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Keywords:

  • arbuscular mycorrhizal symbiosis;
  • laser capture microdissection;
  • Medicago truncatula;
  • gene expression;
  • transcriptomic;
  • transport

Summary

  1. Top of page
  2. Summary
  3. Introduction
  4. Results and discussion
  5. Experimental procedures
  6. Acknowledgements
  7. References
  8. Supporting Information

Most vascular plants form a mutualistic association with arbuscular mycorrhizal (AM) fungi, known as AM symbiosis. The development of AM symbiosis is an asynchronous process, and mycorrhizal roots therefore typically contain several symbiotic structures and various cell types. Hence, the use of whole-plant organs for downstream analyses can mask cell-specific variations in gene expression. To obtain insight into cell-specific reprogramming during AM symbiosis, comparative analyses of various cell types were performed using laser capture microdissection combined with microarray hybridization. Remarkably, the most prominent transcriptome changes were observed in non-arbuscule-containing cells of mycorrhizal roots, indicating a drastic reprogramming of these cells during root colonization that may be related to subsequent fungal colonization. A high proportion of transcripts regulated in arbuscule-containing cells and non-arbuscule-containing cells encode proteins involved in transport processes, transcriptional regulation and lipid metabolism, indicating that reprogramming of these processes is of particular importance for AM symbiosis.


Introduction

  1. Top of page
  2. Summary
  3. Introduction
  4. Results and discussion
  5. Experimental procedures
  6. Acknowledgements
  7. References
  8. Supporting Information

Most plants live in close symbiosis with arbuscular mycorrhizal (AM) fungi, which colonize the plant roots and form intracellular structures, so-called arbuscules. Such AM fungi form an extensive hyphal network that reaches far beyond the root depletion zone, and are thus able to acquire nutrients from the soil much more efficiently than the plant root system alone (Smith and Smith, 1990). Their early evolutionary origin (Redecker et al., 2000) and the wide occurrence of AM symbiosis in nearly all ecosystems and in over 80% of angiosperm species suggest that plants harbour a distinct genetic program for endosymbiosis with AM fungi (Parniske, 2008; Oldroyd et al., 2009).

The development of AM symbiosis starts with a signal exchange between the AM fungus and host plants before direct contact (Akiyama et al., 2005; Besserer et al., 2006; Maillet et al., 2011). After the pre-contact stage, the fungus forms a hyphopodium at the root surface. Interestingly, the plant cell underneath the hyphopodium forms a novel cellular apparatus, the pre-penetration apparatus, in order to guide hyphal growth through the cell (Genre et al., 2005). All subsequent intracellular colonization events are encompassed by formation of the pre-penetration apparatus prior to plant cell penetration by the fungal hyphae (Genre et al., 2008). Arbuscules are formed in inner cortical cells. They represent tree-like fungal hyphae structures surrounded by the peri-arbuscular membrane (PAM), an extension of the plant plasma membrane with novel biological features. The most obvious difference between the two membrane types is probably the presence of highly specific membrane transporter proteins. MtPT4, an AM-specific phosphate transporter, is localized to the PAM but absent from the plasma membrane (Javot et al., 2007). The same probably is true for an H+-ATPase that is exclusively transcribed in mycorrhizal roots, localized to arbuscule-specific cells and presumably provides the proton gradient for active transport processes across the PAM (Krajinski et al., 2002). The specific localization of the blue copper binding-like protein of Medicago truncatula to the PAM trunk further indicates the unique composition of this membrane (Pumplin and Harrison, 2009). Improved phosphate uptake is probably the main benefit of AM symbiosis for the plant; however, transcripts of a number of plant transporter genes, including putative nitrate, ammonium, zinc, copper, iron and sulphate transporters, are up-regulated during AM symbiosis and absent in non-mycorrhizal roots (Wulf et al., 2003; Frenzel et al., 2005; Hohnjec et al., 2005; Gomez et al., 2009; Benedito et al., 2010), suggesting that other mineral nutrients and microelements are also supplied to the plant by the AM fungus.

In contrast to the root nodule symbiosis between rhizobia and legumes, AM symbiosis is a non-synchronous process: this means that after the first occurrence of arbuscules, all developmental stages of the symbiosis (hyphopodia, intracellular hyphae, fungal vesicles and arbuscules of various developmental stages) are present in the root system. This is due to the fact that, in a fully developed symbiosis, fungal hyphae continuously grow out of the root and start re-infecting the root system.

Laser capture microdissection (LCM) offers a powerful tool for non-contact, contamination-free and precise collection of specific cell groups or single cells excised from histological tissues. Originally developed in animal tissues, LCM has been successfully applied to plant tissues such as root cortical cells, vascular tissue, mesophyll, epidermis, petiolar cortical cells, endosperm and syncytia (Kerk et al., 2003; Schad et al., 2005a; Agusti et al., 2009; Gomez et al., 2009; Klink et al., 2009; Tauris et al., 2009). Recently, LCM-coupled transcriptome profiling provided insight into specific transcriptomic changes in Arabidopsis leaf cells at the site of infection with the biotrophic fungus Golovinomyces orontii (Chandran et al., 2010), and into the molecular mechanisms underlying distinct developmental stages of a further biotrophic fungus, Melampsora larici-populina (Hacquard et al., 2010). Depending on the desired cell population, the tissue preparation method is adjusted prior to LCM, in order to achieve a balance between morphological preservation and specific molecule recovery (RNA, DNA, proteins; Nelson et al., 2006). To identify AM symbiosis-related genes, extensive transcript analyses in whole root organs have been performed using cDNA microarray hybridizations, but cell-specific alterations were shown for only a limited number of genes by quantitative real-time or semi-quantitative PCR using single cell-derived RNA or RNA derived from homogenous cell populations (Balestrini et al., 2007; Fiorilli et al., 2009; Gomez et al., 2009; Gomez-Ariza et al., 2009; Guether et al., 2009a; Kuznetsova et al., 2010). Here we describe use of a combination of high-throughput transcriptome analysis and a high-resolution method (LCM) in order to investigate the cell type-specific transcriptomic reprogramming of root cells during AM development.

Results and discussion

  1. Top of page
  2. Summary
  3. Introduction
  4. Results and discussion
  5. Experimental procedures
  6. Acknowledgements
  7. References
  8. Supporting Information

Coupling of cryosectioning and laser capture microdissection enables the isolation of root cortical cell RNA for transcriptome profiling

In order to study the reprogramming of roots during AM development at cellular resolution, we used LCM to isolate distinct cell types of mycorrhizal roots. We used Medicago truncatula plants, which were inoculated with Glomus intraradices and harvested 3 weeks after inoculation. At this time point, roots were completely colonized, with 19.2% arbuscule frequency in the root systems. Mycorrhizal parameters (Trouvelot et al., 1988) are shown in Table S1. Prior to cortical cell sampling by LCM, an appropriate sectioning method was developed to ensure sufficient RNA quality. In order to avoid degradation resulting from the fixation procedure, cryosectioning of frozen and embedded root material of M. truncatula plants was performed 3 weeks after inoculation. Use of cryosectioning has been reported to yield high-quality RNA from plant cells (Nakazono et al., 2003; Casson et al., 2005; Corpas et al., 2006; Dembinsky et al., 2007; Agusti et al., 2009). In this study, distinct cell populations were identified in longitudinal cryosections and successively collected by LCM. These cell types were non-arbuscule-containing (i.e. non-colonized cells) cortex cells of mycorrhizal roots (NAC), arbuscule-containing cells of mycorrhizal roots (s), and cortical cells of non-mycorrhizal roots as a control (COR; Figure 1). To confirm that arbuscules were clearly recognized in cryosections, we stained a number of sections using wheat germ agglutinin (WGA) Alexa Fluor 488 to visualize fungal structures by green fluorescence (Figure S1). Only those cells that had already been identified as ARB cells under bright-field conditions showed intracellular green fluorescence after WGA/Alexa Fluor 488 staining. This confirmed that arbuscules were readily recognized in 35 μm cryosections under bright-field conditions. A harvest of at least 5000–10 000 individual root cortical cells per biological replicate was required to obtain sufficient amounts of RNA (50–100 ng). The RNA integrity number, which indicates the quality of the RNA samples, was determined for each RNA sample obtained. Only cell type-specific total RNA samples with RNA integrity numbers above six were considered for further processing. In such cases, RNA samples were pooled and subjected to amplification and cDNA synthesis. Representative electropherograms and corresponding images of the gel after electrophoresis of analysed cell type-specific RNA batches are illustrated in Figure S2. Up to 3 μg biotin-labelled cDNA was generated from each cell type, and hybridized to Medicago genome arrays.

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Figure 1.  Cryosections of Medicago truncatula roots and laser microdissected-mediated isolation of root cortical cells. Longitudinal sections (35 μm) of roots 21 day post-infection with Glomus intraradices. Scale bar = 100 μm. (a) Cortical cells of non-mycorrhizal roots (COR) (highlighted in yellow). (b) Arbuscule-containing cells (ARB; highlighted in green) and non-colonized cortical cells of mycorrhizal roots (NAC; highlighted in red) of mycorrhizal roots.

