Comparative Metabolomics Approach Detects Stress-Specific

Apr 19, 2018 - Sarcophyton ehrenbergi and S. glaucum soft corals are propagated in the aquarium facility of the Leibniz Centre for Tropical Marine Res...
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A comparative metabolomics approach detects stressspecific responses during coral bleaching in soft corals Mohamed A. Farag, Achim Meyer, Sara E. Ali, Mohamed A. Salem, Patrick Giavalisco, Hildegard Westphal, and Ludger A. Wessjohann J. Proteome Res., Just Accepted Manuscript • DOI: 10.1021/acs.jproteome.7b00929 • Publication Date (Web): 19 Apr 2018 Downloaded from http://pubs.acs.org on April 19, 2018

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A comparative metabolomics approach detects stress-specific responses during coral bleaching in soft corals Mohamed A. Farag1,2*, Achim Meyer3, Sara E. Ali4, Mohamed A. Salem1,5, Patrick Giavalisco5, Hildegard Westphal3,6, Ludger A. Wessjohann7** 1

Pharmacognosy department, College of Pharmacy, Cairo University, Cairo, Egypt, Kasr el Aini

st., P.B. 11562 2

Department of Chemistry, School of Sciences & Engineering, The American University in

Cairo (AUC), New Cairo 11835, Egypt. 3

Leibniz Centre for Tropical Marine Research (ZMT), Fahrenheit Str. 6, D-28359 Bremen,

Germany 4

Department of Pharmaceutical Biology, Faculty of Pharmacy & Biotechnology, The German

University in Cairo, Egypt 5

Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Golm, Potsdam,

Germany 6

Department of Geosciences, University of Bremen, 28359 Bremen, Germany

7

Leibniz Institute of Plant Biochemistry, Dept. Bioorganic Chemistry, Weinberg 3,

D-06120 Halle (Saale), Germany *Corresponding author: [email protected], [email protected] **Co-corresponding author: [email protected]

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ABSTRACT

Chronic exposure to ocean acidification and elevated sea-surface temperatures pose significant stress to marine ecosystems. This in turn necessitates costly acclimation responses in corals in both the symbiont and host, with a re-organization of cell metabolism and structure. A largescale untargeted metabolomics approach comprising gas chromatography mass spectrometry (GC-MS) and ultraperformance liquid chromatography coupled to high resolution mass spectrometry (UPLC–MS) was applied to profile the metabolite composition of the soft coral Sarcophyton ehrenbergi and its dinoflagellate symbiont. Metabolite profiling compared ambient conditions with response to simulated climate change stressors and with the sister species, S. glaucum. Among ca. 300 monitored metabolites, 13 metabolites were modulated. Incubation experiments providing four selected upregulated metabolites (alanine, GABA, nicotinic acid and proline) in the culturing water failed to subside the bleaching response at temperature-induced stress, despite their known ability to mitigate heat stress in plants or animals. Thus the results hint to metabolite accumulation (marker) during heat stress. This study provides the first detailed map of metabolic pathways transition in corals in response to different environmental stresses, accounting for the superior thermal tolerance of S. ehrenbergi versus S. glaucum which can ultimately help maintain a viable symbiosis and mitigate against coral bleaching.

Keywords: Bleaching; Sarcophyton; metabolomics; symbiosis; climate

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INTRODUCTION Coral reefs represent one of the biologically richest ecosystems on the planet which provide essential services (i.e., fisheries habitat, tourism, costal protection) to millions of people worldwide1-2. One of the most abundant soft coral genera on many coral reefs is Sarcophyton, which tends to form large monospecific carpets3. Soft corals are marine invertebrates with some taxa possessing endosymbiotic dinoflagellates of the genus Symbiodinium, also known as zooxanthellae, which provide photosynthates to the host coral tissue. The coral host, on the other hand, provides carbon dioxide (CO2) and nutrients in the form of waste products to the zooxanthellae4-5. A specific suite of associated microbes is also thought to contribute to these nutritional interactions, together with host and symbiont forming the coral ‘holobiont’6. Under suitable conditions, this efficient exchange of mobile compounds within the coral drives photosynthesis and nitrogen assimilation in the symbiont, and fuels growth, calcification and reproduction in the host7. Soft corals do not possess huge calcium carbonate skeletons, but secrete abundant and small (30ºC) was found to impact the lipidome of S. glaucum. Our data revealed that lipid metabolites accumulation patterns concur previous reports

