Book club on "Origins of Evolutionary Innovations" by A. Wagner http://bioinfoblog.it/

1. Book club
Andreas Wagner,
The Origins of Evolutionary Innovations
Chapter 2
Book club presented by G. M. Dall'Olio,
Pompeu Fabra, IBE-CEXS

2. Reminder:
Genotype network
 A genotype network is a set of genotypes that have the same
phenotype, and are connected by single pairwise differences
AAAAA AAAAC AAAAG AAAAT AAATT
AAACA AAACC AAACG AAACT AAATC
AACCA AACCC AACCG AACCT …..
ACCCA ACCCC ACCCG ACCCT …..
CCCCA CCCCC CCCCG CCCCT …..
….. ….. ….. ….. …..
 Yellow = same phenotype = a genotype network
 Note: genotype network == neutral network

3. Metabolic networks,
definitions (1)
 Genotype: the set of
reactions that an
organism can
catalyze
 It also represents the
metabolic network of
an organism
 Represented as a binary [1]: A. Wagner, The Origins of Evolutionary Innovations. Figure 2.1
string

4. Each genotype is a
metabolic network
Matias Rodrigues, J.F. & Wagner, A., 2009. Evolutionary plasticity and innovations in complex metabolic reaction networks. PLoS computational biology, 5(12),
p.e1000613.

5. Example of Genotype space
00....00 10....00 110000 111000  Each genotype is represented as a
00.....1 10....10 ….. ….. binary string
00....10 10..110 ….. …..
00..1..0 ….. ….. …..
00.1...0 ….. ….. …..
….. ….. ….. …..
[1]: A. Wagner, The Origins of Evolutionary Innovations. Figure 2.1

6. Microbial genotype space
00......0 10....00 110000 111000  In KEGG, there are about 5800
00......1 10....10 ….. …..
possible metabolic reactions
00....10 10..110 ….. …..
[1] for microbes
00..1..0 ….. ….. …..
00.1...0 ….. ….. 111110  There are 2^5800 possible
….. 0...1....1 ….. 111111 genotypes
….. ….. ….. …..
….. ….. ….. …..  The metabolism of E.coli
….. ….. ….. ….. corresponds to a point in this
….. ….. 0.1.1..0 ….. space (example: the blue cell)
….. ….. ….. …..
….. ….. ….. …..
….. ….. ….. …..
….. ….. ….. ….. [1]: Matias Rodrigues, J.F. & Wagner, A., 2009. Evolutionary plasticity and
innovations in complex metabolic reaction networks. PLoS
computational biology, 5(12), p.e1000613.

7. Distribution of Genetic
Distance among microbes
 On average, two
different microbes
share only 33% of
reactions
 Microbes living in the
same habitat can be
very different
Wagner, A., 2009. Evolutionary constraints permeate large metabolic networks. BMC evolutionary biology, 9, p.231. Available at:
http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2753571&tool=pmcentrez&rendertype=abstract

8. Metabolic networks,
definitions (2)
 Phenotype: whether that organism can survive on a
certain sugar as the sole carbon source (...)
[1]: A. Wagner, The Origins of Evolutionary Innovations. Figure 2.1

9. Two metabolic genotype
networks
 Yellow → can 0....0 ….. ….. ….. ….. …..
survive on 0....1 ….. ….. ….. ….. …..
Glucose as sole 0...10 ….. ….. ….. ….. …..
0..1.0 ….. ….. …..
carbon source 0.1..0 ….. ….. …..
 Blue → can survive 0..... ….. ….. …..
on Alanine as ….. ….. …..
….. ….. …..
sole carbon
….. ….. …..
source ….. ….. ….. …..
 Green → ….. ….. ….. ….. ….. …..
intersection ….. ….. ….. ….. ….. …..
….. ….. ….. ….. ….. …..

10. Flux Balance Analysis (FBA)
 Flux Balance Analysis is a computational technique
 It allows to predict whether an organism will
survive on a certain sugar as the sole carbon
source (….)

