MS method for quantitation of phytoestrogens and the distribution of enterolactone in an Alabama estuary

Journal Pre-proof A Rapid UHPLC-MS/MS Method for Quantitation of Phytoestrogens and the Distribution of Enterolactone in an Alabama Estuary

Jingyi Qi, Vanisree Mulabagal, Lan Liu, Caleb Wilson, Joel S. Hayworth PII:

S0045-6535(19)31696-0

DOI:

https://doi.org/10.1016/j.chemosphere.2019.124472

Article Number:

124472

Reference:

CHEM 124472

To appear in:

Chemosphere

Received Date:

19 April 2019

Accepted Date:

26 July 2019

Please cite this article as: Jingyi Qi, Vanisree Mulabagal, Lan Liu, Caleb Wilson, Joel S. Hayworth, A Rapid UHPLC-MS/MS Method for Quantitation of Phytoestrogens and the Distribution of Enterolactone in an Alabama Estuary, Chemosphere (2019), https://doi.org/10.1016/j.chemosphere. 2019.124472

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A Rapid UHPLC-MS/MS Method for Quantitation of Phytoestrogens and the Distribution of

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Enterolactone in an Alabama Estuary

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Jingyi Qi, Vanisree Mulabagal, Lan Liu, Caleb Wilson, Joel S. Hayworth*

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Department of Civil Engineering, Auburn University, Auburn, AL 36849

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*Corresponding Author Contact Information

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Joel S. Hayworth, Ph.D., P.E. Associate Professor 238 Harbert Engineering Center Department of Civil Engineering Auburn University, Auburn, AL 36849 Office: (334) 844-7374 E-mail: [email protected]

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Abstract

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Endocrine disrupting chemicals (EDCs) are natural or synthetic compounds that can interfere

29

with the endocrine systems of humans and wildlife.

30

treatment systems, or run off from urban areas or agricultural operations, into natural water

31

bodies, exposing resident and migratory organisms to complex EDC mixtures.

32

phytoestrogenic polyphenolics (PEPP) are known or suspected EDCs; however, their

33

contribution to total EDC burden in natural surface water systems is largely unknown. We

34

describe a rapid, sensitive, and reproducible quantitative method for analysis of 15 PEPP in

35

estuarine sediment and water, using ultra-high performance liquid chromatography-triple

36

quadrupole mass spectrometry (UHPLC-MS/MS).

37

resolution, peak separation, and rapid run times (method separation/total run time: 8/12.5 min).

38

With two exceptions, spiking experiments demonstrated that the percent recoveries for target

39

PEPP in sediment and water samples were within acceptable analytical validation limits. LOD

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and LOQ values ranged from 0.004 to 0.010 ng/injection and 0.013 to 0.032 ng/injection,

41

respectively. The validated method was used for PEPP analysis of sediment and water samples

42

collected from 11 locations within the Perdido Bay estuary in coastal Alabama. No PEPP above

43

the LOD were detected in sediment samples. The mammalian-derived lignin enterolactone was

44

observed at low concentrations in water throughout the estuary, and significantly, at elevated

45

concentrations at two locations associated with small-scale septic systems (3.66 ± 0.27 ng L-1

46

and 4.01 ± 0.33 ng L-1) and a large wastewater treatment system (4.56 ± 0.24 ng L-1 and 5.69 ±

47

0.43 ng L-1).

EDCs can pass through wastewater

The method provides excellent peak

48 49

Keywords: UHPLC-MS/MS, EDC, phytoestrogens, enterolactone, estuary

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Some

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1.0 Introduction

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Endocrine disrupting chemicals (EDCs) are natural or synthetic compounds that can

52

interfere with the endocrine systems of humans and wildlife, potentially resulting in adverse

53

developmental, reproductive, neurological, and immune effects (NIEHS, 2016).

54

EDCs, there may be no threshold value below which effects do not occur. Also, the effects of

55

mixtures of EDCs can be additive and synergistic, causing organism alterations where individual

56

EDCs may not (Colborn et al., 1996; Diamanti-Kandarakis et al., 2009; Bergman et al., 2013;

57

Gore et al., 2015). Modern human activities are the primary source of EDCs in the environment.

58

It is not uncommon for EDCs to pass through municipal or industrial wastewater treatment

59

systems, or run off from urban areas or agricultural operations, eventually reaching natural water

60

bodies like rivers, estuaries, and marine systems (Laganà et al., 2004; Stackelberg et al., 2004;

61

Bacaloni et al., 2005; Beck et al., 2005; Liu et al., 2010). Resident and migratory organisms

62

living in these natural systems are at risk of exposure to complex mixtures of EDCs.

For many

63

Some phytoestrogenic polyphenolics (PEPP) are known or suspected EDCs (Waring et

64

al., 2008; Liu et al., 2010; Chighizola and Meroni, 2012; Boberg et al., 2013; Ferreira-Dias et al.,

65

2013). PEPP are synthesized in many plants to protect them from predators and to attract

66

symbiotic soil bacteria and insects (Fox, 2004). The major synthesized PEPP are isoflavones and

67

lignans, which are found predominantly in the Leguminosae family (Dixon, 2004). The amount

68

and location of PEPP within individual plants vary; however, many of these compounds are

69

found in food products at high concentrations (Mazur et al., 1998; Kuhnle et al., 2009; Michel et

70

al., 2013).

