Identification of Bioactive Phytochemicals in Mulberries

Abstract

Mulberries are consumed either freshly or as processed fruits and are traditionally used to tackle several diseases, especially type II diabetes. Here, we investigated the metabolite compositions of ripe fruits of both white (Morus alba) and black (Morus nigra) mulberries, using reversed-phase HPLC coupled to high resolution mass spectrometry (LC-MS), and related these to their in vitro antioxidant and α-glucosidase inhibitory activities. Based on accurate masses, fragmentation data, UV/Vis light absorbance spectra and retention times, 35 metabolites, mainly comprising phenolic compounds and amino sugar acids, were identified. While the antioxidant activity was highest in M. nigra, the α-glucosidase inhibitory activities were similar between species. Both bioactivities were mostly resistant to in vitro gastrointestinal digestion. To identify the bioactive compounds, we combined LC-MS with 96-well-format fractionation followed by testing the individual fractions for α-glucosidase inhibition, while compounds responsible for the antioxidant activity were identified using HPLC with an online antioxidant detection system. We thus determined iminosugars and phenolic compounds in both M. alba and M. nigra, and anthocyanins in M. nigra as being the key α-glucosidase inhibitors, while anthocyanins in M. nigra and both phenylpropanoids and flavonols in M. alba were identified as key antioxidants in their ripe berries.

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Article
Identification of Bioactive Phytochemicals
in Mulberries
Gilda D’Urso 1, Jurriaan J. Mes 2, Paola Montoro 1, Robert D. Hall 3,4 and
Ric C.H. de Vos 3, *
1Department of Pharmacy, University of Salerno, 84084 Fisciano SA, Italy; gidurso@unisa.it (G.D.);
pmontoro@unisa.it (P.M.)
2
Business Unit Fresh Food and Chains, Wageningen Food & Biobased Research, Wageningen University and
Research, 6708 WG Wageningen, The Netherlands; jurriaan.mes@wur.nl
3Business Unit Bioscience, Wageningen Plant Research, Wageningen University and Research,
6708 PB Wageningen, The Netherlands; robert.hall@wur.nl
4Laboratory of Plant Physiology, Wageningen University and Research, 6708 PB Wageningen,
The Netherlands
*Correspondence: ric.devos@wur.nl; Tel.: +31-317480841
Received: 29 November 2019; Accepted: 18 December 2019; Published: 20 December 2019


Abstract:
Mulberries are consumed either freshly or as processed fruits and are traditionally used to
tackle several diseases, especially type II diabetes. Here, we investigated the metabolite compositions
of ripe fruits of both white (Morus alba) and black (Morus nigra) mulberries, using reversed-phase
HPLC coupled to high resolution mass spectrometry (LC-MS), and related these to their
in vitro
antioxidant and
α
-glucosidase inhibitory activities. Based on accurate masses, fragmentation data,
UV/Vis light absorbance spectra and retention times, 35 metabolites, mainly comprising phenolic
compounds and amino sugar acids, were identified. While the antioxidant activity was highest in
M. nigra, the
α
-glucosidase inhibitory activities were similar between species. Both bioactivities
were mostly resistant to
in vitro
gastrointestinal digestion. To identify the bioactive compounds, we
combined LC-MS with 96-well-format fractionation followed by testing the individual fractions for
α
-glucosidase inhibition, while compounds responsible for the antioxidant activity were identified
using HPLC with an online antioxidant detection system. We thus determined iminosugars and
phenolic compounds in both M. alba and M. nigra, and anthocyanins in M. nigra as being the key
α
-glucosidase inhibitors, while anthocyanins in M. nigra and both phenylpropanoids and flavonols in
M. alba were identified as key antioxidants in their ripe berries.
Keywords:
mulberry; high resolution mass spectrometry; antioxidant activity;
in vitro
gastrointestinal
digestion; α-glucosidase inhibitory activity
1. Introduction
Mulberry belongs to the genus Morus, plant family Moraceae, which comprises 24 different
species and one subspecies, with at least 100 varieties [
1
]. The most commonly known Morus species
are Morus alba (white mulberry), Morus nigra (black mulberry) and Morus rubra (red mulberry.) [
2
].
They are deciduous trees originating from China and Japan, and have spread into America and Europe
for silkworm breeding. Globally, the main use of mulberry trees is to produce leaves as feed for
cultivating silkworms, but in various regions, they are also much appreciated for their fruit, which can
be consumed both fresh and as an ingredient in processed food products [3].
Metabolites 2020,10, 7; doi:10.3390/metabo10010007 www.mdpi.com/journal/metabolites

Metabolites 2020,10, 7 2 of 16
Mulberry species have been used in Traditional Chinese Medicines (TCM) for the treatment of
several diseases, especially diabetes mellitus type II; they contain specific molecules, i.e., iminosugars
or iminocyclitols, which are low molecular weight carbohydrates in which the endocyclic oxygen
atom has been replaced by a nitrogen atom. These compounds are known to be able to inhibit the
enzyme
α
-glucosidase which is present in the brush border of the human intestine [
4
–
6
]. Inhibition of
α
-glucosidase leads to a decreased rate of glucose absorption thus resulting in a lower postprandial
blood glucose level. Inhibitors of
α
-glucosidase can prevent the development of diabetes in individuals
with impaired glucose tolerance and/or impaired fasting of blood glucose [7].
Mulberries are also a good nutritional source of a variety of phenolic compounds, like flavonols
and phenolic acids, as well as coloured anthocyanins in the case of black and red mulberry fruits [
8
–
10
].
Phenolic compounds are the subject of increasing scientific interest; they are natural antioxidants
in plant-derived foods and food products and their intake is frequently related to human health.
Many of the bioactivities ascribed to mulberries, such as antioxidant action, hypolipidemic effect and
macrophage activating effect, have also been linked to their phenolic compound composition [
11
–
14
].
The present study aimed to determine differences in chemical composition between the ripe fruits of
M. alba and M. nigra, which are the major species growing in Italy, by metabolomic analysis and to identify
the bioactive compounds responsible for their antioxidant and
α
-glucosidase inhibitory bioactivities.
To this purpose, we used I) HPLC-PDA with an online, post-column antioxidant detection system,
and II) HPLC-PDA- HR Orbitrap FTMS with on-line fractionation into 96-wells plates followed by off
line
in vitro α
-glucosidase inhibitory activity testing of the contents of the individual wells. A series
of compounds present in mulberry fruits as well as major bioactives were further characterized using
MS
n
fragmentation. In addition, we subjected mulberries to an
in vitro
gastrointestinal digestion system
in order to investigate potential effects of digestion on the observed bioactivities upon consumption of
these berries.
2. Results
2.1. Identification of Phytochemicals in Morus using LC-PDA-Orbitrap FTMS
To identify the metabolites present in white and black mulberry fruits, HPLC-PDA-Orbitrap
FTMS analysis was performed on their aqueous methanol extracts, thus generating both an LC-PDA
and an LC-MS profile per extract (Figures S1 and S2, respectively). Based on the exact mass of their
molecular [M+H]
+
ion masses, their MS
n
fragmentation patterns and their UV/Vis absorbance spectra,
we putatively identified 35 compounds in the fruits (Table 1).

