SlideShare une entreprise Scribd logo
1  sur  42
Télécharger pour lire hors ligne
SYLICA 'Omic Technologies – Bowater Feb 2013
SYLICA 2013
Bowater lectures
Using ‘Omic Technologies to
Investigate Gene Function
Bowater Lectures in Brno, Feb. 2013
4 lectures on linked topics will be delivered during the
coming week:
• Contemporary DNA Sequencing Technologies –
26/2/2013 @ 10:00
• Using ‘Omic Technologies to Investigate Gene
Function – 26/2/2013 @ 14:00
• Biophysical Methods to Study Molecular Interactions
– 27/2/2013 @ 10:00
• Synthetic Biology & Nanotechnology: Tomorrow’s
Molecular Biology? – 28/2/2013 @ 10:00
SYLICA 'Omic Technologies – Bowater Feb 2013
Genomics, ‘Omics & Technology
• Molecular biology: major scientific discipline for
past ~50 years
• Genomics = “analysis of genomes”: became
important science during 1990’s
• Analyses of various other biological molecules have
developed into their own scientific disciplines; e.g.
Metabolomics = “analysis of metabolites”, etc.
• Transcriptomics/Proteomics: developed during past
10-15 years
• Bioinformatics: has developed as major branch of
science - enables efficient analysis of data from
“omics” experiments
SYLICA 'Omic Technologies – Bowater Feb 2013
Genomics & Technology
• Significance of “omics” coincides with dramatic
improvements in different technologies:
molecular biology: increased range of
approaches for purification and manipulation of
proteins and nucleic acids
computers: required for gathering and analysis
of data
internet: allows data to be shared, quickly and
easily
• All developments have increased speed and cost-
effectiveness - available to much wider audience
SYLICA 'Omic Technologies – Bowater Feb 2013
Transcriptomes
• Genome: all of hereditary information encoded in
the DNA (or RNA)
• Transcriptome: set of all mRNAs ("transcripts”)
produced from a genome
• Term can be applied to:
complete set of transcripts for a given organism
specific subset of transcripts present in a
particular cell type or under specific growth
conditions
• Transcriptome varies because it reflects genes that
are actively expressed at any given time
SYLICA 'Omic Technologies – Bowater Feb 2013
DNA Microarrays Show
Differences in Gene Expression
• Microarray chips contain fragments from genes in
the group to be analyzed
– Full genome of bacteria or yeast, or protein
families from larger genomes
• mRNA or cDNA from different samples are
differentially tagged
• Analysis on the same chip shows differences
SYLICA 'Omic Technologies – Bowater Feb 2013
Transcriptomics
• Transcriptomics uses high-
throughput techniques
based on DNA microarrays
• For further details about
microarrays see Lucchini et
al., Microbiology, 147, 1403-
1414 (2001)
Nelson & Cox, “Lehninger, Principles of
Biochemistry”, 4th edn, 2004, p. 328
SYLICA 'Omic Technologies – Bowater Feb 2013
Transcriptomics
Nelson & Cox, “Lehninger, Principles of
Biochemistry”, 4th edn, 2004, p. 328
SYLICA 'Omic Technologies – Bowater Feb 2013
Nelson & Cox, “Lehninger, Principles of
Biochemistry”, 4th edn, 2004, p. 328
SYLICA 'Omic Technologies – Bowater Feb 2013
Transcriptomics
Nelson & Cox, “Lehninger, Principles of
Biochemistry”, 4th edn, 2004, p. 328
SYLICA 'Omic Technologies – Bowater Feb 2013
Transcriptomics
Nelson & Cox, “Lehninger, Principles of
Biochemistry”, 4th edn, 2004, p. 328
SYLICA 'Omic Technologies – Bowater Feb 2013
Transcriptomics
Nelson & Cox, “Lehninger, Principles of
Biochemistry”, 4th edn, 2004, p. 328
SYLICA 'Omic Technologies – Bowater Feb 2013
Transcriptomics
Nelson & Cox, “Lehninger, Principles of
Biochemistry”, 4th edn, 2004, p. 328
•Experiments performed
under different
conditions
•Determines effect of
conditions on
expression
•Produces huge amount
of data
•Lots of repeats required
- expensive
SYLICA 'Omic Technologies – Bowater Feb 2013
Transcriptomics
Polymerase Chain Reaction (PCR)
• Used to amplify DNA in the test tube
– Can amplify regions of interest (genes) within DNA
– Can amplify complete circular plasmids
• Mix together
– Target DNA
– Primers (oligonucleotides complementary to target)
– Nucleotides: dATP, dCTP, dGTP, dTTP
– Thermostable DNA polymerase
• Place the mixture into thermocycler
– Melt DNA at ~95°C
– Cool to ~ 50–60°C, primers anneal to target
– Polymerase extends primers in 5’3’ direction
– After a round of elongation is done, repeat steps
SYLICA 'Omic Technologies – Bowater Feb 2013
General Steps of PCR
SYLICA 'Omic Technologies – Bowater Feb 2013
•Repeat steps 1–3 many times:
General Steps of PCR
SYLICA 'Omic Technologies – Bowater Feb 2013
Photolitographic Synthesis of DNA
SYLICA 'Omic Technologies – Bowater Feb 2013
DNA Microarrays: Applications
DNA microarrays allow simultaneous screening of
many thousands of genes: high-throughput screening
• Genome-wide genotyping
– Which genes are present in this individual?
• Tissue-specific gene expression
– Which genes are used to make proteins?
• Mutational analysis
– Which genes have been mutated?
SYLICA 'Omic Technologies – Bowater Feb 2013
Adaptations to PCR
• Reverse Transcriptase PCR (RT-PCR)
– Used to amplify RNA sequences
– First step uses reverse transcriptase to convert
RNA to DNA
• Quantitative PCR (Q-PCR)
– Used to show quantitative differences in gene
levels
SYLICA 'Omic Technologies – Bowater Feb 2013
qPCR
SYLICA 'Omic Technologies – Bowater Feb 2013
Proteomes
• Proteome: set of all proteins produced under a given
set of conditions
• Term can be applied to:
complete set of proteins for a given organism
specific subset of proteins present in a particular
cell type or under specific growth conditions
• Proteome varies because it reflects genes that are
actively expressed at any given time
• Proteomics analyses many samples using 2D-
electrophoresis and mass spectrometry
• High-throughput, but less than transcriptomics
SYLICA 'Omic Technologies – Bowater Feb 2013
