Bioinformatic Prohormone Discovery in Basal Metazoans: Insights from Trichoplax

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Ctenophores

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2757))

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Abstract

Experimental discovery of neuropeptides and peptide hormones is a long and tedious task. Mining the genomic and transcriptomic sequence data with robust secretory peptide prediction tools can significantly facilitate subsequent experiments. We describe the application of various in silico neuropeptide discovery methods for the placozoan Trichopax adhaerens as an illustrated example and a powerful experimental paradigm for cellular and evolutionary biology. In total, 33 placozoan (neuro)peptide-like hormone precursors were found using homology-based BLAST search and repeat-based and comparative evolutionary methods. Some of the discovered precursors are homologous to insulins and RFamide precursors from Cnidaria and other animal phyla.

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References

  1. Moroz LL, Romanova DY, Kohn AB (2021) Neural versus alternative integrative systems: molecular insights into origins of neurotransmitters. Philos Trans R Soc Lond Ser B Biol Sci 376:20190762

    Article  CAS  Google Scholar 

  2. Martinez P, Sprecher SG (2020) Of circuits and brains: the origin and diversification of neural architectures. Front Ecol Evol 8:82

    Article  Google Scholar 

  3. Jékely G (2021) The chemical brain hypothesis for the origin of nervous systems. Philos Trans R Soc Lond Ser B Biol Sci 376:20190761

    Article  Google Scholar 

  4. Arendt D (2021) Elementary nervous systems. Philos Trans R Soc Lond Ser B Biol Sci 376:20200347

    Article  Google Scholar 

  5. Srivastava M, Simakov O, Chapman J et al (2010) The Amphimedon queenslandica genome and the evolution of animal complexity. Nature 466:720–726

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Moroz LL, Kocot KM, Citarella MR et al (2014) The ctenophore genome and the evolutionary origins of neural systems. Nature 510(7503):109–114

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Ryan JF, Pang K, Schnitzler CE et al (2013) The genome of the ctenophore Mnemiopsis leidyi and its implications for cell type evolution. Science 342:1242592

    Article  PubMed  PubMed Central  Google Scholar 

  8. Srivastava M, Begovic E, Chapman J et al (2008) The Trichoplax genome and the nature of placozoans. Nature 454:955–960

    Article  CAS  PubMed  Google Scholar 

  9. Eitel M, Francis WR, Varoqueaux F et al (2018) Comparative genomics and the nature of placozoan species. PLoS Biol 16:e2005359

    Article  PubMed  PubMed Central  Google Scholar 

  10. Putnam NH, Srivastava M, Hellsten U et al (2007) Sea anemone genome reveals ancestral eumetazoan gene repertoire and genomic organization. Science 317:86–94

    Article  CAS  PubMed  Google Scholar 

  11. Leclère L, Horin C, Chevalier S et al (2019) The genome of the jellyfish Clytia hemisphaerica and the evolution of the cnidarian life-cycle. Nat Ecol Evol 3:801–810

    Article  PubMed  Google Scholar 

  12. Khalturin K, Shinzato C, Khalturina M et al (2019) Medusozoan genomes inform the evolution of the jellyfish body plan. Nat Ecol Evol 3:811–822

    Article  PubMed  Google Scholar 

  13. Voolstra CR, Li Y, Liew YJ et al (2017) Comparative analysis of the genomes of Stylophora pistillata and Acropora digitifera provides evidence for extensive differences between species of corals. Sci Rep 7:17583

    Article  PubMed  PubMed Central  Google Scholar 

  14. Veenstra JA (2011) Neuropeptide evolution: neurohormones and neuropeptides predicted from the genomes of Capitella teleta and Helobdella robusta. Gen Comp Endocrinol 171:160–175

    Article  CAS  PubMed  Google Scholar 

  15. Hayakawa E, Watanabe H, Menschaert G et al (2019) A combined strategy of neuropeptide prediction and tandem mass spectrometry identifies evolutionarily conserved ancient neuropeptides in the sea anemone Nematostella vectensis. PLoS One 14:e0215185

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Sachkova MY, Nordmann E-L, Soto-Àngel JJ et al (2021) Neuropeptide repertoire and 3D anatomy of the ctenophore nervous system. Curr Biol 31:5274–5285.e6

    Article  CAS  PubMed  Google Scholar 

  17. Koziol U, Koziol M, Preza M et al (2016) De novo discovery of neuropeptides in the genomes of parasitic flatworms using a novel comparative approach. Int J Parasitol 46:709–721

