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1 CHARACTERIZATION OF THE TOMATO BRANCHED-CHAIN AMINO ACID AMINOTRANSFERASE ENZYME FAMILY MEMBERS By GREGORY S. MALONEY A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2009

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CHARACTERIZATION OF THE TOMATO BRANCHED-CHAIN AMINO ACID AMINOTRANSFERASE ENZYME FAMILY MEMBERS

By

GREGORY S. MALONEY

A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT

OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY

UNIVERSITY OF FLORIDA

2009

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© 2010 Gregory S. Maloney

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To my parents, James and Maureen Maloney

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ACKNOWLEDGMENTS

I would first like to thank the members of my supervisory committee, Dr. Balasubramani

Rathinasabapathi, Dr. Don McCarty, Dr. Jay Scott for their constructive criticism and helpful

advice. I would next like to thank my advisor, Dr. Harry Klee, for his guidance and for keeping

me focused in my research and for teaching me to write scientifically. I would also like to thank

all of the members of our lab, including Peter Bliss, Mark Taylor, Denise Teiman, and Dawn

Bies, for their assistance with my research. For teaching me fundamental research techniques and

giving great advice I would like to thank Jonathan Vogel, Brian Kevany, Michelle Ziegler,

Sandrine Matheiu, Valeriano Dal Cin, Melissa Hamner, and Charles Goulet from our lab. I am

also obliged to Romain Fouqet for sharing his experience in various techniques, especially

protoplast culture and GFP microscopy. For advice and letting me use his StepOnePlus

instrument I thank Kevin Folta. For helping me with bacterial complementation I would like to

thank Valerie De Crecy-Lagard and Basma El Yacoubi. I also thank fellow members of the Plant

Molecular and Cellular Biology program, in particular Jon Martin, for his help with RT-PCR

work. I also thank the PMCB program, in particular Lindsey Freeman and Eliana Kampf for

keeping my academic life organized. I am also grateful to the University of Florida Alumni

Association for providing me with my Fellowship and the funds to stay afloat through graduate

school.

I give special thanks to all of my family, who have been very supportive throughout my

graduate school process, and to my friends, who have always helped me to relax and keep an

open mind, and to Katherine McGrath for her constant support and for making my time in

Florida so enjoyable.

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TABLE OF CONTENTS

page

ACKNOWLEDGMENTS ...............................................................................................................4

LIST OF TABLES ...........................................................................................................................7

LIST OF FIGURES .........................................................................................................................8

LIST OF ABBREVIATIONS ..........................................................................................................9

ABSTRACT ...................................................................................................................................11

LITERATURE REVIEW ..............................................................................................................13

Tomato as a Research Tool for Flavor ...................................................................................13 Tomato Flavor ........................................................................................................................16 Branched-Chain VOC Metabolism .........................................................................................18 BCAA Metabolism in Plants ..................................................................................................20 Branched-Chain Aminotransferases in Plants ........................................................................23

CHARACTERIZATION OF TOMATO BCATs ..........................................................................31

Cloning of SlBCAT cDNAs ....................................................................................................31 Expression Analysis of SlBCATs ............................................................................................32

Subcellular Localization of SlBCATs ....................................................................................33 Functional Verification of SlBCATs by Bacterial Complementation ....................................34 BCAT Enzyme Assays ...........................................................................................................35 Analysis of SlBCAT1 and SlBCAT3 Transgenic Fruit ............................................................37 Conclusion of Results .............................................................................................................38

BRANCHED-CHAIN VOLATILES IN TOMATO .....................................................................49

Rationale and Background ......................................................................................................49

Results of Substrate Feeding ..................................................................................................50 BCAA and Branched-Chain Volatile Loci .............................................................................56

DISCUSSION OF RESULTS .......................................................................................................63

Diversity of SlBCAT Family ...................................................................................................63 Significance of Substrate Feeding ..........................................................................................66 Concluding Remarks ..............................................................................................................71

MATERIALS AND METHODS ...................................................................................................74

Cloning of SlBCATs...............................................................................................................74

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Constructs ...............................................................................................................................74

Protein Production and Purification........................................................................................75 Enzyme Assays .......................................................................................................................76 Volatile Collection and Analysis ............................................................................................77 Microscopy and Subcellular Localization ..............................................................................78 Metabolite Feeding .................................................................................................................79 GC-MS Analyses of Nonvolatile Plant Metabolites ...............................................................79 Analysis of [U-13C6]Leucine-Labeled Samples .....................................................................79 Expression Analysis ................................................................................................................80 E. coli Complementation ........................................................................................................81 Amino Acid Analysis of Tomato Fruit by GC-MS ................................................................81 Statistical analysis ...................................................................................................................82

LIST OF REFERENCES ...............................................................................................................84

BIOGRAPHICAL SKETCH .........................................................................................................92

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LIST OF TABLES

Table page 1-1 Flavor volatile compounds impacting the perception of ripe tomato fruit flavor ...............30

2-1 Measurement of E. coli cell culture growth rate .................................................................45

2-2 Kinetic parameters of SlBCATs ..........................................................................................46

2-4 Levels of free amino acids in red ripe fruit of M82 and SlBCAT over-expression lines. ...................................................................................................................................48

3-1 Label accumulation in metabolite pools following incubation with [U-13C]leucine ...........61

3-2 Occurrences of loci containing BCAA and branched-chain volatile phenotypes ...............62

4-1 Primer sequences used in this study. ...................................................................................83

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LIST OF FIGURES

Figure page 1-1 BCAA metabolic pathways. ................................................................................................27

1-2 Reported pathway of BCAA catabolism in plants leading to TCA cycle intermediates. ....28

1-3 Schematic of S. lycopersicum and S. pennellii introgression line population and corresponding branched-chain volatile loci. ......................................................................29

2-1 Evolutionary relationships of mature SlBCAT proteins......................................................40

2-2 Evolutionary relationships of mature SlBCAT and AtBCAT proteins ...............................41

2-3 Quantification of SlBCATs RNA in different tissue types. .................................................42

2-5 Growth complementation of E. coli ΔilvE/ΔtyrB mutant cells expressing SlBCAT3 and 4..........................................................................................................................................45

2-6 Analysis of transgenic fruit SlBCAT transcript levels .........................................................47

3-1 Leucine and KIC feeding .....................................................................................................58

3-2 Isoleucine and KMV feeding ...............................................................................................59

3-3 Valine and KIV feeding. ......................................................................................................60

4-1 Hypothesized pathways forming branched-chain volatiles from BCKAs ...........................73

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LIST OF ABBREVIATIONS

AAT Alcohol acetyl transferase

ABA Abscisic acid

ADH Aldehyde dehydrogenase

ALS Acetolactate synthase

At Arabidopsis thaliana

BCAT Branched-chain amino acid aminotransferase

BCAA Branched-chain amino acid

BCKA Branched-chain α-keto acid

BCKADH Branched-chain keto acid dehydrogenase complex

BLAST Basic local alignment search tool

CoA Co-enzyme A

DPA Days post anthesis

EST Expressed sequence tag

GABA Gamma aminobutyric acid

GC-MS Gas chromatography-mass spectrometry

GFP Green fluorescent protein

Hv Hordeum vulgare

IL Intogression line

Kcat Catalyticconstant

KIC α-Ketoisocaproate

KID Keto acid decarboxylase

KIV α-Ketoisovalerate

Km Michealis-Menten constant

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KMV α-Keto-3-methylvalerate

Nb Nicotiana benthamiana

NMR Nuclear magnetic resonance

NADH Nicotinamide adenine dinucleotide (reduced)

PDC Pyruvate decarboxylase

PLP Pyridoxal 5’ phosphate

PMP Pyridoxamine 5’ phosphate

QTL Quantitative trait loci

RFLP Restriction fragment length polymorphism

RT-PCR Reverse transcriptase polymerase chain reaction

Sl Solanum lycopersicum

SNP Single nucleotide polymorphism

TCA Trichloroacetic acid

Vmax Maximum velocity

VOC Volatile organic compound

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Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy

CHARACTERIZATION OF THE TOMATO BRANCHED-CHAIN AMINO ACID

AMINOTRANSFERASE ENZYME FAMILY MEMBERS

By

Gregory S. Maloney

May 2010

Chair: Harry J. Klee Major: Plant Molecular and Cellular Biology

Branched-chain amino acids (BCAAs) are essential to animals and are synthesized in

plants from branched-chain keto acids (BCKAs), but their metabolism in plants is not completely

understood. The interface of BCAA anabolism and catabolism lies with branched-chain

aminotransferases (BCAT). In this study six BCAT genes from the cultivated tomato species

Solanum lycopersicum were identified and characterized. Quantitative RT-PCR showed that

SlBCAT1, 2, 3, and 4 were expressed in multiple plant tissues, while SlBCAT5 and 6 transcripts

were undetectable. SlBCAT2 and 3 were expressed nearly equally in all tissues, while SlBCAT1

was expressed most highly in ripening fruit and SlBCAT4 was expressed primarily in

inflorescences. SlBCAT1 and 2 are located in the mitochondria, SlBCAT3 and 4 in chloroplasts,

while SlBCAT5 and 6 are located in the cytosol and vacuole, respectively. Expression of

SlBCAT3 and 4 were able to restore growth of Escherichia coli BCAA auxotrophic cells, while

expression of SlBCAT1 and 2 were less effective. All SlBCAT enzymes were active in the

forward (BCAA synthesis) and reverse (BCKA synthesis) reactions. SlBCAT3 and SlBCAT4

exhibited a preference for the forward reactions while SlBCAT1 and SlBCAT2 were more active

in the reverse reactions. Over-expression of either SlBCAT1 or SlBCAT3 in tomato fruit did not

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significantly alter amino acid levels or branched-chain volatile emissions. BCAAs and BCKAs

were applied to fruit samples which were then analyzed for branched-chain volatiles. The results

support a model in which these volatile compounds are synthesized primarily from BCKAs and

not BCAAs in tomato fruit, unlike their synthesis from BCAAs in yeast.

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CHAPTER 1 LITERATURE REVIEW

Tomato as a Research Tool for Flavor

The cultivated tomato, Solanum lycopersicum, is the most valuable vegetable crop in

Florida, the leading US producer of fresh market tomatoes (Lucier, 2009). Consumers’ opinions

of the average grocery store tomatoes reflect poor flavor compared to the more flavorful

heirloom tomatoes. This is due in part to the fact that tomato breeding has focused principally on

economically important traits such as yield, appearance, maturity, and disease resistance. It is

difficult and impractical for breeders to select for better flavor in tomatoes because it is a highly

multigenic trait that is greatly influenced by environmental conditions and the composition of a

tasty fruit is not completely understood. Commercial tomatoes are often picked green, stored and

shipped at low temperatures, and bruised during handling, all of which have been shown to

decrease positive flavor compounds (Maul et al., 2000). Tomato varieties targeted towards home

gardeners tend to have superior flavor but are not grown commercially because they yield less

fruit, are softer, ripen too quickly, and do not ship or store well. These issues concerning fresh

tomato flavor quality may have the best chance of being resolved following research that focuses

on the genetics and biochemistry of flavor.

Tomato flavor comes from a blend of three chemical classes: acids, sugars, and volatile

organic compounds (volatiles). Flavor is also determined by the interactions of these chemicals

with alcohols, glycosidic bonds, and other compounds produced during fruit ripening (Tandon et

al., 2000; Ortiz-Serrano and Gil, 2007). Volatiles, which outnumber by far all other classes of

flavor compounds, are sensed by the olfactory system and are important in the diversity and

complexity of fresh uncooked tomato flavor.

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Volatiles are low molecular weight hydrophobic compounds derived from fatty acids,

carotenoids, and amino acids, which diffuse readily through fruit tissue to be released into the

atmosphere. The difficulties in studying ripe tomato flavor include the multitude of metabolic

pathways leading to volatile synthesis, their interconnectivity, and the lack of genes identified in

these pathways. However, some information concerning these pathways is known and serves as a

starting point for research. For instance, the C6-alcohol and aldehyde flavor volatiles are thought

to be derived from fatty acids (Chen et al., 2004), the ketone volatiles from carotenoids (Simkin

et al., 2004), and the amino acid-derived volatiles from alanine, phenylalanine, and branched-

chain amino acids (Tressl and Drawert, 1973; Tieman et al., 2006b).

The study of tomato flavor was previously undertaken (Tieman et al., 2006) by utilizing

the S. pennellii exotic introgression line population created by Dani Zamir in Israel. This

population is a series of 76 near isogenic introgression lines (ILs) that span the whole tomato

genome and overlap to form over 100 bins. It was created from a cross of S. pennellii (accession

code LA716), a wild species, and S. lycopersicum cv. M82, a common processing tomato (Eshed

and Zamir, 1995)

The formation of an introgression population takes about 10 generations of backcrossing.

In brief, the two parent species, in this case S. pennellii and M82, are crossed. The sites of

recombination are determined using existing RFLP markers. Individuals with the best

distribution are backcrossed into the M82 parent, and this is repeated for ten or more generations.

Once lines are found with single small segments of S. pennellii genome in the M82 near-isogenic

background, those plants are self-pollinated until homozygous, creating pure lines. The last step

is to create a map showing the alignment of all of the different introgression lines such that the

whole S. pennellii genome is covered, and finally assignment of bins.

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The importance of these lines is two-fold. First, a large amount of genetic diversity can be

exploited for new traits, given the wide range of evolutionary divergence between the two

species. Second, one can narrow down the genetic location of a phenotype to a particular

chromosomal segment via map-based cloning, eventually leading to gene discovery. This is

possible because S. pennellii has a high enough frequency of single nucleotide polymorphisms

(SNPs) that a dense map of genetic markers has been created and is available for public use

(Mueller et al., 2005).

One argument for the use of introgression populations is that the current cultivated

varieties represent a very narrow genetic base. Many wild species of the Solanaceae family and a

few closely related to tomato exist throughout the world. The genetic backgrounds of these

species are useful for introduction into the tomato varieties that are sold commercially. It is from

these wild species that tomato researchers hope to find the answers to problems with disease and

pest resistance, adaptation tolerance, yield, flavor, postharvest and other tomato qualities.

The method of improving tomato quality by QTL identification has already been used for

traits such as increased sugars and soluble solids (Fridman et al., 2002). By analyzing each

introgression line and comparing its phenotype to that of the M82 parent, the genetic location of

the trait can be immediately localized to a relatively small chromosomal segment. It has already

been found that many of these ILs contain important flavor volatile QTL (Tieman et al., 2006).

Many ripe tomato flavor volatile QTL have also been identified in the IL population of S.

habrochaites, another wild relative of cultivated tomato (Mathieu et al., 2009).

Among the many ILs that show alterations in flavor volatile profiles, twelve of them are

relevant to the research presented here. The volatile profiles of those lines were studied

previously (Tieman et al., 2006). Gas chromatography analysis of fruit from these lines revealed

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elevated levels of the volatiles 2-methylbutanal, 2-methylbutanol, 3-methylbutanal, 3-

methylbutanol, isovaleronitrile, isobutylthiazole, and isobutyl acetate compared to the M82

control. These volatiles are collectively called branched-chain volatiles because of their

structural similarities to BCAAs. The aldehyde and alcohol branched-chain volatiles are known

to attribute unpleasant flavor to tomatoes (Tandon et al., 2000; Baldwin et al., 2008). The

metabolic route leading to these compounds in plants is unknown and presents a challenging

study. Using evidence from microorganisms and predicting putative pathways based on chemical

structures provides a platform to begin studying the synthesis of these compounds and the

enzymatic steps involved.

Tomato Flavor

Much of tomato fruit flavor composition has been worked out qualitatively and

quantitatively (Buttery et al., 1986; Buttery et al., 1987; Buttery et al., 1987; Buttery et al., 1988;

Buttery et al., 1989). The significance of those studies was in the identification of many of the

most important tomato fruit volatiles and determining their odor thresholds, gas chromatography

retention times, and mass spectra. The odor threshold of a volatile compound is the smallest

amount of the compound that can be sensed by human olfaction, and is determined by trained

panelists. If the concentration of a compound exceeds its odor threshold, it is a positive

contributor to flavor. If its concentration is below its odor threshold, it does not contribute to

perceived flavor. Odor units determine the impact of a volatile flavor compound and are

determined by dividing the log of its concentration by its odor threshold. Determination of odor

units is important in choosing compounds to study. For example, in the study by Buttery et. al

(1988), the volatile compound isovaleronitrile was discovered and was present from 10-200 ppb,

depending on the cultivar. They also found that its odor threshold was relatively high, at 150

ppb. Given both figures, this compound probably is not important to tomato aroma. However,

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this compound is structurally related to the volatiles isobutyl cyanide and 2-isobutylthiazole, the

second of which has positive odor units in tomato fruit. On the other hand, the volatile β-

damascenone has an odor threshold of 0.002 ppb and a fresh fruit concentration of 1-3 ppb,

making it a positive contributor to fruit flavor. Table I shows the odor thresholds and

concentrations typically found in ripe fruits for most of the volatiles important in tomato flavor,

adapted from Buttery et al. (1971,1986, 1987,and 1988).

