Predição de promotores de Bacillus subtilis usando técnicas de aprendizado de máquina

One of the most important goals of bioinformatics is the ability to identify genes in uncharacterized DNA sequences on world wide database. Gene expression on prokaryotes initiates when the RNA-polymerase enzyme interacts with DNA regions called promoters. In these regions are located the main regulatory elements of the transcription process. Despite the improvement of in vitro techniques for molecular biology analysis, characterizing and identifying a great number of promoters on a genome is a complex task. Nevertheless, the main drawback is the absence of a large set of promoters to identify conserved patterns among the species. Hence, a in silico method to predict them on any species is a challenge. Improved promoter prediction methods can be one step towards developing more reliable ab initio gene prediction methods. In this work, we present an empirical comparison of Machine Learning (ML) techniques such as Na¨ýve Bayes, Decision Trees, Support Vector Machines and Neural Networks, Voted Perceptron, PART, k-NN and and ensemble approaches (Bagging and Boosting) to the task of predicting Bacillus subtilis. In order to do so, we first built two data set of promoter and nonpromoter sequences for B. subtilis and a hybrid one. In order to evaluate of ML methods a cross-validation procedure is applied. Good results were obtained with methods of ML like SVM and Naïve Bayes using B. subtilis. However, we have not reached good results on hybrid database

Minimal cross-subsidies approach for loss allocation in distribution networks with open access

Open access philosophy applied by regulatory agencies may lead to a scenario where captive consumers will solely face the responsibility on distribution network's losses even with Independent Energy Producers (also known as Distributed Generation) and Independent Energy Consumers connected to the system. This work proposes the utilization of a loss allocation method in distribution systems where open access is allowed, in which cross-subsidies, that appear due to the influence the generators have over the system losses, are minimized. Thus, guaranteeing to some extent the efficiency and transparency of the economic signals of the market. Results obtained through the Zbus loss allocation method adapted for distribution networks are processed in such a way that the corresponding allocation to the generation buses is divided among the consumer buses, while still considering consumers spatial characteristics. © 2007 IEEE.

Prediction of Oncogenic Interactions and Cancer-Related Signaling Networks Based on Network Topology

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

The SUCEST-FUN regulatory network database: Designing an energy grass

Modern sugarcane cultivars are complex hybrids resulting from crosses among several Saccharum species. Traditional breeding methods have been employed extensively in different countries over the past decades to develop varieties with increased sucrose yield and resistance to pests and diseases. Conventional variety improvement, however, may be limited by the narrow pool of suitable genes. Thus, molecular genetics is seen as a promising tool to assist in the process of developing improved varieties. The SUCEST-FUN Project (http://sucest-fun.org) aims to associate function with sugarcane genes using a variety of tools, in particular those that enable the study of the sugarcane transcriptome. An extensive analysis has been conducted to characterise, phenotypically, sugarcane genotypes with regard to their sucrose content, biomass and drought responses. Through the analysis of different cultivars, genes associated with sucrose content, yield, lignin and drought have been identified. Currently, tools are being developed to determine signalling and regulatory networks in grasses, and to sequence the sugarcane genome, as well as to identify sugarcane promoters. This is being implemented through the SUCEST-FUN (http://sucest-fun.org) and GRASSIUS databases (http://grassius.org), the cloning of sugarcane promoters, the identification of cis-regulatory elements (CRE) using Chromatin Immunoprecipitation-sequencing (ChIP-Seq) and the generation of a comprehensive Signal Transduction and Transcription gene catalogue (SUCAST Catalogue).

Constraint-based analysis of gene interactions using restricted boolean networks and time-series data

Abstract Background A popular model for gene regulatory networks is the Boolean network model. In this paper, we propose an algorithm to perform an analysis of gene regulatory interactions using the Boolean network model and time-series data. Actually, the Boolean network is restricted in the sense that only a subset of all possible Boolean functions are considered. We explore some mathematical properties of the restricted Boolean networks in order to avoid the full search approach. The problem is modeled as a Constraint Satisfaction Problem (CSP) and CSP techniques are used to solve it. Results We applied the proposed algorithm in two data sets. First, we used an artificial dataset obtained from a model for the budding yeast cell cycle. The second data set is derived from experiments performed using HeLa cells. The results show that some interactions can be fully or, at least, partially determined under the Boolean model considered. Conclusions The algorithm proposed can be used as a first step for detection of gene/protein interactions. It is able to infer gene relationships from time-series data of gene expression, and this inference process can be aided by a priori knowledge available.