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Transcript profiling of LCM-derived cortical cell populations using Medicago genome arrays

In order to compare the transcript profiles of ARB cells, NAC cells and COR cells, we used LCM-derived cells for microarray hybridization. RNA samples isolated from specific cell types were hybridized to the Medicago genome array, which contains more than 61 200 probe sets including 32 167 M. truncatula EST/mRNA-based genes and 18 733 M. truncatula probe sets based on International Medicago Genome Annotation Group (IMGAG) predictions. The complete hybridization data set is available at Array express (http://www.ebi.ac.uk/arrayexpress) (identifier: E-MEXP-3395). When comparing hybridization data for the three cell types, 1951 Medicago probe sets displayed differential transcription levels between at least two cell types, with log2 fold changes >1 or <−1. Recently, a Medicago genome array analysis with RNA samples derived from whole mycorrhizal or non-mycorrhizal roots identified 652 probe sets as showing a twofold or greater change in transcription levels in mycorrhizal roots (Gomez et al., 2009). To evaluate the overlap between the transcriptional changes observed at global root level and at cell type-specific level, we compared the raw data from both experiments using robust multichip average (RMA) normalization with Benjamimi–Hochberg correction of P values and separate multiple testing strategy. This showed that 73% of the probe sets that were differentially regulated at the whole-root level were also differentially regulated in at least one comparision between cell types (Figure S3). The proportion of regulation events not detected by the approach described here indicates that non-cortex cells also display transcriptome changes in mycorrhizal roots compared to non-mycorrhizal roots, and such changes were not detected using the three cell types in the present study. On the other hand, only 10% of the genes with significantly altered transcript levels between two of the three cortex cell types were detected at whole-root level, indicating the significantly increased sensitivity and resolution of the present approach for analysing transcriptome changes in specific cell types. Hence, use of cell type-specific RNA in the present study increased the number of transcripts identified as showing differential expression in mycorrhizal roots, and also provides information about the spatial expression pattern. The transcriptional changes in the analysed cell populations are shown in Figure 2. Remarkably, NAC cells showed the greatest changes in gene expression. A total of 778 transcripts were at least twofold increased in NAC cells compared to cortical cells of non-colonized roots, but showed no or non-significant changes when comparing the expression to that in ARB cells. This result indicates a substantial reprogramming of cortex cells of mycorrhizal roots that is not directly related to arbuscule development. However, reprogramming of NAC cells may also indicate that cells are preparing for subsequent colonization. This is in line with observations on development of the pre-penetration apparatus and the resulting nuclear movement defining the infection pathway of arbuscule-adjacent cells described recently (Genre et al., 2005). A total of 283 transcripts showed specifically increased transcript levels in ARB cells compared with non-mycorrhizal cortical cells, but were not induced in NAC cells, indicating a specific role for these genes in arbuscule functioning. However, 576 genes were significantly induced in both ARB cells and NAC cells. Remarkably, the highest number of significantly down-regulated genes (252) was observed in ARB cells compared to NAC cells, with no significant regulation between ARB cells and COR cells. Table S2 lists all Medicago probe sets with significant regulation (log2 fold change between at least two cell types >1 or <−1), including P values.

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Figure 2.  Venn diagram illustrating significant transcriptional changes in arbuscule-containing cells (ARB), non-colonized cortical cells of mycorrhizal roots (NAC) and cortical cells of non-mycorrhizal roots (COR). Differentially expressed AM symbiosis-responsive transcripts with at least a twofold change (no P value adjustment) are shown. Red numbers indicate the number of probe sets showing increased transcript levels (log2 fold change >1); green numbers indicate the number of probe sets showing decreased transcript levels (log2 fold change <−1).

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Confirmation of transcriptional regulation by quantitative real-time RT-PCR

In order to confirm the transcriptional regulation observed by microarray hybridization, we selected nine candidate genes for quantitative real-time RT-PCR analysis (Table 1). For the microarray hybridization, linear amplification of the RNA was performed. To exclude technical artefacts during RNA amplification, we used non-amplified RNA samples for quantitative RT-PCR conformation of these candidate genes. New RNA samples were isolated from the three cell types and directly transcribed into cDNA without prior amplification. We selected well-characterized mycorrhizal marker genes as well as genes with different RNA accumulation levels between ARB and NAC cells, including genes that showed strongest induction in NAC or COR cells, respectively. We confirmed the expression of three genes encoding transporter proteins, including MtPt4, which is a well-described marker for functional AM symbiosis (Javot et al., 2007). The relative transcript levels of the nine genes in the three cell types are shown in Figure 3. MtPt4 transcripts were not detected in COR cells but accumulated in both mycorrhizal root cell types, with stronger accumulation in ARB cells, confirming the regulation pattern observed by microarray hybridization. This is in contrast to previous studies with the MtPt4 promoter, which suggested promoter activity specific to ARB cells. A possible explanation for this discrepancy may be the increased sensitivity of the transcriptome approach described here that uses distinct cell types. However, we cannot rule out the possibility that the population of NAC cells contains a proportion of cells that harbour not fully expanded senescent or young arbuscules, which were not recognized after sectioning because the fungal structures were in the part of the cell that has been removed from the section. Previously reported arbuscule-specific transcripts were also observed in non-arbusculated cells of mycorrhizal roots by other researchers working with laser-microdissected cell lines, i.e. in arbuscule-containing root cortical cells of tomato (Solanum lycopersicum; Balestrini et al., 2007). However, we also found that a number of genes showed significant differences in transcription levels between ARB cells and NAC cells, including two putative transporter genes [a putative proton-dependent oligopeptide transporter (medtr4g136300.1) and a putative copper transporter (medtr2g008130.1)]. Hence, the strong accumulation of distinct transcripts observed in NAC cells cannot be solely due to contamination of this cell type by arbuscules or other fungal structures. In addition to genes with increased transcript levels in ARB cells, we considered genes with decreased RNA levels in ARB cells. We confirmed the transcriptional regulation of a homeobox protein, which shows the highest transcript levels in NAC cells. In parallel, we also observed down-regulation of an expansin-like gene in both cell types of mycorrhizal roots compared with COR cells, although the observed changes in transcription were not significant (P values > 0.05) in the microarray hybridization experiment. However, the significant changes in gene transcription observed after quantitative RT-PCR may be the consequence of the higher sensitivity of the primers used compared to the microarray probe. In general, the quantitative RT-PCR measurements confirmed the transcription profiles obtained by microarray analysis of the candidate genes.

Table 1.   Candidate transcripts used for quantitative real-time RT-PCR confirmation of microarray hybridization results
Probe set IDmt3.0 IDAnnotationARB/CORNAC/COR
Log2 fold changesaPbLog2 fold changesaPb
  1. ARB, arbuscule-containing cells of mycorrhizal roots; NAC, non-arbuscule containing cells of mycorrhizal roots; COR, cortex cells of non-mycorrhizal roots; NA, not available.

  2. The log2 fold changes obtained by microarray analysis and the corresponding P values are given.

  3. aValues are means of two biological replicates. Normalization was performed by RMA, bP values were calculated by a t test.

mtr.43062.1.S1NAMtPt47.360.004.970.00
mtr.37110.1.S1medtr2g008130.1Copper transporter9.210.006.500.00
mtr.17764.1.S1medtr4g136300.1Proton-dependent oligopeptide transporter7.020.000.940.10
mtr.51511.1.S1medtr2g095930.1HAP5 transcription factor8.200.006.470.00
mtr.8863.1.S1medtr5g035250.1Myb family transcription factor9.220.008.150.00
mtr.43644.1.S1medtr5g019580.1Homeobox protein−1.320.263.200.03
mtr.35424.1.S1medtr2g019110.1Protease inhibitor-like9.340.007.700.00
mtr.20107.1.S1medtr5g013580.1Expansin−1.570.240.760.55
mtr.10562.1.S1medtr3g136390.1Specific tissue protein10.400.009.000.00
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Figure 3.  Quantitative RT-PCR-based confirmation of the cell type-specific transcript regulation observed by microarray hybridization. Relative expression levels were measured using gene-specific primers and cDNA of arbuscule-containing cells (ARB), non-colonized cortical cells of mycorrhizal roots (NAC) and cortical cells of non-mycorrhizal roots (COR). All plants were harvested 3 weeks after inoculation with Glomus intraradices. The relative expression levels (inline image) after normalization to MtEf1 transcript levels (Wulf et al., 2003) are shown. Values are means of two biological replicates; error bars indicate standard deviation.

