1
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Marshall DJ, Cameron HE, Loreau M. Relationships between intrinsic population growth rate, carrying capacity and metabolism in microbial populations. THE ISME JOURNAL 2023; 17:2140-2143. [PMID: 37891425 PMCID: PMC10689727 DOI: 10.1038/s41396-023-01543-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Revised: 10/10/2023] [Accepted: 10/11/2023] [Indexed: 10/29/2023]
Affiliation(s)
- Dustin J Marshall
- School of Biological Sciences/Centre for Geometric Biology, Monash University, Victoria, 3800, VIC, Australia.
| | - Hayley E Cameron
- School of Biological Sciences/Centre for Geometric Biology, Monash University, Victoria, 3800, VIC, Australia
| | - Michel Loreau
- Theoretical and Experimental Ecology Station, CNRS, 2 route du CNRS, 09200, Moulis, France
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2
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Jiang D, Zhang J. Detecting natural selection in trait-trait coevolution. BMC Ecol Evol 2023; 23:50. [PMID: 37700252 PMCID: PMC10496359 DOI: 10.1186/s12862-023-02164-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Accepted: 09/04/2023] [Indexed: 09/14/2023] Open
Abstract
No phenotypic trait evolves independently of all other traits, but the cause of trait-trait coevolution is poorly understood. While the coevolution could arise simply from pleiotropic mutations that simultaneously affect the traits concerned, it could also result from multivariate natural selection favoring certain trait relationships. To gain a general mechanistic understanding of trait-trait coevolution, we examine the evolution of 220 cell morphology traits across 16 natural strains of the yeast Saccharomyces cerevisiae and the evolution of 24 wing morphology traits across 110 fly species of the family Drosophilidae, along with the variations of these traits among gene deletion or mutation accumulation lines (a.k.a. mutants). For numerous trait pairs, the phenotypic correlation among evolutionary lineages differs significantly from that among mutants. Specifically, we find hundreds of cases where the evolutionary correlation between traits is strengthened or reversed relative to the mutational correlation, which, according to our population genetic simulation, is likely caused by multivariate selection. Furthermore, we detect selection for enhanced modularity of the yeast traits analyzed. Together, these results demonstrate that trait-trait coevolution is shaped by natural selection and suggest that the pleiotropic structure of mutation is not optimal. Because the morphological traits analyzed here are chosen largely because of their measurability and thereby are not expected to be biased with regard to natural selection, our conclusion is likely general.
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Affiliation(s)
- Daohan Jiang
- Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI, 48109, USA.
- Present address: Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, 90089, USA.
| | - Jianzhi Zhang
- Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI, 48109, USA
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3
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Zhang J. What Has Genomics Taught An Evolutionary Biologist? GENOMICS, PROTEOMICS & BIOINFORMATICS 2023; 21:1-12. [PMID: 36720382 PMCID: PMC10373158 DOI: 10.1016/j.gpb.2023.01.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Revised: 01/06/2023] [Accepted: 01/19/2023] [Indexed: 01/30/2023]
Abstract
Genomics, an interdisciplinary field of biology on the structure, function, and evolution of genomes, has revolutionized many subdisciplines of life sciences, including my field of evolutionary biology, by supplying huge data, bringing high-throughput technologies, and offering a new approach to biology. In this review, I describe what I have learned from genomics and highlight the fundamental knowledge and mechanistic insights gained. I focus on three broad topics that are central to evolutionary biology and beyond-variation, interaction, and selection-and use primarily my own research and study subjects as examples. In the next decade or two, I expect that the most important contributions of genomics to evolutionary biology will be to provide genome sequences of nearly all known species on Earth, facilitate high-throughput phenotyping of natural variants and systematically constructed mutants for mapping genotype-phenotype-fitness landscapes, and assist the determination of causality in evolutionary processes using experimental evolution.
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Affiliation(s)
- Jianzhi Zhang
- Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI 48109, USA.