There are many thousands of aroma compounds known today, and over 400 have been

identified in tomatoes. However, only about 16 of these show evidence of being important in

flavor, given their odor units (Buttery and Ling, 1993). Interestingly, some of these compounds

have a pleasant odor in small amounts, but can be perceived as unpleasant when present at higher

concentrations. Examples of these are some of the branched-chain volatiles, which have been

described as pungent and stale, and phenylacetaldehyde, which is responsible for the malodorous

fruit aroma phenotype of IL8-2 (Tadmor et al., 2002). The branched-chain volatiles only seem to

give food a desirable quality when present at low concentration or in certain fermented foods

such as breads, cheeses, beers, and wines, in which they are crucial flavor components. Some

volatiles, however, make a fruit more pleasant when in concentration is increased, such as cis-3-

hexenal, one of the most abundant tomato volatiles, which gives a green aroma (Tandon et al.,

2000).

As mentioned previously, a study was performed in our lab on several of the S. pennellii

introgression lines to find loci important to fruit flavor (Tieman et al., 2006). Twenty-five

different quantitative trait loci (QTL) affecting 23 volatile flavor compounds were identified.

Four QTL that were significantly different in citric acid content were also identified. Other

results in the study are highly relevant to the experiments reported here. First, it was found that

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12 loci had alterations of multiple branched-chain volatile compounds. The fact that this class of

volatiles is altered in so many QTLs suggests that there are many factors or regulatory elements

influencing their metabolism. Second, it was found that isovaleronitrile, whose synthetic

pathway has never been determined, was altered in several QTLs along with other branched-

chain volatiles, suggesting it forms from the same precursors. The authors speculate that the

changes in branched-chain volatile content observed in the IL population could be due to

transcriptional regulators or rate-limiting enzymes affecting the metabolism of any of the

intermediate compounds in their synthesis.

Branched-Chain VOC Metabolism

Largely based on structural considerations and substrate feeding studies, the BCAAs have

been proposed to be precursors for the important flavor volatiles 2-methylbutanol, 3-

methylbutanol, 2-methylbutanal, and 3-methylbutanal in plants (Tressl and Drawert, 1973;

Gonda et al., 2010). These branched-chain volatiles are produced in bacteria, fungi, and plants

(Tressl and Drawert, 1973; Vergnais et al., 1998; Perez et al., 2002; Dickinson et al., 2003;

Nimitkeatkaia et al., 2005) and contribute to flavor in many foods including tomato (Guadagni et

al., 1972; Buttery et al., 1987; Mayer et al., 2003). In microorganisms these volatiles are formed

by the catabolism of BCAAs first by a branched-chain aminotransferase (BCAT, 2.6.1.42) to

form BCKAs. Those acids are subsequently acted upon by pyruvate decarboxylase-like (PDC-

like, 4.1.1.1) enzymes to form branched-chain aldehydes followed by alcohol dehydrogenases

(ADH, 1.1.1.1) to form branched-chain alcohols (Hazelwood et al., 2008). These reactions are

collectively known as the Ehrlich pathway (Ehrlich, 1904) and are illustrated in Figure 1-1A.

BCAAs can also be catabolized by another, more established, primary metabolic pathway

that does not produce volatile compounds. In this pathway, BCKAs are produced from

deamination of BCAAs by BCATs, but are substrates for the branched-chain alpha keto acid

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dehydrogenase (BCKADH) enzyme complex (Fujiki et al., 2000). This step and those that follow

produce acyl-CoA-conjugated compounds, which then yield the intermediate compounds of the

TCA cycle, acetyl-CoA and succinyl-CoA (Taylor et al., 2004). This catabolic pathway is

illustrated in Figure 1-2. It has been shown that high BCAA and BCKA levels induce the

expression of enzymes in this complex as a mechanism for these compounds to regulate their

own concentrations (Fujiki et al., 2001). This pathway has never been shown to produce volatile

compounds. However, when this primary pathway is highly active in yeast, very little branched-

chain alcohols and aldehydes are synthesized, presumably because this pathway uses up

intermediates that would otherwise be used in the volatile-producing pathway.

The volatile synthesis pathways of BCAA catabolism have been best studied in the

budding yeast, Saccharomyces cerevisiae, and the information gained from those studies may be

useful for gene discovery and pathway elucidation in plants. S. cerevisiae makes many long

chain alcohols including 3-methylbutanol from leucine, isobutanol from valine, 2-methylbutanol

from isoleucine, 2-phenylethanol from phenylalanine, and tryptophol from tryptophan.

Isobutanol, 3-methylbutanol, and 2-methylbutanol were shown to be synthesized from valine,

leucine, and isoleucine, respectively, by experiments utilizing 13C-valine and NMR analysis

(Dickinson et al., 1997; Dickinson et al., 1998; Dickinson et al., 2000).

Studies in yeast also demonstrated the enzymatic steps by which the branched-chain

volatiles are synthesized from BCAA catabolism. They also suggest that in some cases the

catabolic pathways of all three BCAAs require different enzymes at each particular step. While

studying leucine catabolism, for example, knocking out one decarboxylase showed that it

contributes to 94% of 3-methylbutanol production, while another decarboxylase contributes 6%.

When both genes are knocked out, no 3-methylbutanol is produced, suggesting the only pathway

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involved in its production in yeast must involve these enzymes. Six of thirteen ADH enzymes in

yeast have been shown through mutant analysis to produce 3-methylbutanol, illustrating the

redundancy of this enzyme group (Dickinson et al., 2003). Yeast mutants lacking BCKADH still

produced wild-type levels of 3-methylbutanol, evidence that the acyl-CoA-mediated pathway of

BCAA catabolism does not contribute to branched-chain volatiles (Dickinson et al., 1997). In

studies of valine catabolism, yeast mutants lacking BCKADH produced wild-type levels of

isobutanol from valine, while PDC triple mutants produced no isobutanol and the PDC-like

mutation had no effect. The evidence together suggests that specificity between valine and

leucine branched-chain alcohol production lies with the carboxylase step. Unlike with leucine

and valine catabolism, in yeast, 2-methylbutanol from isoleucine can be produced from any of

the three PDCs, the PDC-like YDL080, or YDR380. BCKADH does not contribute to 2-

methylbutanol production (Dickinson et al., 2000).

Though it seems the specificity of branched-chain volatile metabolism lies at the

decarboxylase steps, the initiation of these pathways lies with BCATs. Yeast has two

characterized BCAT genes, the products of which are localized in the cytosol or in mitochondria

(Liepman and Olsen, 2004). Mutagenesis or overexpression of these BCATs both resulted in

dramatically decreased and increased values, respectively, of isobutanol emission (Lilly et al.,

2006). A different study found that both yeast BCATs are involved in 3-methylbutanol

production (Schoondermark-Stolk et al., 2006). The function of yeast BCATs in branched-chain

volatile metabolism has encouraged the study of this enzyme family in tomato, the results of

which are described in this work.

BCAA and Volatile Metabolism in Plants

The BCAAs leucine, isoleucine, and valine are primary plant metabolites involved in

many processes. They are synthesized from threonine or pyruvate in plastids of mostly young

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tissues (Schulze-Siebert et al., 1984; Hagelstein et al., 1997). Threonine feeds into the isoleucine

pathway and pyruvate into the valine pathway, and hydroxyethyl-TPP into both, after which the

same four enzymatic steps are shared to form these two amino acids. Leucine is synthesized by a

branch of the valine pathway starting with α-ketoisovalerate in four enzymatic steps (Holmberg

and Petersen, 1988; Kohlhaw, 2003). These steps and their corresponding enzymes are illustrated

in Figure 1-1B.

Although synthesis of BCAAs is well characterized in plants, the catabolic pathways are

not completely understood. Their catabolism is believed to be initiated in mitochondria, where

the BCKDH complex is located (Taylor et al., 2004). The primary fates of BCAAs in plant cells

are peptide elongation, glutamate recycling, glucose and sucrose linked branched-chain ester

synthesis, branched-chain fatty acid synthesis, and respiration through synthesis of TCA cycle

intermediates (Kandra et al., 1990; Walters and Steffens, 1990; Kroumova et al., 1994; Daschner

et al., 1999; Li et al., 2003; Beck et al., 2004; Taylor et al., 2004). BCAA catabolism may be

more central to plant metabolism than previously appreciated. For example, Gu et al. (2010)

showed that a mutation in isovaleryl-CoA dehydrogenase, an enzyme in the BCAA catabolic

pathway, influences the metabolism of many unrelated compounds in Arabidopsis seeds,

including twelve amino acids.

In a banana study, it was shown that leucine and valine levels accumulate during ripening,

while isoleucine levels remain constant (Tressl and Drawert, 1973). Labeling studies in banana

showed that a small but significant amount of [14C]leucine was converted into 3-methylbutanol,

3-methylbutyl esters, 3-methylbutyric acid, and KIC. The largest amount of radioactive label was

found in 3-methylbutanol. Similar results were found for [14C]valine. Banana fruit have a volatile

profile consisting mostly of esters, with small amounts of alcohols, ketones, aldehydes, and

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phenolic ethers (Tressl and Drawert, 1973). Alcohol acetyl transferase (AAT) in banana makes

esters using 2-methylbutanol and 3-methylbutanol as precursors, and the amount of volatile

esters produced is limited by alcohol substrate. Banana also produces 2-methypropyl esters from

valine (Wyllie and Fellman, 2000). In a similar study in strawberry, incubation with isoleucine

resulted in increased 2-methylbutanol and 2-methylbutanal, but levels started to drop off after 48

h, while esters derived from these compounds increased (Perez et al., 2002). A study in

Gypsophila showed that in pre-anthesis flowers, 3-methylbutanol and 3-methylbutanal are

produced from leucine via PDC and ADH enzymes, while leucine is made into 3-methylbutyric

acid via isovaleryl-CoA from the same enzymes in open flowers (Nimitkeatkaia et al., 2005). A

recent study in cucumber fruit provided evidence that some fruit volatiles are derived directly

from amino acids by the action of aminotransferases. Although they showed direct evidence of

labeled phenylalanine incorporation into volatiles, the authors were not able to show this for

volatile formation from BCAAs via BCATs (Gonda et al., 2010), These studies all suggest that

the Ehrlich pathway probably occurs in some plants and tissues, but is not the only route to

branched-chain volatiles. The results in chapter three suggest an alternate route to the synthesis

of these volatiles in tomato which bypasses the BCAT step.

As mentioned previously, there are twelve QTLs in the S. pennellii introgression

population affecting emission of branched-chain volatiles in tomato (Figure 1-3). QTLs from

these lines were generally were altered in multiple branched-chain volatiles, suggesting common

pathways for synthesis. In a study by Schauer et al. (2006), approximately 26 QTLs for BCAA

content of ripe tomato fruits were identified in the S. pennellii introgression population. Of these

QTLs, seven were altered in the levels of all three BCAAs, suggesting that they encode major

BCAA pathway regulatory elements. However, there is no consistent correlation between QTLs

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with increased BCAAs and QTLs with increased branched-chain volatiles. These observations

shed doubt on the likelihood that BCAAs and branched-chain volatiles are metabolically related

in tomato, a thought that is strongly supported by the results in chapter three.

BCAA metabolism is under strict control by multiple regulatory mechanisms, including

gene expression, enzymatic substrate specificity, and feedback inhibition. Most of what is known

about regulation of BCAA metabolism in plants, however, pertains to the BCAA synthesis

enzymes threonine deaminase (TD) and acetolactate synthase (ALS). Product inhibition appears

to be the strongest regulator of plant BCAA metabolism. TD is very specifically feedback-

inhibited by excess isoleucine, but can be reactivated by increased concentrations of valine. ALS

is feedback inhibited by both leucine and valine and to a lesser extent isoleucine. It is the target

of many commercial sulfonylurea-based herbicides. Isopropylmalate synthase (IPMS), the first

enzyme unique to leucine biosynthesis, is feedback inhibited by excess levels of leucine

(Hagelstein and Schultz, 1993; Singh and Shaner, 1995). BCAT enzymes under control of

feedback regulation in plants have not been observed. BCATs may, however, be involved in

regulation of BCAA concentrations by their substrate specificities and expression patterns, as

will be discussed in chapter 2. The feedback mechanisms serve to regulate the levels of BCAAs

in cells, and they may also control the amount of branched-chain volatiles produced in tomato

fruit. This potential regulation will be discussed along with the results in chapter 3.

Branched-Chain Aminotransferases in Plants

BCAT enzymes reversibly catalyze the last reaction in BCAA synthesis and the first

reaction in BCAA catabolism, and therefore are very important targets in elucidating the

pathway to BCAA-derived volatiles. All BCAT enzymes, including those in plants, exhibit ping-

pong kinetics. In the first half reaction, the coenzyme pyridoxal 5’ phosphate (PLP)-bound form

of the enzyme reacts with the amino group of a BCAA. The enzyme then shifts to the

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pyridoxamine 5’ phosphate (PMP)-bound form, releasing a BCKA. The PMP-bound enzyme

aminates a second α-keto acid, forms the PLP-bound enzyme and releases an amino acid, usually

glutamate (Hutson et al., 2005).

Much of the enzymatic and genetic analyses of the BCAA catabolic pathway in plants

has been done in Arabidopsis, the BCATs being the most characterized to date. In Arabidopsis

there are six BCAT genes that have been studied. Given the localization of AtBCAT1-GFP in

mitochondria, it is thought to be active primarily in BCAA catabolism. The chloroplastic

locations of AtBCATs 2, 3, and 5–GFP suggest they are active primarily in BCAA synthesis.

AtBCATs 4 and 6-GFP locations were not unambiguously determined, but signal peptide

prediction programs suggest cytoplasmic locations for both proteins (Diebold et al., 2002).

Complementation analysis in yeast strains deficient in BCAT activity were also performed

with AtBCATs, confirming the functions of AtBCATs 1, 2, 3, 5, and 6 proteins, but not

AtBCAT4 (Diebold et al., 2002). AtBCAT1 is the primary enzyme candidate for initiating

BCAA catabolism. However, AtBCAT5 has also been isolated from mitochondria fractions in

Arabidopsis cell suspension cultures, suggesting that it may be dually targeted and may have a

catabolic role under certain growth conditions. (Binder et al., 2007). AtBCAT1 catabolizes all

BCAAs to BCKAs in almost all tissues, and its affinity is greatest in the order of isoleucine >

leucine > valine. In the direction of BCAA synthesis, its highest affinity is for KIV (Schuster and

Binder, 2005). AtBCAT2 expression is only observed in flowers, and elevates under stress, while

AtBCAT6 expression is only seen in flowers and siliques. The expression of the other AtBCATs is

not as tissue specific (Liepman and Olsen, 2004). In spinach, only two BCAT genes have been

identified, one with a higher affinity towards KIV and one with a higher affinity towards KIC

and KMV (Binder et al., 2007).

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Two other studies in Arabidopsis showed that both AtBCAT3 and AtBCAT4 participate in

methionine chain elongation and the production of aliphatic glucosinolates (Schuster et al., 2006;

Knill et al., 2008). In another example of plant BCAT function, a Nicotiana benthamiana

chloroplast-localized BCAT protein was implicated in transcriptional regulation of KNOX genes

that affect levels of gibberellins. The same NbBCAT can restore growth of a BCAT-deficient

yeast strain and is expressed highly in young leaves, suggesting it has a primary role in BCAA

synthesis (Gao et al., 2009). Kochevenko et al. (2010) present evidence that BCATs may also be

partly responsible for increased respiration in ripening tomato fruit. Together, these studies show

that BCATs have functions beyond primary amino acid metabolism, making it important to

understand the characteristics of each isoform in a species.

The BCAAs are considered cytotoxic in mammals when in excess and have been shown

to induce apoptosis in some species (Malatrasi et al., 2006), which suggests BCAT regulation is

very important to cellular health. Leucine toxicity has been reported in the bacteriums

Pseudomonas putida, E. coli, and Hydrogenomonas species. As one might expect, most of the

leucine catabolic pathway genes, including a BCAT, are induced in P. putida grown on leucine

media (Massey et al., 1974). BCAA toxicity has not been studied in detail in plants, but there

have been several studies on their control of BCAT expression. In a BCAA metabolism study in

barley, it was shown that HvBCAT1 expression is induced by drought stress, which the authors

suggest may be part of the cell’s detoxification mechanism to get rid of BCAAs in a stressful

environment (Malatrasi et al., 2006). It is not known for certain what benefits tomato fruit gain

from producing branched-chain volatiles, but it’s possible that they synthesize them as a means

of disposing of excess BCAAs.

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Not much is known about how BCATs contribute to the regulation of BCAA metabolism

in plants and even less about their contribution to branched-chain volatiles. Nevertheless, they

make interesting candidates for study due to their being the only known BCAA pathway

enzymes with multiple subcellular locations and their position at the interface of BCAA

catabolism and anabolism. Given the importance of these enzymes in primary plant metabolism

and the possibilities of unique secondary metabolic functions, in addition to the immense

commercial value of tomato fruit, there is great justification in studying the BCAT family of

tomato. The experiments and results outlined in Chapter 2 will give insights to the characteristics

of the tomato BCAT family and examine their possible roles in the metabolism of tomato fruit

volatiles. Chapter 3 will describe the experiments and results leading to the elucidation of the

pathways synthesizing some of the branched-chain flavor volatiles. Chapter 4 will discuss the

implications of the experimental results described in this dissertation and how they contribute to

the field of plant metabolism.

