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A Survey of Anthocyanin Composition and Concentration in Diverse Maize Germplasm Michael Paulsmeyer, Laura Chatham, Talon Becker, Megan West, Leslie West, and John Juvik J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.7b00771 • Publication Date (Web): 26 Apr 2017 Downloaded from http://pubs.acs.org on May 4, 2017

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Journal of Agricultural and Food Chemistry

A Survey of Anthocyanin Composition and Concentration in Diverse Maize Germplasm

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Michael Paulsmeyer1, Laura Chatham1, Talon Becker1, Megan West2, Leslie West3, and John Juvik1*

5 1Department

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61801, USA

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2Kraft

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of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL

Heinz Company, 801 Waukegan Road, Glenview, IL 60025, USA

3Depart

of Food Science and Human Nutrition, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA

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**To whom correspondence should be addressed

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John A. Juvik

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Department of Crop Science, University of Illinois at Urbana-Champaign, 307 ERML,

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1201 West Gregory Drive, Urbana, University of Illinois, Urbana, Illinois 61801. Tel.: 217-333-

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1966, email: [email protected]

ACS Paragon Plus Environment


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Survey of Anthocyanin Composition and Concentration in Diverse Maize Germplasm

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Abstract

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Increasing consumer demand for natural ingredients in foods and beverages justifies

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investigations into more economic sources of natural colorants. In this study, 398 genetically

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diverse pigmented accessions of maize were analyzed using HPLC to characterize the diversity

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of anthocyanin composition and concentration in maize germplasm. 167 accessions were

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identified that could produce anthocyanins in the kernel pericarp or aleurone and were classified

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into compositional categories. Anthocyanin content was highest in pericarp-pigmented

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accessions with flavanol-anthocyanin condensed forms, similar to the Andean Maíz Morado

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landraces. A selected subset of accessions exhibited high broad-sense heritability estimates for

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anthocyanin production, indicating this trait can be manipulated through breeding. This study

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represents the most comprehensive screening of pigmented maize lines to date, and will provide

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information to plant breeders looking to develop anthocyanin-rich maize hybrids as an economic

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source of natural colorants in foods and beverages.

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Keywords: Anthocyanin; natural colorants; Zea mays L.; germplasm diversity

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Introduction Anthocyanins are the visually appealing water-soluble pigments responsible for most of

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the red/orange to blue/purple pigments exhibited in plants. The most obvious function of

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anthocyanins is as a colorful signal for pollinators and seed dispersers 1. However, anthocyanins

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also protect the plant from photodamage and herbivory 2,3. In addition to their role in plants,

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anthocyanins have been shown to possess anti-inflammatory, anti-carcinogenic, anti-angiogenic,

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anti-microbial, cardioprotective and neuroprotective bioactivity in mammals 4. Furthermore,

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they have been suggested to assist in the prevention of obesity and diabetes as well as in the

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improvement of eye health 4,5.

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Because of their attractive color and ease of aqueous extraction, anthocyanins make

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suitable natural replacements for certain synthetic dyes such as FD&C Red 40. Red 40 is the

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most abundant synthetic color additive produced in the US with over six million pounds certified

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production each year. It accounts for almost 25% of the color additives produced in the US 6.

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Synthetic dyes are preferred by the industry to most natural colors due to their lower cost and

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relatively greater stability. However, the use of synthetic dyes has been a topic of public

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controversy due to possible links with a number of detrimental health effects 7. Despite the

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scientific uncertainty of the health effects of synthetic food dyes and additives, growing

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consumer distrust of synthetic ingredients in foods and beverages has increased demand for more

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economical sources of natural food colorants. Currently, anthocyanins are recovered from purple

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fruits and vegetables and the remaining biomass is used as animal feed or is considered waste.

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To meet the growing demand for natural colorants, more economical sources of anthocyanin

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pigments need to be investigated. The focus of this investigation will be on maize anthocyanins.

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Pigmented maize has been utilized as a source of natural colors for centuries. In Andean

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cultures, high anthocyanin yielding “Maíz Morado” is still important for producing local foods

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and beverages 8. Blue corn varieties are also important pigmented maize varieties and are used

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widely for blue corn chips among other products. The distinction between blue and purple corn

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varieties is that purple corn produces anthocyanins most abundantly in the pericarp of the kernel,

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which is the outermost layer of the kernel (Figure 1). Blue corn varieties typically produce

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anthocyanins in the peripheral layer of the endosperm called the aleurone 9. Genetically, the

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location of synthesis is determined by the set of regulatory genes within the variety. The

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combination of Booster1 (B1)/Plant color1 (Pl1) and R1/Colorless1 (C1) most often determine

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pericarp color and aleurone color, respectively, although there are exceptions 10–12. Pigmented

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maize presents a unique opportunity from a processing standpoint because the normally

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inexpensive pericarp tissue can be isolated using one of several milling processes commercially

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available to concentrate pigmented fractions while the remaining fractions can be sold for the

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production of food, fuel, or feed 13.This provides the opportunity for anthocyanin colorants to be

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value-added co-products in the corn processing supply chain.

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The chemical structure of an anthocyanin consists of an anthocyanidin bound to a

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glycoside. Three types of anthocyanidins are known to be produced in maize: pelargonidin,

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cyanidin, and peonidin. These differ by hydroxylation or methoxylation of the phenyl group on

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the flavylium cation. The structure of an anthocyanidin molecule is provided in Figure 2. A

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flavonoid 3’-hydroxylase (F3’H) adds the hydroxyl group to the 3’-position of flavanones and

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dihydroflavonols during the production of cyanidin. This is accomplished by the Purple

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aleurone1 (Pr1) gene in maize 14. Subsequently, an anthocyanin O-methyltransferase (OMT) can

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add a methyl group to cyanidin to form peonidin. The OMT in maize has not been characterized

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to date. Flavanones can also be converted to phlobaphene pigments if an active Pericarp color1

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(P1) gene is present. Phlobaphenes are water insoluble red pigments found in pericarp, cob and

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tassel glumes, and husks 15.

