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Commentary Blackwell Oxford, New NPH © 1469-8137 0028-646X November 10.1111/j.1469-8137.2008.02719.x 2719 2 0 Commentary Commentary 245??? 43??? ThePhytologist Authors UK Publishing 2008(2008).Ltd Journal compilation © New Phytologist (2008)

Stable carbon isotopes reveal dynamics of respiratory metabolism Measurement of respiration via the rate of CO2 release is conceptually simple, but assigning the metabolic origin of respired CO2 to the appropriate biochemical pathway is extremely difficult. By comparing the stable carbon isotope composition of CO2 respired by plant organs with that of likely respiratory substrates, by consideration of potential isotope fractionations and by the judicious application of labeled substrates, three papers in this issue of New Phytologist were able to draw strong conclusions regarding the metabolism involved in leaf (Gessler et al.; pp. 374–386) and root (Bathellier et al.; pp. 387–399) respiration in model species, and leaf respiration across plant functional groups (Priault et al.; pp. 400–412). These three papers used elegant experimental methods to test a number of theories regarding the relative importance of different respiratory pathways and, as such, provide a significant advance in understanding the processes involved.

‘... leaf-respired CO2 has been found to be even more enriched than the theoretical maximum of 6‰, ...’

For some years, considerable research has been carried out on terrestrial carbon cycling because it has become evident that understanding vegetation responses to the environment are vital to mitigating and adapting to future climate change. While net fluxes of carbon into and out of ecosystems may be directly measured (for instance using eddy covariance techniques), partitioning the net flux into component fluxes is challenging. Stable isotopes are seen as a powerful tool in understanding carbon cycling, both as a tracer and as a record of processes where isotopic fractionation occurs (Yakir & Sternberg, 2000; Bowling et al., 2008). Accurate partitioning of ecosystem fluxes requires a mechanistic understanding of plant metabolism, and while photosynthetic metabolic pathways and related isotopic fractionations have been described in

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mechanistic models (Brugnoli & Farquhar, 2000), the same cannot be said for respiration. Not only are the relative activities of metabolic pathways involved in plant respiration poorly understood, but carbon isotope effects during plant respiration are only just becoming elucidated (Ghashghaie et al., 2003; Schnyder et al., 2003; Barbour et al., 2007; Bathellier et al., 2008). Respiration is the broad term used to describe the release of CO2, or the uptake of O2, during cellular metabolism of a carbon substrate to provide energy. CO2 is released by (1) decarboxylation of pyruvate as the first glycolytic step in the mitochondria; (2) by isocitrate dehydrogenase and (3) 2oxoglutarate dehydrogenase in the mitochondrial Krebs cycle; (4) during the formation of ribulose 5-phosphate from glucose in the pentose phosphate pathway operating in the cytosol and plastids; and (5) during decarboxylation of malate in the mitochondria by the NAD-dependent malic enzyme. Each of these reactions may contribute to the measured CO2 flux to a greater or a lesser extent in different tissues and at different times during growth. A number of recent papers have suggested that the carbon isotope composition of respired CO2 (δ13Cr) may provide information on the relative importance of these pathways, because δ13Cr has been shown to vary between species (Werner et al., 2007) and plant organs (Klumpp et al., 2005), with environmental conditions such as light (Hymus et al., 2005) and to co-vary with the type of substrates used for respiration (Tcherkez et al., 2003). The probability of finding a 13C atom in the six different carbon positions of a hexose molecule is not equal, with atoms C3 and C4 being 2 and 6‰ more enriched, respectively, than the average for the whole molecule (Roßmann et al., 1991). These carbon atoms are released as CO2 by pyruvate dehydrogenase during glycolysis and provide a credible explanation for 13C enrichment in respired CO2 under conditions when the resulting acetyl-CoA is diverted to lipid synthesis rather than being fully consumed in the Krebs cycle (Ghashghaie et al., 2003; Tcherkez et al., 2003). However, leaf-respired CO2 has been found to be even more enriched than the theoretical maximum of 6‰, which is only achievable with atom C4 of glucose as the sole source of respired CO2. This was particularly evident during the light-enhanced dark respiration (LEDR) peak observed immediately after darkening a leaf. This extreme and transient enrichment led Barbour et al. (2007) to hypothesize that malate derived from phosphoenolpyruvate carboxylase (PEPc) activity was used for respiration during the LEDR peak. Phosphoenolpyruvate carboxylase fixes 13Cenriched carbon into position C4 in malate in the light. Some cytosolic malate is transported into the mitochondria and is decarboxylated by the NAD+-dependent malic enzyme,

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releasing the enriched carbon at position C4. Using measurements of δ13Cr, activities of key enzymes and metabolite concentrations, Gessler et al. (2009) were able to demonstrate that the enriched δ13Cr obtained during LEDR is indeed a result of the rapid decarboxylation of malate. They estimated that about 22% of the CO2 emitted during the LEDR peak is obtained through the decarboxylation of malate. After the LEDR peak in pre-illuminated leaves, leaf-respired CO2 is often still enriched compared with likely respiratory substrates. The degree of this enrichment varies considerably between species and, in some experiments, diurnally. For example, Priault et al. (2009) found that δ13Cr in the slowgrowing woody shrub Halimium halifolium was increasingly enriched during the day, reaching a peak of −21‰ just before dusk and a minimum of −29‰ predawn. By contrast, the fast-growing herb Oxalis triangularis showed a constant δ13Cr of −30‰ during the day, which decreased, by only 2‰, to −32‰ predawn. By applying pyruvate labeled with 13C, in position C1 or in both positions C2 and C3, to these contrasting species, Priault et al. were able to determine that slow-growing woody plants had greatly reduced carbon flow through the Krebs cycle, relative to pyruvate dehydrogenase activity, compared with fast-growing herbaceous plants. In slow-growing plants, a higher proportion of carbon is diverted from the Krebs cycle into the secondary metabolism. This fits well with theoretical predictions made by Bowling et al. (2008), that CO2 respired by leaves of slow-growing plants will be 2.6‰ more enriched than that respired by leaves of fast-growing plants (given hexose substrates of the same isotope composition), as a result of differences in the balance between maintenance and growth respiration between the functional groups. This estimate is based on the higher levels of secondary metabolites found in slow-growing plants and the fact that differences in chemical composition have accompanying isotope effects. While carbon respired by leaves is generally enriched in 13 C, root-respired CO2 is often slightly depleted compared with likely respiratory substrates. A number of hypotheses have been advanced to explain this difference. The pentose phosphate pathway is thought to account for about one-quarter of root-respired CO2, but pyruvate dehydrogenase and the Krebs cycle are also thought to contribute significantly to CO2 respired by roots (Dieuaide-Noubhani et al., 1995). As described in a previous paragraph, the CO2 released by pyruvate dehydrogenase will probably be enriched in 13C, but the Krebs cycle in all probability releases depleted CO2, as does the pentose phosphate pathway. Anaplerotic carbon fluxes, through PEPc, may also be significant in heterotrophic tissues. Using measurements at both natural abundance and with 13C-labeled substrates, Bathellier et al. (2009) were able to estimate that in Phaseolus vulgaris roots, 50% of respired CO2 comes from the Krebs cycle, 28% comes from pyruvate dehydrogenase and 22% comes from glucuronic acid decarboxylase, after 10 h in the dark. These proportions shifted, after the plant had been in the dark for 4 days, to 57, 28 and 15%,

