Stress-induced flowering

Many plant species can be induced to flower by responding to stress factors. The short-day plants Pharbitis nil and Perilla frutescens var. crispa flower under long days in response to the stress of poor nutrition or low-intensity light. Grafting experiments using two varieties of P. nil revealed that a transmissible flowering stimulus is involved in stress-induced flowering. The P. nil and P. frutescens plants that were induced to flower by stress reached anthesis, fruited and produced seeds. These seeds germinated, and the progeny of the stressed plants developed normally. Phenylalanine ammonialyase inhibitors inhibited this stress-induced flowering, and the inhibition was overcome by salicylic acid (SA), suggesting that there is an involvement of SA in stress-induced flowering. PnFT2, a P. nil ortholog of the flowering gene FLOWERING LOCUS T (FT) of Arabidopsis thaliana, was expressed when the P. nil plants were induced to flower under poor-nutrition stress conditions, but expression of PnFT1, another ortholog of FT, was not induced, suggesting that PnFT2 is involved in stress-induced flowering.Key words: flowering, stress, phenylalanine ammonia-lyase, salicylic acid, FLOWERING LOCUS T, Pharbitis nil, Perilla frutescensFlowering in many plant species is regulated by environmental factors, such as night-length in photoperiodic flowering and temperature in vernalization. On the other hand, a short-day (SD) plant such as Pharbitis nil (synonym Ipomoea nil) can be induced to flower under long days (LD) when grown under poor-nutrition, low-temperature or high-intensity light conditions.^1–9 The flowering induced by these conditions is accompanied by an increase in phenylalanine ammonia-lyase (PAL) activity.¹⁰ Taken together, these facts suggest that the flowering induced by these conditions might be regulated by a common mechanism. Poor nutrition, low temperature and high-intensity light can be regarded as stress factors, and PAL activity increases under these stress conditions.¹¹ Accordingly, we assumed that such LD flowering in P. nil might be induced by stress. Non-photoperiodic flowering has also been sporadically reported in several plant species other than P. nil, and a review of these studies suggested that most of the factors responsible for flowering could be regarded as stress. Some examples of these factors are summarized in 12^–14

Table 1

Some cases of stress-induced flowering

Genome-wide analysis of lipoxygenase gene family in Arabidopsis and rice

The enzymes called lipoxygenases (LOXs) can dioxygenate unsaturated fatty acids, which leads to lipoperoxidation of biological membranes. This process causes synthesis of signaling molecules and also leads to changes in cellular metabolism. LOXs are known to be involved in apoptotic (programmed cell death) pathway, and biotic and abiotic stress responses in plants. Here, the members of LOX gene family in Arabidopsis and rice are identified. The Arabidopsis and rice genomes encode 6 and 14 LOX proteins, respectively, and interestingly, with more LOX genes in rice. The rice LOXs are validated based on protein alignment studies. This is the first report wherein LOXs are identified in rice which may allow better understanding the initiation, progression and effects of apoptosis, and responses to bitoic and abiotic stresses and signaling cascades in plants.Key words: apoptosis, biotic and abiotic stresses, genomics, jasmonic acid, lipidsLipoxygenases (linoleate:oxygen oxidoreductase, EC 1.13.11.-; LOXs) catalyze the conversion of polyunsaturated fatty acids (lipids) into conjugated hydroperoxides. This process is called hydroperoxidation of lipids. LOXs are monomeric, non-heme and non-sulfur, but iron-containing dioxygenases widely expressed in fungi, animal and plant cells, and are known to be absent in prokaryotes. However, a recent finding suggests the existence of LOX-related genomic sequences in bacteria but not in archaea.¹ The inflammatory conditions in mammals like bronchial asthama, psoriasis and arthritis are a result of LOXs reactions.² Further, several clinical conditions like HIV-1 infection,³ disease of kidneys due to the activation of 5-lipoxygenase,^4,5 aging of the brain due to neuronal 5-lipoxygenase⁶ and atherosclerosis⁷ are mediated by LOXs. In plants, LOXs are involved in response to biotic and abiotic stresses.⁸ They are involved in germination⁹ and also in traumatin and jasmonic acid biochemical pathways.^10,11 Studies on LOX in rice are conducted to develop novel strategies against insect pests¹² in response to wounding and insect attack,¹³ and on rice bran extracts as functional foods and dietary supplements for control of inflammation and joint health.¹⁴ In Arabidopsis, LOXs are studied in response to natural and stress-induced senescence,¹⁵ transition to flowering,¹⁶ regulation of lateral root development and defense response.¹⁷The arachidonic, linoleic and linolenic acids can act as substrates for different LOX isozymes. A hydroperoxy group is added at carbons 5, 12 or 15, when arachidonic acid is the substrate, and so the LOXs are designated as 5-, 12- or 15-lipoxygenases. Sequences are available in the database for plant lipoxygenases (EC:1.13.11.12), mammalian arachidonate 5-lipoxygenase (EC:1.13.11.34), mammalian arachidonate 12-lipoxygenase (EC:1.13.11.31) and mammalian erythroid cell-specific 15-lipoxygenase (EC:1.13.11.33). The prototype member for LOX family, LOX-1 of Glycine max L. (soybean) is a 15-lipoxygenase. The LOX isoforms of soybean (LOX-1, LOX-2, LOX-3a and LOX-3b) are the most characterized of plant LOXs.¹⁸ In addition, five vegetative LOXs (VLX-A, -B, -C, -D, -E) are detected in soybean leaves.¹⁹ The 3-dimensional structure of soybean LOX-1 has been determined.^20,21 LOX-1 was shown to be made of two domains, the N-terminal domain-I which forms a β-barrel of 146 residues, and a C-terminal domain-II of bundle of helices of 693 residues²¹ (Fig. 1). The iron atom was shown to be at the centre of domain-II bound by four coordinating ligands, of which three are histidine residues.²²Open in a separate windowFigure 1Three-dimensional structure of soybean lipoxygenase L-1. The domain I (N-terminal) and domain II (C-terminal) are indicated. The catalytic iron atom is embedded in domain II (PDB ID-1YGE).²¹This article describes identification of LOX genes in Arabidopsis and rice. The Arabidopsis genome encodes for six LOX proteins²³ (www.arabidopsis.org) (

Efflux of hydraulically lifted water from mycorrhizal fungal hyphae during imposed drought