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AM fungal gene expression

As reported previously (Gomez et al., 2009), G. intraradices genes are represented on the M. truncatula genome array, and 49 probe sets were identified as putative fungal genes as they were exclusively derived from M. truncatula/G. intraradices mycorrhizal root cDNA libraries. Of these 49 genes, 15 were present in our set of regulated genes (Table 2). The fact that not all fungal probe sets were detected in this study may be explained by the fact that we analysed single cell types containing only arbuscules. Fungal genes that are not expressed in arbuscules but only in other fungal structures such as vesicles or hyphae were not covered by our approach. Similarly, other fungal genes may be expressed only at different stages of AM symbiosis development, such as initial colonization of epidermal cells or appressorium formation. Transcripts with similarities to ribosomal sequences showed strongest up-regulation in ARB cells. However, they were also induced in NAC cells, possibly indicating the presence of fungal structures in this cell population. Transcripts of fungal glutamine synthetase and a fatty acid desaturase were highly abundant in ARB cells and NAC cells, suggesting an active fungal glutamin-synthetase/glutamin-oxoglutarat-aminotransferase (GS/GOGAT) cycle and fatty acid metabolism in mycorrhizal roots.

Table 2.   Detected fungal genes present on the Medicago genome array with more than twofold altered accumulation levels between at least two cell types
IdentifierPutative functionLog2 fold changea
NAC/CORARB/COR
  1. ARB, arbuscule-containing cells of mycorrhizal roots; NAC, non-arbuscule-containing cells of mycorrhizal roots; COR, cortical cells of non-mycorrhizal roots.

  2. aValues are means of two biological replicates. Listed are putative fungal genes (Gomez et al., 2009) with expression data showing log2 fold changes <−1 or >1 for at least one comparison between two cell types. Normalization was performed by RMA, and a P value cutoff of 0.05 after t test was used.

mtr.10406.1.s1_at18S rRNA gene10.2110.66
mtr.45158.1.s1_at18S rRNA gene6.547.84
mtr.35993.1.s1_at28S rRNA gene6.977.72
mtr.4378.1.s1_atElongation factor 1α (EF-1α)4.966.57
mtr.10012.1.s1_atΔ9 fatty acid desaturase2.076.09
mtr.36015.1.s1_atGlutamine synthetase3.115.20
mtr.7402.1.s1_atWeakly similar to carboxypeptidase2.444.04
mtr.40011.1.s1_at60S ribosomal protein1.173.21
mtr.39701.1.s1_atUnknown protein (autophagy protein; AUT7-like)1.092.96
mtr.42494.1.s1_atUnknown protein (ERP1 protein-like)1.652.72
mtr.39905.1.s1_atAdenine phosphoribosyltransferase-like protein1.672.25
mtr.35483.1.s1_at40S ribosomal protein0.521.91
mtr.4817.1.s1_atRHO protein/GDP dissociation inhibitor-like protein−0.161.32
mtr.11832.1.s1_atLEM3/CDC50 family protein0.451.30
mtr.4791.1.s1_at14-3-3 protein1.281.11

Functional distribution of genes differentially expressed in ARB cells or NAC cells compared to COR cells

For functional characterization of genes regulated in ARB cells and NAC cells, we mapped the Medicago genome array probe set sequences to the M. truncatula genome version 3.0 and analysed the distribution of the regulated transcripts to functional classes using MapMan (Usadel et al., 2009). More than half (58%) of all regulated transcripts could not be assigned to a functional class, and 25% mapped to either protein, RNA, lipid or secondary metabolism, signalling, transport or development. A distribution of the regulated transcripts (log2 fold change cut-off 1) is shown in Figure 4. In NAC cells, 9% of all up-regulated transcripts and 4% of all down-regulated transcripts are involved in protein metabolism. In the other six functional categories, ARB cells showed a higher percentage of down-regulated genes compared with NAC or COR cells. Transporter-encoding genes were not down-regulated in NAC cells compared with COR cells. This analysis showed that a substantial proportion of genes identified as differentially regulated in mycorrhizal roots encode proteins that are involved in RNA and lipid metabolism as well as transport processes, and these are discussed below.

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Figure 4.  Distribution of regulated genes into functional categories. Probe sets representing genes that were differentially expressed between the three cell types were analysed using MapMan. The percentages of genes that were up- or down-regulated in ARB cells (black bars) or NAC cells (grey bars) relative to COR cells are shown for the most prominent functional classes. Positive values indicate the number of genes that were up-regulated and negative values indicate the number of genes that were down-regulated compared to COR cells. LFC, log2 fold change.

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Transporter gene expression in mycorrhizal roots.  The exchange of mineral nutrients and carbohydrates between host plant and AM fungus is the key element of AM symbiosis, with a number of specific transporter genes being involved in symbiosis functioning. For uptake of mineral nutrients released into the peri-arbuscular space by the AM fungus, ARB cells express specific transporter proteins, which are located in the PAM (Javot et al., 2007). In contrast to the plant transporters induced in ARB cells that are involved in the uptake of nutrients into the plant cell, the mechanism of carbohydrate transfer from plant to fungus is still unknown. Surprisingly, we found that two putative sucrose transporters and one hexose transporter were induced in NAC cells compared with COR cells. To confirm the expression pattern of the hexose transporter gene MtHex1/medtr1g132750.1, we analysed promoter–GUS fusions (Figure 5a–d). Microarray data indicated that this hexose transporter is induced in NAC cells but only weakly in ARB cells relative to COR cells, and this was confirmed by the location of promoter activity. The promoter of this putative hexose transporter shows no activity in cortex cells of non-mycorrhizal roots, but is active in central cylinder and pericycle cells. In addition to activity in the central cylinder, the promoter also shows strong activity in distinct inner cortical cells adjacent to ARB cells in mycorrhizal roots (Figure 5a–d). The closest homologue of medtr1g132750.1 in Arabidopsis thaliana is sugar transport protein 13 (STP13), a high-affinity, hexose-specific, plasma membrane-localized H+ symporter, with 77% identity at amino acid level (Norholm et al., 2006). If MtHEX1 shows an identical subcellular localization, transport specificity and direction as STP13, it may be involved in the uptake of hexose from the apoplast into cells in the vicinity of arbuscules or hyphae in mycorrhizal roots.

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Figure 5.  Histochemical localization of GUS activity in transgenic Medicago truncatula roots expressing promoter–GUS fusions. (a–c) MtHext1 (hexose transporter; medtr1g132750.1) promoter–GUS fusion; (e–h) MtSut1 (sucrose transporter; medtr5g076420) promoter–GUS fusion. (a, d, e, h) Bright-field images showing exclusively GUS activity; (b, f) green fluorescence indicating fungal structures, after staining with WGA Alexa Fluor 488; (c, g) merged images of GUS activity and WGA Alexa Fluor 488 fluorescence. (d, h) GUS activity of the promoter fusions in sections of non-mycorrhizal roots; (a–c) and (e–g) are identical sections of mycorrhizal roots. Red arrowheads indicate non-arbuscule-containing cells showing promoter activity.

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A further gene involved in carbohydrate transmembrane transport that is regulated in NAC cells encodes a putative sucrose transporter (MtSut1/medtr5g076420.1). The amino acid sequence encoded by this gene is 81% identical to LjSUT4 of Lotus japonicus, a sucrose transporter, which is thought to function in the proton-coupled uptake of sucrose and possibly other glucosides into the cytoplasm from the vacuole (Reinders et al., 2008). The fact that LjSut4 transcripts accumulate in root nodules suggests altered sugar metabolism in these cells, probably in order to provide sucrose to sink cells during nodule development (Flemetakis et al., 2003). Promoter–reporter fusions showed strong promoter activity in cortex cells adjacent to extracellular fungal hyphae, whereas promoter activity in non-mycorrhizal roots was restricted to the central cylinder and pericycle (Figure 5e–h). Therefore the putative sucrose transporter identified here may be involved in the export of sucrose from the vacuole and thus mobilization of carbohydrate resources in cells adjacent to fungal structures in mycorrhizal roots.

Although increased phosphate uptake is probably the greatest benefit for the mycorrhizal plant, symbiotic transfer of nitrogen compounds have been demonstrated (Govindarajulu et al., 2005; Chalot et al., 2006), and a L. japonicus ammonium transporter whose expression is induced in arbuscule-containing cells has recently been described (Guether et al., 2009a,b). We identified two putative ammonium transporters, of which one (medtr7g075790.2) is induced in NAC cells only, whereas the other (medtr7g140920.1) is strongly induced in ARB cells only. The protein encoded by the latter gene shares 66% identity to the L. japonicus ammonium transporter induced in arbuscule-containing cells (Guether et al., 2009b). Interestingly, this ammonium transporter sequence is different to that of the M. truncatula ammonium transporter expressed in arbuscule-containing cells described recently (Gomez et al., 2009), indicating that several transporter proteins of the same family may be involved in symbiotic ammonium transfer.

