From ome to ome: revolutions in current biology Deri Tomos (Ysgol Gwyddorau Biolegol, Prifysgol...

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

Peirianneg Genynnau

Ensymau “cyfyngu”

Lladd dafad ddall

Yr Offer

Peirianneg Genynnau

A

B