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4
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Mullis MN, Ghione C, Lough-Stevens M, Goldstein I, Matsui T, Levy SF, Dean MD, Ehrenreich IM. Complex genetics cause and constrain fungal persistence in different parts of the mammalian body. Genetics 2022; 222:6698696. [PMID: 36103708 PMCID: PMC9630980 DOI: 10.1093/genetics/iyac138] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Accepted: 08/26/2022] [Indexed: 12/05/2022] Open
Abstract
Determining how genetic polymorphisms enable certain fungi to persist in mammalian hosts can improve understanding of opportunistic fungal pathogenesis, a source of substantial human morbidity and mortality. We examined the genetic basis of fungal persistence in mice using a cross between a clinical isolate and the lab reference strain of the budding yeast Saccharomyces cerevisiae. Employing chromosomally encoded DNA barcodes, we tracked the relative abundances of 822 genotyped, haploid segregants in multiple organs over time and performed linkage mapping of their persistence in hosts. Detected loci showed a mix of general and antagonistically pleiotropic effects across organs. General loci showed similar effects across all organs, while antagonistically pleiotropic loci showed contrasting effects in the brain vs the kidneys, liver, and spleen. Persistence in an organ required both generally beneficial alleles and organ-appropriate pleiotropic alleles. This genetic architecture resulted in many segregants persisting in the brain or in nonbrain organs, but few segregants persisting in all organs. These results show complex combinations of genetic polymorphisms collectively cause and constrain fungal persistence in different parts of the mammalian body.
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Affiliation(s)
- Martin N Mullis
- University of Southern California Molecular and Computational Biology Section, Department of Biological Sciences, , Los Angeles, CA 90089, USA
| | - Caleb Ghione
- University of Southern California Molecular and Computational Biology Section, Department of Biological Sciences, , Los Angeles, CA 90089, USA
| | - Michael Lough-Stevens
- University of Southern California Molecular and Computational Biology Section, Department of Biological Sciences, , Los Angeles, CA 90089, USA
| | - Ilan Goldstein
- University of Southern California Molecular and Computational Biology Section, Department of Biological Sciences, , Los Angeles, CA 90089, USA
| | - Takeshi Matsui
- Stanford University Joint Initiative for Metrology in Biology, , CA 94305, USA
- SLAC National Accelerator Laboratory , Menlo Park, CA, 94025, USA
- Stanford University Department of Genetics, , Stanford, CA 94305, USA
| | - Sasha F Levy
- Stanford University Joint Initiative for Metrology in Biology, , CA 94305, USA
- SLAC National Accelerator Laboratory , Menlo Park, CA, 94025, USA
- Stanford University Department of Genetics, , Stanford, CA 94305, USA
| | - Matthew D Dean
- University of Southern California Molecular and Computational Biology Section, Department of Biological Sciences, , Los Angeles, CA 90089, USA
| | - Ian M Ehrenreich
- University of Southern California Molecular and Computational Biology Section, Department of Biological Sciences, , Los Angeles, CA 90089, USA
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5
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Different life strategies in genetic backgrounds of the Saccharomyces cerevisiae yeast cells. Fungal Biol 2022; 126:498-510. [DOI: 10.1016/j.funbio.2022.04.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2021] [Revised: 04/12/2022] [Accepted: 04/19/2022] [Indexed: 11/18/2022]
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6
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Turkarslan S, Stopnisek N, Thompson AW, Arens CE, Valenzuela JJ, Wilson J, Hunt KA, Hardwicke J, de Lomana ALG, Lim S, Seah YM, Fu Y, Wu L, Zhou J, Hillesland KL, Stahl DA, Baliga NS. Synergistic epistasis enhances the co-operativity of mutualistic interspecies interactions. THE ISME JOURNAL 2021; 15:2233-2247. [PMID: 33612833 PMCID: PMC8319347 DOI: 10.1038/s41396-021-00919-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/26/2020] [Revised: 12/18/2020] [Accepted: 01/29/2021] [Indexed: 01/31/2023]
Abstract
Early evolution of mutualism is characterized by big and predictable adaptive changes, including the specialization of interacting partners, such as through deleterious mutations in genes not required for metabolic cross-feeding. We sought to investigate whether these early mutations improve cooperativity by manifesting in synergistic epistasis between genomes of the mutually interacting species. Specifically, we have characterized evolutionary trajectories of syntrophic interactions of Desulfovibrio vulgaris (Dv) with Methanococcus maripaludis (Mm) by longitudinally monitoring mutations accumulated over 1000 generations of nine independently evolved communities with analysis of the genotypic structure of one community down to the single-cell level. We discovered extensive parallelism across communities despite considerable variance in their evolutionary trajectories and the perseverance within many evolution lines of a rare lineage of Dv that retained sulfate-respiration (SR+) capability, which is not required for metabolic cross-feeding. An in-depth investigation revealed that synergistic epistasis across pairings of Dv and Mm genotypes had enhanced cooperativity within SR- and SR+ assemblages, enabling their coexistence within the same community. Thus, our findings demonstrate that cooperativity of a mutualism can improve through synergistic epistasis between genomes of the interacting species, enabling the coexistence of mutualistic assemblages of generalists and their specialized variants.