Preimplantation development regulatory pathway construction through a text-mining approach

Background: The integration of sequencing and gene interaction data and subsequent generation of pathways and networks contained in databases such as KEGG Pathway is essential for the comprehension of complex biological processes. We noticed the absence of a chart or pathway describing the well-studied preimplantation development stages; furthermore, not all genes involved in the process have entries in KEGG Orthology, important information for knowledge application with relation to other organisms. Results: In this work we sought to develop the regulatory pathway for the preimplantation development stage using text-mining tools such as Medline Ranker and PESCADOR to reveal biointeractions among the genes involved in this process. The genes present in the resulting pathway were also used as seeds for software developed by our group called SeedServer to create clusters of homologous genes. These homologues allowed the determination of the last common ancestor for each gene and revealed that the preimplantation development pathway consists of a conserved ancient core of genes with the addition of modern elements. Conclusions: The generation of regulatory pathways through text-mining tools allows the integration of data generated by several studies for a more complete visualization of complex biological processes. Using the genes in this pathway as “seeds” for the generation of clusters of homologues, the pathway can be visualized for other organisms. The clustering of homologous genes together with determination of the ancestry leads to a better understanding of the evolution of such process.

Modularity and evolutionary constraints in a baculovirus gene regulatory network

Abstract Background The structure of regulatory networks remains an open question in our understanding of complex biological systems. Interactions during complete viral life cycles present unique opportunities to understand how host-parasite network take shape and behave. The Anticarsia gemmatalis multiple nucleopolyhedrovirus (AgMNPV) is a large double-stranded DNA virus, whose genome may encode for 152 open reading frames (ORFs). Here we present the analysis of the ordered cascade of the AgMNPV gene expression. Results We observed an earlier onset of the expression than previously reported for other baculoviruses, especially for genes involved in DNA replication. Most ORFs were expressed at higher levels in a more permissive host cell line. Genes with more than one copy in the genome had distinct expression profiles, which could indicate the acquisition of new functionalities. The transcription gene regulatory network (GRN) for 149 ORFs had a modular topology comprising five communities of highly interconnected nodes that separated key genes that are functionally related on different communities, possibly maximizing redundancy and GRN robustness by compartmentalization of important functions. Core conserved functions showed expression synchronicity, distinct GRN features and significantly less genetic diversity, consistent with evolutionary constraints imposed in key elements of biological systems. This reduced genetic diversity also had a positive correlation with the importance of the gene in our estimated GRN, supporting a relationship between phylogenetic data of baculovirus genes and network features inferred from expression data. We also observed that gene arrangement in overlapping transcripts was conserved among related baculoviruses, suggesting a principle of genome organization. Conclusions Albeit with a reduced number of nodes (149), the AgMNPV GRN had a topology and key characteristics similar to those observed in complex cellular organisms, which indicates that modularity may be a general feature of biological gene regulatory networks.

