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1. PDBe-KB: a community-driven resource for structural and functional annotations

Author

Luxembourg Centre for Systems Biomedicine (LCSB): Bioinformatics Core (R. Schneider Group) [research center], Varadi, M., Berrisford, J., Deshpande, M., Nair, S. S., Gutmanas, A., Armstrong, D., Pravda, L., Al-Lazikani, B., Anyango, S., Barton, G. J., Berka, K., Blundell, T., Borkakoti, N., Dana, J., Das, S., Dey, S., Micco, P. D., Fraternali, F., Gibson, T., Helmer-Citterich, M., Hoksza, David, Huang, L. C., Jain, R., Jubb, H., Kannas, C., Kannan, N., Koca, J., Krivak, R., Kumar, M., Levy, E. D., Madeira, F., Madhusudhan, M. S., Martell, H. J., MacGowan, S., McGreig, J. E., Mir, S., Mukhopadhyay, A., Parca, L., Paysan-Lafosse, T., Radusky, L., Ribeiro, A., Serrano, L., Sillitoe, I., Singh, G., Skoda, P., Svobodova, R., Tyzack, J., Valencia, A., Fernandez, E. V., Vranken, W., Wass, M., Thornton, J., Sternberg, M., Orengo, C., Velankar, S., Luxembourg Centre for Systems Biomedicine (LCSB): Bioinformatics Core (R. Schneider Group) [research center], Varadi, M., Berrisford, J., Deshpande, M., Nair, S. S., Gutmanas, A., Armstrong, D., Pravda, L., Al-Lazikani, B., Anyango, S., Barton, G. J., Berka, K., Blundell, T., Borkakoti, N., Dana, J., Das, S., Dey, S., Micco, P. D., Fraternali, F., Gibson, T., Helmer-Citterich, M., Hoksza, David, Huang, L. C., Jain, R., Jubb, H., Kannas, C., Kannan, N., Koca, J., Krivak, R., Kumar, M., Levy, E. D., Madeira, F., Madhusudhan, M. S., Martell, H. J., MacGowan, S., McGreig, J. E., Mir, S., Mukhopadhyay, A., Parca, L., Paysan-Lafosse, T., Radusky, L., Ribeiro, A., Serrano, L., Sillitoe, I., Singh, G., Skoda, P., Svobodova, R., Tyzack, J., Valencia, A., Fernandez, E. V., Vranken, W., Wass, M., Thornton, J., Sternberg, M., Orengo, C., and Velankar, S.

Abstract

The Protein Data Bank in Europe-Knowledge Base (PDBe-KB, https://pdbe-kb.org) is a community-driven, collaborative resource for literature-derived, manually curated and computationally predicted structural and functional annotations of macromolecular structure data, contained in the Protein Data Bank (PDB). The goal of PDBe-KB is two-fold: (i) to increase the visibility and reduce the fragmentation of annotations contributed by specialist data resources, and to make these data more findable, accessible, interoperable and reusable (FAIR) and (ii) to place macromolecular structure data in their biological context, thus facilitating their use by the broader scientific community in fundamental and applied research. Here, we describe the guidelines of this collaborative effort, the current status of contributed data, and the PDBe-KB infrastructure, which includes the data exchange format, the deposition system for added value annotations, the distributable database containing the assembled data, and programmatic access endpoints. We also describe a series of novel web-pages—the PDBe-KB aggregated views of structure data—which combine information on macromolecular structures from many PDB entries. We have recently released the first set of pages in this series, which provide an overview of available structural and functional information for a protein of interest, referenced by a UniProtKB accession.