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There is evidence that some PEPP are structurally and/or functionally similar to ovarian

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and placental estrogens and their active metabolites (Martin et al., 1978; Verdeal et al., 1980;

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Setchell and Adlercreutz, 1988; Whitten and Patisaul, 2001). Phytoestrogenic PEPP are thought

74

to bind to estrogen receptors (ERs) and induce estrogenic or anti-estrogenic responses in target

75

tissues (Shutt and Cox, 1972; Wynne-Edwards, 2001; Bacciottini et al., 2007), or interfere with

76

estrogenic response or the amount of free estrogen in organisms through alternative mechanisms

77

(Michel et al., 2013). Although the estrogen-like hormonal activity of some PEPP is two to five

78

orders of magnitude below that of estradiol, their abundance in certain plants and slow metabolic

79

utilization can lead to tissue concentrations exceeding endogenous estrogen by several orders of

80

magnitude (Ward and Thompson, 2012).

81

Isoflavones with a 3 phenyl chromone ring structure represent the largest group of plant

82

phenolics exhibiting estrogenic activity. Isoflavones with significant estrogenic activity mainly

83

exist as glucosides (daizin, genistin, and glycitin) or methoxylated (formononetin and biochanin

84

A) in soy. Aglycone structures have demonstrated higher estrogenic potency compared to their

85

corresponding glycosides (Clarke et al., 2008).

86

shown ERα agonist activity 100 times more potent than genistein (Quifer-Rada et al., 2013).

87

Studies have demonstrated that flavonoids exhibit higher estrogenic activity when compared to

88

lignans (Whitten and Patisaul, 2001). The most common lignans, matairesinol and

89

secolariciresinol, are found predominantly in flaxseed.

90

mammalian gastrointestinal bacteria to yield enterolactone and enterodiol, respectively (Michel

91

et al., 2013).

8-prenylnaringenin, a prenylflavonoid, has

These lignans are metabolized by

92

Advancements in liquid chromatography/mass spectrometry (LC/MS) instrumentation

93

have led to methods for analyzing some PEPP at low concentrations in food, botanical

94

supplements, and in environmental samples. However, rapid quantitative analysis of multiple

95

PEPP in complex environmental samples at trace concentrations is a continuing need. The goal

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of the work presented here was to develop and validate a rapid, sensitive and reproducible

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analytical method for the detection and quantitation of 15 target PEPP in estuarine sediment and

98

water using ultra-high performance liquid chromatography, triple quadrupole mass spectrometry

99

(UHPLC-MS/MS). We describe an extraction method followed by dispersive solid phase

100

cleanup and UHPLC-MS/MS quantitation. The method presented here was used to investigate

101

the presence and distribution of target PEPP in sediment and water in the northern Gulf of

102

Mexico estuary of Perdido Bay.

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2.0 Materials and methods

104

2.1 Chemicals, reagents and materials

105

A total of 15 PEPP and 1 internal standard were used in this study (Fig. 1). Analytical

106

phenolic standards having >98% purity (daidzein, genistein, biochanin A, formononetin,

107

coumestrol, glycitin, ononin, naringenin, apigenin, resveratrol, 8-pyenylnaringenin, 6-

108

pyenylnaringenin, xanthohumol, isoxanthohumol, enterodiol, enterolactone); chrysin (internal

109

standard), magnesium sulfate, and dimethyl sulfoxide were acquired from Sigma Aldrich (St.

110

Louis, MO), as were Whatman glass microfiber filters GF/C (47 mm). LC/MS grade solvents

111

(methanol, acetonitrile, and water), analytical grade formic acid, and ammonium acetate reagents

112

were acquired from VWR International (Suwanee, GA). Chem Tube-Hydromatrix, ammonium

113

formate, Captiva Nylon/PTFE syringe filters (0.2 µm), analytical columns (InfinityLab Poroshell

114

120 Bonus-RP, 2.1 x 100 mm, 2.7 µm, p/n 861768-901; InfinityLab Poroshell 120 Phenyl-

115

Hexyl, 2.1 x 100 mm, 2.7 µm, p/n 695775-912) and guard column (InfinityLab Poroshell 120

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Phenyl-Hexyl guard column, 2.1x 5 mm, p/n 821725-914) were acquired from Agilent

117

Technologies (Wilmington, DE). Oasis PRiME HLB 6 cc extraction cartridge and 20-Position

118

vacuum manifold were acquired from Waters Corporation (Milford, MA, USA).

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Fig. 1. Chemical structure of 15 target PEPP and 1 internal standard used in this study. 119

2.2 Standard Solutions

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Stock solutions of PEPP reference standards were prepared in a solvent mixture (80%

121

methanol/20% water, v/v) to obtain 1 mg/mL concentration. Working concentrations of

122

reference standards (0.1 µg mL-1 and 0.01 µg mL-1) for method development and for generating

123

calibration curves (concentrations range: 0.1 to 50 ng mL-1) were prepared by diluting stock

124

solutions with the same solvent mixture.

