Reconstruction of molecular networks involved in citokine-induced myotubes atrophy integrating microRNA and mRNA expression

Pós-graduação em Ciências Biológicas (Genética) - IBB

Identifying regulational alterations in gene regulatory networks by state space representation of vector autoregressive models and variational annealing

Background: In the analysis of effects by cell treatment such as drug dosing, identifying changes on gene network structures between normal and treated cells is a key task. A possible way for identifying the changes is to compare structures of networks estimated from data on normal and treated cells separately. However, this approach usually fails to estimate accurate gene networks due to the limited length of time series data and measurement noise. Thus, approaches that identify changes on regulations by using time series data on both conditions in an efficient manner are demanded. Methods: We propose a new statistical approach that is based on the state space representation of the vector autoregressive model and estimates gene networks on two different conditions in order to identify changes on regulations between the conditions. In the mathematical model of our approach, hidden binary variables are newly introduced to indicate the presence of regulations on each condition. The use of the hidden binary variables enables an efficient data usage; data on both conditions are used for commonly existing regulations, while for condition specific regulations corresponding data are only applied. Also, the similarity of networks on two conditions is automatically considered from the design of the potential function for the hidden binary variables. For the estimation of the hidden binary variables, we derive a new variational annealing method that searches the configuration of the binary variables maximizing the marginal likelihood. Results: For the performance evaluation, we use time series data from two topologically similar synthetic networks, and confirm that our proposed approach estimates commonly existing regulations as well as changes on regulations with higher coverage and precision than other existing approaches in almost all the experimental settings. For a real data application, our proposed approach is applied to time series data from normal Human lung cells and Human lung cells treated by stimulating EGF-receptors and dosing an anticancer drug termed Gefitinib. In the treated lung cells, a cancer cell condition is simulated by the stimulation of EGF-receptors, but the effect would be counteracted due to the selective inhibition of EGF-receptors by Gefitinib. However, gene expression profiles are actually different between the conditions, and the genes related to the identified changes are considered as possible off-targets of Gefitinib. Conclusions: From the synthetically generated time series data, our proposed approach can identify changes on regulations more accurately than existing methods. By applying the proposed approach to the time series data on normal and treated Human lung cells, candidates of off-target genes of Gefitinib are found. According to the published clinical information, one of the genes can be related to a factor of interstitial pneumonia, which is known as a side effect of Gefitinib.

Disruption of vitellogenin gene function in adult honeybees by intra-abdominal injection of double-stranded RNA

Abstract Background The ability to manipulate the genetic networks underlying the physiological and behavioural repertoires of the adult honeybee worker (Apis mellifera) is likely to deepen our understanding of issues such as learning and memory generation, ageing, and the regulatory anatomy of social systems in proximate as well as evolutionary terms. Here we assess two methods for probing gene function by RNA interference (RNAi) in adult honeybees. Results The vitellogenin gene was chosen as target because its expression is unlikely to have a phenotypic effect until the adult stage in bees. This allowed us to introduce dsRNA in preblastoderm eggs without affecting gene function during development. Of workers reared from eggs injected with dsRNA derived from a 504 bp stretch of the vitellogenin coding sequence, 15% had strongly reduced levels of vitellogenin mRNA. When dsRNA was introduced by intra-abdominal injection in newly emerged bees, almost all individuals (96 %) showed the mutant phenotype. An RNA-fragment with an apparent size similar to the template dsRNA was still present in this group after 15 days. Conclusion Injection of dsRNA in eggs at the preblastoderm stage seems to allow disruption of gene function in all developmental stages. To dissect gene function in the adult stage, the intra-abdominal injection technique seems superior to egg injection as it gives a much higher penetrance, it is much simpler, and it makes it possible to address genes that are also expressed in the embryonic, larval or pupal stages.