Published
2019

2. PDBe-KB: a community-driven resource for structural and functional annotations

Author

Luxembourg Centre for Systems Biomedicine (LCSB): Bioinformatics Core (R. Schneider Group) [research center], Varadi, M., Berrisford, J., Deshpande, M., Nair, S. S., Gutmanas, A., Armstrong, D., Pravda, L., Al-Lazikani, B., Anyango, S., Barton, G. J., Berka, K., Blundell, T., Borkakoti, N., Dana, J., Das, S., Dey, S., Micco, P. D., Fraternali, F., Gibson, T., Helmer-Citterich, M., Hoksza, David, Huang, L. C., Jain, R., Jubb, H., Kannas, C., Kannan, N., Koca, J., Krivak, R., Kumar, M., Levy, E. D., Madeira, F., Madhusudhan, M. S., Martell, H. J., MacGowan, S., McGreig, J. E., Mir, S., Mukhopadhyay, A., Parca, L., Paysan-Lafosse, T., Radusky, L., Ribeiro, A., Serrano, L., Sillitoe, I., Singh, G., Skoda, P., Svobodova, R., Tyzack, J., Valencia, A., Fernandez, E. V., Vranken, W., Wass, M., Thornton, J., Sternberg, M., Orengo, C., Velankar, S., Luxembourg Centre for Systems Biomedicine (LCSB): Bioinformatics Core (R. Schneider Group) [research center], Varadi, M., Berrisford, J., Deshpande, M., Nair, S. S., Gutmanas, A., Armstrong, D., Pravda, L., Al-Lazikani, B., Anyango, S., Barton, G. J., Berka, K., Blundell, T., Borkakoti, N., Dana, J., Das, S., Dey, S., Micco, P. D., Fraternali, F., Gibson, T., Helmer-Citterich, M., Hoksza, David, Huang, L. C., Jain, R., Jubb, H., Kannas, C., Kannan, N., Koca, J., Krivak, R., Kumar, M., Levy, E. D., Madeira, F., Madhusudhan, M. S., Martell, H. J., MacGowan, S., McGreig, J. E., Mir, S., Mukhopadhyay, A., Parca, L., Paysan-Lafosse, T., Radusky, L., Ribeiro, A., Serrano, L., Sillitoe, I., Singh, G., Skoda, P., Svobodova, R., Tyzack, J., Valencia, A., Fernandez, E. V., Vranken, W., Wass, M., Thornton, J., Sternberg, M., Orengo, C., and Velankar, S.

Abstract

The Protein Data Bank in Europe-Knowledge Base (PDBe-KB, https://pdbe-kb.org) is a community-driven, collaborative resource for literature-derived, manually curated and computationally predicted structural and functional annotations of macromolecular structure data, contained in the Protein Data Bank (PDB). The goal of PDBe-KB is two-fold: (i) to increase the visibility and reduce the fragmentation of annotations contributed by specialist data resources, and to make these data more findable, accessible, interoperable and reusable (FAIR) and (ii) to place macromolecular structure data in their biological context, thus facilitating their use by the broader scientific community in fundamental and applied research. Here, we describe the guidelines of this collaborative effort, the current status of contributed data, and the PDBe-KB infrastructure, which includes the data exchange format, the deposition system for added value annotations, the distributable database containing the assembled data, and programmatic access endpoints. We also describe a series of novel web-pages—the PDBe-KB aggregated views of structure data—which combine information on macromolecular structures from many PDB entries. We have recently released the first set of pages in this series, which provide an overview of available structural and functional information for a protein of interest, referenced by a UniProtKB accession.

