Diversity of the Antimicrobial Peptide Genes in Collembola
Abstract
:Simple Summary
Abstract
1. Introduction
2. Materials and Methods
2.1. Collembola Species and Genetic Data
2.2. Transcriptome Assembly
2.3. Identification of AMP Genes
2.4. Physicochemical Property and Functional Prediction
2.5. Phylogenetic Analysis
3. Results
3.1. Transcriptome Assembly
3.2. Overview of the Collembolan Candidate AMPs
3.3. Physicochemical Properties of Collembolan AMPs
3.4. Collembola AMP Family Description
3.4.1. Diapausin Family
3.4.2. Alo Peptide Family
3.4.3. Diptericin Family
3.4.4. Cecropin Family
3.4.5. Defensin Family
3.5. Functional Prediction
4. Discussion
4.1. Roles of Antimicrobial Peptides in Collembola Immunity
4.2. Evolution of Collembola AMPs
4.3. Significance and Implications
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Murray, C.J.; Ikuta, K.S.; Sharara, F.; Swetschinski, L.; Aguilar, G.R.; Gray, A.; Han, C.; Bisignano, C.; Rao, P.; Wool, E.; et al. Global Burden of Bacterial Antimicrobial Resistance in 2019: A Systematic Analysis. Lancet 2022, 399, 629–655. [Google Scholar] [CrossRef] [PubMed]
- O’Neill, J. Tackling Drug-Resistant Infections Globally: Final Report and Recommendations; Government of the United Kingdom: London, UK, 2016; Available online: https://wellcomecollection.org/works/thvwsuba (accessed on 10 December 2022).
- Talebi Bezmin Abadi, A.; Rizvanov, A.A.; Haertlé, T.; Blatt, N.L. World Health Organization Report: Current Crisis of Antibiotic Resistance. BioNanoScience 2019, 9, 778–788. [Google Scholar] [CrossRef]
- Marr, A.K.; Gooderham, W.J.; Hancock, R.E. Antibacterial Peptides for Therapeutic Use: Obstacles and Realistic Outlook. Curr. Opin. Pharmacol. 2006, 6, 468–472. [Google Scholar] [CrossRef] [PubMed]
- Browne, K.; Chakraborty, S.; Chen, R.; Willcox, M.D.; Black, D.S.; Walsh, W.R.; Kumar, N. A New Era of Antibiotics: The Clinical Potential of Antimicrobial Peptides. Int. J. Mol. Sci. 2020, 21, 7047. [Google Scholar] [CrossRef] [PubMed]
- Magana, M.; Pushpanathan, M.; Santos, A.L.; Leanse, L.; Fernandez, M.; Ioannidis, A.; Giulianotti, M.A.; Apidianakis, Y.; Bradfute, S.; Ferguson, A.L.; et al. The Value of Antimicrobial Peptides in the Age of Resistance. Lancet Infect. Dis. 2020, 20, e216–e230. [Google Scholar] [CrossRef]
- Rima, M.; Rima, M.; Fajloun, Z.; Sabatier, J.-M.; Bechinger, B.; Naas, T. Antimicrobial Peptides: A Potent Alternative to Antibiotics. Antibiotics 2021, 10, 1095. [Google Scholar] [CrossRef]
- Lazzaro, B.P.; Zasloff, M.; Rolff, J. Antimicrobial Peptides: Application Informed by Evolution. Science 2020, 368, eaau5480. [Google Scholar] [CrossRef]
- Le, C.-F.; Fang, C.-M.; Sekaran, S.D. Intracellular Targeting Mechanisms by Antimicrobial Peptides. Antimicrob. Agents Chemother. 2017, 61, e02340-16. [Google Scholar] [CrossRef]