54

affirming that elevated temperature leads to a decrease in FA levels viz. FA 20:4 (x0.55 fold

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decline), FA 24:4 (x0.18 fold decline), and MGDG 32:4 (x0.5 fold decline) (Fig. S4B, Table S2). One explanation for the decrease in FAs is that they function in cellular homeostasis by acting in anaplerotic pathways for energy production under stress conditions57-58. Shifts in TAG levels were also demonstrated in response to thermal stress. Albeit, contrasting accumulation patterns were observed for S. ehrenbergi versus S. glaucum (Fig. 6). Whereas, TAG levels declined in heat stressed S. ehrenbergi (Fig. S3), increase in TAGs viz. TAG 48:0 (x2 fold), TAG 48:2 (x1.9 fold), TAG 50:1 (x2.4 fold) and TAG 50:2 (x2 fold) was observed in S. glaucum upon high temperature treatment groups (>30 ºC) (Fig. S4B). In conclusion, compared to polar metabolites derived models (Fig. 3-5), discrimination of coral samples based on lipid profiles (Fig. S3&S4) was found less uniform. Our data suggest that corals shift primary and nitrogencontaining metabolites in a more predictable pattern in comparison to lipid compounds when responding to simulated stress events2. This could be attributed to higher energetic cost of lipid synthesis or a quicker regulation in amino acid metabolism2. Metabolic pathway analysis A large-scale untargeted metabolomics approach was applied to profile the intracellular polar and non-polar free metabolite pools, respectively, of each partner at ambient conditions and following exposure to thermal stress or high CO2 concentration over 4 days. These two stress factors represent a future scenario of simultaneous increases in sea-surface temperatures and ocean acidification. Our data revealed marked changes in the free metabolite pools of S. ehrenbergi “bleached” holobiont and its isolated zooxanthellae, as well as of S.glaucum, in response to simulated climate change conditions. A total of 13 potential bleaching indicative marker metabolites were identified in polar extracts of corals and their symbiont partners using GC-MS. These metabolites were mostly altered in

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response to both thermal stress or increased in CO2 levels suggestive that they may be regarded as biomarkers for stressors associated to climate change in nature. Identified metabolites included 7 amino acids (i.e. valine, proline, alanine, serine, isoleucine, glutamate and glutamine), 2 polyamines (i.e. guanidine and putrescine), 1 amine (i.e. β-ethanolamine), 1 non-protein amino acid (i.e. GABA), 1 organic acid (i.e. nicotinic acid) and 1 sugar (i.e. glucose), though content of the latter will likely be also guided a lot by photosynthesis conditions (light, availability of nutrients). Especially the amino acids (foremost proline vs. glutamate/glutamine), polyamines and for S. glaucum the nicotinic acid contents may serve as biomarkers. From the non-polar fraction of corals and zooxanthellae analyzed via UPLC-MS, 8 marker metabolites showing differential response were revealed including 5 TAGs viz.TAG 48:0, TAG 54:8, TAG 50:2, TAG 48:2, TAG 50:1, 2 FAs viz. FA 20:4C and FA 24:4 and 1 galactolipid viz. MGDG 32:4. In conclusion, changes in these metabolites reflect alterations in the activities of central metabolic pathways, such as energy metabolism and amino acids metabolism, in addition to those associated with nitrogen assimilation and metabolism, biosynthesis, cellular homeostasis and cell signaling. These shifts are likely due to the ongoing energetic costs associated with maintaining homeostasis under elevated temperature or high CO2 levels. These bleaching markers were subsequently mapped onto their respective metabolic pathways using Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database (Fig. 6). What needs more detailed future consideration is the role of these components and nitrogen flux: amino acids like proline and sugars with water can form eutectic mixtures and interact with proteins influencing cellular processes. Also, the nitrogen for the extra amino acids has to be provided.

