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Chen SL, Wang TY, Tang CC, Wang R, He ZW, Li ZH, Tian Y, Wang XC. Revealing mechanisms of triclosan on the removal and distribution of nitrogen and phosphorus in microalgal-bacterial symbiosis system. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 337:122539. [PMID: 37699452 DOI: 10.1016/j.envpol.2023.122539] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Revised: 09/03/2023] [Accepted: 09/09/2023] [Indexed: 09/14/2023]
Abstract
Microalgal-bacterial symbiosis (MABS) system performs synergistic effect on the reduction of nutrients and carbon emissions in the water treatment process. However, antimicrobial agents are frequently detected in water, which influence the performance of MABS system. In this study, triclosan (TCS) was selected to reveal the effects and mechanisms of antimicrobial agents on MABS system. Results showed that the removal efficiencies of chemical oxygen demand, NH4+-N and total phosphorus decreased by 3.0%, 24.0% and 14.3% under TCS stress. In contrast, there were no significant decrease on the removal effect of total nitrogen. Mechanism analysis showed that both the growth rate of microorganisms and the nutrients retention capacity of extracellular polymeric substances were decreased. The intracellular accumulation for nitrogen and phosphorus was promoted due to the increased cytomembrane permeability caused by lipid peroxidation. Moreover, microalgae were dominant in MABS system with ratio between microalgae and bacteria of more than 5.49. The main genus was Parachlorella, with abundance of more than 90%. Parachlorella was highly tolerant to TCS, which might be conductive to maintain its survival. This study revealed the nutrients pathways of MABS system under TCS stress, and helped to optimize the operation of MABS system.
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Affiliation(s)
- Sheng-Long Chen
- Shaanxi Key Laboratory of Environmental Engineering, School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an, 710055, China; Key Laboratory of Northwest Water Resource, Environment and Ecology, Ministry of Education, Xi'an University of Architecture and Technology, Xi'an, 710055, China
| | - Tian-Yang Wang
- Shaanxi Key Laboratory of Environmental Engineering, School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an, 710055, China; Key Laboratory of Northwest Water Resource, Environment and Ecology, Ministry of Education, Xi'an University of Architecture and Technology, Xi'an, 710055, China
| | - Cong-Cong Tang
- Shaanxi Key Laboratory of Environmental Engineering, School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an, 710055, China; Key Laboratory of Northwest Water Resource, Environment and Ecology, Ministry of Education, Xi'an University of Architecture and Technology, Xi'an, 710055, China.
| | - Rong Wang
- Shaanxi Key Laboratory of Environmental Engineering, School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an, 710055, China; Key Laboratory of Northwest Water Resource, Environment and Ecology, Ministry of Education, Xi'an University of Architecture and Technology, Xi'an, 710055, China
| | - Zhang-Wei He
- Shaanxi Key Laboratory of Environmental Engineering, School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an, 710055, China; Key Laboratory of Northwest Water Resource, Environment and Ecology, Ministry of Education, Xi'an University of Architecture and Technology, Xi'an, 710055, China
| | - Zhi-Hua Li
- Shaanxi Key Laboratory of Environmental Engineering, School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an, 710055, China; Key Laboratory of Northwest Water Resource, Environment and Ecology, Ministry of Education, Xi'an University of Architecture and Technology, Xi'an, 710055, China
| | - Yu Tian
- State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin, 150090, China
| | - Xiaochang C Wang
- Shaanxi Key Laboratory of Environmental Engineering, School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an, 710055, China; Key Laboratory of Northwest Water Resource, Environment and Ecology, Ministry of Education, Xi'an University of Architecture and Technology, Xi'an, 710055, China; International Science & Technology Cooperation Center for Urban Alternative Water Resources Development, Xi'an, 710055, China
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Shaukat MA, Nguyen TT, Hsu EB, Yang S, Bhatti A. Comparative study of encoded and alignment-based methods for virus taxonomy classification. Sci Rep 2023; 13:18662. [PMID: 37907535 PMCID: PMC10618506 DOI: 10.1038/s41598-023-45461-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2023] [Accepted: 10/19/2023] [Indexed: 11/02/2023] Open
Abstract
The emergence of viruses and their variants has made virus taxonomy more important than ever before in controlling the spread of diseases. The creation of efficient treatments and cures that target particular virus properties can be aided by understanding virus taxonomy. Alignment-based methods are commonly used for this task, but are computationally expensive and time-consuming, especially when dealing with large datasets or when detecting new virus variants is time sensitive. An alternative approach, the encoded method, has been developed that does not require prior sequence alignment and provides faster results. However, each encoded method has its own claimed accuracy. Therefore, careful evaluation and comparison of the performance of different encoded methods are essential to identify the most accurate and reliable approach for virus taxonomy classification. This study aims to address this issue by providing a comprehensive and comparative analysis of the potential of encoded methods for virus classification and phylogenetics. We compared the vectors generated for each encoded method using distance metrics to determine their similarity to alignment-based methods. The results and their validation show that K-merNV followed by CgrDft encoded methods, perform similarly to state-of-the-art multi-sequence alignment methods. This is the first study to incorporate and compare encoded methods that will facilitate future research in making more informed decisions regarding selection of a suitable method for virus taxonomy.
