Detoxification and Transcriptome Response in Arabidopsis Seedlings Exposed to the Allelochemical Benzoxazolin-2(3H)-one
2005; Elsevier BV; Volume: 280; Issue: 23 Linguagem: Inglês
10.1074/jbc.m500694200
ISSN1083-351X
AutoresScott R. Baerson, Adela M. Sánchez‐Moreiras, Nuria Pedrol, Margot Schulz, Isabelle A. Kagan, Ameeta K. Agarwal, Manuel J. Reigosa, Stephen O. Duke,
Tópico(s)Plant Parasitism and Resistance
ResumoBenzoxazolin-2(3H)-one (BOA) is an allelochemical most commonly associated with monocot species, formed from the O-glucoside of 2,4-dihydroxy-2H-1,4-benzoxazin-3(4H)-one by a two-step degradation process. The capacity of Arabidopsis to detoxify exogenously supplied BOA was analyzed by quantification of the major known metabolites BOA-6-OH, BOA-6-O-glucoside, and glucoside carbamate, revealing that detoxification occurs predominantly through O-glucosylation of the intermediate BOA-6-OH, most likely requiring the sequential action of as-yet-unidentified cytochrome P450 and UDP-glucosyltransferase activities. Transcriptional profiling experiments were also performed with Arabidopsis seedlings exposed to BOA concentrations, representing I50 and I80 levels based on root elongation inhibition assays. One of the largest functional categories observed for BOA-responsive genes corresponded to protein families known to participate in cell rescue and defense, with the majority of these genes potentially associated with chemical detoxification pathways. Further experiments using a subset of these genes revealed that many are also transcriptionally induced by a variety of structurally diverse xenobiotic compounds, suggesting they comprise components of a coordinately regulated, broad specificity xenobiotic defense response. The data significantly expand upon previous studies examining plant transcriptional responses to allelochemicals and other environmental toxins and provide novel insights into xenobiotic detoxification mechanisms in plants. Benzoxazolin-2(3H)-one (BOA) is an allelochemical most commonly associated with monocot species, formed from the O-glucoside of 2,4-dihydroxy-2H-1,4-benzoxazin-3(4H)-one by a two-step degradation process. The capacity of Arabidopsis to detoxify exogenously supplied BOA was analyzed by quantification of the major known metabolites BOA-6-OH, BOA-6-O-glucoside, and glucoside carbamate, revealing that detoxification occurs predominantly through O-glucosylation of the intermediate BOA-6-OH, most likely requiring the sequential action of as-yet-unidentified cytochrome P450 and UDP-glucosyltransferase activities. Transcriptional profiling experiments were also performed with Arabidopsis seedlings exposed to BOA concentrations, representing I50 and I80 levels based on root elongation inhibition assays. One of the largest functional categories observed for BOA-responsive genes corresponded to protein families known to participate in cell rescue and defense, with the majority of these genes potentially associated with chemical detoxification pathways. Further experiments using a subset of these genes revealed that many are also transcriptionally induced by a variety of structurally diverse xenobiotic compounds, suggesting they comprise components of a coordinately regulated, broad specificity xenobiotic defense response. The data significantly expand upon previous studies examining plant transcriptional responses to allelochemicals and other environmental toxins and provide novel insights into xenobiotic detoxification mechanisms in plants. Allelopathy, the chemical inhibition of one plant species by another, represents a form of chemical warfare between neighboring plants competing for limited light, water, and nutrient resources (1Bais H.P. Park S.W. Weir T.L. Callaway R.M. Vivanco J.M. Trends Plant Sci. 2004; 9: 26-32Abstract Full Text Full Text PDF PubMed Scopus (646) Google Scholar, 2Inderjit Duke S.O. Planta. 2003; 217: 529-539Crossref PubMed Scopus (497) Google Scholar, 3Weston L.A. Duke S.O. Crit. Rev. Plant Sci. 2003; 22: 367-389Crossref Scopus (363) Google Scholar). Allelopathic interactions have been proposed to have profound effects on the evolution of plant communities through the loss of susceptible species via chemical interference and by imposing selective pressure favoring individuals resistant to inhibition from a given allelochemical (1Bais H.P. Park S.W. Weir T.L. Callaway R.M. Vivanco J.M. Trends Plant Sci. 2004; 9: 26-32Abstract Full Text Full Text PDF PubMed Scopus (646) Google Scholar, 4Schulz M. Wieland I. Chemoecology. 