The cell as a living computeradanchin/lectures/Stockholm_04.pdfThe cell factory A cell behaves like a computer that would program the construction of similar computers It has a magnetic

© Genetics of Bacterial Genomes Institut Pasteur1 http://www.pasteur.fr/recherche/unites/REG/ [email protected]

The cell as a livingcomputer


A preconceivedideology

Mathematics

Physics

Chemistry

Biology

Sociology

MolecularMolecularBiologyBiology

StructuralStructuralBiologyBiology

GeneticsGeneticsandandGenomicsGenomics


Background

Physics: matter, energy, timeBiology: Physics + information, coding,control...Arithmetics: strings of whole numbers,recursivity, coding…Computing: Arithmetics + program +machine...


InformationTransfer

As is the case for building up a machine, oneneeds a book of recipe to build up a cell

This asks for changing the text of the recipe intosomething concrete: this transfers« information »

In a cell, information transfer is managed by thegenetic program


Three processes are needed for Life:

Information transfer (Living Computers?) => the goal ofgenomics is to decipher the blueprint of the “read-only”memory of the machine

Driving force for a coupling between the genome structure andthe structure of the cell:

Metabolism (Internal organisation)Compartmentalization (General structure)

What is Life?


Two processes are needed for computing:

A read/write machine

A program on a physical support (typically, a tape illustrates thesequential string of symbols that makes up the program), split (inpractice) into two entities:

Program (providing the goal)Data (providing the context)

The machine is distinct from the program

What iscomputing?


The cell factory

A cell behaves like acomputer that wouldprogram theconstruction ofsimilar computers

It has a magnetic tape,or hard disk (the« genetic program »)and reading deviceswhich allow it to readthe program and put itinto action

The « cloning » of the ewe Dolly was exactly that:changing the program from a machine (an egg) toanother one (an egg without a nucleus)


From the recipe to the dish:from the genetic program

to the cell

When you read therecipe, you performactions to make the dish.A special machineryreads the DNA andcopies it into activeagents, the proteins(enzymes are proteins).

DNA

protein


Cells as computers

Genomics rest on an alphabetic metaphor, that of a textwritten with a four-letter alphabet, acting as a program

Conjecture: do cells behave as computers?

Genetic engineeringVirusesHorizontal gene transferCloning animal cells

all point to separation betweenMachineData + Program


If the machine has not only to behaveas a computer but has also toconstruct the machine itself, onemust find an image of the machinesomewhere in the machine (J. vonNeumann)

Is there a map of thecell in thechromosome?

A. Danchin The Delphic Boat. What genomes tell us (2003) Harvard University Press


Genome organisationIs the gene order random in the chromosomes?

At first sight, despite different DNA managementprocesses not much is conserved, and genestransferred from other organisms are distributedthroughout genomes

However, groups of genes such as operons orpathogenicity islands tend to cluster in specificplaces, and they code for proteins with commonfunctions

First question: how are generated and where arelocated repeats in the genome sequence?


Repeats inbacteria

Abcissa: first occurrence of the repeatOrdinate: second position of the repeat

Diagonal: repeats are located near to eachother


.

0

0

1000

2000

3000

4000

1000 2000 3000 4000

Escher i ch i a

c o l i

1000

0 200

2000

600 1000 1400 1800

Haemophi lus

in f l uenzae00

500

1000

1500

0 500 1000 1500

Methanococcus

j an n asch i i 100

200

300

400

0

0 100 200 300 400 500

Mycoplasma

gen i ta l i um

500

0200

400

600

800

0 200 400 600 800

Mycoplasma

pneumoniae

0500

1000

1500

0 500 1000 1500

Hel icobacter

py l o r i

0 1000 2000 3000 4000

0

B a c i l l u s

s u b t i l i s

1000

2000

3000

4000

0 500 1000 1500

0

Methanobacterium

thermoautotrophicum

500

1000

1500

NR = 397

NT = 283

NR = 170

NT = 54

NR = 204

NT = 111

NR = 139

NT = 82

NR = 260

NT = 187

NR = 552

NT = 250

NR = 183

NT = 75

NR = 280

NT = 137

DNA management:Repeats in genomes


Repeats: DNAmanagement differs

according to organism

Ξ No correlation with the length of the genomeΞ Non-random distribution of repeats in bacteria that can catch up

DNA from the environmentΞ When repeats are rare, they are located not far from each other

(10-15 kb)Ξ DNA is managed very differently in different bacteria

Ξ A side view: genomes from higher cells are much morerepeated than genomes of microbes, that look highly random atfirst sight


Caveat:Repeats are meaningful

Remember also:

This clock has aminute minutehand

….Thereis nojunkDNA


Genomeorganisation

Is the genes’ order random?

