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and biological eects of kratom
(Mitragyna speciosa): In vitro
studies with implications
for ecacy and drug interactions
D. A. Todd1, J. J. Kellogg1,2, E. D. Wallace1,3, M. Khin1, L. Flores‑Bocanegra1, R. S. Tanna4,
S. McIntosh5, H. A. Raja1, T. N. Graf1, S. E. Hemby5, M. F. Paine4, N. H. Oberlies1 &
N. B. Cech1*
The safety and ecacy of kratom (Mitragyna speciosa) for treatment of pain is highly controversial.
Kratom produces more than 40 structurally related alkaloids, but most studies have focused
on just two of these, mitragynine and 7‑hydroxymitragynine. Here, we proled 53 commercial
kratom products using untargeted LC–MS metabolomics, revealing two distinct chemotypes that
contain dierent levels of the alkaloid speciofoline. Both chemotypes were conrmed with DNA
barcoding to be M. speciosa. To evaluate the biological relevance of variable speciofoline levels
in kratom, we compared the opioid receptor binding activity of speciofoline, mitragynine, and
7‑hydroxymitragynine. Mitragynine and 7‑hydroxymitragynine function as partial agonists of the
human µ‑opioid receptor, while speciofoline does not exhibit measurable binding anity at the µ‑,
δ‑ or ƙ‑opioid receptors. Importantly, mitragynine and 7‑hydroxymitragynine demonstrate functional
selectivity for G‑protein signaling, with no measurable recruitment of β‑arrestin. Overall, the study
demonstrates the unique binding and functional proles of the kratom alkaloids, suggesting potential
utility for managing pain, but further studies are needed to follow up on these in vitro ndings. All
three kratom alkaloids tested inhibited select cytochrome P450 enzymes, suggesting a potential risk
for adverse interactions when kratom is co‑consumed with drugs metabolized by these enzymes.
According to the US Department of Health and Human Services, opioids were responsible for more than 42,000
deaths in the US in 2016, the highest in recorded history1. More than 40% of these deaths involved a prescription
opioid. Some individuals who suer from chronic pain are turning to other options, one of which is the plant
known as kratom [Mitragyna speciosa (Korth.) Havil. (Rubiaceae)], a tropical tree native to peninsular ailand,
Myanmar, Malaysia and other countries in Southeast Asia1,2. Kratom has skyrocketed in popularity in western
countries in the past decade; current estimates are that as many as 5 million individuals in the US use kratom on
a regular basis3. ere has been considerable controversy over the safety and ecacy of kratom use by US con-
sumers. Citing safety concerns (one study reports that kratom has been implicated as at least partially involved
in 91 deaths)4, the United States Department of Agriculture (USDA) has made it their practice to conscate ship-
ments of kratom into the US. e US Drug Enforcement Administration (DEA) threatened to assign kratom as a
schedule 1 controlled substance, which would make possession of kratom illegal. e DEA then suspended that
decision in response to a backlash from some US consumers5, who claim that it is a safer alternative to opioids
for treatment of pain and/or opioid addiction6. e eectiveness of kratom for these purposes continues to be a
hotly debated and politically charged topic, and one that requires rigorous scientic investigation.
Department of Chemistry, The University of North Carolina Chapel
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Widespread kratom use is a relatively new phenomenon in the US6. However, the medicinal use of kratom
in southeast Asia has a long history. Kratom was rst documented in the scientic literature in 18367, in a paper
that described use of kratom leaves by the Malays as a substitute for opium. e isolation of mitragynine was
reported in 1921 by Ellen Field8, who ended the introduction of her paper with the following statements, “Accord-
ing to Redley………..Mitragyne [sic] speciosa is used in Perak against the opium habit, whilst, according to Dr. P.P.
Laidlaw, mitragynine is a local anaesthetic [sic]…” us, controversy over the use and eectiveness of kratom
was documented nearly 100years ago. It is a controversy that continues today.
Consistent with the claim that kratom can be eective in the treatment of pain, extracts from this plant dem-
onstrated opioid-receptor mediated analgesic eects in mouse model studies9. is activity has generally been
attributed to alkaloids that the plant produces, of which mitragynine (1) and 7-hydroxymitragynine (2) (Fig.1)
have been the focus of multiple pharmacological investigations10–13. Mitragynine and 7-hydroxymitragynine
both bind to the human µ-opioid and ƙ-opioid receptors (hMOR, hKOR) with nanomolar anity, and func-
tion as partial agonists at the µ-opioid receptor and weak antagonists at ƙ-opioid and δ-opioid receptors14,15.
7-Hydroxymitragynine exhibits approximately vefold greater anity at the μ-opioid receptor compared to
mitragynine. Upon receptor activation, mitragynine and 7-hydroxymitragynine exhibit functional selectivity
for G-protein signaling, with no measurable recruitment of β-arrestin14. In antinociception assays, 7-hydroxymi-
tragynine exhibits 40-fold greater potency than mitragynine and tenfold greater potency than morphine16,17,
whereas mitragynine is less potent than morphine in antinociceptive assays18. Combined administration of
mitragynine with morphine increases antinociception compared with morphine alone and prevents the devel-
opment of morphine tolerance19. In contrast to mitragynine, repeated administration of 7-hydroxymitragynine
produces antinociceptive tolerance as well as cross-tolerance to morphine’s antinociceptive action and induces
physical dependence13. Furthermore, mitragynine does not exhibit abuse liability and decreases the reinforcing
eects of morphine whereas 7-hyroxymitragynine demonstrates abuse liability and increased morphine self-
administration in rats10. Interestingly, a recent study by Kruegel etal.12 shows that mitragynine can be converted
to 7-hydroxymitragynine both invitro and in a mouse model, therefore, some of the invitro activity attributed
to mitragynine may in fact be due to the action of it metabolite 7-hydroxymitragynine.
Collectively, the scientic data on mitragynine and 7-hydroxymitragynine suggest that kratom tea might
indeed be an eective alternative to opioids against pain. However, kratom products are sold to consumers under
a variety of trade names with no data regarding the chemical composition of plant material being consumed.