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respectively. After 4 days in the dark, the Krebs cycle was increasingly fed by lipids, rather than by carbohydrates, but these changes did not result in variation in overall δ13Cr under natural abundance conditions. Similarly, PEPc activity was thought to have only a small overall effect on δ13Cr in P. vulgaris. However, in Ricinus communis stems and roots, Gessler et al. (2009) found that the PEPc activity was very high in roots, and that the depletion of δ13Cr could be explained by the refixation of CO2 by PEPc. Further species differences in the relative allocation of carbon to the different pathways in roots and stems may become apparent as more species are studied. Taken together, these three papers highlight that understanding δ13Cr is a complex, yet tractable, endeavor. It is now clear that one must take a systems approach to understand the balance among the pentose phosphate pathway, pyruvate dehydrogenase activity, the Krebs Cycle and PEPc activity because they vary by tissue, species and environmental conditions. Future studies should take advantage of the labelling and nuclear magnetic resonance (NMR) techniques. developed in the laboratory of Ghashghaie & Tcherkez, to elucidate, in more detail, the metabolic processes contributing to respiration under a wider range of environmental and growth conditions and in a wider range of species. This will be particularly important for root respiration, where metabolic understanding is in its infancy. More experiments also need to be conducted in natural ecosystems at natural abundance to start to describe environmental, species, temporal and spatial variation in δ13Cr. The recent development of field-based laser-absorption spectroscopy will rapidly advance data collection and understanding in this area. The potential for using techniques involving stable isotopes to help understand terrestrial carbon cycling has been recognized for many years, and it is time for this potential to be realized. Margaret M. Barbour1* and David T. Hanson2 1Landcare

Research, PO Box 40, Gerald St., Lincoln 7640, New Zealand; 2University of New Mexico, Department of Biology, MSC03 2020, 167 Castetter Hall, Albuquerque, NM 87131-1091, USA (*Author for correspondence: tel +64 03 321 9608; fax +64 03 321 9999; email [email protected])

References Barbour MM, McDowell NG, Tcherkez G, Bickford CP, Hanson DT. 2007. A new measurement technique reveals rapid post-illumination changes in the carbon isotope composition of leaf-respired CO2. Plant, Cell & Environment 30: 469–482. Bathellier C, Badeck FW, Couzi P, Harscoët S, Mauve C, Ghashghaie J. 2008. Divergence in δ13C of dark respired CO2 and bulk organic matter occurs during the transition between heterotrophy and autotrophy in Phaseolus vulgaris L. plants. New Phytologist 177: 406–418.

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Commentary Bathellier C, Tcherkez G, Bligny R, Gout E, Cornic G, Ghashghaie J. 2009. Metabolic origin of the δ13C of respired CO2 in roots of Phaseolus vulgaris. New Phytologist 181: 387–399. Bowling DR, Pataki DE, Randerson JT. 2008. Carbon isotopes in terrestrial ecosystem pools and CO2 fluxes. New Phytologist 178: 24–40. Brugnoli E, Farquhar GD. 2000. Photosynthetic fractionation of carbon isotopes. In: Leegood RC, Sharkey TD, von Caemmerer S, eds. Photosynthesis: physiology and metabolism. Norwell, MA, USA: Kluwer Academic Publishers, 399– 434. Dieuaide-Noubhani M, Rafford G, Canioni P, Pradet A, Raymond P. 1995. Quantification of compartmented metabolic fluxes in maize root tips using isotope distribution from C-13 or C-14-labeled glucose. Journal of Biological Chemistry 270: 13147–13159 Gessler A, Tcherkez G, Karyanto O, Keitel C, Ferrio JP, Ghashghaie J, Kreuzwieser J, Farquhar GD. 2009. On the metabolic origin of the carbon isotope composition of CO2 evolved from darkened lightacclimated leaves in Ricinus communis. New Phytologist 181: 374–386. Ghashghaie J, Badeck F, Lanigan G, Nogúes S, Tcherkez G, Deléens E, Cornic G, Griffiths H. 2003. Carbon isotope fractionation during dark respiration and photorespiration in C3 plants. Phytochemistry Reviews 2: 145–161. Hymus GJ, Maseyk K, Valentini R, Yakir D. 2005. Large daily variation in 13C-enrichment of leaf-respired CO in two Quercus forest canopies. New 2 Phytologist 167: 377–384. Klumpp K, Schaufele R, Lotscher M, Lattanzi FA, Feneis W, Schnyder H. 2005. C-isotope composition of CO2 respired by shoots and roots: fractionation during dark respiration? Plant, Cell & Environment 28: 241–250. Priault P, Wegener F, Werner C. 2009. Pronounced differences in diurnal variation of carbon isotope composition of leaf respired CO2 among functional groups. New Phytologist 181: 400–412. Roßmann A, Butzenlechner M, Schmidt HL. 1991. Evidence for a nonstatistical carbon isotope distribution in natural glucose. Plant Physiology 96: 609–614. Schnyder H, Schäufele R, Lötscher M, Gebbing T. 2003. Disentangling CO2 fluxes: direct measurements of mesocosm-scale natural abundance 13 CO2/12CO2 gas exchange, 13C discrimination, and labeling of CO2 exchange flux components in controlled environments. Plant, Cell & Environment 26: 1863–1874. Tcherkez G, Nogués S, Bleton J, Cornic G, Badeck F, Ghashghaie J. 2003. Metabolic origin of carbon isotope composition of leaf dark-respired CO2 in French bean. Plant Physiology 131: 237–244. Werner C, Hasenbein N, Maia R, Beyschlag W, Máguas C. 2007. Evaluating high time-resolved changes in carbon isotope ratio of respired CO2 by a rapid in-tube incubation technique. Rapid Communication in Mass Spectrometry 21: 1352–1360 Yakir D, Sternberg L. 2000. The use of stable isotopes to study ecosystem gas exchange. Oecologia 123: 297–311. Key words: 13C labelling, isotope discrimination, light-enhanced dark respiration, stable carbon isotope, respiration. November 10.1111/j.1469-8137.2008.02691.x 2691 2 0 Commentary Commentary 245??? 43??? 2008 Commentary Commentary

Spores of ectomycorrhizal fungi: ecological strategies for germination and dormancy Some plant seeds germinate immediately following dispersal if provided with favorable water, oxygen, temperature and

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light conditions, whereas others do not germinate even when environmental conditions are suitable. Such dormancy strategies are widespread in many temperate plant species to prevent the germination of seeds during unfavorable seasons such as winter. The seeds of some plant species can undergo dormant periods exceeding 1000 yr (Shen-Miller et al., 1995) while waiting for rare chances of regeneration. The traits of seed germination/dormancy are directly relevant to plant life and have therefore been studied extensively in various scientific fields, from molecular genetics to ecology (Finch-Savage & Leubner-Metzger, 2006, Holdsworth et al., 2008).

‘... only a small proportion of spores (1–8% at maximum estimates) were initially receptive to host roots, and receptive spores increased year by year as a result of the release of spore dormancy.’

Fungal spores are functionally analogous to plant seeds in many respects. Spores are dispersed from mature individuals, germinate in new places and grow into mature individuals. Thus, spore germination and dormancy traits have a substantial influence on fungal life. However, few published studies have examined the germination and dormancy of fungal spores. This is especially true for ectomycorrhizal fungi (EMF), which are indispensable symbionts to major trees in many forests. Specifically, it is unclear whether EMF spores become dormant and how long they remain viable. In this issue of New Phytologist, Bruns et al. (pp. 463–470) report an important step towards answering these fundamental questions by providing evidence that spores of some Rhizopogon species remained viable for at least 4 yr in field soil and, more surprisingly, that the infectivity of spores increased with time. The importance of basidiospores in EMF ecology Most EMF communities are dominated by basidiomycetes, which include many mushrooms, puffballs, boletes, chanterelles and earth stars. Recent molecular ecological studies revealed that EMF populations are usually composed of many genetically different individuals of the same species, or genets. Moreover, genets of many EMF are relatively small in size (e.g. Redecker et al., 2001), and in some EMF species, rapid genet turnover is apparent (e.g. Guidot et al., 2004). These studies strongly indicate the importance of basidiospores (hereafter referred to as spores) for the development and maintenance of EMF populations because spore-mediated regeneration is the only


