Factors responsible for co-dominance of two beech species in a cool temperate forest in central Japan: interspecific comparison of spatial distribution and growth traits

To understand the co-existence mechanisms of related species,the recruitment processes of Fagus crenata and F. japonica were censused during 3 and 4 years from emergence, respectively, in a cool-temperate forest in Japan. The distributional properties and the growth traits were compared between two Fagus species. To evaluate the distributional properties, the spatial abundance of seedlings was estimated by a generalized linear model (GLM), with explanatory variables such as topographic variables, light conditions, the presence of dwarf bamboo, and the abundance of the overstory. To evaluate the growth traits under herbivory pressure, both the elongated shoot length and the proportion of recovery frompredation (re-growth) were also compared. No spatial segregation and no species-specific differences were detected by GLM, which was consistent throughout the census period. Only F. japonica exhibited a slope-related distribution, while F. crenata exhibited no topographical dependence, indicates the distributional overlaps. For the growth traits, contrasting trends were detected, F. crenata was superior in shoot growth, whereas the proportion of regrowth was higher in F. japonica than F. crenata. We concluded that co-dominance of these species was not attributed to the spatial segregationbut to the trade-off between growth and resistance to herbivory

MUCHA: multiple chemical alignment algorithm to identify building block substructures of orphan secondary metabolites

[Background]In contrast to the increasing number of the successful genome projects, there still remain many orphan metabolites for which their synthesis processes are unknown. Metabolites, including these orphan metabolites, can be classified into groups that share the same core substructures, originated from the same biosynthetic pathways. It is known that many metabolites are synthesized by adding up building blocks to existing metabolites. Therefore, it is proposed that, for any given group of metabolites, finding the core substructure and the branched substructures can help predict their biosynthetic pathway. There already have been many reports on the multiple graph alignment techniques to find the conserved chemical substructures in relatively small molecules. However, they are optimized for ligand binding and are not suitable for metabolomic studies. [Results]We developed an efficient multiple graph alignment method named as MUCHA (Multiple Chemical Alignment), specialized for finding metabolic building blocks. This method showed the strength in finding metabolic building blocks with preserving the relative positions among the substructures, which is not achieved by simply applying the frequent graph mining techniques. Compared with the combined pairwise alignments, this proposed MUCHA method generally reduced computational costs with improving the quality of the alignment. [Conclusions]MUCHA successfully find building blocks of secondary metabolites, and has a potential to complement to other existing methods to reconstruct metabolic networks using reaction patterns