Development and evaluation of a loop-mediated isothermal amplification (LAMP) assay for rapid detection of Actinobacillus pleuropneumoniae based the dsbE-like gene

This paper reports on the development and validation of a loop-mediated isothermal amplification assay (LAMP) for the rapid and specific detection of Actinobacillus pleuropneumoniae (A. pleuropneumoniae). A set of six primers were designed derived from the dsbE-like gene of A.pleuropneumoniae and validate the assay using 9 A. pleuropneumoniae reference/field strains, 132 clinical isolates and 9 other pathogens. The results indicated that positive reactions were confirmed for all A. pleuropneumoniae strains and specimens by LAMP at 63ºC for 60 min and no cross-reactivity were observed from other non-A.pleuropneumoniae including Haemophilus parasuis, Escherichia coli, Pasteurella multocida, Bordetella bronchiseptica, Streptococcus suis, Salmonella enterica, Staphylococcus, porcine reproductive and respiratory syndrome virus (PRRSV), and Pseudorabies virus. The detection limit of the conventional PCR was 10² CFU per PCR test tube, while that of the LAMP was 5 copies per tube. Therefore, the sensitivity of LAMP was higher than that of PCR. Moreover, the LAMP assay provided a rapid yet simple test of A. pleuropneumoniae suitable for laboratory diagnosis and pen-side detection due to ease of operation and the requirement of only a regular water bath or heat block for the reaction.

Chromosomal evolution and comparative gene mapping in the Drosophila repleta species group

A review of our recent work on the cromosomal evolution of the Drosophila repleta species group is presented. Most studies have focused on the buzzatii species complex, a monophyletic set of 12 species which inhabit the deserts of South America and the West Indies. A statistical analysis of the length and breakpoint distribution of the 86 paracentric inversions observed in this complex has shown that inversion length is a selected trait. Rare inversions are usually small while evolutionary successful inversions, fixed and polymorphic, are predominantly of medium size. There is also a negative correlation between length and number of inversions per species. Finally, the distribution of inversion breakpoints along chromosome 2 is non-random, with chromosomal regions which accumulate up to 8 breakpoints (putative "hot spots"). Comparative gene mapping has also been used to investigate the molecular organization and evolution of chromosomes. Using in situ hybridization, 26 genes have been precisely located on the salivary gland chromosomes of D. repleta and D. buzzatii; another nine have been tentatively identified. The results are fully consistent with the currently accepted chromosomal homologies between D. repleta and D. melanogaster, and no evidence for reciprocal translocations or pericentric inversions has been found. The comparison of the gene map of D. repleta chromosome 2 with that of the homologous chromosome 3R of D. melanogaster shows an extensive reorganization via paracentric inversions and allows to estimate an evolution rate of ~1 inversion fixed per million years for this chromosome

The GATO gene annotation tool for research laboratories

Large-scale genome projects have generated a rapidly increasing number of DNA sequences. Therefore, development of computational methods to rapidly analyze these sequences is essential for progress in genomic research. Here we present an automatic annotation system for preliminary analysis of DNA sequences. The gene annotation tool (GATO) is a Bioinformatics pipeline designed to facilitate routine functional annotation and easy access to annotated genes. It was designed in view of the frequent need of genomic researchers to access data pertaining to a common set of genes. In the GATO system, annotation is generated by querying some of the Web-accessible resources and the information is stored in a local database, which keeps a record of all previous annotation results. GATO may be accessed from everywhere through the internet or may be run locally if a large number of sequences are going to be annotated. It is implemented in PHP and Perl and may be run on any suitable Web server. Usually, installation and application of annotation systems require experience and are time consuming, but GATO is simple and practical, allowing anyone with basic skills in informatics to access it without any special training. GATO can be downloaded at [http://mariwork.iq.usp.br/gato/]. Minimum computer free space required is 2 MB.

Differential gene expression profiles of hepatocellular carcinomas associated or not with viral infection

