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Overpeck, Nature 421, 354 (2003). 20. J. U. L. Baldini, F. McDermott, I. J. Fairchild, Science 296, 2203 (2002). 21. D. R. Rousseau, R. Precce, N. Limondin, Geology 26, 651 (1998). 22. D. C. Barber et al., Nature 400, 344 (1999). 23. W. Wu, T. Liu, Quat. Int. 117, 153 (2004). 24. Y. T. Hong et al., Earth Planet. Sci. Lett. 211,371 (2003). 25. B. Peter, Science 292, 667 (2001). 26. Eighty-two time-points were selected using a crite- rion of QT10 ° fluctuation in atmospheric D 14 C for tuning. The tuned DA time scale is within the 230 Th dating error. The tuned age-depth relation remains smooth and is essentially the same as the 230 Th dated age-depth relation (Fig. 1B). 27. M. Stuiver, T. Braziunas, Holocene 3, 289 (1993). 28. D. T. Shindell, G. A. Schmidt, M. E. Mann, D. Rind, A. Waple, Science 294, 2149 (2001). 29. Supported by National Science Foundation of China grants 40225007 and 40328005, FANEDD 200227, National Basic Research Program of China 2004CB720204, U.S. NSF Grants 0214041, 0116395, and 023239, and Gary Comer Science and Education Foundation Grant CC8. The Minnesota authors thank G. Comer and W. S. Broecker for their generous support. Supporting Online Material www.sciencemag.org/cgi/content/full/308/5723/854/ DC1 Figs. S1 and S2 Tables S1 and S2 References 12 October 2004; accepted 3 March 2005 10.1126/science.1106296 Computational Thermostabilization of an Enzyme Aaron Korkegian, 1,2 Margaret E. Black, 4 David Baker, 3 Barry L. Stoddard 1 * Thermostabilizing an enzyme while maintaining its activity for industrial or biomedical applications can be difficult with traditional selection methods. We describe a rapid computational approach that identified three mutations within a model enzyme that produced a 10-C increase in apparent melting temperature T m and a 30-fold increase in half-life at 50-C, with no reduction in catalytic efficiency. The effects of the mutations were synergistic, giving an increase in excess of the sum of their individual effects. The redesigned en- zyme induced an increased, temperature-dependent bacterial growth rate under conditions that required its activity, thereby coupling molecular and meta- bolic engineering. Enzymes are the most efficient catalysts of chemical reactions known, enhancing reac- tion rates by as much as 23 orders of mag- nitude (1, 2). However, there has been little evolutionary pressure for them to become more thermostable than is required by their native environment. Many studies indicate that en- zymes (like most proteins) exhibit closely bal- anced free energy profiles for folding and unfolding, thereby allowing functionally impor- tant dynamic motions and appropriate degra- dation in vivo (3). However, in a laboratory or industrial setting, this lack of thermostability can lead to undesirable loss of activity (4). The physical principles of protein folding that result in a balance of stability and flexi- bility, while maintaining function, are not per- fectly understood and have been difficult to exploit for the development of thermostabilized enzymes (4). For hyperthermophiles, se- lective pressures have generated proteins with denaturation temperatures upwards of 110-C(5). Their proteins exhibit topologies and stabilizing interactions similar to those from mesophilic and thermophilic organisms (6, 7), leading to diverse hypotheses regarding their relative behaviors (8). However, a key mech- anism for thermostabilization appears to be the optimization of interactions between amino acids within a protein_score(5), complement- ing computational design methods that opti- mize a sequence for a given fold (9?13). The thermostabilization of an enzyme presents additional challenges for computa- tional protein design methods, because the active-site substrate geometry and the molec- ular dynamic behavior during an enzymatic reaction often appear fine-tuned for maxi- mum catalytic efficiency (2, 3). Therefore, the design method must be capable of predicting thermostabilizing mutations within a given fold while minimizing any shift in the back- bone that might structurally disrupt the active- site structure or quench its flexibility. In the past several years, methods for com- putational protein structure prediction and de- sign have improved substantially (10, 11, 14). Recently, computational design has been used successfully in thermostabilizing noncatalytic proteins (15?18), redesigning binding pockets (19?23), creating a protein fold (24), and de- signing catalytic activity into a bacterial recep- tor (25). We use the program RosettaDesign (26), which uses an energy