Dairy Biotechnology

Lesson 28. METABOLOMICS, STRUCTURAL BIOLOGY, NUTRIGENOMICS AND PHARMACOGENOMICS

Module 6. Bioinformatics and 'Omics' revolution

Lesson 28
METABOLOMICS, STRUCTURAL BIOLOGY, NUTRIGENOMICS AND PHARMACOGENOMICS

28.1 Introduction

Metabolomics is the comprehensive quantitative analysis of all the metabolites of an organism or specified biological sample. On the other hand, Metabonomics is the quantitative measurement of the multiparametric time related metabolic responses of a complex (multicellular) system to a patho-physiological intervention or genetic modification. Thus, where metabolomics means the global analysis of all metabolites in a sample, metabonomics is the analysis of metabolic responses to drugs or diseases. Several factors affect metabolic profile such as diet and lifestyle, environment and genetics as well as pharmaceutical effects. The metabolome is a direct reflection of the physiological status of a cell and unlike transcriptomics or proteomics studies, which only reveal part of what might be happening in a cell, metabolomics can give us an instantaneous picture of the entire physiology of the cell. The science of metabolomics can help us in generating metabolic signatures, monitor enzyme kinetics/pathways, measure metabolite flux, identify phenotypes, monitor gene/environment interactions and identify functions of unknown genes.

The measurement of such a large number of metabolites requires advanced methodologies which include nuclear magnetic resonance (NMR), functional magnetic resonance imaging (MRI) and high performance liquid chromatography (HPLC), and handling of a large amount of mathematical data which require advanced Bio-informatics tools. Mass spectrometry (MS) is used for measuring compounds with molecular weight of 70-500 Da. However, it can not distinguish compounds with similar molecular weights. Hence it needs to be combined with other techniques such as liquid chromatography (LC) and gaschromatography (GC), denoted as LC/MS and GC/MS. Analysis of data thus obtained requires sophisticated tools of information technology (IT). Recently, capillary electrophoresis (CE) which combines MS, known as CE/MS has been found suitable for obtaining the metabolome. One of the application of studying metabolome is that of normal versus diseased cells and their modulation by drugs or nutrients.

The Human Metabolome Database (HMDB) is a freely available electronic database containing detailed information about small molecule metabolites found in the human body. It is intended to be used for applications in metabolomics, clinical chemistry and biomarker discovery.

28.1.1 Samples

The clinical samples for analysis include biofluids such as urine, blood (plasma and serum), saliva, bile, cerebrospinal, digestive, seminal, amniotic etc. and also cells, their supernatants, tissue extracts and biopsies.

28.1.2 Tools

The techniques to be used include:
Mass Spectrometry (MS),
Gas chromatography (GC),
High Pressure Liquid Chromatography (HPLC),
Ultra Performance Liquid Chromatography (UPLC),
Nuclear Magnetic Resonance (NMR),
Capillary Electrophoresis (CE)‏
Flux analysis,
Fourier transform ion cyclotron mass spectrometers (FT-ICR-MS).

28.1.3 Applications

1. Metabolomics offer the direct measure of physiological activity, hence can be used for biomarker discovery, drug discovery, physiological exploration, diet and disease.
2. Metabolomics have tremendous applications in food as well as in livestock sector to find how various feeding strategies like concentrates affect the development of epithelial tissue from young calves during weaning.
3. Nutritionists can determine physiological response of nutrients. Metabolomic assays can be used to measure small molecule biomarkers of oxidative stress, redox potential, anti-oxidant activity, inflammation and cardiovascular disease risk.