RNA Interference and cyclooxygenase-2 (COX-2) regulation in colon cancer cells

Despite new methods and combined strategies, conventional cancer chemotherapy still lacks specificity and induces drug resistance. Gene therapy can offer the potential to obtain the success in the clinical treatment of cancer and this can be achieved by replacing mutated tumour suppressor genes, inhibiting gene transcription, introducing new genes encoding for therapeutic products, or specifically silencing any given target gene. Concerning gene silencing, attention has recently shifted onto the RNA interference (RNAi) phenomenon. Gene silencing mediated by RNAi machinery is based on short RNA molecules, small interfering RNAs (siRNAs) and microRNAs (miRNAs), that are fully o partially homologous to the mRNA of the genes being silenced, respectively. On one hand, synthetic siRNAs appear as an important research tool to understand the function of a gene and the prospect of using siRNAs as potent and specific inhibitors of any target gene provides a new therapeutical approach for many untreatable diseases, particularly cancer. On the other hand, the discovery of the gene regulatory pathways mediated by miRNAs, offered to the research community new important perspectives for the comprehension of the physiological and, above all, the pathological mechanisms underlying the gene regulation. Indeed, changes in miRNAs expression have been identified in several types of neoplasia and it has also been proposed that the overexpression of genes in cancer cells may be due to the disruption of a control network in which relevant miRNA are implicated. For these reasons, I focused my research on a possible link between RNAi and the enzyme cyclooxygenase-2 (COX-2) in the field of colorectal cancer (CRC), since it has been established that the transition adenoma-adenocarcinoma and the progression of CRC depend on aberrant constitutive expression of COX-2 gene. In fact, overexpressed COX-2 is involved in the block of apoptosis, the stimulation of tumor-angiogenesis and promotes cell invasion, tumour growth and metastatization. On the basis of data reported in the literature, the first aim of my research was to develop an innovative and effective tool, based on the RNAi mechanism, able to silence strongly and specifically COX-2 expression in human colorectal cancer cell lines. In this study, I firstly show that an siRNA sequence directed against COX-2 mRNA (siCOX-2), potently downregulated COX-2 gene expression in human umbilical vein endothelial cells (HUVEC) and inhibited PMA-induced angiogenesis in vitro in a specific, non-toxic manner. Moreover, I found that the insertion of a specific cassette carrying anti-COX-2 shRNA sequence (shCOX-2, the precursor of siCOX-2 previously tested) into a viral vector (pSUPER.retro) greatly increased silencing potency in a colon cancer cell line (HT-29) without activating any interferon response. Phenotypically, COX-2 deficient HT-29 cells showed a significant impairment of their in vitro malignant behaviour. Thus, results reported here indicate an easy-to-use, powerful and high selective virus-based method to knockdown COX-2 gene in a stable and long-lasting manner, in colon cancer cells. Furthermore, they open up the possibility of an in vivo application of this anti-COX-2 retroviral vector, as therapeutic agent for human cancers overexpressing COX-2. In order to improve the tumour selectivity, pSUPER.retro vector was modified for the shCOX-2 expression cassette. The aim was to obtain a strong, specific transcription of shCOX-2 followed by COX-2 silencing mediated by siCOX-2 only in cancer cells. For this reason, H1 promoter in basic pSUPER.retro vector [pS(H1)] was substituted with the human Cox-2 promoter [pS(COX2)] and with a promoter containing repeated copies of the TCF binding element (TBE) [pS(TBE)]. These promoters were choosen because they are partculary activated in colon cancer cells. COX-2 was effectively silenced in HT-29 and HCA-7 colon cancer cells by using enhanced pS(COX2) and pS(TBE) vectors. In particular, an higher siCOX-2 production followed by a stronger inhibition of Cox-2 gene were achieved by using pS(TBE) vector, that represents not only the most effective, but also the most specific system to downregulate COX-2 in colon cancer cells. Because of the many limits that a retroviral therapy could have in a possible in vivo treatment of CRC, the next goal was to render the enhanced RNAi-mediate COX-2 silencing more suitable for this kind of application. Xiang and et al. (2006) demonstrated that it is possible to induce RNAi in mammalian cells after infection with engineered E. Coli strains expressing Inv and HlyA genes, which encode for two bacterial factors needed for successful transfer of shRNA in mammalian cells. This system, called “trans-kingdom” RNAi (tkRNAi) could represent an optimal approach for the treatment of colorectal cancer, since E. Coli in normally resident in human intestinal flora and could easily vehicled to the tumor tissue. For this reason, I tested the improved COX-2 silencing mediated by pS(COX2) and pS(TBE) vectors by using tkRNAi system. Results obtained in HT-29 and HCA-7 cell lines were in high agreement with data previously collected after the transfection of pS(COX2) and pS(TBE) vectors in the same cell lines. These findings suggest that tkRNAi system for COX-2 silencing, in particular mediated by pS(TBE) vector, could represent a promising tool for the treatment of colorectal cancer. Flanking the studies addressed to the setting-up of a RNAi-mediated therapeutical strategy, I proposed to get ahead with the comprehension of new molecular basis of human colorectal cancer. In particular, it is known that components of the miRNA/RNAi pathway may be altered during the progressive development of colorectal cancer (CRC), and it has been already demonstrated that some miRNAs work as tumor suppressors or oncomiRs in colon cancer. Thus, my hypothesis was that overexpressed COX-2 protein in colon cancer could be the result of decreased levels of one or more tumor suppressor miRNAs. In this thesis, I clearly show an inverse correlation between COX-2 expression and the human miR- 101(1) levels in colon cancer cell lines, tissues and metastases. I also demonstrate that the in vitro modulating of miR-101(1) expression in colon cancer cell lines leads to significant variations in COX-2 expression, and this phenomenon is based on a direct interaction between miR-101(1) and COX-2 mRNA. Moreover, I started to investigate miR-101(1) regulation in the hypoxic environment since adaptation to hypoxia is critical for tumor cell growth and survival and it is known that COX-2 can be induced directly by hypoxia-inducible factor 1 (HIF-1). Surprisingly, I observed that COX-2 overexpression induced by hypoxia is always coupled to a significant decrease of miR-101(1) levels in colon cancer cell lines, suggesting that miR-101(1) regulation could be involved in the adaption of cancer cells to the hypoxic environment that strongly characterize CRC tissues.

