Development and validation of a prototype microarray based on ribosomal DNA-targeting oligonucleotide probes for the analysis of ectomycorrhizal fungi community
1. State of the art
A central theme in community ecology research is to understand the composition, patterns, and dynamics of species diversity at various spatial scales, from a single field site to the planet. In addition to adding to our basic knowledge on mechanisms that control species coexistence, such studies have fundamental applications because they offer the framework that serve biologists interested in maintaining and restoring diversity in natural ecosystems. In the proposed project, our aim is to develop and validate a prototype DNA microarray for high resolution screening of communities of ectomycorrhizal (ECM) fungi.
Similarly to bacteria, fungi are incredibly diverse at all spatial scales, and much of their diversity has been unexplored. Hawksworth (2001) recently estimated that there are likely 1,2 million species of fungi on earth, of which less than 5% had been described by 1999. Fungal diversity may exceed plant diversity > six-fold. Thus, over 5000 species of ECM fungi have been described, which occur in at least 15 families and 40 genera, within two major divisions of fungi, Basidiomycota (mainly) and Ascomycota (Molina et al. 1992). These fungi are ecologically important on a global scale because they form symbiotic structures (called ectomycorrhizae) with roots of dominant trees and shrubs in temperate and boreal forests and in large territories of tropical forests. They mobilize soil nutrients (such as phosphorous and nitrogen) in exchange from photosynthate (Smith & Read, 1997). They are also important in human affairs because they include high value edible fungi such as chanterelles, boletes, and truffles. However, these are also the source of numerous food poisoning each year as a result of many inadvertent (and sometimes fatal) confusion of poisonous species with edible ones!
Hundreds of species of ECM fungi can be found in stands dominated by a single tree species, and even a single root system can be colonized by dozen of species (Horton & Bruns, 2001). Analysis of the community can be achieved through fruitbody surveys, sampling of mycorrhizae and mycelia in the soil. This investigation of diversity is a challenge for several reasons: 1- many fungi fruit sporadically or cryptically, or both, 2- fruitbodies surveys can lead to considerable investment in time and labor and usually require long-term expertise in fungal systematics, 3- the morphological simplicity of the vegetative state (mycorrhizae and mycelia) provides a very limited set of informative characters for identifying the fungal symbionts, 4- there is differential investment in vegetative growth and sexual reproductive structures among members of a given community. As a consequence, there are only a few reports in the mycorrhizal literature that have thoroughly addressed this issue of species diversity and community dynamics. Most come from recent publications on molecular ecology using polymerase chain reaction (PCR)-based identification methods and analysis of mycorrhizae (Horton & Bruns, 2001). In contrast to bacteria, no report has been published yet on DNA microarray in fungal detection and ecology. However, this technology is the most promising molecular approach for the screening of fungal diversity because it allows the simultaneous application of a nearly unlimited number of probes in a single hybridization experiment (Buscot et al., 2000; Horton & Bruns, 2001). Thus, compared to conventional DNA-based methods, micoarrays offer the advantages of rapid and sensitive detection, lower cost and automation (Small et al., 2001; Peplies et al., 2003).
