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PhD defense

Characterising the CRISPR immune system in Archaea using genome sequence analysis
by

Shiraz Shah

on 16 September 2013

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Transcript of PhD defense

TREE OF LIFE
Archaea
Bacteria
Eukaryotes
Characterising the CRISPR immune system
in Archaea using genome sequence analysis
Ph. D defence
Supervisor
Professor Roger A. Garrett
University of Copenhagen - Department of Biology - Danish Archaea Centre
superficially they resemble bacteria

their cellular machinery looks eukaryotic

they live in extreme environments
BACTERIA
ARCHAEA
EUKARYOTES
Picture courtesy of Xiangyux
CRISPR
adaptive
immunity

repeat
~30 bp
spacer
~40 bp
non-coding
100 - 500 bp
adaptation complex
made of aCas proteins
Cas1
Cas2
Cas4
processing complex
made of pCas proteins
Cas6
interference complex
made of iCas proteins
Cas3
Cas5
Cas7
Cas8
cmr modules
located seperately on the genome
an additional optional set of cas genes
encoding multiple RAMP proteins
iCmr complex made of
Cas10
Cmr5
3-6 RAMP proteins
uses crRNAs and pCas from other CRISPR loci, to target viral RNA
Every living organism has a genetic sequence
which defines it
10 kilobases
=
10 kilobytes
common cold
small text document
5 MB
typical email attachment
Salmonella bacterium
You and I
typical usb pen drive
4 GB
Paris japonica
laptop hard drive
150 GB
So what does it look like
Functional Cas modules - Real world examples
Functionally independent modules
Functionally independent modules
Are they exchangable?

Characterising the
CRISPR
immune system
in
Archaea
using
genome
sequence analysis
Introduction
What is genome sequence analysis?
What are Archaea?
What is CRISPR?

Functional modules of cas genes
(collaboration with Gisle)

Predicting the target of the immune response
Why modular exchange?
viruses have a high mutation rate
for the immune system to be effective it has to be dynamic and susceptible to change
Spacers were mapped back onto the viral genome.
We looked at the distribution to predict the target of the immune response

If crRNAs target viral mRNA
spacers should match the opposite strand of important genes
If crRNAs target viral DNA
spacers matches should be randomly distributed
Statistical tests
Spacer match distributions in 30 viruses and plasmids were tested against a random (Poisson) distribution
Results suggested DNA targeting
Later confirmed experimentally by another lab
Acknowledgements
Full transcript