A polymerase chain reaction method adapted for selective amplification and cloning of 3' sequences of potyviral genomes: application to dasheen mosaic virus

One-Step Reverse-Transcription Loop-Mediated Isothermal Amplification (RT-LAMP) Assay for the Detection of Canna Yellow Streak Virus

Canna yellow streak virus (CaYSV) is a potyvirus that causes severe damage to the ornamental plant canna in the United Kingdom and Brazil. Here, we identified CaYSV in China by isolating total RNA from an infected plant, amplifying the virus genome segments, and cloning and sequencing the amplicons. After assembly, the full-length genome of the virus was obtained and uploaded to the NCBI database. Phylogenetic analysis results showed that the Guizhou isolate (OL546222) was most closely related to the KS isolate (MG545919.1). Virus detection is essential for virus disease control but the subclinical infection of CaYSV on canna in its early development increases the difficulty of CaYSV diagnosis. The goal of this study was to develop an efficient method for detection of CaYSV. We designed the primers, optimized the reaction conditions, and finally established a one-step reverse-transcription loop-mediated isothermal amplification (RT-LAMP) method. The product of RT-LAMP can be analyzed by both agarose gel electrophoresis and visible color change. The established one-step RT-LAMP assay showed high specificity and sensitivity in detecting CaYSV. This RT-LAMP method was also applied in analysis of 61 field samples collected from Guizhou and Jiangsu Provinces. The results showed that the infection rates of CaYSV on canna samples from these two provinces were very high (63 and 96% respectively).

Network, degeneracy and bow tie. Integrating paradigms and architectures to grasp the complexity of the immune system

Recently, the network paradigm, an application of graph theory to biology, has proven to be a powerful approach to gaining insights into biological complexity, and has catalyzed the advancement of systems biology. In this perspective and focusing on the immune system, we propose here a more comprehensive view to go beyond the concept of network. We start from the concept of degeneracy, one of the most prominent characteristic of biological complexity, defined as the ability of structurally different elements to perform the same function, and we show that degeneracy is highly intertwined with another recently-proposed organizational principle, i.e. 'bow tie architecture'. The simultaneous consideration of concepts such as degeneracy, bow tie architecture and network results in a powerful new interpretative tool that takes into account the constructive role of noise (stochastic fluctuations) and is able to grasp the major characteristics of biological complexity, i.e. the capacity to turn an apparently chaotic and highly dynamic set of signals into functional information.

Investigative proteomics: identification of an unknown plant virus from infected plants using mass spectrometry

We describe the identification of a previously uncharacterized plant virus that is capable of infecting Nicotiana spp. and Arabidopsis thaliana. Protein extracts were first prepared from leaf tissue of uninfected tobacco plants, and the proteins were visualized with two-dimensional electrophoresis (2-DE). Matching gels were then run using protein extracts of a tobacco plant infected with tobacco mosaic virus (TMV). After visual comparison, the proteins spots that were differentially expressed in infected plant tissues were cut from the gels and analyzed by high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS). Tandem mass spectrometry data of individual peptides was searched with SEQUEST. Using this approach we demonstrated a successful proof-of-concept experiment by identifying TMV proteins present in the total protein extract. The same procedure was then applied to tobacco plants infected with a laboratory viral isolate of unknown identity. Several of the differentially expressed protein spots were identified as proteins of potato virus X (PVX), thus successfully identifying the causative agent of the uncharacterized viral infection. We believe this demonstrates that HPLC-MS/MS can be used to successfully characterize unknown viruses in infected plants.