Monarda Fistulosa Flower Extract Decreases Interleukin-6 Production by Lipopolysaccharide-Stimulated RAW 264.7 Murine Macrophages

Abstract

Monarda fistulosa (M. fistulosa) is a flowering plant used as an herbal remedy due to its anti-inflammatory properties. In this study, we sought to test the anti-inflammatory properties of a M. fistulosa methanolic flower crude extract and found that the extract decreased lipopolysaccharide-induced interleukin-6 cytokine production by RAW 264.7 macrophages. We went on to characterize potential anti-inflammatory bioactive compounds present in the methanolic extract of M. fistulosa flower using liquid chromatography-tandem mass spectrometry and molecular networking analysis. In total, 183 compounds were putatively identified. These findings contribute to our knowledge of the anti-inflammatory medicinal properties and underlying chemistry of M. fistulosa.

INTRODUCTION

Nature has produced some of the most important molecules of human history, from the fungal-derived antibiotic penicillin¹ to the cancer pharmaceutical paclitaxel, isolated from the bark of the Pacific Yew.² The natural products and their structural analogues have contributed greatly to human society, especially in the realm of medicine. To that end, our goal in this study was to investigate how the natural products within the flower of Monarda fistulosa affect the process of inflammation.

M. fistulosa belongs to the genus Monarda in the family Lamiaceae and is commonly referred to as wild bergamot or bee balm. The plant is easily cultivated, making it widespread on continents that have a temperate climate, and was widely cultivated in North America by Native Americans.³ M. fistulosa was historically used for its medicinal properties in Native American cultures, where the aerial parts of the plant were harvested and used to treat physical ailments. The most common use for M. fistulosa in Native American medicine was the treatment of various infections, headaches, colds, and other physical ailments.^3,4 The Cherokee used M. fistulosa to relieve headaches, and the Flambeau Ojibwe used the entire aerial part of the plant to obtain essential oil for treatments of bronchial and other conditions through inhalation.⁵ M. fistulosa is therefore widely regarded to have anti-inflammatory properties, and there have been several studies to characterize these properties and how the plant affects the body’s natural process of inflammation.³

M. fistulosa has been found to have a variety of compounds in the aerial parts of the plant, in particular in the flower of the plant, including monoterpenes, polyphenols, and phenylpropanoids.^3,4,6,7 These compound classes often fulfill endogenous functions as pigments in plants, signaling, or defense molecules, and many of these compounds can also possess strong anti-inflammatory, antioxidant, antinociceptive, and antimicrobial⁸ properties, which could contribute to the plant’s medicinal and therapeutic properties.⁹

In some cases, M. fistulosa has been found to have high levels of rosmarinic acid, luteolin-7-O-glucoside, and caffeic acid.³ Rosmarinic acid has strong anti-inflammatory, antioxidant, antinociceptive, and antimicrobial properties, demonstrated in both in vitro and in vivo studies.^3,10

–13 The anti-inflammatory properties have been demonstrated to be in part due to inhibition of interleukin (IL)-6 and tumor necrosis factor alpha (TNF-α) cytokine production.¹⁴ Caffeic acid has significant anti-inflammatory, antioxidant, antiviral, and anticancer properties.^15,16 Luteolin-7-O-glucoside has significant free radical scavenging activities and significant anti-inflammatory activity, confirmed in both in vivo and in vitro studies.^17,18

Prior work has shown that M. fistulosa extract significantly decreased paw edema of rats after an injection of carrageenan, which was used to cause a time-dependent increase in paw edema.¹³ Rosmarinic acid on its own demonstrated a significant anti-inflammatory effect on paw edema in rats over a 6-h period, with an overall reduction in edema of roughly 60% when compared with a control group.¹¹ Luteolin and luteolin-7-O-glucoside have also shown significant reduction of inflammation in a mouse model¹⁹ and decrease pro-inflammatory cytokine production in macrophages.^20,21

In this study, we used lipopolysaccharide (LPS)-stimulated RAW 264.7 murine macrophages to investigate the anti-inflammatory effect of the methanolic M. fistulosa flower extract treatment. Methanol was chosen as the extraction solvent in order to observe the polar metabolites of the plant. Previous works to characterize the anti-inflammatory properties of M. fistulosa have used the whole plant, the flowers and leaves together, or just the petals of the flower to make an extract or essential oil, so our study is unique in using the entire flower for the extract.^3,4,6,7 Additionally, we sought to ascertain a more complete picture of the chemical composition of a methanolic M. fistulosa flower extract using liquid chromatography-tandem mass spectrometry (LC-MS/MS) and Global Natural Product Social Molecular Networking (GNPS) molecular networking, looking at metabolites with molecular weights ranging from 150 to 1200 m/z.