Published
2019

3. Crop pests and predators exhibit inconsistent responses to surrounding landscape composition

Author

Karp, DS, Chaplin-Kramer, R, Meehan, TD, Martin, EA, DeClerck, F, Grab, H, Gratton, C, Hunt, L, Larsen, AE, Martinez-Salinas, A, O'Rourke, ME, Rusch, A, Poveda, K, Jonsson, M, Rosenheim, JA, Schellhorn, NA, Tscharntke, T, Wratten, SD, Zhang, W, Iverson, AL, Adler, LS, Albrecht, M, Alignier, A, Angelella, GM, Anjum, MZ, Avelino, J, Batary, P, Baveco, JM, Bianchi, FJJA, Birkhofer, K, Bohnenblust, EW, Bommarco, R, Brewer, MJ, Caballero-Lopez, B, Carriere, Y, Carvalheiro, LG, Cayuela, L, Centrella, M, Cetkovic, A, Henri, DC, Chabert, A, Costamagna, AC, De la Mora, A, de Kraker, J, Desneux, N, Diehl, E, Diekoetter, T, Dormann, CF, Eckberg, JO, Entling, MH, Fiedler, D, Franck, P, van Veen, FJF, Frank, T, Gagic, V, Garratt, MPD, Getachew, A, Gonthier, DJ, Goodell, PB, Graziosi, I, Groves, RL, Gurr, GM, Hajian-Forooshani, Z, Heimpel, GE, Herrmann, JD, Huseth, AS, Inclan, DJ, Ingrao, AJ, Iv, P, Jacot, K, Johnson, GA, Jones, L, Kaiser, M, Kaser, JM, Keasar, T, Kim, TN, Kishinevsky, M, Landis, DA, Lavandero, B, Lavigne, C, Le Ralec, A, Lemessa, D, Letourneau, DK, Liere, H, Lu, Y, Lubin, Y, Luttermoser, T, Maas, B, Mace, K, Madeira, F, Mader, V, Cortesero, AM, Marini, L, Martinez, E, Martinson, HM, Menozzi, P, Mitchell, MGE, Miyashita, T, Molina, GAR, Molina-Montenegro, MA, O'Neal, ME, Opatovsky, I, Ortiz-Martinez, S, Nash, M, Ostman, O, Ouin, A, Pak, D, Paredes, D, Parsa, S, Parry, H, Perez-Alvarez, R, Perovic, DJ, Peterson, JA, Petit, S, Philpott, SM, Plantegenest, M, Plecas, M, Pluess, T, Pons, X, Potts, SG, Pywell, RF, Ragsdale, DW, Rand, TA, Raymond, L, Ricci, B, Sargent, C, Sarthou, J-P, Saulais, J, Schackermann, J, Schmidt, NP, Schneider, G, Schuepp, C, Sivakoff, FS, Smith, HG, Whitney, KS, Stutz, S, Szendrei, Z, Takada, MB, Taki, H, Tamburini, G, Thomson, LJ, Tricault, Y, Tsafack, N, Tschumi, M, Valantin-Morison, M, Mai, VT, van der Werf, W, Vierling, KT, Werling, BP, Wickens, JB, Wickens, VJ, Woodcock, BA, Wyckhuys, K, Xiao, H, Yasuda, M, Yoshioka, A, Zou, Y, Karp, DS, Chaplin-Kramer, R, Meehan, TD, Martin, EA, DeClerck, F, Grab, H, Gratton, C, Hunt, L, Larsen, AE, Martinez-Salinas, A, O'Rourke, ME, Rusch, A, Poveda, K, Jonsson, M, Rosenheim, JA, Schellhorn, NA, Tscharntke, T, Wratten, SD, Zhang, W, Iverson, AL, Adler, LS, Albrecht, M, Alignier, A, Angelella, GM, Anjum, MZ, Avelino, J, Batary, P, Baveco, JM, Bianchi, FJJA, Birkhofer, K, Bohnenblust, EW, Bommarco, R, Brewer, MJ, Caballero-Lopez, B, Carriere, Y, Carvalheiro, LG, Cayuela, L, Centrella, M, Cetkovic, A, Henri, DC, Chabert, A, Costamagna, AC, De la Mora, A, de Kraker, J, Desneux, N, Diehl, E, Diekoetter, T, Dormann, CF, Eckberg, JO, Entling, MH, Fiedler, D, Franck, P, van Veen, FJF, Frank, T, Gagic, V, Garratt, MPD, Getachew, A, Gonthier, DJ, Goodell, PB, Graziosi, I, Groves, RL, Gurr, GM, Hajian-Forooshani, Z, Heimpel, GE, Herrmann, JD, Huseth, AS, Inclan, DJ, Ingrao, AJ, Iv, P, Jacot, K, Johnson, GA, Jones, L, Kaiser, M, Kaser, JM, Keasar, T, Kim, TN, Kishinevsky, M, Landis, DA, Lavandero, B, Lavigne, C, Le Ralec, A, Lemessa, D, Letourneau, DK, Liere, H, Lu, Y, Lubin, Y, Luttermoser, T, Maas, B, Mace, K, Madeira, F, Mader, V, Cortesero, AM, Marini, L, Martinez, E, Martinson, HM, Menozzi, P, Mitchell, MGE, Miyashita, T, Molina, GAR, Molina-Montenegro, MA, O'Neal, ME, Opatovsky, I, Ortiz-Martinez, S, Nash, M, Ostman, O, Ouin, A, Pak, D, Paredes, D, Parsa, S, Parry, H, Perez-Alvarez, R, Perovic, DJ, Peterson, JA, Petit, S, Philpott, SM, Plantegenest, M, Plecas, M, Pluess, T, Pons, X, Potts, SG, Pywell, RF, Ragsdale, DW, Rand, TA, Raymond, L, Ricci, B, Sargent, C, Sarthou, J-P, Saulais, J, Schackermann, J, Schmidt, NP, Schneider, G, Schuepp, C, Sivakoff, FS, Smith, HG, Whitney, KS, Stutz, S, Szendrei, Z, Takada, MB, Taki, H, Tamburini, G, Thomson, LJ, Tricault, Y, Tsafack, N, Tschumi, M, Valantin-Morison, M, Mai, VT, van der Werf, W, Vierling, KT, Werling, BP, Wickens, JB, Wickens, VJ, Woodcock, BA, Wyckhuys, K, Xiao, H, Yasuda, M, Yoshioka, A, and Zou, Y