Chronic hepatitis B (HBV) and C (HCV) virus infections are the most important factors associated with hepatocellular carcinoma (HCC), but tumor prognosis remains poor due to the lack of diagnostic biomarkers. In order to identify novel diagnostic markers and therapeutic targets, the gene expression profile associated with viral and non-viral HCC was assessed in 9 tumor samples by oligo-microarrays. The differentially expressed genes were examined using a z-score and KEGG pathway for the search of ontological biological processes. We selected a non-redundant set of 15 genes with the lowest P value for clustering samples into three groups using the non-supervised algorithm k-means. Fisher’s linear discriminant analysis was then applied in an exhaustive search of trios of genes that could be used to build classifiers for class distinction. Different transcriptional levels of genes were identified in HCC of different etiologies and from different HCC samples. When comparing HBV-HCC vs HCV-HCC, HBV-HCC/HCV-HCC vs non-viral (NV)-HCC, HBC-HCC vs NV-HCC, and HCV-HCC vs NV-HCC of the 58 non-redundant differentially expressed genes, only 6 genes (IKBKβ, CREBBP, WNT10B, PRDX6, ITGAV, and IFNAR1) were found to be associated with hepatic carcinogenesis. By combining trios, classifiers could be generated, which correctly classified 100% of the samples. This expression profiling may provide a useful tool for research into the pathophysiology of HCC. A detailed understanding of how these distinct genes are involved in molecular pathways is of fundamental importance to the development of effective HCC chemoprevention and treatment.

Gene trio signatures as molecular markers to predict response to doxorubicin cyclophosphamide neoadjuvant chemotherapy in breast cancerpatients

In breast cancer patients submitted to neoadjuvant chemotherapy (4 cycles of doxorubicin and cyclophosphamide, AC), expression of groups of three genes (gene trio signatures) could distinguish responsive from non-responsive tumors, as demonstrated by cDNA microarray profiling in a previous study by our group. In the current study, we determined if the expression of the same genes would retain the predictive strength, when analyzed by a more accessible technique (real-time RT-PCR). We evaluated 28 samples already analyzed by cDNA microarray, as a technical validation procedure, and 14 tumors, as an independent biological validation set. All patients received neoadjuvant chemotherapy (4 AC). Among five trio combinations previously identified, defined by nine genes individually investigated (BZRP, CLPTM1,MTSS1, NOTCH1, NUP210, PRSS11, RPL37A, SMYD2, and XLHSRF-1), the most accurate were established by RPL37A, XLHSRF-1based trios, with NOTCH1 or NUP210. Both trios correctly separated 86% of tumors (87% sensitivity and 80% specificity for predicting response), according to their response to chemotherapy (82% in a leave-one-out cross-validation method). Using the pre-established features obtained by linear discriminant analysis, 71% samples from the biological validation set were also correctly classified by both trios (72% sensitivity; 66% specificity). Furthermore, we explored other gene combinations to achieve a higher accuracy in the technical validation group (as a training set). A new trio, MTSS1, RPL37 and SMYD2, correctly classified 93% of samples from the technical validation group (95% sensitivity and 80% specificity; 86% accuracy by the cross-validation method) and 79% from the biological validation group (72% sensitivity and 100% specificity). Therefore, the combined expression of MTSS1, RPL37 and SMYD2, as evaluated by real-time RT-PCR, is a potential candidate to predict response to neoadjuvant doxorubicin and cyclophosphamide in breast cancer patients.

Transcriptional regulation of bidirectional gene pairs by 17-β-estradiol in MCF-7 breast cancer cells

Using cDNA microarray analysis, we previously identified a set of differentially expressed genes in primary breast tumors based on the status of estrogen and progesterone receptors. In the present study, we performed an integrated computer-assisted and manual search of potential estrogen response element (ERE) binding sites in the promoter region of these genes to characterize their potential to be regulated by estrogen receptors (ER). Publicly available databases were used to annotate the position of these genes in the genome and to extract a 5’flanking region 2 kb upstream to 2 kb downstream of the transcription start site for transcription binding site analysis. The search for EREs and other binding sites was performed using several publicly available programs. Overall, approximately 40% of the genes analyzed were potentially able to be regulated by estrogen via ER. In addition, 17% of these genes are located very close to other genes organized in a head-to-head orientation with less than 1.0 kb between their transcript units, sharing a bidirectional promoter, and could be classified as bidirectional gene pairs. Using quantitative real-time PCR, we further investigated the effects of 17β-estradiol and antiestrogens on the expression of the bidirectional gene pairs in MCF-7 breast cancer cells. Our results showed that some of these gene pairs, such as TXNDC9/EIF5B, GALNS/TRAPPC2L, and SERINC1/PKIB, are modulated by 17β-estradiol via ER in MCF-7 breast cancer cells. Here, we also characterize the promoter region of potential ER-regulated genes and provide new information on the transcriptional regulation of bidirectional gene pairs.