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2.3 Sample collection and storage

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Sediment and water sampling locations are shown in Fig. 2 and summarized in Table 1.

127

Sediment samples were obtained using a vibracore system designed for collecting relatively long

128

cores (10 cm in diameter and up to 2 m in length) in high energy shallow water coastal

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environments (Mulabagal et al., 2017). Surface water samples were collected in duplicate into

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high-density polyethylene (HDPE) containers (~4.1 L total volume per sample container, ~8.2 L 6

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Fig. 2. Sediment and water sampling locations within Perdido Bay watershed. 131

total per sample location) using a 1L stainless steel Kemmerer Bottle water sampler. At each

132

location, water samples were collected at one-half of the total water depth. All sediment and

133

water samples were placed in coolers on ice (approximately 4 ºC) during transportation and

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archived at -20 ºC until analyzed.

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2.4 Sample preparation

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Frozen archived sediment samples (10 cm in diameter and approximately 91 cm in

137

length) were thawed to room temperature and cut into two identical portions: 0-46 cm

138

approximate depth below sediment surface and 46-91 cm approximate depth below sediment

139

surface. Each portion was homogenized and a subsample (10 g ± 0.05 g) placed directly into a

140

Nalgene centrifuge tube. To this hydromatrix (0.5 g), anhydrous magnesium sulfate (0.5 g) were

141

added to enhance sediment homogenization and extraction efficiency. The resultant mixture was

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Table 1 Sediment and water sampling locations within Perdido Bay watershed. Location

Description

Longitude

Latitude

1 2 3 4 5 6

Moccasin Bayou Middle Wolf Bay Lower Wolf Bay Intracoastal Waterway Perdido River Mouth of Elevenmile Creek

-87.60110 -87.58830 -87.61080 -87.58910 -87.39970 -87.37720

30.34883 30.32215 30.30161 30.30012 30.45064 30.45778

7 8 9 10 11

Mouth of Bayou Marcus Upper Perdido Bay Middle Perdido Bay Lower Perdido Bay Tarkiln Bayou

-87.34000 -87.37400 -87.41990 -87.45090 -87.42220

30.43054 30.43432 30.40769 30.36529 30.35155

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extracted with 10 mL of solvent (70% methanol and 30% water). The combined sediment-

143

hydromatrix-anhydrous sulfate-extraction solvent samples were vortexed for 30 s, every 20 min

144

during equilibration to room temperature (2 h). Once equilibrated to room temperature, samples

145

were centrifuged at 4000 rpm (4 ºC) for 5 min. After centrifugation, supernatants (6 mL) were

146

transferred into clean centrifuge tubes containing Agilent Bond Elut QuEChERS dispersive-SPE

147

and vortexed for 30 s. Samples were then centrifuged at 13000 rpm (4º C) for 5 min. Extracts

148

were then filtered through Captiva PTFE membrane filters (0.2 µm) and spiked with chrysin

149

(internal standard, 5ng mL-1) prior to UHPLC/MS/MS analysis.

150

Water samples were equilibrated to room temperature prior to extraction. Each sample

151

(~4.1 L) was passed through GE Whatman glass microfiber 47 mm filters using a micro-

152

filtration assembly under vacuum to remove suspended particulate matter (SPM). Filtrates (4 L

153

measured) were processed using Waters Oasis PRiME HLB 6 cc solid phase extraction (SPE)

154

cartridges and a vacuum manifold system. Samples were loaded onto cartridges at a controlled 8

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flow rate of 5 mL min-1, and then eluted with LC grade water (10 mL) to remove salt-based

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matrices. Cartridges were then vacuum-dried and target analytes retained on the sorbent were

157

eluted with methanol (10 mL). Methanol extracts were filtered through 0.2 µm membrane

158

syringe filters and spiked with 5 ng mL-1 chrysin prior to UHPLC-MS/MS analysis.

159

2.5 UHPLC-MS/MS conditions

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Target PEPP were analyzed using an Agilent UHPLC-MS/MS system: Agilent 1290

161

Infinity II pump (model G7120A), degasser, autosampler, and temperature-controlled column

162

compartment coupled to a triple quadrupole mass spectrometer (model G6460C) with a Jet-

163

Stream Electrospray Ionization source (Agilent Technologies Inc., Santa Clara, CA, USA).

164

Chromatographic separation was assessed using the two narrow bore UHPLC columns

165

previously noted. Different binary mobile phase compositions (methanol-water, acetonitrile-

166

water, mixture of methanol and acetonitrile-water), infused with modifiers (formic acid,

167

ammonium formate, ammonium acetate), as well as varied column temperatures (20 °C to 60 °C)

168

and flow rates (0.15 to 3.0 ml min-1) were tested during analytical runs.