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Fig. 1 Spore germination, infectivity and longevity of major ectomycorrhizal fungal (EMF) genera with reference to their ecological traits. Note that the data in this figure do not indicate that all species in each genus have the same properties. Data were derived from several representative studies using a small number of species in each genus. Direct comparison of data may be difficult owing to different experimental conditions/measures. A complete list of references for this figure is available as Supporting information online (Table S1). *The maximum germination rate (%) recorded in each EMF genus is shown by bar graphs. If detailed data are available for a specific species/ study where a maximum value was detected, upper and lower quartiles are shown by a gradation box with the mean value in the darkest color. R and M beside the maximum bars indicate stimulation with host roots and microbes, respectively. Data are mostly from Theodorou & Bowen (1987) and Ishida et al. (2008). †Significant germination/infectivity decrease and increase after 1 yr is shown by descending and ascending arrows, respectively, P < 0.05. Data are from Ashkannejhad & Horton (2006), Ishida et al. (2008) and Bruns et al. (2009). ‡Ecological traits shown here are derived from some representative species used in spore germination and inoculation studies, and are not applicable to all species in a genus.

way to produce new genets. Spores also play critical roles in the development of EMF communities because new EMF species are mostly delivered to new habitats in the form of spores. This is especially true in primary successional areas where no other inoculum sources are available (e.g. Ashkannejhad & Horton, 2006). Interactions between EMF spores and host roots Despite growing evidence indicating the importance of spores in EMF ecology, there is a lack of information regarding EMF spore germination. This is partly a result of the difficulty in managing EMF spore germination. Spores of most EMF species do not germinate on ordinary synthetic media, on which saprophytic fungal spores easily germinate (Fries, 1987 and references therein). In the presence of host roots, however, spore germination is significantly improved for some EMF


(Fig. 1). In particular, pioneer EMF, which appear early in undeveloped habitats, usually respond to host roots very well. For example, the maximum spore-germination rates of Rhizopogon, Laccaria, Hebeloma and Inocybe can exceed 50% in the presence of host roots (Theodorou & Bowen, 1987; Ishida et al., 2008). Such stimulation might be caused by chemicals secreted from host roots (e.g. flavonoids, as reported by Kikuchi et al., 2007). Given that EMF live in symbiosis with host roots, it is a reasonable strategy to germinate only in their presence. In contrast to these pioneer EMF, spores of Russula, Lactarius, Amanita and Cortinarius germinate poorly, even in the presence of host roots (Fig. 1). These poorly germinating species usually do not appear in pioneer habitats but are often dominant in many mature forests. Thus, nonpioneer EMF species may require additional stimuli that are specific to mature forests, given their ecological traits. The contrasting germination patterns between pioneer and


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nonpioneer EMF are inevitably reflected in infection efficiency. Indeed, spore inoculation is generally successful for pioneer EMF but not successful for nonpioneer fungi, as documented by many experiments using seedlings as well as practical applications in nurseries (Fig. 1). Dormancy and longevity of EMF spores The term dormancy is used often in seed science, but its definition is unclear and under debate (see Finch-Savage & Leubner-Metzger, 2006). In a strict sense, dormancy is defined as the incapacity of a viable seed to germinate during a certain period of time, even under favorable external conditions. Thus, seeds can germinate under the same conditions after the dormant period ends. If the same definition is applied to EMF spores, the existence of host roots can be regarded as a type of external condition that stimulates germination. By this definition, spores of most pioneer EMF may not undergo innate dormant states because fresh spores can readily germinate in the presence of host roots immediately following spore collection (Fig. 1). However, using seedling bioassays and serially diluted spores in soil, Bruns et al. found that the infectivity of Rhizopogon spores increased with time over 4 yr. They concluded that only a small proportion of spores (1–8% at maximum estimates) were initially receptive to host roots, and receptive spores increased year by year as a result of the release of spore dormancy. This conclusion apparently contradicts some previous studies that reported high germination rates (up to 69%) and high infectivity of fresh Rhizopogon spores (e.g. Theodorou & Bowen, 1987). Although the reason for this inconsistency is unknown, further research on Rhizopogon spores may be necessary to confirm the existence of dormancy sensu stricto, as observed in some wooddecomposing Crepidotus species inhabiting temperate areas (Aime & Miller, 2002). The longevity of EMF spores may be less controversial in definition, but this has been tested by only a few studies. Ishida et al. (2008) demonstrated a significant decrease in spore germination, after approx. 1 yr of preservation at 4°C, for many EMF species belonging to Laccaria, Inocybe, Scleroderma, Hebeloma and Russula, all of which are major EMF species in an early successional volcanic desert on Mt Fuji, Japan. Their seedling bioassays showed that the infectivity of these fungal spores also decreased after approx. 1 yr of preservation in soil under ambient conditions (Ishida et al., 2008). Furthermore, field-transplanted nonmycorrhizal seedlings remained nonmycorrhizal during the first growing season when mycorrhizal networks were unavailable, indicating that EMF spore banks are rare or absent in this desert (Nara & Hogetsu, 2004). Similarly, in mature pine forests in California, members of Russula, Lactarius, Amanita and Thelephorales tend to dominate EMF communities, but their viable spores were rarely detected in soil using seedling bioassays (e.g. Taylor & Bruns, 1999). Therefore, the spore longevity of most EMF


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basidiomycetes is likely to be short and insufficient to accumulate effective numbers of viable spores as soil spore banks. In contrast to these ephemeral EMF species, Rhizopogon spores remain viable for exceptionally long periods of time; Bruns et al. report viability periods of at least 4 yr and it is suspected that longer periods are possible. The high longevity of Rhizopogon spores would enable the accumulation of abundant numbers of viable spores in soil. Indeed, Rhizopogon species are dominant in soil spore banks in pine forests in western North America, even when Rhizopogon species are almost absent from existing tree roots and sporocarps (Taylor & Bruns, 1999). Soil spore banks enable quick colonization after disturbance in advance of other EMF species (Baar et al., 1999). It is unclear what has enabled the exceptional longevity of some Rhizopogon species. It may be interesting to compare Rhizopogon with its close relative Suillus; these genera are phylogenetically very close and exhibit host specificity to Pinaceae. Rhizopogon spores showed no decrease in infectivity when preserved for 1 yr, while the infectivity of Suillus spores decreased drastically over the same time period (Ashkannejhad & Horton, 2006). Although the mechanism of this difference in infectivity is uncertain, we know that these two EMF genera produce different types of sporocarp: Suillus produces epigeous sporocarps from which spores are dispersed mainly by wind, while Rhizopogon produces hypogeous sporocarps and largely depends on mycophagous animals for spore dispersal. Such differences in ecological traits, including niche preference, may have produced different spore longevity through evolution. Given the great morphological and physiological variations in seed germination/dormancy mechanisms (Finch-Savage & Leubner-Metzger, 2006), it is reasonable to propose that there are similar variations in EMF spores. The findings by Bruns et al. highlight such underlying diversity of EMF spore traits by providing solid evidence of exceptionally long spore viability of Rhizopogon. Although the 4-yr time-period of monitoring was insufficient to determine the exact longevity of Rhizopogon spores, the experimental design used by Bruns et al. potentially allows to extend the monitoring over 99 years. Thus, Rhizopogon spore longevity will be determined in follow-up studies, hopefully in my lifetime.

Acknowledgements This commentary was supported, in part, by the Japan Society for the Promotion of Science. I apologize that space limitations prohibit me from citing many other interesting references. Kazuhide Nara Asian Natural Environmental Science Center, The University of Tokyo, Midori-cho 1-1-8, Nishi-Tokyo, Tokyo 188-0002, Japan (tel +81-424-655601; fax +81-424-655616; email [email protected])


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References Aime MC, Miller OK. 2002. Delayed germination of basidiospores in temperate species of Crepidotus (fr) staude. Canadian Journal of Botany 80: 280–287. Ashkannejhad S, Horton TR. 2006. Ectomycorrhizal ecology under primary succession on coastal sand dunes: interactions involving Pinus contorta, suilloid fungi and deer. New Phytologist 169: 345–354. Baar J, Horton TR, Kretzer AM, Bruns TD. 1999. Mycorrhizal colonization of Pinus muricata from resistant propagules after a stand-replacing wildfire. New Phytologist 143: 409– 418. Bruns TD, Peay KG, Boynton PJ, Grubisha LC, Hynson NA, Nguyen NH, Rosenstock NP. 2009. Inoculum potential of Rhizopogon spores increases with time over the first 4 yr of a 99-yr spore burial experiment. New Phytologist 181: 463–470. Finch-Savage WE, Leubner-Metzger G. 2006. Seed dormancy and the control of germination. New Phytologist 171: 501–523. Fries N. 1987. Ecological and evolutionary aspects of spore germination in the higher basidiomycetes. Transactions of the British Mycological Society 88: 1–7. Guidot A, Debaud JC, Effosse A, Marmeisse R. 2004. Below-ground distribution and persistence of an ectomycorrhizal fungus. New Phytologist 161: 539–547. Holdsworth MJ, Bentsink L, Soppe WJJ. 2008. Molecular networks regulating Arabidopsis seed maturation, after-ripening, dormancy and germination. New Phytologist 179: 33– 54. Ishida TA, Nara K, Tanaka M, Kinoshita A, Hogetsu T. 2008. Germination and infectivity of ectomycorrhizal fungal spores in relation to their ecological traits during primary succession. New Phytologist 180: 491–500. Kikuchi K, Matsushita N, Suzuki K, Hogetsu T. 2007. Flavonoids induce germination of basidiospores of the ectomycorrhizal fungus Suillus bovinus. Mycorrhiza 17: 563– 570.

