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Information Storage and Processing in Biological Systems: A seminar course for the Natural Sciences. Sept 16 Introduction / DNA, Gene regulation Sept 18 Translation and Proteins Sept 23 Enzymes and Signal transduction Sept 25 Biochemical Networks Sept 30 Simple Genetic Networks

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slide1
Information Storage and Processing in Biological Systems:

A seminar course for the Natural Sciences

Sept 16 Introduction / DNA, Gene regulation

Sept 18 Translation and Proteins

Sept 23 Enzymes and Signal transduction

Sept 25 Biochemical Networks

Sept 30 Simple Genetic Networks

Oct 2 Adventures in Multicellularity

Nov 6 Evolution, Evolvability and Robustness

slide2
Reading List for Part 1

Chapters 1-3 “The Thread of Life” S. Aldridge Cambridge University Press. 1996.

“Genes & Signals” by Mark Ptashne and Alexander Gann. (2002) CSHL Press.

--------------------------------------------------------------------------------------------

From molecular to modular cell biology. (1999) L. H. Hartwell, J. J. Hopfield, S. Leibler and A. W. Murray. Nature 402 (SUPP): C47-C52.

It’s a noisy business! Genetic regulation at the nanomolar scale. H. Harley and A Arkin. Trends In Genetics February 1999, volume 15, No. 2

The challenges of in silico biology. (2000) B. Palsson. Nature Biotechnology 18: 1147-1150.

slide3
What is “biological information”

and how is it “Stored” and Processed”?

M.C. Escher Spirals

slide5
What is “biological information”?

Genetic(DNA and RNA)

Epigenetic(DNA modification)

slide6
What is “biological information”?

Genetic(DNA and RNA)

Epigenetic(DNA modification)

Non-Genetic Inheritance(template dependent replication)

paragenetic

slide7
Global patterning of organelles and cilia in Paramecium relies on paragenetic information and is template dependent.

Another example is Mad Cow Disease

slide8
What is “biological information”?

Genetic(DNA and RNA)

Epigenetic(DNA modification)

Non-Genetic Inheritance(template dependent replication)

Physiological-Cellular Level

(Structural/Metabolism/Signal Transduction)

slide9
Simplified Connectivity of Map of Metabolism

Each node represents a chemical in the cell (E. coli)

Each connection represents an enzymatic step or steps

slide10
What is “biological information”?

Genetic(DNA and RNA)

Epigenetic(DNA modification)

Non-Genetic Inheritance(template dependent replication)

Physiological-Cellular Level

(Structural/Metabolism/Signal Transduction)

Physiological- Organism Level

(Structural/Metabolism/Signal Transduction,

Development, Immune System)

slide11
What is “biological information”?

Genetic(DNA and RNA)

Epigenetic(DNA modification)

Non-Genetic Inheritance(template dependent replication)

Physiological-Cellular Level

(Structural/Metabolism/Signal Transduction)

Physiological- Organism Level

(Structural/Metabolism/Signal Transduction,

Development, Immune System)

Populations (Population dynamics, Evolution)

slide12
What is “biological information”?

Genetic(DNA and RNA)

Epigenetic(DNA modification)

Non-Genetic Inheritance(template dependent replication)

Physiological-Cellular Level

(Structural/Metabolism/Signal Transduction)

Physiological- Organism Level

(Structural/Metabolism/Signal Transduction,

Development, Immune System)

Populations (Population dynamics, Evolution)

Ecosystem(Interacting Populations,

environment  populations )

slide13
DNA

transcription

mRNA

translation

Protein

The“Central Dogma”

The central dogma relates to the flow of ‘genetic’ information in biological systems.

DNARNAProtein

slide14
Overview of Biological Systems

Organization of the Tree of Life

Three evolutionary branches of life:

Eubacteria, Archaebacteria, Eukaryotes

The macroscopic world represents a small portion of the tree.

slide15
The Eubacteria (bacteria), Archaebacteria (archae), and Eukaryotes represent three fundamental branches of life and represent two fundamental differences in organization of the cell.

Major Similarities:

Genetic code

Basic machinery for interpreting the code

Major Differences:

Organization of genes

Organization of the cell

sub-cellular organelles in Eukaryotes *

cytoskeletal structure in Eukaryotes **

No true multicellular organization in bacteria and archae (there are

many single celled eukaryotes). (debatable)

* compartmentalization of function

** morphologically distinct cell structure

slide16
Bacteria

Morphologically “simple” - shape defined by cell surface structure.