Metabolites 2020,10, 7 3 of 16
Table 1.
Metabolites manually identified in Morus alba and Morus nigra using accurate mass LC-MS
n
in positive ESI mode. L. I.: level of identification according to the
Metabolomics Society Initiative [15].
N◦RT Accurate
Mass
Molecular Ion
[M+H]+
Molecular
Formula Putative ID Fragment Ions [M+H]+L. I. References
11.58 163.0844 164.0923 C6H13NO41-deoxynojirimycin - 3 [16]
21.70 289.2253 290.2332 C15H31 NO4n-nonil-deoxynojirimycin 206.8857/122.9243 3 [16]
32.14 147.0895 148.0974 C6H13NO3fagomine - 3 [16]
42.19 181.0738 182.0817 C9H11NO32-formyl-1H-pyrrole-1-butanoic acid 165.0544/136.0755 3 [11]
58.16 354.0951 355.1024 C16H18 O9caffeoylquinic acid isomer I 163.0386 2 [17]
69.30 449.1084 449.1084 C21H21O11 +cyanidin hexoside 287.0546 2 [17]
79.35 507.3043 508.3122 C24H45 NO10 morusimic acid E 346.2587/284.2579 3 [18]
810.21 595.1662 595.1662 C27H30O15 +cyanidin hexose deoxyhexose 449.1058/287.0546 2 [17]
910.93 433.1135 433.1135 C21H21O10 +pelargonidin hexoside 271.0596 2 [17]
10 11.52 354.0951 355.1024 C16H18 O9caffeoylquinic acid isomer II 163.0386 2 [17]
11 11.92 579.1714 579.1714 C27H31O14 +pelargonidin hexose deoxyhexose 433.1115/271.0596 2 [17]
12 12.24 626.1483 627.1542 C27H30 O17 quercetin hexose hexose 465.1023/303.0489 2 [17]
13 12.38 354.0951 355.1024 C16H18 O9caffeoylquinic acid isomer III 163.0386 2 [17]
14 12.42 772.2062 773.2135 C33H40 O21 quercetin-3-O-rutinoside-7-O-glucoside 303.0496/465.0995/611.1576 1 [19]
15 13.25 466.1111 467.1190 C21H22 O12 dihydroquercetin hexoside/taxifolin hexoside 449.1069/305.0650 3 [20]
16 14.41 712.1487 713.1544 C30H32 O20 quercetin hexoside malonyl hexoside 551.1015/463.1021/303.0496 2 [21]
17 14.71 756.2112 757.2192 C33H40 O21 kaempferol-3-O-rutinoside-7-O-glucoside 611.1576/449.1065/287.547 1 [19]
18 15.35 386.1940 387.2020 C19H30 O8roseoside 370.1118/208.0599 3 [22]
19 16.37 772.2062 773.2135 C33H40 O21 quercetin-hexose-hexose-deoxyhexose 303.0496/465.0995/611.1576 3 [19]
20 16.52 450.1162 451.1235 C21H22 O11 dihydrokaempferol-hexoside 289.0703 3 [23]
21 17.02 696.1517 697.1597 C30H32 O19 kaempferol hexoside malonyl hexoside 287.0545/449.1065/535.1076 2 [24]
22 17.22 772.2062 773.2135 C34H40 O31 quercetin-hexose-hexose-deoxyhexose 303.0496/465.0995/611.1576 2 [19]
23 18.28 756.2112 757.2192 C33H40 O20 kaempferol hexose-hexose deoxyhexose 611.1576/449.4065/287.0547 2 [19]
24 18.63 756.2112 757.2192 C33H40 O20 kaempferol hexose hexose deoxyhexose 611.1576/449.4065/287.0547 2 [19]
25 19.59 491.3094 492.3173 C24H46 O9N morusimic acid C 330.2640 3 [18]
26 21.39 610.1534 611.1606 C27H30 O16 quercetin-3-O-rutinoside 303.0495/465.1019 1 [25]
27 22.06 329.2566 330.2645 C18H35 NO4morusimic acid B 312.2529/268.2630/250.2525 3 [18]
28 22.42 464.0954 465.1027 C21H20 O12 quercetin-hexoside 303.0498 2 [17]
29 24.39 594.1584 595.1664 C27H30 O15 kaempferol-3-O-rutinoside 449.1066/287.0546 1 [17]
30 24.88 550.0958 551.1038 C24H22 O15 quercetin-malonylhexoside 303.0499 2 [26]
31 25.10 516.1268 517.1341 C25H24 O12 dicaffeoylquinic acid I 163.0387 2 [27]
32 25.59 448.1006 449.1078 C21H20 O11 kaempferol-hexoside 287.0546 2 [17]
33 25.66 516.1268 517.1341 C25H24 O12 dicaffeoylquinic acid II 325.0913/163.0387 2 [27]
34 27.83 516.1268 517.1341 C25H24 O12 dicaffeoylquinic acid III 325.0913/163.0387 2 [27]
35 28.53 534.1009 535.1088 C24H22 O14 kaempferol malonyl hexoside 287.0546 2 [28]