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Assessment of amino acids and nitrogenous compounds effect in mitigating against coral bleaching The greatest metabolic changes occurring in corals with either thermal stress or elevated CO2 levels were associated with the accumulation of amino acids viz. alanine, proline, GABA and nitrogenous compounds viz. nicotinic acid. To determine whether these chemicals function as markers (indicator of heat stress) or additionally can mitigate coral bleaching, an assay was developed by applying them in coral tanks prior to bleaching induction. The dose of the potential effector chemicals: L-alanine, L-proline, nicotinic acid and GABA (4-aminobutyric acid) was set to 1 mM based on previous reports of being capable to elicit a metabolic response, without affecting photosynthesis in coral holobiont59. The amount of bleaching was approximated by chlorophyll extraction and further hemocytometer counts of released zooxanthellae. Comparing the effect of pooled chemicals with a single marker treatment on chlorophyll-a extraction values revealed low differences for corals grown at 28 ºC, 30 ºC and up to 32 ºC for all four tested chemicals; but a strong bleaching response was observed at corals incubated above 33ºC (Fig. S5) independent of the applied chemical. Thus, the provision of these chemicals within the culturing water of S. ehrenbergi did not mitigate stress resistance at higher temperatures in the bleaching experiments (Fig. S5) but this might be different in S. glaucum. Reports indicate enhanced stress tolerance when proline is supplied exogenously to plants at low concentrations44. In the current study, slightly lower bleaching rates were measured with six specimens incubated with proline and GABA. Thus, this first experiment guided the selection of proline and GABA for a second combined treatment applying hemocytometer cell counts and higher coral replication. Herein, zooxanthellae count of control samples revealed 1800-2800 expelled cells×coral-1d-1at 28 ºC and about tenfold increase to 15700-21500 cells×coral-1d-1 at

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34°C independent of the applied chemical (Fig. 7). Chlorophyll data offered lower resolution, but nevertheless detected strong bleaching events and were further monitored for 72h without changing this general pattern (Fig. S6). During this second run, wet weight was gained within the control incubation at 28°C, whereas other treatments showed weight loss during the experiment (Fig. S7). Remarkably, despite the multiple evidence of protective mechanisms by amino acid uptake60-61, S. ehrenbergi did not demonstrate a lowered bleaching response with the combined GABA proline incubation (Fig. 7), it even lost weight in the elicitor treatment at ambient temperatures

(Fig.

S7).

The outcome of this experiment is though rather limited by the degradation of amino acids in seawater, with the possibility that amino acids applied doses were altered upon heating. In this perspective, there seems to be inadequate evidence about the active uptake of amino acids from seawater. It is also possible that these amino acids are metabolized into other forms upon their uptake. To the best of our knowledge this is the first study aiming to also modulate the bleaching response in corals by chemical treatments, which could potentially have mitigated heat stress.

CONCLUSIONS Our results provide insights into the corals adaptation to environmental stress at the metabolite level and define biomarkers of stress in corals. The metabolic response of each partner was characterized to assess the unique response of each host/symbiont system to environmental stress. As suggested from coral metabolome coverage, exposure to thermal stress or high CO2 appears to mostly impact the energy metabolism and osmotic balance of soft corals through a generalized stress response. Hypotheses generated from this study will help to study and understand coral dynamics under future climate change conditions, as well as for the interpretation of metabolomic data as a biomarker of environmental stress with the ultimate goal 22 ACS Paragon Plus Environment

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of identifying the processes that can maintain or re-install a viable symbiosis and prevent or revert bleaching effects. Further studies that apply high resolution visualization of metabolite pools, such as nanoscale secondary ion mass spectrometry, coupled with stable isotope tracers will serve to provide further insight into the potential roles of free metabolites in different compartments of the holobiont and their origin. These data, coupled with the on-going outputs from rapidly developing ‘omics’ studies (i.e., genomics, transcriptomics and proteomics) will aid in further elucidating the metabolic cross-talk both within and between partners, which is essential for maintaining a functional holobiont.