    Article  CAS  PubMed  Google Scholar 

  18. Toporik A, Borukhov I, Apatoff A et al (2014) Computational identification of natural peptides based on analysis of molecular evolution. Bioinformatics 30:2137–2141

    Article  CAS  PubMed  Google Scholar 

  19. Clynen E, Liu F, Husson SJ et al (2010) Bioinformatic approaches to the identification of novel neuropeptide precursors. In: Soloviev M (ed) Peptidomics: methods and protocols. Humana Press, Totowa, pp 357–374

    Chapter  Google Scholar 

  20. Karsenty S, Rappoport N, Ofer D et al (2014) NeuroPID: a classifier of neuropeptide precursors. Nucleic Acids Res 42:W182–W186

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Liu F, Baggerman G, D’Hertog W et al (2006) In silico identification of new secretory peptide genes in Drosophila melanogaster. Mol Cell Proteomics 5:510–522

    Article  CAS  PubMed  Google Scholar 

  22. McVeigh P, Mair GR, Atkinson L et al (2009) Discovery of multiple neuropeptide families in the phylum Platyhelminthes. Int J Parasitol 39:1243–1252

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Kamm K, Osigus H-J, Stadler PF et al (2018) Trichoplax genomes reveal profound admixture and suggest stable wild populations without bisexual reproduction. Sci Rep 8:11168

    Article  PubMed  PubMed Central  Google Scholar 

  24. Jansen E, Ayoubi TAY, Meulemans SMP et al (1995) Neuroendocrine-specific expression of the human prohormone convertase 1 Gene hormonal regulation of transcription through distinct cAMP responsive elements. J Biol Chem 270:15391–15397

    Article  CAS  PubMed  Google Scholar 

  25. Fricker LD (2005) Neuropeptide-processing enzymes: applications for drug discovery. AAPS J 7:E449–E455

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Seidah NG, Prat A (2012) The biology and therapeutic targeting of the proprotein convertases. Nat Rev Drug Discov 11:367–383

    Article  CAS  PubMed  Google Scholar 

  27. Van Bael S, Watteyne J, Boonen K et al (2018) Mass spectrometric evidence for neuropeptide-amidating enzymes in Caenorhabditis elegans. J Biol Chem 293:6052–6063

    Article  PubMed  PubMed Central  Google Scholar 

  28. Schierwater B, Osigus H-J, Bergmann T et al (2021) The enigmatic Placozoa part 1: exploring evolutionary controversies and poor ecological knowledge. BioEssays 43:2100080

    Article  Google Scholar 

  29. Schierwater B, Osigus H-J, Bergmann T et al (2021) The enigmatic Placozoa part 2: exploring evolutionary controversies and promising questions on earth and in space. BioEssays 43:2100083

    Article  Google Scholar 

  30. Fortunato A, Fleming A, Aktipis A et al (2021) Upregulation of DNA repair genes and cell extrusion underpin the remarkable radiation resistance of Trichoplax adhaerens. PLoS Biol 19:e3001471

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Anctil M (2009) Chemical transmission in the sea anemone Nematostella vectensis: a genomic perspective. Comp Biochem Physiol Part D Genomics Proteomics 4:268–289

    Article  PubMed  Google Scholar 

  32. Veenstra JA (2010) Neurohormones and neuropeptides encoded by the genome of Lottia gigantea, with reference to other mollusks and insects. Gen Comp Endocrinol 167:86–103

    Article  CAS  PubMed  Google Scholar 

  33. Husson SJ, Mertens I, Janssen T et al (2007) Neuropeptidergic signaling in the nematode Caenorhabditis elegans. Prog Neurobiol 82:33–55

    Article  CAS  PubMed  Google Scholar 

  34. Li C (2008) Neuropeptides. WormBook 25:1–36

    Google Scholar 

  35. Clynen E, Reumer A, Baggerman G et al (2010) Neuropeptide biology in Drosophila. Adv Exp Med Biol 692:192–210

    Article  CAS  PubMed  Google Scholar 

  36. Li B, Predel R, Neupert S et al (2008) Genomics, transcriptomics, and peptidomics of neuropeptides and protein hormones in the red flour beetle Tribolium castaneum. Genome Res 18:113–122

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Menschaert G, Vandekerckhove TTM, Baggerman G et al (2010) A hybrid, de novo based, genome-wide database search approach applied to the sea urchin neuropeptidome. J Proteome Res 9:990–996

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Sonmez K, Zaveri NT, Kerman IA et al (2009) Evolutionary sequence modeling for discovery of peptide hormones. PLoS Comput Biol 5:e1000258

