International Journal of Genomics

International Journal of Genomics / 2009 / Article

Research Article | Open Access

Volume 2009 |Article ID 983636 | 8 pages | https://doi.org/10.1155/2009/983636

Molecular Diversity of the Antimicrobial Domain of Beta-Defensin 3 and Homologous Peptides

Academic Editor: Graziano Pesole
Received12 May 2009
Accepted17 Aug 2009
Published02 Nov 2009

Abstract

Human -defensin 3 has received great interest for possible pharmaceutical applications. To characterize the biology of this antimicrobial peptide, the mouse -defensin 14 has been selected as a prototypical model. This report provides definite evidence of true orthology between these defensins and reveals molecular diversity of a mammalian specific domain responsible for their antimicrobial activity. Specifically, this analysis demonstrates that eleven amino acid residues of the antimicrobial domain have been mutated by positive selection to confer protein niche specialization. These data support the notion that natural selection acts as evolutionary force driving the proliferation and diversification of defensins and introduce a novel strategy for the design of more effective antibiotics.

1. Introduction

A variety of antimicrobial peptides are produced by animals and plants as elemental components of their defense system to combat infectious microbes, including bacteria, fungi, viruses, and protozoa [1]. Among this antimicrobial protein repertoire, defensins are the most efficient and ancient components of host defense [2]. Recent analyses indicated that the cysteine-stabilized and protein fold characteristic of the defensin family originated before the emergence of eukaryotes [3]. Even though defensins have an ancient origin, the majority of microbial pathogens have not developed highly effective mechanisms of resistance against these antimicrobial compounds [1, 2]. Antimicrobial resistance to defensins have been observed in some pathogens [4]; however, it has been proposed that the production of antimicrobial peptides and mechanisms of resistance have coevolved at similar rate, generating a niche specific transitory stage for host-pathogen balance, and this scenario has shaped the existing defensin repertoire [2, 5, 6]. To this end, the understanding of the evolutionary forces driving this molecular process should facilitate the design of more effective antibiotics.

Among all these antimicrobial peptides, human 3 (DEFB103A) has received the most interest for possible pharmaceutical applications [7, 8]. This protein exhibits not only a broad-spectrum antibacterial effect [9] but also other important biological functions such as chemoattraction of immune cells [7] and initiation of remodeling processes in articular cartilage [10]. To identify and functionally characterize the role of DEFB103A peptide in host-microbe interactions, the putative homologous protein, the mouse 14 (DEFB14) has been selected as a prototypical model [1113]. Human DEFB103A and mouse DEFB14 carry the highest number of cationic charges ( and , resp.) of all (BDEFs) [11]. The DEFB14 gene is constitutively expressed in epithelial cells of eye, tongue, trachea, esophagus, thymus, lung, liver, small intestine, spleen, testis, epididymis, and dendritic cells [11, 12].

The present report reveals the precise orthologous relationship between 3 and homologous peptides and provides new insights into the protein niche specialization of these antimicrobial proteins. These findings provide important molecular bases for the design of more effective antibiotics.

2. Materials and Methods

2.1. Identification and Analysis of 3 Orthologous Groups

The widely used approach of reciprocal (bi-directional) best hits (RBH) [14, 15] was implemented for constructing related orthologous groups of DEFB103A and DEFB14 across multiple eukaryotic taxa. BLASTP analysis [16] was used to back-search amino acid sequences against well-annotated and -curated protein sequences from the RefSeq database (NCBI Reference Sequence Project). Protein sequences from this orthologous group were aligned using the M-Coffee software, a metamethod for assembling multiple sequence alignments [17]. Jalview software analysis [18] was used to estimate degree of conservation and consensus between all protein sequences. Then, the protein alignments were used for phylogenetic tree reconstruction using the maximum parsimony method [19] with the PAU 4.0 b10 program [20]. The statistical significance of branch order was estimated by the generation of 1000 replications of bootstrap resampling of the originally-aligned amino acid sequences.

2.2. Evolution of 3 in the Eutheria–Metatheria Clade

Because the identification of domains that occur within proteins can provide insights into their function [21, 22], the identification of conserved domains in protein sequences of the Eutheria–Metatheria BDEF3 (hereafter mammalian BDEF3) clade was analyzed. Pfam algorithm [23, 24] was used for the identification of conserved domains within the predicted mammalian BDEF3 orthologous group. Protein sequences of the mammalian BDEF3 orthologous group were aligned using the M-Coffee software and phylogenetic tree reconstruction by means of maximum parsimony was performed as described above.

