Explains the systems biology approach (holistic approach), its advantages and tools used compared to the reductionist approach in natural products research.

1. A
Systems Biology
Approach to
Natural Products
Research
A
Systems Biology
Approach to
Natural Products
Research
P l a n t B i o t e c h n o l o g y 2 0 th
A p r i l 2 0 1 5
Ritesh Bhagea, Rouksaar Buctowar, Christabelle Cécile, Keshavi Ghoorbin, Huda Nazeer

2. Contents
● Introduction
● Overview
● Reductionist Approach
● Holistic Approach
● What is Systems Biology?
○ Advantages of Systems Biology
● Tools of Holistic Approach - Systems Biology
○ Proteomics, Transcriptomics and Metabolomics
● Conclusion
● References
2

3. Introduction
● Medicine is the most important health care; to cure diseases (antibiotics),
relieve symptoms (analgesics), for preventive measures (antihypertensive
drugs) or for the substitution of endogenous compounds (insulin).
● Many modern drugs have been developed thanks to traditional medicines
with receptors and mechanisms of action.
● These consequently lead to the screening for novel bioactive compounds,
and the design and synthesis of similar structures.
● Nevertheless, with the advent of technology, society moved from broad
screening and testing on humans towards molecular-level of screening
(Holistic approach -> reductionist approach)
3

4. Overview
4

5. Reductionist approach
An approach to understanding the nature of complex things by reducing to a
simpler level - Introduced by Descartes in Part V of his “Discourses” of 1637.
Also known to be the basis for many of the well-developed areas of modern
science, including physics, chemistry and cell biology.
5

6. Holistic approach
A way to analyze all components
and interactions within and among
organisms unlike the reductionist
approach.
The collective data gives a broad
picture how:
● an organism operates
● affects systems
● other biological processes
respond to an organism
Better understanding and
interpretation of data, thereby
making more accurate predictions
about the human immune system’s
response.
Approach can be done in two
different ways,
● via clinical trials
● systems biology
● (or both)
6

7. Systems Biology - What is it?
“Systems biology is an approach in biomedical research to understanding the
larger picture - be it at the level of the organism, tissue, or cell - by putting its
pieces together. It is in stark contrast to decades of reductionist biology,
which involves taking the pieces apart.” (NIH, 2015)
Measurements
Genetic level: genome,
transcriptome, proteome,
metabolome
Physiological level: pulse,
blood pressure, pain, fever
“Systems biology aims at understanding
biological complexity by unbiased
measurements of as many as possible
parameters without having any hypothesis.”
(Verpoorte et al., 2006)
7

8. Systems Biology - What is it?
● It thus explains the biological
phenomenon, not on a gene basis,
but through the interaction of all
cellular and biochemical
components in a cell or an
organism.
● It identifies the elements (genes,
molecules, cells), ascertains their
relationships and involves new
dynamic computer modeling
programs which integrate the info
and allow to simulate entire
organisms based on their biological
components.
The Systems Biology Triangle
8

9. The different levels of measurement in a
systems approach
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10. Advantages of the Systems Biology Approach
● Decrease development time of drugs by half.
● Decrease the cost of development by 70%.
○ Can further reduce costs if coupled with traditional medicines.
10

11. Tools of Holistic approach
● The present-day reductionist approach for drug development is not
sufficient to prove efficacy of natural products (medicinal plants).
● Thus, Holistic approaches are employed because:
○ Activity might be due to pro-drugs which are activated upon
administration of the medicine,
○ To synergy among compounds.
● Important tools of Holistic approaches:
1. Transcriptomics
2. Proteomics
3. Metabolomics
11

12. 1. Transcriptomics in Systems Biology
● The genome is a store of biological
information.
● Biochemical reactions involving enzymes
and proteins w.r.t the genome is genome
expression.
● Transcriptome is the initial product of
genome expression.
● It is a collection of RNA molecules derived
from protein-coding genes in a cell at a
point in time.
● Transcriptomes are maintained by
transcription.
● Transcriptomes are then translated into
proteomes. 12

13. 1. Transcriptomics in Systems Biology
● Transcriptomics aims to comprehensively profile all information that
appears in the RNA pool within a system.
● Cellular functions are mediated by mRNA via gene expression.
● RNA profiling provides clues to:
○ Expressed sequences and genes of a sequence.
○ Gene regulation and regulatory sequences.
○ Function and interactions between genes.
○ Functional differences between tissues and cell types.
○ Identification of candidate genes for any given disease.
● There are various types of RNA molecules:
○ rRNA, snoRNA, tRNA, snRNA, miRNA
13