function for eval- uating the fitness of a particular sequence for a given fold and a Metropolis Monte Carlo search algorithm for sampling sequence space. The program requires a backbone structure as input and generates sequences that have the lowest energy for that fold. We picked the homodimeric hydrolase en- zyme yeast cytosine deaminase (yCD), which converts cytosine to uracil, as a target for com- putational thermostabilization. yCD was cho- sen because its high-resolution crystal structure is available (27), its catalytic mechanism is well characterized (27), it is thermolabile (28, 29), and it has potential use in antitumor suicide gene applications (27, 29?31). As do many commercially useful enzymes, yCD displays irreversible unfolding behavior at high temper- atures (presumably because of aggregation) rather than the more simple, fully reversible be- havior common among model systems for the study of protein folding. The problems inherent in engineering such catalysts have been recently reviewed (4). We used computational redesign to predict a series of point mutations in the enzyme core that might lead to thermosta- bilization of the enzyme without losing cat- alytic efficiency. We then prepared a series of designed enzyme variants and determined their folded thermostability, catalytic behav- ior, ability to complement metabolic cytosine deaminase activity, and three-dimensional crystal structures. Our general computational strategy was largely unchanged from that described by Kuhlman and Baker (26, 32). An energy func- tion evaluated target sequences threaded onto a template backbone (12, 13, 26, 33). Sequence space was searched with an iterative Metrop- olis Monte Carlo procedure, starting with a random sequence, replacing a single amino acid rotamer with a rotamer from the Dunbrack backbone-dependent rotamer library (34), and reevaluating the energy. Sequences with lower energy were automatically adopted, whereas 1 Division of Basic Sciences, Fred Hutchinson Cancer Research Center (FHCRC), 1100 Fairview Avenue North, Seattle, WA 98109, USA. 2 Graduate Program in Molecular and Cellular Biology, 3 Department of Biochemistry and Howard Hughes Medical Institute, University of Washington, Seattle, WA 98195, USA. 4 Department of Pharmaceutical Sciences, College of Pharmacy, Washington State University, Pullman, WA 99164?6534, USA. *To whom correspondence should be addressed. E-mail: email@example.com R EPORTS www.sciencemag.org SCIENCE VOL 308 6 MAY 2005 857 sequences with higher energy were accepted with a probability based on the Metropolis criterion in order to prevent trapping in a local energy minimum. All residues directly involved in catalysis, those located within 4 ) of the active site, and those involved in the dimer interface were held fixed (fig. S1). The remaining 65 residues of the 153-residue monomer were included in the re- design, allowing them to be changed to any amino acid except cysteine. Thirty-three of the 65 residues subjected to redesign (49%) re- mained wild-type, a result similar to those of prior applications (18, 26). Sixteen of the point mutations suggested by the program were lo- cated on the surface of the protein and were not pursued, whereas the remainder were in the core. The core mutations could be further subdivided into two localized clusters of inter- acting residues, as well as four additional iso- lated point mutations (table S1) (22). Site-directed mutagenesis was used to gener- ate each of the two complete clusters of point mutations and the four individual mutations de- scribed above. Cluster 1, consisting of nine simul- taneous mutations packed between an a helix and several b-strands (including replacement of a buried salt-bridge), aggregated at concentra- tions above 0.4 mg/mL and was not char- acterized further. Cluster 2, consisting of four mutations packed between two a helices, remained soluble when concentrated to 20 mg/mL. Individual mutations from this cluster revealed that A23L and I140L (35)werekeyto the thermostabilization of the enzyme and were included in the final construct described below. Of the remaining four individual mutations, one (V108I) was also incorporated in the thermostabilized triple-mutant enzyme, whereas the remaining three (W10T, T67E, and E69L) were not as well behaved and were not characterized further. Both the double mu- tant (A23L/I140L) and the final triple mutant (A23L/I140L/V108I) were well behaved dur- ing expression and purification, more thermo- stable than the wild-type enzyme, and fully active (table S1) (22). We performed thermal denaturation experi- ments on all constructs using circular