2.3. Assessment of Protein Niche Specialization in the Mammalian BDEF3 Clade

To examine the likelihood of protein niche specialization in the mammalian BDEF3 clade, homologous proteins were aligned using the M-Coffee software and Jalview was used to identify the twenty-three residues, FLPKTLRKFFCRIRGGRCAVLNC, responsible for the antimicrobial activity [7, 8, 11]. This antimicrobial-domain was retrieved from each mature peptide region of proteins included in the mammalian BDEF3 orthologous group, and divergence of amino acid residues was analyzed by generating sequence logos [25]. To confirm the specificity of this antimicrobial-domain among the mammalian BDEF3 lineage, RBH was performed to identify other peptides containing this domain. BLASTP analysis was used to back-search amino acid sequences against the RefSeq database. In addition, site-specific synonymous and nonsynonymous substitution rate was estimated by maximum likelihood-based methods [26] for identification of residues subject to positive selection.

3. Results

3.1. Identification and Analysis of 3 Orthologous Group

Fifty-six BDEF protein sequences were obtained in the construction of DEFB103A and DEFB14 orthologous groups. This dataset enclosed protein sequences of BD1, -2, -3, and -4 across different taxa (Figure 1). Phylogenetic analysis using the maximum parsimony identified seven major BDEF clades: ( ) rat-mouse BDEF38, ( ) Eutheria–Metatheria BDEF3, ( ) horse BDEF, ( ) cow BDEF, ( ) primate BDEF4, ( ) rat-mouse BDEF4 and ( ) rat-mouse BDEF2 (Figure 1). Moreover, alignment and analysis of the BDEF proteins confirmed the conservation of the canonical six-cysteine motif in the BDEF orthologous group (Figure 2).

3.2. Evolution of 3 in the Eutheria–Metatheria Clade

To gain some insights into protein function of the mammalian BDEF3, the identification of conserved domains was performed with the Pfam algorithm [23, 24]. All proteins enclosed in the mammalian BDEF3 clade contained the structural components of the domain (data not shown). Moreover, phylogenetic analysis revealed that protein similarity is greater among closely related species and identified primate-, ungulate-, cow-, and rodent-BDEF3 protein clusters (Figure 3). Interestingly, when cationic charges were estimated for each amino acid sequence, it was found that charges are similar within proteins of the primate-, ungulate-, cow-, and rodent-BDEF3 clusters ( , and , , ; resp.).

3.3. Assessment of Protein Niche Specialization in the Mammalian BDEF3 Clade

To gain some insights into the molecular basis for protein niche specialization of mammalian BDEF3, antimicrobial-domains were retrieved from each mature peptide region of proteins included in the mammalian BDEF3 orthologous group (Figure 4). Then, sequence logos were generated for each antimicrobial-domain identified (Figure 5). These analyses demonstrate that eleven out of twenty-three residues in the antimicrobial-domain are highly variable across the mammalian BDEF3 clade (Figures 4 and 5). Moreover, primate-, ungulate-, cow-, and rodent-BDEF3 clusters show different amino acid residue variation (Figure 5). To confirm the specificity of this antimicrobial-domain among the mammalian lineage, the amino acid residues contained in the antimicrobial domain were subject to RBH analysis with BLASTP algorithm against the RefSeq database. This analysis confirmed that this antimicrobial domain is a particular attribute of the mammalian BDEF3 clade. This unusual pattern is evidence of natural selection acting on the diversification of BDEFs and supports the idea of mammalian BDEF3 niche specialization. To confirm this notion, site-specific synonymous and nonsynonymous substitution rates were estimated by maximum likelihood-based methods [26] for the identification of residues subject to positive selection. This analysis demonstrates that eleven amino acid residues of the antimicrobial domain have been mutated by positive selection to confer BDEF3 niche specialization (Figure 5).

4. Discussion

In an effort to improve our understanding of the molecular basis regarding the mechanism of action of BDEF and facilitate the design new therapeutic agents, the present study examines the evolution of 3 and its antimicrobial-domain. Herein, the phylogenetic analysis of the BDEF protein family across multiple species provides definite evidence of true orthology between human DEFB103A and mouse DEFB14. Moreover, it is revealed that positive selection has acted to diversify defensins and that mammalian BDEF3 undergoes niche specialization during protein evolution.