Gene expression profiling analysis of lung adenocarcinoma

The present study screened potential genes related to lung adenocarcinoma, with the aim of further understanding disease pathogenesis. The GSE2514 dataset including 20 lung adenocarcinoma and 19 adjacent normal tissue samples from 10 patients with lung adenocarcinoma aged 45-73 years was downloaded from Gene Expression Omnibus. Differentially expressed genes (DEGs) between the two groups were screened using the t-test. Potential gene functions were predicted using functional and pathway enrichment analysis, and protein-protein interaction (PPI) networks obtained from the STRING database were constructed with Cytoscape. Module analysis of PPI networks was performed through MCODE in Cytoscape. In total, 535 upregulated and 465 downregulated DEGs were identified. These included ATP5D, UQCRC2, UQCR11 and genes encoding nicotinamide adenine dinucleotide (NADH), which are mainly associated with mitochondrial ATP synthesis coupled electron transport, and which were enriched in the oxidative phosphorylation pathway. Other DEGs were associated with DNA replication (PRIM1, MCM3, and RNASEH2A), cell surface receptor-linked signal transduction and the enzyme-linked receptor protein signaling pathway (MAPK1, STAT3, RAF1, and JAK1), and regulation of the cytoskeleton and phosphatidylinositol signaling system (PIP5K1B, PIP5K1C, and PIP4K2B). Our findings suggest that DEGs encoding subunits of NADH, PRIM1, MCM3, MAPK1, STAT3, RAF1, and JAK1 might be associated with the development of lung adenocarcinoma.

Characterisation of Cladonia rangiferina transcriptome and genome, and the effects of dehydration and rehydration on its gene expression

Lichens are symbiotic organisms, which consist of the fungal partner and the photosynthetic partner, which can be either an alga or a cyanobacterium. In some lichen species the symbiosis is tripartite, where the relationship includes both an alga and a cyanobacterium alongside the primary symbiont, fungus. The lichen symbiosis is an evolutionarily old adaptation to life on land and many extant fungal species have evolved from lichenised ancestors. Lichens inhabit a wide range of habitats and are capable of living in harsh environments and on nutrient poor substrates, such as bare rocks, often enduring frequent cycles of drying and wetting. Most lichen species are desiccation tolerant, and they can survive long periods of dehydration, but can rapidly resume photosynthesis upon rehydration. The molecular mechanisms behind lichen desiccation tolerance are still largely uncharacterised and little information is available for any lichen species at the genomic or transcriptomic level. The emergence of the high-throughput next generation sequencing (NGS) technologies and the subsequent decrease in the cost of sequencing new genomes and transcriptomes has enabled non-model organism research on the whole genome level. In this doctoral work the transcriptome and genome of the grey reindeer lichen, Cladonia rangiferina, were sequenced, de novo assembled and characterised using NGS and traditional expressed sequence tag (EST) technologies. RNA extraction methods were optimised to improve the yield and quality of RNA extracted from lichen tissue. The effects of rehydration and desiccation on C. rangiferina gene expression on whole transcriptome level were studied and the most differentially expressed genes were identified. The secondary metabolites present in C. rangiferina decreased the quality – integrity, optical characteristics and utility for sensitive molecular biological applications – of the extracted RNA requiring an optimised RNA extraction method for isolating sufficient quantities of high-quality RNA from lichen tissue in a time- and cost-efficient manner. The de novo assembly of the transcriptome of C. rangiferina was used to produce a set of contiguous unigene sequences that were used to investigate the biological functions and pathways active in a hydrated lichen thallus. The de novo assembly of the genome yielded an assembly containing mostly genes derived from the fungal partner. The assembly was of sufficient quality, in size similar to other lichen-forming fungal genomes and included most of the core eukaryotic genes. Differences in gene expression were detected in all studied stages of desiccation and rehydration, but the largest changes occurred during the early stages of rehydration. The most differentially expressed genes did not have any annotations, making them potentially lichen-specific genes, but several genes known to participate in environmental stress tolerance in other organisms were also identified as differentially expressed.

Evolutionary synthesis of stochastic gene network models using feature-based search spaces

A feature-based fitness function is applied in a genetic programming system to synthesize stochastic gene regulatory network models whose behaviour is defined by a time course of protein expression levels. Typically, when targeting time series data, the fitness function is based on a sum-of-errors involving the values of the fluctuating signal. While this approach is successful in many instances, its performance can deteriorate in the presence of noise. This thesis explores a fitness measure determined from a set of statistical features characterizing the time series' sequence of values, rather than the actual values themselves. Through a series of experiments involving symbolic regression with added noise and gene regulatory network models based on the stochastic 'if-calculus, it is shown to successfully target oscillating and non-oscillating signals. This practical and versatile fitness function offers an alternate approach, worthy of consideration for use in algorithms that evaluate noisy or stochastic behaviour.