Kratom has been documented to produce variable levels of its more than 40 alkaloids, depending on genetic
variation and dierences in growth and processing conditions6,20–22. What are the potential health implications
of the variability in chemical content of kratom preparations? As of yet, this question has been dicult to answer
because mechanistic studies of kratom alkaloids have focused largely on isolated alkaloids without consideration
of how these alkaloids are represented in kratom materials used medicinally. Herein, we sought to connect the
dots between investigations of pure alkaloids and their relevance to medicinally used kratom. Towards this goal,
we employed untargeted metabolomics to determine which alkaloids vary in content across commercial kratom
products. We then isolated these relevant alkaloids and compared their biological eects invitro, including
activity at the µ-opioid receptors and inhibitory eects on CYP isoforms involved in the metabolism of opioids
and other drugs. Our ultimate objective with this study was to capture the variability of commercial kratom
products being employed by US consumers and to evaluate (based on vitro studies) the potential implications
of this variability in terms of safety and ecacy.
Commercial kratom products can be divided into two chemotypes with diering alkaloid pro‑
les. We conducted untargeted metabolomics analysis of more than 50 commercial available kratom prod-
ucts (TableS1) to obtain a global comparison of chemical composition. A principal component analysis (PCA)
plot of the resulting data (Fig.2) reveals what appear to be two dierent groupings of the data. It was of interest
to determine which chemical constituent(s) were responsible for these dierences. To do so, we examined load-
ings and volcano plots (Fig.3) and determined that the peak area of a constituent with m/z of 401.2064 and
retention time of 2.70 varied across the two groups. is constituent was isolated and identied as the known
kratom oxindole alkaloid speciofoline (3, Fig.1) ([M + H]+ = 401.2071, Δ = 1.7ppm) based on comparison of
NMR, ECD, and mass spectrometry data with literature values23–26 (TableS2, FigureS1 and S2). Several other
Figure1. Structures of select alkaloids present in kratom (Mitragyna speciosa), mitragynine (1),
7-hydroxymitragynine (2) and speciofoline (3).
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ions were also observed to vary in content across the samples (Fig.3), and based on their similar mass defect to
indole alkaloids27, are likely other more minor alkaloids of kratom. Structures of these other putative alkaloids
were not determined in this study.
Based on the chemical data (Fig.3), it appears that the commercial kratom products studied herein can be
grouped into separate “high-speciofoline” and “low-speciofoline” chemotypes. To demonstrate this further, a
comparison is shown of chromatographic peak area across all samples for the ions corresponding to mitragy-
nine and speciofoline (Fig.4). e mitragynine content in the commercial samples varied by fourfold, while the
speciofoline content varied by more than 90-fold, with a minority of samples appearing as “high-speciofoline”
To further explore the phenomenon of variable speciofoline levels in kratom samples, we utilized the isolated
speciofoline to conduct quantitative analysis for representative high and low-speciofoline materials (Table1). A
limitation of working with commercial kratom samples is that morphological information that could be used to
identify the plants is lost when they are powdered. To address this limitation, we obtained a young, living plant
from a supplier in Ohio, which appeared based on morphological characteristics to be authentic M. speciosa.
is sample was coded as K55 and was included in the quantitative analysis.
As expected, the quantities of alkaloids dier in the two commercial kratom products subjected to quantita-
tive analysis (K51 and K52). Sample K51 contained mitragynine at a level of 11.45 ± 0.74mg/g (1.145 ± 0.074%),
and 7-hydroxymitragynine at a level of 0.056 ± 0.019 (0.0056 ± 0.002%). ese values are consistent with prior
literature28, which found that mitragynine was detected in commercial kratom products at a concentration
range between 1 and 6% of leaf content and that 7-hydroxymitragynine levels ranged from 0.01 to 0.04% of
leaf content. In contrast, sample K52 contains lower levels of mitragynine (8.13 ± 0.95mg/g) but, as expected
based on the data in Fig.4, has a much higher content of speciofoline (Table1) than sample K51. Interestingly,
the kratom plant used for morphological identication (K55) showed much lower abundance of mitragynine
and 7-hydroxymitragynine than either of the commercial kratom samples (K51 and K52). e reason for this
dierence cannot be ascertained with the experimental design employed for this study, but may be related to
dierences in plant age and/or growing conditions for K55 as compared to the commercial kratom products.
Because of the markedly low alkaloid levels (Table1), the K55 kratom sample was employed only for genetic
studies and was not further evaluated for pharmacological activity.
Genetic dierences do not appear to explain the observed chemotypes in commercial kratom
samples. ere are 10 related species within the Mitragyna genus6, including Mitragyna speciosa (Korth.)
Havil., Mitragyna diversifolia (Wall. ex G. Don) Havil., Mitragyna hirsuta Havil., and Mitragyna rotundifolia
(Roxb.) Kuntze. While these species can be distinguished by morphological characteristics in raw plant material,
contamination or misidentication could occur during collection and could not be distinguished in powdered
material such as that used in this study. e dramatic dierences in alkaloid quantity in various kratom samples
Figure2. Principal component analysis (PCA) scores plot generated based on LC–MS metabolomics traces of
kratom (Mitragyna speciosa) samples in Table1. Each data point represents the average peak areas of triplicate
extractions prepared for each sample. Samples selected for in-depth analysis herein (K50–K52) are highlighted
in orange. Two groupings were evident from the initial analysis (indicated here with separate Hotelling’s T2 95%
condence intervals). e underlying cause for these apparent dierences in the data was further explored with
loadings plot and volcano plot data (Fig.3).
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Figure3. Plots of signicant features based upon the PCA analysis. (A) Loadings plot, where the spatial
arrangement of the features (uniquem/z-RT pairings) corresponds to the distribution of the samples (i.e., scores
plot, Fig.2). Speciofoline (3) appears to be a feature that is responsible for discriminating between the two
sample groupings along the y-axis (PC2). (B) Volcano plot, highlighting signicant features of the metabolites
based on statistical testing (p value < 0.05, fold change > 2 or < 0.5) between the two groupings, with the further
a feature’s position away from the origin (0, 0), the more signicant the feature is. e speciofoline-rich group
(red circles) yielded 120 signicant features, while 19 features were signicantly distinct in the non-speciofoline-
rich grouping of commercial samples (purple circles). Speciofoline (3) was found to be a metabolite that diered
signicantly across sample groups, while mitragynine (1) and 7-hydroxymitragynine (2) were not signicantly
dierent between the two groups (orange circles). Other features predicted to be alkaloids based on mass defect
(open circles). Labels on plot refer to the compound number and the type of ion observed (i.e.[3 + H]+ refers to
the protonated molecule of speciofoline).