dichroism (CD) spectroscopy (Fig. 1A). Wild-type yCD and the redesigned mutants displayed largely reversible unfolding behavior over the range of temperatures examined; however, at higher tem- peratures, they unfolded irreversibly (36). We quantified the thermal stability of yCD and the mutant constructs by deriving an apparent melt- ing temperature (T m ) from the CD-unfolding curves. This value for the wild-type enzyme was determined to be 52-C. The isolated single mutations A23L, I140L, and V108I each slight- ly thermostabilized the enzyme, increasing the apparent T m by È2-C. However, simultaneous incorporation of all three mutations increased apparent T m to 62-C, 10-C higher than that of the wild type. Therefore, combination of in- dividual point mutations in a single construct produced a synergistic effect beyond their individual contributions. This result is not sim- ply due to the formation of contacts between redesigned residues, because residue 108 was physically separated from residues 23 and 140. The kinetic behavior of the wild-type en- zyme and the double and triple mutants was measured at 22-C to determine the effects of the mutations (Table 1 and fig. S2), as were their relative activities as a function of tem- perature (fig. S3). At 22-C, the wild-type en- zyme displays a turnover (k cat ) of 160 mol (mol enzyme) j1 s j1 and a Michaelis constant K m of 1.98 mM, and the double and triple mutants displayed a slightly reduced maximum rate V max coupled with a reduction in the K m . The catalytic efficiency of the enzyme mutants (expressed as the ratio k cat /K m ) was unchanged relative to the wild-type enzyme. The overall temperature activity profile was broadened, for the redesigned enzyme, with near?wild-type activity retained at lower temperatures and high- er activity above 50-C. The preservation of overall catalytic effi- ciency (achieved by reducing both k cat and K m , rather than by maximizing overall velocity) and the unusual change in shape and breadth of the enzyme_s thermal profile might suggest that the computational redesign generated muta- tions that natural or directed evolution pathways might not select, except perhaps as intermedi- ate species. Therefore, computational strategies for thermostabilization might offer a bonus of Fig. 1. Thermal dena- turation and activity half-life measurements. (A) Temperature melt measuring the change in signal at 220 nm over a range of temperatures. All constructs show a folded baseline followed by a sigmodial two-state transition to an unfolded baseline. Only data from 40- to 70- are shown; at lower temperatures, the baseline plateaus corre- spondedtoanassign- ment of 100% folded protein. (B)Activityde- cay at 50-C. Wild-type yCD and the double and triple mutant constructs were incubated at 50-C, and their activity was measured over time (32). The resulting curves gave half-lives for the enzymes at 50-Cof4 hours for the wild type (WT), 21 hours for the double mutant, and 117 hours for the triple mutant. Table 1. Kinetic behavior of wild-type and redesigned yCD catalysts. Both the double and triple mutants displayed a slightly reduced V max , coupled with a reduction in the Michaelis constant K m . The catalytic efficiency of the various enzyme mutants (expressed as the ratio k cat /K m ) was unchanged relative to the wild-type enzyme. M prod, molar concentration of product; enz, enzyme. Wild type Double mutant Triple mutant K m (mM) 1.98 1.50 1.33 V max (M prod s j1 ) 0.00016 0.00012 0.00011 k cat (M prod M enz j1 s j1 ) 160 120 110 k cat /K m (M enz j1 s j1 ) 80800 80000 82700 R EPORTS 6 MAY 2005 VOL 308 SCIENCE www.sciencemag.org858 selecting mutations that differ in these proper- ties, as compared to selection or redesign ex- periments based on natural selection. In order to visualize the time-dependent decay of activity at elevated temperatures, wild- type yCD and the double and triple mutants were incubated at 50-C, and the decrease in their relative activity was monitored over time (Fig. 1B). The wild-type enzyme showed a rapid loss of activity at 50-C, with a half-life of È4 hours. The double mutant displayed a half-life of È21 hours, whereas the triple mutant had a half-life at 50-CofÈ117 hours (a 30-fold increase over that of the wild type). In order to determine the effects of the mutations in vivo, a strain of Escherichia coli dependent on cytosine deaminase function for uracil synthesis was engineered and trans- formed with both wild-type and mutant yCD reading frames. Doubling times were then measured at 30-Cand37-C on minimal media lacking uracil (Fig. 2). The thermostabilized mutant construct