- van Eijk, E.; Wittekoek, B.; Kuijper, E.J.; Smits, W.K. DNA Replication Proteins as Potential Targets for Antimicrobials in Drug-Resistant Bacterial Pathogens. J. Antimicrob. Chemother. 2017, 72, 1275–1284. [Google Scholar] [CrossRef]
- Struyfs, C.; Cammue, B.P.A.; Thevissen, K. Membrane-Interacting Antifungal Peptides. Front. Cell Dev. Biol. 2021, 9, 649875. [Google Scholar] [CrossRef]
- Hancock, R.E.W.; Haney, E.F.; Gill, E.E. The Immunology of Host Defence Peptides: Beyond Antimicrobial Activity. Nat. Rev. Immunol. 2016, 16, 321–334. [Google Scholar] [CrossRef]
- Jhong, J.-H.; Chi, Y.-H.; Li, W.-C.; Lin, T.-H.; Huang, K.-Y.; Lee, T.-Y. DbAMP: An Integrated Resource for Exploring Antimicrobial Peptides with Functional Activities and Physicochemical Properties on Transcriptome and Proteome Data. Nucleic Acids Res. 2019, 47, D285–D297. [Google Scholar] [CrossRef]
- Ratcliffe, N.A.; Mello, C.B.; Garcia, E.S.; Butt, T.M.; Azambuja, P. Insect Natural Products and Processes: New Treatments for Human Disease. Insect Biochem. Mol. Biol. 2011, 41, 747–769. [Google Scholar] [CrossRef]
- Brady, D.; Grapputo, A.; Romoli, O.; Sandrelli, F. Insect Cecropins, Antimicrobial Peptides with Potential Therapeutic Applications. Int. J. Mol. Sci. 2019, 20, 5862. [Google Scholar] [CrossRef]
- Cudic, M.; Condie, B.A.; Weiner, D.J.; Lysenko, E.S.; Xiang, Z.Q.; Insug, O.; Bulet, P.; Otvos, L. Development of Novel Antibacterial Peptides That Kill Resistant Isolates. Peptides 2002, 23, 2071–2083. [Google Scholar] [CrossRef]
- Buonocore, F.; Fausto, A.M.; Della Pelle, G.; Roncevic, T.; Gerdol, M.; Picchietti, S. Attacins: A Promising Class of Insect Antimicrobial Peptides. Antibiotics 2021, 10, 212. [Google Scholar] [CrossRef]
- Bulet, P.; Stöcklin, R.; Menin, L. Anti-Microbial Peptides: From Invertebrates to Vertebrates. Immunol. Rev. 2004, 198, 169–184. [Google Scholar] [CrossRef]
- Silva, P.M.; Gonçalves, S.; Santos, N.C. Defensins: Antifungal Lessons from Eukaryotes. Front. Microbiol 2014, 5, 97. [Google Scholar] [CrossRef]
- Mylonakis, E.; Podsiadlowski, L.; Muhammed, M.; Vilcinskas, A. Diversity, Evolution and Medical Applications of Insect Antimicrobial Peptides. Philos. Trans. R. Soc. B Biol. Sci. 2016, 371, 20150290. [Google Scholar] [CrossRef]
- Cipola, N.G.; da Silva, D.D.; Bellini, B.C. Chapter 2—Class Collembola. In Thorp and Covich’s Freshwater Invertebrates, 4th ed.; Hamada, N., Thorp, J.H., Rogers, D.C., Eds.; Academic Press: Cambridge, MA, USA, 2018; pp. 11–55. ISBN 978-0-12-804223-6. [Google Scholar]
- Faddeeva-Vakhrusheva, A.; Derks, M.F.L.; Anvar, S.Y.; Agamennone, V.; Suring, W.; Smit, S.; van Straalen, N.M.; Roelofs, D. Gene Family Evolution Reflects Adaptation to Soil Environmental Stressors in the Genome of the Collembolan Orchesella cincta. Genome Biol. Evol. 2016, 8, 2106–2117. [Google Scholar] [CrossRef]
