- Email: [email protected]
Plant Pathogen Effectors: Getting Mixed Messages
Current Biology Vol 18 No 3 R128
7. Worm, B., Barbier, E.B., Beaumont, N., Duffy, J.E., Folke, C., Halpern, B.S., Jackson, J.B.C., Lotze, H.K., Micheli, F., Palumbi, S.R., et al. (2006). Impacts of biodiversity loss on ocean ecosystem services. Science 314, 787–790. 8. Danovaro, R., Gambi, C., Dell’Anno, A., Corinaldesi, C., Fraschetti, S., Vanreusel, A., Vincx, M., and Gooday, A.J. (2008). Exponential decline of deep-sea ecosystem functioning linked to benthic biodiversity loss. Curr. Biol. 18, 1–8. 9. Loreau, M. (1998). Biodiversity and ecosystem functioning: a mechanistic model. Proc. Natl. Acad. Sci. USA 95, 5632–5636. 10. Vila, M., Vayreda, J., Comas, L., Ibanez, J., Mata, T., and Obon, B. (2007). Species richness and wood production: a positive association in Mediterranean forests. Ecol. Lett. 10, 241–250.
11. Grace, J.B., Anderson, T.M., Smith, M.D., Seabloom, E., Andelman, S.J., Meche, G., Weiher, E., Allain, L.K., Jutila, H., Sankaran, M., et al. (2007). Does species diversity limit productivity in natural grassland communities? Ecol. Lett. 10, 680–689. 12. Loreau, M., and Hector, A. (2001). Partitioning selection and complementarity in biodiversity experiments. Nature 412, 72–76. 13. Cardinale, B.J., Wright, J.P., Cadotte, M.W., Carroll, I.T., Hector, A., Srivastava, D.S., Loreau, M., and Weis, J.J. (2007). Impacts of plant diversity on biomass production increase through time because of species complementarity. Proc. Natl. Acad. Sci. USA 104, 18123–18128. 14. Gross, K., and Cardinale, B.J. (2005). The functional consequences of random vs. ordered species extinctions. Ecol. Lett. 8, 409–418.
Plant Pathogen Effectors: Getting Mixed Messages Plant pathogen effectors have now been shown to mimic plant transcription factors and turn on genes that help the pathogen. Some plants, however, have evolved to use these pathogen-derived transcription factors to turn on defence. David L. Greenshields and Jonathan D.G. Jones The ability to live and reproduce within a plant has evolved independently several times in pathogens from different kingdoms of life. The apparent widespread success of this lifestyle suggests that it provides a comfortable living for organisms that have the right skill set. Although plants appear to be sessile nutrient reserves ripe for the plundering, inside plant cells it is a different story: pathogens that attempt entry can be simultaneously encased in fortified barriers, subjected to potent oxidizers and toxic small molecules and even thwarted by the suicide of the targeted host cell. Thus, the road to the good life within a plant requires a lot of disguise and deception, and only the most cunning can enjoy what the plant has to offer. In response to pathogens, plants have evolved sophisticated recognition capabilities that sense conserved molecules expressed by fungal, bacterial and oomycete pathogens. The bacterial flagellum protein flagellin is the best characterized of these pathogen signatures [1]. To evade plant recognition and encourage a suitable environment for growth and reproduction, pathogens secrete a range of protein effectors into plant cells that can block the recognition of these molecules and manipulate
host machinery for the pathogen’s benefit. In turn, plants have evolved surveillance systems to recognize the effectors themselves, thereby triggering another layer of the plant immune response [2]. To enable pathogen survival and growth within the host, effectors must turn on pathways to promote pathogen nutrition and turn off pathways leading to defence activation. Therefore, plants must be able to recognize these attempts at manipulation and mount a defence response. Two recent papers [3,4] describe an interesting twist on pathogen effectors and their recognition. They show that the bacterial spot-causing pathogen Xanthomonas campestris pv. vesicatoria (Xcv) secretes AvrBs3, a transcription factor effector that induces the plant cell-size regulator upa20 in susceptible plants and the resistance gene Bs3 in resistant plants. While activation of upa20 leads to cell hypertrophy, which supports the infecting bacteria [4], activation of Bs3 triggers a defence response leading to plant cell death [3]. These two different transcription factor activities account for the phenotypes seen in resistant and susceptible plants. Bacterial pathogens of both plants and animals have evolved a syringe-like organelle called the type III secretion system that delivers effector proteins directly into
15. Callaway, R.M. (2007). Positive Interactions and Interdependence in Plant Communities (Dordrecht: Springer). 16. Lohrer, A.M., Thrush, S.F., and Gibbs, M.M. (2004). Bioturbators enhance ecosystem function through complex biogeochemical interactions. Nature 431, 1092–1095.
