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Okoye CO, Nyaruaba R, Ita RE, Okon SU, Addey CI, Ebido CC, Opabunmi AO, Okeke ES, Chukwudozie KI. Antibiotic resistance in the aquatic environment: Analytical techniques and interactive impact of emerging contaminants. ENVIRONMENTAL TOXICOLOGY AND PHARMACOLOGY 2022; 96:103995. [PMID: 36210048 DOI: 10.1016/j.etap.2022.103995] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Revised: 09/19/2022] [Accepted: 10/02/2022] [Indexed: 06/16/2023]
Abstract
Antibiotic pollution is becoming an increasingly severe threat globally. Antibiotics have emerged as a new class of environmental pollutants due to their expanding usage and indiscriminate application in animal husbandry as growth boosters. Contamination of aquatic ecosystems by antibiotics can have a variety of negative impacts on the microbial flora of these water bodies, as well as lead to the development and spread of antibiotic-resistant genes. Various strategies for removing antibiotics from aqueous systems and environments have been developed. Many of these approaches, however, are constrained by their high operating costs and the generation of secondary pollutants. This review aims to summarize research on the distribution and effects of antibiotics in aquatic environments, their interaction with other emerging contaminants, and their remediation strategy. The ecological risks associated with antibiotics in aquatic ecosystems and the need for more effective monitoring and detection system are also highlighted.
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Affiliation(s)
- Charles Obinwanne Okoye
- Biofuels Institute, School of Environment & Safety Engineering, Jiangsu University, Zhenjiang 212013, PR China; Department of Zoology & Environmental Biology, University of Nigeria, Nsukka 410001, Nigeria; Organization of African Academic Doctor, Nairobi, Kenya
| | - Raphael Nyaruaba
- Center for Biosafety Megascience, Wuhan Institute of Virology, CAS, Wuhan, PR China; Organization of African Academic Doctor, Nairobi, Kenya
| | - Richard Ekeng Ita
- Department of Biological Sciences Ritman University, Ikot Ekpene, Akwa Ibom State, Nigeria; Organization of African Academic Doctor, Nairobi, Kenya
| | - Samuel Ukpong Okon
- Department of Marine Science, Akwa Ibom State University, Mkpat Enin, P.M.B. 1167, Nigeria; Department of Ocean Engineering, Ocean College, Zhejiang University, Zhoushan 316021, PR China; Organization of African Academic Doctor, Nairobi, Kenya
| | - Charles Izuma Addey
- College of Ocean and Earth Sciences, Xiamen University, Xiamen, PR China; Organization of African Academic Doctor, Nairobi, Kenya
| | - Chike C Ebido
- Department of Zoology & Environmental Biology, University of Nigeria, Nsukka 410001, Nigeria; Organization of African Academic Doctor, Nairobi, Kenya
| | | | - Emmanuel Sunday Okeke
- Department of Biochemistry, Faculty of Biological Sciences & Natural Science Unit, School of General Studies, University of Nigeria, Nsukka, Enugu State 410001, Nigeria; Institute of Environmental Health and Ecological Security, School of Environment and Safety Engineering, Jiangsu University, 212013, PR China; Organization of African Academic Doctor, Nairobi, Kenya.
| | - Kingsley Ikechukwu Chukwudozie
- Department of Microbiology, University of Nigeria, Nsukka, Enugu State 410001, Nigeria; Organization of African Academic Doctor, Nairobi, Kenya; Department of Clinical Medicine, School of Medicine, Jiangsu University 212013, PR China.
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Mid-infrared and near-infrared spectroscopies to classify improper fermentation of pineapple wine. CHEMICAL PAPERS 2022. [DOI: 10.1007/s11696-022-02472-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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Cuadros-Rodríguez L, Ortega-Gavilán F, Martín-Torres S, Arroyo-Cerezo A, Jiménez-Carvelo AM. Chromatographic Fingerprinting and Food Identity/Quality: Potentials and Challenges. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2021; 69:14428-14434. [PMID: 34813301 PMCID: PMC8896688 DOI: 10.1021/acs.jafc.1c05584] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
Chromatograms are a valuable source of information about the chemical composition of the food being analyzed. Sometimes, this information is not explicit and appears in a hidden or not obvious way. Thus, the use of chemometric tools and data-mining methods to extract it is required. The fingerprint provided by a chromatogram offers the possibility to perform both identity and quality testing of foodstuffs. This perspective is aimed at providing an updated opinion of chromatographic fingerprinting methodology in the field of food authentication. Furthermore, the limitations, its absence in official analytical methods, and the future directions of this methodology are discussed.
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Monago-Maraña O, Cabrera-Bañegil M, Rodas NL, Muñoz de la Peña A, Durán-Merás I. First-order discrimination of methanolic extracts from plums according to harvesting date using fluorescence spectra. Quantification of polyphenols. Microchem J 2021. [DOI: 10.1016/j.microc.2021.106533] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
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Monago-Maraña O, Eskildsen CE, Galeano-Díaz T, Muñoz de la Peña A, Wold JP. Untargeted classification for paprika powder authentication using visible – Near infrared spectroscopy (VIS-NIRS). Food Control 2021. [DOI: 10.1016/j.foodcont.2020.107564] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
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PLS-DA vs sparse PLS-DA in food traceability. A case study: Authentication of avocado samples. Talanta 2021; 224:121904. [PMID: 33379108 DOI: 10.1016/j.talanta.2020.121904] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2020] [Revised: 11/08/2020] [Accepted: 11/15/2020] [Indexed: 11/23/2022]
Abstract
Conventional and sparse partial least squares-discriminant analysis (PLS-DA and sPLS-DA) have been successfully tested in order to authenticate avocado samples in terms of three different geographical origins and six kinds of cultivar. For this, lipid chromatographic fingerprints of different avocado fruits have been acquired using gas chromatography coupled with flame ionization detector (GC-FID) and employed for building classification models. In addition, classification models concatenating strategy has been applied, which has proved to be successful to resolve multiclass problems in food authentication. Finally, fine performance metrics around of 0.95 were obtained for both multivariate classification methods.
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