from ome to ome: revolutions in current biology deri tomos (ysgol gwyddorau biolegol, prifysgol...
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From ome to ome: revolutions in current biology
Deri Tomos(Ysgol Gwyddorau Biolegol,
Prifysgol Cymru Bangor)
Friedrich Wohler 1828
Gregor Mendel1866
(de Vries 1900)
Proteins – the most complex bio-molecules
The Substance of Life & Inheritance ?
From Protein to DNA
1944-1953 - 9 anni mirabili
Watson & Crick (Franklin, Wilkins ……. & Herbert Wilson)
- 1953
Wilson
Crick
Self replicating
Okazaki fragments
C = G
A = T
A new biology
A universal language
Haemoglobin
Reading the Genome
Escherischia coli - 4.6 million Yeast - 23 million
Virus X 174 - 8 genes - 5386 letters (1976)
Nematode
Rice
Arabidopsis
Zebra Fish
Drosophila
Mouse
Human (3 billion letters)
So many sequences !
Automated sequencing
Genetic mapping
Three types of “reading”
Gene sequencing
Fingerprinting
Genetic fingerprinting
Unique sequences – cf car registration numbers or NI numbers
Catching criminals/Disaster identification/families
Genetic mapping
Whole series of tabloid headline “genes for” ……
In plant and animal breeding – marker assisted breeding
Dangerous (?) statistical correlations
“Real” gene identification
Genetic disease – eg CF, PKU (some 10,000
examples)
Each has already raised moral issues – eg insurance, genetic councelling etc)
What does the Genome do ?
Central Dogma – a “photocopy” !
DNA RNA ProteinTranslationTranscription
Genome Hans Winkler, 1920
Genomics was introduced 24 years ago by Victor McKusick and Frank Ruddle, as the catchword for the new journal of that name they had just founded
Proteome 1994 Marc Wilkins (Proteome Systems)
Jeremy Nicholson "metabolomics"-- 1996
Minimum number of genes ~ 300 ?
The Central Dogma today ?
Outcomes of reading the genome in 1980s.
Introns
The gene for one type of collagen found in chickens is split into 52 separate exons.
The gene for dystrophin, which is mutated in boys with muscular dystrophy, has 79 exons.
Even the genes for rRNA and tRNA are split.
Gene (DNA)
Transcript (RNA)copy, cut and splice
Only 2% of the Human Genome codes for proteins !
and 25,000 such genes produce 100,000 proteins !
We need to know what genes are actually making
Studying the transcriptome (RNA)
Microarrays
In humans :~ 25,000
Each spot is an active gene
Enormous power – the bits of the book that are being read at any time
What makes a Queen Bee ?
9 genes
Disease and design of new
treatments
Doctor’s surgery soon
Non-protein RNA. “Junk genes” (Steve Jones) ?
50% of human genome - “transposons”
Internalised viruses
EpigeneticsNon-genome inheritance.
Imprinting
Chromosome structure
On / Off switches
Epigenetics
Lamarck ?
Stem cell role – resetting the clock.
Another Solid Gold sheep story
Epigenetics at work
The need to look directly at the Proteins that are made.
Proteomics
Proteome
Gel electrophoresis
Robots essential for “high
throughput”
$700 million 1999$5.6 billion 2005
Robots cut out spots and feed
them to powerful mass
spectrometersFragments can be
identified by reference to the genome, if known, prediction. But needs powerful computers !
BIOINFORMATICS
This Biology is BIG and expensive
So why do we bother ?
New drugs are harder and harder to develop.
In 2000 $30 billion and R&D – only 30 drugs approved.
But ultimately it is the small molecules - the metabolites - that
matter.
Metabolomics
Chromatography and nmr
- but again need high throughput analysis
Pharmaceutical companies need millions of analyses per year.
Powerful - and expensive - mass spectrometers
In Fig A is depicted the metabolomic analysis of a wide variety of compounds across 11 different tissues from a mouse. The height of each dot represents the relative concentration of each compound. The distribution of a single compound across all 11 tissues is depicted in Fig B.
but 2,000 - 20,000 per tissue type ?
Drug targets and effects
Transcriptome
Metabolome
Proteome
Genome
Serious bioinformatics challenges !
This Biology is Multidisciplinary
Where will this approach take us ?
Genetic (metabolic) diseasesFood production, nutrition and environmental protectionCancer and developmentNew pharmaceuticalsBrain and consciousnessINDIVIDUALISATION
of treatmentsFunctional imaging ?
But remember Wohler !
NNB. Expected time scale for our students
Diolch
Thank you
In physics, probably starting with Faraday's ion, cation, anion, the -on suffix has tended to signify an elementary particle, later materially focused on the photon, electron, proton, meson, etc., whereas -ome in biology has the opposite intellectual function, of directing attention to a holistic abstraction, an eventual goal, of which only a few parts may be initially at hand. [ Joshua Lederberg and Alexa T. McCray "'Ome Sweet 'Omics: A Genealogical Treasury of Words" Scientist 15 (7): 8 April 2, 2001] http://www.the-scientist.com/yr2001/apr/comm_010402.html
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