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Changes in iTRAQ-based proteomic profiling of the cladoceran Daphnia magna exposed to microcystin-producing (MP) and microcystin-free (MF) Microcystis aeruginosa Kai Lyu, Qingguo Meng, Xuexia Zhu, Daoxin Dai, Lu Zhang, Yuan Huang, and Zhou Yang Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.6b00101 • Publication Date (Web): 08 Apr 2016 Downloaded from http://pubs.acs.org on April 17, 2016
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Changes in iTRAQ-based proteomic profiling of the cladoceran Daphnia magna
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exposed to microcystin-producing (MP) and microcystin-free (MF) Microcystis
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aeruginosa
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Kai Lyu, Qingguo Meng, Xuexia Zhu, Daoxin Dai, Lu Zhang, Yuan Huang, Zhou
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Yang*
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Jiangsu Key Laboratory for Biodiversity and Biotechnology, School of Biological
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Sciences, Nanjing Normal University, 1 Wenyuan Road, Nanjing 210023, China
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Address Correspondence to
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*Zhou Yang,
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Jiangsu Key Laboratory for Biodiversity and Biotechnology, School of Biological
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Sciences, Nanjing Normal University, 1 Wenyuan Road, Nanjing 210023, China
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E-mail:
[email protected] 15
Tel: +86-25-85891671
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Fax: +86-25-85891671
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ABSTRACT: Global warming and increased nutrient fluxes cause cyanobacterial
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blooms in freshwater ecosystems. These phenomena have increased the concern for
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human health and ecosystem services. The mass occurrences of toxic cyanobacteria
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strongly affect freshwater zooplankton communities, especially the unselective filter
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feeder Daphnia. However, the molecular mechanisms of cyanobacterial toxicity
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remain poorly understood. This study is the first to combine the established body
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growth rate (BGR), which is an indicator of life-history fitness, with differential
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peptide labeling (iTRAQ)-based proteomics in Daphnia magna influenced by
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microcystin-producing (MP) and microcystin-free (MF) Microcystis aeruginosa. A
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significant decrease in BGR was detected when D. magna was exposed to MP or MF
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M. aeruginosa. Conducting iTRAQ proteomic analysis, we successfully identified and
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quantified 211 proteins with significant changes in expression. A cluster of
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orthologous groups revealed that M. aeruginosa-affected differential proteins were
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strongly associated with lipid, carbohydrate, amino acid, and energy metabolism.
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There parameters could potentially explain the reduced fitness based on the cost of
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substance metabolism.
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Table of Contents Art
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INTRODUCTION
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With global warming and remarkable increase in nutrient fluxes, such as nitrates and
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phosphates from agricultural run-off, sewage treatment plants, and other
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anthropogenic sources, the number of cyanobacteria, including toxin-producing taxa,
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has possibly increased; thus, these organisms may pose threats to human and
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environmental health (reviewed by O’Neil, et al. 1). Cyanobacterial blooms can elicit
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detrimental effects on freshwater ecology, economy 2, and human health by altering
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the trophic structure and functionality 3, deoxygenating water columns to cause
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aquatic animal mortalities, and reducing water quality. As a toxin-producing
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cyanobacterium, Microcystis is a common bloom-forming genus. This genus is
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composed of microcystin-producing (MP) and microcystin-free (MF) strains, which
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are distinguished by a 55-kb microcystin synthetase gene cluster 4. Toxigenic (i.e. MP)
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and nontoxigenic (i.e. MF) species are involved in seasonal successions of bloom
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formation and bloom outbreak that vary among lakes 5. The concentration of the
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second metabolic product microcystins in the environment varies from traces amounts
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to 1800 µg L-1 or even higher immediately after the collapse of a highly toxic bloom 6.
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Thus far, more than 100 different microcystin congeners have been identified; these
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congeners mostly result from substitutions of the variable l-amino acids 7.
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Microcystin-LR is the most common and potent variant, followed by microcystin-RR
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and microcystin-YR. On the basis of the LD50 after microcysitns are intraperitoneally
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injected in mice, microcystin-LR with an LD50 value of 50 µg kg−1 is more toxic than 4
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microcystin-RR 8 at 500-800 µg kg−1 and microcystin-YR 8 at 150-200 µg kg−1. Daphnia is a key species in freshwater ecosystems 9. In cyanobacterial blooms,
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the transfer of energy from phytoplankton to Daphnia becomes inefficient because
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cyanobacteria interfere with filter feeding 10, 11, provide inadequate nutrition 12, 13, and
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produce toxic secondary metabolites 14. These factors can contribute to the reduced
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growth, inhibited reproduction, and Daphnia population decline; as a consequence,
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this phenomenon decreases the efficiency of energy transfer from primary producers
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to higher trophic levels 15. Moreover, microcystins may accumulate in primary
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consumers, such as Daphnia; thus, these toxins possibly transfer to higher levels of
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the aquatic food web and may reach humans 16.