MATERIALS AND METHODS

Sample collection and preparation

M. fistulosa flowers were collected from the Pomme de Terre Outlook at the West Central Research and Outreach Center in Morris, Minnesota. M. fistulosa flowers were pressed between cardboard and dried in a plant oven at approximately 60°C for 2 days. To obtain the extract used in the biological assays, 2.59 g of dried M. fistulosa flowers were subjected to Soxhlet extraction using methanol for 24 h. The resulting methanolic solution was evaporated in vacuo to yield a green residue, which was then resuspended in phosphate-buffered saline.

Endotoxin detection assay

A chromogenic LAL endotoxin detection kit was purchased from GenScript and used according to the manufacturer’s protocol. No endotoxin was detectable in the methanolic M. fistulosa flower extract.

Cell culture

RAW 264.7 murine macrophage cells were provided by Dr. Tanya Freedman (UMN Center for Immunology). Cells were cultured in Dulbecco’s modified Eagle’s minimum essential medium (HyClone) containing 10% Cosmic Calf Serum (Hyclone), 100 U/mL penicillin (Gibco), and 100 µg/mL streptomycin (Gibco) at 37°C in an atmosphere containing 5% CO₂.

Cell viability

A 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay kit was purchased from Biotium and performed according to the manufacturer’s protocol. RAW 264.7 cells in exponential growth phase were seeded on 96-well plates at a density of 0.5 × 10⁶ cells/mL. Cells were treated with the M. fistulosa plant extract at various doses (12.5, 3.1, and 0.8 µg/mL) in the presence or absence of LPS stimulation (Invitrogen) for 48 h. Supernatants were harvested for cytokine assays, and the cells were used for the MTT assay. Plates were read at 570 nm using an ELx808IU plate reader. A two-sided paired Student’s t test was used to assess statistical differences in experimental groups. A P value ≤.05 was considered statistically significant.

Cytokine assays

RAW 264.7 culture supernatants were tested for IL-6 and TNF-α cytokine levels after co-culture with M. fistulosa extract and LPS. Mouse IL-6 and TNF-α ELISA MAX kits were purchased from BioLegend and used according to the manufacturer’s protocol. Plates were read at 450 nm using an ELx808IU plate reader. A two-sided paired Student’s t test was used to assess statistical differences in experimental groups. A P value ≤.05 was considered statistically significant.

Extraction of samples and LC-MS/MS analysis

Dried M. fistulosa flowers (0.2 g) were placed into a 2-mL tissuelyser tube containing 10 Zirconia/silica beads (2.3-mm diameter) and frozen on dry ice. Frozen M. fistulosa samples were then lysed with a Fastprep-24 5G tissuelyser (MP Biomedicals) by three 40 s cycles at 6 m/s speed. One milliliter of 80% methanol/20% water was added to the tubes with the ground M. fistulosa tissue, then lysed for one additional cycle on the tissuelyser and incubated for 10 min at 60°C. Crude M. fistulosa extracts were centrifuged at 16,000 g for 5 min, filtered by Whatman syringeless filters (0.2 μm) and were subjected to LC-MS/MS analysis.

Samples were run on a Thermo QExactive orbitrap mass spectrometer in positive ion mode coupled to a Vanquish UPLC using the following parameters: Injection volume 5 μL, LC—Phenomenex Kinetex® 2.6 μm C18 reverse phase 100 Å 150 × 3 mm LC column, LC gradient: solvent A—0.1% formic acid, solvent B—acetonitrile (0.1% formic acid), 0 min: 10% B, 5 min: 60% B, 5.1 min: 95% B, 6 min: 95% B, 6.1 min: 10% B, 9.9 min: 10% B, 0.5 mL/min, MS—positive ion mode, full MS: resolution 70,000, mass range (a) 400–1200 m/z or (b) 150–450 m/z, dd-MS2 (data-dependent MS/MS): resolution 17,500, AGC target 1e5, loop count 5, isolation width 1.0 m/z, collision energy 25 eV, dynamic exclusion 0.5 s.

Two LC-MS/MS datasets were generated: one with MS1 mass range of 400–1200 m/z for larger metabolite analysis (10 min methods) and one with MS1 mass range of 150–450 m/z for small metabolite analysis (30 min methods).