The presence of a given fungal species may cause change in its immediate environment (i.e. the host plant), which results in an increase or decrease of its own expected fitness. At the community level, feedbacks through the mycorrhizal fungi may exert strong effects on the numerical and spatial dynamics of tree populations and communities (Smith & Read, 1997; van der Heidjen & Sanders, 2002). However, the magnitude, and consequences of such feedbacks have rarely been examined in natural conditions because very little is known on the diversity of the fungal symbionts and their functional roles. For example, more information is needed about the extent to which the relative abundance of fungal species and host specificity may affect both plant establishment and nutrient cycling, and ultimately the functioning of ecosystems. Our goal in this study is to investigate environmental feedback through the community of ectomycorrhizal fungi with a particular focus on the riparian ecosystem. This system is highly dynamic with steep ecological gradients that may favor plant-fungal associations which present selective advantages. In a previous work, we have conducted a survey of mycorrhizal fungi associated to black poplar (Populus nigra) on a riparian site located near Toulouse along the Garonne river, using conventional PCR based molecular methods (Gardes et al. 2003, and unpublished results). We have shown that shifts occur along a gradient of hydrological disturbance (from a gravel bar to the river bank), from communities dominated by endomycorrhizal fungi to ones dominated by ectomycorrhizal fungi (such as Tuber spp. or Hebeloma spp.). Because several species were found repeatedly over several years, we concluded that inoculum of ectomycorrhizal fungi has the ability to survive flooding. However, there was suggestive evidence that the maintenance on the site of two common fruiting ECM species, Tricholoma scalpturatum and Tricholoma populinum, was mainly a result of spore establishment, rather than long term survival through vegetative growth. In the present study, we would like to expand the evidence for the widespread presence of ECM fungal taxa to a large number of riparian sites as well as on roots of different host plants such as willows. The microarray will be use to address hypotheses relating to 1) the presence of ectomycorrhizal guilds (i.e. fungal species which are constant associates of black poplar), 2) host specificity in a highly disturbed habitat, and 3) the correlation between fruiting record and root colonization of two Tricholoma species. Ultimately, our aim is to build a microarray that would allow detection of all potential taxa in the community. However, we are fully aware that more methodological development is needed to meet this long-term goal. Thus, to make our objective a tractable goal, we will target abundant and/or fruiting species. The applicability of the pilot microarray will be tested by using various sources of biological material such as fruitbodies, soil mycelia, and mycorrhizae of the targeted species.
In summary, this project joins distinct approaches and expertise (see section 3.1) in bioinformatics (probe design), molecular biology (DNA array) and fungal ecology (analysis of mycorrhizal fungi communities), to examine how ectomycorrhizal fungi respond to changes in the biotic and abiotic environment, with a particular focus on the fungal community associated to riparian host trees, mainly black poplar and willow (Salix sp.)
2. Working hypothesis
The major objective of this project is to develop a prototype microarray for the identification of selected taxa of ectomycorrhizal fungi in riparian poplar-willow forests. The central ecological questions we hope to answer are listed below:
3- What is the spatial and temporal dynamics on poplar roots of both Tricholoma scalpturatum (a host generalist species) and T. populinu? How do patterns from below ground (mycorrhizae and soil mycelia) correlate with the fruiting pattern (and turn-over of genets) of these two species?
The problem of molecular identification of ECM fungi
In most molecular studies of ECM communities, ribosomal genes and spacers are amplified by PCR using fungal-specific primers (Gardes & Bruns, 1993). The amplified fragments are subsequently differentiated by their size using tetrameric restriction enzymes (Gardes et al., 1991; Gardes & Bruns, 1996b). Putative operational taxonomic units (RFLP-types) are identified, and in a first screening step, attempts are made to match unknown RFLP-types obtained from mycorrhizae with known types from identified fruitbody collections (Gardes & Bruns 1996a, Gardes & Bruns, 1996b). In a second step, representatives of the dominant or unidentified RFLP-types are sequenced and placed into a phylogenetic system for further taxonomic identification of the fungi forming mycorrhizae (Gardes & Bruns, 1996b; Bruns et al, 1998; Horton & Bruns, 2001). In these studies, genetic markers are developed without the need of PCR quantification because the ectomycorrhizae (that are usually obvious from the external appearance of the root) can be collected individually and thus, species sorted into discrete units that can be counted or weighed.
The ITS region (i.e. two noncoding spacers separated by the 5.8 S rRNA gene) of the nuclear ribosomal unit has been particularly popular for ECM species identification because: 1- it lies between conserved tracks of the small subunit (SSU) and the large subunit (LSU) ribosomal RNA (rRNA) genes that serve as sites for the design of both universal, and plant or fungal specific amplification primers (Gardes & Bruns, 1993), and 2- it contains conserved and variable domains useful to distinguish many morphological species (Horton & Bruns, 2001). Because it has greater interspecific and lower intraspecific variability, it rapidly appeared as a choice molecule for species detection, and many sequences have already been deposited. Other molecules such as the 5’ end of LSU rRNA gene, small regions of both the nuc-SSU rRNA gene and the mitochondrial large subunit rRNA gene (mtLSU) have been used to a lesser extent, but mainly for taxonomic placement at the generic level or above (Bruns & Gardes, 1993; Gardes & Bruns, 1996b; Bruns et al., 1998).