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Molecular approaches in ecotoxicology have greatly contributed to the
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mechanistic understanding of the effects of aquatic pollutants on organisms. These
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approaches include high-throughput omics technologies 17. Holistic approaches have
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also been performed with the available transcriptome sequences to reveal the mRNA
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profile of Daphnia in response to Microcystis. Asselman et al. 18 identified four
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Microcystis-affected networks, namely, ribosome, oxidative phosphorylation,
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mitochondrial dysfunction, and protein export networks in Daphnia. The substance
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transportation pathway and energy production have been proposed as adaptive
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mechanisms that provide Daphnia with resistance to toxic cyanobacteria 19, 20.
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Asselman et al.21 further demonstrated that the poor nutritional quality among
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cyanobacterial species can be a potential primary cause of cyanobacterial effects on 5
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Daphnia. These findings are consistent with those described in previous studies 11, 22,
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cyanobacterial toxins are primary inducers of cyanobacterial toxicity. The underlying
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mechanisms of cyanobacterial effects on Daphnia have not been extensively
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addressed because mRNA levels sometimes may be inaccurate predictors of protein
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abundance 24-26. Meanwhile, proteins are the major determinants of biological
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functions in the actual phenotype of an organism; information on the functional
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protein populations should be obtained to understand the relationship between an
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organism and its environment. This understanding can be achieved by analyzing the
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proteome of exposed animals through proteomic technologies. Furthermore,
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molecular modes of toxic action in panoramic form can be potentially improved by
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the complementation of transcriptomics and proteomics.
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at the population level. However, this evidence does not support the hypothesis that
Proteomics is defined as the simultaneous analysis and quantification of cellular
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or extracellular protein abundance. Compared with transcriptomics, proteomics can
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provide functional mechanistic information because mRNA is a disposable message,
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and a limited amount of mRNA is translated into protein. Proteomic techniques can
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detect changes in protein activities determined as posttranslational modifications.
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Despite its advantages, proteomics faces several challenges in ecotoxicology. For
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example, proteomic data are largely dependent on the scale of protein databases;
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inadequate genome annotation lowers the significance of proteomic results 27. The
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direct linking of protein expression profiles to phenotypic and population-level effects 6
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are not easily built, and this drawback also limits transcriptomic analysis. iTRAQ labeling is an efficient quantitative proteomic technology that uses a
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family of isobaric isotope tags to label tryptic peptides from differential protein
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samples; this process is followed by liquid chromatography-tandem mass
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spectrometry (LC-MS/MS) analysis to identify and quantify proteins. The
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LC-MS/MS-based proteome profiling in Daphnia has demonstrated that
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high-throughput proteomics based on the Daphnia genome database is feasible 28.
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Mass spectrometry-based proteomics can be applied to investigate the cyanobacterial
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effects on a Daphnia model system and to elucidate the phenotypic role of functional
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proteins in tolerating toxic cyanobacteria in diet.
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Schwarzenberger et al. 29 reported that the increased proteases activity in
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Daphnia gut facilitated the capacity for protein digestion in the presence of dietary
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protease inhibitors, as a first attempt to explore the response mechanism to
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cyanobacteria at a protein level. The present study aimed to analyze the changes in the
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proteomic profile of Daphnia magna challenged by MP and MF M. aeruginosa. D.
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magna is the most common freshwater invertebrate model species used extensively to
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investigate ecotoxicity 30 because of its relatively high sensitivity to toxicants, rapid
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reproduction, and short lifespan. We examined the effects of dietary exposure to live
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M. aeruginosa cells instead of the effects of individually purified cyanobacterial
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toxins on the basis of previous findings 18. Moreover, studies on the response of
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Microcystis to feeding provide a realistic understanding of its impact on the 7
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environment. Body growth rate (BGR) was utilized as an agent of life-history fitness
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in the presence of MP and MF Microcystis. The animals were examined in terms of
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BGR and used for proteomic analysis. We determined the differentially expressed
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proteins in a pairwise manner because of different food sources. Subsequently, we
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then calculated the significantly affected cluster of orthologous groups (COG) of
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proteins. This study is the first to implement iTRAQ in LC-MS/MS-based proteomics
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to identify cyanobacterium-responsive proteins that mediate life-history changes in
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Daphnia, which can also verify the previous transcriptomic results 18. Furthermore,
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this study aimed to demonstrate how researchers can continue to ecologically improve
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D. magna genome annotation 31, which is characterized by a very high number of
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hypothetical proteins. Some hypothetical proteins may be significantly linked to
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environment-responsive trait variation, but their biological functions have not been
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confirmed in a Daphnia model. When a function of a hypothetical gene/protein is
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identified or when its link to a specific environmental variable (e.g., Microcystis
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exposure considered in this study) is established in the model organism (e.g.,
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Daphnia), the homologs of this gene/-protein in other species can be extensively
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analyzed for their relevance to similar environmental gradients.