Apart from improving plant and soil water status during drought, it has been suggested that hydraulic lift (HL) could enhance plant nutrient capture through the flow of mineral nutrients directly from the soil to plant roots, or by maintaining the functioning of mycorrhizal fungi. We evaluated the extent to which the diel cycle of water availability created by HL covaries with the efflux of HL water from the tips of extramatrical (external) mycorrhizal hyphae, and the possible effects on biogeochemical processes. Phenotypic mycorrhizal fungal variables, such as total and live hyphal lengths, were positively correlated with HL efflux from hyphae, soil water potential (dawn), and plant response variables (foliar ¹⁵N). The efflux of HL water from hyphae was also correlated with bacterial abundance and soil enzyme activity (P), and the moistening of soil organic matter. Such findings indicate that the efflux of HL water from the external mycorrhizal mycelia may be a complementary explanation for plant nutrient acquisition and survival during drought.Key words: hydraulic lift, nitrogen, phosphorus, microbial abundance, mycorrhizal hyphae, QuercusIn environments that experience seasonal or extended drought, plant productivity, resource partitioning, and competition are limited by the availability of water and mineral nutrients. One mechanism that is important to whole plant water balance in these environments is hydraulic lift (HL), a passive process driven by gradients in water potential among soils layers. Soil water is transported upwards from deep moist soils and released into the nutrient-rich upper soil layers by root systems accessing both deep and shallow soil layers.¹ HL water may improve the lifespan and activity of fine roots in a wide variety of plant life forms.²Hydraulic lift may also have a second ecological function in facilitating plant nutrient acquisition.² It been hypothesized that HL water could enhance the supply of nutrients to roots through mass flow or diffusion,³ or trigger episodes of soil biotic activity such as microbe-mediated nutrient transformations^4,5 that are analogous to the increased inflow of nitrogen (N) into roots and flushes of carbon (C) and N mineralization respectively that follow precipitation events.^4,6 However, few data currently exist with which to test these possibilities.Hydraulically lifted water also sustains mycorrhizal fungi,^7,8 a mutualism that enhances the acquisition of water and mineral nutrients in many terrestrial plant species. Mycorrhizal fungal hyphae provide comprehensive exploration and rapid access to small-scale or temporary nutrient flushes that may not be available to plant roots.⁹ This resource flow has often been assumed to be a unidirectional flux whereby resources are moved from source (soil) into the sink (plant) by the fungal hyphae. However, there is now evidence to suggest that the physiological plasticity of the peripheral extramatrical hyphae, and in particular the hyphal tips, permits the exudation, and subsequent reabsorption, of water and solutes.^10,11 Laboratory experiments using pure cultures have demonstrated that water may be exuded from the hyphal tips, especially in fungal species with hydrophobic hyphae, along with a variety of organic molecules, such as free amino acids.^10–13 At the same time, water, mobile minerals, amino acids and other low-molecular weight metabolites may be selectively and actively reabsorbed by mycorrhizal fungal hyphae.¹¹ However, quantitative data on the environmental impact of hyphal exudation and reabsorption is still largely lacking.We ask: could the diel cycle of water availability created by HL produce a water efflux from hyphal tips and if so, would this be sufficient to impact biogeochemical processes? Is there also an opposite rhythm driven by plant transpiration so that any resultant soil solution is pulled towards hyphal tips and consequently, the host plant? By imposing drought on seedlings of Quercus agrifolia Nee (coast live oak; Fagaceae) grown in mesocosms (Fig. 1), we identified a composite of feedbacks that could influence nutrient capture with HL (Fig. 2). Our analyses provide support for the key predictions of the HL-nutrient cycling scenario including the efflux of HL water from the extramatrical hyphae (Fig. 3), moistening of soil organic matter (Figs. 3 and ​and4),4), and the maintenance of soil microbial activity and nutrient capture (N, P; Open in a separate windowFigure 1Quercus mesocosms demonstrating the plant, root, and hyphal compartments. Details of soil conditions, plant inoculation protocol, mycorrhizal fungi and dye injection methods are detailed in previous work (ref. 7) Point 1 (tap root compartment) denotes the region in which fluorescent tracer dyes were injected into the mesocosm at dusk to track the path of HL water. Point 2 (hyphal chamber) denotes spots adjacent to or distant from the mesh screen into which a small volume (200 µl) of fluorescent and ¹⁵N tracers (99% as ¹⁵NH₄¹⁵NO₃) were injected at dawn to measure water and nutrient uptake by the external hyphae.Open in a separate windowFigure 2Path analysis of the influence of different soil and mycorrhizal factors on nutrient capture with HL, and resultant model showing the significant path coefficients among variables in the Q. agrifolia mesocosms. Lines with a single arrow denote possible cause-effect relationships. The partial correlation coefficients adjacent to each line indicate the strength of the association between the individual factors. Thick lines are statistically significant (p < 0.05) whereas thin lines indicate no significant relationship between parameters (p > 0.05) and only significant coefficients are given (p < 0.05).Open in a separate windowFigure 3Fluorescently-labeled structures recovered from the hyphal chamber of Quercus microcosms following 80 days of soil drying and with nocturnal hydraulic lift. Yellow-green fluorescence indicates samples labeled with Lucifer yellow CH (LYCH), blue fluorescence denotes samples labeled with Cascade blue (CB) hydrazide. (A) CB-labeled leaf litter from the soil and (B) soil particle; (C) LYCH-labeled root fragment in the soil mixture with adherent extramatrical hyphae; (D) LYCH tracer dye fluorescence in labeled extramatrical hyphae and in efflux (arrow) from the hyphal tip onto organic matter; (E and F) external hyphae filled with LYCH (influx; arrow) and (G) background fluorescence in non-labeled extramatrical hyphae.Open in a separate windowFigure 4Measurements of hyphal efflux and influx based on the quantitative analysis of LYCH fluorescence intensity in soil solution. Fluorescent intensity values were converted to LYCH concentration using a standard curve generated for the dye since fluorescent intensity correlates with the number of fluorescent molecules in solution. Influx is the uptake of LYCH by hyphae as driven by plant transpiration demands (day), and measured efflux is the passive loss of LYCH from hyphae into the surrounding soil during HL (night). Vertical bars indicate the standard error of the means.

Table 1

Summary of soil, microbial, mycorrhizal and plant parameters in plant or hyphal compartments

Sources of floral scent variation: Can environment define floral scent phenotype?

Studies of floral scent generally assume that genetic adaptation due to pollinator-mediated natural selection explains a significant amount of phenotypic variance, ignoring the potential for phenotypic plasticity in this trait. In this paper, we assess this latter possibility, looking first at previous studies of floral scent variation in relation to abiotic environmental factors. We then present data from our own research that suggests among-population floral scent variation is determined, in part, by environmental conditions and thus displays phenotypic plasticity. Such an outcome has strong ramifications for the study of floral scent variation; we conclude by presenting some fundamental questions that should lead to greater insight into our understanding of the evolution of this trait, which is important to plant-animal interactions.Key words: abiotic factors, aromatics, floral scent, GxE interaction, phenotypic plasticity, pollination, terpenoids, volatilesFloral scent is thought to function as a major non-visual attractive cue for many pollinators in a large number of plant systems^1,2 and therefore most research on this plant trait has proceeded in the context of pollination ecology. Such studies have revealed the physiological and behavioral responses of pollinators to various floral volatiles (reviewed in refs. ³ and ⁴), convergent evolution of odor phenotypes attractive to specific pollinator classes (reviewed in refs. ⁵ and ⁶), reproductive isolation of plant species due to differences in pollinator attraction by scent,⁷ and instances of deception in which flowers mimic insect pheromones to effect pollination.⁸ Together, this body of evidence suggests that specific floral scent profiles can have important implications for the reproductive potential of many plant species.This pollinator-centered viewpoint has carried through to research on floral scent variation, including our most recent work on the insect-pollinated species Hesperis matronalis (Brassicaceae).⁹ Such studies usually suggest that the floral scent variation commonly found within and among individuals, populations and species (reviewed in ref. ²) is due to genetic differentiation as a result of selection by pollinators over time (reviewed in ref. ¹⁰). But an organism''s genes are only one factor determining phenotype. Both biotic (living) and abiotic (non-living) environmental conditions can profoundly affect phenotype expression, leading to significant variation. For plants, abiotic factors such as climate and soil chemistry can have particularly strong effects on phenotypes. When these environmental conditions cause changes in phenotype, we would say that a trait displays phenotypic plasticity.^11–13 A number of studies have uncovered phenotypic plasticity for many different plant traits.¹² However, while phenotypic variation in floral scent has been well-documented^1,2 and correlated with variation in biotic factors like pollinator behavior,^14–17 these studies were decidedly focused on natural selection, rather than phenotypic plasticity, as an organizational framework.However, in examining the scientific literature on floral scent, we found four studies in which the effects of naturally variable abiotic factors on floral scent profiles were examined, three of which were performed by the same research group (18^–21 (21). Moreover, these studies are decidedly not analyzed and interpreted using standard protocols for phenotypic plasticity studies.¹³

Table 1

A survey of previous studies examining changes in floral scent phenotype due to abiotic factors

Genome-wide analysis of thioredoxin fold superfamily peroxiredoxins in Arabidopsis and rice