Metabolites 2020,10, 7 4 of 16
In the fruits of M. nigra, four anthocyanins with a characteristic absorbance maximum at around
500–520 nm were identified. Compound
6
, cyanidin hexoside, showed a pseudomolecular ion at m/z
449.1084, corresponding to the molecularformula C
21
H
21
O
11+
that, upon fragmentation, gave one principal
product ion at m/z287.0546; Compound
8
, cyanidin hexose-deoxyhexose, showed a pseudomolecular ion
at m/z595.1662, corresponding to the molecular formula C
27
H
31
O
15+
, that fragmented into two principal
product ions at 449.1058 (C
21
H
21
O
11+
: loss of deoxyhexose) and 287.0546 (loss of hexose+deoxyhexose);
Compound
9
, pelargonidin hexoside, showed a pseudomolecular ion at m/z433.1135, corresponding
to the molecular formula C
21
H
21
O
10+
, and gave one principal product ion at 271.0596; Compound
11
, pelargonidin hexose-deoxyhexose showed a pseudomolecular ion at m/z579.1714 corresponding
to molecular formula C
27
H
31
O
14+
that, upon fragmentation, gave two principal product ions of m/z
433.1115 and 271.0596. Thus, anthocyanins detected represented both pelargonidin and cyanidin
conjugated with one, two or three C
6
-sugars. These anthocyanin compounds have previously been
identified in Morus alba fruits [
17
] and are responsible for the dark color of black mulberry fruits.
These anthocyanins were present in berries of M. nigra and were not detectable in those of M. alba
(Supplemental Table S1), as was expected from their differential colors.
A series of flavonols with different substituents were present in both white and black mulberry
fruits (
12
,
14–17
,
19–24
,
26
,
28–30
,
32
,
35
). All these compounds showed the characteristic flavonol
absorbance peaks at around 260 nm (resulting from the A-ring) and at around 350 nm (due to
B-ring) and producing daughter ions of m/z303.0496 (quercetin) or 287.0547 (kaempferol); many of
the compounds detected have not previously been described for mulberry fruits. For instance,
compounds
14
,
19
,
22
show the same pseudomolecular ion [M+H]
+
at m/z773.2135 with the same
fragments of m/z303.0496, 465.0995 and 611.1565, corresponding to the loss of two hexose and one
deoxyhexose moiety, but with different RTs. These compounds were thus identified as different
isomers of quercetin-hexose-hexose-deoxyhexose. A similar fragmentation pattern has been reported
for a quercetin-trisaccharide in tomato fruit [
19
]. Specifically, compound
14
was confirmed as
quercetin-3-O-rutinoside-7-O-glucoside based on the retention time of the reference compound
reported in tomato fruit database [19].
Compounds
17
,
23
, and
24
likewise showed a similar pseudomolecular ion [M+H]
+
at m/z
757.2192 with the same fragments of m/z287.0547, 449.1065 and 611.1576, corresponding to the loss
of two hexoses and one deoxyhexose moiety, but with different RTs. These were thus identified as
kaempferol-hexose-hexose-deoxyhexose isomers. The fragmentation pattern of these compounds
agrees with known kaempferol glycosides in tomato [
19
]. Moreover, compound
17
was confirmed
as kaempferol-3-O-rutinoside-7-O-glucoside based on the retention time of the reference compound
reported in tomato fruit database [19].
Compound
16
showed a pseudomolecular ion at m/z713.1544 that upon fragmentation, gave
three principal product ions at m/z303.0496, 463.1021 and 551.1015 corresponding to the loss of
two hexose moieties and one malonyl moiety; this compound was thus tentatively identified as
quercetin hexose-malonyl-hexoside. This fragmentation pattern is consistent with that reported for
a quercetin malonyl glucoside in lettuce [
21
]. Compound
21
showed a pseudomolecular ion at m/z
697.1597 which gave three principal product ions at m/z287.0545, 449.1065 and 535.1076, corresponding
to the loss of two hexose and one malonyl moiety; this compound was identified as kaempferol
hexose-malonyl-hexoside. This compound showed a similar fragmentation pattern as reported in
Cycorium intibus [
24
]. Thus, similar flavonol conjugates consisting of both quercetin and kaempferol
esterified with one to three C
6
-sugars, or one or two sugars with one malonyl group, were present in
both white and black mulberries.
Compound
20
showed a pseudomolecular ion at m/z451.1235 that gave one principal product ion
at m/z289.0703, corresponding to the loss of a hexose moiety; this compound was tentatively identified
as dihydrokaempferol-hexoside. A similar fragmentation pattern was reported for dihydrokaempferol-
hexoside in raspberry [23].

Metabolites 2020,10, 7 5 of 16
Three N-containing sugars, i.e., compounds (
1
) 1-deoxynojirimicin, (
2
) N-nonil deoxynojirimicin
and (
3
) fagomine, were found in fruits of both mulberry species. These compounds have previously
been reported for leaves of M. alba [
16
] and are well known for inhibiting the enzyme
α
-glucosidase
and consequently, might contribute to an antihyperglycemic effect [4–6].
Four piperidine alkaloids, morusimic acids B, C and E (compounds
7
,
25
,
27
) were also identified
based on their exact molecular mass and fragmentation; these compounds have previously been
reported in fruits of M. alba from Turkey [18].
Both M. alba and M. nigra fruits also contained caffeoylquinic acids monomers (
5
,
10
,
13
) as well
as dimers (
31
,
33
,
34
). All three caffeoylquinic acid isomers (
5
,
10
,
13
) showed a pseudomolecular
ion at 355.1024 that, upon fragmentation, gave the same daughter ion at m/z163.0386, corresponding
to the loss of their quinic acid moiety. These compounds have also been reported in M. alba fruits
from Serbia [
17
]. The three dicaffeoylquinic acid isomers (
31
,
33
,
34
) showed a pseudomolecular ion at
517.1341 that produced the same MS/MS base peak at 163.0387. These compounds have previously
been reported in leaves of M. alba [27].
Compound
4
showed a pseudomolecular ion at m/z182.0817, that fragmented into two principal
product ions at 165.0544 and 136.0755. It was putatively identified as the alkaloid 2-formyl-1H-
pyrrole-1-butanoic acid, previously reported in M. alba fruits by Kim et al. [11].
2.2. Global Metabolome Differences between Morus Alba and Morus Nigra Fruits
Ripe fruits of Morus alba and Morus nigra were collected from trees growing at various locations in
the Campania Region (Italy) and subjected to untargeted LCMS-based metabolite profiling. Subsequent
unbiased data processing generated a dataset with the relative intensities and in-source mass spectra
of 361 putative metabolites in the samples (Supplemental Table S1; note that this metabolite list
misses some of the manually identified compounds described in Table 1, indicating that one or more
parameter settings in the untargeted data processing workflow appears suboptimal for these specific
compounds). An unsupervised multivariate statistical method, Principal Components Analysis (PCA),
was subsequently applied to the entire metabolite dataset resulting in a clear differentiation of M. alba
and M. nigra fruit samples (Figure S3). Among the most significantly (p<0.05) differing metabolites
were anthocyanins (Supplemental Table S1), as was expected from the differential fruit colours of
both species. In addition, it was possible to identify two other flavonoids only detectable in M. nigra,
namely dihydroquercetin hexoside and dihydrokaempferol hexoside. In fact, an important step for
the biosynthesis of anthocyanidins is the reduction of dihydroflavonols catalysed by the enzyme DFR
(dihydroflavonol 4-reductase) converting dihydroquercetin and dihydrokaempferol into colorless
leucoanthocyanidins, which are further converted by the enzyme anthocyanin synthase (ANS) into
cyanidin and pelargonidin, respectively [
29
], thereby providing the fruit colour in M. nigra. Several
flavonol conjugates, including quercetin glycosides
19
and
26
and kaempferol glycoside
29
(Table 1),
were also significantly (p<0.05) higher in M. nigra fruit, while the mono- and di-caffeoyl quinic
acids (phenylpropanoids) were not differential between both fruit species (Supplemental Table S1).
These data suggest that M. nigra fruits exhibit a higher activity of the general flavonoid pathway than
M. alba fruit. The alkaloids identified did not significantly differ between the M. nigra and M. alba fruit
samples analyzed (Supplemental Table S1).
2.3. α-Glucosidase Inhibitory Activity and Effect of In Vitro Gastrointestinal Digestion
The
α
-glucosidase inhibitory activity of the black and white mulberries was firstly evaluated
using the crude aqueous-methanol extracts of the fresh fruits. The extraction solvent was evaporated
by freeze-drying and the metabolites re-dissolved in MQ-water. These water extracts were then tested
for inhibiting
α
-glucosidase enzyme activity, monitored through the increase in the pNP product,
detected at 412 nm, using 96-wells plates kept at 30
◦
C; the
α
-glucosidase inhibitor acarbose was used
as a positive control (Figure 1b). Both mulberry extracts showed a marked and similar
α
-glucosidase
inhibitory activity as compared to the water blank (Figure 1a).