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MATERIALS AND METHODS
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Animals and algal cultivation. A clonal culture of D. magna was provided by
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the State Key Laboratory of Pollution Control and Resource Reuse, Nanjing
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University (Nanjing, China) and has been maintained in the laboratory for more than 8
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ten years 14, 20. D. magna was cultured in clean tap water 19 and fed with Scenedesmus
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obliquus (FACHB-416; 1.5 mg C L−1) at 25 °C under fluorescent light at 40 mmol
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photons m−2 s−1 in a light-dark period of 14 h:10 h. The medium was gently aerated
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with filtered air for 24 h before use, and the animals were transferred to a new
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medium twice a week. Brood stocks were maintained at 50 females in 4 L.
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The high-quality alga S. obliquus, the MP M. aeruginosa strain PCC7806, and
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the MF M. aeruginosa strain FACHB-469 were obtained from the Freshwater Algae
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Culture Collection of the Institute of Hydrobiology at the Chinese Academy of
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Sciences. Both M. aeruginosa strains grow as single cells (5-6 µm diameter spheres)
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or paired cells and were chosen to prevent mechanical interference from large
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colonies that might influence Daphnia fitness. We also conducted a pilot experiment
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and confirmed through high-performance liquid chromatography (HPLC) 32 that M.
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aeruginosa PCC7806 produces two types of microcystin, namely, MC-LR and
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MC-RR, with 3.6 pg per cell. Three algal strains were stored in 1 L flasks, which
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contained 400 mL of BG-11 medium 33. The cultures were grown semi-continuously
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at 25 °C under fluorescent light at 40 µmol photons m−2 s−1 supplied in a 14 h:10 h
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light: dark cycle. The strains were harvested in the exponential stage and fed to
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Daphnia. Diet algal densities were determined with a blood cell counting chamber
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under an inverted Nikon microscope at a magnification of 400× and converted to the
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total organic carbon based on a previously developed calibration curve 20.
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Experimental design. The test animals were obtained from the third clutch of D. 9
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magna mothers. These animals were released within 12 h. Afterward, 20 neonates
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from each beaker were transferred to 1000 mL of tap water. These neonates were
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exposed to three different food treatments for 15 days at a total food concentration of
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1.5 mg C L−1: (1) 100% S. obliquus (hereafter labeled as SO); (2) a mixture of 50%
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MP M. aeruginosa + 50% S. obliquus (by carbon content; labeled as MP); and (3) a
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mixture of 50% MF M. aeruginosa + 50% S. obliquus (by carbon content; labeled as
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MF). Food and medium were replaced daily. The three food treatments comprised a
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total of nine biological replicates (three replicates per treatment) in a constant
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photoperiod of 14 h:10 h (light: dark) cycle and at a constant temperature of 25 °C.
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During the experiment, the pH of the medium was monitored at regular intervals and
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stabilized at 7.8±0.2. The BGR of D. magna was determined from the body dry
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weight of a subsample of the animals at the beginning and at the end of the
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experiment (15th day) according to the equation described in a previous study 34. Half
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of the D. magna individuals for BGR determination were quick-frozen after the
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measurements. These individuals were subjected to protein extraction, followed by
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proteomic analyses.
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Measurement of microcystin levels in exposed animals. The remaining D.
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magna individuals were used for microcystin measurement by HPLC 32 with some
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modification. In brief, D. magna were ground in 5 mL of 100% methanol, stirred, and
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left overnight to enable the complete extraction of the microcystins. The methanol
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extract was centrifuged at 9300 × g for 10 min. The supernatant was applied to a 10
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conditioned SPE cartridge (SepPak C18, Waters). The cartridge was first washed with
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5 mL methanol followed by 5 mL distilled water. Impurities were eluted with 2 mL
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methanol and MCs were eluted with 2 mL 80% (v/v) methanol. The eluate was
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analyzed by an Agilent HPLC 1100 system equipped with an ODS (Cosmosil
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5C18-AR, column 250 mm × 4.6 mm, Japan) kept at 40 °C. The mobile phases were
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composed of Milli-Q water containing 0.05% (v/v) trifluoracetic acid and
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HPLC-quality methanol, which were blended at a rate of 45:55 over 25 min. The flow
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rate was 1 mL min-1. The eluent was passed through a variable wavelength detector
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(VWD) operated at 238 nm and calculated against a standard curve with MC-LR and
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MC-RR (Express, China).
