Perspectives in the control of infectious diseases by transgenic mosquitoes in the post-genomic era: a review

Arthropod-borne diseases caused by a variety of microorganisms such as dengue virus and malaria parasites afflict billions of people worldwide imposing major economic and social burdens. Despite many efforts, vaccines against diseases transmitted by mosquitoes, with the exception of yellow fever, are not available. Control of such infectious pathogens is mainly performed by vector management and treatment of affected individuals with drugs. However, the numbers of insecticide-resistant insects and drug-resistant parasites are increasing. Therefore, inspired in recent years by a lot of new data produced by genomics and post-genomics research, several scientific groups have been working on different strategies to control infectious arthropod-borne diseases. This review focuses on recent advances and perspectives towards construction of transgenic mosquitoes refractory to malaria parasites and dengue virus transmission.

Genomic organization, fine-mapping, and expression of the human islet-brain 1 (IB1)/c-Jun-amino-terminal kinase interacting protein-1 (JIP-1) gene.

Islet-brain 1 (IB1), a regulator of the pancreatic beta-cell function in the rat, is homologous to JIP-1, a murine inhibitor of c-Jun amino-terminal kinase (JNK). Whether IB1 and JIP-1 are present in humans was not known. We report the sequence of the 2133-bp human IB1 cDNA, the expression, structure, and fine-mapping of the human IB1 gene, and the characterization of an IB1 pseudogene. Human IB1 is 94% identical to rat IB1. The tissue-specific expression of IB1 in human is similar to that observed in rodent. The IB1 gene contains 12 exons and maps to chromosome 11 (11p11.2-p12), a region that is deleted in DEFECT-11 syndrome. Apart from an IB1 pseudogene on chromosome 17 (17q21), no additional IB1-related gene was found in the human genome. Our data indicate that the sequence and expression pattern of IB1 are highly conserved between rodent and human and provide the necessary tools to investigate whether IB1 is involved in human diseases.

Local WMR navigation with monocular data

This article presents recent WMR (wheeled mobile robot) navigation experiences using local perception knowledge provided by monocular and odometer systems. A local narrow perception horizon is used to plan safety trajectories towards the objective. Therefore, monocular data are proposed as a way to obtain real time local information by building two dimensional occupancy grids through a time integration of the frames. The path planning is accomplished by using attraction potential fields, while the trajectory tracking is performed by using model predictive control techniques. The results are faced to indoor situations by using the lab available platform consisting in a differential driven mobile robot

Genomic and proteomic approaches towards an understanding of sleep.

The basic functions of sleep are still unclear, however, recent advances in genomics and proteomics have begun to contribute to our understanding of both normal and pathological sleep. In this review, we focus primarily on normal sleep and wake that have been studied in model organisms such as mice. Mice have been especially valuable since many different inbred strains exist that differ in sleep-related traits, and genes can be altered by either mutagenesis or targeted approaches. Advances in QTL (Quantitative Trait Loci) analysis have also helped to identify important sleep related genes, and several other QTLs have been mapped as a first step toward finding the genes that underlie basic sleep traits. In addition to more traditional genetic approaches, the abundance of different mRNAs across sleep and wake can now be studied and compared in different brain regions much more thoroughly using microarray methods. Progress at the protein level has been more difficult, but a few studies have begun to investigate changes in proteins during sleep and wake, and we present some of our own preliminary data in this area. A knowledge of which genes and proteins control or respond to changes in sleep will not only help answer fundamental questions, but may also suggest novel drug targets for improving multiple aspects of sleep and wake.

Retroviral Integration Site Selection

The stable insertion of a copy of their genome into the host cell genome is an essential step of the life cycle of retroviruses. The site of viral DNA integration, mediated by the viral-encoded integrase enzyme, has important consequences for both the virus and the host cell. The analysis of retroviral integration site distribution was facilitated by the availability of the human genome sequence, revealing the non-random feature of integration site selection and identifying different favored and disfavored genomic locations for individual retroviruses. This review will summarize the current knowledge about retroviral differences in their integration site preferences as well as the mechanisms involved in this process.

Genomic acute myeloid leukemia-associated inv(16)(p13q22) breakpoints are tightly clustered.