Gel Electrophoresis
• Electrophoresis separates molecules by size
• Resolution is limited
Berg, Tymoczko & Stryer, “Biochemistry”,
6th edn, 2006, p. 71
SYLICA 'Omic Technologies – Bowater Feb 2013
Isoelectric Focusing
• Electrophoresis across a pH gradient
• Proteins migrate to their isoelectric pH
Berg, Tymoczko & Stryer, “Biochemistry”,
6th edn, 2006, p. 73
SYLICA 'Omic Technologies – Bowater Feb 2013
Two-dimensional Gel
Electrophoresis
• Protein sample
initially fractionated
in one dimension by
isoelectric focusing
• SDS-PAGE
performed
perpendicular to
original direction
• Separates proteins
according to pI and
mass Berg, Tymoczko & Stryer, “Biochemistry”,
6th edn, 2006, p. 74
SYLICA 'Omic Technologies – Bowater Feb 2013
• Proteins from E.
coli separated by
2D-electrophoresis
• >1,000 proteins
can be resolved
Berg, Tymoczko & Stryer, “Biochemistry”,
6th edn, 2006, p. 74
SYLICA 'Omic Technologies – Bowater Feb 2013
Two-dimensional Gel
Electrophoresis
Mass Spectrometry
• MALDI-TOF mass spectrometry
• Protein sample is ionized and exposed to electrical field
• Ions travel according to size
Berg, Tymoczko & Stryer, “Biochemistry”,
6th edn, 2006, p. 94
SYLICA 'Omic Technologies – Bowater Feb 2013
MALDI-TOF Mass Spectrum
• MALDI-TOF gives good estimates of molecular weights
• Can be used to identify a few proteins within a mixture
Berg, Tymoczko & Stryer, “Biochemistry”,
6th edn, 2006, p. 94
SYLICA 'Omic Technologies – Bowater Feb 2013
Proteomic Analysis by Mass
Spectrometry
• Proteins separated by 2D
electrophoresis
• Single proteins eluted
• Digestion with trypsin
will give fragments with
unique set of sizes
• Sizes identified by mass
spectrometry and
matched to database
• Allows identification of
unknown proteins Berg, Tymoczko & Stryer, “Biochemistry”,
6th edn, 2006, p. 95
SYLICA 'Omic Technologies – Bowater Feb 2013
Transcriptomics v Proteomics
• Transcriptomics and proteomics are both very
powerful
• Differences in their practical application:
Transcriptomics is robust, relatively cost-effective
and user-friendly
Proteomics still relatively limited – problems can
remain with purification and stability of proteins
• Increasing potential to combine and compare data
sets - for discussion see Hegde et al., Curr. Opin.
Biotech., 14, 647-651 (2003)
SYLICA 'Omic Technologies – Bowater Feb 2013
Bioinformatics:
Mining the Data
SYLICA 'Omic Technologies – Bowater Feb 2013
Bioinformatics & Databases
 Latest biological data is gathered, organised and
disseminated through large databases
 Databases include:
- EBI, NCBI, Pfam, SMART, SWISS-PROT, TAIR
 Information in bioinformatic databases:
- sequences, structures, homology searches
 Fast search engines allow searches by all with
internet access – databases are as useful as the
results they help generate!
 Improved tools for analysis of sequences
SYLICA 'Omic Technologies – Bowater Feb 2013
Databases – Some URLs
Resource URL
European Bioinformatics
Institute
GenBank
NCBI
Protein DataBank
Sanger Centre
SMART
The Arabidopsis
Information Resource
(TAIR)
www.ebi.ac.uk/
www.ncbi.nlm.nih.gov/Genbank/
www.ncbi.nlm.nih.gov/
http://www.rcsb.org/pdb/home/home.do
www.sanger.ac.uk/
smart.embl-heidelberg.de
www.arabidopsis.org/
SYLICA 'Omic Technologies – Bowater Feb 2013
NCBI: Complete Genomes
SYLICA 'Omic Technologies – Bowater Feb 2013
NCBI: Eukaryotic Genomes
SYLICA 'Omic Technologies – Bowater Feb 2013
NCBI: Eukaryotic Genomes
SYLICA 'Omic Technologies – Bowater Feb 2013
NCBI: Microbial Genomes
SYLICA 'Omic Technologies – Bowater Feb 2013
NCBI: Microbial Genomes
SYLICA 'Omic Technologies – Bowater Feb 2013
Databases - The Caveats
 Databases contain mistakes (low as a proportion of
total data)
- primary data errors
- data analysis errors
- annotation errors
 Errors are difficult to correct
 Make the interpretation of data your own
responsibility!!
SYLICA 'Omic Technologies – Bowater Feb 2013
NCBI – Useful Links
Links to brief description of all
resources at NCBI
SYLICA 'Omic Technologies – Bowater Feb 2013
PubMed: retrieval system
containing citations,
abstracts, and indexing terms
for journal articles in the
biomedical sciences
NCBI – Useful Links
BLAST: BLAST® (Basic Local
Alignment Search Tool) is a
set of similarity search
programs
All resources:
provides integrated
access to nucleotide
and protein
sequence data from
>100,000 organisms
Genetics & Medicine:
continuously updated
catalogues of human
genes and genetic
disorders
Domains & Structure:
NCBI Structure Group,
including tools to search
and display structures
Taxonomy: general
information about
taxonomy
SYLICA 'Omic Technologies – Bowater Feb 2013
Databases Summary
•Many databases are available
- some have lot of general information (NCBI, EBI)
- some have specific data (Pfam, SWISS-PROT)
- some relate to specific research interests (TAIR)
•Become well acquainted with specific databases
•Wide range of databases, web sites and other resources
are available for in silico analysis of biological data
•Great advantages, but beware caveats and potential
pitfalls – understand capabilities and limitations!
•Use information intelligently:
- always ask if the conclusions make biological sense
- may require further analyses or experimentation
SYLICA 'Omic Technologies – Bowater Feb 2013
“Omics” Overview
• Analyses of various biological molecules have
developed into their own scientific disciplines; e.g.
Metabolomics = “analysis of metabolites”, etc.
• Transcriptome: set of all mRNAs ("transcripts”)
produced from a genome
• Proteome: set of all proteins produced under a given
set of conditions
• Both can vary because they reflect genes that are
actively expressed at any given time
• Transcriptomics and proteomics are both powerful,
but are used differently: transcriptomics is cheaper
and more user friendly than proteomics
SYLICA 'Omic Technologies – Bowater Feb 2013