    Article  PubMed  PubMed Central  Google Scholar 

  39. Delfino KR, Southey BR, Sweedler JV et al (2010) Genome-wide census and expression profiling of chicken neuropeptide and prohormone convertase genes. Neuropeptides 44:31–44

    Article  CAS  PubMed  Google Scholar 

  40. Petersen TN, Brunak S, Heijne G von et al (2011) SignalP 4.0: discriminating signal peptides from transmembrane regions. Nat Methods 8:785–786

    Article  CAS  PubMed  Google Scholar 

  41. Southey BR, Amare A, Zimmerman TA et al (2006) NeuroPred: a tool to predict cleavage sites in neuropeptide precursors and provide the masses of the resulting peptides. Nucleic Acids Res 34:W267–W272

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Hummon AB, Hummon NP, Corbin RW et al (2003) From precursor to final peptides: a statistical sequence-based approach to predicting prohormone processing. J Proteome Res 2:650–656

    Article  CAS  PubMed  Google Scholar 

  43. Nikitin M (2014) Bioinformatic prediction of Trichoplax adhaerens regulatory peptides. Gen Comp Endocrinol 212:145–155

    Article  PubMed  Google Scholar 

  44. Katoh K, Standley DM (2013) MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Mol Biol Evol 30:772–780

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Trifinopoulos J, Nguyen L-T, von Haeseler A et al (2016) W-IQ-TREE: a fast online phylogenetic tool for maximum likelihood analysis. Nucleic Acids Res 44:W232–W235

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Ofer D, Linial M (2014) NeuroPID: a predictor for identifying neuropeptide precursors from metazoan proteomes. Bioinformatics 30:931–940

    Article  CAS  PubMed  Google Scholar 

  47. Senatore A, Reese TS, Smith CL (2017) Neuropeptidergic integration of behavior in Trichoplax adhaerens, an animal without synapses. J Exp Biol 220:3381–3390

    Article  PubMed  PubMed Central  Google Scholar 

  48. Varoqueaux F, Williams EA, Grandemange S et al (2018) High cell diversity and complex peptidergic signaling underlie placozoan behavior. Curr Biol 28:3495–3501.e2

    Article  CAS  PubMed  Google Scholar 

  49. Gajewski M, Leitz T, Schloßherr J et al (1996) LWamides from Cnidaria constitute a novel family of neuropeptides with morphogenetic activity. Rouxs Arch Dev Biol 205:232–242

    Article  CAS  PubMed  Google Scholar 

  50. Pernet V, Anctil M, Grimmelikhuijzen CJP (2004) Antho-RFamide-containing neurons in the primitive nervous system of the anthozoan Renilla koellikeri. J Comp Neurol 472:208–220

    Article  CAS  PubMed  Google Scholar 

  51. Cropper EC, Tenenbaum R, Kolks MA et al (1987) Myomodulin: a bioactive neuropeptide present in an identified cholinergic buccal motor neuron of Aplysia. Proc Natl Acad Sci U S A 84:5483–5486

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Miller M, Beushausen S, Vitek A et al (1993) The myomodulin-related neuropeptides: characterization of a gene encoding a family of peptide cotransmitters in Aplysia. J Neurosci 13:3358–3367

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Chan SJ, Steiner DF (2000) Insulin through the ages: phylogeny of a growth promoting and metabolic regulatory hormone. Am Zool 40:213–222

    CAS  Google Scholar 

  54. McDougall C, Hammond MJ, Dailey SC et al (2018) The evolution of ependymin-related proteins. BMC Evol Biol 18:182

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgments

This work was supported by Russian Foundation for Basic Research #18–29-13014mk grant. This work was also supported in part by the Human Frontiers Science Program (RGP0060/2017) and National Science Foundation (IOS-1557923) grants to L.L.M. Research reported in this publication was also supported in part by the National Institute of Neurological Disorders and Stroke of the National Institutes of Health under Award Number R01NS114491 (to L.L.M). D.R. and M.A.N. were supported by the Russian Science Foundation grant (23-14-00050). The content is solely the authors’ responsibility and does not necessarily represent the official views of the National Institutes of Health.

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Correspondence to Leonid L. Moroz .

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Nikitin, M.A., Romanova, D.Y., Moroz, L.L. (2024). Bioinformatic Prohormone Discovery in Basal Metazoans: Insights from Trichoplax. In: Moroz, L.L. (eds) Ctenophores. Methods in Molecular Biology, vol 2757. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-3642-8_22

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  • DOI: https://doi.org/10.1007/978-1-0716-3642-8_22

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