Nara K, Hogetsu T. 2004. Ectomycorrhizal fungi on established shrubs facilitate subsequent seedling establishment of successional plant species. Ecology 85: 1700–1707. Redecker D, Szaro TM, Bowman RJ, Bruns TD. 2001. Small genets of Lactarius xanthogalactus, Russula cremoricolor and Amanita francheti in late-stage ectomycorrhizal successions. Molecular Ecology 10: 1025–1034. Shen-Miller J, Mudgett MB, Schope JW, Clarke S, Berger R. 1995. Exceptional seed longevity and robust growth: ancient sacred lotus from China. American Journal of Botany 82: 1367–1380. Taylor DL, Bruns TD. 1999. Community structure of ectomycorrhizal fungi in a Pinus muricata forest: minimal overlap between the mature forest and resistant propagule communities. Molecular Ecology 8: 1837–1850. Theodorou C, Bowen GD. 1987. Germination of basidiospores of mycorrhizal fungi in the rhizosphere of Pinus radiata D. Don. New Phytologist 106: 217–223. Key words: basidiospores, dormancy, ectomycorrhizal fungi, host roots, infectivity, longevity, pioneer species, spore germination.

Supporting Information Additional supporting information may be found in the online version of this article. Table S1 Complete list of references for the data used in Fig. 1 Please note: Wiley-Blackwell are not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing material) should be directed to the New Phytologist Central Office. October 10.1111/j.1469-8137.2008.02659.x 2659 2 0 Letters Letters 245??? 43??? 2008 Letters

Letters Fungal proteins in the extraradical phase of arbuscular mycorrhiza: a shotgun proteomic picture The mycelial network that develops outside the roots in arbuscular mycorrhiza (AM) is considered as the most functionally diverse component of this symbiosis. Extra-radical mycelia (ERM) not only provide extensive pathways for nutrient fluxes through the soil, but also have strong influences upon biogeochemical cycling and agro-ecosystem functioning (Purin & Rillig, 2008). Despite the recognized importance of ERM in AM symbiosis ecology, the mechanisms by which fungal


networks extend and function remain poorly characterized at a large scale, with most of the studies performed so far being devoted to the analysis of fungal morphological features and nutrient metabolism (Fortin et al., 2002). The functioning of ERM presumably relies on the existence of a complex regulation of fungal gene expression with regard to nutrient sensing, production of specific enzymes and resource partitioning between host roots and microsymbionts (Leake et al., 2004). In this respect, proteomics is likely to be one of the best methodologies to decipher some key functions of mycelial networks. However, so far, only one study based on two-dimensional electrophoresis (2D-PAGE) has been conducted to monitor the fungal proteins that accumulate in the extra-radical phase of mycorrhiza (Dumas-Gaudot et al., 2004). Although large-scale protein-profiling experiments have been dominated by the use of 2D-PAGE because it features

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high protein separation capacity, this method was reported to under-represent proteins with extreme physicochemical properties (size, isoelectric point, transmembrane domains) and those of low abundance (Haynes & Roberts, 2007). Such limitations of 2D-PAGE for analytical protein profiling have led to the more recent development of shotgun proteomic approaches designed to optimize proteome coverage, including one-dimensional (1D)-PAGE-nanoscale capillary liquid chromatography-MS/MS, namely GeLC-MS/MS, which combines a size-based protein separation to an in-gel digestion of the resulting fractions. As part of our interest in identifying the AM fungal functions that are expressed in the ERM mycorrhiza, we have explored the efficiency of GeLC-MS/MS to identify proteins from the mycelium of Glomus intraradices developed on root organ cultures, and report on the identification of 92 different proteins.

Materials and Methods

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MS/MS data were analysed with Mascot (Matrix Science, London, UK) against the ‘Fungi’ subset of Swiss-Prot (release 54.4) and TrEMBL (release 37.4) databases. Trypsin was specified as the proteolytic enzyme and one miss cleavage was allowed. Fixed and variable modifications were carbamidomethylation of cysteine and oxidation of methionine, respectively. Mass tolerance was set at 150 ppm for peptide precursors and at 0.3 Da for fragment ions. Only matches with P < 0.05 for random occurrence were considered to be significant and a minimum of two unique peptides at disparate sites within a protein were required for a positive identification. When less than two proteins could be identified per gel slice, MS/MS spectra were interpreted de novo using Protein Lynx Global Server 2.0 (Micromass/Waters). The MS BLAST search was performed against the nrdb95 protein database following the procedure described by Shevchenko et al. (2001). Hits were considered statistically confident according to the MS BLAST scoring scheme (Habermann et al., 2004). Only proteins identified with at last two peptide sequences were validated.

Biological material Glomus intraradices (DAOM 181602) was grown at 27°C in the dark with carrot (Daucus carota) hairy roots on modified minimal nutrient medium (Bécard & Fortin, 1988) containing 10 g sucrose l–1 and 0.3% Phytagel. To recover root-free extraradical hyphae and spores, Petri dishes were incubated vertically after placing a mycorrhizal root organ plug in the upper side of the plate. Areas colonized by the ERM were collected after 12 wk, as previously described (Dumas-Gaudot et al., 2004). Two independent experiments were performed, each consisting of 50 root organ cultures. Protein extraction and separation Protein extraction was performed as previously described (Dumas-Gaudot et al., 2004), except that proteins were solubilized in Laemmli buffer (Laemmli et al., 1970) and boiled for 3 min at 95°C before ultracentrifugation. For each independent experiment, proteins (75 µg) were separated on a linear 12%, pH 8.8, SDS-PAGE gel (Valot et al., 2006), which was stained with Coomassie Brilliant Blue (Mathesius et al., 2001). In-gel trypsin digestion, LC-MS/MS and database searching The whole gel lane from one representative experiment was sliced into 40 bands of equal size. In-gel trypsin digestion of proteins and nano-LC-MS/MS analyses of the digests using a Switchos-Ultimate II capillary LC system (LC Packings/ Dionex, Amsterdam, the Netherlands) coupled to a hybrid quadrupole time-of flight mass spectrometer (Q-TOF Global, Micromass/Waters, Manchester, UK) were performed as described in Repetto et al. (2008).


Sequence analysis Identified proteins were functionally classified according to Ruepp et al. (2004) using Uniprot annotations at ExPASy (http://www.expasy.org/sprot/). Theoretical molecular weight (Mw) and isoelectric point (pI) were calculated using the Compute pI/Mw tool from ExPASy. Subcellular location of proteins was determined using Uniprot annotations or predicted by Wolf PSORT (http://wolfpsort.seq.cbrc.jp). Transmembrane (TM) domains were predicted using the TMpred server with a minimum score of 1000 (Valot et al., 2006). Proteins were classified as integral membrane proteins when predicted to have at least two TM regions or were annotated as an integral membrane protein in Swiss-Prot (Everberg et al., 2006). The MetaCyc database (Caspi & Karp, 2007) was used to retrieve biochemical pathways.