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Protein preparation. For each biological replicate of the food experiment, the
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quick-frozen animals from the three different food treatments were transferred into the
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lysis buffer (7 M Urea, 2 M Thiourea, 4% CHAPS, 40 mM Tris-HCl, pH 8.5, 1mM
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PMSF, 2mM EDTA) and sonicated in ice. The proteins were reduced with 10 mM
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DTT (final concentration) at 56 °C for 1 h and alkylated by 55 mM IAM (final
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concentration) in the darkroom for 1 h. The reduced and alkylated protein mixtures
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were precipitated by adding 4× volume of chilled acetone at -20 °C overnight. After
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centrifugation at 4 °C, 30,000 × g, the pellet was dissolved in 0.5 M TEAB
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(Applied Biosystems, Milan, Italy) and sonicated in ice. After centrifugation at 30,000
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× g at 4°C, an aliquot of the supernatant was taken to determine the protein
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concentration with a 2-D Quant Kit (GE Healthcare). The proteins in the supernatant 11
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were kept at -80°C for further analysis. iTRAQ labeling and SCX fractionation. The total protein (100 µg) was taken
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from each sample solution, and the protein was digested with Trypsin Gold (Promega,
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Madison, WI, USA) with a protein: trypsin = ratio of 30:1 at 37 °C for 16 hours. After
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trypsin digestion, peptides were dried by vacuum centrifugation, reconstituted in 0.5
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M TEAB, and processed according to the manufacturer’ s protocol for the 8-plex
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iTRAQ reagent (Applied Biosystems). More details of the iTRAQ labeling and SCX
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fractionation are provided in Supporting Information.
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LC-ESI-MS/MS analysis based on Triple TOF 5600. Each fraction was
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re-suspended in buffer A (5% ACN, 0.1%FA) and centrifuged at 20,000×g for 10 min;
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the average final peptide concentration was approximately 0.5 µg µl-1. Subsequently,
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10 µl of the supernatant was loaded in a LC-20AD nanoHPLC appartus (Shimadzu,
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Kyoto, Japan) by the autosampler onto a 2 cm C18 trap column. More details of the
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LC-ESI-MS/MS analysis are provided in Supporting Information.
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Database searches and analysis of identified proteins. Raw data files were
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acquired from the Orbitrap and converted into MGF files by Proteome Discoverer 1.2
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(PD 1.2, Thermo). These MGF files were searched. Protein identification was
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performed by the Mascot search engine (Matrix Science, UK). The search parameters
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included: Gln->pyro-Glu (N-term Q), Oxidation (M), and Deamidated (NQ) as the
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potential variable modifications, and Carbamidomethyl (C), iTRAQ8plex (N-term),
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and iTRAQ8plex (K) as the fixed modifications. The charge states of peptides were 12
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set to +2 and +3. iTRAQ data from three biological replicates were analyzed by the MASCOT
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2.3.02 software before protein identification was performed with Daphnia_nr which
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contained 30455 sequences
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(ftp://ftp.ensemblgenomes.org/pub/release-22/metazoa/fasta/daphnia_pulex/pep/;
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http://www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi? id=35525). To reduce
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the probability of false peptide identification, only peptides with significance scores
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(≥20) at the 99% confidence interval and a Mascot probability analysis greater than
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“identity” were counted as identified. The confident identification of each protein
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involved at least one unique peptide. For protein quantization, a protein must contain
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at least two unique peptides. The quantitative protein ratios were weighted and
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normalized by the median ratio in Mascot. We only used ratios with P 50%) was observed in MF and MP compared with SO
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(one-way ANOVA, F1,8: 42.107, P < 0.05; Fig. 1). We detected 67 ng of total
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microcystins per gram of D. magna after the 15-day exposure to MP M. aeruginosa.
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Proteomics in Daphnia. The MS/MS spectra were processed with the Mascot
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software. The iTRAQ analysis of D. magna global proteome revealed 7,511 peptides
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in the database (30,455 sequences) and generated 2,232 protein hits in Mascot. Fig. 2
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illustrates the cellular component determined through the GO analysis of the peptides.
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By performing GO analyses, we can categorize the differential proteins into several
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biological process categories, namely, cellular (16.38%), metabolic (14.38%), and
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single-organism (10.61%). We can also classify the proteins according to two
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regulatory stages (Fig. 3), namely, biological regulation (6.56%) and the regulation of
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biological process (5.77%). The major molecular functions of the proteins as obtained
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by GO analysis (Fig. 4) were binding (41.46%) and catalytic activity (41.99%). 14
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We assumed a 1.2-fold increase or decrease in protein expression as a benchmark
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of a significant physiological change. Two pairwise determinations were classified
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into MP/SO and MF/SO and presented in this study.
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A. MP/SO pairwise analysis
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iTRAQ analysis revealed that 94 proteins, including 24 upregulated proteins
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(Supporting Information, Table S1) and 70 downregulated proteins, were quantified
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and showed differential expression after D. magna were exposed to MP M.
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aeruginosa (Supporting Information, Table S2). Among the 24 upregulated proteins,
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10 proteins were involved in metabolism; these proteins included succinyl-CoA
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synthetase for energy production, glutamine-oxaloacetic transaminase for amino acid
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metabolism, protoporphyrinogen oxidase for coenzyme metabolism, and acetyl-CoA
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acetyltransferase for lipid metabolism. Furthermore, 7 proteins were classified as
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hypothetical. Meanwhile, 6 proteins were included in the category of cellular
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processes and signaling, including peroxiredoxin, glutathione S-transferase, and
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tubulin. Only 1 protein was associated with information storage and processing.
