Non-segmented negative sense RNA viruses as vectors for vaccine development

This article intends to cover two aspects of non-segmented negative sense RNA viruses. In the initial section, the strategy employed by these viruses to replicate their genomes is discussed. This would help in understanding the later section in which the use of these viruses as vaccine vectors has been discussed. For the description of the replication strategy which encompasses virus genome transcription and genome replication carried out by the same RNA dependent RNA polymerase complex, a member of the prototype rhabdovirus family - Chandipura virus has been chosen as an example to illustrate the complex nature of the two processes and their regulation. In the discussion on these viruses serving as vectors for carrying vaccine antigen genes, emphasis has been laid on describing the progress made in using the attenuated viruses as vectors and a description of the systems in which the efficiency of immune responses has been tested.

COMMON-Sense net:Improved water management for resource-poor farmers via sensor networks

We describe the on-going design and implementation of a sensor network for agricultural management targeted at resource-poor farmers in India. Our focus on semi-arid regions led us to concentrate on water-related issues. Throughout 2004, we carried out a survey on the information needs of the population living in a cluster of villages in our study area. The results highlighted the potential that environment-related information has for the improvement of farming strategies in the face of highly variable conditions, in particular for risk management strategies (choice of crop varieties, sowing and harvest periods, prevention of pests and diseases, efficient use of irrigation water etc.). This leads us to advocate an original use of Information and Communication Technologies (ICT). We believe our demand-driven approach for the design of appropriate ICT tools that are targeted at the resource-poor to be relatively new. In order to go beyond a pure technocratic approach, we adopted an iterative, participatory methodology.

A course for teaching design research methodology

Design research informs and supports practice by developing knowledge to improve the chances of producing successful products.Training in design research has been poorly supported. Design research uses human and natural/technical sciences, embracing all facets of design; its methods and tools are adapted from both these traditions. However, design researchers are rarely trained in methods from both the traditions. Research in traditional sciences focuses primarily on understanding phenomena related to human, natural, or technical systems. Design research focuses on supporting improvement of such systems, using understanding as a necessary but not sufficient step, and it must embrace methods for both understanding reality and developing support for its improvement. A one-semester, postgraduate-level, credited course that has been offered since 2002, entitled Methodology for Design Research, is described that teaches a methodology for carrying out research into design. Its steps are to clarify research success; to understand relevant phenomena of design and how these influence success; to use this to envision design improvement and develop proposals for supporting improvement; to evaluate support for its influence on success; and, if unacceptable, to modify, support, or improve the understanding of success and its links to the phenomena of design. This paper highlights some major issues about the status of design research and describes how design research methodology addresses these. The teaching material, model of delivery, and evaluation of the course on methodology for design research are discussed.

NETGEM: Network Embedded Temporal GEnerative Model for gene expression data

Background: Temporal analysis of gene expression data has been limited to identifying genes whose expression varies with time and/or correlation between genes that have similar temporal profiles. Often, the methods do not consider the underlying network constraints that connect the genes. It is becoming increasingly evident that interactions change substantially with time. Thus far, there is no systematic method to relate the temporal changes in gene expression to the dynamics of interactions between them. Information on interaction dynamics would open up possibilities for discovering new mechanisms of regulation by providing valuable insight into identifying time-sensitive interactions as well as permit studies on the effect of a genetic perturbation. Results: We present NETGEM, a tractable model rooted in Markov dynamics, for analyzing the dynamics of the interactions between proteins based on the dynamics of the expression changes of the genes that encode them. The model treats the interaction strengths as random variables which are modulated by suitable priors. This approach is necessitated by the extremely small sample size of the datasets, relative to the number of interactions. The model is amenable to a linear time algorithm for efficient inference. Using temporal gene expression data, NETGEM was successful in identifying (i) temporal interactions and determining their strength, (ii) functional categories of the actively interacting partners and (iii) dynamics of interactions in perturbed networks. Conclusions: NETGEM represents an optimal trade-off between model complexity and data requirement. It was able to deduce actively interacting genes and functional categories from temporal gene expression data. It permits inference by incorporating the information available in perturbed networks. Given that the inputs to NETGEM are only the network and the temporal variation of the nodes, this algorithm promises to have widespread applications, beyond biological systems. The source code for NETGEM is available from https://github.com/vjethava/NETGEM