- Coulibaly, S.F.M.; Winck, B.R.; Akpa-Vinceslas, M.; Mignot, L.; Legras, M.; Forey, E.; Chauvat, M. Functional Assemblages of Collembola Determine Soil Microbial Communities and Associated Functions. Front. Environ. Sci. 2019, 7, 52. [Google Scholar] [CrossRef]
- Broza, M.; Pereira, R.M.; Stimac, J.L. The Nonsusceptibility of Soil Collembola to Insect Pathogens and Their Potential as Scavengers of Microbial Pesticides. Pedobiologia 2001, 45, 523–534. [Google Scholar] [CrossRef]
- Dromph, K.M.; Vestergaard, S. Pathogenicity and Attractiveness of Entomopathogenic Hyphomycete Fungi to Collembolans. Appl. Soil Ecol. 2002, 21, 197–210. [Google Scholar] [CrossRef]
- Roelofs, D.; Janssens, T.K.S.; Timmermans, M.J.T.N.; Nota, B.; Mariën, J.; Bochdanovits, Z.; Ylstra, B.; Van Straalen, N.M. Adaptive Differences in Gene Expression Associated with Heavy Metal Tolerance in the Soil Arthropod Orchesella cincta. Mol. Ecol. 2009, 18, 3227–3239. [Google Scholar] [CrossRef]
- Faddeeva, A.; Studer, R.A.; Kraaijeveld, K.; Sie, D.; Ylstra, B.; Mariën, J.; Camp, H.O.D.; Datema, E.; Dunnen, J.T.D.; van Straalen, N.M.; et al. Collembolan Transcriptomes Highlight Molecular Evolution of Hexapods and Provide Clues on the Adaptation to Terrestrial Life. PLoS ONE 2015, 10, e0130600. [Google Scholar] [CrossRef]
- Kouno, T.; Mizuguchi, M.; Tanaka, H.; Yang, P.; Mori, Y.; Shinoda, H.; Unoki, K.; Aizawa, T.; Demura, M.; Suzuki, K.; et al. The Structure of a Novel Insect Peptide Explains Its Ca2+ Channel Blocking and Antifungal Activities. Biochemistry 2007, 46, 13733–13741. [Google Scholar] [CrossRef]
- Faddeeva-Vakhrusheva, A.; Kraaijeveld, K.; Derks, M.F.L.; Anvar, S.Y.; Agamennone, V.; Suring, W.; Kampfraath, A.A.; Ellers, J.; Le Ngoc, G.; van Gestel, C.A.M.; et al. Coping with Living in the Soil: The Genome of the Parthenogenetic Springtail Folsomia candida. BMC Genom. 2017, 18, 493. [Google Scholar] [CrossRef]
- Suring, W.; Meusemann, K.; Blanke, A.; Mariën, J.; Schol, T.; Agamennone, V.; Faddeeva-Vakhrusheva, A.; Berg, M.P.; The 1KITE Basal Hexapod Consortium; Brouwer, A.; et al. Evolutionary Ecology of Beta-Lactam Gene Clusters in Animals. Mol. Ecol. 2017, 26, 3217–3229. [Google Scholar] [CrossRef]
- Wu, C.; Jordan, M.; Newcomb, R.; Gemmell, N.; Bank, S.; Meusemann, K.; Dearden, P.; Duncan, E.; Grosser, S.; Rutherford, K.; et al. Analysis of the Genome of the New Zealand Giant Collembolan (Holacanthella duospinosa) Sheds Light on Hexapod Evolution. BMC Genom. 2017, 18, 795. [Google Scholar] [CrossRef]
- Zhang, F.; Ding, Y.; Zhou, Q.-S.; Wu, J.; Luo, A.; Zhu, C.-D. A High-Quality Draft Genome Assembly of Sinella curviseta: A Soil Model Organism (Collembola). Genome Biol. Evol. 2019, 11, 521–530. [Google Scholar] [CrossRef]
- Biobam: Bioinformatics Solutions. Available online: https://www.biobam.com/omicsbox (accessed on 10 January 2021).
- FastQC: A Quality Control Tool for High Throughput Sequence Data. Available online: http://www.bioinformatics.babraham.ac.uk/projects/fastqc (accessed on 10 January 2021).