Results and Discussion Protein identification In this GeLC-MS/MS approach, the 40 LC-MS/MS runs first allowed the confident identification of 158 proteins (data not shown). This initial repertoire was manually curated to provide a minimal list of proteins sufficient to explain all observed peptides, resulting in a final record of 92 (54 distinct and 38 differentiable) proteins (Table 1), according to the nomenclature and principles of parsimony described in Nesvizhskii & Aebersold (2005). Most of proteins (86.9%) were identified when using the MASCOT search engine against Uniprot with taxonomies restricted to Fungi in order to minimize the generation of false-positive identifications and measurement time (Table 1). For seven datasets that led


249

Accessiona (reference organism)


Peptide sequencesb

Scoreb

Theoretical pI/Mwc

Putative cellular locationd

Glutamine synthase (fragment)

GGFPGPQGPYYCSVGANVAFGR GGDNILVLNECFNNDGTPNR HADHITVYGEDNDQR DVVEAHYR RPASNIDPYR IPVIGFDMGGTSTDVSR MGTTVATNALLER GGFPGPQGPYYCSVGANVAFGR IQAEYIWIDGDGGLR GGDNILVLAECYNNDGTPNR DVVEAHYR HAEHIAVYGEDNDKR RPASNIDPYR LGILGFSNTLALEGR LALVSFTETLAK VDIIINNAGILR LAAPVFPGETLETQMWK VAIVTGAGGGLGR VAVVAGYGDVGK VPAINVNDSVTK ESLVDGLKR SKFDNLYGCR LKVPAINVNDSVTK

128.32 79.39 77.92 56.26 39.12 109.79 88.52 128.32 84.41 62.35 56.26 41.41 39.12 106.82 94.2 83.07 67.02 44.26 78.8 68.17 54.75 51.43 44.33

5.68/39.12

cyto

5.72/138.62

cyto

5.65/39.13

cyto

8.88/108.89

cyto

5.58/39.12

cyto

KPFVLPVPAFNVINGGSHAGNK LGSEVYHTLK AALVFGQMNEPPGAR TIAMDGTEGLVR IGLFGGAGVGK VLSIGDGIAR EAYPGDVFYLHSR VGHEELVGEVIR TTLVANTSNMPVAAR VGINGFGR AGIAISKSFVK VIPGLMACGEAACVSVHGANR TVIATGGYGR

89.68 57.07 84.58 73.18 41.53 72.66 71.63 87.41 69.93 52.54 45.34 200.22 94.02

5.15/46.87

cyto

5.6/54.06

mito

9.18/58.58

mito

5.8/66.61

cyto (2)

7.01/36.05

cyto

6.95/69.38

mito

9.37/59.10

mito

5.16/54.06

mito

Q4WL95 (Aspergillus fumigatus)

Putative 5-oxo-L-prolinase

Q6UTX7 (Glomus mosseae)

Glutamine synthase

Q9UVH9 (Glomus mosseae)

Fox2 protein

Q753T3 (Ashbya gossypii)

Adenosylhomocysteinase

Energy O74286 (Cunninghamella elegans)

Enolase (fragment)

P22068 (Schizosaccharomyces pombe)

ATP synthase subunit beta, mitochondrial precursor


ATP synthase subunit alpha, mitochondrial precursor Vacuolar ATP synthase catalytic subunit A Glyceraldehyde 3-phosphate dehydrogenase (fragment) Succinate dehydrogenase ubiquinone flavoprotein subunit 2 mitochondrial precursor ATP synthase subunit alpha, mitochondrial precursor ATP synthase subunit beta, mitochondrial precursor

P31406 (Schizosaccharomyces pombe) P32638 (Schizophyllum commune) P47052 (Saccharomyces cerevisiae)

P49375 (Kluyveromyces lactis) P49376 (Kluyveromyces lactis)

TAVALDTILNQK VVDALGNPIDGK VALTGLTIAEYFR TIAMDGTEGLVR IGLFGGAGVGK

81.37 48.86 99.79 73.18 41.53

Letters

Metabolism Q4PNS5 (Glomus intraradices)

Identificationb

250 Forum


Table 1 GeLC-MS/MS-identified proteins in the extra-radical mycelium of Glomus intraradices of 3-month-old carrot (Daucus carota) root organ cultures


Table 1 continued

Identificationb

Peptide sequencesb

Scoreb

Theoretical pI/Mwc

P49382 (Kluyveromyces lactis)

ADP/ATP-carrier protein 6-phosphogluconic dehydrogenase 6-phosphogluconic dehydrogenase Glyceraldehyde 3-phosphate dehydrogenase (fragment) ATP synthase subunit beta

55.52 46.49 62.79 39.62 61.59 39.62 140.12 106.58 110.46 91.1 40.42 110.46 61.03 43.59 83* 73* 71.63 56.05 52.71 110.46 57.05 49.78 43.59 40.42 69.93 63.41 53.01 43.77 62.89 62.46 55.19 50.41 40.64 75.17 55.19 50.41 105.99 65.24

9.74/33.09

P53319 (Saccharomyces cerevisiae)

LLIQNQDEMIK YFPTQALNFAFK LPANLLQAQR DYFGAHTFR IISYAQGFMLMR DYFGAHTFR VINDKFGIIEGLMTTVHSTTATQK FGIIEGLMTTVHSTTATQK FTQAGSEVSALLGR AHGGYSVFCGVGER IGLFGGAGVGK FTQAGSEVSALLGR IINVIGEPIDERGPIK DEEGQDVLLFIDNIFR DVLHSFAVPSLGLK* LLDEVLDPVLTVK* EAYPGDVFYLHSR SVHEPMQTGLK EVAAFAQFGSDLDASTR FTQAGSEVSALLGR TVLIQELINNIAK IPSAVGYQPTLSTDMGGMQER DEEGQDVLLFIDNIFR IGLFGGAGVGK TTLVANTSNMPVAAR VLDALFPCVQGGTTAIPGAFGCGK FCDELGHR VQVHPTGLVDPK VNQIGSLSESIK SGETEDTFIADLVVGLR HYFIEINPR DAHQSLLATR ITTEDPAKNFQPDTGK SEALASFGDGTVFIER HYFIEINPR DAHQSLLATR LPANEAMTLLGGPIALLK AQSTQTFEYCAR

P78812 (Schizosaccharomyces pombe) Q09HW5 (Lactarius rufus) Q0CFC5 (Aspergillus terreus)

Q0ZIE6 (Kluyveromyces marxianus)

ATP synthase subunit beta (fragment)

Q5EM39 (Mortierella verticillata) Q5KFB9 (Cryptococcus neoformans)

Cytochrome c oxidase* subunit 2 ATP synthase subunit alpha

Q5KFU0 (Cryptococcus neoformans)

ATP synthase subunit beta

Q5KGV5 (Cryptococcus neoformans) Q7SHN7 (Neurospora crassa)

Putative vacuolar ATP synthase catalytic subunit A Probable fumarate reductase

Q70CP7 (Kluyveromyces lactis)

Enolase

Q8X1T3 (Pichia angusta)

Pyruvate carboxylase

Q9UUE1 (Schizosaccharomyces pombe)

Pyruvate carboxylase

Q96VP9 (Glomus intraradices)

Probable acyl-CoA dehydrogenase Histone H2B.2

KETYSSYIYK LILPGELAK

68.64 44.1

6.84/53.92

mito (3) integral to membrane cyto

6.73/53.67

cyto

9.28/20.39

cyto

5.44/53.68

mito integral to membrane

5.00/36.18


4.47/28.51

mito (4) integral to membrane mito

9.1/58.04

6.00/58.56


5.24/68.33

cyto

6.59/66.84

mito (2)

5.33/46.51

cyto

5.95/129.81

cyto

6.64/130.86

cyto

6.93/57.67

cyto (2)

10.07/14.23

nucleus

Forum

Cell cycle and DNA processing P02294 (Saccharomyces cerevisiae)