The nomenclature of BDEF proteins is complicated. Defensins have been annotated sequentially on discovery, and in some instances, orthologous proteins receive the same number [27]. However, there are cases such as human DEFB103A and mouse DEFB14, in which orthologous relationships are not so obvious. In the present study, the phylogenetic analysis of the BDEF protein family across multiple species identified seven major BDEF clades and established orthologous relationships among these proteins. For example, the Eutheria–Metatheria clade is comprised by human, chimp, and cow DEFB103A; mouse and rat DEFB14; and cow, horse, and pig BDEF3 proteins. Moreover, the phylogenetic analysis confirmed the conservation of the canonical cysteine motif in the defensin family [27]. Disulphide bridges generated between these conserved cysteines confer more resistance to bacterial proteolysis, even though the disulphide bridges are not essential for the antimicrobial activity [2, 7, 28, 29]. These results demonstrate that likely evolved to encode similar functions among eukaryotic taxa but these protein sequences have undergone niche specialization.

In the present study, protein niche specialization of mammalian BDEF3 is supported by at least three molecular bases. First, phylogenetic analysis of proteins from mammalian BDEF3 clade identified primate-, ungulate-, cow-, and rodent- protein clusters within the mammalian BDEF3 clade. It was also found that proteins of each BDEF3 cluster have similar cationic charges. Second, analysis of amino acid residues of the antimicrobial-domain [7, 8, 11] revealed that this protein domain is a particular attribute of the mammalian BDEF3 clade. Third, it was found that eleven out of twenty-three residues in the antimicrobial-domain are highly variable across the mammalian BDEF3 clade and that these amino acids have been mutated by positive selection to confer BDEF3 niche specialization. A similar evolutionary scenario was determined for clusters of mammalian [30] and other [31, 32].

It can be hypothesized that the selection pressures on the evolution of defensins might have occurred to preserve an adaptive phenotype, increase functional divergence, and enhance microbe killing efficiency [27, 31]. In fact, it was demonstrated that amino acid substitutions at sites subject to positive selection increase the antimicrobial activity of BDEFs against bacterial pathogens [33]. Accordingly, it was suggested that positive selection at particular residues is involved in directing a new antimicrobial response against specific pathogens [33]. The value of these observations for biomedical research is also established by the elegant study by Antcheva et al. [34]. These authors demonstrated that the increase in antimicrobial activity of two homologous 2 (human and macaque) is caused by amino acid residues subject to positive selection [34].

Together, these data are consistent with the notion that natural selection acts as evolutionary force driving the proliferation and diversification of defensins. Indeed, these results strongly support the hypothesis that BDEFs niche specialization is caused by host-pathogen coevolution [2, 31, 35]. Thus, this information has potential for the structure-guide design of novel antimicrobial peptides.

In summary, this report indicates that the production of antimicrobial peptides is a response to pathogen diversity and their coevolution generates niche specialization for maintaining a host-pathogen balance. These data support the notion that natural selection acts as evolutionary force driving the proliferation and diversification of defensins and introduce a novel strategy for the design of more effective antibiotics.

