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Biochemistry,
computing
in
biology
Course outline
1
Introduction
2
Theoretical background
Biochemistry/molecular biology
3
Theoretical background computer science
4
History of the field
5
Splicing systems
6
P systems
7
Hairpins
8
Detection techniques
9
Micro technology introduction
10
Microchips and fluidics
11
Self assembly
12
Regulatory networks
13
Molecular motors
14
DNA nanowires
15
Protein computers
16
DNA computing - summery
17
Presentation of essay and discussion
Recombination
Recombination and crossover
Recombination and crossover
Recombination and crossover
If no exchange of genes
(i.e. phenotypic marker)
occurs, recombination
event can not be detected
Recombination and crossover
Introduction to ciliates
literature

Genome Gymnastics: Unique Modes
of DNA
Evolution and Processing in Ciliates. David
M. Prescott, Nature Reviews Genetics

Computational
power
of
gene
rearrangement.
Lila Kari and Laura Landweber, DIMACS series
in
discreet
mathematics
and
theoretical
computer science
The ciliate

Very ancient ( ~ 2 . 109 years ago)

Very rich group ( ~ 10000 genetically
different organisms)

Very important from the evolutionary
point of view
The ciliate

DNA molecules in micronucleus are very
long (hundreds of kilo bps)

DNA molecules in macronucleus are genesize, short (average ~ 2000 bps)
The ciliate
The ciliate tree
Baldauf et al.
2000.
Science 290:972.
Urostyla grandis
Eschaneustyla sp.
Holosticha kessleri Uroleptus
Bar: 50 mm
Scrambled Genes
sp. S.Found
lemnae
O. trifallax
O. nova
Bar: 25 mm
Bar: 100 mm
Bar: 100 mm
The ciliate
The ciliate
Dapi staining of the ciliate
Nuclei

Micronucleus the small nucleus containing a
single copy of the genome that is used for
sexual reproduction

Macronucleus the large nucleus that carries
up to several hundred copies of the genome
and
controls
metabolism
and
asexual
reproduction
Lifecycle of a ciliate
Micronucleus
Macronucleus
Cutting, splicing,
elimination, reordering,
and amplification of DNA
Prescott, 2000
The ciliate, meiosis
The ciliate, reproduction
MIC
MAC
Cell
Pairing
Meiosis and
Nuclear Exchange
Nuclear Fusion and
Duplication of the
Zygotic Nucleus
Macronuclear Development
and Nuclear Degeneration
Polytenization
Chromatid breakage
De novo telomere formation
Modified from Larry Klobutcher & Carolyn Jahn Ann. Review Microbiology, 2002
Computing in ciliates
The ciliate
Astounding feats of ‘DNA computing’
are routine in this ‘simple’ single
-celled organism— a protozoan. In
initial micronucleus, DNA is‘junky’
and scrambled, but….
….it reassembles itself in proper
sequence by means of computer-like
acrobatics (unscrambling, throwing
out genetic ‘junk’)—in macronucleus
The complexity of spirotrich biology
Telomere
Pointers
MAC
MIC
MDS: macronuclear destined sequences
IES: internal eliminated segments
Splicing
Fractioned genes
The complexity of gene scrambling

Intervening non-coding DNA regions (IES: internal
eliminated segments) interrupt protein-coding
sequences (MDS macronuclear destined sequences)

IESs are removed during macronuclear development

MDSs are unscrambled
Prescott, 2000
Scramble genes -TBP, actin I, DNA pol 
-TBP
Prescott et al., 1998
Actin I
Oxytricha nova
Hogan et al., 2001
DNA polymerase 
Landweber et al., 2000
Degree of scrambling in -TBP
Prescott et al, 1998
Unscrambling of actin I
Hogan et al, 2001
Degree of scrambling in DNA pol 
Landweber et al, 2000
DNA folding and recombination DNA pol 
DNA folding and recombination
DNA folding and recombination DNA pol 
DNA pol : Hairpin loop
Prescott, 2000
Recombination -TBP
Prescott et al, 1998
Tracing evolutionary scrambling
(i)
Isolate the micronuclear and macronuclear forms
of the -TBP gene
(ii) Compare the micronuclear and macronuclear gene
structures (MDS and IESs) to determine whether
the gene is scrambled
(iii) Compare homologous MDSs and scrambling patterns
in various stichotrich species (earlier
diverging species vs later diverging species)
(iv) Trace a parsimonious evolutionary scrambling
pathway
Comparisons of scrambling complexity
Oxytrichidae and Paraurostyla weissei
Uroleptus sp.
The evolution of recombination
Paraurostyla weissei
Uroleptus sp.
Stylonychia mytilus
100
100
Oxytricha nova
100
Oxytricha trifallax
Evolutionary scrambling pathway
Holosticha sp.
S. mytilus
O. nova
O. trifallax
P. weissei
Uroleptus sp.
Formal theory
Ciliate computing
 The
process
of
gene
unscrambling
in
hypotrichous ciliates represents one of
nature’s
ingenious
solutions
to
the
computational problem of gene assembly.
 With
some essential genes fragmented in as
many as 50 pieces, these organisms rely on a
set of sequence and structural
detangle their coding regions.
clues
to
 For
example, pointer sequences present at
the junctions between coding and non-coding
sequences
permit
reassembly
of
the
functional copy. As the process of gene
unscrambling appears to follow a precise
algorithm or set of algorithms, the question
remains: what is the actual problem being
solved?
The problem in the cell