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Among the 70 downregulated proteins (Supporting Information, Table S2), 16
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were grouped under information storage and processing. Of these 16 proteins, 11 were
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ribosomal proteins with various subunits. Among the 70 downregulated proteins, 6
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proteins were associated with cellular processing and signaling, such as ABC
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transporter with a 0.66-fold change. Furthermore, 20 metabolism-related proteins
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were identified, including xanthine dehydrogenase for nucleotide metabolism, 15
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pyruvate dehydrogenase for energy production, and dihydropteridine reductase and
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aminopeptidase N for amino acid transport and metabolism. Only 26 of the
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downregulated proteins remained unknown after functional classification was
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performed.
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B. MF/SO pairwise analysis
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A total of 117 proteins were differentially expressed after D. magna were
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exposed to MF M. aeruginosa, including 50 upregulated proteins (Supporting
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Information, Table S3) and 67 downregulated proteins (Supporting Information, Table
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S4). Among the upregulated proteins, 11 proteins were involved in information
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storage and processing, including 7 ribosomal proteins with various subunits.
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Meanwhile, 7 upregulated proteins, such as peroxiredoxin with a 1.577-fold change
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and calponin with a 1.338-fold change, were associated with cellular processing and
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signaling. Furthermore, 9 upregulated proteins were implicated in metabolism and
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transportation, such as glycogen synthase and phosphomannomutase for carbohydrate
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metabolism and 4-aminobutyrate aminotransferase for amino acid metabolism.
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Alpha-spectrin, cuticle proteins, hemoglobin, and 23 other proteins were classified in
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a group without available COG IDs.
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Among the 67 downregulated proteins (Supporting Information, Table S4), the
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translation initiation factor-6 and an RNA-binding protein, were associated with
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information storage and processing; 10 were grouped within cellular processing and
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signaling; 33 were implicated in metabolism and transportation; and 29 were involved 16
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in lipid metabolism, energy production, carbohydrate metabolism, and amino acid
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metabolism. Although 21 proteins did not have an available COG ID, some of these
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proteins exhibited substantially reduced expression levels, such as the hypothetical
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proteins with accession numbers EFX61611, EFX72825, EFX79807, and EFX64299.
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DISCUSSION
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Anthropogenic eutrophication and global warming have altered the composition
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of phytoplankton communities into cyanobacterial populations 1, such as Microcystis.
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Some aquatic herbivores, such as copepods, facilitate cyanobacterial blooms because
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of their selective grazing on non-cyanobacterial prey 35. By contrast, Daphnia species
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are large generalist grazers that inevitably suffer from the harmful effects of
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Microcystis; as such, Daphnia species experience individual growth inhibition 36.
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Given that the BGR of Daphnia is highly correlated with fitness estimates 19, 37-38,
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we demonstrated that chronic dietary exposure to MP and MF Microcystis
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significantly affected the growth of individual Daphnia, as indicated by the reduced
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BGR (Fig. 1). The negative effects of harmful Microcystis on Daphnia can be
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attributed to the toxic effects of MCs 36, the low nutritional value of these cells 13, or
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the mechanical interference in the filtering structures of cladocerans caused by the
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colonial or thick filament morphologies of cyanobacteria 9. The Microcystis strains
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used in the present study primarily consisted of single cells; therefore, the observed
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fitness decrease after Daphnia species were exposed to Microcystis can be attributed
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to toxic substances or poor food quality rather than mechanical obstruction. 17
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This study was designed to explain the life-history changes of the important
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zooplankton Daphnia at the protein level in response to Microcystis, including MP
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and MF strains. Given the advances in analytical techniques, proteomic analysis has
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become a new frontier in molecular biology; this technique can be applied to
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determine the differences or changes in protein expression patterns of organs, cells, or
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subcellular compartments to a reasonably high level of coverage. Over the past few
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years, 2D differential in-gel electrophoresis (DIGE) is a quantitative proteomic
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method that has been successfully applied in Daphnia research which focused on
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predation risk 39-40, protein acetylation 41 and exposure to copper and paraquat 42. As
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an approach for quantifying changes with higher-throughput than DIGE, iTRAQ
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profiling is an emerging and useful technique to quantify changes in global-scale
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proteins (especially for less-abundant proteins) among individuals responsive to
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various environmental stressors 43-45. To the best of our knowledge, the present study
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is the first to use an iTRAQ approach to identify and quantify proteomes of
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zooplankton mobilized against environmental pollutants, even though iTRAQ was
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previously used to study anti-predation response in Daphnia 34. To acquire valuable
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evidence supporting the global-scale proteomic changes in Daphnia in response to
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cyanobacterial effects, we discussed our results in two pairwise comparisons, namely,
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MP/SO and MF/SO.