Contenu connexe

Similaire à Brno_2013_Omic_technologies (1).ppt

Molecular pathology in microbiology and metagenomics
Molecular pathology in microbiology and metagenomicsMolecular pathology in microbiology and metagenomics
Molecular pathology in microbiology and metagenomicsCharithRanatunga
 
Primary and secondary database
Primary and secondary databasePrimary and secondary database
Primary and secondary databaseKAUSHAL SAHU
 
Biochip (Bioinformatics & Biotechnology)
Biochip  (Bioinformatics & Biotechnology)Biochip  (Bioinformatics & Biotechnology)
Biochip (Bioinformatics & Biotechnology)Sijo A
 
Techniques used for separation in proteomics
Techniques used for separation in proteomicsTechniques used for separation in proteomics
Techniques used for separation in proteomicsNilesh Chandra
 
Reconstructing paleoenvironments using metagenomics
Reconstructing paleoenvironments using metagenomicsReconstructing paleoenvironments using metagenomics
Reconstructing paleoenvironments using metagenomicsRutger Vos
 
Next Generation Sequencing - An Overview
Next Generation Sequencing - An OverviewNext Generation Sequencing - An Overview
Next Generation Sequencing - An OverviewEdizonJambormias2
 
Bioinformatics n bio-bio-1_uoda_workshop_4_july_2013_v1.0
Bioinformatics n bio-bio-1_uoda_workshop_4_july_2013_v1.0Bioinformatics n bio-bio-1_uoda_workshop_4_july_2013_v1.0
Bioinformatics n bio-bio-1_uoda_workshop_4_july_2013_v1.0Fokhruz Zaman
 
AMIA Webinar - BioSharing - Mapping the landscape of standards in the life sc...
AMIA Webinar - BioSharing - Mapping the landscape of standards in the life sc...AMIA Webinar - BioSharing - Mapping the landscape of standards in the life sc...
AMIA Webinar - BioSharing - Mapping the landscape of standards in the life sc...Peter McQuilton
 
What can you learn from molecular modeling?
What can you learn from molecular modeling?What can you learn from molecular modeling?
What can you learn from molecular modeling?digitalbio
 
Bioinformatics (Exam point of view)
Bioinformatics (Exam point of view)Bioinformatics (Exam point of view)
Bioinformatics (Exam point of view)Sijo A
 
Whole Cell Bioluminescent Bacterial Biosensors
Whole Cell Bioluminescent Bacterial BiosensorsWhole Cell Bioluminescent Bacterial Biosensors
Whole Cell Bioluminescent Bacterial BiosensorsJennifer Lyons
 
What should Bioinformatics do for EvoDevo?
What should Bioinformatics do for EvoDevo?What should Bioinformatics do for EvoDevo?
What should Bioinformatics do for EvoDevo?ylog
 
B.pharmacy notes of pharmaceutical nanotechnology
B.pharmacy notes of pharmaceutical nanotechnologyB.pharmacy notes of pharmaceutical nanotechnology
B.pharmacy notes of pharmaceutical nanotechnologyGulviShivaji
 
Proteomics.pptx1
Proteomics.pptx1Proteomics.pptx1
Proteomics.pptx1hanifalpha
 
Reverse-and forward-engineering specificity of carbohydrate-processing enzymes
Reverse-and forward-engineering specificity of carbohydrate-processing enzymesReverse-and forward-engineering specificity of carbohydrate-processing enzymes
Reverse-and forward-engineering specificity of carbohydrate-processing enzymesLeighton Pritchard
 
Nowomics at Cambridge Open Research
Nowomics at Cambridge Open ResearchNowomics at Cambridge Open Research
Nowomics at Cambridge Open ResearchNowomics
 

Similaire à Brno_2013_Omic_technologies (1).ppt (20)

ngs.pptx
ngs.pptxngs.pptx
ngs.pptx
 
Molecular pathology in microbiology and metagenomics
Molecular pathology in microbiology and metagenomicsMolecular pathology in microbiology and metagenomics
Molecular pathology in microbiology and metagenomics
 
Primary and secondary database
Primary and secondary databasePrimary and secondary database
Primary and secondary database
 
Biochip (Bioinformatics & Biotechnology)
Biochip  (Bioinformatics & Biotechnology)Biochip  (Bioinformatics & Biotechnology)
Biochip (Bioinformatics & Biotechnology)
 
Genomics types
Genomics typesGenomics types
Genomics types
 
Techniques used for separation in proteomics
Techniques used for separation in proteomicsTechniques used for separation in proteomics
Techniques used for separation in proteomics
 