169

2.6 Multiple reaction monitoring (MRM) conditions

170

Full (MS2), single ion monitoring (SIM), and product ion (PI) scan experiments were

171

performed to optimize ion source conditions and MRM data acquisition parameters for detection

172

of target PEPP. MS and MS/MS experiments were performed in dual mode (both negative and

173

positive ionization mode), and source conditions (gas temperature and flow, sheath gas

174

temperature and flow, fragmentor voltage, collision cell energy, nebulizer pressure, nozzle

175

voltage and capillary voltage) were systematically optimized.

176

2.7 Method validation and data analysis

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An internal standard quantitative method was used for PEPP analysis. Linear calibration

178

curves were constructed by using analyte/internal standard response ratios to quantify unknown 9

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PEPP concentrations in experimental samples. Identification of target PEPP in environmental

180

samples was achieved by comparing chromatographic peak retention times and MRM

181

parameters (specific qualifier and quantifier ions) with those of reference standards.

182

Experimental samples (sediments, water samples) were prepared twice and each sample was

183

analyzed five times to obtain multiple data points.

184

Method specificity was assessed by analyzing solvent blanks between sample runs to test

185

for interference due to chromatography carryover. Method recovery and repeatability parameters

186

were evaluated by conducting a spiking study. Sediments used in the spiking experiments were

187

randomly selected subsets of top and bottom core sediment collected from each of the 11

188

sampling locations. Prior to conducting spiking experiment, PEPP analysis of the composite

189

sediment was performed, and no target PEPP were detected. Spiking concentrations of PEPP

190

used in sediment and water samples were 20 ng mL-1, and 50 ng mL-1, respectively. Percent

191

recoveries (%R) were calculated using: %R =

ARspiked sample ― ARunspiked sample 100 Spiked standard concentration

(1)

192

where %R = ((AR spiked sample−AR un-spiked sample)/spiked standard concentration)*100.

193

Linear calibration curves were used to compute LOD (3SD/b) and LOQs (10SD/b). SD is the

194

standard deviation of the response and b is the slope of the calibration curve. Internal standard

195

peak areas in samples were measured and compared with average areas measured during initial

196

calibration. The internal standard measured area calculated in samples ranged from 80 to 85%

197

compared to peak response observed in calibration samples. Quantitative and qualitative data

198

analysis was carried out using Agilent Mass Hunter software version B. 07.1.

199

3.0 Results and discussion

200

3.1 Optimization of sample preparation 10

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PEPP in environmental samples are often at trace concentrations and accompanied by

202

complex biological matrices. To achieve reliable and reproducible quantitative results, sample

203

preparation involving extraction, purification, and pre-concentration is necessary. For sediment

204

samples, an efficient extraction and purification method based on a previously published

205

approach was used (Mulabagal et al., 2017). Initially, homogenized sediment samples (from 1 g

206

to 10 g) were extracted with various compositions of solvent mixtures (methanol/water;

207

acetonitrile/water: 90:10; 80:20; and 70:30 ratio) to achieve optimal PEPP extraction. This was

208

followed by SPE using Hydromatrix (HM), an inert sorbent with a porous structure which

209

enables solvents to penetrate the matrix and extract analytes while retaining biological matrices

210

(Blasco et al., 2007). HM quantities were optimized to improve target compound extraction

211

efficiency; optimal extraction for sediment samples was achieved with 70% methanol in water,

212

0.5 g of anhydrous magnesium sulfate and 0.5 g of HM. Extracts were then purified using

213

QuEChERS dispersive-SPE to eliminate substances with potential to negatively influence target

214

PEPP ionization. After cleanup, samples were filtered through 0.2 µm captive premium PTFE

215

syringe filters prior to UHPLC-MS/MS analysis.

216

Water samples were passed through glass fiber membrane filters to remove SPM and

217

then pre-concentrated using Oasis HLB cartridges. These cartridges require no preconditioning

218

and thus require less time for sample processing.

219

3.2 Optimization of chromatographic conditions

220

Details of optimized UHPLC conditions are presented in Table 2. An organic mobile

221

phase with methanol resulted in higher response for all target analytes compared to acetonitrile.

222

To achieve optimal response and peak shape, different concentrations of ammonium formate in

223

the mobile phase were tested. Overall, methanol infused with 1 mM ammonium formate resulted

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Table 2 Optimized UHPLC-MS/MS conditions for PEPP quantitative method. Pump Analytical column Guard column Mobile phase Gradient method conditions

Flow rate Total run time analysis Column temperature Injection volume Injection wash solvent Gas temperature Gas flow Nebulizer Sheath gas temperature Sheath gas flow Capillary voltage Nozzle voltage Delta EMV Cell acceleration voltage MS1 and MS2 resolution

UHPLC Conditions Agilent Infinity 1290 II Agilent Poroshell 120 Phenyl-Hexyl (2.1×100 mm, 2.7 µm, p/n 695775-912) Agilent Poroshell 120 Phenyl-Hexyl (2.1×5 mm, 2.7 µm, p/n 821725-914) A. 1 mM ammonium formate in water; B. 1 mM ammonium formate in methanol Time (min) B% 0 30 1-4 50 4.5-6.2 55 7 68 13 85 13.2-13.9 99 14 30 Post run: 3 min 0.25 mL min-1 12.5 min 40 ºC 5 µL Methanol/acetonitrile/water (40/40/20, v/v) MS/MS Conditions 300 ºC 10 L min-1 40 Psi 350 ºC 10 L/min +3500 V / -4000 V +500 V / -1000 V +/- 400 V 4V Unit