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The anthocyanin glycoside in maize is most often glucose, but arabinose, galactose,

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rutinose, and rhamnose glycosides have been detected 16-18. The glycoside is often modified by

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acylation, commonly in the form of malonylation. Malonylation increases stability in planta by

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protecting the glycosylated sugar from enzymatic breakdown and stabilizing the anthocyanin

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structure under more alkaline conditions 19. Malonylation has also been shown to increase

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anthocyanin content (AC) by enhancing anthocyanin solubility and increasing uptake into

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vacuoles 20.

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Another modification that may be important for stability is the formation of flavanol-

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anthocyanin dimers, also known as “condensed forms”. These compounds were first discovered

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as a product of wine fermentation 21. Since their discovery in wine, condensed forms were found

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to be important naturally occurring pigments in many crops, including strawberries, black

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currants, beans, and maize. The major condensed forms in maize were first characterized by LC-

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MS/MS and H-NMR in a previous study 22.

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Maize has potential as an economical source of natural colors due to its high yield

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potential and the large market for processed maize byproducts. To assess the diversity of

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anthocyanin production in maize, 398 diverse accessions of pigmented maize were analyzed

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using High Performance Liquid Chromatography (HPLC). To test repeatability and/or

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heritability of this trait, a subset of these accessions were grown for several seasons and analyzed.

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To our knowledge, this is the largest collection gathered to date for the purpose of characterizing

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anthocyanin production in maize. Data from this investigation will provide information to plant

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breeders looking to develop varieties of maize with enhanced levels of stable anthocyanins to be

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used as an economical source of natural colorants in foods and beverages.

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Materials and Methods

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Plant Materials

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Pigmented maize (Zea mays L.) accessions were collected from the North Central

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Regional Plant Introduction Station (NCRPIS) in Ames, IA, USA; the International Maize and

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Wheat Improvement Center (CIMMYT) in Mexico; Native Seeds/SEARCH (NS) in Tucson, AZ,

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USA; the Maize Genetics Cooperation Stock Center (MGCSC) in Urbana, IL, USA; and various

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commercial sources (See Table S1). Representative kernels of the original stock analyzed on the

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HPLC were designated as the first pseudo-environment. In 2014, remaining stock from the

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NCRPIS, MGCSC, and commercial sources were grown in two replications at the University of

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Illinois Vegetable Research Farm in Champaign, IL, USA (40˚ 04′ 38.89″ N, 88˚ 14′ 26.18″ W)

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with 7.62 m plots spaced 0.76 m apart. In 2015, a subset of 43 accessions was grown in a

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randomized complete block design at the same location with three replications in 7.62 m plots

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and 0.76 m spacing (Table 1). The subset of 43 accessions was initially chosen based on

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estimated yield potential from 2014 data. If it was known that an accession would not be able to

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produce sufficient kernels for analysis, it was excluded. After grain yield, accessions were

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narrowed down based on their phenotypic stability. Many accessions were segregating for genes

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with large effects on anthocyanin composition and were avoided in the subset. Accessions still

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unknowingly segregating only had the genetically dominant phenotype included for analyses.

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For both years, individual plants were self-pollinated to maintain genetic purity and to produce

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stock for the next season. After harvest, ears were dried in a heated forced air dryer (35 ˚C) for at

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least five days to maintain a similar moisture percentage and then shelled. Ears of a given plot

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were either shelled separately or as a bulk sample. In 2014, samples from one plot were analyzed

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in most cases. In 2015, a maximum of three ears per plot were chosen for analyses and averaged.

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Sample Preparation

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Representative kernel samples (30-50 kernels) of each accession were ground to a fine

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powder in a coffee grinder. Accessions knowingly segregating for pr1 alleles were separated

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visually (blue/purple vs. pink/red) and analyzed separately. One gram of whole corn powder was

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weighed into a 15 mL conical centrifuge tube and extracted with 5 mL 2% (v/v) formic acid

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(ACS Reagent Grade) in distilled, 2 µm Millipore (Billerica, MA, USA) filtered water. To

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compare aqueous formic acid extraction to an organic solvent extraction, one gram of MM was

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extracted in 5 mL 0.01% HCl in methanol. Air in the centrifuge tube was purged with argon (0

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grade or purer) before extracting overnight (12-16 hours). Samples were kept in the dark, at

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room temperature, and were constantly rotated on a LabQuake (Thermo Fisher Scientific Inc.)

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test tube rotator to evenly extract the powder. After extraction, samples were centrifuged and the

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supernatant was filtered through a 25 mm 0.45 µm Millex Millipore LCR PTFE syringe filter.

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HPLC Analysis

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The technique by West and Mauer (2013) was adapted for this work 23. A 20 µL aliquot

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of anthocyanin extract was separated within a Grace Prevail C18 5 µm (250 mm x 4.6 mm)

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analytical column (W. R. Grace & Co., Columbia, MD, USA) maintained at 30.0 ˚C on a Hitachi

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L-7250 HPLC (Hitachi High Technologies America, Inc., Schaumburg, IL, USA) equipped with

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a Hitachi L-7400 ultraviolet-visible detector set to 520 nm to generate chromatograms. The

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mobile phase used 2% (v/v) formic acid as solvent A and 100% acetonitrile (HPLC grade) as

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solvent B at a flow rate of 1 mL/min in the following linear gradient: 100% to 90% A for 3 min,

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60% A at 30 min, then 100% A at 35 min. The column was allowed to equilibrate for 10 min

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before each sample with 100% A.