Reconstructing paleoenvironments using metagenomics
Reconstructing paleoenvironments using metagenomicsReconstructing paleoenvironments using metagenomics
Reconstructing paleoenvironments using metagenomics
 
Ijetr021102
Ijetr021102Ijetr021102
Ijetr021102
 
Ijetr021102
Ijetr021102Ijetr021102
Ijetr021102
 
Next Generation Sequencing - An Overview
Next Generation Sequencing - An OverviewNext Generation Sequencing - An Overview
Next Generation Sequencing - An Overview
 
Bioinformatics n bio-bio-1_uoda_workshop_4_july_2013_v1.0
Bioinformatics n bio-bio-1_uoda_workshop_4_july_2013_v1.0Bioinformatics n bio-bio-1_uoda_workshop_4_july_2013_v1.0
Bioinformatics n bio-bio-1_uoda_workshop_4_july_2013_v1.0
 
AMIA Webinar - BioSharing - Mapping the landscape of standards in the life sc...
AMIA Webinar - BioSharing - Mapping the landscape of standards in the life sc...AMIA Webinar - BioSharing - Mapping the landscape of standards in the life sc...
AMIA Webinar - BioSharing - Mapping the landscape of standards in the life sc...
 
What can you learn from molecular modeling?
What can you learn from molecular modeling?What can you learn from molecular modeling?
What can you learn from molecular modeling?
 
Bioinformatics (Exam point of view)
Bioinformatics (Exam point of view)Bioinformatics (Exam point of view)
Bioinformatics (Exam point of view)
 
Whole Cell Bioluminescent Bacterial Biosensors
Whole Cell Bioluminescent Bacterial BiosensorsWhole Cell Bioluminescent Bacterial Biosensors
Whole Cell Bioluminescent Bacterial Biosensors
 
What should Bioinformatics do for EvoDevo?
What should Bioinformatics do for EvoDevo?What should Bioinformatics do for EvoDevo?
What should Bioinformatics do for EvoDevo?
 
B.pharmacy notes of pharmaceutical nanotechnology
B.pharmacy notes of pharmaceutical nanotechnologyB.pharmacy notes of pharmaceutical nanotechnology
B.pharmacy notes of pharmaceutical nanotechnology
 
Proteomics.pptx1
Proteomics.pptx1Proteomics.pptx1
Proteomics.pptx1
 
Reverse-and forward-engineering specificity of carbohydrate-processing enzymes
Reverse-and forward-engineering specificity of carbohydrate-processing enzymesReverse-and forward-engineering specificity of carbohydrate-processing enzymes
Reverse-and forward-engineering specificity of carbohydrate-processing enzymes
 
Nowomics at Cambridge Open Research
Nowomics at Cambridge Open ResearchNowomics at Cambridge Open Research
Nowomics at Cambridge Open Research
 

Plus de DESMONDEZIEKE1

GUT MICROBIOME IMPACT ON HUMAN GASTROINTESTINAL TRACT
GUT MICROBIOME IMPACT ON   HUMAN GASTROINTESTINAL TRACTGUT MICROBIOME IMPACT ON   HUMAN GASTROINTESTINAL TRACT
GUT MICROBIOME IMPACT ON HUMAN GASTROINTESTINAL TRACTDESMONDEZIEKE1
 
bioluminescence-130423221826-phpapp02.pptx
bioluminescence-130423221826-phpapp02.pptxbioluminescence-130423221826-phpapp02.pptx
bioluminescence-130423221826-phpapp02.pptxDESMONDEZIEKE1
 
presentation1-090331081630-phpapp01 (2).pptx
presentation1-090331081630-phpapp01 (2).pptxpresentation1-090331081630-phpapp01 (2).pptx
presentation1-090331081630-phpapp01 (2).pptxDESMONDEZIEKE1
 
GK12-Fifth-BioluminescencePPT.ppt
GK12-Fifth-BioluminescencePPT.pptGK12-Fifth-BioluminescencePPT.ppt
GK12-Fifth-BioluminescencePPT.pptDESMONDEZIEKE1
 
bioluminescencezas.ppt
bioluminescencezas.pptbioluminescencezas.ppt
bioluminescencezas.pptDESMONDEZIEKE1
 
PadminiNarayanan-Intro-2018.pptx
PadminiNarayanan-Intro-2018.pptxPadminiNarayanan-Intro-2018.pptx
PadminiNarayanan-Intro-2018.pptxDESMONDEZIEKE1
 

Plus de DESMONDEZIEKE1 (8)

GUT MICROBIOME IMPACT ON HUMAN GASTROINTESTINAL TRACT
GUT MICROBIOME IMPACT ON   HUMAN GASTROINTESTINAL TRACTGUT MICROBIOME IMPACT ON   HUMAN GASTROINTESTINAL TRACT
GUT MICROBIOME IMPACT ON HUMAN GASTROINTESTINAL TRACT
 
bioluminescence-130423221826-phpapp02.pptx
bioluminescence-130423221826-phpapp02.pptxbioluminescence-130423221826-phpapp02.pptx
bioluminescence-130423221826-phpapp02.pptx
 
presentation1-090331081630-phpapp01 (2).pptx
presentation1-090331081630-phpapp01 (2).pptxpresentation1-090331081630-phpapp01 (2).pptx
presentation1-090331081630-phpapp01 (2).pptx
 
GK12-Fifth-BioluminescencePPT.ppt
GK12-Fifth-BioluminescencePPT.pptGK12-Fifth-BioluminescencePPT.ppt
GK12-Fifth-BioluminescencePPT.ppt
 
bioluminescencezas.ppt
bioluminescencezas.pptbioluminescencezas.ppt
bioluminescencezas.ppt
 
giesy-gwf-omics.pptx
giesy-gwf-omics.pptxgiesy-gwf-omics.pptx
giesy-gwf-omics.pptx
 
i202082802.pptx
i202082802.pptxi202082802.pptx
i202082802.pptx
 
PadminiNarayanan-Intro-2018.pptx
PadminiNarayanan-Intro-2018.pptxPadminiNarayanan-Intro-2018.pptx
PadminiNarayanan-Intro-2018.pptx
 