LC-MS/MS data analysis

The MS-MS data were analyzed by creating molecular networks (MN) while comparing sample MS/MS data to the spectral libraries and tools from the GNPS database.²² Raw mass spectral datafiles were converted to an mzML format using MSConvert.²³ A MN was created using the online workflow (https://ccms-ucsd.github.io/GNPSDocumentation/, version “release_30”) on the GNPS website (http://gnps.ucsd.edu). The data were filtered by removing all MS/MS fragment ions within ±17 Da of the precursor m/z. MS/MS spectra were window filtered by choosing only the top six fragment ions in the ±50 Da window throughout the spectrum. The precursor ion mass tolerance was set to 0.05 Da, and a MS/MS fragment ion tolerance of 0.25 Da. A network was then created where edges were filtered to have a cosine score above 0.7 and more than four matched peaks (150–450 m/z analysis) or more than six matched peaks (400–1200 m/z). Edges between two nodes were kept in the network only if each of the nodes appeared in each other’s respective top 10 most similar nodes. Finally, the maximum size of a molecular family was set to 100, and the lowest-scoring edges were removed from molecular families until the molecular family size was below this threshold. The spectra in the network were then searched against GNPS’ spectral libraries. Library spectra were filtered in the same manner as the input data. All matches kept between network spectra and library spectra were required to have a score above 0.7 and at least four matched peaks (150–450 m/z) or at least six matched peaks (400–1200 m/z).

Positive mode task ID (150–450 m/z): ae3154e2ec7f4cf59cee161f0e05b2ac

Positive mode task ID (400–1200 m/z): e89ad7bbde5246ec9c88c7753697c956

Classification of identified compounds was done using ClassyFire²⁴ by submitting InCHE or SMILES codes for each compound.

RESULTS

To characterize the anti-inflammatory activity of the M. fistulosa methanolic flower extract, we first determined whether the extract had any cytotoxic effect on RAW 264.7 murine macrophages using an MTT assay. As shown in Figure 1, the M. fisulosa methanolic flower extract did not influence the viability of RAW 264.7 cells in the presence or absence of LPS stimulation. We went on to determine the influence of the M. fisulosa methanolic flower extract on the production of the pro-inflammatory cytokines IL-6 and TNF-α. As shown in Figure 2, RAW 264.7 cells produce high levels of IL-6 and TNF-α in response to LPS stimulation. The M. fisulosa methanolic flower extract treatment led to a decrease in IL-6 production by LPS-stimulated RAW 264.7 cells in a dose-dependent manner but did not significantly influence TNF-α production by LPS-stimulated RAW 264.7 cells.

FIG. 1.

M. fistulosa extract does not influence survival of RAW macrophages ± LPS stimulation. RAW macrophages were cultured ± LPS and varying amounts of M. fistulosa plant extract as indicated for 48 h. Percent survival was determined by MTT assay. (Horizontal dashes indicate mean, n = 4). LPS, lipopolysaccharide; MTT, 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide.

FIG. 2.

M. fistulosa extract decreases IL-6 production but has no effect on TNF-α production by LPS-stimulated RAW macrophages. RAW macrophages were cultured ± LPS and varying amounts of M. fistulosa plant extract as indicated for 48 h. Supernatants were harvested and used for IL-6 ELISA assay and TNF-α ELISA assay. (Horizontal dashes indicate mean, n = 3, *P ≤ .005, **P ≤ .0005.) ELISA, enzyme-linked immunosorbent assay; IL-6, interleukin 6.

Using molecular networking, 2384 compounds and 132 spectral families made up of at least two structurally related compounds were found in the M. fistulosa extract analysis of analytes in the 150–450 m/z sample (Fig. 3). Additionally, 928 compounds and 84 spectral families made up of at least two structurally related compounds were found in the M. fistulosa extract analysis of analytes in the 400–1200 m/z sample (Fig. 4), for a total of 3312 compounds and 216 spectral families. In this analysis, the similarity of compounds’ MS2 spectra was evaluated based on their cosine score within GNPS, which is a value between 0 (no similarity) and 1 (identical spectra). The cosine value takes into account the precursor ion, fragment ions, and peak intensities.²² In all, 183 compounds (5.5%) were putatively identified with previously characterized compounds within GNPS spectral libraries with a cosine value of 0.7 or greater, signified by a red node border. The color of the node itself signifies chemical superclasses as annotated by ClassyFire.²⁴ Because of the small sample size, no compounds in this study were isolated. Instead, the relative abundance of the compounds in each dataset was approximated by the intensity of the precursor ion (MS1) in mass spectrometry for each dataset, shown by the relative size of each node in the MN.