224

in a more defined and intense chromatographic peak compared to that of formic acid and

225

ammonium acetate. Excellent peak separation for all 15 target analytes was achieved on an

226

Agilent Poroshell 120 Phenyl Hexyl column, with a column temperature of 40 °C, in a total run

227

time of 12.5 min. During analysis, a diverter valve on the UHPLC system was used to minimize

228

matrix interference, directing flow to waste from 0 to 2 min and from 10 to 12.5 min before and

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after all PEPP were eluted. Sample flow was sent to the detector from 2 to 10 min resulting in an

230

8 minute data acquisition time. The MRM chromatogram was processed to ensure all analytes

231

were eluted within the 8 minute data acquisition time. Several sample injection volumes were

232

also considered (1, 2, 5, and 10 µL), with 5 µL providing an optimal peak shape.

233

3.3 Optimization of MRM conditions

234

Experiments were performed in MS2, SIM, PI scan modes using target PEPP standards.

235

Precursor ions were chosen as the most abundant signal in the MS2 scan spectra corresponding

236

to a particular molecular ion (Kuhnle et al., 2009). MS2 scan experiments were conducted in

237

dual (positive and negative) mode to identify the most intense molecular ion for each target

238

PEPP with suitable ionization conditions. SIM scans were performed at varied fragmentor

239

voltages (80 to 180 V), and conditions were optimized to achieve the most pronounced target

240

analyte peaks. PI scans were conducted at different collision cell energies (0-60 eV) to obtain

241

quantitative and qualitative mass transition ions required to perform MRM experiments. For each

242

target analyte, quantitative analysis used the most abundant product ion, confirmed by the next

243

abundant ion. Experiments were performed in MRM mode and method conditions were adjusted

244

further to produce an optimal response for each target analyte, resulting in excellent peak shape

245

and separation within a short run time (Fig. 3). MRM conditions and results are summarized

246

Tables 2 and 3.

247

3.4 Analytical method validation

248

Quantitative analysis was performed using an internal standard approach (7 point

249

calibration curves for each target analyte; concentration range 0.1 to 50 ng mL-1) to control

250

variation in mass detection during the ionization process and minimize matrix effects in actual

251

environmental samples. Chrysin was used as the internal standard because of its structural

252

similarity to the target analytes (Prasain et al., 2010; Magiera et al., 2012). Calibration curves 13

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Fig. 3. Extracted MRM chromatograms for 15 PPEP and 1 internal standard in 10 ng mL-1 PEPP standard mixture (2 ng/mL internal standard). 253

for each target PEPP demonstrate method linearity (r2 >0.998) and accuracy.

254

reproducibility was acceptable based on multiple analysis of retention times (Fig. 3). Limits of

255

quantitation and detection (LOQ and LOD, respectively) further demonstrate method sensitivity

256

for quantitation of target PEPP in sediment and water (Table 3).

257

resveratrol and enterodiol in 6 sediment samples, percent recoveries of target PEPP obtained in

258

spiking experiments in sediment and water samples were within the acceptable recovery range of 14

Method

With the exception of

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Precursor Ion

Product Ions

Fragmentor voltage (V)

Collision cell energy (eV)

Polarity

LOQ (ng/inj)

LOD (ng/inj)

1 Resveratrol 2 Daidzein 3 Formononetin 4 Apigenin 5 Genistein 6 Naringenin 7 Biochanin A 8 Enterolactone 9 Enterodiol 10 8-Prenylnaringenin 11 6-Prenylnaringenin 12 Xanthohumol 13 Isoxanthohumol 14 Ononin 15 Glycitin IS* Chrysin *IS: internal standard

Retention Time (min)

Target analyte

No.

Table 3 Optimized MRM data acquisition parameters, LOQ and LOD for target PEPP.

2.943 4.064 7.814 6.388 5.649 5.959 9.187 5.879 3.94 9.833 11.933 12.158 8.911 4.19 2.476 8.994

227 253 267 269 269 271 285.1 297 301.1 339.1 339.1 353.1 355.1 431.1 447.1 253

143, 185 132, 208 252, 222.9 116.9, 151 132.9, 63.1 151, 118.9 213.1, 152 253.1, 106.9 253, 106 218.9, 118.9 219.1, 118.9 118.9, 233 179, 299 269.1 285 143

130 160 130 150 150 120 150 140 140 140 150 150 130 100 80 150

25 40 20 30 30 10 40 15 20 15 15 20 25 10 5 30

N N N N N N P N N N N N P P P P

0.021 0.017 0.013 0.014 0.016 0.032 0.018 0.030 0.022 0.022 0.027 0.021 0.015 0.014 0.015

0.006 0.005 0.004 0.004 0.005 0.010 0.005 0.009 0.007 0.007 0.008 0.006 0.005 0.004 0.005

259 260

80-120% (Lin et al., 2016) (Table 4). Thus, the developed method is appropriate for quantitative

261

analysis of all target PEPP in estuarine water, but may not be appropriate for quantitative

262

analysis of resveratrol and enterodiol in estuarine sediment (although it is applicable to

263

qualitative analysis of these analytes in sediment).