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Affiliation(s)
- Muhammad Arslan Shaukat
- Institute for Intelligent Systems Research and Innovation (IISRI), Deakin University, Victoria, Australia.
| | - Thanh Thi Nguyen
- Faculty of Information Technology, Monash University, Victoria, Australia
| | - Edbert B Hsu
- Department of Emergency Medicine, Johns Hopkins University, Maryland, USA
| | - Samuel Yang
- Department of Emergency Medicine, Stanford University, California, USA
| | - Asim Bhatti
- Institute for Intelligent Systems Research and Innovation (IISRI), Deakin University, Victoria, Australia
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Qin H, Sandrini G, Piel T, Slot PC, Huisman J, Visser PM. The harmful cyanobacterium Microcystis aeruginosa PCC7806 is more resistant to hydrogen peroxide at elevated CO 2. HARMFUL ALGAE 2023; 128:102482. [PMID: 37714576 DOI: 10.1016/j.hal.2023.102482] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Revised: 07/28/2023] [Accepted: 07/28/2023] [Indexed: 09/17/2023]
Abstract
Rising atmospheric CO2 can intensify harmful cyanobacterial blooms in eutrophic lakes. Worldwide, these blooms are an increasing environmental concern. Low concentrations of hydrogen peroxide (H2O2) have been proposed as a short-term but eco-friendly approach to selectively mitigate cyanobacterial blooms. However, sensitivity of cyanobacteria to H2O2 can vary depending on the available resources. To find out how cyanobacteria respond to H2O2 under elevated CO2, Microcystis aeruginosa PCC 7806 was cultured in chemostats with nutrient-replete medium under C-limiting and C-replete conditions (150 ppm and 1500 ppm CO2, respectively). Microcystis chemostats exposed to high CO2 showed higher cell densities, biovolumes, and microcystin contents, but a lower photosynthetic efficiency and pH compared to the cultures grown under low CO2. Subsamples of the chemostats were treated with different concentrations of H2O2 (0-10 mg·L-1 H2O2) in batch cultures under two different light intensities (15 and 100 μmol photons m-2·s-1) and the response in photosynthetic vitality was monitored during 24 h. Results showed that Microcystis was more resistant to H2O2 at elevated CO2 than under carbon-limited conditions. Both low and high CO2-adapted cells were more sensitive to H2O2 at high light than at low light. Microcystins (MCs) leaked out of the cells of cultures exposed to 2-10 mg·L-1 H2O2, while the sum of intra- and extracellular MCs decreased. Although both H2O2 and CO2 concentrations in lakes vary in response to many factors, these results imply that it may become more difficult to suppress cyanobacterial blooms in eutrophic lakes when atmospheric CO2 concentrations continue to rise.
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Affiliation(s)
- Hongjie Qin
- Guangdong Provincial Key Lab of Ornamental Plant Germplasm Innovation and Utilization, Environmental Horticulture Research Institute, Guangdong Academy of Agricultural Sciences, Guangzhou, 510640, China; Department of Freshwater and Marine Ecology, Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, PO Box 94240, 1090 GE Amsterdam, The Netherlands; Institute of Agricultural Resources and Environment, Jiangsu Academy of Agricultural Sciences, Nanjing, 210014, China
| | - Giovanni Sandrini
- Department of Freshwater and Marine Ecology, Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, PO Box 94240, 1090 GE Amsterdam, The Netherlands; Department of Technology & Sources, Evides Water Company, Rotterdam, The Netherlands
| | - Tim Piel
- Department of Freshwater and Marine Ecology, Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, PO Box 94240, 1090 GE Amsterdam, The Netherlands
| | - Pieter C Slot
- Department of Freshwater and Marine Ecology, Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, PO Box 94240, 1090 GE Amsterdam, The Netherlands
| | - Jef Huisman
- Department of Freshwater and Marine Ecology, Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, PO Box 94240, 1090 GE Amsterdam, The Netherlands
| | - Petra M Visser
- Department of Freshwater and Marine Ecology, Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, PO Box 94240, 1090 GE Amsterdam, The Netherlands.