Transcription (reading the genetic message) and Translation (converting the genetic message into protein) are coupled- they take place within the same compartment (cytoplasm).

slide17
Compartmentalization of Function in eukaryotic cells

Transcription (reading the genetic message) and Translation (converting the genetic message into protein) occur in different compartments in the eukaryotic cell.

slide18
Example of single celled eukaryotic organisms

Morphological diversity (cytoskeleton as well as cell surface structures)

slide19
There are many distinct morphological cell types within a multicellular organism.

Morphological diversity arises from cytoskeletal networks - architectural proteins

slide20
Some ‘Model’ Experimental Eukaryotic Organisms

Caenorhabditis elegans

(round worm)

Saccharomyces cerevisiae

Drosophila melanogaster (fruit fly)

mouse

Antirrhinum majus

(snapdragons )

Zebrafish

Arabidopsis thaliana

slide21
Bacteriophage (Phage) and Viruses

1) genetic material / nucleic acid

2) protective coat protein

The information for their own replication and the means to “target” the correct cell/host but no interpretive machinery

slide22
Genotype

The genetic constitution of an organism.

Phenotype

The appearance or other characteristic of an organism resulting from the interaction of its genetic constitution with the environment.

slide23
Constraints in Biological Systems
  • Chemical/Physical constraints
  • stability of biological material
  • reaction rates and diffusion rates
    • - properties of biochemical reactions (enzymes) differ from chemical reactions
  • time dependency of many steps - time scales over many orders of magnitude for different steps
    • -receptor ligand binding msec
    • -biochemical response sec
    • -genetic response minutes- hours-days
  • statistical properties of ‘small-scale” chemistry, i.e. where concentration of reacting molecules is low.
  • Evolutionary constraints
  • a biological system is constrained by it’s own evolutionary history (and also ‘biological’ history)
slide24
“Alarm clock” from the movie Brazil

Evolution of new functions is rarely de novo invention but is typically due to the modification of pre-existing functions/structures.

slide25
Modularity
  • Is the cell/organism designed in a modular fashion?
  • Can we approximate cell behavior into modules?
  • Can interactions of cells, individuals, organisms be treated in a similar way?
  • Coarse graining
  • At what level of detail do we need to study/model a system to extract information about the underlying mechanisms?
  • What level of detail is required to define the “state” of the cell, the individual, the population and ecosystem…?
  • Can we define the “state” of the cell or only “states” of modules?
slide26
Stochastic variations and Individuality
  • What is the source of stochastic variation (independent of genetic variation)?
  • In genetically identical populations, does this play a role in adaptation?
  • What role do stochastic processes play in development?
  • Robustness
  • Despite stochastic variations, many cellular processes are extremely robust (genetic networks, biochemical networks, cell divisions, development,…)
  • How does the cell overcome the limitations imposed by stochastic variations?
  • Where does robustness arise? Is it a network property?
slide27
Redundancy
  • - Many biological processes are duplicated so that the same function is present in multiple elements. Mutations (changes in genotype) may have no apparent phenotype or one that is less severe than expected.
  • - Many biological systems are degenerate, they can occur by alternative pathways.
  • Complexity
  • “the whole is greater than the sum of its parts.”
slide28
Genotype  Phenotype

Can we understand the mechanisms and processes that shape the expression of genetic variation in phenotypes?

slide29
The Natural History of Dictyostelium discoideum

Adventures in Multicellularity

The social amoeba (a.k.a. slime molds)

slide30
The Natural History of Dictyostelium discoideum

Adventures in Multicellularity

The social amoeba (a.k.a. slime molds)

slide31
The Natural History of Dictyostelium discoideum

Adventures in Multicellularity

The social amoeba (a.k.a. slime molds)

slide32
DNA Basics

Four bases

A - adenine

T - thymine

C - cytosine

G - guanine

anti- parallel double stranded structure with specific bonding between the two strands:

A  T base pairing

C  G base pairing

slide33
DNA Structure
  • DNA is composed of two strands
  • Each strand is composed of a sugar phosphate backbone with one of four bases attached to each sugar
  • The arrangement of bases along a strand is aperiodic
  • The two strands are arranged anti-parallel
  • There is base specific pairing between the strands such that A pairs with T and C with G, consequently knowing the sequence of one strand gives us the sequence of the opposite strand.