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Figure 1-1. BCAA catabolic and anabolic pathways. A. Ehrlich pathway of BCAA catabolism in microbes. 1) branched-chain aminotransferase, 2) α-keto-acid decarboxylase, and 3) aldehyde dehydrogenase. B. Synthetic pathway of BCAAs in plants. 1) threonine deaminase, 2) acetolactate synthase, 3) acetolactate isomeroreductase, 4) dihydroxy-acid dehydratase, 5) branched-chain aminotransferase, 6) 2-isopropylmalate synthase, 7) isopropylmalate isomerase, 8) isopropylmalate dehydrogenase.

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Figure 1-2. Reported pathway of BCAA catabolism in plants leading to TCA cycle

intermediates. Pathway is adapted from the KEGG database. 1) BCAT, 2) BCKDH complex, 3) Isovaleryl-CoA dehydrogenase, 4) 3-methylcrotonyl-CoA carboxylases, 5) Methylglutaconyl-CoA hydratase, 6) Hydroxymethylglutaryl-CoA lyase, 7) Isobutyryl-CoA dehydrogenase, 8) Enoyl-CoA hydratase, 9) 3-hydroxyisobutyryl-CoA hydrolase, 10) 3-hydroxyisobutyrate dehydrogenase, 11) Malonate-semialdehyde dehydrogenase (acetylating), 12) Methylmalonyl-CoA mutase, 13) Butyryl-CoA dehydrogenase, 14) 3-hydroxyacyl-CoA dehydrogenase, 15) Acetyl-CoA acyltransferase.

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/

Figure 1-3. Schematic of S. lycopersicum and S. pennellii introgression line population and corresponding branched-chain volatile loci. S. lycopersicum chromosomes are represented by long bars and introgressed genomic fragments of S. pennellii by small bars. Introgression fragments containing loci for branched-chain volatile phenotypes are designated by letters. The letters indicate which volatile phenotypes correspond to a particularintrogression line. Figure was adapted from Tieman et al. (2006).

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Table 1-1. Flavor volatile compounds impacting the perception of ripe tomato fruit flavor.

Volatile

Conc.

(ppb)

Odor

units* Precursor

Odor

Characteristic

cis-3-Hexenal 12,000 3.7 lipid tomato/green ß-ionone 4 2.8 carotenoid fruity/floral Hexanal 3,100 2.8 lipid green/grassy ß-Damascenone 1 2.7 carotenoid fruity 1-Penten-3-one 520 2.7 lipid fruity floral/green 2-Methylbutanal 27 2.1 BCAAs/BCKAs musty/foot odor 3-Methylbutanal 27 2.1 BCAAs/BCKAs musty/foot odor trans-2-Hexenal 270 1.2 lipid green 2-Isobutylthiazole 36 1 BCAAs/BCKAs tomato vine 1-nitro-2-Phenylethane 17 0.9 phenylalanine musty, earthy trans-2-Heptenal 60 0.7 lipid green Phenylacetaldehyde 15 0.6 phenylalanine floral/alcohol 6-Methyl-5-hepten-2-one 130 0.4 carotenoid fruity, floral cis-3-Hexenol 150 0.3 lipid green 2-Phenylethanol 1,900 0.3 phenylalanine nutty 3-Methylbutanol 380 0.2 BCAAs/BCKAs earthy, musty 2-Methylbutanol 100 0.2 BCAAs/BCKAs earthy, musty Methyl salicylate 48 0.08 phenylalanine wintergreen *Odor unit is defined as the log of the concentration of a volatile divided by its odor threshold Data are from Buttery and Ling (1993).

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CHAPTER 2 CHARACTERIZATION OF TOMATO BCATS

Cloning of SlBCAT cDNAs

In order to better understand the dynamics of branched-chain amino acid metabolism, six

unique tomato sequences potentially encoding BCAT enzymes were identified by searching the

Sol Genomics Network tomato expressed sequence tag (EST) database

(http://solgenomics.net/index.pl) (Mueller et al., 2005) for unigene sequences similar to those of

BCATs from other species. Unigenes are collections of transcripts that appear to originate from

the same locus. Full-length cDNAs from each unigene were cloned and sequenced, and proteins

were deduced from their open reading frames. The unigene SGN-U569828 (SlBCAT1, 45

members) has the most ESTs of all putative SlBCATs, while the unigene SGN-U569952

(SlBCAT3, 27 members) has the second highest, both far surpassing the numbers of ESTs of the

other putative SlBCATs. Phylogenetic analysis of all putative SlBCATs and comparisons with

Arabidopsis BCATs (Diebold et al., 2002) revealed that SlBCAT1 is most similar to the AtBCAT2

and AtBCAT1 genes from Arabidopsis, respectively. The unigene SGN-U569830 (SlBCAT2,

seven members) is most similar to AtBCAT3. SlBCAT3 and the unigene SGN-U569953

(SlBCAT4, seven members) are highly similar to each other and most similar to AtBCAT5. The

unigenes SGN-U569831 (SlBCAT5, five members) and SGN-U569829 (SlBCAT6, two

members) are most similar to AtBCAT2 and most similar to each other within the putative

SlBCATs (Figures 2-1 and 2-2).

A seventh unigene, SGN-U566152, a putative branched-chain aminotransferase-like

protein, was identified and considered to be a possible member of the tomato BCAT family.

However, after comparing the phylogeny of this gene with the rest of the family, it was decided

that this gene is most likely not a BCAT based on its 29% homology with its closest SlBCAT

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relative. It is possible that this gene encodes an aminotransferase using amino acids other than

the BCAAs as its substrate.

Another unigene, SGN-U565681, annotated as a branched-chain aminotransferase-like

protein was identified. This gene had only 25% homology with its closest SlBCAT relative, and

was also not considered a BCAT.

The identification of these six BCAT cDNAs gave a preliminary view of the diversity and

depth of this enzyme family in tomatoes. This result parallels the six confirmed BCAT genes in

Arabidopsis, indicating that the gene families in both plants may have similar characteristics and

division of function.

Expression Analysis of SlBCATs

To gain a better understanding of the different roles of each SlBCAT family member,

expression analysis was performed by quantitative RT-PCR on all six SlBCAT cDNAs. As stated

in the introduction, the Arabidopsis BCATs all have unique expression patterns which in some

cases seem to be related to specific functions of those genes. We expected to find similar patterns

with SlBCAT expression in different tissues. The expression patterns observed in most cases

validated the predictions made from the numbers and tissue locations of available ESTs in the

SGN database.

The tissues tested were partially expanded young leaves, inflorescences at one day after

anthesis, and mature green, breaker, turning, and red ripe fruit stages (Figure 2-3). Mature green

is the stage at which the fruit is fully expanded but has not yet started developing color. Breaker

is the stage at which fruits have started to develop external color, but covering no more than 10%

of the fruit. Turning is the stage at which fruits have from 20% to 40% external color coverage.

Red ripe fruit must be at least 95% red in color.

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Expression of SlBCAT1 is higher in both stages of ripening fruit and in red fruit than all

other SlBCATs, but is very low in leaves, inflorescences, and undetectable in green fruit.

SlBCAT2 is expressed in all tissues at similar levels except much more highly in inflorescences.

SlBCAT3 is expressed nearly equally in all tissues but is most highly expressed in leaves.

Expression of SlBCAT4 is highest in inflorescences, but relatively low in all other tissues

compared to the other SlBCATs. No SlBCAT5 and SlBCAT6 transcripts were detected in this

experiment in the tissues tested. ESTs for these two cDNAs were isolated only from callus

tissue, suggesting they may only be expressed under specific environmental conditions.

The result of these expression analyses helps us define the specificity of the tomato BCAT

family. They show that some isoforms may have functions tailored to particular plant tissues. A

BCAT expressed very highly in ripening fruit, for example, may function in respiration and

catabolism due to the senescent nature of that tissue. A BCAT expressed highly in flowers,

however, may function primarily in BCAA synthesis, given the high demand for primary

metabolites in reproductive tissues.

Subcellular Localization of SlBCATs

Plant organelles have very specific functions that can change during cell and organ

development, as is the case with ripening tomato fruit. Therefore, the subcellular locations of

metabolic enzymes can be important in predicting function. All six SlBCAT cDNAs were cloned

with a C-terminal E-GFP gene fusion, expressed in N. benthamiana leaf protoplasts and

analyzed with confocal microscopy (Figure 2-4).

SlBCAT3 and SlBCAT4 were localized to plastids, consistent with localization algorithm

software and homology with the chloroplast-localized AtBCAT proteins. SlBCAT1 and

SlBCAT2 were localized to mitochondria, consistent with localization prediction software

outputs. Mitochondrial localization was confirmed by overlap of the E-GFP signal with

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Mitotracker Orange stain. SlBCAT5 appeared to be cytosolic, consistent with the lack of an N-

terminal targeting signal. SlBCAT6 appeared to be localized to the vacuole, based on the E-GFP

signal filling the majority of the space inside the protoplasts, typical of vacuoles in leaf cells. The

subcellular locations of SlBCATs 1 and 4 are consistent with results of Kochevenko et al.

(2010).

These results show that, as in Arabidopsis, SlBCAT enzymes are diverse in their

subcellular locations. The mitochondrial and chloroplast locations of the four expressed

SlBCATs suggest that each may have specific functions in either BCAA synthesis or catabolism,

respectively. Similarly, the cytoplasmic and vacuolar locations of SlBCAT5 and SlBCAT6,

respectively, suggest unique metabolic functions for these two enzymes.

Verification of SlBCAT function by Bacterial Complementation

In order to demonstrate that the isolated SlBCAT cDNA products function as BCATs in

vivo, a complementation assay was performed in E. coli. The E. coli genome contains one BCAT

gene, ilvE. A different gene, tyrB, which encodes an aromatic amino acid aminotransferase

(EC2.6.1.57), can restore BCAT activity in ΔilvE cells (Gelfand and Steinberg, 1977; Powell and

Morrison, 1978; Vartak et al., 1991). The knockout strains for each of these two genes, neither of

which is lethal on minimal medium, were obtained from the Keio collection (Baba et al., 2006).

The double knockout ΔilvE/ΔtyrB was constructed to ensure that cells had no BCAT activity and

were complete branched-chain amino acid auxotrophs. This double knockout did not grow when

streaked on minimal medium.

SlBCAT1, SlBCAT2, SlBCAT3, and SlBCAT4 cDNAs were cloned into the E. coli

expression vector pBAD24 under control of the Pbad promoter (Guzman et al., 1995) and

transformed into the ΔilvE/ΔtyrB double knockout strain. Expression of proteins in the knockout

was confirmed by a protein gel blot of cell extracts, which confirmed that protein concentrations

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did not vary greatly (data not shown). SlBCAT3 and SlBCAT4 expression restored growth in the

ΔilvE/ΔtyrB knockout in minimal medium lacking branched-chain amino acids, with

approximately half the optical density of wild-type cells when measured after 10 hours of growth

(Table 2-1) (Figure 2-5). SlBCAT1 and SlBCAT2 were able to complement growth in the double

mutant strain, but cultures were much lower in density than those expressing SlBCATs 3 and 4

(Table 2-1). Cells expressing these two cDNAs did not show visible growth on plates after two

days. Restoration of growth by the chloroplastic SlBCAT3 and SlBCAT4 supports the hypothesis

that they are the major branched-chain amino acid synthesizing enzymes in tomato. The less

effective complementation by SlBCAT1 and SlBCAT2 is consistent with mitochondrial

localization, suggesting that these genes are primarily active in BCAA catabolism.

The results of these complementation experiments add further evidence to the potential

activities of these enzymes and support the conclusions formed from the localization

experiments. The mitochondrial locations of SlBCAT1 and 2 suggest they are involved in BCAA

catabolism but not synthesis, which is supported by their poor ability to restore growth in BCAA

auxotrophic cells. The chloroplastic locations of SlBCAT3 and 4 suggest that these enzymes are

primarily involved in BCAA synthesis, which they show a clear ability to do in their restoration

of BCAA auxotrophic cells.

BCAT Enzyme Assays

In order to determine the kinetic characteristics of each SlBCAT, the proteins were

expressed in E. coli cells and purified. Enzyme assays were performed with each recombinant

SlBCAT in both the forward (amino acid forming) and reverse (amino acid degrading)

directions. In the forward direction, product formation was quantified indirectly by measuring

decreasing absorbance upon NADH oxidation in a reaction coupled to glutamate dehydrogenase.

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In the reverse reaction, product formation was quantified by measuring the absorbance of the

ketone-hydrazone species formed by reaction of the BCKA with 2,4-dinitrophenyl hydrazine.

Table 2-2 shows the Km, Vmax, Kcat and Kcat/Km values determined for each SlBCAT

enzyme with all six branched-chain substrates. All SlBCATs had affinities for all six branched-

chain substrates. SlBCAT3 has a higher affinity for the BCKAs than BCAAs. SlBCAT4 exhibits

slightlyly higher affinities for KMV and isoleucine than other substrates. Like SlBCAT3, its

most closely related isoform, SlBCAT4 has an overall higher affinity for BCKAs than BCAAs,

consistent with the role of chloroplastic BCATs in BCAA synthesis in tomato.

SlBCAT1 has relatively low affinities for BCKAs and much higher affinities for leucine

and isoleucine in the reverse direction. This preference for BCAA substrates, together with its

mitochondrial location, supports a primarily catabolic function for SlBCAT1. SlBCAT2, also

located within mitochondria, has a much higher affinity for the BCAAs than their corresponding

BCKAs, similar to SlBCAT1, suggesting that it also principally functions in BCAA catabolism.

SlBCAT5demonstrates relatively high affinities for BCAAs and BCKAs, with the highest

for KMV and KIC. SlBCAT6 also demonstrates high affinities for BCAAs and BCKAs, but with

a much higher affinity for KIV, which suggests a very specific function for this enzyme in the

valine metabolic pathway.

These kinetic data provide vital information about the functions of particular SlBCATs.

The kinetic evidence suggests that SlBCAT1 and 2 are primarily catabolic in function, given that

they have very low affinities for BCKAs and much higher activity for BCAAs. These data are

consistent with SlBCAT1 expression levels spiking in ripening fruit, a senescent organ which

likely has less demand for protein synthesis than for amino acid catabolism. The kinetic evidence

for SlBCAT3 and 4 is consistent with their role in BCAA synthesis, but also shows they are

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capable of BCAA catabolism as well. They may have specific enzymatic functions dependent on

environmental conditions, tissue types, or developmental stages. The preference of SlBCAT3 for

BCKAs is consistent with its expression throughout the plant, since BCAAs are needed in

abundance in all tissues for protein synthesis. Since both SlBCATs 2 and 4 are both expressed

highly in flowers, the kinetic data suggests there is a likely a high demand for both BCAA

anabolism and catabolism in reproductive tissues. The specific functions of SlBCAT5 and 6

remain ambiguous even with their kinetic data, although the unusually high specificity of

SlBCAT6 on KIV may indicate that this enzyme has a very specific role in the plant. This is the

only case of a tomato BCAT having a much higher specificity for one substrate over all others.

Analysis of SlBCAT1 and SlBCAT3 Transgenic Fruit

In order to determine if an increase in either a single synthetic or catabolic SlBCAT could

alter fruit metabolism, over-expression constructs of two genes, SlBCAT1 and SlBCAT3, under

control of the FMV constitutive promoter, were created and stably transformed into M82 tomato

plants. These two cDNAs were chosen due to their expression in ripening fruits and because they

represent a primarily catabolic and primarily anabolic enzyme, respectively, given their

localization, kinetic, and growth complementation data.

Plants from the T1 generation were grown in the field and ripe fruits were

analyzed for amino acid content and flavor volatiles in comparison with M82 controls. Three

independent lines from each construct were chosen for this analysis, and RNA from each line

was analyzed by qRT-PCR to show the degree of over-expression. Although there were

significant increases in expression of the transgenes (Figure 2-6), there were no consistent

differences from the control in amino acid content throughout all of the SlBCAT1-OE lines

(Table 2-3). The only significant and consistent change was an increase in isoleucine in all of the

SlBCAT3-OE lines. Some of the lines showed significant increases in emissions of several of the

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branched-chain volatile (Table 2-4). All lines of SlBCAT1 showed significantly increased

emissions of 3-methylbutanal, while all lines of SlBCAT3 showed significantly increased

emissions of 3-methylbuanal, 2-methylbutanal, and 2-methylbutanol. Though these results were

significant, higher elevation of branched-chain volatiles would have been expected if BCATs are

solely responsible for initiating branched-chain volatile synthesis. In comparison, when the

tomato aromatic amino acid decarboxylase was overexpressed in tomato fruit, 10-fold increases

in 2-phenylethanol and 2-phenylacetaldehyde emissions were observed, demonstrating that

altered expression of a single amino acid metabolic gene can have profound effects on volatile

biosynthesis (Tieman et al., 2006b).