- Bolger, A.M.; Lohse, M.; Usadel, B. Trimmomatic: A Flexible Trimmer for Illumina Sequence Data. Bioinformatics 2014, 30, 2114–2120. [Google Scholar] [CrossRef]
- Haas, B.J.; Papanicolaou, A.; Yassour, M.; Grabherr, M.; Blood, P.D.; Bowden, J.; Couger, M.B.; Eccles, D.; Li, B.; Lieber, M.; et al. De Novo Transcript Sequence Reconstruction from RNA-Seq: Reference Generation and Analysis with Trinity. Nat. Protoc. 2013, 8, 1494–1512. [Google Scholar] [CrossRef]
- Li, W.; Godzik, A. Cd-Hit: A Fast Program for Clustering and Comparing Large Sets of Protein or Nucleotide Sequences. Bioinformatics 2006, 22, 1658–1659. [Google Scholar] [CrossRef]
- Simão, F.A.; Waterhouse, R.M.; Ioannidis, P.; Kriventseva, E.V.; Zdobnov, E.M. BUSCO: Assessing Genome Assembly and Annotation Completeness with Single-Copy Orthologs. Bioinformatics 2015, 31, 3210–3212. [Google Scholar] [CrossRef]
- Jalili, V.; Afgan, E.; Gu, Q.; Clements, D.; Blankenberg, D.; Goecks, J.; Taylor, J.; Nekrutenko, A. The Galaxy Platform for Accessible, Reproducible and Collaborative Biomedical Analyses: 2020 Update. Nucleic Acids Res. 2020, 48, W395–W402. [Google Scholar] [CrossRef]
- The UniProt Consortium. UniProt: The Universal Protein Knowledgebase in 2023. Nucleic Acids Res. 2023, 51, D523–D531. [Google Scholar] [CrossRef]
- Gasteiger, E.; Gattiker, A.; Hoogland, C.; Ivanyi, I.; Appel, R.D.; Bairoch, A. ExPASy: The Proteomics Server for in-Depth Protein Knowledge and Analysis. Nucleic Acids Res. 2003, 31, 3784–3788. [Google Scholar] [CrossRef]
- Camacho, C.; Coulouris, G.; Avagyan, V.; Ma, N.; Papadopoulos, J.; Bealer, K.; Madden, T.L. BLAST+: Architecture and Applications. BMC Bioinform. 2009, 10, 421. [Google Scholar] [CrossRef]
- Birney, E.; Clamp, M.; Durbin, R. GeneWise and Genomewise. Genome Res. 2004, 14, 988–995. [Google Scholar] [CrossRef]
- Quevillon, E.; Silventoinen, V.; Pillai, S.; Harte, N.; Mulder, N.; Apweiler, R.; Lopez, R. InterProScan: Protein Domains Identifier. Nucleic Acids Res. 2005, 33, W116–W120. [Google Scholar] [CrossRef]
- Rice, P.; Longden, I.; Bleasby, A. EMBOSS: The European Molecular Biology Open Software Suite. Trends Genet. 2000, 16, 276–277. [Google Scholar] [CrossRef] [PubMed]
- QIAGEN CLC Main Workbench: The User-Friendly Solution for Basic Sequencing Analysis. Available online: https://digitalinsights.qiagen.com (accessed on 10 January 2021).
- Wang, G.; Li, X.; Wang, Z. APD3: The Antimicrobial Peptide Database as a Tool for Research and Education. Nucleic Acids Res. 2016, 44, D1087–D1093. [Google Scholar] [CrossRef] [PubMed]
- Kelley, L.A.; Mezulis, S.; Yates, C.M.; Wass, M.N.; Sternberg, M.J.E. The Phyre2 Web Portal for Protein Modeling, Prediction and Analysis. Nat. Protoc. 2015, 10, 845–858. [Google Scholar] [CrossRef] [PubMed]
- Waghu, F.H.; Barai, R.S.; Gurung, P.; Idicula-Thomas, S. CAMPR3: A Database on Sequences, Structures and Signatures of Antimicrobial Peptides. Nucleic Acids Res. 2016, 44, D1094–D1097. [Google Scholar] [CrossRef]
- Joseph, S.; Karnik, S.; Nilawe, P.; Jayaraman, V.K.; Idicula-Thomas, S. ClassAMP: A Prediction Tool for Classification of Antimicrobial Peptides. IEEE/ACM Trans. Comput. Biol. Bioinform. 2012, 9, 1535–1538. [Google Scholar] [CrossRef]