Metabolites 2020,10, 7 6 of 16
Metabolites 2019, 9, x 7 of 17
(a)
(b)
Figure 1. α-glucosidase inhibitory activity of mulberry methanol extracts. The Y axis represents the
α-glucosidase activity (increase in 415 nm absorbance per minute) and the X axis the sample type
tested. (a) inhibitory activity of water extracts of Morus alba and Morus nigra compared to the
negative control (water). (b) enzyme activity inhibition by acarbose (positive control) at increasing
concentrations (mM) in the assay. Data represent means and standard deviations (n = 3 assays).
The M. nigra fruit showed an IC50 value of 0.75 ± 0.004 mg/g DW (n = 3), while that for M. alba
fruit was 0.93 ± 0.003 mg/g DW (n = 3). In comparison, the IC50 value of acarbose was 13.83 ± 0.02
mg/g.
A simulated gastrointestinal digestion was then applied to estimate the effect of consumption
and digestion on the α-glucosidase inhibitory activity of mulberry fruits (Figure 2). For both fruit
types, the bioactivity measured in the original fruit extracts was partially lost upon this in vitro
digestion (GI samples compared to MN and MA samples). Gastric digestion (PG) resulted in a slight
decrease in bioactivity in M. nigra only. The control incubation consisting of water instead of fruit
extract in the digestion test (DC samples) showed a slight inhibition of the α-glucosidase activity as
compared to the negative control (NC of undigested fruits: water instead of both fruit extract and
digestion enzymes and buffer): a decrease of 0.04 enzyme units. Taking this inhibiting effect of the
digestion conditions on α-glucosidase into account, it was calculated that the simulated
gastrointestinal digestion resulted in an overall reduction in α-glucosidase inhibitory activity of
about 50% (a decrease of about 0.055 units from 0.13 in DC to 0.075–0.08 in GI samples, compared to
a decrease of about 0.115, i.e., from 0.17 units in NC to about 0.055 in original MN and MA extracts).
Figure 1. α
-glucosidase inhibitory activity of mulberry methanol extracts. The Y axis represents the
α
-glucosidase activity (increase in 415 nm absorbance per minute) and the X axis the sample type tested.
(
a
) inhibitory activity of water extracts of Morus alba and Morus nigra compared to the negative control
(water). (
b
) enzyme activity inhibition by acarbose (positive control) at increasing concentrations (mM)
in the assay. Data represent means and standard deviations (n=3 assays).
The M. nigra fruit showed an IC
50
value of 0.75
±
0.004 mg/g DW (n=3), while that for M. alba fruit
was 0.93 ±0.003 mg/g DW (n=3). In comparison, the IC50 value of acarbose was 13.83 ±0.02 mg/g.
A simulated gastrointestinal digestion was then applied to estimate the effect of consumption and
digestion on the
α
-glucosidase inhibitory activity of mulberry fruits (Figure 2). For both fruit types,
the bioactivity measured in the original fruit extracts was partially lost upon this
in vitro
digestion
(GI samples compared to MN and MA samples). Gastric digestion (PG) resulted in a slight decrease in
bioactivity in M. nigra only. The control incubation consisting of water instead of fruit extract in the
digestion test (DC samples) showed a slight inhibition of the
α
-glucosidase activity as compared to the
negative control (NC of undigested fruits: water instead of both fruit extract and digestion enzymes
and buffer): a decrease of 0.04 enzyme units. Taking this inhibiting effect of the digestion conditions on
α-glucosidase into account, it was calculated that the simulated gastrointestinal digestion resulted in
an overall reduction in
α
-glucosidase inhibitory activity of about 50% (a decrease of about 0.055 units
from 0.13 in DC to 0.075–0.08 in GI samples, compared to a decrease of about 0.115, i.e., from 0.17 units
in NC to about 0.055 in original MN and MA extracts).

Metabolites 2020,10, 7 7 of 16
Metabolites 2019, 9, x 8 of 17
Figure 2. α-glucosidase inhibitory activity after in vitro gastrointestinal digestion. Inhibition activity
of original Morus nigra (MN) and Morus alba (MA) fruit extracts, and after their in vitro stomach (Post
Gastric, PG) digestion and in vitro gastrointestinal (GI) digestion. DC: digestion control, representing
the digestion process, including all enzymes, without plant material; NC: negative control (NC),
representing only water. Data represent means values and standard deviations (n = 3 measurements).
2.4. LCMS Combined with 96-Well Format Fractionation
In order to pinpoint those compounds in Morus fruits that are responsible for the observed
α-glucosidase inhibitory activity, we subsequently used HPLC separation combined with both
96-well plate fractionation and Orbitrap FTMS detection. Injection, fractionation and FTMS analyses
of the M. alba and M. nigra crude extracts, as used in the α-glucosidase inhibition assay, were
performed in triplicate; a water blank was injected as a control. The fractionation plates were
subsequently dried under a gentle N2 flow at 30 °C, the dried well contents re-dissolved in water and
tested for α-glucosidase inhibitory activity. Compounds present in bioactive wells were then further
characterized from their corresponding UV/Vis spectra and FT-MS data.
The results of the α-glucosidase inhibitory activity of individual wells are shown in Figure 3A,B
for M. alba and M. nigra, respectively. Based on the average enzyme activity measured in the wells of
the water control sample, we set a threshold value at 0.17 absorbance units per minute, below which
we considered a sample well to possess α-glucosidase inhibitory bioactivity.
Figure 2. α
-glucosidase inhibitory activity after
in vitro
gastrointestinal digestion. Inhibition activity of
original Morus nigra (MN) and Morus alba (MA) fruit extracts, and after their
in vitro
stomach (Post Gastric,
PG) digestion and
in vitro
gastrointestinal (GI) digestion. DC: digestion control, representing the digestion
process, including all enzymes, without plant material; NC: negative control (NC), representing only
water. Data represent means values and standard deviations (n=3 measurements).
2.4. LCMS Combined with 96-Well Format Fractionation
In order to pinpoint those compounds in Morus fruits that are responsible for the observed
α
-glucosidase inhibitory activity, we subsequently used HPLC separation combined with both 96-well
plate fractionation and Orbitrap FTMS detection. Injection, fractionation and FTMS analyses of the
M. alba and M. nigra crude extracts, as used in the
α
-glucosidase inhibition assay, were performed
in triplicate; a water blank was injected as a control. The fractionation plates were subsequently
dried under a gentle N
2
flow at 30
◦
C, the dried well contents re-dissolved in water and tested for
α
-glucosidase inhibitory activity. Compounds present in bioactive wells were then further characterized
from their corresponding UV/Vis spectra and FT-MS data.
The results of the α-glucosidase inhibitory activity of individual wells are shown in Figure 3A,B
for M. alba and M. nigra, respectively. Based on the average enzyme activity measured in the wells of
the water control sample, we set a threshold value at 0.17 absorbance units per minute, below which
we considered a sample well to possess α-glucosidase inhibitory bioactivity.
The compounds identified in the active wells of both fruit types were the amino sugar acids
1–3
and
the flavonoids
15
–
17
,
19
–
20
and
32
. Two anthocyanins,
6
and
9
, only present in M. nigra (see Table 1),
also showed bioactivity. In addition, other fractions clearly showing
α
-glucosidase inhibitory were
detected e.g., between 34.7 and 35.2 min in M. alba, although we have yet been unable to pinpoint and
identify the specific bioactive compound(s) (Table 2).

