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A novel epsilon-poly-L-lysine (epsilon-PL)-producing strain PL6-3 was isolated from soil, and was identified as a strain of Kitasatospora sp. This is the first detailed report of production of epsilon-PL by a strain in the genera of Kitasatospora. By controlling the culture pH at 4.0, the yield of epsilon-PL from PL6-3 reached 13.9 g/L after 120 h of cultivation in fed-batch fermentation. The morphological characteristics of Kitasatospora sp. PL6-3 in culture broth were different from those reported from strains of Streptomycetaceae, as no mycelium pellets were observed during the course of fermentation of PL6-3, which was beneficial to the assimilation of nutrition and secretion of the products. Furthermore, the molecular mass of the purified epsilon-PL from PL6-3 was determined to be 5.01 kDa by SDS-PAGE and 5.05 kDa by gel permeation chromatography, indicating that the epsilon-PL produced by this strain might be composed of 40 lysine residues. Usually, epsilon-PL with more lysine residues showed higher antimicrobial activity; however, it was difficult to obtain epsilon-PL with more than 36 lysine residues in this study. As a result, epsilon-PL from Kitasatospora sp. PL6-3, which contains more lysine residues than that from other strains, is more promising in the field of food preservatives.

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SUMMARY This paper presents a soft robot which can imitate the crawling locomotion of an earthworm. Locomotion of the robot can be achieved by expanding and contracting the body that is made of flexible material. A link of the earthworm-like robot is combined with three modules, and a multi-cavity earthworm-like soft robot is combined with multiple links. The multiple links of the earthworm-like soft robot are fabricated by silicone in the three-dimensional printed customized molds. Experiments on a single module, two-links, and three-links show that the soft robot can move and bend on condition of modules extension and contraction in a specified gait. The development of the earthworm-like soft robot shows a great prospect in many complicated environments such as pipeline detection.

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