28.2 Structural Biology

Structural biology is a branch of molecular biology, biochemistry and biophysics concerned with the molecular structure and shape of biological macromolecules particularly proteins and nucleic acids to find what causes these molecules to acquire the structures they have, and how alterations in their structures can affect the biological function. The typical three dimensional structure of macromoleules (proteins) is very important for their physiological functions. With the help of structural biology, we can understand how a macromolecule, a complex of macromolecules, or a cellular sub-section functions through elucidation of its three-dimensional structure. The field of Structural Biology was essentially born when the DNA Double Helix structure was discovered by Watson and Crick in 1953 whereby the structure of the DNA was linked to the way DNA is replicated and transcribed in the cell. The first and foremost thing a structural biologist needs to know is the systematic experimental determination of many more three dimensional structures of biological macromolecules and complexes of macromolecules (such as proteins, DNA, RNA, carbohydrates or lipids). Determination of structures will form the basis of our understanding the relationships between primary structures and the tertiary structures of biologically active macromolecules and, even more so, the quaternary structures of the multi-subunit complexes which mediate most biological activities. Next is the methods that the structural biologists require to determine the structures of macromolecules which generally include X ray Crystallography (crystal of chymosin shown in Fig. 28.1), Nuclear Magnetic Resonance (NMR), Electron Microscopy/Tomography and Circular Dichroism (CD) which have expanded the repertoire and capabilities of macromolecular imaging to unprecedented levels. With contributions from mass-spectrometry and high-resolution fluorescence microscopy, structural biology has grown to a powerful methodological arsenal for the study of macromolecules regardless of their size and complexity. Using X ray crystallography, several structures e.g. lactoferrin, lysozyme, hemoglobin etc. have been elucidated as shown in Fig. 28.2. The most important role is played by Bioinformatics. Three dimensional structures can also be determined using in silico methods.

Fig. 28.1 Crystal of buffalo chymosin

Sheep lactoferrin

Buffalo Mammary gland lysozyme

Haemoglobin

Fig. 28.2 Predicted structure of few proteins

Structural biologists compare the structure of proteins by superimposing them i.e. they use web server called ‘Superpose’ wherein the proteins structures are uploaded and compared. Fig. 28.3 shows the superimposition of buffalo and bovine chymosin. Since, structural biology plays a major role in the understanding of biological processes at the molecular level, there has been a continuing demand for faster and more cost-effective determination of protein structures and their in-depth functional, mechanistic and biological analysis. Detailed structural descriptions using structural biology can provide a better understanding of the basis by which different proteins achieve selectivity and specific binding to their cognate ligands and drugs. Several drugs have been developed using structure-based methods which target several of the diseases particularly AIDS, leukaemia and cancers.

Fig. 28.3 Superimposition of buffalo and bovine chymosin structures

28.2.1 Tools

These methods include

• X ray crystallography
• NMR
• Electron Microscopy
• Single molecule scattering
• Circular Dichroism (CD)
• Cryo-electron microscopy (cryo-EM)
• Multiangle light scattering
• Ultra fast laser spectroscopy
• Dual polarization interferometry
• Bioinformatics - Protein structures can be viewed at
Jmol

– http://jmol.sourceforge.net
PyMOL
– http://pymol.sourceforge.net
Swiss PDB viewer
– http://www.expasy.ch/spdbv
Mage/KiNG
– http://kinemage.biochem.duke.edu/software/mage.php
– http://kinemage.biochem.duke.edu/software/king.php
Rasmol
– http://www.umass.edu/microbio/rasmol/

Structures can be predicted using threading. 3D threading servers predict the structure or gives models based on input sequence :

• PredictProtein-PHDacc

o http://www.predictprotein.org

• PredAcc

o http://mobyle.rpbs.univ-paris-diderot.fr/cgi-bin/portal.py?form=PredAcc

• Loopp (version 2)

o http://cbsuapps.tc.cornell.edu/loopp.aspx

• Phyre

o http://www.sbg.bio.ic.ac.uk/~phyre/

• SwissModel

– http://swissmodel.expasy.org/

28.2.2 Applications

1. Based on structure predictions and spatial organization, improved biomolecules with the desired properties can be designed.
2. Structural biology has an important role to play in drug discovery.
3. Knowledge about three dimensional structural analysis of biomolecules can help in rational designing of molecules with certain desirable properties e.g. proteins with increased temperature and pH stability (protein engineering), or small molecules that inhibit or activate certain biological processes (drug design).