SUPPORTING INFORMATION The

following

supporting

information

is

available

free

of

charge

at

ACS

website http://pubs.acs.org Figure S1 Bleaching effect occurring on S. ehrenbergi soft coral in response to thermal stress; Figure S2 GC/MS-based multivariate data analyses of zooxanthellae isolated from S. ehrenbergi subjected to thermal stress; Figure S3 UPLC/MS-based multivariate data analyses of S. ehrenbergi lipid metabolites subjected to thermal stress; Figure S4 UPLC/MS-based multivariate data analyses of S. glaucum lipid metabolites subjected to thermal stress; Figure S5 Chlorophyll-a data of released zooxanthellae post incubation with L-alanine, L-proline, GABA & nicotinic acid.; Figure S6 Cumulative chlorophyll-a data from released zooxanthellae; Figure S7 Gain and loss of wet weight of S. ehrenbergi corals incubated in treated and untreated seawater post 72 h of heat stress; Table S1 Metabolites fold change in polar extracts of S. ehrenbergi and S. glaucum following exposure to thermal stress or high CO2 concentration; Table S2 Metabolites fold change in nonpolar extracts of S. ehrenbergi and S. glaucum following exposure to thermal stress or high CO2 concentration AUTHOR INFORMATION Corresponding Author 23 ACS Paragon Plus Environment

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*E-mail: [email protected]. Phone: +20-1004142567

ACKNOWLEDGMENTS Dr. M. A. Farag thanks the Hanse-Wissenschaftskolleg (HWK), Germany, for financial support. The study was further supported by the Leibniz Center for Tropical Marine Research, Bremen, Germany and the Leibniz Institute of Plant Biochemistry, Halle Saale, Germany.

Figures 1-7 Fig. 1 Schematic diagram for study experimental design including 1) corals bleaching using heat and CO2 stress factors followed by 2) separation of zooxanthellae from coral, 3) metabolites profiling of polar and nonpolar fractions and finally 4) multivariate data analysis for samples classification and biomarkers identification.

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Fig. 2 Metabolites classes relative percentile in S. ehrenbergi and its zooxanthellae. Polar metabolites in S. ehrenbergi coral (A) and its isolated zooxanthellae (B) analyzed using GC-MS post silylation. Non-polar metabolites classes distribution percentile in S. ehrenbergi coral (C) and its isolated zooxanthellae (D) analyzed using UPLC-MS.

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Fig. 3 GC/MS-based multivariate data analyses of S. ehrenbergi subjected to an increase in temperature starting from 30 °C till 36 °C for a period of 24 h. (A) PCA Score plot of PC1 and PC2 scores (B) Loading plot for PC1 components contributing peaks and their assignments. GC/MS based orthogonal projection to latent structures-discriminant analysis (OPLS-DA) of S. ehrenbergi coral harvested at 30 °C, 32 °C ( ) modeled against those harvested at 34 °C, 36 °C ( ) (C) OPLS-DA score plot (D) loading S-plot derived from samples modeled against each other.

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Fig. 4 GC/MS-based multivariate data analyses of S. ehrenbergi subjected to an increase in CO2. Samples were collected over 4 days. (A) PCA Score plot of PC1 and PC2 scores (B) Loading plot for PC1 components contributing peaks and their assignments. GC/MS based orthogonal projection to latent structures-discriminant analysis (OPLS-DA) of S. ehrenbergi coral incubated at high CO2 levels and harvested at d1 ( ) modelled against those harvested at d2, d3 and d4 ( ) (C) OPLS-DA score plot (D) loading S-plot derived from samples modeled against each other.

PC2(30%)

PC1 (41%)

B

d1 d2, d3 & d4

C u[1]

d1 d2 d3 d4

A

t[1] Serine

D

β-ethanolamine

Proline

Proline

Alanine

Alanine

GABA

P(cor)[1]

PC2

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β-ethanolamine

p[1]

PC1

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Fig. 5 GC/MS-based multivariate data analyses of S. glaucum subjected to an increase in temperature starting from 30 °C till 34 °C for a period of 24 h. (A) Score plot of PC1 and PC2 scores (B) Loading plot for PC1 components contributing peaks and their assignments. GC/MS based orthogonal projection to latent structures-discriminant analysis (OPLS-DA) of S. glaucum coral harvested at 30 °C and 32 °C ( ) modeled against those harvested at

34 °C (

)

(A) OPLS-DA score plot (B) loading S-plot derived from samples modeled against each other.