FIG. 3.

Molecular network (MN) of the M. fistulosa flower extract, excluding single nodes for 150–450 m/z. The size of the node indicates the relative abundance of the precursor (MS1) ion. Nodes with red borders indicate spectral matches within the GNPS libraries. GNPS, Global Natural Product Social Molecular Networking.

FIG. 4.

Chromatograms (Supplementary Figs. S1 and Figs. S2) and tables of all library hits identified by GNPS for each dataset sorted by mass range, along with mirror matches for putatively identified compounds, can be found in the Supplementary Data S2 and S3.

DISCUSSION

M. fisulosa is widely used as a medicinal herb, so in this study, we sought to better characterize the anti-inflammatory activity and molecular composition of M. fistulosa flower extracts.

We determined that the M. fisulosa methanolic flower extract did not impact survival of the macrophages in our model. The extract did not have a strong influence on LPS-induced TNF-α cytokine production, but the M. fisulosa methanolic flower extract did cause a dose-dependent decrease in LPS-induced IL-6 production by RAW 264.7 macrophages, meaning that the extract does have an anti-inflammatory effect.

Based on this result, we sought to better understand the composition of the extract on a molecular level using mass spectrometric analysis using GNPS molecular networking. Using classical molecular networking, 183 compounds were able to be putatively identified as level 2 metabolomic identifications, which characterize analytes by match to a tandem MS library spectrum (for level 1 characterization, LC-MS comparison to an authentic standard is required).

Of the compounds identified using GNPS, most are phenylpropanoid derivatives, such as flavonoids and isoflavonoids, and their related glycosides, many of which have been seen in the oil distillate of this flower.^3,7 For example, the largest spectral families for both datasets (Figs. 5 and 6) include many flavonoid-like compounds. Other spectral families include compounds such as phosphocholines, lipids, and lipid-like molecules, and organic oxygen compounds (see Supplementary Figs. S3–S6 in the Supplementary Data S1). The six most abundant compounds in each data set (by the sum of the precursor MS1 ions) are given in Tables 1 and 2.

FIG. 5.

Largest spectral family of the 150–450 m/z dataset containing phenylpropanoid compounds. The size of each node indicates the relative abundance of the precursor (MS1) ion. Nodes with red borders indicate spectral matches within the GNPS libraries.

FIG. 6.

Largest spectral family of the 400–1200 m/z dataset containing phenylpropanoid compounds. The size of each node indicates the relative abundance of the precursor (MS1) ion. Nodes with red borders indicate spectral matches within the GNPS libraries.

Table 1.

Six Most Abundant Compounds in the M. fistulosa 150–450 m/z Dataset

Compound name	Chemical formula	Molecular weight (g/mol)	Cosine value
l-Tryptophan	C₁₁H₁₂N₂O₂	204.23	0.85
Isosakuranetin	C₁₆H₁₄O₅	286.27	0.84
Baicalin	C₂₁H₁₈O₁₁	446.36	0.92
Cyclopentaneacetic acid, 2-[(2Z)-5-(hexopyranosyloxy)-2-penten-1-yl]−3-oxo-, (1R,2R)-	C₁₈H₂₈O₉	388.17	0.73
(2R,3S,4S,5R,6S)-2-(hydroxymethyl)-6-(4-hydroxy-2-methyl-5-propan-2-ylphenoxy)oxane-3,4,5-triol	C₁₆H₂₄O₇	328.15	0.82
Isovitexin	C₂₁H₂₀O₁₀	432.38	0.8

Table 2.

Six Most Abundant Compounds in the M. fistulosa 400–1200 m/z Dataset

Compound name	Chemical formula	Molecular weight (g/mol)	Cosine value
Biochanin A 7-O-rutinoside	C₂₈H₃₂O₁₄	592.18	0.95
Apigenin + glucose/rhamnose disaccharide	C₂₇H₃₀O₁₄	578.16	0.94
5,7-dihydroxy-3-(4-hydroxyphenyl)-6,8-bis[3,4,5-trihydroxy-6-(hydroxymethyl)oxan-2-yl]chromen-4-one	C₂₇H₃₀O₁₅	594.16	0.86
Poncirin	C₂₈H₃₄O₁₄	594.47	0.87
5,7-dihydroxy-2-[4-[(2S,3R,4S,5S,6R)-3,4,5-trihydroxy-6-(hydroxymethyl)oxan-2-yl]oxyphenyl]-3-[(2S,3R,4S,5S,6R)-3,4,5-trihydroxy-6-[[(2R,3R,4R,5R,6S)-3,4,5-trihydroxy-6-methyloxan-2-yl]oxymethyl]oxan-2-yl]oxychromen-4-one	C₃₃H₄₀O₂₀	756.21	0.7
Kaempferol 3-glucuronide	C₂₁H₁₈O₁₂	462.08	0.83