Our methodological objective is to get insights into: (i) the best strategy for efficient probe design, and (ii) the mechanisms underlying microarray hybridization for species detection. First, we will design and test a redundant and hierarchically set of oligonucleotide probes (about 20 nucleotides in length) that target the nuclear ribosomal genes and the ITS region of ECM fungi. Second, we propose to: (i) systematically evaluate the suitability of the microarray by testing various parameters that may influence hybridization (such as specificity of the probes, detection sensitivity and steric hindrance), and (ii)- narrow down our investigation to a limited number of about 50 taxa (in the form of OGUs, see section 3.3) of ECM fungi.
3. Previous experience in the field (including preliminary results)
3. 1. Qualification of the P.I. and collaborators in relation to the project
Monique Gardes is Professor of Mycology at the University of Toulouse III / Paul Sabatier..
Richard Christen is Professor of Bioinformatics at the University of Nice Sophia Antipolis. .
Jean-Marie François is the head manager of Transcriptom-biochips platform of Toulouse Genopole. .
3.2. Previous experience in collaborative work between the three teams
During the last 6 months, M. Gardes, R. Christen and J.M. François have started a collaborative work on microarray for the detection of fungi through a research project financed by "la Génopôle Microbiologie" at Toulouse University. This small grant covers part of the expenses for the supplies and equipments. However, no support is available for salaries of highly trained postdocs or technicians, and participant support costs. This lack of support is a major problem because the work that needs to be accomplished for the development of the microarray is labor intensive and time-consuming, and so help to support qualified researchers is critical for the 3 laboratories.
3.3. Preliminary results on ITS-based probe design
Looking for probes that would be specific of any single fungal species is not a trivial task because of taxonomic and nomenclatural pitfalls in fungal systematics (for example, most North American fungi have been named based on European description of species, however they often correspond to different species. Conversely, the same fungi can be described under two species names by mycologists from separate parts of the world). To circumvent these problems, 1- we used specific queries (getz queries within SRS) to retrieve all sequences from the fungal ITS region, 2- we organized these sequences into a relational database to check if these sequences encompass the ITS domain (local blast + parse routines), and 3- we finally retained sequences containing both ITS1 and ITS2 domains. About 6900 ITS fungal sequences have now been compiled. Because the domains are much too divergent (the exact reason why we chose this region as target sequences) we cannot compare homologous characters through a classical molecular phylogeny analysis. In order to establish a temporary molecular classification we, therefore, proceed as follows: 1- blast all 6900 sequences against themselves and use the scores to build a distance matrix between every 2 pairs of sequences, 2- derive partitions of similar sequences from this matrix using an aggregative algorithm. Each partition is defined by its maximal radius (to have compact partitions), but the problem is the definition of that value (for example two distances allowed to separate the 6900 sequences into 1353 or 2930 partitions). Careful analysis of results by a mycologist expert of some of these partitions allowed to retain a value that produced a meaningful classification. Then, all sequences within a single partition are attributed to a single operational genetic unit (OGU). The goal is to obtain, for each OGU, at least a probe (20 nucleotide in length) that would recognize every sequence within a single OGU and no sequence outside this OGU. The algorithm proposed is as follows: (i) for each OGU, all possible probes are obtained, (ii) a quick step allows a downsizing of the data set: retain only those that are present once in every sequence of the OGU and not in any other sequence, and (iii) the remaining probes are tested against the "Plant" Genbank division (that also contains the Fungi!). The resulting file is parsed with a program specially designed for that purpose. For each probe, the following parameters are calculated: Tm of the probe on its target, stability of potential hairpin, Tm of the probe on interfering species, control probes (exact match on these interfering species). We have started this (time-consuming) investigation on about 10 OGUs of ECM fungi. A list of about 50 oligonucleotide probes is already available for DNA array building and testing.