A -T

C -G

G -C

A -T

T -A

G -C

G -C

G -C

T-A

slide35
A -T

C -G

G -C

A -T

T -A

G -C

G -C

G -C

T-A

A

C

G

A

T

G

G

G

T-A

  • DNA Replication
  • Template copying
  • Semi-conservative

A -T

C -G

G -C

A -T

T -A

G -C

G -C

G -C

T-A

A -T

C -G

G -C

A -T

T -A

G -C

G -C

G -C

T-A

A -T

G

C

T

A

C

C

C

A

slide36
The Genetic Code – Triplet Code

- directional (always read 5’ 3’)

- each triplet of bases codes one amino acid (Codon)

- degenerate (many AA have more than one codon)

slide37
For a given sequence there are three possible reading frames

DNA contains information about the start and end of the gene as well as when to make or if to make transcribe the information.

slide38
DNA as an information molecule
  • DNA sequence itself
  • DNA sequence as a code of protein
  • (sequence/properties of the protein)
  • DNA sequence as controlling elements and recognition sites for cellular machinery
  • DNA secondary structure and chemical modifications (e.g. methylation)
  • genetic networks from multiple controlling elements and recognition sites with multiple genes and feedback and or feedforward systems
slide39
5001 CATAAACCGG GGTTAATTTA AATACTGGAA CCGCTTACCA ATAAGACTAA

GTATTTGGCC CCAATTAAAT TTATGACCTT GGCGAATGGT TATTCTGATT

-2 end of luxS ***I

? gene start

+1 MetGlnPhe LeuGlnPhe PhePheArgGln ArgGlnLeu PheIleAla

5051 ATATGCAATT CCTGCAGTTT TTCTTTCGGC AGCGCCAGCT CTTTATTGCT

TATACGTTAA GGACGTCAAA AAGAAAGCCG TCGCGGTCGA GAAATAACGA

-2 leHisLeuGlu GlnLeuLys GluLysProLeu AlaLeuGlu LysAsnSer

+1 hrProAspArg ArgArgLeu HisProGlyMet IleAspCys GluAlaIle

5501 CCCCGGACCG CCGGCGCTTG CATCCGGGTA TGATCGACTG CGAAGCTATC

GGGGCCTGGC GGCCGCGAAC GTAGGCCCAT ACTAGCTGAC GCTTCGATAG

-2 lyArgValAla ProAlaGln MetArgThrHis AspValAla PheSerAsp

+1 ***end of ? gene

5551 TAATAATGGC ATTTAGTCAC CTCCGATAAT TTTTTAAAAA TAAACTGAAC

ATTATTACCGTAAATCAGTG GAGGCTATTA AAAAATTTTT ATTTGACTTG

-2 LeuLeuProMet luxS start

slide40
Two ways of thinking about “information” in DNA

1) DNA has sequence information which is TRANSCRIBED into RNA (i.e. it is a template) and TRANSLATED from RNA into protein (Genetic Code).

5’---CTCAGCGTTACCAT---3’

3’---GAGTCGCAATGGTA---5’

5’---CUCAGCGUUACCAU---3’

N---Leu-Ser-Val-Thr---C

DNA

RNA

PROTEIN

Transcription

Translation

  • In RNA T’s are replaced by U’s
  • Some gene products are RNA, i.e. they are not translated (e.g. tRNA, rRNA)
slide41
Two ways of thinking about “information” in DNA

2) DNA has sequence information at a structural level. This form of information directs the ‘interpretative machinery’ in the cell (protein complexes), in most instances binding sites for proteins. This type of ‘information’ is important for example in determining where(along a sequence of DNA) and whena gene may be turned on, initiation of DNA replication, packaging of DNA etc…

i.e - Regulation

slide42
The Basic Transcription Components (Bacterial)

Transcription

Machinery

s factor

a2bb’holoenzyme

RNA Polymerase

start

DNA

-35

-10

Promoter - binding site for RNA polymerase, defines where the process will begin.

slide43
Promoter Binding

-35

-10

Open Complex Formation

Promoter Clearance

Messenger RNA (mRNA)

slide44
Regulation of Gene Expression: The Basics

Transcriptional Regulators are proteins that act to modulate gene expression.

