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Updated: Jan 20, 2026

Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples
Published on: June 8, 2020
Novel shortcut biological nitrogen removal method using an algae-bacterial consortium in a photo-sequencing batch
S Arun1, N Arul Manikandan2, Kannan Pakshirajan1
1Department of Biosciences and Bioengineering, Indian Institute of Technology Guwahati, Guwahati, 781039, Assam, India.
Abstract:
This study evaluated a novel shortcut nitrogen removal method using a mixed consortium of microalgae, enriched ammonia oxidizing bacteria (AOB) and methanol utilizing denitrifier (MUD) in a photo-sequencing batch reactor (PSBR) for treating ammonium rich wastewater (ARWW). Alternating light and dark periods were followed to obtain complete biological nitrogen removal (BNR) without any external aeration and with the addition of methanol as the sole carbon source, respectively. The results showed that influent NH4+ was oxidized to NO2- by AOB during the light periods at a rate of 8.09 mg NH4+-N L-1h-1. Subsequently, NO2- was completely reduced during the dark period due to the action of MUD in presence of methanol. The high activities of ammonia monooxygenase (AMO) and nitrite reductase (NIR) enzymes revealed the strong role of AOB and MUD for achieving shortcut nitrogen removal from the wastewater. The reduced activities of nitrate reductase (NR) and nitrite oxidoreductase (NOR) at a high concentration of DO, NH4+ and NO2-in the system further confirmed the nitrogen removal pathway involved in the process. The biomass produced from these experiments showed good settling properties with a maximum sedimentation rate of 0.7-1.8 m h-1, a maximum sludge volume index (SVI) of 193 ml g-1- 256 ml g-1and floc size of 0.2-1.2 mm. In order to describe the growth and interaction among the algae, AOB and MUD for nitrogen removal in the system, the experimental results were fitted to four metabolic models, which revealed best fit of the experimental data due to the models based on algae-AOB and algae-AOB-MUD activities than with the other two models.
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