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Chinmedomics strategy for discovery of effective constituents from traditional herbal medicine
Satyender KumarDepartment of Natural Products
The World Health Organization (WHO) has recently defined traditional medicine (including herbal drugs) as comprising therapeutic practices that have been in existence, often for hundreds of years, before the development and spread of modern medicine and are still in use today.
Traditional Herbal Medicine (THM)
Current Science, Vol. 78, No. 1, 10 January 2000
Herbs
•Crude plant material such as leaves, flowers, fruit, seed, stems,
wood, bark, roots, rhizomes or other plant parts, which may be
entire, fragmented or powdered.
Herbal materials
•Fresh juices, gums, fixed oils, essential oils, resins and
dry powders of herbs.
Herbal preparations
•Powdered herbal materials, or extracts, tinctures and
fatty oils of herbal materials.
Finished herbal
products
•Finished herbal products and mixture herbal products may
contain excipients in addition to the active ingredients, finished
products or mixture products to which chemically defined active
substances have been added.
Herbal medicine
The earliest recorded evidence of their use in Indian, Chinese, Egyptian, Greek,
Roman and Syrian texts dates back to about 5000 years.
Herbal medicines (HM) have been widely used for their antibacterial, antifungal,
anticancer, antiviral, and anti-inflammatory activities, and other pharmacological
activities.
Traditional Chinese medicine (TCM) has its own unique medical system with the
significant characteristics of pursuing an overall therapeutic effect with a multi-
target treatment.
It consists of multiple plants (called ‘formulae or prescription’) that could regulate
balance and homeostasis of the body in a holistic fashion.
Why herbal medicine?
Current Science, Vol. 78, No. 1, 10 January 2000
HM are not pure products with a single active ingredient. Therefore, conventional
methods for screening and identifying the active ingredients in natural products
are time-consuming and labour intensive.
Traditional natural product discovery, using conventional methods, affords no
information about mode of action until late in the discovery process. This leads to
high rates of rediscovery and low probabilities of finding compounds with unique
biological properties.
Need some update in herbal medicine?
Currently, HM development has been hampered due to the lack of high
throughput, rapid methods for screening and identifying bioactive constituents.
Therefore, it is essential to develop a method able to overcome these
limitations.
OMICS A Journal of Integrative Biology Volume 16, Numbers 7 and 8, 2012
Syndrome Formulae Effectiveness of Herbal medicine
Components of TCM
•TCM is so complicated that it’s almost impossible to explore the molecular mechanism and
effective substances thoroughly.
•Moreover, compounds in TCM exert therapeutic effects in combination rather than as
individuals.
TCM treatment with therapeutic strategies in holistic fashion is focuses on the
patient rather than disease, promoting enhancing the quality of life.
From the point of modern system medicine, TCM syndrome is a functional state
that caused by the body’s metabolic imbalances.
Syndrome is a basic description of the disease in TCM, due to lack of objective
criteria for syndrome diagnostics, and thus it is difficult to properly evaluate the
efficacy of formulae.
TCM Syndrome
Current Science, Vol. 78, No. 1, 10 January 2000
Cinmediformulae
Cinmediformulae
Formulae include four elements:
the monarch (which plays the most
important role in the formulae),
the minister (which increases the
effectiveness of the monarch herb),
the assistant (which helps the monarch and minister herbs reach their target positions)
the servant (which can reduce the adverse effects and/or increase
the potency of the whole formulae)
Cinmediformulae
• Practitioners often prescribe a combination of herbs called formulae based on
an over-all symptoms and signs of syndrome, and work together harmoniously
to achieve ideally therapeutic effects.
• Single herb already contains thousands of compounds, formulae consisting of
multi-herb has become the chemical composition giant system.
• That means to say, the efficacy of TCM depends on the combined action of
multiple herbs because it usually contains a lot of ingredients and exert
synergistic therapeutic efficacies.
• However, this can cause many difficulties in the search for the effective
substances of TCM.