Identification and characterization of the sRNA network in Neisseria meningitidis

Bacterial small regulatory RNAs (sRNAs) are posttranscriptional regulators involved in stress responses. These short non-coding transcripts are synthesised in response to a signal, and control gene expression of their regulons by modulating the translation or stability of the target mRNAs, often in concert with the RNA chaperone Hfq. Characterization of a Hfq knock out mutant in Neisseria meningitidis revealed that it has a pleiotropic phenotype, suggesting a major role for Hfq in adaptation to stresses and virulence and the presence of Hfq-dependent sRNA activity. Global gene expression analysis of regulated transcripts in the Hfq mutant revealed the presence of a regulated sRNA, incorrectly annotated as an open reading frame, which we renamed AniS. The synthesis of this novel sRNA is anaerobically induced through activation of its promoter by the FNR global regulator and through global gene expression analyses we identified at least two predicted mRNA targets of AniS. We also performed a detailed molecular analysis of the action of the sRNA NrrF,. We demonstrated that NrrF regulates succinate dehydrogenase by forming a duplex with a region of complementarity within the sdhDA region of the succinate dehydrogenase transcript, and Hfq enhances the binding of this sRNA to the identified target in the sdhCDAB mRNA; this is likely to result in rapid turnover of the transcript in vivo. In addition, in order to globally investigate other possible sRNAs of N. meningitdis we Deep-sequenced the transcriptome of this bacterium under both standard in vitro and iron-depleted conditions. This analysis revealed genes that were actively transcribed under the two conditions. We focused our attention on the transcribed non-coding regions of the genome and, along with 5’ and 3’ untranslated regions, 19 novel candidate sRNAs were identified. Further studies will be focused on the identification of the regulatory networks of these sRNAs, and their targets.

Ribosome Biogenesis and cell cycle regulation: Effect of RNA Polymerase III inhibition

In cycling cells positive stimuli like nutrient, growth factors and mitogens increase ribosome biogenesis rate and protein synthesis to ensure both growth and proliferation. In contrast, under stress situation, proliferating cells negatively modulate ribosome production to reduce protein synthesis and block cell cycle progression. The main strategy used by cycling cell to coordinate cell proliferation and ribosome biogenesis is to share regulatory elements, which participate directly in ribosome production and in cell cycle regulation. In fact, there is evidence that stimulation or inhibition of cell proliferation exerts direct effect on activity of the RNA polymerases controlling the ribosome biogenesis, while several alterations in normal ribosome biogenesis cause changes of the expression and the activity of the tumor suppressor p53, the main effector of cell cycle progression inhibition. The available data on the cross-talk between ribosome biogenesis and cell proliferation have been until now obtained in experimental model in which changes in ribosome biogenesis were obtained either by reducing the activity of the RNA polymerase I or by down-regulating the expression of the ribosomal proteins. The molecular pathways involved in the relationship between the effect of the inhibition of RNA polymerase III (Pol III) activity and cell cycle progression have been not yet investigated. In eukaryotes, RNA Polymerase III is responsible for transcription of factors involved both in ribosome assembly (5S rRNA) and rRNA processing (RNAse P and MRP).Thus, the aim of this study is characterize the effects of the down-regulation of RNA Polymerase III activity, or the specific depletion of 5S rRNA. The results that will be obtained might lead to a deeper understanding of the molecular pathway that controls the coordination between ribosome biogenesis and cell cycle, and might give useful information about the possibility to target RNA Polymerase III for cancer treatment.