Metabolites 2020,10, 7 8 of 16
Metabolites 2019, 9, x 9 of 17
Figure 3. α-glucosidase inhibitory activity of 96-well LC-MS fractions of (A) M. alba and (B) M. nigra
extracts. The Y axis shows the enzyme activity and the X axis the retention time corresponding to the
LC-MS fraction. The vertical line at an enzyme activity of 0.17 indicates the average value in the
water control. The wells considered bioactive are the ones below an enzyme activity value of 0.15.
The compounds identified in the active wells of both fruit types were the amino sugar acids 1–3
and the flavonoids 15–17, 19–20 and 32. Two anthocyanins, 6 and 9, only present in M. nigra (see
Table 1), also showed bioactivity. In addition, other fractions clearly showing α-glucosidase
inhibitory were detected e.g., between 34.7 and 35.2 min in M. alba, although we have yet been
unable to pinpoint and identify the specific bioactive compound(s) (Table 2).
Table 2. Retention time window of bioactive 96-well fractions and putatively corresponding
compounds (numbers refer to Table 1) in M. alba and M. nigra. n.i. = not identified.
M. alba
Retention Time (min) Bioactive Metabolite
M. nigra
Retention Time
(min)
Bioactive Metabolite
1.6–2.08 1-2-3 1.8–2.27 1-2-3
4.88–5.35 n.i. 4.13–4.6 n.i.
12.82–13.28 15 8.33–8.8 6
13.75–14.23 16/17 10.2–10.67 9
19.82–20.3 25 10.2–10.67 9
22.62–23.08 28 12.53–13 15
23.55–24.02 29 13.4–13.93 16
24.95–25.42 32 14.4–14.87 17
31.02–31.5 n.i. 15.8–16.27
19
34.7–35.2 n.i. 16.27–16.73
20
35.22–35.68 n.i. 24.67–25.12
31/32
- 40.07–40.53 n.i.
2.5. Total Antioxidant Activity and HPLC with Online Antioxidant Detection
Figure 3. α
-glucosidase inhibitory activity of 96-well LC-MS fractions of (
A
)M. alba and (
B
)M. nigra
extracts. The Y axis shows the enzyme activity and the X axis the retention time corresponding to the
LC-MS fraction. The vertical line at an enzyme activity of 0.17 indicates the average value in the water
control. The wells considered bioactive are the ones below an enzyme activity value of 0.15.
Table 2.
Retention time window of bioactive 96-well fractions and putatively corresponding compounds
(numbers refer to Table 1) in M. alba and M. nigra. n.i. =not identified.
M. alba Retention Time (min) Bioactive Metabolite M. nigra Retention Time (min) Bioactive Metabolite
1.6–2.08 1-2-31.8–2.27 1-2-3
4.88–5.35 n.i. 4.13–4.6 n.i.
12.82–13.28 15 8.33–8.8 6
13.75–14.23 16/17 10.2–10.67 9
19.82–20.3 25 10.2–10.67 9
22.62–23.08 28 12.53–13 15
23.55–24.02 29 13.4–13.93 16
24.95–25.42 32 14.4–14.87 17
31.02–31.5 n.i. 15.8–16.27 19
34.7–35.2 n.i. 16.27–16.73 20
35.22–35.68 n.i. 24.67–25.12 31/32
- 40.07–40.53 n.i.
2.5. Total Antioxidant Activity and HPLC with Online Antioxidant Detection
The total antioxidant activity of the mulberry fruits was compared between other fruits well
known for their antioxidant activity: cultivated strawberry (Fragaria
×
ananassa) and wild strawberry
(Fragaria vesca). This antioxidant assay (Table 3) indicated that the aqueous-methanol extract of M. nigra
is slightly more active than that of M. alba; in fact the mulberry fruits showed about the same activity
as strawberry, which is among the fruit species with the highest antioxidant capacity [30].

