Overview

1. 1 10 12 2 4 6 5 18 52 58 59 21 28 33 22 23 36 54 53 55 56 57 34 48 49 50 51 39 35 43 44 47 37 45 46 3 24 25 26 27 29 30 31 38 32 40 41 42 7 13 17 20 19 9 14 8 16 11 15 Anatomically Resolved Metabolomics of Mutant Arabidopsis Pollen for the Functional Characterization of Pollen Exine Biosynthesis Bennie John Bench1, Ewa Urbanczyk-Wochniak2, David V. Huhman1, Zhentian Lei1, Anna Dobritsa3, Robert Swanson4, Anna F. Edlund5, Daphne Preuss6, and Lloyd W. Sumner1 1Plant Biology Division, Samuel Roberts Noble Foundation, Ardmore, Oklahoma 73401, 2Monsanto Company, St. Louis, MO 63167, 3Dept. of Molecular Genetics & Cell Biology., University of Chicago, Chicago, IL 60637, 4Dept. of Biology, Valparaiso University, Valparaiso, IN 46383, 5Dept. of Biology, Spelman College, Atlanta, GA 30314, 6Chromatin, Inc., Chicago, IL, 60637 B) • Overview • Purpose: Pollen grains of land plants are surrounded by complex cell walls that are divided into three layers: (i) an inner intine, made primarily of cellulose, (ii) an outer exine, a multilayered structure primarily made of sporopollenin, and (iii) a lipid- and pollen-rich extracellular matrix, known as a pollen coat, which fills in the crevices of exine. Exines of various species have large morphological diversity. Exine provides protection to pollen against various environmental stresses, bacterial and fungal attacks, and plays a role in species recognition. This remarkable structure is impermeable to chemical degradation. Therefore, we have chosen a genetic approach that utilizes n array of exine mutants to better understand the metabolic pathways and compounds responsible for the complex chemical composition of pollen exine. The fundamental goal of this project is to understand the alterations in metabolic composition of 30 different Arabidopsis pollen mutant lines including three different lap (less adherent pollen) mutants for a better understanding of the e metabolic components involved in pollen development. • Methods • Fifty Arabidopsis inflorescences were collected for 30 mutant lines and analyzed along side wild type tissues. • Anthers were collected from stage 9 and 10 wild type and mutant flower buds • Cumulative weight less than 500 µg • Three replicates of 60 anthers were analyzed per genotype. Samples were lyophilized, homogenized and extracted with 80% methanol (50μL) for two hours • GC-MS profiling of primary metabolites in polar and non-polar extracts performed • UPLC-ESI-QTofMS profiling of secondary metabolites performed • Compound identification was based upon Rt-m/z pair matching (UPLC-MS) and mass spectral matching (GC-MS) • Secondary metabolite profiles were processed using MarkerLynx XS 4.1 software (Waters Inc.) for mass signal extraction and alignment as well as creating a metabolite marker list with the following parameters: noise elimination level set at 6.0, minimum peak intensity at 200 ion counts, and retention time window at ±0.1 • MATLAB (R2008b) was utilized to normalize the abundance values from MET-IDEA to the internal standard and also performed single factor analysis of variance (ANOVA) for MET-IDEA or MarkerLynx outputs • Resulting metabolites with p-values 95% confidence interval were then used for further analyses • Principal components analysis (PCA) models were generated with UmetricsEZinfo software using Pareto scaling • The two-way hierarchical clustering analysis (HCA) dendrograms were generated in JMP 5.0 software using the "Ward" method, "standardized data" option, and sample ordering based on principal component one from the PCA analyses • Results • Substantial spatial differences in metabolite content were observed within the 30 Arabidopsis mutants relative to wild type tissue. Differential levels of several primary and secondary metabolites including amino acids, phenolics, fatty acids, and as yet unidentified compounds were observed and used to characterize multiple mutants to date. Mutants were identified and annotated by a reverse genetic screen. As shown with a PCA, the mutants that are similar in function cluster nicely and an examples of the significant metabolites can be observed with the S-plots. HCA is presented to help visualize metabolite differences within the mutant populations. A representation of these genes affecting pollen exine development is shown with mutants LAP5 and LAP6. • Conclusions • UPLC-MS and GC-MS (not shown) analysis revealed differential levels of several primary and secondary metabolites including amino acids, phenolics, fatty acids, and as yet unidentified compounds. • Flavonoid glycosides (rather than aglycones) are the major forms of flavonoids in Arabidopsis anthers. • A single mutation of lap5 or lap6 gene resulted in a broad impact on plant metabolism: amino acids, carbohydrate, flavonoids, lipid and fatty