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Chua FJD, Kim SY, Hill E, Cai JW, Lee WL, Gu X, Afri Affandi SA, Kwok WCG, Ng W, Leifels M, Armas F, Chandra F, Chen H, Alm EJ, Tay M, Wong CCJ, Ng LC, Wuertz S, Thompson JR. Co-incidence of BA.1 and BA.2 at the start of Singapore's Omicron wave revealed by Community and University Campus wastewater surveillance. Sci Total Environ 2023; 875:162611. [PMID: 36871716 DOI: 10.1016/j.scitotenv.2023.162611] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Revised: 02/28/2023] [Accepted: 02/28/2023] [Indexed: 06/18/2023]
Abstract
Wastewater surveillance (WWS) has been globally recognised to be a useful tool in quantifying SARS-CoV-2 RNA at the community and residential levels without biases associated with case-reporting. The emergence of variants of concern (VOCs) have given rise to an unprecedented number of infections even though populations are increasingly vaccinated. This is because VOCs have been reported to possess higher transmissibility and can evade host immune responses. The B.1.1.529 lineage (Omicron) has severely disrupted global plans to return to normalcy. In this study, we developed an allele-specific (AS) RT-qPCR assay which simultaneously targets the stretch of deletions and mutations in the spike protein from position 24-27 for quantitative detection of Omicron BA.2. Together with previous assays that detect mutations associated with Omicron BA.1 (deletion at position 69 and 70) and all Omicron (mutation at position 493 and 498), we report the validation and time series of these assays from September 2021 to May 2022 using influent samples from two wastewater treatment plants and across four University campus sites in Singapore. Viral RNA concentrations at the treatment plants corroborate with locally reported clinical cases, AS RT-qPCR assays revealed co-incidence of Omicron BA.1 and BA.2 on 12 January 2022, almost two months after initial BA.1 detection in South Africa and Botswana. BA.2 became the dominant variant by the end of January 2022 and completely displaced BA.1 by mid-March 2022. University campus sites were similarly positive for BA.1 and/or BA.2 in the same week as first detection at the treatment plants, where BA.2 became rapidly established as the dominant lineage within three weeks. These results corroborate clinical incidence of the Omicron lineages in Singapore and indicate minimal silent circulation prior to January 2022. The subsequent simultaneous spread of both variant lineages followed strategic relaxation of safe management measures upon meeting nationwide vaccination goals.
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Affiliation(s)
- Feng Jun Desmond Chua
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, 637551, Singapore
| | - Se Yeon Kim
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, 637551, Singapore
| | - Eric Hill
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, 637551, Singapore
| | - Jia Wei Cai
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, 637551, Singapore
| | - Wei Lin Lee
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, 138602, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), 138602, Singapore
| | - Xiaoqiong Gu
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, 138602, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), 138602, Singapore
| | - Siti Aisyah Afri Affandi
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, 637551, Singapore
| | - Wee Chiew Germaine Kwok
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, 637551, Singapore
| | - Weijie Ng
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, 637551, Singapore
| | - Mats Leifels
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, 637551, Singapore
| | - Federica Armas
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, 138602, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), 138602, Singapore
| | - Franciscus Chandra
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, 138602, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), 138602, Singapore
| | - Hongjie Chen
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, 138602, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), 138602, Singapore
| | - Eric J Alm
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, 138602, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), 138602, Singapore; Centre for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Biological Engineering, Massachusetts Institute of Technology, MA 02139, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Martin Tay
- Environmental Health Institute, National Environmental Agency, 138667, Singapore
| | | | - Lee Ching Ng
- Environmental Health Institute, National Environmental Agency, 138667, Singapore; School of Biological Sciences, Nanyang Technological University, 637551, Singapore
| | - Stefan Wuertz
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, 637551, Singapore; School of Civil and Environmental Engineering, Nanyang Technological University, 639798, Singapore
| | - Janelle R Thompson
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, 637551, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), 138602, Singapore; Asian School of the Environment, Nanyang Technological University, 637459, Singapore.