Genomic Copies of some Protein-coding
genes are obscured by intervening nonprotein-coding DNA sequence elements
(internally eliminated sequences, IES)

Protein-coding sequences (macronuclear
destined sequences, MDS) are present in
a
permuted
order,
and
must
be
rearranged.
Assumption

By clever structural alignment…, the cell
decides which sequences are IES and MDS, as well
as which are guides.

After this decision, the process is simply
sorting, O(n).

Decision process unknown, but amounts to finding
the correct path. Most Costly.
Ciliate computing

there
is
some
as
yet
undiscovered
“oracle”mechanism within the cell,

or the cell simulates non-determinism

the former solution lacks biological
credibility
and
the
latter
implies
exponential time and space explosion.

What we want is a deterministic algorithm
for applying the inter- and intramolecular recombination operations to
descramble an arbitrary gene.
Ciliate computing
The first proposed step in gene unscrambling—
alignment or combinatorial pattern matching—
may involve searches through several possible
matches,
via
either
intra-molecular
or
intermolecular strand associations.
This part could be similar to Adleman’s
(1994) DNA solution of a directed Hamiltonian
path problem.
Ciliate computing
The second step—homologous
recombination at
aligned repeats—involves the choice of whether
to retain the coding or the non-coding segment
between each pair of recombination junctions.
This decision process could even be equivalent
to solving an n-bit instance of a satisfiability
problem, where n is the number of scrambled
segments.
Ciliate computing
We use
develop
our knowledge
a model for
of the first step to
the guided homologous
recombinations and prove that such a model has
the computational power of a Turing machine, the
accepted formal model of computation. This
indicates that, in principle, these unicellular
organisms may have the capacity to perform at
least
any
computation
electronic computer.
carried
out
by
an
Ciliate computing, the naïve model



Assume the cell simply reconstructs
the genes by matching up pointers.
Just one problem... pointer sequences
are not unique. In fact, may have
multiplicities greater than 13.
The proposed solution to this was
that the cell would simply try every
possible
combination
of
pointers
until it found the right two.
How the cell computes

Relies on short repeat sequences to act
as guides in homologous recombination
events

Splints analogous to edges in Adleman

One example represents solution
city HP (50 pieces reordered)
of
50
Formal model

Guided recombination system
uxwxv  uxv  wx
Formal model

Context necessary for a recombination between repeats x
(p, x, q) ~ (p’, x, q’)
Formal model, splicing operation

Formal Language Model
uxwxv  uxv  wx
Where u=u’p, w=qw’=w’’p’, v=q’v’

Intramolecular recombination.
x.
The guide is
Delete x wx from original.

Intermolecuar recombination.
Exchange.
Strand

This is a universal Turing machine (proven
by Tom Head)
Formal model, splicing operation
Gene unscrambling algorithm
Ciliate computing
Gene assembly in ciliates

Micronucleus: cell mating

Macronucleus: RNA transcripts (expression)

Micro: I0 M1 I1 M2 I2 M3 … Ik Mk Ik+1

M = P1 N P2

Macro: permutation of (possibly rotated)
M1,…, Mk and I0 ,…, Ik+1are removed
Molecular operators
Molecular operators
Molecular operators
Molecular operators
Molecular operators
Molecular operators
Molecular operators
Molecular operators
Molecular operators
Molecular operators
Molecular operators
Molecular operators
Molecular operators
Pointers

The pointer sequences
must be in spatial
proximity during
unscrambling

Topology must be
faithfully reproduced
somehow
Relocation of a locus

Recombination event
attaches Minor Locus to
end of Major Locus