In addition to a number of transporters that are likely to be involved in nutrient transfer, a recent large-scale analysis of transporter gene expression identified transporter genes that are induced in mycorrhizal roots but are unlikely to be involved in direct uptake of nutrients from the plant–fungus interface (Benedito et al., 2010). Recently, two plant half-size ATP binding cassette (ABC) transporter proteins (STR/STR2) were identified that are essential for AM symbiosis (Zhang et al., 2010); their sequence similarities to other plant ABC transport proteins suggest that the proteins form a heteromeric export pump located in the PAM and involved in the export of as yet unidentified signalling molecules into the peri-arbuscular space. In our experiment, one full-size ABC transporter gene MtABCB1 (Medtr8g025810), which belongs to the ABCB sub-family (Verrier et al., 2008), shows strongly increased transcript levels in ARB cells and also in adjacent cells. This is in contrast to STR gene expression, which was induced in ARB cells but not in adjacent cells. Use of promoter–GUS fusions confirmed strong promoter activity in ARB cells and additional activity in adjacent cells that are surrounded by extracellular fungal hyphae (Figure 6a,d). Given this expression pattern and its homology to other ABCB transporter proteins, we suggest that MtABCB1 may be involved in the transport of signalling molecules between plant cells during AM symbiosis. Expression of a transcript with similarities to divalent anion/Na+ symporter proteins was also increased in ARB cells, and, to a lower extent, in NAC cells, and this was confirmed by promoter activity analysis (Figure 6b,e).

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Figure 6.  Promoter activity of selected genes transcriptionally regulated in ARB or NAC cells and encoding putative transporter proteins. (a–c, g–i, m, n) Bright-field images showing promoter-driven GUS activity; (d–f, j–l, o, p) green fluorescence indicating fungal structures after staining with WGA Alexa Fluor 488. Corresponding bright-field and florescence images show identical root sections of Glomus intraradices-colonized Medicago truncatula roots expressing promoter–GUS fusions for the following genes: (a, d) sub-family B ABC transporter (medtr8g025810); (b, e) divalent anion: Na+ symporter (medtr2g009260.1); (c, f) major intrinsic protein medtr5g072770.1; (g, j) major intrinsic protein medtr4g136190.1; (h, k) proton-dependent oligopeptide or low-affinity nitrate transporter medtr2g021270.1; (i, l) proton-dependent oligopeptide or low-affinity nitrate transporter medtr4g136330.1; (m, o) proton-dependent oligopeptide or low-affinity nitrate transporter medtr7g116510.1; (n, p) proton-dependent oligopeptide or low-affinity nitrate transporter medtr4g136300.1. Red arrowheads indicate non-arbuscule-containing cells with promoter activity; yellow arrowheads indicate examples for arbuscule-containing cells with promoter activity.

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A further gene with strongly induced transcript levels in ARB cells and also NAC cells relative to COR cells encodes a major intrinsic protein (Medtr4g136190) (Figure 6c,f). In contrast, we also found that a member of this gene family was strongly induced in ARB cells, with only weak transcription, if at all, in NAC cells (Figure 6g,j), indicating that several members of this gene family are important for AM symbiosis in different cells.

The most abundant transporter gene family found to be differentially regulated between the three cell types is the family of H+-dependent oligopeptide transporters, which is represented by seven genes. Substrate selectivity for most plant H+-dependent oligopeptide transporters remains largely unknown, although some members of this family have been shown to transport either peptides, or other non-peptide substrates, such as nitrate, nitrite, histidine and carboxylate (Jeong et al., 2004; Segonzac et al., 2007; Sugiura et al., 2007; Tsay et al., 2007). The observed GUS activity confirmed that four selected genes are strongly transcribed in ARB cells, and two (medtr2g021270 and medtr7g116510) were also found to be transcribed in cells adjacent to ARB cells (Figure 6h,k–p).

In conclusion, mycorrhizal roots show a complex reprogramming of transporter gene expression related to direct nutrient transfer across the PAM and carbohydrate homeostasis in NAC cells. In addition, a number of transporter-encoding genes that are unlikely to be involved in plant–fungus nutrient transfer are regulated in mycorrhizal roots, indicating an exchange of signalling molecules between plant cells during symbiosis development.

Arbuscule development strongly alters the expression of genes involved in lipid metabolism.  The development of fungal structures within the host cells affects cell morphology and results in drastic membrane reorganization. The PAM constitutes the structural and functional interface between the plant cell and the fungus, and its lipid and protein composition is adapted to its biological roles. The reconstruction of plant cell membranes requires large amounts of fatty acids and lipids, which are obtained by both breakdown of storage lipids and enhanced de novo synthesis. The present study clearly suggests remodelling of the cellular membrane system as indicated by strong alterations in the expression of genes involved in lipid metabolism. The colonization of host cells by G. intraradices and arbuscule development resulted in up-regulation of 27 transcripts involved in lipid metabolism, but two transcripts in this category were down-regulated. Similar strongly enhanced expression levels of genes involved in lipid metabolism were found in adjacent cells: 23 transcripts were up-regulated and none showed significantly decreased expression. Transcripts encoding proteins involved in lipid breakdown accumulated in cells containing arbuscules, e.g. a lipase class 3 family protein, which hydrolyses storage lipids such as triacylglycerides. Triacylglycerides in particular are generated in the intra-radical parts of the fungus and are exported to the extra-radical mycelium (Pfeffer et al., 1999). High expression levels in ARB cells were also found for genes encoding key enzymes of the fatty acid synthase system, namely a biotin carboxyl carrier protein, a ketoacyl-acyl carrier protein, a β-hydroxyacyl-acyl carrier protein dehydratase and an enoyl-acyl carrier protein reductase, indicating strongly induced plastid-localized de novo fatty acid synthesis during arbuscule functioning. In addition, the level of a transcript encoding a glycerol-3-phosphate acyltransferase was greatly increased in both ARB and NAC cells. This enzyme participates in glycerolipid and glycerophospholipid metabolism; glycolipids are indispensable for cell membrane composition and are components of several signalling processes. In Arabidopsis thaliana, nine isoforms of glycerol-3-phosphate acyltransferase have been described. Glycerol-3-phosphate acyltransferase is an essential enzyme in catalysis of the initial step of the glycerolipid synthesis, namely the formation of lysophosphatidic acid from glycerol-3-phosphate and acylthioesters (Nishida et al., 1993). Recently, phospholipid-derived lysophosphatidylcholine was identified as a bioactive compound participating in signalling processes during AM symbiosis (Drissner et al., 2007). We also found induced expression of digalactosyldiacylglycerol synthase 2, which catalyses the formation of galactose-containing digalactosyldiacylglycerol, an extraplastidial lipid, that accumulates both under phosphate deprivation conditions (Kelly et al., 2003) and in specialized membranes such as the symbiosome-surrounding membrane in root nodules (Gaude et al., 2004).

In conclusion, these transcriptional changes for genes involved in lipid metabolism strongly suggest the importance of lipid-related processes during AM symbiosis, especially during arbuscule development and functioning.

A notable number of transcription factors are transcriptionally regulated in cells of mycorrhizal roots.  The dramatic reprogramming of root cells during AM symbiosis is thought to involve transcription factors. Interestingly, the majority of regulated transcription factors were strongly up-regulated in NAC cells compared to COR cells, suggesting reprogramming of these cells for subsequent colonization. The transcription factors most strongly induced in ARB cells and NAC cells of mycorrhizal roots encoded CCAAT-binding factors, basic leucine zipper (bZIP) transcriptional factors, basic helix-loop-helix (bHLH) transcription factors, and C2H2 zinc finger, MADS box and Myb family transcription factors (Table 3). The Myb family transcription factor was also recently found to be strongly induced in mycorrhizal roots (Gomez et al., 2009), and a similar Myb transcription factor has been described as specifically induced in ARB cells (Guether et al., 2009a). Furthermore, DNA-binding WRKY and AP2/pathogenesis-related transcription factors were induced by more than 2.5- and 18-fold, respectively, in ARB cells. WRKY transcription factors are involved during pathogen-related stress responses, similar to AP2/pathogenesis-related transcription factors, which activate plant defence genes (Hahlbrock et al., 2003). Two HAP transcription factors (Mtr.16863.1.s1_at and Mtr.51511.1.s1_at), members of the CCAAT-binding family, were found to be highly up-regulated in ARB cells. Several transcription factor genes have been implicated in nodule development, such as members of the C2H2 zinc finger family, the bZIP family and the CCAAT-binding family (Frugier et al., 2000; Nishimura et al., 2002; Combier et al., 2006; Udvardi et al., 2007). The greatly increased expression levels of members of these transcription factor families in ARB cells appear to play an important role in general aspects of plant–microbe interactions. It is worth mentioning that none of the transcription factors known to be important for root nodule symbiosis were found to be transcriptionally regulated in the three cell types analysed in this study. In contrast, it appears that individual members of transcription factor families are involved in either root nodule or mycorrhizal symbiosis. One example is the GRAS transcription factor family. Two members of this family (NSP1 and NSP2) are essential for root nodule symbiosis (Oldroyd and Long, 2003; Kalo et al., 2005; Smit et al., 2005), and we found a different member of the GRAS transcription factor family to be strongly induced in ARB cells. A previously described TFA heat shock factor-encoding gene was the most highly down-regulated transcription factor (ninefold) in our dataset. In the absence of abiotic cellular stresses, such as heat, these heat shock factors are typically inactivated. The down-regulation of this TFA heat shock factor-encoding gene may suggest repression of cellular stress responses during mycorrhizal colonization. Overall, colonization of cortex cells by G. intraradices resulted in up-regulation of 30 transcription factors and down-regulation of 15.