A broad range of peroxides generated in subcellular compartments, including chloroplasts, are detoxified with peroxidases called peroxiredoxins (Prx). The Prx are ubiquitously distributed in all organisms including bacteria, fungi, animals and also in cyanobacteria and plants. Recently, the Prx have emerged as new molecules in antioxidant defense in plants. Here, the members which belong to Prx gene family in Arabidopsis and rice are been identified. Overall, the Prx members constitute a small family with 10 and 11 genes in Arabidopsis and rice respectively. The prx genes from rice are assigned to their functional groups based on homology search against Arabidopsis protein database. Deciphering the Prx functions in rice will add novel information to the mechanism of antioxidant defense in plants. Further, the Prx also forms the part of redox signaling cascade. Here, the Prx gene family has been described for rice.Key words: antioxidant defense, chloroplast, gene family, oxidative stress, reactive oxygen speciesThe formation of free radicals and reactive oxygen species (ROS) occur in several enzymatic and non-enzymatic reactions during cellular metabolism. The accumulation of these reactive and deleterious intermediates is suppressed by antioxidant defense mechanism comprised of low molecular weight antioxidants and enzymes. In photosynthetic organisms, the defense against the damage from free radicals and oxidative stress is crucial. For instance, the ROS production occurs in photosystem II with generation of singlet oxygen (¹O₂) and hydrogen peroxide (H₂O₂),^1,2 photosystem I from superoxide anion radicals (O₂⁻),³ and during photorespiration with generation of H₂O₂.⁴ ROS production may exceed under environmental stress conditions like excess light, low temperature and drought.⁵The antioxidant defense mechanism is activated by antioxidant metabolities and enzymes which detoxify ROS and lipid peroxides. The detoxification of ROS can occur in various cellular compartments such as chloroplasts, mitochondria, peroxisomes and cytosol.⁶ The enzymes like ascorbate peroxidase, catalase, glutathione peroxidase and superoxide dismutase are prominent antioxidant enzymes.⁶ The peroxiredoxins (Prx) emerged as new components in the antioxidant defense network of barley.^7,8 Later, Prx were studied in other plants.^9–14Prx can be classified into four different functional groups, PrxQ, 1-Cys Prx, 2-Cys Prx and Type-2 Prx.^15,16 They are members of the thioredoxin fold superfamily.^17,18 In this study, the prx genes found in Arabidopsis and rice genomes are been identified. The Arabidopsis genome encodes 10 prx genes classified into four functional categories, 1-Cys Prx, 2-Cys Prx, PrxQ and Type-2 Prx.¹³ Of these, one each of 1-Cys Prx and PrxQ, two of 2-Cys Prx (2-Cys PrxA and 2-Cys PrxB) and six Type-2 Prx (PrxA–F) are identified¹³ (LocusAnnotationSynonymA^*B^*C^*AT1G481301-Cysteine peroxiredoxin 1 (ATPER1)1-Cys Prx21624081.36.603AT1G60740Peroxiredoxin type 2Type-2 PrxD16217471.95.2297AT1G65970Thioredoxin-dependent peroxidase 2 (TPX2)Type-2 PrxC16217413.95.2297AT1G65980Thioredoxin-dependent peroxidase 1 (TPX1)Type-2 PrxB16217427.84.9977AT1G65990Type 2 peroxiredoxin-relatedType-2 PrxA55362653.66.4368AT3G06050Peroxiredoxin IIF (PRXIIF)Type-2 PrxF20121445.29.3905AT3G116302-Cys Peroxiredoxin A (2CPA, 2-Cys PrxA)2-Cys PrxA26629091.77.5686AT3G26060ATPRX Q, periredoxin QPrxQ21623677.810.0565AT3G52960Peroxiredoxin type 2Type-2 PrxE23424684.09.572AT5G062902-Cysteine Peroxiredoxin B (2CPB, 2-Cys PrxB)2-Cys PrxB27329779.55.414Open in a separate window^*A, amino acids; B, molecular weight; C, isoelectric point.In rice (rice.plantbiology.msu.edu/), there are 11 genomic loci which encode for Prx proteins (​and33). Interestingly, a new prx gene (LOC_Os07g15670) annotated as “peroxiredoxin, putative, expressed” is identified making the tally of prx genes to eleven in rice as compared to ten in Arabidopsis (​and22). The BLAST search has identified its counterpart in Arabidopsis which has been annotated as “antioxidant/oxidoreductase” (AT1G21350) in the TAIR database (www.arabidopsis.org). The rice LOC_Os07g15670 and Arabidopsis AT1G21350 share protein homology %68/78 for 236 amino acids (ChromosomeLocus IdPutative function/AnnotationA^*B^*C^*1LOC_Os01g16152peroxiredoxin, putative, expressed19920873.68.22091LOC_Os01g24740peroxiredoxin-2E-1, chloroplast precursor, putative10711591.56.79061LOC_Os01g48420peroxiredoxin, putative, expressed16317290.85.68282LOC_Os02g09940peroxiredoxin, putative, expressed22623179.56.5352LOC_Os02g33450peroxiredoxin, putative, expressed26228096.95.77094LOC_Os04g339702-Cys peroxiredoxin BAS1, chloroplast precursor, putative, expressed12213410.24.37056LOC_Os06g09610peroxiredoxin, putative, expressed2662892610.50976LOC_Os06g42000peroxiredoxin, putative, expressed23323688.39.20597LOC_Os07g15670peroxiredoxin, putative, expressed25327684.69.85457LOC_Os07g44440peroxiredoxin, putative, expressed22124232.65.36187LOC_Os07g44430peroxiredoxin, putative25627785.36.8544Open in a separate window^*A, amino acids; B, molecular weight; C, isoelectric point.

Table 3

Identification of rice homologs of peroxiredoxins in A. thaliana

Influence of polyploidy on insect herbivores of native and invasive genotypes of Solidago gigantea (Asteraceae)