induced slightly accelerated growth relative to the wild-type enzyme at 30-C and a clear acceleration at 37-C. This suggests that the properties of the engineered variants (a reduced K M and thermostabilization) measured in vitro correlate with improved enzyme flux in vivo under growth conditions limited by the activity of the enzyme. The crystal structures of both the double and triple mutants were solved to 1.9 ) and 1.7 ), respectively. The interpretation of den- sity around the redesigned regions of the protein core (in unbiased omit maps) was un- ambiguous (fig. S4). The root mean square deviation values comparing the wild-type en- zyme and both constructs were under 0.5 ) on all common a carbons and under 0.8 ) on all common atoms. Thus, the redesign and sub- sequent incorporation of point mutations in the enzyme core had a negligible effect on overall structure of the enzyme, including the active site (fig. S4). The redesigned, mutated resi- dues all appear to pack more tightly in the en- zyme core, with more surface area in contact with neighboring residues without altering the nearby side chain rotamers or backbone con- formation. Approximately 70 ) 2 of additional buried surface area is incorporated as a result of the three mutations Ebasedonananalysisof residue-by-residue packing, using the program NACCESS (37)^. The A23L/I140L double mutation increased the amount of hydropho- bic packing against a neighboring tyrosine ring (Fig. 3A), and the addition of V108I in the triple mutant added an additional methyl group to fill a cavity (Fig. 3B). The stabilized triple mutant was pieced together from part of a cluster of mutations predicted by the program and another single mutation predicted in a separate part of the core. Although the degree of thermostabiliza- tion produced by these mutations was relatively modest (an increase for T m of 2-C for the first change and 4-C for each subsequent mutation), there is no obvious reason why additional mu- tations predicted by the program could not be iteratively incorporated into the enzyme core, resulting in a panel of catalysts that display sequential increases in thermal stability. Not all mutations predicted by the program were equally thermostabilizing. Redesigns in- volving incorporation or alteration of polar or charged residues in the core (such as replace- ment of a buried salt-bridge in cluster 1 and individual mutations T67E, E69L, and W10T) were less successful than mutations involving substitution of one hydrophobic side chain for another. These latter mutations were predicted and observed to fill cavities within the core with additional van der Waals packing interactions. In future design efforts, selecting mutations of this type in silico may be most successful. Furthermore, modeling of interactions involv- ing buried polar and charged side chains in the enzyme core is an area for future development in computational redesign algorithms. References and Notes 1. V. L. Schramm, Annu. Rev. Biochem. 67, 693 (1998). 2. D. A. Kraut, K. S. Carroll, D. Herschlag, Annu. Rev. Biochem. 72, 517 (2003). 3. R. M. Daniel, R. V. Dunn, J. L. Finney, J. C. Smith, Annu. Rev. Biophys. Biomol. Struct. 32, 69 (2003). 4. V. G. Eijsink et al., J. Biotechnol. 113, 105 (2004). 5. R. Scandurra, V. Consalvi, R. Chiaraluce, L. Politi, P. C. Engel, Biochimie 80, 933 (1998). 6. M. K. Eidsness, K. A. Richie, A. E. Burden, D. M. Kurtz Jr., R. A. Scott, Biochemistry 36, 10406 (1997). 7. D. C. Rees, M. W. Adams, Structure 3, 251 (1995). 8. R. Sterner, W. Liebl, Crit. Rev. Biochem. Mol. Biol. 36, 39 (2001). 9. B. I. Dahiyat, S. L. Mayo, Science 278, 82 (1997). 10. A.G.Street,S.L.Mayo,Struct. Fold. Des. 7, R105 (1999). 11. C. M. Kraemer-Pecore, A. M. Wollacott, J. R. Desjarlais, Curr. Opin. Chem. Biol. 5, 690 (2001). 12. D. B. Gordon, S. A. Marshall, S. L. Mayo, Curr. Opin. Struct. Biol. 9, 509 (1999). 13. J. Mendes, R. Guerois, L. Serrano, Curr. Opin. Struct. Biol. 12, 441 (2002). 14. C. Venclovas, A. Zemla, K. Fidelis, J. Moult, Proteins 53 (suppl. 6), 585 (2003). 15. B. I. Dahiyat, Curr. Opin. Biotechnol. 10, 387 (1999). 16. P. Luo et al., Protein Sci. 11, 1218 (2002). 17. S. M. Malakauskas, S. L. Mayo, Nat. Struct. Biol. 5, 470 (1998). 18. G.Dantas,B.Kuhlman,D.Callender,M.Wong,D.Baker, J. Mol. Biol. 332, 449 (2003). 19. D. E. Benson, A. E. Haddy, H. W. Hellinga, Biochemistry 41, 3262 (2002). 20. J. Reina et al., Nat. Struct. Biol. 9, 621 (2002). 21. J. M. Shifman, S. L. Mayo, J. Mol. Biol. 323, 417 (2002). 22. D. T. Berg et al., Proc. Natl. Acad. Sci. U.S.A. 100, 4423 (2003). 23. L. L. Looger, M. A. Dwyer, J. J. Smith, H. W. Hellinga, Nature 423, 185 (2003). 