Figure4. Comparison of mitragyine and speciofoline levels across samples of M. speciosa. e x-axis represents
arbitrary codes assigned to the samples, as described in TableS1, and the y-axis represents the log of the peak
area for the relevant selected ion trace in LC–MS analysis.
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demonstrated in Table1 and Fig.4 led us to ask whether the samples reported to be Mitragyna speciosa might be
dierent species or strains of Mitragyna. To address this question, we extracted DNA from three kratom samples
with varying speciofoline content (K51, K52 and K55 in Table1), and used the resulting data for DNA barcod-
ing via BLAST search of rbcL + matK (core plant barcoding markers) and performed maximum likelihood and
Bayesian phylogenetic analysis, of the combined matK + trnH-psbA and the separate nrDNA ITS regions. ese
regions were selected because they are designated as the ocial DNA barcodes for the plant kingdom29–37.
Molecular identication of plant samples using a BLAST search of core plant loci (rbcL + matK) using the
BOLDSYSTEMS database (version 4) showed that samples K51, K52 and K55 had ≥ 99% sequence similarity with
M. speciosa (FiguresS4–S6). Based on uncorrected p distances calculated for trnH-psbA, there was ≥ 99–100%
sequence similarity with sequences of published M. speciosa. is means that samples K51, K52 and K55 were
more similar to sequences of M. speciosa and more dissimilar to sequences of M. diversifolia, M. hirsuta, M.
rotundifolia, and M. parvifolia (TableS5a and b). Maximum likelihood analysis of the partial matK + trnH-psbA
fragments placed all three samples in a strongly supported clade (100% RAxML bootstrap support, 78% PhyML
bootstrap and ≥ 95% Bayesian posterior probability support) with the published sequences for M. speciosa (Fig-
ureS7). Notably, this analysis included a partial matK sequence from a recently sequenced genome of M. speciosa
(BioProject: PRJNA325670). Finally, phylogenetic analysis using the nrDNA ITS region also placed K51 and K52
in a strongly supported clade (≥ 84% PhyML bootstrap and ≥ 95% Bayesian posterior probability support) with
M. speciosa sequences (FigureS8). However, the ITS analysis showed that K55 does not group with M. speciosa,
but rather formed a cluster with other Mitragyna spp., albeit without any signicant bootstrap support and/or
Bayesian posterior probability support (FigureS8).
e results of DNA barcoding and phylogenetic analyses classify all three kratom products as Mitragyna
speciosa, based on comparison with the published sequences for this species, except for the ITS analysis, which
showed a conicting outcome for sample K55. us, it appears that the observed dierences in speciofoline
content among the various kratom samples is not due to misidentication of species or substitution of a dierent
Mitragyna species for M. speciosa. Notably, a number of other factors including plant age, growing conditions,
and processing methods could all contribute to the observed dierences in alkaloid level in the various kratom
samples. Exploring these dierences would require a dierent experimental design and could be the subject of
future studies. For the purpose of the current investigation, the important nding is that dramatic dierences in
alkaloid content can be observed among dierent samples of what appear to be authentic (based on molecular
data) M. speciosa. Such dierences in alkaloid prole could have implications for biological activity, a possibility
that we explore in the next sections.
Dierences in alkaloid prole in kratom plant material is expected to have implications for
opioid receptor‑mediated activity. e alkaloid speciofoline is an oxindole, while the more commonly
studied alkaloids mitragynine and 7-hydroxymitragynine are indoles (Scheme1). us, we hypothesized that
there might be biological implications to the observed variability in speciofoline levels across kratom extracts
(Table1). To explore this hypothesis, we tested mitragynine (1), 7-hydroxymitragynine (2) and speciofoline (3)
for µ-opioid receptor inhibition of forskolin-stimulated cyclic-AMP (cAMP) accumulation and for their ability
to recruit β-arrestin-2 in CHO-K1 cells stably expressing the µ-opioid receptor. Results indicate that DAMGO
and morphine fully inhibit cAMP accumulation, mitragynine and 7-hydroxymitragynine partially inhibit cAMP
accumulation, whereas speciofoline has no eect in this assay (Fig.5A). Furthermore, DAMGO and morphine
eectively recruit β-arrestin-2 in CHO cells (Fig.5B), while mitragynine, 7-hydroxymitragynine, and speciofo-
line fail to recruit β-arrestin-2 at concentrations as high as 10mM.
To further characterize the pharmacology of the kratom alkaloids, competitive radioligand binding assays
were conducted with HEK293 cells stably expressing µ-, ƙ- and δ-opioid receptors to assess the anity of the
alkaloids at these receptors (Table2). Mitragynine exhibited moderate anity at µ- and ƙ-opioid receptors
whereas 7-hydroxymitragynine showed strong anity at the µ- opioid receptor (14X greater than mitragynine)
and moderate anity at the ƙ- and δ-opioid receptors (4X and 70X greater than mitragynine). In contrast,
speciofoline did not exhibit appreciable anity for any of the opioid receptors. Results for mitragynine and
7-hydroxymitragynine are consistent with previous literature reports14,15; however, this is the rst published
assessment of receptor binding of speciofoline at opioid receptors.
Table 1. Alkaloid quantity in Kratom products. Samples K50, K51 and K52 are commercial kratom products
that were purchased for this study. Sample K55 is a young cultivated kratom plant. Quantities were calculated
by preparing methanolic extracts in triplicate and analyzing by LC–MS. a Quantity is denoted as mg of
compound per g of dried kratom plant material. b Uncertainty calculated using standard deviation of triplicate
extractions, each analyzed separately. c Limit of quantitation (LOQ) for speciofoline is 4.9ng/mL (TableS3) and
this sample contained speciofoline below that level. d LOQ for 7-hydroxymitragynine is 0.49ng/mL (TableS3)
and this sample contained 7-hydroxymitragynine below that level.