Abstract

The idea that noncrop habitat enhances pest control and represents a win-win opportunity to conserve biodiversity and bolster yields has emerged as an agroecological paradigm. However, while noncrop habitat in landscapes surrounding farms sometimes benefits pest predators, natural enemy responses remain heterogeneous across studies and effects on pests are inconclusive. The observed heterogeneity in species responses to noncrop habitat may be biological in origin or could result from variation in how habitat and biocontrol are measured. Here, we use a pest-control database encompassing 132 studies and 6,759 sites worldwide to model natural enemy and pest abundances, predation rates, and crop damage as a function of landscape composition. Our results showed that although landscape composition explained significant variation within studies, pest and enemy abundances, predation rates, crop damage, and yields each exhibited different responses across studies, sometimes increasing and sometimes decreasing in landscapes with more noncrop habitat but overall showing no consistent trend. Thus, models that used landscape-composition variables to predict pest-control dynamics demonstrated little potential to explain variation across studies, though prediction did improve when comparing studies with similar crop and landscape features. Overall, our work shows that surrounding noncrop habitat does not consistently improve pest management, meaning habitat conservation may bolster production in some systems and depress yields in others. Future efforts to develop tools that inform farmers when habitat conservation truly represents a win-win would benefit from increased understanding of how landscape effects are modulated by local farm management and the biology of pests and their enemies.