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Affiliation(s)
- Serdar Turkarslan
- grid.64212.330000 0004 0463 2320Institute for Systems Biology, Seattle, WA 98109 USA
| | - Nejc Stopnisek
- grid.34477.330000000122986657Civil and Environmental Engineering, University of Washington, Seattle, WA 98195 USA
| | - Anne W. Thompson
- grid.262075.40000 0001 1087 1481Department of Biology, Portland State University, Portland, OR 97201 USA
| | - Christina E. Arens
- grid.64212.330000 0004 0463 2320Institute for Systems Biology, Seattle, WA 98109 USA
| | - Jacob J. Valenzuela
- grid.64212.330000 0004 0463 2320Institute for Systems Biology, Seattle, WA 98109 USA
| | - James Wilson
- grid.64212.330000 0004 0463 2320Institute for Systems Biology, Seattle, WA 98109 USA
| | - Kristopher A. Hunt
- grid.34477.330000000122986657Civil and Environmental Engineering, University of Washington, Seattle, WA 98195 USA
| | - Jessica Hardwicke
- grid.34477.330000000122986657Civil and Environmental Engineering, University of Washington, Seattle, WA 98195 USA
| | | | - Sujung Lim
- grid.20861.3d0000000107068890Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA 91125 USA
| | - Yee Mey Seah
- grid.462982.30000 0000 8883 2602Biological Sciences, University of Washington Bothell, Bothell, WA 98011 USA
| | - Ying Fu
- grid.266900.b0000 0004 0447 0018Institute for Environmental Genomics and Department of Microbiology & Plant Biology, University of Oklahoma, Norman, OK 73072 USA
| | - Liyou Wu
- grid.266900.b0000 0004 0447 0018Institute for Environmental Genomics and Department of Microbiology & Plant Biology, University of Oklahoma, Norman, OK 73072 USA
| | - Jizhong Zhou
- grid.266900.b0000 0004 0447 0018Institute for Environmental Genomics and Department of Microbiology & Plant Biology, University of Oklahoma, Norman, OK 73072 USA
| | - Kristina L. Hillesland
- grid.462982.30000 0000 8883 2602Biological Sciences, University of Washington Bothell, Bothell, WA 98011 USA
| | - David A. Stahl
- grid.34477.330000000122986657Civil and Environmental Engineering, University of Washington, Seattle, WA 98195 USA
| | - Nitin S. Baliga
- grid.64212.330000 0004 0463 2320Institute for Systems Biology, Seattle, WA 98109 USA
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7
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Correlational selection in the age of genomics. Nat Ecol Evol 2021; 5:562-573. [PMID: 33859374 DOI: 10.1038/s41559-021-01413-3] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2019] [Accepted: 02/11/2021] [Indexed: 02/01/2023]
Abstract
Ecologists and evolutionary biologists are well aware that natural and sexual selection do not operate on traits in isolation, but instead act on combinations of traits. This long-recognized and pervasive phenomenon is known as multivariate selection, or-in the particular case where it favours correlations between interacting traits-correlational selection. Despite broad acknowledgement of correlational selection, the relevant theory has often been overlooked in genomic research. Here, we discuss theory and empirical findings from ecological, quantitative genetic and genomic research, linking key insights from different fields. Correlational selection can operate on both discrete trait combinations and quantitative characters, with profound implications for genomic architecture, linkage, pleiotropy, evolvability, modularity, phenotypic integration and phenotypic plasticity. We synthesize current knowledge and discuss promising research approaches that will enable us to understand how correlational selection shapes genomic architecture, thereby linking quantitative genetic approaches with emerging genomic methods. We suggest that research on correlational selection has great potential to integrate multiple fields in evolutionary biology, including developmental and functional biology, ecology, quantitative genetics, phenotypic polymorphisms, hybrid zones and speciation processes.