It can be concluded that increasing expression of an individual SlBCAT does not greatly

alter amino acid metabolism in tomato fruit, likely due to a tight enzymatic regulation of the

BCAA pathways and/or redundancy of individual SlBCATs in fruit. Interestingly, the study by

Kochevenko et al. (2010) shows that tomato plants constitutively expressing an SlBCAT1

antisense construct have elevated levels of branched-chain amino acids. Their finding adds

support to the hypothesis that SlBCAT1 is primarily catabolic in function.

Conclusion of Results

It is clear from the results presented in this chapter that the BCATs of tomato are diverse

and probably share many different functions among their multiple isoforms. The results show

that there are probably two SlBCATs dedicated primarily to BCAA catabolism and two dedicated

primarily to BCAA anabolism. The subcellular locations of the SlBCATs demonstrate that

anabolic and catabolic BCAA pathways are spatially separated in plant cells. Expression analysis

of all SlBCATs shows that there are isoforms that probably serve as primary metabolic enzymes

throughout the plant, while others have more specific functions. The lack of detectable

expression of the remaining two SlBCATs suggests they are not involved in primary plant

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metabolism, but likely have more specialized, unidentified secondary functions. The results of

the transgenic experiments indicate that the over-production of either an anabolic or a catabolic

SlBCAT protein is not sufficient to greatly alter BCAA or branched-chain volatile metabolism in

tomato fruit. BCAT protein levels in the overexpression transgenic fruits were not validated.

Therefore, it is possible the proteins were degraded and would not be truly represented by

transcript levels, which could possibly account for the low levels of volatiles.

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SlBCAT5 1 IDWDNLGFQLMQTDYMYVTK-CSDDGIFRQGQLNRYGNIQLSPSAGVLNYGQGLFEGTKA

SlBCAT6 1 IDWDNLGFQLIQTDYMYMTK-CSDDGIFRKGQLNRYGNINLSPSAGVLNYGQGLFEGTKA

SlBCAT2 1 VDWDKLGFGFTPTDYMYITKSCDVAGNFKQGQLNGYDNIQLSPSAGVLNYGQGLFEGTKA

SlBCAT1 1 FDWDNLGFKLIQTDYMFMTK-SSQNGNFEKGKLNPYGNIELSPSAGVLNYGQGLIEGTKA

SlBCAT4 1 IDWDNIGFAVMPTDYMYSMK-CSQDGNFSKGELQRFGNIELSPASGILNYGQGLFEGLKA

SlBCAT3 1 IDWDNLGFGFMPTDYMYSMK-CSQGENFSKGELQRFGNIELSPSAGILNYGQGLFEGLKA

SlBCAT5 60 YRREDGRIFLFRPDQNAMRMQIGAERMCMPCPSTDQFVEAVKQTAIANKRWIPPFGKGAL

SlBCAT6 60 YRRDDGRVFLFRPEQNAIRMQIGAERMCMPSPTTDQFVDAVKQTALANKRWIPPSGKGSL

SlBCAT2 61 YRQDNGGLSLFRPRENAIRMQIGAERMCMPYPSTDQFVDAVKQTALANKRWIPPPGKGSL

SlBCAT1 60 YRVDDGRIFLFRPQESGIRMQIGAKRMCMPSPSIQQFVDAVKLTTIANKRWIPPAGKGSL

SlBCAT4 60 YKRHDGNILLFRPEENALRMKMGAERICMPSPSVEQFVEAVKATVLANERWIPPPGKGSL

SlBCAT3 60 YRKHDGNILLFRPEENATRLKMGAERMCMPSPSVEQFVEAVKATVLANERWIPPPGKGSL

SlBCAT5 120 YIRPLLIGSGPIFGLAPAPEYTFLVYACPVGYYFKQGTAPLNLYVEEDVHRASRGGAGGV

SlBCAT6 120 YIRPLLIGTGPILGLAPAPEYTFLVYACPVGNYFKQGTAPLNLYVEEDVHRASRGGAGGV

SlBCAT2 121 YIRPLLYGSGSILGLAPAPEYTFLVYACPVGNYFKEGTAPLNLYVDEEFHRASRGGAGGV

SlBCAT1 120 YIRPLLIGNGPILGIAPAPEYTFIVYACPVGNYLRNGTQPLTLYVEEEHHRASQGGAGGV

SlBCAT4 120 YIRPLLMGSGAILGVAPAPEYTFLIYVSPVGNYFKEGMAPINLLIETEMHRATPGGTGGV

SlBCAT3 120 YIRPLLMGSGAVLGLAPAPEYTFLIYVSPVGNYFKEGLAPINLVVETEMHRATPGGTGGV

SlBCAT5 180 KSITNYAPVLKAMKNAKANGYSDVLYLDAVNKKYIEEVSSCNIFLVKGNVLSTPIAKGTI

SlBCAT6 180 KSITNYAPVLKAMKNAKANGYSDVLYLDAVNKKYIEEVSSCNIFLVKGNVLSTPIAKGTI

SlBCAT2 181 KSITNYAPVLRAIRNARERGFSDVLYLDSVNKKYIEEVSSCNIFLVKGKVISTPIACGTI

SlBCAT1 180 KSITNYAPVIKAIQEAKDRGYSDVLYLDSVNKKYIEEVSAANIFLVKGKNISTPIASGTI

SlBCAT4 180 KTIGNYAAVLKAQSAAKAKGYSDVLYLDSVNNRYLEEVSSCNVFIVKGNLIATPAIKGTI

SlBCAT3 180 KTIGNYAAVLKAQSAAKAKGYSDVLYLDCVQKKYLEEVSSCNVFIVKGNLIVTPAIKGTI

SlBCAT5 240 LEGITRKSIMDIAHDLGYTVEERLIEADELFTADEVFCTGTAVGVAPVGSITYKGQRIEY

SlBCAT6 240 LEGITRKSIMDIAHDLGYTVEERLIEADELISADEVFCTGTAVGVAPVGSITYKGQRIDY

SlBCAT2 241 LEGVTRKSIMEIAIDLGYQVEERLIEADELISADEVFCTGTAVGVAPVGSITYKGQRIEY

SlBCAT1 240 LEGVTRKSIIDIAHDLGYKVEERLIEADELFSADEVFCTGTALGVAPVGSITYKNKRINY

SlBCAT4 240 FPGITRKSIIDVALSQGFQVEERQVSVDELLDADEVFCTGTAVVVSPVGSITHLGKRVSY

SlBCAT3 240 LPGITRKSIIDVAISQGFEVEERQVSVDELLDADEVFCTGTAVVVSPVGSITHQGRRVTY

SlBCAT5 300 KIS-SDLSCKQFYSRLVGIQRGVIKDERNWIVEIE

SlBCAT6 300 KIS-SDLSCKQXYSRLVGIQRGVIKDERDWIVEIE

SlBCAT2 301 KIR-SELVCKKLYSTLVGIQKRHIEDKRDWIVDIE

SlBCAT1 300 KVS-SDLISEQLNSRLVAIQKGIIEDKRGWIIEIK

SlBCAT4 300 GSDGVGRVSKQLYSTLTSLQMGLATDNMNWTVELK

SlBCAT3 300 GNDGVGLVSQQLYSALTSLQMGLSEDKMGWIVELK

Figure 2-1. Evolutionary relationships of mature SlBCAT proteins. Mature peptides were predicted by omitting highly divergent N-terminal residues thought to be transit peptides. A, Alignment of amino acid sequences using ClustalW (Larkin et al., 2007). B, The evolutionary history was inferred using the Neighbor-Joining method (Saitou and Nei, 1987). The optimal tree with the sum of branch length = 1.21366717 is shown. The percentage of replicate trees in which the proteins clustered together in the bootstrap test (500 replicates) are shown next to the branches (Felsenstein, 1985). The tree is drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. There were a total of 332 amino acids in the final dataset. Phylogenetic analyses were conducted in MEGA4 (Tamura et al., 2007).

SlBCAT5

SlBCAT6

SlBCAT1

SlBCAT2

SlBCAT4

SlBCAT3100

100

83

0.1

A

B

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SlBCAT5 1 IDWDNLGFQLMQTDYMYVTK-CSDDGIFRQGQLNRYGNIQLSPSAGVLNYGQGLFEGTKA

