African Journal of Biotechnology Vol. 2 (3), pp. 51-55, March 2003

ISSN 1684-5315  © 2003 Academic Journals  

Molecular phylogeny of Fusarium species by AFLP fingerprint

Mohmed A. Abdel-Satar¹, Mohmed. S. Khalil², I. N. Mohmed¹, Kamel A. Abd-Elsalam^2,3*, and Joseph A. Verreet³ 

¹Suez Canal University, Faculty of Agriculture, Ismailia, Egypt.

²Agricultural Research Center, Plant Pathology Research Institute, Giza, Egypt.

³Christian Albrechts Universität zu Kiel, Institut für Phytopathologie, Kiel, Germany.

*Corresponding author; Phone: (49 431) 880 2993; fax: (49 431) 880 1583; e-mail: kaabdelsalam@msn.com

The high-resolution genotyping method of amplified fragment length polymorphism (AFLP) analysis was used to study the genetic relationships within and between natural populations of five Fusarium spp. AFLP templates were prepared by the digestion of Fusarium DNA with EcoRI and MseI restriction endonucleases and subsequent ligation of corresponding site-specific adapters. An average of 44 loci was assayed simultaneously with each primer pair and DNA markers in the range 100 to 500 bp were considered for analysis. A total of 80 AFLP polymorphic markers were obtained using four primer combinations, with an average of 20 polymorphic markers observed per primer pair. UPGMA analyses indicated 5 distinct clusters at the phenon line of 30% on the genetic similarity scale corresponding to the 5 taxa. The similarity percent of each group oscillated between 87 and 97%. The phenetic dendrogram generated by UPGMA as well as principal coordinate analysis (PCA) grouped all of the Fusarium spp. isolates into five major clusters. No clear trend was detected between clustering in the AFLP dendrogram and geographic origin, host genotype of the tested isolates with a few exceptions. The results of the present study provide evidence of the high discriminatory power of AFLP analysis, suggesting the possible applicability of this method to the molecular characterization of Fusarium.

Key words: AFLP, Fusarium, molecular phylogeny, selective amplification.

Abbreviations: AFLP, amplified fragment length polymorphism; GS, genetic similarity; PCA, principal coordinate analysis; UPGMA, unweighted pair group method using arithmetic.

Fungal culture and DNA extraction

Fungal isolates utilized in this study are listed in (Table 1). DNA extractions were conducted as previously described in Liu et al. (2000) from 100 mg fresh fungal mycelium grown in 5 ml potato dextrose broth in 15 ml Falcon tube at 28°C. Cultures were filtered through a double layer of sterile muslin, and the mycelium was washed with sterile distilled water. DNA concentrations were quantified on agarose gels stained with ethidium bromide in comparison with commercially obtained standard.

 Table 1. Isolates of Fusarium spp analyzed in this study.    

   (Click to view table)

AFLP analysis

The AFLP procedure was carried out as reported by Vos et al. (1995) with few modifications. In brief, two combinations of restriction endonucleases were used. For the combination EcoRI/MseI, genomic DNA (50 ng) was incubated for 2 h at 37°C with 2 U of MseI, 5 U of EcoRI, 1.2 U of T4 DNA ligase (New England Biolabs, Beverly, Mass.), 50 pmol of MseI adapters and 5 pmol of EcoRI adapters. This reaction was done in a volume of 50 µl of restriction-ligation buffer containing 10 mM TRIS-acetate pH 7.5, 10 mM MgCl₂, 50 mM potassium acetate, 5 mM dithiothreitol (DTT), 1 mM ATP and 50 ng/µl BSA. For digestion with EcoRI/ MseI, genomic DNA (50 ng) was digested at 65°C for 1.5 h with 5 U MseI, in a volume of 25 µl of the restriction-ligation buffer described above. The reaction was cooled to 37°C, supplemented with 15 µl of the restriction-ligation buffer containing 5 U of EcoRI and incubated at 37°C for an additional 2 h. For adapter ligation, 10 µl of the restriction-ligation buffer, containing 50 pmol of MseI adapters, 5 pmol of EcoRI adapters, 0.5 mM ATP and 1.2 U of T4 DNA ligase, was added, and the reaction was incubated in 37°C for 3 h. In both cases, a 30-µl aliquot of the adapter-ligated DNA was diluted 1:10 with distilled water to serve as template in the preselective PCR. The remaining 20-µl portion was used to verify that digestion was complete.