Department of Biology, McGill University, 1205 Avenue Docteur Penfield, Montreal, Quebec H3A 1B1, Canada. E-mail: [email protected]
DOI: 10.1016/j.cub.2007.11.060
eukaryotic cells [5]. AvrBs3 is the signature member of a family of conserved proteins in Xanthomonas that is injected into host cells through type III secretion and is characterized by a nuclear localization signal [6], a transcriptional activation domain [7], and a central repeat domain that determines resistance and susceptible responses in different plant genotypes [8]. To isolate direct targets of AvrBs3, Kay et al. [4] screened cDNAs from infected pepper plants impaired in protein synthesis, and this led to the identification of Upa20, a basic helix–loop–helix transcription factor related to the Arabidopsis petal-size regulator BIGPETAL. Silencing of upa20 reduced cell hypertrophy in infected plants and expression of upa20 led to hypertrophy in uninfected plants [4]. Mutation of the upa20 promoter identified a so-called upa box that is the direct target of AvrBs3 [4]. Interestingly, there is also a upa box in the promoter of the pepper Bs3 resistance gene, which recognizes Xcv isolates carrying AvrBs3 [3]. Ro¨mer et al. [3] show that AvrBs3 activates the transcription of its cognate resistance gene Bs3, thereby triggering a defensive localized plant cell death (Figure 1). Another AvrBs3-like protein, AvrXa27 from X. oryzae pv. oryzae, also activates transcription of its associated rice resistance gene Xa27 [9], suggesting a common mode of action for this protein family. How does Upa20 promote hypertrophy and what benefit does host cellular hypertrophy provide the pathogen? Upa20 induces expression of upa7, which encodes a putative a-expansin [4]. Interestingly, expansin gene induction is also seen in the enlarged root cells that harbour plant
Dispatch R129
pathogens. By mimicking a host transcription factor, pathogens have found a direct route for getting what they want from the plant. Plants, on the other hand, have adapted to give the pathogen more than they bargained for. The ability to launch a defence response with a pathogen’s transcription factor effector has evolved in distantly related plants [3,9]. With the rapid expansion in available pathogen genomes and the falling prices of genome sequencing, we should now be able to catalogue similar effectors from diverse pathogens by analysis of nuclear localization signals and transcriptional activation domains. Indeed, efforts are underway to describe the entire ‘effectoromes’ of filamentous plant pathogens [14]. It will be interesting to see how widespread this mode of effector action is in distantly related plant pathogens.
T3SS
Susceptible
upa20
Upa20
AvrBs3 upa
Upa7 + ?
Resistant
Bs3
AvrBs3 upa ?
Bs3 ?
Hypertrophy
Cell death References Current Biology
Figure 1. The transcription factor activity of AvrBs3 elicits different responses in resistant and susceptible plants. AvrBs3 is delivered into host cells via the Xanthomonas type III secretion system (T3SS). In susceptible pepper plants (left, green background), AvrBs3 binds the upa box and activates transcription of upa20, which encodes a basic helix–loop–helix transcription factor. Upa20 then activates transcription of genes like upa7, which together give rise to cellular hypertrophy. In resistant pepper plants (right, yellow background) AvrBs3 binds the Bs3 upa box and activates Bs3 transcription. Bs3 initiates a cell death response either through recognition by a guard protein or by modification of an unidentified interacting protein.