14. 1. Transcriptomics in Systems Biology
● There are also non-coding RNA molecules, with activities like:
○ Binding to target sequence by base pairing,
○ Functioning as an enzyme by folding on itself,
○ Binding to protein and modulating its activity.
● Every cell in an organism is, at any given time point, transcribing thousands
of its genes in various quantities.
● Both from basic science and clinical perspectives, it is vital to accurately
quantify the levels of different transcripts and identify the proteins they
code for.
● Various methods are available for quantification and analysis of messenger
RNA levels:
○ Gene by gene methods
○ Global methods
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15. 1. Transcriptomics in Systems Biology
Gene by gene method:
● Northern blot
● qRT-PCR
Global methods:
● Expressed sequence tag (EST) sequencing - generates random, 200-900
bp single-pass sequences of cDNA clones.
● Serial analysis of gene expression (SAGE) - was the first approach to
provide large-scale absolute estimates of transcript frequencies. Tags are
sequenced using standard sequencing technology to derive a digital
representation of the transcript frequencies.
● Cap analysis of gene expression (CAP) - uses 5’ cap-trapping methods to
selectively isolate full-length cDNAs and generates 20-bp tags from these.
Tags are cloned in vectors and sequenced.
15

16. 1. Transcriptomics in Systems Biology
● Massive parallel signature sequencing (MPSS). 3’ sequences of each
transcript are isolated using biotinylated primer in the cDNA synthesis. 3’
signature sequences are ligated into specifically designed plasmid vectors
and amplified using PCR . Tags coupled with microbeads, for mapping
and sequencing.
● Gene identification signature (GIS)- relies on sequencing of
concatenated 3’ and 5’ paired-end ditags.
Mostly applied technology in transcriptomics is the use of Microarrays.
● Microarrays are used to measure levels
of mRNA transcripts, miRNAs, and proteins
but also to analyse characteristics of genomes.
● Fundamental underlying advantage is analysis
of all known protein-coding transcripts.
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17. Applications of transcriptomics
● Microarray platforms are used for genome-wide analysis of expression
changes in diverse experiments investigating mechanisms of neural injury
and repair (Neurosciences).
● Toxicogenomics determines global transcriptomic responses to chemical
exposures and can predict their effects. (E.g: aquatic toxicology)
● Information on how individual cells respond to signals and other
environmental cues at critical stages of cell-fate determination.
● Assess the gene regulatory network -physiological functions, behavior
and phenotype during development in multicellular organisms.
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18. Applications of transcriptomics
● Plant extracts have been used as flavour, fragrances and medicines for
millennia, which are complex molecules and are difficult to produce
synthetically. Much interest is given to natural products.
○ Research was carried out on Salvia plant for aromatic and
pharmacological attributes and is known for tanshinone synthesis.
○ Sequence analysis were carried out before and after hairy root
cultures were established. Combined metabolomic and
transcriptomic approach towards elucidating tanshinone synthesis
was used.
○ Data has revealed a distinct expression pattern correlated with
tanshinone production, providing a firm foundation for further
investigation of the biosynthesis of these medically important
natural products.
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19. 2. Proteomics in Systems Biology
● Proteomics aims to detect and quantify a system’s entire protein content,
hence understanding the expression and function of proteins on a global
level (Weston and Hood, 2004).
● More than simply cataloguing the proteome-a quantitative assessment of
the full complement of proteins within a cells the field of proteomics strives
to characterize:
- protein structure and function - enzyme-substrate interactions
- protein-protein - post-translational modifications
- protein-nucleic acid - protein processing and folding
- protein-lipid - protein turnover and synthesis rates
- cellular and subcellular localization - Protein activation
Current Proteomic Technologies:
● high-resolution, two-dimensional electrophoresis (2DE)
● stable isotope tagging
19

20. 2. Proteomics in Systems Biology
● Detection of known nonribosomal peptide synthetases /polyketide
synthases systems in members of the genera Bacillus and Streptomyces
which are known to synthesize natural products with antibiotic,
anticancer and antifungal properties (Bumpus et al., 2009)
20

21. 3. Metabolomics in Systems Biology
● Metabolomics is the study of
global metabolite profiles in a
system (cell, tissue or organism)
under a given set of condition.
● Integration of genomics,
proteomics, transcriptomics and
metabolomics is a goal of systems
biology.
21

22. Techniques used in metabolomics
MS
NMRGC
Microarray
Optical spectroscopy
Fourier transformed infrared spectroscopy
22