Sample code Mitragynine (mg/g)b7-Hydroxymitragynine (mg/g)bSpeciofoline (mg/g)b
K50 11.37 ± 0.83 0.053 ± 0.014 < LOQc
K51 11.45 ± 0.74 0.056 ± 0.019 < LOQc
K52 8.13 ± 0.95 0.0349 ± 0.0030 4.13 ± 0.45
K55 0.75 ± 0.14 < LOQd < LOQ c
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e dierential binding anity of mitragynine and 7-hydroxymitragynine at opioid receptors (Table2) is con-
sistent with previous literature14,15. Also consistent with literature reports14,15 both mitragynine and 7-hydroxymi-
tragynine function as partial agonists at the µ-opioid receptors and are functionally selective for G protein versus
β-arrestin-2 signaling (Fig.5). ese eects are quite dierent from the binding and activity of typical opioids
such as morphine (Fig.5). e failure of mitragynine or 7-hydroxymitragynine to recruit β-arrestin-2 may be an
important factor separating the analgesic eect from the adverse eects of typical opiates such as abuse liability,
respiratory depression and constipation. However, 7-hydroxymitgraynine, but not mitragynine, exhibits abuse
liability in rodent models of human drug-taking18, suggesting that β-arrestin-2 signaling may not be a signicant
contributing factor to the addictive properties of opiates. In contrast, speciofoline does not bind at the opioid
receptors and does not exhibit functional activity via the µ-opioid receptor. Future studies are warranted to
characterize speciofoline and determine if the ligand may induce antinociception or other activities through
non-opioid receptor systems, and to further characterize the pharmacological eects of kratom extracts and
their isolated alkaloids invivo.
Figure5. Kratom alkaloid mediated inhibition of forskolin-stimulated cAMP accumulation and β-arrestin
recruitment. (A) CHO-K1 cells stably expressing hMOR were incubated with the indicated concentrations
of compounds as described in Methods. Data are expressed as the percent of forskolin-stimulated cAMP
accumulation and represent mean ± SEM of 3–4 experiments. (B) β-arrestin-2 recruitment. CHO-K1 cells stably
expressing the µ-opioid receptor and β-galactosidase linked β-arrestin-2 were incubated with the indicated
concentrations of compounds as described in Methods. Data are expressed as the percent of maximal DAMGO
mediated response and represent mean ± SEM of 3–4 experiments. Emax and EC50 values for cAMP accumulation
and β-arrestin2 recruitment are listed in the table.
Table 2. Opioid receptor anities for kratom alkaloids. Competitive binding studies were performed against
3H-DAMGO, 3H-U69-593 and 3H-deltorphin for µ-, ƙ-,and δ-opioid receptors respectively. Results are
presented as nM ± SEM from a minimum of three replicates.
Receptor binding anity (Ki ± SEM, nM)
µ-opioid ƙ-opioid δ-opioid
Mitragynine 238 ± 28 482 ± 29 > 10,000
7-Hydroxymitragynine 16 ± 1 113 ± 37 137 ± 21
Speciofoline > 10,000 > 10,000 > 10,000
Morphine 1.50 ± 0.04 48.9 ± 5.0 > 10,000
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High‑speciofoline and low‑speciofoline kratom extracts have similar inhibitory eects on
three major CYPs in vitro. e cytochromes P450 (CYPs) constitute a superfamily of oxidative enzymes
that mediate the metabolism of approximately 50% of the top 200 most prescribed drugs38. Inhibition of these
enzymes by xenobiotics, including drugs and botanical products (precipitants), can lead to increased systemic
exposure to the object drug and potential adverse or toxic eects. Kratom extracts39 and mitragynine11,40 have
been tested as inhibitors of several CYPs, including CYP1A2, CYP2C9, CYP2C19, CYP2D6, and CYP3A4.
Tested extracts and mitragynine were generally stronger inhibitors of CYP2D6 activity relative to the other
Mitragynine has been reported to inhibit several cytochrome P450s (CYPs)11,39–41, which could lead to
increased systemic exposure to co-consumed drugs, including opioids, and potential adverse eects. We evalu-
ated whether the observed variability in alkaloid prole for kratom extracts results in altered inhibitory eects
on three major CYPs, specically CYP2C9 (Fig.6A), CYP2D6 (Fig.6B), and CYP3A (Fig.6C). All three kratom
extracts tested showed concentration-dependent inhibition of each CYP, with stronger eects on CYP2D6 com-
pared to CYP2C9 and CYP3A. Eects on each CYP were similar between the high speciofoline (K52) and low
speciofoline (K50 and K51) kratom samples (Fig.6). Mitragynine and speciofoline showed similar inhibitory
Figure6. Kratom extracts (K50, K51, and K52), mitragynine, 7-hydroxymitragynine (7-HMG), and
speciofoline showed concentration-dependent inhibition of cytochrome P450 (CYP) enzymes in human
liver microsomes. Diclofenac 4′-hydroxylation (A), dextromethorphan O-demethylation (B), and midazolam
1′-hydroxylation (C) were used as measures of CYP2C9, CYP2D6, and CYP3A activity, respectively. Extracts
were tested at 2, 10, and 20µg/mL; alkaloids were tested at 1, 10, and 100µM. Positive control inhibitors
included sulfaphenazole (1µM), quinidine (2µM), and ketoconazole (0.1µM) for CYP2C9, CYP2D6, and
CYP3A activity, respectively. Control activities averaged 220, 70, and 1270pmol/min/mg, respectively. Bars and
error bars denote means and standard deviations, respectively, of triplicate incubations.
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eects towards CYP2C9 and CYP3A activity, whereas mitragynine showed stronger inhibition than speciofoline
against CYP2D6 activity. Relative to mitragynine and speciofoline, 7-hydroxymitragynine was a weak inhibitor
of CYP2C9 and CYP3A activity and a moderate inhibitor of CYP2D6 activity (i.e., inhibitory eects via mitragy-
nine > 7-hydroxymitragynine > speciofoline).e concentration of mitragynine in the kratom extracts tested at
20µg/mL was ~ 1µM. e stronger inhibitory eects of the extracts compared to an equimolar concentration
of isolated mitragynine indicated additional CYP inhibitors are present in the extracts. If the concentration of
mitragynine in the liver upon kratom consumption nears the IC50 values estimated from the screening assay
(~ 1µM for CYP2D6; 10–100µM for CYP2C9 and CYP3A), a CYP-mediated kratom-drug interaction is possible.