Charakterisierung einer pflanzlichen Variante des Cytoskelettproteins gamma-Tubulin durch Strukturmodellierung, Überexpression und Analyse der Interaktionspartner

Wie alle Eukaryoten besitzen auch höhere Pflanzen ein mikrotubuläres Cytoskelett. Einige Funktionen dieses Cytoskeletts sind relativ stark konserviert, andere dagegen scheinen sehr pflanzenspezifisch zu sein. Dies betrifft insbesondere charakteristische mikrotubuläre Netzwerke, die bei der Neubildung und der Verstärkung der Zellwände wichtige Rollen übernehmen. Wie der Aufbau dieser Netzwerke kontrolliert wird, ist bisher relativ unklar. Typische Mikrotubuli organisierende Zentren (MTOC), insbesondere Centrosomen oder Spindelpolkörper, sind bei höheren Pflanzen nicht beobachtet worden. Von pilzlichen und tierischen Organismen weiß man, dass gamma-Tubulin (gTUB) mit seinen assoziierten Proteinen in den MTOC bei der Nukleation von Mikrotubuli eine Schlüsselfunktion hat. Dieses Mitglied der Tubulin-Superfamilie wird aber auch in Pflanzen gefunden, dessen genaue Funktion bisher unbekannt ist. Zu Beginn der Arbeit wurden mittels in silico Berechnungen Strukturmodelle des pflanzlichen gTUBs aus Nicotiana tabacum erarbeitet, da die Struktur, die zu einem Verständnis der pflanzlichen Wachstumsregulation beitragen könnte, bisher unbekannt ist. Auf Grundlage der bioinformatischen Daten konnte für weitere Studien eine notwendige gTUB-Deletionsmutante entwickelt werden. Für Röntgendiffraktionsstudien und gTUB-Interaktionspartneranalysen war die Verfügbarkeit verhältnismäßig großer Proteinmengen notwendig. Die Expression der gTUB-Volllängensequenz in gelöster und aktiver Form stellte einen immanent wichtigen Zwischenschritt dar. Das Escherichia coli T7/lacO-Expressionssystem lieferte, trotz vielversprechender Erfolge in der Vergangenheit, kein gelöstes rekombinantes gTUB. So wurden zwar verhältnismäßig hohe Expressionsraten erzielt, aber das rekombinante gTUB lag quantitativ als Inclusion bodies vor. Eine Variationen der Expressionsparameter sowie umfangreiche Versuche mittels verschiedenster Konstrukte sowie potentiell die Löslichkeit erhöhenden Tags gTUB in gelöster Form in E. coli zu exprimieren blieben erfolglos. Eine Denaturierung der Inclusion bodies und Rückfaltung wurde aufgrund der wohl bei der Tubulinfaltung notwendigen komplexeren Chaperone sowie thermodynamischer Überlegungen ausgeschlossen. Die höher evolvierte Chaperonausstattung war ein Hauptgrund für die Verwendung der eukaryotischen Hefe-Expressionssysteme K. lactis und des S. cerevisiae-Stammes FGY217 zur gTUB-Expression. So konnten nach der Selektion nur transgene Hefe-Zellen dokumentiert werden, die die gTUB-Expressionskassette nachweislich an der vorgesehenen Zielposition in ihrem Genom integrierten, aber keine dokumentierbare Expression zeigten. Die wahrscheinlichste Begründung hierfür ist, dass ein erhöhter intrazellulärer gTUB-Titer mit dem Zellwachstum und der Zellteilung dieser eukaryotischen Organismen interferierte und durch Rückkopplungen die rekombinante gTUB-CDS aus N. tabacum ausgeschaltet wurde. Der Versuch einer transienten gTUB-Überexpression in differenzierten Blattgeweben höherer Pflanzen war eine logische Konsequenz aus den vorherigen Ergebnissen und lieferte, wenn auch nicht die für eine Proteinkristallisation notwendigen Mengen, gelöstes gTUB. Bestrebungen einer stabilen Transfektion von A. thaliana oder BY-2-Zellkulturen mit einer gTUB-CDS lieferten keine transgenen Organismen, was starke Interferenzen der rekombinanten gTUB-CDS in den Zellen vermuten lies. Transfektionsversuche mit nur GFP tragenden Konstrukten ergaben hingegen eine hohe Anzahl an transgenen Organismen, die auch verhältnismäßig starke Expressionsraten zeigten. Die erzielten Proteinmengen bei der transienten gTUB-Überexpression in N. benthamiana Blattgeweben, in Co-Expression mit dem Posttransriptional Gene Silencing-Suppressorprotein p19, waren für einen Pull-Down sowie eine massenspektroskopische Analyse der Interaktionspartner ausreichend und ergaben Befunde. Eine abschließende Auswertung des erarbeiteten massenspektroskopischen Datensatzes wird jedoch erst dann möglich sein, wenn das Tabak-Proteom vollständig sequenziert ist. Die Erweiterung der bestehenden pflanzlichen Vergleichsdatenbanken um das bisher bekannte Tabak-Proteom vervielfachte die Anzahl der in dieser Studie identifizierten gTUB-Interaktionspartner. Interaktionen mit dem TCP1-Chaperon untermauern die Hypothese der zur Faltung pflanzlichen gTUBs notwendigen Chaperone. Beobachtete gTUB-Degradationsmuster in Verbindung mit Interaktionen des 26S-Proteasoms deuten auf eine Gegenregulationen bei erhöhtem gTUB-Titer auf Proteinebene hin. Da Blattgewebe selbst nur noch über eine sehr geringe und inhomogene Teilungsaktivität verfügen ist diese Regulation hoch spannend. Auch konnte durch Co-Expression des PTGS-Suppressorproteins p19 gezeigt werden, dass bei der gTUB-Expression eine Regulation auf RNA-Ebene erfolgt.