Table 3.   Transcripts assigned to protein, secondary, lipid and RNA metabolism, as well as development, transport and signalling showing more than fourfold altered accumulation levels between at least two cell types are sorted according to their assigned functional category and induction level between ARB and COR cells
mt3.0/Medicago genome array identifierDescriptionLog2 fold changea
NAC/CORARB/COR
  1. ARB, arbuscule-containing cells of mycorrhizal roots; NAC, non-colonized cells of mycorrhizal roots; COR, cortical cells of non-mycorrhizal roots. If available, mt3.0 identifiers are given.

  2. aMean of two biological replicates. Listed are transcripts with expression data showing log2 fold changes <−2 or >2 for at least one comparison between cell types (including the comparison between NAC and ARB cells). Normalization was performed by RMA and a P value cutoff of 0.05 after t-test for at least one cell type comparison was applied.

Transport
 mtr.7210.1.s1Plant defensin6.359.27
 mtr.37110.1.s1Copper transporter6.509.21
 medtr2g021270.1H+-dependent oligopeptide or low-affinity nitrate transporter3.857.54
 mtr.43062.1.s1Phosphate transporter (MtPt4)4.977.36
 medtr4g136300.1H+-dependent oligopeptide or low-affinity nitrate transporter0.947.02
 medtr4g136190.1Major intrinsic protein4.366.71
 mtr.35854.1.s1Plant defensin3.586.38
 mtr.43470.1.s1Plasma-membrane proton-efflux P-type ATPase4.416.31
 mtr.31214.1.s1_sPlant defensin3.086.31
 medtr3g122110.1Small solute transporter5.506.23
 medtr8g025810.1Sub-family B ABC-type transporter4.246.11
 mtr.39705.1.s1Mitochondrial carrier3.475.51
 mtr.35484.1.s1Plant defensin1.905.18
 mtr.2246.1.s1Major intrinsic protein1.334.73
 medtr7g140920.1Ammonium transporter0.304.72
 medtr7g116510.1H+-dependent oligopeptide or low-affinity nitrate transporter1.994.68
 medtr4g136330.1H+-dependent oligopeptide or low-affinity nitrate transporter0.414.36
 mtr.27765.1.s1H+-dependent oligopeptide or low-affinity nitrate transporter2.254.11
 medtr4g159100.1H+-dependent oligopeptide or low-affinity nitrate transporter1.153.36
 medtr2g009260.1Divalent anion: Na+ symporter1.103.06
 mtr.44555.1.s1Amino acid/auxin permease1.202.57
 medtr5g072770.1Major intrinsic protein0.912.51
 medtr8g093390.1SEC14-like phosphoinositide-binding protein1.692.22
 medtr6g089710.1H+-dependent oligopeptide or low-affinity nitrate transporter1.472.14
 mtr.8825.1.s1Sub-family B ABC-type transporter1.482.10
 medtr2g100530.1Proton pump interactor−0.032.01
 mtr.28814.1.s1Sucrose/H+ symporter2.140.57
 medtr5g076420.1Sucrose/H+ symporter2.610.28
 medtr1g132750.1Hexose/H+ symporter2.860.13
 medtr1g117250.1Small solute transporter2.32−0.07
 medtr1g117260.1Small solute transporter1.90−0.34
 medtr7g075790.1Ammonium transporter1.62−0.43
 mtr.12831.1.s1Sub-family A ABC-type transporter2.65−0.51
 mtr.34624.1.s1Cellular retinaldehyde binding1.77−0.53
 medtr2g005850.1Metabolite transporter0.85−1.17
 medtr5g104490.1Amino acid/auxin permease0.85−1.22
 mtr.27606.1.s1Sugar porter1.25−1.27
 medtr4g133980.1Neutral amino acid transporter1.59−1.37
 medtr4g114830.1Zinc/iron permease0.79−1.48
 mtr.38200.1.s1Facilitator-like protein1.46−1.55
 mtr.12983.1.s1Oligopeptide transporter superfamily0.04−2.12
Lipid metabolism
 medtr1g059560.11-acylglycerol-3-phosphate O-acyltransferase5.578.17
 medtr7g092600.1MPL1 (Myzus persicae-induced lipase 1)6.337.31
 medtr3g111420.1Ceramidase family protein4.007.14
 mtr.10012.1.s1Δ9 fatty acid desaturase2.076.09
 mtr.13800.1.s1Lipase class 3 family protein2.825.75
 medtr6g022550.1Glycerol-3-phosphate dehydrogenase (NAD+)0.515.14
 medtr4g165920.1KAS I (3-ketoacyl-acyl carrier protein synthase I)3.354.82
 ac231342_10.1BCCP2 (biotin carboxyl carrier protein 2)2.374.62
 mtr.38606.1.s1Pyruvate kinase2.224.27
 mtr.31871.1.s1Transketolase family protein1.653.99
 medtr7g084010.1DGD2 (digalactosyldiacylglycerol synthase 2)2.593.65
 mtr.35910.1.s1Acyl-(acyl carrier protein) thioesterase1.863.28
 mtr.41225.1.s1β-hydroxyacyl-acyl carrier protein dehydratase1.263.27
 medtr4g132740.1AMP-dependent synthetase and ligase0.653.25
 medtr4g165430.1KASI (3-ketoacyl-acyl carrier protein synthase I)1.233.15
 medtr4g128410.1Acyl-(acyl carrier protein) desaturase1.883.12
 mtr.37723.1.s1Transketolase family protein0.193.10
 medtr4g161110.1Acetyl coenzyme A carboxylase/biotin carboxylase subunit1.032.96
 medtr4g158530.1Lipase family protein3.322.96
 medtr3g033970.1Acyl transferase2.062.92
 mtr.14050.1.s1_sβ subunit of acetyl CoA carboxylase0.682.73
 mtr.43890.1.s1Enoyl-acyl carrier protein reductase (NADH)0.762.69
 medtr3g103330.13-oxoacyl-acyl carrier protein reductase0.792.60
 medtr4g161000.1Phosphorylethanolamine cytidylyltransferase 1−0.912.37
 mtr.12585.1.s13-ketoacyl-acyl carrier protein synthase I0.342.14
 medtr7g089920.1Biotin carboxyl carrier protein 11.702.03
 medtr8g145530.1FAD6 (fatty acid desaturase 6)2.341.40
 mtr.38283.1.s1Lipase class 3 family protein1.86−0.62
 medtr8g043850.1Sulfotransferase family protein1.60−0.86
 medtr4g109960.1Lipase class 3 family protein1.28−0.99
 medtr3g139610.2Coclaurine N-methyltransferase1.39−1.06
 medtr1g065950.1Lipase class 3 family protein0.75−2.03
RNA metabolism
 mtr.8863.1.s1Myb family transcription factor8.159.22
 medtr2g095980.1HAP5 transcription factor7.748.89
 medtr2g095930.1HAP5 transcription factor6.478.2
 medtr8g109760.1GRAS transcription factor5.557.75
 medtr4g092780.1CSL zinc finger domain-containing protein3.016.52
 medtr7g121260.1NAC-like transcription factor (activated by AP3/PI)4.056.00
 medtr7g130150.1Zinc finger, C2H2-type2.695.41
 medtr4g141530.1AP2/ERF transcription factor2.824.23
 medtr3g159850.1SWIRM; homeodomain-related2.342.82
 medtr1g129430.1RNA-binding region RNP-11.762.81
 mtr.9962.1.s1Zinc finger0.762.60
 medtr3g130470.1HD-ZIP transcription factor1.982.58
 medtr5g009440.1AP2/ERF transcription factor1.512.41
 medtr1g024100.1AP2/ERF transcription factor0.342.38
 medtr2g104900.1DNA-directed RNA polymerase subunit β1.022.29
 medtr8g042620.1bZIP transcription factor2.371.98
 medtr7g064510.1WD-40 repeat family protein2.121.95
 medtr1g025470.2Transcriptional factor B32.051.76
 medtr8g129150.1AP2/ERF transcription factor3.111.74
 ac235567_21.1Myb family transcription factor2.631.65
 medtr4g110140.1Small nuclear ribonucleoprotein F2.721.55
 mtr.40530.1.s1_sCCAAT-binding factor2.201.52
 medtr5g015580.1GRAS transcription factor2.691.44
 medtr2g052850.1WRKY42 (WRKY DNA-binding protein 42)2.031.32