Disease-Gene Association Using a Genetic Algorithm

Understanding the relationship between genetic diseases and the genes associated with them is an important problem regarding human health. The vast amount of data created from a large number of high-throughput experiments performed in the last few years has resulted in an unprecedented growth in computational methods to tackle the disease gene association problem. Nowadays, it is clear that a genetic disease is not a consequence of a defect in a single gene. Instead, the disease phenotype is a reflection of various genetic components interacting in a complex network. In fact, genetic diseases, like any other phenotype, occur as a result of various genes working in sync with each other in a single or several biological module(s). Using a genetic algorithm, our method tries to evolve communities containing the set of potential disease genes likely to be involved in a given genetic disease. Having a set of known disease genes, we first obtain a protein-protein interaction (PPI) network containing all the known disease genes. All the other genes inside the procured PPI network are then considered as candidate disease genes as they lie in the vicinity of the known disease genes in the network. Our method attempts to find communities of potential disease genes strongly working with one another and with the set of known disease genes. As a proof of concept, we tested our approach on 16 breast cancer genes and 15 Parkinson's Disease genes. We obtained comparable or better results than CIPHER, ENDEAVOUR and GPEC, three of the most reliable and frequently used disease-gene ranking frameworks.

Skeletal muscle protein content of lipolytic inhibitor G(0)/G(1) switch gene-2 protein: the effect of endurance training

The first and rate-limiting step of lipolysis is the removal of the first fatty acid from a triglyceride molecule; it is catalyzed by adipose triglyceride lipase (ATGL). ATGL is co-activated by comparative gene identification-58 (CGI-58) and inhibited by the G(0)/G(1) switch gene-2 protein (G0S2). G0S2 has also recently been identified as a positive regulator of oxidative phosphorylation within the mitochondria. Previous research has demonstrated in cell culture, a dose dependent mechanism for inhibition by G0S2 on ATGL. However our data is not consistent with this hypothesis. There was no change in G0S2 protein content during an acute lipolytic inducing set of contractions in both whole muscle, and isolated mitochondria yet both ATGL and G0S2 increase following endurance training, in spite of the fact that there should be increased reliance on intramuscular lipolysis. Therefore, inhibition of ATGL by G0S2 appears to be regulated through more complicated intracellular or post-translation regulation.

Probe-level linear model fitting and mixture modeling results in high accuracy detection of differential gene expression

Affiliation: Institut de recherche en immunologie et en cancérologie, Université de Montréal

Globin Gene Expression: Role of Transcription Factors

La dérégulation de l'expression génétique est une base pathophysiologique de plusieurs maladies. On a utilisé le locus du gène β-globine humain comme modèle pour élucider le mécanisme de régulation de la transcription génétique et évaluer son expression génétique durant l'érythropoïèse. La famille des protéines 'E' est composée de facteurs de transcription qui possèdent plusieurs sites de liaison au sein de locus du gène β-globine, suggérant leur rôle potentiel dans la régulation de l’expression de ces gènes. Nous avons montré que les facteurs HEB, E2A et ETO2 interagissent d’une manière significative avec la région contrôle du Locus (LCR) et avec les promoteurs des gènes de la famille β-globine. Le recrutement de ces facteurs au locus est modifié lors de l'érythropoïèse dans les cellules souches hematopoitiques et les cellules erythroides de souris transgéniques pour le locus de la β-globine humain, ainsi que dans les cellules progénitrices hématopoïétiques humaines. De plus par cette étude, nous démontrons pour la première fois que le gène β-globine humain est dans une chromatine active et qu’il interagit avec des facteurs de transcriptions de type suppresseurs dans les cellules progénitrices lymphoïdes (voie de différentiation alternative). Cette étude a aussi été faite dans des souris ayant une génétique mutante caractérisée par l'absence des facteurs de transcription E2A ou HEB.

