1.
Nitrite accumulation inside sludge flocs significantly influencing nitrous oxide production by ammonium-oxidizing bacteria.
Chen, X, Yuan, Z, Ni, BJ
Water research. 2018;:99-108
Abstract
This work aims to clarify the role of potential nitrite (NO2-) accumulation inside sludge flocs in N2O production by ammonium-oxidizing bacteria (AOB) at different dissolved oxygen (DO) levels with focus on the conditions of no significant bulk NO2- accumulation (<0.2 mg N/L). To this end, an augmented nitrifying sludge with much higher abundance of nitrite-oxidizing bacteria (NOB) than AOB was enriched and then used for systematically designed batch tests, which targeted a range of DO levels from 0 to 3.0 mg O2/L at a fixed ammonium concentration of 10 mg N/L. A two-pathway N2O model was applied to facilitate the interpretation of batch experimental data, thus shedding light on the relationships between N2O production pathways and key process parameters (i.e., DO and NO2- accumulation inside sludge flocs). The results demonstrated (i) the biomass specific N2O production rate firstly increased and then decreased with DO, with the maximum value of 3.03 ± 0.05 mg N/h/g VSS obtained at DO level of 0.75 mg O2/L, (ii) the AOB denitrification pathway for N2O production was dominant (98.0%) at all DO levels tested even without significant bulk NO2- accumulation (<0.2 mg N/L) observed in the system, but its contribution decreased with DO, (iii) DO had a positive impact on the hydroxylamine pathway for N2O production which therefore increased with DO, and (iv) the nitrite accumulation existed inside the sludge flocs and induced significant N2O production from the AOB denitrification pathway.
2.
CINPER: an interactive web system for pathway prediction for prokaryotes.
Mao, X, Chen, X, Zhang, Y, Pangle, S, Xu, Y
PloS one. 2012;(12):e51252
Abstract
We present a web-based network-construction system, CINPER (CSBL INteractive Pathway BuildER), to assist a user to build a user-specified gene network for a prokaryotic organism in an intuitive manner. CINPER builds a network model based on different types of information provided by the user and stored in the system. CINPER's prediction process has four steps: (i) collection of template networks based on (partially) known pathways of related organism(s) from the SEED or BioCyc database and the published literature; (ii) construction of an initial network model based on the template networks using the P-Map program; (iii) expansion of the initial model, based on the association information derived from operons, protein-protein interactions, co-expression modules and phylogenetic profiles; and (iv) computational validation of the predicted models based on gene expression data. To facilitate easy applications, CINPER provides an interactive visualization environment for a user to enter, search and edit relevant data and for the system to display (partial) results and prompt for additional data. Evaluation of CINPER on 17 well-studied pathways in the MetaCyc database shows that the program achieves an average recall rate of 76% and an average precision rate of 90% on the initial models; and a higher average recall rate at 87% and an average precision rate at 28% on the final models. The reduced precision rate in the final models versus the initial models reflects the reality that the final models have large numbers of novel genes that have no experimental evidences and hence are not yet collected in the MetaCyc database. To demonstrate the usefulness of this server, we have predicted an iron homeostasis gene network of Synechocystis sp. PCC6803 using the server. The predicted models along with the server can be accessed at http://csbl.bmb.uga.edu/cinper/.
3.
tRNA-dependent pre-transfer editing by prokaryotic leucyl-tRNA synthetase.
Tan, M, Zhu, B, Zhou, XL, He, R, Chen, X, Eriani, G, Wang, ED
The Journal of biological chemistry. 2010;(5):3235-44
Abstract
To prevent genetic code ambiguity due to misincorporation of amino acids into proteins, aminoacyl-tRNA synthetases have evolved editing activities to eliminate intermediate or final non-cognate products. In this work we studied the different editing pathways of class Ia leucyl-tRNA synthetase (LeuRS). Different mutations and experimental conditions were used to decipher the editing mechanism, including the recently developed compound AN2690 that targets the post-transfer editing site of LeuRS. The study emphasizes the crucial importance of tRNA for the pre- and post-transfer editing catalysis. Both reactions have comparable efficiencies in prokaryotic Aquifex aeolicus and Escherichia coli LeuRSs, although the E. coli enzyme favors post-transfer editing, whereas the A. aeolicus enzyme favors pre-transfer editing. Our results also indicate that the entry of the CCA-acceptor end of tRNA in the editing domain is strictly required for tRNA-dependent pre-transfer editing. Surprisingly, this editing reaction was resistant to AN2690, which inactivates the enzyme by forming a covalent adduct with tRNA(Leu) in the post-transfer editing site. Taken together, these data suggest that the binding of tRNA in the post-transfer editing conformation confers to the enzyme the capacity for pre-transfer editing catalysis, regardless of its capacity to catalyze post-transfer editing.