Characterization of the gut microbes of greater wax moth (Galleria mellonella Linnaeus) shows presence of potential polymer degraders.

Greater wax moth (GWM), Galleria mellonella (Lepidoptera: Pyralidae), is a highly destructive honey bee pest prevalent throughout the world. It is considered as a major factor to the alarming decline in honey bee population. GWM destroys active honey combs as it feeds on the beeswax and lays eggs in bee hives, and the primary food of their larva is beeswax. Beeswax is a polymer composed mainly of saturated and unsaturated, linear and complex monoesters, and hydrocarbons. The most frequent bond in beeswax is ethene (CH2-CH2) which is also found in the common plastic polyethylene. As wax-digestion is not a common animal character, we hypothesized about a possible role of GWM gut microflora in the process; which could possibly degrade polyethylene-like polymers as well. This study was aimed to identify the GWM gut microflora via culture-dependant approach. We characterized several bacterial species based on the culture characteristics, Gram-reaction, and various biochemical tests. Sequencing of 16S-rDNA revealed nine bacterial and one microalgal species from GWM gut. The bacterial species included Gram-positive Exiguobacterium aestuarii, Bacillus circulans, Microbacterium zaea, Microbacterium sp. and Enterococcus faecalis; Gram-negative Agrobacterium sp., Sphingomonas pseudosanguinis, Sphingobium yanoikuyae and Acinetobacter radioresistens; the microalgae was Picochlorum oklahomensis. Some of them have been previously reported to degrade polycyclic aromatic hydrocarbon, low-density polyethylene, and 2-methylphenanthrene. Meanwhile, the microalga, P. oklahomensis, was reported to steal bacterial genes to adapt with abiotic stresses. Further investigation is necessary to explore the precise details about polymer degrading capabilities of these microbes; nevertheless, this study builds a foundation for elaborate and advanced future research.

Dissecting the Role of Promoters of Pathogen-sensitive Genes in Plant Defense.

Plants inherently show resistance to pathogen attack but are susceptible to multiple bacteria, viruses, fungi, and phytoplasmas. Diseases as a result of such infection leads to the deterioration of crop yield. Several pathogen-sensitive gene activities, promoters of such genes, associated transcription factors, and promoter elements responsible for crosstalk between the defense signaling pathways are involved in plant resistance towards a pathogen. Still, only a handful of genes and their promoters related to plant resistance have been identified to date. Such pathogen-sensitive promoters are accountable for elevating the transcriptional activity of certain genes in response to infection. Also, a suitable promoter is a key to devising successful crop improvement strategies as it ensures the optimum expression of the required transgene. The study of the promoters also helps in mining more details about the transcription factors controlling their activities and helps to unveil the involvement of new genes in the pathogen response. Therefore, the only way out to formulate new solutions is by analyzing the molecular aspects of these promoters in detail. In this review, we provided an overview of the promoter motifs and cis-regulatory elements having specific roles in pathogen attack response. To elaborate on the importance and get a vivid picture of the pathogen-sensitive promoter sequences, the key motifs and promoter elements were analyzed with the help of PlantCare and interpreted with available literature. This review intends to provide useful information for reconstructing the gene networks underlying the resistance of plants against pathogens.

Molecular characterization and sequence analyses of Banana bunchy top virus infecting banana cultivar Jahaji (Dwarf Cavendish) in Assam, India.

Several isolates of Banana bunchy top virus (BBTV) have been reported worldwide. They are members of either the Pacific Indian Ocean (PIO) or the South East Asian (SEA) group. However, there is only one completely sequenced isolate published from the northeastern part of India till date. Therefore, we obtained the complete sequences of all the six genomic components of a BBTV isolate from the northeastern Indian state of Assam. The isolate was named as BBTV-As-JOR, and its genome showed the presence of the reported conserved motifs. Nevertheless, like other Indian BBTV isolate, the major common regions in DNA-R and DNA-U3 of BBTV-As-JOR had deletions of 26 and 36 nucleotides, respectively. Phylogenetic analysis based on 312 sequences of BBTV DNA-R classified BBTV-As-JOR as a member of the PIO group; similar phylogenetic patterns were also found with the other genomic segments. Analysis with Recombination Detection Program revealed two intra-segment recombination events involving DNA-C of geographically distinct BBTV isolates. On the other hand, DNA-U3 and DNA-N were found to be involved in few inter-segment recombination events in BBTV-As-JOR. This is the first report of a BBTV isolate from Assam and also of another PIO isolate from the region (the other isolate, BBTV-Umiam, was much closer to the SEA group). The detected possible recombinants could emerge as a major future threat for the banana cultivations in the country considering the asexual nature of propagation of banana crop.

Revealing shared differential co-expression profiles in rice infected by virus from reoviridae and sequiviridae group.

Differential co-expression is a cutting-edge approach to analyze gene expression data and identify both shared and divergent expression patterns. The availability of high-throughput gene expression datasets and efficient computational approaches have unfolded the opportunity to a systems level understanding of functional genomics of different stresses with respect to plants. We performed the meta-analysis of the available microarray data for reoviridae and sequiviridae infection in rice with the aim to identify the shared gene co-expression profile. The microarray data were downloaded from ArrayExpress and analyzed through a modified Weighted Gene Co-expression Network Analysis (WGCNA) protocol. WGCNA clustered the genes based on the expression intensities across the samples followed by identification of modules, eigengenes, principal components, topology overlap, module membership and module preservation. The module preservation analysis identified 4 modules; salmon (638 genes), midnightblue (584 genes), lightcyan (686 genes) and red (562 genes), which are highly preserved in both the cases. The networks in case of reoviridae infection showed neatly packed clusters whereas, in sequiviridae, the clusters were loosely connected which is due to the differences in the correlation values. We also identified 83 common transcription factors targeting the hub genes from all the identified modules. This study provides a coherent view of the comparative aspect of the expression of common genes involved in different virus infections which may aid in the identification of novel targets and development of new intervention strategy against the virus.