pathogenic nematodes [10]. However, because Upa20 expression is sufficient for the hypertrophy symptoms seen in susceptible pepper plants, it is likely inducing other genes in addition to upa7. Although AvrBs3 is important in causing disease symptoms and plays a role in disease transmission, it seems to have very little effect on bacterial growth in planta [11]. Finding new targets of Upa20 and discovering how host cellular hypertrophy allows for higher bacterial transmission rates will help to explain the unusual mode of action of AvrBs3. How does Bs3 expression trigger cell death? Bs3 is not a classical resistance gene of the nucleotide-binding leucine-rich-repeat variety. Instead, Bs3 encodes a flavin monooxygenase with similarity to Arabidopsis FMO1 [3]. Expression of Bs3, either by AvrBs3 activation or by constitutive
overexpression, causes cell death [3]. Arabidopsis FMO1 is involved in pathogen defence in Arabidopsis but does not trigger cell death [12]. Interestingly, related flavin monooxygenases are also involved in biosynthesis of the cell-size-controlling hormone auxin [13], suggesting that the resistance gene function of Bs3 may have evolved after the inclusion of a upa box in its promoter. How a single flavin monooxygenase is able to initiate a cell death response remains unclear, but there are at least two distinct possibilities. First, Bs3 could act enzymatically on downstream targets, and these resulting modifications could perpetuate a cell death signal. Alternatively, the plant may perceive Bs3 itself as a signal for initiating a cell death response. These new results reveal a fresh layer in the co-evolution of plants and plant
1. Zipfel, C., Robatzek, S., Navarro, L., Oakeley, E.J., Jones, J.D.G., Felix, G., and Boller, T. (2004). Bacterial disease resistance in Arabidopsis through flagellin perception. Nature 428, 764–767. 2. Jones, J.D.G., and Dangl, J.L. (2006). The plant immune system. Nature 444, 323–329. 3. Ro¨mer, P., Hahn, S., Jordan, T., Strauß, T., Bonas, U., and Lahaye, T. (2007). Plant pathogen recognition mediated by promoter activation of the pepper Bs3 resistance gene. Science 318, 645–648. 4. Kay, S., Hahn, S., Marois, E., Hause, G., and Bonas, U. (2007). A bacterial effector acts as a plant transcription factor and induces a cell size regulator. Science 318, 648–651. 5. Gala´n, J.E., and Wolf-Watz, H. (2006). Protein delivery into eukaryotic cells by type III secretion machines. Nature 444, 567–573. 6. Van den Ackerveken, G., Marois, E., and Bonas, U. (1996). Recognition of the bacterial avirulence protein AvrBs3 occurs inside the host plant cell. Cell 87, 1307–1316. 7. Szurek, B., Marois, E., Bonas, U., and Van den Ackerveken, G. (2001). Eukaryotic features of the Xanthomonas type III effector AvrBs3: protein domains involved in transcriptional activation and the interaction with nuclear import receptors from pepper. Plant J. 26, 523–534. 8. Herbers, K., Conrads-Strauch, J., and Bonas, U. (1992). Race-specificity of plant resistance to bacterial spot disease determined by repetitive motifs in a bacterial avirulence protein. Nature 356, 172–174. 9. Gu, K., Yang, B., Tian, D., Wu, L., Wang, D., Sreekala, C., Yang, F., Chu, Z., Wang, G.-L., White, F.F., et al. (2005). R gene expression induced by a type-III effector triggers disease resistance in rice. Nature 435, 1122–1125. 10. Wieczorek, K., Golecki, B., Gerdes, L., Heinen, P., Szakasits, D., Durachko, D.M., Cosgrove, D.J., Kreil, D.P., Puzio, P.S., Bohlmann, H., et al. (2006). Expansins are involved in the formation of nematode-induced syncytia in roots of Arabidopsis thaliana. Plant J. 48, 98–112. 11. Wichmann, G., and Bergelson, J. (2004). Effector genes of Xanthamonas axonopodis pv. vesicatoria promote transmission and enhance
Current Biology Vol 18 No 3 R130
other fitness traits in the field. Genetics 166, 693–706. 12. Koch, M., Vorwerk, S., Masur, C., Sharifi-Sirchi, G., Olivieri, N., and Schlaich, N.L. (2006). A role for a flavin-containing mono-oxygenase in resistance against microbial pathogens in Arabidopsis. Plant J. 47, 629–639.
13. Zhao, Y., Christensen, S.K., Fankhauser, C., Cashman, J.R., Cohen, J.D., Weigel, D., and Chory, J. (2001). A role for flavin monooxygenase-like enzymes in auxin biosynthesis. Science 291, 306–309. 14. Kamoun, S. (2007). Groovy times: filamentous pathogen effectors revealed. Curr. Opin. Plant Biol. 10, 358–365.