SlBCAT6 1 IDWDNLGFQLIQTDYMYMTK-CSDDGIFRKGQLNRYGNINLSPSAGVLNYGQGLFEGTKA

SlBCAT2 1 VDWDKLGFGFTPTDYMYITKSCDVAGNFKQGQLNGYDNIQLSPSAGVLNYGQGLFEGTKA

SlBCAT1 1 FDWDNLGFKLIQTDYMFMTK-SSQNGNFEKGKLNPYGNIELSPSAGVLNYGQGLIEGTKA

AtBCAT2 1 LDWDNLGFGLNPADYMYVMK-CSKDGEFTQGELSPYGNIQLSPSAGVLNYGQAIYEGTKA

AtBCAT3 1 IDWDTVGFGLKPADYMYVMK-CNIDGEFSKGELQRFGNIEISPSAGVLNYGQGLFEGLKA

AtBCAT5 1 IDWDKIDFGLKPTDYMYAMK-CSRDGEFSQGQLQPFGNIDINPAAGVLNYGQGLFEGLKA

SlBCAT4 1 IDWDNIGFAVMPTDYMYSMK-CSQDGNFSKGELQRFGNIELSPASGILNYGQGLFEGLKA

SlBCAT3 1 IDWDNLGFGFMPTDYMYSMK-CSQGENFSKGELQRFGNIELSPSAGILNYGQGLFEGLKA

AtBCAT1 1 VDWDNLGFSLVRTDFMFATK-SCRDGNFEQGYLSRYGNIELNPAAGILNYGQGLIEGMKA

AtBCAT6 1 VKWEELGFALTPIDYMYVAK-CRQGESFTQGKIVPYGDISISPCSPILNYGQGLFEGLKA

AtBCAT7 1 VKWDELGFALVPTDYMYVAK-CKQGESFSTGEIVPYGDISISPCAGILNYGQGLFEGLKA

AtBCAT4 1 VKWEELAFKFVRTDYMYVAK-CNHGESFQEGKILPFADLQLNPCAAVLQYGQGLYEGLKA

SlBCAT5 60 YRREDGR-IFLFRPDQNAMRMQIGAERMCMPCPSTDQFVEAVKQTAIANKRWIPPFGKGA

SlBCAT6 60 YRRDDGR-VFLFRPEQNAIRMQIGAERMCMPSPTTDQFVDAVKQTALANKRWIPPSGKGS

SlBCAT2 61 YRQDNGG-LSLFRPRENAIRMQIGAERMCMPYPSTDQFVDAVKQTALANKRWIPPPGKGS

SlBCAT1 60 YRVDDGR-IFLFRPQESGIRMQIGAKRMCMPSPSIQQFVDAVKLTTIANKRWIPPAGKGS

AtBCAT2 60 YRKENGK-LLLFRPDHNAIRMKLGAERMLMPSPSVDQFVNAVKQTALANKRWVPPAGKGT

AtBCAT3 60 YRKKDGNNILLFRPEENAKRMRNGAERMCMPAPTVEQFVEAVTETVLANKRWVPPPGKGS

AtBCAT5 60 YRKQDGN-ILLFRPEENAIRMRNGAERMCMPSPTVEQFVEAVKTTVLANKRWIPPPGKGS

SlBCAT4 60 YKRHDGN-ILLFRPEENALRMKMGAERICMPSPSVEQFVEAVKATVLANERWIPPPGKGS

SlBCAT3 60 YRKHDGN-ILLFRPEENATRLKMGAERMCMPSPSVEQFVEAVKATVLANERWIPPPGKGS

AtBCAT1 60 YRGEDGR-VLLFRPELNAMRMKIGAERMCMHSPSVHQFIEGVKQTVLANRRWVPPPGKGS

AtBCAT6 60 YRTEDDR-IRIFRPDQNALRMQTGAERLCMTPPTLEQFVEAVKQTVLANKKWVPPPGKGT

AtBCAT7 60 YRTEDGR-ITLFRPDQNAIRMQTGADRLCMTPPSPEQFVEAVKQTVLANNKWVPPPGKGA

AtBCAT4 60 YRTEDGR-ILLFRPDQNGLRLQAGADRLYMPYPSVDQFVSAIKQVALANKKWIPPPGKGT

SlBCAT5 119 LYIRPLLIGSGPIFGLAPAPEYTFLVYACPVGYYFKQGTAPLNLYVEEDVHRASRGGAGG

SlBCAT6 119 LYIRPLLIGTGPILGLAPAPEYTFLVYACPVGNYFKQGTAPLNLYVEEDVHRASRGGAGG

SlBCAT2 120 LYIRPLLYGSGSILGLAPAPEYTFLVYACPVGNYFKEGTAPLNLYVDEEFHRASRGGAGG

SlBCAT1 119 LYIRPLLIGNGPILGIAPAPEYTFIVYACPVGNYLRNGTQPLTLYVEEEHHRASQGGAGG

AtBCAT2 119 LYIRPLLMGSGPILGLGPAPEYTFIVYASPVGNYFKEGMAALNLYVEEEYVRAAPGGAGG

AtBCAT3 120 LYVRPLLMGTGAVLGLAPAPEYTFIIYVSPVGNYFKEGVAPINLIVENEFHRATPGGTGG

AtBCAT5 119 LYIRPLLMGTGAVLGLAPAPEYTFLIFVSPVGNYFKEGVAPINLIVETEFHRATPGGTGG

SlBCAT4 119 LYIRPLLMGSGAILGVAPAPEYTFLIYVSPVGNYFKEGMAPINLLIETEMHRATPGGTGG

SlBCAT3 119 LYIRPLLMGSGAVLGLAPAPEYTFLIYVSPVGNYFKEGLAPINLVVETEMHRATPGGTGG

AtBCAT1 119 LYLRPLLFGSGASLGVAAASEYTFLVFGSPVQNYFKEGTAALNLYVEEVIPRAYLGGTGG

AtBCAT6 119 LYIRPLLLGSGATLGVAPAPEYTFLIYASPVGDYHKV-SSGLNLKVDHKYHRAHSGGTGG

AtBCAT7 119 LYIRPLLIGTGAVLGVASAPEYTFLIYTSPVGNYHKA-SSGLNLKVDHNHRRAHFGGTGG

AtBCAT4 119 LYIRPILFGSGPILGSFPIPETTFTAFACPVGRYHKD-NSGLNLKIEDQFRRAFPSGTGG

SlBCAT5 179 VKSITNYAPVLKAMKNAKANGYSDVLYLDAVNKKYIEEVSSCNIFLVKGNVLSTPIAKGT

SlBCAT6 179 VKSITNYAPVLKAMKNAKANGYSDVLYLDAVNKKYIEEVSSCNIFLVKGNVLSTPIAKGT

SlBCAT2 180 VKSITNYAPVLRAIRNARERGFSDVLYLDSVNKKYIEEVSSCNIFLVKGKVISTPIACGT

SlBCAT1 179 VKSITNYAPVIKAIQEAKDRGYSDVLYLDSVNKKYIEEVSAANIFLVKGKNISTPIASGT

AtBCAT2 179 VKSITNYAPVLKALSRAKSRGFSDVLYLDSVKKKYLEEASSCNVFVVKGRTISTPATNGT

AtBCAT3 180 VKTIGNYAAVLKAQSIAKAKGYSDVLYLDCIYKRYLEEVSSCNIFIVKDNVISTPEIKGT

AtBCAT5 179 VKTIGNYAAVLKAQSIAKAKGYSDVLYLDCLHKRYLEEVSSCNIFIVKDNVISTPEIKGT

SlBCAT4 179 VKTIGNYAAVLKAQSAAKAKGYSDVLYLDSVNNRYLEEVSSCNVFIVKGNLIATPAIKGT

SlBCAT3 179 VKTIGNYAAVLKAQSAAKAKGYSDVLYLDCVQKKYLEEVSSCNVFIVKGNLIVTPAIKGT

AtBCAT1 179 VKAISNYGPVLEVMRRAKSRGFSDVLYLDADTGKNIEEVSAANIFLVKGNTIVTPATSGT

AtBCAT6 178 VKSCTNYSPVVKSLLEAKSAGFSDVLFLDAATGRNIEELTACNIFIVKGNIVSTPPTSGT

AtBCAT7 178 VKSCTNYSPVVKSLIEAKSSGFSDVLFLDAATGKNIEEVSTCNIFILKGNIVSTPPTSGT

AtBCAT4 178 VKSITNYCPVWIPLAEAKKQGFSDILFLDAATGKNIEELFAANVFMLKGNVVSTPTIAGT

SlBCAT5 239 ILEGITRKSIMDIAHDLGYTVEERLIEADELFTADEVFCTGTAVGVAPVGSITYKGQRIE

SlBCAT6 239 ILEGITRKSIMDIAHDLGYTVEERLIEADELISADEVFCTGTAVGVAPVGSITYKGQRID

SlBCAT2 240 ILEGVTRKSIMEIAIDLGYQVEERLIEADELISADEVFCTGTAVGVAPVGSITYKGQRIE

SlBCAT1 239 ILEGVTRKSIIDIAHDLGYKVEERLIEADELFSADEVFCTGTALGVAPVGSITYKNKRIN

AtBCAT2 239 ILEGITRKSVMEIASDQGYQVVEKAVHVDEVMDADEVFCTGTAVVVAPVGTITYQEKRVE

AtBCAT3 240 ILPGITRKSMIDVARTQGFQVEERNVTVDELLEADEVFCTGTAVVVSPVGSVTYKGKRVS

AtBCAT5 239 ILPGITRKSIIEVARSQGFKVEERNVTVDELVEADEVFCTGTAVVLSPVGSITYKSQRFS

SlBCAT4 239 IFPGITRKSIIDVALSQGFQVEERQVSVDELLDADEVFCTGTAVVVSPVGSITHLGKRVS

SlBCAT3 239 ILPGITRKSIIDVAISQGFEVEERQVSVDELLDADEVFCTGTAVVVSPVGSITHQGRRVT

AtBCAT1 239 ILGGITRKSIIEIALDLGYKVEERSVPVEELKEAEEVFCTGTAAGVASVGSITFKNTRTE

AtBCAT6 238 ILPGVTRKSISELAHDIGYQVEERDVSVDELLEAEEVFCTGTAVVVKAVETVTFHDKKVK

AtBCAT7 238 ILPGITRKSICELARDIGYEVQERDLSVDELLEAEEVFCTGTAVVIKAVETVTFHDKRVK

AtBCAT4 238 ILPGVTRNCVMELCRDFGYQVEERTIPLVDFLDADEAFCTGTASIVTSIASVTFKDKKTG

SlBCAT5 299 YKISSD-LSCKQFYSRLVGIQRGVIKDERNWIVEIE

SlBCAT6 299 YKISSD-LSCKQXYSRLVGIQRGVIKDERDWIVEIE

SlBCAT2 300 YKIRSE-LVCKKLYSTLVGIQKRHIEDKRDWIVDIE

SlBCAT1 299 YKVSSD-LISEQLNSRLVAIQKGIIEDKRGWIIEIK

AtBCAT2 299 YKTGDE-SVCQKLRSVLVGIQTGLIEDNKGWVTDIN

AtBCAT3 300 YGEGTFGTVSKQLYTVLTSLQMGLIEDNMKWTVNLS

AtBCAT5 299 YGEDGFGTVSKQLYTSLTSLQMGLSEDNMNWTVQLS

SlBCAT4 299 YGSDGVGRVSKQLYSTLTSLQMGLATDNMNWTVELK

SlBCAT3 299 YGNDGVGLVSQQLYSALTSLQMGLSEDKMGWIVELK

AtBCAT1 299 YKVGDG-IVTQQLRSILVGIQTGSIQDTKDWVLQIA

AtBCAT6 298 YRTGEA-ALSTKLHSMLTNIQMGVVEDKKGWMVDID

AtBCAT7 298 YRTGEE-AFSTKLHLILTNIQMGVVEDKKGWMMEID

AtBCAT4 298 FKTGEE-TLAAKLYETLSDIQTGRVEDTKGWTVEID

Figure 2-2. Evolutionary relationships of mature SlBCAT and AtBCAT proteins. Mature peptides were predicted by omitting highly divergent N-terminal residues thought to be transit peptides. A, Alignment of amino acid sequences using ClustalW (Larkin et al., 2007). B, The evolutionary history was inferred using the Neighbor-Joining method (Saitou and Nei, 1987). The optimal tree with the sum of branch length = 2.55921922 is shown. The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (500 replicates) are shown next to the branches (Felsenstein, 1985). The tree is drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. There were a total of 331 positions in the final dataset. Phylogenetic analyses were conducted in MEGA4 (Tamura et al., 2007).

SlBCAT5

SlBCAT6

SlBCAT1

AtBCAT2

AtBCAT1

AtBCAT5

SlBCAT4

SlBCAT3

AtBCAT4

AtBCAT6

AtBCAT7

AtBCAT3

SlBCAT2100

100

100

100

100

100

100

100

99

39

0.1

A B

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Figure 2-3. Quantification of SlBCATs RNA in different tissue types. A, Comparison of

expression of genes relative to each other in each tissue. B, Comparison of expression in tissues within each gene. Analysis was performed on three biological and three technical replicates of tissues for each sample. Values represent percentage of total mRNA per sample ± SD, calculated from a standard curve for each gene. Note differences in y-axes. Expression of SlBCAT5 and SlBCAT6 was below the limit of detection. L = young leaves, F = inflorescences 1dpa, G = mature green fruit, B = breaker fruit, T = turning fruit, R = red ripe fruit.

A

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Figure 2-3. Continued.

B

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Figure 2-4. Subcellular localization of SlBCATs. Each gene was fused to E-GFP at the C-

terminal and expressed in N. benthamiana leaf protoplasts. The left column shows GFP fluorescence, the middle column shows marker fluorescence, and the right column shows merging of GFP and marker. Chlorophyll autofluorescence was used to show presence of chloroplasts for SlBCAT-3, 4, 5, and 6. Mitotracker Orange dye was used to show mitochondria for SlBCAT-1 and 2. Scale bars are each 10µm.

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Figure 2-5. Growth complementation of E. coli ΔilvE/ΔtyrB mutant cells expressing SlBCAT3

and 4. Cells are streaked on media lacking amino acids and SlBCAT cDNAs are expressed under control of the Pbad promoter in mutant cells. The top image shows growth restoration by SlBCAT4, while the bottom image shows restoration by SlBCAT3. Cells expressing the other SlBCATs are not shown, as they did not show visible growth on plates.

Table 2-1. Measurement of E. coli cell culture growth rate Strain BW25113 ΔilvE/ΔtyrB

ΔilvE/ΔtyrB

::SlBCAT1

ΔilvE/ΔtyrB

::SlBCAT2

ΔilvE/ΔtyrB

::SlBCAT3

ΔilvE/ΔtyrB

::SlBCAT4

OD600 1.44 ± 0.021 0.108± 0.004 0.214 ± 0.011 0.197 ± 0.008 0.670 ± 0.010 0.433 ± 0.006

Cultures were grown for 10 h after which OD600 was measured. BW25113 and ΔilvE/ΔtyrB carried an empty pBAD24 vector. SlBCAT cDNAs are under control of the Pbad promoter in the pBAD24 vector (Guzman et al., 1995). Values are averages of two replicates ± SD.

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Table 2-2. Kinetic parameters of SlBCATs.

Km

(mM) Vmax

(nkatal mg-1) Kcat

(s-1) Kcat/Km

(µM-1 s-1)

KIC SlBCAT1 7.09 ± 0.92 0.5 11.7 0.002

SlBCAT2 7.90 ± 0.80 3.5 84.8 0.011 SlBCAT3 0.35 ± 0.06 1.1 28.1 0.080 SlBCAT4 0.41 ± 0.02 1.4 35.0 0.085 SlBCAT5 0.34 ± 0.06 2.2 54.6 0.160 SlBCAT6 0.22 ± 0.02 1.2 28.7 0.130 KMV SlBCAT1 11.65 ± 1.89 0.7 16.3 0.001 SlBCAT2 12.40 ± 0.90 2.8 67.6 0.006 SlBCAT3 0.19 ± 0.02 1.0 23.6 0.120 SlBCAT4 0.14 ± 0.01 0.8 18.4 0.131 SlBCAT5 0.19 ± 0.02 1.0 23.6 0.120 SlBCAT6 0.16 ± 0.02 1.0 22.7 0.140 KIV SlBCAT1 5.57 ± 0.75 1.0 23.0 0.004 SlBCAT2 5.50 ± 0.60 3.5 84.3 0.015 SlBCAT3 0.65 ± 0.07 1.9 46.5 0.070 SlBCAT4 0.37 ± 0.02 2.5 60.6 0.164 SlBCAT5 1.20 ± 0.10 0.9 22.1 0.020 SlBCAT6 0.15 ± 0.01 4.6 109.8 0.730 Leucine SlBCAT1 0.56 ± 0.04 1.6 39.1 0.070 SlBCAT2 0.20 ± 0.02 0.3 8.1 0.040 SlBCAT3 2.70 ± 0.30 4.8 121.0 0.045 SlBCAT4 0.57 ± 0.03 0.7 17.9 0.031 SlBCAT5 1.80 ± 0.10 4.7 118.0 0.066 SlBCAT6 0.21 ± 0.02 0.6 15.7 0.075 Isoleucine SlBCAT1 0.67 ± 0.09 1.6 40.8 0.061 SlBCAT2 0.31 ± 0.02 0.3 7.6 0.025 SlBCAT3 4.90 ± 0.90 6.9 174.0 0.036 SlBCAT4 0.43 ± 0.03 0.8 20.0 0.047 SlBCAT5 3.20 ± 0.20 6.5 163.0 0.051 SlBCAT6 0.34 ± 0.03 0.8 20.0 0.059 Valine SlBCAT1 1.00 ± 0.10 2.0 50.5 0.050 SlBCAT2 1.40 ± 0.50 0.2 3.8 0.003 SlBCAT3 2.00 ± 0.20 4.4 111.0 0.056 SlBCAT4 1.40 ± 0.10 0.8 20.6 0.015 SlBCAT5 2.60 ± 0.20 4.9 123.0 0.047 SlBCAT6 1.20 ± 0.10 1.0 24.0 0.020

Activities of purified recombinant SlBCAT proteins on all BCAA and BCKA substrates. Km is presented as average ± SE. Km data were obtained using GraphPad Prism5 software. Other parameters were obtained by calculations listed in Materials and Methods.

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Table 2-3. Volatile emissions of BCAT over-expressing transgenic ripe tomato fruit. Line 3-methyl-

1-butanal 3-methyl-1-butanol

2-methyl-1-butanal

2-methyl-1-butanol

Isovalero nitrile

isobutyl acetate

2-isobutyl thiazole

SlBCAT1-OE-1 190 ± 25 205 ± 33 147 ± 29 123 ± 14 113 ± 22 130 ± 21 115 ± 8 SlBCAT1-OE-2 163 ± 19 126 ± 17 136 ± 8 107 ± 9 199 ± 22 60 ± 7 221 ± 42

SlBCAT1-OE-3 138 ± 16 125 ± 6 129 ± 10 99 ± 10 115 ± 15 102 ± 14 124 ± 16 SlBCAT3-OE-1 148 ± 20 197 ± 34 152 ± 23 227 ± 48 77 ± 7 228 ± 14 109 ± 7 SlBCAT3-OE-2 246 ± 35 275 ± 10 141 ± 22 180 ± 22 184 ± 13 141 ± 10 182 ± 9

SlBCAT3-OE-3 171 ± 32 130 ± 20 141 ± 15 146 ± 7 141 ± 29 205 ± 43 143 ± 22

V Values are percentages compared to 100% of M82 control fruit volatiles, ± SD (n=6). Values in bold are statistically significant as determined by one-way ANOVA followed by Dunnet’s test, (p<0.05).

Figure 2-6. Analysis of transgenic fruit SlBCAT transcript levels. Analysis was performed on three biological and three technical replicates of ripe fruit for each sample. Values represent percentage of total mRNA per sample ± SD, calculated from a standard curve for each gene. Data were analyzed by one-way ANOVA and values of each line are significantly different compared to control as determined by Dunnet’s test (p<0.05).

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Table 2-4. Levels of free amino acids in red ripe fruit of M82 and SlBCAT over-expression lines.

Line

Amino acid quantity

(ng gFW-1)

Val Leu Ile Ala Pro Met Lys

M82 0.79 ± 0.06 1.12 ± 0.14 2.19 ± 0.26 6.69 ± 0.48 1.91 ± 0.28 0.65 ± 0.10 3.01 ± 0.22 SlBCAT1-OE-1 0.61 ± 0.06 0.95 ± 0.09 2.22 ± 0.18 3.25 ± 0.29 3.73 ± 0.35 0.60 ± 0.05 2.58 ± 0.19 SlBCAT1-OE-2 0.70 ± 0.10 1.06 ± 0.09 2.21 ± 0.18 6.92 ± 1.27 3.45 ± 0.54 0.47 ± 0.05 2.04 ± 0.21

SlBCAT1-OE-3 0.72 ± 0.17 1.13 ± 0.15 2.64 ± 0.40 6.20 ± 1.65 3.32 ± 0.41 0.62 ± 0.04 2.62 ± 0.45 SlBCAT3-OE-1 0.73 ± 0.12 1.19 ± 0.20 3.38 ± 0.60 3.44 ± 0.50 2.88 ± 0.06 0.74 ± 0.16 1.87 ± 0.26

SlBCAT3-OE-2 0.64 ± 0.07 1.08 ± 0.12 3.52 ± 0.42 5.02 ± 0.68 2.61 ± 0.29 0.62 ± 0.06 2.37 ± 0.26 SlBCAT3-OE-3 1.47 ± 0.32 2.61 ± 0.45 7.96 ± 1.81 7.92 ± 1.00 5.57 ± 1.05 1.00 ± 0.03 4.83 ± 0.72

Values are expressed as means ± SD, (n=3).Values in bold are significantly different from control fruit by one-way ANOVA followed by Dunnet’s test (P<0.05).

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CHAPTER 3 BRANCHED-CHAIN VOLATILES IN TOMATO

Rationale and Background

In order to identify the components involved in the synthesis of branched-chain flavor

compounds in fruit, tomato fruit pericarp discs were supplemented with potential precursors to

those volatiles, including the branched-chain amino acids and their α-keto acid analogs. These

experiments were performed to provide evidence that the pathway leading to branched-chain

volatiles in tomato fruit is either similar or dissimilar to the Ehrlich pathway in yeast. The

experiments may also provide evidence of the rate limiting factors and steps in the putative

pathways, whether they be substrate limited or enzyme limited.

Similar experiments to those described here were performed in yeast with positive results,

showing that such a feeding experiment can yield the downstream branched-chain volatile

compounds as long as the appropriate Ehrlich pathway enzymes are present: branched-chain

amino acid aminotransferase, pyruvate decarboxylase, and aldehydes dehydrogenase (Dickinson

et al., 2003). The yeast studies showed that the flavor volatiles 2-methylbutanal and 2-

methylbutanol are downstream products of isoleucine catabolism and 3-methylbutanal and 3-

methylbutanol are downstream products of leucine catabolism (Dickinson et al., 1997; Dickinson

et al., 2000).

The hypothesis held before performing these experiments was that the branched-chain

volatiles emitted from tomato fruit are synthesized from BCAA substrates. The justification is

that the same volatiles in yeast are products of BCAAs and these substrates share similar

chemical structure with the volatiles. Since BCKAs are synthesized from BCAAs and are

downstream in the Ehrilch pathway, it was predicted that feeding these compounds would also

increase branched-chain volatile emissions. The results from the following experiments,

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however, were unexpected and required a revision of the current hypothesis that branched-chain

volatiles in tomato are formed via the Ehrlich pathway.

Results of Substrate Feeding

The free amino acids leucine, isoleucine, and valine were applied to M82 red ripe fruit

pericarp discs and incubated for eight hours after which volatiles were quantified by GC-MS.

Emissions of seventeen tomato volatiles having the most impact on flavor were analyzed and

compared to emissions from controls supplemented with only water. Significant changes were

not seen in many of the non-branched-chain volatiles, as was expected due to structural

dissimilarities to the provided substrates.

In tissues supplemented with leucine, small but significant (p<0.05) increases of about 1.5-

fold were observed in 3-methylbutanol and 3-methylbutanal emissions (Figure 3-1). Both of

these volatiles share side-chain structure with leucine. A significant decrease in cis-3-hexenal

and highly variable increase in trans-2-hexenal were also observed in these samples.

The volatile trans-2-hexenal, along with other green leaf volatiles (GLV), is usually

formed from linolenic and linoleic acids via lipoxygenase enzymes (Hatanaka, 1993). GLVs are

thought to exist in low concentrations in healthy plant tissues, but concentrate rapidly in stressed

or wounded tissues, and that tissue laceration provides the lipid substrates and triggers hydrolysis

to form these volatiles (Matsui et al., 2000). It is possible that the tissue injury from creating

pericarp discs and addition of high amounts of branched-chain substrates elicits a stress response

that causes trans-2-hexenal to form.

In tissues supplemented with KIC, significant increases of about nine-fold and ten-fold in

3-methylbutanal and 3-methylbutanol, respectively, were observed (Figure3-1). This result may

be explained by the fact that KIC is one step closer to these volatile compounds than leucine in

the hypothesized Ehrlich pathway. Although 3-methylbutanal is closer in this pathway to KIC

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than 3-methylbutanol, a greater concentration of 3-methylbutanol was emitted. This could be due

to the fact that 3-methylbutanol is the end product in this pathway causing it to accumulate, and

no reverse reaction exists for conversion back into the aldehyde. Interestingly, a decrease of

almost 50% was seen in 2-methylbutanal in KIC-supplemented tissue. Three possible

explanations include: the steps converting KIC and KMV to 3- and 2-methylbutanal,

respectively, occur via the same enzyme, for which both substrates are in competition, the

unnaturally high levels of substrates applied causes competitive or feedback inhibition of the

isoleucine synthetic pathway, or a several-fold increase in 3-methylbutanal or 3-methylbutanol

signals feedback inhibition of that pathway. In either case, 2-methylbutanal is still catabolized to

cause accumulation of 2-methylbutanol, as shown by the lack of change in 2-methylbutanol

levels from control samples.