1999; 9: 133-141Crossref Scopus (55) Google Scholar). In addition, allelochemicals released by grain crop species such as barley, rye, and sorghum are thought to play a significant role in their efficacy as weed suppressants when used as cover crops or within intercropping systems (3Weston L.A. Duke S.O. Crit. Rev. Plant Sci. 2003; 22: 367-389Crossref Scopus (363) Google Scholar, 5Duke S.O. Rimando A.M. Baerson S.R. Scheffler B.E. Ota E. Belz R.G. J. Pestic. Sci. 2002; 27: 298-306Crossref Scopus (33) Google Scholar). Despite the ecological and agronomic importance of this class of natural products, relatively little is known concerning the molecular target sites mediating their toxicity or the adaptive strategies mounted by plants in defense against these compounds. Furthermore, in comparison to other areas of chemical ecology, molecular and genomics based approaches have seldom been employed in the field of allelopathy. One recent exception is the use of DNA microarrays to characterize the transcriptome response of Arabidopsis seedlings exposed to (–)-catechin, an allelochemical identified in root exudates of Centaurea maculosa (6Bais H.P. Vepachedu R. Gilroy S. Callaway R.M. Vivanco J.M. Science. 2003; 301: 1377-1380Crossref PubMed Scopus (923) Google Scholar). Benzoxazinoids and their benzoxazolinone derivatives represent one of the more intensively studied classes of allelochemicals (7Sicker D. Frey M. Schulz M. Gierl A. Int. Rev. Cytol. 2000; 198: 319-346Crossref PubMed Google Scholar, 8Friebe A. J. Crop Prod. 2001; 4: 379-400Crossref Scopus (33) Google Scholar). For example, the genes encoding all of the enzymes required for the biosynthesis of the benzoxazinoid 2,4-dihydroxy-7-methoxy-2H-1,4-benzoxazin-3(4H)-one have been identified in corn via transposon tagging, and they represent the first known example of a plant secondary metabolic pathway organized as a gene cluster (9Frey M. Chomet P. Glawischnig E. Stettner C. Grun S. Winklmair A. Eisenreich W. Bacher A. Meeley R.B. Briggs S.P. Simcox K. Gierl A. Science. 1997; 277: 696-699Crossref PubMed Scopus (540) Google Scholar). The biosynthesis of benzoxazinoids, particularly in young seedlings, is generally associated with cereals such as corn, rye, and wheat but have also been identified in species of Acanthaceae, Ranunculaceae, and Scrophulariaceae (7Sicker D. Frey M. Schulz M. Gierl A. Int. Rev. Cytol. 2000; 198: 319-346Crossref PubMed Google Scholar). Benzoxazinoids and benzoxazolinones act as defense compounds against microbial pathogens as well as insect herbivores, and within the rhizosphere they play an important role as allelochemicals (7Sicker D. Frey M. Schulz M. Gierl A. Int. Rev. Cytol. 2000; 198: 319-346Crossref PubMed Google Scholar, 8Friebe A. J. Crop Prod. 2001; 4: 379-400Crossref Scopus (33) Google Scholar). Formation of the benzoxazolinone, benzoxazolin-2(3H)-one (BOA), 1The abbreviations used are: BOA, benzoxazolin-2(3H)-one; DIBOA, 2,4-dihydroxy-2H-1,4-benzoxazin-3(4H)-one; ABC, ATP binding cassette; MATE, multidrug and toxic compound extrusion; MFS, major facilitator superfamily; AKR, aldo-keto reductase; GSTs, glutathione S-transferases; UGTs, UDP-glucosyltransferases; AhR, aryl hydrocarbon receptor; RT, reverse transcription; 2,4-D, 2,4-dichlorophenoxyacetic acid. results from a two-step degradation of the glucoside of DIBOA (2,4-dihydroxy-2H-1,4-benzoxazin-3(4H)-one; see Fig. 1). Numerous plant species exhibit tolerance to benzoxazinoids, such as BOA, and can rapidly metabolize them to less phytotoxic glucoside and glucoside carbamate derivatives (Fig. 1), potentially due to having co-evolved in association with allelopathic species within the same communities (4Schulz M. Wieland I. Chemoecology. 1999; 9: 133-141Crossref Scopus (55) Google Scholar). A primary response to the presence of xenobiotic compounds in both prokaryotic and eukaryotic organisms involves the induction of detoxifying enzymes and transporters, which facilitate the inactivation and elimination of toxins, and the associated metabolic processes can be divided into discrete phases (10Parkinson A. Klaassen C.D. Toxicology: The Basic Science of Poisons. McGraw-Hill Inc., New York1996: 113-186Google Scholar, 11Coleman J.O.D. Blake-Kalff M.M.A. Emyr Davies T.G. Trends Plant Sci. 1997; 2: 144-151Abstract Full Text PDF Scopus (528) Google Scholar, 12Sandermann Jr., H. Altman A. Plant Biotechnology and In Vitro Biology in the 21st Century. Kluwer Academic Publishers Group, Dordrecht, Netherlands1999: 321-328Google Scholar). In phase I, compounds are typically modified such that a functional group such as a hydroxyl moiety is added or exposed through the action of hydrolases, cytochrome P450s, or peroxidases. 