Letters



251

85 79.5

4.82/91.99

nucleus

AMSILNSFVNDIFER KETYSSYIYK IISSIEQKEESR DSTLIMQLLR ISGLIYEETR DNIQGITKPAIR TVTSLDVVYALKR VFLENVIR SVVAQFNASQLITQR DLQMVNITCR YALGVSNPSALR VVSQLLTLMDGMK

62.47 49.65 88.74 53.49 89.3 77.44 69.21 47.87 104 54.67 80.88 79.5

10.12/14.84

nucleus

4.78/30.36

nucleus

11.36/11.40

nucleus

9.65/37.10

cyto (2)

5.09/90.21

nucleus

TLLEAIDSIEPPSRPTDKPLR IGGIGTVPVGR EHALLAYTLGVK LPLQDVYK AYLPVNESFGFTADLR GTVAFGSGLHGWAFTVR IKPVVIINKVDR GTVAFGSGLHGWAFTVR TIESVNVIISTYFDK ASITPGTVLIILAGR* VNQAYVIATSTK* ADGVHIINLGK RADGVHIINLGK TSFFQALGVPTK AGALAPLDVFVPAGNTGMEPGK HIDFALTSPYGGGRPGR LFEGNALIR KILQLLR QANNFLWPFK KQANNFLWPFK* NNLLETSAGK* KYDAFLASESLIK* VLCLAVAVGHVK* MFVLDEADEMLSR GHDVIAQAQSGTGK IVDNETLGYFLAR EYTPNVIEPSFGIGR

78.86 66.95 65.24 46.54 99.3 83.69 67.16 83.69 83.34 101* 87* 58.41 56.02 89.41 45.06 61.98 42.6 54.63 40.92 76* 35* 91* 89* 63.35 56.96 101.06 52.56

8.54/45.20

cyto

6.24/93.09

cyto

6.48/92.27

cyto

10.22/26.00

mito

5.23/32.80

cyto

4.94/34.06

cyto (2)

9.95/26.67

cyto

10.00/28.71

nucleus

10.78/25.87

nucleus

9.94/24.62

nucleus

5.9/47.96

nucleus

5.65/74.17

cyto

Peptide sequencesb


Cell division control protein

NVFVIGATNRPDQIDPAILRPGR VVSQLLTLMDGMK

P37210 (Neurospora crassa)

Cdc48 Histone H2B

P42657 (Schizosaccharomyces pombe) Q9HDF5 (Mortierella alpina)

DNA damage checkpoint protein rad25 Histone H4

Q561J1 (Cryptococcus neoformans)

Putative prohibitin

Q876M7 (Aspergillus fumigatus)

Cell division control protein Cdc48 Elongation factor 1-alpha (fragment)

A3LNB1 (Pichia stipitis)

Elongation factor

A4RJR6 (Magnaporthe grisea)

Putative elongation factor

P34091 (Mesembryanthemum crystallinum)

60S ribosomal protein L6*

Q01661 (Pneumocystis carinii)

40S ribosomal protein S0

Q0TZB5 (Phaeosphaeria nodorum)

60S acidic ribosomal protein P0

Q4WWT2 (Aspergillus fumigatus)

40S ribosomal protein S9

Q5AX73 (Emericella nidulans)

Putative ribosomal protein

Q6EE80 (Protopterus dolloi)

Ribosomal protein L7* (fragment) 60S ribosomal protein L10a*

Q6PC69 (Danio rerio) Q7RV88 (Neurospora crassa) Q7RYQ5 (Neurospora crassa)

Translation initiation factor 1 Glycyl-tRNA synthetase 1

Scoreb

Letters


Identificationb

Protein synthesis A0AAR3 (Geosiphon pyriformis)


Theoretical pI/Mwc


252 Forum


Table 1 continued


Table 1 continued

Peptide sequencesb

Q7SDY7 (Neurospora crassa)

Putative 40S ribosomal protein S9

LFEGNALIR MKLDYVLALK

Putative T-complex protein 1, epsilon subunit

IAVDAVLSVADLER WVGGPEIELIAIATNGR SLHDAICVVR ELISNASDALDKIR APFDLFETK IEEVDEEEEKK RAPFDLFETK ITPSYVAFTDDER IVNEPTAAAIAYGLDK HITIFSPEGR LYQVEYAFK IKNFMIQGGDFT* FADENFTLK* ELISNASDALDKIR SLTNDWEDHLAVK ESTLHLVLR TLSDYNIQK IQDKEGIPPDQQR TNEMAGDGTTTATILTR TIVDNAGEEGAVIVGK ATPDLFGSTGSVTITK VGGSSELEVGEK TALVDASGVASLLTTTECMITEAPEENK TLSNDWEDHLAVK RAPFDLFETK AVAEAMEVIPR ILQIEEEQIK LDGVTNALDNVDAR EFLVGAGAIGCEMLK KPLLESGTLGTK NFPNAIEHTIQWAR QLYVLGHDAMK SLLEVVQTGAK LTVEDPVTVDYITR SQIFSTAADNQPTVLIQVYEGER VEIIANDQGNR EVGDGTTSVVLIAAELLR GYALNCTVASQAMK AIANECQANFISIK VLNQILTEMDGMNAK

Protein fate A1CT43 (Aspergillus clavatus)

A1C4S0 (Aspergillus clavatus)

Chaperone Mod-E/Hsp90



78 kDa glucose-regulated protein homologue precursor Proteasome component C7-alpha Peptidyl-prolyl cis-trans* isomerase, precursor Heat shock protein 90 homologue

P61862 (Candida albicans)

Ubiquitin

Q0H0L1 (Glomus intraradices)

Heat shock protein 60 (glomalin)

Q1DY84 (Coccidioides immitis)

Heat shock protein hsp1

Q1E1V6 (Coccidioides immitis)

T-complex protein 1

Q1EAX1 (Coccidioides immitis)

Ubiquitin-activating enzyme E1

Q4P125 (Ustilago maydis)

Putative ubiquitin-activating enzyme E1 Putative ubiquitin-dependent proteinase Putative Hsp70 BiP/Kar2

P21243 (Saccharomyces cerevisiae) P34791 (Arabidopsis thaliana)


Q4P356 (Ustilago maydis) Q4WHP9 (Aspergillus fumigatus) Q4WZR6 (Aspergillus fumigatus) Q5KA71 (Cryptococcus neoformans)

Putative T-complex protein 1, alpha subunit Putative endoprotease MMS2

Theoretical pI/Mwc


50.91 49.75

10.41/21.80

mito

114.36 58.22 49.91 144.17 71.34 51.86 47.66 96.56 77.81 65.48 51.47 89* 59* 65.51 53.88 66.37 59.12 50.51 107 100.86 91.52 88.83 52.51 47.17 39.56 56.84 47.89 130.066 94.03 86.83 87.7 53.15 54.51 39.36 84.69 74.75 56.99 44.12 88.32 59.44

5.43/59.05

cyto

4.91/80.18

nucleus

4.79/74.47

ER (2)

5.89/28.00

cyto

8.83/28.20

mito

4.89/80.59

cyto

6.56/8.35

cyto-nucleus

6.07/63.01

cyto

4.95/80.09

cyto

6.04/58.89

cyto

5.20/11.48

cyto (4)

5.18/11.33

cyto (2)

5.78/25.15

cyto

4.91/73.38

ER (2)

6.42/61.72

cyto

4.9/89.45

cyto

Scoreb

Forum

Identificationb

Letters


253

254 Forum


Identificationb

Peptide sequencesb

Scoreb

Theoretical pI/Mwc


Q6C342 (Yarrowia lipolytica)

6.07/50.96

cyto

Heat shock protein 80

82.55 60.99 57* 40* 34* 29* 114.44 43.67

mito

Q9P8T6 (Neurospora crassa)

TIEDELEITEGMR NVAAGCNPMDLR GVTFDSGGISIK* TAALFLK* DYLQC* SDVAD* ELISNASDALDKIR ADLVNNLGTIAR

5.3/60.55

Q8RLK 7 (Mycoplasma gallinarum)