Dernier

Generative AI in Health Care a scoping review and a persoanl experience.
Generative AI in Health Care a scoping review and a persoanl experience.Generative AI in Health Care a scoping review and a persoanl experience.
Generative AI in Health Care a scoping review and a persoanl experience.Vaikunthan Rajaratnam
 
Breast cancer -ONCO IN MEDICAL AND SURGICAL NURSING.pptx
Breast cancer -ONCO IN MEDICAL AND SURGICAL NURSING.pptxBreast cancer -ONCO IN MEDICAL AND SURGICAL NURSING.pptx
Breast cancer -ONCO IN MEDICAL AND SURGICAL NURSING.pptxNaveenkumar267201
 
Trustworthiness of AI based predictions Aachen 2024
Trustworthiness of AI based predictions Aachen 2024Trustworthiness of AI based predictions Aachen 2024
Trustworthiness of AI based predictions Aachen 2024EwoutSteyerberg1
 
Physiotherapy Management of Rheumatoid Arthritis
Physiotherapy Management of Rheumatoid ArthritisPhysiotherapy Management of Rheumatoid Arthritis
Physiotherapy Management of Rheumatoid ArthritisNilofarRasheed1
 
concept of total quality management (TQM).
concept of total quality management (TQM).concept of total quality management (TQM).
concept of total quality management (TQM).kishan singh tomar
 
Male Infertility, Antioxidants and Beyond
Male Infertility, Antioxidants and BeyondMale Infertility, Antioxidants and Beyond
Male Infertility, Antioxidants and BeyondSujoy Dasgupta
 
Mental health Team. Dr Senthil Thirusangu
Mental health Team. Dr Senthil ThirusanguMental health Team. Dr Senthil Thirusangu
Mental health Team. Dr Senthil Thirusangu Medical University
 
EXERCISE PERFORMANCE.pptx, Lung function
EXERCISE PERFORMANCE.pptx, Lung functionEXERCISE PERFORMANCE.pptx, Lung function
EXERCISE PERFORMANCE.pptx, Lung functionkrishnareddy157915
 
Basic structure of hair and hair growth cycle.pptx
Basic structure of hair and hair growth cycle.pptxBasic structure of hair and hair growth cycle.pptx
Basic structure of hair and hair growth cycle.pptxkomalt2001
 
Microbiology lecture presentation-1.pptx
Microbiology lecture presentation-1.pptxMicrobiology lecture presentation-1.pptx
Microbiology lecture presentation-1.pptxkitati1
 
Role of Soap based and synthetic or syndets bar
Role of  Soap based and synthetic or syndets barRole of  Soap based and synthetic or syndets bar
Role of Soap based and synthetic or syndets barmohitRahangdale
 
The Importance of Mental Health: Why is Mental Health Important?
The Importance of Mental Health: Why is Mental Health Important?The Importance of Mental Health: Why is Mental Health Important?
The Importance of Mental Health: Why is Mental Health Important?Ryan Addison
 
CONNECTIVE TISSUE (ANATOMY AND PHYSIOLOGY).pdf
CONNECTIVE TISSUE (ANATOMY AND PHYSIOLOGY).pdfCONNECTIVE TISSUE (ANATOMY AND PHYSIOLOGY).pdf
CONNECTIVE TISSUE (ANATOMY AND PHYSIOLOGY).pdfDolisha Warbi
 
Male Infertility Panel Discussion by Dr Sujoy Dasgupta
Male Infertility Panel Discussion by Dr Sujoy DasguptaMale Infertility Panel Discussion by Dr Sujoy Dasgupta
Male Infertility Panel Discussion by Dr Sujoy DasguptaSujoy Dasgupta
 
World-TB-Day-2023_Presentation_English.pptx
World-TB-Day-2023_Presentation_English.pptxWorld-TB-Day-2023_Presentation_English.pptx
World-TB-Day-2023_Presentation_English.pptxsumanchaulagain3
 
Good Laboratory Practice (GLP) in Pharma-LikeWays.pptx
Good Laboratory Practice (GLP) in Pharma-LikeWays.pptxGood Laboratory Practice (GLP) in Pharma-LikeWays.pptx
Good Laboratory Practice (GLP) in Pharma-LikeWays.pptxLikeways
 
Physiology of Smooth Muscles -Mechanics of contraction and relaxation
Physiology of Smooth Muscles -Mechanics of contraction and relaxationPhysiology of Smooth Muscles -Mechanics of contraction and relaxation
Physiology of Smooth Muscles -Mechanics of contraction and relaxationMedicoseAcademics
 
power point presentation of Clinical evaluation of strabismus
power point presentation of Clinical evaluation  of strabismuspower point presentation of Clinical evaluation  of strabismus
power point presentation of Clinical evaluation of strabismusChandrasekar Reddy
 
Pharmacokinetic Models by Dr. Ram D. Bawankar.ppt
Pharmacokinetic Models by Dr. Ram D.  Bawankar.pptPharmacokinetic Models by Dr. Ram D.  Bawankar.ppt
Pharmacokinetic Models by Dr. Ram D. Bawankar.pptRamDBawankar1
 
General_Studies_Presentation_Health_and_Wellbeing
General_Studies_Presentation_Health_and_WellbeingGeneral_Studies_Presentation_Health_and_Wellbeing
General_Studies_Presentation_Health_and_WellbeingAnonymous
 

Dernier (20)

Generative AI in Health Care a scoping review and a persoanl experience.
Generative AI in Health Care a scoping review and a persoanl experience.Generative AI in Health Care a scoping review and a persoanl experience.
Generative AI in Health Care a scoping review and a persoanl experience.
 
