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Phylogenetic Analysis of the SecA gene in Phytoplasmas
Phylogenetic Analysis of the SecA gene in Phytoplasmas
Clare Elliott
Dissertation submitted to The University of Nottingham in partial fulfilment of the requirements for the degree of Bachelor of Science with Hons Biology
figures available on request
Abstract
Phytoplasmas are small bacteria lacking a cell wall, they cannot be cultured in vitro, and have been identified as the causative agents of a number of plant diseases resulting in a wide range of symptoms. These pathogens have a large number of plant hosts covering much of the tropics, and include some economically important crop plants. This investigation aims to further research into the phylogenetic position of this group of mollicutes and assess the current methods of classification as well as potentially lead on to the development of more accurate and practical methods for the detection and diagnosis of phytoplasma infections in the field. Using nested PCR techniques the SecA gene was amplified from phytoplasma DNA samples and cloned into the pGEM-T Easy vector system using E. coli. The SecA gene was sequenced and a phylogenetic analysis conducted using DNASTAR. Eleven phytoplasma SecA gene initial sequences are published, 9 of which are from the group I phytoplasmas. Analysis of the phylogenetic relationships between these sequences concurs with the sub-groupings in the existing classification system. This is the first time a phylogenetic analysis of the phytoplasmas classification has been based on a non-ribosomal gene sequence. Results confirm the classification system currently based on 16S rRNA sequence data. The low guanine and cytosine levels of the phytoplasma genome were confirmed. Additional primers for the SecA gene were designed giving the potential to sequence the SecA gene in many more phytoplasmas in all the groups.
Results
Phylogenetic Analysis
Figure 3.17 illustrates the phylogenetic relationships between the SecA gene sequences of the phytoplasmas in Table 3.2. The tree includes some published sequences to compare how the sequences are arranged in groups using the SecA gene sequences so that this can be compared with the groups and subgroups in the classification based on the 16S rRNA gene. The Lactobacillus sequence acts as an outlier. PWB and BVK (shown in grey in Table 3.2) were not included as these were not good sequences. AYA, AYC and DIV sequences were also omitted from this phylogenetic tree as they presented problems when aligning the sequences together. The ‘onion publish’ sequence in the tree is a group I-B phytoplasma. The ‘aster publish’ sequence is a group I-A phytoplasma. The top four sequences (red) have all been grouped closely together in the tree and these sequences are all from group I, subgroup B phytoplasmas. RIV and KVE (blue) are both group I, sub group C phytoplasmas and these sequences have been grouped closely together. CHRYM and the published aster sequence (green) have also been grouped together which is also in accordance with their grouping as I-A phytoplasmas based on the 16S rRNA gene classification. However LWB (group II) and STOL-IT (group XII) have been grouped together in this tree but this is not in accordance with the classification using the 16SrRNA gene.
Figure 3.17; Phylogenetic tree showing the relationships between the SecA gene sequences obtained during this project (Appendix B, Table 0.3)
In colour are the group I phytoplasmas, in red are sub group B, in blue, C, and in green, A.
Discussion
Phylogenetic Analysis
Between Group Analysis
The primers used have enabled the sequencing of many group I phytoplasmas and only two good sequences from other groups (Table 3.2) so a meaningful comparison of the phylogenetic analysis based on the SecA gene sequence with the existing phytoplasma classification system based on 16S rRNA genes was not possible. It can be seen from the phylogenetic tree in Figure 3.17 that all the group I phytoplasmas are more closely related than the other phytoplasma SecA sequences here. In this analysis LWB and STOL IT have been stuck together but since they are from groups II and XII respectively this is unexpected. It is possible that LWB should be classified as a group XII phytoplasma. Alternatively this could have arisen from errors in the sequences as discussed further in paragraph 4.1.2.
Within Group Analysis
It was possible to sequence the SecA gene from 9 phytoplasma samples in group I which enabled a within group analysis of the phylogeny and classification of phytoplasmas, visualised in Figure 3.17. This phylogenetic tree groups the phytoplasma SecA gene from the group I phytoplasmas according to their sub groups as defined by the 16S rRNA gene classification (Lee et al., 2000). There were some problems encountered when attempting to align the sequences for phylogenetic analysis (Appendix B, Table 0.3). Some difficulties in alignments may have been due to miss reads in the sequencing process. Figure 4.1 shows how discerning the correct sequence can be difficult and mistakes can be introduced. For example between bases 590 and 600 it is hard to determine exactly how many bases of thymine there are, and later it is difficult to say whether base 609 should be guanine or adenosine. The sequences displayed in Appendix A are the crude data from the initial sequencing. In order to improve the accuracy of sequences the entire gene must be sequenced in both directions and then compared together. The sequences for AYA, AYC and DIV were relatively unclear and were therefore excluded from the phylogenetic analysis.
Figure 4.1; Chromas 2.31 visualisation of part of the STOL IT sequence which is difficult to discern
Comparison of Phylogenetic Trees
Figure 3.17 shows that the SecA gene sequences separate nicely into the three subgroups (A, B and C) of the group I phytoplasmas. This grouping concurs with the classification of the phytoplasmas based on the 16S rRNA gene (Seemüller et al., 1998). This is the first time a phylogenetic analysis of the phytoplasmas classification has been based on a non-ribosomal gene sequence and these results confirm the use of the 16S rRNA gene as suitable for phylogenetic classification. These findings also confirm the high degree of relatedness between the aster yellows group of phytoplasmas (group I) and may add to the debate over whether there is scope for further divisions in the classification system for these phytoplasmas (Firrao et al., 2005).
Low Guanine and Cytosine Levels
Analysis of the sequences obtained in this study (in full in Appendix A) confirms that the G+C content of the phytoplasma genome is extremely low (Christensen et al., 2005). The data gathered from the sequences obtained in this study (Table 3.2) shows that the average G+C content of the SecA gene is 35.1% (excluding the PWB and BVK sequences which were questionable, Table 3.2). This is probably the lowest level of G+C in any known functioning genome and could be the lowest threshold for viability. It is interesting to note that the Aster Yellows phytoplasmas (group I-B) tend to have around 5% higher levels of G+C in their genome. This may be linked to the fact that there are many phytoplasmas in this group with very closely related genomes. Perhaps this higher amount of G+C allows for the more rapid evolution of successful variants through random mutations. The increasingly global movement and ever faster transport of plant species around the world and the fact that phytoplasmas are hosted by both plants and insects puts ever changing selection pressures on phytoplasmas in geographically isolated areas (Lee et al., 2000). These factors may account for the numbers of similar phytoplasmas calling for the sub-grouping of the classification system of phytoplasmas.
PCR and Primers
Polymerase Chain Reaction
Some problems encountered in getting the primers to amplify the desired fragment of DNA could be overcome given more time to adjust and perfect the PCR conditions. This may account for the sequencing of a plant heat shock protein rather than the PWB SecA gene as desired (Table 2).