Yarrowia lipolytica chromosome F chaperone Hsp60 Aminopeptidase*

5.12/78.91

nucleus

LVLVGDGGTGK NLQYYDISAK LQIWDTAGQER FADDTYTESYISTIGVDFK ILFLGLDNAGK FTTYDLGGHQQAR FQSLGVAFYR DPENFPFVVIGNK KDDEYDYLFK* NVENAF* VIILGDSGVGK GNIPYFETSAK TSLMNQYVNKK

63.81 45.13 65.9 64.06 52.2 48.7 53.15 43.7 80* 34* 142.343 94.634 40.812

6.22/24.9

nucleus

5.47/22.47

cyto

5.53/21.41

ER

4.91/22.92

cyto

5.70/24.37

cyto-nucleus

4.88/23.12

cyto

IVSSIEQKEESK DSTLIMQLLR QAFDDAIAELDTLSEESYK HLTDYFTFK VYDACMESFCALPLAAIMNK YLFLGDYVDR DNLTLWTSDLQDAEGEKPEEAK HATDIAQTDLAPTHPIR DSTLIMQLLR QAFDDAIAELDTLSEESYK KLVIVGDGACGK TGEGVREVFEHATR FSPNPSNPVLVS* VDDLKPEFTETGK* YSLEAGD*

65.84 61.4 48.63 67.4 56.55 51.83 164 81.8 61.4 48.63 65.85 64.41 75* 63* 36*

4.76/2928

nucleus

5.41/61.46

cyto

4.92/29.61

nucleus

5.58/21.69

cyto

6.36/35.06

nucleus

Protein transport P32836 (Saccharomyces cerevisiae) P33723 (Neurospora crassa) Q4P0I7 (Ustilago maydis) Q5GJ06 (Aspergillus parasiticus) Q6XP51 (Limulus polyphemus) Q9C2L8 (Neurospora crassa)

Signal transduction P34730 (Saccharomyces cerevisiae)


Q1DSP6 (Coccidioides immitis)

GTP-binding nuclear protein GSP2/CNR2 GTP-binding protein ypt1 Small COPII coat GTPase SAR1 Rab GTPase vacuolar biogenesis protein Rab11-1b* Probable Ras-related protein Rab7

Bmh2 14-3-3 protein

Q2PBB6 (Glomus intraradices)

Calcineurin A (serine/threonine protein phosphatase 2B catalytic subunit) 14-3-3 protein

Q8TG28 (Mucor rouxii)

Rho1 GTP-binding protein

Q9HGV7 (Emericella nidulans)

Cross-pathway control WD-* repeat protein Cpc-2 Gbeta-like protein

Letters


Table 1 continued

Table 1 continued No claim to original French government works. Journal compilation © New Phytologist (2008)

Identificationb

Peptide sequencesb

Scoreb

Theoretical pI/Mwc


Cell rescue and defense A3GGW0 (Pichia stipitis)

Heat shock protein 70

cyto

Thioredoxin-1*

4.67/11.80

cyto

Q8CPZ0 (Staphylococcus epidermidis)

Excinuclease ABC subunit B*

5.11/76.16

nucleus

Q8J1Y0 (Rhizopus stolonifer)

70 kDa Hsp 2

5.01/70.44

cyto

Q8QHI0 (Oncorhynchus mykiss)

Cu-Zn superoxide dismutase*

5.67/15.75

cyto

Q87UI0 (Pseudomonas syringae)

Thioredoxin peroxidase* (antioxidant, AhpC/Tsa)

116.17 95.37 92.29 78.78 74.75 63.75 123* 87* 80* 34* 94.59 87.99 78.35 69.85 67.45 60.17 55.69 69* 39* 28* 65* 64* 37*

5.12/70.71

P0AA27 (Escherichia coli)

ATAGDTHLGGEDFDNR IINEPTAAAIAYGLDKK IDKSQVHEIVLVGGSTR TTPSYVAFTDTER VEIIANDQGNR SQVHEIVLVGGSTR MIAPILDEIADEYQGK* LNIDQNPGTAPK* TIENIEKEMK* LLESQR* ATAGDTHLGGEDFDNR IINEPTAAAIAYGLDK TTPSYVAFTDTER ARFEELNQDLFR NGLESYAYNLR NQVAMNPHNTVFDAK VEIIANDQGNR HVGDLGDVTAG* GLAPGE* QESENGP* LTYPASTGRD* LMLTYPASTGR* PVDTHL*

5.54/23.74

cyto

SYELPDGQVITIGNER QEYDESGPSIVHR DSYVGDEAQSKR GHYTEGAELVDSVLDVVR AVLVDLEPGTMDSVR FPGQLNADLR ALTVPELTQQMFDAK LAVNMVPFPR AGFAGDDAPR YPIEHGIVTNWDDMEK AVFPSIVGRPR DSYVGDEAQSKR HQGVMVGMGQK EITALAPSSMK QLFHPEQLITGKEDAANNYAR IHFPLVTYAPVISAEK LIAQVVSSITASLR TVFVDLEPTVVDEVR TIQFVDWCPTGFK YMACCLLYR

107.68 94.29 46.52 102.69 78.43 71.24 68.54 65.21 91.24 87.05 65.8 61.5 55.78 39.95 79.19 55.68 85.55 84.29 53.81 49.15

5.84/43.89

cysk (2)

5.76/43.12

cysk

5.37/41.76

cysk (2)

5.96/42.63

cysk (2)

6.07/42.69

cysk (2)

Actin Act1

Q9P8Y7 (Harpochytrium sp. JEL94)

Beta-tubulin 1 (fragment)

Q58YD9 (Blakeslea trispora)

Gamma-actin

Q86ZY8 (Nowakowskiella elegans)

Alpha-tubulin (fragment)

Q86ZZ3 (Gaertneriomyces semiglobiferus)

Alpha-tubulin (fragment)

Forum

Cytoskeleton Q4WDH2 (Aspergillus fumigatus)

Letters



255

256 Forum Letters


Table 1 continued


Identificationb

Peptide sequencesb

Scoreb

Theoretical pI/Mwc


Unclassified proteins Q8NJ38 (Glomus intraradices)

Binding protein (fragment)

cyto

Hsp70 protein 1

4.99/71.05

cyto

Q754F6 (Ashbya gossypii)

AFR114Wp Hsp70

124.86 77.81 68.7 61.64 94.59 88.01 70.15 69.85 67.45 55.69 94.59 79.74 48.4

5.89/24.93

Q9UVM1 (Rhizopus stolonifer)

IEIESFHDGKDFSETLTR IVNEPTAAAIAYGLDK DAGVIAGLNVLR DVHDIVLVGGSTR ATAGDTHLGGEDFDNR IINEPTAAAIAYGLDKK NAVITVPAYFNDSQR ARFEELNQDLFR NGLESYAYNLR VEIIANDQGNR ATAGDTHLGGEDFDNR SQVHEIVLVGGSTR LVNHFVQEFK

5.00/69.54

cyto

a

Accessions refer to Uniprot entries. Unless otherwise specified by an asterisk, identifications, peptide sequences and scores refer to the use of the probability-based MASCOT search engine against Swiss-Prot and TrEMBL databases with taxonomies restricted to Fungi. Asterisks refer to de novo interpretation of MS/MS spectra and protein identification using the MS BLAST scoring scheme. c Theoretical Mw and pI were determined using the Compute pI/Mr tool from ExPASy. d Subcellular location of proteins was determined using Uniprot annotations or predicted by Wolf PSORT (cyto, cytoplasm; cysk, cytoskeleton; ER, endoplasmic reticulum; mito, mitochondrion). Numbers into brackets refer to proteins predicted to display two or more transmembrane domains when using the TMpred server. Proteins designated as integral membrane proteins refer to Swiss-Prot annotations. b


