Systems biology(integrative biology)

Systems biology is the study of an organism, viewed as an integrated and interacting network of genes, proteins and biochemical reactions which give rise to life.o (Institute of Systems Biology).

Ultimate goal:to predict de novo biological outcomes given  the  list  of  components  involved. (Genome Institute of Singapore).

Systemic perturbation of biological system

Monitoring the pathway responses

Integration of the data

Formulation of mathematical models that

describe the structure of the system &

its response to pertubations.

Systems biology : a network of disciplines

System biology view

Figure from Oltvai , Z.N. and Barabasi Life's complexity pyramid.

Interactions between various levelsof biological organization

(from Noble 2008)

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Concepts in systems biology• System• Systems thinking• Complexity theory• Nonlinear dynamics• Feedback control• Robustness• Emergent properties• Network

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• Network analysis I. Network architecture (topology): 1. Microscale 2. Mesoscale 3. Macroscale II. Network dynamics• Network topology• Pathway• Pathway modularity• Pathway analysis

A FRAMEWORK FOR SYSTEMS BIOLOGY

Define all of the components of the system.

Systematically perturb and monitor the components.

Reconcile the experimentally observed responses with those predicted by the model.

Design and perform new perturbation experiments to distinguish between multiple or competing model hypotheses.

After choosing the set of new perturbations, repeat steps 2 through 4 and iterate.

Structure of systems : Networks

APPROACHES:1.Bottom up approach

•tries to construct a gene regulatory network based on the compilation of independent experimental data2.Top down approach

•tries to make use of high throughput data

SYSTEM BIOLOGY USES VARIOUS OMIC TECHNOLOGIES TO STUDY

AT DIFFERENT LEVELS

GENOMICS• The branch of molecular biology concerned with the

structure, function, evolution, and mapping of genomes i.e.study of genome.

• GENOME : the collection of genes contained within a complete (haploid) set of chromosomes. The genome is a static information resource with a defined gene content.

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Overview of microarray hybridization.

DNA SEQUENCINGCommonly used methods :• Chain termination method

• Maxam and gilberts sequencing method

Chain termination method

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In this process ,four reactin mixtures are set up; each one including:1.DNA to be sequenced 2.DNA polymerase3.A supply of nucleotides(A,G,C,T)

4.A small amount of labelled chain terminating nucleotide :one in each of reaction mixture.

.

DNA polymerase synthesise the DNA but incorporation of terminating nucleotide cause polymerization t

o stop.

Ending chain at every possible nucleotide position creates a no. of DNA terminated at same nucleotide but different

positions(shown for 1 reaction mixture)

Visualization on gel (from smallest to largest)

If different fluorescent labels are used sequencing can be done in a single mixture

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Maxam gilbert method

Pyrosequencing

Proteomics

The term proteomics describes the study and characterization of complete set of proteins present in a cell, organ, or organism at a given time .

Two-Dimensional Gel Electrophoresis

Mass spectrometry (MS)• Mass spectrometry (MS) is used to determine

the accurate masses of molecules.• Mass spectrometry (MS) is an extremely

valuable analytical technique in which the molecules in a test sample are converted to

gaseous ions that are subsequently separated in a mass spectrometer according to their

mass-to-charge (m/z) ratio and detected.

Components of a mass spectrometer

MS/MS Overview

MS/MS Overview

MALDI-TOF mass spectrometry

MALDI ionisation mechanism

Principle of time-of-flight (TOF)

Common proteomic technologies, applications & limitations

Human Genomics and Proteomics Volume 2009, Article ID 239204

Phage display library

Systems Biology vs. traditional cell and molecular biology

• Experimental techniques in systems biology are high throughput;but Intensive computation is involved from the start in systems biology, in order to organize the data into usable computable databases.

• Exploration in traditional biology proceeds by successive cycles of hypothesis formation and testing; data accumulates during these cycles;while Systems biology initially gathers data without prior hypothesis formation; hypothesis formation and testing comes during post-experiment data analysis and modeling.

APPLICATIONS

Understanding environment•Understanding microbes interaction with ecosystems• Explain and predict consequences of complex phenomena such as climate changes•Recombine various mechanisms within these diverse organisms to deal with some extraordinary human problems

APPLICATIONS IN FIELD OF MEDICINE

• In DRUG DISCOVERY• Understanding complex situations such

as cancer• Understanding developmental

neurotoxicology

CHALLENGES1.MODELLING CHALLENGES

• Providing the means for checking the constraints and devising modeling schemes with sound compositional mechanisms; and

• managing models that may not be consistent with each other, either across schemes or across scales

2.CHALLENGES IN PROTEOMICS • Membrane Proteome• Serum Proteomics and Biomarker

Discovery

3.CHALLENGES IN HANDLING LARGE AMOUNT OF DATA GENERATED AND COMBINING THEM TO CREATE NETWORKS

4.SOME TIMES HYPOTHETICAL NETWORKS GET CREATED