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In plant systems, it is also well established that the expression of specific genes involved in processes related to the detoxification of allelochemicals and synthetic herbicides can be induced in the presence of these compounds (18Cole D.J. Edwards R. Roberts T. Metabolism of Agrochemicals in Plants. John Wiley & Sons Ltd., Hoboken, NJ2000: 108-154Google Scholar); however, evidence for the existence of integrated, coordinately regulated chemical detoxification gene networks, such as those identified in animal systems, is scarce. Furthermore, the signaling components involved in plant responses to xenobiotic stress have not been identified at present. An important class of agrichemicals, the herbicide safeners, may act as potent inducers of these signaling pathways, thereby rendering crops less susceptible to herbicide-induced injury (19Davies J. Caseley J.C. Pestic. Sci. 1999; 55: 1043-1058Crossref Google Scholar, 20, Ramsey, R. J. L., Mena, F. L., and Stephenson, G. R. 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In the present work we have focused on the analysis of the physiological response, detoxification pathways, and transcriptome responses in Arabidopsis seedlings exposed to the model benzoxazolinone allelochemical BOA. Feeding studies using exogenously supplied BOA revealed that detoxification in Arabidopsis occurs predominantly through O-glucosylation of the intermediate BOA-6-OH, most likely requiring the sequential action of as-yet-unidentified cytochrome P450 and UDP glucosyltransferase activities. Transcriptional profiling experiments using microarrays representing ∼24,000 transcripts identified a significant number of genes potentially involved in phase I, II, and III detoxification processes that are induced following exposure to this allelochemical. By using a subset of these genes, we further demonstrate their induction in response to a variety of structurally diverse xenobiotic compounds, suggesting they comprise components of a general xenobiotic response network. These data significantly expand upon previous studies examining plant transcriptional responses to allelochemicals and other environmental toxins and provide a foundation for elucidating both the enzymes and regulatory mechanisms involved. BOA Metabolite Studies—Seeds of A. thaliana (Col-0) were germinated in a mixture of sand, mold, and Perlite (4:4:2) and then maintained in a greenhouse at 20 °C for a period of 3 weeks. Under these conditions, plants did not initiate flowering during this time period. Approximately 30 plants per experimental group were carefully removed from the potting media to avoid root damage and then washed extensively to remove soil particles. Incubations with BOA (Sigma) were performed for 24 h, as described previously (4Schulz M. Wieland I. Chemoecology. 1999; 9: 133-141Crossref Scopus (55) Google Scholar), using 10, 100, 250, and 500 μm treatment solutions. After incubation, plants were rinsed, dried between paper sheets, and then weighed. Plant material was ground in 100% methanol using a mortar and pestle with quartz sand. Homogenates were then centrifuged for 15 min at 4 °C, 10,000 × g, and the volumes of the supernatants were determined. The extracts were analyzed for detoxification products by high pressure liquid chromatography using a model 126 chromatograph (Beckman Instruments, Fullerton, CA) equipped with a diode array detector (model 168) and an Ultrasphere ODS RP 18 column. Compounds were eluted with the following gradients: 1 min, 100% eluent A (0.1% trifluoroacetic acid in H2O); 1–21 min, 20% eluent B (methanol) linear; 21–41 min, 80% eluent B linear; 41–43 min, 100% eluent B linear, using a flow rate of 1 ml/min. The detection wavelengths used were 280 and 405 nm. Major metabolites were identified by co-chromatography with natural BOA-6-O-glucoside and with synthetic BOA-6-OH and glucoside carbamate prepared as described previously (4Schulz M. Wieland I. Chemoecology. 