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Anthocyanin Content (AC)

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Anthocyanin content (AC) was determined by summing peak areas integrated on the

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Hitachi HPLC Software Management 4.0 software. All measurements were calibrated using a

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bulk sample of commercially available Angelina’s Gourmet Maize Morado (MM) (Swanson, CT,

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USA) as a relative external standard. To prepare bulk MM standard, large quantities of MM

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kernels would be ground in a coffee grinder then extracted as described above. AC of each new

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batch of MM powder was quantified using cyanidin 3-glucoside (C3G) standard (Phytolab

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GmbH & Co., Vestenbergsgreuth, Germany). C3G standard curves ranging from 1 to 1000

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µg/mL were produced using Excel (Microsoft Corp., Redmond, WA, USA). AC of MM was

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determined to be approximately 1000 mg/kg C3G equivalents, based on the C3G standard curve.

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MM was included in every new sample run. A run was considered new if the HPLC was turned

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off and a new set of samples were extracted. MM standard was a relative check to ensure

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consistency between batches. To quantify the anthocyanin content of a sample per weight of

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whole corn, Equation 1 was used. In Equation 1, AC is expressed in units of mg anthocyanins in

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C3G equivalents per kg whole corn relative to the MM concentration. For simplicity, units for

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AC will be shortened to mg/kg from this point forward. In Equation 1, MM represents the Maize

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Morado concentration of 1000 mg anthocyanins per kg MM.

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Equation 1:

=

×

Anthocyanin Identification C3G, pelargonidin 3-glucoside (Pg3G), and peonidin 3-glucoside (Pn3G) standards were obtained from Phytolab GmbH & Co. (Vestenbergsgreuth, Germany) at 89% purity and run to

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determine retention times (Figure 3). Remaining compounds identified were presumed based on

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atomic masses obtained by LC-MS and by comparing elution order seen in previous literature 24-

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cyanidin 3-(3”,6”-dimalonyl)glucoside (C3DMG). Because of this, the proportion of peonidin or

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cyanidin in a sample can only be estimated. The proportion of condensed forms was calculated

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by summing the areas of peaks eluted before C3G. The retention time for the major condensed

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form, catechin-(4,8)-cyanidin-3,5-diglucoside, is within this region according to LC-MS results.

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The formation of this condensed form was generally accompanied by several other minor peaks

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which eluted before C3G and are tentatively identified as condensed forms (Figure 3c).

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Proportion of acylation was calculated by summing the peak areas of major identified acylated

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compounds: Pg3MG, Pn3MG, C3DMG, cyanidin 3-(6”-malonyl)glucoside (C3MG),

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pelargonidin 3-(3”,6”-dimalonyl)glucoside (Pg3DMG), and peonidin 3-(3”,6”-

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dimalonyl)glucoside (Pn3DMG). Concentrations of individual compounds in mg/kg were

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calculated similarly to AC in Equation 1. The only difference is the Total Peak Area Sample

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term is substituted with peak area of the compound.

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Microscopy

. In the gradient method used, peonidin 3-(6”-malonyl)glucoside (Pn3MG) coelutes with

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Blue aluerone pigmented kernels and purple pericarp pigmented kernels were soaked in

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deionized water overnight to soften prior to sectioning. Using a razor blade, kernels were cut in

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half sagittally and subsequently embedded in O.C.T. compound (Thermo Fisher Scientific,

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Waltham, MA, USA) in a 15 mm x 15 mm x 5 mm disposable vinyl specimen mold (Sakura

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Finetek USA, Inc., Torrance, CA, USA). After freezing, 14 µm sections of each embedded

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kernel were cut using a Leica Reichert Cyrocut 1800 cryostat (Leica Biosystems, Buffalo Grove,

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IL, USA) at -15°C. Sections were imaged at 40x using an Olympus BX51 microscope (Olympus

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America Inc., Lombard, IL, USA) equipped with a Canon EOS Rebel T3i Digital SLR Camera

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(Canon U.S.A. Inc., Lake Success, NY, USA)

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Statistical Analyses

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Coefficient of variation (CV) was calculated as (σ / ̅ ) × 100 where σ is the standard

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deviation and ̅ refers to the average of the samples. Tukey Honest Significant Differences

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(HSDs) among the various anthocyanin compositional categories were calculated using Proc

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GLM in SAS Enterprise Edition Release 3.5 (SAS Institute Inc., Cary, NC, USA). Correlations

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between compounds used the average concentrations (mg/kg) from each accession and were

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calculated using Proc Corr in SAS. Principal component analysis (PCA) was performed in R

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using the “princomp” function 27. Peak areas for all known compounds or groups of compounds

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were converted to percentages of total peak area in the sample so before principal components

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(PCs) were calculated. PCA was performed on the variance-covariance matrix since phenotypes

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were already approximately normalized when converted to percentages. Hierarchical clustering

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used Ward’s minimum variance method in R 27,28. PCA plots were generated using the ggplot2

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function 29. Mixed model ANOVAs were calculated using Proc Mixed in SAS with method

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equal to Type 3. The model to calculate a single year ANOVA is shown in Equation 2. yijk is the

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response for the phenotype, µ is the grand mean, is the random effect of the ith replication

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with variance σ2r, is the random effect of the jth genotype with variance σ2g, and ε(ij)k is the

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random error term with variance σ2error.

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Equation 2:

= μ + + + #$

)%

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The model to calculate a multiple-year ANOVA is shown in Equation 3. yijkl is the response for

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the phenotype, µ is the grand mean, ' is the random effect of the ith environment with variance

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σ2e, $) is the random effect of the jth replication within environment with variance σ2r(e), is 9


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the random effect of the kth genotype with variance σ2g, ' is the random interaction of the kth

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genotype in the ith environment with variance σ2g×e, and ε(ijk)l is the random error term with

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variance σ2error.

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Equation 3:

= μ + ' + $) + + ' + #$

)

Heritability Calculations Broad-sense heritability (H2) was calculated using the method from Bernardo 30 and

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adapted as shown in Equation 4. In Equation 4, r is the average degrees of freedom fornumber

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replications across all years (r=2) and e is the number of environments (e=3). All variance

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components were estimated using Proc Mixed in SAS with the model in Equation 3.