In addition, because CYP3A is also expressed in the intestine, mitragynine concentrations in the intestine could
well exceed 10µM, increasing the possibility of CYP3A-mediated kratom-drug interactions. A comprehensive
clinical pharmacokinetic study with a well-characterized kratom product is needed to determine the systemic
exposure to mitragynine and other kratom alkaloids, as well as additional mechanistic invitro studies, to ascer-
tain the likelihood of pharmacokinetic kratom-drug interactions.
Collectively, our chemical and invitro studies support previous studies suggesting that the purported ecacy
of kratom against pain is mediated at least in part by kratom alkaloids that function as biased ligands of the
µ-opioid receptors. ese ndings further highlight the value of pursuing mitragynine and related alkaloids as
an alternative strategy to treat pain, as, consistent with previous literature, our ndings suggest that they have
less abuse liability than classic opiates such as morphine. Future invivo studies are necessary to further explore
Our results also demonstrate that the identity and abundance of major alkaloids is highly variable in geneti-
cally similar kratom plant material, with some kratom products being dominated by the indole alkaloid mitragy-
nine and others containing high levels of both mitragynine and the oxindole alkaloid speciofoline. On the basis
of our studies, it is reasonable to predict that individuals who self-administer kratom tea to treat pain, addiction,
or depression might achieve very dierent results depending on the alkaloid prole of the product that they
use. Such dierences in activity would be dicult to predict for consumers, given that the variability in alka-
loid content is in no way reected in the product labeling. Additional studies are warranted to understand the
underlying causes for variability in alkaloid content in kratom plant material, and to evaluate the therapeutic
implications of this variability.
Consistent with previous literature, our results raise concern about potential drug interactions that may occur
when kratom is consumed concurrently with opiates or other drugs metabolized by the cytochrome P450s. Fol-
lowing up on these ndings, future clinical studies to evaluate the safety and ecacy of kratom and its alkaloids
would be of great benet to the public that may employ this botanical for the treatment of pain, currently or
in the future. In such studies, it would be useful to consider the potential dierences in activity that would be
observed by complex M. speciosa preparations as compared to their isolated alkaloids, and to account for potential
dierences in alkaloid prole in dierent kratom materials. Chemical proling of samples prior to evaluating
their biological activity is clearly crucial, and it is important that the biological studies be informed by the results
of the chemical analyses. is study demonstrates how untargeted mass spectrometry metabolomics followed
by targeted mass spectrometric quantitation can be eectively employed to generate chemical data valuable to
inform biological evaluation. As such, our approach can serve as a model for the design of future studies.
General. DAMGO, quinidine, ketoconazole, morphine sulfate, and alprazolam were purchased from Mil-
liporeSigma (St Louis, MO). Mitragynine, 7-hydroxymitragynine, midazolam, 1′-hydroxymidazolam, sul-
faphenazole, and NADPH were obtained from Cayman Chemical Company (Ann Arbor, MI). Diclofenac,
4′-hydroxydiclofenac, dextromethorphan, and dextrorphan were obtained from Toronto Research Chemicals,
Inc. (Toronto, Canada). Potassium phosphate buer salts were obtained from Fisher Scientic (Fair Lawn, NJ).
Human liver microsomes were obtained from XenoTech, LLC (H0604, mixed gender, pool from 15 donors, lot
no. 1010191; Kansas City, KS). All other chemicals and reagents used were analytical grade.
Acquisition of Kratom plant material. Fiy commercial products labeled as kratom were obtained from
vendors within the US. A table with details about these products is available in the supporting information
(TableS1). e commercial kratom products were obtained as dried powders and were various shades of grey-
green, with the exception of product K49, which was obtained as a cut leaf. All plant material was stored dry at
room temperature until time of analysis.
A cultivated plant of kratom (Mitragyna speciosa) (coded as K55) was generously donated to the project by
Shon Lenzo. e plant was grown from the cutting of a 7-year-old tree from a strain labeled as “rifat.” Prior to
shipping to the University of North Carolina Greensboro, the cutting was grown indoors in a greenhouse under
a 1000W high pressure sodium (HPS) LED light for 6months. Upon receipt, the plant was repotted and trans-
ferred to an outdoor location near the University of North Carolina Greensboro, where it was grown for several
summer months. Leaves were cut from this plant, dried at room temperature and powdered for extraction using
a Wiley Mill Standard Model No. 3 (Arthur omas Company). A sample of leaves from this plant, harvested at
the coordinates 36°4′53.616″ N 79°47′6.18″ W, was pressed and submitted to the University of North Carolina
Herbarium, with accession #670043 (sernecportal.org catalog number NCU00433756).
Isolation of speciofoline. Kratom plant material (K52, 1kg) was extracted exhaustively with 2 L of CHCl3/
CH3OH (1:1) and 50mL of KOH (10%) by maceration over 24h at room temperature. e mixture was ltered,
Scientic Reports | (2020) 10:19158 |
and the solvent was evaporated under reduced pressure. e dried extract was reconstituted in 1N HCl solu-
tion and hexanes (1:1), transferred to a separatory funnel, and shaken vigorously. Aer removal of the hexanes
phase, the pH of the aqueous phase was adjusted to 9.0 with concentrated NH4OH solution. e basic phase was
exhaustively extracted with CHCl3, and the organic phase was evaporated to dryness to yield 1.0g of the dried
extract. Fractionation of the extract was conducted with normal phase ash chromatography using a silica col-
umn (24g) and a gradient solvent system of hexane–acetone-CH3OH over 52min at a ow rate of 35mL/min.