264

3.5 Application to environmental samples

265

The validated UHPLC-MS/MS method was used to analyze target PEPP in estuarine

266

sediment and water samples collected from locations in Perdido Bay (Table 1 and Fig. 2) in early

267

March, 2017. Solvent blanks were used between field samples to minimize PEPP carryover

268

from sample to sample during analysis. No target PEPP were observed in sediment samples.

269

The only target PEPP observed in water samples was the lignin enterolactone, observed in nearly 15

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Table 4 Results of PEPP method recovery experiments. Analyte

1T

1B

Sediment* 2B 3T

2T

3B

4T

4B

Resveratrol

79.7 ± 4.0

83.4 ± 5.2

83.0 ± 4.0

75.0 ± 4.0

64.2 ± 4.6

50.6 ± 4.0

53.2 ± 5.2

45.5 ± 2.2

Daidzein

110.5 ± 3.1

107.8 ± 5.3

102.7 ± 7.7

105.2 ± 3.5

105.4 ± 8.3

95.8 ± 3.7

97.4 ± 7.4

99.0 ± 6.0

Formononetin

111.4 ± 4.2

110.0 ± 5.4

109.0 ± 6.7

111.0 ± 4.9

106.2 ± 3.0

110.2 ± 4.4

106.6 ± 4.3

108.0 ± 3.5

Apigenin

108.3 ± 9.5

102.9 ± 6.4

102.4 ± 4.4

90.8 ± 5.9

107.0 ± 4.1

112.1 ± 3.6

103.1 ± 2.9

108.8 ± 6.3

Genistein

110.9 ± 3.2

111.5 ± 2.0

108.5 ± 6.7

103.1 ± 2.3

111.0 ± 2.1

103.4 ± 6.7

106.0 ± 3.8

103.4 ± 5.4

Naringenin

105.0 ± 6.5

103.7 ± 2.3

101.5 ± 2.4

101.6 ± 2.8

96.1 ± 4.8

88.7 ± 3.6

87.7 ± 6.8

85.1 ± 7.0

Biochanin A

109.2 ± 3.5

112.0± 5.1

110.1 ± 6.4

105.2 ± 1.7

115.0 ± 4.8

109.2 ± 3.3

110.4 ± 3.8

113.6 ± 7.1

Enterolactone

108.4 ± 7.0

112.9 ± 1.8

114.5± 3.5

114.4 ± 3.6

113.8 ± 5.3

113.6 ± 1.2

109.6 ± 5.1

112.2 ± 8.1

Enterodiol

86.0 ± 3.0

87.3 ± 6.0

79.6 ± 5.2

70.9 ± 4.5

77.2 ± 5.3

66.4 ± 3.1

73.2 ± 4.7

61.3 ± 4.4

8-Prenylnaringenin

115.3 ± 3.6

117.2 ± 3.0

112.1 ± 4.8

107.3 ± 6.9

115.2 ± 5.8

102.4 ± 5.2

106.1 ± 4.7

101.1 ± 6.6

6-Prenylnaringenin

114.1 ± 2.2

114.8 ± 2.8

110.4 ± 4.3

107.3 ± 6.6

120.5 ± 4.3

112.3 ± 2.0

110.9 ± 5.6

111.8 ± 7.7

Xanthohumol

108.0 ± 6.4

108.8 ± 6.5

113.7 ± 2.5

123.7 ± 8.2

111.7 ± 3.0

115.1 ± 2.4

108.7 ± 4.5

110.5 ± 7.1

Isoxanthohumol

114.0 ± 4.0

116.1 ± 1.8

114.3 ± 3.5

116.8 ± 4.9

106.2 ± 3.0

113.4 ± 1.4

112.0 ± 6.2

116.9 ± 6.2

Ononin

110.2 ± 6.0

108.5 ± 3.3

108.4 ± 4.2

110.2 ± 4.6

112.5 ± 3.6

115.6 ± 4.9

112.8 ± 2.8

120.5 ± 7.5

Glycitin

106.2 ± 3.0

103.1 ± 4.1

96.4 ± 3.7

103.0 ± 2.7

103.4 ± 3.3

102.5 ± 2.9

97.2 ± 2.4

108.1 ± 7.9

*T: top (0-46 cm) of sediment core; B: bottom (46-91 cm) of sediment core

Analyte

Water 1

2

3

4

Resveratrol

97.3 ± 3.5

101.4 ±1.3

93.1 ± 2.3

93.4 ± 1.5

Daidzein

103.6 ± 5.0

101.4 ± 2.5

99.9 ± 2.5

100.1 ± 1.9

Formononetin

105.8 ± 3.0

100.4 ± 1.4

90.7 ± 1.7

98.6 ± 2.2

Apigenin

95.8 ± 2.4

104.6 ± 1.6

100.9 ± 5.9

107.9 ± 2.3

Genistein

104.2 ± 7.6

101.0 ± 1.3

99.0 ± 2.5

102.3 ±1.3

Naringenin

116.8 ± 4.1

103.8 ± 1.6

97.3 ± 2.8

101.2 ± 1.4

Biochanin A

92.3± 2.2

99.7 ± 5.7

88.8 ± 1.5

89.7 ± 1.6

Enterolactone

107.4 ± 1.9

104.2 ± 2.9

101.1 ± 2.5

103.0 ± 2.5

Enterodiol

102.2 ± 1.1

106.6 ± 1.1

103.3 ± 2.4

106.9 ± 1.6

8-Prenylnaringenin

108.3 ± 1.4

105.5 ± 3.3

106.0 ± 1.4

113.0 ± 1.1

6-Prenylnaringenin

97.6 ± 1.3

101.1 ± 1.9

102.9 ± 2.1

107.7 ± 1.2

Xanthohumol

100.2 ± 1.5

99.2 ± 0.2

97.2 ± 1.1

99.7 ± 1.6

Isoxanthohumol

93.5 ± 1.9

97.5 ± 1.9

92.4 ± 2.3

92.1 ± 1.6

Ononin

79.3 ± 2.6

106.0 ± 1.8

101.4 ± 3.6

102.1 ± 2.4

Glycitin

108.1 ± 2.5

109.3 ± 3.6

108.2 ± 1.6

108.4 ± 2.8

270 271