Computationally Efficient Sub-optimal Mid Course Guidance Using Model Predictive Static Programming (MPSP)

For a homing interceptor, suitable initial condition must be achieved by mid course guidance scheme for its maximum effectiveness. To achieve desired end goal of any mid course guidance scheme, two point boundary value problem must be solved online with all realistic constrain. A Newly developed computationally efficient technique named as MPSP (Model Predictive Static Programming) is utilized in this paper for obtaining suboptimal solution of optimal mid course guidance. Time to go uncertainty is avoided in this formulation by making use of desired position where midcourse guidance terminate and terminal guidance takes over. A suitable approach angle towards desired point also can be specified in this guidance law formulation. This feature makes this law particularly attractive because warhead effectiveness issue can be indirectly solved in mid course phase.

Acidic pH induced STM1485 gene is essential for intracellular replication of Salmonella

During the course of infection, Salmonella has to face several potentially lethal environmental conditions, one such being acidic pH. The ability to sense and respond to the acidic pH is crucial for the survival and replication of Salmonella. The physiological role of one gene (STM1485) involved in this response, which is upregulated inside the host cells (by 90- to 113-fold) is functionally characterized in Salmonella pathogenesis. In vitro, the DSTM1485 neither exhibited any growth defect at pH 4.5 nor any difference in the acid tolerance response. The DSTM1485 was compromised in its capacity to proliferate inside the host cells and complementation with STM1485 gene restored its virulence. We further demonstrate that the surface translocation of Salmonella pathogenicity island-2 (SPI-2) encoded translocon proteins, SseB and SseD were reduced in the DSTM1485. The increase in co-localization of this mutant with lysosomes was also observed. In addition, the DSTM1485 displayed significantly reduced competitive indices (CI) in spleen, liver and mesenteric lymph nodes in murine typhoid model when infected by intra-gastric route. Based on these results, we conclude that the acidic pH induced STM1485 gene is essential for intracellular replication of Salmonella.

Diel variation in fig volatiles across syconium development: making sense of scents

Plants produce volatile organic compounds (VOCs) in a variety of contexts that include response to abiotic and biotic stresses, attraction of pollinators and parasitoids, and repulsion of herbivores. Some of these VOCs may also exhibit diel variation in emission. In Ficus racemosa, we examined variation in VOCs released by fig syconia throughout syconium development and between day and night. Syconia are globular enclosed inflorescences that serve as developing nurseries for pollinating and parasitic fig wasps. Syconia are attacked by gallers early in their development, serviced by pollinators in mid phase, and are attractive to parasitoids in response to the development of gallers at later stages. VOC bouquets of the different development phases of the syconium were distinctive, as were their day and night VOC profiles. VOCs such as alpha-muurolene were characteristic of the pollen-receptive diurnal phase, and may serve to attract the diurnally-active pollinating wasps. Diel patterns of release of volatiles could not be correlated with their predicted volatility as determined by Henry's law constants at ambient temperatures. Therefore, factors other than Henry's law constant such as stomatal conductance or VOC synthesis must explain diel variation in VOC emission. A novel use of weighted gene co-expression network analysis (WGCNA) on the volatilome resulted in seven distinct modules of co-emitted VOCs that could be interpreted on the basis of syconium ecology. Some modules were characterized by the response of fig syconia to early galling by parasitic wasps and consisted largely of green leaf volatiles (GLVs). Other modules, that could be characterized by a combination of syconia response to oviposition and tissue feeding by larvae of herbivorous galler pollinators as well as of parasitized wasps, consisted largely of putative herbivore-induced plant volatiles (HIPVs). We demonstrated the usefulness of WGCNA analysis of the volatilome in making sense of the scents produced by the syconia at different stages and diel phases of their development.