Herbivores are sensitive to the genetic structure of plant populations, as genetics underlies plant phenotype and host quality. Polyploidy is a widespread feature of angiosperm genomes, yet few studies have examined how polyploidy influences herbivores. Introduction to new ranges, with consequent changes in selective regimes, can lead to evolution of changes in plant defensive characteristics and also affect herbivores. Here, we examine how insect herbivores respond to polyploidy in Solidago gigantea, using plants derived from both the native range (USA) and introduced range (Europe). S. gigantea has three cytotypes in the US, with two of these present in Europe. We performed bioassays with generalist (Spodoptera exigua) and specialist (Trirhabda virgata) leaf-feeding insects. Insects were reared on detached leaves (Spodoptera) or potted host plants (Trirhabda) and mortality and mass were measured. Trirhabda larvae showed little variation in survival or pupal mass attributable to either cytotype or plant origin. Spodoptera larvae were more sensitive to both cytotype and plant origin: they grew best on European tetraploids and poorly on US diploids (high mortality) and US tetraploids (low larval mass). These results show that both cytotype and plant origin influence insect herbivores, but that generalist and specialist insects may respond differently.Key words: polyploidy, cytotype, Solidago gigantea, insect herbivore, herbivory, invasive plant, introduced plantPolyploidy, or the possession of more than two sets of homologous chromosomes, is a fundamental force in angiosperm evolution.^1,2 Many plant species or species complexes consist of multiple cytotypes that may occur sympatrically;³ this is an important source of genetic structure in plant populations that is often overlooked.⁴ Possession of multiple genomes may confer advantages to polyploid plants such as increased heterozygosity, a decreased probability of inbreeding depression, or a greater gene pool available for selection; these traits contribute to the widespread success of polyploids and may make them prone to invasiveness.^5,6 In a recent article,⁷ we examined the functional consequences of polyploidy for different cytotypes of Solidago gigantea Ait. (Asteraceae), collected from both its native range (North America) and its introduced range (Europe). In this addendum, we show how cytotype and continent of origin influence interactions of S. gigantea with insect herbivores. Interactions with herbivores are expected to vary with cytotype because of phenotypic changes associated with polyploidy, but this area has received little study (reviewed in refs. ^8–11). Plant origin, from either the native range or an introduced range, should also influence herbivores. Plants may escape from their specialist natural enemies in the introduced range, thereby experiencing reduced herbivore pressure from an insect community dominated by generalists.^12,13 Given sufficient time, plants from the introduced range may evolve to decrease investment in anti-herbivore defenses, particularly those effective against specialists.¹⁴ While a growing body of research has addressed whether plant defenses against herbivory are lower in the introduced range,^12,15,16 few of these studies have also examined the influence of cytotype.¹⁷Three cytotypes of S. gigantea can be found in its native range in North America (diploid, tetraploid and hexaploid, 2n = 18, 36 and 54 respectively). These are morphologically indistinguishable and not generally treated as separate species.¹⁸ In Europe, where S. gigantea was introduced in the mid 18^th century,¹⁹ tetraploids are the dominant cytotype but diploids also occur. S. gigantea supports a diverse array of insect herbivores in its native range, but has few natural enemies in its introduced range.²⁰ We report here on experiments using both a generalist and a specialist leaf-chewing insect. The generalist, Spodoptera exigua (Lepidoptera: Noctuidae) is widely distributed and highly polyphagous, while the specialist Trirhabda virgata (Coleoptera: Chrysomelidae) feeds only on closely-related species within the genus Solidago. T. virgata is an outbreak insect that can be a major defoliator of S. gigantea and related species in North America.²¹ We grew plants originating from 10 populations in the US and 20 populations in Europe in common gardens at the University of Wisconsin-Milwaukee Field Station in Saukville, Wisconsin. There were five plant origin-cytotype combinations: three cytotypes from the US and two from Europe. Insects were reared on detached leaves from a single plant (Spodoptera) or on potted host plants (Trirhabda), for a set period of 21 d (Spodoptera) or until pupation (Trirhabda). We recorded insect survival and mass at the end of 21 d (Spodoptera) or at pupation (Trirhabda) (reviewed in ref. ²²).Overall survival was much better for the specialist Trirhabda than for the generalist Spodoptera (91% vs. 72%). Spodoptera larvae are not generally found on S. gigantea in the field, and while they are able to complete development, we found that this plant was not an ideal host. Spodoptera larvae were more sensitive to differences among cytotype and plant origin than were Trirhabda larvae. Percent survival was particularly poor for Spodoptera larvae reared on diploids from the US, where slightly more than half of the caterpillars survived for 21 days (Fig. 1). Trirhabda pupal mass was remarkably consistent across the five ploidy-plant origin combinations. In contrast, Spodoptera larvae responded to both cytotype and continent of origin. Surviving Spodoptera larvae did particularly well on tetraploid plants from the introduced range (Europe), and particularly poorly on tetraploids from the US (Fig. 1). We have previously reported that Spodoptera grow better on plants from Europe;²² our current results reveal that this difference is due exclusively to better growth on tetraploid plants. However, our results also show that both diploids and tetraploids from the US were poor hosts for Spodoptera: diploids because they caused high mortality and tetraploids because they resulted in poor growth. These results indicate that plants from the introduced range have reduced defenses against herbivores, even when accounting for polyploidy.Open in a separate windowFigure 1Mass ± se of S. exigua (A) and T. virgata (B) larvae reared on host plants of different cytotypes of Solidago gigantea originating from the US (native range) or europe (introduced range). Means in A followed by different letters are significantly different at p < 0.05 (ANOVA followed by multiple Student''s t-tests with Bonferroni correction). There were no significant differences in (B). Sample sizes for (A and B) shown in SpodopteraTrirhabdaNo. SurvivingInitial No.% SurvivalNo. SurvivingInitial No.% SurvivalUS-Diploid213954373995US-Tetraploid709375829289US-Hexaploid162467232496EU-Diploid152365232496EU-Tetraploid1011297811412988Open in a separate windowInsects were reared on a single genotype of each cytotype-origin combination for 21 days (Spodoptera) or until pupation (Trirhabda). Sample sizes for each cytotype-origin combination vary because cytotypes were not known at the time plants were collected; these distributions represent frequencies of cytotypes in our collections.Effects of the host plant on Spodoptera were probably driven, at least in part, by changes in secondary chemistry. We have previously shown that foliar terpenoids, chemicals known to influence insect herbivores,^23,24 are affected by both cytotype and continent of origin.⁷ It is surprising that Trirhabda larvae were not more sensitive to these differences in secondary chemistry among the five ploidy-origin combinations, given that Trirhabda is known to respond to host-plant chemistry.²³ We have previously reported that Trirhabda growth does not differ on European and US plants²² and show here that accounting for cytotype does not change this conclusion. In a recent study on the closely-related Solidago altissima, Halverson et al.¹¹ reported that the effects of plant cytotype on 5 gall-making herbivores were complex and not easily characterized. All five herbivores responded to plant cytotype, but for four of the five insects the most preferred cytotype was not consistent across sites. It is possible in our study that Trirhabda were responding to cytotype at a finer scale than that examined here. There may be differences due to cytotype that shift among the populations that we sampled, and that are averaged out when examined at the continental scale. We lack sufficient replication of cytotypes within populations to test this possibility. Even so, our results reported here reveal that plant cytotype can be an important source of variation affecting insect herbivores, but that generalist and specialist insects may respond differently.     

Prion interference with multiple prion isolates

Co-inoculation of prion strains into the same host can result in interference, where replication of one strain hinders the ability of another strain to cause disease. The drowsy (DY) strain of hamster-adapted transmissible mink encephalopathy (TME) extends the incubation period or completely blocks the hyper (HY) strain of TME following intracerebral, intraperitoneal or sciatic nerve routes of inoculation. However, it is not known if the interfering effect of the DY TME agent is exclusive to the HY TME agent by these experimental routes of infection. To address this issue, we show that the DY TME agent can block hamster-adapted chronic wasting disease (HaCWD) and the 263K scrapie agent from causing disease following sciatic nerve inoculation. Additionally, per os inoculation of DY TME agent slightly extends the incubation period of per os superinfected HY TME agent. These studies suggest that prion strain interference can occur by a natural route of infection and may be a more generalized phenomenon of prion strains.Key words: prion diseases, prion interference, prion strainsPrion diseases are fatal neurodegenerative diseases that are caused by an abnormal isoform of the prion protein, PrP^Sc.¹ Prion strains are hypothesized to be encoded by strain-specific conformations of PrP^Sc resulting in strain-specific differences in clinical signs, incubation periods and neuropathology.^2–7 However, a universally agreed upon definition of prion strains does not exist. Interspecies transmission and adaptation of prions to a new host species leads to the emergence of a dominant prion strain, which can be due to selection of strains from a mixture present in the inoculum, or produced upon interspecies transmission.^8,9 Prion strains, when present in the same host, can interfere with each other.Prion interference was first described in mice where a long incubation period strain 22C extended the incubation period of a short incubation period strain 22A following intracerebral inoculation.¹⁰ Interference between other prion strains has been described in mice and hamsters using rodent-adapted strains of scrapie, TME, Creutzfeldt-Jacob disease and Gerstmannn-Sträussler-Scheinker syndrome following intracerebral, intraperitoneal, intravenous and sciatic nerve routes of inoculation.^10–15 We previously demonstrated the detection of PrP^Sc from the long incubation period DY TME agent correlated with its ability to extend the incubation period or completely block the superinfecting short incubation period HY TME agent from causing disease and results in a reduction of HY PrP^Sc levels following sciatic nerve inoculation.¹² However, it is not known if a single long incubation period agent (e.g., DY TME) can interfere with more than one short incubation period agent or if interference can occur by a natural route of infection.To examine the question if one long incubation period agent can extend the incubation period of additional short incubation period agents, hamsters were first inoculated in the sciatic nerve with the DY TME agent 120 days prior to superinfection with the short-incubation period agents HY TME, 263K scrapie and HaCWD.^16–18 The HY TME and 263K scrapie agents have been biologically cloned and have distinct PrP^Sc properties.^19,20 The HaCWD agent used in this study is seventh hamster passage that has not been biologically cloned and therefore will be referred to as a prion isolate. Sciatic nerve inoculations were performed as previously described.^11,12 Briefly, hamsters were inoculated with 103.0 i.c. LD₅₀ of the DY TME agent or equal volume (2 µl of a 1% w/v brain homogenate) of uninfected brain homogenate 120 days prior to superinfection of the same sciatic nerve with either 10^4.6 i.c. LD₅₀ of the HY TME agent, 10^5.2 i.c. LD₅₀ of the HaCWD agent or 10^4.6 i.c. LD₅₀/g 263K scrapie agent (Bartz J, unpublished data).^16,18,21 Animals were observed three times per week for the onset of clinical signs of HY TME, 263K and HaCWD based on the presence of ataxia and hyperexcitability, while the clinical diagnosis of DY TME was based on the appearance of progressive lethargy.^16–18 The incubation period was calculated as the number of days between the onset of clinical signs of the agent strain that caused disease and the inoculation of that strain. The Student''s t-test was used to compare incubation periods.¹² We found that sciatic nerve inoculation of both the HaCWD agent and 263K scrapie agent caused disease with a similar incubation period to animals infected with the HY TME agent (12 In hamsters inoculated with the DY TME agent 120 days prior to superinfection with the HaCWD or 263K agents, the animals developed clinical signs of DY TME with an incubation period that was not different from the DY TME agent control group (12 The PrP^Sc migration properties were consistent with the clinical diagnosis and all co-infected animals had PrP^Sc that migrated similar to PrP^Sc from the DY TME agent infected control animal (Fig. 1, lanes 1–10). This data indicates that the DY TME agent can interfere with more than one isolate and that interference in the CNS may be a more generalized phenomenon of prion strains.Open in a separate windowFigure 1The strain-specific properties of PrP^Sc correspond to the clinical diagnosis of disease. Western blot analysis of 250 µg brain equivalents of proteinase K digested brain homogenate from prion-infected hamsters following intracerebral (i.c.), sciatic nerve (i.sc.) or per os inoculation with either the HY TME (HY), DY TME (DY), 263K scrapie (263K), hamster-adapted CWD (CWD) agents or mock-infected (UN). The unglycoyslated PrP^Sc glycoform of HY TME, 263K scrapie and hamster-adapted CWD migrates at 21 kDa. The unglycosylated PrP^Sc glycoform of DY PrP^Sc migrates at 19 kDa. Migration of 19 and 21 kDa PrP^Sc are indicated by the arrows on the left of the figure. n.a., not applicable.