- Meher, P.K.; Sahu, T.K.; Saini, V.; Rao, A.R. Predicting Antimicrobial Peptides with Improved Accuracy by Incorporating the Compositional, Physico-Chemical and Structural Features into Chou’s General PseAAC. Sci. Rep. 2017, 7, 42362. [Google Scholar] [CrossRef]
- Vishnepolsky, B.; Gabrielian, A.; Rosenthal, A.; Hurt, D.E.; Tartakovsky, M.; Managadze, G.; Grigolava, M.; Makhatadze, G.I.; Pirtskhalava, M. Predictive Model of Linear Antimicrobial Peptides Active against Gram-Negative Bacteria. J. Chem. Inf. Model. 2018, 58, 1141–1151. [Google Scholar] [CrossRef]
- Vishnepolsky, B.; Grigolava, M.; Managadze, G.; Gabrielian, A.; Rosenthal, A.; Hurt, D.E.; Tartakovsky, M.; Pirtskhalava, M. Comparative Analysis of Machine Learning Algorithms on the Microbial Strain-Specific AMP Prediction. Brief. Bioinform. 2022, 23, bbac233. [Google Scholar] [CrossRef]
- Katoh, K.; Standley, D.M. MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability. Mol. Biol. Evol. 2013, 30, 772–780. [Google Scholar] [CrossRef]
- Capella-Gutiérrez, S.; Silla-Martínez, J.M.; Gabaldón, T. TrimAl: A Tool for Automated Alignment Trimming in Large-Scale Phylogenetic Analyses. Bioinformatics 2009, 25, 1972–1973. [Google Scholar] [CrossRef]
- Guindon, S.; Dufayard, J.-F.; Lefort, V.; Anisimova, M.; Hordijk, W.; Gascuel, O. New Algorithms and Methods to Estimate Maximum-Likelihood Phylogenies: Assessing the Performance of PhyML 3.0. Syst. Biol. 2010, 59, 307–321. [Google Scholar] [CrossRef]
- Lefort, V.; Longueville, J.-E.; Gascuel, O. SMS: Smart Model Selection in PhyML. Mol. Biol. Evol. 2017, 34, 2422–2424. [Google Scholar] [CrossRef]
- Tanaka, H.; Sato, K.; Saito, Y.; Yamashita, T.; Agoh, M.; Okunishi, J.; Tachikawa, E.; Suzuki, K. Insect Diapause-Specific Peptide from the Leaf Beetle Has Consensus with a Putative Iridovirus Peptide. Peptides 2003, 24, 1327–1333. [Google Scholar] [CrossRef]
- Barbault, F.; Landon, C.; Guenneugues, M.; Meyer, J.-P.; Schott, V.; Dimarcq, J.-L.; Vovelle, F. Solution Structure of Alo-3: A New Knottin-Type Antifungal Peptide from the Insect Acrocinus longimanus. Biochemistry 2003, 42, 14434–14442. [Google Scholar] [CrossRef]
- Rádai, Z.; Kiss, J.; Nagy, N.A. Taxonomic Bias in AMP Prediction of Invertebrate Peptides. Sci. Rep. 2021, 11, 17924. [Google Scholar] [CrossRef]
- Souhail, Q.A.; Hiromasa, Y.; Rahnamaeian, M.; Giraldo, M.C.; Takahashi, D.; Valent, B.; Vilcinskas, A.; Kanost, M.R. Characterization and Regulation of Expression of an Antifungal Peptide from Hemolymph of an Insect, Manduca sexta. Dev. Comp. Immunol. 2016, 61, 258–268. [Google Scholar] [CrossRef]
- Li, M.; Al Souhail, Q.; Veerapandian, R.; Vediyappan, G.; Kanost, M. Investigation of an Antifungal Peptide, Diapausin, from Manduca sexta. FASEB J. 2019, 33, 800.2. [Google Scholar] [CrossRef]
- Keppi, E.; Pugsley, A.P.; Lambert, J.; Wicker, C.; Dimarcq, J.-L.; Hoffmann, J.A.; Hoffmann, D. Mode of Action of Diptericin A, a Bactericidal Peptide Induced in the Hemolymph of Phormia terranovae Larvae. Arch. Insect Biochem. Physiol. 1989, 10, 229–239. [Google Scholar] [CrossRef]