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Equation 4:

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Results and Discussion

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Extraction and HPLC Method

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()* * , ,* ()* + )×+ -../. .×-

Presented here is a simple and reproducible method for analyzing anthocyanin

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composition and content in maize. Using bulk MM as a relative standard simplifies

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quantification, reduces run time, and reduces costs by eliminating the reliance purely on

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standards. Since MM was replicated 2 to 3 times every new run, a good estimate of extraction

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repeatability can be calculated. A subsample of nine extractions of MM from the same bulk

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powder was chosen to calculate repeatability. The CV of the nine runs ranged from 0.62% to

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6.06% with an overall average CV of 2.92% (data not shown), meaning the HPLC method has

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high consistency within runs of samples. Error can be introduced when a new bulk sample of

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MM is ground and goes uncalibrated. Every new batch of bulk MM powder must be calibrated

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with C3G standard to ensure that relative quantification is accurate. The CV was also compared

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among five 2 g and five 1 g samples of MM powder extracted with a 1:5 (w/v) dilution as

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described above. CV was similar (2% to 4%) with both extraction methods indicating both have

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highly repeatability (data not shown). More whole corn powder should theoretically increase

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homogeneity, but a 1 g to 5 mL dilution was chosen for consistency in an effort to minimize

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sample/seed destruction.

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The extraction method here is reproducible, but cannot be considered an exhaustive

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extraction of anthocyanins. An exhaustive extraction method was not chosen because it would

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increase the technicality of the protocol, the time to complete the protocol, and the reagent costs.

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The method was developed so large amounts of samples could be analyzed. Since anthocyanin

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composition was of interest in this investigation, high-throughput techniques like the pH

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differential method 31 and Near-Infrared Spectroscopy (NIR) were not utilized. In the future,

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non-destructive NIR can be utilized if AC is the only measure of interest. This technique has

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been demonstrated in grapes 32 and flowering teas 33 and is currently used for determining major

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constituents like oil, protein, starch, etc., in maize grain 34.

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The aqueous extraction utilized in this study was meant to more closely resemble

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commercial extraction procedures for purposes of comparison. Acidified methanol is a common

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alternative to the extraction method used here. Using the same HPLC method, it was found that

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an aqueous extraction was better at extracting condensed forms and acylated anthocyanins than

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an organic solvent (data not shown). Preferentially extracting these compounds is advantageous

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because condensed forms and acylated anthocyanins are thought to be important pigments for

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AC and stability. Knowing that certain compounds extract more efficiently in different solvents,

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compound proportions calculated here are relative to the extraction method and not absolute.

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Despite these limitations, this extraction method is efficient, reproducible, and ideal for assaying

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numerous samples that would be expected in a breeding program.

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Categorization of Accessions

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With the abundance of accessions in the survey, categories based on visual characteristics

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and compositional data were developed to make meaningful clusters. Of the 398 accessions

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collected, 167 were capable of producing anthocyanins in detectable amounts in the grain.

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Categorization of anthocyanin-producing accessions with anthocyanin yields are shown in Table

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S1. A summary of Table S1 is in Table 2. Phlobaphenes were the most common flavonoids

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outside of anthocyanins (n=166). Phlobaphenes are brick-red pigments that can be mistaken for

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anthocyanin coloration (Figure 4f). These pigments are produced in anthocyanin-pigmented lines

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if an active P1 regulatory gene is present. These pigments are not extractable with aqueous

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solvents, which is not ideal for food and beverage systems 15. A list of phlobaphene-producing

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accessions is in Table S2. This list may not be complete since accessions that produced

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anthocyanins in the pericarp masked phlobaphene pigments. A few accessions (n=11) produced

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bronze pigments not detectable with the HPLC method used (Figure 4g). Many of these

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accessions may be homozygous recessive Bronze mutants 35. A list of accessions producing

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bronze pigments is also in Table S2.

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Within the anthocyanin producing germplasm, accessions were categorized visually

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based on the presence/absence of anthocyanins in the pericarp (Figure 1). Aleurone layers do not

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develop near the germ of the kernel, which aids in the categorization of aleurone- versus

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pericarp-pigmented accessions (Figure 4a, 4b, and 4d). Accessions for which visual

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categorization was uncertain were sectioned roughly with a razorblade and viewed under a

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compound microscope. Aleurone-pigmented accessions had the highest representation in the

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survey. Over 82% (n=137) were capable of producing pigments in the aleurone (Table 2).

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Several accessions (n=4) were found to produce anthocyanins in both kernel layers. Separating

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the two layers is difficult, so in all cases the accessions that produced anthocyanins in both layers

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were combined with aleurone-pigmented lines for analyses. The AC of these four accessions

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ranged from 22.6 to 85.2 mg/kg, which is within the normal range observed for aleurone-

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pigmented accessions.

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Within the category of kernel tissue (pericarp or aleurone) pigmentation, accessions could

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be further divided based on anthocyanin composition. Pericarp-pigmented accessions were

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further subdivided based on the presence/absence of condensed forms (Figure 3c and 3d).

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Aleurone-pigmented lines could be visually separated by whether they produced blue or pink

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kernels (Figure 4a and 4b). In the pink aleurone category, Pg3G and its derivatives are the most

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abundant pigments (>50% of total pigments) while in the blue aleurone category, C3G and its

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derivatives are most abundant. Genetically, this is due to a homozygous recessive pr1 gene that

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is unable to convert Pg3G precursors to C3G precursors 14. Only three homozygous pr1

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recessive accessions produced anthocyanins in the pericarp. Puebla 403 (PI 485071) and Puebla

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456 (PI 489081) produced both pericarp and aleurone pigmentation, while Apache Red (Siskiyou

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Seeds, Williams, OR, USA) produced anthocyanins exclusively in the pericarp. Apache Red was

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also unique because it abundantly produced condensed forms that are generally in low

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abundance or undetectable in other accessions.