New Primers
The new primers designed during this project showed promise but there was not sufficient time to get positive results. It is recommended that further combinations of primers are used in nested PCR reactions to try to optimise the results (3.2.4). Judging by the initial success of the results here (Table 3.2) using the first primers based on only three phytoplasmas sequences (Appendix A, Table 0.1) it should be possible to sequence the SecA gene of phytoplasmas from all the groups.
Conclusions and Future Prospects
These data confirm the validity of the classification system currently based on the 16S rRNA gene. The phylogenetic sub groupings resulting from analysis of the relatively less well conserved SecA gene sequences obtained in this investigation are in agreement with the sub groupings resulting from analysis of the 16S rRNA gene. Results will be more conclusive when SecA gene sequences are obtained from all the different Candidatus phytoplasma groups. Further work with the new primers designed in this study (Section 3.2) will play a key role in this process. Additional sequencing of the SecA gene in both directions will provide more precise sequences and will allow a more accurate phylogenetic analysis of the SecA gene sequences of the phytoplasmas. Further understanding of the SecA gene in phytoplasmas may well lead to the development of more efficient and accurate diagnostic techniques for phytoplasma infections of plants.
The Effect of Temperature on Sporulation of Hop Powdery Mildew
The Effect of Temperature on Sporulation of Hop Powdery Mildew
Clare R. Elliott
Oregon State University, Department of Botany and Plant Pathology, Corvallis, OR
Introduction
Disease forecasting systems are becoming increasingly important tools in agriculture. Particularly as scientific methods for monitoring the environmental conditions in the field have become more reliable, communications systems more efficient and modeling software more accurate. However, their utility is often limited due to a lack of understanding of, and/or ability to model the pathogen biology and its relationship to disease development.
Hop powdery mildew (Podosphaera macularis), is an economically important disease of hops (Humulus lupulus L.) worldwide which can result in 100% crop loss if not controlled. It is a polycyclic disease that can have as many as 50 generations in a growing season (7). Current management is accomplished using protectant fungicides applied based on a calendar program or an infection risk forecaster (4) that was adapted from the Gubler/Thomas infection risk forecaster for grape powdery mildew (3). Its’ use has resulted in the reduction of fungicide applications used to manage hop powdery mildew (HPM) but it still appears to call for unnecessary applications (Mahaffee, unpublished).
Current HPM models assume that the secondary spores are always present during the asexual phase of the epidemic (4). This assumption may not always be true. It is likely that conditions for sporulation and dissemination do not always precede conditions conducive to infection. Thus the model would incorrectly classify periods as high risk for infection even when there are no viable spores available, potentially resulting in excessive fungicide applications.
Exposure to temperature above optimum has been shown to reduce lesion size (7) and preliminary investigations have shown that sporulating colonies exposed to temperatures >30ºC for 6h result in spores with reduced infection potential 15h after exposure (Mahaffee, unpublished). Field surveys also indicate that the rate of disease development also decreases during July and August when temperatures routinely exceed 30ºC for more than 6h continuously (1,4). The magnitude, length and time of exposure to supraconducive temperatures in relation to time of inoculation has been observed to significantly affect disease development of HPM (5) and it is likely that temperature impacts spore availability in a similar manner.
There have been no studies on the temperature effect of sporulation for P. macularis but there has been some similar work on other genera of powdery mildew. Experiments on grape powdery mildew (Uncinula necator) by Chellemi and Marois (1, 2) found that sporulation was reduced with increasing temperatures above 26ºC. Similarly, experiments on begonia powdery mildew (Oidium begoniae) by Quinn and Powell (6) showed that temperatures above 28ºC caused inhibition of sporulation. These data indicate that accounting for the effects of temperature on sporulation may enhance accuracy of disease or infection risk models.
The aim of this study was to assess the effect of temperature on the sporulation of Podosphaera macularis. It will then be possible to consider the usefulness of this information in developing a forecasting model for hop powdery mildew and to suggest further investigation to lead to the development of an improved forecasting technique.
Materials and Methods
Plant preparation. Greenwood cuttings of the Symphony variety were propagated, from clonal mother plants, into 4” pots of Sunshine mix #1 (SunGro Horticulture, Bellevue, WA) with Soil Moist granules (JRM Cleveland, OH) added to the soil and APEX nursery fertilizer 14-14-14 pellets (JR Simplot Company, Lathrop, CA) on the soil surface. Plants were fertigated with Sunshine Technigro 16-17-17 (SunGro Horticulture, Bellevue, WA) when watered. Sulphur was vaporized for 4h each night to keep the plants free of powdery mildew. Plants were pruned to maintain one bine which was trained clockwise around stakes. Plants were grown under greenhouse conditions (15-26ºC) where light was supplemented with high pressure sodium lamps to achieve a photoperiod of at least a 15h.
Inoculation. A field population of P. macularis, isolated from Oregon hop yards, maintained on successive transfers of potted symphony plants incubated in growth chambers at 13ºC with a 15h photoperiod (~300µmol/m2/s) was used for all inoculations. Inoculum was prepared by selecting infected hop leaves and rubbing the spores from the lesions into a solution of 0.01% (w/v) TWEEN 20. Plants with 4 to 6 unfurled leaves were inoculated with a spore suspension of 60,000 conidia/ml using a hand held atomizer (Nalgene, Rochester, NY) after the apical bud was removed. Plants were air dried at 25ºC within an hour of immersing leaves in the TWEEN solution (to prevent lysis of the conidia). Plants were then incubated at 18ºC in a growth chamber with a 15h day length until mature, sporulating lesions had developed (typically 9-10 days after inoculation).
Effect of constant temperature on sporulation. Plants with mature, sporulating lesions were prepared for the temperature treatments by removing all but the single most infected leaf, blowing the available spores from the lesions using a 14000kg/m2 (20psi) air supply, and positioning the stem so that the leaf was 8cm above the top of the pot. Plants were then placed in 29.5 cm × 11.8 cm × 12.1 cm plastic vessels (Snapware, Inc, Mira Loma, CA) with an airtight lid. A custom impaction spore sampler was mounted in the lid (figure 1). The trap was capable of sampling 57L/min when using 1.5 mm × 22 mm acrylic rods. Perforated tubing was placed around the stem of the plant and linked to an air source (figure 1). Plants were placed at each temperature, 5, 10, 15, 20, 25, and 30ºC and incubated for 48 h with a 15h photoperiod (~300µmol/m2/s). After transferring two acrylic rods coated with petroleum jelly to each spore trap, the traps were turned on and 30 x 1 sec air blasts (28,000kg/m2) were administered using the perforated tubing. After running the traps for 15 min rods were collected and number of spores on the leading edge enumerated microscopically. Leaf and lesion area was determined using Access image analysis software (APS Press, St. Paul, MN). Data were transformed to trapped spores/cm2 of lesion area for each leaf.