Difficulties of TCM
Lack of a comprehensive
understanding of the relationship
between syndrome and formulae,
For TCM to be modernized, it is
critical to use modern tools to
determine the mechanism of action
of TCM.
Process and leads to low
probabilities of finding compounds
with unique biological properties.
New tools and methods help revive ancient traditional Chinese medicine
A new platform, termed chinmedomics which is capable of directly
discover the bioactive constituents from herbal medicine.
It is base upon an analyzing the correlation between the endogenous
biomarker of diseases or TCM syndrome and exogenous constituents to
find the highly associated constituents with efficacy of formulae as the
effective substances.
Further clarifying the activities of effective substances, and may discover
lead compounds and make the innovative drug discovery based on clinical
experiences. It will significantly advance the drug discovery from
traditional medicine.
Key points in Chinmedomics
Serum Pharmacoche
mistry of TCM (SPT)
• providing methodology for the discovery of
active constituents in vivo from TCM, solving
the efficacy and effectiveness of TCM
Metabolomics technology
• is used to clarify the molecular mechanisms of
syndrome.
Screening of active
constituents
• using the plotting of correlation between
(endogenous) marker metabolites and
(exogenous) serum constituents, and is ongoing
verification by further biological experiments.
Correlation analysis
•between the exogenous compounds in vivo after oral
formulae and endogenous marker metabolites in vivo
are used to clarify the effective substances and their
synergistic properties.
After being metabolized by the liver and gastrointestinal tract, the components
that finally reach the blood are usually not the original ingredients, and there are
also some metabolism ingredients.
The blood contained, ingredients may be the substances playing a direct role in the
body.
Research on the components in the serum could be an effective approach to
identify the effective substances of TCM.
To resolve these problems, in early 1990s, we firstly established the SPT that can
reflect drug action, absorption, distribution and interaction in the body.
Serum pharmacochemistry of TCM
Metabolomics and related metabonomics approach is a specific ‘top-down’
systems biology manifestation of metabolic profiling of small-molecule metabolites
have an important role in biological systems
Metabolomics can capture information with regard to mechanisms of disease and
drug action.
Samples of interest (e.g., plasma, urine, cerebral spinal fluid, or tissue biopsies) are
collected. Blood samples are the most commonly collected biological fluid,
providing a representation of the global metabolome.
Metabolomics: an overview
such as lipids, amino acids, peptides, nucleic acids, and organic acids, vitamins,
thiols, carbohydrates, etc, and represent attractive candidates to understand
disease phenotypes.
Figure: The overall procedure of chinmedomics analysis. Chinmedomics technology consists of three sequential steps: (1) an experimental technique, based on MS or NMR spectroscopy, designed to profile endogenous low-weight metabolites, (2) multivariate data analysis using bioinformatics techniques, and (3) metabolites identification and quantification resulting in biomarkers (UPLC-ESI-MS, ultra-performance liquid chromatography/electrospray ionization/mass spectrometry; TIC, total ion chromatogram).
Metabolomics: an overview
Potential biomarkers which are very useful for diagnosing and monitoring disease
progress, were extracted from loading-plots constructed following the PLS-DA
(Partial Least Square- Data Analysis), and biomarkers were chosen based on their
contribution to the variation and correlation within the data set.
Figerprinting of biomarkers from urine sample
Figure: Typical metabolomics experiment flow diagram. Samples are analysed by full scan profile to collect all metabolites. Pattern recognition approach aims to highlight underlying trends. Receiver operating characteristic curves are generally considered the method of choice for evaluating the performance of potential biomarkers. The markers are eventually placed in metabolic pathway to provide insight on the biochemical phenomena.
Case study
Case study
SQW was selected for the bioactive constituents analysis in the treatment of SYX by using
chinmedomics strategy.