Breast cancer -ONCO IN MEDICAL AND SURGICAL NURSING.pptx
Breast cancer -ONCO IN MEDICAL AND SURGICAL NURSING.pptxBreast cancer -ONCO IN MEDICAL AND SURGICAL NURSING.pptx
Breast cancer -ONCO IN MEDICAL AND SURGICAL NURSING.pptx
 
Trustworthiness of AI based predictions Aachen 2024
Trustworthiness of AI based predictions Aachen 2024Trustworthiness of AI based predictions Aachen 2024
Trustworthiness of AI based predictions Aachen 2024
 
Physiotherapy Management of Rheumatoid Arthritis
Physiotherapy Management of Rheumatoid ArthritisPhysiotherapy Management of Rheumatoid Arthritis
Physiotherapy Management of Rheumatoid Arthritis
 
concept of total quality management (TQM).
concept of total quality management (TQM).concept of total quality management (TQM).
concept of total quality management (TQM).
 
Male Infertility, Antioxidants and Beyond
Male Infertility, Antioxidants and BeyondMale Infertility, Antioxidants and Beyond
Male Infertility, Antioxidants and Beyond
 
Mental health Team. Dr Senthil Thirusangu
Mental health Team. Dr Senthil ThirusanguMental health Team. Dr Senthil Thirusangu
Mental health Team. Dr Senthil Thirusangu
 
EXERCISE PERFORMANCE.pptx, Lung function
EXERCISE PERFORMANCE.pptx, Lung functionEXERCISE PERFORMANCE.pptx, Lung function
EXERCISE PERFORMANCE.pptx, Lung function
 
Basic structure of hair and hair growth cycle.pptx
Basic structure of hair and hair growth cycle.pptxBasic structure of hair and hair growth cycle.pptx
Basic structure of hair and hair growth cycle.pptx
 
Microbiology lecture presentation-1.pptx
Microbiology lecture presentation-1.pptxMicrobiology lecture presentation-1.pptx
Microbiology lecture presentation-1.pptx
 
Role of Soap based and synthetic or syndets bar
Role of  Soap based and synthetic or syndets barRole of  Soap based and synthetic or syndets bar
Role of Soap based and synthetic or syndets bar
 
The Importance of Mental Health: Why is Mental Health Important?
The Importance of Mental Health: Why is Mental Health Important?The Importance of Mental Health: Why is Mental Health Important?
The Importance of Mental Health: Why is Mental Health Important?
 
CONNECTIVE TISSUE (ANATOMY AND PHYSIOLOGY).pdf
CONNECTIVE TISSUE (ANATOMY AND PHYSIOLOGY).pdfCONNECTIVE TISSUE (ANATOMY AND PHYSIOLOGY).pdf
CONNECTIVE TISSUE (ANATOMY AND PHYSIOLOGY).pdf
 
Male Infertility Panel Discussion by Dr Sujoy Dasgupta
Male Infertility Panel Discussion by Dr Sujoy DasguptaMale Infertility Panel Discussion by Dr Sujoy Dasgupta
Male Infertility Panel Discussion by Dr Sujoy Dasgupta
 
World-TB-Day-2023_Presentation_English.pptx
World-TB-Day-2023_Presentation_English.pptxWorld-TB-Day-2023_Presentation_English.pptx
World-TB-Day-2023_Presentation_English.pptx
 
Good Laboratory Practice (GLP) in Pharma-LikeWays.pptx
Good Laboratory Practice (GLP) in Pharma-LikeWays.pptxGood Laboratory Practice (GLP) in Pharma-LikeWays.pptx
Good Laboratory Practice (GLP) in Pharma-LikeWays.pptx
 
Physiology of Smooth Muscles -Mechanics of contraction and relaxation
Physiology of Smooth Muscles -Mechanics of contraction and relaxationPhysiology of Smooth Muscles -Mechanics of contraction and relaxation
Physiology of Smooth Muscles -Mechanics of contraction and relaxation
 
power point presentation of Clinical evaluation of strabismus
power point presentation of Clinical evaluation  of strabismuspower point presentation of Clinical evaluation  of strabismus
power point presentation of Clinical evaluation of strabismus
 
Pharmacokinetic Models by Dr. Ram D. Bawankar.ppt
Pharmacokinetic Models by Dr. Ram D.  Bawankar.pptPharmacokinetic Models by Dr. Ram D.  Bawankar.ppt
Pharmacokinetic Models by Dr. Ram D. Bawankar.ppt
 
General_Studies_Presentation_Health_and_Wellbeing
General_Studies_Presentation_Health_and_WellbeingGeneral_Studies_Presentation_Health_and_Wellbeing
General_Studies_Presentation_Health_and_Wellbeing
 