 medtr8g147760.1DNA-directed RNA polymerase2.291.13
 medtr7g018180.1TCP transcription factor2.130.87
 medtr4g158010.1Zinc finger, RING-type2.80.48
 medtr5g103350.1CCAAT-binding factor2.37−0.06
 medtr7g103750.1MYB105 (Myb domain protein 105)2.00−0.11
 ac235757_43.1Dof zinc finger protein 11.92−0.24
 medtr3g106460.1bZIP family transcription factor2.06−0.27
 medtr1g121520.1Homeodomain-related1.75−0.33
 mtr.37926.1.s1Helix-loop-helix DNA-binding protein2.40−0.35
 medtr8g083970.1RNA recognition motif (RRM)-containing protein2.34−0.37
 medtr3g087570.1MYB20 (Myb domain protein 20)2.13−0.45
 mtr.41219.1.s1AUX/IAA protein2.18−0.63
 medtr6g093250.1Pentatricopeptide (PPR) repeat-containing protein2.33−1.01
 mtr.44141.1.s1NAC domain-containing protein 1041.50−1.05
 medtr3g136200.1H3/H4 acetyltransferase/transcription co-factor1.69−1.06
 medtr3g150500.1Zinc finger (MYND type) family protein1.9−1.16
 medtr4g121780.1GTE4 (global transcription factor group E4)0.83−1.27
 medtr5g019580.1Homeobox protein 403.20−1.32
 mtr.9397.1.s1Helix-loop-helix DNA-binding protein1.46−1.35
 mtr.8901.1.s1MADS-box transcription factor0.60−1.75
 medtr8g102510.1bHLH transcription factor0.09−1.95
 medtr3g110250.1Leucine zipper, homeobox-associated0.97−2.14
 mtr.35872.1.s1Zinc finger protein-related−1.03−2.53
 medtr8g094180.1PRLI-interacting factor-related−0.62−2.68
 medtr7g108580.1HSFB3 (heat shock transcription factor B3)−0.23−3.2
Protein metabolism and processing
 medtr3g111040.2Serine carboxypeptidase4.387.41
 medtr5g048110.1Proteinase inhibitor I135.627.16
 medtr3g111060.1Serine carboxypeptidase4.057.30
 medtr5g011380.1Protease associated (PA) peptidase S8A4.286.64
 ac233658_1.1Protein kinase family protein3.956.47
 medtr5g022460.1Cysteine-type peptidase4.206.23
 medtr4g109320.1Cysteine-type peptidase2.665.48
 medtr4g109630.1Cysteine-type peptidase2.245.15
 medtr1g092860.1Protease associated (PA) proteinase inhibitor I92.874.90
 medtr3g059060.1Cysteine-type peptidase1.594.89
 medtr5g011480.1Protease associated (PA) peptidase S8A2.174.75
 mtr.40562.1.s1Cyclin-like F-box1.764.74
 mtr.42508.1.s1Calcineurin B subunit3.264.70
 medtr4g069680.1AIR3 (auxin-induced in root cultures 3); subtilase3.614.68
 mtr.43715.1.s1Der1-like protein1.914.64
 medtr2g014450.1Kelch repeat-containing F-box family protein2.574.64
 mtr.31975.1.s140S ribosomal protein S151.804.39
 mtr.31878.1.s126S protease regulatory complex subunit 40.084.22
 mtr.13963.1.s1Subtilase family protein1.073.99
 mtr.31843.1.s1Ubiquitin-specific protease 121.313.78
 mtr.11615.1.s160S ribosomal protein L172.103.78
 mtr.45022.1.s160S ribosomal protein L261.163.61
 medtr3g107040.1AIR3 (auxin-induced in root cultures 3); subtilase−0.083.56
 mtr.4756.1.s140S ribosomal protein S41.243.47
 medtr8g044470.1Putative cysteine protease inhibitor/cystatin2.393.43
 mtr.42806.1.s160S ribosomal protein L351.173.22
 medtr7g106750.1F-box family protein1.173.01
 medtr3g068490.1PMSR1 (peptidemethionine sulfoxide reductase)1.942.96
 medtr5g037460.1MMP (matrix metalloproteinase)1.402.94
 mtr.35730.1.s1Clathrin adaptor complex family protein3.002.91
 mtr.37943.1.s1Cyclin-like F-box2.232.85
 medtr8g105940.1ATG8F (autophagy 8F); microtubule-binding2.382.76
 medtr7g089840.1Serine carboxypeptidase1.362.75
 medtr7g089870.1Aspartyl protease family protein1.082.70
 medtr3g044180.1F-box family protein0.572.62
 mtr.37326.1.s1Ribosomal protein S161.482.61
 mtr.27782.1.s1Cysteine proteinase−0.182.56
 mtr.8244.1.s1Calcineurin-like phosphoesterase family protein0.792.45
 medtr1g068620.1Proteinase inhibitor1.362.44
 medtr4g161030.1FeS assembly ATPase SufC1.562.38
 medtr4g133940.1Kelch repeat-containing F-box family protein3.252.34
 medtr7g092800.1APG4a (autophagy 4a)/peptidase C542.122.28
 medtr5g033900.1Threonine endopeptidase3.302.23
 medtr3g142590.1HEN3 (HUA enhancer 3); kinase2.712.22
 medtr5g085850.1ATARLA1A (ADP-ribosylation factor-like A1A)1.192.22
 medtr5g024990.1Lectin protein kinase family protein0.482.12
 medtr4g042490.1ClpP (caseinolytic protease)−0.512.06
 medtr7g138460.1ATP-dependent Clp protease proteolytic subunit1.882.04
 medtr3g114750.1Octicosapeptide/Phox/Bem1p domain-containing0.862.02
 mtr.4778.1.s160S ribosomal protein L6−0.142.00
 medtr8g137700.2Ubiquitin–protein ligase2.631.83
 mtr.38389.1.s1Signal recognition particle 19 kDa protein2.661.78
 medtr8g084110.1Metalloendopeptidase2.261.77
 medtr7g076140.1PAC1 (20S proteasome α subunit C1)2.571.73
 medtr8g109480.1Eukaryotic release factor 1-3−0.881.70
 medtr5g033220.1NORK_MEDTR protein kinase2.621.56
 medtr6g014210.1Membrane-anchored ubiquitin-fold protein 12.271.16
 ac225517_19.1Tyrosine protein kinase2.851.08
 medtr7g084980.1Proteinase inhibitor I12, Bowman–Birk family2.851.08
 medtr4g110840.130S ribosomal protein S132.210.97
 medtr4g159820.2RNA-binding S4 domain-containing protein3.510.94
 mtr.41396.1.s1KCBP-interacting protein kinase3.220.85
 medtr2g021360.126S proteasome regulatory subunit2.080.82
 mtr.30693.1.s1Eukaryotic translation initiation factor 3E2.410.82
 medtr2g097890.2Shaggy-related protein kinase δ2.030.77
 medtr7g140540.1Protein kinase2.260.68
 medtr3g135900.3Zinc finger (C3HC4-type RING finger) family protein3.740.61
 medtr1g146370.1Similar to protein binding/zinc ion binding protein2.290.44
 medtr1g100510.1ATP-dependent peptidase/serine-type peptidase2.440.36
 medtr2g034150.1Leucine-rich repeat protein kinase2.040.27
 medtr8g120190.1Ribosomal protein L36 family protein2.390.24
 ac235567_12.1Zinc finger, RING-type2.740.20
 medtr4g084210.1Ubiquitin–protein ligase/zinc ion binding protein2.260.14
 medtr1g116870.1Cyclin-like F-box2.290.14
 medtr3g160100.1Protein phosphatase 2C2.000.11
 medtr2g026380.1F-box family protein2.29−0.08
 medtr4g084200.1Ubiquitin–protein ligase/zinc ion binding protein2.18−0.16
 mtr.33815.1.s1Calcium-binding EF hand family protein1.99−0.21
 medtr7g143210.1Cyclin-like F-box1.79−0.22
 medtr1g022850.1Ribosomal protein S171.83−0.27
 medtr4g134000.1Kelch repeat-containing F-box family protein3.32−0.35
 medtr4g095590.1Phenylalanyl-tRNA synthetase1.83−0.39
 medtr7g085030.1Proteinase inhibitor I12, Bowman–Birk family2.78−0.45
 medtr2g125990.1Nucleoporin-interacting component family protein2.00−0.46
 medtr4g152260.1Signal recognition particle-related1.46−0.54
 medtr4g041620.1Protein kinase1.53−0.63
 medtr8g134040.1CIPK1 (CBL-interacting protein kinase 1)1.51−0.68
 medtr5g006650.1Kinase-interacting family protein1.52−0.70
 medtr2g117520.1RPL18AA (60S ribosomal protein L18A-1)1.71−0.77