Table 1

Clinical signs and incubation periods of hamsters inoculated in the sciatic nerve with either the HY TME, HaCWD or 263K scrapie agents, or co-infected with the DY TME agent 120 days prior to superinfection of hamsters with the HY TME, HaCWD or 263K agents

Metabolome-ionome-biomass interactions: What can we learn about salt stress by multiparallel phenotyping?

Long-term exposure of plants to saline soil results in mineral ion imbalance, altered metabolism and reduced growth. Currently, the interaction between ion content and plant metabolism under salt-stress is poorly understood. Here we present a multivariate correlation study on the metabolome, ionome and biomass changes of Lotus japonicus challenged by salt stress. Using latent variable models, we show that increasing salinity leads to reproducible changes of metabolite, ion and nutrient pools. Strong correlations between the metabolome and the ionome or biomass may allow one to estimate the degree of salt stress experienced by a plant based on metabolite profiles. Despite the apparently high predictive power of the models, it remains to be investigated whether such metabolite profiles of non- or moderately-stressed plants can be used by breeding programs as ideal ideotypes for the selection of enhanced salt-tolerant genotypes.Key words: acclimation, ionomic, lotus, metabolic, metabolomic, nutrients, salinity, salt stressAcclimation of plants to saline soils involves changes in the uptake, transport and/or partitioning of mineral ions.^1–3 These responses not only alter ion concentrations but also impair metabolism and growth.⁴ Exactly how metabolism as a whole changes in response to salinity is still unknown because of the complexity of the processes involved. Nevertheless, one might expect plant metabolism to respond in a predictable way to salt stress. With this in mind we carried out a multivariate correlation analysis of 137 metabolome and ionome profiles, and the corresponding biomass measurements, of shoot samples from Lotus japonicus exposed to two different salinity regimes.⁵Metabolome data obtained using GC/EI-TOF-MS technology were analyzed using the TagFinder software,⁶ resulting in a series of discrete metabolic-features. A metabolic-feature may be defined to represent a quantitative signal, measured by any analytical means or technology, which is distinct from analytical signals that arise as artefacts from electronic or chemical noise. A total of 1019 metabolic-features were obtained after filtering for those represented by 3 or more inter-correlated mass fragments.⁶ Corresponding ionomic data were obtained using ICP-AES technology and included measurements of Na and 10 macro- and micro-nutrients (K, Ca, S, P, Mg, B, Mn, Fe, Zn and Mo).⁵To integrate metabolomic and ionomic data, we used the statistical multivariate regression technique called orthogonal projections to latent structures (OPLS^7,8), which performs a regression of two matrices or a matrix versus a single variable and simultaneously corrects the resulting model for systematic, irrelevant variance. The metabolite profile matrix was regressed in three different models against the concentrations of Na, K and a matrix of all nutrients excluding K and Na. These regressions were designated metabolome-[ Na], metabolome-[K] and metabolome [nutrients-K] models, respectively. With OPLS it is possible to estimate how well associated the different metabolites are with the modeled variance of the different ions. The used measure is called the correlation loading and can be interpreted as a multivariate version of the standard Pearson correlation. In order to compare how the metabolic profiles may predict the different matrices, we regressed the correlation loadings vectors of the three different models amongst each other (Fig. 1). Remarkably, the loadings were highly correlated. Despite the high magnitude of change in K content compared to the other nutrients under salinity, the metabolome-[K] and metabolome-[nutrients-K] loadings were nearly identical, highlighting that K levels correlate strongly with the main metabolome correlated variance in the rest of the nutrient matrix. These observations suggest that salinity leads to reproducible changes in metabolite pools which match both the concentration of salt accumulated in the shoot and induced changes in the content of other elements.⁵ Since metabolome profiles have been considered a predictor of plant biomass under non-stressed growth conditions,⁹ a metabolome-biomass model was evaluated for the stress cue of our experimental setup. The metabolome data appeared to be correlated to shoot biomass in a manner similar to the predictability of [Na], [K] and [nutrients-K] (Fig. 2). Presumably, this observation reflects the property of the plant system to integrate in a highly interdependent process the nutritive elements, metabolism and growth.Open in a separate windowFigure 1Regression of the correlation loadings obtained from the models metabolome [Na], metabolome [K] and metabolome [nutrients-K].Open in a separate windowFigure 2Regression of the correlation loadings of the metabolome [Na], metabolome [K] and metabolome [nutrients-K] models with the metabolome biomass model.The correlation loadings of the models allowed a ranking of metabolite-features according to their contribution to the modeled regressions. We used the magnitude of the weight of each metabolic-feature to assess which metabolites may be more characteristic or diagnostic of salt stress, as determined by Na levels (Fig. 3).Open in a separate windowFigure 3Predictive power of the analysis, as revealed by a linear regression between the measured [Na] or biomass and the predicted [Na] or biomass from the models. The predictions were performed based on 10-fold crossvalidation, where in each segment the true values of Na content and biomass were held out and predicted from the corresponding metabolome data using the OPLS model.

Table 1

The top-most positively and negatively correlated metabolites of the metabolite [Na] regression model

Induction of systemic resistance in rice by leaf extracts of Zizyphus jujuba and Ipomoea carnea against Rhizoctonia solani