30°C 32°C 34°C

30°C, 32°C 34°C

C u[1]

PC2(16%)

A

PC1 (47%)

t[1]

B Proline

Alanine

Glutamine

P(cor)[1]

Nicotinic acid Guanidine

Valine

p[1]

PC1

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Alanine Proline

D Glutamate

PC2

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Fig. 6 Metabolites altered in corals and harbored zooxanthellae in response to thermal stress or increased CO2 concentration. "

" denote increase or decrease in the levels of metabolites, respectively.

(*) illustrates variations observed in the levels of TAGs between S. ehrenbergi and S. glaucum.

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Fig. 7 Zooxanthellae counts revealed no mitigation of bleaching by proline and GABA incubations. Chlorophyll-a extraction values confirm general trends but give weak resolution. Data were sampled from released zooxanthellae between 24h and 48h of heat stress. Relative bleaching rates were calculated from coral nubbin 12 (rightmost specimen). Chlorophyll data of the complete 72h bleaching experiment is given in Fig. S6.

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35. Ali, S. E.; Farag, M. A.; Holvoet, P.; Hanafi, R. S.; Gad, M. Z., A Comparative Metabolomics Approach Reveals Early Biomarkers for Metabolic Response to Acute Myocardial Infarction. Scientific reports 2016, 6, 36359. 36. Paudel, G.; Bilova, T.; Schmidt, R.; Greifenhagen, U.; Berger, R.; Tarakhovskaya, E.; Stockhardt, S.; Balcke, G. U.; Humbeck, K.; Brandt, W.; Sinz, A.; Vogt, T.; Birkemeyer, C.; Wessjohann, L.; Frolov, A., Osmotic stress is accompanied by protein glycation in Arabidopsis thaliana. Journal of experimental botany 2016, 67 (22), 6283-6295. 37. Du, H.; Wang, Z.; Yu, W.; Liu, Y.; Huang, B., Differential metabolic responses of perennial grass Cynodon transvaalensisxCynodon dactylon (C(4)) and Poa Pratensis (C(3)) to heat stress. Physiologia plantarum 2011, 141 (3), 251-64. 38. Rosenblum, E. S.; Viant, M. R.; Braid, B. M.; Moore, J. D.; Friedman, C. S.; Tjeerdema, R. S., Characterizing the metabolic actions of natural stresses in the California red abalone, Haliotis rufescens using 1H NMR metabolomics. Metabolomics 2005, 1 (2), 199-209. 39. Hines, A.; Oladiran, G. S.; Bignell, J. P.; Stentiford, G. D.; Viant, M. R., Direct sampling of organisms from the field and knowledge of their phenotype: key recommendations for environmental metabolomics. Environ Sci Technol 2007, 41 (9), 3375-81. 40. Zhang, L.; Liu, X.; You, L.; Zhou, D.; Wu, H.; Li, L.; Zhao, J.; Feng, J.; Yu, J., Metabolic responses in gills of Manila clam Ruditapes philippinarum exposed to copper using NMR-based metabolomics. Marine environmental research 2011, 72 (1-2), 33-9. 41. Tuffnail, W.; Mills, G.; Cary, P.; Greenwood, R., An environmental 1H NMR metabolomic study of the exposure of the marine mussel Mytilus edulis to atrazine, lindane, hypoxia and starvation. Metabolomics 2009, 5 (1), 33-43. 42. Bowne, J. B.; Erwin, T. A.; Juttner, J.; Schnurbusch, T.; Langridge, P.; Bacic, A.; Roessner, U., Drought responses of leaf tissues from wheat cultivars of differing drought tolerance at the metabolite level. Molecular plant 2012, 5 (2), 418-29. 43. Taylor, N. L.; Heazlewood, J. L.; Day, D. A.; Millar, A. H., Lipoic acid-dependent oxidative catabolism of alpha-keto acids in mitochondria provides evidence for branched-chain amino acid catabolism in Arabidopsis. Plant physiology 2004, 134 (2), 838-48. 44. Hayat, S.; Hayat, Q.; Alyemeni, M. N.; Wani, A. S.; Pichtel, J.; Ahmad, A., Role of proline under changing environments: a review. Plant signaling & behavior 2012, 7 (11), 1456-66. 45. Groppa, M. D.; Benavides, M. P., Polyamines and abiotic stress: recent advances. Amino acids 2008, 34 (1), 35-45. 46. Kinnersley, A. M.; Turano, F. J., Gamma Aminobutyric Acid (GABA) and Plant Responses to Stress. Critical Reviews in Plant Sciences 2000, 19 (6), 479-509. 47. Muscatine, L.; Porter, J. W., Reef Corals: Mutualistic Symbioses Adapted to Nutrient-Poor Environments. Bioscience 1977, 27 (7), 454-460. 48. Kelecom, A., Secondary metabolites from marine microorganisms. Anais da Academia Brasileira de Ciencias 2002, 74 (1), 151-70. 49. Whitehead, L. F.; Douglas, A. E., Metabolite comparisons and the identity of nutrients translocated from symbiotic algae to an animal host. The Journal of experimental biology 2003, 206 (Pt 18), 3149-57. 50. Mia, O. H.; Kenneth, R. N. A.; Sean, R. C., Energetic cost of photoinhibition in corals. Marine Ecology Progress Series 2006, 313, 1-12. 51. Anthony, K. R.; Kline, D. I.; Diaz-Pulido, G.; Dove, S.; Hoegh-Guldberg, O., Ocean acidification causes bleaching and productivity loss in coral reef builders. Proceedings of the National Academy of Sciences of the United States of America 2008, 105 (45), 17442-6. 52. Mathesius, S.; Hofmann, M.; Caldeira, K.; Schellnhuber, H. J., Long-term response of oceans to CO2 removal from the atmosphere. Nature Climate Change 2015, 5, 1107. 34 ACS Paragon Plus Environment

