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Cited by 14Enzyme Structure and FunctionEnzyme Catalysis and ImmobilizationLipid metabolism and biosynthesis

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Discovery of a non-canonical prototype long-chain monoacylglycerol lipase through a structure-based endogenous reaction intermediate complex

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Pinotsis, Nikos, Krüger, Anna, Tomas, Nicolas, Chatziefthymiou, Spyros D., Litz, Claudia, Mortensen, Simon Arnold, Daffé, Mamadou, Marrakchi, Hedia, Antranikian, Garabed, Wilmanns, Matthias·2023·Nature Communications
DOI 10.1038/s41467-023-43354-4PMC PMC10682391

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Abstract

The identification and characterization of enzyme function is largely lacking behind the rapidly increasing availability of large numbers of sequences and associated high-resolution structures. This is often hampered by lack of knowledge on in vivo relevant substrates. Here, we present a case study of a high-resolution structure of an unusual orphan lipase in complex with an endogenous C18 monoacylglycerol ester reaction intermediate from the expression host, which is insoluble under aqueous conditions and thus not accessible for studies in solution. The data allowed its functional characterization as a prototypic long-chain monoacylglycerol lipase, which uses a minimal lid domain to position the substrate through a hydrophobic tunnel directly to the enzyme’s active site. Knowledge about the molecular details of the substrate binding site allowed us to modulate the enzymatic activity by adjusting protein/substrate interactions, demonstrating the potential of our findings for future biotechnology applications.

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Research works printed but not linked: 55