When isoleucine was fed to M82 pericarp discs, small but significant increases of about

2.5-fold and 1.5-fold were observed in the levels of 2-methylbutanal and 2-methylbutanol

emissions, respectively (Figure 3-2). This result was expected because these two volatiles share

the same side chain structure as isoleucine and thus predicted to be metabolically related. This

result shows that only a small amount of isoleucine can be converted to branched-chain

volatiles.

M82 pericarp discs supplemented with KMV showed significant increases of about 15-fold

and 9-fold in 2-methylbutanal and 2-methylbutanol emissions, respectively, from water fed

controls (Figure 3-2). Like the results from the KIC and leucine feeding experiment, the greater

conversion of KMV than isoleucine to branched-chain volatiles may be explained by a revision

of the putative pathway to branched-chain volatiles. These results suggest BCKAs are more

likely than BCAAs to be the primary precursors to these volatiles. Similar to the KIC feeding

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results, KMV feeding resulted in decreases of about 60% and 20% in levels of 3-methylbutanal

and 3-methylbutanol emissions. As with KIC, this may be due to high substrate competitive or

feedback inhibition of the pathway leading to these volatiles by the substrate. Similar decreases

of about 20% were seen in the branched-chain volatiles isovaleronitrile and 2-isobutylthiazole,

suggesting high amounts of supplied KMV or the 2-methylbutanal or 2-methylbutanol products

may cause inhibition of the synthetic pathways of those compounds as well. There is also a

significant 1.5-fold increase of isobutyl acetate observed from KMV feeding and significant

increases in trans-2-hexenal in both isoleucine and KMV feeding. Lack of structural similarities

between these volatiles and the substrates suggest they are not related metabolically, but that the

substrates signal a change in these volatiles’ pathways. These changes are not likely due to

metabolic relatedness of volatiles to substrate but rather to regulatory mechanisms.

M82 pericarp discs supplemented with valine did not exhibit significant increases in

branched-chain flavor volatiles (Figure 3-3). In yeast, catabolism of valine results in KIV and the

volatiles isobutanal and isobutanol (Dickinson et al., 1998). Though these volatile compounds

are likely produced in tomato fruit, given that leucine and isoleucine feeding yield their

respective branched-chain volatiles, they are not considered important compounds to flavor

perception and are of less concern in this study. Also, due to their very low molecular weights,

they have a very short retention time on the gas chromatograph and are not detectable with the

methods used in this analysis. The only significant changes observed with valine feeding were a

three-fold increase in trans-2-hexenal and about 0.3-fold decreases in cis-3-hexenal and trans-2-

heptenal.

M82 pericarp discs supplemented with KIV displayed increases of about 4.5-fold and 5-

fold in 3-methylbutanal and 3-methylbutanol emissions, respectively. This result is similar to that

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observed with leucine feeding and can be explained by the fact that KIV is a precursor to KIC,

therefore it is expected that the same branched-chain volatiles would increase in this experiment.

This explanation is reinforced by results from yeast, in which it was reported that products of

both leucine and valine catabolic pathways are derived from a shared pool of KIV (Dickinson et

al., 1998). It is interesting, however, that although the same amount of leucine and KIV were fed

in each experiment the amount of 3-methylbutanal and 3-methylbutanol increase was greater

with KIV than with leucine. It is possible that a high concentration of leucine, but not KIV, in the

cell exhibits feedback inhibition to steps downstream in the pathway to KIC and volatile

synthesis, such as isopropylmalate synthase. It is also possible that the flux from KIV to KIC is

greater than that of leucine to KIC, since application of KIC yields the greatest increase in 3-

methylbutanal and 3-methylbutanol of all branched-chain substrates. The likely explanation is

that the hypothesis of the Ehrlich pathway occurring in tomatoes is incorrect. These data suggest

that KIC is more likely the primary precursor of 3-methylbutanal and 3-methylbutanol, rather

than leucine. Leucine catabolism may not result in these volatiles at all under biological

conditions, but is observed only when unnaturally high concentrations are fed to fruit. A decrease

of about 40% in 2-methylbutanal emission was observed with KIV feeding, similar to the result

from KIC feeding. KIV feeding also resulted in an increase of about fourteen-fold of the

branched-chain ester isobutyl acetate, making it the only tomato flavor volatile so far known to

be produced predominantly from the valine catabolic pathway. This compound is likely

produced by the reaction of isobutanol with acetyl-CoA and an acetyltransferase enzyme. There

was also an observed 1.5-fold increase in isobutyl acetate in tissues supplemented with KIC,

which may be explained by feeding of KIC into the valine pathway (Figure1-1). As in the other

feeding experiments, feeding of KIV caused significant increases in trans-2-hexenal.

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[U-13

C]leucine Feeding Reinforces BCAA Catabolic Pathway

The analysis of the feeding experiments above gave evidence for the synthetic pathways of

the volatile end-products of branched-chain catabolism, but did not measure the non-volatile

intermediates upon feeding of BCAAs. Additional evidence is also needed to support the

possibility that the Ehrlich pathway does not occur in tomato fruit as it does in yeast. The above

feeding experiments only provide indirect evidence of a pathway leading to branched-chain

volatiles. To further test and validate the hypothesis of a pathway in tomato fruit, a similar

feeding experiment was performed in which [U-13C]leucine heavy isotope was used as a

substrate. It is likely that the catabolic pathway of leucine is parallel to the pathways of

isoleucine and valine, similar to these pathways in yeast. Leucine was used as a representative of

all three BCAAs and their potential catabolic pathways.

The [U-13C]leucine compound was fed to red ripe fruit pericarp discs and incubated in

Petri dishes. Tissues were immediately frozen after 4 and 8 h time points. Metabolites were

extracted with methanol, then derivitized with methoxyamine hydrochloride in pyrimidines

followed by MSTFA and analyzed by GC-MS. The two time points were used to allow

measurement of 13C label incorporation over time. Analyzing the concentrations of compounds

which have incorporated label should provide evidence of the steps in the leucine catabolic

pathway in tomato fruit, and analyzing them temporally should give an indication of the

sequence of steps in the pathway. 13C-labeled substrate and GC-MS analysis was used in the

experiment to assess this pathway because it has proved useful in previous studies, such as in the

analysis of glycolysis in Arabidopsis (Giege et al., 2003). Molar enrichment of 13C label into

intermediate compounds was determined by comparison to 12C spectral fragments from

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standards. We specifically analyzed the accumulation of label in putative BCAA catabolic

intermediates and branched-chain volatiles (Table 3-1).

A significant quantity of 13C was observed in KIC, which is the direct catabolic product of

leucine by BCAT (Table 3-1). Significant amounts of label in KIV and KMV were also

observed. The quantities of labeled KIC and KIV were about double that of labeled KMV, which

is likely due to the connection of the leucine metabolic pathway to that of valine but not

isoleucine. It is interesting that the quantity of 13C label in KIV was higher than in KIC after 4 h,

but the opposite is observed after 8 hours. This may be due to a lower rate of carbon transfer into

KIC than KIV, which eventually reaches a steady state while KIC continues to accumulate label.

Of the branched-chain volatiles the incorporation of label was very low, though 3-

methylbutanol and 2-methylbutanol accumulated the most label, while their aldehyde forms had

nearly 10-fold less accumulation. The incorporation of label into these two alcohols about

doubled from 4 h to 8 h, while most other branched-chain intermediates appeared to reach their

isotopic steady-state by 4 h. Both of these observations are evidence that the branched-chain

alcohols are likely the end-products of the pathway in tomato. It also appears from these results

that the conversion of BCKAs from BCAAs occurs rapidly before reaching a steady-state. The

very low concentration of label in the branched-chain volatiles is likely because the pool of

BCKAs with label is used in other more primary pathways such as protein synthesis, leaving

only a small amount to be used in volatile synthesis. There may also be technical difficulties in

detecting such small amounts of volatile compounds.

That there is not a much higher amount of label in the volatiles supports the hypothesis

that BCAAs are not immediate precursors to branched-chain volatiles. It is also supported by the

fact that more label was incorporated into 2-methylbutanol than 3-methylbutanol, while the

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opposite result would be expected if 3-methylbutanol was produced by a direct route from

leucine. The results of this experiment show that carbon flux from leucine is highly dynamic,

which creates difficulty in interpreting the data. This is evident by the unexpected incorporation

of label into valine and isoleucine, which suggests that much of the carbon was first cycled into

pyruvate and threonine, the precursors to valine and isoleucine.

BCAA and Branched-Chain Volatile Loci

As was mentioned in the introductory chapter, much information can be gained about

tomato traits by identifying loci of interest using the population of S. pennellii introgression

lines. It was previously determined that there are at least 26 genetic loci with significant volatile

emission phenotypes, 12 of which are altered in branched-chain volatile emissions (Tieman et

al., 2006). This high number of branched-chain volatile loci suggests there are many factors

contributing to their synthesis and many points of regulation in their pathways in tomato.

Therefore, it is not surprising that drastic phenotypes were not observed in the transgenic

BCAT over-expression plants, or that the pathway leading to these volatiles may not be as

straightforward as they are in yeast. To further support the theory that branched-chain volatiles

are not derived directly from BCAAs, it is possible to cross-reference volatile loci to loci that are

changed in BCAA quantity in the S. pennellii population. These BCAA loci have already been

established in a previous report in which, like the volatiles, there were a surprisingly high

number of loci with BCAA phenotypes (Schauer et al., 2006). As mentioned in the introduction,

there is no consistent pattern of BCAA loci and branched-chain volatile loci occurring together,

as illustrated in Table 3-2. This observation adds additional evidence to the hypothesized

pathway which suggests branched-chain volatiles are not derived from BCAA catabolism, but

directly from catabolism of BCKAs.

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The evidence presented in this chapter suggests that branched-chain volatiles are more

likely derived directly from BCKAs, and not from BCAAs as they are in yeast (Dickinson et al.,

2003). Feeding of BCKAs in tomato fruit tissue resulted in much greater production of branched-

chain volatiles than BCAA feeding. The isotopic feeding showed that only a small transfer of

carbon into branched-chain volatiles from leucine occurs. Along with the IL data, these

observations reinforce the possibility of this novel branched-chain catabolic pathway existing in

tomato fruit.

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Figure 3-1. Leucine and KIC feeding. Levels of relevant flavor volatiles extracted from tomato

pericarp samples supplemented with either leucine or KIC, expressed as a percentage of water-fed control pericarp normalized to 100%. Asterisks mark compounds that were significantly different from control, as determined by one-way ANOVA followed by Dunnet’s test, (p<0.05) (n=3).

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Figure 3-2. Isoleucine and KMV feeding. Levels of relevant flavor volatiles extracted from

tomato pericarp samples supplemented with either isoleucine or KMV, expressed as a percentage of water-fed control pericarp normalized to 100%. Asterisks mark compounds that were significantly different from control, as determined by one-way ANOVA followed by Dunnet’s test, (p<0.05) (n=3).

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Figure 3-3. Valine and KIV feeding. Levels of relevant flavor volatiles extracted from tomato

pericarp samples supplemented with either valine or KIV, expressed as a percentage of water-fed control pericarp normalized to 100%. Asterisks mark compounds that were significantly different from control, as determined by one-way ANOVA followed by Dunnet’s test, (p<0.05) (n=3).

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Table 3-1. Label accumulation in metabolite pools following incubation with [U-13C]leucine.

Metabolite Label accumulation

(nmol gFW-1) 4 h 8 h

BCAAs

Leu 1302 ± 129 1285 ± 106 Iso 412 ± 32.0 461 ± 42.0 Val 256 ± 25.0 267 ± 24.0

BCKAs

KMV 10.9 ± 0.80 10.5 ± 1.00 KIV 21.9 ± 1.05 15.8 ± 1.00 KIC 19.6 ± 1.40 20.0 ± 2.40

Volatiles

3-methylbutanal 0.002 ± 0.000 0.003 ± 0.000 3-methylbutanol 0.025 ± 0.001 0.055 ± 0.003 2-methylbutanal 0.004 ± 0.000 0.004 ± 0.000 2-methylbutanol 0.037 ± 0.001 0.062 ± 0.003 Isovaleronitrile 0.002 ± 0.000 0.003 ± 0.000 Isobutylacetate 0.003 ± 0.001 0.003 ± 0.001

2-isobutylthiazole 0.005 ± 0.000 0.005 ± 0.001 Values are presented as means ± SE from four independent determinants.

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Table 3-2. Occurrences of loci containing BCAA and branched-chain volatile phenotypes.

BCAA IL

locus

Fold-

change

BCV

locus BCAA

IL

locus

Fold-

change

BCV

locus

L 2-2 0.74 - I 6-2 1.83 - V 0.65 V 1.89 V 2-3 0.61 + L 6-2-2 2.07 - L 2-4 2.15 + I 3.19 I 2.6 V 2.43 V 2-5 0.36 + L 7-1 1.72 + L 2-6-5 1.41 - I 2.16 L 3-1 0.64 - V 1.76 L 3-2 2.49 - L 7-2 2.02 + I 1.96 I 2.37 V 1.69 V 7-3 2.4 - L 3-4 1.94 - I 8-1 2.59 - V 1.87 V 1.99 V 3-5 0.59 + I 8-1-1 2.35 L 4-1 1.76 - V 2.06 I 2.61 L 8-3-1 2.33 - V 1.99 L 9-3 1.78 + L 4-4 1.54 + L 10-1 2.83 + I 2.09 I 2.75 I 5-1 0.55 + V 1.64 V 0.63 L 11-2 2.11 + L 5-2 1.75 - V 1-1-3 0.68 - I 2.6 V 12-1-1 1.51 - V 2.06 L 12-3 2.08 - I 5-3 2.24 - I 2.66 V 1.97

The first column indicates which BCAA is changed. The second column indicates the introgression line containing the phenotype. The third column values indicate fold differences of BCAA concentration in red ripe fruit from each introgression line from M82 control values, as reported by Schauer et al. (2006). The fourth column indicates if an overlapping branched-chain volatile phenotype was observed in the line, according to Tieman et al. (2006). Shaded rows indicate ILs with phenotypes for all three BCAAs. BCAA = branched-chain amino acid, BCV = branched-chain volatile, L = leucine, I = isoleucine, V = valine. Data have been adapted from Schauer et al. (2006) and Tieman et al. (2006).

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CHAPTER 4 DISCUSSION OF RESULTS

Diversity of SlBCAT Family

In this work we have discovered six BCATs that exist in S. lycopersicum, and expression of

four of these cDNAs was detected in the parts of the plant that were analyzed. The experiments

that followed their discovery revealed important information about this enzyme family and its

individual members in a plant species in which they have not yet been extensively characterized.

It is clear from BCAT studies in other plant species that this is a very important metabolic

enzyme family whose members perform functions in addition to BCAA synthesis and

degradation, making their continued study important to the overall understanding of plant

metabolism. The SlBCATs have very distinct characteristics from each other, suggesting some of

them they may also perform non-primary metabolic processes in the plant.

SlBCAT1 and SlBCAT2 were shown to be located in mitochondria in tobacco leaf cells.

Given that mitochondria are the primary location of BCAA catabolism in plant cells and the

preferences of these two enzymes is primarily catabolic and only minimally restore growth in E.

coli auxotrophs, these are likely to be the primary BCAA-degrading enzymes in tomato. Since

SlBCAT1 is highest in expression in ripening fruit, it may be the primary enzyme for recycling of

BCAAs resulting from protein degradation in senescent fruit tissue. Since SlBCAT2 is expressed

in all green tissues analyzed and very highly in floral tissues, it may be the responsible for

BCAA catabolism throughout. We expect a catabolic mitochondrial gene to exist in all tissues

since BCAAs are known precursors to the TCA cycle intermediates succinyl-CoA and acetyl-

CoA. This gene may also function in the crucial process of maintaining steady-state levels of

BCAAs in cells, which is crucial for compounds of such primary importance in cellular

metabolism.

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The very low preference of SlBCAT1 for the forward direction was may be explained by

the multiple amino acid substitutions this enzyme has in conserved regions. It has an I101 in its

active site whereas the other SlBCATs all have F101, as do the E. coli, human, and yeast BCAT

proteins at this position. However, AtBCAT1 also contains an isoleucine at this position and is

highly active in the forward direction, making this substitution an unlikely cause (Schuster and

Binder, 2005). More likely are the residues S122, which is an asparagine in all BCATs from

Arabidopsis, human, and yeast, and N175, which is a serine or threonine at the same position in

all Arabidopsis and yeast genes. The human mitochondrial BCAT has this same amino acid

substitution, but humans do not synthesize BCAAs. Future mutagenesis experiments may

determine if forward activity can be enhanced in this tomato enzyme by changing these residues

to their more conserved amino acids. If successful it will provide crucial evidence to the amino

acid configurations of BCAT enzymes that give them reversible catalytic activity.