Experimental design and statistical analysis. The experiment was a randomized complete block design with replication in time and 3 sub samples per replication. Between each replication, growth chambers were randomly assigned temperatures and reprogrammed. A control vessel was placed in each growth chamber, which consisted of a plant with mature, sporulating lesions and a thermo coupler inside to monitor temperature.
Figure 1. Custom impaction spore sampler.
1) Motor; 2) Power supply wire; 3) Air tight lid; 4) Plastic vessel; 5) Training stake; 6) Tape to secure leaf; 7) Infected hop plant; 8) Air supply inlet; 9) Perforated tubing; 10) Plant pot.
Results
Effect of constant temperature on sporulation. There was a significant curvilinear relationship between temperature and trapped spores. It shows that there is a lot of variation between the results in each temperature treatment. Figure 2 shows the average of all the repetitions at each temperature treatment. It indicates that there is a steady increase in sporulation with temperature increase up to 20ºC. The graph plateaus around 25ºC which where the maximum average sporulation occurs. The graph then declines as the temperature reaches 30ºC.
Figure 2: Effect of temperature on sporulation. Symbols represent mean number of spores/cm2 from 6 replications. Bars indicate standard deviation from the mean
Discussion
Effect of constant temperature on sporulation. The results in figure 2 show the expected trend, of increasing sporulation up to 25ºC and then a decline in the level of sporulation.
However there is a wide range of data observed at each temperature treatment and there is not a significant difference between temperature treatment even though figure 2 shows a trend in the data there is too much variation for this to have any significance with such a small sample size.
There are several factors that can be identified as possible sources variation.
Condensation was present in some of the tubes but not others which is indicative of differences in relative humidity. RH has been shown to influence sporulation slightly. Quinn and Powell (6) observed that decreasing relative humidity caused slight decreases in conidial germination and the development of mildew colonies on begonia.
The presence of condensation in the tubes should be included as part of the statistical analysis to see if this had a barring on the sporulation results.
The leaves that were chosen for spore collection and lesion area analysis were not all the same size and there was variation in the maturity and density of the lesions. In some cases lesions were present on the underside of the leaves too. This may cause variation since the conidia will get blown differently here than the lesions on the upper surface of the leaf so spore samples may be higher in the cases where lesions were present on the underside of the leaves.
Some plants had thrips and/or mites present on the leaf surface which reduced the capacity of the lesions to produce spores.
It is possible to assess all of the leaves for mites or thrips after taking the photographic data so that any sub samples with these pests can be thrown out and thus remove another source of variation.
Post analysis assessment of the photographs may shed light on the quality of the lesions and could indicate other sources of variation in the data.
Although the growth chambers were randomized and set to target temperatures it is possible that there was some fluctuation in the actual temperatures achieved and whether the temperature remained constant.
Extracting the temperature readings from the thermo coupler in the control plants It was found that the chambers didn’t always attain the target temperature. The average temperatures for each chamber were calculated for each treatment. This allowed the data to be plotted against a more accurate temperature scale rather than against the target temperature intervals.
The total area of each leaf in the sub samples should be calculated to see if it is a significant factor causing variation.
All of these are factors which were not properly controlled or accounted for in the data and could have been a cause of the high degree of variation that was observed in the data in figure 2.
After these factors have been accounted for in the existing data further statistical analysis may show more significant trends in the data and less variation or noise.
Improvements for further experiments. The observed variation in the data indicates that further improvement in experimental design is necessary to address the significant uncontrolled experimental error.
It was found that some of the data from the thermo couplers in the control plant tubes gathered inaccurate data and so it is suggested that new, more accurate HOBO’s are purchased to gather both temperature and relative humidity (RH) data from the control plants to allow the sporulation data to be plotted against a more accurate temperature scale. This would smooth out variation caused by fluctuations in the growth chamber temperatures. The inclusion of RH data could also be of benefit in analyzing the data.
When setting up the experiment, where possible all equipment should be assembled on the start date of the temperature treatments to minimize any unnecessary disturbance to the plants on the sampling date.
An improved method of applying the inoculum could be devised to ensure that leaves of similar area are inoculated with a similar number of spores, resulting in a more uniform density of lesions and eliminating the variation of lesions forming on the underside of the leaves.
Application. With this knowledge the current hop powdery mildew forecasting model could be improved (4). Rather than assuming that the inoculum is always present the observed temperature in the field can be used to predict a level of inoculum which when combined with data predicting the conduciveness of conditions for infection will provide more accurate forecasts for the disease development in the field. This will enable fungicide application at the appropriate times for maximum effectiveness and minimum waste.
Acknowledgements
I would like to thank Walt Mahaffee and Amy Peetz for their patient advice and guidance.
Literature Cited
Chellemi, D. O., and Marois, J. J. 1991. Effect of fungicides and water on sporulation of Uncinula necator. Plant Disease 75:455-157.
Chellemi, D. O., and Marois, J. J. 1991. Sporulation of Uncinula necator on grape leaves as influenced by temperature and cultivar. Phytopathology 81:197-201.
Gubler, W. D., Rademacher, M. R., Vasquez, S. J., and Thomas, C. S. 1999. Control of powdery mildew using the UC Davis powdery mildew risk index. Online. APSnet Feature Story, January 1999. American Phytopathological Society, St. Paul, MN.
Mahaffee, W.F., Thomas, C.S., Turechek, W.W., Ocamb, C.M., Nelson, M.E., Fox, A., and Gubler, W. D. 2003. Responding to an introduced pathogen: Podosphaera macularis (hop powdery mildew) in the Pacific Northwest. Online. Plant Health Progress doi: 10.1094/PHP-200301113-07-RV.
Mahaffee, W.F., Turechek, W.W., and Ocamb, C.M. 2003. Effect of variable temperature on infection severity of Podosphaera macularis on hops. Phytopathology 93:1587-1592.
Quinn, J. A., and Powell, C. C., Jr. 1982. Effects of temperature, light, and relative humidity on powdery mildew of begonia. Phytopathology 72:480-484.
Turechek, W.W., Mahaffee, W.F., and Ocamb, C.M. 2001. Development of management strategies for hop powdery mildew in the Pacific Northwest. Online. Plant Health Progress doi: 10.1094/PHP-2001-0313-01-RS.
Clare R. Elliott
Oregon State University, Department of Botany and Plant Pathology, Corvallis, OR
Figures available on request
Introduction
Disease forecasting systems are becoming increasingly important tools in agriculture. Particularly as scientific methods for monitoring the environmental conditions in the field have become more reliable, communications systems more efficient and modeling software more accurate. However, their utility is often limited due to a lack of understanding of, and/or ability to model the pathogen biology and its relationship to disease development.
Hop powdery mildew (Podosphaera macularis), is an economically important disease of hops (Humulus lupulus L.) worldwide which can result in 100% crop loss if not controlled. It is a polycyclic disease that can have as many as 50 generations in a growing season (7). Current management is accomplished using protectant fungicides applied based on a calendar program or an infection risk forecaster (4) that was adapted from the Gubler/Thomas infection risk forecaster for grape powdery mildew (3). Its’ use has resulted in the reduction of fungicide applications used to manage hop powdery mildew (HPM) but it still appears to call for unnecessary applications (Mahaffee, unpublished).