28.3 Nutrigenomics

Nutrigenomics is the study of the influence of foods and their constituents on gene expression profile of individuals using high-throughput genomic tools (Fig 28.4). It can also be defined as the use of genomic analysis to investigate diet-gene interactions that impact human health and disease. Several such definitions for nutrigenomics exist. Nutrigenomics make use of all the post genomic tools such as genomics, transcriptomics, proteomics, metabolomics, metabonomics, interactomics etc. Nutrigenomics helps us in understanding how our body responds to food components using ‘System Biology’. These ‘omics’ technologies use the information from genomics and study the effect of dietary constituents and their influence on proteins and metabolites produced in our body. The two terms nutrigenomics and nutrigenetics are commonly used and are distinguished by defining them as - nutrigenomics is the identification of genes involved in physiological responses to diet and the genes in which small changes, called polymorphisms, might have significant impact on nutritional consequences. On the other hand, Nutrigenetics is the study of these individual genetic variations or polymorphisms, their interaction with nutritional factors, and linkage with health and disease. Basically, nutrigenomics explore how nutrients in foods interact with genes which will provide an understanding of how diet and genes interact. This information will help us to better manage our own health and possibly prevent, mitigate and delay the onset of chronic and age related diseases. Today’s life style diseases like obesity, diabetes and cardiovascular diseases are all related to diet and such diseases can be very well managed by following nutrigenomic approach. The concept of linkage between diet and health is an ancient one. In 400 B.C. Hippocrates said “let food by thy medicine and medicine by thy food”. Nutrigenomics will lead to evidence-based dietary intervention strategies for restoring health besides preventing diet-related diseases. Nutrigenomics is like a personalized medicine which means personalized dietary regimen to follow healthy life style.

Fig. 28.4 Nutrigenomics

Nutrigenomic studies demonstrate that diets have variable effects on individuals which depend on the genetic makeup of the individual. Identification of DNA variants that contribute towards diet related disease risk is important in order to understand the causes of diseases in humans. The Human Variome project (www.humanvariomeproject.org) is an international effort to identify genes, their mutations and variants associated with disease risk. The genes examined in most of the studies are generally those that have been previously identified as genetically or biochemically involved in altering either an intermediate risk factor or the chronic disease itself. One example is the thymidine variant instead of cytosine at position 677 (C677T) in the methylenetetrahydrofolate reductase (MTHFR) gene, which is associated with neural tube defects in women with low intakes of dietary folate in certain populations. Women with TT allele are more prone to neural tube defect. The nutrients from foods can be investigated as modulators of gene expression rather than as simple nutrients for providing basic nutrition e.g. the addition of folate in the diet of a pregnant women alters gene expression in a positive way. Genistein, an isoflavone from soybeans has been shown to possess anti-cancer potential and is a good supplement for prevention of cancer.

Gene expression can be affected by nutrient – gene interaction that involves transcriptional factors. These transcriptional factors bind to response element sequences to initiate transcription. Nutrients bind to transcription factors to modulate gene expression. The positive effect of omega – 3 fatty acids has been shown to affect lipid profile since it binds to PPAR receptors to initiate transcription of genes for fatty acid oxidation.

Diagnostics, preventive lifestyle guidelines, more efficacious dietary recommendations, health-promoting food supplements, and drugs are some of the anticipated end-products of nutrigenomics research. It has been found from the outcome of several investigations that the same dietary factors are responsible for causing disease in a person who had a genetic predisposition to that particular disease, but not in others with a different genetics. The individual’s response to a food or nutrient could be traced to differences in metabolic handling of a dietary component, involving complex interactions between genotypes, metabolic phenotypes, other dietary factors, lifestyle and environmental factors. This led to the concept of developing personal diets for individuals. As a result of emerging high through put techniques associated with Human Genome Project, tools have become available which could lead to a deeper understanding of interactions among food, genes, protein structure, post-translational changes in protein structure and consequent effects on metabolism.