1999; 9: 133-141Crossref Scopus (55) Google Scholar, 26Sicker D. Schneider B. Hennig L. Knop M. Schulz M. Phytochemistry. 2001; 58: 819-825Crossref PubMed Scopus (36) Google Scholar). These compounds were also used as external standards for quantification. BOA Treatments for Growth Inhibition and Microarray Studies—For all BOA growth inhibition and microarray experiments, aseptically germinated A. thaliana (Col-0) seedlings were maintained in a growth chamber at 21 °C under a 16-h photoperiod and light intensity of 150 μmol m–2 s–1. Seeds were surface-sterilized in 70% ethanol for 5 min and then rinsed two times in sterile distilled water, followed by treatment with 0.5× bleach (3% sodium hypochlorite) and 0.05% Tween 20 for 10 min, and then finally rinsed four times in sterile distilled water. Following surface sterilization, seeds were placed on top of an ∼2.0-cm-high stack of 9.0-cm Whatman No. 4 filter disks and allowed to air-dry in a sterile hood. Liquid and semi-solid germination media used for all experiments contained 0.5 × Murashige and Skoog salts, 1× Gamborg's B5 vitamins, and 1.0% sucrose (w/v), adjusted to pH 5.7 with KOH. Semi-solid media also contained 1.0% (w/v) agar. For root elongation assays, seeds were placed in a horizontal line ∼2.0 cm from the edge in 9.0 × 9.0 × 1.5-cm square Petri dishes containing semi-solid germination media supplemented with different concentrations of BOA. Control plates contained solvent alone (0.1% ethanol). Plates were cold-treated for 3 days, transferred to a growth chamber, and then maintained in a vertical position for 10 days, at which time root lengths were scored. All BOA and control treatments were performed in duplicate; each replicate consisted of 25 seedlings. For BOA treatments prior to microarray analyses, ∼200 seeds were scooped into a microspatula and then distributed evenly over the surface of a sterile 0.3-μm microporous membrane raft supported by a buoyant float (Osmotek Ltd., Rehovat, Israel). Seeds, rafts, and floats were placed on liquid germination media in Lifeguard tissue culture vessels with 4.0-cm vented lids (Osmotek Ltd., Rehovat, Israel), cold-treated for 3 days, and then transferred to a growth chamber. After 10 days, BOA (or 0.1% ethanol for control treatments) was added to the media and then the vessels were returned to the growth chambers until harvest. At the end of the treatment period, seedlings were removed from the vessels, flash-frozen in liquid nitrogen, and then stored at –80 °C prior to analysis. Chemical Treatments for Real Time PCR Assays—Follow-up chemical treatments for quantitative real time PCR experiments were performed as described above for microarray experiments. Ten-day-old seedlings grown on floating microporous membrane/raft assemblies were exposed to two different concentrations of fenclorim (Toronto Research Chemicals, Inc., Ontario, Canada), benoxacor (Sigma), 2,4-dichlorophenoxyacetic acid (Sigma), phenobarbital (Sigma), p-hydroxybenzoic acid (sodium salt; Sigma), and 4-dimethylaminoantipyrine (free base; Sigma). For 2,4,5-trichlorophenol (Sigma), due to extensive injury observed on seedlings exposed to 10 mm treatments, only 100 μm treatments were used. Stock solutions were prepared in either Me2SO or ethanol and then added to seedlings growing on liquid media as described above in duplicate treatments. Control treatments (0.25% ethanol and 0.5% Me2SO) were also performed in duplicate. At 24 h post-treatment, seedlings were flash-frozen in liquid nitrogen and stored at –80 °C prior to analysis. RNA Isolation—Total RNAs for use in microarray experiments were isolated from 0.5 g of flash-frozen, pulverized 10-day-old seedling tissues using the Trizol reagent (Invitrogen), with an additional homogenization step of 30 s at 25,000 rpm using a hand held homogenizer. The RNA recovered was then re-purified with an RNeasy plant mini-kit (Qiagen, Valencia, CA) per the manufacturer's instructions. RNA recovery and purity were determined spectrophotometrically, and sample integrity was assessed by agarose gel electrophoresis. Total RNAs for real time PCR experiments shown in Fig. 5 were isolated from 50 mg of flash-frozen, pulverized 10-day-old seedling tissues using an RNeasy plant mini-kit, with an additional homogenization step of 30 s at 25,000 rpm as described above. The RNA samples were also treated with DNase I "on column" using an RNase-free DNase kit as per the manufacturer's instructions (Qiagen, Inc., Valencia, CA) to