Transcript A Positive Selection Function for miRNA

Crick/Clark/Student Petition
Evolution of Genetic Coding
Pieczenik- Theory of Genotypic Selection
Coding Constraints
Palindromes
Internal Terminators
Base pairingNussinov,Pieczenik,Griggs,Kleitman
Algoritm
GU base pairing
Evolution of Genetic Coding
Crick, Brenner, Klug, Pieczenik Model of
tRNA-mRNA interaction and Evolution
of the code.
Pieczenik Hypothesis of Combinatorial
RNA Ligation
Mechanism for evolution of mRNA
sequences
Selective Constraints on
Combinatorial Possibilities
All combinations are made a priori
Selection under constraints are made a
posteriori
Selection can be for physical chemical
constraints and/or for informational
coding constraints.
Problems
1) Are Nucleotide Sequences Random or are there Rules of
Harmony?
2) What are the Constraints on Nucleotide and Protein
Sequences?
3) What are the Constraints on mRNA imposed by Ribosome
Binding Sites?
4) What are the Constraints on mRNA imposed by translation
by tRNA?
5) What are the Constraints on mRNA imposed by miRNA
combinatorial ligation?
6) What are the Constraints imposed on antibody-antigen
interactions and their codings?
7) What are the Constraints imposed on the lipid combinatorial?
Constraint on mRNA
imposed by translation by
tRNA
Common Uracil 5’ to the anti-codon
and Pu 3 ‘ to anti-codon creates
PuNPy constraint on mRNA if there is a
flip of anti-codon in translation.
PuNPy, PuNPy,PuNPy
tRNA Competing for
Translation
Combinatorial Constraint
Not Imposed on mRNA
The inverse non existent G 5’ to the
anti-codon and U 3’ to the anti-codon
Creates PyNPu constraint on mRNA, if
there is a flip of anti-codon in translation
PyNPu,PyNPu,PyNPu
Combinatorial Sequence
Constraints on
Ribosome Binding Sites
First DNA Sequence- ΦX 174 Gene G
Ribosome Binding Site
ATG.TTTCAGACTTT- Palindrome
Mirror Image
Two Combinatorial
mRNA Sequence
Constraints on RBS
Gene V- f1 bacteriophage
–RBS
Palindrome
Internal Terminator
Combined Into One
Sequence
fMet.Ile.Lys.Val.Glu.Ile.Lys
Combinatorial RNA
Ligation- Problem
How does one code 1-2 million proteins
with only 19.000-30,000 coding
sequences?
Combinatorial RNA
Ligation- Background
miRNA are 22 base RNA strands
cleaved from hairpin structures
miRNA are known to suppress
translation of mammalian mRNA
miRNA catalyze the cleavage of plant
mRNA.
Cleavage reactions are reversible as
ligation reactions
miRNA are conserved across species
miRNA can base pair with mRNA
forming double helix
22 bp is exactly 2 full turns of the A form
RNA helix- Rosalind Franklin/Hugh
Robertson.
Around 321 miRNA exist in most
organisms
miRNA as adaptors and
ligase
Most miRNA have a
splice site, AG / GU,
directly in the middle of
sequence
Rnase III, discovered by
Hugh Robertson, and
Dicer are enzymes that
cleave the A-form RNA
helix
Hypothesis
miRNA catalyzes the combinatorial
ligation of 2 independent mRNA
This creates a completely new coding
sequence which means a novel protein
Each of the mRNA will contain one 11
bp seq. complementary to the halves of
the miRNA
This creates an RNA triplex where half
of the miRNA is hybridized with the 11
bp complement in each mRNA
The miRNA is thought to bring the 2
mRNA and 2 H2O into close contact
Because the mRNA must be
complementary to the miRNA sequence
the ligation is sequence specific. GU
base pairing is allowed.
Now any coding can be paired with any
other coding to give an entirely novel
sequence
This allows for (20k)^2 / 321= 1.25 mil.
proteins
Negative Selection vs
Positive Selection for
miRNA
Sequences that contain the entire
complement to the miRNA compete with other
mRNA to form a helix
These sequences are negatively selected
against because the helix will prevent
translation of the sequence and Dicer
recognizes the helix and destroys it-Silencing
Sequence Search
BLAST is a program that compares a
query to known sequences
Difficulty in using BLAST because on
requires combinatorial matches of GU
base pairing in addition to GC base
pairing. BLAST is not suited for this type
of search.