Published
2018

4. Crop pests and predators exhibit inconsistent responses to surrounding landscape composition

Author

National Science Foundation (US), Karp, D.S., Chaplin-Kramer, R., Meehan, T. D., Martin, E. A., DeClerck, F., Grab, H., Gratton, C., Hunt, L., Larsen, A. E., Martínez-Salinas, A., O'Rourke, M. E., Rusch, A., Poveda, K., Jonsson, M., Rosenheim, J. A., Schellhorn, N. A., Tscharntke, T., Wratten, S. D., Zhang, W., Iverson, A. L., Adler, L. S., Albrecht, M., Alignier, A., Angelella, G. M., Anjum, M. Z., Avelino, J., Batáry, P., Baveco, J. M., Bianchi, F.J.J.A., Birkhofer, K., Bohnenblust, E. W., Bommarco, R., Brewer, M. J., Caballero-López, Berta, Carrière, Y., Carvalheiro, L.G., Cayuela, Luis, Centrella, M., Cetkovic, Aleksandar, Henri, D. C., Chabert, A., Costamagna, A. C., De la Mora, A., Kraker, Joop de, Desneux, N., Diehl, E., Diekötter, T., Dormann, C. F., Eckberg, J. O., Madeira, F., Paredes, Daniel, Pons, Xavier, National Science Foundation (US), Karp, D.S., Chaplin-Kramer, R., Meehan, T. D., Martin, E. A., DeClerck, F., Grab, H., Gratton, C., Hunt, L., Larsen, A. E., Martínez-Salinas, A., O'Rourke, M. E., Rusch, A., Poveda, K., Jonsson, M., Rosenheim, J. A., Schellhorn, N. A., Tscharntke, T., Wratten, S. D., Zhang, W., Iverson, A. L., Adler, L. S., Albrecht, M., Alignier, A., Angelella, G. M., Anjum, M. Z., Avelino, J., Batáry, P., Baveco, J. M., Bianchi, F.J.J.A., Birkhofer, K., Bohnenblust, E. W., Bommarco, R., Brewer, M. J., Caballero-López, Berta, Carrière, Y., Carvalheiro, L.G., Cayuela, Luis, Centrella, M., Cetkovic, Aleksandar, Henri, D. C., Chabert, A., Costamagna, A. C., De la Mora, A., Kraker, Joop de, Desneux, N., Diehl, E., Diekötter, T., Dormann, C. F., Eckberg, J. O., Madeira, F., Paredes, Daniel, and Pons, Xavier

Abstract

The idea that noncrop habitat enhances pest control and represents a win–win opportunity to conserve biodiversity and bolster yields has emerged as an agroecological paradigm. However, while noncrop habitat in landscapes surrounding farms sometimes benefits pest predators, natural enemy responses remain heterogeneous across studies and effects on pests are inconclusive. The observed heterogeneity in species responses to noncrop habitat may be biological in origin or could result from variation in how habitat and biocontrol are measured. Here, we use a pest-control database encompassing 132 studies and 6,759 sites worldwide to model natural enemy and pest abundances, predation rates, and crop damage as a function of landscape composition. Our results showed that although landscape composition explained significant variation within studies, pest and enemy abundances, predation rates, crop damage, and yields each exhibited different responses across studies, sometimes increasing and sometimes decreasing in landscapes with more noncrop habitat but overall showing no consistent trend. Thus, models that used landscape-composition variables to predict pest-control dynamics demonstrated little potential to explain variation across studies, though prediction did improve when comparing studies with similar crop and landscape features. Overall, our work shows that surrounding noncrop habitat does not consistently improve pest management, meaning habitat conservation may bolster production in some systems and depress yields in others. Future efforts to develop tools that inform farmers when habitat conservation truly represents a win–win would benefit from increased understanding of how landscape effects are modulated by local farm management and the biology of pests and their enemies.

Published
2018

5. Mechanical agitation induces counterintuitive aggregation of pre-dispersed carbon nanotubes

Author

Fernandes, Ricardo Madeira F., Buzaglo, M., Regev, O., Furó, Istvan, Marques, E. F., Fernandes, Ricardo Madeira F., Buzaglo, M., Regev, O., Furó, Istvan, and Marques, E. F.

Abstract

Mechanical agitation is commonly used to fragment and disperse insoluble materials in liquids. However, here we show that when pristine single-walled carbon nanotubes pre-dispersed in water are subject to vortex-shaking for very short periods (typically 10–60 s, power density ∼0.002 W mL−1), re-aggregation counterintuitively occurs. The initial dispersions are produced using surfactants as dispersants and powerful tip sonication (∼1 W mL−1) followed by centrifugation. Detailed imaging by light and electron microscopies shows that the vortex-induced aggregates consist of loose networks (1–102 μm in size) of intertwined tubes and thin bundles. The average aggregate size increases with vortexing time in an apparently logarithmic manner and depends on the dispersant used, initial concentration of nanotubes and size distribution of bundles. The aggregation is, nonetheless, reversible: if the vortex-shaken dispersions are mildly bath-sonicated (∼0.03 W mL−1), the flocs break down and re-dispersal occurs. Molecular insight for the mechanism behind this surprising phenomenon is put forth., QC 20170208

Published
2017
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