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Interpretation of differentially expressed proteins in MP/SO. Among the
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upregulated proteins associated with cellular processes and signaling (Supporting 18
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Information, Table S1), peroxiredoxin and glutathione S-transferase (GST) are
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antioxidant enzymes with important roles in protecting organisms against the toxicity
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of reactive oxygen species. Oxidative stress is a toxicological consequence of MC
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exposure in different organisms 46. Peroxiredoxin catalyzes the reduction of hydrogen
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peroxide, organic hydroperoxides, and peroxynitrites to less reactive products; thus,
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this enzyme is implicated in the first line of defense against oxidative stress and key
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apoptosis events 47, which are potentially caused by MCs 48. As a phase-II
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detoxification enzyme, GST has been identified as upregulated by MC exposure; this
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finding is consistent with previous studies, which revealed that an increase in GST
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gene expression is induced by the oxidative stress caused by the toxin 18 and the
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conjugation of MC with glutathione (GSH) during detoxification 49. Sadler and von
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Elert 50 investigated whether a cyanobacterial diet of the MP Microcystis causes the
366
biotransformation of MC conjugation products in a Daphnia clone in vivo; their group
367
found that GSTs in Daphnia are involved in oxidative stress response rather than in
368
the specific biotransformation of MCs conjugated with GSH. The increased GST and
369
peroxiredoxin in this study corresponded to the enhanced antioxidation ability of
370
Daphnia in response to cyanobacterial effects.
371
Serine/threonine protein kinase (STPK) is a sensor of the unfolded protein
372
response pathway; this enzyme plays a crucial role in the homeostatic regulation of
373
protein folding and in stress response to cope with an increased number of unfolded
374
proteins 51. Therefore, exposure to MP Microcystis possibly interfered with the normal 19
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modification of protein because higher STPK protein expression was induced by
376
Microcystis. However, transcriptome profiling revealed that the STPK gene
377
expression was inhibited in Daphnia fed with MP Microcystis18. This contradictory
378
result may be attributed to the increased MC content (80 ng > 67 ng in our study) that
379
accumulated in Daphnia. Alternatively, complicated and varied post-transcriptional
380
mechanisms involved in turning mRNA into protein may cause the absence of
381
positive correlation in protein abundance and mRNA expression levels 52. Therefore,
382
we cannot exclude the possibility that the down-regulated STPK gene expression is a
383
result of feedback control by sufficient levels of the STPK protein in the cell.
384
Ribosomal proteins were mostly identified in the information storage and processing
385
(Supporting Information, Table S2). These downregulated proteins were related to the
386
inhibited protein synthesis in Daphnia exposed to MP Microcystis; this finding has
387
been confirmed by transcriptomic analysis 18.
388
One of the cytotoxic events triggered by MC that was first to be described is
389
cytoskeleton disruption 53, which is a frequent reaction to toxic substances. The
390
microtubule dynamics in cells partially relies on tubulin post-translational
391
modifications, such as phosphorylation, which is controlled by the balance between
392
protein phosphatases and kinases. MCs are strong inhibitors of protein phosphatase 1
393
and 2A, which eventually cause the hyperphosphorylation of cytoskeletal proteins,
394
such as tubulin 54. Tubulin maintains the cellular architecture, internal organization,
395
cell shape, motility, cell division, and other processes 55. MCs may disrupt the 20
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cytoskeletal structure by directly binding to tubulin cysteine residues after toxins enter
397
cells. Ding et al. 56 reported the morphological changes in microtubules from evenly
398
distributed structures to dense aggregations after Daphnia was treated with
399
Microsystis extract. Our study revealed that the upregulated tubulin protein was
400
stimulated by Microsystis, thereby further suggesting that MP Microsystis affected the
401
quantitative changes in microtubules.
402
Some upregulated proteins, such as succinyl-CoA synthetase (SCS), are involved
403
in metabolism to enable Daphnia to cope with MP Microcystis. SCS is a
404
hydrogenosomal enzyme that catalyzes the formation of ATP via substrate-level
405
phosphorylation 57. The observed upregulation of SCS protein is related to cushion
406
energy deficiency in Daphnia exposed to MP Microcystis. Nevertheless, the number
407
of downregulated metabolic proteins was more than that of the upregulated proteins.
408
These downregulated proteins were involved in the metabolism of carbohydrates,
409
amino acids, lipids, and energy. Ribulose-5-phosphate 4-epimerase (RPE) is an
410
enzyme that catalyzes the interconversion of ribulose 5-phosphate and xylulose
411
5-phosphate in the oxidative phase of the pentose phosphate pathway (PPP) 58. As the
412
main product of PPP, nicotinamide adenine dinucleotide phosphate is essential for
413
lipid production. Therefore, the reduced RPE, which is induced by MP Microcystis,
414
may result in carbohydrate metabolism disturbances, lipid production inhibition, and
415
enhanced energy deficiency. Pyruvate dehydrogenase (PD), which synthesizes
416
high-energy compounds, such as ATP 59, is also required for glycolysis. We found that 21
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the presence of MP Microcystis downregulated PD protein expression; this finding
418
confirmed the potential energy deficiency.