remove residual DNA contamination. RNA recovery and purity were also determined spectrophotometrically for these samples, and sample integrity was also assessed by agarose gel electrophoresis. Microarray Hybridization and Analysis—Microarray hybridizations were performed for three independent replicates with Affymetrix Arabidopsis ATH1 Genome Arrays, using protocols described by Affymetrix, Inc. (Santa Clara, CA). GeneTraffic software (Iobion Informatics, La Jolla, CA) was used to conduct a two-class comparison analysis on normalized and log-transformed signal values obtained from Affymetrix Microarray Suite software version 5.0. A significance analysis test (unpaired t test with Benjamini-Hochberg false discovery rate correction) was performed to test the equality of the mean signal values between the two classes. Means for each class were then inverse-transformed to provide a geometrical mean as an overall estimate of expression. In this manner, a more robust estimate of overall expression, less impacted by outliers or skewed expression levels (as compared with a simple arithmetic average of the raw signal values from each array), was obtained. Fold change was then calculated as the simple ratio of overall signal values from the two classes. Genes with p values of ≤0.05 were considered to be significantly differentially expressed. Genes that were common to both the I50 and I80 data were identified. A floor adjustment of 64 was applied to genes with very low signal values to avoid artifactually large fold change calculations. Genes that were induced or repressed by at least 2.5-fold in either the I50 or I80 data were identified and retained for further analysis. Differentially expressed genes, thus identified, were then annotated using the NetAffx data base provided by Affymetrix (www.affymetrix.com). In some cases the annotations of unknown genes were further refined by performing additional BLAST searches or updated as additional literature reports became available. Quantitative Real Time RT-PCR Assays—First strand cDNAs were synthesized from 2 μg of total RNA in a 100-μl reaction volume using the TaqMan reverse transcription reagents kit (Applied Biosystems, Foster City, CA) as per the manufacturer's instructions. Quantitative real time PCRs were performed in triplicate using the GenAmp® 5700 sequence detection system (Applied Biosystems). Independent PCRs were performed using the same cDNA for both the gene of interest and 18 S rRNA, using the SYBR® Green PCR Master Mix (Applied Biosystems). Gene-specific primers were designed for the gene of interest and 18 S rRNA using Primer Express® software (Applied Biosystems) and the Amplify program (27Engels W.R. Trends Biochem. Sci. 1993; 18: 448-450Abstract Full Text PDF PubMed Scopus (160) Google Scholar). Closely related sequences within the Arabidopsis (Col-0) genome were identified via BLASTN queries of the AGI transcripts data base using the BLAST server at The Arabidopsis Information Resource (www.arabidopsis.org/Blast/). All sequences thus identified were then aligned using the ClustalW alignment function of MegAlign software (DNAstar, Inc. Madison, WI). Gene-specific primer pairs were then manually selected such that at least one primer per pair contained a minimum of two consecutive mismatches at the 3′ end when compared against all related Arabidopsis transcripts. For almost all genes analyzed, both primers within a pair fulfilled the above criteria and contained numerous additional mismatches when compared against related sequences. The PCR conditions consisted of denaturation at 95 °C for 10 min, followed by 40 cycles of denaturation at 95 °C for 15 s and annealing/extension at 60 °C for 1 min. A dissociation curve was generated at the end of each PCR cycle to verify that a single product was amplified using software provided with the GeneAmp® 5700 sequence detection system. A negative control reaction in the absence of template (no template control) was also routinely performed in triplicate for each primer pair. The change in fluorescence of SYBR® Green I dye in every cycle was monitored by the GenAmp® 5700 system software, and the threshold cycle (CT) above background for each reaction was calculated. The CT value of 18 S rRNA was subtracted from that of the gene of interest to obtain a ΔCT value. The CT value of an arbitrary calibrator (e.g. untreated sample in the case of up-regulated genes) was