Metabolites 2020,10, 7 9 of 16
Table 3.
Antioxidant capacity of Morus alba and Morus nigra fruits compared with strawberry fruits.
Data represent average values
±
standard deviation of three independent extractions. All antioxidant
values are expressed as mg Trolox per g of fresh weight. TEAC: Trolox-equivalent antioxidant capacity.
Extracts TEAC mg/g FW
Morus alba (White mulberry) 39.40 ±0.02
Morus nigra (Black mulberry) 49.42 ±0.01
Fragaria vesca (Wild strawberry) 50.61 ±0.01
Fragaria ananassa (Strawberry) 51.31 ±0.01
Subsequently, a HPLC-PDA system coupled to online ABTS
·+
cation radical reaction and
detection [
31
] was used to determine the relative contribution of each individual component to the total
antioxidant activity (Figure 4). Several antioxidant components could be identified by comparison of
their retention times and absorption spectra with those of the LC-PDA-FTMS/MS analysis using the same
chromatographic conditions. According to this online antioxidant assay, the key antioxidants in M. nigra
corresponded to anthocyanins, in particular, compounds
6
and
9
. The other compounds responsible for
antioxidant activity in both M. alba and M. nigra were caffeoylquinic acids, like compounds
10
and
13
,
and flavonols like compounds 15,26,28,32 (see Table 1).
Metabolites 2019, 9, x 10 of 17
The total antioxidant activity of the mulberry fruits was compared between other fruits well
known for their antioxidant activity: cultivated strawberry (Fragaria x ananassa) and wild strawberry
(Fragaria vesca). This antioxidant assay (Table 3) indicated that the aqueous-methanol extract of M.
nigra is slightly more active than that of M. alba; in fact the mulberry fruits showed about the same
activity as strawberry, which is among the fruit species with the highest antioxidant capacity [30].
Table 3. Antioxidant capacity of Morus alba and Morus nigra fruits compared with strawberry fruits.
Data represent average values ± standard deviation of three independent extractions. All antioxidant
values are expressed as mg Trolox per g of fresh weight. TEAC: Trolox-equivalent antioxidant
capacity.
Extracts TEAC
mg/g FW
Morus alba (White mulberry) 39.40 ± 0.02
Morus nigra (Black mulberry) 49.42 ± 0.01
Fragaria vesca (Wild strawberry) 50.61 ± 0.01
Fragaria ananassa (Strawberry) 51.31 ± 0.01
Subsequently, a HPLC-PDA system coupled to online ABTS·+ cation radical reaction and
detection [31] was used to determine the relative contribution of each individual component to the
total antioxidant activity (Figure 4). Several antioxidant components could be identified by
comparison of their retention times and absorption spectra with those of the LC-PDA-FTMS/MS
analysis using the same chromatographic conditions. According to this online antioxidant assay, the
key antioxidants in M. nigra corresponded to anthocyanins, in particular, compounds 6 and 9. The
other compounds responsible for antioxidant activity in both M. alba and M. nigra were
caffeoylquinic acids, like compounds 10 and 13, and flavonols like compounds 15, 26, 28, 32 (see
Table 1).
Figure 4. Antioxidant activity. Overlay of representative antioxidant chromatograms of fruit of
Morus alba (in blue) and Morus nigra (in black). Antioxidant profiles of fruit extracts were determined
online, by a post column reaction with ABTS.
+ cation radicals after HPLC separation and PDA
detection of compounds. The ABTS-radicals remaining after post-column reaction were recorded at
Figure 4.
Antioxidant activity. Overlay of representative antioxidant chromatograms of fruit of
Morus alba (in blue) and Morus nigra (in black). Antioxidant profiles of fruit extracts were determined
online, by a post column reaction with ABTS
·+
cation radicals after HPLC separation and PDA
detection of compounds. The ABTS-radicals remaining after post-column reaction were recorded
at 600 nm: negative peaks thus indicate antioxidant activity. The numbers refer to the main peaks
identified (see Table 1):
6
cyanidin hexoside,
9
pelargonidin hexoside,
10
and
13
caffeoylquinic acid
isomers,
15
dihydroquercetin hexoside,
26
quercetin hexose deoxyhexose,
28
quercetin hexoside, and
32
kaempferol hexoside.
3. Discussion
In the present study, we compared ripe fruits of Morus alba and Morus nigra for their metabolite
composition in relation to their potential relevant bioactivities upon consumption, i.e., α-glucosidase
inhibiting and antioxidative activities. Using HPLC-PDA-Orbitrap FTMS analysis of aqueous-methanol
extracts, we were able to detect a large series of compounds and identified a number of metabolites,
previously reported for mulberry or other fruit species, as well as new compounds being present in either

Metabolites 2020,10, 7 10 of 16
or both M. alba and M. nigra. Fruit of both species exhibited a marked
α
-glucosidase inhibiting activity
in vitro
, an indication of their potential beneficial effect with regard to type II diabetes. Moreover,
we showed that this
α
-glucosidase inhibiting activity was partially resistant to simulated gastric and
intestinal digestion. Anthocyanins appear among the potential bioactive compounds in M. nigra fruit
(Figure 3) and the general instability of anthocyanins at the alkaline conditions of gastrointestinal
digestion [
32
] may at least partly explain the loss of
α
-glucosidase inhibitory activity in M. nigra fruits.
When calculating the
α
-glucosidase inhibiting activity of mulberries in units of acarbose, a well known
type II diabetes drug based on its
α
-glucosidase inhibiting activity (https://www.drugs.com/pro/precose.
html), our data suggest that consumption of about 20–25 g of fresh mulberry fruit corresponds to 50 mg
of acarbose, taking into account a 50% bioactivity loss upon digestion. It has been shown that an intake
of 100 mg acarbose 3 times a day can significantly reduce type II diabetes risk factors [
33
]. Thus, a daily
consumption of 100–150 g fresh mulberries may exert relevant pharmacological effects with regard to
type II diabetes. Using analytical LC-based extract fractionation, it was possible to pinpoint three
known iminosugar acids, i.e., [1-deoxynojirimycin (
1
), N-nonil-deoxynojirimycin (
2
) and fagomine
(
3
)], and 7 phenolic compounds, including five flavonols [dihydroquercetin hexoside, (
15
) quercetin
hexoside malonyl hexoside (
16
), kaempferol-3-O-rutinoside-7-O-glucoside (
17
), quercetin hexose (
28
)
and kaempferol hexoside (
32
)] present in both M. alba and M. nigra, and 2 anthocyanins [cyanidin
hexoside (
6
), pelargonidin hexoside (
9
)] only present in M. nigra, as the key
α
-glucosidase inhibitors
in mulberry fruits. While compounds
1
,
2
,
3
,
6
,
28
and
32
have already been reported to exert this
bioactivity [
5
,
16
,
34
,
35
], in our study, we were able to detect novel
α
-glucosidase inhibitory compounds
in mulberries. A similar approach, using accurate mass LCMS coupled to 96-well fractionation and
bioactivity testing, has recently been used to identify novel compounds in pepper fruits interacting
with the human hot-taste receptor [36].
Although it was not yet possible to identify the novel
α
-glucosidase inhibitory compounds in
mulberry fruits on the basis of the observed accurate mass only, this method can well be optimized and
adapted for further structural characterization of these bioactives, e.g., by using so-called multistage
mass spectrometry at high mass resolution [
19
], if needed, combined with NMR experiments. For the
latter approach, the same bioactive wells from replicate plates may be pooled to get sufficient NMR
signals for the de novo identification. Alternatively, bioactive extracts can be re-injected in a LC-MS-SPE
set up to collect and concentrate individual LC-MS peaks upon repeated injections; the SPE cartridges
containing the active compounds (based on their known accurate mass and LC-retention time) can
then be subjected to NMR for structural elucidation [37].
In addition to the
α
-glucosidase inhibitory activity, the ABTS
+
-radical based total antioxidant
assay indicated significant antioxidant activity present in the same mulberries, comparable to that of
strawberries, which are among the fruit species with the highest antioxidant capacity [
32
]. The higher
activity in M. nigra compared to M. alba fruits is likely due to the presence of anthocyanins, which both
provide fruits with their dark color and contribute to antioxidant activity [
38
]. Indeed, using HPLC
with online antioxidant detection [
32
], we were able to pinpoint anthocyanins as the main phenolic
antioxidants in M. nigra, while both phenylpropanoids and flavonols were the key phenolic antioxidants
in M. alba.
This work shows that it is well possible, using analytical scale techniques, to pinpoint the compounds
that are key to the well described bioactivities of mulberry fruits, and to validate the value of metabolomics
technologies in the phytochemical and bioactivity evaluation of functional foods. However, further
studies towards, for example growth conditions, genotypic variation, fruit development and ripening
are needed to obtain the best material for preparation of such functional foods with optimal composition
of bioactive ingredients or for purification of the bioactive compounds.

