackle the difficult and controversial problem of data quality in protein interaction networks. We propose a novel measure for accuracy and completeness of genome-wide protein interaction networks based on network compressibility. We validate this new measure by i) verifying the detrimental effect of false positives and false negatives, ii) showing that gold standard networks are highly compressible, iii) showing that authors' choice of confidence thresholds is consistent with high network compressibility, iv) presenting evidence that compressibility is correlated with co-expression, co-localization and shared function, v) showing that complete and accurate networks of complex systems in other domains exhibit similar levels of compressibility than current high quality interactomes. Third, we apply power graph analysis to networks derived from text-mining as well to gene expression microarray data. In particular, we present i) the network-based analysis of genome-wide expression profiles of the neuroectodermal conversion of mesenchymal stem cells. ii) the analysis of regulatory modules in a rare mitochondrial cytopathy: emph{Mitochondrial Encephalomyopathy, Lactic acidosis, and Stroke-like episodes} (MELAS), and iii) we investigate the biochemical causes behind the enhanced biocompatibility of tantalum compared with titanium.