The inv(16) and related t(16;16) are found in 10% of all cases with de novo acute myeloid leukemia. In these rearrangements the core binding factor beta (CBFB) gene on 16q22 is fused to the smooth muscle myosin heavy chain gene (MYH11) on 16p13. To gain insight into the mechanisms causing the inv(16) we have analysed 24 genomic CBFB-MYH11 breakpoints. All breakpoints in CBFB are located in a 15-Kb intron. More than 50% of the sequenced 6.2 Kb of this intron consists of human repetitive elements. Twenty-one of the 24 breakpoints in MYH11 are located in a 370-bp intron. The remaining three breakpoints in MYH11 are located more upstream. The localization of three breakpoints adjacent to a V(D)J recombinase signal sequence in MYH11 suggests a V(D)J recombinase-mediated rearrangement in these cases. V(D)J recombinase-associated characteristics (small nucleotide deletions and insertions of random nucleotides) were detected in six other cases. CBFB and MYH11 duplications were detected in four of six cases tested.

Bayesian Markov chain Monte Carlo inversion of geophysical data for the purpose of estimating the hydraulic properties of the unsaturated zone

Ground-penetrating radar (GPR) has the potential to provide valuable information on hydrological properties of the vadose zone because of their strong sensitivity to soil water content. In particular, recent evidence has suggested that the stochastic inversion of crosshole GPR data within a coupled geophysical-hydrological framework may allow for effective estimation of subsurface van-Genuchten-Mualem (VGM) parameters and their corresponding uncertainties. An important and still unresolved issue, however, is how to best integrate GPR data into a stochastic inversion in order to estimate the VGM parameters and their uncertainties, thus improving hydrological predictions. Recognizing the importance of this issue, the aim of the research presented in this thesis was to first introduce a fully Bayesian inversion called Markov-chain-Monte-carlo (MCMC) strategy to perform the stochastic inversion of steady-state GPR data to estimate the VGM parameters and their uncertainties. Within this study, the choice of the prior parameter probability distributions from which potential model configurations are drawn and tested against observed data was also investigated. Analysis of both synthetic and field data collected at the Eggborough (UK) site indicates that the geophysical data alone contain valuable information regarding the VGM parameters. However, significantly better results are obtained when these data are combined with a realistic, informative prior. A subsequent study explore in detail the dynamic infiltration case, specifically to what extent time-lapse ZOP GPR data, collected during a forced infiltration experiment at the Arrenaes field site (Denmark), can help to quantify VGM parameters and their uncertainties using the MCMC inversion strategy. The findings indicate that the stochastic inversion of time-lapse GPR data does indeed allow for a substantial refinement in the inferred posterior VGM parameter distributions. In turn, this significantly improves knowledge of the hydraulic properties, which are required to predict hydraulic behaviour. Finally, another aspect that needed to be addressed involved the comparison of time-lapse GPR data collected under different infiltration conditions (i.e., natural loading and forced infiltration conditions) to estimate the VGM parameters using the MCMC inversion strategy. The results show that for the synthetic example, considering data collected during a forced infiltration test helps to better refine soil hydraulic properties compared to data collected under natural infiltration conditions. When investigating data collected at the Arrenaes field site, further complications arised due to model error and showed the importance of also including a rigorous analysis of the propagation of model error with time and depth when considering time-lapse data. Although the efforts in this thesis were focused on GPR data, the corresponding findings are likely to have general applicability to other types of geophysical data and field environments. Moreover, the obtained results allow to have confidence for future developments in integration of geophysical data with stochastic inversions to improve the characterization of the unsaturated zone but also reveal important issues linked with stochastic inversions, namely model errors, that should definitely be addressed in future research.

Can we continue to neglect genomic variation in introgression rates when inferring the history of speciation? A case study in a Mytilus hybrid zone.

The use of molecular data to reconstruct the history of divergence and gene flow between populations of closely related taxa represents a challenging problem. It has been proposed that the long-standing debate about the geography of speciation can be resolved by comparing the likelihoods of a model of isolation with migration and a model of secondary contact. However, data are commonly only fit to a model of isolation with migration and rarely tested against the secondary contact alternative. Furthermore, most demographic inference methods have neglected variation in introgression rates and assume that the gene flow parameter (Nm) is similar among loci. Here, we show that neglecting this source of variation can give misleading results. We analysed DNA sequences sampled from populations of the marine mussels, Mytilus edulis and M. galloprovincialis, across a well-studied mosaic hybrid zone in Europe and evaluated various scenarios of speciation, with or without variation in introgression rates, using an Approximate Bayesian Computation (ABC) approach. Models with heterogeneous gene flow across loci always outperformed models assuming equal migration rates irrespective of the history of gene flow being considered. By incorporating this heterogeneity, the best-supported scenario was a long period of allopatric isolation during the first three-quarters of the time since divergence followed by secondary contact and introgression during the last quarter. By contrast, constraining migration to be homogeneous failed to discriminate among any of the different models of gene flow tested. Our simulations thus provide statistical support for the secondary contact scenario in the European Mytilus hybrid zone that the standard coalescent approach failed to confirm. Our results demonstrate that genomic variation in introgression rates can have profound impacts on the biological conclusions drawn from inference methods and needs to be incorporated in future studies.