Plants accumulate a great diversity of natural products, many of which confer protective effects against phytopathogenic attack. Earlier we had demonstrated that the leaf extracts of Zizyphus jujuba and Ipomoea carnea inhibit the in vitro mycelial growth of Rhizoctonia solani, and effectively reduce the incidence of sheath blight disease in rice.⁷ Here we demonstrate that foliar application of the aqueous leaf extracts of Z. jujuba and I. carnea followed by challenge inoculation with R. solani induces systemic resistance in rice as evident from significantly increased accumulation of pathogenesis-related proteins such as chitinase, β-1,3-glucanase and peroxidase, as well as defense-related compounds such as phenylalanine ammonia-lyase and phenolic substances. Thin layer chromatographic separation of secondary metabolites revealed presence of alkaloid and terpenoid compounds in the leaf extracts of Z. jujuba that exhibited toxicity against R. solani under in vitro condition. Thus, the enhanced sheath blight resistance in rice seedlings treated with leaf extracts of Z. jujuba or I. carnea can be attributed to the direct inhibitory effects of these leaf extracts as well as their ability to elicit systemic resistance against R. solani.Key words: sheath blight, Zizyphus jujuba, Ipomoea carnea, Rhizoctonia solani, induced systemic resistance, antimicrobial compoundsSheath blight disease of rice, caused by Rhizoctonia solani, has become a major production constraint in intensive rice cropping systems where semi-dwarf, nitrogen-responsive and high-yielding rice cultivars are grown. The disease causes an annual yield loss of upto 50%.¹ R. solani is both soil- and water-borne, and can infect more than 27 families of both monocot and dicot species.² Natural host genetic resistance to R. solani has not been recorded in cultivars or wild relatives of rice.³ Several broad spectrum fungicides have been recommended for control of sheath blight, however, chemical method of disease management is neither practical due to high cost of fungicides nor sustainable as it can affect the balance of ecosystem by destroying beneficial microbial population. In addition, the environmental pollution problems associated with indiscriminate use of synthetic pesticides have prompted investigations on exploiting bio-pesticides of plant and microbial origin.Plants accumulate an enormous variety of over 100,000 secondary metabolites,⁴ which can act as pre-existing chemical inhibitors to invading pathogens and/or help strengthen defense response of host plant. The pre-formed infectional barriers in plants are generally referred to as “phytoanticipins;” whereas, the antimicrobial compounds that are synthesized de novo in response to pathogen attack are referred to as “phytoalexins.”⁵ Because of years of selective breeding leading to removal of natural products, the endogenous levels of phytoanticipins in commonly cultivated crop species are generally low and often not sufficient to fight pathogen attack, effectively.⁴ Various weed species and wild relatives of crop plants that are not subjected to selective breeding are believed to contain higher levels of antimicrobial compounds, consistent with their ability to fight invading pathogens more effectively than cultivated crop species. Identification of such weed/plant species that are enriched with antimicrobial principles, isolation of bio-active compounds from them, and application in the form of concentrated formulations to crop plants can augment their disease resistance capability by directly inhibiting the growth of pathogen and inducing defense responses. Indeed, the antimicrobial properties of tissue extracts of several weed/plant species have been reported by a number of research groups world-wide, especially in Asia and Latin America.^6–13Earlier, we had evaluated the antimicrobial activity of leaf extracts of 16 different plant species belonging to 16 different families and demonstrated that leaf extracts of most of these plant species exhibit growth-inhibitory activities against R. solani and Xanathomoas oryzae pv. oryzae (Xoo).⁷ Among these, the leaf extracts of Datura metel were found to be the most effective in inhibiting the mycelial growth and sclerotia formation of R. solani, and the growth of Xoo, as well as in reducing the incidence of sheath blight and bacterial blight diseases caused by these pathogens, respectively, under greenhouse condition.⁷ We further demonstrated that rice seedlings treated with leaf extracts of D. metel accumulated significantly higher levels of pathogenesis-related (PR) proteins and other defense related compounds following challenge inoculation with R. solani or Xoo.⁷ Our attempts to identify biologically active compounds from D. metel revealed the presence of a withanolide compound “daturilin” that exhibited remarkable antibacterial activity against Xoo.⁷Apart from D. metel, two other plants species, Zizyphus jujuba and Ipomoea carnea, were found to possess remarkable antifungal activity against R. solani.⁷ Z. jujuba is a thorny rhamnaceous plant that is widely distributed in Europe and South-eastern Asia. I. carnea of convolvulaceae family, commonly known as morning glory, is a toxic weed found in abundance in India, Brazil, the United States and other countries.¹⁴ Both of these plant species have allelopathic effect and are commonly used in folklore medicine for curing multiple diseases.^15–18 The aqueous and methanol leaf extracts of Z. jujuba and I. carnea have been found to be highly effective in reducing in vitro mycelial growth, and therefore, sclerotia production of R. solani.⁷ In the greenhouse experiments, rice seedlings sprayed with leaf extracts of Z. jujuba and I. carnea exhibited 44 and 34% reduction in severity of sheath blight disease over the control, respectively.⁷ While these findings are encouraging, the mechanisms by which the leaf extracts of Z. jujuba and I. carnea modulate defense responses in rice have not yet been explored.Plants are endowed with defense genes which remain quiescent or are expressed at basal levels in healthy plants. Activation of defense genes results in induction of systemic resistance in host plant; this defense response, designated as induced systemic resistance (ISR), plays an important role in development of disease resistance.¹⁹ The onset of ISR in plants correlates with accumulation of phytoalexins and increased activity of PR proteins such as chitinases, β-1,3-glucanases and peroxidases;^20–23 consequently, PR proteins are generally used as ISR markers.¹⁹ The classical inducers of ISR include both biotic and abiotic factors, including disease causing microorganisms themselves,^24,25 plant growth promoting rhizobacteria,^22,26 chemicals^27,28 and natural plant products.^{7,10,12,13,29,30} Plant products have been considered as one of the major groups of compounds that induce ISR. To date, extracts of at least a few plant species have been reported to contain allelopathic substances which can act as elicitors and induce systemic resistance in host plants resulting in reduction or inhibition of disease development.^7,10,12,13In the present study, with the objective of understanding the mechanisms of disease suppression by leaf extracts of Z. jujuba and I. carnea, we investigated their ability to induce ISR in rice by analyzing the activities of ISR markers including PR-proteins and other defense enzymes involved in phenylpropanoid metabolism. The changes in activities of chitinase, β-1,3-glucanase, peroxidase, phenylalanine ammonia-lyase (PAL) and phenolic compounds induced in rice seedlings that were elicited with leaf extracts (at 1:10 dilution; w/v) of Z. jujuba or I. carnea and infected with R. solani were analyzed, and compared to changes in non-elicited and uninfected seedlings. Rice seedlings that were both elicited with leaf extracts of Z. jujuba or I. carnea and infected with R. solani accumulated significantly higher levels (2–5-fold) of ISR markers as compared to non-elicited and/or uninfected seedlings (Fig. 1). About two-fold increase in activities of ISR markers was also observed in seedlings that were either infected but not elicited or elicited but not infected; however, this increase was significantly lower than the changes in seedlings that were both elicited and infected (Fig. 1). Although the activity of all ISR markers began to increase around or after 24 h post-infection, at least two distinct induction patterns were observed. For instance, the activities of chitinase and phenolic substances gradually increased to reach maximum levels at 164 h post-infection (Fig. 1A and E); whereas, the activities of β-1,3-glucanase, peroxidase and PAL reached maximum levels at 72 to 96 h post-infection and decreased thereafter (Fig. 1B–D). The leaf extracts of Z. jujuba were found slightly more effective in inducing ISR markers than the leaf extracts of I. carnea. There was no significant change in the activity of ISR markers in control seedlings sprayed with sterile distilled water (Fig. 1). Collectively, these results suggested that the leaf extracts of Z. jujuba and I. carnea have the ability to induce systemic resistance in rice seedlings infected with R. solani. The fungitoxicity of the leaf extracts of Z. jujuba and I. carnea ⁷ combined with their ability to elicit ISR is possibly responsible for low sheath blight disease incidence observed in rice seedlings treated with these leaf extracts.⁷Open in a separate windowFigure 1Activity of ISR markers and defense-related compounds in rice seedlings elicited with the leaf extracts of Zizyphus jujuba or Ipomoea carnea and challenge inoculated with Rhizoctonia solani. Total activity of chitinase (A), β-1,3-glucanase (B), peroxidase (C) phenylalanine ammonia-lyase (PAL; D) and phenolic substances (E) was analyzed in rice seedlings. The inoculation of rice seedlings with R. solani was performed 45 days after planting. Spraying of leaf extracts (1:10 dilution; w/v) of Z. jujuba or I. carnea was performed two days prior to inoculation. Tissue samples (sheath) from elicited and/or infected seedlings were collected for analysis at various time intervals.The in vitro antimicrobial and in vivo disease inhibitory effects of natural plant products are generally attributed to the allelopathic substances present in them. However, very few attempts have been made to purify and characterize active principles from bio-active natural plant products. We have previously identified a withanolide compound from leaf extracts of D. metel which exhibited antibacterial activity against Xoo.⁷ Both Z. jujuba and I. carnea are rich source of secondary metabolites including alkaloids, terpenoids, flavonoids and phenolic compounds.^31–35 To determine the composition of bio-active ingredients within the leaf extracts of Z. jujuba and I. carnea, we performed thin layer chromatographic separation of alkaloid, terpenoid and phenolic compounds. The partially purified compounds, as reported in Leaf extractR_f valueAnti-fungal activity against R. solani^*VisibleIodine vaporsUV-lightSpray reagentPhenolic substances¹Z. jujuba0.6960.696-0.696-I. carnea-0.807-0.807-Terpenoid compounds²Z. jujuba---0.189-0.3580.3580.3580.3585.1 mm---0.4463.7 mmI. carnea-0.5900.5900.590-Alkaloid compounds³Z. jujuba-0.784-0.7845.1 mmI. carnea-0.806-0.806-Open in a separate window^*Inhibition zone diameter (mm) as mean of triplicate tests.¹Solvent-acetic acid:chloroform (1:9); Spray reagent-Diazotised sulphanilic acid.²Solvent-methanol:chloroform (2:9); Spray reagent-10% vanillin-sulphuric acid.³Solvent-methanol:chloroform (1:1); Spray reagent-Drag endorffs reagent.In conclusion, our results together with several other reports in the literature have established that natural plant products possess antimicrobial substances that can inhibit the growth of the pathogens and augment disease resistance capability of plants by eliciting ISR in host plants. In the immediate future, identification and characterization of additional novel bio-active compounds from natural plant products is essential for developing commercial formulations of potential use in controlling pathogenic diseases in crop plants.Rice cultivar, IR-50 (susceptible to sheath blight) and virulent isolate of R. solani (RS7 Anastamosis group AG1),³⁶ were used in all experiments. The leaf tissues of Z. jujuba and I. carnea were collected from local areas around Coimbatore, India and aqueous extracts were prepared, as described previously in reference ⁷. Forty-five-day-old rice seedlings were sprayed with either aqueous leaf extracts (1:10 dilution) or sterile distilled water, two-days prior to inoculation with sclerotia of R. solani.³⁷ Sheath tissues from infected seedlings were collected at various time intervals, including 0, 24, 48, 72, 96 and 164 h after pathogen inoculation. The changes in the chitinase and peroxidase activities were determined by colorimetric assays, as described previously by Boller and Mauch,³⁸ and Hammerschmidt et al.³⁹ respectively. β-1,3-glucanase activity was assayed by the laminarin-dinitrosalicylic acid method.⁴⁰ PAL activity was determined as the rate of conversion of L-phenylalanine to trans-cinnamic acid at 290 nm as described by Dickerson et al.⁴¹ The amount of trans-cinnamic acid synthesized was calculated using its extinction coefficient of 9,630 M⁻¹. Estimation of phenolic substances was carried out as described previously in reference ⁷.TLC was carried out on 20 × 20 cm glass plate coated with0.5 mm thickness silica gel. Twenty microliters of Z. jujuba and I. carnea leaf extracts (1 g/ml) were spotted on each plate. The mixture of solvents comprising acetic acid:chloroform (1:9), methanol:chloroform (2:9) or methanol:chloroform (1:1) were used to develop the chromatograms for detection of phenolic, terpenoid or alkaloid compounds, respectively. The developed chromatograms were observed under visible, UV light and after exposing to iodine vapours. Additionally, the chemical class specific visualization spray reagents were used for detection of phenolic substances (Diazotized sulphanilic acid), terpenoids (10% vanillin-sulphuric acid) and alkaloids (Dragendorffs reagent). Preparative TLC was carried out using 2 mm thickness silica gel. The Rf value of each spot detected on the chromatogram was recorded. The silica gel corresponding to each spot was scraped off and the chemical compound was eluted using sterile water. The eluted compound was tested for its antimicrobial activity using the inhibition zone technique.⁴²     