Vertebrate Ageing: An Evolutionary Process with a Genetic Basis? Theories that explain the persistence of ageing in the face of natural selection implicitly assume that there is a genetic basis for ageing. This has now for the first time been shown to be the case in two free-living populations of mammals. Jean-Michel Gaillard and Christophe Bonenfant Senescence (or ageing) is a biological process occurring after the period of development of an organism and involves several mechanisms of deterioration. At first sight, senescence could simply be due to wear reflecting a physiological deterioration of cells with increasing age. This interpretation would explain why senescence occurs in free-ranging populations despite the apparent negative effects of decreasing individual performance with age. However, in our current evolutionary theory senescence is viewed as a life-history process that is moulded by natural selection. This poses the question of why senescence occurs even though it should be selected against. Two main, non-mutually exclusive hypotheses have been proposed to explain this apparent paradox: the mutation-accumulation hypothesis [1] suggests that the strength of selection decreases with age, such that more deteriorating mutations would accumulate; the antagonisticpleiotropy hypothesis [2] involves positive selection for genes that confer short-term fitness benefits early in life, but at the same time cause fitness reduction in later ages. In both of these models, senescence has a genetic basis. However, evidence for a genetic basis of variation of senescence had not yet been provided for free-ranging vertebrate populations. In a recent issue of Current Biology, Wilson et al. [3] fill this gap and report that genetic differences among individuals account for variation in their senescence rates. This offers
the first firm empirical support for the current evolutionary theory of senescence in vertebrates — either mutation accumulation or antagonistic pleiotropy, as these hypotheses are not easy to disentangle in practice [3]. This finding is a major contribution to our understanding of senescence in vertebrates. The results of Wilson et al. [3] are based on two key components that should shape future empirical studies on senescence in free-ranging populations: the availability of detailed long-term (>30 years) data collected at the individual level and the use of an appropriate metric for measuring senescence. Using exceptionally detailed, long-term monitoring of Red deer and Soay sheep populations living on Scottish Islands, Wilson et al. [3] were able to estimate accurately the age-specific variation in both reproductive success and survival for large numbers of individuals. This provided a direct measure of senescence in annual fitness. Moreover, the knowledge of pedigree structures in those populations allowed the authors to apply quantitative genetic models in order to assess whether variation in ageing rates in annual fitness in sheep and deer females had an additive genetic basis. Detecting Senescence in Free-Ranging Populations of Vertebrates: Is Ageing Universal? Senescence has always intrigued people, but research on ageing has traditionally focused on humans, laboratory invertebrates or captive vertebrates [4–6]. Whether findings obtained on these models will apply to free-ranging populations is, however, questionable. Unlike experimental
The Sainsbury Laboratory, John Innes Centre, Norwich NR4 7BU, UK. E-mail: [email protected]
DOI: 10.1016/j.cub.2007.11.064
animals, free-ranging animals face a large amount of environmental fluctuation and are typically subject to much higher mortality during the first stages of the life-cycle, which indicates that natural selection will operate mainly at early stages of life. As illustrated by Wilson et al. [3], the availability of long-term data on an individual level is required to analyse the senescence reliably in the wild. Consequently, empirical evidence of senescence in free-ranging populations of vertebrates has so far almost entirely focused on a few particular groups, such as seabirds and passerines [7] or large herbivore mammals [8]. By contrast, other species, such as fishes or tortoises, were reported not to age in the wild [9], although these conclusions were based on limited sample sizes. Whether senescence is a universal process cannot be answered without long-term, individual-based data and in particular the duration of a study constitutes a key component for our ability to detect senescence in free-ranging populations. Of course, the required study length will depend on the focal species. Ideally, a study should include several cohorts monitored until extinction. Nowadays, the paucity of data in terms of taxonomic range, sample size and duration prevent a reliable answer to the question of how universal senescence is in the wild. Of course, this also hampers our understanding of the mechanism involved in shaping age-specific changes in life-history traits. Long-term studies involving the monitoring of individual performance from birth to death, such as those reported by Wilson et al. [3] for red deer and Soay sheep are badly needed. Assessing Senescence from an Evolutionary Perspective From an evolutionary perspective, the effects of senescence should be measured with respect to the fitness of individuals rather than to specific life
7. Worm, B., Barbier, E.B., Beaumont, N., Duffy, J.E., Folke, C., Halpern, B.S., Jackson, J.B.C., Lotze, H.K., Micheli, F., Palumbi, S.R., et al. (2006). Impacts of biodiversity loss on ocean ecosystem services. Science 314, 787–790. 8. Danovaro, R., Gambi, C., Dell’Anno, A., Corinaldesi, C., Fraschetti, S., Vanreusel, A., Vincx, M., and Gooday, A.J. (2008). Exponential decline of deep-sea ecosystem functioning linked to benthic biodiversity loss. Curr. Biol. 18, 1–8. 9. Loreau, M. (1998). Biodiversity and ecosystem functioning: a mechanistic model. Proc. Natl. Acad. Sci. USA 95, 5632–5636. 10. Vila, M., Vayreda, J., Comas, L., Ibanez, J., Mata, T., and Obon, B. (2007). Species richness and wood production: a positive association in Mediterranean forests. Ecol. Lett. 10, 241–250.