11. Definitions, overview
 In this context, a
genotype network
is a network of
metabolic networks
Matias Rodrigues, J.F. & Wagner, A., 2009. Evolutionary plasticity and innovations in complex metabolic reaction networks. PLoS computational biology, 5(12),
p.e1000613.

12. Exploring a Genotype
Network
 Let's start from the genotype
00......0 10....00 110000 111000
of E.coli (blue)
00......1 10....10 ….. …..
 We can simulate single gene 00....10 10..110 ….. …..
additions/deletions and 00..1..0 ….. ….. …..
predict their effects using 00.1...0 ….. ….. 111110
….. 0...1....1 ….. 111111
Flux Balance Analysis
….. ….. ….. …..
 Each change must preserve ….. ….. ….. …..
the ability to survive on ….. ….. ….. …..
….. ….. 0.1.1..0 …..
glucose as sole source of
….. ….. ….. …..
carbon ….. ….. ….. …..
 1000 simulations, 10,000 ….. ….. ….. …..
….. ….. ….. …..
mutations each

13. Exploring a Genotype
Network
alternative representation
[1]: Matias Rodrigues, J.F. & Wagner, A., 2009. Evolutionary plasticity and
innovations in complex metabolic reaction networks. PLoS
computational biology, 5(12), p.e1000613.

14. Exploring glucose
genotype network
 After 1000 simulations
of 10,000 mutations
of a genotype
network, average
distance is 0,76
 → so, a metabolism
can change up to
76% of its reactions,
and still preserve the
ability to survive on [1]: Matias Rodrigues, J.F. & Wagner, A., 2009. Evolutionary plasticity and
innovations in complex metabolic reaction networks. PLoS
glucose
computational biology, 5(12), p.e1000613.

15. Most neighbors have similar
phenotype
00......0 10....00 110000 111000  E.coli can catalyze ~726 reactions
00......1 10....10 ….. …..
00....10 10..110 ….. …..  Genotype space: 5870 reactions
00..1..0 ….. ….. …..
00.1...0 ….. ….. 111110
 226 reactions are essential to
….. 0...1....1 ….. 111111 preserve ability of using
….. ….. ….. ….. glucose
….. ….. ….. …..  Only 3,6% (226/5870) of E.coli
….. ….. ….. …..
….. ….. 0.1.1..0 …..
metabolome's neighbors can
….. ….. ….. ….. not survive on glucose only [1]
….. ….. ….. …..
….. ….. ….. …..
….. ….. ….. ….. [1]: Matias Rodrigues, J.F. & Wagner, A., 2009. Evolutionary plasticity and
innovations in complex metabolic reaction networks. PLoS
computational biology, 5(12), p.e1000613.

16. Neighbors of genotypes in a
genotype network
 Two genotypes of a
genotype network
have, by definition,
the same phenotype.
 But what about their
neighbors?
[1]: A. Wagner, The Origins of Evolutionary Innovations. Figure 2.6

17. Neighbors of genotypes in a
genotype network (1)
 Neighbors of two
points of a genotype
network can be very
different
 (based on 1000
simulations)
[1]: Matias Rodrigues, J.F. & Wagner, A., 2009. Evolutionary plasticity and
innovations in complex metabolic reaction networks. PLoS
computational biology, 5(12), p.e1000613.

18. Neighbors of genotypes in a
genotype network (2)
 Difference between
neighbors increases
with distance
(number of
mutations)
[1]: Matias Rodrigues, J.F. & Wagner, A., 2009. Evolutionary plasticity and
innovations in complex metabolic reaction networks. PLoS
computational biology, 5(12), p.e1000613.

19. Take Home Messages
 A metabolism can change a lot, while still
preserving the phenotype
 Metabolic networks are robust to changes, it is
difficult to break its functionality

21. Definitions, overview
Matias Rodrigues, J.F. & Wagner, A., 2009. Evolutionary plasticity and innovations in complex metabolic reaction networks. PLoS computational biology, 5(12),
p.e1000613.