At first sight, perhaps because of different DNAmanagement processes, not much is conserved, andhorizontally transferred genes are distributedthroughout genomes

However, pathogenicity islands tend to cluster atspecific places, and they code for proteins withcommon functions


Genome organisation

The genome organisation is so rigid thatthe overall result of selection pressureon DNA is visible in the genome text,which differentiates the leading strandfrom the lagging strand




To lead or tolag...

Is it possible to see whether the position ofgenes in the chromosome is randomlydistributed on the leading and laggingstrand?


Chosing arbitrarilyan origin ofreplication and aproperty of thestrand (basecomposition, codonusage bias, aminoacid composition ofthe codedprotein…) one canuse statistics tosee whether thehypothesis holds

To lag or to lead...


To lag or to lead, thatis the question

.

Bases

Amino acids

Codons

Dinucleotides

0,450,5

0,550,6

0,650,7

0,750,8

0,85

0 20 40 60 80 100

Bacillussubtilis

accu

racy

Borreliaburgdorferi

0,4

0,5

0,6

0,7

0,8

0,9

1

0 20 40 60 80 100 0,4

0,5

0,6

0,7

0,8

0,9

1 Chlamydiatrachomatis

0 20 40 60 80 100

0,45

0,5

0,55

0,6

0,65

0,7

0,75

0 20 40 60 80 100

Escherichiacoli

accu

racy

0,45

0,5

0,55

0,6

0,65

0,7

0,75

0 20 40 60 80 100

Haemophilusinfluenzae

0 20 40 60 80 100

Helicobacterpylori

0,4

0,45

0,5

0,55

0,6

0,65

0,7

0,40,45

0,50,55

0,60,65

0,70,75

0,8

0 20 40 60 80 100

Methanobacteriumthermoautotrophicum

position (%) position (%) position (%)

accu

racy

0,45

0,5

0,55

0,6

0,65

0,7

0,75

0 20 40 60 80 100

Mycobacteriumtuberculosis

0,4

0,5

0,6

0,7

0,8

0,9

1

0 20 40 60 80 100

Treponemapallidum


Conclusion 1

Proteins are made of 20 amino acidtypes, among which Valine andThreonine, and one observes thatValine-rich protein are on the leadingstrand while Threonine-rich proteins areon the lagging strand! Isologousproteins replace preferentially oneresidue for the other when their genechange strand


To lag or to lead, thatis the question

.

0

5

10

15

0 5 10 15

% V

% T

Borreliaburgdorferi

0

5

10

15

0 5 10 15

% V%

T

Chlamydiatrachomatis

180

90

0

270

55% leading

Escherichia coli

Ori

Ter

90270

65% leading

Treponema pallidum

Ori

Ter

180

9027075% leading

Bacillus subtilis

Ori

Ter

90270

87% leading

Thermoanaerobactertengcongensis

Ori

Ter

CDS densityLeading CDS density

(updated from Kunst etal , Nature, 97)

Different “OperatingSystems”?


Conclusion 2 andmore questions

… The genome organisation is much more rigid

than usually assumed. Some regions (suchas the terminus) are rather unstable, but mostof the genome structure is preserved throughevolution. The distribution of genes on theleading and lagging strands is highly non-random. Is it associated to some particularfunction (such as the Operating System in acomputer)? Where are essential geneslocated?


Essentiality, notexpressivity dominates

the strand-choice

Most essential genes are located in theleading strandMany highly expressed genes arelocated in the lagging strandEssentiality organises the genome’sarchitecture


(adapted from Brewer, Cell, 88)


Essentiality in B. subtilis

highly

expressed

0%

25%

50%

75%

100%

non-highly

expressed

Essential genes

highly

expressed

non-highly

expressed

Non-essential genes

Lagging

Leading


Distribution of highly expressed genes

Highly expressed genescluster near the origin infast-growing bacteria

Origin

Terminus

Middle

Ori

Ter

10%

20%

30%

40%

50%

60%

70%

0%

C. c

resc

entu

s

M. t

uber

culo

sis

E. c

oli

B. su

btili

s

Fast growers | Slow growersFast growers | Slow growers


Gene order conservationGene order conservation

16S:.063 nt-1 16S:.051 nt-1

16S:.071 nt-116S:.076 nt-1

.

Chlamydia pneumoniae

Ch

lam

yd

ia

mu

rid

aru

m

.