28.3.1 Tools

1. Microarrays - powerful tool for studying functions of food and nutrients
2. Bioinformatics tools

28.3.2 Applications

Nutrigenomics will have a significant impact on the field of dietetics and personalized diet to prevent disease risk.

28.4 Pharmacogenomics

Pharamcogenomics is the study of how variations in the human genome affect the response to various drugs (Fig. 28.5). The older term "pharmacogenetics" was created from the words “pharmacology” and "genetics" to indicate the intersection of pharmaceuticals and genetics. With the availability of human genome sequence and the introduction of new technologies particularly ‘omics’ have made it possible to analyze multiple genes simultaneously, rather than one at a time. The recently coined term "pharmacogenomics" describes genomewide approaches.The two terms ‘pharmacogenomics’ and ‘pharmacogenetics’ tend to be used interchangeably. Pharmacogenomics is the whole genome application of pharmacogenetics which examine single gene interaction with drugs. Pharmacokinetics is the study of uptake, conversion and breakdown of drugs in the body over time. Pharmacodynamics deals with the influence of genes on the interactions between drugs and their molecular targets. Pharmacists may use a patient's genetic profile to select the most appropriate drug for the treatment or prevention of a disease to which the patient is genetically predisposed. An individual's genetic profile may also be used to choose a medication with minimal side effects. One drug may work for one person and may not work for another. It is all due to genetic blueprint which is unique for every person and hence the concept of personalized medicine. Pharmacogenomics is closely linked to nutrigenomics as in both cases effect of drug or a nutrient is investigated on genome profile of an individual i.e. how genetic variations influence the responses to these chemicals. Although, a person’s response to medication may be influenced by environment, age, diet, lifestyle, and health status, the major factor is the genetic make up. Hence, a person’s genetic make up can help in designing of a personalized drug with greater efficacy and safety.

In vitro model systems i.e. cell lines from large numbers of individuals represent an attractive and cost-effective approach to identify genes associated with variations in drug response by the application of genome-wide techniques and these laboratory based results are validated by translation in clinical trials.

One of the key emerging areas in today’s ‘omic’ era for personalized medicine is to test the patients prior to prescribing a particular drug therapy in order to determine their ability to metabolize different classes of drugs. Pharmacogenomics is being used in some of the cases like cytochrome P450 (CYP) family of liver enzymes and TPMT (thiopurine methyltransferase). The patients are screened for TPMT deficiency and to look for variations in cytochrome P450 genes. TPMT is responsible for breakdown of drug thiopurine used for leukaemia and when not broken down, increases to toxic levels. Another example is cystic fibrosis patients. There are several such examples in which patient’s genetic profile is very useful in prescribing a particular drug. One of the most important area is the tumor therapy. Looking at the molecular differences between several tumors, initial drug treatment could be improved significantly.

Pharmacogenomic test results sometimes are difficult to interpret since enzymes involved in drug metabolism arise from multiple genes which is a complex process. The results are predictions based on information about the specific gene variants, associated diseases, adverse drug reactions, and patient outcomes.

28.4.1 Tools

• Sequencing
• Next generation sequencing technologies
• RFLP (Restriction Fragment length Polymorphism)
• Common genotypic methods
• Single nucleotide polymorphisms (SNPs)
• Real Time PCR (TaqMan)
• DNA Microarray for expression studies
• Denaturing high-performance liquid chromatography (DHPLC) - uses a reverse-phase ion-pair column to discriminate between variant and non-variant alleles.
• Mass spectrometry differentiates DNA molecules using a defined mass
• Bioinformatic tools

28.4.2 Applications

1. Pharmacogenomics will determine the most effective treatment for patients prior to drug prescription.
2. Pharmacogenomics will help in drug discovery that is targeted towards a specific disease. Pharmaceutical companies will be able to discover potential therapies more easily using genome targets.
3. It will help the Doctors to prescribe the drug after looking at the person’s genetic profile which will make the recovery faster and minimize the adverse effects.
4. Pharmacogenomics can be used for all critical illnesses like cancer, diabetes, CVD, obesity, tuberculosis etc.

References

Internet resources