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Leifels M, Khalilur Rahman O, Sam IC, Cheng D, Chua FJD, Nainani D, Kim SY, Ng WJ, Kwok WC, Sirikanchana K, Wuertz S, Thompson J, Chan YF. The one health perspective to improve environmental surveillance of zoonotic viruses: lessons from COVID-19 and outlook beyond. ISME Commun 2022; 2:107. [PMID: 36338866 PMCID: PMC9618154 DOI: 10.1038/s43705-022-00191-8] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Revised: 09/26/2022] [Accepted: 10/11/2022] [Indexed: 11/11/2022]
Abstract
The human population has doubled in the last 50 years from about 3.7 billion to approximately 7.8 billion. With this rapid expansion, more people live in close contact with wildlife, livestock, and pets, which in turn creates increasing opportunities for zoonotic diseases to pass between animals and people. At present an estimated 75% of all emerging virus-associated infectious diseases possess a zoonotic origin, and outbreaks of Zika, Ebola and COVID-19 in the past decade showed their huge disruptive potential on the global economy. Here, we describe how One Health inspired environmental surveillance campaigns have emerged as the preferred tools to monitor human-adjacent environments for known and yet to be discovered infectious diseases, and how they can complement classical clinical diagnostics. We highlight the importance of environmental factors concerning interactions between animals, pathogens and/or humans that drive the emergence of zoonoses, and the methodologies currently proposed to monitor them-the surveillance of wastewater, for example, was identified as one of the main tools to assess the spread of SARS-CoV-2 by public health professionals and policy makers during the COVID-19 pandemic. One-Health driven approaches that facilitate surveillance, thus harbour the potential of preparing humanity for future pandemics caused by aetiological agents with environmental reservoirs. Via the example of COVID-19 and other viral diseases, we propose that wastewater surveillance is a useful complement to clinical diagnosis as it is centralized, robust, cost-effective, and relatively easy to implement.
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Affiliation(s)
- Mats Leifels
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore, Singapore
| | - Omar Khalilur Rahman
- Department of Medical Microbiology, Faculty of Medicine, Universiti Malaya, Kuala Lumpur, Malaysia
| | - I-Ching Sam
- Department of Medical Microbiology, Faculty of Medicine, Universiti Malaya, Kuala Lumpur, Malaysia
- Department of Medical Microbiology, University Malaya Medical Centre, Kuala Lumpur, Malaysia
| | - Dan Cheng
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore, Singapore
| | - Feng Jun Desmond Chua
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore, Singapore
| | - Dhiraj Nainani
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore, Singapore
| | - Se Yeon Kim
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore, Singapore
| | - Wei Jie Ng
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore, Singapore
| | - Wee Chiew Kwok
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore, Singapore
| | - Kwanrawee Sirikanchana
- Research Laboratory of Biotechnology, Chulabhorn Research Institute, Bangkok, Thailand
- Centre of Excellence on Environmental Health and Toxicology, CHE, Ministry of Education, Bangkok, Thailand
| | - Stefan Wuertz
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore, Singapore
- School of Civil and Environmental Engineering, Nanyang Technological University, Singapore, Singapore
| | - Janelle Thompson
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore, Singapore
- Campus for Research Excellence and Technological Enterprise (CREATE), Singapore, Singapore
- Asian School of the Environment, Nanyang Technological University, Singapore, Singapore
| | - Yoke Fun Chan
- Department of Medical Microbiology, Faculty of Medicine, Universiti Malaya, Kuala Lumpur, Malaysia
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Lee WL, Gu X, Armas F, Leifels M, Wu F, Chandra F, Chua FJD, Syenina A, Chen H, Cheng D, Ooi EE, Wuertz S, Alm EJ, Thompson J. Monitoring human arboviral diseases through wastewater surveillance: Challenges, progress and future opportunities. Water Res 2022; 223:118904. [PMID: 36007397 DOI: 10.1016/j.watres.2022.118904] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Revised: 07/19/2022] [Accepted: 07/23/2022] [Indexed: 05/21/2023]
Abstract
Arboviral diseases are caused by a group of viruses spread by the bite of infected arthropods. Amongst these, dengue, Zika, west nile fever and yellow fever cause the greatest economic and social impact. Arboviral epidemics have increased in frequency, magnitude and geographical extent over the past decades and are expected to continue increasing with climate change and expanding urbanisation. Arboviral prevalence is largely underestimated, as most infections are asymptomatic, nevertheless existing surveillance systems are based on passive reporting of loosely defined clinical syndromes with infrequent laboratory confirmation. Wastewater-based surveillance (WBS), which has been demonstrated to be useful for monitoring diseases with significant asymptomatic populations including COVID19 and polio, could be a useful complement to arboviral surveillance. We review the current state of knowledge and identify key factors that affect the feasibility of monitoring arboviral diseases by WBS to include viral shedding loads by infected persons, the persistence of shed arboviruses and the efficiency of their recovery from sewage. We provide a simple model on the volume of wastewater that needs to be processed for detection of arboviruses, in face of lower arboviral shedding rates. In all, this review serves to reflect on the key challenges that need to be addressed and overcome for successful implementation of arboviral WBS.