Current HPM models assume that the secondary spores are always present during the asexual phase of the epidemic (4). This assumption may not always be true. It is likely that conditions for sporulation and dissemination do not always precede conditions conducive to infection. Thus the model would incorrectly classify periods as high risk for infection even when there are no viable spores available, potentially resulting in excessive fungicide applications.
Exposure to temperature above optimum has been shown to reduce lesion size (7) and preliminary investigations have shown that sporulating colonies exposed to temperatures >30ºC for 6h result in spores with reduced infection potential 15h after exposure (Mahaffee, unpublished). Field surveys also indicate that the rate of disease development also decreases during July and August when temperatures routinely exceed 30ºC for more than 6h continuously (1,4). The magnitude, length and time of exposure to supraconducive temperatures in relation to time of inoculation has been observed to significantly affect disease development of HPM (5) and it is likely that temperature impacts spore availability in a similar manner.
There have been no studies on the temperature effect of sporulation for P. macularis but there has been some similar work on other genera of powdery mildew. Experiments on grape powdery mildew (Uncinula necator) by Chellemi and Marois (1, 2) found that sporulation was reduced with increasing temperatures above 26ºC. Similarly, experiments on begonia powdery mildew (Oidium begoniae) by Quinn and Powell (6) showed that temperatures above 28ºC caused inhibition of sporulation. These data indicate that accounting for the effects of temperature on sporulation may enhance accuracy of disease or infection risk models.
The aim of this study was to assess the effect of temperature on the sporulation of Podosphaera macularis. It will then be possible to consider the usefulness of this information in developing a forecasting model for hop powdery mildew and to suggest further investigation to lead to the development of an improved forecasting technique.
Materials and Methods
Plant preparation. Greenwood cuttings of the Symphony variety were propagated, from clonal mother plants, into 4” pots of Sunshine mix #1 (SunGro Horticulture, Bellevue, WA) with Soil Moist granules (JRM Cleveland, OH) added to the soil and APEX nursery fertilizer 14-14-14 pellets (JR Simplot Company, Lathrop, CA) on the soil surface. Plants were fertigated with Sunshine Technigro 16-17-17 (SunGro Horticulture, Bellevue, WA) when watered. Sulphur was vaporized for 4h each night to keep the plants free of powdery mildew. Plants were pruned to maintain one bine which was trained clockwise around stakes. Plants were grown under greenhouse conditions (15-26ºC) where light was supplemented with high pressure sodium lamps to achieve a photoperiod of at least a 15h.
Inoculation. A field population of P. macularis, isolated from Oregon hop yards, maintained on successive transfers of potted symphony plants incubated in growth chambers at 13ºC with a 15h photoperiod (~300µmol/m2/s) was used for all inoculations. Inoculum was prepared by selecting infected hop leaves and rubbing the spores from the lesions into a solution of 0.01% (w/v) TWEEN 20. Plants with 4 to 6 unfurled leaves were inoculated with a spore suspension of 60,000 conidia/ml using a hand held atomizer (Nalgene, Rochester, NY) after the apical bud was removed. Plants were air dried at 25ºC within an hour of immersing leaves in the TWEEN solution (to prevent lysis of the conidia). Plants were then incubated at 18ºC in a growth chamber with a 15h day length until mature, sporulating lesions had developed (typically 9-10 days after inoculation).
Effect of constant temperature on sporulation. Plants with mature, sporulating lesions were prepared for the temperature treatments by removing all but the single most infected leaf, blowing the available spores from the lesions using a 14000kg/m2 (20psi) air supply, and positioning the stem so that the leaf was 8cm above the top of the pot. Plants were then placed in 29.5 cm × 11.8 cm × 12.1 cm plastic vessels (Snapware, Inc, Mira Loma, CA) with an airtight lid. A custom impaction spore sampler was mounted in the lid (figure 1). The trap was capable of sampling 57L/min when using 1.5 mm × 22 mm acrylic rods. Perforated tubing was placed around the stem of the plant and linked to an air source (figure 1). Plants were placed at each temperature, 5, 10, 15, 20, 25, and 30ºC and incubated for 48 h with a 15h photoperiod (~300µmol/m2/s). After transferring two acrylic rods coated with petroleum jelly to each spore trap, the traps were turned on and 30 x 1 sec air blasts (28,000kg/m2) were administered using the perforated tubing. After running the traps for 15 min rods were collected and number of spores on the leading edge enumerated microscopically. Leaf and lesion area was determined using Access image analysis software (APS Press, St. Paul, MN). Data were transformed to trapped spores/cm2 of lesion area for each leaf.
Experimental design and statistical analysis. The experiment was a randomized complete block design with replication in time and 3 sub samples per replication. Between each replication, growth chambers were randomly assigned temperatures and reprogrammed. A control vessel was placed in each growth chamber, which consisted of a plant with mature, sporulating lesions and a thermo coupler inside to monitor temperature.
Figure 1. Custom impaction spore sampler.
1) Motor; 2) Power supply wire; 3) Air tight lid; 4) Plastic vessel; 5) Training stake; 6) Tape to secure leaf; 7) Infected hop plant; 8) Air supply inlet; 9) Perforated tubing; 10) Plant pot.
Results
Effect of constant temperature on sporulation. There was a significant curvilinear relationship between temperature and trapped spores. It shows that there is a lot of variation between the results in each temperature treatment. Figure 2 shows the average of all the repetitions at each temperature treatment. It indicates that there is a steady increase in sporulation with temperature increase up to 20ºC. The graph plateaus around 25ºC which where the maximum average sporulation occurs. The graph then declines as the temperature reaches 30ºC.
Figure 2: Effect of temperature on sporulation. Symbols represent mean number of spores/cm2 from 6 replications. Bars indicate standard deviation from the mean
Discussion
Effect of constant temperature on sporulation. The results in figure 2 show the expected trend, of increasing sporulation up to 25ºC and then a decline in the level of sporulation.
However there is a wide range of data observed at each temperature treatment and there is not a significant difference between temperature treatment even though figure 2 shows a trend in the data there is too much variation for this to have any significance with such a small sample size.
There are several factors that can be identified as possible sources variation.
Condensation was present in some of the tubes but not others which is indicative of differences in relative humidity. RH has been shown to influence sporulation slightly. Quinn and Powell (6) observed that decreasing relative humidity caused slight decreases in conidial germination and the development of mildew colonies on begonia.
The presence of condensation in the tubes should be included as part of the statistical analysis to see if this had a barring on the sporulation results.
The leaves that were chosen for spore collection and lesion area analysis were not all the same size and there was variation in the maturity and density of the lesions. In some cases lesions were present on the underside of the leaves too. This may cause variation since the conidia will get blown differently here than the lesions on the upper surface of the leaf so spore samples may be higher in the cases where lesions were present on the underside of the leaves.