The preselective PCR contained 5 µl of template, 1 U of AmpliTaq polymerase, 2 µl of 10 AmpliTaq polymerase buffer, 0.25 mM of each of the four dNTPs, 2.5 mM MgCl₂ and 25 ng of EcoRI and MseI primers with one selective nucleotide (A), in a total volume of 20 µl. The PCR program consisted of thirty cycles of 30 s at 94°C, 1 min at 56°C and 1 min at 72°C, followed by 10 min at 72°C.The selective PCR contained 5 µl of the diluted (1:10) product of the preselective PCR, 0.5 U of AmpliTaq polymerase, 2 µl of 10 AmpliTaq polymerase buffer, dNTPs and MgCl₂ as mentioned above, in a total volume of 20 µl. Four primer pairs; EcoRI+AG/MseI+AA, EcoRI+AA/MseI+AG, EcoRI+CC/MseI+AA and EcoRI+CC/MseI+CC (MWG-Biotech, Germany) were used for the selective amplification. The first amplification cycle was carried out for 30 s at 94°C, 30 s at 65°C and 1 min at 72°C. In each of the following 10 cycles, the annealing temperature was reduced by 1°C. The last 25 cycles were carried out at an annealing temperature of 56°C, and the final extension step was carried out at 72°C for 10 min. Each sample was diluted 1:1 with loading buffer, denatured and fractionated on a 5% polyacrylamide sequencing gel in TRIS-borate-EDTA buffer. Gels were run at constant power (55 W), and then stained by a modification of the silver staining method of Creste et al. (2001).

Data analysis

Polymorphic AFLP markers were manually scored as binary data with presence as "1" and absence as "0". Monomorphic markers were not scored. Cluster analysis was performed on the similarity matrix employing the "unweighted pair group method using arithmetic means" (UPGMA) algorithm (Sneath and Sokal, 1973) provided in the computer program NTSYSpc, version 2.1 (Exeter Software Co., New York).

Fast screening of AFLP primers combination

Thirty-two primer combinations were tested on five isolates from different populations. The generated fingerprints were evaluated for overall clearness of the banding pattern and the number of polymorphic markers present was recorded (data not shown). Four primer combinations were chosen for further screening on 46 Fusarium spp. isolates. Two primer combinations resulted in not-scoreable fingerprints due to the amplification of too many and/or faint bands. Finally, four primer combinations were chosen for the diversity screening; EcoRI+AG/MseI+AA, EcoRI+AA/MseI+AG, EcoRI+CC/MseI+AA and EcoRI+CC/MseI+CC.

Genetic diversity as defined by AFLP fingerprinting

A total of 176 bands were amplified from four primer combinations, of which 80 bands (45%) were polymorphic (Figure 1), with an average of 20 polymorphic bands per primer combinations. The genetic relationship among all AFLP patterns of Fusarium spp. based on the combination of data obtained with the four primers is represented in the dendrogram shown in Figure 2. A total of 80% of the isolates were clustered in the first major cluster with 30% similarity among them. The first major cluster divided into three subclusters, the first subcluster included all F. oxysporum with genetic similarity of GS=34%, isolates Fo16 and Fo25 showed very high genetic similarity of GS=99.80%. F. chlamydosporum constituted one cluster branched from the second main cluster at level of 33%. The second subcluster consist of the six isolates of F. solani at the genetic similarity of GS=90%, isolates Fs2 and Fs5 showed very high genetic relatedness. The third subcluster included all F. avenaceum isolates at the genetic similarity of GS=93%. The minor cluster contains all F. moniliforme at the genetic similarity of GS=26%, isolates Fm3 and Fm7 showed very high genetic similarity relatedness, although they came from Minufiya governorate and isolated from Giza 89. There was no clear-cut relationship between clustering in the AFLP dendrogram and geographic origin, host genotype of  the tested isolates with a few exceptions. The similarity percent of each group oscillated between 87 and 97%. The results of the AFLP analysis showed great genetic diversity among the Fusarium spp.  

Figure 1.   Normalized AFLP band patterns generated from 46 Fusarium spp. isolates using primer combinationsEcoRI+AA/MseI+AG. M is a 50 bp (numbers represent size in bp).

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Figure 2. Combined cluster analysis derived from AFLP analysis of 46 Fusarium spp. isolates using 4 AFLP primers.