  1. Jacobson, M. P., Kalyanaraman, C., Zhao, S. & Tian, B. Leveraging structure for enzyme function prediction: methods, opportunities, and challenges. Trends Biochem. Sci. 39, 363–371 (2014). · DOI
  2. Mills, C. L., Beuning, P. J. & Ondrechen, M. J. Biochemical functional predictions for protein structures of unknown or uncertain function. Comput Struct. Biotechnol. J. 13, 182–191 (2015). · DOI
  3. Bastard, K. et al. Revealing the hidden functional diversity of an enzyme family. Nat. Chem. Biol. 10, 42–49 (2014). · DOI
  4. Calhoun, S. et al. Prediction of enzymatic pathways by integrative pathway mapping. Elife 7, e31097 (2018). · DOI
  5. Zhao, S. et al. Discovery of new enzymes and metabolic pathways by using structure and genome context. Nature 502, 698–702 (2013). · DOI
  6. Carter, M. S. et al. Functional assignment of multiple catabolic pathways for D-apiose. Nat. Chem. Biol. 14, 696–705 (2018). · DOI
  7. Sévin, D. C., Fuhrer, T., Zamboni, N. & Sauer, U. Nontargeted in vitro metabolomics for high-throughput identification of novel enzymes in Escherichia coli. Nat. Methods 14, 187–194 (2017). · DOI
  8. Zhao, S. et al. Prediction and characterization of enzymatic activities guided by sequence similarity and genome neighborhood networks. Elife 3, e03275 (2014).
  9. Lee, C. W. et al. Structural basis for the ligand-binding specificity of fatty acid-binding proteins (pFABP4 and pFABP5) in gentoo penguin. Biochem. Biophys. Res. Commun. 465, 12–18 (2015). · DOI
  10. Lücke, C., Qiao, Y., van Moerkerk, H. T., Veerkamp, J. H. & Hamilton, J. A. Fatty-acid-binding protein from the flight muscle of Locusta migratoria: evolutionary variations in fatty acid binding. Biochemistry 45, 6296–6305 (2006). · DOI
  11. Vasiliauskaité-Brooks, I. et al. Structural insights into adiponectin receptors suggest ceramidase activity. Nature 544, 120–123 (2017). · DOI
  12. Rengachari, S. et al. Conformational plasticity and ligand binding of bacterial monoacylglycerol lipase. J. Biol. Chem. 288, 31093–31104 (2013). · DOI
  13. Kim, J. et al. Structure-guided discovery of the metabolite carboxy-SAM that modulates tRNA function. Nature 498, 123–126 (2013). · DOI
  14. Jaeger, K. E., Dijkstra, B. W. & Reetz, M. T. Bacterial biocatalysts: molecular biology, three-dimensional structures, and biotechnological applications of lipases. Annu. Rev. Microbiol. 53, 315–351 (1999). · DOI
  15. Labar, G., Wouters, J. & Lambert, D. M. A review on the monoacylglycerol lipase: at the interface between fat and endocannabinoid signalling. Curr. Med. Chem. 17, 2588–2607 (2010). · DOI
  16. Salhi, A., Carriere, F., Grundy, M. M. L. & Aloulou, A. Enzymes Involved in Lipid Digestion. In Bioaccessibility and Digestibility of Lipids from Food (eds. Grundy, M. M. L. & Wilde, P. J.) 3–28 (Springer International Publishing, Cham, 2021). · DOI
  17. Jaeger, K. E. & Eggert, T. Lipases for biotechnology. Curr. Opin. Biotechnol. 13, 390–397 (2002). · DOI
  18. Borrelli, G. M. & Trono, D. Recombinant lipases and phospholipases and their use as biocatalysts for industrial applications. Int. J. Mol. Sci. 16, 20774–20840 (2015). · DOI
  19. Anobom, C. D. et al. From structure to catalysis: recent developments in the biotechnological applications of lipases. Biomed. Res. Int. 2014, 684506 (2014). · DOI
  20. Reis, P., Watzke, H., Leser, M., Holmberg, K. & Miller, R. Interfacial mechanism of lipolysis as self-regulated process. Biophys. Chem. 147, 93–103 (2010). · DOI
  21. Aloulou, A. et al. Exploring the specific features of interfacial enzymology based on lipase studies. Biochim. Biophys. Acta 1761, 995–1013 (2006). · DOI
  22. Khan, F. I. et al. The lid domain in lipases: structural and functional determinant of enzymatic properties. Front. Bioeng. Biotechnol. 5, 16 (2017). · DOI
  23. Aschauer, P. et al. Crystal structure of the Saccharomyces cerevisiae monoglyceride lipase Yju3p. Biochim. Biophys. Acta 1861, 462–470 (2016). · DOI
  24. Bauer, T. L., Buchholz, P. C. F. & Pleiss, J. The modular structure of α/β-hydrolases. FEBS J. 287, 1035–1053 (2020). · DOI
  25. López-López, O., Cerdán, M. E. & González Siso, M. I. New extremophilic lipases and esterases from metagenomics. Curr. Protein Pept. Sci. 15, 445–455 (2014). · DOI
  26. Salameh, M. A. & Wiegel, J. Purification and characterization of two highly thermophilic alkaline lipases from Thermosyntropha lipolytica. Appl. Environ. Microbiol. 73, 7725–7731 (2007). · DOI
  27. Littlechild, J. A. Improving the ‘tool box’ for robust industrial enzymes. J. Ind. Microbiol. Biotechnol. 44, 711–720 (2017). · DOI
  28. Royter, M. et al. Thermostable lipases from the extreme thermophilic anaerobic bacteria Thermoanaerobacter thermohydrosulfuricus SOL1 and Caldanaerobacter subterraneus subsp. tengcongensis. Extremophiles 13, 769–783 (2009). · DOI
  29. Klingeberg, M., Hippe, H. & Antranikian, G. Production of novel pullulanases at high concentrations by two newly isolated thermophilic clostridia. FEMS Microbiol. Lett. 57, 145–152 (1990). · DOI
  30. Jørgensen, B. B. & Cohen, Y. Solar Lake (Sinai). 5. The sulfur cycle of the bcnthic cyanobacterial mats 1. Limnol. Oceanogr. 22, 657–666 (1977). · DOI
  31. Mirdita, M., Steinegger, M. & Söding, J. MMseqs2 desktop and local web server app for fast, interactive sequence searches. Bioinformatics 35, 2856–2858 (2019). · DOI · Paper page
  32. Holmquist, M. Alpha/Beta-hydrolase fold enzymes: structures, functions and mechanisms. Curr. Protein Pept. Sci. 1, 209–235 (2000). · DOI
  33. Reis, P., Holmberg, K., Watzke, H., Leser, M. E. & Miller, R. Lipases at interfaces: a review. Adv. Colloid Interface Sci. 147-148, 237–250 (2009). · DOI
  34. Fischer, F., Mutschler, J. & Zufferey, D. Enzyme catalysis with small ionic liquid quantities. J. Ind. Microbiol. Biotechnol. 38, 477–487 (2011). · DOI
  35. Winkler, U. K. & Stuckmann, M. Glycogen, hyaluronate, and some other polysaccharides greatly enhance the formation of exolipase by Serratia marcescens. J. Bacteriol. 138, 663–670 (1979). · DOI
  36. Barros, J. et al. Role of bifunctional ammonia-lyase in grass cell wall biosynthesis. Nat. Plants 2, 16050 (2016). · DOI
  37. Goldstone, D. C. et al. Structural and functional characterization of a promiscuous feruloyl esterase (Est1E) from the rumen bacterium Butyrivibrio proteoclasticus. Proteins 78, 1457–1469 (2010). · DOI
  38. Lai, K. K. et al. An inserted α/β subdomain shapes the catalytic pocket of Lactobacillus johnsonii cinnamoyl esterase. PLoS One 6, e23269 (2011). · DOI
  39. Nardini, M. & Dijkstra, B. W. Alpha/beta hydrolase fold enzymes: the family keeps growing. Curr. Opin. Struct. Biol. 9, 732–737 (1999). · DOI
  40. Scalvini, L., Piomelli, D. & Mor, M. Monoglyceride lipase: structure and inhibitors. Chem. Phys. Lipids 197, 13–24 (2016). · DOI
  41. Rypniewski, W. R., Holden, H. M. & Rayment, I. Structural consequences of reductive methylation of lysine residues in hen egg white lysozyme: an X-ray analysis at 1.8-A resolution. Biochemistry 32, 9851–9858 (1993). · DOI
  42. Mueller-Dieckmann, J. The open-access high-throughput crystallization facility at EMBL Hamburg. Acta Cryst. D62, 1446–1452 (2006).
  43. Otwinowski, Z. & Minor, W. Processing of X-ray diffraction data collected in oscillation mode. Macromol. Crystallogr. Pt A 276, 307–326 (1997). · DOI · Paper page
  44. Sheldrick, G. M. A short history of SHELX. Acta Crystallogr. A 64, 112–122 (2008). · DOI
  45. Terwilliger, T. C. et al. Iterative model building, structure refinement and density modification with the PHENIX AutoBuild wizard. Acta Crystallogr. Sect. D. 64, 61–69 (2008). · DOI · Paper page
  46. Langer, G., Cohen, S. X., Lamzin, V. S. & Perrakis, A. Automated macromolecular model building for X-ray crystallography using ARP/wARP version 7. Nat. Protoc. 3, 1171–1179 (2008). · DOI · Paper page
  47. Winn, M. D. et al. Overview of the CCP4 suite and current developments. Acta Crystallogr. D. Biol. Crystallogr. 67, 235–242 (2011). · DOI · Paper page
  48. Emsley, P. & Cowtan, K. Coot: model-building tools for molecular graphics. Acta Crystallogr. D. Biol. Crystallogr. 60, 2126–2132 (2004). · DOI · Paper page
  49. Vagin, A. & Teplyakov, A. Molecular replacement with MOLREP. Acta Crystallogr. D. Biol. Crystallogr. 66, 22–25 (2010). · DOI
  50. Afonine, P. V. et al. Towards automated crystallographic structure refinement with phenix.refine. Acta Crystallogr. D. Biol. Crystallogr. 68, 352–367 (2012). · DOI · Paper page
  51. Krissinel, E. & Henrick, K. Secondary-structure matching (SSM), a new tool for fast protein structure alignment in three dimensions. Acta Crystallogr. D. Biol. Crystallogr. 60, 2256–2268 (2004). · DOI
  52. Heier, C. et al. Identification of Yju3p as functional orthologue of mammalian monoglyceride lipase in the yeast Saccharomyces cerevisiae. Biochim Biophys. Acta 1801, 1063–1071 (2010). · DOI
  53. Lanéelle, M. A., Spina, L., Nigou, J., Lemassu, A. & Daffé, M. Lipid and lipoarabinomannan isolation and characterization. Methods Mol. Biol. 2314, 109–150 (2021). · DOI
  54. Kotov, V. et al. In-depth interrogation of protein thermal unfolding data with MoltenProt. Protein Sci. 30, 201–217 (2021). · DOI
  55. Provencher, S. W. & Glöckner, J. Estimation of globular protein secondary structure from circular dichroism. Biochemistry 20, 33–37 (1981). · DOI

