Vacuolar and cytoskeletal dynamics during elicitor-induced programmed cell death in tobacco BY-2 cells

Responses of plant cells to environmental stresses often involve morphological changes, differentiation and redistribution of various organelles and cytoskeletal network. Tobacco BY-2 cells provide excellent model system for in vivo imaging of these intracellular events. Treatment of the cell cycle-synchronized BY-2 cells with a proteinaceous oomycete elicitor, cryptogein, induces highly synchronous programmed cell death (PCD) and provide a model system to characterize vacuolar and cytoskeletal dynamics during the PCD. Sequential observation revealed dynamic reorganization of the vacuole and actin microfilaments during the execution of the PCD. We further characterized the effects cryptogein on mitotic microtubule organization in cell cycle-synchronized cells. Cryptogein treatment at S phase inhibited formation of the preprophase band, a cortical microtubule band that predicts the cell division site. Cortical microtubules kept their random orientation till their disruption that gradually occurred during the execution of the PCD twelve hours after the cryptogein treatment. Possible molecular mechanisms and physiological roles of the dynamic behavior of the organelles and cytoskeletal network in the pathogenic signal-induced PCD are discussed.Key words: actin microfilament, cell cycle, cryptogein, microtubules, nuclei, programmed cell death, tobacco BY-2 cells, vacuoles     

A predominant β-CGTase G1 engineered to elucidate the relationship between protein structure and product specificity

Low reaction yields and the high cost of obtaining a single type of pure CD make γ-CD costly. Using rational design and with the aid of 3D modeling structures, recombinant CGTase from Bacillus sp. G1 was molecularly engineered with the aim of producing a higher percentage of γ-CD. A single mutation at subsite −3, denoted H43T, was found to increase γ-CD production from 10% to approximately 39% using tapioca starch. This novel increment was probably the result of reduced steric hindrance to the formation of γ-CD because of the shortened side chain together with the shortened loop at positions 86–89, at substrate-binding subsite −3. A mutation (Tyr188 → Trp) and a deletion at loop 139–144 showed little effect on product specificity; however, mutagenesis at these sites affected cyclization, coupling and hydrolysis activities as well as the kinetic properties of the mutant CGTase. Based on rational design, three further mutations of the mutant H43T (denoted H43T/Δ(139–144)/S134T/A137V/L138D/V139I, H43T/S85G and H43T/Y87F) were constructed and produced γ-CD with yields of 20%, 20% and 39%, respectively. The mutant H43T/Δ(139–144)/S134T/A137V/L138D/V139I had very low cyclization and coupling activities, however their hydrolysis activity was retained. Double mutation (H43T/S85G) caused the enzyme to exhibit higher starch hydrolysis activity, approximately 26 times higher than the native CGTase G1. Although the mutants H43T and H43T/Y87F could produce the same percentage (39%) of γ-CD, the latter was more efficient as the total amount of CD produced was higher based on the V_max and k_cat values.     

Development of microsatellite markers in the marine phytoplankton Karenia mikimotoi (Dinophyceae)

The marine phytoplankton, Karenia mikimotoi, causes severe red tides which are associated with mass mortality of marine fish, and have expanded their distributions in the coastal waters of western Japan. To assess the dispersal mechanism, a population genetic study using highly polymorphic genetic markers is one of the crucial approaches. Here we developed 12 polymorphic microsatellite markers from K. mikimotoi. These loci provide a class of highly variable genetic markers, as the number of alleles ranged from 5 to 23, and the estimate of gene diversity was from 0.551 to 0.933 across the 12 microsatellites. We consider these loci potentially useful for detailing the genetic structure and gene flow among K. mikimotoi populations.     

Association pattern mining of intron retention events in human based on hybrid learning machine

Alternative splicing is a main component of protein diversity, and aberrant splicing is known to be one of the main causes of genetic disorders such as cancer. Many statistical and computational approaches have identified several major factors that determine the splicing event, such as exon/intron length, splice site strength, and density of splicing enhancers or silencers. These factors may be correlated with one another and thus result in a specific type of splicing, but there has not been a systematic approach to extracting comprehensible association patterns. Here, we attempted to understand the decision making process of the learning machine on intron retention event. We adopted a hybrid learning machine approach using a random forest and association rule mining algorithm to determine the governing factors of intron retention events and their combined effect on decision-making processes. By quantifying all candidate features into five category values, we enhanced the understandability of generated rules. The interesting features found by the random forest algorithm are that only the adenine- and thymine-based triplets such as ATA, TTA, and ATT, but not the known intronic splicing enhancer GGG triplet is shown the significant features. The rules generated by the association rule mining algorithm also show that constitutive introns are generally characterized by high adenine- and thymine-based triplet frequency (level 3 and above), 3' and 5' splice site scores, exonic splicing silencer scores, and intron length, whereas retained introns are characterized by low-level counterpart scores.