Letters

to very little conclusive MASCOT identification, spectra were further interpreted de novo. Despite high-quality spectra (data not shown), only 12 additional proteins (Table 1) could be further identified using the MS-BLAST algorithm, probably by reason of significant amino acid variation between AM fungal proteins and their orthologues in other species. Of the 92 proteins identified in the ERM of G. intraradices, only five were inferred from peptides belonging to proteins from this species (Table 1). At the time of data analysis, there were no more than 75 entries for G. intraradices proteins in Uniprot, meaning that the current work, with the identification of 87 additional proteins, represents a significant quantitative breakthrough in the characterization of the AM fungal proteome. As a benchmark for shotgun proteomics of plantcolonizing fungi lacking full genome characterization, the two-dimensional LC-MS/MS analysis performed on fungal uredospores from the obligate pathogen Uromyces appendiculatus led to the identification of 486 proteins (Cooper et al., 2006). Among them, 56 distinct and differentiable proteins were identified with at least two peptides, which is in a range similar to the 92 proteins retrieved in the current work with similar criteria. Compared with the four extra-radical and six in planta-detected proteins of G. intraradices that were previously identified using 2D-PAGE analyses, these GeLCMS/MS data represent the most comprehensive list of AM fungal proteins so far identified (Dumas-Gaudot et al., 2004; Valot et al., 2005). Additionally, only 75 µg of proteins were used as starting material instead of the 300–600 µg amount required for micro-preparative 2D-PAGE gels. Protein characterization GeLC-MS/MS was reported to sample, in a relatively unbiased manner, proteins with extreme properties. In this work, 15 proteins with pI greater than 9, and 13 proteins with theoretical Mw less than 10 and greater than 80 kDa could be retrieved (Table 1), which are beyond the reported 2D-PAGE separation limits for G. intraradices (Dumas-Gaudot et al., 2004). When analysing the ERM proteins for subcellular location, half of them were localized to the cytoplasm, and nucleus and mitochondrion were the two other cellular components most commonly retrieved (Supporting information, Fig. S1). Regarding the presence of putative integral membrane proteins, 15 proteins were predicted to have at least two TM domains, and three additional proteins (ATP synthase β subunits) lacking putative TM domains were also retrieved as annotated as integral membranes in Swiss-Prot (Table 1). Proteins containing at least two membranespanning hydrophobic sequences are estimated to represent c. 18–27% of all proteins in organisms with sequenced genomes (Ward, 2001). In the current work, 19.5% of the identifications were assigned to poorly soluble integral membrane proteins, which is noteworthy in the absence of any specific enrichment for this class of proteins. Of the 92 proteins identified in this


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study, functional roles for 89 proteins were known or could be predicted from database analysis (Table 1). The FunCat annotation scheme assigned them to nine biological processes, in which energy, protein fate and synthesis were the most prominent retrieved categories (Fig. S2). Functional significance of the identified proteins To obtain an overview of the metabolism of root organ culture-developed ERM, proteins were analysed with the MetaCyc database, which retrieved 11 pathways that span energy, metabolism and cell rescue processes as schematically represented in Fig. 1. Consistent with the use of neutral lipids as the main respiratory substrate in ERM (Requena et al., 1999; Bago et al., 2002), there were enzymes involved in the catabolism of long-chain fatty acids, their subsequent βoxidation, and energy generation through the TCA cycle coupled to electron transport and oxidative phosphorylation. Additionally, GeLC-MS/MS data pointed to enzymes involved in dark CO2 fixation, glycolysis/gluconeogenesis, pentose phosphate and glutamine biosynthesis-related pathways, the existence of which in AM fungi have so far been inferred from enzymatic, isotopic labelling and/or gene expression studies (Saito, 1995; Pfeffer et al., 1999; Tamasloukht et al., 2003; Breuninger et al., 2004). Of the proteins related to cell redox homeostasis, trans-sulphuration pathway and γ-glutamyl cycle, accumulation in the ERM of AM fungi of the corresponding transcripts has only been reported previously for a superoxide dismutase and an adenosylhomocysteinase (Jun et al., 2002; Lanfranco et al., 2005). Similar to other fungi previously classified within the traditional Zygomycota that is no longer considered as a phylum (White et al., 2006), polar growth of extra-radical AM hyphae requires the delivery at the growing apex of secretory vesicles involved in wall and plasma membrane increase (Wessels, 1993). In this study, we identified several proteins related to vesicular trafficking, including the GTP-binding protein Ypt1, the small GTPase SAR1, and three members of the Rab GTPase subfamily (Table 1). Furthermore, signal-transducing proteins calcineurin, Rho1, Cpc2 and Bmh2, for which a role has been demonstrated in fungal morphogenesis (Won et al., 2001; Steinbach et al., 2006; Argimón et al., 2007; Zannis-Hadjopoulos et al., 2008), also accumulated in the ERM of G. intraradices. Bmh proteins are additionally involved in cell cycle regulation as being necessary for the initiation of DNA replication and are positive regulators of rapamycin-sensitive signalling via the TOR kinase pathway, whose expression was previously reported in G. mosseae (Requena et al., 2000). Among proteins playing roles in the cell division cycle, the DNA damage checkpoint protein rad25, two isoforms of the AAA ATPase Cdc48, and a putative prohibitin were concomitantly identified in the ERM of G. intraradices. Currently, the mechanisms underlying AM fungus cell cycle mostly refer to the moving from G0/G1 to S/M during infection and DNA


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Fig. 1 Schematic overview of energy, metabolism, and cell rescue pathways retrieved in the extra-radical mycelia (ERM) of Glomus intraradices on the basis of the proteins identified in the current study. Pathways are shown in bold capital letters. Proteins identified in this study are indicated in green and numbered according to the corresponding pathway. Inferred metabolic intermediates are shown in nonbold letters. FA, fatty acid; TCA, tricarboxylic acid cycle; I, II, III, IV, V, complexes I, II, III, IV, V of the electron transport chain, respectively; UQ, ubiquinone; UQH2, ubiquinol; GAPDH, glyceraldehyde 3-phosphate dehydrogenase; GS, glutamine synthase; PPP, pentose phosphate pathway; 6PGD, 6-phosphogluconic dehydrogenase; SOD, superoxide dismutase; TrxS2, thioredoxin disulfide; TRx(SH)2, reduced thioredoxin; TrxPx, thioredoxin peroxidase; GSH, reduced glutathione; GSSG, glutathione disulphide; TrxR, thioredoxin reductase; GR, glutathione reductase; GPX, glutathione peroxidase.

replication occurring during the production of germinating mycelium (Bianciotto & Bonfante, 1993; Bianciotto et al., 1995). GeLC-MS/MS data, together with previous identifications of putative homologues of cell-cycle gene in G. mosseae and G. intraradices (Requena et al., 2000; Jun et al., 2002), suggest that signalling pathways known in model species may also operate in AM fungi. Overall, this GeLC-MS/MS strategy opens the way towards analysing at large-scale fungal responses to environmental cues on the basis of quantitative shotgun proteinprofiling experiments.

Acknowledgements The authors are grateful to Audrey Geairon and Franck Robert for extensive technical assistance and to Benoît Schoefs, Benoît Valot and Natalia Requena for critical reading and helpful suggestions.


Ghislaine Recorbet1*, Hélène Rogniaux2, Vivienne Gianinazzi-Pearson1 and Eliane DumasGaudot1 1

Unité Mixte de Recherche Plante-Microbe-Environnement INRA 1088/CNRS 5184/Université de Bourgogne. INRA-CMSE. BP 86510. 21065 Dijon Cedex, France; 2 Unité de Recherche 1268 BiopolymèresInteractions-Assemblages, Spectrométrie de Masse, INRA, rue de la Géraudière. BP 71627, 44316 Nantes Cedex 3, France (*Author for correspondence: tel +33 (3) 80 69 34 27; fax +33 (3) 80 69 37 53; email [email protected])

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Supporting Information Additional supporting information may be found in the online version of this article. Fig. S1 Subcellular location of the proteins identified in the ERM of Glomus intraradices following GeLC-MS/MS, as determined using Swiss-Prot/TrEMBL annotations or Wolf PSORT predictions.

Fig. S2 Biological process grouping of the proteins identified in the ERM of Glomus intraradices following GeLC-MS/MS according to the MIPS Functional Catalogue Database. Please note: Wiley-Blackwell are not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing material) should be directed to the New Phytologist Central Office.

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