Assignments for Friday's class:


ATP synthases

link

The F1-ATPase as three cylinder three-cycle engine

figure

Nojiet al (1997) Direct observation of the rotation of F1-ATPase. Nature, 386, 299 - 302 tehered the headgroup of an ATPase to a coverslip and linked the gamma subumit to an actin filament that was flurescently labeled:

ATPase tethered

The resulting movie after ATP addition is here .

 

Today's Slides

What does Bioinformatics have to do with Molecular Evolution? 

Problem: Application of first principles does not (yet) work

The following chain although (believed to be) mainly determined by the DNA sequence (plus other components of the cell which in turn are encoded by other parts of the genome) can at present not be simulated in a computer.  

DNA sequence ->
transcription ->
translation ->
protein folding ->
protein function (catalytic and other properties) ->
properties of the organism(s) ->
ecology (taking also the non biological environment into account) ->

... .

 

Most scientists believe that the principle of reductionism (plus new laws and relations emerging on each level) is true for this chain; however, this is clearly "in principle" only.
Biology relies on this sequence to work more or less unambiguously (prions), but:

At several steps along the way from DNA to function our understanding of the chemical and physical processes involved is so incomplete that prediction of protein function based on only a single DNA sequence is at present impossible (at least for a protein of reasonable size).

Solution:
Use evolutionary context:

"Nothing in biology makes sense except in the light of evolution"

Theodosius Dobzhansky



Present day proteins evolved through substitution and selection from ancestral proteins. Related proteins have similar sequence AND similar structure AND similar function.

In the above mantra "similar function" can refer to:

  • identical function,

  • similar function, e.g.:
    • identical reactions catalyzed in different organisms; or
    • same catalytic mechanism but different substrate (malic and lactic acid dehydrogenases);
    • similar subunits and domains that are brought together through a (hypothetical) process called domain shuffling, e.g. nucleotide binding domains in hexokinase, myosin, HSP70, and ATPsynthases.

The Size of Protein Sequence Space (back of the envelope calculation):

Consider a protein of 600 amino acids.
Assume that for every position there could be any of the twenty possible amino acid.
Then the total number of possibilities is
20 choices for the first position times 20 for the second position times 20 to the third .... = 20 to the 600 = 4*10^780 different proteins possible with lengths of 600 amino acids.

For comparison the universe contains only about 10^89 protons and has an age of about 5*10^17 seconds or 5*10^29 picoseconds.

If every proton in the universe were a computer that explored one possible protein sequence per picosecond, we only would have explored 5*10^118 sequences, i.e. a negligible fraction of the possible sequences with length 600 (one in about 10^662).

The following is based on observation and not on an a priori truth:

If two proteins (not necessarily true for nucleotide sequences) show significant similarity in their primary sequence, they have shared ancestry, and probably similar function.
(although some proteins acquired radically new functional assignments, lysozyme -> lense crystalline). 


To date there is no example known where convergent evolution has let to significant similarity of the primary sequence (although here are examples where similar selection pressures have resulted in similar convergent substitutions in homologous proteins).

THE REVERSE IS NOT TRUE:

PROTEINS WITH THE SAME OR SIMILAR FUNCTION DO NOT ALWAYS SHOW SIGNIFICANT SEQUENCE SIMILARITY
for one of two reasons:

a)  they evolved independently
(e.g. different types of nucleotide binding sites);

or

b)   they underwent so many substitution events that there is no readily detectable similarity remaining.

In particular, PROTEINS WITH SHARED ANCESTRY DO NOT ALWAYS SHOW SIGNIFICANT SIMILARITY
(reason: see B above); many recent advances concern the improved detection of similarity.

 

Natural Selection and Evolution

When does "evolution" occur? An algorithmic approach.

"Darwin's Dangerous Idea" by Daniel C. Dennett, Chapter on Evolution as algorithm is a reading assignment for Monday, Sept. 13. [available through WebCT]

What is needed for evolution to occur?

(Note, this is different from stating that this is all that occurs in evolution)

  • Offspring not identical to parents
  • More offsring than necessary
  • Competition for resources, mates => survival of the fittest.

What processes in biological evolution go beyond inheritance with variation and selection? (We'll discuss many of the following later in the semester.)

  • Horizontal gene transfer and recombination
  • Polyploidization (botany, vertebrate evolution) see here
  • Fusion and cooperation of organisms (Kefir, lichen, also the eukaryotic cell)
  • Targeted mutations (?), genetic memory (?) (see Foster's and Hall's reviews on directed/adaptive mutations; see here for a counterpoint)
  • Random genetic drift
  • Gratuitous complexity
  • Selfish genes (who/what is the subject of evolution??)
  • Parasitism, altruism, Morons, gene transfer agents

Discussion

Evolution, different meanings, fact vs theory, natural selection -- what else. Is variation gradual?

 

What is life?

(see Thomas Mann's excerpt from Dr. Faustus)

Traditional criteria:

  • Uptake and dissipation of Energy
  • Metabolism
  • Responsiveness
  • Gestalt (distinctive shape, separate from environment)
  • Growth
  • Reproduction with variation - Ability to evolve
See essay on definitions of life: The Seven Pillars of Life by Daniel E. Koshland

von Neumann's computers - alive? A-life?

Turing machines and universal computers (Turing's biography)

Cellular automata: A'life; John Conway's game of life. [rules: a cell survives if it has two or three living neighbors. A new cell is created on a "dead" square if it has exactly three living neighbors.] The game was popularized by Martin Gardner in Scientific American in 1970.

Examples:

More information on digital life is at Digital evolution homepage at MSU. Karl Sims' virtual creatures are worth a look, movie here . He describes his work as follows:

"A population of several hundred creatures is created within a supercomputer, and each creature is tested for their ability to perform a given task, such the ability to swim in a simulated water environment. Those that are most successful survive, and their virtual genes containing coded instructions for their growth, are copied, combined, and mutated to make offspring for a new population. The new creatures are again tested, and some may be improvements on their parents. As this cycle of variation and selection continues, creatures with more and more successful behaviors can emerge. The creatures shown are results from many independent simulations in which they were selected for swimming, walking, jumping, following, and competing for control of a green cube."

Genetic Algorithms in engineering: Ingo Rechenberg and others used "natural selection" in the computer to optimize aerodynamic profiles. Biased walk through "sequence" space. Finding optimal solutions. (To avoid local maxima: use demes with limited migration). For more information you can check a comprehensive collection of links on Evolutionary Computation and its application to art and design. It is amazing that GA work fine with rather small populations.

Eigen_Rechenberg Sequence Space

Can living systems be divided in smaller sub-systems that are themselves alive? Or, is life a property of the larger system? The ecosystem of the Sargasso sea that includes algae, bacteria and phage (viruses that live on bacteria). The cyanophage play an important role in the system as predators of the primary producers. They lyses the cells allowing for recycling of limiting elements. The phage are part of a living system, but usually are not cindered alive themselves.

The Gaia hypothesis argues that the whole biosphere should be regarded as a single organism, with its own homeostatic feed back loops.
Problems of the hypothesis:

  • Earth also includes many feed-forward loops (e.g., melting ice caps lower the albedo, which leads to more warming*). Relying on Gaia's regulatory mechanisms can provide a false sense of safety.
  • How does a single organism evolve? With only one Gaia, who would natural selection work?

* Lovelock and Watson developped the Daisyworld model (simulation here), in which black and whie Daisies stabilize the climate of the model planet. The release of DMS heat stressed algae creates a Daisyworld like feed back loop, because it acts as nucleating agent in cloud formation.