24. B. Kuhlman et al., Science 302, 1364 (2003). 25. M. A. Dwyer, L. L. Looger, H. W. Hellinga, Science 304, 1967 (2004). 26. B. Kuhlman, D. Baker, Proc. Natl. Acad. Sci. U.S.A. 97, 10383 (2000). 27. G. C. Ireton, M. E. Black, B. L. Stoddard, Structure 11, 961 (2003). 28. T. Katsuragi, T. Sonoda, K. Matsumoto, T. Sakai, K. Tonomura, Agric. Biol. Chem. 53, 1313 (1989). Fig. 2. In vivo assay for meta- bolic growth phenotype showing bacterial growth curves in media conditions requiring cytosine de- aminase activity for generation of uracil (32). Both wild-type and reengineered mutants of yCD complement the bacterial activity; the thermostabilized en- zyme variant displayed a slight increase in growth rate at 30-C and a clear increase at 37-C. OD (600), optical density at 600 nm. Fig. 3. Structural analy- ses. (A) Van der Waals representation of resi- dues Y19, A23, Y26, and I140 in the wild- type yCD crystal struc- ture (left) and the same representation and orientation for the mutant construct with A23L and I140L muta- tions (right). (B)Van der Waals radii repre- sentation of the area around V108 in the wild-type structure (left) and a similar rep- resentation of the area around the V108I mu- tation in the triple mu- tant crystal structure. R EPORTS www.sciencemag.org SCIENCE VOL 308 6 MAY 2005 859 29. E. Kievit et al., Cancer Res. 59, 1417 (1999). 30. M. E. Black, Genet. Eng. (N.Y.) 23, 113 (2001). 31. O. Greco, G. U. Dachs, J. Cell. Physiol. 187, 22 (2001). 32. Materials and methods are available as supporting material on Science Online. 33. T. Lazaridis, M. Karplus, Proteins 35, 133 (1999). 34. R. L. Dunbrack Jr., F. E. Cohen, Protein Sci. 6, 1661 (1997). 35. Single-letter abbreviations for the amino acid residues are as follows: A, Ala; C, Cys; D, Asp; E, Glu; F, Phe; G, Gly; H, His; I, Ile; K, Lys; L, Leu; M, Met; N, Asn; P, Pro; Q, Gln; R, Arg; S, Ser; T, Thr; V, Val; W, Trp; and Y, Tyr. 36. A. Korkegian, M. E. Black, D. Baker, B. L. Stoddard, unpublished data. 37. S. J. Hubbard, J. M. Thornton, NACCESS (Department of Biochemistry and Molecular Biology, Univ. College London, 1993), available at http://wolf.bms.umist.ac.uk/naccess. 38. The authors acknowledge the assistance and advice of the Baker Laboratory in running RosettaDesign, the FHCRC structural biology program for assistance with data collection, and critiques and suggestions from R. Strong and A. Ferre-D?Amare. Funding was provided by NIH grant nos. GM49857 and CA97328 (B.L.S.), CA97328 and CA85939 (M.E.B.), GM59224 (D.B.), and T32-GM08268 (A.K.). Crystal structures of the yCD double and triple mutants have been submitted to the Research Collaboratory for Structural Bioinformatics Protein Databank with accession codes 1YSD and 1YSB, respectively. Supporting Online Material www.sciencemag.org/cgi/content/full/308/5723/857/ DC1 Materials and Methods Figs. S1 to S4 Table S1 References and Notes 10 November 2004; accepted 16 February 2005 10.1126/science.1107387 Swimming Against the Flow: A Mechanism of Zooplankton Aggregation Amatzia Genin, 1 * Jules S. Jaffe, 2 Ruth Reef, 1 Claudio Richter, 3 Peter J. S. Franks 2 Zooplankton reside in a constantly flowing environment. However, infor- mation about their response to ambient flow has remained elusive, because of the difficulties of following the individual motions of these minute, nearly transparent animals in the ocean. Using a three-dimensional acoustic imaging system, we tracked 9375,000 zooplankters at two coastal sites in the Red Sea. Resolution of their motion from that of the water showed that the animals effectively maintained their depth by swimming against upwelling and down- welling currents moving at rates of up to tens of body lengths per second, caus- ing their accumulation at frontal zones. This mechanism explains how oceanic fronts become major feeding grounds for predators and targets for fishermen. Buoyant phytoplankton and nonliving flotsam accumulate at the sea surface along conver- gent fronts because they remain afloat while the water submerges (1, 2). Accumulations at fronts have also been reported for zooplank- ton (3, 4); however, their aggregations often occur below the surface and at both conver- gent (downwelling) and divergent (upwelling) zones (5). Hardy (6) was the first to suggest that such patchiness must be caused by some dynamic principles involving zooplankton be- havior and water movement. A common, yet untested explanation for subsurface accumu- lations at frontal zones is that the animals actively swim against vertical currents in an attempt to maintain their depth (5, 7?10). Mod- els (7, 8) show that complete depth retention