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In addition to these four compositional categories, a unique trait was discovered that had

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previously never been characterized in maize. Seven accessions within the collection produced

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markedly less acylated anthocyanins than most other accessions (Figure 3e). Average C3G

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content per category ranged from 2.99% to 28.3% of AC in typical accessions (Table 2). In

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accessions with this unique trait, C3G was the dominant pigment and averaged 57.7% of total

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anthocyanins. Some acylated anthocyanins can be detected in these unique lines, but the average

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is only 7.6%, which is much lower than the average of 58.9% observed in other categories. This

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unique phenotype has been found in several diverse backgrounds that seem to have no relation.

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This trait will be referred to as “reduced acylation”. The hypothesis is that reduced acylation is

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due to a functionally reduced anthocyanin acyltransferase.

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It is important to note that some accessions belonged to more than one category. All the

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compositional categories presented here can be described by the actions of a few genes, so

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segregating between categories is common. Accessions belonging to more than one category

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were coded as unique accessions so accurate conclusions could be made about each category in

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terms of composition. For example, Apache Red was segregating for pr1 alleles and the ability to

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produce condensed forms simultaneously, so it appears four times in Table S1.

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AC Results

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Across the whole survey, average AC was 64.7 mg/kg with an individual sample

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maximum of 2560 mg/kg (PI 571427; Table 2). The highest performing accession in terms of

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AC was the Peruvian landrace named Arequipa 204 (PI 571427) that had an average AC of 1100

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mg/kg (Table S1). Andean purple corn landraces in general had high AC, but very low grain

340

yield. Landraces from the tropics are poorly adapted to the Midwest and are plagued with

341

photoperiod sensitivity and disease susceptibility 36. Adapting these landraces to the Corn Belt

342

region of the US will require backcrossing to Midwestern inbreds to improve grain yield. Within

343

the aleurone-pigmented accessions, the highest total anthocyanin yielding varieties were genetic

344

stocks provided by the Maize Genetics Cooperative Stock Center that were homozygous

345

recessive for intensifier1 (in1). Genetic stocks designated 707G and 707B were differentiated by

14



346

homozygous dominant and recessive Pr1 alleles, respectively. 707G and 707B averaged 133

347

mg/kg and 128 mg/kg, respectively, which contained almost 1.5 times the AC of the next best

348

aleurone-pigmented accession (Table S1). This demonstrates the importance of in1 as an

349

enhancer of AC in the aleurone.

350

The highest-performing category in terms of AC was that of pericarp-pigmented

351

accessions that could produce condensed forms (Table 2). The condensation of flavanols with

352

anthocyanins may provide improved stability to the compounds, just as malonylation does in

353

planta. In general, pericarp-pigmented accessions have a greater AC potential. This is in

354

agreement with other studies that found the highest AC in purple pericarp corn 18,37,38. The

355

greater potential for anthocyanin production in pericarp may be due to the processes that form

356

pericarp tissue. Pericarp during kernel development contains as many as 5 to 22 cell layers due to

357

the fusion of maternal tissues during development 39. Typically, the aleurone is only a single

358

layer, but several accessions have been found that are capable of producing up to six layers 40.

359

Integrating multiple aleurone layers and the in1 gene may be a route to increase AC in the

360

aleurone.

361

Comparisons between categories found no statistical difference in AC between blue and

362

pink aleurone accessions (p>0.05), but on average, pink aleurone had lower AC (Table 2). Blue

363

aleurone accessions were not statistically different for AC from pericarp-pigmented lines without

364

condensed forms, but pink aleurone was significantly different. The most likely reason

365

significance could not be established was because of the underrepresentation of pericarp-

366

pigmented accessions in the survey. Only thirteen accessions were included in the pericarp-

367

pigmentation without condensed forms category, while 98 were included in blue aleurone

368

category.

15


Page 16 of 39

Page 17 of 39

369 370


Compositional Differences Between Compositional Categories Proportion of known acylated compounds was lowest (7.6%) in the reduced acylation

371

category, as expected (Table 2). However, acylation was also significantly lower in the pericarp-

372

pigmentation with condensed forms category. One possible explanation may be due to the

373

limited identification of condensed forms. González-Manzano et al. (2008) 19 confirm that

374

malonylglucoside anthocyanins can be conjugated to catechins and epicatechins. Many acylated

375

anthocyanins may have been included within the condensed form calculation. With the results of

376

this survey, it can be concluded that acylated anthocyanins are typically the most predominant

377

pigments produced in maize. Despite preferential extraction of acylated anthocyanins in aqueous

378

solvents, the result found here is similar to other studies that analyzed blue and purple corn 18,37,41.

379

Acylation has been shown to increase stability, which may help maize be a more economical

380

source of natural colorants 42.

381

C3MG is the single most abundant compound, on average, in the whole collection. It was

382

the most abundant compound in the pericarp-pigmented without condensed forms and blue

383

aleurone categories with a difference of C3G of 3.98% and 16.4%, respectively. The fact that

384

C3MG is in higher abundance than C3G is in contrast with another study that found C3G to be

385

31% to 51% of total anthocyanins in Pr1 dominant lines 18. Abdel-Aal et al. (2006) 18 used an

386

acidified methanol extraction which may have inflated the C3G concentration within their

387

samples and may explain this discrepancy.