Generative Maximum Entropy Learning for Multiclass Classification

Maximum entropy approach to classification is very well studied in applied statistics and machine learning and almost all the methods that exists in literature are discriminative in nature. In this paper, we introduce a maximum entropy classification method with feature selection for large dimensional data such as text datasets that is generative in nature. To tackle the curse of dimensionality of large data sets, we employ conditional independence assumption (Naive Bayes) and we perform feature selection simultaneously, by enforcing a `maximum discrimination' between estimated class conditional densities. For two class problems, in the proposed method, we use Jeffreys (J) divergence to discriminate the class conditional densities. To extend our method to the multi-class case, we propose a completely new approach by considering a multi-distribution divergence: we replace Jeffreys divergence by Jensen-Shannon (JS) divergence to discriminate conditional densities of multiple classes. In order to reduce computational complexity, we employ a modified Jensen-Shannon divergence (JS(GM)), based on AM-GM inequality. We show that the resulting divergence is a natural generalization of Jeffreys divergence to a multiple distributions case. As far as the theoretical justifications are concerned we show that when one intends to select the best features in a generative maximum entropy approach, maximum discrimination using J-divergence emerges naturally in binary classification. Performance and comparative study of the proposed algorithms have been demonstrated on large dimensional text and gene expression datasets that show our methods scale up very well with large dimensional datasets.

In the Sense of Transcription Regulation by G-Quadruplexes: Asymmetric Effects in Sense and Antisense Strands

G-Quadruplexes occupy important regulatory regions in the genome. DNA G-quadruplexes in the promoter regions and RNA quadruplexes in the UTRs (untranslated regions) have been individually studied and variously implicated at different regulatory levels of gene expression. However, the formation of G-quadruplexes in the sense and antisense strands and their corresponding roles in gene regulation have not been studied in much detail. In the present study, we have elucidated the effect of strand asymmetry in this context. Using biophysical methods, we have demonstrated the formation of stable G-quadruplex structure in vitro using CD and UV melting. Additionally, ITC was employed to demonstrate that a previously reported selective G-quadruplex ligand was able to bind and stabilize the G-quadruplex in the present sequence. Further, we have shown using reporter constructs that although the DNA G-quadruplex in either strand can reduce translation efficiency, transcriptional regulation differs when G-quadruplex is present in the sense or antisense strand. We demonstrate that the G-quadruplex motif in the antisense strand substantially inhibits transcription, while when in the sense strand, it does not affect transcription, although it does ultimately reduce translation. Further, it is also shown that the G-quadruplex stabilizing ligand can enhance this asymmetric transcription regulation as a result of the increased stabilization of the G-quadruplex.

Demonstration of helicase activity in the nonstructural protein, NSs, of the negative-sense RNA virus, Groundnut bud necrosis virus

The nonstructural protein NSs, encoded by the S RNA of groundnut bud necrosis virus (GBNV) (genus Tospovirus, family Bunyaviridae) has earlier been shown to possess nucleic-acid-stimulated NTPase and 50 a phosphatase activity. ATP hydrolysis is an essential function of a true helicase. Therefore, NSs was tested for DNA helicase activity. The results demonstrated that GBNV NSs possesses bidirectional DNA helicase activity. An alanine mutation in the Walker A motif (K189A rNSs) decreased DNA helicase activity substantially, whereas a mutation in the Walker B motif resulted in a marginal decrease in this activity. The parallel loss of the helicase and ATPase activity in the K189A mutant confirms that NSs acts as a non-canonical DNA helicase. Furthermore, both the wild-type and K189A NSs could function as RNA silencing suppressors, demonstrating that the suppressor activity of NSs is independent of its helicase or ATPase activity. This is the first report of a true helicase from a negative-sense RNA virus.