Some plants had thrips and/or mites present on the leaf surface which reduced the capacity of the lesions to produce spores.
It is possible to assess all of the leaves for mites or thrips after taking the photographic data so that any sub samples with these pests can be thrown out and thus remove another source of variation.
Post analysis assessment of the photographs may shed light on the quality of the lesions and could indicate other sources of variation in the data.
Although the growth chambers were randomized and set to target temperatures it is possible that there was some fluctuation in the actual temperatures achieved and whether the temperature remained constant.
Extracting the temperature readings from the thermo coupler in the control plants It was found that the chambers didn’t always attain the target temperature. The average temperatures for each chamber were calculated for each treatment. This allowed the data to be plotted against a more accurate temperature scale rather than against the target temperature intervals.
The total area of each leaf in the sub samples should be calculated to see if it is a significant factor causing variation.
All of these are factors which were not properly controlled or accounted for in the data and could have been a cause of the high degree of variation that was observed in the data in figure 2.
After these factors have been accounted for in the existing data further statistical analysis may show more significant trends in the data and less variation or noise.
Improvements for further experiments. The observed variation in the data indicates that further improvement in experimental design is necessary to address the significant uncontrolled experimental error.
It was found that some of the data from the thermo couplers in the control plant tubes gathered inaccurate data and so it is suggested that new, more accurate HOBO’s are purchased to gather both temperature and relative humidity (RH) data from the control plants to allow the sporulation data to be plotted against a more accurate temperature scale. This would smooth out variation caused by fluctuations in the growth chamber temperatures. The inclusion of RH data could also be of benefit in analyzing the data.
When setting up the experiment, where possible all equipment should be assembled on the start date of the temperature treatments to minimize any unnecessary disturbance to the plants on the sampling date.
An improved method of applying the inoculum could be devised to ensure that leaves of similar area are inoculated with a similar number of spores, resulting in a more uniform density of lesions and eliminating the variation of lesions forming on the underside of the leaves.
Application. With this knowledge the current hop powdery mildew forecasting model could be improved (4). Rather than assuming that the inoculum is always present the observed temperature in the field can be used to predict a level of inoculum which when combined with data predicting the conduciveness of conditions for infection will provide more accurate forecasts for the disease development in the field. This will enable fungicide application at the appropriate times for maximum effectiveness and minimum waste.
Acknowledgements
I would like to thank Walt Mahaffee and Amy Peetz for their patient advice and guidance.
Literature Cited
Chellemi, D. O., and Marois, J. J. 1991. Effect of fungicides and water on sporulation of Uncinula necator. Plant Disease 75:455-157.
Chellemi, D. O., and Marois, J. J. 1991. Sporulation of Uncinula necator on grape leaves as influenced by temperature and cultivar. Phytopathology 81:197-201.
Gubler, W. D., Rademacher, M. R., Vasquez, S. J., and Thomas, C. S. 1999. Control of powdery mildew using the UC Davis powdery mildew risk index. Online. APSnet Feature Story, January 1999. American Phytopathological Society, St. Paul, MN.
Mahaffee, W.F., Thomas, C.S., Turechek, W.W., Ocamb, C.M., Nelson, M.E., Fox, A., and Gubler, W. D. 2003. Responding to an introduced pathogen: Podosphaera macularis (hop powdery mildew) in the Pacific Northwest. Online. Plant Health Progress doi: 10.1094/PHP-200301113-07-RV.
Mahaffee, W.F., Turechek, W.W., and Ocamb, C.M. 2003. Effect of variable temperature on infection severity of Podosphaera macularis on hops. Phytopathology 93:1587-1592.
Quinn, J. A., and Powell, C. C., Jr. 1982. Effects of temperature, light, and relative humidity on powdery mildew of begonia. Phytopathology 72:480-484.
Turechek, W.W., Mahaffee, W.F., and Ocamb, C.M. 2001. Development of management strategies for hop powdery mildew in the Pacific Northwest. Online. Plant Health Progress doi: 10.1094/PHP-2001-0313-01-RS.
Variation in Acacia drepanolobium defence by Crematogaster mimosae and a previously undescribed acacia ant at Hell’s Gate National Park, Kenya
Variation in Acacia drepanolobium defence by Crematogaster mimosae and a previously undescribed acacia ant at Hell’s Gate National Park, Kenya
Clare Elliott, University of Nottingham, United Kingdom
Christina Ieronymidou, Imperial College London, Cyprus
Evelyn Fosuah, Kwame Nkrumah University, Ghana
Abstract
An as yet unidentified brown ant species (right in photo above) associated with Acacia drepanolobium, found in Hell’s Gate National Park, Kenya, was compared to the well known acacia ant Crematogaster mimosae (left in photo above) in terms of tree guarding behaviour against herbivory. Baseline information was also collected on its activity patterns and pseudogall occupancy. The brown ants were found to be significantly less aggressive than C. mimosae, and were also present at a lower abundance on the acacia trees. The location at which the trees were artificially ‘browsed’ affected the level of recruitment of ant guards for both species, with more ants being recruited at basal locations rather than at shoot tips, suggesting an effect of proximity to inhabited pseudogalls. Brown ants were found to occupy trees that were taller and healthier than C. mimosae trees, but the nectaries of brown ant acacias were significantly smaller that those of trees hosting C. mimosae. The brown ants appear to be poor defenders of A. drepanolobium against megaherbivores, and their place within the ant succession on A. drepanolobium is still unclear, as are their effects on tree trade-offs in plant resource allocation to defences.
Introduction
Acacia drepanolobium, locally known as whistling thorn, is one of the dominant tree species found in the climax vegetation of the savannah ecosystem in the Kenyan Rift Valley, here studied in Hell’s Gate National Park, Naivasha. A. drepanolobium is an important source of food for many browsing megaherbivores. It has developed a number of strategies for defence against such damage from herbivory; one is to intersperse its leaves with long spines, and another is to play host to ants who defend the tree by attacking and irritating any herbivores who try to eat the leaves. The tree produces domatia, also termed pseudogalls, which provide a home for the ants, and nectaries on the leaves, which provide a source of food (Coe and Beentje, 1991).
Four species of obligate acacia-ants have been studied on A. drepanolobium (Palmer et al., 2000). Crematogaster sjostedti is completely black in appearance. C. mimosae has a red head and thorax and a black abdomen (RRB). C. nigriceps is black except for a red abdomen. The Crematogaster ants are often characterised by raising their abdomens when alarmed, and are also known as the ‘cock-tail’ ants. Tetraponera penzigi is the fourth species of ant to be studied in association with A. drepanolobium and is also completely black but is much longer and thinner than the Crematogaster ants. Previous investigations into the interactions between A. drepanolobium and ants carried out in Hell’s Gate National Park on past Tropical Biology Association (TBA) courses observed only three ant species in 1997, C. mimosae, C. nigriceps, and Tetraponera penzigi (Ahmed and Leturque, unpublished data; Burston and Jelnes, unpublished data) and in 2000 four ant species were observed (the aforementioned and C. sjostedti) (Swainson and Mucha, unpublished data).