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Xia Q, Tang H, Fu L, Tan J, Govindjee G, Guo Y. Determination of Fv / Fm from Chlorophyll a Fluorescence without Dark Adaptation by an LSSVM Model. PLANT PHENOMICS (WASHINGTON, D.C.) 2023; 5:0034. [PMID: 37011261 PMCID: PMC10065787 DOI: 10.34133/plantphenomics.0034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Accepted: 02/26/2023] [Indexed: 06/19/2023]
Abstract
Evaluation of photosynthetic quantum yield is important for analyzing the phenotype of plants. Chlorophyll a fluorescence (ChlF) has been widely used to estimate plant photosynthesis and its regulatory mechanisms. The ratio of variable to maximum fluorescence, Fv /Fm , obtained from a ChlF induction curve, is commonly used to reflect the maximum photochemical quantum yield of photosystem II (PSII), but it is measured after a sample is dark-adapted for a long time, which limits its practical use. In this research, a least-squares support vector machine (LSSVM) model was developed to explore whether Fv /Fm can be determined from ChlF induction curves measured without dark adaptation. A total of 7,231 samples of 8 different experiments, under diverse conditions, were used to train the LSSVM model. Model evaluation with different samples showed excellent performance in determining Fv /Fm from ChlF signals without dark adaptation. Computation time for each test sample was less than 4 ms. Further, the prediction performance of test dataset was found to be very desirable: a high correlation coefficient (0.762 to 0.974); a low root mean squared error (0.005 to 0.021); and a residual prediction deviation of 1.254 to 4.933. These results clearly demonstrate that Fv /Fm , the widely used ChlF induction feature, can be determined from measurements without dark adaptation of samples. This will not only save experiment time but also make Fv /Fm useful in real-time and field applications. This work provides a high-throughput method to determine the important photosynthetic feature through ChlF for phenotyping plants.
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Affiliation(s)
- Qian Xia
- Key Laboratory of Advanced Process Control for Light Industry, Ministry of Education,
Jiangnan University, Wuxi 214122, China
| | - Hao Tang
- Key Laboratory of Advanced Process Control for Light Industry, Ministry of Education,
Jiangnan University, Wuxi 214122, China
| | - Lijiang Fu
- Key Laboratory of Advanced Process Control for Light Industry, Ministry of Education,
Jiangnan University, Wuxi 214122, China
| | - Jinglu Tan
- Department of Biomedical, Biological and Chemical Engineering,
University of Missouri, Columbia, MO 65211, USA
| | - Govindjee Govindjee
- Center of Biophysics and Quantitative Biology, Department of Biochemistry and Department of Plant Biology,
University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Ya Guo
- Key Laboratory of Advanced Process Control for Light Industry, Ministry of Education,
Jiangnan University, Wuxi 214122, China
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Zuo J, Tan F, Zhang H, Xue Y, Grossart HP, Jeppesen E, Xiao P, Chen H, Yang J. Interaction between Raphidiopsis raciborskii and rare bacterial species revealed by dilution-to-extinction experiments. HARMFUL ALGAE 2022; 120:102350. [PMID: 36470605 DOI: 10.1016/j.hal.2022.102350] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/10/2022] [Revised: 10/31/2022] [Accepted: 11/06/2022] [Indexed: 06/17/2023]
Abstract
Interactions between heterotrophic bacteria and cyanobacteria regulate the structure and function of aquatic ecosystems and are thus crucial for the prediction and management of cyanobacterial blooms in relation to water security. Currently, abundant bacterial species are of primary concern, while the role of more diverse and copious rare species remains largely unknown. Using a dilution-to-extinction approach, rare bacterial species from reservoir water were co-cultured with the bloom-forming cyanobacterium Raphidiopsis raciborskii in the lab to explore their interactions by using Phyto-PAM and 16S rRNA gene high-throughput sequencing. We found that a ≤1000-fold bacterial dilution led to bacteria control of the growth and photosynthesis of R. raciborskii. Moreover, the bacterial community compositions in the low-dilution groups were clearly diverged from the high-dilution groups. Importantly, rare species changed dramatically in the low-dilution groups, resulting in lower phylogenetic diversity and narrower niche width. The network complexity and compositional stability of bacterial communities decreased in the low-dilution groups. Collectively, our results suggest that rare bacterial species inhibit R. raciborskii growth and photosynthesis through microbial interactions mediated by species coexistence and interaction mechanisms. Our study provides new knowledge of the ecological role of rare bacteria and offers new perspectives for understanding the outbreak and regression of R. raciborskii blooms.