Metadata

Authors
Pinotsis, N., Krüger, A., Tomas, N., Chatziefthymiou, S. D., Litz, C., Mortensen, S. A., Daffé, M., Marrakchi, H., Antranikian, G., & Wilmanns, M.
Affiliations
  • National and Kapodistrian University of Athens (GR)
  • Hamburg University of Technology (DE)
  • Centre National de la Recherche Scientifique (FR)
  • European Molecular Biology Laboratory (DE)
  • Universität Hamburg (DE)
Corresponding author
Wilmanns, Matthias
ORCID
Venue
Nature Communications
Publisher
Springer Science and Business Media LLC
Published
2023-11-27
Volume
14
Issue
1
Pages
7649-7649
ISSN
2041-1723 (ISSN-L)
DOI
10.1038/s41467-023-43354-4
PMC
PMC10682391
OpenAlex
W4389049710
Cited by
14
References
1
Citations by year
2026: 8 · 2025: 3 · 2024: 3
FWCI
1.03
Type
journal article
Language
en
Open access
Licence
Locations
  • Nature Communications (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
  • Research Square (acceptedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • UCL Discovery (University College London) (submittedVersion, cc-by)
  • HAL (submittedVersion, other-oa)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • tub.dok (Hamburg University of Technology) (submittedVersion, cc-by)
  • TUHH Open Research (cc-by)
Funders
  • European Molecular Biology Laboratory
  • European Synchrotron Radiation Facility
  • Centre National de la Recherche Scientifique
  • Westfälische Wilhelms-Universität Münster
  • Universität Hamburg
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Structural Biology › Enzyme Structure and Function
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Enzyme Catalysis and Immobilization
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Biochemistry › Lipid metabolism and biosynthesis
Keywords
enzyme-substrate complex, lid domain, hydrophobic tunnel, substrate binding site, protein-substrate interactions, enzyme activity modulation, biocatalysis
MeSH terms
Protein Domains, Lipase, Monoacylglycerol Lipases, Catalytic Domain

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