Metabolites 2020,10, 7 11 of 16
4. Materials and Methods
4.1. Mulberry Materials
Fruits of M. alba and M. nigra were manually picked at ripe stage in May 2014 in different areas of
the Campania region in Italy, in particular, the geographical locations Solofra (GPS coordinates latitude:
40.8291: longitude: 14.8456), Roccadaspide (GPS coordinates latitude: 40.4253: longitude: 15.1917),
Fisciano (GPS coordinates latitude: 40.7728: longitude: 14.7994), San Sossio Baronia (GPS coordinates
latitude: 410712: longitude: 15.2005). Morus alba fruits (MAF) were collected from 4 locations and
coded as MAF-S (collected in Solofra) MAF-big (collected in San Sossio Baronia), MAF-wt (collected
in San Sossio Baronia), MAF-R (collected in Roccadaspide); M. nigra fruits (MNF) were collected at
five locations and coded as MNF-R (collected in Roccadaspide), MNF-U14 (collected in Fisciano),
MNF-U13 (collected in Fisciano), MNF-S (collected in Solofra) and MNF-U13 (collected in Fisciano).
All samples were botanically identified by Prof. V. De Feo (Department of Pharmacy University of
Salerno) and compared with reference materials, then were freeze-dried before being transported to
The Netherlands. They were then ground to a fine powder and stored at −80 ◦C until analysis.
For comparing antioxidant activities, fresh frozen mulberries were compared with fresh fruit of
strawberry and wild strawberry collected in June 2014 in Campania (Italy).
4.2. Extract Preparation
The sample extracts used for LC-MS analysis were prepared essentially as described in De Vos
et al. [
31
]: 30 mg of freeze dried samples were extracted with 1200
µ
L of 75% methanol in MQ water
containing 0.1% of formic acid. Mixtures were then sonicated for 15 min, centrifuged at 12,500 g for
10 min and filtered over a 0.45 µm filter (Minisart SRP4, Biotech GmbH, Germany).
For
α
-glucosidase inhibitory activity testing, for both NanoMate fractionation and HPLC with
online antioxidant analysis, 1 mL of supernatant was dried in a speedvac and taken up in 250
µ
L
of water, sonicated and filtered through a 0.45
µ
m filter (Minisart SRP4, Biotech GmbH, Germany).
These concentrated extracts were prepared in 3 independent replicates.
4.3. LC-PDA-Orbitrap FTMS Analysis
A metabolite analysis was performed using an HPLC (Waters Aquity) coupled to both a photodiode
array detector (PDA; Waters) and an LTQ Ion trap-Orbitrap Fourier transformed Mass spectrometer
(FTMS; Thermo) hybrid system. A Luna 3
µ
m C18 150
×
2 mm column (Phenomenex, USA) at
40
◦
C was used to separate the extracted metabolites, with MQ water with 0.1% formic acid (A) and
acetonitrile with 0.1% formic acid (B) as solvents. A linear gradient from 5% to 35% B in 45 min, at a
flow rate of 0.19 mL/min, was used [
33
]. In order to prevent possible order and batch effects in the
LCMS analysis, all samples were analysed in a single series and in random order. Three quality control
samples (QCs) prepared from a mix of all samples were included and equally distributed over the
study samples, in order to check system stability and estimate overall technical variation.
Electrospray ionization (ESI) in positive mode was used to generate ions from eluting compounds.
ESI source parameters were as follows: capillary voltage 43 V; tube lens voltage 120 V; capillary
temperature 295
◦
C; Sheath and Auxiliary Gas flow at 40 and 3 (arbitrary units), respectively, Sweep gas
0 n, Spray voltage 5 V. MS spectra were acquired by full range acquisition covering m/z104–1350 at a
resolution of 60,000 FWHM.
4.4. LCMS data Processing and Multivariate Analysis
The raw LCMS data files were processed using Metalign software [
34
] for baseline correction,
noise estimation, and ion-wise mass spectral alignment. MSClust software [
35
] was then used to assemble
redundant mass signals derived from the same metabolite, including natural isotopes, adducts and
in-source fragments, based on their corresponding retention times and relative abundance patterns
across samples. This resulted in the relative intensities of 361 mass peak clusters, each representing a

Metabolites 2020,10, 7 12 of 16
(reconstructed) putative metabolite, present in at least two samples. These metabolite intensity data were
then subjected to a multivariate analysis using GeneMaths XT software version 2.12 (Applied Maths,
Belgium). Metabolite intensities were firstly log2-transformed and then mean-centred across samples.
Using multiple online databases, including KNApSAcK (http://kanaya.naist.jp/KNApSAcK/),
Dictionary of Natural Products (http://dnp.chemnetbase.com), Metlin (https://metlin.scripps.edu/),
HMD (http://www.hmdb.ca), in-house libraries based on standards, as well as the mass spectra
information within the clustered mass peaks and from additional LC-MS
n
runs generating accurate
mass spectral trees from the top 3 intensity ions every 30 s [
19
]. Selected metabolites (Table 1) were
manually annotated as far as was possible using the mass data and the UV/Vis-absorbance spectral
data available.
4.5. In Vitro Simulated Gastrointestinal Digestion
In vitro
digestion was carried out on freeze-dried fruit samples of both M. alba and M. nigra, following
the protocol described by McDougall et al. [
36
] with slight modification. Release of phytochemicals
from fruit was checked by LC-MS at different stages of digestion, i.e., after gastric digestion (post gastric,
PG) and gastrointestinal digestion (GI). Both PG and GI samples were stored at
−
80
◦
C until further
analysis. During the process, three different controls were used: (1) plant material without digestion
solutions and enzymes, diluted in water using the same ratio used for the samples coming from the
digestion process (2) the solutions with all the ingredients for digestion but without plant material (DC:
Digestion control), (3) plant material with all the ingredients for digestion but without active enzymes
(the enzymes where added at the end of the digestion process, to the cold extract). Both
α
-glucosidase
inhibitory activity and antioxidant activity were investigated for each of these PG and GI samples using
the methods described below.
4.6. α-Glucosidase Inhibition Assay
The
α
-glucosidase assay uses the synthetic substrate p-nitrophenyl-
α
-D-glucopyranoside (pNPG),
which is hydrolyzed by
α
-glucosidase to release p-nitrophenol (pNP), a color agent that can be
monitored at 415 nm. Briefly, 10
µ
L of extract was combined with 40
µ
L of 100 mM phosphate buffer
(pH 6.8) and 20
µ
L of
α
-glucosidase (0.6 units per mL buffer). After mixing and incubation for 5 min
at 37
◦
C, 20
µ
L of a 20 mM pNPG solution in buffer was added to start the reaction. The reaction
was monitored in time at 415 nm by a TECAN SpectraFluor microplate reader. Acarbose was used
as a positive control, while water was used as a negative control for enzyme inhibition. The enzyme
activities were evaluated as increase in the absorbance at 415 nm per minute and the percentage of
enzyme inhibition was calculated. Three dilution series of extracts were used for IC
50
determination.
Dose
−
response curves and IC
50
values were obtained by use of GraphPad Prism (version 6.00.283).
The assay was performed with 3 replicates.
4.7. NanoMate LC-Fractionation of Extracts
The HPLC–PDA–FTMS system was adapted with a chip-based nano-electrospray ionization
source/fractionation robot (NanoMate Triversa, Advion BioSciences) coupled between the PDA
and the inlet of the Ion Trap/Orbitrap hybrid instrument [
19
]. In this system, the compounds
separated and eluting from the analytical column firstly passed the PDA detector for determining their
UV/Vis absorbance spectra and then the eluent was automatically split by a NanoMate LC-fraction
collector/injection robot (Advion) into a nanoflow for chip-based ESI nanospray Orbitrap FTMS analysis
and the rest for fractionation into microwells with a collection time of 28 sec per well. The sample
injection volume was 5
µ
L. The gradient and flow conditions were the same as described above, with an
additional 30
µ
L/min 100% isopropanol added into the LC flow via a T-junction between the PDA and
the NanoMate, in order to improve the solvent composition for generating a stable nano-electrospray.
The eluent flow was split by the NanoMate at a ratio of 219.5
µ
L/min to the fraction collector and
0.5
µ
L/min to the nano-electrospray source. LC-fractions were collected every 28.2 s (i.e., 100
µ
L

