Cloning and expression of first gene for biodegrading microcystins by Sphingopyxis sp. USTB-05

Harmful cyanobacterial blooms (HCBs) in natural waters are a growing environmental problem worldwide because microcystins (MCs) produced by cyanobacteria are potent hepatotoxins and tumor promoters. MCs are resistant against physical and chemical factors. Thus, biodegradation is the most efficient method for removing MCs, and a number of bacterial strains, especially genus _Sphingomonas_, have been isolated for biodegrading MCs. Although the pathway, enzyme, and gene for biodegrading MCs by _Sphingomonas sp._ have been widely identified recently, no gene concerned with the biodegradation of MCs has been successfully cloned and expressed. In this study, we show that the first and most important gene of mlrA, containing 1,008 bp nucleotides in length, in the biodegradation pathway of MCs by _Sphingopyxis sp._ USTB-05, which encodes an enzyme MlrA containing 336 amino acid residues, is firstly cloned and expressed in _E. coli_ DH5α, with a cloning vector of pGEM-T easy and an expression vector of pGEX-4T-1. The encoded and expressed enzyme MlrA is responsible for cleaving the target peptide bond between 3-amino-9-methoxy-2,6,8-trimethyl-10-phenyl-deca-4,6-dienoic acid (Adda) and Arg in the cyclic structure of microcystin-RR （MC-RR）and microcystin-LR（MC-LR), two typical and toxic types of MCs. Linear MC-RR and MC-LR are produced as the first products. These findings are important in constructing a new genetic bacterial strain for the efficient removal of MCs from the important water supplies and resolving the controversy on the biodegradation pathway of different types of MCs by genus _Sphingomonas_

Quantifying immediate price impact of trades based on the kk-shell decomposition of stock trading networks

Traders in a stock market exchange stock shares and form a stock trading network. Trades at different positions of the stock trading network may contain different information. We construct stock trading networks based on the limit order book data and classify traders into $k$ classes using the $k$-shell decomposition method. We investigate the influences of trading behaviors on the price impact by comparing a closed national market (A-shares) with an international market (B-shares), individuals and institutions, partially filled and filled trades, buyer-initiated and seller-initiated trades, and trades at different positions of a trading network. Institutional traders professionally use some trading strategies to reduce the price impact and individuals at the same positions in the trading network have a higher price impact than institutions. We also find that trades in the core have higher price impacts than those in the peripheral shell.Comment: 6 pages including 3 figures and 1 tabl