 medtr3g110330.1CERK1 (chitin elicitor receptor kinase 1)1.68−0.78
 medtr2g032890.1Protein kinase1.37−0.96
 ac233560_16.1ATSLY1; protein transporter1.15−0.97
 medtr2g025150.1Zinc finger (C3HC4-type RING finger) family protein1.23−1.16
 mtr.38662.1.s1Protease-related1.49−1.50
 mtr.31914.1.s1Protein kinase1.66−1.57
 medtr3g083740.1Leucine-rich repeat transmembrane protein kinase1.69−2.02
 medtr8g129250.2Protein kinase family protein−1.05−2.07
 medtr2g110490.1Zinc finger (C3HC4-type RING finger) family protein0.84−2.13
 medtr1g111800.1HSP60 (heat shock protein 60)−1.36−2.18
 medtr2g032890.1Protein kinase1.37−0.96
 ac233560_16.1ATSLY1; protein transporter1.15−0.97
 medtr2g025150.1Zinc finger (C3HC4-type RING finger) family protein1.23−1.16
 mtr.38662.1.s1Protease-related1.49−1.50
 mtr.31914.1.s1Protein kinase1.66−1.57
 medtr3g083740.1Leucine-rich repeat transmembrane protein kinase1.69−2.02
 medtr8g129250.2Protein kinase family protein−1.05−2.07
 medtr2g110490.1Zinc finger (C3HC4-type RING finger) family protein0.84−2.13
 medtr1g111800.1HSP60 (heat shock protein 60)−1.36−2.18
 mtr.40802.1.s1Vacuolar protein sorting-associated protein 26−0.42−2.21
Secondary metabolism
 medtr2g118030.14-coumarate–CoA ligase family protein5.888.21
 mtr.31949.1.s1β-amyrin synthase4.726.58
 mtr.36022.1.s1CAS1 (cycloartenol synthase 1)−0.025.19
 medtr2g110470.1IspG protein; dihydropteroate synthase-like2.113.83
 mtr.4975.1.s1_sSRG1 (senescence-related gene 1)0.852.41
 mtr.37824.1.s1DXR (1-deoxy-d-xylulose 5-phosphate reductoisomerase)1.332.27
 mtr.37674.1.s1Acetyl CoA carboxylase0.942.23
 medtr8g079260.1CLA1 (chloroplastos alterados 1), transketolase0.582.13
 mtr.9757.1.s1Putative quinolinate phosphoribosyltransferase3.142.10
 medtr1g126460.2β-hydroxylase 1, carotene hydroxylase4.251.18
 medtr5g106000.1Acetyl CoA C-acetyltransferase2.201.08
 medtr8g088630.1Strictosidine synthase2.660.98
 medtr7g073460.1O-methyltransferase family 2 protein2.110.92
 mtr.37805.1.s1NAD-dependent epimerase/dehydratase2.800.17
 medtr1g146220.1Chalcone–flavanone isomerase3.30−0.11
 medtr4g121200.1Isochorismatase hydrolase1.85−0.28
 medtr3g143560.1O-diphenol-O-methyltransferase1.66−0.34
 medtr2g009860.1Aldehyde dehydrogenase1.62−0.54
 mtr.10514.1.s1Acyl-activating enzyme 132.41−0.62
 medtr7g015000.1Naringenin chalcone synthase1.48−0.85
 mtr.8728.1.s1Pectinacetylesterase1.29−1.11
 medtr8g081340.1Isochorismatase hydrolase2.33−1.24
 mtr.33281.1.s1_sTerpene synthase/cyclase family protein1.02−1.82
 medtr8g105360.2Oxidoreductase, 2OG-Fe(II) oxygenase family protein0.56−1.85
 medtr5g081380.1Copper ion binding/oxidoreductase−2.62−2.10
 medtr4g108960.1O-methyltransferase family 2 protein−0.14−2.54
Development
 medtr7g084780.1Barwin-related endoglucanase4.427.07
 mtr.29627.1.s1Putative ankyrin repeat protein5.476.45
 medtr7g084780.1Barwin-related endoglucanase4.427.07
 mtr.29627.1.s1Putative ankyrin repeat protein5.476.45
 mtr.10916.1.s1_sMtN28 protein precursor2.905.65
 medtr5g023140.1SEN1 (dark inducible 1) rhodanese-like4.175.58
 medtr7g077340.1Late nodulin1.275.35
 medtr7g084890.1Barwin-related endoglucanase1.385.33
 medtr7g011830.1Barwin-related endoglucanase2.334.83
 medtr4g042690.1Barwin-related endoglucanase2.464.80
 mtr.42041.1.s1Nodulin MtN3 family protein1.664.49
 medtr7g084580.1Barwin-related endoglucanase1.494.24
 medtr7g084870.1Ripening-related protein 1 precursor0.684.21
 medtr3g087200.1Late nodulin2.144.07
 medtr7g084810.1Barwin-related endoglucanase2.263.38
 mtr.2424.1.s1Nodulin family protein0.992.77
 medtr7g088940.2Late embryogenesis abundant protein 21.732.43
 medtr4g129640.1Defective embryo and meristems protein-related2.272.21
 medtr6g022850.1Late nodulin1.362.08
 mtr.12327.1.s1Late embryogenesis abundant protein3.081.32
 medtr7g117340.1Transducin family protein/WD-40 repeat family2.481.01
 medtr8g101630.1EMB1408 (embryo-defective 1408)2.270.46
 mtr.28791.1.s1Plastid developmental protein DAG2.060.11
 medtr4g165720.1WD-40 repeat-containing protein MSI12.80−0.24
 medtr1g009230.1Seven in absentia (SINA) family protein2.07−0.26
 medtr7g137990.1TPR3 (topless-related 3)1.57−0.49
 medtr5g048760.1Tyrosine protein kinase1.67−0.73
 medtr1g031190.1Gibberellin-regulated protein−3.20−5.54
Signalling
 mtr.3391.1.s1GPI ethanolamine phosphate transferase 26.178.20
 medtr7g143320.1Protein kinase family protein4.386.97
 mtr.4781.1.s1Calmodulin 73.596.05
 medtr5g032540.1Lectin protein kinase1.925.81
 medtr5g032550.1Lectin protein kinase1.325.20
 mtr.11696.1.s1Remorin3.144.62
 medtr2g126830.1Calcium-binding EF hand family protein2.414.49
 medtr8g079070.1Lectin protein kinase0.743.03
 medtr8g137890.1ARF/SAR superfamily2.482.95
 medtr8g078040.1Inositol 1.3.4-trisphosphate 5/6-kinase2.092.79
 mtr.44516.1.s1Calcium-transporting ATPase2.882.70
 medtr3g144560.1BRI1 (brassinosteroid-insensitive 1); kinase1.212.41
 medtr2g041370.1Lectin protein kinase family protein−0.072.17
 medtr4g132720.1Rapid alkalinization factor2.731.72
 medtr2g091020.1Leucine-rich repeat family protein2.581.08
 mtr.41267.1.s1Zinc finger (Ran-binding) family protein3.231.01
 mtr.42199.1.s1Leucine-rich repeat transmembrane protein2.360.70
 mtr.10974.1.s1Membrane occupation and recognition nexus2.250.41
 medtr1g127100.1Photoassimilate-responsive protein2.300.41
 medtr2g034150.1Leucine-rich repeat family protein2.040.27
 medtr5g034280.1Leucine-rich repeat family protein2.360.26
 medtr5g017130.1Ralf-like 34, rapid alkalinization factor2.020.22
 medtr5g106530.1Zinc finger, SWIM-type2.310.11
 medtr1g024260.1Remorin family protein2.44−0.07
 medtr2g121730.1Light-repressible receptor protein kinase3.26−0.23
 medtr5g094910.1Leucine-rich repeat protein1.74−0.36
 medtr8g015050.1S-locus lectin protein kinase family protein1.99−0.42
 medtr8g068080.1Leucine-rich repeat family protein/protein kinase1.50−0.70
 medtr5g005710.1CRK10 (cysteine-rich RLK10); kinase1.27−0.84
 medtr1g087250.133 kDa secretory protein-related1.80−0.98
 mtr.44482.1.s1Calmodulin binding1.00−1.05
 medtr8g025050.3RelA/spoT homologue; metal-dependent phosphohydrolase−2.02−1.52
 medtr7g025040.1PGIP1 (polygalacturonase-inhibiting protein 1)0.78−1.60
 medtr7g025000.1PGIP1 (polygalacturonase-inhibiting protein 1)1.64−1.63
 mtr.39538.1.s1Protein kinase family protein2.59−1.63
 medtr6g065100.1Protein kinase family protein0.17−2.12
 medtr3g030480.1Leucine-rich repeat family protein−1.63−2.22
 mtr.11268.1.s1Leucine-rich repeat family protein1.36−2.41
 medtr8g144660.1Leucine-rich repeat family protein−0.52−2.58