Metabolites 2020,10, 7 13 of 16
solvent) into 96-well plates (Twin tec, Eppendorf). After collection, the plates were dried at 30
◦
C under
a gentle N
2
flow, and then tested for
α
-glucosidase inhibitory activity as described above (performed
in 3 replicates).
4.8. Antioxidant Activity and HPLC Analysis with Online Antioxidant Detection
The total antioxidant capacity of fruits was analyzed using the ABTS
·+
radical scavenging method,
essentially according to Capanoglu et al. [
37
] with slight modifications. The fruits were collected in
June 2014 and the antioxidant activity was tested on basis of fresh weight. 0.5 g of samples (fresh fruit)
were extracted in 1.5 mL of methanol (final MeOH concentration about 77%, taking into account a
fruit water content of 95%) containing 0.05% of formic acid, sonicated for 15 min and centrifuged at
12,500 g for 15 min, filtered through 0.45
µ
m (Minisart SRP4, Biotech GmbH, Germany) and then 10
µ
L
of extract was used to test the antioxidant activity. Trolox was used as a reference.
To determine total antioxidant capacity, 10
µ
L of sample extracts or standard solution was mixed
with 90
µ
L of ABTS-radical working solution (pH 7.4) and after 40 s, the remaining ABTS
·+
radicals
were measured at 415 nm using 96-well microplates (Nunc, Roskilde, Denmark) and an Infinite
®
M200 micro plate reader (Tecan, Gröding, Austria). The analyses were done using 3 replicates and
the results were expressed in terms of mg Trolox Equivalent Antioxidant Capacity (TEAC) per g fruit
FW. In addition, the contribution of individual antioxidants to the total antioxidant capacity of the
crude mulberry extracts was determined using an HPLC-PDA system coupled to post-column on-line
antioxidant detection [
37
,
38
]. For this, the extracts of M. alba and M. nigra fruits, also used for the
LC-MS analysis, were analyzed using a W600 Waters HPLC system coupled to a Waters 996 PDA
detector (240–600 nm) [
37
,
38
]. Eluted compounds were allowed to react online for 30 s at 40
◦
C in a
buffered solution of ABTS
·+
cation radicals (pH 7.4). Then, the absorption of the remaining ABTS
·+
radicals was monitored at 412 nm by a second detector (Waters 2487, dual-wavelength UV–vis detector).
Peak identification was done by comparing PDA-absorbance spectra and retention times of eluting
peaks with data taken from the literature and annotations were confirmed by HPLC-FTMS and MS/MS
analyses, as described above.
Supplementary Materials:
The following are available online at http://www.mdpi.com/2218-1989/10/1/7/s1,
Figure S1: Representative LC-MS chromatograms, recorded in ESI positive ionization mode, of M. nigra (upper
trace) and M. alba (lower trace) fruit extracts; Y-axes are on the same scale (1.5*E7; base peak intensity in
ion counts/sec). Values above peaks indicate retention times (in minutes) and detected m/zvalue, Figure S2:
Representative LC-PDA chromatograms of aqueous-methanol extracts from ripe fruits of M. nigra (A and B) and
M. alba (C and D). Figures show absorbance at 520 nm (A and C) representing elution profile of anthocyanins,
and at 355 nm (B and D) representing mainly flavonoids and phenylpropanoids, Values above peaks indicate
retention times (in minutes). Note: intensity scales (Y-axes) are similar for all traces, Figure S3: 3 dimensional
PCA plot of 5 Morus alba and 4 M. nigra fruit samples, harvested from trees spread over region Campania, Italy,
based on their variation in 371 metabolites detected by the untargeted LCMS approach. The 3 quality control
samples are technical replicates of a mix of samples. The X-axis (PC1) explains 33.2% of the total metabolites
variation, the Y-axis (PC2) 18.6% and the Z-axis (PC3) 14.2%, Table S1: Relative intensity of all putative metabolite
features (clusterID’s) for each of the analyzed mulberry samples, Table S2: Description of column heads, Table S3:
MSI Identification level.
Author Contributions:
Conceptualization, G.D., P.M. and R.C.H.d.V.; methodology, G.D., J.J.M. and R.C.H.d.V.;
software, G.D. and R.C.H.d.V.; formal analysis, G.D.; investigation, G.D., P.M. and R.C.H.d.V.; resources, P.M.,
J.J.M. and R.D.H.; data curation, G.D. and R.C.H.d.V.; writing—original draft preparation, G.D.; writing—review
and editing, G.D., J.J.M., P.M., R.D.H. and R.C.H.d.V.; visualization G.D’U and R.C.H.d.V.; supervision, P.M.,
J.J.M., and R.C.H.d.V.; project administration, G.D., P.M. and R.C.H.d.V. All authors have read and agreed to the
published version of the manuscript.
Funding: This research received no external funding.
Acknowledgments:
This research was carried out at the Bioscience department of Wageningen Plant Research of
Wageningen UR. Special thanks to Harry Jonker and Bert Schipper for their technical help in HPLC-antioxidant
and LC-PDA-FTMS analysis, and to Monic Tomassen (Fresh Food and Chains, Food & Biobased Research,
Wageningen UR) for helping with the in vitro gastrointestinal digestions.
Conflicts of Interest: The authors declare no conflict of interest.

Metabolites 2020,10, 7 14 of 16
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