Proteins that negatively regulate expression (i.e decrease transcription) are called Repressors and those that act positively (i.e. increase transcription of a gene) are called Activators.

These proteins act by binding at specific DNA sites are modulate RNA polymerase function. These binding sites are called operators.

start

-35

-10

promoter

operator

slide45
Repressor

X

start

-35

-10

Repression can be viewed as a competition for binding between the polymerase and the repressor (an oversimplification).

slide46
Activator

start

-35

-10

promoter

operator

An Activator promotes RNA polymerase biding activity through direct protein-protein interactions (an oversimplification).

slide47
Any DNA binding protein, with an appropriately placed binding site can act as a repressor. Activation requires specific protein-protein interaction between the activator and RNA polymerase.
  • Typically bacterial promoters are regulated by a few proteins at most and the control regions tend to be quite small.
  • Eukaryotic gene regulatory regions can be very large and involve many transcriptional regulators.
  • Activation and repression depend on positioning of operator sites.
  • Multiple inputs can be integrated at the level of gene expression.
slide48
Consensus Binding Sites

The interaction of a DNA-Binding Protein (such as RNA Polymerase or transcriptional regulators) is dependent on the ‘affinity’ of the protein for the binding site. This affinity will vary under different physiological conditions, as the concentration of the protein changes and also will depend on the binding site itself.

The optimal binding site is usually close to the consensus sequence for that site obtain by aligning all the know binding sites. On can thus have a range of ‘activity’ at different promoters/operators by having differences in DNA binding sites.

E. coli Promoters

-35 box-10 box

ConsensusTTGACA- N17- TATAAT

Examples:TTGATA- N16- TATAAT TTCCAA- N17- TATACT

TGTACA- N19- CATAAT

TTGATC- N17- TACTAT

TTGACA- N17- TAGCTT

slide49
“Activity” of Transcriptional Regulators in Response to ‘Signals’

Case 1. Affinity of the protein for DNA may be modified by binding a ‘ligand’ (Allosteric mechanism).

Case 2. Affinity of the protein may be affected by covalent modification such as phosphorylation.

DNA

R R-DNA

x DNA

Rx Rx-DNA

DNA

Both of these mechanisms (ligand binding and post-translational modification) are common themes in the regulation of proteins, not just in transcription control.

slide50
Regulation of Gene Expression

DNA

RNA polymerase binding

Open Complex Formation

Transcription

mRNA

mRNA stability

Translation

Protein

Polypeptide folding

Protein stability

Both positive and negative regulation can occur at any step in this process.

slide51
General Principles of Regulation of Gene Expression
  • Regulation occurs through recruitment or preventing recruitment of transcription machinery.
    • Repressors typically prevent recruitment of polymerase
    • Activators increase recruitment of polymerase
  • Multiple inputs from different transcription factors (TFs) can be integrated or compete.
  • Protein-DNA interactions (TF, RNAP) can have different affinities, ie can act differently at different promoters at the same level of activity.
slide52
Eukaryotic Gene Expression

- the same principles but added complexity

slide53
Eukaryotic Gene Expression

- the same principles but added complexity

“simple’ RNA polymerase replaced by a large transcription complex (As many as 50 proteins)

slide54
CAP

O3

O1

O2

Eukaryotic Gene Expression

- the same principles but added complexity

e.g. E. colilac , ~250 bp, 2 inputs

Drosophilaeve stripe 2 enhancer, >1000bp, multiple TFs

Relatively compact regulatory regions in bacteria are spread over larger regions, more transcription factors

- more inputs /signal integrations.

slide55
The added regulatory components increases the potential complexity of gene regulation in eukaryotic cells.

Organism complexity a number of genes

Organism complexity a regulatory elements

Eukaryotic Gene Expression

- the same principles but added complexity

slide56
Organism # of genes

Mycoplasma genetalium 750

Escherichia coli5000

Pseudomonas aeruginosa 6000

Saccharomyces cerevisiae 6000

Caenorhabditis elegans 19,000

Drosophila melanogaster 15,000

Homo sapiens (man) 40,000

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