acids, indicating the intricacy of interactions among metabolic pathways. • Significant reduction of naringeninchalcone and naringenin in the single mutants and their complete loss in the double mutants strongly suggest that LAP5 and LAP6 are anther-specific chalconesynthase. • PCA analysis reveals multiple interesting clusters suggesting functional relationships relative to pollen exine development that will be further investigated. • HCA has given us a better understanding of how metabolite concentrations vary within each genetic mutant which will aid in the structuring of the metabolite pathways involved with pollen exine production. A) A) C) D) B) Figure 1. A)Depiction of Arabadopsis flower size along with confocal images of anthers containing pollen (red). B) Illustration of the structure of a mature pollen grain. Table 1. Mutant lines analyzed with along with functions and pollen visual defects associated with the defect. Figure 5. Representative S-plots of various clusters. Shown here are mutants 15-3-2 (A), 127-1-1 (B), Lap6 (C), and 110-2-1 (D) against wild type tissue. S-plot analysis shows the difference in metabolites from the WT and the mutant. Table 2. Peak annotations for UPLC-MS analyses of pollen exine mutatnts and WT. Mutant from Table 1. WT WT WT lap6_3 lap6_2 lap6_1 lap5_3 lap5_2 lap5_1 Lap4_3 Lap4_2 Lap4_1 Lap3_3 Lap3_2 Lap3_1 55-1-1_2 55-1-1_1 12-1-2_2 12-1-2_3 12-1-2_1 62-1-1_3 40-4-1_2 40-4-1_1 40-4-1_3 15-3-2_3 15-3-2_2 15-3-2_1 55-1-1_3 24-1-1_2 24-1-1_3 24-1-1_1 16-3-1_2 47-3-1_2 16-3-1_1 47-3-1_1 16-3-1_3 47-3-1_3 52-1-1_3 52-1-1_2 52-1-1_1 lap5-6_3 52-4-2_3 28-3-1_2 28-3-1_1 62-1-1_2 62-1-1_1 lap6-2_3 lap6-2_2 lap6-2_1 lap5-6_2 lap5-6_1 52-4-2_2 52-4-2_1 28-3-1_3 127-1-1_2 127-1-1_3 127-1-1_1 155-2-1_2 155-2-1_3 155-2-1_1 103-3-2_2 103-3-2_3 103-3-2_1 135-2-3_2 135-2-3_3 135-2-3_1 119-1-1_3 119-1-1_2 119-1-1_1 131-1-2_3 131-1-2_1 110-2-1_3 154-1-1_2 137-2-1_3 137-2-1_2 137-2-1_1 110-2-1_2 110-2-1_1 131-1-2_2 155-2-1_2 154-1-1_3 155-2-1_3 154-1-1_1 155-2-1_1 At3g28780_2 At3g28780_3 At3g28780_1 At1g65060_3 At1g65060_2 At1g65060_1 At1g33430_3 At1g33430_2 At1g33430_1 Metabolite number assocated with Table 2. Figure 5. HCA dendogram depicting metabolite differences in each pollen exine mutant. Scale for this model is from blue (low accumulation) to red (high accumulation). Round grains Large and square grains Generally abnormal, collapsed grains WT . Large and square grains Indolylmethyl glucosinolate RuBP H2O, CO2 Glycine, Serine, Methionine Glucose Calvin cycle Tryptophan PPP 8-Methylthiooctyl (heptyl) glucosinolates Phenylalanine very thin exine easily dissociated exine Glycolysis “zebra” WT PAL C4H Round grains erythrose-4-phosphate very thin exine 20% C Alanine Shikimate pathway Leucine, Valine Pyruvate 4-Coumaric acid Coenzyme A CO2 Coenzyme A pantothenic acid 4CL ACC Lipids, fatty acids 4-Coumaroyl-CoA Acetyl-CoA Malonyl-CoA (3) Figure 2. Examples of several pollen mutant phenotypes. Lysine CHS Aspartate Naringenin chalcone OAA Glutamine TCA CHI Asparagine Naringenin αKG Glutamate Figure 7. An exampAlterations in metabolic pathways affected by mutations in Lap5 and Lap6 as seen in Figure 6. Figure 6. Representative example of UPLC-MS metabolic profiles. Annotations shown in Table 2. Shown here is changes in Lap 5 and Lap6 mutants. Lignin Proline Arginine 14 Flavonoids Isoflavonoids Putrescine 29 Unknowns AcknowledgmentsFunding for this research was provided by The Samuel Roberts Noble Foundation and the National Science Foundation 2010 project #MCB-05283. References Broeckling, C.D., Reddy, I.R., Duran, A.L., et al. (2006) MET-IDEA: Data extraction tool for mass spectrometry-based metabolomics. Analytical Chemistry, 78, 4334-4341. Dobritsa, A.A., Lei, Z., Nishikawa, S.-i., et al. (2010) LAP5 and LAP6 encode anther-specific proteins with similarity to chalconesynthase essential for pollen exine development in Arabidopsis thaliana. Plant Physiology, pp.110.157446. Dobritsa, A.A., Nishikawa, S., Preuss, D., et al. (2009) LAP3, a novel plant protein required for pollen development, is essential for proper exine formation. Sexual Plant Reproduction, 22, 167-177. Edlund AF, Swanson R, Preuss D (2004) Pollen and stigma structure and function: the role of diversity in pollination. Plant Cell 16, S84-S97. Zinkl GM, Zwiebel BI, Grier DG, Preuss D (1999) Pollen-stigma adhesion in Arabidopsis: a species-specific interaction mediated by lipophilic molecules in the pollen exine. Development 126, 5431-5440. Rohde, A. et al. (2004) Molecular phenotyping of the pal1 and pal2 mutants of Arabidopsis thaliana reveals far-reaching consequences on phenylpropanoid, amino acid, and carbohydrate metabolism. Plant Cell 16: 2749-2771 Figure 4. PCA of pollen exine mutants. Note the distinct separation of pollen exine mutant from the WT.