11. Grace, J.B., Anderson, T.M., Smith, M.D., Seabloom, E., Andelman, S.J., Meche, G., Weiher, E., Allain, L.K., Jutila, H., Sankaran, M., et al. (2007). Does species diversity limit productivity in natural grassland communities? Ecol. Lett. 10, 680–689. 12. Loreau, M., and Hector, A. (2001). Partitioning selection and complementarity in biodiversity experiments. Nature 412, 72–76. 13. Cardinale, B.J., Wright, J.P., Cadotte, M.W., Carroll, I.T., Hector, A., Srivastava, D.S., Loreau, M., and Weis, J.J. (2007). Impacts of plant diversity on biomass production increase through time because of species complementarity. Proc. Natl. Acad. Sci. USA 104, 18123–18128. 14. Gross, K., and Cardinale, B.J. (2005). The functional consequences of random vs. ordered species extinctions. Ecol. Lett. 8, 409–418.
Plant Pathogen Effectors: Getting Mixed Messages Plant pathogen effectors have now been shown to mimic plant transcription factors and turn on genes that help the pathogen. Some plants, however, have evolved to use these pathogen-derived transcription factors to turn on defence. David L. Greenshields and Jonathan D.G. Jones The ability to live and reproduce within a plant has evolved independently several times in pathogens from different kingdoms of life. The apparent widespread success of this lifestyle suggests that it provides a comfortable living for organisms that have the right skill set. Although plants appear to be sessile nutrient reserves ripe for the plundering, inside plant cells it is a different story: pathogens that attempt entry can be simultaneously encased in fortified barriers, subjected to potent oxidizers and toxic small molecules and even thwarted by the suicide of the targeted host cell. Thus, the road to the good life within a plant requires a lot of disguise and deception, and only the most cunning can enjoy what the plant has to offer. In response to pathogens, plants have evolved sophisticated recognition capabilities that sense conserved molecules expressed by fungal, bacterial and oomycete pathogens. The bacterial flagellum protein flagellin is the best characterized of these pathogen signatures [1]. To evade plant recognition and encourage a suitable environment for growth and reproduction, pathogens secrete a range of protein effectors into plant cells that can block the recognition of these molecules and manipulate
host machinery for the pathogen’s benefit. In turn, plants have evolved surveillance systems to recognize the effectors themselves, thereby triggering another layer of the plant immune response [2]. To enable pathogen survival and growth within the host, effectors must turn on pathways to promote pathogen nutrition and turn off pathways leading to defence activation. Therefore, plants must be able to recognize these attempts at manipulation and mount a defence response. Two recent papers [3,4] describe an interesting twist on pathogen effectors and their recognition. They show that the bacterial spot-causing pathogen Xanthomonas campestris pv. vesicatoria (Xcv) secretes AvrBs3, a transcription factor effector that induces the plant cell-size regulator upa20 in susceptible plants and the resistance gene Bs3 in resistant plants. While activation of upa20 leads to cell hypertrophy, which supports the infecting bacteria [4], activation of Bs3 triggers a defence response leading to plant cell death [3]. These two different transcription factor activities account for the phenotypes seen in resistant and susceptible plants. Bacterial pathogens of both plants and animals have evolved a syringe-like organelle called the type III secretion system that delivers effector proteins directly into
15. Callaway, R.M. (2007). Positive Interactions and Interdependence in Plant Communities (Dordrecht: Springer). 16. Lohrer, A.M., Thrush, S.F., and Gibbs, M.M. (2004). Bioturbators enhance ecosystem function through complex biogeochemical interactions. Nature 431, 1092–1095.
