Intracolony variation of bacterial gut microbiota among castes and ages in the fungus-growing termite Macrotermes gilvus.

The fungus-growing termites Macrotermes cultivate the obligate ectosymbiontic fungi, Termitomyces. While their relationship has been extesively studied, little is known about the gut bacterial symbionts, which also presumably play a crucial role for the nutrition of the termite host. In this study, we investigated the bacterial gut microbiota in two colonies of Macrotermes gilvus, and compared the diversity and community structure of bacteria among nine termite morphotypes, differing in caste and/or age, using terminal restriction fragment length polymorphism (T-RFLP) and clonal analysis of 16S rRNA. The obtained molecular community profiles clustered by termite morphotype rather than by colony, and the clustering pattern was clearly more related to a difference in age than to caste. Thus, we suggest that the bacterial gut microbiota change in relation to the food of the termite, which comprises fallen leaves and the fungus nodules of Termitomyces in young workers, and leaves degraded by the fungi, in old workers. Despite these intracolony variations in bacterial gut microbiota, their T-RFLP profiles formed a distinct cluster against those of the fungus garden, adjacent soil and guts of sympatric wood-feeding termites, implying a consistency and uniqueness of gut microbiota in M. gilvus. Since many bacterial phylotypes from M. gilvus formed monophyletic clusters with those from distantly related termite species, we suggest that gut bacteria have co-evolved with the termite host and form a microbiota specific to a termite taxonomic and/or feeding group, and furthermore, to caste and age within a termite species.

Evolutionary molecular engineering by random elongation mutagenesis.

We describe a new method of random mutagenesis that employs the addition of peptide tails with random sequences to the C-terminal of enzyme molecules. A mutant population of catalase I from Bacillus stearothermophilus prepared by this method has a diversity in thermostability and enzyme activity equal to that obtained after random point mutagenesis. When a triple mutant of catalase I (I108T/D130N/1222T)-the thermostability of which is much lower than that of the wild type-was subjected to random elongation mutagenesis, we generated a mutant population containing only mutants with higher thermostability than the triple mutant. Some had an even higher stability than the wild-type enzyme, whose thermostability is considered to be optimized. These results indicate that peptide addition expands the protein sequence space resulting in a new fitness landscape. The enzyme can then move along the routes of the new landscape until it reaches a new optimum. The combination of random elongation mutagenesis with random point mutagenesis should be a useful approach to the in vitro evolution of proteins with new properties.

Nonadditivity of mutational effects on the properties of catalase I and its application to efficient directed evolution.

Catalase I of Bacillus stearothermophilus has high catalatic and low peroxidatic activities. The mutant from the first random mutant population, D130N, which has higher peroxidatic and lower catalatic activities than those exhibited by the wild-type enzyme, was subjected to second random mutagenesis in observance of the change in reaction specificity. From the second mutant population, the mutant I108T/D130N/I222T was selected and examined. The reaction specificity of the purified enzymes revealed that catalase I being originally 98% catalase and 2% peroxidase was brought to 58% specificity to peroxidase after two-step adaptive walks. From the statistical analysis of the two random mutant populations, the average degree of nonadditivity of the mutational effects was estimated to be 0.13 irrespective of the properties of the enzyme. It was demonstrated that the distribution pattern of a property of the second mutant population can be predicted well from the data of the first mutant population by taking into consideration the degree of nonadditivity. The strategy for an efficient adaptive walk in directed evolution of enzymes through the prediction of appropriate mutation rate and effective sample size for further mutation and selection was presented and discussed.