419
Considering that MCs constitute a family of potent cyclic heptapeptide toxins 46,
420
we found that the degradation of heptapeptides that depends on amino acid
421
metabolism is a direct approach to buffer the cytotoxicity of MCs in exposed
422
individuals. Trypsin-like serine proteases are remarkably affected by MP Microcystis
423
with an approximately 0.3-fold change. A trypsin-like serine protease cleaves peptide
424
chains mainly at the carboxyl side of the amino acid lysine or arginine; this protease is
425
the major compound in the digestive system of amino acids in the Daphnia gut 60.
426
Czarnecki et al. 61 found a Microcystis-induced decrease in the trypsin activity of
427
Daphnia; this result is consistent with that obtained of our study. Aeruginosins are
428
toxins produced by M. aeruginosa 62; these toxins inhibit trypsin-like serine proteases
429
by directly interacting with proteins. A previous study19 suggested that the transport of
430
MCs out of a cell is carrier mediated and involves certain permeases. We also found a
431
decrease in the permease and ATPase components of Daphnia subjected to long-term
432
exposure to MP Microcystis. Therefore, the inhibited transport of MC out of cells and
433
the decreased degradation of MCs could increase the toxin accumulation in cells.
434
Interpretation of differentially expressed proteins in MF /SO. Although
435
studies on the interaction of Daphnia with MP Microcystis have been extensively
436
conducted, research on the interactions between MF Microcystis and Daphnia has
437
been rarely performed probably because of the lack of toxins. However, poor somatic 22
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growth, survival, and reproduction of Daphnia have been observed when the species
439
is cultured on mixtures containing good green algal food with MF Microcystis63.
440
Nutritional deficiency in some polyunsaturated fatty acids that essential for
441
zooplankton growth may also reduce the food quality of cyanobacteria64. By
442
considering the hypothesis related to fatty acids, Demott and Müller‐Navarra 65 found
443
that the growth rates of three Daphnia species are markedly reduced when these
444
species are fed with a MF cyanobacterium as a sole food source. However, growth is
445
promoted when an emulsion rich in omega-3 fatty acids is mixed with the
446
cyanobacterium. This finding suggests that Synechococcus lacks lipids that are
447
essential for Daphnia growth. Nevertheless, limited molecular evidence explains the
448
serious effects of toxin-lacking cyanobacterium on zooplankton.
449
In the present study, iTRAQ proteomic analysis was applied to investigate
450
potential protein changes in Daphnia exposed to MF Microcystis. Insufficient
451
essential lipids in the toxin-free cyanobacterium were considered as the main factor
452
contributing to the growth reduction of Daphnia. Therefore, the exposure to MF
453
Microcystis may trigger lipid metabolism dysfunction. Our proteomic results verified
454
our prediction that the four lipid-metabolic proteins are downregulated; by contrast,
455
no lipid-metabolic proteins are upregulated in Daphnia exposed to MF Microcystis
456
(Supporting Information, Table S4). Long-chain fatty acid-CoA ligase (also called
457
fatty acid acyl-CoA synthetase) play an essential role in lipid biosynthesis and fatty
458
acid degradation; this enzyme catalyzes the conversion of free fatty acids into fatty 23
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acyl-CoA esters 66. This reaction is essential for energy storage. The three remaining
460
lipid-metabolic proteins involved in the synthesis and degradation of ketone bodies
461
were also identified as 3-ketoacid CoA transferase, 3-hydroxyacyl-CoA
462
dehydrogenase, and acetyl-CoA acetyltransferase. The ketone body pathway is
463
normally used in mammals as an energy reserve when the citric acid cycle becomes
464
saturated with acetyl-CoA from fatty acid oxidation 67. In invertebrates, the
465
metabolism of ketone bodies has been poorly studied; in insects, the concentration of
466
acetoacetate increases after long periods of starvation, and ketone bodies are used as
467
an energy source for development 68. The low protein expression of 3-ketoacid CoA
468
transferase in Daphnia suggested that ketone bodies might be degraded; this finding
469
indicated a probable pathway that weakens energy production via the citric acid cycle.
470
In addition to lipid metabolic dysfunction-related proteins, the downregulation of
471
7 carbohydrate-metabolic proteins, such as hexokinase and
472
fructose-1,6-bisphosphatase was induced by MF Microcystis. Hexokinase catalyzes
473
the first step in the oxidative metabolism of hexoses via glycolysis.
