CH391L/S13/DNA Computing

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A computer scientist at the University of Southern California named Leonard Adleman first came up with the idea of using DNA for computing purposes after reading "Molecular Biology of the Gene," a book written by James Watson (co-discoverer of the structure of DNA).

"The principle of Leonard Adleman's DNA computer to solve the 'Travelling salesman' problem."
"The principle of Leonard Adleman's DNA computer to solve the 'Travelling salesman' problem."

In 1994 Adleman published an article in the journal Science[1] that proposed how DNA could be used to solve a well-known mathematical problem, called the directed Hamilton Path problem, also known as the "traveling salesman" problem. The goal of the problem is to find the shortest path between a number of cities, going through each city only once.

Pipeline for Generating Ancestral Genes

  1. Sequences from extant species of the desired common ancestral gene and outgroup genes are aligned.
  2. The ancestral gene is inferred based on evolutionary models (typically maximum parsimony or maximum likelihood).
  3. Ancestral genes are synthesized via overlapping oligonucleotides and PCR assembly.
  4. Ancestral genes are cloned and tested for function.

Methods of Inferring Ancient Sequences

  • Consensus Sequence - the most frequently occurring residue of a extant organisms is assumed to be the ancestral state.
  • Maximum Parsimony - minimization of the total number of changes required to account for the terminal sequences.
  • Maximum Likelihood - ancestral states are evaluated at each internal node in the tree based on the likelihood of each mutation. This process uses a statistical framework of molecular evolution which takes into account differences in certain types of mutations. The generated ancestral sequence gives the probability that each residue is correctly predicted.

Precambrian Thioredoxin

Perez-Jiminez et. al resurrected various Precambrian Thioredoxins. These belonged to the last common ancestors of the last bacterial common ancestor (LBCA), the last archaeal common ancestor (LACA) and the archaeal-eukaryotic common ancestor (AECA)"[2]. All of these sequences are believed to have been present over 3.5 Gya. The amino-acid sequence in each case was determined by maximum likelihood inference from 200 extant sequences. The genes to code for these proteins were synthesized and cloned into E. coli for expression and purification.

All three reconstructed proteins showed a Tm around 113°C, with a ΔTm between the highest extant Thioredoxin and the ancestors of around 25°C. The three paleo Thioredoxins also showed substantially greater activity at pH5 than representative extant enzymes from the each domain. The lower substrate specificity exhibited by the reconstructed enzymes indicates the abundance of sulfur rich compounds in the early oceans of Earth, and also hints at the generalist nature of archaic enzymes.


  1. Adleman, L. M. (1994). "Molecular computation of solutions to combinatorial problems". Science 266 (5187): 1021–1024. doi:10.1126/science.7973651. PMID 7973651. [Adleman]
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