Department of Biology, McGill University, 1205 Avenue Docteur Penfield, Montreal, Quebec H3A 1B1, Canada. E-mail: [email protected]
DOI: 10.1016/j.cub.2007.11.060
eukaryotic cells [5]. AvrBs3 is the signature member of a family of conserved proteins in Xanthomonas that is injected into host cells through type III secretion and is characterized by a nuclear localization signal [6], a transcriptional activation domain [7], and a central repeat domain that determines resistance and susceptible responses in different plant genotypes [8]. To isolate direct targets of AvrBs3, Kay et al. [4] screened cDNAs from infected pepper plants impaired in protein synthesis, and this led to the identification of Upa20, a basic helix–loop–helix transcription factor related to the Arabidopsis petal-size regulator BIGPETAL. Silencing of upa20 reduced cell hypertrophy in infected plants and expression of upa20 led to hypertrophy in uninfected plants [4]. Mutation of the upa20 promoter identified a so-called upa box that is the direct target of AvrBs3 [4]. Interestingly, there is also a upa box in the promoter of the pepper Bs3 resistance gene, which recognizes Xcv isolates carrying AvrBs3 [3]. Ro¨mer et al. [3] show that AvrBs3 activates the transcription of its cognate resistance gene Bs3, thereby triggering a defensive localized plant cell death (Figure 1). Another AvrBs3-like protein, AvrXa27 from X. oryzae pv. oryzae, also activates transcription of its associated rice resistance gene Xa27 [9], suggesting a common mode of action for this protein family. How does Upa20 promote hypertrophy and what benefit does host cellular hypertrophy provide the pathogen? Upa20 induces expression of upa7, which encodes a putative a-expansin [4]. Interestingly, expansin gene induction is also seen in the enlarged root cells that harbour plant
Dispatch R129
pathogens. By mimicking a host transcription factor, pathogens have found a direct route for getting what they want from the plant. Plants, on the other hand, have adapted to give the pathogen more than they bargained for. The ability to launch a defence response with a pathogen’s transcription factor effector has evolved in distantly related plants [3,9]. With the rapid expansion in available pathogen genomes and the falling prices of genome sequencing, we should now be able to catalogue similar effectors from diverse pathogens by analysis of nuclear localization signals and transcriptional activation domains. Indeed, efforts are underway to describe the entire ‘effectoromes’ of filamentous plant pathogens [14]. It will be interesting to see how widespread this mode of effector action is in distantly related plant pathogens.
T3SS
Susceptible
upa20
Upa20
AvrBs3 upa
Upa7 + ?
Resistant
Bs3
AvrBs3 upa ?
Bs3 ?
Hypertrophy
Cell death References Current Biology
Figure 1. The transcription factor activity of AvrBs3 elicits different responses in resistant and susceptible plants. AvrBs3 is delivered into host cells via the Xanthomonas type III secretion system (T3SS). In susceptible pepper plants (left, green background), AvrBs3 binds the upa box and activates transcription of upa20, which encodes a basic helix–loop–helix transcription factor. Upa20 then activates transcription of genes like upa7, which together give rise to cellular hypertrophy. In resistant pepper plants (right, yellow background) AvrBs3 binds the Bs3 upa box and activates Bs3 transcription. Bs3 initiates a cell death response either through recognition by a guard protein or by modification of an unidentified interacting protein.