Aluminum induced proteome changes in tomato cotyledons

Cotyledons of tomato seedlings that germinated in a 20 µM AlK(SO₄)₂ solution remained chlorotic while those germinated in an aluminum free medium were normal (green) in color. Previously, we have reported the effect of aluminum toxicity on root proteome in tomato seedlings (Zhou et al.¹). Two dimensional DIGE protein analysis demonstrated that Al stress affected three major processes in the chlorotic cotyledons: antioxidant and detoxification metabolism (induced), glyoxylate and glycolytic processes (enhanced), and the photosynthetic and carbon fixation machinery (suppressed).Key words: aluminum, cotyledons, proteome, tomatoDifferent biochemical processes occur depending on the developmental stages of cotyledons. During early seed germination, before the greening of the cotyledons, glyoxysomes enzymes are very active. Fatty acids are converted to glucose via the gluconeogenesis pathway.^2,3 In greening cotyledons, chloroplast proteins for photosynthesis and leaf peroxisomal enzymes in the glycolate pathway for photorespiration are metabolized.^2–4 Enzymes involved in regulatory mechanisms such as protein kinases, protein phosphatases, and mitochondrial enzymes are highly expressed.^3,5,6The chlorotic cotyledons are similar to other chlorotic counterparts in that both contains lower levels of chlorophyll, thus the photosynthetic activities are not as active. In order to understand the impact of Al on tomato cotyledon development, a comparative proteome analysis was performed using 2D-DIGE following the as previously described procedure.¹ Some proteins accumulated differentially in Al-treated (chlorotic) and untreated cotyledons (Fig. 1). Mass spectrometry of tryptic digestion fragments of the proteins followed by database search has identified some of the differentially expressed proteins (Open in a separate windowFigure 1Image of protein spots generated by Samspot analysis of Al treated and untreated tomato cotyledons proteomes separated on 2D-DIGE.

Table 1

Proteins identified from tomato cotyledons of seeds germinating in Al-solution

Multi-element fingerprinting and high throughput sequencing identify multiple elements that affect fungal communities in Quercus macrocarpa foliage

Diverse fungal mutualists, pathogens and saprobes colonize plant leaves. These fungi face a complex environment, in which stochastic dispersal interplays with abiotic and biotic filters. However, identification of the specific factors that drive the community assembly seems unattainable. We mined two broad data sets and identified chemical elements, to which dominant molecular operational taxonomic units (OTUs) in the foliage of a native tree respond most extremely. While many associations could be identified, potential complicating issues emerged. Those were related to unevenly distributed OTU frequency data, a large number of potentially explanatory variables and the disproportionate effects of outlier observations.Key words: community assembly, environmental filter, fungi, heavy metal enrichment, nutrient enrichment, oak, Quercus macrocarpaHyperdiverse fungal communities inhabit the foliage of most plants^1,2 and these fungal communities have been reported for virtually every plant that has been examined.³ Baas-Becking hypothesis states that environment selects microbial communities from the abundant and possibly globally distributed propagule pools.⁴ Although the foliage-associated communities—like other microbial communities—are suspected to be sensitive to environmental drivers, determination of the mechanisms that control the assembly of these foliar communities has remained difficult and elusive. Some of the proposed mechanisms include distance limitations to propagule dispersal,^5–7 volume limitations to propagule loads,⁷ or limitations set by the environmental conditions either on the scale of the site of fungal colonization⁸ or more broadly on a landscape level.^6,9 The forces that may control the fungal community assembly are overlaid by additional biotic controls that include compatibilities between the fungi and host species^10,11 or genotypes^6,12 and the competitive or facilitative interactions among the component fungal genotypes.^6,10–13 Although a variety of potential controls for the foliage-associated fungal communities have been speculated, very little consensus exists on the relative importance of the different drivers. For example, while macronutrient and heavy metal enrichment may have an influence on the composition fungal communities¹⁴ and populations,¹⁵ relative importance of various chemical elements in the foliage remains yet to be investigated.To evaluate the use of multi-element fingerprinting data produced by Inductively Coupled Plasma Mass Spectrometry (ICP-MS) in combination with high throughput 454-pyrosequencing for determining influential chemical elements in structuring of the leaf-associated fungal communities, we mined a recent dataset¹⁶ that explored the effects of urbanization on the diversity and composition of the fungal communities associated with a native tree Quercus macrocarpa. From a total list of more than 700 non-singleton fungal OTUs, we selected fifty with highest overall frequency to provide an observationrich dataset for elemental effect assessment; these OTUs accounted for 84.5% of all sequences. Even so, many of these OTUs had a number of zero frequencies (Fig. 1), highlighting one of the difficulties in the use of environmental sequencing data. We omitted one OTU (OTU630 with a likely affinity to Trimmatostroma cordae [Mycosphaerellaceae]) that was strongly affected by the original land use design (urbanization; Wilcoxon rank sum test with a Bonferroni adjustment) and therefore unlikely to be representative for the present analyses of elemental drivers. This OTU was replaced with one with the next highest frequency. The frequencies of these 50 OTUs were investigated in the context of concentrations for 29 elements after the omission of five (Ag, Au, C, δ¹³C, δ¹⁵N) in the final analyses because of their strong association with the land use or the difficulty of finding a biological relevance. Of the remaining elements three (Fe, Cr and Ni) had pairwise correlations exceeding 0.98 between the three pairings; others showed no similar high correlations. To allow comparable evaluation across the broad array of elements, all concentrations were standardized to have a mean equal to zero and a standard deviation equal to one.Open in a separate windowFigure 1Rank-ordered distribution of observed frequencies for those OTU s whose frequency had an extreme slope when associated with the concentrations of one or more chemical elements in the mixed effects model. The asterisk denotes one extreme frequency for OTU 313 with a value 0.8636. Numbers in parentheses indicate the number of observations with a frequency equal to zero. The OTU s were assigned to approximate taxa using BLAST:²⁰ 425: Alternaria alternata (Pleosporaceae); 46: Phoma glomerata (Pleosporaceae); 686: Aureobasidium pullulans (Dothioraceae); 520: Davidiella tassiana (Davidiellaceae); 567: Cladosporioum tenuissimum (Davidiellaceae); 313 Oidium heveae (mitosporic Erysiphaceae); 586: Erysiphe hypogena (Erysiphaceae); 671: Mycosphaerella microsora (Mycosphaerellaceae); 555: Pestalotiopsis sp. (Amphisphaeriaceae); 607: Pleiochaeta setosa (incertae sedis).To rank elements according to their magnitude of association with the abundance of each OTU, a total of 1,450 models (50 OTUs times 29 elements) relating element concentration to OTU abundance were fit to the data. For each model, OTU frequency was the dependent variable, element concentration and time (a factor with three levels) were fixed effects, and—to account for the spatial arrangement of the experimental units—random effects associated with tree nested within site were included in the error structure. Time by element interactions were also investigated and tested using a likelihood ratio test. These mixed effect models were fit using R and the package lme4 (www.rproject.org).Statistical “tests of significance” that produce p-values can be sensitive to assumptions or outliers. Because of this and the fact that our analyses evaluated a total of 1,450 models, p-values themselves were not considered a reliable measure of importance when associating elements with OTU frequency. Instead, we emphasized metrics that highlight extraordinary findings rather than rely on tests of statistical significance. This approach facilitates finding few elements that have the strongest effect on OTU frequency. Note that the use of standardized element concentrations (above) provided slope coefficients that are comparable across all models. “Extreme slopes”, i.e., models where the OTU response to element concentration was strongest, were identified as those with estimated slope coefficients in the lower or upper 2.5 percentile, i.e., those farther than 1.8 standard deviations from the mean across all estimated slopes (Fig. 2). Using this approach, we identified a total of 69 models with extreme slopes (Open in a separate windowFigure 2Distribution of estimated slopes (i.e., the slope for element concentration) for a model relating OTU frequency to element concentration, time and a concentration by time interaction, including a tree-nested-within-site random effect. The mean across all 1,450 OTU s is approximately zero; the two vertical lines identify upper and lower 2.5 percentiles, beyond which the slopes were considered extreme (large black symbols). The horizontal line identifies the cut off maximum leverage (0.24), above which the slopes were considered to have observations with high leverage. Models with observations with a high leverage were tested for extreme slopes by refitting without those observations. Models are ranked from bottom to top in order of increasing leverage and the element for which the high-leverage observations and extreme slopes were recorded are identified on the right y-axis.