Yersinia pestis

Esch

eri

ch

ia

co

li

.

Ba

cil

lus

su

btil

is

Bacillus halodurans

origin

terminus

Buchnera Ap

Buch

nera

Bp


Exploring“neighborhoods”

Genes do not operate inisolationProteins are part ofcomplexes, as are partsin an engine

It is important tounderstand theirrelationships, as those inthe planks which make aboat


Exploringneighborhoods

To make discoveries we explore the general« neighborhoods » of genes of interest: proximity in thechromosome, in evolution, in the literature, in biochemicalcomplexes, in metabolism etc.

Comparative genomics is essential, hence the launching ofseveral parallel genome programs


Gene vicinity: synteny



Information transfer: groups of co-variant geneexpression

Driving force for a coupling between the genomestructure and the structure of the cell:


What is Life?


Co-variation of geneexpression

Collecting data using large scale genomicstechniques :

DNA chips and protein fingerprinting


Expressionneighborhood: all genes

on a chip

•Green:

Firstcondition

•Red:

Secondcondition

•Yellow:

no difference

Two conditions are compared on the same chip


Protein fingerprinting

A technique named « two-dimensional gelelectrophoresis » allows oneto separate all the proteinsof a cell, and to color them.Once colored, proteins aresorted and identified by« mass spectrometry ».Different cells or cells indifferent environments havea different pattern, exactlyas individuals have differentfingerprints.



Information transfer



What is Life?


Metabolicneighborhoods:

Chemical pathways

Often, drug targets are found in metabolic pathways.The idea is to mimick a normal molecule in the celland to replace it by a similar one which kills theactivity of some protein: this is exactly what poisonsdo! Antibiotics are poisons of a special kind, whichact against microbes: to discover a new antibiotic isto discover a self-consistent pathway


Metabolic neighborhood:unexpected selective

constraints

OMP UMP UDPUDP UTP CTP

RNA

DNA

CMP

CDPdCDP

target

target

CDP diglycerides

phospholipids

AnticancerAnticancertargettarget??

DNA is made from NDP nucleotides, but CDP is absent:



Information transfer



What is Life?


A dangerous intermediate

OMP UMP UDPUDP UTP CTP

dUDP

dUTPDNA dUMP + PPi

dTMP

dTDP

dTTP

DNA

pyrHUridylate

kinase (UMK)

DNA is made from NDP nucleotides, but UDP must not get in:


Uridylatekinase

] Essential enzyme] Different origin in cells without a nucleus

(bacteria) and in cells with a nucleus] Conjecture: UDP must be

compartmentalized to prevent U to enterDNA


Cellcompatmentalisation

in vivoThe pyrH geneis fused withthe reportergfp gene andreplaces itswild-typecounterpart.One observeslocalisation ofGFP under themembrane,and at foci….


Conclusion

The genome organisation is much morerigid than usually assumed.

Some regions (such as the terminus)are rather unstable, but most of thegenome structure is preserved throughevolution


Why a computer?The power ofalgorithms

The analogy between the cell is a computer goes beyongthe separation between the program and the machine

The structure of the program itself is subject toarchitectural constraints, that must derive from somesort of selection pressure, building up an image of thecell in the program

Computing allows one to reinvestigate the idea ofpreformism: the cell is not preformed, but its algorithmof construction is


Gestalt andAlgorithms

« Start from the top, middle

Go downfrom right to left

Accelerate

Turn right

etc.


From the cell tothe animal?

The analogy between the cell is a computer goes beyongthe separation between the program and the machine

Can this analogy be extended to organisms as wholeentities?

Homeogene control the development of animals (andplants): the order of these genes along chromosomesfollow the plan of the body of the animal


Drosophiloculus,Homunculus ?


Drosophiloculus,

Homunculus ?


Our working hypothesis was that thecell would behave as a computer.This conjectures that an architecturalprogram exists in the chromosome.This may be wrong, but science goesto India… and may find America !

From the geneticprogram to a research

programme?

A. Danchin The Delphic Boat. What genomes tell us (2003) Harvard University Press


Anglo-American

NATO

Bottom Up

Data-driven

Greco-Latin

OTAN

Top Down

Hypothesis-driven

Chinese

« Bombardment of the Chinese Embassy in Belgrade »

Sideways

Context-driven

causeries/Western.html

Documents

The cell as a living computeradanchin/lectures/Stockholm_04.pdfThe cell factory A cell behaves like a computer that would program the construction of similar computers It has a magnetic