388

Pink aleurone accessions were much more represented in this collection than previously

389

reported in other pigmented maize collections, indicating that pr1 recessive alleles are common

390

variations in maize germplasm. Homozygous recessive pr1 lines almost always produced low,

391

but detectable amounts of C3G, although non-functional alleles of pr1 should not theoretically be

16



392

able to produce C3G. This may be evidence that homozygous recessive pr1 alleles have reduced

393

or repressed function, or possibly there is an additional F3’H expressed in maize at lower levels

394

than Pr1 43. Selecting for pr1 recessive alleles in breeding programs can provide a wider range of

395

hues in anthocyanin extracts that the food industry may be able to utilize. Higher proportions of

396

pelargonidin pigments within extracts tend to produce orange to red-orange hues, while

397

cyanidin-predominant extracts tend to produce red to purple hues (Figure 4). The pink aleurone

398

category did not have significantly greater proportions of total acylation, but it did have greater

399

proportions of Pg3DMG compared to all other categories. The proportion of dimalonyl

400

anthocyanins in pink aleurone lines may be indicative of the rate of dimalonyltransferase activity

401

in maize. Since Pn3MG and C3DMG co-elute in our current protocol, dimalonylglucoside

402

content cannot be measured directly, but the Pg3MG:Pg3DMG ratio in pink aleurone accessions

403

may inform of the C3MG:C3DMG ratio in others. For future work, if the concentration of

404

C3DMG in a sample is of interest, the proportion of cyanidin and peonidin anthocyanins before

405

and after acid or alkaline hydrolysis is an alternative way to calculate approximate C3DMG

406

concentration 37.

407

Peonidin has potential for adding stability to maize extracts and is therefore a pigment

408

that must be investigated. It has been demonstrated that anthocyanins with fewer free hydroxyl

409

groups on the B-ring tend to be more stable, but the results are somewhat unclear 44.

410

Nevertheless, the category with the highest proportion of Pn3G was pericarp-pigmented without

411

condensed forms (Table 2). This category also had the highest average abundance of Pn3DMG

412

with 4.5 mg/kg, on average. Generally, peonidin was in low amounts in all samples.

413 414

Condensed form pigments are much more prevalent in this study than previously found. An earlier characterization of condensed form pigments in maize found them to account for 0.3%

17


Page 18 of 39

Page 19 of 39


415

to 3.2% of total anthocyanins 22. In the condensed form category of this study, the average

416

proportion of condensed forms in each accession ranges from 3.8% to 32.8%, with an overall

417

average of 22.7% (Table S1). The most abundant condensed form in maize, catechin-(4,8)-

418

cyanidin-3,5-diglucoside, was characterized in González-Manzano, et al. (2008), but also

419

confirmed here with LC-MS (data not shown) 22. In MM, this pigment alone is approximately

420

13% to 14% of total anthocyanins. The underrepresentation of condensed forms in most studies

421

may be due to the utilization of acidified methanol as the choice solvent system. Aqueous

422

solvents should be utilized to accurately represent the concentration of these pigments since they

423

have potentially important effects on AC. Wide variation in condensed form content among

424

accessions in the collection indicates there may also be genetic diversity for condensed form

425

production that can be improved with breeding.

426

Correlation of Compounds

427

Initially, correlations were calculated using the complete dataset, regardless of category.

428

Concentrations of each compound significantly correlated with the AC of the sample. Most were

429

moderate to strong correlations (ρ>0.60) with the exception of Pg3DMG in the complete data set

430

(ρ=0.32). When separating the dataset by Pr1 alleles, the correlation of Pg3DMG improved to

431

≈0.60 and ≈0.70 for dominant and homozygous recessive alleles of pr1, respectively (Table S3).

432

Principal Component Analysis (PCA)

433

Overall, the principal component analysis (PCA) was effective at explaining a large

434

proportion of the variability in the dataset (Figure 5a). Principle component 1 (PC1) explained

435

60.1% of the total variance, and PC2 explained 23.8% of the total variability in the data set.

436

Based on the loadings, PC1 primarily appears to be explaining the variability associated with the

437

presence or absence of functional Pr1 alleles. Cyanidin-based anthocyanins have positive PC1

18



438

loadings, while pelargonidin-based anthocyanins have negative PC1 loadings (Table S4). PC2

439

primarily appears to be a contrast between accessions with higher proportions of condensed

440

forms and C3G versus accessions with higher proportions of acylated anthocyanins.

441

Observations with the highest scores for PC2 tended be aleurone-pigmented accessions, while

442

the most negative observations in PC2 were more indicative of pericarp with condensed forms

443

and the reduced acylation category. Pericarp without condensed forms were intermediate in PC2

444

most likely due to the higher proportion of C3G on average than the blue aleurone category

445

(Table 2).

446

Additionally, by visual observation, the biplot suggests there may be three natural groups

447

within the compositional data. A hierarchical clustering approach was used to cluster accessions

448

without a priori knowledge so clustering could be unbiased. Ward’s minimum variance method

449

was used for hierarchical clustering 28. While dividing the dendrogram at the largest distance

450

would produce two clusters in the dataset, dividing to make three clusters provides more

451

separation and makes more meaningful clusters (Figure 5b). The first cluster comprises a bulk of

452

the dataset and includes blue aleurone lines and pericarp without condensed forms. The second

453

cluster is mainly a mixture of pericarp-pigmented accessions that produce condensed forms and

454

reduced acylation accessions, but pericarp accessions without condensed forms are also within

455

this cluster. The third cluster consisted of accessions homozygous recessive for pr1 and includes

456

all pink aleurone accessions plus Apache Red. Results of the PCA show that variation in

457

composition is largely explained by genetic factors that have a large effect on composition. This

458

provides evidence that the visual and compositional categories created for the accessions are

459

sufficiently explaining the biology of the collection.

19


Page 20 of 39

Page 21 of 39

460 461


Heritability of Anthocyanin Content A representative subset of the survey was planted in 2015 with three randomized

462

replications to test the repeatability of anthocyanin production (Table 1). Table 1 shows the

463

number of ears analyzed for each accession. Some had limited representation because in certain

464

years, entire plots would be lost to disease pressure associated with the poor adaptation of that

465

germplasm to the Midwestern growing environment. Accessions with data from every year were

466

included in the analysis because they provide more degrees of freedom to test environments.