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9
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Bautista C, Marsit S, Landry CR. Interspecific hybrids show a reduced adaptive potential under DNA damaging conditions. Evol Appl 2021; 14:758-769. [PMID: 33767750 PMCID: PMC7980265 DOI: 10.1111/eva.13155] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2020] [Accepted: 10/12/2020] [Indexed: 12/15/2022] Open
Abstract
Hybridization may increase the probability of adaptation to extreme stresses. This advantage could be caused by an increased genome plasticity in hybrids, which could accelerate the search for adaptive mutations. High ultraviolet (UV) radiation is a particular challenge in terms of adaptation because it affects the viability of organisms by directly damaging DNA, while also challenging future generations by increasing mutation rate. Here we test whether hybridization accelerates adaptive evolution in response to DNA damage, using yeast as a model. We exposed 180 populations of hybrids between species (Saccharomyces cerevisiae and Saccharomyces paradoxus) and their parental strains to UV mimetic and control conditions for approximately 100 generations. Although we found that adaptation occurs in both hybrids and parents, hybrids achieved a lower rate of adaptation, contrary to our expectations. Adaptation to DNA damage conditions comes with a large and similar cost for parents and hybrids, suggesting that this cost is not responsible for the lower adaptability of hybrids. We suggest that the lower adaptive potential of hybrids in this condition may result from the interaction between DNA damage and the inherent genetic instability of hybrids.
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Affiliation(s)
- Carla Bautista
- Institut de Biologie Intégrative et des Systèmes (IBIS)Université LavalQuébecQCCanada
- Département de BiologieFaculté des Sciences et de GénieUniversité LavalQuébecQCCanada
- Regroupement québécois de recherche sur la fonction, la structure et l'ingénierie des protéines (PROTEO)Université LavalQuébecQCCanada
- Centre de Recherche en Données Massives (CRDM)Université LavalQuébecQCCanada
| | - Souhir Marsit
- Institut de Biologie Intégrative et des Systèmes (IBIS)Université LavalQuébecQCCanada
- Département de BiologieFaculté des Sciences et de GénieUniversité LavalQuébecQCCanada
- Regroupement québécois de recherche sur la fonction, la structure et l'ingénierie des protéines (PROTEO)Université LavalQuébecQCCanada
- Centre de Recherche en Données Massives (CRDM)Université LavalQuébecQCCanada
| | - Christian R. Landry
- Institut de Biologie Intégrative et des Systèmes (IBIS)Université LavalQuébecQCCanada
- Département de BiologieFaculté des Sciences et de GénieUniversité LavalQuébecQCCanada
- Regroupement québécois de recherche sur la fonction, la structure et l'ingénierie des protéines (PROTEO)Université LavalQuébecQCCanada
- Centre de Recherche en Données Massives (CRDM)Université LavalQuébecQCCanada
- Département de Biochimie, de Microbiologie et de Bio‐informatiqueFaculté des Sciences et de GénieUniversité LavalQuébecQCCanada
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10
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Li T, Liu J, Feng J, Liu Z, Liu S, Zhang M, Zhang Y, Hou Y, Wu D, Li C, Chen Y, Chen H, Lu X. Variation in the life history strategy underlies functional diversity of tumors. Natl Sci Rev 2021; 8:nwaa124. [PMID: 34691566 PMCID: PMC8288455 DOI: 10.1093/nsr/nwaa124] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2019] [Revised: 05/12/2020] [Accepted: 05/14/2020] [Indexed: 12/27/2022] Open
Abstract
Classical r- vs. K-selection theory describes the trade-offs between high reproductive output and competitiveness and guides research in evolutionary ecology. While its impact has waned in the recent past, cancer evolution may rekindle it. Herein, we impose r- or K-selection on cancer cell lines to obtain strongly proliferative r cells and highly competitive K cells to test ideas on life-history strategy evolution. RNA-seq indicates that the trade-offs are associated with distinct expression of genes involved in the cell cycle, adhesion, apoptosis, and contact inhibition. Both empirical observations and simulations based on an ecological competition model show that the trade-off between cell proliferation and competitiveness can evolve adaptively. When the r and K cells are mixed, they exhibit strikingly different spatial and temporal distributions. Due to this niche separation, the fitness of the entire tumor increases. The contrasting selective pressure may operate in a realistic ecological setting of actual tumors.