23. Main applications of metabolomics
● Drug assessment
● Clinical toxicology
● Nutrigenomics
● Functional genomics
23

24. Application of metabolomics
Metabolomics for natural products research
● The use of metabolomic approach, with appropriate statistical analysis,
allows rapid analysis of these complex data.
○ E.g., NMR clustering techniques have also been used to cluster the
spectra of crude plant extracts to determine the biochemical
mechanism of action for herbicides (Rochfort, 2005).
■ In this study, 27 herbicidal compounds with 19 different MOAs
were applied to plants for 24h before an aqueous extract of the
plant was taken.
■ Artificial neural network analysis was employed to analyse the
NMR spectroscopic data of these extracts.
24

25. Application of metabolomics
■ Treated samples were easily
distinguished from untreated
samples and with the use of
an appropriate training set,
many different MOAs were
distinguished for the
commercially available
compounds tested.
■ This approach has been recently
demonstrated for a herbal medicine.
● A medicinal herb extract
(Anoectochilus formosanus: a popular
folk medicine with anticancer activity)
was compared to a single compound
drug in MCF-17 cells by metabolomic
and transcriptomic analysis, and a
similar level of gene expression
regulation was observed in both,
suggesting a similar MOA.
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26. Conclusion
For phytochemist and pharmacognosist, metabolomics and systems biology
are great opportunities as they have all the knowledge for analysis of natural
products.
These approaches could be associated with chemometrics and bioinformatics
to make a major contribution in the research of medicinal plants.
“To waste, to destroy, our natural resources, to skin and exhaust the land;
instead of using it so as to increase its usefulness, will result in undermining in
the days of our children, the very prosperity we ought by right to hand down
to them amplified and developed.”
-Theodore Roosevelt
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27. References
Bumpus, S.B., Evans, B.S., Thomas, P.M., Ntai, I. and Kelleher, N.L. (2009). A
Proteomics Approach to Discovery of Natural Products and Their Biosynthetic
Pathways., Nat Biotechnol, 27(10), pp 951–956.
Fang, F.C. and Casadevall, A. (2011). Reductionistic and Holistic Science. Infect.
Immun. 79 (4), pp. 1401-1404.
Gao, W., Sun, H.-X., Xiao, H., Cui, G., Hillwig, M. L. and Jackson, A. (2014). Combining
metabolomics and transcriptomics to characterize tanshinone biosynthesis in Salvia miltiorrhiza.
BMC Genomics 15(1), 73.
Munro, K. M. and Perreau, V. M. (2009). Current and Future Applications of
Transcriptomics for Discovery in CNS Disease and Injury. Neurosignals 17(4), 311–327.
Rochfort, S. (2005). Metabolomics reviewed: A new “ omics” platform technology for systems biology
and implications for natural products research. J. Nat.Prod, 68, pp 1813-1820.
Sumner, L.W., Mendes, P. and Dixon R.A. (2003). Plant metabolomics: large-scale
phytochemistry in the functional genomics era. Phytochemistry ,62, pp 817–836.
Tang, F., Lao, K. and Surani, M. A. (2011). Development and applications of single-cell transcriptome
analysis. Nature Methods.
Verpoorte, R., Choi, Y.H. and Kim, H.K. (2005). Ethnopharmacology and systems
biology: A perfect holistic match. Journal of Ethnopharmacology, 100, pp 53-56.
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28. Verpoorte, R., Choi, Y.H. and Kim, H.K. (2006). Plants as source of medicine: new
perspectives. In: Medicinal and Aromatic plants - Agricultural, Commercial,
Ecological, Legal, Pharmacological and Social aspects. Eds: Bogers, R.J. Cracker,
L.E. and Lange, D. Springer, Dordrecht, pp 261.
Wang, M., Lamers, R.J.A.N., Korthout, H.A.A.J., Nesselrooij, J.H.J.V., Witkamp, R.F.,
Heijden, R., Voshol, P.J., Havekes, L.M., Verpoorte, R. and Greefan, J.V. (2005).
Metabolomics in the Context of Systems Biology: Bridging Traditional Chinese
Medicine and Molecular Pharmacology. Phytother. Res., 19, pp 173–182.
Wei Chen. (2013). Transcriptome profiling--Past, Present and Future. Berlin Institute for Medical
Systems Biology. Max-Delbrueck-Center for Molecular Medicine
Weston, A.D. and Hood, L. (2004). Systems Biology, Proteomics, and the Future of
Health Care: Toward Predictive, Preventative, and Personalized Medicine.
Journal of Proteome Research, 3, pp 179-196.
Wirta, V. (2006). Mining the transcriptome - methods and applications. School of Biotechnology, Royal
Institute of Technology, Stockholm.
References
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