Shan Qi Wan (SQW) is a typical TCM formula consisting of Radix rahmanniae preparata, Fructus
macrocarpii, Rhizoma dioscoreae, Rhizoma zlismatis, Poaria, Cortex moutan radicis, Radix aconiti
lateralis preparata and Rahmulus cinnamomi was selected.
These 23 metabolites were found involved in multiple biochemical processes such as: energy
metabolism, lipid metabolism and amino acid metabolism
23 endogenous urinary metabolites of rat perturbed after treatment of hydrocortisone were measured
by using metabolomics
Shen Yang Xu (SYX, Kidney-yang deficiency syndrome) was produced by high doses of Hydrocortisone
Experimental work
1. Preparation of SQW samples
2. Animal handling
3. Sample collection and preparation
4. Metabolomics study
a. UPLC analysis
b. MS analysis
c. Metabolic analysis
5. Constituent analysis
6. Correlation analysis of marker metabolites and absorbed constituents
7. Potential target prediction of highly correlated ingredients
SQW powder was dissolved in distilled water to form a stock solution (0.3389 g/ml).
The freeze-dried powder was dissolved in water to make 1.08 g/ml solutions.
then ground, mixed and reflux extracted in a rotary evaporator with six times of 100%
methanol for 2 hr. Then the filtrate was freeze dried.
Shan Qi Wan (SQW) is a typical TCM formula consisting of Radix rahmanniae preparata,
Fructus macrocarpii, Rhizoma dioscoreae, Rhizoma zlismatis, Poaria, Cortex moutan radicis,
Radix aconiti lateralis preparata and Rahmulus cinnamomi in proportion of (8: 4: 4: 3: 3: 3: 1:
1)
1. Preparation of SQW samples
Male Wistar rats (200-249 g)
• Conditions: 21 ± 5 C with 60 ± 5% relative humidity, 12 h light-dark cycle ⁰withstandard diet and water.
• Dose: 1 ml/100 g body mass of SQW solution (0.3389 g/ml).
Groups: (15 rats in each group)
• Control group (olive oil injected i.p. for 21 consecutive days)
• Model group (corticosterone injected i.p. at 10 mg/kg for 21 consecutive days
• SQW group (corticosterone injected i.p. at 10 mg/kg for 21 consecutive days +
after that an accurate volume of SQW for consecutive 15 days)
2. Animal handling
The mixture solution was filtered through a 0.22 mm PTFE membrane and
transferred to vials for UPLC/MS analysis.
Supernatants were dried under nitrogen and redissolved with 80% methanol to
volumes of 200 µl.
After vortexing for 10 s, supernatants (800 µl) were collected after centrifugation
13,000 rpm for 10 minutes.
The supernatant was collected and stored at -80 C before analysis.⁰
Serum and plasma were separated by centrifugation at 4000 rpm for 10 minutes at 4
C after standing for 30 minutes.⁰
Blood was collected from abdominal aorta
3. Sample collection and preparation
Metabolite analysisMS data acquired were performed to Markerlynx within
Masslynx software (version 4.1) for detection and alignment.
The multivariate data matrix was input to Ezinfo Ver. 2.0 software for Principal component analysis (PCA), Partial least
square discriminant analysis (PLS-DA) and orthogonal projection to latent structures (OPLS) analysis.
MS analysis
Mass spectrometer was connected to UPLC system via an electrospray ionization (ESI) interface.
UPLC analysis
HSS T3 column was used Acetonitrile with 0.1% formic acid and water with 0.1% formic acid at flow rate 0.4 ml/min and injection volume was 3 µl.
4. Metabolomics study
Correlation analysis of marker metabolites and
absorbed constituents• A plot of correlation between marker metabolites and chemical composition was
used to screen the constituents or metabolites absorbed in to blood after oral
administration.
Potential target prediction of highly correlated
ingredients• The target numbers were entered into the KEGG database (
http://www.genome.jp/kegg/) to annotate and analysis the pathway.
