Nucleic Acids Research Advance Access originally published online on October 4, 2008
Nucleic Acids Research 2009 37(Database issue):D963-D968; doi:10.1093/nar/gkn655
Nucleic Acids Research, 2009, Vol. 37, Database issue D963-D968
© 2008 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
PhytAMP: a database dedicated to antimicrobial plant peptides
Riadh Hammami1,2,3,
Jeannette Ben Hamida1,
Gérard Vergoten2 and
Ismail Fliss3,*
1Unité de Protéomie Fonctionnelle & Biopréservation Alimentaire, Institut Supérieur des Sciences Biologiques Appliquées de Tunis, Université El Manar, Tunis, Tunisie 2UMR CNRS 8576 Glycobiologie Structurale et Fonctionnelle, Université des Sciences et Technologie de Lille, Lille, France and 3Institut des Nutraceutiques et des Aliments Fonctionnels (INAF), Université Laval, Québec, Canada
*To whom correspondence should be addressed. Tel: +1 418 656 2131 (ext. 6825); Fax: +1 418 656 3353; Email: Ismail.Fliss{at}fsaa.ulaval.ca
Received June 20, 2008. Accepted September 18, 2008.
 |
ABSTRACT
|
|---|
Plants produce small cysteine-rich antimicrobial peptides as
an innate defense against pathogens. Based on amino acid sequence
homology, these peptides were classified mostly as

-defensins,
thionins, lipid transfer proteins, cyclotides, snakins and hevein-like.
Although many antimicrobial plant peptides are now well characterized,
much information is still missing or is unavailable to potential
users. The compilation of such information in one centralized
resource, such as a database would therefore facilitate the
study of the potential these peptide structures represent, for
example, as alternatives in response to increasing antibiotic
resistance or for increasing plant resistance to pathogens by
genetic engineering. To achieve this goal, we developed a new
database, PhytAMP, which contains valuable information on antimicrobial
plant peptides, including taxonomic, microbiological and physicochemical
data. Information is very easy to extract from this database
and allows rapid prediction of structure/function relationships
and target organisms and hence better exploitation of plant
peptide biological activities in both the pharmaceutical and
agricultural sectors. PhytAMP may be accessed free of charge
at
http://phytamp.pfba-lab.org.
 |
INTRODUCTION
|
|---|
The first antimicrobial peptide from a eukaryotic organism,
wheat