References

  1. M. Zasloff, “Antimicrobial peptides of multicellular organisms,” Nature, vol. 415, pp. 389–395, 2002. View at: Google Scholar
  2. A. Peschel and H. G. Sahl, “The co-evolution of host cationic antimicrobial peptides and microbial resistance,” Nature Reviews Microbiology, vol. 4, no. 7, pp. 529–536, 2006. View at: Publisher Site | Google Scholar
  3. S. Zhu, “Evidence for myxobacterial origin of eukaryotic defensins,” Immunogenetics, vol. 59, pp. 949–954, 2007. View at: Google Scholar
  4. R. I. Lehrer, “Primate defensins,” Nature Reviews Microbiology, vol. 2, pp. 727–738, 2004. View at: Google Scholar
  5. D. Kraus and A. Peschel, “Molecular mechanisms of bacterial resistance to antimicrobial peptides,” Current Topics in Microbiology and Immunology, vol. 306, pp. 231–250, 2006. View at: Google Scholar
  6. J. B. McPhee, M. G. Scott, and R. E. Hancock, “Design of host defence peptides for antimicrobial and immunity enhancing activities,” Combinatorial Chemistry & High Throughput Screening, vol. 8, pp. 257–272, 2005. View at: Google Scholar
  7. V. Dhople, A. Krukemeyer, and A. Ramamoorthy, “The human β-defensin-3, an antibacterial peptide with multiple biological functions,” Biochimica et Biophysica Acta, vol. 1758, no. 9, pp. 1499–1512, 2006. View at: Publisher Site | Google Scholar
  8. D. M. Hoover, Z. Wu, K. Tucker, W. Lu, and J. Lubkowski, “Antimicrobial characterization of human β-defensin 3 derivatives,” Antimicrobial Agents and Chemotherapy, vol. 47, no. 9, pp. 2804–2809, 2003. View at: Publisher Site | Google Scholar
  9. J. Harder, J. Bartels, E. Christophers, and J. M. Schroder, “Isolation and characterization of human β-defensin-3, a novel human inducible peptide antibiotic,” The Journal of Biological Chemistry, vol. 276, no. 8, pp. 5707–5713, 2001. View at: Publisher Site | Google Scholar
  10. D. Varoga, T. Pufe, J. Harder et al., “Human β-defensin 3 mediates tissue remodeling processes in articular cartilage by increasing levels of metalloproteinases and reducing levels of their endogenous inhibitors,” Arthritis & Rheumatism, vol. 52, no. 6, pp. 1736–1745, 2005. View at: Publisher Site | Google Scholar
  11. K. Taylor, D. J. Clarke, B. McCullough et al., “Analysis and separation of residues important for the chemoattractant and antimicrobial activities of β-defensin 3,” The Journal of Biological Chemistry, vol. 283, no. 11, pp. 6631–6639, 2008. View at: Publisher Site | Google Scholar
  12. J. Rohrl, D. Yang, J. J. Oppenheim, and T. Hehlgans, “Identification and biological characterization of mouse β-defensin 14, the orthologue of human β-defensin 3,” The Journal of Biological Chemistry, vol. 283, no. 9, pp. 5414–5419, 2008. View at: Publisher Site | Google Scholar
  13. K. Hinrichsen, R. Podschun, S. Schubert, J. M. Schroder, J. Harder, and E. Proksch, “Mouse β-defensin-14, an antimicrobial ortholog of human β-defensin-3,” Antimicrobial Agents and Chemotherapy, vol. 52, no. 5, pp. 1876–1879, 2008. View at: Publisher Site | Google Scholar
  14. D. P. Wall, H. B. Fraser, and A. E. Hirsh, “Detecting putative orthologs,” Bioinformatics, vol. 19, pp. 1710–1711, 2003. View at: Publisher Site | Google Scholar
  15. W. M. Fitch, “Distinguishing homologous from analogous proteins,” Systematic Zoology, vol. 19, pp. 99–113, 1970. View at: Google Scholar
  16. S. F. Altschul, T. L. Madden, A. A. Schaffer et al., “Gapped BLAST and PSI-BLAST: a new generation of protein database search programs,” Nucleic Acids Research, vol. 25, no. 17, pp. 3389–3402, 1997. View at: Publisher Site | Google Scholar
  17. I. M. Wallace, O. O'Sullivan, D. G. Higgins, and C. Notredame, “M-Coffee: combining multiple sequence alignment methods with T-Coffee,” Nucleic Acids Research, vol. 34, no. 6, pp. 1692–1699, 2006. View at: Publisher Site | Google Scholar
  18. M. Clamp, J. Cuff, S. M. Searle, and G. J. Barton, “The Jalview java alignment editor,” Bioinformatics, vol. 20, pp. 426–427, 2004. View at: Google Scholar
  19. R. V. Eck and M. O. Dayhoff, Atlas of Protein Sequence and Structure, National Biomedical Research Foundation, Silver Spring, Md, USA, 1966.