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Affiliation(s)
- Tao Li
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650223, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jialin Liu
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jing Feng
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650223, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zhenzhen Liu
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Sixue Liu
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Minjie Zhang
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yuezheng Zhang
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China
| | - Yali Hou
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China
| | - Dafei Wu
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China
| | - Chunyan Li
- Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Medicine and Engineering and Key Laboratory of Big Data-Based Precision Medicine (Ministry of Industry and Information Technology), Beihang University, Beijing 100191, China
| | - Yongbin Chen
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650223, China
- University of Chinese Academy of Sciences, Beijing 100049, China
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Kunming 650223, China
| | - Hua Chen
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650223, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xuemei Lu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650223, China
- University of Chinese Academy of Sciences, Beijing 100049, China
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11
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Lin W, Su F, Lin M, Jin M, Li Y, Ding K, Chen Q, Qian Q, Sun X. Effect of microplastics PAN polymer and/or Cu 2+ pollution on the growth of Chlorella pyrenoidosa. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2020; 265:114985. [PMID: 32563949 DOI: 10.1016/j.envpol.2020.114985] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/24/2020] [Revised: 05/31/2020] [Accepted: 06/05/2020] [Indexed: 06/11/2023]
Abstract
Polyacrylonitrile polymer (PAN), a common representative textile material and a microplastic, has significant influence on phytoplankton algae, especially with co-exposure with other pollutants, e.g. Cu2+. In the present study, we carried out experiments to reveal the population size variation trends of Chlorella pyrenoidosa over time (during a whole growth cycle of 6 days) under PAN and/or Cu2+. The levels of pigments (chlorophyll a, b, total chlorophyll and carotenoids), chlorophyll a fluorescence parameters, and other physiological and biochemical indices, containing total protein measurements of H2O2, catalase (CAT), and malondialdehyde (MDA) under different treatment groups were measured to explain the physio-ecological mechanism of the effect of PAN and/or Cu2+ on the growth of C. pyrenoidosa. The results showed that PAN, Cu2+ and the combination of PAN and Cu2+ inhibited the growth of C. pyrenoidosa. Chlorophyll a and b decreased significantly with increasing levels of pollutants (PAN and/or Cu2+); however, the carotenoid levels increased with increasing levels of pollutants (PAN and/or Cu2+) for the first three cultivation days. The oxygen-evolving complexes (OECs) of C. pyrenoidosa had been damaged under Cu2+ pollution. The results also showed that CAT activity, MDA content and H2O2 activity of C. pyrenoidosa increased with increasing levels of pollutants (PAN and/or Cu2+); however, total protein content decreased with increasing levels of pollutants (PAN and/or Cu2+) at the first cultivation day. These results indicate that pollutants (PAN and/or Cu2+) are harmful to the growth of the C. pyrenoidosa population and negatively affect the levels and function of the pigments in C. pyrenoidosa by decreasing chlorophyll a and b levels, increasing carotenoid levels, and increasing antioxidant enzyme activity.
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Affiliation(s)
- Wei Lin
- College of Environmental Science and Engineering, Fujian Normal University, Fuzhou, Fujian Province, 350007, China; Fujian Provincial Key Lab of Coastal Basin Environment (Fujian Polytechnic Normal Univeristy), Fuqing, Fujian Province, 350300, China
| | - Fang Su
- Institute of Ocean Research, Fujian Polytechnic Normal Univeristy, Fuqing, Fujian Province, 350300, China; Fujian Provincial Key Lab of Coastal Basin Environment (Fujian Polytechnic Normal Univeristy), Fuqing, Fujian Province, 350300, China
| | - Maozi Lin
- Institute of Ocean Research, Fujian Polytechnic Normal Univeristy, Fuqing, Fujian Province, 350300, China; Fujian Provincial Key Lab of Coastal Basin Environment (Fujian Polytechnic Normal Univeristy), Fuqing, Fujian Province, 350300, China.
| | - Meifang Jin
- Institute of Ocean Research, Fujian Polytechnic Normal Univeristy, Fuqing, Fujian Province, 350300, China; Fujian Provincial Key Lab of Coastal Basin Environment (Fujian Polytechnic Normal Univeristy), Fuqing, Fujian Province, 350300, China
| | - Yuanheng Li
- Institute of Ocean Research, Fujian Polytechnic Normal Univeristy, Fuqing, Fujian Province, 350300, China; Fujian Provincial Key Lab of Coastal Basin Environment (Fujian Polytechnic Normal Univeristy), Fuqing, Fujian Province, 350300, China
| | - Kewu Ding
- Institute of Ocean Research, Fujian Polytechnic Normal Univeristy, Fuqing, Fujian Province, 350300, China; Fujian Provincial Key Lab of Coastal Basin Environment (Fujian Polytechnic Normal Univeristy), Fuqing, Fujian Province, 350300, China
| | - Qinhua Chen
- College of Environmental Science and Engineering, Fujian Normal University, Fuzhou, Fujian Province, 350007, China.
| | - Qingrong Qian
- College of Environmental Science and Engineering, Fujian Normal University, Fuzhou, Fujian Province, 350007, China
| | - Xiaoli Sun
- College of Environmental Science and Engineering, Fujian Normal University, Fuzhou, Fujian Province, 350007, China
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