These ants are mutually exclusive, and as such only one species of ant occupies a tree at any one time. There is variation in the ecologies of these different ant species; some colonies live on more than one tree at a time, whereas other ant colonies, such as T. penzigi, complete their entire ecology on the tree and never need to leave it. There is considerable variation in the aggressiveness and therefore the effectiveness in tree defence between the different ant species. It has been suggested that there is a succession of ant species on acacia trees, with the relatively subordinate ant T. penzigi being an early successional ant, and is evicted by the more dominant Crematogaster spp. Young et al. (1997) observed the eviction of T. penzigi and also noted a significant relationship between host tree height and resident ant species, with taller and presumably older trees hosting later successional ants.
The findings of Young et al. (1997) showed that different acacia ant species have different effects and activities on A. drepanolobium trees. C. nigriceps is noted for its pruning behaviour, as it is the only ant associated with eating axillary shoots on the host tree. As such it is also thought to be an early successional ant, and it has been hypothesised that this pruning behaviour may avoid the host tree growing into contact with other acacia trees potentially hosting rival ant species. Nectaries are destroyed by T. penzigi, which may discourage the colonisation of the tree by the dominant Crematogaster spp. C. sjostedti and C. mimosae both tend scale insects on A. drepanolobium as a source of food. This variety of relationships between the different ants and the acacia trees hosting them is an example of coexisting diversity on an apparently uniform resource (Young et al., 1997).
The relationship between these obligate plant-ants and their host acacia is considered to be a mutualistic one, however the degree to which each of the parties benefits is subject to variability, especially considering the variation in the behaviour of the different ant species and their effects on A. drepanolobium. This can be seen where C. nigriceps prunes the tree to avoid conflicts with other acacia ants. Another studied example of the tree overcoming the apparent conflict between the ant guards and the trees own interests is that of acacia flowers repelling the resident ants for the period of pollen release to permit pollinators to visit (Willmer and Stone, 1997).
It has been hypothesised that a tree may alter its resource allocation to other forms of herbivory defence such as mechanical defence according to the effectiveness of the ants it is hosting. It has also been suggested that a tree could control the concentration of ants on particularly vulnerable parts of the plant by altering the nectar production at the nectaries around the tree.
At Hell’s Gate National Park another ant has been observed living on A. drepanolobium around the gorge entrance. This brown ant appears to be distinctly different from any of the four species mentioned above and, as such, is suspected to be a different species altogether. It is larger than the Crematogaster spp.; the abdomen is similar in shape but it does not cock its tail in the characteristic way of the Crematogaster ants.
In this project brown ants were studied to obtain some baseline data, since as far as can be seen in the literature, they have not been previously studied in their relationship with A. drepanolobium. A comparative study with C. mimosae was also carried out and the following hypotheses were considered:
Hypothesis 1: Crematogaster mimosae are more aggressive in tree defence than brown ants.
Hypothesis 2: Tree resource allocation to mechanical defence and ant benefits varies with ant species.
Materials and Methods
Location
Thirty-five Acacia drepanolobium trees were selected in the area around the gorge entrance at Hell’s Gate National Park, Kenya. Twenty trees inhabited by brown ants and fifteen trees inhabited by C. mimosae.
Ant behaviour
Ant aggression was measured and compared for both the brown ants and C. mimosae (15 trees for each ant species) by attacking each tree in two places, a branch tip and the base of a branch, using forceps to simulate browsing. Each tree was ‘browsed’ at a regular rate using forceps for 3 minutes. The number of ants within a distance of 10cm from the point of ‘browsing’ was counted before and after attacking the plant as a measure of ant recruitment. The time taken for the ants to attack the forceps by walking onto them was also recorded as a measure of ant aggression.
Brown ant activity on nine of the A. drepanolobium trees was assessed during the course of one day. Three branches were selected on each tree and a count of the total number of ants present on the distal 30cm was taken every half hour from 0900h to 1230h, and from 1430h to 1800h.
On a further five A. drepanolobium trees, three pseudogalls inhabited by brown ants were selected by observing ant activity around the entrance hole. The holes were plugged with modelling clay, and detached from the tree. Pseudogall contents were killed using ethyl acetate and opened up to count the number of ants in each.
Tree status
Data were collected from 30 trees, inhabited by each of the two ant species being studied, to ascertain the general status of the trees hosting the two ant species by assessing tree height and health (good, moderate or poor) based on number of growing shoots and general appearance. The density of leaves and spines was measured by counting the number present in a 20cm length of two randomly selected branches of each tree. Leaf and spine length were measured for the ten terminal spines and leaves of the two selected branches. Ten leaves were randomly selected from each tree and the length of the basal nectaries was measured along the midrib.
Analysis
The data were tested for normality using the Anderson-Darling normality test and transformations were used to achieve normality where possible. The standard error of the means was calculated throughout and is shown in the relevant figures. Appropriate statistical tests were conducted using Minitab and R statistical software.
Results
Ant behaviour
There was no significant difference between the time taken for the ants to attack at the tip of a branch or at a branch base within each ant species (brown - B or C. mimosae - RRB). Wilcoxon signed-rank test, for B W = 6, n = 15, p = 0.181, RRB W = 61, n = 15, p = 0.977. Therefore data were combined for the two ‘browsing’ locations on the tree (Figure 1). There was a significant difference between brown ant time to attack (median = 180s, n = 15) and C. mimosae time to attack (median = 96.5s, n = 15); Mann-Whitney test, W = 328.5, p<0.001. Hence, C. mimosae were more aggressive defenders of A. drepanolobium.
Figure 1; Time to attack as a measure of ant aggression (means; B 165.4s ± 7.82, RRB 91.1s ± 10.54, n=15).
Recruitment of ants to the point of attack differed significantly between the two ant species (analysis of deviance with quasi-Poisson error structure, t = 5.135, p < 0.001), with C. mimosae showing more recruitment than brown ants (Figure 2). The location of attack also affected recruitment, with more ants aggregating at basal locations (analysis of deviance with quasi-Poisson error structure, t = 3.472, p < 0.001) and more ants vacating shoot tips (analysis of deviance with quasi-Poisson error structure, t = 2.15, p = 0.036).
Figure 2; Difference in the number of ants before and after ‘browsing’ as a measure of ant recruitment (means; B tip 1.47 ± 1.10, B base 0.60 ± 0.45, R tip 1.33 ± 1.14, R base 6.73 ± 1.53, n=15).
Figure 3 shows mean brown ant activity on all trees surveyed. The numbers of ants on the branches surveyed varied appreciably from 0 to 38 and variation of numbers within branches was low, with standard errors ranging from 0 to 1.79. There was an overall trend of increased activity as the day progressed.