4. Description of the project
Task. 1 (R. Christen & M. Gardes): Design of oligonucleotide probes from current sequence databases.
We will search for probes in the ITS domains as described above (see section 3.3). A selected group of species will be targeted from various genera of ECM fungi. These names will then be used to select the particular OGU that contain them. Because of the taxonomic problems stated above, identification of each species will sometimes be based on a multiple-probe (OGU) approach. Alternatively, since the same species may bear different names, a single probe may identify different "species" that in fact are distinct labels for the same specimen. For example, see below the number of "species" (and sequences available) for the OGU identified as n° 67 :
Suillus brevipes: 1; Suillus luteus 10; Suillus pseudobrevipes 1; Suillus weaverae: 1
Probes in more conserved regions (e.g the 5,8S) of the nuclear ribosomal unit will also be searched to allow additional hierarchical specificity. They may also be useful for detection of rRNA/rDNA molecules. All the probe data will be stored into a relational database used to derive software to assist in correct interpretation of the DNA chip readings.
A specific software (the eDashboard) developed in our laboratory will be used to facilitate communication between teams. This tools allows efficient sharing of data and management of the program (see screen capture below).
Task 2. (M. Gardes): Collecting specimens for DNA extraction and sequencing.
For each species, we will collect fruitbodies in different sites. We will sequence the ITS (and other target ribosomal genes) of these samples in order to increase the existing (sometimes limited) sequence databases, and use these sequences for probe searching.
Task 3. (J.M. François & M. Gardes): Microarray manufacture and analysis
Oligonucleotides will be obtained from an external biotech company, and tailed at the 5' end to increase the on-chip accessibility of spotted probes to target molecules. The probes (about 100 hundred) will be spotted using the robotic printer of the "plate-forme transcriptome", and arranged as a matrix of rows and columns with at least three replicates on each glass slide. To fluorescently label DNA, we will test both a direct procedure and a labeling by PCR amplification, using Cy3-dCTP or Cy5-dCTP.
Task. 4 (J.M. François, M. Gardes & R. Christen): Optimization of the hybridization conditions on microarrays
We will evaluate various conditions and buffers to determine the optimal conditions in terms of reducing the number of false hybridization events for each targeted species. The impact of secondary structures and steric hindrance will also be tested. For spot detection and signal quantification, we will use the image software analysis available at the "génopôle Transcriptome". If necessary, a second investigation will be done to further reduce false-positive and false-negative results. A new probe search will be initiated (because new sequences keep adding in the sequence database each week) and a novel microarray will be designed for final validation.
Task 5 (M. Gardes & J.M. François): Investigations of ectomycorrhizal guild structure in riparian forests.
In addition to fruitbodies of selected species, mycorrhizae and soil mycelia will be collected in several riparian poplar-willow forests. Validation of the chips will be done against these various sources of biological material. The sampling scheme will give us a view of diversity heterogeneity according to host, season and space.
Year 1: We intend to complete tasks 1, 2 and 3.
Year 2: Our efforts will be mainly concentrated on tasks 4 and 5.
6. Expected results
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Bruns T.D., Szaro T.M., Gardes M., Cullings K.W., Pan J.J., Taylor D.L., Horton T.R., Kretzer A., Garbelotto M. & Li Y. 1998. A working nucleotide database for the identification of ectomycorrhizal basidiomycetes by phylogenetic analysis. Mol. Ecol. 7: 257-272.
Buscot F., Munch J.C., Charcosset J.Y., Gardes M. & Hampp R. 2000. Recent advances in exploring physiology and biodiversity of ectomycorrhizas highlight the functioning of these symbisoses in ecosystems . FEMS Microbiology 24: 601-614
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