Systems Biologymy Ppt

8/7/2019 Systems Biologymy Ppt

http://slidepdf.com/reader/full/systems-biologymy-ppt 1/29

Guide : Dr. Abhay Harsulkar By : Rashmi Godbole1sr yr M.Pharm

Department of Pharmaceutical Biotechnology

Poona College of Pharmacy- BVU





�

Many proteins control the activity of DNA itselfit can be visualizedto be a loop hich is highly robust

�Hence DNA or genes receive various stimuli and send

appropriate commands by coding for proteins so that the

various path ays, organelles, cell membrane etc functionnormally, for normal functioning of the hole cell

�DNA, the mastermind of the cell, transcribes mRNA hich are

translated into proteins

�Proteins ultimately carry out all the cells activities mentioned

above





�But this is not all..cells talk to each other

�Cells of same structure and function communicate or talk to

each other and function together to form a tissue

co

Cell-cell

c icati

thr gh

glyc r tei s

�A set of tissues in harmony makes

an organ

�Different organs functioning

together make an organism



�Unfortunately for nearly last 50 yrs biologists ent top-do n

Organism-cells-proteins-genes

They used the reducti ist approach to study the cell

�i.e. They studied the various components of the cell and their

function in isolation

�Ex. Studying the nucleus, sugar metabolism etc

�The reductionist approach has been extremely important to

develop a basic understanding of living systems

�Last 10 years has seen amazing development of high

throughput techniques for measurement of biomolecules

(nucleic acids, proteins, other metabolites) like microarrays, LC-

MS-MS



� Study of the DNA or entire Genome --GENOMICS

�Study of the Genes actually expressed --TRANSCRIPTOMICS

i.e. the mRNA produced

�Study of properties, localization, and

function of the Proteins made --PROTEIOMICS

�Study of the sugars made in a cell --GLYCOMICS

�The Metabolites produced and

path ays of energy production --METABOLOMICS

�Study of phenotypes --PHENOMICS

�The reductionist approach coupled ith high throughput

techniques has helped biologists delve deeper and a lot of

data is generated�This lead to development of independent desciplines like:



What is Systems Biology??

� But its high time today to put all the pieces together integrate the data

� Because in reality these components interact, or net ork toform a SYSTEM

�Systems biology is the study of an organism, vie ed as anintegrated a d interacting network of genes, proteins and biochemical reactions hich give rise to life

� It is holism or integration as opposed to reduction

� The biological system may be a metabolic path ay, cell

organelle, an entire cell , a set of cells, or in distant future anorganism in entirety

� All the relevant omics data for a system is integrated tounderstand the system on a whole



Components of Systems Biology

BIOLOGICAL

SYSTEM

Genome

mRNA

expression

profileProteins

expressed

Protein

localization

Molecular

dynamics

Metabolites

Transcri tomeProteiome

Metabolome



Approach or Paradigm

Defining system structure:� Identification of components of the system

� Define the regulatory net orks of genes, the protein interactions,biochemical path ays

� Basically interaction bet een components is defined roughly

� Done by using high throughput techniques like yeast t o-hybridassays, co-immunoprecipitation

Analyzing systems behavior:

� Environmental or genetic perturbations are used

� Environmental perturbations like say lo glucose levels, change inion concentration

� Genetic perturbations like knocking out a gene, mutating aparticular receptor etc.



�

Perturbation analysis�Experimental data after perturbations is collected

�Gene expression is analyzed using microarrays, protein

production using protein chips, structure and folding of

proteins using modelling soft ares,

�Metabolites analyzed using LC-MS etc

Modelling�All this data is then integrated by using mathematical

modelling,

�Ex cellular net orks can be converted to mechanistic

models using chemical kinetics , control theory etc

�Follo ed by computational modelling to produce a

biological system model





Data

Integration



Model simulation�Simulation is mimicking or imitation of some real thing or

process�Simulation is the use of a model to develop conclusions that

provide insight on the behavior of any real orld elements

�Computer simulation uses same concept but requires that the

model be created through programming on a computer

�

It is the process of defining, creating and studying a model iththe intentions of dra ing inferences and conclusions as to the

behavior of the actual systems

�Simulation includes not only model development but also

experimenting ith the model to predict



�Ultimately e obtain a predictive model of the biological

system

�We can play ith

these models for

�Hence systems biology is an inter-

disciplinary science to understand biology

hich is today a set of systems



History and development

� Term was coined in 96 s,

owever t eoretical people

and experimental iologists

diverged

� enaissance in 99 s� Since t en iology is

ecoming cross-disciplinary,

information ased, ig

t ro g p t�T e f t re of iology is

systems iology a predictive

science



1

2

3

45

7 8

�After computer simulation , the model is validated

�The biological system is no better understood



�Ne hypothesis are put forth

�Ne experiments are designed

�

More data is generated hich isno added to the previous model

to lead to model refinement

�Thus systems biology is an

iterative process of laboratory

ex erimental observations and

computational modeling

of the system

�

The result of this process is an optimised mathematical modeldescribing the behaviour of a given biological system in a defined

environment.

�This thus facilitates predictions about the behaviour under the

influence of internal and external factors.



More on Modeling and Simulation

� Starting point for mathematical modeling is

quantification of omics data

�A computer simulation of a model typecreates sampling of representative outcomes

or sequences of events for an input



�Biological systems are stochastic i.e random, in behavior

non-deterministic

�Biological systems dont do differential equations

� Hence Stochastic algorithms like the gillespie

algorithms (a Monte Carlo type) are used

� Simulation systems are based on solving ordinary

differential equations, partial differential equations orstochastic differential equations



Tools of Systems biology

� Genomics data- by High Throughput-DNA sequencing

Systems biology got a boost after the completion of the human genome project

Since then gene sequencingtechniques have evolved

Today faster and more efficient

systems like second generation

sequencing are available

Ex. SOLID



�Transcriptomics- Gene/Transcript measurement, SAGE,

Gene Chips, cDNA microarrays

� Proteomics- MS, 2D-PAGE, protein chips, Yeast-2-

hybrid, X-ray, NMR

�

Metabolomics -NMR, LC-MS-MS, X-ray, capillaryelectrophoresis

�Mutation detection- SNP methods



mRNA profilling using cDNA microarray and Gene Chip technology



Proteiomics data�Commonly analyzed using 2D gel electrophoresis- complex protein

mixtures are resolved by isoelectric point and then on size using

polyacrylamide gel



�The spots on 2D gels can be analyzed using MS, MALDI-TOF

�Complex protein

samples are analyzed

using LC-MS-MS

�Metabolites up to even

nanogram quantity are

separated and detectedusing LC-MS-MS



�Protein-protein and protein small molecule interactions are

studied using yeast t o hybrid screening, co- immunoprecipitation,

spotted protein arrays

Protein chips



Transcriptional net orks



Applications



Thank you

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Systems Biologymy Ppt