Assessing the gain of biological data integration in gene networks inference

Background: A current challenge in gene annotation is to define the gene function in the context of the network of relationships instead of using single genes. The inference of gene networks (GNs) has emerged as an approach to better understand the biology of the system and to study how several components of this network interact with each other and keep their functions stable. However, in general there is no sufficient data to accurately recover the GNs from their expression levels leading to the curse of dimensionality, in which the number of variables is higher than samples. One way to mitigate this problem is to integrate biological data instead of using only the expression profiles in the inference process. Nowadays, the use of several biological information in inference methods had a significant increase in order to better recover the connections between genes and reduce the false positives. What makes this strategy so interesting is the possibility of confirming the known connections through the included biological data, and the possibility of discovering new relationships between genes when observed the expression data. Although several works in data integration have increased the performance of the network inference methods, the real contribution of adding each type of biological information in the obtained improvement is not clear. Methods: We propose a methodology to include biological information into an inference algorithm in order to assess its prediction gain by using biological information and expression profile together. We also evaluated and compared the gain of adding four types of biological information: (a) protein-protein interaction, (b) Rosetta stone fusion proteins, (c) KEGG and (d) KEGG+GO. Results and conclusions: This work presents a first comparison of the gain in the use of prior biological information in the inference of GNs by considering the eukaryote (P. falciparum) organism. Our results indicates that information based on direct interaction can produce a higher improvement in the gain than data about a less specific relationship as GO or KEGG. Also, as expected, the results show that the use of biological information is a very important approach for the improvement of the inference. We also compared the gain in the inference of the global network and only the hubs. The results indicates that the use of biological information can improve the identification of the most connected proteins.

Evaluation of the acquired immune responses to Plasmodium vivax VIR variant antigens in individuals living in malaria-endemic areas of Brazil

Abstract Background The naturally-acquired immune response to Plasmodium vivax variant antigens (VIR) was evaluated in individuals exposed to malaria and living in different endemic areas for malaria in the north of Brazil. Methods Seven recombinant proteins representing four vir subfamilies (A, B, C, and E) obtained from a single patient from the Amazon Region were expressed in Escherichia coli as soluble glutathione S-transferase fusion proteins. The different recombinant proteins were compared by ELISA with regard to the recognition by IgM, IgG, and IgG subclass of antibodies from 200 individuals with patent infection. Results The frequency of individuals that presented antibodies anti-VIR (IgM plus IgG) during the infection was 49%. The frequencies of individuals that presented IgM or IgG antibodies anti-VIR were 29.6% or 26.0%, respectively. The prevalence of IgG antibodies against recombinant VIR proteins was significantly lower than the prevalence of antibodies against the recombinant proteins representing two surface antigens of merozoites of P. vivax: AMA-1 and MSP119 (57.0% and 90.5%, respectively). The cellular immune response to VIR antigens was evaluated by in vitro proliferative assays in mononuclear cells of the individuals recently exposed to P. vivax. No significant proliferative response to these antigens was observed when comparing malaria-exposed to non-exposed individuals. Conclusion This study provides evidence that there is a low frequency of individuals responding to each VIR antigens in endemic areas of Brazil. This fact may explain the host susceptibility to new episodes of the disease.

Associations among genotype, clinical phenotype, and intracellular localization of trafficking proteins in ARC syndrome

Arthrogryposisrenal dysfunctioncholestasis (ARC) syndrome is a rare autosomal recessive multisystem disorder caused by mutations in vacuolar protein sorting 33 homologue B (VPS33B) and VPS33B interacting protein, apicalbasolateral polarity regulator (VIPAR). Cardinal features of ARC include congenital joint contractures, renal tubular dysfunction, cholestasis, severe failure to thrive, ichthyosis, and a defect in platelet alpha-granule biogenesis. Most patients with ARC do not survive past the first year of life. We report two patients presenting with a mild ARC phenotype, now 5.5 and 3.5 years old. Both patients were compound heterozygotes with the novel VPS33B donor splice-site mutation c.1225+5G>C in common. Immunoblotting and complementary DNA analysis suggest expression of a shorter VPS33B transcript, and cell-based assays show that c.1225+5G>C VPS33B mutant retains some ability to interact with VIPAR (and thus partial wild-type function). This study provides the first evidence of genotypephenotype correlation in ARC and suggests that VPS33B c.1225+5G>C mutation predicts a mild ARC phenotype. We have established an interactive online database for ARC (https://grenada.lumc.nl/LOVD2/ARC) comprising all known variants in VPS33B and VIPAR. Also included in the database are 15 novel pathogenic variants in VPS33B and five in VIPAR. Hum Mutat 33:16561664, 2012. (c) 2012 Wiley Periodicals, Inc.

Development of a recombinant fusion protein based on the dynein light chain LC8 for non-viral gene delivery

The low efficiency of gene transfer is a recurrent problem in DNA vaccine development and gene therapy studies using non-viral vectors such as plasmid DNA (pDNA). This is mainly due to the fact that during their traffic to the target cell's nuclei, plasmid vectors must overcome a series of physical, enzymatic and diffusional barriers. The main objective of this work is the development of recombinant proteins specifically designed for pDNA delivery, which take advantage of molecular motors like dynein, for the transport of cargos from the periphery to the centrosome of mammalian cells. A DNA binding sequence was fused to the N-terminus of the recombinant human dynein light chain LC8. Expression studies indicated that the fusion protein was correctly expressed in soluble form using E. coli BL21(DE3) strain. As expected, gel permeation assays found the purified protein mainly present as dimers, the functional oligomeric state of LC8. Gel retardation assays and atomic force microscopy proved the ability of the fusion protein to interact and condense pDNA. Zeta potential measurements indicated that LC8 with DNA binding domain (LD4) has an enhanced capacity to interact and condense pDNA, generating positively charged complexes. Transfection of cultured HeLa cells confirmed the ability of the LD4 to facilitate pDNA uptake and indicate the involvement of the retrograde transport in the intracellular trafficking of pDNA: LD4 complexes. Finally, cytotoxicity studies demonstrated a very low toxicity of the fusion protein vector, indicating the potential for in vivo applications. The study presented here is part of an effort to develop new modular shuttle proteins able to take advantage of strategies used by viruses to infect mammalian cells, aiming to provide new tools for gene therapy and DNA vaccination studies. (C) 2012 Elsevier B.V. All rights reserved.