-purothionin, was discovered in 1942 by Balls and collaborators
(
1). The next peptide in this category was not reported until
30 years later and studies describing the discovery of new antimicrobial
peptides from plant tissues have become numerous only in recent
years (
2). Antimicrobial peptides (AMPs) are cysteine-rich short
amino acid sequences common in the seeds of many species (
3).
Plant AMPs are grouped into several families and many share
general features, such as an overall positive charge, the presence
of disulfide bonds (which stabilize the structure) and a mechanism
of action targeting outer membrane structures, such as ion channels.
In addition to their role in host defense and their appeal as
simple models for studying the molecular mechanism of antimicrobial
peptide action, AMPs have the potential to combat pathogens,
including those showing increased resistance to conventional
antimicrobial compounds. These peptides usually have broad-spectrum
antimicrobial activity against pathogenic fungi and thus are
promising candidates for managing diseases in sensitive transgenic
plants (
4). Although many plant AMPs are now well characterized,
much physicochemical and structural information is still missing,
unavailable to potential users or buried in the scientific literature.
The majority of sequenced AMPs are stored in the manually annotated
UniProtKB/Swiss-Prot which represents a large database with
broad domains. Thus, there is a clear need to gather, filter
and critically evaluate this mass of information and store into
smaller, more specialized, resources so that it can then be
used in a way that enhances efficiency. Few different databases
have been created for antimicrobial peptides and are mentioned
in the literature. ANTIMIC (
5) database is currently inactive.
The Antimicrobial Peptide Database (APD) (
6) contains general
information about peptides of all types having antibacterial,
antifungal or antiviral activities and originating from either
eukaryotic or prokaryotic cells. Plant AMPs are not described
with sufficient details in this database. A centralized resource,
such as a database designed specifically for plant AMPs would
facilitate the comprehensive investigation of their structure/activity
associations and potential uses. This could have implications
not only for the genetic improvement of plants by increased
resistance to pathogens, but also for the development of new
drugs for medical use.
 |
CONSTRUCTION AND CONTENT
|
|---|
Database construction and methods
PhytAMP runs on a Windows NT platform (Microsoft Windows 2000)
with the Apache web server (version 2.0.54), MySQL server (v
5.0.30) and PHP (v 4.3.11). The web server and all parts of
the database are hosted at the Centre de Calcul El Khawarizmi
(CCK), Tunisia. Antimicrobial plant peptide sequences were collected
from the UniProt database (
7) and from the scientific literature
using PubMed. Microbiological information was collected from
the literature by PubMed search. Since not all known AMPs sequences
were present in the ExPASy (
http://www.expasy.org/srs/) SRS
server or NCBI server (
http://www.ncbi.nlm.nih.gov/entrez/),
literature search was used to complete the PhytAMP sequence
database. Sequences were retrieved in SciDBMaker (
8) and curated
and the resulting tables exported to the MySQL server. The FASTA
program (
9) was used for the sequence homology search in the
database. The BLAST search (
10) was implemented using the NCBI
binaries. The Smith–Waterman search was implemented using
the SSEARCH program from the FASTA3 distribution (
9). The sequence
alignment was done using various methods, such as ClustalW (v2.07)
(
11), MUSCLE (v3.6) (
12) and T-Coffee (v1.37) (
13). The Java
platform is required for visualizing generated phylogenic trees.
The program HMMER was used for the implementation of hidden-profile
Markov models (
14). The peptides collected in this version of
PhytAMP are mainly from natural sources. Precursor sequences
were removed to keep only mature peptide sequences. For each
peptide, a unique nine-digit identification number (ID) starting
with the prefix PHYT was assigned. Each entry was checked in
the Protein Data Bank (PDB) or UniProtKB/Swiss-Prot. A web link
in PhytAMP to UniProt and PDB was created for all peptides that
already exist in these databases, to facilitate consultation
of the original databases. In addition, each entry contains
general data, such as peptide name, sequence, class, plant taxonomy,
activity data (bacterial, fungal or viral target) and relevant
references in the UniProt. Additional physicochemical data are
provided, including empirical formula, mass, length, isoelectric
point, net charge, the numbers of basic, acidic, hydrophobic
and polar residues, hydropathy index, binding potential index,
instability index, aliphatic index, half-life in mammalian cells,
yeast and
Escherichia coli, cysteine and glycine content, extinction
coefficient, absorbance at 280 nm, absent and most prevalent
amino acids, secondary (