467

Although there were several accessions cut from the original collection, the subset still

468

accurately represented the whole survey. The limitation of the entire survey overall was the

469

limited representation of pericarp-pigmented accessions, which are of most importance for AC.

470

There were no lines with condensed forms chosen for the 2015 subset because these accessions

471

could not produce enough grain for analysis. Conclusions drawn from this subset may more

472

accurately describe the genetics of aleurone-pigmented lines rather than pericarp-pigmented lines.

473

Within 2015, the effect of replication for AC was insignificant (p=0.70), meaning that

474

AC does not change drastically within the same environment (Table 3). Since replications were

475

occasionally significant in 2015, the term was kept in the model for the combined analysis

476

(Equation 3). A strong estimation of variance due to replication could not be calculated since

477

there was only a single replication in the source packets and most often only a single replication

478

in 2014. Genotypic variance was always much higher than variance for replication, so the

479

variance of this term should have a small effect on H2 calculations. Results of subset of

480

accessions tested across years show high consistency in anthocyanin composition from

481

environment to environment. The variances contributed by genotype by environment effects are

482

magnitudes lower than the variances due to genotypes in all cases (Table 4).

20



483

H2 for each compound or group of compounds is listed in Table 5. The lowest H2 are

484

from peonidin-based compounds Pn3G (H2=0.76) and Pn3DMG (H2=0.53). These two

485

compounds generally had low or undetectable concentrations in most samples. The compound

486

with the highest H2 was C3G, with an H2 of 0.97. AC results were promising, with values of 0.93

487

for untransformed and log-transformed AC. High H2 values mean most of the variability in

488

anthocyanin production is attributed to genetics and not environmental factors. Due to the

489

apparently significant genetic control of AC and minimal environmental effect, it is likely that

490

breeding for increased AC and estimating the genetic potential of potential breeding lines can be

491

done with relatively few replications and locations.

492

Results of this survey are consistent with Ryu et al. (2013) 30 that found no outstanding

493

differences between 48 US/Mexican landraces grown in Ohio and Arizona. Jing et al. (2007) 27

494

found that purple corncobs grown in three locations around Lima, Peru did not vary significantly

495

either, but across all locations in Peru, they were significantly different according to an ANOVA.

496

Several factors varied across the locations in these two studies: precipitation, elevation,

497

temperature, etc. Any combinations of these factors may have influenced anthocyanin production.

498

From the data presented here and some support from the two other studies, it appears that the

499

results of this study can extend to environments typical of the Corn Belt region of the US.

500

Maize is a diverse source of anthocyanins and has great potential as an economic source

501

of natural colors. Here, 398 pigmented maize accessions were screened for anthocyanin content

502

and anthocyanin-containing accessions were categorized based on the kernel layer in which the

503

anthocyanins loaded as well as anthocyanin composition. This investigation represents the most

504

comprehensive analysis of anthocyanin content in maize germplasm to date. Presented here is a

505

simple and repeatable high-throughput method for analyzing anthocyanin composition and

21


Page 22 of 39

Page 23 of 39


506

content in maize. Five anthocyanin production categories were identified for the 167

507

anthocyanin-pigmented accessions in the survey. One category has previously never been

508

described in maize; some accessions produced markedly less acylated anthocyanins than the

509

typical anthocyanin-producing lines. The genetics behind this unique trait are currently being

510

investigated. PCA was performed on compounds quantified by HPLC and compositional

511

categories were confirmed by hierarchical clustering, confirming their efficacy in describing the

512

variation seen in this survey. Since the main goal of this study was to provide information to

513

plant breeders, the category of accessions from this survey that should be of most interest for

514

developing anthocyanin-rich hybrids are the pericarp-loading accessions with high proportions of

515

condensed forms. Andean purple corn landraces may be a key to developing new purple corn

516

hybrids, but issues with adaptation and grain yield need to be overcome for them to be more

517

economical. To provide a broader range of hues in maize extracts for the food and beverage

518

industry, pr1 recessive alleles should be incorporated into these purple corn accessions. Breeding

519

for AC and anthocyanin composition will be straightforward, according to the H2 results, since

520

most of the phenotypic variance is controlled by genetic factors as opposed to environmental

521

factors. Marker assisted selection to breed for purple corn has already been demonstrated 10,46.

522

Selecting for the major regulatory genes B1/Pl1 can aid in the rapid development of purple corn

523

varieties. AC of maize on a whole kernel basis is much lower than AC reported for fruit and

524

vegetable juices, but maize has value-added benefits fruit and vegetable juices do not have 47.

525

Current milling processes are able to concentrate pericarp fractions for a higher anthocyanin

526

recovery 13. Pericarp fractions can then be collected for anthocyanin extraction while the rest of

527

the kernel can still be utilized for food, fuel, and feed. These value-added benefits should make

528

maize an economical source of natural colors.

22



529 530

Acknowledgements: This work was supported by a grant from the Kraft Heinz Company of

531

Glenview, Illinois. Fellowship support for Michael Paulsmeyer was provided by the Illinois Corn

532

Grower’s Association. Fellowship support for Laura Chatham was provided by The Monsanto

533

Company.

534

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615 616 617 618 619 620

26



621

Figure captions:

622

Figure 1: Micrographs showing pigmentation in the major anthocyanin-producing tissues of the

623

maize kernel: Pericarp (A) and aleurone (B)

624

Figure 2: Structure of an anthocyanidin molecule with molecular nomenclature. R = H,

625

Pelargonidin; R = OH, Cyanidin; R = OCH3, Peonidin.

626

Figure 3: Representative HPLC chromatograms of each anthocyanin category.

627

Figure 4: Kernel samples from each major pigment category; blue aleurone (A), pink aleurone

628

(B), blue aleurone without acylated anthocyanins (C), pericarp without condensed forms (D),

629

pericarp with condensed forms (E), phlobabaphenes (F), and bronze pigment (G).