by zooplankton should generate increasingly dense accumulations, whereas partial reten- tion, due to fatigue or inability to match the velocity of the current, should lead to ephem- eral patches. Copepods can form fine-scale aggregations in layers where the turbulence velocity is substantially weaker than their typical swimming speed (11). Although diel vertical migrations are well known among zoo- plankton in response to seasonal cues, their behavioral response to ambient currents has not been demonstrated in the ocean, largely be- cause of the lack of a technology that can track in situ the motions of these small, nearly trans- parent organisms in a large volume of water. We tested the hypothesis that zooplankton swim against vertical currents by acoustically tracking animals while simultaneously measur- ing currents at two coastal sites in the northern Gulf of Aqaba, Red Sea (table S1). The sites experience persistent (hours-long) periods of upwelling and downwelling driven by differen- tial heating and cooling across the gradually sloping bottom (12, 13) and by the interaction between mesoscale currents and coastal topog- raphy. The three-dimensional trajectories of individual zooplankters as small as 1 mm in length were measured with FishTV-1.6 (FTV- 1.6), a new, high-frequency (1.6-MHz), multi- beam sonar (14), within volumes of water up to 3.8 m in length and 0.1 to 0.4 m in width (Fig. 1) (15). The sonar_s transducer, attached to a large submerged tripod (Fig. 1), was varied in depth and orientation among deployments (table S1). Three experiments using FTV-1.6 accomplished 274 tracking sessions, most of them acquiring 910 min of uninterrupted bioacoustic data at a rate of three Bframes[ per second, yielding a total of 375,171 tracks. The sessions were performed day and night under conditions of upwelling and downwelling currents (table S1). Vertical and horizontal currents at the depth of the insonified volume were measured nearby (G15 m) during each tracking session (Fig. 1) (15). The average vertical flow during the three experiments, approximately 1 cm/s, was 10 to 15% of the prevailing horizontal currents. Net tows near the insonified volume indi- cated that during the day, zooplankton assem- blages consisted mostly of pelagic species typical of the open waters of the Red Sea (16). At night, the emergence of demersal zooplank- ton doubled the zooplankton density (17). At all times, copepods were the dominant group (50 to 85% by number). Additional common taxa included mollusks, chaetognaths, and tu- nicates; and during the night, decapod larvae and other crustaceans. More than 70% of the targets recorded by FTV-1.6 had weak re- flectivity (G?80 dB referenced to 1 mPa at 1 m range), in agreement with the dominance in the net samples of small (G5 mm) zoo- plankton from the aforementioned taxa. Comparison of the tracks obtained from the sonar with the currents revealed that under both downwelling and upwelling condi- tions, the zooplankton swam against the ver- tical currents (Fig. 2 and Table 1). Complete depth retention, with a regression coefficient of ?1.0 between the zooplankton_s vertical swimming velocity (V z , relative to water) and the vertical current (V w ), was found in the first and second experiments; and nearly complete retention (V z 0 ?0.82 V w ) was found in the third experiment (Table 1). These results in- dicated that under strong vertical velocities, the small zooplankton recorded with FTV-1.6 swam vertically at velocities of 910 body lengths/s. In contrast, the animals_ mean hori- zontal displacement (H z ) was indistinguish- able from that of the current (H w ), with a regression coefficient of 1.0 (H z 0 H w ) in the first and second experiments, indicating that the animals were passively drifting with hori- zontal currents; and nearly so (H z 0 0.73 H w ) in the third experiment (Fig. 2). Planktonic organisms that maintain their depth are expected to accumulate where ver- tical currents persist (7, 8). Because shal- low downwelling and upwelling zones at the study sites were confined to near-shore waters (12, 13), a greater abundance of zooplankton was expected near the coast (movie S1). To test this prediction, we examined the distri- 1 The Interuniversity Institute for Marine Sciences and the Hebrew University, Eilat, Israel. 2 Scripps Institu- tion of Oceanography, La Jolla, CA, USA. 3 Center for Tropical Marine Ecology, Bremen, Germany. *To whom correspondence should be addressed. E-mail: firstname.lastname@example.org R EPORTS 6 MAY 2005 VOL 308 SCIENCE www.sciencemag.org860 857 857..860
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