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Principal coordinate analysis (PCA)

The PCA is one of the multi-variate approaches of grouping based on the similarity coefficients or variance-covariance values of the component traits of the entities. It is expected to be more informative about differentiation among major groups, while the cluster-analysis provides higher resolution among closely related populations (Liu et al., 2001). In our PCA analysis, more than 70% of the variation in the estimates of genetic similarity was explained by the first three components, indicating the suitability of the AFLP approach for genetic clustering. The isolates of each species and the groups within Fusarium spp. were clearly assigned to distinct group. Isolates of F. moniliforme, F. solani and F. oxysporum are most distinctly separated and were located at the marginal position on the plane defined by X, Y and Z axis respectively. Isolates within the species F. oxysporum and F. moniliforme were densely aggregated and intra-specific variability was not discernable, F. solani isolates formed a more dispersed group. Isolates of F. avenaceum and F. chlamydosporum were placed between the groups of F. moniliforme, F. solani and F. oxysporum isolates. Hence, PCA (Figure 3) agreed well with the UPGMA cluster.

Figure 3. Three-dimensional display generated by NTSYS of principal coordinate analysis (PCA) of five Fusarium spp. based on the combination of data obtained with the four AFLP primers. X, Y and Z-axes are accounted 70% of the variation observed.

For a wide range of taxa, including plants, fungi and bacteria, AFLP markers have been used to uncover cryptic genetic variation of strains, or closely related species, that have been impossible to resolve with morphological or other molecular systematic characters. Therefore, AFLP have broad taxonomic applicability and have been used effectively in a variety of taxa including bacteria (Huys, 1996) and fungi (Majer et al., 1998). In view of the results of the present study, complex AFLP patterns were obtained using four different primer pairs and genomic similarity analyses derived from qualitative data enabled us to identify 46 isolates of five Fusarium spp. whose taxa had been uncertain based on morphological criteria. We have demonstrated that AFLP markers are useful in the study of genetic variation of Fusarium isolates. Using four primer combinations with EcoR1 (E) + 2 and MseI (M) + 2 at the 3`-end of the primers on 46 isolates, a total of 176 bands were amplified with 80 polymorphic bands. Janssen et al., (1996) have showed that the choice of the restriction enzymes and the length and composition of selective nucleotide will determine the complexity of the final AFLP fingerprint. The present finding is consistent with the work of Majer et al. (1996) in the AFLP analysis of pathogenic isolates of Cladosporium fulvum where they used E + 2 and M + 2 nucleotides. Gonzalez et al. (1998) also used two instead of three selective nucleotides (E + 2 and M + 2) in order to generate adequate number of fragments for AFLP analysis of C. lindemuthianum isolates. Primer selectivity is good for primers with one or two selective nucleotides in simple genomes such as fungi, bacteria and some plants, although selectivity is still acceptable with primers having three selective nucleotides, but it is lost with addition of the fourth nucleotide (Vos et al., 1995). 

Statistical analysis of AFLP data enabled the classification of Fusarium isolates from Egypt into 5 AFLP groups, although these groups were not genetically distinct. There was no correlation between AFLP and geographic origin of the isolates, our result in harmony with these obtained by Abd-Elsalam et al. (2002a) and Kiprop et al. (2002). The similarity matrices generated by each of four primer pairs were highly correlated and were combined to determine the genetic relationships among the Fusarium species and isolates. Genetic similarity was detected among and within Fusarium spp. More than 30% similarity was found between 46 isolates of five Fusarium spp, and there was more than 85% similarity between F. solani and F. moniliforme.

AFLP analysis will be useful in the identification of genetic diversity and analysis of population structure within complex genera such as Fusaria. Leissner et al. (1997) has employed AFLP fingerprinting methodology to study 18 different Fusarium graminearum strains. Fifteen of the 18 strains showed a high degree of similarity in banding patterns. The banding patterns of the remaining three strains completely differed from the F. graminearum pattern found. Of these strains, one was revealed as F. cerealis by comparison of its pattern against an AFLP database of different Fusarium species. O’Neill et al. (1998) also found that there was less than 70% similarity between F. udum and F. oxysporum formae species pathogenic to coca, cowpea, and tomato. In our PCA analysis, more than 70% of the variation in the estimates of genetic similarity was explained by the first three components, indicating the suitability of the AFLP approach for genetic clustering. Use of the AFLP fingerprinting method resulted in a high degree of discrimination and identification of Fusarium spp. isolates and was found to be useful and practical.

ACKNOWLEDGEMENT

This research was partly supported by funding from Institut für Phytopathologie, Christian Albrechts Universität zu Kiel, D-24118, Kiel, Germany.