Modeling gene expression regulatory networks with the sparse vector autoregressive model

Abstract Background To understand the molecular mechanisms underlying important biological processes, a detailed description of the gene products networks involved is required. In order to define and understand such molecular networks, some statistical methods are proposed in the literature to estimate gene regulatory networks from time-series microarray data. However, several problems still need to be overcome. Firstly, information flow need to be inferred, in addition to the correlation between genes. Secondly, we usually try to identify large networks from a large number of genes (parameters) originating from a smaller number of microarray experiments (samples). Due to this situation, which is rather frequent in Bioinformatics, it is difficult to perform statistical tests using methods that model large gene-gene networks. In addition, most of the models are based on dimension reduction using clustering techniques, therefore, the resulting network is not a gene-gene network but a module-module network. Here, we present the Sparse Vector Autoregressive model as a solution to these problems. Results We have applied the Sparse Vector Autoregressive model to estimate gene regulatory networks based on gene expression profiles obtained from time-series microarray experiments. Through extensive simulations, by applying the SVAR method to artificial regulatory networks, we show that SVAR can infer true positive edges even under conditions in which the number of samples is smaller than the number of genes. Moreover, it is possible to control for false positives, a significant advantage when compared to other methods described in the literature, which are based on ranks or score functions. By applying SVAR to actual HeLa cell cycle gene expression data, we were able to identify well known transcription factor targets. Conclusion The proposed SVAR method is able to model gene regulatory networks in frequent situations in which the number of samples is lower than the number of genes, making it possible to naturally infer partial Granger causalities without any a priori information. In addition, we present a statistical test to control the false discovery rate, which was not previously possible using other gene regulatory network models.

An mRNA-Derived Noncoding RNA Targets and Regulates the Ribosome.

The structural and functional repertoire of small non-protein-coding RNAs (ncRNAs) is central for establishing gene regulation networks in cells and organisms. Here, we show that an mRNA-derived 18-nucleotide-long ncRNA is capable of downregulating translation in Saccharomyces cerevisiae by targeting the ribosome. This 18-mer ncRNA binds to polysomes upon salt stress and is crucial for efficient growth under hyperosmotic conditions. Although the 18-mer RNA originates from the TRM10 locus, which encodes a tRNA methyltransferase, genetic analyses revealed the 18-mer RNA nucleotide sequence, rather than the mRNA-encoded enzyme, as the translation regulator. Our data reveal the ribosome as a target for a small regulatory ncRNA and demonstrate the existence of a yet unkown mechanism of translation regulation. Ribosome-targeted small ncRNAs are found in all domains of life and represent a prevalent but so far largely unexplored class of regulatory molecules.

The ribosome as novel target for small regulatory RNAs

Small non-protein-coding RNA (ncRNA) molecules have been recognized recently as major contributors to regulatory networks in controlling gene expression in a highly efficient manner. While the list of validated ncRNAs that regulate crucial cellular processes grows steadily, not a single ncRNA has been identified that directly interacts and regulates the ribosome during protein biosynthesis (with the notable exceptions of 7SL RNA and tmRNA). All of the recently discovered regulatory ncRNAs that act on translation (e.g. microRNAs, siRNAs or antisense RNAs) target the mRNA rather than the ribosome. This is unexpected, given the central position the ribosome plays during gene expression. Furthermore it is strongly assumed that the primordial translation system in the ‘RNA world’ most likely received direct regulatory input from ncRNA-like cofactors. The fundamental question that we would like to ask is: Does the ‘RNA world still communicate’ with the ribosome? To address this question, we have analyzed the small ncRNA interactomes of ribosomes of prokaryotic (H. volcanii, S. aureus) and unicellular eukaryotic model organisms. Deep-sequencing and subsequent bioinformatic analyses revealed thousands of putative ribosome-associated ncRNAs. For a subset of these ncRNA candidates we have gathered experimental evidence that they are expressed in a stress-dependent manner and indeed directly target the ribosome. In the archaeon H. volcanii a tRNA-derived fragment was identified to target the small ribosomal subunit upon alkaline stress in vitro and in vivo. As a consequence of ribosome binding, this tRNA-fragment reduces protein synthesis by interfering with the peptidyl transferase activity. Our data reveal the ribosome as a novel target for small regulatory ncRNAs in all domains of life. Ribosome-bound ncRNAs are capable of fine tuning translation and might represent a so far largely unexplored class of regulatory sRNAs.