Automatic Design of Boolean Networks for Modelling Differentiation Trees

Real living cell is a complex system governed by many process which are not yet fully understood: the process of cell differentiation is one of these. In this thesis work we make use of a cell differentiation model to develop gene regulatory networks (Boolean networks) with desired differentiation dynamics. To accomplish this task we have introduced techniques of automatic design and we have performed experiments using various differentiation trees. The results obtained have shown that the developed algorithms, except the Random algorithm, are able to generate Boolean networks with interesting differentiation dynamics. Moreover, we have presented some possible future applications and developments of the cell differentiation model in robotics and in medical research. Understanding the mechanisms involved in biological cells can gives us the possibility to explain some not yet understood dangerous disease, i.e the cancer. Le cellula è un sistema complesso governato da molti processi ancora non pienamente compresi: il differenziamento cellulare è uno di questi. In questa tesi utilizziamo un modello di differenziamento cellulare per sviluppare reti di regolazione genica (reti Booleane) con dinamiche di differenziamento desiderate. Per svolgere questo compito abbiamo introdotto tecniche di progettazione automatica e abbiamo eseguito esperimenti utilizzando vari alberi di differenziamento. I risultati ottenuti hanno mostrato che gli algoritmi sviluppati, eccetto l'algoritmo Random, sono in grado di poter generare reti Booleane con dinamiche di differenziamento interessanti. Inoltre, abbiamo presentato alcune possibili applicazioni e sviluppi futuri del modello di differenziamento in robotica e nella ricerca medica. Capire i meccanismi alla base del funzionamento cellulare può fornirci la possibilità di spiegare patologie ancora oggi non comprese, come il cancro.