Figure 3; Mean number of Brown ants recorded on branches between 9:00h and 18:00h.
The mean number of ants found in the inhabited pseudogalls sampled from brown ant trees was 28.8 ± 5.69 (Figure 4).
Figure 4; Box and whisker plot showing number of brown ants found in 15 pseudogalls (mean 28.8 ± 5.69).
Tree Status
Tree height data were log10 transformed to give a normal distribution (B mean = 2.22m ± 0.35m, n = 15, RRB mean = 1.47m ± 0.09m, n =15). Trees hosting brown ants were found to be significantly taller than trees hosting C. mimosae (Figure 5), independent samples t-test, t = 2.160, d.f. = 19, p = 0.043.
Figure 5; Height of trees hosting Brown ants (B) and C. mimosae (RRB) (means; B 2.22m ± 0.35m, RRB 1.47m ± 0.09m, n=15).
Crematogaster mimosae tends to occupy trees of poorer health than brown ants (Figure 6; Fisher’s exact test, p = 0.040).
Figure 6; Health status of trees hosting Brown ants (B) and C. mimosae.
There is a small but significant difference in the size of the nectaries on trees hosted by brown ants or C. mimosae (Figure 7) B mean = 0.61mm ± 0.03mm, n = 15, RRB mean = 0.77mm ± 0.04mm, n =15, independent samples t-test, t = 3.130, d.f. = 28, p = 0.004.
Figure 7; Mean length of nectaries on trees hosting each ant species (means; B 0.61mm ± 0.03mm, RRB 0.77mm ± 0.04mm, n=15).
Leaf length, spine length and leaf density were not significantly different between trees hosting brown ants or C. mimosae, however there was a significant difference in spine density between ant species. Trees hosting C. mimosae have a significantly higher density of spines, B mean = 1.64cm ± 0.07cm, n = 15, RRB mean = 1.92cm ± 0.07cm, n =15, independent samples t-test, t = 2.910, d.f. = 28, p = 0.007.
Discussion
The brown ants were observed in considerably lower abundance on A. drepanolobium than C. mimosae and they were frequently absent from large parts of their tree, but relatively concentrated in other places such as on growing shoots or with scale insects. Observations of the pseudogalls and their contents confirmed the suspicion that these brown ants are living and reproducing on the tree, rather than just visiting. These results show that the brown ants are less aggressive against herbivory than C. mimosae, but both ant species seem to have similar strategies for recruitment to defence depending on proximity to ants on other branches and inhabited pseudogalls. However, there are differences in the characteristics of the host acacia trees between the two ant species.
Ant behaviour
According to Young et al. (1997), C. mimosae is the most aggressive ant guard of the four species found in Laikipia, Kenya, and the hypothesis that C. mimosae are more aggressive in tree defence than brown ants is strongly supported by these results. The brown ants almost always failed to attack the forceps throughout the 3 minutes the tree was ‘browsed’. C. mimosae were much more reliable in attacking the ‘browsing’ forceps (Figure 1). They were also the more numerous ant species as they showed greater recruitment of ants to the point of ‘browsing’ to defend the tree (Figure 2). More ants were recruited at basal ‘browse’ locations than at the tips of the branches (Figure 2). This is somewhat counter intuitive as it was expected that a more efficient ant guard would defend the more delicate growing tips more aggressively. The reason for this apparent paradox could be proximity to the rest of the colony, in terms of access to other pseudogalls; however, data relating to pseudogall location were not collected.
A single day of ant counts was not sufficient to elucidate the exact activity patterns of the brown ant and this was further compromised by the low abundance of brown ants on the acacia trees. Branches selected randomly on the tree were more likely to carry no or very few ants, and the numbers of ants on each branch remained relatively constant for the entire survey period. Therefore, selection of those branches carrying the most ants may have produced more informative results. There was a tendency for increasing ant activity during the course of the day, which is most likely due to increasing temperature. This was particularly evident between 9:00am and 10:30am (Figure 3). A large number of replications of such surveys, covering a range of weather conditions, would be necessary to determine the activity patterns of this ant species and the factors which affect them.
Pseudogall inspection confirmed that brown ants are an A. drepanolobium resident species (Figure 4), since larvae and eggs as well as adult ants were found inside the domatia. Inhabited galls were selected for this survey, as the brown ant abundance on the acacia trees is quite low. An estimate of colony size on a tree could be achieved by determining the proportion of inhabited galls however, considerable variation in the numbers of ants was found between pseudogalls. Consequently, the accuracy of a colony size estimate obtained in this way would be limited.
Scale insects were found inside the dissected pseudogalls and were also observed on the branches of trees hosting brown ants. The brown ants were seen tending the scale insects, presumably as a source of food. The effect of scale insect tending by ants on the tree could alter the cost benefit ratio for the ant-acacia association, as it poses an extra cost to the tree of supporting ant guards. Scale insects may be directly harmful to the acacia or may require a larger investment of resources. It would be interesting to compare the trade offs for the two different ant species since C. mimosae also tend scale insects inside their domatia. It is expected that A. drepanolobium trees will tolerate the higher cost of scale insect tending within the pseudogalls when the quality of defence against herbivory by the ant guards is high. Therefore, the better defender is more likely to be tending scale insects within domatia and is also expected to tend larger numbers of these.
Tree Status
Brown ants were generally found on taller trees with better health than the trees hosting C. mimosae ants (Figure 5; Figure 6). Young et al. (1997) suggest that the height of a tree can be an indicator of the age of a tree and therefore the height of the acacia hosting a particular ant species could be suggestive of the position the ant takes in the succession of ant species inhabiting acacia over the tree lifetime. Although less aggressive than C. mimosae in defending the tree against herbivory brown ants may be more successful in interspecific conflicts. Alternatively, the ants may take advantage of trees vacated by the more dominant Crematogaster spp. thus avoiding interspecific conflict.
Despite the better health of trees hosting brown ants, the nectaries were found to be smaller than those on trees hosting C. mimosae (Figure 7). This may be indicative of the quality of guarding afforded by hosting C. mimosae who were found to be much more aggressive against herbivory. An alternative explanation could be that nectary size is dependent on the levels of ant activity; since brown ant are less abundant than C. mimosae the average nectary size across a brown ant acacia would be lower. To test this, nectaries on occupied branches should be compared with those on unoccupied branches.
Stapley (1998) points out that there is an important interaction between thorns and ants as two methods of herbivore defence and that the combination of the two methods may be the most effective use of the trees resources. Since the succession of ants on acacia trees leads to relatively short term occupancy of a tree by any one species of ant (Young et al., 1997) the tree is unlikely to perceivably alter its resource allocation to mechanical defence mechanisms to match the guarding abilities of the different ant species in the time available. This may explain the lack of difference in leaf and spine length and leaf density between trees hosting the two ant species. However, trees hosting the less aggressive brown ants had a significantly lower density of spines suggesting less intensive herbivory. It would be necessary to study the differential levels of herbivory on the trees hosting the two species of ants and any effect this may have on the trees resource allocation. The hypothesis that ‘tree resource allocation to mechanical defence and ant rewards varies with ant species,’ therefore cannot be fully supported.