SlBCAT3 and SlBCAT4 were located in chloroplasts of tobacco leaf cells and were able to

restore growth of E. coli cells lacking the ability to synthesize BCAAs, suggesting that these

enzymes are primarily involved in BCAA synthesis. The substrate affinities of these two

enzymes, especially of SlBCAT3, suggest the same. It is possible, however, that under certain

conditions these two enzymes may have a role in BCAA catabolism as well, which is evident

from these two enzymes’, especially SlBCAT4, ability to use BCAAs as substrates in the kinetic

studies. SlBCAT3 may function as the BCAA synthetic enzyme throughout the plant, since it is

expressed nearly equally in all tissues analyzed, including the four fruit stages. SlBCAT4 appears

to be more specialized in function, given that its expression is by far the highest in flowers and is

relatively low in other tissues compared to the other SlBCATs. An enzyme with such a specific

expression pattern may have a specialized function, possibly in the metabolism of compounds

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other than BCAAs as is observed with the Arabidopsis AtBCAT3 and AtBCAT4 (Schuster et al.,

2006; Knill et al., 2008). Kochevenko et al. (2010) showed that tomato inflorescences contain

nearly twice the concentration of all three BCAAs as leaves. The same study also revealed that

SlBCAT4 maps to IL3-2 and SlBCAT1 maps to IL12-3, both of which have QTLs for increased

levels of all three BCAAs. A N. benthamiana BCAT, recently found to be involved in hormonal

regulation, is also expressed highly in flowers and located in chloroplasts (Gao F, 2009). The

similarities of SlBCAT4 to this N. benthamiana gene make it an even more interesting subject for

the study of non-primary BCAT functions.

SlBCAT5 and SlBCAT6 transcripts were not detected in any of the tissues analyzed. The

only EST accessions that exist for these two unigenes were isolated from callus tissue cDNA,

therefore they may only be expressed under specific developmental, hormonal, or environmental

conditions. Despite their scarcity of expression, the distinct localization patterns and multi-

substrate kinetics of these two enzymes make them interesting candidates for study. The vacuolar

location of SlBCAT6 suggests that it may function in the recycling of BCAAs from the products

of proteolysis. This function is further supported by its lack of substrate specificity and relatively

high affinity for all branched-chain substrates. Of particular interest is this enzyme’s specificity

on KIV, which is extremely high compared to all other SlBCATs and substrates. It is unclear

why this enzyme has such a strong tendency toward valine synthesis.

The overall results of the SlBCAT kinetic experiments show that these enzymes are

diverse in function and are not entirely specific to individual branched-chain substrates, as might

have been expected from a multi-gene family. SlBCATs tend to have higher overall efficiencies

toward the BCKAs than the BCAAs, although it is assumed that BCATs are generally reversible

enzymes.

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The lack of striking fruit volatile or BCAA phenotypes in transgenic plants was

unexpected. However, a simple explanation may exist as to why there were no clear phenotypes.

It would be expected that an increase in the expression of SlBCAT1, a catabolic enzyme, would

cause a decrease in BCAAs and thus a decrease in volatiles. As is observed in bacteria (Massey

et al., 1974), the enzymes in the pathway of BCAA synthesis are very tightly regulated by

substrate feedback, therefore if catabolism of BCAAs is increased, one might expect a

simultaneous increase in BCAA synthesis. The opposite effect may occur with overexpression of

SlBCAT3, a primarily anabolic enzyme. Increased BCAA synthesis resulting from an

overproduction of this enzyme might elicit a feedback mechanism to earlier steps in the BCAA

synthesis pathway, such as threonine deaminase or acetolactate synthase, inhibiting excess

BCAAs from being synthesized.

Significance of Substrate Feeding

The substrate feeding experiments were performed to gain insight into the catabolic

pathways of BCAAs and the formation of their respective volatiles in tomato fruit, of which little

is known. It seems the tomato branched-chain volatile synthesis pathways share at least some of

the same steps as in yeast (Dickinson et al., 2003). However, it was particularly interesting that

in the case of isoleucine/KMV and leucine/KIC, feeding of the α-keto-acid resulted in much

greater incorporations into the same branched-chain volatiles than feeding of the amino acid.

These results may be explained by the fact that the α-keto-acids are capable of a greater flux into

these compounds than amino acids. It may also be that the amino acids are quickly metabolized

by other pathways in the cell, such as in protein synthesis, while the α-keto-acids are in less

demand by enzymes other than those forming branched-chain aldehydes. It is likely that BCATs

and BCAAs do not participate in the volatile synthesis pathway, and the BCKAs are converted to

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volatiles directly following their synthesis via dihydroxy-acid dehydratase and 3-isopropylmalate

dehydrogenase (Figure 4-1).

Tomato fruit cells are capable of disposing a small percentage of excess BCKA substrate

in the form of volatiles. The quantities of 3-methylbutanal and 3-methylbutanol emitted after

KIC feeding were 0.5 and 5.7 nmols/g FW, respectively, corresponding to 0.25 and 2.9 percent,

respectively, of substrate fed. The quantities of 2-methylbutanal and 2-methylbutanol emitted

after KMV feeding were 0.7 and 3.4 nmols/g FW, respectively, which corresponds to 0.35 and

1.7 percent, respectively, of substrate fed. The quantity of isobutyl acetate emitted after KIV

feeding was 0.45 nmols/g FW, corresponding to 0.25 percent of substrate fed. The quantity of

emissions after BCKA feeding compared to control fruit is evidence that these compounds are

limiting factors in the production of branched-chain volatile compounds. The results show that

tomato fruit cells are capable of producing more volatiles than they do under standard conditions

but are limited by the quantity of these intermediate metabolites in the cell. Conversely, it seems

that BCAAs are not limiting to the production of branched-chain volatiles. This is evident from

the lack of correlation between BCAA and volatile phenotypes in the S. pennellii IL population

and from low incorporation of BCAAs into volatiles seen in the feeding experiments.

The slight increase of isobutyl acetate observed with KIC feeding cannot be explained at

present. Since isopropylmalate synthase, the enzyme diverting KIV to the leucine synthetic

pathway, is thought to be irreversible, the conversion of KIC back to KIV and then to isobutyl

acetate is unlikely.

Decreases of 3-methylbutanal and 3-methylbutanol were observed after KMV feeding

and a decrease of 2-methylbutanal after KIC feeding. There are two possible explanations for

these occurrences: the steps in the pathways converting KIC and KMV to 3-methylbutanal and 2-

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methylbutanal, respectively, may occur via the same enzyme and therefore both substrates would

be in competition for that enzyme, or a great increase in KIC, 3-methylbutanal, or 3-

methylbutanol may cause feedback inhibition of the pathway generating 2-methylbutanal and

vice-versa. In either case the step converting the branched-chain aldehydes to alcohols does not

seem to be affected as much, given the wild-type levels of 2-methylbutanol observed in KIC

feeding and only a 20% decrease of 3-methylbutanol compared with a 60% decrease of 3-

methylbutanal observed in KMV feeding. Also with KMV feeding, decreases of about 20% each

were seen in the branched-chain volatiles isovaleronitrile and 2-isobutylthiazole, suggesting that

KMV, 2-methylbutanal, or 2-methylbutanol may cause feedback inhibition in the pathways

synthesizing those compounds as well.

Feeding of valine and KIV yielded some expected and unexpected results. No significant

changes were seen in branched-chain volatile emissions with valine feeding. This lack of aroma

change was also observed in strawberries supplemented with valine (Perez et al., 2002).We

expected to see an increase in leucine-related volatiles since the valine and leucine pathways are

interrelated. On the other hand, valine is known to be one of the most potent feedback inhibitors

of BCAA synthesis by inhibiting ALS (Borstlap, 1972), so if that enzyme is involved in

branched-chain volatile production it would likely be repressed upon valine feeding (Massey et

al., 1974; Massey et al., 1976). We had not previously seen any evidence of a pathway leading to

isobutyl acetate synthesis, but feeding KIV has provided such evidence. The increase in isobutyl

acetate was greater than any other volatile in these feeding experiments, suggesting that KIV

follows a direct path to the synthesis of this compound. As is the case in microorganisms

(Dickinson et al., 1998), it is likely that this pathway occurs by conversion of KIV to isobutanal,

then to isobutanol, then to isobutyl acetate, this final step being catalyzed by an alcohol acetyl-

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transferase. Dissection of this putative pathway may provide a new branch of tomato flavor-

related research in our laboratory. Also of interest in KIV feeding was that although the same

concentration of leucine and KIV were supplied in each experiment the amount of 3-

methylbutanal and 3-methylbutanol increases were greater with KIV feeding than with leucine

feeding. These volatiles were expected to increase with KIV feeding, but not to a greater degree

than with leucine, which was predicted to be closer to these volatiles. It could be that a high

concentration of leucine in the cell exhibits feedback inhibition to the downstream steps in the

volatile pathway while KIV does not. It is more likely that the flux from KIV to KIC is greater

than the flux from leucine to KIC, since KIC supplementation yields the greatest increase in

these two volatiles of all substrates supplies. This observation adds strong support to the

hypothesis that branched-chain volatiles are derived from BCKAs and do not involve the activity

of BCATs and BCAA substrates. The facts that only very small amounts of 13C label are

incorporated into branched-chain volatiles and that there is more label in 2-methylbutanol than in

3-methylbutanol also support the hypothesis that leucine is not a direct precursor of 3-

methylbutanal and 3-methylbutanol.

There is no clear indication in current literature that the involvement of BCKAs and

BCAAs in formation of trans-2-hexenal. Those compounds do not share enough structural

similarity to suggest that trans-2-hexenal may be converted from them directly. It is more likely

that the branched-chain compounds induce formation of trans-2-hexenal from long chain fatty

acids. A plausible explanation was given in Chapter 3 for this volatile’s biogenesis. It is known

that trans-2-hexenal and other C6-volatile compounds are synthesized from the degradation of

polyunsaturated fatty acids in plants (Zhuang et al., 1996). It is also known that trans-2-hexenal

and other C6 compounds are induced upon wounding and stress, and that their application to

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plants induces defense-related genes (Kishimoto et al., 2005). The signaling pathways for these

stress responses are currently unknown. A recent study, however, has implicated γ-aminobutyric

acid (GABA) in this signaling pathway after isolating a GABA-aminotransferase mutant in

Arabidopsis. The authors showed that an increase in GABA elicits a resistance to the effects of

the trans-2-hexenal defense response on the plant (Mirabella et al., 2008). It is possible that

exogenous addition of branched-chain compounds down-regulates GABA formation, which in

turn causes an up-regulation of trans-2-hexenal production. This interaction with the GABA

pathway is feasible because BCAAs and BCKAs share similar structure with GABA, all are

precursors to TCA cycle intermediates, and all are substrates for aminotransferase enzymes and

use glutamate and α-ketoglutarate as donor and acceptor molecules, respectively. An application

of such high amounts of exogenous BCAAs and BCKAs to tomato fruit may have caused

competitive inhibition of GABA-aminotransferase. In addition, high concentrations of branched-

chain compounds may directly trigger a stress response which up-regulates the production of

trans-2-hexenal.

It is important to bear in mind that these feeding experiments are partly artificial in nature,

and the results may not entirely reflect the in vivo characteristics of fruit metabolism, due to the

higher-than-natural concentration of substrate supplementation. In addition, it is not currently

known which subcellular compartments volatile synthesis occurs in, and most of the substrate

presumably pools in the cytosol after application. Nevertheless, the results of these feeding

experiments show convincing evidence that the pathways to branched-chain flavor volatiles in

tomato fruit may share the same steps as in yeast and the Ehrlich pathway (Figure 1-1B),

excluding the first BCAT step. The results also show that the BCKAs are converted into a much

greater amount of their corresponding volatiles than are BCAAs. This may be due to the fact that

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the BCKAs are only one enzymatic step from their corresponding volatiles while the amino acids

are two steps away, according to the Ehrlich pathway. This could also indicate that the BCAT

step converting BCAAs to BCKAs is much more limiting than the decarboxylase step converting

the BCKAs to aldehydes. Alternatively, and what is now our current hypothesis, BCATs and

BCAAs have only minimal roles in the branched-chain volatile synthetic pathways, while

BCKAs are the primary volatile precursors. BCKAs may be converted to volatiles directly from

their synthesis via dihydroxy-acid dehydratase and 3-isopropylmalate dehydrogenase in plastids

(Figure 4-1).

Concluding Remarks

Taken together, the results of the experiments presented here give much new detail about

BCAA metabolism and to the characteristics of the BCAT family, adding support to the

information that already exists about them in plants. Future work on this family will provide a

full characterization of its members and how they coordinate BCAA anabolism and catabolism

in plant organs. Alternative functions are also expected to be found in more detailed studies of

individual BCATs, particularly in SlBCATs 4, 5, and 6. Transgenic plants over-expressing and

silencing the four SlBCATs not described in this work are in the process of construction and

should soon expand what we know about these enzymes in vivo.

The complexity of tomato flavor, as stated previously, is an interaction of sugars, acids,

and volatile organic compounds. There are only a handful of volatiles that are thought to

contribute to tomato flavor, and of these there are seven believed to be derivatives of the BCAAs

and/or the BCKAs: 3-methylbutanol, 3-methylbutanal, 2-methylbutanol, 2-methylbutanal,

isobutylthiazole, isovaleronitrile, and isobutyl acetate. These compounds were thought to be

directly derived from their most structurally related BCAAs, but the tomato feeding experiments

shown here with valine and KIV suggest that isobutyl acetate derives directly from KIV and not

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valine, since KIV precedes valine in the pathway of its synthesis. Similar results were found with

the addition of KIC and KMV and labeled metabolite feeding did not indicate a clear pathway

from BCAAs to volatiles, all of which support our new hypothesis that branched-chain volatiles

are the products of BCKAs and not BCAAs, which is a deviation from the Ehrlich pathway.

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Figure 4-1. Hypothesized pathways forming branched-chain volatiles from BCKAs. 1) threonine

deaminase, 2) acetolactate synthase, 3) acetolactate isomeroreductase, 4) dihydroxy-acid dehydratase, 5) branched-chain aminotransferase, 6) 2-isopropylmalate synthase, 7) isopropylmalate isomerase, 8) isopropylmalate dehydrogenase, 9) α-keto-acid decarboxylase, 10) aldehyde dehydrogenase, 11) alcohol acetyltransferase. Asterisks indicate steps which constitute the Ehrlich pathway of branched-chain volatiles from BCAAs in microbes.

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CHAPTER 5 MATERIALS AND METHODS

All chemicals and reagents used were purchased from Sigma-Aldrich (St. Louis, MO),

unless otherwise noted. All supplies were purchased from Fisher Scientific (Pittsburgh, PA),

unless otherwise noted. All oligonucleotides were purchased from Integrated DNA Technologies

Inc. (Coralville, IA).

Cloning of SlBCATs

EST sequences of each SlBCAT were found by searching the SGN tomato EST database

(http://solgenomics.net/index.pl) with its BLAST tool for sequences that share homology with

known plant BCATs. The full length 5’ and 3’ ends of each SlBCAT were obtained using RACE

PCR with the SMART RACE cDNA synthesis kit (Clontech Laboratories, Mountain View, CA).

PCR with Advantage HF2 polymerase (Clontech Laboratories, Mountain View, CA) was used to

amplify the full-length open reading frames from cDNA. These were cloned into pGEMT

(Promega, Madison, WI) and sequenced. Alignment of protein sequences were produced using

ClustalW (Larkin et al., 2007) and phylogram trees produced using MEGA4 (Tamura et al.,

2007).

Constructs

Open reading frames for each construct were amplified from cDNA by PCR and cloned

into pGEMT-easy vector (Promega, Madison, WI). Protein expression constructs of each

SlBCAT were made by cloning into the Nhe1 and Sal1 restriction sites of pET-28b, (Invitrogen,

Carlsbad, CA) containing an N-terminal 6xHis tag. Subcellular localization and signal peptides

of each SlBCAT were predicted using outputs from SignalP subcellular localization software

(Emanuelsson et al., 2007). Primers were designed to omit signal peptides, and are listed in

Supplementary Figure S2.

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Bacterial complementation constructs were made by excising the inserts from pET28b

and inserting them into the pBAD24 (Guzman et al., 1995) using Sal1 and Not1 restriction sites,

resulting in a pBAD24 construct containing a 6xHis tag.

For transgenic plant overexpression constructs, SlBCAT1 and SlBCAT3 cDNAs were

cloned in the sense orientation into pENTR-TOPO and cloned using Gateway LR Recombinase

(Invitrogen, Carlsbad, CA) into a vector containing the figwort mosaic virus promoter (Richins

et al., 1987), a kanamycin resistance gene, and an Agrobacterium tumefaciens nopaline synthase

(nos) 3’terminator. The overexpression constructs were introduced into S. lycopersicum cv. M82

plants by Agrobacterium-mediated transformation using a method previously described

(McCormick et al., 1986). Primary transgenic tomato plants were grown in greenhouses under

standard conditions and supplemented with slow release fertilizer. Subsequent generations of

transgenic and control tomato plants were grown at the North Florida Research and Education

Center (7580 County Road 136, Live Oak, FL 32060).

C-terminal GFP constructs were made by cloning full-length SlBCAT open reading

frames into pDONR221 (Invitrogen, Carlsbad, CA) then cloning into the pK7WGF2 gateway

binary destination vector (Karimi et al., 2002). GFP constructs were transformed into

Agrobacterium strain ABI (Koncz and Schell, 1986).