In total, thirteen pooled fractions were obtained. Fraction 4 was subjected to preparative reversed phase HPLC
over a Luna PFP(2) (pentauorophenyl) column (Phenomenex, 250mm × 21.2mm, 5µm) using a gradient of
70:30 to 100:0 CH3OH–H2O (10mM of ammonium acetate in both phases) over 20min at a ow rate of 20mL/
min. is process yielded 25.0mg of speciofoline (95% purity based on UPLC-UV), the structure of which was
solved by comparison of the calculated ([M + H]+ C22H29N2O5, 401.2076) and measured (401.2067) m/z values
and by comparison of key 1H-NMR signals (FigureS1 and TableS2) and the ECD spectra (FigureS2) with those
reported in the literature25.
Extraction for metabolomics proling. For each extraction of powdered kratom sample, 50mg of dried
kratom plant material was extracted with 5.0mL of methanol in a 25mL scintillation vial. Extracts were shaken
at 150rpm for 12h and the powder was allowed to settle. e extracts were decanted into clean scintillation
vials and dried under nitrogen. Extracts were resuspended in methanol containing 0.125µg/mL of mitragynine-
D3 (MilliporeSigma, St. Louis, MO, USA) for analysis. All diluted extracts contained mitragynine-D3 at a nal
concentration of 0.125µg/mL as an internal standard to monitor the consistency of the instrument performance.
Ultraperformance liquid chromatography–mass spectrometry (UPLC‑MS) analysis of Kratom
extracts. Untargeted metabolomics analyses were conducted using an Acquity Ultra-Performance Liq-
uid Chromatography system (Waters, Milford, MA, USA) coupled to a Q Exactive Plus Hybrid Quadrupole-
Orbitrap mass spectrometer (ermo Fisher Scientic, Waltham, MA). A Kinetex F5 column (Phenomenex,
50mm × 1mm, 2.6µm) was employed with a ow rate of 0.6mL/min and a column temperature of 40°C. e
starting conditions were 65% A, optima grade water with 0.1% formic acid and 2mM ammonium formate, and
35% B, optima grade methanol with 0.1% formic acid and 2mM ammonium formate. e gradient is as follows:
a slight decrease to 55% A at 0.5min which is held until 3.0min, followed by a linear decrease to 20% A at 10min
down to 0% A at 11.0min. e gradient returns to starting conditions at 12min and that is held for 1min. A 5µL
injection was employed for all samples using a 5µL sample loop.
Mass spectrometry analysis utilized a heated electrospray ionization (HESI) source: spray voltage 3.5kV,
capillary temperature 275°C, sheath gas 55 arbitrary units, auxiliary gas 15 arbitrary units, sweep gas 3 arbitrary
units, heater temperature 450°C, and an RF level of 50. A scan range of 150–900m/z was employed in positive
mode with a resolving power of 70,000 and an AGC target of 3E6. MS/MS data were collected on the standards
using a normalized collision energy (NCE) of 35V.
Metabolomics data processing. e UPLC-MS data were analyzed, aligned, and ltered using MZmine
2.28 soware (https ://mzmin e.githu b.io/) with a slightly modied version of a previously reported method42.
e following parameters were used for peak detection of the data: noise level (absolute value), 1 × 105 counts;
minimum peak duration 0.5min; tolerance for m/z intensity variation, 20%. Peak list ltering and retention time
alignment algorithms were performed to rene peak detection. e join algorithm was used to integrate all the
chromatograms into a single data matrix using the following parameters: the balance between m/z and retention
time was set at 10.0 each, m/z tolerance was set at 0.001 or 5ppm, and retention time tolerance was dened as
0.5min. Once an aligned peak list was created, features (m/z and retention time pairs) present in the rst blank
sample of the run were deleted as a means of blank ltering. e peak areas for individual ions detected in the
process replicates and analytical replicates were exported from the data matrix for further analysis. e peak
list from MZmine was exported into Excel (Microso, Redmond, WA) for further ltering based on relative
standard deviation between analytical replicates. Analytical replicates would be expected to have comparable
proles, and similar peak areas for each feature. Ions detected within the analytical replicates with disparate
peak areas (based on an RSD cuto of 25%) were assigned as artefacts of the instrument and excluded from the
Principal component analysis (PCA) was performed using Sirius version 10.0 (Pattern Recognition Systems
AS, Bergen, Norway). e 95% condence intervals were calculated using Hotelling’s T2 with the R package ‘car’44
using an R script available from https ://githu b.com/joshk ellog g/Compo site-score .
Identication and quantitative analysis of alkaloids in kratom plant material. Standard solu-
tions of mitragynine and 7-hydroxymitragynine were purchased from MilliporeSigma (St. Louis, MO, USA) and
supplied as methanolic solutions at a concentration of 100µg/mL. An analytical standard for speciofoline was
unavailable for purchase, therefore an aliquot of puried speciofoline isolated as part of this study was dissolved
in methanol at a concentration of 100µg/mL. A 100 µL aliquot of each standard solution was combined with 600
µL of methanol and 100 µL of water to make a stock solution containing 10µg/mL of each alkaloid of interest.
A standard calibration curve was prepared using the stock solution in two-fold dilutions from 5000ng/mL to
4.9ng/mL followed by a single 1:10 dilution of the lowest concentration in methanol. All samples were analyzed
using the UPLC-MS method previously described. e selected-ion chromatograms for the calculated m/z val-
ues of the alkaloids of interest (mitragynine, [M + H]+ = 399.2284; 7-hydroxymitragynine, [M + H]+ = 415.2233;
speciofoline, [M + H]+ = 401.2076) within a mass error of 5ppm were plotted, and a calibration curve was con-
structed as area of these chromatograms versus concentrations. Calibration parameters are provided in TableS3.
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Identity of the alkaloids in the M. speciosa plant material was conrmed by matching retention time and m/z
value with that of the standards. e alkaloid concentrations in the kratom extracts were determined using linear
regression of these calibration curves. Peak areas were calculated using the ermo Xcalibur QuanBrowser ver-
sion 3.0.63 and statistical analysis was performed using RStudio version 1.2.1335.