The ribosome as novel target for small regulatory RNAs

Small non-protein-coding RNA (ncRNA) molecules have been recognized recently as major contributors to regulatory networks in controlling gene expression in a highly efficient manner. While the list of validated ncRNAs that regulate crucial cellular processes grows steadily, not a single ncRNA has been identified that directly interacts and regulates the ribosome during protein biosynthesis (with the notable exceptions of 7SL RNA and tmRNA). All of the recently discovered regulatory ncRNAs that act on translation (e.g. microRNAs, siRNAs or antisense RNAs) target the mRNA rather than the ribosome. This is unexpected, given the central position the ribosome plays during gene expression. Furthermore it is strongly assumed that the primordial translation system in the ‘RNA world’ most likely received direct regulatory input from ncRNA-like cofactors. The fundamental question that we would like to ask is: Does the ‘RNA world still communicate’ with the ribosome? To address this question, we have analyzed the small ncRNA interactomes of ribosomes of organisms from all three domains of life. Deep-sequencing and subsequent bioinformatic analyses revealed thousands of putative ribosome-associated ncRNAs.1,2 For a subset of these ncRNA candidates we have gathered experimental evidence that they are expressed in a stress-dependent manner and indeed directly target the ribosome. We show that some of these ribosome-bound small ncRNAs are capable of fine tuning protein synthesis in vitro and in vivo. Our data therefore reveal the ribosome as a novel target for small regulatory ncRNAs in all domains of life and suggest the existence of a so far largely unexplored mechanism of translation regulation.

The ribosome as novel target for stress-induced small regulatory RNAs

Small non-protein-coding RNA (ncRNA) molecules represent major contributors to regulatory networks in controlling gene expression in a highly efficient manner. All of the recently discovered regulatory ncRNAs that act on translation (e.g. microRNAs, siRNAs or antisense RNAs) target the mRNA rather than the ribosome. To address the question, whether small ncRNA regulators exist that are capable of modulating the rate of protein production by directly interacting with the ribosome, we have analyzed the small ncRNA interactomes of ribosomes Deep-sequencing and subsequent bioinformatic analyses revealed thousands of putative ribosome-associated ncRNAs in various model organisms (1,2). For a subset of these ncRNA candidates we have gathered experimental evidence that they associate with ribosomes in a stress-dependent manner and are capable of regulating gene expression by fine-tuning the rate of protein biosynthesis (3,4). Many of the investigated ribosome-bound small ncRNA appear to be processing products from larger functional RNAs, such as tRNAs (2,3) or mRNAs (3). Post-transcriptional cleavage of RNA molecules to generate smaller fragments is a widespread mechanism that enlarges the structural and functional complexity of cellular RNomes. Our data reveal the ribosome as a target for small regulatory ncRNAs and demonstrate the existence of a yet unknown mechanism of translation regulation. Ribosome-associated ncRNAs (rancRNAs) are found in all domains of life and represent a prevalent but so far largely unexplored class of regulatory molecules (5). Future work on the small ncRNA interactomes of ribosomes in a variety of model systems will allow deeper insight into the conservation and functional repertoire of this emerging class of regulatory ncRNA molecules.

Correction of aberrant FGFR1 RNA splicing through blocking intronic regulatory elements