Protein Production and Purification

Protein expression constructs were transformed into BL21(DE3) competent cells

(Invitrogen, Carlsbad, CA) by heat shock at 42̊ C. Cultures were grown in Luria broth

supplemented with 0.005 mM pyridoxal phosphate at 37̊̊̊ C until reaching an OD600 = 0.5, then

induced with 0.25 mM Isopropyl β-D-1-thiogalactopyranoside (IPTG) and grown at 16̊ C for 18

h. All of the following steps were carried out at 4̊ C. Cells were pelleted and lysed by sonication

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in phosphate buffered saline (PBS), then treated with Histidine-tag Protease Inhibitor Cocktail

(Sigma-Aldrich, St. Louis, MO) according to manufacturer’s directions and 0.1 mM β-

mercaptoethanol. Lysed cells were centrifuged at 10,000 rpm for 10 min and supernatant was

taken off and incubated with 200 µl TALON Affinity Purification Resin (Clontech, Mountain

View, CA) on ice with gentle shaking for 1 h. Resin was pelleted by brief centrifugation on

lowest speed in a 5415C tabletop centrifuge (Eppendorf, Westbury, NY) and put into a 15 ml

gravity flow column (Bio-Rad, Hercules, CA). Resin bed was washed with 50 ml of PBS buffer

containing 10 mM imidizole, then protein was eluted with 3 ml PBS containing 150 mM

imidizole and collected in 0.5 ml fractions. Protein fractions were quantified using the Bradford

method (Bradford, 1976). Protein purity was determined to be at least 95 percent by analysis

with SDS-PAGE and staining with coomassie blue Safestain (Invitrogen, Carlsbad, CA).

Enzyme Assays

The following assays were adapted from known methods (Prohl et al., 2000). The

forward reaction was performed by adding 400 µl of buffer (200 mM Tris-HCl pH 8, 100 mM

NH4Cl), 10 µl 20 mM pyridoxal 5’-phosphate, 10 µl 20 mM NaN3, 40 µl 0.2 M glutamic acid,

10 µl 10 mM NADH, 1U glutamate dehydrogenase (bovine pancreas)(Sigma-Aldrich, St. Louis,

MO), and 1 µg purified SlBCAT protein to a quartz cuvette and left to equilibrate at 25̊ C for 5

min. Sample was read in a SmartSpec (BioRad, Hercules, CA) spectrophotometer at 340 nm

until stable absorbance was reached. Reaction was started by addition of 10 µl branched-chain α-

keto acid, after which a decrease in absorbance of NADH was recorded at 340 nm.

The reverse reaction was performed by adding 400 µl of 75 mM Na4P2O7 pH 8, 10 µl of

BCAA, 5 µl of 20 mM pyridoxal phosphate, and 5 µg of purified protein to a 1.5 ml tube and

incubating at 25̊ C for 5 min. The reaction was started by adding 10 µl 10 mM α-ketoglutarate

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and incubating at 25̊ C for 5 min. To stop the reaction, 100 µl of 60% w/v trichloroacetic acid

was added and mixed. Tubes were centrifuged at 10,000 rpm for 1 min to pellet precipitate.

Reactions were transferred to 15 ml polypropylene tubes and 2 ml 2,4-dinitrophenylhydrazine

(0.5% w/v in 2 N H2SO4) were added to each , mixed thoroughly, and incubated at 25̊ C for 10

min. Five ml of toluene was added to each tube and shaken vigorously for 2 min to separate

branched-chain α-keto acids from α-ketoglutarate. The bottom aqueous layer was taken out and

discarded. Five ml of 0.5 N HCl was added to each tube containing the organic phase, shaken

vigorously for 1 min, and then centrifuged at 4000 rpm for 1 min to pellet precipitate. Two ml of

toluene layer was taken off and put in a clean tube containing 2 ml of 10% w/v Na2CO3 and

shaken vigorously for 1 min. One ml of aqueous layer was taken out and added to a clean tube

containing 1 ml 1.5 N NaOH and mixed by inversion. Samples were transferred to plastic

cuvettes and absorbance at 440 nm was recorded by spectrophotometry. Sample with heat-

denatured enzyme was used to obtain blank reading on the spectrophotometer.

For both assays, reactions lacking substrate, enzyme, or with boiled enzyme were used as

controls. Kinetic data for both forward and reverse reactions were calculated using non-linear

regression on GraphPad Prism 5 software (Graphpad Software, La Jolla, CA).

Volatile Collection and Analysis

The following method has been described previously (Tieman et al., 2006). Fruit were

grown in fields at the North Florida Research and Education Center (Live Oak, FL). Fruit were

picked from several plots of six plants each which were randomly distributed throughout the

growing area. Fruits were picked from all parts of the plant near the time of 1:00 pm once per

week for six weeks. Several ripe tomato fruits from each of six replicates of each construct and

S. lycopersicum cv. M82 control were chopped uniformly and placed in glass tubes. Air was

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filtered through a hydrocarbon trap (Agilent, Palo Alto, CA) before flowing through glass tubes

for 1 h and collected with a Super Q (Alltech, Deerfield, IL) column. After collection, 5 µl nonyl

acetate was added to each column as an internal standard, and volatiles were eluted from

columns by rinsing with 150 µl methylene chloride and forcing into a collection vial with

nitrogen gas. Eluted samples were separated through a DB-5 column (Agilent, Palo Alto, CA)

and analyzed on an Agilent 6890N gas chromatograph. Retention times of volatile compounds

were compared to known standards. An Agilent 5975 MS was used to confirm identity of

volatile peaks. Volatile peaks were analyzed using ChemStation software (Agilent, Palo Alto,

CA). Volatile levels were first calculated in ng g-1 FW h-1, and then reported as a percentage of

M82.

Microscopy and Subcellular Localization

Agrobacterium tumefaciens cultures transformed with SlBCAT GFP constructs were

grown overnight in 10 ml Luria broth, then pelleted by centrifugation at 10,000 rpm for 5 min.

Pellets were resuspended in infiltration solution (10 mM MgCl2, 10 mM MES) to an absorbance

of at OD600=0.4. Agrobacterium solutions were injected into the underside of young fully

expanded N. benthamiana leaves with a 2 ml syringe with needle removed. Plants were grown

for four days after infection. Protoplasts were released from N. benthamiana leaves using the

protocol of Yoo et al. (2007). Protoplasts transformed with SlBCAT1 and SlBCAT2 GFP

constructs were stained with 500 nM MitoTracker Orange, as directed by the manufacturer

(Invitrogen, Carlsbad, CA). Cells were visualized using a Zeiss Pascal LSM5 Confocal Laser

Scanning Microscope (Carl Zeiss MicroImaging Inc., Thornwood, NY) with a 40x objective.

GFP was visualized with an argon laser exciting at 488 nm and detected between 500-530 nm. A

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HeNe laser, exciting at 543 nm, was used to visualize chlorophyll autofluorescence, detected at

633, and MitoTracker Orange, detected at 576 nm.

Metabolite Feeding

S. lycopersicum cv. M82 plants were grown in fields at the North Florida Research and

Education Center (Live Oak, FL). Fruits were harvested and infiltrated with substrate the same

day. Fruits were cut in half, cored, and pericarp discs were cut out with a 1 cm cork borer. Discs

were trimmed horizontally to a depth of 0.5 cm to insure uniformity. For each sample, forty discs

were placed single-layered in plastic Petri dishes. Thirty µl of 10 mM amino acid, 10 mM α-keto

acid, or deionized water were pipetted onto the surface of each pericarp disc, after which the

plates were sealed and incubated at 25̊ C in darkness for 6 h. Discs from each sample were

weighed and placed in glass tubes and volatiles were collected and analyzed as described above.

GC-MS Analyses of Nonvolatile Plant Metabolites

Metabolite extraction, derivatization, GC-MS analysis and data processing were

performed as described previously (Lisec et al., 2006; Schauer et al., 2006), with the exception

that, for low abundance metabolites, a substantially higher extract concentration was injected

onto the GC-MS. The absolute concentration of metabolites was determined by comparison to

standard concentration curves as defined in Schauer et al. (2005a). Metabolites were identified in

comparison to database entries of authentic standards (Kopka et al., 2005; Schauer et al., 2005b).

In addition, the metabolites KIC, KMV, and KIV for which no MST information was available

were identified by analysis of identically derivatized authentic standards.

Analysis of [U-13

C6]Leucine-Labeled Samples

Isotope was purchased from Cambridge Isotope Laboratories, Inc. (Andover, MA).

Tomato pericarp discs were extracted as described above. Uncorrected molar percentage

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enrichments of metabolites were evaluated as described in Giege et al. (2003) by comparison of

the 12C spectral fragments and the isotopic spectral fractions of non-labeled control incubations

with the fragmentation patterns of the [U-13C]leucine-fed tomato pericarp discs as detailed in

Roessner-Tunali et al. (2004). For the calculation of the total label present in a metabolite pool

the mole fractional enrichment of that metabolite was multiplied by the absolute concentration of

that metabolite.

Expression Analysis

RNA was isolated from tomato fruit tissue using the RNeasy Plant RNA Extraction Kit

(Qiagen, Valencia, CA), followed by DNase treatment to rid samples of contaminating DNA.

RNA was quantified using a Nanodrop spectrophotometer (Thermo Fisher Scientific, Waltham,

MA). Omniscript reverse transcriptase (Qiagen, Valencia, CA) was used with 1 µg of each RNA

sample to synthesize cDNA. SYBR Green Master Mix (Applied Biosystems, Foster City, CA)

was used with 1 µl of each cDNA sample for quantitative RT-PCR on the Applied Biosystems

StepOnePlus real-time PCR machine. Five-point standard curves were made for each SlBCAT to

calculate absolute quantity of transcript. Primer specificity was confirmed with melting curve

analysis on the StepOnePlus real-time PCR machine. Plants for expression analysis were grown

in greenhouses. Leaves were harvested when near completely expanded. Flowers, including

calyx, were harvested when fully opened. Green fruit were harvested when fully expanded, light

green in color, hardened seeds and gelatinous locular tissue. For breaker stage, fruit were picked

with 10% or less color change from green. For turning stage, fruit were picked with 20-30%

color change. For red ripe, fruit were picked with 90% or more color change.

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E. coli Complementation

E. coli strain BW25113 with knockouts in ilvE (JW5606-1) or tyrB (JW4014-2) were

purchased from the Keio Collection (Baba et al., 2006). Double knockouts were constructed as

previously described (Cherepanov and Wackernagel, 1995; Baba et al., 2006) using the FLP

recombinase plasmid pCP20 to excise the kanamycin resistance gene from Δtyrb and then using

P1vir Le392 phage transduction of the Δilve lesion into the Δtyrb background to create the strain

ΔilvE/ΔtyrB. The knockouts were validated by PCR with primers flanking the sites of the two

genes (Supplementary Table S2). Constructs of SlBCATs in pBAD24 were transformed into

ΔilvE/ΔtyrB cells. Cells were first grown in liquid M9 minimal media supplemented with 0.2%

casamino acids and 1mM thiamine hydrochloride, centrifuged to pellet, and resuspended in

sterile water to OD600=0.6. 50 µl of resuspended cells was transferred to 3 ml liquid M9 minimal

medium lacking amino acids (Sambrook et al., 1989) and supplemented with 0.5% w/v arabinose

for induction, 1.0% w/v glycerol for carbon source, and 50 µg/ml carbenicillin. Cell culture

density was measured by OD600 with a SmartSpec spectrophotometer (Bio-Rad, Hercules, CA)

after 10 hours shaking at 37̊ C. Protein expression levels of SlBCATs were confirmed by protein

gel blotting of cells normalized by OD600, probed with mouse Anti-His Antibody (Invitrogen,

Carlsbad, CA).

Amino Acid Analysis of Tomato Fruit by GC-MS

Amino acid levels in M82 control and SlBCAT1-OE and SlBCAT3-OE transgenic ripe

tomato fruit were determined by derivitization with methyl chloroformate and quantification by

GC-MS according to the method of Chen et al. (2010), using an Agilent 6890N GC and 5975

MS. Three technical replicates of each of three biological replicates were analyzed for each

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transgenic line. Fruit were grown in fields at the North Florida Research and Education Center

(Live Oak, FL).

Statistical analysis

All statistical analysis of data was performed by algorithms in GraphPad Prism5

software. Data indicated as significant is by Students t-test or one-way ANOVA with p<0.05.

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Table 4-1. Primer sequences used in this study. All oligonucleotides were ordered from Integrated DNA Technologies, Inc. (Coralville, IA).

Primer name Primer sequence (5'→ 3')

ilvE-FlankF GATGCAACATCAGGTCAATGT ilvE-FlankR CGCAATGGTGTTGAACTCTT tyrB-FlankF CTTATTACGCGCCTGACTTC tyrB-FlankR CACAGGCAATAAGGCAAAGC SlBCAT3-pET28bF GCTAGCGAGAGCGCCGCCGTATTT SlBCAT3-pET28bR GTCGACTTTGAGCTCAACAATCCAACCC SlBCAT1-pET28bF GCTAGCTCTGCACAACCTTCAACTTATAG SlBCAT1-pET28bR GTCGACCTTAATCTCAATAATCCAACCCCT SlBCAT4-pET28bF GCTAGCTTTCAGAAGCAGTCACATTTTGC SlBCAT4-pET28bR GTCGACTCATTTTAGCTCAACAGTCCAATT SlBCAT2-pET28bF GCTAGCTACTACACAGCTCAGGTTG SlBCAT2-pET28bR GTCGACTCATTCAATGTCAACAATCCAATC SlBCAT5-pET28bF GCTAGCGCTTCTTCTCAATCTGTTCTCT SlBCAT5-pET28bR GTCGACTTCGATCTCCACGATCCAATT SlBCAT6-pET28bF GCTAGCTGTTATACAGCTCAGGCGG SlBCAT6-pET28bR GTCGACTCATTCAATCTCCACGATCCAAT SlBCAT3-pDONRF AAAAAGCAGGCTCCATGGAGAGCGCCGCCGTATTT SlBCAT3-pDONRR AGAAAGCTGGGTCTTTGAGCTCAACAATCCAACC SlBCAT1-pDONRF AAAAAGCAGGCTCCATGATCATCCAAAGGGCTTCA SlBCAT1-pDONRR AGAAAGCTGGGTCCTTAATCTCAATAATCCAACCC SlBCAT4-pDONRF AAAAAGCAGGCTCCATGGAGAGCGGCGGCG SlBCAT4-pDONRR AGAAAGCTGGGTCTTTTAGCTCAACAGTCCAATTCA SlBCAT2-pDONRF AAAAAGCAGGCTCCATGATTCAAAGGGCCGCACCT SlBCAT2-pDONRR AGAAAGCTGGGTCTTCAATGTCAACAATCCAATC SlBCAT5-pDONRF AAAAAGCAGGCTCCATGGCTTCTTCTCAATCTGTT SlBCAT5-pDONRR AGAAAGCTGGGTCTTCGATCTCCACGATCC SlBCAT6-pDONRF AAAAAGCAGGCTCCATGATTCGAGGAGCCGCATG SlBCAT6-pDONRR AGAAAGCTGGGTCGTAAAGTGACCCTTTTCCAGAAG Attb1-pDONR GGGGACAAGTTTGTACAAAAAAGCAGGCT Attb2-pDONR GGGGACCACTTTGTACAAGAAAGCTGGGT SlBCAT3-pENTR-TOPOF GAATTCATACTCCCTACAGGAGCAACACCA SlBCAT3-pENTR-TOPOR AGAGCTCATTTGAGCTCAACAATCCAACC SlBCAT1-pENTR-TOPOF CACCATGATCATCCAAAGGGCTTCA SlBCAT1-pENTR-TOPOR TTCCACTAGCAATTGGTGTTGAAATGTTT SlBCAT3-qRT-PCRF GTCACCATAACCACCTTCTGG SlBCAT3-qRT-PCRR GGACTCAACTCAATGTTACCG SlBCAT1-qRT-PCRF AGGGCTCTATTTACTTCTTTTGAG SlBCAT1-qRT-PCRR CATACACATTCTTTTAGCACCAATT SlBCAT4-qRT-PCRF TACTTGCCACCACCTTCCC SlBCAT4-qRT-PCRR TCCATAATTCAATATCCCAGAAGC SlBCAT2-qRT-PCRF AATTGTTTGAATTTTCATCTCTGCG SlBCAT2-qRT-PCRR ATACACATTCTTTCAGCTCCAATC SlBCAT5-qRT-PCRF CTCACCTCTTCTCTACACCAC SlBCAT5-qRT-PCRR AATAGCCGTTTGCTTAACAGCC SlBCAT6-qRT-PCRF GGTGTTATACAGCTCAGGCG SlBCAT6-qRT-PCRR CAGGACGAAATAAAAATACTCTCC

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BIOGRAPHICAL SKETCH

Gregory Stephen Maloney was born in Wilmington, Delaware and graduated in 2005from

the University of Delaware with a Bachelors of Science degree in Plant Biology and Landscape

Horticulture. After working at Pioneer Hi-Bred for half a year after college, he started graduate

school at University of Florida, where he earned a Doctor of Philosophy in 2010 in Plant

Molecular and Cellular Biology. From there he went on to a post-doctorate position at Wake

Forest University in Winston-Salem, NC.