Table 1

Slopes identified as extreme in our analyses

Specificity of induction responses in Sinapis alba L.: Plant growth and development

Plant defenses are expected to be negatively correlated with plant growth, development and reproduction. In a recent study, we investigated the specificity of induction responses of chemical defenses in the Brassicaceae Sinapis alba.¹ It was shown that glucosinolate levels and myrosinase activities increased to different degrees after 24-hours-feeding by a specialist or generalist herbivore or mechanical wounding. Here, we present the specific influences of these treatments on organ biomasses which were recorded as a measure of growth. Directly after the treatments, organ biomasses were reduced locally and systemically by herbivore feeding, but not by mechanical wounding compared to control plants. Induction of glucosinolates, which increased in all treatments, is thus not necessarily expressed as cost in terms of reduced growth in S. alba. No significant long-term differences in plant development between herbivore treated and control plants were found. Thus, tissue loss and increased investments in chemical defenses could be compensated over time, but compensation patterns depended on the inducing agent. Furthermore, herbivore treatments resulted in an increased mechanical defense, measured as abaxial trichome densities. Plants respond highly dynamic with regard to defense and growth allocation and due to different inductors.Key words: Brassicaceae, organ biomass, plant development, specialist, generalist, herbivore, mechanical wounding, costs, trichome densityPlant defenses are generally thought to impose costs in relation to growth and fitness.² The ability to increase defense levels only after herbivory, i.e., induction, is one possible mechanism of lowering these allocation costs.³ In Brassicaceae, the glucosinolate-myrosinase system is known to hold a defensive function.⁴ The constitutive and induced production of glucosinolates and myrosinases is thought to be connected to allocation and ecological costs.^2,5In a recent study, we investigated the specificity of short-term induction patterns of chemical defenses in Sinapis alba L. var. Silenda damaged by a glucosinolate-sequestering specialist herbivore (turnip sawfly, Athalia rosae (L.), Hymenoptera), a generalist herbivore (fall armyworm, Spodoptera frugiperda J. E. Smith, Lepidoptera) or mechanical wounding (cork borer).¹ Feeding by the specialist as well as mechanical wounding led to 3-fold increases in both glucosinolate- and myrosinase-levels, whereas generalist feeding induced up to 2-fold increases in glucosinolates only.Different strengths of plant chemical responses might be mirrored in differences of subsequent fitness-related parameters of the plants.⁶ To assess short-term effects within 24 hours of induction on organ growth in S. alba, organ dry biomasses were calculated from the previous plant set.¹ Water content was determined of the organ halves which were freeze-dried and analyzed for glucosinolate content¹ and organ dry weights were calculated from water content and total organ fresh weight. The percentage of removed tissue area was determined by photo analysis and organ dry weights of treated leaves were corrected for the respective area. The percentage of lost area in damaged leaves was 7.9 ± 0.5 % after mechanical wounding, 15.1 ± 2.3 % after feeding by S. frugiperda and 15.6 ± 2.3 % after feeding by A. rosae (mean values ± SE, n = 7–8). The plants'' habits and total number of leaves did not vary between the tested plant groups (Fig. 1B; ANOVA: f = 2.36, df = 3, p = 0.095).Open in a separate windowFigure 1Organ dry biomasses of leaves and stems (A) and total numbers of leaves (B) of Sinapis alba cv. Silenda directly after induction. The second youngest leaves of three weeks old plants were treated with either mechanical wounding (cork borer), one Spodoptera frugiperda caterpillar (third instar) or one larva of Athalia rosae (third instar) enclosed in a muslin bag for 24 hours. Bagged leaves without any further treatment served as controls (mean values ± SE, n = 6–8 per treatment). Letters above bars indicate significant differences (ANOVA, Tukey-HSD tests: p < 0.05; n.s., not significant). DL, damaged leaf; OL, older leaf; YL, younger leaf; OS, older stem; YS, younger stem.The short-term growth responses were highly specific between treatments. Herbivore damage did not only result in reduced organ biomass growth of the damaged leaf (ANOVA: f = 11.29, df = 3, p < 0.001), but also of adjacent tissues compared to organs from bag treated and mechanically wounded plants after 24 hours of treatment (Fig. 1A; older leaf - ANOVA: f = 3.87, df = 3, p = 0.021; younger leaf - ANOVA: f = 6.02, df = 3, p = 0.003; younger stem - ANOVA: f = 4.12, df = 3, p = 0.017). Significant differences from bag treated control plants were found for damaged and systemic younger leaves of plants treated with A. rosae larvae. Differences of organ dry biomasses between mechanically wounded and herbivore treated plants were more pronounced, with reduced growth in the latter of 15 to 36 % in leaves and 23 to 48 % in stem parts. This specificity in growth response could be brought about by elicitors introduced to the wounded plant tissues from the herbivores'' saliva which can influence C-allocation to roots.⁷ The reduced growth of organ biomasses observed in herbivore treated leaves could be the result of specifically saliva elicited resource allocation away from leaf tissue,⁸ and might not represent costs of increased chemical defense.Long-term effects of herbivore feeding on development of S. alba were monitored in a second set of plants which were treated (as described previously in ref. ¹) for 24 hours with either the specialist or the generalist, enclosed in a bag. About three weeks later, on the day when the first flower opened, several parameters were recorded (9^,10 Thereby, thresholds for damage seem to exist, beyond which no compensation of tissue loss is possible.¹¹ The percentages of damage in S. alba were, however, below the threshold values reported for other Brassicaceae.¹¹ Influences on growth rates can be obviously transitory. In Arabidopsis thaliana (L.) Heynh., reduced growth rates were observed directly after treatment, but later growth increased so much, that these plants overcompensated and were even larger than control plants.⁹ Such plastic plant responses can be again modified by elicitors.^7,12

Table 1

Developmental responses of 3-week-old Sinapis alba plants treated for 24 hours with either one larva of the specialist Athalia rosae or one caterpillar of the generalist Spodoptera frugiperda