all water samples (Table 5). Higher concentrations of enterolactone were observed in duplicate

272

water samples collected from two sampling locations: the mouth of Moccasin Bayou (location 1;

273

3.66 ± 0.27 ng L-1 and 4.01 ± 0.33 ng L-1) and the mouth of Bayou Marcus (location 7; 4.56 ± 16

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Table 5 Observed enterolactone concentrations in surface water samples. Location

Enterolactone (ng L-1 ± SD )*

Description

Sample 1

Sample 2

1

Moccasin Bayou

3.66 ± 0.27

4.01 ± 0.33

2

Middle Wolf Bay

0.47 ± 0.02

0.48 ± 0.03

3

Lower Wolf Bay

0.08 ± 0.01

0.09 ± 0.01

4

Intracoastal Waterway

0.19 ± 0.03

0.14 ± 0.01

5

Perdido River

ND

ND

6

Mouth of Elevenmile Creek

0.61 ± 0.05

0.12 ± 0.06

7

Mouth of Bayou Marcus

4.56 ± 0.24

5.69 ± 0.43

8

Upper Perdido Bay

0.29 ± 0.04

0.07 ± 0.01

9

Middle Perdido Bay

0.11 ± 0.01

0.61 ± 0.05

10

Lower Perdido Bay

ND

ND

11

Tarkiln Bayou

ND

ND

*Results from duplicate collected samples; SD: standard deviation; ND: below LOD 274

0.24 ng L-1 and 5.69 ± 0.43 ng L-1).

275

Enterolactone and enterodiol are formed by bacteria in the intestinal tract of mammals

276

after consuming the plant lignans matairesinol and secoisolariciresinol, which exist primarily in

277

whole-grains like flaxseed, lentils, barley, rye and wheat (Wang, 2002). Studies focusing on the

278

presence, distribution, behavior, and ecological implications of mammalian phytoestrogens are

279

limited. Based on a limited number of studies, a 2015 review of phytoestrogens in surface

280

waters world-wide estimated enterolactone concentrations ranging from 0.2-74 ng/ L-1 in

281

freshwater rivers. A one year seasonal sampling study in the Douro River estuary on the west

282

coast of Portugal in 2015 found an average summer enterolactone concentration of < 44 ng L-1;

283

enterolactone was not detected during other seasonal sampling events (Ribeiro et al., 2016). 17

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284

Because enterolactone and enterodiol is produced in mammals as opposed to plants, their

285

presence in natural water bodies is due entirely to mammalian urine and fecal excretions (Wang,

286

2002). Land use in the Perdido Bay watershed is primarily urban/undeveloped with no livestock

287

agriculture. Fig. 4 shows sample locations 1 and 7 with respect to the likely sources of elevated

288

and other observed enterolactone concentrations in Perdido Bay. There are a number of on-site,

289

individual septic waste treatment systems in the vicinity of location 1 (Fig. 4A). Although there

290

are no available data on the relationship between leaking septic systems and enterolactone

291

concentrations in adjacent surface water bodies, it is reasonable to expect that one or more of

292

these septic systems are responsible for the observed elevated enterolactone concentrations at

293

this location. Fig. 4B shows the proximity of sample location 7 to the Bayou Marcus Water

294

Reclamation Facility (BMWRF), an advanced tertiary wastewater treatment plant permitted to

295

discharge approximately 10 million gallons per day (MGD) of treated municipal wastewater into

296

wetlands west and southwest of the facility (FDEP, 2010). Water discharged into the wetlands

297

flows into both Bayou Marcus Creek and northern Perdido Bay, and is the most likely source of

298

elevated enterolactone concentrations observed at location 7.