-helix or β-strand) and tertiary
structure (when available), physical method used for structural
determination (e.g. NMR spectroscopy or X-ray diffraction) and
critical residues for activity, when information is available.
Web interface description
PhytAMP database is available at http://phytamp.pfba-lab.org. There are various ways to access to information related to a given peptide in PhytAMP database. The simplest way is to use the browse interfaces (general information, physicochemical data, structural data, taxonomy and literature). A quick search formula on the header part on browse web pages is included for keyword search. An extended search interface (query for general information, physicochemical data, structural data, taxonomy and literature) is provided for combined search. Various tools and links are also provided including user sequence analysis interface, user sequence similarity search interface, statistical data, useful links and contact information (Figure 1). The query forms provide quick or advanced search with a variety of parameters. Users can find a specific antimicrobial plant peptide using its ID, name or UniProt ID, query for lists of organisms targeted by a plant AMP or for lists of AMPs that target a specific organism. Detailed information for each entry in the database can be viewed by clicking on the peptide name. The advanced search tool allows query of all available data. When a sequence is entered, the program returns all peptides containing this sequence and search results can be sorted into visible columns. A combinatorial search can be done by query of search results. Files containing the sequence (Fasta format) may be downloaded for all of the entries identified by the query, to facilitate other analyses. Registered users can also download output result tables in XLS, DOC, XML and CSV format. In addition, various tools including BLAST, FASTA and SSEARCH enable users to search the database for homologous sequences and save successful results temporarily in the server for subsequent access. Users may thus select some or all of the homologous sequences for multiple aligning with their submitted sequences. The statistical interface provides data on peptide sequence, function and structure. The average length, net charge and amino acid residue percentages for all entries in the database are also listed, as is the frequency of given values for each physicochemical parameter. For structural analysis, the number of peptides with a defined structural type is shown.
 |
UTILITY AND DISCUSSION
|
|---|
Phylogenetic tree construction
Multiple sequence alignments of 271 plant antimicrobial peptides
found in the PhytAMP were made using the CLUSTALW v2.07 program
(
11) and further refined manually. The parameters used in the
CLUSTALW program were as follows: gap opening, 10; gap extension,
0.2; delay divergent sequence, 30%; DNA transition weight, 0.5;
protein weight matrix, Gonnet series. Based on the initial alignment,
a resample was performed by the generation of 1000 bootstrapped
data sets using the SEQBOOT program (
15). Genetic distances
of the alignments were calculated using the Dayhoff PAM matrix
with the PROTDIST program (
15). Subsequently, the trees were
constructed by successive clustering of lineages using the neighbor-joining
algorithm as implemented in the NEIGHBOR program (
15). Their
strict consensus tree was obtained using the CONSENSE program
(
15). The unrooted tree diagram was generated with the FigTree
program (
http://tree.bio.ed.ac.uk/software/figtree/). 3D structure
data were obtained from the PDB (
http://www.rcsb.org/pdb) and
edited with the molecule analysis and molecule display (PyMOL)
program (
http://www.pymol.org).
The PhytAMP database
The current version of PhytAMP holds 271 antimicrobial plant peptides (AMPs), secreted by various families, such as Amaranthaceae [9], Andropogoneae [10], Brassicaceae [36], Oryzeae [11], Santalaceae [11], Spermacoceae [17], Triticeae [34], Vicieae [12] and Violaceae [51]. Classification has been proposed on the basis of primary structure (16, 17). Viola (family Violaceae) and Arabidopsis (family Brassicaceae) appear to be the predominant genera among AMP producers, although this may be due to the extensive studies on these species. Plant AMPs in the database are classified as cyclotides [76], defensins [55], Hevein-like [14], Impatiens [4], knottins [4], lipid-transfer proteins [45], shepherins [2], snakins [20], thionins [43] or vicilin-like [6], MBP-1 (18) and beta-barellin (19). An unrooted tree of the AMPs was generated, as shown in Figure 2. It is noteworthy that only 69% of the peptides have been sequenced directly, the remaining structures having been predicted from genome sequences. For 83.4%, the amino acid sequence length varies from 20–67 (Figure 3). Table 1 summarizes the amino acid percentages. It is generally presumed that AMPs are cysteine-rich proteins and this was apparent in our statistical results. Glycine is also an abundant amino acid, 98.5% of these AMPs containing at least one glycine residue. The majority (84.9%) have net charges varying from 0 to +10, while <6% possess a positive charge superior to +10, the highest being +17 (PHYT00099). In addition, only 9.2% have a net negative charge, the most negative being –6 (PHYT00259). As a result, the average net charge of all AMPs in PhytAMP is +4.6. Figure 4 shows the correlation between acidic (a) and basic (b) amino acid content and sequence length among peptides in the PhytAMP database. In general, peptides are randomly distributed across families, except sequence length 20 which correspond to cyclotide family and the cluster for sequence length about 90 which fall specifically in lipid-transfer protein family. The majority of sequences display a basic pattern, 53.1% having from 6–11 basic residues. In comparison, acidic residue content