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Affiliation(s)
- Wei Lin Lee
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore 138602, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore 138602, Singapore
| | - Xiaoqiong Gu
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore 138602, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore 138602, Singapore
| | - Federica Armas
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore 138602, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore 138602, Singapore
| | - Mats Leifels
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore 637551, Singapore
| | - Fuqing Wu
- Department of Epidemiology, Human Genetics, and Environmental Sciences, Center for Infectious Disease, University of Texas School of Public Health, Houston, TX, USA
| | - Franciscus Chandra
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore 138602, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore 138602, Singapore
| | - Feng Jun Desmond Chua
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore 637551, Singapore
| | - Ayesa Syenina
- Program in Emerging Infectious Diseases, Duke-NUS Medical School, Singapore 169857, Singapore; Viral Research and Experimental Medicine Centre (ViREMiCS), SingHealth Duke-NUS Academic Medical Centre, Singapore 169856, Singapore
| | - Hongjie Chen
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore 138602, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore 138602, Singapore
| | - Dan Cheng
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore 637551, Singapore
| | - Eng Eong Ooi
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore 138602, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore 138602, Singapore; Program in Emerging Infectious Diseases, Duke-NUS Medical School, Singapore 169857, Singapore; Viral Research and Experimental Medicine Centre (ViREMiCS), SingHealth Duke-NUS Academic Medical Centre, Singapore 169856, Singapore; Saw Swee Hock School of Public Health, National University of Singapore, Singapore 117549, Singapore
| | - Stefan Wuertz
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore 637551, Singapore; School of Civil and Environmental Engineering, Nanyang Technological University, Singapore 639798, Singapore
| | - Eric J Alm
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore 138602, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore 138602, Singapore; Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Biological Engineering, Massachusetts Institute of Technology, MA 02139, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
| | - Janelle Thompson
- Campus for Research Excellence and Technological Enterprise (CREATE), Singapore 138602, Singapore; Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore 637551, Singapore; Asian School of the Environment, Nanyang Technological University, Singapore 637459, Singapore.