Conditional and syllogistic deductive tasks dissociate functionally during premise integration.

Deduction allows us to draw consequences from previous knowledge. Deductive reasoning can be applied to several types of problem, for example, conditional, syllogistic, and relational. It has been assumed that the same cognitive operations underlie solutions to them all; however, this hypothesis remains to be tested empirically. We used event-related fMRI, in the same group of subjects, to compare reasoning-related activity associated with conditional and syllogistic deductive problems. Furthermore, we assessed reasoning-related activity for the two main stages of deduction, namely encoding of premises and their integration. Encoding syllogistic premises for reasoning was associated with activation of BA 44/45 more than encoding them for literal recall. During integration, left fronto-lateral cortex (BA 44/45, 6) and basal ganglia activated with both conditional and syllogistic reasoning. Besides that, integration of syllogistic problems additionally was associated with activation of left parietal (BA 7) and left ventro-lateral frontal cortex (BA 47). This difference suggests a dissociation between conditional and syllogistic reasoning at the integration stage. Our finding indicates that the integration of conditional and syllogistic reasoning is carried out by means of different, but partly overlapping, sets of anatomical regions and by inference, cognitive processes. The involvement of BA 44/45 during both encoding (syllogisms) and premise integration (syllogisms and conditionals) suggests a central role in deductive reasoning for syntactic manipulations and formal/linguistic representations.

Genomic organization and gene expression in a chromosomal region of Leishmania major.

Little is known about the relation between the genome organization and gene expression in Leishmania. Bioinformatic analysis can be used to predict genes and find homologies with known proteins. A model was proposed, in which genes are organized into large clusters and transcribed from only one strand, in the form of large polycistronic primary transcripts. To verify the validity of this model, we studied gene expression at the transcriptional, post-transcriptional and translational levels in a unique locus of 34kb located on chr27 and represented by cosmid L979. Sequence analysis revealed 115 ORFs on either DNA strand. Using computer programs developed for Leishmania genes, only nine of these ORFs, localized on the same strand, were predicted to code for proteins, some of which show homologies with known proteins. Additionally, one pseudogene, was identified. We verified the biological relevance of these predictions. mRNAs from nine predicted genes and proteins from seven were detected. Nuclear run-on analyses confirmed that the top strand is transcribed by RNA polymerase II and suggested that there is no polymerase entry site. Low levels of transcription were detected in regions of the bottom strand and stable transcripts were identified for four ORFs on this strand not predicted to be protein-coding. In conclusion, the transcriptional organization of the Leishmania genome is complex, raising the possibility that computer predictions may not be comprehensive.

A genomic analysis identifies a novel component in the genetic structure of sub-Saharan African populations

Studies of large sets of SNP data have proven to be a powerful tool in the analysis of the genetic structure of human populations. In this work, we analyze genotyping data for 2,841 SNPs in 12 Sub-Saharan African populations, including a previously unsampled region of south-eastern Africa (Mozambique). We show that robust results in a world-wide perspective can be obtained when analyzing only 1,000 SNPs. Our main results both confirm the results of previous studies, and show new and interesting features in Sub-Saharan African genetic complexity. There is a strong differentiation of Nilo-Saharans, much beyond what would be expected by geography. Hunter-gatherer populations (Khoisan and Pygmies) show a clear distinctiveness with very intrinsic Pygmy (and not only Khoisan) genetic features. Populations of the West Africa present an unexpected similarity among them, possibly the result of a population expansion. Finally, we find a strong differentiation of the south-eastern Bantu population from Mozambique, which suggests an assimilation of a pre-Bantu substrate by Bantu speakers in the region.

