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Transcript of Biochemistry, computing in biology 1Introduction 2Theoretical background Biochemistry/molecular...
Biochemistry, computing in biology
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
Course outline
Recombination
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
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
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 gene-
size, short (average ~ 2000 bps)
The ciliate
The ciliate
Baldauf et al. 2000. Science 290:972.
The ciliate tree
Urostyla grandis
Bar: 50 m
Holosticha kessleri
Bar: 100 m
Uroleptus sp.
Bar: 100 m
Scrambled Genes Found
S. lemnaeO. trifallaxO. nova
Eschaneustyla sp.
Bar: 25 m
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
Prescott, 2000
Macronucleus
Micronucleus
Cutting, splicing, elimination, reordering, and amplification of DNA
Lifecycle of a ciliate
The ciliate, meiosis
CellPairing
Meiosis andNuclear Exchange
Nuclear Fusion andDuplication of theZygotic Nucleus
Macronuclear Developmentand Nuclear Degeneration
MIC
MAC
Modified from Larry Klobutcher & Carolyn Jahn Ann. Review Microbiology, 2002
Polytenization
Chromatid breakage
De novo telomere formation
The ciliate, reproduction
Computing in ciliates
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 ciliate
IES: internal eliminated segmentsMDS: macronuclear destined sequences
MAC
MIC
Telomere Pointers
The complexity of spirotrich biology
Splicing
Fractioned genes
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
The complexity of gene scrambling
Actin I
DNA polymerase
Landweber et al., 2000
Hogan et al., 2001
-TBP
Prescott et al., 1998
Oxytricha nova
Scramble genes -TBP, actin I, DNA pol
Prescott et al, 1998
Degree of scrambling in -TBP
Hogan et al, 2001
Unscrambling of actin I
Landweber et al, 2000
Degree of scrambling in DNA pol
DNA folding and recombination DNA pol
DNA folding and recombination
DNA pol : Hairpin loop
Prescott, 2000
DNA folding and recombination DNA pol
Prescott et al, 1998
Recombination -TBP
(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
Tracing evolutionary scrambling
Uroleptus sp.
Oxytrichidae and Paraurostyla weissei
Comparisons of scrambling complexity
Oxytricha trifallax
Oxytricha nova
Stylonychia mytilus
Uroleptus sp.
Paraurostyla weissei
100
100
100
The evolution of recombination
P. weissei Uroleptus sp.
Holosticha sp.
O. trifallax
O. nova
S. mytilus
Evolutionary scrambling pathway
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 clues to
detangle their coding regions.
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?
Genomic Copies of some Protein-coding
genes are obscured by intervening non-
protein-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.
The problem in the cell
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.
Assumption
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 intra-
molecular 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 our knowledge of the first step to develop
a model for 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
carried out by an electronic computer.
Ciliate computing
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.
Ciliate computing, the naïve model
Relies on short repeat sequences to act
as guides in homologous recombination
events
Splints analogous to edges in Adleman
One example represents solution of 50
city HP (50 pieces reordered)
How the cell computes
Guided recombination system
wxuxvuxwxv
Formal model
Context necessary for a re-
combination between repeats x
(p, x, q) ~ (p’, x, q’)
Formal model
Formal Language Model
Where u=u’p, w=qw’=w’’p’, v=q’v’
Intramolecular recombination. The guide is
x. Delete x wx from original.
Intermolecuar recombination. Strand
Exchange.
This is a universal Turing machine (proven
by Tom Head)
wxuxvuxwxv
Formal model, splicing operation
Formal model, splicing operation
Gene unscrambling algorithm
Ciliate computing
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
Gene assembly in ciliates
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
The pointer sequences
must be in spatial
proximity during
unscrambling
Topology must be
faithfully reproduced
somehow
Pointers
Recombination event
attaches Minor Locus to
end of Major Locus
Relocation of a locus