Short Protein-Protein
BLAST Searches
However, protein-protein matches
eliminate this problem initially.
What is found is that sequences that are
coded by antiparallel complements of
miRNA, which is what would be created
in the new ligated message, do appear
much more frequently than once in the
protein data base of known protein
sequences
The combinations are then translated
For example, miRNA let-7 (6) in the 5′ to
3′ has one open reading frame and
three open reading frames in its
antiparallel complement in the 5′ to 3′
direction. The antiparallel complement
would correspond to coding sequences
which would appear in mRNA which are
ligated with the mechanism postulated.
into protein sequence in all six frames
Peptide Sequences Coded by
Complement of miRNAs
Three phases of the antiparallel complement of let-7 are
(i) Asn.Tyr.Thr.Thr.Tyr.Tyr.Leu;
(ii) Thr. Ile.Gln.Pro.Thr.Thr.Ser; and
(iii) Leu.Tyr.Asn. Leu.Leu.Pro.His/Gln
These sequences are found in several proteins e.g. splicing
factor U2Af, bromodomain-containing protein (stimulates
transcription activity), testis-determining factor, coiled-coil
domain-containing protein 3 precursor, DNA-directed RNA
polymerase I subunit 2, inter alia.in-containing protein
(stimulates transcription activity), testis-determining factor,
coiled-coil domain-containing protein 3 precursor, DNA-directed
RNA polymerase I subunit 2, inter alia.
Experimental Tests
Create triplex RNAs with miRNA
sequences and complementary mRNA
sequences and demonstrate ligation of
the two mRNA sequences, generating a
ligated mRNA and the miRNA
unreacted.
Develop an miRNA dependant mRNA
ligating system and translation system.
Michaelis-Menton
Equation for miRNA
Ligation
Vo = Vmax [mRNA1+mRNA2]
Kmi + [mRNA1+mRNA2]
Kmi=MM constant for miRNA ligation
Symmetry of
Antibody=Antigen
Universes
4-5 amino acids
define monoclonal
antibody binding
specificity =
160,000-3.2 million
20^4.66=1.15million
20^5=3.2 million
Combinatorial of V,
J, D Antibody
segments = 2-3
million
Combinatorial Lipids
Tiacly Glycerides
N^3/2 + N^2/2 = unique stereoisomers
N = number of saturated and
unsaturated fatty acid chains
Selection for 37 degree fluidity creates a
ratio of 1:1 saturated to unsaturated
fatty acid chains
Theory of Genotypic
Selection
Direct Genotypic Selection, historical or
present, on nucleic acids for replication,
transcription, processing and
translation.
A Posteriori Imposes Sequence and
Amino Acid Constraints on A priori all
possible Nucleic Acid Sequences
GU Base Pairing
Constraint
tRNA-mRNA interactions- Crick,
Brenner, Klug, Pieczenik Model
Hairpin Structures-Nussinov, Pieczenik,
Grigg, Kleitman Base Pairing AlgorithmmiRNA, IRIS, RNA editing, polio
pathogenicity C to U at 472
Polio Pathogenicity
Sequence of NonPathogenic Competitive
HIV Strain- Donor (A)and
Recipient (C)
Infectious
Hypovirulence
Non-Pathogenic Donor Strain Evolved from
Healthy HIV sero-positive Gabonese, through
Mexico unto San Francisco Where it Was
Identified in Long Term Asymptomatic HIV
positive with Healthy HIV positive Partner.
Frequency 22/10,000= 1/500
4 asymptomatics in HIV patient pop of 2,000
1 with healthy HIV partner
miRNA mimics
HIV, Hep C, RNA virus may mimic miRNA
Combinatorial Ligation Adaptor Functions
Creating new combinations and suppressing
proper cellular miRNA Combinatorial Ligation
Functions
Stable Hairpin and miRNA duplex both 22
nucleotides long on average
Similar Target Region Size of 22 for
pathogenicity may either be hairpin or miRNA
ligation mimicking site.
Crick/Clark
Crick/Clark
Submitted Nature
Petition Gets
George Pavlakis
Out of Prison.
George Pavlakis
continues work on
HIV vaccine