Conclusion

The method for LCM-mediated harvest of distinct cells types of mycorrhizal roots described here enabled elucidation of transcriptome profiles at cellular resolution. Arbuscule-containing cells and non-arbuscule-containing cells of mycorrhizal roots show specific reprogramming of expression of genes involved in transport, lipid metabolism and transcription regulation, indicating the importance of these cellular functions for symbiosis development.

Experimental procedures

  1. Top of page
  2. Summary
  3. Introduction
  4. Results and discussion
  5. Experimental procedures
  6. Acknowledgements
  7. References
  8. Supporting Information

Plant material and growth conditions

Medicago truncatula Gaertn., cv. Jemalong (A17) seed germination was performed as described by Branscheid et al. (2010). The seedlings were transplanted into pots containing a mixture of clay, silica sand, vermiculite and 10% v/v G. intraradices. The G. intraradices inoculum was obtained by growing Allium schoenoprabum with G. intraradices as described by Mrosk et al. (2009). The plants were grown in a greenhouse for 21 days at 24°C with a 8 h light/ 16 h dark cycle. Plants were fertilized with half-strength Hoagland solution (Hoagland and Martin, 1950) containing 20 μm phosphate, twice per week.

Preparation of tissue sections and laser microdissection

Fresh 1 cm root pieces of mycorrhizal and non-mycorrhizal M. truncatula plants (21 days post-inoculation) were dissected, immediately mounted in a pre-cooled specimen holder with embedding material (tissue freezing medium; Electron Microscopy Sciences, http://www.emsdiasum.com/microscopy), and snap-frozen in liquid nitrogen. Longitudinal sections (35 μm thick) were obtained using a cryostat at −22°C (Leica CM 1950 Cryostat; Leica Microsystems, http://www.leica.com/). Root sections were arranged in parallel on UV-treated poly-l-lysine slides. A laser microbeam system (P.A.L.M. Microlaser Technologies, http://www.zeiss.de/microdissection) was utilized for microdissection of cortical root cells. For cutting, the following parameters were selected using P.A.L.M. Robosoftware 2003 (http://www.zeiss.de/microdissection): auto-LPC focus 50, with energy of 95 and a speed of 100. The cutting and isolation of combined cell units of the various cell types was performed at 40-fold magnification. Approximately 5000–10 000 cortical cells were isolated as combined cell units. Isolated specimens were directly catapulted onto the adhesive surface on the inside of the lid of a 0.5 ml reaction tube (Carl Zeiss, http://www.zeiss.com/), collected by centrifugation (11 000 g for 30 sec), and immediately subjected to lytic digestion in the case of subsequent RNA isolation.

RNA isolation and quality assessment

The digestion of collected cells was subsequently performed in the collection tube by adding 350 μl RLT buffer (Qiagen, http://www.qiagen.com/), 40 units μl−1 RNaseOUT (Invitrogen, http://www.invitrogen.com/) and 3.5 μl β-mercaptoethanol (Sigma-Aldrich, http://www.sigmaaldrich.com/). The sample was vigorously mixed and incubated at 56°C for 5 min to facilitate cell-wall disruption. At this stage, the lysate was either stored at −80°C or further processed for RNA isolation.

Total RNA of each cell population was extracted using an RNeasy micro kit (Qiagen) according to the manufacturer’s instructions. The RNA concentration was determined using NanoDrop ND-1000 (NanoDrop Products, http://www.nanodrop.com). The RNA quality was assessed by determining the OD260/OD280 ratio. In addition, the integrity of RNA molecules was determined by utilization of an RNA 6000 Pico LabChip Kit and Bioanalyzer 2100 (Agilent Technologies, http://www.agilent.com).

Affymetrix Genechip® Medicago genome array hybridization

Total RNA (50–100 ng) was subjected to amplification by the WT-Ovation™ One-Direct amplification system (NuGEN, http://www.nugeninc.com). This technology was designed for direct amplification of RNA in picogram quantities in cell lysates. For expression analysis, up to 3 μg of amplified biotin-labelled cDNA was hybridized to Affymetrix GeneChip®Medicago genome arrays (Affymetrix, http://www.affymetrix.com/). Hybridization, washing steps, staining and scanning were performed according to the manufacturer’s instructions.

Statistical analysis of the transcriptomic dataset

Data normalization was performed using the RMA algorithm (Irizarry et al., 2003). Presence/absence calls for each probe set were determined using the MAS5.0 statistical algorithm (Li and Wong, 2001). The Affymetrix expression software Console™ was used for background correction, to summarize probe set data and to facilitate the generation of CEL files for genes assigned as present. For RMA normalization and P value and background correction, CEL files were imported into the Robin software package (http://mapman.gabipd.org/web/guest/robin). A cut-off for genes showing a P value > 0.05 was used, and normalization was performed via RMA. Probes showing significant differential gene expression were identified using linear modelling with LIMMA (Smyth, 2004). For visualization of expression data in a functional context, the results were directly subjected to the MapMan software package (http://mapman.gabipd.org/web/guest/mapman). Functional classification of the selected genes was performed by MIPS categorization (http://mips.helmholtz-muenchen.de/plant/medi3/).

Quantitative RT-PCR

Total RNA of microdissected cells was isolated using an RNeasy micro kit (Qiagen) and the concentration was determined using NanoDrop ND-1000 followed by quality assessment using the Agilent Bioanalyzer 2100, as described above. For each cell population, a final concentration of 1–2 ng μl−1 DNase-treated RNA was subjected to cDNA synthesis using a Superscript II™ kit (Invitrogen) according to the manufacturer’s instructions. Quantitative RT-PCR was performed as described by Branscheid et al. (2010). Oligonucleotide sequences for all primers are listed in Table S3. As a constitutively expressed M. truncatula reference gene, we used the MtEf1 gene (Wulf et al., 2003) for normalization of expression levels of the genes of interest. Amplification efficiencies were calculated using the LinRegPCR program (Ramakers et al., 2003). Two biological replicates were performed for each quantitative RT-PCR analysis.

Histochemical localization of promoter activities

Using specific primers listed in Table S3, promoter fragments of the selected genes were amplified and inserted into the vector pGWB433 (Karimi et al., 2002) by Gateway cloning (Invitrogen). Binary vectors were transformed into M. truncatula A17 roots by A. rhizogenes-mediated transformation. Composite plants with transgenic roots were inoculated with G. intraradices and harvested 3 weeks after inoculation. Roots were stained for GUS activity and mycorrhizal structures as described previously (Harrison et al., 2002).

Acknowledgements

  1. Top of page
  2. Summary
  3. Introduction
  4. Results and discussion
  5. Experimental procedures
  6. Acknowledgements
  7. References
  8. Supporting Information

We are grateful to Carola Kuhn (Plant Physiology Department, University of Potsdam, Germany) for helpful advice on cryosectioning. We thank Julia Kehr (Department of Functional Genomics, Centre of Plant Biotechnology and Genomics, Madrid, Spain) for an introduction to laser capture microdissection. This research was financed by the Max Planck Society.

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  2. Summary
  3. Introduction
  4. Results and discussion
  5. Experimental procedures
  6. Acknowledgements
  7. References
  8. Supporting Information
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Supporting Information

  1. Top of page
  2. Summary
  3. Introduction
  4. Results and discussion
  5. Experimental procedures
  6. Acknowledgements
  7. References
  8. Supporting Information

Figure S1. Visualization of fungal structures in 35 μm cryosections. The upper figure shows the bright field image of a representative cryosection as it appeared during cell selection for Laser Capture Microdissection (LCM). Under bright field, arbuscules show up as dense structures in cortical cells (yellow arrowhead). In the lower picture, the green signal arises from WGA-Alexafluor 488-staining of fungal cell walls and clearly confirms arbuscule-containing cells. The blue arrowhead indicates an example of a non-arbusculated cell (nac) of mycorrhizal roots, which would have been selected by LCM. WGA-Alexafluor 488-staining confirmed the absence of fungal structures in these cells. However, intercellular hyphae (red arrowhead) are present adjacent to non-arbusculated cells and are unrecognizable by bright field microscopy.

Figure S2. Quality control of the integrity of LCM-derived total RNA prior to hybridization with Medicago GeneChip® array. Visualization of single-cell-derived RNA by electropherogram and gel depiction obtained using bioanalyzer measurements. (a) Cortical cells of non-mycorrhizal roots (cor); (b) arbuscule-containing cells (arb); (c) non-colonized cortical cells of mycorrhizal roots (nac); (d) RNA ladder.

Figure S3. Venn diagram representing the overlap of transcriptional regulation events observed at global root level (Gomez et al., 2009) and at cell type specific level (this study). Raw data after microarray hybridisation were compared using Robust Multichip Average normalization with Benjamimi–Hochberg correction of P-values and separate multiple testing strategy with the Robin software package.

Table S1. Mycorrhizal colonization parameter of M.  truncatula plants three weeks after inoculation with G.  intraradices. Roots of five individual plants were stained with trypan blue and mycorrhizal colonization parameter were estimated as described earlier (Trouvelot et al. 1988)

Table S2. Gene expression data for transcrips with at least twofold changed expression bewteen two of the analyzed cell types (arb, arbuscule-containing cells; nac, non-colonized cells of mycorrhizal roots; cor, cortical cells of non-myorrhizal roots). The affymetrix identifier (id) have been assigned to functional classes using MapMan (Usadel et al. 2009).

Table S3. Oligonucleotide sequences for qRT–PCR measurements and promoter reporter fusions.

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