Brno_2013_Omic_technologies (1).ppt

  • 1. SYLICA 'Omic Technologies – Bowater Feb 2013 SYLICA 2013 Bowater lectures Using ‘Omic Technologies to Investigate Gene Function
  • 2. Bowater Lectures in Brno, Feb. 2013 4 lectures on linked topics will be delivered during the coming week: • Contemporary DNA Sequencing Technologies – 26/2/2013 @ 10:00 • Using ‘Omic Technologies to Investigate Gene Function – 26/2/2013 @ 14:00 • Biophysical Methods to Study Molecular Interactions – 27/2/2013 @ 10:00 • Synthetic Biology & Nanotechnology: Tomorrow’s Molecular Biology? – 28/2/2013 @ 10:00 SYLICA 'Omic Technologies – Bowater Feb 2013
  • 3. Genomics, ‘Omics & Technology • Molecular biology: major scientific discipline for past ~50 years • Genomics = “analysis of genomes”: became important science during 1990’s • Analyses of various other biological molecules have developed into their own scientific disciplines; e.g. Metabolomics = “analysis of metabolites”, etc. • Transcriptomics/Proteomics: developed during past 10-15 years • Bioinformatics: has developed as major branch of science - enables efficient analysis of data from “omics” experiments SYLICA 'Omic Technologies – Bowater Feb 2013
  • 4. Genomics & Technology • Significance of “omics” coincides with dramatic improvements in different technologies: molecular biology: increased range of approaches for purification and manipulation of proteins and nucleic acids computers: required for gathering and analysis of data internet: allows data to be shared, quickly and easily • All developments have increased speed and cost- effectiveness - available to much wider audience SYLICA 'Omic Technologies – Bowater Feb 2013
  • 5. Transcriptomes • Genome: all of hereditary information encoded in the DNA (or RNA) • Transcriptome: set of all mRNAs ("transcripts”) produced from a genome • Term can be applied to: complete set of transcripts for a given organism specific subset of transcripts present in a particular cell type or under specific growth conditions • Transcriptome varies because it reflects genes that are actively expressed at any given time SYLICA 'Omic Technologies – Bowater Feb 2013
  • 6. DNA Microarrays Show Differences in Gene Expression • Microarray chips contain fragments from genes in the group to be analyzed – Full genome of bacteria or yeast, or protein families from larger genomes • mRNA or cDNA from different samples are differentially tagged • Analysis on the same chip shows differences SYLICA 'Omic Technologies – Bowater Feb 2013
  • 7. Transcriptomics • Transcriptomics uses high- throughput techniques based on DNA microarrays • For further details about microarrays see Lucchini et al., Microbiology, 147, 1403- 1414 (2001) Nelson & Cox, “Lehninger, Principles of Biochemistry”, 4th edn, 2004, p. 328 SYLICA 'Omic Technologies – Bowater Feb 2013
  • 8. Transcriptomics Nelson & Cox, “Lehninger, Principles of Biochemistry”, 4th edn, 2004, p. 328 SYLICA 'Omic Technologies – Bowater Feb 2013
  • 9. Nelson & Cox, “Lehninger, Principles of Biochemistry”, 4th edn, 2004, p. 328 SYLICA 'Omic Technologies – Bowater Feb 2013 Transcriptomics
  • 10. Nelson & Cox, “Lehninger, Principles of Biochemistry”, 4th edn, 2004, p. 328 SYLICA 'Omic Technologies – Bowater Feb 2013 Transcriptomics
  • 11. Nelson & Cox, “Lehninger, Principles of Biochemistry”, 4th edn, 2004, p. 328 SYLICA 'Omic Technologies – Bowater Feb 2013 Transcriptomics
  • 12. Nelson & Cox, “Lehninger, Principles of Biochemistry”, 4th edn, 2004, p. 328 SYLICA 'Omic Technologies – Bowater Feb 2013 Transcriptomics
  • 13. Nelson & Cox, “Lehninger, Principles of Biochemistry”, 4th edn, 2004, p. 328 •Experiments performed under different conditions •Determines effect of conditions on expression •Produces huge amount of data •Lots of repeats required - expensive SYLICA 'Omic Technologies – Bowater Feb 2013 Transcriptomics
  • 14. Polymerase Chain Reaction (PCR) • Used to amplify DNA in the test tube – Can amplify regions of interest (genes) within DNA – Can amplify complete circular plasmids • Mix together – Target DNA – Primers (oligonucleotides complementary to target) – Nucleotides: dATP, dCTP, dGTP, dTTP – Thermostable DNA polymerase • Place the mixture into thermocycler – Melt DNA at ~95°C – Cool to ~ 50–60°C, primers anneal to target – Polymerase extends primers in 5’3’ direction – After a round of elongation is done, repeat steps SYLICA 'Omic Technologies – Bowater Feb 2013
  • 15. General Steps of PCR SYLICA 'Omic Technologies – Bowater Feb 2013
  • 16. •Repeat steps 1–3 many times: General Steps of PCR SYLICA 'Omic Technologies – Bowater Feb 2013
  • 17. Photolitographic Synthesis of DNA SYLICA 'Omic Technologies – Bowater Feb 2013
  • 18. DNA Microarrays: Applications DNA microarrays allow simultaneous screening of many thousands of genes: high-throughput screening • Genome-wide genotyping – Which genes are present in this individual? • Tissue-specific gene expression – Which genes are used to make proteins? • Mutational analysis – Which genes have been mutated? SYLICA 'Omic Technologies – Bowater Feb 2013
  • 19. Adaptations to PCR • Reverse Transcriptase PCR (RT-PCR) – Used to amplify RNA sequences – First step uses reverse transcriptase to convert RNA to DNA • Quantitative PCR (Q-PCR) – Used to show quantitative differences in gene levels SYLICA 'Omic Technologies – Bowater Feb 2013
  • 20. qPCR SYLICA 'Omic Technologies – Bowater Feb 2013
  • 21. Proteomes • Proteome: set of all proteins produced under a given set of conditions • Term can be applied to: complete set of proteins for a given organism specific subset of proteins present in a particular cell type or under specific growth conditions • Proteome varies because it reflects genes that are actively expressed at any given time • Proteomics analyses many samples using 2D- electrophoresis and mass spectrometry • High-throughput, but less than transcriptomics SYLICA 'Omic Technologies – Bowater Feb 2013