pathogenic nematodes [10]. However, because Upa20 expression is sufficient for the hypertrophy symptoms seen in susceptible pepper plants, it is likely inducing other genes in addition to upa7. Although AvrBs3 is important in causing disease symptoms and plays a role in disease transmission, it seems to have very little effect on bacterial growth in planta [11]. Finding new targets of Upa20 and discovering how host cellular hypertrophy allows for higher bacterial transmission rates will help to explain the unusual mode of action of AvrBs3. How does Bs3 expression trigger cell death? Bs3 is not a classical resistance gene of the nucleotide-binding leucine-rich-repeat variety. Instead, Bs3 encodes a flavin monooxygenase with similarity to Arabidopsis FMO1 [3]. Expression of Bs3, either by AvrBs3 activation or by constitutive
overexpression, causes cell death [3]. Arabidopsis FMO1 is involved in pathogen defence in Arabidopsis but does not trigger cell death [12]. Interestingly, related flavin monooxygenases are also involved in biosynthesis of the cell-size-controlling hormone auxin [13], suggesting that the resistance gene function of Bs3 may have evolved after the inclusion of a upa box in its promoter. How a single flavin monooxygenase is able to initiate a cell death response remains unclear, but there are at least two distinct possibilities. First, Bs3 could act enzymatically on downstream targets, and these resulting modifications could perpetuate a cell death signal. Alternatively, the plant may perceive Bs3 itself as a signal for initiating a cell death response. These new results reveal a fresh layer in the co-evolution of plants and plant
1. Zipfel, C., Robatzek, S., Navarro, L., Oakeley, E.J., Jones, J.D.G., Felix, G., and Boller, T. (2004). Bacterial disease resistance in Arabidopsis through flagellin perception. Nature 428, 764–767. 2. Jones, J.D.G., and Dangl, J.L. (2006). The plant immune system. Nature 444, 323–329. 3. Ro¨mer, P., Hahn, S., Jordan, T., Strauß, T., Bonas, U., and Lahaye, T. (2007). Plant pathogen recognition mediated by promoter activation of the pepper Bs3 resistance gene. Science 318, 645–648. 4. Kay, S., Hahn, S., Marois, E., Hause, G., and Bonas, U. (2007). A bacterial effector acts as a plant transcription factor and induces a cell size regulator. Science 318, 648–651. 5. Gala´n, J.E., and Wolf-Watz, H. (2006). Protein delivery into eukaryotic cells by type III secretion machines. Nature 444, 567–573. 6. Van den Ackerveken, G., Marois, E., and Bonas, U. (1996). Recognition of the bacterial avirulence protein AvrBs3 occurs inside the host plant cell. Cell 87, 1307–1316. 7. Szurek, B., Marois, E., Bonas, U., and Van den Ackerveken, G. (2001). Eukaryotic features of the Xanthomonas type III effector AvrBs3: protein domains involved in transcriptional activation and the interaction with nuclear import receptors from pepper. Plant J. 26, 523–534. 8. Herbers, K., Conrads-Strauch, J., and Bonas, U. (1992). Race-specificity of plant resistance to bacterial spot disease determined by repetitive motifs in a bacterial avirulence protein. Nature 356, 172–174. 9. Gu, K., Yang, B., Tian, D., Wu, L., Wang, D., Sreekala, C., Yang, F., Chu, Z., Wang, G.-L., White, F.F., et al. (2005). R gene expression induced by a type-III effector triggers disease resistance in rice. Nature 435, 1122–1125. 10. Wieczorek, K., Golecki, B., Gerdes, L., Heinen, P., Szakasits, D., Durachko, D.M., Cosgrove, D.J., Kreil, D.P., Puzio, P.S., Bohlmann, H., et al. (2006). Expansins are involved in the formation of nematode-induced syncytia in roots of Arabidopsis thaliana. Plant J. 48, 98–112. 11. Wichmann, G., and Bergelson, J. (2004). Effector genes of Xanthamonas axonopodis pv. vesicatoria promote transmission and enhance
Current Biology Vol 18 No 3 R130
other fitness traits in the field. Genetics 166, 693–706. 12. Koch, M., Vorwerk, S., Masur, C., Sharifi-Sirchi, G., Olivieri, N., and Schlaich, N.L. (2006). A role for a flavin-containing mono-oxygenase in resistance against microbial pathogens in Arabidopsis. Plant J. 47, 629–639.
13. Zhao, Y., Christensen, S.K., Fankhauser, C., Cashman, J.R., Cohen, J.D., Weigel, D., and Chory, J. (2001). A role for flavin monooxygenase-like enzymes in auxin biosynthesis. Science 291, 306–309. 14. Kamoun, S. (2007). Groovy times: filamentous pathogen effectors revealed. Curr. Opin. Plant Biol. 10, 358–365.