474
Fructose-1,6-bisphosphatase is an enzyme that converts fructose-1,6-bisphosphate to
475
fructose-6-phosphate via gluconeogenesis. Glycolysis and gluconeogenesis achieve a
476
dynamic balance between the generation and utilization of glucose; these pathways
477
are also involved in energy production. Therefore, the low expression of
478
carbohydrate-metabolic proteins, together with lipid-metabolic proteins, indicated the
479
energy deficiency in Daphnia exposed to MF Microcystis. The proteins directly 24
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related to energy production exhibited reduced expression (Supporting Information,
481
Table S4). Among these energy-related enzymes, the enzyme lactate dehydrogenase
482
(LDH; converting pyruvate to lactate and vice versa) is involved in the supply or
483
storage of energy from carbohydrates. The decreased LDH activity was also found in
484
Daphnia exposed to MCs 69. These findings are consistent with those observed in our
485
study. However, we cannot assume that MF and MP Microcystis share the same
486
pathway that interrupts energy production in Daphnia because the energy-related
487
NAD-dependent aldehyde dehydrogenases was detected (Supporting Information,
488
Tables S2 and S4).
489
Interpretation of hypothetical proteins identified in pairwise MP/SO and
490
MF/SO. After the publication of the D. pulex genome 31, research on Daphnia has
491
provided new insights into the genome structure, function, and expression associated
492
with the variation in ecologically important traits. The partially annotated genome
493
information of D. magna and D. pulex facilitates the proteomic identification and
494
characterization of proteins by existing databases. However, we found that 36% of the
495
differentially expressed proteins were hypothetical proteins without verified
496
biological functions in vivo. Some of these hypothetical proteins showed significant
497
changes, such as EFX67764 (Supporting Information, Table S2) with 0.313-fold
498
change, EFX77516 (Supporting Information, Table S3) with 5-fold change and
499
EFX64299 (Supporting Information, Table S4) with 0.338-fold change. The
500
gene/protein functions and their relationship with phenotypes can be fully elucidated 25
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based on the the ecological context of organisms and natural selection. Thus, further
502
studies should be performed to confirm the ecological function of hypothetical
503
proteins. Hypothetical proteins with significant changes can be considered as
504
appropriate first targets.
505
In conclusion, this study described the large-scale effects of Microcystis on the
506
changes in the proteome of D. magna through a high-throughput iTRAQ labeling
507
quantitative technology. With this technology, 94 and 117 differentially expressed
508
proteins were determined after Daphnia was exposed to MP and MF Microcystis,
509
respectively. These proteins were mostly associated with lipid, carbohydrate, amino
510
acid, and energy metabolism. These proteins may correspond to changes in
511
metabolism necessary to adjust the BGR of Daphnia. In addition, hypothetical
512
proteins detected in the model organism Daphnia should also be considered to
513
enhance our understanding of their functionally explicit relationship with phenotypes
514
on the basis of environmental context.
515
ASSOCIATED CONTENT
516
Supporting Information Available
517
Details on iTRAQ labeling, SCX fractionation and LC-ESI-MS/MS analysis.
518
Table S1 describes the upregulated proteins in Daphnia magna fed with 50% S.
519
obliquus + 50% MP M. aeruginosa compared to those fed with 100% S. obliquus.
520
Table S2 describes the downregulated proteins in D. magna fed with 50% S. obliquus
521
+ 50% MP M. aeruginosa compared to those fed with 100% S. obliquus. Table S3 26
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describes the upregulated proteins in D. magna fed with 50% S. obliquus + 50% MF
523
M. aeruginosa compared to those fed with 100% S. obliquus. Table S4 describes the
524
downregulated proteins in D. magna fed with 50% S. obliquus + 50% MF M.
525
aeruginosa compared to those fed with 100% S. obliquus. This information is
526
available free of charge via the Internet at http://pubs.acs.org/.
527
NOTES
528
The authors declare no competing financial interest.
529
ACKNOWLEDGMENTS
530
We thank the three anonymous reviewers for their helpful comments. This study was
531
supported by the National Basic Research Program of China (2012CB956102), the
532
National Natural Science Foundation of China (31270504), NSFC for Talent Training
533
in Basic Science (J1103507), and the Priority Academic Program Development of
534
Jiangsu Higher Education Institutions.
535
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Figure Captions
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Figure 1. Changes in body growth rate (BGR) of Daphnia magna fed with different
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food treatments containing either 100% Scenedesmus obliquus (SO), 50% S. obliquus
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+ 50% microcystin-free Microcystis aeruginosa (MF), or 50% S. obliquus + 50%
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microcystin-producing M. aeruginosa (MP). Significant difference (P < 0.05) among
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treatment levels was detected by one-way ANOVA followed by Duncan’s multiple
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range test.
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Figure 2. Gene ontology (GO) analysis of the proteins of Daphnia magna in terms of
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cellular component.
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Figure 3. Gene ontology (GO) analysis of the proteins of Daphnia magna in terms of
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biological process.
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Figure 4. Gene ontology (GO) analysis of the proteins of Daphnia magna in terms of
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molecular function.
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Figure 1.
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Figure 2.
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Figure 3.
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Figure 4.
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