information storage and processing in biological systems:

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

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

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

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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.

Reading List for Part 1

What is “biological information” and how is it “Stored” and Processed”?

M.C. Escher Spirals

What is “biological information”?

Genetic (DNA and RNA)



Epigenetic (DNA modification)




Non-Genetic Inheritance (template dependent replication)paragenetic

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

Another example is Mad Cow Disease




Non-Genetic Inheritance (template dependent replication)

Physiological-Cellular Level (Structural/Metabolism/Signal Transduction)

Simplified Connectivity of Map of Metabolism

Each node represents a chemical in the cell (E. coli)Each connection represents an enzymatic step or steps






Physiological- Organism Level(Structural/Metabolism/Signal Transduction,

Development, Immune System)








Populations (Population dynamics, Evolution)








Populations (Population dynamics, Evolution)

Ecosystem (Interacting Populations, environment populations )

The“Central Dogma”

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

DNA

transcription

mRNA

translation

Protein

DNARNAProtein

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.

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 codeBasic machinery for interpreting the code

Major Differences:Organization of genesOrganization 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

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).

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.

Example of single celled eukaryotic organisms

Morphological diversity (cytoskeleton as well as cell surface structures)

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

Morphological diversity arises from cytoskeletal networks - architectural proteins

Some ‘Model’ Experimental Eukaryotic Organisms

Caenorhabditis elegans (round worm)

Saccharomyces cerevisiae

Drosophila melanogaster (fruit fly)

mouse

Antirrhinum majus (snapdragons )Arabidopsis thalianaZebrafish

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

GenotypeThe genetic constitution of an organism.

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

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)

“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.

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?

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?

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.”

Genotype Phenotype

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

The Natural History of Dictyostelium discoideum

Adventures in MulticellularityThe social amoeba (a.k.a. slime molds)

DNA Basics

Four bases A - adenineT - thymineC - cytosineG - guanine

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

A T base pairingC G base pairing

DNA Structure

A - TC - GG - CA - TT - AG - CG - CG - CT - A

• 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.

Chemical Structure of DNA The Double Helix

DNA Replication• Template copying• Semi-conservative


ACGATGGGT - A



A - T G C T A C C C A

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)

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.

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

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 ATTATTACCG TAAATCAGTG GAGGCTATTA AAAAATTTTT ATTTGACTTG -2 LeuLeuProMet luxS start

5’---CTCAGCGTTACCAT---3’3’---GAGTCGCAATGGTA---5’

5’---CUCAGCGUUACCAU---3’

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

DNA

RNA

PROTEIN

Transcription

Translation

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

Two ways of thinking about “information” in DNA

• In RNA T’s are replaced by U’s• Some gene products are RNA, i.e. they are not translated (e.g. tRNA, rRNA)

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 when a gene may be turned on, initiation of DNA replication, packaging of DNA etc…

i.e - Regulation

Two ways of thinking about “information” in DNA

2’holoenzymefactor

-35 -10

start

The Basic Transcription Components (Bacterial)

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

RNA Polymerase

DNA

TranscriptionMachinery

Promoter Binding

Open Complex Formation

Promoter Clearance

-35 -10

Messenger RNA (mRNA)

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.

Regulation of Gene Expression: The Basics

-35 -10

start

promoteroperator

-35 -10

startX

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

Repressor

-35 -10

start

promoteroperator

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

Activator

• 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.

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.

Consensus Binding Sites

E. coli Promoters -35 box -10 box

Consensus TTGACA- N17- TATAAT

Examples: TTGATA- N16- TATAATTTCCAA- N17- TATACTTGTACA- N19- CATAATTTGATC- N17- TACTATTTGACA- N17- TAGCTT

“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.

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

DNA

R R-DNA x DNA

Rx Rx-DNA

DNA

Regulation of Gene Expression

DNA

RNA polymerase bindingOpen Complex Formation Transcription

mRNAmRNA stabilityTranslation

Protein Polypeptide foldingProtein stability

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

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.

Eukaryotic Gene Expression

- the same principles but added complexity



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



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

- more inputs /signal integrations.

O1O3 O2CAP

e.g. E. coli lac , ~250 bp, 2 inputs

Drosophila eve stripe 2 enhancer, >1000bp, multiple TFs



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

Organism complexity number of genes

Organism complexity regulatory elements

Organism # of genesMycoplasma genetalium 750

Escherichia coli 5000

Pseudomonas aeruginosa 6000

Saccharomyces cerevisiae 6000

Caenorhabditis elegans 19,000

Drosophila melanogaster 15,000

Homo sapiens (man) 40,000

information storage and processing in biological systems:

Documents

biological information

flow of genetic information

paragenetic information

information storage

genetic regulation

simple genetic networksoct

immune systemwhat

modular cell biology