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Penicillin-binding protein 3 (PBP3) of Pseudomonas aeruginosa is the primary target of β-lactams used to treat pseudomonas infections. Meanwhile, structure change and overproduction of PBP3 play important roles in the drug resistance of P. aeruginosa. Therefore, studies on the gene and structure of PBP3 are urgently needed. P. aeruginosa CMCC 10104 is a type culture strain common used in China. However, there is no report on its genomic and proteomic profiles. In this study, based on ftsI of P. aeruginosa PAO1, the gene encoding PBP3 was cloned from CMCC 10104. A truncated version of the ftsI gene, omitting the bases encoding the hydrophobic leader peptide (amino acids 1-34), was amplified by PCR. The cloned DNA shared 99.76% identity with ftsI from PAO1. Only four bases were different (66 C-A, 1020 T-C, 1233 T-C, and 1527 T-C). However, there were no differences between their deduced amino acid sequences. The recombinant PBP3 (rPBP3), containing a 6-histidine tag, was expressed in Escherichia coli BL21 (DE3). Immobilized metal affinity chromatography (IMAC) with Ni(2+)-NTA agarose was used for its purification. The purified rPBP3 was identified by SDS-PAGE and western blot analysis, and showed a single band at about 60kDa with purity higher than 95%. The penicillin-binding assay indicated that the obtained rPBP3 was functional and not hindered by the presence of the C-terminal His-tag. The protocol described in this study offers a method for obtaining purified recombinant PBP3 from P. aeruginosa CMCC 10104.

The Fibonacci numbers are the numbers defined by the linear recurrence equation, in which each subsequent number is the sum of the previous two. In this paper, we propose Fibonacci networks using Fibonacci numbers. The analytical expressions involving degree distribution, average path length and mean first passage time are obtained. This kind of networks exhibits the small-world characteristic and follows the exponential distribution. Our proposed models would provide the valuable insights into the deterministically delayed growing networks.

On the basis of recursive trees, we propose a new kind of deterministic recursive trees (DRT) with a feature that the initial state of recursive trees is a lattice with an arbitrary number of nodes. In the subsequent evolving step, existing nodes create finite nodes. We obtain analytical formulae for degree distribution and average path length. We also study mean first passage time (MFPT) between two nodes over all pairs, which is used to measure the efficiency of random walks in a network. In addition, we derive an exact formula for the MFPT by using the relationship between random walks and resistance distance in a electronic network.