is more limited, 79.7% containing three or fewer acidic amino acids. Current analysis revealed that three quarters of the plant AMPs contain between 4 and 13 hydrophobic residues. Only 39 were found to have 3D structures filed in the PDB database and resolved by NMR spectroscopy, crystallography or molecular modeling. Some of them nevertheless possess more than one structure in the PDB database, bringing the total number of 3D entries to 102. Only 39.5% are tested for biological activity. The majority possesses antifungal (51%), antibacterial (33%) and antiviral (10%) activities, as shown in Figure 5. These findings may be useful in isolating and characterizing novel plant AMPs or designing novel peptides with higher potency against pathogens or with broad antimicrobial spectra. As future development, we plan to integrate a system that will allow automatic prediction of the amino acids that are key to biological function and a server for building tertiary structures by homology with existent plant AMP structures.
 |
CONCLUSION
|
|---|
PhytAMP allows all plant AMP sequence information and physicochemical
or biological data to be accessed via a user-friendly, web-based
interface. The database can be queried using various criteria
and retrieval of microbiological or physicochemical data includes
specific information on each peptide. The microbiological, physicochemical
and structural proprieties thus provided should allow more comprehensive
analysis of this group of antimicrobial peptides and enhance
our understanding of plant defense biology. This could contribute
not only to genetic improvement of plants by increased resistance
to pathogens, but also has implications for the development
of new drugs for medical use based on derivatives or analogs
of natural antimicrobial peptides. PhytAMP currently contains
271 entries of plant AMPs and is expected to grow quickly with
the rapid development of genomic and proteomic projects. As
more information about plant AMPs becomes available, the database
will be expanded and improved accordingly.
 |
FUNDING
|
|---|
The Natural Sciences and Engineering Research Council of Canada;
the Ministry of Higher Education, Scientific Research and Technology,
Republic of Tunisia.
Conflict of interest statement. None declared.
 |
ACKNOWLEDGEMENTS
|
|---|
Authors thank Dr. Stephen Davids for his critical reading of
the article.
 |
REFERENCES
|
|---|
- Balls AK, Hale WS, Harris TH. A crystalline protein obtained from a lipoprotein of wheat flour. Cereal Chem. (1942) 19:279–288.
- Broekaert WF, Terras FR, Cammue BP, Osborn RW. Plant defensins: novel antimicrobial peptides as components of the host defense system. Plant Physiol. (1995) 108:353–1358.[Abstract]
- Broekaert WF, Cammue BPA, De Bolle MFC, Thevissen K, De Samblanx GW, Osborn RW. Antimicrobial peptides from plants. Critical Rev. Plant Sci. (1997) 16:297–323.[CrossRef]
- Terras FR, Eggermont K, Kovaleva V, Raikhel NV, Osborn RW, Kester A, Rees SB, Torrekens S, Van Leuven F, Vanderleyden J, et al. Small cysteine-rich antifungal proteins from radish: their role in host defense. Plant Cell (1995) 7:573–588.[Abstract]
- Brahmachary M, Krishnan SPT, Koh JLY, Khan AM, Seah SH, Tan TW, Brusic V, Bajic VB. ANTIMIC: a database of antimicrobial sequences. Nucleic Acids Res. (2004) 32:D586–D589.[Abstract/Free Full Text]
- Wang Z, Wang G. APD: the Antimicrobial Peptide Database. Nucleic Acids Res. (2004) 32:D590–D592.[Abstract/Free Full Text]
- The Universal Protein Resource (UniProt). Nucleic Acids Res. (2007) 35:D193–D197.[Abstract/Free Full Text]
- Hammami R, Zouhir A, Naghmouchi K, Ben Hamida J, Fliss I. SciDBMaker: new software for computer-aided design of specialized biological databases. BMC Bioinformatics (2008) 9:121.[CrossRef][Medline]
- Pearson WR, Lipman DJ. Improved tools for biological sequence comparison. Proc. Natl Acad. Sci. USA (1988) 85:2444–2448.[Abstract/Free Full Text]
- Altschul SF, Madden TL, Schaffer AA, Zhang J, Zhang Z, Miller W, Lipman DJ. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res. (1997) 25:3389–3402.[Abstract/Free Full Text]
- Thompson JD, Higgins DG, Gibson TJ. CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res. (1994) 22:4673–4680.[Abstract/Free Full Text]
- Edgar RC. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. (2004) 32:1792–1797.[Abstract/Free Full Text]
- Notredame C, Higgins DG, Heringa J. T-Coffee: a novel method for fast and accurate multiple sequence alignment. J. Mol. Biol. (2000) 302:205–217.[CrossRef][Web of Science][Medline]
- Durbin R, Eddy S, Krogh A, Mitchison G. Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids (1998) Cambridge University Press: Cambridge.
- Felsenstein J. PHYLIP - Phylogeny Inference Package (Version 3.2). Cladistics (1989) 5:164–166.
- Garcia-Olmedo F, Molina A, Alamillo JM, Rodriguez-Palenzuela P. Plant defense peptides. Biopolymers (1998) 47:479–491.[CrossRef][Web of Science][Medline]
- Castro MS, Fontes W. Plant defense and antimicrobial peptides. Protein Pept. Lett. (2005) 12:13–8.[Web of Science][Medline]
- Duvick JP, Rood T, Rao AG, Marshak DR. Purification and characterization of a novel antimicrobial peptide from maize (Zea mays L.) kernels. J. Biol. Chem. (1992) 267:18814–18820.[Abstract/Free Full Text]
- McManus AM, Nielsen KJ, Marcus JP, Harrison SJ, Green JL, Manners JM, Craik DJ. MiAMP1, a novel protein from Macadamia integrifolia adopts a Greek key beta-barrel fold unique amongst plant antimicrobial proteins. J. Mol. Biol. (1999) 293:629–638.[CrossRef][Web of Science][Medline]

CiteULike
Connotea
Del.icio.us What's this?
This article has been cited by other articles:

|
 |

|
 |
 
S. Thomas, S. Karnik, R. S. Barai, V. K. Jayaraman, and S. Idicula-Thomas
CAMP: a useful resource for research on antimicrobial peptides
Nucleic Acids Res.,
November 18, 2009;
(2009)
gkp1021v1.
[Abstract]
[Full Text]
[PDF]
|
 |
|