Analysis of the human genome has revealed that more than 74% of human genes undergo alternative RNA splicing. Aberrations in alternative RNA splicing have been associated with several human disorders, including cancer. ^ We studied the aberrant expression of alternative RNA splicing isoforms of the Fibroblast Growth Factor Receptor 1 (FGFR1) gene in a human glioblastoma cancer model. Normal glial cells express the FGFR1α, which contains three extracellular domains. In tumors the most abundant isoform is the FGFR1β, which lacks the first extracellular domain due to the skipping of a single exon, termed alpha. The skipping of the α-exon is regulated by two intronic silencing sequences within the precursor mRNA. Since we observed no mutations on these elements in tumor cells, we hypothesized that the over-expression of regulatory proteins that recognize these sequences is responsible for the aberrant expression of splicing isoforms. Hence, we blocked the formation of protein complexes on the ISS using antisense RNA oligonucleotides in vitro. We also evaluated the impact of the ISS antisense oligonucleotides on the endogenous FGFR1 splicing, in a glioblastoma cell model. By targeting intronic regulatory elements we were able to increase the level of alpha exon inclusion up to 90% in glioblastoma cells. The effect was dose dependent, sequence specific and reproducible in glioblastoma and other cancer cells, which also exhibit an alpha exon skipping phenotype. Targeting FGFR1 endogenous ISS1 and ISS2 sequences did not have an additive or synergistic effect, which suggest a regulatory splicing mechanism that requires the interaction of complexes formed on these elements. An increase in the levels of the FGFR1α isoform resulted in a reduction in cell invasiveness. Also, a significant increase in the levels of caspase 3/7 activities, which is indicative of an elevation in apoptosis levels, suggests that expression of FGFR1β might be relevant for tumor survival. These studies demonstrate that it is possible to prevent aberrant expression of exon skipping events through the targeting of intronic regulatory elements, providing an important new therapeutic tool for the correction of human disease caused by alternative RNA splicing. ^

bZIP transcription factors in the regulatory networks controlling seed maturation and germination of Arabidopsis thaliana

Se describe la expresión por RTqPCR de los genes que codifican los factores transcripcionales bZIP44 y bZIP9. Asimismo se establece la interacción entre ambas proteínas en el sistema de 2 híbridos de levadura y in planta por complementación bimolecular fluorescente.

Heterogeneous nuclear ribonucleoprotein A1 binds to the transcription-regulatory region of mouse hepatitis virus RNA

A cellular protein, previously described as p35/38, binds to the complementary (−)-strand of the leader RNA and intergenic (IG) sequence of mouse hepatitis virus (MHV) RNA. The extent of the binding of this protein to IG sites correlates with the efficiency of the subgenomic mRNA transcription from that IG site, suggesting that it is a requisite transcription factor. We have purified this protein and determined by partial peptide sequencing that it is heterogeneous nuclear ribonucleoprotein (hnRNP) A1, an abundant, primarily nuclear protein. hnRNP A1 shuttles between the nucleus and cytoplasm and plays a role in the regulation of alternative RNA splicing. The MHV(−)-strand leader and IG sequences conform to the consensus binding motifs of hnRNP A1. Recombinant hnRNP A1 bound to these two RNA regions in vitro in a sequence-specific manner. During MHV infection, hnRNP A1 relocalizes from the nucleus to the cytoplasm, where viral replication occurs. These data suggest that hnRNP A1 is a cellular factor that regulates the RNA-dependent RNA transcription of the virus.

Conserved stem–loop structures in the HIV-1 RNA region containing the A3 3′ splice site and its cis-regulatory element: possible involvement in RNA splicing

The HIV-1 transcript is alternatively spliced to over 30 different mRNAs. Whether RNA secondary structure can influence HIV-1 RNA alternative splicing has not previously been examined. Here we have determined the secondary structure of the HIV-1/BRU RNA segment, containing the alternative A3, A4a, A4b, A4c and A5 3′ splice sites. Site A3, required for tat mRNA production, is contained in the terminal loop of a stem–loop structure (SLS2), which is highly conserved in HIV-1 and related SIVcpz strains. The exon splicing silencer (ESS2) acting on site A3 is located in a long irregular stem–loop structure (SLS3). Two SLS3 domains were protected by nuclear components under splicing condition assays. One contains the A4c branch points and a putative SR protein binding site. The other one is adjacent to ESS2. Unexpectedly, only the 3′ A residue of ESS2 was protected. The suboptimal A3 polypyrimidine tract (PPT) is base paired. Using site-directed mutagenesis and transfection of a mini-HIV-1 cDNA into HeLa cells, we found that, in a wild-type PPT context, a mutation of the A3 downstream sequence that reinforced SLS2 stability decreased site A3 utilization. This was not the case with an optimized PPT. Hence, sequence and secondary structure of the PPT may cooperate in limiting site A3 utilization.