RNA interference in mammalian cell systems

In the last decade, few areas of biology have been transformed as thoroughly as RNA molecular biology. Without any doubt, one of the most significant advances has been the discovery of small (20-30 nucleotide) noncoding RNAs that regulate genes and genomes. The effects of small RNAs on gene expression and control are generally inhibitory, and the corresponding regulatory mechanisms are therefore collectively subsumed under the heading of RNA silencing and/or RNA interference. Two primary categories of these small RNAs - short interfering RNAs (siRNAs) and microRNAs (miRNAs) - act in both somatic and germline lineages of eukaryotic species to regulate endogenous genes and to defend the genome from invasive nucleic acids. Recent advances have revealed unexpected diversity in their biogenesis pathways and the regulatory mechanisms that they access. Our understanding of siRNA and miRNA-based regulation has direct implications for fundamental biology as well as disease aetiology and treatment as it is discussed in this review on 'new techniques in molecular biology'.

Alba-domain proteins of Trypanosoma brucei are cytoplasmic RNA-binding proteins that interact with the translation machinery

Trypanosoma brucei and related pathogens transcribe most genes as polycistronic arrays that are subsequently processed into monocistronic mRNAs. Expression is frequently regulated post-transcriptionally by cis-acting elements in the untranslated regions (UTRs). GPEET and EP procyclins are the major surface proteins of procyclic (insect midgut) forms of T. brucei. Three regulatory elements common to the 3' UTRs of both mRNAs regulate mRNA turnover and translation. The glycerol-responsive element (GRE) is unique to the GPEET 3' UTR and regulates its expression independently from EP. A synthetic RNA encompassing the GRE showed robust sequence-specific interactions with cytoplasmic proteins in electromobility shift assays. This, combined with column chromatography, led to the identification of 3 Alba-domain proteins. RNAi against Alba3 caused a growth phenotype and reduced the levels of Alba1 and Alba2 proteins, indicative of interactions between family members. Tandem-affinity purification and co-immunoprecipitation verified these interactions and also identified Alba4 in sub-stoichiometric amounts. Alba proteins are cytoplasmic and are recruited to starvation granules together with poly(A) RNA. Concomitant depletion of all four Alba proteins by RNAi specifically reduced translation of a reporter transcript flanked by the GPEET 3' UTR. Pulldown of tagged Alba proteins confirmed interactions with poly(A) binding proteins, ribosomal protein P0 and, in the case of Alba3, the cap-binding protein eIF4E4. In addition, Alba2 and Alba3 partially cosediment with polyribosomes in sucrose gradients. Alba-domain proteins seem to have exhibited great functional plasticity in the course of evolution. First identified as DNA-binding proteins in Archaea, then in association with nuclear RNase MRP/P in yeast and mammalian cells, they were recently described as components of a translationally silent complex containing stage-regulated mRNAs in Plasmodium. Our results are also consistent with stage-specific regulation of translation in trypanosomes, but most likely in the context of initiation.

Generation and analysis of a mouse intestinal metatranscriptome through Illumina based RNA-sequencing

With the advent of high through-put sequencing (HTS), the emerging science of metagenomics is transforming our understanding of the relationships of microbial communities with their environments. While metagenomics aims to catalogue the genes present in a sample through assessing which genes are actively expressed, metatranscriptomics can provide a mechanistic understanding of community inter-relationships. To achieve these goals, several challenges need to be addressed from sample preparation to sequence processing, statistical analysis and functional annotation. Here we use an inbred non-obese diabetic (NOD) mouse model in which germ-free animals were colonized with a defined mixture of eight commensal bacteria, to explore methods of RNA extraction and to develop a pipeline for the generation and analysis of metatranscriptomic data. Applying the Illumina HTS platform, we sequenced 12 NOD cecal samples prepared using multiple RNA-extraction protocols. The absence of a complete set of reference genomes necessitated a peptide-based search strategy. Up to 16% of sequence reads could be matched to a known bacterial gene. Phylogenetic analysis of the mapped ORFs revealed a distribution consistent with ribosomal RNA, the majority from Bacteroides or Clostridium species. To place these HTS data within a systems context, we mapped the relative abundance of corresponding Escherichia coli homologs onto metabolic and protein-protein interaction networks. These maps identified bacterial processes with components that were well-represented in the datasets. In summary this study highlights the potential of exploiting the economy of HTS platforms for metatranscriptomics.