Bacteria that mediate the anaerobic oxidation of ammonium (anammox) have been detected in natural ecosystems, as well as various wastewater treatment systems. In this study, sludge from a particular landfill leachate anaerobic treatment system was selected as the incubation seed for anammox microorganism enrichment owing to its possible anammox activity. Transmission electron microscopy observation, denaturing gradient gel electrophoresis analysis, and cloning/sequencing techniques were applied to identify the diversity of anammox microorganisms throughout the incubation. During the early stage of operation, the diversity of anammox microorganisms was similar to the original complex microbes in the seed sludge. However, as incubation time increased, the anammox microorganism diversity within the system that was originally dominated by Candidatus (Ca.) Brocadia sp. was replaced by Ca. Anammoxoglobus propionicus. The domination of Ca. Anammoxoglobus propionicus produced a stable removal of ammonia (70 mg-N/l) and nitrite (90 mg-N/l), and the total nitrogen removal efficiency was maintained at nearly 95%. The fluorescence in situ hybridization results showed that Ca. Anammoxoglobus propionicus was successfully enriched from 1.8 ± 0.6% initially to 65 ± 5% after 481 days of operation. Therefore, the present results demonstrated the feasibility of enriching Ca. Anammoxoglobus propionicus from leachate sludge, even though the original cell count was extremely low. Application of this seldom found anammox organism could offer an alternative to current ammonia-nitrogen treatment.

Mass spectrometry biomarker discovery may assist patient's diagnosis in time and realize the characteristics of new diseases. Our previous work built a preprocess method called HHTmass which is capable of removing noise, but HHTmass only a proof of principle to be peak detectable and did not tested for peak reappearance rate and used on medical data. We developed a modified version of biomarker discovery method called Enhance HHTMass (E-HHTMass) for MALDI-TOF and SELDI-TOF mass spectrometry data which improved old HHTMass method by removing the interpolation and the biomarker discovery process. E-HHTMass integrates the preprocessing and classification functions to identify significant peaks. The results show that most known biomarker can be found and high peak appearance rate achieved comparing to MSCAP and old HHTMass2. E-HHTMass is able to adapt to spectra with a small increasing interval. In addition, new peaks are detected which can be potential biomarker after further validation.