Authentication of plant material. Authentication (assignment of genus and species) of kratom products
K51, K52 (powdered material), and K55 (vouchered plant specimen) was accomplished using DNA barcod-
ing and maximum likelihood phylogenetic analysis. e most widely recommended loci, the plastid intergenic
spacer trnH-psbA, rbcL, matK, and the nuclear ribosomal internal transcribed spacers (ITS) were employed.
ese regions have been designated as the ocial DNA barcodes for the plant kingdom29,30.
For DNA extraction from the plant material (K55), a whole leaf sample was ground to a ne powder with
a sterile mortar and pestle using liquid nitrogen. Approximately 5mg of plant powder from the plant (K55) or
from commercial sources (K51, K52) was transferred to a bashing bead tube with DNA lysis buer provided by
Zymo Research Quick-DNA plant/seed miniprep DNA extraction kit. e powder in the bashing bead tube was
further disrupted and homogenized in a Qiagen TissueLyser LT beadmill for ve minutes. For K51 and K52, the
samples were separately ground in bashing bead tubes, without treatment with liquid nitrogen. Genomic DNA
was then extracted according to kit instructions.
Detailed methods for DNA extraction, PCR amplication, and Sanger sequencing are outlined previously45.
e partial rbcL region was amplied and sequenced using primers rbcLa-F and rbcLa-R30,46. Details of PCR
primers and thermocycler parameters for all fragments amplied are outlined in Supplementary TableS4.
For identication of kratom plant material via DNA Barcoding, two plastid regions (rbcL + matK) sequences
were utilized in a combined analysis for plant identication by BLAST searching against the BOLDSYSTEMS
Uncorrected p-distances were calculated in Geneious, a bioinformatics desktop soware package (https ://
www.bioma tters .com) for sequences obtained from the trnH-psbA plastid region, which is considered as one
of the most variable regions of angiosperm plants47–50. Comparisons were made using published sequence data
from NCBI GenBank for Mitragyna spp., including M. speciosa and the newly obtained sequences in this study
(Supplementary TableS5). e p-distances were obtained by dividing the number of nucleotide dierences by
the total number of nucleotides being compared. A cut o proxy of ≥ 98–100% was applied as a criterion to desig-
nate similar species; therefore, to be considered the same species based on trnH-psbA sequence comparison, the
taxa being compared should have ≥ 98% sequence similarity (with 1–2% intraspecic variation or dierences).
Maximum likelihood and Bayesian analysis was performed separately for both the combined analysis using
matK + trnH-psbA, and the nrDNA ITS region to place the kratom samples (K51, K52, and K55) into a phylo-
genetic framework with authentic published sequences of M. speciosa48–52 using methods outlined previously53
(see Supplementary for details).
Nauclea ocinalis (Rubiaceae) was used as an outgroup taxon in both matK + trnH-psbA and ITS region
analysis, respectively. e sequence data obtained from samples K51, K52, and K55 are deposited in GenBank
and accession numbers are provided in TableS6.
Cytochrome P450 (CYP) inhibition assay. Mitragynine and 7-hydroxymitragynine (purchased), speci-
ofoline (the isolated alkaloid), and three methanolic kratom extracts (prepared from commercial products K50,
K51, and K52; Table1), were tested as inhibitors of CYP2C9, CYP2D6, and CYP3A activities using a cocktail
approach54. Diclofenac (4µM), dextromethorphan (4µM), and midazolam (2µM) were used as probe substrates
for CYP2C9, CYP2D6, and CYP3A activities, respectively. Kratom extract (2, 10, 20µg/mL) or alkaloid (1, 10,
100µM) was incubated with human liver microsomes (0.05mg/mL) in 100mM potassium phosphate buer,
pH 7.4. Positive control inhibitors included sulfaphenazole (1µM; CYP2C9), quinidine (2µM; CYP2D6), and
ketoconazole (0.1µM; CYP3A). Final organic solvent (methanol) concentration in each incubation was limited
to 0.8% v/v. Aer equilibrating the mixtures for 5min at 37°C, the reaction was initiated by addition of NADPH
(1mM nal concentration) and incubated for 10min (CYP2C9 and CYP2D6 activities) or 2min (CYP3A activ-
ity) at 37°C. Reactions were quenched with 2 volumes of cold methanol containing internal standard (alpra-
zolam, 0.1µM). e quenched mixtures were centrifuged at 2270 × g for 10min, and the supernatants were
subjected to UPLC-MS/MS analysis for quantication of 4′-hydroxydiclofenac, dextrorphan, and 1′-hydroxy-
midazolam. e percent of CYP inhibition in the presence of the test article was calculated relative to solvent
e CYP-mediated metabolites (4′-hydroxydiclofenac, dextrorphan, and 1′-hydroxymidazolam) were quanti-
ed using a QTRAP system (AB Sciex, Framingham, MA), operating in positive electrospray ionization mode,
coupled to a Shimadzu Nexera X2 UHPLC (Shimadzu Corporation, Tokyo, Japan). Chromatographic separation
was achieved using an Acquity C18 column (3µm, 50 × 2.1mm, ermo Scientic, Waltham, MA) with a guard
column, heated to 40°C, and a binary gradient at a ow rate of 0.5mL/min. e mobile phase consisted of 0.1%
formic acid in water (A) and 0.1% formic acid in methanol (B). e following gradient was applied: 0–0.4min,
10% B; 0.4–1.0min, 10–95% B; 1.0–2.0min, 95% B; 2.0–2.1min, 95%-10% B; and 2.1–3.0min, 10% B. e
following multiple reaction monitoring transitions were used: m/z 312.0 → 231.0 (4′-hydroxydiclofenac), m/z
258.2 → 157.2 (dextrorphan), m/z 342.0 → 324.0 (1′-hydroxymidazolam), and m/z 309.1 → 281.0 (alprazolam).
All analyte concentrations were quantied using MultiQuant soware (version 2.1.1; AB Sciex; https ://sciex
.com/produ cts/sow are/multi quant -sow are) by interpolation from calibration curves prepared from relevant
matrix-matched standards over a range of concentrations (1.37–1000nM).
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cAMP accumulation assay. e cAMP Hunter eXpress OPRM1 CHO-K1 GPCR assay (Eurons Discov-
erX Corporation, St. Charles, MO, USA) was performed according to manufacturer’s instructions. Briey, cells
were seeded in 100µL cell plating reagent in 96 well plates and allowed to incubate at 37°C (5% CO2, 95% rela-
tive humidity) for 24h. Medium was removed from cells, and cells were washed with 30μL of cell assay buer.