The brown ants studied here are suggested to be poor defenders against herbivory as they are sparsely distributed on A. drepanolobium and exhibit low aggressiveness. More research needs to be carried out to determine, more accurately, the ecology and biology of these brown ants to provide further insights into the mutualism between ants and acacias, and to identify and place this species more firmly in the succession of ants already described on A. drepanolobium in Kenya. More information on these relationships would help to elucidate the cost-benefit ratios and tradeoffs involved in the ant-acacia mutualism.
Acknowledgements
Thanks are due to Clive Nuttman and Graham Stone for their valuable advice and assistance, to Rosie Trevelyan, Kizito Masinde for the impeccable organisation of this TBA course and to Moses Kamoga and the staff at the Elsamere Field Studies Centre, and the Kenya Wildlife Service for logistical support and access to the National Park. Financial support was gratefully received from the TBA and the British Ecological Society.
References
Ahmed, H.M. and Leturque, H. (1997) Protection of A. drepanolobium from mammalian browsing by the association of its galls and ants. The Darwin Courses in Tropical Biology, Project Reports, Naivasha and Hell’s Gate, Kenya. TBA 97/3: 64-71.
Burson, P. and Jelnes, I.K.S. (1997) The relationship between A. drepanolobium and ants associated with the galls in Hell’s Gate National Park, Kenya. The Darwin Courses in Tropical Biology, Project Reports, Naivasha and Hell’s Gate, Kenya. TBA 97/3: 72-80.
Coe, M. and Beentje, H. (1991) A Field Guide to the Acacias of Kenya. Oxford University Press, Oxford.
Palmer, T.M., Young, T.P., Stanton, M.L. and Wenk, E. (2000) Short-term dynamics of an acacia ant community in Laikipia, Kenya. Oecologia 123: 425-435.
Stapley, L. (1998) The interaction of thorns and symbiotic ants as an effective defence mechanism of swollen-thorn acacias. Oecologia 115: 401-405.
Swainson, C. and Mucha, A. (2000) Aspects of ant-acacia interactions on Acacia drepanolobium in the Lake Naivasha area. Tropical Biology Association, Field Course Project Reports. TBA 00/1: 111-125.
Willmer P.G. and Stone, G.N. (1997) How aggressive ant-guards assist seed-set in Acacia flowers. Nature 388:165-167.
Young, T.P., Stubblefield, C.H. and Isbell, L.A. (1997) Ants on swollen –thorn acacias: species coexistence in a simple system. Oecologia 109: 98-107.
A study of the airborne inoculum of two mycotoxin producing wheat pathogens
BSPP Report from undergraduate bursary:
Claviceps purpurea, which causes Ergot of wheat and Fusarium graminearum which causes Fusarium head blight (FHB) of wheat were studied. These two Ascomycete fungi can produce harmful mycotoxins in wheat grain and Fusarium can also reduce grain yield in infected crops.
Inoculated field experiments were carried out to assess the timing and quantity of spore release. Ergot fruiting bodies and inoculated black grass were planted in a wheat field as two sources of inoculum. Some of the fruiting bodies (stroma) were dissected and sectioned using a cryostat. The sections were stained and visualised under a light microscope to assess the sexual spore producing potential of a single stroma (Figure 1 and Figure 2).
Despite our inoculations, the incidence of ergot on the wheat in the inoculated field was surprisingly low, when compared to the high incidence observed on the grasses in the surrounding area. It is therefore hypothesised that insect vectoring of the asexual spores may be the more significant method of spore dispersal resulting in disease symptoms (rather than air borne sexual spores) and that either the timing of insect transmission did not coincide with wheat flowering (when the wheat is susceptible to infection) or the insects vectoring the pathogen did not visit the wheat.
Another wheat field was inoculated with Fusarium spp. by spreading leaf litter from infected wheat from the previous season. The field was misted to ensure the conditions were favourable for the production of the spores. A gradient of Fusarium incidence was observed over the Fusarium spp. inoculated wheat field which followed the direction of the prevailing winds, which were predominantly from one direction throughout the bulk of the flowering period. There was also a much higher incidence within the water misted part of the experiment than in the surrounding guard crop (Figure 3), but even here, the exceptionally wet June allowed a substantial amount of infection.
Burkhard spore traps were used to sample the air borne inoculum in both the Ergot and Fusarium fields. These sample air at 10 litres per minute with airborne particles impacted onto a wax-coated tape, which is moved by a clockwork mechanism past the air intake at 2 mm per hour. Microscopy and molecular techniques were employed to analyse the spore deposit on the tape. A considerable increase in detectable airborne F. graminearum spores was observed to coincide with the time of wheat flowering, when the wheat is most susceptible for infection.
Unfortunately the molecular analysis from the spore traps in the Ergot experimental field all came back negative suggesting a problem with the process of DNA extraction from the spore tape. DNA was extracted from spore tapes using a Microlysis buffer for the Fusarium experiment and using a Qiagen kit for the Ergot experiment. Although the Microlysis method yields a lower volume of DNA it seems to be a more reliable method for the purpose of spore tape extractions.
Spore tape samples analysed from both the Ergot and Fusarium fields for the presence of Fusarium pathogens showed a strong positive PCR band for the presence of Microdochium nivale cv. nivale. (another causative agent of FHB on wheat) on the same day in the two separate fields. This indicates that there was a considerable local presence of the pathogen in the air on this day.
Wheat grain harvested from the Fusarium experimental field was taken from each of the fungicide untreated plots and cultured on potato dextrose agar to assess the level of infection in the grain and to identify the pathogen species present (Figure 4). Over 96% of the grain tested was infected with Fusarium spp.
This project has provided me with some extremely valuable experiences in carrying out field experiments and I have learnt skills which I will take with me into my further studies as I embark on a PhD in plant pathology at Oregon State University.
Thanks are due to Jon West, Richard Gutteridge, Sarah Rogers, Simon Atkins, and Bruce Fitt for their support, advice and assistance in this project. Thanks also go to the British Society of Plant Pathology for funding this work and to Paul Nicholson at the John Innes Centre and David Kenyon at NIAB for assistance with molecular techniques.
Clare Elliott, Rothamsted Research.
Figure 1; 10µm section of C. purpurea stroma, stained using Toluidine blue and Ruthenium red
Figure 2; Thread like ascospores are visible in the ascocarp covering the surface of the C. purpurea stroma
Graph available on request
Figure 3; Gradient of FHB incidence assessment of fungicide untreated plots. Each line is a separate transect through the field with data collected at fungicide untreated plots only.
Figure 4; Fusarium infected wheat grain on PDA (5 days, 20˚C)
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