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Lee WL, Armas F, Guarneri F, Gu X, Formenti N, Wu F, Chandra F, Parisio G, Chen H, Xiao A, Romeo C, Scali F, Tonni M, Leifels M, Chua FJD, Kwok GW, Tay JY, Pasquali P, Thompson J, Alborali GL, Alm EJ. Rapid displacement of SARS-CoV-2 variant Delta by Omicron revealed by allele-specific PCR in wastewater. Water Res 2022; 221:118809. [PMID: 35841797 PMCID: PMC9250349 DOI: 10.1016/j.watres.2022.118809] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Revised: 06/18/2022] [Accepted: 07/01/2022] [Indexed: 05/06/2023]
Abstract
On November 26, 2021, the B.1.1.529 COVID-19 variant was classified as the Omicron variant of concern (VOC). Reports of higher transmissibility and potential immune evasion triggered flight bans and heightened health control measures across the world to stem its distribution. Wastewater-based surveillance has demonstrated to be a useful complement for clinical community-based tracking of SARS-CoV-2 variants. Using design principles of our previous assays that detect SARS-CoV-2 variants (Alpha and Delta), we developed an allele-specific RT-qPCR assay which simultaneously targets the stretch of mutations from Q493R to Q498R for quantitative detection of the Omicron variant in wastewater. We report their validation against 10-month longitudinal samples from the influent of a wastewater treatment plant in Italy. SARS-CoV-2 RNA concentrations and variant frequencies in wastewater determined using these variant assays agree with clinical cases, revealing rapid displacement of the Delta variant by the Omicron variant within three weeks. These variant trends, when mapped against vaccination rates, support clinical studies that found the rapid emergence of SARS-CoV-2 Omicron variant being associated with an infection advantage over Delta in vaccinated persons. These data reinforce the versatility, utility and accuracy of these open-sourced methods using allele-specific RT-qPCR for tracking the dynamics of variant displacement in communities through wastewater for informed public health responses.
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Affiliation(s)
- Wei Lin Lee
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore
| | - Federica Armas
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore
| | - Flavia Guarneri
- Istituto Zooprofilattico Sperimentale della Lombardia e dell'Emilia Romagna "Bruno Ubertini" (IZSLER), Italy
| | - Xiaoqiong Gu
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore
| | - Nicoletta Formenti
- Istituto Zooprofilattico Sperimentale della Lombardia e dell'Emilia Romagna "Bruno Ubertini" (IZSLER), Italy
| | - Fuqing Wu
- Center for Infectious Disease, Department of Epidemiology, Human Genetics, and Environmental Sciences, University of Texas School of Public Health, Houston, TX, USA
| | - Franciscus Chandra
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore
| | - Giovanni Parisio
- Istituto Zooprofilattico Sperimentale della Lombardia e dell'Emilia Romagna "Bruno Ubertini" (IZSLER), Italy
| | - Hongjie Chen
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore
| | - Amy Xiao
- Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, USA; Department of Biological Engineering, Massachusetts Institute of Technology, USA
| | - Claudia Romeo
- Istituto Zooprofilattico Sperimentale della Lombardia e dell'Emilia Romagna "Bruno Ubertini" (IZSLER), Italy
| | - Federico Scali
- Istituto Zooprofilattico Sperimentale della Lombardia e dell'Emilia Romagna "Bruno Ubertini" (IZSLER), Italy
| | - Matteo Tonni
- Istituto Zooprofilattico Sperimentale della Lombardia e dell'Emilia Romagna "Bruno Ubertini" (IZSLER), Italy
| | - Mats Leifels
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore
| | - Feng Jun Desmond Chua
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore
| | - Germaine Wc Kwok
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore
| | - Joey Yr Tay
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore
| | - Paolo Pasquali
- Dipartimento di Sicurezza Alimentare, Nutrizione e Sanità Pubblica Veterinaria, Istituto Superiore di Sanità, Italy
| | - Janelle Thompson
- Campus for Research Excellence and Technological Enterprise (CREATE), Singapore; Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore; Asian School of the Environment, Nanyang Technological University, Singapore.