Each compound was assessed using an 11 point vefold serial dilution with a starting concentration of 10μM.
Aliquots of compound/forskolin solution were added to cells (nal concentrations were 20μM forskolin, and
0.4% DMSO) and incubated at 37°C and 5% CO2for 30min. Next, cAMP antibody reagent detection solution
was added to each well according to manufacturer’s instructions at room temperature and protected from light
for 1h. Next, enzyme acceptor solution was added and the solution allowed to incubate at room temperature
and protected from light for 3h. Luminescence was quantied using a SpectraMax iD5 multi-mode microplate
reader with SoMax Pro soware (version 7.1, Molecular Devices, San Jose, CA, https ://www.molec ulard evice
s.com/produ cts/micro plate -reade rs/acqui sitio n-and-analy sis-sow are/som ax-pro-sow are). Data were nor-
malized to vehicle and forskolin only control values and analyzed using nonlinear regression with Prism 8.4
(Graphpad, San Diego, CA).
β‑arrestin recruitment assay. e PathHunter eXpress OPRM1 CHO-K1 β-Arrestin GPCR assay (Euro-
ns DiscoverX Corporation) was performed according to the manufacturer’s protocol. Briey, cells were seeded
in 100 µL cell plating reagent in 96 well plates and allowed to incubate at 37°C (5% CO2, 95% relative humidity)
for 48h. Each compound was assessed using an 11 point vefold serial dilution with a starting concentration
of 10µM. Aliquots of compound solution were added to cells (nal concentrations were 20μM forskolin, and
0.4% DMSO) and incubated at 37°C and 5% CO2for 30min. Detection solution was then added to cells and
incubated at room temperature protected from light for 1h. Luminescence was quantied using a SpectraMax
iD5 multi-mode microplate reader with SoMax Pro soware (Molecular Devices, San Jose, CA). Data were
normalized to control values and analyzed using nonlinear regression to determine maximal and EC50 values
(Prism 8.4 for Mac; Graphpad San Diego, CA).
Binding anity to µ‑opioid receptors. HEK293 cells expressing human µ, δ- or κ-opioid receptors
were washed in ice cold PBS and scraped from cell culture plates in cold 50mM Tris–HCl buer, pH 7.4. Cells
were pelleted at 5200 × g for 10min at 4°C. Supernatant was discarded and the pellet was washed with more
Tris–HCl buer, sonicated, and centrifuged at 24,000 × g for 40min at 4°C. e pellet was re-suspended in Tris–
HCl buer, sonicated, and aliquoted for storage at − 80°C until use. A Pierce BCA Protein Assay was utilized
to determine protein concentration in the membrane, according to manufacturer’s instructions. Membranes
were evaluated in saturation experiments to determine the optimal concentration for radioligand binding and
functional assays. A competitive binding assay was utilized to determine the Ki of each compound similar to
previous reports55,56. For this, 25μg of cell membrane was diluted in 50mM Tris–HCl, pH 7.4 and pipetted into
a 96 well plate. Test compounds were reconstituted in DMSO and added to the reaction plate.[3H]-DAMGO,
[3H]-U69-593 or [3H]-deltorphin (for µ-, ƙ-, and δ-opioid receptors respectively) was then added at a nal
concentration of 2–4nM (Perkin Elmer, Waltham, MA, USA). e reaction was incubated for 1h at room tem-
perature prior to transfer onto GF/B lter plates (Perkin Elmer). e plates were washed 10 × with cold buer
and dried for 15min at 50°C. MicroScint20 was then added to each well, the plates were sealed, and the counts
per minute were quantied on the TopCount NXT Microplate Scintillation counter (Perkin Elmer). e percent
displacement of the radiolabeled compound was calculated as described57. Unlabeled DAMGO was used to
determine non-specic binding control counts, while vehicle (DMSO) was added to determine total radioligand
binding on each plate. A series of three-fold dilutions were used for each test compound starting at 10μM. A
control curve of naloxonewas included on each plate for internal control.
Raw mass spectrometric data have been made publicly available through MassIVE (MassIVE ID: MSV000086288,
https ://doi.org/10.25345 /C59V0 X). All other data are available by request to the corresponding author.
Received: 19 June 2020; Accepted: 22 October 2020
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We are grateful to Shon Lenzo and Richard A. (Richo) Cech for expertise in the cultivation of Mitragyna speciosa
plants and for providing cultivated M. speciosa samples. Research reported in this publication was supported in
part by the National Center for Complementary and Integrative Health, U.S. National Institutes of Health under
award numbers F32 AT009816 (fellowship to JJK) and U54 AT008909 (Center of Excellence for Natural Product
Drug Interaction Research) and by a supplement to U54 AT008909 provided by the NIH Oce of Dietary Sup-
plements. Mass spectrometry data were collected in the Triad Mass Spectrometry Facility at the University of
North Carolina at Greensboro. e Neuropharmacology Core Facility at the University of Mississippi School of
Pharmacy conducted the receptor binding experiments. e Core is funded by NIH P30GM122733. We thank
Ali Shahbandi and Zoie Bunch for technical assistance.
D.A.T., J.J.K., N.B.C., L.F.B., R.S.T., H.A.R., S.H.E., M.F.P., N.H.O. and N.B.C. wrote and edited the manuscript,
D.A.T. coordinated the experimental work and prepared gures, J.J.K. and E.D.W. conducted the extractions
and metabolomics analysis, M.K. performed quantitative analysis, L.F.B. performed isolation experiments, R.S.T.
conducted the C.Y.P. inhibition assays, S.M. and S.E.H. evaluated receptor binding, T.N.G. provided experimental
support for extract analysis and sample acquisition, HAR conducted genetic analysis, M.F.P., N.H.O., N.B.C.
secured project funding, analyzed data, and supervised the experimental work.
e authors declare no competing interests.
Supplementary information is available for this paper at https ://doi.org/10.1038/s4159 8-020-76119 -w.
Correspondence and requests for materials should be addressed to N.B.C.
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