Since the methanolic M. fistulosa extract did show an anti-inflammatory effect, it makes sense that many of the compounds found in the extract are molecules with known anti-inflammatory effects, such as flavonoids. Other plants that have been studied for their anti-inflammatory properties have also been found to contain flavonoids.²⁵ In this work, a prominent putatively identified flavonoid is biochanin A (BCA), an isoflavone commonly found in a wide variety of plants, in this case found as a rutinoside.²⁶ BCA has been studied for its anti-inflammatory properties and its effect on many different inflammatory-related diseases.²⁷ Wu et al. in 2014 characterized the anti-inflammatory role of BCA using murine microglial cells. In LPS-stimulated BV2 microglial cells treated with BCA, there was a significant decrease in both TNF-α and IL-1β levels in a dose-dependent manner.²⁸

Another prominent flavonoid emerging in the data was apigenin, appearing as apigenin glycosides. Apigenin is found in a wide variety of fruits and vegetables and has been reported to have anti-inflammatory responses on its own, as well as apigenin glycosides.^29

–32

Luteolin-7-O-glucoside, which has also been reported as a major component of M. fistulosa hydrodistillation extracts, was not identified in our analysis. However, luteolin-4′-O-glucoside was identified in both data sets (Figs. 5 and 6), though not as a major component. Luteolin-4’-O-glucoside has been shown to improve the symptoms of inflammation by decreasing the levels of IL-1β, TNF-α, and IL-6.^17,21,33

It should be noted that rosmarinic acid, a major component in M. fistulosa hydrodistillation extracts,³ was identified as a relatively minor component in our methanolic extract. Caffeic acid, another major constituent of the M. fistulosa hydrodistillation extract, was not identified in our sample. This is likely because rosmarinic and caffeic acids are carboxylic acids that do not ionize well in positive ion mode mass spectrometry. Organic acids are better suited for ionization in negative ion mode, which will be run in future experiments in the untargeted metabolomic analysis of M. fistulosa.

Together, these findings contribute to our understanding of the anti-inflammatory properties of M. fisulosa. Future work will investigate other methods of analyzing the MS data using additional options available on GNPS and obtaining negative ion mode mass spectral data for this plant species.

Footnotes

ACKNOWLEDGMENTS

Thanks you to Dr. Roland Kersten and Dr. Jenan Kharbush for data collection and their sage advice and thoughts about the MS/MS data and analysis. Special thanks to the following UMN Morris undergraduate students who contributed to this work: Amanda Hansmann, Mercede Hess, Kim Peters, Nina Valentini, Mackenzie Vorderbruggen, Ayla Wicklow, Sydney Swanson, and Esther Okorofor.

Authors’ Contributions

M.D.G.: Writing—original draft (supporting); investigation (supporting); formal analysis (supporting). S.M.P.: Conceptualization (equal); writing—review and editing (supporting). K.M.N.: Conceptualization (supporting), investigation (supporting); writing—review and editing (supporting). R.M.G.: Conceptualization (equal); writing—original draft (equal); formal analysis (equal); writing—review and editing (equal). B.P.N.: Formal analysis (equal); writing—original draft (equal); writing—review and editing (equal).

AUTHOR DISCLOSURE STATEMENT

The authors declare that no competing financial interests exist. K.M.N., S.M.P., and B.P.N. were affiliated with the University of Minnesota Morris when this research was initiated. K.M.N. is currently employed at Kimberly-Clark Inc., S.M.P. is a chemistry graduate student at the University of Montana, and B.P.N. is currently employed at Ripon College.

FUNDING INFORMATION

This work was supported by the University of Minnesota Undergraduate Research Opportunity Program and the Office of the Vice President for Research of the University of Minnesota (UMN Morris Faculty Enhancement Research Fund).

SUPPLEMENTARY MATERIAL

Supplementary Data S1

Supplementary Data S2

Supplementary Data S3

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. Naturally occurring small molecules with dual effect upon inflammatory signaling pathways and endoplasmic reticulum stress response. J Physiol Biochem, 2024; 80(2):421–437; doi: 10.1007/s13105-024-01014-1

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