Vertebrate Ageing: An Evolutionary Process with a Genetic Basis? Theories that explain the persistence of ageing in the face of natural selection implicitly assume that there is a genetic basis for ageing. This has now for the first time been shown to be the case in two free-living populations of mammals. Jean-Michel Gaillard and Christophe Bonenfant Senescence (or ageing) is a biological process occurring after the period of development of an organism and involves several mechanisms of deterioration. At first sight, senescence could simply be due to wear reflecting a physiological deterioration of cells with increasing age. This interpretation would explain why senescence occurs in free-ranging populations despite the apparent negative effects of decreasing individual performance with age. However, in our current evolutionary theory senescence is viewed as a life-history process that is moulded by natural selection. This poses the question of why senescence occurs even though it should be selected against. Two main, non-mutually exclusive hypotheses have been proposed to explain this apparent paradox: the mutation-accumulation hypothesis [1] suggests that the strength of selection decreases with age, such that more deteriorating mutations would accumulate; the antagonisticpleiotropy hypothesis [2] involves positive selection for genes that confer short-term fitness benefits early in life, but at the same time cause fitness reduction in later ages. In both of these models, senescence has a genetic basis. However, evidence for a genetic basis of variation of senescence had not yet been provided for free-ranging vertebrate populations. In a recent issue of Current Biology, Wilson et al. [3] fill this gap and report that genetic differences among individuals account for variation in their senescence rates. This offers
the first firm empirical support for the current evolutionary theory of senescence in vertebrates — either mutation accumulation or antagonistic pleiotropy, as these hypotheses are not easy to disentangle in practice [3]. This finding is a major contribution to our understanding of senescence in vertebrates. The results of Wilson et al. [3] are based on two key components that should shape future empirical studies on senescence in free-ranging populations: the availability of detailed long-term (>30 years) data collected at the individual level and the use of an appropriate metric for measuring senescence. Using exceptionally detailed, long-term monitoring of Red deer and Soay sheep populations living on Scottish Islands, Wilson et al. [3] were able to estimate accurately the age-specific variation in both reproductive success and survival for large numbers of individuals. This provided a direct measure of senescence in annual fitness. Moreover, the knowledge of pedigree structures in those populations allowed the authors to apply quantitative genetic models in order to assess whether variation in ageing rates in annual fitness in sheep and deer females had an additive genetic basis. Detecting Senescence in Free-Ranging Populations of Vertebrates: Is Ageing Universal? Senescence has always intrigued people, but research on ageing has traditionally focused on humans, laboratory invertebrates or captive vertebrates [4–6]. Whether findings obtained on these models will apply to free-ranging populations is, however, questionable. Unlike experimental
The Sainsbury Laboratory, John Innes Centre, Norwich NR4 7BU, UK. E-mail: [email protected]
DOI: 10.1016/j.cub.2007.11.064
animals, free-ranging animals face a large amount of environmental fluctuation and are typically subject to much higher mortality during the first stages of the life-cycle, which indicates that natural selection will operate mainly at early stages of life. As illustrated by Wilson et al. [3], the availability of long-term data on an individual level is required to analyse the senescence reliably in the wild. Consequently, empirical evidence of senescence in free-ranging populations of vertebrates has so far almost entirely focused on a few particular groups, such as seabirds and passerines [7] or large herbivore mammals [8]. By contrast, other species, such as fishes or tortoises, were reported not to age in the wild [9], although these conclusions were based on limited sample sizes. Whether senescence is a universal process cannot be answered without long-term, individual-based data and in particular the duration of a study constitutes a key component for our ability to detect senescence in free-ranging populations. Of course, the required study length will depend on the focal species. Ideally, a study should include several cohorts monitored until extinction. Nowadays, the paucity of data in terms of taxonomic range, sample size and duration prevent a reliable answer to the question of how universal senescence is in the wild. Of course, this also hampers our understanding of the mechanism involved in shaping age-specific changes in life-history traits. Long-term studies involving the monitoring of individual performance from birth to death, such as those reported by Wilson et al. [3] for red deer and Soay sheep are badly needed. Assessing Senescence from an Evolutionary Perspective From an evolutionary perspective, the effects of senescence should be measured with respect to the fitness of individuals rather than to specific life