- Ishikawa, M.; Kubo, T.; Natori, S. Purification and Characterization of a Diptericin Homologue from Sarcophaga peregrina (Flesh Fly). Biochem. J. 1992, 287, 573–578. [Google Scholar] [CrossRef]
- Unckless, R.L.; Howick, V.M.; Lazzaro, B.P. Convergent Balancing Selection on an Antimicrobial Peptide in Drosophila. Curr. Biol. 2016, 26, 257–262. [Google Scholar] [CrossRef]
- Wu, Q.; Patočka, J.; Kuča, K. Insect Antimicrobial Peptides, a Mini Review. Toxins 2018, 10, E461. [Google Scholar] [CrossRef] [PubMed]
- Mukherjee, K.; Mraheil, M.A.; Silva, S.; Müller, D.; Cemic, F.; Hemberger, J.; Hain, T.; Vilcinskas, A.; Chakraborty, T. Anti-Listeria Activities of Galleria mellonella Hemolymph Proteins. Appl. Environ. Microbiol. 2011, 77, 4237–4240. [Google Scholar] [CrossRef] [PubMed]
- Jayamani, E.; Rajamuthiah, R.; Larkins-Ford, J.; Fuchs, B.B.; Conery, A.L.; Vilcinskas, A.; Ausubel, F.M.; Mylonakis, E. Insect-Derived Cecropins Display Activity against Acinetobacter baumannii in a Whole-Animal High-Throughput Caenorhabditis elegans Model. Antimicrob. Agents Chemother. 2015, 59, 1728–1737. [Google Scholar] [CrossRef] [PubMed]
- Romoli, O.; Mukherjee, S.; Mohid, S.A.; Dutta, A.; Montali, A.; Franzolin, E.; Brady, D.; Zito, F.; Bergantino, E.; Rampazzo, C.; et al. Enhanced Silkworm Cecropin B Antimicrobial Activity against Pseudomonas aeruginosa from Single Amino Acid Variation. ACS Infect. Dis. 2019, 5, 1200–1213. [Google Scholar] [CrossRef] [PubMed]
- Kalsy, M.; Tonk, M.; Hardt, M.; Dobrindt, U.; Zdybicka-Barabas, A.; Cytrynska, M.; Vilcinskas, A.; Mukherjee, K. The Insect Antimicrobial Peptide Cecropin A Disrupts Uropathogenic Escherichia coli Biofilms. Npj. Biofilms Microbiomes 2020, 6, 6. [Google Scholar] [CrossRef]
- Agamennone, V.; Roelofs, D.; van Straalen, N.M.; Janssens, T.K. Antimicrobial Activity in Culturable Gut Microbial Communities of Springtails. J. Appl. Microbiol. 2018, 125, 740–752. [Google Scholar] [CrossRef]
- Roelofs, D.; Timmermans, M.J.T.N.; Hensbergen, P.; van Leeuwen, H.; Koopman, J.; Faddeeva, A.; Suring, W.; de Boer, T.E.; Mariën, J.; Boer, R.; et al. A Functional Isopenicillin N Synthase in an Animal Genome. Mol. Biol. Evol. 2013, 30, 541–548. [Google Scholar] [CrossRef]
- Mitpuangchon, N.; Nualcharoen, K.; Boonrotpong, S.; Engsontia, P. Identification of Novel Toxin Genes from the Stinging Nettle Caterpillar Parasa lepida (Cramer, 1799): Insights into the Evolution of Lepidoptera Toxins. Insects 2021, 12, 396. [Google Scholar] [CrossRef]
- Engsontia, P.; Sangket, U.; Chotigeat, W.; Satasook, C. Molecular Evolution of the Odorant and Gustatory Receptor Genes in Lepidopteran Insects: Implications for Their Adaptation and Speciation. J. Mol. Evol. 2014, 79, 21–39. [Google Scholar] [CrossRef]
- Engsontia, P.; Sangket, U.; Robertson, H.M.; Satasook, C. Diversification of the Ant Odorant Receptor Gene Family and Positive Selection on Candidate Cuticular Hydrocarbon Receptors. BMC Res. Notes 2015, 8, 380. [Google Scholar] [CrossRef]