Results
Figure: Base peak ion chromatograms of plasma samples in UPLC/QTOF MS analysed by MarkerLynx software
(A) control group
(B) model group
(C) SQW group
% Intensity
Time
Base peak intensity (BPI) chromatgrams of biosamples
(A), Score plots of PCA based on serum metabolite profiling
Multivariate data analyses of the UPLC/MS serum spectra data of control and model group
Control group Model group
(B), The S-plot of PLS-DA for the control and model groups.
Multivariate data analyses of the UPLC/MS serum spectra data of control and model group
Relative signal intensities of serum metabolites identified by UPLC/MS
The 3-d PCA plot for SQW treatment on SYX (control group; ■, model group; , SQW group)
Control group Model group SQW treated group
ESI base peak ion chromatogram of the SQW analysed by UPLC/QTOF MS in negative ion mode (A) and positive ion mode (B).
Base peak intensity (BPI) chromatgrams of biosamples
Extracted ions chromatogram of rat serum after oral administration of SQW with Metabolynx™ in negative ion mode (A) and positive ion mode (B). The peak numbers are
listed in Table S4 and S5.
Extracted ions chromatogram
Correlation between marker metabolites and serum constituents in SQW. The correlation coefficients are listed in Table S6.
Highly positively correlatedhighly negatively correlatedlow correlation
left column: chemical components top column: marker metabolites
Highly positively correlatedhighly negatively correlatedlow correlation
Overview of chinmedomics
A schematic diagram of the Chinmedomics-based investigation into the molecular mechanisms and effective substances of syndrome and formulae by integratingSerum Pharmacochemistry of TCM and metabolomics analysis.
Conclusion
• 23 biomarkers were identified for KYX syndrome and out of these 5 were up-regulated and 18
were down regulated.
• 84 compounds were identified or tentatively characterized from the constituents of SQW and
out of 84 compounds 51 were found in positive ion mode and 33 were found in negative ion
mode.
• The extracted ions cromatogram of plasma samples with the MetabolynxTM were separated
using UPLC method.
• 20 compounds out of absorbed constituents of SQW were highly correlated with the effect of
SQW.
Thank You for your time today!
Questions?
Theory of yin-yang
Initially, yin and yang refer to the light and darkness of the sunlight, anything that is exposed to the sun belongs to yang, and that is unexposed to the sun belongs to yin.
Some examples for Yin-yang properties of things
• Yang----Heaven, big, sun, day, fire, upward, active, male, Spring and Summer, warm, bright, function, et. al.
• Yin----Earth, small, moon, night, water, downward, still, female, Autumn and Winter, cold, dim, material et. al.
In medical field
Any materials and functions which have the feature of promoting,
warming or exciting
Any materials and functions which have the feature of coagulating,
moistening and inhibiting
Yang
Yin
Relativity of yin and yang
e.g. Human body viscera
Yang back fu organs
Yin Chest and abdomen zang organs
Application of theory of yin and yang in TCM
(1) To explain morphology and structure of the human body
e.g. chest and abdomen, lower part, yin meridians, blood……. back, upper part, yang meridians, qi……
(2) To explain physiological functions of the human body
e.g. Yin qi
Yang qi
Application of theory of yin and yang in TCM
preponderance of yin or yang
decline of yin or yang
simultaneous of yin and yang
inter-transformation and repelling of yin and yang
(3) To explain pathological changes of the human body
Application of theory of yin and yang in TCM
(4) To guide clinical diagnosis
It is to differentiate yin or yang properties of a certain syndrome
(5) To treat diseases
e.g. To determine the therapeutic
principles
To generalize properties and actions of Chinese drugs
Reducing excess
Supplementing insufficiency
UPLC-HDMS chromatograms of SQW in negative ion mode. The peak numbers are listed in Table S2. (A), in vitro; (B), dosed serum; (C), control serum.
UPLC-HDMS chromatograms of SQW in positive ion mode. The peak numbers are listed in Table S2. (A), in vitro; (B), dosed serum; (C), control serum.