From SNPs to pathways: integration of functional effect of sequence variations on models of cell signalling pathways

Background: Single nucleotide polymorphisms (SNPs) are the most frequent type of sequence variation between individuals, and represent a promising tool for finding genetic determinants of complex diseases and understanding the differences in drug response. In this regard, it is of particular interest to study the effect of non-synonymous SNPs in the context of biological networks such as cell signalling pathways. UniProt provides curated information about the functional and phenotypic effects of sequence variation, including SNPs, as well as on mutations of protein sequences. However, no strategy has been developed to integrate this information with biological networks, with the ultimate goal of studying the impact of the functional effect of SNPs in the structure and dynamics of biological networks. Results: First, we identified the different challenges posed by the integration of the phenotypic effect of sequence variants and mutations with biological networks. Second, we developed a strategy for the combination of data extracted from public resources, such as UniProt, NCBI dbSNP, Reactome and BioModels. We generated attribute files containing phenotypic and genotypic annotations to the nodes of biological networks, which can be imported into network visualization tools such as Cytoscape. These resources allow the mapping and visualization of mutations and natural variations of human proteins and their phenotypic effect on biological networks (e.g. signalling pathways, protein-protein interaction networks, dynamic models). Finally, an example on the use of the sequence variation data in the dynamics of a network model is presented. Conclusion: In this paper we present a general strategy for the integration of pathway and sequence variation data for visualization, analysis and modelling purposes, including the study of the functional impact of protein sequence variations on the dynamics of signalling pathways. This is of particular interest when the SNP or mutation is known to be associated to disease. We expect that this approach will help in the study of the functional impact of disease-associated SNPs on the behaviour of cell signalling pathways, which ultimately will lead to a better understanding of the mechanisms underlying complex diseases.

An integrated genomic and expression analysis of 7q deletion in splenic marginal zone lymphoma.

Splenic marginal zone lymphoma (SMZL) is an indolent B-cell lymphoproliferative disorder characterised by 7q32 deletion, but the target genes of this deletion remain unknown. In order to elucidate the genetic target of this deletion, we performed an integrative analysis of the genetic, epigenetic, transcriptomic and miRNomic data. High resolution array comparative genomic hybridization of 56 cases of SMZL delineated a minimally deleted region (2.8 Mb) at 7q32, but showed no evidence of any cryptic homozygous deletion or recurrent breakpoint in this region. Integrated transcriptomic analysis confirmed significant under-expression of a number of genes in this region in cases of SMZL with deletion, several of which showed hypermethylation. In addition, a cluster of 8 miRNA in this region showed under-expression in cases with the deletion, and three (miR-182/96/183) were also significantly under-expressed (P<0.05) in SMZL relative to other lymphomas. Genomic sequencing of these miRNA and IRF5, a strong candidate gene, did not show any evidence of somatic mutation in SMZL. These observations provide valuable guidance for further characterisation of 7q deletion.

MAR elements and transposons for improved transgene integration and expression.

Reliable and long-term expression of transgenes remain significant challenges for gene therapy and biotechnology applications, especially when antibiotic selection procedures are not applicable. In this context, transposons represent attractive gene transfer vectors because of their ability to promote efficient genomic integration in a variety of mammalian cell types. However, expression from genome-integrating vectors may be inhibited by variable gene transcription and/or silencing events. In this study, we assessed whether inclusion of two epigenetic control elements, the human Matrix Attachment Region (MAR) 1-68 and X-29, in a piggyBac transposon vector, may lead to more reliable and efficient expression in CHO cells. We found that addition of the MAR 1-68 at the center of the transposon did not interfere with transposition frequency, and transgene expressing cells could be readily detected from the total cell population without antibiotic selection. Inclusion of the MAR led to higher transgene expression per integrated copy, and reliable expression could be obtained from as few as 2-4 genomic copies of the MAR-containing transposon vector. The MAR X-29-containing transposons was found to mediate elevated expression of therapeutic proteins in polyclonal or monoclonal CHO cell populations using a transposable vector devoid of selection gene. Overall, we conclude that MAR and transposable vectors can be used to improve transgene expression from few genomic transposition events, which may be useful when expression from a low number of integrated transgene copies must be obtained and/or when antibiotic selection cannot be applied.

Methods for integration site distribution analyses in animal cell genomes.

The question of where retroviral DNA becomes integrated in chromosomes is important for understanding (i) the mechanisms of viral growth, (ii) devising new anti-retroviral therapy, (iii) understanding how genomes evolve, and (iv) developing safer methods for gene therapy. With the completion of genome sequences for many organisms, it has become possible to study integration targeting by cloning and sequencing large numbers of host-virus DNA junctions, then mapping the host DNA segments back onto the genomic sequence. This allows statistical analysis of the distribution of integration sites relative to the myriad types of genomic features that are also being mapped onto the sequence scaffold. Here we present methods for recovering and analyzing integration site sequences.