- Hanson, M.A.; Lemaitre, B.; Unckless, R.L. Dynamic Evolution of Antimicrobial Peptides Underscores Trade-Offs Between Immunity and Ecological Fitness. Front. Immunol. 2019, 10, 2620. [Google Scholar] [CrossRef]
- Yoo, W.G.; Lee, J.H.; Shin, Y.; Shim, J.-Y.; Jung, M.; Kang, B.-C.; Oh, J.; Seong, J.; Lee, H.K.; Kong, H.S.; et al. Antimicrobial Peptides in the Centipede Scolopendra subspinipes mutilans. Funct. Integr. Genom. 2014, 14, 275–283. [Google Scholar] [CrossRef]
- Lee, J.H.; Chung, H.; Shin, Y.P.; Kim, M.-A.; Natarajan, S.; Veerappan, K.; Kim, S.H.; Park, J.; Hwang, J.S. Deciphering Novel Antimicrobial Peptides from the Transcriptome of Papilio xuthus. Insects 2020, 11, 776. [Google Scholar] [CrossRef]
- Lee, J.H.; Chung, H.; Shin, Y.P.; Kim, M.-A.; Natarajan, S.; Veerappan, K.; Kim, S.H.; Park, J.; Hwang, J.S. Uncovering Antimicrobial Peptide from Zophobas atratus Using Transcriptome Analysis. Int. J. Pept. Res. Ther. 2021, 27, 1827–1835. [Google Scholar] [CrossRef]
Taxonomic Order | Species (RNA-Seq SRA ID) | Raw Sequence Reads (Counts) | Unique Contigs (Unigenes) | Contig Length Average (bp) | N50 (bp) | BUSCO Analysis (% Completeness) |
---|---|---|---|---|---|---|
Entomobryomorpha | Orchesella cincta (SRR935330) | 18,994,903 | 31,396 | 616 | 907 | 72% |
Sinella curviseta (SRR7948082) | 26,192,990 | 68,491 | 1337 | 2725 | 91.5% | |
Poduromorpha | Anurida maritima (SRR921564) | 12,272,329 | 36,311 | 1314 | 2454 | 89% |
Holacanthella duospinosa (SRR5626546) | 52,089,655 | 72,356 | 1274 | 2873 | 90% | |
Symphypleona | Sminthurus viridis (SRR921641) | 10,273,556 | 48,144 | 853 | 1454 | 88% |
Properties | Diapausin | Alo Peptide | Diptericin | Cecropin | Defensin | |||||
---|---|---|---|---|---|---|---|---|---|---|
Mean | SD | Mean | SD | Mean | SD | Mean | SD | Mean | SD | |
No. of amino acids | 44.48 | 5.401 | 35.75 | 3.596 | 97.50 | 5.916 | 40.00 | 1.732 | 44.66 | 6.658 |
Molecular weight | 4871.0 | 576.94 | 3930.4 | 545.26 | 9979.3 | 522.88 | 4423.2 | 318.77 | 4890.3 | 610.43 |
pI | 8.19 | 1.345 | 6.91 | 1.973 | 11.1 | 0.645 | 11.57 | 0.607 | 7.65 | 1.769 |
Net charge at pH 7 | 2.05 | 2.416 | 0.44 | 3.631 | 7.56 | 1.546 | 7.5 | 1.639 | 0.92 | 2.184 |
Hydrophobic ratio | 0.37 | 0.059 | 0.35 | 0.055 | 0.57 | 0.012 | 0.58 | 0.041 | 0.44 | 0.043 |
% polar amino acids | 44.19 | 4.692 | 43.09 | 4.959 | 40.21 | 1.509 | 41.61 | 4.101 | 37.36 | 0.565 |
% positive charge | 16.15 | 2.843 | 10.87 | 5.188 | 12.01 | 1.719 | 25.72 | 4.219 | 13.86 | 4.475 |
% negative charge | 8.33 | 4.666 | 8.57 | 4.805 | 2.55 | 0.476 | 5.82 | 3.69 | 7.32 | 2.711 |
% proline and glycine | 16.07 | 3.494 | 15.81 | 3.514 | 26.66 | 1.627 | 16.52 | 5.733 | 20.94 | 1.941 |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Pradhan, G.; Engsontia, P. Diversity of the Antimicrobial Peptide Genes in Collembola. Insects 2023, 14, 215. https://doi.org/10.3390/insects14030215
Pradhan G, Engsontia P. Diversity of the Antimicrobial Peptide Genes in Collembola. Insects. 2023; 14(3):215. https://doi.org/10.3390/insects14030215
Chicago/Turabian StylePradhan, Goma, and Patamarerk Engsontia. 2023. "Diversity of the Antimicrobial Peptide Genes in Collembola" Insects 14, no. 3: 215. https://doi.org/10.3390/insects14030215