| | - Giovanni Loris Alborali
- Istituto Zooprofilattico Sperimentale della Lombardia e dell'Emilia Romagna "Bruno Ubertini" (IZSLER), Italy
| | - Eric J Alm
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore; Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, USA; Department of Biological Engineering, Massachusetts Institute of Technology, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
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Chua FJD, Yan W, Zhou Y. The interaction between ionic liquids (ILs) and an enriched ammonia oxidising bacteria (AOB) culture. Chemosphere 2019; 235:842-848. [PMID: 31284132 DOI: 10.1016/j.chemosphere.2019.07.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/19/2019] [Revised: 06/13/2019] [Accepted: 07/01/2019] [Indexed: 06/09/2023]
Abstract
Ionic liquids (ILs) have attracted attention in recent years due to their "greener" properties compared to conventional organic solvents. However, they may still pose a risk to the environment as their toxicity is not fully understood. Bioremediation of such ILs can be an economically and environmentally friendly approach. Therefore, this study aims to examine the interaction of three ILs (1-dodecylpyridnium chloride [DPy]+Cl, 1-Butyl-3-methylimidazolium chloride [BMIm]+Cl, and 1-Carbamoylmethyl pyridinium chloride [CMPy]+Cl) at different concentrations with an enriched ammonia oxidising bacteria (AOB) culture, and investigate their effects on the ammonia oxidation rate (AOR) as well as their removal and transformation. The results indicated that the longer chain IL [DPy]+Cl had a negative effect on the AOR while [BMIm]+Cl and [CMPy]+Cl enhanced the AOR. However, the IL removal rates displayed the opposite results as [DPy]+Cl was observed with the highest removal. It was found that biosorption played a major role in [DPy]+Cl removal. Biotransformation products for each IL were identified and their pathways were proposed. This study demonstrated that although longer chain ILs have a greater degree of removal, and they are also more toxic to AOB at higher concentration.
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Affiliation(s)
- Feng Jun Desmond Chua
- School of Civil and Environmental Engineering, Nanyang Technological University, 639798, Singapore; Advanced Environmental Biotechnology Centre, Nanyang Environment and Water Research Institute, Nanyang Technological University, 637141, Singapore
| | - Wangwang Yan
- Advanced Environmental Biotechnology Centre, Nanyang Environment and Water Research Institute, Nanyang Technological University, 637141, Singapore
| | - Yan Zhou
- School of Civil and Environmental Engineering, Nanyang Technological University, 639798, Singapore; Advanced Environmental Biotechnology Centre, Nanyang Environment and Water Research Institute, Nanyang Technological University, 637141, Singapore.
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Chua FJD, Sun F, Mukherjee M, Zhou Y. Comparison of nitrous oxide emission between a partial and full nitrification enriched ammonia-oxidising culture. Chemosphere 2019; 220:974-982. [PMID: 33395819 DOI: 10.1016/j.chemosphere.2018.12.204] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/29/2018] [Revised: 12/04/2018] [Accepted: 12/30/2018] [Indexed: 06/12/2023]
Abstract
Nitrification systems are known to be a source of nitrous oxide (N2O) emission, however, the contribution from partial and full nitrification systems remains controversial. In this study, N2O emission from a partial and full nitrification culture was investigated. In all tests, nitrite, dissolved oxygen concentration and pH levels were controlled within a similar range limiting ammonium concentration to be the only variable. The results reveal with the same amount of ammonium removed, the full nitrification culture produced far greater N2O than the partial nitrification culture for both pulse (25-36 times) and continuous feeding modes (2-110 times). The relative gene expression data indicate that under pulse feeding there is a decreasing trend of nirK and norB genes for the partial and full nitrification culture respectively while under continuous feeding, increasing norB trends were observed for both. This possibly indicated the hydroxylamine pathway was favoured for the partial nitrification culture while the hybrid N-nitrosation pathway maybe the major contributor for the full nitrification culture. These findings improve our understanding on N2O production pathways and enable researchers to propose better mitigation strategies.
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Affiliation(s)
- Feng Jun Desmond Chua
- School of Civil and Environmental Engineering, Nanyang Technological University, 639798, Singapore; Advanced Environmental Biotechnology Centre, Nanyang Environment and Water Research Institute, Nanyang Technological University, 637141, Singapore
| | - Faqian Sun
- School of Civil and Environmental Engineering, Nanyang Technological University, 639798, Singapore; Advanced Environmental Biotechnology Centre, Nanyang Environment and Water Research Institute, Nanyang Technological University, 637141, Singapore
| | - Manisha Mukherjee
- School of Civil and Environmental Engineering, Nanyang Technological University, 639798, Singapore; Singapore Centre for Environmental Life Sciences and Engineering, Nanyang Technological University, 637551, Singapore
| | - Yan Zhou
- School of Civil and Environmental Engineering, Nanyang Technological University, 639798, Singapore; Advanced Environmental Biotechnology Centre, Nanyang Environment and Water Research Institute, Nanyang Technological University, 637141, Singapore.
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