630

Figure 5: (A) Prinicipal component analysis (PCA) of all anthocyanin containing lines. PC1 and

631

PC2 explained 60.1% and 23.8% of variability in the dataset, respectively. Individual

632

observations are colored by cluster determined using hierarchical cluster analysis, while shapes

633

indicate pigment location in the kernel. Eigenvector numbers correspond to labels given in

634

Figure 3f. (B) Dendrogram illustrating results from hierarchical cluster analysis.

27


Page 28 of 39

Page 29 of 39


635

Figures and Tables

636

Figure 1

637

638

28



639 640

Figure 2

641

642 643

29


Page 30 of 39

Page 31 of 39


Figure 3 b) Pink aleurone

a) Blue aleurone 4

5 6

1

2

5

3

7

1

7

c) Pericarp with condensed forms

2

4 6

d) Pericarp without condensed forms

1

4

9

1

6

4 2

3

e) Reduced acylation

2

56

2 3

5 78

f) Legend for identified anthocyanin compounds Label

1

3

Compound

1

Cyanidin 3-Glucoside

2

Pelargonidin 3-Glucoside

3

Peonidin 3-Glucoside

4

Cyanidin malonylglucoside

5

Pelargonidin malonylglucoside

6

Cyanidin dimalonylglucoside / Peonidin malonylglucoside

7

Pelargonidin dimalonylglucoside

8

Peonidin dimalonylglucoside

9

Condensed forms

Note: The x-axis of chromatograms corresponds to retention time in minutes.

30



Figure 4

31


Page 32 of 39

Page 33 of 39


Figure 5

32



Page 34 of 39

Table 1: Subset of 43 accessions grown in 2015 labeled with major phenotypes Accession

Pr11

Tissue2

Acyl3

Count4

Accession

Pr11

Tissue2

Acyl3

Count4

Ames 6084 Z14-008

0

0

0

16

PI 218175 Moencopi Pueblo

0

0

0

4

Ames 14276 Black Beauty

0

0

1

12

PI 340838 B-4541

0/1

0

0

9

Ames 25207 Burford 2

0/1

0

0

4

PI 340841 B-15

0

0

0

11

Ames 27451 A632.75

0

0/1

0

15

PI 340846 RB-15

1

0

0

12

BGEM-0085-N

0

0

0

13

PI 340850 B-17

0

0

0

10

Black Aztec

0

0

0/1

11

PI 340854 RB-17

1

0

0

11

MGCSC 218GA

0

0

0

11

PI 340855 B-18

0

0

0

12

MGCSC 219AA

0

0

0

8

PI 340857 B-22

0

0

0

12

MGCSC 506B

1

0

0

12

PI 483476 Aguascalientes 27

0

0

0/1

10

MGCSC 707B

1

0

0

9

PI 483517 Guanajuato 31

1

0

0

10

MGCSC 707G

0

0

1

14

PI 483527 Guanajuato 98

1

0

0

7

MGCSC M142A

0

0

0

5

PI 485071 Puebla 403

1

0/1

0

4

MGCSC X13l

0

1

0

14

PI 489081 Puebla 456

1

0/1

0

13

MGCSC X19A

0

0

0

12

PI 511613 Nicaragua 115

1

0

0

12

MGCSC X19EA

0

0

0

5

PI 553055 OC2

0

0

0

11

MGCSC Z433C

0

0

0

11

PI 553057 OC4

0

0

0

10

MGCSC Z433E

0

0

0

11

PI 596502 OC15

0

0

0

11

Siskiyou Seeds Hopi Blue Star

0

0

0

6

PI 596503 OC16

0

0

0

4

Ohio Blue Clarage SESE5

0

0

0

9

PI 596504 OC17

1

0

0

12

PI 213756 Fairfax Brown

0

0

0

11

PI 596505 OC18

1

0

0

11

PI 213791 SD RAINBOW

0

0

0

10

PI 596506 OC19

0

1

0

10

PI 217411 Tama Flint

1

0

0

11

1

0 = Pr1__, 1 = pr1pr1 0 = aleurone, 1=pericarp 3 0 = normal profile, 1 = reduced acylation 4 Count refers to the number of HPLC samples 5 SESE = Southern Exposure Seed Exchange, Mineral, VA, USA 2

33


Page 35 of 39


Table 2: Anthocyanin concentration (mg/kg) and composition (% of AC)

Categories

Count of Accession s

AC (mg/kg) 30.81

*

C3G (%)

*

Pg3 G (%)

*

Pn3 G (%)

*

Acylatio n (%)

*

BC

17.91

C

3.82

B

6.58

B

63.19

A

Blue Aleurone

98

Pericarp Condensed

25

251.97

A

28.26

B

4.41

B

7.98

B

35.69

B

Pericarp Not Condensed

13

118.29

B

22.14

BC

5.18

B

11.69

A

56.84

A

46

22.63

BC

7

46.36

BC

167

64.67

Pink Aleurone Reduced Acylation Grand Total

2.99

D

14.88

A

1.11

C

62.84

A

57.23

A

2.33

B

7.40

B

7.57

C

17.40

6.63

5.82

* Means with the same letter are not significantly different with a Tukey HSD p>0.05

34


56.97


Table 3: Type 3 ANOVAs for 2015 for AC and Percentage of Acylation AC 2015

DF

Mean Square

Expected Mean Square

Rep

2

49.64

σ2error + 33.5 σ2r

Variance Components -2.69

Genotype

42

3105.54

σ2error + 2.5476 σ2g

1164.11***

Residual

65

139.82

σ

2

139.82

error

Acylation % 2015

DF

Mean Square

Expected Mean Square

Rep

2

86.74

σ2error + 33.5 σ2r

Variance Components 1.67*

Genotype Residual *** p

Survey of Anthocyanin Composition and ... - ACS Publications

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