The in vivo characterization of the DNA repair gene apn-1 in the model organism Caenorhabditis elegans

Les sites apuriniques/apyrimidinique (AP) représentent une forme de dommage à l’ADN hautement mutagène et ce type de dommage peut survenir spontanément ou être induit par une variété d’agents. Afin de préserver la stabilité génomique, deux familles d’endonucléases de type AP, endo-IV et exo-III, sont nécessaires pour contrecarrer les effets mutagènes des sites AP. Malgré l’identification de membres des deux familles dans plusieurs organismes unicellulaire tels que E.coli et S. cerevisiae, aucun membre de la famille endo-IV n’a été identifié chez les organismes multicellulaires à l’exception de C. elegans et de C. briggsae. Nous avons donc décidé d’investiguer l’importance biologique de APN-1 chez C. elegans par l’utilisation d’une approche de knockdown du gène. Dans notre étude, nous avons montré que le knockdown du gène apn-1 chez C. elegans, en utilisant des ARN d’interférence (ARNi), cause une accumulation de mutations spontanées et induites par des drogues résultant en un délai de l’éclosion des œufs ainsi que par une diminution de la survie et de la longévité des vers adultes. De plus, nous avons montré que cette accumulation de mutations mène à un délai dans la progression du cycle cellulaire durant l’embryogénèse, représentant possiblement une explication du délai dans l’éclosion des œufs. Nous avons montré qu’il y avait une augmentation du niveau de mutations dans la gorge des vers, sans toutefois pouvoir confirmer la distribution de APN-1 qui possède une étiquette GFP. Les animaux transgéniques APN-1-GFP n’exprimaient pas suffisamment de la protéine de fusion pour permettre une visualisation à l’aide d’un microscope à fluorescence, mais la protéine a été détectée par immunobuvardage de type western. Les animaux transgéniques APN-1-GFP étaient instables et avaient des phénotypes concordants avec les défauts génétiques. En conclusion, il semble que C. elegans aie évolué afin de retenir un niveau de base de APN-1 jouant ainsi un rôle versatile afin de maintenir l’intégrité génétique d’autant plus que cet organisme semble manquer plusieurs enzymes de la voie de réparation par excision de base.

Clustering algorithms and shape factor methods to discriminate among small GTPase phenotypes using DIC image analysis.

Naïvement perçu, le processus d’évolution est une succession d’événements de duplication et de mutations graduelles dans le génome qui mènent à des changements dans les fonctions et les interactions du protéome. La famille des hydrolases de guanosine triphosphate (GTPases) similaire à Ras constitue un bon modèle de travail afin de comprendre ce phénomène fondamental, car cette famille de protéines contient un nombre limité d’éléments qui diffèrent en fonctionnalité et en interactions. Globalement, nous désirons comprendre comment les mutations singulières au niveau des GTPases affectent la morphologie des cellules ainsi que leur degré d’impact sur les populations asynchrones. Mon travail de maîtrise vise à classifier de manière significative différents phénotypes de la levure Saccaromyces cerevisiae via l’analyse de plusieurs critères morphologiques de souches exprimant des GTPases mutées et natives. Notre approche à base de microscopie et d’analyses bioinformatique des images DIC (microscopie d’interférence différentielle de contraste) permet de distinguer les phénotypes propres aux cellules natives et aux mutants. L’emploi de cette méthode a permis une détection automatisée et une caractérisation des phénotypes mutants associés à la sur-expression de GTPases constitutivement actives. Les mutants de GTPases constitutivement actifs Cdc42 Q61L, Rho5 Q91H, Ras1 Q68L et Rsr1 G12V ont été analysés avec succès. En effet, l’implémentation de différents algorithmes de partitionnement, permet d’analyser des données qui combinent les mesures morphologiques de population native et mutantes. Nos résultats démontrent que l’algorithme Fuzzy C-Means performe un partitionnement efficace des cellules natives ou mutantes, où les différents types de cellules sont classifiés en fonction de plusieurs facteurs de formes cellulaires obtenus à partir des images DIC. Cette analyse démontre que les mutations Cdc42 Q61L, Rho5 Q91H, Ras1 Q68L et Rsr1 G12V induisent respectivement des phénotypes amorphe, allongé, rond et large qui sont représentés par des vecteurs de facteurs de forme distincts. Ces distinctions sont observées avec différentes proportions (morphologie mutante / morphologie native) dans les populations de mutants. Le développement de nouvelles méthodes automatisées d’analyse morphologique des cellules natives et mutantes s’avère extrêmement utile pour l’étude de la famille des GTPases ainsi que des résidus spécifiques qui dictent leurs fonctions et réseau d’interaction. Nous pouvons maintenant envisager de produire des mutants de GTPases qui inversent leur fonction en ciblant des résidus divergents. La substitution fonctionnelle est ensuite détectée au niveau morphologique grâce à notre nouvelle stratégie quantitative. Ce type d’analyse peut également être transposé à d’autres familles de protéines et contribuer de manière significative au domaine de la biologie évolutive.