  20. D. L. Swofford, PAUP. Phylogenetic Analysis Using Parsimony (and Other Methods), Sinauer Associates, Sunderland, Mass, USA, 2002.
  21. E. L. Sonnhammer and D. Kahn, “Modular arrangement of proteins as inferred from analysis of homology,” Protein Science, vol. 3, no. 3, pp. 482–492, 1994. View at: Google Scholar
  22. T. K. Attwood, M. E. Beck, A. J. Bleasby, K. Degtyarenko, A. D. Michie, and D. J. Parry-Smith, “Novel developments with the PRINTS protein fingerprint database,” Nucleic Acids Research, vol. 25, no. 1, pp. 212–217, 1997. View at: Publisher Site | Google Scholar
  23. A. Bateman, L. Coin, R. Durbin et al., “The Pfam protein families database,” Nucleic Acids Research, vol. 32, pp. D138–D141, 2004. View at: Google Scholar
  24. R. D. Finn, J. Mistry, B. Schuster-Bockler et al., “Pfamml: clans, web tools and services,” Nucleic Acids Research, vol. 34, pp. D247–D251, 2006. View at: Google Scholar
  25. G. E. Crooks, G. Hon, J. M. Chandonia, and S. E. Brenner, “WebLogo: a sequence logo generator,” Genome Research, vol. 14, no. 6, pp. 1188–1190, 2004. View at: Publisher Site | Google Scholar
  26. S. L. Pond and S. D. Frost, “Datamonkey: rapid detection of selective pressure on individual sites of codon alignments,” Bioinformatics, vol. 21, no. 10, pp. 2531–2533, 2005. View at: Publisher Site | Google Scholar
  27. C. A. Semple, P. Gautier, K. Taylor, and J. R. Dorin, “The changing of the guard: molecular diversity and rapid evolution of β-defensins,” Molecular Diversity, vol. 10, no. 4, pp. 575–584, 2006. View at: Publisher Site | Google Scholar
  28. M. Pazgier, D. M. Hoover, D. Yang, W. Lu, and J. Lubkowski, “Human β-defensins,” Cellular and Molecular Life Sciences, vol. 63, no. 11, pp. 1294–1313, 2006. View at: Publisher Site | Google Scholar
  29. Z. Wu, D. M. Hoover, D. Yang et al., “Engineering disulfide bridges to dissect antimicrobial and chemotactic activities of human β-defensin 3,” Proceedings of the National Academy of Sciences of the United States of America, vol. 100, no. 15, pp. 8880–8885, 2003. View at: Publisher Site | Google Scholar
  30. A. L. Hughes, “Evolutionary diversification of the mammalian defensins,” Cellular and Molecular Life Sciences, vol. 56, pp. 94–103, 1999. View at: Google Scholar
  31. Y. Radhakrishnan, M. A. Fares, F. S. French, and S. H. Hall, “Comparative genomic analysis of a mammalian β-defensin gene cluster,” Physiological Genomics, vol. 30, no. 3, pp. 213–222, 2007. View at: Publisher Site | Google Scholar
  32. E. J. Hollox and J. A. Armour, “Directional and balancing selection in human β-defensins,” BMC Evolutionary Biology, vol. 8, article 113, 2008. View at: Google Scholar
  33. R. Higgs, D. J. Lynn, S. Cahalane et al., “Modification of chicken avian β-defensin-8 at positively selected amino acid sites enhances specific antimicrobial activity,” Immunogenetics, vol. 59, pp. 573–580, 2007. View at: Google Scholar
  34. N. Antcheva, M. Boniotto, I. Zelezetsky et al., “Effects of positively selected sequence variations in human and macaca fascicularis β-defensins 2 on antimicrobial activity,” Antimicrobial Agents and Chemotherapy, vol. 48, no. 2, pp. 685–688, 2004. View at: Publisher Site | Google Scholar
  35. Y. Radhakrishnan, K. G. Hamil, S. Yenugu, S. L. Young, F. S. French, and S. H. Hall, “Identification, characterization, and evolution of a primate β-defensin gene cluster,” Genes and Immunity, vol. 6, no. 3, pp. 203–210, 2005. View at: Publisher Site | Google Scholar

Copyright © 2009 Gerardo M. Nava et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


More related articles

678 Views | 504 Downloads | 2 Citations
 PDF  Download Citation  Citation
 Download other formatsMore
 Order printed copiesOrder

Related articles

We are committed to sharing findings related to COVID-19 as quickly and safely as possible. Any author submitting a COVID-19 paper should notify us at help@hindawi.com to ensure their research is fast-tracked and made available on a preprint server as soon as possible. We will be providing unlimited waivers of publication charges for accepted articles related to COVID-19. Sign up here as a reviewer to help fast-track new submissions.