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GRAPHICAL ABSTRACT "For TOC Only"

ͦC

PH

A b u n d a n ce

A b u n d a n ce

T IC : 0 3 0 4 0 2 0 4 .D

450000 400000

A b u n d a n c e

T IC : 0 3 0 4 0 2 0 4 .D

450000 350000 400000

A b u n d a n ce

300000

T I C :0 3 0 4 0 2 0 4 . D

4 5 0 0 0 0 350000 250000

A b u n d a n ce

4 0 0 0 0 0 300000 450000 3 5 0 0 0 0 250000 400000

450000

3 0 0 0 0 0 200000 350000

400000

2 5 0 0 0 0 150000 300000

T IC : 0 3 0 4 0 2 0 4 .D 200000 150000

50000

350000

2 0 0 0 0 0 100000 250000

300000

1 5 0 0 0 0 50000 200000 T im e --> 1 0 0 0 0 0 0 150000

250000 200000

100000

5 0 0 0 0 T im e -->

T IC : 0 3 0 4 0 2 0 4 .D

100000

0 2 0 .0 0

2 0 .0 0

2 5 .0 0

2 5 .0 0

3 0 .0 0

3 0 .0 0

3 5 .0 0

3 5 .0 0

4 0 .0 0

4 0 .0 0

4 5 .0 0

4 5 .0 0

5 0 .0 0

5 0 .0 0

5 5 .0 0

5 5 .0 0

6 0 .0 0

6 0 .0 0

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0 2 0 . 0 0 2 5 . 0 0 3 0 . 0 0 3 5 . 0 0 4 0 . 0 0 4 5 . 0 0 5 0 . 0 0 5 5 . 0 0 6 0 . 0 0 50000 100000 T im e > 0 2 0 .0 0 2 5 .0 0 3 0 .0 0 3 5 .0 0 4 0 .0 0 4 5 .0 0 5 0 .0 0 5 5 .0 0 6 0 .0 0 50000 T im e --> 0 2 0 .0 0 2 5 .0 0 3 0 .0 0 3 5 .0 0 4 0 .0 0 4 5 .0 0 5 0 .0 0 5 5 .0 0 6 0 .0 0 T im e -->

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