subtracted from the ΔCT value to obtain a ΔΔCT value. The fold changes in expression level relative to the calibrator were expressed as 2–ΔΔCT. For determination of statistical significance, pairwise comparisons were performed between treated and control sample ΔΔCT values using an independent two-tailed t test, assuming common variance. Differences associated with p values ≤0.05 were considered significant. Motif Searches—5′ upstream sequences from –1500 to –1 (relative to potential transcription start sites if available) were retrieved using RSA tools (see Ref. 28van Helden J. Nucleic Acids Res. 2003; 31: 3593-3596Crossref PubMed Scopus (353) Google Scholar; rsat.ulb.ac.be/rsat/), by selecting the "mRNA" feature type, and preventing overlap with upstream open reading frames. The program Motif Sampler (see Ref. 29Thijs G. Marchal K. Lescot M. Rombauts S. De Moor B. Rouze P. Moreau Y. J. Comput. Biol. 2002; 9: 447-464Crossref PubMed Scopus (266) Google Scholar; www.esat.kuleuven.ac.be/~thijs/Work/MotifSampler.html) was then used for the identification of over-represented motifs within the retrieved sequences. All searches were performed using a precompiled 3rd order Markov background model based on Arabidopsis upstream sequences (29Thijs G. Marchal K. Lescot M. Rombauts S. De Moor B. Rouze P. Moreau Y. J. Comput. Biol. 2002; 9: 447-464Crossref PubMed Scopus (266) Google Scholar), prior probability of finding 1 motif instance = 0.5, maximum number of motif instances per sequence = 0 (no limit), and maximum allowed overlap between different motifs = 2. Each data set was analyzed 10 times using the same parameters to reduce local optima (30Rombauts S. Florquin K. Lescot M. Marchal K. Rouze P. van de Peer Y. Plant Physiol. 2003; 132: 1162-1176Crossref PubMed Scopus (139) Google Scholar), and only cases where an identical or similar consensus sequence was returned from multiple runs were further considered. In addition, two independent statistical tests were employed for motif validation. For the first, searches were performed on 28,577 Arabidopsis –1500 to –1 (see above) 5′ upstream sequences to determine the total number of motif instances for all predicted Arabidopsis genes using the RSA-tools "genome-scale DNA pattern" search function (28van Helden J. Nucleic Acids Res. 2003; 31: 3593-3596Crossref PubMed Scopus (353) Google Scholar). These values were used to estimate the probability (p) of occurrence for a given motif within the total number of nucleotides searched on both DNA strands, and then p values for each experimental result were determined based on calculated binomial probabilities using the "PROBBNML" function within the SAS version 9.1 statistical analysis software package (SAS Institute, Inc., Cary, NC). The second test involved a bootstrap analysis using the POBO program (31Kankainen M. Holm L. Nucleic Acids Res. 2004; 32: W222-W229Crossref PubMed Scopus (48) Google Scholar). For each motif, 1000 bootstrap pseudoclusters were generated by random sampling with replacement from the input promoter data set and then compared with 1000 pseudoclusters generated in a similar manner from a background data set consisting of all predicted Arabidopsis 5′ upstream regions. The number of sequences in each pseudo-cluster generated was equal to the number in the input data set, and all background data set sequences were 1500 bp in length. An independent t test was then performed using pseudo-cluster values to estimate the probability for the number of motifs observed in the input data set to occur by chance. A p value ≤ 0.05 was considered significant for both of these tests. Detoxification of BOA in Arabidopsis—Two major pathways leading to the formation of BOA metabolites exhibiting reduced phytotoxicity have been identified in plants (Fig. 1). BOA-6-O-glucosides are formed via the intermediate BOA-6-OH, which is subsequently O-glucosylated. The second pathway involves direct N-glucosylation of BOA, which undergoes spontaneous isomerization to form the glucoside carbamate (1-(2-hydroxyphenylamino)-1-deoxy-β-glucoside 1,2-carbamate) shown in Fig. 1 (26Sicker D. Schneider B. Hennig L. Knop M. Schulz M. Phytochemistry. 2001; 58: 819-825Crossref PubMed Scopus (36) Google Scholar). An additional metabolite, gentiobioside carbamate (1-(2-hydroxyphenylamino)-1-deoxy-β-gentiobioside 1,2-carbamate) derived from the glucoside
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