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Affiliation(s)
- Jun Zuo
- Aquatic EcoHealth Group, Fujian Key Laboratory of Watershed Ecology, Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
| | - Fengjiao Tan
- Aquatic EcoHealth Group, Fujian Key Laboratory of Watershed Ecology, Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Hongteng Zhang
- Aquatic EcoHealth Group, Fujian Key Laboratory of Watershed Ecology, Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yuanyuan Xue
- Aquatic EcoHealth Group, Fujian Key Laboratory of Watershed Ecology, Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
| | - Hans-Peter Grossart
- Leibniz-Institute of Freshwater Ecology and Inland Fisheries (IGB), Stechlin 16775, Germany; University of Potsdam, Institute of Biochemistry and Biology, Potsdam 14469, Germany
| | - Erik Jeppesen
- Department of Ecoscience, Aarhus University, Aarhus 8000, Denmark; Sino-Danish Centre for Education and Research, Beijing 100049, China; Limnology Laboratory, Department of Biological Sciences and Centre for Ecosystem Research and Implementation, Middle East Technical University, Ankara 06800, Turkey; Institute of Marine Sciences, Middle East Technical University, Mersin 33731, Turkey
| | - Peng Xiao
- Aquatic EcoHealth Group, Fujian Key Laboratory of Watershed Ecology, Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; National and Local Joint Engineering Research Center of Ecological Treatment Technology for Urban Water Pollution, College of Life and Environmental Science, Wenzhou University, Wenzhou 325035, China
| | - Huihuang Chen
- Aquatic EcoHealth Group, Fujian Key Laboratory of Watershed Ecology, Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jun Yang
- Aquatic EcoHealth Group, Fujian Key Laboratory of Watershed Ecology, Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China.
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Transcriptomic Analysis of the Molecular Response Mechanism of Microcystis aeruginosa to Iron Limitation Stress. WATER 2022. [DOI: 10.3390/w14111679] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Iron is an essential micronutrient for cyanobacteria. It is involved in physiological activities such as photosynthesis, respiration, and the synthesis of pigments. The impact of iron limitation on planktonic algae growth occurs in surface oceans globally, as well as in freshwater ecosystems. However, the molecular and physiological effects and response mechanism of cyanobacteria under iron-limited conditions have not been reported in detail. In this study, the effects of iron limitation on the cell density, chlorophyll content, and photosynthetic activity of Microcystis aeruginosa were determined, and transcriptome sequencing was undertaken. In a severely iron-deficient environment, the cell density and chlorophyll-a content of M. aeruginosa were significantly lower than in the iron-rich group (a 55.42% and 83.51% reduction, respectively). Similarly, the photosynthetic efficiency of M. aeruginosa was also inhibited by iron deficiency, and the maximum photochemical efficiency (Fv/Fm) of the severe iron deficiency group was only 66.72% of the control group. The transcriptome results showed that to cope with the iron-deficient environment, most genes involved in iron absorption and transport in M. aeruginosa were up-regulated. In particular, the fur and perR genes that regulate the iron uptake regulatory protein (Fur) were both up-regulated. Due to the high demand for iron in the photosynthetic electron transport chain of M. aeruginosa, most photosynthesis-related genes were down-regulated, for example, petJ, which regulates iron-containing cytochrome c6. In contrast, most of the genes related to glycolysis and respiration were up-regulated. These changes in gene expression may be a survival strategy for M. aeruginosa to cope with a long-term iron-deficient environment. This study provides insights into the molecular response mechanism of M. aeruginosa under iron limitation stress.
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Chlorophyll fluorescence as a valuable multitool for microalgal biotechnology. Biophys Rev 2022; 14:973-983. [PMID: 36124274 PMCID: PMC9481855 DOI: 10.1007/s12551-022-00951-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Accepted: 03/26/2022] [Indexed: 01/14/2023] Open
Abstract
Variable fluorescence of chlorophyll (CF) of the photosynthetic apparatus is an ample source of valuable information on physiological condition of photosynthetic organisms. Currently, the most widespread CF-based technique is represented by recording pulse-amplitude modulated (PAM) induction of CF by saturating light. The CF-based monitoring techniques are increasingly employed for characterization of performance and stress resilience of microalgae in microalgal biotechnology. Analysis of CF induction curves reveals the fate of light energy absorbed by photosynthetic apparatus, the proportions of the energy that have been utilized for photochemistry (culture growth), and heat dissipated by photoprotective mechanisms. Hence CF and its derived parameters are an accurate proxy of the metabolic activity of the photosynthetic cell and the engagement of photoprotective mechanisms. This information is a solid foundation for making decisions on the microalgal culture management during the lab-scale and industrial-scale cultivation. Applications of CF and PAM include the monitoring of stressor (high light, nutrient deprivation, extreme temperatures, etc.) effects for assessment of the culture robustness. It also serves as a non-invasive express test for gauging the effect of assorted toxicants in microalgae. This approach is becoming widespread in ecological toxicology and environmental biotechnology, particularly for bioprospecting strains capable of the destruction of dangerous pollutants such as pharmaceuticals. In the review, we discuss the advantages and drawbacks of using CF-based methods for assessment of the culture conditions. Special attention is paid to the potential caveats and applicability of different variations of CF and PAM measurements for solving problems of microalgal biotechnology.
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