299

Very few studies have examined the removal efficiencies of phytoestrogens from

300

wastewater treatment systems.

The overall removal rates of the phytoestrogen daidzein,

301

genistein and coumestrol in two wastewater treatment plants in Rome, Italy were estimated to be

302

>88%, 97%, and 66%, respectively (Bacaloni et al., 2005). Another study found that in two

303

advanced tertiary treatment plants in Australia, very high influent concentrations of daidzein

304

(341–1688 ng L-1), enterodiol (60–834 ng L-1), and enterolactone (581–2111 ng L-1) were

305

reduced by over 99%. A case study in one of these plants showed that the primary removal

306

mechanism was biological treatment using activated sludge (Kang and Price, 2009). Assuming

18

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Fig. 4. Sample locations were elevated enterolactone concentrations were observed: (A) Moccasin Bayou; and (B) Bayou Marcus; (Table 5). 307

similar influent concentrations and removal efficiencies for the Bayou Marcus Water

308

Reclamation Plant results in an expected enterolactone effluent concentration range of 5.8119

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309

21.11 ng L-1, comparable to that observed at location 7 (Table 5).

310

4.0 Conclusions

311

In this study, a rapid, sensitive and reproducible analytical method for the detection and

312

quantitation of 15 target PEPP in estuarine sediment and water was developed and validated

313

using UHPLC-MS/MS. The method provided excellent peak resolution, peak separation, and

314

rapid run times (method separation/total run time: 8/12.5 min). With the exception of resveratrol

315

and enterodiol in 6 sediment samples, percent recoveries of target PEPP obtained in spiking

316

experiments in sediment and water samples were within the acceptable recovery range of 80-

317

120% (Lin et al., 2016) (Table 4). Thus, the developed method is appropriate for quantitative

318

analysis of all target PEPP in estuarine water, but may not be appropriate for quantitative

319

analysis of resveratrol and enterodiol in estuarine sediment (although it is applicable to

320

qualitative analysis of these analytes in sediment). LOD and LOQ values ranged from 0.004 to

321

0.010 ng/injection and 0.013 to 0.032 ng/injection, respectively. The method was used to

322

investigate the presence and distribution of target PEPP in sediment and water in the northern

323

Gulf of Mexico estuary of Perdido Bay. Although no target PEPP were detected in sediment, our

324

results indicated the ubiquitous presence of enterolactone in Perdido Bay surface water, with two

325

areas of higher concentration likely associated with leaking septic systems and discharge from a

326

water treatment plant. However, the ecological significance of the enterolactone concentrations

327

noted in this study is challenging to assess. Enterolactone has been shown to exhibit endocrine

328

modulating effects in vitro and in vivo, exhibiting weak estrogenic activity at low concentrations

329

and weak antiestrogenic activities at higher concentrations (Waters and Knowler, 1982; Mousavi

330

and Adlercreutz, 1992; Wang, 2002; Damdimopoulou et al., 2011). In humans, there is evidence

331

that dietary exposure to enterolactone is positively correlated with reduced risk of breast,

20

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332

prostate, and colorectal cancer, cardiovascular disease (Adlercreutz, 2007; Saarinen et al., 2007;

333

Buck et al., 2010). There is also evidence that dietary exposure to enterolactone can delay the

334

onset of puberty in females (Wolff et al., 2017; Greenspan and Lee, 2018). However, studies

335

specifically considering the effects of exposure to enterolactone on wildlife living in natural

336

surface water systems are lacking. Moreover, most natural waters will contain complex mixtures

337

of both natural and anthropogenic compounds, many of which are known or suspected EDCs.

338

Although there is evidence that the combined effects of EDCs having similar properties can be

339

predicted by dose addition, little is known about similar effects from mixtures of chemicals from

340

different classes of EDCs (Kortenkamp, 2007). The method developed and described in this

341

study provides a means for further elucidating the effects of complex EDC mixtures on both

342

humans and wildlife, contributing to our evolving understanding of the potential risks posed by

343

EDCs in environmental systems.

344

Acknowledgements

345

This research was supported by a gift to the Coastal Estuarine Environment Fund for

346

Excellence through the Auburn University Foundation. We greatly appreciate the generous

347

support provided by the donor to this fund. Additional funding was provided by the City of

348

Orange Beach, Alabama and the Auburn University Presidential Awards for Interdisciplinary

349

Research (PAIR). Our thanks are extended to graduate students Danyang Wang, Brian Ross,

350

Roger Viticoski, Meredith Ayers, and Shushan Wu for field and laboratory assistance.

351

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   

Some phytoestrogenic polyphenolics are known or suspected EDCs Developed MRM method for simultaneous quantitation of target PEPP in estuarine sediment and water Method separation/total run time (8/12.5 min), LOD (0.004 to 0.010 pg/inj), LOQ (0.013 to 0.032 pg/inj) Method used to examine enterolactone distribution in Alabama estuarine waters