  • 22. Gel Electrophoresis • Electrophoresis separates molecules by size • Resolution is limited Berg, Tymoczko & Stryer, “Biochemistry”, 6th edn, 2006, p. 71 SYLICA 'Omic Technologies – Bowater Feb 2013
  • 23. Isoelectric Focusing • Electrophoresis across a pH gradient • Proteins migrate to their isoelectric pH Berg, Tymoczko & Stryer, “Biochemistry”, 6th edn, 2006, p. 73 SYLICA 'Omic Technologies – Bowater Feb 2013
  • 24. Two-dimensional Gel Electrophoresis • Protein sample initially fractionated in one dimension by isoelectric focusing • SDS-PAGE performed perpendicular to original direction • Separates proteins according to pI and mass Berg, Tymoczko & Stryer, “Biochemistry”, 6th edn, 2006, p. 74 SYLICA 'Omic Technologies – Bowater Feb 2013
  • 25. • Proteins from E. coli separated by 2D-electrophoresis • >1,000 proteins can be resolved Berg, Tymoczko & Stryer, “Biochemistry”, 6th edn, 2006, p. 74 SYLICA 'Omic Technologies – Bowater Feb 2013 Two-dimensional Gel Electrophoresis
  • 26. Mass Spectrometry • MALDI-TOF mass spectrometry • Protein sample is ionized and exposed to electrical field • Ions travel according to size Berg, Tymoczko & Stryer, “Biochemistry”, 6th edn, 2006, p. 94 SYLICA 'Omic Technologies – Bowater Feb 2013
  • 27. MALDI-TOF Mass Spectrum • MALDI-TOF gives good estimates of molecular weights • Can be used to identify a few proteins within a mixture Berg, Tymoczko & Stryer, “Biochemistry”, 6th edn, 2006, p. 94 SYLICA 'Omic Technologies – Bowater Feb 2013
  • 28. Proteomic Analysis by Mass Spectrometry • Proteins separated by 2D electrophoresis • Single proteins eluted • Digestion with trypsin will give fragments with unique set of sizes • Sizes identified by mass spectrometry and matched to database • Allows identification of unknown proteins Berg, Tymoczko & Stryer, “Biochemistry”, 6th edn, 2006, p. 95 SYLICA 'Omic Technologies – Bowater Feb 2013
  • 29. Transcriptomics v Proteomics • Transcriptomics and proteomics are both very powerful • Differences in their practical application: Transcriptomics is robust, relatively cost-effective and user-friendly Proteomics still relatively limited – problems can remain with purification and stability of proteins • Increasing potential to combine and compare data sets - for discussion see Hegde et al., Curr. Opin. Biotech., 14, 647-651 (2003) SYLICA 'Omic Technologies – Bowater Feb 2013
  • 30. Bioinformatics: Mining the Data SYLICA 'Omic Technologies – Bowater Feb 2013
  • 31. Bioinformatics & Databases  Latest biological data is gathered, organised and disseminated through large databases  Databases include: - EBI, NCBI, Pfam, SMART, SWISS-PROT, TAIR  Information in bioinformatic databases: - sequences, structures, homology searches  Fast search engines allow searches by all with internet access – databases are as useful as the results they help generate!  Improved tools for analysis of sequences SYLICA 'Omic Technologies – Bowater Feb 2013
  • 32. Databases – Some URLs Resource URL European Bioinformatics Institute GenBank NCBI Protein DataBank Sanger Centre SMART The Arabidopsis Information Resource (TAIR) www.ebi.ac.uk/ www.ncbi.nlm.nih.gov/Genbank/ www.ncbi.nlm.nih.gov/ http://www.rcsb.org/pdb/home/home.do www.sanger.ac.uk/ smart.embl-heidelberg.de www.arabidopsis.org/ SYLICA 'Omic Technologies – Bowater Feb 2013
  • 33. NCBI: Complete Genomes SYLICA 'Omic Technologies – Bowater Feb 2013
  • 34. NCBI: Eukaryotic Genomes SYLICA 'Omic Technologies – Bowater Feb 2013
  • 35. NCBI: Eukaryotic Genomes SYLICA 'Omic Technologies – Bowater Feb 2013
  • 36. NCBI: Microbial Genomes SYLICA 'Omic Technologies – Bowater Feb 2013
  • 37. NCBI: Microbial Genomes SYLICA 'Omic Technologies – Bowater Feb 2013
  • 38. Databases - The Caveats  Databases contain mistakes (low as a proportion of total data) - primary data errors - data analysis errors - annotation errors  Errors are difficult to correct  Make the interpretation of data your own responsibility!! SYLICA 'Omic Technologies – Bowater Feb 2013
  • 39. NCBI – Useful Links Links to brief description of all resources at NCBI SYLICA 'Omic Technologies – Bowater Feb 2013
  • 40. PubMed: retrieval system containing citations, abstracts, and indexing terms for journal articles in the biomedical sciences NCBI – Useful Links BLAST: BLAST® (Basic Local Alignment Search Tool) is a set of similarity search programs All resources: provides integrated access to nucleotide and protein sequence data from >100,000 organisms Genetics & Medicine: continuously updated catalogues of human genes and genetic disorders Domains & Structure: NCBI Structure Group, including tools to search and display structures Taxonomy: general information about taxonomy SYLICA 'Omic Technologies – Bowater Feb 2013
  • 41. Databases Summary •Many databases are available - some have lot of general information (NCBI, EBI) - some have specific data (Pfam, SWISS-PROT) - some relate to specific research interests (TAIR) •Become well acquainted with specific databases •Wide range of databases, web sites and other resources are available for in silico analysis of biological data •Great advantages, but beware caveats and potential pitfalls – understand capabilities and limitations! •Use information intelligently: - always ask if the conclusions make biological sense - may require further analyses or experimentation SYLICA 'Omic Technologies – Bowater Feb 2013
  • 42. “Omics” Overview • Analyses of various biological molecules have developed into their own scientific disciplines; e.g. Metabolomics = “analysis of metabolites”, etc. • Transcriptome: set of all mRNAs ("transcripts”) produced from a genome • Proteome: set of all proteins produced under a given set of conditions • Both can vary because they reflect genes that are actively expressed at any given time • Transcriptomics and proteomics are both powerful, but are used differently: transcriptomics is cheaper and more user friendly than proteomics SYLICA 'Omic Technologies – Bowater Feb 2013